Utilize proteomic analysis to identify potential therapeutic targets for combating sepsis and sepsis-related death.

Background: Sepsis is an inflammatory disease that leads to severe mortality, highlighting the urgent need to identify new therapeutic strategies for sepsis. Proteomic research serves as a primary source for drug target identification. We employed proteome-wide Mendelian randomization (MR), genetic correlation analysis, and colocalization analysis to identify potential targets for sepsis and sepsis-related death. Methods: Genetic data for plasma proteomics were obtained from 35,559 Icelandic individuals and an initial MR analysis was conducted using 13,531 sepsis cases from the FinnGen R10 cohort to identify associations between plasma proteins and sepsis. Subsequently, significant proteins underwent genetic correlation analysis, followed by replication in 54,306 participants from the UK Biobank Pharma Proteomics Project and validation in 11,643 sepsis cases from the UK Biobank. The identified proteins were then subjected to colocalization analysis, enrichment analysis, and protein-protein interaction network analysis. Additionally, we also investigated a MR analysis using plasma proteins on 1,896 sepsis cases with 28-day mortality from the UK Biobank. Results: After FDR correction, MR analysis results showed a significant causal relationship between 113 plasma proteins and sepsis. Genetic correlation analysis revealed that only 8 proteins had genetic correlations with sepsis. In the UKB-PPP replication analysis, only 4 proteins were found to be closely associated with sepsis, while validation in the UK Biobank sepsis cases found overlaps for 21 proteins. In total, 30 proteins were identified in the aforementioned analyses, and colocalization analysis revealed that only 2 of these proteins were closely associated with sepsis. Additionally, in the 28-day mortality MR analysis of sepsis, we also found that only 2 proteins were significant. Conclusions: The identified plasma proteins and their associated metabolic pathways have enhanced our understanding of the complex relationship between proteins and sepsis. This provides new avenues for the development of drug targets and paves the way for further research in this field.

Advances in Nanotherapy for Targeting Senescent Cells.

Aging is an inevitable process in the human body, and cellular senescence refers to irreversible cell cycle arrest caused by external aging-promoting mechanisms. Moreover, as age increases, the accumulation of senescent cells limits both the health of the body and lifespan and even accelerates the occurrence and progression of age-related diseases. Therefore, it is crucial to delay the periodic irreversible arrest and continuous accumulation of senescent cells to address the issue of aging. The fundamental solution is targeted therapy focused on eliminating senescent cells or reducing the senescence-associated secretory phenotype. Over the past few decades, the remarkable development of nanomaterials has revolutionized clinical drug delivery pathways. Their unique optical, magnetic, and electrical properties effectively compensate for the shortcomings of traditional drugs, such as low stability and short half-life, thereby maximizing the bioavailability and minimizing the toxicity of drug delivery. This article provides an overview of how nanomedicine systems control drug release and achieve effective diagnosis. By presenting and analyzing recent advances in nanotherapy for targeting senescent cells, the underlying mechanisms of nanomedicine for senolytic and senomorphic therapy are clarified, providing great potential for targeting senescent cells.

Shared genetic correlations between kidney diseases and sepsis.

Background: Clinical studies have indicated a comorbidity between sepsis and kidney diseases. Individuals with specific mutations that predispose them to kidney conditions are also at an elevated risk for developing sepsis, and vice versa. This suggests a potential shared genetic etiology that has not been fully elucidated. Methods: Summary statistics data on exposure and outcomes were obtained from genome-wide association meta-analysis studies. We utilized these data to assess genetic correlations, employing a pleiotropy analysis method under the composite null hypothesis to identify pleiotropic loci. After mapping the loci to their corresponding genes, we conducted pathway analysis using Generalized Gene-Set Analysis of GWAS Data (MAGMA). Additionally, we utilized MAGMA gene-test and eQTL information (whole blood tissue) for further determination of gene involvement. Further investigation involved stratified LD score regression, using diverse immune cell data, to study the enrichment of SNP heritability in kidney-related diseases and sepsis. Furthermore, we employed Mendelian Randomization (MR) analysis to investigate the causality between kidney diseases and sepsis. Results: In our genetic correlation analysis, we identified significant correlations among BUN, creatinine, UACR, serum urate, kidney stones, and sepsis. The PLACO analysis method identified 24 pleiotropic loci, pinpointing a total of 28 nearby genes. MAGMA gene-set enrichment analysis revealed a total of 50 pathways, and tissue-specific analysis indicated significant enrichment of five pairs of pleiotropic results in kidney tissue. MAGMA gene test and eQTL information (whole blood tissue) identified 33 and 76 pleiotropic genes, respectively. Notably, genes PPP2R3A for BUN, VAMP8 for UACR, DOCK7 for creatinine, and HIBADH for kidney stones were identified as shared risk genes by all three methods. In a series of immune cell-type-specific enrichment analyses of pleiotropy, we identified a total of 37 immune cells. However, MR analysis did not reveal any causal relationships among them. Conclusions: This study lays the groundwork for shared etiological factors between kidney and sepsis. The confirmed pleiotropic loci, shared pathogenic genes, and enriched pathways and immune cells have enhanced our understanding of the multifaceted relationships among these diseases. This provides insights for early disease intervention and effective treatment, paving the way for further research in this field.

Discrete Illumination-Based Compressed Ultrafast Photography for High-Fidelity Dynamic Imaging.

Compressed ultrafast photography (CUP) can capture irreversible or difficult-to-repeat dynamic scenes at the imaging speed of more than one billion frames per second, which is obtained by compressive sensing-based image reconstruction from a compressed 2D image through the discretization of detector pixels. However, an excessively high data compression ratio in CUP severely degrades the image reconstruction quality, thereby restricting its ability to observe ultrafast dynamic scenes with complex spatial structures. To address this issue, a discrete illumination-based CUP (DI-CUP) with high fidelity is reported. In DI-CUP, the dynamic scenes are loaded into an ultrashort laser pulse train with controllable sub-pulse number and time interval, thus the data compression ratio, as well as the overlap between adjacent frames, is greatly decreased and flexibly controlled through the discretization of dynamic scenes based on laser pulse train illumination, and high-fidelity image reconstruction can be realized within the same observation time window. Furthermore, the superior performance of DI-CUP is verified by observing femtosecond laser-induced ablation dynamics and plasma channel evolution, which are hardly resolved in the spatial structures using conventional CUP. It is anticipated that DI-CUP will be widely and dependably used in the real-time observations of various ultrafast dynamics.

One-Dimensional Copper-Doped Rb2AgI3 with Efficient Sky-Blue Emission as a High-Performance X-ray Scintillator.

Scintillators have garnered heightened attention for their diverse applications in medical imaging and security inspection. Nonetheless, commercial scintillators encounter challenges with costly rare-earth metals and toxic elements like thallium (Tl), driving the need for sustainable, cost-effective, and eco-friendly alternatives to meet contemporary X-ray detection demands. This study focuses on exploring the potential of Cu+-doped Rb2AgI3 as an effective metal halide (MH) scintillator. One-dimensional (1D) Rb2AgI3 and Cu+-doped Rb2AgI3 single crystals (SCs) were synthesized by using the conventional temperature-lowering crystallization method. When excited by UV light, Cu+-doped SCs emitted a broad sky-blue light at 490 nm with a high photoluminescence (PL) quantum yield (PLQY) of 76.48%. Remarkably, under X-ray excitation, these Cu+-doped SCs demonstrated an outstanding light yield of 36,293 photons MeV-1, a relatively low detection threshold of 1.022 µGyair s-1, and a rapid scintillation decay time of 465 ns. The prepared translucent scintillation film has good uniformity and flexibility, with a high spatial resolution of 10.2 lp mm-1. These results position Cu+-doped Rb2AgI3 as a leading candidate among promising X-ray scintillators, offering superior scintillation light yield, excellent stability, and nontoxicity.

Copper-Graphene Composite (CGC) Conductors: Synthesis, Microstructure, and Electrical Performance.

Improving the electrical performance of copper, the most widely used electrical conductor in the world is of vital importance to the progress of key technologies, including electric vehicles, portable devices, renewable energy, and power grids. Copper-graphene composite (CGC) stands out as the most promising candidate for high-performance electrical conductor applications. This can be attributed to the superior properties of graphene fillers embedded in CGC, including excellent electrical and thermal conductivity, corrosion resistance, and high mechanical strength. This review highlights the recent progress of CGC conductors, including their fabrication processes, electrical performances, mechanisms of copper-graphene interplay, and potential applications.

Engineered Exosomes Biopotentiated Hydrogel Promote Hair Follicle Growth via Reprogramming the Perifollicular Microenvironment.

Androgenetic alopecia (AGA) is a highly prevalent condition in contemporary society. The conventional treatment of minoxidil tincture is hindered by issues such as skin irritation caused by ethanol, non-specific accumulation in hair follicles, and short retention due to its liquid form. Herein, we have developed a novel minoxidil-incorporated engineered exosomes biopotentiated hydrogel (Gel@MNs) that has the capability to modulate the perifollicular microenvironment for the treatment of AGA. Leveraging the exceptional skin penetration abilities of flexible liposomes and the targeting properties of exosomes, the encapsulated minoxidil can be effectively delivered to the hair follicles. In comparison to free minoxidil, Gel@MNs demonstrated accelerated hair regeneration in an AGA mouse model without causing significant skin irritation. This was evidenced by an increase in both the number and size of hair follicles within the dermal layer, enhanced capillary formation surrounding the follicles, and the regulation of the transition of hair follicle cells from the telogen phase to the anagen growth phase. Therefore, this safe and microenvironment-modifying hybrid exosome-embedded hydrogel shows promising potential for clinical treatment of AGA.

Single-Shot Intensity- and Phase-Sensitive Compressive Sensing-Based Coherent Modulation Ultrafast Imaging.

Ultrafast imaging can capture the dynamic scenes with a nanosecond and even femtosecond temporal resolution. Complementarily, phase imaging can provide the morphology, refractive index, or thickness information that intensity imaging cannot represent. Therefore, it is important to realize the simultaneous ultrafast intensity and phase imaging for achieving as much information as possible in the detection of ultrafast dynamic scenes. Here, we report a single-shot intensity- and phase-sensitive compressive sensing-based coherent modulation ultrafast imaging technique, shortened as CS-CMUI, which integrates coherent modulation imaging, compressive imaging, and streak imaging. We theoretically demonstrate through numerical simulations that CS-CMUI can obtain both the intensity and phase information of the dynamic scenes with ultrahigh fidelity. Furthermore, we experimentally build a CS-CMUI system and successfully measure the intensity and phase evolution of a multimode Q-switched laser pulse and the dynamical behavior of laser ablation on an indium tin oxide thin film. It is anticipated that CS-CMUI enables a profound comprehension of ultrafast phenomena and promotes the advancement of various practical applications, which will have substantial impact on fundamental and applied sciences.

Association between biomarkers of zinc and copper status and heart failure: a meta-analysis.

AIMS: Previous studies have investigated the relationship between heart failure (HF) and levels of zinc and copper, but conflicting results have been reported. This meta-analysis aims to clarify the role of zinc and copper in HF progression by examining the associations between HF and concentrations of these minerals. METHODS AND RESULTS: We utilized STATA 12.0 software to calculate the standard mean difference (SMD) and 95% confidence interval (CI) for serum zinc and copper levels in patients with HF compared with healthy controls (HCs). The meta-analysis indicated a lower serum zinc level in patients with HF compared with HCs, using a random effects model (SMD = -0.77; 95% CI: -1.01, -0.54; I2 = 61.9%, the P-value for Q test = 0.002). Additionally, the meta-analysis showed an increased serum copper level in patients with HF compared with HCs, using a random effects model (SMD = 0.66; 95% CI: 0.09, 1.23; I2 = 93.8%, the P-value for Q test < 0.001). Meta-regression analysis indicated that publication year, age, and gender were not responsible for heterogeneity across studies. CONCLUSIONS: This meta-analysis demonstrates that patients with HF have lower serum zinc and higher copper concentrations compared with healthy subjects. However, the potential of zinc supplementation as a therapy for HF should be approached with caution. The heterogeneity among the included studies was found to be high. It is recommended that further well-designed large sample studies be conducted to validate these findings.

The Effect of Telemedicine Interventions on Patients with Diabetic Foot Ulcers: A Systematic Review and Meta-Analysis of Randomized Controlled Trials.

Objective: The meta-analysis was performed to evaluate the effectiveness of telemedicine interventions on patients with diabetic foot ulcers (DFU). Approach: The authors conducted a comprehensive search across eight databases. The aim was to identify randomized controlled trials examining the effectiveness of telemedicine for patients with DFU. Methodological qualities of included studies were assessed using Cochrane Handbook for Systematic Reviews of Intervention. Subsequently, a meta-analysis was conducted using RevMan 5.3 to synthesize the findings. Results: Ten studies involving 1,678 patients with DFU were included in the meta-analysis. In comparison to the face-to-face intervention group, telemedicine interventions significantly reduced the amputation rate (risk ratio = 0.64, 95% confidence interval [CI] = 0.44-0.92, p = 0.02), decreased costs (mean difference [MD] = -4158.51, 95% CI = -7304.69 to -1012.34, p = 0.01), better controlled fasting blood glucose (MD = -0.89, 95% CI = -1.43 to -0.36, p = 0.001), and achieved superior glycated hemoglobin control (MD = -0.71, 95% CI = -1.01 to -0.41, p < 0.00001). No significant differences were observed between the telemedicine group and the face-to-face group in terms of healing rate, mortality, and healing time. Innovations: Our study suggests that telemedicine is a viable strategy for managing DFU. Conclusions: The meta-analysis indicates that telemedicine interventions have a positive effect on DFU. Nevertheless, more well-designed and high-quality studies are needed to reach a conclusion with greater confidence.

Uncovering the Power of HSCCC: Separation of Diastereomeric and Regioisomeric Styrylpyrones from the Stem Bark of Goniothalamus leiocarpus.

The plant Goniothalamus leiocarpus of the Annonaceae family is used as an alternative medicine in tropical regions. Applying high-speed counter current chromatography (HSCCC), eight new bioactive styrylpyrone isomers, including 6R,7S,8R,2'S-goniolactone B (1), 6S,7S,8S,2'S-goniolactone B (2), 6R,7R,8R,2'S-goniolactone B (3), 6R,7S,8S,2'S-goniolactone C (4), 6R,7S,8R,2'S-goniolactone C (5), 6S,7R,8S,2'S-goniolactone C (6), and two positional isomers, 6R,7R,8R,2'S-goniolactone G (7) and 6S,7R,8R,2'S-goniolactone G (8), were isolated from a chloroform fraction (2.1 g) of G. leiocarpus, which had a prominent spot by TLC analysis. The structures of the new compounds were elucidated by MS, NMR, IR, and UV spectra, and their absolute configurations were determined by Mosher's method, ECD, and X-ray diffraction analysis. The isolates are characteristic components found in plants of the genus Goniothalamus and consist of two structural moieties: a styrylpyrone and a dihydroflavone unit. The isolation of the eight new compounds demonstrates the effectiveness of HSCCC in separating the isomers of natural styrylpyrone. In a bioactivity assessment, compounds 1 and 6 exhibited cytotoxic effects against the human colon carcinoma cell lines LS513 and SW620 with IC50 values ranging from 1.6 to 3.9 µM. Compounds 1, 2, 7, and 8 showed significant synergistic activity against antibiotic-resistant Staphylococcus aureus strains.

Design, synthesis, and evaluation of cyclic C7-bridged monocarbonyl curcumin analogs containing an o-methoxy phenyl group as potential agents against gastric cancer.

The structure-activity relationship (SAR) between toxicity and the types of linking ketones of C7 bridged monocarbonyl curcumin analogs (MCAs) was not clear yet. In the pursuit of effective and less cytotoxic chemotherapeutics, we conducted a SAR analysis using various diketene skeletons of C7-bridged MCAs, synthesized cyclic C7-bridged MCAs containing the identified low-toxicity cyclopentanone scaffold and an o-methoxy phenyl group, and assessed their anti-gastric cancer activity and safety profile. Most compounds exhibited potent cytotoxic activities against gastric cancer cells. We developed a quantitative structure-activity relationship model (R2 > 0.82) by random Forest method, providing important information for optimizing structure. An optimized compound 2 exhibited in vitro and in vivo anti-gastric cancer activity partly through inhibiting the AKT and STAT3 pathways, and displayed a favorable in vivo safety profile. In summary, this paper provided a promising class of MCAs and a potential compound for the development of chemotherapeutic drugs.

Clinical nursing mentors' motivation, attitude, and practice for mentoring and factors associated with them.

OBJECTIVE: To investigate the motivation, attitude, and practice toward mentoring and related factors among clinical nursing mentors. METHODS: This cross-sectional study included clinical nursing mentors from 30 hospitals in Zhejiang Province between August and September 2023. Demographic information, motivation, attitude, and practice were collected through a self-administered questionnaire. RESULTS: A total of 495 valid questionnaires were collected, and most of the participants were 30-39 years old (68.7%). Average motivation, attitude, and practice scores were 29 [26, 32] (possible range: 8-40), 87 (82, 94) (possible range: 22-110), and 41 (38, 45) (possible range: 11-55), respectively. Correlation analyses showed that the motivation scores were positively correlated with attitude scores (r = 0.498, P < 0.001) and practice scores (r = 0.408, P = 0.001), while attitude scores were positively correlated with practice scores (r = 0.554, P < 0.001). Multivariate logistic regression showed that intermediate and senior nursing mentors (OR = 0.638, 95% CI: [0.426-0.956], P = 0.030) and different hospitals (OR = 1.627, 95% CI: [1.054-2.511], P = 0.028) were independently associated with motivation. The hospital's frequency of psychological care was a significant factor associated with nursing mentoring motivation, attitude, and practice. Participation in training (OR = 2.908, 95% CI: [1.430, 5.913], P = 0.003) and lower frequency of job evaluation in hospital ("Often": OR = 0.416, 95% CI: [0.244-0.709], P = 0.001 and "Sometimes": OR = 0.346, 95% CI: [0.184-0.650], P = 0.001) were independently associated with practice. CONCLUSION: Clinical nursing mentors had adequate motivation, positive attitude, and proactive practice towards mentoring and associated factors. Clinical nursing mentorship should be enhanced by prioritizing mentor training, fostering a supportive environment with consistent psychological care, and promoting structured mentorship activities.

Comprehensive Long-Read Sequencing Analysis Discloses the Transcriptome Features of Papillary Thyroid Microcarcinoma.

CONTEXT: Papillary thyroid microcarcinoma (PTMC) is the most common type of thyroid cancer. It has been shown that lymph node metastasis is associated with poor prognosis in patients with PTMC. OBJECTIVE: We aim to characterize the PTMC transcriptome landscape and identify the candidate transcripts that are associated with lateral neck lymph node metastasis of PTMC. METHODS: We performed full-length transcriptome sequencing in 64 PTMC samples. Standard bioinformatic pipelines were applied to characterize and annotate the full-length expression profiles of 2 PTMC subtypes. Functional open reading frame (ORF) annotation of the known and novel transcripts were predicted by HMMER, DeepLoc, and DeepTMHMM tools. Candidate transcripts associated with the pN1b subtype were identified after transcript quantification and differential gene expression analyses. RESULTS: We found that skipping exons accounted for the more than 27.82% of the alternative splicing events. At least 42.56% of the discovered transcripts were novel isoforms of annotated genes. A total of 39 193 ORFs in novel transcripts and 18 596 ORFs in known transcripts were identified. Distribution patterns of the characterized transcripts in functional domain, subcellular localization, and transmembrane structure were predicted. In total, 1033 and 1204 differentially expressed genes were identified in the pN0 and pN1b groups, respectively. Moreover, novel isoforms of FRMD3, NOD1, and SHROOM4 were highlighted for their association with pN1b subtype. CONCLUSION: Our data provided the global transcriptome landscape of PTMC and also revealed the novel isoforms that associated with PTMC aggressiveness.

Green synthesis and anti-tumor efficacy via inducing pyroptosis of novel 1H-benzo[e]indole-2(3H)-one spirocyclic derivatives.

Pyroptosis induction is anticipated to be a new approach to developing anti-tumor medications. A novel class of spirocyclic compounds was designed by hybridization of 1H-Benzo[e]indole-2(3H)-one with 1,4-dihydroquinoline and synthesized through a new green "one-pot" synthesis method using 10 wt% SDS/H2O as a solvent to screen novel tumor cell pyroptosis inducers. The anti-tumor activity of all compounds in vitro was determined by the MTT method, and a fraction of the compounds showed good cell growth inhibitory activity. The quantitative structure-activity relationship models of the compounds were established by artificial intelligence random forest algorithm (R2 = 0.9656 and 0.9747). The ideal compound A9 could, in a concentration-dependent manner, prevent ovarian cancer cells from forming colonies, migrating, and invading. Furthermore, A9 could significantly induce pyroptosis and upregulate the expression of pyroptosis-related proteins GSDME-N, in addition to inducing apoptosis and mediating the expression of apoptosis-related proteins in ovarian cancer cells. A9 (5 mg/kg) significantly reduced tumor volume and weight of ovarian cancer in vivo, decreased caspase-3 expression in tumor tissue, and induced the production of GSDME-N. This study provides a green and efficient atom-economic synthesis method for 1H-Benzo[e]indole-2(3H)-one spirocyclic derivatives and a promising pyroptosis inducer with anti-tumor activity.

Application of direct observation of operational skills in nursing skill evaluation of pressure injury: A randomized clinical trial.

This was a non-blinded, single-centre, randomized, controlled clinical trial that compared the effectiveness of direct observation of procedural skills (DOPSs)with traditional assessment methods in pressure injury (PI) care skills. The study population included 82 nursing professionals randomly assigned to the study group (n = 41) and the control group (n = 41). Both groups of nurses underwent a 6-month training in PI care skills and were subsequently evaluated. The main outcome variables were the PI skill operation scores and theoretical scores. Secondary outcome variables included satisfaction and critical thinking abilities. Independent sample t-tests and chi-square tests were used to assess differences between the two groups of nurses. The results showed no statistically significant difference in PI skill operation scores between the two groups of nurses (p > 0.05). When comparing the PI theoretical scores, the study group scored higher than the control group, and this difference was statistically significant (p < 0.05). In terms of satisfaction assessment, the study group and the control group showed differences in improving self-directed learning, enhancing communication skills with patients, improving learning outcomes and increasing flexibility in clinical application (p < 0.05). When comparing critical thinking abilities between the two groups of nurses, there was no statistically significant difference at the beginning of the training, but after 3 months following the training, there was a statistically significant difference between the two groups (p < 0.01).The results indicated that the DOPS was effective in improving PI theoretical scores, increasing nurse satisfaction with the training and enhancing critical thinking abilities among nurses.

Predictive Value of Glycemic Variability and HDL-C for Secondary Persistent Inflammatory Immunosuppressed Catabolic Syndrome in Patients with Sepsis.

Purpose: Sepsis patients with persistent inflammation, immunosuppression, and catabolism syndrome (PICS) have a poor prognosis, and early detection of biomarkers to predict its prognosis is particularly important. The purpose of this study is to investigate the predictive value of glycemic variability (GV) and high density lipid-cholesterol (HDL-C) for secondary PICS in patients with sepsis. Patients and Methods: One hundred and sixty-five patients with sepsis were enrolled in the retrospective study and divided into sepsis secondary PICS and non-PICS group. The daily blood glucose levels from 1 to 7 days after the diagnosis of sepsis were recorded, and GV was calculated. Logistic regression was used to analyze the risk factors of sepsis with PICS, receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of GV, and HDL-C for the prognosis of sepsis with PICS. Results: In a study of 165 patients, PICS group tended to have higher GV and lower HDL-C levels than those in the non-PICS group. Logistic regression analysis identified GV and HDL-C as independent risk factors for the secondary PICS of sepsis. The results of ROC curve showed that GV and HDL-C had a certain predictive value for the secondary PICS of sepsis, the sensitivity of GV was 77.5%, specificity of 81.8%, the sensitivity of HDL-C was 76.6%, and specificity of 74.8%. Conclusion: GV and HDL are risk factors for PICS secondary to sepsis and have predictive value for patients' prognosis.

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on stroke.

BACKGROUND: Stroke is a common neurological disorder that disproportionately affects middle-aged and elderly individuals, leading to significant disability and mortality. Recently, human blood metabolites have been discovered to be useful in unraveling the underlying biological mechanisms of neurological disorders. Therefore, we aimed to evaluate the causal relationship between human blood metabolites and susceptibility to stroke. METHODS: Summary data from genome-wide association studies (GWASs) of serum metabolites and stroke and its subtypes were obtained separately. A total of 486 serum metabolites were used as the exposure. Simultaneously, 11 different stroke phenotypes were set as the outcomes, including any stroke (AS), any ischemic stroke (AIS), large artery stroke (LAS), cardioembolic stroke (CES), small vessel stroke (SVS), lacunar stroke (LS), white matter hyperintensities (WMH), intracerebral hemorrhage (ICH), subarachnoid hemorrhage (SAH), transient ischemic attack (TIA), and brain microbleeds (BMB). A two-sample Mendelian randomization (MR) study was conducted to investigate the causal effects of serum metabolites on stroke and its subtypes. The inverse variance-weighted MR analyses were conducted as causal estimates, accompanied by a series of sensitivity analyses to evaluate the robustness of the results. Furthermore, a reverse MR analysis was conducted to assess the potential for reverse causation. Additionally, metabolic pathway analysis was performed using the web-based MetOrigin. RESULTS: After correcting for the false discovery rate (FDR), MR analysis results revealed remarkable causative associations with 25 metabolites. Further sensitivity analyses confirmed that only four causative associations involving three specific metabolites passed all sensitivity tests, namely ADpSGEGDFXAEGGGVR* for AS (OR: 1.599, 95% CI 1.283-1.993, p = 2.92 × 10-5) and AIS (OR: 1.776, 95% CI 1.380-2.285, p = 8.05 × 10-6), 1-linoleoylglycerophosph-oethanolamine* for LAS (OR: 0.198, 95% CI 0.091-0.428, p = 3.92 × 10-5), and gamma-glutamylmethionine* for SAH (OR: 3.251, 95% CI 1.876-5.635, p = 2.66 × 10-5), thereby demonstrating a high degree of stability. Moreover, eight causative associations involving seven other metabolites passed both sensitivity tests and were considered robust. The association result of one metabolite (glutamate for LAS) was considered non-robust. As for the remaining metabolites, we speculate that they may potentially possess underlying causal relationships. Notably, no common metabolites emerged from the reverse MR analysis. Moreover, after FDR correction, metabolic pathway analysis identified 40 significant pathways across 11 stroke phenotypes. CONCLUSIONS: The identified metabolites and their associated metabolic pathways are promising circulating metabolic biomarkers, holding potential for their application in stroke screening and preventive strategies within clinical settings.

Interaction between N6-methyladenosine modification and the tumor microenvironment in colorectal cancer.

The incidence and mortality of colorectal cancer (CRC) are rapidly increasing worldwide. Recently, there has been significant attention given to N6-methyladenosine (m6A), the most common mRNA modification, especially for its effects on CRC development. It is important to note that the progression of CRC would be greatly hindered without the tumor microenvironment (TME). The interaction between CRC cells and their surroundings can activate and influence complex signaling mechanisms of epigenetic changes to affect the survival of tumor cells with a malignant phenotype. Additionally, the TME is influenced by m6A regulatory factors, impacting the progression and prognosis of CRC. In this review, we describe the interactions and specific mechanisms between m6A modification and the metabolic, hypoxia, inflammatory, and immune microenvironments of CRC. Furthermore, we summarize the therapeutic role that m6A modification can play in the CRC microenvironment, and discuss the current status, limitations, and potential future directions in this field. This review aims to provide new insights into the molecular targets and theoretical foundations for the treatment of CRC.

Risk prediction models for type 2 diabetes using either fasting plasma glucose or HbA1c in Chinese, Malay, and Indians: Results from three multi-ethnic Singapore cohorts.

AIMS: To assess three well-established type 2 diabetes (T2D) risk prediction models based on fasting plasma glucose (FPG) in Chinese, Malays, and Indians, and to develop simplified risk models based on either FPG or HbA1c. METHODS: We used a prospective multiethnic Singapore cohort to evaluate the established models and develop simplified models. 6,217 participants without T2D at baseline were included, with an average follow-up duration of 8.3 years. The simplified risk models were validated in two independent multiethnic Singapore cohorts (N = 12,720). RESULTS: The established risk models had moderate-to-good discrimination (area under the receiver operating characteristic curves, AUCs 0.762 - 0.828) but a lack of fit (P-values < 0.05). Simplified risk models that included fewer predictors (age, BMI, systolic blood pressure, triglycerides, and HbA1c or FPG) showed good discrimination in all cohorts (AUCs ≥ 0.810), and sufficiently captured differences between the ethnic groups. While recalibration improved fit the simplified models in validation cohorts, there remained evidence of miscalibration in Chinese (p ≤ 0.012). CONCLUSIONS: Simplified risk models including HbA1c or FPG had good discrimination in predicting incidence of T2D in three major Asian ethnic groups. Risk functions with HbA1c performed as well as those with FPG.