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PubMed2026

Recovering membrane interaction kinetics of single molecules from 3D tracking data.

Interactions between cytosolic biomolecules and the bacterial inner membrane are fundamental to many cellular processes, yet directly measuring their binding kinetics in living cells remains challenging. Conventional 2D single-molecule tracking analyses can be insufficient, particularly when membrane association does not markedly alter the diffusion rate. Here, we present a method to recover membrane interaction kinetics from 3D single-molecule trajectories in rod-shaped bacteria. Using simulated 3D tracking data, we identify membrane-associated motion by quantifying how well short trajectory segments follow the circular curvature of the cell membrane. The resulting measure is further analyzed using a hidden Markov modeling framework, enabling robust discrimination between cytosolic and membrane-bound states and capturing the dynamics of state transitions without requiring diffusion-rate changes or direct colocalization with membrane markers. This work establishes a general framework for extracting membrane interaction kinetics from 3D single-molecule tracking data in live bacteria and highlights the value of realistic microscopy simulations for quantitative interpretation and systematic bias assessment.

Kinetics↗

PubMed2026

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↗

PubMed2026

A conserved distal-tail helical extension defines a tailspike attachment architecture in Gram-negative siphophages.

Rapid growth of bacteriophage genome collections has outpaced functional annotation of tail-tip proteins, limiting comparative analysis of host-recognition structures. Starting from a shared distal-tail gene organization in the Salmonella phages 9NA and Jersey, I developed a morphogenetic bioinformatic framework integrating gene synteny, sequence comparison, profile hidden Markov model (HMM) screening, structural evidence, structure-aware searching, and AlphaFold modeling. Comparison with the experimentally characterized lambda and Sf11 tail assemblies identified a predominantly alpha-helical C-terminal extension of the distal-tail (DT) protein associated with tailspike attachment, termed the distal-tail helical extension (DT-helix). Screening 541,986 proteins from 5167 complete NCBI RefSeq tailed-phage genomes, followed by evidence-based evaluation of sequence, genomic context, and structural architecture, identified 165 curated DT-helical-extension-associated phages. Their DT proteins segregated into six sequence groups. In the four principal multi-member groups, cognate tailspikes showed group-specific conservation in proximal N-terminal regions but substantially greater downstream diversity, consistent with sequence constraint at the DT-tailspike attachment boundary. A complementary ProstT5/Foldseek search supported the established groups but revealed no convincing additional highly divergent family. Together with the experimentally characterized Sf11 attachment interface, these findings define a recurrent morphogenetic architecture linking conserved distal-tail scaffolds to more variable receptor-binding proteins across siphophages infecting Gram-negative bacteria. Although universal exchangeability is not established, the identified scaffold-receptor-binding boundaries provide a framework for molecular characterization and rational phage engineering. Accession-level information for the 165 curated phages is available through PhageTailDB.

Viral Tail Proteins↗

PubMed2026

The hidden threat from food-derived carbon dots: Formation, biodistribution, and potential health risks.

Food-derived carbon dots (CDs) are a new class of carbon-based nanoparticles generated during the thermal processing of food matrices. These nanomaterials have been extensively studied for their unique fluorescence, good biocompatibility, and tunable surface chemistry in food detection, intelligent packaging, and biomedical applications. However, their nanoscale size and high surface activity have raised safety concerns regarding biological interactions, in vivo biodistribution, and potential long-term health hazards. Although CDs have traditionally been regarded as low-toxicity materials due to their favorable biocompatibility, the potential hidden risks of CDs have not received sufficient attention. CDs exhibit dose-dependent toxicity, not only accumulating in various tissues and organs but also potentially inducing oxidative stress and interfering with cellular metabolic functions. Therefore, this review summarizes the advances in sources, synthetic strategies, and core properties of CDs, with a special focus on in vivo biological interactions, fates, and potential safety challenges. In addition, it is proposed that the standardized detection and risk assessment system should be established to further explore the long-term health effects of CDs under real dietary exposure, thereby ensuring their safety and sustainable application.

Carbon Quantum Dots↗

PubMed2026

Uncovering hidden complexity in the Apis mellifera mitotranscriptome: a polyadenylation-centered perspective.

Mitochondrial transcription is gaining increasing attention as researchers seek to better understand the full coding potential of mitochondrial DNA (mtDNA). Emerging evidence suggests that mtDNA may encode additional elements beyond classical oxidative phosphorylation genes, pointing to a more complex transcriptional architecture than previously recognized. In this study, we explored the mitochondrial transcriptome of Apis mellifera (Insecta: Hymenoptera), with a particular focus on polyadenylation-associated features. Our analysis revealed that both sense and antisense transcripts undergo polyadenylation, although transcript abundance and poly(A) tail lengths varied markedly across mitochondrial genes. Several transcripts exhibited alternative isoforms, either extended or truncated, frequently including intergenic regions. These regions may represent functional non-coding elements or structural variants rather than conventional untranslated regions (UTRs). Interestingly, some transcripts also contained non-templated nucleotide additions particularly cytosine residues immediately upstream of the poly(A) tails. Monocistronic units that included portions of downstream intergenic regions were among the most abundantly represented, suggesting a possible regulatory role for these sequences. To experimentally validate our in silico findings, we performed RT-qPCR to assess relative gene expression and applied 3' RACE-PCR to define transcript boundaries. These approaches confirmed the presence of multiple transcript isoforms and supported the involvement of polyadenylation in shaping mitochondrial RNA diversity. Together, our findings reveal a previously underappreciated level of complexity in the A. mellifera mitochondrial transcriptome and highlight the potential regulatory significance of polyadenylation dynamics and intergenic region transcription.

Animals↗

PubMed2026

Meta-analysis and pharmacoeconomic study of rasagiline versus selegiline in the treatment of Parkinson's disease.

OBJECTIVE: Given the persistent absence of direct head-to-head trials, this study aimed to evaluate the comparative efficacy, safety, and cost-effectiveness of rasagiline versus selegiline as early-stage monotherapy for Parkinson's disease (PD), informing clinical selection and healthcare policies in China. METHODS: A systematic search of PubMed, Embase, and the Cochrane Library identified randomized controlled trials (RCTs) up to April 2026. Focusing on short-term outcomes (10-16 weeks), an adjusted indirect treatment comparison (ITC) using placebo as a common anchor evaluated symptom improvement (UPDRS total scores) and adverse event (AE) incidence. For economic evaluation, a 2-year Markov model was constructed from a Chinese healthcare-system perspective. The incremental cost-effectiveness ratio (ICER) was calculated alongside robust sensitivity analyses. RESULTS: Ten RCTs (rasagiline: 6; selegiline: 4) were included. The ITC revealed no statistically significant differences between rasagiline and selegiline in short-term symptomatic relief (Mean Difference = -0.82, 95% CI [-2.08, 0.44], p = 0.203) or AE risk (Odds Ratio = 0.83, 95% CI [0.50, 1.38], p = 0.475). The overall evidence certainty was rated as moderate. Economically, the base-case simulation indicated rasagiline yielded a marginal benefit of 0.0088 QALYs over selegiline but incurred an additional 17,111.10 Yuan. This resulted in an ICER of 1,951,505.55 Yuan/QALY, substantially exceeding the conventional willingness-to-pay threshold. CONCLUSION: Supported by moderate-certainty evidence, rasagiline and selegiline provide comparable short-term efficacy and safety for early-stage PD monotherapy. However, at its current pricing, rasagiline is not cost-effective. Significant price reductions or definitive proof of long-term superiority are required to justify its economic value.

Humans↗

PubMed2026

A novel neoadjuvant immunotherapy confers improved overall survival in oral cancer patients with low tumor PD-L1 expression The IT-MATTERS Clinical trial - Prognostic role of tumor PD-L1 expression.

OBJECTIVE: Five-year overall survival (OS) remains < 50% for patients with resectable, locally advanced (LA) primary oral squamous cell carcinoma (OSCC) and soft palate, receiving current standard of care (SOC). The aim of our study was to examine neoadjuvant Leukocyte Interleukin Injection (LI) with CIZ (intravenous low dose cyclophosphamide, indomethacin and zinc multivitamins) effect on OS, in low-risk (LR) OSCC patients. PATIENTS AND METHODS: In a randomized, controlled Phase 3 trial, treatment-naïve locally advanced patients, with stage III/IVa OSCC and soft-palate cancer, had surgical tumor samples assessed for pre-defined thresholds of PD-L1 tumor proportion score (TPS). OS was analyzed using proportional hazard models for LI + CIZ + SOC vs SOC, in the intention-to-treat (ITT) population. RESULTS: OS was superior in low risk (LR) patients receiving LI + CIZ + SOC compared to SOC; OS advantage hazard ratio (HR) 0.64, p = 0.0569 (without selecting for N0, PD-L1 TPS < 10%), and the Kaplan-Meier (K-M) lifetable achieved significance (log rank p = 0.0340) favoring LI + CIZ + SOC vs SOC. Applying the selection criteria (cN0 and TPS < 10%) to ITT, OS reached HR 0.34p = 0.0012, Kaplan-Meier log rank p = 0.0015. The ITT LR cohort (cN0 and TPS < 10%) achieved a HR 0.26 (p = 0.0023), Kaplan-Meier log rank p = 0.0013, supported by progression free survival (PFS) HR 0.43, p = 0.0178, Kaplan-Meier log rank p = 0.0431, with 32% absolute survival advantage over control at 60 months. CONCLUSIONS: Significant OS prolongation was observed in ITT population for LI + CIZ + SOC vs SOC, in LR and in ITT LR cN0, PD-L1TPS < 10% cohort having locally advanced squamous cell carcinoma tumors in oral cavity/soft-palate. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT01265849; EudraCT (Identifier: 2010-019952-35).

Humans↗

PubMed2026

Proteome-level evidence that tebuconazole, both alone and in interaction with thiacloprid, affects epigenetic events in bumblebee heads.

Tebuconazole, a widely used ergosterol biosynthesis-inhibiting fungicide, can affect nontargets, especially when combined with insecticides. We employed label-free quantitative proteomics to investigate the effects of long-term exposure to sublethal concentrations (100 μg/L) of tebuconazole, either by itself or alongside the neonicotinoid thiacloprid (100 μg/L), on the heads of Bombus terrestris workers. A Bayesian factor power analysis revealed that the experiment produced conclusive proteomic results. Tebuconazole treatment revealed eleven differentially abundant proteins, which increased elevenfold with thiacloprid. The proteins that changed in the same direction in both treatments suggest the occurrence of epigenetic events because they are involved in histone trimethylation (H3K4me3), pre-mRNA processing, and folate (vitamin B9) metabolism. Following co-exposure, the abundance of histone H2A.V and its associated proteins was affected. Two important detoxification-related proteins, CYP6BE1 and CYP6AQ1 (honey bee homologs), were identified, as well as proteins that suggest hormonal and neurotoxic effects. Overall, this study suggests that tebuconazole affects key epigenetic processes in bumblebee heads at the proteome level, though this was not confirmed at the biological level or through orthogonal methods. The tested chemicals were previously found to affect trimethylations, but not H3K4me3. We suggest analyzing the different trimethylations, their interplay, and associated hallmarks, such as folate levels. SIGNIFICANCE: The effects of pesticides and their combinations on organisms can be unexpected until they are examined using modern, complex methods. High-throughput proteomics can provide data on important biochemical processes affected by pesticides, offering a different perspective to that at the expression level. Despite their low acute toxicity, a group of fungicides that inhibit (ergo)sterol biosynthesis (EBI or SBI) are considered dangerous to pollinators, including bumblebees. This is due to the increasing toxicity of insecticides through the inhibition of cytochrome P450 detoxification enzymes. We found that tebuconazole had a similar effect on epigenetic events when used alone or in combination with the insecticide thiacloprid. Key proteins suggest that H3K4 histone trimethylation (H3K4me3) was impacted. To our knowledge, this expands the existing evidence suggesting that tebuconazole/triazole fungicides affect histone trimethylation H3K27me3. Since literature shows that thiacloprid affects H3K9me3, it is possible that thiacloprid and tebuconazole interact in these epigenetic events that affect each other. Overall, our results suggest that tebuconazole affects proteins involved in histone trimethylation, pre-mRNA processing, and folate metabolism. These are all hallmarks of epigenetic processes and were further extended by the co-exposure of tebuconazole and thiacloprid to more differently abundant proteins. Additionally, the results provide data on cytochrome P450s of the CYP6 family, which act as detoxifying proteins, as well as proteins that indicate hormonal and neurotoxic effects in bumblebee heads. Finally, the results of the Bayesian power analysis confirmed the meaningfulness of the proteomic data analyzed in this study. If the new findings obtained at the proteome level are verified by different methods, the full extent of the side effects of tebuconazole can be revealed.

Animals↗

PubMed2026

Reliability-aware hierarchical learning for Chagas disease screening from 12-lead ECGs: tackling label uncertainty and class imbalance.

Objective.Chagas disease, a neglected tropical disease (NTD) with significant cardiovascular impact, remains underdiagnosed in resource-limited regions. Electrocardiogram (ECG) screening offers a low-cost tool for detecting cardiac involvement, yet algorithm development is challenged by label noise, data scarcity, and the latent nature of infection. This study proposes a robust ECG-based screening framework that explicitly addresses these constraints.Approach.We introduce aReliability-Aware Hierarchical Learningstrategy that calibrates supervision according to data provenance, prioritizing serology-confirmed labels over noisy self-reports. To mitigate data scarcity, we compare a specialized convolutional neural network (CNN) trained from scratch with a transfer learning approach based on a Spatio-Temporal ECG foundation Model (FM). Performance is evaluated across varying data scales, and the representation structure is analyzed to interpret model behavior.Main results.On the official hidden test set of the George B. Moody PhysioNet/Computing in Cardiology Challenge 2025, our approach achieved a Challenge Score of 0.163. We observe that while the specialized CNN performs competitively in data-rich regimes, the FM exhibits superior robustness in extreme low-resource settings. Furthermore, performance reaches a plateau imposed by underlying disease physiology. Bimodal score distributions suggest that models distinguish established cardiomyopathy from indeterminate infection, which remains electrophysiologically indistinguishable from healthy controls.Significance.These findings clarify both the potential and intrinsic limits of ECG-based AI screening for NTD-associated cardiac involvement. Reliability-aware supervision and data-efficient transfer learning provide a practical framework toward scalable and clinically meaningful ECG screening systems in resource-constrained environments.

Humans↗

PubMed2026

Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.

PURPOSE: The purpose of this study was to analyze the association between disease progression of geographic atrophy (GA) from optical coherence tomography (OCT) with retinal sensitivity (RS) in microperimetry (MP) over a 2-year follow-up period. METHODS: This is a longitudinal analysis of the OAKS Phase-III clinical trial. Both study and fellow eyes with GA that underwent imaging with the Spectralis OCT and consecutive MP examination were eligible. Pointwise quantification of ellipsoid zone (EZ) thickness, EZ and retinal pigment epithelium (RPE) loss from OCT volumes was correlated with localized RS. A longitudinal predictive model using a Markov Chain framework was implemented to predict RS change over time based on OCT biomarkers. The modeling of morphological and functional progression was based on the fellow-eye cohort. RESULTS: A total of 39,681 MP points from 406 patients were analyzed. In the fellow eye cohort, baseline (BSL) EZ thickness was positively associated with RS (0.3 decibel [dB]/µm, P < 0.001). Decrease in EZ thickness between visits during follow-up was significantly associated with decrease in RS (0.1 dB / 1 µm change). RS was significantly lower in MP points within EZ loss during follow-up compared with MP points within the retina with measurable EZ (P < 0.001). The largest functional decline was observed within RPE loss, also associated with the highest probability of absolute scotoma (P < 0.001). Morphological progression to EZ and RPE loss was influenced by EZ thickness and the morphology of adjacent MP points (P < 0.001). CONCLUSIONS: Two exploratory endpoints were developed, namely quantification of EZ thickness and loss, and localized RS within high-risk OCT areas. RS decline during follow-up is associated with automatically quantified disease progression in OCT.

Humans↗

PubMed2026

Exploring the dose-response relationship between prenatal exercise and postpartum depression: A systematic review and meta-analysis of randomized controlled trials.

IMPORTANCE: Postpartum depression (PPD) is a hidden and widespread global public health crisis affecting millions of mothers and infants annually. Prenatal exercise is a potentially accessible nonpharmacological strategy for PPD prevention, but its optimal dose remains uncertain. OBJECTIVE: To explore the dose-response relationship between prenatal exercise and the incidence of PPD through meta-analysis of randomized controlled trials (RCTs). DATA SOURCES: Systematic searches were conducted in PubMed, Embase, Web of Science, and Cochrane Library using MeSH terms and keywords related to "pregnant women," "prenatal exercise," and "postpartum depression," up to June 23, 2025. STUDY SELECTION: RCTs included examined prenatal exercise interventions in pregnant women without a history of depression, with PPD incidence reported using validated depression scales (such as EPDS, CES-D). Non-RCT studies, duplicate publications, and studies with insufficient data were excluded. DATA EXTRACTION AND SYNTHESIS: Two researchers independently extracted data according to the PRISMA guidelines. A random-effects model was used to pool odds ratios (OR) and their 95% confidence intervals (CI). Linear and nonlinear dose-response models were employed to analyze and evaluate the relationship between exercise dose (measured in METs-min/week) and the incidence of PPD. MAIN OUTCOME(S) AND MEASURE(S): The primary outcome is the incidence of PPD, analyzing its relationship with prenatal exercise dose. RESULTS: Eight RCTs involving 2231 pregnant women were included. The pooled analysis showed that prenatal exercise was associated with a potential reduction in PPD incidence, although the overall effect did not reach statistical significance (OR=0.58, 95% CI [0.33, 1.02]). In dose-stratified analysis, exercise doses ≥500 METs-min/week were associated with significantly lower PPD incidence (OR=0.44, 95% CI [0.24, 0.78]). Subgroup analyses suggested trends toward greater benefits among women aged ≥30 years and those initiating exercise between 14 and 28 weeks of gestation; however, subgroup differences did not reach statistical significance. The linear dose-response trend did not reach statistical significance (p = 0.0533), and neither the overall spline association (p = 0.1704) nor the test for nonlinearity (p = 0.6361) was statistically significant. CONCLUSIONS AND RELEVANCE: Prenatal exercise may be associated with a lower risk of PPD, but the overall pooled effect did not reach statistical significance. Findings concerning ≥500 METs-min/week and the apparent flattening of the dose-response curve should be considered exploratory and require confirmation in larger trials.

Humans↗

PubMed2026

Analyzing the impact of subcutaneous injection needle, device, and administration characteristics on patient pain, anxiety, and safety: a systematic literature review.

The subcutaneous (SC) injection route is a commonly used and important method for therapeutic delivery of a wide range of compounds, and needle characteristics have a significant influence on patient pain, anxiety, safety, and other outcomes. This systematic review evaluates the evidence on how needle-specific characteristics (e.g. gauge, length, tip design, wall thickness, concealment) and administration- or device-related factors can affect patient-reported outcomes and clinical safety indicators during and following SC injections. A comprehensive search was conducted in MEDLINE, PubMed, Embase, and ClinicalTrials.gov in June 2024. Studies were included if they assessed the relationship between needle characteristics and pain, anxiety, safety, or related outcomes in individuals receiving SC injections. A dual-reviewer process was used for study selection, data extraction, and quality assessment. Sixty-two studies met inclusion criteria. Evidence consistently indicated that thinner and shorter needles reduced patient-reported pain and adverse events such as bruising and bleeding. Tapered and lubricated needles, hidden or retractable needle designs, and use of autoinjectors or prefilled syringes also contributed to reduced anxiety and improved user satisfaction. However, results were heterogeneous, and many studies lacked sufficient power or single-variable evaluation of individual needle parameters, limiting definitive conclusions. Needle characteristics significantly influence patient experience and safety with SC delivery. While both clinical evidence and practical experience clearly favor thinner, shorter, and concealed needles, further standardized, high-quality research is needed to isolate and quantify the specific contributions of individual needle characteristics to optimize injection practices and support patient-centered device design.

Humans↗

PubMed2026

[Tafluprost/timolol fixed-dose combination versus tafluprost monotherapy for open-angle glaucoma and ocular hypertension: a multicenter, randomized, double-blind, parallel-group trial].

Objective: To evaluate the efficacy and safety of a preservative-free tafluprost/timolol maleate fixed-dose combination compared with preservative-free tafluprost monotherapy in Chinese patients with open-angle glaucoma (OAG) or ocular hypertension (OHT). Methods: This was a multicenter, randomized, double-blind, parallel-controlled clinical trial conducted across 25 centers, including the Eye & ENT Hospital of Fudan University, from January 2019 to November 2022. Patients diagnosed with OAG or OHT who required enhanced intraocular pressure (IOP) reduction after a 4-week washout period were enrolled. Participants were randomized 1∶1 to receive either tafluprost/timolol or tafluprost once daily for 3 months. The primary endpoint was the change from baseline in mean diurnal IOP (the average of measurements at 8:00, 10:00, and 16:00) at Month 3. Secondary endpoints included IOP changes at individual time points and the proportion of responders achieving predefined IOP reduction thresholds. Safety was assessed via the incidence of adverse events (AEs). Analysis of covariance (ANCOVA) using the Markov Chain Monte Carlo (MCMC) method was employed for the primary endpoint; superiority was established if the upper limit of the 95% confidence interval (CI) was<0 mmHg (1 mmHg=0.133 kPa). Continuous variables in secondary endpoints were compared using ANCOVA, and responder rates were analyzed using Fisher's exact test. Results: A total of 219 patients were enrolled (tafluprost/timolol group: n=110; tafluprost group: n=109). The primary efficacy analysis set included 215 patients (tafluprost/timolol: n=107; tafluprost: n=108). Baseline characteristics were well-balanced between the two groups. The majority of patients were male [127 (59.1%)] with a mean age of (44.80±15.71) years at screening. At Month 3, the mean diurnal IOP reduction from baseline was (6.56±3.44) mmHg in the tafluprost/timolol group and (5.36±2.94) mmHg in the tafluprost group. After adjusting for baseline IOP, the between-group difference was -1.312 mmHg (95%CI: -2.010 to -0.696); as the upper limit was<0 mmHg, tafluprost/timolol demonstrated superior IOP-lowering efficacy to tafluprost. Responder rates for IOP reductions of≥15%,≥25%, and≥30% were significantly higher in the tafluprost/timolol group (P=0.016, 0.028, and 0.032, respectively). The incidence of ocular AEs was 20.0% (22/110) in the tafluprost/timolol group and 26.6% (29/109) in the tafluprost group. The most common AE was conjunctival hyperemia, occurring in 2.7% (3/110) and 8.3% (9/109) of the groups, respectively. Conclusion: Compared with preservative-free tafluprost monotherapy, the tafluprost/timolol combination provides significantly greater IOP reduction in patients with OAG and OHT, while maintaining a favorable safety profile.

Humans↗

PubMed2026

Modelling the effects of biological intervention in a dynamical gene network.

Cellular response to environmental and internal signals can be modeled by dynamical gene regulatory networks (GRN). In the literature, three main classes of gene network models can be distinguished: (1) non-quantitative (or data-based) models which do not describe the probability distribution of gene expressions; (2) quantitative models which fully describe the probability distribution of all genes co-expression; and (3) mechanistic models which allow for a causal interpretation of gene interactions. We propose two rigorous frameworks to model gene alteration in a dynamical GRN, depending on whether the network model is quantitative or mechanistic. We explain how these models can be used for design of experiment, or, if additional alteration data are available, for validation purposes or to improve the parameter estimation of the original model. We apply these methods to the Gaussian graphical model, which is quantitative but non-mechanistic, and to mechanistic models of Bayesian networks and penalized linear regression.

Gene Regulatory Networks↗

PubMed2026

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↗

PubMed2025

An integrated multiscale air quality modelling framework for industrial park pollution: Linking local emissions to regional transport.

Capturing the spatiotemporal distribution of pollutants in industrial parks remains challenging for regional air quality models because of their coarse resolution (3 km), resulting in uncertainties in local emission quantification. To address this, we developed the Integrated Multiscale Air Quality Modelling System for Industry (IAQMS-Industry), coupling the regional Nested Air Quality Prediction Modelling System (NAQPMS) with a city-scale chemical transport model. This framework integrates point-source locations and Gaussian plume dispersion to simulate particulate matter with a diameter smaller than 2.5 micrometres (PM2.5) at 100 m resolution. Applied to the Beijing Yi Zhuang and Tangshan industrial parks and evaluated against observations. The coupled model achieved a normalized mean bias (NMB) ranging from 3.1 % to 6.2 %, improving upon NAQPMS (-16.9 % to -7.7 %). Spatial analysis revealed that coarse regional grids underestimated the PM2.5 concentrations at industrial sites by smoothing gradients, whereas IAQMS-Industry successfully resolved spatial patterns. Industrial point emissions accounted for 22.9 %-26.4 % of PM2.5 in the coupled model, which was significantly greater than the regional model estimates of 1.6 %-13.7 %. These findings indicate that regional models overestimate pollutant dispersion processes in industrial parks while underestimating local industrial impacts. By explicitly resolving point-source dynamics and linking them to regional transport, IAQMS-Industry provides a robust tool for designing targeted emission controls in industrial cities and balancing local air quality improvements with minimized regional pollution outflow. This study underscores the necessity of multiscale modelling for accurate source apportionment and informed environmental governance in industrial zones.

Air Pollution↗

PubMed2026

Snow carps as an emerging model for polyploid genome evolution.

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Editorial↗

PubMed2026

Penalized Cumulative Probability Model for a Continuous Outcome Subject to Detection Limits.

Mixed-type outcome data occur when the outcome variable's distribution is a mixture of both continuous and discrete ordinal variables. Such mixed-type outcomes are common in biomedical, psychological, and the health sciences, particularly for variables having either a detection or quantitation limit. When interest lies in identifying a combination of genomic features associated with a mixed-type outcome, any method used would require a variable selection strategy for high-dimensional data. Unfortunately, few variable selection methods exist for modeling a mixed-type outcome when the covariate space is high dimensional. This study develops a high-dimensional penalized cumulative probability model (CPM), to allow for the identification of genomic features associated with mixed-type outcome of interest. We demonstrated how such model may be estimated using the iterative penalization procedure-the generalized monotone incremental forward stagewise (GMIFS) algorithm. The Model-X knockoffs procedure was combined with the estimation algorithm to control the false discovery rates (FDR) when performing variable selection. Through extensive simulation studies, our penalized CPM was shown to outperform alternative methods in terms of controlled variable selection performance by achieving high statistical power with the FDR being controlled at the target level. We demonstrate the utility of our method by applying it to predict estimated glomeruli filtration rate (eGFR) in kidney transplant recipients at 24 months post-transplant using baseline gene expression data as predictors. Our CPM model identified five genes associated with this mixed-type outcome which have important links to renal disease, which may provide prognostic guidance for kidney transplantation recipients.

Models, Statistical↗