Causal role of immune cells in Hashimoto's thyroiditis: Mendelian randomization study.

Objectives: Hashimoto's thyroiditis (HT) is a common autoimmune disease whose etiology involves a complex interplay between genetics and environment. Previous studies have demonstrated an association between immune cells and HT. However, the casual relationship was not clear. We aimed to explore the causal associations between signatures of immune cells and HT. Methods: In this study, bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the potential causal relationship between 731 immune cell signatures and HT by using genome-wide association study (GWAS) data. Heterogeneity and horizontal pleiotropy were detected through extensive sensitivity analyses. Results: The increased levels of six immune phenotypes were observed to be causally associated with increased risk of HT P < 0.01, which were CD3 on CM CD8br, CD3 on CD39+ secreting Treg, HLA DR on CD33dim HLA DR+ CD11b-, CD3 on CD4 Treg, CD62L- plasmacytoid DC %DC, and CD3 on CD45RA+ CD4+. In addition, the levels of FSC-A on HLA DR+ T cell and CD62L on monocyte were associated with disease risk of HT P < 0.01. In addition, HT also had causal effects on CD3 on CM CD8br, CCR2 on monocyte, CD25 on CD39+ resting Treg, and CCR2 on CD62L+ myeloid DC P < 0.05. Conclusions: In this study, we demonstrated the genetic connection between immune cell traits and HT, thereby providing guidance and direction for future treatment and clinical research.

Nomogram for Risk of Secondary Venous Thromboembolism in Stroke Patients: A Study Based on the MIMIC-IV Database.

This study aims to identify risk factors for secondary venous thromboembolism (VTE) in stroke patients and establish a nomogram, an accurate predictor of probability of VTE occurrence during hospitalization in stroke patients. Medical Information Mart for Intensive Care IV (MIMIC-IV) database of critical care medicine was utilized to retrieve information of stroke patients admitted to the hospital between 2008 and 2019. Patients were randomly allocated into train set and test set at 7:3. Univariate and multivariate logistic regression analyses were used to identify independent risk factors for secondary VTE in stroke patients. A predictive nomogram model was constructed, and the predictive ability of the nomogram was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). This study included 266 stroke patients, with 26 patients suffering secondary VTE after stroke. A nomogram for predicting risk of secondary VTE in stroke patients was built according to pulmonary infection, partial thromboplastin time (PTT), log-formed D-dimer, and mean corpuscular hemoglobin (MCH). Area under the curve (AUC) of the predictive model nomogram was 0.880 and 0.878 in the train and test sets, respectively. The calibration curve was near the diagonal, and DCA curve presented positive net benefit. This indicates the model's good predictive performance and clinical utility. The nomogram effectively predicts the risk probability of secondary VTE in stroke patients, aiding clinicians in early identification and personalized treatment of stroke patients at risk of developing secondary VTE.

Petroleum ether extract of Schisandra sphenanthera prevents hyperglycemia and insulin resistance in association with modulation of sweet taste receptors and gut microbiota in T2DM rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Schisandra sphenanthera (Schisandra sphenanthera Rehd. et Wils.) is the dried mature fruit of Schisandra sphenanthera, a plant in the Magnoliaceae family. It was used in the treatment of diabetes mellitus in the Jade Fluid Decoction and the Xiaoke pills, which were recorded in ancient books. However, its mechanism of action in the treatment of type 2 diabetes mellitus (T2DM) was unclear and needs further study. AIM OF THE STUDY: This research aimed to investigate the chemical composition and lignan content of Schisandra sphenanthera petroleum ether parts (SPEP) and to evaluate the effects of SPEP on sweet taste receptors (STRs) and intestinal flora in rats on a high-fat diet (HFD). Additionally, the relationships between SPEP and hyperglycemia and insulin resistance were examined. MATERIALS AND METHODS: GC-MS was used to determine the chemical composition of SPEP, and HPLC was used to determine the lignin content. A combination of the HFD and the administration of streptozotocin (STZ) was employed to generate a rat model of T2DM. Petroleum ether extracts from Schisandra sphenanthera were used as the focus of the research to evaluate the effects of these extracts on the glucolipid metabolism of T2DM rats, as well as the underlying mechanisms. RESULTS: Analysis of the GC-MS spectrum of SESP revealed a total of 58 compounds. HPLC analysis revealed that SPEP had the highest concentration of Schisandrin A and the lowest concentration of Schisandrol A. The drug administration intervention resulted in a significant decrease in body weight and pancreatic weight of diabetic rats compared to the Normal group. When compared to the Model group, the body weight of rats in the drug administration group and the Metformin group had a more moderate decrease, while the pancreatic weight and pancreatic-to-body ratio increased. The Model group shown significant increases in FBG, OGTT, GHb, TC, TG, LDL-C, ALT, AST, MDA, FINS, and NEFA, as well as significant decreases in HDL-C and SOD, when compared to the Normal group (P < 0.05). The administration of each group was found to be significantly effective in decreasing FBG, OGTT, GHb, TC, TG, LDL-C, ALT, AST, MDA, FINS, NEFA, while increasing HDL-C and SOD when compared to the Model group. The application of SPEP had a positive impact on hepatocyte swelling, hepatocyte degeneration, and necrosis, as well as the morphological structure of pancreatic islet cells. Furthermore, the protein expression levels of T1R2, TRPM5 and GLP-1 in the small intestine of the Model group were reduced. After a period of six weeks, the protein expression levels began to align more closely with those of the Normal group of rats. Analysis of 16S rRNA sequencing revealed that the intestinal microbiota of diabetic rats was significantly disrupted, with a decrease in the abundance of the Firmicutes phylum and an increase in the abundance of the Bacteroidetes phylum. Furthermore, the composition of the dominant genus was distinct from that of the control group. After the drug intervention, the microbiota of diabetic rats was significantly altered, exhibiting a higher abundance and diversity, as well as a significant enrichment of the community. The SPEP treatment resulted in a significant increase in acetic acid, propionic acid, and butyric acid. CONCLUSIONS: The findings of this research indicated that SPEP could be effective in treating T2DM through the regulation of STRs, the adjustment of disturbed metabolite levels, and the alteration of intestinal flora.

A novel model combining genes associated with disulfidptosis and glycolysis to predict breast cancer prognosis, molecular subtypes, and treatment response.

Breast cancer (BC) is a heterogeneous malignancy with a dismal prognosis. Disulfidptosis is a novel type of regulated cell death that happens in the presence of glucose deficiency and is linked to the metabolic process of glycolysis. However, the mechanism of action of disulfidptosis and glycolysis-related genes (DGRG) in BC, as well as their prognostic value in BC patients, remain unknown. After identifying the differentially expressed DGRG in normal and BC tissues, a number of machine learning algorithms were utilized to select essential prognostic genes to develop a model, including SLC7A11, CACNA1H, SDC1, CHST1, and TFF3. The expression characteristics of these genes were then examined using single-cell RNA sequencing, and BC was classified into three clusters using "ConsensusClusterPlus" based on these genes. The DGRG model's median risk score can categorize BC patients into high-risk and low-risk groups. Furthermore, we investigated variations in clinical landscape, immunoinvasion analysis, tumor immune dysfunction and rejection (TIDE), and medication sensitivity in patients in the DGRG model's high- and low-risk groups. Patients in the low-risk group performed better on immunological and chemotherapeutic therapies and had lower TIDE scores. In conclusion, the DGRG model we developed has significant clinical application potential because it can accurately predict the prognosis of BC, TME, and pharmacological treatment responses.

Thyroid function and polycystic ovary syndrome: a Mendelian randomization study.

Background: Multiple evidence suggests that thyroid function is associated with polycystic ovary syndrome (PCOS), but whether thyroid function is causally related to PCOS is unclear. To investigate whether the association reflect causality, a Mendelian randomization (MR) analysis was conducted. Methods: Single nucleotide polymorphisms (SNPs) involved in this study were acquired from The ThyroidOmics Consortium and the IEU Open Genome-wide association study (GWAS) database, respectively. In forward MR analysis, we included normal free thyroxine (FT4, n=49,269), normal thyroid-stimulating hormone (TSH, n=54,288), hypothyroidism (n=53,423) and hyperthyroidism (n=51,823) as exposure. The outcome was defined as PCOS in a sample size of 16,380,318 individuals. The exposure in the reverse MR analyses was chosen as PCOS, while the outcome consisted of the four phenotypes of thyroid function. The inverse-variance weighted (IVW) method was performed as the major analysis, supplemented by sensitivity analyses. Results: The occurrence of PCOS was associated with increased risk of hyperthyroidism (IVW, OR=1.08, 95%CI=1.02-1.13, P=0.004). No evidence suggested that other phenotypes of thyroid function were related to PCOS. Conclusions: Our findings demonstrate a cause-and-effect connection between PCOS and hyperthyroidism. The study established foundation for further investigation for interaction between thyroid function and PCOS.

Metal organic framework-derived CuO/Cu2O polyhedron-CdS quantum dots double Z-scheme heterostructure for cathodic photoelectrochemical detection of Hg2+ in food and environment.

This study employed an innovative copper oxide/cuprous oxide (CuO/Cu2O) polyhedron­cadmium sulphide quantum dots (CdS QDs) double Z-scheme heterostructure as a matrix for the cathodic PEC determination of mercury ions (Hg2+). First, the CuO/Cu2O polyhedral composite was prepared by calcining a copper-based metal organic framework (Cu-MOF). Subsequently, the amino-modified CuO/Cu2O was integrated with mercaptopropionic acid (MPA)-capped CdS QDs to form a CuO/Cu2O polyhedron-CdS QDs double Z-scheme heterostructure, producing a strong cathodic photocurrent. Importantly, this heterostructure exhibited a specifically reduced photocurrent for Hg2+ when using CdS QDs as Hg2+-recognition probe. This was attributed to the extreme destruction of the double Z-scheme heterostructure and the in situ formation of the CuO/Cu2O-CdS/HgS heterostructure. Besides, p-type HgS competed with the matrix for electron acceptors, further decreasing the photocurrent. Consequently, Hg2+ was sensitively assayed, with a low detection limit (0.11 pM). The as-prepared PEC sensor was also used to analyse Hg2+ in food and the environment.

Optimization of fermentation conditions and medium components for chrysomycin a production by Streptomyces sp. 891-B6.

BACKGROUND: Chrysomycin A (CA) is a promising antibiotic for treatment of Gram-positive bacterial infections and cancers. In order to enhance CA yield, optimization of fermentation conditions and medium components was carried out on strain Streptomyces sp. 891-B6, an UV-induced mutant with improved CA titer compared with its wide-type marine strain 891. RESULTS: Using one-way experiment, the optimal fermentation conditions for CA production in 1-L shake flask were obtained as follows: 12 days of fermentation time, 5 days of seed age, 5% of inoculum volume ratio, 200 mL of loading volume and 6.5 of initial pH. By response surface methodology, the optimal medium components determined as glucose (39.283 g/L), corn starch (20.662 g/L), soybean meal (15.480 g/L) and CaCO3 (2.000 g/L). CONCLUSION: Validation tests showed that the maximum yield of CA reached 1601.9 ± 56.7 mg/L, which was a 60% increase compared to the initial yield (952.3 ± 53.2 mg/L). These results provided an important basis for scale-up production of CA by strain 891-B6.

Medium-sized peptides from microbial sources with potential for antibacterial drug development.

Covering: 1993 to the end of 2022As the rapid development of antibiotic resistance shrinks the number of clinically available antibiotics, there is an urgent need for novel options to fill the existing antibiotic pipeline. In recent years, antimicrobial peptides have attracted increased interest due to their impressive broad-spectrum antimicrobial activity and low probability of antibiotic resistance. However, macromolecular antimicrobial peptides of plant and animal origin face obstacles in antibiotic development because of their extremely short elimination half-life and poor chemical stability. Herein, we focus on medium-sized antibacterial peptides (MAPs) of microbial origin with molecular weights below 2000 Da. The low molecular weight is not sufficient to form complex protein conformations and is also associated to a better chemical stability and easier modifications. Microbially-produced peptides are often composed of a variety of non-protein amino acids and terminal modifications, which contribute to improving the elimination half-life of compounds. Therefore, MAPs have great potential for drug discovery and are likely to become key players in the development of next-generation antibiotics. In this review, we provide a detailed exploration of the modes of action demonstrated by 45 MAPs and offer a concise summary of the structure-activity relationships observed in these MAPs.

Causal effect between gut microbiota and gastroesophageal reflux disease: a bidirectional two-sample Mendelian randomization study.

Previous observational studies have found that the gut microbiota is closely related to the pathogenesis of gastroesophageal reflux disease (GERD), while their causal relationship is unclear. A two-sample multivariate Mendelian randomization analysis was implemented to estimate the causal effect of gut microbiota on GERD. The gut microbiota aggregated statistics were derived from a meta-analysis of the largest available genome-wide association studies (GWAS) conducted by the MiBioGen alliance (n = 13 266). GERD aggregated statistics were derived from published GWAS (129 080 cases and 473 524 controls). A bidirectional two-sample Mendelian randomization study was conducted to explore the causal relationship between gut microbiota and GERD using the inverse variance weighted (IVW), Mendelian randomization Egger, single model, weighted median, and weighted model. To verify the stability of the main results of Mendelian randomization analysis, we performed sensitivity analysis. Based on the results of IVW, we found that Anaerostipes was causally associated with an increased risk of GERD [odds ratio (OR): 1.09, P = 0.018]. Eight gut microbiota taxa (Actinobacteria, Bifidobacteriales, Bifidobacteriaceae, Clostridiales vadin BB60 group, Rikenellaceae, Lachnospiraceae UCG004, Methanobrevibacter, and unknown genus id.1000000073) are predicted to act causally in suppressing the risk of GERD (P < 0.05). In addition, reverse Mendelian randomization analyses revealed that the abundance of 15 gut microbiota taxon was found to be affected by GERD. No significant estimation of heterogeneity or pleiotropy is detected. Our study presents a complicated causal relationship between gut microbiota and GERD that offers guidance on the selection of appropriate probiotics as clinical interventions for GERD.

Research Progress on the Combination of Quorum-Sensing Inhibitors and Antibiotics against Bacterial Resistance.

Bacterial virulence factors and biofilm development can be controlled by the quorum-sensing (QS) system, which is also intimately linked to antibiotic resistance in bacteria. In previous studies, many researchers found that quorum-sensing inhibitors (QSIs) can affect the development of bacterial biofilms and prevent the synthesis of many virulence factors. However, QSIs alone have a limited ability to suppress bacteria. Fortunately, when QSIs are combined with antibiotics, they have a better therapeutic effect, and it has even been demonstrated that the two together have a synergistic antibacterial effect, which not only ensures bactericidal efficiency but also avoids the resistance caused by excessive use of antibiotics. In addition, some progress has been made through in vivo studies on the combination of QSIs and antibiotics. This article mainly expounds on the specific effect of QSIs combined with antibiotics on bacteria and the combined antibacterial mechanism of some QSIs and antibiotics. These studies will provide new strategies and means for the clinical treatment of bacterial infections in the future.

Transcriptional regulators of secondary metabolite biosynthesis in Streptomyces.

In the post-genome era, great progress has been made in metabolic engineering using recombinant DNA technology to enhance the production of high-value products by Streptomyces. With the development of microbial genome sequencing techniques and bioinformatic tools, a growing number of secondary metabolite (SM) biosynthetic gene clusters in Streptomyces and their biosynthetic logics have been uncovered and elucidated. In order to increase our knowledge about transcriptional regulators in SM of Streptomyces, this review firstly makes a comprehensive summary of the characterized factors involved in enhancing SM production and awakening SM biosynthesis. Future perspectives on transcriptional regulator engineering for new SM biosynthesis by Streptomyces are also provided.

The causal impact of gut microbiota on circulating adipokine concentrations: a two-sample Mendelian randomization study.

PURPOSE: Evidence from previous experimental and observational research demonstrates that the gut microbiota is related to circulating adipokine concentrations. Nevertheless, the debate as to whether gut microbiome composition causally influences circulating adipokine concentrations remains unresolved. This study aimed to take an essential step in elucidating this issue. METHODS: We used two-sample Mendelian randomization (MR) to causally analyze genetic variation statistics for gut microbiota and four adipokines (including adiponectin, leptin, soluble leptin receptor [sOB-R], and plasminogen activator inhibitor-1 [PAI-1]) from large-scale genome-wide association studies (GWAS) datasets. A range of sensitivity analyses was also conducted to assess the stability and reliability of the results. RESULTS: The composite results of the MR and sensitivity analyses revealed 22 significant causal associations. In particular, there is a suggestive causality between the family Clostridiaceae1 (IVW: ß = 0.063, P = 0.034), the genus Butyrivibrio (IVW: ß = 0.029, P = 0.031), and the family Alcaligenaceae (IVW: ß=-0.070, P = 0.014) and adiponectin. Stronger causal effects with leptin were found for the genus Enterorhabdus (IVW: ß=-0.073, P = 0.038) and the genus Lachnospiraceae (NK4A136 group) (IVW: ß=-0.076, P = 0.01). Eight candidate bacterial groups were found to be associated with sOB-R, with the phylum Firmicutes (IVW: ß = 0.235, P = 0.03) and the order Clostridiales (IVW: ß = 0.267, P = 0.028) being of more interest. In addition, the genus Roseburia (IVW: ß = 0.953, P = 0.022) and the order Lactobacillales (IVW: ß=-0.806, P = 0.042) were suggestive of an association with PAI-1. CONCLUSION: This study reveals a causal relationship between the gut microbiota and circulating adipokines and may help to offer novel insights into the prevention of abnormal concentrations of circulating adipokines and obesity-related diseases.

Dynamic Metabolons Using Stimuli-Responsive Protein Cages.

Naturally evolved metabolons have the ability to assemble and disassemble in response to environmental stimuli, allowing for the rapid reorganization of chemical reactions in living cells to meet changing cellular needs. However, replicating such capability in synthetic metabolons remains a challenge due to our limited understanding of the mechanisms by which the assembly and disassembly of such naturally occurring multienzyme complexes are controlled. Here, we report the synthesis of chemical- and light-responsive protein cages for assembling synthetic metabolons, enabling the dynamic regulation of enzymatic reactions in living cells. Particularly, a chemically responsive domain was fused to a self-assembled protein cage subunit, generating engineered protein cages capable of displaying proteins containing cognate interaction domains on their surfaces in response to small molecular cues. Chemical-induced colocalization of sequential enzymes on protein cages enhances the specificity of the branched deoxyviolacein biosynthetic reactions by 2.6-fold. Further, by replacing the chemical-inducible domain with a light-inducible dimerization domain, we created an optogenetic protein cage capable of reversibly recruiting and releasing targeted proteins onto and from the exterior of the protein cages in tens of seconds by on-off of blue light. Tethering the optogenetic protein cages to membranes enables the formation of light-switchable, membrane-bound metabolons, which can repeatably recruit-release enzymes, leading to the manipulation of substrate utilization across membranes on demand. Our work demonstrates a powerful and versatile strategy for constructing dynamic metabolons in engineered living cells for efficient and controllable biocatalysis.

Non-ribosomal peptide synthetase (NRPS)-encoding products and their biosynthetic logics in Fusarium.

Fungal non-ribosomal peptide synthetase (NRPS)-encoding products play a paramount role in new drug discovery. Fusarium, one of the most common filamentous fungi, is well-known for its biosynthetic potential of NRPS-type compounds with diverse structural motifs and various biological properties. With the continuous improvement and extensive application of bioinformatic tools (e.g., anti-SMASH, NCBI, UniProt), more and more biosynthetic gene clusters (BGCs) of secondary metabolites (SMs) have been identified in Fusarium strains. However, the biosynthetic logics of these SMs have not yet been well investigated till now. With the aim to increase our knowledge of the biosynthetic logics of NPRS-encoding products in Fusarium, this review firstly provides an overview of research advances in elucidating their biosynthetic pathways.

Phage Display Screening of Anchor Peptides for Red Blood Cell-Derived Extracellular Vesicles.

Extracellular vesicles (EVs) are increasingly used for disease diagnosis and treatment. Among them, red blood cell-derived EVs (RBC-EVs) have attracted great attention due to their abundant sources and low risks of gene transfer (RBC-EVs lack nuclear and mitochondrial DNA). Here, we first revealed the high expression level of membrane protein solute carrier family 4 member 1 (SLC4A1) in RBC-EVs through proteomic analysis. We then identified several binding peptides with high affinity for the SLC4A1 extracellular domain (SLC4A1-EC) from phage display library screening. A high affinity of SLC4A1-EC and the three peptides (XRB2, XRE4, and XRH7) were assessed in vitro using surface plasmon resonance analysis and SDS-polyacrylamide gel electrophoresis (SDS-PAGE). The binding sites of SLC4A1-EC and polypeptides were further predicted by LigPlot + analysis, and the results showed that these three polypeptides could bind to part of the hydrophobic residues of SLC4A1-EC. The binding efficiency of the anchor peptides to the RBC-EVs was further verified by flow cytometry and fluorescence imaging. In conclusion, we successfully screened three specific RBC-EV-targeting peptides which could potentially be utilized for isolating RBC-derived EVs from serum samples. More importantly, this peptide could be coupled with targeting peptides to modify RBC-EVs for drug delivery. Our work will provide a viable method for optimizing the function of RBC-EVs.

Genus Helleborus: a comprehensive review of phytochemistry, pharmacology and clinical applications.

The genus Helleborus belongs to the Ranunculaceae family, distributed in southeastern Europe and western Asia. In folk medicine, it is commonly used as an anti-inflammatory and analgesic medicine for rheumatoid arthritis and bruises. Through reviewing recent articles, it was found that two hundred and twenty-six compounds have been isolated and identified from the genus Helleborus. These compounds include steroids, flavonoids, phenylpropanoids, lignans, anthraquinones, phenolics and others. Among them, the main chemical constituents are steroids. Pharmacological studies show Helleborus has anti-cancer, immunomodulatory, anti-inflammatory, analgesic, anti-hyperglycaemic, antioxidant and antibacterial properties. This article reviews the botany, phytochemistry, pharmacological effects and clinical applications of the genus Helleborus. Hopefully, it will provide a reference for in-depth research and exploitation of the genus Helleborus.

Disrupted small-world white matter networks in patients with major depression and recent suicide plans or attempts.

Suicide is a major concern for health, and depression is an established proximal risk factor for suicide. This study aimed to investigate white matter features associated with suicide. We constructed white matter structural networks by deterministic tractography via diffusion tensor imaging in 51 healthy controls, 47 depressed patients without suicide plans or attempts and 56 depressed patients with suicide plans or attempts. Then, graph theory analysis was used to measure global and nodal network properties. We found that local efficiency was decreased and path length was increased in suicidal depressed patients compared to healthy controls and non-suicidal depressed patients; moreover, the clustering coefficient was decreased in depressed patients compared to healthy controls; and the global efficiency and normalized characteristic path length was increased in suicidal depressed patients compared to healthy controls. Similarly, compared with those in non-suicidal depressed patients, nodal efficiency in the thalamus, caudate, medial orbitofrontal cortex, hippocampus, olfactory cortex, supplementary motor area and Rolandic operculum was decreased. In summary, compared with those of non-suicidal depressed patients, the structural connectome of suicidal depressed patients exhibited weakened integration and segregation and decreased nodal efficiency in the fronto-limbic-basal ganglia-thalamic circuitry. These alterations in the structural networks of depressed suicidal brains provide insights into the underlying neurobiology of brain features associated with suicide.

Molecular basis for curvature formation in SepF polymerization.

The self-assembly of proteins into curved structures plays an important role in many cellular processes. One good example of this phenomenon is observed in the septum-forming protein (SepF), which forms polymerized structures with uniform curvatures. SepF is essential for regulating the thickness of the septum during bacteria cell division. In Bacillus subtilis, SepF polymerization involves two distinct interfaces, the ß-ß and α-α interfaces, which define the assembly unit and contact interfaces, respectively. However, the mechanism of curvature formation in this step is not yet fully understood. In this study, we employed solid-state NMR (SSNMR) to compare the structures of cyclic wild-type SepF assemblies with linear assemblies resulting from a mutation of G137 on the ß-ß interface. Our results demonstrate that while the sequence differences arise from the internal assembly unit, the dramatic changes in the shape of the assemblies depend on the α-α interface between the units. We further provide atomic-level insights into how the angular variation of the α2 helix on the α-α interface affects the curvature of the assemblies, using a combination of SSNMR, cryo-electron microscopy, and simulation methods. Our findings shed light on the shape control of protein assemblies and emphasize the importance of interhelical contacts in retaining curvature.

Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder.

BACKGROUND: Although brain structural covariance network (SCN) abnormalities have been associated with suicidal thoughts and behaviors (STBs) in individuals with major depressive disorder (MDD), previous studies have reported inconsistent findings based on small sample sizes, and underlying transcriptional patterns remain poorly understood. METHODS: Using a multicenter magnetic resonance imaging dataset including 218 MDD patients with STBs, 230 MDD patients without STBs, and 263 healthy control participants, we established individualized SCNs based on regional morphometric measures and assessed network topological metrics using graph theoretical analysis. Machine learning methods were applied to explore and compare the diagnostic value of morphometric and topological features in identifying MDD and STBs at the individual level. Brainwide relationships between STBs-related connectomic alterations and gene expression were examined using partial least squares regression. RESULTS: Group comparisons revealed that SCN topological deficits associated with STBs were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STBs. Topological features made a greater contribution to distinguishing between patients with and without STBs. STBs-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling. CONCLUSIONS: These findings revealed robust brain structural deficits at the network level, highlighting the importance of SCN topological measures in characterizing individual suicidality and demonstrating its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.

Marine Streptomyces-Derived Novel Alkaloids Discovered in the Past Decade.

Natural alkaloids originating from actinomycetes and synthetic derivatives have always been among the important suppliers of small-molecule drugs. Among their biological sources, Streptomyces is the highest and most extensively researched genus. Marine-derived Streptomyces strains harbor unconventional metabolic pathways and have been demonstrated to be efficient producers of biologically active alkaloids; more than 60% of these compounds exhibit valuable activity such as antibacterial, antitumor, anti-inflammatory activities. This review comprehensively summarizes novel alkaloids produced by marine Streptomyces discovered in the past decade, focusing on their structural features, biological activity, and pharmacological mechanisms. Future perspectives on the discovery and development of novel alkaloids from marine Streptomyces are also provided.