Search

Abstract We propose a fully automatic multi-task Bayesian model, named Bayesian Sequential Network (BSN), for predicting high-grade (Gleason $$\ge$$ ≥ 8) prostate cancer (PCa) prognosis using pre-prostatectomy FDG-PET/CT images and clinical data. BSN performs one classification task and five survival tasks: predicting lymph node invasion (LNI), biochemical recurrence-free survival (BCR-FS), metastasis-free survival, definitive androgen deprivation therapy-free survival, castration-resistant PCa-free survival, and PCa-specific survival (PCSS). Experiments are conducted using a dataset of 295 patients. BSN outperforms widely used nomograms on all tasks except PCSS, leveraging multi-task learning and imaging data. BSN also provides automated prostate segmentation, uncertainty quantification, personalized feature-based explanations, and introduces dynamic predictions, a novel approach that relies on short-term outcomes to refine long-term prognosis. Overall, BSN shows great promise in its ability to exploit imaging and clinicopathological data to predict poor outcome patients that need treatment intensification with loco-regional or systemic adjuvant therapy for high-risk PCa.

Abstract Background DNA methylation plays a critical role in asthma development, but differences in DNA methylation among adults with varying asthma severity are less well-defined. Objective To examine how DNA methylomic patterns differ among adults with asthma based on asthma severity and airway inflammation. Methods Peripheral blood T cells from 35 adults with asthma in Beijing, China, were serially collected over time (130 samples total) and analyzed for global DNA methylation using the Illumina MethylationEPIC Array. Differential methylation was compared among subjects with varying airway inflammation and severity, as measured by fraction of exhaled nitric oxide, forced expiratory volume in one second (FEV1), and Asthma Control Test (ACT) scores. Results Significant differences in DNA methylation were noted among subjects with different degrees of airway inflammation and asthma severity. These differences in DNA methylation were annotated to genes that were enriched in pathways related to asthma or T cell function and included gene ontology categories related to MHC class II assembly, T cell activation, interleukin (IL)-1, and IL-12. Genes related to P450 drug metabolism, glutathione metabolism, and developmental pathways were also differentially methylated in comparisons between subjects with high vs low FEV1 and ACT. Notable genes that were differentially methylated based on asthma severity included RUNX3, several members of the HLA family, AGT, PTPRC, PTPRJ, and several genes downstream of the JAK2 and TNF signaling pathway. Conclusion These findings demonstrate how adults with asthma of varying severity possess differences in peripheral blood T cell DNA methylation that contribute to differences in clinical indices of asthma.

Introduction: Childhood cancer survivors (CCS) are at risk of experiencing psychological distress years after completing cancer treatments. We aimed to assess the prevalence and associated risk factors affecting psychological distress and health-related quality of life (HRQOL) among CCS in Singapore, and compare with their siblings without a history of or existing cancer as control. Method: We recruited 143 young adult CCS aged ≥18 years attending survivorship clinics at KK Women’s and Children’s Hospital in Singapore who were in remission for ≥5 years and treatment-free for ≥2 years, and 57 siblings. CCS and siblings were matched at a 1:1 ratio based on sociodemographic factors yielding 46 pairs for comparison. Among CCS participants, 79 (55.2%) were male, 86 (60.1%) had leukaemia, 29 (20.3%) had solid tumours, 15 (10.5%) had lymphoma and 13 (9.1%) had brain tumours. All participants completed the Brief Symptom Inventory-18 (BSI-18) and Medical Outcomes Short Form-36 (MOS SF-36) questionnaires from August 2021 to July 2022. Results: There were 35 (24.5%) CCS who reported psychological distress in the BSI-18 Global Severity Index. Five (3.5%) and 31 (21.7%) CCS reported low HRQOL in the physical and mental composite scores, respectively. Mean scores between CCS and their siblings were not statistically significant across all domains of the BSI-18 and MOS SF-36. Associated risk factors for psychological distress and low HRQOL among CCS were history of psychiatric illness after cancer diagnosis and mood affected by the COVID-19 pandemic. Conclusion: CCS reported significant psychological distress and low HRQOL although they were not statistically different from their siblings. A holistic and risk factor-centric follow-up programme can aid early detection and mitigation of psychological late effects for CCS and their families.

Integrating machine learning into medical diagnostics has revolutionized the field, particularly enhancing Computer-aided Diagnosis (CAD) systems. These systems assist healthcare professionals by leveraging medical data and machine learning algorithms for more accurate diagnosis and treatment plans. Mammography, an X-ray-based imaging technique, is pivotal in early breast cancer detection, enabling the differentiation between benign and malignant lesions. Recent studies have focused on developing deep learning-enabled mammography CAD systems, which have shown promising results in detecting, segmenting, and classifying anomalies in mammogram images. This comprehensive review presents an innovative system architecture for breast cancer detection, segmentation, and classification using deep learning within mammography CAD systems. It also explores publicly available mammogram datasets and the critical parameters for assessing deep learning system performance. The literature review is meticulously conducted using the PRISMA methodology to evaluate and synthesise novel research findings in this domain. This survey highlights the technological advancements and underlines the potential of deep learning in transforming mammographic analysis for breast cancer detection.

Abstract Background During the coronavirus disease of 2019 (COVID-19) pandemic, in-person interviews for the recruitment of family medicine residents shifted to online (virtual) interviews. The purpose of this study was twofold: (1) to gather the ideas about virtual interviews of family medicine applicants (interviewees), and faculty and staff who interviewed these applicants (interviewers), and (2) to describe interviewers’ and interviewees’ opinions of use of emerging technologies such as artificial intelligence (AI) and virtual reality (VR) in the recruitment process as well as during clinical practice. Methods This was a cross-sectional survey study. Participants were both interviewers and candidates who applied to the McGill University Family Medicine Residency Program for the 2020–2021 and 2021–2022 cycles. Results The study population was constituted by N = 132 applicants and N = 60 interviewers. The response rate was 91.7% (55/60) for interviewers and 43.2% (57/132) for interviewees. Both interviewers (43.7%) and interviewees (68.5%) were satisfied with connecting through virtual interviews. Interviewers (43.75%) and interviewees (55.5%) would prefer for both options to be available. Both interviewers (50%) and interviewees (72%) were interested in emerging technologies. Almost all interviewees (95.8%) were interested in learning about AI and VR and its application in clinical practice with the majority (60.8%) agreeing that it should be taught within medical training. Conclusion Although experience of virtual interviewing during the COVID-19 pandemic has been positive for both interviewees and interviewers, the findings of this study suggest that it will be unlikely that virtual interviews completely replace in-person interviews for selecting candidates for family medicine residency programs in the long term as participants value aspects of in-person interviews and would want a choice in format. Since incoming family medicine physicians seem to be eager to learn and utilize emerging technologies such as AI and VR, educators and institutions should consider family physicians’ needs due to the changing technological landscape in family medicine education.

Abstract The relationship between economic growth and CO2 emissions has been analyzed testing the environmental Kuznets curve hypothesis, but traditional econometric methods may be flawed. An alternative method is proposed using segmented-sample regressions and implemented in 164 countries (98.34% of world population) over different periods from 1822 to 2018. Results suggest that while the association between GDP per capita and CO2 emissions per capita is weakening over time, it remains positive globally, with only some high-income countries showing a reversed association in recent years. While 49 countries have decoupled emissions from economic growth, 115 have not. Most African, American, and Asian countries have not decoupled, whereas most European and Oceanians have. These findings highlight the urgency for effective climate policies because decoupling remains unachieved on a global scale, and we are moving away from, rather than approaching, the Paris Agreement goal of limiting temperature increase to 1.5 °C above preindustrial levels.

Abstract The Department of Biotechnology at Savitribai Phule Pune University organized an International Conference on Biology Beyond Boundaries: Mitochondrial Insights, Computational Breakthroughs, and Clinical Transformations. The symposium provided a highly interactive platform for sharing scientific ideas, cultural enrichment, and collaborations between scientists working across multidisciplinary areas including cell death and mitochondrial biology, computational approaches, and translational research to combat various human diseases. More than 250 delegates including international scientists, junior investigators, and students joined this exciting event. Several sessions were dedicated for junior investigators and graduate students to highlight scientific excellence as well as to gather scientific feedback in advancing their ongoing research. Although promising progress has been made in infectious diseases in India, noncommunicable diseases such as cancer, cardiac, and neurodegenerative diseases are increasing, leading to higher funding in these areas of research. The success of this meeting has provided a platform for future scientific conferences, which will foster collaborations between multidisciplinary areas of biological sciences to prevent and treat various human diseases in India, as well as further showcase the progress in Biomedical Sciences and Biotechnology throughout India.

Abstract The tissues of origin of plasma DNA can be revealed by methylation patterns. However, the relative DNA contributions from megakaryocytes and erythroblasts into plasma appeared inconsistent among studies. To shed light into this phenomenon, we developed droplet digital PCR (ddPCR) assays for the differential detection of contributions from these cell types in plasma based on megakaryocyte-specific and erythroblast-specific methylation markers. Megakaryocytic DNA and erythroid DNA contributed a median of 44.2% and 6.2% in healthy individuals, respectively. Patients with idiopathic thrombocytopenic purpura had a significantly higher proportion of megakaryocytic DNA in plasma compared to healthy controls (median: 59.9% versus 44.2%; P = 0.03). Similarly, patients with β-thalassemia were shown to have higher proportions of plasma erythroid DNA compared to healthy controls (median: 50.9% versus 6.2%) (P

Abstract Climate-induced changes in hypoxia are among the most serious threats facing estuaries, which are among the most productive ecosystems on Earth. Future projections of estuarine hypoxia typically involve long-term multi-decadal continuous simulations or more computationally efficient time slice and delta methods that are restricted to short historical and future periods. We make a first comparison of these three methods by applying a linked terrestrial–estuarine model to the Chesapeake Bay, a large coastal-plain estuary in the eastern United States. Results show that the time slice approach accurately captures the behavior of the continuous approach, indicating a minimal impact of model memory. However, increases in mean annual hypoxic volume by the mid-twenty-first century simulated by the delta approach (+ 19%) are approximately twice as large as the time slice and continuous experiments (+ 9% and + 11%, respectively), indicating an important impact of changes in climate variability. Our findings suggest that system memory and projected changes in climate variability, as well as simulation length and natural variability of system hypoxia, should be considered when deciding to apply the more computationally efficient delta and time slice methods.

Abstract The interleukin (IL)-23 pathway is a pathogenic driver in psoriasis, psoriatic arthritis, and inflammatory bowel disease. Currently, no oral therapeutics selectively target this pathway. JNJ-77242113 is a peptide targeting the IL-23 receptor with high affinity (KD: 7.1 pM). In human cells, JNJ-77242113 potently and selectively inhibited proximal IL-23 signaling (IC50: 5.6 pM) without impacting IL-12 signaling. JNJ-77242113 inhibited IL-23–induced interferon (IFN)γ production in NK cells, and in blood from healthy donors and psoriasis patients (IC50: 18.4, 11 and 9 pM, respectively). In a rat trinitrobenzene sulfonic acid-induced colitis model, oral JNJ-77242113 attenuated disease parameters at doses ≥ 0.3 mg/kg/day. Pharmacologic activity beyond the gastrointestinal tract was also demonstrated. In blood from rats receiving oral JNJ-77242113, dose-dependent inhibition of ex vivo IL-23–stimulated IL-17A production was observed. In an IL-23–induced rat skin inflammation model, JNJ-77242113 inhibited IL-23–induced skin thickening and IL-17A, -17F and -22 gene induction. Oral dosing of JNJ-77242113 in healthy human volunteers inhibited ex vivo IL-23–stimulated IFNγ production in whole blood. Thus, JNJ-77242113 provided selective, systemic IL-23 pathway inhibition in preclinical models which translated to pharmacodynamic activity in healthy human volunteers, supporting the potential for JNJ-77242113 as a selective oral therapy for IL-23–driven immune-mediated diseases.

Abstract Background Social behaviour plays a key role in mental health and wellbeing, and developing greater understanding of mechanisms underlying social interaction—particularly social motivation—holds substantial transdiagnostic impact. Common rodent behavioural assays used to assess social behaviour are limited in their assessment of social motivation, whereas the social operant conditioning model can provide unique and valuable insights into social motivation. Further characterisation of common experimental parameters that may influence social motivation within the social operant model, as well as complementary methodological and analytical approaches, are warranted. Methods This study investigated the effects of biological sex, housing condition, and time-of-day, on social motivation using the social operant model. This involved training rats to lever press (FR1) for 60-s access to a social reward (same-sex conspecific stimulus). Subjects were male and female Wistar rats, housed under individual or paired conditions, and sessions were conducted either in the mid-late light phase (ZT6-10) or early-mid dark phase (ZT13-17). A behavioural economics approach was implemented to measure social demand and the influence of stimulus partner sex (same- vs. opposite-sex stimulus) on social operant responding. Additionally, video tracking analyses were conducted to assess the degree of convergence between social appetitive and consummatory behaviours. Results Biological sex, housing conditions, the interaction between sex and housing, and stimulus partner sex potently influenced social motivation, whereas time-of-day did not. Behavioural economics demonstrated that sex, housing, and their interaction influence both the hedonic set-point and elasticity of social demand. Video analysis of social interaction during social operant sessions revealed that social appetitive and consummatory behaviours are not necessarily convergent, and indicate potential social satiety. Lastly, oestrus phase of female experimental and stimulus rats did not impact social motivation within the model. Conclusions Social isolation-dependent sex differences exist in social motivation for rats, as assessed by social operant conditioning. The social operant model represents an optimal preclinical assay that comprehensively evaluates social motivation and offers a platform for future investigations of neurobiological mechanisms underlying sex differences in social motivation. These findings highlight the importance of continued consideration and inclusion of sex as a biological variable in future social operant conditioning studies. Plain English summary Humans are social creatures—our everyday interactions with others and the support this provides play a key role in our wellbeing. For those experiencing mental health conditions, people’s motivation to engage with others can wane, which can lead them to withdraw from those who support them. Therefore, to develop better treatment strategies for these conditions, we need to gain a deeper understanding of social motivation. Studying social behaviour in animals can facilitate this investigation of social motivation as it allows for a causal understanding of underlying neurobiology that is not possible in human experiments. An optimal way to study social motivation in animals is using the social operant conditioning model, where rats learn to press a lever that opens a door and allows them to interact with another rat for a short time. This study characterised the social operant model by testing whether sex, housing conditions, time-of-day, and the sex of the stimulus partner influence rats’ motivation to seek interaction with another rat. We found that female rats were more socially motivated than males, and that rats living alone were more motivated than those living with another rat; interestingly, this effect of housing affected females more than males. Regardless of sex, rats were more motivated to interact with a rat of the opposite sex. These findings provide insights into sex differences in social motivation in rats and new insights into the social operant model which will help guide future research into social motivation and other mental health conditions.

Abstract Background An increasing proportion of lung adenocarcinoma (LUAD) occurs in patients even after they have stopped smoking. Here, we aimed to determine whether tobacco smoking induced changes across LUADs from patients who formerly smoked correspond to different biological and clinical factors. Methods Random forest models (RFs) were trained utilizing a smoking associated signature developed from differentially expressed genes between LUAD patients who had never smoked (NS) or currently smoked (CS) from TCGA (n = 193) and BCCA (n = 69) cohorts. The RFs were subsequently applied to 299 and 131 formerly smoking patients from TCGA and MSKCC cohorts, respectively. FS were RF-classified as either CS-like or NS-like and associations with patient characteristics, biological features, and clinical outcomes were determined. Results We elucidated a 123 gene signature that robustly classified NS and CS in both RNA-seq (AUC = 0.85) and microarray (AUC = 0.92) validation test sets. The RF classified 213 patients who had formerly smoked as CS-like and 86 as NS-like from the TCGA cohort. CS-like and NS-like status in formerly smoking patients correlated poorly with patient characteristics but had substantially different biological features including tumor mutational burden, number of mutations, mutagenic signatures and immune cell populations. NS-like formerly smoking patients had 17.5 months and 18.6 months longer overall survival than CS-like patients from the TCGA and MSKCC cohorts, respectively. Conclusions Patients who had formerly smoked with LUAD harbor heterogeneous tumor biology. These patients can be divided by smoking induced gene expression to inform prognosis and underlying biological characteristics for treatment selection.

Abstract Background Cognitive dysfunction is one of the common symptoms in patients with major depressive disorder (MDD). Repetitive transcranial magnetic stimulation (rTMS) and transcranial direct current stimulation (tDCS) have been studied separately in the treatment of cognitive dysfunction in MDD patients. We aimed to investigate the effectiveness and safety of rTMS combined with tDCS as a new therapy to improve neurocognitive impairment in MDD patients. Methods In this brief 2-week, double-blind, randomized, and sham-controlled trial, a total of 550 patients were screened, and 240 MDD inpatients were randomized into four groups (active rTMS + active tDCS, active rTMS + sham tDCS, sham rTMS + active tDCS, sham rTMS + sham tDCS). Finally, 203 patients completed the study and received 10 treatment sessions over a 2-week period. The Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) was performed to assess patients’ cognitive function at baseline and week 2. Also, we applied the 24-item Hamilton Depression Rating Scale (HDRS-24) to assess patients’ depressive symptoms at baseline and week 2. Results After 10 sessions of treatment, the rTMS combined with the tDCS group showed more significant improvements in the RBANS total score, immediate memory, and visuospatial/constructional index score (all p

Abstract The primary hurdles for small interference RNA (siRNA) in clinical use are targeted and cytosolic delivery. To overcome both challenges, we have established a novel platform based on phage display, called NNJA. In this approach, a lysosomal cathepsin substrate is engineered within the flexible loops of PIII, that is displaying a unique random sequence at its N-terminus. NNJA library selection targeting cell-expressed targets should yield specific peptides localized in the cytoplasm. That is because phage internalization and subsequent localization to lysosome, upon peptide binding to the cell expressed target, will result in cleavage of PIII, rendering phage non-infective. Such phage will be eliminated from the selected pool and only peptide-phage that escapes lysosomes will advance to the next round. Proof of concept studies with the NNJA library demonstrated cytosolic localization of selected peptide-phage and peptide-siRNA, confirmed through confocal microscopy. More importantly, conjugation of siHPRT to monomeric or multimeric NNJA peptides resulted in significant reduction in HPRT mRNA in various cell types without significant cytotoxicity. Sequence similarity and clustering analysis from NGS dataset provide insights into sequence composition facilitating cell penetration. NNJA platform offers a highly efficient peptide discovery engine for targeted delivery of oligonucleotides to cytosol.

Abstract In exploring nature's potential in addressing diabetes-related conditions, this study investigates the therapeutic capabilities of 3-formyl chromone derivatives. Utilizing in silico methodologies, we focus on 6-substituted 3-formyl chromone derivatives (1–16) to assess their therapeutic potential in treating diabetes. The research examined the formyl group at the chromone’s C-3 position. ADMET, biological activities, were conducted along with B3LYP calculations using 3 different basis sets. The analogues were analyzed based on their parent structure obtained from PubChem. The HOMO–LUMO gap confirmed the bioactive nature of the derivatives, NBO analysis was performed to understand the charge transfer. PASS prediction revealed that 3-formyl chromone derivatives are potent aldehyde oxidase inhibitors, insulin inhibitors, HIF1A expression inhibitors, and histidine kinase. Molecular docking studies indicated that the compounds had a strong binding affinity with proteins, including CAD, BHK, IDE, HIF-α, p53, COX, and Mpro of SARS-CoV2. 6-isopropyl-3-formyl chromone (4) displayed the highest affinity for IDE, with a binding energy of − 8.5 kcal mol−1. This result outperformed the affinity of the reference standard dapagliflozin (− 7.9 kcal mol−1) as well as two other compounds that target human IDE, namely vitexin (− 8.3 kcal mol−1) and myricetin (− 8.4 kcal mol−1). MD simulations were revealed RMSD value between 0.2 and 0.5 nm, indicating the strength of the protein–ligand complex at the active site.

BackgroundThe underdiagnosis of cognitive impairment hinders timely intervention of dementia. Health professionals working in the community play a critical role in the early detection of cognitive impairment, yet still face several challenges such as a lack of suitable tools, necessary training, and potential stigmatization. ObjectiveThis study explored a novel application integrating psychometric methods with data science techniques to model subtle inconsistencies in questionnaire response data for early identification of cognitive impairment in community environments. MethodsThis study analyzed questionnaire response data from participants aged 50 years and older in the Health and Retirement Study (waves 8-9, n=12,942). Predictors included low-quality response indices generated using the graded response model from four brief questionnaires (optimism, hopelessness, purpose in life, and life satisfaction) assessing aspects of overall well-being, a focus of health professionals in communities. The primary and supplemental predicted outcomes were current cognitive impairment derived from a validated criterion and dementia or mortality in the next ten years. Seven predictive models were trained, and the performance of these models was evaluated and compared. ResultsThe multilayer perceptron exhibited the best performance in predicting current cognitive impairment. In the selected four questionnaires, the area under curve values for identifying current cognitive impairment ranged from 0.63 to 0.66 and was improved to 0.71 to 0.74 when combining the low-quality response indices with age and gender for prediction. We set the threshold for assessing cognitive impairment risk in the tool based on the ratio of underdiagnosis costs to overdiagnosis costs, and a ratio of 4 was used as the default choice. Furthermore, the tool outperformed the efficiency of age or health-based screening strategies for identifying individuals at high risk for cognitive impairment, particularly in the 50- to 59-year and 60- to 69-year age groups. The tool is available on a portal website for the public to access freely. ConclusionsWe developed a novel prediction tool that integrates psychometric methods with data science to facilitate “passive or backend” cognitive impairment assessments in community settings, aiming to promote early cognitive impairment detection. This tool simplifies the cognitive impairment assessment process, making it more adaptable and reducing burdens. Our approach also presents a new perspective for using questionnaire data: leveraging, rather than dismissing, low-quality data.

Summary: Background: Brain ageing is highly heterogeneous, as it is driven by a variety of normal and neuropathological processes. These processes may differentially affect structural and functional brain ageing across individuals, with more pronounced ageing (older brain age) during midlife being indicative of later development of dementia. Here, we examined whether brain-ageing heterogeneity in unimpaired older adults related to neurodegeneration, different cognitive trajectories, genetic and amyloid-beta (Aβ) profiles, and to predicted progression to Alzheimer’s disease (AD). Methods: Functional and structural brain age measures were obtained for resting-state functional MRI and structural MRI, respectively, in 3460 cognitively normal individuals across an age range spanning 42–85 years. Participants were categorised into four groups based on the difference between their chronological and predicted age in each modality: advanced age in both (n = 291), resilient in both (n = 260) or advanced in one/resilient in the other (n = 163/153). With the resilient group as the reference, brain-age groups were compared across neuroimaging features of neuropathology (white matter hyperintensity volume, neuronal loss measured with Neurite Orientation Dispersion and Density Imaging, AD-specific atrophy patterns measured with the Spatial Patterns of Abnormality for Recognition of Early Alzheimer’s Disease index, amyloid burden using amyloid positron emission tomography (PET), progression to mild cognitive impairment and baseline and longitudinal cognitive measures (trail making task, mini mental state examination, digit symbol substitution task). Findings: Individuals with advanced structural and functional brain-ages had more features indicative of neurodegeneration and they had poor cognition. Individuals with a resilient brain-age in both modalities had a genetic variant that has been shown to be associated with age of onset of AD. Mixed brain-age was associated with selective cognitive deficits. Interpretation: The advanced group displayed evidence of increased atrophy across all neuroimaging features that was not found in either of the mixed groups. This is in line with biomarkers of preclinical AD and cerebrovascular disease. These findings suggest that the variation in structural and functional brain ageing across individuals reflects the degree of underlying neuropathological processes and may indicate the propensity to develop dementia in later life. Funding: The National Institute on Aging, the National Institutes of Health, the Swiss National Science Foundation, the Kaiser Foundation Research Institute and the National Heart, Lung, and Blood Institute.

Background and Objective: Adverse Childhood Experiences(ACEs) have a powerful influence on mental health, physical health, and life expectancy. Screening for ACEs and the clinician response to ACEs are critical to addressing the health and well-being of children; however, little is known about the actions clinicians take in response to ACE screening. Therefore, we aimed to examine clinician responses to ACE screening at five California pediatric clinics in a large public health care system. Methods: Patient demographics, indicators of social and behavioral determinants of health (e.g., housing insecurity), the number of ACEs endorsed on a screening instrument, and the actions clinicians took in response to each ACE screen were collected. Data was collected from May to October 2021. These data were used to examine the association between number of ACEs reported and clinician response, controlling for patient demographics and their social and behavioral determinants of health using multiple logistic regression. Results: Five participating pediatric clinics conducted 2,652 ACE screens in six-months. Clinicians documented an action twice as often when ACEs were present, after controlling for patient demographics and their social and behavioral determinants of health (odds ratio(OR) = 2.2, 95 % confidence interval(CI): 1.5–3.3, p-value

Patients present a wide range of clinical severities in response severe acute respiratory syndrome coronavirus 2 infection, but the underlying molecular and cellular reasons why clinical outcomes vary so greatly within the population remains unknown. Here, we report that negative clinical outcomes in severely ill patients were associated with divergent RNA transcriptome profiles in peripheral immune cells compared with mild cases during the first weeks after disease onset. Protein–protein interaction analysis indicated that early-responding cytotoxic natural killer cells were associated with an effective clearance of the virus and a less severe outcome. This innate immune response was associated with the activation of select cytokine–cytokine receptor pathways and robust Th1/Th2 cell differentiation profiles. In contrast, severely ill patients exhibited a dysregulation between innate and adaptive responses affiliated with divergent Th1/Th2 profiles and negative outcomes. This knowledge forms the basis of clinical triage that may be used to preemptively detect high-risk patients before life-threatening outcomes ensue.

Abstract The extracellular matrix (ECM) governs a wide spectrum of cellular fate processes, with a particular emphasis on anoikis, an integrin‐dependent form of cell death. Currently, anoikis is defined as an intrinsic apoptosis. In contrast to traditional apoptosis and necroptosis, integrin correlates ECM signaling with intracellular signaling cascades, describing the full process of anoikis. However, anoikis is frequently overlooked in physiological and pathological processes as well as traditional in vitro research models. In this review, we summarized the role of anoikis in physiological and pathological processes, spanning embryonic development, organ development, tissue repair, inflammatory responses, cardiovascular diseases, tumor metastasis, and so on. Similarly, in the realm of stem cell research focused on the functional evolution of cells, anoikis offers a potential solution to various challenges, including in vitro cell culture models, stem cell therapy, cell transplantation, and engineering applications, which are largely based on the regulation of cell fate by anoikis. More importantly, the regulatory mechanisms of anoikis based on molecular processes and ECM signaling will provide new strategies for therapeutic interventions (drug therapy and cell‐based therapy) in disease. In summary, this review provides a systematic elaboration of anoikis, thus shedding light on its future research.

Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Summary: Background: De novo amino acid substitutions (DNS) frequently emerge among immunocompromised patients with chronic SARS-CoV-2 infection. While previous studies have reported these DNS, their significance has not been systematically studied. Methods: We performed a review of DNS that emerged during chronic SARS-CoV-2 infection. We searched PubMed until June 2023 using the keywords “(SARS-CoV-2 or COVID-19) and (mutation or sequencing) and ((prolonged infection) or (chronic infection) or (long term))”. We included patients with chronic SARS-CoV-2 infection who had SARS-CoV-2 sequencing performed for at least 3 time points over at least 60 days. We also included 4 additional SARS-CoV-2 patients with chronic infection of our hospital not reported previously. We determined recurrent DNS that has appeared in multiple patients and determined the significance of these mutations among epidemiologically-significant variants. Findings: A total of 34 cases were analyzed, including 30 that were published previously and 4 from our hospital. Twenty two DNS appeared in ≥3 patients, with 14 (64%) belonging to lineage-defining mutations (LDMs) of epidemiologically-significant variants and 10 (45%) emerging among chronically-infected patients before the appearance of the corresponding variant. Notably, nsp9-T35I substitution (Orf1a T4175I) emerged in all three patients with BA.2.2 infection in 2022 before the appearance of Variants of Interest that carry nsp9-T35I as LDM (EG.5 and BA.2.86/JN.1). Structural analysis suggests that nsp9-T35I substitution may affect nsp9-nsp12 interaction, which could be critical for the function of the replication and transcription complex. Interpretation: DNS that emerges recurrently in different chronically-infected patients may be used as a marker for potential epidemiologically-significant variants. Funding: Theme-Based Research Scheme [T11/709/21-N] of the Research Grants Council (See acknowledgements for full list).

Summary: Background: Understanding how SARS-CoV-2 breakthrough infections impacts the breadth of immune responses against existing and pre-emergent SARS-CoV-2 strains is needed to develop an evidence-based long-term immunisation strategy. Methods: We performed a randomised, controlled trial to assess the immunogenicity of homologous (BNT162b2) versus heterologous (mRNA-1273) booster vaccination in 100 BNT162b2-vaccinated infection-naïve individuals enrolled from October 2021. Post hoc analysis was performed to assess the impact of SARS-CoV-2 infection on humoral and cellular immune responses against wild-type SARS-CoV-2 and/or Omicron subvariants. Findings: 93 participants completed the study at day 360. 71% (66/93) of participants reported first SARS-CoV-2 Omicron infection by the end of the study with similar proportions of infections between homologous and heterologous booster groups (72.3% [34/47] vs 69.6% [32/46]; p = 0.82). Mean wildtype SARS-CoV-2 anti-S-RBD antibody level was significantly higher in heterologous booster group compared with homologous group at day 180 (14,588 IU/mL; 95% CI, 10,186–20,893 vs 7447 IU/mL; 4646–11,912; p = 0.025). Participants who experienced breakthrough infections during the Omicron BA.1/2 wave had significantly higher anti-S-RBD antibody levels against wildtype SARS-CoV-2 and antibody neutralisation against BA.1 and pre-emergent BA.5 compared with infection-naïve participants. Regardless of hybrid immunity status, wildtype SARS-CoV-2 anti-S-RBD antibody level declined significantly after six months post-booster or post-SARS-CoV-2 infection. Interpretation: Booster vaccination with mRNA-1273 was associated with significantly higher antibody levels compared with BNT162b2. Antibody responses are narrower and decline faster among uninfected, vaccinated individuals. Boosters may be more effective if administered shortly before infection outbreaks and at least six months after last infection or booster. Funding: Singapore NMRC, USFDA, MRC.

Item-level information, such as difficulty and discrimination are invaluable to the test assembly, equating, and scoring practices. Estimating these parameters within the context of large-scale performance assessments is often hindered by the use of unbalanced designs for assigning examinees to tasks and raters because such designs result in very sparse data matrices. This article addresses some of the issues using a multistage confirmatory factor analytic approach. The approach is illustrated using data from a performance test in medicine for which examinees encounter multiple patients with medical problems (tasks), with each problem portrayed by a different trained patient (rater). A series of models was fit to rating data (1) to obtain alternative task difficulty and discrimination parameters and (2) to evaluate the observed improvement in the goodness of model fit due to accounted rater and test site effects. The results suggest that availability of alternative task parameter estimates can be useful in practice for making decisions related to task banking, rater training, and test assembly. (Contains 3 figures, 2 tables and 1 footnote.)

Introduction Complex trauma can have serious impacts on the health and well-being of Aboriginal and Torres Strait Islander families. The perinatal period represents a ‘critical window’ for recovery and transforming cycles of trauma into cycles of healing. The Healing the Past by Nurturing the Future (HPNF) project aims to implement and evaluate a programme of strategies to improve support for Aboriginal and Torres Strait islander families experiencing complex trauma.Method The HPNF programme was codesigned over 4 years to improve awareness, support, recognition and assessment of trauma. Components include (1) a trauma-aware, healing-informed training and resource package for service providers; (2) trauma-awareness resources for parents; (3) organisational readiness assessment; (4) a database for parents and service providers to identify accessible and appropriate additional support and (5) piloting safe recognition and assessment processes. The programme will be implemented in a large rural health service in Victoria, Australia, over 12 months. Evaluation using a mixed-methods approach will assess feasibility, acceptability, cost, effectiveness and sustainability. This will include service user and provider interviews; service usage and cost auditing; and an administrative linked data study of parent and infant outcomes.Analysis Qualitative data will be analysed using reflexive thematic analysis. Quantitative and service usage outcomes will be described as counts and proportions. Evaluation of health outcomes will use interrupted time series analyses. Triangulation of data will be conducted and mapped to the Consolidated Framework for Implementation Research and Reach, Effectiveness, Adoption, Implementation and Maintenance frameworks to understand factors influencing feasibility, acceptability, effectiveness, cost and sustainability.Ethics and dissemination Approval granted from St Vincent’s Melbourne Ethics Committee (approval no. 239/22). Data will be disseminated according to the strategy outlined in the codesign study protocol, in-line with the National Health and Medical Research Council Aboriginal and Torres Strait Islander Research Excellence criteria.

Patients with Parkinson’s disease (PD) may present with prodromal (e.g. hyposmia, sleep disorders, constipation), motor (e.g. tremors, rigidity, bradykinesia, postural dysfunction) and non-motor (e.g. cognitive dysfunction, depression) symptoms.1 Treatment is symptomatic, targeting motor and non-motor manifestations, but there is presently no effective disease modifying treatment.1 Although PD therapies have primarily been focused on supplementing dopamine, which has improved survival and quality of life of PD patients,1-3 other neurotransmitter systems (e.g. serotonergic, cholinergic and noradrenergic) are also dysfunctional, especially for the non-motor symptoms.1,4,5 By the time patients reach the later stages of PD, many of them would have developed significant gait and balance difficulties, dysarthria, dysphagia and motor fluctuations like wearing off and levodopa-induced dyskinesias (LID), as well as non-motor symptoms such as orthostasis, depression, dementia and psychosis.1,2,6,7

Abstract A paper published in Orphanet Journal of Rare Diseases proposes a new classification of osteogenesis imperfecta (OI) based upon underlying pathological mechanisms. The proposed numbering of OI types conflicts with the currently used numbering and is likely to lead to confusion. In addition, classification of OI according to underlying pathogenic mechanisms is not novel.

Despite advances in hookworm control and prevention campaigns, the prevalence remains high in sub-Saharan Africa. Iron deficiency anaemia is a major complication in those with prolonged infection, a high hookworm burden, and undernutrition, though most infected people are asymptomatic. While infected patients are commonly diagnosed by the presence of ova or cysts in the stool, gastrointestinal (GI) endoscopy is required for those with negative stool tests and chronic iron deficiency anaemia. A 48-year-old female with symptoms of anaemia for nearly two years presented to Mbarara Regional Referral Hospital with worsening palpitations, easy fatigability, and dizziness over a period of one month. She was given blood transfusions on two occasions. She lives near the lake where she also gets water for drinking and domestic use. We advise GI endoscopy for all patients with chronic iron deficiency anaemia of unexplained aetiology on standard non-invasive testing. Hookworm’s mass empirical treatment policy in endemic areas should be further emphasised.

Abstract Right-sided colon cancer (RCC) and left-sided colon cancer (LCC) differ in features and outcomes because of variations in embryology, epidemiology, pathology, and prognosis. This study sought to identify significant factors impacting patient survival through Bayesian modelling. Data was retrospectively analysed from a colorectal neoplasia database. Data on demographics, perioperative risks, treatment, mortality, and survival was analysed from patients who underwent colon cancer surgery from January 2010 to December 2021. This study involved 2475 patients, with 58.7% having RCC and 41.3% having LCC. RCC patients had a notably higher mortality rate, and their overall survival (OS) rates were slightly lower than those with LCC (P

Abstract Chronic imbalance is a frequent and limiting symptom of patients with chronic unilateral and bilateral vestibulopathy. A full-body kinematic analysis of the movement of patients with vestibulopathy would provide a better understanding of the impact of the pathology on dynamic tasks such as walking. Therefore, this study aimed to investigate the global body movement during walking, its variability (assessed with the GaitSD), and the strategies to stabilise the head (assessed with the head Anchoring Index). The full-body motion capture data of 10 patients with bilateral vestibulopathy (BV), 10 patients with unilateral vestibulopathy (UV), and 10 healthy subjects (HS) walking at several speeds (slow, comfortable, and fast) were analysed in this prospective cohort study. We observed only a few significant differences between groups in parts of the gait cycle (shoulder abduction–adduction, pelvis rotation, and hip flexion–extension) during the analysis of kinematic curves. Only BV patients had significantly higher gait variability (GaitSD) for all three walking speeds. Head stabilisation strategies depended on the plan of motion and walking speed condition, but BV and UV patients tended to stabilise their head in relation to the trunk and HS tended to stabilise their head in space. These results suggest that GaitSD could be a relevant biomarker of chronic instability in BV and that the head Anchoring Index tends to confirm clinical observations of abnormal head-trunk dynamics in patients with vestibulopathy while walking.

Abstract Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of retinal ganglion cells, leading to irreversible blindness worldwide. Therefore, timely and accurate diagnosis of glaucoma is crucial, enabling early intervention and facilitating effective disease management to mitigate further vision deterioration. The advent of optical coherence tomography (OCT) has marked a transformative era in ophthalmology, offering detailed visualization of the macula and optic nerve head (ONH) regions. In recent years, both 2D and 3D convolutional neural network (CNN) algorithms have been applied to OCT image analysis. While 2D CNNs rely on post-prediction aggregation of all B-scans within OCT volumes, 3D CNNs allow for direct glaucoma prediction from the OCT data. However, in the absence of extensively pre-trained 3D models, the comparative efficacy of 2D and 3D-CNN algorithms in detecting glaucoma from volumetric OCT images remains unclear. Therefore, this study explores the efficacy of glaucoma detection through volumetric OCT images using select state-of-the-art (SOTA) 2D-CNN models, 3D adaptations of these 2D-CNN models with specific weight transfer techniques, and a custom 5-layer 3D-CNN-Encoder algorithm. The performance across two distinct datasets is evaluated, each focusing on the macula and the ONH, to provide a comprehensive understanding of the models’ capabilities in identifying glaucoma. Our findings demonstrate that the 2D-CNN algorithm consistently provided robust results compared to their 3D counterparts tested in this study for glaucoma detection, achieving AUC values of 0.960 and 0.943 for the macular and ONH OCT test images, respectively. Given the scarcity of pre-trained 3D models trained on extensive datasets, this comparative analysis underscores the overall utility of 2D and 3D-CNN algorithms in advancing glaucoma diagnostic systems in ophthalmology and highlights the potential of 2D algorithms for volumetric OCT image-based glaucoma detection.

Abstract Background Mucopolysaccharidosis VII (MPS VII) is an ultra-rare, autosomal recessive, debilitating, progressive lysosomal storage disease caused by reduced activity of β-glucuronidase (GUS) enzyme. Vestronidase alfa (recombinant human GUS) intravenous enzyme replacement therapy is an approved treatment for patients with MPS VII. Methods This disease monitoring program (DMP) is an ongoing, multicenter observational study collecting standardized real-world data from patients with MPS VII (N ≈ 50 planned) treated with vestronidase alfa or any other management approach. Data are monitored and recorded in compliance with Good Clinical Practice guidelines and planned interim analyses of captured data are performed annually. Here we summarize the safety and efficacy outcomes as of 17 November 2022. Results As of the data cutoff date, 35 patients were enrolled: 28 in the Treated Group and seven in the Untreated Group. Mean (SD) age at MPS VII diagnosis was 4.5 (4.0) years (range, 0.0 to 12.4 years), and mean (SD) age at DMP enrollment was 13.9 (11.1) years (range, 1.5 to 50.2 years). Ten patients (29%) had a history of nonimmune hydrops fetalis. In the 23 patients who initiated treatment prior to DMP enrollment, substantial changes in mean excretion from initial baseline to DMP enrollment were observed for the three urinary glycosaminoglycans (uGAGs): dermatan sulfate (DS), -84%; chondroitin sulfate (CS), -55%; heparan sulfate (HS), -42%. Also in this group, mean reduction from initial baseline to months 6, 12, and 24 were maintained for uGAG DS (-84%, -87%, -89%, respectively), CS (-70%, -71%, -76%, respectively), and HS (+ 3%, -32%, and − 41%, respectively). All adverse events (AEs) were consistent with the known vestronidase alfa safety profile. No patients discontinued vestronidase alfa. One patient died. Conclusions To date, the DMP has collected invaluable MPS VII disease characteristic data. The benefit-risk profile of vestronidase alfa remains unchanged and favorable for its use in the treatment of pediatric and adult patients with MPS VII. Reductions in DS and CS uGAG demonstrate effectiveness of vestronidase alfa to Month 24. Enrollment is ongoing.

Jamestown Canyon virus (JCV) is a mosquitoborne orthobunyavirus in the California serogroup that circulates throughout Canada and the United States. Most JCV exposures result in asymptomatic infection or a mild febrile illness, but JCV can also cause neurologic diseases, such as meningitis and encephalitis. We describe a case series of confirmed JCV-mediated neuroinvasive disease among persons from the provinces of British Columbia, Alberta, Quebec, and Nova Scotia, Canada, during 2011–2016. We highlight the case definitions, epidemiology, unique features and clinical manifestations, disease seasonality, and outcomes for those cases. Two of the patients (from Quebec and Nova Scotia) might have acquired JCV infections during travel to the northeastern region of the United States. This case series collectively demonstrates JCV’s wide distribution and indicates the need for increased awareness of JCV as the underlying cause of meningitis/meningoencephalitis during mosquito season.

Understanding SARS-CoV-2 infection in populations at increased risk for poor health is critical to reducing disease. We describe the epidemiology of SARS-CoV-2 infection in Kakuma Refugee Camp Complex, Kenya. We performed descriptive analyses of SARS-CoV-2 infection in the camp and surrounding community during March 16, 2020‒December 31, 2021. We identified cases in accordance with national guidelines.We estimated fatality ratios and attack rates over time using locally weighted scatterplot smoothing for refugees, host community members, and national population. Of the 18,864 SARS-CoV-2 tests performed, 1,024 were positive, collected from 664 refugees and 360 host community members. Attack rates were 325.0/100,000 population (CFR 2.9%) for refugees,150.2/100,000 population (CFR 1.11%) for community, and 628.8/100,000 population (CFR 1.83%) nationwide. During 2020–2021, refugees experienced a lower attack rate but higher CFR than the national population, underscoring the need to prioritize SARS-CoV-2 mitigation measures, including vaccination.

In Singapore, nasopharyngeal cancer (NPC) is among the top 3 cancers afflicting middle-aged males (30–49 years old).1 Unfortunately, patients with early-stage NPC are often asymptomatic, and most patients (approx. 70%) are diagnosed with advanced disease with adversely reduced survival. First-degree relatives of NPC patients have about 4 to 10 times increased risk of developing NPC,2 and strategies for reducing NPC-specific mortality among this high-risk group are feasible. Herein, a working group from the Chapter Board of Otorhinolaryngologists Singapore proposed a screening algorithm for these high-risk individuals of NPC based on existing available evidence.

The purpose of this study was to evaluate the effects of a mobile app designed to improve chronic disease self-management in patients aged 40 years and older with low health literacy and who had at least one chronic health condition, and to assess the impact of delivering information at different levels of reading difficulty. A randomized controlled trial was completed at two sites. Individuals aged 40 years and older screened for low health literacy who had at least one chronic health condition were randomly assigned to a tailored information multimedia app with text at one of three grade levels. Four primary outcomes were assessed: patient activation, chronic disease self-efficacy, health-related quality of life, and medication adherence. All groups showed overall increases in activation, self-efficacy, and health-related quality of life, but no change in medication adherence. No between-group differences were observed. The mobile app may have been effective in increasing participants’ levels of several psychosocial variables, but this interpretation can only be advanced tentatively in light of the lack of control-experimental group differences. Reading difficulty level was not significantly related to outcomes.

Abstract Background Patients with cancer often have unmet psychosocial needs. Early detection of who requires referral to a counsellor or psychiatrist may improve their care. This work used natural language processing to predict which patients will see a counsellor or psychiatrist from a patient’s initial oncology consultation document. We believe this is the first use of artificial intelligence to predict psychiatric outcomes from non-psychiatric medical documents. Methods This retrospective prognostic study used data from 47,625 patients at BC Cancer. We analyzed initial oncology consultation documents using traditional and neural language models to predict whether patients would see a counsellor or psychiatrist in the 12 months following their initial oncology consultation. Results Here, we show our best models achieved a balanced accuracy (receiver-operating-characteristic area-under-curve) of 73.1% (0.824) for predicting seeing a psychiatrist, and 71.0% (0.784) for seeing a counsellor. Different words and phrases are important for predicting each outcome. Conclusion These results suggest natural language processing can be used to predict psychosocial needs of patients with cancer from their initial oncology consultation document. Future research could extend this work to predict the psychosocial needs of medical patients in other settings.

Abstract Development and progression of malignancies are accompanied and influenced by alterations in the surrounding immune microenvironment. Understanding the cellular and molecular interactions between immune cells and cancer cells has not only provided important fundamental insights into the disease, but has also led to the development of new immunotherapies. The C-type lectin Dendritic Cell ImmunoReceptor (DCIR) is primarily expressed by myeloid cells and is an important regulator of immune homeostasis, as demonstrated in various autoimmune, infectious and inflammatory contexts. Yet, the impact of DCIR on cancer development remains largely unknown. Analysis of available transcriptomic data of colorectal cancer (CRC) patients revealed that high DCIR gene expression is associated with improved patients’ survival, immunologically "hot" tumors and high immunologic constant of rejection, thus arguing for a protective and immunoregulatory role of DCIR in CRC. In line with these correlative data, we found that deficiency of DCIR1, the murine homologue of human DCIR, leads to the development of significantly larger tumors in an orthotopic murine model of CRC. This phenotype is accompanied by an altered phenotype of tumor-associated macrophages (TAMs) and a reduction in the percentage of activated effector CD4+ and CD8+ T cells in CRC tumors of DCIR1-deficient mice. Overall, our results show that DCIR promotes antitumor immunity in CRC, making it an attractive target for the future development of immunotherapies to fight the second deadliest cancer in the world.

Abstract Leukaemia of various subtypes are driven by distinct chromosomal rearrangement or genetic abnormalities. The leukaemogenic fusion transcripts or genetic mutations serve as molecular markers for minimal residual disease (MRD) monitoring. The current study evaluated the applicability of several droplet digital PCR assays for the detection of these targets at RNA and DNA levels (atypical BCR::ABL1 e19a2, e23a2ins52, e13a2ins74, rare types of CBFB::MYH11 (G and I), PCM1::JAK2, KMT2A::ELL2, PICALM::MLLT10 fusion transcripts and CEBPA frame-shift and insertion/duplication mutations) with high sensitivity. The analytical performances were assessed by the limit of blanks, limit of detection, limit of quantification and linear regression. Our data demonstrated serial MRD monitoring for patients at molecular level could become “digitalized”, which was deemed important to guide clinicians in treatment decision for better patient care.

Abstract This study aimed to investigate whether attentional bias to threat, commonly observed in clinically anxious children, also manifests in healthy children, potentially aiding the early detection of at-risk individuals. Additionally, it sought to explore the moderating role of parent–child attachment security on the association between vulnerability factors (anxiety sensitivity, intolerance of uncertainty, perseverative cognitions) as indicators of vulnerability to anxiety, and attentional bias towards threat in healthy children. A total of 95 children aged 8 to 12 years completed the Visual Search Task to assess attentional bias. Vulnerability to anxiety was measured using a composite score derived from the Childhood Anxiety Sensitivity Index, Intolerance of Uncertainty Scale for Children, and Perseverative Thinking Questionnaire. Parent–child attachment security was assessed using the Security Scale-Child Self-Report. Analyses revealed that higher vulnerability to anxiety was associated with faster detection of anger-related stimuli compared to neutral ones, and this association was further influenced by high maternal security. These findings in healthy children suggest an interaction between specific factors related to anxiety vulnerability and the security of the mother–child relationship, leading to cognitive patterns resembling those seen in clinically anxious individuals. These results hold promise for early identification of children at risk of developing anxiety disorders.

Abstract Humans have a long history of transporting and trading plants, contributing to the evolution of domesticated plants. Theobroma cacao originated in the Neotropics from South America. However, little is known about its domestication and use in these regions. In this study, ceramic residues from a large sample of pre-Columbian cultures from South and Central America were analyzed using archaeogenomic and biochemical approaches. Here we show, for the first time, the widespread use of cacao in South America out of its native Amazonian area of origin, extending back 5000 years, likely supported by cultural interactions between the Amazon and the Pacific coast. We observed that strong genetic mixing between geographically distant cacao populations occurred as early as the middle Holocene, in South America, driven by humans, favoring the adaptation of T. cacao to new environments. This complex history of cacao domestication is the basis of today's cacao tree populations and its knowledge can help us better manage their genetic resources.

Introduction Sexual violence is a significant public health concern with severe physical, social and psychological consequences, which can be mitigated by health service utilisation. However, in Uganda and much of sub-Saharan Africa, these services are significantly underused, with 9 out of 10 survivors not seeking care due to a range of psychological, cultural, economic and logistical factors. Thus, there is a strong need for research to improve health service utilisation for survivors of sexual violence.Methods and analysis The proposed study seeks to address the underutilization of health services for female survivors of sexual violence using a discrete choice experiment (DCE). The study will be conducted in the greater Masaka region of southwestern Uganda and target adult female survivors of sexual violence. We will first undertake qualitative interviews with 56 survivors of sexual violence to identify the key attributes and levels of the DCE. In order to ensure a sufficiently powered sample, 312 women who meet inclusion criteria will be interviewed. Our primary analysis will employ a mixed (random parameters) logit model. We will also model the role of individual-specific characteristics through latent class models.Ethics and dissemination The study protocol was reviewed and approved by the following ethics review boards in Uganda and the USA: the Uganda Virus Research Institute (UVRI), the Uganda National Council for Science and Technology (HS2364ES), Washington University in St Louis and the University of Michigan. Our methods conform to established guidelines for the protection of human subjects involved in research. Our dissemination plan targets a broad audience, ranging from policymakers and government agencies to healthcare providers, academic communities and survivors themselves.

Background and objectives Vaginal digital examination and transvaginal ultrasound are routinely for clinical assessment. Many women find these procedures uncomfortable, embarrassing, and stressful. Negative experiences increase anxiety and discomfort experienced during subsequent examinations. Emotional distress and fear of pain result in women avoiding gynaecological screening and follow-up. This study uses qualitative methods to evaluate the experience of patients who have undergone both vaginal digital and transvaginal ultrasound examinations, collectively called pelvic examinations (PE) in the outpatient setting of a tertiary hospital in Singapore. Methods Qualitative semi-structured interviews were conducted on 12 participants aged 30-57 years. Interviews were audio-recorded, transcribed, audited, and analysed iteratively based on grounded theory. Emergent themes were first externally validated and finalized after rounds of deliberations amongst the investigators. This included descriptions and concepts reflecting the most important matters experienced by participants. Results Majority of participants found PE unpleasant and uncomfortable especially when providers were perceived to have poor communication and examination skills. Factors that improve their experience include a conducive environment that is, privacy, dim lights, and warm lubricant. Having adequate information before and during the procedure was important especially for first time. Conclusion Patient-centred care ensures a positive experience in relation to the themes found in this study. Gaps in HCP training on communication and procedure skills should be addressed. Efforts should be made improve the clinic environment and provide adequate information to patients.

Objective This meta-analysis aimed to estimate the national prevalence of postpartum depression (PPD) in Uganda and identify predictors in both pre-COVID-19 and post-COVID-19 eras.Design Used a systematic review and meta-analysis methodology.Data sources Reviewed papers were sourced from Medline/PubMed, PsycINFO, CINAHL/EBSCOhost, Google Scholar, ScienceDirect and African Journals Online.Eligibility criteria for selected studies The review encompassed observational studies published on PPD in Uganda from 1 January 2000 to 30 November 2023.Results 11 studies (involving 7564 participants) published from 1 January 2000 to 30 November 2023 were reviewed. The pooled prevalence of PPD in Uganda was 29% (95% CI 21% to 37%, I2=98.32%). Subgroup analysis indicated a similar prevalence before (29%, 95% CI 20% to 39%) and during (28%, 95% CI 22% to 32%) the COVID-19 period. Special groups exhibited a higher prevalence (32%, 95% CI 16% to 47%) than general postpartum women (28%, 95% CI 19% to 37%). Factors associated with PPD included poor social support (OR 1.19, 95% CI 1.17 to 1.22, I2=96.8%), maternal illness (OR 1.22, 95% CI 1.19 to 1.26, I2=96.9%), poor socioeconomic status (OR 1.43, 95% CI 1.40 to 1.46, I2=99.5%) and undergoing caesarean section (OR 1.15, 95% CI 1.12 to 1.17, I2=80.6%). Surprisingly, there was a marginal decrease in PPD during the COVID-19 period. Subgroup analysis highlighted a higher prevalence among mothers with HIV.Conclusion This study underscores the significant prevalence of PPD in Uganda, with sociodemographic factors increasing risk. Despite a slight decrease during the COVID-19 period, the importance of prioritising maternal mental health is emphasised, considering sociodemographic factors and pandemic challenges, to improve maternal and child health outcomes and overall well-being.

Immune checkpoint inhibitors have produced encouraging results in cancer patients. However, the majority of ß-catenin-mutated tumors have been described as lacking immune infiltrates and resistant to immunotherapy. The mechanisms by which oncogenic ß-catenin affects immune surveillance remain unclear. Herein, we highlighted the involvement of ß-catenin in the regulation of the exosomal pathway and, by extension, in immune/cancer cell communication in hepatocellular carcinoma (HCC). We showed that mutated ß-catenin represses expression of SDC4 and RAB27A, two main actors in exosome biogenesis, in both liver cancer cell lines and HCC patient samples. Using nanoparticle tracking analysis and live-cell imaging, we further demonstrated that activated ß-catenin represses exosome release. Then, we demonstrated in 3D spheroid models that activation of β-catenin promotes a decrease in immune cell infiltration through a defect in exosome secretion. Taken together, our results provide the first evidence that oncogenic ß-catenin plays a key role in exosome biogenesis. Our study gives new insight into the impact of ß-catenin mutations on tumor microenvironment remodeling, which could lead to the development of new strategies to enhance immunotherapeutic response.