COVID-19 knowledge deconstruction and retrieval: an intelligent bibliometric solution.

COVID-19 has been an unprecedented challenge that disruptively reshaped societies and brought a massive amount of novel knowledge to the scientific community. However, as this knowledge flood continues surging, researchers have been disadvantaged by not having access to a platform that can quickly synthesize emerging information and link the new knowledge to the latent knowledge foundation. Aiming to fill this gap, we propose a research framework and develop a dashboard that can assist scientists in identifying, retrieving, and understanding COVID-19 knowledge from the ocean of scholarly articles. Incorporating principal component decomposition (PCD), a knowledge mode-based search approach, and hierarchical topic tree (HTT) analysis, the proposed framework profiles the COVID-19 research landscape, retrieves topic-specific latent knowledge foundation, and visualizes knowledge structures. The regularly updated dashboard presents our research results. Addressing 127,971 COVID-19 research papers from PubMed, the PCD topic analysis identifies 35 research hotspots, along with their inner correlations and fluctuating trends. The HTT result segments the global knowledge landscape of COVID-19 into clinical and public health branches and reveals the deeper exploration of those studies. To supplement this analysis, we additionally built a knowledge model from research papers on the topic of vaccination and fetched 92,286 pre-Covid publications as the latent knowledge foundation for reference. The HTT analysis results on the retrieved papers show multiple relevant biomedical disciplines and four future research topics: monoclonal antibody treatments, vaccinations in diabetic patients, vaccine immunity effectiveness and durability, and vaccination-related allergic sensitization.

Multi-bioinspired hierarchical integrated hydrogel for passive fog harvesting and solar-driven seawater desalination.

In recent years, with the outbreak and epidemic of the novel coronavirus in the world, how to obtain clean water from the limited resources has become an urgent issue of concern to all mankind. Atmospheric water harvesting technology and solar-driven interfacial evaporation technology have shown great potential in seeking clean and sustainable water resources. Here, inspired by a variety of organisms in nature, a multi-functional hydrogel matrix composed of polyvinyl alcohol (PVA), sodium alginate (SA) cross-linked by borax as well as doped with zeolitic imidazolate framework material 67 (ZIF-67) and graphene owning macro/micro/nano hierarchical structure has successfully fabricated for producing clean water. The hydrogel not only can reach the average water harvesting ratio up to 22.44 g g-1 under the condition of fog flow after 5 h, but also be capable of desorbing the harvested water with water release efficiency of 1.67 kg m-2 h-1 under 1 sun. In addition to excellent performance in passive fog harvesting, the evaporation rate over 1.89 kg m-2 h-1 is attained under 1 sun on natural seawater during long-term. This hydrogel indicates its potential in producing clean water resources in multiple scenarios in different dry or wet states, and which holds great promise for flexible electronic materials and sustainable sewage or wastewater treatment applications.

The post-discharge coping difficulty of puerperal women in a middle and low-income tourist city during the COVID-19 pandemic.

BACKGROUND: Since the coronavirus disease 2019 (COVID-19) pandemic outbreak, the incidence of mental health problems in perinatal women has been high, and particularly prominent in China which was the first country affected by COVID-19. This paper aims to investigate the current situation and the related factors of maternal coping difficulties after discharge during COVID-19. METHODS: General information questionnaires (the Perinatal Maternal Health Literacy Scale, Postpartum Social Support Scale and Post-Discharge Coping Difficulty Scale-New Mother Form) were used to investigate 226 puerperal women in the third week of puerperium. The influencing factors were analyzed by single factor analysis, correlation and multiple linear regression. RESULTS: The total score of coping difficulties after discharge was 48.92 ± 12.05. At the third week after delivery, the scores of health literacy and social support were 21.34 ± 5.18 and 47.96 ± 12.71. There were negative correlations among health literacy, social support and coping difficulties after discharge (r = -0.34, r = -0.38, P < 0.001). Primipara, family income, health literacy and social support were the main factors influencing maternal coping difficulties after discharge. CONCLUSION: During the COVID-19 pandemic, puerperal women in a low- and middle-income city had moderate coping difficulties after discharge and were affected by many factors. To meet the different needs of parturients and improve their psychological coping ability, medical staff should perform adequate assessment of social resources relevant to parturients and their families when they are discharged, so they can smoothly adapt to the role of mothers.

Biology-Informed Recurrent Neural Network for Pandemic Prediction Using Multimodal Data.

In the biomedical field, the time interval from infection to medical diagnosis is a random variable that obeys the log-normal distribution in general. Inspired by this biological law, we propose a novel back-projection infected-susceptible-infected-based long short-term memory (BPISI-LSTM) neural network for pandemic prediction. The multimodal data, including disease-related data and migration information, are used to model the impact of social contact on disease transmission. The proposed model not only predicts the number of confirmed cases, but also estimates the number of infected cases. We evaluate the proposed model on the COVID-19 datasets from India, Austria, and Indonesia. In terms of predicting the number of confirmed cases, our model outperforms the latest epidemiological modeling methods, such as vSIR, and intelligent algorithms, such as LSTM, for both short-term and long-term predictions, which shows the superiority of bio-inspired intelligent algorithms. In general, the use of mobility information improves the prediction accuracy of the model. Moreover, the number of infected cases in these three countries is also estimated, which is an unobservable but crucial indicator for the control of the pandemic.

Predicting the impact of the COVID-19 pandemic on globalization.

The COVID-19 pandemic has significantly influenced the global economy, international travel, global supply chains, and how people interact, and subsequently affect globalization in coming years. In order to understand the impact of COVID-19 on globalization and provide potential guidance to policymakers, the present study predicted the globalization level of the world average and 14 specific countries in scenarios with and without COVID-19 based on a new Composite Indicator method which contains 15 indicators. Our results revealed that the world average globalization level is expected to decrease from 2017 to 2025 under the scenario without COVID-19 by -5.99%, while the decrease of globalization under the COVID-19 scenario is predicted to reach -4.76% in 2025. This finding implies that the impact of COVID-19 on globalization will not be as severe as expected in 2025. Nevertheless, the downward trend of globalization without COVID-19 is due to the decline of the Environmental indicators, whereas the decline under the COVID-19 scenario is attributed to Economic aspects (almost -50%). The impact of COVID-19 on globalization varies across individual countries. Among the countries investigated, COVID-19 had a positive impact on the globalization of Japan, Australia, the United States, the Russian Federation, Brazil, India and Togo. In contrast, the globalization in the United Kingdom, Switzerland, Qatar, Egypt, China and Gabon are expected to decrease. The variation of impact induced by COVID-19 on those countries is attributed to the weighting of economic, environmental and political aspects of globalization is different across these countries. Our results can help governments take suitable measures to balance economic, environmental and political policies, which may better support their decision-making.

[Clinical features of severe acute respiratory syndrome coronavirus 2 Omicron variant infection in children: an analysis of 201 cases]. / 201ä¾‹å„¿ç«¥æ–°åž‹å† çŠ¶ç— æ¯’Omicronå˜å¼‚æ ªæ„ŸæŸ“çš„ä¸´åºŠç‰¹å¾åˆ†æž.

OBJECTIVES: To study the clinical features of children with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant infection. METHODS: A retrospective analysis was performed on the medical data of 201 children with coronavirus disease 2019 (COVID-19) who were hospitalized and diagnosed with SARS-CoV-2 Omicron variant infection in Quanzhou First Hospital from March 14 to April 7, 2022. Among the 201 children, there were 34 children with asymptomatic infection and 167 with symptomatic infection. The two groups were compared in terms of clinical features, results of experimental examinations, and outcome. RESULTS: Of all the 201 children, 161 (80.1%) had a history of exposure to COVID-19 patients and 132 (65.7%) had a history of COVID-19 vaccination. Among the 167 children with symptomatic infections, 151 had mild COVID-19 and 16 had common COVID-19, with no severe infection or death. Among the 101 children who underwent chest CT examination, 16 had ground glass changes and 20 had nodular or linear opacities. The mean time to nucleic acid clearance was (14±4) days for the 201 children with Omicron variant infection, and the symptomatic infection group had a significantly longer time than the asymptomatic infection group [(15±4) days vs (11±4) days, P<0.05]. The group vaccinated with one or two doses of COVID-19 vaccine had a significantly higher positive rate of IgG than the group without vaccination (P<0.05). The proportions of children with increased blood lymphocyte count in the symptomatic infection group was significantly lower than that in the asymptomatic infection group (P<0.05). Compared with the asymptomatic infection group, the symptomatic infection group had significantly higher proportions of children with increased interleukin-6, increased fibrinogen, and increased D-dimer (P<0.05). CONCLUSIONS: Most of the children with Omicron variant infection have clinical symptoms, which are generally mild. The children with symptomatic infection are often accompanied by decreased or normal blood lymphocyte count and increased levels of interleukin-6, fibrinogen, and D-dimer, with a relatively long time to nucleic acid clearance. Some of them had ground glass changes on chest CT.

Effect of non-pharmaceutical interventions in the early phase of the COVID-19 epidemic in Saudi Arabia

Non-pharmaceutical interventions have been widely employed to control the COVID-19 pandemic. Their associated effect on SARS-CoV-2 transmission have however been unequally studied across regions. Few studies have focused on the Gulf states despite their potential role for global pandemic spread, in particular in the Kingdom of Saudi Arabia through religious pilgrimages. We study the association between NPIs and SARS-CoV-2 transmission in the Kingdom of Saudi Arabia during the first pandemic wave between March and October 2020. We infer associations between NPIs introduction and lifting through a spatial SEIR-type model that allows for inferences of region-specific changes in transmission intensity. We find that reductions in transmission were associated with NPIs implemented shortly after the first reported case including Isolate and Test with School Closure (region-level mean estimates of the reduction in R0 ranged from 25–41%), Curfew (20–70% reduction), and Lockdown (50–60% reduction), although uncertainty in the estimates was high, particularly for the Isolate and Test with School Closure NPI (95% Credible Intervals from 1% to 73% across regions). Transmission was found to increase progressively in most regions during the last part of NPI relaxation phases. These results can help informing the policy makers in the planning of NPI scenarios as the pandemic evolves with the emergence of SARS-CoV-2 variants and the availability of vaccination.

CRISPR‐Cas Biochemistry and CRISPR‐Based Molecular Diagnostics

Polymerase chain reaction (PCR)‐based nucleic acid testing has played a critical role in disease diagnostics, pathogen surveillance, and many more. However, this method requires a long turnaround time, expensive equipment, and trained personnel, limiting its widespread availability and diagnostic capacity. On the other hand, the clustered regularly interspaced short palindromic repeats (CRISPR) technology has recently demonstrated capability for nucleic acid detection with high sensitivity and specificity. CRISPR‐mediated biosensing holds great promise for revolutionizing nucleic acid testing procedures and developing point‐of‐care diagnostics. This review focuses on recent developments in both fundamental CRISPR biochemistry and CRISPR‐based nucleic acid detection techniques. Four ongoing research hotspots in molecular diagnostics‐target preamplification‐free detection, microRNA (miRNA) testing, non‐nucleic‐acid detection, and SARS‐CoV‐2 detection‐are also covered.

COVID-19-induced neurological symptoms: focus on the role of metal ions.

Neurological symptoms are prevalent in both the acute and post-acute phases of coronavirus disease 2019 (COVID-19), and they are becoming a major concern for the prognosis of COVID-19 patients. Accumulation evidence has suggested that metal ion disorders occur in the central nervous system (CNS) of COVID-19 patients. Metal ions participate in the development, metabolism, redox and neurotransmitter transmission in the CNS and are tightly regulated by metal ion channels. COVID-19 infection causes neurological metal disorders and metal ion channels abnormal switching, subsequently resulting in neuroinflammation, oxidative stress, excitotoxicity, neuronal cell death, and eventually eliciting a series of COVID-19-induced neurological symptoms. Therefore, metal homeostasis-related signaling pathways are emerging as promising therapeutic targets for mitigating COVID-19-induced neurological symptoms. This review provides a summary for the latest advances in research related to the physiological and pathophysiological functions of metal ions and metal ion channels, as well as their role in COVID-19-induced neurological symptoms. In addition, currently available modulators of metal ions and their channels are also discussed. Collectively, the current work offers a few recommendations according to published reports and in-depth reflections to ameliorate COVID-19-induced neurological symptoms. Further studies need to focus on the crosstalk and interactions between different metal ions and their channels. Simultaneous pharmacological intervention of two or more metal signaling pathway disorders may provide clinical advantages in treating COVID-19-induced neurological symptoms.

Application of Hybrid Swarming Algorithm on a UAV Regional Logistics Distribution.

This paper proposes a hybrid algorithm based on the ant colony and Physarum Polycephalum algorithms. The positive feedback mechanism is used to find the globally optimal path. The crossover and mutation operations of the genetic algorithm are introduced into the path search mechanism for the first time. The Van der Waals force is applied to the pheromone updating mechanism. Simulation results show that the improved algorithm has advantages in quality and speed of solution compared with other mainstream algorithms. This paper provides fast and accurate route methods for solving the Traveling Salesman Problem first and a delivery scheme is also presented for UAVs to realize "contactless delivery" to users in the Changchun Mingzhu District during the COVID-19 epidemic, which confirms the practicability and robustness of the algorithm.

Using an influenza surveillance system to estimate the number of SARS-CoV-2 infections in Beijing, China, weeks 2 to 6 2023.

With COVID-19 public health control measures downgraded in China in January 2023, reported COVID-19 case numbers may underestimate the true numbers after the SARS-CoV-2 Omicron wave. Using a multiplier model based on our influenza surveillance system, we estimated that the overall incidence of SARS-CoV-2 infections was 392/100,000 population in Beijing during the 5 weeks following policy adjustment. No notable change occurred after the Spring Festival in early February. The multiplier model provides an opportunity for assessing the actual COVID-19 situation.

Chronic Liver Disease and Cirrhosis are Associated with Worse Outcomes Following SARS-CoV-2 Infection.

Background and aims: Studies evaluating the impact of SARS-CoV-2 on chronic liver disease (CLD) are limited and have focused mostly on hospitalized patients or those with cirrhosis. We aim to evaluate the impact of underlying CLD on patient outcomes following COVID-19 using a one of the largest COVID-19+CLD cohorts to date. Methods: Data from the COVID-19 Research Database (https://covid19researchdatabase.org) were evaluated from April 1, 2020, to August 31, 2021, to determine whether concurrent CLD was associated with worse outcomes within 30 day of COVID-19 diagnosis, including need for hospitalization, pneumonia, severe pneumonia, respiratory failure, and multiorgan failure. Among patients with COVID-19+CLD, risks of liver decompensation and acute on chronic liver failure (ACLF) were evaluated, stratified by presence of cirrhosis. Adjusted multivariate logistic regression models evaluated the impact of CLD on COVID-19 outcomes. Results: In total, 1,208,905 unique patients with COVID-19 were identified; 44,008 (3.6%) had concurrent CLD, among which 6515 (14.8%) had cirrhosis. Compared to patients without CLD, COVID-19+CLD patients were significantly more likely to require hospitalization (aOR 1.65, 95% CI 1.61-1.69), develop pneumonia (aOR 1.11, 95% CI 1.08-1.14), severe pneumonia (aOR 1.74, 95% CI 1.62-1.86), respiratory failure (aOR 1.14, 95% CI 1.10-1.17), and multiorgan failure (aOR 1.84, 95% CI 1.72-1.97), P < 0.0001 for all. Among COVID-19+CLD patients, underlying cirrhosis was associated with even higher risk of these poor outcomes, and higher risk of acute liver decompensation or ACLF. Conclusions: Among one of the largest studies to date evaluating patients with COVID-19 and CLD, underlying CLD is associated with significantly greater risk of poor outcomes following SARS-CoV-2 infection, particularly among cirrhotic patients.

CRISPR-Cas Biochemistry and CRISPR-Based Molecular Diagnostics.

Polymerase chain reaction (PCR)-based nucleic acid testing has played a critical role in disease diagnostics, pathogen surveillance, and many more. However, this method requires a long turnaround time, expensive equipment, and trained personnel, limiting its widespread availability and diagnostic capacity. On the other hand, the clustered regularly interspaced short palindromic repeats (CRISPR) technology has recently demonstrated capability for nucleic acid detection with high sensitivity and specificity. CRISPR-mediated biosensing holds great promise for revolutionizing nucleic acid testing procedures and developing point-of-care diagnostics. This review focuses on recent developments in both fundamental CRISPR biochemistry and CRISPR-based nucleic acid detection techniques. Four ongoing research hotspots in molecular diagnostics-target preamplification-free detection, microRNA (miRNA) testing, non-nucleic-acid detection, and SARS-CoV-2 detection-are also covered.

Case Report: A case of multisystem inflammatory syndrome in an 11-year-old female after COVID-19 inactivated vaccine.

Background: Multisystem inflammatory syndrome in children (MIS-C), also known as pediatric inflammatory, multisystem syndrome temporally associated with SARS-CoV-2, is a rare but serious complication of SARS-CoV-2 infection in children that typically occurs 2-6 weeks after SARS-CoV-2 infection. The pathophysiology of MIS-C is unknown. MIS-C, first recognized in April 2020, is characterized by fever, systemic inflammation, and multi-system organ involvement. Post-vaccination adverse effects have increased with COVID-19 vaccinations, and MIS linked to immunization with COVID-19 vaccines has also been observed. Case Report: An 11-year-old Chinese girl presented with a high-grade fever, rash, and dry cough for 2 days. She had her 2nd SARS-CoV-2 inactivated vaccination dose five days before hospital admission. On day 3 & 4, she experienced bilateral conjunctivitis, hypotension (66/47 mmHg), and a high CRP level. She was diagnosed with MIS-C. The patient's condition deteriorated rapidly, necessitating intensive care unit admission. The patient's symptoms improved after intravenous immunoglobulin, methylprednisolone, and oral aspirin therapy. She was discharged from the hospital after 16 days as her general condition, and laboratory biomarkers returned to normal. Conclusion: Inactivated Covid-19 vaccination might trigger MIS-C. Further research is needed to evaluate whether a correlation exists between COVID-19 vaccination and MIS-C development.

Forecasting on metal resource spot settlement price: New evidence from the machine learning model

Accurate prediction of the price of metal mineral resources is of great practical significance for guiding the production of non-renewable resource enterprises and maintaining the stability of related economic price indexes. Based on the daily frequency spot settlement price data of lead, aluminium, aluminium alloy, tin, copper(A) and other metal minerals from Sep. 21, 2005 to Dec. 1, 2021, machine learning method is used to analyze the accuracy of hybrid models for predicting spot settlement prices of metal minerals. Firstly, we compared and analyzed the in-sample prediction accuracy of different models in spot settlement price of metal minerals, and found that the prediction accuracy of LSTM-GRU and LSTM-CNN models is significantly better than other models. Secondly, we verified the out-of-sample prediction results of spot settlement prices of metal minerals, which further demonstrates the robustness of the prediction accuracy of the LSTM hybrid model. Finally, we considered the impact of COVID-19 and explored the prediction accuracy of different hybrid models on spot settlement prices of metal minerals. We found that LSTM-GRU and other models also perform well with strong robustness. Therefore, we believed that the LSTM hybrid model, especially the LSTM-GRU model, is suitable for analyzing the prediction of spot settlement price of metal minerals.

The correlation between lifestyle health behaviors, coping style, and mental health during the COVID-19 pandemic among college students: Two rounds of a web-based study.

Background: During the last months of 2019, worldwide attention has focused on a pandemic of COVID-19, and the pandemic spread rapidly, becoming a public health emergency of international concern. The Chinese government has quickly taken quarantine measures and the drastic measures incurred to curtail it, which could have harmful consequences for everyone's behavior and mental health. Objective: This study aimed to investigate the correlation of influencing factors and mental health symptoms among Chinese college students according to two rounds of surveys during the COVID-19 pandemic. Materials and methods: This study was divided into two stages of cross-sectional investigation. In February 2020 and May 2020, two cross-sectional surveys were conducted on college students in the above areas by means of cluster sampling. From February 4 to February 12, 2020, 14,789 college students completed the first round of online study from 16 cities and universities in 21 in China, excluding participants who completed the questionnaire, and finally included 11,787 college students. After 3 months, we also conducted a large-scale questionnaire survey based on the first study area to observe the behavioral changes and psychological symptoms of college students within 3 months. Using the convenience sampling method, a survey on the cognitive and psychological status of COVID-19 among college students was conducted in 21 universities in 16 regions in May 2020. The regions among the two surveys are divided into Wuhan (District 1), neighboring Hubei (District 2), first-tier cities, namely, Beijing, Shanghai and Guangzhou (District 3), and other provinces (District 4). Results: (1) In the first survey, the average age of the participants was 20.51 ± 1.88 years. One-third of the college students were male. In total, 25.9 and 17.8% of college students reported depression and anxiety symptoms, respectively. College students, who reported higher ST, lower PA, higher soda beverage and tea beverage intake, have Chinese herbal medicine and vitamin drinking, and decreased frequency of diet had higher depression and anxiety symptoms. Moreover, infection risk, perceived resistance to COVID-19, concerns about physical symptoms, family/friends directly/indirectly contacted with confirmed cases, and seeking psychological counseling had significant associations with anxiety and depression symptoms. (2) In the second round of surveys, 6803 males (41.7%) and 9502 females (58.3%) had a mean age of 20.58 ± 1.81 years. The prevalence of depressive symptoms and anxiety symptoms during COVID-19 was 30.7 and 23.9%, respectively. (3) In both surveys, college students who reported having higher ST, lower PA, higher soda beverage and tea beverage intake, Chinese herbal medicine and vitamin drinking, and decreased frequency of diet also had higher depression and anxiety symptoms. Coping styles with COVID-19 partially mediate the association between some related lifestyle behaviors and anxiety and depression. The results of the conditional process model analysis support our hypothesis that lifestyle behaviors, and coping styles are both predictors of anxiety and depression symptoms, with both direct and indirect effects moderated by gender level. In logistic regression analysis, the correlation of depression and anxiety in the second rounds of the survey was higher than that in the first survey. In two surveys, there was a correlation between lifestyle health behaviors and coping style, gender and mental health. Conclusions: Our findings demonstrated that the prevalence of anxiety and depression in the two rounds of surveys was different, and the prevalence in the second round was higher than that in the first round, as well as that in the two rounds of surveys. All survey identified that unhealthy lifestyle behaviors were positively associated with depression and anxiety symptoms. Compared with the emerged city of risk areas, other pandemic regions have a lower risk of mental health problems. The survey findings complement each other. Lifestyle health behaviors and coping style alleviated mental health symptoms. COVID-19-related social stressors were positively associated with mental health symptoms. The study also suggests that at the beginning of the pandemic, the effective management of college students' mental health problems, corresponding coping measures and maintaining a good lifestyle play a key role in the prevention and control of other cities. Understanding the college students' lifestyle behaviors during COVID-19 lockdown will help public health authorities reshape future policies on their nutritional recommendations, in preparation for future pandemics.

Assessing the potential anti-neuroinflammatory effect of minocycline in chronic low back pain: Protocol for a randomized, double-blind, placebo-controlled trial.

INTRODUCTION: Both preclinical studies, and more recent clinical imaging studies, suggest that glia-mediated neuroinflammation may be implicated in chronic pain, and therefore might be a potential treatment target. However, it is currently unknown whether modulating neuroinflammation effectively alleviates pain in humans. This trial tests the hypothesis that minocycline, an FDA-approved tetracycline antibiotic and effective glial cell inhibitor in animals, reduces neuroinflammation and may reduce pain symptoms in humans with chronic low back pain. METHODS AND ANALYSIS: This study is a randomized, double-blind, placebo-controlled clinical trial. Subjects, aged 18-75, with a confirmed diagnosis of chronic (≥ six months) low back pain (cLBP) and a self-reported pain rating of at least four out of ten (for at least half of the days during an average week) are enrolled via written, informed consent. Eligible subjects are randomized to receive a 14-day course of either active drug (minocycline) or placebo. Before and after treatment, subjects are scanned with integrated Positron Emission Tomography/Magnetic Resonance Imaging (PET/MRI) using [11C]PBR28, a second-generation radiotracer for the 18 kDa translocator protein (TSPO), which is highly expressed in glial cells and thus a putative marker of neuroinflammation. Pain levels are evaluated via daily surveys, collected seven days prior to the start of medication, and throughout the 14 days of treatment. General linear models will be used to assess pain levels and determine the treatment effect on brain (and spinal cord) TSPO signal. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov (NCT03106740).

Engineered LwaCas13a with enhanced collateral activity for nucleic acid detection.

Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 13 (Cas13) has been rapidly developed for nucleic-acid-based diagnostics by using its characteristic collateral activity. Despite the recent progress in optimizing the Cas13 system for the detection of nucleic acids, engineering Cas13 protein with enhanced collateral activity has been challenging, mostly because of its complex structural dynamics. Here we successfully employed a novel strategy to engineer the Leptotrichia wadei (Lwa)Cas13a by inserting different RNA-binding domains into a unique active-site-proximal loop within its higher eukaryotes and prokaryotes nucleotide-binding domain. Two LwaCas13a variants showed enhanced collateral activity and improved sensitivity over the wild type in various buffer conditions. By combining with an electrochemical method, our variants detected the SARS-CoV-2 genome at attomolar concentrations from both inactive viral and unextracted clinical samples, without target preamplification. Our engineered LwaCas13a enzymes with enhanced collateral activity are ready to be integrated into other Cas13a-based platforms for ultrasensitive detection of nucleic acids.

Hematopoietic stem cell transplantation activity in China 2020-2021 during the SARS-CoV-2 pandemic: a report from the Chinese Blood and Marrow Transplantation Registry Group.

Between 2020 and 2021, 31,525 hematopoietic stem cell transplantations (HSCTs) were reported to the Chinese Blood and Marrow Transplantation Registry Group (CBMTRG) throughout mainland China. In this report, we describe the activity and current trends for HSCT in China during the SARS-CoV-2 pandemic. In 2020, a total of 13,415 cases of HSCT were reported from 166 transplant teams, and 75% (10,042 cases) were allogeneic HSCTs. In 2021, a total of 18,110 cases of HSCT were reported from 174 transplant teams, and 70% (12,744 cases) were allogeneic HSCTs. Haploidentical donor (HID) transplantation accounted for 63% (7977 cases) of allogeneic HSCTs in 2021. The most common indications for allogeneic HSCT for malignant disease were acute myeloid leukemia (AML) (37%) and acute lymphoblastic leukemia (ALL) (23%), and the largest proportion of nonmalignant disease comprised aplastic anemia (AA) (13%). The PB stem cell source accounted for 41% of HIDs and 75% of MSDs. The BuCy-based regimen (57%) was the most popular conditioning regimen for allogeneic HSCT, followed by the BuFlu-based regimen (28%) and TBI-based regimen (11%). This survey provides comprehensive information about the current activities and might benefit clinical physicians' decision planning for HSCT.

Rare, convergent antibodies targeting the stem helix broadly neutralize diverse betacoronaviruses.

Humanity has faced three recent outbreaks of novel betacoronaviruses, emphasizing the need to develop approaches that broadly target coronaviruses. Here, we identify 55 monoclonal antibodies from COVID-19 convalescent donors that bind diverse betacoronavirus spike proteins. Most antibodies targeted an S2 epitope that included the K814 residue and were non-neutralizing. However, 11 antibodies targeting the stem helix neutralized betacoronaviruses from different lineages. Eight antibodies in this group, including the six broadest and most potent neutralizers, were encoded by IGHV1-46 and IGKV3-20. Crystal structures of three antibodies of this class at 1.5-1.75-Å resolution revealed a conserved mode of binding. COV89-22 neutralized SARS-CoV-2 variants of concern including Omicron BA.4/5 and limited disease in Syrian hamsters. Collectively, these findings identify a class of IGHV1-46/IGKV3-20 antibodies that broadly neutralize betacoronaviruses by targeting the stem helix but indicate these antibodies constitute a small fraction of the broadly reactive antibody response to betacoronaviruses after SARS-CoV-2 infection.