Evidence supports several countries introducing legislation to allow cannabis-based medicine as an adjunctive treatment for the symptomatic relief of chronic pain, chemotherapy-induced nausea, spasticity in multiple sclerosis (MS), epileptic seizures, depression, and anxiety. However, clinical trial participants do not represent the entire spectrum of disease and health status seen in patients currently accessing medicinal cannabis in practice.This study aims to collect real-world data to evaluate health-related quality of life in patients prescribed medicinal cannabis oil and describe any differences over time, from before starting therapy to after 3 and 12 months of therapy.Adult patients newly prescribed medicinal cannabis oil by authorized prescribers and under the Special Access Schemes across Australia will be screened for eligibility and invited to participate. A sample size of 2142 is required, with a 3-month follow-up. All participants will complete the EuroQol 5-Dimension; European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-30; Depression, Anxiety, and Stress Scale-21; Patients’ Global Impression of Change; Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form (SF) version 1.0: Sleep Disturbance 8b; and PROMIS SF Fatigue 13a questionnaires. Patients with chronic pain conditions will also complete the PROMIS SF version 1.0: Pain Intensity 3a and PROMIS SF version 1.0: Pain Interference 8a. Patients with movement disorders will also complete Quality of Life in Neurological Disorders (Neuro-QoL) SF version 1.0: Upper Extremity Function (Fine Motor and Activities of Daily Living) and if chorea is indicated, the Neuro-QoL SF version 2.0: Huntington’s Disease health-related Quality of LIFE-Chorea 6a. All questionnaires will be administered at baseline, 2 weeks (titration), monthly up to 3 months, and then every 2 months up to 1 year.Recruitment commenced in November 2020. By June 2021, 1095 patients were screened for the study by 69 physicians in centers across 6 Australian states: Australian Capital Territory, New South Wales, Queensland, South Australia, Victoria, and Western Australia. Of the patients screened, 833 (39% of the target sample size) provided consent and completed baseline questionnaires. Results are expected to be published in 2022. Results of this study will show whether patient-reported outcomes improve in patients accessing prescribed medicinal cannabis from baseline to 3 months and whether any changes are maintained over a 12-month period. This study will also identify differences in improvements in patient-reported outcomes among patients with different chronic conditions .This protocol contains detailed methods that will be used across multiple sites in Australia. The findings from this study have the potential to be integral to treatment assessment and recommendations for patients with chronic pain and other health indicators for accessing medicinal cannabis.Australian New Zealand Clinical Trials Registry: ANZCTRN12621000063819; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=380807&isReview=trueDERR1-10.2196/32327 With the first accounts of cannabis being used as medicine dating back to China in 2600 BC, its use for medicinal purposes has been recorded on nearly every continent throughout history . Many coreal-world setting may be confounded by drug-drug interactions [real-world evidence.Evidence from randomized controlled trials indicates that medicinal cannabis can reduce chronic pain -12, neurractions . This suA patient-reported outcome (PRO) is any report coming directly from patients without interpretation by physicians or others about how the patient feels in relation to a health condition and its therapy . PROs caThe Australian Therapeutic Goods Administration (TGA) currently approves Special Access Scheme (SAS) applications from health care providers who provide a clinical justification for prescribing medicinal cannabis where conventional therapies have failed . There achronic primary pain—a disease in its own right such as nonspecific low-back pain—or as chronic secondary pain initiated as a symptom of an underlying disease, such as cancer-related pain or neuropathic pain [Chronic pain is a widespread health issue broadly defined as pain that lasts or recurs for more than 3 months  and is chic pain . In Austhic pain . In the hic pain . In 2016hic pain .Cancer-related pain is experienced by approximately one-third of patients with cancer at diagnosis and during treatment and by approximately three-fourths of patients with advanced-stage cancer. However, 10%-15% of the patients are nonresponsive to conventional pain therapy . ResiduaNeuropathic pain, which is caused by a lesion or disease of the somatosensory nervous system , is expeThe prevalence of chronic pain increases dramatically in patients receiving palliative care ,41. A stMS is a chronic inflammatory and demyelinating neurodegenerative disorder that often involves symptoms such as spasms, tremors, pain, fatigue, bladder dysfunction, cognitive impairment, depression, and impairments in swallowing, speech, vision, and balance . In 2018Epilepsy is a chronic neurological disease characterized by 2 or more unprovoked seizures and affects approximately 50 million people worldwide . High-quPRO assessment can assist health care professionals in monitoring treatment outcomes over time from patients’ perspectives. In 2020, there were no published results from a centralized PRO data collection for a large sample of patients accessing prescribed medical cannabis within Australia that covers all approved health indications using a comprehensive battery of PROMs. Participants studied under controlled clinical trial environments have not always been representative of the entire spectrum of disease and health status seen in people currently accessing medicinal cannabis in practice . TherefoA scoping review that we conducted identified the following limitations in the current evidence on PROs for medicinal cannabis:Very few studies have collected PRO data longitudinally, including baseline, maintenance, and long-term use data .A large proportion of cannabinoid research was focused on pharmacokinetic, animal, and preclinical studies.Many cannabinoid clinical studies include case studies  or have Early studies did not use the currently recommended individualized dosing titration paradigm of starting low and gradually escalating to achieve optimal effects .Formulations studied may not reflect current commercially available cannabinoid products .Many PROMs used have limited validity in the health conditions assessed .Very few clinical studies used comprehensive pain assessments.Therefore, the real-world collection of a comprehensive suite of PROs in a large sample of people across all health conditions, as approved by the TGA, accessing current formulations of prescribed medicinal cannabis in Australia is needed to enable clinically relevant assessment and provide ongoing evidence for decision-making both in practice and at a policy level.The aim of this study is to evaluate PROs in patients who are prescribed medicinal cannabis by authorized prescribers and under the SAS across clinics within Australia. The findings from this study have the potential to be integral to treatment assessment and recommendations for chronic pain sufferers and other patients with health indicators for accessing medicinal cannabis.The primary objective of this study is to describe changes in the PROs  from baseline to 3 months for a large cohort receiving medicinal cannabis.The secondary objectives of this study are to describe changes in PROS  from baseline up to 12 months and to describe differences between patients accessing medicinal cannabis with different chronic health conditions, including, but not limited to, chronic pain, MS, epilepsy, Parkinson disease, and cancer.The exploratory objectives of this study are to explore (1) which individuals are more likely to have lower symptom burden and greater HRQL, (2) associations among PROs, with the hypothesis that a high symptom burden is associated with poorer HRQL, and (3) associations between PROs and resource and medication use over time, with the hypothesis that lower symptom burden is associated with reduced health care–resource use and reduced use of opioids and other prescribed medications for managing symptoms.The study includes 3 hypotheses: (1) PROs will improve from baseline to 3 months in patients accessing medicinal cannabis, (2) improvements in PROs at 3 months will be maintained over a 12-month period, and (3) no differences in PROs will be observed between patients being treated for different conditions .This is a multicenter prospective longitudinal cohort study of patients newly prescribed with medicinal cannabis in Australia by authorized prescribers and under the SAS. The study is registered in the Australian New Zealand Clinical Trials Registry (ACTRN12621000063819).To be eligible to participate in the study, participants must have already been identified as eligible to receive a medicinal cannabis product from an authorized prescriber or under the SAS category B pathway, with approval given by the Australian TGA. This means that a suitable health practitioner has seen and assessed their patient, adhering to relevant standards of good medical practice, and successfully applied to the TGA for access to the particular medicinal cannabis product for the patient. Little Green Pharma Ltd (LGP) is responsible for the manufacture and quality of the products following the TGA guidelines. The prescriber is responsible for the prescription of the product for the patient and seeking TGA approval either as an authorized prescriber or under the SAS-B scheme, including the patient’s informed consent for the product.The University of Sydney researchers are responsible for the design of the cohort study and the data collection and analysis, as outlined in this protocol.LGP is responsible for arrangements for delivery of the product, any subsidization arrangements, and the arrangements entered into with the participating sites and the physicians at these sites.The prescriber is responsible for identifying the patients suitable for the study and obtaining consent to email them an invitation to participate in the study.The inclusion and exclusion criteria are provided in Inclusion criteriaPatient is an adult (aged ≥18 years).Patient has been identified as eligible to receive medicinal cannabis by a Therapeutic Goods Administration–approved authorized prescriber or through the Special Access Scheme  and the physician has sought and obtained Therapeutic Goods Administration approval for the Little Green Pharma Ltd product for their patient.Patient is able to read and understand English.Patient is able to provide informed consent.Patient has not started any prescribed medicinal cannabis therapy in the last 4 weeks or started prescribed Little Green Pharma Ltd medicinal cannabis therapy within the last 2 days (we expect no therapeutic benefit within 2 days) and did not receive any prescribed medicinal cannabis therapy in the last 4 weeks.Patient has a life expectancy of >3 months.Exclusion criteriaPatient is unconscious or confused.Patient has cognitive impairment .Patient is pregnant or breastfeeding.Patient is unable to read and write in English.Patient is denied access to medicinal cannabis under the relevant Special Access Scheme for their country of registration.Objectives section.Our aim is to recruit a large, broad, and representative sample of medicinal cannabis users. Therefore, we will invite every eligible patient treated at each participating center during a 12-month recruitment period. This large real-world cohort will enable several important analyses exploring differences in PROs between disease groups commonly treated with medicinal cannabis, as discussed in the Following the guidelines  for the Recruitment will take place between November 2020 and November 2021, with the aim of including all eligible patients receiving medicinal cannabis at participating sites during the recruitment period. LGP, following the World Health Organization Guidelines on Good Agricultural and Collection Practices for Medicinal Plants and European Union-Goods Manufacturing Practices standards, provides its medicinal cannabis products in Australia under the SAS. As part of this process, LGP engages with medical cannabis–focused clinics, authorized prescribers, and other health care professionals prescribing LGP products and will be responsible for identifying recruitment sites for this study. Advertising and information relevant to the study will be disseminated via a dedicated study website and social media platforms. Content on the study website will inform potential participants and recruitment sites of the study objectives, terms, and conditions, including eligibility criteria, and who to contact for more information. Approved recruitment sites will receive study-specific training from the University of Sydney researchers regarding participant screening and recruitment.Patients from participating centers who meet the eligibility criteria will be invited to participate in the study. Patients will be identified by physicians at recruitment sites and approached to participate by either the physician or site staff. A record of those identified as eligible and invited to participate will be logged in the web-based research database with the patient’s verbal consent. Physicians at recruitment sites will use a generic link to access the study database to create a new record for each patient screened.Registration and Clinical Data section, into the research database, which then sends an invitation to them automatically. Participants will be informed that email addresses are stored within the Research Electronic Data Capture (REDCap) system and used solely for sending reminders to complete questionnaires at scheduled time points. REDCap [The physician or staff at recruitment sites will ask if the patient agrees to have the Participant Information Statement and invitation sent to them through email. Patients will be informed that the process involves recruitment site staff entering the information, as per the . REDCap  is a secAll patients who provide their email address to receive an invitation for the study will receive their medicinal cannabis product at a standardized cost. As medicinal cannabis is still an unregistered product, it has been difficult to control the cost of the product; consequently, there has been considerable variability in what people pay for the product. LGP has partnered with several pharmacies across Australia to ensure that all participants taking part in this study will be charged the same amount for their product, eliminating variability in out-of-pocket costs and enabling a health economic evaluation.opt out without reason.As soon as an email address is entered in the web-based database, the patient will receive an email invitation with a link to the web-based forms for their record. The email will include the Participant Information Statement  to be coParticipants will remain free to withdraw from the study at any time without giving reasons and without prejudicing any further treatment. Participants can withdraw responses from the study before the data have been analyzed; otherwise, they will be included.When physicians at recruitment sites complete the web-based screening form, REDCap will automatically generate a number to be used as the participant’s study ID number for study registration.Study data will be recorded by physicians at recruitment sites on case report forms and by participants in the questionnaire booklets. These will be completed on the web through the University of Sydney research data capture system, REDCap .Screening and registration and clinical data will be completed by the physician at the recruitment sites. The REDCap database will collect information only identifiable by REDCap-assigned study record ID numbers. Physicians at recruitment sites will maintain a record of participants’ study ID numbers for each screened and registered participant entered. Where required, data can be updated for individual participants by notifying the study project manager of the corresponding study ID numbers . If 2 consecutive assessments are missed by participants, the study project manager will contact the physician at the recruitment site to determine the reasons for missed assessments, if known.The following patient screening details will be entered into the REDCap web-based registration form by physicians at recruitment sites: age, sex, country, email address, health indications for accessing medicinal cannabis, neuropathic pain screening using the short-form Douleur Neuropathique en 4 Questions ,56 (if pPatients who provide email addresses will receive an email with a link to the patient consent and demographic form corresponding to their study record ID. Patient consent and demographic questions include the following: consent to participate (or opt out), reasons for declining study participation (if applicable), ethnicity and cultural background, education, living arrangements, marital status, height, weight, gender identity, work status, access to health services, any medication other than medicinal cannabis taken during the last 4 weeks for health indication, and previous history of cannabis use.Baseline PROMs will be presented to participants on the web automatically after completing the demographic questions. Participants self-complete the questionnaires through the web-based platform at home, accessible on a computer or other device with an internet connection, depending on their preference. All the questionnaires will be administered in the same order. It is anticipated that completion of baseline questionnaires may take up to 30 minutes. Follow-up questionnaires may take approximately 25 minutes. We have estimated the time to complete the questionnaires (including demographic questions) based on 10-12 seconds per item .All participants will complete the following PROMs.today. In addition to the 5 items, there is a visual numeric scale of global health rated on a scale of 0-100. The questionnaire has validated language translations suitable for use in Australia.Generic HRQL will be assessed in all participants using the EuroQol 5-Dimension questionnaire (EQ-5D-5L). The EQ-5D-5L is a standardized measure of health status developed by the EuroQol Group to provide a simple, generic measure of health for clinical and economic appraisals . EQ-5D-5To make the EQ-5D-5L suitable for use in economic evaluations, health states were valued using a preference-elicitation method in the general population. Australian national values have been collected and subsequently modeled and will be used for economic analysis .All participants will receive the EORTC QLQ-C30 core quality of life cancer questionnaire , which iThe QLQ-C30 can be used for economic evaluation through the QLU-C10D , a healtsince beginning medicinal cannabis treatment.Patients’ subjective rating of overall change in health status related to their primary health condition will be assessed using the Patients’ Global Impression of Change . The PatAnxiety, depression, and stress will be assessed in all participants with the validated 21-item short version of the Depression, Anxiety, and Stress Scale . The DepSleep quality will be assessed in all participants using the Patient-Reported Outcomes Measurement Information System (PROMIS) Short Form version 1.0: Sleep Disturbance 8b . This meFatigue will be assessed in all participants using the PROMIS Fatigue 13a or the Functional Assessment of Chronic Illness Therapy Fatigue Scale . The 13-The following questionnaires will only be administered to patients with identified conditions or health status.To reduce the burden on patients with a primary health indication of palliative care for advanced, symptomatic, incurable cancer with a life expectancy of a few months, they will receive the EORTC QLQ-C15-PAL instead of the QLQ-C30. It is a shorter, 15-item questionnaire that assesses the same outcomes as the QLQ-C30 questionnaire and is used extensively in the palliative care setting . PalliatParticipants with pain as a health indication in their baseline clinical data will complete additional pain-specific questionnaires :Pain intensity will be assessed using the PROMIS Scale version 1.0: Pain Intensity 3a (PS-PI) . The scaPain interference will be assessed using the PROMIS Short Form version 1.0: Pain Interference 8a . This meParticipants with movement disorder, chorea, as a health indication will be assessed with the Quality of Life in Neurological Disorders Short Form version 2.0–Huntington’s Disease health-related Quality of LIFE-Chorea 6a . This 6-Participants with movement disorders affecting the upper body as a health indication will be assessed using the Quality of Life in Neurological Disorders version 1.0: Upper Extremity Function (Fine Motor and Activities of Daily Living) Short Form . This 8-For participants who indicate that they are working or would normally be working , the impact of health on work performance will be assessed using the absenteeism and presenteeism questions of the World Health Organization’s Health and Work Performance Questionnaire . The queParticipants will receive automatic reminders from the REDCap system to their email addresses at scheduled follow-up assessment time points . Follow-Prospective assessment of newly prescribed patients before and after treatment is required to assess changes in PROs over time. PROs will be completed at baseline before starting medicinal cannabis, at 2-3 weeks after starting medicinal cannabis (end of titration period), and then at 1, 2, 3, 5, 7, 9, and 12 months after the titration period.The acceptable PRO assessment time windows are indicated in All analyses will be performed using SPSS software . Baseline demographic and clinical data will be summarized descriptively for all patients registered for the study. Categorical data will be presented as frequencies and percentages. For continuous scale data, mean, SD, median, 25th and 75th percentiles, and minimum and maximum scores will be presented.PRO analyses will explore changes over time using mixed linear models. Subgroup analyses will compare differences in PROs between underlying conditions, dose, and duration of pain and over time using linear mixed models.A comprehensive PRO-specific statistical analysis plan will be produced by the study statistician. The key considerations include the following:PRO questionnaire responses will be scored into PRO scales for outcome analysis according to standard scoring algorithms provided by the questionnaire developers and custodians.Rates and reasons for missed PRO assessments will be summarized to assess likely missing data mechanisms against missing data assumptions of statistical modeling.For each PRO, all participants with a score for that PRO at baseline and at least one time point after starting medicinal cannabis will be analyzed.Linear mixed models will be used to compare groups in their PRO scores, adjusted for their PRO levels at baseline and with additional covariates such as duration of pain, previous cannabis use, use of other medications, and overall and prespecified subgroups.If the scores are highly skewed, a suitable transformation will be sought to achieve normality.As there are several PRO scales and time points and correlation among them is anticipated, statistical significance levels will be adjusted using an appropriate method .The clinical significance of differences in the PRO questionnaires will be interpreted using existing guidelines  , maintaiMissing items within the PRO questionnaires are not expected. This is because of the web-based administration platform alerting participants of missed items and the requirement to complete those items before progressing to the next page. Only those participants who complete at least 2 questionnaires (baseline and one other) will be included in the analysis. Single missed assessments will be imputed using the last value carried forward technique, that is, no change from that individual’s last assessment. Pattern mixture models will be used to impute scores for missed assessments based on recorded reasons .The economic evaluation will use collected data around pharmaceutical and other medical costs to explore the drivers of patient-level costs. As this study is not a comparative randomized trial, we are not proposing to conduct a formal economic evaluation, resulting in a cost per quality-adjusted life year. We will instead use baseline resource use as an indicator of typical care and contrast resource use throughout the study with baseline data. We will explore the relationship between HRQL and resource use across the cohort, which is potentially important information for future economic evaluation of medicinal cannabis.Participant recruitment in Australia commenced on November 27, 2020. By June 4, 2021, 1095 patients were screened for the study by 69 physicians in centers across 6 Australian states: Australian Capital Territory, New South Wales, Queensland, South Australia, Victoria, and Western Australia. Of the 1095 patients screened, 833 (76.07%) participants provided consent, completed baseline questionnaires, and remained on the study. Baseline recruitment is expected to end in March 2022 when the target sample size of participants has completed the baseline questionnaires and a 3-month follow-up. The final results for the primary objective are expected to be published in 2022.The results of this study will show whether PROs improve in patients accessing prescribed medicinal cannabis from baseline to 3 months and whether any changes are maintained over a 12-month period. This study will also identify whether there are differences in improvements in PROs among patients being treated for different conditions .The findings from this study have the potential to be integral to treatment assessment and recommendations for chronic pain sufferers and other patients with health indicators for accessing medicinal cannabis.


Imaging the dynamics of proteins in living cells is a powerful means for understanding cellular functions at a deeper level. Here, we report a versatile method for spatiotemporal imaging of specific endogenous proteins in living mammalian cells. The method employs a bifunctional aptamer capable of selective protein recognition and fluorescent probe-binding, which is induced only when the aptamer specifically binds to its target protein. An aptamer for β-actin protein preferentially recognizes its monomer forms over filamentous forms, resulting in selective G-actin staining in both fixed and living cells. Through actin-drug treatment, the method permitted direct monitoring of the intracellular concentration change of endogenous G-actin. This protein-labeling method, which is highly selective and non-covalent, provides rich insights into the study of spatiotemporal protein dynamics in living cells.  Imaging of subcellular localization and dynamics of proteins is a powerful means for elucidating biochemical pathways in cells. Immunostaining, a method used with antibodies to visualize the intracellular distribution of protein in fixed cells, has an edge, but it provides only a snapshot image taken at the time of fixation. Therefore, establishing live-cell protein imaging methods has ever been in high demand, and a number of unique methods have been proposed to visualize protein dynamics in living cells. Out of the numerous techniques developed, the most widely used method to date is the overexpression of the protein of interest as a fusion with a fluorescent protein ,2 or a sTo overcome such limitations, an unconventional live-cell imaging technology that is applicable to non-engineered, endogenous proteins would be useful to a notable extent. One of the most powerful approaches ever developed so far is ligand-directed labeling, where binding of a protein target to its modified ligand leads to proximity-induced covalent labeling of the protein. Selective protein labeling, such as using quenched ligand-directed tosylate compounds  and diazAdditional details are available in the supplemental information.2O and 0.1% trifluoroacetic acid in acetonitrile (0−90%) as the solvent, and a flow rate of 3.0 ml/min. All fluorescence spectra were measured with an LS 55 fluorescence spectrometer (Perkin Elmer). Fluorescence spectra were recorded using a FluoroMax®-4 . The live-cell and fixed-cell imaging were performed using a CellVoyager™ CV1000 Confocal Scanner Box (Yokogawa Electric Corporation) equipped with an ultra-sensitive EMCCD C9100-13 camera (512 × 512 pixels) and an Olympus UPLSAPO 100XO 1.4 oil objective.ESI-mass spectra for the probes and peptides were measured with an LCMS-2020 system (Shimadzu). HPLC purification and profiling was done with an Inertsil ODS-3 reversed phase column , with a linear gradient of 0.1% trifluoroacetic acid in H20 - TGG CCT AGA TAA ATT CGG AGC TT - N20 - GCT TTC GAC GGA GAA TTC -3′] as the template. All PCR reactions were done with KOD FX Neo (Toyobo). Primers used for PCR amplification were: forward [5′-GCT AAT ACG ACT CAC TAT AGG GAT CCA AGC TTG T-3′ (T7 promoter sequence is underlined)] and reverse [5′-GAA TTC TCC GTC GAA AG-3′]. The original DNA pool was in vitro transcribed with T7 RNA polymerase  to give the first RNA pool. After transcription, the mixture was treated with DNase I (Ambion) and precipitated with 1.25 M ammonium acetate/isopropanol. The precipitated RNA was applied to a NAP-5 column  to remove unincorporated NTPs, precipitated with 0.136 M sodium acetate/isopropanol, pelleted by centrifugation, washed with 70% ethanol, and used for the selection step. In each round of selection, RNA was heated to 85°C in binding buffer (10 mM Tris−HCl (pH7.6), 100 mM KCl) for 10 min and cooled in ice for 10 min. MgCl2 was then added to a concentration of 10 mM, and the RNA was incubated on BHQ1-immobilized affinity resin for 15 min at 4°C. The unbound RNA was collected and 10 μg of monomeric β-actin was added. The resulting solution was mixed with BHQ1-immobilized affinity resin and incubated for 30 min at 4°C. The resin was then drained and washed eight times with binding buffer to remove the non-binding species. Bound RNA species were eluted using binding buffer containing 2 μg of eluting antibody (BA3R/AC40), three times for 5 min each. The eluted fractions were pooled and precipitated with 0.136 M sodium acetate/isopropanol. Selected RNAs were reverse-transcribed using Prime Script reverse transcriptase (TAKARA), and the resulting cDNA was PCR-amplified with the forward and the reverse primers described above. The DNA templates were transcribed in vitro, and the resulting RNAs were subjected to the next round of selection. After 16 rounds of selection, enriched RNAs were reverse-transcribed and converted to dsDNA by PCR. The resulting DNAs were ligated into pUC19 at the EcoR I and BamH I sites and transformed to Escherichia coli strain DH5α. Several clones were isolated and sent for sequencing (Eurofins Genomics).The original double-stranded DNA pool was constructed via PCR, using a synthetic oligonucleotide containing 20 random nucleotides flanking both sides of the reported BHQ1 binding sequence [5′- GGA TCC AAG CTT GTT TGG C - NT AAT ACG ACT CAC TAT AGG GAT CCA AGC TTG T-3′], and reverse primer [5′-GAA TTC TCC GTC GAA AG-3′]. RNAs were transcribed from the dsDNA templates using T7 RNA polymerase from T7 MegaScript Kit (Ambion®) and purified using a NAP-5 column to remove unincorporated NTPs as described above.The dsDNAs for T7 transcription of RNA aptamers were PCR amplified using the recombinant pUC19 plasmid as a template, with T7 primer [5′-GC1  in a buffer , 100 mM KCl, 10 mM MgCl2) and incubated at room temperature for 10 min. Fluorescence spectra of the sample were measured at the excitation wavelength of 620 nm and emission range of 640–800 nm. Competition experiments were performed by adding competitors together with β-actin. Antibodies were added at a final concentration of 3 μM, and peptides were added from 0 to 20 μM at 1% DMSO.RNA aptamer (3 μM) was denatured at 85°C for 10 min and cooled on ice for 10 min. The RNA was then mixed with β-actin (3 μM) in buffer , 100 mM KCl) for 30 min at 25°C. The resulting RNA solution was mixed with a solution of conjugate 2, and 0.1 mM ATP. The G actin stock solution was centrifuged at 21,500 × g at 4°C for 30 min. The supernatant was obtained, and 80 μl was taken and adjusted to binding buffer conditions (10 mM Tris–HCl (pH 7.6), 100 mM KCl and 10 mM MgCl2). RNA aptamer and conjugate 1 were added to a final concentration of 3 and 2 μM, respectively. The probe fluorescence of this solution was measured and taken as t = 0 min. ME buffer  was then added to the remaining G actin stock and incubated at room temperature for 2 min. KMEI was immediately added containing 50 mM KCl, 1 mM MgCl2, 1 mM EGTA and 10 mM imidazole (pH 7.0). A 100-μl aliquot was taken, and the fluorescence was immediately measured at the excitation wavelength of 365 nm and emission wavelength of 410 nm every 20 s for 15 min. An aliquot of the remaining, polymerizing G actin stock was taken every 3 min and mixed with the RNA aptamer and conjugate 1. The solutions were adjusted to binding buffer conditions and the probe fluorescence was measured at the excitation wavelength of 620 nm and emission range of 640–800 nm.Monitoring of actin polymerization was adapted according to the protocol described in the Actin Polymerization Biochem Kit , with some modifications. Briefly, 600 μl of G actin stock solution was prepared by dissolving 5 μM of actin (3% pyrene labeled) in G-buffer containing 2 mM Tris−HCl (pH 8.0), 0.1 mM CaCl2O) and precipitated with ice-cold ether. The crude product was then dried and subjected to HPLC purification and LC−MS analysis.The peptide epitope with sequence DDDIAALVVDNGSG (BA3R Antibody epitope) was prepared according to standard Fmoc solid phase peptide synthesis. Fmoc-Gly-OH was loaded on to 300 mg of Wang resin (1.03 mmol/g) using 2 eq. of DIC, 2 eq. of HOBt, and 0.1 eq. of DMAP in DCM/DMF for 2 h. Unreacted sites were capped with 0.5 eq. each of acetic anhydride and DIEA in DMF. Fmoc was removed by adding 20% piperidine in DMF in two 2 ml portions for 15 min each. Subsequent amino acids were loaded on the resin using 2 eq. each of HBTU and HOBt with 4 eq. of DIEA and mixed for 1.5 h. Success of couplings and deprotections was monitored by Kaiser test. Successful couplings were followed by capping and deprotection steps. This cycle was repeated until the whole sequence peptide was synthesized on the resin. The peptide was cleaved from the resin with a TFA cleavage cocktail (95% TFA/2.5% TIS/2.5% H®), supplemented with 1% penicillin, 100 μg/ml streptomycin sulfate, and 10% (v/v) fetal bovine serum (Biowest), at 37°C in a humidified incubator kept at 5% CO2. The cells were co-transfected with the RNA-aptamer expression plasmids and pSuper.gfp using FuGENE® HD transfection reagent (Promega), according to the manufacturer's protocol. The RNA−aptamer sequences were cloned into pSuper vector (Oligoengine). Non-recombinant pSuper vector was used as a control.HeLa cells were maintained in Dulbecco's modified Eagle medium  at 7.5 × 103 cells per well. After 24 h, cells were fixed with 4% paraformaldehyde solution  at room temperature for 10 min, then washed twice with PBS and permeabilized with 0.5% Triton-X 100 for 10 min. The cells were then incubated with a blocking solution containing 10% dextran sulfate, 2 mM vanadyl-ribonucleoside complex, 0.01% salmon DNA, 30 μg yeast tRNA, 10 mM Tris−HCl (pH 7.6), and 100 mM KCl at room temperature for 1 h. The wells were washed twice with PBS and stained with 50 μl of 0.3 μM DNase I at room temperature for 30 min. Excess solution was removed, and the wells were washed twice with PBS. The cells were then incubated with 10 μM of P-TRap in binding buffer (10 mM Tris−HCl (pH7.6), 100 mM KCl and 10 mM MgCl2) at 4°C for 12 h, and then the solution was washed out twice with the binding buffer. The cells were stained with DAPI (10 μg/ml) in a binding buffer (50 μl) at room temperature for 20 min and treated with 5-μM conjugate 1 in the binding buffer (30 μl) at room temperature for 5 min. Excess conjugate 1 was washed out with the binding buffer, and the cells were observed on CV1000. Images were collected as 2 μm of vertical z-stack range  and presented as MIP.HeLa cells were seeded on poly-5 cells per well. On day 1, the cells were co-transfected with pSuper vector encoding each AcP-TRap1Ex and pSuper.gfp. On day 2, they were stained with Hoechst 33342  in complete growth medium (500 μl) and incubated at 37°C for 20 min in a humidified 5% CO2 incubator. Conjugate 1  in a complete growth medium (100 μl) was then added and incubated at 37°C for 5 min in a humidified 5% CO2 incubator. Afterwards, the solution was replaced with fresh media, and the cells were observed on CV1000. Live-cell images were collected as 3.3 μm of vertical z-stack range  and presented as MIP. Time-lapse images were taken every 5 min up to 1 h. For the observation of β-actin drug effects on fluorescent response, the cells were transfected as described above. The cells were stained with Hoechst 33342 and conjugate 2 and then treated with the actin drug . The live-cell images were collected immediately as 3.3 μm of vertical z-stack range  and presented as MIP. The time-lapse images were taken as follows: Cytochalasin B 10-min intervals for up to 2 h; Latrunculin B 5-min intervals for up to 1 h; Jasplakinolide 3-min intervals for up to 30 min. The cells transfected with the non-recombinant pSuper were always prepared as control in every imaging experiment.On day 0, HeLa cells were seeded on a 35 mm 4-well Advanced TC glass bottom cell culture dish (Greiner Bio-One) at 5.0 × 10Kd value of BHQ1-binding aptamer with conjugate 1 is 4.7 μM), which was previously discovered through in vitro selection   of 1.5 μM    . The thrg Figure . Of the The proposed mechanism of aptamer binding involves the binding of two protein-targeting RNA ‘arms’ to the target protein. We attempted to truncate the arm sequence on both sides to ascertain whether we could optimize a minimal sequence for protein targeting. All the truncated aptamers showed reduced fluorescent response, indicating that the whole sequence of the protein-targeting arms is required for optimal β-actin binding .1, but no significant increase in fluorescent response was observed even up to 20 μM of the peptide . Increasing concentrations of the peptide were mixed with AcP-TRap1 and conjugate  peptide . Additio peptide . These r peptide . Anti-β-To determine whether the aptamers are capable of fluorescent labeling of endogenous β-actin in the context of human cells, we proceeded to imaging experiments in fixed cells. To verify the specific labeling of actin protein, co-staining of actin was performed with AcP-TRap1 and phalloidin, a well-known actin stain in fixed cells. Interestingly, no overlap staining was observed between AcP-TRap1 and phalloidin . Actin ein vitro actin polymerization assay. During actin polymerization reaction, the response of the aptamer was checked at different time points. As a result, the aptamer response showed an inverse relationship with the degree of actin polymerization  showed equivalent efficacy to the original AcP-TRap1  that is specific for the C-terminal epitope of β-actin , which has different sequences from those of AcP-TRap1 in the β-actin targeting ‘arms’  was also performed from the same initial RNA library as β-actin targeting aptamers. A bifunctional aptamer, KrP-TRap1 obtained from the in vitro selection for KRAS restored the fluorescence of BHQ1-probe only in the presence of KRAS in in vitro binding assay  or between AcP-TRap4 and antibody (BAR3)) was observed Figure . The antng assay . Thus, tin vitro selection is performed for such a complex, a highly specific P-TRap for the complex of G-actin and the partner protein could be isolated. These results reinforce the fact that this new method excels at protein labeling in an exquisitely selective manner. However, the binding of AcP-TRap to G-actin may affect the G-actin localization or the F-actin formation. Further validation of the new method might permit the detection of a variety of proteins without affecting their dynamics.This non-covalent and cooperative labeling technology permits live-cell imaging of protein dynamics in an extremely selective manner. A bifunctional aptamer for a given target protein can easily be isolated with a well-designed conventional selection. We have demonstrated the effectiveness of this new protein-labeling method through imaging of β-actin in human cells. In live-cell imaging of β-actin, the method allowed us to monitor the concentration change of G-actin through response to known chemical stimuli. This is the first reported imaging tool specific for G-actin in mammalian living cells. The identity of G-actin was confirmed independently by co-staining with fluorophore-conjugated DNase I in fixed cells. Although the fluorescent signals well overlapped with those of the fluorescent DNase I, the number of fluorescent spots observed was less than that of the fluorescent DNase I. One possible reason behind this is that AcP-TRap may not recognize G-actin that exists as a complex with other partner proteins. To verify this hypothesis, we examined the binding competition of AcP-TRap1 with three well-known G-actin-binding proteins, cofilin . Both coin vitro selection. A cell-permeable turn-on probe can simply be added to culture media to visualize protein dynamics. As for the modularity of the method, the probe-binding stem-loop structure can be replaced by other probe-binding structures (We have developed a live-cell protein imaging technology that uses a protein-targeting RNA aptamer with a turn-on fluorescent probe. One notable advantage of the technology is that it simply requires practices of commonly used cell biology techniques. A highly selective P-TRap for a specific target protein can be easily isolated by well-designed ructures  (Supplemructures . These agkab839_Supplemental_FilesClick here for additional data file.


In view of the rising relevance of emerging pollutants in the environment, this work studies the photodegradation of three antibiotics, evaluating the effects of the pH of the medium and the concentration of dissolved organic matter. Simulated light  was applied to the antibiotics Ciprofloxacin (Cip), Clarithromycin (Cla) and Trimethoprim (Tri), at three different pH, and in the presence of different concentrations of humic acids. The sensitivity to light followed the sequence: Cip > Cla > Tri, which was inverse for the half-life (Tri > Cla > Cip). As the pH increased, the half-life generally decreased, except for Cla. Regarding the kinetic constant k, in the case of Cip and Tri it increased with the rise of pH, while decreased for Cla. The results corresponding to total organic carbon (TOC) indicate that the complete mineralization of the antibiotics was not achieved. The effect of humic acids was not marked, slightly increasing the degradation of Cip, and slightly decreasing it for Tri, while no effect was detected for Cla. These results may be relevant in terms of understanding the evolution of these antibiotics, especially when they reach different environmental compartments and receive sunlight radiation. In recent years, antibiotics have been used massively to combat bacterial diseases, both in humans and in domestic animals, being recognized as emerging pollutants. This has even increased their scientific interest, as well as the concern of public administrations regarding this topic . To be nDegradation of the antibiotics that reach waterbodies is of main importance to avoid/diminish the magnitude of potential environmental issues. Within degradation processes, it is worth highlighting biodegradation and abiotic degradation, with especial relevance of photodegradation for the latter. As indicated by different authors ,13, it iThe evaluation of photodegradation processes can provide information about the persistence of antibiotics in the environment when they receive sunlight, but also about their possible removal during wastewater treatment ,15. It iAdditionally, it is necessary to bear in mind that one of the potential sources of organic matter in water is that which is solubilized from the soil and ends up reaching waterbodies . It alsoTaking all this background into account, this study is aimed to evaluate the effects of pH and humic acids on the photodegradation of three different antibiotics. Specifically, they belong to three of the groups most widely used in human medicine, being chemically clearly different: Ciprofloxacin (which belongs to the group of quinolones), Clarithromycin (which belongs to the group of macrolides), and Trimethoprim (which is an antibiotic of the group of diaminopyrimidines).The antibiotics used were ciprofloxacin (Cip) (purity 98%), clarithromycin (Cla) (purity 98%), and trimethoprim (Tri) (purity 98%), which were supplied by Sigma Aldrich . Its main characteristics are presented in + simulator  equipped with a 550 W m−2 Xenon lamp, and with quartz filters, with a cut-off at 285 nm. It is characterized by having a light spectrum similar to that of natural sunlight, in which the temperature is maintained at 32 ± 2 °C. Exposure times to simulated light were in the range 0.0833–192 h. Simultaneously, another set of samples remained in the dark at the same time intervals. A 50 µM antibiotic solution was used, containing separately each of the three antibiotics. Six mL of solution were introduced into glass tubes (in triplicate), with some of them being exposed to simulated light, and other equivalent in number remained in the dark, all this during the different times of the experiments. The concentration of each of the antibiotics was analyzed by HPLC after the different contact times.The photodegradation experiments were carried out in a Suntest CPS−1 for the first two antibiotics, and 1 mL min−1 for Cla. The temperature was kept constant at 25 °C throughout the analysis. Between each measurement, a wash was made with a solution composed of methanol and water (50:50).The equipment used for the quantification of antibiotics was an UltiMate 3000 HPLC chromatography device , with a quaternary pump, an autosampler, a thermostatted column compartment, and an UltiMate 3000 ultraviolet-visible detector. Attached to this equipment was a computer with version 7 of the Chromeleon software . Chromatographic separations were performed on a Luna C18 analytical column  from Phenomenex , and a safety column , packed with the same material as the column. The injection volume was 50 μL in the case of Cip and Tri, and 200 μL in the case of Cla. Flow rates were 1.5 mL minThe conditions in which Cla was separated were the following: the mobile phase consisted of acetonitrile (phase A), and 0.025 M monopotassium phosphate (phase B). The linear gradient elution program was run from 5 to 70% for phase A (and therefore 95 to 30% for phase B), with a time of 18 min. The initial conditions were restored in 2 min and were maintained for 3 min. The total analysis time was 25 min, with a retention of 13.6 min. The wavelength used for detection was 210 nm.In the case of Cip and Tri, they were separated under the following conditions: the mobile phase was acetonitrile (phase A) and 0.01 M phosphoric acid (pH = 2) for phase B. The linear gradient elution program was executed from 5 to 32% for phase A and from 95 to 68% for phase B, in a period of 10.5 min. The initial conditions were restored in 2 min. The total analysis time was 15 min, with a retention time of 6.5 min for Cip and 5.6 min for Tri. The wavelength used was 212 nm.C/C0 is the fraction of the initial concentration (C0) that remains in the suspension after a given time t (expressed in h), and k (h−1) is the dissipation kinetic constant. The half-life  of each compound was calculated as:After finishing with the quantification of all three antibiotics, a pseudo-first order kinetic model was used to describe kinetics results, as follows:To study the photodegradation at different pH, it was firstly adjusted in the solutions corresponding to each antibiotic, to reach values of 4.0, 5.5 and 7.0, using 0.5 M NaOH or 0.5 M HCl. Subsequently, the same steps described above were followed until the completion of the quantification of each of the antibiotics.−1. The pH of all solutions was adjusted to 5.5, with 0.5 M NaOH or 0.5 M HCl. The contact time was similar to the half-life of each of the antibiotics, being 15 min for Cip, 8 h for Tri, and 2 h for Cla. The half-lives were previously calculated from the experimental data of degradation in water at pH 4.0, described by the exponential decay model, from which the kinetic constant (k) was obtained, and from this the half-lives were calculated. The chemical characteristics of the humic acids used are described in [The study of the effect of humic acids was carried out at an antibiotic concentration of 50 µM, with different concentrations of humic acids, specifically: 0.1, 0.2, 0.4, 1.0, 2.0, and 20.0 mg Lribed in .Total organic carbon (TOC) was determined at time zero, 2 h, 16 h and 48 h (end of the experiment) by using a Multi N/C 2100 . It was quantified for Cip and Tri samples. TOC was not measured in the Cla samples since ethanol was used when dissolving the antibiotic, as previously mentioned.All determinations were made by triplicate.None of the three antibiotics showed significant degradation in the dark, at any of the pH and contact times (between 0–72 h) tested. Belden et al.  also repConsidering each antibiotic individually, starting with the one that showed the highest sensitivity to light, the degradation of Cip under simulated light was quite rapid for the three pH values studied, being above 85% after 1 h of exposure to the light radiation .Cla degradation under simulated light was slower and decreased with increasing pH values. After 1 h of exposure, it reached 30% at pH 4.0, 27% at pH 5.5, and 17% at pH 7.0 .Even slower was the degradation of Tri. After 1 h of exposure to simulated light, it reached less than 5%, at any of the three pH values tested .2 values (ranging 0.906–0.990, k follows the reverse order, increasing with pH for both Cip and Tri, while it decreases for Cla (The pseudo-first order kinetic model satisfactorily described experimental data, judging by the R for Cla .This behavior can be related to the percentages of the different species of antibiotics present as a function of pH, which are presented in a values (between 6.00–8.74, The distribution of species as a function of pH is similar for Cip and Tri, with dominance of positively charged forms at pH 4, while neutral forms predominate at pH 7. However, for Cla, positively charged species are predominant at both pH 4 and 7. Similar results were reported in a previous study , where tIn addition, TOC was determined in each of the samples exposed to simulated light at different times and pHs . The resC/C0 value going from 0.12 to 0.37 when the highest concentration of humic acids was added.In general, the presence of humic acids did not cause any changes in the degradation of the three antibiotics when the experiments were carried out in the dark . Under sPrevious studies reported that the presence of humic acids could cause opposite effects on the degradation of antibiotics, promoting it , or decrAll these results could be useful to understand the probable evolution of these three antibiotics when they are spread in environmental comportments, and they are subsequently exposed to variable incidence of solar radiation, under natural conditions. In addition, the results could aid in case of programing eventual treatments applicable in WWTP, in order to achieve the photodegradation of these compounds.Regarding future studies, this line of research could be further explored, with new antibiotics and with an additional variety of conditions tested. It would be interesting to shed further light and achieve further knowledge as regards eventual degradation under simulated natural sunlight, and also testing various catalyst materials with potential to enhance photocatalytic degradation.


The remarkable elastic properties of polymers are ultimatelydueto their molecular structure, but the relation between the macroscopicand molecular properties is often difficult to establish, in particularfor (bio)polymers that contain hydrogen bonds, which can easily rearrangeupon mechanical deformation. Here we show that two-dimensional infraredspectroscopy on polymer films in a miniature stress tester sheds newlight on how the hydrogen-bond structure of a polymer is related toits viscoelastic response. We study thermoplastic polyurethane, ablock copolymer consisting of hard segments of hydrogen-bonded urethanegroups embedded in a soft matrix of polyether chains. The conventionalinfrared spectrum shows that, upon deformation, the number of hydrogenbonds increases, a process that is largely reversible. However, the2DIR spectrum reveals that the distribution of hydrogen-bond strengthsbecomes slightly narrower after a deformation cycle, due to the disruptionof weak hydrogen bonds, an effect that could explain the strain-cycleinduced softening (Mullins effect) of polyurethane. These resultsshow how rheo-2DIR spectroscopy can bridge the gap between the molecularstructure and the macroscopic elastic properties of (bio)polymers. A detailed understandingof the connection between the macroscopic and microscopic propertiesof polymers is essential, not only for predicting the mechanical propertiesof synthetic polymers but also for understanding the molecular originof dysfunctional polymer systems, such as occur in for instance collagen-relateddiseases. The most straightforward way to investigate the molecularorigin of polymer elastic response is to directly observe the changesin molecular structure induced by externally applied strain. Suchexperiments have used a range of different structural probing methods,notably X-ray diffraction12 Combiningrheology with infrared spectroscopy (rheo-IR) to study the molecularchanges in polymers under applied strain . Furthermore, with conventional IR spectroscopy, inhomogeneousspectral broadening (due to a distribution of transition frequencies)cannot be easily separated from homogeneous spectral broadening .In the case of hydrogen-bonded (H-bonded) polymer networks,thestrain-induced structural changes generally involve rearrangementof the hydrogen-bonds (H-bonds) between molecular groups of adjacent(bio)polymer chains. Among the above-mentioned techniques, IR spectroscopyis very suitable to investigate such rearrangements, since the frequenciesand line shapes of the vibrational transitions contain detailed informationon the hydrogen-bond structure.d strain 1A has pr13 Inspired by rheo-IR spectroscopy, we here combinetwo-dimensional infrared spectroscopy with rheometry by insertinga miniature universal stress tester into a 2DIR setup (rheo-2DIR).We use this new method to investigate strain-induced changes in theH-bond distribution of thermal polyurethane, one of the most commonlyused polymers, that exhibits strain-cycle induced softening behaviorthat is believed to be related to changes in the H-bond structure.2These challenges can be addressed by means of two-dimensionalinfrared(2DIR) spectroscopy, which makes it possible to separate overlappingspectral bands, measure vibrational couplings, and separate the homogeneousand inhomogeneous contributions to the line broadening.–1 (fwhm) at 1 kHz repetition rate. The IR beamis split into a probe and reference beam (each 5%), and a pump beam(90%) that is aligned through a Fabry-Pérot interferometer.The pump and probe beams are overlapped in the sample , and the transmitted spectra of the probepulse in the presence and absence of the pump pulse are recorded witha 32-pixel mercury cadmium telluride array. The pump and probe polarizationsare at the magic angle (54.5°) to obtain polarization-independentspectra.13 In the rheo-2DIR setup (Supporting Information). The film thickness was31 ± 5 μm (Protex 002) and 18 ± 5 μm (Sagami001).A detailed description of the 2DIR setupcan be found in refs  and 15)15). BrieIR setup 1B, the p16 The mechanical response to deformation of TPUinvolves changes in the arrangement and strength of the H-bonds formedbetween the urethane links within hard segments and between the urethanelinks of hard and soft segments. In particular, the stress-softeningbehavior upon recovery of zero-stress condition after deformation(Mullins effect) is believed to be connected to the disruption ofweak H-bonds between hard and soft domains.2Thermoplastic polyurethane (TPU) is a block copolymercomposedof urethane- and polyether-based segments 1C. At ro17 Above400%, the polyurethane again stiffens (strain hardening), due to thelimited extensibility of polymer chains as it approaches the fracturepoint. The mechanical response of the sample during the second cycleis much more compliant compared to the first cycle. This strain-softeningbehavior (the Mullins effect)16 has beenextensively investigated, but its molecular origins are still notcompletely understood.2 Here, we show that rheo-2DIR spectroscopycan shed new light on this phenomenon by revealing how the H-bonddistribution changes upon deformation.–1, which are due to the hydrogen-bonded(1703 cm–1) and free (1733 cm–1) carbonyl groups.22 As we mentioned above, since these materials are poly(ether–urethane)s,H-bonds of different strength can form between urethane groups andurethane N–H and ether groups. Clearly, however, ether groupscannot H-bond to the urethane carbonyls. The lowering of the CO-stretchfrequency upon H-bond formation is a well-known effect, that can beused as a sensitive probe of the H-bond structure. The peak of thehydrogen-bonded carbonyl groups is much broader than that of the freeCO groups, and its shape reflects the distribution of H-bond strengthsin the sample (convoluted with the homogeneous line shape). 24). At higher strain, the finite extensibility of the chains leadsto an upturn of the stress–strain curve. When approaching themaximum extension of the chain, hydrogen bonds are weakened and broken,leading to a decrease in intensity of the hydrogen-bonded carbonylvibration in the strain-hardening region.25 To summarize, rheo-IR shows that in the strain-softening regime,the number of H-bond increases because of an enhanced alignment ofthe chains, while it decreases in the strain-hardening regime becausehydrogen bonds are weakened and broken while resisting extension.4, whileconventional IR scales as μ2, where μ is thetransition dipole moment of the vibrational transition).13–1 fwhm) pump pulseto excite molecular vibrations (in this case the CO-stretch vibration)at a specific frequency νpump, and measure the pump-inducedchange in absorption ΔA at all frequenciesusing a broad-band probing pulse that is detected in frequency-resolvedmanner. The pump polarization is set at an angle of ∼54.5◦ with respect to the strain direction and the probepolarization. Plotting ΔA we obtain two-dimensional IR spectra ata specific time delay, Tw, between pumpand probe pulses.13 In A is plotted as red contour areas and negative ΔA as blue contour areas.After unloading the sample, the infrared spectrumis very similarto the one observed before the deformation cycle 2D with tv = 0 →1 transition by the pump pulse causes a decrease in absorption atthe v = 0 → 1 transition (due to depletionof the v = 0 state and v = 1 →0 stimulated emission) and an increase in absorption at the v = 1 → 2 transition frequency.13 The dependence of the 2DIR response on the pump frequencyis a measure of the inhomogeneous broadening of the IR band, and thetwo-dimensional line shape can be used to disentangle inhomogeneousand homogeneous contributions to the line broadening.13 Since the inhomogeneous line shape reflects the distributionof H-bond strengths, we can thus investigate changes in this distributioncaused by the strain cycle. The simplest and most robust parameterto characterize the extent of inhomogeneous broadening is the inversevalue of the slope  of the2DIR contours:27 in the limiting case of purelyhomogeneous broadening, the ΔA contours arevertically aligned , whereas in thecase of purely inhomogeneous broadening the slope is 1.The resonant excitation of the Tw = 1 ps . Samples were strained up to desired deformation and allowed torelax for 10–15 min before measuring (measurement time 1–2h). In 27 which represents analternative observable of the H-bond inhomogeneity (see Supporting Information). When comparing experimentson Protex 002 and Sagami 001, we find that the decrease of the slopeafter the deformation cycle is reproducible, although the values ofthe nodal line slopes show small variations. Repeating the deformationcycle on the same sample does not further change the slope (see Supporting Information), similar to the stress–straincurve, which also tends to stabilize, with most of the softening occurringin the first deformation cycle. The decrease of the NLS indicatesthat the H-bond distribution has become narrower after a deformationcycle, suggesting that some of the H-bonds that are broken duringloading are not reformed upon recovery of zero-stress condition. Thisis confirmed by A < 0) signal ismaximal. It is difficult to observe this narrowing in the conventionalIR spectrum because of the changes in the background absorption upondeformation . After the deformation cycle, the diagonal carbonylpeak has become narrower, mostly due to disappearance of intensityat the high-frequency side. Thus, the narrowing of the H-bond distributionafter a deformation cycle is due to the disappearance of weak hydrogenbonds.28 Recent X-ray studies have attributed the strain-softeningbehavior of TPU to strain-induced softening of interfacial “fuzzy”regions between the hard and soft domains.2 Ourresults seem to confirm this idea, and they provide a molecular-levelexplanation of the strain-softening of the fuzzy regions. This pictureis confirmed by the lower nodal line slope observed in 2DIR spectrarecorded after deforming the sample at high (∼100 °C)temperature, which probably also destroys the weak hydrogen bondsin the unordered regions (see Supporting Information). The presence and the amount of the fuzzy interface will likelydepend on the degree of mixing between the hard and soft phases, whichis in turn determined by different experimental parameters, such assegments length, chemical composition, and thermal treatment.32 A different degree of mixing will thus affect the initial inhomogeneityand the amplitude of the decrease upon deformation, which probablyexplains the differences between the examined samples (Sagami 001and Protex 002).The rheo-2DIR results show that a strain cyclecauses an irreversiblereduction in the number of weak hydrogen bonds in TPU. These weakH-bonds are found mostly in the amorphous regions between the hardand soft segments, where the urethane NH groups form hydrogen bondsmostly to polyether instead of carbonyl groups.33 canprovide direct information on the degree of interchain coupling asa function of strain in biopolymer networks, where the mechanicalproperties are modulated by the formation and/or disruption of H-bonds.37 Rheo-2DIR can thus help to improve our understanding of the molecularorigin of the elastic response of not only synthetic but also, inparticular, biological polymer-based materials.To conclude, rheo-2DIR spectroscopy sheds newlight on the molecularprocesses that underlie the Mullin effect in polyurethane. Based onthese first experiments, we believe that rheo-2DIR can be a valuableaddition to the existing physical methods for studying the elasticproperties of materials. In particular, comparing the relative amplitudesof the rheo-IR and rheo-2DIR spectra


Max). A modified stenting technique was applied by landing an oversized DES in the distal segment with the largest luminal diameter and maintaining the distal stent edge partially expanded. Results. The mean dsDMax and stent lengths were 1.7 ± 0.3 mm and 62.6 ± 18.1 mm in the ESDV group and 2.7 ± 0.5 mm and 59.1 ± 16.0 mm in non-ESDV groups, respectively. The acute procedural success rate was high in both the ESDV and non-ESDV groups  with rare distal dissection . The target vessel failure (TVF) rate was 16.3% in the ESDV group and 12.1% in the non-ESDV group at a median follow-up of 65 months without significant differences after propensity score matching. Conclusions. PCI using contemporary DES with this modified stenting technique is effective and safe for diffuse CAD with extremely small distal vessels.Background. The optimal percutaneous coronary intervention (PCI) strategy and clinical outcomes of long lesions with an extremely small residual lumen remain unclear. This study aimed to assess the efficacy of a modified stenting strategy for diffuse coronary artery disease (CAD) with an extremely small distal residual lumen. Methods. 736 Patients who received PCI using second-generation drug-eluting stents (DES) ≥38 mm long were retrospectively included and categorized into an extremely small distal vessel (ESDV) group (≤2.0 mm) and a non-ESDV group (>2.0 mm) according to the maximal luminal diameter of the distal vessel (dsD Substantial clinical evidence supports the efficacy and safety of percutaneous coronary intervention (PCI) using the current generation drug-eluting stents (DESs) for treating long diffuse coronary lesions ,2,3,4,5.Max) measuring ≤2.0 mm treated using the modified stenting technique and current-generation DESs. We sought to evaluate patient outcomes in this at-risk population and compared them with those with a distal lumen of >2.0 mm.In this study, we investigated the acute procedural and long-term clinical outcomes in patients with long diffuse coronary artery disease (CAD) and maximal diameter of the distal segment  group, and the remaining patients were assigned to the non-ESDV group (dsDMax > 2.0 mm). Patients with simultaneous long lesions of dsDMax ≤ 2.0 and dsDMax > 2.0 mm in different vessels were categorized into the ESDV group. The baseline characteristics, risk factors for atherosclerotic cardiovascular disease, comorbidities, and medications of the included patients were obtained from the electronic medical records.Consecutive patients who underwent PCI at Chang Gung Memorial Hospital, LinKou, Taiwan, between January 2010 and December 2017 were screened retrospectively for eligibility. We identified cases from the medical records with at least one long coronary lesion treated with one or multiple overlapping second-generation DESs with a total stent length of ≥38 mm. We excluded patients presenting with ST-segment elevation myocardial infarction (STEMI) or cardiogenic shock. The included patients with dsDThe study was approved by the Institutional Review Board of Chang Gung Memorial Hospital. All the patients underwent standard medical management. The requirement for written consent from patients was waived owing to the retrospective nature of this study.All interventions were performed according to standard techniques, except for the modified stent deployment technique. For lesions with a small distal luminal diameter ≤ 2.0 mm, a modified stenting technique was used . To accoAll patients were pretreated with standard-dose dual antiplatelet therapy before and after the PCI procedure, according to the clinical condition and judgment of the primary care physician.Max ≤ 2.0 and >2.0 mm in different vessels, only events related to the vessel with dsDMax ≤ 2.0 mm were counted. All patients were clinically followed up via clinic visits or telephone interviews.Procedural success was defined as the attainment of residual diameter stenosis of ≤30% and thrombolysis in myocardial infarction (TIMI) flow grade 3 without angiographic dissection. The primary clinical endpoint was target vessel failure (TVF), defined as a composite of cardiac death, target vessel myocardial infarction (TVMI), and clinically driven-target vessel revascularization (TVR). Death was considered cardiac in origin unless obvious noncardiac causes could be identified. TVMI was defined as myocardial infarction that could be related to the target vessel but not to another vessel. TVR was defined as any repeat percutaneous intervention or coronary artery bypass graft (CABG) of any segment of the target vessel. TVR was considered clinically driven if revascularization was performed in patients with ischemic signs confirmed using noninvasive tests or functional assessment, irrespective of the ischemic symptoms. Definite or probable stent thrombosis was defined according to the Academic Research Consortium criteria . For thet-test was used to test continuous variables, and the results were expressed as mean ± standard deviation (SD). Propensity score matching was performed at a ratio of 1:1 between the groups. The following variables were used in this analytical model: age, sex, smoking status, diabetes mellitus, hypertension, hyperlipidemia, chronic kidney disease, peripheral artery disease, left ventricular ejection fraction < 40%, clinical presentation of MI, history of MI, history of stroke, number of diseased vessels, culprit vessel, left main disease, chronic total occlusion (CTO), moderate-to-severe calcification, duration of dual-antiplatelet therapy, and stent length. The match tolerance was set to 0.01. The survival curve was plotted using the Kaplan–Meier method, and significance was examined using the log-rank test. Univariate Cox proportional hazard analysis was used to evaluate potential predictors of TVF. All variables (p < 0.05) in the univariate Cox regression analysis were then entered into the multivariate Cox proportional hazard model to determine the independent predictors of long-term TVF. p < 0.05 for a two-sided test was considered statistically significant. All statistical analyses were performed using SPSS version 20.0 . The Chi-square test and Fisher’s exact test, if necessary, were used to compare the categorical variables. The two-sample p = 0.019), and a lower prevalence of smoking  compared with the non-ESDV group. The mean dsDMax was 1.7 ± 0.3 mm and 2.7 ± 0.5 mm in ESDV and non-ESDV groups, respectively (p < 0.005). The ESDV group had more CTO lesions than the non-ESDV group .Among the screened patients, 736 were eligible for analysis. Of these, 307 (42%) patients were categorized into the ESDV group and the remaining 429 (58%) into the non-ESDV group. The baseline and angiographic characteristics of the study population are summarized in p < 0.0001). High-pressure post-dilatation was performed in 99.3% of patients in both groups. There was no significant difference in the number of stents . However, patients in the ESDV group had a longer stent length  and a smaller mean stent diameter  than those in the non-ESDV group.Procedural details and outcomes are summarized in p = 0.7). Angiographically detectable distal edge dissection was observed in one (0.3%) patient in the ESDV group and two (0.5%) patients in the non-ESDV group and was successfully rescued by additional stenting in all cases.The acute procedural success rates were similar between the ESDV and non-ESDV groups . The rate of complete follow-up was 94.1% and 96.5% (p = 0.15) in the ESDV and the non-ESDV groups, respectively. As shown in The median follow-up was 65.4 months (interquartile range: 50.9–89.8 months) in the ESDV group and 64.5 months (interquartile range: 51.3–88.8 months) in the non-ESDV group (p = 0.73) along with cardiac death, all-cause mortality, TVMI, CDTVR, stroke, and stent thrombosis  is another potential treatment for small and very small vessels, and it has been shown to be non-inferior to DES in recent years. However, the lesions treated with DCB in these clinical trials were short (ranging from 10.5–23 mm in length) with a relatively larger vessel diameter (ranging from 2.11–2.75 mm in size) ,22,23,24Our study had several limitations. First, this was a single-center retrospective study; therefore, it is inherently prone to bias. Because that patients with the long diffuse disease and an extremely small distal lumen represented a small proportion of patients treated with PCI, the patient number in this study was also limited. Seconds, patients estimated by operators to have a high procedural risk may have avoided PCI. The findings of this study cannot be extrapolated to all long ESDV lesions. Third, this study lacked a control group with ESDV treated using the standard stenting technique, which is not feasible in terms of the risk of distal edge dissection. Therefore, we could not conclude any improvement in the outcomes with the modified stenting technique. Fourth, intravascular imaging was performed in a relatively small proportion of patients. Angiography alone was not capable of evaluating atherosclerotic burden and distinguishing between true small vessels and diffuse diseases with small residual diameters. Last, at the segment distal to the stent of the target vessel, significant stenosis could exist because of diffuse atherosclerosis. Stenting was hardly possible for this segment. Even if adjunctive balloon dilation was performed, residual ischemia could remain after the procedure. Further prospective multicenter trials enrolling larger patient numbers with the guidance of intravascular imaging and functional assessment are mandatory to validate the efficacy and safety of this modified stenting technique in treating the long diffuse lesion with an extremely small luminal diameter.The present study demonstrated that PCI using a contemporary DES and a modified stenting technique resulted in high acute procedural success and favorable long-term clinical outcomes in long diffuse coronary lesions with an extremely small residual lumen. Larger prospective studies are required to corroborate the findings of this retrospective analysis.


Cholesterol, lipids, and lipid metabolism are important in prostate cancer. Lipid metabolism interacts with androgens which are of clear importance in prostate cancer. Additionally, lipid metabolism is intimately involved in the interaction between immune and cancer cells. During cancer progression, there are changes in lipid metabolism in both prostate cancer cells and immune cells; furthermore, these cells can interact with each other. Lipids and cholesterol in the circulation also have a role and may prove to be a future target for diagnostic tools and surveillance in prostate cancer. Modulation of lipid metabolism during cancer development and progression is one of the hallmarks of cancer in solid tumors; its importance in prostate cancer (PCa) has been demonstrated in numerous studies. Lipid metabolism is known to interact with androgen receptor signaling, an established driver of PCa progression and castration resistance. Similarly, immune cell infiltration into prostate tissue has been linked with the development and progression of PCa as well as with disturbances in lipid metabolism. Immuno-oncological drugs inhibit immune checkpoints to activate immune cells’ abilities to recognize and destroy cancer cells. These drugs have proved to be successful in treating some solid tumors, but in PCa their efficacy has been poor, with only a small minority of patients demonstrating a treatment response. In this review, we first describe the importance of lipid metabolism in PCa. Second, we collate current information on how modulation of lipid metabolism of cancer cells and the surrounding immune cells may impact the tumor’s immune responses which, in part, may explain the unimpressive results of immune-oncological treatments in PCa. Prostate cancer (PCa) is the most common malignancy among men and either the second or the third most common cause of cancer death in the developed countries . In 2020While localized prostate cancer can often be managed curatively, treatment of advanced disease is based on androgen deprivation since the growth of PCa initially relies on androgens. Unfortunately, PCa eventually develops castration resistance, i.e., its ability to grow and progress despite a low androgen level. Lipid metabolism is known to be disturbed in cancer cells . In addiThe growth and progression of PCa depend on androgen receptor (AR) signaling, which is the target of established oncological treatments of advanced PCa. Activation of AR targets several genes in the lipid metabolic pathway ,6,7. ConIntraprostatic inflammation is another trait associated with PCa and which can be affected by androgens. In humans, androgen deprivation therapy leads to increased infiltration by immune cells into the prostate . In addiInflammation and immune cell infiltration may have dual roles in the microenvironment surrounding cancer cells . While oCancers can be roughly categorized into immunologically hot or cold types based on their immune responses and immunological activity . In immuImmune-oncological (IO) treatments targeted to activate cytotoxic T-cells have mostly failed in PCa treatment; only a minority of patients have exhibited good treatment responses . The mecRecently, research interest has been focused on the possible link between the regulation of lipid metabolism and immune responses. It remains unclear to what degree the altered lipid metabolism in PCa cells modulates the regulation of the immune response, and whether lipid metabolism is reciprocally altered by immune responses. This review assesses the current knowledge about how lipid metabolism interacts with the immune environment around the PCa tumor cells. First, we describe how lipid metabolism is involved in PCa progression. Second, we review current knowledge on how lipid metabolism in surrounding immune cells is altered in PCa and other solid tumors, and how this may impact the regulation of tumor immune responses. Finally, we review how these may be affected by the circulating lipids and cholesterol.Lipid metabolism is upregulated in PCa, especially in the context of castration resistance. Lounis et al.  conducteIn PCa cells, AR modulates the expression of many important genes in the lipid metabolism pathways . Sterol SREBPs act as transcription factors which bind to sterol regulatory element or E-boxes in the promoter area and activate the expression of lipid metabolism-related genes such as low-density lipoprotein (LDL) receptor and HMG CoA synthase and reductase genes . SREBPs Lipid metabolism is also affected by a host of external influences and other metabolic disorders which are too numerous to cover in this article. A review on that topic has been published elsewhere .Because of their crucial role in the regulation of lipid metabolism, SREBPs can be thought of as master regulators of fatty acid and cholesterol synthesis since not only do they induce the activation of FASN, but they also upregulate cholesterol metabolism by inducing the mevalonate pathway . In partThe importance of SREBP activity for prostate cancer growth is now well demonstrated. Preclinical studies have shown that inhibition of SREBP signaling using fatostatin, a compound which blocks the activity of all forms of SREBP by inhibiting the binding of the SCAP protein to SREBP, suppressing cell proliferation in AR-positive prostate cancer cells, decreasing AR-positive prostate tumor growth, and lowering blood PSA in mice. When combined with docetaxel, fatostatin decreased the proliferation and induced cellular apoptosis in AR-negative cells especially if the cells harbored the p53 mutation ,25. FurtFASN likely has a role in PCa progression. In human samples, the expressions of the FASN and androgen receptor variant 7 (AR-V7) were found in many metastatic tumors, highlighting their importance in advanced PCa . The inhThus, in summary, a modulation of lipid metabolism in PCa has been shown to be important especially during cancer progression and the development of drug resistance. The AR regulates lipid metabolism especially by inducing SCAP expression, mandatory conjugates for SREBP activation. SREBPs in turn augment the expression of the AR. Thus, inhibition of SREBPs and FASN can be considered as potential targets for future PCa therapies. Burch et al.  investigIn another study, the lipidome and activity of lipid pathways were characterized in non-cancerous prostate cells and hormone-sensitive, castration resistant, and docetaxel resistant PCa cell lines . While gLi et al.  investigLipidomic changes in liquid biopsies using blood or urine samples have been investigated among PCa patients for the purpose of finding novel biomarkers for PCa detection. In 2000, Filella et al.  noticed Zhou et al.  were ablIn urine and prostate tissue samples, a high ratio of phosphatidylcholines and lysophosphatidylcholines was associated with PCa compared to samples from benign prostate hyperplasia patients in a Japanese trial . Lin et Taken together, the lipidome profile is altered in tissue samples and liquid biopsy specimens of PCa patients as well as PCa cells compared to non-cancerous cells. The lipidome seems to be constantly modulated during cancer progression and castration resistance. Unfortunately, it remains unclear whether a lipidomic change is the cause or consequence of cancer progression. Nevertheless, in the future, either the lipidome or specific lipid species might prove to be prognostic for PCa surveillance and could possibly be used as a diagnostic tool for PCa diagnosis. Distinct from lipid metabolism, cholesterol metabolism also has an important role in prostate tissue and in PCa progression; while benign prostate epithelial cells synthesize cholesterol, it seems that PCa cells accumulate even more cholesterol. The abundance of cholesterol in PCa cells is due to increased cholesterol production de novo and elevated uptake from the circulation ,43. In aIn PCa, it has been shown that in comparison to normal cells, cancer cells are able to produce more cholesterol; the cholesterol producing pathways and cholesterol uptake are upregulated whereas the cholesterol efflux is downregulated. These alterations are known to occur especially during PCa progression . CholestCholesterol metabolism in PCa cells is affected by the interaction with the microenvironment. Co-culturing of PCa cells and cancer-associated fibroblasts (CAFs) in a three-dimensional (3D) culture, gene expression analysis of PCa cells revealed that cholesterol and steroid biosynthesis pathways were upregulated as compared to the state where PCa cells were cultured without the presence of CAFs . EspeciaIn summary, cholesterol is crucial for prostate cancer cells, and its production is upregulated during the development of castration resistance. In addition, cholesterol production likely has an important role in enzalutamide resistance. Cholesterol metabolism in PCa cells is affected by the microenvironment surrounding the tumor.Even though statin treatment in preclinical models seemed to inhibit the growth of tumor cells, one study in experimental animals administered a low-dose of statin (50 nM) and showed opposite results; after low-dose statin treatment, PCa tumors in mice were growing even better than in the untreated mice . These iIt was demonstrated that androgen depletion enhanced the transition of bone marrow stromal cells into adipocytes . AdipocySo far, only a few clinical trials investigating the impact of statin use on prostate cancer progression have been conducted. We performed a clinical trial assessing the impact of high-dose (80 mg daily) atorvastatin administration on prostate cancer tissue and blood markers before prostatectomy . In the Recently Jeong et al.  investigThese trials once again underline the importance of understanding cholesterol metabolism as a whole during PCa progression and indicate that perhaps statins need to be used in high doses in order to elicit beneficial responses in PCa.Fatty acid metabolism is important for tumor development and progression in many ways, such as increasing the synthesis and storage of fatty acids and decreasing lipotoxicity and ferroptosis in tumors . MaintaiFerroptosis is a recently identified new form of programmed cell death. Ferroptosis is caused by the accumulation of iron-dependent lipid peroxides in the cells. Lipid metabolism is the main regulator of this event. The role of ferroptosis in cancer development and progression is under investigation. Ferroptosis might also impact the immune responses against tumors. Thus, targeting the upregulation of ferroptosis in tumor cells might be a good target for cancer treatment, especially in cancers with high lipid metabolism. This topic has been recently reviewed ,64. HereAn evaluation of the RNA-Seq in prostate cancer tumors compared to noncancerous prostate tissue showed that the gene panel of ferroptosis-related genes was differently expressed in tumors as compared to healthy tissue . Based oWhile it is known that AR activation promotes lipid accumulation in prostate cancer cells, intracellular lipid levels were increased even after treatment with enzalutamide, an AR signaling inhibitor . EspeciaIt appears that cancer cells can downregulate ferroptosis via a SREBP1 mediated pathway: in tumors where PI3K–Akt–mTOR signaling is active, SREBP1 is activated, and this protein suppresses ferroptosis . When SRCastration levels of testosterone inhibited the growth of testosterone sensitive PCa cells by inducing ferroptosis which led to increased immune cell infiltration into the tumor site ,70. In pIncreasing ferroptosis by modulation of lipid metabolism in PCa might be a novel target for treatment to enhance the impact of the traditional therapies. The impact of the induction of ferroptosis in the immune environment of the PCa tumor needs further clarification. AR activation can not only induce energy production via glycolysis but also upregulate de novo fatty acid synthesis and fatty acid uptake and oxidation ,73. LipiIn castration resistance, PCa cells typically display over-expression of AR-regulated metabolic genes compared to androgen-sensitive tissues or cells. Thus, interest has been focused on whether lipid metabolic processes could be targeted as a novel treatment for advanced PCa ,78. SeveIn antiandrogen resistance, there is an increased number of glycerophospholipid species with longer and more unsaturated fatty acyl chains detected in PCa cells . FurtherIn summary, fatty acid metabolism appears to be another crucial metabolic factor in castration resistance and may provide a target for reversing of resistance to antiandrogen resistance. Fatty acid metabolism appears to be linked with ferroptosis in PCa.The metabolism and supply of lipids in both prostate cancer cells and immune cells of the tumor microenvironment may be altered at multiple levels. First, the disturbed lipid metabolism in cancer cells may affect the surrounding immune cells. Second, changes in lipid metabolism in the immune cells may affect their activity and reciprocally also affect cancer cells. Third, the supply of lipids from the serum may promote changes in both immune and cancerous cells.In a mouse model of melanoma, gene enrichment analysis of tumors revealed that lipid associated metabolic pathways were enriched in Treg cells in the tumor as compared to cells from peripheral tissue . A furthRecently the role of cholesterol in immune cell regulation in solid tumors has become a focus of research interest. Ma et al. showed that an increased cholesterol content in CD8+ T-cells and in the tumor microenvironment increased the expression of several immune checkpoints, PD-1, 2B4, TIM-3, and LAG-3, and led to T-cell exhaustion . Thus, bMany cholesterol metabolism related enzymes have an impact on the activity of CD8+ T-cells. Yang et al.  showed tChanges in lipid metabolism of immune cells can induce treatment resistance in prostate cancer cells. In a pre-clinical trial exploiting both mice and cell models, El-Kenawi et al.  were ablIn castrated and eugonadal mice fed with an omega-3-enriched diet, the growth of TRAM-C2 cell xenografts was decreased in comparison to mice fed with an omega-6-enriched diet . An omegA summary of studies in this section is collected in Pharmacological interventions targeting lipid metabolism have demonstrated effects on immune cells in the tumor microenvironment in cases of prostate cancer. In the ESTO1 trial, atorvastatin use before prostatectomy did not significantly change the intraprostatic inflammation score compared to placebo when all subjects were analyzed together. However, when the analysis excluded patients who dropped out during the trial (did not use the study drugs), the intraprostatic inflammation score was decreased among statin users in men with high-grade PCa . In the REduction by DUtasteride of prostate Cancer Events (REDUCE) trial, a high level of high-density lipoprotein (HDL) in the serum was associated with a lower risk for acute inflammation in prostate tissue, while serum levels of total cholesterol, LDL, and triglycerides had no impact . On the The Prostate Cancer Prevention Trial (PCPT) randomized men with no known history of prostate cancer to either finasteride, a 5α-reductase inhibitor of conversion of testosterone to dihydrotestosterone, or placebo. In the placebo arm, chronic inflammation in prostate biopsies was associated with the risk of high-grade PCa . In the Furthermore, a positive correlation between LDL levels and pro-inflammatory (M1) macrophages and a negative correlation between LDL and anti-inflammatory (M2) macrophages was shown in human adipose tissue collected from healthy kidney donors . TreatmeIn addition, exposure to the tyrosine kinase inhibitor, ESK981, decreased tumor growth in prostate cancer cell lines and mouse xenografts by targeting 1-phosphatidylinositol-3-phosphate 5-kinase (PIKfyve), a lipid kinase . InhibitTreatment with ezetimibe decreased the tumor growth of several cancer cells, including prostate cancer cells, in mice . This waThe prostate is surrounded by white adipose tissue called the periprostatic adipose tissue (PPAT). Prostate and PPAT are separated by the prostate capsule, however, the prostate vasculature crosses the PPAT . As PPATPPAT serves as a source of fatty acids for tumor cells. There is some evidence that PPAT can secrete the adipokine, leptin, which might stimulate PCa progression ,111,112.Cholesterol, lipids, and lipid metabolism play key roles in the progression of PCa. While lipid metabolism interacts with AR signaling, in addition it is closely involved in the regulation of the immune system in the tumor microenvironment. Disturbances in the regulation and changes in the properties of PCa cells and immune cells seem to be important during cancer progression. It is evident that PCa cells can influence lipid metabolism in immune cells in the microenvironment of the tumor and vice versa since both cell types are susceptible to changes in the regulation of lipid metabolism. Furthermore, serum lipid profiling might serve as a target for diagnostic tools and surveillance of PCa progression. Thus, it is important to characterize the impact of changes in the regulation of lipid metabolism leading to disturbances in the properties of prostate cancer cells and immune cells in the tumor microenvironment during tumor progression. By clarifying these alterations, we can gain a better understanding of the interaction between PCa and immune responses, thus creating an opportunity to improve the treatment of this life-threatening disease.