Browse Articles

Tracing early life stress in human molar morphology: Associations between linear enamel hypoplasia and maxillary first molar form

Permanent tooth structures can respond to environmental disruptions even after the initiation of hard tissue deposition at the cusp tips, affecting dental morphology. In bioarcheological studies, linear enamel hypoplasia (LEH) provides evidence of both the presence and timing of developmental stressors that can occur during first molar odontogenesis. Yet, previous studies used LEH from the entirety of the anterior tooth surface to relate disruptions to changes in permanent tooth morphology, which could conflate causality by misrepresenting the timing of events. This study assessed associations between LEH formed during maxillary permanent first molar development and dental characteristics of these molars in contemporary humans with known health and nutritional histories from Tezonteopan, Mexico. LEH were observed in the field, and dental characteristics (crown size, principal cusp spacing, expression of cusp 5 and Carabelli trait) were observed on maxillary dental casts taken of the same adolescent study participants (n = 54). Statistical analyses included multivariate- and generalized linear models, and Principal Component Analyses. Slightly larger crown sizes, decreased buccolingual principal cusp spacing, and a slight decrease in cusp 5 expression were associated with the presence of LEH. The decrease in cusp spacing and decrease in cusp 5 expression follow expectations of the Patterning Cascade Model. Our results differ in some ways from those of previous studies possibly due to our focus on LEH defects forming during molar developmental periods. Our findings support the growing body of studies highlighting the unpredictability of molar morphology in the presence of developmental disruptions.

Distinct NK cell dynamics in SARIFA positive colorectal cancer patients indicate persistent patient-intrinsic immune signatures after tumor resection

Abstract The recently introduced H&E-based biomarker SARIFA (Stroma AReactive Invasion Front Areas) is defined by a direct tumor-adipocyte interaction at the invasion front and is highly predictive for worse outcome in colorectal cancer (CRC). Further analysis revealed an altered lipid metabolism and an immune dysregulation in SARIFA-positive cancers, specifically reduced natural killer (NK) cells. In this study, we investigated whether these lower NK cells in SARIFA-positive patients persist after tumor resection, indicating a patient-intrinsic factor that might contribute to the development of SARIFA-positive tumors. Flow cytometric analysis of NK cells of CRC patients was performed before, 7–10 days and 6 months after resection of the tumors. Using multiplex ELISA (enzyme-linked immunosorbent assay), various inflammatory mediators were examined. 28 SARIFA-negative, 12 SARIFA-positive patients and 27 matched healthy individuals were included. Preoperative NK cell values were previously published and showed significantly lower values for SARIFA-positive patients. Postoperatively NK cells and all their subsets declined in SARIFA-negative patients. Regarding the 6 months follow-up measurements, SARIFA-negative patients showed increasing values of NK cells reaching the initial level, while lower NK-cell levels persisted in SARIFA-positive patients. Multiplex ELISA of inflammatory mediators revealed a postoperative increase of IL5, IL6 and IL8 but no differences between SARIFA-positive and -negative patients. Postoperative measurements of NK cells and different subsets showed a persisting difference between SARIFA-positive and SARIFA-negative patients six months after surgery, which may indicate that patient-intrinsic immunological characteristics are associated with the development of the more aggressive SARIFA-positive tumors.

Chemically Separable Ruthenium Hydride Isomers with Distinct Hydride Transfer Properties

Abstract Transition metal hydrides are key intermediates in biological and industrial catalysis, where control over hydride donor ability (hydricity) is essential for optimizing reactivity. Herein, we report a series of isomeric ruthenium hydrides in which the ligand trans to the ruthenium hydride bond–either an N-heterocyclic carbene or pyridine–modulates the thermodynamic hydricity by up to 8 kcal mol–1. These hydrides exhibited distinct reactivity toward CO2 and various organic hydride acceptors, enabling detailed kinetic and mechanistic analysis. Stopped-flow experiments, isotopic labeling, and computational studies supported an outer-sphere hydride transfer mechanism. Linear free energy relationships (LFERs) and Marcus relationships were utilized to correlate the changes in thermodynamics and kinetics, revealing that ligands with strong trans effects and trans influence can disrupt conventional scaling relationships, which can be a powerful strategy for promoting new reactivity paradigms in hydride transfer reactions.

Dopaminergic genetic variation and response to social comparative feedback when learning a motor sequence task

Positive social comparative feedback during motor skill practice is hypothesized to enhance motor learning by triggering a dopaminergic response. Individual differences in dopamine-related genes impact dopamine neurotransmission and may influence responsiveness to motor practice conditions that target dopaminergic pathways. The purpose of this study was to examine the impact of dopamine genotype on learning of a motor sequence task under two different feedback conditions: response time only feedback or response time with positive social comparison. Fifty-two adults practiced a joystick-based motor sequence task over two consecutive days. On Day 1, participants were randomized to receive either 1) response time only feedback (i.e., “You completed the block in 80 seconds”) or 2) positive social comparative feedback (i.e., “You completed the block in 80 seconds. You were faster than others”). Motor learning was assessed by retention performance, or the change in response time from the first block of Day 1 to the first block on Day 2. Saliva samples were used to genotype for dopamine receptors DRD1, DRD2 and DRD3 and COMT. Individual genes were scored (0–2) and summed to create a polygene score (0–8). Participants were then categorized as having Low (1–4) or High (5–8) dopamine neurotransmission. A significant interaction was found between time, summary polygene group and feedback group (p = 0.048). The Low dopamine group showed greater improvements with response time only feedback versus positive social comparative feedback. The High dopamine group showed similar improvements in response time regardless of feedback type. This suggests that feedback targeting dopaminergic pathways may not be beneficial for individuals with lower dopamine neurotransmission. Our findings suggest that dopaminergic genetics may impact the efficacy of positive social comparative feedback on motor learning in low dopamine genotypes.

Sequential game dynamics produce subgame perfect equilibria in sports networks through bounded rationality

Computational analysis reveals historical trajectory of East Polynesian lunar calendars

We investigate a type of lunar calendar known as lists of the ‘nights of the moon’, found throughout East Polynesia, including Rapa Nui (Easter Island). Using computational methods, we analyzed the lexical and structural divergence of 48 calendrical lists from all major archipelagos, each containing about 30 night names. Our results, presented as a rooted phylogenetic tree, show a split into two main groups: one including lists from Rapa Nui, Mangareva, and the Marquesas; the other comprising lists from New Zealand, Hawai’i, the Cook Islands, the Austral Islands, Tahiti, and the Tuamotu. This result aligns with a recent alternative classification of East Polynesian languages into ‘Distal’ (Marquesan, Mangarevan, Rapanui) and ’Proximal’ (Māori, Hawaiian, Tahitian, etc.) subgroups. Since both language and lunar calendars are symbolic systems passed down and changed within communities—and given the geographic isolation of many archipelagos—we interpret this correspondence as evidence that the early divergence of East Polynesian lunar calendars mirrors early population movements and language splits in the region.

A cross-sectional comparison of health-related quality of life in people with subjective cognitive decline and the general population

Coverage-Dependent Lateral Interactions Shape the Electrocatalytic Activity of High-Entropy Alloys

Abstract While the rich diversity of surface sites on high-entropy alloys (HEAs) is essential for tuning electrocatalytic activity, the coverage-dependent lateral interactions that shape reactive interfaces are often neglected in theoretical studies. Here, we develop a machine learning interatomic potential (MLIP)-enabled framework to model the oxygen reduction reaction (ORR) within an Ag–Ir–Ru–Pd–Pt–Cu–Rh–Re alloy composition space. By tracking the binding strengths of O* and OH* intermediates during competitive coadsorption on crowded surfaces, this framework highlights the key role of lateral interactions, including attractive hydrogen-bond networks and electrostatic repulsion, in evaluating electrocatalytic activity. Incorporating these coverage-induced effects improves agreement with reported PtIr and AgPd composition–activity trends relative to an isolated-site baseline. We further show that increasing compositional complexity within the studied alloy space can amplify lateral repulsion under finite-coverage conditions, broadening binding strength distributions and reducing the population of optimal active sites. The competition between local electronic optimization and coverage-dependent lateral interactions gives rise to a volcano-shaped activity–entropy relationship, offering guidance for the rational design of HEA-based ORR electrocatalysts.

Drug use patterns at a Kenyan referral hospital: A cross-sectional study using WHO core indicators

Background Suboptimal medicine use practices remain a major global health challenge, particularly in low- and middle-income countries, where it contributes to increased healthcare costs, and the growing burden of antimicrobial resistance. This study aimed to evaluate drug use patterns at Thika Level 5 Hospital in Kenya using World Health Organization (WHO) core drug use indicators. Methods A facility-based cross-sectional study was conducted in the outpatient department. Data were collected from 600 prescriptions, 100 patient encounters, and facility-level assessments using standardized WHO/INRUD data collection tools. Descriptive and inferential analyses were performed using IBM SPSS Statistics (version 29), and findings were descriptively compared with WHO reference standards. Results The mean number of drugs per prescription was 3.18, which was higher than the WHO recommended range of 1.6–1.8. Generic prescribing was 45.86% while antibiotic prescribing was observed in 58.7% of encounters. Injection use was 13.0% and 76.86% of prescribed medicines were from the Essential Medicines List (EML). Patient-care indicators showed a mean consultation time of 4.26 minutes and a mean dispensing time of 122.8 seconds, which was below the WHO- recommended reference value. Only 30.0% of medicines were adequately labelled, and 44.0% of patients demonstrated complete knowledge of their medications. Significant associations were observed between dispensing time and patient knowledge (p = 0.001), as well as between labelling adequacy and patient understanding (p < 0.001). In contrast, all facility indicators met WHO standards, with full availability of essential medicines, treatment guidelines, and stock records. Conclusion Despite strong facility readiness, important gaps were identified in prescribing and patient-care practices. These findings highlight opportunities for interventions aimed at strengthening antimicrobial stewardship initiatives, promoting generic prescribing, improving dispensing practices, and enhancing patient counselling to support improved medicine use practices..

Relationship between transversus abdominis thickness and inter-recti distance across body positions and motor tasks in nulliparous women

Droplet-Enhanced Asymmetric Catalysis: Squaramide-Derived Pseudopeptide for Enantioselective Addition Reactions

Abstract Droplets formed through phase separation represent an emerging strategy to enhance enzyme-mimetic catalysis, demonstrating significant potential in catalytic science. However, due to the lack of systematic methodologies for precise engineering of chiral microenvironments within droplets, their application to asymmetric catalysis remains largely unexplored. To address this challenge, we integrate l-phenylalanine into an L-tert-leucine-derived squaramide to design the squaramide-derived pseudopeptide droplets. This catalytic system demonstrates remarkably enhanced catalytic performance in the enantioselective conjugate addition of α-nitrosulfone to acrylates and enones, as well as Michael addition of acetylacetone to β-nitroalkenes. Mechanistic investigations reveal that the increased local substrate concentration significantly enhances reactivity, while the engineered favorable chiral microenvironment boosts enantioselectivity. This study establishes a methodological framework for elucidating differentiated catalytic behaviors within the droplets, thereby advancing the design and application of droplet-based asymmetric catalytic systems.

Water-Mediated Ion Selectivity in 2D MXene Channels

Abstract At the Ångström scale, water confined between two-dimensional layers behaves fundamentally differently from bulk water; this behavior governs ion transport in natural and engineered nanofluidic systems, yet the mechanisms by which confined water mediates selective ion transport remain poorly understood. As classical descriptions of aqueous ion transport break down under extreme confinement, experimental studies often face challenges in controlling both nanoconfined structure and surface chemistry, limiting our ability to explain and predict water and ion behavior in subnanometer channels and membranes. Here, we show that 2D Ti3C2Tx MXene nanosheets with precisely controlled interlayer spacing (0.9–5.0 Å), surface terminations, and electrode potentials provide a platform to systematically tune ion transport. Combined experimental measurements, including ion permeation, spatial secondary-ion mass spectrometry, and Fourier transform infrared spectroscopy, together with molecular dynamics simulations, reveal that ultranarrow confinement reorganizes confined water, imposes ion-specific energetic penalties for dehydration, and modulates ion–MXene interactions. Li+ permeation in horizontally aligned Ti3C2Tx channels is 2 orders of magnitude faster than in conventional vertically aligned MXene membranes, while electrochemical surface charge modulation further regulates ion selectivity. These coupled effects of confinement, surface chemistry, and water-mediated energetics define a transport regime beyond classical diffusion, offering design principles for artificial ion channels and high-performance membranes for ion separation, water desalination, and sustainable water treatment technologies.

Procedural or declarative deficit in adults with developmental dyslexia? A study of Artificial grammar learning

Artificial grammar learning (AGL) has frequently been employed to investigate the procedural hypothesis of dyslexia. However, most studies did not distinguish whether performance depended upon the acquisition of grammatical rules (procedural memory), distributional knowledge (statistical learning) or reference to individual memory traces (instances). An AGL paradigm was administered to 32 young adults with dyslexia and 60 controls. During the learning phase, adults with dyslexia learned artificial grammar and then utilized procedural memory in the grammaticality judgment and recognition tasks to a similar extent as controls. An overall group difference was observed only on the grammaticality judgment task; however, the performance of both groups was similarly modulated by the grammaticality of the stimuli. Adults with dyslexia acquired and used individual memories (instances) in both grammaticality judgment and recognition tasks. However, they exhibited some difficulty in forming individual memories, as indicated by their greater tendency to mistakenly identify non-grammatical control items as previously seen during the training phase (recognition task). On untrained items, adults with dyslexia also showed an advantage with high compared to low-bigram frequency stimuli, indicating reliance on sublexical statistical cues to foster their performance. In conclusion, adults with dyslexia acquired procedural rules and showed sensitivity to the distributional properties of the stimuli, providing little support for the procedural hypothesis of dyslexia. This study highlighted both spared and compensatory mechanisms in adults with dyslexia. Previous conflicting results may depend on not having isolated which components (procedural vs declarative memory vs statistical learning) are involved in the AGL paradigm.

A hierarchical machine learning framework for detecting loss cause misclassification in insurance claims using narrative text

Formulation development of a biphasic release tablet-in-tablet system containing ketorolac tromethamine

Ketorolac tromethamine (KT) is a potent nonsteroidal anti-inflammatory drug (NSAID) used for moderate to severe pain management. Its short elimination half-life necessitates frequent dosing, which can reduce patient compliance. The objective of this study was to formulate, develop, and optimize a novel biphasic-release tablet-in-tablet (TIT) system for KT to provide immediate pain relief followed by extended drug release. A TIT system was designed, comprising an immediate-release (IR) outer layer and an extended-release (ER) core matrix. The ER core was optimized using a 3 2 full factorial design, with the amounts of HPMC K100M and HPMC K4M as independent variables. Formulations were evaluated for pre- and post-compression parameters, drug-excipient compatibility, and in vitro drug release. The drug release kinetics and mechanism were analyzed using various mathematical models. The optimal ER core formulation (F1) exhibited a drug release of 4.6% at 0.5 h and 66.1% at 12 h, closely matching the theoretical profile (similarity factor f 2  = 51). Release kinetics followed the first-order model and the Korsmeyer-Peppas model indicated an anomalous (non-Fickian) release mechanism (n = 0.831). The corresponding TIT formulation (F11) demonstrated desired physicochemical properties: hardness of 75 N, friability of 0.59%, and rapid outer layer disintegration (<50 s). The TIT provided an initial burst release (~30%) within 30 minutes, followed by sustained release exceeding 90% over 24 hours. This TIT system represents a promising alternative to conventional KT tablets for effective pain management.

An integrated reliability assessment framework for hemodialysis machines: a Syrian multi-hospital case study

Object detection in histology: A multi-dataset benchmark and test-time inference

Medical image analysis has become increasingly important for automated medical diagnosis, as well as deep learning. Specifically, object detection models may help in automatically identifying pathological structures and features. This study presents a comprehensive comparative analysis for object detection tasks in histological images of the latest models including the YOLO (You Only Look Once) architectures, from YOLOv8 to the recently introduced YOLOv12. These models were evaluated alongside alternative architectures including RT-DETR, YOLO-World, and YOLOE across five diverse histology datasets: BCNB, Nuclei, TNBC, MoNuSAC, and CryoNuSeg. The experimental analysis employed standardized training protocols with consistent hyperparameters and data augmentation strategies, evaluating the performance through multiple metrics, inference time, and computational cost. The results obtained on the five datasets indicate that YOLOv11 consistently showed a strong performance across multiple datasets, however the newly introduced attention mechanisms of YOLOv12 show good performance, despite the model having slightly lower overall performance. Specialized variants like YOLOE demonstrated promising results for specific applications, while RT-DETR showed poor performance on smaller objects, which are typical in histological images. Statistical analyses indicate that YOLOv11 indeed has the best performance but that all models have a poor performance on objects of small sizes; moreover, the most common cases of failure are background false positives and missed detections. This comprehensive evaluation provides insights for the current state of object detection architectures for clinical histopathology applications and establishes benchmarks for future avenues of research in automated medical image analysis. In addition to the multi-model benchmark, we propose Test-time Graph Similarity Propagation (TGSP), a test-time self-supervised refinement that uses ResNet50 deep features to build a k-NN similarity graph over detections and performs label propagation to re-score predicted boxes. TGSP replaces TSBP’s iterative Earth-Mover matching with adaptive per-class quantile thresholds and graph-based label propagation, eliminating K-means hyperparameters and better scalability. Our analysis on histology datasets TGSP consistently matches or improves F1 relative to both a fixed 0.5 threshold and TSBP, with the biggest gains when base-model confidence calibration is poor.

Assessment of knowledge, perceptions, and preventive practices regarding Mpox among the Congolese population living in Brazzaville

Gene-transcription factor regulatory networks implicate primary cilia in the evolution of vertebrate sex determination and expand models of epigenetic regulation

The molecular architecture underlying diverse vertebrate sex-determining systems remains elusive despite fragmentary evidence of changes in upstream regulators and downstream mediators. Here we modeled species-specific regulatory networks of urogonadal development for turtles with contrasting mechanisms [ Apalone spinifera – ZZ/ZW genotypic sex determination (GSD) , and Chrysemys picta – temperature-dependent sex determination (TSD)] using matched data from time-course sampling. We uncovered key steps in the evolutionary transition of sex determination by testing for conservation or divergence of network modular components. Specifically, we tested these alternative hypotheses: first, transcription factor (TF) hubs and their target genes are conserved between species (null H0); second, the same TF hub acquired a new set of target genes in a species, retaining or not ancestral functions (H1 and variants); third, a new TF hub took over the regulation of the former gene targets of an ancestral TF (H2); and finally, complete overhaul occured where both ancestral TF hubs and their target genes were replaced in a species (H3). Results implicate primary cilia as integrators of environmental signals underlying TSD, because known thermosensitive TSD components (e.g., calcium-redox, pSTAT3, Wnt / Rspo1 / β-catenin , Dhh ) overrepresented in our results are linked to primary cilia. TFs that evolved between species also regulate primary cilia and point to key changes in their sensory machinery that accompanied TSD-GSD transitions (e.g., calcium/ion channels or membrane transport components in Chrysemys versus structural elements and ciliogenesis in Apalone ). This novel Primary Cilia Integration hypothesis expands current models of epigenetic regulation of turtle sexual development, the evolution of plasticity versus canalization, and warrants functional validation.

Structured evidence-guided discrete diffusion for image-conditioned radiology report generation