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Abstract Human genetics analysis has identified many noncoding SNPs associated with diabetic traits, but whether and how these variants contribute to diabetes is largely unknown. Here, we focus on a noncoding variant, rs6048205, and report that the risk-G variant impairs the generation of PDX1+/NKX6-1+ pancreatic progenitor cells and further results in the abnormal decrease of functional β cells during pancreatic differentiation. Mechanistically, this risk-G variant greatly enhances RXRA binding and over-activates FOXA2 transcription, specifically in the pancreatic progenitor stage, which in turn represses NKX6-1 expression. Consistently, inducible FOXA2 overexpression could phenocopy the differentiation defect. More importantly, mice carrying risk-G exhibit abnormal pancreatic islet architecture and are more sensitive to streptozotocin or a high-fat diet to develop into diabetes eventually. This study not only identifies a causal noncoding variant in diabetes susceptibility but also dissects the underlying gain-of-function mechanism by recruiting stage-specific factors.

Abstract Background In research to improve the quality of transgenic crops, it is often necessary to introduce multiple functionally related genes into recipient plants simultaneously to improve crop genetic traits effectively. Compared with unidirectional promoters, bidirectional promoters simultaneously regulate the expression of multiple genes and improve the efficiency of biotechnology. Therefore, in this study, bidirectional gene pairs were systematically analyzed in Gossypium hirsutum TM-1, and the structure, function and evolutionary relationships of the bidirectional genes were analyzed. The endogenous bidirectional promoters of cotton were mined, and their specific regulatory elements and biological functions were explored to provide useful promoter resources and a theoretical basis for cultivating new cotton germplasms with excellent fiber quality. Results Using an improved search model, a total of 1,383 bidirectional transcript pairs were identified in the Gossypium hirsutum TM-1 genome, and their gene structure and functional annotations were systematically analyzed. Thirty bidirectional intergenic sequences were randomly screened for promoter activity analysis via a transient expression system, and 25 intergenic sequences were found to have bidirectional promoter activity. Comparative analysis of the bidirectional gene profiles of the four cotton subspecies revealed that these subspecies presented abundant bidirectional gene pairs with high homology and that the bidirectional genes in the cotton subspecies were more similar in terms of their molecular functions, cellular components and biological processes. In addition, parallel analysis of bidirectional genes in dicotyledons and monocotyledons revealed that abundant bidirectional gene pairs exist in different species. Although the total number of orthologous bidirectional genes was similar, there was a significant difference in the number of orthologous bidirectional gene pairs between dicotyledons and monocotyledons. This evolutionary analysis of the function and structure of homologous bidirectional gene pairs in different varieties and different subspecies of the same species revealed potential pathways by which these gene pairs originated, which may be necessary for the evolution of a new species. Conclusion In this study, many bidirectional gene pairs in Gossypium hirsutum TM-1 were identified using computer programming, and systematic analysis was conducted to explore their functions and evolutionary relationships. In addition, the promoter activity of the bidirectional intergenic sequences was verified. The combination of computer programming screening, experimental validation and other methods is expected to provide preferred bidirectional promoters for transgenic breeding work via multigene cotransformation methods, and this information is valuable for genetic engineering research and applications.

Introduction Sentinel lymph node biopsy (SLNB) is a standard procedure for patients with clinically assessed negative axillary lymph nodes (cN0) during early-stage breast cancer (EBC). However, the majority of EBC patients have a negative pathological confirmation of the sentinel lymph node (SLN), and axillary surgery is inevitably associated with postoperative complications. Considering that SLNB has no therapeutic benefit, this trial aims to determine the safety of omitting SLNB in patients with cN0 early invasive breast cancer.Methods and analysis The OMSLNB trial is a prospective, single-arm, non-inferiority, phase II, open-label study design involving female breast cancer patients with a tumor of ≤3 cm in diameter, who are considered axillary lymph-node-negative based on two or more radiological examinations, including axillary lymph node ultrasonography. Eligible patients will avoid axillary surgery but will undergo breast surgery, which is not limited to breast-conserving surgery. The trial begins in 2023 and is scheduled to end in 2027. The primary endpoint is 3 year invasive disease-free survival (iDFS). The secondary endpoints include the incidence of breast cancer-related lymphoedema, patient-reported outcomes, locoregional recurrence, local recurrence and regional recurrence. It is expected that the 3 year iDFS in patients undergoing SLNB is about 90%, combined with a non-inferiority cut-off of 5%, 80% power, 95% CIs, 0.05 test level, and 10% loss to follow-up rate, the planned enrollment is 311 patients. All enrolled patients will be included in the intention-to-treat analysis.Ethics and dissemination This trial was approved by the Ethics Committee of the First Affiliated Hospital of Nanjing Medical University (No.2023-SR-193). All participants must provide written informed consent to be eligible. The protocol will be described in a peer-reviewed manuscript, and the results will be published in scientific journals and/or at academic conferences.Trial registration number NCT05935150.

Understanding the complex influencing factors of soil erosion is critical for maintaining regional ecological security. The revised wind erosion equation (RWEQ) and partial least squares regression (PLSR) model were used to reveal the primary factors affecting soil erosion. Based on the results of the RWEQ model, the wind erosion area was 8,439.3 km2 in 2018, accounting for 54.3% of the total planning area, and mild erosion, moderate erosion, intense erosion, very intense erosion, and fierce erosion accounted for 18.22%, 11.43%, 11.78%, 10.16%, and 2.74% of the total planning area, respectively. Based on the results of the PLSR model, the results indicate that the proportion of mining land, meteorological indicators, and mean square deviation of slope difference were positively correlated with the soil erosion area, intensity, and severity, respectively. The proportion of grassland and forest land was negatively correlated with the soil erosion area, intensity, and severity. The mean square deviation of slope difference, the mean square deviation of difference in elevation, and the proportion of urban land use contributed the most to the soil erosion severity index, with variable importance in projection (VIP) scores of 1.55, 1.44 and 1.43, respectively. The mean square deviation of slope difference, the proportion of urban land, and the mean square deviation of difference in elevation contributed the most to the soil erosion area, with VIP scores of 1.53, 1.26 and 1.24, respectively. The results provide new insights into wind erosion and the influences of weather conditions and human influences, which can guide regional soil and water conservation planning in wind erosion regions.

Digitalization has enabled the potential for artificial intelligence techniques to lead the power system to a sustainable transition by extracting the data generated by widely deployed edge devices, including advanced sensing and metering. Due to the increasing concerns about data privacy, federated learning has attracted much attention and is emerging as an innovative application for machine learning solutions in the power and energy sector. This paper presents a holistic analysis of federated learning applications in the energy sector, ranging from applications in generation, microgrids, and distribution systems to the energy market and cyber security. The following federated learning-based services for energy sectors are analyzed: non-intrusive load monitoring, fault detection, energy theft detection, demand forecasting, generation forecasting, energy management systems, voltage control, anomaly detection, and energy trading. The identification and classification of the data-driven methods are conducted in collaboration with federated learning implemented in these services. Furthermore, the interrelation is mapped between the categories of machine learning, data-driven techniques, the application domain, and application services. Finally, the future opportunities and challenges of applying federated learning in the energy sector will be discussed.

Peripheral blood mononuclear cell (PBMC) are recognized as a conveniently collected reprogramming resource. Several methods are available in academia to reprogram PBMC into induced pluripotent stem cells (iPSC). In this research, we reprogrammed PBMC of different genders by using non-integrative non-viral liposome electrotransfer containing the reprogramming factors OCT4, SOX2, KLF4, and c-MYC. The three obtained iPSC cell lines were karyotypically normal and showed significant tritiated differentiation potential in vitro and in vivo. Our study provided an efficient procedure for reprogramming PBMC into iPSC and obtained three well-functioning iPSC, that may contribute to advance personalized cell therapy in the future.

Abstract Background We explored the potential novel anticancer mechanisms of 25‐hydroxyvitamin D (25(OH)D), a vitamin D metabolite with antitumour effects in breast cancer. It is stable in serum and is used to assess vitamin D levels in clinical practice. Transfer RNA‐derived small RNAs are small noncoding RNAs that generate various distinct biological functions, but more research is needed on their role in breast cancer. Methods Small RNA microarrays were used to explore the novel regulatory mechanism of 25(OH)D. High‐throughput RNA‐sequencing technology was used to detect transcriptome changes after 25(OH)D treatment and tRF‐1‐Ser knockdown. RNA pull‐down and high‐performance liquid chromatography–mass spectrometry/mass spectrometry were used to explore the proteins bound to tRF‐1‐Ser. In vitro and in vivo functional experiments were conducted to assess the influence of 25(OH)D and tRF‐1‐Ser on breast cancer. Semi‐quantitative PCR was performed to detect alternative splicing events. Western blot assay and qPCR were used to assess protein and mRNA expression. Results The expression of tRF‐1‐Ser is negatively regulated by 25(OH)D. In our breast cancer (BRCA) clinical samples, we found that the expression of tRF‐1‐Ser was higher in cancer tissues than in paired normal tissues, and was significantly associated with tumour invasion. Moreover, tRF‐1‐Ser inhibits the function of MBNL1 by hindering its nuclear translocation. Functional experiments and transcriptome data revealed that the downregulation of tRF‐1‐Ser plays a vital role in the anticancer effect of 25(OH)D. Conclusions In brief, our research revealed a novel anticancer mechanism of 25(OH)D, unveiled the vital function of tRF‐1‐Ser in BRCA progression, and suggested that tRF‐1‐Ser could emerge as a new therapeutic target for BRCA.

IntroductionAnti-PD-1/PD-L1 inhibitors therapy has become a promising treatment for hepatocellular carcinoma (HCC), while the therapeutic efficacy varies significantly among effects for individual patients are significant difference. Unfortunately, specific predictive biomarkers indicating the degree of benefit for patients and thus guiding the selection of suitable candidates for immune therapy remain elusive.no specific predictive biomarkers are available indicating the degree of benefit for patients and thus screening the preferred population suitable for the immune therapy. MethodsUltra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) considered is an important method for analyzing biological samples, since it has the advantages of high rapid, high sensitivity, and high specificity. Ultra-high-pressure liquid chromatography-mass spectrometry (UHPLC-MS) has emerged as a pivotal method for analyzing biological samples due to its inherent advantages of rapidity, sensitivity, and specificity. In this study, potential metabolite biomarkers that can predict the therapeutic effect of HCC patients receiving immune therapy were identified by UHPLC-MS. ResultsA partial least-squares discriminant analysis (PLS-DA) model was established using 14 glycerophospholipid metabolites mentioned above, and good prediction parameters (R2 = 0.823, Q2 = 0.615, prediction accuracy = 0.880 and p < 0.001) were obtained. The relative abundance of glycerophospholipid metabolite ions is closely related to the survival benefit of HCC patients who received immune therapy. DiscussionThis study reveals that glycerophospholipid metabolites play a crucial role in predicting the efficacy of immune therapy for HCC.

Affected by the Hetao trough and low vortex, an extreme short-term heavy rainfall (referred to as the "6.26" event) occurred on 26 June 2022 from 12∶00 BT to 13∶00 BT in the western part of Shangnan County in Shaanxi province. During this process, an hourly rainfall of up to 108.3 mm was observed. This event was a typical local heavy rainstorm event caused by a newly-born mesoscale thunderstorm, which was characterized by its localized, sudden, short duration, and high-intensity precipitation. All numerical models failed to predict this event. Based on the data from conventional meteorological observations, encrypted automatic weather stations, Doppler weather radar, and the fifth-generation atmospheric reanalysis data of the European Center for Medium-Range Weather Forecasting (ERA5), this study analyzed in detail the environmental field characteristics and convective triggering mechanisms of this short-time heavy precipitation event. The results are as follows: (1) This event occurred under a combined circulation background of the 500 hPa low trough in Hetao and 700 hPa low vortex shear slowly moving eastward. The dynamic uplift and energy conditions over Shangnan were favorable, and the K-index reached 42.83 ℃ before the convection occurred. (2) The local abundant water vapor and the strong vertical upward movement at the lower level could rapidly transport the water vapor upward, which was conducive to the formation of short-term heavy rain over Jinsi Gorge. (3) The small and medium-scale surface convergence line formed between the local circulation caused by the thermal heterogeneity underlying surface near Jinsi Gorge and the local flow field caused by variable pressure wind is the main reason for the extremely short-term heavy precipitation in Jinsi Gorge.In this process, the special valley terrain of Jinsi Gorge played a significant role. On the one hand, it triggered the generation of convection. On the other hand, because of its block, the low-level southeast airflow rose along the mountain slope. This further strengthened the convergence of the atmosphere over Jinsi Gorge, which finally enhanced the precipitation of this rainstorm.

Existing research models can neither indicate the availability of shared bikes nor detect unusable ones owing to a lack of information on bike maintenance and failure. To improve awareness regarding the availability of shared bikes, we propose an innovative approach for detecting unusable shared bikes based on reinforcement learning and the PageRank algorithm. The proposed method identifies unusable shared bikes depending on the local travel data and provides a ranking of the shared bikes according to their availability levels. Given a sliding time window, the value function for the reinforcement learning model was determined by considering the cumulative number of unavailable shared bikes, the proportion of rental cancelations at the same stations, and the mean time between the cancelations. Reinforcement learning was then used to identify shared bikes with the worst availability. An availability ranking for the shared bikes below the reward threshold was performed using the PageRank algorithm. The proposed detection approach was applied to a trip dataset of a real-world bike-sharing system to illustrate the modeling process and its effectiveness. The detection results of unusable shared bikes in the absence of failure and feedback data can provide essential information to support the maintenance management decisions regarding shared bikes.

Telecommunication network operations and maintenance is a basic and critical work for communications service providers (CSP).At present, there is little public operations and maintenance information of CSP.In addition, it is lack of effective evaluation model of telecommunication network operations and maintenance.A multi-dimensional evaluation model of telecommunication network operations and maintenance was proposed, which took abalanced score card as a basis and was combined with long-term operations and maintenance work and research practice.The model was verified by applying different types of CSP, including international large CSP, innovative CSP, and high-growth CSP.

In recent years, the frequent occurrence of public health emergencies has affected people’s daily lives. In response, this paper evaluates the risk of logistics terminal distribution and puts forward the corresponding countermeasures. Firstly, this paper summarizes relevant literature and analyzes the characteristics of public health emergencies and logistics terminal distribution. This paper constructs the risk index system of logistics terminal distribution under public health emergencies for the first time. Secondly, this paper conducts a questionnaire survey on a domestic e-commerce enterprise. In this paper, the intuitionistic fuzzy entropy weight method is applied to the obtained data to determine the weight of risk index. Finally, this paper adopts the grey fuzzy comprehensive evaluation method to evaluate the risk index of logistics terminal distribution under public health emergencies. This paper takes the impact of public health emergencies into account for the risk of logistics terminal distribution for the first time. Some suggestions are provided for preventing the logistics terminal distribution from stagnation and paralysis when public health emergencies occur. This paper supplements the existing research in this field.

Abstract Background Inflammasome activation has a pathogenic role in Parkinson’s disease (PD). Up-regulated expressions of inflammasome adaptor apoptosis-associated speck-like protein containing a CARD (ASC) and assembly of ASC specks have been observed in postmortems of human PD brains and experimental PD models. Extracellular ASC specks behave like danger signals and sustain prolonged inflammasome activation. However, the contribution of ASC specks in propagation of inflammasome activation and pathological progression in PD has not been fully established. Methods Herein, we used human A53T mutant α-synuclein preformed fibrils (PFFs)-stimulated microglia in vitro and unilateral striatal stereotaxic injection of PFFs-induced mice model of PD in vivo, to investigate the significance of ASC specks in PD pathological progression. Rotarod and open-field tests were performed to measure motor behaviors of indicated mice. Changes in the molecular expression were evaluated by immunofluorescence and immunoblotting (IB). Intracellular knockdown of the ASC in BV2 cells was performed using si-RNA. Microglial and neuronal cells were co-cultured in a trans-well system to determine the effects of ASC knockdown on cytoprotection. Results We observed a direct relationship between levels of ASC protein and misfolded α‑synuclein aggregates in PD mice brains. ASC specks amplified NLRP3 inflammasome activation driven by α-synuclein PFFs stimulation, which aggravated reactive microgliosis and accelerated α‑synuclein pathology, dopaminergic neurodegeneration and motor deficits. Endogenous ASC knockdown suppressed microglial inflammasome activation and neuronal α‑synuclein aggregation. Conclusions In conclusion, our study elucidated that ASC specks contribute to the propagation of inflammasome activation-associated α‑synuclein pathology in PD, which forms the basis for targeting ASC as a potential therapy for PD.

Abstract Background Grain weight/size influences not only grain yield (GY) but also nutritional and appearance quality and consumer preference in Tartary buckwheat. The identification of quantitative trait loci (QTLs)/genes for grain weight/size is an important objective of Tartary buckwheat genetic research and breeding programs. Results Herein, we mapped the QTLs for GY, 1000-grain weight (TGW), grain length (GL), grain width (GW) and grain length–width ratio (L/W) in four environments using 221 recombinant inbred lines (XJ-RILs) derived from a cross of 'Xiaomiqiao × Jinqiaomai 2'. In total, 32 QTLs, including 7 for GY, 5 for TGW, 6 for GL, 11 for GW and 3 for L/W, were detected and distributed in 24 genomic regions. Two QTL clusters, qClu-1-3 and qClu-1-5, located on chromosome Ft1, were revealed to harbour 7 stable major QTLs for GY (qGY1.2), TGW (qTGW1.2), GL (qGL1.1 and qGL1.4), GW (qGW1.7 and qGW1.10) and L/W (qL/W1.2) repeatedly detected in three and above environments. A total of 59 homologues of 27 known plant grain weight/size genes were found within the physical intervals of qClu-1-3 and qClu-1-5. Six homologues, FtBRI1, FtAGB1, FtTGW6, FtMADS1, FtMKK4 and FtANT, were identified with both non-synonymous SNP/InDel variations and significantly differential expression levels between the two parents, which may play important roles in Tatary buckwheat grain weight/size control and were chosen as core candidate genes for further investigation. Conclusions Two stable major QTL clusters related to grain weight/size and six potential key candidate genes were identified by homology comparison, SNP/InDel variations and qRT‒qPCR analysis between the two parents. Our research provides valuable information for improving grain weight/size and yield in Tartary buckwheat breeding.

The fungal genus Nigrospora is known to be a plant pathogen, endophyte, and saprobe, and it is usually isolated from various substrates like soil and air. During the surveys of soil fungi in Hebei Province of China, two isolates of Nigrospora were obtained. A multi-locus phylogeny of combined loci of the 5.8S nuclear ribosomal gene with the two flanking transcribed spacers (ITS), part of the translation elongation factor 1-alpha (tef1), and the beta-tubulin (tub2) loci, in conjunction with morphological characters were used to identify the newly collected isolates. Nigrospora humicola sp. Nov. is described and proposed herein, which differs from its phylogenetically close species N. chinensis and N. globosa by the sequences of ITS, tef1, and tub2.

This paper presents an efficient and compact Matlab code for 2D and 3D topology optimization of multi-materials. We extend a classical 88-line-based educational code to the multi-material problem using the mapping-based interpolation function, with which each material is modeled equally and can obtain a clear 0, 1 result for each material of the optimized structures that can be manufactured easily. A solution of topology optimization of multi-materials with minimum compliance under volume constraints is documented, including the details of the optimization model, filtering, projection, and sensitivity analysis procedures. Several numerical examples are also conducted to demonstrate the effectiveness of the code, and the influence of the parameter on the optimized results is also analyzed. Complete 2D and 3D Matlab codes are provided.

Using unmanned aerial vehicles (UAVs) for bridge inspection is becoming increasingly popular due to its ability to improve efficiency and ensure the safety of monitoring personnel. Compared to traditional manual monitoring methods, UAV inspections are a safer and more efficient alternative. This paper examines the impact of meteorological conditions on UAV-based bridge monitoring during specific tasks, with the aim of enhancing the safety of the UAV’s costly components. The wake vortex behind a bridge structure can vary over time due to airflow, which can have a direct impact on the safety of UAV flights. To assess this impact, numerical analysis is conducted based on monitoring requirements specific to different tasks, taking into account wind speed, wind direction, and air temperature. In order to optimize UAV trajectory, it is important to consider the wake vortex intensity and its associated influence region, which can pose a potential danger to UAV flight. Additionally, the analysis should take into account the aerodynamic effects of different types of bridge columns on the wake vortex. An optimization algorithm was utilized to optimize the trajectory of a UAV during bridge inspections within the safe region affected by wind fields. This resulted in the determination of an effective and safe flight path. The study reveals that varying wind speeds have an impact on the safe flight zone of UAVs, even if they are below the operational requirements. Therefore, when monitoring bridges using UAVs, it is important to take into account the influence of meteorological conditions. Furthermore, it was observed that the flight path of UAVs during square cylinder column monitoring is longer and more time-consuming than round cylinder column monitoring. Determining an effective UAV inspection path is crucial for completing bridge monitoring tasks in windy conditions, establishing bridge inspection standards, and developing the Intelligent Bridge Inspection System (IBIS).

Abstract Recent evidence suggests that innate and adaptive immunity play a crucial role in Parkinson’s disease (PD). However, studies regarding specific immune cell classification in the peripheral blood in PD remain lacking. Therefore, we aimed to explore the different immune status in patients with PD at different ages of onset. We included 22 patients; among them were 10 who had early-onset PD (EOPD) and 12 had late-onset PD (LOPD) and 10 young healthy controls (YHCs) and 8 elder HCs (EHCs). Mass cytometry staining technology was used to perform accurate immunotyping of cell populations in the peripheral blood. Motor symptoms and cognitive function were assessed using the Unified Parkinson’s Disease Rating Scale (UPDRS) III score and Mini-mental State Examination (MMSE) score, respectively. T test and ANOVA statistical analysis were performed on the frequency of annotated cell population. Linear regression model was used to analyze the correlation between clusters and clinical symptoms. We characterized 60 cell clusters and discovered that the immune signature of PD consists of cluster changes, including decreased effector CD8+ T cells, lower cytotoxicity natural killer (NK) cells and increased activated monocytes in PD patients. In summary, we found that CD8+ T cells, NK cells, and monocytes were associated with PD. Furthermore, there may be some differences in the immune status of patients with EOPD and LOPD, suggesting differences in the pathogenesis between these groups.

Contemporary social reform promotes rapid social transformation, and social practice has a special educational function in higher education. However, research shows weak willingness to participate in social practice among college students. Using the mixed research method, 438 completed questionnaire surveys on perceived environmental support were collected from college students. The influence of perceived environmental support on Chinese college students’ willingness to participate in social practice was analyzed using partial least squares structural equation modeling, and an empirical test was conducted. The findings are as follows: (1) Perceived environmental support significantly impacts students’ participation attitude and perceived behavioral control. (2) Participation attitude and perceived behavioral control significantly influence participation intention, but behavioral norms have no significant influence. (3) Participation intention and perceived behavioral control significantly influence actual behavior. This study provides the theoretical basis of perceived environmental support for future research on social practice participation intention and offers some theoretical guidance for the implementation of social practice in China.

Abstract Background To date, the genetic contribution to Parkinson’s disease (PD) remains unclear. Mutations in the collagen type VI alpha 3 (COL6A3) gene were recently identified as a cause of isolated dystonia. Since PD and dystonia are closely related disorders with shared clinical and genetic characteristics, we explored the association between COL6A3 and PD in a Chinese cohort. Methods We performed genetic screening of COL6A3 in a Chinese cohort of 173 patients with sporadic PD and 200 healthy controls. We identified variants that are likely to have pathogenic effects based on: 1) a minor allele frequency of

Objective To explore the targets and signaling pathways of flavanomarein in the treatment of non-alcoholic fatty liver disease (NAFLD) by network pharmacology, and to investigate the effect and mechanisms in the treatment. Methods ① The potential active targets of flavanomarein were retrieved in the Swiss Target Prediction database, and the disease-related targets were searched in the DisGeNET database. The prediction targets of lipid metabolism of NAFLD regulated by flavanomarein was obtained through Venn analysis. The Biso Genet database was used to construct the protein-protein interaction (PPI) network diagram, the Metascape database was used to analyze GO functional enrichment and KEGG pathway enrichment, and the Cytoscape software was used to draw the "target-pathway" network diagram. ② NAFLD db/db mice was employed for in vivo verification. Thirty male db/db mice were randomly divided into db/m group, db/db model group, and db/db+flavanomarein group (50 mg/kg). After the administration of 0.5% sodium carboxymethyl cellulose solution and flavanomarein for 12 weeks, the mice were sacrificed, and the liver contents of TG, GSH and GSSG was detected. HE staining and oil red O staining were used to observe the pathological changes of the liver. qRT-PCR and Western blotting were used to detect the mRNA and protein levels of key molecules in the lipid metabolism in the liver. ③HepG2 cells were treated with free fatty acids (FFAs, oleic acid∶palmitic acid =2∶1) and divided into normal group, FFAs treatment group (500 μmol/L), and FFAs+ low, medium and high concentrations of flavanomarein (25, 50, 100 μmol/L) for 24 h. Oil red O staining was used to detect the TG content in HepG2 cells. qRT-PCR and Western blotting were used to detect the mRNA and protein levels of key molecules in the lipid metabolism of HepG2 cells. Results ① A total of 29 core targets of flavanomarein docking NAFLD were screened through Venn analysis, including peroxisome proliferator-activated receptor-gamma (PPARγ), vascular endothelial growth factor (VEGF), and mitogen-activated protein kinase 14 (MAPK14). The GO analysis enriched 6 molecular functions, 20 biological processes and 5 cellular components. KEGG analysis enriched 40 key signaling pathways related to the effect of flavanomarein on NAFLD, which mainly focuses on the AMPK lipid metabolism pathway, insulin resistance (IR) pathway, and apoptosis pathway. ② The results of animal experiments showed that flavanomarein treatment reduced TG level in the NAFLD mice (P < 0.05) and improved the ratio of GSH/GSSG (P < 0.05). HE and oil red O staining showed that flavanomarein could reverse hepatocyte enlargement and reduce lipid drop infiltration of hepatocytes. qRT-PCR results showed that the treatment decreased the mRNA levels of ACC1, SCD1, and FASN for lipid synthesis (P < 0.05), while increased those of ACOX-1 and CPT1α for β-oxidation (P < 0.05). Western blot assay results indicated that the expression levels of SREBP and FASN were obviously lower (P < 0.05), and those of PPARγ and PPARα were increased (P < 0.05) in the flavanomarein group than the model group. ③ In vitro cell experiments showed that flavanomarein reduced the TG content of HepG2 cells (P < 0.05) and the expression of SREBP, SCD1 and ACC1, but increased the levels of CPT1α and ACOX-1 mRNA (P < 0.05). And, the protein expression of SREBP and FASN was also significantly reduced (P < 0.05). Conclusion Flavanomarein may play a therapeutic role in NAFLD by improving oxidative stress, up-regulating fatty acid β-oxidation, reducing lipid synthesis through regulating the PPARγ/SREBP/FASN signaling pathway.

Abstract Background Tartary buckwheat (Fagopyrum tataricum), an important pseudocereal crop, has high economic value due to its nutritional and medicinal properties. However, dehulling of Tartary buckwheat is difficult owing to its thick and tough hull, which has greatly limited the development of the Tartary buckwheat processing industry. The construction of high-resolution genetic maps serves as a basis for identifying quantitative trait loci (QTLs) and qualitative trait genes for agronomic traits. In this study, a recombinant inbred lines (XJ-RILs) population derived from a cross between the easily dehulled Rice-Tartary type and Tartary buckwheat type was genotyped using restriction site-associated DNA (RAD) sequencing to construct a high-density SNP genetic map. Furthermore, QTLs for 1000-grain weight (TGW) and genes controlling hull type were mapped in multiple environments. Results In total, 4151 bin markers comprising 122,185 SNPs were used to construct the genetic linkage map. The map consisted of 8 linkage groups and covered 1444.15 cM, with an average distance of 0.35 cM between adjacent bin markers. Nine QTLs for TGW were detected and distributed on four loci on chromosome 1 and 4. A major locus detected in all three trials was mapped in 38.2–39.8 cM region on chromosome 1, with an LOD score of 18.1–37.0, and explained for 23.6–47.5% of the phenotypic variation. The genes controlling hull type were mapped to chromosome 1 between marker Block330 and Block331, which was closely followed by the major locus for TGW. The expression levels of the seven candidate genes controlling hull type present in the region between Block330 and Block336 was low during grain development, and no significant difference was observed between the parental lines. Six non-synonymous coding SNPs were found between the two parents in the region. Conclusions We constructed a high-density SNP genetic map for the first time in Tartary buckwheat. The mapped major loci controlling TGW and hull type will be valuable for gene cloning and revealing the mechanism underlying grain development and easy dehulling, and marker-assisted selection in Tartary buckwheat.

UNet and its variations achieve state-of-the-art performances in medical image segmentation. In end-to-end learning, the training with high-resolution medical images achieves higher accuracy for medical image segmentation. However, the network depth, a massive number of parameters, and low receptive fields are issues in developing deep architecture. Moreover, the lack of multi-scale contextual information degrades the segmentation performance due to the different sizes and shapes of regions of interest. The extraction and aggregation of multi-scale features play an important role in improving medical image segmentation performance. This paper introduces the MH UNet, a multi-scale hierarchical-based architecture for medical image segmentation that addresses the challenges of heterogeneous organ segmentation. To reduce the training parameters and increase efficient gradient flow, we implement densely connected blocks. Residual-Inception blocks are used to obtain full contextual information. A hierarchical block is introduced between the encoder-decoder for acquiring and merging features to extract multi-scale information in the proposed architecture. We implement and validate our proposed architecture on four challenging MICCAI datasets. Our proposed approach achieves state-of-the-art performance on the BraTS 2018, 2019, and 2020 Magnetic Resonance Imaging (MRI) validation datasets. Our approach is 14.05 times lighter than the best method of BraTS 2018. In the meantime, our proposed approach has 2.2 times fewer training parameters than the top 3D approach on the ISLES 2018 Computed Tomographic Perfusion (CTP) testing dataset. MH UNet is available at https://github.com/parvezamu/MHUnet.

Phytopathogenic fungi, such as Fusarium spp., synthesize trichothecene family phytotoxins. The type B trichothecene, namely deoxynivalenol (DON), is highly prevalent in small-grain cereals, such as wheat, corn and barley. DON is thought to be a virulence factor allowing plant infections and has an elicitor activity. We used the model plant Arabidopsis thaliana to evaluate the phytotoxic effects of DON in host plants. The growth of A. thaliana on media was significantly inhibited by DON. Moreover, DON induced cell death in detached leaves was observed by trypan blue staining. This is consistent with the phenomenon of organelle changes observed at the ultrastructural level. In our study, DON exposure stimulated oxidative bursts in the leaves, resulting in the concomitant down-regulation of antioxidant enzyme defense responses and up-regulation of lipid peroxidation. In addition, a real-time PCR analysis revealed that the DON treatment rapidly induced the transcription of defense genes, like AtrbohC and AtrbohD, and up-regulated the transcriptional level of the ascorbic acid peroxidase gene. These results suggested that DON phytotoxicity might result from reactive oxygen species pathways, and that DON production by the plant pathogen Fusarium graminearum can act as an elicitor influencing plant cell fate.

BackgroundParkinson's disease (PD) and dystonia are closely related in terms of pathophysiology and clinical manifestations, but their common genetic characteristics remain unclear. Some genome-wide association studies (GWASs) and replication studies have revealed correlations between single nucleotide polymorphisms (SNPs) of the ARSG, BDNF, NALCN, OR4X2, KIAA1715, and OR4B1 genes and dystonia. This study was conducted to assess the association between these genetic loci and PD in a population from Eastern China.MethodsWe genotyped the SNPs (rs11655081 of ARSG; rs6265 of BDNF; rs61973742, rs1338051, rs9518384, and rs9518385 of NALCN; rs67863238 of OR4X2; rs10930717 of KIAA1715; and rs35875350 of OR4B1) in a cohort of 474 patients with PD and 439 healthy controls from East China. To determine the genotypes of these SNPs, we used an Agena MassARRAY Typer 4.0. Odds ratios (ORs) and 95% CIs were computed to evaluate the correlations between these SNPs and the risk of PD.ResultsThere were significant differences in the genotype distribution (OR = 0.649, 95% CI = 0.478–0.880) and minor allele frequency (MAF) (OR = 0.703, 95% CI = 0.533–0.929) of SNP rs61973742 (NALCN) between patients with PD and healthy controls. A significant difference was detected in the genotype distribution of rs11655081 (ARSG) (OR = 1.486, 95% CI = 1.080–2.045).ConclusionSingle nucleotide polymorphisms rs11655081 (ARSG) and rs61973742 (NALCN) may be associated with PD. The C allele of rs11655081 may increase the risk of PD, whereas the G allele of rs61973742 may be a protective factor.

In this paper, we present a monitoring program of loss control prevention for airlines to enhance aviation safety and operational efficiency. The assessments of dynamic stability characteristics based on the approaches of oscillatory motion and eigenvalue motion modes for jet transport aircraft response to sudden plunging motions are demonstrated. A twin-jet transport aircraft encountering severe clear-air turbulence in transonic flight during the descending phase was examined as the study case. The flight results in sudden plunging motions with abrupt changes in attitude and gravitational acceleration (i.e., the normal load factor) are provided. Development of the required thrust and aerodynamic models with the flight data mining and the fuzzy logic modeling techniques was carried out. The oscillatory derivatives extracted from these aerodynamic models were then used in the study of variations in stability characteristics during the sudden plunging motion. The fuzzy logic aerodynamic models were utilized to estimate the nonlinear unsteady aerodynamics while performing numerical integration of flight dynamic equations. The eigenvalues of all motion modes were obtained during time integration. The positive real part of the eigenvalues is to indicate unstable motion. The dynamic stability characteristics during sudden plunging motion are easily judged by the values in positive or negative. The present quantitative assessment method is an innovation to examine possible mitigation concepts of accident prevention and promote the understanding of aerodynamic responses of the jet transport aircraft.

Epigenetic modifications play a crucial role in neurogenesis, learning, and memory, but the study of their role in early neuroectoderm commitment from pluripotent inner cell mass is relatively lacking. Here we utilized the system of directed neuroectoderm differentiation from human embryonic stem cells and identified that KDM6B, an enzyme responsible to erase H3K27me3, was the most upregulated enzyme of histone methylation during neuroectoderm differentiation by transcriptome analysis. We then constructed KDM6B-null embryonic stem cells and found strikingly that the pluripotent stem cells with KDM6B knockout exhibited much higher neuroectoderm induction efficiency. Furthermore, we constructed a series of embryonic stem cell lines knocking out the other H3K27 demethylase KDM6A, and depleting both KDM6A and KDM6B, respectively. These cell lines together confirmed that KDM6 impeded early neuroectoderm commitment. By RNA-seq, we found that the expression levels of a panel of WNT genes were significantly affected upon depletion of KDM6. Importantly, the result that WNT agonist and antagonist could abolish the differential neuroectoderm induction due to manipulating KDM6 further demonstrated that WNT was the major downstream of KDM6 during early neural induction. Moreover, we found that the chemical GSK-J1, an inhibitor of KDM6, could enhance neuroectoderm induction from both embryonic stem cells and induced pluripotent stem cells. Taken together, our findings not only illustrated the important role of the histone methylation modifier KDM6 in early neurogenesis, providing insights into the precise epigenetic regulation in cell fate determination, but also showed that the inhibitor of KDM6 could facilitate neuroectoderm differentiation from human pluripotent stem cells.

IntroductionMutations in the teneurin transmembrane protein 4 (TENM4) gene, known to be involved in neuropsychiatric disorders, have been identified in three pedigree of essential tremor (ET) from Spain. ET has overlapping clinical manifestations and epidemiological symptoms with Parkinson’s disease (PD), suggesting these two disorders may reflect common genetic risk factors. In this study, we investigated clinical and genetic manifestations in four unrelated pedigrees with both ET and PD in which TENM4 variants were identified.MethodsWe subsequently explored whether TENM4 variants contributed to the risk of developing PD. The frequency of TENM4 variants was evaluated from four PD pedigrees and other 407 subjects.ResultsThe results revealed 12 different novel heterozygous variants, all at low frequency. A clear general enrichment of TENM4 variants was detected in early onset PD patients (p < 0.001, OR = 5.264, 95% CI = 1.957–14.158).ConclusionThe results indicate that rare TENM4 variants may be associated with an increased risk of PD.

Abstract Background To date, several studies have suggested that genes involved in monogenic forms of Parkinson's disease (PD) contribute to unrelated sporadic cases, but there is limited evidence in the Chinese population. Methods We performed a systematic analysis of 12 autosomal‐dominant PD (AD‐PD) genes (SNCA, LRRK2, GIGYF2, VPS35, EIF4G1, DNAJC13, CHCHD2, HTRA2, NR4A2, RIC3, TMEM230, and UCHL1) using panel sequencing and database filtration in a case‐control study of a cohort of 391 Chinese sporadic PD patients and unrelated controls. We evaluated the association between candidate variants and sporadic PD using gene‐based analysis. Results Overall, 18 rare variants were discovered in 18.8% (36/191) of the index patients. In addition to previously reported pathogenic mutations (LRRK2 p.Arg1441His and p.Ala419Val), another four unknown variants were found in LRRK2, which also contribute to PD risk (p = 0.002; odds ratio (OR) = 7.83, 95% confidence intervals (CI) = 1.76–34.93). The cumulative frequency of undetermined rare variants was significantly higher in PD patients (14.1%) than in controls (3.5%) (p = 0.0002; OR=4.54, 95% CI = 1.93‐10.69). Conclusion Our results confirm the strong impact of LRRK2 on the risk of sporadic PD, and also provide considerable evidence of the existence of additional undetermined rare variants in AD‐PD genes that contribute to the genetic etiology of sporadic PD in a Chinese cohort.

Star sensors are indispensable spatial measurement sensors for high-resolution earth observation and astronomical observations, and the demand for high measurement accuracy of satellite sensors continues to increase; thus, the star sensor optical machine adjustment error cannot be ignored. The commonly used installation error correction method cannot solely meet the precision analysis requirements. In this paper, the relationship between the optical machine installation and the star sensor measurement error is analyzed, and several common adjustment error correction methods are compared. An adjustment method for optical machines is proposed to meet the requirements of very high precision star sensors. The assembly precision requirements of the investigated very high precision star sensor are analyzed considering the whole machine, and then the optical components are controlled through optical precision adjustments to satisfy the precision requirements. Finally, through the complete machine calibration, the star sensor precision adjustment for an optical machine structure is verified. This method meets the requirements of very high precision sensors and is suitable for the precision adjustment of optical machine structures, which is of practical significance to improve the precision of star sensors. Keywords: Very high precision star sensor, Optical machine structure, Alignment precision, Precision adjustment

Abstract Aims Idiopathic congenital nystagmus (ICN) is an oculomotor disorder caused by the defects in the ocular motor control regions of the brain. Mutations in FRMD7, a member of the FERM family of proteins, associated with cytoskeletal dynamics, are the most frequent causes of X‐linked ICN. Previous studies illustrated that FRMD7 is involved in the elongation of neurites during neuronal development; however, almost all the studies were performed on mice cell models. The complexity in the human neuronal network might suggest a unique vulnerability of human neurons to FRMD7 mutations. Methods Herein, we successfully established human neuronal cell models with FRMD7 mutations, from fibroblasts‐reprogrammed neurons (iNs). In these neurons, the complexity of the neuronal processes was measured by the induced ratio, total neurite length, the number of terminals, and the number of maturation neurons. Results The complexity of the neuronal processes was greatly reduced during various reprogramming stages in the presence of FRMD7 mutations. Consistently, the expression of the three main Rho GTPases was significantly increased by FRMD7 mutations. Interestingly, a slightly diverse phenotype is observed in different derived neurons. Conclusion We established ideal human neuron models and confirmed that the mutation in FRMD7 influences the maturation and complexities of neuronal processes, which might be involved with the Rho GTPase signaling.

Parkinson’s disease is primarily caused by the loss of dopaminergic neurons in the substantia nigra compacta. Ferroptosis, a novel form of regulated cell death characterized by iron accumulation and lipid peroxidation, plays a vital role in the death of dopaminergic neurons. However, the molecular mechanisms underlying ferroptosis in dopaminergic neurons have not yet been completely elucidated. NADPH oxidase 4 is related to oxidative stress, however, whether it regulates dopaminergic neuronal ferroptosis remains unknown. The aim of this study was to determine whether NADPH oxidase 4 is involved in dopaminergic neuronal ferroptosis, and if so, by what mechanism. We found that the transcriptional regulator activating transcription factor 3 increased NADPH oxidase 4 expression in dopaminergic neurons and astrocytes in an 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine-induced Parkinson’s disease model. NADPH oxidase 4 inhibition improved the behavioral impairments observed in the Parkinson’s disease model animals and reduced the death of dopaminergic neurons. Moreover, NADPH oxidase 4 inhibition reduced lipid peroxidation and iron accumulation in the substantia nigra of the Parkinson’s disease model animals. Mechanistically, we found that NADPH oxidase 4 interacted with activated protein kinase C α to prevent ferroptosis of dopaminergic neurons. Furthermore, by lowering the astrocytic lipocalin-2 expression, NADPH oxidase 4 inhibition reduced 1-methyl-4-phenyl-1,2,3,6 tetrahydropyridine-induced neuroinflammation. These findings demonstrate that NADPH oxidase 4 promotes ferroptosis of dopaminergic neurons and neuroinflammation, which contribute to dopaminergic neuron death, suggesting that NADPH oxidase 4 is a possible therapeutic target for Parkinson’s disease.

In large-scale wireless sensor networks, massive sensor data generated by a large number of sensor nodes call for being stored and disposed. Though limited by the energy and bandwidth, a large-scale wireless sensor network displays the disadvantages of fusing the data collected by the sensor nodes and compressing them at the sensor nodes. Thus the goals of reduction of bandwidth and a high speed of data processing should be achieved at the second-level sink nodes. Traditional compression technology is unable to appropriately meet the demands of processing massive sensor data with a high compression rate and low energy cost. In this paper, Parallel Matching Lempel-Ziv-Storer-Szymanski (PMLZSS), a high speed lossless data compression algorithm, making use of the CUDA framework at the second-level sink node is presented. The core idea of PMLZSS algorithm is parallel matrix matching. PMLZSS algorithm divides the data compression files into multiple compressed dictionary window strings and prereading window strings along the vertical and horizontal axes of the matrices, respectively. All of the matrices are parallel matched in the different thread blocks. Compared with LZSS and BZIP2 on the traditional serial CPU platforms, the compression speed of PMLZSS increases about 16 times while, for BZIP2, the compression speed increases about 12 times when the basic compression rate unchanged.

Surveillance video service (SVS) is one of the most important services provided in a smart city. It is very important for the utilization of SVS to provide design efficient surveillance video analysis techniques. Key frame extraction is a simple yet effective technique to achieve this goal. In surveillance video applications, key frames are typically used to summarize important video content. It is very important and essential to extract key frames accurately and efficiently. A novel approach is proposed to extract key frames from traffic surveillance videos based on GPU (graphics processing units) to ensure high efficiency and accuracy. For the determination of key frames, motion is a more salient feature in presenting actions or events, especially in surveillance videos. The motion feature is extracted in GPU to reduce running time. It is also smoothed to reduce noise, and the frames with local maxima of motion information are selected as the final key frames. The experimental results show that this approach can extract key frames more accurately and efficiently compared with several other methods.