Research progress on central mechanism of acupuncture treatment for chronic fatigue syndrome.

Chronic fatigue syndrome is a neurological disorder characterized by extreme fatigue that lasts for a long time and doesn't alleviate with rest. The number of the cases has been increasing during the era of COVID-19 pandemic. Acupuncture may have some effect on chronic fatigue syndrome, but its mechanism remains unclear. This article was to summarize the specific manifestations of abnormal central mechanism in patients with chronic fatigue syndrome through laboratory tests and neuroimaging. It was found from the laboratory evaluation that there were changes in the structure of the frontal cortex, thalamus and other brain tissues; factors, including IFN-α and IL-10 in cerebrospinal fluid were found abnormal; results of oxidative and nitrosative stress and changes in neurobiochemical substances, e.g. hypothalamus hormone levels and neurotransmitter concentrations, were observed. With magnetic resonance imaging and positron emission tomography, it was shown that the partial brain of persons with chronic fatigue syndrome had morphological changes with diminished grey matter and white; changes in cerebral blood flow velocity caused by decreased perfusion and functional activity with abnormal connectivity in brain were detected. In addition, there was significant decrease in glucose metabolism accompanied with neuroinflammatory response; metabolic disorders of serotonergic, cholinergic, glutamatergic and γ-aminobutyric acid energy neurotransmitters were also discovered. The regulatory effect of acupuncture on the above central neurological abnormalities in chronic fatigue syndrome model animals was elaborated, and the direction for further research was analyzed in order to provide ideas for further research on the central mechanism of acupuncture treatment for chronic fatigue syndrome.

Research progress on central mechanism of acupuncture treatment for chronic fatigue syndrome : 针刺调控慢性疲劳综合征中枢机制研究进展

Chronic fatigue syndrome is a neurological disorder characterized by extreme fatigue that lasts for a long time and doesn't alleviate with rest. The number of the cases has been increasing during the era of COVID-19 pandemic. Acupuncture may have some effect on chronic fatigue syndrome, but its mechanism remains unclear. This article was to summarize the specific manifestations of abnormal central mechanism in patients with chronic fatigue syndrome through laboratory tests and neuroimaging. It was found from the laboratory evaluation that there were changes in the structure of the frontal cortex, thalamus and other brain tissues;factors, including IFN-α and IL-10 in cerebrospinal fluid were found abnormal;results of oxidative and nitrosative stress and changes in neurobiochemical substances, e.g. hypothalamus hormone levels and neurotransmitter concentrations, were observed. With magnetic resonance imaging and positron emission tomography, it was shown that the partial brain of persons with chronic fatigue syndrome had morphological changes with diminished grey matter and white;changes in cerebral blood flow velocity caused by decreased perfusion and functional activity with abnormal connectivity in brain were detected. In addition, there was significant decrease in glucose metabolism accompanied with neuroinflammatory response;metabolic disorders of serotonergic, cholinergic, glutamatergic and γ-aminobutyric acid energy neurotransmitters were also discovered. The regulatory effect of acupuncture on the above central neurological abnormalities in chronic fatigue syndrome model animals was elaborated, and the direction for further research was analyzed in order to provide ideas for further research on the central mechanism of acupuncture treatment for chronic fatigue syndrome.

Risk of insomnia during COVID-19: effects of depression and brain functional connectivity.

Normal sleepers may be at risk for insomnia during COVID-19. Identifying psychological factors and neural markers that predict their insomnia risk, as well as investigating possible courses of insomnia development, could lead to more precise targeted interventions for insomnia during similar public health emergencies. Insomnia severity index of 306 participants before and during COVID-19 were employed to determine the development of insomnia, while pre-COVID-19 psychometric and resting-state fMRI data were used to explore corresponding psychological and neural markers of insomnia development. Normal sleepers as a group reported a significant increase in insomnia symptoms after COVID-19 outbreak (F = 4.618, P = 0.0102, df = 2, 609.9). Depression was found to significantly contribute to worse insomnia (ß = 0.066, P = 0.024). Subsequent analysis found that functional connectivity between the precentral gyrus and middle/inferior temporal gyrus mediated the association between pre-COVID-19 depression and insomnia symptoms during COVID-19. Cluster analysis identified that postoutbreak insomnia symptoms followed 3 courses (lessened, slightly worsened, and developed into mild insomnia), and pre-COVID-19 depression symptoms and functional connectivities predicted these courses. Timely identification and treatment of at-risk individuals may help avoid the development of insomnia in the face of future health-care emergencies, such as those arising from COVID-19 variants.

Single-nucleus RNA sequencing reveals the shared mechanisms inducing cognitive impairment between COVID-19 and Alzheimer's disease.

Alzheimer's disease (AD)-like cognitive impairment, a kind of Neuro-COVID syndrome, is a reported complication of SARS-CoV-2 infection. However, the specific mechanisms remain largely unknown. Here, we integrated single-nucleus RNA-sequencing data to explore the potential shared genes and pathways that may lead to cognitive dysfunction in AD and COVID-19. We also constructed ingenuity AD-high-risk scores based on AD-high-risk genes from transcriptomic, proteomic, and Genome-Wide Association Studies (GWAS) data to identify disease-associated cell subtypes and potential targets in COVID-19 patients. We demonstrated that the primary disturbed cell populations were astrocytes and neurons between the above two dis-eases that exhibit cognitive impairment. We identified significant relationships between COVID-19 and AD involving synaptic dysfunction, neuronal damage, and neuroinflammation. Our findings may provide new insight for future studies to identify novel targets for preventive and therapeutic interventions in COVID-19 patients.

COVID-19 public health measures reduce the incidence of respiratory infectious diseases.

BACKGROUND: Children and the elderly are two special subpopulations for coronavirus disease 2019 (COVID-19) and respiratory tract infections (RTIs). The study aimed to evaluate the effect of COVID-19 public health measures on the burden of RTIs in China by performing a two-center investigation. METHODS: The electronic medical records of all inpatients in departments of pediatrics and respiratory medicine of Taizhou Fourth People's Hospital (Taizhou, China) and Shaanxi Provincial People's Hospital (Xi'an, China) during January 1, 2019 to June 30, 2021 were analyzed. A total of 18,084 child inpatients and 14,802 adult inpatients were included. RESULTS: The vast majority (88.3%-90.6%) of the adult inpatients were the elderly, aged over 50 years. The numbers of child and adult (elderly) inpatients, and the proportions of RTI-associated diseases substantially decreased during COVID-19 pandemic (2020-2021) compared to that before the pandemic (2019) in Taizhou and Xi'an. A significantly higher proportion of LRTI-associated diseases was observed in elderly female inpatients (53.4-55.6%) than elderly male inpatients (34.3-41.5%) (p < 0.001) in spite of more male inpatients than female inpatients (1.94-1.95:1). CONCLUSIONS: COVID-19-related interventions provide an additional beneficial effect on reduction of RTI-associated diseases in both children and the elderly.

Deep GRU-CNN Model for COVID-19 Detection From Chest X-Rays Data.

In the current era, data is growing exponentially due to advancements in smart devices. Data scientists apply a variety of learning-based techniques to identify underlying patterns in the medical data to address various health-related issues. In this context, automated disease detection has now become a central concern in medical science. Such approaches can reduce the mortality rate through accurate and timely diagnosis. COVID-19 is a modern virus that has spread all over the world and is affecting millions of people. Many countries are facing a shortage of testing kits, vaccines, and other resources due to significant and rapid growth in cases. In order to accelerate the testing process, scientists around the world have sought to create novel methods for the detection of the virus. In this paper, we propose a hybrid deep learning model based on a convolutional neural network (CNN) and gated recurrent unit (GRU) to detect the viral disease from chest X-rays (CXRs). In the proposed model, a CNN is used to extract features, and a GRU is used as a classifier. The model has been trained on 424 CXR images with 3 classes (COVID-19, Pneumonia, and Normal). The proposed model achieves encouraging results of 0.96, 0.96, and 0.95 in terms of precision, recall, and f1-score, respectively. These findings indicate how deep learning can significantly contribute to the early detection of COVID-19 in patients through the analysis of X-ray scans. Such indications can pave the way to mitigate the impact of the disease. We believe that this model can be an effective tool for medical practitioners for early diagnosis.

Saliva-based COVID-19 detection: A rapid antigen test of SARS-CoV-2 nucleocapsid protein using an electrical-double-layer gated field-effect transistor-based biosensing system.

Facing the unstopped surges of COVID-19, an insufficient capacity of diagnostic testing jeopardizes the control of disease spread. Due to a centralized setting and a long turnaround, real-time reverse transcription polymerase chain reaction (real-time RT-PCR), the gold standard of viral detection, has fallen short in timely reflecting the epidemic status quo during an urgent outbreak. As such, a rapid screening tool is necessitated to help contain the spread of COVID-19 amid the countries where the vaccine implementations have not been widely deployed. In this work, we propose a saliva-based COVID-19 antigen test using the electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET). The detection of SARS-CoV-2 nucleocapsid (N) protein is validated with limits of detection (LoDs) of 0.34 ng/mL (7.44 pM) and 0.14 ng/mL (2.96 pM) in 1× PBS and artificial saliva, respectively. The specificity is inspected with types of antigens, exhibiting low cross-reactivity among MERS-CoV, Influenza A virus, and Influenza B virus. This portable system is embedded with Bluetooth communication and user-friendly interfaces that are fully compatible with digital health, feasibly leading to an on-site turnaround, an effective management, and a proactive response taken by medical providers and frontline health workers.

Clinical features of children with coronavirus disease 2019 caused by Delta variant infection. / 11例Deltaå˜å¼‚æ ªæ–°åž‹å† çŠ¶ç— æ¯’è‚ºç‚Žå„¿ç«¥ç— ä¾‹çš„ä¸´åºŠç‰¹å¾åˆ†æž.

OBJECTIVES: To study the epidemiological and clinical features of children with coronavirus disease 2019 (COVID-19) caused by Delta variant infection and their differences from children with ordinary COVID-19 (non-Delta variant infection). METHODS: Eleven children aged <14 years, who were diagnosed with COVID-19 caused by Delta variant infection from August to September 2021 were enrolled (variant group). Five children aged <14 years who were diagnosed with ordinary COVID-19 from February to March 2020 served as the control group. The epidemiological data, clinical features, and laboratory examination results were compared between the two groups. RESULTS: There was no significant difference in the proportion of children with clinical symptoms between the two groups (P>0.05). There were no significant differences in white blood cell count, lymphocyte count, and platelet count between the two groups (P>0.05), while the variant group had a lower neutrophil count than the control group (P<0.05). Lymphocytopenia was not observed in either group. Compared with the control group, the variant group had a higher proportion of children with an increase in creatine kinase isoenzyme (P<0.05), while there were no significant differences in the proportion of children with an increase in lactate dehydrogenase, D-Dimer, C-reactive protein or interleukin-6 between the two groups (P>0.05). Among the 9 children in the variant group, 5 tested positive for IgM antibody at week 2 after admission, and all children tested positive for IgG antibody. At week 3 after admission, the level of IgM antibody tended to decrease in 9 children, and the level of IgG antibody tended to decrease in 8 children. CONCLUSIONS: Delta variant is more infectious. COVID-19 caused by Delta variant infection may cause more serious myocardial damage than ordinary COVID-19 in children. In children infected with Delta variant, IgG antibody appears at almost the same time as IgM antibody.

A second functional furin site in the SARS-CoV-2 spike protein.

The ubiquitously-expressed proteolytic enzyme furin is closely related to the pathogenesis of SARS-CoV-2 and therefore represents a key target for antiviral therapy. Based on bioinformatic analysis and pseudovirus tests, we discovered a second functional furin site located in the spike protein. Furin still increased the infectivity of mutated SARS-CoV-2 pseudovirus in 293T-ACE2 cells when the canonical polybasic cleavage site (682-686) was deleted. However, K814A mutation eliminated the enhancing effect of furin on virus infection. Furin inhibitor prevented infection by 682-686-deleted SARS-CoV-2 in 293T-ACE2-furin cells, but not the K814A mutant. K814A mutation did not affect the activity of TMPRSS2 and cathepsin L but did impact the cleavage of S2 into S2' and cell-cell fusion. Additionally, we showed that this functional furin site exists in RaTG13 from bat and PCoV-GD/GX from pangolin. Therefore, we discovered a new functional furin site that is pivotal in promoting SARS-CoV-2 infection.

DC-GAN-based synthetic X-ray images augmentation for increasing the performance of EfficientNet for COVID-19 detection.

Currently, many deep learning models are being used to classify COVID-19 and normal cases from chest X-rays. However, the available data (X-rays) for COVID-19 is limited to train a robust deep-learning model. Researchers have used data augmentation techniques to tackle this issue by increasing the numbers of samples through flipping, translation, and rotation. However, by adopting this strategy, the model compromises for the learning of high-dimensional features for a given problem. Hence, there are high chances of overfitting. In this paper, we used deep-convolutional generative adversarial networks algorithm to address this issue, which generates synthetic images for all the classes (Normal, Pneumonia, and COVID-19). To validate whether the generated images are accurate, we used the k-mean clustering technique with three clusters (Normal, Pneumonia, and COVID-19). We only selected the X-ray images classified in the correct clusters for training. In this way, we formed a synthetic dataset with three classes. The generated dataset was then fed to The EfficientNetB4 for training. The experiments achieved promising results of 95% in terms of area under the curve (AUC). To validate that our network has learned discriminated features associated with lung in the X-rays, we used the Grad-CAM technique to visualize the underlying pattern, which leads the network to its final decision.

A Rapid Detection of COVID-19 Viral RNA in Human Saliva Using Electrical Double Layer-Gated Field-Effect Transistor-Based Biosensors

Abstract In light of the swift outspread and considerable mortality, coronavirus disease 2019 (COVID-19) necessitates a rapid screening tool and a precise diagnosis. Saliva is considered as an alternative specimen to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since the viral load is comparable to what are found in a throat and a nasal cavity. The electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET) emerges as a promising candidate for salivary COVID-19 tests due to a high sensitivity, a portable configuration, a label-free operation, and a matrix insensitivity. In this work, the authors utilize EDL-gated BioFETs to detect complementary DNAs (cDNAs) and viral RNAs with various testing conditions such as switches of probes, temperature treatments, and matrices. The selectivity is confirmed with cDNA and noncomplementary DNA (ncDNA), exhibiting an eightfold difference in electrical signals. The matrix insensitivity is evaluated, and BioFETs successfully validate the detection of SARS-CoV-2 N-gene RNA down to 1 fm in diluted human saliva with a 95°C- and a 25°C-treatment, respectively. This proposed system has a high potential to be deployed for an on-site COVID-19 screening, improving the disease control and benefitting frontline healthcare system.

A Rapid Detection of COVID-19 Viral RNA in Human Saliva Using Electrical Double Layer-Gated Field-Effect Transistor-Based Biosensors.

In light of the swift outspread and considerable mortality, coronavirus disease 2019 (COVID-19) necessitates a rapid screening tool and a precise diagnosis. Saliva is considered as an alternative specimen to detect the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) since the viral load is comparable to what are found in a throat and a nasal cavity. The electrical double layer (EDL)-gated field-effect transistor-based biosensor (BioFET) emerges as a promising candidate for salivary COVID-19 tests due to a high sensitivity, a portable configuration, a label-free operation, and a matrix insensitivity. In this work, the authors utilize EDL-gated BioFETs to detect complementary DNAs (cDNAs) and viral RNAs with various testing conditions such as switches of probes, temperature treatments, and matrices. The selectivity is confirmed with cDNA and noncomplementary DNA (ncDNA), exhibiting an eightfold difference in electrical signals. The matrix insensitivity is evaluated, and BioFETs successfully validate the detection of SARS-CoV-2 N-gene RNA down to 1 fm in diluted human saliva with a 95°C- and a 25°C-treatment, respectively. This proposed system has a high potential to be deployed for an on-site COVID-19 screening, improving the disease control and benefitting frontline healthcare system.

Comprehensive Analysis of the Systemic Transcriptomic Alternations and Inflammatory Response during the Occurrence and Progress of COVID-19.

The pandemic of the coronavirus disease 2019 (COVID-19) has posed huge threats to healthcare systems and the global economy. However, the host response towards COVID-19 on the molecular and cellular levels still lacks full understanding and effective therapies are in urgent need. Here, we integrate three datasets, GSE152641, GSE161777, and GSE157103. Compared to healthy people, 314 differentially expressed genes were identified, which were mostly involved in neutrophil degranulation and cell division. The protein-protein network was established and two significant subsets were filtered by MCODE: ssGSEA and CIBERSORT, which comprehensively revealed the alternation of immune cell abundance. Weighted gene coexpression network analysis (WGCNA) as well as GO and KEGG analyses unveiled the role of neutrophils and T cells during the progress of the disease. Based on the hospital-free days after 45 days of follow-up and statistical methods such as nonnegative matrix factorization (NMF), submap, and linear correlation analysis, 31 genes were regarded as the signature of the peripheral blood of COVID-19. Various immune cells were identified to be related to the prognosis of the patients. Drugs were predicted for the genes in the signature by DGIdb. Overall, our study comprehensively revealed the relationship between the inflammatory response and the disease course, which provided strategies for the treatment of COVID-19.

Biological function of furin in viral infections

Most viruses require their glycoproteins to be hydrolyzed in order to enter host cells.In some cases, the severability of viral glycoproteins is a determinant of their virulence.These viral glycoproteins can be cleaved by one or more proteases in host cells with furin as the common one.Furin further promotes viral infection by identifying specific amino acid sequences in glycoprotein precursors.Morever, furin plays a critical role in the infections of many viruses including human immunodeficiency virus, flavivirus, filamentavirus and coronavirus, and is considered as a promising drug treatment and prevention target.In this review, we summarize the biological background of furin and its hydrolysis function to viral glycoproteins.

The first case study of wastewater-based epidemiology of COVID-19 in Hong Kong.

Early detection and surveillance of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) virus are key pre-requisites for the effective control of coronavirus disease (COVID-19). So far, sewage testing has been increasingly employed as an alternative surveillance tool for this disease. However, sampling site characteristics impact the testing results and should be addressed in the early use stage of this emerging tool. In this study, we implemented the sewage testing for SARS-CoV-2 virus across sampling sites with different sewage system characteristics. We first validated a testing method using "positive" samples from a hospital treating COVID-19 patients. This method was used to test 107 sewage samples collected during the third wave of the COVID-19 outbreak in Hong Kong (from June 8 to September 29, 2020), covering sampling sites associated with a COVID-19 hospital, public housing estates, and conventional sewage treatment facilities. The highest viral titer of 1975 copy/mL in sewage was observed in a sample collected from the isolation ward of the COVID-19 hospital. Sewage sampling at individual buildings detected the virus 2 days before the first cases were identified. Sequencing of the detected viral fragment confirmed an identical nucleotide sequence to that of the SARS-CoV-2 isolated from human samples. The virus was also detected in sewage treatment facilities, which serve populations of approximately 40,000 to more than one million people.

Rehabilitation programs for patients with COronaVIrus Disease 2019: consensus statements of Taiwan Academy of Cardiovascular and Pulmonary Rehabilitation.

The COronaVIrus Disease 2019 (COVID-19), which developed into a pandemic in 2020, has become a major healthcare challenge for governments and healthcare workers worldwide. Despite several medical treatment protocols having been established, a comprehensive rehabilitation program that can promote functional recovery is still frequently ignored. An online consensus meeting of an expert panel comprising members of the Taiwan Academy of Cardiovascular and Pulmonary Rehabilitation was held to provide recommendations for rehabilitation protocols in each of the five COVID-19 stages, namely (1) outpatients with mild disease and no risk factors, (2) outpatients with mild disease and epidemiological risk factors, (3) hospitalized patients with moderate to severe disease, (4) ventilator-supported patients with clear cognitive function, and (5) ventilator-supported patients with impaired cognitive function. Apart from medications and life support care, a proper rehabilitation protocol that facilitates recovery from COVID-19 needs to be established and emphasized in clinical practice.