Enhancing genome-wide populus trait prediction through deep convolutional neural networks.

As a promising model, genome-based plant breeding has greatly promoted the improvement of agronomic traits. Traditional methods typically adopt linear regression models with clear assumptions, neither obtaining the linkage between phenotype and genotype nor providing good ideas for modification. Nonlinear models are well characterized in capturing complex nonadditive effects, filling this gap under traditional methods. Taking populus as the research object, this paper constructs a deep learning method, DCNGP, which can effectively predict the traits including 65 phenotypes. The method was trained on three datasets, and compared with other four classic models-Bayesian ridge regression (BRR), Elastic Net, support vector regression, and dualCNN. The results show that DCNGP has five typical advantages in performance: strong prediction ability on multiple experimental datasets; the incorporation of batch normalization layers and Early-Stopping technology enhancing the generalization capabilities and prediction stability on test data; learning potent features from the data and thus circumventing the tedious steps of manual production; the introduction of a Gaussian Noise layer enhancing predictive capabilities in the case of inherent uncertainties or perturbations; fewer hyperparameters aiding to reduce tuning time across datasets and improve auto-search efficiency. In this way, DCNGP shows powerful predictive ability from genotype to phenotype, which provide an important theoretical reference for building more robust populus breeding programs.

Designing antimicrobial peptides using deep learning and molecular dynamic simulations.

With the emergence of multidrug-resistant bacteria, antimicrobial peptides (AMPs) offer promising options for replacing traditional antibiotics to treat bacterial infections, but discovering and designing AMPs using traditional methods is a time-consuming and costly process. Deep learning has been applied to the de novo design of AMPs and address AMP classification with high efficiency. In this study, several natural language processing models were combined to design and identify AMPs, i.e. sequence generative adversarial nets, bidirectional encoder representations from transformers and multilayer perceptron. Then, six candidate AMPs were screened by AlphaFold2 structure prediction and molecular dynamic simulations. These peptides show low homology with known AMPs and belong to a novel class of AMPs. After initial bioactivity testing, one of the peptides, A-222, showed inhibition against gram-positive and gram-negative bacteria. The structural analysis of this novel peptide A-222 obtained by nuclear magnetic resonance confirmed the presence of an alpha-helix, which was consistent with the results predicted by AlphaFold2. We then performed a structure-activity relationship study to design a new series of peptide analogs and found that the activities of these analogs could be increased by 4-8-fold against Stenotrophomonas maltophilia WH 006 and Pseudomonas aeruginosa PAO1. Overall, deep learning shows great potential in accelerating the discovery of novel AMPs and holds promise as an important tool for developing novel AMPs.

nCoVDock2: a docking server to predict the binding modes between COVID-19 targets and its potential ligands.

The rapid emergence of SARS-CoV-2 variants with multi-sites mutations is considered as a major obstacle for the development of drugs and vaccines. Although most of the functional proteins essential for SARS-CoV-2 have been determined, the understanding of the COVID-19 target-ligand interactions remains a key challenge. The old version of this COVID-19 docking server was built in 2020, and free and open to all users. Here, we present nCoVDock2, a new docking server to predict the binding modes for targets from SARS-CoV-2. First, the new server supports more targets. We replaced the modeled structures with newly resolved structures and added more potential targets of COVID-19, especially for the variants. Second, for small molecule docking, Autodock Vina was upgraded to the latest version 1.2.0, and a new scoring function was added for peptide or antibody docking. Third, the input interface and molecular visualization were updated for a better user experience. The web server, together with an extensive help and tutorial, are freely available at: https://ncovdock2.schanglab.org.cn.

Implication of genotypes for prognosis of Candida glabrata bloodstream infections.

BACKGROUND: Genotyping isolates of a specific pathogen may demonstrate unique patterns of antimicrobial resistance, virulence or outcomes. However, evidence for genotype-outcome association in Candida glabrata is scarce. We aimed to characterize the mycological and clinical relevance of genotypes on C. glabrata bloodstream infections (BSIs). METHODS: Non-duplicated C. glabrata blood isolates from hospitalized adults were genotyped by MLST, and further clustered by the unweighted pair group method with arithmetic averages (UPGMA). A clonal complex (CC) was defined by UPGMA similarities of >90%. Antifungal susceptibility testing was performed by a colorimetric microdilution method and interpreted following CLSI criteria. RESULTS: Of 48 blood isolates evaluated, 13 STs were identified. CC7 was the leading CC (n = 14; 29.2%), including 13 ST7. The overall fluconazole and echinocandin resistance rates were 6.6% and 0%, respectively. No specific resistance patterns were associated with CC7 or other CCs. Charlson comorbidity index (adjusted OR, 1.49; 95% CI, 1.05-3.11) was the only predictor for CC7. By multivariable Cox regression analyses, CC7 was independently associated with 28 day mortality [adjusted HR (aHR), 3.28; 95% CI, 1.31-8.23], even after considering potential interaction with neutropenia (aHR, 3.41; 95% CI, 1.23-9.42; P for interaction, 0.24) or limited to 34 patients with monomicrobial BSIs (aHR, 2.85; 95% CI, 1.15-7.08). Also, the Kaplan-Meier estimate showed greater mortality with CC7 (P = 0.003). Fluconazole resistance or echinocandin therapy had no significant impact on mortality. CONCLUSIONS: Our data suggested comorbid patients were at risk of developing CC7 BSIs. Further, CC7 was independently associated with worse outcomes.

HLA3D: an integrated structure-based computational toolkit for immunotherapy.

MOTIVATION: The human major histocompatibility complex (MHC), also known as human leukocyte antigen (HLA), plays an important role in the adaptive immune system by presenting non-self-peptides to T cell receptors. The MHC region has been shown to be associated with a variety of diseases, including autoimmune diseases, organ transplantation and tumours. However, structural analytic tools of HLA are still sparse compared to the number of identified HLA alleles, which hinders the disclosure of its pathogenic mechanism. RESULT: To provide an integrative analysis of HLA, we first collected 1296 amino acid sequences, 256 protein data bank structures, 120 000 frequency data of HLA alleles in different populations, 73 000 publications and 39 000 disease-associated single nucleotide polymorphism sites, as well as 212 modelled HLA heterodimer structures. Then, we put forward two new strategies for building up a toolkit for transplantation and tumour immunotherapy, designing risk alignment pipeline and antigenic peptide prediction pipeline by integrating different resources and bioinformatic tools. By integrating 100 000 calculated HLA conformation difference and online tools, risk alignment pipeline provides users with the functions of structural alignment, sequence alignment, residue visualization and risk report generation of mismatched HLA molecules. For tumour antigen prediction, we first predicted 370 000 immunogenic peptides based on the affinity between peptides and MHC to generate the neoantigen catalogue for 11 common tumours. We then designed an antigenic peptide prediction pipeline to provide the functions of mutation prediction, peptide prediction, immunogenicity assessment and docking simulation. We also present a case study of hepatitis B virus mutations associated with liver cancer that demonstrates the high legitimacy of our antigenic peptide prediction process. HLA3D, including different HLA analytic tools and the prediction pipelines, is available at http://www.hla3d.cn/.

Achievements of COVID-19 vaccination programs: Taiwanese perspective.

The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a global health crisis. The specific characteristics of aerosol transmission in the latent period and the contagiousness of SARS-CoV-2 lead to rapid spread of infection in the community. Vaccination is the most effective method for preventing infection and severe outcomes. As of December 1, 2022, 88% of the Taiwanese population had received at least two doses of COVID-19 vaccines. Heterologous vaccination with ChAdOx1-mRNA-based or ChAdOx1-protein-based vaccines has been found to elicit higher immunogenicity than homologous vaccination with ChAdOx1-ChAdOx1 vaccines. A longitudinal cohort study revealed that 8-12-week intervals between the two heterologous vaccine doses of the primary series led to good immunogenicity and that the vaccines were safe. A third booster dose of mRNA vaccine is being encouraged to evoke effective immune responses against variants of concern. A novel domestic recombinant protein subunit vaccine (MVC-COV1901) was manufactured and authorized for emergency use in Taiwan. It has shown a good safety profile, with promising neutralizing antibody titers against SARS-CoV-2. Given the global pandemic due to emerging novel variants of SARS-CoV-2, booster COVID-19 vaccines and appropriate intervals between booster doses need to be investigated.

Antiviral therapy of coronavirus disease 2019 (COVID-19).

The coronavirus disease 2019 (COVID-19) pandemic has reached a turning point. The non-pharmaceutical interventions for preventing COVID-19 are lifting. Vaccination uptake is increasing in general, but this strategy is continuously challenged by the rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Of note, the Omicron subvariants spread globally for at least one year, and the most recently developed subvariants show strong immune evasion to preexisting immunity, either from previous infection, vaccination or both. Therefore, early and appropriate antiviral agents to treat patients at risk for severe COVID-19 or death is crucial to decrease morbidities and mortalities, to restore the healthcare capacities and to facilitate a return to the new normal. Current antiviral therapy for COVID-19 consist of neutralizing monoclonal antibodies (mAbs) and direct antiviral agents. Each agent has been proved for early ambulatory treatment of COIVD-19, but suffer from variable effectiveness and limitations due to patients' comorbidities, drug properties, or antiviral resistance. Besides, some specific mAbs are indicated for prophylaxis of COVID-19 before or after close contact with confirmed COVID-19 patients. This review article summarizes the evidence and unmet needs of the currently available antiviral agents for management of COVID-19 in the context of the Omicron subvariants.

Immunogenicity and safety of heterologous booster with protein-based COVID-19 vaccine (NVX-CoV2373) in healthy adults: A comparative analysis with mRNA vaccines.

BACKGROUND: Information on the protein-based severe acute respiratory syndrome (SARS-CoV-2) vaccine-NVX-CoV2373 (Novavax), as a heterologous booster remains limited. We investigated the immunogenicity and adverse events of NVX-CoV2373 as a second booster and compared them with those of mRNA vaccines in healthy adults. METHODS: Healthcare workers who had received an mRNA vaccine (mRNA-1273 or BNT-162b2) as the first booster (third dose) 12 weeks prior were recruited. Participants voluntarily received either NVX-CoV2373 or an mRNA vaccine as a second booster. Participants with a history of SARS-CoV-2 infection were excluded. The primary outcomes included serum anti-SARS-CoV-2 spike protein (SP) and neutralizing antibody titers against B.1.1.7 (Alpha), B.1.1.529 (Omicron) BA2, and BA5 variants on the 28th day after the boost. Secondary outcomes included new SARS-CoV-2 infections and adverse events reported during the study period. RESULTS: A total of 160 participants were enrolled in this study. Compared with the mRNA vaccination group (n = 59), the NVX-CoV2373 vaccination group (n = 101) had significantly lower anti-SARS-CoV-2 SP antibody titers and neutralizing antibody titers against all variants tested after the boost. During the study period, higher rates of new SARS-CoV-2 infections and a lower incidence of adverse events were observed in the NVX-CoV2373 vaccination group. No significant differences in cellular immune responses were observed between the two groups. CONCLUSION: Compared to a homologous mRNA booster vaccination, heterologous boosters with NVX-CoV2373 showed lower antibody responses, a higher incidence of new SARS-CoV-2 infections, and fewer adverse events.

Preventing and controlling intra-hospital spread of COVID-19 in Taiwan - Looking back and moving forward.

COVID-19 has exposed major weaknesses in the healthcare settings. The surge in COVID-19 cases increases the demands of health care, endangers vulnerable patients, and threats occupational safety. In contrast to a hospital outbreak of SARS leading to a whole hospital quarantined, at least 54 hospital outbreaks following a COVID-19 surge in the community were controlled by strengthened infection prevention and control measures for preventing transmission from community to hospitals as well as within hospitals. Access control measures include establishing triage, epidemic clinics, and outdoor quarantine stations. Visitor access restriction is applied to inpatients to limit the number of visitors. Health monitoring and surveillance is applied to healthcare personnel, including self-reporting travel declaration, temperature, predefined symptoms, and test results. Isolation of the confirmed cases during the contagious period and quarantine of the close contacts during the incubation period are critical for containment. The target populations and frequency of SARS-CoV-2 PCR and rapid antigen testing depend on the level of transmission. Case investigation and contact tracing should be comprehensive to identify the close contacts to prevent further transmission. These facility-based infection prevention and control strategies help reduce hospital transmission of SARS-CoV-2 to a minimum in Taiwan.

Fibrosis-4 index stratifies risks of hepatocellular carcinoma in patients with chronic hepatitis C.

BACKGROUND AND AIMS: Risk stratification for patients with a higher risk of hepatocellular carcinoma (HCC) is crucial. We aimed to investigate the role of the Fibrosis-4 (FIB-4) index in predicting chronic hepatitis C (CHC)-related HCC. METHODS: A retrospective cohort study consecutively included treatment-naive CHC patients receiving longitudinal follow-up at the National Taiwan University Hospital from 1986 to 2014. The clinical data were collected and traced for HCC development. Multivariable Cox proportional hazard regression analysis was used to investigate the predictors for HCC. RESULTS: A total of 1285 patients in the ERADICATE-C cohort were included. The median age was 54, 56% were females, and 933 had HCV viremia. There were 33%, 38%, and 29% of patients having FIB-4 index <1.45, 1.45-3.25, and ≥3.25, respectively. After a median of 9-year follow-up, 186 patients developed HCC. Multivariable analysis revealed that older age, AFP≥20 ng/mL, cirrhosis, and a higher FIB-4 index were independent predictors for HCC. Compared with patients with FIB-4 index <1.45, those with FIB-4 1.45-3.25 had a 5.51-fold risk (95% confidence interval [CI]: 2.65-11.46), and those with FIB-4 ≥ 3.25 had 7.45-fold risk (95% CI: 3.46-16.05) of HCC. In CHC patients without viremia, FIB-4 index 1.45-3.25 and FIB-4 ≥ 3.25 increased 6.78-fold and 16.77-fold risk of HCC, respectively, compared with those with FIB-4 < 1.45. CONCLUSION: The baseline FIB-4 index can stratify the risks of HCC in untreated CHC patients, even those without viremia. The FIB-4 index should thus be included in the management of CHC.

CoDock-Ligand: combined template-based docking and CNN-based scoring in ligand binding prediction.

For ligand binding prediction, it is crucial for molecular docking programs to integrate template-based modeling with a precise scoring function. Here, we proposed the CoDock-Ligand docking method that combines template-based modeling and the GNINA scoring function, a Convolutional Neural Network-based scoring function, for the ligand binding prediction in CASP15. Among the 21 targets, we obtained successful predictions in top 5 submissions for 14 targets and partially successful predictions for 4 targets. In particular, for the most complicated target, H1114, which contains 56 metal cofactors and small molecules, our docking method successfully predicted the binding of most ligands. Analysis of the failed systems showed that the predicted receptor protein presented conformational changes in the backbone and side chains of the binding site residues, which may cause large structural deviations in the ligand binding prediction. In summary, our hybrid docking scheme was efficiently adapted to the ligand binding prediction challenges in CASP15.

WHSC1 is involved in DNA damage, cellular senescence and immune response in hepatocellular carcinoma progression.

Wolf-Hirschhorn syndrome candidate 1 (WHSC1) is a transcriptional regulatory protein that encodes a histone methyltransferase to control H3K36me2 modification. WHSC1 was upregulated and associated with poor prognosis in HCC. The elevated WHSC1 likely due to the alterations of DNA methylation or RNA modification. WHSC1 perhaps form a chromatin cross talk with H3K27me3 and DNA methylation to regulate transcription factors expression in HCC. Functional analysis indicated that WHSC1 was involved in DNA damage repair, cell cycle, cellular senescence and immune regulations. Furthermore, WHSC1 was associated with the infiltrating levels of B cell, CD4+, Tregs and macrophage cells. Therefore, our findings suggested that WHSC1 might function as a promotor regulator to affect the development and progression of HCC. Thus, WHSC1 could be a potential biomarker in predicting the prognosis and therapeutic target for patients with HCC.

Impact of AlphaFold on structure prediction of protein complexes: The CASP15-CAPRI experiment.

We present the results for CAPRI Round 54, the 5th joint CASP-CAPRI protein assembly prediction challenge. The Round offered 37 targets, including 14 homodimers, 3 homo-trimers, 13 heterodimers including 3 antibody-antigen complexes, and 7 large assemblies. On average ~70 CASP and CAPRI predictor groups, including more than 20 automatics servers, submitted models for each target. A total of 21 941 models submitted by these groups and by 15 CAPRI scorer groups were evaluated using the CAPRI model quality measures and the DockQ score consolidating these measures. The prediction performance was quantified by a weighted score based on the number of models of acceptable quality or higher submitted by each group among their five best models. Results show substantial progress achieved across a significant fraction of the 60+ participating groups. High-quality models were produced for about 40% of the targets compared to 8% two years earlier. This remarkable improvement is due to the wide use of the AlphaFold2 and AlphaFold2-Multimer software and the confidence metrics they provide. Notably, expanded sampling of candidate solutions by manipulating these deep learning inference engines, enriching multiple sequence alignments, or integration of advanced modeling tools, enabled top performing groups to exceed the performance of a standard AlphaFold2-Multimer version used as a yard stick. This notwithstanding, performance remained poor for complexes with antibodies and nanobodies, where evolutionary relationships between the binding partners are lacking, and for complexes featuring conformational flexibility, clearly indicating that the prediction of protein complexes remains a challenging problem.

CXCL9 as a Reliable Biomarker for Discriminating Anti-IFN-γ-Autoantibody-Associated Lymphadenopathy that Mimics Lymphoma.

The diagnosis of adult-onset immunodeficiency syndrome associated with neutralizing anti-interferon γ autoantibodies (AIGA) presents substantial challenges to clinicians and pathologists due to its nonspecific clinical presentation, absence of routine laboratory tests, and resemblance to certain lymphoma types, notably nodal T follicular helper cell lymphoma, angioimmunoblastic type (nTFHL-AI). Some patients undergo lymphadenectomy for histopathological examination to rule out lymphoma, even in the absence of a preceding clinical suspicion of AIGA. This study aimed to identify reliable methods to prevent misdiagnosis of AIGA in this scenario through a retrospective case-control analysis of clinical and pathological data, along with immune gene transcriptomes using the NanoString nCounter platform, to compare AIGA and nTFHL-AI. The investigation revealed a downregulation of the C-X-C motif chemokine ligand 9 (CXCL9) gene in AIGA, prompting an exploration of its diagnostic utility. Immunohistochemistry (IHC) targeting CXCL9 was performed on lymph node specimens to assess its potential as a diagnostic biomarker. The findings exhibited a significantly lower density of CXCL9-positive cells in AIGA compared to nTFHL-AI, displaying a high diagnostic accuracy of 92.3% sensitivity and 100% specificity. Furthermore, CXCL9 IHC demonstrated its ability to differentiate AIGA from various lymphomas sharing similar characteristics. In conclusion, CXCL9 IHC emerges as a robust biomarker for differentiating AIGA from nTFHL-AI and other similar conditions. This reliable diagnostic approach holds the potential to avert misdiagnosis of AIGA as lymphoma, providing timely and accurate diagnosis.

Molnupiravir for the treatment of COVID-19 in immunocompromised participants: efficacy, safety, and virology results from the phase 3 randomized, placebo-controlled MOVe-OUT trial.

PURPOSE: Immunocompromised patients have a potentially increased risk for progression to severe COVID-19 and prolonged replication of SARS-CoV-2. This post hoc analysis examined outcomes among immunocompromised participants in the MOVe-OUT trial. METHODS: In phase 3 of MOVe-OUT, non-hospitalized at-risk adults with mild-to-moderate COVID-19 were randomized to receive molnupiravir 800 mg or placebo twice daily for 5 days. Immunocompromised participants were identified based on prior/concomitant medications and/or medical history. All-cause hospitalization/death, adverse events, SARS-CoV-2 titers, infectivity, and RNA sequences were compared between immunocompromised participants who received molnupiravir or placebo and with non-immunocompromised participants. RESULTS: Fifty-five of 1408 participants were considered immunocompromised. Compared to placebo, fewer molnupiravir-treated immunocompromised participants were hospitalized/died through Day 29 (22.6% [7/31] vs. 8.3% [2/24]), with fewer adverse events (45.2% [14/31] vs. 25.0% [6/24]). A larger mean change from baseline in SARS-CoV-2 RNA was observed with molnupiravir compared to placebo in non-immunocompromised participants (least squares mean [LSM] difference Day 5: - 0.31, 95% confidence interval [CI] - 0.47 to - 0.15), while the mean change was comparable between treatment groups in immunocompromised participants (LSM difference Day 5: 0.23, 95% CI - 0.71 to 1.17). Molnupiravir treatment was associated with increased clearance of infectious virus. Increased errors in viral nucleotide sequences in post-baseline samples compared to placebo support molnupiravir's mechanism of action and were not associated with observation of novel treatment-emergent amino acid substitutions in immunocompromised participants. CONCLUSION: Although the study population was small, these data suggest that molnupiravir treatment for mild-to-moderate COVID-19 in non-hospitalized immunocompromised adults is efficacious and safe and quickly reduces infectious SARS-CoV-2. GOV REGISTRATION NUMBER: NCT04575597.

SPATS2 is correlated with cell cycle progression and immune cells infiltration in hepatocellular carcinoma.

The spermatogenesis associated serine rich 2 (SPATS2) is a member of RNA-binding protein in which the abnormal expression is linked with carcinogenesis in serval types of cancer. However, there is no systematic study on the differential expression, prognostic significance, epigenetic regulation, immune infiltration of SPATS2 in hepatocellular carcinoma (HCC). In the present study, we investigated the expression, prognosis, epigenetic regulation, and immune cell infiltration of SPATS2 in HCC. We found that the elevated expression of SPATS2 was unfavorably associated with the clinical pathological stage and prognosis. Functional enrichment analysis revealed that SPATS2 is associated with cell cycle, apoptosis and cancer cell metastasis processes in HCC. Our results confirmed that knockdown of SPATS2 will affect cell cycle, apoptosis and invasion of HCC cell lines. Moreover, the expression of SPATS2 is upregulated by epigenetic regulation, including DNA methylation, m6A and histone modification in HCC. In addition, SPATS2 expression was positively correlated with immune cell infiltration or expression of immune related gene markers in HCC. Taken together, our data demonstrated that SPATS2 is associated with progression and immune infiltration, and could serve as a prognostic biomarker for HCC. In conclusion, these results highlight the potential of SPATS2 to be used as a therapeutic target for HCC.

Serial increase and high alpha-fetoprotein levels predict the development of hepatocellular carcinoma in 6 months.

AIM: Alpha-fetoprotein (AFP) checkup with abdominal ultrasonography for hepatocellular carcinoma (HCC) surveillance remains controversial. We evaluated a serial AFP-increase and high AFP levels in the prediction of HCC. METHODS: At-risk patients with chronic liver disease underwent HCC surveillance with trimonthly AFP measurement were included and categorized into HCC and non-HCC groups. Their AFP levels at 12, 9, and 6 months (-6M) before the outcome date were evaluated. Group-based trajectory analysis and multivariable regression analysis were performed to identify AFP trajectories as risk predictors for HCC. RESULTS: Overall, 2776 patients were included in the HCC (n = 326) and non-HCC (n = 2450) groups. Serial AFP levels were significantly higher in the HCC than the non-HCC groups. Trajectory analysis identified AFP-increase group (11%) increased 24-fold risks of HCC compared with the AFP-stable (89%) group. Compared with patients without the AFP-increase, a serial 3-month AFP-increase ≥10% elevated HCC risk by 12.1-fold (95% CI: 6.5-22.4) in 6 months, and the HCC risks increased 13-60 fold in patients with cirrhosis, hepatitis B, or C receiving antiviral therapy, or AFP levels <20 ng/ml. Combining serial AFP-increase ≥10% and AFP ≥20 ng/ml at -6M significantly increased 41.7-fold (95% CI: 13.8-126.2) HCC risks. In patients who underwent biannual AFP checkups, those with both 6-month AFP-increase ≥10% and AFP ≥20 ng/ml increased 22.1-fold (95% CI: 12.52-39.16) HCC risks in 6 months. Most HCCs were detected at an early stage. CONCLUSIONS: Serial 3-6-month AFP-increase of ≥10% previously and AFP level of ≥20 ng/ml significantly increased HCC risks in 6 months.

Serological response and safety of heterologous ChAdOx1-nCoV-19/mRNA-1273 prime-boost vaccination with a twelve-week interval.

The appropriate interval between heterologous prime adenoviral vectored vaccination and boost mRNA vaccination remains unclear. We recruited 100 adult participants to receive a prime adenoviral vectored vaccine (ChAdOx1, AstraZeneca) and a boost mRNA vaccine (mRNA-1273, Moderna) 12 weeks apart and checked their serum SARS-CoV-2 anti-spike IgG titers and neutralizing antibody titers against B.1.1.7 (alpha) and B.1.617.2 (delta) variants on the 28th day after the boost dose. Results were compared with our previous study cohorts who received the same prime-boost vaccinations at 4- and 8-week intervals. Compared to other heterologous vaccination groups, the 12-week interval group had higher neutralizing antibody titers against SARS-CoV-2 variants than the 4-week interval group and was similar to the 8-week interval group at day 28. Adverse reactions after the boost dose were mild and transient. Our results support deploying viral vectored and mRNA vaccines in a flexible schedule with intervals from 8 to 12 weeks.

COVID-19 outbreaks in long-term care facilities-a nationwide population-based cohort study in Taiwan, May-July 2021.

BACKGROUND/PURPOSE: Long-term care facilities (LTCFs) are high-risk settings for the novel coronavirus disease (COVID-19). The aim of the study was to describe the extent and the impacts of 2021 COVID-19 outbreaks on LTCFs in Taiwan. METHODS: We retrospectively analyzed the data of each COVID-19 outbreak in LTCFs from May 15 to July 31, 2021 in Taiwan. We characterized the features of LTCFs with outbreaks and compared the characteristics of infected staff members and residents of the affected LTCFs. RESULTS: COVID-19 outbreaks were reported in 16 LTCFs (0.9%). The outbreak was significantly associated with LTCFs with ≥50 beds [adjusted odds ratio (aOR), 6.3; 95%confidence interval [CI], 1.9-21.1] and location of Taipei metropolitan area (aOR, 4.6; 95%CI, 1.7-12.8). Resident cases accounted for 75.4% (203/269) of confirmed cases affected by outbreaks. The 30-day all-cause mortality was 24.2% for residents only and was significantly associated with age ≥65 years [adjusted hazard ratio (aHR, 4.3; 95%CI, 1.7-10.5)], presence of symptoms on diagnosis (aHR, 2.2; 95%CI, 1.3-3.7), and LTCF occupancy rate ≥80% (aHR, 3.0, 95%CI, 1.3-7.4). CONCLUSION: COVID-19 outbreaks have a critical impact on residents in LTCFs owing to the advanced age and high prevalence of chronic comorbidities in this population. Multi-pronged infection control measures and mass testing are vital for mitigating COVID-19 transmission in LTCFs.

Correlation of adverse effects and antibody responses following homologous and heterologous COVID19 prime-boost vaccinations.

BACKGROUND: Studies correlating reactogenicity and immunogenicity of COVID-19 vaccines are limited to BNT162b2, with inconsistent results. We investigated whether adverse reactions after other COVID-19 vaccines reliably predict humoral responses. METHODS: Adult volunteers were recruited for homologous or heterologous prime-boost vaccinations with adenoviral (ChAdOx1, AstraZeneca) and/or mRNA (mRNA-1273, Moderna) vaccines administered either 4 or 8 weeks apart. Adverse effects were routinely solicited and recorded by subjects in a standard diary card for up to 84 days post booster vaccination. Anti-SARS-CoV-2 IgG titers were measured pre- (visit 1), and post-booster dose at days 14 (visit 2) and 28 (visit 3). RESULTS: A total of 399 participants (75% women) with a median age of 41 (interquartile range, 33-48 IQR) years were included. Vaccine-induced antibody titers at days 14 and 28 were significantly higher among subjects who reported local erythema, swelling, pain, as well as systemic fever, chills, headache, myalgia, arthralgia, fatigue compared to those who did not experience local or systemic reactogenicity. Post-vaccination humoral responses did not correlate with the occurrence of skin rash and correlated weakly with gastrointestinal symptoms. A significant correlation between post-vaccination peak body temperature and anti-SARS-CoV-2 spike IgG at Day 14, independent of vaccine type and schedule, was found. CONCLUSION: Specific symptoms of reactogenicity such as post-vaccination injection site pain, swelling, erythema and fever, myalgia and fatigue are significantly predictive of the magnitude of the anti-SARS-CoV-2 antibody response.