Personalized venlafaxine dose prediction using artificial intelligence technology: a retrospective analysis based on real-world data.

BACKGROUND: Venlafaxine dose regimens vary considerably between individuals, requiring personalized dosing. AIM: This study aimed to identify dose-related influencing factors of venlafaxine through real-world data analysis and to construct a personalized dose model using advanced artificial intelligence techniques. METHOD: We conducted a retrospective study on patients with depression treated with venlafaxine. Significant variables were selected through a univariate analysis. Subsequently, the predictive performance of seven models (XGBoost, LightGBM, CatBoost, GBDT, ANN, TabNet, and DT) was compared. The algorithm that demonstrated optimal performance was chosen to establish the dose prediction model. Model validation used confusion matrices and ROC analysis. Additionally, a dose subgroup analysis was conducted. RESULTS: A total of 298 patients were included. TabNet was selected to establish the venlafaxine dose prediction model, which exhibited the highest performance with an accuracy of 0.80. The analysis identified seven crucial variables correlated with venlafaxine daily dose, including blood venlafaxine concentration, total protein, lymphocytes, age, globulin, cholinesterase, and blood platelet count. The area under the curve (AUC) for predicting venlafaxine doses of 75 mg, 150 mg, and 225 mg were 0.90, 0.85, and 0.90, respectively. CONCLUSION: We successfully developed a TabNet model to predict venlafaxine doses using real-world data. This model demonstrated substantial predictive accuracy, offering a personalized dosing regimen for venlafaxine. These findings provide valuable guidance for the clinical use of the drug.

Developing a machine learning model for predicting venlafaxine active moiety concentration: a retrospective study using real-world evidence.

BACKGROUND: Venlafaxine is frequently prescribed for patients with depression. To control the concentration of venlafaxine within the therapeutic window for the best treatment effect, a model to predict venlafaxine concentration is necessary. AIM: Our objective was to develop a prediction model for venlafaxine concentration using real-world evidence based on machine learning and deep learning techniques. METHOD: Patients who underwent venlafaxine treatment between November 2019 and August 2022 were included in the study. Important variables affecting venlafaxine concentration were identified using a combination of univariate analysis, sequential forward selection, and machine learning techniques. Predictive performance of nine machine learning and deep learning algorithms were assessed, and the one with the optimal performance was selected for modeling. The final model was interpreted using SHapley Additive exPlanations. RESULTS: A total of 330 eligible patients were included. Five influential variables that affect venlafaxine concentration were venlafaxine daily dose, sex, age, hyperlipidemia, and adenosine deaminase. The venlafaxine concentration prediction model was developed using the eXtreme Gradient Boosting algorithm (R2 = 0.65, mean absolute error = 77.92, root mean square error = 93.58). In the testing cohort, the accuracy of the predicted concentration within ± 30% of the actual concentration was 73.49%. In the subgroup analysis, the prediction accuracy was 69.39% within the recommended therapeutic range of venlafaxine concentration within ± 30% of the actual value. CONCLUSION: The XGBoost model for predicting blood concentration of venlafaxine using real-world evidence was developed, guiding the adjustment of regimen in clinical practice.

Effects of the ZrO2 Crystalline Phase and Morphology on the Thermocatalytic Decomposition of Dimethyl Methylphosphonate.

Thermocatalytic decomposition is an efficient purification technology that is potentially applicable to degrading chemical warfare agents and industrial toxic gases. In particular, ZrO2 has attracted attention as a catalyst for the thermocatalytic decomposition of dimethyl methylphosphonate (DMMP), which is a simulant of the nerve gas sarin. However, the influence of the crystal phase and morphology on the catalytic performance of ZrO2 requires further exploration. In this study, monoclinic- and tetragonal-phase ZrO2 (m- and t-ZrO2, respectively) with nanoparticle, flower-like shape and hollow microsphere morphologies were prepared via hydrothermal and solvothermal methods, and their thermocatalytic decomposition of DMMP was systematically investigated. For a given morphology, m-ZrO2 performed better than t-ZrO2. For a given crystalline phase, the morphology of hollow microspheres resulted in the longest protection time. The exhaust gases generated by the thermocatalytic decomposition of DMMP mainly comprised H2, CO2, H2O and CH3OH, and the by-products were phosphorus oxide species. Thus, the deactivation of ZrO2 was attributed to the deposition of these phosphorous oxide species on the catalyst surface. These results are expected to help guide the development of catalysts for the safe disposal of chemical warfare agents.

Integrative analysis with machine learning identifies diagnostic and prognostic signatures in neuroblastoma based on differentially DNA methylated enhancers between INSS stage 4 and 4S neuroblastoma.

INTRODUCTION: Accumulating evidence demonstrates that aberrant methylation of enhancers is crucial in gene expression profiles across several cancers. However, the latent effect of differently expressed enhancers between INSS stage 4S and 4 neuroblastoma (NB) remains elusive. METHODS: We utilized the transcriptome and methylation data of stage 4S and 4 NB patients to perform Enhancer Linking by Methylation/Expression Relationships (ELMER) analysis, discovering a differently expressed motif within 67 enhancers between stage 4S and 4 NB. Harnessing the 67 motif genes, we established the INSS stage related signature (ISRS) by amalgamating 12 and 10 distinct machine learning (ML) algorithms across 113 and 101 ML combinations to precisely diagnose stage 4 NB among all NB patients and to predict the prognosis of NB patients. Based on risk scores calculated by prognostic ISRS, patients were categorized into high and low-risk groups according to median risk score. We conducted comprehensive comparisons between two risk groups, in terms of clinical applications, immune microenvironment, somatic mutations, immunotherapy, chemotherapy and single-cell analysis. Ultimately, we empirically validated the differential expressions of two ISRS model genes, CAMTA2 and FOXD1, through immunochemistry staining. RESULTS: Through leave-one-out cross-validation, in both feature selection and model construction, we selected the random forest algorithm to diagnose stage 4 NB, and Enet algorithm to develop prognostic ISRS, due to their highest average C-index across five NB cohorts. After validations, the ISRS demonstrated a stable predictive capability, outperforming the previously published NB signatures and several clinic variables. We stratified NB patients into high and low-risk group based on median risk score, which showed the low-risk group with a superior survival outcome, an abundant immune infiltration, a decreased mutation landscape, and an enhanced sensitivity to immunotherapy. Single-cell analysis between two risk groups reveals biologically cellular variations underlying ISRS. Finally, we verified the significantly higher protein levels of CAMTA2 and FOXD1 in stage 4S NB, as well as their protective prognosis value in NB. CONCLUSION: Based on multi-omics data and ML algorithms, we successfully developed the ISRS to enable accurate diagnosis and prognostic stratification in NB, which shed light on molecular mechanisms of spontaneous regression and clinical utilization of ISRS.

Long-term recurrence of ischemic events in patients with intracranial atherosclerotic stenosis stratified by symptoms and pathogenesis.

BACKGROUND: Intracranial atherosclerotic stenosis (ICAS) can cause either transient ischemic attack (TIA) or acute ischemic stroke (AIS). Pathogenesis of ICAS-AIS can be divided into artery-to-artery embolism(A-A), hypoperfusion(HP), and parent-artery atherosclerosis occluding penetrating artery(POPA). However, the prognosis of each type remains uncertain. Our study aimed to investigate potential disparities in the recurrent risk among these four subtypes of symptomatic ICAS. METHODS: From a prospective, single-center cohort study of acute cerebrovascular diseases from January 2017 to November 2021, we recruited 120 ICAS patients and classified them into four groups based on diffusion weighted imaging. Patients were retrospectively followed up for recurrence in December 2022. The primary outcome was recurrent cerebral vascular events (RCVE) in the same territory. RESULTS: Among 120 recruited patients, POPA(33%) was the most common subtype, followed by A-A(32%), HP(29%), and TIA(6%). Cumulative recurrent rate was 31.2% with median months of follow-up as 27(20-45.5). There was no significant difference in the risk of RCVE in the same territory among four subgroups within three months. However, when considering the risk after three months, TIA(57%) had the highest risk of RCVE, followed by A-A(26%), while HP(4%) and POPA(8%) had lower risks (P = 0.001). Cox regression model indicated that symptom and pathogenesis was an independent risk factor for RCVE in long-term prognosis (P = 0.022), after adjusting for a history of hypertension and cerebral infarction. CONCLUSIONS: Distinctive symptoms and pathogenesis of ICAS exhibit varying risks of RCVE in long-term prognosis. The differentiation in recurrent risk may provide valuable insights for guiding secondary prevention strategies.

Human Mesenchymal Stem Cells-Derived Exosome Mimetic Vesicles Regulation of the MAPK Pathway and ROS Levels Inhibits Glucocorticoid-Induced Apoptosis in Osteoblasts.

Background: Long-term extensive use of glucocorticoids will lead to hormonal necrosis of the femoral head, and osteoblasts play an important role in the prevention of osteonecrosis. However, there is no complete cure for necrosis of the femoral head. Mesenchymal stem cell- (MSCs-) derived exosomes are widely used for the repair of various tissue lesions. Therefore, the aim of this study was to investigate the mechanism of dexamethasone- (DEX-) induced osteoblast apoptosis and the therapeutic effect of human umbilical cord MSC- (hucMSC-) derived exosome mimetic vesicles (EMVs) on osteoblast-induced apoptosis by DEX. Methods: The viability and apoptosis of primary MC3T3-E1 cells were determined by the Cell Counting Kit-8 (CCK-8), FITC-Annexin V/PI staining and immunoblot. The intracellular levels of reactive oxygen species (ROS) after DEX treatment were measured by 2', 7' -dichlorodihydrofluorescein diacetate (DCFH-DA) staining. In this study, hucMSC-EMVs and N-acetyl-l-cysteine (NAC) were used as therapeutic measures. The expression of B-cell lymphoma 2-associated X, Bcl 2, HO-1, and nuclear factor erythroid-derived 2-like 2 and MAPK- signaling pathway in osteogenic cell MC3T3-E1 cells treated with Dex was analyzed by the immunoblotting. Results: DEX significantly induced osteoblasts MC3T3-E1 apoptosis and ROS accumulation. MAPK-signaling pathway was activated in MC3T3-E1 after DEX treatment. hucMSC-EMVs intervention significantly downregulated DEX-induced MAPK-signaling pathway activation and ROS accumulation. In addition, hucMSC-EMVs can reduce the apoptosis levels in osteoblast MC3T3-E1 cells induced by DEX. Conclusions: Our study confirmed that hucMSC-EMVs regulates MAPK-signaling pathway and ROS levels to inhibit DEX-induced osteoblast apoptosis.

Al Doped into Si/P Sites of Na3Zr2Si2PO12 with Conducted Na3PO4 Impurities for Enhanced Ionic Conductivity.

Natrium superionic conductor (NASICON) is a promising solid-state electrolyte because of its high stability under air as well as its safety. Doping is an effective way to improve its ionic conductivity, but there is limited information about the explanation of the doping sites. In this work, Al-doped NASICONs are designed. When Al doping is 0.3 (NAl0.3ZSP), the ionic conductivity is the highest and is 5.08 × 10-5 S cm-1 at 30 °C, which is 3.3 times that of undoped NASICON. NAl0.3ZSP consists of a NASICON structure (monoclinic and rhombohedral phases), an amorphous glassy phase, and Na3PO4 impurities. After Al doping, more Si/P sites are occupied by Al; thus, the ratio of Na3PO4 impurities increases. Na3PO4 at the grain boundary is beneficial for grain boundary resistance decrease, contributing to the decrease of the total resistance. Our work first provides a detailed explanation of doped-Al sites and interprets their effects on ionic conductivity.

Stress response and tolerance mechanisms of spirobudiclofen exposure based on multiomics in Panonychus citri (Acari: Tetranychidae).

The toxicity of insecticides used in the field decreases gradually to sublethal concentrations over time. Therefore, it is necessary to study sublethal effects of pesticides for controlling population explosion. Panonychus citri is a global pest which control is based on insecticides. This study explores the stress responses of spirobudiclofen on the P. citri. Spirobudiclofen significantly inhibited survival and reproduction of P. citri, and the effects aggravated as concentration increased. The transcriptomes and metabolomes of spirobudiclofen-treated and control were compared to characterize spirobudiclofen molecular mechanism. Transcriptomics indicated stress induced by spirobudiclofen stimulated immune defense, antioxidative system, cuticle formation, and lipid metabolism, as deduced from RNA-seq analysis. Meanwhile, our study found that tolerance metabolism in P. citri was regulated by promoting the metabolism of glycerophospholipids, glycine, serine, and threonine. The results of this study can provide a basis for exploring the adaptation strategies of P. citri to spirobudiclofen stress.

Individualized network analysis reveals a link between the gut microbiome, diet intervention and Gestational Diabetes Mellitus.

Gestational Diabetes Mellitus (GDM), a serious complication during pregnancy which is defined by abnormal glucose regulation, is commonly treated by diabetic diet and lifestyle changes. While recent findings place the microbiome as a natural mediator between diet interventions and diverse disease states, its role in GDM is still unknown. Here, based on observation data from healthy pregnant control group and GDM patients, we developed a new network approach using patterns of co-abundance of microorganism to construct microbial networks that represent human-specific information about gut microbiota in different groups. By calculating network similarity in different groups, we analyze the gut microbiome from 27 GDM subjects collected before and after two weeks of diet therapy compared with 30 control subjects to identify the health condition of microbial community balance in GDM subjects. Although the microbial communities remain similar after the diet phase, we find that the structure of their inter-species co-abundance network is significantly altered, which is reflected in that the ecological balance of GDM patients was not "healthier" after the diet intervention. In addition, we devised a method for individualized network analysis of the microbiome, thereby a pattern is found that GDM individuals whose microbial networks are with large deviations from the GDM group are usually accompanied by their abnormal glucose regulation. This approach may help the development of individualized diagnosis strategies and microbiome-based therapies in the future.

The Enhancement of CO Oxidation Performance and Stability in SO2 and H2S Environment on Pd-Au/FeOX/Al2O3 Catalysts.

Carbon monoxide (CO) is a colourless, odourless, and toxic gas. Long-term exposure to high concentrations of CO causes poisoning and even death; therefore, CO removal is particularly important. Current research has focused on the efficient and rapid removal of CO via low-temperature (ambient) catalytic oxidation. Gold nanoparticles are widely used catalysts for the high-efficiency removal of high concentrations of CO at ambient temperature. However, easy poisoning and inactivation due to the presence of SO2 and H2S affect its activity and practical application. In this study, a bimetallic catalyst, Pd-Au/FeOx/Al2O3, with a Au:Pd ratio of 2:1 (wt%) was formed by adding Pd nanoparticles to a highly active Au/FeOx/Al2O3 catalyst. Its analysis and characterisation proved that it has improved catalytic activity for CO oxidation and excellent stability. A total conversion of 2500 ppm of CO at -30 °C was achieved. Furthermore, at ambient temperature and a volume space velocity of 13,000 h-1, 20,000 ppm CO was fully converted and maintained for 132 min. Density functional theory (DFT) calculations and in situ FTIR analysis revealed that Pd-Au/FeOx/Al2O3 exhibited stronger resistance to SO2 and H2S adsorption than the Au/FeOx/Al2O3 catalyst. This study provides a reference for the practical application of a CO catalyst with high performance and high environmental stability.

Plasma metabolomic characterization of SARS-CoV-2 Omicron infection.

Omicron variants of SARS-CoV-2 have spread rapidly worldwide; however, most infected patients have mild or no symptoms. This study aimed to understand the host response to Omicron infections by performing metabolomic profiling of plasma. We observed that Omicron infections triggered an inflammatory response and innate immune, and adaptive immunity was suppressed, including reduced T-cell response and immunoglobulin antibody production. Similar to the original SARS-CoV-2 strain circulating in 2019, the host developed an anti-inflammatory response and accelerated energy metabolism in response to Omicron infection. However, differential regulation of macrophage polarization and reduced neutrophil function has been observed in Omicron infections. Interferon-induced antiviral immunity was not as strong in Omicron infections as in the original SARS-CoV-2 infections. The host response to Omicron infections increased antioxidant capacity and liver detoxification more than in the original strain. Hence, these findings suggest that Omicron infections cause weaker inflammatory alterations and immune responses than the original SARS-CoV-2 strain.

Symptom relationships between internet addiction and anxiety across primary and middle school students during the Omicron lockdown.

During the Omicron pandemic, students in Shenzhen took classes at home via the internet, which could lead to internet addiction (IA) symptoms, and anxiety is often considered an important risk factor for IA. There are several different developmental stages within adolescence. However, no studies have explored the interaction between IA and anxiety at the symptom level using a longitudinal design stratified by age. A total of 2744 students completed the questionnaire 50 days after starting the online classes (T1) and 50 days after they returned to school (T2). A cross-lagged panel network model was used to describe the structure of the comorbidity network. With the help of bootstrapping, the Mann-Whitney U test was used to examine the differences between primary school students' and middle school students' networks. The results found that there is a bidirectional interaction between IA and anxiety, and anxiety plays a dominant role. Feeling afraid is the bridge symptom between IA and anxiety. IA did not show developmental stage differences, but anxiety did. These findings extend the model of compensatory internet use and suggest that, when alleviating IA symptoms in adolescents, attention should be given to their possible comorbid anxiety symptoms, especially in middle school students.

Prediction and validation of microbial community function from normal pulp to pulpitis caused by deep dentinal caries.

INTRODUCTION: Microbial function changes may be responsible for dental pulp transformation from normal to diseased. However, studies on the prediction and verification of the function of the microbial community in the deep dentine and pulp of caries-induced pulpitis are lacking. METHODS: This study included 171 cases of deep dentinal caries divided into normal pulp (NP), reversible pulpitis (RP), and irreversible pulpitis (IRP). In Experiment I, the microbial community composition was identified in 111 samples using 16S ribosomal DNA. Function prediction was performed through phylogenetic investigation of communities by Phylogenetic Investigation of Communities by Reconstruction of Unobserved States prediction and qPCR. In Experiment II, different microbiome functions were confirmed in 60 samples using liquid chromatography-tandem mass spectrometry. RESULTS: In Experiment I, microbial abundance significantly differed in the IRP group compared to the other two groups. The RP and NP groups had the same microbiome composition, but the predicted functional difference between the RP and NP groups pertained to membrane transport (p < .010). The predicted functional difference between the IRP and NP groups pertained to amino-acid, co-factor, and vitamin metabolism (p < .010). In Experiment II, Kyoto Encyclopedia of Genes and Genomes functional annotation revealed that the differential metabolites between the RP and NP groups did not participate in membrane transport; however, the differential metabolites between the IRP and NP groups participated in amino-acid metabolism. CONCLUSIONS: The near-pulp microbiome in RP and NP with deep dentinal caries had the same differential function. However, amino acid metabolism in near the pulp microbial community differed between IRP and NP with deep dentinal caries.

A series of two-sample non-parametric tests for quantile residual life time.

Quantile residual lifetime (QRL) is of significant interest in many clinical studies as an easily interpretable quantity compared to other summary measures of survival distributions. In cancer or other chronic diseases, treatments are often compared based on the distributions or quantiles of the residual lifetime. Thus a common problem of interest is to test the equality of the QRL between two populations. In this paper, we propose two classes of tests to compare two QRLs; one class is based on the difference between two estimated QRLs, and the other is based on the estimating function of the QRL, where the estimated QRL from one sample is plugged into the QRL-estimating-function of the other sample. We outline the asymptotic properties of these test statistics. Simulation studies demonstrate that the proposed tests produced Type I errors closer to the nominal level and are superior to some existing tests based on both Type I error and power. Our proposed test statistics are also computationally less intensive and more straightforward compared to tests based on the confidence intervals. We applied the proposed methods to a randomized multicenter phase III trial for breast cancer patients.

Delayed-onset swelling around the implant after cochlear implantation: a series of 26 patients.

PURPOSE: We aimed to clarify the clinical features of delayed-onset swelling around cochlear implants (CI), and to present our experience on how to avoid and address this problem. METHODS: We performed a retrospective review of all CI cases at our institution between June 2001 and June 2020. Information on postoperative complications of swelling in the receiver area > 3 months after implantation were analyzed, and clinical data sheets were drawn. RESULTS: Twenty-six of 1425 patients (1.82%) with an age at implantation ranging from 1 to 9 years experienced delayed-onset swelling around the implant. Swelling episodes occurred as early as 4 months, and as late as 178 months after implantation (median, 79.7 months). The predisposing factor in 12 cases was unclear, 7 cases were caused by trauma at the implantation site, 5 cases were without predisposing factors, and 2 cases were related to infection. We found the frequency of delayed-onset swelling after cochlear implantation with different incision was statistically insignificant (P = 0.423). Nineteen patients (73.1%) were cured after one treatment, and five patients (19.2%) relapsed. Follow-up examinations at least 18 months after surgery revealed that all patients experienced a complete recovery. CONCLUSIONS: Delayed-onset swelling at the receiver site is a long term but not exactly uncommon complication after cochlear surgery and long-term follow-up is eagerly required. It can recur more than once, causing more complex treatment strategies in clinical practice. Conservative treatment first recommended, while needle aspiration should initially be considered in recurrent cases also when the effusion swelling is > 3 ml.

Comammox Nitrospira Clade B is the most abundant complete ammonia oxidizer in a dairy pasture soil and inhibited by dicyandiamide and high ammonium concentrations.

The recent discovery of comammox Nitrospira, a complete ammonia oxidizer, capable of completing the nitrification on their own has presented tremendous challenges to our understanding of the nitrification process. There are two divergent clades of comammox Nitrospira, Clade A and B. However, their population abundance, community structure and role in ammonia and nitrite oxidation are poorly understood. We conducted a 94-day microcosm study using a grazed dairy pasture soil amended with urea fertilizers, synthetic cow urine, and the nitrification inhibitor, dicyandiamide (DCD), to investigate the growth and community structure of comammox Nitrospira spp. We discovered that comammox Nitrospira Clade B was two orders of magnitude more abundant than Clade A in this fertile dairy pasture soil and the most abundant subcluster was a distinctive phylogenetic uncultured subcluster Clade B2. We found that comammox Nitrospira Clade B might not play a major role in nitrite oxidation compared to the role of canonical Nitrospira nitrite-oxidizers, however, comammox Nitrospira Clade B is active in nitrification and the growth of comammox Nitrospira Clade B was inhibited by a high ammonium concentration (700 kg synthetic urine-N ha-1) and the nitrification inhibitor DCD. We concluded that comammox Nitrospira Clade B: (1) was the most abundant comammox in the dairy pasture soil; (2) had a low tolerance to ammonium and can be inhibited by DCD; and (3) was not the dominant nitrite-oxidizer in the soil. This is the first study discovering a new subcluster of comammox Nitrospira Clade B2 from an agricultural soil.

Screening and Analysis of Serum Protein Biomarkers Infected by Coronavirus Disease 2019 (COVID-19).

Coronavirus disease 2019 (COVID-19) has spread widely around the world, and in-depth research on COVID-19 is necessary for biomarkers and target drug discovery. This analysis collected serum from six COVID-19-infected patients and six healthy people. The protein changes in the infected and healthy control serum samples were evaluated by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and high-performance liquid chromatography (HPLC). The differential protein signature in both groups was retrieved and analyzed by the Kyoto Encyclopedia of Gene and Genomes (KEGG), Gene ontology, COG/KOG, protein-protein interaction, and protein domain interactions tools. We shortlisted 24 differentially expressed proteins between both groups. Ten genes were significantly up-regulated in the infection group, and fourteen genes were significantly down-regulated. The GO and KEGG pathway enrichment analysis suggested that the chromosomal part and chromosome were the most enriched items. The oxytocin signaling pathway was the most enriched item of KEGG analysis. The netrin module (non-TIMP type) was the most enriched protein domain in this study. Functional analysis of S100A9, PIGR, C4B, IL-6R, IGLV3-19, IGLV3-1, and IGLV5-45 revealed that SARS-CoV-2 was closely related to immune response.

Age-Stage, Two-Sex Life Table and Functional Response of Amblyseius orientalis (Acari: Phytoseiidae) Feeding on Different Nutrient Sources.

Amblyseius orientalis Ehara is a predatory mite that belongs to the family Phytoseiidae. It is mainly found in Jiangxi, Shanghai, Guangdong, and other areas of China. Although A. orientalis is a dominant predatory mite species in China and is also important for agriculture and biological control, not many studies have investigated it. Thus, research on A. orientalis is necessary. However, its application in biological control is hindered by the absence of techniques for the mass rearing of A. orientalis in captivity. We conducted experiments to determine the growth, development, reproduction, and functional response of A. orientalis in this study by indoor single-head rearing at 25 ± 1 °C, 65 ± 5% relative humidity, and a photoperiod of a 16 h:8 h light/dark cycle under laboratory conditions. The results of the age stage, two-sex life table showed that the individuals in the pollen + yeast and pollen + yeast + sucrose groups had significantly higher oviposition period, fecundity, net reproductive rate (R0), and gross reproduction rate (GRR) than those in the pollen group. The results of the function response showed that the pollen + yeast + sucrose group was the most favorable for captive breeding of A. orientalis and had the best predatory ability along with rejuvenation and recovery ability. The results of the study provided a theoretical basis for indoor rearing, propagation, and utilization of A. orientalis.

Fucosylated Chondroitin Sulfate against Parkinson's Disease through Inhibiting Inflammation Induced by Gut Dysbiosis.

Growing evidence for the importance of the gut-brain axis in Parkinson's disease (PD) has attracted researchers' interest in the possible application of microbiota-based treatment approaches. Using a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model, we looked into the prospect of treating PD with fucosylated chondroitin sulfate obtained from sea cucumbers Isostichopus badionotus (fCS-Ib). We showed that giving fCS-Ib polysaccharide orally greatly reduced the motor deficits, dopamine depletion, and alpha-synuclein increase caused by MPTP in the substantia nigra (SN). It appears that the anti-PD action of fCS-Ib polysaccharide could be attained by squelching inflammation. Glial cell hyperactivation in SN and overproduction of proinflammatory substances in serum could both be suppressed by fCS-Ib polysaccharide injection. The bacterial DNA in fresh colonic feces was submitted to 16S rRNA and untargeted metabolic analyses to confirm the participation of the microbiota-gut-brain axis in the aforementioned interpretation. The findings showed that the MPTP treatment-induced decrease in norank_f_Muribaculaceae and the increase in Staphylococcus were reversed by the administration of fCS-Ib polysaccharide. The NF-κB signaling pathway was shown to be involved in the fCS-Ib polysaccharide-induced anti-inflammation. In conclusion, our research demonstrated for the first time how fCS-Ib polysaccharide combats PD by reducing inflammation caused by gut microbial dysbiosis.

Complete mitochondrial genome of the top hat blenny, Omobranchus fasciolatoceps Richardson (Blenniiformes: Blenniinae) in Southern China Coast.

The complete mitochondrial genome sequence of Omobranchus fasciolatoceps was firstly described in this article. The total length of mitogenome was 16,569 bp. It contains 13 protein-coding genes, 22 tRNA genes, and two ribosomal RNA genes. The overall base composition of H-strand was 29.04% A, 27.14% C, 27.89% T, and 15.93% G, with an A＋T bias of 56.93%. The phylogenetic analysis results showed that the O. fasciolatoceps was most closely related to O. elegans.