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Zoonotic endoparasites and Toxoplasma gondii seropositivity in free-roaming cats (Felis catus) from New York City boroughs

Free-roaming cats ( Felis catus ) can serve as reservoirs of various zoonotic parasites in urban settings. Despite a large population of free-roaming cats around New York City, studies assessing the prevalence and shedding of various parasites in the New York urban landscape are scarce. This study utilized fecal and blood samples opportunistically collected during the Trap Neuter Return (TNR) program from 87 free-roaming cats in New York City between May and July 2023. Samples were analyzed using centrifugal fecal flotation, coproantigen immunoassays, serologic assays, and PCR-based assays for gastrointestinal and vector-borne parasites. Fecal flotation (n = 87) results revealed that 57.5% (50/87; 95% CI: 46.9–67.4) of cats were infected with at least one species of parasite. The most prevalent infection was Toxocara spp. (54%; 95% CI: 43.4–64.3), followed by Ancylostoma spp. (13.8%; 95% CI: 8.2–22.6) and coccidia (11.5%; 95% CI: 6.4–19.9). Coproantigen testing (n = 43) identified Giardia spp. in 11.6% (5/43; 95% CI: 5.1–24.5) and Cryptosporidium spp. in 2.3% (1/43; 95% CI: 0.4–12.1) of cats. Antibodies to Toxoplasma gondii were detected in 8.9% (4/45; 95% CI: 3.5–20.7) of serum samples; no Dirofilaria immitis antigen and Cytauxzoon felis DNA were found in the blood samples (n = 45). Male cats were significantly more likely to be infected with Toxocara spp. (OR = 4.36) and, along with juvenile cats (<1 year), shed significantly higher numbers of eggs (p < 0.05), identifying young males as high-intensity “super-shedders” driving environmental contamination. The high prevalence of zoonotic helminths, particularly Toxocara spp., underscores the public health risks associated with unmanaged feline populations in densely populated urban centers. These findings highlight the utility of integrating disease surveillance into TNR programs to monitor urban ecosystem health and mitigate zoonotic risks.

Aggression and fear of missing out as mediators between problematic smartphone use and psychological distress among Moroccan high school students

Cryo-EM structures of naturally occurring dimeric photosystem II complexes lacking the Mn4CaO5 cluster

Diagnostic accuracy, operational feasibility, and cost considerations of Truenat MTB Plus and Xpert MTB/RIF Ultra for pulmonary tuberculosis

Background Tuberculosis (TB) remains a major global health challenge, necessitating rapid and accurate diagnostic tools. The World Health Organization (WHO) endorses nucleic acid amplification tests (NAATs) like Truenat MTB Plus and Xpert MTB/RIF Ultra. While both are widely implemented, direct comparisons integrating diagnostic accuracy with operational and cost considerations across real-world settings are limited. This study aimed to compare the diagnostic accuracy of Truenat MTB Plus and Xpert MTB/RIF Ultra for the detection of Mycobacterium tuberculosis (MTB) and rifampicin resistance (RIF-R) among presumptive pulmonary TB patients in India, while also assessing their operational feasibility and cost-related parameters. Methods This prospective diagnostic accuracy study was conducted at New Delhi Tuberculosis Centre, in New Delhi, India, enrolling 664 presumptive pulmonary TB patients. Paired sputum specimens were tested using Truenat MTB Plus/MTB-RIF and Xpert MTB/RIF Ultra. Mycobacterial culture was used as the primary reference standard for MTB detection, and phenotypic drug susceptibility testing (pDST) was used for RIF-R detection. Sensitivity, specificity, and overall accuracy were calculated, and operational parameters, including invalid/indeterminate rates and cost per test, were recorded. Results The overall prevalence of culture-confirmed TB was 14.8% (98/664), with a RIF-R prevalence of 7.1% (7/98). Compared with culture, Xpert MTB/RIF Ultra demonstrated a sensitivity of 97.9% (95% CI: 95.2–100%) and a specificity of 95.5% (95% CI: 93.7–97.3%). Truenat MTB Plus showed a sensitivity of 92.5% (95% CI: 85.1–96.6%) and a specificity of 90.1% (95% CI: 86.8–92.6%). For RIF-R detection, Xpert Ultra had a sensitivity of 83.3% and a specificity of 100%, compared to Truenat MTB-RIF’s sensitivity of 75.0% and specificity of 100%. Operationally, Truenat had a significantly higher rate of invalid results (5.9% vs 0%) and RIF indeterminate results (46.5% vs 13.2%) compared to Xpert Ultra, resulting in an increased need for repeat testing. The cost per test was lower for Truenat (approximately INR 800 for MTB Plus) compared to Xpert MTB/RIF Ultra (approximately INR 1800). Conclusion Both Truenat MTB Plus and Xpert MTB/RIF Ultra demonstrated excellent diagnostic accuracy for TB detection. Xpert Ultra showed superior accuracy and lower indeterminate rates, while Truenat offers substantial operational and cost advantages for decentralized deployment; however, higher rates of invalid and indeterminate results may increase operational burden due to repeat testing. These findings support a tiered diagnostic approach, leveraging the strengths of both platforms to expand molecular testing access and accelerate progress toward global TB elimination goals.

A vision-based sign language recognition & voice conversion system for inclusive communication

Targeting and antioxidant surface-engineered mesenchymal stromal cells for enhanced erectile dysfunction therapy

Recognizing distance-count matrices

Axiomatizing centrality measures often requires proving that certain properties do not hold by exhibiting a counterexample (i.e., a graph for which a given centrality measure does not satisfy a specified property). In the context of geometric centralities, constructing such counterexamples requires building a graph with prescribed distance counts, as encoded in its distance-count matrix (DCM). We prove that deciding whether a matrix is the distance-count matrix of an undirected graph is strongly NP-complete. This negative result implies that a brute-force approach to constructing such counterexamples is out of the question. We complement this negative result with some positive findings: while recognizing DCM matrices is strongly NP-hard, the construction of DCM matrices is algorithmically well-behaved under some natural graph operations (which we call DCM-stable ): that is, for many important graph operations ⊗, the DCM of G ⊗ H can be computed efficiently from those of G and H , without having to reconstruct the graphs themselves. This observation shows that, although the inverse problem is intractable in general, distance-count matrices admit a rich and tractable compositional theory on structured graph classes generated by DCM-stable operations.

Effectiveness of a multidisciplinary “crisis checklist” on nursing performance during intraoperative cardiac arrest: A simulation-based study

A general strategy for access intrinsically antioxidant polyolefins

A lab-scale prototype development of Lignin-Formaldehyde (LF) resin: A bio-renewable adhesive for wood panel industries

This study evaluated laboratory-prepared wood adhesives synthesized from alkaline lignins isolated from three locally available biomasses: chir pine needles (CP), eucalyptus sawdust (ESD), and sugarcane bagasse (SB). After alkaline extraction, each lignin was reacted with formaldehyde under alkaline conditions to synthesize resol-type lignin-formaldehyde resins under a complete phenol-replacement system. The Lignins differed in molecular weight, extraction yield, and hydroxyl distribution. Quantitative 31 P NMR showed total OH + COOH contents of 3.70 mmol g -1 for CP, 4.60 mmol g -1 for ESD, and 4.83 mmol g -1 for SB. Thermogravimetric analysis indicated comparable thermal stability among the lignins, with char yields of 19.22–24.23% at 1000°C. The lignin formaldehyde (LF) resin showed alkaline pH, workable solid content, 3–4shear-thinning viscosity, and gel times suitable for laboratory hot pressing. Differential scanning calorimetry confirmed curing in the hot-pressing temperature range, with CP resin showing the highest glass transition temperature. In lap-shear testing, the laboratory phenol formaldehyde (PF) control showed the highest dry and wet strengths, while CP performed best among the LF resins, followed by ESD and SB. The results show that adhesive performance was not governed by total hydroxyl content alone. Instead, feedstock-dependent lignin structure, hydroxyl distribution, molecular size, and cured-network development jointly influenced bond strength and moisture resistance. The study supports the laboratory-scale potential of Pakistani biomass residues for lower-phenol wood adhesive development, while further work is needed on residual carbohydrates, panel formaldehyde emissions, commercial PF benchmarking, and scale-up feasibility.

Clinical outcomes and treatment costs of endoscopic-first strategy compared with emergency surgery for sigmoid volvulus in a multicenter retrospective study

TREM1 signaling amplifies neutrophil-mediated inflammation in inflammatory bowel disease

Explainability in action: A metric-driven assessment of local explanations for healthcare tabular models

Explainable AI (XAI) is increasingly used in clinical machine learning, yet quantitative evaluation of explanation quality is often reported inconsistently across methods and datasets. We present a reproducible, metric-driven framework for evaluating XAI methods on healthcare tabular data. The framework consolidates six established, family-specific metrics, fidelity, simplicity, consistency, robustness, precision, and coverage, into explicit equations; pairs them with a pre-specified focal-model protocol; and releases open-source code with a method–metric applicability map. We evaluate LIME, SHAP, Anchors, EBM, and TabNet across four public healthcare tabular datasets. Post-hoc explainers are applied to a single selected Random Forest focal predictor to control model-induced variability, whereas EBM and TabNet are assessed through their native interpretability mechanisms. Global explanation summaries are reported descriptively only. The results show that SHAP/TreeSHAP provides exact score reconstruction for the Random Forest setting, while LIME produces simpler but lower-fidelity explanations with greater instance-level variability. LIME and SHAP show the strongest rank agreement among the evaluated pairs, although agreement varies across datasets. TabNet often yields compact native explanations, but these must be interpreted alongside its dataset-specific predictive performance. EBM and TabNet show low sensitivity under the fixed Gaussian-jitter robustness protocol, while Anchors produces high-precision rules with reduced coverage at stricter thresholds. Overall, the framework enables controlled comparison under explicit method–metric and focal-model assumptions, supporting more transparent XAI selection for tabular machine learning. Although demonstrated in healthcare, the framework is transferable to other high-stakes tabular domains. Source code: https://github.com/matifq/XAI_Tab_Health .

Age-dependent prognostic value of biological age for metastasis and survival in gastrointestinal cancer

System-level assessment of dynamic reconfiguration for lifetime and cost outcomes in electric vehicle battery packs

Abstract The electrification of transport relies heavily on lithium-ion batteries, yet conventional fixed-configuration battery packs suffer from structural inefficiencies such as cell-to-cell variability and premature failure. Dynamic battery reconfiguration, enabled by intelligent control of switching hardware around individual cells, provides an alternative pack architecture. Here we present a systematic, battery technology-agnostic evaluation of the lifetime and economic benefits of reconfigurable battery packs using a statistically grounded framework based on detailed cell modelling across diverse design and usage conditions. We show that reconfigurable battery packs can extend battery lifetime by over 20%, particularly in high-voltage applications such as electric trucks and long-range passenger vehicles. Despite higher upfront costs, reconfigurable packs can reduce lifetime cost by deferring replacements and retaining greater residual value. A sensitivity analysis identifies robust thresholds for economic viability: battery capacities above approximately 50 kWh, annual driving distances below 12,150 km, and additional upfront costs under 7.16%. These findings position dynamic reconfiguration as a scalable, cost-optimised architecture for next-generation battery platforms, and provide a quantitative foundation for future hardware design, management software, and life-cycle sustainability assessments.

Determinants of HIV testing uptake among adolescent girls and young women in mainland Tanzania: A stratified analysis of the 2016/17 and 2022/2023 national surveys

Background Adolescent girls and young women (AGYW) are disproportionately vulnerable to HIV. Despite expanded HIV testing services (HTS), the majority of AGYW remain unaware of their HIV status. This study aimed to assess determinants of HIV testing uptake among AGYW in mainland Tanzania before and after stratifying by age group (15–19 and 20–24 years) using data from two national surveys conducted over time. Methods The data from the Tanzania HIV Impact Surveys (2016/17 and 2022/23), collected using multi-stage stratified sampling, were analyzed on 12,714 adolescent girls and young women. Data analysis was performed using STATA version 17. Weighted Modified Poisson regression models with robust standard error were fitted to identify factors associated with HIV testing uptake before and after stratifying by age group (15–19 and 20–24 years). Results were presented as adjusted prevalence ratio (APR) with a 95% confidence interval. Results HIV testing uptake among adolescents remained stable at 40% in both the 2016/17 and 2022/23 surveys, while it increased among young women from 86% to 90% over the same period. Several factors were consistently associated with a higher prevalence of HIV testing uptake in both groups. Being in a union was more strongly associated with testing among adolescents (aPR = 1.52, 95% CI: 1.38–1.68) compared with young adults (aPR = 1.12, 95% CI: 1.07–1.17). Similarly, having secondary or higher education was associated with increased testing among adolescents (aPR = 1.22, 95% CI: 1.04–1.43) and young adults (aPR = 1.15, 95% CI: 1.06–1.25). A history of sexually transmitted infections (STIs) was also strongly associated with HIV testing uptake, particularly among adolescents (aPR = 1.53, 95% CI: 1.41–1.64), compared with young adults (aPR = 1.12, 95% CI: 1.09–1.15). Conclusions HIV testing uptake among AGYW in Tanzania has improved over time, with significant disparities between adolescents and young women. These findings highlight the need for age-specific strategies, intensifying adolescent-focused interventions while sustaining efforts among young women and reinforcing integrated reproductive health and HIV services.

A decentralized authorization framework for medical data protection in NDN-based healthcare systems

Abstract In recent years, there has been a significant shift from host-centric to data-centric networking across various digital sectors and critical environments. Named data networking (NDN) is the most prominent paradigm of data-centric networking implemented in real-world applications. The healthcare industry is considered one of the most prominent sectors to have adapted to this transformation. While NDN-based healthcare systems have demonstrated significant advances in building data-centric security frameworks, the expansion of interconnected medical systems has introduced novel security breaches, such as unauthorized access to medical data. Therefore, continuous improvements to access control mechanisms in NDN-based healthcare systems are extremely important. Most of the existing NDN-based access control mechanisms lack comprehensive integration of security deployment, in-network caching, and distributed content retrieval. To address this issue, this study proposes a decentralized authorization framework for NDN-based healthcare systems, providing fine-grained access control to medical data. The proposed framework integrates a smart contract-based access control (SCBAC) mechanism to provide an attribute-based and policy-driven enforced data access approach and proxy re-encryption (PRE) to enable secure delegation of decryption rights without exposing original data. The evaluation of the proposed framework encompassed three main aspects: performance, security, and scalability, under three different load conditions for scalability testing. The results of the simulation experiments show that the proposed framework achieves a response time of around 132 ms, maintains more than 94% accuracy in access success and denial rates, and accurately delegates to authorized entities with 97.4%-96.5% accuracy, while incurring re-encryption overhead of up to 8 ms. These outcomes improve the response to multiple cyber threats, including unauthorized access and breaches of medical data in dynamic NDN-based healthcare environments.

Unlocking the capacity of Mn-based Prussian blue cathodes in capacitive deionization

Compression benchmarking of holotomography data using OME-Zarr format

Holotomography (HT) is a label-free, three-dimensional quantitative phase imaging technique that captures refractive index distributions of biological samples at sub-micron resolution. As modern HT systems enable high-throughput and large-scale acquisition, they produce terabyte-scale datasets that require efficient data management. This study presents a systematic benchmarking of data compression strategies for HT data stored in the OME-Zarr format, a cloud-compatible chunked data structure suitable for scalable imaging workflows. Using six representative datasets from five biological samples, we evaluated combinations of preprocessing filters and 13 compression algorithms across multiple compression levels. Performance was assessed in terms of compression ratio, bandwidth, and decompression speed. A throughput-based evaluation metric was introduced to capture realistic performance under varying network constraints, revealing that the optimal compression strategy is strongly dependent on available system bandwidth. Across a wide range of bandwidth conditions, Pcodec consistently exhibited the most balanced overall performance, followed by Blosc-zstd and zstd. The results offer practical guidance for the storage and transmission of large HT datasets and serve as a reference for implementing scalable, FAIR-aligned imaging workflows in cloud and high-performance computing environments.

Adult sex ratios in captive reptiles, birds and mammals vary with the sex determination system

Abstract The adult sex ratio (ASR; the proportion of males in the adult population) is a key demographic trait that varies widely across species and is linked to mating systems and sexually selected traits. Previous research on wild tetrapods showed that ASR is associated with genotypic sex determination system: species with male-heterogamety (XY sex chromosome system) tend to have more female-biased ASRs than species with female-heterogamety (ZW system). If genotypic mechanisms of sex determination are involved, these may also shape ASRs in controlled environments. Here, we test the latter proposition using demographic data from 1,192 zoo-housed reptile, bird, and mammal species. Across amniotes, ASRs in captive populations follow patterns similar to those observed in the wild: XY species tend to have more female-biased ASRs than ZW species. Captive mammals and birds showed similar ASR biases as found in wild populations, although in reptiles, the clade with diverse sex determination systems, the ASR did not differ significantly between XY and ZW species. Instead, reptiles with temperature-dependent sex determination (TSD) differed from reptiles of both genotypic sex determination groups. Together these results support that non-ecological processes linked to sex determination systems contribute to ASR patterns both in captive and wild animals.