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Multi-objective collaborative optimization of conical pick group based on factor space theory
Structure of a MenB de-N-acetyl polysialic acid antibody and mechanism of immune cell inhibition
Quercetin ameliorates iron overload-induced liver injury via NRF2/GPX4 pathway
PAX8 controls proximal tubule epithelial identity and stress response through epigenetic modification of distal regulatory elements
Proteomic signatures reveal stage-specific progression across gastrointestinal–neuropsychiatric comorbidity: a deep learning and multi-state trajectory analysis
Structural architecture of a hybrid β-barrel assembly machinery BAM-TAM complex in Borrelia burgdorferi
Brachiocephalic vein distensibility during passive leg raising in healthy adults
Abstract Passive leg raising (PLR) is a validated test of fluid responsiveness, but the value of brachiocephalic vein (BCV) distensibility as an ultrasound marker remains uncertain. In this prospective study, 129 volunteers were assessed for eligibility and 122 were analyzed (45 nonfasting controls, 77 fasting). Cardiac output (CO) was measured before and after PLR by echocardiography, and BCV distensibility was calculated from respiratory diameter variation. PLR increased CO in both groups ( P < 0.001). Median ΔCO was lower in fasting participants than in controls (21.05 [12.93–37.32] vs. 29.88 [22.13–39.86], P = 0.038), with lower responder rates at ΔCO ≥ 10% (79.2% vs. 95.6%, P = 0.016) and ΔCO ≥ 15% (74.0% vs. 91.1%, P = 0.032). ΔBCV distensibility did not differ between groups and was not associated with ΔCO overall (Spearman r = 0.148, P = 0.105). ROC analysis showed poor discrimination (AUC 0.38 overall, 0.51 in controls, 0.31 in fasting participants for ΔCO ≥ 15%), and exploratory adjusted analyses did not support an independent association between fasting status and responder status. BCV distensibility showed limited value and poor discriminatory performance as a marker of PLR-induced cardiac output change in spontaneously breathing healthy adults.
Atg23 interacts with both the N- and C-termini of Atg9 via a hydrophobic binding pocket
Increased renal PCSK9 expression may be partly responsible for the elevated serum PCSK9 level and hypercholesterolemia in primary nephrotic syndrome
Kinetics study reveals interconnected relationships of component activities in trifunctional RNA capping enzymes
Severe pollution with toxic elements in road dust from Baia Mare city, Romania
Nrf2 dynamically regulates RANKL-induced osteoclastogenesis and cathepsin K function
Decoupling of allele frequency and predicted pathogenicity in the tandem repeat filaggrin (FLG) gene
Abstract Tandemly repetitive genes present a paradox in that their duplicated architecture may buffer against mutation yet often exhibits strong position-dependent functional constraints. The filaggrin gene ( FLG ), with its massive repetitive core, provides a key model to examine how repeat architecture and demographic forces shape variation in such recalcitrant genomic regions. We integrated population-scale data from gnomAD ( n > 140,000) with deep learning predictions from AlphaMissense to map FLG ’s variant landscape. Constraint metrics indicated relaxed selection (missense o/e = 1.63), yet a clear spatial discordance emerged: predicted pathogenic variants were enriched in terminal repeats, whereas observed allele counts in human populations were concentrated in a few recurrent truncating variants in central repeats. These prevalent alleles exhibited strong alignment with population ancestry, while common variants (AF > 0.01) lacked definitive pathogenic annotations, highlighting the primacy of demographic history over uniform selection. Amino acid composition across repeats revealed significant divergence, with biases in Ser, Gly, and His correlating with predicted pathogenicity, providing a mechanistic basis for repeat-specific evolutionary constraints. Together, these findings demonstrate that variant interpretation in large tandem repeats requires explicit integration of repeat structure and population history. This framework has implications for ancestry-aware assessment of FLG variation and for the broader analysis of repetitive genes in human disease genetics.
Phosphatidylethanolamine binds to human perilipins via a hydrophobic cleft in their 4-helix bundle domain for lipid droplet targeting
Passenger density prediction and gate allocation via GA-optimized ELM
Dimerization of natively folded molecules drives misfolding and aggregation in Cys-depleted variants of cataract-associated human lens γD-crystallin
Vitamin D levels and other factors associated with depressive symptoms and cognitive impairment in the oldest-old patients with diabetes
Rapid reduction in global chromatin loop size after acute STAG2 reconstitution in human cancer cells
Feasibility of energy expenditure estimation during outdoor walking using multimodal in-ear sensors: a preliminary validation study against indirect calorimetry
Abstract A growing number of portable devices has become available for daily physical activity and energy expenditure (EE) monitoring. Although several studies have examined EE estimation using heart rate (HR) and accelerometry (ACC), no study to date has explored EE prediction based on HR and ACC data measured simultaneously in the ear canal by a single commercial wearable device. Therefore, the aim of this study was to assess the feasibility of estimating EE using the cosinuss $$^\circ$$ in-ear sensors $$^\circ$$ One and $$^\circ$$ Two. Twenty-four healthy adults (12 female, 12 male, age 26.91 ± 2.91 years, body mass 65.43 ± 8.01 kg) completed two test sessions: a laboratory treadmill test (Modified Bruce Protocol) and an outdoor walking test consisting of three phases (uphill at comfortable pace, downhill at comfortable pace, and uphill as fast as possible). EE was measured by the portable indirect calorimetry device MetaMax 3B (criterion measure), while HR and ACC were recorded continuously by the in-ear sensors $$^\circ$$ One and $$^\circ$$ Two. Linear mixed-effects models were developed from laboratory data and applied to outdoor walking data from the same participants (participant-calibrated prediction). Prediction accuracy was assessed using root mean square error (RMSE), mean absolute percentage error (MAPE), and Bland-Altman analysis. Both in-ear sensors showed preliminary potential for EE prediction during outdoor walking. The integration of HR, ACC, and biological sex produced the best-fitting calibration models, with marginal $$R^2$$ values of 0.79 and 0.80 for $$^\circ$$ One and $$^\circ$$ Two respectively. In the outdoor walking test, no significant systematic bias was detected across conditions ( $$p> 0.05$$ ). However, prediction accuracy was variable across conditions and subgroups, with MAPE ranging from 22% to 37% for $$^\circ$$ One and 22% to 38% for $$^\circ$$ Two (following exclusion of one participant with implausible reference data in the Down phase). Pearson correlation coefficients were stronger for female participants, while male subgroup correlations were weak or negative in several conditions, limiting conclusions about individual-level prediction accuracy for this subgroup. The cosinuss $$^\circ$$ in-ear sensors demonstrated preliminary feasibility for group-level EE estimation during outdoor walking, with accuracy broadly comparable to several commercial wrist-worn devices. Given the variable prediction accuracy, particularly for male participants and during downhill walking, further validation with larger and more diverse samples is needed before clinical or sports application.