The ubiquitin-like protein UBTD1 promotes colorectal cancer progression by stabilizing c-Myc to upregulate glycolysis.

Dysfunction of the ubiquitin-proteasome system (UPS) is involved in the pathogenesis of various malignancies including colorectal cancer (CRC). Ubiquitin domain containing 1 (UBTD1), a ubiquitin-like protein, regulates UPS-mediated protein degradation and tumor progression in some cancer types. However, the biological function and mechanism of UBTD1 are far from being well elucidated, and its role in CRC has not been explored yet. In our study, we analyzed CRC patients' clinical information and UBTD1 expression data, and found that the expression of UBTD1 in cancer tissue was significantly higher than that in adjacent normal tissue. Higher UBTD1 expression was significantly associated with poorer survival and more lymph node metastasis. Overexpression of UBTD1 could facilitate, while knockdown could inhibit CRC cell proliferation and migration, respectively. RNA-seq and proteomics indicated that c-Myc is an important downstream target of UBTD1. Metabolomics showed the products of the glycolysis pathway were significantly increased in UBTD1 overexpression cells. In vitro, we verified UBTD1 upregulating c-Myc protein and promoting CRC cell proliferation and migration via regulating c-Myc. UBTD1 promoted CRC cells' glycolysis, evidenced by the increased lactate production and glucose uptake following UBTD1 overexpression. Mechanistically, UBTD1 prolonged the half-life of the c-Myc protein by binding to E3 ligase ß-transducin repeat-containing protein (ß-TrCP), thereby upregulated the expression of glycolysis rate-limiting enzyme hexokinase II (HK2), and enhanced glycolysis and promoted CRC progression. In conclusion, our study revealed that UBTD1 promotes CRC progression by upregulating glycolysis via the ß-TrCP/c-Myc/HK2 pathway, suggesting its potential as a prognostic biomarker and therapeutic target in CRC.

Bufadienolide-Fatty Acid Conjugates from the Fertilized Eggs of Toad Bufo gargarizans: Isolation, Characterization, Toxicity, and Antiproliferative Evaluation.

Bufadienolides (BDs) are a class of naturally occurring toxins present in amphibian toads. Serving as the chemical weapons, they exist not only in the adult toads but also in toad eggs. Guided by mass spectrometry (MS)-based component analysis and feature-based molecular networking (FBMN), 30 bufadienolide-fatty acid conjugates (BDFs) were isolated from the fertilized eggs of toad Bufo gargrizans, including 25 previously undescribed compounds (1-25). Their chemical structures were elucidated by extensive spectroscopic analysis, chemical methods, and GC-MS. The toxicities of all BDFs and their corresponding free BDs were assessed using the zebrafish model. The structure-toxicity relationship analysis showed that the modification of BDs by hydroxy fatty acids can cause a significant increase of the toxicity. Furthermore, all the isolated compounds were evaluated for their antiproliferative activities in pancreatic cancer cell lines ASPC-1 and PANC10.05. The structure-activity relationship (SAR) analysis revealed that BDFs with hellebrigenin as the bufogenin moiety (6 and 7) exhibited the most potent antiproliferative effect. Further investigation into their functional mechanism demonstrated that 6 and 7 induced apoptosis in pancreatic cancer cells PANC10.05 and significantly suppressed the expression of the apoptosis-related gene c-MYC. In addition, 6 and 7 effectively inhibited the expression of the PI3K/Akt/mTOR pathway in PANC10.05. Moreover, we assessed the efficacy of 6 and 7 on cancer cells from various tissues and observed their broad-spectrum antiproliferative activity.

Prenatal Exposure of PFAS in Cohorts of Pregnant Women: Identifying the Critical Windows of Vulnerability and Health Implications.

Cohorts of pregnant women in 2018 and 2020 were selected to explore prenatal exposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS). Maternal serum during the whole pregnancy (first to third trimesters) and matched cord serum were collected for the analysis of 50 PFAS. Perfluorooctanoic acid (PFOA), perfluorooctanesulfonic acid (PFOS), and 6:2 fluorotelomer sulfonic acid (6:2 FTS) were the dominant PFAS in both the maternal and cord serum. The median ∑PFAS concentration was 14.18 ng/mL, and the ∑PFAS concentration was observed to decline from the first trimester to the third trimester. The transplacental transfer efficiencies (TTE) of 29 PFAS were comprehensively assessed, and a "U"-shaped trend in TTE values with increasing molecular chain length of perfluoroalkyl carboxylic acid (PFCA) was observed in this study. Moreover, the maternal concentrations of 9-chlorohexadecafluoro-3-oxanonane-1-sulfonic acid (6:2 Cl-PFESA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), perfluoroundecanoic acid (PFUdA), perfluorododecanoic acid (PFDoA), PFOS, and hexafluoropropylene oxide dimer acid (HFPO-DA) in the 2020 cohort were significantly lower than those in the 2018 cohort, declining by about 23.85-43.2% from 2018 to 2020 (p < 0.05). Higher proportions of emerging PFAS were observed in fetuses born in 2020. This birth cohort was collected during the COVID-19 epidemic period. The change in the PFAS exposure scene might be in response to the different exposure profiles of the 2018 and 2020 cohorts, which are attributed to the impact of COVID-19 on the social activities and environment of pregnant women. Finally, by application of a multiple informant model, the third trimester was identified as the critical window of vulnerability to PFAS exposure that affects birth weight and birth length.

Improving quantitative prediction of protein subcellular locations in fluorescence images through deep generative models.

Machine learning has been employed in recognizing protein localization at the subcellular level, which highly facilitates the protein function studies, especially for those multi-label proteins that localize in more than one organelle. However, existing works mostly study the qualitative classification of protein subcellular locations, ignoring fraction of one multi-label protein in different locations. Actually, about 50 % proteins are multi-label proteins, and the ignorance of quantitative information highly restricts the understanding of their spatial distribution and functional mechanism. One reason of the lack of quantitative study is the insufficiency of quantitative annotations. To address the data shortage problem, here we proposed a generative model, PLocGAN, which could generate cell images with conditional quantitative annotation of the fluorescence distribution. The model was a conditional generative adversarial network, in which the condition learning utilized partial label learning to overcome the lack of training labels and allowed training with only qualitative labels. Meanwhile, it used contrastive learning to enhance diversity of the generated images. We assessed the PLocGAN on four pixel-fused synthetic datasets and one real dataset, and demonstrated that the model could generate images with good fidelity and diversity, outperforming existing state-of-the-art generative methods. To verify the utility of PLocGAN in the quantitative prediction of protein subcellular locations, we replaced the training images with generated quantitative images and built prediction models, and found that they had a boosting effect on the quantitative estimation. This work demonstrates the effectiveness of deep generative models in bioimage analysis, and provides a new solution for quantitative subcellular proteomics.

Depressive symptoms and associated factors among older patients with arthritis: evidence from a community-based study in eastern China.

Introduction: Depressive symptoms are often experienced by patients with arthritis and are correlated with poor health outcomes. However, the association between depressive symptoms and multidimensional factors (sociodemographic characteristics, health conditions, health behaviors, and social support) among older patients with arthritis in China remains poorly understood. This study aimed to explore the prevalence of depressive symptoms in older patients with arthritis in eastern China and identify the associated factors. Methods: We analyzed data of 1,081 older patients with arthritis using secondary data from 2014 to 2020 from a community-based ongoing study initiated in 2014 in eastern China. The prevalence of depressive symptoms was calculated, and univariate and multilevel logistic regression analyses were used to identify the associated factors. Results: The mean age of older patients with arthritis was 69.16 ± 7.13 years; 42.92% were men and 57.08% were women. The prevalence of depressive symptoms in older patients with arthritis was 14.99% (95% confidence interval: 12.91-17.26%), about 1.8 times higher than that in older adults without arthritis (8.49%, p < 0.001). Multilevel logistic regression identified perception of poor economic status (odds ratio [OR] = 5.52, p < 0.001), multimorbidity (OR = 1.96, p = 0.001), limitations in activities of daily living (OR = 2.36, p = 0.004), and living alone (OR = 3.13, p = 0.026) as factors positively associated with depressive symptoms. Patients diagnosed with arthritis at an older age had lower odds of experiencing depressive symptoms (OR = 0.67, p = 0.046). Conclusion: Screening for depressive symptoms is essential among older patients with arthritis, especially those who perceive themselves as having a poor economic status, are diagnosed at an earlier age, have multimorbidity, have limitations in activities of daily living, and live alone. The associations of age at arthritis diagnosis and dietary behaviors with depressive symptoms require further research.

Cadmium contamination decreased bacterial network complexity and stability in coastal reclamation areas.

Cadmium(Cd) contamination can exert significantly adverse effects on soil microbiota in reclaimed areas, however, its effects on bacterial network structure are still limitedly understood. Here we collected soil samples from typical reclaimed wetlands (RW) and ditch wetlands (DW) in coastal reclamation areas and examined the effects of Cd contamination on the bacterial network complexity and stability. The results showed that the bacterial networks were destabilized by the Cd contamination, while bacteria in DW soils showed robust invulnerability characterized by higher node constancy and compositional stability compared with RW soils. Soil bacteria resisted Cd stress by forming a network with intensive connections in the module but sparser connections among the modules. Especially, network modularity was higher in DW soils than in RW soils, but made it more vulnerable to nodes removal. In addition, Cd contamination promoted bacterial positive cohesion but decreased negative cohesion in RW soils. Flavobacteriaceae, Xanthomonadaceae, and Alcaligenaceae were identified as core phylotypes, which played pivotal roles in regulating interspecies interactions due to higher contributions to cohesion and significant correlations with soil nutrients. The findings of this work indicate the changes of bacterial network structure and the indispensable role of core phylotypes in regulating interactions and maintaining network sustainability under Cd contamination.

Serum albumin is associated with the inherent property of acute myeloid leukemia and correlates with patient outcomes.

An accurate prognostic model for acute myeloid leukemia (AML) can guide personalized treatment. In our prospective cohort of 591 patients newly diagnosed with AML, we evaluated the prognostic significance of serum albumin levels. We recognized baseline serum albumin as a prognostic factor by univariate Cox regression analysis (albumin-high vs albumin-low: overall survival [OS]: hazard ratio [HR]: 0.679, 95% confidence interval [CI]: 0.529-0.870, P = .002; cumulative incidence of relapse [CIR]: HR: 0.705, 95% CI: 0.530-0.938, P = .017) and multivariate Cox regression analysis (OS: HR per g/L: 0.966, 95% CI: 0.940-0.993, P = .014; CIR: HR per g/L: 0.959, 95% CI: 0.927-0.993, P = .017). In the subgroup analysis, serum albumin was prognostic significant in patients who received intermediate-dose cytarabine combined with daunorubicin and omacetaxine mepesuccinate induction (albumin-high vs albumin-low: OS: HR: 0.585, 95% CI: 0.397-0.863, P = .007; CIR: HR: 0.551, 95% CI: 0.353-0.861, P = .009) rather than those receiving conventional-dose induction regimens. In addition, the impact of baseline serum albumin level was evident in patients with intermediate European LeukemiaNet risk (albumin-high vs albumin-low: OS: HR: 0.617, 95% CI: 0.424-0.896, P = .011; CIR: HR: 0.617, 95% CI: 0.388-0.979, P = .040). Gene set enrichment analysis revealed that leukemia stem cell signatures were enriched in patients with low serum albumin levels. Our study suggested that baseline serum albumin level was associated with the inherent properties of AML and correlated with patient outcomes.

O-GlycoIsoQuant: A Novel O-Glycome Quantitative Approach through Superbase Release and Isotopic Girard's P Labeling.

Quantitative glycosylation analysis serves as an effective tool for detecting changes in glycosylation patterns in cancer and various diseases. However, compared with N-glycans, O-glycans present challenges in both qualitative and quantitative mass spectrometry analysis due to their low abundance, ease of peeling, lack of a universal enzyme, and difficult accessibility. To address this challenge, we developed O-GlycoIsoQuant, a novel O-glycome quantitative approach utilizing superbase release and isotopic Girard's P labeling. This method facilitates rapid and efficient nonreducing ß-elimination to dissociate O-glycans from proteins using the organic superbase, 1,8-diazabicyclo[5.4.0]undec-7-ene (DBU), combined with light and heavy isotopic Girard's reagent P (GP) labeling for relative quantification of O-glycans by mass spectrometry. Employing this method, labeled O-glycans exhibit a double peak with a mass difference of 5 Da, suitable for stable relative quantification. The O-GlycoIsoQuant method is characterized by its high labeling efficiency, excellent reproducibility (CV < 20%), and good linearity (R2 > 0.99), across a dynamic range spanning a 100-fold range. This method was applied to various complex sample types, including human serum, porcine spermatozoa, human saliva, and urinary extracellular vesicles, detecting 33, 39, 49, and 37 O-glycans, respectively, thereby demonstrating its broad applicability.

A comprehensive N-glycome map of porcine sperm membrane before and after capacitation.

Mapping the N-glycome of porcine sperm before and after sperm capacitation is important for understanding the rearrangement of glycoconjugates during capacitation. In this work, we characterized the N-glycome on the membranes of 18 pairs of fresh porcine sperm before capacitation and porcine sperm after capacitation by MALDI-MS (Matrix-assisted laser desorption/ionization-mass spectrometry). A total of 377 N-glycans were detected and a comprehensive N-glycome map of porcine sperm membranes before and after capacitation was generated, which presents the largest N-glycome dataset of porcine sperm cell membranes. Statistical analysis revealed a significantly higher level of high mannose glycosylation and a significantly lower level of fucosylation, galactosylation, and α-2,6-NeuAc after capacitation, which is further verified by flow cytometry and lectin blotting. This research reveals new insights into the relationship between N-glycosylation variations and sperm capacitation, including the underlying mechanisms of the capacitation process.

Longitudinal Cervical Length Measurements and Spontaneous Preterm Birth in Singleton and Twin Pregnancies.

Importance: Changes in cervical length in twin pregnancies exhibit various patterns, but it is unclear whether the mechanism underlying spontaneous preterm birth (sPTB) is consistent. The existence of detailed phenomena in singleton pregnancies is also unclear. Objectives: To explore the different patterns in cervical length trajectories in singleton and twin pregnancies and to analyze whether the immunological mechanisms of sPTB are consistent among these cervical length patterns. Design, Setting, and Participants: This cohort study recruited pregnant individuals who received antenatal care and delivered at Peking University Third Hospital in Beijing, China, between January 1, 2014, and December 31, 2022. Individuals with singleton and twin pregnancies were included. Exposures: Cervical length measurements and white blood cell (WBC) indicators. Main Outcomes and Measures: The primary outcome was sPTB. Longitudinal trajectory cluster analysis was used to identify patterns of changes in cervical length in singleton and twin pregnancies. A random-effects model with cubic spline was used to fit and compare the longitudinal trajectory of WBC indicators among early preterm birth, moderate to late preterm birth, and term birth. Results: A total of 43 559 pregnant individuals were included; of these, 41 706 had singleton pregnancies (mean [SD)] maternal age, 33.0 [4.0] years) and 1853 had twin pregnancies (mean [SD] maternal age, 33.3 [3.6] years). Two distinct patterns of cervical length changes were observed in both singleton and twin pregnancies: shortened (21 366 singletons and 546 twins) and stable (20 340 singletons and 1307 twins). In singleton pregnancies, WBC count was associated with early sPTB in individuals with both shortened cervix (odds ratio [OR], 1.35; 95% CI, 1.00-1.82) and stable cervix (OR, 1.64; 95% CI, 1.07-2.50). However, for twin pregnancies, the association of WBC count (OR, 3.13; 95% CI, 1.58-6.18) with the risk of early sPTB was observed only in individuals with a shortened cervix. Conclusions and Relevance: This study identified 2 distinct cervical length patterns: shortened and stable. These patterns revealed 2 preterm birth mechanisms in twin pregnancies, with the immunopathogenesis of sPTB found only in the shortened cervix pattern; in singleton pregnancies, maternal immune response was associated with a higher risk of sPTB regardless of a shortened or stable cervix.

Identification of red blood cell distribution width as a prognostic factor in acute myeloid leukemia.

Many prognostic factors have been identified in acute myeloid leukemia (AML). In this study, we investigated novel prognostic biomarkers using machine learning and Cox regression models in a prospective cohort of 591 patients with AML and tried to identify potential therapeutic targets based on transcriptomic data. We found that elevated red blood cell distribution width (RDW) at diagnosis was an adverse prognostic factor for AML, independent of the 2022 European LeukemiaNet (ELN2022) genetic risk. As a continuous variable, higher RDW was associated with shorter overall survival (OS) (hazard ratio [HR] 1.087, 95% confidence interval [CI] 1.036-1.139, p < 0.001) and event-free survival (EFS) (HR 1.078, 95% CI 1.033-1.124, p < 0.001). Elevated RDW returned to normal after consolidation therapy, which indicated that leukemia cells resulted in abnormal RDW. We further investigated the relationship between RDW and transcriptome in another cohort of 191 patients with AML and public datasets using gene set enrichment analysis (GSEA) and cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT). We found that patients in the high-RDW group were significantly enriched in the positive regulation of erythroid differentiation and inflammation-related pathways. Finally, we identified the inflammation-associated gene IL12RB2 and verified its prognostic relevance with patients with AML in public databases, suggesting it as a potential therapy target.

Deep learning-assisted 3D laser steering using an optofluidic laser scanner.

Laser ablation is an effective treatment modality. However, current laser scanners suffer from laser defocusing when scanning targets at different depths in a 3D surgical scene. This study proposes a deep learning-assisted 3D laser steering strategy for minimally invasive surgery that eliminates laser defocusing, increases working distance, and extends scanning range. An optofluidic laser scanner is developed to conduct 3D laser steering. The optofluidic laser scanner has no mechanical moving components, enabling miniature size, lightweight, and low driving voltage. A deep learning-based monocular depth estimation method provides real-time target depth estimation so that the focal length of the laser scanner can be adjusted for laser focusing. Simulations and experiments indicate that the proposed method can significantly increase the working distance and maintain laser focusing while performing 2D laser steering, demonstrating the potential for application in minimally invasive surgery.

LncRNA SNHG26 promotes gastric cancer progression and metastasis by inducing c-Myc protein translation and an energy metabolism positive feedback loop.

Metastasis is a bottleneck in cancer treatment. Studies have shown the pivotal roles of long noncoding RNAs (lncRNAs) in regulating cancer metastasis; however, our understanding of lncRNAs in gastric cancer (GC) remains limited. RNA-seq was performed on metastasis-inclined GC tissues to uncover metastasis-associated lncRNAs, revealing upregulated small nucleolar RNA host gene 26 (SNHG26) expression, which predicted poor GC patient prognosis. Functional experiments revealed that SNHG26 promoted cellular epithelial-mesenchymal transition and proliferation in vitro and in vivo. Mechanistically, SNHG26 was found to interact with nucleolin (NCL), thereby modulating c-Myc expression by increasing its translation, and in turn promoting energy metabolism via hexokinase 2 (HK2), which facilitates GC malignancy. The increase in energy metabolism supplies sufficient energy to promote c-Myc translation and expression, forming a positive feedback loop. In addition, metabolic and translation inhibitors can block this loop, thus inhibiting cell proliferation and mobility, indicating potential therapeutic prospects in GC.

The prevalence of COVID-19 infection, associated risk factors and post-COVID-19 symptoms among vaccinated people, in Anhui Province, China: A cross-sectional study.

To investigate the infection status of coronavirus disease 2019 (COVID-19) among people in Anhui Province, China after the epidemic prevention and control measures were lifted, and to study and analyze its related influencing factors. From March 11 to May 20, 2023, questionnaires on COVID-19 were distributed on the Questionnaire Star platform, and Statistical Product and Service Solutions software (version 19.0) was used for statistical processing. The results showed that the infection rate of COVID-19 among respondents reached 72.24%. 58.81% of the infected people reported post COVID-19 symptoms. Fever, fatigue, and cough were the main symptoms during infection. The results of multi-factor logistic regression analysis showed that there is statistical significance between age (P = .002), residential area (P = .025), number of vaccine injections (P < .001) and the risk of new coronavirus infection. COVID-19 had a high infection rate, and children had a lower risk of COVID-19. People living in cities were more susceptible to COVID-19, and it was necessary to increase the number of vaccine doses.

Pollution levels and potential ecological risks of trace elements in relation to bacterial community in surface water of shallow lakes in northern China before and after ecological water replenishment.

Ecological water replenishment is a crucial and effective measure to improve the water quality and ecological function of lakes. However, the effects of ecological water replenishment on the pollution characteristics and ecological risks of trace elements and bacterial communities in lake surface water are still kept unclear. We investigated the pollution levels and potential ecological risks for trace elements, as well as variation of the bacterial community in surface water in the BYD lake before and after ecological water replenishment. Our results revealed that higher levels and pollution indexes (Igeo) of trace metals (e.g., As, Cd, Co, Cu and Ni; p < 0.05) after ecological water replenishment were observed than before ecological water replenishment and their total potential ecological risk (∑RI) were increased. In contrast, the network complexity of these trace elements, including nodes, edges, average diameter, modularity, clustering coefficient and average pathlength showed a decrease after ecological water replenishment than before. The diversity (community richness, community diversity and phylogenetic diversity decreased) and community structure of the bacterial community in the surface water (p < 0.05) were greatly changed after ecological water replenishment than before, with the increase in heavy metal-resistant phylum (e.g., Acidobacteriota). Moreover, the concentration of trace elements and ∑RI were significantly correlated with the alpha diversity of bacterial community, as well as dissolved organic carbon (DOC) and ORP, after ecological water replenishment. The findings indicate that it is very necessary to continuously monitor trace metal pollution levels and heavy metal-resistant phylum and identify their potential pollution sources for water environment control and lake ecosystem health.

Seasonal changes in N-cycling functional genes in sediments and their influencing factors in a typical eutrophic shallow lake, China.

N-cycling processes mediated by microorganisms are directly linked to the eutrophication of lakes and ecosystem health. Exploring the variation and influencing factors of N-cycling-related genes is of great significance for controlling the eutrophication of lakes. However, seasonal dynamics of genomic information encoding nitrogen (N) cycling in sediments of eutrophic lakes have not yet been clearly addressed. We collected sediments in the Baiyangdian (BYD) Lake in four seasons to explore the dynamic variation of N-cycling functional genes based on a shotgun metagenome sequencing approach and to reveal their key influencing factors. Our results showed that dissimilatory nitrate reduction (DNRA), assimilatory nitrate reduction (ANRA), and denitrification were the dominant N-cycling processes, and the abundance of nirS and amoC were higher than other functional genes by at least one order of magnitude. Functional genes, such as nirS, nirK and amoC, generally showed a consistent decreasing trend from the warming season (i.e., spring, summer, fall) to the cold season (i.e., winter). Furthermore, a significantly higher abundance of nitrification functional genes (e.g., amoB, amoC and hao) in spring and denitrification functional genes (e.g., nirS, norC and nosZ) in fall were observed. N-cycling processes in four seasons were influenced by different dominant environmental factors. Generally, dissolved organic carbon (DOC) or sediment organic matter (SOM), water temperature (T) and antibiotics (e.g., Norfloxacin and ofloxacin) were significantly correlated with N-cycling processes. The findings imply that sediment organic carbon and antibiotics may be potentially key factors influencing N-cycling processes in lake ecosystems, which will provide a reference for nitrogen management in eutrophic lakes.

One-Year Disability Trajectories and Long-Term Cardiovascular Events, Recurrent Stroke, and Mortality After Ischemic Stroke.

BACKGROUND: Patients with stroke are often affected by varying degrees of functional disability and have different evolution patterns in functional disability. However, little is known about the predictive usefulness of disability changes after stroke. We aimed to describe 1-year disability trajectories and to assess the associations of longitudinal disability trajectories with 24-month clinical outcomes after ischemic stroke. METHODS AND RESULTS: A total of 3533 patients with ischemic stroke from CATIS (China Antihypertensive Trial in Acute Ischemic Stroke) were studied. Distinct trajectories of disability were identified by the group-based trajectory model, as measured by modified Rankin Scale score within 12 months. Cox proportional hazards regression models were used to examine the associations of disability trajectories with 24-month cardiovascular events and all-cause mortality. We identified 4 distinct disability trajectories: no significant disability (562 participants [15.9%]), slight disability to recovery (1575 participants [44.6%]), severe to moderate disability (1087 participants [30.8%]), and persistent severe disability (309 participants [8.7%]). Compared with no significant disability trajectory, the multivariable adjusted hazard ratios (95% CIs) of patients within the persistent heavy-severe trajectory were 2.63 (1.20-5.76) for cardiovascular events, 2.55 (1.12-5.79) for recurrent stroke, and 6.10 (2.22-16.72) for all-cause mortality; notably, the hazard ratios (95% CIs) for patients within the severe to moderate disability trajectory were 1.99 (1.01-3.94) for cardiovascular events and 1.85 (1.03-3.33) for the composite outcome of cardiovascular events and all-cause mortality. CONCLUSIONS: Functional disability trajectories within 12 months after stroke onset were associated with the risk of 24-month adverse outcomes. Patients with persistent severe disability or severe to moderate disability had higher risk of cardiovascular events and all-cause mortality. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01840072.

Efficacy of Immediate Antihypertensive Treatment in Patients With Acute Ischemic Stroke With Different Blood Pressure Genetic Variants.

BACKGROUND: It remains unclear whether blood pressure (BP) genetic variants could modify the efficacy of immediate antihypertensive treatment after acute ischemic stroke. We conducted a secondary analysis of the CATIS (China Antihypertensive Trial in Acute Ischemic Stroke) to investigate the effect of early antihypertensive treatment on clinical outcomes among patients with acute ischemic stroke according to 5 BP-associated genetic variants. METHODS: The CATIS randomized 4071 patients with acute ischemic stroke with elevated systolic BP to receive antihypertensive treatment or discontinue all antihypertensive agents during hospitalization. Randomization was conducted centrally and was stratified by participating hospitals and use of antihypertensive medications. Five BP-associated single nucleotide polymorphisms (rs16849225, rs17030613, rs1173766, rs6825911, and rs35444 in FIGN-GRB14, ST7L-CAPZA1, NPR3, ENPEP, and near TBX3, respectively) were genotyped among 2590 patients. The primary outcome was a combination of death and major disability at 14 days or hospital discharge. A weighted BP genetic risk score was constructed by the 5 single nucleotide polymorphisms. RESULTS: At 14 days or hospital discharge, the primary outcome was not significantly different between antihypertensive treatment and control groups based on genotype subgroups for all 5 single nucleotide polymorphisms (all P>0.05 for interaction). In addition, the BP genetic risk score did not modify the effect of antihypertensive treatment. The odds ratios (95% CIs) for the primary outcome were 0.95 (0.71-1.26), 1.08 (0.80-1.44), and 0.91 (0.69-1.22) in patients with low, intermediate, and high BP genetic risk score, respectively (P=0.88 for interaction). CONCLUSIONS: Early antihypertensive treatment had a neutral effect on clinical outcomes among patients with acute ischemic stroke according to 5 BP-associated genetic variants. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT01840072.

Multimedia distribution, partitioning, sources, comprehensive toxicity risk and co-occurrence network characteristics of trace elements in a typical Chinese shallow lake with high antibiotic risk.

Although the combined pollution of trace elements and antibiotics has received extensive attention, the fate and toxicity risk of trace elements with high antibiotic risk are still unclear. The multimedia distributions, partitioning, sources, toxicity risks and co-occurrence network characteristics of trace elements in surface water (SW), overlying water (OW), pore water (PW) and sediment (Sedi) samples of 61 sites from Baiyangdian (BYD) Lake were investigated. The trace elements in the SW and OW are derived mainly from traffic and agricultural sources, and those in PW and Sedi samples are primarily from lithogenic and industrial sources. The total toxicity risk index (TRI) of nine trace elements (ΣTRI) in Sedi samples showed a very high toxicity risk (18.35 ± 8.84), and a high combined pollution toxicity risk (ΣΣTRI) was observed in PW (149.17 ± 97.52) and Sedi samples (46.37 ± 24.00). The co-occurrence network from SW to PW became more vulnerable. Generally, total antibiotics and TP may be keystones of trace elements in water and sediment. The high antibiotic risk significantly influenced ΣΣTRI in water samples but not in Sedi samples. The findings provide new implications for the monitoring and control of combined antibiotic-trace element pollution in shallow lakes.

A liquid biopsy signature of circulating extracellular vesicles-derived RNAs predicts response to first line chemotherapy in patients with metastatic colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is one of the most threatening tumors in the world, and chemotherapy remains dominant in the treatment of metastatic CRC (mCRC) patients. The purpose of this study was to develop a biomarker panel to predict the response of the first line chemotherapy in mCRC patients. METHODS: Totally 190 mCRC patients treated with FOLFOX or XEOLX chemotherapy in 3 different institutions were included. We extracted the plasma extracellular vesicle (EV) RNA, performed RNA sequencing, constructed a model and generated a signature through shrinking the number of variables by the random forest algorithm and the least absolute shrinkage and selection operator (LASSO) algorithm in the training cohort (n = 80). We validated it in an internal validation cohort (n = 62) and a prospective external validation cohort (n = 48). RESULTS: We established a signature consisted of 22 EV RNAs which could identify responders, and the area under the receiver operating characteristic curve (AUC) values was 0.986, 0.821, and 0.816 in the training, internal validation, and external validation cohort respectively. The signature could also identify the progression-free survival (PFS) and overall survival (OS). Besides, we constructed a 7-gene signature which could predict tumor response to first-line oxaliplatin-containing chemotherapy and simultaneously resistance to second-line irinotecan-containing chemotherapy. CONCLUSIONS: The study was first to develop a signature of EV-derived RNAs to predict the response of the first line chemotherapy in mCRC with high accuracy using a non-invasive approach, indicating that the signature could help to select the optimal regimen for mCRC patients.