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Abstract Background This study aimed to analyze the epidemic characteristics and influencing factors of school influenza outbreaks in Jiangsu Province, China from 2020 to 2023,following the COVID-19 pandemic, to inform prevention and control strategies. Methods Data on influenza-like illness(ILI) outbreaks from the Chinese Influenza Surveillance Information System and national-level influenza surveillance sentinel hospitals were analyzed. The temporal distribution, school type, virus strains, and outbreak scales were examined using descriptive statistics. Results From 2020 to 2023, 1142 influenza outbreaks occurred in schools, with primary schools(ages 6 to 12) accounting for 71.80%. Most large outbreaks were caused by A(H1N1) and A(H3N2), responsible for 8.99% of total outbreaks. Outbreaks were predominantly reported in the pre-peak periods of B(Victoria) and A(H1N1) circulation, accounting for 86.31% and 92.32% of their respective total outbreaks. No concurrent influenza and COVID-19 outbreaks were observed during the study period. Conclusion Primary and secondary schools are high-risk settings for influenza outbreaks. A(H3N2) shows higher adaptability and is more likely to co-circulate with other subtypes/lineages, especially A(H1N1), leading to larger outbreaks. B(Victoria)-caused outbreaks are more frequent but smaller in scale. School influenza outbreaks are more likely to occur during the early stages of seasonal peaks, particularly for B(Victoria) and A(H1N1). This suggests that influenza outbreaks in schools may play a crucial role in seeding and accelerating the spread of the virus within the broader community.

PurposeTo investigate the association between dietary vitamin D intake and low muscle mass (LMM) in a representative adult population, accounting for total energy intake and other potential confounders.Materials and methodsThis cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES) involving 8,443 participants. Dietary vitamin D intake was assessed using 24-h dietary recalls, and LMM was defined based on appendicular lean mass (ALM) adjusted for body mass index (BMI). Multivariable logistic regression models were used to examine the association between quartiles of dietary vitamin D intake and the odds of LMM, adjusting for age, gender, race/ethnicity, BMI, total energy intake, and additional covariates.ResultsIn Model 1, after adjusting for age, gender, race/ethnicity, BMI, and poverty-to-income ratio, participants in the highest quartile of vitamin D intake had an odds ratio (OR) of 0.54 (95% CI: 0.37–0.79) compared to the lowest quartile, with a p for trend

BackgroundThe Metabolic Score for Insulin Resistance (METS-IR) offers a promising and reliable non-insulin-based approach to assess insulin resistance and evaluate cardiometabolic risk. However, evidence for the association between METS-IR and hypertension was still limited.MethodsParticipants from the National Health and Nutrition Examination Survey (NHANES) database from 2007-2016 were selected for weighted multivariable regression analyses, subgroup analyses and restricted cubic spline (RCS) modeling to assess the association between the METS-IR and hypertension, as well as systolic blood pressure (SBP) and diastolic blood pressure (DBP).ResultsThis study enrolled 7,721 adults aged ≥20 years, 2,926 (34.03%) of whom was diagnosed as hypertension. After adjusting for all potential covariates, an increased METS-IR (log2 conversion, denoted as log2METS-IR) was independently associated with a higher prevalence of hypertension (odd ratio [OR] 3.99, 95% confidence interval [CI] 3.19~5.01). The OR for hypertension in subjects with the highest quartile of METS-IR was 3.89-fold (OR 3.89, 95% CI 3.06~4.94) higher than that in those with the lowest quartile of METS-IR. This positive correlation became more significant as METS-IR increased (p for trend < 0.001). Log2METS-IR was significantly correlated with increase in SBP (β 6.75, 95% CI 5.65~7.85) and DBP (β 5.59, 95% CI 4.75~6.43) in a fully adjusted model. Consistent results were obtained in subgroup analyses. Hypertension, SBP and DBP all exhibited a non-linear increase with the rise in METS-IR. The minimal threshold for the beneficial association of METS-IR with hypertension, SBP and DBP were all identified to be 46.88.ConclusionThe findings of this study revealed a significant positive association between METS-IR and hypertension among US adults, suggesting METS-IR as a potential tool for assessing hypertension risk.

Abstract Background The effect of long‐standing prediabetes or its transition on incident cardiovascular disease (CVD) is unclear. This study aimed to evaluate the association of changes in fasting blood glucose (FBG) status with the risk of developing CVD. Methods This research included 12 145 Chinese adults aged 35–74 years and free from diabetes mellitus (DM) at baseline. Study participants were cross‐classified into six categories according to glucose at the first (1998–2001) and the second visit after 8 years: normal fasting glucose (NFG; 50–99 mg/dl), impaired FBG (IFG; 100–125 mg/dl), and DM. Cox proportional hazard regression model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for CVD associated with transition of glucose status. Results During a median follow‐up of 5.5 years, 373 incident CVD cases occurred. Compared with participants remaining persistent NFG, a higher risk of developing CVD was identified among those remaining persistent IFG, progressing to DM from NFG or from IFG, with the multivariate‐adjusted HR (95% CI) of 1.792 (1.141, 2.816), 1.723 (1.122, 2.645) and 1.946 (1.120, 3.381), respectively. Furthermore, when stratified by glucose status at baseline, persistent IFG and progression from IFG to DM still increased CVD risk in comparison with reversion from IFG to NFG, with the multivariate‐adjusted HR (95% CI) of 1.594 (1.003, 2.532) and 1.913 (1.080, 3.389). Conclusions Participants with long‐standing IFG and progressing to DM had a higher risk of developing CVD. Further well‐designed studies are warranted to assess the association of other phenotypes or prediabetes duration with CVD.

Background: Osteosarcoma (OS) is the most common malignant bone tumor in clinical practice, and currently, the ability to predict prognosis in the diagnosis of OS is limited. There is an urgent need to find new diagnostic methods and treatment strategies for OS. Material and methods: We downloaded the multi-omics data for OS from the TARGET database. Prognosis-associated methylation sites were used to identify clustered subtypes of OS, and OS was classified into 3 subtypes (C1, C2, C3). Survival analysis showed significant differences between the C3 subtype and the other subtypes. Subsequently, differentially expressed genes (DEGs) across subtypes were screened and subjected to pathway enrichment analysis. Results: A total of 249 DEGs were screened from C3 subtype to other subtypes. Metabolic pathway enrichment analysis showed that DEGs were significantly enriched to the hypoxic pathway. Based on univariate and multivariate COX regression analysis, 12 genes from the hypoxia pathway were further screened and used to construct hypoxia-related prognostic model (HRPM). External validation of the HRPM was performed on the GSE21257 dataset. Finally, differences in survival and immune infiltration between high and low risk score groups were compared. Conclusion: In summary, we proposed a hypoxia-associated risk model based on a 12-gene expression signature, which is potentially valuable for prognostic diagnosis of patients with OS.

The vertical component magnetic field signal in the ground–airborne frequency domain electromagnetic (GAFDEM) method is detected by the air coil sensor, which is parallel to the ground. Unfortunately, the air coil sensor has low sensitivity in the low-frequency band, making it challenging to detect effective low-frequency signals and causing low accuracy and large error for interpreted deep apparent resistivity in actual detection. This work develops an optimized weight magnetic core coil sensor for GAFDEM. The cupped flux concentrator is used in the sensor to reduce the weight of the sensor while maintaining the magnetic gathering capacity of the core coil. The winding of the core coil is optimized to resemble the shape of a rugby ball, taking full advantage of the magnetic gathering capacity at the core center. Laboratory and field experiment results show that the developed optimized weight magnetic core coil sensor for the GAFDEM method is highly sensitive in the low-frequency band. Therefore, the detection results at depth are more accurate compared with those obtained using existing air coil sensors.

Obesity is a leading contributor to colorectal cancer (CRC) risk, but the metabolic mechanisms linking obesity to CRC are not fully understood. We leveraged untargeted metabolomics data from two 1:1 matched, nested case–control studies for CRC, including 223 pairs from the US Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial and 190 pairs from a prospective Chinese cohort. We explored serum metabolites related to body mass index (BMI), constructed a metabolomic signature of obesity, and examined the association between the signature and CRC risk. In total, 72 of 278 named metabolites were correlated with BMI after multiple testing corrections (p FDR < 0.05). The metabolomic signature was calculated by including 39 metabolites that were independently associated with BMI. There was a linear positive association between the signature and CRC risk in both cohorts (p for linear < 0.05). Per 1-SD increment of the signature was associated with 38% (95% CI: 9–75%) and 28% (95% CI: 2–62%) higher risks of CRC in the US and Chinese cohorts, respectively. In conclusion, we identified a metabolomic signature for obesity and demonstrated the association between the signature and CRC risk. The findings offer new insights into the underlying mechanisms of CRC, which is critical for improved CRC prevention.

With a purely optical modulation of fluorescent behaviors, stimulated emission depletion (STED) microscopy allows for far-field imaging with a diffraction-unlimited resolution in theory. The performance of STED microscopy is affected by many factors, of which aberrations induced by the optical system and biological samples can distort the wave front of the depletion beam at the focal plane to greatly deteriorate the spatial resolution and the image contrast. Therefore, aberration correction is imperative for STED imaging, especially for imaging thick specimens. Here, we present a wave front compensation approach based on the genetic algorithm (GA) to restore the distorted laser wave front for improving the quality of STED images. After performing aberration correction on two types of zebrafish samples, the signal intensity and the imaging resolution of STED images were both improved, where the thicknesses were 24 μm and 100 μm in the zebrafish retina sample and the zebrafish embryo sample, respectively. The results showed that the GA-based wave front compensation approach has the capability of correction for both system-induced and sample-induced aberrations. The elimination of aberrations can prompt STED imaging in deep tissues; therefore, STED microscopy can be expected to play an increasingly important role in super-resolution imaging related to the scientific research in biological fields.

Objective The goal of this study was to investigate the effects of dietary standard ileal digestible (SID) valine:lysine ratios on performance, intestinal morphology, amino acids of liver and muscle, plasma indices and mRNA expression of branched-chain amino acid (BCAA) metabolism enzymes. Methods A total of 144 crossbred pigs (Duroc×Landrace×Large White) weaned at 28±4 days of age (8.79±0.02 kg body weight) were randomly allotted to 1 of 4 diets formulated to provide SID valine:lysine ratios of 50%, 60%, 70%, or 80%. Each diet was fed to 6 pens of pigs with 6 pigs per pen (3 gilts and 3 barrows) for 28 days. Results Average daily gain increased quadratically (p

Beta-actin (ACTB) loss-of-function mutations result in a pleiotropic developmental disorder of kidney. The present study aims to explore whether the common variants at the ACTB gene contribute to diabetic kidney disease (DKD) susceptibility in patients with type 2 diabetes mellitus (T2DM). From the baseline population of 20,340 diabetic patients, 1,510 DKD cases and 1,510 age-matched T2DM controls were selected. All subjects were Han Chinese. Three tagging single nucleotide polymorphisms (SNPs), rs852423, rs852426, and rs2966449, at the ACTB gene were genotyped. Logistic regression was performed to estimate the association with DKD. SNPs, rs852426 and rs2966449, were significantly associated with DKD [additive model; odds ratio (OR), 1.217 and 1.151; P = 0.001 and 0.018, respectively]. The association of rs852426 with DKD still remained statistically significant after Bonferroni correction and particularly significant in the population older than 70 years rather than the 70 years or younger (P = 0.047 for heterogeneity test). Furthermore, the association of rs852426 with DKD was observed in populations of male and females without smoking, drinking, and with duration for T2DM 10–20 years. The association of rs2966449 with DKD was also found in the populations older than 70 years, male, not smoking, not drinking, and with duration for T2DM over 20 years. The estimated glomerular filtration rate (eGFR) levels of the individuals with TT or CC genotypes of rs2966449 were significantly lower than that of TC genotype in DKD cases (P = 0.021). The present study provides evidence that the ACTB variants, i.e., rs852426 and rs2966449, may confer the genetic susceptibility to DKD in a Han Chinese population.

In water conservancy and transportation engineering, self-healing cement has been widely used. This paper researches the optimal water-cement ratio of self-healing cement mortar to obtain the best basic performance, and on this basis, researches the occasional effect of self-healing agent and fibers on the mechanical properties of cement mortar. In addition, the research on the shrinkage characteristics and impermeability of cement mortar by self-healing agent was carried out to provide the basis for the curing methods of bacterial cement in the project. Finally, the microstructure of self-healing cement provides a theoretical basis for the macroscopic performance. The results show that the best water-cement ratio of the self-healing cement mortar is 0.42, and the fiber can effectively improve the toughness of the material. In addition, bacterial can increase the auto-shrinkage and impermeability of cement. These results will offer valuable experience for experimenters to assist the experiment work.

Medium- and high-entropy alloys (M/HEAs) mix several principal elements with near-equiatomic composition and represent a model-shift strategy for designing previously unknown materials in metallurgy1-8, catalysis9-14 and other fields15-18. One of the core hypotheses of M/HEAs is lattice distortion5,19,20, which has been investigated by different numerical and experimental techniques21-26. However, determining the three-dimensional (3D) lattice distortion in M/HEAs remains a challenge. Moreover, the presumed random elemental mixing in M/HEAs has been questioned by X-ray and neutron studies27, atomistic simulations28-30, energy dispersive spectroscopy31,32 and electron diffraction33,34, which suggest the existence of local chemical order in M/HEAs. However, direct experimental observation of the 3D local chemical order has been difficult because energy dispersive spectroscopy integrates the composition of atomic columns along the zone axes7,32,34 and diffuse electron reflections may originate from planar defects instead of local chemical order35. Here we determine the 3D atomic positions of M/HEA nanoparticles using atomic electron tomography36 and quantitatively characterize the local lattice distortion, strain tensor, twin boundaries, dislocation cores and chemical short-range order (CSRO). We find that the high-entropy alloys have larger local lattice distortion and more heterogeneous strain than the medium-entropy alloys and that strain is correlated to CSRO. We also observe CSRO-mediated twinning in the medium-entropy alloys, that is, twinning occurs in energetically unfavoured CSRO regions but not in energetically favoured CSRO ones, which represents, to our knowledge, the first experimental observation of correlating local chemical order with structural defects in any material. We expect that this work will not only expand our fundamental understanding of this important class of materials but also provide the foundation for tailoring M/HEA properties through engineering lattice distortion and local chemical order.

In this paper, the selective laser melting (SLM) simulation analysis of components is carried out. The residual stress distribution of the formed part was predicted, and the influence of process parameters such as exposure time, laser power and laser scanning speed on the residual stress of the SLM formed part was analyzed. It was found that the residual stress concentration of the formed part was in the middle of the upper surface or the bottom surface. In addition, the laser power and the laser scanning speed have a great influence on the residual stress of the formed part. The results of this study lay a theoretical and experimental basis for the optimization of residual stress and quality control of SLM components.