CYP2E1 in 1,4-dioxane metabolism and liver toxicity: insights from CYP2E1 knockout mice study.

1,4-Dioxane (DX), an emerging water contaminant, is classified as a Group 2B liver carcinogen based on animal studies. Understanding of the mechanisms of action of DX liver carcinogenicity is important for the risk assessment and control of this environmental pollution. Previous studies demonstrate that high-dose DX exposure in mice through drinking water for up to 3 months caused liver mild cytotoxicity and oxidative DNA damage, a process correlating with hepatic CYP2E1 induction and elevated oxidative stress. To access the role of CYP2E1 in DX metabolism and liver toxicity, in the current study, male and female Cyp2e1-null mice were exposed to DX in drinking water (5000 ppm) for 1 week or 3 months. DX metabolism, redox and molecular investigations were subsequently performed on male Cyp2e1-null mice for cross-study comparisons to similarly treated male wildtype (WT) and glutathione (GSH)-deficient Gclm-null mice. Our results show that Cyp2e1-null mice of both genders were resistant to DX-induced hepatocellular cytotoxicity. In male Cyp2e1-null mice exposed to DX for 3 months, firstly, DX metabolism to ß-hydroxyethoxyacetic acid was reduced to ~ 36% of WT levels; secondly, DX-induced hepatic redox dysregulation (lipid peroxidation, GSH oxidation, and activation of NRF2 antioxidant response) was substantially attenuated; thirdly, liver oxidative DNA damage was at a comparable level to DX-exposed WT mice, accompanied by suppression of DNA damage repair response; lastly, no aberrant proliferative or preneoplastic lesions were noted in DX-exposed livers. Overall, this study reveals, for the first time, that CYP2E1 is the main enzyme for DX metabolism at high dose and a primary contributor to DX-induced liver oxidative stress and associated cytotoxicity. High dose DX-induced genotoxicity may occur via CYP2E1-independent pathway(s), potentially involving impaired DNA damage repair.

A KLF2-BMPER-Smad1/5 checkpoint regulates high fluid shear stress-mediated artery remodeling.

Vascular remodeling to match arterial diameter to tissue requirements commonly fails in ischemic disease. Endothelial cells sense fluid shear stress (FSS) from blood flow to maintain FSS within a narrow range in healthy vessels. Thus, high FSS induces vessel outward remodeling, but mechanisms are poorly understood. We previously reported that Smad1/5 is maximally activated at physiological FSS. Smad1/5 limits Akt activation, suggesting that inhibiting Smad1/5 may facilitate outward remodeling. Here we report that high FSS suppresses Smad1/5 by elevating KLF2, which induces the bone morphogenetic protein (BMP) pathway inhibitor, BMP-binding endothelial regulator (BMPER), thereby de-inhibiting Akt. In mice, surgically induced high FSS elevated BMPER expression, inactivated Smad1/5 and induced vessel outward remodeling. Endothelial BMPER deletion impaired blood flow recovery and vascular remodeling. Blocking endothelial cell Smad1/5 activation with BMP9/10 blocking antibodies improved vascular remodeling in mouse models of type 1 and type 2 diabetes. Suppression of Smad1/5 is thus a potential therapeutic approach for ischemic disease.

Aberrant patterns of spontaneous brain activity in schizophrenia: A resting-state fMRI study and classification analysis.

BACKGROUND: Schizophrenia is a prevalent mental disorder, leading to severe disability. Currently, the absence of objective biomarkers hinders effective diagnosis. This study was conducted to explore the aberrant spontaneous brain activity and investigate the potential of abnormal brain indices as diagnostic biomarkers employing machine learning methods. METHODS: A total of sixty-one schizophrenia patients and seventy demographically matched healthy controls were enrolled in this study. The static indices of resting-state functional magnetic resonance imaging (rs-fMRI) including amplitude of low frequency fluctuations (ALFF), fractional ALFF (fALFF), regional homogeneity (ReHo), and degree centrality (DC) were calculated to evaluate spontaneous brain activity. Subsequently, a sliding-window method was then used to conduct temporal dynamic analysis. The comparison of static and dynamic rs-fMRI indices between the patient and control groups was conducted using a two-sample t-test. Finally, the machine learning analysis was applied to estimate the diagnostic value of abnormal indices of brain activity. RESULTS: Schizophrenia patients exhibited a significant increase ALFF value in inferior frontal gyrus, alongside significant decreases in fALFF values observed in left postcentral gyrus and right cerebellum posterior lobe. Pervasive aberrations in ReHo indices were observed among schizophrenia patients, particularly in frontal lobe and cerebellum. A noteworthy reduction in voxel-wise concordance of dynamic indices was observed across gray matter regions encompassing the bilateral frontal, parietal, occipital, temporal, and insular cortices. The classification analysis achieved the highest values for area under curve at 0.87 and accuracy at 81.28% when applying linear support vector machine and leveraging a combination of abnormal static and dynamic indices in the specified brain regions as features. CONCLUSIONS: The static and dynamic indices of brain activity exhibited as potential neuroimaging biomarkers for the diagnosis of schizophrenia.

Calcineurin inhibition rescues alloantigen-specific central memory T cell subsets that promote chronic GVHD.

Calcineurin inhibitors (CNIs) constitute the backbone of modern acute graft-versus-host disease (aGVHD) prophylaxis regimens but have limited efficacy in the prevention and treatment of chronic GVHD (cGVHD). We investigated the effect of CNIs on immune tolerance after stem cell transplantation with discovery-based single-cell gene expression and T cell receptor (TCR) assays of clonal immunity in tandem with traditional protein-based approaches and preclinical modeling. While cyclosporin and tacrolimus suppressed the clonal expansion of CD8+ T cells during GVHD, alloreactive CD4+ T cell clusters were preferentially expanded. Moreover, CNIs mediated reversible dose-dependent suppression of T cell activation and all stages of donor T cell exhaustion. Critically, CNIs promoted the expansion of both polyclonal and TCR-specific alloreactive central memory CD4+ T cells (TCM) with high self-renewal capacity that mediated cGVHD following drug withdrawal. In contrast to posttransplant cyclophosphamide (PT-Cy), CSA was ineffective in eliminating IL-17A-secreting alloreactive T cell clones that play an important role in the pathogenesis of cGVHD. Collectively, we have shown that, although CNIs attenuate aGVHD, they paradoxically rescue alloantigen-specific TCM, especially within the CD4+ compartment in lymphoid and GVHD target tissues, thus predisposing patients to cGVHD. These data provide further evidence to caution against CNI-based immune suppression without concurrent approaches that eliminate alloreactive T cell clones.

Association of anhedonia with brain-derived neurotrophic factor and interleukin-10 in major depressive disorder.

BACKGROUND: Anhedonia, a core symptom of major depressive disorder (MDD), manifests in two forms: anticipatory and consummatory, reflecting a diminished capacity to anticipate or enjoy pleasurable activities. Prior studies suggest that brain-derived neurotrophic factor (BDNF) and interleukin-10 (IL-10) may play key roles in the emergence of anhedonia in MDD. The specific relationships between these biomarkers and the two forms of anhedonia remain unclear. This study investigated the potential links between BDNF, IL-10, and both forms of anhedonia in MDD patients. METHODS: This study included 43 participants diagnosed with MDD and 58 healthy controls. It involved detailed assessments of depression and anxiety levels, anticipatory and consummatory pleasure, cognitive functions, and a broad spectrum of plasma biomarkers, such as C-reactive protein, various interleukins, and BDNF. Using partial correlation, variables related to pleasant experiences were identified. Stepwise multiple linear regression analysis was applied to pinpoint the independent predictors of anhedonia in the MDD group. RESULTS: Demographically, both groups were comparable in terms of age, sex, body mass index, educational year, and marital status. Individuals with MDD displayed markedly reduced levels of anticipatory and consummatory pleasure, higher anxiety, and depression scores compared to healthy controls. Additionally, cognitive performance was notably poorer in the MDD group. These patients also had lower plasma diamine oxidase levels. Analysis linked anhedonia to impaired delayed memory. Regression results identified IL-10 and BDNF as independent predictors of anticipatory and consummatory anhedonia, respectively. CONCLUSION: These findings demonstrate that anticipatory and consummatory anhedonia are influenced by independent factors, thereby providing critical insights into the distinct neuroimmunological mechanisms that underlie various forms of anhedonia. Clinicl Trial Registration Number: NCT03790085.

Placental transcriptome variation associated with season, location, and urinary prenatal pyrethroid metabolites of Thai farm-working women.

Prenatal exposure to pyrethroids is linked to adverse health effects in early life and proper placental function is critical to fetal development. This study explores the impact of prenatal pyrethroid exposure, as well as factors impacting exposure and effect, on the placental transcriptome, to understand pyrethroid exposures' relationship to placental function. The study of Asian Women and their Offspring's Development and Environmental Exposures (SAWASDEE) recruited pregnant farm-working women from two agricultural districts in the Chiang Mai province of Thailand between 2017 and 2019. This cohort was predominantly exposed to cypermethrin (type II), alongside pyrethroids such as cyfluthrin (type II) and permethrin (type I). In 253 participants, maternal urinary pyrethroid metabolites, 3-phenoxybenzoic acid (PBA), cis-3-(2,2-Dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (CDCCA), and trans-3-(2,2-Dichlorovinyl)-2,2-dimethylcyclopropane carboxylic acid (TDCCA) were measured in early, middle, and late pregnancy and adjusted for urinary creatinine. The placental transcriptome was analyzed using RNA-Seq. Using generalized linear regression, we identified differentially expressed genes (DEGs) associated with the sum of each metabolite across pregnancy, as well as those associated with location of residence and season of birth. Pathway and upstream transcription factor analyses were performed to examine potential mechanisms associated with DEGs. Notably, TDCCA and CDCCA levels peaked in late pregnancy, with significant regional differences, particularly higher levels in the Fang region. Placental gene expression analysis showed no DEGs associated with individual metabolites at FDR<0.05. However, 251 DEGs by location, implicating immune response and oxidative phosphorylation pathways, were identified, while season of birth was associated with 2585 DEGs, over-represented in fibrosis signaling and metabolism pathways. Finally, transcription factor analysis identified 226 and 282 transcription factors associated with location and season, respectively, related to cell proliferation, differentiation, and the immune system. These alterations may have significant implications for fetal development and other pathologic processes, highlighting the importance of monitoring environmental exposures during pregnancy.

SRplot: A free online platform for data visualization and graphing.

Graphics are widely used to provide summarization of complex data in scientific publications. Although there are many tools available for drawing graphics, their use is limited by programming skills, costs, and platform specificities. Here, we presented a freely accessible easy-to-use web server named SRplot that integrated more than a hundred of commonly used data visualization and graphing functions together. It can be run easily using all Web browsers and there are no strong requirements on the computing power of users' machines. With a user-friendly graphical interface, users can simply paste the contents of the input file into the text box according to the defined file format. Modification operations can be easily performed, and graphs can be generated in real-time. The resulting graphs can be easily downloaded in bitmap (PNG or TIFF) or vector (PDF or SVG) format in publication quality. The website is updated promptly and continuously. Functions in SRplot have been improved, optimized and updated depend on feedback and suggestions from users. The graphs prepared with SRplot have been featured in more than five hundred peer-reviewed publications. The SRplot web server is now freely available at http://www.bioinformatics.com.cn/SRplot.

Predicting the prognosis of lung cancer patients treated with intensity-modulated radiotherapy based on radiomic features.

AIMS: This study aimed to develop a method for predicting short-term outcomes of lung cancer patients treated with intensity-modulated radiotherapy (IMRT) using radiomic features detected through computed tomography images. METHOD: A prediction model was developed based on a dataset of radiomic features obtained from 132 patients with lung cancer receiving IMRT. Dimension reduction was performed for the features using the maximum-relevance and minimum-redundancy (mRMR) algorithm, and the least absolute shrinkage and selection operator (LASSO) regression model was utilized to optimize feature selection for the IMRT-sensitivity prediction model. The model was constructed using binary logistic regression analysis and was evaluated using the concordance index (C-index), calibration plots, receiver operating characteristic curve, and decision curve analysis. RESULTS: Fifty features were selected from 1348 radiomic features using the mRMR method. Of these, three radiomic features were selected by LASSO logistic regression to construct the radiomics nomogram. The C-index of the model was 0.776 (95% confidence interval: 0.689-0.862) and 0.791 (95% confidence interval: 0.607-0.974) in the training and validation cohorts, respectively. Decision curve analysis showed that the radiomics nomogram was clinically useful. CONCLUSION: Radiomic features have the potential to be applied to predict the short-term efficacy of IMRT in patients with inoperable lung cancer.

Multi-omics profiling reveals cellular pathways and functions regulated by ALDH1B1 in colon cancer cells.

Colon cancer is the third leading cause of cancer death globally. Although early screenings and advances in treatments have reduced mortality since 1970, identification of novel targets for therapeutic intervention is needed to address tumor heterogeneity and recurrence. Previous work identified aldehyde dehydrogenase 1B1 (ALDH1B1) as a critical factor in colon tumorigenesis. To investigate further, we utilized a human colon adenocarcinoma cell line (SW480) in which the ALDH1B1 protein expression has been knocked down by 80% via shRNA. Through multi-omics (transcriptomics, proteomics, and untargeted metabolomics) analysis, we identified the impact of ALDH1B1 knocking down (KD) on molecular signatures in colon cancer cells. Suppression of ALDH1B1 expression resulted in 357 differentially expressed genes (DEGs), 191 differentially expressed proteins (DEPs) and 891 differentially altered metabolites (DAMs). Functional annotation and enrichment analyses revealed that: (1) DEGs were enriched in integrin-linked kinase (ILK) signaling and growth and development pathways; (2) DEPs were mainly involved in apoptosis signaling and cellular stress response pathways; and (3) DAMs were associated with biosynthesis, intercellular and second messenger signaling. Collectively, the present study provides new molecular information associated with the cellular functions of ALDH1B1, which helps to direct future investigation of colon cancer.

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model.

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

Endocrine pancreas-specific Gclc gene deletion causes a severe diabetes phenotype.

Reduced glutathione (GSH) is an abundant antioxidant that regulates intracellular redox homeostasis by scavenging reactive oxygen species (ROS). Glutamate-cysteine ligase catalytic (GCLC) subunit is the rate-limiting step in GSH biosynthesis. Using the Pax6-Cre driver mouse line, we deleted expression of the Gclc gene in all pancreatic endocrine progenitor cells. Intriguingly, Gclc knockout (KO) mice, following weaning, exhibited an age-related, progressive diabetes phenotype, manifested as strikingly increased blood glucose and decreased plasma insulin levels. This severe diabetes trait is preceded by pathologic changes in islet of weanling mice. Gclc KO weanlings showed progressive abnormalities in pancreatic morphology including: islet-specific cellular vacuolization, decreased islet-cell mass, and alterations in islet hormone expression. Islets from newly-weaned mice displayed impaired glucose-stimulated insulin secretion, decreased insulin hormone gene expression, oxidative stress, and increased markers of cellular senescence. Our results suggest that GSH biosynthesis is essential for normal development of the mouse pancreatic islet, and that protection from oxidative stress-induced cellular senescence might prevent abnormal islet-cell damage during embryogenesis.

Revisiting scaling of calcium sulfate in membrane distillation: Uncertainty of crystal-membrane interactions.

Scaling of calcium sulfate (CaSO4) is a stumbling block to the development of membrane distillation (MD), which holds promise for the treatment of saline water/wastewater. Despite increasing efforts made to understand the scaling behavior of CaSO4 in a process of MD and thereby develop strategies for mitigating the negative effects, considerable uncertainty remains about occurrence of the wetting and structural damage that could result from the strong crystal-membrane interactions. This study combined experimental and theoretical approaches to corroborate that a higher degree of supersaturation could be achieved by concentrating the CaSO4 in the feed at a faster rate; the elevated supersaturation would be in favor of exerting substantially high crystallization pressure on the membrane structures. In particular, the theoretical analysis established two dimensionless groups for measuring the relative importance of the concentration effect and quantifying the essential role played by the crystalline growth, respectively. In addition to alleviating the uncertainty, this study would be beneficial to the design of MD processes with improved scaling resistance.

Safety profile of 0.0015% tafluprost eye drops in China: a post-marketing observational study.

AIM: To investigate the treatment pattern and safety of tafluprost for glaucoma and ocular hypertension (OH) in clinical practice in China. METHODS: This post-marketing observational study included patients who received tafluprost to lower intraocular pressure (IOP) within 30d between September 2017 and March 2020 in 20 hospitals in China. Adverse drug reactions (ADRs) during tafluprost treatment and within 30d after the treatment were collected. RESULTS: A total of 2544 patients were included in this study, of them 58.5% (1488/2544) had primary open angle glaucoma (POAG), 21.9% (556/2544) had OH and 19.7% (500/2544) used tafluprost for other reasons. Of 359 ADRs occurred in 10.1% (258/2544) patients, and no serious adverse event occurred. The most common ADR was conjunctival hyperemia (128 ADRs in 124 patients, 4.9%). Totally 1670 participants (65.6%) combined tafluprost with carbonic anhydrase inhibitors (CAIs; 37.1%, 620/1670), sympathomimetics (33.5%, 559/1670), ß-blockers (33.2%, 555/1670), other prostaglandin analogs (PGAs; 15.6%, 260/1670) and other eye drops (15.1%, 253/1670). The highest incidence of conjunctival hyperemia was noted in patients who received tafluprost in combination with other PGAs (23 ADRs in 23 patients, 8.8%, 23/260) and the lowest was in combination with CAIs (16 ADRs in 16 patients, 2.6%, 16/620). Tafluprost was applied in primary angle-closure glaucoma (41.6%, 208/500), after glaucoma surgery (17.8%, 89/500) and after non-glaucoma surgery (15.8%, 79/500). CONCLUSION: Tafluprost is safe for POAG and OH, and tolerable when combined with other eye drops and under various clinical circumstances.

A generalization performance study on the boosting radiotherapy dose calculation engine based on super-resolution.

PURPOSE: During the radiation treatment planning process, one of the time-consuming procedures is the final high-resolution dose calculation, which obstacles the wide application of the emerging online adaptive radiotherapy techniques (OLART). There is an urgent desire for highly accurate and efficient dose calculation methods. This study aims to develop a dose super resolution-based deep learning model for fast and accurate dose prediction in clinical practice. METHOD: A Multi-stage Dose Super-Resolution Network (MDSR Net) architecture with sparse masks module and multi-stage progressive dose distribution restoration method were developed to predict high-resolution dose distribution using low-resolution data. A total of 340 VMAT plans from different disease sites were used, among which 240 randomly selected nasopharyngeal, lung, and cervix cases were used for model training, and the remaining 60 cases from the same sites for model benchmark testing, and additional 40 cases from the unseen site (breast and rectum) was used for model generalizability evaluation. The clinical calculated dose with a grid size of 2 mm was used as baseline dose distribution. The input included the dose distribution with 4 mm grid size and CT images. The model performance was compared with HD U-Net and cubic interpolation methods using Dose-volume histograms (DVH) metrics and global gamma analysis with 1%/1 mm and 10% low dose threshold. The correlation between the prediction error and the dose, dose gradient, and CT values was also evaluated. RESULTS: The prediction errors of MDSR were 0.06-0.84% of Dmean indices, and the gamma passing rate was 83.1-91.0% on the benchmark testing dataset, and 0.02-1.03% and 71.3-90.3% for the generalization dataset respectively. The model performance was significantly higher than the HD U-Net and interpolation methods (p < 0.05). The mean errors of the MDSR model decreased (monotonously by 0.03-0.004%) with dose and increased (by 0.01-0.73%) with the dose gradient. There was no correlation between prediction errors and the CT values. CONCLUSION: The proposed MDSR model achieved good agreement with the baseline high-resolution dose distribution, with small prediction errors for DVH indices and high gamma passing rate for both seen and unseen sites, indicating a robust and generalizable dose prediction model. The model can provide fast and accurate high-resolution dose distribution for clinical dose calculation, particularly for the routine practice of OLART.

Rumination mediates the relationship between childhood trauma and depressive symptoms in schizophrenia patients.

Rumination and childhood trauma are related to depressive symptoms in clinical and non-clinical individuals. This is the first study aimed to test the mediating effect of rumination on the relationship between childhood trauma and depressive symptoms in schizophrenia patients. A total of 313 schizophrenia patients were recruited in the present study. The 17-item Hamilton Depression Rating Scale (HAMD-17) was adopted to evaluate depressive symptoms, the short-form Childhood Trauma Questionnaire (CTQ-SF) and the 10-item Ruminative response scale (RRS-10) were utilized to assess the childhood trauma and rumination in patients, respectively. Our results showed that 168 schizophrenia patients (53.67%) had comorbid depressive symptoms. These patients with depressive symptoms had higher levels of childhood trauma [both CTQ-SF total scores and emotional abuse (EA), emotional neglect (EN), physical neglect (PN) subscale scores] and rumination (both RRS-10 total scores and brooding, reflection subscale scores) compared to patients without depressive symptoms. The stepwise logistic regression analysis identified that EN (OR 1.196, P = 0.003), PN (OR 1.1294, P < 0.001), brooding (OR 1.291, P < 0.001) and reflection (OR 1.481, P < 0.001) could independently predict the depressive symptoms in schizophrenia patients. Moreover, RRS-10 and its subscale scores could mediate the relationship between depressive symptoms and childhood trauma, especially EA, EN and PN in schizophrenia. Our preliminary findings suggest that the rigorous assessment and psychosocial interventions of rumination are important to alleviate the influence of childhood trauma on depressive symptoms in schizophrenia patients.

Differences in inflammatory marker profiles and cognitive functioning between deficit and nondeficit schizophrenia.

Deficit schizophrenia (DS) patient is a homogenous subtype of schizophrenia that includes primary and enduring negative symptoms. This study aimed to compare the differences in cognitive functioning and plasma levels of C-reactive protein (CRP) and inflammatory cytokines among DS patients, nondeficit schizophrenia (NDS) patients, and healthy controls (HCs). A total of 141 schizophrenia patients and 67 HCs were included in this study. The schizophrenia patients were divided into DS (N= 51) and NDS (N=90) groups based on the Proxy for the Deficit Syndrome Scale (PDS). The Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were used to evaluate the clinical symptoms and cognitive performances, respectively. The plasma level of CRP, IL-1ß, Il-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-17, TNF-α, and IFN-γ were measured using enzyme-linked immunosorbent assays (ELISAs). Our results showed that DS patients had the worst cognitive performance, especially in the immediate memory, attention, and language dimensions, compared to the NDS and HC groups. Compared to the HCs group, DS patients had higher levels of CRP, IL-1ß, IL-6, IL-8, IFN-γ, and total proinflammatory cytokines, and NDS patients had higher levels of IL-1ß, IFN-γ, and proinflammatory cytokines. We also found that CRP levels were significantly increased in DS patients compared to NDS patients. Moreover, stepwise logistic regression analysis revealed that CRP is an independent risk factor for DS. Sex stratification analysis showed significant differences in almost all cytokines in female samples but not in male samples. The significant differences in cognitive performance and inflammatory components among groups suggest that deficit syndrome is an independent endophenotype of schizophrenia patients with unique immune-inflammatory features, but may have sex characteristics.

Proteomic profiling reveals an association between ALDH and oxidative phosphorylation and DNA damage repair pathways in human colon adenocarcinoma stem cells.

Several members of the aldehyde dehydrogenase (ALDH) family, especially ALDH1 isoenzymes, have been identified as biomarkers of cancer stem cells (CSCs), a small subpopulation of oncogenic cells with self-renewal and multipotency capability. Consistent with this contention, cell populations with high ALDH enzymatic activity exhibit greater carcinogenic potential. It has been reported that ALDH1, especially ALDH1A1, serves as a valuable biomarker for colon CSCs. However, the functional roles of ALDHs in CSCs and solid tumors of the colon tissue is not fully understood. The aim of the present study was to identify molecular signature associated with high ALDH activity in human colorectal adenocarcinoma (COLO320DM) cells by proteomics profiling. Aldefluor™ assay was performed to sort COLO320DM cells exhibiting high (ALDHhigh) and low (ALDHlow) ALDH activity. Label-free quantitative proteomics analyses were conducted on these two cell populations. Proteomics profiling revealed a total of 229 differentially expressed proteins (DEPs) in ALDHhigh relative to ALDHlow cells, of which 182 were down-regulated and 47 were up-regulated. In agreement with previous studies, ALDH1A1 appeared to be the principal ALDH isozyme contributing to the Aldefluor™ assay activity in COLO320DM cells. Ingenuity pathway analysis of the proteomic datasets indicated that DEPs were associated with mitochondrial dysfunction, sirtuin signaling, oxidative phosphorylation and nucleotide excision repair. Our proteomics study predicts that high ALDH1A1 activity may be involved in these cellular pathways to promote a metabolic switch and cellular survival of CSCs.

Association of handgrip strength with all-cause mortality: a nationally longitudinal cohort study in China.

OBJECTIVES: Handgrip strength is considered a vital and reliable measure of comprehensive physical assessments, whereas the association of handgrip strength with overall mortality risk among Chinese adults was less studied. We prospectively investigated the association between handgrip strength and all-cause mortality among Chinese middle-aged and older people based on data from the China Health and Retirement Longitudinal Study (CHARLS).3 DESIGN: Longitudinal cohort study. METHODS: Grip strength was assessed for both hands by a dynamometer. Odds ratios (ORs)4 and 95 % confidence intervals (CIs)5 were estimated applying logistic regression models with adjustments for age, body mass index, ethnicity, education level, annual household income, marital status, drinking, smoking, physical activity, and medical insurance among men and women. Deaths were ascertained by each follow-up survey in which the household member who lived with the participants were inquired. RESULTS: Over an average follow-up period of approximately 8 years among the screened 11,618 participants ≥45 years old, 1290 deaths were documented. The age range was 45-93 for men and 45-96 for women. Greater handgrip strength was associated with a lower overall mortality risk, with adjusted ORs (comparing with extreme tertiles) of 0.47 (95 % CI: 0.35-0.64; P-trend<0.001) in men and 0.51 (95 % CI: 0.24-1.08; P-trend = 0.059) in women. Such inverse association seemed stronger among younger men (OR = 0.29, 95 % CI: 0.18-0.45), compared with the older men (OR = 0.49, 95 % CI: 0.33-0.73; P-interaction = 0.023). CONCLUSIONS: Handgrip strength was inversely associated with all-cause mortality risk, especially among the younger men. Further investigations are warranted to elucidate the underlying mechanism.

CHST15 gene germline mutation is associated with the development of familial myeloproliferative neoplasms and higher transformation risk.

Herein, we describe the clinical and hematological features of three genetically related families predisposed to myeloproliferative neoplasms (MPNs). Using whole-exome sequencing, we identified a c.1367delG mutation(p.Arg456fs) in CHST15 (NM_001270764), a gene encoding a type II transmembraneglycoproteinthat acts as a sulfotransferase and participates in the biosynthesis of chondroitin sulfate E, in germline and somatic cells in familial MPN. CHST15defects caused an increased JAK2V617F allele burden and upregulated p-Stat3 activity,leading to an increase in the proliferative and prodifferentiation potential of transgenic HEL cells. We demonstrated that mutant CHST15 is able to coimmmunoprecipitate the JAK2 protein,suggesting the presence of a CHST15-JAK2-Stat3 signaling axis in familial MPN. Gene expression profiling showed that the FREM1, IFI27 and C4B_2 genes are overexpressed in familial MPN, suggesting the activation of an "inflammatory response-extracellular matrix-immune regulation" signaling network in the CHST15 mutation background.We thus concluded that CHST15 is a novel gene that predisposes to familial MPN and increases the probability of disease development or transformation.

A new L-shaped rigid beam FBG acceleration sensor.

Acceleration detection is an important technology in the fields of seismic monitoring, structural health monitoring and resource exploration. A FBG acceleration sensor with the combination of L-shaped rigid beam and spring structure based on bearings is proposed against the low sensitivity that predominates in the low-frequency vibration measurement by FBG acceleration sensors, where L-shaped rigid beam is utilized to amplify the vibration signal, and is fixed by the bearings at both ends to effectively suppress the transverse crosstalk. The effects of structural parameters on the sensitivity and natural frequency of the sensors were analyzed using Origin theory, and such parameters were optimized; next, static stress and modal simulation analysis was made using COMSOL; in the end, a test system was built to test the performance of the real sensors. According to the findings, the acceleration sensor, whose natural frequency is 57 Hz, is of a flat sensitivity response in the low frequency range of 1-35 Hz, with the dynamic range being 89.83 dB, the acceleration sensitivity being up to 1241.85 pm/g, the coefficient of determination R2 for the sensitivity fit is 0.9997, and the transverse crosstalk being -26.20 dB within the operating frequency band. The findings offer a reference for improving the low-frequency vibration measurement capability of FBG acceleration sensors.