Abstract: Pediatric acute-onset neuropsychiatric presentations occurring in the context of prior streptococcal exposure remain clinically important but diagnostically inconclusive, particularly at the interface between PANS and PANDAS. This observational cohort study examined whether serological, psychometric, and electroencephalographic findings converged within a clinically selected pediatric psychiatric sample. Children and adolescents presenting with acute-onset or abruptly worsened neuropsychiatric symptoms and a history suggestive of prior streptococcal exposure were recruited over a 12-month period through inpatient and outpatient child psychiatric services. Of 154 screened cases, 96 with analyzable baseline data were retained and stratified by ASO status. Symptom burden was quantified using the Pediatric Acute-onset Neuropsychiatric Syndrome 31-Item Symptom Rating Scale (PANS-31) and examined in relation to ASO titers, time since the last reported streptococcal infection, EEG findings, and selected developmental and clinical-history variables. Higher ASO values were strongly associated with greater PANS-31 symptom burden, whereas a shorter interval since the last reported streptococcal infection was associated with both higher ASO titers and higher symptom scores. PANS-31 showed good total-scale internal consistency and meaningful domain-level convergence with age-appropriate CSI-4 and ASI-4 domains. These findings do not support a disease-specific biomarker model, but suggest that higher antistreptococcal serology, more recent streptococcal exposure, and greater neuropsychiatric burden may cluster within a more clearly expressed clinical phenotype in a real-world psychiatric environment.

Abstract: ABS is widely used as engineering plastic, but extensive use generates a significant amount of waste which is difficult to recycle due to material's complex composition. Physical recycling of ABS using TNO Möbius dissolution technique has been used here to separate pure SAN polymer, from PBR, and other substances. Relationships between properties and composition of the original materials were investigated as a starting point for evaluation of the effects of recycling on the quality of recycled materials. Three ABS materials were used in the recycling process to produce pure SAN polymers. The recycled SANs were then melt-blended with fresh masterbatch. The final ABS ma-terials had the same composition which allowed to investigate whether SAN recycled from different sources causes differences in properties of the final ABS materials. All properties of ABS materials made with recycled SAN are similar regardless of the source of SAN. Substances were quantified in the original ABS materials and in SAN polymers obtained by the recycling process. The substances were largely removed from all materials except one. The main conclusions from this study are that SAN polymer obtained by physical recycling from different sources does not affect properties of the final ABS material and the TNO process successfully separates SAN from other substances.

Abstract: Background/Objectives: Aluminum-adjuvanted vaccines are widely used in pediatric immunization, yet particle size and distribution are critical but under-standardized quality attributes. Methods: This study aimed to establish and validate a laser diffraction particle size analysis for evaluating particle size consistency and stability of inactivated enterovirus 71 (EV71) vaccine and adsorbed acellular diphtheria–tetanus–pertussis (DTaP) vaccine. Results: EV71 vaccine stock solution (40–350 nm) and aluminum adjuvant (75–600 nm) exhibited distinct distributions, with the final product showing bimodal distribution (50–14,000 nm): main peak at 0.1–0.2 μm (~65%) and secondary peak at 0.3–3 μm (~14%). DTaP final product (2000–20,000 nm) showed significant aggregation with 79.6% at 3–8 μm and 15.7% at >8 μm. Four EV71 batches (A1–A4) showed uneven inter-batch consistency (D50: 100, 132, 103, 103 nm; CV 13.8%), while intra-batch CVs were acceptable (3.9% for EV71, 8.0% for DTaP). Long-term stability at 4°C revealed gradual aggregation: EV71 D50 increased from 100 nm to 134 nm over 60 days, with >0.2 μm aggregates increasing from 0.03% to 1.50%; DTaP showed severe tailing at day 60 (>50 μm particles: 2.8%). Accelerated studies showed 37°C caused slight enlargement, whereas −20°C induced marked aggregation (EV71 D50: ~37 μm, CV 16.1%; DTaP D50: ~45 μm, CV 13.8%). Conclusions: Laser particle size analysis is a robust, reliable tool for assessing particle size consistency and stability of aluminum-adjuvanted vaccines. It supports process control, batch release, and stability monitoring to improve vaccine quality and safety.

Abstract: This study investigates the structural and sorption characteristics of nanostructured polysaccharide biopolymers isolated from the tubers of dahlias (Dahlia spp.) and Jerusalem artichokes (Helianthus tuberosus). The plant raw materials were subjected to preparation and extraction to isolate pectin biopolymers, after which the resulting pectins were purified and dried to a stable state, ensuring their suitability for further physicochemical and sorption studies. The obtained pectin matrices were characterized using scanning electron microscopy (SEM) to analyze morphology and nanostructure, infrared (FTIR) and Raman spectroscopy to identify functional groups, as well as atomic absorption spectrometry to study sorption properties. The use of Raman spectroscopy further confirmed the presence of characteristic structural fragments of pectin and revealed changes in the vibrational spectra of functional groups upon interaction with metal ions. The ability of biopolymers to adsorb the heavy metal ions Cu²⁺ and Zn²⁺ from aqueous solutions was investigated. It was shown that as the concentration change (ΔC) increases, the sorption capacity increases; in most cases, the sorbent derived from dahlia tubers (DT) exhibits higher activity compared to Jerusalem artichoke (HT), which is associated with structural features and the availability of functional groups. Analysis of sorption isotherms showed that the adsorption of Cu²⁺ is well described by the Langmuir and Freundlich models, indicating a mixed sorption mechanism, whereas the Freundlich model is more appropriate for Zn²⁺, reflecting the heterogeneity of the surface and the presence of active sites with different interaction energies. The obtained data confirm the potential of nanostructured pectin biopolymers as environmentally safe sorbents for the removal of heavy metals from aqueous media and serve as a basis for the development of new sorption materials.

Abstract: Background/Objectives: The Child-Pugh system is widely used to grade cirrhosis severity but includes clinical components that may be variably documented. This study evaluated the association and diagnostic performance of the aspartate aminotransferase-to-platelet ratio index (APRI), fibrosis-4 (FIB-4) index, and albumin-bilirubin (ALBI) score for discriminating Child-Pugh classes in cirrhosis. Methods: We conducted a retrospective cross-sectional study using medical records from 302 adults with cirrhosis treated at Thai Binh General Hospital, Vietnam, from January to June 2025. Child-Pugh class was reconstructed from bilirubin, albumin, PT%, ascites, and hepatic encephalopathy. APRI, FIB-4, and ALBI were calculated from routine laboratory data. Group comparisons, correlation analysis, multivariable regression, receiver operating characteristic analysis with bootstrap 95% confidence intervals, optimal cut-offs, and reclassification metrics were assessed. Results: Among 302 patients, 48 (15.9%) were Child-Pugh A, 120 (39.7%) Child-Pugh B, and 134 (44.4%) Child-Pugh C. ALBI values differed consistently across Child-Pugh classes (-2.23 ± 0.37, -1.65 ± 0.45, and -0.80 ± 0.46; p < 0.001), whereas APRI and FIB-4 showed less distinct separation between classes. ALBI showed a strong correlation with the Child-Pugh score (r = 0.853, p < 0.001) and remained associated with Child-Pugh severity in multivariable linear and logistic regression models. Among the three indices, ALBI showed the highest discrimination for Child-Pugh B/C versus A in this cohort (AUC, 0.919; 95% CI, 0.884-0.950), with an estimated optimal cut-off of -1.753. Conclusions: In this retrospective cohort, ALBI showed closer agreement with Child-Pugh severity and higher discrimination for Child-Pugh B/C versus A than APRI and FIB-4. ALBI may be considered as a simple laboratory-based adjunct to support Child-Pugh stratification in routine cirrhosis assessment, but further prospective validation is required before broader clinical application.

Abstract: This paper presents a method for continuously optimizing the turn-on and turn-off angles of a switched reluctance generator (SRG) operating in single-pulse mode and connected to an asymmetric bridge converter. The optimal angles are defined as those that minimize total SRG loss while ensuring accurate tracking of the terminal voltage reference. The Pearson correlation coefficient between SRG loss and selected SRG variables was calculated, with the highest correlation found for the average value of all phase currents. Therefore, the average phase current was selected as the variable to be minimized in a perturb-and-observe (P&O) method used to determine the optimal turn-on angle at a given operating point. The turn-off angle was calculated to maintain the terminal voltage at its reference value. The method was validated using both a conventional SRG simulation model and an advanced model that accounts for mutual coupling, iron losses, and remanent magnetism, and was further verified experimentally on an 8/6 SRG rated at 1.1 kW under various load conditions, terminal voltages, and rotor speeds.

Abstract: Bispecific T-cell engager (TCE) development continues to attract substantial industrial investment alongside a translation record that remains uneven across target antigens and disease settings. Multiple independent reports across the field have observed that target antigen density on tumor cells does not predict cytotoxic potency or clinical response, while other reports describe within-target density-potency correlations of widely varying strength. These findings, when read in parallel, appear contradictory and have not been organized by any unifying analytical framework that has gained adoption in the field's standard practice. A mechanistically motivated joint binding-effector framework suggested that this apparent contradiction may reflect a single biological structure being read through analytical conventions that examine target antigen density and effector-side biology in isolation. To investigate this systematically, we assembled a verified dataset of bispecific TCE clinical-stage programs spanning eleven target antigens (CD19, CD20, BCMA, GPRC5D, CD33, CD123, CLL-1, FLT3, EpCAM, PSMA, and DLL3) and read it against the published primary-source record of within-target density-outcome reports. The systematic empirical pattern that emerges is consistent with a joint binding-effector structure in which neither variable alone is sufficient. In the limiting case, target cells lacking the antigen produce no cytotoxicity at any effector-to-target ratio. The published record reflects the two variables asymmetrically by design: target antigen density is reported across cell-line panels, primary samples, and clinical correlative cohorts, while effector-side variation is structurally absent from cell-line panels (which fix effector-to-target ratios at non-biological values with uniform donor T cells) and is observable only in primary-sample and clinical correlative analyses. Across approved drug programs at clinical exposure, target antigen density does not predict outcome (verified in multiple peer-reviewed primary samples and clinical correlative analyses including a registration-trial cohort of n=165); in those same settings, measures of effector-side biology -- effector-to-target ratio, T-cell counts, regulatory T-cell frequency, and exhaustion markers -- are associated with outcome, consistent with the elementary requirement that both antigen-bearing targets and adequate effector cells are needed for TCE activity. Within-program triangulation in a discontinued clinical-development program (CD33/AMG 330) demonstrates the same structural pattern in the failure direction. We propose the joint binding-effector account as a testable explanation that reconciles the systematic empirical record assembled here: it is logically coherent, internally consistent, and consistent with the field's documented findings. The systematic dataset and the verified primary-source documentation are deposited as supplementary material to support independent evaluation.

Abstract: Complex adaptive systems (CAS) have two defining characteristics. First, they are complex, i.e., composed of several interacting parts. Second, they are adaptive, i.e., their behavior can be changed in response to external stimuli and changes in the external environment. Due to this, managing such systems is quite challenging. Traditional approaches have involved defining policies that determine the behavior of any CAS under particular circumstances. However, such approaches are rigid and inflexible, since they are dependent on pre-specified policies. To that end, in this position paper, we describe an intent-driven approach to modeling and managing CAS. This would be a more flexible approach, not dependent on any specific policies, but which can be customized based on the context in which the CAS is functioning. We describe the various components of our approach, which include compositional reasoning to decompose the intent into sub-intents as per the context; mapping the sub-intents onto the execution model which will satisfy the intent; and feeding back the results of the execution to facilitate continual learning and continuous improvement in managing the CAS. In particular, one aspect that we highlight is the application of neurochaos learning, which uses chaos theory to facilitate rapid continual learning that would help improve the overall efficiency of our approach. For each component of our approach, we also present several research questions that need to be addressed before intent-driven management of CAS can become a reality.

Abstract: Background: Stress may have an impact on the course of inflammatory bowel disease (IBD), but evidence is still lacking regarding a potential association between perceived (subjective) stress and objectively measured stress, and whether patients’ levels of stress in relapse differ from those in remission. The aim of this study was to investigate patients’ level of stress in relapse and in remission. Methods: Twenty-three patients with active IBD participated in the study. Cortisol was assessed in saliva and in blood to obtain objective measurements. For subjective meas-urements, the patients completed the Short Health Scale (SHS) and Perceived Stress Scale (PSS) questionnaires. Physiological measurements were taken and questionnaires com-pleted at the beginning of relapse and when the patient was classified as being in re-mission. Relapses and remissions were determined by endoscopic examination and faecal calprotectin. Results: Cortisol levels did not differ between measurements in active disease and in remission. PSS showed no differences between the two measurements, but on both oc-casions medium-high levels of stress were shown. Inflammatory cytokines IL-6 and IL-8 showed significantly lowered values at remission. Conclusion: This study demonstrated moderate levels of perceived stress in patients with IBD, both during active disease and remission. However, no evidence of elevated ob-jective stress was found when levels of cortisol in saliva were measured. Further research is needed to establish the possible association between stress and IBD and how it affects patients.

Abstract: This study examines how the Internet of Things (IoT) acts as a key enabler of sustainability in industrial production systems within the Industry 4.0 paradigm, addressing the fragmented understanding of the mechanisms linking digital technologies to environmental, operational, and emerging human-centric outcomes. A systematic literature review was conducted following PRISMA 2020 guidelines using the Web of Science Core Collection. After applying explicit inclusion and exclusion criteria, 69 peer-reviewed studies published between 2016 and 2026 were analyzed through qualitative thematic synthesis and comparative analysis. The findings reveal that IoT functions as a foundational digital infrastructure enabling real-time monitoring, operational transparency, and data-driven decision-making in production environments. Four dominant application domains are identified: (i) energy and resource efficiency, (ii) production monitoring and control, (iii) predictive maintenance and asset management, and (iv) emerging human-centric production systems aligned with Industry 5.0. While IoT consistently improves operational reliability and resource efficiency, its contribution to the social dimension of sustainability remains comparatively underdeveloped. This study advances existing literature by providing a mechanism-oriented synthesis that explains how IoT-enabled infrastructures generate sustainability outcomes across production systems. Furthermore, it establishes a conceptual bridge between Industry 4.0 digitalization and the transition toward human-centric and resilient manufacturing models associated with Industry 5.0. From a practical perspective, the results highlight that IoT adoption contributes to reducing energy consumption, optimizing resource utilization, and enhancing operational performance, while also supporting safer and more adaptive working environments. However, challenges related to data integration, workforce adaptation, and digital capability gaps persist, underscoring the need for inclusive and strategically aligned digital transformation processes.

Abstract: Self-check-in via digital technology is becoming increasingly prevalent to streamline workflows and improve primary care efficiency, including kiosks, eCheck-in via portals, mobile check-in apps, and pre-appointment questionnaires. This scoping review examines the value-creation potential of digital self-check-in tools by assessing the quality of intake data generated with these tools and their reuse. Following the Joanna Briggs Institute guidelines for conducting scoping reviews and the PRISMA-ScR reporting criteria, searches were conducted across the CINAHL, PubMed, and Google Scholar databases to identify English-language peer-reviewed studies published between 2021 and 2026. In total, 488 studies were identified; 361 were assessed based on titles and abstracts after duplicate removal, 65 were reviewed in full text, and 15 studies were included in the final review and graded using the Johns Hopkins Nursing Evidence-Based Practice (JHEBP) levels and quality ratings. Most of the evidence was level III with a B quality rating. Findings showed that the portal and pre-visit questionnaire approaches provided the most reliable support for data structuring, visit preparation, and communication between the patient and the clinician. In turn, improvements in workflow efficiency, reduced patient congestion, increased throughput, and minimized front-desk burden could be achieved primarily through studies focused on kiosks and registration processes. Across the study, the strongest evidence supports operational and informational value rather than return on investment (ROI). The main barriers to the effective implementation of the interventions included access inequity, workflow integration, staff training, and bad data quality. Overall, digital self-check-in tools create value in primary care when patient-generated intake data are timely, complete, structured, and reusable across downstream clinical and administrative workflows. However, stronger evidence is still needed regarding measurable economic return.

Abstract: Quantumgateestimationandtomographypipelinesroutinelycombineintrinsicallydefined likelihoods with priors or regularization terms specified in local Euclidean coordinates. This practice implicitly replaces the Haar reference measure on SU(2) with Lebesgue measure, specifying a different statistical model rather than a reparametrization of the intended one. Weshowthat omitting the associated chart-volume factor alters the optimization objective itself, modifying its gradient field and stationary-point structure. The mismatch persists arbitrarily close to the identity, so that flat-coordinate surrogate objectives can converge to points that are non-stationary for the corresponding Haar-consistent objective even in regimes where local Gaussian approximations are assumed valid. We prove a formal non-equivalence proposition and validate a leading-order Fisher-information correction analytically and numerically. Large-scale multi-start optimization experiments (N = 11,900 runs) demonstrate that the discrepancy is regime-dependent and most pronounced under moderate-to-strong regularization or limited data. The fix requires a single-line modification to any gradient-based optimizer. These results identify reference-measure selection as an explicit modeling decision with direct consequences for optimization and inference in gate-set tomography, randomized benchmarking, and Bayesian gate estimation on curved parameter manifolds.

Abstract: Background/Objectives: Peri-implant diseases, encompassing peri-implant mucositis and peri-implantitis, affect 43% and 18.8–23% of implant-bearing patients respectively, representing significant clinical challenges in implant dentistry. While mechanical debridement remains foundational, biologically active materials offer promising adjunctive regenerative strategies. This narrative review synthesises current evidence regarding five biologically active materials: enamel matrix derivative (EMD), platelet-rich fibrin (PRF), fibroblast growth factor-2 (FGF-2), recombinant human platelet-derived growth factor-BB (rhPDGF-BB/GEM 21S®), and polynucleotide-hyaluronic acid combinations (Regenfast®). Methods: Relevant literature was identified through electronic databases, including MEDLINE, PubMed, Scopus, and Google Scholar. The review focused on clinical studies and randomised controlled trials with a minimum follow-up of six months investigating biologically active materials in peri-implant disease management. Material mechanisms, clinical efficacy, therapeutic limitations, and evidence quality were systematically evaluated. Particular attention was directed toward distinguishing genuine biological distinctions between peri-implant and periodontal disease contexts. Results: EMD demonstrates efficacy exclusively within multimodal surgical protocols, with isolated application yielding limited benefits. rhPDGF-BB shows superior periodontal regenerative capacity; however, dedicated peri-implantitis trials remain absent. FGF-2 exhibits paradoxical osteogenic suppression despite bone fill achievement, limiting peri-implant applicability. PRF and Regenfast® demonstrate mechanistically sound rationale yet lack substantive peri-implant disease validation. Critical findings revealed that peri-implant regeneration fundamentally differs from periodontal regeneration: implants lack periodontal ligament anatomy, rendering ligamentogenic differentiation–promoting agents biologically inappropriate. Conclusion: Contemporary biologically active materials demonstrate compelling periodontal efficacy yet remain inadequately validated for peri-implantitis management. This disparity reflects authentic biological distinctions rather than insufficient investigation. Until multicentre randomised controlled trials stratify efficacy across distinct peri-implant disease presentations, practitioners must prioritise evidence-based surgical fundamentals: meticulous decontamination, strategic grafting, and optimised wound healing, integrating biologically active materials judiciously within comprehensive, anatomy-respecting treatment protocols.

Abstract: Sirolimus is a potent mTOR inhibitor used primarily to prevent acute rejection in transplant recipients. Its clinical management is challenging because of its narrow therapeutic index, low and highly variable oral bioavailability, and pronounced inter-individual variability driven by CYP3A4/5-mediated metabolism and P-glycoprotein efflux. Extensive partitioning into erythrocytes further complicates its disposition and necessitates therapeutic drug monitoring. Here, we developed a mechanistic whole-body physiologically based pharmacokinetic (PBPK) digital twin of rapamycin that integrates complex absorption kinetics, nonlinear distribution, and first-pass metabolism. The SBML-encoded model was calibrated and evaluated against a comprehensive library of curated clinical pharmacokinetic data, comprising studies primarily in healthy volunteers and stable renal transplant recipients. The dataset covers diverse ethnic populations, cohorts with varying degrees of renal and hepatic impairment, and individuals with relevant genetic polymorphisms. The digital twin captured overall trends in rapamycin blood concentrations across a wide range of doses and dosing regimens. Simulations showed good agreement with observed data under hepatic and renal impairment, as well as under fasted and fed conditions. Furthermore, the model reproduced the magnitude of drug--drug interactions involving potent CYP3A4 inhibitors, CYP3A4 inducers, and concomitant immunosuppressive agents. This SBML-based digital twin provides a quantitative framework for characterizing sirolimus dose dependency and the multifactorial effects of intrinsic and extrinsic factors on systemic exposure. By providing the model in a standards-based, executable format together with simulation scripts and curated pharmacokinetic datasets, this work supports independent reproduction, transparent model evaluation, and systematic reuse in accordance with FAIR principles.

Abstract: Autism spectrum disorder (ASD) is a neurological condition with an increasingly high incidence rate due to more effective diagnostic tools. The symptoms of ASD vary widely, making it difficult to detect. It represents a spectrum of alterations ranging from mild indications to severe impairments. Given this clinical presentation, each patient should be treated on an individual basis. Nevertheless, certain neuropathological changes are common, although the background of this disorder remains still unknown. Therefore, some research aimed at better understanding the pathology of the neurological alterations in ASD, as well as the possibilities for early diagnosis and treatment of this disorder, is urgently needed. This study presents the results of the studies on some selected proteins such as Tau protein, NFL, BDNF as well as IGF-1 that appear to be the best protein candidates for better understanding the causes of autism, as well as for use as fluid biomarkers in diagnosis and monitoring of ASD.

Abstract: Product recognition in e-commerce live streaming is hindered by rapid viewpoint changes, occlusions, motion blur, and inconsistencies between visual and spoken information. Existing approaches typically focus on individual components such as detection, OCR, or speech recognition, which limits their effectiveness in end-to-end scenarios.To address this problem, we propose an integrated framework that combines task-oriented keyframe selection with multimodal semantic fusion. The framework first uses D-FINE to localize product regions, and then selects informative frames through two complementary strategies. Strategy A considers both detection confidence and Laplacian-based sharpness, while Strategy B combines detection confidence with a learned image-quality score estimated by an EfficientNetV2-based model. OCR, visual recognition, and ASR are then applied to the selected data, and a Qwen-Plus large language model is used to integrate multimodal evidence into structured product outputs. Experiments on an in-house dataset demonstrate significant gains over a last-frame baseline. Strategy A increases Perfect Match Rate from 58.00% to 80.00% and Product Name Recognition Accuracy from 78.00% to 98.00%. Strategy B achieves 77.00% and 98.00%, respectively. Ablation studies further show that the full multimodal framework consistently outperforms unimodal and dual-modality variants. In addition, Top-K analysis indicates that single-frame inference provides a good balance between performance and efficiency.Overall, the proposed framework offers an effective and practical solution for product recognition in complex live-streaming scenarios.

Abstract: Determining the compatible prestress and geometry under self-weight constitutes a key challenge in the form-finding of cable-truss structures. To overcome the limitations of experience-dependent trial methods and enhance computational efficiency, this paper proposes an automated and integrated methodology by synergistically combining a simplified mechanical model with an improved Particle Swarm Optimization (PSO) algorithm. The core of the method lies in formulating the form-finding process as an optimization problem, where the horizontal inclination angles of the lower chord cables serve as the design variables for all radial cable-truss frames. To efficiently solve this high-dimensional optimization problem, an improved PSO algorithm, which introduces logistic chaotic mapping for particle initialization and a mutation operator within the iterative loop. Ablation studies confirm the individual contribution of each algorithmic enhancement. The algorithm intelligently searches for the optimal angle set, thereby simultaneously resolving the prestress and geometry. The proposed approach is rigorously validated through two representative numerical examples: a circular Type I and an elliptical Type II cable-truss, considering both cases with and without self-weight. The results demonstrate that the improved PSO-based solution achieves prestress distributions and nodal coordinates in excellent agreement with established benchmark data. More importantly, it attains this high precision with significantly reduced computational cost in terms of particle swarm size and iteration number. In conclusion, this improved PSO‑based approach provides an efficient, accurate, and automated tool for the integrated prestress‑geometry design of cable‑truss structures, demonstrating strong potential for practical engineering application.

Abstract: Chikungunya virus (CHIKV), traditionally recognized as a mosquito-borne alphavirus that causes febrile illness and debilitating arthralgia, has increasingly been associated with atypical organ involvement, including respiratory manifestations. These observations raise important questions regarding whether respiratory symptoms reflect severe systemic disease or signal previously underappreciated respiratory exposure routes. This review aimed to synthesize current evidence on respiratory complications of CHIKV infection and to evaluate the plausibility of respiratory or aerosol-associated transmission. A systematic literature search of PubMed, EMBASE, and MEDLINE (Ovid) identified five eligible studies spanning clinical virology, outbreak surveillance, epidemiology, and experimental aerosol models. Across human studies conducted in India, Réunion Island, Puerto Rico, and Brazil, respiratory presentations—including pneumonia, dyspnea, and respiratory failure—were uncommon but consistently associated with increased hospitalization and mortality risk. Respiratory symptoms generally arose in the context of respiratory viral coinfections, systemic inflammation, or cardiopulmonary decompensation rather than primary viral tropism for the respiratory tract. Only one non-human primate study directly evaluated aerosol exposure, demonstrating that cynomolgus macaques could be infected via inhaled CHIKV, confirming biological plausibility but showing no evidence of enhanced respiratory pathology. Importantly, no epidemiologic data support human-to-human airborne or droplet transmission. Collectively, available evidence indicates that respiratory involvement serves as a marker of disease severity rather than a transmission route. Nonetheless, rare aerosol-acquisition events in laboratory settings underscore the need for continued vigilance, strengthened surveillance, and re-evaluation of respiratory risks as climate change and viral evolution expand CHIKV’s global footprint.

Abstract: Bacillus velezensis is a rhizosphere-associated bacterium widely recognized for its roles in biological control and plant growth promotion; however, its functional diversity and evolutionary structure across scales remain incompletely understood. This study evaluated strains 2A-2B, 3A-6A, 2A-10A and 3A-25B from the Center-North of Mexico through integrated phenotypic assays and comparative genomics. Antagonistic activity was assessed via dual confrontation assays against major chili pepper phytopathogens, and plant–bacteria compatibility was examined in vitro. Genome-based analyses included pan-genome reconstruction, phylogenetic inference, and functional annotation, incorporating the screening of plant-associated genetic traits using the PLaBAse platform. All strains consistently inhibited phytopathogens (40–80%), with no significant differences among them, and displayed non-pathogenic interactions with the host plant. Genomic analyses revealed highly conserved core features alongside variation in accessory and strain-specific genes, with strain 3A-25B showing the highest divergence. Pan-genome analyses at regional and global scales indicated an open structure shaped by geography. Phylogenetically, three strains clustered together, whereas strain 3A-25B grouped with distant lineages. All genomes encoded extensive plant growth–promoting traits, while a substantial fraction of genes remained unannotated. These findings highlight functional consistency despite genomic divergence and support the ecological versatility and biotechnological potential of native B. velezensis strains.

Abstract: Phase-separated biomolecular condensates in the cytoplasm and nucleus are now recognized to contribute to carcinogenesis through aberrant signaling by assorted transcription factors and fusion oncoproteins. Oral cancer, the sixth most prevalent malignancy worldwide, frequently occurs in a U-shaped “high-risk” zone (floor of mouth, side of tongue, and anterior fauces) reflecting the path of liquid transit through the mouth. We previously reported that environmental stresses of saliva-like hypotonicity and beverage-like temperature changes triggered cycles of disassembly/reassembly of biomolecular condensates of GFP-tagged human myxovirus resistance protein (MxA; alias Mx1) in oral cancer cells. In the present study we identified some of the constituents of GFP-MxA cytoplasmic condensates in oral cells. GFP-MxA condensates were isolated from interferon (IFN)-λ1-treated GFP-MxA expressing OECM1 human oral cancer cells using magnetic bead-based immunoisolation. Unbiased peptide identification confirmed presence of MxA/Mx1 peptides; however, the strongest intensity was for the BACH1 transcription factor family. Immunofluorescence analyses confirmed the association of BACH1 and the family member Nrf2 with cytoplasmic human GFP-MxA condensates. Moreover, GFP-BACH1 and GFP-Nrf2 colocalized with cytoplasmic human HA-MxA condensates in transiently transfected OECM1 cells. Western blot assays confirmed presence of BACH1 and Nrf2 proteins in complexes isolated using anti-MxA pAb. In as much as BACH1 and Nrf2 regulate oxidative stress response genes, it was remarkable that immunofluorescence assays revealed the presence of heme oxygenase 1 (HO1) – a downstream redox regulator - in GFP-MxA condensates. In terms of aberrant function, in live cells, the Nrf2 transcription factor underwent rapid disassembly and reassembly cycles driven by saliva-like hypotonicity. The data highlight the unexpected intersections in oral cells between MxA condensates and BACH1, Nrf2 and HO1 – proteins well known to be involved in pathways regulating cellular responses to environmental and oxidative stresses, antiviral defense, oral epithelial dysplasia, and cancer progression and metastases.