Abstract: Background: Chronic pain following thoracotomy remains a common and clinically significant complication that adversely affects functional recovery and quality of life. Despite advances in perioperative analgesic techniques, chronic post-thoracotomy pain continues to be under-recognized and insufficiently managed in routine clinical practice. This study aimed to determine the incidence of chronic pain after thoracotomy and to evaluate its impact on daily activities and postoperative pain management behaviors. Methods: This retrospective observational study was conducted after institutional ethics committee approval (approval no. 2023/61). Patients aged ≥15 years who underwent thoracotomy between 15 June 2022 and 15 June 2023 and were at least three months postoperative were included. Patients who underwent video-assisted thoracoscopic surgery were excluded. Demographic, surgical, anesthetic, and postoperative analgesia data were obtained from medical records. Patients were contacted by telephone to assess pain intensity using a Numeric Rating Scale (NRS), functional impact on daily activities, and analgesic medication use. The primary outcome was the incidence of chronic post-thoracotomy pain, defined as pain persisting beyond three months and reported at the time of the interview. Results: A total of 56 patients were included in the analysis. Chronic pain was reported by 55.4% of patients. Pain that interfered with daily activities and required medication use was reported by 51.5% of patients. Thirty-three patients (57.9%) reported an NRS score >3 during movement. Among patients with chronic pain, 64.7% reported self-medication without physician consultation, whereas only 11.8% sought medical advice for pain management. Conclusions: Chronic pain remains highly prevalent after thoracotomy and substantially interferes with daily functioning. A considerable proportion of patients self-manage their pain without medical supervision, underscoring the need for structured postoperative follow-up, early identification of high-risk patients, and individualized multimodal analgesic strategies to reduce the burden of chronic post-thoracotomy pain.

Abstract: Clutch persistence, the ability to sustain consecutive egg-laying cycles, is a critical determinant of profitability in the poultry industry, especially for aging laying hens (≥65 weeks). However, its underlying regulatory mechanisms remain poorly understood, largely due to limitations of the traditional “ovary-centric” research paradigm, which ignores the long-range regulatory effects of intestinal microbiota on ovarian metabolism. To address this knowledge gap, the present study aimed to dissect the comprehensive regulatory network governing clutch persistence using integrated multi-omics analyses. A total of 20 sixty-five-week-old Rhode Island Red (RIR) laying hens with cumulative egg production exceeding 300 eggs but distinct clutch persistence was stratified into high-persistence group (DLCD, ≥25 clutches, n=10) and low-persistence group (DLCS, ≤15 clutches, n=10). Multi-omics profiling, including ovarian transcriptomics, proteomics, and metabolomics, serum metabolomics and cecal microbiota 16S rRNA sequencing was performed. Data integration and association mining were conducted via Spearman correlation analysis with stringent thresholds (r > 0.6, P < 0.01). Integrated analyses revealed a “gut-ovary axis” regulatory model mediated by a lipid mediator network, operating through a three-tiered mechanism: 1) Gut Initiation: The DLCD group exhibited enriched cecal γ-Proteobacteria promoted biosynthesis of lipid precursors. 2) Serum Transport: Key serum lipid mediators, most notably LysoPC (22:6) (VIP = 4.5) and cholesterol ester CE (20:4)—served as critical carriers transducing gut-derived signals to the ovary. 3) Ovarian Execution: These lipid signals activated a core ovarian metabolic pathway centered on the PLA2G6-ALOX15B-AGPAT3 axis, which coordinated follicular development and ovulation by supplying steroid hormone synthesis substrates, exerting anti-inflammatory effects, and stabilizing membrane structures. Collectively, this study demonstrates that gut microbiota modulates clutch persistence in aging laying hens via lipid mediators, orchestrating a systemic “gut-serum-ovary” regulatory cascade. These findings provide a novel theoretical framework for extending the economic egg-laying cycle through targeted manipulation of intestinal microbiota or serum lipid metabolism.

Abstract: Wastewater-integrated microalgal cultivation offers a sustainable pathway to reduce biofuel production costs while simultaneously addressing nutrient-rich effluent management. In this study, matured compost leachate was systematically evaluated as a sole cultivation medium for Desmodesmus sp. under different dilution regimes, with emphasis on growth kinetics, wastewater remediation efficiency, lipid accumulation behavior, and biodiesel quality. Desmodesmus sp. successfully acclimatized to 100% undiluted matured compost leachate within four days and maintained stable mixotrophic growth without dilution or pre-treatment. Cultivation in undiluted leachate achieved a maximum biomass concentration of 2.69 ± 0.09 g L⁻¹, representing an approximately fourfold increase compared to Bold’s Basal Medium. Concurrently, high treatment efficiencies were obtained, with chemical oxygen demand removal of 82.6%, total nitrogen reduction of 60–72%, and total phosphorus removal of 65–66%, confirming effective integration of biomass production with wastewater remediation. Lipid biosynthesis was strongly governed by nitrogen availability, with lipid concentration increasing from 0.32 g L⁻¹ during exponential growth to 0.72 g L⁻¹ under nitrogen-depleted stationary conditions. Fatty acid methyl ester profiling revealed a stress-induced shift toward saturated and monounsaturated fatty acids, accounting for 75.6% of total fatty acids and dominated by palmitic acid (C16:0). This compositional restructuring resulted in biodiesel properties characterized by a high cetane number of 64.5, low iodine value, and oxidative stability exceeding 30 h, meeting or surpassing international biodiesel quality benchmarks.

Abstract: Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However, existing reviews primarily treat MI as an observational science, summarizing analytical insights while lacking a systematic framework for actionable intervention. To bridge this gap, we present a practical survey structured around the pipeline: "Locate, Steer, and Improve." We formally categorize Localizing (diagnosis) and Steering (intervention) methods based on specific Interpretable Objects to establish a rigorous intervention protocol. Furthermore, we demonstrate how this framework enables tangible improvements in Alignment, Capability, and Efficiency, effectively operationalizing MI as an actionable methodology for model optimization. With actionable mechanistic interpretability evolving at a fast pace, we pledge to keep this survey up to date, ensuring it reflects the cutting-edge advances in this area.

Abstract: As dockless bike-sharing systems rapidly expanded across China, scholars have increasingly examined bicycle usage efficiency across locations and its relationship to the geographical environment. Existing studies rely primarily on big data to evaluate location-specific efficiency using Time-to-Booking (ToB)—the idle duration before a bicycle is rented at a given location. This indicator, however, ignores network flow effects: bicycles departing from the same location may reach destinations with vastly different ToB values. This gap is addressed by incorporating the destination ToB after each trip, developing a flow-integrated ToB index for central Beijing. Analysis reveals that the improved index exhibits significant spatial heterogeneity while maintaining the overall distribution pattern of the original metric, indicating that most bicycles flow to areas with efficiency similar to that of their origin. The flow-integrated index compresses the efficiency range—maximum values decrease, minimum values increase—suggesting greater spatial balance in usage efficiency. Bicycles in the city center consistently show higher usage efficiency than those in peripheral areas. Multiple factors influence usage efficiency with significant spatial heterogeneity. Understanding of bike-sharing efficiency is advanced, and practical insights are provided for operators and urban planners in developing refined management strategies.

Abstract:

Introduction of species consists today one of the most important problem of nature conservation. Special attention is paid to alien vascular plants and vertebrates. In the Afrotropical Region (sub-Saharan Africa), avian and mammalian introductions have attracted the attention of many re-searchers and was recently reviewed, but there is a lack of such comprehensive review of alien amphibians and reptiles. The presented paper constitutes an attempt to overview the status, distribution, threats introduced herp species to sub-Saharan Africa since he second half of the 18^th century. This review includes 21 amphibian (including 10 established) and 57 reptile (including 19 established) species introduced to sub-Saharan. The introduced amphibians are representatives of Urodela (n=4 spp., none established) and Anura (n=17 species, incl. 10 established). Introduced reptiles species belonged to the following orders: Testudines (n=11 species, incl. 6 established), Sauria (n=32 spp., incl. 29 established), Serpentes (n=13 spp., incl. 2 established) and Crocolylia (1 sp. not established). Most species introduced to sub-Saharan Africa which subsequently developed viable populations originated from the Afrotropical (35%), Malagasy (27%) and Oriental (27%) regions. However, the proportions of introduced species which failed to establish viable populations were quite different: Nearctics (25%), Afrotropics (22%), and Neotropics (17%); Malagasy 11%, Oriental Region only 6%. First introduction of alien herp species, i.e. Gehyra mutilate and Ptachadena mascareniensis, in Africa took place in 18^th century. By the end of 19^th century, four other species have been introduced and in the two last decades of that century – 5 species. Similarly, in 20^th century, most introduction were made in the last two decades, when an exponential growth of introduction begun and lasts till present. This growth has been caused by an increase in international trade and herp pet industry, especially in South Africa. Stowaway and pet trade are the most common pathways of introductions. Few factors determine the successful establishment of introduced alien herp species in sub-Saharan Africa, viz.: the behavioural and morphological traits, propagula pressure, climate and habitat overlap, and presence of potentially competing species. The impact of alien herps in sub-Saharan Africa on the local biodiversity is not well-investigated. Negative effects have been, however, evidenced for species such as Sclerophrys gutturalis, Agama agama, Hemidactylus frenatus, Trachemys scripta (competition); Xenopus laevis, Sclerophrys gutturalis, Rhinella marina, Lycodon aulica (predation); Xenopus laevis, Python sabae (hybridization); Xenopus laevis, Palea steindachneri (diseases and parasites). In comparison with other continents (Europe and North America) the number of introduced and established herp species in sub-Saharan Africa is relatively low, possibly because the Afrotropical region is saturated with herps which can potentially compete and prey on the alien species, preventing their successful establishment. Madagascar, the Mascarenes and other small islands in the Malagasy Region have the highest number of introduced herp species in sub-Saharan Africa. However these numbers are still much lower than those recorded for instance in the Greater Caribbean, probably for the same reasons as in the mainland.

Abstract: Viticulture is a vital sector of agriculture and economy exhibiting susceptibility to climate change, particularly in the Mediterranean regions. The present investigation examines the climatic suitability for vineyards development in Greece by exploiting geomorphological and bioclimatic data for the reference climatic period 1970–2000. The data are sourced from the ERA5-Land dataset and analyzed with R. The objective is to create a specific crop suitability map based on a simple, transparent model using coding processes. This map identifies the climatically suitable areas for grapevine cultivation during the reference period. Results demonstrate that the model is highly adaptable, as both variable thresholds and areas of interest can be modified, while incorporating future climate scenarios (e.g., RCP models) can be performed, allowing for dynamic reconfiguration. According to the mapped climatic suitability, 55.1% of Greece is rated 3.5-4.0, and 12.9% is rated 4.0-4.5. The total suitability over Greece is calculated with a score of 3.5-4.0 for the 50.9 % of total area, and for a score of 4.0-4.5, the covered area is 12.9%. Considering the Corine Land Cover classification as the reference land cover dataset, the false-negative areas are only 1.5% of the areas defined as viticultural. By providing clear and accurate spatial information, the model supports informed decision-making and the development of adaptation strategies, enhancing, therefore, the resilience and sustainability of viticulture in the context of climate change.

Abstract: Gait is a repetitive whole-body movement that encodes inter-segmental coordination and spatiotemporal patterns and has been used not only for identity recognition but also for inferring attributes such as sex. Many vision-based approaches, however, rely on appearance cues, which are sensitive to occlusion and clothing variation and may raise privacy concerns; robustness under everyday perturbations remains insufficiently quantified. Here, we investigate skeleton-based gait sex classification using 2D pose sequences from the PsyMo dataset. We rendered 17 COCO keypoints into 50×50 grayscale skeleton images and trained a 3D residual CNN on non-overlapping 15-frame clips. Evaluation used a subject-wise, stratified split with balanced sexes, and the same test-subject set was shared across four aggregated conditions (A: overall; B: partial occlusion/carrying; C: speed changes; D: smartphone use). Accuracy ranged from 0.658 to 0.749, with the lowest performance in B. Confusion-matrix–based error decomposition with subject-level bootstrap confidence intervals revealed pronounced sex-wise error asymmetry in B and C, driven by reduced male recall and increased male-to-female misclassification. In D, a simple arm-swing amplitude index was not significantly associated with prediction confidence or misclassification. Grad-CAM quantification further suggested that joint-group importance shifts across conditions, indicating condition-dependent reliance on motion cues.

Abstract: Background: Cubital Tunnel Syndrome (CuTS) is the second most common compressive neuropathy of the upper limb, traditionally associated with prolonged elbow flexion, trauma, or anatomical constraints. With the widespread adoption of smartphones, sustained upper-limb postures have emerged as potential novel risk factors for ulnar nerve compression. This retrospective study aimed to investigate the potential correlation between smartphone use patterns and the development of CuTS. Methods: A retrospective observational study was conducted on 100 subjects recruited between 2021 and 2024, including 50 patients with EMG-confirmed CuTS who underwent surgical decompression and 50 matched controls without clinical or electrophysiological evidence of ulnar neuropathy. Demographic variables, daily smartphone use (hours/day), predominant activity type, and habitual posture during device handling were collected through clinical records and questionnaires. Group comparisons were performed using t-tests and Chi-square analyses, with significance set at p < 0.05. Results: Daily smartphone use was higher in the CuTS group compared with controls (4.94 ± 1.8 vs. 4.04 ± 1.5 hours/day), although the difference did not reach statistical significance (p = 0.0716). Posture during device use showed a significant association with CuTS: 82% of affected patients reported using smartphones with the elbow flexed, compared with 56% of controls, whereas supportive postures were less frequent among CuTS patients (16% vs. 38%) (p = 0.019). No significant differences were found between groups regarding smartphone activity type (p = 0.858). Conclusions: Smartphone use may contribute to ulnar nerve compression primarily through ergonomically disadvantageous postures, particularly sustained elbow flexion, rather than total usage time. These findings highlight a modifiable behavioral risk factor relevant to the rising prevalence of CuTS in the digital era. Increased clinical attention to device-handling habits and public-health strategies promoting ergonomic posture may support CuTS prevention. Prospective and biomechanically informed studies are warranted to further elucidate causal mechanisms.

Abstract: Marijuana use in the United States (U.S.) has diversified alongside expanding legalization, yet little is known about the psychosocial factors that distinguish medical from recreational use. This study examined whether psychological distress mediates the association between perceived social isolation and marijuana use type among U.S. adults. We analyzed cross-sectional, nationally representative data from the 2024 Health Information National Trends Survey (HINTS, cycle 7). Marijuana use was categorized as medical (including medical and both medical/recreational) versus recreational. Perceived social isolation was measured using the Patient-Reported Outcomes Measurement Information System (PROMIS) Social Isolation t-score, and psychological distress was assessed with the Personal Health Questionnaire (PHQ)-4. Sur-vey-weighted descriptive analyses and a structural equation mediation model accounting for the complex sampling design were conducted. Medical marijuana users reported significantly higher levels of psychological distress and perceived social isolation than recreational users. Greater social isolation was strongly associated with higher psychological distress, and higher distress was associated with a greater likelihood of medical (vs. recreational) marijuana use. The indirect effect of social isolation on marijuana use type through psychological distress was statistically significant, while the direct effect of social isolation was not significant after accounting for distress. Overall, greater perceived social isolation predicted medical marijuana use primarily through elevated psychological distress. These findings suggest that medical marijuana use among U.S. adults may reflect coping with psychological distress linked to social disconnection, under-scoring the importance of integrating mental health and social context in-to clinical and public health approaches to cannabis use.

Abstract: Explainability is increasingly expected to support not only interpretation, but also accountability, human oversight, and auditability in high-risk Artificial Intelligence (AI) systems. However, in many deployments, explanations are generated as isolated technical reports, remaining weakly connected to decision provenance, governance actions, audit logs, and regulatory documentation. This short communication introduces XAI-Compliance-by-Design, a modular engineering framework for explainable artificial intelligence (XAI) systems that routes explainability outputs and related technical traces into structured, audit-ready evidence throughout the AI lifecycle, designed to align with key obligations under the European Union Artificial Intelligence Act (EU AI Act) and the General Data Protection Regulation (GDPR). The framework specifies (i) a modular architecture that separates technical evidence generation from governance consumption through explicit interface points for emitting, storing, and querying evidence, and (ii) a Technical–Regulatory Correspondence Matrix—a mapping table linking regulatory anchors to concrete evidence artefacts and governance triggers. As this communication does not report measured results, it also introduces an Evidence-by-Design evaluation protocol defining measurable indicators, baseline configurations, and required artefacts to enable reproducible empirical validation in future work. Overall, the contribution is a practical blueprint that clarifies what evidence must be produced, where it is generated in the pipeline, and how it supports continuous compliance and auditability efforts without relying on post-hoc explanations.

Abstract: This study addresses the challenge of accurately forecasting electricity load in Pakistan, focusing on the Faisalabad Electric Supply Company (FESCO). The load forecasting problem in this region is exacerbated by the highly volatile nature of the data and the low baseload, further complicated by external factors such as weather conditions. To tackle this issue, we utilized historical electricity load data from FESCO from 2019 to 2022 and weather data from NASA's LaRC POWER Project. Our approach involved comprehensive exploratory data analysis (EDA) to identify significant input features, including temperature, humidity, and lagged predictors like previous hour and previous day readings. We employed a range of deep learning models to develop and test prediction models like long short-term memory (LSTM), bidirectional LSTM (BiLSTM), and gated recurrent unit (GRU) networks. The analysis revealed that lagged predictors significantly enhance prediction accuracy, with BiLSTM models demonstrating the best performance, achieving a remarkably low mean absolute percentage error (MAPE) of 0.2%. Compared to other models, our approach using time-series data arrangement without external weather predictors proved to be more accurate and economical. This model can support effective power system planning and expansion, leading to the development of a competitive bidding-based wholesale energy market in Pakistan.

Abstract: Gravitational fingering often occurs for water flow in the vadose zone and accurate modeling of this important flow process remains a significant scientific challenge. This paper presents the latest theoretical developments of the optimality-based Active Region Model (ARM), a macroscopic framework developed for describing gravitational fingering flow in the vadose zone. ARM divides the soil into active (fingering) and in-active regions, introducing a relationship between water flux and hydraulic gradient derived from the principle of optimality that the system self-organizes to maximize water flow conductivity. Unlike traditional models, ARM’s hydraulic conductivity de-pends on both capillary pressure or water saturation and water flux, reflecting the un-stable nature of fingering flow. The paper provides an updated mathematical derivation of ARM relationships using calculus of variations and extends ARM to account for small water flux in the non-fingering zone, resulting in a dual-flow field model. These new developments should make ARM more rigorous and realistic for field-scale applications.

Abstract: The dystrophin gene encodes multiple dystrophin isoforms with tissue-specific functions, including several shorter isoforms expressed in the central nervous system and retina. While Duchenne muscular dystrophy (DMD) has historically been charac-terized as a primary myopathy resulting from loss of the full-length dystrophin Dp427, increasing clinical evidence indicates that dysfunction of shorter dystrophin isoforms contributes to significant extramuscular pathology, including retinal disease. In par-ticular, loss of the Dp71 isoform has been implicated in retinal inflammation, blood–retinal barrier breakdown, and pathological angiogenesis. In this study, we investigated whether low-level residual expression of Dp71 is sufficient to mitigate retinal inflammation in the mdx3Cv mouse model, which displays reduced—but not absent—expression of multiple dystrophin isoforms. Western blot analysis revealed that mdx3Cv retinas express approximately 4% of wild-type Dp71 protein levels. Despite this marked reduction, mdx3Cv mice did not exhibit the in-flammatory phenotype previously observed in Dp71-null mice. Retinal VEGF protein levels and VEGF receptor (FLT-1 and KDR) mRNA expression were preserved, while VEGF mRNA levels were modestly reduced. Furthermore, expression of inflammatory markers ICAM-1 and ALOX5AP, leukocyte adhesion to retinal vasculature, Aqua-porin-4 expression, and BRB permeability to albumin were all comparable to wild-type littermates. Together, these findings demonstrate that minimal residual expression of Dp71 is sufficient to preserve retinal vascular homeostasis and prevent inflammatory and permeability defects in the mdx3Cv retina. These results further suggest that partial dystrophin restoration—at levels achievable with current exon-skipping or gene-based therapies—may be adequate to prevent or attenuate retinal pathology in DMD, providing a realistic and clinically relevant therapeutic target.

Abstract: T-cell malignancies represent a complex spectrum of clinically and biologically heteroge-neous diseases. Effective translational research and drug development are critically de-pendent on preclinical models that faithfully recapitulate this diversity. This review ana-lyzes the current preclinical landscape, identifying a profound disparity between the clin-ical spectrum of T-cell neoplasms and the available in vitro tools. We demonstrate that the existing armamentarium of cell lines is heavily skewed, with an abundance of models for T-cell lymphoblastic leukemia/lymphoma (T-ALL), cutaneous T-cell lymphoma (CTCL), and anaplastic large cell lymphoma (ALCL). This skew is a direct result of a biological se-lection bias, as these entities are often driven by potent, TME-independent oncogenes (e.g., NOTCH1 mutations, NPM1-ALK fusions) conducive to immortalization. Conversely, the majority of peripheral T-cell lymphoma (PTCL) subtypes, which are frequently TME-dependent and clinically aggressive, remain "preclinical orphans" with few or no authenticated models. This "preclinical void" constitutes a major bottleneck, impeding mechanistic studies and therapeutic progress. We discuss the limitations of 2D cultures and highlight the necessity of adopting advanced platforms, such as patient-derived xen-ografts (PDX) and 3D organoid systems. These "avatar" models preserve vital tumor het-erogeneity and microenvironmental context, offering superior predictive value. The sys-tematic development and integration of these next-generation models are essential to bridge the translational gap and advance precision medicine for all patients with T-cell malignancies.

Abstract: Acne vulgaris remains a common condition, with current topical therapies often limited by suboptimal efficacy and tolerability. This study evaluated the efficacy and safety of two novel 1% hydrogen peroxide (H₂O₂) formulations, a cream-gel for facial and a sprayable lotion for truncal mild to moderate acne. 42 participants presenting facial acne and 41 with truncal acne were treated twice daily for 8 weeks. Efficacy was assessed using the Investigator’s Global Assessment (IGA), the Spanish Acne Severity Scale (EGAE), and lesion counts. After 56 days, facial acne severity improved significantly (IGA −26%, p=0.01; EGAE −31%, p=0.01), with reductions in papules (−45%, p=0.017), porphyrin count (−27%, p=0.04), sebum production (−75%, p=0.005), erythema (−35%, p=0.0001), and desquamation (−22%, p=0.02). Truncal acne severity also improved sig-nificantly (IGA −32%, p=0.001; EGAE −45%, p=0.001), with reductions in inflammatory lesions (−60%, p=0.001), porphyrin size and count (-55% and −48%, both p=0.001), ery-thema (−7%, p=0.005), and desquamation (−27%, p=0.001). Both formulations were ac-cepted by the users, with minimal local irritation and high patient satisfaction. Topical 1% H₂O₂ formulations demonstrated significant and well-tolerated efficacy in both fa-cial and truncal acne, supporting their potential as safe and patient-friendly options for managing mild to moderate acne.

Abstract: Background :Mas-related G-protein-coupled receptor b4 (Mrgprb4)-lineage neurons in the peripheral nervous system, were a type of C fibers in the hairy skin. Our prior work demonstrated that these neurons respond to both noxious and innocuous mechanical and thermal stimuli. Ablating them eliminates the pleasant sensation elicited by gentle pressure on the mouse nape. However, their potential role in mitigating pain and pain-related negative emotions in response to somatic stimuli remains unclear. Methods:Animal experiments investigated the pivotal role of Mrgprb4-lineage neurons in mediating the analgesic and anxiolytic effects of transcutaneous electrical nerve stimulation (TENS) applied to the Zusanli (ST36) acupoint. In vivo calcium imaging of lumbar 4 dorsal root ganglia (DRG) neurons in Mrgprb4-GCaMP6s transgenic mice characterized neuronal encode of distinct TENS intensities. Mechanical pain thresholds and anxiety-like behaviors were assessed in a CFA-induced mouse model of comorbid chronic pain and anxiety. To simulate TENS, optogenetic stimulation was applied to the ST36 acupoint in Mrgprb4-ChR2 mice; intrathecal viral injection specifically ablated L3-L5 Mrgprb4-lineage neurons, and TENS effects were evaluated with their gain- or loss-of-function manipulation. Results: 0.5 mA TENS on ST36 ameliorated pain and anxiety-like behaviors in model mice and activated Mrgprb4-lineage neurons. Photostimulation on ST36 induced analgesic and anxiolytic effect in comorbidity of chronic pain and anxiety model of Mrgprb4-ChR2 mice. Ablating these neurons attenuated the therapeutic effects of 0.5 mA TENS in model mice. Conclusion:These genetic engineering-assisted findings may deepen our understanding of the analgesic and anxiolytic effect and mechanism of somatic stimulation and further improve the clinical efficacy.

Abstract: Ambient gamma radiation is a key component of environmental radiation monitoring and is strongly modulated by atmospheric and meteorological processes. This study presents a long-term analysis of near-surface gamma radiation measured in Ponta Delgada (São Miguel Island, Azores), integrating continuous observations from the Portuguese National Alert Network for Environmental Radioactivity (RADNET) with meteorological data. The dataset spans more than a decade and includes a documented instrumental upgrade in 2020, which introduced enhanced sensitivity and radionu-clide identification capability. Results reveal pronounced variability across daily, seasonal, and interannual time-scales. A clear level shift is observed after 2020, attributable to the instrumental up-grade rather than to physical environmental changes, while the temporal structure and seasonal phasing of the series remain preserved. Seasonal analysis shows higher gamma radiation values during autumn and winter and lower values in late spring and summer, consistent with precipitation-driven washout and boundary-layer dy-namics. Generalized Additive Models (GAMs) highlight precipitation, wind speed, and relative humidity as dominant meteorological drivers acting through non-linear rela-tionships. Overall, the results support the use of ambient gamma radiation as an atmospheric in-dicator of boundary-layer processes and meteorological modulation in remote mari-time environments, extending its role beyond routine environmental surveillance.

Abstract: Background: Prognostic prediction for colorectal cancer patients with peritoneal metastasis remains challenging due to clinical and biological heterogeneity. We aimed to evaluate the utility of machine learning, comparing high-performance boosting models with interpretable regression approaches for overall survival (OS) prediction. Methods: We analyzed a multi-institutional registry cohort of 150 colorectal cancer patients with synchronous peritoneal metastases. A total of 124 variables were included; continuous variables were standardized, categorical variables were one-hot encoded, and missing values were imputed using the median. Models included XGBoost, LightGBM, Ridge regression, Lasso regression, and linear regression. Training was performed with 3-fold cross-validation, and hyperparameters were optimized using Optuna. Evaluation metrics included mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²). Model interpretability was assessed using SHAP values, LIME local explanations, and regression coefficients. Results: Boosting models consistently outperformed linear models. XGBoost achieved the best performance (MAE 424, RMSE 526, R² = 0.04), while LightGBM showed comparable accuracy. In contrast, Ridge, Lasso, and Linear regression yielded high errors (MAE > 900, RMSE > 1200) with negative R² values, indicating poor predictive ability. SHAP analysis highlighted systemic inflammation markers (CRP, BUN), surgical assessment of tumor depth, operative factors (time, bleeding), and peritoneal metastasis characteristics as major determinants of OS. LIME analyses further provided case-specific interpretability, identifying feature contributions in long-, intermediate-, and short-term survivors. Conclusion: Boosting models, particularly XGBoost, demonstrated superior performance compared with traditional regression models in predicting OS for colorectal cancer patients with peritoneal metastasis, although absolute predictive accuracy remains modest. Integration of SHAP and LIME linked model outputs with clinically plausible prognostic factors, enhancing interpretability. Ensemble learning may provide a promising adjunct for prognostic assessment and should be validated in larger, genomically enriched cohorts.

Abstract: The cytoplasmic accumulation of TDP-43 aggregates remains a persistent pathological hallmark of neurodegenerative diseases, including amyotrophic lateral sclerosis (ALS), frontotemporal dementia (FTD), and limbic predominant age-related TDP-43 encephalopathy. The cell’s natural clearance mechanisms, the Ubiquitin-Proteasome System (UPS) and the autophagy-lysosome pathway (ALP), frequently fail due to a ‘vicious cycle’ created by the sequestration of essential downstream components by aberrant TDP-43, which interrupts autophagic flux. Classical autophagic activators (e.g., rapamycin) often initiate the pathway but cannot address downstream bottlenecks due to flux failure. This review revisits classical strategies and discusses newer approaches to modulate TDP-43 clearance, including TFEB activators, PROTACs (proteolysis-targeting chimeras), and antisense oligonucleotides (ASOs). We propose that adopting multi-targeting strategies and developing better biomarkers are vital for clinical success.