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Abstract Circular RNA (CircRNA)–microRNA (miRNA) interaction (CMI) is an important model for the regulation of biological processes by non-coding RNA (ncRNA), which provides a new perspective for the study of human complex diseases. However, the existing CMI prediction models mainly rely on the nearest neighbor structure in the biological network, ignoring the molecular network topology, so it is difficult to improve the prediction performance. In this paper, we proposed a new CMI prediction method, BEROLECMI, which uses molecular sequence attributes, molecular self-similarity, and biological network topology to define the specific role feature representation for molecules to infer the new CMI. BEROLECMI effectively makes up for the lack of network topology in the CMI prediction model and achieves the highest prediction performance in three commonly used data sets. In the case study, 14 of the 15 pairs of unknown CMIs were correctly predicted.

Androgen deprivation therapy (ADT) has long been the only treatment for metastatic hormone-sensitive prostate cancer (mHSPC). In recent years, with the use of docetaxel chemotherapy and the emergence of various novel hormone therapy drugs, such as Abiraterone, Enzalutamide, Apalutamide, Darolutamide, and Rezvilutamide, the treatment strategies for mHSPC have been greatly changed. Furthermore, local treatment has been added to the treatment of low tumor burden mHSPC and triple therapy has been regarded as an important treatment choice for high tumor burden mHSPC. The survival rate of mHSPC patients has increased significantly and the quality of life also improved with these new treatment strategies. This article reviews the latest advances and controversies in the current treatment of mHSPC. Ongoing clinical trials are introduced and further directions are also discussed in this mini-review.

Neuroendocrine prostate cancer (NEPC) is a highly aggressive variant of castration-resistant prostate cancer. It is characterized by low or no expression of the androgen receptor (AR), activation of AR-independent signaling, and increased neuroendocrine phenotype. Most of NEPC is induced by treatment of androgen deprivation therapy and androgen receptor pathway inhibitors (ARPIs). Currently, the treatment of NEPC follows the treatment strategy for small-cell lung cancer, lacking effective drugs and specific treatment options. This review summarizes potential novel targets and therapies for NEPC treatment, including epigenetic regulators (zeste homolog 2 inhibitors, lysine-specific demethylase 1 inhibitors), aurora kinase A inhibitors, poly-ADP-ribose polymerase inhibitors, delta-like ligand 3 targeted therapies, a combination of immunotherapies, etc. Other promising targets and future directions are also discussed in this review. These novel targets and therapies may provide new opportunities for the treatment of NEPC.

Background: The relation between the human body movements and cognition has been a research hotspot in physical education and health promotion in recent years. This study applied the embodied cognition theory to examine the effects of the Movement Integrity with Intelligent Play (MIIP) program on preschoolers' math performance. Objective: This study explores whether the Movement Integrity with Intelligent Play is connected with math performance, physical activity (PA) levels, and enjoyment of kindergarten students. Method: A quasi-experimental trial was delivered to evaluate the effects of the MIIP program that integrated bodily movements into math cognitive tasks related to pattern cognitive skills. A total of 54 (N = 54, 30 girls, M[subscript age] = 75.69 ± 3.36) children from two preschool classrooms served as participants and were assigned to one of the following two conditions: the integrated condition group (ICG, n = 28), and the conventional condition group (CCG, n = 26). During a 2-week intervention period, the ICG received a task-relevant PA (3×30 min/wk) in addition to their regular in-school math lessons (2×30 min/wk). Finally, math performance, PA levels, and enjoyment were assessed. Results: Following the intervention, significant differences (p < 0.05) in math performance, PA levels, and enjoyment were found in the ICG. The results demonstrated that preschool children in ICG outperformed children in the CCG. Children in the CCG showed no significant differences in math performance and PA levels. In addition, children in the ICG scored higher scores (M = 9.25 ± 2.71) on perceived enjoyment of the instructional method than children in the CCG (M = 7.07 ± 3.91). Conclusions: The integrated intervention has beneficial effects not only on math performance, PA levels but also on enjoyment. Transforming the focus of instruction to an integrated PA enhanced both math performance, PA levels, and increased enjoyment.

Abstract According to the expression of miRNA in pathological processes, miRNAs can be divided into oncogenes or tumor suppressors. Prediction of the regulation relations between miRNAs and small molecules (SMs) becomes a vital goal for miRNA-target therapy. But traditional biological approaches are laborious and expensive. Thus, there is an urgent need to develop a computational model. In this study, we proposed a computational model to predict whether the regulatory relationship between miRNAs and SMs is up-regulated or down-regulated. Specifically, we first use the Large-scale Information Network Embedding (LINE) algorithm to construct the node features from the self-similarity networks, then use the General Attributed Multiplex Heterogeneous Network Embedding (GATNE) algorithm to extract the topological information from the attribute network, and finally utilize the Light Gradient Boosting Machine (LightGBM) algorithm to predict the regulatory relationship between miRNAs and SMs. In the fivefold cross-validation experiment, the average accuracies of the proposed model on the SM2miR dataset reached 79.59% and 80.37% for up-regulation pairs and down-regulation pairs, respectively. In addition, we compared our model with another published model. Moreover, in the case study for 5-FU, 7 of 10 candidate miRNAs are confirmed by related literature. Therefore, we believe that our model can promote the research of miRNA-targeted therapy.

The relation between aphids and Sclerotinia stem rot (SSR) in oilseed rape is rarely examined because they are often studied alone. We have observed a significant correlation between the number of aphids and the occurrence of SSR in our field studies. Electropenetrography (EPG) was used to evaluate the effects of Brevicoryne brassicae (Linnaeus) on two oilseed rape cultivars while acquiring, vectoring and inoculating of Sclerotinia sclerotiorum Lib. (de Bary) ascospores. The results demonstrated that aphid feeding followed by the application of an ascospore suspension significantly increased S. sclerotiorum incidence. Aphids were capable of adhering to ascospores and carrying them to healthy plants, thereby causing diseases. The results of the EPG analysis indicated that aphid feeding behaviour was significantly altered in all leaf tissue levels following infection with S. sclerotiorum. Aphids initiated their first puncture significantly sooner than the control group, began probing mesophyll cells earlier, significantly increased the frequency of both short probes and intracellular punctures and had a significantly shorter pathway duration. On infected aphid-susceptible cultivars, aphids secreted more saliva but had reduced ingestion compared with aphids feeding on non-infected oilseed rape. In addition, ascospores can affect aphid feeding behaviour by adhering to aphids. Aphids carrying ascospores punctured cells earlier, with a significant increase in the frequency and duration of short probes and cell punctures, shortened pathway durations, increased salivation and reduced ingestion compared with aphids not carrying ascospores. On aphid-susceptible cultivars, aphids carrying ascospores delayed puncture onset, but on resistant cultivars, puncture onset was shortened. There is a correlation between aphids and S. sclerotiorum. The impact of S. sclerotiorum on aphid feeding behaviour is directional, favouring the spread of the fungus. This promotion does not appear to be altered by the aphid resistance of the cultivar.

Abstract Hepatocellular carcinoma (HCC) is acknowledged as an immunosuppressive neoplasm, whereby the inactive microenvironment facilitates immune tolerance and evasion of HCC. Post‐surgical resected liver cancer exhibits a proclivity for relapse, rendering prevention of recurrence challenging as it may transpire at any point subsequent to surgery. Among the various anti‐recurrence interventions, the primary clinical approach involving the administration of regimens atezolizumab and bevacizumab (A+T) is deemed the most efficacious in reversing the tumor microenvironment, albeit still lacking in complete satisfaction. Therefore, the objective is to utilize a recently developed block copolymer as a protective carrier for two specific monoclonal antibody drugs. Subsequently, a modified hemostatic hydrogel will be synthesized for application during hepatic surgery. The immunotherapy impact of this approach is significantly prolonged and intensified due to the combined hemostasis properties and controlled release of the constituents within the synthesized nanocomposite hydrogel. Furthermore, these nanocomposite hydrogels exhibit remarkable efficacy in preventing postoperative wound bleeding and substantially enhancing the safety of liver cancer resection. This research on the anti‐recurrence hydrogel system presents a novel therapeutic approach for addressing local recurrence of liver cancer, potentially offering a substantial contribution to the field of surgical treatment for liver cancer in the future.

Abstract Background Drug-target interaction (DTI) prediction has become a crucial prerequisite in drug design and drug discovery. However, the traditional biological experiment is time-consuming and expensive, as there are abundant complex interactions present in the large size of genomic and chemical spaces. For alleviating this phenomenon, plenty of computational methods are conducted to effectively complement biological experiments and narrow the search spaces into a preferred candidate domain. Whereas, most of the previous approaches cannot fully consider association behavior semantic information based on several schemas to represent complex the structure of heterogeneous biological networks. Additionally, the prediction of DTI based on single modalities cannot satisfy the demand for prediction accuracy. Methods We propose a multi-modal representation framework of ‘DeepMPF’ based on meta-path semantic analysis, which effectively utilizes heterogeneous information to predict DTI. Specifically, we first construct protein–drug-disease heterogeneous networks composed of three entities. Then the feature information is obtained under three views, containing sequence modality, heterogeneous structure modality and similarity modality. We proposed six representative schemas of meta-path to preserve the high-order nonlinear structure and catch hidden structural information of the heterogeneous network. Finally, DeepMPF generates highly representative comprehensive feature descriptors and calculates the probability of interaction through joint learning. Results To evaluate the predictive performance of DeepMPF, comparison experiments are conducted on four gold datasets. Our method can obtain competitive performance in all datasets. We also explore the influence of the different feature embedding dimensions, learning strategies and classification methods. Meaningfully, the drug repositioning experiments on COVID-19 and HIV demonstrate DeepMPF can be applied to solve problems in reality and help drug discovery. The further analysis of molecular docking experiments enhances the credibility of the drug candidates predicted by DeepMPF. Conclusions All the results demonstrate the effectively predictive capability of DeepMPF for drug-target interactions. It can be utilized as a useful tool to prescreen the most potential drug candidates for the protein. The web server of the DeepMPF predictor is freely available at http://120.77.11.78/DeepMPF/ , which can help relevant researchers to further study.

Aphids and Sclerotinia stem rot in oilseed rape are often studied in isolation, and their relationship is rarely explored. Our field studies have revealed a significant positive correlation between the number of aphids and the incidence of Sclerotinia stem rot. Hence, starting with the colonizing stages of the two pests, Breveroryne brassicae was assessed for its potential to acquire, transmit, and inoculate Sclerotinia sclerotiorum by being sprayed with an ascospore suspension. Moreover, distinctions in aphid feeding behavior were examined between aphids on inoculated/uninoculated winter and spring oilseed rape plants or aphids, both with and without S. sclerotiorum ascospores, using electropenetrography (EPG). The results showed that aphid feeding followed by dropping ascospore suspension significantly increased the incidence of S. sclerotiorum. Ascospores were able to adhere to aphids and were carried by aphids to healthy plants, causing disease. The results of the EPG analysis indicated that aphid feeding behavior was significantly altered in all leaf tissue levels following infection with S. sclerotiorum. Specifically, aphids initiated their first puncture significantly sooner, began probing mesophyll cells earlier, had a significantly shorter pathway duration, and secreted saliva more frequently but reduced salivation prior to feeding and ingestion compared to aphids feeding on uninfected oilseed rape. Additionally, the feeding behavior of aphids carrying ascospores was markedly different from that of aphids not carrying ascospores, implying that ascospores directly influence aphid feeding behavior but that this influence appeared to be beneficial only for S. sclerotiorum infection. Aphids carrying ascospores started to puncture cells more quickly, with a significant increase in the frequency and duration of short probes and cell punctures, shortened pathway durations, and reduced salivation before feeding compared to aphids not carrying ascospores. It is clear that there is an interaction between aphids and S. sclerotiorum. The impact of S. sclerotiorum on aphid feeding behavior is directional, favoring the spread of the fungus.

Self-efficacy theory assumes that students' efficacy beliefs affect their performance through process variables, including behavior, cognition, and affection. The purpose of this study was to utilize self-efficacy theory as a theoretical framework to propose a conceptual model of a mediating relationship among perceived motor skill competence, successful practice trials, and motor skill performance in physical education. In addition, the authors reviewed the literature to provide evidence to support the potential mediating relationship by following the steps recommended by Baron and Kenny. This paper is significant because the authors integrated the literature of motor development/learning and physical education pedagogy to propose a conceptual model where successful practice trials would act as a behavioral mediator through which perceived motor skill competence affects students' motor skill performance. This conceptual model can guide future research to identify students' behaviors affecting their skill development, thus helping teachers develop pedagogies to improve motor skill performance in physical education.

Summary: Circular RNA (circRNA) plays an important role in the diagnosis, treatment, and prognosis of human diseases. The discovery of potential circRNA-miRNA interactions (CMI) is of guiding significance for subsequent biological experiments. Limited by the small amount of experimentally supported data and high randomness, existing models are difficult to accomplish the CMI prediction task based on real cases. In this paper, we propose KS-CMI, a novel method for effectively accomplishing CMI prediction in real cases. KS-CMI enriches the ‘behavior relationships’ of molecules by constructing circRNA-miRNA-cancer (CMCI) networks and extracts the behavior relationship attribute of molecules based on balance theory. Next, the denoising autoencoder (DAE) is used to enhance the feature representation of molecules. Finally, the CatBoost classifier was used for prediction. KS-CMI achieved the most reliable prediction results in real cases and achieved competitive performance in all datasets in the CMI prediction.

Rhodotorula mucilaginosa, an environmental yeast widely used in industry and agriculture, is also an opportunistic pathogen resistant to multi-antifungals. During the national surveillance in China, R. mucilaginosa has been documented from various hospitals and regions. At present, the molecular epidemiology of invasive infections caused by R. mucilaginosa and their resistance profiles to antifungals were unknown. Here we collected 49 strains from four hospitals located in different geographic regions from 2009 to 2019 in China, determined their genotypes using different molecular markers and quantified susceptibilities to various antifungals. Sequencing of ITS and D1/D2 regions in rDNA indicated that 73.5% (36/49) of clinical strains belong to same sequence type (rDNA type 2). Microsatellite (MT) genotyping with 15 (recently developed) tandem repeat loci identified 5 epidemic MT types, which accounted for 44.9% (22/49) of clinical strains, as well as 27 sporadic MT types. Microsatellite data indicated that the presence of an epidemic cluster including 35 strains (71.4%) repeatedly isolated in four hospitals for eight years. Single nucleotide variants (SNVs) from the whole genome sequence data also supported the clustering of these epidemic strains due to low pairwise distance. In addition, phylogenetic analysis of SNVs from these clinical strains, together with environmental and animal strains showed that the closely related epidemic cluster strains may be opportunistic, zoonotic pathogens. Also, molecular data indicated a possible clonal transmission of pan echinocandins-azoles-5-flucytosine resistant R. mucilaginosa strains in hospital H01. Our study demonstrated that R. mucilaginosa is a multi-drug resistant pathogen with the ability to cause nosocomial infection.

ABSTRACT Candida albicans remains the most common species causing invasive candidiasis. In this study, we present the population structure of 551 global C. albicans strains. Of these, the antifungal susceptibilities of 370 strains were tested. Specifically, 66.6% of the azole-nonsusceptible (NS)/non-wild-type (NWT) strains that were tested belonged to Clade 1. A phylogenetic analysis, a principal components analysis, the population structure, and a loss of heterozygosity events revealed two nested subclades in Clade 1, namely, Clade 1-R and Clade 1-R-α, that exhibited higher azole-NS/NWT rates (75.0% and 100%, respectively). In contrast, 6.4% (21/326) of the non-Clade 1-R isolates were NS/NWT to at least 1 of 4 azoles. Notably, all of the Clade 1-R-α isolates were pan-azole-NS/NWT that carried unique A114S and Y257H double substitutions in Erg11p and had the overexpression of ABC-type efflux pumps introduced by the substitution A736V in transcript factor Tac1p. It is worth noting that the Clade 1-R and Clade 1-R-α isolates were from different cities that are distributed over a large geographic span. Our study demonstrated the presence of specific phylogenetic subclades that are associated with antifungal resistance among C. albicans Clade 1, which calls for public attention on the monitoring of the future spread of these clones. IMPORTANCE Invasive candidiasis is the most common human fungal disease among hospitalized patients, and Candida albicans is the predominant pathogen. Considering the large number of infected cases and the limited alternative therapies, the azole-resistance of C. albicans brings a huge clinical threat. Here, our study suggested that antifungal resistance in C. albicans could also be associated with phylogenetic lineages. Specifically, it was revealed that more than half of the azole-resistant C. albicans strains belonged to the same clade. Furthermore, two nested subclades of the clade exhibited extremely high azole-resistance. It is worth noting that the isolates of two subclades were from different cities that are distributed over a large geographic span in China. This indicates that the azole-resistant C. albicans subclades may develop into serious public health concerns.

LncRNA-protein interaction plays an important role in the development and treatment of many human diseases. As the experimental approaches to determine lncRNA–protein interactions are expensive and time-consuming, considering that there are few calculation methods, therefore, it is urgent to develop efficient and accurate methods to predict lncRNA-protein interactions. In this work, a model for heterogeneous network embedding based on meta-path, namely LPIH2V, is proposed. The heterogeneous network is composed of lncRNA similarity networks, protein similarity networks, and known lncRNA-protein interaction networks. The behavioral features are extracted in a heterogeneous network using the HIN2Vec method of network embedding. The results showed that LPIH2V obtains an AUC of 0.97 and ACC of 0.95 in the 5-fold cross-validation test. The model successfully showed superiority and good generalization ability. Compared to other models, LPIH2V not only extracts attribute characteristics by similarity, but also acquires behavior properties by meta-path wandering in heterogeneous networks. LPIH2V would be beneficial in forecasting interactions between lncRNA and protein.