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User identification is an essential technical support for downstream tasks such as recommendation systems, information retrieval, and collaborative filtering. Computing the similarity between user display names through classifiers is an effective solution for user identification across social networks. However, there are two problems with existing methods. Applying expert domain knowledge to extract handcrafted features of display names ignores the semantic information, resulting in poor performance of these methods. Selecting influential display names, and handcrafted features in user identification problems are also one of the difficulties. To solve these two problems, we propose a method based on the multi-feature fusion of display names using gated units. First, we extract the deep semantic features of display names through the BERT pre-trained multi-language model. Then, the gated mechanism is applied to select the handcrafted features we extracted to retain the essential features. Then, the adaptive factors are used to fuse handcrafted features and deep features to obtain user identification results across social networks. Finally, the efficiency of our model is verified on three constructed real-world multilingual display names datasets across multiple online social networks and compared with existing state-of-the-art methods. Experimental results show that the proposed algorithm outperforms the compared algorithms.

Human activity recognition(HAR) is an important research focus in ubiquitous computing. It has been widely applied in various domains, such as smart homes, healthcare assistance, and sports training. Accurate human activity recognition directly impacts the performance of downstream tasks. Existing methods for human activity recognition primarily rely on extracting temporal or spatial features from the data. These features are used for the task of human activity recognition. The existing methods mainly use CNN or RNN models to model the Euclidean correlations among spatially adjacent sensors or channels. However, non-Euclidean pairwise correlations among all sensors or channels are even critical for accurate classification, which has been ignored by the existing methods. In this paper, we incorporate fine-grained spatial structural data into the model to overcome these limitations. A novel deep learning model for human activity recognition is proposed, which is called the fine-grained data-oriented Spatial-Temporal Graph Transformer network (STGT). The introduction of the STGT model can eliminate the limitations of existing spatial feature extraction methods by leveraging a novel data organization approach proposed in this study. This model enhances the spatial features within the time feature extraction module for effective spatio-temporal feature extraction. We conducted experiments on four large-scale real-world HAR datasets to evaluate its performance. The experimental results demonstrate the superiority of our method over state-of-the-art approaches.

BackgroundPolycystic ovary syndrome (PCOS) can lead to infertility and increase the risk of endometrial cancer. Analyzing the macrophage polarization characteristics in ovarian tissues of PCOS is crucial for clinical treatment.MethodsWe obtained 13 PCOS and nine control ovarian samples from the CEO database and analyzed differentially expressed genes (DEGs). Macrophage polarization-related genes (MPRGs) were sourced from the GeneCards and MSigDB databases. Intersection of DEGs with MPRGs identified DEGs associated with macrophage polarization (MPRDEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein–protein interaction (PPI) Network analysis were conducted on MPRDEGs. Moreover, the top 10 genes from three algorithms were identified as the hub genes of MPRGs. In addition, miRNAs, transcription factors (TFs), and drugs were retrieved from relevant databases for regulatory network analysis of mRNA-miRNA, mRNA-TF, and mRNA-Drug interactions. Immune cell composition analysis between the PCOS and control groups was performed using the CIBERSORT algorithm to calculate correlations across 22 immune cell types.ResultsA total of 13 PCOS samples and nine control ovarian samples were obtained in this study. We identified 714 DEGs between the two groups, with 394 up-regulated and 320 down-regulated. Additionally, we identified 774 MPRGs, from which we derived 30 MPRDEGs by intersecting with DEGs, among which 21 exhibited interaction relationships. GO and KEGG analyses revealed the enrichment of MPRDEGs in five biological processes, five cell components, five molecular functions, and three biological pathways. Immune infiltration analysis indicated a strong positive correlation between activated nature killer (NK) cells and memory B cells, while neutrophils and monocytes showed the strongest negative correlation. Further investigation of MPRDEGs identified nine hub genes associated with 41 TFs, 82 miRNAs, and 44 drugs or molecular compounds. Additionally, qRT-PCR results demonstrated overexpression of the CD163, TREM1, and TREM2 genes in ovarian tissues from the PCOS group.ConclusionThis study elucidated the polarization status and regulatory characteristics of macrophages in ovarian tissues of the PCOS subjects, confirming significant overexpression of CD163, TREM1, and TREM2. These findings contribute to a deeper understanding of the pathogenesis of PCOS.

IntroductionExit selection is crucial in indoor emergency evacuation. Domestic and foreign scholars have found that exit choice behavior is influenced by three factors: environmental factors, social interactions, and individual internal factors. Previous studies have shown that in addition to a single environmental factor affecting exit decisions, the influence of other available exit options in the context can ultimately lead to a reversal of exit decisions -The context effect. However, the impact of context effects on exit decisions in emergency situations has not been thoroughly explored. Therefore, this article identifies three basic independent variables: context effects, crowd flows, and gender differences, to study the exit decisions of different gender groups facing different crowd flows, as well as how context effects affect existing exit decisions.MethodsIn this paper, we used virtual reality technology to construct an indoor fire scene and designed a total of 15 virtual experiments with different crowd distribution or context effects. 131 participants were divided into two groups, male and female, and their exit decisions were observed under different crowd flows and contextual effects.ResultsThe research results show that: 1) Both men and women have an innate preference to avoid crowded exits, and the proportion of following crowd evacuation significantly decreases when there are crowded crowds in the scene; 2) The exit decisions of female participants are more influenced by the crowd, while men tend to be more influenced by context effects when evacuating independently; 3) The context effects on exit decisions in emergency situations is statistically significant, and this performance is more significant in the male population. Further analysis reveals that similarity effects have a more significant impact on exit decisions than attraction effects.DiscussionsThese findings provide deeper insights into the exit choice behavior of the population and may contribute to the design of safe exits in indoor buildings. In addition, this article emphasizes the importance of context effects and provides a foundation for future research.

Abstract Background Systemic lupus erythematosus (SLE) is a common autoimmune disease that impacts various organs. Lupus nephritis (LN) significantly contributes to death in children with SLE. Toll-like receptor (TLR) adaptor interacting with SLC15A4 on the lysosome (TASL) acts as an innate immune adaptor for TLR and is implicated in the pathogenesis of SLE. A transcription factor known as signal transducer and activator of transcription 3 (STAT3), which is known to be linked to autoimmune diseases, is also involved in the development of SLE. Methods Bioinformatics and real-time quantitative PCR (qRT-PCR) was used to detect the expression of STAT3 and TASL in peripheral blood of SLE patients and their correlation. Bioinformatics analysis, qRT-PCR, luciferase assay and chromatin immunoprecipitation (ChIP) were used to verify the regulation of transcription factor STAT3 on TASL. The expression levels of STAT3, TASL and apoptosis-related genes in LPS-induced HK2 cells were detected by qRT-PCR and Western blot. TUNEL staining were used to detect the apoptosis of HK2 cells after LPS stimulation. ELISA and qRT-PCR were used to detect the levels of inflammatory cytokines in the cell culture supernatant. TASL knockdown in HK2 cells was used to detect the changes in apoptosis-related genes and inflammatory factors. The expression level of TASL in LPS-stimulated HK2 cells and its effect on cell apoptosis and inflammatory factors were observed by knocking down and overexpressing STAT3, respectively. It was also verified in a rescue experiment. Results The expressions of STAT3 and TASL were higher in SLE than in healthy children, and the expression of STAT3 was positively correlated with TASL. Transcription factor STAT3 can directly and positively regulate the expression of TASL through the promoter region binding site. The expression of STAT3, TASL and inflammatory cytokines was elevated, and the change of apoptosis was up-regulated in LPS-stimulated HK2 cells. Inhibition of STAT3 alleviates LPS-stimulated apoptosis and inflammatory response in HK2 cells through transcriptional regulation of TASL. Conclusions These findings provide new insights into the transcriptional regulation of TASL and provide new evidence of a direct regulatory relationship between signaling nodes in the lupus signaling network. Graphical Abstract

Information sources affect people’s tourism, culture, and entertainment buying. It is therefore important to study the apportionment effects by information source type and comprehensively analyze how information sources positively or negatively impact the consumption of tourism, culture, and entertainment. This research analyzed the influence of four information sources on such buying based on data from the China Family Panel Studies (CFPS) from 2014 to 2018. Regression analysis was used to examine the relationships among variables. The findings were that: (1) information sources (Internet, broadcast, print, and word of mouth) had a significant positive impact on tourism, culture, and entertainment buying; (2) the effects of information were significantly different based on age, education level, and place of residence (urban vs. rural); and (3) information source digitalization increased the share of TCE consumption in overall household consumption through improving social interactions and convenience of transactions. The findings contribute to alleviating the information asymmetry in tourism consumption, helping tourism enterprises develop targeted marketing measures, and promoting the improvement of residents’ tourism consumption.

Modification of activated carbon has the potential to improve its adsorption and separation capacity. Different concentrations of ammonia (6%, 9%, 12%, 15%) and treatment times (4 h, 6 h, 8 h, 10 h) were used to modify jujube shell carbon and coconut shell carbon in ultrasonic washing equipment. Biogas adsorption experiments were carried out with modified activated carbon to study the effect of adsorption and decarbonization on activated carbon surface functional groups. After modification, the surface alkaline functional groups of activated carbon increased, the acidic functional groups decreased, and the adsorption performance of CO2 was enhanced. In addition, the specific surface area and total pore volume of activated carbon decreased, the average pore size increased, and the degree of graphitization increased. In the experimental research range, under ultrasonic conditions, jujube shell carbon impregnated with 12% ammonia water for 4 h and coconut shell carbon impregnated with 9% ammonia water for 10 h had the best modification effect. The adsorption capacity for CO2 was 1.83 and 1.745 mmol/g, respectively, which increased by 0.8 mmol/g and 0.599 mmol/g, respectively, compared with the unmodified sample.

Abstract Ischaemia of the heart and limbs attributable to compromised blood supply is a major cause of mortality and morbidity. The mechanisms of functional angiogenesis remain poorly understood, however. Here we show that FNIP1 plays a critical role in controlling skeletal muscle functional angiogenesis, a process pivotal for muscle revascularization during ischemia. Muscle FNIP1 expression is down-regulated by exercise. Genetic overexpression of FNIP1 in myofiber causes limited angiogenesis in mice, whereas its myofiber-specific ablation markedly promotes the formation of functional blood vessels. Interestingly, the increased muscle angiogenesis is independent of AMPK but due to enhanced macrophage recruitment in FNIP1-depleted muscles. Mechanistically, myofiber FNIP1 deficiency induces PGC-1α to activate chemokine gene transcription, thereby driving macrophage recruitment and muscle angiogenesis program. Furthermore, in a mouse hindlimb ischemia model of peripheral artery disease, the loss of myofiber FNIP1 significantly improved the recovery of blood flow. Thus, these results reveal a pivotal role of FNIP1 as a negative regulator of functional angiogenesis in muscle, offering insight into potential therapeutic strategies for ischemic diseases.

Abstract Background Previous studies have suggested that systemic metabolic abnormalities are closely related to psoriatic arthritis (PsA). Gamma-glutamyl transpeptidase (GGT) and indirect bilirubin (IBIL), two essential active substances in hepatic metabolism that have been demonstrated as an oxidative and anti-oxidative factor respectively, have been proved to be involved in oxidative stress damage and inflammation in several human diseases. However, their role in PsA remains unclear. Methods In this retrospective comparative cohort study, a case group of 68 PsA patients and a control group of 73 healthy volunteers from the Third Hospital of Hebei Medical University were enrolled. Serum GGT, IBIL, GGT/IBIL ratio and C-reactive protein (CRP), a well applied bio-marker of systemic inflammatory in PsA, were compared between the two groups. Furthermore, the relationship of GGT, IBIL and GGT/IBIL with CRP were explored in PsA patients. Finally, the patients were divided into high inflammation group and low inflammation group according to the median value of CRP. Multivariate logistic regression analyses were used for the association of systemic inflammation level with GGT, IBIL and GGT/IBIL. Results Compared with healthy controls, PsA patients exhibited significantly higher serum GGT, GGT/IBIL, and CRP levels and lower IBIL levels. Serum GGT and GGT/IBIL were positively correlated with CRP, whereas IBIL were negatively correlated with CRP. Binary logistic regression analysis revealed that serum GGT was a risk factor for high CRP in PsA, whereas IBIL was a protective factor. Furthermore, GGT/IBIL was a better indicator of high CRP condition in PsA patients than either GGT or IBIL alone, as determined by the receiver operating characteristic curves. Conclusion GGT and IBIL may participate in the pathogenesis of PsA. Additionally, GGT, IBIL and the balance of the two may reflect systemic inflammation mediated by oxidative stress events related to metabolic abnormalities to a certain extent.

Epithelial–mesenchymal transition (EMT) is a complex physiological process that transforms polarized epithelial cells into moving mesenchymal cells. Dysfunction of EMT promotes the invasion and metastasis of cancer. The architectural transcription factor high mobility group AT-hook 2 (HMGA2) is highly overexpressed in various types of cancer (e.g., colorectal cancer, liver cancer, breast cancer, uterine leiomyomas) and significantly correlated with poor survival rates. Evidence indicated that HMGA2 overexpression markedly decreased the expression of epithelial marker E-cadherin (CDH1) and increased that of vimentin (VIM), Snail, N-cadherin (CDH2), and zinc finger E-box binding homeobox 1 (ZEB1) by targeting the transforming growth factor beta/SMAD (TGFβ/SMAD), mitogen-activated protein kinase (MAPK), and WNT/beta-catenin (WNT/β-catenin) signaling pathways. Furthermore, a new class of non-coding RNAs (miRNAs, circular RNAs, and long non-coding RNAs) plays an essential role in the process of HMGA2-induced metastasis and invasion of cancer by accelerating the EMT process. In this review, we discuss alterations in the expression of HMGA2 in various types of cancer. Furthermore, we highlight the role of HMGA2-induced EMT in promoting tumor growth, migration, and invasion. More importantly, we discuss extensively the mechanism through which HMGA2 regulates the EMT process and invasion in most cancers, including signaling pathways and the interacting RNA signaling axis. Thus, the elucidation of molecular mechanisms that underlie the effects of HMGA2 on cancer invasion and patient survival by mediating EMT may offer new therapeutic methods for preventing cancer progression.

Although microgravity has been implicated in osteoporosis, the precise molecular mechanism remains elusive. Here, we found that microgravity might induce mitochondrial protein buildup in skeletal muscle, alongside reduced levels of LONP1 protein. We revealed that disruptions in mitochondrial proteolysis, induced by the targeted skeletal muscle-specific deletion of the essential mitochondrial protease LONP1 or by the acute inducible deletion of muscle LONP1 in adult mice, cause reduced bone mass and compromised mechanical function. Moreover, the bone loss and weakness phenotypes were recapitulated in skeletal muscle-specific overexpressing ΔOTC mice, a known protein degraded by LONP1. Mechanistically, mitochondrial proteostasis imbalance triggered the mitochondrial unfolded protein response (UPRmt) in muscle, leading to an up-regulation of multiple myokines, including FGF21, which acts as a pro-osteoclastogenic factor. Surprisingly, this mitochondrial proteostasis stress influenced muscle–bone crosstalk independently of ATF4 in skeletal muscle. Furthermore, we established a marked association between serum FGF21 levels and bone health in humans. These findings emphasize the pivotal role of skeletal muscle mitochondrial proteostasis in responding to alterations in loading conditions and in coordinating UPRmt to modulate bone metabolism.

ObjectivePreeclampsia (PE) is a severe complication of unclear pathogenesis associated with pregnancy. This research aimed to elucidate the properties of immune cell infiltration and potential biomarkers of PE based on bioinformatics analysis.Materials and methodsTwo PE datasets were imported from the Gene ExpressioOmnibus (GEO) and screened to identify differentially expressed genes (DEGs). Significant module genes were identified by weighted gene co-expression network analysis (WGCNA). DEGs that interacted with key module genes (GLu-DEGs) were analyzed further by Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analyses. The diagnostic value of the genes was assessed using receiver operating characteristic (ROC) curves and protein-protein interaction (PPI) networks were constructed using GeneMANIA, and GSVA analysis was performed using the MSigDB database. Immune cell infiltration was analyzed using the TISIDB database, and StarBase and Cytoscape were used to construct an RBP-mRNA network. The identified hub genes were validated in two independent datasets. For further confirmation, placental tissue from healthy pregnant women and women with PE were collected and analyzed using both RT-qPCR and immunohistochemistry.ResultsA total of seven GLu-DEGs were obtained and were found to be involved in pathways associated with the transport of sulfur compounds, PPAR signaling, and energy metabolism, shown by GO and KEGG analyses. GSVA indicated significant increases in adipocytokine signaling. Furthermore, single-sample Gene Set Enrichment Analysis (ssGSEA) indicated that the levels of activated B cells and T follicular helper cells were significantly increased in the PE group and were negatively correlated with GLu-DEGs, suggesting their potential importance.ConclusionIn summary, the results showed a correlation between glutamine metabolism and immune cells, providing new insights into the understandingPE pathogenesis and furnishing evidence for future advances in the treatment of this disease.

Introduction: With recent advances in breast cancer (BC) treatment, the disease-free survival (DFS) of patients is increasing and the risk factors for recurrence and metastasis are changing. However, a dynamic approach to assessing the risk of recurrent metastasis in BC is currently lacking. This study aimed to develop a dynamically changing prediction model for recurrent metastases based on conditional survival (CS) analysis. Methods: Clinical and pathological data from patients with BC who underwent surgery at the Affiliated Hospital of Qingdao University between August 2011 and August 2022 were retrospectively analysed. The risk of recurrence and metastasis in patients with varying survival rates was calculated using CS analysis, and a risk prediction model was constructed. Results: A total of 4244 patients were included in this study, with a median follow-up of 83.16 ± 31.59 months. Our findings suggested that the real-time DFS of patients increased over time, and the likelihood of DFS after surgery correlated with the number of years of prior survival. We explored different risk factors for recurrent metastasis in baseline patients, 3-year, and 5-year disease-free survivors, and found that low HER2 was a risk factor for subsequent recurrence in patients with 5-year DFS. Based on this, conditional nomograms were developed. The nomograms showed good predictive ability for recurrence and metastasis in patients with BC. Conclusion: Our study showed that the longer patients with BC remained disease-free, the greater their chances of remaining disease-free again. Predictive models for recurrence and metastasis risk based on CS analysis can help improve the confidence of patients fighting cancer and help doctors personalise treatment and follow-up plans.

The wettability of reservoir rocks saturated with oil and water is one of the most important factors influencing petrophysics and oil recovery. Minerals with different wettability constitute the overall heterogeneous wettability in rocks. Variations in sample composition can be detected by nuclear magnetic resonance (NMR) measurements. In this paper, the method of using the magnetic susceptibility contrast between rock skeleton and saturated fluid to estimate wettability is proposed. The theoretical feasibility was firstly analyzed, and then the internal gradients caused by magnetic susceptibility contrasts were employed to interpret wettability alteration before and after ageing process in rocks. It was discovered that water and oil in the same pores experienced different internal gradients after ageing, which were associated with the differences in magnetic susceptibility contrasts. After that, the free induction decay measurement was performed to acquire magnetic susceptibility contrasts of artificial sandstone samples with the intermediate-wet condition. A refined NMR wettability index was presented and correlated with the Amott wettability tests. The experimental results demonstrate that the new method for determining wettability is feasible.

Abstract The communication between tumor cells and tumor microenvironment plays a critical role in cancer development. Cancer-associated fibroblasts (CAFs) are the major components of the tumor microenvironment and take part in breast cancer formation and progression. Here, by comparing the gene expression patterns in CAFs and normal fibroblasts, we found SPRY2 expression was significantly decreased in CAFs and decreased SPRY2 expression was correlated with worse prognosis in breast cancer patients. SPRY2 knockdown in fibroblasts promoted tumor growth and distant metastasis of breast cancer in mice. Loss of stromal SPRY2 expression promoted CAF activation dependent on glycolytic metabolism. Mechanically, SPRY2 suppressed Y10 phosphorylation of LDHA and LDHA activity by interfering with the interaction between LDHA and SRC. Functionally, SPRY2 knockdown in fibroblasts enhanced the stemness of tumor cell dependent on glycolysis in fibroblasts. Collectively, this work identified SPRY2 as a negative regulator of CAF activation, and SPRY2 in CAFs may potentially be therapeutically targeted in breast cancer treatment.

User identification across multiple online social networks is beneficial for building knowledge graphs. Under privacy protection considerations, researchers have shown increasing interest in user identification based on username similarity. However, existing solutions rely on manual features extracted by domain experts and do not exploit the deep semantic features of usernames. Moreover, existing solutions are limited to monolingual user names such as English or Chinese, ignoring other multilingual usernames. This paper proposes a multilingual pre-trained model-based username similarity method for user identification across multiple online social networks. First, we use many multilingual corpora to enable the model to learn more semantic information and extract deep semantic features of usernames. Then, fine-tuning is performed on our constructed dataset of multilingual usernames across multiple online social networks. Ultimately assess the similarity of user identities across multiple online social networks. Our method facilitates user identification with limited data. Finally, the efficiency of our model is verified on three constructed real-world multilingual username datasets across multiple online social networks and compared with existing state-of-the-art methods. Experimental results show that the proposed algorithm outperforms the compared algorithms.

Bone age is one of the most important evaluation indexes for the growth and development of children and adolescents. The bone age assessment method based on deep learning generally uses the whole left wrist X-ray film or some regions of interest in the left wrist X-ray film. Based on the entire X-ray film, the intelligent evaluation process is simple, but the accuracy is low. Although intelligent evaluation based on regions of interest has high accuracy, it requires prior knowledge and the process is complex. To solve the above problems, this paper proposes a multi-region combined method for bone age assessment. A small number of regions of interest in wrist bone X-ray films are extracted, and then the whole X-ray film and these regions of interest were used to evaluate the bone age. The experiment uses the improved Inception-ResNet-V2 convolutional neural network. The results show that compared with other bone age assessment studies on the open data set published by the North American radiological Association, this method can obtain higher accuracy of bone age assessment, with an average absolute error of 7.11 months. This method improves the efficiency and accuracy of bone age assessment while simplifying the assessment process.

IntroductionTo investigate the spatiotemporal evolution of agricultural carbon emissions and carbon absorption, analyse the spatiotemporal variations in the carbon balance, delineate carbon-offsetting regions, and formulate low-carbon development strategies tailored to various major functional zones, this study aims to promote coordinated regional ecological and environmental governance.MethodsThis study takes a perspective based on major functional zones, focuses on 17 cities in Hubei Province, studies the spatiotemporal variations in agricultural carbon budgets and carbon offsets in each city from the perspective of functional zoning and proposes a spatial optimization scheme for reducing carbon emissions.Results and discussionThe results show that both agricultural carbon emissions and carbon absorption in Hubei Province gradually increased, although the agricultural carbon budgets varied significantly among cities. Arable lands were the main agricultural carbon sinks in Hubei Province. Overall, carbon emissions exhibited declining core–periphery zonation, with Xiangyang, Jingzhou, and Huanggang serving as the centre (high emissions) and the cities of Shennongjia, Enshi, and Yichang serving as the periphery (low emissions). Carbon absorption displayed a U-shaped distribution, with high values in the east, south, and west and low values in the centre and north. The cities of Yichang, Jingmen, and Huanggang were the peak carbon sink areas. In recent years, the coordination between the agricultural carbon emissions and carbon budgets in Hubei Province has gradually improved, and agricultural carbon absorption and emissions have become increasingly balanced. Seven carbon-positive, five carbon-neutral, and five carbon-negative areas were identified in the province. Based on these findings, differentiated carbon emission reduction strategies were proposed to promote coordinated and low-carbon agriculture.

Ferroptosis has emerged as a significant factor in the development of bronchopulmonary dysplasia (BPD). Nevertheless, our understanding of the potential involvement of ferroptosis-related genes (FRGs) in BPD remains incomplete. In this study, we leveraged the Gene Expression Omnibus (GEO) database to investigate this aspect. We identified 20 differentially expressed FRGs that are associated with BPD, shedding light on their potential role in the condition.LASSO along with SVM-RFE algorithms found that 12 genes: MEG3, ACSL1, DPP4, GALNT14, MAPK14, CD82, SMPD1, NR1D1, PARP3, ACVR1B, H19, and SLC7A11 were closely related to ferroptosis modulation and immunological response. These genes were used to create a nomogram with good predictive power and were found to be involved in BPD-linked pathways. In addition, the marker genes-based prediction model performed well in external validation data sets. The study also showed a significance between BPD and control samples in terms of immune cell infiltration. These findings may help improve our understanding of FRGs in BPD and lead to the development of more effective immunotherapies.

Abstract Pet dogs are our good friends. Realizing the dog’s emotions through the dog's facial expressions is beneficial to the harmonious coexistence between human beings and pet dogs. This paper describes a study on dog facial expression recognition using convolutional neural network (CNN), which is a representative algorithm model of deep learning. Parameter settings have a profound impact on the performance of a CNN model, improper parameter setting will make the model exposes several shortcomings, such as slow learning speed, easy to fall into local optimal solution, etc. In response to these shortcomings and improve the accuracy of recognition, a novel CNN model based on the improved whale optimization algorithm (IWOA) called IWOA–CNN is applied to complete this recognition task. Unlike human face recognition, a dedicated face detector in Dlib toolkit is utilized to recognize the facial region, and the captured facial images are augmented to build an expression dataset. The random dropout layer and L2 regularization are introduced into the network to reduce the number of transmission parameters of network and avoid over fitting. The IWOA optimizes the keep probability of the dropout layer, the parameter λ of L2 regularization and the dynamic learning rate of gradient descent optimizer. Carry out a comparative experiment of IWOA–CNN, Support Vector Machine, LeNet-5 and other classifiers for facial expression recognition, its results demonstrate that the IWOA–CNN has better recognition effect in facial expression recognition and also explain the efficiency of the swarm intelligence algorithm in dealing with model parameter optimization.

PurposeIt has been reported that breast cancer (BC) with low expression of human epidermal growth factor receptor 2 (HER2) might be a distinct subtype of BC. However, the prognostic effect of low HER2 expression on BC patients remains controversial. We aim to conduct this single-institution retrospective analysis to assess HER2-low-positive BC outcomes in Chinese women and the prognostic role of TILs in HER2-low-positive early-stage BC.MethodWe retrospectively enrolled 1,763 BC patients treated in a single institution from 2017 to 2018. TILs are regarded as continuous variables and are divided into low TILs (≤10%) and high TILs (>10%) for statistical analysis. Univariate and multivariable Cox proportional hazards regression models were used to test the associations between TILs and disease-free survival (DFS) with adjustment for clinicopathologic characteristics.ResultHigh TIL levels (>10%) were associated with tumor size (>2 cm, p = 0.042), age at diagnosis (p = 0.005), Ki-67 index (>25%; p 10%), DFS was significantly improved in both the univariate (HR = 0.44, 95% CI 0.22–0.87, P = 0.018) and multivariate (HR = 0.47, 95% CI 0.23–0.95, P = 0.035) Cox models. For further subgroup analysis, HR (+)/HER2-low-positive BC with high TIL (>10%) levels was associated with improved DFS in both the univariate (HR = 0.41, 95% CI 0.19–0.90, P = 0.025) and multivariate (HR = 0.42, 95% CI 0.19–0.93, P = 0.032) Cox models. The HR (−)/HER2-0 BC with high TIL (>10%) level was not statistically significant in the univariate Cox model, but it was statistically significant in the multivariate (HR = 0.16, 95% CI 0.28–0.96, P = 0.045) Cox model.ConclusionAmong early-stage BC, no significant survival difference could be found between the HER2-positive, HER2-low-positive, and HER2-0 cohorts. High levels of TILs were significantly associated with improved DFS in HER2-low-positive patients, especially in the HR (+)/HER2-low-positive subtype.

BackgroundGlobal patterns of immune cell communications in the immune microenvironment of skin cutaneous melanoma (SKCM) haven’t been well understood. Here we recognized signaling roles of immune cell populations and main contributive signals. We explored how multiple immune cells and signal paths coordinate with each other and established a prognosis signature based on the key specific biomarkers with cellular communication.MethodsThe single-cell RNA sequencing (scRNA-seq) dataset was downloaded from the Gene Expression Omnibus (GEO) database, in which various immune cells were extracted and re-annotated according to cell markers defined in the original study to identify their specific signs. We computed immune-cell communication networks by calculating the linking number or summarizing the communication probability to visualize the cross-talk tendency in different immune cells. Combining abundant analyses of communication networks and identifications of communication modes, all networks were quantitatively characterized and compared. Based on the bulk RNA sequencing data, we trained specific markers of hub communication cells through integration programs of machine learning to develop new immune-related prognostic combinations.ResultsAn eight-gene monocyte-related signature (MRS) has been built, confirmed as an independent risk factor for disease-specific survival (DSS). MRS has great predictive values in progression free survival (PFS) and possesses better accuracy than traditional clinical variables and molecular features. The low-risk group has better immune functions, infiltrated with more lymphocytes and M1 macrophages, with higher expressions of HLA, immune checkpoints, chemokines and costimulatory molecules. The pathway analysis based on seven databases confirms the biological uniqueness of the two risk groups. Additionally, the regulon activity profiles of 18 transcription factors highlight possible differential regulatory patterns between the two risk groups, suggesting epigenetic event-driven transcriptional networks may be an important distinction. MRS has been identified as a powerful tool to benefit SKCM patients. Moreover, the IFITM3 gene has been identified as the key gene, validated to express highly at the protein level via the immunohistochemical assay in SKCM.ConclusionMRS is accurate and specific in evaluating SKCM patients’ clinical outcomes. IFITM3 is a potential biomarker. Moreover, they are promising to improve the prognosis of SKCM patients.

An autoimmune condition known as systemic lupus erythematosus (SLE) is characterized by B cell hyperresponsiveness and persistent generation of pathogenic autoantibodies that cause damage to various organs and tissues. The treatments available today are either ineffective or have adverse effects. The dysregulation of B cell activation is crucial for the emergence of SLE. MiR-7 explicitly targeted PTEN mRNA in B cells. Treatment with antagomiR-7 reduced B cell hyperresponsiveness and prevented the onset of lupus. As a result, inhibiting miR-7 may be used therapeutically to treat SLE. We developed a SA (sialic acid)-poly (D, L-lactide-co-glycolide) (SA-PLGA) nano delivery system to deliver antagomiR-7 into splenic B cells since the stability and targeted delivery of miRNA remain significant challenges in vivo. Results show that SA-PLGA nanoparticles (SA-PLGA@antagomiR-7) loaded with antagomiR-7 display good biocompatibility and shield antagomiR-7 from degradation, extending the miRNA’s duration in circulation in vivo. Additionally, in MRL/Ipr lupus mice, SA-PLGA@antagomiR-7 is successfully delivered to the splenic B cells and preferentially enriched in the diseased spleen in MRL/Ipr lupus mice. The SA-PLGA@antagomiR-7 NPs therapy effectively decreases immunological abnormalities, normalizes splenic B cell subtypes, and suppresses B cell activation. The antagomiR-7 NPs exhibit excellent therapeutic efficiency and high biosafety collectively, which may result in a more effective treatment for SLE.

Long noncoding RNAs (lncRNAs) are transcripts with lengths of more than 200 nt and limited protein-coding potential. They were found to play important roles in plant stress responses. In this study, the maize drought-tolerant inbred line AC7643 and drought-sensitive inbred line AC7729/TZSRW, as well as their recombinant inbred lines (RILs) were selected to identify drought-responsive lncRNAs in roots. Compared with non-responsive lncRNAs, drought-responsive lncRNAs had different sequence characteristics in length of genes and number of exons. The ratio of down-regulated lncRNAs induced by drought was significantly higher than that of coding genes; and lncRNAs were more widespread expressed in recombination sites in the RILs. Additionally, by integration of the modifications of DNA 5-methylcytidine (5mC), histones, and RNA N6-methyladenosine (m6A), it was found that the enrichment of histone modifications associated with transcriptional activation in the genes generated lncRNAs was lower that coding genes. The lncRNAs-mRNAs co-expression network, containing 15,340 coding genes and 953 lncRNAs, was constructed to investigate the molecular functions of lncRNAs. There are 13 modules found to be associated with survival rate under drought. We found nine SNPs located in lncRNAs among the modules associated with plant survival under drought. In conclusion, we revealed the characteristics of lncRNAs responding to drought in maize roots based on multiomics studies. These findings enrich our understanding of lncRNAs under drought and shed light on the complex regulatory networks that are orchestrated by the noncoding RNAs in response to drought stress.

Abstract Anger is a key factor affecting drivers' subjective judgment and driving skills. The influence of anger on driving behavior has been widely studied, but there is a lack of comparative research under different lighting conditions. Through a driving simulation experiment, this paper studies the influence of anger on left-turn driving behavior under two light conditions day and night. In the experiment, 32 licensed participants were divided into two groups, one in emotional neutrality and the other in anger. Among them, the emotional state of anger is induced by a traffic-related video. The results showed that compared with daytime participants, participants at night had higher anger intensity, shorter gap acceptance, and post encroachment time (PET) when left-turn driving. In addition, compared with neutral emotion participants, angry participants tended to accept shorter gap acceptance and PET when turning left. This indicates that participants failed to respond correctly to left-turn driving behavior in a state of anger. However, the response of gender differences to situational driving anger was not affected by light conditions. The anger intensity of male participants during the day and night was higher than that of female participants, and the gap between acceptance and PETs during left-turn was shorter than that of female participants. This shows that male participants are more likely to produce high-intensity anger and are more likely to make dangerous driving decisions in a state of anger. This paper puts forward some suggestions on identifying anger and preventing angry driving.

BackgroundOwing to the emergence of drugs targeting human epidermal growth factor receptor 2 (HER2), remarkable prognostic enhancement has been seen for patients with HER2-positive breast carcinoma. However, anti-HER2 medicines are applicable merely to individuals with HER2-positive tumors, and the benefit for those with low HER2 expression is unclear. The DESTINY-Breast04 phase III and RC48 clinical trial results showed the benefit of antibody-drug couples for low HER2-expressing individuals with breast carcinoma, challenging the traditional dichotomy between HER2-negative and -positive tumors. Hence, the purposes of the present work are to explore the clinicopathological traits and prognostic differences in the HER2-low expression Chinese population with early-stage breast carcinoma.MethodsData from the database of the Breast Center of the Affiliated Hospital of Qingdao University were collected from January 2008 to December 2017. We screened a total of 4,598 patients, of which 2,837 had HER2-0 tumors and 1,761 had HER2-low tumors. Additionally, clinicopathological characteristics, survival, and prognostic information were obtained. Difference comparisons were made between HER2-0 and HER2-low groups regarding the clinical traits and outcomes.ResultsWe enrolled 4598 patients, with the HR-positive subjects suffering from HER2-low breast carcinoma higher in proportion than the HR-negative patients. In contrast to HER2-0 tumors, the HER2-low tumors were linked to an older median age at diagnosis, T1 tumors, N1 stage, a higher Ki-67 index, as well as inferior histological grade. Insignificant inter-group difference was noted regarding overall survival (OS), although the HER2–0 group exhibited better disease-free survival (DFS) than the HER2-low group for the entire (P = 0.003), lymph node-negative (P = 0.009) and HR-positive (P = 0.007) populations. According to the multivariate regression finding, low HER2 expression was an inferior DFS prognostic factor in the HER2-negative population with early-stage breast cancer (HR,1.33;95% CI, 1.06-1.66; P = 0.013).ConclusionThe clinical traits of the HER2-low carcinomas differed from those of HER2–0 tumors. Despite the insignificant inter-group difference in OS, the differences in DFS were found for the overall, lymph node-negative and HR-positive subjects, suggesting the possibility of HER2-low as an inferior prognostic factor for disease progression in early-stage breast cancer.

Monitoring the dynamic fluctuations of plant immune signaling molecules is particularly meaningful and challenging in crop protection. Herein, four rhodamine-functionalized probes (F1-F4) were designed and synthesized to attempt to selectively detect a plant hormone salicylic acid (SA). Screening results revealed that probe F1 bearing a 4,5-dimethoxy-2-nitrobenzyl carbamate moiety was extremely sensitive and selective towards SA along with a conspicuous fluorescence “turn-on” manner. The Job’s plot experiment disclosed a 1:1 binding mode together with a binding constant of 1.34 × 104 M−1, indicating that an appreciable hydrogen bonding interaction happened between probe F1 and SA, thereby leading to the spirolactam ring breakage and the succeeding fluorescence generation. Concentration-dependent titration assays offered an available linear relationship for quantifying SA (15–70 μM) and the detection limit of probe F1 to SA was 1 μM. Density functional theory (DFT) calculations displayed that a smaller energy gap (ΔEF1-Ⅱ = 498.89 kJ/mol) was obtained between its lowest unoccupied molecular orbital (LUMO) and highest occupied molecular orbital (HOMO), manifesting that probe F1 was more reactive and sensitive than those of probes F2-F4 (ΔE = 567.07 ∼ 601.74 kJ/mol) after adsorption with salicylic acid. Meanwhile, the possible monitoring mechanism was elucidated by 1H NMR titration experiments, probe-SA DFT calculations, and HRMS. Finally, in vivo confocal imaging results found that probe F1 could delicately and selectively monitor SA on the roots of cucumber. This study can motivate the intensive exploration of multitudinous fluorescent probes for direct SA monitoring in vivo.

Plant trichomes are epidermal structures with a wide variety of functions in plant development and stress responses. Although the functional importance of trichomes has been realized, the tedious and time-consuming manual phenotyping process greatly limits the research progress of trichome gene cloning. Currently, there are no fully automated methods for identifying maize trichomes. We introduce TrichomeYOLO, an automated trichome counting and measuring method that uses a deep convolutional neural network, to identify the density and length of maize trichomes from scanning electron microscopy images. Our network achieved 92.1% identification accuracy on scanning electron microscopy micrographs of maize leaves, which is much better performed than the other 5 currently mainstream object detection models, Faster R-CNN, YOLOv3, YOLOv5, DETR, and Cascade R-CNN. We applied TrichomeYOLO to investigate trichome variations in a natural population of maize and achieved robust trichome identification. Our method and the pretrained model are open access in Github (https://github.com/yaober/trichomecounter). We believe TrichomeYOLO will help make efficient trichome identification and help facilitate researches on maize trichomes.

Purpose Acteoside (Act), a phenylethanoid compound that was first isolated from mullein, has been widely used for the investigation of anti-inflammatory and anti-fibrotic effect. However, the mechanism of Act against unilateral ureteral obstruction (UUO)-mediated renal injury is largely unknown. Therefore, this study aimed to explore the effects of Act on UUO rats and possible mechanisms. Methods A total of 20 Sprague-Dawley (SD) rats were divided randomly into three groups (n ≥ 6): (i) sham-operated group (Sham); (ii) UUO group (UUO+Saline); and (iii) UUO + Act 40 mg/kg/day, (UUO+Act); Continuous gavage administration for 2 weeks postoperatively, while the rats in Sham and UUO+saline groups were given equal amounts of saline. All rats were sacrificed after 14 days, the urine and blood samples were collected for biochemical analysis, the renal tissues were collected for pathological staining and immunohistochemistry. Correlations between individual proteins were analyzed by Pearson correlation analysis. Results The results of renal function indexes and histopathological staining showed that Act could improve renal function by reducing serum creatinine, blood urea nitrogen and urine protein at the same time, Act could alleviate renal inflammation and fibrosis. In addition, the results of immunohistochemistry showed that Act could reduce the expression of inflammation and kidney injury-related proteins F4/80, Mcp-1, KIM-1 proteins, as well as the expression of fibrosis-related protein α-SMA and β-catenin. More importantly, Act can also reduce the expression of HMGN1, TLR4 and TREM-1 proteins. Conclusion These data demonstrate that Act can ameliorate UUO-induced renal inflammation and fibrosis in rats probably through triggering HMGN1/TLR4/TREM-1 pathway.

There is uncertainty regarding the usefulness of CDK4/6-inhibitor-based therapy for hormone receptor positive (HR+), human epidermal grow factor receptor 2 negative (HER2−), metastatic breast cancer (MBC), when CDK4/6 inhibitor treatment had previously failed. Furthermore, a biomarker for abemaciclib resistance has not been identified. Herein, we reported outcomes for an HR+/HER2− MBC patient diagnosed with multiple myeloma and treated with abemaciclib and exemestane, who had cancer progression after treatment with palbociclib and fulvestrant. Thalidomide was used in conjunction with all treatments. The patient had a good response to abemaciclib and exemestane, with progression-free survival much longer than previously reported. PIK3CA and TP53 mutations were identified after cancer progression following abemaciclib treatment. It is unclear whether thalidomide increased the effectiveness of abemaciclib. Whether benefit can be derived by the use of PI3K inhibitors, after cancer progression, requires further investigation, and this may be best accomplished by the use of next-generation sequencing.

Introduction: Bronchopulmonary dysplasia (BPD) is a life-threatening lung illness that affects premature infants and has a high incidence and mortality. Using interpretable machine learning, we aimed to investigate the involvement of endoplasmic reticulum (ER) stress-related genes (ERSGs) in BPD patients.Methods: We evaluated the expression profiles of endoplasmic reticulum stress-related genes and immune features in bronchopulmonary dysplasia using the GSE32472 dataset. The endoplasmic reticulum stress-related gene-based molecular clusters and associated immune cell infiltration were studied using 62 bronchopulmonary dysplasia samples. Cluster-specific differentially expressed genes (DEGs) were identified utilizing the WGCNA technique. The optimum machine model was applied after comparing its performance with that of the generalized linear model, the extreme Gradient Boosting, the support vector machine (SVM) model, and the random forest model. Validation of the prediction efficiency was done by the use of a calibration curve, nomogram, decision curve analysis, and an external data set.Results: The bronchopulmonary dysplasia samples were compared to the control samples, and the dysregulated endoplasmic reticulum stress-related genes and activated immunological responses were analyzed. In bronchopulmonary dysplasia, two distinct molecular clusters associated with endoplasmic reticulum stress were identified. The analysis of immune cell infiltration indicated a considerable difference in levels of immunity between the various clusters. As measured by residual and root mean square error, as well as the area under the curve, the support vector machine machine model showed the greatest discriminative capacity. In the end, an support vector machine model integrating five genes was developed, and its performance was shown to be excellent on an external validation dataset. The effectiveness in predicting bronchopulmonary dysplasia subtypes was further established by decision curves, calibration curves, and nomogram analyses.Conclusion: We developed a potential prediction model to assess the risk of endoplasmic reticulum stress subtypes and the clinical outcomes of bronchopulmonary dysplasia patients, and our work comprehensively revealed the complex association between endoplasmic reticulum stress and bronchopulmonary dysplasia.

Pyroptosis plays a crucial role in bronchopulmonary dysplasia (BPD) and is associated with various lung injury illnesses. However, the function of pyroptosis-related genes (PRGs) in BPD remains poorly understood. The gene expression omnibus (GEO) database was searched for information on genes associated with BPD. Twenty-five BPD-related DE-PRGs were identified, all of which were closely associated with pyroptosis regulation and immunological response. LASSO and SVM-RFE algorithms identified CHMP7, NLRC4, NLRP2, NLRP6, and NLRP9 among the 25 differentially expressed PRGs as marker genes with acceptable diagnostic capabilities. Using these five genes, we also generated a nomogram with excellent predictive power. Annotation enrichment analyses revealed that these five genes may be implicated in BPD and numerous BPD-related pathways. In addition, the ceRNA network showed an intricate regulatory link based on the marker genes. In addition, CIBERSORT-based studies revealed that alterations in the immunological microenvironment of BPD patients may be associated with the marker genes. We constructed a diagnostic nomogram and gave insight into the mechanism of BPD. Its diagnostic value for BPD must be evaluated in further research before it can be used in clinical practice.

Abstract Background Despite extensive investigations on photothermal therapy, the clinical application is restricted due to poor stability, low therapeutic efficacy of photothermal therapy agents and its affinity loss in the multistep synthesis of delivery carriers. To address this, we designed an IR792-MCN@ZIF-8-PD-L1 siRNA (IM@ZP) nanoparticle drug delivery system. IM@ZP was prepared by in situ synthesis and physical adsorption, followed by characterization. Photothermal conversion ability of IM@ZP was assessed by irradiation of near-infrared (NIR) laser, followed by analysis of its effect on 4T1 cell viability, maturation of dendritic cells (DCs) and the secretion of related cytokines in vitro, and the changes of tumor infiltrating T cells and natural killer (NK) cells in vivo. Subcutaneous 4T1 tumor-bearing mouse and lung metastasis models were established to investigate the role of IM@ZP in killing tumor and inhibiting metastasis in vivo. Results IM@ZP was uniform nanoparticles of 81.67 nm with the characteristic UV absorption peak of IR792, and could effectively adsorb PD-L1 siRNA. Under the irradiation of 808 nm laser, IM@ZP exhibited excellent photothermal performance. IM@ZP could be efficiently uptaken by 4T1 cells, and had high transfection efficiency of PD-L1 siRNA. Upon NIR laser irradiation, IM@ZP effectively killed 4T1 cells, upregulated HSP70 expression, induced DC maturation and increased secretion of TNF-α and IL-6 in vitro. Moreover, in vivo experimental results revealed that IM@ZP enhanced photothermal immunotherapy as shown by promoted tumor infiltrating CD8 + and CD4 + T cells and NK cells, and inhibited tumor growth and lung metastasis. Conclusion Together, biocompatible IM@ZP nanoparticles result in high photothermal immunotherapy efficiency and may have a great potential as a delivery system for sustained cancer therapy. Graphical Abstract

Abstract Evidence has been emerging of the importance of long non‐coding RNAs (lncRNAs) in genome instability. However, no study has established how to classify such lncRNAs linked to genomic instability, and whether that connection poses a therapeutic significance. Here, we established a computational frame derived from mutator hypothesis by combining profiles of lncRNA expression and those of somatic mutations in a tumor genome, and identified 185 candidate lncRNAs associated with genomic instability in lung adenocarcinoma (LUAD). Through further studies, we established a six lncRNA‐based signature, which assigned patients to the high‐ and low‐risk groups with different prognosis. Further validation of this signature was performed in a number of separate cohorts of LUAD patients. In addition, the signature was found closely linked to genomic mutation rates in patients, indicating it could be a useful way to quantify genomic instability. In summary, this research offered a novel method by through which more studies may explore the function of lncRNAs and presented a possible new way for detecting biomarkers associated with genomic instability in cancers.

The construction of agricultural green bases is an important part of sustainable agricultural development. This paper takes urban agriculture green bases in Shanghai as an example, choosing base construction elements, production, and ecological construction elements, as well as status assessment elements as evaluation indicators, in order to construct an evaluation system for urban agriculture green bases. Using a Bayesian network, typical urban agricultural green bases in six agricultural districts of Shanghai were evaluated. The construction of the evaluation system was analyzed by using intervention, counterfactual inference, and other methods to analyze the correlation and importance of the indicators. The results show that there are differences among the bases in various indicators, but they all reach a high level overall; base construction elements as well as production and ecological construction elements are the main factors affecting the level of urban agricultural green bases; improving the base management system (BMS), innovativeness (IN), and economic benefits (EBs) are key ways to improve the production capacity of agriculture green bases. Green base construction should pay attention to top-level design, coordinate the planning of industrial layout, technical mode, scientific and technological support, and supporting policies. Based on the conclusion, this paper provides some useful recommendations for creating urban agriculture green bases, which help promote urban agriculture transformation, upgrading, and coordinating development between urban and rural areas.

Carbon-neutral strategies have become the focus of international attention, and many countries around the world have adopted building-integrated photovoltaic (BIPV) technologies to achieve low-carbon building operation by utilizing power-generating building materials to generate energy in buildings. The purpose of this study is to review the basic status of the development of building-integrated photovoltaic (BIPV) technologies in China, to identify and analyze the existing problems and challenges, and to propose optimization strategies and methods so as to better promote the overall development of green buildings and net-zero energy consumption buildings in China and the world. Primarily, the research area of BIPV is focused on the Chinese region through a case study approach. Subsequently, it elaborates on the theoretical basis of zero-net energy buildings and BIPV as well as the current status of the construction of the world’s low-carbon building standard system, and it summarizes the annual electricity generation of zero carbon buildings adopting BIPV in some European countries. Then, the article further quantitatively and comprehensively analyzes six successful BIPV application cases in China, and it graphically and visually evaluates and demonstrates the average annual net-zero energy performance percentage of the application cases by using the EPI evaluation and measurement tool. At the same time, based on the results of the above assessment, the challenges facing the development of BIPV in China are summarized, and specific incentives for new BIPVs are proposed to address the challenges as well as strategic approaches to optimize BIPVs that are applicable to China as well as Europe and the US. Ultimately, it is concluded that several classic BIPV building cases have achieved essentially 100% net-zero energy operation and maintenance with significant reductions in CO2 emissions and savings of tens of thousands of tonnes of coal consumption. This shows that BIPV technology is gradually developing and maturing in China, and there are great advantages and incremental development space for promoting BIPV in China in the future. The application and promotion strategy of its results in China is also applicable to other countries in the world. It is hoped that based on this experience, countries around the world will implement the “carbon neutral” strategy and zero-net energy consumption development more efficiently and with higher quality so as to realize a greener and cleaner future.

Toxic pollutants in the environment, such as toxins and abused drugs, have posed a major threat to human health and ecosystem security. It is extremely desirable to develop simple, low-cost, sensitive, and reliable techniques for the detection of these pollutants in the environment. As a booming analytical method, photoelectrochemical (PEC) sensors possess low background noise and high sensitivity. The performances of PEC sensors are fundamentally related to the photoelectric conversion efficiency, which mainly depends on the properties of photoactive materials. This review aims to summarize the engineered photoactive materials, i.e., semiconductors and semiconductor-based heterojunctions, as well as their actual applications, with emphasis on sensing mechanisms in PEC sensors for the analysis of toxins and abused drugs in the environment. Finally, the future research perspectives in this field are also discussed.

Abstract Optogenetic systems and tetracycline‐induced expression systems have been used in biological research. In gene circuits, light and tetracycline are often used to control the activation or inhibition of gene expression. In our study, we used a blue light induction system and tetracycline induction system to construct an “OR” logic gate, which can specifically induce the expression of p53 protein or E‐cadherin in the case of blue light or tetracycline, thus inhibiting the growth of cutaneous squamous cell carcinoma cells. Cutaneous squamous cell carcinoma is a kind of skin surface tumour. The activation of two tumour suppressor genes has a synergistic inhibitory effect on cutaneous squamous cell carcinoma, and blue light and tetracycline also provide a flexible means for gene regulation.

Abstract Acute myeloid leukemia (AML) is the most prevalent form of acute leukemia. Patients with AML often have poor clinical prognoses. Hypoxia can activate a series of immunosuppressive processes in tumors, resulting in diseases and poor clinical prognoses. However, how to evaluate the severity of hypoxia in tumor immune microenvironment remains unknown. In this study, we downloaded the profiles of RNA sequence and clinicopathological data of pediatric AML patients from Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, as well as those of AML patients from Gene Expression Omnibus (GEO). In order to explore the immune microenvironment in AML, we established a risk signature to predict clinical prognosis. Our data showed that patients with high hypoxia risk score had shorter overall survival, indicating that higher hypoxia risk scores was significantly linked to immunosuppressive microenvironment in AML. Further analysis showed that the hypoxia could be used to serve as an independent prognostic indicator for AML patients. Moreover, we found gene sets enriched in high-risk AML group participated in the carcinogenesis. In summary, the established hypoxia-related risk model could act as an independent predictor for the clinical prognosis of AML, and also reflect the response intensity of the immune microenvironment in AML.

In malignancies, cellular senescence is critical for carcinogenesis, development, and immunological regulation. Patients with acute myeloid leukemia (AML) have not investigated a reliable cellular senescence-associated profile and its significance in outcomes and therapeutic response. Cellular senescence-related genes were acquired from the CellAge database, while AML data were obtained from the GEO and TCGA databases. The TCGA-AML group served as a training set to construct a prognostic risk score signature, while the GSE71014 set was used as a testing set to validate the accuracy of the signature. Through exploring the expression profiles of cellular senescence-related genes (SRGs) in AML patients, we used Lasso and Cox regression analysis to establish the SRG-based signature (SRGS), which was validated as an independent prognostic predictor for AML patients via clinical correlation. Survival analysis showed that AML patients in the low-risk score group had a longer survival time. Tumor immune infiltration and functional enrichment analysis demonstrated that AML patients with low-risk scores had higher immune infiltration and active immune-related pathways. Meanwhile, drug sensitivity analysis and the TIDE algorithm showed that the low-risk score group was more susceptible to chemotherapy and immunotherapy. Cell line analysis in vitro further confirmed that the SRGs in the proposed signature played roles in the susceptibility to cytarabine and YM155. Our results indicated that SRGS, which regulates the immunological microenvironment, is a reliable predictor of the clinical outcome and immunotherapeutic response in AML.

Costimulatory molecules have been found to play significant roles in anti-tumor immune responses, and are deemed to serve as promising targets for adjunctive cancer immunotherapies. However, the roles of costimulatory molecule-related genes (CMRGs) in the tumor microenvironment (TME) of acute myeloid leukemia (AML) remain unclear. In this study, we described the CMRG alterations in the genetic and transcriptional fields in AML samples chosen from two datasets. We next evaluated their expression and identified two distinct costimulatory molecule subtypes, which showed that the alterations of CMRGs related to clinical features, immune cell infiltration, and prognosis of patients with AML. Then, a costimulatory molecule-based signature for predicting the overall survival of AML patients was constructed, and the predictive capability of the proposed signature was validated in AML patients. Moreover, the constructed costimulatory molecule risk model was significantly associated with chemotherapeutic drug sensitivity of AML patients. In addition, the identified genes in the proposed prognostic signature might play roles in pediatric AML. CMRGs were found to be potentially important in the AML through our comprehensive analysis. These findings may contribute to improving our understanding of CMRGs in patients with AML, as well as provide new opportunities to assess prognosis and develop more effective immunotherapies.

Glioma is a highly malignant brain tumor with a poor survival rate. The involvement of fatty acid metabolism in glioma was examined to find viable treatment options. The information was gathered from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) databases. A prognostic signature containing fatty acid metabolism-dependent genes (FAMDs) was developed to predict glioma outcome by multivariate and most minor absolute shrinkage and selection operator (LASSO) regression analyses. In the TCGA cohort, individuals with a good score had a worse prognosis than those with a poor score, validated in the CGGA cohort. According to further research by “pRRophetic” R package, higher-risk individuals were more susceptible to crizotinib. According to a complete study of the connection between the predictive risk rating model and tumor microenvironment (TME) features, high-risk individuals were eligible for activating the immune cell-associated receptor pathway. We also discovered that anti-PD-1/PD-L1 and anti-CTLA4 immunotherapy are more effective in high-risk individuals. Furthermore, we demonstrated that CCNA2 promotes glioma proliferation, migration, and invasion and regulates macrophage polarization. Therefore, examining the fatty acid metabolism pathway aids our understanding of TME invasion properties, allowing us to develop more effective immunotherapies for glioma.

Frailty is a critical aging-related syndrome but the underlying metabolic mechanism remains poorly understood. The aim of this study was to identify novel biomarkers and reveal potential mechanisms of frailty based on the integrated analysis of metabolome and gut microbiome. In this study, twenty subjects consisted of five middle-aged adults and fifteen older adults, of which fifteen older subjects were divided into three groups: non-frail, pre-frail, and frail, with five subjects in each group. The presence of frailty, pre-frailty, or non-frailty was established according to the physical frailty phenotype (PFP). We applied non-targeted metabolomics to serum and feces samples and used 16S rDNA gene sequencing to detect the fecal microbiome. The associations between metabolites and gut microbiota were analyzed by the Spearman’s correlation analysis. Serum metabolic shifts in frailty mainly included fatty acids and derivatives, carbohydrates, and monosaccharides. Most of the metabolites belonging to these classes increased in the serum of frail older adults. Propylparaben was found to gradually decrease in non-frail, pre-frail, and frail older adults. Distinct changes in fecal metabolite profiles and gut microbiota were also found among middle-aged adults, non-frail and frail older subjects. The relative abundance of Faecalibacteriu, Roseburia, and Fusicatenibacter decreased while the abundance of Parabacteroides and Bacteroides increased in frailty. The above altered microbes were associated with the changed serum metabolites in frailty, which included dodecanedioic acid, D-ribose, D-(-)-mannitol, creatine and indole, and their related fecal metabolites. The changed microbiome and related metabolites may be used as the biomarkers of frailty and is worthy of further mechanistic studies.

Bone loss occurs in astronauts during long-term space flight, but the mechanisms are still unclear. We previously showed that advanced glycation end products (AGEs) were involved in microgravity-induced osteoporosis. Here, we investigated the improvement effects of blocking AGEs formation on microgravity-induced bone loss by using the AGEs formation inhibitor, irbesartan. To achieve this objective, we used a tail-suspended (TS) rat model to simulate microgravity and treated the TS rats with 50 mg/kg/day irbesartan, as well as the fluorochrome biomarkers injected into rats to label dynamic bone formation. To assess the accumulation of AGEs, pentosidine (PEN), non-enzymatic cross-links (NE−xLR), and fluorescent AGEs (fAGEs) were identified in the bone; 8-hydroxydeoxyguanosine (8-OHdG) was analyzed for the reactive oxygen species (ROS) level in the bone. Meanwhile, bone mechanical properties, bone microstructure, and dynamic bone histomorphometry were tested for bone quality assessment, and Osterix and TRAP were immunofluorescences stained for the activities of osteoblastic and osteoclastic cells. Results showed AGEs increased significantly and 8-OHdG expression in bone showed an upward trend in TS rat hindlimbs. The bone quality (bone microstructure and mechanical properties) and bone formation process (dynamic bone formation and osteoblastic cells activities) were inhibited after tail-suspension, and showed a correlation with AGEs, suggesting the elevated AGEs contributed to the disused bone loss. After being treated with irbesartan, the increased AGEs and 8-OHdG expression were significantly inhibited, suggesting irbesartan may reduce ROS to inhibit dicarbonyl compounds, thus suppressing AGEs production after tail-suspension. The inhibition of AGEs can partially alter the bone remodeling process and improve bone quality. Both AGEs accumulation and bone alterations almost occurred in trabecular bone but not in cortical bone, suggesting AGEs effects on bone remodeling under microgravity are dependent on the biological milieu.

Traditional villages are the spatial carriers of the excellent traditional culture of the Chinese nation, the concentrated expression of thousands of years of farming civilization, and a nonrenewable precious cultural heritage. However, in recent decades, with the rapid development of urbanization and modernization, traditional villages have rapidly declined or even disappeared. Therefore, exploring the spatial distribution characteristics and influencing factors of traditional villages and clarifying their formation and development laws, can provide a new perspective for the continuity protection of traditional villages on a cross-regional scale. This study takes six batches of 462 traditional villages in the Wuling Mountains, Hunan, China as the research object. On the basis of the analysis of the spatial distribution characteristics of overall and different ethnic minority traditional villages, this research proposes the idea of simulating the spatial distribution mechanism of traditional villages by using the multiscale geographical weighted regression (MGWR) model. Results indicate that (1) the spatial distribution of the traditional villages of the overall and different ethnic minorities shows significant agglomeration characteristics (among them, traditional Miao and Tujia villages have formed the main and sub cores of the space gathering of traditional villages in the Wuling Mountains in Hunan); and (2) compared with the least squares (OLS) method and the classic geographical (GWR) weighted regression model, the MGWR model can reflect the impact scales of different factors, and the simulation effect is better. From the perspective of influence factors, natural factors are the basis of affecting the distribution of traditional villages in the Wuling Mountain area and are generally positively correlated. Socioeconomic factors have a dual influence on the spatial distribution of traditional villages and generally have a negative correlation. Cultural factors are the key to the spatial distribution of traditional villages and are generally positively correlated. Spatial factors have no significant impact on the spatial distribution of traditional villages. On the basis of these conclusions, this study discusses the relevant strategies for the protection and development of traditional villages.

Abstract Backgrounds Stroke is a sudden disorder of cerebral blood circulation. Many studies have illustrated that dyslipidemia, hypertension, diabetes, smoking and excessive drinking are the traditional risk factors for stroke. This study aimed to observe the relationship between CYP1A1 and CYP1A2 variants and stroke risk in the Chinese population. Methods Agena MassARRAY Assay was used to genotype four single nucleotide polymorphisms (SNPs) in 477 cases and 480 controls. The chi-square test and logistic-regression analysis were used to explore the relationship between CYP1A1 and CYP1A2 variants and stroke risk. Results Individuals with CYP1A2 rs762551 C was associated with a lower risk of stroke than that of allele A. Age stratification analysis showed that rs762551 was only observed to be associated with a lower risk of stroke in ≤64ys age group. After gender stratification analysis, a significant association between rs762551 and stroke risk was found in males, but not in females. The four SNPs were found to be correlated with stroke risk in patients with hypertension, coronary heart disease, cerebral infarction and lacunar infarction. Conclusion In this study, the results first showed that CYP1A1 and CYP1A2 variants were associated with stroke risk. Larger and well-designed studies are needed to confirm the results.

Papillary renal cell carcinoma (pRCC) is one of the epithelial renal cell carcinoma (RCC) histological subtypes. Ferroptosis is a new iron-dependent form of cell death that has been seen in a variety of clinical situations. Using differentially expressed ferroptosis-related long non-coding RNAs (lncRNAs) from patients with pRCC in The Cancer Genome Atlas; we built a prognostic lncRNA-based signature. We discovered seven different lncRNAs that were strongly linked to the prognosis of patients with pRCC. High-risk scores were linked to a poor prognosis for pRCC, which was confirmed by the findings of Kaplan–Meier studies. In addition, the constructed lncRNA signature has a 1-year area under the curve (AUC) of 0.908, suggesting that it has a high predictive value in pRCC. In the high-risk group, Gene set enrichment analyses (GSEA) analysis identified immunological and tumor-related pathways. Furthermore, single-sample GSEA (ssGSEA) revealed significant differences in T cell functions checkpoint, antigen presenting cell (APC) co-stimulation, inflammation promoting, and para inflammation between the two groups with different risk scores. In addition, immune checkpoints like PDCD1LG2 (PD-L2), LAG3, and IDO1 were expressed differently in the two risk groups. In summary, a novel signature based on ferroptosis-related lncRNAs could be applied in predicting the prognosis of patients with pRCC.

Drivers’ driving decisions at yellow lights are an important cause of accidents at intersections. As proved by existing studies, driving style is an important basis for a driver to decide to pass a yellow light or not. This study, therefore, aims to investigate the effects of different driving styles on driving decisions at yellow lights under different lighting conditions. Specifically, 64 licensed drivers were recruited to comparative study the effects of different driving styles on the decision to pass through yellow lights under both daytime and nighttime lighting conditions using a driving simulator and a VR device. The results showed that maladjusted drivers more likely to pass the yellow light faster than adapted drivers (81.25% vs 43.75%) during both day and night. Male drivers had higher overall driving style scores than female drivers, and male drivers were faster and more likely to pass a yellow light than female drivers (56.25% vs 31.25%). This study also found that inexperienced drivers were faster and more likely to pass a yellow light than experienced drivers (50% vs 37.5%). Overall, maladjusted drivers are more likely to pass yellow lights, which can be improved and society properties by enhancing driving learning for maladjusted drivers.

Abstract Background In order to mitigate the risk of allele dropout (ADO) and ensure the accuracy of preimplantation genetic testing for monogenic disease (PGT-M), it is necessary to construct parental haplotypes. Typically, haplotype resolution is obtained by genotyping multiple polymorphic markers in both parents and a proband or a relative. Sometimes, single sperm typing, or tests on the polar bodies may also be useful. Nevertheless, this process is time-consuming. At present, there was no simple linkage analysis strategy for patients without affected relatives. Method To solve this problem, we established a haplotyping by linked-read sequencing (HLRS) method without the requirement for additional relatives. First, the haplotype of the genetic disease carriers in the family was constructed by linked-read sequencing, and then the informative single nucleotide polymorphisms (SNPs) in upstream and downstream mutation region were selected to construct the embryo haplotype and to determine whether the embryo was carrying the mutation. Two families were selected to validate this method; one with alpha thalassemia and the other with NDP gene disorder. Results The haplotyping by linked-read sequencing (HLRS) method was successfully applied to construct parental haplotypes without recruiting additional family members; the method was also validated for PGT-M. The mutation carriers in these families were sequenced by linked-read sequencing, and their haplotypes were successfully phased. Adjacent SNPs of the mutation gene were identified. The informative SNPs were chosen for linkage analyses to identify the carrier embryos. For the alpha thalassemia family, a normal blastocyst was transferred to the uterus and the accuracy of PGT-M was confirmed by amniocentesis at 16 weeks of gestation. Conclusions Our results suggest that HLRS can be applied for PGT-M of monogenic disorders or de novo mutations where the mutations haplotype cannot be determined due to absence of affected relatives.