Artificial neural network (ANN) analysis on thermophysical properties of magnetohydrodynamics flow with radiation in an arc-shaped enclosure with a rotating cylinder.

The objective of this research is to examine the thermophysical features of magnetic parameter (Ha) and time step (τ) in a lid-driven cavity using a water-based Al2O3 nanofluid and the efficacy of ANN models in accurately predicting the average heat transfer rate. The Galerkin weighted residual approach is used to solve a set of dimensionless nonlinear governing equations. The Levenberg-Marquardt back propagation technique is used for training ANN using sparse simulated data. The findings of the investigation about the flow and thermal fields are shown. Furthermore, a comparative study and prediction have been conducted on the impact of manipulating factors on the average Nusselt number derived from the numerical heat transfer analysis. The findings of the research indicate that, in the absence of magnetohydrodynamics, a rise in the Hartmann number resulted in a drop in both the fluid velocity profile and magnitude. Conversely, it was observed that the temperature and Nusselt number exhibited an increase under these conditions. The mean temperature of the fluid rises as the Hartmann number drops, reaching a peak value of 0.114 when Ha = 0. The scenario where Ha = 0, representing the lack of magnetohydrodynamics, shows the highest average Nusselt number, whereas the instance with Ha = 45 presents the lowest Nusselt number. The ANN model has a high level of accuracy, as seen by an MSE value of 0.00069 and a MAE value of 0.0175, resulting in a 99% accuracy rate.

Single-cell RNA-seq data analysis reveals functionally relevant biomarkers of early brain development and their regulatory footprints in human embryonic stem cells (hESCs).

The complicated process of neuronal development is initiated early in life, with the genetic mechanisms governing this process yet to be fully elucidated. Single-cell RNA sequencing (scRNA-seq) is a potent instrument for pinpointing biomarkers that exhibit differential expression across various cell types and developmental stages. By employing scRNA-seq on human embryonic stem cells, we aim to identify differentially expressed genes (DEGs) crucial for early-stage neuronal development. Our focus extends beyond simply identifying DEGs. We strive to investigate the functional roles of these genes through enrichment analysis and construct gene regulatory networks to understand their interactions. Ultimately, this comprehensive approach aspires to illuminate the molecular mechanisms and transcriptional dynamics governing early human brain development. By uncovering potential links between these DEGs and intelligence, mental disorders, and neurodevelopmental disorders, we hope to shed light on human neurological health and disease. In this study, we have used scRNA-seq to identify DEGs involved in early-stage neuronal development in hESCs. The scRNA-seq data, collected on days 26 (D26) and 54 (D54), of the in vitro differentiation of hESCs to neurons were analyzed. Our analysis identified 539 DEGs between D26 and D54. Functional enrichment of those DEG biomarkers indicated that the up-regulated DEGs participated in neurogenesis, while the down-regulated DEGs were linked to synapse regulation. The Reactome pathway analysis revealed that down-regulated DEGs were involved in the interactions between proteins located in synapse pathways. We also discovered interactions between DEGs and miRNA, transcriptional factors (TFs) and DEGs, and between TF and miRNA. Our study identified 20 significant transcription factors, shedding light on early brain development genetics. The identified DEGs and gene regulatory networks are valuable resources for future research into human brain development and neurodevelopmental disorders.

Performance evaluation of nanofluid-based photovoltaic thermal (PVT) system with regression analysis.

The recent global energy crisis has shocked Bangladesh's power sectors, and experts recommend using alternative energy sources to conserve natural gas, fossil fuels, and electricity. Numerous investigations on the photovoltaic thermal (PVT) system have been carried out to get the source efficiently. As a result, a parametric evaluation of the PVT system's efficiency in Dhaka, Bangladesh, is investigated numerically using CNT nanofluid as a coolant. The numerical simulation is performed using the Galerkin weighted residual based finite element method. For accurate computations, the meteorological data for Dhaka, Bangladesh, is taken from open sources of Renewables.ninja. The effect of regulating parameters Reynolds number (200 ≤ Re ≤ 1000), solar irradiation (200 W/m2 ≤ G ≤ 1000 W/m2), and the monthly influence on performance such as cell temperature, fluid domain exit temperature, efficiencies, and energy are discussed. In addition, regression analyses of electrical efficiency and thermal efficiency are discussed for the input variables Reynolds number and solar irradiation. After postprocessing, empirical results are compiled and presented as 3D surface graphs, tables, and line diagrams. As the Reynolds number increased, the cell temperature and discharge temperature decreased, resulting in increased efficiency. However, the opposite situation is found for solar irradiation. Month-to-month variation also has a considerable impact on photovoltaic thermal performance. This research will help to improve the efficacy of PVTs in Dhaka, Bangladesh, by identifying useful alternative renewable energy sources.

Rotational effect of a cylinder on hydro-thermal characteristics in a partially heated square enclosure using CNT-water nanofluid.

Rotating cylinder movement in a cavity flow is an exciting field of study in heat transfer. Considerable research has been carried out on rotating cylinders under MHD mixed convection in various types of enclosures. However, considering partially heated square enclosure and magnetic field using CNT-water nanofluid is very limited. This study's goal is to assess the hydrothermal phenomena in a square enclosure with a rotating cylinder. Simulation has been conducted for different rotational speeds (Ω) and dimensionless times (τ) to observe the thermal and fluid flow behaviour. The Galerkin Residual based finite element method has been used to conduct numerical calculations. The results are shown as isotherms, streamlines, and average Nusselt number at the cylinder wall. Moreover, the drag force at the moving wall, and the fluid properties such as the root mean square (rms) of velocity, the temperature, the vorticity functions, and the average fluid temperature are also presented. The heat transfer rate, drag force, rms velocity, and temperature increase with the rise of rotational speed and dimensionless time rise. Maximum vorticity occurs at Ω = 8 and τ = 1. The maximum vorticity function increases 12 times with the increasing rotational speed. Higher rotational speed leads to increased average fluid temperature. The case of Ω = 8, τ = 1 shows the most temperature variance, while Ω = 1, τ = 0.1 has the least. Increasing rotational speed results in higher drag force on the cylinder's surface. At Ω = 4, the drag force is 2.8 times greater than at Ω = 2. Overall, the fluid flow and thermal performance boost up while the rotating speed of the cylinder is higher.

Assessing the hypolipidemic and gastro-liver protective activity of herbal combination with emphasis on PPI amid selected multiple antihypertensive drug combination in experimental animal models.

OBJECTIVE: Peptic ulcer (PU) and hypertension are chronic diseases affecting up to 10% and 30% of the adult population worldwide. Most of these patients will require treatment with a combination of antihypertensive medicines, which have adverse effects on the body's different organs. This study specifically focused on antihypertensive multi-drug induced PU disease and disturbance of liver function. MATERIALS AND METHODS: During a 14-day oral administration of antihypertensive drugs, Cilnidipine (1 mg/kg), Rosuvastatin (1 mg/kg), Bisoprolol (0.52 mg/kg), and Clopidogrel (7.81 mg/kg) were observed for their effects on the stomach lining and liver function in Wister albino rats. This study aimed to assess the potential of an herbal combination of (BO) + (BA) + (ZO) 0.26 mg/kg body weight (b.w.) Powder and water mixture on the ulcer, lipid profile, and liver function for 14 days in the treatment of the indomethacin-induced gastric ulcers in rats at doses of 30 mg/kg b.w. for three days. Esomeprazole (20 mg/kg b.w.) is used as a standard reference to evaluate antiulcer activity in rat models. The experiment suggests that the gastroprotective effect of the herbal combination can be attributed to its reducing effect on the peptic and the Serum Glutamic Pyruvic Transaminase (SGPT) levels and within the normal range of 34.67 ± 0.88 IU/L. RESULTS: The results for Total Cholesterol (TC), Triglyceride (TG), High-density lipoprotein (HDL) and Low-density lipoprotein (LDL) of the herbal combination were 52 ± 9.81495 (mg/dl), 70 ± 12.12435 (mg/dl), 23.33 ± 6.06446 (mg/dl), 14.5 ± 1.32790 (mg/dl), respectively, where the standard group (atorvastatin) 5 mg/kg TC, TG, HDL and LDL were 69.77 ± 9.92 (mg/dl), 47.7 ± 10.35 (mg/dl), 33.43 ± 5.70 (mg/dl), 26.8 ± 3.70 (mg/dl), and control group total cholesterol, triglyceride, HDL and LDL were 68.67 ± 2.20 (mg/dl), 124.07 ± 2.94 (mg/dl), 49.14 ± 1.05 (mg/dl), 54.11 ± 1.15 (mg/dl). CONCLUSIONS: CThis investigation reported that antihypertensive drugs did not produce gastrointestinal (GI) toxicity, and the morphological structure of the organ was not changed. So, it could be concluded that the herbal combination used in this experiment has a promising role in controlling lipid profile, liver function, and antiulcer effects. Moreover, multiple drug therapy for hypertension does not cause any harm to the stomach. Further investigations might be carried out on a larger scale to make these statements more valid.

BOO-ST and CBCEC: two novel hybrid machine learning methods aim to reduce the mortality of heart failure patients.

Heart failure (HF) is a leading cause of mortality worldwide. Machine learning (ML) approaches have shown potential as an early detection tool for improving patient outcomes. Enhancing the effectiveness and clinical applicability of the ML model necessitates training an efficient classifier with a diverse set of high-quality datasets. Hence, we proposed two novel hybrid ML methods ((a) consisting of Boosting, SMOTE, and Tomek links (BOO-ST); (b) combining the best-performing conventional classifier with ensemble classifiers (CBCEC)) to serve as an efficient early warning system for HF mortality. The BOO-ST was introduced to tackle the challenge of class imbalance, while CBCEC was responsible for training the processed and selected features derived from the Feature Importance (FI) and Information Gain (IG) feature selection techniques. We also conducted an explicit and intuitive comprehension to explore the impact of potential characteristics correlating with the fatality cases of HF. The experimental results demonstrated the proposed classifier CBCEC showcases a significant accuracy of 93.67% in terms of providing the early forecasting of HF mortality. Therefore, we can reveal that our proposed aspects (BOO-ST and CBCEC) can be able to play a crucial role in preventing the death rate of HF and reducing stress in the healthcare sector.

Identification of genetic biomarkers, drug targets and agents for respiratory diseases utilising integrated bioinformatics approaches.

Respiratory diseases (RD) are significant public health burdens and malignant diseases worldwide. However, the RD-related biological information and interconnection still need to be better understood. Thus, this study aims to detect common differential genes and potential hub genes (HubGs), emphasizing their actions, signaling pathways, regulatory biomarkers for diagnosing RD and candidate drugs for treating RD. In this paper we used integrated bioinformatics approaches (such as, gene ontology (GO) and KEGG pathway enrichment analysis, molecular docking, molecular dynamic simulation and network-based molecular interaction analysis). We discovered 73 common DEGs (CDEGs) and ten HubGs (ATAD2B, PPP1CB, FOXO1, AKT3, BCR, PDE4D, ITGB1, PCBP2, CD44 and SMARCA2). Several significant functions and signaling pathways were strongly related to RD. We recognized six transcription factor (TF) proteins (FOXC1, GATA2, FOXL1, YY1, POU2F2 and HINFP) and five microRNAs (hsa-mir-218-5p, hsa-mir-335-5p, hsa-mir-16-5p, hsa-mir-106b-5p and hsa-mir-15b-5p) as the important transcription and post-transcription regulators of RD. Ten HubGs and six major TF proteins were considered drug-specific receptors. Their binding energy analysis study was carried out with the 63 drug agents detected from network analysis. Finally, the five complexes (the PDE4D-benzo[a]pyrene, SMARCA2-benzo[a]pyrene, HINFP-benzo[a]pyrene, CD44-ketotifen and ATAD2B-ponatinib) were selected for RD based on their strong binding affinity scores and stable performance as the most probable repurposable protein-drug complexes. We believe our findings will give readers, wet-lab scientists, and pharmaceuticals a thorough grasp of the biology behind RD.

Community Based Rehabilitation for Accessibility of Disable Person in a Low and Middle-income Country like Bangladesh.

Not Available.

Estimation of 10-Year Fracture Risk with and without Bone Mineral Density in Patients with Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is the most common inflammatory arthritis affecting 0.5-1.0% of the general population worldwide and although RA is properly considered a disease of the joints, it can cause a variety of extra-articular manifestations. This study was performed to find out any discrepancy in fracture risk estimates with and without bone mineral density (BMD) in rheumatoid arthritis (RA) patients. This observational cross-sectional study was carried out in the Department of Rheumatology, Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh from July 2013 to July 2015. Total 65 consecutive patients with RA fulfilling ACR/EULAR criteria aged 40-90 year were recruited. Ten year fracture risk of these patients was evaluated by the FRAX score with and without BMD and differences were observed. FRAX score without BMD revealed that major fracture risk was low in 58(89.2%) patients, moderate in 7(10.8%) patients but re-estimation with BMD revealed that 55(84.6%) patients remained in low risk group, 8(12.3%) patients in moderate risk group and 2(3.1%) patients went to the high risk group. In case of hip fracture risk without BMD, risk was low in 58(89.2%) patients, high in 7(10.8%) patients; but with BMD, 50(76.9%) patients remained in low risk group but risk of 15(23.1%) patients became high. Almost all the high risk patients (93.3%) were ≥55 years of age. Increasing age, female sex, disease duration and use of steroid were positively correlated with increased FRAX score where as high BMI and high BMD were associated with low FRAX score. But in multivariate analysis it was found that only relation with age was at statistically significant level. Significant numbers of patients with rheumatoid arthritis have high risk of fracture especially hip fracture. The mean of FRAX score increased in both major & hip osteoporotic fracture risk after adding BMD. More than half of the patients above fifty five years or more had high risk of fracture. So, BMD should be done in patients aged more than fifty five.

Association of Chest Pain with Rate Pressure Product and ST-segment Changes after Sub Arachnoid Block in Caesarean Section.

When healthy women undergo caesarean section (CS) under sub arachnoid anaesthesia, transient electrocardiographic changes, such as ST-segment depression and T-wave abnormalities, are observed. During an elective caesarean section under sub arachnoid anaesthesia, about one-third of healthy parturient experience chest pain and ECG changes suggestive of myocardial ischemia. To assess the ST-segment and Rate Pressure Product changes with chest pain in patients with elective caesarean section under subarachnoid block. The Department of Anesthesia, Analgesia and Intensive Care Medicine at Bangabandhu Sheikh Mujib Medical University (BSMMU), Bangladesh was the site of this prospective observational study. The study included 86 healthy women between the ages of 20 and 35 who needed an elective caesarean section under a single shot sub arachnoid block and who visited the Department of Anesthesia, Analgesia, and Intensive Care Medicine at BSMMU in Shahbagh, Dhaka from January 2019 to June 2019. In comparison to the no chest pain group, ST-segment changes among the chest pain group at delivery, 5 minute, 10 minute after delivery and at the end of the surgery were highly significant (p=0.001). Comparatively, Rate Pressure Product changes were found to be significantly higher in the group with chest pain than in the group without chest pain (p=0.001). It is concluded that there is a substantial association of chest pain with rate pressure product and ST-segment changes after subarachroid block in caesarean section.

Digital Gangrene is a Rare Presentation of Takayasu's Arteritis.

Takayasu's arteritis is a chronic large vessel vasculitis that mainly affects the aorta and its major branches such as brachiocephalic, carotid, subclavian, vertebral, renal, coronary and pulmonary arteries. It most commonly occurs in female at child bearing age and female to male ratio is 8:2. Initial presentations of Takayasu's arteritis may be nonspecific like fever, malaise, weakness, fatigue, arthralgia, myalgia and weight loss but in advanced stage there may be features of vascular inflammation like segmental stenosis, occlusion, dilatation and/or aneurysm. It is a sub acute process over months to years and usually with good collateral formation. So, critical limb ischemia due to acute onset of vascular stenosis is very rare. Here we are reporting a case of a 50-year- old male patient who presented with digital gangrene due to critical limb ischemia. Though the age of onset was at 50 years and the patient lacks clinical features like constitutional symptoms, bruit, claudication, asymmetrical blood pressure, the patient was diagnosed as a case of Takayasus's arteritis. The patient dramatically improved with oral glucocorticoid treatment. Although rare, takayasu's arteritis can presents only with digital gangrene without having other clinical features. The physicians should be aware of this unusual but limb threatening presentation and more studies are needed to find out the exact mechanism of this presentation.

Enhancing radiative efficiency in MHD micropumps using plasma-infused hybrid bioconvective nanofluids for advanced radiative oncology at tertiary level.

This research paper investigates the optimization of radiation performance of a plasma-based bioconvective nanofluid integrated Magneto-hydrodynamic (MHD) micropump for radiative oncology. It addresses a literature gap by analysing the radiative impact of blood-based hybrid nanofluids in MHD micropumps. Three blood-based bio-convective radiating hybrid nanofluids-blood-Pt, blood-Au and blood-MWCNT are studied to understand their radiation behaviour in MHD pump while being employed as transportation medium. The investigation employs two non-dimensional parameters, namely Rd (Radiation number) and Ha (Hartmann number), to examine the fluid dynamics, magnetic characteristics, and electrical properties of the MHD micropump. The temperature gradient, velocity distribution, and pressure drop along the flow channel are examined within the specified range of Rd and Ha. Magnetic flux density (MFD) and electric flux intensity (EFI) are evaluated to understand nanoparticle behaviour during drug delivery and blood transportation. Findings highlight that MWCNT and Pt are the most efficient bioconvective nanoparticles for plasma transportation under high radiative conditions. MWCNT-based blood flow exhibits desirable characteristics, including sufficient intake pressure of 4.5 kPa and minimal relative pressure drop of 34%. Coherence between radiation flux and electromagnetic flux reduces pumping power and ensures uniform heat dissipation for improved drug delivery. Au nanoparticles provide moderate magnetic flux density with least fluctuation within the range of Ha and Rd number (2.57 T to 4.39 T), even in highly radiative environments (such as-Rd = 4, Rd = 5), making them suitable for applications like embedded chemotherapy or cell treatment. Au nanoparticles maintain moderate electrical flux intensity with a minimal drop of 16nA, particularly at higher radiative environments influenced by the Radiation number (Rd = 4 to Rd = 5) while Ha values from Ha = 2 to Ha = 4. Conclusively, it has been identified that MWCNT and Au are superior nanofluids for advanced radiative oncological treatments. These nanofluids have the potential to enhance plasma transportation, thermal regulation, and aetilogical disease management. The present study provides significant findings on enhancing the radiation performance in MHD micropumps through utilization of blood-based hybrid nanofluids, thereby offering potential advantages to the domain of biomedical engineering.

Dexmedetomidine as an Adjuvant to Bupivacaine in Caudal Analgesia in Children Undergoing Infra-Umbilical Surgery.

When performing infra-umbilical procedures, caudal epidural analgesia with bupivacaine is frequently used to provide both intra- and post-operative analgesia. Dexmedetomidine, an alpha 2 agonistsare extensively used in neuraxial blocks and peripheral nerve blocks to prolong the action of bupivacaine. To find out the effects of dexmedetomidine as an adjuvant to bupivacaine for caudal analgesia in children undergoing infra-umbilical surgery. This was a randomized, controlled double-blinded prospective observational study and was performed from July 2019 to December 2019. A total of 60 (Sixty) patients with different infra-umbilical surgical problems underwent different procedure under caudal anaesthesia in different operation theatre in Bangabandhu Sheikh Mujib Medical University, Dhaka were enrolled in this study. Elaborate personal history, meticulous clinical examinations and relevant laboratory investigations was done. Post-operative adverse effects also were monitored. All information from history of illness, clinical, laboratory findings, duration of analgesia and post-operative adverse effects were recorded in a preformed data sheet (Appendix-I) and statistical analysis was done by SPSS 22.0. Mean age of the children in Group A (dexmedetomidine + bupivacaine) was 5.50±2.61 years and in Group B (bupivacaine) was 5.66±2.75. Mean weight of the children in Group A was 19.22±8.58 kg and in Group B was 19.70±8.94 kg in this study. Mean duration of anaesthesia was 27.5±6.5 minute in Group A and 28.5±5.5 minute in Group B. The mean duration of analgesia was 4.32±0.54 hours for Group A and 2.12±0.32 hours in Group B. In Group A, 46.7% patients required 1 and 3.3% required 2 rescue analgesic but in Group B, 43.3% patients required single rescue analgesic and 33.3% required two rescue analgesics (p<0.05). In Group A, 6.7% patients had nausea/ vomiting and in Group B, 16.7% patients had nausea/ vomiting (p>0.05). It can be concluded that dexmedetomidine with bupivacaine for caudal analgesia in infra-umbilical surgery significantly prolongs the duration of postoperative analgesia when compared to bupivacaine alone without any side-effects.

Predicting Difficult Intubation by using Modified Mallampati (MMT) with or without Thyromental Height Test (TMHT).

Failed Tracheal Intubation with Subsequent inability to maintain an open airway and adequate oxygenation is the most frequent cause of brain damage or death during anesthesia. Recognizing before anesthesia the potential for difficult intubation allows time for optimal preparation. Proper Selection of equipment and techniques is needed to avoid unwanted situation. To find out difficulties associated with endotracheal intubation using Modified Mallampati Test (MMT) combined with Thyromental Height Test (TMHT) and MMT without TMHT. This prospective observational study was conducted at the Department of Anesthesia in Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka, Bangladesh from April 2018 to September 2018. Two hundred two patients with different surgical procedures under general anaesthesia in different operation theaters of BSMMU, Dhaka were selected as study population. After taking written consents from each patient or his/her attendant elaborate history of illness, meticulous clinical examinations were performed and relevant laboratory investigations were done. All information was recorded in a preformed data sheet and statistical analysis was done by SPSS-22.0. Mean age ±SD of the study subjects was 42.49±14.29 years in MMT with TMHT group and 43.40±15.39 years in MMT without TMHT group. Females were enrolled more than males in both the groups. BMI was 28.75±3.59kg/m² in MMT with TMHT group and 29.44±8.64kg/m² in MMT without TMHT group. There were no significant differences in age, gender and BMI between the groups. Sensitivity, specificity, PPV, NPV and accuracy were 100.0%, 96.0%, 96.2%, 100.0% and 98.0% respectively of MMT with TMHT in predicting intubation difficulty. Sensitivity, specificity, PPV, NPV and accuracy were 100.0%, 96.0%, 96.2%, 100.0% and 98.0% respectively of MMT only in predicting intubation difficulty. MMT combined with TMHT is a better predictor of intubation difficulty than MMT alone.

Influence of thermal conductivity on transient mixed convection in a vented cavity with a hollow cylinder and filled with CNT-water nanofluid.

This study is aimed to perform a numerical time-dependent investigation thermal conductivity effect of the annular cylinder within a vented cavity using CNT based-water nanofluid. For demonstrating the effect of thermal conductivity, four distinct hollow cylinder materials such as Ks = 0.5(Plastic tiles), Ks = 0.84(Clay tiles), Ks = 1.1(Concrete tiles), and Ks = 2(Slate tiles) are introduced together with a suitable variation of dimensionless time (0 ≤ τ ≤ 1). The governing equations of the model with associated boundary conditions is solved using finite element based Galerkin's weighted residual method. Different contour plots for thermal and flow field transformation and mean Nusselt number, mean fluid temperature, bulk convective field temperature, temperature gradient, pressure gradient, vortices, and fluid velocity magnitude are presented for qualitative and quantitative thermal performance analysis. With the decrease of solid thermal conductivity, 27.3% thermal transport enhancement is noted from the heated surface of the cylinder. However, a 16.3% increase in the bulk fluid temperature has been recorded with the increase in cylinder conductivity. The numerical outcomes from this investigation propose a better thermo-fluid efficiency compared to the existing methodology which can be suggestive to engineers and researchers for designing heat exchangers, heat pipes, and other thermal systems.

dRNASb: a systems biology approach to decipher dynamics of host-pathogen interactions using temporal dual RNA-seq data.

Infection triggers a dynamic cascade of reciprocal events between host and pathogen wherein the host activates complex mechanisms to recognise and kill pathogens while the pathogen often adjusts its virulence and fitness to avoid eradication by the host. The interaction between the pathogen and the host results in large-scale changes in gene expression in both organisms. Dual RNA-seq, the simultaneous detection of host and pathogen transcripts, has become a leading approach to unravelling complex molecular interactions between the host and the pathogen and is particularly informative for intracellular organisms. The amount of in vitro and in vivo dual RNA-seq data is rapidly growing, which demands computational pipelines to effectively analyse such data. In particular, holistic, systems-level, and temporal analyses of dual RNA-seq data are essential to enable further insights into the host-pathogen transcriptional dynamics and potential interactions. Here, we developed an integrative network-driven bioinformatics pipeline, dRNASb, a systems biology-based computational pipeline to analyse temporal transcriptional clusters, incorporate molecular interaction networks (e.g. protein-protein interactions), identify topologically and functionally key transcripts in host and pathogen, and associate host and pathogen temporal transcriptome to decipher potential between-species interactions. The pipeline is applicable to various dual RNA-seq data from different species and experimental conditions. As a case study, we applied dRNASb to analyse temporal dual RNA-seq data of Salmonella-infected human cells, which enabled us to uncover genes contributing to the infection process and their potential functions and to identify putative associations between host and pathogen genes during infection. Overall, dRNASb has the potential to identify key genes involved in bacterial growth or host defence mechanisms for future uses as therapeutic targets.

Immunity after Primary Hepatitis B Vaccination in Children 7 Years or More Attending A Tertiary Care Hospital.

Hepatitis B virus is a serious public health problem. Effective hepatitis B vaccination gives protection in about 85-90% cases. Most follow-up studies in different countries showed a similar pattern of antibody decline with increasing age. Many authors observed a declined level of HBs-antibody over a period of 3-6 years. This study was aimed at to observe immune status in children 7 years or more after primary hepatitis B vaccination. This cross sectional descriptive study was conducted at the department of Pediatric Gastroenterology and Nutrition, BSMMU, Dhaka, Bangladesh from April 2015 to March 2016. For this study children of both sexes aged between 7 to 18 years, who had history of 2 or more doses of hepatitis B vaccine 7 or more years back were included in the study. All the serum samples were tested for anti HBs by chemiluminescence's technique. Total 120 children were studied among them male was 59.2% and male female ratio was 1.4:1 with a mean age of 8.6±1.7 years. Good immune response (66.7%) was observed against hepatitis B. Significantly higher geometric mean titer of anti HBs was found in the age group of 7-8 years (p=0.02). Waning of immunity including non seroprotectivity was significantly associated with increasing age (p=0.015). Majority (96.7%) of children received EPI vaccination than commercially available vaccine. Children with weight for age percentile (WAP), height for age percentile (HAP) and BMI for age lies below 5th percentile had comparatively lower non seroprotection rate than normal children, but this was not statistically significant. History of dental or surgical procedure, blood transfusion and family history of contact with known case of hepatitis B infection did not have any significant inference on anti- HBs response. The study detected a good immune response against hepatitis B. About 66.7% of children were seroprotective 7 years or more after primary hepatitis B vaccination. Waning of immunity including non seroprotectivity was significantly associated with increasing age. Further studies with larger sample size are needed about booster dose to come to a final conclusion.

Psychological Assessment of Health-Care Workers Working during COVID-19 Pandemic Condition in Bangladesh.

The study was aimed to assess the psychological aspects and relevant factors of the health-care workers (HCWs) working in COVID 19 pandemic condition in Bangladesh. This online cross-sectional survey was conducted from different tertiary, secondary and primary hospitals in Bangladesh. Eligible 638 HCWs who were directly involved in the caring of confirmed or suspected COVID-19 patients were recruited in this study. The mental health was assessed by the Patient Health Questionnare-9 (PHQ-9), Generalized Anxiety Disorder-7 (GAD-7) and Athens Insomnia Scale (AIS). High frequency of depression 536(84.0%), anxiety 386(60.5%) and insomnia 302(47.3%) was found among the HCWs, which were significantly higher in physicians (p<0.001) than nurses. Moderate to severe depression was significantly higher in female, whereas minimal to mild depression was significant in male HCWs (p=0.014). Symptoms of depression (p<0.001), anxiety (p<0.001) and insomnia (p=0.004) were significantly higher among the HCWs of primary and secondary compared to the tertiary level. The HCWs developed psychological trauma due to family health (45.3%) and contagious disease property (66.6%). After adjusting confounders, multivariable logistic regression analysis showed that physicians and HCWs of secondary hospital had significant symptoms of severe depression (OR=2.95, 95% CI=0.50-17.24; p<0.001), anxiety (OR=2.64, 95% CI=0.80-8.72; p<0.001) and insomnia (OR=2.67, 95% CI=1.23-5.84; p=0.018); whereas female HCWs had more risk of developing symptoms of severe insomnia (OR= 1.84; 95% CI=1.23-2.75; p=0.003). High rate of depression, anxiety and insomnia was found among HCWs working in the COVID-19 pandemic condition in this survey.

A classification of MRI brain tumor based on two stage feature level ensemble of deep CNN models.

The brain tumor is one of the deadliest cancerous diseases and its severity has turned it to the leading cause of cancer related mortality. The treatment procedure of the brain tumor depends on the type, location and size of the tumor. Relying solely on human inspection for precise categorization can lead to inevitably dangerous situation. This manual diagnosis process can be improved and accelerated through an automated Computer Aided Diagnosis (CADx) system. In this article, a novel approach using two-stage feature ensemble of deep Convolutional Neural Networks (CNN) is proposed for precise and automatic classification of brain tumors. Three unique Magnetic Resonance Imaging (MRI) datasets and a dataset merging all the unique datasets are considered. The datasets contain three types of brain tumor (meningioma, glioma, pituitary) and normal brain images. From five pre-trained models and a proposed CNN model, the best models are chosen and concatenated in two stages for feature extraction. The best classifier is also chosen among five different classifiers based on accuracy. From the extracted features, most substantial features are selected using Principal Component Analysis (PCA) and fed into the classifier. The robustness of the proposed two stage ensemble model is analyzed using several performance metrics and three different experiments. Through the prominent performance, the proposed model is able to outperform other existing models attaining an average accuracy of 99.13% by optimization of the developed algorithms. Here, the individual accuracy for Dataset 1, Dataset 2, Dataset 3, and Merged Dataset is 99.67%, 98.16%, 99.76%, and 98.96% respectively. Finally a User Interface (UI) is created using the proposed model for real time validation.

Network based systems biology approach to identify diseasome and comorbidity associations of Systemic Sclerosis with cancers.

Systemic Sclerosis (SSc) is an autoimmune disease associated with changes in the skin's structure in which the immune system attacks the body. A recent meta-analysis has reported a high incidence of cancer prognosis including lung cancer (LC), leukemia (LK), and lymphoma (LP) in patients with SSc as comorbidity but its underlying mechanistic details are yet to be revealed. To address this research gap, bioinformatics methodologies were developed to explore the comorbidity interactions between a pair of diseases. Firstly, appropriate gene expression datasets from different repositories on SSc and its comorbidities were collected. Then the interconnection between SSc and its cancer comorbidities was identified by applying the developed pipelines. The pipeline was designed as a generic workflow to demonstrate a premise comorbid condition that integrate regarding gene expression data, tissue/organ meta-data, Gene Ontology (GO), Molecular pathways, and other online resources, and analyze them with Gene Set Enrichment Analysis (GSEA), Pathway enrichment and Semantic Similarity (SS). The pipeline was implemented in R and can be accessed through our Github repository: https://github.com/hiddenntreasure/comorbidity. Our result suggests that SSc and its cancer comorbidities share differentially expressed genes, functional terms (gene ontology), and pathways. The findings have led to a better understanding of disease pathways and our developed methodologies may be applied to any set of diseases for finding any association between them. This research may be used by physicians, researchers, biologists, and others.