Noradrenaline-induced changes in cerebral blood flow in health, traumatic brain injury and critical illness: a systematic review with meta-analysis.

BACKGROUND: Noradrenaline is a standard treatment for hypotension in acute care. The precise effects of noradrenaline on cerebral blood flow in health and disease remain unclear. METHODS: We systematically reviewed and synthesised data from studies examining changes in cerebral blood flow in healthy participants and patients with traumatic brain injury and critical illness. RESULTS: Twenty-eight eligible studies were included. In healthy subjects and patients without critical illness or traumatic brain injury, noradrenaline did not significantly change cerebral blood flow velocity (-1.7%, 95%CI -4.7-1.3%) despite a 24.1% (95%CI 19.4-28.7%) increase in mean arterial pressure. In patients with traumatic brain injury, noradrenaline significantly increased cerebral blood flow velocity (21.5%, 95%CI 11.0-32.0%), along with a 33.8% (95%CI 14.7-52.9%) increase in mean arterial pressure. In patients who were critically ill, noradrenaline significantly increased cerebral blood flow velocity (20.0%, 95%CI 9.7-30.3%), along with a 32.4% (95%CI 25.0-39.9%) increase in mean arterial pressure. Our analyses suggest intact cerebral autoregulation in healthy subjects and patients without critical illness or traumatic brain injury., and impaired cerebral autoregulation in patients with traumatic brain injury and who were critically ill. The extent of mean arterial pressure changes and the pre-treatment blood pressure levels may affect the magnitude of cerebral blood flow changes. Studies assessing cerebral blood flow using non-transcranial Doppler methods were inadequate and heterogeneous in enabling meaningful meta-analysis. CONCLUSIONS: Noradrenaline significantly increases cerebral blood flow in humans with impaired, not intact, cerebral autoregulation, with the extent of changes related to the severity of functional impairment, the extent of mean arterial pressure changes and pre-treatment blood pressure levels.

FASTKD1 as a diagnostic and prognostic biomarker for STAD: Insights into m6A modification and immune infiltration.

Fas-activated serine/threonine kinase domain 1 (FASTKD1), a known modulator of mitochondrial-mediated cell death and survival processes, has garnered attention for its potential role in various biological contexts. However, its involvement in gastric cancer remains unclear. Thus, the present study aimed to investigate the relationship between FASTKD1 expression and key factors, including clinicopathological characteristics, immune infiltration and m6A modification in stomach adenocarcinoma (STAD). The expression of FASTKD1 was analyzed in STAD and normal adjacent tissues to assess its association with clinicopathological characteristics and survival prognosis. Data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were used in this study. Additionally, the findings were validated through immunohistochemical staining. Co-expression analysis of FASTKD1 was performed using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (GO/KEGG) enrichment analysis, Gene Set Enrichment Analysis (GSEA) and LinkedOmics database analysis. An in-depth analysis was conducted using databases, such as Tumor Immune Estimation Resource (TIMER), Gene Expression Profiling Interactive Analysis (GEPIA), GEO and TCGA to explore the potential correlation between FASTKD1 expression and immune infiltration and m6A modification in STAD. The results revealed that FASTKD1 was significantly upregulated across different tumor types, including STAD. Notably, FASTKD1 was able to distinguish between tumor and normal tissue samples with accuracy. Furthermore, the expression levels of FASTKD1 were significantly associated with clinical stage and survival. Through GO/KEGG enrichment analysis and GSEA, it was revealed that the genes co-expressed with FASTKD1 were active in a variety of biological processes. Within the TIMER, GEPIA and TCGA databases, a notable inverse correlation was observed between FASTKD1 expression and the abundance of immune cell subsets. Notably, significant correlations were established between FASTKD1 and m6A modification genes, YTHDF1 and LRPPRC, in both TCGA and GEO datasets. In conclusion, FASTKD1 may serve a significant role in m6A modification and immune infiltration processes, making it a potentially valuable diagnostic and prognostic biomarker in STAD.

Prescriptions of opioid-containing drugs in patients with chronic cough.

BACKGROUND: Chronic cough (CC) affects about 10% of adults, but opioid use in CC is not well understood. OBJECTIVES: To determine the use of opioid-containing cough suppressant (OCCS) prescriptions in patients with CC using electronic health records. DESIGN: Retrospective cohort study. METHODS: Through retrospective analysis of Midwestern U.S. electronic health records, diagnoses, prescriptions, and natural language processing identified CC - at least three medical encounters with cough, with 56-120 days between first and last encounter - and a 'non-chronic cohort'. Student's t-test, Pearson's chi-square, and zero-inflated Poisson models were used. RESULTS: About 20% of 23,210 patients with CC were prescribed OCCS; odds of an OCCS prescription were twice as great in CC. In CC, OCCS drugs were ordered in 38% with Medicaid insurance and 15% with commercial insurance. CONCLUSION: Findings identify an important role for opioids in CC, and opportunity to learn more about the drugs' effectiveness.

Dynamic hierarchical state space forecasting.

In this paper, we aim to both borrow information from existing units and incorporate the target unit's history data in time series forecasting. We consider a situation when we have time series data from multiple units that share similar patterns when aligned in terms of an internal time. The internal time is defined as an index according to evolving features of interest. When mapped back to the calendar time, these time series can span different time intervals that can include the future calendar time of the targeted unit, over which we can borrow the information from other units in forecasting the targeted unit. We first build a hierarchical state space model for the multiple time series data in terms of the internal time, where the shared components capture the similarities among different units while allowing for unit-specific deviations. A conditional state space model is then constructed to incorporate the information of existing units as the prior information in forecasting the targeted unit. By running the Kalman filtering based on the conditional state space model on the targeted unit, we incorporate both the information from the other units and the history of the targeted unit. The forecasts are then transformed from internal time back into calendar time for ease of interpretation. A simulation study is conducted to evaluate the finite sample performance. Forecasting state-level new COVID-19 cases in United States is used for illustration.

Clinical characteristics of cerebral amyloid angiopathy and risk factors of cerebral amyloid angiopathy related intracerebral hemorrhage.

OBJECTIVES: There is limited understanding of the differences between cerebral amyloid angiopathy (CAA) with and without intracerebral hemorrhage (ICH). This article aimed to describe the characteristics of CAA and identify the risk factors of CAA-ICH in a multicenter cohort. METHODS: Patients consecutively enrolled in the national multicenter prospective Cerebral Small Vessel Disease Cohort Study who met the Boston diagnostic criteria for CAA or CAA-related inflammation were included in this study. The demographic characteristics and clinical data were collected. The clinical and radiographic differences between CAA with and without ICH were compared to identify the risk factors for CAA-ICH. RESULTS: A total of 219 CAA patients were included, with an average age of 67.12 ± 9.93. Of all patients, 26.0% were CAA with ICH. Univariate analysis showed that CAA-ICH is associated with carrying more APOE ε2 allele, less lobar cerebral microbleeds (CMBs), cortical superficial siderosis (cSS), lower Fazekas scale, a tendency of gait disorder, and acute onset (P < 0.05). The generalized linear mixed model yielded statistically significant associations between CAA with ICH and carrying the APOE ε2 allele, cSS, the lower number of lobar CMBs, and the lower Fazekas scale (P < 0.05). CONCLUSION: It is meaningful to classify CAA with and without ICH, as there may be different mechanisms between the two. CAA with ICH has a susceptibility to carrying APOE ε2, cSS, and a relatively small number of CMBs. Fewer CMBs do not mean lower susceptibility to ICH in CAA. Larger prospective cohort studies are necessary to further clarify these conclusions.

Therapeutic Prospects of Mesenchymal Stem Cell and Their Derived Exosomes in the Regulation of the Gut Microbiota in Inflammatory Bowel Disease.

Mesenchymal stem cells (MSCs) have shown great potential in the treatment of several inflammatory diseases due to their immunomodulatory ability, which is mediated by exosomes secreted by MSCs (MSC-Exs). The incidence of inflammatory bowel disease (IBD) is increasing globally, but there is currently no long-term effective treatment. As an emerging therapy, MSC-Exs have proven to be effective in alleviating IBD experimentally, and the specific mechanism continues to be explored. The gut microbiota plays an important role in the occurrence and development of IBD, and MSCs and MSC-Exs can effectively regulate gut microbiota in animal models of IBD, but the mechanism involved and whether the outcome can relieve the characteristic dysbiosis necessary to alleviate IBD still needs to be studied. This review provides current evidence on the effective modulation of the gut microbiota by MSC-Exs, offering a basis for further research on the pathogenic mechanism of IBD and MSC-Ex treatments through the improvement of gut microbiota.

Dynamic Mechanism of Cerebral Venous Disruption: Longitudinal Evidence From a Community-Based Cohort.

BACKGROUND: This study aims to investigate the temporal and spatial patterns of structural brain injury related to deep medullary veins (DMVs) damage. METHODS AND RESULTS: This is a longitudinal analysis of the population-based Shunyi cohort study. Baseline DMVs numbers were identified on susceptibility-weighted imaging. We assessed vertex-wise cortex maps and diffusion maps at both baseline and follow-up using FSL software and the longitudinal FreeSurfer analysis suite. We performed statistical analysis of global measurements and voxel/vertex-wise analysis to explore the relationship between DMVs number and brain structural measurements. A total of 977 participants were included in the baseline, of whom 544 completed the follow-up magnetic resonance imaging (age 54.97±7.83 years, 32% men, mean interval 5.56±0.47 years). A lower number of DMVs was associated with a faster disruption of white matter microstructural integrity, presented by increased mean diffusivity and radial diffusion (ß=0.0001 and SE=0.0001 for both, P=0.04 and 0.03, respectively), in extensive deep white matter (threshold-free cluster enhancement P<0.05, adjusted for age and sex). Of particular interest, we found a bidirectional trend association between DMVs number and change in brain volumes. Specifically, participants with mild DMVs disruption showed greater cortical enlargement, whereas those with severe disruption exhibited more significant brain atrophy, primarily involving clusters in the frontal and parietal lobes (multiple comparison corrected P<0.05, adjusted for age, sex, and total intracranial volume). CONCLUSIONS: Our findings posed the dynamic pattern of brain parenchymal lesions related to DMVs injury, shedding light on the interactions and chronological roles of various pathological mechanisms.

A stable Zr(IV)-MOF for efficient removal of trace SO2 from flue gas in dry and humid conditions.

Obtaining suitable adsorbents for selective separation of SO2 from flue gas still remains an important issue. A stable Zr(IV)-MOF (Zr-PTBA) can be conveniently synthesized through the self-assembly of a tetracarboxylic acid ligand (H4L = 4,4',4'',4'''-(1,4-phenylenebis(azanetriyl))tetrabenzoic acid) and ZrCl4 in the presence of trace water. It exhibits a three-dimensional porous structure. The BET surface area is 1112.72 m2/g and the average pore size distribution focus on 5.9, 8.0 and 9.3 Å. Interestingly, Zr-PTBA shows selective adsorption of SO2. The maximum uptake reaches 223.21 cm3/g at ambient condition. While it exhibits lower adsorption uptake of CO2 (30.50 cm3/g) and hardly adsorbs O2 (2.57 cm3/g) and N2 (1.31 cm3/g). Higher IAST selectivities of SO2/CO2 (21.9), SO2/N2 (912.7), SO2/O2 (2269.9) and SO2/CH4 (85.0) have been obtained, which reveal its' excellent gas separation performance. Breakthrough experiment further confirms its application for flue gas deep desulfurization both in dry and humid conditions. Furthermore, the gas adsorption results and mechanisms have also been studied by theoretical calculations.

Pan-cancer analysis reveals correlation between RAB3B expression and tumor heterogeneity, immune microenvironment, and prognosis in multiple cancers.

RAB3B is essential for the transportation and secretion within cells. Its increased expression is linked to the development and progression of various malignancies. However, understanding of RAB3B's involvement in carcinogenesis is mostly limited to specific cancer subtypes. Hence, exploring RAB3B's regulatory roles and molecular mechanisms through comprehensive cancer datasets might offer innovative approaches for managing clinical cancer. To examine the potential involvement of RAB3B in the development of cancer, we analyzed data from various sources including The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression Project (GTEx), cBioPortal, HPA, UALCAN, and tissue microarray (TAM). Using bioinformatics techniques, we examined the correlation between RAB3B expression and prognosis, tumor heterogeneity, methylation modifications, and immune microenvironment across different cancer types. Our findings indicate that elevated RAB3B expression can independently predict prognosis in many tumors and has moderate accuracy for diagnosing most cancers. In most cancer types, we identified RAB3B mutations that showed a significant correlation with tumor mutational burden (TMB), mutant-allele tumor heterogeneity (MATH), and microsatellite instability (MSI). Abnormal DNA methylation patterns were also observed in most cancers compared to normal tissues. Additionally, we found significant correlations between RAB3B expression, immune cell infiltration, and immune scores across various cancers. Through pan-cancer analysis, we observed significant differences in RAB3B expression levels between tumors and normal tissues, making it a potential primary factor for cancer diagnosis and prognosis. The IHC results revealed that the expression of RAB3B in six types of tumors was consistent with the results of the pan-cancer analysis of the database. Furthermore, RAB3B showed potential associations with tumor heterogeneity and immunity. Thus, RAB3B can be utilized as an auxiliary diagnostic marker for early tumor detection and a prognostic biomarker for various tumor types.

Patient-Reported Outcomes in Autosomal Dominant Osteopetrosis: Findings from the Osteopetrosis Registry Study.

CONTEXT: Autosomal dominant osteopetrosis (ADO) is a rare sclerotic bone disease characterized by impaired osteoclast activity, resulting in high bone mineral density and skeletal fragility. The full phenotype and disease burden on patients' daily lives has not been systematically measured. OBJECTIVE: We developed an online registry to ascertain population-based data on the spectrum and rate of progression of disease and to identify relevant patient centered outcomes that could be used to measure treatment effects and guide the design of future clinical trials. DESIGN: Cross-sectional data from participants with osteopetrosis were collected using an online REDCap-based database. PARTICIPANTS: Thirty-four participants with a confirmed diagnosis of ADO, aged 4-84 years. MAIN OUTCOME MEASURES: Participants aged 18 years and older completed the PROMIS 57, participants aged 8 to 17 years completed the PROMIS Pediatric 49, and parents of participants aged <18 years completed the PROMIS Parent Proxy 49. RESULTS: Based on the PROMIS 57, relative to the general population, adults with ADO reported low physical function and low ability to participate in social roles and activities, and high levels of anxiety, fatigue, sleep problems, and pain interference. Daily pain medications were reported by 24% of the adult population. In contrast, neither pediatric participants, nor their parent proxy reported a negative impact on health-related quality of life. CONCLUSIONS: Data from this registry demonstrate the broad spectrum of ADO disease severity and high impact on health-related quality of life in adults with ADO.

Brain network hypersensitivity underlies pain crises in sickle cell disease.

Sickle cell disease (SCD) is a genetic disorder causing painful and unpredictable Vaso-occlusive crises (VOCs) through blood vessel blockages. In this study, we propose explosive synchronization (ES) as a novel approach to comprehend the hypersensitivity and occurrence of VOCs in the SCD brain network. We hypothesized that the accumulated disruptions in the brain network induced by SCD might lead to strengthened ES and hypersensitivity. We explored ES's relationship with patient reported outcome measures (PROMs) as well as VOCs by analyzing EEG data from 25 SCD patients and 18 matched controls. SCD patients exhibited lower alpha frequency than controls. SCD patients showed correlation between frequency disassortativity (FDA), an ES condition, and three important PROMs. Furthermore, stronger FDA was observed in SCD patients with a higher frequency of VOCs and EEG recording near VOC. We also conducted computational modeling on SCD brain network to study FDA's role in network sensitivity. Our model demonstrated that a stronger FDA could be linked to increased sensitivity and frequency of VOCs. This study establishes connections between SCD pain and the universal network mechanism, ES, offering a strong theoretical foundation. This understanding will aid predicting VOCs and refining pain management for SCD patients.

METTL3 as a novel diagnosis and treatment biomarker and its association with glycolysis, cuproptosis and ceRNA in oesophageal carcinoma.

METTL3 has been shown to be involved in regulating a variety of biological processes. However, the relationship between METTL3 expression and glycolysis, cuproptosis-related genes and the ceRNA network in oesophageal carcinoma (ESCA) remains unclear. ESCA expression profiles from databases were obtained, and target genes were identified using differential analysis and visualization. Immunohistochemistry (IHC) staining assessed METTL3 expression differences. Functional enrichment analysis using GO, KEGG and GSEA was conducted on the co-expression profile of METTL3. Cell experiments were performed to assess the effect of METTL3 interference on tumour cells. Correlation and differential analyses were carried out to assess the relationship between METTL3 with glycolysis and cuproptosis. qRT-PCR was used to validate the effects of METTL3 interference on glycolysis-related genes. Online tools were utilized to screen and construct ceRNA networks based on the ceRNA theory. METTL3 expression was significantly higher in ESCA compared to the controls. The IHC results were consistent with the above results. Enrichment analysis revealed that METTL3 is involved in multiple pathways associated with tumour development. Significant correlations were observed between METTL3 and glycolysis-related genes and cuproptosis-related gene. Experiments confirmed that interfered with METTL3 significantly inhibited glucose uptake and lactate production in tumour cells, and affected the expression of glycolytic-related genes. Finally, two potential ceRNA networks were successfully predicted and constructed. Our study establishes the association between METTL3 overexpression and ESCA progression. Additionally, we propose potential links between METTL3 and glycolysis, cuproptosis and ceRNA, presenting a novel targeted therapy strategy for ESCA.

Protective effect of carbon dots as antioxidants on intestinal inflammation by regulating oxidative stress and gut microbiota in nematodes and mouse models.

Inflammatory bowel disease (IBD) is a recurrent chronic colitis disease with increasing incidence and prevalence year by year. The single efficacy and significant side effects of traditional IBD treatment drugs have promoted the flourishing development of new drugs. Inspired by many health benefits of carbon dots (CDs) based nanomedicine in biomedical applications, a metal-free carbon dots (CP-CDs) was synthesized from citric acid and polyethylene polyamine to treat colitis. Oxidative stress tests at the cellular and nematode levels demonstrated CP-CDs have good antioxidant effects, while the toxicity of CP-CDs to cells and nematodes is low. CP-CDs were further applied to dextran sodium sulfate (DSS)-induced colitis in mice models, and it was found that CP-CDs can reduce the disease activity index (DAI) score of colon tissue and restore the intestinal barrier. Further, the anti-colitis mechanisms of CP-CDs were explored, one of which is to regulate intestinal oxidative stress in inflammatory mice, further reducing the expression of inflammatory cytokines, and thus alleviating colitis. Notably, 16S rRNA sequence analysis showed that the abundance of beneficial bacteria (Ligilactobacillus and Enterorhabdus) in the intestinal tract increased, while that of harmful bacteria (unclassified_Clostridia_UCG_014) decreased after CP-CDs treatment, indicating that CP-CDs rebalancing the gut microbiota destroyed by DSS is another important mechanism. In short, these non-toxic carbon dots not only have the potential for multi-factor combined relief of colitis but also offer an alternative therapy medicine for patients suffering from IBD.

Functional enrichment analysis reveals the involvement of DARS2 in multiple biological pathways and its potential as a therapeutic target in esophageal carcinoma.

OBJECTIVE: The enzyme Aspartyl tRNA synthetase 2 (DARS2) is a crucial enzyme in the mitochondrial tRNA synthesis pathway, playing a critical role in maintaining normal mitochondrial function and protein synthesis. However, the role of DARS2 in ESCA is unclear. MATERIALS AND METHODS: Transcriptional data of pan-cancer and ESCA were downloaded from UCSC XENA, TCGA, and GEO databases to analyze the differential expression of DARS2 between tumor samples and normal samples, and its correlation with clinicopathological features of ESCA patients. R was used for GO, KEGG, and GSEA functional enrichment analysis of DARS2 co-expression and to analyze the connection of DARS2 with glycolysis and m6A-related genes. In vitro experiments were performed to assess the effects of interfering with DARS2 expression on ESCA cells. TarBase v.8, mirDIP, miRTarBase, ENCORI, and miRNet databases were used to analyze and construct a ceRNA network containing DARS2. RESULTS: DARS2 was overexpressed in various types of tumors. In vitro experiments confirmed that interfering with DARS2 expression significantly affected the proliferation, migration, apoptosis, cell cycle, and glycolysis of ESCA cells. DARS2 may be involved in multiple biological pathways related to tumor development. Furthermore, correlation and differential analysis revealed that DARS2 may regulate ESCA m6A modification through its interaction with METTL3 and YTHDF1. A ceRNA network containing DARS2, DLEU2/has-miR-30a-5p/DARS2, was successfully predicted and constructed. CONCLUSIONS: Our findings reveal the upregulation of DARS2 in ESCA and its association with clinical features, glycolysis pathway, m6A modification, and ceRNA network. These discoveries provide valuable insights into the molecular mechanisms underlying ESCA.

Am I big boned? Bone length scaled reference data for HRpQCT measures of the radial and tibial diaphysis in White adults.

Cross-sectional size of a long bone shaft influences its mechanical properties. We recently used high-resolution peripheral quantitative computed tomography (HRpQCT) to create reference data for size measures of the radial and tibial diaphyses. However, data did not take into account the impact of bone length. Human bone exhibits relatively isometric allometry whereby cross-sectional area increases proportionally with bone length. The consequence is that taller than average individuals will generally have larger z-scores for bone size outcomes when length is not considered. The goal of the current work was to develop a means of determining whether an individual's cross-sectional bone size is suitable for their bone length. HRpQCT scans performed at 30 % of bone length proximal from the distal end of the radius and tibia were acquired from 1034 White females (age = 18.0 to 85.3 y) and 392 White males (age = 18.4 to 83.6 y). Positive relationships were confirmed between bone length and cross-sectional areas and estimated mechanical properties. Scaling factors were calculated and used to scale HRpQCT outcomes to bone length. Centile curves were generated for both raw and bone length scaled HRpQCT data using the LMS approach. Excel-based calculators are provided to facilitate calculation of z-scores for both raw and bone length scaled HRpQCT outcomes. The raw z-scores indicate the magnitude that an individual's HRpQCT outcomes differ relative to expected sex- and age-specific values, with the scaled z-scores also considering bone length. The latter enables it to be determined whether an individual or population of interest has normal sized bones for their length, which may have implications for injury risk. In addition to providing a means of expressing HRpQCT bone size outcomes relative to bone length, the current study also provides centile curves for outcomes previously without reference data, including tissue mineral density and moments of inertia.

SFXN1 as a potential diagnostic and prognostic biomarker of LUAD is associated with 18F-FDG metabolic parameters.

BACKGROUND: Sideroflexin 1 (SFXN1) has been discovered as a novel tumor marker for lung adenocarcinoma, but data on its importance in the development of lung adenocarcinoma is still limited. This study evaluated the correlation between SFXN1 and parameters related to 18F-flurodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT), and further explored the role of SFXN1 in the value-added and glycolytic processes of LUAD. METHOD: The expression and prognostic value of SFXN1 mRNA in LUAD were analyzed using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data base. Retrospective analysis of 18F-FDG PET imaging and metabolic parameters in 42 patients to explore the relationship between the expression of SFXN1 and glucose metabolism levels in lung adenocarcinoma and its clinical significance. H1975 cells were selected as the in vitro research object, and the biological effects of SFXN1 on LUAD were further elucidated through Edu proliferation assay, CCK8 activity assay, wound healing experiment, and cell flow cytometry. RESULT: SFXN1 is highly expressed in various tumors, including LUAD, and its high expression can serve as an independent predictor of overall survival in lung adenocarcinoma. In addition, the expression of SFXN1 in LUAD was significantly correlated with 18F-FDG PET/CT parameters: maximum and average standardized uptake values (SUVmax and SUVmean), as well as total lesion glycolysis (TLG) (rho = 0.574, 0.589, and 0.338, p < 0.05), which can predict the expression of SFXN1 with an accuracy of 0.934. In vitro functional experiments have shown that knocking down SFXN1 inhibits the proliferation and migration of LUAD cells, promotes cell apoptosis, and may inhibit tumor activity by regulating the expression of glycolytic related genes SLC2A1, HK2, GPI, ALDOA, GAPDH, ENO1, PKM, and LDHA. CONCLUSION: The overexpression of SFXN1 is closely related to FDG uptake, and SFXN1, as a promising prognostic biomarker, may mediate the development of LUAD through the glycolytic pathway.

Identification and validation of a necroptosis-related gene prognostic signature for colon adenocarcinoma.

Background: Necroptosis is a novel programmed cell death pathway proposed in 2005, which is mainly activated by the tumor necrosis factor (TNF) family and mediates cellular disassembly via receptor interacting serine/threonine kinase 1 (RIPK1), receptor interacting serine/threonine kinase 3 (RIPK3) and mixed lineage kinase domain like pseudokinase (MLKL). We tried to analyze the relationship of necroptosis-related genes (NRGs) expression with colon adenocarcinoma (COAD) and propose potential therapeutic targets through immunological analysis. Methods: First, we evaluated the expression of NRGs in COAD patients and constructed a prognostic signature. The prognostic signature was validated using The Cancer Genome Atlas (TCGA)-COAD and GSE39582 datasets, respectively. And the Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis were used to evaluate the signature. Then we analyzed the enrichment of NRGs in the signature using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Finally, we analyzed the immunological characteristics of the COAD patients by single sample gene set enrichment analysis (ssGSEA) and predicted the possible immune checkpoints. Results: We constructed a prognostic signature with 8 NRGs (RIPK3, MLKL, TRAF2, CXCL1, RBCK1, CDKN2A, JMJD7-PLA2G4B and CAMK2B). The Kaplan-Meier analysis, ROC curves, and principal component analysis demonstrated good predictivity of the signature. In addition, we constructed a nomogram with good individualized predictive ability (C-index =0.772). The immunological analysis revealed that the prognosis of COAD was associated with autoimmune function, and we proposed 10 potential therapeutic targets. Conclusions: Overall, we constructed an NRGs prognostic signature and suggested potential therapeutic targets for the COAD treatment.

γ-Aminobutyric acids (GABA) and serum GABA/AABA (G/A) ratio as potential biomarkers of physical performance and aging.

Declining physical performance with age and disease is an important indicator of declining health. Biomarkers that identify declining physical performance would be useful in predicting treatment outcomes and identifying potential therapeutics. γ-aminobutyric acid (GABA), a muscle autocrine factor, is a potent inhibitor of muscle function and works as a muscle relaxant. L-α-aminobutyric acid (L-AABA) is a biomarker for malnutrition, liver damage, and depression. We sought to determine if GABA and L-AABA may be useful for predicting physical performance. Serum levels of GABA and L-AABA were quantified in 120 individuals divided by age, sex, and physical capacity into low, average, and high performer groups. Analyses explored correlations between serum levels and physical performance. Both GABA and the ratio of GABA/AABA (G/A), but not AABA, were highly positively associated with age (Pearson correlations r = 0.35, p = 0.0001 for GABA, r = 0.31, p = 0.0007 for G/A, n = 120). GABA showed negative associations in the whole cohort with physical performance [fast gait speed, 6 min walk test (6MWT), PROMIS score, and SF36PFS raw score] and with subtotal and femoral neck bone mineral density. L-AABA was positively associated with usual gait speed, 6MWT, total SPPB score, and SF36PFS raw score in the total cohort of 120 human subjects, also with 6MWT and SF36PFS raw score in the 60 male subjects, but no associations were observed in the 60 females. As both GABA and L-AABA appear to be indicative of physical performance, but in opposite directions, we examined the G/A ratio. Unlike GABA, the G/A ratio showed a more distinct association with mobility tests such as total SPPB score, usual and fast gait speed, 6MWT, and SF36PFS raw score in the males, regardless of age and metabolic status. Serum G/A ratio could be potentially linked to physical performance in the male population. Our findings strongly suggest that GABA, L-AABA, and the G/A ratio in human serum may be useful markers for both age and physical function. These new biomarkers may significantly enhance the goal of identifying universal biomarkers to accurately predict physical performance and the beneficial effects of exercise training for older adults.

L-ß-aminoisobutyric acid, L-BAIBA, a marker of bone mineral density and body mass index, and D-BAIBA of physical performance and age.

As both L- and D-BAIBA are increased with exercise, we sought to determine if circulating levels would be associated with physical performance. Serum levels of L- and D-BAIBA were quantified in 120 individuals (50% female) aged 20-85 years and categorized as either a "low" (LP), "average" (AP) or "high" performing (HP). Association analysis was performed using Spearman (S) and Pearson (P) correlation. Using Spearman correlation, L-BAIBA positively associated with (1) body mass index BMI (0.23) and total fat mass (0.19) in the 120 participants, (2) total fat mass in the 60 males (0.26), and (3) bone mineral density, BMD, (0.28) in addition to BMI (0.26) in the 60 females. In HP females, L-BAIBA positively associated with BMD (0.50) and lean mass (0.47). D-BAIBA was positively associated with (1) age (P 0.20) in the 120 participants, (2) age (P 0.49) in the LP females and (3) with gait speed (S 0.20) in the 120 participants. However, in HP males, this enantiomer had a negative association with appendicular lean/height (S - 0.52) and in the AP males a negative correlation with BMD (S - 0.47). No associations were observed in HP or AP females, whereas, in LP females, a positive association was observed with grip strength (S 0.45), but a negative with BMD (P - 0.52, S - 0.63) and chair stands (P - 0.47, S - 0.51). L-BAIBA may play a role in BMI and BMD in females, not males, whereas D-BAIBA may be a marker for aging and physical performance. The association of L-BAIBA with BMI and fat mass may reveal novel, not previously described functions for this enantiomer.

Identifying underlying patterns in Alzheimer's disease trajectory: a deep learning approach and Mendelian randomization analysis.

Background: Alzheimer's disease (AD) is a heterogeneously progressive neurodegeneration disorder with varied rates of deterioration, either between subjects or within different stages of a certain subject. Estimating the course of AD at early stages has treatment implications. We aimed to analyze disease progression to identify distinct patterns in AD trajectory. Methods: We proposed a deep learning model to identify underlying patterns in the trajectory from cognitively normal (CN) to a state of mild cognitive impairment (MCI) to AD dementia, by jointly predicting time-to-conversion and clustering out distinct subgroups characterized by comprehensive features as well as varied progression rates. We designed and validated our model on the ADNI dataset (1370 participants). Prediction of time-to-conversion in AD trajectory was used to validate the expression of the identified patterns. Causality between patterns and time-to-conversion was further inferred using Mendelian randomization (MR) analysis. External validation was performed on the AIBL dataset (233 participants). Findings: The proposed model clustered out patterns characterized by significantly different biomarkers and varied progression rates. The discovered patterns also showed a strong prediction ability, as indicated by hazard ratio (CN→MCI, HR = 3.51, p < 0.001; MCI→AD, HR = 8.11, p < 0.001), C-Index (CN→MCI, 0.618; MCI→AD, 0.718), and AUC (CN→MCI, 3 years 0.802, 5 years 0.876; MCI→AD, 3 years 0.914, 5 years 0.957). In the external validation cohort, our model demonstrated competitive performance on conversion time prediction (CN→MCI, C-Index = 0.693; MCI→AD, C-Index = 0.752). Moreover, suggestive associations between CN→MCI/MCI→AD patterns with four/three SNPs were mediated and MR analysis indicated a causal link between MCI→AD patterns and time-to-conversion in the first three years. Interpretation: Our proposed model identifies biologically and clinically meaningful patterns from real-world data and provides promising performance on time-to-conversion prediction in AD trajectory, which could promote the understanding of disease progression, facilitate clinical trial design, and provide potential for decision-making. Funding: The National Key Research and Development Program of China, the Key R&D Program of Zhejiang, and the National Nature Science Foundation of China.