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Pediatric foot anthropometry and its correlation with growth assessment
Abstract Foot dimensions, particularly length and width, are essential anthropometric parameters often used in health, ergonomics, and footwear design. This study aimed to investigate the correlation between foot dimensions, age, and height among children aged 4 to 12 years in Ekpoma, Edo State, Nigeria. A cross-sectional descriptive survey was conducted with 389 children, randomly selected from schools and community centres. Data were collected using standardised anthropometric measurements, including foot length, foot width, and height, ensuring accuracy and consistency. Pearson’s correlation and independent t-tests were used to examine relationships among variables and to identify sex-based differences. Descriptive statistics revealed variations in foot dimensions across the age groups, with a mean foot length of 19.49 cm and a mean foot width of 6.87 cm. Foot length showed moderate-to-strong correlations with age in younger children (overall r = 0.549, p < 0.001) and a strong correlation with height ( r = 0.652, p < 0.001), while foot width exhibited weaker positive correlations with age (r range 0.254–0.513) and height ( r = 0.233, p < 0.001). No significant sex differences were observed (all p > 0.05). The findings highlight the progressive changes in foot dimensions with age and height and their potential applications in pediatric health, footwear design, and ergonomic planning.
Suppression of transgenerational lipid provisioning inhibits desiccation resistance, but not diapause, in the vector mosquito, Aedes albopictus
A probabilistic framework for effective battery energy storage sizing in microgrids with demand response
Abstract Microgrids (MGs) are increasingly integrating Battery Energy Storage Systems (BESSs) to improve operational flexibility and minimize overall costs. However, probabilistic BESS sizing remains computationally demanding due to uncertainties associated with renewable energy generation, load demand, and market price volatility. This paper presents a hybrid probabilistic sizing framework that integrates the 2m + 1 Point Estimation Method (PEM) with the Equilibrium Optimizer (EO), referred to as the EO–PEM approach. Unlike conventional Monte Carlo simulation–based formulations, the presented method embeds EO within the PEM uncertainty evaluation loop, enabling accurate results with substantially reduced computational effort. Additionally, an incentive-based Demand Response (IDR) model is integrated into the Energy Management (EM) framework. The main objective of the EM is to minimize operational costs and maximize the MG operator’s benefits while ensuring customer satisfaction. Simulation results from the test MG system confirm the superiority of the EO over other applied optimization techniques in solving the deterministic EM problem without BESS. Under uncertainties, the EO–PEM method identifies an optimal BESS capacity of 1 kWh, achieving a reduction in the expected operational cost while maintaining high computational efficiency and robustness. Overall, the results demonstrate the effectiveness of the EO–PEM framework for probabilistic BESS sizing under multi-source uncertainties.
Crystallographic data for Pyrococcus furiosus dolichylphosphate mannose synthase suggest that the enzyme could flip its glycolipid product
Abstract Dolichylphosphate mannose synthase (DPMS) performs an essential function by synthesizing the activated lipid-linked mannose intermediate used in protein glycosylation pathways. In eukaryotes and archaea, DPMS catalyzes the transfer of mannose from GDP-mannose to dolichylphosphate to generate dolichylphosphate mannose (Dol- P -Man). Type-III DPMS from Pyrococcus furiosus ( Pf DPMS) has a catalytic domain attached to a GtrA-like transmembrane (TM) domain with an unusual topology. Here, we present crystallographic data from a crystal complex determined from an enzymatic reaction mixture that provides detailed information about donor- and acceptor binding in the active site prior to mannosyl transfer. We also present a new, unexpected structural state for the TM domain in which a Dol- P -Man molecule is bound “upside-down” with its mannosylphosphate headgroup positioned in a polar pocket between the TM helices. By generating a panel of TM-domain mutants, we confirm that the TM domain does not participate directly in the catalysis of mannosyl transfer and discuss the possibility of this domain providing moonlighting function to Pf DPMS by translocating the Dol- P -Man product to the cell exterior.
The role of early intervention with upper limb rehabilitation robots in upper limb functional reconstruction and improving sarcopenia-related indicators in stroke patients
Evaluating generative AI’s potential to dispel misinformation about wind farms
Dynamics of household water use determinants in selected Local Government Areas in Oyo Zone of Oyo State Nigeria
ITPR3 promotes liver fibrosis by damaging hepatocytes via the Ca2+/NF-B/LECT2 pathway
Immune, inflammatory, and metal biomarker profiles in chronic respiratory diseases receiving oligo-fucoidan under ambient PM₂.₅ exposure
Abstract Industrial zones are prevalent in central Taiwan, with major sources of ambient air pollution including large thermal power plants and steel manufacturing facilities. Fine particulate matter (PM₂.₅) is a critical component of air pollution and has been implicated in the development and progression of chronic respiratory diseases (CRDs), primarily through pathways involving immune dysregulation and persistent low-grade inflammation. Oligo-fucoidan (OF), a low–molecular-weight derivative of fucoidan, has been reported to exert immunomodulatory and anti-inflammatory effects in experimental and preclinical studies. However, clinical evidence regarding its potential role in air pollution–associated respiratory conditions remains limited. This exploratory, non-randomized, open-label study aimed to descriptively evaluate changes in immune and inflammatory parameters among patients with air pollution–associated chronic pulmonary diseases residing in central Taiwan. A total of 46 participants received OF supplementation (2.2 g daily) for 12 weeks in addition to standard care. Blood samples were collected at baseline and at weeks 4, 8, and 12 to assess biochemical indices, lymphocyte subsets, inflammatory cytokines, and serum heavy metal concentrations. Ambient PM₂.₅ data during the study period were obtained from nearby governmental air quality monitoring stations. Ambient PM₂.₅ concentrations during the study period were within a relatively low range (11.1 ± 4.0 to 14.7 ± 10.3 µg/m³). Over the 12-week supplementation period, descriptive variations were observed in several immune and inflammatory markers, including white blood cell count, C-reactive protein, ferritin levels, lymphocyte subset distributions, and selected cytokines. Serum mercury concentrations demonstrated a positive association with ambient PM₂.₅ levels. Among the measured cytokines, IL-8 values at later time points were lower than at baseline; these changes are presented descriptively and should be interpreted cautiously given the exploratory, single-arm nature of the study. This exploratory study provides a descriptive characterization of immune, inflammatory, and heavy metal–related parameters in patients with air pollution–associated chronic pulmonary diseases receiving oligo-fucoidan as an adjunct to standard therapy. While causal relationships and statistically confirmed longitudinal effects cannot be established, these preliminary observations may inform the design of future controlled trials and mechanistic investigations in the context of environmental respiratory health.
Correlation between anti-retinal antibodies and lupus retinopathy in systemic lupus erythematosus
Abstract Lupus retinopathy (LR) is one of the most frequent and serious ocular complications of systemic lupus erythematosus (SLE), because it may cause irreversible visual impairment. The aim of this study was to evaluate the association between serum anti-retinal antibodies levels of SLE patients and the incidence of LR. Levels of serum anti-α-enolase antibody (Ab), anti-arrestin Ab, anti-recoverin Ab and anti-IRBP3 Ab were detected in 89 SLE patients (divided into LR group and non-LR group) and 81 healthy controls by enzyme-linked immunosorbent assay (ELISA). The correlation between these four anti-retinal Ab, SLE activity and the incidence of LR was evaluated. LR group had a higher SLE disease activity index (average SLEDAI score, 18 (7) versus 9 (5), P < 0.001), higher frequency of pleurisy (40% versus 20.4%, P = 0.044) and lower level of hemoglobin (102.343 ± 23.157 versus 112.759 ± 19.678, P = 0.025) comparing to non-LR group. LR group had higher levels of anti-α-enolase than non-LR group ( P = 0.033) and control group ( P < 0.0001). The levels of anti-recoverin in LR group was higher than non-LR group ( P = 0.036) and control group ( P < 0.0001), while the difference was not significant between non-LR group and control group ( P = 0.109). Using combination of anti-α-enolase Ab and anti-recoverin Ab to diagnose LR in SLE patients is more effective (with area under the receiver operating characteristic curve (AUC): 72.68%) than use anti-α-enolase Ab (AUC: 65.65%) or anti-recoverin (AUC: 61.96%) only. Our results suggested that anti-α-enolase and anti-recoverin may be used as potential biomarkers of lupus retinopathy in SLE patients.
A fuzzy time-series driven ensemble approach for accurate forecasting of higher education rankings
An intelligent computational framework combining neural networks with complex Pythagorean fuzzy FUCA for airspace capacity evaluation and traffic forecasting
Rheological and biochemical comparison of cord and adult blood red cells for transfusion applications
Abstract Cord blood (CB) is a promising alternative source of red blood cells (CB-RBC) for neonatal transfusion due to their high fetal hemoglobin content and potential physiological benefits in preterm infants, but their metabolic and rheological stability during storage and irradiation is not fully defined. This study examined whole cord blood (WCB) and processed CB-RBC stored up to 10 days (D10), with or without irradiation, and compared them with adult RBC (A-RBC) following neonatal transfusion guidelines. Ektacytometry showed significantly lower EImax in CB-RBC at day 0 (D0) and D10 ( p < 0.05), while Omin and Ohyper remained stable. CB-RBC had lower ATP than A-RBC at baseline (2.8 ± 1.0 µmol/g Hb vs. 4.0 ± 0.3 µmol/g Hb) and after 10 days (2.0 ± 1.1 µmol/g Hb vs. 3.0 ± 1.9 µmol/g Hb). Hemolysis in CB-RBC was minimal (median 0.05, range 0.04–1.17% at D0 vs. median 0.19, range 0.16–1.23% at D10), and residual WBC content met limits (< 1 × 10⁶). Storage induced expected biochemical changes in both CB-RBC and A-RBC, including increased potassium, pO2 and lactate, decreased sodium and glucose, and pH decline, though D10 pH and potassium evaluation in CB-RBC was partly affected by hemolysis. Irradiation produced minimal effects on ATP and rheology. Overall, CB-RBC preserved acceptable metabolic and rheological properties during short-term storage and irradiation, supporting further exploration of their suitability for neonatal transfusion.
Investigating serum free light chains in patients with common variable immunodeficiency disorder in compare with other immunodeficiency diseases
Abstract Serum free light chains (sFLCs) have recently been introduced as a diagnostic biomarker in common variable immunodeficiency (CVID) patients. Most patients with CVID have undetectable or lower levels of sFLCs compared to people with other types of immune system deficiencies with hypogammaglobulinemia, except for patients with agammaglobulinemia (AGG). Decreased production of kappa (κ) and lambda (λ) light chains over immunoglobulins (Ig) suggests a malfunction in early B cell development or plasma cell dysfunction may cause CVID. In this cross-sectional study, immunoturbidimetry was used to measure sFLCs in 70 immunodeficiency patients, including 39 patients with CVID, 31 patients with other immunodeficiencies with hypogammaglobulinemia such as combined immunodeficiency (CID), AGG, and other primary immunodeficiencies (PIDs), and 20 healthy controls. The levels of both κ and λ chains were significantly higher in patients with CID than patients with CVID and AGG patients (p < 0.05). The median (Q1–Q3) κ level in patients with other primary immunodeficiency disorders (PIDs) was significantly higher than that observed in patients with AGG and CVID (p < 0.01). Similarly, the median (Q1–Q3) λ level was higher in patients with other PIDs compared with those with AGG and CVID (p < 0.05).ROC analysis of κ and λ disclosed an area under the curve (AUC) for κ was 0.98 (95% CI: 0.96–0.99, p < 0.0001) and for λ was 0.95 (95% CI: 0.89–0.99, p < 0.0001) in patients with CVID. The sFLCs test can help distinguish between CVID and other immunodeficiency patients with hypogammaglobulinemia and the diagnosis of hypogammaglobulinemia.
Predictive temperature control of electric two wheeler hub motor using gradient aware neural regulation with degradation tracking and fault tolerant multi condition torque adaptation
A Machine learning pipeline to investigate tissue ingrowth in cerebral aneurysms using preclinical animal models
Abstract Cerebral aneurysm is a life-threatening condition characterized by the formation of a saccular bulge in brain blood vessels, which can rupture and lead to severe complications. One treatment involves inserting a soft, flexible wire (coil) into the aneurysm to promote clotting and sealing. Mediators are often used to simulate tissue ingrowth within the sac to stabilize healing and prevent recurrence. However, quantitative assessment of tissue ingrowth in preclinical models remains labor-intensive, subjective, and poorly standardized, limiting the ability to compare therapeutic strategies and healing mechanisms. We developed a robust machine learning (ML) pipeline based on a Unet + + convolutional neural network (CNN), optimized for segmenting and quantifying tissue ingrowth in a preclinical carotid aneurysm mouse model. The model was trained and validated on 64 high-resolution histological images using 10-fold cross-validation. Image preprocessing included resizing, normalization, and augmentation, while post-processing applied thresholding techniques to CNN-generated heatmaps. Our method achieved Dice coefficients of 94.58% for sac segmentation and 95.23% for tissue ingrowth detection, with AUCs of 99.24% and 96.78%, respectively. The model’s predictions showed strong agreement with ground truth ( $$R^{2}=0.94$$ ), supporting its potential for assessing biological stability and informing clinical decisions. In a blinded evaluation against expert annotations, our AI model achieved the highest agreement (Cohen’s κ) among all raters, demonstrating its potential to provide consistent and expert-level tissue ingrowth assessments. A user-friendly graphical interface was developed, to enable non-technical users to perform segmentation and quantify tissue ingrowth. By providing objective, reproducible metrics of intra-aneurysmal healing, this approach supports mechanistic studies of therapeutic efficacy in preclinical aneurysm models and establishes a foundation for standardized evaluation of pro-healing interventions.
Correction: A new mamenchisaurid sauropod dinosaur from the Upper Jurassic of Southwest China reveals new evolutionary evidence from East Asian eusauropods
Association between B and T lymphocyte attenuator/herpes virus entry mediator immunoregulatory axis and outcome prediction in a mixed critically ill population
Network inequality through preferential attachment, triadic closure, and homophily
Abstract Inequalities in social networks arise from linking mechanisms, such as preferential attachment (connecting to popular nodes), homophily (connecting to similar others), and triadic closure (connecting through mutual contacts). Preferential attachment drives degree inequality and homophily drives segregation, but we know less about how these two mechanisms interact with triadic closure. This gap limits our understanding of how network inequalities emerge. We introduce PATCH, a network growth model that combines all three mechanisms, and use it to study how they create disparities within and between two groups in undirected networks. Simulations show that homophily and preferential attachment increase segregation and degree inequality. Triadic closure has varied effects: conditional on the other mechanisms, it increases population-wide degree inequality while reducing segregation and between-group degree disparities. We demonstrate PATCH’s explanatory potential using fifty years of Physics and Computer Science collaboration and citation networks exhibiting persistent gender disparities. PATCH reproduces these gender disparities when it combines preferential attachment, moderate gender homophily, and triadic closure. By connecting mechanisms to observed inequalities, PATCH shows how their interplay sustains group disparities and how improving one inequality dimension may affect others.