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Abstract This study critically examines the factors influencing satisfaction with environmental governance in China, focusing on air pollution perception, environmental tax, and government trust within the Environmental, Social, and Governance (ESG) framework. Utilizing data from Chinese societal surveys, the research investigates the impact of air pollution perception on environmental governance satisfaction, as well as how this relationship is mediated by environmental tax and moderated by government trust. The findings reveal a strong inverse correlation between air pollution perception and satisfaction with environmental governance, highlighting the direct impact of environmental challenges on ESG outcomes. The relationship is nuanced by regional and demographic variations, highlighting the diverse impact of air pollution perception across different segments of society. The study also reveals the pivotal role of environmental tax in mediating this relationship, suggesting that tax policies can effectively enhance ESG strategies. Additionally, government trust is identified as a key moderating factor, underscoring the importance of trust in governance for the effectiveness of ESG practices. This research contributes to the broader field of air pollution perception and environmental governance, providing valuable insights into the complex interplay between public perception, tax policy, and trust in government. It offers practical implications for policymakers seeking to use taxation and trust-building measures to mitigate pollution and improve public satisfaction with environmental governance within the ESG ambit.

Abstract Background The aim of this study was to investigate the association between systemic immune‐inflammation index (SII) and all‐cause mortality in individuals with chronic kidney disease (CKD). Patients and Methods This prospective cohort study was carried out among 9303 participants with CKD from the National Health and Nutrition Examination Survey cycles spanning 1999 to 2018. The mortality data were ascertained by linking participant records to the National Death Index up to December 31, 2019. Complex sampling‐weighted multivariate Cox proportional hazards models were employed to estimate the association between SII level and all‐cause mortality, providing hazard ratios (HR) and 95% confidence intervals (CI). A restricted cubic spline analysis was conducted to explore potential nonlinear correlation. Subgroup analyses and sensitivity analyses were also conducted. Results During a median follow‐up period of 86 months, 3400 (36.54%) all‐cause deaths were documented. A distinctive “J”‐shaped relationship between SII level and all‐cause mortality was discerned among individuals with CKD, with the nadir observed at an SII level of 478.93 within the second quartile. After adjusting for potential covariates, the risk of all‐cause mortality escalated by 13% per increment of one standard deviation of SII, once SII exceeded 478.93 (HR = 1.13; 95% CI = 1.08–1.18). An elevated SII was associated with an increased risk of all‐cause mortality among patients with CKD (Q4 vs. Q2: HR = 1.23; 95% CI = 1.01–1.48). Subgroup analyses indicated that the correlation between SII and CKD mortality was particularly pronounced among participants over 60 years old and individuals with diabetes. Sensitivity analyses revealed a linear positive association between SII and all‐cause mortality after removing the extreme 5% outliers of SII. Conclusions A distinctive “J”‐shaped relationship between SII level and all‐cause mortality was identified among individuals with CKD. Further research is warranted to validate and expand upon these findings.

BackgroundIn light of the global effort to eradicate stunting in childhood, the objective of this research endeavor was to assess the prevalence of stunting and associated factors, simultaneously construct and validate a risk prediction model for stunting among children under the age of three in Shenzhen, China.MethodsUsing the stratified random sampling method, we selected 9,581 children under the age of three for research and analysis. The dataset underwent a random allocation into training and validation sets, adhering to a 8:2 split ratio. Within the training set, a combined approach of LASSO regression analysis and binary logistic regression analysis was implemented to identify and select the predictive variables for the model. Subsequently, model construction was conducted in the training set, encompassing model evaluation, visualization, and internal validation procedures. Finally, to assess the model's generalizability, external validation was performed using the validation set.ResultsA total of 684 (7.14%) had phenotypes of stunt. Utilizing a combined approach of LASSO regression and logistic regression, key predictors of stunting among children under three years of age were identified, including sex, age in months, mother's education, father's age, birth order, feeding patterns, delivery mode, average daily parent-child reading time, average time spent in child-parent interactions, and average daily outdoor time. These variables were subsequently employed to develop a comprehensive prediction model for childhood stunting. A nomogram model was constructed based on these factors, demonstrating excellent consistency and accuracy. Calibration curves validated the agreement between the nomogram predictions and actual observations. Furthermore, ROC and DCA analyses indicated the strong predictive performance of the nomograms.ConclusionsThe developed model for forecasting stunt risk, which integrates a spectrum of variables. This analytical framework presents actionable intelligence to medical professionals, laying down a foundational framework and a pivot for the conception and execution of preemptive strategies and therapeutic interventions.

Abstract. Background:. In the clinic, practitioners encounter many patients with an abnormal pattern of dense punctate magnetic resonance imaging (MRI) signal in the basal ganglia, a phenomenon known as "cheese sign". This sign is reported as common in cerebrovascular diseases, dementia, and old age. Recently, cheese sign has been speculated to consist of dense perivascular space (PVS). This study aimed to assess the lesion types of cheese sign and analyze the correlation between this sign and vascular disease risk factors. Methods:. A total of 812 patients from Peking Union Medical College Hospital (PUMCH) dementia cohort were enrolled. We analyzed the relationship between cheese sign and vascular risk. For assessing cheese sign and defining its degree, the abnormal punctate signals were classified into basal ganglia hyperintensity (BGH), PVS, lacunae/infarctions and microbleeds, and counted separately. Each type of lesion was rated on a four-level scale, and then the sum was calculated; this total was defined as the cheese sign score. Fazekas and Age-Related White Matter Changes (ARWMC) scores were used to evaluate the paraventricular, deep, and subcortical gray/white matter hyperintensities. Results:. A total of 118 patients (14.5%) in this dementia cohort were found to have cheese sign. Age (odds ratio [OR]: 1.090, 95% confidence interval [CI]: 1.064–1.120, P

Abstract Global financial systems are inherently fragile due to their complexities. Thus, it is of great interest to devise various methods to assess the dynamics of financial fragility. As such, this study builds a financial fragility evaluation index system. The study finds three major fluctuations in the trend of financial fragility due to the great recession in 2008, the huge financial volatility in 2015, and the COVID-19 pandemic in 2019. It also tests the index system on the Chinese finance market from 2007 to 2022. Observations of capital adequacy, non-performing loans, and liquidity ratios, in addition to the average return on total assets, are used to assess banking fragility. The results attained show that amongst the tested banks, the Bank of Ningbo has the lowest vulnerability score, mainly due to its higher average return on total assets, capital adequacy ratios, and lower non-performing loan ratio. On the other end of the spectrum, China Minsheng Bank has the highest vulnerability score due to its lower capital adequacy and higher non-performing loan ratios. These findings provide valuable insights into the banking sector in China for policy formulation.

Abstract The interest rate derivatives market is an important force in promoting the development of the bond market and is an effective tool to manage interest rate risk. The research on price discovery and volatility spillover of the market can help provide valuable reference information for investors. Based on treasury bond futures and interest rate swaps, the paper aims to discuss the price discovery function and spillover structure of the interest rate derivatives market. The paper establishes the information share model and spillover index model for empirical analysis. The results show that: First, the calculation results of the information share model show that the price discovery of treasury bond futures and interest rate swap markets is stronger than that of the spot market. Second, based on structural break analysis, treasury bond futures and interest rate swaps do not have breakpoints, while the treasury bond spot has three breakpoints. The paper divides the entire sample into four stages based on structural breakpoints and finds that the price discovery ability of the interest rate derivative market dynamically changed. Third, as a net spillover in the market, treasury bond futures have developed relatively stable. Both treasury bond futures and interest rate swaps have spillover effects on the spot market, indicating that China’s interest rate derivatives market can impact the treasury bond spot market.

Abstract The current challenge of wearable/implantable personal dosimeters for medical diagnosis and radiotherapy applications is lack of suitable detector materials possessing both excellent detection performance and biocompatibility. Here, we report a solution-grown biocompatible organic single crystalline semiconductor (OSCS), 4-Hydroxyphenylacetic acid (4HPA), achieving real-time spectral detection of charged particles with single-particle sensitivity. Along in-plane direction, two-dimensional anisotropic 4HPA exhibits a large electron drift velocity of 5 × 105 cm s−1 at “radiation-mode” while maintaining a high resistivity of (1.28 ± 0.003) × 1012 Ω·cm at “dark-mode” due to influence of dense π-π overlaps and high-energy L1 level. Therefore, 4HPA detectors exhibit the record spectra detection of charged particles among their organic counterparts, with energy resolution of 36%, (μt)e of (4.91 ± 0.07) × 10−5 cm2 V−1, and detection time down to 3 ms. These detectors also show high X-ray detection sensitivity of 16,612 μC Gyabs −1 cm−3, detection of limit of 20 nGyair s−1, and long-term stability after 690 Gyair irradiation.

Background Renal impairment has been previously linked to peripheral eosinophil count (PEC), prompting an investigation into its potential relationship with chronic kidney disease (CKD). This cross-sectional study utilized data from the National Health and Nutrition Examination Survey (NHANES 1999–2018) to comprehensively explore the association between PEC and CKD.Methods Survey-weighted generalized multivariate linear regression was employed to evaluate the associations between PEC, urinary albumin-to-creatinine ratio (UACR), and estimated glomerular filtration rate (eGFR), with meticulous adjustment for potential covariates. To assess non-linear correlations, a restricted cubic spline analysis was conducted. Sensitivity analysis was performed to test the stability of results.Results The study included a total of 9224 participants with non-dialysis CKD. In the multivariate linear regression model, after comprehensive adjustment for potential covariates, PEC showed a negative association with eGFR (β per 100 cells/uL increase in PEC, −0.71; 95% CI, −1.04, −0.37), while demonstrating a positive trend with UACR (β per 100 cells/uL increase in PEC, 10.21; 95% CI, 1.37, 19.06). The restrictive cubic spline curve analysis suggested that these associations occurred within the range of 0 to 400 cells/uL for PEC. Sensitivity analysis supported the stability of the observed results.Conclusions Circulating eosinophil levels are negatively correlated with eGFR and demonstrate a positive trend with UACR, when PEC falls within the range of less than 400 cells/uL among adults with CKD. Further research is warranted to validate these findings.

Presenilin-2 (PSEN2) mutation is one of the pathogenic factors of autosomal dominant early-onset Alzheimer's disease (EOAD). We generated a human induced pluripotent stem cell (iPSC) line from fibroblasts of an EOAD patient carrying PSEN2 mutation (c.716 T > C) utilizing Sendai reprogramming kit. The resulting iPSC line carried patient-specific point mutation, exhibited typical iPSC morphology, retained a normal karyotype, expressed pluripotency markers, and could form embryoid bodies. Established iPSC line serve as valuable resource for EOAD disease pathogenesis modelling and drug screening.

The edge computing utilizes vehicles as resources to assist in computational offloading can shorten the distance between users and computing servers, thereby improving the reliability of communication between them. In this paper, we investigate a Vehicle-assisted Edge Computing (VEC) model by jointly considering wireless access and backhaul links, and formulate an optimization problem that combines computational offloading and resource allocation, aiming at minimizing system delay. Further, the formulated problem is decomposed into two subproblems, e.g., computation offloading and resource allocation. In particular, we propose a new computational offloading approach that models the offloading decision for joint wireless access and backhaul as a potential game. The Nash equilibrium is guaranteed by the rational design of potential function, and the corresponding solution is solved by a backward induction method. On the other hand, the resource allocation subproblem is transformed from a nonconvex to a convex optimization problem based on equivalent transformation with successive convex approximation methods and finally derives the optimal solution satisfying Karush-Kuhn-Tucker (KKT) conditions. Simulation results show that the proposed algorithm have near-optimal performance and is superior to the state-of-the-art over a wide range of parameter settings.

Abstract Aim Atrial fibrillation (AF) is a progressive disease from paroxysmal to persistent, and persistent AF (PerAF) had worse prognosis. AF has potential link with inflammation, but it is not clear whether PerAF or paroxysmal AF (ParAF) is more closely related to inflammation. On the basis of inhibiting myocardial physiological uptake, 18F-fluorodeoxyglucosepositron emission tomography/computed tomography (18F-FDG PET/CT) is an established imaging modality to detect cardiac inflammation. We aimed to decipher the association between AF and atrial inflammatory activity by 18F-FDG PET/CT. Methods Thirty-five PerAF patients were compared to age and sex matched ParAF group with baseline 18F-FDG PET/CT scans prior to radiofrequency catheter ablation (RFCA) in the prospective case-control study. High-fat and low-carbohydrate diet and prolonged fast (HFLC+Fast) was applied to all AF patients before PET/CT. Then 22 AF patients with positive right atrial (RA) wall FDG uptake (HFLC+Fast) were randomly selected and underwent HFLC+Fast+heparin the next day. The CHA2DS2-VASc score was calculated to evaluate the risk of stroke. Clinical data, ECG, echocardiography, and atrial 18F-FDG uptake were compared. Results PerAF patients had significantly higher probability of RA wall positive FDG uptake and higher SUVmax than ParAF group [91.4% VS. 28.6%, P

Abstract Background The pediatric genetic white matter disorders are characterized by a broad disease spectrum. Genetic testing is valuable in the diagnosis. However, there are few studies on the clinical and genetic spectrum of Chinese pediatric genetic white matter disorders. Methods The participants were enrolled from the cohort of Peking Union Medical College Hospital. They all received history collection, brain MRI and gene sequencing. Their neurologic complaints which were related to white matter disorders occurred before 18. Brain MRI indicated periventricular and/or deep white matter lesions, fazekas grade 2–3. Results Among the 13 subjects, there were 11 males and two females. The average age of onset was 10.0 ± 5.5 years old. The potential genetic variants were found in 84.6% (11/13) subjects. The ABCD1 showed the greatest mutation frequency (30.8%, 4/13). The EIF2B3 A151fs, EIF2B4 c.885 + 2T > G, EIF2B5 R129X and MPV17 Q142X were novel pathogenic/likely pathogenic variants. 100% (4/4) ABCD1 carriers were accompanied by visual impairment, whereas 100% (3/3) EIF2B carriers developed dysuria. 100% (4/4) ABCD1 carriers exhibited diffuse white matter hyperintensities mainly in the posterior cortical regions, while the EIF2B4 and EIF2B5 carriers were accompanied by cystic degeneration. Conclusion There is genotypic and phenotypic heterogeneity among Chinese subjects with pediatric genetic white matter disorders. The knowledge of these clinical and genetic characteristics facilitates an accurate diagnosis of these diseases.

Abstract Background Breast cancer stem cells (BCSCs) are resistant to standard therapies, facilitate tumor dissemination, and contribute to relapse and progression. Super-enhancers are regulators of stemness, and BET proteins, which are critical for super-enhancer function, are a potential therapeutic target. Here, we investigated the effects of BET proteins on the regulation of breast cancer stemness using the pan-BET degrader ZBC260. Methods We evaluated the effect of ZBC260 on CSCs in TNBC cell lines. We assessed the effect of ZBC260 on cellular viability and tumor growth and measured its effects on cancer stemness. We used RNA sequencing and stemness index to determine the global transcriptomic changes in CSCs and bulk cells and further validated our findings by qPCR, western blot, and ELISA. Results ZBC260 potently inhibited TNBC growth both in vitro and in vivo. ZBC260 reduced stemness as measured by cell surface marker expression, ALDH activity, tumorsphere number, and stemness index while increasing differentiated cells. GSEA analysis indicated preferential downregulation of stemness-associated and inflammatory genes by ZBC260 in ALDH+ CSCs. Conclusions The BET degrader ZBC260 is an efficient degrader of BET proteins that suppresses tumor progression and decreases CSCs through the downregulation of inflammatory genes and pathways. Our findings support the further development of BET degraders alone and in combination with other therapeutics as CSC targeting agents.

Cancer continues to pose a significant threat to global health, with its status as a leading cause of death remaining unchallenged. Within the realm of cancer research, the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) stands out as a critical player, having been identified in the 1990s as the tenth member of the TNF family. This review examines the pivotal role of TRAIL in cancer biology, focusing on its ability to induce apoptosis in malignant cells through both endogenous and exogenous pathways. We provide an in-depth analysis of TRAIL’s intracellular signaling and intercellular communication, underscoring its potential as a selective anticancer agent. Additionally, the review explores TRAIL’s capacity to reshape the tumor microenvironment, thereby influencing cancer progression and response to therapy. With an eye towards future developments, we discuss the prospects of harnessing TRAIL’s capabilities for the creation of tailored, precision-based cancer treatments, aiming to enhance efficacy and improve patient survival rates.

Ferroptosis is a novel and iron-dependent form of programmed cell death, which has been implicated in the pathogenesis of various human cancers. EBV is a well-recognized oncogenic virus that controls multiple signaling pathways within the host cell, including ferroptosis signaling. Recent studies show that inducing ferroptosis could be an efficient therapeutic strategy for EBV-associated tumors. This review will firstly describe the mechanism of ferroptosis, then summarize EBV infection and EBV-associated tumors, as well as the crosstalk between EBV infection and the ferroptosis signaling pathway, and finally discuss the role and potential application of ferroptosis-related reagents in EBV-associated tumors.

In this study, different sugar alcohols (maltitol, erythritol, xylitol, sorbitol) were added to make low sugar orange sweet potato puree. The effects of different sugar alcohols on rheological properties, storage color, β-carotene content and digestive properties of orange sweet potato puree were investigated. The results showed that all samples were pseudoplastic fluid. After Power-law model fitting, maltitol and erythritol significantly reduced the viscosity of sweet potato puree (P

As a strong economic and populous province in China, Jiangsu is home to four endemic diseases. Despite efforts in the past decade, the prevention and control of these four endemic diseases are not uniform because of the different etiological chains and influencing factors of these diseases. Among the evaluation methodologies for endemic disease control, only one method is currently available for each disease. In this study, we selected 14 indicators to comprehensively evaluate the effectiveness of endemic disease control in Jiangsu between 2013 and 2022. We improved the method for calculating the weights of the indicators and established a fuzzy comprehensive evaluation model based on the weighted Technique for Order Preference by Similarity to an Ideal Solution model and a weighted grey relational analysis model. The results of the comprehensive evaluation showed that the progress of endemic disease control in Jiangsu was not always in line with our expectations of improvement, with the top five years of better control occurring in 2015, 2013, 2021, 2022, and 2014. The results of the sensitivity analysis confirm the reliability and accuracy of these findings. We discovered that measures such as the reform of the salt industry, use of thyroid ultrasound, and new water supply projects for residents in Jiangsu affected the progress of endemic disease prevention and control. The tracking of endemic disease status should consider the potential effects of changes in policies implemented in other industries on endemic disease prevention and control. Additionally, the results of this study provide a theoretical basis for enhancing prevention and control practices in other regions of China.

As one of the most commonly used metal cutting machines in modern manufacturing industry, the drilling and tapping center machine tool has an irreplaceable position in modern manufacturing industry due to its high operating speed and fast tool changing speed. However, in the process of machining, the thermal deformation of the x-axis lead screw is caused due to the changes of the ambient end temperature, the wire mother end temperature and the bearing temperature of the motor seat end, resulting in the error of the workpiece. In this paper, through the above three kinds of thermal deformation simulation and experimental data measurement, and then through the analysis and modeling of the experimental data by MATLAB, a scheme of real-time compensation for the thermal error of the x-axis lead screw is proposed. After the compensation, the products produced by an enterprise are verified. The verification results show that the accuracy after the compensation can be improved by 56.25% compared with that before the compensation.

ObjectiveTo investigate the relationship between the perpetrator’s sex, victim’s position and slashing location as well as anthropometric parameters on distance and space required for slashing, to provide the theoretical basis for the judgment of whether the crime scene was consistent with the criminal activity space.MethodsThe kinematics data of 12 male and 12 female subjects slashing the neck of standing and supine mannequins as well as the chest of the standing mannequins with a kitchen knife were obtained by using a 3D motion capture system. The relationship between the perpetrator’s sex-victim’s position, the perpetrator’s sex-slashing location, and anthropometric parameters and the distance and space required for the slashing were analyzed by two-factor repeated measures ANOVA and Pearson correlation analysis respectively.ResultsCompared with slashing the neck of supine mannequins, the distance （L） and normalized L （l） of slashing the neck of standing mannequins were greater, while vertical distance （LVR） and normalized LVR （lVR） of the knife side were smaller. Compared with slashing the neck of standing mannequins, the L and l slashing the chest of standing mannequins were greater, while LVR and lVR were smaller. Horizontal distance （LHR） and normalized LHR （lHR） of the knife side in males were greater than that in females. Height and arm length were positively correlated with L, LHR, and LVR when striking the standing mannequins.ConclusionWhen slashing the neck of supine or standing victims, the slashing distance is shorter and the slashing height is greater. Furthermore, the distance and space required for slashing are correlate with anthropometric parameters.

In view of the increasing number of power grid equipment and a large number of indoor deployments, the existing positioning technology cannot meet the requirements. In this paper, a DOA estimation method based on deep learning is proposed to improve the indoor positioning accuracy. Firstly, by studying the propagation characteristics of wireless signals and the transmission characteristics of indoor wireless channels, a statistical channel model with multi subcarrier characteristics is established to generate channel impulse response information. Furthermore, the transformation matrix required for virtual antenna expansion is designed by using the idea of interpolation transformation. This matrix is combined with the channel impulse response to obtain the virtual antenna array data for DOA estimation. The DOA estimation model based on CNN is optimized to obtain high-precision DOA. Finally, the simulation results show that the positioning accuracy can be doubled by using the virtual antenna array technology. The performance of the two-stage DOA estimation algorithm proposed in this paper is slightly better than the accuracy of a large difference step. Even when there are fewer APS, the positioning accuracy is better than the traditional MUSIC algorithm, which is more suitable for indoor positioning of a large number of power grid equipment in the future.

Abstract High‐grade meningioma has an unsatisfactory outcome despite surgery and postoperative radiotherapy; however, the factors driving its malignancy and recurrence remain largely unknown, which limits the development of systemic treatments. Single‐cell RNA sequencing (scRNA‐Seq) technology is a powerful tool for studying intratumoral cellular heterogeneity and revealing the roles of various cell types in oncogenesis. In this study, scRNA‐Seq is used to identify a unique initiating cell subpopulation (SULT1E1+) in high‐grade meningiomas. This subpopulation modulates the polarization of M2‐type macrophages and promotes meningioma progression and recurrence. A novel patient‐derived meningioma organoid (MO) model is established to characterize this unique subpopulation. The resulting MOs fully retain the aggressiveness of SULT1E1+ and exhibit invasiveness in the brain after orthotopic transplantation. By targeting SULT1E1+ in MOs, the synthetic compound SRT1720 is identified as a potential agent for systemic treatment and radiation sensitization. These findings shed light on the mechanism underlying the malignancy of high‐grade meningiomas and provide a novel therapeutic target for refractory high‐grade meningioma.

Welded joints in metallic pipelines and other structures are used to connect metallic structures. Welding defects, such as cracks and lack of fusion, are vulnerable to initiating early-age cracking and corrosion. The present damage identification techniques use ultrasonic-guided wave procedures, which depend on the change in the physical characteristics of waveforms as they propagate to determine damage states. However, the complexity of geometry and material discontinuity (e.g., the roughness of a weldment with or without defects) could lead to complicated wave reflection and scatters, thus increasing the difficulty in the signal processing. Artificial intelligence and machine learning exhibit their capability for data fusion, including processing signals originally from ultrasonic-guided waves. This study aims to utilize deep learning approaches, including a convolutional neural network (CNN), Long-short term memory network (LSTM), or hybrid CNN-LSTM model, to demonstrate the capability in automation for damage detection for pipes with welded joints embedded in soil. The damage features in terms of welding defect types and severity as well as multiple defects are used to understand the effectiveness of the hybrid CNN-LSTM model, which is further compared to the two commonly used deep learning approaches, CNN and LSTM. The results showed the hybrid CNN-LSTM model has much higher classification accuracy for damage states under all scenarios in comparison with the CNN and LSTM models. Furthermore, the impacts of the pipelines embedded in different types of materials, ranging from loose sand to stiff soil, on signal processing and data classification were further calibrated. The results demonstrated these deep learning approaches can still perform well to detect various pipeline damage under varying embedment conditions. However, the results demonstrate when concrete is used as an embedding material, high attention to absorbing the signal energy of concrete could pose a challenge for the signal processing, particularly under high noise levels.

ABSTRACT Aims/Introduction Sleep problems are important public health concern worldwide. We carried out a meta‐analysis to quantitatively evaluate whether sleep duration was associated with pregnancy outcomes, and the associations were modified by important characteristics of studies. Materials and Methods Based on PubMed, Embase and the Cochrane Central Register of Controlled Trials databases, we searched for published literature related to maternal sleep duration and adverse pregnancy outcomes before 30 June 2021. We carried out risk of bias assessment, subgroup analyses and sensitivity analysis. The relative risks or odds ratios with 95% confidence intervals (CI) were used to estimate the pooled effects. Results A total of 5,246 references were identified through a database search, and 41 studies were included in the study. Pregnant women with short sleep duration had 1.81‐fold (95% CI 1.35–2.44, P 0.05). Furthermore, long sleep duration was significantly correlated with gestational diabetes mellitus (odds ratio1.24. 95% CI 1.12–1.36, P 0.05). Conclusions Short/long sleep duration appeared to be associated with adverse pregnancy outcomes, specifically with an increased risk of gestational diabetes mellitus. Sleep should be systematically screened in the obstetric population.

Objective: To improve the availability of cherry seed, cherry seed oil was extracted by the aqueous enzymatic method. Methods: the ratio of mixed enzymes was optimized by mixture design on the basis of single factor experiment. The basic indexes of oil such as fatty acid composition and physical and chemical properties were detected. Results: the optimum extraction conditions were a 2.0% addition of mixed enzyme comprising cellulase, pectinase and acid protease （0.67∶0.10∶0.23）, liquid to material ratio of 10∶1 (mL/g), enzymolysis temperature of 45 ℃, pH of 4.0 and time of 4.0 h. The recovery of oil was 93.18% and the actual extraction rate was 28.66%. The oil from aqueous enzymatic technology was rich in oleic acid and linoleic acid, with the color of oil light-colored and transparent. Acid value and peroxide value conformed to the hygiene standard for edible vegetable oil. Conclusion: The mixture design assisted aqueous enzymatic extraction of cherry seed oil is feasible.

BackgroundApolipoprotein-E (APOE) ε4 is a major genetic risk factor for Alzheimer’s disease (AD). Current studies, which were mainly based on the clinical diagnosis rather than biomarkers, come to inconsistent conclusions regarding the associations of APOE ε4 homozygotes (APOE ε4/ε4) and cerebrospinal fluid (CSF) biomarkers of AD. In addition, few studies have explored the associations of APOE ε4/ε4 with plasma biomarkers. Therefore, we aimed to investigate the associations of APOE ε4/ε4 with fluid biomarkers in dementia and biomarker-diagnosed AD.MethodsA total of 297 patients were enrolled. They were classified into Alzheimer’s continuum, AD, and non-AD, according to CSF biomarkers and/or β amyloid PET results. AD was a subgroup of the AD continuum. Plasma Amyloid β (Aβ) 40, Aβ42, glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), and phosphorylated tau (P-tau)181 were quantified in 144 of the total population using an ultra-sensitive Simoa technology. We analyzed the associations of APOE ε4/ε4 on CSF and plasma biomarkers in dementia and biomarker diagnosed AD.ResultsBased on the biomarker diagnostic criteria, 169 participants were diagnosed with Alzheimer’s continuum and 128 individuals with non-AD, and among the former, 120 patients with AD. The APOE ε4/ε4 frequencies were 11.8% (20/169), 14.2% (17/120), and 0.8% (1/128) in Alzheimer’s continuum, AD and non-AD, respectively. Only CSF Aβ42 was shown to be decreased in APOE ε4/ε4 carriers than in non-carriers for patients with AD (p = 0.024). Furthermore, we did not find any associations of APOE ε4 with plasma biomarkers of AD and non-AD. Interestingly, we found that in non-AD patients, APOE ε4 carriers had lower CSF Aβ42 (p = 0.018) and higher T-tau/Aβ42 ratios (p

Abstract Fluorescence photoswitch is becoming increasingly desirable for many applications, but its controllable fabrication still remains challenging yet. In this paper, a new strategy is proposed to fabricate fluorescence photoswitch by harnessing dual roles of albumin proteins as both photochrome carriers and biotemplates of fluorophore. As an example, we demonstrated the successful fabrication of a fluorescence photoswitch by incorporating both the photochromic diarylethene dye (CMTE) and red‐emitting fluorescent gold nanoclusters (AuNCs) into the specific domains of bovine serum albumin (BSA) in a highly controllable manner. Detailed spectral and photophysical characterisation showed that CMTE well‐retains the photochromic properties within the CMTE–BSA–AuNC construct, although its photoconversion rate is slightly retarded. Different from previously reported photoswitches, the fluorescence of the present system is mainly modulated via the inner filter effect (IFE) mechanism, which exhibits high switching efficiency with an on–off ratio up to 90%, reversible fluorescence response and good antifatigue performance. This work provides a new, generable albumin protein‐assisted strategy of fabricating advanced fluorescence photoswitch, which can find wide applications in biological, optical and information fields.

ABSTRACT Pleurotus ostreatus is usually cultivated in horticultural facilities that lack environmental control systems and often suffer heat stress (HS). Salicylic acid (SA) is recognized as a plant defense-related hormone. Here, SA treatment (200 μM) induced fungal resistance to HS of P. ostreatus, with decreased malondialdehyde (MDA) content and HSP expression. Further analysis showed that SA treatment in P. ostreatus increased the cytosolic trehalose content and reduced the intracellular reactive oxygen species (ROS) level. Moreover, H2O2 could restore the MDA content and HSP expression of P. ostreatus treated with SA under HS. In addition, trehalose (25 mM) or CaCl2 (5 mM) treatment induced fungal resistance to HS, and CaCl2 treatment increased the cytosolic trehalose content of P. ostreatus under HS. However, inhibiting Ca2+ levels using Ca2+ inhibitors or mutants reversed the trehalose content induced by SA in P. ostreatus under HS. In addition, inhibiting trehalose biosynthesis using Tps-silenced strains reversed the MDA content and HSP expression of P. ostreatus treated with SA under HS. Taken together, these results indicate that SA treatment alleviates the HS response of P. ostreatus by reducing the intracellular ROS level and increasing the cytosolic trehalose content. IMPORTANCE Heat stress (HS) is a crucial environmental challenge for edible fungi. Salicylic acid (SA), a plant defense-related hormone, plays key roles in plant responses to biotic and abiotic stresses. In this study, we found that SA treatment increased the cytosolic trehalose content and induced fungal resistance to HS in P. ostreatus. Further analysis showed that SA can alleviate the HS of P. ostreatus by reducing the intracellular ROS level and increasing the cytosolic trehalose content. Our results help to understand the mechanism underlying the responses of P. ostreatus to HS. In addition, this research provides new insights for the cultivation of P. ostreatus.

The ultrasonic guided lamb wave approach is an effective non-destructive testing (NDT) method used for detecting localized mechanical damage, corrosion, and welding defects in metallic pipelines. The signal processing of guided waves is often challenging due to the complexity of the operational conditions and environment in the pipelines. Machine learning approaches in recent years, including convolutional neural networks (CNN) and long short-term memory (LSTM), have exhibited their advantages to overcome these challenges for the signal processing and data classification of complex systems, thus showing great potential for damage detection in critical oil/gas pipeline structures. In this study, a CNN-LSTM hybrid model was utilized for decoding ultrasonic guided waves for damage detection in metallic pipelines, and twenty-nine features were extracted as input to classify different types of defects in metallic pipes. The prediction capacity of the CNN-LSTM model was assessed by comparing it to those of CNN and LSTM. The results demonstrated that the CNN-LSTM hybrid model exhibited much higher accuracy, reaching 94.8%, as compared to CNN and LSTM. Interestingly, the results also revealed that predetermined features, including the time, frequency, and time–frequency domains, could significantly improve the robustness of deep learning approaches, even though deep learning approaches are often believed to include automated feature extraction, without hand-crafted steps as in shallow learning. Furthermore, the CNN-LSTM model displayed higher performance when the noise level was relatively low (e.g., SNR = 9 or higher), as compared to the other two models, but its prediction dropped gradually with the increase of the noise.

Cash holding is an important strategic decision of enterprises. As a macro-level factor, economic policy uncertainty causes risks, affecting enterprises' cash holdings. Taking the quarterly financial data of China's A-share non-financial listed firms for 2010-2020 as a sample, this study adopts the OLS and fixed effect models to investigate how corporate cash holdings are affected by economic policy uncertainty. The findings indicate that economic policy uncertainty is directly proportional to the level of cash that listed corporations hold. The higher the uncertainty, the more cash the company holds. Among them, state-owned enterprises and the manufacturing industry are more significantly affected by economic policy uncertainty. Finally, considering the regional marketization level and the differences in financing constraints enterprises face, it is concluded through grouping empirical studies that enterprises located in regions with lower marketization levels are more susceptible to policy uncertainty, while financially constrained enterprises are more susceptible to economic policy uncertainty. The study of economic policy uncertainty is helpful to guide enterprises to realize the importance of coping strategies in advance under the background of intensifying economic policy uncertainty. Therefore, this paper proposes to introduce policies on the premise of fully considering the smoothness of the economy and the differences in the conditions of firms of different natures, as well as some proposals to alleviate financing constraints, reduce the adverse effects of uncertainty on firms, and bolster the marketization process.

Abstract Programmable smart materials that can respond locally to specific stimuli hold great potential for many applications, but controllable fabrication of these materials remains challenging. This work reports the development of novel programmable anisotropic materials with both magnetic and photothermal stimuli‐responsiveness, which are fabricated by anchoring thermosensitive poly(N‐isopropyl acrylamide) (PNIPAm) and magnetic Fe3O4 nanoparticles on the surface of MoS2 nanosheets. Further embedding PNIPAm‐MoS2/Fe3O4 into 3D‐printed hydrogel cubes results in stimuli‐responsive building blocks, and the magnetic field can precisely control their orientation and near‐infrared (NIR) light absorbing property. Particularly, the variation of the orientation of MoS2/Fe3O4 block results in obvious changes of their photothermal efficiency and optical property. By exploiting the anisotropy of MoS2/Fe3O4 and their NIR light responsiveness, thermally‐induced phase transitions in individual 3D printed hydrogel building block can be locally controlled for magnetic field‐assisted programming a quick response (QR) code. Alternatively, fluorescent QR code with high contrast and security level can be achieved by photothermal‐induced release of fluorescent dyes. These 3D printed magnetically programmed hydrogels hold great potential for application in information storage, intelligent materials, and precise therapy.

Abstract Background The incidence of endometrial cancer has tended to increase in recent years. However, competing risk nomogram combining comprehensive factors for endometrial cancer patients treated with hysterectomy is still scarce. Therefore, we aimed to build a competing risk nomogram predicting cancer‐specific mortality for endometrial cancer patients treated with hysterectomy. Methods Patients diagnosed with endometrial cancer between 2010 and 2012 were abstracted from the Surveillance, Epidemiology, and End Results (SEER) database. Competing risk model was performed to select prognostic variables to build the competing risk nomogram to predict the cumulative 3‐ and 5‐year incidences of endometrial cancer‐specific mortality. Harrell's C‐index, receiver operating characteristic (ROC) curve, and calibration plot were used in the internal validation. And decision curve analysis was applied to evaluate clinical utility. Results A total of 10,447 patients were selected for analysis. The competing risk nomogram identified eight prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, and number of regional nodes positive. The C‐index of the competing risk nomogram was 0.857 (95% confidence interval [CI]: 0.854–0.859), and the calibration plots were adequately fitted. When the threshold probabilities were between 1% and 57% for 3‐year prediction and between 2% and 67% for 5‐year prediction, the competing risk nomogram was of good clinical utility. Conclusions A competing risk nomogram for endometrial cancer patients treated with hysterectomy was successfully built and internally validated. It was an accurately predicted and clinical useful tool, which could play an important role in consulting and health care management of endometrial cancer patients.

BackgroundRecent data indicate the importance of gut-kidney axis in the pathogenesis of Immunoglobulin A nephropathy (IgAN). Growing evidence suggests the alterations of diversity and composition of gut microbiome among patients with IgAN, however, the details are not yet fully understood.MethodsEligible studies comparing the gut microbiome between patients with IgAN and non-IgAN individuals were systematically searched from PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, and ClinicalTrials.gov. The primary outcomes were alpha- and beta-diversity, and the differences in gut microbiota composition between patients with IgAN and non-IgAN persons. Qualitative analysis and meta-analysis were performed according to available data.ResultsEleven cross-sectional studies, including 409 patients with IgAN and 243 healthy controls, were enrolled. No significant differences in the diversity and enrichment of gut bacteria were found between IgAN and healthy individuals, whereas the beta-diversity consistently showed significant microbial dissimilarities among the two groups. Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Fusobacteria, and Verrucomicrobia were the dominant phyla, however, no significant differences were found between IgAN patients and healthy controls at the phylum level. The genera, Streptococcus and Paraprevotella showed a higher proportion in patients with IgAN compared to healthy individuals, whereas Fusicatenibacter showed a lower abundance according to meta-analysis. Qualitative analyses suggested that Escherichia-Shigella might be increased in IgAN patients; the genera, Clostridium, Prevotella 9,and Roseburia, members of Ruminococcaceae and Lachnospiraceae families, were likely to have decreased abundances in patients with IgAN compared to healthy individuals.ConclusionGut microbiota dysbiosis was demonstrated in IgAN, which might be involved in the pathogenesis of IgAN. Further studies are needed to confirm the findings of this study, due to the substantial heterogeneity.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/, identifier PROSPERO (CRD42022304034).

Climate change and urban heat island effects affect the energy consumption of buildings in urban heat islands. In order to meet the requirements of engineering applications for detailed daily design parameters for air conditioning, the 15-year summer meteorological data for Beijing and Shanghai and the corresponding average heat island intensity data were analyzed. Using the CRITIC objective weighting method and K-means clustering analysis, the hourly change coefficient, β, of dry bulb temperature was calculated, and the LSTM algorithm was used to predict the changing trends in β. Finally, the air conditioning load model for a hospital was established using DeST (version DeST3.0 1.0.2107.14 20220712) software, and the air conditioning cooling load in summer was calculated and predicted. The results show that, compared with the original design days, regional differences in the new design days are more obvious, the maximum temperature and time have changed, and the design days parameters are more consistent with the local meteorological conditions. Design day temperatures in Shanghai are expected to continue rising for some time to come, while those in Beijing are expected to gradually return to previous levels. Among hospital buildings, the cooling load of outpatient buildings in Beijing and Shanghai will decrease by 0.69% and increase by 12.61% and by 12.12% and 15.51%, respectively, under the influence of the heat island effect. It is predicted to decrease by 1.35% and increase by 29.75%, respectively, in future. The cooling load of inpatient buildings in Beijing and Shanghai increased by 0.27% and 6.71%, respectively, and increased by 7.13% and 8.09%, respectively, under the influence of the heat island effect, and is predicted to decrease by 0.93% and increase by 16.07%, respectively, in future.

Petroleum has become a strategic resource to the national economy, and forecasting its demand is a critical step to supporting energy planning and policy-making for carbon reduction. We first conducted a characteristic analysis of end consumption for petroleum products, and the key affecting factors are identified through an extended logarithmic mean Divisia index (LMDI) method. Afterwards, the long-range energy alternatives planning system (LEAP) was adopted to predict the petroleum products demand by considering the potential impacts of different policies on the identified key factors. Through comparative analysis of three scenarios including five sub-scenarios, the findings show that the dual carbon constraints are crucial to petroleum demand control. Under the enforcement of existing carbon peaking policies, the petroleum products demand will peak around 2043 at 731.5 million tons, and the impact of energy intensity-related policies is more significant than that of activity level. However, even if the existing policy efforts are continued, supporting the carbon-neutral target will not be easy. By further strengthening the constraints, the demand will peak around 2027 at 680 million tons, and the abatement contribution will come mainly from industry (manufacturing), construction, and transportation. Additional abatement technologies are necessary for the petroleum industry to achieve carbon neutrality.

Abstract Background Most studies have shown that maternal age is associated with birth weight. However, the specific relationship between each additional year of maternal age and birth weight remains unclear. The study aimed to analyze the specific association between maternal age and birth weight. Methods Raw data for all live births from 2015 to 2018 were obtained from the Medical Birth Registry of Xi’an, China. A total of 490,143 mother-child pairs with full-term singleton live births and the maternal age ranging from 20 to 40 years old were included in our study. Birth weight, gestational age, neonatal birth date, maternal birth date, residence and ethnicity were collected. Generalized additive model and two-piece wise linear regression model were used to analyze the specific relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia. Results The relationships between maternal age and birth weight, risk of low birth weight, and risk of macrosomia were nonlinear. Birth weight increased 16.204 g per year when maternal age was less than 24 years old (95%CI: 14.323, 18.086), and increased 12.051 g per year when maternal age ranged from 24 to 34 years old (95%CI: 11.609, 12.493), then decreased 0.824 g per year (95% CI: -3.112, 1.464). The risk of low birth weight decreased with the increase of maternal age until 36 years old (OR = 0.917, 95%CI: 0.903, 0.932 when maternal age was younger than 27 years old; OR = 0.965, 95%CI: 0.955, 0.976 when maternal age ranged from 27 to 36 years old), then increased when maternal age was older than 36 years old (OR = 1.133, 95%CI: 1.026, 1.250). The risk of macrosomia increased with the increase of maternal age (OR = 1.102, 95%CI: 1.075, 1.129 when maternal age was younger than 24 years old; OR = 1.065, 95%CI: 1.060, 1.071 when maternal age ranged from 24 to 33 years old; OR = 1.029, 95%CI: 1.012, 1.046 when maternal age was older than 33 years old). Conclusions For women of childbearing age (20–40 years old), the threshold of maternal age on low birth weight was 36 years old, and the risk of macrosomia increased with the increase of maternal age.

Abstract Background Cervical cancer has long been a common malignance troubling women. However, there are few studies developing nomogram with comprehensive factors for the prognosis of cervical cancer. Hence, we aimed to build a nomogram to calculate the overall survival (OS) probability in patients with cervical cancer. Methods Data of 9876 female patients in SEER database and diagnosed as cervical cancer during 2010–2015, was retrospectively analyzed. Univariate and multivariate Cox proportional hazard regression model were applied to select predicted factors and a nomogram was developed to visualize the prediction model. The nomogram was compared with the FIGO stage prediction model. Harrell’s C-index, receiver operating curve, calibration plot and decision curve analysis were used to assess the discrimination, accuracy, calibration and clinical utility of the prediction models. Result Eleven independent prognostic variables, including age at diagnosis, race, marital status at diagnosis, grade, histology, tumor size, FIGO stage, primary site surgery, regional lymph node surgery, radiotherapy and chemotherapy, were used to build the nomogram. The C-index of the nomogram was 0.826 (95% CI: 0.818 to 0.834), which was better than that of the FIGO stage prediction model (C-index: 0.785, 95% CI: 0.776 to 0.793). Calibration plot of the nomogram was well fitted in 3-year overall OS prediction, but overfitting in 5-year OS prediction. The net benefit of the nomogram was higher than the FIGO prediction model. Conclusion A clinical useful nomogram for calculating the overall survival probability in cervical cancer patients was developed. It performed better than the FIGO stage prediction model and could help clinicians to choose optimal treatments and precisely predict prognosis in clinical care and research.

In higher plants, vacuolar invertases play essential roles in sugar metabolism, organ development, and sink strength. In sorghum (Sorghum bicolor), two vacuolar invertase genes, SbVIN1 (Sobic. 004G004800) and SbVIN2 (Sobic. 006G160700) have been reported, but their enzymatic properties and functional differences are largely unknown. We combined molecular, biochemical and genomic approaches to investigate their roles in sorghum stem and grain traits. SbVIN1 and SbVIN2 showed different expression levels in internodes, leaves, and panicles, indicating that their importance in each organ was different. In an in vitro sucrose hydrolysis assay, proteins of both genes heterologously expressed in Pichia pastoris displayed similar enzyme properties including the same optimum reaction pH (5) and similar Km for sucroe (49 mmol L−1 and 45 mmol L−1 for SbVIN1 and SbVIN2, respectively). The optimum reaction temperatures of SbVIN1 and SbVIN2 were 45 °C and 65 °C, respectively. SbVIN2 showed higher tolerance to high temperature than SbVIN1. We characterized the sequence variation of these two vacuolar invertase genes in a panel of 216 diverse inbred lines of sweet and grain sorghum and performed gene-based association analysis. SbVIN1 showed significant associations with stem traits including stem length, stem diameter, internode number, stem fresh weight, and Brix, as well as grain traits including hundred-grain weight and grain width. Significantly associated variation sites were mainly in 5′ upstream and intron regions. SbVIN2 only associated with grain width and stem water-soluble carbohydrates (WSCs) content. We conclude that the vacuolar invertase genes SbVIN1 and SbVIN2 are differently associated with stem and grain traits in sorghum. Keywords: Sorghum (Sorghum bicolor), Vacuolar invertase, SbVIN1, SbVIN2, Enzymatic properties, Association analysis

Nan Yao Shen Xiao (《南药神效》Miraculous Vietnamese Medicine) is “an ancient Vietnamese medical book in Chinese language” that is extant in Vietnam and plays an important part in Vietnamese medical development history. In the chapter of “Pestilences,” the characteristics, prevention, and treatment of pestilences were described in detail. By comparing Miraculous Vietnamese Medicine with Chinese medical books including Ben Cao Gang Mu (《本草纲目》Compendium of Materia Medica), it can be seen that the prevention and treatment of pestilences were profoundly influenced by Chinese medical books. The folk-proven prescriptions in Compendium of Materia Medica, Zhou Hou Bei Ji Fang (《肘后备急方》Handbook of Prescriptions for Emergency), Bei Ji Qian Jin Yao Fang (《备急千金要方》Important Prescriptions Worth a Thousand Gold for Emergency), and other Chinese medical books were included directly or after adaptation (slight modification in dosage and usage) in Miraculous Vietnamese Medicine. This form of “foreign acceptance” witnessed the history of medical culture communication between China and Vietnam, expanded the application scope of Chinese medicine in prevention and treatment of pestilences in a foreign land, promoted the overseas spread of folk-proven prescriptions in Chinese medicine to treat pestilences, and played a major part in treatment and prevention of disease in ancient Vietnam.

Abstract Background Maternal exposure to air pollution is related to fetal dysplasia. However, the association between maternal exposure to air pollution and the risk of congenital hypothyroidism (CH) in the offspring is largely unknown. Methods We conducted a national database based study in China to explore the association between these two parameters. The incidence of CH was collected from October 1, 2014 to October 1, 2015 from the Chinese Maternal and Child Health Surveillance Network. Considering that total period of pregnancy and consequently the total period of particle exposure is approximately 10 months, average exposure levels of PM2.5, PM10 and Air Quality Index (AQI) were collected from January 1, 2014 to January 1, 2015. Generalized additive model was used to evaluate the association between air pollution and the incidence of CH, and constructing receiver operating characteristic (ROC) curve was used to calculate the cut-off value. Results The overall incidence of CH was 4.31 per 10,000 screened newborns in China from October 1, 2014 to October 1, 2015. For every increase of 1 μg/m3 in the PM2.5 exposure during gestation could increase the risk of CH (adjusted OR = 1.016 per 1 μg/m3 change, 95% CI, 1.001–1.031). But no significant associations were found with regard to PM10 (adjusted OR = 1.009, 95% CI, 0.996–1.018) or AQI (adjusted OR = 1.012, 95% CI,0.998–1.026) and the risk of CH in the offspring. The cut-off value of prenatal PM2.5 exposure for predicting the risk of CH in the offspring was 61.165 μg/m3. Conclusions The present study suggested that maternal exposure to PM2.5 may exhibit a positive association with increased risk of CH in the offspring. We also proposed a cut-off value of PM2.5 exposure that might determine reduction in the risk of CH in the offspring in highly polluted areas.

The global regulator LaeA plays crucial roles in morphological development and secondary metabolite biosynthesis in filamentous fungi. However, the functions of LaeA in basidiomycetes are less reported. The basidiomycete Pleurotus ostreatus is a well-known fungus used both in medicine and as food that produces polysaccharides and cellulolytic enzymes. In this study, we characterized three LaeA homologs (PoLaeA1, PoLaeA2, and PoLaeA3) in P. ostreatus. PoLaeA1 showed different expression patterns than PoLaeA2 and PoLaeA3 during different developmental stages. Silencing PoLaeA1 decreased the intracellular polysaccharide (IPS) content by approximately 28–30% and reduced intracellular ROS levels compared with those of the WT strain. However, silencing PoLaeA2 and PoLaeA3 decreased cellulase activity by 31–34% and 35–40%, respectively, and reduced the cytosolic Ca2+ content, compared with those of the WT strain. Further analysis showed that PoLaeA1 regulated IPS biosynthesis through intracellular ROS levels, whereas PoLaeA2 and PoLaeA3 regulated cellulase activity through intracellular Ca2+ signaling. Our results provide new insights into the regulation of polysaccharide biosynthesis and cellulase production in filamentous fungi.

Background: This study investigated the impact of socio-economic factors on the spread and outbreak of COVID-19 based on Chinese data. Methods: Cumulative confirmed cases were collected and divided into the First-stage cases cluster dominated by imported cases, and the Second-stage cases cluster dominated by secondary cases, according to the time of emergency state and Wuhan city lockdown. The linear regression was used for data analysis. Results: A total of 12,877 cases in 30 provinces were analyzed in the study. The First-stage cases cluster included 675 cases and Second-stage cases cluster included 12,202 cases. The socio-economic factors were significantly associated with the cases (P0, P0, P

Abstract Background There was a wider disparity in the diet characterization among most studies on diet and pregnancy outcomes in different countries, and the research in northern China is limited. Therefore, the purpose of the present study that was conducted in northwest China was to understand the dietary characteristics of periconceptional women and to explore the relationship between and specific dietary patterns with adverse pregnancy outcomes. Methods A nested case-control study was conducted from October 2017 to November 2018 in Shaanxi, China. Based on a prospective cohort of 368 women who were pregnant or prepared for pregnancy, 63 participants who developed the outcomes of gestational hypertension, gestational diabetes, preterm birth, low birth weight, and birth defects were included in the case group. A total of 237 healthy pregnant women were included during the same period in the control group. Dietary intake was assessed using a validated food frequency questionnaire for the three months before pregnancy and the first trimester. Information on delivery details and antenatal pregnancy complications was obtained from the hospital maternity records. Dietary patterns were derived using factor analysis. Stratified analysis was performed on the overall, single and multiple adverse pregnancy outcomes categories. Adjustment was made for sociodemographic characteristics and nutritional supplement status. Results Six major dietary patterns were identified. The ‘starchy’ dietary pattern, composed of high intake in noodle and flour products and/or rice and its products, was associated with the odds of developing of adverse pregnancy outcomes (OR: 2.324, 95% CI: 1.293–4.178). This risk remained significant following adjustment for potential confounders of maternal demographic characteristics and nutritional status (aOR: 2.337, 95% CI:1.253–4.331). Strong association were found during the first trimester of pregnancy, but showed no association during the three months before pregnancy (aOR:1.473, 95% CI: 0.682–3.234). Conclusions High starchy food intake was associated with adverse pregnancy outcomes, particularly during the first trimester of pregnancy. Health education focusing on periconceptional dietary patterns could be a practical strategy for preventing adverse pregnancy outcomes.

Abstract Background Identifying and understanding the knowledge, attitude and practice (KAP) level of women at the periconceptional period has implications for formulating and measuring the adverse pregnancy outcomes for primary prevention. Methods A cross-sectional study among pregestational and pregnant women was conducted in Shaanxi during 2016–2017. Results Among 791 participants, the average score of periconceptional healthcare knowledge awareness was 6.32 ± 1.78, whereas 28.8% of women have failed. Women who planned to or had undergone premarital and pre-pregnancy examinations accounted for 50.2, and 62.5%, respectively. Less than half (42.0%) of the women started taking folic acid (FA) before pregnancy, and only 37.9% of them took FA regularly at the right time. Multivariate analysis showed that age was the main factor influencing the Attitude and Practice level of women at the periconceptional period, and demonstrated a positive effect on the awareness of right timing of folic acid supplementation, and high rates of premarital and pre-pregnancy examinations. Also, the knowledge pass rate was increased with education level. Fewer women who have birth experience were willing to take FA consistently at the right time compared to those women without birth. Conclusions The women at the periconceptional period in Shaanxi lacked the total KAP level of periconceptional healthcare, especially those who live in rural areas and have less education. Government agencies should reinforce more effective primary preventive measures and policies for the prevention of adverse pregnancy outcomes.