VIBRANT: spectral profiling for single-cell drug responses.

High-content cell profiling has proven invaluable for single-cell phenotyping in response to chemical perturbations. However, methods with improved throughput, information content and affordability are still needed. We present a new high-content spectral profiling method named vibrational painting (VIBRANT), integrating mid-infrared vibrational imaging, multiplexed vibrational probes and an optimized data analysis pipeline for measuring single-cell drug responses. Three infrared-active vibrational probes were designed to measure distinct essential metabolic activities in human cancer cells. More than 20,000 single-cell drug responses were collected, corresponding to 23 drug treatments. The resulting spectral profile is highly sensitive to phenotypic changes under drug perturbation. Using this property, we built a machine learning classifier to accurately predict drug mechanism of action at single-cell level with minimal batch effects. We further designed an algorithm to discover drug candidates with new mechanisms of action and evaluate drug combinations. Overall, VIBRANT has demonstrated great potential across multiple areas of phenotypic screening.

Mid-infrared metabolic imaging with vibrational probes.

Understanding metabolism is indispensable in unraveling the mechanistic basis of many physiological and pathological processes. However, in situ metabolic imaging tools are still lacking. Here we introduce a framework for mid-infrared (MIR) metabolic imaging by coupling the emerging high-information-throughput MIR microscopy with specifically designed IR-active vibrational probes. We present three categories of small vibrational tags including azide bond, 13C-edited carbonyl bond and deuterium-labeled probes to interrogate various metabolic activities in cells, small organisms and mice. Two MIR imaging platforms are implemented including broadband Fourier transform infrared microscopy and discrete frequency infrared microscopy with a newly incorporated spectral region (2,000-2,300 cm-1). Our technique is uniquely suited to metabolic imaging with high information throughput. In particular, we performed single-cell metabolic profiling including heterogeneity characterization, and large-area metabolic imaging at tissue or organ level with rich spectral information.

Optimizing multicontrast MRI reconstruction with shareable feature aggregation and selection.

This paper proposes a new method for optimizing feature sharing in deep neural network-based, rapid, multicontrast magnetic resonance imaging (MC-MRI). Using the shareable information of MC images for accelerated MC-MRI reconstruction, current algorithms stack the MC images or features without optimizing the sharing protocols, leading to suboptimal reconstruction results. In this paper, we propose a novel feature aggregation and selection scheme in a deep neural network to better leverage the MC features and improve the reconstruction results. First, we propose to extract and use the shareable information by mapping the MC images into multiresolution feature maps with multilevel layers of the neural network. In this way, the extracted features capture complementary image properties, including local patterns from the shallow layers and semantic information from the deep layers. Then, an explicit selection module is designed to compile the extracted features optimally. That is, larger weights are learned to incorporate the constructive, shareable features; and smaller weights are assigned to the unshareable information. We conduct comparative studies on publicly available T2-weighted and T2-weighted fluid attenuated inversion recovery brain images, and the results show that the proposed network consistently outperforms existing algorithms. In addition, the proposed method can recover the images with high fidelity under 16 times acceleration. The ablation studies are conducted to evaluate the effectiveness of the proposed feature aggregation and selection mechanism. The results and the visualization of the weighted features show that the proposed method does effectively improve the usage of the useful features and suppress useless information, leading to overall enhanced reconstruction results. Additionally, the selection module can zero-out repeated and redundant features and improve network efficiency.

Panax Notoginseng Saponins Protect H9c2 Cells From Hypoxia-reoxygenation Injury Through the Forkhead Box O3a Hypoxia-inducible Factor-1 Alpha Cell Signaling Pathway.

ABSTRACT: Panax notoginseng saponins (PNS) are commonly used in the treatment of cardiovascular diseases. Whether PNS can protect myocardial ischemia-reperfusion injury by regulating the forkhead box O3a hypoxia-inducible factor-1 alpha (FOXO3a/HIF-1α) cell signaling pathway remains unclear. The purpose of this study was to investigate the protective effect of PNS on H9c2 cardiomyocytes through the FOXO3a/HIF-1α cell signaling pathway. Hypoxia and reoxygenation of H9C2 cells were used to mimic MIRI in vitro, and the cells were treated with PNS, 2-methoxyestradiol (2ME2), and LY294002." Cell proliferation, lactate dehydrogenase, and malonaldehyde were used to evaluate the degree of cell injury. The level of reactive oxygen species was detected with a fluorescence microscope. The apoptosis rate was detected by flow cytometry. The expression of autophagy-related proteins and apoptosis-related proteins was detected by western blot assay. PNS could reduce H9c2 hypoxia-reoxygenation injury by promoting autophagy and inhibiting apoptosis through the HIF-1α/FOXO3a cell signaling pathway. Furthermore, the protective effects of PNS were abolished by HIF-1α inhibitor 2ME2 and PI3K/Akt inhibitor LY294002. PNS could reduce H9c2 hypoxia-reoxygenation injury by promoting autophagy and inhibiting apoptosis through the HIF-1α/FOXO3a cell signaling pathway.

Panax Notoginseng Saponins Attenuate Myocardial Ischemia-Reperfusion Injury Through the HIF-1α/BNIP3 Pathway of Autophagy.

BACKGROUND AND OBJECTIVE: Panax Notoginseng Saponins (PNS) is a formula of Chinese medicine commonly used for treating ischemia myocardial in China. However, its mechanism of action is yet unclear. This study investigated the effect and the mechanism of PNS on myocardial ischemia-reperfusion injury (MIRI) through the hypoxia-inducible factor 1α (HIF-1α)/bcl-2/adenovirus E1B19kDa-interacting protein3 (BNIP3) pathway of autophagy. METHODS: We constructed a rat model of myocardial injury and compared among 4 groups (n = 10, each): the sham-operated group (Sham), the ischemia-reperfusion group (IR), the PNS low-dose group, and the PNS high-dose group were pretreated with PNS (30 and 60 mg/kg, respectively). Serum creatine kinase, malonaldehyde (MDA), lactate dehydrogenase, myocardial tissue superoxide dismutase, and reactive oxygen species were detected in rats with myocardial ischemia-reperfusion after the intervention of PNS. The rat myocardial tissue was examined using hematoxylin and eosin (H&E) staining, and the mitochondria of myocardial cells were observed using transmission electron microscopy. The expressions of microtubule-associated protein light chain 3 (LC3), HIF-1α, BNIP3, Beclin-1, and autophagy-related gene-5 (Atg5) in rat myocardial tissue were detected using Western blotting. RESULTS: The results showed that PNS was significantly protected against MIRI, as evidenced by the decreasing in the concentration of serum CK, MDA, lactate dehydrogenase, and myocardial tissue superoxide dismutase, reactive oxygen species, the attenuation of myocardial tissue histopathological changes and the mitochondrial damages of myocardial cells, and the increase of mitochondria autophagosome in myocardial cells. In addition, PNS significantly increased the expression of LC3 and the ratio of LC3II/LC3I in rat myocardial tissue. Moreover, PNS significantly increased the expression of HIF-1α, BNIP3, Atg5, and Beclin-1 in rat myocardial tissue. CONCLUSIONS: The protective effect of PNS on MIRI was mainly due to its ability to enhance the mitochondrial autophagy of myocardial tissue through the HIF-1α/BNIP3 pathway.

Peroxidase-Mimicking Nanozyme with Enhanced Activity and High Stability Based on Metal-Support Interactions.

Peroxidase-mimicking nanozymes offer unique advantages in terms of high stability and low cost over natural peroxidase for applications in bioanalysis, biomedicine, and the treatment of pollution. However, the design of high-efficiency peroxidase-mimicking nanozymes remains a great challenge. In this study, we adopted a structural-design approach through hybridization of cube-CeO2 and Pt nanoparticles to create a new peroxidase-mimicking nanozyme with high efficiency and excellent stability. Relative to pure cube-CeO2 and Pt nanoparticles, the as-hybridized Pt/cube-CeO2 nanocomposites display much improved activities because of the strong metal-support interaction. Meanwhile, the nanocomposites also maintain high catalytic activity after long-term storage and multiple recycling. Based on their excellent properties, Pt/cube-CeO2 nanocomposites were used to construct high-performance colorimetric biosensors for the sensitive detection of metabolites, including H2 O2 and glucose. Our findings highlight opportunities for the development of high-efficiency peroxidase-mimicking nanozymes with potential applications such as diagnostics, biomedicine, and the treatment of pollution.

Emodin, A Chinese Herbal Medicine, Inhibits Reoxygenation-Induced Injury in Cultured Human Aortic Endothelial Cells by Regulating the Peroxisome Proliferator-Activated Receptor-γ (PPAR-γ) and Endothelial Nitric Oxide Synthase (eNOS) Signaling Pathway.

BACKGROUND Ischemia-reperfusion injury is associated with vascular dysfunction. The aim of this study was to investigate the role of emodin, a Chinese herbal medicine, in hypoxia-reoxygenation injury in cultured human aortic endothelial cells (HAECs) and its effects on the expression of the peroxisome proliferator-activated receptor-γ (PPAR-γ) and endothelial nitric oxide synthase (eNOS) signaling pathway. MATERIAL AND METHODS An in vitro hypoxia-reoxygenation model used cultured human aortic endothelial cells (HAECs). A colorimetric method evaluated the activity of peroxisome proliferator-activated receptor-γ (PPAR-γ). Phosphorylation of PPAR-γ and endothelial nitric oxide synthase (eNOS) were measured by Western blotting. Expression of inflammatory cytokines, tumor necrosis factor (TNF)-α, interleukin (IL)-6 and IL-8 were evaluated by enzyme-linked immunosorbent assay (ELISA) and Western blotting. Nitric oxide (NO) production was detected by diaminofluorescein-FM diacetate (DAF-FM DA) fluorescence. Immunoprecipitation was used to evaluate the molecular coupling of heat shock protein (HSP)90 and eNOS. RESULTS Hypoxia-reoxygenation injury of HAECs reduced the activity and phosphorylation of PPAR-γ, and eNOS, NO production, and HSP90/eNOS molecular coupling in a time-dependent manner. Hypoxia-reoxygenation increased the levels of inflammatory cytokines TNF-α, IL-6, and IL-8 in a time-dependent manner. Emodin treatment recovered PPAR-γ activity and phosphorylation, eNOS phosphorylation, and HSP90/eNOS coupling in HAECS in a concentration-dependent manner, which was reversed by the PPAR-γ inhibitor GW9662, and the eNOS inhibitor, L-NAME. The recovery of HSP90/eNOS coupling by emodin was impaired by GW9662 treatment. CONCLUSIONS An in vitro hypoxia-reoxygenation (ischemia-reperfusion injury) model of induction of endothelial cell inflammatory mediators showed that emodin recovered the PPAR-γ and eNOS pathway activity.

Distribution characteristics of different human papillomavirus genotypes in women in Wuhan, China.

BACKGROUND: Human papillomaviruses (HPVs) are strongly associated with the development of cervical carcinoma, and the distribution of HPV genotypes varies regionally. METHODS: To investigate the distribution characteristics of different genotypes of HPV infection in women in Wuhan, China, a total of 13 775 patients were enrolled over 2 years. RESULTS: Of these, 2436 patients were infected with HPVs, and the total infection rate was 17.68%. The infection rate of high-risk HPV (HR-HPV) was significantly higher (13.96%) than that of single low-risk HPV (LR-HPV; 3.72%). Among the HR-HPV infections, the most common genotype was HPV 52 with an infection rate of 4.23%, followed by HPVs 16, 58, 39, and 51. The most common LR-HPV genotype was HPV 81, followed by HPVs 6, 11, and 44. Patients under the age of 25 years were found to have the highest HPV infection rate (P < .05). After the age range of 51-55 years, a downward trend in total HPVs and HR-HPVs was observed. The HPV infection rate for a single genotype was higher than that for multiple HPVs (P < .01), and the detection rates in summer and winter were significantly higher than those in spring and autumn. CONCLUSIONS: The results demonstrate that the distribution characteristics of various HPV genotype infections are associated with region and age and may be related to season. These data could be the basis for further epidemiological analysis into the control and prevention of HPV infection in this region.

Simultaneous Visualization and Quantitation of Multiple Steroid Hormones Based on Signal-Amplified Biosensing with Duplex Molecular Recognition.

The simultaneous quantitation of multiple steroid hormones in real time is of great importance in medical diagnosis. In this study, a portable hormone biosensor based on duplex molecular recognition coupled with a signal-amplified substrate was successfully developed for the simultaneous visualization and quantitation of multiple steroid hormones. Aptamer-functionalized upconversion nanoparticles (UCNPs) with different emission peaks are immobilized on the photonic crystal (PC) substrate as the nanoprobes, leading to the specific and simultaneous assay of multiple steroid hormones. Coupled with the luminescence-enhanced effect of the PC substrate, nanomolar quantification limits of multiple hormones are achieved. This well-designed biosensor is also promising in the quantification of multiple hormones in serum samples. The amplified luminescence signals can be visualized with the naked eye and captured by an unmodified phone camera. This hormone quantitation biosensor exhibits the advantages of multi-detection, visualization, high sensitivity, and selectivity for potential applications in clinical disease diagnosis.

Possible mechanism of PNS protection against cisplatin-induced nephrotoxicity in rat models.

This study investigates the mechanism of the protective effect of Panax notoginsenosides (PNS) against cisplatin-induced nephrotoxicity via the hypoxia inducible factor 1 (HIF-1)/Bcl-2/adenovirus E1B 19 kDa-interacting protein 3 (BNIP3) pathway of autophagy. The rats underwent intraperitoneal injection with a single dose of cisplatin and a subset of rats were also intraperitoneally injected with 31.35 mg/kg PNS once a day. After 24 h exposure to cisplatin, the concentrations of urinary N-acetyl-ß-D-glucosaminidase (NAG), blood urea nitrogen (BUN) and serum creatinine (Scr) were determined. The rat renal tissue was examined using H&E-staining, and the mitochondria of renal tubular epithelial cells were observed using transmission electron microscopy. The expressions of microtubule-associated protein-1 light chain (LC)3, autophagy-related gene (Atg)5, Beclin-1 and BNIP3 in rat renal tissue were detected using western blotting. The expression of HIF-1 was detected by immunohistochemistry. The results showed that PNS significantly protected against cisplatin-induced nephrotoxicity, as evidenced by decreasing the concentration of blood BUN and Scr, the attenuation of renal histopathological changes and the mitochondrial damages of renal cells, and the increase of mitochondria autophagosome in renal tubular epithelial cells. Additionally, PNS significantly increased the expression of LC3 and the ratio of LC3II/LC3I in rat renal tissue. Moreover, PNS significantly increased the expression of HIF-1α, BNIP3, Atg5 and Beclin-1 in rat renal tissue. In conclusion, the protective effect of PNS on cisplatin-induced nephrotoxicity was mainly due to its ability to enhancing the mitochondrial autophagy of renal tissue via the HIF-1α/BNIP3 pathway, and here is the first demonstration about it.

Extracellular polymeric substances and dewaterability of waste activated sludge during anaerobic digestion.

Anaerobic digestion of waste activated sludge was conducted to gain insight into the mechanisms underlying change in sludge dewaterability during its anaerobic digestion. Unexpectedly, the results indicated that sludge dewatering properties measured by capillary suction time only deteriorated after 10 days of anaerobic digestion, after which dewaterability recovered and remained stable. The loosely bound extracellular polymeric substance (LB-EPS) content increased three-fold after 20 days of anaerobic digestion, and did not change significantly during the remaining 30 days. The tightly bound EPS (TB-EPS) content reduced slightly after 20 days of anaerobic digestion, and stabilized during the last 30 days. Polysaccharides (PS) and proteins (PN) content in LB-EPS increased after 10 days of anaerobic digestion. However, PS and PN contents in TB-EPS decreased slightly. The relationship analysis showed that only LB-EPS correlated with dewaterability of the sludge during anaerobic digestion.

Identifying Links Between Productivity and Biobehavioral Rhythms Modeled From Multimodal Sensor Streams: Exploratory Quantitative Study.

BACKGROUND: Biobehavioral rhythms are biological, behavioral, and psychosocial processes with repeating cycles. Abnormal rhythms have been linked to various health issues, such as sleep disorders, obesity, and depression. OBJECTIVE: This study aims to identify links between productivity and biobehavioral rhythms modeled from passively collected mobile data streams. METHODS: In this study, we used a multimodal mobile sensing data set consisting of data collected from smartphones and Fitbits worn by 188 college students over a continuous period of 16 weeks. The participants reported their self-evaluated daily productivity score (ranging from 0 to 4) during weeks 1, 6, and 15. To analyze the data, we modeled cyclic human behavior patterns based on multimodal mobile sensing data gathered during weeks 1, 6, 15, and the adjacent weeks. Our methodology resulted in the creation of a rhythm model for each sensor feature. Additionally, we developed a correlation-based approach to identify connections between rhythm stability and high or low productivity levels. RESULTS: Differences exist in the biobehavioral rhythms of high- and low-productivity students, with those demonstrating greater rhythm stability also exhibiting higher productivity levels. Notably, a negative correlation (C=-0.16) was observed between productivity and the SE of the phase for the 24-hour period during week 1, with a higher SE indicative of lower rhythm stability. CONCLUSIONS: Modeling biobehavioral rhythms has the potential to quantify and forecast productivity. The findings have implications for building novel cyber-human systems that align with human beings' biobehavioral rhythms to improve health, well-being, and work performance.

Normal saline: Past, present, and future.

Normal saline (NS) is the most widely used agent in the medical field. However, from its origin to its widespread application, it remains a mystery. Moreover, there is an ongoing debate on whether its existence is reasonable, harmful to the human body, or will still exist in the future. The current review traces back to the origins of NS and provides a brief overview of the current situation of infusion. The purpose may shed some light on the possibility of the existence of NS in the future by elaborating on the origin of NS and the research status of the impact of NS on the human body.

The mediation role of resilience and postpartum traumatic stress disorder on parental attachment and the maternal-infant bonding.

AIMS: This study aimed to evaluate the correlation between parental attachment, resilience, postpartum traumatic stress disorder (PTSD), and maternal-infant bonding at 1 to 3 months postpartum. The mediation effect of resilience and PTSD on the postpartum parental attachment and maternal-infant bond was also evaluated. DESIGN: A cross-sectional research design was used. METHODS: A total of 400 postpartum women examined at a tertiary hospital in Wuhan from January 2021 to June 2021 were enrolled in the study. At about 1 to 3 months after giving birth, the women were asked to complete the Postpartum Bonding Questionnaire (PBQ), Connor-Davidson Resilience scale(CD-RISC), PTSD CheckList-Civilian version (PCL-C), and the Parental Bonding Instrument (PBI). The data were summarized using descriptive statistics. Mediation analyse and the Spearman correlation (r) were used to correlate the resilience and PTSD questionnaire scores. RESULTS: The care attachment dimension was significantly associated with resilience (r = 0.24, p < 0.01), PTSD (r = - 0.27, p < 0.01), and maternal-infant bonding (r = 0.10, p < 0.01), and the overprotection attachment dimension was significantly associated with resilience (r = - 0.11, p < 0.01), PTSD (r = 0.33, p < 0.01), and maternal-infant bonding (r = 0.16, p < 0.01). Resilience and PTSD can mediate the relationship between attachment and maternal-infant bonding. CONCLUSION: Parental attachment, resilience, and PTSD significantly affect maternal-infant bonding at 1 to 3 months postpartum. IMPACT: This study demonstrated that new interventions aimed at addressing PTSD symptoms and improving resilience might increase parental attachment and maternal-infant bonding after birth. However, further research is required to evaluate the success of these interventions.

Reduced nuclear export of HuR mRNA by HuR is linked to the loss of HuR in replicative senescence.

The RNA-binding protein, HuR, associates with the HuR mRNA, but the consequences of this interaction are unknown. Here, we use human diploid fibroblasts (HDFs) and cervical carcinoma cells to study this regulatory paradigm. Ectopic overexpression of HuR potently enhanced the translation and cytoplasmic levels of endogenous HuR, but did not affect HuR mRNA levels. Inhibition of CRM1 function by Lemptomycin B or by knockdown of CRM1 greatly diminished the cytoplasmic levels of endogenous HuR mRNA and hence blocked the induction of endogenous HuR by exogenous HuR. Further studies showed that HuR interacted with the 3'-untranslated region (UTR) of HuR and that overexpression of HuR increased the cytoplasmic levels of a chimeric luciferase-HuR 3'-UTR reporter transcript, as well as luciferase activity; conversely, HuR knockdown reduced both parameters. Moreover, the loss of HuR in senescent, late-passage HDFs was accompanied by a reduced cytoplasmic presence of endogenous HuR mRNA, ectopic Luc-HuR-3'UTR reporter transcript, and luciferase activity relative to what was observed in young, early-passage cells. Our results reveal a positive feedback mechanism for the regulation of HuR, which may play an important role in the regulation of HuR during replicative senescence.

Towards Mapping Mouse Metabolic Tissue Atlas by Mid-Infrared Imaging with Heavy Water Labeling.

Understanding metabolism is of great significance to decipher various physiological and pathogenic processes. While great progress has been made to profile gene expression, how to capture organ-, tissue-, and cell-type-specific metabolic profile (i.e., metabolic tissue atlas) in complex mammalian systems is lagging behind, largely owing to the lack of metabolic imaging tools with high resolution and high throughput. Here, the authors applied mid-infrared imaging coupled with heavy water (D2 O) metabolic labeling to a scope of mouse organs and tissues. The premise is that, as D2 O participates in the biosynthesis of various macromolecules, the resulting broad C-D vibrational spectrum should interrogate a wide range of metabolic pathways. Applying multivariate analysis to the C-D spectrum, the authors successfully identified both inter-organ and intra-tissue metabolic signatures of mice. A large-scale metabolic atlas map between different organs from the same mice is thus generated. Moreover, leveraging the power of unsupervised clustering methods, spatially-resolved metabolic signatures of brain tissues are discovered, revealing tissue and cell-type specific metabolic profile in situ. As a demonstration of this technique, the authors captured metabolic changes during brain development and characterized intratumoral metabolic heterogeneity of glioblastoma. Altogether, the integrated platform paves a way to map the metabolic tissue atlas for complex mammalian systems.

Integrative analysis of DNA methylation and gene expression reveals key molecular signatures in acute myocardial infarction.

BACKGROUNDS: Acute myocardial infarction (AMI) has been one of the most fatal diseases among all types of heart diseases due to its rapid onset and high rates of fatality. Understanding accurately how multi-omics molecular features change at the early stage of AMI is crucial for its treatment. Currently, the changes involved in DNA methylation modification and gene expression of multiple genes have remained unexplored. RESULTS: We used the RNA-seq and MeDIP-seq on heart tissues from AMI mouse models at series of time points (Sham, AMI 10-min, 1-h, 6-h, 24-h and 72-h), to comprehensively describe the transcriptome and genome-wide DNA methylation changes at above time points. We identified 18814, 18614, 23587, 26018 and 33788 differential methylation positions (DMPs) and 123, 135, 731, 1419 and 2779 differentially expressed genes (DEGs) at 10-min, 1-h, 6-h, 24-h and 72-h AMI, respectively, compared with the sham group. Remarkably, the 6-h AMI with the drastic changes of DEGs and a large number of enriched functional pathways in KEGG may be the most critical stage of AMI process. The 4, 9, 40, 26, and 183 genes were further identified at each time point, based on the negative correlation (P < 0.05) between the differential mRNA expression and the differential DNA methylation. The mRNA and the promoter methylation expressions of five genes (Ptpn6, Csf1r, Col6a1, Cyba, and Map3k14) were validated by qRT-PCR and BSP methods, and the mRNA expressions were further confirmed to be regulated by DNA methylation in cardiomyocytes in vitro. CONCLUSIONS: Our findings profiled the molecular variations from the perspective of DNA methylation in the early stage of AMI and provided promising epigenetic-based biomarkers for the early clinical diagnosis and therapeutic targets of AMI.

Effect of aerobic training on exercise capacity and quality of life in patients older than 75 years with acute coronary syndrome undergoing percutaneous coronary intervention.

BACKGROUND: Limited clinical studies are available on early exercise-based cardiac rehabilitation in elderly acute coronary syndrome (ACS) patients. OBJECTIVE: To evaluate the effect of aerobic exercise on exercise capacity and quality of life (QoL) in such patients. METHODS: Seventy elderly patients with ACS undergoing percutaneous coronary intervention in Zhejiang Hospital during August 2016-June 2017 were randomly divided into the control (n = 35) or cardiac rehabilitation group (CR, n = 35). The control group was treated with standard medical treatments without exercise, whereas the CR group was treated with standard medical treatments and exercise-based cardiac rehabilitation. General information, cardiopulmonary exercise test (CPET) results, responses to QoL and mental health questionnaires, and clinical outcomes and safety were collected. RESULTS: The CR group safely finished CPET and the 12-week exercise-based cardiac rehabilitation. After the 12-week intervention, the CR group showed significant differences in maximal oxygen uptake (VO2max) and greater improvements in VO2max, compared with the control group. The CR group showed statistically significant differences in QoL and mental health compared with the control group. CONCLUSION: CPET-based exercise in cardiac rehabilitation can safely increase exercise capacity and QoL in such patients.

Genetic identification of tissues and cell types underlying attention-deficit/hyperactivity disorder.

Background: Genome-wide association studies (GWASs) have identified numerous genetic variants associated with attention-deficit/hyperactivity disorder (ADHD), which is considered highly genetically heritable. However, because most of the variants located in the non-coding region of the human genome, the onset of ADHD requires further exploration. Methods: The risk genes involved in ADHD were identified by integrating GWAS summary data and expression quantitative trait locus (eQTL) data using summary-data-based Mendelian randomization (SMR) method. We then used a stratified linkage disequilibrium score regression (LDSR) method to estimate the contribution of ADHD-relevant tissues to its heritability to screen out disease-relevant tissues. To determine the ADHD-relevant cell types, we used an R package for expression-weighted cell type enrichment (EWCE) analysis. Results: By integrating the brain eQTL data and ADHD GWAS data using SMR, we identified 247 genes associated with ADHD. The LDSR applied to specifically expressed genes results showed that the ADHD risk genes were mainly enriched in brain tissue, especially in the mesencephalon, visual cortex, and frontal lobe regions. Further cell-type-specific analysis suggested that ADHD risk genes were highly expressed in excitatory neurons. Conclusion: The study showed that the etiology of ADHD is associated with excitatory neurons in the midbrain, visual cortex, and frontal lobe regions.

An Approach for Deep Learning in ECG Classification Tasks in the Presence of Noisy Labels.

Cardiovascular disease (CVD) is a serial of diseases with global leading causes of death. Electrocardiogram (ECG) is the most commonly used basis for CVD diagnosis due to its low cost and no injury. Due to the great performance shown in classification tasks with large-scale data sets, deep learning has been widely applied in ECG diagnosis. Manual labeling is a time-consuming and labor-intensive job, which makes it error-prone and easy to labeled wrongly. These noisy labels cause deterioration in performance since deep neural network is easy to over-fitting with noisy labels. However, currently, only limited studies have been concerned with this problem. To alleviate the performance degradation caused by noisy labels, we come up with an optimization method combining data clean and anti-noise loss function. Our method filters the noisy data by data-clean method, followed by training the network with boot-hard loss function. The experiment is carried on MIT-BIH arrhythmia database and we take a 1-D CNN model for test. The result indicates that our optimization method can produce an effective improvement for noisy label problems when the proportion of incorrect labels ranging from 10% to 50%.Clinical Relevance- The proposed algorithm can be potentially applied to deal with the noisy label problem in ECG diagnosis task.