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ObjectiveFalls in older people have become a major public health, economic and societal problem. Osteoporosis predisposes older adults to high risk of falls, which were the most common outcome attributable to low bone mineral density (LBMD). In this study, we analyze the long-term trends in falls burden attributable to LBMD among people aged 60 years and over from 1990 to 2019, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019).MethodsData from GBD 2019 were used to assess the long-term trends in mortality and disability-adjusted life-year (DALY) rates by Joinpoint regression. The age-period-cohort (APC) model was used to evaluate the effects of age, period and cohort on mortality rate of falls attributable to LBMD.ResultsThe mortality and DALYs rates of falls attributable to LBMD among people aged 60 years and over increased from 1990 to 2019, with average annual percentage changes (AAPCs) of 1.74% (95% CI: −1.47 to 2.01%) and 0.99% (95% CI: 0.80–1.19%), respectively. APC analysis revealed that the mortality rate due to LBMD significantly increased among the older people over the age of 75 years. The risk of falls mortality due to LBMD during the period of 1990–2019 initially declined but later elevated. An overall increasing risk for falls death attributable to LBMD was presented across birth cohorts, but in cohorts born after 1930, the upward trend has slowed down. The overall net drift per year attributable to LBMD was above 0. The corresponding results showed that the negative impact of period and cohort effects among males was more pronounced than those among females.ConclusionsFalls attributable to LBMD remain an ongoing health burden in the older people in China, and the mortality has been on the rise from 1990 to 2019, especially among the older people aged 80+ years group. The prevention and treatment of LBMD should be emphasized, especially among males and oldest-old people. Furthermore, there is an urgent need to strengthen the implementation of system-wide, integrated and effective public health policies and other health interventions in China.

Based on the study of the feature extraction algorithm based on the multiple empirical mode decomposition of the Duffing equation, this paper proposes a corresponding improved algorithm, completes the identification and analysis of the psychological pressure dimension space under the audiovisual induction method, and designs two typical psychological types of music and pictures. Based on the stress induction experiment, an audiovisual-induced psychological stress recognition system based on EEG (electroencephalogram) signals was built. Aiming at the problem that the spatial uniform sampling method cannot well reflect the dynamic characteristics of the multivariate EEG signal, based on the Duffing equation, a nonuniform sampling algorithm that adaptively selects the projection direction is proposed. At present, the use of the Duffing equation to detect weak unknown signals is to select a set of fixed parameters. Analysis of these two aspects to determine the parameters of the system is based on the parameter analysis of the Duffing equation oscillator. Due to the sensitivity of the Duffing equation to the initial value, the choice of parameters has a great influence on the detection effect. In response to this situation, the relationship between the parameters and initial values of the Duffing equation is analyzed. From the relationship between the parameters and the initial values, the influence of different parameters on the detection effect is analyzed to verify the superiority of the current equation parameters. First, the multichannel EEG signal is nonuniformly sampled multiempirical modal decomposition, and an effective intrinsic modal function is selected to extract the mental stress EEG characteristics. Experimental results show that the EEG signal recognition algorithm based on the Duffing equation effectively extracts EEG signal features and improves the classification accuracy of mental stress EEG signals.

Dating back to the first epidemic among injection drug users in 1989, the Yunnan province has had the highest number of human immunodeficiency virus type 1 (HIV-1) infections in China. However, the molecular epidemiology of HIV-1 in Yunnan has not been fully characterized.Using immunoassays, we identified 103,015 accumulated cases of HIV-1 infections in Yunnan between 1989 and 2004. We studied 321 patients representing Yunnan's 16 prefectures from four risk groups, 11 ethnic populations, and ten occupations. We identified three major circulating subtypes: C/CRF07_BC/CRF08_BC (53%), CRF01_AE (40.5%), and B (6.5%) by analyzing the sequence of p17, which is part of the gag gene. For patients with known risk factors, 90.9% of injection drug users had C/CRF07_BC/CRF08_BC viruses, whereas 85.4% of CRF01_AE infections were acquired through sexual transmission. No distinct segregation of CRF01_AE viruses was found among the Dai ethnic group. Geographically, C/CRF07_BC/CRF08_BC was found throughout the province, while CRF01_AE was largely confined to the prefectures bordering Myanmar. Furthermore, C/CRF07_BC/CRF08_BC viruses were found to consist of a group of viruses, including C, CRF08_BC, CRF07_BC, and new BC recombinants, based on the characterization of their reverse transcriptase genes.This is the first report of a province-wide HIV-1 molecular epidemiological study in Yunnan. While C/CRF07_BC/CRF08_BC and CRF01_AE are codominant, the discovery of many sexually transmitted CRF01_AE cases is new and suggests that this subtype may lead to a new epidemic in the general Chinese population. We discuss implications of our results for understanding the evolution of the HIV-1 pandemic and for vaccine development.

Hot-rolled 3207 duplex stainless steel (DSS) was solution treated at 1250℃ for 30 min, and cold rolled at 40-80 % reduction. The superplastic deformation was drawn with a constant speed of 1.5 × 10-3 s-1 at 950℃. The effect of cold-rolling reduction on microstructure and properties of 3207 duplex stainless steel was studied. The results show that austenite and ferrite are elongated along a rolling direction with increased reduction With the increase of reduction, the elongation of 3207 DSS at a high-temperature tensile process increased significantly. When the reduction reached 70 %, the elongation could exceed 100 %. When the reduction rate of cold rolling reached 80 %, the elongation reached the maximum value of 408.63 %. When the reduction was less than 60 %, the peak stress was stabilized at about 300 MPa. When the reduction reached 60 %, the peak stress decreased gradually with the increase of the reduction, and the lowest value, 140.34 MPa, was obtained when the reduction reached 80 %. [ABSTRACT FROM AUTHOR]

Abstract To explore the role of AVAPS combined with TCM monitoring in the weaning of patients with AECOPD. In this study, 100 patients with AECOPD were included, who were divided into the AVAPS group and the S/T group after weaning. The respiration-related parameters were compared between the two groups at the time of weaning and after 1 h and 12 h of noninvasive ventilation. The correlations between PtcCO2 and PaCO2 and the differences in each parameter were compared. The predictive value of PtcCO2 variability after 1 h and 12 h of noninvasive respiratory support for the 48-h reintubation rate were analysed. Logistic regression analysis was performed to explore the risk factors affecting the 48-h reintubation rate of AECOPD patients. After 1 h and 12 h of treatment with different ventilation modes, the variations in the respiration-related parameters in the AVAPS group were all significantly greater than those in the S/T group (P

Gamma spectrometry analysis of uranium enrichment is an important technical tool for international nuclear safeguards verification. As a kind of special nuclear materials，235U is an important verification object of nuclear safeguards verification. In addition，the determination of uranium enrichment in samples is a key measurement for product process control，process measurement and waste characterization in uranium enrichment production facilities，uranium conversion facilities，fuel manufacturing plants and reprocessing plants，as well as a key technical means for tracking illicit trafficking in nuclear materials and responding to terrorist threats and attacks in homeland security activities. Simulated annealing algorithm is aiming to simulate the solid annealing process，and iteratively solve the solution problem by continuously reducing the annealing temperature and combining with the Metropolis criterion. The result has been proved to converge to the global optimal solution according to probability 1，which is one of the common solutions for solving optimization problems. In the article，a uranium enrichment calculation method based on simulated annealing algorithm is proposed for gamma spectrometry analysis. A corresponding mathematical model is established for the practical problem of enrichment calculation，the generation and iterative process of algorithmic solutions are improved by using the sampling theory and the forbidden searching strategy，and the iterative solution is combined with the nonlinear least-squares fitting for the enrichment of the samples，which realizes the relative efficiency of the curve fitting and the calculation of the enrichment degree within the energy range of 143 keV to 1001 keV. The performance test of the algorithm and the results of sample analysis show that the uranium enrichment calculation method based on the improved simulated annealing algorithm has the ability to escape the local optimal problem in uranium enrichment calculation，and can be applied to the enrichment calculation of different uranium samples，the relative deviation of the results of the enrichment analysis over all measured samples is within ±5%.

Abstract Background Determining the optimal timing of surgical intervention for Neonatal necrotizing enterocolitis (NEC) poses significant challenges. This study develops a predictive model using the long short-term memory network (LSTM) with a focal loss (FL) to identify infants at risk of developing Bell IIB + NEC early and issue timely surgical warnings. Methods Data from 791 neonates diagnosed with NEC are gathered from the Neonatal Intensive Care Unit (NICU), encompassing 35 selected features. Infants are categorized into those requiring surgical intervention (n = 257) and those managed medically (n = 534) based on the Mod-Bell criteria. A fivefold cross-validation approach is employed for training and testing. The LSTM algorithm is utilized to capture and utilize temporal relationships in the dataset, with FL employed as a loss function to address class imbalance. Model performance metrics include precision, recall, F1 score, and average precision (AP). Results The model tested on a real dataset demonstrated high performance. Predicting surgical risk 1 day in advance achieved precision (0.913 ± 0.034), recall (0.841 ± 0.053), F1 score (0.874 ± 0.029), and AP (0.917 ± 0.025). The 2-days-in-advance predictions yielded (0.905 ± 0.036), recall (0.815 ± 0.057), F1 score (0.857 ± 0.035), and AP (0.905 ± 0.029). Conclusion The LSTM model with FL exhibits high precision and recall in forecasting the need for surgical intervention 1 or 2 days ahead. This predictive capability holds promise for enhancing infants’ outcomes by facilitating timely clinical decisions.

Objective: Perihematomal edema (PHE) is one of the significant secondary cerebral damages, with the blood–brain barrier's integrity playing a pivotal role in its progression. Strengthening tight junction (TJ) proteins enhances blood–brain barrier integrity, yet the complex genetics behind brain edema remain not fully understood. Our research endeavors to uncover pivotal genes and their roles in brain edema following cerebral hemorrhage, and to investigate potential treatment strategies. Methods: By analyzing intracerebral hemorrhage (ICH) and control samples using the GSE216607 and GSE206971 datasets, we identified differentially expressed genes. Cross-referencing with the KEGG database, we aligned these genes with those related to tight junctions. Extensive enrichment analysis and protein interactions were performed to examine the expression and clinical significance of the identified genes. Our study employed the C57BL/6J mouse ICH model and qRT-PCR for key gene validation. Results: Notably, VASP, HCLS1, MSN, and EZR, critical for tight junctions, showed increased expression post-ICH, emphasizing their significance in BBB upkeep and PHE progression. Drug validation indicated potential therapeutic effects of Testosterone enanthate, SELENIUM, and LY 294002 on tight junction-related genes. Conclusion: This study sheds light on the potential involvement of these genes in brain edema progression post-ICH, offering promising therapeutic targets. Further research is needed for deeper understanding.

A three-dimensional model was established for coupled simulation of the physical field in a liquid subjected to dual-frequency ultrasonic vibration. The effect of sonotrode position, tip shape, and vessel on the distributions of acoustic pressure and acoustic streaming were clarified. The influence of physical fields on the solidification behavior of Mg alloy was investigated. The simulation results show that the interaction between the two ultrasounds was weakened as the sonotrode spacing increased, and the radiating angle had little effect on the acoustic pressure distribution. The volume mean pressure in the liquid radiated by the plane tip was the smallest, but with the greatest acoustic streaming intensity. In contrast, the spherical tip radiated the highest volume mean pressure in the liquid medium, but the acoustic streaming was severely suppressed. Attributed to the smooth spherical surface that facilitated fluid flow, high flow velocity could be achieved using a round-bottomed crucible without severe acoustic pressure attenuation. The experimental results show that cavitation and acoustic flow caused the coarse dendrites to turn into fine isometric crystals. The acoustic flow accelerated the melt flow and alleviated the segregation and precipitation of Zn elements, leading to a decrease in the content and size of the second phase in the billet.

Phascolosoma esculenta is an economically species inhabiting a soft substrate of mud in the intertidal zone, which is bad breathability, especially during the prolonged heavy rainstorms, that will bring hypoxia environment to P. esculenta. In this study, the negative impact of hypoxia on P. esculenta was firstly studied. The results showed that there were no P. esculenta died post 7 days hypoxia. However, P. esculenta surface became black after hypoxia stress and changed to brown after reoxygenation. The body cavity fluid’s total antioxidant capacity (T-AOC) showed notable increases at 48 h, 120 h, and 168 h post hypoxia stress and returned to the control level after reoxygenation. The contents of malondialdehyde (MDA) increased significantly at 24 h, 48 h, and 96 h but decreased substantially after reoxygenation. The activity of lactate dehydrogenase (LDH) increased during the hypoxia but decreased significantly after reoxygenation. Transcriptomic analysis was performed and a total of 55.26 GB of clean data were collected, 362 DEGs were obtained based on FPKM values, including 77 DEGs between control and hypoxia groups, 48 DEGs between control and reoxygenation groups, and 237 DEGs between hypoxia and reoxygenation groups. DEGs are enriched in pathways associated with immune system, carbon metabolism, apoptosis, ribosome and ion transport. These data enriched the molecular mechanism of invertebrate hypoxia tolerance and provided genetic material reference for future breeding of hypoxia-tolerant P. esculenta and other aquatic species.

Food supplementation has become an increasingly prevalent strategy for animal conservation. A large white-tailed eagle (Haliaeetus albicilla) population exists in a wetland in Northeast Asia during the boreal winter, mainly because of regular supplementary feeding. However, the use of supplementary food by eagles has not been assessed. In this study, we used non-invasive sampling and DNA metabarcoding to investigate the food composition of white-tailed eagles in a lake near a supplementary feeding site. Our results revealed that supplemental food was present in 94 % of the samples, with a weighted percent of occurrence (wPOO) of 64.62 %. In addition to supplementation, we identified 11 natural prey species, including fish, birds, and mammals, from freshwater, marine, and terrestrial ecosystems. After February, there was an increasing trend in the frequency of natural food items, especially of marine fish, in the diet of the eagles. Our study demonstrates the power of DNA metabarcoding in dietary studies of raptor species in the presence of supplementary feeding. Based on our results, multiple recommendations have been provided to achieve adaptive management of large nonbreeding populations of eagles in our study area.

Abstract Structure, stability, electronic structure, spectroscopy and chemical bonding properties of a fluorine atom doped gas-phase small to medium-sized magnesium clusters, FMgn (n = 2–20), systematically investigated by CALYPSO software together with density functional theory (DFT). Structural calculations showed that FMgn has a structural diversity which is rarely reported in other magnesium-based clusters before. F atoms were always located in the outer layer of the Mgn host clusters and only two or three Mg atoms surround it. FMg18 was revealed to be supposed to have robust relative stability. Charge transfer and density of states were calculated for analyzing the electronic structure characteristics. Theoretical calculations of IR, Raman and UV–Vis spectra were computed to provide data guidelines for future experimental observations. Finally, the F–Mg and Mg–Mg chemical bonds of the FMgn clusters were analyzed, including the critical bonding points (BCPs) of Laplacian of electron density (Δρ), electron localization function (ELF) and interaction region indicator (IRI). The kind and strength of chemical bonds reveal the mechanism by which the F atom was rapidly stabilized by Mgn (n = 2–20) host clusters.

Abstract The dynamics of proteins are crucial for understanding their mechanisms. However, computationally predicting protein dynamic information has proven challenging. Here, we propose a neural network model, RMSF-net, which outperforms previous methods and produces the best results in a large-scale protein dynamics dataset; this model can accurately infer the dynamic information of a protein in only a few seconds. By learning effectively from experimental protein structure data and cryo-electron microscopy (cryo-EM) data integration, our approach is able to accurately identify the interactive bidirectional constraints and supervision between cryo-EM maps and PDB models in maximizing the dynamic prediction efficacy. Rigorous 5-fold cross-validation on the dataset demonstrates that RMSF-net achieves test correlation coefficients of 0.746 ± 0.127 at the voxel level and 0.765 ± 0.109 at the residue level, showcasing its ability to deliver dynamic predictions closely approximating molecular dynamics simulations. Additionally, it offers real-time dynamic inference with minimal storage overhead on the order of megabytes. RMSF-net is a freely accessible tool and is anticipated to play an essential role in the study of protein dynamics.

Abstract As our planet is entering into the “global boiling” era, understanding regional climate change becomes imperative. Effective downscaling methods that provide localized insights are crucial for this target. Traditional approaches, including computationally-demanding regional dynamical models or statistical downscaling frameworks, are often susceptible to the influence of downscaling uncertainty. Here, we address these limitations by introducing a diffusion probabilistic downscaling model (DPDM) into the meteorological field. This model can efficiently transform data from 1° to 0.1° resolution. Compared with deterministic downscaling schemes, it not only has more accurate local details, but also can generate a large number of ensemble members based on probability distribution sampling to evaluate the uncertainty of downscaling. Additionally, we apply the model to generate a 180-year dataset of monthly surface variables in East Asia, offering a more detailed perspective for understanding local scale climate change over the past centuries.

In this study, we demonstrate the tunable modulation of the electromagnetically induced transparency (EIT) effect using L-shaped complementary graphene metamaterials. The structure consists of a horizontal line slot and a vertical line slot, representing the bright and dark modes, respectively. The synergistic interaction between the bright and dark modes generates a pronounced transparent window within the transmission spectrum. Owing to symmetry, the EIF effect can be realized in two perpendicular polarization directions. Compared to metallic metamaterials, graphene metamaterials are tunable by controlling the Fermi energy of graphene via the gate voltage rather than by redesigning the structure. The regulation of the Fermi energy level in the complementary graphene metamaterials presented herein is more straightforward than that in the discrete graphene configurations. By tuning the EIT transparent window, we enabled actively controlled sensing capabilities and the realization of slow light effects. This work illuminates potential applications in the development of environmental sensors, slow-light devices, and terahertz modulators.

Abstract The degeneration of the neuromuscular junction (NMJ) and the decline in motor function are common features of aging, but the underlying mechanisms have remained largely unclear. This study reveals that Sirt6 is reduced in aged mouse muscles. Ablation of Sirt6 in skeletal muscle causes a reduction of Dystrophin levels, resulting in premature NMJ degeneration, compromised neuromuscular transmission, and a deterioration in motor performance. Mechanistic studies show that Sirt6 negatively regulates the stability of the Dystrophin repressor YY1 (Yin Yang 1). Specifically, Sirt6 mono‐ADP‐ribosylates YY1, causing its disassociation from the Dystrophin promoter and allowing YY1 to bind to the SMURF2 E3 ligase, leading to its degradation. Importantly, supplementation with nicotinamide mononucleotide (NMN) enhances the mono‐ADP‐ribosylation of YY1 and effectively delays NMJ degeneration and the decline in motor function in elderly mice. These findings provide valuable insights into the intricate mechanisms underlying NMJ degeneration during aging. Targeting Sirt6 could be a potential therapeutic approach to mitigate the detrimental effects on NMJ degeneration and improve motor function in the elderly population.

Metal exposure has been reported to be associated with metabolic syndrome (MetS), however, the evidence remains inconclusive, particularly in elderly individuals. From May to July 2016, serum levels of 16 metals were measured using inductively coupled plasma mass spectrometry (ICP-MS) in 852 elderly individuals (≥65 years) residing in Wuhan, China. Biological detection and disease recognition were based on individual surveys conducted during health check-ups. Spearman’s rank correlation analysis was performed to identify the correlation among serum metals. The data were Ln-transformed to fit a normal distribution for further analyses. Linear and logistic regression were applied to explore the associations between metals and diseases. Restricted cubic spline (RCS) analysis was utilized to examine dose-response relationships. The Weighted Quantile Sum (WQS) score was applied to determine the empirical weights of each heavy metal in the context of their combined effect on metabolic diseases. The prevalence of MetS, hypertension, diabetes, and hyperlipidemia were 46.36 %, 68.90 %, 24.65 %, and 21.60 %, respectively. Serum metal mixture was positively associated with the prevalence of MetS (OR = 1.92, 95 % CI: 1.30–2.82), hypertension (OR = 1.50, 95 % CI: 1.01–2.23), and diabetes (OR = 2.18, 95 % CI: 1.48–3.22). In single metal models, we found that serum zinc levels were associated with an increased risk of MetS, while rubidium had a protective effect against MetS. Interestingly, different metals had distinct effects on specific diseases in this study: lithium and barium were more likely to influence blood pressure, while selenium had a more significant effect on blood glucose. Lipids were more susceptible to the effects of zinc, selenium, and strontium. Platelet count (PLT) and lymphocyte count (LYM) mediated the association between selenium exposure and hyperlipidemia, while neutrophil count (NEU) mediated the relationship between serum rubidium exposure and MetS. Our findings offer valuable etiological insights into the relationship between serum heavy metals and the prevalence of MetS, suggesting that peripheral blood cells may play a mediating role in this association.

Vascular cognitive impairment (VCI) is a clinical syndrome that arises from cerebrovascular issues and associated risk factors, resulting in difficulties in at least one area of cognitive function. VCI has emerged as the second most prevalent type of dementia following Alzheimer's disease, yet there is no effective clinical treatment. Botch, an endogenous Notch1 antagonist, demonstrates neuroprotective effects by inhibiting neuroinflammatory responses mediated through the Notch pathway. While its role in stroke-induced neuroinflammation is well-established, its involvement in VCI remains largely unexplored. This study investigates the role and potential mechanisms of Botch in a rat model of cognitive impairment caused by bilateral common carotid artery occlusion (BCCAO). Firstly, we observed that Botch levels were down-regulated in BCCAO rats, which correlated with increased release of inflammatory cytokines and neuronal damage. Microglia in BCCAO rats released interleukin-1α (IL-1α), tumor necrosis factor-α (TNF-α), and complement component 1q (C1q), leading to the activation of neurotoxic C3+ A1 reactive astrocytes. Then, the down-regulation of Botch exacerbated microglia-mediated inflammation, activated C3+ A1 astrocytes, worsened neuronal damage, and led to a decline in cognitive function. Conversely, the re-expression of Botch alleviated C3+ astrocyte activation, inhibited neuronal damage, and improved mental function. In conclusion, Botch plays a crucial role in inhibiting neuroinflammation induced by type A1 reactive astrocytes. It achieves this by blocking the activation of microglia triggered by the Notch pathway. Ultimately, it inhibits neuronal damage to play a neuroprotective role. These findings suggest that Botch may represent a novel potential target for treating VCI.

BackgroundThe role of vitamin C in osteoarthritis (OA) is still a subject of debate. Our aim was to combine the National Health and Nutrition Examination Survey (NHANES) and MR studies to explore the relationship between vitamin C intake and OA.MethodsClinical information on participants during NHANES 2003–2018 was collected and the relationship between vitamin C intake and OA risk was assessed using logistic regression modelling. In MR analyses, three methods were used to explore the causality of vitamin C intake with OA. Sensitivity analysis to verify the stability of the MR study.ResultsThe cross-sectional study included a total of 31,527 participants, categorizing them into low (93.0 mg) level groups based on their vitamin C intake levels. Logistic regression models showed that vitamin C intake was not associated with OA risk (p > 0.05). Inverse-variance weighted (IVW) method of MR study showed no causality between vitamin C intake and OA (OR = 0.993, 95% CI: 0.901 ~ 1.095, p = 0.882). Sensitivity analysis indicated that the MR study was reliable.ConclusionOur cross-sectional and MR studies showed that vitamin C intake was not associated with OA risk. More researches are needed in the future to investigate the link between vitamin C and OA.

Summary: Motor neurons are highly polarized, and their axons extend over great distances to form connections with myofibers via neuromuscular junctions (NMJs). Local translation at the NMJs in vivo has not been identified. Here, we utilized motor neuron-labeled RiboTag mice and the TRAP (translating ribosome affinity purification) technique to spatiotemporally profile the translatome at NMJs. We found that mRNAs associated with glucose catabolism, synaptic connection, and protein homeostasis are enriched at presynapses. Local translation at the synapse shifts from the assembly of cytoskeletal components during early developmental stages to energy production in adulthood. The mRNA of neuronal Agrin (Agrn), the key molecule for NMJ assembly, is present at motor axon terminals and locally translated. Disrupting the axonal location of Agrn mRNA causes impairment of synaptic transmission and motor functions in adult mice. Our findings indicate that spatiotemporal regulation of mRNA local translation at NMJs plays critical roles in synaptic transmission and motor functions in vivo.

Objective: This study aimed to explore the influencing factors of dynamic changes in traditional Chinese medicine (TCM) constitution based on general statistics, Apriori-DEMATEL algorithm, and DoWhy causal inference framework methods. Methods: Dynamic collection of TCM constitution identification data was conducted from the population aged 18 − 60, containing collection time and constitution type, and 11 constitution influencing factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, stress level, living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. General statistical analysis was used to analyze the relative percentage of corresponding influencing factors of different types of constitution changes, the Apriori-DEMATEL algorithm was used to analyze the correlation between 11 constitution influencing factors such as dietary habit and constitution changes, and the DoWhy causal inference framework was used to analyze the causality between dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, explore the frequency of constitution type transformation-change factors, and determine the key influencing factors causing dynamic changes in constitution type. Results: After preprocessing, 13536 valid data points were obtained. Based on the Apriori-DEMATEL algorithm, the factors were divided into six original factors including dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level, and five result factors including living environment, work/life calamity, family atmosphere, business trip frequency, and overtime situation. Combining with general statistics, we found that among the original factors, changes in dietary habit, sleeping habit, sleeping duration, and stress level had a greater impact on other factors. In the process of constitution conditioning, attention should be paid to these four factors to maintain constitution balance. Among the five result factors, the absolute values of work/life calamity and family atmosphere were relatively large, indicating that these two factors were easily influenced by other factors. The dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level have higher centrality in changes, indicating that these six factors had important in constitution changes. According to the statistical frequency of constitution changes corresponding to each factor, we found that the changes of these six factors accounted for a large proportion of the constitution transformation frequency among Qi deficiency constitution, balanced constitution, and allergic constitution, indicating that the changes of these six factors played an important role in the changes of the three constitution types. Combined with the results of the Apriori-DEMATEL algorithm, and DoWhy causal inference framework analysis, it was inferred that dietary habit and sleeping duration indirectly lead to constitution changes by affecting the changes of other factors. Conclusion: This study explored the influencing factors of dynamic changes in TCM constitution from the perspective of dynamic data and multiple analysis methods, and the results showed that the changes of dietary habit, sleeping habit, sleeping duration, exercise habit, emotion state, and stress level had a great impact on the changes of Qi deficiency constitution, balanced constitution and allergic constitution. Attention should be paid to the changes of these six factors in daily life, and corresponding improvement plans should be formulated to reduce the probability of transforming into biased constitution. Our study also provided data support and objective analysis reference for the analysis of influencing factors of dynamic changes in TCM constitution types.

The paramount significance of temperature’s influence on rock engineering endeavors underscores its profound capacity to alter the physical and mechanical attributes of rocks. Among the most crucial techniques utilized to thermally induce damage and diminish the tensile resilience of rock materials are microwave irradiation and heat treatment. This research examines and compares the effects of these two modalities on the dynamic tensile characteristics of Fangshan granite (FG), including their implications under conditions of overload and dependencies on loading rate, utilizing the sophisticated Split Hopkinson Pressure Bar (SHPB) apparatus. In particular, the dynamic real tensile strength (RST) of Brazilian disc (BD) specimens was meticulously gauged and contrasted after subjecting them to microwave irradiation at a potent 6 kW for varying durations (1.5, 3.0, and 4.5 min) and heat treatment across distinct temperature thresholds (178 °C, 345 °C, and 473 °C). To enhance the precision of the measurements, an overload correction was implemented by affixing a strain gauge in close proximity to the core of the BD specimen. The conventional dynamic tensile strength exhibited a reduction of approximately 20 to 30% with the prolongation of microwave radiation time. Furthermore, an additional decrease in tensile strength was observed with the elevation of heat treatment temperatures, reaching a maximum reduction of up to 40%. This phenomenon can be attributed to the proliferation and expansion of microcracks within the rock matrix. It was noteworthy that the RTS, corrected for overloading effects, exhibited a comparable trend to the dynamic traditional tensile strength (TTS). Both were significantly correlated with the loading rate, with the dynamic tensile strength demonstrating an average decrease of approximately 25% when the loading rate was increased. Interpolation and fitting analyses were employed to investigate the effects of microwave radiation duration, heat treatment temperature, and loading rate on the dynamic tensile strength of FG samples. Furthermore, it was established that the overload ratio increased in conjunction with an increase in microwave radiation duration, heat treatment temperature, and loading rate, reaching a maximum value of 1.5.

Objectives: To investigate the effects of music intervention on the vital signs, weight gain, feeding, hospital stays, and cost of premature infants. Methods: 100 premature infants were randomized into two groups: the experimental group (given music for 30 min at a time, once every day until discharge) and the control group (without music). To compare the vital signs (RR, HR, SPO2) before, during, and after the music intervention, as well as the weight gain and feeding, follow up to 3 months after discharge. Results: Although respiratory rate (RR) showed a decreasing trend at certain time points during and after music exposure, these changes did not reach statistical significance after adjusting for multiple comparisons. The experimental group had a shorter time to regain birth weight (6.07 ± 2.47 days) compared to the control group (8.93 ± 4.31 days) and a shorter time of intravenous nutrition (8.6 ± 3.87 days vs. 11.66 ± 5.85 days). The experimental group also exhibited a lower fasting rate, a faster-sucking speed, a lower hospital stay (10.36 ± 4.36 days vs. 12.46 ± 5.73 days), lower cost, higher NBNA scores, and a lower re-hospitalization rate within 3 months after the first discharge. Conclusions: Early music intervention may contribute to the growth and development of preterm infants, improve feeding, reduce hospitalization duration and costs, and improve short-term prognosis, though effects on respiratory rate require further study with a larger sample size.

ABSTRACT: The aim of this study was to examine the effects of NH3 variations across different positions within a cage-reared duck house on the egg production performance and fecal microbiome in Muscovy ducks. Totals of 3,168 female Muscovy ducks (180 ± 2 d) were randomly assigned to 1,056 cages. From d 293 to 300, the egg production rate and levels of NH3, H2S, CO2, temperature, humidity, light intensity, and dust particles were recorded. Two spatial distribution-based experimental classification methods were applied, one grouping ducks into Front, Middle, and End categories, and the other into First, Second, and Third layers. On d 300, serum and feces samples were collected for further analysis. The result showed that both the egg production rate and serum PROG level in the Front were higher than End (P < 0.05). However, no significant differences were found among the First, Second, and Third groups. Among the environmental factors, ammonia (NH3) is a major harmful gas in cage-reared duck houses, with observed concentrations showing a gradient from lower levels in the Front group to higher levels in the Middle group (P < 0.05), and even higher levels in the End group (P < 0.05). Gene sequencing of the 16S rRNA gene revealed a higher relative abundance of Firmicutes in both the Front and Middle groups compared to the End group (P < 0.05). Specifically, within the Firmicutes phylum, the relative abundance of Lactobacillus and Romboutsia was notably higher in the Front group compared to both the Middle and End groups (P < 0.05). What's more, the abundance of Lactobacillus had a negative correlation with NH3 concentration and positive correlation with egg production rate. In conclusion, NH3 concentrations showed variations across different areas of the cage-reared duck house, with higher levels detected at the rear. The elevated NH3 level was identified as the main factor negatively impacting egg production in Muscovy ducks and contributing to a decline in the abundance of Firmicutes, specifically Lactobacillus.

Cancer is a major disease with ever-increasing morbidity and mortality. The metabolites derived from traditional Chinese medicine (TCM) have played a significant role in combating cancers with curative efficacy and unique advantages. Ferroptosis, an iron-dependent programmed death characterized by the accumulation of lipid peroxide, stands out from the conventional forms of cell death, such as apoptosis, pyroptosis, necrosis, and autophagy. Recent evidence has demonstrated the potential of TCM metabolites targeting ferroptosis for cancer therapy. We collected and screened related articles published in or before June 2023 using PubMed, Google Scholar, and Web of Science. The searched keywords in scientific databases were ferroptosis, cancer, tumor, traditional Chinese medicine, botanical drugs, and phytomedicine. Only research related to ferroptosis, the metabolites from TCM, and cancer was considered. In this review, we introduce an overview of the current knowledge regarding the ferroptosis mechanisms and review the research advances on the metabolites of TCM inhibiting cancer by targeting ferroptosis.

Differentiation of oligodendrocyte progenitor cells into mature myelin-forming oligodendrocytes contributes to remyelination. Failure of remyelination due to oligodendrocyte progenitor cell death can result in severe nerve damage. Ferroptosis is an iron-dependent form of regulated cell death caused by membrane rupture induced by lipid peroxidation, and plays an important role in the pathological process of ischemic stroke. However, there are few studies on oligodendrocyte progenitor cell ferroptosis. We analyzed transcriptome sequencing data from GEO databases and identified a role of ferroptosis in oligodendrocyte progenitor cell death and myelin injury after cerebral ischemia. Bioinformatics analysis suggested that perilipin-2 (PLIN2) was involved in oligodendrocyte progenitor cell ferroptosis. PLIN2 is a lipid storage protein and a marker of hypoxia-sensitive lipid droplet accumulation. For further investigation, we established a mouse model of cerebral ischemia/reperfusion. We found significant myelin damage after cerebral ischemia, as well as oligodendrocyte progenitor cell death and increased lipid peroxidation levels around the infarct area. The ferroptosis inhibitor, ferrostatin-1, rescued oligodendrocyte progenitor cell death and subsequent myelin injury. We also found increased PLIN2 levels in the peri-infarct area that co-localized with oligodendrocyte progenitor cells. Plin2 knockdown rescued demyelination and improved neurological deficits. Our findings suggest that targeting PLIN2 to regulate oligodendrocyte progenitor cell ferroptosis may be a potential therapeutic strategy for rescuing myelin damage after cerebral ischemia.

Abstract Electrocatalytic acetylene semi-hydrogenation to ethylene powered by renewable electricity represents a sustainable pathway, but the inadequate current density and single-pass yield greatly impedes the production efficiency and industrial application. Herein, we develop a F-modified Cu catalyst that shows an industrial partial current density up to 0.76 A cm−2 with an ethylene Faradic efficiency surpass 90%, and the maximum single-pass yield reaches a notable 78.5%. Furthermore, the Cu-F showcase the capability to directly convert acetylene into polymer-grade ethylene in a tandem flow cell, almost no acetylene residual in the production. Combined characterizations and calculations reveal that the Cuδ+ (near fluorine) enhances the water dissociation, and the generated active hydrogen are immediately transferred to Cu0 (away from fluorine) and react with the locally adsorbed acetylene. Therefore, the hydrogen evolution reaction is surpassed and the overall acetylene semi-hydrogenation performance is boosted. Our findings provide new opportunity towards rational design of catalysts for large-scale electrosynthesis of ethylene and other important industrial raw.

Background: Ocular predominant mucous membrane pemphigoid (oMMP) is a severe subtype of autoimmune blistering disease (AIBD), which can result in scarring and vision loss. The diagnosis of oMMP is challenging as patients often have undetectable levels of circulating autoantibodies by conventional assays. Likewise, the principal autoantigen in oMMP has been an area of debate. Methods: In this preliminary experiment, we performed Phage Immunoprecipitation Sequencing (PhIP-seq) on sera from patients with oMMP, as well as non-ocular MMP, bullous pemphigoid, and mucocutaneous-type pemphigus vulgaris. Results: We identified several autoantigens unique to oMMP relative to other AIBDs. We then cross-referenced these antigens against previously published single-nuclei datasets, as well as the International Mouse Phenotyping Consortium Database. Several protein hits identified in our study demonstrated enriched expression on the anterior surface epithelia, including TNKS1BP1, SEC16B, FNBP4, CASZ1, GOLGB1, DOT1L, PRDM 15, LARP4B, and RPL6. Likewise, a previous study of mouse knockout models of murine analogs CASZ1, HIP1, and ELOA2 reported that these mice showed abnormalities in terms of the ocular surface and development in the eyes. Notably, PhIP-seq failed to identify the canonical markers of AIBDs such as BP180, BP230, desmogleins 1 and 3, or integrin β4, indicating that the patient autoantibodies react with conformational epitopes rather than linear epitopes. Conclusions: oMMP patients demonstrate a unique autoantibody repertoire relative to the other AIBDs. Further validation of the identified autoantibodies will shed light on their potentially pathogenic role.

Estimation of forest above-ground biomass (AGB) using multi-source remote sensing data is an important method to improve the accuracy of the estimate. However, selecting remote sensing factors that can effectively improve the accuracy of forest AGB estimation from a large amount of data is a challenge when the sample size is small. In this regard, the Least Absolute Shrinkage and Selection Operator (Lasso) has advantages for extensive redundant variables but still has some drawbacks. To address this, the study introduces two Least Absolute Shrinkage and Selection Operator Lasso-based variable selection methods: Least Absolute Shrinkage and Selection Operator Genetic Algorithm (Lasso-GA) and Variance Inflation Factor Least Absolute Shrinkage and Selection Operator (VIF-Lasso). Sentinel 2, Sentinel 1, Landsat 8 OLI, ALOS-2 PALSAR-2, Light Detection and Ranging, and Digital Elevation Model (DEM) data were used in this study. In order to explore the variable selection capabilities of Lasso-GA and VIF-Lasso for remote sensing estimation of forest AGB. It compares Lasso-GA and VIF-Lasso with Boruta, Random Forest Importance Selection, Pearson Correlation, and Lasso for selecting remote sensing factors. Additionally, it employs eight machine learning models—Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), Bayesian Regression Neural Network (BRNN), Elastic Net (EN), K-Nearest Neighbors (KNN), Extremely Randomized Trees (ETR), and Stochastic Gradient Boosting (SGBoost)—to estimate forest AGB in Wuyi Village, Zhenyuan County. The results showed that the optimized Lasso variable selection could improve the accuracy of forest biomass estimation. The VIF-Lasso method results in a BRNN model with an R2 of 0.75 and an RMSE of 16.48 Mg/ha. The Lasso-GA method results in an ETR model with an R2 of 0.73 and an RMSE of 16.70 Mg/ha. Compared to the optimal SGBoost model with the Lasso variable selection method (R2 of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R2 by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R2 by 0.04 and reduces RMSE by 1.93 Mg/ha. From another perspective, they also demonstrated that the RX sample count and sensitivity provided by LiDAR, as well as the Horizontal Transmit, Vertical Receive provided by Microwave Radar, along with the feature variables (Mean, Contrast, and Correlation) calculated from the Green, Red, and NIR bands of optical remote sensing in 7 × 7 and 5 × 5 windows, play an important role in forest AGB estimation. Therefore, the optimized Lasso variable selection method shows strong potential for forest AGB estimation using multi-source remote sensing data.

The purpose of this study is to examine how students may hold coexisting and competing conceptual ideas and how students’ uses of such ideas may evolve during the process of conceptual change by combining two complementary methods including model analysis and the conceptual framework model of knowledge integration. Conceptual change is fundamental to science learning, highlighting the processes of students’ transitions from predominantly relying on alternative views to using scientific ones. Recent studies suggest a growing consensus that alternative views and scientific conceptions coexist and compete in students’ learning. However, explicit research on how the states of coexistence and competition evolve during the process of conceptual change is underdeveloped. Building on existing research, the model analysis provides a quantitative framework to represent the different consistent and coexisting/competing states through probabilities of consistent and/or mixed (coexisting) use of incorrect and scientific ideas. Meanwhile, the conceptual framework model of knowledge integration provides content-specific, cognitive explanations for the developmental levels and processes of conceptual change from novice to expert. By combining these two methods, researchers can gain insights into how the coexistence and competition among different conceptual ideas may evolve as conceptual change progresses. To target the research goal, a model-based knowledge integration assessment of Newton’s third law is developed to measure students’ levels of knowledge integration and model states in a single test. Quantitative data were collected from Chinese high school students, supplemented by interviews with a subgroup from the same population. The model analysis results show the heterogeneity of conceptual development and the evolving competition across novice, intermediate, and expert students, as well as across different concept dimensions. The interviews provide cognitive explanations for the observed model states, framed from the lens of knowledge integration. These insights can inform the development of effective assessments and instructional strategies to facilitate favorable conceptual change in student learning.

The galvanic cell is a typical interdisciplinary topic, which is primarily taught in chemistry but its underpinning is closely related to physics. Student learning in galvanic cell has been extensively studied in chemistry education, which has revealed a large number of misconceptions that are difficult to change through traditional instruction. A source of the learning difficulties is that most students lack an explanatory framework to integrate the many complex phenomena and processes into a coherent knowledge system. As a result, students often rely on memorization of terms, laws, and equations in solving problems but without a meaningful understanding of their reasoning. To address the deficit in learning, this study aims to help students develop an explanatory framework for supporting an integrated knowledge structure. Specifically, a conceptual framework model for galvanic cell is developed based on the central idea from physics, which is used as the core concept for mechanistic explanations of the related chemistry concepts. Guided by the conceptual framework, an instrument is developed to assess the knowledge integration in student learning of galvanic cell. A combination of qualitative and quantitative measures was used to assess the levels of knowledge integration in learning galvanic cell with a large number of Chinese high school and college students. The assessment results show that the conceptual framework model can effectively represent the knowledge structures of students at different levels of knowledge integration. The galvanic cell conceptual framework and assessment results can provide useful resources for teachers to develop instruction for promoting knowledge integration.