Seasonal variation and ecological risk assessment of Pharmaceuticals and Personal Care Products (PPCPs) in a typical semi-enclosed bay — The Bohai Bay in northern China

The Bohai Bay as a typical semi-enclosed bay in northern China with poor water exchange capacity and significant coastal urbanization, is greatly influenced by land-based inputs and human activities. As a class of pseudo-persistent organic pollutants, the spatial and temporal distribution of Pharmaceuticals and Personal Care Products (PPCPs) is particularly important to the ecological environment, and it will be imperfect to assess the ecological risk of PPCPs for the lack of systematic investigation of their distribution in different season. 14 typical PPCPs were selected to analyze the spatial and temporal distribution in the Bohai Bay by combining online solid-phase extraction (SPE) and HPLC-MS/MS techniques in this study, and their ecological risks to aquatic organisms were assessed by risk quotients (RQs) and concentration addition (CA) model. It was found that PPCPs widely presented in the Bohai Bay with significant differences of spatial and seasonal distribution. The concentrations of ∑PPCPs were higher in autumn than in summer. The distribution of individual pollutants also showed significant seasonal differences. The high values were mainly distributed in estuaries and near-shore outfalls. Mariculture activities in the northern part of the Bohai Bay made a greater contribution to the input of PPCPs. Caffeine, florfenicol, enrofloxacin and norfloxacin were the main pollutants in the Bohai Bay, with detection frequencies exceeding 80 %. The ecological risk of PPCPs to algae was significantly higher than that to invertebrates and fish. CA model indicated that the potential mixture risk of total PPCPs was not negligible, with 34 % and 88 % of stations having mixture risk in summer and autumn, respectively. The temporary stagnation of productive life caused by Covid-19 weakened the input of PPCPs to the Bohai Bay, reducing the cumulative effects of the pollutants. This study was the first full-coverage investigation of PPCPs in the Bohai Bay for different seasons, providing an important basis for the ecological risk assessment and pollution prevention of PPCPs in the bay. © 2022 Elsevier B.V.

Screening rate for Hepatitis D in Hepatitis B patients: Tips and tricks

Introduction: Hepatitis B virus (HBV) and its satellite virus hepatitis D (HDV) are common worldwide hepatotrophic infections responsible for cirrhosis and hepatocellular carcinoma. EASL practice guidelines recommend HDV screening in all Hep B patients. Novel therapies for Hep D are promising. Aim: To determine screening rates for HDV in HBV patients referred to our Laboratory of Hub Hospital Pordenone (Friuli Venezia Giulia). Methods: We retrospectively considered HBsAg positive results from 01.01.2018 to 31.12.2021. Using an extended database to 30.11.2022, we considered, among those were HBsAg positive, anti-HDV results and if we detected positivity for anti-HDV, we checked if HDV-RNA was performed. Results: 931 patients (55% non-Italian native) positive for hepatitis B surface antigen were studied with a majority male patients (65%). Of 931, 470 (50%) Hep B patients were screened for Hep D and 13 (1.4%) (9 non-Italian native) were positive for anti-HDV. Of 13, 6 were positive for serum HDV-RNA;3 subjects were negative for HDV-RNA while 4 patients did not perform HDV-RNA. 10 Hep-B patients (1%) negative for anti-HDV at first time were re-tested for anti-HDV more than once. Comparing 2018-2019 vs 2020-2021, screening rate for Hep D decreased from 56% to 40%. Conclusions: Despite current HDV guidelines, in our Hospital HDV screening is suboptimal and it is actually declining. In fact COVID-19 has caused the slowing down of hepatitis testing program. Therefore we suggest: 1) anti-HDV simplified and automated reflex testing algorithms in Hep B patients for an early diagnosis and linkage to care of HDV infection;2) enhancement of molecular biology for HDV-RNA assay in our Italian Labs;3) repeating more than once anti-HDV especially in high-risk HBV patients. Furthermore, we need to be careful for Hep B vaccine to reduce Hep D screening and disease burden.

Split aminoacyl-tRNA synthetases for proximity-induced stop codon suppression.

Synthetic biology tools for regulating gene expression have many useful biotechnology and therapeutic applications. Most tools developed for this purpose control gene expression at the level of transcription, and relatively few methods are available for regulating gene expression at the translational level. Here, we design and engineer split orthogonal aminoacyl-tRNA synthetases (o-aaRS) as unique tools to control gene translation in bacteria and mammalian cells. Using chemically induced dimerization domains, we developed split o-aaRSs that mediate gene expression by conditionally suppressing stop codons in the presence of the small molecules rapamycin and abscisic acid. By activating o-aaRSs, these molecular switches induce stop codon suppression, and in their absence stop codon suppression is turned off. We demonstrate, in Escherichia coli and in human cells, that split o-aaRSs function as genetically encoded AND gates where stop codon suppression is controlled by two distinct molecular inputs. In addition, we show that split o-aaRSs can be used as versatile biosensors to detect therapeutically relevant protein-protein interactions, including those involved in cancer, and those that mediate severe acute respiratory syndrome-coronavirus-2 infection.

Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals.

Individuals infected with the SARS-CoV-2 virus present with a wide variety of symptoms ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe response to COVID-19. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the genetic predisposition to severe COVID-19 outcomes. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform a locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify four introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. Using reporter assays in the presence/absence of SARS-CoV-2, we find evidence that these variants respond to viral infection. These variants likely drive the locus' impact on severity by modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.

Agent-Based Simulation for Infectious Disease Modelling over a Period of Multiple Days, with Application to an Airport Scenario.

With the COVID-19 pandemic, the role of infectious disease spreading in public places has been brought into focus more than ever. Places that are of particular interest regarding the spread of infectious diseases are international airport terminals, not only for the protection of staff and ground crew members but also to help minimize the risk of the spread of infectious entities such as COVID-19 around the globe. Computational modelling and simulation can help in understanding and predicting the spreading of infectious diseases in any such scenario. In this paper, we propose a model, which combines a simulation of high geometric detail regarding virus spreading with an account of the temporal progress of infection dynamics. We, thus, introduce an agent-based social force model for tracking the spread of infectious diseases by modelling aerosol traces and concentration of virus load in the air. We complement this agent-based model to have consistency over a period of several days. We then apply this model to investigate simulations in a realistic airport setting with multiple virus variants of varying contagiousness. According to our experiments, a virus variant has to be at least twelve times more contagious than the respective control to result in a level of infection of more than 30%. Combinations of agent-based models with temporal components can be valuable tools in an attempt to assess the risk of infection attributable to a particular virus and its variants.

A Synthetic Biology Approach for Vaccine Candidate Design against Delta Strain of SARS-CoV-2 Revealed Disruption of Favored Codon Pair as a Better Strategy over Using Rare Codons.

The SARS-CoV-2 delta variant (B.1.617.2) appeared for the first time in December 2020 and later spread worldwide. Currently available vaccines are not so efficacious in curbing the viral pathogenesis of the delta strain of COVID; therefore, the development of a safe and effective vaccine is required. In the present study, we envisaged molecular patterns in the structural genes' spike, nucleoprotein, membrane, and envelope of the SARS-CoV-2 delta variant. The study was based on determining compositional features, dinucleotide odds ratio, synonymous codon usage, positive and negative codon contexts, rare codons, and insight into relatedness between the human host isoacceptor tRNA and preferred codons from the structural genes. We found specific patterns, including a significant abundance of T nucleotide over all other three nucleotides. The underrepresentation of GpA, GpG, CpC, and CpG dinucleotides and the overrepresentation of TpT, ApA, CpT, and TpG were observed. A preference towards ACT- (Thr), AAT- (Asn), TTT- (Phe), and TTG- (Leu) initiated codons and aversion towards CGG (Arg), CCG (Pro), and CAC (His) was present in the structural genes of the delta strain. The interaction between the host tRNA pool and preferred codons of the envisaged structural genes revealed that the virus preferred the codons for those suboptimal numbers of isoacceptor tRNA were present. We see this as a strategy adapted by the virus to keep the translation rate low to facilitate the correct folding of viral proteins. The information generated in the study helps design the attenuated vaccine candidate against the SARS-CoV-2 delta variant using a synthetic biology approach. Three strategies were tested: changing TpT to TpA, introducing rare codons, and disrupting favored codons. It found that disrupting favored codons is a better approach to reducing virus fitness and attenuating SARS-CoV-2 delta strain using structural genes.

Protocol for investigating the biogenesis of SARS-CoV-2 S pseudoviruses in HEK293T cells transduced to express the virus-specific intrabodies.

The protocol is designed to investigate the influence of an anti-cleavage site intrabody in modulating the output of LV(CoV-2 S), a lentivirus-based pseudovirus expressing CoV-2 S protein using HEK293T cells. We clone the single-domain antibody sequence into a lentiviral vector (pLenti-GFP) for intracellular expression and assess not only the viral biogenesis but also the fate of the CoV-2 S protein in such cells. For complete details on the use and execution of this protocol, please refer to Singh et al. (2022).1.

Evolution of increased positive charge on the SARS-CoV-2 spike protein may be adaptation to human transmission.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and infect individuals. The exterior surface of the SARS-CoV-2 virion is dominated by the spike protein, and the current work examined spike protein biochemical features that have changed during the 3 years in which SARS-CoV-2 has infected humans. Our analysis identified a striking change in spike protein charge, from -8.3 in the original Lineage A and B viruses to -1.26 in most of the current Omicron viruses. We conclude that in addition to immune selection pressure, the evolution of SARS-CoV-2 has also altered viral spike protein biochemical properties, which may influence virion survival and promote transmission. Future vaccine and therapeutic development should also exploit and target these biochemical properties.

Genomic diversity of SARS-CoV-2 can be accelerated by mutations in the nsp14 gene.

Coronaviruses, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), encode a proofreading exonuclease, nonstructural protein 14 (nsp14), that helps ensure replication competence at a low evolutionary rate compared with other RNA viruses. In the current pandemic, SARS-CoV-2 has accumulated diverse genomic mutations including in nsp14. Here, to clarify whether amino acid substitutions in nsp14 affect the genomic diversity and evolution of SARS-CoV-2, we searched for amino acid substitutions in nature that may interfere with nsp14 function. We found that viruses carrying a proline-to-leucine change at position 203 (P203L) have a high evolutionary rate and that a recombinant SARS-CoV-2 virus with the P203L mutation acquired more diverse genomic mutations than wild-type virus during its replication in hamsters. Our findings suggest that substitutions, such as P203L, in nsp14 may accelerate the genomic diversity of SARS-CoV-2, contributing to virus evolution during the pandemic.

Structural evolution of Delta lineage of SARS-CoV-2.

One of the main obstacles in prevention and treatment of COVID-19 is the rapid evolution of the SARS-CoV-2 Spike protein. Given that Spike is the main target of common treatments of COVID-19, mutations occurring at this virulent factor can affect the effectiveness of treatments. The B.1.617.2 lineage of SARS-CoV-2, being characterized by many Spike mutations inside and outside of its receptor-binding domain (RBD), shows high infectivity and relative resistance to existing cures. Here, utilizing a wide range of computational biology approaches, such as immunoinformatics, molecular dynamics (MD), analysis of intrinsically disordered regions (IDRs), protein-protein interaction analyses, residue scanning, and free energy calculations, we examine the structural and biological attributes of the B.1.617.2 Spike protein. Furthermore, the antibody design protocol of Rosetta was implemented for evaluation the stability and affinity improvement of the Bamlanivimab (LY-CoV55) antibody, which is not capable of interactions with the B.1.617.2 Spike. We observed that the detected mutations in the Spike of the B1.617.2 variant of concern can cause extensive structural changes compatible with the described variation in immunogenicity, secondary and tertiary structure, oligomerization potency, Furin cleavability, and drug targetability. Compared to the Spike of Wuhan lineage, the B.1.617.2 Spike is more stable and binds to the Angiotensin-converting enzyme 2 (ACE2) with higher affinity.

Bioinformatics and system biology approach to identify the influences of COVID-19 on primary sjogren's syndrome patients

Background: Primary Sjogren's syndrome (pSS) is a chronic, systemic, inflammatory autoimmune disease in which existing studies have found the presence of pSS-specific antibodies anti-SSA/ Ro in acute infection with COVID-19.1 The emergence of this phenomenon makes us aware that in the context of the long-term epidemic of COVID-19, it is necessary to further study the molecular mechanisms of the high susceptibility of pSS patients to COVID-19. Method(s): The gene expression profiles of 8 COVID-19 datasets and 5 pSS datasets were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between COVID-19 and PSS were identified using the limma software package and Weighted Gene Co-expression Network Analysis (WGCNA). A Venn diagram was used to discover common upregulated DEGs. To explore the possible pathogenesis of both diseases, common signaling pathways were explored by enriching DEGs using Gene Ontology (GO) and the Kyoto Gene and Genome Encyclopedia (KEGG) pathway. Protein-protein interactions (PPIs) were established to identify hub genes and key modules. The analysis of key gene expression characteristics by The Connectivity Map was used to predict potentially effective drugs. Finally, the CIBERSORT method was used to comprehensively evaluate the immune infiltrates of patients with COVID-19 and PSS to study the mechanisms that may have a common immune response or immune cell infiltration. Result(s): A total of 82 upregulated DEGs were identified in both COVID-19 and PSS (Figure 1 A-E). Functional enrichment analysis illustrated the important role of enhanced signaling pathways in response to virus defense and interferon-alpha in both diseases (Figure 1F).Three key modules including 25 hub genes were identified (Figure 1G). The correlation analysis of immune cell infiltration showed the expression of B cells memory resting decreased and NK cells resting increased significantly in the two diseases (Figure 1H, I). Finally, estradiol in drug prediction outcomes has been shown to reduce susceptibility to COVID-19 and its severity through its involvement in regulating immune cells, while the most common manifestation of dry eye in pSS patients is strongly associated with low estrogen. Conclusion(s): High defense response to virus and response to interferon-alpha in pSS patients might be a crucial susceptible factor for COVID-19 and predictive drugs such as estradiol, suggested by susceptibility genes common to COVID-19 and pSS, may help in the clinical treatment of both diseases.

Formal Concept Analysis Applications in Bioinformatics

The bioinformatics discipline seeks to solve problems in biology with computational theories and methods. Formal concept analysis (FCA) is one such theoretical model, based on partial orders. FCA allows the user to examine the structural properties of data based on which subsets of the dataset depend on each other. This article surveys the current literature related to the use of FCA for bioinformatics. The survey begins with a discussion of FCA, its hierarchical advantages, several advanced models of FCA, and lattice management strategies. It then examines how FCA has been used in bioinformatics applications, followed by future prospects of FCA in those areas. The applications addressed include gene data analysis (with next-generation sequencing), biomarkers discovery, protein-protein interaction, disease analysis (including COVID-19, cancer, and others), drug design and development, healthcare informatics, biomedical ontologies, and phylogeny. Some of the most promising prospects of FCA are identifying influential nodes in a network representing protein-protein interactions, determining critical concepts to discover biomarkers, integrating machine learning and deep learning for cancer classification, and pattern matching for next-generation sequencing. [ FROM AUTHOR]

SCIENTIFIC LITERACY-BASED FLIPPED CLASSROOM VIRTUAL STRATEGY FOR BIOLOGY LEARNING IN THE NEW NORMAL ERA

Various research results concerned with flipped classrooms reported to mandate more benefits to form a positive attitude, self-efficacy, and self-regulated learning and affect students' abilities and skills. This research, which in-volved three studies, aims to develop a flipped classroom strategy model for virtual biology learning. The research was conducted in three high schools and the Department of Biology, Faculty of Mathematics and Natural Sci-ences, Universitas Negeri Semarang, at the beginning of the new normal habit of the COVID-19 pandemic. The analysis results of study 1 were applied in designing study 2, and the results of study 2 were applied to develop the model in study 3. The results showed that the flipped strategy was proven to improve skills employing information technology to benefit learning and student participation. The flipped strategy is proven to have better effects on learning outcomes and students' self-efficacy. The strategy model, arranged with asynchronous-synchronous-asynchronous in scientific literacy-based learning syntax and practiced with flipped e-learning instructions, is an ideal flipped classroom model. It is well appreciated by validators, teachers, and students and has proven to function well. © 2022 Science Education Study Program FMIPA UNNES Semarang.

The Changes of Biology Learning Activities in Higher Education During the COVID-19 Pandemic

Biology learning during the Covid-19 pandemic was undoubtedly run online. This causes changes in student learning activities. This study aimed to determine the effect of the COVID-19 pandemic biology learning activities. This study was a quantitative descriptive through a survey of biology education student's at 4 universities (55 students). The survey was conducted by giving a questionnaire to 55 students.. The questionnaire consisted of 50 statement items that included indicators of learning activities for learning before and during the COVID-19 pandemic. The survey results show the average percentage of all indicators of biology learning activities before the pandemic was 79.06%, while during the pandemic it was 70.97%. Student's activities such as group discussions, collaborative work in problem solving, be on time for learning, focus during learning and presentations with online learning during a pandemic have decreased compared to learning activities before the pandemic. The results of this study indicate that student learning activities in learning biology have changed during the Covid-19 pandemic. Online biology learning needs to be well developed so that it has a good impact on learning activities. © 2023 American Institute of Physics Inc.. All rights reserved.

Characterization of exogenous αSN response genes and their relation to Parkinson's disease using network analyses.

Despite extensive research, the molecular mechanisms underlying the toxicity of αSN in Parkinson's disease (PD) pathology are still poorly understood. To address this, we used a microarray dataset to identify genes that are induced and differentially expressed after exposure to toxic αSN aggregates, which we call exogenous αSN response (EASR) genes. Using systems biology approaches, we then determined, at multiple levels of analysis, how these EASR genes could be related to PD pathology. A key result was the identification of functional connections between EASR genes and previously identified PD-related genes by employing the proteins' interactions networks and 9 brain region-specific co-expression networks. In each brain region, co-expression modules of EASR genes were enriched for gene sets whose expression are altered by SARS-CoV-2 infection, leading to the hypothesis that EASR co-expression genes may explain the observed links between COVID-19 and PD. An examination of the expression pattern of EASR genes in different non-neurological healthy brain regions revealed that regions with lower mean expression of the upregulated EASR genes, such as substantia nigra, are more vulnerable to αSN aggregates and lose their neurological functions during PD progression. Gene Set Enrichment Analysis of healthy and PD samples from substantia nigra revealed that a specific co-expression network, "TNF-α signaling via NF-κB", is an upregulated pathway associated with the PD phenotype. Inhibitors of the "TNF-α signaling via NF-κB" pathway may, therefore, decrease the activity level of this pathway and thereby provide therapeutic benefits for PD patients. We virtually screened FDA-approved drugs against these upregulated genes (NR4A1, DUSP1, and FOS) using docking-based drug discovery and identified several promising drugs. Altogether, our study provides a better understanding of αSN toxicity mechanisms in PD and identifies potential therapeutic targets and small molecules for treatment of PD.

Exploring Innovation with Scientific Thinking.

The mode of scientific thinking is undergoing rapid and profound changes. In the 21st century, macro and micro civilizations go parallel. A systematic and scientific methodology is required for the study of complex things. The thinking mode in modern medicine is gradually shifting from analytical, reductive thinking to holistic and systematic thinking. As such Western medicine and traditional Chinese medicine are gradually approaching the epistemology of health and disease state. The importance of scientific thinking in innovation has been expounded in this study. The development trends in medicine in the current era are analyzed, the importance of systems theory in the study of human bodies is discussed, and a new medical model named Novel Systems Medicine is proposed.