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Motivation The capability to predict the potential drug binding affinity against a protein target has always been a fundamental challenge in silico drug discovery. The traditional experiments in vitro and in vivo are costly and time-consuming which need to search over large compound space. Recent years have witnessed significant success on deep learning-based models for drug-target binding affinity prediction task. Results Following the recent success of the Transformer model, we propose a multigranularity protein–ligand interaction (MGPLI) model, which adopts the Transformer encoders to represent the character-level features and fragment-level features, modeling the possible interaction between residues and atoms or their segments. In addition, we use the convolutional neural network to extract higher-level features based on transformer encoder outputs and a highway layer to fuse the protein and drug features. We evaluate MGPLI on different protein–ligand interaction datasets and show the improvement of prediction performance compared to state-of-the-art baselines. Availability and implementation The model scripts are available at https://github.com/IILab-Resource/MGDTA.git

Pharmacokinetics/pharmacodynamics is the foundation for guiding the rational application of antibiotics in clinical practice, so it is necessary to establish quantitative methods for accurate drug concentration determination. This study aimed to develop a rapid and simple ultrahigh-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for simultaneous quantification of 14 antibiotics (amikacin, etimicin, ceftazidime, cefepime, cefoperazone, ceftriaxone, daptomycin, latamoxef, linezolid, meropenem, biapenem, ampicillin, norvancomycin, and vancomycin) in human plasma and cerebrospinal fluid. Antibiotics were chromatographically separated on a Waters ACQUITY UPLC BEH C18 column (2.1 mm × 50 mm, 1.7 μm) via gradient elution within 3 minutes and were monitored using positive ion fitted with multiple reaction monitoring. The lower limit of quantification was 0.05–2.0 μg·mL−1. The method was verified according to the FDA bioanalysis method validation guidelines, which showed excellent accuracy (from 86.75% to 110.85%) and precision (from 0.46% to 10.97%). At last, this method was successfully applied to therapeutic drug monitoring in 113 patients under antibiotics treatment.

The age-related decay in oocyte quality contributes to the gradual decline in fertility and the final occurrence of natural sterility. In this study, we aimed to investigate the effects of the hyperbaric oxygen treatment (HBOT) on oocyte quality in aging mouse oocyte. Eight- and forty-week-old female C57BL/6 J mice were treated with HBO for 10 days, and the quality of oocytes was analyzed. The results revealed that HBOT improved the age-related serum AMH levels. While compared with untreated aged mice, HBOT showed reduced follicular apoptosis and improved oocyte maturation, fertilization, and blastocyst formation in aged mice. HBO triggered changes in the microRNA expression in the ovaries of aged mice. In this study, 27 DEGs were identified in the HBOT mouse ovarian tissues, of which 9 were upregulated and 18 were downregulated. Notably, KEGG analysis revealed that these genes involved in different biological processes differed significantly in the ovary. Among these, the PI3K-Akt signaling was the most prominent pathway that controlled the recruitment and growth of primordial follicles. The calcium signaling pathway was found to be involved during the peri-implantation period. These results suggest that HBOT can be applied to improve the quality of oocytes, and it could be a potential clinical application to improve the fertility of aged female.

The invention discloses a data transmission method of farmland production monitoring system based on the Internet of Things, which belongs to the field of agricultural Internet of Things. The agricultural Internet of Things system includes an Internet of Things perception layer, an Internet of Things network layer and an application layer. The Internet of Things perception layer transmits the received information to the application layer through the Internet of Things network layer by wired or wireless network; A plurality of test instruments and equipment collect farmland crop data, and a plurality of wireless transmission modules collect farmland data and transmit them to the data management platform, which queries and calls farmland data in real time. In this design, the obtained field data can be imported into the storage location accurately and quickly, and the data of each site can be collected into a data management platform. It can monitor the equipment status and data quality in real time, reduce the workload of testers and improve the data transmission speed and quality.

Objective: To investigate the outcome of Laparoscopic Nerve-Sparing Ultra-Radical Hysterectomy (LNSURH), open radical hysterectomy (ORH), and concurrent platinum-based chemoradiation therapy (CCRT) on patients with locally advanced cervical carcinoma (LACC). Design：Retrospective clinical study. Population：LACC patients (74) who received ORH (29), LNSRH (20), or CCRT (25) between January 2011 and December 2019 at the Affiliated Changzhou No. 2 People’s Hospital of Nanjing Medical University. Methods: The age, tumor size, early and late postoperative morbidities, disease-free survival (DFS), and overall survival (OS) were recorded. A series of questions regarding urinary, bowel, and sexual functions were asked to the patients after their operation. Results: The Kaplan Meier curves revealed that the OS and DFS times in the CCRT group were comparable to the ORH or LNSURH groups (P = 0.106 for DFS and 0.190 for OS). The rates of early complications in the CCRT, ORH, and LNSURH groups, were also not statistically significant differences among the three groups (P = 0.46). Compared with CCRT groups, the rate of late complications in the ORH and LNSURH groups was significantly lower. The urinary and bowel functions were restored to the preoperative state although the resultant sexual function was not satisfactory. Main outcome measures：Postoperative prognosis and life quality of these patients. Conclusion: The CCRT, ORH, and LNSURH can be provided as options for LACC patients as they showed no statistically significant difference in the OS and DFS. LNSURH exhibited a lower rate of late complications and a high score of sexual function.

Background: Ontology, as a formal description and organization for domain-specific knowledge, is served as a significant approach of information retrieval and biological discovery in biomedical research, attracting more and more attention in computational biomedical and bioinformatics. It is quantified entities using semantic similarity based on ontology terms when using ontologies for description or annotation. More recently, machine learning approaches have enabled ontologies to describe concepts in ”computable” semantics. However, ontology semantics representation is not yet well-explored by existing learning-based methods. Results: We propose OSR2Vec, an ontology semantic representation approach that includes transforming structured ontology information into natural language and applying a pre-trained natural language model to vectorize semantics. OSR2Vec converts directly linked ontology words into sentence sequences, which are then embedded to semantics representation using the ouBioBERT model and the TSDAE method. We evaluate our method on a protein semantic similarities task using the kgsim dataset. We demonstrate the advantages of OSR2Vec by constructing sentence sequence to attain more specific semantics and confirm that performance on the protein semantic similarities task is favorable when using a combination of ouBioBERT and TSDAE according to our method. Conclusions: OSR2Vec is a method to represent ontology semantics using pre-training natural language model embedding sentences. With increasing the quality of representation, OSR2Vec provides an effective method in the ontology-based semantic task.

Measuring the semantic similarity between Gene Ontology (GO) terms is a fundamental step in numerous functional bioinformatics applications. To fully exploit the metadata of GO terms, word embedding-based methods have been proposed recently to map GO terms to low-dimensional feature vectors. However, these representation methods commonly overlook the key information hidden in the whole GO structure and the relationship between GO terms. In this paper, we propose a novel representation model for GO terms, named GT2Vec, which jointly considers the GO graph structure obtained by graph contrastive learning and the semantic description of GO terms based on BERT encoders. Our method is evaluated on a protein similarity task on a collection of benchmark datasets. The experimental results demonstrate the effectiveness of using a joint encoding graph structure and textual node descriptors to learn vector representations for GO terms.

BACKGROUND: In polycystic ovary syndrome (PCOS), ovarian physiology is tightly linked to the metabolic disturbances observed in this disease. Vitamin D (VD) plays an important role in the regulation of ovulatory dysfunction and can influence genes involved in steroidogenesis in granulosa cells (GCs). However, its role in the proliferation and apoptosis of ovarian GCs is unclear. The present study aimed to investigate the role of microRNA-196-5p (miR-196b-5p) in the hormone synthesis, proliferation, and apoptosis of ovarian GCs. METHODS: The abnormal expression of miRNAs in ovarian tissues of VD-deficient mice was analyzed using transcriptome sequencing. The direct target of miR-196b-5p was predict and confirmed by bioinformatics analysis and the dual-luciferase reporter assay. Reverse transcription-quantitative PCR (RT-qPCR) was used to detect the levels of miR-196b-5p, cell proliferation was detected via the CCK8 assay, and cell apoptosis and reactive oxygen species (ROS) were measured via flow cytometry. The levels of radixin (RDX), leucine rich repeat containing 17 (LRRC17), aromatase (CYP19A1), and glucose transporter 4 (GLUT4) were detected by performing RT-qPCR or western blot. RESULTS: We found that miR-196b-5p was significantly downregulated among the 672 miRNAs that were differentially expressed (DE) in VD-deficient mice. In addition, the results demonstrated that downregulated expression of miR-196b-5p significantly increased the level of RDX and LRRC17, and reduced expression of miR-196b-5p significantly promoted ovarian GC apoptosis and inhibited cell proliferation. Downregulated expression of miR-196b-5p promoted cellular ROS production and inhibited sex hormone production and glucose uptake. Transfection with miR-196b-5p mimics significantly increased the expression of CYP19A1 and GLUT4 and decreased the RDX and LRRC17 levels in ovarian GCs. CONCLUSIONS: This study shows that miR-196b-5p can regulate the oxidative stress (OS), glucose uptake, and steroid production pathway of GCs, thus promoting follicular development and maturation. This is a step towards a feasible treatment for PCOS.

As a serine/threonine phosphatase, protein phosphatase 2A (PP2A) is essential in numerous physiological processes. By generating a catalytic subunit of PP2A (Ppp2ca) conditional knockout (CKO) in C57BL/6 J mice, we explored the possible mechanisms of azoospermia by focusing on meiosis initiation and spermatogenesis. The deficiency of Ppp2ca in germ cells conspicuously disturbed spermatogonial differentiation and led to pachynema arrest, accompanied by significant apoptosis in germ cells and defects in programmed double-strand break (DSB) repair. While the formation of XY body was normal, respectively. Ppp2ca-deficient spermatocytes exhibited an abnormal cohesion complex degradation of chromosome, probably contributing to cell death. Furthermore, transcriptomics analysis was conducted to prove several genes involved in spermatogenesis and exhibited transcriptional dysregulations in Ppp2ca-deficient testes. Our study demonstrates the irreplaceable role of PP2A in spermatogenesis and provides more evidences of azoospermia etiology.

Vitamin D (VD) is not only associated with bone growth and development, but is also closely associated with numerous other pathological conditions. The present study aimed to investigate the effect of microRNA (miRNA/miR)-378d on ovarian granulosa cells by regulating the round spermatid basic protein 1 (Rsbn1) in the absence of VD. The abnormal expression of miRNAs in ovarian tissues of the VD-deficient mouse was analyzed using transcriptome sequencing. miR-378d, glucose transporter 4 (Glut4) and aromatase (Cyp19a) expression levels were examined via reverse transcription-quantitative (RT-q)PCR and western blotting. The expression levels of Rsbn1, Glut4 and Cyp19a were detected in transfected mouse ovarian granulosa cells. The targeting regulation between miR-378d and Rsbn1 was verified using double reporter gene assay and functional rescue experiments. Among the 672 miRNAs that were differentially expressed, cluster analysis revealed that 17 were significantly upregulated and 16 were significantly downregulated. Moreover, miR-378d showed significant upregulation, which was further verified via RT-qPCR. It was identified that the protein expression level of Rsbn1 was significantly downregulated. Furthermore, Glut4 mRNA expression was significantly decreased in the mimic group but markedly increased in the inhibitor group. By contrast, the mRNA expression levels of Rsbn1 and Cyp19a did not demonstrate any significant difference. The western blotting results indicated that the protein expression levels of Rsbn1 and Glut4 were decreased and increased, respectively, while Cyp19a did not show any significant change. In addition, the double reporter gene experiments confirmed that Rsbn1 was the target gene of miR-378d. Collectively, the present results demonstrated that miR-378d was abnormally overexpressed in the ovarian tissues of the VD-deficient mice, and that miR-378d could inhibit Glut4 production by targeting Rsbn1, which may lead to insulin resistance.

Background Because responses of patients with cancer to immunotherapy can vary in success, effective biomarkers are urgently needed for predicting clinical response with anti-PD-1 treatment. We aimed to evaluate the IL-5 and IFN-γ level with the response of anti-PD-1 blockade in non-small-cell lung cancer (NSCLC) and gastric cancer (GC). Methods Metastatic NSCLC and GC patients treated with anti-PD-1 monoclonal antibody were studied. Blood samples were taken before PD-1 McAb treatment, after the first cycle treatment, and during efficacy evaluation. The association between IL-5 and IFN-γ levels and clinical response were analyzed by the nonparametric Wilcoxon matched-pairs ranked tests. The progression-free survival (PFS) time was obtained by imaging evaluation and telephone follow-up of all the patients. Kaplan-Meier and the log rank test were used to plot the survival curve. Results IL-5 and IFN-γ levels were detected in the peripheral blood of 40 NSCLC and 35 GC patients who have received anti-PD-1 treatment. In effective group, IL-5 and IFN-γ levels at best response points significantly decreased (P < 0.001) compared with pretherapeutic levels in NSCLC and GC patients with lymph node or distant metastasis. Compared with pretherapeutic levels, IL-5 and IFN-γ levels largely increased as the tumor progresses (P < 0.01). Higher IL-5 and IFN-γ levels before treatment indicated shorter progression-free survival in patients with NSCLC metastasis (P = 0.007, P = 0.0111). Moreover, their levels also accurately reflected the pseudoprogression of two NSCLC patients to anti-PD-1 treatment. Conclusions Our results suggested that serum IL-5 and IFN-γ levels could be an effective indicator for predicting clinical efficacy and survival with anti-PD-1 blockade in NSCLC and GC patients.

Mobile edge computing (MEC) is a new paradigm that has recently received a lot of attention. It extends computing power to the network edge, where tasks are not transmitted over long distances, thus reducing the risk of sensitive information leakage and theft. By offloading tasks to MEC servers, user equipments (UEs) can not only address its own lack of computing resources, but also reduce time and energy consumption. However, compared to the increasing computing requirements of UEs, the limited resources and heavy burden of MEC servers are becoming more and more obvious. Therefore, it will be a great challenge to design a proper computation offloading scheme to meet the requirements of UEs in resource-constrained MEC. In this paper, we analyze main computation offloading schemes. We divide computation offloading scenarios into two types. One is a single-server scenario, the other is a collaborative scenario with cloud, edge server, vehicle, etc. Challenges and conclusions have also been suggested in this paper.

Reflux welding is widely used in SMT (surface patch technology) During this production process, the quality of the product is essential to maintain the temperature and the furnace speed required by the process. The furnace temperature curve in the furnace is an important form of reaction welding process. In order to improve the process efficiency of the return furnace, the heating welding process model is established based on the Fourier heat conduction law,1 D heat conduction model and Newton cooling law and draws the furnace temperature curve model. Then, the upper boundary of the conveyor speed using the boundary analysis and multiple target planning, and further explore the research and optimization direction of subsequent process flow. At the same time, this paper examines and analyzes the modeling process and results, and effectively demonstrates the scientific nature and accuracy of the model. Finally, the paper analyzes the significance of the above model and research in chip processing.

Mesoporous CuO nanosheets threaded with carbon nanotubes (CNTs) were synthesized via a simple solution-phase method, where Birch reduction chemistry was introduced for the functionalization of CNTs. Selective loading of CuO nanosheets was achieved due to the in situ nucleation and growth of CuO near the functional bands. Finally, discrete CuO nanosheets distributed along the axis direction of CNTs were revealed. The obtained CuO nanosheets exhibited the features of extremely thin thickness, mesoporous structure and high surface area. More importantly, the CNTs pass through the inner part of the CuO nanosheets, which ensures enhanced conductivity for electron transportation. When used as anode materials for lithium ion batteries, these CuO/CNT hybrids exhibited much lower charge transfer resistance, in contrast to pure CuO nanosheets. The construction of the necklace-like CuO/CNT hybrids can largely enhance the kinetic performance of the CuO anodes.

A lithium-assisted approach has been developed for the exfoliation of pristine graphite, which allows the large-scale preparation of few-layer graphene nanosheets. The process involves an unexpected physical insertion and exfoliation, and the graphene nanosheets prepared by this method reveal undisturbed sp2-hybridized structures. A possible two-step mechanism, which involves the negative charge being trapped around the edges of the graphite layers and a subsequent lithiation process, is proposed to explain the insertion of lithium inside the graphite interlayers. If necessary, the present exfoliation can be repeated and thinner (single or 2–3 layer) graphene can be achieved on a large scale. This simple process provides an efficient process for the exfoliation of pristine graphite, which might promote the future applications of graphene.

Introduction: Ovarian cancer is the most deadly gynecologic cancer, and the therapy is very difficult. Apatinib is a novel tyrosine kinase inhibitor targeting vascular endothelial growth factor receptor-2. At present, there are few studies or case reports on apatinib treatment for patients with ovarian cancer. Case presentation: A 75-year-old Chinese woman had a medical history of ovarian high-grade serous papillary adenocarcinoma, who got many lines of chemotherapy and apatinib—an antiangiogenesis drug therapy. Either alone or in combination, apatinib may extend the survival time of patients with advanced ovarian cancer. Conclusion: Apatinib may be an option for advanced ovarian cancer after failure of chemotherapy or other targeted therapy. The role of apatinib in the treatment of advanced ovarian cancer needs further study.