Efficacy and safety of sympathetic mapping and ablation of renal nerves for the treatment of hypertension (SMART): 6-month follow-up of a randomised, controlled trial.

Background: Previous trials of renal denervation (RDN) have been designed to investigate reduction of blood pressure (BP) as the primary efficacy endpoint using non-selective RDN without intraoperatively verified RDN success. It is an unmet clinical need to map renal nerves, selectively denervate renal sympathetic nerves, provide readouts for the interventionalists and avoid futile RDN. We aimed to examine the safety and efficacy of renal nerve mapping/selective renal denervation (msRDN) in patients with uncontrolled hypertension (HTN) and determine whether antihypertensive drug burden is reduced while office systolic BP (OSBP) is controlled to target level (＜140 mmHg). Methods: We conducted a randomized, prospective, multicenter, single-blinded, sham-controlled trial. The study combined two efficacy endpoints at 6 months as primary outcomes: The control rate of patients with OSBP ＜140 mmHg (non-inferior outcome) and change in the composite index of antihypertensive drugs (Drug Index) in the treatment versus Sham group (superior outcome). This design avoids confounding from excess drug-taking in the Sham group. Antihypertensive drug burden was assessed by a composite index constructed as: Class N (number of classes of antihypertensive drugs) × (sum of doses). 15 hospitals in China participated in the study and 220 patients were enrolled in a 1:1 ratio (msRDN vs Sham). The key inclusion criteria included: age (18-65 years old), history of essential HTN (at least 6 months), heart rate (≥70 bpm), OSBP (≥150 mmHg and ≤180 mmHg), ambulatory BP monitoring (ABPM, 24-h SBP ≥130 mmHg or daytime SBP ≥135 mmHg or nighttime SBP ≥120 mmHg), renal artery stenosis (＜50%) and renal function (eGFR ＞45 mL/min/1.73 m2). The catheter with both stimulation and ablation functions was inserted in the distal renal main artery. The RDN site (hot spot) was selected if SBP increased (≥5 mmHg) by intra-renal artery (RA) electrical stimulation; an adequate RDN was confirmed by repeated electronic stimulation if no increase in BP otherwise, a 2nd ablation was performed at the same site. At sites where there was decreased SBP (≥5 mmHg, cold spot) or no BP response (neutral spot) to stimulation, no ablation was performed. The mapping, ablation and confirmation procedure was repeated until the entire renal main artery had been tested then either treated or avoided. After msRDN, patients had to follow a predefined, vigorous drug titration regimen in order to achieve target OSBP (＜140 mmHg). Drug adherence was monitored by liquid chromatography-tandem mass spectrometry analysis using urine. This study is registered with ClinicalTrials.gov (NCT02761811) and 5-year follow-up is ongoing. Findings: Between July 8, 2016 and February 23, 2022, 611 patients were consented, 220 patients were enrolled in the study who received standardized antihypertensive drug treatments (at least two drugs) for at least 28 days, presented OSBP ≥150 mmHg and ≤180 mmHg and met all inclusion and exclusion criteria. In left RA and right RA, mapped sites were 8.2 (3.0) and 8.0 (2.7), hot/ablated sites were 3.7 (1.4) and 4.0 (1.6), cold spots were 2.4 (2.6) and 2.0 (2.2), neutral spots were 2.0 (2.1) and 2.0 (2.1), respectively. Hot, cold and neutral spots was 48.0%, 27.5% and 24.4% of total mapped sites, respectively. At 6 M, the Control Rate of OSBP was comparable between msRDN and Sham group (95.4% vs 92.8%, p = 0.429), achieved non-inferiority margin -10% (2.69%; 95% CI -4.11%, 9.83%, p ＜ 0.001 for non-inferiority); the change in Drug Index was significantly lower in msRDN group compared to Sham group (4.37 (6.65) vs 7.61 (10.31), p = 0.010) and superior to Sham group (-3.25; 95% CI -5.56, -0.94, p = 0.003), indicating msRDN patients need significantly fewer drugs to control OSBP ＜140 mmHg. 24-hour ambulatory SBP decreased from 146.8 (13.9) mmHg by 10.8 (14.1) mmHg, and from 149.8 (12.8) mmHg by 10.0 (14.0) mmHg in msRDN and Sham groups, respectively (p < 0.001 from Baseline; p > 0.05 between groups). Safety profiles were comparable between msRDN and Sham groups, demonstrating the safety and efficacy of renal mapping/selective RDN to treat uncontrolled HTN. Interpretation: The msRDN therapy achieved the goals of reducing the drug burden of HTN patients and controlling OSBP <140 mmHg, with only approximately four targeted ablations per renal main artery, much lower than in previous trials. Funding: SyMap Medical (Suzhou), LTD, Suzhou, China.

Impact of fine particulate matter on liver injury: evidence from human, mice and cells.

BACKGROUND: A recently discovered risk factor for chronic liver disease is ambient fine particulate matter (PM2.5). Our research aims to elucidate the effects of PM2.5 on liver injury and the potential molecular mechanisms. METHODS AND RESULTS: A population-based longitudinal study involving 102,918 participants from 15 Chinese cities, using linear mixed-effect models, found that abnormal alterations in liver function were significantly associated with long-term exposure to PM2.5. The serum levels of alanine aminotransferase, aspartate aminotransferase, gamma-glutamyl transferase, direct bilirubin, and triglyceride increased by 2.05%, 2.04%, 0.58%, 2.99%, and 1.46% with each 10 µg/m3 increase in PM2.5. In contrast, the serum levels of total protein, albumin, and prealbumin decreased by 0.27%, 0.48%, and 2.42%, respectively. Mice underwent chronic inhalation exposure to PM2.5 experienced hepatic inflammation, steatosis and fibrosis. In vitro experiments found that hepatocytes experienced an inflammatory response and lipid metabolic dysregulation due to PM2.5, which also activated hepatic stellate cells. The down-regulation and mis-localization of polarity protein Par3 mediated PM2.5-induced liver injury. CONCLUSIONS: PM2.5 exposure induced liver injury, mainly characterized by steatosis and fibrosis. The down-regulation and mis-localization of Par3 were important mechanisms of liver injury induced by PM2.5.

PPARγ Agonist Rosiglitazone and Antagonist GW9662: Antihypertensive Effects on Chronic Intermittent Hypoxia-Induced Hypertension in Rats.

The increased incidence of hypertension associated with obstructive sleep apnea (OSA) presents significant physical, psychological, and economic challenges. Peroxisome proliferator-activated receptor gamma (PPARγ) plays a role in both OSA and hypertension, yet the therapeutic potential of PPARγ agonists and antagonists for OSA-related hypertension remains unexplored. Therefore, we constructed a chronic intermittent hypoxia (CIH)-induced hypertension rat model that mimics the pathogenesis of OSA-related hypertension in humans. The model involved administering PPARγ agonist rosiglitazone (RSG), PPARγ antagonist GW9662, or normal saline, followed by regular monitoring of blood pressure and thoracic aorta analysis using staining and electron microscopy. Intriguingly, our results indicated that both RSG and GW9662 appeared to potently counteract CIH-induced hypertension. In silico study suggested that GW9662's antihypertensive effect might mediated through angiotensin II receptor type 1 (AGTR1). Our findings provide insights into the mechanisms of OSA-related hypertension and propose novel therapeutic targets.

Scbean: a python library for single-cell multi-omics data analysis.

SUMMARY: Single-cell multi-omics technologies provide a unique platform for characterizing cell states and reconstructing developmental process by simultaneously quantifying and integrating molecular signatures across various modalities, including genome, transcriptome, epigenome, and other omics layers. However, there is still an urgent unmet need for novel computational tools in this nascent field, which are critical for both effective and efficient interrogation of functionality across different omics modalities. Scbean represents a user-friendly Python library, designed to seamlessly incorporate a diverse array of models for the examination of single-cell data, encompassing both paired and unpaired multi-omics data. The library offers uniform and straightforward interfaces for tasks, such as dimensionality reduction, batch effect elimination, cell label transfer from well-annotated scRNA-seq data to scATAC-seq data, and the identification of spatially variable genes. Moreover, Scbean's models are engineered to harness the computational power of GPU acceleration through Tensorflow, rendering them capable of effortlessly handling datasets comprising millions of cells. AVAILABILITY AND IMPLEMENTATION: Scbean is released on the Python Package Index (PyPI) (https://pypi.org/project/scbean/) and GitHub (https://github.com/jhu99/scbean) under the MIT license. The documentation and example code can be found at https://scbean.readthedocs.io/en/latest/.

Hourly air pollution exposure and the onset of symptomatic arrhythmia: an individual-level case-crossover study in 322 Chinese cities.

BACKGROUND: Few studies have explored the relationship between air pollution and arrhythmia onset at the hourly level. We aimed to examine the association of exposure to air pollution with the onset of acute symptomatic arrhythmia at an hourly level. METHODS: We conducted a nationwide, time-stratified, case-crossover study in China between 2015 and 2021. We obtained hourly information on the onset of symptomatic arrhythmia (including atrial fibrillation, atrial flutter, atrial and ventricular premature beats and supraventricular tachycardia) from the Chinese Cardiovascular Association Database - Chest Pain Center (including 2025 certified hospitals in 322 cities). We obtained data on hourly concentrations of 6 air pollutants from the nearest monitors, including fine particles (PM2.5), coarse particles (PM2.5-10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO) and ozone. For each patient, we matched the case period to 3 or 4 control periods during the same hour, day of week, month and year. We used conditional logistic regression models to analyze the data. RESULTS: We included a total of 190 115 patients with acute onset of symptomatic arrhythmia. Air pollution was associated with increased risk of onset of symptomatic arrhythmia within the first few hours of exposure; this risk attenuated substantially after 24 hours. An interquartile range increase in PM2.5, NO2, SO2 and CO in the first 24 hours after exposure (i.e., lag period 0-24 h) was associated with significantly higher odds of atrial fibrillation (1.7%-3.4%), atrial flutter (8.1%-11.4%) and supraventricular tachycardia (3.4%-8.9%). Exposure to PM2.5-10 was associated with significantly higher odds of atrial flutter (8.7%) and supraventricular tachycardia (5.4%), and exposure to ozone was associated with higher odds of supraventricular tachycardia (3.4%). The exposure-response relationships were approximately linear, without discernible concentration thresholds. INTERPRETATION: Exposure to air pollution was associated with the onset of symptomatic arrhythmia shortly after exposure. This finding highlights the importance of further reducing air pollution and taking prompt protective measures for susceptible populations during periods of elevated levels of air pollutants.

Low ambient temperature increases the risk and burden of atrial fibrillation episodes: A nationwide case-crossover study in 322 Chinese cities.

BACKGROUND: Non-optimum ambient temperature has recently been acknowledged as an independent risk factor for disease burden, but its impact on atrial fibrillation (AF) episodes was rarely evaluated. OBJECTIVES: To examine the associations between ambient non-optimum temperature and symptom onset of AF episodes and calculate the corresponding disease burden. METHODS: We conducted an individual-level, time-stratified, case-crossover analysis based on a nationwide registry, which comprises of 94,711 eligible AF patients from 1993 hospitals in 322 Chinese cities from January 2015 to December 2021. Multiple moving 24 h average temperatures prior to the symptom onset of AF episodes were calculated as lag days. The associations were analyzed using conditional logistic regression combined with distributed lag non-linear models with a duration of lag 0-7 days, after controlling for criteria air pollutants. Stratification analyses were performed to explore possible effect modifiers. RESULTS: There was a monotonically increasing relationship of AF onset risk with decreasing temperature. The excess AF risk occurred at lag 1 d and lasted for 5 days. Nationally, the cumulative relative risk of AF episode onset associated with extremely low temperature (-9.3 °C) over lag 0-7 d was 1.25 (95 % confidence interval: 1.08, 1.45), compared with the reference temperature (31.5 °C). The exposure-response curve was steeper in the south than in the north where there was levelling-off at lower temperature. Nationally, 7.59 % of acute AF episodes could be attributable to non-optimum temperatures. The attributable fraction was larger for southern residents, males and patients <65 years. CONCLUSION: This nationwide study provides novel and robust evidence that declining ambient temperature could increase the risk of AF episode onset. We also provide the first-hand evidence that a considerable proportion of acute AF episodes could be attributable to non-optimum temperatures.

Application of smart devices in investigating the effects of air pollution on atrial fibrillation onset.

Few studies have examined the link between short-term exposure to air pollutants and atrial fibrillation (AF) episodes. This study aims to examine the association of hourly criteria air pollutants with AF episodes. We employ a smart device-based photoplethysmography technology to screen AF from 2018 to 2021. Hourly concentrations of six criteria air pollutants are matched to the onset hour of AF for each participant. We adopt a time-stratified case-crossover design to capture the acute effects of air pollutants on AF episodes, using conditional logistic regression models. Subgroup analyses are conducted by age, gender, and season. A total of 11,906 episodes of AF are identified in 2976 participants from 288 Chinese cities. Generally, the strongest associations of air pollutants are present at lag 18-24 h, with positive and linear exposure-response relationships. For an interquartile range increase in inhalable particles, fine particles, nitrogen dioxide, and carbon monoxide, the odds ratio (OR) of AF is 1.19 [95% confidential interval (CI): 1.03, 1.37], 1.38 (95%CI: 1.14, 1.67), 1.60 (95%CI: 1.16, 2.20) and 1.48 (95%CI: 1.19, 1.84), respectively. The estimates are robust to the adjustment of co-pollutants, and they are larger in females, older people, and in cold seasons. There are insignificant associations for sulfur dioxide and ozone. This nationwide case-crossover study demonstrates robust evidence of significant associations between hourly exposure to air pollutants and the onset of AF episodes, which underscores the importance of ongoing efforts to further improve air quality as an effective target for AF prevention.

A multi-view latent variable model reveals cellular heterogeneity in complex tissues for paired multimodal single-cell data.

MOTIVATION: Single-cell multimodal assays allow us to simultaneously measure two different molecular features of the same cell, enabling new insights into cellular heterogeneity, cell development and diseases. However, most existing methods suffer from inaccurate dimensionality reduction for the joint-modality data, hindering their discovery of novel or rare cell subpopulations. RESULTS: Here, we present VIMCCA, a computational framework based on variational-assisted multi-view canonical correlation analysis to integrate paired multimodal single-cell data. Our statistical model uses a common latent variable to interpret the common source of variances in two different data modalities. Our approach jointly learns an inference model and two modality-specific non-linear models by leveraging variational inference and deep learning. We perform VIMCCA and compare it with 10 existing state-of-the-art algorithms on four paired multi-modal datasets sequenced by different protocols. Results demonstrate that VIMCCA facilitates integrating various types of joint-modality data, thus leading to more reliable and accurate downstream analysis. VIMCCA improves our ability to identify novel or rare cell subtypes compared to existing widely used methods. Besides, it can also facilitate inferring cell lineage based on joint-modality profiles. AVAILABILITY AND IMPLEMENTATION: The VIMCCA algorithm has been implemented in our toolkit package scbean (≥0.5.0), and its code has been archived at https://github.com/jhu99/scbean under MIT license. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Ambient temperature and ambulatory blood pressure: An hourly-level, longitudinal panel study.

BACKGROUND: Variations of blood pressure (BP) related to air temperature have been reported previously; however, no evidence is available regarding the association of hourly ambient temperature with ambulatory blood pressure. METHODS: We conducted a longitudinal panel study among 1895 patients from an outpatient department who received repeated ambulatory blood pressure monitoring in Urumqi, China between July 2020 and December 2021. We obtained hourly ambient temperature from the nearest monitoring station to the residential address, and measured 4 ambulatory blood pressure indicators. Linear mixed-effect model combined with distributed lag models were applied to investigate the cumulative associations of hourly temperature with BP. RESULTS: A total of 97,466 valid blood pressure measurements were evaluated. We observed almost linear and monotonically decreasing relationships between temperature and blood pressure. The effects occurred in the same hour, attenuated thereafter and became insignificant approximately 36 h. A 10 °C decrease in temperature was significantly associated with increments of 0.84 mmHg in systolic blood pressure, 0.56 mmHg in diastolic blood pressure, 1.38 mmHg in mean arterial pressure, and 0.66 mmHg in pulse pressure over lag 0 to 36 h. Stronger associations were found among patients of female sex, age between 18 and 65 years, overweight or obesity, minority, less education or in the cold season, as well as those without hypertension or with coronary heart disease, or did not take anti-hypertension medication. CONCLUSION: Our study provides robust evidence that hourly ambient temperature is inversely associated with ambulatory blood pressure. It also highlights a linear relationship between decreased ambient temperature and elevated BP, which may have implications for the prevention and management of hypertension in susceptible populations.

Deciphering the Efficacy and Mechanism of Astragalus membranaceus on High Altitude Polycythemia by Integrating Network Pharmacology and In Vivo Experiments.

Hypoxic exposure makes plateau migrators susceptible to high altitude polycythemia (HAPC). Astragalus membranaceus (AM) is an edible and medicinal plant with remarkable immunomodulatory activities. The purpose of this study was to discover if AM could be a candidate for the prevention of HAPC and its mechanism. Here, network pharmacology was applied to screen active compounds, key targets, and enriched pathways of AM in the treatment of HAPC. Molecular docking evaluated the affinity between compounds and core targets. Subsequently, the mechanisms of AM were further verified using the hypoxia exposure-induced mice model of HAPC. The network pharmacology analysis and molecular docking results identified 14 core targets of AM on HAPC, which were predominantly mainly enriched in the HIF-1 pathway. In the HAPC animal models, we found that AM inhibited the differentiation of hematopoietic stem cells into the erythroid lineage. It also suppressed the production of erythrocytes and hemoglobin in peripheral blood by reducing the expression of HIF-1α, EPO, VEGFA, and Gata-1 mRNA. Furthermore, AM downregulated the expression of IL-6, TNF-α, and IFN-γ mRNA, thereby alleviating organ inflammation. In conclusion, AM supplementation alleviates hypoxia-induced HAPC in mice, and TNF-α, AKT1, HIF-1α, VEGFA, IL-6, and IL-1B may be the key targets.

Low ambient temperature might trigger the symptom onset of pulmonary embolism: A nationwide case-crossover study at hourly level in China.

BACKGROUND: Pulmonary embolism (PE) is an important cause of death and its seasonality has long been observed. Very few epidemiological studies have explored the potential role of ambient temperature in PE symptom onset, especially at the hourly level. METHODS: We conducted a time-stratified case-crossover study among 17,903 PE patients with hourly onset of symptom from 1590 hospitals across China between January 2015 and September 2020. Conditional logistic regression model combined with distributed lag non-linear models were used to explore the associations between hourly ambient temperature and PE symptom onset. The attributable fractions due to non-optimum temperature were calculated. RESULTS: The exposure-response relationship curve was inverse and almost linear. Lower temperature was significantly associated with higher risk of PE symptom onset when temperature was below 18 °C. This risk occurred immediately at the same hour, attenuated thereafter, and became nonsignificant at approximately 72 h after exposure. Compared with the referent temperature (P99, 34.1 °C), the odds ratio of PE symptom onset associated with extremely low temperature (P1, -16.1 °C) over lag 0-72 h was 1.63 (95%CI: 1.23, 2.16). Low temperature may account for 16.19 % of the symptom onset nationally with higher proportion in the south of China. The effects were stronger in older adults, males, and cold seasons. CONCLUSIONS: We provided the first-hand robust evidence that transient exposure (at the hourly level) to low temperature might trigger the symptom onset of PE and constitute a considerable burden for PE patients. Targeted protections and health education are needed for susceptible populations.

Low temperature and temperature decline increase acute aortic dissection risk and burden: A nationwide case crossover analysis at hourly level among 40,270 patients.

Background: Acute aortic dissection (AAD) is a life-threatening cardiovascular emergency with high mortality, so identifying modifiable risk factors of AAD is of great public health significance. The associations of non-optimal temperature and temperature variability with AAD onset and the disease burden have not been fully understood. Methods: We conducted a time-stratified case-crossover study using a nationwide registry dataset from 1,868 hospitals in 313 Chinese cities. Conditional logistic regression and distributed lag models were used to investigate associations of temperature and temperature changes between neighboring days (TCN) with the hourly AAD onset and calculate the attributable fractions. We also evaluated the heterogeneity of the associations. Findings: A total of 40,270 eligible AAD cases were included. The exposure-response curves for temperature and TCN with AAD onset risk were both inverse and approximately linear. The risks were present on the concurrent hour (for temperature) or day (for TCN) and lasted for almost 1 day. The cumulative relative risks of AAD were 1.027 and 1.026 per 1°C lower temperature and temperature decline between neighboring days, respectively. The associations were significant during the non-heating period, but were not present during the heating period in cities with central heating. 23.13% of AAD cases nationwide were attributable to low temperature and 1.58% were attributable to temperature decline from the previous day. Interpretation: This is the largest nationwide study demonstrating robust associations of low temperature and temperature decline with AAD onset. We, for the first time, calculated the corresponding disease burden and further showed that central heating may be a modifier for temperature-related AAD risk and burden. Funding: This work was supported by the National Natural Science Foundation of China (92043301 and 92143301), Shanghai International Science and Technology Partnership Project (No. 21230780200), the Medical Research Council-UK (MR/R013349/1), and the Natural Environment Research Council UK (NE/R009384/1).

Non-optimum temperature increases risk and burden of acute myocardial infarction onset: A nationwide case-crossover study at hourly level in 324 Chinese cities.

Background: The associations of ambient temperature with acute myocardial infarction (AMI) have seldom been examined based on the time of symptom onset. Methods: We conducted a time-stratified case-crossover study among 1,046,773 eligible AMI patients from 2,093 hospitals in 324 Chinese cities from January 1, 2015 to June 30, 2021, after excluding those transferred from other hospitals or having not reported the time of symptom onset. Hourly exposure to ambient temperature was calculated as multiple moving 24-h averages (days) before hourly onset of AMI symptoms. Conditional logistic regression and distributed lag non-linear models with a duration of 0-21 days were used to estimate the cumulative associations of non-optimum temperature with AMI onset and the corresponding disease burden nationally. Subgroup analyses by region and period were conducted. Specifically, cities with and without centralized heating system were classified into heating and non-heating regions, respectively. The whole year in heating region was divided into heating and non-heating periods based on the duration of centralized heating in each city. Findings: Almost monotonically increasing risks were observed for both overall AMI and its two subtypes when ambient temperature declined. The effects of extremely low temperature occurred immediately on the concurrent day, and lasted up to almost 3 weeks. The excess risks of AMI onset associated with non-optimum ambient temperatures were observed during the whole year in the non-heating region and non-heating period in the heating region, but not during heating period. Specifically, odds ratios of AMI onset associated with extremely low temperature cumulated over 0-21 days were 1.24 (95% CI: 1.13-1.37), 1.46 (95% CI: 1.20-1.76), and 1.62 (95% CI: 1.46-1.81) in the heating region during non-heating period, in the non-heating region during winter and non-winter period, respectively. The heat effects on AMI onset were very modest and transient. Totally, 13.26% of AMI cases could be attributable to non-optimum temperatures nationally. The burden of AMI attributable to non-optimum temperature was much smaller in heating region than in non-heating region. Somewhat stronger effects were observed in females and patients aged older than 65. Interpretation: This nationwide study provided robust evidence that non-optimum ambient temperature may significantly trigger AMI onset, and for the first time estimated the disease burden after accounting for spatial and seasonal heterogeneity. Centralized heating might substantially mitigate AMI burden due to non-optimum temperature. Funding: Shanghai International Science and Technology Partnership Project, National Natural Science Foundation of China, Talent Training Program of Zhongshan Hospital, Fudan University.

Hourly Air Pollutants and Acute Coronary Syndrome Onset in 1.29 Million Patients.

BACKGROUND: Short-term exposure to ambient air pollution has been linked with daily hospitalization and mortality from acute coronary syndrome (ACS); however, the associations of subdaily (hourly) levels of criteria air pollutants with the onset of ACS and its subtypes have rarely been evaluated. METHODS: We conducted a time-stratified case-crossover study among 1 292 880 patients with ACS from 2239 hospitals in 318 Chinese cities between January 1, 2015, and September 30, 2020. Hourly concentrations of fine particulate matter (PM2.5), coarse particulate matter (PM2.5-10), nitrogen dioxide (NO2), sulfur dioxide (SO2), carbon monoxide (CO), and ozone (O3) were collected. Hourly onset data of ACS and its subtypes, including ST-segment-elevation myocardial infarction, non-ST-segment-elevation myocardial infarction, and unstable angina, were also obtained. Conditional logistic regressions combined with polynomial distributed lag models were applied. RESULTS: Acute exposures to PM2.5, NO2, SO2, and CO were each associated with the onset of ACS and its subtypes. These associations were strongest in the concurrent hour of exposure and were attenuated thereafter, with the weakest effects observed after 15 to 29 hours. There were no apparent thresholds in the concentration-response curves. An interquartile range increase in concentrations of PM2.5 (36.0 µg/m3), NO2 (29.0 µg/m3), SO2 (9.0 µg/m3), and CO (0.6 mg/m3) over the 0 to 24 hours before onset was significantly associated with 1.32%, 3.89%, 0.67%, and 1.55% higher risks of ACS onset, respectively. For a given pollutant, the associations were comparable in magnitude across different subtypes of ACS. NO2 showed the strongest associations with all 3 subtypes, followed by PM2.5, CO, and SO2. Greater magnitude of associations was observed among patients older than 65 years and in the cold season. Null associations of exposure to either PM2.5-10 or O3 with ACS onset were observed. CONCLUSIONS: The results suggest that transient exposure to the air pollutants PM2.5, NO2, SO2, or CO, but not PM2.5-10 or O3, may trigger the onset of ACS, even at concentrations below the World Health Organization air quality guidelines.

Fine particulate matter air pollution and subclinical cardiovascular outcomes: A longitudinal study in 15 Chinese cities.

AIMS: Although previous studies have linked short-term exposure to fine particulate matter (PM2.5) air pollution with various molecular biomarkers of cardiovascular system, limited evidence is available for indicators at clinical or subclinical levels. We examined the associations between short-term PM2.5 exposure and a range of clinical or subclinical indicators of cardiovascular health in general population. METHODS AND RESULTS: A longitudinal repeated-measure study was conducted among 247,640 participants who repeatedly visited health examination centers in 15 typical cities across China from 2013 to 2020. A total of 19 well-established indicators of cardiovascular risk or injury were evaluated and air quality data at nearest fixed-site monitors were collected. Linear mixed-effects models with distributed lag models were used to analyze the potentially lagged effects of PM2.5. The average daily PM2.5 concentration was 48 µg/m3 during the study period. PM2.5 exposure was associated with significant changes of 16 indicators with the effects generally peaked on lag 0 to 3 day. For an interquartile range (IQR) elevation (37 µg/m3) in PM2.5 concentrations over lag 0-7 day, the cumulative percentage changes were 0.50% to 1.27% in heart rates and blood pressure, 0.10% to 5.04% in inflammatory markers, -0.29% to 1.39% in blood viscosity parameters, -0.67% to 3.45% in blood lipids, 0.89% in blood homocysteine, 0.13% to 0.78% in myocardial enzymes, and 3.03% in pulse wave velocity. These associations were not substantially changed after adjusting concomitant exposures to gaseous pollutants. CONCLUSION: Short-term exposure to PM2.5 may induce early cardiovascular effects in general population, including acute inflammation, myocardial injury, increased blood viscosity, vascular stiffness and hyperlipidemia.

Single-cell RNA sequencing to track novel perspectives in HSC heterogeneity.

As the importance of cell heterogeneity has begun to be emphasized, single-cell sequencing approaches are rapidly adopted to study cell heterogeneity and cellular evolutionary relationships of various cells, including stem cell populations. The hematopoietic stem and progenitor cell (HSPC) compartment contains HSC hematopoietic stem cells (HSCs) and distinct hematopoietic cells with different abilities to self-renew. These cells perform their own functions to maintain different hematopoietic lineages. Undeniably, single-cell sequencing approaches, including single-cell RNA sequencing (scRNA-seq) technologies, empower more opportunities to study the heterogeneity of normal and pathological HSCs. In this review, we discuss how these scRNA-seq technologies contribute to tracing origin and lineage commitment of HSCs, profiling the bone marrow microenvironment and providing high-resolution dissection of malignant hematopoiesis, leading to exciting new findings in HSC biology.

Evaluation of pharmacist-led telemedicine medication management for hypertension established patients during COVID-19 pandemic: A pilot study.

Aim: To evaluate the impact of a telemedicine medication management service in patients with hypertension. Methods: Participants were allocated to either a telemedicine service (N = 173) or usual care (UC) (N = 179). The primary outcome was blood pressure (BP) reduction from baseline to the 6-month follow-up visit, the proportion of the target BP achievement, overall adherence to prescribed medication as well as a composite of non-fatal stroke, non-fatal myocardial infarction and cardiovascular death. Results: At 6 months, BP was controlled in 89.6% (n = 155) of intervention patients and 78.8% (n = 141) of UC patients (OR = 1.14, 95% CI = 1.04-1.25, P = 0.006), giving a mean difference of -6.0 (-13.0 to -2.5 mmHg) and -2.0 mmHg (-4.0 to -0.1 mmHg) in SBP and DBP, respectively. 17.9% (n = 31) of the patients in the intervention group were non-adherent with medications, compared with 29.1% (n = 52) in the UC group (P = 0.014). The composite clinical endpoints were reached by 2.9% in the intervention group and 4.5% in the control group with no significant differences (OR = 1.566, 95% CI = 0.528-4.646). Conclusion: Telemedicine medication management for hypertension management had led to better BP control and medication adherence improvement than UC during COVID-19 epidemic, resulting in a reduction of overall adverse cardiovascular events occurrence.

A versatile and scalable single-cell data integration algorithm based on domain-adversarial and variational approximation.

Single-cell technologies provide us new ways to profile transcriptomic landscape, chromatin accessibility, spatial expression patterns in heterogeneous tissues at the resolution of single cell. With enormous generated single-cell datasets, a key analytic challenge is to integrate these datasets to gain biological insights into cellular compositions. Here, we developed a domain-adversarial and variational approximation, DAVAE, which can integrate multiple single-cell datasets across samples, technologies and modalities with a single strategy. Besides, DAVAE can also integrate paired data of ATAC profile and transcriptome profile that are simultaneously measured from a same cell. With a mini-batch stochastic gradient descent strategy, it is scalable for large-scale data and can be accelerated by GPUs. Results on seven real data integration applications demonstrated the effectiveness and scalability of DAVAE in batch-effect removing, transfer learning and cell-type predictions for multiple single-cell datasets across samples, technologies and modalities. Availability: DAVAE has been implemented in a toolkit package "scbean" in the pypi repository, and the source code can be also freely accessible at https://github.com/jhu99/scbean. All our data and source code for reproducing the results of this paper can be accessible at https://github.com/jhu99/davae_paper.

Effective and scalable single-cell data alignment with non-linear canonical correlation analysis.

Data alignment is one of the first key steps in single cell analysis for integrating multiple datasets and performing joint analysis across studies. Data alignment is challenging in extremely large datasets, however, as the major of the current single cell data alignment methods are not computationally efficient. Here, we present VIPCCA, a computational framework based on non-linear canonical correlation analysis for effective and scalable single cell data alignment. VIPCCA leverages both deep learning for effective single cell data modeling and variational inference for scalable computation, thus enabling powerful data alignment across multiple samples, multiple data platforms, and multiple data types. VIPCCA is accurate for a range of alignment tasks including alignment between single cell RNAseq and ATACseq datasets and can easily accommodate millions of cells, thereby providing researchers unique opportunities to tackle challenges emerging from large-scale single-cell atlas.

The acute effects of particulate matter air pollution on ambulatory blood pressure: A multicenter analysis at the hourly level.

Epidemiological evidence from ambulatory blood pressure monitoring is needed to clarify the associations of particulate air pollution with blood pressure and potential lag patterns. We examined the associations of fine and coarse particulate matter (PM2.5, PM2.5-10) with ambulatory blood pressure among 7108 non-hypertensive participants from 7 Chinese cities between April 2016 and November 2020. Hourly concentrations of PM2.5 and PM2.5-10 were obtained from the nearest monitoring stations. We measured four blood pressure indicators, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP) and pulse pressure (PP). Linear mixed-effect models combined with distributed lag models were applied to analyze the data. Generally, very short-term exposure to PM2.5 was significantly associated with elevated blood pressure. These effects occurred on the same hour of blood pressure measurement, attenuated gradually, and became insignificant approximately at lag 12 h. An interquartile range (IQR, 33 µg/m3) increase of PM2.5 was significantly associated with cumulative increments of 0.58 mmHg for SBP, 0.31 mmHg for DBP, 0.38 mmHg for MAP, and 0.33 mmHg for PP over lag 0 to 12 h. The exposure-response relationship curves were almost linear without thresholds, but tended to be flat at very high concentrations. No significant associations were observed for PM2.5-10. Our study provides independent and robust associations between transient PM2.5 exposure and elevated blood pressure within the first 12 h, and reinforces the evidence for a linear and non-threshold exposure-response relationship, which may have implications for blood pressure management and hypertension prevention in susceptible population.