The study assessed the health and economic implications as well as the cost-utility of implementing universal alcohol use disorder (AUD) screening in 15-74 years population at the primary healthcare level compared with the current practice of diagnosis and management of symptomatic AUD patients seeking formal healthcare. Model-based cost-utility analysis using a hybrid model comprising a decision tree and lifetime age- and gender-specific Markov models for alcohol attributable conditions, including road traffic accident injuries, alcohol-related liver disease and head and neck cancers. The analysis was undertaken from both an abridged societal (consideration of direct cost of care) and a societal (consideration of direct and indirect costs) perspective. India (national and sub-national level analysis). 15-74 years population segregated by gender. The intervention was 10-year annual population-based screening for alcohol use disorders using alcohol use disorder identification test by community health workers at primary care facilities. The comparator was 'usual care' scenario of diagnosis and management of symptomatic AUD patients, considering care seeking patterns in India. Differences in life years, quality-adjusted life years (QALYs), alcohol attributable deaths and morbidities, direct costs and indirect costs in the comparative scenarios, along with incremental cost-utility ratio (ICUR), benefit-cost ratio and net monetary benefit. ICUR was evaluated using the per-capita gross domestic product (GDP) threshold of ₹171 498 (US$2182), as per Indian economic evaluation guidelines. Probabilistic and deterministic sensitivity analysis was conducted to identify the parameters that are likely to have an impact on efficiency of the screening programme. The AUD universal screening programme was associated with a gain of 71.16 million QALYs at population level, with approximately one-fourth reduction in the incidence of alcohol-attributable conditions. The ICUR value indicated that the programme is likely to be cost-effective from an abridged societal perspective. The intervention is projected to generate a gain of ₹8.21 (US$1.03) trillion, equivalent to per year gain of 0.59% of GDP, based on the abridged societal perspective. The deterministic sensitivity analysis indicated that reductions in diagnostic accuracy of the screening method, prevalence of AUD and treatment coverage had an inverse impact on the ICURs and could impact efficiency of the programme. There is good health and economic evidence to support the integration of alcohol use disorder screening and management within routine primary care. It would be essential to deploy measures for effectiveness of the screening tool and continuity of care to enhance efficiency of the programme.
Light Detection and Ranging (LiDAR) three-dimensional (3D) object detection degrades under point sparsity, outliers, coordinate noise, and calibration drift, yet detector evaluation remains largely limited to clean benchmarks. This study focuses on sensing robustness rather than detector redesign. We introduce Bounded Graph Conditioning (BGC)-a deterministic pre-voxelization front-end that applies k-nearest-neighbor (kNN) neighborhood averaging with bounded residual correction upstream of an unchanged detector backbone. BGC is evaluated together with a reproducible sensor-degradation stress protocol and a risk-constrained operating-boundary analysis. Experiments on KITTI with PointPillars, SECOND, and Voxel R-CNN show that BGC most clearly improves retained detection quality and feasible operating coverage under strong noise and strong outlier stress; gains under other degradation types are smaller and backbone-dependent. In the primary score-level box-disjoint calibration/test evaluation on SECOND, maximum feasible coverage at a target risk bound of 0.2 improves from 0.0754 to 0.1374 under strong noise (σ=0.10 m) and from 0.1323 to 0.1591 under strong outliers (p=0.10); a cross-backbone check on Voxel R-CNN confirms the same direction (0.1860→0.2864). Comparison with traditional filtering (SOR and ROR) reveals complementary strengths across fault types. A range-adaptive BGC variant that adjusts parameters per distance bin further improves performance under mixed unknown faults, spherical-coordinate noise, and on a dataset-matched nuScenes validation (adaptive BGC mAP/NDS: 0.2687/0.4493 vs. baseline 0.2471/0.3846 under strong noise). Severe translation drift collapses all configurations to full rejection, exposing an explicit sensing boundary beyond the reach of local conditioning. These results support BGC as a practical sensor-side robustness enhancement under the studied degradation protocol, with conditional rather than universal applicability across backbones and fault types.
Bacteriophages are ubiquitous biological entities that profoundly influence microbiology research and biotechnology. Among coliphages, T1-like viruses (family Drexlerviridae) are notoriously known for their environmental stability and propensity to contaminate laboratory cultures and equipment. Despite this, the genomic features that may underlie their persistence and recurrent detection as laboratory contaminants remain insufficiently characterized. Here, we describe a novel T1-like bacteriophage, KanT1, identified as a recurrent contaminant emerging from environmental samples. Comparative genomics and phylogenetic analyses position KanT1 within the Tunavirus lineage, confirming its close relationship to canonical T1-like phages. Structure-informed annotation enabled the functional characterization of previously unannotated proteins, highlighting the importance of integrating structural predictions into phage genome analysis. Notably, we provide novel details regarding the distribution of superinfection exclusion cassette cor and identify an SH3 domain-containing protein associated with the lysis cassette. We show that SH3 is widespread, though non-universal, across Drexlerviridae genomes. Given the established role of SH3 domains as determinants of cell-wall binding specificity for endolysins of phages infecting Gram-positive bacteria, we propose that this protein represents an auxiliary component of the T1-like lysis module. Together, these findings expand the current understanding of T1-like phage genome organization and provide new insights into molecular features that may contribute to their broad host range and persistence in laboratory environments.
The domesticated silkworm (Bombyx mori) is an established model for investigating pesticide ecotoxicology in Lepidoptera. However, a systems-level integration of its molecular response networks across diverse pesticide classes is still lacking. This review synthesizes multi-omics, physiological, and biochemical data to construct a comprehensive framework for the toxicity of B. mori. Our analysis revealed that pesticide exposure universally disrupts energy homeostasis by inhibiting mitochondrial oxidative phosphorylation (OXPHOS) and dysregulating trehalose metabolism, culminating in severe ATP depletion. The resulting overproduction of ROS sequentially triggers major defense pathways, such as the PI3K/Akt, MAPK/CREB, and CncC/Keap1 pathways. These pathways coordinate the transcriptional activation of antioxidant enzymes and detoxification proteins, including P450s, GSTs, and CarEs, via ARE- and XRE-dependent mechanisms. Concurrently, pesticides induce autophagy-apoptosis crosstalk via calcium dysregulation and caspase cascade activation. This molecular disruption is compounded by the reshaping of the gut microbiota, characterized by the enrichment of opportunistic pathogens, such as Enterobacter, and the depletion of beneficial symbionts, such as Bifidobacterium, alongside the suppression of Toll/IMD/JAK-STAT immune signaling. This dual assault on immunity and metabolism creates a synergistic 'multi-hit' effect that dramatically increases susceptibility to pathogens, such as BmNPV. This integrated framework identifies the CncC-ARE axis, mitochondrial energy sensors, and gut microbiota-host interactions as central regulatory hubs and promising targets for intervention. By translating these mechanistic insights from silkworms to broader lepidopteran pests, this study provides a theoretical foundation for ecological risk assessment and biomarker discovery. Furthermore, it establishes a roadmap for developing targeted green pest management strategies with direct implications for advancing sustainable sericulture and precision pest control. © 2026 Society of Chemical Industry.
There are no unique and universally accepted procedures for the determination of the maximum and minimum void ratios, emax and emin. This issue is particularly pertinent in the characterisation of the alternative sustainable materials examined in this study: well-graded tyre-derived aggregate (TDA), recycled concrete aggregate (RCA) and their mixtures (RCA-TDA), with a rubber content by weight of ΧM = 11, 23 and 55%. Uniformly graded TDA-sand mixtures with ΧM = 0, 15, 27, 42, and 100% were also considered. The results from dry and moist samples were compared with void ratios obtained after Proctor compaction and static loading. It was found that, in contrast to vibration for sand and sand-TDA mixtures, the most efficient densification techniques involve impact compaction at the optimum water content for RCA and RCA-TDA and static loading for TDA. Inversion of dry RCA, TDA and RCA-TDA samples in a graduated cylinder was the most effective to consistently achieve emax but induced visible segregation. Unlike sand-rubber mixtures, well-graded RCA-TDA did not exhibit a threshold rubber content at which emax and emin fell below those of RCA and TDA alone, suggesting reduced segregation. The findings offer practical guidance for improving specimen preparation reproducibility in the laboratory.
Pulse-width-modulated (PWM) automotive headlights enhance nighttime event-based camera detection, yet systematic parameter optimization for vulnerable road user detection remains unexplored. This study evaluates PWM frequency, duty cycle, light distribution, ego-vehicle speed, and ambient lighting under European New Car Assessment Programme-inspired crossing scenarios for cyclist and pedestrian detection. Results establish performance ranging from substantial improvements to severe degradation relative to continuous illumination. Cyclist detection achieves robust performance with high-frequency modulation across light distributions, while low-frequency operation with low beam produces severe degradation through background noise accumulation. Pedestrian detection requires high beam with street lighting enabled; low beam universally fails regardless of modulation parameters. Limited parameter combinations achieve simultaneous improvements for both targets. Detection performs optimally on retroreflective surfaces, while low-reflectivity clothing limits capability, requiring target-specific optimization.
The apolipoprotein ε4 (APOE ε4) isoform directly alters cholesterol and immune biology and is associated with an increased risk of neurodegenerative and cardiometabolic disease in industrialized settings; nevertheless, APOE ε4-which is ancestral in humans-has persisted over evolutionary time. One potential explanation is that the costs and benefits of APOE ε4 were significantly different in the environments in which humans evolved compared to those we experience today. In support, previous work has suggested that living in a high pathogen environment, engaging in high levels of physical activity, or eating a low fat diet can dampen the detrimental effects of APOE ε4, and has revealed positive effects for fertility. However, direct tests of whether APOE isoforms are associated with different biological outcomes in non-industrial versus industrialized contexts are lacking. Working with the Turkana of Kenya and the Orang Asli of Peninsular Malaysia-two Indigenous groups in which individuals of shared ancestry span a continuum of subsistence, non-industrial to urban, industrialized lifestyles-we investigated how APOE genotypes impact cholesterol, immunological, and reproductive traits and tested for genotype x environment (GxE) interactions. First, we confirmed established genotype effects across lifestyles, showing that more APOE ε4 alleles are associated with higher total cholesterol, higher LDL cholesterol, and lower HDL cholesterol. Second, we tested for lifestyle interactions, finding lifestyle-dependent effects of genotype on innate immune biomarkers in the Orang Asli but not Turkana. Finally, we show that more APOE ε4 alleles are correlated with an extended reproductive lifespan, however this effect is relatively weak, is not consistent across populations, and does not correspond with a higher reproductive output. Together, our study provides evidence that industrialized environments can modify the biology of APOE ε4; however, we find that APOE ε4 is not universally beneficial in non-industrial contexts, highlighting the role of local environmental variation in determining its specific costs and benefits.
Nowadays, people spend over 80% of their lives indoors, which makes indoor air quality (IAQ) research important. The paper presents, firstly, a structured overview of publicly available IAQ datasets suitable for machine learning (ML) research, secondly, a comparative analysis of the reviewed datasets, thirdly, an ML-oriented mapping between tasks and algorithms, to outline the algorithmic families that are most appropriate given the dataset structure and the prediction target, and fourthly, an investigation on IAQ-ML using custom-made solutions that include sensors for data acquisition. The methodology included an analysis of 1162 papers from the Web of Science, 1536 from Scopus, and 756 from IEEE Xplore, between 1 January 2020 and 31 December 2025, to capture recent trends in ML-based IAQ research. The findings show that linear regression (132 articles), Logistic regression (91), random forest-RF (77), Long Short-Term Memory-LSTM (77), Principal Component Analysis (63), and Elastic Net are the most popular among researchers. Most studies report accuracy over 90%, with maximum values of 99.37% for LSTM and 99.20% for RF. In the case of regression, the R2 values range between 82% and 98%, especially for CO2 and PM2.5 prediction. eXtreme Gradient Boosting or hybrid RF-LSTM architectures achieve R2 values of up to 99%. The IAQ public and private datasets analyzed for this study provide a strong foundation for transfer learning, but differences require careful preprocessing to ensure consistent comparisons and reliable conclusions. The distribution of articles by sensor type for IAQ parameters shows that linear regression remains the most widely used ML method (26 studies), followed by LSTM (19) and RF (18). The research results confirm that there is no universal algorithm for IAQ, and the quality and structure of the data contribute to the success of ML models. This study aims to be a foundation for the development of future intelligent IAQ monitoring systems.
While both Urbach tails and dangling bonds are known to be present in a-Si films, the current literature lacks parametrization that simultaneously accounts for both types of defects using only transmittance spectra, reflectance spectra, or spectroscopic ellipsometry. To address this issue, we performed parametrizations of three magnetron-sputtered a-Si thin films deposited on glass substrates at different low pressures of argon gas, using only their measured UV-Vis-NIR transmittance spectra T(λ = [300, 2500] nm) and different dispersion models. We preprocessed T(λ) by suppressing both general and bandpass noise to yield the spectrum Td(λ). The films were parametrized from Td(λ) using two versions of the Tauc-Lorentz-Urbach dispersion model and the universal dispersion model (UDM) of Franta. The most accurate parametrization was achieved employing UDM including Urbach tail and three subgap oscillators. JDOS and the dielectric function ε(E) were computed by this UDM, and it was concluded that these three oscillators correspond to electron transitions via two bands of dangling bonds. The respective DOS is similar to the DOS previously reported for a-Si:H, but not to a-Si, indicating a relatively low density of dangling bonds in our a-Si films. Record low parametrization errors are achieved, which confirms the accuracy of these results.
Imidodiphosphorimidate (IDPi) has emerged as a powerful chiral organocatalyst featuring a specially designed cavity constructed by aryl group-substituted BINOL units. Despite extensive applications of IDPi in asymmetric reactions, the understanding of its structure-selectivity relationship (SSR) remains underdeveloped. In this study, we employed aryl fragment descriptors for the statistical modeling of IDPi-catalyzed asymmetric reactions, offering a cost-effective and efficient approach to explore the SSR of IDPi. Specifically, site parameters of remote sp2 carbon atoms were defined to capture the features of the distal ring of the aryl substituents. The established statistical models of IDPi-catalyzed cyanosilylation reactions align well with the mechanistic understandings of the crucial role of C-H···π and cation-π interactions between the distal ring of IDPi and substrate in stereo-control. More selective catalysts for the challenging cyanosilylation reaction of 3-hexanone were successfully identified by using these descriptors to define and screen the chemical space of IDPi catalysts. This work not only enriches our understanding of the SSR of IDPi catalysts but also highlights the potential application of aryl fragment and remote site parameters as universal descriptors for IDPi in statistical modeling.
This study evaluated how the addition of 5 wt% bioactive glass and 15 wt% short glass fibers to EQUIA Forte HT affects the microhardness, micromorphology, and elemental composition of demineralized dentin. Class I cavities in 28 human third molars were demineralized with 37% phosphoric acid and restored with: (1) Filtek Universal composite, (2) EQUIA Forte HT, (3) EQUIA Forte HT + 5wt% BAG, or (4) EQUIA Forte HT + 15wt% short glass fibers. After 4 weeks of storage in phosphate-buffered saline at 37 °C, the teeth were cut in half, obtaining two samples from each tooth (n = 14). Vickers microhardness (HV0.1) was measured on demineralized dentin 50-100 μm apical to the restoration interface. Representative specimens (n = 2) were examined using scanning electron microscopy (SEM) and energy-dispersive X-ray spectroscopy (EDS). Data were analyzed with one-way ANOVA (α = 0.05). Unmodified EQUIA Forte HT showed the highest mean dentin microhardness recovery (25.06 ± 1.42 HV0.1), followed by composite (17.31 ± 0.66 HV0.1), BAG-modified (23.74 ± 1.37 HV0.1) and fiber-reinforced (22.15 ± 1.06 HV0.1) groups (p < 0.001, all pairwise comparisons p ≤ 0.039). Glass hybrids showed prominent Ca/P peaks; modified groups had elevated Si (BAG) and Al (fibers). SEM revealed smoother surfaces with fewer cracks in modified materials. Unmodified EQUIA Forte HT produced the highest short-term microhardness recovery, while BAG and fiber additions altered surface morphology and elemental composition but slightly reduced early hardness.
Background: Sex estimation represents a pivotal element of forensic anthropological investigation, conventionally dependent on highly dimorphic skeletal components such as the pelvis and skull. The purpose of the current study was to systematically evaluate the diagnostic accuracy of sternal measurements for sex estimation and to identify methodological- or population-based moderators that influence classification performance. Methods: A systematic review and meta-analysis were conducted in accordance with PRISMA 2020 guidelines. R programming software was used to perform statistical meta-analysis. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), likelihood ratios (LR±), and overall accuracy were calculated using random-effects meta-analysis. Subgroup analyses and meta-regression were performed based on population origin, study design, statistical approach, and measurement protocol. Results: Forty-one studies comprising 293 predictive models were included. The overall pooled sensitivity and specificity were 80.9% (95% CI: 79.7-82.1) and 74.0% (95% CI: 72.4-75.5), respectively, with a mean accuracy of 77.3%. Subgroup analysis revealed that studies involving African populations and imaging-based methods achieved the highest accuracy. Machine learning- and ROC-based methods outperformed traditional discriminant analysis. Combined sternal measurements (manubrium and body) yielded the most robust diagnostic performance (accuracy: 87.3%). Significant heterogeneity (I2 > 85%) was observed. Conclusions: Sternal morphometry exhibits a moderate to high degree of diagnostic accuracy in sex estimation and possesses significant forensic importance, especially in situations where more sexually dimorphic features are inaccessible. Nonetheless, variations across populations, the absence of standardized protocols, and methodological heterogeneity constrain its universal applicability.
Whole-body estrogen receptor α (ERα) knockout mice develop hepatic steatosis; however, liver-specific ERα knockout (LERKO) mice fail to recapitulate this susceptibility and maintain normal hepatic mitochondrial function. However, estrogen-mediated protection against hepatic steatosis is lost in LERKO mice following ovariectomy (OVX). Here, we tested whether loss of hepatic ERα blunts estrogen modulation of hepatic mitochondrial respiratory capacity and mitochondrial proteome following ovariectomy (OVX). Sham or ovariectomy (OVX) surgery was performed in middle-aged female mice (36-40 weeks), followed by AAV injection to generate Control (Con; GFP) or LERKO mice (Cre). All mice were placed on a high-fat diet (HFD) for 10 weeks following surgery. Half of the OVX mice received 17-beta estradiol (E2) replacement (OVX+E2) for the last 4 weeks of HFD. OVX mice had greater body mass and adiposity, which was reversed by E2 replacement in both Con and LERKO mice. While E2 replacement reduced steatosis in both Con and LERKO OVX mice, the LERKO OVX mice maintained greater hepatic triglyceride content. E2 replacement promoted greater basal and ADP-stimulated (State 3) mitochondrial respiration in Con OVX but not in LERKO OVX mice under palmitate-supported conditions. Changes in mitochondrial respiration could not be attributed to altered responses to changes in energy demand (G ATP ) or to alterations in mitochondrial H 2 O 2 production. Conversely, maximal coupled branched-chain amino acid-supported respiration was universally suppressed by E2 replacement. Proteomics analysis revealed E2-mediated reductions in hepatic mitochondrial energy transduction, with relatively minimal differences between Con and LERKO mice. In conclusion, post-ovariectomy estrogen treatment reduces steatosis in the absence of hepatic ERα; however, triglyceride levels remain higher, and mitochondrial respiratory deficits persist despite similar proteomic signatures, suggesting that ERα signaling is required for optimal estrogen hepatic responsiveness.
The use of resin-based composite imitating gum tissue enhances the aesthetics of fillings located below the physiological gum line. The shear bond strength (SBS) between the gum-imitating composite and the traditional composite with different surface preparation methods was examined. The aim of the study was to evaluate which base material-G-aenial Universal Injectable (GC, Japan, flow) or G-aenial A'CHORD (GC, Japan, paste)-performs better, as well as to determine the most effective preparation method among sandpaper (control), 36% orthophosphoric acid (H3PO4), sandblasting, and 9.5% hydrofluoric acid (HF). The tested gum-imitating material was Amaris Gingiva (VOCO, Germany). The connection between the composites was evaluated using a Z005 (Zwick-Roell) universal device. Surface tests were carried out using an SJ-410 (Mitutoyo) profilometer. Evaluation of the prepared surface structures was performed using scanning electron microscopy (HITACHI S-4700). Etching with HF significantly improved the shear bond strength between composites. Sandblasting also enhanced the adhesion results, but the H3PO4 group achieved comparable results to the control group. However, since HF is not recommended for intraoral use, sandblasting (30 μm aluminum oxide particles applied with three passes at constant speed under a pressure of 2 bar from 1.5 cm) appears to be the most suitable clinical alternative.
Mental healthcare has emerged as a major public health issue in the aftermath of COVID-19 worldwide due to global health system challenges which hinder effective healthcare. In this, there is a knowledge gap on research exploring the perceived quality of mental healthcare amongst hospital-based health workers with a particular focus on knowledge and practice, organization and system, and job satisfaction factors for an insight towards strengthening ongoing effort for the realization of the universal health coverage goal of the comprehensive global mental health action plans. The aim of this study was to assess health workers' perceptions of quality in mental healthcare at three district hospitals in Johannesburg, South Africa. An exploratory cross-sectional research design was used on a stratified random sample of 160 health workers recruited as participants at the three selected hospitals in Johannesburg. Data were collected using a self-administered questionnaire and then subjected to descriptive statistical analysis using SPSS Version 29. It was established that healthcare workers' at the three district hospitals in Johannesburg were generally familiar with mental health guidelines and mental disorders which resulted in better patient engagement and prioritisation of mental health as being important as physical health. However the majority of these healthcare workers perceived the quality of mental healthcare at the three hospitals was low. Further assessment however revealed that these perceptions may have emanated from organizational and system incapacity, and limited satisfaction with compensation and benefits, recognition for work done and limited training. Health worker perceptions of quality in mental healthcare help provide an insight into what health systems may need to address mental health service delivery. The study of the three hospitals in Johannesburg, South Africa underscore the need to reinforce knowledge sharing through healthcare worker training, strengthen organisational and system capacity, provide adequate remuneration and benefits, and reinforce clear referral pathways and collaboration with specialists for the realisation of quality improvement and sustenance in pursuing the universal health coverage goal of the WHO Comprehensive Mental Health Action Plans and the Sustainable development Agenda on health of 2030 and beyond.
Blood is a key component of organisms, serving numerous functions, including metabolism, innate and humoral responses, and hemostasis. Variations in hematological parameters can indicate the presence of infectious and non-infectious diseases, chronic stress, and other pathological or physiological conditions. Complete blood count testing is common in human and veterinary medicine and, when combined with clinical examination, contributes to disease diagnosis and prognosis and the monitoring of therapeutic progression. Nevertheless, hematological analysis is not routinely performed in sheep due to the lack of case-specific reference intervals, complicating the interpretation of the results. Indeed, hematological parameters may be affected by various non-pathological (environmental, genetic, physiological) and pathological factors, and they require further understanding and relevant adjustments to be universally applicable. Therefore, the objective of this paper is to summarize the existing literature and describe how various pathological and non-pathological factors affect hematological parameters in sheep, thereby supporting their incorporation into health management practices.
Universal Credit (UC) was a large-scale reform of the UK welfare system, replacing six existing benefits. UC aimed to simplify claims and encourage more claimants into work. Previous research has found evidence of harm to the mental health of recipients, potentially exacerbating existing health inequalities. We identify the effect of UC on self-reported measures of psychological well-being, treating the phased rollout from 2013 to 2018 as a natural experiment. We estimated differences in psychological well-being outcomes associated with the staggered introduction of the UC across local authorities, using areas where UC was not yet available as controls. We included working-age (aged 18-64 years) respondents of the Annual Population Survey in Great Britain from 2012 to 2019 (n=245 658), living in low-income households. We used the four self-reported measures of psychological well-being recorded in the survey: Life Satisfaction, Happiness, Life Worthwhile and Anxiety. We tested for differential effects by disability, age, caring responsibilities, sex, country, ethnicity, education and household structure. UC was associated with per-claimant decreases in Life Satisfaction (-0.66; 95% CI -1.01 to -‍0.30), Happiness (-‍0.41; 95% CI -‍0.77 to -0.05) and Life Worthwhile (-0.73; 95% CI -1.03 to -‍0.42), and increases in Anxiety (+0.79; 95% CI 0.30 to 1.27). These changes were 2-6 times as large as the effects on well-being of the COVID-19 pandemic. Respondents in Wales and Scotland saw comparatively greater effects compared with those in England across several outcomes. UC exposure saw greater comparative increases in anxiety among people with disabilities (+0.19; 95% CI 0.12 to 0.27), single people (+0.13; 95% CI 0.06 to 0.21) and people aged under 25 years (+0.27; 95% CI 0.15 to 0.39). The introduction of UC had adverse effects across all four measures of well-being. Vulnerable groups typically experienced greater harms, reinforcing calls for reforms to UC to reduce the health and well-being impacts of poverty and unemployment.
Uveal melanoma (UM) is the most common primary intraocular malignant tumor among adults and has a high risk of metastasis. Recently, artificial intelligence (AI) tools have been developed to support the management of UM across different clinical tasks. The definition of ground truth, the reference standard that models use in training and development, greatly influences the performance and clinical relevance of the models. Currently, there is limited consensus regarding which ground truth methods are most appropriate for each clinical application. This review aims to evaluate the advantages and limitations of available ground truth options in UM and proposes task-specific recommendations based on clinical utility, feasibility, and cost. A narrative review of the existing literature was conducted to identify and evaluate commonly used ground truth methods for UM AI applications based on factors such as time, cost, invasiveness, and required level of expertise. Each ground truth method offers distinct benefits and drawbacks in relation to biological precision, invasiveness, availability, cost, and turnaround time. No single ground truth is universally optimal across all applications. Instead, the ideal choice depends on the intended clinical task, and practical alternatives exist to mitigate the constraints that result from limited time and institutional resources. The selection of ground truth for AI models in UM should be chosen based on the specific clinical task to balance predictive relevance with feasibility of implementation. The adoption of task-specific ground truth standards may improve the development of clinically meaningful AI tools and facilitate their integration into real-world practice.
Acinetobacter baumannii is a leading nosocomial pathogen in intensive care units (ICUs), often resistant to multiple antibiotics. Data from the Baltic region remain scarce, limiting infection control and stewardship strategies. We conducted an integrated phenotypic-genotypic analysis of A. baumannii isolates collected from ICU patients in a tertiary-care hospital in Latvia (July 2022-June 2024). Antimicrobial susceptibility testing was performed for major antibiotic classes, and whole-genome sequencing (WGS) was used to identify genomic resistance determinants. We analysed 52 clinical isolates from 45 ICU patients. Multidrug resistance was nearly universal (98%), with complete resistance to carbapenems and fluoroquinolones and > 95% resistance to aminoglycosides and trimethoprim-sulfamethoxazole. Colistin activity was largely preserved, with resistance detected in only one isolate, despite widespread polymyxin resistance-associated mutations. Genotypic findings were mostly in line with the phenotypic results. All isolates belonged to the ST2 lineage, highlighting clonal homogeneity. No plasmid replicons were detected, suggesting chromosomal elements as the primary resistance drivers. Our first integrated dataset in an ICU setting from the Baltic region demonstrates alarming resistance levels and clonal dominance of ST2. Our findings highlight the importance of combining WGS with susceptibility testing for accurate resistance assessment.
This paper discusses ways to improve the kinematic accuracy of worm gears in batch production. Worm gears are used in applications where high positioning accuracy, uniform motion and vibration damping is required. The paper focuses on three main methods: design changes, manufacturing process improvements and assembly optimization. Design changes aim to reduce dimensional and shape deviations of worm and worm wheel surfaces, with focus on the axially flexible worm design, which allows for minimizing backlash without disassembly. Manufacturing refinements, especially helical surface grinding, improve gear accuracy and durability. The developed algorithm for small batch production allows for selecting components based on specific criteria and thus improves overall production quality. With respect to optimization, the backlash ranges between 2 and 22 micrometers, meaning that its entire range is 20 micrometers. However, after optimizing, the backlash range falls between 7 and 10 micrometers, depending on the criterion for optimization, which amounts to about 50 to 65 percent of the initial range. The methods and algorithms are universal and can be used in small batch and large scale production. They bring economic benefits by reducing production costs and downtime through easy backlash adjustment.