Cytotoxic t-lymphocyte antigen-4 in colorectal cancer: Another therapeutic side of capecitabine

Cytotoxic T lymphocyte antigen-4 (CTLA-4) is an inhibitory immune checkpoint that can be expressed in tumor-infiltrating lymphocytes and colorectal cancer (CRC) cells. This immune checkpoint can attenuate anti-tumoral immune responses and facilitate tumor growth and metastasis. Although capecitabine is an effective chemotherapeutic agent for treating CRC, its effect on the tumoral CTLA-4 expression remains unclear. In the current research, we applied the GSE110224 and GSE25070 datasets to characterize CTLA-4 expression in CRC patients. Then, we analyzed CTLA-4 expression in CRC samples, HT-29, HCT-166, and SW480 cell lines using real-time PCR. Our bioinformatic results have highlighted the overexpression of CTLA-4 in the CRC tissues compared to the adjacent non-tumoral tissues. Our in vitro studies have indicated that SW480 cells can sub-stantially overexpress CTLA-4 compared to HT-29 and HCT 116 cells. In addition, capecitabine can remarkably downregulate the expression of CTLA-4 in SW480 cells. Collectively, capecitabine can inhibit the expression of CTLA-4 in CRC cells and might bridge the immunotherapy approaches with chemotherapy

Investigation of the effect of temper rolling on the texture evolution and mechanical behavior of IF steels using multiscale simulation

The main objective of this study is to simulate texture and deformation during the temper-rolling process. To this end, a rate-independent crystal plasticity model, based on the self-consistent scale-transition scheme, is adopted to predict texture evolution and deformation heterogeneity during temper-rolling process. For computational efficiency, a decoupled analysis is considered between the polycrystalline plasticity model and the finite element analysis for the temper rolling. The elasto-plastic finite element analysis is first carried out to determine the history of velocity gradient during the numerical simulation of temper rolling. The thus calculated velocity gradient history is subsequently applied to the polycrystalline plasticity model. By following some appropriately selected strain paths (i.e., streamlines) along the rolling process, one can predict the texture evolution of the material at the half thickness of the sheet metal as well as other parameters related to its microstructure. The numerical results obtained by the proposed strategy are compared with experimental data in the case of IF steels.French program “Investment in the future” operated by the National Research Agency (ANR)-11-LABX-0008-01, LabEx DAMAS (LST)

AN OVERVIEW OF THE HISTORY, APPLICATIONS, ADVANTAGES, DISADVANTAGES AND PROSPECTS OF GENE THERAPY

Gene therapy has become a significant issue in science-related news. The principal concept of gene therapy is an experimental technique that uses genes to treat or prevent disease. Although gene therapy was originally conceived as a way to treat life-threatening disorders (inborn defects, cancers) refractory to conventional treatment, it is now considered for many non life-threatening conditions, such as those adversely impacting a patient's quality of life. An extensive range of efficacious vectors, delivery techniques, and approaches for developing gene-based interventions for diseases have evolved in the last decade. The lack of suitable treatment has become a rational basis for extending the scope of gene therapy. The aim of this review is to investigate the general methods by which genes are transferred and to give an overview to clinical applications. Maximizing the potential benefits of gene therapy requires efficient and sustained therapeutic gene expression in target cells, low toxicity, and a high safety profile. Gene therapy has made substantial progress albeit much slower than was initially predicted. This review also describes the basic science associated with many gene therapy vectors and the present progress of gene therapy carried out for various surface disorders and diseases. The conclusion is that, with increased pathobiological understanding and biotechnological improvements, gene therapy will become a standard part of clinical practice

An overview of the history, applications, advantages, disadvantages and prospects of gene therapy

Gene therapy has become a significant issue in science-related news. The principal concept of gene therapy is an experimental technique that uses genes to treat or prevent disease. Although gene therapy was originally conceived as a way to treat life-threatening disorders (inborn defects, cancers) refractory to conventional treatment, it is now considered for many nonlife-threatening conditions, such as those adversely impacting a patients quality of life. An extensive range of efficacious vectors, delivery techniques, and approaches for developing gene-based interventions for diseases have evolved in the last decade. The lack of suitable treatment has become a rational basis for extending the scope of gene therapy. The aim of this review is to investigate the general methods by which genes are transferred and to give an overview to clinical applications. Maximizing the potential benefits of gene therapy requires efficient and sustained therapeutic gene expression in target cells, low toxicity, and a high safety profile. Gene therapy has made substantial progress albeit much slower than was initially predicted. This review also describes the basic science associated with many gene therapy vectors and the present progress of gene therapy carried out for various surface disorders and diseases. The conclusion is that, with increased pathobiological understanding and biotechnological improvements, gene therapy will become a standard part of clinical practic

Sleep Patterns and Affect Dynamics Among College Students during COVID-19 Pandemic (Preprint)

BACKGROUND Sleep disturbance is a transdiagnostic risk factor so prevalent among young adults it is considered a public health epidemic, exacerbated by the COVID-19 pandemic. Sleep may contribute to mental health via affect dynamics. Prior literature on contribution of sleep to affect is largely based on correlational studies or experiments that do not generalize to the daily lives of young adults. Furthermore, the literature examining the associations between sleep variability and affect dynamics remains scant. OBJECTIVE In an ecologically valid context, using an intensive longitudinal design, we aimed to assess the daily and long-term associations between sleep patterns and affect dynamics among young adults during the COVID-19 pandemic. METHODS College student participants (N=20, 65% female) wore an Oura ring continuously for 3-months to measure sleep patterns, such as average and variability in total sleep time (TST), wake after sleep onset (WASO), sleep efficiency (SE), and sleep onset latency (SOL), resulting in 1173 unique observations. We administered a daily ecological momentary assessment (EMA) using a mobile health app to evaluate positive (PA) and negative affect (NA), and COVID-worry once per day. RESULTS Participants with higher SOL and TST on the prior day had lower PA the next day. Further, higher average TST across the 3-month period predicted lower average PA. TST variability predicted higher affect variability across all affect domains. CONCLUSIONS Fluctuating sleep patterns are associated with affect dynamics at daily and long-term scales. Low PA and affect variability may be potential pathways through which sleep has implications for mental health. </sec

Sleep Patterns and Affect Dynamics Among College Students During the COVID-19 Pandemic: Intensive Longitudinal Study.

BackgroundSleep disturbance is a transdiagnostic risk factor that is so prevalent among young adults that it is considered a public health epidemic, which has been exacerbated by the COVID-19 pandemic. Sleep may contribute to mental health via affect dynamics. Prior literature on the contribution of sleep to affect is largely based on correlational studies or experiments that do not generalize to the daily lives of young adults. Furthermore, the literature examining the associations between sleep variability and affect dynamics remains scant.ObjectiveIn an ecologically valid context, using an intensive longitudinal design, we aimed to assess the daily and long-term associations between sleep patterns and affect dynamics among young adults during the COVID-19 pandemic.MethodsCollege student participants (N=20; female: 13/20, 65%) wore an Oura ring (Ōura Health Ltd) continuously for 3 months to measure sleep patterns, such as average and variability in total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, and sleep onset latency (SOL), resulting in 1173 unique observations. We administered a daily ecological momentary assessment by using a mobile health app to evaluate positive affect (PA), negative affect (NA), and COVID-19 worry once per day.ResultsParticipants with a higher sleep onset latency (b=-1.09, SE 0.36; P=.006) and TST (b=-0.15, SE 0.05; P=.008) on the prior day had lower PA on the next day. Further, higher average TST across the 3-month period predicted lower average PA (b=-0.36, SE 0.12; P=.009). TST variability predicted higher affect variability across all affect domains. Specifically, higher variability in TST was associated higher PA variability (b=0.09, SE 0.03; P=.007), higher negative affect variability (b=0.12, SE 0.05; P=.03), and higher COVID-19 worry variability (b=0.16, SE 0.07; P=.04).ConclusionsFluctuating sleep patterns are associated with affect dynamics at the daily and long-term scales. Low PA and affect variability may be potential pathways through which sleep has implications for mental health

Sleep Patterns and Affect Dynamics Among College Students During the COVID-19 Pandemic: Intensive Longitudinal Study

Background Sleep disturbance is a transdiagnostic risk factor that is so prevalent among young adults that it is considered a public health epidemic, which has been exacerbated by the COVID-19 pandemic. Sleep may contribute to mental health via affect dynamics. Prior literature on the contribution of sleep to affect is largely based on correlational studies or experiments that do not generalize to the daily lives of young adults. Furthermore, the literature examining the associations between sleep variability and affect dynamics remains scant. Objective In an ecologically valid context, using an intensive longitudinal design, we aimed to assess the daily and long-term associations between sleep patterns and affect dynamics among young adults during the COVID-19 pandemic. Methods College student participants (N=20; female: 13/20, 65%) wore an Oura ring (Ōura Health Ltd) continuously for 3 months to measure sleep patterns, such as average and variability in total sleep time (TST), wake after sleep onset (WASO), sleep efficiency, and sleep onset latency (SOL), resulting in 1173 unique observations. We administered a daily ecological momentary assessment by using a mobile health app to evaluate positive affect (PA), negative affect (NA), and COVID-19 worry once per day. Results Participants with a higher sleep onset latency (b=−1.09, SE 0.36; P=.006) and TST (b=−0.15, SE 0.05; P=.008) on the prior day had lower PA on the next day. Further, higher average TST across the 3-month period predicted lower average PA (b=−0.36, SE 0.12; P=.009). TST variability predicted higher affect variability across all affect domains. Specifically, higher variability in TST was associated higher PA variability (b=0.09, SE 0.03; P=.007), higher negative affect variability (b=0.12, SE 0.05; P=.03), and higher COVID-19 worry variability (b=0.16, SE 0.07; P=.04). Conclusions Fluctuating sleep patterns are associated with affect dynamics at the daily and long-term scales. Low PA and affect variability may be potential pathways through which sleep has implications for mental health. </jats:sec