Organic cation transporter 1 primarily governs the action of metformin in the liver. There are considerable inter-individual variations in metformin response. In light of this, it is crucial to obtain a greater understanding of the influence of OCT1 expression or polymorphism in the context of variable responses elicited by metformin treatment.We observed that the variable response to metformin in the responders and non-responders is independent of isoform variation and mRNA expression of OCT-1. We also observed an insignificant difference in the serum metformin levels of the patient groups. Further, molecular docking provided us with an insight into the hotspot regions of OCT-1 for metformin binding. Genotyping of these regions revealed SNPs 156T>C and 1222A>G in both the groups, while as 181C>T and 1201G>A were found only in non-responders. The 181T>C and 1222A>G changes were further found to alter OCT-1 structure in silico and affect metformin transport in vitro which was illustrated by their effect on the activation of AMPK, the marker for metformin activity.Taken together, our results corroborate the role of OCT-1 in the transport of metformin and also point at OCT1 genetic variations possibly affecting the transport of metformin into the cells and hence its subsequent action in responders and non-responders.The online version contains supplementary material available at 10.1186/s12902-022-01033-3. SLC22A1/OCT-1 is one of the main hepatic-uptake transporters positioned on the sinusoidal membrane of hepatocytes. The human OCT-1 gene has 11 exons and 10 introns. OCT-1 has four isoforms, a long-form that has been reported to be functionally active and three shorter forms that are splice variants of the gene –5. PolymIn general, the hypothesis laid down for this study is based on the consequential variability of drug response apropos of polymorphism and gene expression/isoform variation in the OCT1 gene. This study was aimed at identifying the variability in the OCT1 gene and the interindividual differences in response to the drug. This study could provide us with a basic picture of the responder, non-responder ratio in our population as no such study has been done in our region to date. Also, this was a pilot study carried out on newly diagnosed type 2 diabetes patients that could be recruited for over 1 year only. It was observed that the response to metformin in these patients was independent of isoform variation and mRNA expression of OCT-1, however, some changes in exon 1 and exon 7 were found to have a profound effect on metformin activity.For PCR-based work, materials like PCR buffer and Taq polymerase were purchased from Sigma Aldrich, USA, and dNTPs were from Fermentas, USA. For expression studies, materials like cDNA synthesis kit, SYBR green, and ROX solution were purchased from Fermentas, USA. RNA later was purchased from Sigma Aldrich, USA. For cell culture studies, DMEM, FBS, and metformin were purchased from Sigma Aldrich, USA. LB agar and LB broth were purchased from Himedia; DPnI from Thermo scientific; A769962 from Abcam; Q5 polymerase from New England Biolabs and Plasmid extraction kit from Qiagen. For western blot analysis, phospho-AMPK rabbit monoclonal antibody, total AMPK rabbit monoclonal antibody, and beta-actin rabbit monoclonal antibody were purchased from CST, USA. The anti-rabbit IR DYE 800 antibody was purchased from Li-COR Biosciences, USA.A total of 41 patients clinically diagnosed with type 2 diabetes mellitus were recruited for this study. They were treated with metformin (500-1000 mg/day) for 3 months in the Department of Endocrinology, Sher-I-Kashmir Institute of Medical Sciences, Soura, Srinagar, Kashmir. Based on the response to metformin, patients were classified into two groups: responder group (decrease in HbA1c levels by more than 1% from the baseline i.e. 5.7%) and non-responder group (decrease in HbA1c levels less than 1% from the baseline). Ten liver tissues and their respective blood samples were obtained from the Department of Surgical Gastroenterology, Sher-I-Kashmir Institute of Medical Sciences, Soura, Srinagar, Kashmir.5 ml peripheral blood samples were collected from responders and non-responders. Out of this quantity, 3 ml was transferred to EDTA vials  for RNA and DNA extraction. The rest of the 2 ml blood was used for serum separation and the serum was stored at -80 °C for further analysis. Liver tissues were stored in RNA later at 4 °C overnight and then transferred to -80 °C till further use.Isoform analysis of OCT-1 was carried out using reverse transcription PCR. 1 µg of RNA (extracted by TRIzol method) was reverse transcribed to cDNA using a first-strand cDNA synthesis kit (Thermo scientific). The isoform analysis for the liver tissue and their corresponding blood samples as well as across the patient groups was carried out by setting a PCR reaction using 10X PCR buffer, 10 mM dNTPs, 5U/µl of Taq polymerase, and 10 µM primers for wild OCT-1, isoform-1, isoform-2 and isoform-3 respectively (Table −∆∆CT). For comparison, OCT-1 expression in blood was calculated using responder sample expression as a reference control. Primers used for qRT-PCR are listed in Table For the expression analysis of OCT-1 mRNA between patient groups (responders and non-responders), real-time quantitative PCR was utilized. The real-time PCR was performed with a light cycler PCR instrument (Applied Biosystems) in a 96 well plate in triplicates using SYBR Green master mix (Fermentas). The ct values of each patient were normalized to GAPDH using the SYBR Green-based comparative CT method 2−∆∆CT. FoMolecular docking was carried out to analyze the interaction of metformin with OCT-1. OCT-1 protein structure was not available and therefore was generated by template modeling using Swiss Model online software and by generating the best fit structure using iTasser. The structure of metformin was acquired from PubChem. SwissDock and Autodock4 were employed for docking metformin on the OCT1 structure. Lamarckian genetic algorithm with local search (GALS) was used as a search engine, with a total of 100 runs. The dock run was programmed to score for blind docking with a minimum forced planner. Cluster analysis was performed on the docked results using an RMS tolerance of 2.0 Å. Finally, the more energetically favorable cluster poses were evaluated by using USCF Chimera software.The exons 1 and 7 of the OCT-1 gene were selected for polymorphic/mutational analysis after carrying out docking analysis. Primers were designed against these exons Table S and a PMolecular Dynamics simulations (MDS) were performed on the wild-type protein and mutants using the GROMACS 4.6 platform and the GROMOS CHARMM force field . Before The sequence analysis of the clinical samples was followed by PCR-based mutagenesis in cell lines. This was followed by the transfection of mutant constructs into a suitable model cell line (HepG2). Functional assays were carried out on transfected cells that include the downstream effector signal molecule analysis viz quantification of activated AMPK by western blot.5 polymerase was used to minimize the incorporation of wrong bases. The PCR product was run on 1% agarose gel to confirm the successful amplification. The mutant constructs of OCT-1 were transformed into DH5α cells separately. The overnight cultured broth was subjected to plasmid extraction using the QIA PrepR Spin miniprep kit from QIAGEN.We received the OCT-1 wild plasmid as a kind gift from Kathleen M. Giacomini, Department of Biopharmaceutical Sciences, University of California, San Francisco. The concentration of the plasmid was 140.1 ng/ul and the reference vector/backbone was pcDNA5. The variants R61C (181C > T), G401S (1201G > A), and M408V (1222A > G) were constructed by site-directed mutagenesis using the wild plasmid as a template and setting up PCR reactions using primers listed in Table HepG2 liver carcinoma cells were cultured in Dulbecco’s modified Eagles medium (DMEM) supplemented with 10% (v/v) fetal bovine serum, 50 μg /ml of penicillin, and 0.1 mg/ml streptomycin. The cells were kept in a humidified atmosphere of 5% CO2/95% air at 37 °C. Further, the HEPG2 cells were transiently transfected with the vector, wild, and mutant OCT-1 constructs using polyethyleneimine (PEI). They were then treated with 20 µM of metformin and 100 µM A769962. Finally, the cells were processed for RNA extraction, and protein extraction, while the expression studies were monitored by western blotting.Western blotting was used for analyzing pAMPK expression in metformin-treated and untreated HEPG2 cells expressing vehicle control, reference OCT-1 and OCT-1 mutant constructs. Briefly, cells were harvested, and lysed in RIPA buffer for protein extraction. The protein concentrations were determined by the Bradford method. Equal amounts of protein from whole-cell lysates were separated on SDS–polyacrylamide gel (10–12%) and then electrophoretically transferred onto the PVDF membrane. Blots were incubated with primary antibodies against phospho AMPK/pAMPK (CST), total AMPK/tAMPK (CST), and β-actin (CST) at 4 °C overnight The dilutions used were 1:1000 for pAMPK, 1:1000 for tAMPK and 1:5000 for β-actin respectively. After washing, the blots were incubated with appropriate IR-tagged secondary antibodies (Licor Biosciences) used at a dilution of 1:10,000 for 1 h at room temperature. The blots were then scanned in an infrared image scanner (Licor Biosciences). .The samples used for the analysis were the serum samples obtained from patients (10 responders and 10 non-responders) who were on 1000 mg of metformin. The analysis was performed on a Shimadzu UFLC chromatographic system equipped with an LC-20AD solvent delivery pump, PDA SPD M-20A detector, DGU-20A degasser, SL-20AHT autosampler, and CTO-10AS column oven. A Merck high resolution chromolith RP-18e column  was used and the mobile phase consisted of 80% acetonitrile: 20% water containing 0.1% formic acid. Analyses were run at a flow rate of 0.5 ml/min. The peak height ratios of six calibration standards (0.02–0.8 µg/µl for responders and 0.01–0.4 µg/µl for non-responders) were used to establish the standard curves and the standard curves were linear  was used for statistical analysis. Student-t test, direct gene count method, Chi-square test, Fischer's exact test, and multivariate analysis were used wherever applicable. Differences were considered statistically significant when the 'n = 25) and non-responders (n = 16). The groups did not differ significantly in age . Of all the participants, 15 were males and 10 were females in responders whereas 8 were male and 8 were female in non-responders. Values of the study parameters based on responders and non-responders are presented in Table In this study, subjects were divided into two groups: responders n = 2 and non-ers n = 1. The grop—value being > 0.05  whereas the genotype 1222 GG was found to be significantly associated with the responders (p < 0.05). As far as allele frequencies are concerned, 181 T allele and 1201A were found to be significantly associated with the non-responders (p < 0.001 and p < 0.05 respectively). However, the 1222 G allele was found to be significantly associated with responders (p < 0.05).Molecular docking revealed the hotspot regions for metformin binding on OCT-1 protein and these regions majorly spanned exon 1 and exon 7. Sequencing of the exon-1 and exon-7 PCR products Figs. S and 10STo assess the effect of the reported SNPs on the OCT-1 protein structure and conformation, molecular dynamic simulation of 181C > T (p.Arg61Cys) and 1201G > A (p.Gly401Ser) variants identified in non-responders leading to Arginine-Cystine and Glycine-Serine substitution was carried out. The energy-minimized structures were subjected to two independent 20 ns runs under the GROMOS CHARMM force field  variant showed the highest SASA followed by the (p.Gly401Ser) variant Fig. . The wilThe wild-type OCT-1 gene was subjected to site-directed mutagenesis to create the mutant constructs having changes that we obtained after genotyping of patient samples. These mutant constructs generated were confirmed by sequencing of the PCR products Fig. S, 13S.AMPK functions as a ser/thr kinase whose activity is known to be altered by metformin. Owing to this fact, we choose to study the transport of metformin via OCT-1 into the cells and considered activation of AMPK as an indicator of metformin activity. Therefore, protein expression of phospho-AMPK and total AMPK was checked to analyze the effect of the mutations in OCT-1 on the transport of metformin. As metformin is known to activate AMPK, therefore, we carried out proteomic studies for the same. We observed that mutant 181C > T and mutant 1201G > A had a profound effect on AMPK activation/ phosphorylation. The activation of AMPK was indicated by increased expression of phospho-AMPK and vice versa. We found that variants 181 C > T and 1201 G > A show decreased expression of phospho-AMPK when compared to the wild OCT-1 counterpart. However, the expression of total AMPK was not affected by any of these changes in OCT-1. Before the metformin treatment and subsequent experiments, the effect of the AMPK activator A769962) was also observed in these cells, to confirm that the effects observed for metformin-treated cells were exclusively due to metformin only .We performed HPLC analysis to evaluate the levels of metformin in the serum of patients from both groups. The mean ± SD values for responders and non-responders were 0.11 ± 0.02 and 0.14 ± 0.06 respectively Table S. Althou. Further, we also found a higher number of people taking PPI in the non-responder group (p < 0.05). Our observation is further supported by the study that identified PPIs as an important drug class inhibiting OCT-mediated metformin transport [p = 0.001). This further clarifies that non-responders do not sufficiently respond to metformin even at higher doses of metformin. There is an increase in HbA1c levels of non-responders as compared to responders, which also comes as a part of studies elsewhere wherein it has been reported that higher doses of metformin lead to better glycemic control in patients with diabetes [Our study was a pilot study, that focussed on patients suffering from diabetes to find the underlying difference between the cohort of patients that were put on metformin medication but were unable to respond to the treatment viz a viz patients who responded to metformin therapy. These patients were divided into responders and non-responders based on their response to metformin which was assessed by the decrease in HbA1c levels in them. HbA1c level has been assessed as a marker of treatment response in patients with diabetes in many studies –12. In transport . In our diabetes , 19. To Further, we studied the isoform pattern between responders and non-responders. We hypothesized that the difference in the response between responders and non-responders might be due to the difference in the type of isoforms between the two groups that could have led to variation in the response due to differential uptake of metformin. Since the four isoforms of OCT-1 were reported from liver tissue [invitro [P = 0.020) in the Han Chinese population [To get a clearer picture of varying metformin responses between the two groups of patients we further moved on to analyze the hotspot domains of OCT-1 protein, likely responsible for metformin binding and transport across the cell. We found that among the other metformin binding regions predicted by docking it on OCT-1 protein model, three regions showed a high docking score Table S. Out ofinvitro . A studyinvitro . The varinvitro , 22. By invitro , Indian invitro , Caucasiinvitro  and Japainvitro , 26 popuinvitro . When repulation . We furtp > 0.05). We next moved on to performing the invitro functional assays to examine the effects of the variations reported in our study, on metformin transport. We generated 181 C > T, 1201 G > A, and 1222 A > G mutants using site-directed mutagenesis. These were transfected into HepG2 cells and experiments were set up using metformin and A769962 (AMPK activator). We assessed the effect of metformin in these mutants by looking at the phosphorylation status of pAMPK, which is known to be a functional reporter or marker for metformin activity. While mutant 1222 A > G did not affect the pAMPK levels, 181 C > T and 1201 G > A led to a decrease in pAMPK expression as compared to reference wild-type OCT-1. Concomitant to our results, Shu et al. also reported seven SNPs in OCT-1 including 181 C > T and 1201 G > A variants that exhibit reduced transport of metformin [We also carried out an estimation of metformin levels in serum by HPLC to find the difference in metformin levels between responders and non-responders. The serum metformin levels were slightly higher in non-responders than responders although the association was statistically insignificant (Our study points out the importance of OCT-1 and its variants in the transport of metformin into the cells and hence its subsequent action. Molecular docking analysis revealed the role played by exon-1 and exon-7 in the binding of metformin to OCT-1 The SNPs associated with these hot spot binding regions of OCT-1 were found to affect the transport of metformin in vitro. Our study also concluded that the variation in the metformin response between the two groups of patients i.e. responders and non-responders is independent of isoform variation and mRNA expression of OCT-1 further hinting that the changes in the OCT-1 gene lead to this varied response to metformin in our patient groups. Furthermore, variations in non-responders were observed to oppose the structural compactness of the protein, thus leading to its compromised and aberrated conformation that may impede the OCT-1 function and hence metformin uptake. However, this work was a pilot study and therefore further studies are needed to be carried out on a larger cohort of patients to get a clearer picture of the OCT-1 and metformin relation. Also, further studies are warranted to examine the effects of the reported SNPs on the protein folding, substrate binding, and substrate selectivity of the OCT-1 transporter.Additional file 1.Additional file 2.Additional file 3.


Streptococcus pyogenes (Sp) Cas9 revealed through these techniques.Cas9 is an RNA-guided endonuclease from the type II CRISPR-Cas system that employs RNA–DNA base pairing to target and cleave foreign DNA in bacteria. Due to its robust and programmable activity, Cas9 has been repurposed as a revolutionary technology for wide-ranging biological and medical applications. A comprehensive understanding of Cas9 mechanisms at the molecular level would aid in its better usage as a genome tool. Over the past few years, single-molecule techniques, such as fluorescence resonance energy transfer, DNA curtains, magnetic tweezers, and optical tweezers, have been extensively applied to characterize the detailed molecular mechanisms of Cas9 proteins. These techniques allow researchers to monitor molecular dynamics and conformational changes, probe essential DNA–protein interactions, detect intermediate states, and distinguish heterogeneity along the reaction pathway, thus providing enriched functional and mechanistic perspectives. This review outlines the single-molecule techniques that have been utilized for the investigation of Cas9 proteins and discusses insights into the mechanisms of the widely used By measuring the resonance energy transfer efficiency   studies the surface structure and properties of samples by detecting the extremely weak interatomic interaction between the sample surface and a miniature force-sensitive sensor , whereas PAM-distal mismatches still allow for the stable binding of the complex to DNA targets. Specifically, 9–10 PAM-proximal matches are sufficient for ultrastable SpCas9–gRNA binding. Moreover, as the dwell-time analysis shows two characteristic binding times, a two-step mechanism of Cas9–RNA binding involving PAM surveillance and RNA-DNA heteroduplex formation (see the next section) was proposed . Fully unwound protospacer DNA coupled with full R-loop formation possibly drives the docking of the HNH domain, thus licensing cleavage-competent SpCas9 (see the following section “DNA dissociation after cleavage”). Modifications of gRNA or the engineering of SpCas9 could rebalance the unwinding-rewinding equilibrium and make it stricter to reach the cleavage-competent state, thus minimizing off-target effects. et al. et al. et al. et al. et al. et al. et al. et al. et al. et al. et al.SpCas9 is a multidomain DNA endonuclease. Structures of SpCas9 showed two distinct lobes, the alpha-helical recognition (REC) lobe and the nuclease lobe (NUS), as well as the more variable C-terminal domain (CTD) , the 3’ flap generated by the cleaved NTS is possibly exposed and can be digested by exonucleases ( et al.One distinguished characteristic of SpCas9 is its stable binding to the on-target site after cleavage. Both ucleases  (Wang et  et al.. Therefo et al.in vitro, could facilitate the dissociation of DNA-cleaved SpCas9 from DNA. Zhang et al. used optical tweezers to examine the consequence of encountering a BLM helicase with a DNA-bound dSpCas9 from both sides ( et al. et al. et al. et al.The long lifetime of the SpCas9–gRNA–DNA complex limits the efficient usage of each SpCas9 protein and impairs the repair of DSBs (Clarketh sides . They prAs evident from this review, single-molecule studies provide not only a fundamental understanding of Cas9 mechanisms but also a framework for rational design aiming at improving Cas9 efficiency and minimizing off-target effects. Based on these studies, a detailed dynamic picture of DNA interrogation and cleavage of SpCas9 has been generated . Upon coQian Zhang, Ziting Chen and Bo Sun declare that they have no conflict of interest.


Animal behavior can be difficult, time-consuming, and costly to observe in the field directly. Innovative modeling methods, such as hidden Markov models (HMMs), allow researchers to infer unobserved animal behaviors from movement data, and implementations often assume that transitions between states occur multiple times. However, some behavioral shifts of interest, such as parturition, migration initiation, and juvenile dispersal, may only occur once during an observation period, and HMMs may not be the best approach to identify these changes. We present two change-point models for identifying single transitions in movement behavior: a location-based change-point model and a movement metric-based change-point model. We first conducted a simulation study to determine the ability of these models to detect a behavioral transition given different amounts of data and the degree of behavioral shifts. We then applied our models to two ungulate species in central Pennsylvania that were fitted with global positioning system collars and vaginal implant transmitters to test hypotheses related to parturition behavior. We fit these models in a Bayesian framework and directly compared the ability of each model to describe the parturition behavior across species. Our simulation study demonstrated that successful change point estimation using either model was possible given at least 12 h of post-change observations and 15 min fix interval. However, our models received mixed support among deer and elk in Pennsylvania due to behavioral variation between species and among individuals. Our results demonstrate that when the behavior follows the dynamics proposed by the two models, researchers can identify the timing of a behavioral change. Although we refer to detecting parturition events, our results can be applied to any behavior that results in a single change in time.The online version contains supplementary material available at 10.1186/s40462-023-00430-0. Knowing the vital rates for wildlife populations of management or conservation concern is critical for determining the best management actions and assessing their outcomes. For example, vital rates can inform quotas and license sales , 40 and Parahyaena brunnea) isolating themselves from the group to give birth in natal dens [Megaptera novaeangliae) moving away from the pod during the birthing process [Rangifer tarandus) are lower in females that gave birth compared to those that did not [Parturition is accompanied not only by morphological , physioltal dens , 49 and  process . Other s did not , 43.Given the large number of wildlife studies using satellite telemetry devices to monitor individual movement , 42, thePrevious work has demonstrated that fine-scale location data can identify behavioral shifts related to parturition in a single individual . HoweverMany studies in the last decade have developed various methods to identify parturient individuals and parturition events using movement metrics derived from location data , 48, 62.To address these hypotheses, we developed two change-point models that capture different parturition-related changes in movement behavior: a location-based model and a movement metric-based model to identify the timing of these events. Comparing the two manifestations of behavioral shifts is important as a change in physical locations does not necessarily result in a change in movement metrics, and vice versa. For example, relocating a core area can be achieved without a detectable change in movement metrics, such as step lengths (the straight-line distance between two points) and turning angles (the change of direction between three successive steps). Meanwhile, the geographic location of the core-use area may not change, but if the core area becomes smaller post-parturition, then quantities such as step length and turning angle must necessarily change.Odocoileus virginianus) and Rocky Mountain elk (Cervus canadensis nelsoni), to test proposed hypotheses about parturition-related behavior in individual ungulates with known timing of parturition events. Species-specific behavior may result in different models being better at detecting parturition-related changes in movement [To test the ability of our change-point models to detect single behavioral shifts, such as parturition, we conducted a simulation study in which we varied the sampling effort (duration and frequency of observations). We used the simulation study to determine the optimal sampling efforts for detecting behavioral events that manifest as either a change in home-range location or derived movement metrics. We then applied our models to a case study of two ungulate species, white-tailed deer  is based on the 2-dimensional spatial location of the individual at time step 7), which did not vary depending on the state. To model the expected location at each time step, we used an autoregressive model of order one (AR(1)) where the location at time t, The multivariate normal distributions were parameterized by their time-varying expected location in space , becausmentclass2pt{minimmentclass2pt{minimPreliminary results indicated that the autocorrelation parameter did not vary between states; therefore, we used a single autocorrelation parameter, ρ, arising from a Uniform prior, which allowed for positive autocorrelation while enforcing some dependence on a geographic centroid.t asIn the Movement Metric-based Change-Point Model (MMCPM), the observations of interest were turning angles and step lengths. Turning angles and step lengths are metrics widely used to characterize behavioral states in animal movement modeling , 47. TurThe wrapped Cauchy distribution was parameterized using location . To assess the effect of fix interval, we again simulated fifty complete datasets that contained locations 48 h prior and 24 h post-parturition with a 15 min fix interval. We thinned each complete dataset to both 30  and 60 min fix intervals.A larger variation in observations and a smaller difference between the two states may make it more challenging to determine when the event of interest occurred. For the MMCPM, we determined four ways in which a difference in behavior might manifest: one with no change in step lengths or turning angles between pre-and post-parturition, one with a change in turning angles but not step lengths, one with a change in step lengths but not turning angles, and one with a change in both step lengths and turning angles. We simulated fifty datasets for each of these movement scenarios. For the LCPMWe first assessed if either LCPM or MMCPM detected a change point by calculating the mode of the posterior distribution of The Pennsylvania Game Commission and the Pennsylvania State University captured 17 deer from January to April 2015–2017 and 37 elk from January to April 2020 in north-central Pennsylvania. Study area details can be found in Additional file Our focus was on parturition events; therefore, we extracted individual location data from 3 days prior to and 4 days following the known parturition event . We explored other pre- and post-parturition durations and found comparable results across durations , 48. BecThe LCPM estimated a change point according to a Level 1 success for all datasets for each variation of post-parturition observation duration Fig. , Table 1When we compared fix intervals, the LCPM estimated the change point according to Level 1 success for all the datasets when the fix interval was 15 min. However, when the datasets were thinned to 30 min and 60 min intervals, the LCPM did not estimate the change point as accurately  and a Level 3 success for one  and in 24 individuals the 95% credible intervals of the estimated change point fell within the 24 h prior to the known parturition event  and the duration of observation. The balance between fix interval and the duration of observation is essential when considering movement behavior because quantities, such as mean, maximum, and total distance moved, will vary as a function of fix interval . AlthougGiven these potential sources of variation in the detection of a change point, our simulation study evaluated the ability of our two models to detect a given change under varying post-event sampling durations, fix intervals, and magnitude of behavioral changes. We determined successful detection of a change point was possible given a 15 min fix interval, at least 3 h of observation following a change for LCPM and at least 12 h for MMCPM. Moreover, for the MMCPM, successful detection of a behavioral change can occur with a 60 min fix rate and at least 24 h of observation following a change. The success of our simulation study demonstrates that when behavior follows the dynamics proposed by the two models, researchers can detect the timing of true behavioral change with current technology.When we applied our change-point models to two ungulate species, not all individuals within a species exhibited movement behaviors captured by the models. This could be due to large behavioral variation across species and individuals. For deer, the LCPM failed to detect a change in a majority of the individuals and the ability to estimate a change was not consistent among individuals. These results indicate deer are not consistently changing their locations prior to or during parturition. In over 50% of the elk, however, the LCPM consistently identified and estimated a change within 12–36 h of parturition (Fig. Much like the LCPM, the MMCPM could not consistently or accurately estimate parturition events in deer. The failure of the MMCPM to capture parturition behavior of deer could be due to brief behavioral changes that are not able to be detected by the MMCPM. For example, females have been observed moving their fawns to a second location within 3 to 24 h after parturition and will only re-visit these secondary locations briefly at dawn and dusk to nurse . While eBased on change point analysis of telemetry data from the mother, locating neonates in real-time is unlikely to be successful given individual variation  and the It is important to be cautious when assigning behaviors or events of interest from the change point estimated by a model . The chaHowever, when a behavioral change event is known to occur, our two change-point models successfully identified it under different monitoring and ecological scenarios. Therefore, these models could be used to identify the timing of parturition events, but only if the methods have been validated a priori. These methods and guidance can be applied in the future to other systems where single behavioral change occurs, such as migration, natal dispersal, or survival of offspring. Our change-point models provide a valuable tool for wildlife managers and researchers to monitor vital rates for populations of management and conservation interest.Additional file 1. Supplementary information on modeling framework, study area, and data collection and processing.Additional file 2. Supplementary figures and tables for simulation and case study.


The purpose of this study is to synthesize evidence on risk factors associated with newborn 31-day unplanned hospital readmissions (UHRs). A systematic review was conducted searching CINAHL, EMBASE (Ovid), and MEDLINE from January 1st 2000 to 30th June 2021. Studies examining unplanned readmissions of newborns within 31 days of discharge following the initial hospitalization at the time of their birth were included. Characteristics of the included studies examined variables and statistically significant risk factors were extracted from the inclusion studies. Extracted risk factors could not be pooled statistically due to the heterogeneity of the included studies. Data were synthesized using content analysis and presented in narrative and tabular form. Twenty-eight studies met the eligibility criteria, and 17 significant risk factors were extracted from the included studies. The most frequently cited risk factors associated with newborn readmissions were gestational age, postnatal length of stay, neonatal comorbidity, and feeding methods. The most frequently cited maternal-related risk factors which contributed to newborn readmissions were parity, race/ethnicity, and complications in pregnancy and/or perinatal period.Conclusion: This systematic review identified a complex and diverse range of risk factors associated with 31-day UHR in newborn. Six of the 17 extracted risk factors were consistently cited by studies. Four factors were maternal , and two factors were neonatal . Implementation of evidence-based clinical practice guidelines for inpatient care and individualized hospital-to-home transition plans, including transition checklists and discharge readiness assessments, are recommended to reduce newborn UHRs.The online version contains supplementary material available at 10.1007/s00431-023-04819-2. Newborn unplanned hospital readmission (UHR) is defined as an unexpected hospital readmission within a specified time period following discharge from the initial hospitalization at the time of birth , 2. NewbIdentifying risk factors associated with UHRs of the newborn can assist in reducing readmission rates through improvements in clinical practice, policy development, and the use of maternal-child healthcare services. While studies have examined causes associated with neonatal morbidity and mortality , 10, theThe systematic review followed the 2009 PRISMA  Statement .An electronic database search was carried out using the CINAHL, EMBASE (Ovid), MEDLINE from 1st January 2000 to 30th June 2021 with key search terms  and (newborn* or new born* or newly born or baby* or babies or premature or prematurity or preterm or pre term or preemie* or premie* or low birth weight or low birthweight (LBW) or very low birthweight (VLBW) or extremely low birth weight (ELBW or infant* or infancy or neonat*) (A complete search strategy is provided in Appendix Four inclusion criteria for this review were (1) primary research studies, (2) UHRs assessment/measurements within 31 days, (3) study design stated clearly and reported statistical analysis procedure/s, and (4) published in peer-reviewed journals and the English language with full text available. Studies were excluded when mixed adverse outcomes, including complications and emergency department (ED) visits post-hospital discharge or readmission were measured more than once. Conference abstract-only references were also excluded.Two reviewers initially read all titles and abstracts independently to assess potential inclusion. Included full-text articles were then assessed against the inclusion criteria. Disagreements between the reviewers on potential articles for inclusion were resolved through discussion. Reference lists of all included articles were screened to identify additional articles.Data extraction included study characteristics, examined variables, and statistically significant risk factors. Study characteristics included study setting, population, sample size, the timing of data collection, study design, data source, readmission rate, and statistical analysis test/s used to identify risk factors as per Table The methodological quality of included studies was assessed independently by two reviewers using a standardised set of predefined criteria in six dimensions . The evaluation results of each item were rated as Yes/Partly/No/Unsure. The potential bias of each study was evaluated by overall risk “low” or “high” , 13.Pooling extracted risk factors is not possible due to the heterogeneity of included studies such as diagnosis, examined variables, or follow-up period to identify readmissions. Therefore, content analysis was used to synthesize the extracted risk factors, and the results are presented narratively . Due to n = 2); (2) readmissions were measured more than once [n = 1). Two additional articles [A total of 6783 records were initially identified, after removing 1771 duplicates, 5012 records remained and were screened through titles and abstracts. Of these, 4979 records were excluded due to irrelevance and 33 relevant references were considered eligible for potential inclusion. A further 4 were excluded as they were conference abstracts only. A total of 29 references were retrieved as full text. Three studies were further excluded for the following reasons: (1) Outcome measures included unplanned ED visits , 15 (n =han once  (n = 1).articles  were ideOverall, the risk of potential bias for the 28 included studies was low against the six predefined dimensions of potential bias , 13. KeyCharacteristics of the 28 included studies are summarized in Table n = 18) recorded the age of patients using gestational age (GA), while nine studies referred to the newborn without specific GA. The four main types of the population involved in the 28 included studies were health-term newborns (n = 2), all live newborns (n = 9), late-preterm newborns with various health condition focus (n = 5), and newborn with varieties of health issues (n = 12).Twenty-two included studies retrieved data from multiple sites, while 6 from a single center. Samples sizes varied from 58 to 4,667,827 and UHRs rates varied from 0.2  to 39% . The majThe time span for the retrieved data varied from 2 months  to 12 yeVariables or confounding factors differed across the 28 included studies. The number of examined variables for each study ranged from one , 25, 26 Seventeen of the 28 included studies identified maternal variables contributing to 31-day newborn UHRs. The three most frequently cited risk factors were maternal parity, pre-existing or perinatal complications, and race/ethnicity. Nine studies , 38, 39 Nine studies reported that mothers with pre-existing or perinatal complications increased the probability of newborn readmission following discharge , 35, 39.In five studies, health care utilization and family resources, including uninsured health care status, unstable family income and inadequate support for the mother following the discharge, were identified as increasing the risk of newborn readmission , 39, 40.The geographic location of both the hospital where the birth occurred and the residential address of parents was cited as risk factors by five differing studies , 40, 41.The maternal age was cited as a risk factor by five studies , 38, 41.Eleven significant risk factors pertaining to the newborns were extracted. The most frequently cited risk factors were gestation age, neonatal comorbidity, postnatal length of stay (LOS), and feeding methods.Gestational age was the most frequently cited significant predictor of unplanned readmission for newborns with OR range from 1.18 to 9.43 –38, 42. Newborns who either had a medical condition at birth or developed medical conditions following their birth were associated with an increased risk of UHRs , 36, 40.P < 0.05) [Eleven included studies , 38, 39  < 0.05) .Two studies , 33 repoFeeding methods and feeding problems were identified in nine studies , 35, 38.Gender was examined and reported consistently across seven differing studies. Compared to females, male newborns experienced a higher risk of unplanned readmission after birth , 38–40.Three studies , 32, 35 The birth weight of newborns was also identified as a statistically significant factor in two studies. The measurement of birth weight, however, was inconsistent amongst the studies. One study  reportedTwo studies cited newborns’ weight at discharge as risk factors. One study  reportedThis systematic review synthesized risk factors associated with newborn 31-day unplanned hospital readmissions following discharge from the hospital where the birth occurred. Twenty-eight studies were reviewed, and 17 significant risk factors were extracted. These included six maternal and 11 newborn-related variables. Of the 17 predictors, six were consistently cited. Four factors were maternal , and two factors were neonatal . The remaining risk factors were inconsistent across the included studies.Newborns of mothers under 20 or over the age of 35, especially primiparous, were at greater risk of unplanned hospital readmission. This is consistent with evidence on the adverse outcomes of pregnancies conceived at extreme maternal age . Adversen = 25) in this review were conducted in western developed countries such as the USA, Canada, UK, Australia, and France with extensive multicultural backgrounds. Mothers of Asian ethnicity experience language and cultural barriers during hospitalization impacting their health literacy and comprehension of discharge information on caring for newborns and themselves [Newborns of Asian mothers were found in this review to have up to a 3 times greater likelihood than other ethnicities of being readmitted. It is noted that almost 90% of the included studies , who are physiologically immature, were often treated the same as a full-term newborn and experienced higher readmission rates , 44. TheReadmission rates associated with the LOS for newborns after their birth were inconsistent and varied from 1.3 to 6.6 days across 92 countries . Since tThis review found that vaginal or assisted vaginal deliveries significantly increased the risk of unplanned newborn readmissions compared with cesarean section. This is opposite to evidence promoting the advantages of vaginal delivery. Compared to newborns delivered by cesarean section, those delivered vaginally were found to have an increased probability of newborn hyperbilirubinemia and jaundice , 58, whiSix included studies cited exclusive breastfeeding as a predictor of newborn readmission, which conflicts with the evidence citing the advantages of breastfeeding. Notably, most studies citing breastfeeding as a risk factor were related to newborn readmissions with jaundice , 33, 38.This systematic review has certain limitations. Firstly, only English language papers with full-text access were considered. The majority of the included studies were conducted in the North America, Europe, and Australia; therefore, generalization of this review’s results should be made with caution considering the characteristic of the healthcare settings. In addition, a meta-analysis was not performed to synthesize the extracted risk factors due to the heterogeneity in the 28 included studies. The studies’ heterogeneity included newborns’ characters, examined variables, time period associated with UHRs, and outcomes coherence. This systematic review did not restrict newborn’s gestational age and comorbidities, which might contribute to the large variation of UHR rate of 0.2% to 39%.This systematic review confirms the diverse and complex nature of risk factors associated with newborn 31-day UHRs. Six consistently cited predictors include 4 maternal factors  and 2 neonatal factors . There is a need to promote healthcare providers’ awareness of risk factors then develop and implement comprehensive individualized hospital-to-home transition plans from the time of admission for the birth through to discharge home to reduce unplanned neonatal readmissions . TransitApplying identified predictive risk factors assists healthcare providers to recognize newborns at higher risk of readmission and implement preventative strategies, for example, individualized discharge planning . Future Supplementary file1 (DOCX 14 KB)Below is the link to the electronic supplementary material.


Owing to the high radiative forcing and short atmospheric residence time of methane, abatement of methane emissions offers a crucial opportunity for effective, rapid slowing of climate change. Here, we report on a colloquium jointly sponsored by the American Society for Microbiology and the American Geophysical Union, where 35 national and international experts from academia, the private sector, and government met to review understanding of the microbial processes of methanogenesis and methanotrophy. The colloquium addressed how advanced knowledge of the microbiology of methane production and consumption could inform waste management, including landfills and composts, and three areas of agricultural management: enteric emissions from ruminant livestock, manure management, and rice cultivation. Support for both basic and applied research in microbiology and its applications is urgently needed to accelerate the realization of the large potential for these near-term solutions to counteract climate change. Methane is a potent greenhouse gas, contributing to about one-fourth of current positive radiative forcing and already having caused about 0.5°C warming since the beginning of the industrial revolution . FortunaThe American Society for Microbiology and the American Geophysical Union, two of the largest scientific societies in the world, jointly convened a colloquium on “The Role of Microbes in Mediating Methane Emissions” on 31 May to 1 June 2023 to explore opportunities to improve methane mitigation options through improved understanding of the microbial processes of methane production and consumption. A group of 35 national and international experts from academia, the private sector, and government met to review the understanding of the microbial processes of methanogenesis and methanotrophy in waste management, including landfills and composts, and in three areas of agricultural management: enteric emissions from ruminant livestock , manure management, and rice cultivation. Presentations on the state of the science in each of these topics revealed that much is already known about the biology of methanogens and methanotrophs 5, but iThe colloquium participants found good reasons for optimism that microbial science is on the verge of facilitating significantly improved abatement of methane emissions from agriculture and waste management systems, but more basic and applied research is still urgently needed to accelerate the realization of the large potential for near-term solutions to climate change from methane emission abatement. Looking forward, the colloquium aims to articulate insights in the form of a roadmap to benchmark progress and to facilitate coordination of the scientific community toward a meaningful goal of methane emission reduction. A full report of the colloquium will be published by ASM in the autumn of 2023. In parallel, the National Academy of Sciences is also collecting information and preparing a report on the removal of atmospheric methane . Meanwhi


This review is an outlook on CAR-T development up to the beginning of 2023, with a special focus on the European landscape and its regulatory field, highlighting the main features and limitations affecting this innovative therapy in cancer treatment. We analysed the current state of the art in the EU and set out a showcase of the field’s potential advancements in the coming years. For this analysis, the data used came from the available scientific literature as well as from the European Medicines Agency and from clinical trial databases. The latter were investigated to query the studies on CAR-Ts that are active and/or relevant to the review process. As of this writing, CAR-Ts have started to move past the “ceiling” of third-line treatment with positive results in comparison trials with the Standard of Care (SoC). One such example is the trial Zuma-7 (NCT03391466), which resulted in approval of CAR-T products (Yescarta™) for second-line treatment, a crucial achievement for the field which can increase the use of this type of therapy. Despite exciting results in clinical trials, limitations are still many: they regard access, production, duration of response, resistance, safety, overall efficacy, and cost mitigation strategies. Nonetheless, CAR-T constructs are becoming more diverse, and the technology is starting to produce some remarkable results in treating diseases other than cancer. Chimeric Antigen Receptor (CAR)-based therapies represent a significant development in immunotherapy, since they have the potential to be effective in relapsed and refractory (r/r) disease, where efficacy of other therapies is lower. They could also virtually be safer and more effective than traditional chemotherapy, though at the moment they present several unsolved limitations. CAR-T cell therapies are ATMPs and all those currently authorised are orphan drugs. This means they are complex medicinal products, made of biological materials engineered with cutting-edge technologies, currently indicated only for rare diseases, thus being subject to a composite regulatory framework.Looking at the European pharmaceutical regulatory landscape, CAR-engineered medicinal products are specifically regulated through the following: The Advanced Therapies Regulation (EC) No. 1394/2007, which had the objective to discipline Advanced Therapy Medicinal Products (ATMPs) [Other pieces of legislation relevant to this review are those respectively establishing the Hospital Exemption (HE) and Compassionate Use (CU) in Europe. The former describes a regulatory option, foreseen by Article 28 of Regulation (EC) No 1394/2007 amending Article 3 of Directive 2001/83/EC, based on which any ATMP can be prepared as an individual medical prescription for an individual patient (named-based) on a non-routine basis, under the exclusive professional responsibility of a medical practitioner for the treatment of severe, disabling, or life-threatening conditions [In order to provide an updated picture of CAR-Ts state of the art, together with developments most likely to be achieved in the near- and mid-term, as well as insights on what is currently possible and how the regulatory sector is enabling these products to reach the clinical setting, several sources and existing projects and initiatives have been considered for this review, namely: The EU Clinical Trials Register , supplemented by the US database of privately and publicly funded clinical studies ; the EMA website’s EPAR Repository, to obtain the latest updates on information and indications of EU-authorised CAR-T medicinal products; the lists of medicinal products awarded with the PRIME scheme, as well as relevant examples of HE and CU to look at possible approaches for future Marketing Authorization Applications (MAAs). From a structural perspective, a CAR is an artificial protein expressed on the surface of an immune cell, encoded by a transgene introduced via a variety of methods, most commonly transfection via viral vectors. The majority of immune cells presently engineered belong to the cellular component of the adaptive immune system (CD4+ and/or CD8+ T cells), but engineering of other families of immune cells, especially those belonging to the innate immune system like Natural-Killer (NK)  and MacrAll approved CAR-T products bear a chimeric antigen receptor composed of an antigen-binding domain typical of antibodies, a co-stimulatory factor from the T cell’s surface, and a signalling domain found in T-cell receptors (TCR), all deriving from different sources, hence the name ‘chimeric’. In a process of innovation already visible today and reported by other authors , this stUp to the first promising results from clinical trials in 2014, the participation in CAR-T research was scarce, but in recent years, Chimeric Antigen Receptor T cells have demonstrated to be an efficacious means to achieve enhanced survival in haematological malignancies and presented enough benefit to warrant marketing authorisations for several of the investigated medicinal products. These drugs are showing a very positive risk/benefit balance, with benefits continuing to improve as safety is enhanced by new construct designs and protocols to deal with treatment complications.The general principle of CAR-T-cell therapy is summarised in In CAR-T design, domains are sometimes referred to as modules . This emhttps://www.ema.europa.eu/en/medicines/whatwe-publish-when/european-public-assessment-reports-background-context, accessed 23 May 2023) was consulted. EPARs publicly report the positive opinion from EMA’s CHMP  on a medicinal product, that subsequently led to its authorisation by the European Commission. Over the past few years, European marketing authorisations have significantly increased in terms of number, and the time to complete the process has been shortened, closely following US FDA (Food and Drug Administration) approvals. In addition, increase in indications for several medicinal products signals the growing use and interest in this therapeutic approach. Currently, six products have been authorised in the EU and thirteen different indications were evaluated by the CHMP (To describe the regulatory activity conducted by the EMA (European Medicines Agency) in terms of marketing authorisations, the online repository for EPARs (European Public Assessment Reports) . The scheme provides the ground for an accelerated assessment by the EMA, as well as regulatory support to the sponsor in overcoming hurdles encountered during clinical trials. PRIME is an acronym standing for “Priority Medicines”. It is a scheme first introduced in 2016 to specifically “enhance support for the development of medicines that target an unmet medical need”  were CAR-Ts  and theiIt is important to note how, among the drugs in this list, some present constructs are not “typical”, in that they do not adhere to the description previously given and use an antibody-derived antigen-binding domain.These “atypical” designs, specifically MB-CART2019.1 and ADP-A2M4, feature a dual-CAR  and a SPOf note, given the successful experience with PRIME in improving and accelerating access to innovative medical products, this scheme is considered one of the key regulatory tools to be strengthened in the new proposal of the European pharmaceutical legislation .Other regulatory paths where CAR-T candidates for future MAAs may be found are those that enable real-world use of the product in a clinical setting before approval. The major options in this regard in the EU are Hospital Exemption and Compassionate Use programs. In Italy, the hospital exemption is implemented through the authorisation procedure for medicines prepared on a non-repetitive basis, regulated through the Ministry of Health Decree of 16 January 2015. By querying the Italian Hospital Exemption database (ISS-AIFA) starting from 2021, twenty-six (26) CAR-T cell-based treatments were retrieved that have been authorised for patients with B precursor acute lymphoblastic leukaemia, neuroblastoma, and lupus erythematosus. Among the authorised treatments, twenty (20) involve paediatric patients (<18 years old) as shown in The products were almost all allogeneic CAR-Ts obtained from HLA-identical donors, being in some cases members of the patients’ family. Fifteen (15) out of the twenty-six (26) cases used reference protocols similar to those used in phase I and I/II clinical trials, meaning they were already approved for experimental use.Of note, despite the presence on the market of licensed products, HE has been successfully used to target patients otherwise excluded from any type of treatment.In the case of Kymriah™, which was suitable for patients with relapsed disease and/or refractory to conventional treatments, some common limitations to its use  led to the demand for allogeneic CD19-CAR-T cells for relapsed and/or refractory B-cell acute lymphoblastic leukaemia (ALL) under HE. The most frequent cases submitted under HE included relapsed patients already undergoing heavily lymphodepleting chemotherapy cycles or treated with HSCT.Similarly, with reference to the application of CAR-T cells in the neuroblastoma indication, an innovative product that uses an inducible iC9 caspase to control the possible CRS due to CAR-T therapy was used on twenty-seven (27) patients aged 1 to 25 years and the extremely promising results were published in April 2023 [As a general limitation of this analysis, it has to be underlined that products administered throughout Hospital Exemption in EU are under the supervision of the corresponding national competent authority of each Member State (MS), after careful risk–benefit analysis of the medicinal product. The lack of a centralised register for HE in EU makes it difficult to retrieve information from each MS. However, reports may be found by looking at the available literature for studies on CAR-T HE use. As an example, the product ARI-0001 or CART19-BE-01, currently included in the list of PRIME medicines, is an anti-CD19 CAR against B-cell malignancies, which was approved by the Spanish Agency of Medicines and Medical Devices (AEMPS) under HE to treat adult patients (>25 years old) with r/r ALL  in 2021.Safety and efficacy of ARI-0001 have been assessed in a study conducted together with the paediatric hospital Sant Joan de Déu (Barcelona), with similar results with respect to those of other products ,22. ARI-Also, in this case, HE constituted a valid alternative path foreseen by the European ATMP Regulation  to enhanCompassionate Use  programsThe study, whose interventions were reported to the relevant legal authorities , demonstrated that MB-CART19.1 cell treatment did in fact led to depletion of B cells and disease remission, which notably did not require maintenance therapy afterwards.On the other hand, it also showed that the CD19-targeted CAR T-cell approach may not be generalised to other autoimmune diseases: this approach requires diseases that not only are B cell-driven, but also develop on B-cell activation. Other autoimmune diseases exist that, despite resulting from B cells, are caused by long-lived plasma cells, which are usually CD19-negative , but sucThis could be the start of an important change in the treatment of this rare disease: the clinical effect of CAR-T-cell treatment is associated with resolution of the SLE patients’ autoimmunity, persisting even after about 100 days, when patients reconstituted their B cells. The likeliest development in the near future regarding CAR-Ts clinical adoption and use is the combination of CAR-T cells with other drugs, already approved, mainly to enhance safety . In the A major objective of the drug combination approach is to try to curb a crucial side effect of CAR-Ts, namely the Cytokine Release Syndrome (CRS).From murine models replicating CRS, cytokines implicated in its development were identified, the main ones being GM-CSF, IL-1, IL-6.Since the Granulocyte Monocyte Colony Stimulating Factor (GM-CSF) is a myeloid cytokine, it was hypothesised that CRS could be prevented from occurring  by reducRecently, Yi and colleagues used GM-CSF knock-out CAR Ts at the clinical level , treatinInterleukin-1 (IL-1) has an important role in severe systemic inflammation, and its association with CAR-T toxicities has been widely described. IL-1 as a target in CAR-T therapy was hit by administering Anakinra, an IL-1R antagonist  already Another therapeutic approach under investigation to control the CRS consists of the administration of a combination of CAR T cells with Dasatinib, at a critical time during the onset of CRS . DasatinFrom clinical trials results on liquid or haematologic tumours, it is known that the majority of patients treated with CAR-Ts do have important responses, yet most of these are still not durable. This is not the case in solid tumours, where current CAR-Ts are not significantly effective, making it an area of unmet need despite being the focus of much of the current research in the field. CAR-T cells appear to be associated with significant toxicities of inflammatory nature, not only the cited Cytokine Release Syndrome (CRS), but also the Immune effector Cell-Associated Neurotoxicity Syndrome (ICANS), as well as cytopenias which then may lead to opportunistic infections. On the other hand, the development of allogeneic CAR-engineered cells, including non-T immune cells like Natural Killer (NK) and Macrophage (M), likely represents the largest gap in knowledge in the field today, which will require substantial investments to reach the clinic, although several reports of CAR-NK clinical trials are already available . The present limitations of CAR-T-cell therapy are summarised in Target choice can be considered a key element in the development of CARs: by choosing an ideal target, the safety of these products can be raised to high standards. The importance of a CAR’s target cannot be overstated, as it ties in directly to both efficacy and safety of these treatments.Even if there is a vast and growing body of literature and expanding research, both preclinical and clinical, dealing with the discovery and testing of novel targets for CAR constructs ,33, “tarWhile some of the toxicities associated with CAR-T-cell therapy were anticipated , the two adverse events which have become distinctive of CAR-T-cell therapy were not anticipated from the early murine studies, i.e., CRS and ICANS . CRS usually develops 3–5 days after infusion, while ‘Immune effector-Cell Associated Neurotoxicity Syndrome’ (ICANS) starts 5–7 days after infusion and is likely connected to CRS development. CRS is caused by extremely high levels of cytokines due to a strong immune response. Typical CRS symptoms range from sustained fevers, hypotension, and in general, the need for airway protection, low blood pressure, high fevers, and circulatory failure, which might require the patient’s admission to the Intensive Care Unit (ICU) and the use of ventilators.This implies that a small clinical centre, not equipped with advanced facilities, will not be authorised for the use of CAR-Ts, thus contributing to a reduced access to this therapeutic opportunity. Recent studies in cytokines involvement in CAR-T therapy’s CRS show that many cytokines derive from the CAR-T treatment. This occurs as engineered cells proliferate in vivo when activated by coming in contact with tumour cells, and produce dramatic increase in cytokines. Moreover, some key cytokines mediating CRS, like IL-6, are produced by Tumour-Associated Macrophages (TAMs), myeloid-type cells found in the patient’s tumour ,36. A direct proportionality between the tumour burden, the scale of T-cell activation and action, and the severity of the syndrome has been observed. As a result, the most fragile segment of patients, those with more severe disease conditions, tend to suffer the direst CRSs.Despite incremental improvement in the ability to recognise Cytokine Release Syndrome and the early treatment with monoclonal antibodies that might induce IL-6 blockade , deaths linked to this side effect continue to be observed. Thus, a deeper understanding of CRS, its causes and mechanism of actions, is needed to control, treat, or reduce occurrence in future CAR-T medicinal products.ICANS appears to be due to the expression of CD19 on some neurons and blood–brain barrier lining. ICANS main symptoms are confusion, aphasia, seizures, and encephalopathy.Even if, according to MRI observations during neurotoxicity, these symptoms tend to be transient, ICANS-induced encephalopathy can be deadly if associated with brain edema, and high-grade ICANS can result in the destruction of the blood–brain barrier (BBB) , with poGM-CSF seems to play a central role in CAR-T-mediated neurotoxicity, as demonstrated by the analysis of some of the 2017 pivotal clinical trials . In addition, the infiltration into the CSF of CD14-positive cells and monocytes, like Tumour-Associated Macrophages (TAMs), has been associated with Grade ≥ 3 neurotoxicity, thus suggesting a role for these cells as a target for preventing ICANS. Currently, the treatment of ICANS includes solely the administration of corticosteroids and supportive care. In addition, since ICANS often occurs with CRS, the resolution of the former is needed for a proper CRS treatment; however, the spontaneous resolution can only happen if ICANS is low-grade, while severe ICANS (grade ≥ 3) remains a critical condition, thus highlighting a gap in knowledge and the need of finding new and resolutive treatments. ICANS and neurotoxicity are obviously crucial concerns to the application of CAR-Ts in the neurological field. Through the observation of haematologic patients with known CNS involvement, presence of MRI changes or baseline neurological disorders have been linked to increased risk of ICANS . In receResistance to CAR-T activity is a multifactorial outcome due to different aspects, mainly related to patients’ cells used to generate the CAR-Ts, T-cell exhaustion and tumour microenvironment (TME).Regarding the influence of starting materials in autologous treatments, patients T cells’ functioning could be defective even before the transduction of T cells with CARs. This seems to be the case in heavily pre-treated patients, who approach CAR-Ts as a third line of treatment , and it is one of the reasons for the interest in allogeneic CAR-Ts. For similar reasons, these therapies have been moved to earlier lines of treatment, like in the case of the Zuma-7 trial (NCT03391466), a comparison trial which allowed Yescarta© to be the first CAR-T to ever be available as second-line treatment, for HGBL and DLBCL.Defective T-cell function may also appear as a result of genetic modification. This specific form of decline in functions is known as ‘T-cell exhaustion’, a poorly understood continuous differentiation process, in which T cells are transformed from precursors to terminally differentiated T cells, thus losing cellular functionality.The tumour microenvironment (TME) plays a critical role in the response to tumour treatments. Suppression exerted by the tumour’s TME can down-regulate activity of both CAR-Ts and physiological T cells. CAR-T inhibition mediated by the TME in solid tumours is a major area of study . CurrentAmong the approaches to TME-mediated resistance, dual-targeting CAR-Ts may be used to stop Cancer-Associated Fibroblasts (CAFs) from inhibiting the CAR-Ts. CAFs are a cellular component of the TME, well documented, for example, in multiple myeloma, which can inhibit BCMA CAR T cells  such as Another approach to overcome TME lies in the CAR design called TRUCK CAR Ts, used against inhibitory extracellular vesicles. Such vesicles are part of the milieu of the TME and have been documented  expressiLastly, another component of the TME for which potential solutions have been investigated is the cytokine Transforming Growth Factor-β (TGF-β), which has a prominent immunosuppressive role in the TME . An apprNovel designs, such as peptide-centric (PC) CAR-Ts , are posThe number of patients having access to CAR-T-cell treatment is currently quite limited, despite the high and increasing level of interest, investments, and research in the field. According to the EBMT registry , 2500 paAlthough the actual CAR-T-based treatment price can vary significantly among EU member states, it may indicatively be considered at around EUR 350.000, with possible variations due to different agreements stipulated between the Marketing Authorization Holders (MAHs) and member states’ NHSs. Despite this very high price tag, in principle making CAR-Ts profitable products, it crushes their ability to fully become part of the mainstream cancer treatment options. Two potential solutions have been discussed in the available literature, consisting of (i) increasing production outputs to lower costs , and (ii) manufacturing of allogeneic products to lower costs . The first is reasonably the near-term solution that can be expected in the coming years, while the second can constitute instead a long-term objective. Allogeneic products will allow a virtually unlimited quantity of medicinal products, with lower costs and the possibility to increase the complexity, and thus hopefully the effectiveness of CARs, by introducing multiple transgenes and/or mutations to the engineered cell. When analysing and comparing the efforts to address the cost and complexity of CAR-T-cell therapy, a recurrent theme across both literature and scientific institutions developing this technology is the need to pass from a centralised process to a decentralised production process ,51, bothIn a centralised model, the key to production is the company and its GMP facilities. Current challenges in access to therapy partly stem from the complex nature of the process, that can take between 3–4 to 6–8 weeks from the time that leukapheresis is performed and patient’s cells are shipped to the company, and the product is back to the hospital for being reinfused. The extremely expensive nature of this kind of medicinal product, due to this complex production process as well as the low scale of production, translates to the fact that only major academic centres can afford this therapeutic option, further decreasing access, similarly to the established third-line treatment alternative to CAR-Ts (bone marrow transplantation), which is not available in small clinical centres. In addition, by looking at the clinical trial results with the centralised model, it was observed that some patients were invariably lost because the time to acquire the medicinal product was too long for the patient to wait, and the bridging therapy was not sufficient.On the other side, the decentralised production model aims at significantly reducing the overall time to reach the patient, by cutting storage and transportation times through the use of mobile cell factories. The possibility of doing CAR-T infusions as an outpatient therapy, an increase in the number of centres that can adopt CAR-T-cell therapies, shortening the time for potentially life-saving innovations to reach the clinical setting, are some of the potential advantages of this approach. A nice example of a decentralised and flexible approach was tested in St. James’s Hospital and the Trinity College Dublin Clinical Research Facility in Dublin (July 2022), moving a cell factory closer to patients using a mobile GMP facility for CAR-T .® [® [Further investigations into the use of more automated manufacturing platforms and co-located GMP-compliant facilities are needed. Examples of currently ongoing innovative developments in the field are carried out by several players, such as Lonza pharmaceuticals® , Mylteni® [® , and aCG® [® . The establishment of GMP manufacturing quality standards is considered an important challenge with regulatory implications. Specific guidelines do not exist yet, and coordination between regulators and manufacturers is needed to bridge this gap in the near future.Another sprawling field of interest which addresses the limitations of CAR-T-cell therapy are “Off-the-shelf” CAR-Ts, obtained from healthy donors , which can provide high amounts of fully functional cells and allow multiple CAR-T-cell products to generate. Such an approach may increase patients’ access to therapy, also reducing the delivery time of products that can be stored like conventional biologics.Their major limitation is the need to undergo an additional editing step to prevent Graft-versus-Host (GvHD) disease-type rejection . Though Another promising approach for the generation of allogeneic CAR-T products foresees the use of in vitro-induced pluripotent stem cells (iPSCs) , insteadThe promise of these engineered stem cells is fascinating: with a potentially perpetual supply of virtually unlimitedly editable cells, the versatility of iPSC-derived CAR-T cells (iCAR-Ts) has garnered increasing investments and interest. iPSC technology is currently in its “first wave” and suffers from several limitations, like the absence of a clear regulation for the product’s quality assessment and release for clinical use, the lacking acceptance of key stakeholders towards iPSC technology, especially patients, and the non-availability of robust and scalable manufacturing protocols for clinical-grade iCAR-T cells.Other gaps in knowledge that are likely to impact in the long term the access to iCAR-T therapies are the suboptimal function and developmental maturity of iPSC-derived CAR-Ts in comparison to ‘primary’, autologous CAR-Ts. So far, studies conducted on T cells derived from iPSCs (TiPSCs) only managed to produce CD8αα CAR-T cells with a low activity profile, similar to innate T cells . This phCurrently, to use TiPSCs as raw material to engineer CAR-Ts, a master iPSC cell bank must be created via gene editing and subcloning, specifically dedicated to the disease in study. This is a long and technically challenging, substantially expensive process, which can generate genotoxic products, and it prevents the introduction of more complex CAR designs . Surpassing this technological challenge appears to be crucial to the ability to scale up quantities of CAR-T produced starting from iPSCs, and the potential of iPSCs to compete with cells from healthy donors. Gene therapies hold a big promise for oncologic patients as well as rare disease patients. The analysed areas for improvement preventing a faster uptake and consolidation of the use of such therapies, and that would require an update in the regulatory approaches, deal with three main aspects: (i) the regulatory approval landscape, which may be overcome by adopting regulatory assessment based on real-world data (RWD) to accelerate approvals; (ii) the manufacture and release model, which could be improved by introducing decentralised (bedside) manufacture to reduce production time and eliminate human variability in case of automated equipment; and (iii) the reimbursement model, which can be approached using the Quality Adjusted Life Years (QALY) shaped for CAR’s Patients ,62.These fields  operate based on conventional pharmaceutical models, which slow down access to ATMPs.In the long term, roadblocks that need to be overcome to achieve widespread cell therapy adoption should primarily include standardising cell therapy production and removing transportation hurdles, like the need for default freezing/thawing and transportation of human cells: this introduces risks to cell viability and potency as well as delayed treatment. Working directly with innovators is needed to develop next-generation cell therapies in-hospital, for example, the so-called “GMP-in-a-POD” platforms , and lasInnovations addressing the high cost and the long manufacturing duration of CAR-T-cell therapy will have a tremendous societal and economic impact, and developing the procedures and tools to efficiently produce off-the-shelf, TiSPC-derived CAR-Ts is key to both endeavours. All approved CAR-T-cell products are orphan medicines, authorised for rare diseases. They present several recurrent challenges regarding efficacy, safety, and access that have been only partially solved. Among those challenges identified by this review, the low efficacy in solid tumour, runaway inflammatory side effects, and difficult and expensive manufacturing are considered priorities in the field and must be addressed by regulators and scientists.From the regulatory point of view, this review proposes that the EU regulatory framework is going to require updates to properly oversee such innovative therapies and the challenges they pose. However, the analysis of the framework as is already shows several possible routes to allow the access to patients suffering from rare diseases.From the scientific point of view, CAR technology holds a great promise. This is attested by recent indications’ expansions for the approved CAR-T products, by the encouraging results in the clinical setting, and finally, by a technological basis that is growing in the direction of increasing production while lowering cost, which constitutes a critical need. The ongoing research in the field of CAR-T-cell therapy, such as developments in the sustainable and safe use of advancements in gene editing techniques to achieve multiplex editing (introducing multiple mutations on the engineered cells), shows potential scenarios for future breakthroughs in their clinical applications, and in creating novel sources of starting cellular materials. At the same time, even if gene editing of CAR T cells is limited to somatic cells, ethical aspects regarding modification of primary lineages and off-target editing will need to be addressed from a scientific and regulatory point of view before the full application of this technique can be transferred to patients. The resulting production of more innovative as well as allogeneic products able to avoid graft-Vs-host disease could reshape treatment of several oncologic indications, and even give hope to develop treatments for many diseases still incurable today.