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The absence of a Mn local moment was observed in Mn-doped amorphous silicon (a- Mnx Si1-x) films. The magnetic susceptibility obeys the Curie-Weiss law for a wide range of x (5× 10-3 up to 0.175) but with extremely small moment. Magnetization measurements suggest that this behavior occurs because only a small percentage of Mn (Mn2+ states with J=S=5/2) contribute to the magnetization. Thus, the magnetic moments are quenched for the majority of Mn atoms, contrary to the general belief of the existence of a localized Mn moment in Si. X-ray absorption spectroscopy suggests that the quenching of Mn moments is attributed to the formation of an itinerant but Anderson-localized impurity band, forming at x as low as 5× 10-3. © 2008 The American Physical Society.

The temperature and field dependence of magnetization and conductivity of amorphous Ge doped with Gd (a- Gdx Ge1-x) has been measured for a wide range of x (0.08

Salivarian trypanosomes comprise a group of extracellular anthroponotic and zoonotic parasites. The only sustainable method for global control of these infection is through vaccination of livestock animals. Despite multiple reports describing promising laboratory results, no single field-applicable solution has been successful so far. Conventionally, vaccine research focusses mostly on exposed immunogenic antigens, or the structural molecular knowledge of surface exposed invariant immunogens. Unfortunately, extracellular parasites (or parasites with extracellular life stages) have devised efficient defense systems against host antibody attacks, so they can deal with the mammalian humoral immune response. In the case of trypanosomes, it appears that these mechanisms have been perfected, leading to vaccine failure in natural hosts. Here, we provide two examples of potential vaccine candidates that, despite being immunogenic and accessible to the immune system, failed to induce a functionally protective memory response. First, trypanosomal enolase was tested as a vaccine candidate, as it was recently characterized as a highly conserved enzyme that is readily recognized during infection by the host antibody response. Secondly, we re-addressed a vaccine approach towards the Invariant Surface Glycoprotein ISG75, and showed that despite being highly immunogenic, trypanosomes can avoid anti-ISG75 mediated parasitemia control.

AbstractDrug-induced liver injury (DILI) is characterized by hepatocyte injury, cholestasis injury, and mixed injury. The liver transplantation is required for serious clinical outcomes such as acute liver failure. Current studies have found that many mechanisms were involved in DILI, such as mitochondrial oxidative stress, apoptosis, necroptosis, autophagy, ferroptosis, etc. Ferroptosis occurs when hepatocytes die from iron-dependent lipid peroxidation and plays a key role in DILI. After entry into the liver, where some drugs or chemicals are metabolized, they convert into hepatotoxic substances, consume reduced glutathione (GSH), and decrease the reductive capacity of GSH-dependent GPX4, leading to redox imbalance in hepatocytes and increase of reactive oxygen species (ROS) and lipid peroxidation level, leading to the undermining of hepatocytes; some drugs facilitated the autophagy of ferritin, orchestrating the increased ion level and ferroptosis. The purpose of this review is to summarize the role of ferroptosis in chemical- or drug-induced liver injury (chemical/DILI) and how natural products inhibit ferroptosis to prevent chemical/DILI. [ABSTRACT FROM AUTHOR]

Based on micro-ecology theory,teachers' support or caregiving which provides students with optimal strategies is the most important factor in decreasing instances of bullying. To address the effect of teacher support on the reduction of campus bullying, this study considered the emotional self-efficacy (ESE) of students as a mediator in relation to teachers' support and being bullied from students' perspectives. Data were collected from 447 elementary school students located in Northern Fujian, China. Confirmatory factor analysis was first applied, and then structural equation modeling (SEM) was performed in order to verify the research hypotheses. The SEM results confirmed the mediational model in which ESE acted as a mediator in the relationships between teacher support (instrumental and emotional support) and three types of perceived bullying (physical, verbal, and relational bullying). [ABSTRACT FROM AUTHOR]

Adenotonsillectomy is the most common daytime surgery performed on children. Anesthesiologists must select the optimal combination of drugs to ensure effective anesthesia effect and prompt recovery in children. The optimal induction dose of ciprofol in children is unclear. In this study, we aim to investigate the effect of different doses of ciprofol on anesthesia induction in children undergoing daytime adenotonsillectomy and provide a reference for clinical use. 144 children aged 3–12 years, ASA I-II, undergoing daytime adenotonsillectomy, were included in this clinical trial. The children were randomly divided into three groups and given 0.4 mg/kg (C4), 0.6 mg/kg (C6), or 0.8 mg/kg (C8) of ciprofol for anesthesia induction. The primary outcome was intubation conditions. Vital signs and injection pain were also recorded. The rates of unacceptable intubation conditions were 30.6%, 8.7%, and 8.2% in the C4, C6, and C8 groups (P value < 0.0167). The overall incidence of reported injection pain was 3.5%. The heart rate and mean arterial pressure did not differ between the groups at the same time points. We found that combining 0.6 mg/kg of ciprofol with low-dose rocuronium could provide optimal intubation conditions in pediatric daytime adenotonsillectomy patients. This combination resulted in stable circulation and BIS values. This study is registered at the Chinese Clinical Trial Registry (Registration number: ChiCTR2200063144, Date of Registration: 31/08/2022) [ABSTRACT FROM AUTHOR]

Accumulated evidence showed that thyroid diseases induced cognitive decline. However, the relationship between thyroid hormones (THs) and cognition in older euthyroid people is still unclear. Our study aimed to estimate the association between THs within the euthyroid range and cognition in community-dwelling older adults in China. Data were extracted from a cohort study on the health status of rural older adults from the Guizhou province in China (HSRO). Serum thyroid-stimulating hormone (TSH), free thyroxine (FT4), and free triiodothyronine (FT3) were measured using the electrochemiluminescence immunoassay. Cognitive function was evaluated by the Mini-Mental State Examination (MMSE). Linear regression and a binary logistic regression model were used to explore the relationship between THs and cognition in euthyroidism (TSH level of 0.27 ~ 4.20mIU/L). A total of 957 euthyroidism individuals were included in this study, with a mean (SD) age of 71.34 (6.35) years. In individuals with euthyroidism, serum TSH and FT3 levels were positively associated with cognition (TSH:β = 0.06, 95% CI 0.01 ~ 0.11, P = 0.03; FT3:β = 0.07, 95% CI 0.01 ~ 0.12, P = 0.01); and serum FT3 and TSH levels were significantly associated with cognitive domains (P < 0.05). Further, euthyroid individuals in the lowest serum FT3(OR = 1.96; 95% CI 1.27 ~ 3.03) quartile had a twofold increased risk of cognitive impairment compared to those in the highest quartile after adjusting for potential confounding factors. These findings suggested that low levels of FT3 could be an independent risk factor for cognitive impairment in older euthyroid adults. Additionally, a positive linear association exists between serum FT3 levels and cognitive domains (such as immediate memory, language, and attention). Further studies are needed to determine the underlying mechanisms and the community significance of these findings. [ABSTRACT FROM AUTHOR]

An Mw 6.8 earthquake occurred in Luding County, Ganzi Tibetan Autonomous Prefecture, Sichuan Province, on 5 September 2022. This seismic event triggered numerous coseismic geohazards in the seismic zone. In this study, the ascending- and descending-track synthetic aperture radar (SAR) images observed by the Sentinel-1A satellite are utilized to extract the coseismic surface deformation of the Luding earthquake. Subsequently, a faulting model is estimated based on the elastic dislocation theory, under the constraint of the InSAR observation. Additionally, the POT technique was employed to detect coseismic geohazards. High-spatial-resolution optical remote sensing images served to validate the reliability of the detection results. The coseismic interferometric synthetic aperture radar (InSAR) deformation field indicated a maximum deformation of ~190 mm and ~140 mm along the ascending and descending tracks, respectively. The estimated best-fitting faulting model suggests that the optimal seismogenic fault strike and dip angles are 169.3° and 70°, respectively. The fault slip predominantly exhibits left-lateral strike-slip characteristics and is concentrated at depths of 3–12 km. The estimated maximum fault slip was 2.67 m, occurring at a depth of 7 km. The pixel offset tracking (POT) result derived from the pre- and post-earthquake SAR images found a total of 245 medium- to large-scale coseismic geohazards, with a verification rate from optical images exceeding 64%. The distribution of these geohazards is notably dense within the significant fault rupture segment. Geohazards on the fault hanging wall are densely packed, whereas landslides along the Dadu River's fault footwall are also notably frequent. [ABSTRACT FROM AUTHOR]

Organic electrosynthesis has consistently aroused significant interest within both academic and industrial spheres. Despite the considerable progress achieved in this field, the majority of electrochemical transformations have been conducted through the utilization of direct‐current (DC) electricity. In contrast, the application of alternating current (AC), characterized by its polarity‐alternating nature, remains in its infancy within the sphere of organic synthesis, primarily due to the absence of a comprehensive theoretical framework. This minireview offers an overview of recent advancements in AC‐driven organic transformations and seeks to elucidate the differences between DC and AC electrolytic methodologies by probing into their underlying physical principles. These differences encompass the ability of AC to preclude the deposition of metal catalysts, the precision in modulating oxidation and reduction intensities, and the mitigation of mass transfer processes. [ABSTRACT FROM AUTHOR]

As the production of electric vehicles and lithium-ion batteries continues to rise, concerns over resource scarcity and supply shortages of critical metals, including Cu, Ni, Co, Mn, and Li, have become increasingly urgent. To address these concerns and promote environmental protection, there is a growing demand for the recycling of hazardous waste containing these critical metals as secondary resources. Therefore, this paper proposes a novel synergistic solvent extraction system of D2EHPA-NNPA, which fills a gap in the lack of a suitable extraction system for the hydrometallurgical industry of secondary resources containing Cu, Ni, Co, Mn, and Li. With the specific extraction sequence of D2EHPA-NNPA, a novel process has been designed and proposed for the stepwise extraction of Cu, Ni, Co, Mn, and Li from secondary resources, which significantly simplifies process flows while avoiding cross-contamination of the extractants and the production of industrial wastewater. Furthermore, the proposed "extraction-scrubbing-stripping" process has been investigated from both macroscopic and microscopic perspectives, demonstrating that the novel synergistic solvent extraction system of D2EHPA-NNPA is a viable option for industrial applications to promote a circular economy and achieve sustainability objectives. [ABSTRACT FROM AUTHOR]

National holidays are associated with high mortality in some diseases, but little is known about patients undergoing peritoneal dialysis (PD). The research aimed to investigate the impact of national holidays on the health outcomes of PD patients. Over ten years, all episodes of unplanned hospitalization, death, and peritonitis in PD patients were collected in our center. Seven national holidays in China were chosen, and non-holiday days were selected as the control period. The effect of national holidays was observed by comparing the hospitalization, death, and peritonitis rates between holiday and non-holiday groups. There were 297 events in all holiday periods and 1247 in non-holiday periods. There is no significant difference in hospitalization rate between holiday and non-holiday groups (32.4% ± 6.4% vs. 29.2% ± 3.4%, p = 0.175). So is the death rate [6.3% (4.8–12.3%) vs.5.0% (4.2–8.9%), p = 0.324] and peritonitis rate [0.19 (0.13–0.53) vs. 0.22 (0.18–0.27), p = 0.445] between the two groups. Significant differences were observed in the distribution of peritonitis causes between the two groups (p = 0.017). The rate of secondary to other infections in the holiday group was significantly higher than in the non-holiday group (25.0 vs. 10.3%, p = 0.015). Our study suggested no national holiday effect on health outcomes of PD patients based on ten-year data in our center. [ABSTRACT FROM AUTHOR]

Introduction: Citri Sarcodactylis Fructus has the effects of relieving cough, removing phlegm, and reducing asthma, but little is known about the metabolic and distribution of its chemical constituents in vivo. Therefore, it is necessary to study the metabolism of Citri Sarcodactylis Fructus in vivo. Objective: We aimed to (1) analyze the distribution of prototype compounds and metabolites of the chemical constituents of Citri Sarcodactylis Fructus in rat and (2) infer the metabolites and metabolic pathways of the chemical constituents. Materials and methods: A C18 column (3 × 100 mm, 2.6 μm) was used. The mobile phase was water containing 0.1% formic acid (eluent A) and acetonitrile containing 0.1% formic acid (eluent B) at a discharge rate of 0.3 mL/min. Mass spectra of biological samples were collected in electrospray ionization (ESI) positive ion mode in the m/z 100–1500 scan range. The obtained biological samples were then subjected to chemical analysis, including plasma, urine, feces, and heart, liver, spleen, lungs, kidneys, stomach, and small intestine tissues. Prototype compounds and metabolites were identified. Results: In all, 40 prototype compounds and 78 metabolites, including 26 phase I metabolites and 52 phase II metabolites, were identified using UHPLC–Q/Orbitrap HRMS. Eight possible metabolic pathways (reduction, hydrolysis, dehydration, methylation, hydroxylation, sulfation, glucuronidation, and demethylation) were proposed. The prototype compounds were predominantly distributed in lung tissues. The metabolites were mainly distributed in plasma and kidney tissues. Conclusion: We systematically investigated the metabolites of CitriSarcodactylis Fructus in vivo. We suggest metabolic pathways that might be relevant for further metabolic studies and screening of active ingredients of Citrus Sarcodactylis Fructus in vivo. In this study, we employed UHPLC–Q/Orbitrap HRMS to identify a total of 40 prototype compounds of Citri Sarcodactylis Fructus, primarily including coumarin‐type, flavonoid‐type, and limonoid‐type compounds. Additionally, we identified 78 metabolites, comprising 26 phase I metabolites and 52 phase II metabolites. The metabolic processes observed in vivo primarily involved reduction, hydrolysis, dehydration, methylation, hydroxylation, sulfation, glucuronidation, and demethylation. These findings provide valuable information for further exploring the pharmacological mechanism of action of Citri Sarcodactylis Fructus. [ABSTRACT FROM AUTHOR]

Cervical cancer (CC) is a common malignant neoplasm in gynecology. There is increasing evidence to suggest that microRNAs (miRNAs) act as crucial regulators of CC. However, whether miR-10a-5p plays a role in CC is under investigation. The aim of this stuy was to assess the miR-10a-5p expression pattern in the development of CC and investigate its downstream target. MiR-10a-5p inhibition decreased CC cell proliferation and impaired CC cell invasion and migration but enhanced apoptosis. UBE2I was a direct target of miR-10a-5p. QRT-PCR results showed a down-regulation of UBE2I in CC cells, opposing miR-10a-5p. Besides, overexpression of miR-10a-5p down-regulated UBE2I. Functional rescue experiments further indicated the miR-10a-5p-UBE2I axis was linked to CC cell growth, apoptosis and metastasis. MiR-10a-5p upregulation promotes cervical cancer development by inhibiting UBE2I. These results also predict that miR-10a-5p may be a potential target for the clinical treatment of CC. What is already known on this subject? As a widely researched cancer-related miRNA, the overexpression of miR-10a-5p has been verified in various cancers. It has been described in a meta-analysis report that there were 42 miRNAs up-regulated and 21 miRNAs down-regulated in different stages of cervical cancer tissue versus healthy tissue. What do the results of this study add? We verified that miR-10a-5p initiates and promotes tumor cell development by decreasing UBE2I abundance. This miR-10a-5p-mediated post-transcriptional regulation of UBE2I is involved in the tumorigenesis, invasion and migration of human cervical cancer. What are the implications of these findings for clinical practice and/or further research? These findings provide mechanistic insights into how miR-10a-5p regulates cervical cancer hyper-proliferation and metastasis, as well as a new target for clinical treatment. Nevertheless, whether miR-10a-5p/UBE2I axis can be regulated by non-invasive methods need further exploration, which will be the focus of our future research. [ABSTRACT FROM AUTHOR]

In this work, we propose adaptive deep learning approaches based on normalizing flows for solving fractional Fokker–Planck equations (FPEs). The solution of a FPE is a probability density function (PDF). Traditional mesh-based methods are ineffective because of a unbounded computation domain, a large number of dimensions and a nonlocal fractional operator. To this end, we represent the solution with an explicit PDF model induced by a flow-based deep generative model, which constructs a transport map from a simple distribution to the target distribution. We consider two methods to approximate the fractional Laplacian. One method is the Monte Carlo approximation. The other method is to construct an auxiliary model with Gaussian radial basis functions (GRBFs) to approximate the solution such that we may take advantage of the fact that the fractional Laplacian of a Gaussian is known analytically. Based on these two different ways for the approximation of the fractional Laplacian, we propose two models to approximate stationary FPEs and one model to approximate time-dependent FPEs. To further improve the accuracy, we refine the training set and the approximate solution alternately. A variety of numerical examples is presented to demonstrate the effectiveness of our adaptive deep density approaches. [ABSTRACT FROM AUTHOR]

Kiwifruit decay caused by endophytic fungi is affected by exogenous pathogens that trigger changes in fungal community composition and interact with the endophytic fungal community. Four fungal pathogens of kiwifruit were identified. These were Aspergillus japonicus, Aspergillus flavus, Botryosphaeria dothidea, and Penicillium oxalicum. Except for P. oxalicum, the remaining three species represent newly described pathogens of kiwifruit. All four fungal species caused disease and decay in mature kiwifruit. Results of the fungal community analysis indicated that three pathogens that A. japonicus, A. flavus and P. oxalicum were the most dominant, however, other fungal species that did not cause disease symptoms were also present. Positive interactions between fungal species were found in asymptomatic, symptomatic, and infected kiwifruit. The ability of all four pathogens to infect kiwifruit was confirmed in an inoculation experiment. The presence of any one of the four identified pathogens accelerated decay development and limited the postharvest longevity of harvested kiwifruit. Results of the study identified and confirmed the ability of four fungal species to infect and cause decay in harvested kiwifruit. Changes in the structure and composition of the kiwifruit microbiome during the decay process were also characterized. This provides a foundation for the further study of the microbiome of kiwifruit and their involvement in postharvest diseases. [ABSTRACT FROM AUTHOR]

Complete blood count (CBC)-derived inflammatory markers are predictive biomarkers for the prognosis of many diseases. However, there was no study on patients with peritoneal dialysis-associated peritonitis (PDAP). We aimed to investigate the value of these markers in predicting treatment failure of acute peritonitis in chronic PD patients. The records of 138 peritonitis episodes were reviewed and divided into treatment success or failure groups in a single center for 10 years. CBC-derived markers and other routine data were recorded before peritonitis treatment was initiated. Univariate and multivariate regression analyses and the receiver operating characteristic (ROC) curve about the predictors of treatment outcomes were performed. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and derived NLR were significantly higher in the failure group. Univariate logistic regression results showed that NLR and PLR were risk factors of treatment outcomes. The backward stepwise multivariate logistic regression results demonstrated that NLR [adjusted odds ratio (aOR), 1.376; 95% confidence intervals (CI), 1.105–1.713; p =.004], PLR (aOR, 1.010; 95%CI, 1.004–1.017; p =.002) were risk factors, but hemoglobin-to-lymphocyte ratio (HLR) (aOR, 0.977; 95%CI, 0.963–0.991; p =.001), and SII (aOR, 0.999; 95%CI, 0.998–1.000; p =.040) were protective factors. A combination of age, PD vintage, Gram-positive peritonitis, staphylococcus aureus, culture-negative, NLR, PLR, HLR, and SII would improve prognostic performance. The area under this ROC curve was 0.85, higher than other factors. NLR, PLR, HLR, and SII were associated with PDAP outcomes. Age, PD vintage, NLR, and PLR were significant risk factors in PDAP patients. [ABSTRACT FROM AUTHOR]

Despite tremendous efforts that have been dedicated to high‐performance electrochemical energy storage devices (EESDs), traditional electrode fabrication processes still face the daunting challenge of limited energy/power density or compromised mechanical compliance. 3D thick electrodes can maximize the utilization of z‐axis space to enhance the energy density of EESDs but still suffer from limitations in terms of poor mechanical stability and sluggish electron/ion transport. Direct ink writing (DIW), an eminent branch of 3D printing technology, has gained popularity in the manufacture of 3D electrodes with intricately designed architectures and rationally regulated porosity, promoting a triple boost in areal mass loading, ion diffusion kinetics, and mechanical flexibility. This focus review highlights the fundamentals of printable inks and typical configurations of 3D‐printed devices. In particular, preparation strategies for high‐performance and multifunctional 3D‐printed EESDs are systemically discussed and classified according to performance evaluation metrics such as high areal energy density, high power density, high volumetric energy density, and mechanical flexibility. Challenges and prospects for the fabrication of high‐performance 3D‐printed EESDs are outlined, aiming to provide valuable insights into this thriving field. [ABSTRACT FROM AUTHOR]

Atmospheric heavy metal pollution presents a severe threat to public health and environmental stability. Transition metal catalysts have emerged as a potent solution for the selective capture and removal of these pollutants. This review provides a comprehensive summary of current advancements in the field, emphasizing the efficiency and specificity of nanostructured transition metals, including manganese, iron, cobalt, nickel, copper, and zinc. Looking forward, we delve into the prospective trajectory of catalyst development, underscoring the need for materials with enhanced stability, regenerability, and environmental compatibility. We project that advancements in computational materials science, nanotechnology, and green chemistry will be pivotal in discovering innovative catalysts that are economically and environmentally sustainable. The integration of smart technologies for real-time monitoring and adaptive control is anticipated to revolutionize heavy metal remediation, ensuring efficient and responsive pollution abatement strategies in the face of evolving industrial scenarios and regulatory landscapes. [ABSTRACT FROM AUTHOR]

The powerful combination of large-scale drug-related interaction networks and deep learning provides new opportunities for accelerating the process of drug discovery. However, chemical structures that play an important role in drug properties and high-order relations that involve a greater number of nodes are not tackled in current biomedical networks. In this study, we present a general hypergraph learning framework, which introduces Drug-Substructures relationship into Molecular interaction Networks to construct the micro-to-macro drug centric heterogeneous network (DSMN), and develop a multi-branches HyperGraph learning model, called HGDrug, for Drug multi-task predictions. HGDrug achieves highly accurate and robust predictions on 4 benchmark tasks (drug-drug, drug-target, drug-disease, and drug-side-effect interactions), outperforming 8 state-of-the-art task specific models and 6 general-purpose conventional models. Experiments analysis verifies the effectiveness and rationality of the HGDrug model architecture as well as the multi-branches setup, and demonstrates that HGDrug is able to capture the relations between drugs associated with the same functional groups. In addition, our proposed drug-substructure interaction networks can help improve the performance of existing network models for drug-related prediction tasks. Author summary: Drugs containing the same functional groups may have similar pharmacochemical properties. However, how to effectively combine chemical information of drugs from molecular fragments containing functional groups into the biomolecular network is challenging and rarely explored. we decompose drugs' SMILES string and construct a drug-centric heterogeneous network that integrates drug substructure and molecular interactions information. Based on the heterogeneous network, we proposed an end-to-end hypergraph attention network framework for the drug multi-task predictions, termed as HGDrug. The efficiency and generalization of the proposed HGDrug have been demonstrated by the state-of-the-art performance in four drug-related interaction predictions tasks with huge improvement compared to previous general-purpose classical models and task-specific models. In addition, HGDrug can effectively identify potential drug-related interactions and the drug-sub-structure networks are able to help to improve the performance of other GNN models. These conclusions present important insights on how to introduce the drug' substructure information for multiple drug-related interactions tasks on biomedical networks. In summary, HGDrug offers a general and powerful tool for the identification of drug-related interactions by constructing the micro-to-macro drug-centric heterogeneous network. [ABSTRACT FROM AUTHOR]

Background: To investigate the prevalence and risk factors of refractive astigmatism (RA) and corneal astigmatism (CA) in preschool children and school-aged children in Shanghai, China. Methods: In this school-based, cross-sectional study, 4–15 years old children across three learning stages of kindergarten, primary school, and junior high school underwent noncycloplegic autorefraction and completed comprehensive questionnaires involving time spent on daily homework and outdoor activities. Data from the right eyes were analysed. Results: Overall, 7084 children (mean ± standard deviation (SD) of age: 8.08 ± 3.11 years) were included, and the prevalence rates of RA/CA (≤ − 1.0 D) in children were 15.8%/64% in kindergartens, 16.5%/65% in primary schools, and 32.8%/76.9% in junior high schools. The magnitude and prevalence of RA and CA all increased with age or with learning stage (all P < 0.001). The presence of RA was associated with more myopic spherical power (odds ratio (OR) 0.956, P = 0.021), junior high school (OR 1.973, P < 0.001), longer homework time on weekdays (OR 1.074, P = 0.029), and shorter outdoor activity time on weekends (odds ratio 0.929, P = 0.013). Conclusion: In the wide age range of 4 to 15 years, the magnitude and prevalence of RA and CA increased with the learning stage, and these increases mainly began at the primary school stage. Factors, including longer homework time and shorter outdoor time were correlated with the presence of RA. [ABSTRACT FROM AUTHOR]

Biodegradable material is a kind of polymer material which has no pollution to the environment. It has been used in food packaging, medical treatment, agriculture and other industries. However, the production cost of biodegradable materials is high and the physical properties are defective, which affects their wide application in various fields. The types and properties of biodegradable materials are reviewed. The advantages and disadvantages of spectroscopy, nuclear magnetic resonance and chromatography and mass spectrometry in the identification of biodegradable materials are compared. It is pointed out that the material characterization of biodegradable materials and the analysis methods of impurities are the key research contents, so as to provide reference for the material analysis of biodegradable materials. [ABSTRACT FROM AUTHOR]

Background: Skin photoaging is a condition caused by long‐term exposure to ultraviolet irradiation, resulting in a variety of changes in the skin, such as capillary dilation, increased or absent pigmentation, dryness, sagging, and wrinkles. Stem cells possess a remarkable antioxidant capacity and the ability to proliferate, differentiate, and migrate, and their main mode of action is through paracrine secretion, with exosomes being the primary form of secretion. Stem cell‐derived exosomes contain a variety of growth factors and cytokines and may have great potential to promote skin repair and delay skin ageing. Methods: This review focuses on the mechanisms of UV‐induced skin photoaging, the research progress of stem cell exosomes against skin photoaging, emerging application approaches and limitations in the application of exosome therapy. Result: Exosomes derived from various stem cells have the potential to prevent skin photoaging. Conclusion: The combination with novel materials may be a key step for their practical application, which could be an important direction for future basic research and practical applications. [ABSTRACT FROM AUTHOR]

Traditional risk measurements have proven inadequate in capturing tail risk and nonlinear correlation. This study proposes a novel approach to measure financial risk in the Internet finance industry: a new Value‐at‐Risk (VaR) measurement based on quantile regression neural network (QRNN). Sparrow Search Algorithm (SSA) is utilized to optimize the QRNN model, which improves the model's performance in predicting internet finance risk. By comparing the TGARCH‐VaR and QR‐VaR approaches, our study demonstrates the effectiveness of the QRNN‐VaR approach and its potential to improve the accuracy of risk prediction in the Internet finance industry. This study further examines and compares the risks between the traditional and internet finance industries. It also considers the unique impact of COVID‐19 on industry risk based on statistical testing for differences and machine learning models. Our results indicate that the level of risk in the Internet finance industry is higher than in the traditional finance industry. Moreover, COVID‐19 has contributed to increased risk within the Internet finance industry. These findings have significant implications for investors and policymakers seeking to better understand and manage risks within the Internet finance industry, particularly in the ongoing COVID‐19 pandemic. [ABSTRACT FROM AUTHOR]

Current methods of molecular image-based drug discovery face two major challenges: (1) work effectively in absence of labels, and (2) capture chemical structure from implicitly encoded images. Given that chemical structures are explicitly encoded by molecular graphs (such as nitrogen, benzene rings and double bonds), we leverage self-supervised contrastive learning to transfer chemical knowledge from graphs to images. Specifically, we propose a novel Contrastive Graph-Image Pre-training (CGIP) framework for molecular representation learning, which learns explicit information in graphs and implicit information in images from large-scale unlabeled molecules via carefully designed intra- and inter-modal contrastive learning. We evaluate the performance of CGIP on multiple experimental settings (molecular property prediction, cross-modal retrieval and distribution similarity), and the results show that CGIP can achieve state-of-the-art performance on all 12 benchmark datasets and demonstrate that CGIP transfers chemical knowledge in graphs to molecular images, enabling image encoder to perceive chemical structures in images. We hope this simple and effective framework will inspire people to think about the value of image for molecular representation learning. [ABSTRACT FROM AUTHOR]

Coal–rock disasters are becoming more and more severe as the intensity of coal mining increases. Due to its destructive power and resulting extensive area damage, rock burst is among the most critical threats to coal mine safety. It results from the combined action of the coal and the rock when affected by the mining process. To this end, we used a combination of coal and rock to conduct our studies. Combining a uniaxial compression experiment with theoretical analysis, this work investigated how different lithologies and coal–rock height ratios affect the mechanical properties of this combination and the law governing energy accumulation. We determined the following: When the coal–rock height ratios are dissimilar, the peak strength and modulus of elasticity of the combination show a negative correlation with the coal thickness share, and the pre-peak energy accumulation and impact energy index of the combination is positively correlated with the coal thickness percentage. In combination with the same coal–rock height ratio, the peak strength, elastic modulus, pre-peak energy accumulation, and impact energy index all increase with increased rock strength and elastic modulus. The presence of a hard rock layer affects the accumulation of pre-peak energy. Based on the experimental analysis, a theoretical model was established, and the surrounding rock stress negatively correlates with the percentage of coal thickness; the energy stored in the surrounding rock is directly proportional to the coal in the zone. Therefore, we inferred that the stress distribution of the surrounding rock as coal thickness changes is abnormal; substantial energy accumulation can swiftly initiate dynamic disasters, such as rock bursts. This study has important reference significance for preventing and controlling rock bursts in areas where coal thickness changes. [ABSTRACT FROM AUTHOR]

Segmenting histopathological image automatically is an important task in computer-aided pathology analysis. However, it is challenging to segment and analyze digitalized histopathology images due to the large size of WSI, diversity and complexity of features. In this paper, we propose a multi-resolution attention and multi-scale convolution network (MAMC-Net) for the automatic tumor segmentation of WSI. First, the proposed MAMC-Net design the multi-resolution attention module that utilizes multi-resolution images as the pyramid inputs to generate a wider range feature information and richer details. Specifically, we employ an attention mechanism at each level to capture discriminative features related with the segmentation task. Furthermore, a multi-scale convolution module is designed to multi-scale feature representation by aggregating intact semantic information from the deep layer of encoder and high-resolution details from the final layer of decoder. To further obtain the accurate segmentation results, we adopt a fully connected Conditional Random Field (CRF) to splice the overlapping maps to avoid discontinuities and inconsistencies of cancer boundaries. Finally, we demonstrate the effectiveness of our framework on open-source datasets, including CAME-LYON17 (breast cancer metastases) and BOT (gastric cancer) datasets. The experimental results show that our proposed MAMC-Net obtains superior performance compared with other state-of-the-art methods, such as a Dice coefficient (DSC) of 0.929, an IOU score of 0.867, recall of 0.933 on the breast cancer dataset, a Dice coefficient (DSC) of 0.89, an IOU score of 0.802, recall of 0.903 on the gastric cancer dataset. [ABSTRACT FROM AUTHOR]

Background: The growth arrest and DNA damage-inducible gene gamma (GADD45G), an important member of GADD45 family, has been connected to the development of certain human cancers. Our previous studies have confirmed that GADD45G expression could be upregulated by 4-methoxydalbergione (4MOD) in liver cancer cells, but its potential pathological role in hepatocellular carcinoma (HCC) has not been fully understood. This study aimed to determine potential role of GADD45G in HCC, and the effects of 4-methoxydalbergione (4MOD) on the regulation of GADD45G expression in vivo were also analyzed. Methods: Publicly available data and in-house immunohistochemistry (IHC) experiments were utilized to explore the expression profiles and clinical significance of GADD45G in HCC samples. Functional enrichment analysis based on GADD45G co-expression genes was used to excavate the molecular mechanism of GADD45G in HCC. We also conducted in vivo experiment on BALB/c nude mice to excavate the inhibitory effect of 4MOD on HCC and to evaluate the differences in the expression of GADD45G in xenograft tissues between the 4MOD-treated and untreated groups. Results: GADD45G displayed significant low expression in HCC tissues. Downregulated expression of GADD45G was positively correlated with some high risk factors in HCC patients and predicted worse prognosis of HCC patients. There was a close association of GADD45G mRNA expression and immune cells, including neutrophils, NK cells, CD8 T cells, and macrophages. Co-expressed genes of GADD45G were involved in several pathways including cell cycle, carbon metabolism, and peroxisome. 4MOD could significantly suppress the growth of HCC in vivo, and this inhibitory effect was dependent on the upregulation of GADD45G expression. Conclusion: GADD45G expression can be used as a new clinical biomarker for HCC and GADD45G may be a potential target for the anti-cancer effect of 4MOD in liver cancer. [ABSTRACT FROM AUTHOR]

Neptune-sized planets exhibit a wide range of compositions and densities, depending on factors related to their formation and evolution history, such as the distance from their host stars and atmospheric escape processes. They can vary from relatively low-density planets with thick hydrogen–helium atmospheres1,2 to higher-density planets with a substantial amount of water or a rocky interior with a thinner atmosphere, such as HD 95338 b (ref. 3), TOI-849 b (ref. 4) and TOI-2196 b (ref. 5). The discovery of exoplanets in the hot-Neptune desert6, a region close to the host stars with a deficit of Neptune-sized planets, provides insights into the formation and evolution of planetary systems, including the existence of this region itself. Here we show observations of the transiting planet TOI-1853 b, which has a radius of 3.46 ± 0.08 Earth radii and orbits a dwarf star every 1.24 days. This planet has a mass of 73.2 ± 2.7 Earth masses, almost twice that of any other Neptune-sized planet known so far, and a density of 9.7 ± 0.8 grams per cubic centimetre. These values place TOI-1853 b in the middle of the Neptunian desert and imply that heavy elements dominate its mass. The properties of TOI-1853 b present a puzzle for conventional theories of planetary formation and evolution, and could be the result of several proto-planet collisions or the final state of an initially high-eccentricity planet that migrated closer to its parent star.Observations of the super-massive Neptune-sized transiting planet TOI-1853 b show a mass almost twice that of any other Neptune-sized planet known so far and a bulk density implying that heavy elements dominate its mass. [ABSTRACT FROM AUTHOR]