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In the context of the aging of the global population, the prevalence of knee joint disorders continues to rise. Concurrently, the integration of robotic systems and intelligent implants represents an inevitable trend in orthopedic surgery. A comprehensive evaluation of the safety and effectiveness of robot-assisted total knee arthroplasty (RA-TKA) is therefore urgently needed to inform clinical decision-making. To explore the advantages of 9 RA-TKAs across 8 outcomes. A systematic literature search was conducted in the PubMed, Web of Science, Embase, Cochrane Library, CBM, CNKI, Wanfang, and VIP databases from inception to December 1, 2025. The risk of bias and methodological quality were assessed via Review Manager (version 5.4). Network meta-analysis was performed via RStudio (version 4.4.1). A total of 36 studies involving 2841 patients were included. In direct comparisons, conventional TKA (C-TKA) yielded shorter operative times than MAKO, HURWA, SkyWalker, ROSA, and Brainlab Knee did. CORI also had a shorter operative time than Brainlab Knee did. Compared with the C-TKA, MAKO, HURWA, SkyWalker and TiRobot groups, the ROSA group presented higher KSS-knee scores. In addition, C-TKA, HURWA, and CORI presented higher KSS-knee scores than did SkyWalker. For the KSS-function scores, the C-TKA and ROSA scores were higher than the HURWA score. C-TKA demonstrated a greater postoperative ROM than HURWA did. For HKA angle deviation, C-TKA resulted in greater deviation than MAKO, HURWA, SkyWalker, TiRobot, and EPMEDBOT did. In the comprehensive best probability ranking, C-TKA (93%) ranked highest in terms of operative time. SkyWalker (87%) ranked highest in terms of blood loss. SkyWalker (91%) ranked highest in terms of the KSS-knee scores. HURWA (87%) ranked highest in terms of the KSS function scores. MAKO (85%) ranked highest for HSS. The YUANHUA (76%) ranked highest for the WOMAC. The CORI (69%) ranked highest for ROM. SkyWalker (87%) ranked highest for HKA angle deviation. Overall, RA-TKA demonstrated superior safety and effectiveness compared with C-TKA, with different robotic systems exhibiting distinct advantages across outcome measures. Nevertheless, C-TKA retains a significant advantage in reducing the operative time, highlighting an important area for further optimization of robotic-assisted TKA.

The progressive skeletal muscle degeneration observed in Duchenne Muscular Dystrophy (DMD) patients requires multiple cycles of satellite cells (SCs) activation to promote tissue regeneration. Dystrophic SCs present intrinsic defects, and the disrupting fibrotic niche hinders appropriate muscle recovery. Traditional 2D culture systems face challenges in modeling the DMD muscle niche and SCs behavior. Our aim was to validate a 3D culture of skeletal muscle spheroids (iSMS) for DMD modeling, as compared to the traditional 2D culture, while investigating the pathophysiological mechanisms of dystrophin deficiency in vitro. To compare iSMS with traditional 2D myogenic differentiation, we differentiated wild-type (WT), dystrophic (DMD) isogenic induced pluripotent stem cells (iPSCs), as well as iPSCs derived from DMD patients, characterized myogenic markers levels and assessed differences in proliferation and differentiation using RT-qPCR, immunofluorescence, and flow cytometry. Our data showed that iSMS improved PAX7 expression in vitro, while MYOD1, MYOG, MYF5, and MYH3 expression were significantly reduced. These findings suggest that, at three weeks of myogenic differentiation, iSMS cultures retained satellite-like cells in a less activated, progenitor-like state. Accordingly, we identified higher expression of canonical Notch signaling genes such as JAG1 and NOTCH1 in iSMS compared to 2D. We also characterized the response of 2D and iSMS to terminal differentiation medium, providing a valuable comparison with muscle fibers derived from human adult myoblasts. Additionally, we showed that DMD iSMS-derived progenitors proliferated at reduced levels compared with WT, a characteristic not observed in progenitors derived from 2D cultures. Finally, we performed iSMS and 2D myogenic differentiation of iPSC lines from three patients with DMD. Our results highlight important advantages of using the iSMS differentiation platform over 2D for DMD in vitro modeling. Exploring these 3D systems may help to gain a deeper understanding of SCs behavior to advance in novel treatments for DMD, which might be applicable to other forms of muscular disorders.

The proliferation of hate speech on social media poses a significant challenge to maintaining safe and inclusive online environments, necessitating accurate and scalable automated detection systems. However, the performance of transformer-based models for hate speech detection is highly sensitive to hyperparameter configurations, making manual and conventional tuning strategies inefficient in high-dimensional search spaces.To address this challenge, this study proposes a hybrid optimization framework that integrates the DeBERTaV3 transformer model with the Grey Wolf Optimizer (GWO) for automated hyperparameter tuning. The proposed approach enables efficient exploration of complex hyperparameter spaces by balancing global search and local refinement. The framework optimizes eight critical hyperparameters, including learning rate, weight decay, and dropout rates, to enhance convergence stability and generalization performance. The proposed method is evaluated on the Davidson et al. (2017) dataset, consisting of 24,783 labeled tweets. Experimental results demonstrate that the GWO-DeBERTaV3 model achieves a peak accuracy of 97.72% and a macro F1-score of 97.71%, with statistically significant improvements over baseline and conventional tuning approaches.These findings highlight the effectiveness of metaheuristic-based optimization for transformer fine-tuning and demonstrate its potential for improving robustness and performance in real-world hate speech detection systems.

Accurate localization of wireless capsule endoscopy is essential for reliable gastrointestinal diagnosis, yet magnetic tracking systems are often degraded by sensor distortions, misalignment, and patient motion in wearable settings. This study presents a magnetic localization framework that combines cylindrical magnetic field modelling with neural network-based sensor calibration to improve robustness under wearable operating conditions. By exploiting the structural properties of cylindrical magnetic field representations, the proposed approach decouples axial and transverse components of the magnetic field, enabling staged estimation of magnetic capsule position and orientation with improved numerical stability. A data-driven calibration model is employed to compensate for nonlinear sensor distortions arising from hard-iron effects, soft-iron effects, and dynamic misalignment. Experimental validation using a four-sensor wearable array demonstrates a mean static localization error of 0.12 cm and [Formula: see text], and a dynamic localization error of 0.20 cm and [Formula: see text], indicating improved performance under both stable and motion-affected conditions. These results suggest that accurate and robust magnetic capsule localization can be achieved with a minimal sensor configuration, supporting practical implementation in wearable capsule endoscopy systems.

Geminal difunctionalization of carbonyl-derived building blocks represents a versatile strategy for the rapid generation of sp3-rich molecular architectures. In this context, diazo compounds provide a powerful platform for installing two distinct functional groups, yet the reaction space for carbonyl-derived donor-donor diazo systems remains underdeveloped. Here, we report a metal-free migratory insertion of diazo compounds into C─S bonds of sulfonyl cyanides, enabling the simultaneous installation of sulfone and nitrile functionalities at a single carbon center. Key to this transformation is the in situ generation of highly reactive diazo intermediates via photochemical decomposition of bench-stable oxadiazolines derived from ketones. This substantially expands the accessible coupling partner space, previously limited to aldehydes or boronic acids. The reaction exhibits broad functional group, water, and air tolerance, delivers high yields, and provides excellent diastereoselectivity in constrained cyclic systems. Compatibility with both batch and continuous-flow processing, as well as its application to a realistic medicinal chemistry combinatorial library synthesis, highlights the practical utility of the method.

Tanzania has adopted artificial intelligence (AI)-assisted chest X-ray screening for tuberculosis (TB), including the use of CAD4TB version 6, which is registered by the Tanzania Medicines and Medical Devices Authority (TMDA). While GeneXpert, practical reference standard used in routine practice, remains the primary bacteriological confirmatory test in routine practice, there is currently no established national threshold for CAD4TB use in either active case finding (ACF) or passive case finding (PCF) settings. This study evaluates the implementation and operational use of CAD4TB version 6 within mobile TB screening units in Tanzania and highlights challenges affecting its effective use. We conducted a retrospective analysis of screening data from 11,923 individuals collected from mobile clinics equipped with digital X-ray, CAD4TB version 6, and GeneXpert systems. Comparisons were made between manual chest X-ray interpretation, CAD4TB scores, and GeneXpert results within the subset of individuals who underwent confirmatory testing. The findings reveal substantial inconsistencies in screening workflows, including non-uniform use of CAD4TB prior to GeneXpert testing, missing radiological records, and deviations from intended protocols across sites. Descriptive analysis showed that CAD4TB scores generally aligned with GeneXpert-positive cases within the tested subset; however, due to selective application of GeneXpert and incomplete data, these observations cannot be interpreted as measures of diagnostic accuracy. This study should be interpreted as an implementation and operational assessment of AI-assisted TB screening rather than a diagnostic accuracy or threshold-setting study. The findings highlight important gaps in protocol adherence, data completeness, and workflow standardization, underscoring the need for prospective, protocol-driven studies to establish validated national thresholds for CAD4TB use in Tanzania.

This study investigates the identification of Benign Prostatic Hyperplasia (BPH) through a deep learning-based analysis of RGB prostate histopathological images. Adaptive Contrast Limited Adaptive Histogram Equalization (CLAHE) is selectively applied to the L-channel in the LAB color space to enhance tissue visibility while preserving chromatic fidelity. At the architectural level, Convolutional Neural Networks (CNNs) are integrated with Bidirectional Long Short-Term Memory (BiLSTM) layers, enhanced further through spatial and temporal attention mechanisms. This hybrid design facilitates both localized pattern recognition and the modeling of long-range contextual dependencies across tissue regions. To mitigate class imbalance and prevent overfitting, the training regime incorporates two key strategies: an adaptive focal loss function and a comprehensive image augmentation protocol. The proposed model achieved an AUC of 0.7220 on the validation set and an AUC of 0.73 on the test set. While the precision for normal tissue classification remained high, the recall for BPH detection highlighted the need for improvement in sensitivity. The proposed CNN-BiLSTM-Attention architecture demonstrates potential as a diagnostic aid in digital pathology, offering interpretable insights and forming a foundation for enhancing histological classification systems. Future work will focus on improving recall performance for BPH detection and expanding the architecture to support multi-class prostate disease grading frameworks. This study utilizes an RGB histopathological dataset consisting of 176 prostate images, each appropriately annotated. The model demonstrates moderate classification performance and a moderate true-positive rate for detecting Normal samples. The model, however, has a low sensitivity in the detection of the cases of BPH as indicated by the relatively low recall values.

The growing proportion of women in veteran communities internationally highlights a rising need for veteran support services tailored to their unique experiences. Despite this, support services remain predominantly designed for men, leading to underutilization and dissatisfaction among women veterans. This scoping review aimed to provide a comprehensive international review of the current state of knowledge regarding the experiences of women veterans in accessing and engaging with veteran-specific support services. This study followed the Joanna Briggs Institute scoping review methodology. Five databases were searched for papers published from 2000 onwards. Studies reporting on barriers and/or facilitators to access and experiences of engaging with veteran-specific support services reported by women veterans were included. There were no limitations on study methodology or country of origin, and all publications reporting primary research were included. A total of 117 studies were included in the review. This research originated predominantly from the US (n = 109), with seven UK papers, and one Canadian. Eleven themes were identified across the literature, highlighting gendered barriers and facilitators of accessing veteran-specific support for women. Women veterans report feelings of discomfort, exclusion, and discrimination within veteran services, which are perceived as being set up and designed for men. Women report experiencing stigma in help-seeking compounded by a perception of feminine weakness experienced during military service. Some women didn't want to access services they saw as military-adjacent, due to gendered adverse experiences during military service, including discrimination, harassment, and sexual violence. A lack of identification with the term 'veteran' further hinders women's engagement with veteran-specific services. Enablers of access include care that is sensitive to women's needs, trauma-informed service user-provider relationships, and peer support. The reviewed evidence suggests women experience unique challenges and needs in accessing veteran-specific services. Support services should focus on developing care that is, culturally competent, trauma-informed and sensitive to the needs of women, to address gendered barriers to engagement. More research is needed to confirm these research findings outside of the US context, and incorporating an intersectional lens in future research will be essential for improving the support systems for women veterans internationally.

Functional validation of candidate genes in congenital anomalies of the kidneys and urinary tract (CAKUT) and other disorders is essential for translating genetic discoveries into clinical applications. Conditional knockout mouse models are indispensable for studying gene function in complex organ systems. The Short Conditional intrON (SCON) system accelerates the generation of such models by inserting the artificial SCON into a coding exon. SCON is designed to be spliced out after transcription, without affecting gene expression. Upon Cre activity, SCON is converted into the ΔSCON allele which cannot be spliced out, introducing premature termination codons (PTCs) to inactivate the gene. Previous validation of the SCON system in mice has focused primarily on phenotypic outcomes. Here, we provide a molecular characterization of the SCON system in Cdh12-a candidate gene implicated in kidney damage in CAKUT. We found that both Cdh12SCON and Cdh12ΔSCON alleles caused unintended skipping of the exon downstream of the insertion site, culminating in a frameshift and PTC. Consequently, the Cdh12SCON allele led to a ~ 25% reduction in mRNA expression, indicating that it was not transcriptionally inert as designed. Despite unintended exon skipping, the Cdh12ΔSCON allele still effectively suppressed mRNA expression. These findings highlight the importance of transcript-level characterization of engineered alleles prior to functional studies, as artefactual splicing events may occur across multiple gene-targeting strategies, including artificial intron-based conditional alleles as shown here.

Understanding the mechanisms of nickel (Ni) uptake by hyperaccumulator plants is essential for advancing sustainable phytomanagement. In this study, saponite materials containing either isotopically natural or 61Ni-enriched Ni were synthesised and applied in RHIZOtest experiments with Odontarrhena chalcidica. The amendments were mixed with two ultramafic soils differing in Ni content, alongside a serpentinite control. Ni bioavailability and uptake were evaluated via elemental and isotopic analysis of plant digests and diffusive gradients in thin films (DGT). Stable isotope spiking with 61Ni allowed tracing of amendment-derived Ni uptake into plant tissues, even though total Ni mass fractions in planted versus unplanted soils did not indicate significant mobilisation during the 14-day growth period. Isotope pattern deconvolution (IPD) revealed clear shifts in Ni isotopic composition in both plant and DGT samples. Tracer uptake was more pronounced in the low Ni soil, with amendment-derived Ni (xamendment) contributing 19.3 ± 5.0% of total Ni in shoots, compared to 7.7 ± 1.8% in the high-Ni soil. In standard solutions containing 50 ng g-1 total Ni, isotope pattern shifts were still detectable at enrichment levels as low as 0.01% xspike (≈ 5 pg g-1 61Ni). The findings demonstrate the sensitivity of stable isotope spiking combined with IPD in the detection of subtle uptake processes, even in short-term experiments. This approach enables the differentiation of various Ni sources in soil-plant systems that would not be achievable with quantification alone, and can thereby provide new insights into how soil mineralogy influences uptake dynamics in metal-hyperaccumulating species.

Expanders in organic Rankine cycle systems serve as critical energy-conversion components in low-grade waste heat recovery installations, yet their reliable operation is threatened by faults such as bearing defects, rotor imbalance, and blade cracking. Conventional diagnostic methods often struggle with non-stationary vibration characteristics, class imbalance, and low signal-to-noise ratios inherent to these working environments. This paper proposes an improved deep residual network, referred to as multi-scale convolutional block attention module residual network, that integrates a multi-scale parallel feature extraction module with convolutional block attention mechanisms for intelligent fault diagnosis. The multi-scale module employs three parallel convolutional branches with different kernel sizes to simultaneously capture transient impulses, periodic modulation, and low-frequency envelope features across multiple temporal scales. Attention-enhanced residual blocks sequentially recalibrate channel and spatial responses to emphasize fault-sensitive features while suppressing noise interference. A training optimization scheme combining Focal Loss, cosine annealing, and targeted data augmentation is further introduced to address the small-sample imbalanced-data challenge. Five-fold cross-validation experiments conducted on a 10 kW single-screw expander test rig demonstrate that the proposed model achieves 98.11 ± 0.34% diagnostic accuracy across four health states, surpassing the standard deep residual network baseline by 6.57 percentage points, with only 3.27% relative accuracy degradation at 10 dB signal-to-noise ratio. Ablation studies confirm a multiplicative synergy between the multi-scale and attention modules, statistical significance tests validate the robustness of the observed improvements, and comparative evaluations against six benchmark methods demonstrate the superiority and generalizability of the proposed approach.

Visual impairment affects over 2.2 billion people worldwide and the major causes include age-related macular degeneration (AMD), glaucoma, and diabetic retinopathy. For research in these areas, although animal models offer a more physiologically complex system than in vitro approaches, their use raises ethical considerations, and species-specific differences such as variations in protein sequences and signaling pathways. This can limit the direct translatability of the outcomes. Traditional 2-D cell cultures, in contrast, lack the multicellular organization and dynamic microenvironment necessary to replicate human retinal complexity. Retinal organoids (ROs), three-dimensional tissue constructs derived from pluripotent stem cells, have emerged as a promising model due to their human origin and complex cellular interactions that cannot be achieved in conventional 2-D/3-D co-culture models. In this review, we provide a brief overview of the evolution from 2-D to 3-D retinal models, highlight the structural and functional features of ROs including the presence of layered retinal architecture, photoreceptor outer segment formation, and light-responsive electrophysiological activity and summarize their applications in disease modeling, drug discovery, and gene and cell therapy. ROs represent a significant advancement over traditional models by enabling the recapitulation of human-specific retinal development, facilitating the study of patient-derived disease phenotypes, and providing a platform for personalized therapeutic screening. Their development has deepened understanding of pathological mechanisms in conditions such as retinitis pigmentosa and AMD, while enabling preclinical testing of targeted interventions like CRISPR-based gene editing and photoreceptor cell replacement. Nonetheless, challenges remain in fully replicating retinal vascularization, long-term functional maturation, and synaptic connectivity, underscoring the need for continued refinement and integration with complementary model systems.

How host organisms adapt their defense systems to newly invading transposable elements remains poorly understood. Here, we show how Drosophila melanogaster acquired PIWI-interacting RNA (piRNA)-mediated immunity against the endogenous retrovirus Tirant. We uncover two distinct modes of de novo piRNA biogenesis by combining genetics, small RNA profiling, and population genomics. The primary route involves antisense insertions into the flamenco cluster, a master locus for transposon control. Unexpectedly, a second, equally potent mechanism arises from antisense Tirant insertions within host gene 3' UTRs. This process requires host gene transcription but is independent of host gene identity. Our findings challenge prevailing models that tie piRNA precursor specification to genomic origin or nuclear RNA processing context. Instead, they reveal a flexible mechanism that turns a critical vulnerability of transposons into an advantage for the host. When transposition occurs into host gene exons, chimeric antisense transcripts are exported to the cytoplasm, inadvertently initiating piRNA production and enabling rapid, adaptive genome defense against new invaders.

Coal exhibits heterogeneous pore networks and chemically diverse surfaces, resulting in complex competitive adsorption among CH4, CO2, and H2O. The underlying molecular mechanisms remain unclear. In this work, molecular simulation methods were applied to investigate the adsorption behavior and interaction characteristics of CH4/CO2/H2O mixtures on two typical coal components (inertinite and vitrinite) under different CO2 enrichment levels, corresponding to gas-phase CO2 mole fractions of 4.8%, 9.1%, and 16.7%. The results demonstrate that CH4 dominates surface occupation in all cases, maintaining 30-70 adsorbed molecules, whereas CO2 adsorption is significantly weaker, remaining below 5 at low loading and increasing to only 10-17 at high loading. This indicates a limited competitive capability of CO2 for adsorption sites. From an interaction perspective, water governs the electrostatic environment, with surface-water Coulombic energies consistently distributed around - 600 to - 750 kJ mol-1. In contrast, CO2-water interactions decrease from - 220 to - 360 kJ mol-1 to - 100 to - 170 kJ mol-1 as CO2 loading increases, reflecting a pronounced screening effect. Meanwhile, direct CO2-surface interactions remain weak (typically - 5 to - 15 kJ mol-1). Overall, CH4 adsorption is primarily controlled by dispersion interactions, while CO2 is constrained by weak surface affinity and reduced hydration strength, resulting in a secondary role in multicomponent competitive adsorption within coal systems.

The paper is an analytical study of a low-pass electrical model of nonlinear type in a fractional perspective, in which the classical derivative is generalized to the Katugampola fractional operator. Precise traveling-wave solutions are built based on an extended Riccati-Bernoulli sub-ODE scheme together with a Bäcklund transformation. The families of obtained solutions contain bright and dark kink type structures. These solutions have a dynamical behavior that is demonstrated with the help of detailed 3D and 2D visualizations. The 3D plots reveal how sensitive the integer-order parameter is to the waveform whereas the 2D plots show how sensitive the waveform is to the changes in the fractional order (α). To deeper examine the qualitative dynamics, a hamiltonian formulation is created and phase-portrait diagrams are plotted. These unveil the local and global organization of the nonlinear flow underlying. Besides, chaotic behavior is also studied by analyzing sensitivity to initial conditions by determining the largest Lyapunov exponent [Formula: see text]. The findings validate the occurrence of regular, quasi-periodic and chaotic regimes in the parameter space. The entire process of analytical calculations and visualization is implemented in MATLAB, which provides the numerical accuracy of calculations and high-resolution graphical confirmation of fractions solutions. The results illustrate the presence of significant enrichment of the dynamical behavior of the nonlinear electrical model by the fractional extension. It also offers a practical and efficient model to study intricate waves phenomena in the systems of the fractional-order.

Limb salvage centers have increased in number over time, but lack standardized defining criteria. This systematic review aimed to assess organizational features of limb salvage centers and determine whether orthoplastic centers, in comparison to vascular limb salvage centers, represent a distinct care model that may benefit from standardization. We conducted a systematic review of publications related to limb salvage centers by searching MEDLINE, Embase, Web of Science, and Cochrane databases from their inception through 2024. We quantified binary data extraction as a reporting score of 26 organizational features across six structural care domains for limb salvage centers, based on a validated quality measurement framework. Organizational features differentiating distinct center types were identified to establish a quality framework for orthoplastic centers. Statistical comparisons between center types were performed using appropriate tests (p&#x2009;<&#x2009;0.05). Of 118 included studies, orthoplastic (n&#x2009;=&#x2009;43) and vascular (n&#x2009;=&#x2009;48) centers represented 77% of all studies. Recent increases in orthoplastic publications show substantial variability in organizational features. Orthoplastic center literature more frequently reported plastic surgery consultation criteria (p&#x2009;<&#x2009;0.001), surgical outcomes (p&#x2009;<&#x2009;0.001), and centralized network integration (p&#x2009;&#x2264;&#x2009;0.006), highlighting acute reconstructive approaches. Vascular center studies documented significantly more organizational team features (p&#x2009;<&#x2009;0.001) and quality systems (p&#x2009;=&#x2009;0.033), reflecting established care frameworks for chronic disease management. Six organizational features characterized orthoplastic centers with >&#x2009;70% prevalence, providing a benchmark framework with standardization priorities. Orthoplastic limb salvage centers demonstrate distinct care paradigms that benefit from standardization. Our findings suggest structural benchmarks to support the need for standardized development of orthoplastic limb salvage centers.

The pre-weaning period is critical because early-life nutrition and management influence growth, metabolic function and Rumen development, thereby affecting subsequent productivity in dairy calves. Zinc (Zn) supplementation plays a key role in supporting these processes through its involvement in enzymatic activity, antioxidant defense systems, and metabolic regulation, but conventional sources often have bioavailability limitations due to the formation of insoluble complexes in the gastrointestinal tract. This study addresses this challenge by evaluating three Zn forms (ZnO, Zn-lysine, and nano-ZnO) to identify the most effective source for enhancing growth rates, nutrient utilization, and metabolic health. Twenty-four newborn Holstein calves, each with an initial body weight of 40.5&#x2009;&#xb1;&#x2009;4.24&#xa0;kg, were selected and randomly allocated to receive one of three treatments: ZnO, Zn-lysine, and nano-ZnO supplementation. Each calf received 80&#xa0;mg of Zn daily. Supplementation with nano-ZnO increased dry matter intake (P&#x2009;<&#x2009;0.01), average daily gain (P&#x2009;<&#x2009;0.01), and hip width (P&#x2009;<&#x2009;0.01) compared to Zn-lysine and ZnO. However, there were no differences in feed conversion ratio. The treatments did not affect apparent digestibility or rumen fermentation, except for a lower rumen ammonia nitrogen concentration in the nano-ZnO group compared to the other two treatments (P&#x2009;<&#x2009;0.01). Regarding blood parameters, calves receiving Nano-ZnO showed higher blood triglyceride concentration (P&#x2009;=&#x2009;0.04) and superoxide dismutase activity (P&#x2009;<&#x2009;0.01), while blood D-lactate concentration was lower in the nano-ZnO and Zn-lysine groups than in the ZnO group (P&#x2009;=&#x2009;0.01). Additionally, both fecal consistency (P&#x2009;=&#x2009;0.02) and nasal discharge (P&#x2009;<&#x2009;0.01) scores were significantly reduced in the nano-ZnO group. In summary, the study suggests that nano-ZnO is a more effective Zn source and an efficient additive for improving dairy calf performance.

Expanded hemodialysis (HDx) using medium cut-off dialyzers has been associated with lower all-cause hospitalization rates compared to conventional high-flux hemodialysis. Reductions in hospitalization frequency represent a major driver of healthcare expenditures and may contribute to improved budget sustainability in resource-constrained healthcare systems. The objective of this study was to estimate the budget impact of adopting HDx from the perspective of the Colombian healthcare system, using real-world evidence. A budget impact analysis was developed according to the ISPOR guidelines using a tool built in Microsoft Excel. Clinical effectiveness inputs were derived from a multicenter cohort study (COREXH-E), including an extended dataset and a difference-in-differences analysis to estimate the effect of HDx on hospitalization rate while accounting for unobserved confounding. Cost inputs were obtained from national administrative databases, including hospitalization costs and bundled dialysis payments. The analysis adopted a one-year time horizon and a third-party payer perspective representing the Colombian healthcare system. Budget impact scenarios were evaluated, assuming HDx market uptake rates of 5%, 10%, 20%, and 50%. Deterministic and probabilistic sensitivity analyses were performed to assess parameter uncertainty. Adoption of HDx was associated with net cost savings for the Colombian healthcare system across all uptake scenarios. Under hospitalization rates observed in the real-world cohort, estimated annual savings ranged from USD 472,756 to USD 4,727,564 as HDx uptake increased from 5% to 50%. In scenarios reflecting higher hospitalization rates observed in the general Colombian hemodialysis population, annual savings ranged from USD 1,344,401 to USD 13,444,010. Cost savings were primarily driven by reductions in hospitalization frequency. Probabilistic sensitivity analysis showed that HDx was cost-saving in 97.8% of simulations. This study suggests that expanded hemodialysis could result in short-term cost savings for the Colombian healthcare system by reducing hospitalization-related costs without increasing dialysis expenses.

Itch is a complex noxious sensation associated with many skin and systemic conditions, which varies in intensity and quality across different body regions. Despite its prevalence, the molecular and cellular mechanisms underlying regional itch differences remain poorly understood. Investigating the neural basis of regional itch differences, we identified a functional divergence in neuropeptide signaling and central circuit engagement between the trigeminal and spinal systems, which was independent of peripheral innervation density. Utilizing a combination of behavioral, pharmacological, genetic, and molecular assays, we identified a unique population of trigeminal (TG) neurons that facilitate specialized itch-pain coding. Our results indicate that while histamine receptors HRH1 and HRH3 are both involved in mediating mixed itch-and-pain sensations, the specific activity of Substance P (SP)- and Somatostatin (SST)-expressing neurons orchestrates this transition in the cheek. This behavioral shift is mediated by a central mechanism wherein sensory neurons activation recruits distinct nociceptive circuits within the brainstem. In brief, these findings provide insights into the molecular and cellular mechanisms underlying regional itch differences, highlighting the importance of considering anatomical location when developing targeted treatments.