Browse Articles

Smad7-based biologic targeting epidermis and stroma promotes healing of diabetic wounds in mice and pigs

Cracking the nut of <i>NUTM1</i> rearrangements in infant leukemia

Future of high mountain endemic species under climate change: predicting the potential scenarios for Stellaria pulvinata in the Altai Mountains

Genetic nurture in intergenerational transmission of substance use

Abstract Substance use runs in families. Beyond genetic transmission, parental genetics can indirectly influence offspring substance use through the rearing environment, known as genetic nurture. This study utilizes transmitted and non-transmitted polygenic scores to investigate genetic nurture on tobacco, alcohol, and cannabis use in up to 15,863 adults with at least one genotyped parent from Lifelines, a population-based cohort study. Genetic nurture significantly influences cigarettes per day (CPD, β  = 0.037, p FDR  = 0.020) and pack-years ( β  = 0.028, p FDR  = 0.035), accounting for 22–26% of direct genetic transmission effects. Longitudinal analysis reveals that genetic nurture on current CPD persists across adulthood, whereas direct genetic transmission effects attenuate with age. Maternal and paternal genetic nurture are similar in magnitude. Mediation analyses indicate that genetic nurture partially operates through both parents’ smoking quantity, with a stronger mediated effect through maternal smoking, particularly among daughters. These findings highlight genetic nurture as a persistent mechanism in the intergenerational transmission of smoking, operating through parental smoking behaviors.

Myelodysplastic CMML-1 mimicking ITP, unmasked by corticosteroids: evolution from clonal monocytosis

Prehospital prediction of survival after out-of-hospital cardiac arrest using point-of-care testing and vital signs: a prospective, multinational study

Deadly heat stress conditions are already occurring

Evolution of multiple myeloma from a genomic perspective

Abstract In this review, we explore the role of complex interactions between genomic evolution, environmental and genetic predispositions, and immune surveillance in disease progression from precursor conditions smoldering multiple myeloma and monoclonal gammopathy of undetermined significance to multiple myeloma (MM). MM has been described to be universally preceded by precursor states, often decades before it is even diagnosed. Genetic predisposition plays an important role in the initial transformation, and is driven by both germline variants and MM-specific loci influencing risk. The reported disparities in occurrence of precursor conditions and MM among racial groups highlights the role of predisposition and the need for broader cohort studies. Early genomic events, such as translocations and hyperdiploidy, are essential in precursor initiation. However, additional factors are usually needed to transform the precursor stages into symptomatic disease, such as positive selection of subclonal populations. This process is affected by aging and environmental factors, such as exposures to Agent Orange and agrochemicals. Therefore, integrating genomic and transcriptomic data with immune profiling or other clinical features is essential for identifying patients with high risk of progressing into MM. Here, we highlight the complexity of myelomagenesis, and underline the importance of state-of-the-art approaches for improved disease prediction.

SODNet: a scale-oriented detection network for efficient UAV-based sewage outfall detection

Abstract Accurate identification of river sewage outfalls is crucial for effective water pollution control. Unmanned Aerial Vehicles (UAVs), with their high mobility and wide coverage, have become a vital tool for this monitoring task. However, this application is hampered by the dual challenges of robust multi-scale object detection and lightweight model deployment on computationally limited platforms. To address the trade-off between accuracy and efficiency, this study proposes an efficient deep learning-based detection method, termed Scale-Oriented Detection Network (SODNet). Specifically, we propose an Efficient Context Feature Pyramid Network (ECFPN) to enhance multi-scale feature representation. Additionally, a shared decoupled head with a Multi-Scale Grouped Fusion (MSGF) module strengthens feature extraction while reducing computational costs. Furthermore, a channel pruning strategy is employed to compress the model, notably improving inference speed. Experimental results demonstrate that SODNet achieves an AP@50 of 89.9% and a precision of 91.1%, representing improvements of 1.2% and 2.7% over the baseline model, respectively. Meanwhile, parameters and GFLOPs are reduced by 77.5% and 73.6%. On a deployed edge device, SODNet achieves 40.3 FPS. These findings indicate that SODNet gains substantial computational efficiency while maintaining excellent detection performance, making it ideal for resource-constrained UAV scenarios and offering a feasible solution for intelligent environmental supervision.

Leveraging weighted embedding and Transformer architecture to improve phenotype prediction of complex traits for crops

<i>Enterococcus faecalis</i> induces MHC-II expression by the intestinal epithelium during murine graft-versus-host disease

Abstract Intestinal Enterococcus domination has been associated with an increased risk of mortality from acute graft-versus-host disease (GVHD) after allogeneic hematopoietic cell transplantation (allo-HCT), a curative-intent treatment for patients with hematologic malignancies. In this study, we investigated interactions between Enterococcus and the intestinal epithelium as a mechanism to aggravate GVHD. We observed that endogenous intestinal Enterococcus outgrowth was associated with increased GVHD mortality and major histocompatibility complex class II (MHC-II) expression by intestinal epithelial cells in the colon in an MHC-disparate mouse model of GVHD. Monocolonization of nontransplanted gnotobiotic mice with Enterococcus faecalis was sufficient to induce colonic MHC-II expression. Conversely, select species within the genus Enterococcus, as well as a consortium of 4 anaerobic commensal bacteria including Blautia producta, did not affect colonic MHC-II expression in gnotobiotic mice. In addition, E faecalis colonization induced inflammatory responses in CD4+ T cells and natural killer cells from the colonic lamina propria, the 2 main sources of interferon gamma production that drives MHC-II expression in nonprofessional antigen-presenting cells. We further explored the potential therapeutic benefit of establishing colonization resistance against E faecalis through administration of a lantibiotic-producing B producta strain after allo-HCT. Colonization of transplanted mice with a consortium of commensal bacteria containing the lantibiotic-producing B producta strain prevented intestinal Enterococcus domination after transplantation and improved GVHD survival. Our results demonstrate a potential mechanism by which Enterococcus aggravates GVHD through increased MHC-II expression in the intestinal epithelium. Targeting the Enterococcus–epithelium–MHC-II axis thus presents a therapeutic opportunity to prevent lethal GVHD.

Ecoepidemiological determinants of Borrelia infection in sigmodontine rodents from the Delta and Parana Islands ecoregion, Argentina

NEOSTI - a neuromorphic electronic-opto spatial-temporal hybrid image sensor

Mandato E, Yan Q, Ouyang J, et al. MYD88L265P augments proximal B-cell receptor signaling in large B-cell lymphomas via an Interaction with DOCK8. <i>Blood</i> . 2023;142(14):1219-1232.

A single course of antibiotics can cause lingering changes in gut microbes

Dysferlin stabilizes membrane nanodomains of cardiomyocytes after myocardial infarction

Abstract Despite advances in acute care medicine, myocardial infarction (MI) remains a predominant cause of premature death and heart failure. In the MI border zone, cardiomyocytes are exposed to high biomechanical stress that impairs the integrity of the sarcolemmal membrane. Hence, we hypothesized that the Ca 2+ -sensitive membrane repair protein dysferlin is crucial for preserving sarcolemmal nanodomains in the MI border zone, like the transverse-axial tubule (TAT) network and the intercalated disc (ICD) membrane folds, and thereby limits the post-MI loss of myocardial function. We employed left anterior descending artery ligation to induce MI in wild-type (WT) versus dysferlin-knockout (KO) mice. While immunohistology identified an upregulated dysferlin expression of 230% in cardiomyocytes of the WT MI border zone, KO mice presented larger infarct sizes and reduced left-ventricular systolic function one week post-MI. To dissect the role of dysferlin in left-ventricular remodelling post-MI, we applied data-independent acquisition mass-spectrometry (DIA-MS) analysing the spatial proteomic profiles in WT versus KO hearts. In total, DIA-MS quantitated 5,700 proteins across all small samples, thereby identifying hundreds of genotype-specific proteomic changes for the left-ventricular infarct, border and remote zones one week post-MI. Complementing with our proteomic results, confocal and super-resolution stimulated emission depletion (STED) microscopy visualized severely degraded TAT membranes and enlarged ICD membrane folds in cardiomyocytes of the MI border zone. Importantly, extensive dysferlin signals clustered in vicinity to residual TAT structures and connexin-43 plaques at the ICD, indicating a stabilizing role of dysferlin in sarcolemmal nanodomain organization. In fact, co-immunoprecipitation-based DIA-MS and complexome profiling decoding the functional cardiac interactome of dysferlin confirmed prominent dysferlin interaction partners at TAT and ICD nanodomains. In conclusion, dysferlin represents a new molecular target that protects the integrity of sarcolemmal nanodomains in cardiomyocytes of the MI border zone, thereby reducing loss of contractility post-MI.

Sustained visceral fat loss is associated with attenuated brain atrophy and improved cognitive function in late midlife

Assessing the utility of statistical downscaling for subseasonal temperature forecasts

Abstract Subseasonal temperature forecasts can guide timely action against heat risks, but their coarse resolution limits regional usefulness. We apply a subseasonal downscaling framework to benchmark 27 statistical methods, including configurations of bias correction, linear and logistic regression, and analogs, to assess how they transfer forecast skill from coarse to local resolution at the weekly scale. As a test case, retrospective forecasts from CFSv2 (Climate Forecast System version 2; ~100 km) are downscaled to ~ 5 km for initializations issued one to four weeks before each target week of the Paris 2024 Olympics. Skill is assessed with the Brier Skill Score at the 10th and 90th percentiles for extremes. We also test whether incorporating atmospheric patterns adds value to downscaling. Methods are implemented with both daily and weekly data to examine the role of temporal resolution. Results show that, although most methods successfully transfer CFSv2 skill to higher resolution, method choice remains critical, as some degrade skill while others enhance it. Methods incorporating atmospheric patterns show promise at longer lead times when the relevant pattern, climatologically a key driver of heat in the target week, is well predicted. At the subseasonal scale, downscaling with weekly predictors outperforms that based on daily predictors.

Lactylation at lysine 145 fosters KAT8-TIP60 complex formation to promote p53 acetylation at lysine 120 and its pro-apoptotic function

Optimizing efficiency and sustainability: ANN-controlled bi-directional EV battery charger with solar PV integration

Abstract This study presents the design and performance evaluation of a bidirectional electric vehicle charging system integrating solar photovoltaic energy with an Artificial Neural Network based control strategy. The proposed architecture employs a modified Single-Ended Primary Inductor Converter capable of supporting both Grid-to-Vehicle and Vehicle-to-Home operating modes while maintaining stable bidirectional power flow between the grid, photovoltaic source, and EV battery. The ANN controller dynamically regulates the duty cycle of the MOSFET switches using battery current feedback and reference current signals, enabling adaptive control under varying solar irradiance and grid conditions. Simulation results indicate that the proposed system achieves charging efficiencies above 90% while maintaining stable operation for both 72 V and 240 V EV battery configurations. Compared with conventional proportional–integral control approaches, the ANN controller demonstrates faster transient response and improved current regulation during dynamic operating conditions. The integration of solar photovoltaic energy further reduces reliance on grid power and enhances renewable energy utilization in EV charging infrastructure. These results indicate that the proposed ANN-controlled bidirectional charging system provides an efficient and flexible solution for renewable-integrated EV charging applications.