Tuberculosis Chest X-Ray Image Retrieval System Using Deep Learning Based Biomarker Predictions.

The world health organization's global tuberculosis (TB) report for 2022 identifies TB, with an estimated 1.6 million, as a leading cause of death. The number of new cases has risen since 2020, particularly the number of new drug-resistant cases, estimated at 450,000 in 2021. This is concerning, as treatment of patients with drug resistant TB is complex and may not always be successful. The NIAID TB Portals program is an international consortium with a primary focus on patient centric data collection and analysis for drug resistant TB. The data includes images, their associated radiological findings, clinical records, and socioeconomic information. This work describes a TB Portals' Chest X-ray based image retrieval system which enables precision medicine. An input image is used to retrieve similar images and the associated patient specific information, thus facilitating inspection of outcomes and treatment regimens from comparable patients. Image similarity is defined using clinically relevant biomarkers: gender, age, body mass index (BMI), and the percentage of lung affected per sextant. The biomarkers are predicted using variations of the DenseNet169 convolutional neural network. A multi-task approach is used to predict gender, age and BMI incorporating transfer learning from an initial training on the NIH Clinical Center CXR dataset to the TB portals dataset. The resulting gender AUC, age and BMI mean absolute errors were 0.9854, 4.03years and 1.67kgm2. For the percentage of sextant affected by lesions the mean absolute errors ranged between 7% to 12% with higher error values in the middle and upper sextants which exhibit more variability than the lower sextants. The retrieval system is currently available from https://rap.tbportals.niaid.nih.gov/find_similar_cxr.

Cuproptosis-related molecular classification and gene signature of hepatocellular carcinoma and experimental verification.

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with poor overall prognosis. Cuproptosis, a recently proposed mode of copper-dependent cell death, plays a critical role in the malignant progression of various tumors; however, the expression and prognostic value of cuproptosis-related regulatory genes in HCC remain unclear. Methods: Genomic, genetic, and expression profiles of ten key cuproptosis-related regulatory genes were analyzed using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset and protein expression data from the Human Protein Atlas (HPA) database. Unsupervised clustering of HCC patients based on these ten key cuproptosis-related regulatory genes was used to identify different HCC subtypes and analyze the differences in clinical and immune characteristics among subtypes. Subsequently, univariate Cox and least absolute shrinkage and selection operator (LASSO) Cox analyses were used to establish a cuproptosis-related prognostic signature, and the accuracy of prognostic signature prediction was internally validated by Kaplan-Meier survival analysis and time-dependent receiver operating characteristic curve in TCGA training and testing cohorts. The prognostic signature was externally validated using TCGA-LIHC entire cohort and International Cancer Genome Consortium Liver Cancer (ICGC-LIRI) cohorts. Finally, the expression landscape of cuproptosis-related regulatory genes in prognostic signature was explored by quantitative real-time polymerase chain reaction (qRT-PCR), western blotting and immunohistochemistry (IHC) experiments. Results: Ten cuproptosis-related genes were differentially expressed in normal and HCC tissues. Unsupervised clustering identified two subtypes and HCC patients with these two subtypes had different clinical prognoses and immune characteristics, as well as different degrees of response to immunotherapy. Lipoyltransferase 1 (LIPT1), dihydrolipoamide s-acetyltransferase (DLAT), and cyclin dependent kinase inhibitor 2A (CDKN2A) were selected to construct a prognostic signature, which significantly distinguished HCC patients with different survival periods in the TCGA training and testing cohorts and was well validated in both the TCGA-LIHC entire cohort and ICGC-LIRI cohort. The risk score of the prognostic signature was confirmed to be an independent prognostic factor, and nomograms were generated to effectively predict the probability of HCC patient survival. The qRT-PCR, western blotting and IHC results also revealed a significant imbalance in the expression of these cuproptosis-related genes in HCC. Conclusions: The classification and prognostic signature based on cuproptosis-related regulatory genes helps to explain the heterogeneity of HCC, which may contribute to the individualized treatment of patients with the disease.

MicroRNA in cardiometabolic health and disease: The perspectives of sex, gender and personalised medicine.

BACKGROUND: Personalized medicine represents a novel and integrative approach that focuses on an individual's genetics and epigenetics, precision medicine, lifestyle and exposures as key players of health status and disease phenotypes. METHODS: In this narrative review, we aim to carefully discuss the current knowledge on gender disparities in cardiometabolic diseases, and we consider the sex- specific expression of miRNAs and their role as promising tool in precision medicine. RESULTS: Personalised medicine overcomes the restricted care of patient based on a binomial sex approach, by enriching itself with a holistic and dynamic gender integration. Recognized as a major worldwide health emergency, cardiometabolic disorders continue to rise, impacting on health systems and requiring more effective and targeted strategies. Several sex and gender drivers might affect the onset and progression of cardiometabolic disorders in males and females at multiple levels. In this respect, distinct contribution of genetic and epigenetic mechanisms, molecular and physiological pathways, sex hormones, visceral fat and subcutaneous fat and lifestyle lead to differences in disease burden and outcomes in males and females. CONCLUSIONS: Sex and gender play a pivotal role in precision medicine because the influence the physiology of each individual and the way they interact with environment from intrauterine life.

Space research to explore novel biochemical insights on Earth.

Travel to space has overcome unprecedent technological challenges and this has resulted in transfer of these technological results on Earth to better our lives. Health technology, medical devices, and research advancements in human biology are the first beneficiaries of this transfer. The real breakthrough came with the International Space Station, which endorsed multidisciplinary international scientific collaborations and boosted the research on pathophysiological adaptation of astronauts to life on space. These studies evidenced that life in space appeared to have exposed the astronauts to an accelerated aging-related pathophysiological dysregulation across multiple systems. In this review we emphasize the interaction between several biomarkers and their alteration in concentrations/expression/function by space stress factors. These altered interactions, suggest that different biochemical and hormonal factors, and cell signals, contribute to a complex network of pathophysiological mechanisms, orchestrating the homeostatic dysregulation of various organs/metabolic pathways. The main effects of space travel on altering cell organelles biology, ultrastructure, and cross-talk, have been observed in cell aging as well as in the disruption of metabolic pathways, which are also the causal factor of rare inherited metabolic disorders, one of the major pediatric health issue. The pathophysiologic breakthrough from space research could allow the development of precision health both on Earth and Space by promoting the validation of improved biomarker-based risk scores and the exploration of new pathophysiologic hypotheses and therapeutic targets. Nonstandard abbreviations: International Space Station (ISS), Artificial Intelligence (AI), European Space Agency (ESA), National Aeronautics and Space Agency (NASA), Low Earth Orbit (LEO), high sensitive troponin (hs-cTn), high sensitive troponin I (hs-cTn I), high sensitive troponin T, Brain Natriuretic Peptide (BNP), N terminal Brain Natriuretic Peptide (NT-BNP), cardiovascular disease (CVD), parathyroid hormone (PTH), urinary hydroxyproline (uHP), urinary C- and N-terminal telopeptides (uCTX and uNTX), pyridinoline (PYD), deoxypyridinoline (DPD), half-time (HF), serum Bone Alkaline Phosphatase (sBSAP), serum Alkaline Phosphatase (sAP), Carboxy-terminal Propeptide of Type 1 Procollagen (P1CP), serum Osteocalcin (sOC)), advanced glycation end products (AGEs), glycated hemoglobin A1c (HbA1c), Insulin-like growth factor 1 (IGF1), Growth Hormone (GH), amino acid (AA), ß-hydroxy-ß methyl butyrate (HMB), maple syrup urine disease (MSUD), non-communicable diseases (NCDs).

Community cohesion looseness in gene networks reveals individualized drug targets and resistance.

Community cohesion plays a critical role in the determination of an individual's health in social science. Intriguingly, a community structure of gene networks indicates that the concept of community cohesion could be applied between the genes as well to overcome the limitations of single gene-based biomarkers for precision oncology. Here, we develop community cohesion scores which precisely quantify the community ability to retain the interactions between the genes and their cellular functions in each individualized gene network. Using breast cancer as a proof-of-concept study, we measure the community cohesion score profiles of 950 case samples and predict the individualized therapeutic targets in 2-fold. First, we prioritize them by finding druggable genes present in the community with the most and relatively decreased scores in each individual. Then, we pinpoint more individualized therapeutic targets by discovering the genes which greatly contribute to the community cohesion looseness in each individualized gene network. Compared with the previous approaches, the community cohesion scores show at least four times higher performance in predicting effective individualized chemotherapy targets based on drug sensitivity data. Furthermore, the community cohesion scores successfully discover the known breast cancer subtypes and we suggest new targeted therapy targets for triple negative breast cancer (e.g. KIT and GABRP). Lastly, we demonstrate that the community cohesion scores can predict tamoxifen responses in ER+ breast cancer and suggest potential combination therapies (e.g. NAMPT and RXRA inhibitors) to reduce endocrine therapy resistance based on individualized characteristics. Our method opens new perspectives for the biomarker development in precision oncology.

Efficacy of bupropion and varenicline genetic markers in choosing pharmacological treatment for smoking cessation, and implications for combining drugs: A randomized controlled trial - GENTSMOKING.

INTRODUCTION: Smoking cessation is the best strategy for reducing tobacco-related morbimortality. The goal of this randomized controlled trial was to test whether using the genetically favorable markers to choose a smoking cessation drug treatment (precision medicine) was superior to using the most effective drug (varenicline) in terms of abstinence rates. Additionally, combination therapy was tested when monotherapy failed. METHODS: This partially blind, single-center study randomized (1:1) 361 participants into two major groups. In the genetic group (n=184), CYP2B6 rs2279343 (genotype AA) participants started treatment with bupropion, and CHRNA4 rs1044396 (genotype CT or TT) participants started treatment with varenicline; when genetic favorable to both, participants started treatment with bupropion, and when favorable to neither, on both drugs. In the control group (n=177), participants started treatment with varenicline, regardless of genetic markers. Drug treatment lasted 12 weeks. Efficacy endpoints were abstinence rates at Weeks 4, and Weeks 8-12, biochemically validated by carbon monoxide in exhaled air. Participants who did not achieve complete abstinence at Week 4, regardless of group, were given the choice to receive combination therapy. RESULTS: Abstinence rates were 42.9% (95% CI: 36-64) in the control group versus 30.4% (95% CI: 23-37) in the genetic group at Week 4 (p=0.01); and 74% (95% CI: 67-80) versus 52% (95% CI: 49-64) at Week 12 (p<0.001), respectively. The strategy of combining drugs after Week 4 increased abstinence rates in both groups and the significant difference between genetic and control groups was maintained. CONCLUSIONS: Results show that using these selected genetic markers was inferior to starting treatment with varenicline (control group), which is currently the most effective smoking cessation drug; moreover, the addition of bupropion in cases of varenicline monotherapy failure improves the efficacy rate until the end of treatment. CLINICAL TRIAL IDENTIFIER: NCT03362099.

A novel approach to designing viral precision vaccines applied to SARS-CoV-2.

Efficient precision vaccines against several highly pathogenic zoonotic viruses are currently lacking. Proteolytic activation is instrumental for a number of these viruses to gain host-cell entry and develop infectivity. For SARS-CoV-2, this process is enhanced by the insertion of a furin cleavage site at the junction of the spike protein S1/S2 subunits upstream of the metalloprotease TMPRSS2 common proteolytic site. Here, we describe a new approach based on specific epitopes selection from the region involved in proteolytic activation and infectivity for the engineering of precision candidate vaccinating antigens. This approach was developed through its application to the design of SARS-CoV-2 cross-variant candidates vaccinating antigens. It includes an in silico structural analysis of the viral region involved in infectivity, the identification of conserved immunogenic epitopes and the selection of those eliciting specific immune responses in infected people. The following step consists of engineering vaccinating antigens that carry the selected epitopes and mimic their 3D native structure. Using this approach, we demonstrated through a Covid-19 patient-centered study of a 500 patients' cohort, that the epitopes selected from SARS-CoV-2 protein S1/S2 junction elicited a neutralizing antibody response significantly associated with mild and asymptomatic COVID-19 (p<0.001), which strongly suggests protective immunity. Engineered antigens containing the SARS-CoV-2 selected epitopes and mimicking the native epitopes 3D structure generated neutralizing antibody response in mice. Our data show the potential of this combined computational and experimental approach for designing precision vaccines against viruses whose pathogenicity is contingent upon proteolytic activation.

Evolving assessment pathways for precision oncology medicines to improve patient access: a tumor-agnostic lens.

BACKGROUND: Genomic and molecular alterations are increasingly important in cancer diagnosis, and scientific advances are opening new treatment avenues. Precision oncology (PO) uses a patient's genomic profile to determine optimal treatment, promising fewer side effects and higher success rates. Within PO, tumor-agnostic (TA) therapies target genomic alterations irrespective of tumor location. However, traditional value frameworks and approval pathways pose challenges which may limit patient access to PO therapies. OBJECTIVES: This study describes challenges in assessing PO and TA medicines, explores possible solutions, and provides actionable recommendations to facilitate an iterative life-cycle assessment of these medicines. METHODS: After reviewing the published literature, we obtained insights from key stakeholders and European experts across a range of disciplines, through individual interviews and an industry workshop. The research was guided and refined by an international expert committee through 2 sounding board meetings. RESULTS: The current challenges faced by PO and TA medicines are multiple and can be demonstrated through real-world examples of the current barriers and opportunities. A life-cycle approach to assessment should be taken, including key actions at the early stages of evidence generation, regulatory and reimbursement stage, as well as payment and adoption solutions that make use of the evolving evidence base. Working toward these solutions to maximize PO medicine value is a shared responsibility and stands to benefit all stakeholders. CONCLUSIONS: Our call to action is to expand access to comprehensive genomic testing, foster a learning health care system, enable fast and equitable access to cost-effective treatments, and ultimately improve health outcomes.

Incorporating functional genomics into the pathology-supported genetic testing framework implemented in South Africa: A future view of precision medicine for breast carcinomas.

A pathology-supported genetic testing (PSGT) framework was established in South Africa to improve access to precision medicine for patients with breast carcinomas. Nevertheless, the frequent identification of variants of uncertain significance (VUSs) with the use of genome-scale next-generation sequencing has created a bottleneck in the return of results to patients. This review highlights the importance of incorporating functional genomics into the PSGT framework as a proposed initiative. Here, we explore various model systems and experimental methods available for conducting functional studies in South Africa to enhance both variant classification and clinical interpretation. We emphasize the distinct advantages of using in vitro, in vivo, and translational ex vivo models to improve the effectiveness of precision oncology. Moreover, we highlight the relevance of methodologies such as protein modelling and structural bioinformatics, multi-omics, metabolic activity assays, flow cytometry, cell migration and invasion assays, tube-formation assays, multiplex assays of variant effect, and database mining and machine learning models. The selection of the appropriate experimental approach largely depends on the molecular mechanism of the gene under investigation and the predicted functional effect of the VUS. However, before making final decisions regarding the pathogenicity of VUSs, it is essential to assess the functional evidence and clinical outcomes under current variant interpretation guidelines. The inclusion of a functional genomics infrastructure within the PSGT framework will significantly advance the reclassification of VUSs and enhance the precision medicine pipeline for patients with breast carcinomas in South Africa.

Co-design of a paediatric oncology medicines database (ProCure) to support complex care provision for children with a hard-to-treat cancer.

Objectives: Paediatric oncologists often encounter challenges when seeking compassionate access to off-label therapies for their patients. This study employed implementation science and co-design techniques to develop the ProCure medicines database, with the goal of streamlining the application process and addressing identified barriers in paediatric oncology. Methods: This study utilised an exploratory qualitative research design. Seventeen healthcare providers, including oncologists, nurse consultants, and allied health professionals, participated in semi-structured interviews guided by the Consolidated Framework for Implementation Research (CFIR) and a visual process map aid. Deductive qualitative data analysis, according to the CFIR constructs, identified key barriers and facilitators. Collaborative design sessions engaged multidisciplinary teams to develop the ProCure beta version. Results: Barriers to off-label therapy access included resource-intensive applications, time sensitive decision-making, and complex pharmaceutical information. Facilitators included Drug Access Navigators, Molecular Tumour Boards, and a multi-disciplinary approach. ProCure addressed end-user needs by centralising medicines information. Additional features suggested by healthcare providers included blood-brain-barrier penetrability data and successful application examples. Conclusion: ProCure represents a promising solution to the challenges paediatric oncologists face in accessing off-label therapies. By centralising information, it simplifies the application process, aids decision-making, and promotes a collaborative approach to patient care. The potential of the database to stream and enhance off-label therapy access underscores its relevance in improving paediatric oncology practise. Further research and implementation efforts are warranted to assess ProCure's real-world impact and refine its features based on user feedback.

[Take-home messages from the 2nd COPD 2023 Biennial of the French Society of Respiratory Diseases. Placing the patient at the center of the care pathway]. / Principaux messages de la deuxième Biennale BPCO 2023 de la SPLF. Le patient au cœur du parcours de soins.

INTRODUCTION: The second COPD Biennial organized by the COPD working group of the French Society of Respiratory Diseases took place in Paris (Cochin) on 13th December 2023. STATE OF THE ART: Major trends in 2023 were discussed; they encompassed concepts, definitions, biologics, care pathways, pulmonary rehabilitation and complex situations entailed by respiratory infections, cardiovascular comorbidities and pulmonary hypertension, and modalities of oxygen therapy and ventilation. PERSPECTIVES: The different talks underlined major changes in COPD including the concepts of pre-COPD, etiotypes, health trajectories and new definitions of exacerbation. Recent results in biologics for COPD open the door to new pharmacological options. Assessment of current care pathways in France highlighted some causes for concern. For example, pulmonary rehabilitation is a key but insufficiently practiced element. Respiratory infections require careful assessment and treatments. Diagnosis and treatment of cardiovascular comorbidities and pulmonary hypertension are of paramount importance. As of late, oxygen therapy and ventilation modalities have evolved, and are beginning to afford more personalized options. CONCLUSIONS: As regards COPD, a personalized approach is crucial, placing the patient at the center of the care pathway and facilitating coordination between healthcare providers.

From means to meaning in the study of sex/gender differences and similarities.

The incorporation of sex and gender (S/G) related factors is commonly acknowledged as a necessary step to advance towards more personalized diagnoses and treatments for somatic, psychiatric, and neurological diseases. Until now, most attempts to integrate S/G-related factors have been reduced to identifying average differences between females and males in behavioral/ biological variables. The present commentary questions this traditional approach by highlighting three main sets of limitations: 1) Issues stemming from the use of classic parametric methods to compare means; 2) challenges related to the ability of means to accurately represent the data within groups and differences between groups; 3) mean comparisons impose a results' binarization and a binary theoretical framework that precludes advancing towards precision medicine. Alternative methods free of these limitations are also discussed. We hope these arguments will contribute to reflecting on how research on S/G factors is conducted and could be improved.

The impact of rare cancer and early-line treatments on the benefit of comprehensive genome profiling-based precision oncology.

BACKGROUND: Comprehensive genome profiling (CGP) serves as a guide for suitable genomically matched therapies for patients with cancer. However, little is known about the impact of the timing and types of cancer on the therapeutic benefit of CGP. MATERIALS AND METHODS: A single hospital-based pan-cancer prospective study (TOP-GEAR; UMIN000011141) was conducted to examine the benefit of CGP with respect to the timing and types of cancer. Patients with advanced solid tumors (>30 types) who either progressed with or without standard treatments were genotyped using a single CGP test. The subjects were followed up for a median duration of 590 days to examine therapeutic response, using progression-free survival (PFS), PFS ratio, and factors associated with therapeutic response. RESULTS: Among the 507 patients, 62 (12.2%) received matched therapies with an overall response rate (ORR) of 32.3%. The PFS ratios (≥1.3) were observed in 46.3% (19/41) of the evaluated patients. The proportion of subjects receiving such therapies in the rare cancer cohort was lower than that in the non-rare cancer cohort (9.6% and 17.4%, respectively; P = 0.010). However, ORR of the rare cancer patients was higher than that in the non-rare cancer cohort (43.8% and 20.0%, respectively; P = 0.046). Moreover, ORR of matched therapies in the first or second line after receiving the CGP test was higher than that in the third or later lines (62.5% and 21.7%, respectively; P = 0.003). Rare cancer and early-line treatment were significantly and independently associated with ORR of matched therapies in multivariable analysis (P = 0.017 and 0.004, respectively). CONCLUSION: Patients with rare cancer preferentially benefited from tumor mutation profiling by increasing the chances of therapeutic response to matched therapies. Early-line treatments after profiling increase the therapeutic benefit, irrespective of tumor types.

Precision medicine for prostate cancer: An international perspective.

Greater personalization of cancer medicine continues to shape therapy development and patient selection accordingly. The treatment of prostate cancer has evolved considerably since the discovery of androgen deprivation therapy. The comprehensive profiling of the prostate cancer genome has mapped the targetable molecular landscape of the disease and identified opportunities for the implementation of novel and combination therapies. In this review, we provide an overview of the molecular biology of prostate cancer and tools developed to aid prognostication and prediction of therapy benefit. Modern treatment of advanced prostate cancer is reviewed as a paradigm of increasing precision-informed approach to patient care, and must be considered on a global scale with respect to the state of science and care delivery.

Biological Basis of Breast Cancer-Related Disparities in Precision Oncology Era.

Precision oncology is based on deep knowledge of the molecular profile of tumors, allowing for more accurate and personalized therapy for specific groups of patients who are different in disease susceptibility as well as treatment response. Thus, onco-breastomics is able to discover novel biomarkers that have been found to have racial and ethnic differences, among other types of disparities such as chronological or biological age-, sex/gender- or environmental-related ones. Usually, evidence suggests that breast cancer (BC) disparities are due to ethnicity, aging rate, socioeconomic position, environmental or chemical exposures, psycho-social stressors, comorbidities, Western lifestyle, poverty and rurality, or organizational and health care system factors or access. The aim of this review was to deepen the understanding of BC-related disparities, mainly from a biomedical perspective, which includes genomic-based differences, disparities in breast tumor biology and developmental biology, differences in breast tumors' immune and metabolic landscapes, ecological factors involved in these disparities as well as microbiomics- and metagenomics-based disparities in BC. We can conclude that onco-breastomics, in principle, based on genomics, proteomics, epigenomics, hormonomics, metabolomics and exposomics data, is able to characterize the multiple biological processes and molecular pathways involved in BC disparities, clarifying the differences in incidence, mortality and treatment response for different groups of BC patients.

Mutational landscape of oral mucosal melanoma based on comprehensive cancer genomic profiling tests in a Japanese cohort.

OBJECTIVES: Oral mucosal melanoma (OMM) is a rare but aggressive melanoma subtype. Due to its rarity, the genomic landscape of OMM remains unknown despite a relatively thorough understanding of the genetic profile of cutaneous melanoma (CM). In this study, we analyzed the genomic mutational profiles of Japanese patients with OMM and compared them with those of patients with nose/sinuses mucosal melanoma (NMM) and CM to identify potential therapeutic targets. MATERIALS AND METHODS: We extracted clinical and genomic information of patients with OMM (n = 15), NMM (n = 63), and CM (n = 413) who underwent comprehensive genomic profiling tests under the National Health Insurance between June 2019 and November 2023 from the Center for Cancer Genomics and Therapeutics database. RESULTS: The most frequent genomic alteration identified in OMM was RICTOR (40%) followed by CDK4 (33.3%), MDM2 (33.3%), KDR (30%), KIT (26.7%), and NF1 (26.7%). CDK4 and MDM2 were co-amplified. Gene alterations in MYC and NRAS were the highest in patients with NMM, followed by those with CM, and no MYC alteration was observed in patients with OMM. BRAF V600 mutation, which is frequently observed in patients with CM (23.2%) were only present in 1.6% of patients with NMM and none in patients with OMM. CONCLUSION: This study clarified the genetic differences between OMM and NMM, and the first to report the frequent occurrence of RICTOR amplification in OMM. This analysis offers insights into the development of personalized therapeutics for OMM.

Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders.

BACKGROUND AND HYPOTHESIS: The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample. STUDY DESIGN: Participants with schizophrenia (SZ; N = 58), bipolar disorder (N = 42), major depression disorder (N = 51), and psychiatrically healthy controls (N = 92) completed a visual perception task in which stimuli appeared briefly. The design allowed us to estimate the lapse rate and the precision of perceptual representations of the stimuli. Electroencephalograms (EEG) were recorded to examine pre-stimulus activity in the alpha band (8-13 Hz), overall and in relation to behavior performance on the task. STUDY RESULTS: We found that the attention lapse rate was elevated in the SZ group compared with all other groups. We also observed group differences in pre-stimulus alpha activity, with control participants showing the highest levels of pre-stimulus alpha when averaging across trials. However, trial-by-trial analyses showed within-participant fluctuations in pre-stimulus alpha activity significantly predicted the likelihood of making an error, in all groups. Interestingly, our analysis demonstrated that aperiodic contributions to the EEG signal (which affect power estimates across frequency bands) serve as a significant predictor of behavior as well. CONCLUSIONS: These results confirm the elevated attention lapse rate that has been observed in SZ, validate pre-stimulus EEG markers of attentional control and their use as a predictor of behavior on a trial-by-trial basis, and suggest that aperiodic contributions to the EEG signal are an important target for further research in this area, in addition to alpha-band activity.

Harnessing gastrointestinal organoids for cancer therapy.

Gastrointestinal organoids have emerged as a model system that authentically recapitulates the in vivo situation. Despite biomedical and technical challenges, self-assembled 3D structures derived from pluripotent stem cells or healthy and diseased tissues have proved to be invaluable tools for cancer drug discovery, disease modeling, and studying infection with carcinogenic pathogens.

Improving predictive accuracy in primary biliary cholangitis: A new genetic risk score.

BACKGROUND AND AIMS: Genetic variants influence primary biliary cholangitis (PBC) risk. We established and tested an accurate polygenic risk score (PRS) using these variants. METHODS: Data from two Italian cohorts (OldIT 444 cases, 901 controls; NewIT 255 cases, 579 controls) were analysed. The latest international genome-wide meta-analysis provided effect size estimates. The PRS, together with human leukocyte antigen (HLA) status and sex, was included in an integrated risk model. RESULTS: Starting from 46 non-HLA genes, 22 variants were selected. PBC patients in the OldIT cohort showed a higher risk score than controls: -.014 (interquartile range, IQR, -.023, .005) versus -.022 (IQR -.030, -.013) (p < 2.2 × 10-16). For genetic-based prediction, the area under the curve (AUC) was .72; adding sex increased the AUC to .82. Validation in the NewIT cohort confirmed the model's accuracy (.71 without sex, .81 with sex). Individuals in the top group, representing the highest 25%, had a PBC risk approximately 14 times higher than that of the reference group (lowest 25%; p < 10-6). CONCLUSION: The combination of sex and a novel PRS accurately discriminated between PBC cases and controls. The model identified a subset of individuals at increased risk of PBC who might benefit from tailored monitoring.

How do grazing beef and dairy cattle respond to virtual fences? A review.

Virtual fencing (VF) is a modern fencing technology that requires the animal to wear a device (e.g. a collar) that emits acoustic signals to replace the visual cue of traditional physical fences (PF) and, if necessary, mild electric signals. The use of devices that provide electric signals leads to concerns regarding the welfare of virtually fenced animals. The objective of this review is to give an overview of the current state of VF research into the welfare and learning behavior of cattle. Therefore, a systematic literature search was conducted using two online databases and reference lists of relevant articles. Studies included were peer-reviewed and written in English, used beef or dairy cattle, and tested neck-mounted VF devices. Further inclusion criteria were a combination of audio and electrical signals and a set-up as a pasture trial, which implied that animals grazed in groups on grassland for four hours minimum while at least one fence side was virtually fenced. The eligible studies (n = 13) were assigned to one or two of the following categories: animal welfare (n studies = 8) or learning behavior (n studies = 9). As data availability for conducting a meta-analysis was not sufficient, a comparison of the means of welfare indicators (daily weight gain, daily lying time, steps per hour, daily number of lying bouts, fecal cortisol metabolites (FCM)) for virtually and physically fenced animals was done instead. In an additional qualitative approach, the results from the welfare-related studies were assembled and discussed. For the learning behavior, the number of acoustic and electric signals and their ratio were used in a linear regression model with duration in days as a numeric predictor to assess the learning trends over time. There were no significant differences between VF and PF for most welfare indicators (except FCM with lower values for VF; P = 0.0165). The duration in days did not have a significant effect on the number of acoustic and electric signals. However, a significant effect of trial duration on the ratio of electric to acoustic signals (P = 0.0014) could be detected, resulting in a decreasing trend of the ratio over time, which suggests successful learning. Overall, we conclude that the VF research done so far is promising but is not yet sufficient to ensure that the technology could not have impacts on the welfare of certain cattle types. More research is necessary to investigate especially possible long-term effects of VF.