New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine.

Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

Home-Based Pilot Pulmonary Program for Dyspneic Patients Post-COVID-19.

It is estimated that at least 10% of people who have had COVID-19 will experience ongoing symptoms such as shortness of breath, fatigue, and cognitive disturbances. Pulmonary exercise has demonstrated improved dyspnea outcomes in other respiratory conditions. Thus, the purpose of this study was to assess the efficacy of a home-based pulmonary rehabilitation program in post-COVID-19 survivors who continue to experience dyspnea. This was a longitudinal, single group pilot study in which 19 patients received a home-based expiratory muscle strength training program over 12 weeks. Outcomes measured at baseline, 6 weeks, and 12 weeks included pulmonary symptoms, functional performance, thoracic expansion, forced expiratory volume, and expiratory resistance measures. Significant improvements were found in pulmonary symptoms (p < .001), functional performance (p = .014), and progressive expiratory resistance capabilities (p < .001). A home-based pulmonary program may be an inexpensive strategy for post-COVID-19 survivors who continue to experience dyspnea.

Multiple-Inputs Convolutional Neural Network for COVID-19 Classification and Critical Region Screening From Chest X-ray Radiographs: Model Development and Performance Evaluation.

Background: The COVID-19 pandemic is becoming one of the largest, unprecedented health crises, and chest X-ray radiography (CXR) plays a vital role in diagnosing COVID-19. However, extracting and finding useful image features from CXRs demand a heavy workload for radiologists. Objective: The aim of this study was to design a novel multiple-inputs (MI) convolutional neural network (CNN) for the classification of COVID-19 and extraction of critical regions from CXRs. We also investigated the effect of the number of inputs on the performance of our new MI-CNN model. Methods: A total of 6205 CXR images (including 3021 COVID-19 CXRs and 3184 normal CXRs) were used to test our MI-CNN models. CXRs could be evenly segmented into different numbers (2, 4, and 16) of individual regions. Each region could individually serve as one of the MI-CNN inputs. The CNN features of these MI-CNN inputs would then be fused for COVID-19 classification. More importantly, the contributions of each CXR region could be evaluated through assessing the number of images that were accurately classified by their corresponding regions in the testing data sets. Results: In both the whole-image and left- and right-lung region of interest (LR-ROI) data sets, MI-CNNs demonstrated good efficiency for COVID-19 classification. In particular, MI-CNNs with more inputs (2-, 4-, and 16-input MI-CNNs) had better efficiency in recognizing COVID-19 CXRs than the 1-input CNN. Compared to the whole-image data sets, the efficiency of LR-ROI data sets showed approximately 4% lower accuracy, sensitivity, specificity, and precision (over 91%). In considering the contributions of each region, one of the possible reasons for this reduced performance was that nonlung regions (eg, region 16) provided false-positive contributions to COVID-19 classification. The MI-CNN with the LR-ROI data set could provide a more accurate evaluation of the contribution of each region and COVID-19 classification. Additionally, the right-lung regions had higher contributions to the classification of COVID-19 CXRs, whereas the left-lung regions had higher contributions to identifying normal CXRs. Conclusions: Overall, MI-CNNs could achieve higher accuracy with an increasing number of inputs (eg, 16-input MI-CNN). This approach could assist radiologists in identifying COVID-19 CXRs and in screening the critical regions related to COVID-19 classifications.

Multiple-Inputs Convolutional Neural Network for COVID-19 Classification and Critical Region Screening From Chest X-ray Radiographs: Model Development and Performance Evaluation

Background The COVID-19 pandemic is becoming one of the largest, unprecedented health crises, and chest X-ray radiography (CXR) plays a vital role in diagnosing COVID-19. However, extracting and finding useful image features from CXRs demand a heavy workload for radiologists. Objective The aim of this study was to design a novel multiple-inputs (MI) convolutional neural network (CNN) for the classification of COVID-19 and extraction of critical regions from CXRs. We also investigated the effect of the number of inputs on the performance of our new MI-CNN model. Methods A total of 6205 CXR images (including 3021 COVID-19 CXRs and 3184 normal CXRs) were used to test our MI-CNN models. CXRs could be evenly segmented into different numbers (2, 4, and 16) of individual regions. Each region could individually serve as one of the MI-CNN inputs. The CNN features of these MI-CNN inputs would then be fused for COVID-19 classification. More importantly, the contributions of each CXR region could be evaluated through assessing the number of images that were accurately classified by their corresponding regions in the testing data sets. Results In both the whole-image and left- and right-lung region of interest (LR-ROI) data sets, MI-CNNs demonstrated good efficiency for COVID-19 classification. In particular, MI-CNNs with more inputs (2-, 4-, and 16-input MI-CNNs) had better efficiency in recognizing COVID-19 CXRs than the 1-input CNN. Compared to the whole-image data sets, the efficiency of LR-ROI data sets showed approximately 4% lower accuracy, sensitivity, specificity, and precision (over 91%). In considering the contributions of each region, one of the possible reasons for this reduced performance was that nonlung regions (eg, region 16) provided false-positive contributions to COVID-19 classification. The MI-CNN with the LR-ROI data set could provide a more accurate evaluation of the contribution of each region and COVID-19 classification. Additionally, the right-lung regions had higher contributions to the classification of COVID-19 CXRs, whereas the left-lung regions had higher contributions to identifying normal CXRs. Conclusions Overall, MI-CNNs could achieve higher accuracy with an increasing number of inputs (eg, 16-input MI-CNN). This approach could assist radiologists in identifying COVID-19 CXRs and in screening the critical regions related to COVID-19 classifications.

A highly powerful nonspecific strategy to reduce COVID-19 deaths.

The coronavirus disease 2019 (COVID-19) pandemic caused by the coronavirus severe acute respiratory syndrome coronavirus 2 remains risky worldwide. We elucidate here that good IDM (isolation, disinfection, and maintenance of health) is powerful to reduce COVID-19 deaths based on the striking differences in COVID-19 case fatality rates among various scenarios. IDM means keeping COVID-19 cases away from each other and from other people, disinfecting their living environments, and maintaining their health through good nutrition, rest, and treatment of symptoms and pre-existing diseases (not through specific antiviral therapy). Good IDM could reduce COVID-19 deaths by more than 85% in 2020 and more than 99% in 2022. This is consistent with the fact that good IDM can minimize co-infections and maintain body functions and the fact that COVID-19 has become less pathogenic (this fact was supported with three novel data in this report). Although IDM has been frequently implemented worldwide to some degree, IDM has not been highlighted sufficiently. Good IDM is relative, nonspecific, flexible, and feasible in many countries, and can reduce deaths of some other relatively mild infectious diseases. IDM, vaccines, and antivirals aid each other to reduce COVID-19 deaths. The IDM concept and strategy can aid people to improve their health behavior and fight against COVID-19 and future pandemics worldwide.

Frameshift Mutations in the Microevolution and Macroevolution of Viruses (preprint)

Some nucleotide insertions or deletions (indels) in protein-coding open reading frames lead to frameshift mutations (FSMs) which can change amino acid sequences drastically. FSMs are widely distributed in the genomes of many organisms. However, few studies have been reported regarding frequencies of FSMs in microevolution or macroevolution. Many viruses evolve much more rapidly than cellular organisms, and they are hence suitable to investigate frequencies of FSMs in microevolution or macroevolution. In this report, we identified 667 FSMs in gene sequences of 13 virus families and each FSM changed approximately 11 amino acid residues on average. Of the FSMs, 89.21% were 2-indel compensatory FSMs, and the remaining were 1-, 3-, 4-, 5-indel FSMs. We found that FSMs usually occurred more frequently in the viruses of the same family with smaller sequence identities, and FSMs occurred in the sequences of with identities of 60.0-69.9% more frequently than in the sequences with identities of 90.0-99.9% or 80.0-89.9% by approximately 34.9 or 13.1 times on average. We also found FSMs occurred at different frequencies among genes in the same virus genome, among species in the same virus family, or among virus families (e.g., more frequently in Coronaviridae than in Orthomyxoviridae). These results suggest that FSMs are more frequent in the inter-species or macroevolution than in the intra-species or microevolution of viruses. They provide novel evidence for the hopeful monster hypothesis in evolutionary biology. They inspire researchers to investigate the roles, frequencies, features, and functions of FSMs in other viruses and cellular organisms.

Proactive Coping and Mental Health Among Airline Pilots During China's Regular Prevention and Control of COVID-19: The Role of Perceived Stress and Social Support.

Mental health has always been a prominent public health concern, and it has become more important in the wake of the COVID-19 pandemic. The mental health of airline pilots plays a significant role in their occupational health and overall performance. It is also vital for ensuring the safe operation of aircrafts. Therefore, it is crucial to identify the factors that may improve the mental health of pilots. This study investigates the relationship between proactive coping, perceived stress, social support, and mental health among airline pilots during China's regular prevention and control of COVID-19. Using a sample consisting of 285 Chinese commercial airline pilots, we tested a moderated mediation model to explore whether, how, and when proactive coping affects the mental health of pilots. The results show that proactive coping has a direct and positive effect on pilots' mental health, as well as an indirect effect on mental health through its influence on perceived stress. Social support was found to weaken the relationship between perceived stress and mental health. It also weakened the indirect relationship between proactive coping and mental health through perceived stress. These findings advance our understanding of the underlying mechanisms that affect the mental health of pilots. It also provides empirical evidence for effective mental health interventions for airline pilots during regular prevention and control of COVID-19.

Cohort profile: The Bariatric Experience Long Term (BELONG): a long-term prospective study to understand the psychosocial, environmental, health and behavioural predictors of weight loss and regain in patients who have bariatric surgery

PurposeThe Bariatric Experience Long Term (BELONG) prospective study cohort was created to address limitations in the literature regarding the relationship between surgical weight loss and psychosocial, health, behaviour and environmental factors. The BELONG cohort is unique because it contains 70% gastric sleeve and 64% patients with non-white race/ethnicity and was developed with strong stakeholder engagement including patients and providers.ParticipantsThe BELONG cohort study included 1975 patients preparing to have bariatric surgery who completed a baseline survey in a large integrated health system in Southern California. Patients were primarily women (84%), either black or Hispanic (59%), with a body mass index (BMI) of 45.1±7.4 kg/m2, age 43.3±11.5 years old, and 32% had at least one comorbidity.Findings to dateA total of 5552 patients were approached before surgery between February 2016 and May 2017, and 1975 (42%) completed a baseline survey. A total of 1203 (73%) patients completed the year 1 and 1033 (74%) patients completed the year 3 postoperative survey. Of these survey respondents, 1341 at baseline, 999 at year 1, and 951 at year 3 were included in the analyses of all survey and weight outcome data. A total of 803 (60% of eligible patients) had survey data for all time points. Data collected were self-reported constructs to support the proposed theoretical model. Height, weight and BMI were ed from the electronic medical record to obtain the main outcomes of the study: weight loss and regain.Future plansWe will collect self-reported constructs and obtain height, weight and BMI from the electronic medical record 5 years after bariatric surgery between April 2022 and January 2023. We will also collect patient experiences using focus groups of 8–12 patients each throughout 2022.

How Risky if China Moves Away from Its Zero-COVID Policy? (preprint)

There are two contrary opinions regarding the risk if mainland China (MC) moves away from its zero-COVID policy. Some experts think the risk shall be much lower than influenza as per MC’s own COVID-19 case fatality rate (CFR), while some other experts think the risk shall be much higher than influenza as per the COVID-19 CFRs of other regions. We elucidate here that this and multiple other striking differences in the CFR between various scenarios all support and substantially resulted from the view that good IDM is highly powerful to mitigate COVID-19, where IDM (isolation-disinfection-maintenance) means isolation of COVID-19 cases from other people, disinfection of their living environments, and health maintenance (e.g., rest, nutrition, breathing). The high effect of good IDM is also supported by the theoretic functions of IDM in minimizing co-infections and maintaining body functions, and the fact that all the 505 COVID-19 deaths reported in MC in 2022 before May 5 died directly of severe underlying diseases with COVID-19. Although it is tough for people in poverty to obtain good IDM, good IDM can be feasible at home for the most mild cases and in hospitals for the most severe cases. Therefore, good IDM can be crucial to mitigating COVID-19 worldwide. It also suggests that the risk for China to end its zero-COVID policy depends on China’s control policies or measures. Based on the effect of IDM, the cautious co-existence policy was proposed for COVID-19 control. This policy could reduce the whole death toll in MC because good IDM is non-specific and can reduce deaths of various other diseases. The cautious co-existence policy (non-specific) and the vaccination policy (specific) aid each other to mitigate COVID-19, and they cannot replace each other. Those who are qualified in health for vaccination should be vaccinated against COVID-19 timely.

Novel statistics predict the COVID-19 pandemic could terminate in 2022.

Many people want to know when the COVID-19 pandemic will end and life will return to normal. This question is highly elusive and distinct predictions have been proposed. In this study, the global mortality and case fatality rate of COVID-19 were analyzed using nonlinear regression. The analysis showed that the COVID-19 pandemic could terminate in 2022, but COVID-19 could be one or two times more deadly than seasonal influenza by 2023. The prediction considered the possibility of the emergence of new variants of SARS-CoV-2 and was supported by the features of the Omicron variant and other facts. As the herd immunity against COVID-19 established through natural infections and mass vaccination is distinct among countries, COVID-19 could be more or less deadly in some countries in the coming years than the prediction. Although the future of COVID-19 will have multiple possibilities, this statistics-based prediction could aid to make proper decisions and establish an example on the prediction of infectious diseases.

Should the world collaborate imminently to develop neglected live-attenuated vaccines for COVID-19?

The rapid spread of the Delta variant suggests that SARS-CoV-2 will likely be rampant for months or years and could claim millions of more lives. All the known vaccines cannot well defeat SARS-CoV-2 due to their limited efficacy and production efficiency, except for the neglected live-attenuated vaccines (LAVs), which could have a much higher efficacy and much higher production efficiency than other vaccines. LAVs, like messiahs, have defeated far more pathogenic viruses than other vaccines in history, and most current human vaccines for viral diseases are safe LAVs. LAVs can block completely infection and transmission of relevant viruses and their variants. They can hence inhibit the emergence of vaccine-escape and virulence-enhancing variants and protect immunologically abnormal individuals better in general. The safety of COVID-19 LAVs, which could save millions of more lives, can be solidly guaranteed through animal experiments and clinical trials. The safety of COVID-19 LAVs could be greatly enhanced with intramuscular or oral administration, or administration along with humanized neutralizing monoclonal antibodies. Together, extensive global collaboration, which can greatly accelerate the development of safe COVID-19 LAVs, is imminently needed.

[Transmission of Coronavirus via Aerosols and Influence of Environmental Conditions on Its Transmission].

The COVID-19 pandemic has endangered human health and production since 2019. As an emerging disease caused by SARS-CoV-2, its potential transmissibility via aerosols has caused heated debate. This work summarizes the current research findings on virus aerosol generation, aerodynamic properties, and environmental influencing factors on their survivability in order to elucidate coronavirus transmission via aerosols. The occurrence and distinction of SARS-CoV-2, SARS-CoV-1, and MERS-CoV in real atmospheric environments are summarized. The deficiencies of existing research and directions for necessary future research on confirming the airborne transmission mechanism of coronavirus as well as the need for multidisciplinary research are discussed.

Live unattenuated vaccines for controlling viral diseases, including COVID-19.

Live unattenuated vaccines (LUVs) have been neglected for decades, due to widespread prejudice against their safety, even though they have successfully controlled yellow fever and adenovirus infection in humans as well as rinderpest and infectious bursal disease in animals. This review elucidated that LUVs could be highly safe with selective use of neutralizing antivirus antibodies, natural antiglycan antibodies, nonantibody antivirals, and ectopic inoculation. Also, LUVs could be of high efficacy, high development speed, and high production efficiency, with the development of humanized monoclonal antibodies and other modern technologies. They could circumvent antibody-dependent enhancement and maternal-derived antibody interference. With these important advantages, LUVs could be more powerful than other vaccines for controlling some viral diseases, and they warrant urgent investigation with animal experiments and clinical trials for defeating the COVID-19 pandemic caused by the novel coronavirus SARS-CoV-2.

SARS-CoV-2 replicating in nonprimate mammalian cells probably have critical advantages for COVID-19 vaccines due to anti-Gal antibodies: A minireview and proposals.

Glycoproteins of enveloped viruses replicating in nonprimate mammalian cells carry α-1,3-galactose (α-Gal) glycans, and can bind to anti-Gal antibodies which are abundant in humans. The antibodies have protected humans and their ancestors for millions of years, because they inhibit replication of many kinds of microbes carrying αGal glycans and aid complements and macrophages to destroy them. Therefore, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) replicating in nonprimate mammalian cells (eg, PK-15 cells) carry αGal glycans and could be employed as a live vaccine for corona virus 2019 (COVID-19). The live vaccine safety could be further enhanced through intramuscular inoculation to bypass the fragile lungs, like the live unattenuated adenovirus vaccine safely used in US recruits for decades. Moreover, the immune complexes of SARS-CoV-2 and anti-Gal antibodies could enhance the efficacy of COVID-19 vaccines, live or inactivated, carrying α-Gal glycans. Experiments are imperatively desired to examine these novel vaccine strategies which probably have the critical advantages for defeating the pandemic of COVID-19 and preventing other viral infectious diseases.