Effects of Tai Chi practice on postural sway for older people during COVID-19 pandemic (preprint)

Tai Chi has been promoted for older people to prevent falls and may be seen as a priority exercise during coronavirus (COVID-19) pandemic. The purpose of this study was to investigate the effects of Tai Chi practice on standing balance for older people in a nursing home. Thirty-eight older people recruited during COVID-19 extended restrictions, a Tai Chi group who were regularly performed Tai Chi during the periods (n = 18, more than five-year experience) and Control group (n = 20, no Tai Chi experience). Postural sway during standing balance was quantified under four different conditions:1) eyes open (EO); 2) eyes closed (EC); 3) eyes open and cross step with right leg forward (ER) and 4) with left leg forward (EL). Significantly less postural sway was observed in the Tai Chi group, particularly during EO and EL conditions. The findings of this study support the positive effects of Tai Chi practice on balance control. During COVID-19, although older people living in the nursing home limited their outdoor mobility, Tai Chi practice may maintain their physical function on a standing balance.

The Impact of Post Embryo Transfer SARS-CoV-2 Infection on Pregnancy in In Vitro Fertilization: A Prospective Cohort Study (preprint)

ImportanceLimited knowledge exists on the effects of SARS-CoV-2 infection after embryo transfer, despite an increasing number of studies exploring the impact of previous SARS-CoV-2 infection on IVF outcomes. ObjectiveThis prospective cohort study aimed to assess the influence of SARS-CoV-2 infection at various time stages after embryo transfer on pregnancy outcomes in patients undergoing conventional in vitro fertilization/intracytoplasmic sperm injection-embryo transfer (IVF/ICSI) treatment. DesignThe study was conducted at a single public IVF center in China. SettingThis was a population-based prospective cohort study. ParticipantsFemale patients aged 20 to 39 years, with a body mass index (BMI) between 18 and 30 kg/m2, undergoing IVF/ICSI treatment, were enrolled from September 2022 to December 2022, with follow-up until March 2023. ExposureThe pregnancy outcome of patients was compared between those SARS-CoV-2-infected after embryo transfer and those noninfected during the follow-up period. Main Outcomes and MeasuresThe pregnancy outcomes included biochemical pregnancy rate, implantation rate, clinical pregnancy rate, and early miscarriage rate. ResultsA total of 857 female patients undergoing IVF/ICSI treatment were included in the analysis. We observed the incidence of SARS-CoV-2 infection within 10 weeks after embryo transfer. The biochemical pregnancy rate and implantation rate were lower in the infected group than the uninfected group (58.1% vs 65.9%; 36.6% vs 44.0%, respectively), but no statistically significant. Although, the clinical pregnancy rate was significant lower in the infection group when compared with the uninfected group (49.1%vs 58.2%, p < 0.05), after adjustment for confounders, this increased risk was no longer significant between the two groups (adjusted OR, 0.736, 95% CI, 0.518-1.046). With continued follow-up, a slightly higher risk of early miscarriage in the infected group compared to the uninfected group (9.3% vs 8.8%), but it was not significant (adjusted OR, 0.907, 95% CI, 0.414-1.986). Conclusions and RelevanceThe studys findings suggested that SARS-CoV-2 infection within 10 weeks after embryo transfer may have not significantly affect pregnancy outcomes. This evidence allays concerns and provides valuable insights for assisted reproduction practices. Key pointsO_ST_ABSQuestionC_ST_ABSDid the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) after embryo transfer affect pregnancy outcomes? FindingsIn this prospective cohort study involving 857 patients, we made a pioneering discovery that SARS-CoV-2 infection following embryo transfer did not exhibit adverse impact on the biochemical pregnancy rate, embryo implantation rate, clinical pregnancy rate, and early miscarriage rate. MeaningThe evidence from this study alleviates existing concerns and offers new insights into the actual risk of SARS-CoV-2 infection after embryo transfer in assisted reproduction.

Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI (preprint)

Heterogeneous data is endemic due to the use of diverse models and settings of devices by hospitals in the field of medical imaging. However, there are few open-source frameworks for federated heterogeneous medical image analysis with personalization and privacy protection simultaneously without the demand to modify the existing model structures or to share any private data. In this paper, we proposed PPPML-HMI, an open-source learning paradigm for personalized and privacy-preserving federated heterogeneous medical image analysis. To our best knowledge, personalization and privacy protection were achieved simultaneously for the first time under the federated scenario by integrating the PerFedAvg algorithm and designing our novel cyclic secure aggregation with the homomorphic encryption algorithm. To show the utility of PPPML-HMI, we applied it to a simulated classification task namely the classification of healthy people and patients from the RAD-ChestCT Dataset, and one real-world segmentation task namely the segmentation of lung infections from COVID-19 CT scans. For the real-world task, PPPML-HMI achieved $\sim$5\% higher Dice score on average compared to conventional FL under the heterogeneous scenario. Meanwhile, we applied the improved deep leakage from gradients to simulate adversarial attacks and showed the solid privacy-preserving capability of PPPML-HMI. By applying PPPML-HMI to both tasks with different neural networks, a varied number of users, and sample sizes, we further demonstrated the strong robustness of PPPML-HMI.

Construction and application of a cold chain logistics supervision platform for agricultural products in port areas during the COVID-19 pandemic

Diversification of agricultural imports is an important strategy for ensuring food security in China. During the COVID-19 pandemic, agricultural cold chain logistics are facing new challenges but also a new round of rapid development opportunities. It's particularly critical to determine how to build the first line of defense in port areas for the supervision of agricultural products to ensure the safety and reliability of incoming cargo. In recent years, China has continued to strengthen the construction of its regulatory traceability system for imported agricultural products, but there are still weak links and a lack of connectivity in the overall construction of the system. In this paper, we propose a supervision platform that addresses the problems of weak correlation and traceability of the cold chain logistics information on agricultural products in port areas during the COVID-19 pandemic. Relying on low-power-based radio frequency identification technology, the platform is combined with wireless sensor networks to collect key real-time data on the microenvironment, including temperature and humidity, influencing the cold chain logistics links of imported agricultural products. The platform unites multiple entities, including production, distribution, operation, and supervision entities, to build a pool of basic information data, such as inspection and quarantine certificates, nucleic acid test reports, and disinfection certificates for imported agricultural products. It integrates the core technologies of the new generation, the Internet of Things, the Internet, big data, cloud computing, and block chain, and builds a standard data flow and database to identify the key links and elements affecting the quality and safety of agricultural products from a large amount of data with the help of advanced algorithms. We establish risk controls and early warnings for imported agricultural products, build a traceability model, and then explore the creation of a comprehensive supervision platform in the port area, undertaking key data cleaning, integration, analysis, and sharing. The platform provides powerful support for government supervision, analysis, and decision-making, including emergency responses and public inquiries, combines "physical defense" and "human defense" in the cold chain logistics network for imported agricultural products, and promotes the improvement of the supervisory system for cold chain logistics of agricultural products in port areas.

Quantitative detection of SARS-CoV-2 antigen: an effective approach for evaluating the infectivity of COVID- 19 convalescent patients (preprint)

BackgroundThis study evaluated the quantitative detection of SARS-CoV-2 antigen by the MAGLUMI chemiluminescent immunoassay (MAG-CLIA) in COVID-19 patients during the peak of COVID-19 Shanghai epidemics in a tertiary hospital in Shanghai.MethodsAnalytical performances of the MAG-CLIA were evaluated, including precision, limit of quantitation (LoQ), linearity and specificity. Nasopharyngeal specimens from 232 patients who were SARS-CoV-2 RT-qPCR positive and from 477 healthy donors were included to evaluate the diagnostic performance. The performance of the Wondfo antigen-detecting lateral flow test (LFT) was evaluated in parallel. The longitudinal studies were performed by monitoring antigen concentrations alongside with RT-qPCR results in 14 COVID-19 participants for up to 22 days. The critical antigen concentration in determining virus infectivity was evaluated at the reference cycle threshold (Ct) of 35.ResultsCOVID-19 patients were well-identified using an optimal threshold of 0.64 pg/mL antigen concentration, with sensitivity and specificity of 95.7% (95% CI: 92.2%-97.9%) and 98.3% (95% CI: 96.7%-99.3%), respectively, while the Wondfo LFT exhibited those of 34.9% (95% CI: 28.8%-41.4%) and 100% (95% CI: 99.23%-100%), respectively. Close dynamic consistence was observed between SARS-CoV-2 Ag and viral load time series in the longitudinal studies. The critical value of 8.82 pg/mL antigen showed adequate sensitivity and specificity in evaluating the infectivity of convalescent patients.ConclusionsThe MAG-CLIA SARS-CoV-2 Ag detection is an effective and alternative approach for rapid diagnosis and enables us to evaluate the infectivity of convalescent patients.

Reinforcing the Supply Chain of Umifenovir and Other Antiviral Drugs with Retrosynthetic Software (preprint)

The global disruption caused by the 2020 coronavirus pandemic stressed the supply chain of many products, including pharmaceuticals. Multiple drug repurposing studies for COVID-19 are now underway. If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it, will be available in the quantities required. We used retrosynthetic software to arrive at alternate chemical supply chains for the antiviral drug umifenovir, as well as eleven other antiviral and anti-inflammatory drugs. We have experimentally validated four routes to umifenovir and one route to bromhexine. In several instances, the software utilizes C–H functionalization logic, and one route to umifenovir employs functionalization of six C–H bonds. The general strategy we apply can be used to identify distinct starting materials, and relieve stress on existing supply chains.

A systematic review of prediction methods for emergency management

With the trend of global warming and destructive human activities, the frequent occurrences of catastrophes have posed devastating threats to human life and social stability worldwide. The emergency management (EM) system plays a significant role in saving people's lives and reducing property damage. The prediction system for the occurrence of emergency events and resulting impacts is widely recognized as the first stage of the EM system, the accuracy of which has a significant impact on the efficiency of resource allocation, dispatching, and evacuation. In fact, the number and variety of contributions to prediction techniques, such as statistic analysis, artificial intelligence, and simulation method, are exploded in recent years, motivating the need for a systematic analysis of the current works on disaster prediction. To this end, this paper presents a systematic review of contributions on prediction methods for emergency occurrence and resource demand of both natural and man-made disasters. Through a detailed discussion on the features of each type of emergency event, this paper presents a comprehensive survey of state-of-the-art prediction technologies which have been widely applied in EM. After that, we summarize the challenges of current efforts and point out future directions.

Thoughts and practice of introducing immunodiagnosis, immunoprophylaxis and immunotherapy of COVID-19 into medical immunology online teaching

The outbreak of COVID-19 has made us recognize the importance of immunology. In combination with the research of immunology in the field of COVID-19, we intend to integrate immunodiagnosis, immunoprophylaxis and immunotherapy into the online teaching of Medical Immunology and discuss latest progress of COVID-19. Its purpose is to enhance the practicability and pertinence of teaching contents, and improve students' application ability and transformation ability, so that they can apply their knowledge to the needs of disease prevention and treatment.

A Method to evaluate analytical sensitivity of qRT-PCR kits for SARS-CoV-2 detection (preprint)

Background: The ongoing Coronavirus disease 2019 (COVID-19) pandemic has spread across the globe and is representing a huge challenge for all human population. Many commercial qRT-PCR assays have been developed to detect SARS-CoV-2, but related method validation especially the sensitivity evaluation has been insufficient, resulting in some false-negative cases have been reported. Methods: The analytical sensitivity of nine brands of qRT-PCR kits for detecting SARS-CoV-2 was evaluated in parallel based on a newly developed certified reference material, which was derived from genomic RNA of SARS-CoV-2 from clinical positive specimens. After validation of the the reference material by digital PCR, the detection sensitivity of these kits was preliminarily tested using the serially diluted reference material, resulting in three kits with two significantly different sensitivity levels were selected for further evaluation. We sequenced the qRT-PCR products for assay specificity evaluation, and used serial dilutions of the reference material to calculate amplification efficiency and estimate the limit of quantification as well as 95% limit of detection..Results: The results indicated that the analytical sensitivity varied markedly among these kits. For the three types of qRT-PCR kits (Kit-1, Kit-2 and Kit-7), specificity of the PCR products was confirmed by sequence alignment, in which the target amplicons completely matched the corresponding parts of the genome of SARS-CoV-2. The resulting limit of detection from replicate tests for the Kit-1 and Kit-2 was 5.6 copies (N), 3.5 copies (ORF 1ab), and 6.4 copies (N), 4.6 copies (ORF 1ab), respectively, at 95% probability. Compared with Kit-7, the limit of detection as well as limit of quantification of Kit-1 and Kit-2 were significantly lower, further supporting that the both kits worked well to detect low abundance of SARS-CoV-2.Conclusions: Considering that most of the tested kits have been approved for in vitro diagnostics (IVD) in China, the established method here provides a reliable tool to evaluate the sensitivity performance of various qRT-PCR kits for SARS-CoV-2 detection and thus enhance quality control of qRT-PCR assays, improving the laboratory diagnostic capability for fighting the COVID-19 pandemic.

Reinforcing the Supply Chain of COVID-19 Therapeutics with Expert-Coded Retrosynthetic Software (preprint)

Supply chains become stressed when demand for essential products increases rapidly in times of crisis. This year, the scourge of coronavirus highlighted the fragility of diverse supply chains, affecting the world’s pipeline of hand sanitizer, 1 toilet paper,2 and pharmaceutical starting materials. 3 Many drug repurposing studies are now underway. 4 If a winning therapeutic emerges, it is unlikely that the existing inventory of the medicine, or even the chemical raw materials needed to synthesize it,5 will be available in the quantities required to satisfy global demand. We show the use of a retrosynthetic artificial intelligence (AI) 6-10 to navigate multiple parallel synthetic sequences, and arrive at plausible alternate reagent supply chains for twelve investigational COVID-19 therapeutics. In many instances, the AI utilizes C–H functionalization logic, 11-13 and we have experimentally validated several syntheses, including a route to the antiviral umifenovir that requires functionalization of six C–H bonds. This general solution to chemical supply chain reinforcement will be useful during global disruptions, such as during a pandemic.

Targeted Pandemic Containment Through Identifying Local Contact Network Bottlenecks (preprint)

Decision-making about pandemic mitigation often relies upon simulation modelling. Models of disease transmission through networks of contacts--between individuals or between population centres--are increasingly used for these purposes. Real-world contact networks are rich in structural features that influence infection transmission, such as tightly-knit local communities that are weakly connected to one another. In this paper, we propose a new flow-based edge-betweenness centrality method for detecting bottleneck edges that connect nodes in contact networks. In particular, we utilize convex optimization formulations based on the idea of diffusion with p-norm network flow. Using simulation models of COVID-19 transmission through real network data at both individual and county levels, we demonstrate that targeting bottleneck edges identified by the proposed method reduces the number of infected cases by up to 10% more than state-of-the-art edge-betweenness methods. Furthermore, the proposed method is orders of magnitude faster than existing methods.

Highly accurate and sensitive diagnostic detection of SARS-CoV-2 by digital PCR (preprint)

BACKGROUND: The outbreak of COVID-19 caused by a novel Coronavirus (termed SARS-CoV-2) has spread to over 140 countries around the world. Currently, reverse transcription quantitative qPCR (RT-qPCR) is used as the gold standard for diagnostics of SARS-CoV-2. However, the positive rate of RT-qPCR assay of pharyngeal swab samples are reported to vary from 30~60%. More accurate and sensitive methods are urgently needed to support the quality assurance of the RT-qPCR or as an alternative diagnostic approach. METHODSWe established a reverse transcription digital PCR (RT-dPCR) protocol to detect SARS-CoV-2 on 194 clinical pharyngeal swab samples, including 103 suspected patients, 75 close contacts and 16 supposed convalescents. RESULTS: The limit of blanks (LoBs) of the RT-dPCR assays were ~1.6, ~1.6 and ~0.8 copies/reaction for ORF 1ab, N and E genes, respectively. The limit of detection (LoD) was 2 copies/reaction. For the 103 fever suspected patients, the sensitivity of SARS-CoV-2 detection was significantly improved from 28.2% by RT-qPCR to 87.4% by RT-dPCR. For close contacts, the suspect rate was greatly decreased from 21% down to 1%. The overall sensitivity, specificity and diagnostic accuracy of RT-dPCR were 90%, 100% and 93 %, respectively. In addition, quantification of the viral load for convalescents by RT-dPCR showed that a longer observation period was needed in the hospital for elderly patients. CONCLUSION: RT-dPCR could be a confirmatory method for suspected patients diagnosed by RT-qPCR. Furthermore, RT-dPCR was more sensitive and suitable for low viral load specimens from the both patients under isolation and those under observation who may not be exhibiting clinical symptoms.