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Abstract Parkinson’s disease is characterized by motor and cognitive deficits. While previous work suggests a relationship between both, direct empirical evidence is scarce or inconclusive. Therefore, we examined the relationship between walking features and executive functioning in patients with Parkinson’s disease using state-of-the-art machine learning approaches. A dataset of 103 geriatric Parkinson inpatients, who performed four walking conditions with varying difficulty levels depending on single task walking and additional motor and cognitive demands, was analyzed. Walking features were quantified using an inertial measurement unit (IMU) system positioned at the patient’s lower back. The analyses included five imputation methods and four regression approaches to predict executive functioning, as measured using the Trail-Making Test (TMT). Multiple imputation by chained equations (MICE) in combination with support vector regression (SVR) reduce the mean absolute error by about 4.95% compared to baseline. Importantly, predictions solely based on walking features obtained with support vector regression mildly but significantly correlated with Δ−TMT values. Specifically, this effect was primarily driven by step time variability, double limb support time variability, and gait speed in the dual task condition with cognitive demands. Taken together, our data provide direct evidence for a link between executive functioning and specific walking features in Parkinson’s disease.

Abstract Nonlinear optical responses in two-dimensional (2D) materials can build free-space optical neuromorphic computing systems. Ensuring the high performance and the tunability of the system is essential to encode diverse functions. However, common strategies, including the integration of external electrode arrays or photonic structures with 2D materials, and barely patterned 2D materials, exhibit a contradiction between performance and tunability. Because the unique band dispersions of 2D materials can provide hidden paths to boost nonlinear responses independently, here we introduced a new free-space optical computing concept within a bare molybdenum disulfide array. This system can preserve high modulation performance with fast speed, low energy consumption, and high signal-to-noise ratio. Due to the freedom from the restrictions of fixed photonic structures, the tunability is also enhanced through the synergistic encodings of the 2D cells and the excitation pulses. The computing mechanism of transition from two-photon absorption to synergistic excited states absorption intrinsically improved the modulation capability of nonlinear optical responses, revealed from the relative transmittance modulated by a pump-probe-control strategy. Optical artificial neural network (ANN) and digital processing were demonstrated, revealing the feasibility of the free-space optical computing based on bare 2D materials toward neuromorphic applications.

Phosphoric acid, as a vital chemical raw material, holds an important position in the chemical industry. Its applications span across various sectors, determined largely by its purity. Low-purity phosphoric acid can be used in industrial and agricultural sectors, while high-purity phosphoric acid is essential for pharmaceuticals, food, electronics and other industries. The rising demand for batteries and semiconductors in recent years has led to increased requirements for phosphoric acid purity. There are two main methods for manufacturing phosphoric acid. The thermal method, while effective, is energy-intensive and environmentally unfriendly, conflicting with China’s green chemistry development goals. On the other hand, the phosphoric acid process, characterized by lower energy consumption, is more adept at handling China’s low-grade phosphate rock despite resulting in bulk and complex product impurities. Among various purification technologies, such as chemical precipitation, crystallization, electrodialysis, and ion exchange resin, the extraction method stands out. It offers environmental benefits, simple operation, and the capacity for large-scale production, marking it as a promising technique for phosphoric acid purification. This article summarizes in detail the research status of various extraction methods in recent years. It focuses on solvent extraction, aqueous two-phase extraction, reverse micelle extraction, ultrasonic-assisted extraction, and supercritical fluid extraction. It sorts out the solvent extraction method along with various extractants. The research on single extractants such as tri-n-butyl phosphate (TBP), methyl isobutyl ketone (MIBK), and n-octanol (NOA) has been primarily focused on identifying the optimal extraction conditions, including the O/A phase ratio, temperature, and air pressure. However, these single extractants typically target a single impurity, which limits their effectiveness in purifying phosphoric acid when multiple impurities are present. This limitation underscores the significant advantages of composite extractants in the purification process. Current research on composite extractants emphasizes determining the ideal proportion of extractants, often based on volume ratio, and establishing the optimal conditions for effective extraction. In addition to composite extractants, the development of new extractants offers promising solutions to the challenges posed by the low extraction efficiency of single extractants. Looking forward, the future of phosphoric acid extraction technology is poised for exciting developments: (1) The development of green composite extractants, alongside new extractants and materials combined with extractants, aims to achieve more efficient separation of impurities from phosphoric acid; (2) There is a growing interest in expanding research into the application of aqueous two-phase extraction and reverse micelle extraction for ion extraction, including the exploration of new aqueous phase systems; (3) The use of ultrasonic technology to accelerate the extraction process, coupled with studies on how supercritical fluids can improve the solubility and extraction efficiency of ions, represents another avenue for innovation. These advancements seek to reduce costs and explore specific application areas.

Abstract Artificial visual system empowered by 2D materials-based hardware simulates the functionalities of the human visual system, leading the forefront of artificial intelligence vision. However, retina-mimicked hardware that has not yet fully emulated the neural circuits of visual pathways is restricted from realizing more complex and special functions. In this work, we proposed a human visual pathway-replicated hardware that consists of crossbar arrays with split floating gate 2D tungsten diselenide (WSe2) unit devices that simulate the retina and visual cortex, and related connective peripheral circuits that replicate connectomics between the retina and visual cortex. This hardware experimentally displays advanced multi-functions of red–green color-blindness processing, low-power shape recognition, and self-driven motion tracking, promoting the development of machine vision, driverless technology, brain–computer interfaces, and intelligent robotics.

BackgroundExcessive radon exposure is considered the second risk factor for lung cancer. Since the opening of the subway in a city of Zhejiang Province, the exposure level of radioactive gas radon in subway stations and its impact on occupational health have become one of the important issues of public concern. ObjectiveTo monitor the radon concentration of subways in a city in Zhejiang Province and explore the effect of radon exposure on chromosome aberration and micronuclei in the working population. MethodsA total of 55 vehicle control rooms of 55 stations affiliated to two different subway lines in a city were measured for one year; the 110 ticket offices and 55 security checkpoints from the same 55 stations were measured from 16 March to 14 June. The radon concentrations were compared by job types, subway lines, and seasons referring to Measurement methods for determination of radon in environmental air (HJ 1212-2021). Peripheral blood lymphocyte chromosome aberration and micronucleus analyses were conducted in 165 subway workers from monitoring sites for three different job types, then the influencing factors were analyzed. The detection methods were adopted from the standards of Test and assessment of chromosomal aberrations on occupational health examinations for radiation workers (GBZ/T 248-2014) and Standard for the method of micronucleus detection in lymphocytes on occupational health examination for radiation workers and exposure dose estimation (GBZ/T 328-2023). ResultsThe radon concentration range of the target subways in Zhejiang Province was 10-320 Bq·m−3, all lower than the national limit (≤400 Bq·m−3). The differences in radon radioactivity levels among different lines, job types, and time segments were statistically significant (P0.05). Chromosome aberration and micronuclei varied by age, subway station seniority, and smoking (P0.05). ConclusionThe radon concentration in the target subway system is at a normal level. The rates of chromosomal aberration and micronucleus formation vary by jobs, but both are lower than the corresponding national limits. Therefore, radon exposure has not yet caused outstanding health impact on the subway workers.

The aim of the present study was to examine the antihypertensive effect of black soybean peptides (BSP) and investigate the role of these peptides in ameliorating hypertension-induced intestinal damage and modulating gut microbiota. The findings demonstrated that BSP could significantly reduce the blood pressure of mice with diet-induced hypertension (P

The operation of a motor vehicle under the influence of alcohol poses a significant risk to the safety of the driver, passengers, and other road users. Electrooculographic (EOG) signal analysis can be used to understand the movements and behavior of the eyes while driving. In our study, we used smart glasses to collect EOG data from nine participants who used a driving simulator. Their level of alcoholic intoxication was simulated by drunk vision goggles at three different levels of inebriation (0, 1, 2, and 3‰ blood alcohol content). We used machine learning algorithms (decision trees, support vector machines, nearest-neighbor classifiers, boosted trees, bagged trees, subspace discriminant classifier, subspace k nearest-neighbor classifier, and RUSBoosted Trees) to analyze the data. The Bagged Trees achieved the highest accuracy of 79%. The most important features to detect simulated alcohol intoxication were the blink rate and the velocity of the saccade, a rapid simultaneous movement of both eyes in the same direction. Our study shows the potential of using smart glasses and machine learning for the automated detection of alcohol intoxication, even when alcohol consumption is simulated.

Viruses are implicated to play key roles as biogeochemical mediators and ecological drivers in freshwater ecosystems. However, the dynamics of viruses and host associations throughout the seasons and during blooming periods in eutrophic freshwater ecosystems remain poorly understood. From the water microbiomes of planktonic biomass from Lake Taihu, a large eutrophic freshwater lake in China that experiences annual Microcystis-dominated harmful algal blooms (HABs), we recovered 41,997 unique viral clusters spanning a wide taxonomic range, including 15,139 Caudovirales clusters targeting bacteria and 1,044 NCLDV clusters targeting eukaryotes. The viral community exhibited clear seasonal succession, driven primarily by microbial communities (particularly Cyanobacteria and Planctomycetes) and environmental factors (mainly nutrients and temperature). Host prediction revealed that viral infection had a more distinct impact on bacteria-driven nitrogen pathways than on phosphate cycling. HAB-induced variations in microbial composition and environmental conditions affected viral strategies including viral lifestyles, host range, and virus-encoded auxiliary metabolic genes (vAMGs) distributions. Viruses infecting Proteobacteria and Actinobacteria showed an enhanced lysogenic lifestyle and a narrower host range during HAB peak in summer, while viruses infecting Bacteroidota adopted an opposite strategy. Notably, vAMGs were most abundant before the HAB outbreak in spring, compensating for bacterial metabolic processes of their hosts such as carbohydrates metabolism, photosynthesis, and phosphate regulation. The findings highlight the intricate relationships between viruses, host microbes, and the bloom-associated environment, underscoring the important biochemical roles viruses play in eutrophic freshwater ecosystems.

Abstract Pancreatic cancer, characterized by its poor prognosis, exhibits a marked resistance to conventional chemotherapy and immunotherapy, underscoring the urgent need for more effective treatment modalities. In light of this, the present study is designed to assess the potential antineoplastic efficacy of a combined regimen involving tetrandrine, a plant-derived alkaloid, and autophagy inhibitors in the context of pancreatic cancer. Electron microscopy and immunoblots showed that tetrandrine promoted the formation of autophagosomes and the upregulation of LC3II and the downregulation of p62 expression, indicating that tetrandrine induced autophagy in pancreatic cancer cells. Western blot revealed that tetrandrine inhibited the phosphorylation of AKT and mTOR, as well as the expression of Bcl-2, while upregulating Beclin-1 expression. Moreover, tetrandrine promoted the transcription and protein expression of ATG7. Following the combination of autophagy inhibitors and tetrandrine, the apoptotic rate and cell death significantly increased in pancreatic cancer cells. Consistent results were obtained when ATG7 was silenced. Additionally, tetrandrine induced the generation of ROS, which was involved in the activation of autophagy and apoptosis. Further investigation revealed that upon autophagy inhibition, ROS accumulated in pancreatic cancer cells, resulting in decreased mitochondrial membrane potential and further induction of apoptosis. The results of treating subcutaneous xenograft tumors with a combination of tetrandrine and chloroquine validated that autophagy inhibition enhances the toxicity of tetrandrine against pancreatic cancer in vivo. Altogether, our study demonstrates that tetrandrine induces cytoprotective autophagy in pancreatic cancer cells. Inhibiting tetrandrine-induced autophagy promotes the accumulation of ROS and enhances its toxicity against pancreatic cancer.

Aiming to improve the gel property of egg white proteins, in this research, taking egg white protein (EWP) as the research object, the changes in texture, water-holding ratio, molecular forces, Fourier transform infrared chromatography, circular dichroism spectrum, particle size, potential, sulphydryl content, surface hydrophobicity, and scanning electron microscopy were analyzed to explore the mechanism and structural changes of heat-induced gel of EWP after the treatments of Ultra-high Pressure (UHP), Transglutaminase (TG) and Ultra-high Pressure Synergistic Transglutaminase (UTG). The results showed that the hardness, elasticity and water holding capacity of UHP-EWP, TG-EWP and UTG-EWP were all improved, and hydrophobic interaction was the main force to maintain gel. The α-helix content of UHP-EWP, TG-EWP and UTG-EWP decreased, while the β-fold content increased. The average particle size and absolute potential of UHP-EWP decreased, while the changes of TG-EWP and UTG-EWP were opposite. The content of free sulfhydryl groups in UHP-EWP, TG-EWP, and UTG-EWP increased, the content of total sulfhydryl groups decreased, and the surface hydrophobicity increased. The gel structure was more compact and smooth, and the flatness was improved. This research provides a theoretical basis and research ideas for the heat induced gel modification of EWP.

Abstract Background In recent decades, China has experienced a rapid increase in the number of elderly individuals and life expectancy, as well as industrialization, which is associated with an increased prevalence of Parkinson's disease (PD). However, inconsistent results have recently been reported. Therefore, this study aimed to investigate the prevalence and distribution characteristics of PD among individuals aged 45 years and older. Methods Using data from the China Health and Retirement Longitudinal Study (CHARLS), we attempted to estimate the prevalence of PD and its distribution characteristics among 19,034 individuals aged 45 years and older residing in 446 communities/villages within 27 provinces/autonomous regions/municipalities in mainland China. Cases were established based on a doctor's previous diagnosis. Crude and age-adjusted prevalence rates were calculated and stratified by age, sex, area of residence, education level, marital status, and geographic region. Logistic regression models were used to identify risk factors associated with PD. Results We identified 178 patients with PD among 19,034 residents aged 45 years and older. The crude prevalence was 0.94%, and the age-adjusted prevalence was 0.82% for individuals aged 45 years and older. The prevalence of PD increased with age (P

IntroductionMelatonin, a tryptophan-derived indoleamine metabolite with important roles in plant growth and defense, has recently been regarded as a new plant hormone. Maize is one of the most important cereal crops in the world. Although the melatonin receptor gene, ZmPMTR1, has already been identified, the genetic basis of melatonin biosynthesis in maize has still not been elucidated. Serotonin N-acetyltransferase (SNAT) is the enzyme that converts serotonin to N-acetylserotonin (NAS) or 5-methoxytryptamine (5MT) to melatonin in Arabidopsis and rice, but no SNAT encoding gene has been identified yet in maize.MethodsThe bioinformatics analysis was used to identify maize SNAT genes and the enzyme activity of the recombinant proteins was determined through in vitro assay. The expression levels of ZmSNAT1 and ZmSNAT3 under drought and heat stresses were revealed by public RNA-seq datasets and qRT-PCR analysis.ResultsWe first identified three maize SNAT genes, ZmSNAT1, ZmSNAT2, and ZmSNAT3, through bioinformatics analysis, and demonstrated that ZmSNAT2 was present in only eight of the 26 cultivars analyzed. We then determined the enzyme activity of ZmSNAT1 and ZmSNAT3 using their recombinant proteins through in vitro assay. The results showed that both ZmSNAT1 and ZmSNAT3 could convert serotonin to NAS and 5-MT to melatonin. Recombinant ZmSNAT1 catalyzed serotonin into NAS with a higher catalytic activity (Km, 8.6 mM; Vmax, 4050 pmol/min/mg protein) than ZmSNAT3 (Km, 11.51 mM; Vmax, 142 pmol/min/mg protein). We further demonstrated that the 228th amino acid Tyr (Y228) was essential for the enzymatic activity of ZmSNAT1. Finally, we revealed that the expression of ZmSNAT1 and ZmSNAT3 varied among different maize cultivars and different tissues of a plant, and was responsive to drought and heat stresses.DiscussionIn summary, the present study identified and characterized the first two functional SNAT genes in maize, laying the foundation for further research on melatonin biosynthesis and its regulatory role in plant growth and response to abiotic stresses.

Pregnancy-induced hypertension syndrome (PIH), a prevalent and critical condition, has garnered increasing attention due to its significant impact on maternal and fetal health outcomes. The conventional treatment approaches rely on magnesium sulfate and various antihypertensive drugs; however, the clinical efficacy of these treatments is limited, highlighting the need to explore alternative avenues for improvement. Recently, a growing number of clinical studies have investigated the use of Salvia-ligustrazine or Ligustrazine in combination with conventional therapy. A comprehensive synthesis and critical analysis of these studies is necessary to evaluate the efficacy and safety of Salvia-ligustrazine or Ligustrazine in treating PIH. We sought all articles published prior to December 2, 2023, from seven databases to identify randomized controlled trials (RCTs) that involved traditional Chinese medicine Salvia-ligustrazine or Ligustrazine in combination with Western medicines for the conventional treatment of PIH, according to predefined inclusion criteria. The studies were assessed using the Cochrane Risk of Bias tool (ROB2.0), and meta-analyses were conducted using Stata 15.0 statistical software. We analyzed 47 RCTs encompassing 4,517 patients. The results demonstrated that combining Salvia-ligustrazine or Ligustrazine with Western medications was more efficacious than using Western medications alone. This combination improved the overall response rate, reduced the incidence of adverse pregnancy outcomes for mothers and infants, and decreased the occurrence of side effects associated with PIH treatment. While we evaluated the efficacy of traditional Chinese medicine injections of Salvia-ligustrazine or Ligustrazine alongside conventional Western treatments, our conclusions must be considered provisional due to potential bias and the limited availability of RCTs.

Abstract Hydrogels are a class of highly absorbent and easily modified polymer materials suitable for use as slow-release carriers for drugs. Gene therapy is highly specific and can overcome the limitations of traditional tissue engineering techniques and has significant advantages in tissue repair. However, therapeutic genes are often affected by cellular barriers and enzyme sensitivity, and carrier loading of therapeutic genes is essential. Therapeutic gene hydrogels can well overcome these difficulties. Moreover, gene-therapeutic hydrogels have made considerable progress. This review summarizes the recent research on carrier gene hydrogels for the treatment of tissue damage through a summary of the most current research frontiers. We initially introduce the classification of hydrogels and their cross-linking methods, followed by a detailed overview of the types and modifications of therapeutic genes, a detailed discussion on the loading of therapeutic genes in hydrogels and their characterization features, a summary of the design of hydrogels for therapeutic gene release, and an overview of their applications in tissue engineering. Finally, we provide comments and look forward to the shortcomings and future directions of hydrogels for gene therapy. We hope that this article will provide researchers in related fields with more comprehensive and systematic strategies for tissue engineering repair and further promote the development of the field of hydrogels for gene therapy. Graphical abstract

Abstract Assessing the effectiveness of vegetation restoration along the Yangtze River shoreline and exploring its relationship with land use changes are imperative for providing recommendations for sustainable management and environmental protection. However, the impact of vegetation restoration post-implementation of the Yangtze River Conservation Project remains uncertain. In this study, utilizing Sentinel-2 satellite imagery and Dynamic World land use data from pre- (2016) and post- (2022) Yangtze River Conservation Project periods, pixel-based binary models, transition matrices, and geographically weighted regression models were employed to analyze the status and evolution of vegetation coverage along the Yangtze River shoreline. The results indicated that there had been an increase in the area covered by high and high-medium vegetation levels. The proportion of vegetation cover shifting to better was 4201.87 km2 (35.68%). Hotspots of vegetation coverage improvement were predominantly located along the Yangtze River. Moreover, areas witnessing enhanced vegetation coverage experienced notable land use changes, notably the conversion of water to crops (126.93 km2, 22.79%), trees to crops (59.93 km2, 10.76%), and crops to built area (59.93 km2, 10.76%). Notably, the conversion between crops and built area emerged as a significant factor influencing vegetation coverage improvement, with average regression coefficients of 0.68 and 0.50, respectively. These outcomes underscore the significance of this study in guiding ecological environmental protection and sustainable management along the Yangtze River shoreline.

Background: This study aimed to explore the longitudinal associations of rumination with suicidal ideation and suicide attempts in individuals with major depressive disorder (MDD). Methods: Participants were derived from the Depression Cohort in China study (DCC). Those who completed at least one follow-up visit during the 12 months were included in the analysis. Dimensions of rumination including brooding and reflection were each measured using five items of the Ruminative Responses Scale. Suicidal ideation was assessed using the Beck Scale for Suicide Ideation. Suicide attempts were also assessed and all were analyzed with generalized estimating equations. Results: Our final sample included 532 participants aged 18 to 59 years (mean [SD], 26.91 [6.94] years) consisting of 148 (27.8%) males and 384 (72.2%) females. After adjusting for temporal trend and potential confounders, individuals with higher levels of reflection were more likely to report suicidal ideation (AOR =1.11, 95% CI:1.01–1.22). However, no statistically significant association was found between brooding and suicidal ideation (AOR =1.06, 95% CI:0.96–1.17). Conversely, individuals with higher levels of brooding were more likely to report suicide attempts (AOR =1.13, 95% CI:1.02–1.24), while no statistically significant association was observed between reflection and suicide attempts (AOR =0.91, 95% CI:0.82–1.01). Conclusion: Rumination reflects a disturbance in cognitive emotional processing and manifests in different dimensions. Our findings suggest that high levels of reflection and brooding may be associated with a higher likelihood of having suicidal ideation and suicide attempts, respectively. However, it should be interpreted with caution, given that effect sizes are small.

Mimicking antibodies are described as autoantibodies with the “wrong” specificity, possessing both specificity and panreactivity. We report the case of a female patient with suspected hemolytic anemia in whom an autoantibody mimicking anti-Rh(e) specificity was found in both plasma and red blood cell samples. Mimicking antibodies are not usually identified in the clinic; however, it is still necessary to determine the specificity of mimicking antibodies to avoid antigen-positive blood transfusions and achieve maximum transfusion compatibility.

The mechanisms underlying the occurrence and development of atherosclerosis (AS) are diverse, among which endoplasmic reticulum stress (ERS) is an important mechanism that should not be overlooked. However, up to now, there has been no bibliometric study on the relationship between ERS and AS. To understand the research progress in ERS and AS, this paper conducted a statistical analysis of publications in this field using bibliometrics. A total of 1,035 records were retrieved from the Web of Science Core Collection. CiteSpace, VOSviewer, and the R package “bibliometric” were used to analyze the spatiotemporal distribution, countries, authors, institutions, journals, references, and keywords of the literature, and to present the basic information of this field through visualized maps, as well as determine the collaboration relationships among researchers in this field. This field has gradually developed and stabilized over the past 20 years. The current research hotspots in this field mainly include the relationship between ERS and AS-related cells, the mechanisms by which ERS promotes AS, related diseases, and associated cytokines, etc. Vascular calcification, endothelial dysfunction, NLRP3 inflammasome, and heart failure represent the frontier research in this field and are becoming new research hotspots. It is hoped that this study will provide new insights for research and clinical work in the field of ERS and AS.

IntoductionIdentification of specific metabolome and lipidome profile of patients with primary sclerosing cholangitis (PSC) is crucial for diagnosis, targeted personalized therapy, and more accurate risk stratification.MethodsNuclear magnetic resonance (NMR) spectroscopy revealed an altered metabolome and lipidome of 33 patients with PSC [24 patients with inflammatory bowel disease (IBD) and 9 patients without IBD] compared with 40 age-, sex-, and body mass index (BMI)-matched healthy controls (HC) as well as 64 patients with IBD and other extraintestinal manifestations (EIM) but without PSC.ResultsIn particular, higher concentrations of pyruvic acid and several lipoprotein subfractions were measured in PSC in comparison to HC. Of clinical relevance, a specific amino acid and lipid profile was determined in PSC compared with IBD and other EIM.DiscussionThese results have the potential to improve diagnosis by differentiating PSC patients from HC and those with IBD and EIM.

Abstract Background In solid-predominantly invasive lung adenocarcinoma (SPILAC), occult lymph node metastasis (OLNM) is pivotal for determining treatment strategies. This study seeks to develop and validate a fusion model combining radiomics and deep learning to predict OLNM preoperatively in SPILAC patients across multiple centers. Methods In this study, 1325 cT1a-bN0M0 SPILAC patients from six hospitals were retrospectively analyzed and divided into pathological nodal positive (pN+) and negative (pN-) groups. Three predictive models for OLNM were developed: a radiomics model employing decision trees and support vector machines; a deep learning model using ResNet-18, ResNet-34, ResNet-50, DenseNet-121, and Swin Transformer, initialized randomly or pre-trained on large-scale medical data; and a fusion model integrating both approaches using addition and concatenation techniques. The model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). Results All patients were assigned to four groups: training set (n = 470), internal validation set (n = 202), and independent test set 1 (n = 227) and 2 (n = 426). Among the 1325 patients, 478 (36%) had OLNM (pN+). The fusion model, combining radiomics with pre-trained ResNet-18 features via concatenation, outperformed others with an average AUC (aAUC) of 0.754 across validation and test sets, compared to aAUCs of 0.715 for the radiomics model and 0.676 for the deep learning model. Conclusion The radiomics-deep learning fusion model showed promising ability to generalize in predicting OLNM from CT scans, potentially aiding personalized treatment for SPILAC patients across multiple centers.

In order to improve the characteristics of uneven melting in the melting process of the horizontal latent heat energy storage system, the triplex-tube latent heat energy storage unit is taken as the research object, and the flip mechanism is applied to its melting process. Numerical simulation is used for the research, and the numerical model is verified by experimental data. The results show that under different dimensionless times, the melting performance of the unit can be significantly improved by a single flip. When the dimensionless time is 0.4576, it is found that the total melting time of the unit is reduced by 16.17 %, the average heat absorption rate is increased by 14.7 %, but the total heat energy absorption is reduced by 3.85 %. The results show that the addition of a flip can effectively shorten the melting time and increase the heat absorption rate, but it has a negative effect on the total heat absorption in one melting cycle. Moreover, through the comparison of dynamic flow rate, dynamic temperature response, and temperature interval, it is shown that the addition of flip effectively reduces the negative influence of the hard-to-melt zone on the melting performance of the unit during the melting process. The flip mechanism reduces the proportion of high-temperature phase change material in the melting process and makes the melting process more uniform.

Plant height and leaf morphology are considered complex agronomy traits; both are significantly related to nutrient utilization, lodging resistance, and photosynthetic efficiency, which ultimately affect biomass and yield. However, the molecular mechanism of leaf morphogenesis is still unclear. WOX is a group of plant-specific transcription factor families that regulate growth and development, cell division, and differentiation in plants. In the present study, we identified and characterized the m-876 mutant in barley (Hordeum vulgare L.), which exhibited an extreme reduction in leaf width and plant height. Using a map-based cloning strategy, the m-876 mutant was narrowed down to an 11.4 Mb genomic interval on the long arm of chromosome 5. By analyzing the gene annotation information and nucleotide sequences, we found that HvWOX3A (HORVU.MOREX.r3.5HG0467090) had a G-to-A substitution at the second exon in the m-876 mutant, resulting in a change of the coding amino acid from Tryptophan to a premature stop codon at the 200th amino acid position. Remarkably, the mutation of the HvWOX3A gene leads to changes in gene expression in the m-876 mutant. Collectively, our results indicate that the loss function of the HORVU.MOREX.r3.5HG0467090 gene might be responsible for the phenotypic variation in barley mutants.

Abstract Background Umbelliprenin is a sesquiterpene coumarin isolated from Artemisia absinthium L. and shows antitumor effects in various cancers by inducing apoptosis. However, the antitumor effect of umbelliprenin in human pancreatic cancer has not been clarified. Methods The antitumor effects were determined by MTT and AnnexinV/PI double staining assay in vitro and xenograft mice in vivo. Autophagy was determined via immunofluorescence analysis. Apoptotic or autophagic related proteins were measured by immunoblotting. The pancreatic cancer cell stemness were determined by mammosphere formation and ALDEFLUOR assay. Results It revealed that umbelliprenin inhibited pancreatic cancer cell proliferation in vitro and pancreatic cancer tumor growth in vivo. Moreover, umbelliprenin induced pancreatic cancer cell BxPC3 apoptosis and autophagy as evidenced by upregulated apoptosis and autophagy‐ related protein expression (p

Background: Breast cancer has the highest prevalence among all cancers in women globally. The classification of histopathological images in the diagnosis of breast cancers is an area of clinical concern. In computer-aided diagnosis, most traditional classification models use a single network to extract features, although this approach has significant limitations. Moreover, many networks are trained and optimized on patient-level datasets, ignoring lower-level data labels. Methods: This paper proposed a deep ensemble model based on image-level labels for the binary classification of breast histopathological images of benign and malignant lesions. First, the BreaKHis dataset was randomly divided into training, validation, and test sets. Then, data augmentation techniques were used to balance the numbers of benign and malignant samples. Third, based on their transfer learning performance and the complementarity between networks, VGG16, Xception, ResNet50, and DenseNet201 were selected as base classifiers. Results: In a ensemble network model with accuracy as the weight, the image-level binary classification achieved an accuracy of 98.90%. To verify the capabilities of our method, it was experimentally compared with the latest transformer and multilayer perception (MLP) models on the same dataset. Our ensemble model showed a 5%–20% advantage, emphasizing its far-reaching abilities in classification tasks. Conclusions: This research focuses on improving the performance of a classification model with an ensemble algorithm. Transfer learning has an essential role in classification of small datasets, improving training speed and accuracy. Our model may outperform many existing approaches with respect to accuracy and has applications in the field of auxiliary medical diagnosis.

Abstract Epitaxial growth is one of the most commonly used strategies to precisely tailor heterostructures with well-defined compositions, morphologies, crystal phases, and interfaces for various applications. However, as epitaxial growth requires a small interfacial lattice mismatch between the components, it remains a challenge for the epitaxial synthesis of heterostructures constructed by materials with large lattice mismatch and/or different chemical bonding, especially the noble metal-semiconductor heterostructures. Here, we develop a noble metal-seeded epitaxial growth strategy to prepare highly symmetrical noble metal-semiconductor branched heterostructures with desired spatial configurations, i.e., twenty CdS (or CdSe) nanorods epitaxially grown on twenty exposed (111) facets of Ag icosahedral nanocrystal, albeit a large lattice mismatch (more than 40%). Importantly, a high quantum yield (QY) of plasmon-induced hot-electron transferred from Ag to CdS was observed in epitaxial Ag-CdS icosapods (18.1%). This work demonstrates that epitaxial growth can be achieved in heterostructures composed of materials with large lattice mismatches. The constructed epitaxial noble metal-semiconductor interfaces could be an ideal platform for investigating the role of interfaces in various physicochemical processes.

Stressful life events (SLEs) and suicidal ideation (SI) are prevalent in persons with major depression disorder (MDD). Less is known about the underlying role of insomnia symptoms in the association between SLEs and SI. This three-wave prospective cohort study sought to investigate the longitudinal association among SLEs, insomnia symptoms, and SI in persons with MDD. The study population included 511 persons with MDD (mean [SD] age, 28.7 [6.7] years; 67.1% were females). Generalized estimated equations (GEEs) were utilized to explore prospective association among exposure of SLEs, insomnia symptoms, and SI. Additionally, a structural equation model (SEM) was employed to estimate the longitudinal mediating effect of insomnia symptoms in the relationship between SLEs and SI. Our study demonstrated that cumulative SLEs were determined to be longitudinally associated with SI in persons with MDD. We further observed that the association between SLEs and SI was significantly mediated by insomnia symptoms. Clinicians assessing persons with MDD, especially those with the history of SLE, could carefully evaluate and promptly treat insomnia symptoms as part of personalized assessment of their depressive illness, thereby achieving early prevention and intervention for suicidal behaviors in persons with MDD.

During shield construction in underground spaces, synchronous grouting slurry is poured between the surrounding rock and tunnel lining to ensure stability. For synchronous grouting slurries, few studies have investigated the relationship between the rheological parameters and physical properties, grout-segregation mechanism, and anti-segregation performance. Therefore, we explored the relationships between the slurry rheological parameters, segregation rate, and bleeding rate. Cement, sand, fly ash, and bentonite were used to prepare the slurry, and the effects of different polycarboxylate water-reducing agents and dispersible latex powder dosages were studied. The rheological parameters of 16 groups of uniformly designed slurries were tested, and the data were fit using the Herschel–Bulkley model. The optimal mix ratio lowered the slurry segregation rate, and its rheological behaviour was consistent with the Herschel–Bulkley fluid characteristics. High-yield-shear-stress synchronous grouting slurries with high and low viscosity coefficients were less likely to bleed and segregate, respectively. The optimised slurry fluidity, 3 h bleeding rate, 24 h bleeding rate, segregation rate, coagulation time, and 28 days compressive strength were 257.5 mm, 0.71%, 0.36%, 3.1%, 6.7 h, and 2.61 MPa, respectively, which meet the requirements of a synchronous grouting slurry of shield tunnels for sufficiently preventing soil disturbance and deformation in areas surrounding underground construction sites.

With the increasing of the installed capacity of wind power, the condition monitoring and maintains technique is becoming more important. Wind Turbines (WT) gearbox is one of the key wind power components as it plays the role of power transmission and speed regulation. Towards this, a number of scholars have pay attention to the fault diagnosis of WT gearbox. The efficiency of Machine Learning (ML) algorithms is highly correlated with signal type, data quality, and extracted features employed. The implementation of ML techniques has proven to be advantageous in simplifying the comprehension prerequisites for fault diagnosis technology concerning fault mechanisms. More and more current studies predominantly concentrate on the utilization and fine-tuning of ML algorithms, while providing limited insights into the features of the acquired data. Therefore, it is necessary to review the research in recent years from the perspective of the combination of feature extraction and ML algorithms, and provide a detailed direction for future WT gearbox fault diagnosis technology research. In this paper, data processing algorithms and typical fault diagnosis methods based on ML methods for WT gearbox are reviewed. For the using of ML method in WT gearbox fault diagnosis, the data prepared for training is very important. The paper firstly reviewed the data analysing method which will support the ML method. The data analysing methods include data acquisition, data preprocessing and feature extraction method. Feature extraction plays a pivotal role in the realm of gearbox fault diagnosis, as it serves as the essence of effective detection. This review will primarily focus on exploring methods that enable the utilization of efficient features in combination with ML techniques to achieve accurate gearbox fault diagnosis. Then typical ML method for WT gearbox fault diagnosis are carefully reviewed. Moreover, some prospects for future research directions are discussed in the end.

The impact of the enhanced heat transfer performance of longitudinal fins on the entire process of melting and solidification in a phase change heat storage unit is investigated through experiments and numerical simulations in this paper. The position and structure of the longitudinal fins are optimized by using the response surface method while ensuring that the total volume of the heat storage medium remains unchanged. Studies have identified that some challenging zones in melting and solidification significantly impact the heat transfer of the entire heat storage cycle. Specifically, the challenging zone in melting primarily exists in the lower part of the unit during the charing process, while the challenging zone in solidification is mainly distributed around the unit during the discharging process. Through optimization, the optimized structure (fin spacing is 22.5 mm, fin width is 6.05 mm) can reduce the charging and discharging time by 16.94 % and 45.90 %, respectively. Additionally, the round trip time is significantly reduced by 39.19 %, and the mean heat absorption rate during the melting process is enhanced by 20.28 %. Moreover, the mean heat release rate during solidification is enhanced by 80.23 %.

Ginseng peptide (GP) (100, 200, 400 mg/kg bw) lowered blood glucose levels, explored the relationship between GP and gut microbiota-based hypoglycemic effects. GP significantly reduced fasting blood glucose levels (25.38–13.37 mM), improved insulin resistance (IR) (9.78–5.02), considerably increased liver glycogen content (64.71–97.95 mg/g), glycolytic and gluconeogenesis enzyme activities in T2DM mice, significantly reduced free fatty acids (1.65–0.93 mM), triglycerides (1.55–0.66 mM), total cholesterol (14.75–5.43 mM), and low-density lipoprotein (4.12–2.36 mM) in the serum, significantly increased high-density lipoprotein levels (6.20–17.44 mM) to improve lipid metabolism disorders. According to colonic 16S rDNA sequencing results, GP-H regulated gut microbiota disorders and short chain fatty acid metabolism. Western blot analysis showed that GP could regulate glycogen synthesis, gluconeogenesis, and glucose transport by activating IRS-1/PI3K/Akt and AMPK signaling pathways and improve IR by inhibiting the mitochondrial apoptosis signaling pathway.

Rapidly global urbanization and economic growth in the past several decades have resulted in a sharp contraction of arable areas worldwide. However, food supply requirements are quickly increasing due to higher living standards and larger populations. Therefore, food crises are still a major threat to human society. The conflict between farmland areas and the increasing need for essential supplies is becoming acuter in China. Therefore, we suggest that a novel strategy would address the issue, in which temporal and spatial arrangement of wheat sowing dates would be highly focused.

Abstract The exchange bias (EB) effect plays an undisputed role in the development of highly sensitive, robust, and high-density spintronic devices in magnetic data storage. However, the weak EB field, low blocking temperature, as well as the lack of modulation methods, seriously limit the application of EB in van der Waals (vdW) spintronic devices. Here, we utilized pressure engineering to tune the vdW spacing of the two-dimensional (2D) FePSe3/Fe3GeTe2 heterostructures. The EB field (H EB, from 29.2 mT to 111.2 mT) and blocking temperature (T b, from 20 K to 110 K) are significantly enhanced, and a highly sensitive and robust spin valve is demonstrated. Interestingly, this enhancement of the EB effect was extended to exposed Fe3GeTe2, due to the single-domain nature of Fe3GeTe2. Our findings provide opportunities for the producing, exploring, and tuning of magnetic vdW heterostructures with strong interlayer coupling, thereby enabling customized 2D spintronic devices in the future.

Abstract Background We aimed to verify the role of hENT1 as a prognostic predictor for patients with resectable pancreatic ductal adenocarcinoma (PDAC) who underwent radical resection followed by intra-arterial infusion of gemcitabine-based regimen. Methods We collected surgical samples from 102 patients with resectable PDAC who received radical resection followed by intra-arterial infusion of gemcitabine-based regimen. The hENT1 expression with the help of immunohistochemistry was conducted using formalin-fixed and paraffin embedded tissues. The Kaplan–Meier analyses and Cox regression were used to evaluate the mortality hazard associated with the discrepancy between strong and weak of hENT1 expression. Patients’ clinical and pathological characteristics were compared between the two groups, then the role of hENT1 as a prognostic predictor was further explored. Results A total of 102 patients were included to assess the hENT1 expression. 50 patients were classified into high hENT1 expression group, the other 52 patients were attributed into low hENT1 expression group. High hENT1 expression was related to a significantly improved overall survival (OS) (p = 0.014) and disease-free survival (DFS) (p = 0.004). Both univariate (p = 0.001) and multivariate analyses (p

Digital X-ray radiography is widely used in clinical diagnosis. High quality chest X-ray is conducive to the accurate diagnosis of diseases by clinicians. However, the quality assessment of the chest X-ray images mainly depends on the subjective evaluation of doctors, and the results are influenced by the skill level and experience of the evaluators, involving many issues such as heavy workload and various uncertain factors in such subjective judgment. In this paper, we propose a chest X-ray quality assessment method that combines image-text contrastive learning with medical domain knowledge fusion. Based on pretraining the model from contrastive text-image pairs, large-scale real clinical chest X-ray and diagnostic report text information are fused, and the model is fine-tuned to achieve cross domain transfer learning. While improving the prediction accuracy of the algorithm, the cost of massive sample data annotation is avoided. The local visual patch features of the X-ray images are aligned with multiple text features to ensure that the visual features contain more fine-grained image information. Theoretical analysis and experimental results show that the contrastive learning algorithm based on the fusion of triplet information in medical knowledge graph and chest X-ray multi-modal data has achieved good performance in terms of accuracy. In addition, the method proposed in this paper can be easily extended to complete other tasks such as medical image multi-lesion segmentation and disease progression prediction.

Pancreatic cancer is one of the leading causes of cancer-related mortality in both developed and developing countries. The incidence of pancreatic cancer in China accounts for about a quater of the global incidence, and the epidemiological characteristics and therapeutic strategies differ due to social, economic, cultural, environmental, and public health factors. Non-domestic guidelines do not reflect the clinicopathologic characteristics and treatment patterns of Chinese patients. Thus, in 2018, the Chinese Society of Clinical Oncology (CSCO) organized a panel of senior experts from all sub-specialties within the field of pancreatic oncology to compile the Chinese guidelines for the diagnosis and treatment of pancreatic cancer. The guidelines were made based on both the Western and Eastern clinical evidence and updated every one or two years. The experts made consensus judgments and classified evidence-based recommendations into various grades according to the regional differences, the accessibility of diagnostic and treatment resources, and health economic indexes in China. Here we present the latest version of the guidelines, which covers the diagnosis, treatment, and follow-up of pancreatic cancer. The guidelines might standardize the diagnosis and treatment of pancreatic cancer in China and will encourage oncologists to design and conduct more clinical trials about pancreatic cancer.

Objective To analyze the specificity of HLA class-Ⅰ antibody in the patients received HLA-matched platelet transfusions and estimate the relative immunogenicity of HLA-Ⅰ antigens. Methods The samples from 96 patients who suffered from platelet transfusion refractorines(PTR) and applied for transfusion with genotype-matched platelet were collected. The specificity of HLA I antibody was detected by Luminex technique, and the antibody expression level was analyzed according to MFI. The mismatch rate of HLA antigen and relative immunogenicity of the population were estimated according to the allele frequency distribution of HLA-A and B loci as well as the yielding frequency of antibody. Results HLA-Ⅰ antibodies were detected in all 96 patients, with varied species of antibodies. The average positive yielding rates of antibodies corresponding to HLA-A, -B and -C magnetic bead coated antigens (97 in total) were 0.38, 0.47 and 0.28, respectively. Among the HLA-A and -B loci in the Zhejiang population, HLA-A2, A11, A24 and HLA-B60, B46, B58 were the antigens with higher frequency, and their relative immunogenicity was 0.403, 0.283, 0.342, and 0.100, 0.067, 0.178, respectively. Conclusion The specificity of HLA-Ⅰ antibodies in PTR patients is different, which confirms that the relative immunogenicity differs by HLA-A and -B antigens.

Objective To explore the influence of anti-HLA-Ⅰ with different mean fluorescence intensity (MFI) on the efficacy of HLA-A and -B gene matching platelet transfusion, so as to provide scientific data for clinical platelet gene matching transfusion strategy. Methods A total of 81 PTR patients had applied for HLA-Ⅰgene matched platelets from the platelet gene database established by our laboratory, and 28 (MFI 0.05), 17.36±7.63 (P>0.05) and -0.77±2.30 (P

Abstract Background Preoperative prediction of severe cholecystitis (SC), including acute gangrenous cholecystitis (AGC) and acute purulent cholecystitis (APC), as opposed to acute exacerbation of chronic cholecystitis (ACC), is of great significance, as SC is associated with high mortality rate. Methods In this study, we retrospectively investigated medical records of 114 cholecystitis patients, treated in Shanghai No. 6 People’s Hospital from February 2009 to July 2020. Gallbladder wall thickness (GBWT), indexes of blood routine examination, including white blood cell (WBC), alkaline phosphatase (ALP), the percentage of neutrophil, alanine transaminase (ALT), aspartate aminotransferase (AST), fibrinogen (FIB), gamma-glutamyl transferase, prothrombin time and total bilirubin were evaluated. One-way analysis of variance (ANOVA) was used to evaluate significant differences between a certain kind of SC and ACC to select a prediction index for each kind of SC. Receiver operating characteristic (ROC) curve analysis was conducted to identify the prediction effectiveness of these indexes and their optimal cut-off values. Results Higher WBC and lower ALP were associated with AGC diagnosis (P

ROP (Rate of Penetration) is a comprehensive indicator of the rock drilling process and how efficiently predicting drilling rates is important to optimize resource allocation, reduce drilling costs and manage drilling hazards. However, the traditional model is difficult to consider the multiple factors, which makes the prediction accuracy difficult to meet the real drilling requirements. In order to provide efficient, accurate and comprehensive information for drilling operation decision-making, this study evaluated the applicability of four typical regression algorithms based on machine learning for predicting pore pressure in Troll West field, namely SVR (Support Vector Regression), Linear regression, Regression Tree and Gradient Boosting regression. These methods allow more parameters input. By comparing the prediction results of these typical regression algorithms based on R 2 (R-Square), explained variance, mean absolute error, mean squared error, median absolute error and other performance indicators, it was found that each method predicted different results, among which Gradient Boosting regression has the best results, their prediction accuracy is high and the error is very low. The prediction accuracy of these methods is positively correlated with the proportion of the training data set. With the increase of logging features, the prediction accuracy is gradually improved. In the prediction of adjacent wells, the ROP prediction methods can achieve a certain prediction effect, which shows that this method is suitable for ROP prediction in Troll West field.

Due to the intermittency and discontinuity of solar energy, thermal energy storage (TES) using phase change materials (PCMs) is generally required to ensure stable operation in solar heating systems (SHS) during winter. This paper presents the design of a TES unit with different horizontal metal foam filling ratios (60%–100%), and simulations of thermal characteristics, such as complete melting time and heat storage capacity by numerical method. Based on the heating demands of an office building in Xi'an, TES units are combined in parallel and economic indexes are calculated based on static evaluation method, including initial investment and investment payback period. Novelty, the contribution of gradient microstructure to the phase transition process is evaluated from thermophysical properties and economy. Results show that the TES unit with a filling ratio of 90% possesses the shortest complete melting time of 5310 s, which is 87.56% shorter than that of a TES unit with pure PCM. Finally, economic assessments of the engineering application of the partially filled metal foam structure are carried out, and it is determined that the SHS with the TES system of 90% filling ratio requires the least number of 548 TES units, with a payback period of three heating seasons.

With the continuing advancement in China’s exploration and development technologies of shale gas resources, there was a significant increase in shale gas oil-based drilling cuttings. In this paper, oil-based drilling cutting pyrolysis residues (ODCPRs) was used as the main raw material for preparing lightweight and high-strength building ceramsites to eliminate the environmental risks and recycle industrial waste. Firstly, orthogonal experiments were used to study the influences of raw material composition, preheating temperature, preheating time, sintering temperature, and sintering time on the properties of building ceramsites. From the results, the sintering temperature and the content of ODCPRs were discovered to be the key factors affecting the sintering process of ceramsites. Secondly, the influences of sintering temperature and heating rate on the properties of building ceramists were further explored to find the optimum sintering conditions. When the content of ODCPRs in the ceramsite was set to be 50%, the obtained building ceramsites presented excellent properties with particle compressive strength of 6.31 MPa, bulk density of 575.11 kg/m3, apparent density of 1097.24 kg/m3, and the water absorption of 1.89%. Finally, XRD, SEM, TG-DSC, and heavy metal leaching experiments were comprehensively conducted to analyze the composition structure variation and sintering mechanism of the building ceramsite. This paper presents an approach for the recycling, utilization, and disposal of oil-based drilling cuttings in the oil field waste management.

Objective To analyze the specificity and Eplets of HLA allele-specific antibody in patients with platelet transfusion refractoriness (PTR). Methods HLA-A and B genotypes were detected by PCR-SBT, and HLA-Ⅰ antibodies in patients′ serum were detected by Luminex single antigen beads coating method. IPD-IMGT/HLA Database was used to find the differential amino acids of allele-specific antibodies, and HLA Eplet database was used to analyze the registry Eplets. Results HLA allele-specific antibodies were found in 12 out of 82 patients with PTR.After sequence alignment, a total of 18 differential amino acids were found, such as 19E>19K, 166D>116E, 167G>167W and so on. Among these differential amino acids, 16 registry Eplets were retrieved such as 19E>19K, 95I>95L, 113YD>113HD and so on.The amino acid substitution of 166DG>166EW, 70Q>70H, 67S>67Y, 94I>94T, 82LR>82RG, and 211G>211A may form new Eplets that have not been registered.The antigens of A11, A24, B15, B27 and B38 can be further subdivided into HLA narrow specific antigens. Conclusion It was found that there were HLA allele-specific antibodies in patients with PTR, suggesting that high-resolution typing of HLA-A, B should be carried out for these patients and platelet donors in HLA compatible transfusion of PTR.

Abstract Based on the energy flow analysis method, this paper establishes the relationship between the heat accumulator and the thermal system from the perspective of heat transfer. Different types of heat accumulators are converted into different equivalent models based on energy flow, the existing sneak circuit analysis methods based on energy flow are optimized, and the starting point and end point of path search are redefined. The energy flow‐based correlation method proposed in this paper is applied to a system with two different types of heat accumulators. The results show that the sneak circuit analysis method based on energy flow proposed in this paper can search for more paths and discover new sneak circuits on the basis of the original method. Therefore, the new method is feasible and effective.

Abstract Increasing both clean water and green energy demands for survival and development are the grand challenges of our age. Here, we successfully fabricate a novel multifunctional 3D graphene-based catalytic membrane (3D-GCM) with active metal nanoparticles (AMNs) loading for simultaneously obtaining the water purification and clean energy generation, via a “green” one-step laser scribing technology. The as-prepared 3D-GCM shows high porosity and uniform distribution with AMNs, which exhibits high permeated fluxes (over 100 L m−2 h−1) and versatile super-adsorption capacities for the removal of tricky organic pollutants from wastewater under ultra-low pressure-driving (0.1 bar). After adsorption saturating, the AMNs in 3D-GCM actuates the advanced oxidization process to self-clean the fouled membrane via the catalysis, and restores the adsorption capacity well for the next time membrane separation. Most importantly, the 3D-GCM with the welding of laser scribing overcomes the lateral shear force damaging during the long-term separation. Moreover, the 3D-GCM could emit plentiful of hot electrons from AMNs under light irradiation, realizing the membrane catalytic hydrolysis reactions for hydrogen energy generation. This “green” precision manufacturing with laser scribing technology provides a feasible technology to fabricate high-efficient and robust 3D-GCM microreactor in the tricky wastewater purification and sustainable clean energy production as well.

In the complex and dynamic processes of replication, transcription, and translation of DNA molecules, a large number of replication errors or damage can occur which lead to obstacles in the development process of germ cells and result in a decreased reproductive rate. DNA damage repair has attracted widespread attention due to its important role in the maintenance and regulation of germ cells. This study reports on a systematic review of the role and mechanism of DNA damage repair in germline development. First, the causes, detection methods, and repair methods of DNA damage, and the mechanism of DNA damage repair are summarized. Second, a summary of the causes of abnormal DNA damage repair in germ cells is introduced along with common examples, and the relevant effects of germ cell damage. Third, we introduce the application of drugs related to DNA damage repair in the treatment of reproductive diseases and related surgical treatment of abnormal DNA damage, and summarize various applications of DNA damage repair in germ cells. Finally, a summary and discussion is given of the current deficiencies in DNA damage repair during germ cell development and future research development. The purpose of this paper is to provide researchers engaged in relevant fields with a further systematic understanding of the relevant applications of DNA damage repair in germ cells and to gain inspiration from it to provide new research ideas for related fields.

HPV (Human papillomavirus) affects 600,000 people worldwide each year. Almost all cervical cancers are associated with a past HPV infection. In particular, the positivity to the high-risk type HPV16 is detected in most of the invasive cervical cancers. FDA has approved prophylactic vaccines that protect against new HPV16 infections, but do not induce immunity in those patients with established infections or neoplasms. To date, no therapeutic vaccine targeting HPV16-associated lesions has been authorized. We have developed an mRNA-based vaccine against the HPV16 late oncoproteins E6 and E7, which are abundantly and exclusively expressed in high-grade squamous intraepithelial lesions (HSILs), a stage of the cervical disease that precedes the progression to carcinoma. Our in vitro and in vivo studies demonstrated that the translated mRNA is functional and elicits an antigen-specific adaptive immune response. Upon immunization with the vaccine, mice with HPV16+ lesions exhibited tumor growth inhibition, extension of lifespan, and development of a protective immune memory. In light of these results and the remarkable clinical success of mRNA vaccines against SARS-CoV2, we believe that our mRNA-based therapeutic vaccine has the potential to offer a non-invasive treatment alternative to the current standard of care for HPV16+ HSILs.

The main purpose of this study was to isolate and identify Angiotensin Converting Enzyme (ACE) inhibitory peptides (IPs) from black soybean protein hydrolysate and compare the activity between single and mixed peptides. Black soybean protein was hydrolyzed, desalted, and separated by size-exclusion ultrafiltration and G-15 Sephadex column. A total of 31 peptides were identified by nano-HPLC-ESI-MS/MS. 7 peptides were screened by molecular docking, only three were ACEIPs after synthetized and bioactive verified, namely KDFPPR (IC50 = 7.91 ± 0.27 mg/mL), VVPPGHPF (IC50 = 12.13 ± 0.38 mg/mL) and DTFPYPR (IC50 = 10.69 ± 0.28 mg/mL), 3 peptides all show mixed-type mode of enzyme inhibition. The synergistic effect on the inhibition of ACE activity was shown among the three ACEIPs. The other four peptides play an auxiliary role in the activity of three ACEIPs mixtures. This study showed that black soybean protein is a reliable source of ACEIPs and the synergism of natural mixed peptides may play an important role in the activity of bioactive peptides.