Identification of BANF1 as a novel prognostic biomarker in gastric cancer and validation via in-vitro and in-vivo experiments.

Gastric cancer (GC) is a widespread malignancy characterized by a notably high incidence rate and an unfavorable prognosis. We conducted a meticulous analysis of GC high-throughput sequencing data downloaded from the Gene Expression Omnibus (GEO) repository to pinpoint distinctive genes associated with GC. Our investigation successfully identified three signature genes implicated in GC, with a specific focus on the barrier to autointegration factor 1 (BANF1), which exhibits elevated expression across various cancer types, including GC. Bioinformatic analysis has highlighted BANF1 as a prognostic indicator for patients with GC, with direct implications for immune cell infiltration. To gain a more comprehensive understanding of the significance of BANF1 in GC, we performed a series of in vitro experiments to confirm its high expression in GC tissues and cellular components. Intriguingly, the induction of BANF1 knockdown resulted in a marked attenuation of proliferation, migratory capacity, and invasive potential in GC cells. Moreover, our in vivo experiments using nude mouse models revealed a notable impediment in tumor growth following BANF1 knockdown. These insights underscore the feasibility of BANF1 as a novel therapeutic target for GC.

MOF@Au NPs/aptamer fluorescent probe for the selective and sensitive detection of thiamethoxam.

The luminescence performance of fluorescent reagents plays a crucial role in fluorescence analysis. Therefore, in this study, a novel bi-ligand Zn-based metal-organic framework, Au nanoparticle (NP) fluorescent material was synthesized using a hydrothermal method with Zn as the metal source. Simultaneously, a DNA aptamer was introduced as a molecular recognition element to develop a Zn-based MOF@Au NPs/DNA aptamer fluorescent probe for the ultra-trace detection of thiamethoxam residues in agricultural products. The probe captured different concentrations of the target molecule, thiamethoxam, through the DNA aptamer, causing a conformational change in the DNA aptamer and bursting the fluorescence of the probe, therefore establishing a fluorometric method for thiamethoxam detection. This method is highly sensitive due to the excellent luminescence properties of the Zn-based MOF@Au NPs, and the DNA aptamer can specifically recognize thiamethoxam, offering high selectivity. The linear range of the method was 2.5-6000 × 10-11  mol L-1 , with a detection limit of 8.33 × 10-12  mol L-1 . This method was applied to the determination of actual samples, such as bananas, and the spiked recovery rate was found to be in the range 84.05-109.07%. Overall, the proposed probe has high sensitivity, high selectivity, and easy operation for the detection of thiamethoxam residues in actual samples.

Weight Loss Promotion in Individuals with Obesity through Gut Microbiota Alterations with a Multiphase Modified Ketogenic Diet.

The occurrence of obesity and related metabolic disorders is rising, necessitating effective long-term weight management strategies. With growing interest in the potential role of gut microbes due to their association with responses to different weight loss diets, understanding the mechanisms underlying the interactions between diet, gut microbiota, and weight loss remains a challenge. This study aimed to investigate the potential impact of a multiphase dietary protocol, incorporating an improved ketogenic diet (MDP-i-KD), on weight loss and the gut microbiota. Using metagenomic sequencing, we comprehensively analyzed the taxonomic and functional composition of the gut microbiota in 13 participants before and after a 12-week MDP-i-KD intervention. The results revealed a significant reduction in BMI (9.2% weight loss) among obese participants following the MDP-i-KD intervention. Machine learning analysis identified seven key microbial species highly correlated with MDP-i-KD, with Parabacteroides distasonis exhibiting the highest response. Additionally, the co-occurrence network of the gut microbiota in post-weight-loss participants demonstrated a healthier state. Notably, metabolic pathways related to nucleotide biosynthesis, aromatic amino acid synthesis, and starch degradation were enriched in pre-intervention participants and positively correlated with BMI. Furthermore, species associated with obesity, such as Blautia obeum and Ruminococcus torques, played pivotal roles in regulating these metabolic activities. In conclusion, the MDP-i-KD intervention may assist in weight management by modulating the composition and metabolic functions of the gut microbiota. Parabacteroides distasonis, Blautia obeum, and Ruminococcus torques could be key targets for gut microbiota-based obesity interventions.

Cellular senescence-related genes: predicting prognosis in hepatocellular carcinoma.

Recent studies have shown that the high incidence and low cure rate of hepatocellular carcinoma (HCC) have not improved significantly. Surgery and liver transplantation are the mainstays of prolonging the survival of HCC patients. However, the surgical resection rate of HCC patients is very low, and even after radical surgical resection, the recurrence rate at 5 years postoperatively remains high and the prognosis is very poor, so more treatment options are urgently needed. Increasing evidence suggests that cellular senescence is not only related to cancer development but may also be one of its primary driving factors. We aimed to establish a prognostic signature of senescence-associated genes to predict the prognosis and therapeutic response of HCC patients. The aim of this study was to develop a risk model associated with cellular senescence and to search for potential strategies to treat HCC. We divided HCC patients into two clusters and identified differentially expressed genes (DEGs) between clusters. In this study, low-risk patients had a better prognosis, higher levels of immune cell infiltration, and better efficacy to fluorouracil, Paclitaxel and Cytarabine chemotherapy compared to high-risk patients. To further identify potential biomarkers for HCC, we further validated the expression levels of the four signature genes in HCC and neighbouring normal tissues by in vitro experiments. In conclusion, we identified and constructed a relevant prognostic signature, which performed well in predicting the survival and treatment response of HCC patients. This helps to differentiate between low-score and high-risk HCC, and the results may contribute to precise treatment protocols in clinical practice.

Modulating the Human Gut Microbiota through Hypocaloric Balanced Diets: An Effective Approach for Managing Obesity.

This study aimed to investigate the effects of a hypocaloric balanced diet (HBD) on anthropometric measures and gut microbiota of 43 people with obesity. Fecal samples were collected from the study subjects at weeks 0 and 12, and a detailed analysis of gut microbiota was performed using 16S rRNA gene sequencing. By comparing anthropometric measures and microbiota changes in subjects before and after the HBD intervention, we revealed the potential effects of HBD on weight loss and gut microbiota. Our results indicated that the HBD resulted in a significant decrease in body mass index (BMI), and most of the physiological indicators were decreased to a greater degree in the effective HBD group (EHBD, weight loss ≥ 5%) than in the ineffective HBD group (IHBD, weight loss < 5%). The HBD intervention also modified the gut microbiota of the subjects with obesity. Specifically, Blautia, Lachnoclostridium, Terrisporobacter, Ruminococcus (R. torques, R. gnavus), and Pseudomonas were significantly reduced. In addition, we employed machine learning models, such as XGBRF and GB models, to rank the importance of various features and identified the top 10 key bacterial genera involved. Gut microbiota co-occurrence networks showed the dominance of healthier microbiota following successful weight loss. These results suggested that the HBD intervention enhanced weight loss, which may be related to diet-induced changes in the gut microbiota.

lncRNA ELFN1-AS1 upregulates TRIM29 by suppressing miR-211-3p to promote gastric cancer progression.

Long noncoding RNA (lncRNA) extracellular leucine rich repeat and fibronectin type III domain containing 1-antisense RNA 1 (ELFN1-AS1) has been found to be upregulated in various tumors. However, the biological functions of ELFN1-AS1 in gastric cancer (GC) are not entirely understood. In the present study, the expression levels of ELFN1-AS1, miR-211-3p, and TRIM29 are determined using reverse transcription-quantitative PCR. Subsequently, CCK8, EdU, and colony formation assays are performed to determine GC cell vitality. The migratory and invasive capabilities of GC cells are further evaluated using transwell invasion and cell scratch assays. Western blot analysis is performed to quantify the levels of proteins associated with GC cell apoptosis and epithelialmesenchymal transition (EMT). The competing endogenous RNA (ceRNA) activity of ELFN1-AS1 on TRIM29 through miR-211-3p is confirmed by pull-down, RIP, and luciferase reporter assays. Our study proves that ELFN1-AS1 and TRIM29 are highly expressed in GC tissues. ELFN1-AS1 silencing inhibits GC cell proliferation, migration, invasion and EMT, and induces cell apoptosis. Rescue experiments reveal that the oncogenicity of ELFN1-AS1 is modulated by acting as a sponge for miR-211-3p, thereby increasing the expression of the target gene of miR-211-3p, TRIM29. In summary, ELFN1-AS1 maintains GC cell tumorigenicity via the ELFN1-AS1/miR-211-3p/TRIM29 axis, indicating that this axis can be directed for GC treatment in the future.

A dicyanoisophorone-based ICT fluorescent probe for the detection of Hg2+ in water/food sample analysis and live cell imaging.

Mercury ions are notoriously difficult to biodegradable, and its abnormal bioaccumulation in the human body through the food chain can cause various diseases. Therefore, the quantitative and real-time detection of Hg2+ is very extremely important. Herein, we have brilliant designed and synthesized (E)-O-(4-(2-(3-(dicyanomethylene)-5,5-dimethylcyclohex-1-en-1-yl)vinyl)phenyl) O-phenyl carbonothioate (ICM-Hg) as a selective fluorescent probe for Hg2+ detection in real samples and intracellular staining. ICM-Hg displayed high specificity toward Hg2+ by activating the intramolecular charge transfer (ICT) process, resulting in distinguished color change from colorless to bright yellow along with noticeable switch on yellow fluorescence emission. The fluorescent intensity of ICM-Hg at 585 nm shows a well linear relationship in the range of Hg2+ concentration (0-45 µM), and the detection of limit for Hg2+ is calculated to be 231 nM. Promisingly, ICM-Hg can efficiently detect Hg2+ in real samples including tap water, tea, shrimp, and crab with quantitative recovery as well as the intracellular fluorescence imaging.

Expression, tumor immune infiltration, and prognostic impact of HMGs in gastric cancer.

Background: In the past decade, considerable research efforts on gastric cancer (GC) have been expended, however, little advancement has been made owing to the lack of effective biomarkers and treatment options. Herein, we aimed to examine the levels of expression, mutations, and clinical relevance of HMGs in GC to provide sufficient scientific evidence for clinical decision-making and risk management. Methods: GC samples were obtained from The Cancer Genome Atlas (TCGA). University of California Santa Cruz (UCSC) XENA, Human Protein Atlas (HPA), Gene Expression Profiling Interactive Analysis (GEPIA), Kaplan-Meier Plotter, cBioPortal, GeneMANIA, STRING, LinkedOmics, and DAVID databases were employed. The "ggplot2" package in the R software (×64 3.6.3) was used to thoroughly analyze the effects of HMGs. qRT-PCR was performed to assess HMG levels in GC cell lines. Results: A total of 375 GC tissues and 32 paraneoplastic tissues were analyzed. The levels of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN1, HMGN2, and HMGN4 expression were increased in GC tissues relative to normal gastric tissues. HMGA1, HMGA2, HMGB1, HMGB2, and HMGB3 were highly expressed in GC cell lines. The OS was significantly different in the group showing low expressions of HMGA1, HMGA2, HMGB1, HMGB2, HMGB3, HMGN2, HMGN3, and HMGN5. There was a significant difference in RFS between the groups with low HMGA2, HMGB3, and high HMGN2 expression. The levels of HMGA2, HMGB3, and HMGN1 had a higher accuracy for prediction to distinguish GC from normal tissues (AUC value > 0.9). HMGs were tightly associated with immune infiltration and tumor immune escape and antitumor immunity most likely participates in HMG-mediated oncogenesis in GC. GO and KEGG enrichment analyses showed that HMGs played a vital role in the cell cycle pathway. Conclusions: Our results strongly suggest a vital role of HMGs in GC. HMGA2 and HMGB3 could be potential markers for prognostic prediction and treatment targets for GC by interrupting the cell cycle pathway. Our findings might provide renewed perspectives for the selection of prognostic biomarkers among HMGs in GC and may contribute to the determination of the optimal strategy for the treatment of these patients.

The Antigastric Cancer Effect of Triptolide is Associated With H19/NF-κB/FLIP Axis.

Background and Objective: Triptolide (TP), one of the fat-soluble components extracted from the Chinese medicinal herb Tripterygium wilfordii Hook F. (TWHF), possesses strong antitumor bioactivities, but its dose-dependent side effects restrict its wide application. This study was designed to investigate whether inflammatory factors increased the antitumor effects of the nontoxic dose of TP on gastric cancer cells and tried to explore the possible molecular mechanisms. Method: AGS and MKN45 cells were treated with different doses of TP and TNF-α. Cell viability and apoptosis were detected in vitro. In addition, NF-κB mediated prosurvival signals and cytoprotective proteins, especially FLICE-inhibitory protein (FLIP), were detected to determine their effects on TP/TNF-α-induced apoptosis. Moreover, the function of lncRNA H19/miR-204-5p/NF-κB/FLIP axis was investigated in vitro, and the antigastric cancer effect of TP plus TNF-α was proved in the mice xenograft model. Result: In vitro experimental results showed that TP pretreatment promoted apoptosis in AGS and MKN45 cells upon TNF-α exposure. TP/TNF-α-mediated apoptosis was partly mediated by the inhibitory effect of NF-κB-mediated FLIP expression. Oncogene H19 lying in the upstream pathway of NF-κB played a vital role upon TNF-α exposure, and bioinformatics analysis proved that H19 participated in TP/TNF-α-induced apoptosis via binding of miR-204-5p. Lastly, a low dose of TP and TNF-α inhibited the tumor weight and tumor volume of AGS and MKN45 cells in vivo. Conclusion: TP pretreatment increased apoptosis in TNF-α-stimulated gastric cancer cells, which are dependent on the disruption of the H19/miR-204-5p/NF-κB/FLIP axis. Cotreatment of TP and TNF-α is a better option for enhancing the anticancer effect and lowering the side effect of TP.

The Optimization of Chlorella vulgaris Flocculation Harvesting by Chitosan and Calcium Hydroxide.

The high cost for microalgae harvesting still is the bottleneck of microalgae commercial production. In the present study, the effect of adjusting pH to alkaline conditions with sodium hydroxide/calcium hydroxide and the addition of chitosan together with pH adjustments on the flocculation of Chlorella vulgaris (C. vulgaris) was studied, respectively. A single-factor experiment showed a maximum flocculation efficiency of 96.7% when adjusting the pH to 12 with calcium hydroxide. There was synergistic action between chitosan and calcium hydroxide. Flocculation conditions of C. vulgaris for the combined use of calcium hydroxide and chitosan was optimized by response surface methodology (RSM) with a Box-Behnken design (BBD). Flocculation efficiency reached 97.08% under optimal flocculation conditions when adjustion of pH to 8.97 with 2 g/L calcium hydroxide, a chitosan dosage of 20 mg/L, and a flocculation time of 60 min. The current study presents one method for efficient flocculation harvesting of C. vulgaris at weak alkaline conditions and low chitosan dosage. Supplementary Information: The online version contains supplementary material available at 10.1007/s12088-022-01004-1.

Efficacy of Probiotic Compounds in Relieving Constipation and Their Colonization in Gut Microbiota.

A number of studies have confirmed the relationship between constipation and gut microbiota. Additionally, many human and animal experiments have identified probiotics as effectors for the relief of constipation symptoms. In this study, probiotic compounds, including Lactobacillus acidophilus LA11-Onlly, Lacticaseibacillus rhamnosus LR22, Limosilactobacillus reuteri LE16, Lactiplantibacillus plantarum LP-Onlly, and Bifidobacterium animalis subsp. lactis BI516, were administered to mice with loperamide-induced constipation, and the impacts of these strains on constipation-related indicators and gut microbiota were evaluated. The effects of probiotic compounds on constipation relief were associated with various aspects, including gastrointestinal transit rate, number and weight of stools, serum and intestinal gastrointestinal regulatory hormones, and serum cytokines. Some of the probiotic compounds, including Limosilactobacillus reuteri, Lactiplantibacillus plantarum, and Lacticaseibacillus rhamnosus, were found to colonize the intestinal tract. Furthermore, higher dosages promoted the colonization of specific strains. This study yields a new perspective for the clinical use of probiotics to improve constipation symptoms by combining strains with different mechanisms for the alleviation of constipation.

Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning.

The human gut microbiome is a complex ecosystem that is closely related to the aging process. However, there is currently no reliable method to make full use of the metagenomics data of the gut microbiome to determine the age of the host. In this study, we considered the influence of geographical factors on the gut microbiome, and a total of 2604 filtered metagenomics data from the gut microbiome were used to construct an age prediction model. Then, we developed an ensemble model with multiple heterogeneous algorithms and combined species and pathway profiles for multi-view learning. By integrating gut microbiome metagenomics data and adjusting host confounding factors, the model showed high accuracy (R2 = 0.599, mean absolute error = 8.33 years). Besides, we further interpreted the model and identify potential biomarkers for the aging process. Among these identified biomarkers, we found that Finegoldia magna, Bifidobacterium dentium, and Clostridium clostridioforme had increased abundance in the elderly. Moreover, the utilization of amino acids by the gut microbiome undergoes substantial changes with increasing age which have been reported as the risk factors for age-associated malnutrition and inflammation. This model will be helpful for the comprehensive utilization of multiple omics data, and will allow greater understanding of the interaction between microorganisms and age to realize the targeted intervention of aging.

A multiphase dietetic protocol incorporating an improved ketogenic diet enhances weight loss and alters the gut microbiome of obese people.

The prevalence of obesity and its associated diseases is increasing. In the current study, 15 obese subjects took part in a 12-week multiphase dietetic protocol incorporating an improved ketogenic diet (MDP-i-KD) (KYLLKS 201806). We investigated the effects of the MDP-i-KD on the anthropometric parameters and the gut microbiota of obese subjects. Our results showed that the MDP-i-KD led to significant reductions in body mass index in obese subjects. The MDP-i-KD significantly decreased the relative abundance of the Lachnospiraceae_ND3007_group, the Eubacterium_hallii_group, and Pseudomonas and Blautia. In addition, gut microbiota co-occurrence networks in obese subjects were restructured to a more healthy condition after weight loss. These results show that the MDP-i-KD enhanced weight loss, which may be associated with dietary-induced changes in the gut microbiome. Our results emphasise the importance of determining the interaction between the host and microbial cells to comprehensively understand the mechanism by which diet affects host physiology and the microbiota.

Predicting the Role of the Human Gut Microbiome in Constipation Using Machine-Learning Methods: A Meta-Analysis.

(1) Background: Constipation is a common condition that affects the health and the quality of life of patients. Recent studies have suggested that the gut microbiome is associated with constipation, but these studies were mainly focused on a single research cohort. Thus, we aimed to construct a classification model based on fecal bacterial and identify the potential gut microbes' biomarkers. (2) Methods: We collected 3056 fecal amplicon sequence data from five research cohorts. The data were subjected to a series of analyses, including alpha- and beta-diversity analyses, phylogenetic profiling analyses, and systematic machine learning to obtain a comprehensive understanding of the association between constipation and the gut microbiome. (3) Results: The alpha diversity of the bacterial community composition was higher in patients with constipation. Beta diversity analysis evidenced significant partitions between the two groups on the base of gut microbiota composition. Further, machine learning based on feature selection was performed to evaluate the utility of the gut microbiome as the potential biomarker for constipation. The Gradient Boosted Regression Trees after chi2 feature selection was the best model, exhibiting a validation performance of 70.7%. (4) Conclusions: We constructed an accurate constipation discriminant model and identified 15 key genera, including Serratia, Dorea, and Aeromonas, as possible biomarkers for constipation.

Nucleocytoplasmic trafficking and turnover mechanisms of BRASSINAZOLE RESISTANT1 in Arabidopsis thaliana.

Regulation of the nucleocytoplasmic trafficking of signaling components, especially transcription factors, is a key step of signal transduction in response to extracellular stimuli. In the brassinosteroid (BR) signal transduction pathway, transcription factors from the BRASSINAZOLE RESISTANT1 (BZR1) family are essential in mediating BR-regulated gene expression. The subcellular localization and transcriptional activity of BZR1 are tightly regulated by reversible protein phosphorylation; however, the underlying mechanism is not well understood. Here, we provide evidence that both BZR1 phosphorylation and dephosphorylation occur in the nucleus and that BR-regulated nuclear localization of BZR1 is independent from its interaction with, or dephosphorylation by, protein phosphatase 2A. Using a photoconvertible fluorescent protein, Kaede, as a living tag to distinguish newly synthesized BZR1 from existing BZR1, we demonstrated that BR treatment recruits cytosolic BZR1 to the nucleus, which could explain the fast responses of plants to BR. Additionally, we obtained evidence for two types of protein turnover mechanisms that regulate BZR1 abundance in plant cells: a BR- and 26S proteosome-independent constitutive degradation mechanism and a BR-activated 26S proteosome-dependent proteolytic mechanism. Finally, treating plant cells with inhibitors of 26S proteosome induces the nuclear localization and dephosphorylation of BZR1, even in the absence of BR signaling. Based on these results, we propose a model to explain how BR signaling regulates the nucleocytoplasmic trafficking and reversible phosphorylation of BZR1.

The role of phenylalanine hydroxylase in lipogenesis in the oleaginous fungus Mortierella alpina.

Phenylalanine hydroxylase (PAH) catalyses the irreversible hydroxylation of phenylalanine to tyrosine, which is the rate-limiting reaction in phenylalanine metabolism in animals. A variety of polyunsaturated fatty acids can be synthesized by the lipid-producing fungus Mortierella alpina, which has a wide range of industrial applications in the production of arachidonic acid. In this study, RNA interference (RNAi) with the gene PAH was used to explore the role of phenylalanine hydroxylation in lipid biosynthesis in M. alpina. Our results indicated that PAH knockdown decreased the PAH transcript level by approximately 55% and attenuated cellular fatty acid biosynthesis. Furthermore, the level of NADPH, which is a critical reducing agent and the limiting factor in lipogenesis, was decreased in response to PAH RNAi, in addition to the downregulated transcription of other genes involved in NADPH production. Our study indicates that PAH is part of an overall enzymatic and regulatory mechanism supplying NADPH required for lipogenesis in M. alpina.

Serum Lactate Dehydrogenase Level as a Prognostic Factor for COVID-19: A Retrospective Study Based on a Large Sample Size.

Background: In this study, we investigated the relationship between serum lactate dehydrogenase (LDH) level and disease progression and prognosis of patients with COVID-19. Methods: We retrospectively reviewed the information of 1,751 patients with COVID-19 from Leishenshan Hospital in Wuhan, China. Univariate and multivariate Cox regression analyses as well as Logistics regression analyses, and Kaplan-Meier curves were used to determine the association between LDH levels and the prognosis of COVID-19 patients. Results: LDH was an independent risk factor for in-hospital death no matter it was taken as classified variable and continuous variable (all P = 0.001) but not for severe or critical illness status. The Kaplan-Meier curves for LDH level showed that an elevated level of LDH was associated with in-hospital death. Conclusions: In patients with COVID-19, the increased LDH level is associated with a higher risk of negative clinical prognosis and higher mortality. This will provide a reference for clinicians and researchers to understand, diagnose, and treat patients with COVID-19. Further prospective studies with larger sample sizes are needed to verify these findings.

Long non-coding RNA LINC01116 accelerates the progression of keloid formation by regulating miR-203/SMAD5 axis.

BACKGROUND: Emerging evidence reveals the importance of long non-coding RNAs (lncRNAs) in the development and progression of keloid formation. However, the roles and molecular mechanism of lncRNA LINC01116 in the progression of keloid formation remain largely unknown. METHODS: The expression levels of LINC01116, microRNA-203 (miR-203) and SMAD family member 5 (SMAD5) were measured by quantitative real-time polymerase chain reaction (qRT-PCR) and western blot. Cell proliferation, migration and invasion were detected by Cell counting Kit-8 (CCK-8) assay and transwell assay. Flow cytometry and western blot assay were used to examine cell apoptosis and extracellular matrix (ECM) production. The interaction between miR-203 and LINC01116 or SMAD5 was predicted by bioinformatics analysis and verified by dual-luciferase reporter and RNA Immunoprecipitation (RIP) and RNA pull-down assays. RESULTS: LINC01116 and SMAD5 were upregulated while miR-203 was downregulated in keloid tissues and keloid fibroblasts. LINC01116 knockdown suppressed the proliferation, migration, invasion, and ECM production but induced apoptosis in keloid fibroblasts through enhancing miR-203 and inhibiting SMAD5. Moreover, SMAD5 was identified as a direct target of miR-203 and miR-203 could directly bind to LINC01116. Besides, LINC01116 regulated SMAD5 expression by targeting miR-203. CONCLUSION: Downregulation of LINC01116 inhibited the progression of keloid formation by regulating miR-203/SMAD5 axis, which might provide a novel target for keloid therapy.

Quantification and Impact of Cold Storage and Heat Exposure on Mass Rearing Program of Bactrocera dorsalis (Diptera:Tephritidae) Genetic Sexing Strain.

Cold storage and heat exposure are crucial components of tephritid fruit fly mass-rearing programs, as they influence the development and fitness traits of produced flies. This work investigated the effects of cold storage on the pupal developmental parameters and quality of Bactrocera dorsalis (Hendel) genetic sexing strain (GSS) adults. Furthermore, the impact of short-term thermal exposure on the fecundity of B. dorsalis (GSS) that also underwent pupal cold storage was examined. Our results show that pupal development time, emergence rate, partial emergence rate, flight ability and fecundity were significantly affected by low temperature and pupal age and their interaction. Pupal cold storage did not pose negative impacts on the mating competition and response to methyl eugenol (ME) in the males. In addition, compared with the adults that were subjected to the same pupal storage protocol (five-day-old pupae stored at 13 °C), adult exposure to 41 °C for 1 h showed significant reparative effects on fecundity. In summary, the cold storage procedure of B. dorsalis (GSS) pupae has the potential to improve the flexibility and efficiency of mass-rearing schedules. Furthermore, short-term thermal exposure showed reparative effects on the fecundity costs induced by pupal cold storage in B. dorsalis (GSS).

Potential of gut microbiome for detection of autism spectrum disorder.

Autism spectrum disorder (ASD) is a neuro developmental disorder characterized by a series of abnormal social behaviors. The increasing prevalence of ASD has led to the discovery of a correlation with the intestinal microbiome in many studies. In our research, we evaluated 297 subjects, including 169 individuals with ASD and 128 neurotypical subjects, from the Sequence Read Archive database. We conducted a series of analyses, including alpha-diversity, phylogenetic profiles, and functional profiles, to explore the correlation between the gut microbiome and ASD. The principal component analysis (PCA) indicated that ASD and neurotypical subjects could be divided based on the unweighted UniFrac distance. The genera Prevotella, Roseburia, Ruminococcus, Megasphaera, and Catenibacterium might be biomarkers of ASD after linear discriminant analysis effect size (LEfSe) evaluation and Random Forest analysis, respectively. The functional analysis found six significant pathways between ASD and neurotypical subjects, including oxidative phosphorylation, nucleotide excision repair, peptidoglycan biosynthesis, photosynthesis, photosynthesis proteins, and two-component system. Based on these alterations of the intestinal microbiome in ASD subjects, we developed four machine learning models: random forest (RF), Multilayer Perceptron (MLP), kernelized support vector machines with the RBF kernel (SVMs), and Decision trees (DT). Notably, the RF model after RF selection was superior, with an F1 score of 0.74 and area under the curve of 0.827(0.004), suggesting the reliability and generalizability of predictive model. Besides, the validation performance of RF model after RF selection could be 0.75(0.01) on external cohort collected by our laboratory. Our study advances the understanding of human gut microbiome in ASD that designing and evaluating microbially based interventions of ASD.