Abstract: A macroscopic boundary-balance framework for gravitational collapse is developed for a timelike thin shell separating an effective interior vacuum reference sector from an exterior Schwarzschild or Schwarzschild–de Sitter region. The interior sector is represented by a coarse-grained reference density ρref(χ) and the associated reference energy Eref=(4π/3)R3ρref. Along the shell history, reference-energy descent occurs when the decrease of ρref dominates the geometric increase of the enclosed volume. This condition defines the effective quasilocal input Φeff=−AΣ−1E˙ref, which is positive precisely on the descending-reference branch. The timelike shell converts this input into a finite boundary response. The central balance law, E˙Σ=AΣ(Φeff−Φout)−PA˙Σ, partitions reference-sector input into quasilocal shell storage, exterior release, and pressure–area work. A trajectory-dependent response coefficient Ceff=dEref/dTΣ parametrizes the local boundary-temperature response; on a negative-response branch, reference-energy descent increases the shell temperature. Local shell temperatures and near-boundary mode frequencies are mapped to exterior static observers by the exterior lapse, with spatial infinity recovered only in the asymptotically Schwarzschild limit. The resulting timelike thin shell is a finite-radius quasilocal boundary that organizes reference-state change through surface stress, flux balance, area response, and redshifted observables. The entropy-like variable SΣ=αAΣ records the macroscopic area response and enters the same balance through the pressure–area work term. The framework identifies the classical boundary variables and closure conditions required for perturbative stability analyses, finite-thickness response models, and microscopic boundary descriptions.

Abstract: Background: The COVID-19 pandemic profoundly disrupted healthcare utilization patterns at both primary care (PC) and hospital emergency department (ED) levels. This study aimed to assess the impact of the pandemic on referral patterns from PC to a hospital ED and on the resource consumption associated with those referrals. Methods: describe briefly the main methods or treatments applied. Methods: A descriptive, retrospective, longitudinal comparative study was conducted at a first level hospital of Madrid (Spain). All consecutive PC-to-ED referrals received during two observation windows were included: a pre-pandemic period (1 June-31 December 2019; n=946) and a post-pandemic period (1 January-30 June 2022; n=1,797). Sociodemographic characteristics, referral form quality, diagnostic specialty, and in-ED resource utilization variables were collected and compared using χ², Student’s t-test, and Mann–Whitney U tests as appropriate. Results: A total of 2,743 referrals were analyzed. The monthly referral rate increased by approximately 122% between periods (135/month vs 300/month). No significant differences were found in patient age (mean 53.1±18.3 vs 54.9±19.0 years; p=0.015) or sex. Referral form completion improved significantly for clinical history (94.5% vs 98.2%; p<0.001). Orthopedics referrals nearly tripled (5.8% vs 18.4%), while respiratory/COVID-19-related referrals represented 22.0% of the 2022 caseload. ED length of stay between 3 and 6 hours increased from 13.0% to 42.8% (p<0.001), while the need for urgent blood tests fell from 68.9% to 56.0% (p<0.001), hospital admission from 68.4% to 10.9% (p<0.001), and referral to another center from 12.3% to 0.9% (p<0.001). Conclusions: indicate the main conclusions or interpretations. The abstract should be an objective representation of the article, it must not contain results which are not presented and substantiated in the main text and should not exaggerate the main conclusions. After the initial COVID-19 waves, PC-to-ED referrals increased substantially while requiring fewer complementary investigations and generating fewer hospital admissions, suggesting improved coordination and clinical resolution capacity between PC and the ED. These findings have important implications for post-pandemic healthcare planning.

Abstract: In the context of the transformation of urban construction from incremental expansion to inventory renewal, the reuse of industrial remnants has gradually shifted from the issue of spatial transformation to that of scene construction. Taking Tianjin as the research object, based on the scene theory framework, by comprehensively applying kernel density spatial analysis and network comment text mining methods, the research is conducted from two levels: spatial structure and public perception. The study found that the three main models of industrial park, museum, and commercial area have significant differences in spatial distribution and accessibility conditions; the network comment analysis further indicates that public perception shows structural differences in the dimensions of neighborhood environment, appropriateness of objects, activities, and values, which essentially stem from the transmission effect of spatial structure on behavior and experience, and then through influencing activity frequency and population structure, shaping differentiated scenes such as "creative life", "consumption leisure", and "historical culture". At the same time, different models generally have problems such as superficial cultural expression, entertainment-oriented experience, and insufficient value recognition. Based on this, a scenario-based renewal strategy oriented towards mechanism optimization is proposed, providing theoretical basis and practical paths for the spatial translation and cultural regeneration of industrial remnants.

Abstract: We conducted a literature review to evaluate global antifungal susceptibility patterns in Candida auris, an emerging multidrug-resistant fungal pathogen of growing clinical concern. A comprehensive search of the literature identified 29 studies reporting min-imum inhibitory concentrations (MICs) and resistance rates across major antifungal classes. Across studies, C. auris demonstrated consistently high resistance to fluconazole, with variable resistance observed among other azoles, amphotericin B, and echi-nocandins, alongside evidence of emerging multidrug resistance. These findings reflect significant geographic variability and highlight ongoing challenges in treatment selec-tion due to inconsistent susceptibility profiles and limited standardized breakpoints. Emerging antifungal agents, including ibrexafungerp and manogepix, demonstrate promising activity and may help address current therapeutic gaps. Overall, the global rise in antifungal resistance among C. auris isolates underscores the narrowing range of effective therapeutic options and reinforces the need for continued surveillance, improved susceptibility testing standardization, and development of novel antifungal agents.

Abstract: Proviral integration — the molecular event that converts HIV infection from reversible to permanent— defines a finite window during which post-exposure prophylaxis (PEP) can succeed. Using a three-state absorbing Markov model parameterized on established HIV-1 kinetic constants, we prove that PEP efficacy decays monotonically to zero and derive the critical prevention window as a function of integrationkinetics rather than drug potency. This window is approximately three-fold shorter for parenteral (injection) than mucosal (sexual) exposure, yielding a parenteral tcrit of 16–28 hours versus 68–76 hours mucosally. For people who inject drugs, empirically documented structural access delays place fewer than 5% of exposures within the parenteral window, bounding expected population-level PEP efficacy below 10%—a failure determined by integration timing, not pharmacology.

Abstract: Aquatic macroinvertebrates inhabit virtually all freshwater ecosystems, yet communities in extreme saline environments remain largely undescribed, particularly in the Tropical Andes. This study characterizes the taxonomic diversity of aquatic macroinvertebrates in a travertine-fed saline stream (salinity: 12.5 ± 0.2 g/L; 2520 m a.s.l., southern Ecuador) and compares it with an adjacent freshwater stream. Macroinvertebrates were sampled on four occasions (n = 4 events per stream) using a multi-habitat D-net technique; physicochemical variables were compared with Mann–Whitney U exact tests, and diversity metrics with exact permutation tests (C(8,4) = 70 permutations) supplemented with Cliff’s delta as effect-size estimator. Community composition was assessed with ANOSIM and non-metric multidimensional scaling (NMDS). A total of 919 individuals were collected. The freshwater stream harbored significantly greater richness (49 genera, 28 families), abundance, and Shannon diversity than the saline stream (14 genera, 8 families; all p = 0.029, Cliff’s δ = 1.00), while Pielou’s evenness did not differ between stream types. Community composition was fully separated (ANOSIM R = 1.00, p = 0.028), with salinity (R² = 0.95, p &lt; 0.01) and water temperature (R² = 0.79, p = 0.03) as the primary environmental drivers. The saline stream was dominated by halotolerant Diptera (Ceratopogonidae, Stratiomyidae) and water mites (Hydrachnidae), with virtually no EPT (Ephemeroptera–Plecoptera–Trichoptera) representation. These findings establish the first macroinvertebrate diversity baseline for a travertine-associated saline stream in the Tropical Andes, highlighting salinity and temperature as key environmental filters of aquatic biodiversity in extreme Andean lotic ecosystems.

Abstract: Alzheimer’s Disease (AD) is now understood as a biologically diverse condition, with amyloid and tau pathology evolving within dynamic neuroimmune networks. This challenges the traditional view that AD-related inflammation can be broadly suppressed therapeutically. We review evidence showing that neuroinflammation in AD is stage-dependent, cell-state-specific, spatially organized, and functionally complex. Microglia and astrocytes can aid in plaque containment, debris clearance, synaptic balance, metabolic adaptation, and tissue repair, but may also exacerbate injury through type-I interferon, inflammasome, complement, tumor necrosis factor, and lipid pathways. Many failed anti-inflammatory trials likely stem from mismatches in targets, timing, spatial considerations, pathway redundancy, and biomarker selection, rather than invalidating neuroinflammation as a therapeutic target. Recent single-cell and spatial transcriptomic, proteomic, metabolomic, and network-medicine studies offer a framework for precision intervention by identifying inflammatory endotypes, anatomical niches, and pathway modules. We propose the Stage–State–Space Neuroimmune Reprogramming Model (S3-NRM), aligning AD immunotherapy with disease stage, glial/endotype state, and spatial inflammatory niche, guided by fluid, imaging, and omics biomarkers. Future therapies should selectively suppress harmful immune responses while preserving beneficial glial functions.

Abstract: The downtime and maintenance associated with the failure of a wind turbine gearbox can be significant, leading to high repair costs. Currently, when warning signals are received through the condition-monitoring system, wind farms typically perform maintenance on the gearbox to ensure continued operation. However, reducing power not only leads to an imbalance between the life of the transmission system and the amount of electricity generated, but also reduces revenue; Moreover, it faces the dilemma of being unable to accurately grasp the health status of the gear transmission system, which increases the difficulty of life extension. To address the above issues, this study proposes a gearbox life extension strategy based on wind turbine control methods. This approach breaks through the limitation of traditional methods where damage assessment is decoupled from operating conditions, and transforms the previous research status where life and power generation optimization were treated as separate entities. And the effectiveness of the life extension strategy was validated using actual operating data from China. The results demonstrated that the proposed strategy could extend the gearbox's life and enhance total power generation.

Abstract: Since tires from end-of-life vehicles are not entirely biodegradable and pose a serious environmental problem, their disposal has grown to be a significant global environmental concern. One technique to decrease these environmental issues is incorporating waste rubber to make sustainable green concrete. This study examined the usage of waste supplementary cementitious materials (SCMs) such as fly ash (FA), metakaolin (MK), marble powder (MP), slag (SL), and silica fume (SF) for surface precoating of crumb rubber (CR) to improve the mechanical properties of the produced crumb rubber concrete (CRC) by strengthening the bond between CR and cement paste in the Interfacial Transition Zone (ITZ). The CR replaced (0, 15%, and 25%) of sand by weight in the preparation of CRC mixtures. A total of eleven CRC mixes were cast to investigate the fresh properties, compressive strength, and splitting tensile strength. In addition, the compressive stress-strain curve was investigated, and peak stress, peak strain, energy absorption, toughness, and modulus of elasticity have been evaluated. The outcomes showed that pre-coating CR using FA, followed by MK, has the maximum effect in increasing the CRC compressive performance. The 25% substitution of sand with FA-treated CR increased compressive strength after 28 days, splitting tensile strength, peak stress, toughness, and modulus of elasticity by 34.7%, 23.7%, 34.8%, 26.1%, and 25.2%, respectively, in comparison to the same percentage of untreated CR. The proposed approach demonstrates a viable pathway for integrating waste materials and SCM-based technologies to develop high-performance, sustainable cementitious composites.

Abstract: Construction management, from the contractor's perspective, is led by the Construc-tion Manager (CM). The work motivation and leadership style of the CM are critical variables for the successful execution of construction projects. Scientific literature identifies participative leadership as the most effective style for mitigating conflicts among various stakeholders. However, analyzing the specific variables that influence a CM's conflict resolution capacity remains an underexplored area. Furthermore, while the CM must act as a leader for their team (subcontractors, suppliers, etc.), they remain accountable to the contractor’s senior management. Therefore, this study aims to ana-lyze the mediating role of CM motivation in the relationship between leadership and conflict resolution capacity using Partial Least Squares Structural Equation Modeling (PLS-SEM). This research contributes to identifying the factors that influence the CM’s conflict resolution capacity during the execution phase, thereby enhancing best prac-tices in knowledge management within the construction industry.

Abstract: Micro-ROS is a lightweight robot operating system for embedded devices with resource-constrained real-time features. Its communication mechanism, based on the XRCE-DDS protocol, facilitates data exchange in constrained environments. To ensure the safety and reliability of message transmission in Micro-ROS, this paper presents an integrated approach that combines simulation and runtime verification. A formal model of XRCE-DDS is constructed using timed automata, while key properties derived from the protocol are expressed in constrained Signal Temporal Logic (STLlb=0). The model is implemented and simulated via Simulink/Stateflow. Furthermore, the key properties are verified with the runtime verification method using the Logical and Temporal Assessments tool in the Test Manager of Simulink Test. Through integrating simulation with runtime verification, this work effectively improves the safety assurance of the Micro-ROS communication mechanisms.

Abstract: Recent advances in CRISPR technology have expanded beyond traditional double-strand break–based genome editing to include base editors and prime editors, enabling precise and programmable sequence modifications. This evolution marks a shift from conventional mutation correction toward platform-based therapeutic systems capable of targeting a broad spectrum of pathogenic variants. Such versatility holds promise for treating over 90% of known disease-causing mutations in rare monogenic disorders. This review will discuss the technological progression of CRISPR systems, highlighting the principles, applications, and limitations of emerging editing modalities. We will explore their translation into personalized gene therapies, emphasizing delivery challenges, off-target safety, and the need for regulatory innovation. The paper will also introduce the concept of interventional genetics, an emerging medical framework linking genomic diagnosis directly to therapeutic intervention through adaptive gene-editing platforms. Finally, we will outline strategies for establishing unified, scalable, and regulatory-ready editing platforms that can accelerate the clinical implementation of individualized therapies for rare diseases.

Abstract: Brain metastases remain a major cause of morbidity and mortality in patients with cancer, particularly melanoma and non-small cell lung cancer. Stereotactic radiosurgery (SRS) is a cornerstone of management for limited intracranial disease, offering high local control while minimizing the neurocognitive toxicity associated with whole-brain radiotherapy. Immune checkpoint inhibitors (ICIs) have also transformed systemic therapy for tumors with central nervous system involvement, creating increasing clinical need to define how best to integrate these modalities.The combined use of SRS and ICIs has raised an important question regarding optimal treatment timing. Retrospective evidence suggests that concurrent or near-concurrent administration, commonly defined as treatment within approximately 2–4 weeks, may improve local control and intracranial response. Several studies also suggest a potential survival advantage compared with sequential treatment, although these findings are limited by selection bias and require prospective validation. Most contemporary analyses do not show a significant increase in radionecrosis (RN) with concurrent single-agent ICI; however, emerging data suggest that dual checkpoint blockade may increase the risk of symptomatic RN.This narrative review synthesizes the biologic rationale, clinical evidence, and toxicity considerations for combining SRS and ICIs in patients with brain metastases. We emphasize differences between single agent and dual ICI strategies, highlight dosimetric predictors of RN such as V12 Gy, and propose a practical framework for treatment integration. Overall, concurrent SRS with single-agent ICI appears feasible and is associated with favorable intracranial outcomes in selected patients, whereas dual ICI warrants more cautious, individualized decision-making. Prospective studies are needed to define optimal sequencing, patient selection, and toxicity mitigation strategies.

Abstract: Background: Gender differences in adolescent mental health are well documented; however, the extent to which modifiable behavioral and psychosocial factors account for the excess of mental health problems in females remains insufficiently quantified. Methods: Data from the 2025 Corona and Psyche South Tyrol (COP-S) survey comprised a base sample of 2,428 adolescents aged 11–19 years (51.4% males) with valid self-reported data. Multivariable regression analyses were conducted on 1,448–1,603 adolescents (depending on the outcome) who provided complete responses to the relevant predictor and outcome measures. Gender differences in depression scores (PHQ-2), anxiety scores (SCARED-GAD), and emotional/behavioral difficulties (SDQ) were examined using Mann-Whitney U and chi-square tests. Multivariable linear regression models were used to assess the associations between mental health outcomes and the ten predictors. Gender effects were quantified by comparing standardized regression coefficients from unadjusted and adjusted models. Results: Female adolescents reported higher anxiety (median 6 vs. 4; rank-biserial r = 0.24), depression (r = 0.13), and emotional/behavioral (r = 0.08) scores than male adolescents. School stress, problematic Internet use, and poor sleep quality were the strongest predictors of all three outcomes (all p &lt; 0.001). After multivariable adjustment, gender remained a significant predictor of anxiety (β = 0.18) and depressive scores (β = 0.09) but no longer reached significance for emotional/behavioral scores (β = 0.04, p = 0.078). The attenuation of the gender effect ranged from 25.3% for anxiety to 37.1% for depression and 58.5% for emotional/behavioral difficulties. Conclusions: Gender differences in adolescent mental health are partially explained by modifiable behavioral and psychosocial factors, with the excess of females in emotional/behavioral scores fully accounted for by these covariates. Persistent gender disparities in anxiety indicate the need for anxiety-specific preventive strategies that target mechanisms beyond the measured behavioral correlates.

Abstract: Background: Acute lymphoblastic leukemia (ALL) is the most common malignancy in the pediatric population. Despite significant therapeutic advances over the past four decades, a critical survival gap persists between North America and Latin America, indicating that non-biological determinants exert a decisive influence on clinical outcomes across the continent. Objective: To synthesize the evidence on the impact of socioeconomic determinants and access barriers on clinical outcomes in pediatric ALL across the Americas, published between 2015 and 2025. Methods: An integrative review was conducted following the five-stage Whittemore and Knafl framework and PRISMA 2020 reporting guidelines. The databases PubMed/MEDLINE, Scopus, SciELO, and LILACS were searched using structured Boolean queries combining MeSH and DeCS controlled vocabulary. Studies examining pediatric ALL (ages 0-18 years) in any country of the Americas, published between January 2015 and December 2025, were included. Results: A five-year overall survival (OS) gap of up to 40 percentage points was identified between high-income countries and Latin American settings (>90% vs. 50-75%). Low household income and lack of private insurance independently predicted inferior event-free survival (EFS), with differences of up to 30%. Treatment abandonment reached 30-40% in rural Latin American areas, driven by geographic distance exceeding 70-150 km to specialized centers and financial toxicity. Treatment-related mortality (TRM) of 15-25% was primarily attributable to sepsis and the absence of pediatric early warning systems (PEWS). A high prevalence of high-risk genomic alterations, including IGH::CRLF2 rearrangements and IKZF1 deletions linked to Amerindian and Hispanic ancestry, was documented. Conclusions: Survival outcomes in pediatric ALL across the Americas are primarily determined by biosocial factors. Closing the survival gap requires strengthening supportive care infrastructure, implementing ancestry-adapted precision medicine, and dismantling the socioeconomic barriers that limit equitable access to curative therapy.

Abstract: Geographical Indications (GIs) are increasingly promoted as instruments for rural up-grading and value capture in commodity-dependent economies. Yet empirical assess-ments of GI feasibility in smallholder export systems remain limited. This study eval-uates whether Cameroon’s red cocoa satisfies the scientific and institutional conditions required to support a credible GI strategy. We develop an integrated qualification framework encompassing four necessary con-ditions: agroecological distinctiveness, physicochemical differentiation, sensory dif-ferentiation, and governance feasibility. Spatial analysis, laboratory characterization, structured sensory evaluation, and institutional diagnostics are combined to assess whether these conditions jointly sustain origin-based differentiation. Results indicate that red cocoa exhibits territorially coherent agroecological features and statistically meaningful biochemical differentiation, including elevated polyphenol and anthocyanin profiles in core production zones. Sensory evaluation confirms identifiable flavor attributes consistent with fine-flavor positioning, though variability linked to post-harvest management affects reproducibility. Institutional analysis reveals partial readiness, with emerging production specifications under the OAPI framework but limited enforcement capacity and traceability infrastructure. The findings suggest that red cocoa meets several scientific preconditions for GI con-sideration, but governance consolidation and post-harvest standardization remain critical constraints. GI feasibility should therefore be interpreted as conditional rather than automatic. More broadly, the study contributes an integrated analytical approach for assessing origin-based upgrading strategies in Global South commodity systems under increasing sustainability regulation.

Abstract: Feature selection is crucial for high-dimensional sensor and biomedical data because it reduces redundancy, improves generalization, and supports interpretable biomarker discovery. In this study, we propose a Binary Chaos-Enhanced Newton-Raphson-Based Optimizer (BCNRBO) for wrapper-based feature selection. The method integrates chaotic search dynamics, a Hamming-distance-based dynamic potential mechanism, and a new binary transfer function to enhance exploration and prevent premature convergence. BCNRBO was evaluated on 26 benchmark datasets using K-nearest neighbor (KNN), decision tree (DT), and Naive Bayes (NB) classifiers. The proposed method consistently achieved competitive or superior classification performance while selecting fewer features than competing binary metaheuristic methods. In particular, BCNRBO obtained the best feature reduction in 15 datasets with DT and 14 datasets with NB, and it achieved top Friedman ranks in 8 DT datasets and 9 NB datasets. Statistical tests confirmed significant improvements over competing methods in most pairwise comparisons. These results suggest that BCNRBO is a promising feature- selection strategy for sensor-derived biomedical and neurorehabilitation data, where compact and reliable digital biomarkers are needed.

Abstract: This study critically examines the construction of medical conceptions regarding the so-called “early intoxications” in the early twentieth century. Its objectives focus on understanding how intoxications from psychoactive stimulants – such as alcohol, tobacco, tea, and coffee – as well as carbon monoxide, were conceptualized. A historical-documentary analysis of medical sources from the period was conducted, prioritizing scientific and clinical texts that describe pathophysiological mechanisms, symptomatology, and explanatory frameworks. The results indicate that these intoxications were understood as gradual, often silent processes capable of weakening the body and reducing its resistance to other pathologies. In the case of carbon monoxide, particular attention was given to the early identification of chronic exposures in domestic and urban contexts. It is concluded that the historical analysis of these formulations contributes to an understanding of the origins of current public health and toxicology models, emphasizing the importance of integrating historical perspectives into contemporary scientific reflection.

Abstract: This study used chemometric models to measure caffeine (CAF), aspirin (ASP), and paracetamol (PAR) in the presence of three hazardous impurities: salicylic acid (SAL), P-nitrophenol (PNP), and P-chloroacetanilide (PCA). A molecular docking study was used to examine how impurities might inhibit cyclooxygenase-2, highlighting the importance of controlling their levels if present in the dosage form. Four sustainable chemometric models: principal component regression, multivariate curve resolution-alternating least squares, artificial neural networks, and partial least squares, were developed. The quantitative analytical performance of all proposed models was evaluated using the per cent recovery, standard error of prediction, and root mean square error of prediction. The developed models covered the concentration ranges (in µg/mL) of PNP (2.00-6.00), PCA (0.50-0.90), SAL (6.00-14.00), ASP (6.00-14.00), CAF (3.00-19.00), and PAR (2.00-10.00). These models effectively addressed collinearity and spectral overlaps. Seven innovative tools, including the Carbon Footprint Reduction Index, Click Analytical Chemistry Index, Multicolour assessment tool, Analytical Green Star Area, spider chart, green solvent selection tool, and Modified Green Analytical Procedure, were used to calculate the sustainability and whiteness of the developed models.

Abstract: Behavioral addiction in digital environments is an increasingly relevant neurobehavioral phenomenon characterized by persistent engagement with high-frequency, algorithmically optimized reward stimuli. Although neural correlates of addictive behaviors have been widely studied, current models only partly explain how modern reinforcement environments reorganize behavior at the systems level. This review introduces Reward Instability Theory, a conceptual dynamical systems framework proposing that behavioral addiction may emerge as an attractor-like state within distorted reward landscapes shaped by high-density and high-variance reinforcement signals. The model shifts focus from static behavioral descriptions toward a systems account of motivation involving reinforcement learning, salience attribution, executive control, and environmental reward structure. We propose that digital environments may increase reinforcement density and reward variance, promoting dominant reward peaks and reducing behavioral diversity. To formalize these dynamics, we outline the Behavioral Reward Instability Index (BRII) as a heuristic systems construct integrating individual reward sensitivity, environmental reinforcement structure, and behavioral variability. The framework also situates established addiction models—including incentive sensitization, habit formation, and allostatic regulation—within a shared dynamical architecture. In addition, digital phenotyping is discussed as a potential empirical strategy for testing reward instability, while acknowledging limitations related to signal noise, ecological validity, bias, and privacy.