Applications of different types of heat pipes in solar desalinations: A comprehensive review

Desalination processes are energy consuming and it is required to apply clean energy sources for supplying them to prevent environmental issues. Solar energy is one of the attractive clean energy sources for desalination. In solar thermal desalination systems, different thermal components could be used for heat transfer purpose. In solar desalination technologies, heat pipe as efficient heat transfer mediums could be employed to transfer absorbed and/or stored thermal energy. The objective of this study is to review applications of heat pipes in solar energy desalination systems. Regarding the performance dependency of these thermal systems on the variety of factors, scholars have investigated these systems by consideration of the effect of different influential factors. Based on the results, it is concluded that use of heat pipes could lead to proper performance of solar desalination systems. Aside from direct transfer of absorbed heat from solar radiation, heat pipes can be applied in the storage units of solar desalination systems to keep the systems active in night-hours or low solar irradiation conditions. The overall performance of the solar desalinations systems with heat pipes can be influenced by some factors such as filling ratio and operating fluid that affect the performance of heat pipes.

Enhanced As-COF nanochannels as a high-capacity anode for K and Ca-ion batteries

Covalent organic frameworks can be used for next-generation rechargeable metal-ion batteries due to their controllable spatial and chemical architectures and plentiful elemental reserves. In this study, the arsenic-based covalent organic framework (As-COF) is designed by employing the geometrical symmetry of a semiconducting phosphazene-based covalent organic framework that uses p-phenylenediamine as a linker and hexachorocyclotriphosphazene as an As-containing monomer in a C3-like spatial configuration. The As-COF with engineered nanochannels demonstrates exceptional anodic behavior for potassium (K) and calcium (Ca) ion batteries. It exhibits a high storage capacity of about 914(2039) mA h g-1, low diffusion barriers of 0.12(0.26) eV, low open circuit voltage of 0.23(0.18) V, and a minimal volume expansion of 2.41(2.32)% for K (Ca) ions. These attributes collectively suggest that As-COF could significantly advance high-capacity rechargeable batteries.

ChestCovidNet: An Effective DL-based Approach for COVID-19, Lung Opacity, and Pneumonia Detection Using Chest Radiographs Images

Currently used lung disease screening tools are expensive in terms of money and time. Therefore, chest radiograph images (CRIs) are employed for prompt and accurate COVID-19 identification. Recently, many researchers have applied Deep learning (DL) based models to detect COVID-19 automatically. However, their model could have been more computationally expensive and less robust, i.e., its performance degrades when evaluated on other datasets. This study proposes a trustworthy, robust, and lightweight network (ChestCovidNet) that can detect COVID-19 by examining various CRIs datasets. The ChestCovidNet model has only 11 learned layers, eight convolutional (Conv) layers, and three fully connected (FC) layers. The framework employs both the Conv and group Conv layers, Leaky Relu activation function, shufflenet unit, Conv kernels of 3×3 and 1×1 to extract features at different scales, and two normalization procedures that are cross-channel normalization and batch normalization. We used 9013 CRIs for training whereas 3863 CRIs for testing the proposed ChestCovidNet approach. Furthermore, we compared the classification results of the proposed framework with hybrid methods in which we employed DL frameworks for feature extraction and support vector machines (SVM) for classification. The study's findings demonstrated that the embedded low-power ChestCovidNet model worked well and achieved a classification accuracy of 98.12% and recall, F1-score, and precision of 95.75%.

Size at sexual maturity estimation for 36 species captured by bottom and mid-water trawls from the marine habitat of Balochistan and Sindh in the Arabian Sea, Pakistan, using maximum length (Lmax) and logistic (L50) models

Abstract The aim of this study was to estimate the size at first sexual maturity (Lm) for 36 species belonging to 24 families from the marine habitat of Balochistan and Sindh in Arabian Sea, Pakistan through maximum length based an empirical and logistic model using commercial catch during June 2020 to May 2021. Individual total length (TL) was noted up to 0.1 cm using measuring broad. The Lm was calculated using two formulae; (i) log (Lm) = - 0.1246 + 0.9924 * log (Lmax) for Elasmobranchs and (ii) log (Lm) = -0.1189 + 0.9157* log (Lmax) for ray-finned fishes. The minimum Lm was recorded as 10.27 cm TL for Caranx malabaricus and 108.38 cm TL for Isurus oxyrinchus, respectively. Around Lm with 58.33% species were ranges from 19.00 cm to 25.00 cm TL. This study was estimated 16 newly Lm which is globally absent and rest 20 Lm are absent in the Arabian Sea (Pakistan coastal habitats). Therefore, the results will be helpful for the sustainable management and conservation of these marine fishes through the establishment of mesh size of trawl nets based on the size at sexual maturity (Lm).

Oral health behind the bars: oral health seeking behavior among jail prisoners at central jail of Peshawar, Pakistan: a cross-sectional study

BACKGROUND

The oral health care-seeking behavior among prison inmates is an overlooked area, often leading to deteriorating general health due to the prisoners' limited awareness of oral hygiene practices. It is crucial to address this issue and understand the factors associated with oral healthcare-seeking behavior in prisons.

OBJECTIVE

To assess the oral healthcare-seeking behavior of prison inmates at Central Prisoner Jail, Peshawar Pakistan and to look the factors associated with their dental care utilization.

MATERIAL AND METHODS

This cross-sectional study was conducted at Central Prisoner Jail, Peshawar Khyber Pakhtunkhwa, Pakistan from November 2021 to April 2022. A consecutive sampling technique was used to collect data from both convicted and under-trial prisoners by using a pre-tested WHO Basic Oral Health Survey 2013 tool. Our outcome variable was "Visit to a dentist in the last 12 months (Never/Once or more than one visit). Chi-square test was used to determine univariate association with other explanatory variables while multivariable logistic regression was performed to adjust for potential confounders.

RESULT

A total of 225 participants were recruited to the study with a mean (SD) age of 32.9(11.4). More than two-thirds of 200(88.9%) of the participants were males. One-third of the sample never visited the dentist75(33.3). Participants who completed college/university education and never visited the dentist in the last 12 months constituted a smaller proportion (17.6%) compared to those who visited the dentist once or more than once n = 28(82.4%, p-value = 0.003). Individuals who were using toothbrushes were most frequently visiting the dentist n = 130(72.6%=p value = 0.001) as compared to never visitors. Multivariate logistic regression analysis revealed that Participants who experienced teeth pain or discomfort had 0.42 times lower odds of visiting the dentist compared to those who did not experience any pain or discomfort [AOR 0.42 (95% CI 0.17-0.80), p = 0.04]. Similarly, Participants who do not use any denture have 4.06 times higher odds[AOR 4.06(95% CI 1.76-9.36), p = 0.001] of visiting the dentist compared to those who use a denture.

CONCLUSION

Our result demonstrates that those prisoners who were experiencing tooth pain or discomfort and not using dentures were the strong predictors with lower dental visit frequency to seek oral health care.

Healthcare workers safety in the COVID-19 era: the impact of pre-pandemic personal protective equipment (PPE) training in Pakistan

BACKGROUND

The COVID-19 pandemic has revealed vulnerabilities in healthcare systems worldwide, emphasizing the importance of healthcare worker safety through adequate utilization of personal protective equipment (PPE). This study aims to assess the impact of pre-pandemic PPE training on the practices and other associated factors among frontline healthcare workers during the COVID-19 pandemic in Pakistan and provide insights into the implications of such training programs for future initiatives.

METHODS

A cross-sectional study from May 9th to June 5th, 2020 was conducted among the frontline healthcare workers against COVID-19 in Pakistan, utilizing an online structured questionnaire shared via WhatsApp and Facebook by using purposive sampling. Statistical analyses, including chi-square tests for proportion and logistic regression for the association while multi-logistic regression for potential confounders, were performed using SPSS version 22.

RESULTS

A total of 453 healthcare staff participated, with 68.9% (n = 312) reporting no prior PPE training and 31.1% (n = 141) having received training. Significant associations were found between prior training and healthcare group distribution (p = 0.006), with doctors exhibiting the highest proportion of training 82 (37.61%), followed by nurses 50 (27.32%) and paramedics 9 (17.31%). Those who didn't receive any prior training in PPEs showed a higher perceived professional risk of 216 (69.23%) compared to those who received prior PPE training 96 (30.77%, p-value 0.005). Similarly, a higher frequency 137 (63.72%) of Perceived Personal risk was observed in those who didn't receive training, labeled as "high risk" compared to those who were trained 78 (36.28%, P value 0.02). Multi-logistic regression analysis identified paramedics as 0.26 times less likely to have received prior PPE training (Adjusted OR 0.26, 95% CI 0.10-0.65, p = 0.01) compared to medical doctors. Healthcare workers in tertiary care hospitals were 0.46 times less likely to undergo PPE training (Adjusted OR 0.46, 95% CI 0.25-0.87,p = 0.01) compared to those working at COVID-19 facilities/hospitals/quarantine centers. Likewise, individuals who doffed disposable gowns [Adjusted OR 3.86, (95% CI, 1.23-12.08, p = 0.02] were 3.86 times more interested in getting prior training in PPE compared to those who don't have skills to wear them.

CONCLUSION

Our findings highlight that healthcare levels, type of healthcare, and doffing skills are important predictors of whether healthcare workers have taken prior training in PPE. These findings imply developing effective training programs for healthcare workers to ensure safety while providing care during pandemics like COVID-19.

Assessment of renal function and prevalence of acute kidney injury following coronary artery bypass graft surgery and associated risk factors: A retrospective cohort study at a tertiary care hospital in Islamabad, Pakistan

Acute kidney injury (AKI) is a sudden decline in renal function after cardiac surgery. It is characterized by a significant reduction in glomerular filtration rate, alterations in serum creatinine (S.Cr) levels, and urine output. This study aimed to retrospectively analyze a cohort of 704 patients selected using stringent inclusion and exclusion criteria. AKI was defined by an increase of 0.3 mg/dL in S.Cr levels compared to baseline. Data were collected from the hospital and analyzed using SPSS 16.0. Data analysis revealed that 22% (n = 155) of the patients developed AKI on the second post-operative day, accompanied by a substantial increase in S.Cr levels (from 1.064 ± 0.2504 to 1.255 ± 0.2673, P < .000). Age and cardiopulmonary bypass duration were identified as risk factors along with ejection fraction and days of hospital stay, contributing to the development of AKI. Early renal replacement therapy can be planned when the diagnosis of AKI is established early after surgery.

Mechanistic Study on Steric Activity Interplay of Olefin/Polar Monomers for Industrially Selective Late Transition Metal Catalytic Reactions

A significant issue in developing metal-catalyzed plastic polymer materials is obtaining distinctive catalytic characteristics to compete with current plastics in industrial commodities. We performed first-principle DFT calculations on the key insertion steps for industrially important monomers, vinyl fluoride (VF) and 3,3,3-trifluoropropene (TFP), to explain how the ligand substitution patterns affect the complex's polymerization behaviors. Our results indicate that the favorable 2,1-insertion of TFP is caused by less deformation in the catalyst moiety of the complexes in contrast to the 1,2-insertion mode. In contrast to the VF monomer, the additional interaction between the fluorine atoms of 3,3,3-trifluoropropene and the carbons of the catalyst ligands also contributed to favor the 2,1-insertion. It was found that the regioselectivity of the monomer was predominated by the progressive alteration of the catalytic geometry caused by small dihedral angles that were developed after the ligand-monomer interaction. Based on the distribution of the 1,2- and 2,1-insertion products, the activity and selectivity were influenced by the steric environment surrounding the palladium center; thus, an increased steric bulk visibly improved the selectivity of the bulkier polar monomer (TFP) during the copolymerization mechanism. In contrast, better activity was maintained through a sterically less hindered Pd metal center; the calculated moderate energy barriers showed that a catalyst with less steric hindrance might provide an opportunity for a wide range of prospective industrial applications.

An effective approach for plant leaf diseases classification based on a novel DeepPlantNet deep learning model

Introduction

Recently, plant disease detection and diagnosis procedures have become a primary agricultural concern. Early detection of plant diseases enables farmers to take preventative action, stopping the disease's transmission to other plant sections. Plant diseases are a severe hazard to food safety, but because the essential infrastructure is missing in various places around the globe, quick disease diagnosis is still difficult. The plant may experience a variety of attacks, from minor damage to total devastation, depending on how severe the infections are. Thus, early detection of plant diseases is necessary to optimize output to prevent such destruction. The physical examination of plant diseases produced low accuracy, required a lot of time, and could not accurately anticipate the plant disease. Creating an automated method capable of accurately classifying to deal with these issues is vital.

Method

This research proposes an efficient, novel, and lightweight DeepPlantNet deep learning (DL)-based architecture for predicting and categorizing plant leaf diseases. The proposed DeepPlantNet model comprises 28 learned layers, i.e., 25 convolutional layers (ConV) and three fully connected (FC) layers. The framework employed Leaky RelU (LReLU), batch normalization (BN), fire modules, and a mix of 3×3 and 1×1 filters, making it a novel plant disease classification framework. The Proposed DeepPlantNet model can categorize plant disease images into many classifications.

Results

The proposed approach categorizes the plant diseases into the following ten groups: Apple_Black_rot (ABR), Cherry_(including_sour)_Powdery_mildew (CPM), Grape_Leaf_blight_(Isariopsis_Leaf_Spot) (GLB), Peach_Bacterial_spot (PBS), Pepper_bell_Bacterial_spot (PBBS), Potato_Early_blight (PEB), Squash_Powdery_mildew (SPM), Strawberry_Leaf_scorch (SLS), bacterial tomato spot (TBS), and maize common rust (MCR). The proposed framework achieved an average accuracy of 98.49 and 99.85in the case of eight-class and three-class classification schemes, respectively.

Discussion

The experimental findings demonstrated the DeepPlantNet model's superiority to the alternatives. The proposed technique can reduce financial and agricultural output losses by quickly and effectively assisting professionals and farmers in identifying plant leaf diseases.

Entropy production with the flow of nanomaterials through the permeable stretched surface with heterogeneous-homogenous chemical reaction

In various thermodynamic procedures and the optimisation of thermal manipulation, nanofluids flowing through porous media represent an emerging perspective. The main objective of this study, from the perspective of thermal applications, was the investigation of the flow of nanofluid over a horizontal stretched surface embedded in a porous medium. The effects of the chemical reactions on the surface, magnetic field, and thermal radiations were invoked in the mathematical formulation. The non-Darcy model examines the fluid flow in the porous media. The principles of thermodynamics were employed to integrate entropy optimisation methods with the established theoretical approach to analyse the thermal behaviour of nanomaterials in the chemical reactive diffusion processes. Using the Tiwari-Das nanofluid model, the volume fraction of the nanomaterials was merged in the mathematical equation for the flow model. Water was taken as a base fluid and nanoparticles composed of aluminium oxide (Al2O3) and silver (Ag) were used. The significance of radiation, heat production, and ohmic heating were included in the energy equation. Furthermore, an innovative mathematical model for the diffusion of the autocatalytic reactive species in the boundary layer flow was developed for a linear horizontally stretched surface embedded in a homogeneous non-Darcy porous medium saturated with the nanofluid. The computer-based built-in bvp5c method was used to compute numerically these equations for varied parameters. It is clear that the magnetic parameter has a reversal influence on the entropy rate and velocity. Temperature and velocity are affected in the opposite direction from a higher volume fraction estimate. Thermal field and entropy were increased when the radiation action intensified. The inclusion of nanoparticle fraction by the volume fraction of nanoparticles and Brinkman number also enhances the system entropy. Entropy production can be minimized with the involvement of the porosity factor within the surface.

TumorDetNet: A unified deep learning model for brain tumor detection and classification

Accurate diagnosis of the brain tumor type at an earlier stage is crucial for the treatment process and helps to save the lives of a large number of people worldwide. Because they are non-invasive and spare patients from having an unpleasant biopsy, magnetic resonance imaging (MRI) scans are frequently employed to identify tumors. The manual identification of tumors is difficult and requires considerable time due to the large number of three-dimensional images that an MRI scan of one patient's brain produces from various angles. Moreover, the variations in location, size, and shape of the brain tumor also make it challenging to detect and classify different types of tumors. Thus, computer-aided diagnostics (CAD) systems have been proposed for the detection of brain tumors. In this paper, we proposed a novel unified end-to-end deep learning model named TumorDetNet for brain tumor detection and classification. Our TumorDetNet framework employs 48 convolution layers with leaky ReLU (LReLU) and ReLU activation functions to compute the most distinctive deep feature maps. Moreover, average pooling and a dropout layer are also used to learn distinctive patterns and reduce overfitting. Finally, one fully connected and a softmax layer are employed to detect and classify the brain tumor into multiple types. We assessed the performance of our method on six standard Kaggle brain tumor MRI datasets for brain tumor detection and classification into (malignant and benign), and (glioma, pituitary, and meningioma). Our model successfully identified brain tumors with remarkable accuracy of 99.83%, classified benign and malignant brain tumors with an ideal accuracy of 100%, and meningiomas, pituitary, and gliomas tumors with an accuracy of 99.27%. These outcomes demonstrate the potency of the suggested methodology for the reliable identification and categorization of brain tumors.

Detection of Extended-spectrum β-lactamase-producing Escherichia coli isolates by isothermal amplification and association of their virulence genes and phylogroups with extraintestinal infection

Extraintestinal pathogenic Escherichia coli (ExPEC) producing extended-spectrum β-lactamases (ESBL) cause serious human infections due to their virulence and multidrug resistance (MDR) profiles. We characterized 144 ExPEC strains (collected from a tertiary cancer institute) in terms of antimicrobial susceptibility spectrum, ESBL variants, virulence factors (VF) patterns, and Clermont's phylogroup classification. The developed multiplex recombinase polymerase amplification and thermophilic helicase-dependent amplification (tHDA) assays for bla_CTX-M, bla_OXA, bla_SHV, and bla_TEM detection, respectively, were validated using PCR-sequencing results. All ESBL-ExPEC isolates carried bla_CTX-M genes with following prevalence frequency of variants: bla_CTX-M-15 (50.5%) > bla_CTX-M-55 (17.9%) > bla_CTX-M-27 (16.8%) > bla_CTX-M-14 (14.7%). The multiplex recombinase polymerase amplification assay had 100% sensitivity, and specificity for bla_CTX-M, bla_OXA, bla_SHV, while tHDA had 86.89% sensitivity, and 100% specificity for bla_TEM. The VF genes showed the following prevalence frequency: traT (67.4%) > ompT (52.6%) > iutA (50.5%) > fimH (47.4%) > iha (33.7%) > hlyA (26.3%) > papC (12.6%) > cvaC (3.2%), in ESBL-ExPEC isolates which belonged to phylogroups A (28.4%), B2 (28.4%), and F (22.1%). The distribution of traT, ompT, and hlyA and phylogroup B2 were significantly different (P < 0.05) between ESBL-ExPEC and non-ESBL-ExPEC isolates. Thus, these equipment-free isothermal resistance gene amplification assays contribute to effective treatment and control of virulent ExPEC, especially antimicrobial resistance strains.

Association and comparison of periodontal and oral hygiene status with serum HbA1c levels: a cross-sectional study

BACKGROUND

Diabetes Mellitus and periodontitis are chronic diseases with known reciprocal association. Studies have shown that uncontrolled diabetes increases the risk of development and progression of periodontal disease. This study aimed to explore the association and severity of periodontal clinical parameters and oral hygiene with HbA1c levels in non-diabetics and T2DM patients.

MATERIALS AND METHODS

In this cross-sectional study, the periodontal status of 144 participants, categorized into non-diabetics, controlled T2DM, and uncontrolled T2DM and were assessed via the Community Periodontal Index (CPI), Loss of Attachment Index (LOA index), and the number of missing teeth, while oral hygiene was measured by utilizing the Oral Hygiene Index Simplified (OHI-S). SPSS was used for data analysis. Chi-square test was used to find out the association of different independent variables with HbA1c groups, while ANOVA and post-hoc tests were run for inter-group and intra-group comparison respectively.

RESULTS

Out of 144 participants, the missing dentition was prevalent in uncontrolled T2DM with mean 2.64 ± 1.97 (95% CI 2.07-3.21; p = 0.01) followed by controlled T2DM 1.70 ± 1.79 (95% CI 1.18-2.23; p = 0.01) and non-diabetics 1.35 ± 1.63 (95% CI 0.88-1.82; p = 0.01) respectively. Furthermore, non-diabetics had a higher proportion of CPI score 0 (Healthy) [30 (20.8%); p = 0.001] as compared to uncontrolled T2DM [6 (4.2%); p = 0.001], while CPI score 3 was more prevalent in uncontrolled T2DM in comparison to non-diabetics. Loss of attachment (codes-2,3 and 4) was also frequently observed in uncontrolled T2DM compared to non-diabetics (p = 0.001). Similarly, based on Oral Hygiene Index- Simplified (OHI-S), the result showed that poor oral hygiene was most commonly observed in uncontrolled T2DM 29 (20.1%) followed by controlled T2DM patients 22 (15.3%) and non-diabetic [14 (9.7%); p = 0.03].

CONCLUSION

This study showed that periodontal status and oral hygiene status were deteriorated in uncontrolled T2DM patients compared to non-diabetic participants and controlled T2DM.

Application of Recently used Green Solvents in Sample Preparation Techniques: A Comprehensive Review of Existing Trends, Challenges, and Future Opportunities

Green solvents (GSs) has gained significant attention in recent years due to their potential as safer and more sustainable alternatives to traditional organic solvents. Solvents are used in a wide range of applications, from industrial processes to everyday products. Solvent emissions and losses can have a significant impact on the environment and human health, which is why many initiatives are being undertaken to get rid of or switch to eco-friendly alternatives. A key area of green chemistry that led to the concept of "green" solvents is the development of alternative solvents that are less toxic and more environmentally friendly than traditional organic solvents. The advantages of using green solvents over conventional ones are their environmental friendliness, biocompatibility, biodegradability, and simplicity of preparation. Different sample preparation techniques have successfully utilized green solvents to offer a sustainable separation media for the extraction of a variety of inorganic and organic compounds which are crucial for research in environmental samples. Recent developments in green analytical chemistry (GAC) have focused on how to prepare and use samples using environmentally sustainable solvents. The current study covers the advance and currently used green solvents with an emphasis on environmentally friendly sample preparation methods. This review aims to briefly summarize the current state of knowledge about the use of green solvents particularly ionic liquids, deep eutectic solvents and switchable solvents (SSs) with the perspective of GAC in sample preparation methods.

Tunable metalensing based on plasmonic resonators embedded on thermosresponsive hydrogel

Metalenses of adjustable power and ultrathin flat zoom lens system have emerged as a promising and key photonic device for integrated optics and advanced reconfigurable optical systems. Nevertheless, realizing an active metasurface retaining lensing functionality in the visible frequency regime has not been fully explored to design reconfigurable optical devices. Here, we present a focal tunable metalens and intensity tunable metalens in the visible frequency regime through the control of the hydrophilic and hydrophobic behavior of freestanding thermoresponsive hydrogel. The metasurface is comprised of plasmonic resonators embedded on the top of hydrogel which serves as dynamically reconfigurable metalens. It is shown that the focal length can be continuously tuned by adjusting the phase transition of hydrogel, the results reveal that the device is diffraction limited in different states of hydrogel. In addition, the versatility of hydrogel-based metasurfaces is further explored to design intensity tunable metalens, that can dynamically tailor the transmission intensity and confined it into the same focal spot under different states, i.e., swollen and collapsed. It is anticipated that the non-toxicity and biocompatibility make the hydrogel-based active metasurfaces suitable for active plasmonic devices with ubiquitous roles in biomedical imaging, sensing, and encryption systems.

Structural insights into the effect of mutations in the spike protein of SARS-CoV-2 on the binding with human furin protein

The SARS COV-2 and its variants are spreading around the world at an alarming speed, due to its higher transmissibility and the conformational changes caused by mutations. The resulting COVID-19 pandemic has imposed severe health consequences on human health. Several countries of the world including Pakistan have studied its genome extensively and provided productive findings. In the current study, the mCSM, DynaMut2, and I-Mutant servers were used to analyze the effect of identified mutations on the structural stability of spike protein however, the molecular docking and simulations approaches were used to evaluate the dynamics of the bonding network between the wild-type and mutant spike proteins with furin. We addressed the mutational modifications that have occurred in the spike protein of SARS-COV-2 that were found in 215 Pakistani's isolates of COVID-19 patients to study the influence of mutations on the stability of the protein and its interaction with the host cell. We found 7 single amino acid substitute mutations in various domains that reside in spike protein. The H49Y, N74K, G181V, and G446V were found in the S1 domain while the D614A, V622F, and Q677H mutations were found in the central helices of the spike protein. Based on the observation, G181V, G446V, D614A, and V622F mutants were found highly destabilizing and responsible for structural perturbation. Protein-protein docking and molecular simulation analysis with that of furin have predicted that all the mutants enhanced the binding efficiency however, the V622F mutant has greatly altered the binding capacity which is further verified by the K_D value (7.1 E^-14) and therefore may enhance the spike protein cleavage by Furin and increase the rate of infectivity by SARS-CoV-2. On the other hand, the total binding energy for each complex was calculated which revealed -50.57 kcal/mol for the wild type, for G181V -52.69 kcal/mol, for G446V -56.44 kcal/mol, for D614A -59.78 kcal/mol while for V622F the TBE was calculated to be -85.84 kcal/mol. Overall, the current finding shows that these mutations have increased the binding of Furin for spike protein and shows that D614A and V622F have significant effects on the binding and infectivity.

Mechanistic study to reveal steric and electronic aspects involved in the formation of microstructures during Pd-catalyzed olefin/divinyl formal copolymerization: reactivity to catalyst choice

The advancement of metal-catalyzed copolymers is a formidable challenge for achieving distinct catalytic properties to compete with existing plastic polymers in industrial commodities. Herein, we reveal the roles of electronic and steric environments in the thermodynamic preference of microstructures in ethylene/divinyl formal (DVF) co-polymerization using a Pd catalyst under mild conditions to accommodate the respective industrial applicabilities. The insertion products of DVF result in the alteration of the steric crowding, ultimately favoring the efficient formation of cyclic units having potential applications in the manufacture of high-strength fibers. More specifically, to achieve an improved yield of the end copolymer, we tuned the catalytic activity and regioselectivity through a variety of catalysts during ethylene-DVF co-polymerization. The naphthalene-bridged (P^O)PdMe catalyst was found to be promising in terms of the least hindered (buried volume of 47.8%) environment with the thermodynamic preference of 2,1-insertion with an energy of 5.1 kcal mol^-1 among all the Pd-metal based catalysts. The highest activity with moderate energy barriers of the proposed catalyst will open new avenues for achieving a variety of potential applications, which is typically not possible using existing polymerization techniques.

A Holistic Approach to Identify and Classify COVID-19 from Chest Radiographs, ECG, and CT-Scan Images Using ShuffleNet Convolutional Neural Network

Early and precise COVID-19 identification and analysis are pivotal in reducing the spread of COVID-19. Medical imaging techniques, such as chest X-ray or chest radiographs, computed tomography (CT) scan, and electrocardiogram (ECG) trace images are the most widely known for early discovery and analysis of the coronavirus disease (COVID-19). Deep learning (DL) frameworks for identifying COVID-19 positive patients in the literature are limited to one data format, either ECG or chest radiograph images. Moreover, using several data types to recover abnormal patterns caused by COVID-19 could potentially provide more information and restrict the spread of the virus. This study presents an effective COVID-19 detection and classification approach using the Shufflenet CNN by employing three types of images, i.e., chest radiograph, CT-scan, and ECG-trace images. For this purpose, we performed extensive classification experiments with the proposed approach using each type of image. With the chest radiograph dataset, we performed three classification experiments at different levels of granularity, i.e., binary, three-class, and four-class classifications. In addition, we performed a binary classification experiment with the proposed approach by classifying CT-scan images into COVID-positive and normal. Finally, utilizing the ECG-trace images, we conducted three experiments at different levels of granularity, i.e., binary, three-class, and five-class classifications. We evaluated the proposed approach with the baseline COVID-19 Radiography Database, SARS-CoV-2 CT-scan, and ECG images dataset of cardiac and COVID-19 patients. The average accuracy of 99.98% for COVID-19 detection in the three-class classification scheme using chest radiographs, optimal accuracy of 100% for COVID-19 detection using CT scans, and average accuracy of 99.37% for five-class classification scheme using ECG trace images have proved the efficacy of our proposed method over the contemporary methods. The optimal accuracy of 100% for COVID-19 detection using CT scans and the accuracy gain of 1.54% (in the case of five-class classification using ECG trace images) from the previous approach, which utilized ECG images for the first time, has a major contribution to improving the COVID-19 prediction rate in early stages. Experimental findings demonstrate that the proposed framework outperforms contemporary models. For example, the proposed approach outperforms state-of-the-art DL approaches, such as Squeezenet, Alexnet, and Darknet19, by achieving the accuracy of 99.98 (proposed method), 98.29, 98.50, and 99.67, respectively.

A critical review of selected preconcentration techniques used for selenium determination in analytical samples

Selenium (Se) is considered to be an essential trace element needed for all living organisms. The importance, deficiency, and toxic effects of Se mainly depend on its quantity and chemical nature. It has been observed that the inorganic versions of Se are more hazardous than the organic versions. This review is mainly focused on the application of different extraction methods used for Se extraction and determination such as microextraction, solid-phase extraction (SPE), and their modified modes in the last 12 years. The use of different dispersive medium (magnetic field, ultrasonic radiation, and vortex agitator) to enhance Se separation is also part of this review. The usage of environmentally friendly solvents such as supramolecular solvents, hydrophobic deep eutectic solvents (DESs), and ionic liquids (ILs) are also the focus of attention in this review. This review is also emphasized the application of advanced microextraction methods, particularly liquid-phase microextraction (LPME). The most recent advances in LPME extraction techniques for Se in various environmental samples, as well as their prospects, are reviewed. Additionally, a summary of cheap, simple, and accurate techniques that have not yet been used to determine small amounts of Se has been provided.

Analysis of associated risk factors among recurrent cutaneous leishmaniasis patients: A cross-sectional study in Khyber Pakhtunkhwa, Pakistan

BACKGROUND

Leishmaniasis is the second and fourth highest cause of mortality and morbidity respectively among all tropical diseases. Recurrence in the onset of leishmaniasis is a major problem that needs to be addressed to reduce the case fatality rate and ensure timely clinical intervention. Here we are investigating the association of risk factors with recurrent cutaneous leishmaniasis to address this issue.

MATERIAL AND METHODS

Patients received by Nasser Ullah Khan Babar Hospital in Peshawar, Pakistan from March 2019 to July 2020 were enrolled in this study. Those patients who developed symptoms after completion of treatment were included in Group-A while those who had atypical scars like leishmaniasis but were negative for cutaneous leishmaniasis were included in the comparison group tagged as Group B. All those individuals who had completed six weeks of treatment for CL but had normal complete blood counts (CBC) were included to avoid other underlying immunological pathologies, while we excluded those participants who had co-morbidities like diabetes, liver disease, cardiac disease, and pregnant and lactating women through their history Association was tested between Group-A and Group-B with other explanatory variables through chi-square test. The regression model was proposed to determine the predictors.

RESULT

A total of 48 participants of both sexes were included in the study with a mean age of 32.2 ± 15.10. The data suggest that females are overrepresented among the patients with recurrent leishmaniasis [21(53.8 %,); p = 0.07]. Compared to patients; healthy participants had a higher proportion of adults (19-59 years) versus adolescents (13-18 years) [26(66.7 %) vs 07(17.9), p = 0.004]. Multivariate logistic regression analysis shows that females are 2.1 times more prone to infections among cases as compared to healthy individuals [unadjusted OR 2.20, 95 % confidence interval (CI) 1.5-10.6, p = 0.02; adjusted OR 2.1, 95 % CI 1.50-10.69, p = 0.02]. We propose that patients receiving intradermal were less likely to be infected as compared to those receiving intralesional injections [unadjusted OR 0.07.0, 95 % confidence interval (CI) 1.18-3.37, p = 0.03; adjusted OR 0.06, 95 % CI 1.18-3.38, p = 0.03].

CONCLUSION

Old age (adults) and sex (females) were the strongest predictors to be associated with recurrent leishmaniasis. Similarly, the choice of intradermal as compared to intralesional injection and the prolonged treatment duration were strongly associated with greater chances of recurrence.

A Robust End-to-End Deep Learning-Based Approach for Effective and Reliable BTD Using MR Images

Detection of a brain tumor in the early stages is critical for clinical practice and survival rate. Brain tumors arise in multiple shapes, sizes, and features with various treatment options. Tumor detection manually is challenging, time-consuming, and prone to error. Magnetic resonance imaging (MRI) scans are mostly used for tumor detection due to their non-invasive properties and also avoid painful biopsy. MRI scanning of one patient's brain generates many 3D images from multiple directions, making the manual detection of tumors very difficult, error-prone, and time-consuming. Therefore, there is a considerable need for autonomous diagnostics tools to detect brain tumors accurately. In this research, we have presented a novel TumorResnet deep learning (DL) model for brain detection, i.e., binary classification. The TumorResNet model employs 20 convolution layers with a leaky ReLU (LReLU) activation function for feature map activation to compute the most distinctive deep features. Finally, three fully connected classification layers are used to classify brain tumors MRI into normal and tumorous. The performance of the proposed TumorResNet architecture is evaluated on a standard Kaggle brain tumor MRI dataset for brain tumor detection (BTD), which contains brain tumor and normal MR images. The proposed model achieved a good accuracy of 99.33% for BTD. These experimental results, including the cross-dataset setting, validate the superiority of the TumorResNet model over the contemporary frameworks. This study offers an automated BTD method that aids in the early diagnosis of brain cancers. This procedure has a substantial impact on improving treatment options and patient survival.

A New Trend and Future Perspectives of the Miniaturization of Conventional Extraction Methods for Elemental Analysis in Different Real Samples: A Review

Sample preparation is one of the viable procedures to be used before analysis to enhance sensitivity and reduce the matrix effect. The current review is mainly emphasized the latest outcome and applications of microextraction techniques based on the miniaturization of the classical conventional methods based on liquid-phase and solid-phase extraction for the quantitative elemental analysis in different real samples. The limitation of the conventional sample preparation methods (liquid and solid phase extraction) has been overcome by developing a new way of reducing size as compared with the conventional system through the miniaturization approach. Miniaturization of the sample preparation techniques has received extensive attention due to its extraction at microlevels, speedy, economical, eco-friendly, and high extraction capability. The growing demand for speedy, economically feasible, and environmentally sound analytical approaches is the main intention to upgrade the conventional procedures apply for sample preparation in environmental investigation. A growing trend of research has been perceived to quantify the trace for elemental analysis in different natures of real samples. This review also recapitulates the current futuristic scenarios for the green and economically viable procedure with special overemphasis and concentrates on eco-friendly miniaturized sample-preparation techniques such as liquid-phase microextraction (LPME) and solid-phase microextraction (SPME). This review also emphasizes the latest progress and applications of the LPME and SPME approach and their future perspective.

Structural and compositional segregation of the gut microbiota in HCV and liver cirrhotic patients: A clinical pilot study

Gut microbial dysbiosis during the development of Hepatitis C virus and liver-related diseases is not well studied. Nowadays, HCV and liver cirrhosis are the major concerns that cause gut bacterial alteration, which leads to dysbiosis. For this purpose, the present study was aimed at correlating the gut bacterial community of the control group in comparison to HCV and liver cirrhotic patients. A total of 23 stool samples were collected, including control (9), liver cirrhotic (8), and HCV (6). The collected samples were subjected to 16S rRNA Illumina gene sequencing. In comparison with control, a significant gut bacterial alteration was observed in the progression of HCV and liver cirrhosis. Overall, Firmicutes were significantly abundant in the whole study. No significant difference was observed in the alpha diversity of the control and patient studies. Additionally, the beta diversity based on non-metric multidimensional scaling (NMDS) has a significant difference (p = 0.005) (ANOSIM R² = 0.14) in all groups. The discriminative results based on the LEfSe tool revealed that the HCV-infected patients had higher Enterobacteriaceae and Enterobacterial, as well as Lactobacillus and Bacilli in comparison than the liver-cirrhotic patients. These taxa were significantly different from the control group (p < 0.05). Regarding prospects, a detailed analysis of the function through metagenomics and transcriptomics is needed.

Regulation of Conformational Changes in C-reactive Protein Alters its Bioactivity

The acute phase C-reactive protein (CRP) is mainly synthesized and secreted by the liver in a cytokine-mediated response to infection or inflammation and circulates as a pentamer (pCRP) in plasma. Recent studies indicate that CRP is not only a marker but is directly involved in inflammation. CRP has a vital role in host defense and inflammation, metabolic function and scavenging through its ability for calcium depended binding to exogenous and endogenous molecules having phosphocholine followed by activation of the classical complement pathway. Accumulating evidence indicates that pCRP dissociates into monomeric CRP (mCRP) and most proinflammatory actions of CRP are only expressed following dissociation of its native pentameric assembly into mCRP. The dissociation of CRP into mCRP altogether promotes the ligand-binding capability. mCRP emerges to be the main conformation of CRP that participates in the regulation of local inflammation, however, little is identified concerning what triggers the significantly enhanced actions of mCRP and their binding to diverse ligands. The separation of mCRP from pCRP may be a direct relationship between CRP and inflammation. Here we review the current literature on CRP dissociation and its interaction with different ligands. The possibility to avoid the generation of the proinflammatory potential of mCRP has driven therapeutic approaches by targeting the dissociation mechanism of pCRP or inhibition of mCRP itself during inflammation.

Monitoring and Efficiency in Governance: A Measure for Sustainability in the Islamic Banking Industry

Corporate governance is a set of rules, regulations, procedures, processes, and practices through which an organization is controlled and directed. The present study aimed to examine the monitoring methods used in Islamic banking, including standardized measures for better performance, an individual's aptitude towards Islamic financial markets, risk propensity, and the level of efficiency of the Islamic banking industry in Pakistan and Malaysia. There is room to improve monitoring systems for Islamic banking operations and standardized measures could improve efficiency, leading to more sustainable performance. The study uses a self-developed semi-structured scale based on literature and expert interviews, after content and context validity to gain a wide range of diverse information. In Pakistan and Malaysia, individuals' perceptions are different because of differences in the banking environment and preferences. Eventually, the Islamic banking growth rate may differ in Pakistan and Malaysia. Thus, there should be regular monitoring to improve banking performance. Similarly, standardized measures for Islamic banking operations and governance performance in Pakistan and Malaysia will result in more sustainable performance. The antecedents of Islamic corporate governance could be improved to enhance banking performance, which helps individuals make decisions based on available product information. The business growth of the banking industry is based on convenient monitoring policies, standardized performance measures, and, most importantly, excellent corporate governance mechanisms. Improved monitoring measures will further enhance these business operations.

Development of a Real-Time qPCR Assay for Detection of Common MPL Mutations in Myeloproliferative Neoplasms (MPNS)

Myeloproliferative neoplasms (MPNs) are blood cell disorders, characterized by overproduction of abnormal cells in bone marrow due to stem cell mutation. The proliferations of blood cell are controlled by many genes particularly MPL gene which encodes thrombopoietin receptor, a hematopoietic growth factor involved in the production and regulation of the platelets and multipotent hematopoietic progenitor cells. Acquired mutations including (W515L and W515K) in this gene have been observed in patients with primary myelofibrosis or essential thrombocythemia lacking JAK2 (V617F) mutations. MPL mutation detection is important for MPNs diagnosis, but due to low frequency of mutant allele burden (< 15%) may be missed by already available common assays such as Sanger sequencing. Furthermore, these techniques are costly, time-consuming, and less sensitive. In present study, we aimed to develop sensitive, less time-consuming, and cost-effective real-time PCR assay for the detection of MPL mutations that is based on TaqMan fluorescent probes. DNA was extracted from blood sample of 128 MPNs patients collected and further analysis was performed on TaqMan RT-PCR. Reference curve was obtained for amplified product of MPL gene containing mutated sequence. The predicted sensitivity level was at least 5% mutant allele burden by our developed assay that is much higher than sequencing output. Out of 128, 2 (1.56%) patients harbored W515L mutation and 1 (0.78%) harbored W515K mutation. It was concluded that TaqMan qRT-PCR assay is an efficient, sensitive, cost-effective, and less time-consuming method capable of detecting MPL mutation in MPNs patients. We suggested that this assay might be helpful in investigating mutant allele load in MPNs patients.

Predicting Students’ Academic Performance with Conditional Generative Adversarial Network and Deep SVM

The availability of educational data obtained by technology-assisted learning platforms can potentially be used to mine student behavior in order to address their problems and enhance the learning process. Educational data mining provides insights for professionals to make appropriate decisions. Learning platforms complement traditional learning environments and provide an opportunity to analyze students’ performance, thus mitigating the probability of student failures. Predicting students’ academic performance has become an important research area to take timely corrective actions, thereby increasing the efficacy of education systems. This study proposes an improved conditional generative adversarial network (CGAN) in combination with a deep-layer-based support vector machine (SVM) to predict students’ performance through school and home tutoring. Students’ educational datasets are predominantly small in size; to handle this problem, synthetic data samples are generated by an improved CGAN. To prove its effectiveness, results are compared with and without applying CGAN. Results indicate that school and home tutoring combined have a positive impact on students’ performance when the model is trained after applying CGAN. For an extensive evaluation of deep SVM, multiple kernel-based approaches are investigated, including radial, linear, sigmoid, and polynomial functions, and their performance is analyzed. The proposed improved CGAN coupled with deep SVM outperforms in terms of sensitivity, specificity, and area under the curve when compared with solutions from the existing literature.

Frequency of Different Neuropsychiatric Manifestations of Systemic Lupus Erythematosus at a Tertiary Care Hospital in Pakistan

Objective: To determine the frequency of different neuropsychiatric manifestations of systemic lupus erythematosus Study Design: Cross-sectional study. Place and Duration of Study: Division of Rheumatology Lady Reading Hospital, Peshawar Pakistan, from Sep 2020 to Feb 2021. Methodology: 31 patients who fulfilled the 2019 ACR/EULAR criteria for SLE diagnosis were included in the study. Different features of neuropsychiatric manifestations of systemic lupus erythematosus were recorded on a proforma. Results: Our study sample included 27 females and four males. Most of the patients were young, with a mean age of 23.12 ± 10.74 years. All patients had positive Anti-nuclear antibodies (100%), while anti-double standard DNA antibody was found in 21 patients (67. 74%). Seizures were the most common neuropsychiatric feature, i.e., found in 18 patients (58%), followed by headache (25.8%), acute confusional state (25.8%) and CNS demyelinating disease (19.3%). Conclusion: We found that seizures, headache and acute confusional state were the most common neuropsychiatric manifestations of systemic lupus erythematosus.

Lactobacillus plantarum strains attenuated DSS-induced colitis in mice by modulating the gut microbiota and immune response

Gut microbiota has become a new therapeutic target in the treatment of inflammatory Bowel Disease (IBD). Probiotics are known for their beneficial effects and have shown good efficacy in the clinical treatment of IBD and animal models of colitis. However, how these probiotics contribute to the amelioration of IBD is largely unknown. In the current study, the DSS-induced mouse colitis model was treated with oral administration of Lactobacillus plantarum strains to investigate their effects on colitis. The results indicated that the L. plantarum strains improved dysbiosis and enhanced the abundance of beneficial bacteria related to short-chain fatty acids (SCFAs) production. Moreover, L. plantarum strains decreased the level of pro-inflammatory cytokines, i.e., IL-17A, IL-17F, IL-6, IL-22, and TNF-α and increased the level of anti-inflammatory cytokines, i.e., TGF-β, IL-10. Our result suggests that L. plantarum strains possess probiotic effects and can ameliorate DSS colitis in mice by modulating the resident gut microbiota and immune response.

Cattaneo–Christov heat flow model for copper–water nanofluid heat transfer under Marangoni convection and slip conditions

This report is devoted to the study of the flow of MHD nanofluids through a vertical porous plate with a temperature-dependent surface tension using the Cattaneo–Christov heat flow model. The energy equation was formulated using the Cattaneo–Christov heat flux model instead of Fourier’s law of heat conduction. The Tiwari–Das model was used to take into account the concentration of nanoparticles when constructing the momentum equation. The problem is described mathematically using the boundary layer approach as a PDE, which is then converted into an ODE with the help of the transformation process. The solution finding process was completed by running the bvp4c code in MATLAB. A quantitative analysis of the influence of some newly occurring parameters on physical quantities was carried out using graphics. The addition of nanoparticles to the base fluid leads to an increase in both skin friction and thermal conductivity. The increase in thermal conductivity is the advantage, while the increase in skin friction is the disadvantage of the nanoparticle concentration. Marangoni convection has proven to be one of the most cost-effective tools available that can reduce skin friction. Marangoni convection improves the heat transfer coefficient during suction but decreases the heat transfer coefficient during the injection.

Mechanism of the Gut Microbiota Colonization Resistance and Enteric Pathogen Infection

The mammalian gut microbial community, known as the gut microbiota, comprises trillions of bacteria, which co-evolved with the host and has an important role in a variety of host functions that include nutrient acquisition, metabolism, and immunity development, and more importantly, it plays a critical role in the protection of the host from enteric infections associated with exogenous pathogens or indigenous pathobiont outgrowth that may result from healthy gut microbial community disruption. Microbiota evolves complex mechanisms to restrain pathogen growth, which included nutrient competition, competitive metabolic interactions, niche exclusion, and induction of host immune response, which are collectively termed colonization resistance. On the other hand, pathogens have also developed counterstrategies to expand their population and enhance their virulence to cope with the gut microbiota colonization resistance and cause infection. This review summarizes the available literature on the complex relationship occurring between the intestinal microbiota and enteric pathogens, describing how the gut microbiota can mediate colonization resistance against bacterial enteric infections and how bacterial enteropathogens can overcome this resistance as well as how the understanding of this complex interaction can inform future therapies against infectious diseases.

Collaborative enhancement in charge separation and photon harvesting of 2D/2D heterojunction photocatalyst by horizontal loading of SnS2 nanosheets on g-CN films

Highly efficient photocatalysts based on Van der Waals 2D type of heterojunction were fabricated by horizontal loading of ultrathin hexagonal SnS2 nanosheets on the surface of g-CN film via spin...

Expression analysis of transcription factors in sugarcane during cold stress

Transcription factors (TF) are a wide class of genes in plants, and these can regulate the expression of other genes in response to various environmental stresses (biotic and abiotic). In the current study, transcription factor activity in sugarcane was examined during cold stress. Initially, RNA transcript reads of two sugarcane cultivars (ROC22 and GT08-1108) under cold stress were downloaded from SRA NCBI database. The reads were aligned into a reference genome and the differential expression analyses were performed with the R/Bioconductor edgeR package. Based on our analyses in the ROC22 cultivar, 963 TF genes were significantly upregulated under cold stress among a total of 5649 upregulated genes, while 293 TF genes were downregulated among a total of 3,289 downregulated genes. In the GT08-1108 cultivar, 974 TF genes were identified among 5,649 upregulated genes and 283 TF genes were found among 3,289 downregulated genes. Most transcription factors were annotated with GO categories related to protein binding, transcription factor binding, DNA-sequence-specific binding, transcription factor complex, transcription factor activity in RNA polymerase II, the activity of nucleic acid binding transcription factor, transcription corepressor activity, sequence-specific regulatory region, the activity of transcription factor of RNA polymerase II, transcription factor cofactor activity, transcription factor activity from plastid promoter, transcription factor activity from RNA polymerase I promoter, polymerase II and RNA polymerase III. The findings of above results will help to identify differentially expressed transcription factors during cold stress. It also provides a comprehensive analysis of the regulation of the transcription activity of many genes. Therefore, this study provides the molecular basis for improving cold tolerance in sugarcane and other economically important grasses.

Synthesis, characterization, POM analyses and biological evaluation of n-[(2-methoxy-5- nitrophenyl)]-4-oxo-4-[oxy] butenamide based zinc(II) carboxylate complexes

ABSTRACT. The aim of medicinal chemistry is to links many scientific disciplines and allows the scientists in researching and developing new drugs with enhance and targeted properties. In this article we are exploring the preparation of four new zinc(II) carboxylate complexes based on N-[(2-methoxy-5-nitrophenyl)]-4-oxo-4-[oxy]butenamide which were characterized through FT-IR and EDX studies. The DNA binding ability and binding type of complexes were assessed by spectroscopic (UV-Visible) and viscosity measurements, exhibiting an intercalative pattern of interaction. The synthesized compounds were also assessed to know theoretically about their nature by molecular docking studies resulting also in intercalation mode. Analysis of the complexes for biological applications such as anti-microbial, anti-leishmanial, cytotoxicity and DNA damage activities showed that these complexes carries good anti-microbial, anti-leishmanial activity with no toxicity to human blood thyrocytes and DNA. The bioavailability prediction and drug likeness score has also been evaluated through Insilco studies.                     KEY WORDS: Zn(II) carboxylate complex, DNA binding, Anti-leishmanial activity, Cytotoxicity, Docking study   Bull. Chem. Soc. Ethiop. 2021, 35(2), 365-380. DOI: https://dx.doi.org/10.4314/bcse.v35i2.11

Construction of optical solitons of magneto-optic waveguides with anti-cubic law nonlinearity

Two efficient integration schemes, new extended hyperbolic function and generalized tanh are employed to discover optical soliton solutions to magneto-optic waveguides that retains anti-cubic form of nonlinear refractive index. Bright, dark, periodic singular, singular, and combo soliton solutions have created. These solutions expose the comprehensive variety of soliton solutions.

Adenine ultrafast photorelaxation via electron-driven proton transfer

Photorelaxation of adenine in water was reported to be ultrafast (within 180 fs) primarily due to radiationless relaxation. However, in the last two decades, several experimental and theoretical investigations on photoexcitation of adenine have revealed diverse types of decay mechanisms. Using time-dependent density functional excited-state nonadiabatic dynamics simulations we show that it is the water to adenine electron-driven proton transfer (EDPT) barrierless reaction responsible for the ultrafast component of the adenine relaxation, which, however, occurred only in the case of the 7H isomer of adenine with five water molecules. This result reveals a known reaction pathway, however not found in previous simulations, with inference for the ultrafast relaxation mechanisms of adenine reported in experiments. The 9H isomer of adenine with six water molecules relaxing in a water cluster followed the previously known structural distortion (C2) decay pathway. The observations of the adenine EDPT reaction with water provide the origin of the experimental ultrafast adenine decay component and present a possible method to tackle future computational challenges in molecular-level biological processes.

Air pollution and associated self-reported effects on the exposed students at Malakand division, Pakistan

Air pollution is associated with several severe physical, behavioral, and psychological health risks and glitches. Air pollution has been linked to 11 million premature deaths in Pakistan, out of the total 153 million premature deaths worldwide. Air pollution is continuously growing as a threatening challenge for Pakistan. Keeping this in view, the current study was designed to assess air pollution in terms of air quality index (AQI), particulate matters (PM_2.5 and PM₁₀), SO₂, NO₂, and O₃ over six districts of Malakand division, Northern Pakistan. The second part of the study appraised the associated self-reported effects of air pollution on Pakistani students and the practices, perceptions, and awareness of the students regarding air pollution through a closed-ended questionnaire, administered to 4100 students. The first section of the questionnaire was focused on the physical effects associated with air pollution; the second section was focused on air pollution-linked behavior and psychology; the third portion was focused on perception and awareness of the subjects, whereas the final section was focused on practices and concerns of the subjects regarding air pollution. The students reported that exposure to air pollution significantly affected their physical health, behavior, and psychology. The subjects were aware of the different air pollutants and health complications associated with air pollution, and therefore had adopted preventive measures. It was concluded that air pollution had adverse impacts on the physical and psychological health of the respondents, which consequently altered their behavior. Mass awareness, proper mitigating plan, suitable management, and implementation of strict environmental laws are suggested before the air gets further polluted and becomes life-threatening.

Prevalence of active HCV infection and genotypic distribution among the general population of district Mardan, Pakistan

Hepatitis C virus (HCV) is the serious global public health burden of liver disease. Approximately 170 million people in the world are infected with (HCV). In Pakistan, where the disease has high occurrence rate. The present study envisages an up-to-date prevalence of HCV and genotypic distribution in the general population of Mardan District, Khyber Pakhtunkhwa (KP), Pakistan. The blood samples from 6,538 individuals including 3,263 males and 3,275 females were analyzed for hepatitis C surface antigen by Immuno-chromatographic test (ICT), Enzyme-linked immunosorbent assay (ELISA), and reverse transcription-polymerase chain reaction (PCR). It was found that 396 (12.13%) out of 3263 individuals contained antibodies in their blood against HCV, while among the different age groups, the highest incidences of HCV antibodies were found in the 31-40 age group (11.01%). The ICT positive samples were further screened by nested PCR to determine the existence of active HCV-RNA. It was identified that 7.11% (3263) of the total population (6538) tested was positive, among which the 461 (14.07%) females possessed antibodies in their blood against HCV. Our data showed total HCV infection in the investigated population was 5.78%. Higher percentage of HCV prevalence was detected in males than females in the age group 31-40 and 41-50. To compare the prevalence of HCV genotypes age-wise in male and female genotype 3a was found most prevalent genotype followed by 1a, 2a and 3b, respectively.

Serological prevalence of hepatitis B virus (HBV) in Mardan district, Khyber Pakhtunkhwa, Pakistan

Hepatitis B virus infection is perilous among the five types of Hepatitis, as it remains clinically asymptomatic. The present study draws up-to-date prevalence of Hepatitis B virus (HBV) in the general population of Mardan, Khyber Pakhtunkhwa Pakistan. The blood samples from 4803 individuals including 2399 male and 2404 females were investigated. All the suspected samples were analyzed for hepatitis B surface antigen using Immuno-chromatographic test (ICT), Enzyme-linked immunosorbent assay (ELISA), and followed by Reverse transcription-polymerase chain reaction (RT-PCR). Results showed that 312 (13.00%) out of 2399 individuals contained antibodies in their blood against HBV, while among the different age groups, the highest incidences of HBV antibodies were found in the age of 21-30 groups (10.73%). Furthermore, the ICT positive samples were screened by nested polymerase chain reaction to detect the existence of active HBV-DNA. It was observed that 169 (7.04%) out of (2399) male of the total population (4803) tested was positive. On the other hand, the female 463 (19.25%) possessed antibodies in their blood against HBV. Accumulatively, our results showed a higher percentage of HBV prevalence in males than females in the age group 21-30 years. The total HCV infected in Mardan general population was recorded at 5.7% comprising both male and female.

Repeated Covid-19 Infection Exists: A Case Series From Pakistan

BACKGROUND

Protection against SARS-CoV-2 in infected individuals of COVID-19 is lacking. We report a case series of repeated infections of SARS-CoV-2.

METHODS

A total of 12 patients were identified with repeated infections for SARS-CoV-2 from 25 April 2020 to 16 March 2021 from Pakistan. Repeated infection was defined as diagnosis of the SARS-CoV-2 with real-time reverse transcriptase-polymerase chain reaction (RT-PCR) tests in the first and second phase of infection after complete recovery from the first phase of infection with a negative RT-PCR.

RESULTS

Of the 12 participants, 75% (n=9) were male and mean age of the participants were 40.1±9.7 years. Mean duration between the first and second phase of infection was 184±68.9 days. Patients presenting with mild infection in the first phase largely developed moderate to severe infection in the second phase. None of them were vaccinated.

CONCLUSION

The pandemic of COVID-19 is on the rise and repeated infection from SARS-CoV-2 is occurring.

Episode of Hepatitis C viral infection in the people of Swat, Pakistan

Infectious agents cause serious diseases in humans worldwide and are responsible for the high rate of morbidity and mortality. The prevalence and epidemiology of infectious disease (HCV) in the hospital visited patients referred by the physicians through the initial findings and their associated risk factors were studied in Swat. The data of 174 infected patients were collected during the period of 2015 to 2017 from two clinical laboratories of Tehsil Matta Swat. Inform consent form was taken before blood collection. After taking informed consent blood samples were collected and ICT test was performed and then ICT positive cases were conform through PCR. A total of 174 ICT positive samples [106 male and 68 females] were included in this study. Age was considered from 10 to 72 years. Of the 174 ICT strip positive, 99 [63 males, 36 females] were confirmed through PCR. The prevalence rate was recorded 56.89%. I.V/I.M injection was recorded in 100% of the individuals. Visits to the barber shop was reported in (58%) of the individuals, married individuals were (81.0), surgical operation was reported in (44.8%), sharing toothbrush was observed in (29.9%), piercing was reported in (39.7%), family history was reported in (26.4%), dental treatment was observed in (21.8%), jaundice were (13.2%) and tattooing was (1.7%). Blood transfusion, surgical operations, Jaundice, family history and dental treatment were found significant risk factors for acquiring HCV infection. It was concluded that proper implementation of precautionary measures should be needed to control the spread of HCV in far near future.

Bioaccumulation of heavy metals in the tissues of Schizothorax plagiostomus at River Swat

Snow trout (Schizothorax plagiostomus) is an economically important freshwater fish, mostly found in northern areas of water reservoirs of Pakistan. The current study was conducted in River Swat to analyze the bioaccumulation of heavy metals (Pb, Cr, Ni, and Zn) in tissues of Schizothorax plagiostomus. Tissues were extracted and dissolved in perchloric acid (HClO4) and nitric acid (HNO3) along with hotplate. The heavy metals, zinc (Zn), lead (Pb), chromium (Cr), and Nickel (Ni) were determined using Perkin Elmer 2380 atomic absorption spectrophotometer. Results shows great variation in the content of the metal related to tissue type and sampling sites. A high concentration of bioaccumulation was reported at Charbagh, whereas lowest at Odigram: Charbagh>Landakai>Odigram. In the same way, Cr was the most accumulated heavy metal followed by lead, nickel, and Zinc.

Comparative brain analysis of wild and hatchery reared Mahseer (Tor putitora) relative to their body weight and length

The present study was aimed at comparing the brain size of mahseer (Tor putitora) in relation to their body weight and standard length, to investigate the potential impact of rearing environment on brain development in fish. The weight of the brain and three of its subdivisions cerebellum (CB), optic tectum (OT), and telencephalon (TC) were measured for both wild and hatchery-reared fish. The data was analysed using multiple analysis of covariance (MANCOVA), analysis of covariance (ANCOVA), and discriminate function analysis (DFA). We found the fish reared under hatchery conditions exhibit smaller brain size related to body weight, when compared to the wild ones. A significant (p<0.5) difference was observed in the length of CB and OT concerning the standard body length while no significant difference was found in TC of the fish from both the origins. The results of the current study highlight a logical assumption that neural deficiency affects the behaviour of fish, that's why the captive-reared fish show maladaptive response and face fitness decline when released to the natural environment for wild stock enhancement. The current study concluded that hatchery-reared fish exhibit variations in gross brain morphology as compared to their wild counterpart.

Rotating flow assessment of magnetized mixture fluid suspended with hybrid nanoparticles and chemical reactions of species

The current study characterizes the effects of Hall current, Arrhenius activation energy and binary chemical reaction on the rotating flow of hybrid nanofluid in two double disks. By the use of suitable similarity transformations, the system of partial differential equations and boundary conditions for hybrid nanofluid are transformed to ordinary differential equations which are solved through optimal homotopy analysis method. The intensified magnetic field and hybrid nanofluid performances are represented in three dimensional model with flow, heat and mass transfer. Radial velocity decreases and tangential velocity increases with the Hall parameter. Temperature rises with high values of rotation parameter while it decreases with the Prandtl number. Nanoparticles concentration enhances with the increments in Arrhenius activation energy parameter and stretching parameter due to lower disk. There exists a close and favorable harmony in the results of present and published work.

Effect of different protein based feed on the growth of mahseer

For the proper growth of fish, it is necessary to feed the fish with a proper and balanced diet. A study was conducted to find out the effect of different protein-based diets on fingerlings of Tor putitora (mahseer). A feed with dietary protein levels of 35%, 40%, 45%, and 50% were prepared. The effect of different protein-based feed on weight gain, standard growth rate (SGR), food conversion ratio (FCR), percent weight gain, food conversion efficiency (FCE), and protein efficiency ratio (PER) was studied. An increase was observed in the growth rate with an increase in protein concentration up to 45%. The fingerlings fed a 45% protein diet shown the highest growth, followed by 50%, 40%, and 35%. The SGR value was greatest for 45% protein diet (8.56) followed by 50% and 40%, while the least values were observed for 35% protein feed (1.57). The same trend was observed for FCE. The highest PER values was observed in fishes fed 45% protein-based feed (0.65) followed by 50% (0.56), 40% (0.38) and35% (0.17). The food conversion ratio was lowest for 45% protein diet (3.41), while the greatest for 35% protein feed (16.85). It was concluded that a 45% protein-based diet was the best feed formulation for higher production of Tor putitora. However, research on the same percentage of protein diet is recommended for yearlings.

Prevalence of Parental refusal rate and its associated factors in routine immunization by using WHO Vaccine Hesitancy tool: A Cross sectional study at district Bannu, KP, Pakistan

OBJECTIVE

To determine the vaccination refusal rate, associated factors and perceptions of parents who refused routine immunization for their children using the World Health Organization (WHO) SAGE Working Group on Vaccine Hesitancy Survey Tool.

MATERIALS AND METHODS

A cross-sectional survey was conducted using multi-stage cluster sampling in Bannu District, Khyber Pakhtunkhwa Province, Pakistan from March 2019 to July 2019. A WHO validated questionaire was used. The outcome variable was parental refusal of routine immunization of their children. Logistic regression was performed for associations, and multi-regression was applied to identify any confounders.

RESULTS

Of 610 parents, 170 (27.9%) refused vaccination of their children. Of these, the majority of mothers had no education [n = 145 (85.3%); p = 0.03], and mothers were less likely to own a mobile phone than fathers [24 (14.1%) vs 152 (89.4%); p ≤ 0.001]. The vaccination refusal rate was higher in parents with food security [n = 88 (51.8%)] compared with parents with minimal food insecurity [n = 62 (36.5%)] and high food insecurity [20 (11.8%); p ≤ 0.05)]. On multi-variate logistic regression, fathers who were employed [adjusted odds ratio (OR) 0.59, 95% confidence interval (CI) 0.37-0.94; p = 0.02] and had a high level of education (adjusted OR 0.21, 95% CI 0.08-0.50; p ≤ 0.001) were less likely to refuse vaccination of their children. Parents with high food insecurity were more likely to refuse vaccination of their children (adjusted OR 2.2, 95% CI 1.0-0.50; p = 0.04) compared with parents with minimal food insecurity (adjusted OR 1.6, 95% CI 1.0-2.5; p = 0.02).

CONCLUSION

The vaccination refusal rate was very high among parents, and this was associated with inability to read or write, no education, owning a mobile phone, unemployment and food security.

Access and Use Experience of Personal Protective Equipment Among Frontline Healthcare Workers in Pakistan During the COVID-19 Emergency: A Cross-Sectional Study

Healthcare workers are at the highest risk of contracting novel coronavirus disease 2019 (COVID-19) and, therefore, require constant protection. This study assesses access to personal protective equipment (PPE), availability of adequate information about PPE use, self-reported ability to correctly wear and remove (donning and doffing) PPE, and risk perceptions associated with COVID-19 among frontline healthcare workers in Pakistan. Using a structured and validated questionnaire, an online survey was conducted from May 9 to June 5, 2020. Responses were received from 453 healthcare workers. Of these, 218 (48.12%) were doctors, 183 (40.40%) were nurses, and 52 (11.48%) were paramedical staff. Only 129 (28.48%) healthcare workers reported having adequate access to PPE at all times, whereas 156 (34.44%) never had access to PPE and 168 (37.09%) had access to PPE occasionally. Lack of access to PPE led the majority (71.74%) of healthcare workers to use coping strategies such as reuse of N95 and surgical masks. A total of 312 (68.87%) respondents believed that the risk of contracting COVID-19 in the work environment was high and the majority (62.69%) adopted precautionary measures at home to keep their families safe. A significantly high (n = 233, 51.43%, P = .03) number of respondents reported self-medicating. Of all the respondents, only 136 (30.02%) were tested for COVID-19 at least once, of which 32 (23.53%) ever tested positive. These findings suggest that healthcare workers in Pakistan had limited access to PPE. Adequate provision and training is vital to protect the healthcare workforce during the COVID-19 pandemic.