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A fungal effector promotes infection via stabilizing a negative regulatory factor of chloroplast immunity
Slow dynamics of human balance control
Abstract When standing on a tilting surface, humans’ sway behavior at frequencies below 0.1 Hz indicates the contribution of a slow feedback component. We suggest this may reflect a self-calibration mechanism of the balance control system, constantly referencing orientation estimates based on kinematic sensory cues to a reference based on force cues. However, attempts to identify this mechanism have been limited by insufficient experimental trial durations and small sample sizes. This study aimed to assess the properties of the mechanism that reduces body sway at very low frequencies in upright standing. Anteroposterior body sway responses to short- and long-duration surface tilts were measured and interpreted using balance control models. Four feedback control model variants, with different mechanisms to account for the slow dynamics, were fit to experimental data. Furthermore, we tested how estimates of the slow component are affected by stimulus period duration. We hypothesized that the model variants containing force cues would provide the best fit to experimental sway responses, particularly in response to long-duration surface tilts. Our results confirm this hypothesis and suggest that humans use integrated force afferents from the feet and legs in a slow, positive feedback mechanism during standing to remain upright. Despite stimulus period durations of ~ 180 s, some properties of this mechanism were difficult to estimate. The positive torque feedback mechanism aligns with the notion of self-calibration.
Relative importance of socioecological domains to predicting opioid-involved mortality
Background The opioid crisis in the United States is a complex issue with interconnected factors that lead to opioid misuse and opioid-involved mortality. This study assessed the relative importance of different risk factor domains in predicting fatal opioid-involved mortality that occurred after hospital encounters involving opioids. Methods A machine learning model was developed by integrating multiple data sources, including hospital records, death records, and societal data. The model allowed simultaneous examination of risk factors across individual drug and non-drug related factors, hospital factors, and societal factors. Results 429,005 patients with opioid-related encounters in 2014 were assessed, where 56.6% were female and the mean age was 44.98. Among deaths that had specific drugs listed for both the hospital encounter and the death, 51.7% of hospital encounters progressed to a more potent opioid at death. Community factors cumulatively had similar importance as individual drug-related factors in predicting opioid-involved deaths and were relatively more important in predicting opioid-involved mortality compared to non-drug involved mortality. In predicting opioid-involved mortality, non-drug related individual-level predictors accounted for 45.1% of the importance. Community factors accounted for 27.9% of the importance and drug-related individual factors accounted for 22.5%. In contrast, community factors accounted for only 16.5% of the importance when predicting non-opioid-involved mortality. Practice Implications Rather than suggesting community factors outweigh individual factors, our results highlight individual vulnerability may be amplified or mitigated by broader environmental factors. Interventions targeting larger social determinants of health may be strongly influential in reducing drug-involved mortality. This study demonstrated a quantitative evaluation of the different domains of risk factors and highlighted the importance of considering societal and community factors in a holistic approach to preventing opioid-involved mortality.
ATG7 in innate immune cells is required for host defense against nontuberculous mycobacterial pulmonary infections
Cytogenetic landscape aberrations in paediatric acute lymphoblastic leukaemia — a polish paediatric population treated according to ALL-IC BFM 2009 protocol
Expression of Concern: Determinants of change in timely first antenatal booking among pregnant women in Ethiopia: A decomposition analysis
A noninvasive model for chronic kidney disease screening and common pathological type identification from retinal images
Shape optimization and mechanical properties analysis of the free-form surface
Communication-efficient decentralized clustering for dynamical multi-agent systems
The paper presents a decentralized, real-time clustering method designed for large-scale, distributed environments such as the Internet of Things (IoT). The approach combines compressed sensing for dimensionality reduction with a consensus protocol for distributed aggregation, enabling each node to generate compact, consistent summaries of the system’s clustering structure with minimal communication overhead. These representations are processed by a pre-trained neural network to reconstruct the global clustering state entirely without centralized coordination. Unlike traditional methods that depend on static topologies and centralized computation, this system adapts to dynamic network changes and supports on-the-fly processing. The system suits IoT applications where data must be processed locally, and immediate results are essential. Experiments on both synthetic and real-world datasets show that the method significantly outperforms baseline approaches in clustering accuracy, making it highly suitable for resource-limited, decentralized IoT scenarios.
Flexibility meets rigidity: a self-assembled monolayer materials strategy for perovskite solar cells
Machine learning-based high-benefit approach versus traditional high-risk approach in statin therapy: the Shizuoka Kokuho database study
Risk of recurrence and bleeding in patients with cancer-associated venous thromboembolism in the direct oral anticoagulants era: Findings from the TULIPE registry
Background The introduction of direct oral anticoagulants (DOACs) for venous thromboembolism (VTE) treatment has led to their widespread adoption in clinical practice, potentially influencing management strategies and patient outcomes. However, real-world data on cancer-associated VTE in the DOAC era remain limited. This study aimed to evaluate the clinical characteristics and long-term outcomes of patients with cancer- and non-cancer-associated VTE in a real-world setting. Methods We retrospectively analyzed patients diagnosed with deep vein thrombosis (DVT) using lower-extremity venous ultrasound between January 2015 and August 2020 at the University of Tsukuba Hospital, a tertiary academic referral center in Japan. Results The cohort included 2,281 patients with DVT, comprising 1,152 with active cancer (cancer group) and 1,129 without cancer (non-cancer group). The cumulative 5-year incidence of recurrent VTE was significantly higher in the cancer group than in the non-cancer group (25% vs. 10%, P < 0.001). After adjusting for confounders and accounting for the competing risk of mortality, cancer remained a significant risk factor for recurrence (adjusted subdistribution hazard ratio [sHR]: 2.00; 95% confidence interval [CI]: 1.46–2.74). Similarly, the cumulative 5-year incidence of major bleeding was significantly higher in the cancer group (30% vs. 9.6%, P < 0.001). After adjustment, the risk of major bleeding remained significantly elevated in the cancer group compared to that in the non-cancer group (adjusted sHR: 2.69; 95% CI: 1.90–3.81). In the cancer group, discontinuation of bleeding-related anticoagulation therapy was associated with increased VTE recurrence (P < 0.001), whereas no such association was observed in the non-cancer group (P = 0.716). Conclusions In the DOAC era, similar to the warfarin era, patients with cancer exhibited significantly higher rates of VTE recurrence and major bleeding than those without cancer.
Coordinatively unsaturated bismuth sites accelerate in-situ hydrogen peroxide electrochemical formation for efficient butanone oxime synthesis
Influence of surface quality on corrosion resistance of stainless steel and aluminum alloy butt welds after innovative finishing
Study on energy evolution and crack propagation of filling mortar-rock at different loading rates
Shotcrete, as a highly efficient reinforcement material widely used in geotechnical engineering, demonstrates irreplaceable advantages in projects such as tunnel excavation, mine roadway support, and slope protection. However, when shotcrete becomes tightly bonded with rock masses, the energy evolution and crack initiation mechanisms between the two materials exhibit remarkable complexity. Different loading rates significantly alter the internal stress distribution and deformation characteristics within the composite system, thereby influencing the patterns of energy evolution and crack propagation. Consequently, it is essential to investigate the mechanical behavior of filling mortar-rock under varying loading rates. Firstly, uniaxial tests with four loading rates were conducted for the composite specimens, and the effects of loading rate on the mechanical parameters, energy evolution and fracture modes were analyzed. The results show that the mechanical parameters of the composite decrease with the rise of loading rate, and the decrease reaches the maximum when the mortar strength is M20. All three types of energies decreased exponentially with increasing loading rate. The decrease reaches the maximum at a mortar strength of M40. Subsequently, a damage model applicable to the composite specimens was established based on the development rules of the dissipated energy and the compaction coefficient. Finally, PFC2D was used to simulate and analyze the specimens with mortar grade of M30 to investigate the crack propagation and stress evolution process at four loading rates. The results show that tensile stress is the causative factor of crack propagation. The cracks first appeared at the interface, and were mainly distributed on both sides of the specimen after cracking.
Stromatolites and pulsed oxygenation events in the Mesoproterozoic Longjiayuan formation of western Henan: evidence for life-environment co-evolution
Abstract The oxygen level in the ocean and atmosphere played a crucial role in the development of Precambrian stromatolites. The Mesoproterozoic represents a critical interval in Earth’s history, characterized by persistently low atmospheric and oceanic oxygen levels under which stromatolites flourished. Stromatolites are particularly abundant in Member II of the Mesoproterozoic Longjiayuan formation in western Henan Province. To investigate the relationship between stromatolites and redox conditions, petrographic and geochemical analyses were conducted on siliceous-banded dolomites and stromatolitic dolomites from the Longjiayuan Formation. The results show that the macromorphology of stromatolites in Member II is classified into stratiform, undulatory, domical, conical, and columnar morphologies. Microscopically, the stromatolites exhibit alternating light and dark laminae, with occasional ooids and spherules. The CeSN/CeSN* values recorded in carbonate rocks from Member II show negative anomalies, reflecting oxidizing conditions influenced by environmental changes and microbial activity. These stromatolite records and oxygen fluctuations in the Mesoproterozoic shallow marine environment provide a valuable basis for studying the co-evolution of early life and the environment.
Associations of estimated glucose disposal rate with kidney stones in U.S. non-diabetic adults and possible mediating mechanisms: NHANES 2009–2020
Background Kidney stone formation has been linked to insulin resistance (IR). However, the association between the estimated glucose disposal rate (eGDR) – a novel surrogate marker for IR – and kidney stone occurrence in non-diabetic adults remains unclear. Methods We analyzed data from adult participants in the National Health and Nutrition Examination Survey (NHANES) collected between 2009 and 2020 who self-reported a history of kidney stones. To assess the relationship between eGDR and kidney stones, we applied a range of statistical methods, including weighted proportions, multivariable logistic regression, restricted cubic splines (RCS), receiver operating characteristic (ROC) curve analysis, subgroup analysis, and mediation analysis. Results The final analysis included 8,051 participants, of whom 8.71% reported a history of kidney stones. Multivariable logistic regression revealed that, compared to the lowest eGDR quartile, the fully adjusted odds ratios (95% confidence intervals) for kidney stone in the second, third, and fourth quartiles were 0.87 (0.61–1.26), 0.54 (0.34–0.85), and 0.46 (0.28–0.77), respectively. The RCS plot indicated a significant non-linear inverse association between eGDR and kidney stone risk. ROC curve analysis showed that the association between eGDR and the risk of kidney stones was more pronounced compared to the other five IR indicators, as evidenced by a higher area under the curve. Mediation analysis identified albumin (ALB) and red cell distribution width (RDW) as partial mediators in the association between IR and kidney stones. Conclusion Our research results indicate that lower levels of eGDR are associated with an increased risk of developing kidney stones in non-diabetic adults. Furthermore, ALB and RDW may partially mediate the relationship between IR and kidney stones.