Symbiotic bacteria confer insecticide resistance by metabolizing buprofezin in the brown planthopper, Nilaparvata lugens (Stål).

Buprofezin, a chitin synthesis inhibitor, is widely used to control several economically important insect crop pests. However, the overuse of buprofezin has led to the evolution of resistance and exposed off-target organisms present in agri-environments to this compound. As many as six different strains of bacteria isolated from these environments have been shown to degrade buprofezin. However, whether insects can acquire these buprofezin-degrading bacteria from soil and enhance their own resistance to buprofezin remains unknown. Here we show that field strains of the brown planthopper, Nilaparvata lugens, have acquired a symbiotic bacteria, occurring naturally in soil and water, that provides them with resistance to buprofezin. We isolated a symbiotic bacterium, Serratia marcescens (Bup_Serratia), from buprofezin-resistant N. lugens and showed it has the capacity to degrade buprofezin. Buprofezin-susceptible N. lugens inoculated with Bup_Serratia became resistant to buprofezin, while antibiotic-treated N. lugens became susceptible to this insecticide, confirming the important role of Bup_Serratia in resistance. Sequencing of the Bup_Serratia genome identified a suite of candidate genes involved in the degradation of buprofezin, that were upregulated upon exposure to buprofezin. Our findings demonstrate that S. marcescens, an opportunistic pathogen of humans, can metabolize the insecticide buprofezin and form a mutualistic relationship with N. lugens to enhance host resistance to buprofezin. These results provide new insight into the mechanisms underlying insecticide resistance and the interactions between bacteria, insects and insecticides in the environment. From an applied perspective they also have implications for the control of highly damaging crop pests.

A novel microbe-drug association prediction model based on graph attention networks and bilayer random forest.

BACKGROUND: In recent years, the extensive use of drugs and antibiotics has led to increasing microbial resistance. Therefore, it becomes crucial to explore deep connections between drugs and microbes. However, traditional biological experiments are very expensive and time-consuming. Therefore, it is meaningful to develop efficient computational models to forecast potential microbe-drug associations. RESULTS: In this manuscript, we proposed a novel prediction model called GARFMDA by combining graph attention networks and bilayer random forest to infer probable microbe-drug correlations. In GARFMDA, through integrating different microbe-drug-disease correlation indices, we constructed two different microbe-drug networks first. And then, based on multiple measures of similarity, we constructed a unique feature matrix for drugs and microbes respectively. Next, we fed these newly-obtained microbe-drug networks together with feature matrices into the graph attention network to extract the low-dimensional feature representations for drugs and microbes separately. Thereafter, these low-dimensional feature representations, along with the feature matrices, would be further inputted into the first layer of the Bilayer random forest model to obtain the contribution values of all features. And then, after removing features with low contribution values, these contribution values would be fed into the second layer of the Bilayer random forest to detect potential links between microbes and drugs. CONCLUSIONS: Experimental results and case studies show that GARFMDA can achieve better prediction performance than state-of-the-art approaches, which means that GARFMDA may be a useful tool in the field of microbe-drug association prediction in the future. Besides, the source code of GARFMDA is available at https://github.com/KuangHaiYue/GARFMDA.git.

Genome-wide analysis of the ABC gene family in almond and functional predictions during flower development, freezing stress, and salt stress.

ABC (ATP-binding cassette) transporter proteins are one of the most extensive protein families known to date and are ubiquitously found in animals, plants, and microorganisms. ABCs have a variety of functions, such as plant tissue development regulation, hormone transport, and biotic and abiotic stress resistance. However, the gene characterization and function of the ABC gene family in almond (Prunus dulcis) have not been thoroughly studied. In this study, we identified 117 PdABC genes using the whole genome of 'Wanfeng' almond obtained by sequencing and explored their protein characterization. The PdABC family members were classified into eight subfamilies. The members of the same subfamily had conserved motifs but poorly conserved numbers of exons and introns and were unevenly distributed among the eight subfamilies and on the eight chromosomes. Expression patterns showed that PdABC family members were significantly differentially expressed during almond development, dormant freezing stress, and salt stress. We found that PdABC59 and PdABC77 had extremely high expression levels in pollen. PdABC63 and PdABC64 had high expression levels during almond petal development and multiple stages of flower development. PdABC98 was highly expressed in annual dormant branches after six temperature-freezing stress treatments. PdABC29, PdABC69, and PdABC98 were highly expressed under different concentrations of salt stress. This study preliminarily investigated the expression characteristics of ABC genes in different tissues of almond during flower development, freezing stress and salt stress, and the results will provide a reference for further in-depth research and breeding of almond in the future.

Feature aggregation graph convolutional network based on imaging genetic data for diagnosis and pathogeny identification of Alzheimer's disease.

The roles of brain regions activities and gene expressions in the development of Alzheimer's disease (AD) remain unclear. Existing imaging genetic studies usually has the problem of inefficiency and inadequate fusion of data. This study proposes a novel deep learning method to efficiently capture the development pattern of AD. First, we model the interaction between brain regions and genes as node-to-node feature aggregation in a brain region-gene network. Second, we propose a feature aggregation graph convolutional network (FAGCN) to transmit and update the node feature. Compared with the trivial graph convolutional procedure, we replace the input from the adjacency matrix with a weight matrix based on correlation analysis and consider common neighbor similarity to discover broader associations of nodes. Finally, we use a full-gradient saliency graph mechanism to score and extract the pathogenetic brain regions and risk genes. According to the results, FAGCN achieved the best performance among both traditional and cutting-edge methods and extracted AD-related brain regions and genes, providing theoretical and methodological support for the research of related diseases.

Appraisal of surgical outcomes and oncological efficiency of intraoperative adverse events in robotic radical gastrectomy for gastric cancer.

BACKGROUND: Surgical quality control is a crucial determinant of evaluating the tumor efficacy. OBJECTIVE: To assess the ClassIntra grade for quality control and oncological outcomes of robotic radical surgery for gastric cancer (GC). METHODS: Data of patients undergoing robotic radical surgery for GC at a high-volume center were retrospectively analyzed. Patients were categorized into two groups, the intraoperative adverse event (iAE) group and the non-iAE group, based on the occurrence of intraoperative adverse events. The iAEs were further classified into five sublevels (ranging from I to V according to severity) based on the ClassIntra grade. Surgical performance was assessed using the Objective Structured Assessment of Technical Skill (OSATS) and the General Error Reporting Tool. RESULTS: This study included 366 patients (iAE group: n = 72 [19.7%] and non-iAE group: n = 294 [80.3%]). The proportion of ClassIntra grade II patients was the highest in the iAE group (54.2%). In total and distal gastrectomies, iAEs occurred most frequently in the suprapancreatic area (50.0% and 54.8%, respectively). In total gastrectomy, grade IV iAEs were most common during lymph node dissection in the splenic hilum area (once for bleeding [grade IV] and once for injury [grade IV]). The overall survival (OS) and disease-free survival of the non-iAE group were significantly better than those of the iAE group (Log rank P < 0.001). Uni- and multi-variate analyses showed that iAEs were key prognostic indicators, independent of tumor stage and adjuvant chemotherapy (P < 0.001). CONCLUSION: iAEs in patients who underwent robotic radical gastrectomy significantly correlated with the occurrence of postoperative complications and a poor long-term prognosis. Therefore, utilization and inclusion of ClassIntra grading as a crucial surgical quality control and prognostic indicator in the routine surgical quality evaluation system are recommended.

Individualized Weight Management and Its Impact on Pregnancy Outcomes in Overweight/Obese Infertile Women: A Retrospective Study.

Background: Previous studies link overweight/obesity to reduced fertility, highlighting weight intervention as vital for better pregnancy outcomes. However, clarity on the role and efficacy of weight loss in enhancing pregnancy is inconsistent. Objective: This study aimed to assess the impact of individualized weight intervention on pregnancy among Chinese overweight/obese infertile women and explore body composition indexes influencing pregnancy outcomes. Methods: This retrospective study involved 363 overweight/obese infertile women admitted to the First Affiliated Hospital of Guangxi Medical University, Guangxi, China, from June 2017 to November 2020. Among them, 249 received personalized weight intervention (intervention group), while 114 did not (control group). Pregnancy outcomes were compared between the two groups, and changes in body composition before and after intervention were measured. Multivariate logistic regression was employed to analyze factors influencing pregnancy outcomes. Results: The intervention group exhibited significantly higher clinical pregnancy rates, natural pregnancy rates, assisted reproductive pregnancy rates, and induced ovulation (IO) pregnancy rates compared to the control group (all P < .05). Following weight intervention, there were significant decreases in body weight, body mass index (BMI), visceral fat area, and body fat (all P < .01). Logistic regression analysis identified polycystic ovary syndrome as the reason for infertility (OR=3.446, P = .016), ∆body weight %≥10% (OR=2.931, P = .014), and ∆visceral fat area% (OR=1.025, P = .047) as positive factors for a successful pregnancy. Conversely, age≥35 years old (OR=0.337, P = .001), BMI≥25 kg/m2 after intervention (OR=0.279, P < .001), and visceral fat area≥100 cm2 after intervention (OR=0.287, P = .007) were identified as negative factors. Conclusions: Individualized weight management enhances pregnancy outcomes in overweight/obese infertile women. Achieving a reduction in body weight by 10% or more, combined with effective control of visceral fat, proves important in improving pregnancy outcomes. Excess visceral fat emerges as an adverse factor impacting successful pregnancy.

Therapeutic effects and molecular mechanisms of natural products in thrombosis.

Thrombotic disorders, such as myocardial infarction and stroke, are the leading cause of death in the global population and have become a health problem worldwide. Drug therapy is one of the main antithrombotic strategies, but antithrombotic drugs are not completely safe, especially the risk of bleeding at therapeutic doses. Recently, natural products have received widespread interest due to their significant efficacy and high safety, and an increasing number of studies have demonstrated their antithrombotic activity. In this review, articles from databases, such as Web of Science, PubMed, and China National Knowledge Infrastructure, were filtered and the relevant information was extracted according to predefined criteria. As a result, more than 100 natural products with significant antithrombotic activity were identified, including flavonoids, phenylpropanoids, quinones, terpenoids, steroids, and alkaloids. These compounds exert antithrombotic effects by inhibiting platelet activation, suppressing the coagulation cascade, and promoting fibrinolysis. In addition, several natural products also inhibit thrombosis by regulating miRNA expression, anti-inflammatory, and other pathways. This review systematically summarizes the natural products with antithrombotic activity, including their therapeutic effects, mechanisms, and clinical applications, aiming to provide a reference for the development of new antithrombotic drugs.

Aberrant splicing of a nicotinic acetylcholine receptor alpha 6 subunit is associated with spinosad tolerance in the thrips predator Orius laevigatus.

Susceptibility to insecticides is one of the limiting factors preventing wider adoption of natural enemies to control insect pest populations. Identification and selective breeding of insecticide tolerant strains of commercially used biological control agents (BCAs) is one of the approaches to overcome this constraint. Although a number of beneficial insects have been selected for increased tolerance to insecticides the molecular mechanisms underpinning these shifts in tolerance are not well characterised. Here we investigated the molecular mechanisms of enhanced tolerance of a lab selected strain of Orius laevigatus (Fieber) to the commonly used biopesticide spinosad. Transcriptomic analysis showed that spinosad tolerance is not a result of overexpressed detoxification genes. Molecular analysis of the target site for spinosyns, the nicotinic acetylcholine receptor (nAChR), revealed increased expression of truncated transcripts of the nAChR α6 subunit in the spinosad selected strain, a mechanism of resistance which was described previously in insect pest species. Collectively, our results demonstrate the mechanisms by which some beneficial biological control agents can evolve insecticide tolerance and will inform the development and deployment of insecticide-tolerant natural enemies in integrated pest management strategies.

The role of the Bemisia tabaci and Trialeurodes vaporariorum cytochrome-P450 clade CYP6DPx in resistance to nicotine and neonicotinoids.

The alkaloid, nicotine, produced by tobacco and other Solanaceae as an anti-herbivore defence chemical is one of the most toxic natural insecticides in nature. However, some insects, such as the whitefly species, Trialeurodes vaporariorum and Bemisia tabaci show strong tolerance to this allelochemical and can utilise tobacco as a host. Here, we used biological, molecular and functional approaches to investigate the role of cytochrome P450 enzymes in nicotine tolerance in T. vaporariorum and B. tabaci. Insecticide bioassays revealed that feeding on tobacco resulted in strong induced tolerance to nicotine in both species. Transcriptome profiling of both species reared on tobacco and bean hosts revealed profound differences in the transcriptional response these host plants. Interrogation of the expression of P450 genes in the host-adapted lines revealed that P450 genes belonging to the CYP6DP subfamily are strongly upregulated in lines reared on tobacco. Functional characterisation of these P450s revealed that CYP6DP1 and CYP6DP2 of T. vaporariorum and CYP6DP3 of B. tabaci confer resistance to nicotine in vivo. These three genes, in addition to the B. tabaci P450 CYP6DP5, were also found to confer resistance to the neonicotinoid imidacloprid. Our data provide new insight into the molecular basis of nicotine resistance in insects and illustrates how divergence in the evolution of P450 genes in this subfamily in whiteflies may have impacted the extent to which different species can tolerate a potent natural insecticide.

The C2H2-type zinc-finger regulator AoKap5 is required for the growth and kojic acid synthesis in Aspergillus oryzae.

Aspergillus oryzae is an important filamentous fungus widely used for the industrial production of fermented foods and secondary metabolites. The clarifying of the mechanism of the growth and secondary metabolites in A. oryzae is important for its industrial production and utilization. Here, the C2H2-type zinc-finger protein AoKap5 was characterized to be involved in the growth and kojic acid production in A. oryzae. The Aokap5-disrupted mutants were constructed by the CRISPR/Cas9 system, which displayed increased colony growth but decreased conidial formation. Deletion of Aokap5 enhanced the tolerance to cell-wall and oxidative but not osmotic stress. The transcriptional activation assay revealed that AoKap5 itself didn't have transcriptional activation activity. Disruption of Aokap5 resulted in the reduced production of kojic acid, coupled with the reduced expression of the kojic acid synthesis genes kojA and kojT. Meanwhile, overexpression of kojT could rescue the decreased production of kojic acid in Aokap5-deletion strain, indicating that Aokap5 serves upstream of kojT. Furthermore, the yeast one-hybrid assay demonstrated that AoKap5 could directly bind to the kojT promoter. These findings suggest that AoKap5 regulates kojic acid production through binding to the kojT promoter. This study provides an insight into the role of zinc finger protein in the growth and kojic acid biosynthesis of A. oryzae.

Functional role of a novel zinc finger protein, AoZFA, in growth and kojic acid synthesis in Aspergillus oryzae.

Kojic acid (KA) is a valuable secondary metabolite that is regulated by zinc finger proteins in Aspergillus oryzae. However, only two such proteins have been characterized to function in kojic acid production of A. oryzae to date. In this study, we identified a novel zinc finger protein, AoZFA, required for kojic acid biosynthesis in A. oryzae. Our results showed that disruption of AozfA led to increased expression of kojA and kojR involved in kojic acid synthesis, resulting in enhanced kojic acid production, while overexpression of AozfA had the opposite effect. Furthermore, deletion of kojR in the AozfA disruption strain abolished kojic acid production, whereas overexpression of kojR enhanced it, indicating that AoZFA regulates kojic acid production by affecting kojR. Transcriptional activation assay revealed that AoZFA is a transcriptional activator. Interestingly, when kojR was overexpressed in the AozfA overexpression strain, the production of kojic acid failed to be rescued, suggesting that AozfA plays a distinct role from kojR in kojic acid biosynthesis. Moreover, we found that AozfA was highly induced by zinc during early growth stages, and its overexpression inhibited the growth promoted by zinc, whereas its deletion had no effect, suggesting that AoZFA is non-essential but has a role in the response of A. oryzae to zinc. Overall, these findings provide new insights into the roles of zinc finger proteins in the growth and kojic acid production of A. oryzae.IMPORTANCEKojic acid (KA) is an economically valuable secondary metabolite produced by Aspergillus oryzae due to its vast biological activities. Genetic modification of A. oryzae has emerged as an efficient strategy for enhancing kojic acid production, which is dependent on the mining of genes involved in kojic acid synthesis. In this study, we have characterized a novel zinc-finger protein, AoZFA, as a negative regulator of kojic acid production by affecting kojR. AozfA is an excellent target for improving kojic acid production without any effects on the growth of A. oryzae. Furthermore, the simultaneous modification of AozfA and kojR exerts a more significant promotional effect on kojic acid production than the modification of single genes. This study provides new insights for the regulatory mechanism of zinc finger proteins in the growth and kojic acid production of A. oryzae.

Future Directions in Optimizing Anesthesia to Reduce Perioperative Acute Kidney Injury.

BACKGROUND: Perioperative acute kidney injury (AKI) is common in surgical patients and is associated with high morbidity and mortality. There are currently few options for AKI prevention and treatment. Due to its complex pathophysiology, there is no efficient medication therapy to stop the onset of the injury or repair the damage already done. Certain anesthetics, however, have been demonstrated to affect the risk of perioperative AKI in some studies. The impact of anesthetics on renal function is particularly important as it is closely related to the prognosis of patients. Some anesthetics can induce anti-inflammatory, anti-necrotic, and anti-apoptotic effects. Propofol, sevoflurane, and dexmedetomidine are a few examples of anesthetics that have protective association with AKI in the perioperative period. SUMMARY: In this study, we reviewed the clinical characteristics, risk factors, and pathogenesis of AKI. Subsequently, the protective effects of various anesthetic agents against perioperative AKI and the latest research are introduced. KEY MESSAGE: This work demonstrates that a thorough understanding of the reciprocal effects of anesthetic drugs and AKI is crucial for safe perioperative care and prognosis of patients. However, more complete mechanisms and pathophysiological processes still need to be further studied.

Exosomal miR-211-5p regulates glucose metabolism, pyroptosis, and immune microenvironment of melanoma through GNA15.

Despite the unprecedented advancement of cancer treatment, the prognosis for patients with metastatic stage of cancer remains poor. The challenge that underlines this clinical dilemma is the complexity of metastasis. The conventional experiment-driven discovery approaches (the "wet lab") yield overly simplified one-to-one mechanistic relationships that are inept of elucidating the complexity of metastasis. Metastasis research also suffers from the knowledge and skill deficiency of the individual investigators. The importance of the present study is the demonstration that the "dry-lab-driven discovery and wet-lab validation" approach can improve the efficiency of studying complex biological behaviors, and can yield more reliable, objective and comprehensive mechanistic findings that are have clinical significance. Specifically, we applied this approach to study the mechanisms that underline the involvement of exosomal miRNAs in transferring the metastatic capability between heterogenous melanoma cancer cells. We show that the highly metastatic melanoma tumor cells (POL) can transfer their metastatic competency to the low-metastatic melanoma tumor cells (OL) by exosomal miR-211-5p. The oncogenic activity of miR-211-5p is mediated by the target gene guanine nucleotide-binding protein subunit alpha-15 (GNA15) through modifying the immune function of the tumor microenvironment extrinsically; as well as through inhibiting pyroptosis and augmenting glycolysis within OL cells intrinsically. In addition, we show that exosomal sorting of miR-211-5p is like selective and is subjected to regulation by a transcriptional feedback loop between miR-211-5p and zinc finger FYVE-type containing 26 (ZFYVE26). Furthermore, the "8-genes pyroptosis Risk model" derived from LASSO regression analysis was verified as an independent prognostic factor for melanoma.

Spectroscopic characterization of heteronuclear iron-chromium carbonyl cluster anions.

Infrared photodissociation spectroscopy has been used to investigate CrFe(CO)n- (n = 4-9) clusters in the gas phase. Comparison of the observed spectra in the carbonyl stretching frequency region with those predicted for low-lying isomers by DFT calculations showed that the observed CrFe(CO)n- (n = 4-8) clusters could be characterized to have Cr-Fe bonded (OC)4Fe-Cr(CO)n-4 structures. The coexistence of isomers with the (OC)Fe-Cr(CO)5 and (OC)3Fe-Cr(CO)4 structures was also observed for CrFe(CO)6- and CrFe(CO)7- anions, respectively. The CrFe(CO)n- (n = 4-8) complexes were strongly bonded systems. The CrFe(CO)8- complex was a coordination-saturated cluster, and the CrFe(CO)9- anion was characterized to contain a CrFe(CO)8- core tagged by one CO molecule. Bonding analysis revealed that the Cr-Fe bonds in the CrFe(CO)n- (n = 4-8) clusters were predominantly σ-type single bonds. The iron center in the Fe(CO)4 moiety and the chromium center in the Cr(CO)5 moiety fulfilled the 18-electron configuration for the CrFe(CO)n- (n = 4-6) clusters. As in the CrFe(CO)n- (n = 7, 8) complexes, the iron center in the Fe(CO)4 moiety exhibited a 17-electron configuration, while the chromium center in the Cr(CO)4 moiety exhibited a 16-electron configuration. These findings provide valuable insights into the structure and bonding mechanism of heterometallic carbonyl clusters.

Association between nickel exposure and body compositions in the United States: a population-based cross-sectional study.

BACKGROUND: Increasing body fat or decreasing muscle and bone mass were associated with worse health outcomes in the adult population. The effects of nickel exposure on body composition are not known. The aim of the current study was to investigate the relationship between urinary nickel levels and body compositions. MATERIALS AND METHODS: Two thousand seven hundred sixty-two participants were included in the analysis from the National Health and Nutrition Examination Surveys of 2017-2018 after excluding participants who have missing data on urinary nickel and those with missing all body mass component data. We used weighted generalized linear models to explore the relationship between urinary nickel and body mass components under interpolating missing covariable values. Simultaneously, sensitivity analyses and subgroup analysis were conducted to verify stability of analysis result. Curve fitting and saturation effect analysis were used to explore the possible nonlinear relationship between urine nickel and body compositions. RESULTS: Among the 2,762 participants, the average urinary nickel level was 1.58 ug/L. The weighted generalized linear models, the sensitivity analyses and subgroup analyses found no significant linear relationship between urinary nickel and body compositions. For body weight, BMI, TLM, ALM, TRF, TOF and BMC, the urine nickel saturation effect values were 0.76, 0.74, 0.5, 0.67, 0.64, 0.48, and 0.45 ug/L, respectively. For each 1 ug/L rise in urinary nickel levels at levels below the turning point, body weight increases (ß = 9.06, 95% CI = 2.75, 15.36, p = 0.01), BMI increases (ß = 3.20, 95% CI = 1.36, 5.05, p = < 0.001), TLM decreases (ß = -47.39, 95% CI = -97.38, 2.59, p = 0.06), ALM decreases (ß = -37.25, 95% CI = -63.25, -11.24, p = 0.01), TRF increases (ß = 20.68, 95% CI = 1.50, 39.86, p = 0.03), TOF increases (ß = 57.92, 95% CI = -0.12, 115.95, p = 0.05), and BMC decreases (ß = -6.84, 95% CI = -12.64, -1.04, p = 0.02). CONCLUSIONS: In summary, our study demonstrated that a dose-response relationship exists between urinary nickel and body compositions, with a low inflection point level of urinary nickel for the saturation effect.

Risk of second primary cancer in patients with head and neck squamous cell carcinoma: a systemic review and meta-analysis.

OBJECTIVES: Second primary cancer is a common event in patients with head and neck squamous cell carcinoma. However, the incidence and relevant factors vary by studies. We conducted a systematic review and meta-analysis of observational studies to estimate the incidence and relevant risk factors. MATERIALS AND METHODS: PubMed and Web of Science were searched for studies published between January 2000 and December 2020 that reported the incidence of SPC in HNSCC patients. Per 1000-person-year incidence and odds ratios were used to estimate the incidence and potential risk factors. Due to the high heterogeneity, random-effects models were used to estimate the incidence and 95% confidence interval. RESULTS: Seven thousand seven hundred thirteen articles were identified from the databases, in which 60 studies were included in this meta-analysis. The pooled incidence of the total, synchronous, and metachronous SPC in patients with HNSCC were 29.116 per 1000-person-year, 6.960 per 1000-person-year, and 26.025 per 1000-person-year, respectively. The head and neck region was the most common area where SPC occurred, followed by the lung (7.472 per 1000-person-year) and upper digestive tract (2.696 per 1000-person-year). Smoking, alcohol consumption, betel quid chewing, primary cancer of T1-2, and N0 were risk factors, while HPV infection (OR 0.47, 95% CI 0.30-0.72) was the protective factor. CONCLUSIONS: SPC is frequently observed in HNSCC patients and had great impact on the prognosis. The findings could promote a more individualized follow-up strategy for SPC in HNSCC patients. CLINICAL RELEVANCE: This systemic review and meta-analysis provide sufficient evidence for the establishment of the follow-up strategy for head and neck squamous cancer patients.

MF-Net: Automated Muscle Fiber Segmentation From Immunofluorescence Images Using a Local-Global Feature Fusion Network.

Histological assessment of skeletal muscle slices is very important for the accurate evaluation of weightless muscle atrophy. The accurate identification and segmentation of muscle fiber boundary is an important prerequisite for the evaluation of skeletal muscle fiber atrophy. However, there are many challenges to segment muscle fiber from immunofluorescence images, including the presence of low contrast in fiber boundaries in immunofluorescence images and the influence of background noise. Due to the limitations of traditional convolutional neural network-based segmentation methods in capturing global information, they cannot achieve ideal segmentation results. In this paper, we propose a muscle fiber segmentation network (MF-Net) method for effective segmentation of macaque muscle fibers in immunofluorescence images. The network adopts a dual encoder branch composed of convolutional neural networks and transformer to effectively capture local and global feature information in the immunofluorescence image, highlight foreground features, and suppress irrelevant background noise. In addition, a low-level feature decoder module is proposed to capture more global context information by combining different image scales to supplement the missing detail pixels. In this study, a comprehensive experiment was carried out on the immunofluorescence datasets of six macaques' weightlessness models and compared with the state-of-the-art deep learning model. It is proved from five segmentation indices that the proposed automatic segmentation method can be accurately and effectively applied to muscle fiber segmentation in shank immunofluorescence images.

Molecular regulation of fungal secondary metabolism.

Many bioactive secondary metabolites synthesized by fungi have important applications in many fields, such as agriculture, food, medical and others. The biosynthesis of secondary metabolites is a complex process involving a variety of enzymes and transcription factors, which are regulated at different levels. In this review, we describe our current understanding on molecular regulation of fungal secondary metabolite biosynthesis, such as environmental signal regulation, transcriptional regulation and epigenetic regulation. The effects of transcription factors on the secondary metabolites produced by fungi were mainly introduced. It was also discussed that new secondary metabolites could be found in fungi and the production of secondary metabolites could be improved. We also highlight the importance of understanding the molecular regulation mechanisms to activate silent secondary metabolites and uncover their physiological and ecological functions. By comprehensively understanding the regulatory mechanisms involved in secondary metabolite biosynthesis, we can develop strategies to improve the production of these compounds and maximize their potential benefits.

Investigating material basis and molecular mechanism of Qing Cuo formula in the treatment of acne based on animal experiments, UPLC-LTQ-Orbitrap-MS and network pharmacology.

CONTEXT: Qing Cuo Formula (QCF) is a traditional Chinese medicine for treating acne, but its active compounds and molecular mechanisms are unclear. OBJECTIVE: To investigate the material basis and molecular mechanism of QCF. MATERIALS AND METHODS: In vivo experiments were conducted on 60 male golden hamsters with damp-heat acne, with a blank group, a spironolactone group and 3 QCF administration groups (given high, medium and low doses) over a 30-day period. Serum androgen and inflammatory cytokine levels were tested by ELISA. In vitro, chemical compositions of QCF were investigated by UPLC-LTQ-Orbitrap-MS. Network pharmacology approaches were used to analyse the protein-protein interaction (PPI) network and QCF active compounds-intersection targets-acne network. GO enrichment and KEGG pathway analysis was conducted subsequently. RESULTS: Low-dose QCF group (11.4 g/kg/day) showed significantly reduced levels of serum T (4.94 ± 0.36; 5.51 ± 0.36 ng/mL), DHT (6.67 ± 0.61; 8.09 ± 0.59 nmol/L), E2 (209.01 ± 20.92; 237.08 ± 13.94 pg/mL), IL-1α (36.84 ± 3.23; 44.07 ± 4.00 pg/mL) and FFA (128.32 ± 10.94; 148.00 ± 12.12 µmol/L) compared to the blank group (p < 0.05). In vitro experiments identified 75 compounds in QCF decoction, with 27 active compounds absorbed in serum. Network pharmacology identified 6 active components connecting 17 targets. GO enrichment and KEGG pathway analysis indicated that QCF's anti-acne targets mainly regulate extracellular matrix function, inflammatory processes, immune response and endocrine function. CONCLUSIONS: This study provides evidence of the molecular mechanism and material basis of QCF in treating androgen-related damp-heat acne, paving the way for further research on its potential in treating other conditions related to damp-heat constitution.

Genome-wide identification of members of the Skp1 family in almond (Prunus dulcis), cloning and expression characterization of PsdSSK1.

Skp1 (S-phase kinase-associated protein 1) is the core gene of SCF ubiquitin ligase, which mediates protein degradation, thereby regulating biological processes such as cell cycle progression, transcriptional regulation, and signal transduction. A variety of plant Skp1 gene family studies have been reported. However, the almond Skp1 gene family has not yet been studied. In this study, we identified 18 members of the Prunus dulcis PdSkp1 family that were unevenly distributed across six chromosomes of the almond genome. Phylogenetic tree analysis revealed that the PdSkp1 members can be divided into three groups: I, II, and III. PdSkp1 members in each subfamily have relatively conserved motif types and exon/intron numbers. There were three pairs of fragment duplication genes and one pair of tandem repeat genes, and their functions were highly evolutionarily conserved. Transcriptome data showed that PdSkp1 is expressed in almond flower tissues, and that its expression shows significant change during cross-pollination. Fluorescence quantitative results showed that eight PdSkp1 genes had different expression levels in five tissues of almond, i.e., branches, leaves, flower buds, flesh, and cores. In addition, we cloned a PsdSSK1 gene based on PdSkp1. The cloned PsdSSK1 showed the same protein sequence as PdSkp1-12. Results of qPCR and western blot analysis showed high expression of PsdSSK1 in almond pollen. In conclusion, we report the first clone of the key gene SSK1 that controls self-incompatibility in almonds. Our research lays a foundation for future functional research on PdSkp1 members, especially for exploring the mechanism of almond self-incompatibility. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01278-9.