Microorganism-mediated biodegradation for effective management and/or removal of micro-plastics from the environment: a comprehensive review.

Micro- plastics (MPs) pose significant global threats, requiring an environment-friendly mode of decomposition. Microbial-mediated biodegradation and biodeterioration of micro-plastics (MPs) have been widely known for their cost-effectiveness, and environment-friendly techniques for removing MPs. MPs resistance to various biocidal microbes has also been reported by various studies. The biocidal resistance degree of biodegradability and/or microbiological susceptibility of MPs can be determined by defacement, structural deformation, erosion, degree of plasticizer degradation, metabolization, and/or solubilization of MPs. The degradation of microplastics involves microbial organisms like bacteria, mold, yeast, algae, and associated enzymes. Analytical and microbiological techniques monitor microplastic biodegradation, but no microbial organism can eliminate microplastics. MPs can pose environmental risks to aquatic and human life. Micro-plastic biodegradation involves fragmentation, assimilation, and mineralization, influenced by abiotic and biotic factors. Environmental factors and pre-treatment agents can naturally degrade large polymers or induce bio-fragmentation, which may impact their efficiency. A clear understanding of MPs pollution and the microbial degradation process is crucial for mitigating its effects. The study aimed to identify deteriogenic microorganism species that contribute to the biodegradation of micro-plastics (MPs). This knowledge is crucial for designing novel biodeterioration and biodegradation formulations, both lab-scale and industrial, that exhibit MPs-cidal actions, potentially predicting MPs-free aquatic and atmospheric environments. The study emphasizes the urgent need for global cooperation, research advancements, and public involvement to reduce micro-plastic contamination through policy proposals and improved waste management practices.

Microbial production of docosahexaenoic acid (DHA): biosynthetic pathways, physical parameter optimization, and health benefits.

Omega-3 fatty acids, including docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and α-linolenic acid (ALA), are essential polyunsaturated fatty acids with diverse health benefits. The limited conversion of dietary DHA necessitates its consumption as food supplements. Omega-3 fatty acids possess anti-arrhythmic and anti-inflammatory capabilities, contributing to cardiovascular health. Additionally, DHA consumption is linked to improved vision, brain, and memory development. Furthermore, omega-3 fatty acids offer protection against various health conditions, such as celiac disease, Alzheimer's, hypertension, thrombosis, heart diseases, depression, diabetes, and certain cancers. Fish oil from pelagic cold-water fish remains the primary source of omega-3 fatty acids, but the global population burden creates a demand-supply gap. Thus, researchers have explored alternative sources, including microbial systems, for omega-3 production. Microbial sources, particularly oleaginous actinomycetes, microalgae like Nannochloropsis and among microbial systems, Thraustochytrids stand out as they can store up to 50% of their dry weight in lipids. The microbial production of omega-3 fatty acids is a potential solution to meet the global demand, as these microorganisms can utilize various carbon sources, including organic waste. The biosynthesis of omega-3 fatty acids involves both aerobic and anaerobic pathways, with bacterial polyketide and PKS-like PUFA synthase as essential enzymatic complexes. Optimization of physicochemical parameters, such as carbon and nitrogen sources, pH, temperature, and salinity, plays a crucial role in maximizing DHA production in microbial systems. Overall, microbial sources hold significant promise in meeting the global demand for omega-3 fatty acids, offering an efficient and sustainable solution for enhancing human health.

Validation of a flow-cytometry-based red blood cell antigen phenotyping method.

BACKGROUND AND OBJECTIVES: Current manual and automated phenotyping methods are based on visual detection of the antigen-antibody interaction. This approach has several limitations including the use of large volumes of patient and reagent red blood cells (RBCs) and antisera to produce a visually detectable reaction. We sought to determine whether the flow cytometry could be developed and validated to perform RBC phenotyping to enable a high-throughput method of phenotyping using comparatively miniscule reagent volumes via fluorescence-based detection of antibody binding. MATERIALS AND METHODS: RBC phenotyping by flow cytometry was performed using monoclonal direct typing antisera (human IgM): anti-C, -E, -c, -e, -K, -Jka , -Jkb and indirect typing antisera (human IgG): anti-k, -Fya , -Fyb , -S, -s that are commercially available and currently utilized in our blood transfusion services (BTS) for agglutination-based phenotyping assays. RESULTS: Seventy samples were tested using both flow-cytometry-based-phenotyping and a manual tube standard agglutination assay. For all the antigens tested, 100% concordance was achieved. The flow-cytometry-based method used minimal reagent volume (0.5-1 µl per antigen) compared with the volumes required for manual tube standard agglutination (50 µl per antigen) CONCLUSION: This study demonstrates the successful validation of flow-cytometry-based RBC phenotyping. Flow cytometry offers many benefits compared to common conventional RBC phenotyping methods including high degrees of automation, quantitative assessment with automated interpretation of results and extremely low volumes of reagents. This method could be used for high-throughput, low-cost phenotyping for both blood suppliers and hospital BTS.

Humoral and T cell responses to SARS-CoV-2 reveal insights into immunity during the early pandemic period in Pakistan.

BACKGROUND: Protection against SARS-CoV-2 is mediated by humoral and T cell responses. Pakistan faced relatively low morbidity and mortality from COVID-19 through the pandemic. To examine the role of prior immunity in the population, we studied IgG antibody response levels, virus neutralizing activity and T cell reactivity to Spike protein in a healthy control group (HG) as compared with COVID-19 cases and individuals from the pre-pandemic period (PP). METHODS: HG and COVID-19 participants were recruited between October 2020 and May 2021. Pre-pandemic sera was collected before 2018. IgG antibodies against Spike and its Receptor Binding Domain (RBD) were determined by ELISA. Virus neutralization activity was determined using a PCR-based micro-neutralization assay. T cell - IFN-γ activation was assessed by ELISpot. RESULTS: Overall, the magnitude of anti-Spike IgG antibody levels as well as seropositivity was greatest in COVID-19 cases (90%) as compared with HG (39.8%) and PP (12.2%). During the study period, Pakistan experienced three COVID-19 waves. We observed that IgG seropositivity to Spike in HG increased from 10.3 to 83.5% during the study, whilst seropositivity to RBD increased from 7.5 to 33.3%. IgG antibodies to Spike and RBD were correlated positively in all three study groups. Virus neutralizing activity was identified in sera of COVID-19, HG and PP. Spike reactive T cells were present in COVID-19, HG and PP groups. Individuals with reactive T cells included those with and without IgG antibodies to Spike. CONCLUSIONS: Antibody and T cell responses to Spike protein in individuals from the pre-pandemic period suggest prior immunity against SARS-CoV-2, most likely from cross-reactive responses. The rising seroprevalence observed in healthy individuals through the pandemic without known COVID-19 may be due to the activation of adaptive immunity from cross-reactive memory B and T cells. This may explain the more favourable COVID-19 outcomes observed in this population.

A community-of-practice-based evaluation methodology for knowledge intensive computational methods and its application to multimorbidity decision support.

OBJECTIVE: The study has dual objectives. Our first objective (1) is to develop a community-of-practice-based evaluation methodology for knowledge-intensive computational methods. We target a whitebox analysis of the computational methods to gain insight on their functional features and inner workings. In more detail, we aim to answer evaluation questions on (i) support offered by computational methods for functional features within the application domain; and (ii) in-depth characterizations of the underlying computational processes, models, data and knowledge of the computational methods. Our second objective (2) involves applying the evaluation methodology to answer questions (i) and (ii) for knowledge-intensive clinical decision support (CDS) methods, which operationalize clinical knowledge as computer interpretable guidelines (CIG); we focus on multimorbidity CIG-based clinical decision support (MGCDS) methods that target multimorbidity treatment plans. MATERIALS AND METHODS: Our methodology directly involves the research community of practice in (a) identifying functional features within the application domain; (b) defining exemplar case studies covering these features; and (c) solving the case studies using their developed computational methods-research groups detail their solutions and functional feature support in solution reports. Next, the study authors (d) perform a qualitative analysis of the solution reports, identifying and characterizing common themes (or dimensions) among the computational methods. This methodology is well suited to perform whitebox analysis, as it directly involves the respective developers in studying inner workings and feature support of computational methods. Moreover, the established evaluation parameters (e.g., features, case studies, themes) constitute a re-usable benchmark framework, which can be used to evaluate new computational methods as they are developed. We applied our community-of-practice-based evaluation methodology on MGCDS methods. RESULTS: Six research groups submitted comprehensive solution reports for the exemplar case studies. Solutions for two of these case studies were reported by all groups. We identified four evaluation dimensions: detection of adverse interactions, management strategy representation, implementation paradigms, and human-in-the-loop support. Based on our whitebox analysis, we present answers to the evaluation questions (i) and (ii) for MGCDS methods. DISCUSSION: The proposed evaluation methodology includes features of illuminative and comparison-based approaches; focusing on understanding rather than judging/scoring or identifying gaps in current methods. It involves answering evaluation questions with direct involvement of the research community of practice, who participate in setting up evaluation parameters and solving exemplar case studies. Our methodology was successfully applied to evaluate six MGCDS knowledge-intensive computational methods. We established that, while the evaluated methods provide a multifaceted set of solutions with different benefits and drawbacks, no single MGCDS method currently provides a comprehensive solution for MGCDS. CONCLUSION: We posit that our evaluation methodology, applied here to gain new insights into MGCDS, can be used to assess other types of knowledge-intensive computational methods and answer other types of evaluation questions. Our case studies can be accessed at our GitHub repository (https://github.com/william-vw/MGCDS).

Impact of Treviamet® & Treviamet XR® on quality of life besides glycemic control in type 2 DM patients.

BACKGROUND: Maintaining the quality of life is the main objective of managing type 2 diabetes (T2DM) (QoL). Since it is a key factor in patient motivation and adherence, treatment-related QoL has always been considered when choosing glucose-lowering medicines. The objective of the study was to evaluate the quality of life besides glycemic control among type 2 diabetes mellitus patients receiving Treviamet® & Treviamet XR® (Sitagliptin with Metformin) in routine care. METHODS: It was a prospective, open-label, non-randomized clinical trial including T2DM patients uncontrolled on Metformin therapy. All patients received Treviamet® & Treviamet XR® for six months. Sequential changes in QoL, fasting plasma glucose, HbA1c, body weight, and blood pressure were monitored from baseline to 3 consecutive follow-up visits. The frequency of adverse events (AEs) was also noted throughout the study. RESULTS: A total of 504 patients were screened; 188 completed all three follow-ups. The mean QoL score significantly declined from 57.09% at baseline to 33.64% at the 3rd follow-up visit (p < 0.01). Moreover, a significant decline in mean HbA1c and FPG levels was observed from baseline to 3rd follow-up visit (p < 0.01). Minor adverse events were observed, including abdominal discomfort, nausea, flatulence, and indigestion. Gender, HbA1c, diarrhea, and abdominal discomfort were significant predictors of a patient's QoL, as revealed by the Linear Regression Model (R2 = 0.265, F(16, 99) = 2.231). CONCLUSION: Treviamet® & Treviamet XR® significantly improved glycemic control (HbA1c levels) and QoL in T2DM patients without serious adverse events. TRIAL REGISTRATION: ClinicalTrials.gov identifier (NCT05167513), Date of registration: December 22, 2021.

Needs and expectations for artificial intelligence in emergency medicine according to Canadian physicians.

BACKGROUND: Artificial Intelligence (AI) is recognized by emergency physicians (EPs) as an important technology that will affect clinical practice. Several AI-tools have already been developed to aid care delivery in emergency medicine (EM). However, many EM tools appear to have been developed without a cross-disciplinary needs assessment, making it difficult to understand their broader importance to general-practice. Clinician surveys about AI tools have been conducted within other medical specialties to help guide future design. This study aims to understand the needs of Canadian EPs for the apt use of AI-based tools. METHODS: A national cross-sectional, two-stage, mixed-method electronic survey of Canadian EPs was conducted from January-May 2022. The survey includes demographic and physician practice-pattern data, clinicians' current use and perceptions of AI, and individual rankings of which EM work-activities most benefit from AI. RESULTS: The primary outcome is a ranked list of high-priority AI-tools for EM that physicians want translated into general use within the next 10 years. When ranking specific AI examples, 'automated charting/report generation', 'clinical prediction rules' and 'monitoring vitals with early-warning detection' were the top items. When ranking by physician work-activities, 'AI-tools for documentation', 'AI-tools for computer use' and 'AI-tools for triaging patients' were the top items. For secondary outcomes, EPs indicated AI was 'likely' (43.1%) or 'extremely likely' (43.7%) to be able to complete the task of 'documentation' and indicated either 'a-great-deal' (32.8%) or 'quite-a-bit' (39.7%) of potential for AI in EM. Further, EPs were either 'strongly' (48.5%) or 'somewhat' (39.8%) interested in AI for EM. CONCLUSIONS: Physician input on the design of AI is essential to ensure the uptake of this technology. Translation of AI-tools to facilitate documentation is considered a high-priority, and respondents had high confidence that AI could facilitate this task. This study will guide future directions regarding the use of AI for EM and help direct efforts to address prevailing technology-translation barriers such as access to high-quality application-specific data and developing reporting guidelines for specific AI-applications. With a prioritized list of high-need AI applications, decision-makers can develop focused strategies to address these larger obstacles.

Efficacy of an mHealth Behavior Change Intervention for Promoting Physical Activity in the Workplace: Randomized Controlled Trial.

BACKGROUND: Insufficient physical activity (PA) is a well-established risk factor for several noncommunicable diseases such as cardiovascular diseases, cancer, diabetes, depression, and dementia. The World Health Organization (WHO) advises that individuals engage in 150 minutes of moderate PA per week or 75 minutes of intense PA per week. According to the WHO's latest report, 23% of adults fail to meet the minimum recommended level of PA. The percentage was even higher in a recent global study that showed 27% of adults were insufficiently active and reported a 5% increase in the prevalence trend of insufficient PA between 2001 and 2016. The study also showed the rate of insufficient PA among countries varied significantly. For instance, it was estimated that 40% were insufficiently active in the United States, and the percentage was even higher in Saudi Arabia (more than 50%). Governments are actively developing policies and methods to successfully establish a PA-inducing environment that encourages a healthy lifestyle in order to address the global steady decline in PA. OBJECTIVE: The purpose of this study was to determine the effectiveness of mobile health (mHealth) interventions, particularly SMS text messaging interventions, to improve PA and decrease BMI in healthy adults in the workplace. METHODS: In this parallel, 2-arm randomized controlled trial, healthy adults (N=327) were randomized to receive an mHealth intervention (tailored text messages combined with self-monitoring (intervention; n=166) or no intervention (control; n=161). Adults who were fully employed in an academic institution and had limited PA during working hours were recruited for the study. Outcomes, such as PA and BMI, were assessed at baseline and 3 months later. RESULTS: Results showed significant improvement in PA levels (weekly step counts) in the intervention group (ß=1097, 95% CI 922-1272, P<.001). There was also a significant reduction in BMI (ß=0.60, 95% CI 0.50-0.69, P<.001). CONCLUSIONS: Combining tailored text messages and self-monitoring interventions to improve PA and lower BMI was significantly effective and has the potential to leverage current methods to improve wellness among the public.

Molecular mechanisms of neuroprotective offerings by rosmarinic acid against neurodegenerative and other CNS pathologies.

Rosmarinic acid (RA) is a natural phenolic compound present in culinary herbs of the Boraginaceae, Lamiaceae/Labiatae, and Nepetoideae families. While the medicinal applications of these plants have been known for ages, RA has only been relatively recently established as an effective ameliorative agent against various disorders including cardiac diseases, cancer, and neuropathologies. In particular, several studies have confirmed the neuroprotective potential of RA in multiple cellular and animal models, as well as in clinical studies. The neuroprotective effects mediated by RA stem from its multimodal actions on a plethora of cellular and molecular pathways; including oxidative, bioenergetic, neuroinflammatory, and synaptic signaling. In recent years, RA has garnered tremendous interest as an ideal therapeutic candidate for treating neurodegenerative diseases. This review first briefly discusses the pharmacokinetics of RA and then proceeds to detail the neuroprotective mechanisms of RA at the molecular levels. Finally, the authors focus on the ameliorative potential of RA against several central nervous system (CNS) disorders, ranging from neuropsychological stress and epilepsy to neurodegenerative diseases such as Alzheimer's disease, Huntington's disease, Parkinson's disease, Lewy body dementia, and amyotrophic lateral sclerosis.

Acute Porphyria: An Unusual Case Of Quadriparesis, Hypertension, Recurrent Severe Cyclic Abdominal Pain, And Seizures.

Porphyria refers to a rare group of genetically inherited or acquired disorders that arise due to reduced metabolic activity of any of the enzymes in the haem biosynthetic pathway. Defect in any enzyme causes the presentation of symptoms of porphyria. The epidemiology of Acute Intermittent Porphyria (AIP) is complicated because of its rarity and delay in diagnosis. We present the case of a seven-year-old girl who presented with multisystem involvement; her symptoms were quadriparesis, hypertension, recurrent severe cyclic abdominal pain, and seizures. These symptoms together were not explained by the differentials taken into account. She presented before puberty with no family history of such conditions, while being born of consanguineous marriage. Her symptoms along with urinary porphobilinogen positivity test helped to reach the diagnosis of AIP in the absence of cutaneous manifestations. This case highlights the variable presentation of porphyria and emphasises the importance of appropriate and timely diagnosis and management in these patients.

Idiopathic Pulmonary Haemosiderosis: An Unusual Case Of Anaemia With Pulmonary Involvement.

Idiopathic pulmonary haemosiderosis is a rare disorder, with recurrent life-threatening alveolar haemorrhages and chronic lung parenchymal changes. It is associated with a triad of haemoptysis, iron deficiency anaemia, and diffuse pulmonary infiltrates. Although most cases are idiopathic, secondary haemosiderosis linked to known diseases has also been observed. Most of the cases remain undiagnosed because the disease is very low on the list of differentials. There is no specified age for the disease. The present study reports on an adolescent female patient who presented with microcytic anaemia and bilateral lung infiltrates to the National Institute of Child Health (NICH), Karachi, a tertiary care hospital. She was diagnosed with Idiopathic pulmonary haemosiderosis after ruling out other possibilities.

Epidemiology Of Male Urethral Strictures In Pakistan.

Urethral stricture disease is relatively common in Pakistan, constituting 4-5% of the urological workload. Despite the high prevalence, little is known about its epidemiology in the country. The current narrative review comprised search on PubMed, Pak MediNet and Google Scholar databases for studies done in Pakistan and published between January 1, 2000, and December 31, 2021. The search yielded 30 local publications on stricture urethra. Demographic data as well as causes and management pattern of male urethral stricture were noted and analysed. There were 5,021 patients, with 3850 (76.6%) being from the province of Sindh. The disease had the greatest impact on younger patients aged up to 40 years (n=1572), while after the age of 60 years, 248 (9%) patients had the disease. The common cause was trauma due to road traffic accidents in both anterior and posterior strictures compared to idiopathic cause reported in the West. Infection 170 (6.9%) and Lichen sclerosis 123(4.5%) as a cause was found to decline in our region. A clinic-based regular urethral dilatation was still in practice at some centres to manage such cases. Vast majority of stricture patients were being treated by endoscopic procedures, and only 1154 (23%) cases underwent urethroplasty.

Chest X-ray Analysis With Deep Learning-Based Software as a Triage Test for Pulmonary Tuberculosis: An Individual Patient Data Meta-Analysis of Diagnostic Accuracy.

BACKGROUND: Automated radiologic analysis using computer-aided detection software (CAD) could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence on the accuracy of commercially available deep learning-based CAD in different populations, including patients with smear-negative tuberculosis and people living with human immunodeficiency virus (HIV, PLWH). METHODS: We collected CXRs and individual patient data (IPD) from studies evaluating CAD in patients self-referring for tuberculosis symptoms with culture or nucleic acid amplification testing as the reference. We reanalyzed CXRs with three CAD programs (CAD4TB version (v) 6, Lunit v3.1.0.0, and qXR v2). We estimated sensitivity and specificity within each study and pooled using IPD meta-analysis. We used multivariable meta-regression to identify characteristics modifying accuracy. RESULTS: We included CXRs and IPD of 3727/3967 participants from 4/7 eligible studies. 17% (621/3727) were PLWH. 17% (645/3727) had microbiologically confirmed tuberculosis. Despite using the same threshold score for classifying CXR in every study, sensitivity and specificity varied from study to study. The software had similar unadjusted accuracy (at 90% pooled sensitivity, pooled specificities were: CAD4TBv6, 56.9% [95% confidence interval {CI}: 51.7-61.9]; Lunit, 54.1% [95% CI: 44.6-63.3]; qXRv2, 60.5% [95% CI: 51.7-68.6]). Adjusted absolute differences in pooled sensitivity between PLWH and HIV-uninfected participants were: CAD4TBv6, -13.4% [-21.1, -6.9]; Lunit, +2.2% [-3.6, +6.3]; qXRv2: -13.4% [-21.5, -6.6]; between smear-negative and smear-positive tuberculosis was: were CAD4TBv6, -12.3% [-19.5, -6.1]; Lunit, -17.2% [-24.6, -10.5]; qXRv2, -16.6% [-24.4, -9.9]. Accuracy was similar to human readers. CONCLUSIONS: For CAD CXR analysis to be implemented as a high-sensitivity tuberculosis rule-out test, users will need threshold scores identified from their own patient populations and stratified by HIV and smear status.

Biobutanol production from sustainable biomass process of anaerobic ABE fermentation for industrial applications.

The growing population increases the need to develop advanced biological methods for utilizing renewable and sustainable resources to produce environmentally friendly biofuels. Currently, energy resources are limited for global demand and are constantly depleting and creating environmental problems. Some higher chain alcohols, like butanol and ethanol, processing similar properties to gasoline, can be alternate sources of biofuel. However, the industrial production of these alcohols remains challenging because they cannot be efficiently produced by microbes naturally. Therefore, butanol is the most interesting biofuel candidate with a higher octane number produced naturally by microbes through Acetone-Butanol-Ethanol fermentation. Feedstock selection as the substrate is the most crucial step in biobutanol production. Lignocellulosic biomass has been widely used to produce cellulosic biobutanol using agricultural wastes and residue. Specific necessary pretreatments, fermentation strategies, bioreactor designing and kinetics, and modeling can also enhance the efficient production of biobutanol. The recent genetic engineering approaches of gene knock in, knock out, and overexpression to manipulate pathways can increase the production of biobutanol in a user friendly host organism. So far various genetic manipulation techniques like antisense RNA, TargeTron Technology and CRISPR have been used to target Clostridium acetobutylicum for biobutanol production. This review summarizes the recent research and development for the efficient production of biobutanol in various aspects.

Seroprevalence and characteristics of Coronavirus Disease (COVID-19) in workers with non-specific disease symptoms.

BACKGROUND: The population-based serosurveys are essential for estimating Coronavirus Disease-19 (COVID-19) burden and monitoring the progression of this pandemic. We aimed to assess the seroprevalence of SARS-CoV-2 antibodies and potential predictors of seropositivity in the Pakistani population. METHODOLOGY: This population-based seroprevalence study includes consenting subjects from the workplaces (factories, corporates, restaurants, media houses, schools, banks, and hospitals) located in the urban areas of Karachi, Lahore, Multan, Peshawar, and Quetta. We analyzed each subject's serum sample for SARS-CoV-2-IgM and/or IgG antibodies using UNIPER IgG/IgM Rapid COVID-19 Testing Kit. The subject's demographics, exposure history, and symptoms experienced (in last 7 days) were also obtained. The collected data was analyzed using SPSS version 22.0. RESULTS: The overall seroprevalence of SARS-CoV-2 antibodies was 16.0% (2810/17,764). The total antibody seropositivity was higher in males than females (OR 1.22, 95% CI 1.110-1.340). The symptomatic subjects had 2.18 times higher odds of IgG seropositivity while 1.2 times for IgM seropositivity than the asymptomatic subjects. The multivariable logistic regression model showed that the odds of SARS-CoV-2 total antibody seroprevalence were affected by the number of dependents (OR = 1.077; 95% CI 1.054-1.099), apparent symptomology (OR = 1.288; 95% CI 1.011-1.643), close unprotected contact with a confirmed or probable case of COVID-19 (OR 2.470; 95% CI 2.164-2.819), traveling history (last 14 days) (OR = 1.537; 95% CI 1.234-1.914) and proximity with someone who traveled (OR = 1.534; 95% CI 1.241-1.896). CONCLUSION: We found a reasonable seroprevalence of SARS-CoV-2 antibodies in the studied population. Several factors like the number of dependents, apparent symptoms, close unprotected contact with a confirmed or probable case of COVID-19, traveling history, and proximity with someone who traveled are associated with increased odds of SARS-CoV-2 antibody seropositivity.

Analysis of the Antimicrobial and Anti-Biofilm Activity of Natural Compounds and Their Analogues against Staphylococcus aureus Isolates.

(1) Background: Staphylococcus aureus (S. aureus) is one of the most frequent causes of biofilm-associated infections. With the emergence of antibiotic-resistant, especially methicillin-resistant S. aureus (MRSA), there is an urgent need to discover novel inhibitory compounds against this clinically important pathogen. In this study, we evaluated the antimicrobial and anti-biofilm activity of 11 compounds, including phenyl propenes and phenolic aldehydes, eugenol, ferulic acid, sinapic acid, salicylaldehyde, vanillin, cinnamoyl acid, and aldehydes, against drug-resistant S. aureus isolates. (2) Methods: Thirty-two clinical S. aureus isolates were obtained from Alkhidmat Diagnostic Center and Blood Bank, Karachi, Pakistan, and screened for biofilm-forming potential, and susceptibility/resistance against ciprofloxacin, chloramphenicol, ampicillin, amikacin, cephalothin, clindamycin, streptomycin, and gentamicin using the Kirby-Bauer disk diffusion method. Subsequently, 5 representative clinical isolates were selected and used to test the antimicrobial and anti-biofilm potential of 11 compounds using both qualitative and quantitative assays, followed by qPCR analysis to examine the differences in the expression levels of biofilm-forming genes (ica-A, fnb-B, clf-A and cna) in treated (with natural compounds and their derivatives) and untreated isolates. (3) Results: All isolates were found to be multi-drug resistant and dominant biofilm formers. The individual Minimum Inhibitory Concentration (MIC) of natural compounds and their analogues ranged from 0.75−160 mg/mL. Furthermore, the compounds, Salicylaldehyde (SALI), Vanillin (VAN), α-methyl-trans-cinnamaldehyde (A-MT), and trans-4-nitrocinnamic acid (T4N) exhibited significant (15−92%) biofilm inhibition/reduction percentage capacity at the concentration of 1−10 mg/mL. Gene expression analysis showed that salicylaldehyde, α-methyl-trans-cinnamaldehyde, and α-bromo-trans-cinnamaldehyde resulted in a significant (p < 0.05) downregulation of the expression of ica-A, clf-A, and fnb-A genes compared to the untreated resistant isolate. (4) Conclusions: The natural compounds and their analogues used in this study exhibited significant antimicrobial and anti-biofilm activity against S. aureus. Biofilms persist as the main concern in clinical settings. These compounds may serve as potential candidate drug molecules against biofilm forming S. aureus.

Interactions of Apigenin and Safranal with the 5HT1A and 5HT2A Receptors and Behavioral Effects in Depression and Anxiety: A Molecular Docking, Lipid-Mediated Molecular Dynamics, and In Vivo Analysis.

BACKGROUND: The current study utilizes in silico molecular docking/molecular dynamics to evaluate the binding affinity of apigenin and safranal with 5HT1AR/5HT2AR, followed by assessment of in vivo effects of these compounds on depressive and anxious behavior. METHODS: The docking between apigenin and safranal and the 5HT1A and 5HT2A receptors was performed utilizing AutoDock Vina software, while MD and protein-lipid molecular dynamics simulations were executed by AMBER16 software. For in vivo analysis, healthy control (HC), disease control (DC), fluoxetine-, and apigenin-safranal-treated rats were tested for changes in depression and anxiety using the forced swim test (FST) and the elevated plus-maze test (EPMT), respectively. RESULTS: The binding affinity estimations identified the superior interacting capacity of apigenin over safranal for 5HT1A/5HT2A receptors over 200 ns MD simulations. Both compounds exhibit oral bioavailability and absorbance. In the rodent model, there was a significant increase in the overall mobility time in the FST, while in the EPMT, there was a decrease in latency and an increase in the number of entries for the treated and HC rats compared with the DC rats, suggesting a reduction in depressive/anxiety symptoms after treatment. CONCLUSIONS: Our analyses suggest apigenin and safranal as prospective medication options to treat depression and anxiety.

HBV S antigen evolution in the backdrop of HDV infection affects epitope processing and presentation.

INTRODUCTION: HBV can evolve under selection pressure exerted by drugs and/or host immunity, resulting in accumulation of escape mutations that can affect the drug or the immune activity. Hepatitis delta virus (HDV) coinfection is also known to exert selection pressure on HBV, which leads to selective amplification of certain mutations, especially in genes that are required for HDV pathogenesis, such as HBsAg. However, little is known about the function of these mutations on HBV or HDV life cycle. The purpose of this study is to determine mutations selectively amplified in the backdrop of HDV, and how these mutations affect processing of CD4- and CD8-T cell epitopes. METHODS: HBsAg was successfully amplified from 49/50 HBV mono- and 36/50 coinfected samples. The sequences were used to identify mutations specific to each study group, followed by an in silico analysis to determine the effect of these mutations on (1) proteasomal degradation, (2) MHC-I and MHC-II biding, and (3) processing of T-cell epitopes. RESULTS: HBV-HDV coinfected sequences exhibited certain unique mutations in HBsAg genes. Some of these mutations affected the generation of proteasomal sites, binding of HBsAg epitopes to MHC-I and -II ligands, and subsequent generation of T- cell epitopes. CONCLUSION: These observations suggest that HBV selectively amplifies certain mutations in the backdrop of HDV coinfection. Selective amplification of these mutations at certain strategic locations might not only enable HBV to counteract the inhibitory effects of HDV on HBV replication but also facilitate its survival by escaping the immune response.

Multifunctional Gold Nanoparticle-Conjugated Cellulose Nanoonions Alleviate Aß42 Fibrillation-Induced Toxicity via Regulation of Oxidative Stress and Ion Homeostasis.

Inhibition of hen egg white lysozyme (HEWL) and Aß42 fibrillation have been established as the main models for the treatment of systemic lysozyme amyloidosis and Alzheimer's disease (AD), respectively. Several antiamyloidogenic nanomaterials have been developed over the period; however, their intracellular mechanism of action is still not well understood. In this context, plant-based, gold-conjugated, injectable, hydrophilic cellulose nanoonions (CNOs), viz., DH-CNO (∼60 ± 5 nm) and LC-CNO (∼55 ± 12 nm), were developed from their respective hydrophobic cellulose nanocrystals (DH-CNC and LC-CNC) using a single-step chemical template-mediated process. This unique nanocellulose architecture was chemically and morphologically characterized by various spectroscopic and microscopic techniques. Further, the different biophysical studies documented marked the inhibition/disintegration potential of gold-conjugated LC-CNO against HEWL and Aß42 peptide aggregation. It was further observed that inhibition of protein fibrillation could be achieved within ∼10 min when the same materials were used under photoirradiation conditions. In vitro protein aggregation studies using HEK293 cells suggested that gold-conjugated LC-CNO could effectively reduce the cellular toxicity via regulation of oxidative stress and ion homeostasis. The outcome of the present study will help in designing cellulose-based novel functional nanochaperones against various neurodegenerative diseases.

Blue Biotechnology: Computational Screening of Sarcophyton Cembranoid Diterpenes for SARS-CoV-2 Main Protease Inhibition.

The coronavirus pandemic has affected more than 150 million people, while over 3.25 million people have died from the coronavirus disease 2019 (COVID-19). As there are no established therapies for COVID-19 treatment, drugs that inhibit viral replication are a promising target; specifically, the main protease (Mpro) that process CoV-encoded polyproteins serves as an Achilles heel for assembly of replication-transcription machinery as well as down-stream viral replication. In the search for potential antiviral drugs that target Mpro, a series of cembranoid diterpenes from the biologically active soft-coral genus Sarcophyton have been examined as SARS-CoV-2 Mpro inhibitors. Over 360 metabolites from the genus were screened using molecular docking calculations. Promising diterpenes were further characterized by molecular dynamics (MD) simulations based on molecular mechanics-generalized Born surface area (MM-GBSA) binding energy calculations. According to in silico calculations, five cembranoid diterpenes manifested adequate binding affinities as Mpro inhibitors with ΔGbinding < -33.0 kcal/mol. Binding energy and structural analyses of the most potent Sarcophyton inhibitor, bislatumlide A (340), was compared to darunavir, an HIV protease inhibitor that has been recently subjected to clinical-trial as an anti-COVID-19 drug. In silico analysis indicates that 340 has a higher binding affinity against Mpro than darunavir with ΔGbinding values of -43.8 and -34.8 kcal/mol, respectively throughout 100 ns MD simulations. Drug-likeness calculations revealed robust bioavailability and protein-protein interactions were identified for 340; biochemical signaling genes included ACE, MAPK14 and ESR1 as identified based on a STRING database. Pathway enrichment analysis combined with reactome mining revealed that 340 has the capability to re-modulate the p38 MAPK pathway hijacked by SARS-CoV-2 and antagonize injurious effects. These findings justify further in vivo and in vitro testing of 340 as an antiviral agent against SARS-CoV-2.