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The identification of growth-promoting lncRNAs in oral cavity squamous cell carcinoma.

Oral Cavity Squamous Cell Carcinoma (OCSCC) is an aggressive tumor that develops within the mouth of patients. Tumor-suppressor gene loss and genomic arrangements fuel tumorigenesis and transcriptional reprogramming. Understanding how these alterations contribute to OCSCC growth and cell survival may identify new therapeutic vulnerabilities or biomarkers. We profiled the role of long non-coding RNAs (lncRNAs) in the growth of three OCSCC cell lines using a CRISPRi-screen and identified 19 lncRNAs that contribute to OCSCC proliferation. By comparing these lncRNAs to other screens, we find that these lncRNAs are uniquely required in OCSCC and not other malignancies. We show that these lncRNAs are abundantly expressed in OCSCC cells and tumors. Independent testing of candidate lncRNAs confirms their role in supporting OCSCC growth. Our results show that a novel subset of lncRNAs are required for the growth of OCSCC cancer cells and that these lncRNAs are cell lineage specific.

CRISPRi

Cooperative anaerobic catabolism of chlorinated organic compounds: implications for sustainable bioremediation.

Biodegradation research historically followed a reductionist approach focused on axenic (pure) cultures capable of catabolizing the specific contaminant(s) of interest. While this approach has substantially advanced our understanding of the microbiology, physiology, biochemistry, and genetics of contaminant degradation under laboratory conditions, it does not capture the complexity of natural and engineered environments. During in situ bioremediation, microbiomes are exposed to mixtures of contaminants, and microbial interactions profoundly influence contaminant transformation and fate. In anoxic environments, degradation of chlorinated compounds is often sustained by metabolic cooperation among taxonomically and physiologically distinct microorganisms. Through the exchange of metabolites such as hydrogen, formate, acetate, and other nutrients, microbial populations establish interdependent networks that overcome thermodynamic and physiological constraints, enabling self-sustaining systems of contaminant transformations that would be inefficient or impossible with individual organisms. We highlight examples of microbial interactions that underpin anaerobic catabolism of chlorinated contaminants, including systems resulting in self-sustained anaerobic bioremediation.

Biodegradation, Environmental

The landscape of pruning for large language models: A systematic review and unified taxonomy.

Confronting the inherent tension between the exceptional capabilities and the immense computational costs of Large Language Models (LLMs), pruning has become a crucial technique for achieving efficient deployment. However, a systematic analytical framework dedicated specifically to LLM pruning remains absent. In this paper, we aim to bridge this gap. We first elucidate the theoretical foundations that underpin the effectiveness of pruning, namely overparameterization and redundancy, and then propose a multidimensional taxonomy that organizes existing approaches along the axes of granularity, timing, and criteria. Building upon this unified perspective, we further analyze performance recovery mechanisms and the broader evaluation ecosystem, while also exploring forward-looking challenges such as interpretability, automation, and hardware-algorithm co-design. Through this comprehensive synthesis, we seek to provide an integrated and coherent analytical lens for advancing both research and practice in LLM pruning.

Large Language Models

Quo vadis, BGA? A collaborative EDNAP exercise on the challenges and progress in forensic biogeographical ancestry inference.

There is a broad consensus that forensic tests for the prediction of externally visible characteristics (EVC) and analysis of biogeographic ancestry (BGA) of an individual are technically reliable. However, interpretation of the results and population-specific genotype distribution patterns remains challenging. EVC and BGA analyses provide valuable information for population genetics studies and as investigative leads for criminal cases, as well as for historical and contemporary identification tests. However, inaccurate or incorrect predictions, for example, from subjective bias in the interpretations made, have the potential to misdirect police investigations. The legal situation regarding EVC and BGA testing varies by country: ranging from countries where it is explicitly prohibited, to those without specific regulations on biogeographic ancestry prediction, and others that have already enacted laws governing its use. The reluctance to utilize these analyses is not only due to legal restrictions and data protection concerns, but also to initial limited sets of sufficiently comprehensive forensic DNA assays. Forensic BGA marker panels typically contain up to ∼300 SNPs. This relatively small number of genetic markers, along with limited reference population data, complicates the interpretation of results from donors of unknown origin. This paper presents the results of a collaborative EDNAP study, which, for the first time, evaluated the approach to reporting EVC and BGA data between international laboratories. For the study, DNA from nine individuals with self-reported ancestry was collected and analysed using various forensic panels differing in the number and composition of ancestry-informative markers genotyped, comprising: the Precision ID mtDNA Whole Genome Panel, the VISAGE Basic Tool and the VISAGE Enhanced Tool for Appearance and Ancestry Prediction, and the Ion AmpliSeq™ PhenoTrivium Panel. To ensure full data protection, all SNP genotypes and uniparental marker haplotypes obtained were not shared with third parties. Instead, the genetic data were analysed using a range of commonly used population analysis software packages. These analysis outcomes were then distributed to twelve European forensic laboratories (both academic and law enforcement institutions), who were asked to prepare reports based on their interpretation of the phenotypes and ancestry they inferred from the analysis data. A questionnaire sent alongside the genetic information, aimed to evaluate which difficulties were encountered by the participants in processing the BGA analysis data they were given.

Humans

Rare clinical complications following scorpion envenomation worldwide: A systematic review.

Scorpion envenomation is an important public health problem in many tropical and subtropical regions and may result in rare but life-threatening grade III complications involving multiple organ systems. This systematic review synthesizes published articles from 2000 to 2025 that describe uncommon, severe clinical manifestations following scorpion stings. A total of 71 rare clinical complications were identified, encompassing cardiovascular, neurological, respiratory, renal, hematological, ocular, dermatological, and other systemic manifestations. Cardiovascular complications were the most frequently reported, whereas neurological complications exhibited the greatest clinical diversity. Mesobuthus tamulus and Hemiscorpius lepturus were most commonly associated with severe complications, and children younger than 10 years appeared to be at increased risk of serious neurological involvement. These findings highlight the remarkable clinical heterogeneity of grade III scorpion envenomation and emphasize the importance of early recognition, species-specific clinical awareness, and timely management to reduce severe outcomes in endemic regions.

Humans

Mapping antibody sequences and effector functions across spatial niches.

Antibodies are fundamental to human health but can also drive pathology. Each antibody has a molecular specificity, encoded by their clonally heritable B cell receptor (BCR). Recent advances in spatial transcriptomics coupled with repertoire sequencing have enabled capturing antibody-secreting cells (ASCs) and their clonal BCR within their tissue microenvironment. However, our understanding of antibody production niches remains limited. Furthermore, where antibodies are produced can be distinct from where antibodies exert their effector function. Here, we propose a conceptual spatial framework to distinguish between 'antibody production niches', defined by the ASC, BCR, and niche composition, versus 'antibody functional niches', composed of the antibody, antigen, and effector landscape. We then examine the possibilities and challenges to map and link antibody-encoding sequences and antibody effector functions using current and emerging technologies. Combined, we argue that integrating spatial sequence data with the antibody functional context is essential to decode the architecture of antibody-mediated immunity.

Humans

Colorimetric gold nanosensors for monitoring protein aggregation: implications for Alzheimer's disease.

Alzheimer's disease (AD) is the leading cause of dementia worldwide. It remains a major public health challenge due to the lack of early diagnostic tools and effective disease-modifying therapies. Molecularly, AD is characterized by extracellular amyloid-β (Aβ) plaques and intracellular Tau tangles, as well as soluble oligomers that are likely the neurotoxic species. However, the transient and heterogeneous nature of these oligomers makes them difficult to detect using conventional biosensing approaches. Nanomaterial-based colorimetric biosensors have emerged as promising platforms for detecting protein aggregates and discovering aggregation inhibitors. Specifically, the localized surface plasmon resonance properties of metallic nanomaterials can enable rapid, label-free, and visually detectable colorimetric sensing of molecular interactions. These features can be leveraged to monitor protein aggregation processes in real time and achieve high-throughput screening of aggregation inhibitors, which may collectively enable early detection and timely intervention of AD progression. This Review Article presents the design and engineering of gold-nanomaterial-based colorimetric biosensors for monitoring protein aggregation and highlights the current challenges and emerging opportunities for applying these nanosensors to combat AD.

Journal Article

Transcription regulation of cell fate plasticity - from embryonic development to tissue regeneration.

Cell fate plasticity refers to the capacity of cells sharing the same genome to alter, reverse, or reconfigure their identity under physiological, pathological, or experimental conditions. This property underlies embryonic development, cellular reprogramming, and tissue regeneration, but becomes progressively restricted as lineage identity is stabilized. Embryonic development represents an intrinsic process of fate transitions, whereas reprogramming and regeneration reveal how differentiated cells can dedifferentiate or transdifferentiate under specific conditions. Across these contexts, plasticity is governed by multilayered regulatory networks involving transcription factors, epigenetic regulators, cofactors, and the core transcription machinery. Robust regulatory programs stabilize cell identity, whereas stochastic fluctuations in gene expression and chromatin state can prime cells for fate transitions, adding a tunable dimension to plasticity control. In this review, we synthesize recent advances in the regulation of cell fate plasticity across development, reprogramming, and regeneration, highlighting how transcription factors, epigenetic modifications, transcriptional cofactors, and core transcription machinery cooperate to control cell fate decisions and plasticity.

Animals

Comprehensive quality profiling and comparative metabolic characterization of seven dominant fresh-eating Chinese olive (Canarium album Lour.) cultivars in Southern China.

Fresh-eating Chinese olive (Canarium album Lour.) is a subtropical fruit endemic to southern China with considerable commercial value, yet systematic quality characterization of dominant cultivars remains scarce. This study established a multi-dimensional quality dataset for seven dominant cultivars from Fujian and Guangdong provinces, integrating nutritional components, soluble sugars, organic acids, mineral elements, volatile profiles, and non-targeted metabolomics. Significant cultivar-specific differences were observed across all evaluated dimensions: "Lingfeng" exhibited a sugar-dominant low-acid profile, whereas "Sanleng" showed elevated phenolic constituents accumulation. Volatile profiling identified terpenoid-based candidate discriminatory biomarkers, and metabolomic analysis revealed phenylpropanoid biosynthesis, tryptophan metabolism, and starch and sucrose metabolism as the most variable pathways. Correlations between untargeted profiling and targeted absolute quantification validated untargeted result reliability and revealed their complementarity in nutritional evaluation. These findings provide baseline data for FECO germplasm evaluation and targeted industrial utilization.

China

Multi-omic biomarkers in cardiovascular disease: Discovery to clinical translation.

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, necessitating improved risk stratification and early detection strategies. Multiomics approaches that integrate genomics, transcriptomics, proteomics, metabolomics, and epigenomics offer unprecedented opportunities for biomarker discovery and precision medicine in cardiovascular care. This narrative review examines the current landscape of multiomics biomarkers for CVD, tracing their evolution from discovery to clinical translation. We synthesize evidence from recent studies evaluating the clinical utility of integrated omics approaches across diverse cardiovascular conditions, including atherosclerotic cardiovascular disease, heart failure, and atrial fibrillation. High-throughput proteomics has identified novel protein signatures that enhance cardiovascular risk prediction beyond traditional risk factors. Metabolomics has revealed pathway-specific biomarkers, including trimethylamine N-oxide and lipid species, associated with atherogenesis. Polygenic risk scores derived from genomic data demonstrate incremental value when combined with clinical risk scores. Multiomics biomarkers represent a transformative approach to cardiovascular risk assessment and disease management.

Humans

Family-Wise Error Rate Control in Clinical Trials With Overlapping Populations.

We consider clinical trials with multiple, overlapping patient populations that test multiple treatment policies specifically tailored to these populations. Such designs may lead to multiplicity issues, as false statements will affect several populations. For type I error control, often the family-wise error rate (FWER) is controlled, which is the probability to reject at least one true null hypothesis. If the joint distribution of the test statistics is known, the FWER level can be exhausted by determining critical values or adjusted-levels. The adjustment is typically done under the common ANOVA assumptions. However, the performed tests are then only valid under the rather strong assumption of homogeneous null effects, that is, when the null hypothesis applies to all subpopulations and their intersections. We show that under cancelling null effects, when heterogeneous effects cancel out in some or all subpopulations, this procedure does not provide FWER control. We also suggest different alternatives and compare them in terms of FWER control and their power.

Humans

Statistical test to compare the linkage model and the admixture model based on central limit results.

In the Admixture Model, the probability that an individual carries a certain allele at a specific marker depends on the allele frequencies in K ancestral populations and the proportion of the individual's genome originating from these populations. The markers are assumed to be independent. The Linkage Model is a Hidden Markov Model that extends the Admixture Model by incorporating linkage between neighboring loci. We prove consistency and asymptotic normality of maximum likelihood estimators for the ancestry of individuals in the Linkage Model, complementing earlier results by (Pfaff et al., 2004; Pfaffelhuber and Rohde, 2022; Heinzel, 2025) for the Admixture Model. These results are used to prove that a statistical test that allows for model selection between the Admixture Model and the Linkage Model is an asymptotic level-α-test. Finally, we demonstrate the practical relevance of our results by applying the test to real-world data from The 1000 Genomes Project Consortium (2015).

Genetic Linkage

Playing with Fire, Losing the Drive: Bidirectional Links Between Problematic Smartphone Use and Grit Dimensions.

This study examined bidirectional longitudinal associations between grit dimensions (consistency of interest [CI] and perseverance of effort [PE]) and problematic smartphone use (PSU) and tested cognitive flexibility as a mediating mechanism. A sample of 1,641 Chinese university students (55.2 percent female; Mage = 20.1 years) completed measures at two time points 6 months apart. A four-variable cross-lagged panel model revealed that CI and PSU negatively predicted each other over time, whereas PSU unidirectionally predicted decreased PE. Cognitive flexibility partially mediated the PSU-to-PE pathway (indirect effect = -0.004, 95 percent bootstrap CI [-0.010, -0.0001]). Competing models analysis confirmed this directionality: the forward mediation (PSU → cognitive flexibility → PE) was significant, whereas the reverse was not. These findings demonstrate that grit dimensions exhibit distinct longitudinal patterns with PSU and identify cognitive flexibility as a cognitive mechanism through which PSU specifically undermines effort persistence. Implications for dimensional approaches to grit and targeted interventions are discussed.

Humans

Morphology-engineered NiFe@C nanocages boosting electrochemical quantification of ractopamine in meat samples.

It is essential to acquire efficient electrocatalysts to develop ractopamine (RAC) electrochemical sensors. Herein, we report the synthesis of a series of carbon coated NiFe alloy nanostructures (e.g., NiFe@C nanoparticles, nanocubes and nanocages) using NiFe Prussian blue analogue (PBA) as the precursor. The NiFe@C nanocages exhibited the best electrocatalytic performance for RAC sensing. This is attributed to the embedded NiFe alloy nanoparticles that provide abundant active sites, and the unique nanocage structure facilitates electron transfer pathways while offering a high specific surface area. The resulting sensor achieves a low detection limit (LOD) of 54 nM (S/N = 3) within a linear range of 0.2-12 μM. Moreover, the sensor demonstrates good reproducibility, stability, and excellent long-term stability. Practical applicability was confirmed in meat samples, yielding satisfactory recovery rates ranging from 98% to 108%. A feasible strategy was introduced herein for rational design of metal@carbon electrocatalysts.

Phenethylamines

Identification of elements determining KIR gene demethylation at the CD56-bright stage of NK cell development.

The variegated expression of the KIR family of class I MHC receptors generates specialized natural killer (NK) cells capable of allele-specific HLA recognition. Understanding the mechanism of KIR gene activation will lead to improved methods for the generation of fully functional NK cells. A central RUNX-binding site in the KIR proximal promoter is required for gene activation. RUNX proteins recruit ten-eleven translocation (TET) proteins that generate 5-hydroxymethylcytosine (5hmC) and drive DNA demethylation. Assessment of 5-methylcytosine (5mC) and 5hmC residues at four stages of NK cell development reveals deposition of 5hmC primarily in a CREB site next to the RUNX site at the CD56Bright stage but not the subsequent CD56Dim stage representing fully mature NK cells. KIR promoter demethylation is delayed relative to other lineage-associated genes, indicating a high threshold for KIR gene demethylation in developing NK cells, and a window of opportunity for RUNX/TET-dependent KIR gene activation in CD56Bright NK cells.

6-base sequencing

SGLF-Net:Staged Global-to-Local Cross-Scale Fusion Network for Colonoscopic Polyp Segmentation.

Polyp segmentation in colonoscopy images plays a pivotal role in computer-aided medical diagnosis and the early prevention of colorectal cancer. However, existing methods often suffer from performance degradation when confronted with extreme polyp scale variation and polyp boundary ambiguity. To address these challenges, we propose the Staged Global-to-Local Cross-Scale Fusion Network (SGLF-Net), which adopts a novel staged global-to-local learning paradigm to progressively refine segmentation from coarse global semantics to fine-grained local details. Specifically, the Global Semantic Perception Stage integrates a Swin Transformer Encoder and a Dynamic Attentive Decoder (DAD) to construct comprehensive multi-scale contextual representations. The Local Detail Refinement Stage employs an Edge-aware Dynamic Attentive Decoder (E-DAD) to enhance structural fidelity and boundary precision through explicit edge-guided supervision. Furthermore, we introduce the Cross Spatial-Scale Feature Aggregation and Reconstitution (CSSAR) module, equipped with hybrid attention mechanisms, to facilitate efficient semantic structural interaction between the two cascaded stages. Extensive experiments on five public benchmark datasets demonstrate that SGLF-Net consistently outperforms state-of-the-art methods in both segmentation accuracy and boundary preservation.

Journal Article

An updated systematic review of buffalo nutritional requirements (2000-2024).

Buffaloes (Bubalus bubalis) are large ruminants with a superior ability to digest and utilize low-quality forages, producing milk and meat of higher quality compared to cattle. Despite their importance in animal production, buffaloes remain the focus of relatively few studies aimed at defining their nutritional requirements, which often results in inadequate diet formulation and management. There, this study aimed to conduct a systematic review of the literature on buffalo nutritional requirements, considering only open-access papers published in English and in indexed journals. A total of 58 studies met the inclusion criteria. Most of them focused on dairy buffaloes, particularly on the evaluation of crude protein, energy levels, and fiber content in the diet. Mineral nutrition was addressed in eight studies; however, in general the evaluated levels showed no significant effects. In contrast, very few or no studies were found concerning beef buffaloes, growing animals, reproduction, or other production stages. These findings highlight a critical gap in the literature and reinforce the urgent need to direct more research efforts and resources toward establishing species-specific nutritional requirements, particularly for beef buffaloes.

Animals

Long-term (>7-year) parental consumption of genetically modified maize (Cry1Ab/Cry2Aj and EPSPS) induces no adverse sperm DNA methylation alterations across two generations of cynomolgus monkeys.

This study assessed the long-term safety of genetically modified (GM) maize from a male reproductive perspective, using a non-human primate model. We analyzed the sperm DNA methylation profiles in cynomolgus monkeys fed GM maize, non-GM parental maize, or a conventional diet over two generations (F0/F1). Whole-genome bisulfite sequencing (WGBS) revealed no significant differences in global methylation levels among groups. The identified differentially methylated regions (DMRs) were short, enriched in non-regulatory genomic areas, and did not cluster after treatment. Functional enrichment analysis showed that DMR-associated genes were consistently involved in the same core biological pathways (e.g., mTOR and Wnt signaling) across all dietary comparisons. These findings indicate that GM maize consumption did not induce specific adverse epigenetic alterations in sperm, with the observed changes reflecting common physiological adaptations to dietary variations rather than GM-related effects.

Animals