Advancements in CHO metabolomics: techniques, current state and evolving methodologies.

Background: Investigating the metabolic behaviour of different cellular phenotypes, i.e., good/bad grower and/or producer, in production culture is important to identify the key metabolite(s)/pathway(s) that regulate cell growth and/or recombinant protein production to improve the overall yield. Currently, LC-MS, GC-MS and NMR are the most used and advanced technologies for investigating the metabolome. Although contributed significantly in the domain, each technique has its own biasness towards specific metabolites or class of metabolites due to various reasons including variability in the concept of working, sample preparation, metabolite-extraction methods, metabolite identification tools, and databases. As a result, the application of appropriate analytical technique(s) is very critical. Purpose and scope: This review provides a state-of-the-art technological insights and overview of metabolic mechanisms involved in regulation of cell growth and/or recombinant protein production for improving yield from CHO cultures. Summary and conclusion: In this review, the advancements in CHO metabolomics over the last 10 years are traced based on a bibliometric analysis of previous publications and discussed. With the technical advancement in the domain of LC-MS, GC-MS and NMR, metabolites of glycolytic and nucleotide biosynthesis pathway (glucose, fructose, pyruvate and phenylalanine, threonine, tryptophan, arginine, valine, asparagine, and serine, etc.) were observed to be upregulated in exponential-phase thereby potentially associated with cell growth regulation, whereas metabolites/intermediates of TCA, oxidative phosphorylation (aspartate, glutamate, succinate, malate, fumarate and citrate), intracellular NAD+/NADH ratio, and glutathione metabolic pathways were observed to be upregulated in stationary-phase and hence potentially associated with increased cell-specific productivity in CHO bioprocess. Moreover, each of technique has its own bias towards metabolite identification, indicating their complementarity, along with a number of critical gaps in the CHO metabolomics pipeline and hence first time discussed here to identify their potential remedies. This knowledge may help in future study designs to improve the metabolomic coverage facilitating identification of the metabolites/pathways which might get missed otherwise and explore the full potential of metabolomics for improving the CHO bioprocess performances.

Ultrasound-Assisted Extraction, Optimization, Phytochemical Screening and Analysis of Phenolics from Cycas Zeylanica and Antioxidant Activity Evaluation.

The present study focuses on investigating the phytochemical screening of indigenous species, C. zeylanica, for the first time. The leaf extracts have been prepared using ultrasound-assisted methods to obtain the best extraction results using different time and temperature conditions such as 30, 60, and 90 min. and 30, 40, and 60 °C, respectively. The results have been optimized using response surface methodology. Under the optimal extraction conditions of 60 °C for 43.57 minutes, an extract was produced with a yield of 0.238 g and a high total phenolic content of 181.1965 mg GAE/g. The total phenolic content has been evaluated and the presence of gallic acid has been confirmed through the HPLC technique. The optimal extract (OE) showed excellent antioxidant activity for the DPPH assay, with an IC50 of 3.1 µg/ml. Finally, GC-MS profiling has been done to screen the volatile component of the plant extract.

Deriving Vocal Fold Oscillation Information from Recorded Voice Signals Using Models of Phonation.

During phonation, the vocal folds exhibit a self-sustained oscillatory motion, which is influenced by the physical properties of the speaker's vocal folds and driven by the balance of bio-mechanical and aerodynamic forces across the glottis. Subtle changes in the speaker's physical state can affect voice production and alter these oscillatory patterns. Measuring these can be valuable in developing computational tools that analyze voice to infer the speaker's state. Traditionally, vocal fold oscillations (VFOs) are measured directly using physical devices in clinical settings. In this paper, we propose a novel analysis-by-synthesis approach that allows us to infer the VFOs directly from recorded speech signals on an individualized, speaker-by-speaker basis. The approach, called the ADLES-VFT algorithm, is proposed in the context of a joint model that combines a phonation model (with a glottal flow waveform as the output) and a vocal tract acoustic wave propagation model such that the output of the joint model is an estimated waveform. The ADLES-VFT algorithm is a forward-backward algorithm which minimizes the error between the recorded waveform and the output of this joint model to estimate its parameters. Once estimated, these parameter values are used in conjunction with a phonation model to obtain its solutions. Since the parameters correlate with the physical properties of the vocal folds of the speaker, model solutions obtained using them represent the individualized VFOs for each speaker. The approach is flexible and can be applied to various phonation models. In addition to presenting the methodology, we show how the VFOs can be quantified from a dynamical systems perspective for classification purposes. Mathematical derivations are provided in an appendix for better readability.

A Gene-Based Algorithm for Identifying Factors That May Affect a Speaker's Voice.

Over the past decades, many machine-learning- and artificial-intelligence-based technologies have been created to deduce biometric or bio-relevant parameters of speakers from their voice. These voice profiling technologies have targeted a wide range of parameters, from diseases to environmental factors, based largely on the fact that they are known to influence voice. Recently, some have also explored the prediction of parameters whose influence on voice is not easily observable through data-opportunistic biomarker discovery techniques. However, given the enormous range of factors that can possibly influence voice, more informed methods for selecting those that may be potentially deducible from voice are needed. To this end, this paper proposes a simple path-finding algorithm that attempts to find links between vocal characteristics and perturbing factors using cytogenetic and genomic data. The links represent reasonable selection criteria for use by computational by profiling technologies only, and are not intended to establish any unknown biological facts. The proposed algorithm is validated using a simple example from medical literature-that of the clinically observed effects of specific chromosomal microdeletion syndromes on the vocal characteristics of affected people. In this example, the algorithm attempts to link the genes involved in these syndromes to a single example gene (FOXP2) that is known to play a broad role in voice production. We show that in cases where strong links are exposed, vocal characteristics of the patients are indeed reported to be correspondingly affected. Validation experiments and subsequent analyses confirm that the methodology could be potentially useful in predicting the existence of vocal signatures in naïve cases where their existence has not been otherwise observed.

Comparison of freeze-thaw and sonication cycle-based methods for extracting AMR-associated metabolites from Staphylococcus aureus.

Emerging antimicrobial resistance (AMR) among Gram-positive pathogens, specifically in Staphylococcus aureus (S. aureus), is becoming a leading public health concern demanding effective therapeutics. Metabolite modulation can improve the efficacy of existing antibiotics and facilitate the development of effective therapeutics. However, it remained unexplored for drug-resistant S. aureus (gentamicin and methicillin-resistant), primarily due to the dearth of optimal metabolite extraction protocols including a protocol for AMR-associated metabolites. Therefore, in this investigation, we have compared the performance of the two most widely used methods, i.e., freeze-thaw cycle (FTC) and sonication cycle (SC), alone and in combination (FTC + SC), and identified the optimal method for this purpose. A total of 116, 119, and 99 metabolites were identified using the FTC, SC, and FTC + SC methods, respectively, leading to the identification of 163 metabolites cumulatively. Out of 163, 69 metabolites were found to be associated with AMR in published literature consisting of the highest number of metabolites identified by FTC (57) followed by SC (54) and FTC + SC (40). Thus, the performances of FTC and SC methods were comparable with no additional benefits of combining both. Moreover, each method showed biasness toward specific metabolite(s) or class of metabolites, suggesting that the choice of metabolite extraction method shall be decided based on the metabolites of interest in the investigation.

Gonadotropins as pharmacological agents in assisted reproductive technology and polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a complex endocrinopathy associated with subfertility/infertility and pregnancy complications. Most PCOS women opt for assisted reproductive technologies (ART) for successful conception; however, optimization of the relative doses of the gonadotropins [follicle-stimulating hormone (FSH), luteinizing hormone (LH)/human chorionic gonadotropin (hCG)] for appropriate steroidogenesis, without causing ovarian hyperstimulatory syndrome (OHSS), is challenging. Embryonic factors probably do not contribute to pregnancy loss in PCOS women, albeit hormonal imbalance impairs the metabolic microenvironment critical for oocyte maturation and endometrial receptivity. Certain clinical studies have confirmed the role of metabolic corrections in increasing the rate of pregnancy in PCOS women. This review focuses on the impact of untimely high LHCGR and/or LH levels on oocyte/embryo quality, pregnancy outcomes in ART, and exploring LHCGR as a potential drug target in PCOS women.

SphereFace Revived: Unifying Hyperspherical Face Recognition.

This paper addresses the deep face recognition problem under an open-set protocol, where ideal face features are expected to have smaller maximal intra-class distance than minimal inter-class distance under a suitably chosen metric space. To this end, hyperspherical face recognition, as a promising line of research, has attracted increasing attention and gradually become a major focus in face recognition research. As one of the earliest works in hyperspherical face recognition, SphereFace explicitly proposed to learn face embeddings with large inter-class angular margin. However, SphereFace still suffers from severe training instability which limits its application in practice. In order to address this problem, we introduce a unified framework to understand large angular margin in hyperspherical face recognition. Under this framework, we extend the study of SphereFace and propose an improved variant with substantially better training stability - SphereFace-R. Specifically, we propose two novel ways to implement the multiplicative margin, and study SphereFace-R under three different feature normalization schemes (no feature normalization, hard feature normalization and soft feature normalization). We also propose an implementation strategy - "characteristic gradient detachment" - to stabilize training. Extensive experiments on SphereFace-R show that it is consistently better than or competitive with state-of-the-art methods.

Exploring the Relationship Between Trust-Building Strategies and Public Engagement on Social Media During the COVID-19 Outbreak.

Communication is critical in a new health emergency because it motivates the public to take preventive actions. Prior research has shown that strategies including source credibility, information transparency and uncertainty reduction actions could enhance trust in health communication on social media. Yet research on how the government in China used these trust-building strategies to engage the public during the outbreak of COVID-19 is limited. Therefore, our exploratory study developed an integrated framework for conducting quantitative content analysis to examine how the most popular government-owned newspaper in China, People's Daily, utilized a major social media platform, to engage the public. Our findings showed that accessibility to external links, provision of emotional support, and information on skills and resources were associated with increased public engagement with government COVID-19 posts. Insights gained can enable public health organizations and governments to focus on specific strategies to enhance public engagement.

Molecular Characterization of Tinospora cordifolia (Willd.) Miers Using Novel g-SSR Markers and Their Comparison with EST-SSR and SCoT Markers for Genetic Diversity Study.

In the present study, novel genomic-SSR (g-SSR) markers generated in our laboratory were used to characterize Tinospora cordifolia and related species. The g-SSR marker was also compared with EST-SSR and SCoT markers used earlier in our laboratory to assess the genetic diversity of T. cordifolia. A total of 26 accessions of T. cordifolia and 1 accession each of Tinospora rumphii and Tinospora sinensis were characterized using 65 novel g-SSR markers. A total of 125 alleles were detected with 49 polymorphic g-SSR markers. The number of alleles per locus varied from 1-4 with a mean value of 2.55 alleles per locus. Mean PIC, gene diversity, and heterozygosity were estimated to be 0.33, 0.41, and 0.65, respectively. The two species, namely T. rumphii and T. sinensis, showed cross-species transferability of g-SSRs developed in T. cordifolia. The success rate of cross-species transferability in T. rumphii was 95.3% and 93.8% in T. sinensis, proving the usefulness of this marker in genetic diversity studies of related species. The Tinospora accessions were also used for molecular characterization using SCoT and EST-SSR markers and compared for genetic diversity and cross-species transferability. The PIC, gene diversity, heterozygosity, and principal coordinate analysis showed that g-SSR is the better maker for a genetic diversity study of T. cordifolia. Additionally, high cross-species transferability of g-SSRs was found (95.3% and 93.8%) compared to EST-SSRs (68.8% and 67.7%) in T. rumphii and T. sinensis, respectively.

The potential of 4D's approach in curbing antimicrobial resistance among bacterial pathogens.

INTRODUCTION: Antibiotics are life-saving drugs but irrational/inappropriate use leads to the emergence of antibiotic-resistant bacterial superbugs, making their treatment extremely challenging. Increasing antimicrobial resistance (AMR) among bacterial pathogens is becoming a serious public health concern globally. If ignorance persists, there would not be any antibiotics available to treat even a common bacterial infection in future. AREA COVERED: This article intends to collate and discuss the potential of 4D's (right Drug, Dose, Duration, and De-escalation of therapy) approach to tackle the emerging problem of AMR. For this, we searched PubMed, Google Scholar, Medline, and clinicaltrials.gov databases primarily using keywords 'optimal antibiotic therapy,' 'antimicrobial resistance,' 'higher versus lower dose antibiotic treatment,' 'shorter versus longer duration antibiotic treatment,' 'de-escalation study', and 'antimicrobial stewardship measures' and based on the findings, form and expressed our opinion. EXPERT OPINION: More efforts are needed for developing diagnostics for rapid, accurate, point-of-care, and cost-effective pathogen identification and antimicrobial susceptibility testing (AST) to facilitate rational use of antibiotics. Current dosing and duration of therapies also need to be redefined to maximize their impact. Furthermore, de-escalation approaches should be developed and encouraged in the clinic. This altogether will minimize selection pressure on the pathogens and reduce emergence of AMR.

Impact of COVID-19 Vaccine Misinformation on Social Media Virality: Content Analysis of Message Themes and Writing Strategies.

BACKGROUND: Vaccines serve an integral role in containing pandemics, yet vaccine hesitancy is prevalent globally. One key reason for this hesitancy is the pervasiveness of misinformation on social media. Although considerable research attention has been drawn to how exposure to misinformation is closely associated with vaccine hesitancy, little scholarly attention has been given to the investigation or robust theorizing of the various content themes pertaining to antivaccine misinformation about COVID-19 and the writing strategies in which these content themes are manifested. Virality of such content on social media exhibited in the form of comments, shares, and reactions has practical implications for COVID-19 vaccine hesitancy. OBJECTIVE: We investigated whether there were differences in the content themes and writing strategies used to disseminate antivaccine misinformation about COVID-19 and their impact on virality on social media. METHODS: We constructed an antivaccine misinformation database from major social media platforms during September 2019-August 2021 to examine how misinformation exhibited in the form of content themes and how these themes manifested in writing were associated with virality in terms of likes, comments, and shares. Antivaccine misinformation was retrieved from two globally leading and widely cited fake news databases, COVID Global Misinformation Dashboard and International Fact-Checking Network Corona Virus Facts Alliance Database, which aim to track and debunk COVID-19 misinformation. We primarily focused on 140 Facebook posts, since most antivaccine misinformation posts on COVID-19 were found on Facebook. We then employed quantitative content analysis to examine the content themes (ie, safety concerns, conspiracy theories, efficacy concerns) and manifestation strategies of misinformation (ie, mimicking of news and scientific reports in terms of the format and language features, use of a conversational style, use of amplification) in these posts and their association with virality of misinformation in the form of likes, comments, and shares. RESULTS: Our study revealed that safety concern was the most prominent content theme and a negative predictor of likes and shares. Regarding the writing strategies manifested in content themes, a conversational style and mimicking of news and scientific reports via the format and language features were frequently employed in COVID-19 antivaccine misinformation, with the latter being a positive predictor of likes. CONCLUSIONS: This study contributes to a richer research-informed understanding of which concerns about content theme and manifestation strategy need to be countered on antivaccine misinformation circulating on social media so that accurate information on COVID-19 vaccines can be disseminated to the public, ultimately reducing vaccine hesitancy. The liking of COVID-19 antivaccine posts that employ language features to mimic news or scientific reports is perturbing since a large audience can be reached on social media, potentially exacerbating the spread of misinformation and hampering global efforts to combat the virus.

Identification of metabolite extraction method for targeted exploration of antimicrobial resistance associated metabolites of Klebsiella pneumoniae.

Antimicrobial resistant Klebsiella pneumoniae (K. pneumoniae), as being a pathogen of critical clinical concern, urgently demands effective therapeutic options. However, the discovery of novel antibiotics over the last three decades has declined drastically and necessitates exploring novel strategies. Metabolomic modulation has been the promising approach for the development of effective therapeutics to deal with AMR; however, only limited efforts have been made to-date, possibly due to the unavailability of suitable metabolites extraction protocols. Therefore, in order to establish a detailed metabolome of K. pneumoniae and identify a method for targeted exploration of metabolites that are involved in the regulation of AMR associated processes, metabolites were extracted using multiple methods of metabolites extraction (freeze-thaw cycle (FTC) and sonication cycle (SC) method alone or in combination (FTC followed by SC; FTC + SC)) from K. pneumoniae cells and then identified using an orbitrap mass analyzer (ESI-LC-MS/MS). A total of 151 metabolites were identified by using FTC, 132 metabolites by using FTC+SC, 103 metabolites by using SC and 69 metabolites common among all the methods used which altogether enabled the identification of 199 unique metabolites. Of these 199, 70 metabolites were known to have an association with AMR phenotype and among these, the FTC + SC method yielded better (identified 55 metabolites), quantitatively and qualitatively compared to FTC and SC alone (identified 51 and 41 metabolites respectively). Each method of metabolite extraction showed a definite degree of biasness and specificity towards chemical classes of metabolites and jointly contributed to the development of a detailed metabolome of the pathogen. FTC method was observed to give higher metabolomic coverage as compared to SC alone and FTC + SC. However, FTC + SC resulted in the identification of a higher number of AMR associated metabolites of K. pneumoniae compared to FTC and SC alone.

The potential of radiation sterilized and banked tissue allografts for management of nuclear casualties.

Processed and radiation sterilized allograft tissues that can be banked for use on demand are a precious therapeutic resource for the repair or reconstruction of damaged or injured tissues. Skin dressings or skin substitutes like allograft skin, amniotic membrane and bioengineered skin can be used for the treatment of thermal burns and radiation induced skin injuries. Bone grafts can be employed for repairing fracture defects, filling in destroyed regions of bone, and treatment of spinal and joint injuries. A nuclear scenario would result in a large number of casualties due to the heat, blast and radiation effects of the weapon. Perspective of radiation sterilized biological tissues provided by the tissue banks for management of casualties in a nuclear disaster scenario is presented.

Virtual discovery of a hetero-cyclic compound from the Universal Natural Product Database (UNPD36) as a potential inhibitor of interleukin-33: molecular docking and dynamic simulations.

Interleukin (IL)-33 is a cytokine implicated in several inflammatory and autoimmune diseases. Upon binding to its receptor ST2, IL-33 activates allergic inflammatory responses. To block this protein-protein interaction with a potential anti-allergic agent, we screened Universal Natural Product Database (UNPD) using a combined approach of molecular docking and dynamic simulations. Six hundred compounds with high gastrointestinal absorption properties from the UNPD were retrieved and subjected to molecular docking using Autodock Vina, out of which four hetero-cyclic compounds (UNPD36, UNPD2045, UNPD8905, UNPD122514) were found to have binding energy score of < -7.0 Kcal/mol. Further analysis from 100 ns MD simulation of the best hit (UNPD36) revealed that IL-33_UNPD36 complex reached average stability at RMSD of 2.7 Å, and residues involved in the interaction showed lower fluctuations compared to the residues at the ß4-ß5 and ß11-ß12 loop region. Further molecular docking using Autodock 4.2 was carried out to determine the binding orientation of UNPD36. Using GROMACS, additional 50 ns MD simulations and MM-PBSA calculation were performed on this complex. Finally, chemoinformatic studies revealed that the UNPD36 had drug-like and pharmacokinetic profiles as well as potentials for oral and topical applications, in addition to good safety profile. Thus, it was concluded that a hetero-cyclic compound with chromone moiety (UNPD36) had a good and stable binding mode to serve as potential inhibitor of IL-33 and/or may provide a scaffold for further optimization toward the design of more potent inhibitors for application in the treatment of respiratory allergies.Communicated by Ramaswamy H. Sarma.

Anaesthesia Choice for Creation of Arteriovenous Fistula (ACCess) study protocol : a randomised controlled trial comparing primary unassisted patency at 1 year of primary arteriovenous fistulae created under regional compared to local anaesthesia.

INTRODUCTION: Arteriovenous fistulae (AVF) are the 'gold standard' vascular access for haemodialysis. Universal usage is limited, however, by a high early failure rate. Several small, single-centre studies have demonstrated better early patency rates for AVF created under regional anaesthesia (RA) compared with local anaesthesia (LA). The mechanistic hypothesis is that the sympathetic blockade associated with RA causes vasodilatation and increased blood flow through the new AVF. Despite this, considerable variation in practice exists in the UK. A high-quality, adequately powered, multicentre randomised controlled trial (RCT) is required to definitively inform practice. METHODS AND ANALYSIS: The Anaesthesia Choice for Creation of Arteriovenous Fistula (ACCess) study is a multicentre, observer-blinded RCT comparing primary radiocephalic/brachiocephalic AVF created under regional versus LA. The primary outcome is primary unassisted AVF patency at 1 year. Access-specific (eg, stenosis/thrombosis), patient-specific (including health-related quality of life) and safety secondary outcomes will be evaluated. Health economic analysis will also be undertaken. ETHICS AND DISSEMINATION: The ACCess study has been approved by the West of Scotland Research and ethics committee number 3 (20/WS/0178). Results will be published in open-access peer-reviewed journals within 12 months of completion of the trial. We will also present our findings at key national and international renal and anaesthetic meetings, and support dissemination of trial outcomes via renal patient groups. TRIAL REGISTRATION NUMBER: ISRCTN14153938. SPONSOR: NHS Greater Glasgow and Clyde GN19RE456, Protocol V.1.3 (8 May 2021), REC/IRAS ID: 290482.

Cellular dormancy in minimal residual disease following targeted therapy.

BACKGROUND: Breast cancer mortality is principally due to tumor recurrence, which can occur following extended periods of clinical remission that may last decades. While clinical latency has been postulated to reflect the ability of residual tumor cells to persist in a dormant state, this hypothesis remains unproven since little is known about the biology of these cells. Consequently, defining the properties of residual tumor cells is an essential goal with important clinical implications for preventing recurrence and improving cancer outcomes. METHODS: To identify conserved features of residual tumor cells, we modeled minimal residual disease using inducible transgenic mouse models for HER2/neu and Wnt1-driven tumorigenesis that recapitulate cardinal features of human breast cancer progression, as well as human breast cancer cell xenografts subjected to targeted therapy. Fluorescence-activated cell sorting was used to isolate tumor cells from primary tumors, residual lesions following oncogene blockade, and recurrent tumors to analyze gene expression signatures and evaluate tumor-initiating cell properties. RESULTS: We demonstrate that residual tumor cells surviving oncogenic pathway inhibition at both local and distant sites exist in a state of cellular dormancy, despite adequate vascularization and the absence of adaptive immunity, and retain the ability to re-enter the cell cycle and give rise to recurrent tumors after extended latency periods. Compared to primary or recurrent tumor cells, dormant residual tumor cells possess unique features that are conserved across mouse models for human breast cancer driven by different oncogenes, and express a gene signature that is strongly associated with recurrence-free survival in breast cancer patients and similar to that of tumor cells in which dormancy is induced by the microenvironment. Although residual tumor cells in both the HER2/neu and Wnt1 models are enriched for phenotypic features associated with tumor-initiating cells, limiting dilution experiments revealed that residual tumor cells are not enriched for cells capable of giving rise to primary tumors, but are enriched for cells capable of giving rise to recurrent tumors, suggesting that tumor-initiating populations underlying primary tumorigenesis may be distinct from those that give rise to recurrence following therapy. CONCLUSIONS: Residual cancer cells surviving targeted therapy reside in a well-vascularized, desmoplastic microenvironment at both local and distant sites. These cells exist in a state of cellular dormancy that bears little resemblance to primary or recurrent tumor cells, but shares similarities with cells in which dormancy is induced by microenvironmental cues. Our observations suggest that dormancy may be a conserved response to targeted therapy independent of the oncogenic pathway inhibited or properties of the primary tumor, that the mechanisms underlying dormancy at local and distant sites may be related, and that the dormant state represents a potential therapeutic target for preventing cancer recurrence.

Development of a PCR-lateral flow assay for rapid detection of Yersinia pestis, the causative agent of plague.

Plague is a zoonotic disease caused by Yersinia pestis, a Gram-negative, rod shaped coccobacillus, which is primarily found in rodents and can be transmitted to humans through flea bite. The disease has three major clinical forms bubonic (by flea bite), pneumonic (by respiratory droplets) and septicemic plague. Y. pestis is classified as a category 'A' agent by NIAID, USA due to its high mortality and easy person to person dissemination. The conventional diagnostic methods available for Y. pestis show cross-reactivity with other enteropathogenic bacteria making its detection difficult. There is a need to develop sensitive and specific molecular assay for accurate detection of Y. pestis. PCR is well suited molecular biology tool for rapid diagnosis of plague but after completion of thermal cycling steps, it requires additional time to analyze amplified product using agarose gel electrophoresis. In the present study, PCR assay coupled with lateral flow strips has been developed for rapid detection of Y. pestis. Lateral flow strips give an alternative to gel electrophoresis and permit easy and rapid detection of PCR products. The PCR was performed with 5' 6-FAM and biotin tagged primers specific for Y. pestis, targeting yihN gene located on chromosome. The PCR product was analyzed using lateral flow strips which yielded result within 2-3 minutes. The analytical sensitivity of PCR-lateral flow (PCR-LF) assay was 1 pg genomic DNA of Y. pestis and 500 copies of target DNA sequence harboured in a recombinant plasmid. The assay could detect Y. pestis DNA extracted from spiked human blood samples containing ≥104 CFU per mL of bacteria. The assay was found to be specific and did not cross react with other closely related bacterial species. The developed assay was highly specific, sensitive and also did not require agarose gel electrophoresis for post amplification analysis.

Wuhan to World: The COVID-19 Pandemic.

COVID-19 is a Severe Acute Respiratory Syndrome (SARS), caused by SARS-CoV-2, a novel virus which belongs to the family Coronaviridae. It was first reported in December 2019 in the Wuhan city of China and soon after, the virus and hence the disease got spread to the entire world. As of February 26, 2021, SARS-CoV-2 has infected ~112.20 million people and caused ~2.49 million deaths across the globe. Although the case fatality rate among SARS-CoV-2 patient is lower (~2.15%) than its earlier relatives, SARS-CoV (~9.5%) and MERS-CoV (~34.4%), the SARS-CoV-2 has been observed to be more infectious and caused higher morbidity and mortality worldwide. As of now, only the knowledge regarding potential transmission routes and the rapidly developed diagnostics has been guiding the world for managing the disease indicating an immediate need for a detailed understanding of the pathogen and the disease-biology. Over a very short period of time, researchers have generated a lot of information in unprecedented ways in the key areas, including viral entry into the host, dominant mutation, potential transmission routes, diagnostic targets and their detection assays, potential therapeutic targets and drug molecules for inhibiting viral entry and/or its replication in the host including cross-neutralizing antibodies and vaccine candidates that could help us to combat the ongoing COVID-19 pandemic. In the current review, we have summarized the available knowledge about the pathogen and the disease, COVID-19. We believe that this readily available knowledge base would serve as a valuable resource to the scientific and clinical community and may help in faster development of the solution to combat the disease.

Direct impact of gonadotropins on glucose uptake and storage in preovulatory granulosa cells: Implications in the pathogenesis of polycystic ovary syndrome.

BACKGROUND: Polycystic ovary syndrome (PCOS) is often associated with higher levels of LH, and arrested ovarian follicular growth. The direct impact of high LH on FSH mediated metabolic responses in PCOS patients is not clearly understood. METHOD: In order to investigate the impact of FSH and LH on glucose metabolism in preovulatory granulosa cells (GCs), we used [U14C]-2 deoxyglucose, D-[U14C]-glucose or 2-NBD glucose to analyse glucose uptake and its incorporation into glycogen. To reproduce the high androgenic potential in PCOS patients, we administered hCG both in vitro and in vivo. The role of IRS-2/PI3K/Akt2 pathway was studied after knockdown with specific siRNA. Immunoprecipitation and specific assays were used for the assessment of IRS-2, glycogen synthase and protein phosphatase 1. Furthermore, we examined the in vivo effects of hCG on FSH mediated glycogen increase in normal and PCOS rat model. HEK293 cells co-expressing FSHR and LHR were used to demonstrate glucose uptake and BRET change by FSH and hCG. RESULTS: In normal human and rat granulosa cells, FSH is more potent than hCG in stimulating glucose uptake, however glycogen synthesis was significantly upregulated only by FSH through increase in activity of glycogen synthase via IRS-2/PI3K/Akt2 pathway. On the contrary, an impaired FSH-stimulated glucose uptake and glycogen synthesis in granulosa cells of PCOS-patients indicated a selective defect in FSHR activation. Further, in normal human granulosa cells, and in immature rat model, the impact of hCG on FSH responses was such that it inhibited the FSH-mediated glucose uptake as well as glycogen synthesis through inhibition of FSH-stimulated IRS-2 expression. These findings were further validated in HEK293 cells overexpressing Flag-LHR and HA-FSHR, where high hCG inhibited the FSH-stimulated glucose uptake. Notably, an increased BRET change was observed in HEK293 cells expressing FSHR-Rluc8 and LHR-Venus possibly suggesting increased heteromerization of LHR and FSHR in the presence of both hCG and FSH in comparison to FSH or hCG alone. CONCLUSION: Our findings confirm a selective attenuation of metabolic responses to FSH such as glucose uptake and glycogen synthesis by high activation level of LHR leading to the inhibition of IRS-2 pathway, resulting in depleted glycogen stores and follicular growth arrest in PCOS patients.

Development of a pair of real-time loop mediated isothermal amplification assays for detection of Yersinia pestis, the causative agent of plague.

Yersinia pestis, the causative agent of plague mainly infects rodents, while humans are the accidental host. The conventional diagnostic methods available for Y. pestis exhibit cross-reactivity with other enteropathogenic bacteria which makes its detection difficult. Rapid and reliable point-of-care detection of Y. pestis is essential for timely initiation of medical treatment. In the present study, a pair of loop mediated isothermal amplification (LAMP) assays has been developed for rapid detection of Y. pestis. Two sets of LAMP primers, each containing 6 primers were specifically designed targeting caf1 and 3a genes located on pFra plasmid and chromosome of Y. pestis, respectively. Isothermal amplification was accomplished at 65 °C for 40 min for caf1 target, and at 63 °C for 50 min for 3a choromosomal target. The analytical sensitivity of the assay for the caf1 and 3a targets was found to be 500 fg and 100 fg genomic DNA of Y. pestis, respectively. The caf1 and 3a LAMP assays detected as few as 100 copies of caf1 and 10 copies of 3a gene targets harboured in the respective recombinant plasmids. The amplified products were detected visually under visible and UV light using SYBR Green 1 dye. The assay pair was found to be highly specific as it did not cross-react with closely related and other bacterial species.