Biosafety and Health最新文献

Climatic factors are closely associated with the occurrence of vector-borne diseases, and they also influence the distribution of vectors. The occurrence of plague is closely related to the population dynamics of fleas and their host animals, as well as climatic conditions. This study focused on Xilingol League, utilizing climatic and flea index data from 2012 to 2021. Spearman correlation and "Boruta" importance analysis were conducted to screen for climatic variables. A generalized additive model (GAM) was employed to investigate the influence of climatic factors and rodent density on the flea index. GAM analysis revealed distinct trends in flea index among different rodent hosts. For Meriones unguiculatus, the flea index declined with increased density and with higher humidity, yet rose with greater lagged sunshine duration. For Spermophilus dauricus, an initial increase in flea index with density was observed, followed by a decrease, and a rise in the index was noted when ground temperatures were low. This study reveals the nonlinear interactions and lag effects among climatic factors, density, and flea index. Climatic factors and density variably influence the flea index of two Yersinia pestis hosts. This research advances the prediction and early warning efforts for plague control, providing a theoretical basis for rodent and flea eradication strategies.

In recent years, as the infectious diseases caused by pathogens such as novel coronavirus and mpox (formerly called monkeypox) spread globally, the significance of identification, preservation, and sharing of pathogenic resources become prominent. Along with the rapid development of biorepositories, it is imperative to evaluate their operation in a scientific manner. By using the literature review and modified Delphi method, this study develops a benchmarking tool for the comprehensive evaluation of the operation of biorepositories for pathogenic resources. The effective response rates of both rounds of expert surveys were 100 %. The authority coefficients (Cr) were 0.82 and 0.85, respectively, manifesting the reliability of consultation results. In the second-round survey, the Kendall’s coefficient of concordance (Kendall’s W) of all indicators ranged from 0.09 to 0.31 (P < 0.001), the comprehensive score ranged from 4.02 to 4.94, the standard deviation ranged from 0.21 to 0.77, and the coefficient of variation (CV) ranged from 0.04 to 0.22, indicating that the expert opinions reached consensus. The final benchmarking tool was composed of 4 primary indicators, 12 secondary indicators, and 65 tertiary indicators. The weights of the four primary indicators allocated through the rank-sum ratio method, namely organizational structure, management requirements, biobanking capacity, and sharing capacity, were 30.50 %, 30.08 %, 25.45 %, and 13.97 %, respectively. The benchmarking tool established in this study provides references for the comprehensive evaluation of the operation and puts forward advice for the sustainable development of biorepositories for pathogenic resources.

In the wake of the largest-ever recorded outbreak of mpox in terms of magnitude and geographical spread in human history since May 2022, we innovatively developed an automated online sewage virus enrichment and concentration robot for disease tracking. Coupled with an artificial intelligence (AI) model, our research aims to estimate mpox cases based on the concentration of the monkeypox virus (MPXV) in wastewater. Our research has revealed a compelling link between the levels of MPXV in wastewater and the number of clinically confirmed mpox infections, a finding that is reinforced by the ability of our AI prediction model to forecast cases with remarkable precision, capturing 87 % of the data’s variability. However, it is worth noting that this high precision in predictions may be related to the relatively high frequency of data acquisition and the relatively non-mobile isolated environment of the hospital itself. In conclusion, this study represents a significant step forward in our ability to track and respond to mpox outbreaks. It has the potential to revolutionize public health surveillance by utilizing innovative technologies for disease surveillance and prediction.

Synthetic biology is a crucial component of the “cyber-biological revolution” in this new industrial revolution. Owing to breakthroughs in synthetic biology, deoxyribonucleic acid (DNA), the storehouse of hereditary material in biological systems, can now be used as a medium for storage (synthesis) and reading (sequencing) of information. However, integrating synthetic biology with computerization has also caused cyberbiosecurity concerns, encompassing biosecurity and information security issues. Malicious codes intended to attack computer systems can be stored as artificially synthesized DNA fragments, which can be released during DNA sequencing and decoding and attack computer and network systems. As these cyberbiosecurity threats become increasingly realistic, spreading awareness and information about how they can be prevented and controlled is crucial. This review aims to address this need by offering crucial theoretical backing for cyberbiosecurity research and raising awareness of risk mitigation and control measures in information security, biosecurity, and national security.

The effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection persist months and years after recovery. We conducted an online survey to assess the health condition of convalescents approximately 5 months following the primary infection of SARS-CoV-2. The study recruited 5,510 individuals who were primary infected, 626 participants who had experienced reinfection, and 521 participants who were without infective history. The most common disorders after the primary infection group were fatigue (15.18 %), memory issue (13.13 %), post-exertional malaise (PEM, 11.68 %), and brain fog (11.29 %) at the time of survey. In addition, SARS-CoV-2 infection had an impact on the reproductive systems. In stepwise logistic regression analysis, smoking currently, with background diseases, and outpatient visits in the acute phase could be associated with moderate / severe disorders. Further analysis of different background diseases showed that allergic rhinitis, hyperlipidemia, cardiovascular disease, autoimmune diseases, neurological diseases, and asthma likely increased the risk of moderate/severe disorders. The probability of developing disorders of individuals with SARS-CoV-2 reinfection was higher before the secondary infection than uninfected people. Fatigue, PEM, muscle pain/spasms, chills, joint pain, excessive sweating at rest, headache / dizziness, sore throat or foreign body sensation in the throat, cough, expectoration, dry / painful / watery eyes, loss of appetite and constipation were associated with an increased risk of reinfection. It was essential to undertake further research with enhanced randomization in a larger sample in the community, and to strengthen the validation of the research conclusions. The findings of this study contribute to a deeper understanding of the health recovery process among coronavirus disease 2019 (COVID-19) convalescents. Moreover, the findings help identify characteristic health risk factors associated with convalescents and highlight the risk of moderate / severe disorders and reinfection. Furthermore, the findings also provide valuable guidance and reference for SARS-CoV-2 rehabilitation strategies and the prevention of reinfection, offering insights for scientific recommendations.

Integrase strand transfer inhibitors (INSTIs) have emerged as the first-line choice for treating human immunodeficiency virus (HIV) infection due to their superior efficacy and safety. However, the impact of INSTIs on the development of neuropsychiatric conditions in people living with HIV (PLWH) is not fully understood due to limited data. In this study, we conducted a cross-sectional examination of PLWH receiving antiretroviral therapy, with a specific focus on HIV-positive men who have sex with men (MSM) on INSTI-based regimens (n = 61) and efavirenz (EFV)-based regimens (n = 28). Participants underwent comprehensive neuropsychiatric evaluations and multimodal magnetic resonance imaging (MRI) scans, including T1-weighted images and resting-state functional MRI. Compared to the EFV group, the INSTI group exhibited primarily reduced gray matter volume (GMV) in the right superior parietal gyrus, higher regional homogeneity (ReHo) in the left postcentral gyrus, lower ReHo in the right orbital part of the inferior frontal gyrus, and increased voxel-wise functional connectivity for the seed region in the left inferior temporal gyrus with clusters in the right cuneus. Furthermore, the analysis revealed a main effect of antiretroviral drugs on GMV changes, but no main effect of neuropsychiatric disorders or their interaction. The repeated analysis of participants who did not switch regimens confirmed the GMV changes in the INSTI group, validating the initial findings. Our study demonstrated gray matter atrophy and functional brain changes in PLWH on INSTI-based regimens compared to those on EFV-based regimens. These neuroimaging results provide valuable insights into the characteristics of brain network modifications in PLWH receiving INSTI-based regimens.

Investigating the genetic and developmental characteristics, infection transmission attributes, and epidemiological trends of pathogens using genomic data represents the foundation for pathogen surveillance and is a crucial prerequisite for guaranteeing global health security. To meet the analytical demands of research relating to pathogen prevention and control, we designed a secure visualization system capable of pathogen genome assembly, annotation, species identification, sequence typing, antibiotic resistance and virulence analysis, genomic mobile element and transferable resistance gene annotation, and phylogenetic tree reconstruction. For highly pathogenic organisms requiring complete data protection, we have developed a secure computing tool that utilizes a trusted execution environment, is combined with blockchain and privacy computing technologies, and is specifically designed for nucleotide basic local alignment search tool (BLASTn) comparison analysis. This technological advancement offers scientific support for in-depth investigations into pathogen transmission and epidemiological mechanisms, environmental adaptability, evolutionary trends, and immune evasion mechanisms, as well as the identification of new or emerging pathogen strains. This, in turn, aids efforts in infectious disease prevention, treatment, and research.

Inactivated coronavirus disease 2019 (COVID-19) vaccines such as CoronaVac and BBIBP-CorV have been widely used in China. However, more investigation is still needed to understand antibodies' duration and effectiveness against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in the real world. In this study, 575 participants who had been vaccinated with two or three doses of the inactivated vaccine were recruited. Serum samples were collected and tested for anti-spike IgG and neutralizing antibodies against SARS-CoV-2 (original strain, Dela, and Omicron). Unsurprisingly, a third dose of the vaccine significantly enhanced antibody responses against SARS-CoV-2 and its variants. However, despite a booster dose, the neutralizing antibody levels against Omicron, particularly the BA.5.2 subvariant, remained low. There was no sex bias, but an age bias was observed. Notably, the predominant IgG subclass antibodies were IgG1 and IgG2, with a much lower level of IgG4. After the booster shot, the ratio of IgG4 to IgG1 significantly increased. The observation of IgG1 to the IgG4 class switch after repeated inactivated vaccinations underscores the importance of continuous monitoring of subclass antibody responses. Further clinical investigations are required to understand the implications of this class switch for optimizing immunization strategies.

The high morbidity and mortality rate of individuals with human immunodeficiency virus (HIV) / acquired immunodeficiency syndrome (AIDS) coinfected with Mycobacterium tuberculosis (MTB) is a tough challenge for current global tuberculosis prevention and control efforts. HIV/MTB coinfection is more complex than a single infection, and the interaction between the two diseases aggravates the deterioration caused by the disease, resulting in increased hospitalizations and deaths. Rapid screening and early diagnosis facilitate the timely initiation of anti-tuberculosis treatment in HIV/MTB coinfected individuals, thereby reducing transmission and the incidence of adverse prognoses. To date, pathogenic detection has remained the gold standard for diagnosing tuberculosis, but its sensitivity and specificity are greatly affected by the body's immune status, which limits its application in the diagnosis of HIV/MTB coinfection. Recently, immunology and molecular detection technology has developed rapidly. New detection technologies, such as interferon-γ release assays, interferon-gamma inducible protein 10, and GeneXpert MTB/RIF assay have overcome the limitations of traditional detection methods, significantly improved the sensitivity and specificity of tuberculosis diagnosis, and brought new hope to the detection of HIV/MTB coinfection. In this article, the principle, scope of application, and latest research progress of relevant detection methods are reviewed to provide a reference for the early diagnosis of HIV/MTB coinfection.