Immune infiltration related CENPI associates with the malignant features and drug resistance of lung adenocarcinoma.

Centromere protein I (CENPI) is an important member of centromeric proteins family, which is crucial to chromosome alignment and segregation. Nevertheless, the interrelation between CENPI expression and tumor progression is in the shadows. In this reserch, we carried out a panoramic bioinformatic analysis about CENPI with TCGA, Timer 2.0, Oncomine, GEPIA, Cbioportal, LinkedOmics and CancerSEA databases. Besides, our bioinformatic results have been further confirmed through in vitro experiments, including Real-Time quantitative PCR (RT-qPCR), immunofluorescence (IF), immunohistochemistry (IHC), western blotting (WB), cell proliferation assays, EdU, cell cycle and apoptosis test. Our results suggested that CENPI was increased in most of the cancers, and may serve as a potential biomarker. What's more, the knock down of CENPI inhibited the expression of CDK2 in lung adenocarcinoma (LUAD), and resulted in the arrest of G0/G1 phase and apoptosis. Besides, CENPI was related to immune cells infiltration and drug sensitivity in pan-cancer, and can act as a potential treatment target to cure cancer patients.

Reinforcement Learning for Blast Furnace Ironmaking Operation With Safety and Partial Observation Considerations.

Making proper decision online in complex environment during the blast furnace (BF) operation is a key factor in achieving long-term success and profitability in the steel manufacturing industry. Regulatory lags, ore source uncertainty, and continuous decision requirement make it a challenging task. Recently, reinforcement learning (RL) has demonstrated state-of-the-art performance in various sequential decision-making problems. However, the strict safety requirements make it impossible to explore optimal decisions through online trial and error. Therefore, this article proposes a novel offline RL approach designed to ensure safety, maximize return, and address issues of partially observed states. Specifically, it utilizes an off-policy actor-critic framework to infer the optimal decision from expert operation trajectories. The "actor" in this framework is jointly trained by the supervision and evaluation signals to make decision with low risk and high return. Furthermore, we investigate a recurrent version of the actor and critic networks to better capture the complete observations, which solves the partially observed Markov decision process (POMDP) arising from sensor limitations. Verification within the BF smelting process demonstrates the improvements of the proposed algorithm in performance, i.e., safety and return.

Causal association of epigenetic aging and osteoporosis: a bidirectional Mendelian randomization study.

BACKGROUND: The relationship between aging and osteoporosis is well established. However, the relationship between the body's physiological age, i.e. epigenetic age, and osteoporosis is not known. Our goal is to analyze the bidirectional causal relationship between epigenetic clocks and osteoporosis using a bidirectional Mendelian randomization study. METHODS: We used SNPs closely associated with GrimAge, Hannum, PhenoAge, and HorvathAge in epigenetic age and SNPs closely associated with femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density as instrumental variables, respectively, using the inverse variance weighting method and several other MR methods to assess the bidirectional causal relationship between epigenetic age and osteoporosis. RESULT: There was no evidence of a clear causal relationship of epigenetic age (GrimAge, Hannum, PhenoAge, and HorvathAge) on femoral neck bone mineral density, lumbar spine bone mineral density, and forearm bone mineral density. In reverse Mendelian randomization analysis showed a significant causal effect of lumbar spine bone mineral density on GrimAge: odds ratio (OR) = 0.692, 95% confidence interval (CI) = (0.538-0.890), p = 0.004. The results suggest that a decrease in lumbar spine bone mineral density promotes an acceleration of GrimAge. CONCLUSION: There was no significant bidirectional causal relationship between epigenetic age and osteoporosis A decrease in lumbar spine bone density may lead to an acceleration of the epigenetic clock "GrimAge". Our study provides partial evidence for a bidirectional causal effect between epigenetic age and Osteoporosis.

Eph receptor B6 shapes a cold immune microenvironment, inhibiting anti-cancer immunity and immunotherapy response in bladder cancer.

Background: The role of Eph receptors and related ephrin (EFN) ligands (as the largest family of transmembrane-bound RTKs) in immunomodulation in many types of cancer, especially bladder cancer (BLCA), is scarcely known. Methods: A pan-cancer dataset was retrieved from The Cancer Genome Atlas (TCGA) to explore the relation between Eph receptor/EFN ligand family genes and immunomodulators and tumor-infiltrated immune cells (TIICs). Local BLCA, GSE32894, and GSE31684 cohorts were applied to validate. The IMvigor210 cohort was employed to explore the relationship between EPHB6 and immunotherapy response. Moreover, association between EPHB6 and molecular subtype was investigated to explore potential therapeutic strategies. Immunohistochemical staining of CD8 and CD68 was performed to validate the correlation between EPHB6 and TIICs. Results: The pan-cancer analysis revealed variations in the immunological effects of Eph receptor/EFN ligand family genes across different types of cancer. EPHB6 expression negatively correlated with the expression of the majority of immunomodulators (including HLA and immune checkpoints), and CD8 T cells and macrophages in both the TCGA-BLCA and validation BLCA cohorts, shaping a cold immune microenvironment with inhibited immunity. In the IMvigor210 cohort, patients with high-EPHB6 highly correlated with a non-inflamed, low PD-L1 expression immune phenotype, and correspondingly, with less responders to immunotherapy. The high-EPHB6 group, enriched with the basal subtype, presented significantly fewer TP53 and more FGFR3 genomic alterations. Finally, a novel EPHB6-related Genes signature, with reliable and robust ability in prognosis prediction, was constructed. Conclusions: This study comprehensively investigated the immunological effects of Eph receptor/EFN ligand family genes pan-cancer, and specially identified the immunosuppressive role of EPHB6 in BLCA. Furthermore, EPHB6 may predict the molecular subtype and prognosis of BLCA, and serve as a novel therapeutic target to improve the sensitivity of immunotherapy.

Fabrication of a protein-dextran conjugates formed oral nanoemulsion and its application to deliver the essential oil from Alpinia zerumbet Fructus.

The injury of vascular endothelial cells caused by high glucose (HG) is one of the driving factors of vascular complications of diabetes. Oral administration is the most common route of administration for the treatment of diabetes and its vascular complications. Essential oil extracts from Chinese medicine possess potential therapeutic effects on vascular endothelial injury. However, low solubility and volatility of essential oils generally result in poor oral absorption. Development of nanocarriers for essential oils is a promising strategy to overcome the physiological barriers of oral absorption. In this study, a nanoemulsion composed of bovine serum albumin (BSA)-dextran sulfate (DS) conjugate and sodium deoxycholate (SD) was constructed. The nanoemulsions were verified with promoted oral absorption and prolonged circulation time. After the primary evaluation of the nanoemulsion, essential oil from Alpinia zerumbet Fructus (EOFAZ)-loaded nanoemulsion (denoted as EOFAZ@BD5/S) was prepared and characterized. Compared to the free EOFAZ, EOFAZ@BD5/S increased the protective effects on HG-induced HUVEC injury in vitro and ameliorative effects on the vascular endothelium disorder and tunica media fibroelastosis in a T2DM mouse model. Collectively, this study provides a nanoemulsion for the oral delivery of essential oils, which holds strong promise in the treatment of diabetes-induced vascular endothelial injury.

Causal relationships between COVID-19 and osteoporosis: a two-sample Mendelian randomization study in European population.

Introduction: The causal relationship between Coronavirus disease 2019 (COVID-19) and osteoporosis (OP) remains uncertain. We aimed to assess the effect of COVID-19 severity (severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, COVID-19 hospitalization, and severe COVID-19) on OP by a two-sample Mendelian randomization (MR) study. Methods: We conducted a two-sample MR analysis using publicly available genome-wide association study (GWAS) data. Inverse variance weighting (IVW) was used as the main analysis method. Four complementary methods were used for our MR analysis, which included the MR-Egger regression method, the weighted median method, the simple mode method, and the weighted mode method. We utilized the MR-Egger intercept test and MR pleiotropy residual sum and outlier (MR-PRESSO) global test to identify the presence of horizontal pleiotropy. Cochran's Q statistics were employed to assess the existence of instrument heterogeneity. We conducted a sensitivity analysis using the leave-one-out method. Results: The primary results of IVW showed that COVID-19 severity was not statistically related to OP (SARS-CoV-2 infection: OR (95% CI) = 0.998 (0.995 ~ 1.001), p = 0.201403; COVID-19 hospitalization: OR (95% CI) =1.001 (0.999 ~ 1.003), p = 0.504735; severe COVID-19: OR (95% CI) = 1.000 (0.998 ~ 1.001), p = 0.965383). In addition, the MR-Egger regression, weighted median, simple mode and weighted mode methods showed consistent results. The results were robust under all sensitivity analyses. Conclusion: The results of the MR analysis provide preliminary evidence that a genetic causal link between the severity of COVID-19 and OP may be absent.

Gate-Level Circuit Partitioning Algorithm Based on Clustering and an Improved Genetic Algorithm.

Gate-level circuit partitioning is an important development trend for improving the efficiency of simulation in EDA software. In this paper, a gate-level circuit partitioning algorithm, based on clustering and an improved genetic algorithm, is proposed for the gate-level simulation task. First, a clustering algorithm based on betweenness centrality is proposed to quickly identify clusters in the original circuit and achieve the circuit coarse. Next, a constraint-based genetic algorithm is proposed which provides absolute and probabilistic genetic strategies for clustered circuits and other circuits, respectively. This new genetic strategy guarantees the integrity of clusters and is effective for realizing the fine partitioning of gate-level circuits. The experimental results using 12 ISCAS '89 and ISCAS '85 benchmark circuits show that the proposed algorithm is 5% better than Metis, 80% better than KL, and 61% better than traditional genetic algorithms for finding the minimum number of connections between subsets.

Global trends in research of achilles tendon injury/rupture: A bibliometric analysis, 2000-2021.

Background: The Achilles tendon is the strongest and most susceptible tendon in humans. Achilles tendon injuries and ruptures have gradually attracted research attention. However, a bibliometric analysis of global research in this field is lacking. This study involved a bibliometric analysis of the developmental trends and research hotspots in Achilles tendon injuries/ruptures from 2000 to 2021. Methods: Articles published between 2001 and 2021 were retrieved from an extended database of the Science Citation Index using Web of Science. VOSviewer and CiteSpace were used to analyze the relationships between publications, countries, institutions, journals, authors, references, and keywords. Results: This study included 3,505 studies of 73 countries, 3,274 institutions, and 12,298 authors and explored the cooperation between them and the relationships between citations. Over the past 22 years, the number of publications has significantly increased. Foot Ankle International has published the most papers on Achilles tendon injuries/ruptures, and British Journal of Sports Medicine is the most famous journal. Re-rupture, exosomes, acute Achilles tendon rupture, and tendon adhesions gradually become the research focus over the past few years. Conclusion: Achilles tendon injury and rupture are important research topics. A vast number of newly published papers on this topic have demonstrated that clinicians and researchers are interested in their study. Over time, these recent studies will be widely cited; therefore, this bibliometric analysis should be constantly updated.

RASGRP2 is a potential immune-related biomarker and regulates mitochondrial-dependent apoptosis in lung adenocarcinoma.

Background: Ras guanine nucleotide-releasing protein 2 (RASGRP2), one of the guanine nucleotide exchange factors (GEFs), has attracted much attention in recent years. However, the correlation between RASGRP2 and immune infiltration and malignant features in lung adenocarcinoma (LUAD) has rarely been mentioned. Methods: The Limma package and the LASSO regression model were performed to screen for differentially expressed genes. Data from the TCGA and 5 GEO databases were used to explore the expression level of RASGRP2 in LUAD patients. A weighted co-expression network and LinkFinder module were established to find the related genes of RASGRP2. The ESTIMATE algorithm was used to analyze the correlation between RASGRP2 and immune infiltration in LUAD. Tumor-infiltrating immune cells were sorted and sequenced at the single-cell level to analyze differences in RASGRP2. Real-time PCR and immunohistochemistry were performed in the real-world cohort to verify the expression of RASGRP2 and its correlation with immune-related genes. Clone formation and EdU assays were used to verify the proliferation ability. The proportion of apoptotic cells was analyzed by flow cytometry. Observation of mitochondrial membrane potential (MMP) changes by fluorescence microscopy. Results: Our results suggested that decreased RASGRP2 was associated with worse clinical parameters and prognosis in LUAD patients. And we constructed a FLI1-HSA-miR-1976-RASGRP2 transcriptional network to support the role of RASGRP2. Enrichment analysis revealed that RASGRP2 was involved in lymphocyte activation and leukocyte adhesion. RASGRP2 was found to be positively correlated with the infiltration of most immune cells, immunoregulators, and chemokines in a subsequent study. Meanwhile, the real-world cohort confirmed that the expression levels of PDCD1, CTLA4, CD40LG, CCL14, CXCR5, and CCR7 were higher in the high-RASGRP2 expression group. Cytological experiments proved that RASGRP2 inhibited cell proliferation in LUAD by regulating mitochondrial-dependent apoptosis. Conclusion: RASGRP2 was a potential immune-related biomarker of LUAD. In addition, RASGRP2 was involved in the malignant progression of LUAD through the regulation of mitochondrial-dependent apoptosis.

Dynamical behaviors, circuit design, and synchronization of a novel symmetric chaotic system with coexisting attractors.

In this paper, we introduce a novel three-dimension chaotic system with strange characteristic by applying construction of a 3D chaotic circuit method. Multiple equilibria and abundant coexisting attractors exist in this system. A mathematical model is developed and detailed stability analyses for equilibrium points are executed with obtaining significant results of the period-doubling bifurcation patterns confirmed by phase plane plots and Lyapunov exponent spectra. By varying the initial value and unique controlled parameter, the double-scroll chaotic attractor is broken up into a pair of symmetric singular attractors. Then, the local basins of attraction are investigated concerning the initial condition. Next, the circuit synthesis results generated by Multisim simulation tool validate the self-excitation characteristics of this system. Finally, the feedback control technique is used to study difference synchronization of this system. Main conclusions prove the validity and reliability of difference synchronization.

A Multi-Omics Analysis of NASH-Related Prognostic Biomarkers Associated with Drug Sensitivity and Immune Infiltration in Hepatocellular Carcinoma.

Background: Nonalcoholic steatohepatitis (NASH)-driven hepatocellular carcinoma (HCC) is becoming a major health-related problem. The exploration of NASH-related prognostic biomarkers and therapeutic targets is necessary. Methods: Data were downloaded from the GEO database. The "glmnet" package was used to identify differentially expressed genes (DEGs). The prognostic model was constructed by the univariate Cox and LASSO regression analyses. Validation of the expression and prognosis by immunohistochemistry (IHC) in vitro. Drug sensitivity and immune cell infiltration were analyzed by CTR-DB and ImmuCellAI. Results: We constructed a prognostic model that identified the NASH-related gene set (DLAT, IDH3B, and MAP3K4), which was validated in a real-world cohort. Next, seven prognostic transcription factors (TFs) were identified. The prognostic ceRNA network included three mRNAs, four miRNAs, and seven lncRNAs. Finally, we found that the gene set was associated with drug response which was validated in six clinical trial cohorts. Moreover, the expression level of the gene set was inversely correlated with CD8 T cell infiltration in HCC. Conclusions: We established a NASH-related prognostic model. Upstream transcriptome analysis and the ceRNA network provided clues for mechanism exploration. The mutant profile, drug sensitivity, and immune infiltration analysis further guided precise diagnosis and treatment strategies.

Flavonoid derivative DMXAA attenuates cisplatin-induced acute kidney injury independent of STING signaling.

Cisplatin-induced nephrotoxicity is the main adverse effect of cisplatin-based chemotherapy and highly limits its clinical use. DMXAA, a flavonoid derivative, is a promising vascular disrupting agent and known as an agonist of STING. Although cGAS-STING activation has been demonstrated to mediate cisplatin-induced acute kidney injury (AKI), the role of DMXAA in this condition is unclear. Here, we defined an unexpected and critical role of DMXAA in improving renal function, ameliorating renal tubular injury and cell apoptosis, and suppressing inflammation in cisplatin-induced AKI. Moreover, we confirmed that DMXAA combated AKI in a STING-independent manner, as evidenced by its protective effect in STING global knockout mice subjected to cisplatin. Furthermore, we compared the role of DMXAA with another STING agonist SR717 in cisplatin-treated mice and found that DMXAA but not SR717 protected animals against AKI. To better evaluate the role of DMXAA, we performed transcriptome analyses and observed that both inflammatory and metabolic pathways were altered by DMXAA treatment. Due to the established role of metabolic disorders in AKI, which contributes to kidney injury and recovery, we also performed metabolomics using kidney tissues from cisplatin-induced AKI mice with or without DMXAA treatment. Strikingly, our results revealed that DMXAA improved the metabolic disorders in kidneys of AKI mice, especially regulated the tryptophan metabolism. Collectively, therapeutic administration of DMXAA ameliorates cisplatin-induced AKI independent of STING, suggesting a promising potential for preventing nephrotoxicity induced by cisplatin-based chemotherapy.

Is Patient-Specific Instrumentation Accurate and Necessary for Open-Wedge High Tibial Osteotomy? A Meta-Analysis.

The purpose of this meta-analysis was to identify if patient-specific instrumentation (PSI) could increase the accuracy of the correction in high tibial osteotomy (HTO) and to explore the assessment indices and the necessity of using a PSI in HTO. A systematic search was carried out using online databases. A total of 466 patients were included in 11 papers that matched the inclusion criteria. To evaluate the accuracy of PSI-assisted HTO, the weight bearing line ratio (WBL%), hip-knee-ankle angle (HKA), mechanical medial proximal tibial angle (mMPTA), and posterior tibial slope angle (PTSA) were measured preoperatively and postoperatively and compared to the designed target values. Statistical analysis was performed after strict data extraction with Review Manager (version 5.4). Significant differences were detected in WBL% (MD = -36.41; 95% CI: -42.30 to -30.53; p < 0.00001), HKA (MD = -9.95; 95% CI: -11.65 to -8.25; p < 0.00001), and mMPTA (MD = -8.40; 95% CI:-10.27 to -6.53; p < 0.00001) but not in PTSA (MD = 0.34; 95% CI: -0.59 to 1.27; p = 0.47) between preoperative and postoperative measurements. There was no significant difference between the designed target values and the postoperative correction values of HKA (MD = 0.14; 95% CI: -0.19 to 0.47; p = 0.41) or mMPTA (MD = 0.11; 95% CI -0.34 to 0.55; p = 0.64). The data show that 3D-based planning of PSI for HTO is both accurate and safe. WBL%, HKA, and mMPTA were the optimal evaluation indicators of coronal plane correction. Sagittal correction is best evaluated by the PTSA. The present study reports that PSI is accurate but not necessary in typical HTO.

The optimal first-line treatment for patients with left-sided RAS wild-type metastatic colorectal cancer: Double-drug regimen or triple-drug regimen therapy.

There are many treatments for metastatic colorectal cancer (mCRC). Among them, uncertainty remains especially concerning the clinical benefit of different regimens for left-sided RAS wild-type (WT) mCRC in the triple-drug therapy era. No studies have been conducted to answer this critical clinical issue. We performed a comprehensive analysis of published data and real-world data. First, we conducted analyses of the published trials to show the landscape of efficacy and safety in the treatments of left-sided RAS WT mCRC. Then, we initiated a multicenter real-world study as the validation dataset. This study included six published randomized controlled trials (RCTs) and a total of 1925 patients. The double-drug regimen plus cetuximab/panitumumab (D + C/P) achieved the longest overall survival (OS) in patients with left-sided mCRC (HR = 0.74, 95%CI: 0.57-0.98), while triple-drug regimen with bevacizumab (T + B, HR = 1.1, 95%CI: 0.63-2.0), compared with double-drug with bevacizumab (D + B). The D + C/P had the highest overall response rate (ORR) in patients with left-sided mCRC (OR = 1.8, 95%CI: 0.89-3.8), while T + B (OR = 1.8, 95%CI: 0.70-4.8), compared with D + B. The multicenter real-world cohort showed the double-drug regimen plus cetuximab had longer progression-free survival (PFS) in left-sided mCRC patients than the triple-drug regimen with bevacizumab. The safety analysis showed the incidence of the adverse events (grade≥3) in the triple-drug therapy plus bevacizumab was higher than that in the double-drug therapy plus cetuximab/panitumumab. This work demonstrates the ranking of three regimens for therapeutic efficacy and safety in patients with left-sided RAS WT mCRC. The double-drug regimen plus cetuximab/panitumumab appears more effective and safer than double-drug and triple-drug based regimens with bevacizumab. Further trials and cohort analyses on this topic would increase confidence in these results.

Prognostic stratification based on m5C regulators acts as a novel biomarker for immunotherapy in hepatocellular carcinoma.

Background: Immunotherapy is a promising anti-cancer strategy in hepatocellular carcinoma (HCC). However, a limited number of patients can benefit from it. There are currently no reliable biomarkers available to find the potential beneficiaries. Methylcytosine (m5C) is crucial in HCC, but its role in forecasting clinical responses to immunotherapy has not been fully clarified. Methods: In this study, we analyzed 371 HCC patients from The Cancer Genome Atlas (TCGA) database and investigated the expression of 18 m5C regulators. We selected 6 differentially expressed genes (DEGs) to construct a prognostic risk model as well as 2 m5C-related diagnostic models. Results: The 1-, 3-, and 5-year area under the curve (AUC) of m5C scores for the overall survival (OS) was 0.781/0.762/0.711, indicating the m5C score system had an ideal distinction of prognostic prediction for HCC. The survival analysis showed that patients with high-risk scores present a worse prognosis than the patients with low-risk scores (p< 0.0001). We got consistent results in 6 public cohorts and validated them in Xiangya real-world cohort by quantitative real-time PCR and immunohistochemical (IHC) assays. The high-m5C score group was predicted to be in an immune evasion state and showed low sensitivity to immunotherapy, but high sensitivity to chemotherapy and potential targeted drugs and agents, such as sepantronium bromide (YM-155), axitinib, vinblastine and docetaxel. Meanwhile, we also constructed two diagnostic models to distinguish HCC tumors from normal liver tissues or liver cirrhosis. Conclusion: In conclusion, our study helps to early screen HCC patients and select patients who can benefit from immunotherapy. Step forwardly, for the less likely beneficiaries, this study provides them with new potential targeted drugs and agents for choice to improve their prognosis.

Effects of inflammation on voriconazole levels: A systematic review.

AIMS: This study aimed to review the studies evaluating the effect of the inflammatory state on voriconazole (VRZ) levels. METHODS: The study included randomized clinical trials, cohort studies, and case-control studies that focused on the influence of the inflammatory state on VRZ levels. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, relevant articles published until 2021 were searched in several databases, including PubMed, Embase, Web of Science and the Cochrane Library. RESULTS: Twenty studies were included in this review, of which 15 described adult populations, three described paediatric populations, and two included both adult and paediatric populations. Seventeen studies used C-reactive protein (CRP) as an indicator of inflammation, six described a dose-response relationship for the effect of inflammation represented by CRP on VRZ concentrations, and four examined the effect of CRP on the metabolic rate of VRZ. CONCLUSIONS: Our findings showed that the level of inflammation can significantly affect VRZ levels. However, the effect of inflammation on VRZ concentrations in children is controversial and must be analysed along with age. Clinicians dosing VRZ should take into account the patient's inflammatory state. The impact of inflammation on genotype-based dosing decisions requires further study to explain the high pharmacokinetic variability of VRZ.

Identification of Hub Genes and Pathways Associated with Oxidative Stress of Cartilage in Osteonecrosis of Femoral Head Using Bioinformatics Analysis.

OBJECTIVE: This study aimed to identify the hub genes and pathways of genes related to oxidative stress of cartilage in osteonecrosis of femoral head (ONFH), and to predict the transcription factors of the hub genes. METHODS: The GSE74089 was obtained from the Gene Expression Omnibus (GEO) database, including 4 necrotic tissues and 4 normal tissues, and the differentially expressed genes (DEGs) were identified by limma package in R language. Simultaneously, we searched for the genes related to oxidative stress in the Gene Ontology (GO) database. GO and signaling pathways analysis were performed using DAVID, Metascape, and GSEA. Protein-protein interaction (PPI) network was constructed using the STRING database, and the Degree algorithm of Cytoscape software was used to screen for hub genes. Finally, the NetworkAnalyst web tool was used to find the hub genes' transcriptional factors (TFs). RESULTS: In total, 440 oxidative stress-related genes were found in GSE74089 and GO database, and 88 of them were significantly differentially expressed. These genes were mainly involved in several signaling pathways, such as MAPK signaling pathway, PI3K-AKT-mTOR signaling pathway, FOXO signaling pathway. The top 10 hub genes were JUN, FOXO3, CASP3, JAK2, RELA, EZH2, ABL1, PTGS2, FBXW7, MCL1. Besides, TFAP2A, GATA2, SP1, and E2F1 may be the key regulatory factors of hub genes. CONCLUSIONS: We identified some hub genes and signaling pathways associated with oxidative stress in ONFH through a series of bioinformatics analyses.

YOLOv5s-FP: A Novel Method for In-Field Pear Detection Using a Transformer Encoder and Multi-Scale Collaboration Perception.

Precise pear detection and recognition is an essential step toward modernizing orchard management. However, due to the ubiquitous occlusion in orchards and various locations of image acquisition, the pears in the acquired images may be quite small and occluded, causing high false detection and object loss rate. In this paper, a multi-scale collaborative perception network YOLOv5s-FP (Fusion and Perception) was proposed for pear detection, which coupled local and global features. Specifically, a pear dataset with a high proportion of small and occluded pears was proposed, comprising 3680 images acquired with cameras mounted on a ground tripod and a UAV platform. The cross-stage partial (CSP) module was optimized to extract global features through a transformer encoder, which was then fused with local features by an attentional feature fusion mechanism. Subsequently, a modified path aggregation network oriented to collaboration perception of multi-scale features was proposed by incorporating a transformer encoder, the optimized CSP, and new skip connections. The quantitative results of utilizing the YOLOv5s-FP for pear detection were compared with other typical object detection networks of the YOLO series, recording the highest average precision of 96.12% with less detection time and computational cost. In qualitative experiments, the proposed network achieved superior visual performance with stronger robustness to the changes in occlusion and illumination conditions, particularly providing the ability to detect pears with different sizes in highly dense, overlapping environments and non-normal illumination areas. Therefore, the proposed YOLOv5s-FP network was practicable for detecting in-field pears in a real-time and accurate way, which could be an advantageous component of the technology for monitoring pear growth status and implementing automated harvesting in unmanned orchards.

Construction of a photosynthetic rate prediction model for greenhouse strawberries with distributed regulation of light environment.

In winter and spring, for greenhouses with larger areas and stereoscopic cultivation, distributed light environment regulation based on photosynthetic rate prediction model can better ensure good crop growth. In this paper, strawberries at flowering-fruit stage were used as the test crop, and the LI-6800 portable photosynthesis system was used to control the leaf chamber environment and obtain sample data by nested photosynthetic rate combination experiments under temperature, light and CO2 concentration conditions to study the photosynthetic rate prediction model construction method. For a small-sample, nonlinear real experimental data set validated by grey relational analysis, a photosynthetic rate prediction model was developed based on Support vector regression (SVR), and the particle swarm algorithm (PSO) was used to search the influence of the empirical values of parameters, such as the penalty parameter C, accuracy ε and kernel constant g, on the model prediction performance. The modeling and prediction results show that the PSO-SVR method outperforms the commonly used algorithms such as MLR, BP, SVR and RF in terms of prediction performance and generalization on a small sample data set. The research in this paper achieves accurate prediction of photosynthetic rate of strawberry and lays the foundation for subsequent distributed regulation of greenhouse strawberry light environment.

Feature fusion and clustering for key frame extraction.

Numerous limitations of Shot-based and Content-based key-frame extraction approaches have encouraged the development of Cluster-based algorithms. This paper proposes an Optimal Threshold and Maximum Weight (OTMW) clustering approach that allows accurate and automatic extraction of video summarization. Firstly, the video content is analyzed using the image color, texture and information complexity, and video feature dataset is constructed. Then a Golden Section method is proposed to determine the threshold function optimal solution. The initial cluster center and the cluster number k are automatically obtained by employing the improved clustering algorithm. k-clusters video frames are produced with the help of K-MEANS algorithm. The representative frame of each cluster is extracted using the Maximum Weight method and an accurate video summarization is obtained. The proposed approach is tested on 16 multi-type videos, and the obtained key-frame quality evaluation index, and the average of Fidelity and Ratio are 96.11925 and 97.128, respectively. Fortunately, the key-frames extracted by the proposed approach are consistent with artificial visual judgement. The performance of the proposed approach is compared with several state-of-the-art cluster-based algorithms, and the Fidelity are increased by 12.49721, 10.86455, 10.62984 and 10.4984375, respectively. In addition, the Ratio is increased by 1.958 on average with small fluctuations. The obtained experimental results demonstrate the advantage of the proposed solution over several related baselines on sixteen diverse datasets and validated that proposed approach can accurately extract video summarization from multi-type videos.