Search Results (4,724)

LGBTQ+ individuals continue to experience substantial barriers to accessing affirming healthcare, including discrimination, structural inequities, and provider-level limitations. This study aimed to develop an emergent grounded theory model of constructing wholeness in healthcare. Methods: This study employed a secondary constructivist grounded theory analysis of qualitative data from The Rainbow Connections Study, a community-based system dynamics project. Data were collected through eight group model-building sessions conducted via Zoom with 28 LGBTQ+ participants, including older adults, youth, transgender and gender-diverse individuals, and staff from the LGBTQ+ community center who also held service and practitioner roles; analytic claims are framed to reflect this mixed-role sample. Sessions were audio- and video-recorded, transcribed verbatim, and analyzed using open, axial, and selective coding procedures. Constant comparative methods, reflexive memoing, and member checking were used to support analytic rigor and trustworthiness. Results: Analysis revealed a dynamic process in which LGBTQ+ individuals encounter external forces within healthcare systems that alternately support or fragment their sense of self. In response, participants engaged in four interconnected internal processes—interconnecting selves, intra-community support, self-determined care, and meaning-finding—that facilitated movement toward wholeness. These processes were non-linear, iterative, and present across diverse identities and life stages. Conclusions: The emergent theory of Constructing Wholeness in Connecting to Healthcare highlights that LGBTQ+ healthcare experiences extend beyond access and utilization to include identity integration, community reliance, and meaning making. Supporting LGBTQ+ health requires healthcare approaches that affirm wholeness, reduce structural harm, and recognize the central role of community in navigating care. Full article

Trace amounts of CO in H₂-rich gas can poison Pt electrodes in proton-exchange-membrane fuel cells, necessitating selective CO removal. Preferential oxidation of CO (PROX) offers an efficient route to oxidize CO while preserving H₂. Although noble-metal-based catalysts are widely used, their high cost has driven interest in non-precious alternatives. Co₃O₄–CeO₂ catalysts have emerged as particularly promising due to their high activity and stability. Two series of Co–Ce/SiO₂ catalysts were prepared via impregnation: in the first, Ce was introduced and calcined prior to Co deposition; in the second, Co and Ce nitrates were co-deposited from a mixed aqueous solution. The latter method enhances the interaction between Co₃O₄ and CeO₂, increasing the availability of surface oxygen species. Stability tests on the most active sample demonstrated remarkable durability, maintaining near-complete CO conversion over 100 h on dry stream. Full article

Serotonin is a neurotransmitter that plays a crucial role in mood regulation and has several health-related functions in humans. Physical exercise (PE) has been proposed as a potential non-pharmacological strategy to modulate serotonin levels. Objective: This systematic review and meta-analysis aimed to investigate the effect of PE on circulating serotonin concentrations. Methods: Following PRISMA guidelines, a systematic search was conducted in PubMed, Web of Science, and Scopus, identifying 938 records. Randomized controlled trials with a PE intervention group and a non-PE usual care control group that meet the inclusion criteria were selected. Data were synthesized using a random-effects meta-analysis with standardized mean differences (SMD), and sensitivity analyses were performed using alternative pre–post correlation assumptions (r = 0.6–0.9). Study quality was assessed using the PEDro scale. Results: Five randomized controlled trials comprising 116 participants, all of them females, were included. The pooled analysis showed a non-significant effect of PE on circulating serotonin levels (SMD 1.48; p = 0.135; 95% CI −0.46 to 3.42), with extremely high heterogeneity (I² = 94.63%). Sensitivity analyses produced similar non-significant results and consistently high heterogeneity, indicating robustness of the original model. Methodological quality ranged from acceptable to good (PEDro scores 4–7). Conclusions: Current evidence, derived exclusively from female participants, does not support a significant effect of PE on serum or plasma serotonin levels. The substantial heterogeneity among studies and the generally moderate methodological quality limit the strength of the conclusions and generalizability of the conclusions. Further, high-quality randomized controlled trials with standardized measurement protocols are needed to clarify the influence of exercise on circulating serotonin levels. Full article

Background: bacterial pathogens and their toxins present analytical challenges for rapid and specific detection, contributing to over 600 million cases of illness annually and worsening antimicrobial resistance (AMR). Conventional detection methods are useful but limited. Single-domain antibodies (sdAbs) offer alternative recognition elements with unique biochemical and engineering benefits, enabling the development of nanobody-based immunoassays and biosensing platforms that provide fast, highly selective, and reliable detection of bacterial pathogens and toxins in both food and clinical environments. Objectives: this systematic review assesses the analytical and functional performance of nanobody-based immunoassays and sensing formats for detecting bacteria and toxins across food and clinical samples. Methods: following PRISMA guidelines, major scientific databases were used to gather research, resulting in 32 eligible studies published between 2011 and 2025. Results: data collected included assay platforms, target bacteria and toxins, limit of detection, sensitivity, specificity, matrix recovery, and practicality. Risk of bias was evaluated using an adapted QUADAS-2 framework. The review shows that nanobody-based immunoassays have achieved high performance, thermostability, compatibility with genetic engineering, and versatile assay design. When combined with advanced transduction and signal amplification strategies, these systems contribute to the development of highly sensitive and user-friendly bioanalytical platforms for detecting bacteria and toxins. Conclusions: however, most studies relied on spiked samples and lacked large-scale validation, emphasizing the need for standardized benchmarking and real-world testing. Full article

Accurate determination of in situ stress is fundamental for the safe and efficient design of underground construction projects such as tunnels, caverns, and deep mining excavations. Conventional techniques—particularly overcoring and hydraulic fracturing—have been widely adopted for decades, but their practical use is often constrained by high operational cost, rigorous field requirements, and logistical limitations at depth. As engineering projects advance into deeper and more complex geological environments, these constraints have prompted growing interest in laboratory-based, core-derived stress measurement approaches. Such methods utilize the stress-relief deformation that occurs when drill cores are extracted, enabling stress estimation without extensive downhole instrumentation. This paper presents a critical review of core-based stress measurement techniques based on a structured survey of peer-reviewed literature retrieved from major scientific databases (Web of Science, Scopus, and Google Scholar), covering studies published from the 1960s to 2025. The review examines Anelastic Strain Recovery (ASR), Differential Strain Curve Analysis (DSCA), Deformation Rate Analysis (DRA), acoustic-emission-based Kaiser effect approaches, and the emerging Diametrical Core Deformation Technique (DCDT). Recent studies show that DCDT, which measures instantaneous elastic diametrical deformation of cores, provides a more direct and physically transparent link to differential in situ stress, with reduced sensitivity to time-dependent effects. The DCDT, based on precise measurement of instantaneous elastic deformation upon coring, offers high-resolution stress estimation with minimal disruption to field operations. Its compatibility with optical scanning, laser micrometers, and CT imaging highlights its potential as a practical alternative to conventional techniques. A comparative synthesis of assumptions, accuracy, and applicability is provided, and key limitations and future research needs of core-based stress measurement methods are identified. The findings of this review provide practical guidance for selecting stress measurement techniques and support the application of core-based methods, particularly DCDT, in deep underground engineering, where cost-effective and reliable stress characterization is required. Full article

Background/Objective: Root resective procedures are well established tooth-preserving techniques used when pathology is confined to one root of a multirooted tooth or in the furcation area. Although in recent years implant therapy has become a standard approach in many cases, the rising incidence of peri-implantitis has renewed interest in classical conservative treatment alternatives, such as hemisection, root resection and bicuspidization. The aim of this study is to present clinical cases in which hemisection and bicuspidization were performed to maintain compromised molars in function and achieve long-term outcomes. Methods: This retrospective case series study was conducted in a private dental practice and included three patients treated between 2009 and 2017. The presented cases involved molar teeth exhibiting a vertical fracture or extensive subgingival carries in one root while the remaining root(s) demonstrated favourable periodontal, endodontic and restorative prognosis. An interdisciplinary approach was followed in each case, involving comprehensive clinical and radiographic evaluation including cone beam computed tomography when indicated. The clinical treatment included an endodontic approach (primary treatment or retreatment if required) followed by hemisection or bicuspidization and placement of a permanent prosthetic rehabilitation with full-coverage restoration designed to optimize proper load distribution. Clinical and radiographic follow-up examination was done up to six years in case one, after six months in case two and up to six years in case three. Results: The teeth remained in function through their respective follow-up periods. Clinical and radiographic assessments, according to predefined success criteria, demonstrated periodontal stability (probing depth ≤ 4 mm), no evidence of secondary caries or root fracture, absence of clinical symptoms, normal tooth mobility and masticatory function, absence or reduction in periradicular radiolucency, and stable bone levels. Conclusions: Resective techniques require an interdisciplinary approach, namely, careful case selection, lege artis endodontic treatment, precise surgical technique, and appropriate prosthetic rehabilitation, in order to provide predictable and long-term outcomes. Within the limitations of this case series, resective techniques appeared to be a reliable and predictable alternative to extraction and implant placement in carefully selected clinical cases. Full article

This work presents Recurrence with Correlation Network(RWCNet), a novel multi-scale recurrent neural network architecture for medical image registration that integrates core principles from optical flow, including correlation volume computation and inference-time instance optimization. In evaluations on the large-displacement National Lung Screening Test (NLST) dataset, RWCNet exhibited superior performance (total registration error (TRE) of 2.11 mm) compared to other deep learning alternatives, and achieved results on par with variational optimization techniques. In contrast, on the OASIS dataset, which is characterized by smaller displacements, RWCNet achieved an average Dice similarity of 81.7%, representing only a modest improvement over other multi-scale deep learning models. Ablation experiments showed that multi-scale features consistently improved performance, whereas the correlation volume, number of recurrent steps, and inference-time instance optimization had large impacts on performance within the large-displacement NLST dataset. The performance of RWCNet compared to approaches that use instance optimization show that deep learning-based methods can find local minima that escape instance optimization methods. The results highlight the need for algorithm hyperparameter selection that adjusts with the dataset characteristics. RWCNet’s promising results may improve registration accuracy and computation efficiency, enabling many potential applications such as treatment planning, intra-procedural guidance, and longitudinal monitoring. Full article

Background: Nanomaterials have emerged as a transformative approach in modern pharmaceutical applications, offering advanced benefits compared to conventional therapies. Among available pharmaceutical nanomaterials, silver nanoparticles (AgNPs) have been reported with broad-spectrum antimicrobial potential and drug delivery potency. Nevertheless, some studies suggested that chemical synthesis of AgNPs might result in redundant chemicals, posing environmental and health risks. To minimize undesired products, a promising approach is to biologically synthesize this potent nanomaterial. Methods: This study ultilized an eco-friendly system for AgNPs synthesis using Aspergillus terreus isolated from the air. Physical properties of biosynthesized AgNPs were evaluated by UV–visible spectroscopy, dynamic light scattering, and scanning electron microscopy analysis. Antibacterial activity of biosynthesized AgNPs was examined by well diffusion and minimum inhibitory concentration, while in vitro cytotoxicity was used to determine the antitumor activity of AgNPs. Results: The biosynthesized AgNPs had a size of around 60 nm, a PDI inferior to 0.2, and a zeta potential of −30 mV. They exhibited potent antibacterial activity against both Gram-positive and Gram-negative pathogens. Additionally, these nanoparticles also exerted a selective antiproliferative effect on MCF-7, A549, and MDA-MB-231 cell lines. Conclusions: Our research presented the potential of biosynthesized AgNPs using Aspergillus terreus for antimicrobial and anticancer applications, offering an eco-friendly and sustainable alternative to traditional chemical methods. Full article

The COVID-19 pandemic necessitated rigorous infection control protocols across hospital environments, particularly in nutrition services. UV-C light emerged as a viable option due to its shortest wavelength, conferring the greatest capacity for nucleic acid (DNA/RNA) penetration in both microorganisms and human cells. We aim to develop and validate an alternative method for decontaminating food carts using UV-C light. A prototype box was created to cover the meal transport carts, with UV-C lamps strategically positioned for irradiation and decontamination. To validate this technology, four different hygiene protocols were compared: Group 1, positive control, with no sanitization procedure; Group 2, cleaned using the standard protocol of the University Hospital of UFS (HU/UFS) with 70% ethanol solution; Group 3, negative control, cleaned using the standard HU/UFS protocol with 70% ethanol and neutral detergent; and Group 4, exposed to UV-C light irradiation for 10 min after food transport. Microbiological samples were collected from 15 distinct points on the carts. Samples were collected using sterile swabs moistened with 0.85% saline solution and incubated in BHI broth at 37 °C for 24 h for presence/absence testing. Positive samples were plated on selective media (CLED, SS, MacConkey and Blood agar), incubated at 37 °C for 24–48 h, and evaluated for colony-forming unit (CFU) count. A statistically significant association was found between the hygiene method and the presence of microbial contamination (p < 0.001), based on both bacterial plate counts and BHI broth growth. Carts sanitized with 70% alcohol showed a lower probability of contamination compared to the control group (alcohol + detergent), while unsanitized carts showed a higher risk. UV-C light treatment resulted in complete absence of bacterial growth. UV-C disinfection demonstrated superior effectiveness in eliminating microorganisms, indicating a promising alternative to traditional methods. Full article

The continuation ratio model is a crucial tool for analyzing ordinal response data. However, its explanatory power diminishes under high-dimensional settings where the number of covariates p is large. To address this, we introduce, for the first time, the smoothly clipped absolute deviation (SCAD) penalty into the forward continuation ratio model framework. We propose a corresponding penalized likelihood estimation method that performs simultaneous variable selection and parameter estimation and provides an efficient algorithm for its implementation. Numerical simulations demonstrate the favorable properties of the SCAD penalty: it precisely identifies significant variables while more aggressively shrinking the coefficients of irrelevant ones to zero, outperforming alternative penalties like Lasso and elastic net in selection accuracy. Finally, we illustrate the practical utility of our method through an empirical application using data from the Chinese General Social Survey (CGSS). Full article

Background/Objectives: Head and neck squamous cell carcinoma (HNSCC) poses a significant health challenge, especially among elderly patients, who are often underrepresented in clinical trials. Transoral robotic surgery (TORS) has emerged as a promising alternative to non-surgical strategies such as chemoradiotherapy (CRT), but its effectiveness in older adults is not well-studied. Methods: A structured narrative review of studies on TORS for elderly HNSCC patients was conducted using the PubMed/MEDLINE database. Studies were selected according to predefined eligibility criteria based on the PICOS framework. PRISMA reporting principles were applied to document study identification and selection. Results: The available evidence suggests that, in carefully selected elderly patients, TORS is associated with disease-specific (DSS) and disease-free survival (DFS) outcomes comparable to those reported in younger cohorts, while overall survival (OS) appears more strongly influenced by comorbidities than chronological age. TORS may facilitate treatment de-escalation in selected cases, potentially reducing exposure to adjuvant therapies and limiting treatment-related toxicity. Functional outcomes, particularly swallowing function and long-term gastrostomy dependence, may be favorable in selected elderly patients; however, comparative data with non-surgical approaches remain limited, heterogeneous, and are partly derived from mixed-age cohorts. Conclusions: TORS represents a viable treatment option for selected elderly HNSCC patients, providing encouraging oncologic outcomes and potential functional advantages. Nevertheless, the current evidence base is predominantly retrospective and heterogeneous. Careful patient selection is essential, and further prospective elderly-specific studies are needed to better define functional and oncologic benefits. Full article

The impact of climate change (CC) includes a decline in agricultural production due to crop damage caused by flooding and drought, which destroys crops before harvest, particularly in small-scale irrigation areas. This has led farmers to look for alternative irrigation methods, i.e., groundwater through dug-wells. However, the volume of water obtained through dug-wells is limited. This has led farmers to select the crops they would cultivate. This study aimed to examine the factors that influence farmers in selecting the crops to be cultivated through multinomial logistic regression (MLR). A total of 118 farmers in Jember and Lumajang were randomly selected and interviewed regarding the use of wells and the selection of crops to be cultivated. The dependent variables consist of three crop pattern categories. The results showed that water access variables—particularly well depth, pumped water volume, pipe length, and pump power—significantly influence crop pattern selection (p < 0.01). Farmers adopting diversified crop patterns (food-other and mixed crop pattern) extracted substantially higher groundwater volumes (>76,659 m³ ha⁻¹ annually) and relied on deeper wells (>90 m) compared with the food-crop-dominated pattern. In contrast, water-use-efficient strategies were characterized by lower extraction volumes (<56,755.99 m³ ha⁻¹ annually), longer distribution pipes, and shallower wells (<90 m). Future research should examine the impacts of CC on aquifer depletion and the consequent implications for agricultural activities. Full article

Background: Albendazole, mebendazole, and ivermectin are effective against adult Trichinella spiralis but show limited efficacy against encapsulated muscle stage larvae. This limitation highlights the need for improved experimental approaches to evaluate anthelmintic activity at this stage and to identify alternative therapeutic candidates. Methods: Seven antiparasitic drugs, albendazole (ABZ), miltefosine (MLT), ivermectin (IVM), tribendimidine (TBD), praziquantel (PZQ), artesunate (ART), and mefloquine (MEQ), were evaluated for in vitro activity against T. spiralis muscle larvae. Larval viability was quantified using a tetrazolium salt XTT assay to determine IC₅₀ values and compare with microscopic assessments. Based on in vitro activity, TBD was selected for in vivo evaluation in a mouse model, where efficacy was assessed by muscle larval burden and histopathological changes. Results: TBD, MEQ, IVM, and ABZ exhibited measurable in vitro efficacies against T. spiralis larvae, with TBD showing the lowest IC₅₀ value at 135.2 μM. XTT formazan absorbance correlated strongly with larval number and incubation time. In vivo, TBD treatment significantly reduced larval burdens in diaphragm and gastrocnemius muscles and was associated with reduced collagen capsule thickness, inflammation, and fibrosis compared with ABZ-treated controls. Conclusions: This study validated an assay for quantitative evaluation of T. spiralis muscle larvae and demonstrates robust in vitro and in vivo activity of TBD against this stage. Full article

Background: Correct preoperative evaluation of glioma grade and molecular profile is a prerequisite for tailored treatment strategies. Specifically, the 1p/19q codeletion status represents a major prognostic and therapeutic marker in low-grade gliomas (LGGs). Nevertheless, its assessment is presently performed through invasive histopathological and genetic studies, thus underlining the need for non-invasive alternative approaches. Methods: We introduce a non-invasive radiomics framework that combines quantitative MRI features with sophisticated ML and DL approaches for glioma grading and 1p/19q codeletion status prediction. High-dimensional radiomic features characterizing tumor geometry, intensity, and texture were derived from preoperative MRI-based tumor delineations. Features were normalized and optimized using correlation-based feature selection. Several traditional ML classifiers were compared and contrasted with DL models, such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and a CNN-Long Short-Term Memory (LSTM) hybrid model tailored to exploit both spatial feature hierarchies and feature correlations. Model validation was conducted using five-fold cross-validation and an independent test dataset, with accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) metrics. Results: Among all the models tested, the hybrid CNN-LSTM model performed the best, with an accuracy of 88.1% and an AUC of 0.93, outperforming conventional ML approaches and single-model DL architectures. Explainability analysis showed that the radiomic features of tumor heterogeneity and morphology had the most prominent impact on model performance. Conclusions: These findings indicate that the combination of radiomic features with hybrid DL models is capable of making non-invasive predictions of glioma grade and 1p/19q codeletion status. The new computational model has the potential to be used as a supplementary approach in precision neuro-oncology. Full article

This study presents a comparative flood frequency analysis of annual maximum discharges for major Romanian river basins, assessing the performance of the Halphen-A distribution relative to the Pearson Type III distribution, the reference model in Romanian hydrological practice. Four long-term discharge series from the Siret, Ialomița, and Danube rivers are analyzed, covering diverse hydroclimatic conditions. Distribution parameters are estimated using the method of moments and maximum likelihood estimation. Model performance is evaluated using RMSE and MAE, complemented by an analysis of extreme quantile behavior. The results show that both distributions fit the observed data well, with only minor differences in global error metrics. However, for high return periods (T > 100 years), Halphen-A exhibits smoother extrapolation and yields more stable extreme quantile estimates, particularly when estimated by MLE. Although Pearson III often achieves slightly lower metrics values, its upper tail is more constrained and sensitive to skewness and record length. The study concludes that classical goodness-of-fit measures alone are insufficient for selecting models for design floods and that Halphen-A provides a robust complementary alternative for extreme flood estimation. Full article