bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gene LY96 is an M2 macrophage‐related biomarker and is associated with immunosuppression in renal cell carcinoma
Authors: Li Weiquan , Meng Xiangui , Yu Tiexi , Shi Xin , Dong Wei , Ruan Hailong , Wang Tao , Xiao Wen 
Published: September 2023

AbstractLymphocyte Antigen 96 (LY96) was identified as an oncogene in several tumors. However, its role in renal cancer has not been explored. In the study, LY96 is identified abnormally expressed using several public kidney cancer sequencing data. The expression level of LY96 is validated using paired clinical samples. Survival analyses and ROC curves are used to examine its prognostic and diagnostic value. Gene sets enrichment analyses (GSEA) show LY96 might influence immune processes. Then immune infiltration analyses results suggest that LY96 is positively correlated with M2 macrophages infiltration in RCC. Single‐cell data are used to verify its association with macrophages. Moreover, LY96 is positively with various immune scores and might affect the efficacy of immunotherapy. Drug screening results show LY96 might be the target of vemurafenib and etoposide. Further experiments confirm the spatial co‐localization of LY96 and M2, and knocking down LY96 can inhibit M2 polarization. Cell viability experiments indicate that knocking down LY96 would result in a decrease in the resistance of M2 macrophages to etoposide. The study shows LY96 could act as an unfavorable biomarker for RCC and possibly contribute to cancer progression by promoting the infiltration of M2 macrophage. LY96 could be a novel therapeutic target for RCC.
Deep learning–based dose prediction to improve the plan quality of volumetric modulated arc therapy for gynecologic cancers
Authors: Gronberg Mary P. , Jhingran Anuja , Netherton Tucker J. , Gay Skylar S. , Cardenas Carlos E. , Chung Christine , Fuentes David , Fuller Clifton D. , Howell Rebecca M. , Khan Meena , Lim Tze Yee , Marquez Barbara , Olanrewaju Adenike M. , Peterson Christine B. , Vazquez Ivan , Whitaker Thomas J. , Wooten Zachary , Yang Ming , Court Laurence E. 
Published: September 2023

AbstractBackgroundIn recent years, deep‐learning models have been used to predict entire three‐dimensional dose distributions. However, the usability of dose predictions to improve plan quality should be further investigated.PurposeTo develop a deep‐learning model to predict high‐quality dose distributions for volumetric modulated arc therapy (VMAT) plans for patients with gynecologic cancer and to evaluate their usability in driving plan quality improvements.MethodsA total of 79 VMAT plans for the female pelvis were used to train (47 plans), validate (16 plans), and test (16 plans) 3D dense dilated U‐Net models to predict 3D dose distributions. The models received the normalized CT scan, dose prescription, and target and normal tissue contours as inputs. Three models were used to predict the dose distributions for plans in the test set. A radiation oncologist specializing in the treatment of gynecologic cancers scored the test set predictions using a 5‐point scale (5, acceptable as‐is; 4, prefer minor edits; 3, minor edits needed; 2, major edits needed; and 1, unacceptable). The clinical plans for which the dose predictions indicated that improvements could be made were reoptimized with constraints extracted from the predictions.ResultsThe predicted dose distributions in the test set were of comparable quality to the clinical plans. The mean voxel‐wise dose difference was −0.14 ± 0.46 Gy. The percentage dose differences in the predicted target metrics of and were −1.05% ± 0.59% and 0.21% ± 0.28%, respectively. The dose differences in the predicted organ at risk mean and maximum doses were −0.30 ± 1.66 Gy and −0.42 ± 2.07 Gy, respectively. A radiation oncologist deemed all of the predicted dose distributions clinically acceptable; 12 received a score of 5, and four received a score of 4. Replanning of flagged plans (five plans) showed that the original plans could be further optimized to give dose distributions close to the predicted dose distributions.ConclusionsDeep‐learning dose prediction can be used to predict high‐quality and clinically acceptable dose distributions for VMAT female pelvis plans, which can then be used to identify plans that can be improved with additional optimization.
Deformable lung 4DCT image registration via landmark‐driven cycle network
Authors: Matkovic Luke , Lei Yang , Fu Yabo , Wang Tonghe , Kesarwala Aparna H. , Axente Marian , Roper Justin , Higgins Kristin , Bradley Jeffrey D. , Liu Tian , Yang Xiaofeng 
Published: September 2023

AbstractBackgroundAn automated, accurate, and efficient lung four‐dimensional computed tomography (4DCT) image registration method is clinically important to quantify respiratory motion for optimal motion management.PurposeThe purpose of this work is to develop a weakly supervised deep learning method for 4DCT lung deformable image registration (DIR).MethodsThe landmark‐driven cycle network is proposed as a deep learning platform that performs DIR of individual phase datasets in a simulation 4DCT. This proposed network comprises a generator and a discriminator. The generator accepts moving and target CTs as input and outputs the deformation vector fields (DVFs) to match the two CTs. It is optimized during both forward and backward paths to enhance the bi‐directionality of DVF generation. Further, the landmarks are used to weakly supervise the generator network. Landmark‐driven loss is used to guide the generator's training. The discriminator then judges the realism of the deformed CT to provide extra DVF regularization.ResultsWe performed four‐fold cross‐validation on 10 4DCT datasets from the public DIR‐Lab dataset and a hold‐out test on our clinic dataset, which included 50 4DCT datasets. The DIR‐Lab dataset was used to evaluate the performance of the proposed method against other methods in the literature by calculating the DIR‐Lab Target Registration Error (TRE). The proposed method outperformed other deep learning‐based methods on the DIR‐Lab datasets in terms of TRE. Bi‐directional and landmark‐driven loss were shown to be effective for obtaining high registration accuracy. The mean and standard deviation of TRE for the DIR‐Lab datasets was 1.20 ± 0.72 mm and the mean absolute error (MAE) and structural similarity index (SSIM) for our datasets were 32.1 ± 11.6 HU and 0.979 ± 0.011, respectively.ConclusionThe landmark‐driven cycle network has been validated and tested for automatic deformable image registration of patients’ lung 4DCTs with results comparable to or better than competing methods.
Rapid MR elastography of the liver for subsecond stiffness sampling
Authors: Anders Matthias , Meyer Tom , Warmuth Carsten , Pfeuffer Josef , Tzschaetzsch Heiko , Herthum Helge , Shahryari Mehrgan , Degenhardt Katja , Wieben Oliver , Schmitter Sebastian , Schulz‐Menger Jeanette , Schaeffter Tobias , Braun Juergen , Sack Ingolf 
Published: September 2023

AbstractPurposeDepicting the stiffness of biological soft tissues, MR elastography (MRE) has a wide range of diagnostic applications. The purpose of this study was to improve the temporal resolution of 2D hepatic MRE in order to provide more rapid feedback on the quality of the wavefield and ensure better temporal sampling of respiration‐induced stiffness changes.MethodsWe developed a rapid MRE sequence that uses 2D segmented gradient‐echo spiral readout to encode 40 Hz harmonic vibrations and generate stiffness maps within 625 ms. We demonstrate the use of this technique as a rapid test for shear wave amplitudes and overall MRE image quality and as a method for monitoring respiration‐induced stiffness changes in the liver in comparison to 3D MRE and ultrasound‐based time‐harmonic elastography.ResultsSubsecond MRE allowed monitoring of increasing shear wave amplitudes in the liver with increasing levels of external stimulation within a single breath‐hold. Furthermore, the technique detected respiration‐induced changes in liver stiffness with peak values (1.83 ± 0.22 m/s) at end‐inspiration, followed by softer values during forced abdominal pressure (1.60 ± 0.22 m/s) and end‐expiration (1.49 ± 0.22 m/s). The effects of inspiration and expiration were confirmed by time‐harmonic elastography.ConclusionOur results suggest that subsecond MRE of the liver is useful for checking MRE driver settings and monitoring breathing‐induced changes in liver stiffness in near real time.
Improved 1H body imaging at 10.5 T: Validation and VOP‐enabled imaging in vivo with a 16‐channel transceiver dipole array
Authors: Schmidt Simon , Ertürk M. Arcan , He Xiaoxuan , Haluptzok Tobey , Eryaman Yiğitcan , Metzger Gregory J. 
Published: September 2023

AbstractPurposeTo increase the RF coil performance and RF management for body imaging at 10.5 T by validating and evaluating a high‐density 16‐channel transceiver array, implementing virtual observation points (VOPs), and demonstrating specific absorption rate (SAR) constrained imaging in vivo.MethodsThe inaccuracy of the electromagnetic model of the array was quantified based on B1+ and SAR data. Inter‐subject variability was estimated using a new approach based on the relative SAR deviation of different RF shims between human body models. The pTx performance of the 16‐channel array was assessed in simulation by comparison to a previously demonstrated 10‐channel array. In vivo imaging of the prostate was performed demonstrating SAR‐constrained static RF shimming and acquisition modes optimized for refocused echoes (AMORE).ResultsThe model inaccuracy of 29% and the inter‐subject variability of 85% resulted in a total safety factor of 1.91 for pelvis studies. For renal and cardiac imaging, inter‐subject variabilities of 121% and 141% lead to total safety factors of 2.25 and 2.45, respectively. The shorter wavelength at 10.5 T supported the increased element density of the 16‐channel array which in turn outperformed the 10‐channel version for all investigated metrics. Peak 10 g local SAR reduction of more than 25% without a loss of image quality was achieved in vivo, allowing a theoretical improvement in measurement efficiency of up to 66%.ConclusionsBy validating and characterizing a 16‐channel dipole transceiver array, this work demonstrates, for the first time, a VOP‐enabled RF coil for human torso imaging enabling increased pTx performance at 10.5 T.
Physico‐chemical properties and in‐vitro biocompatibility of thermo‐sensitive hydrogel developed with enhanced antimicrobial activity for soft tissue engineering
Authors: Shahzadi Uzma , Zeeshan Rabia , Tabassum Sobia , Khadim Hina , Arshad Muhammad , Ansari Arsalan Ahmad , Safi Sher Zaman , ul Haq Rana Intisar , Asif Anila 
Published: September 2023

AbstractSmart materials such as thermo‐sensitive in situ forming hydrogels can be effective agents in drug delivery and tissue regeneration with minimal invasion. Injection method would avoid complex surgical procedures facilitating rapid recovery process. In this research, we report the fabrication of an easy, reproducible thermo‐sensitive hydrogel constituting of chitosan (CHI), glycerol phosphate (GP) with variable quantity of ‐poly‐l‐lysine (PS). Fourier‐transform infrared spectra exhibited hydrogel formation where interactions between CHI and GP were seen. The gelation kinetics presented gelation time of 8 min at physiological temperature. The results indicated an increase in degradation rate with the passage of time. Contact angles measurements were employed to observe hydrophilic characteristics which were shown to be favorable. Mechanical strength was determined to be in the range of ~0.1–0.6 MPa for all the hydrogels. Due to intrinsic antibacterial features of CHI and PS, the hydrogels showed potent antibacterial activity against Escherichia coli, Staphylococcus aureus, and Methicillin‐resistant S. aureus (MR‐SA). Interestingly, PS's addition in the hydrogel resulted in potent antibacterial activity against clinically relevant MR‐SA. The hydrogels can hence be delivered to a specific target for localized treatments where the potential of inhibiting multidrug resistant strain is clinically relevant. Biocompatibility of the hydrogels was seen by an overall increase in cell viability of mouse fibroblast cells and scratch assay revealed favorable migration potential. Proangiogenic Vascular endothelial growth factor (VEGF)'s expression showed a gradual increase with increasing concentration of PS, whereas one composition demonstrated a slight increase in the expression of cytosolic prostaglandin E synthase (cPGES) as determined by RT‐PCR. Overall, an increase in PS content of the hydrogels resulted in simultaneously enhanced antibacterial efficiency and marked increase in fibroblast cell viability, hence, reiterating their potential as potent antibacterial agents that can be explored as wound healing agents. In conclusion, novel antibacterial thermo‐sensitive hydrogels were synthesized with a potential of regulating proangiogenic and tissue regeneration factors that highlight their role as wound healing agents.
Socioeconomic status significantly impacts childhood cancer survival in South Africa
Authors: Hendricks Marc , Cois Annibale , Geel Jennifer , van Heerden Jaques , Dandara Collet , Mohamed Kharnita , Donald Kirsten A. , Kruger Mariana 
Published: September 2023

AbstractBackground and aimsSignificantly discrepant survival rates have been documented in single disease childhood cancer cohorts in South Africa; those from higher socioeconomic groups were shown to have a significantly lower risk of death than those from less affluent households. This study aimed to determine the impact of socioeconomic status (SES) on childhood cancer survival using pooled South African data.MethodsFive databases spanning January 2000 to December 2021 were interrogated. SES status was assigned based on a public sector annual household income classification. H0 households (formally unemployed) received free healthcare. H1, H2 and H3 (annual income > United States Dollar [USD] 19,000) households paid for healthcare relative to their income. The Spearman test assessed correlations between SES and disease stage in patients with solid tumours. Hazard ratios were determined using Cox regression modelling. The Kaplan–Meier procedure estimated overall survival (OS).ResultsA total of 1598 children were eligible for analysis; 1269 had a solid tumour with a negative correlation between SES and stage (Spearman rho = −.178; p < .001). Patients with solid tumours and lower SES showed proportionately higher numbers of stage III and IV disease (p < .01). This proportion decreased with higher SES categories. In the multivariate analyses adjusted for sex, age, tumour type and stage, higher SES was associated with lower mortality risk (p < .001), indicating that the impact of SES on survival was in excess of any effect that could be explained by lower stage disease alone. There was a strong positive correlation between race and SES (Fisher's exact tests, p < .001) across all groups and all SES strata. Five‐year OS was 85.3% in children from H3 households versus 46.3% in children from H0 households (p < .001).ConclusionSES significantly impacts childhood cancer survival for children with solid tumours in South Africa. SES is a robust surrogate for race in South Africa as a prognostic metric of disease outcome in childhood cancer. Advocacy to increase social support for impoverished patients is essential to achieve equitable improvements in outcomes treated with standardised national treatment guidelines.
A meta‐analysis assessing the prevalence of drug–drug interactions among hospitalized patients
Authors: Aksoy Nilay , Ozturk Nur 
Published: September 2023

AbstractPurposeDrug–drug interactions (DDIs), particularly in hospitalized patients can result in adverse drug events and unfavorable health consequences. The aim of this meta‐analysis is to provide up‐to‐date evidence on the prevalence of clinically evident adverse drug events due to DDIs in hospitalized patients.MethodsData from Scopus, PubMed, Cochrane and Web of Science were extracted using these keywords (Drug interaction/drug–drug interactions, Hospital/ hospitals, Adverse drug event, Hospitalized patients, inpatient, Department, Hospital stay, Harm, Mortality, death). The studies that include Observational studies on hospitalized patients, reporting potential DDIs using an electronic database, and reporting the clinically observed adverse drug interactions (ADI) through symptoms, signs or Laboratory tests are included. Using Open meta‐Software (version 12.11.14), the incidence of clinically evident DDIs among hospitalized patients was determined and shown in a forest plot.ResultsOnly 15 of the 8261 articles found through a literature search met the inclusion criteria and reported the desired outcome. The pooled prevalence of potential drug–drug interactions is 64.9% (CI 95% 0.618–0.736). While clinically evident DDIs have a pooled frequency of 17.17% (CI 95% 0.133–0.256).ConclusionThe issue of DDIs remains a significant concern in hospitalized patients, with a notable rise in their prevalence. This meta‐analysis encompassed a greater quantity of studies and demonstrated a heightened proportion of drug–drug interaction prevalence in comparison to the percentages reported in the previously published meta‐analysis.
The impact of employment loss on mentally unhealthy days among LGBTQ+ cancer survivors during the COVID‐19 pandemic: Findings from the OUT National Survey
Authors: Waters Austin R. , Lyerly Reece , Scout N. F. N. , Kent Erin E. 
Published: September 2023

AbstractObjectiveLesbian, Gay, Bisexual, Transgender, Queer, and all other sexual and gender minority (LGBTQ+) populations made up 7.1% of the US population in 2021. LGBTQ+ cancer survivors face a variety of economic and mental health disparities; however, the determinants of poor mental health among LGBTQ+ cancer survivors are understudied.MethodsThis analysis utilized the OUT National Survey which consists of N = 2233 LGBTQ+ cancer survivors (complete cases). Multivariable negative binomial and logit regression models were used to generate predicted values, predicted probabilities, and average marginal effects (AME) to assess the association between COVID‐19 related employment loss and mentally unhealthy days (MUDs) and frequent mental distress among LGBTQ+ cancer survivors. Predicted values and marginal effects were generated with interaction terms (demographics interacted with employment loss) to explore the heterogeneity of the effect of employment loss among LGBTQ+ sub‐populations.ResultsIn bivariate analyses employment loss was associated with a higher number of MUDs (10.3, SD = 9.9 vs. 8.4, SD = 9.6; p‐value<0.001) and frequent mental distress (34% vs. 26%; p‐value = 0.001). AME from a multivariable negative binomial model revealed that employment loss was associated with 1.42 more MUDs (95%CI: 0.33–2.86). Demographic factors such as some sexual orientations, cis‐female and non‐binary gender, younger age, and a current cancer diagnosis were also associated with significant expected increases in the number of MUDs. When assessing the heterogeneity of the effect of employment loss some sub‐populations experienced changes in the number of MUDs that pushed them over the threshold of frequent mental distress while others did not. Furthermore, identifying with multiple sexual orientations (AME: 0.19, 95%CI: 0.11–0.27), cis‐female and non‐binary genders (AME: 0.07, 95%CI: 0.2–0.12; AME: 0.18, 95%CI: 0.07–0.28), American Indian and Alaska Native race (AME: 0.17, 95%CI: 0.03–0.31), and a current cancer diagnosis (AME: 0.14, 95%CI: 0.09–0.19) were associated with an increase in the probability of experiencing frequent mental distress.ConclusionsCOVID‐19 related employment loss negatively impacted the mental health of LGBTQ+ cancer survivors. LGBTQ+ specific supportive services as well as equity‐based employment and income interventions are needed.
Model based assessment of food and acid reducing agent effects on oral absorption of mezigdomide (CC‐92480), a novel cereblon E3 ligase modulator
Authors: Wu Fan , Liu Liangang , Gaudy Allison , Wang Xiaomin , Carayannopoulos Leon , Pourdehnad Michael , Lamba Manisha 
Published: September 2023

AbstractMezigdomide is a novel cereblon E3 ligase modulator (CELMoD) agent with enhanced autonomous cell‐killing activity in multiple myeloma (MM) cells, and promising immunomodulatory and antitumor activity in patients with MM. We developed a population pharmacokinetics (PKs) model for mezigdomide in healthy subjects (HSs), and quantified effects of high‐fat meal and proton pump inhibitor (PPI) on human disposition parameters. Plasma concentrations from 64 HS in two phase I clinical studies (NCT03803644 and NCT04211545) were used to develop a population PK model. The HSs received single oral doses of 0.4–3.2 mg mezigdomide with full PK profiles collected. A two‐compartment linear PK model with first‐order absorption and lag time best described mezigdomide PK profiles in HSs. The population PK parameters of absorption rate constant, lag time, central volume of distribution, clearance, peripheral volume of distribution, and intercompartmental clearance were estimated to be 1.18 h−1 (interoccasion variability [IOV]: 65%), 0.423 h (IOV: 31%), 440 L (interindividual variability [IIV]: 63%), 35.1 L/h (IIV: 40%), 243 L (IIV: 26%), and 36.8 L/h (IIV: 26%), respectively. High‐fat meal increased oral bioavailability by ~30% and PPI co‐administration decreased oral bioavailability by ~64%. Mezigdomide demonstrated a linear dose‐exposure relationship in HSs. The PK model suggests a modest effect of high‐fat meal, and a substantial effect of PPIs on mezigdomide oral bioavailability. This population PK model enables data integration across studies to identify important covariate effects and is being used to guide dose selection in clinical study designs for mezigdomide in patients with MM.
A riming‐dependent parameterization of scattering by snowflakes using the self‐similar Rayleigh–Gans approximation
Authors: Maherndl Nina , Maahn Maximilian , Tridon Frederic , Leinonen Jussi , Ori Davide , Kneifel Stefan 
Published: September 2023

AbstractRiming is a key process of precipitation formation in ice‐containing clouds, but quantifying riming from observations is challenging, limiting our ability to evaluate the riming process in numerical weather models. One challenge for radar observations is that riming changes both the physical properties (mass, area cross‐section) and scattering properties of ice particles. These changes need to be implemented consistently as a function of riming in radar forward operators, which are required for retrievals and model evaluation in observation space. In this study, mass–size, cross‐section area–size, and backscattering cross‐section relations are developed as a function of the normalized rime mass for aggregates composed of various monomer types (columns, dendrites, needles, plates, and rosettes). The proposed framework allows us to simulate scattering properties of aggregated ice particles consistently as a function of riming in retrievals and radar forward operators. The parameterizations are developed from a large data set of simulated rimed aggregates of different sizes and monomer crystal types. The backscattering cross‐section parameterization (the “riming‐dependent parameterization”) is evaluated for radar frequencies of 35.6 and 94.0 GHz and is based on the Self‐Similar Rayleigh–Gans approximation (SSRGA), which is increasingly used to calculate microwave scattering of ice crystals and snowflakes. Compared with parameterizations from the literature that do not consider riming, the riming‐dependent parameterization leads to significantly smaller biases in terms of backscattering cross‐section. When using the particle masses and scattering properties of the individual particles simulated by the aggregation and riming model as a reference, the bias of our parameterization is below 1 dB when integrating over an exponential particle size distribution with sizes from 0.1–10 mm.