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Sri Lankan maternal ancestry reveals early migrations from Africa along the Indian Ocean

The African origin of anatomically modern humans is widely accepted. However, there is ongoing debate about the route they took and whether the early expansion into Oceania was through South Asia. Despite Sri Lanka being an island South Asian nation with the earliest known human fossils in South Asia and strategically located along a putative ‘southern route’, a comprehensive examination of its temporal settlement using high-resolution complete mitochondrial DNA analysis has never been conducted. To address this gap, 139 mitogenomes were sequenced in this study from the Sinhalese, Sri Lankan Tamil, and Vedda populations in Sri Lanka and integrated with 247 previously published global mitogenomes, resulting in the largest mitogenome dataset analyzed thus far. Phylogeographic analyses revealed four distinct settlement phases in Sri Lanka, with the earliest phase overlapping with the initial entry of modern humans into South Asia, thus supporting the southern dispersal route. The introduction of West Eurasian lineages into Sri Lanka was mediated via India. A significant decline in effective population size was observed across all studied populations, reflecting the demographic history of the island. Findings from the present study provide valuable insights into the long-standing debate on the southern and inland migration routes out of Africa and subsequent migrations from across Eurasia, thus highlighting the complex settlement patterns of Sri Lanka and broader Asia.

An ultra-sensitive multi-channel MEG system for the non-invasive single-trial detection of cortical population spikes

Abstract We describe the design and performance of a highly sensitive 12-channel magnetoencephalography (MEG) system to be operated in a magnetically shielded room. The aim of the recording system is to measure spatially resolved high frequency (450–850 Hz) somatosensory evoked responses (hfSERs), as elicited by electrostimulation of the median nerve, at a single-trial level. The system uses current sensing superconducting quantum interference devices (SQUIDs) operated in an ultra-low noise dewar. The sensor head consists of 9 multi-turn, hexagonal signal magnetometers, 2 single-turn, circular reference magnetometers and one circular axial gradiometer. Given limitations in the dewar’s size, a balance was found between minimising the magnetic field noise and the spatial distribution of the individual MEG channels. Using SQUIDs currently made at the Physikalisch-Technische Bundesanstalt, the minimum white noise performance is expected to be $$\mathrm {\approx 380~aT/Hz^{1/2}}$$ , with the achieved noise performance in the frequency band of interest of $$\mathrm {\approx 500~aT/Hz^{1/2}}$$ . Additionally, simulations of the neuronal magnetic field of the hfSERs predicted a peak-to-peak strength of 35 fT for our system, in accordance with previous recordings. We also present measures to increase the dynamic range of our MEG device and show in vivo measurement results which demonstrate spatially resolved detection of the hfSERs with amplitudes of $$\mathrm {\approx 50~fT_{pp}}$$ at the single-trial level.

Detecting changepoints in dynamical systems: Modeling time-varying transmission of seasonal influenza

Seasonal influenza epidemics exhibit complex transmission dynamics influenced by time-varying extrinsic factors such as social behavior and seasonal effects. Estimating changes in transmission rates is critical to enable accurate forecasting of the epidemic curve. This study presents a framework for detecting changepoints in the transmission parameter ( β t ), applied as a piecewise constant function within a deterministic compartmental model. Using hospitalized case data from four recent influenza A seasons in Ireland (2019/2020 and 2022–2025), we applied iterated filtering and kernel density estimation to identify season-specific and cross-seasonal changepoint structures. The algorithm integrates stochastic search, local perturbation, and resampling to infer the most plausible changepoint configurations. Results reveal consistent changepoint patterns across seasons, particularly during periods of increased social mixing, such as the December holiday period. A universal changepoint model was also developed, enabling medium-term forecasting and scenario planning. This approach offers a robust method for capturing abrupt shifts in transmission and may be applicable to other dynamical systems.

Correction: Pneumococcal vaccination at 65 years and vaccination coverage in at-risk adults: A retrospective population-based study in France

Retraction Note: Investigating the use of green synthesized copper oxide nanoparticles from Melia azedarach to combat cadmium stress in wheat

Genome-wide CG hypomethylation of the <i>Arabidopsis</i> ecotype Cvi linked to structural variation and RNAi at the <i>VIM4</i> – <i>VIM2</i> locus

The Cape Verde Island (Cvi)-0 ecotype, a relict lineage of Arabidopsis thaliana , is characterized by exceptionally low CG methylation levels genome-wide. Numerous population-level and molecular studies have highlighted links between this epigenomic feature, phenotypic traits and environmental factors; however, the molecular mechanism underlying Cvi-0’s distinctive methylation profile remains unknown. Using multiomics comparisons between Cvi-0 and Col-0, we identified Cvi-specific small-RNAs derived from an inverted repeat (IR) formed by two inverted-orientation DNA methylation pathway genes, VARIANT IN METHYLATION 2 and 4 ( VIM2 and VIM4 ). An intergenic 2.8-kb deletion brings these genes closer in Cvi-0, enabling read-through transcription and formation of chimeric transcripts. Targeted 5′ RACE and WGBS showed that the resulting siRNAs mediate both posttranscriptional gene silencing and local DNA hypermethylation in cis and trans, reducing the expression of the VIM1 gene, which is required for methyltransferase activity in A.thaliana . Comparative analysis across A. thaliana ecotypes and related species revealed substantial structural polymorphism at the VIM4 – VIM2 IR locus, likely shaped by nonallelic homologous recombination—facilitated by local palindromic structures, intronic repeats, and transposable element activity. Notably, the Cvi-0 VIM4 – VIM2 IR configuration was unique, suggesting it is a rare, lineage-specific natural variant. Taken together, natural variation at the VIM4 – VIM2 palindrome locus, uniquely found in Cvi-0, appears to be the causal variant driving siRNA biogenesis and down-regulation of the methyltransferase pathway. This distinctive regulatory mechanism is likely to have contributed to long-term reduction of CG methylation in Cvi-0, potentially maintained over millennia due to its geographical isolation from the mainland.

Correction: AI-powered detection of cyberbullying in short-form video content: A hybrid deep learning framework

Association between dietary inflammatory potential and chronic kidney disease among patients at Korle-Bu Teaching Hospital, Ghana

Evolutionary branching and consistency in group cooperation

Understanding the origins of volunteerism and free-riding is crucial in collective action situations where a sufficient number of cooperators is necessary to achieve shared benefits, such as in vaccination campaigns and social change movements. Despite the importance of attaining behavioral consistency for successful collective action, the theoretical mechanisms behind this process remain largely elusive. Here, we address this issue by studying the evolutionary dynamics of individual cooperativity levels in multiround threshold public goods games. By using adaptive dynamics, we explore how individual behavior responses are shaped by incentives, with and without reward or punishment. We demonstrate that rewarding consistent cooperators can lead to the emergence of two distinct populations: volunteers who consistently cooperate and free-riders who consistently defect. In contrast, punishing consistent defectors does not lead to similar evolutionary branching. Our results help offer insights into designing effective interventions that promote collective action and address collective risk dilemmas ranging from climate mitigation to pandemic control.

Enhancing products performance evaluation through hybrid DistilRoBERTa and BiGRU models

Online reviews have a direct bearing on what prospective customers will choose to buy. Consumers need help to make effective use of online reviews for purchasing decisions. The current sentiment analysis methods often overlook the complexity and usability of products in reviews which are critical for potential buyers. The existing approaches solely rely on sentiment polarity but this approach offers a comprehensive way to analyze product’ reviews by integrating appraisal theory with hybrid deep learning methods. This research study aims to explore product complexity in customer reviews by utilizing transformer and recurrent neural network-based models. Amazon product reviews dataset is manually annotated according to perceived complexity using attitudinal categories of appraisal theory, i.e., appreciation and judgment and then cross-validated through shapley additive explanations method of eXplainable AI. Appreciation has to do with how much a product is user-friendly or has a learning curve to operate. Judgment deals with evaluation of products on the basis of effectiveness and appropriateness. The proposed model uses a hybrid approach by combining DistilRoBERTa, a pre-trained transformer model, and a bi-directional gated recurrent unit, a recurrent neural network-based model, to learn both contextual and sequential dependencies in product reviews. The proposed approach makes use of fine-tuned DistilRoBERTa embeddings for extracting features, and this model is improved further using a bi-directional gated recurrent unit layer, which takes into account the context of the past and the future. A 5-fold stratified cross-validation method is used to address imbalance learning, with class weighting applied to further balance the impact of sentiment classes in training. The proposed model has achieved a mean fold accuracy of 96.13%,which is higher than that of existing state-of-the-art approaches such as Random Forest (89.93%) [11], DistilBERT with advanced embeddings (92%) [25], XLNet (89.62%) [28], and GPT-based sentiment models (94.5%) [30]. By utilizing Shapley Additive Explanations (SHAP) for explainability, this model provides transparency in understanding emotional tendencies, functional effectiveness, and overall user perceptions, offering insights that traditional models lack. This framework provides a scalable, automated solution for Amazon products’ performance evaluation and provides insights into emotional tendencies, functional effectiveness and overall perceptions from the users. It will help in optimizing product development strategies using advanced natural language processing techniques with explainability by setting a new standard for understanding products’product feedback.

Metaheuristic machine learning based factor of safety prediction of MSE walls

Dynamic creation of topological solitons via nematic vortex lines

Topologically protected solitonic structures have garnered significant attention in condensed matter physics due to their unique stability and potential applications in next-generation technologies such as high-density data storage and spintronics. Vortex lines, another class of topological defects, are ubiquitous in nematic liquid crystals (LCs) and provide a versatile platform for studying topological phase transitions. A key challenge in the field is understanding how to transition between these fundamentally distinct topological objects. By combining experimental observations and numerical simulations, we demonstrate that vortex lines can transition into soliton strings through interactions with wedge or twist vortices of topological charge ± 1 / 2 . By anchored patterns on surfaces, we are able to control topological structures of soliton strings. Using laser tweezers, we manipulate vortex lines to dynamically create and annihilate soliton strings, revealing the compatibility between vortices and solitonic structures. The soliton ring with continuously varying topological profiles can be created by using two adjacent vortex loops with Möbius strip topology. We also create complex topological configurations, such as arbitrary shaped hybrid structures composed of intertwined vortex lines and soliton strings, by leveraging out-of-equilibrium transitions. These findings pave the way for designing smart materials with tailored topological properties.

Potential reasons for the decline of new HIV cases among people who inject drugs (PWID) in Kyrgyzstan

There has been a declining trend in the number of reported cases of human immunodeficiency virus (HIV) among people who inject drugs (PWID) in Kyrgyzstan. The local HIV and public health community has suggested that this decline may be driven by interventions targeting HIV transmission among PWID, changes in drug use patterns, or possible underreporting of new HIV cases. The present study aims to examine these hypotheses using a deterministic compartmental model. Three intervention scenarios were evaluated to assess their impact on PWID population trends, HIV incidence, and case reporting. Scenario I (baseline) included needle and syringe exchange programmes, opioid substitution therapy, behavioural interventions, and pre-exposure prophylaxis, collectively referred to as preventive interventions, alongside antiretroviral therapy (ART). Scenario II excluded preventive interventions while maintaining ART. Scenario III excluded both preventive interventions and ART. The model results suggest that the decline in PWID may be a key factor contributing to the reduction of the HIV epidemic in this group. While preventive interventions and ART are unlikely to have been the primary drivers of HIV incidence trends, they appear to have played a meaningful role in reducing the overall HIV burden. Furthermore, the model indicates that observed trends in reported HIV incidence are likely to reflect changes in testing behaviour rather than actual fluctuations in the number of new infections.

Quercetin-loaded cellulose nanofibers improve memory, learning, and attenuate endoplasmic reticulum stress in a rat model of Alzheimer’s disease

Systematic determination of disulfide bond reduction potentials reveals a nonequilibrium redox hierarchy in cyanobacteria

Disulfide bonds act as reversible switches that regulate cellular function in nearly all organisms. Their behavior is set by the midpoint potential ( E m ), yet E m is known for only a small number of sites, mostly in purified proteins studied away from their natural partners. We developed a mass-spectrometry workflow that measures E m directly from native cell lysates. By equilibrating proteins of the cyanobacterium Synechocystis sp. PCC 6803 in defined redox buffers and reading out the oxidation state of individual cysteines, we obtained 368 E m values across the proteome and validated them against purified proteins. A key example is the regulatory protein CP12: its E m in isolation differs strongly from the value measured in lysate and converges only when its physiological partner, thioredoxin, is included, showing that our approach captures the effective potentials that operate inside cells. Combining E m with absolute measurements of cysteine redox state in light and darkness, we mapped intracellular redox “operating points” for Calvin–Benson–Bassham (CBB) cycle enzymes. Phosphoribulokinase sits near thioredoxin, whereas fructose 1,6-bisphosphatase/sedoheptulose 1,7-bisphosphatase (F/SBPase) and CP12 are maintained at more oxidized, nonequilibrium states. These results reveal a hierarchical redox control network in photosynthetic metabolism and provide a general strategy for measuring context-dependent redox switches in living systems.

Use of virtual reality medical hypnosis for anxiolytic purposes during frozen embryo transfer: A prospective pilot study

Objective To assess the feasibility of using a virtual reality medical hypnosis (VRH) device for anxiolytic purposes during frozen embryo transfer (FET) and to observe its effect on subsequent pregnancy rate. Design This is a prospective, single-center study conducted in a French public reproductive medicine ward between December 2023 and 1 May 2024. Subjects Women aged 18–45 years who undergoing IVF at the center. The present study included 50 women who had a scheduled FET. Interventions Study participants were using the VRH device during the FET. Main outcomes measures Feasibility was defined as optimal and incident-free device use. Anxiety levels were measured pre- and post-procedure using the State-Trait Anxiety Inventory (STAI-Y1). Women and caregiver satisfaction were assessed using Likert scales, while acceptability of the procedure was assessed by recording adverse events. HCG test was conducted afterward and compared with a concurrent non-exposed cohort from the same unit and inclusion period using causal inference to analyze pregnancy rates. Results 50 women were included from the active patient file undergoing FET at the center. The feasibility of using the VRH device was assessed at 96%, with 100% acceptability of the procedure. Women satisfaction was 98%, and caregiver satisfaction reached 100%, with a favorable device’s use opinion in routine practice. A significant reduction in anxiety was observed, with a mean anxiety score of 28.8/80 after the procedure compared to 39.3/80 before (p &lt; 0.001). Regarding pregnancy outcomes, 25 women had a positive HCG test after the procedure, including 20 with HCG &gt; 100 IU/L, resulting in a pregnancy rate of 40%. Although a positive trend was observed in the comparison with the concurrent non-exposed cohort, the difference was not statistically significant (OR 1.18, 95% CI 0.65–2.14; p = 0.583). Conclusion The use of a VRH device during FET is feasible and safe, suggesting a promising anxiolytic effect and a useful non-medical tool for optimizing care pathways in assisted reproduction. Further larger and controlled studies are warranted to confirm these encouraging findings and to more thoroughly assess the impact on pregnancy outcomes.

Epstein–Barr virus-specific T-cells in pediatric liver transplant recipients

The Greenland shark genome: Insights into lifespan extremes and population dynamics

The Greenland shark ( Somniosus microcephalus ) is known for its slow metabolism and deep-sea habitat. It is thought to be the longest-lived vertebrate on Earth, with an estimated lifespan of 392 ± 120 y. Despite its remarkable longevity and unusual lifestyle, no genomic studies are yet available for this species. Here, we report a chromosome-level assembly of the Greenland shark genome, which is 5.9 Gb in size with an N50 length of 233 Mb and a completeness score of 96.7%. Our analyses of gene family expansion and positive selection revealed classical longevity-related mechanisms, including immune enhancement, cancer resistance, and DNA repair, as well as additional features potentially associated with extended lifespan limits. Unique amino acid substitutions in the globular domain of linker histone H1.0 are predicted to enhance chromatin stability, and the species’ distinctive gene repertoire provides a framework for generating hypotheses potentially linking ferroptosis to exceptional longevity. We also elucidate the dynamics of the effective population size ( N e ) of the Greenland shark and its close relative, the Pacific sleeper shark ( Somniosus pacificus ). These genomic analyses offer insights into the molecular basis of the exceptional longevity of the Greenland shark and highlight potential genetic mechanisms that could inform future research into longevity.

Intraspecific drought tolerance in Ugandan Coffea canephora for accelerated breeding selection

Robusta coffee (Coffea canephora ) accounts for about 80% of Uganda’s coffee production and supports over 2.2 million livelihoods. Yet recurrent droughts and erratic rainfall, exacerbated by climate change, pose severe threat to its productivity. Despite this threat, Ugandan breeding programs lack drought-tolerant varieties, largely because selection has not incorporated precise physiological traits linked to drought adaptation. Here, we evaluated 165 diverse Ugandan C. canephora genotypes, including local wild accessions, commercial lines, and breeders’ selections, under controlled screenhouse drought assay. Morphophysiological traits were collected before, during, and after drought stress. Using linear mixed-effects models, K-means clustering, and the Drought Factor Index, variation in drought tolerance was characterized across genotypes differing in biomass. Drought reduced water relations, gas exchange (gs and E), and PSII efficiency (Fv/Fm, Fo/Fv, ETR, Y(II), and PI) across all biomass groups. Nevertheless, 24 genotypes maintained higher DFI values, stable PSII function (Fv/Fm, PI, Fv/F₀), and less negative pre‑dawn water potential under severe stress. Among all traits, photosynthetic performance index (PI) and Fv/F₀ emerged as the most robust and biologically interpretable predictors of drought tolerance. These fluorescence‑based markers, together with the identified drought‑tolerant genotypes, provide a powerful foundation for accelerating climate‑smart coffee breeding in Uganda.

Combined jump rope and elastic resistance band training improves agility, body balance and neuromuscular performance in young male basketball players