Application of Deep Learning on Single-cell RNA Sequencing Data Analysis: A Review.

Single-cell RNA sequencing (scRNA-seq) has become a routinely used technique to quantify the gene expression profile of thousands of single cells simultaneously. Analysis of scRNA-seq data plays an important role in the study of cell states and phenotypes, and has helped elucidate biological processes, such as those occurring during the development of complex organisms, and improved our understanding of disease states, such as cancer, diabetes, and coronavirus disease 2019 (COVID-19). Deep learning, a recent advance of artificial intelligence that has been used to address many problems involving large datasets, has also emerged as a promising tool for scRNA-seq data analysis, as it has a capacity to extract informative and compact features from noisy, heterogeneous, and high-dimensional scRNA-seq data to improve downstream analysis. The present review aims at surveying recently developed deep learning techniques in scRNA-seq data analysis, identifying key steps within the scRNA-seq data analysis pipeline that have been advanced by deep learning, and explaining the benefits of deep learning over more conventional analytic tools. Finally, we summarize the challenges in current deep learning approaches faced within scRNA-seq data and discuss potential directions for improvements in deep learning algorithms for scRNA-seq data analysis.

Sodium Reduction in Restaurant Food: A Randomized Controlled Trial in China.

Restaurant food is one of the important sources of sodium intake in China. We aimed to determine whether a restaurant-based comprehensive intervention program may induce lower sodium content in restaurant food. A randomized controlled trial was implemented between 2019 and 2020 in 192 restaurants in China. After baseline assessment, the restaurants were randomly assigned to either an intervention or a control group (1:1). Comprehensive activities designed for intervention restaurants were conducted for one year. The primary outcome was the difference in change of sodium content estimated by the mean values of five best-selling dishes for each restaurant, from baseline to the end of the trial between groups. In total, 66 control restaurants and 80 intervention restaurants completed the follow-up assessment. The average sodium content of dishes at baseline was 540.9 ± 176.8 mg/100 g in control and 551.9 ± 149.0 mg/100 g in intervention restaurants. The mean effect of intervention after adjusting for confounding factors was -43.63 mg/100 g (95% CI: from -92.94 to 5.66, p = 0.08), representing an 8% reduction in sodium content. The restaurant-based intervention led to a modest but not significant reduction in the sodium content of restaurant food. There is great urgency for implementing effective and sustainable salt reduction programs, due to the rapid increase in the consumption of restaurant food in China.

Auricular acupressure for adverse events following immunization after COVID-19 vaccine injection: A multicentre, blinded, randomized controlled trial.

BACKGROUND: Some adverse events following immunization (AEFI) were observed in potential corelation with COVID-19 vaccination but without prevention or ongoing trial for it. We aimed to investigate efficacy of auricular acupressure (AuriAc) therapy in preventing AEFI after first dosage of the vaccine. METHODS: We performed a multicentre randomized controlled trial with three arms, including AuriAc, SAuriAc (sham auricular acupressure), and TrAsU (treatment as usual) group, carried out in four medical institutions in Chengdu, China, from March 17th to April 23rd, 2021. We enrolled participants based on eligibility criteria and randomized them into three groups: AuriAc (AEFI-specific auricular points applied, n = 52), SAuriAc (n = 51) or TrAsU (n = 44) group. Primary outcomes were percentages of any AEFI and local pain, and secondary outcomes were percentages who reported other AEFI. They were followed at 1, 3, 5, 7, and 14 days, by phone or online, with severity evaluated. RESULTS: 147 participants (73.47% females) were included with median age as 31 years (25-45, IQR). One day after the injection, participants in AuriAc group reported significant reduction on percentages of any AEFI [intention-to-treat, difference of percentage (DP) = -20.13, 95%CI: - 0.39, - 0.02, p = 0.01; per-protocol, DP = -22.21, 95%CI: - 0.40, - 0.03, P = 0.02] and local pain (per-protocol, DP = -18.40, 95%CI: -0.36, -0.01, P = 0.04), compared with TrAsU group. The effects were slight at other follow-up days and for other outcomes, and with a low percentage of mild local allergic reactions. CONCLUSIONS: We firstly explored potential of AuriAc for preventing AEFI related to COVID-19 vaccine injection, which is beneficial for the vaccine recipients, but evidence is limited. TRIAL REGISTRATION: chictr.org.cn no. ChiCTR2100043210 (http://www.chictr.org.cn/showproj.aspx?proj=121519).

The Psychological Well-Being of Older Chinese Immigrants in Canada amidst COVID-19: The Role of Loneliness, Social Support, and Acculturation.

This study examined the effects of loneliness, social support, and acculturation on psychological well-being, as indexed by general emotional well-being and life satisfaction, of older Chinese adults living in Canada during the COVID-19 pandemic. A total of 168 older Chinese adults, recruited via WeChat and the internet, completed an online study through a facilitated Zoom or phone meeting, or through a website link, individually or in a group. The testing package included demographic information, The UCLA Loneliness Scale, The Multidimensional Perceived Social Support Scale, Vancouver Index of Acculturation, The Satisfaction with Life Scale, and The World Health Organization's Five Well-Being Index. The results showed that the psychological well-being (both general emotional well-being and cognitively perceived life satisfaction) was positively predicted by perceived social support but negatively predicted by loneliness. Acculturation was not predictive of both outcomes, and it did not moderate the predictive relationships of social support or loneliness. The results shed light on the importance of community services that target enhancing social support and reducing loneliness in promoting psychological well-being of older Chinese immigrants in Canada amidst and post the pandemic.

Using Crowdsourced Big Data to Unravel Urban Green Space Utilization during COVID-19 in Guangzhou, China

Urban green spaces (UGSs) can meet the spiritual and cultural needs of citizens and provide various ecosystem services. In the context of the COVID-19 pandemic, the utilization of UGSs has been affected in various countries worldwide. This study considered 13 UGSs in Guangzhou, China, as examples. It obtained user check-in data by sampling the check-in pages of Sina Weibo locations using a Python-based web crawler program. The study was conducted for 731 days from 1 October 2019 to 30 September 2021, during different phases of the pandemic. Based on automated Chinese corpus recognition technology, statistical results were obtained after periodization and sentiment calculation. The study assessed the pandemic's impact on the use of UGSs by analyzing the time, frequency, and emotions of residents visiting UGSs. The study concluded that the emotions of UGS users during COVID-19 tended to be positive. They tended to choose UGSs with low expected population density and visited UGSs on weekdays. Additionally, the religious attributes of UGSs also influenced their utilization.

Clinical characteristics of COVID-19 in young patients differ from middle-aged and elderly patients.

Introduction: Coronavirus disease-2019 (COVID-19) has spread worldwide. The study aimed to understand the clinical characteristics of young COVID-19 patients. Material and methods: Ninety patients with severe COVID-19 infection in western Chongqing were collected from 21 January to 14 March 2020. They were divided into 4 groups based on age: youth (< 39 years), middle-aged (39-48 years), middle-elderly aged (49-60 years), and elderly (> 60 years). The clinical symptoms, laboratory findings, imaging findings, and treatment effects were compared among the groups. Results: There were 22, 27, 19, and 22 cases in the youth, middle-aged, middle-elderly, and elderly groups, respectively. There were no significant differences with respect to gender or smoking status among the four groups. The clinical indicators of severe disease in the youth group were significantly different from the other three groups, and included the lymphocyte count (p < 0.001), C-reactive protein level (p = 0.03), interleukin-6 level (p = 0.01), chest computed tomography (CT) findings (p < 0.001), number of mild cases (p = 0.02), education level (p < 0.001), and CD4 + T lymphocyte level (p = 0.02) at the time of admission, and the pneumonia severity index (PSI) at the time of discharge (p < 0.001). The complications (p < 0.001) among the youth group were also significantly different from the other groups. Conclusions: Young patients have milder clinical manifestations, which may be related to higher education level, higher awareness and higher acceptance of the prevention and control of the COVID-19 epidemic, as well as their good immune function.

Artificial intelligence for COVID-19: battling the pandemic with computational intelligence.

The new coronavirus disease 2019 (COVID-19) has become a global pandemic leading to over 180 million confirmed cases and nearly 4 million deaths until June 2021, according to the World Health Organization. Since the initial report in December 2019 , COVID-19 has demonstrated a high transmission rate (with an R0 > 2), a diverse set of clinical characteristics (e.g., high rate of hospital and intensive care unit admission rates, multi-organ dysfunction for critically ill patients due to hyperinflammation, thrombosis, etc.), and a tremendous burden on health care systems around the world. To understand the serious and complex diseases and develop effective control, treatment, and prevention strategies, researchers from different disciplines have been making significant efforts from different aspects including epidemiology and public health, biology and genomic medicine, as well as clinical care and patient management. In recent years, artificial intelligence (AI) has been introduced into the healthcare field to aid clinical decision-making for disease diagnosis and treatment such as detecting cancer based on medical images, and has achieved superior performance in multiple data-rich application scenarios. In the COVID-19 pandemic, AI techniques have also been used as a powerful tool to overcome the complex diseases. In this context, the goal of this study is to review existing studies on applications of AI techniques in combating the COVID-19 pandemic. Specifically, these efforts can be grouped into the fields of epidemiology, therapeutics, clinical research, social and behavioral studies and are summarized. Potential challenges, directions, and open questions are discussed accordingly, which may provide new insights into addressing the COVID-19 pandemic and would be helpful for researchers to explore more related topics in the post-pandemic era.

Evaluation of Albumin Kinetics in Critically Ill Patients With Coronavirus Disease 2019 Compared to Those With Sepsis-Induced Acute Respiratory Distress Syndrome.

OBJECTIVES: This report aims to characterize the kinetics of serum albumin in critically ill patients with coronavirus disease 2019 compared with critically ill patients with sepsis-induced acute respiratory distress syndrome. DESIGN: Retrospective analysis. SETTING: We analyzed two critically ill cohorts, one with coronavirus disease 2019 and another with sepsis-induced acute respiratory distress syndrome, treated in the New York Presbyterian Hospital-Weill Cornell Medical Center. PATIENTS: Adult patients in the coronavirus disease 2019 cohort, diagnosed through reverse transcriptase-polymerase chain reaction assays performed on nasopharyngeal swabs, were admitted from March 3, 2020, to July 10, 2020. Adult patients in the sepsis-induced acute respiratory distress syndrome cohort, defined by Sepsis III criteria receipt of invasive mechanical ventilation and a Pao2/Fio2 ratio less than 300 were admitted from December 12, 2006, to February 26, 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We evaluated serial serum albumin levels within 30 days after ICU admission in each cohort. We then examined the albumin progression trajectories, aligned at ICU admission time to test the relationship at a similar point in disease progression, in survivors and nonsurvivors. Albumin trajectory in all critically ill coronavirus disease 2019 patients show two distinct phases: phase I (deterioration) showing rapid albumin loss and phase II (recovery) showing albumin stabilization or improvement. Meanwhile, albumin recovery predicted clinical improvement in critical coronavirus disease 2019. In addition, we found a deterioration and recovery trends in survivors in the sepsis-induced acute respiratory distress syndrome cohort but did not find such two-phase trend in nonsurvivors. CONCLUSIONS: The changes in albumin associated with coronavirus disease 2019 associated respiratory failure are transient compared with sepsis-associated acute respiratory distress syndrome and highlight the potential for recovery following a protracted course of severe coronavirus disease 2019.

Auricular acupressure for adverse events following immunization related to COVID-19 vaccine injection: study protocol for a multicenter, three-arm, blinded randomized controlled trial.

BACKGROUND: Some pain, fatigue, and gastrointestinal adverse events were observed in potential association with injection of COVID-19 vaccines, while there was no preventive intervention for it. We aim to investigate the efficacy of auricular acupressure (AA) therapy in preventing and relieving AEFI after injection of COVID-19 vaccine. METHODS: The study design is a randomized, multicentre, three-arm controlled, single-blind trial. Participants meeting the inclusion criteria will be advertised and enrolled and assigned in the medical institutions randomly for post-injection observation. No less than 360 participants will be randomized into one of three groups: auricular acupressure group, sham auricular acupressure group, and wait-list group. Interventions will be performed immediately and will happen 4 to 5 times per day for 5 days. The primary clinical outcomes will be quality and quantity evaluation among participants who reported any AEFI and who reported local pain at injection site. Secondary outcomes will concern headache, muscle and (or) joint pain, fatigue, nausea, vomiting, diarrhoea, and other potential events. All the outcomes will be assessed at baseline and 1, 3, 5, 7, and 14 days after the injection. Both intention-to-treat and per-protocol analyses will be performed, with significance level determined as 5%. DISCUSSION: Results of this trial will help to clarify the value of auricular acupressure therapy in preventing and relieving overall and certain adverse events following immunization after injection of COVID-19 vaccine. TRIAL REGISTRATION: China Clinical Trial Registry (ChiCTR) ( ChiCTR2100043210 ). Registered on 8 February, 2021.

Identifying organ dysfunction trajectory-based subphenotypes in critically ill patients with COVID-19.

COVID-19-associated respiratory failure offers the unprecedented opportunity to evaluate the differential host response to a uniform pathogenic insult. Understanding whether there are distinct subphenotypes of severe COVID-19 may offer insight into its pathophysiology. Sequential Organ Failure Assessment (SOFA) score is an objective and comprehensive measurement that measures dysfunction severity of six organ systems, i.e., cardiovascular, central nervous system, coagulation, liver, renal, and respiration. Our aim was to identify and characterize distinct subphenotypes of COVID-19 critical illness defined by the post-intubation trajectory of SOFA score. Intubated COVID-19 patients at two hospitals in New York city were leveraged as development and validation cohorts. Patients were grouped into mild, intermediate, and severe strata by their baseline post-intubation SOFA. Hierarchical agglomerative clustering was performed within each stratum to detect subphenotypes based on similarities amongst SOFA score trajectories evaluated by Dynamic Time Warping. Distinct worsening and recovering subphenotypes were identified within each stratum, which had distinct 7-day post-intubation SOFA progression trends. Patients in the worsening suphenotypes had a higher mortality than those in the recovering subphenotypes within each stratum (mild stratum, 29.7% vs. 10.3%, p = 0.033; intermediate stratum, 29.3% vs. 8.0%, p = 0.002; severe stratum, 53.7% vs. 22.2%, p < 0.001). Pathophysiologic biomarkers associated with progression were distinct at each stratum, including findings suggestive of inflammation in low baseline severity of illness versus hemophagocytic lymphohistiocytosis in higher baseline severity of illness. The findings suggest that there are clear worsening and recovering subphenotypes of COVID-19 respiratory failure after intubation, which are more predictive of outcomes than baseline severity of illness. Distinct progression biomarkers at differential baseline severity of illness suggests a heterogeneous pathobiology in the progression of COVID-19 respiratory failure.

Clinical subphenotypes in COVID-19: derivation, validation, prediction, temporal patterns, and interaction with social determinants of health.

The coronavirus disease 2019 (COVID-19) is heterogeneous and our understanding of the biological mechanisms of host response to the viral infection remains limited. Identification of meaningful clinical subphenotypes may benefit pathophysiological study, clinical practice, and clinical trials. Here, our aim was to derive and validate COVID-19 subphenotypes using machine learning and routinely collected clinical data, assess temporal patterns of these subphenotypes during the pandemic course, and examine their interaction with social determinants of health (SDoH). We retrospectively analyzed 14418 COVID-19 patients in five major medical centers in New York City (NYC), between March 1 and June 12, 2020. Using clustering analysis, 4 biologically distinct subphenotypes were derived in the development cohort (N = 8199). Importantly, the identified subphenotypes were highly predictive of clinical outcomes (especially 60-day mortality). Sensitivity analyses in the development cohort, and rederivation and prediction in the internal (N = 3519) and external (N = 3519) validation cohorts confirmed the reproducibility and usability of the subphenotypes. Further analyses showed varying subphenotype prevalence across the peak of the outbreak in NYC. We also found that SDoH specifically influenced mortality outcome in Subphenotype IV, which is associated with older age, worse clinical manifestation, and high comorbidity burden. Our findings may lead to a better understanding of how COVID-19 causes disease in different populations and potentially benefit clinical trial development. The temporal patterns and SDoH implications of the subphenotypes may add insights to health policy to reduce social disparity in the pandemic.

Circular economy for clean energy transitions: A new opportunity under the COVID-19 pandemic.

This paper models the energy and emissions scenarios for a circular economy based clean energy transitions in a 140,000-population town in China, taking into account the new situation encountered by the COVID-19 pandemic. The modelled scenarios propose new clean energy transition roadmaps towards a sustainable urban system through the implementation of circular economy strategies. This is represented by the cascading use of industrial excess heat to form symbiosis between factories and to cover the growing building heat demand, as well as by the electrification of the transport sector and reusing the batteries for a second life as energy storage devices. The results show that for a circular economy scenario, during 2020-2040, an accumulated saving of 7.1 Mtoe final energy use (34%), a decline in 14.5 Mt CO2 emissions (40%) and 592 t PM2.5 emissions (43%) could be achieved compared with the business-as-usual scenario. The outcomes of the circular economy strategies are at least 7% better than the new policy scenario which simply has energy efficiency improvements. The outbreak of the COVID-19 tremendously impacts the socio-economic activities in the town. If taking the pandemic as an opportunity to enhance the circular economy, by 2040, compared with the scenario without introducing circular economy measures, the extra avoided final energy use, CO2 emissions and PM2.5 emissions could be 1.6 Mtoe (8%), 3.8 Mt (11%) and 229 t (17%) respectively.

Traditional Chinese medicine auricular point acupressure for the relief of pain, fatigue, and gastrointestinal adverse reactions after the injection of novel coronavirus-19 vaccines: a structured summary of a study protocol for a multicentre, three-arm, single-blind, prospective randomized controlled trial.

OBJECTIVES: To investigate if traditional Chinese medicine (TCM) auricular point acupressure (APA) can alleviate and (or) reduce the pain (including injection site pain, headache, other muscle and joint pain), fatigue, and gastrointestinal adverse reactions (including nausea, vomiting, diarrhea), after the injection of novel coronavirus-19 vaccines (NCVs). TRIAL DESIGN: The study is designed as a multicentre, parallel-group, three-arm, single-blind, prospective, randomized (1:1:1 ratio) study. PARTICIPANTS: More than 360 participants will be recruited from healthy people who vaccinate NCVs in 5 community healthcare centres in the Sichuan province of China and 1 university hospital (Hospital of Chengdu University of Traditional Chinese Medicine). INCLUSION CRITERIA: ①Vaccinators meets the conditions of NCVs injection and have no contraindications to it. The details shall be subject to the instructions of the NCVs used and the statement of medical institutions. The first dose of NCVs injection shall be completed within 24 hours from the time of injection to the time of enrolment; ②No redness, swelling, injury or infection of the skin or soft tissue of both ears, which is not suitable for APA; ③No history of alcohol and adhesive tape contact allergy; ④18-59 years old, regardless of gender; ⑤Those who were able to complete the questionnaire independently at the time of the first and second dose of NCVs and on the 3rd, 7th and 15th day after the first and second dose of NCVs respectively; ⑥Those who agree to participate in the trial and sign the informed consent, and can seriously abide by the precautions after the injection of NCVs and the requirements of traditional Chinese medicine auricular point plasters sticking and acupressure. EXCLUSION CRITERIA: ①Those who are not suitable to be vaccinated because they belong to the contraindication or cautious population; ②Those who have participated in other clinical trials within 4 weeks before the start of this study; ③No chronic/habitual/persistent headache, Muscle or joint pain, fatigue, diarrhea, nausea, retching or vomiting before the injection of NCVs, and no related diseases present (details of this item is listed in full protocol); ④Those who are in use or have received TCMAPA within 2 weeks before the trial; ⑤Pregnant or lactating women; ⑥Participants with other serious primary diseases and psychosis. INTERVENTION AND COMPARATOR: ①Auricular point acupressure group: participants receive bilateral, symptom-specific TCMAPA in 5 auricular points (per side, 10 points bilateral) for 5 days, 3-4 times (about 1 min each time) of self-acupressure per day, after each NCVs injection (10 days in total). ②Sham auricular point acupressure group: participants receive bilateral, none symptom-specific, sham APA in 5 auricular points (per side, 10 points bilateral) for 5 days, 3-4 times (about 1 min each time) of self-acupressure per day, after each NCVs injection (10 days in total). ③Blank control group: Non-intervention blank control. The Hebei medical device Co. Ltd, Hebei, China manufactured the auricular point sticking plasters. MAIN OUTCOMES: Primary outcomes are all scores of visual analogue scale (VAS) based on subjective judgment of the participants included, including VAS score of pain at injection site, headache, muscle and joint pain, fatigue, nausea, retching, vomiting and diarrhea. Time points for outcomes above are the same: ①Immediately after first and second injection of the vaccine (Baseline assessment); ②Three days after first and second injection of the vaccine; ③Seven days after first and second injection of the vaccine; ④Fifteen days after first and second injection of the vaccine. RANDOMISATION: Participants will be randomized in 1:1:1 ratio to each group by computerized random number generator, and independently in each sub-centre. BLINDING (MASKING): Participants, information collectors and statistical evaluators will be blinded between APA group and sham APA group. No blinding in the control group. NUMBERS TO BE RANDOMISED (SAMPLE SIZE): No less than 360 participants will be randomized in 1:1:1 ratio to each group. TRIAL STATUS: Protocol version 2.0 of February 3rd, 2021. Recruitment is expected to start on February 18th, 2021, and to finish on March 12th, 2021. TRIAL REGISTRATION: This trial was registered in the China Clinical Trial Registry (ChiCTR) ( ChiCTR2100043210 ) on 8th February, 2021. FULL PROTOCOL: The full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.