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Protein secondary structure prediction (PSSP) is a pivotal research endeavour that plays a crucial role in the comprehensive elucidation of protein functions and properties. Current prediction methodologies are focused on deep-learning techniques, particularly focusing on multi-factor features. Diverging from existing approaches, in this study, we placed special emphasis on the effects of amino acid properties and protein secondary structure propensity scores (SSPs) on secondary structure during the meticulous selection of multi-factor features. This differential feature-selection strategy results in a distinctive and effective amalgamation of the sequence and property features. To harness these multi-factor features optimally, we introduced a hybrid deep feature extraction model. The model initially employs mechanisms such as dilated convolution (D-Conv) and a channel attention network (SENet) for local feature extraction and targeted channel enhancement. Subsequently, a combination of recurrent neural network variants (BiGRU and BiLSTM), along with a transformer module, was employed to achieve global bidirectional information consideration and feature enhancement. This approach to multi-factor feature input and multi-level feature processing enabled a comprehensive exploration of intricate associations among amino acid residues in protein sequences, yielding a Q3 accuracy of 84.9% and an Sov score of 85.1%. The overall performance surpasses that of the comparable methods. This study introduces a novel and efficient method for determining the PSSP domain, which is poised to deepen our understanding of the practical applications of protein molecular structures.

Abstract Behçet’s disease (BD) is a multifaceted autoimmune disorder affecting multiple organ systems. Vascular complications, such as venous thromboembolism (VTE), are highly prevalent, affecting around 50% of individuals diagnosed with BD. This study aimed to identify potential biomarkers for VTE in BD patients. Three microarray datasets (GSE209567, GSE48000, GSE19151) were retrieved for analysis. Differentially expressed genes (DEGs) associated with VTE in BD were identified using the Limma package and weighted gene co-expression network analysis (WGCNA). Subsequently, potential diagnostic genes were explored through protein–protein interaction (PPI) network analysis and machine learning algorithms. A receiver operating characteristic (ROC) curve and a nomogram were constructed to evaluate the diagnostic performance for VTE in BD patients. Furthermore, immune cell infiltration analyses and single-sample gene set enrichment analysis (ssGSEA) were performed to investigate potential underlying mechanisms. Finally, the efficacy of listed drugs was assessed based on the identified signature genes. The limma package and WGCNA identified 117 DEGs related to VTE in BD. A PPI network analysis then selected 23 candidate hub genes. Four DEGs (E2F1, GATA3, HDAC5, and MSH2) were identified by intersecting gene sets from three machine learning algorithms. ROC analysis and nomogram construction demonstrated high diagnostic accuracy for these four genes (AUC: 0.816, 95% CI: 0.723–0.909). Immune cell infiltration analysis revealed a positive correlation between dysregulated immune cells and the four hub genes. ssGSEA provided insights into potential mechanisms underlying VTE development and progression in BD patients. Additionally, therapeutic agent screening identified potential drugs targeting the four hub genes. This study employed a systematic approach to identify four potential hub genes (E2F1, GATA3, HDAC5, and MSH2) and construct a nomogram for VTE diagnosis in BD. Immune cell infiltration analysis revealed dysregulation, suggesting potential macrophage involvement in VTE development. ssGSEA provided insights into potential mechanisms underlying BD-induced VTE, and potential therapeutic agents were identified.

Abstract This study employed a commercial software velocity to perform deformable registration and dose calculation on deformed CT images, aiming to assess the accuracy of dose delivery during the radiotherapy for lung cancers. A total of 20 patients with lung cancer were enrolled in this study. Adaptive CT (ACT) was generated by deformed the planning CT (pCT) to the CBCT of initial radiotherapy fraction, followed by contour propagation and dose recalculation. There was not significant difference between volumes of GTV and CTV calculated from the ACT and pCT. However, significant differences in dice similarity coefficient (DSC) and coverage ratio (CR) between GTV and CTV were observed, with lower values for GTV volumes below 15 cc. The mean differences in dose corresponding to 95% of the GTV, GTV-P, CTV, and CTV-P between ACT and pCT were − 0.32%, 4.52%, 2.17%, and 4.71%, respectively. For the dose corresponding to 99%, the discrepancies were − 0.18%, 8.35%, 1.92%, and 24.96%, respectively. These differences in dose primarily appeared at the edges of the target areas. Notably, a significant enhancement of dose corresponding to 1 cc for spinal cord was observed in ACT, compared with pCT. There was no statistical difference in the mean dose of lungs and heart. In general, for lung cancer patients, anatomical motion may result in both CTV and GTV moving outside the original irradiation region. The dose difference within the original target area was small, but the difference in the planning target area was considerable.

This study establishes a model for the coupling of passenger compartment and air-conditioning systems. The model takes human thermal comfort as the evaluation index, which can achieve dynamic data exchange during the transient calculation process, and control the air-conditioning systems with the core goal of reducing energy consumption. The optimal air supply angle and air distribution ratio were analyzed using this model. When the external environment changes, the air supply parameters corresponding to the lowest energy consumption are analyzed based on the air conditioning system with optimal air supply angle and air distribution ratio. The results show that the best direct blowing position is the neck. When the air distribution ratio of the driver's left air outlet is 25 %, the overall thermal comfort value of the dummy is the best. The overall thermal comfort of the dummy was maintained at the optimal value with an air speed of 8 m/s for dynamic external environments, but this air speed was not the lowest energy consumption. Subsequently, under the premise of maintaining the comfort of the dummy, the fitted curves of the air supply speed that minimizes the energy consumption are obtained by comparing the energy consumption under different air supply speeds.

Study region: The study region is a typical desert oasis ecotone of the Hexi Corridor, Northwest China. Study focus: Based on four years of in situ observational data of soil water, temperature, and electrical conductivity obtained from three Haloxylon ammodendron (H. ammodendron) forests (20, 30 and 50 years) in a typical desert oasis ecotone (DOE) of the Hexi Corridor, in this study, the mechanisms of change and coupled effects of water, heat, and salt in frozen desert soils along a long-term shrub plantation in a typical desert oasis ecotone are presented. New hydrological insights for the region: This study revealed that changes in soil water, heat, and salt and their coupling effects were completely different between shallow (0–80 cm) and deep (160–200 cm) depths. At 0–80 cm, soil water gradually decreased in the 50-year-old H. ammodendron plot, but soil salt first increased in the 30-year plot and then decreased in the 50-year plot. When the freezing process occurred in the 0–80 cm depth interval, the soil water and salt contents decreased nonlinearly with the absolute value of the soil temperature (|T|), following a power function and logarithmic function, respectively. For the thawing process in the 0–80 cm depth interval, soil water and salt increased with increasing temperature, and there was a significant linear relationship between soil water and salt (P

The open and generative nature of multimedia learning environments tends to cause cognitive overload in learners, and cognitive load is difficult for researchers to observe objectively because of its implicit and complex nature. Event-related potentials (ERP), a method of studying potential changes associated with specific events or stimuli by recording the electroencephalogram (EEG), has become an important method of measuring cognitive load in cognitive psychology. Although many studies have relied on ERP output measurements to compare different levels of cognitive load in multimedia learning, the results of the effect of cognitive load on ERP have been inconsistent. In this study, we used a meta-analysis of evidence-based research to quantitatively analyze 17 experimental studies to quantitatively evaluate which ERP component (amplitude) is most sensitive to cognitive load. Forty five effect sizes from 26 studies involving 360 participants were calculated. (1) The results of the studies analyzed in subgroups indicated high level effect sizes for P300 and P200 (2) Analyses of moderating variables for signal acquisition did not find that different methods of signal acquisition had a significant effect on the measurement of cognitive load (3) Analyses of moderating variables for task design found that a task system with feedback was more convenient for the measurement of cognitive load, and that designing for 3 levels of cognitive load was more convenient for the measurement of cognitive load than for 2 levels of cognitive load. (4) Analyses of continuous moderating variables for subject characteristics did not find significant effects of age, gender, or sample size on the results.

Abstract While phonon anharmonicity affects lattice thermal conductivity intrinsically and is difficult to be modified, controllable lattice defects routinely function only by scattering phonons extrinsically. Here, through a comprehensive study of crystal structure and lattice dynamics of Zintl-type Sr(Cu,Ag,Zn)Sb thermoelectric compounds using neutron scattering techniques and theoretical simulations, we show that the role of vacancies in suppressing lattice thermal conductivity could extend beyond defect scattering. The vacancies in Sr2ZnSb2 significantly enhance lattice anharmonicity, causing a giant softening and broadening of the entire phonon spectrum and, together with defect scattering, leading to a ~ 86% decrease in the maximum lattice thermal conductivity compared to SrCuSb. We show that this huge lattice change arises from charge density reconstruction, which undermines both interlayer and intralayer atomic bonding strength in the hierarchical structure. These microscopic insights demonstrate a promise of artificially tailoring phonon anharmonicity through lattice defect engineering to manipulate lattice thermal conductivity in the design of energy conversion materials.

Objective Previous studies have shown that bone mineral density (BMD) is a predictor of cage subsidence. Phantom‐less quantitative computed tomography (PL‐QCT) can measure volumetric bone mineral density (vBMD) of lumbar trabecular and cortical bone. The study of endplate vBMD (EP‐vBMD) is important in predicting cage settlement after extreme lateral interbody fusion (XLIF). This study aimed to determine the risk factors for postoperative cage subsidence after XLIF, particularly focusing on the relationship between vBMD measured by automatic PL‐QCT and cage subsidence. Methods Patients who underwent XLIF surgery from January 2018 to October 2020 with a minimum of 6 months of follow‐up were retrospectively included. Cage subsidence was defined as >2 mm cage sinking on the adjacent endplate in follow‐up imaging evaluation. Outcome measures were localized vBMDs included EP‐vBMDs with different region of interest (ROI) heights measured by PL‐QCT based on a customized muscle‐fat algorithm. Shapiro–Wilk test, one‐way ANOVA, Mann–Whitney test, Fisher exact test, univariable and multivariable logistic regression and receiver operating characteristic (ROC) curve analysis were executed in this study. Results One hundred and thirteen levels of 78 patients were included in the analysis. The mean age was 65 ± 7.9 years for 11 males and 67 females. Cage subsidence occurred on 45 (39.8%) surgical levels. There was no significant difference in demographics, fused levels, or preoperative radiographic parameters. 1.25‐mm EP‐vBMD (0.991 [0.985,0.997], p = 0.004) and P‐TB‐vBMD (cage‐positioned trabecular volumetric bone mineral density) (0.988 [0.977–0.999], p = 0.026) were cage‐subsidence relevant according to univariate analysis. Low 1.25‐mm EP‐vBMD (0.992 [0.985, 0.999], p = 0.029) was an independent risk factor according to multifactorial analysis. Conclusion Preoperative low EP‐vBMD was an independent risk factor for postoperative cage subsidence after XLIF. EP‐vBMD measured by most cortex‐occupied ROI may be the optimal vBMD parameter for cage subsidence prediction.

Protein secondary structure prediction (PSSP) plays a crucial role in resolving protein functions and properties. Significant progress has been made in this field in recent years, and the use of a variety of protein-related features, including amino acid sequences, position-specific score matrices (PSSM), amino acid properties, and secondary structure trend factors, to improve prediction accuracy is an important technical route for it. However, a comprehensive evaluation of the impact of these factor features in secondary structure prediction is lacking in the current work. This study quantitatively analyzes the impact of several major factors on secondary structure prediction models using a more explanatory four-class machine learning approach. The applicability of each factor in the different types of methods, the extent to which the different methods work on each factor, and the evaluation of the effect of multi-factor combinations are explored in detail. Through experiments and analyses, it was found that PSSM performs best in methods with strong high-dimensional features and complex feature extraction capabilities, while amino acid sequences, although performing poorly overall, perform relatively well in methods with strong linear processing capabilities. Also, the combination of amino acid properties and trend factors significantly improved the prediction performance. This study provides empirical evidence for future researchers to optimize multi-factor feature combinations and apply them to protein secondary structure prediction models, which is beneficial in further optimizing the use of these factors to enhance the performance of protein secondary structure prediction models.

Moringa oleifera leaves (MOLs) have gained significant attention due to their nutritional and biological activity. Therefore, this study aimed to examine its flavor characteristics and underlying compositions. In this study, we used ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS), gas chromatography-mass spectrometry (GC-MS), electronic nose, electronic tongue, and molecular docking to comprehensively investigate the chemical properties and flavor profiles of MOLs. UPLC-Q-TOF-MS and GC-MS were instrumental in identifying the 20 non-volatile and 19 volatile constituents of MOLs, respectively. The electronic nose and electronic tongue systems provided an objective evaluation of the sweet, bitter, and spicy attributes and flavor characteristics of MOLs. Concurrently, molecular docking was employed to elucidate the material basis of flavor profiles. It revealed that glucosinolates and flavonoids are probably the key components for the bitter taste of MOLs. The sweet taste may be attributed to glucosinolates and flavonoids. The spicy scent appears to be linked to the presence of glucosinolates and alkaloids. The integration of these techniques confers a thorough understanding of the chemical composition and sensory properties of MOLs. These findings have significant implications for innovative applications in the food industry as well as pharmaceuticals and agriculture sectors; furthermore, they contribute towards enhancing the perception of Moringa oleifera as a valuable natural resource.

AbstractBackground Polycystic Ovary Syndrome (PCOS) is the most frequent endocrine disorder in female adults, and hyperandrogenism (HA) is the typical endocrine feature of PCOS. This study aims to investigate the trends and hotspots in the study of PCOS and HA.Methods Literature on Web of Science Core Collection (WoSCC) from 2008 to 2022 was retrieved, and bibliometric analysis was conducted using VOSviewer and CiteSpace software.Results A total of 2,404 papers were published in 575 journals by 10,121 authors from 2,434 institutions in 86 countries. The number of publications in this field is generally on the rise yearly. The US, China and Italy contributed almost half of the publications. Monash University had the highest number of publications, while the University of Adelaide had the highest average citations and the Karolinska Institute had the strongest cooperation with other institutions. Lergo RS contributed the most to the field of PCOS and HA. The research on PCOS and HA mainly focused on complications, adipose tissue, inflammation, granulosa cells, gene and receptor expression.Conclusion Different countries, institutions, and authors should facilitate cooperation and exchanges. This study will be helpful for better understanding the frontiers and hotspots in the areas of PCOS and HA.

Abstract Hypobaric hypoxia (HH) exposure affects appetite and serum iron levels in both humans and animals. Thus, whether appetite-regulating ghrelin is involved in iron regulation under HH needs to be elucidated. In vivo, C57BL/6J mice were placed in a hypobaric chamber to establish a 6000-m-high altitude exposure animal model. In vitro, mouse primary hepatocytes and peritoneal macrophages were exposed to hypoxia (1% O2) to examine the effects of ghrelin on iron-regulating proteins. HH obviously reduced the body weight of mice and significantly increased the levels of erythrocytes, and also significantly enhanced the levels of serum iron and plasma ghrelin. However, iron content in the liver and spleen was decreased, while ferroportin (Fpn) expression was increased. Moreover, ghrelin significantly induced Fpn and pERK expression in both hepatocytes and macrophages under hypoxia, which were reversed by pretreatment with growth hormone secretagogue receptor 1a (GHSR1a) antagonist or pERK inhibitor. Our findings indicated that HH leads to decreased appetite and insufficient dietary intake, which may negatively regulate the levels of ghrelin. Furthermore, GHSR1a/ERK signalling pathway is further activated to upregulate the expression of Fpn, and then promoting iron mobilization both in the liver/hepatocytes and spleen/macrophages in mice. Thus, these results revealed that ghrelin may be a potential iron regulatory hormone, and raised the possibility of ghrelin as a promising therapeutic target against iron disorders under HH.

Abstract Background To examine the expression characteristics of single nucleotide polymorphisms (SNPs) in the SRD5A2 gene and investigate their potential association with differences in the clinical characteristics between sexes in patients with chronic hepatitis B virus (HBV) infection. Methods A total of 30 loci in six genes primarily involved in the metabolism and signaling of sex hormones/sex hormone receptors, namely AKR1C2, AKR1C3, HSD17B6, SRD5A1, SRD5A2, and ESR1, were genotyped in 1007 patients from eight counties (cities) in Northeastern China with chronic HBV infection and 1040 healthy controls, and their association with viral replication characteristics and the differences in disease severity between sexes was assessed. Western blotting was conducted to determine the hepatic SRD5A2 protein level and its relationship with the inflammatory activity and fibrosis degree in male and female patients. Results Two SNP loci in the SRD5A2 gene (rs12470143 and rs7594951) exhibited significant differences in genotype and allele frequencies between sexes, with the proportion of T alleles significantly higher in males than in females. It was found that the incidence and severity of HBV-related liver fibrosis were significantly higher in patients with the T/T genotype in SRD5A2 rs12470143 and rs7594951 than those with the non-T/T genotype. Additionally, serum HBV DNA levels were significantly elevated in T/T patients compared to non-T/T patients. Female patients exhibited significantly lower serum DNA levels compared to male patients. Western blot analysis indicated that greater hepatic SRD5A2 protein levels were associated with higher METAVIR inflammation and fibrosis scores. Furthermore, multivariate analysis showed that the two genetic variants in the SRD5A2 gene (rs12470143 C > T, r7594951 C > T), together with the male sex, age > 50 years old, HBeAg positive status, elevated serum HBsAg load, high serum HBV DNA load, and HBV genotype C, were independent risk factors for HBV-related liver fibrosis. Conclusions This study demonstrated that two genetic variants in the SRD5A2 gene (rs12470143 C > T, r7594951 C > T) are associated with sex differences in the clinical characteristics of patients with chronic HBV infection.

Abstract Background Single-cell RNA sequencing (scRNA-seq) has revolutionized the transcriptomics field by advancing analyses from tissue-level to cell-level resolution. Despite the great advances in the development of computational methods for various steps of scRNA-seq analyses, one major bottleneck of the existing technologies remains in identifying the molecular relationship between disease phenotype and cell subpopulations, where “disease phenotype” refers to the clinical characteristics of each patient sample, and subpopulation refer to groups of single cells, which often do not correspond to clusters identified by standard single-cell clustering analysis. Here, we present PACSI, a method aimed at distinguishing cell subpopulations associated with disease phenotypes at the single-cell level. Results PACSI takes advantage of the topological properties of biological networks to introduce a proximity-based measure that quantifies the correlation between each cell and the disease phenotype of interest. Applied to simulated data and four case studies, PACSI accurately identified cells associated with disease phenotypes such as diagnosis, prognosis, and response to immunotherapy. In addition, we demonstrated that PACSI can also be applied to spatial transcriptomics data and successfully label spots that are associated with poor survival of breast carcinoma. Conclusions PACSI is an efficient method to identify cell subpopulations associated with disease phenotypes. Our research shows that it has a broad range of applications in revealing mechanistic and clinical insights of diseases.

Abstract Background Neuroinflammation in the rostral ventrolateral medulla (RVLM) has been associated with the pathogenesis of stress-induced hypertension (SIH). Neuronal mitochondrial dysfunction is involved in many pathological and physiological processes. However, the impact of neuroinflammation on neuronal mitochondrial homeostasis and the involved signaling pathway in the RVLM during SIH are largely unknown. Methods The morphology and phenotype of microglia and the neuronal mitochondrial injury in vivo were analyzed by immunofluorescence, Western blot, RT-qPCR, transmission electron microscopy, and kit detection. The underlying mechanisms of microglia-derived tumor necrosis factor‐α (TNF-α) on neuronal mitochondrial function were investigated through in vitro and in vivo experiments such as immunofluorescence and Western blot. The effect of TNF-α on blood pressure (BP) regulation was determined in vivo via intra-RVLM microinjection of TNF-α receptor antagonist R7050. Results The results demonstrated that BP, heart rate (HR), renal sympathetic nerve activity (RSNA), plasma norepinephrine (NE), and electroencephalogram (EEG) power increased in SIH rats. Furthermore, the branching complexity of microglia in the RVLM of SIH rats decreased and polarized into M1 phenotype, accompanied by upregulation of TNF‐α. Increased neuronal mitochondria injury was observed in the RVLM of SIH rats. Mechanistically, Sirtuin 3 (Sirt3) and p-AMPK expression were markedly downregulated in both SIH rats and TNF-α–treated N2a cells. AMPK activator A769662 upregulated AMPK–Sirt3 signaling pathway and consequently reversed TNF-α–induced mitochondrial dysfunction. Microinjection of TNF-α receptor antagonist R7050 into the RVLM of SIH rats significantly inhibited the biological activities of TNF-α, increased p‐AMPK and Sirt3 levels, and alleviated neuronal mitochondrial injury, thereby reducing c-FOS expression, RSNA, plasma NE, and BP. Conclusions This study revealed that microglia-derived TNF-α in the RVLM impairs neuronal mitochondrial function in SIH possibly through inhibiting the AMPK–Sirt3 pathway. Therefore, microglia-derived TNF-α in the RVLM may be a possible therapeutic target for the intervention of SIH.

The atomic pathway in the photoinduced ultrafast structural phase transition of VO2 has been a controversial problem for a long time. Here the authors, using MeV ultrafast electron diffraction, show that the melting of V-V dimers and the transformation of crystal symmetry are two processes with different timescales.

Relieving the emotions of the public through government response is an important part of government emergency management. How governments respond in different situations can avoid stimulating negative emotions during emergencies? This paper analyzes the problem from the perspective of configuration; that is, this paper explores the combined effects of multiple factors on emotions. We construct the theoretical framework “Situation-Responder-Content” from situation, responder and response content, and use the government microblogs (n= 1517) from 23 major production accidents in China for the discussion with the use of fuzzy set qualitative comparison analysis (fsQCA). According to the results, the effective response types of different agencies in emergencies are summarized. Local authorities can respond in ways that include “Measures type” and “Measures-Emotion type”. Functional agencies can respond through “Measures type”, “Measures-Emotion type” and “Government feature-Driven” type. This study emphasizes that government response in emergencies is a systematic process. Responsive agencies need to release effective information on the basis of fully considering the situation and other factors. Configuration analysis should also be an important direction in government response research, which is helpful to the practice of government response in emergencies.

The heterogeneity of tumors poses a challenge for understanding cell interactions and constructing complex ecosystems within cancer tissues. Current research strategies integrate spatial transcriptomics (ST) and single-cell sequencing (scRNA-seq) data to thoroughly analyze this intricate system. However, traditional deep learning methods using scRNA-seq data tend to filter differentially expressed genes through statistical methods. In the context of cancer tissues, where cancer cells exhibit significant differences in gene expression compared to normal cells, this heterogeneity renders traditional analysis methods incapable of accurately capturing differences between cell types. Therefore, we propose a graph-based deep learning method, GTADC, which utilizes Silhouette scores to precisely capture genes with significant expression differences within each cell type, enhancing the accuracy of gene selection. Compared to traditional methods, GTADC not only considers the expression similarity of genes within their respective clusters but also comprehensively leverages information from the overall clustering structure. The introduction of graph structure effectively captures spatial relationships and topological structures between the two types of data, enabling GTADC to more accurately and comprehensively resolve the spatial composition of different cell types within tissues. This refinement allows GTADC to intricately reconstruct the cellular spatial composition, offering a precise solution for inferring cell spatial composition. This method allows for early detection of potential cancer cell regions within tissues, assessing their quantity and spatial information in cell populations. We aim to achieve a preliminary estimation of cancer occurrence and development, contributing to a deeper understanding of early-stage cancer and providing potential support for early cancer diagnosis.

Digital radio frequency memory (DRFM) has emerged as an advanced technique to achieve a range of jamming signals, due to its capability to intercept waveforms within a short time. multiple-input multiple-output (MIMO) radars can transmit agile orthogonal waveform sets for different pulses to combat DRFM-based jamming, where any two groups of waveform sets are also orthogonal. In this article, a group orthogonal waveform optimal design model is formulated in order to combat DRFM-based jamming by flexibly designing waveforms for MIMO radars. Aiming at balancing the intra- and intergroup orthogonal performances, the objective function is defined as the weighted sum of the intra- and intergroup orthogonal performance metrics. To solve the formulated model, in this article, a group orthogonal waveform design algorithm is proposed. Based on a primal-dual-type method and proper relaxations, the proposed algorithm transforms the original problem into a series of simple subproblems. Numerical results demonstrate that the obtained group orthogonal waveforms have the ability to flexibly suppress DRFM-based deceptive jamming, which is not achievable using p-majorization–minimization (p-MM) and primal-dual, two of the most advanced orthogonal waveform design algorithms.

Retinal Müller glia (MG) can act as stem-like cells to generate new neurons in both zebrafish and mice. In zebrafish, retinal regeneration is innate and robust, resulting in the replacement of lost neurons and restoration of visual function. In mice, exogenous stimulation of MG is required to reveal a dormant and, to date, limited regenerative capacity. Zebrafish studies have been key in revealing factors that promote regenerative responses in the mammalian eye. Increased understanding of how the regenerative potential of MG is regulated in zebrafish may therefore aid efforts to promote retinal repair therapeutically. Developmental signaling pathways are known to coordinate regeneration following widespread retinal cell loss. In contrast, less is known about how regeneration is regulated in the context of retinal degenerative disease, i.e., following the loss of specific retinal cell types. To address this knowledge gap, we compared transcriptomic responses underlying regeneration following targeted loss of rod photoreceptors or bipolar cells. In total, 2,531 differentially expressed genes (DEGs) were identified, with the majority being paradigm specific, including during early MG activation phases, suggesting the nature of the injury/cell loss informs the regenerative process from initiation onward. For example, early modulation of Notch signaling was implicated in the rod but not bipolar cell ablation paradigm and components of JAK/STAT signaling were implicated in both paradigms. To examine candidate gene roles in rod cell regeneration, including several immune-related factors, CRISPR/Cas9 was used to create G0 mutant larvae (i.e., "crispants"). Rod cell regeneration was inhibited in stat3 crispants, while mutating stat5a/b, c7b and txn accelerated rod regeneration kinetics. These data support emerging evidence that discrete responses follow from selective retinal cell loss and that the immune system plays a key role in regulating "fate-biased" regenerative processes.

ObjectiveThis study aimed to explore the radiomics model based on magnetic resonance imaging (MRI) T2WI and compare the value of different machine algorithms in preoperatively predicting tumor budding (TB) grading in rectal cancer.MethodsA retrospective study was conducted on 266 patients with preoperative rectal MRI examinations, who underwent complete surgical resection and confirmed pathological diagnosis of rectal cancer. Among them, patients from Qingdao West Coast Hospital were assigned as the training group (n=172), while patients from other hospitals were assigned as the external validation group (n=94). Regions of interest (ROIs) were delineated, and image features were extracted and dimensionally reduced using the Least Absolute Shrinkage and Selection Operator (LASSO). Eight machine algorithms were used to construct the models, and the diagnostic performance of the models was evaluated and compared using receiver operating characteristic (ROC) curves and the area under the curve (AUC), as well as clinical utility assessment using decision curve analysis (DCA).ResultsA total of 1197 features were extracted, and after feature selection and dimension reduction, 11 image features related to TB grading were obtained. Among the eight algorithm models, the support vector machine (SVM) algorithm achieved the best diagnostic performance, with accuracy, sensitivity, and specificity of 0.826, 0.949, and 0.723 in the training group, and 0.713, 0.579, and 0.804 in the validation group, respectively. DCA demonstrated the clinical utility of this radiomics model.ConclusionThe radiomics model based on MR T2WI can provide an effective and noninvasive method for preoperative TB grading assessment in patients with rectal cancer.

Abstract Background CircRNAs are essential for the regulation of post-transcriptional gene expression, including as miRNA sponges, and play an important role in disease development. Some computational tools have been proposed recently to predict circRNA, since only one classifier is used, there is still much that can be done to improve the performance. Results StackCirRNAPred was proposed, the computational classification of long circRNA from other lncRNA based on stacking strategy. In order to cope with the potential problem that a single feature might not be able to distinguish circRNA well from other lncRNA, we first extracted features from different sources, including nucleic acid composition, sequence spatial features and physicochemical properties, Alu and tandem repeats. We innovatively apply the stacking strategy to integrate the more advantageous classifiers of RF, LightGBM, XGBoost. This allows the model to incorporate these features more flexibly. StackCirRNAPred was found to be significantly better than other tools, with precision, accuracy, F1, recall and MCC of 0.843, 0.833, 0.831, 0.819 and 0.666 respectively. We tested it directly on the mouse dataset. StackCirRNAPred was still significantly better than other methods, with precision, accuracy, F1, recall and MCC of 0.837, 0.839, 0.839, 0.841, 0.677. Conclusions We proposed StackCirRNAPred based on stacking strategy to distinguish long circRNAs from other lncRNAs. With the test results demonstrating the validity and robustness of StackCirRNAPred, we hope StackCirRNAPred will complement existing circRNA prediction methods and is helpful in down-stream research.

Rheumatoid arthritis (RA) is an ordinarily occurring autoimmune disease with systemic inflammatory. Targeted drug delivery systems have many successful applications in the treatment of rheumatoid arthritis. In order to develop nanoparticles for targeted delivery of Celastrol (Cel) to rheumatoid arthritis and specific drug release, the dextran sulfate (DS) was modified as the targeting molecular by binding to the scavenger receptor of macrophage. The dextran-sulfate-PVGLIG-celastrol (DS-PVGLIG-Cel), named DPC, amphiphilic polymeric prodrug was synthesized and characterized. The resulting DPC@Cel micelles had the average size of 189.9 nm. Moreover, the micelles had ultrahigh entrapment efficiency (about 44.04%) and zeta potential of −11.91 mV. In the in vitro release study, due to the excessive production of matrix metalloproteinase-2 (MMP-2) at the inflammatory joint, the MMP-2 reactive peptide was used to crack in the inflammatory microenvironment to accelerate the release of Cel. The results have shown that the nanoparticles can effectively deliver Cel to activated macrophages and significantly improve the bioavailability. In vivo experiments showed that DPC@Cel have better anti-rheumatoid arthritis effects and lower systemic toxicity than free Cel. This study provided a new therapeutic strategy for the treatment of RA.

Objectives Despite the advancement in anticancer drug therapies, cancer treatment decisions are often complex and preference-sensitive, making them well suited for studying shared decision-making (SDM). Our study aimed to assess preferences for new anticancer drugs among three common types of patients with cancer to inform SDM.Design We identified five attributes of new anticancer drugs and used a Bayesian-efficient design to generate choice sets for a best–worst discrete choice experiment (BWDCE). The mixed logit regression model was applied to estimate patient-reported preferences for each attribute. The interaction model was used to investigate preference heterogeneity.Setting The BWDCE was conducted in Jiangsu province and Hebei province in China.Participants Patients aged 18 years or older, who had a definite diagnosis of lung cancer, breast cancer or colorectal cancer were recruited.Results Data from 468 patients were available for analysis. On average, the most valued attribute was the improvement in health-related quality of life (HRQoL) (p

Abstract Background Anovulation is one of the main causes of female infertility. This study will evaluate the effectiveness and safety of Bushen Culuan Decoction for anovulatory infertility caused by six diseases, including anovulatory abnormal uterine bleeding, polycystic ovarian syndrome, hyperprolactinemia, luteinized unruptured follicle syndrome, corpus luteum insufficiency, and premature ovarian insufficiency. Methods This is a randomized, double-blinded, double-dummy, parallel, positively controlled, adaptive, multicenter clinical trial. All participants will be randomly allocated by a central randomization system to the treatment group or the control group in a 1:1 ratio. The treatment group will undergo a 14-day treatment with Bushen Culuan Decoction 13 g three times a day and a 5-day treatment with clomiphene citrate placebo tablets 50 mg once a day starting on day 5 of every menstrual period. The control group will undergo a 14-day treatment with Bushen Culuan Decoction placebo 13 g three times a day and a 5-day treatment with clomiphene citrate tablets 50 mg once a day from day 5 in every menstrual period. The whole treatment will last through 3 menstrual periods or 6 menstrual periods, depending on whether ovulation is regained in the first 3 menstrual periods. All statistical analyses will be performed in SPSS 21.0 (SPSS, Chicago, Illinois, USA), and a p value

Abstract This letter formulates a high‐dimensional multi‐objective optimization model to minimize all correlation function values for multiple input multiple output (MIMO) radar waveforms. Then, to solve this problem, this letter proposes an adaptive weighted cyclic algorithm‐new (CAN), named p‐norm weighted cyclic algorithm‐new (p‐WeCAN). Specifically, the adaptive weight updating function is constructed using p‐norm to minimize peak side‐lobe level (PSL) and integrated side‐lobe level (ISL) simultaneously. Numerical results show that the p‐norm weighted cyclic algorithm‐new obtains similar PSL values as the best PSL minimization algorithm and low integrated side‐lobe level values close to its lower bound at the same time.

Traumatic brain injury (TBI) is one of the main causes of disability and death, especially in plateau areas, where the degree of injury is often more serious than in plain areas. It is likely that high altitude (HA) aggravates neuroinflammation; however, prior studies are limited. This study was designed to evaluate the effects of HA on the degree of TBI and the neuroprotective effects and underlying mechanisms of L-serine against TBI at HA (HA-TBI). In in vivo experiments, wild-type mice and mice with Nfat1 (Nfat1−/−) deficiency in the C57BL/6 background were kept in a hypobaric chamber for 3 days under simulated conditions of 4,000 m, 6,000 m and 8,000 m above sea level. After leaving the chamber, the standardized TBI model was established immediately. Mice were then intraperitoneally injected with L-serine (342 mg.kg−1) 2 h after TBI and then daily for 5 days. Behavioral tests and histological analysis were assessed at different time points post TBI induction. In vitro, we applied primary cultured microglia for hypoxia treatment (1% O2 for 24 h). The major findings include the following: (1) with increasing altitude, the neurological function of TBI mice decreased, and the damage to cerebral gray matter and white matter became more significant, (2) L-serine significantly improved the sensorimotor function of mice, reversed the increase in brain lesion volume, and promoted the renovation of brain tissue after HA-TBI, (3) L-serine significantly decreased the activation of microglia and promoted microglia polarization toward the protective M2 phenotype both in vivo and in vitro, (4) L-serine significantly suppressed the expression of NFAT1 in mice after HA-TBI and inhibited NFAT1 expression in primary microglia after hypoxia, and (5) knockout of Nfat1 inhibited the inflammatory reaction caused by excessive activation of microglia, and L-serine lost its neuroprotective effect in Nfat1 knockout mice. The present study suggests that HA aggravates brain damage after TBI and that the damage also increases with increasing altitude. As an endogenous amino acid, L-serine may be a neuroprotective agent against HA-TBI, and suppression of NFAT1 in microglia is a potential therapy for neuroinflammation in the future.

ObjectiveTo evaluate the impact of deep learning image reconstruction (DLIR) and adaptive statistical iterative reconstruction-Veo (ASIR-V) on abdominal CT radiomic features acquired in portal venous phase in liver tumor patients.MethodsSixty patients with liver tumors who underwent contrast-enhanced abdominal CT were retrospectively enrolled. Six groups including filtered back projection (FBP), ASIR-V (30%, 70%) and DLIR at low (DLIR-L), medium (DLIR-M and high (DLIR-H), were reconstructed using portal venous phase data. CT-based radiomic features (first-order, texture and wavelet features) were extracted from 2D and 3D liver tumors, peritumor and liver parenchyma. All features were analyzed for comparison. P < 0.05 indicated statistically different. The consistency of 3D lesion feature extraction was assessed by calculating intraclass correlation coefficient (ICC).ResultsDifferent reconstruction algorithms influenced most radiomic features. The percentages of first-order, texture and wavelet features without statistical difference among 2D and 3D lesions, peritumor and liver parenchyma for all six groups were 27.78% (5/18), 5.33% (4/75) and 5.56% (1/18), respectively (all p > 0.05), and they decreased while the level of reconstruction strengthened for both ASIR-V and DLIR. Compared with FBP, the features of ASIR-V30% and 70% without statistical difference decreased from 71.31% to 23.95%, and DLIR-L, DLIR-M, and DLIR-H decreased from 31.65% to 27.11% and 23.73%. Among texture features, unaffected features of peritumor were larger than those of lesions and liver parenchyma, and unaffected 3D lesions features were larger than those of 2D lesions. The consistency of 3D lesion first-order features was excellent, with intra- and inter-observer ICCs ranging from 0.891 to 0.999 and 0.880 to 0.998.ConclusionsBoth ASIR-V and DLIR algorithms with different strengths influenced the radiomic features of abdominal CT images in portal venous phase, and the influences aggravated as reconstruction strength increased.

Abstract Background As a metastasis-related protein, NEDD9 has been reported in breast cancer (BC) metastasis research. However, there are few studies on the upstream regulators of NEDD9, especially involving the potential role of miRNAs. The purpose of this study was to explain whether miR-107 potentially regulates NEDD9, which may lead to invasion and metastasis of BC. Methods MCF-7 and MDA-MB-231 cells were transduced with lentiviruses to construct stably transduced cells with miR-107 overexpression, miR-107 silencing or empty vectors. A luciferase reporter assay was performed to verify the binding of miR-107 and NEDD9. The scratch test and Transwell assay were used to measure cell migration and invasion ability, respectively. For the study of metastasis in vivo, we injected MDA-MB-231 cells into the fat pad of nude mice to develop an orthotopic breast cancer model. Results We found that NEDD9 expression correlates with the prognosis of BC patients. In BC cell lines, NEDD9 was positively correlated with cell migration ability. Further research revealed that miR-107 inhibited NEDD9 expression by targeting the 3′-untranslated region of NEDD9. Overexpression of miR-107 suppressed the expression of NEDD9, thereby inhibiting the invasion, migration and proliferation of BC cells, but interference with miR-107 promoted the expression of NEDD9 as well as invasion, migration and proliferation. In an in vivo model, overexpression of miR-107 decreased the expression of NEDD9 and inhibited tumour growth, invasion and metastasis; however, these effects were reversed by inhibiting miR-107. Conclusions These findings indicated the potential role of miR-107 in regulating NEDD9 in the invasion, migration and proliferation of BC.

A growing number of studies have shown that aberrant microRNA (miRNA) expression is closely associated with the evolution and development of various complex human diseases. These key biomarkers’ identification and observation are significant for gaining a deeper understanding of disease pathogenesis and therapeutic mechanisms. Consequently, pinpointing potential miRNA–disease associations (MDA) has become a prominent bioinformatics subject, encouraging several new computational methods given the advances in graph neural networks (GNN). Nevertheless, these existing methods commonly fail to exploit the network nodes’ global feature information, leaving the generation of high-quality embedding representations using graph properties as a critical unsolved issue. Addressing these challenges, we introduce the DAEMDA, a computational method designed to optimize the current models’ efficacy. First, we construct similarity and heterogeneous networks involving miRNAs and diseases, relying on experimentally corroborated miRNA–disease association data and analogous information. Then, a newly-fashioned parallel dual-channel feature encoder, designed to better comprehend the global information within the heterogeneous network and generate varying embedding representations, follows this. Ultimately, employing a neural network classifier, we merge the dual-channel embedding representations and undertake association predictions between miRNA and disease nodes. The experimental results of five-fold cross-validation and case studies of major diseases based on the HMDD v3.2 database show that this method can generate high-quality embedded representations and effectively improve the accuracy of MDA prediction.

With the increasing intelligence of automobiles, vehicle pre-ventilation can be better controlled. In summer, cars parked in the open air are directly exposed to sunlight; thus, a high-temperature environment is formed in the occupant cabin, which seriously affects the passengers and driver’s riding and driving experience. Meanwhile, lowering the temperature of the passenger compartment from a very high temperature to a comfortable temperature consumes a lot of energy. Therefore, it is increasingly important to study the pre-ventilation of the cabin in order to improve the thermal comfort of the occupant cabin and reduce energy consumption. In this paper, a new theoretical model of a cabin temperature control system is proposed. To support the theoretical model, an outdoor parking temperature rise test was carried out. Environmental parameters were obtained and used as the boundary conditions of the subsequent simulation. Based on the mechanism of the cabin temperature rise, the convective heat transfer coefficient on the body surface, the equivalent heat transfer model of the cabin, the solar radiation model and the physical properties of the air, a computational simulation of the temperature rise in the occupant cabin was carried out, and a simulation of the temperature rise in the occupant cabin exposure was studied. The simulation results were compared with the experimental findings to verify the accuracy of the simulation, which provided a reference for the design of the pre-cooling function of the occupant cabin. This study revealed that the pre-ventilation model developed reduces the vehicle cabin temperature through optimal control of air supply volumes and air supply angles. Furthermore, the developed pre-ventilation model is capable of reducing energy consumption, thereby reducing greenhouse gas emissions.

Abstract Dual‐band photomultiplication type polymer photodetectors (PM‐PPDs) are achieved with the structure of ITO/PDIN/poly[N,N′‐bis(4‐butylphenyl)‐N,N′‐bis(phenyl)benzidine] (poly‐TPD):2,2′‐((2Z,2′Z‐(12,13‐bis(2‐ethylhexyl)‐3,9‐diundecyl‐12,13‐dihydro‐[1,2,5]thiadiazolo[3,4‐e]thieno[2′′,3′′:4′,5′]thieno‐[2′,3′:4,5] pyrrolo‐[3,2‐g]thieno[2′,3′:4,5]thieno[3,2‐b]indole‐2,10‐diyl)bis‐(methanylylidene)) bis‐(5,6‐difluoro‐3‐oxo‐2,3‐dihydro‐1H‐indene‐2,1‐diylidene))‐dimalononitrile (Y6) (100:2, wt/wt)/MoO3/poly(3‐hexylthiophene) (P3HT):[6,6]‐phenyl‐C71‐butyric acid methyl ester (PC71BM) (100:2, wt/wt)/Al. Electron traps can be formed with Y6 surrounded by poly‐TPD or with PC71BM surrounded by P3HT. Trapped electrons near ITO/PDIN or Al electrode can assist hole tunneling injectionunder forward or reverse bias, respectively. The dual‐band PM‐PPDs exhibit ultraviolet spectral response under forward bias dependent on trapped electron distribution near ITO/PDIN electrode, while presenting visible spectral response under reverse bias determined by trapped electron distribution near Al electrode. The performance of dual‐band PM‐PPDs can be optimized by decreasing P3HT:PC71BM layer thickness. The optimal dual‐band PM‐PPDs exhibit external quantum efficiency (EQE) of 2800% at 350 nm under +10 V bias with full‐width at half‐maximum of 80 nm, while achieving EQE of 7500% at 430 nm under −10 V bias. The EQE values of optimal dual‐band PM‐PPDs are markedly improved by raising bias, reaching 13 000% at 350 nm under +16 V bias and 27 000% at 430 nm under −16 V bias. This work provides an effective method to prepare dual‐band PM‐PPDs by manipulating the interfacial trapped electron distribution.

Fencing is the most economical method of restoring degraded desert ecosystems, and plays an important role in promoting plant community diversity and productivity, as well as stable ecosystem structure and function. In this study, we selected a typical degraded desert plant community (Reaumuria songorica–Nitraria tangutorum) on the edge of a desert oasis in the Hexi Corridor in northwest China. We then investigated succession in this plant community and corresponding changes in soil physical and chemical characteristics over 10 years of fencing restoration to analyze the mutual feedback mechanisms. The results showed that: 1) The diversity of plant species in the community increased significantly over the study period, especially the number of herbaceous layer species, which increased from four in the early stage to seven in the late stage. The dominant species also changed, with the dominant shrub layer species shifting from N. sphaerocarpa in the early stage to R. songarica in the late stage. The dominant herbaceous layer species changed from the annual herb Suaeda glauca in the early stage to S. glauca and Artemisia scoparia in the middle stage, and ultimately to A. scoparia and Halogeton arachnoideus in the late stage. In the late stage, Zygophyllum mucronatum, H. arachnoideus, and Eragrostis minor began to invade, and the density of perennial herbs also increased significantly (from 0.01 m-2 to 0.17 m-2 for Z. kansuense in year seven). 2) As the duration of fencing increased, the soil organic matter (SOM) and total nitrogen (TN) contents first decreased then increased, whereas the available nitrogen, potassium, and phosphorus contents showed the opposite trend. 3) Changes in community diversity were mainly affected by the nursing effects of the shrub layer, as well as soil physical and chemical properties. That is, fencing significantly increased the vegetation density of the shrub layer, which promoted growth and development of the herbaceous layer. However, community species diversity was positively correlated with SOM and TN. The diversity of the shrub layer was positively correlated with the water content of deep soil, whereas that of the herbaceous layer was positively correlated with SOM, TN, and soil pH. The SOM content in the later stage of fencing was 1.1 times that in the early stage of fencing. Thus, fencing restored the density of the dominant shrub species and significantly increased species diversity, especially in the herb layer. Studying plant community succession and soil environmental factors under long-term fencing restoration is highly significant for understanding community vegetation restoration and ecological environment reconstruction at the edge of desert oases.

IntroductionMechanical circulatory support (MCS) can help to maintain hemodynamic stability, improve cardiac function, reduce cardiac load, and is an important method for the treatment of advanced heart failure. However, traditional MCS systems [IABP, Impella, TandemHerat, veno-arterial extracorporeal membrane oxygenation (VA-ECMO)] are associated with limitations including trauma, a high rate of complications (hemolysis, bleeding) and require complex care from nurses.Case summaryWe report a case of left heart failure resulting from dilated cardiomyopathy in a 24 years-old man. A catheter was placed through the right jugular vein and a drainage tube was positioned under ultrasound guidance through the superior vena cava, right atrium, atrial septum, to the left atrium, and returned to the axillary artery using an extracorporeal magnetic levitation ventricular assist device (VAD). The patient was successfully supported for 10 days and bridged to heart transplant.DiscussionTo the best of our knowledge, this is the first report of the use of an extracorporeal magnetic levitation VAD for MCS via a percutaneous approach. Our findings support the wider use of this strategy for patients awaiting myocardial recovery or who require heart bridging or transplantation.

Abstract Background Amyloids are insoluble fibrillar aggregates that are highly associated with complex human diseases, such as Alzheimer’s disease, Parkinson’s disease, and type II diabetes. Recently, many studies reported that some specific regions of amino acid sequences may be responsible for the amyloidosis of proteins. It has become very important for elucidating the mechanism of amyloids that identifying the amyloidogenic regions. Accordingly, several computational methods have been put forward to discover amyloidogenic regions. The majority of these methods predicted amyloidogenic regions based on the physicochemical properties of amino acids. In fact, position, order, and correlation of amino acids may also influence the amyloidosis of proteins, which should be also considered in detecting amyloidogenic regions. Results To address this problem, we proposed a novel machine-learning approach for predicting amyloidogenic regions, called ReRF-Pred. Firstly, the pseudo amino acid composition (PseAAC) was exploited to characterize physicochemical properties and correlation of amino acids. Secondly, tripeptides composition (TPC) was employed to represent the order and position of amino acids. To improve the distinguishability of TPC, all possible tripeptides were analyzed by the binomial distribution method, and only those which have significantly different distribution between positive and negative samples remained. Finally, all samples were characterized by PseAAC and TPC of their amino acid sequence, and a random forest-based amyloidogenic regions predictor was trained on these samples. It was proved by validation experiments that the feature set consisted of PseAAC and TPC is the most distinguishable one for detecting amyloidosis. Meanwhile, random forest is superior to other concerned classifiers on almost all metrics. To validate the effectiveness of our model, ReRF-Pred is compared with a series of gold-standard methods on two datasets: Pep-251 and Reg33. The results suggested our method has the best overall performance and makes significant improvements in discovering amyloidogenic regions. Conclusions The advantages of our method are mainly attributed to that PseAAC and TPC can describe the differences between amyloids and other proteins successfully. The ReRF-Pred server can be accessed at http://106.12.83.135:8080/ReRF-Pred/.

Abstract Background Efficient and effective genome scaffolding tools are still in high demand for generating reference-quality assemblies. While long read data itself is unlikely to create a chromosome-scale assembly for most eukaryotic species, the inexpensive Hi-C sequencing technology, capable of capturing the chromosomal profile of a genome, is now widely used to complete the task. However, the existing Hi-C based scaffolding tools either require a priori chromosome number as input, or lack the ability to build highly continuous scaffolds. Results We design and develop a novel Hi-C based scaffolding tool, pin_hic, which takes advantage of contact information from Hi-C reads to construct a scaffolding graph iteratively based on N-best neighbors of contigs. Subsequent to scaffolding, it identifies potential misjoins and breaks them to keep the scaffolding accuracy. Through our tests on three long read based de novo assemblies from three different species, we demonstrate that pin_hic is more efficient than current standard state-of-art tools, and it can generate much more continuous scaffolds, while achieving a higher or comparable accuracy. Conclusions Pin_hic is an efficient Hi-C based scaffolding tool, which can be useful for building chromosome-scale assemblies. As many sequencing projects have been launched in the recent years, we believe pin_hic has potential to be applied in these projects and makes a meaningful contribution.

The honeycomb lattice with a spin-orbit interaction can give rise to exotic quantum states. With the measurements of bulk properties and inelastic neutron scattering, Lin et al demonstrate the existence of a field induced spin-disordered state in Na2Co2TeO6 and extend the Kitaev model to 3d system.

The water diversion scheme of Heihe River Basin was implemented in 2000. Herein, we investigated the dynamic changes in soil moisture content and analyzed the fundamental reasons supporting the water diversion plan in this typical inland river basin in northwest China. Accordingly, we selected three typical landscape gradients—a mountain water conservation forest belt, an artificial sand-fixing forest belt at the edge of a desert oasis, and a desert riparian forest belt in the upper, middle, and lower reaches of the Heihe River Basin, respectively. In these diverse landscapes, an environmental measuring system was used to continuously monitor the dynamic and differentiation regularity of soil moisture in the 0–160 cm layer for 5 years. The results revealed that 1) the soil moisture content in each landscape increased and varied significantly across seasons. In the upper and middle reaches, the soil moisture content was significantly higher during the growing season than in the non-growing season, whereas the lower reach displayed a converse pattern. 2) The distribution of soil moisture at various depths of soil profiles varied significantly for each landscape. As the soil depth increased, the soil moisture in the upper reach decreased. Although the deep layers (120–160 cm) could store water in the non-growing season, the stored water was consumed during the growing season. The soil moisture content in the mid-reach initially increased, later decreased, and ultimately attained its highest level at 40–60 cm; however, the soil moisture content in the lower reach increased, and reached its highest level at 120–160 cm. 3) In the upper and middle reaches, the coefficient of variation of soil moisture decreased with an increasing soil depth, whereas the lower reach exhibited a converse trend. Similarly, the coefficient of variation of soil water storage were higher during the non-growing season than during the growing season within the upper and middle reaches, whereas an opposite trend was observed in the lower reach. 4) Since the implementation of the Heihe river water diversion plan, the soil moisture content in both the upper and middle reaches have increased but that of the lower reach has fluctuated and declined, especially in the shallow depths during the growing season. The present findings imply that the lower reaches of the Heihe River may require additional water transfers during the growing season.

BackgroundThe nucleus accumbens (NAc) is involved in the expression of cocaine addictive phenotypes, including acquisition, extinction, and reinstatement. In the NAc, D1-medium spiny neurons (MSNs) encode cocaine reward, whereas D2-MSNs encode aversive responses in drug addiction. Glutamate receptor-interacting protein 1 (GRIP1) is known to be associated with cocaine addiction, but the role of GRIP1 in D1-MSNs and D2-MSNs of the NAc in cocaine acquisition and reinstatement remains unknown.MethodsA conditioned place preference apparatus was used to establish cocaine acquisition, extinction, and reinstatement in mouse models. GRIP1 expression was evaluated using Western blotting. Furthermore, GRIP1-siRNA and GRIP1 overexpression lentivirus were used to interfere with GRIP1 in the NAc. After the behavioral test, green fluorescent protein immunostaining of brain slices was used to detect spine density.ResultsGRIP1 expression decreased during cocaine acquisition and reinstatement. GRIP1-siRNA enhanced cocaine-induced CPP behavior in acquisition and reinstatement and regulated associated spine plasticity. Importantly, the decreased GRIP1 expression that mediated cocaine acquisition and reinstatement was mainly driven by the interference of the GRIP1-GluA2 interaction in D1-MSNs and could be blocked by the interference of the GRIP1-GluA2 interaction in D2-MSNs. Interference with the GRIP1-GluA2 interaction in D1- and D2-MSNs decreased spine density in D1- and D2-MSNs, respectively.ConclusionGRIP1 in D1- and D2-MSNs of the NAc differentially modulates cocaine acquisition and reinstatement. GRIP1 downregulation in D1-MSNs has a positive effect on cocaine acquisition and reinstatement, while GRIP1 downregulation in D2-MSNs has a negative effect. Additionally, GRIP1 downregulation in D1-MSNs plays a leading role in cocaine acquisition and reinstatement.

BackgroundAlthough the left atrium (LA) plays a key role in the pathophysiology and disease progression of heart failure with preserved ejection fraction (HFpEF), the impact of type 2 diabetes mellitus (T2DM) on LA function and stiffness in HFpEF patients remains unclear. Furthermore, the prognostic value of different phases of LA function and stiffness is less well-established in HFpEF patients.MethodsThis study prospectively enrolled 164 HFpEF patients who were in sinus rhythm at the time of echocardiography, including 61 (37%) HFpEF patients with T2DM. LA reservoir, conduit, and pump function were assessed using two-dimensional volume indices and speckle tracking echocardiography. The LA stiffness was calculated as the ratio of early mitral inflow velocity-to-early annular tissue velocity (E/e’) and LA reservoir function. The primary end point was a combined outcome of heart failure hospitalization or death.ResultsLeft atrium reservoir function [measured by peak LA strain (LAS-peak)] and LA pump function (measured by LAS-active) remained significantly lower in the HFpEF patients with T2DM compared with those without T2DM, even after adjustment for potential confounders. In addition, the LA stiffness of HFpEF patients with T2DM was higher than those without T2DM. After a median follow-up of 13.7 months, 46 patients (28.1%) reached the composite end point. LAS-peak (hazard ratios: 0.88; 95% confidence interval: 0.81–0.95; P = 0.001) was significantly associated with the risk of heart failure hospitalization or death after adjusting for demographic and clinical characteristics, LV global longitudinal strain, E/e’, and LA volume index. In contrast, other LA function and stiffness parameters did not independently predict the risk of adverse events. Kaplan-Meier analysis showed that HFpEF patients with T2DM and low LAS-peak (

Abstract Bronchopulmonary dysplasia is a chronic pulmonary disease with a high incidence in premature infants, and there is still no effective treatment. The purpose of our study was to analyze the association between the use of probiotics and BPD in premature infants. We retrospectively collected clinical data of infants with gestational age

BackgroundAcute kidney injury (AKI) commonly occurs after heart transplantation (HTx), but its association with preoperative right ventricular (RV) function remains unknown. Consequently, we aimed to determine the predictive value of preoperative RV function for moderate to severe AKI after HTx.Materials and methodsFrom 1 January 2016 to 31 December 2019, all the consecutive HTx recipients in our center were enrolled and analyzed for the occurrence of postoperative AKI staged by the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Conventional RV function parameters, including RV fractional area change (RVFAC) and tricuspid annular plane systolic excursion (TAPSE), were obtained. The primary endpoint was moderate to severe AKI (the KDIGO stage 2 or 3). The secondary endpoints included the impact of AKI on intensive care unit (ICU) mortality, in-hospital mortality, and 1-year mortality.ResultsA total of 273 HTx recipients were included in the study. Postoperative AKI occurred in 209 (77%) patients, including 122 (45%) patients in stage 1 AKI, 49 (18%) patients in stage 2 AKI, and 38 (14%) patients in stage 3 AKI. Patients with higher AKI stage had lower baseline estimated glomerular filtration rate (eGFR), more frequent diabetes, higher right atrial pressure (RAP), longer cardiopulmonary bypass (CPB) duration, more perioperative red blood cell (RBC) transfusions, and worse preoperative RV function. A multivariate logistic regression model incorporating previous diabetes mellitus [odds ratio (OR): 2.21; 95% CI: 1.06–4.61; P = 0.035], baseline eGFR (OR: 0.99; 95% CI: 0.97–0.10; P = 0.037), RAP (OR: 1.05; 95% CI: 1.00–1.10; P = 0.041), perioperative RBC (OR: 1.18; 95% CI: 1.08–1.28; P < 0.001), and TAPSE (OR: 0.84; 95% CI: 0.79–0.91; P < 0.001) was established to diagnose moderate to severe AKI more accurately [the area under the curve (AUC) = 79.8%; Akaike information criterion: 274].ConclusionPreoperative RV function parameters provide additional predicting value over clinical and hemodynamic parameters, which are imperative for risk stratification in patients with HTx at higher risk of AKI.

In response to the economic and social hazards posed by the COVID-19 global pandemic, many countries have adopted various information technologies to rapidly track and control the spread of the epidemic. Health Quick Response (QR) codes are emergency measures implemented by the Chinese government in the epidemic environment to balance epidemic prevention and control with recovery of economic and social development, and facilitate public mobility across regions and access to various public spaces. The use of health codes by the public is a practical necessity, but the satisfaction of their use is influenced by multiple factors such as environment, technology, and organization. In this paper, we collected data through a questionnaire to analyze the basic situation of public satisfaction with the use of health QR codes in China and its influencing factors. The results show that perceived quality and platform trust directly affect the satisfaction of health code usage, while environmental risk and platform trust indirectly affect the satisfaction of health code usage through the mediating effect of perceived quality.

A new pH-sensitive film was developed using Artemisia sphaerocephala Krasch. gum (ASKG), soybean protein isolate (SPI), and natural anthocyanin extracted from Lycium ruthenicum Murr. The film was prepared by adsorbing anthocyanins dissolved in an acidified alcohol solution on a solid matrix. ASKG and SPI were used as the solid matrix for the immobilization of the Lycium ruthenicum Murr. anthocyanin extract, which was absorbed into the film as a natural dye using the facile-dip method. Regarding the mechanical properties of the pH-sensitive film, the tensile strength (TS) values increased approximately 2–5-fold, but the elongation at break (EB) values decreased significantly by about 60% to 95%. With the increase in anthocyanin concentration, the oxygen permeability (OP) values first decreased by about 85%, and then increased by about 364%. The water vapor permeability (WVP) values increased by about 63%, and then decreased by about 20%. Colorimetric analysis of the films revealed variations in color at different pH values (pH 2.0–10.0). Fourier-transform infrared (FT-IR) spectra and XRD patterns indicated compatibility among ASKG, SPI, and anthocyanin extracts. In addition, an application test was conducted to establish a correlation between film color change and carp meat spoilage. At storage temperatures of 25 °C and 4 °C, when the meat was totally spoiled, the TVB-N values reached 99.80 ± 2.53 mg/100 g and 58.75 ± 1.49 mg/100 g, and the film’s color changed from red to light brown and from red to yellowish green, respectively. Therefore, this pH-sensitive film could be used as an indicator to monitor the freshness of meat during storage.

Identifying readers of epigenetic marks is a critical step for understanding the role of epigenetic marks in biology. Here, the authors applied DAPPL, an all-to-all approach to profile the interactions between TFs and epigenetic modified DNA libraries.

The family with sequence similarity 13 member A (FAM13A) gene has been discovered in recent years and is related to metabolism. In this study, the function of FAM13A in precursor adipocyte proliferation in Qinchuan cattle was investigated using fluorescence quantitative polymerase chain reaction (PCR), western blotting, 5-ethynyl-2′-deoxyuridine staining, and other tests. FAM13A promoted precursor adipocyte proliferation. To determine the pathway FAM13A was involved in, transcriptome sequencing, fluorescence quantitative PCR, western blotting, and other tests were used, which identified the hypoxia inducible factor-1 (HIF-1) signalling pathway. Finally, cobalt chloride, a chemical mimic of hypoxia, was used to treat precursor adipocytes. mRNA and protein levels of FAM13A were significantly increased after hypoxia. Thus, FAM13A promoted bovine precursor adipocyte proliferation by inhibiting the HIF-1 signalling pathway, whereas chemically induced hypoxia negatively regulated FAM13A expression, regulating cell proliferation.

Abstract People prefer an attractive human–machine interaction interface, and color is an important factor affecting attractiveness. Therefore, to evaluate the color of human–machine interaction interfaces, a back propagation neural network (BPNN) optimized by the artificial bee colony (ABC) algorithm was proposed to predict and evaluate the interface color. The process of determining the weights and thresholds of each layer of BPNN was transformed into the process of searching for the best honey source. Based on a comprehensive analysis of visual aesthetics and usability, the five color evaluation characteristics of human–machine interaction interfaces (color type, color harmony, color area, color distribution, and color difference) were extracted and expressed mathematically. The color evaluation model of the human–machine interaction interface was constructed by considering the color evaluation characteristic values as the input of BPNN and the mean values of aesthetic degree and usability by subjective evaluation as the output. The color evaluation data of websites and iPhone apps were used to train and validate the model. In Study 1, the mean squared error (MSE) and R‐Square of ABC‐BPNN were 0.0399 and 0.9400, respectively. In Study 2, the MSE and R‐Square of ABC‐BPNN were 0.0285 and 0.9195, respectively. The results showed that the prediction effect of the ABC‐BPNN model was more accurate than that of the standard BPNN and Elman‐NN models. Finally, the proposed method was applied to the interface color design of an app to improve young people's sleep, producing a color scheme that fulfilled the user's psychological expectations, which accelerated the design process.

Background and Aims: Hepatic iron overload always leads to oxidative stress, which has been found to be involved in the progression of liver disease. However, whether iron disorder is involved in acute liver disease and the further molecular mechanisms remain unclear.Methods: A mice model of acute liver injury (ALI) was established via intraperitoneal injection of thioacetamide (TAA) (250 mg/kg/day) for 3 consecutive days. Ferrostatin-1 (Fer-1) was administered intraperitoneally (2.5 μM/kg/day) starting 3 days before TAA treatment. Deferoxamine (DFO) was intraperitoneally injected (200 mg/kg/day) with TAA treatment for 3 days. We further observed the effect of Fer-1 on TAA model with high-iron diet feeding. ALI was confirmed using histological examination and liver function activity. Moreover, expressions of iron metabolism and ferroptosis proteins were measured by Western blot analysis.Results: The study revealed that the iron accumulation and ferroptosis contributed to TAA-induced ALI pathogenesis. TAA induced prominent inflammation and vacuolar degeneration in the liver as well as liver dysfunction. In addition, protein expression of the cystine/glutamate antiporter SLC7A11 (xCT) and glutathione peroxidase 4 (GPX4) was significantly decreased in the liver, while transferrin receptor 1 (TfR1), ferroportin (Fpn) and light chain of ferritin (Ft-L) expression levels were increased after TAA exposure. As the same efficiency as DFO, pre-administration of Fer-1 significantly decreased TAA-induced alterations in the plasma ALT, AST and LDH levels compared with the TAA group. Moreover, both Fer-1 and DFO suppressed TfR1, Fpn and Ft-L protein expression and decreased iron accumulation, but did not affect xCT or GPX4 expression in the liver. Both Fer-1and DFO prevented hepatic ferroptosis by reducing the iron content in the liver. Furthermore, Fer-1 also reduced iron and reversed liver dysfunction under iron overload conditions.Conclusion: These findings indicate a role of TAA-induced iron accumulation and ferroptosis in the pathogenesis of ALI model. The effect of Fer-1 was consistent with that of DFO, which prevented hepatic ferroptosis by reducing the iron content in the liver. Thus, Fer-1 might be a useful reagent to reverse liver dysfunction and decreasing the iron content of the liver may be a potential therapeutic strategy for ALI.

Thermal-jet for water Measurement spallation is a rock removal process that utilizes induced thermal stress to fracture the rock into small fragments before melting of the rock occurs. Because of the low conductivity, thermal stress will be created on the rock surface. When the thermal stress exceeds the strength of the rock, cracks will form and expand. Eventually, rocks disintegrating into small fragments. The simulation result obtained by the Crank–Nicolson method of the temperature field and the distribution of thermal stress has been analyzed. The result indicates that during thermal spallation drilling, the temperature of the surface exposed to the thermal-jet for water Measurement rises rapidly and create temperature gradients in both radial and axial directions. Because of volume expansion, the heated part is subjected to compressive stress in radial direction and shear stress in axial direction, respectively. The result is very helpful to the field application.

Abstract Background Methylation of cytosine bases in DNA is a critical epigenetic mark in many eukaryotes and has also been implicated in the development and progression of normal and diseased cells. Therefore, profiling DNA methylation across the genome is vital to understanding the effects of epigenetic. In recent years the Illumina HumanMethylation450 (HM450K) and MethylationEPIC (EPIC) BeadChip have been widely used to profile DNA methylation in human samples. The methods to predict the methylation states of DNA regions based on microarray methylation datasets are critical to enable genome-wide analyses. Result We report a computational approach based on the two layers two-state hidden Markov model (HMM) to identify methylation states of single CpG site and DNA regions in HM450K and EPIC BeadChip. Using this mothed, all CpGs detected by HM450K and EPIC in H1-hESC and GM12878 cell lines are identified as un-methylated, middle-methylated and full-methylated states. A large number of DNA regions are segmented into three methylation states as well. Comparing the identified regions with the result from the whole genome bisulfite sequencing (WGBS) datasets segmented by MethySeekR, our method is verified. Genome-wide maps of chromatin states show that methylation state is inversely correlated with active histone marks. Genes regulated by un-methylated regions are expressed and regulated by full-methylated regions are repressed. Our method is illustrated to be useful and robust. Conclusion Our method is valuable for DNA methylation genome-wide analyses. It is focusing on identification of DNA methylation states on microarray methylation datasets. For the features of array datasets, using two layers two-state HMM to identify to methylation states on CpG sites and regions creatively, our method which takes into account the distribution of genome-wide methylation levels is more reasonable than segmentation with a fixed threshold.