Optimizing hierarchical membrane/catalyst systems for oxidative coupling of methane using additive manufacturing.

The advantage of a membrane/catalyst system in the oxidative coupling of methane compared with conventional reactive systems is that by introducing oxygen into the catalytic sites through a membrane, the parasitic gas-phase reactions of O2(g)-responsible for lowering product selectivity-can be avoided. The design and fabrication of membrane/catalyst systems has, however, been hampered by low volumetric chemical conversion rates, high capital cost and difficulties in co-designing membrane and catalyst properties to optimize the performance. Here we solve these issues by developing a dual-layer additive manufacturing process, based on phase inversion, to design, fabricate and optimize a hollow-fibre membrane/catalyst system for the oxidative coupling of methane. We demonstrate the approach through a case study using BaCe0.8Gd0.2O3-δ as the basis of both catalyst and separation layers. We show that by using the manufacturing approach, we can co-design the membrane thickness and catalyst surface area so that the flux of oxygen transport through the membrane and methane activation rates in the catalyst layer match each other. We demonstrate that this 'rate matching' is critical for maximizing the performance, with the membrane/catalyst system substantially overperforming conventional reactor designs under identical conditions.

Transcobalamin deficiency - a rare genetic defect in transportation of cobalamin; case report.

BACKGROUND: Vitamin B12 is primarily transported from plasma to cells by Transcobalamin. Deficiency of Transcobalamin is a rare autosomal recessive disorder that results in unavailability of cobalamin in cells and accumulation of homocysteine and methylmalonic acid. CASE REPORT: We report a case of a 2-year-old male child with persistent pancytopenia, recurrent infections, and megaloblastic anemia. Next-generation sequencing identified a novel variant in exon 8 of TCN2 gene. Substantial improvement has been observed following administration of high doses of parenteral methylcobalamin. CONCLUSION: In patients with unresolved pancytopenia and megaloblastic anemia, Transcobalamin deficiency should be investigated and treated promptly to prevent any irreversible and harmful outcome.

Mental health literacy and help-seeking behaviour among Egyptian undergraduates: a cross-sectional national study.

BACKGROUND: Mental health literacy (MHL) and help-seeking behaviors are pivotal in managing mental well-being, especially among Egyptian undergraduates. Despite the importance and prevalent psychological distress in this group, limited research has addressed MHL and associated behaviors in Egypt. This study aimed to assess the levels of MHL and help-seeking behavior among Egyptian university students. METHODS: A cross-sectional study was conducted across ten Egyptian universities during the academic year 2022-2023. A convenience sample of 1740 students was obtained through online questionnaires distributed via social media platforms. The survey comprised demographic characteristics, the Mental Health Literacy Scale (MHLS), and the General Help Seeking Behavior Questionnaire (GHSPQ). RESULTS: Among 1740 Egyptian undergraduates, medical students scored higher in recognizing disorders (p < 0.05), while non-medical students excelled in attitudes (p < 0.05). A strong correlation was observed between attitudes toward mental illness and total mental health literacy (coefficients of 0.664 and 0.657). Univariate analysis indicated a significant association with professional help-seeking (OR = 1.023). Females, individuals aged 21 or above, and non-medical students were more likely to seek mental health information (OR = 1.42, 1.82, 1.55 respectively). Help-seeking behavior for emotional problems was more inclined towards intimate partners, whereas suicidal thoughts prompted seeking professional help. CONCLUSION: The findings advocate for comprehensive mental health education, particularly in rural areas, and emphasis on the role of personal relationships in mental well-being. Implementing these insights could foster improved mental health outcomes and reduce related stigma in Egypt.

Risk factors and early preventive measures for long COVID in non-hospitalized patients: analysis of a large cohort in the United Arab Emirates.

OBJECTIVES: Long COVID is characterized by persistent symptoms lasting for 4 weeks or more following the acute infection with SARS-CoV-2. Risk factors for long COVID and the impact of pre-COVID vaccination and treatment during acute COVID-19 remain uncertain. This study aimed to investigate patient-specific factors associated with long COVID in a large cohort of non-hospitalized adult patients with mild to moderate COVID-19 in Dubai. STUDY DESIGN: Cohort study. METHODS: The study included 28,375 non-hospitalized adult patients diagnosed with mild to moderate COVID-19 between January 1, 2021, and September 31, 2022, in Dubai, who were followed up for 90 days. The presence of long COVID symptoms was documented by physicians during patient visits to the family medicine department. Furthermore, long COVID-related risk factors were collected and analyzed, including patient demographics, comorbidities, pre-COVID vaccination status, and the COVID-related treatments received during the acute phase of the illness. Cox proportional hazard models were applied for the statistical analysis. RESULTS: Among the cohort, 2.8% of patients experienced long COVID symptoms during the 90-day follow-up. Patients with long COVID tended to be younger, female, and of Caucasian race. Common symptoms included fatigue, muscle pain, respiratory symptoms, abdominal and neurological symptoms, allergic reactions, skin rashes, and hair loss. Risk factors for long COVID were identified as diabetes mellitus, asthma, and Vitamin D deficiency. Females and Caucasians had a higher risk of long COVID during the pre-Omicron period compared to the Omicron period. Pre-COVID vaccination was associated with a reduced risk of long COVID in all patient subgroups. Treatment with favipiravir or sotrovimab during the acute phase of COVID-19 was linked to a decreased risk of long COVID, although favipiravir showed limited effectiveness in the high-risk group. CONCLUSION: This study contributes to the existing knowledge by identifying risk factors for long COVID among non-hospitalized patients and emphasizing the potential benefits of pre-COVID vaccination and timely treatment.

Solar desalination system for fresh water production performance estimation in net-zero energy consumption building: A comparative study on various machine learning models.

This study employs diverse machine learning models, including classic artificial neural network (ANN), hybrid ANN models, and the imperialist competitive algorithm and emotional artificial neural network (EANN), to predict crucial parameters such as fresh water production and vapor temperatures. Evaluation metrics reveal the integrated ANN-ICA model outperforms the classic ANN, achieving a remarkable 20% reduction in mean squared error (MSE). The emotional artificial neural network (EANN) demonstrates superior accuracy, attaining an impressive 99% coefficient of determination (R2) in predicting freshwater production and vapor temperatures. The comprehensive comparative analysis extends to environmental assessments, displaying the solar desalination system's compatibility with renewable energy sources. Results highlight the potential for the proposed system to conserve water resources and reduce environmental impact, with a substantial decrease in total dissolved solids (TDS) from over 6,000 ppm to below 50 ppm. The findings underscore the efficacy of machine learning models in optimizing solar-driven desalination systems, providing valuable insights into their capabilities for addressing water scarcity challenges and contributing to the global shift toward sustainable and environmentally friendly water production methods.

The Effects of Six Weeks Pulmonary Rehabilitation on Functional and Psychological Outcomes in Long-COVID Patients: Preliminary Results from Serbian Single Center Study.

Background and Objectives: In this study, we aimed to evaluate the effects of six weeks of pulmonary rehabilitation on functional and psychological outcomes in long-COVID patients. Material and Methods: The prospective clinical study included 46 patients that were diagnosed with COVID-19. A respiratory rehabilitation program was implemented for six weeks. Further valuables were tested before the beginning of the rehabilitation program (admission) and six weeks after (discharge): SpO2, heart rate, respiratory rate, Visual Analogue Scale (VAS) score, Borg score, Sit-to-Stand (StS) test number of repetition, distance of 6-Minute Walking Test (6MWT), Patient Health Questionnaire (PHQ) 9 score and Generalized anxiety disorder (GAD) anxiety score. These parameters were tested before the rehabilitation program on admission and at discharge and after the rehabilitation program on admission and at discharge. The results were presented with standard descriptive and analytical methods. Differences between the continuous variables before and after physical rehabilitation intervention were tested using the Wilcoxon test. Graphical analysis is presented with a box plot. Results: On discharge, in comparison with admission, the values of SpO2 were significantly lower (p = 0.007) before the 6MWT, and VAS scores were significantly higher (p = 0.036), while after the 6MWT, VAS scores were significantly lower (p < 0.001) as were Borg scores (p = 0.016). On discharge, in comparison with admission, the respiratory rate was significantly higher (p = 0.005) before the StS test, and Borg scores were significantly lower (p = 0.001), while after the StS test, SpO2 levels were significantly higher (p = 0.036) and VAS scores were significantly lower (p < 0.001), as were Borg scores (p = 0.008). After discharge, the values of the StS test were significantly higher (p = 0.011), PHQ9 scores were significantly lower (p < 0.001) and GAD anxiety scores were significantly lower as well (p = 0.005), while the distances measured in meters on the 6MWT were significantly increased (p < 0.001). Conclusions: A structured rehabilitation program in our study was shown to have beneficial effects on physiological, psychological and functional improvements in patients with long-COVID, and therefore it is advisable for these patients.

Effectiveness of functional electrical stimulation machine in managing neurological diseases - A retrospective study.

Background & Objective: Cerebrovascular Accident (CVA) or stroke, Spinal Cord injury can lead to neurological diseases resulting in major loss in motor function causing hemiplegia or tetraplegia. In 2019, according to The Global Burden of Diseases (GBD) CVA/Stroke is the second leading cause of death and the third leading cause of death and disability combined, globally. Its prevalence vary drastically among South Asian countries. The objective of this study was to determine the effectiveness of Functional Electrical Stimulation (FES) machine on neurologically impaired patients at the Physical Therapy department at IHHN, Karachi, Pakistan. Method: In this retrospective study data was extracted from August 2016 to February 2022 on patients with neurological symptoms i.e. hemiplegia or paraplegia with muscle power of two or less on Manual Muscle Testing (MMT). The parameters for evaluating patients progress pre and post treatment were MMT results and their mobility status. The number of sessions ranged between 40 to 100 sessions of Functional Electrical Stimulation (FES) provided on alternate days according to the patient's need. Result: Data of 51 patients who had completed their treatment were extracted and analyzed. The mean age of patients who completed treatment was 49.62 ± 17.26 years. Out of 51(100%), 30 (58.8%) were male and 21 (41.2%) were female. Pre- and post-treatment median (IQR) showed remarkable improvement in MMT of upper limb muscle (from 1.0 to 4.0) and lower limb muscle (from 2.0 to 4.0). Conclusion: FES cycling is an effective treatment for patients with neurological impairments, as it resulted in improvement in both upper and lower limb muscle strength, along with mobility status.

Microkinetic Modeling: A Tool for Rational Catalyst Design.

The design of heterogeneous catalysts relies on understanding the fundamental surface kinetics that controls catalyst performance, and microkinetic modeling is a tool that can help the researcher in streamlining the process of catalyst design. Microkinetic modeling is used to identify critical reaction intermediates and rate-determining elementary reactions, thereby providing vital information for designing an improved catalyst. In this review, we summarize general procedures for developing microkinetic models using reaction kinetics parameters obtained from experimental data, theoretical correlations, and quantum chemical calculations. We examine the methods required to ensure the thermodynamic consistency of the microkinetic model. We describe procedures required for parameter adjustments to account for the heterogeneity of the catalyst and the inherent errors in parameter estimation. We discuss the analysis of microkinetic models to determine the rate-determining reactions using the degree of rate control and reversibility of each elementary reaction. We introduce incorporation of Brønsted-Evans-Polanyi relations and scaling relations in microkinetic models and the effects of these relations on catalytic performance and formation of volcano curves are discussed. We review the analysis of reaction schemes in terms of the maximum rate of elementary reactions, and we outline a procedure to identify kinetically significant transition states and adsorbed intermediates. We explore the application of generalized rate expressions for the prediction of optimal binding energies of important surface intermediates and to estimate the extent of potential rate improvement. We also explore the application of microkinetic modeling in homogeneous catalysis, electro-catalysis, and transient reaction kinetics. We conclude by highlighting the challenges and opportunities in the application of microkinetic modeling for catalyst design.

Nano biomaterials based strategies for enhanced brain targeting in the treatment of neurodegenerative diseases: an up-to-date perspective.

Neurons and their connecting axons gradually degenerate in neurodegenerative diseases (NDs), leading to dysfunctionality of the neuronal cells and eventually their death. Drug delivery for the treatment of effected nervous system is notoriously complicated because of the presence of natural barriers, i.e., the blood-brain barrier and the blood cerebrospinal fluid barrier. Palliative care is currently the standard care for many diseases. Therefore, treatment programs that target the disease's origin rather than its symptoms are recommended. Nanotechnology-based drug delivery platforms offer an innovative way to circumvent these obstacles and deliver medications directly to the central nervous system, thereby enabling treatment of several common neurological problems, i.e., Alzheimer's, Parkinson's, Huntington's, and amyotrophic lateral sclerosis. Interestingly, the combination of nanomedicine and gene therapy enables targeting of selective mutant genes responsible for the progression of NDs, which may provide a much-needed boost in the struggle against these diseases. Herein, we discussed various central nervous system delivery obstacles, followed by a detailed insight into the recently developed techniques to restore neurological function via the differentiation of neural stem cells. Moreover, a comprehensive background on the role of nanomedicine in controlling neurogenesis via differentiation of neural stem cells is explained. Additionally, numerous phytoconstituents with their neuroprotective properties and molecular targets in the identification and management of NDs are also deliberated. Furthermore, a detailed insight of the ongoing clinical trials and currently marketed products for the treatment of NDs is provided in this manuscript.

Suppression of MAPK/NF-kB and activation of Nrf2 signaling by Ajugarin-I in EAE model of multiple sclerosis.

Multiple sclerosis (MS) is a debilitating neurodegenerative autoimmune disease of the central nervous system (CNS). The current study aimed to investigate the neuroprotective properties of Ajugarin-I (Aju-I) against the experimental autoimmune encephalomyelitis (EAE) model of MS and explored the underlying mechanism involved. The protective potential of Aju-I was first confirmed against glutamate-induced HT22 cells and hydrogen peroxide (H2 O2 )-induced BV2 cells. Next, an EAE model has been established to investigate the mechanisms of MS and identify potential candidates for MS treatment. The behavioral results demonstrated that Aju-I post-immunization treatment markedly reduced the EAE-associated clinical score, motor impairment, and neuropathic pain. Evans blue and fluorescein isothiocyanate extravasation in the brain were markedly reduced by Aju-I. It effectively restored the EAE-associated histopathological changes in the brain and spinal cord. It markedly attenuated EAE-induced inflammation in the CNS by reducing the expression levels of p-38/JNK/NF-κB but increased the expression of IkB-α. It suppressed oxidative stress by increasing the expression of Nrf2 but decreasing the expression of keap-1. It suppressed EAE-induced apoptosis in the CNS by regulating Bax/Bcl-2 and Caspase-3 expression. Taken together, this study suggests that Aju-I treatment exhibits neuroprotective properties in the EAE model of MS via regulation of MAPK/NF-κB, Nrf2/Keap-1, and Bcl2/Bax signaling.

Machine Learning-Enabled NIR Spectroscopy. Part 2: Workflow for Selecting a Subset of Samples from Publicly Accessible Data.

An increasingly large dataset of pharmaceutics disciplines is frequently challenging to comprehend. Since machine learning needs high-quality data sets, the open-source dataset can be a place to start. This work presents a systematic method to choose representative subsamples from the existing research, along with an extensive set of quality measures and a visualization strategy. The preceding article (Muthudoss et al.. in AAPS PharmSciTech 23, 2022) describes a workflow for leveraging near infrared (NIR) spectroscopy to obtain reliable and robust data on pharmaceutical samples. This study describes the systematic and structured procedure for selecting subsamples from the historical data. We offer a wide range of in-depth quality measures, diagnostic tools, and visualization techniques. A real-world, well-researched NIR dataset was employed to demonstrate this approach. This open-source tablet dataset ( http://www.models.life.ku.dk/Tablets ) consists of different doses in milligrams, different shapes, and sizes of dosage forms, slots in tablets, three different manufacturing scales (lab, pilot, production), coating differences (coated vs uncoated), etc. This sample is appropriate; that is, the model was developed on one scale (in this research, the lab scale), and it can be great to investigate how well the top models are transferable when tested on new data like pilot-scale or production (full) scale. A literature review indicated that the PLS regression models outperform artificial neural network-multilayer perceptron (ANN-MLP). This work demonstrates the selection of appropriate hyperparameters and their impact on ANN-MLP model performance. The hyperparameter tuning approaches and performance with available references are discussed for the data under investigation. Model extension from lab-scale to pilot-scale/production scale is demonstrated. HIGHLIGHTS: • We present a comprehensive quality metrics and visualization strategy in selecting subsamples from the existing studies • A comprehensive assessment and workflow are demonstrated using historical real-world near-infrared (NIR) data sets • Selection of appropriate hyperparameters and their impact on artificial neural network-multilayer perceptron (ANN-MLP) model performance • The choice of hyperparameter tuning approaches and performance with available references are discussed for the data under investigation • Model extension from lab-scale to pilot-scale successfully demonstrated.

Design and Evaluation of Continentalic Acid Encapsulated Transfersomal Gel and Profiling of its Anti-arthritis Activity.

Rheumatoid arthritis restricts the physical ability of patients and increases the disease burden; therefore, research has always been focused on evaluating better therapeutic options. The present research aimed to design Continentalic acid (CA)-loaded transfersomes (CA-TF) embedded in Carbopol gel containing permeation enhancer (PE) for the treatment of rheumatoid arthritis. CA-TF was developed via a modified thin film hydration method and incorporated into Carbopol 934 gel containing Eucalyptus oil (EO) as PE. The fabricated CA-TF showed particle size of < 140 nm with spherical geometry, optimal encapsulation efficiency (EE), and sustained drug release pattern. CA-TF-gel along with PE (CA-TF-PE-gel) showed better ex vivo skin penetration than plain CA gel and CA-TF-gel without PE. In vivo evaluation supported improved therapeutic outcomes of CA-TF-PE-gel in terms of behavioral findings, arthritic index, and histological findings whereas biochemical assays and pro-inflammatory cytokines (TNF-α and IL-1ß) showed a significant decrease in their levels. Furthermore, immunohistochemistry assay for Nrf2 and HO-1 signaling pathways showed significant improvement in the expression of the Nrf2, and HO-1 proteins to depict improvement in arthritic condition in the animal model. CA-TF-PE-gel significantly delivered CA to the diseased target site via a topical route with promising therapeutic outcomes displayed in the CFA-induced arthritic model.

Machine Learning-Enabled NIR Spectroscopy. Part 3: Hyperparameter by Design (HyD) Based ANN-MLP Optimization, Model Generalizability, and Model Transferability.

Data variations, library changes, and poorly tuned hyperparameters can cause failures in data-driven modelling. In such scenarios, model drift, a gradual shift in model performance, can lead to inaccurate predictions. Monitoring and mitigating drift are vital to maintain model effectiveness. USFDA and ICH regulate pharmaceutical variation with scientific risk-based approaches. In this study, the hyperparameter optimization for the Artificial Neural Network Multilayer Perceptron (ANN-MLP) was investigated using open-source data. The design of experiments (DoE) approach in combination with target drift prediction and statistical process control (SPC) was employed to achieve this objective. First, pre-screening and optimization DoEs were conducted on lab-scale data, serving as internal validation data, to identify the design space and control space. The regression performance metrics were carefully monitored to ensure the right set of hyperparameters was selected, optimizing the modelling time and storage requirements. Before extending the analysis to external validation data, a drift analysis on the target variable was performed. This aimed to determine if the external data fell within the studied range or required retraining of the model. Although a drift was observed, the external data remained well within the range of the internal validation data. Subsequently, trend analysis and process monitoring for the mean absolute error of the active content were conducted. The combined use of DoE, drift analysis, and SPC enabled trend analysis, ensuring that both current and external validation data met acceptance criteria. Out-of-specification and process control limits were determined, providing valuable insights into the model's performance and overall reliability. This comprehensive approach allowed for robust hyperparameter optimization and effective management of model lifecycle, crucial in achieving accurate and dependable predictions in various real-world applications.

Hepatitis-associated aplastic anaemia: surveillance of frequency,clinico-haematological features, and demographic distribution at a tertiary care hospital in Pakistan.

OBJECTIVE: We aim to document the frequency of HAAA cases among AA patients presenting at a tertiary care hospital, and to determine the most common agents (viral/drug induced) and Clinico-haematological features among HAAA patients at a tertiary care hospital. Methods: This study was a retrospective review, conducted at a tertiary care hospital in Karachi, Pakistan. RESULTS: A total of 21 patients were included in the study. Hepatitis among the HAAA patients was viral in 17 cases, while 4 were idiopathic. All the patients acquired aplastic anaemia within 3-12 months of the Hepatitis episode and most presented with bleeding, bruises and petechiae. CONCLUSIONS: This study indicates and proves that presence and prevalence of this disease in the Pakistani population is quite significant. Unlike the rest of the world, HAAA in Pakistan is not entirely of unknown aetiology, most of the cases can be associated with one of the Hepatitis viruses.

Talectomy for arthrogrypotic foot deformities: A systematic review.

BACKGROUND: Arthrogryposis multiplex congenita (AMC) is one of the most common congenital joint contracture syndromes. Talectomy has been proposed for severe foot deformities in AMC, but the literature is limited. The purpose of this systematic review is to evaluate the indications, outcomes and complications of talectomy in arthrogrypotic foot deformities. METHODS: The articles were found through Embase and Medline. Screening was conducted by two independent investigators with disagreements resolved by a third reviewer. Relevant data regarding demographics, outcomes and complications were collected. RESULTS: Of 232 feet, 71.98 % and 62.22 % had clinical and radiographic improvements respectively. Amongst 122 patients, 92.62 % could ambulate following surgery. Recurrent deformities and revision surgery were seen in 16.81 % and 13.36 % of cases respectively. CONCLUSIONS: Talectomy is a valid surgical option for severe arthrogrypotic foot deformities with favorable post-operative outcomes and low complication rate.

Saliva metabolomic profile of COVID-19 patients associates with disease severity.

INTRODUCTION: Coronavirus disease 2019 (COVID-19) is strongly linked to dysregulation of various molecular, cellular, and physiological processes that change abundance of different biomolecules including metabolites that may be ultimately used as biomarkers for disease progression and severity. It is important at early stage to readily distinguish those patients that are likely to progress to moderate and severe stages. OBJECTIVES: This study aimed to investigate the utility of saliva and plasma metabolomic profiles as a potential parameter for risk stratifying COVID-19 patients. METHOD: LC-MS/MS-based untargeted metabolomics were used to profile the changes in saliva and plasma metabolomic profiles of COVID-19 patients with different severities. RESULTS: Saliva and plasma metabolites were screened in 62 COVID-19 patients and 18 non-infected controls. The COVID-19 group included 16 severe, 15 moderate, 16 mild, and 15 asymptomatic cases. Thirty-six differential metabolites were detected in COVID-19 versus control comparisons. SARS-CoV-2 induced metabolic derangement differed with infection severity. The metabolic changes were identified in saliva and plasma, however, saliva showed higher intensity of metabolic changes. Levels of saliva metabolites such as sphingosine and kynurenine were significantly different between COVID-19 infected and non-infected individuals; while linoleic acid and Alpha-ketoisovaleric acid were specifically increased in severe compared to non-severe patients. As expected, the two prognostic biomarkers of C-reactive protein and D-dimer were negatively correlated with sphingosine and 5-Aminolevulinic acid, and positively correlated with L-Tryptophan and L-Kynurenine. CONCLUSION: Saliva disease-specific and severity-specific metabolite could be employed as potential COVID-19 diagnostic and prognostic biomarkers.

New-onset and relapsed liver diseases following COVID-19 vaccination: a systematic review.

BACKGROUND: Liver diseases post-COVID-19 vaccination is extremely rare but can occur. A growing body of evidence has indicated that portal vein thrombosis, autoimmune hepatitis, raised liver enzymes and liver injuries, etc., may be potential consequence of COVID-19 vaccines. OBJECTIVES: To describe the results of a systematic review for new-onset and relapsed liver disease following COVID-19 vaccination. METHODS: For this systematic review, we searched Proquest, Medline, Embase, PubMed, CINAHL, Wiley online library, Scopus and Nature through the Preferred Reporting Items for Systematic Reviews and Meta Analyses PRISMA guideline for studies on the incidence of new onset or relapsed liver diseases post-COVID-19 vaccination, published from December 1, 2020 to July 31, 2022, with English language restriction. RESULTS: Two hundred seventy-five cases from one hundred and eighteen articles were included in the qualitative synthesis of this systematic review. Autoimmune hepatitis (138 cases) was the most frequent pathology observed post-COVID-19 vaccination, followed by portal vein thrombosis (52 cases), raised liver enzymes (26 cases) and liver injury (21 cases). Other cases include splanchnic vein thrombosis, acute cellular rejection of the liver, jaundice, hepatomegaly, acute hepatic failure and hepatic porphyria. Mortality was reported in any of the included cases for acute hepatic failure (n = 4, 50%), portal vein thrombosis (n = 25, 48.1%), splanchnic vein thrombosis (n = 6, 42.8%), jaundice (n = 1, 12.5%), raised liver enzymes (n = 2, 7.7%), and autoimmune hepatitis (n = 3, 2.2%). Most patients were easily treated without any serious complications, recovered and did not require long-term hepatic therapy. CONCLUSION: Reported evidence of liver diseases post-COIVD-19 vaccination should not discourage vaccination against this worldwide pandemic. The number of reported cases is relatively very small in relation to the hundreds of millions of vaccinations that have occurred and the protective benefits offered by COVID-19 vaccination far outweigh the risks.

Women's Status and its Association With Home Delivery: A Cross-Sectional Study Conducted in Khyber-Pakhtunkhwa, Pakistan.

INTRODUCTION: Home delivery is a predominant driver of maternal and neonatal deaths in developing countries. Despite the efforts of international organizations in Pakistan, home childbirth is common in the remote and rural areas of Khyber Pakhtunkhwa province. We studied women's position within the household (socio-economic dependence, maternal health decision making, and social mobility) and its association with the preference for home delivery. METHODS: We conducted a cross-sectional household survey among 503 ever-married women of reproductive age (15-49 years), who have had childbirth in the last twelve months or were pregnant (more than 6 months) at the time of the interview. A two-stage cluster sampling technique has been used for recruitment. Descriptive and bivariate analyses have been conducted. A binary logistic regression model was calculated to present odds ratios and corresponding 95% confidence intervals for factor associated with home delivery. RESULTS: An inferior status of women, restrictions in mobility and limited power in decision making related to household purchases, maternal health care, and outdoor socializing are contributing factors of home delivery. Furthermore, women having faced intimate partner violence were much more likely to deliver at home (OR = 2.66, 95% CI: 1.83.3.86, p < 0.001). DISCUSSION: We concluded that women are in a position with minimal authority in decision making to access and deliver the baby in any health facility. We recommend that the government should ensure the availability of health facilities in nearby locations to increase institutional deliveries in the study area.

Alleviation of Memory Deficit by Bergenin via the Regulation of Reelin and Nrf-2/NF-κB Pathway in Transgenic Mouse Model.

The present study aims to determine the neuroprotective effect of Bergenin against spatial memory deficit associated with neurodegeneration. Preliminarily, the protective effect of Bergenin was observed against H2O2-induced oxidative stress in HT-22 and PC-12 cells. Further studies were performed in 5xFAD Tg mouse model by administering Bergenin (1, 30 and 60 mg/kg; orally), whereas Bergenin (60 mg/kg) significantly attenuated the memory deficit observed in the Y-maze and Morris water maze (MWM) test. Fourier transform-infrared (FT-IR) spectroscopy displayed restoration of lipids, proteins and their derivatives compared to the 5xFAD Tg mice group. The differential scanning calorimeter (DSC) suggested an absence of amyloid beta (Aß) aggregation in Bergenin-treated mice. The immunohistochemistry (IHC) analysis suggested the neuroprotective effect of Bergenin by increasing Reelin signaling (Reelin/Dab-1) and attenuated Aß (1-42) aggregation in hippocampal regions of mouse brains. Furthermore, IHC and western blot results suggested antioxidant (Keap-1/Nrf-2/HO-1), anti-inflammatory (TLR-4/NF-kB) and anti-apoptotic (Bcl-2/Bax/Caspase-3) effect of Bergenin. Moreover, a decrease in Annexin V/PI-stained hippocampal cells suggested its effect against neurodegeneration. The histopathological changes were reversed significantly by Bergenin. In addition, a remarkable increase in antioxidant level with suppression of pro-inflammatory cytokines, oxidative stress and nitric oxide production were observed in specific regions of the mouse brains.

Butein and Frondoside-A Combination Exhibits Additive Anti-Cancer Effects on Tumor Cell Viability, Colony Growth, and Invasion and Synergism on Endothelial Cell Migration.

Despite the significant advances in targeted- and immuno-therapies, lung and breast cancer are at the top list of cancer incidence and mortality worldwide as of 2020. Combination therapy consisting of a mixture of different drugs taken at once is currently the main approach in cancer management. Natural compounds are extensively investigated for their promising anti-cancer potential. This study explored the anti-cancer potential of butein, a biologically active flavonoid, on two major solid tumors, namely, A549 lung and MDA-MB-231 breast cancer cells alone and in combination with another natural anti-cancer compound, frondoside-A. We demonstrated that butein decreases A549 and MDA-MB-231 cancer cell viability and colony growth in vitro in addition to tumor growth on chick embryo chorioallantoic membrane (CAM) in vivo without inducing any noticeable toxicity. Additionally, non-toxic concentrations of butein significantly reduced the migration and invasion of both cell lines, suggesting its potential anti-metastatic effect. We showed that butein anti-cancer effects are due, at least in part, to a potent inhibition of STAT3 phosphorylation, leading to PARP cleavage and consequently cell death. Moreover, we demonstrated that combining butein with frondoside-A leads to additive effects on inhibiting A549 and MDA-MB-231 cellular viability, induction of caspase 3/7 activity, inhibition of colony growth, and inhibition of cellular migration and invasion. This combination reached a synergistic effect on the inhibition of HUVECs migration in vitro. Collectively, this study provides sufficient rationale to further carry out animal studies to confirm the relevance of these compounds' combination in cancer therapy.