Search

Background: Increasing incidence has been seen among women of reproductive age with every one out of five women being affected by obesity. Obesity poses unfavorable outcomes for both mother and child causing ten percent of gestational diabetes and pre-eclampsia, neonatal deaths. Objective: To find the association of obesity in pregnancy with maternal and perinatal outcomes.The objective is to investigate the association between maternal obesity during pregnancy and various fetomaternal outcomes and outcome of occurrence of cesarean section deliveries, gestational diabetes, preeclampsia, macrosomia, low birth weight babies, and shoulder dystocia among pregnant women with obesity compared to non-obese pregnant women. The study will assess the relative risk and confidence intervals for all the described outcomes. Subject and Methods: This cohort study was performed in the Department of Obstetrics and Gynaecology, Kulsoom Bai Valika Hospital, site area, Karachi from February to August 2021. A total of 220 patients were included, 110 patients with a BMI equal to or more than 30 kg/m2 were exposed group and 110 cases BMI less than 30 kg/m2 were in the non-exposed group. A detailed history and examination, baseline investigations were carried out. Performa was given to patients of each group, and outcomes were recorded. Results: The average age of the patients was 28.73±6.52 years. The rate of cesarean section and PIH was 3 times more likely in obese groups than non-obese groups [RR=2.74 95%CI: 1.69-3.31] and [RR=3.08 95%CI: 2.11-4.49] respectively. The rate of GDM and preeclampsia was also 2 times more likely in the obese group than the non-obese group [RR=1.48 95%CI: 1.07-2.05] and [RR=2; 95%CI: 1.05-3.79] respectively. The rate of low birth weight was not statistically significant between obese and non-obese groups (p=0.053). While rate of macrosomia 7 times and Shoulder Dystocia time 5 more likely in obese groups than non- obese groups [RR=6.85; 95%CI: 3.24-14.48] and [RR=4.80; 95%CI: 2.56-8.99] respectively. Conclusion: Obesity is a challenge of the present era for obstetricians, which is reaching the status of epidemic worldwide. This study shows that obesity in pregnant females is directly proportional to poor fetomaternal outcomes, therefore pregnant obese females should be managed as a high-risk case.

Congenital bilateral absence of vas deferens (CBAVD) is a urological syndrome of Wolffian ducts and is responsible for male infertility and obstructive azoospermia. This study is designed to explore the integrity of exon 10 of CFTR and its role in male infertility in a cohort of CBVAD patients in Pakistan. Genomic DNA was extracted from 17 male patients with CBAVD having clinical symptoms, and 10 healthy controls via phenol-chloroform method. Exon 10 of the CFTR gene was amplified, using PCR with specific primers and DNA screening was done by Sanger sequencing. Sequencing results were analyzed using freeware Serial Cloner, SnapGene, BioEdit and FinchTV. Furthermore, bioinformatics tools were used to analyze the mutations and their impact on the protein function and stability. We have identified 4 mutations on exon 10 of CFTR in 6 out of 17 patients. Two of the mutations were missense variants V456A, K464E, and the other two were silent mutations G437G, S431S. The identified variant V456A was present in 4 of the studied patients. Whereas, the presence of K464E in our patients further weighs on the crucial importance for its strategic location to influence the gene function at post-transcriptional and protein level. Furthermore, Polyphen-2 and SIFT analyze the mutations as harmful and deleterious. The recurrence of V456A and tactically conserved locality of K464E are evidence of their potential role in CBAVD patients and in male infertility. The data can contribute in developing genetic testing and treatment of CBAVD.

Although batteries are a highly popular energy source in biosensors, batteries can be an economic limitation for low‐cost sensing applications and pose significant challenges in miniaturization, biocompatibility, and disposal. To surmount such issues, “self‐powered sensors” gain the spotlight thanks to their energy harvesting from the environment through embedded miniaturized systems. In this review, the recent developments in self‐powered devices are summarized with a specific focus on the integration of supercapacitors with sensors and biosensors. The working principles of microsupercapacitors, fabrication methods, their integration with biosensors, and their ultimate applications (i.e., biomedical monitoring and analytical biomarker detection) are described. Different energy harvesting systems are summarized and their integration with self‐powered sensors or biosensors is highlighted. The limitations and challenges of the existing approaches and the future of supercapacitor‐integrated sensing systems are also critically discussed.

IntroductionInconsistent results observed in recent phase III trials assessing chimeric antigenic receptor T (CAR-T) cell therapy as a second-line treatment compared to standard of care (SOC) in patients with relapsed/refractory diffuse large B-cell lymphoma (R/R DLBCL) prompted a meta-analysis to assess the effectiveness of CAR-T cell therapy in this setting.MethodsRandom-effects meta-analysis was conducted to pool effect estimates for comparison between CAR-T cell therapy and SOC. Mixed treatment comparisons were made using a frequentist network meta-analysis approach.ResultsMeta-analysis of three trials with 865 patients showed significant improvement in event-free survival (EFS: HR: 0.51; 95% CI: 0.27-0.97; I2: 92%), progression-free survival (PFS: HR: 0.47; 95% CI: 0.37-0.60; I2: 0%) with CAR-T cell therapy compared to SOC. Although there was a signal of potential overall survival (OS) improvement with CAR-T cell therapy, the difference was not statistically significant between the two groups (HR 0.76; 95% CI: 0.56 to 1.03; I2: 29%). Mixed treatment comparisons showed significant EFS benefit with liso-cel (HR: 0.37; 95% CI: 0.22-0.61) and axi-cel (HR: 0.42; 95% CI: 0.29-0.61) compared to tisa-cel.DiscussionCAR-T cell therapy, as a second-line treatment, appears to be effective in achieving higher response rates and delaying the disease progression compared to SOC in R/R DLBCL.

Introduction: Chemodynamic therapy (CDT) holds great promise in achieving cancer therapy through Fenton and Fenton-like reactions, which generate highly toxic reactive species. However, CDT is limited by the lower amount of catalyst ions that can decompose already existing intracellular H2O2 and produce reactive oxygen species (ROS) to attain a therapeutic outcome. Objectives: To overcome these limitations, a tailored approach, which utilizes dual metals cations (Ag+, Fe2+) based silver pentacyanonitrosylferrate or silver nitroprusside (AgNP) were developed for Fenton like reactions that can specifically kill cancer cells by taking advantage of tumor acidic environment without used of any external stimuli. Methods: A simple solution mixing procedure was used to synthesize AgNP as CDT agent. AgNP were structurally and morphologically characterized, and it was observed that a minimal dose of AgNP is required to destroy cancer cells with limited effects on normal cells. Moreover, comprehensive in vitro studies were conducted to evaluate antitumoral mechanism. Results: AgNP have an effective ability to decompose endogenous H2O2 in cells. The decomposed endogenous H2O2 generates several different types of reactive species (•OH, O2•−) including peroxynitrite (ONOO−) species as apoptotic inducers that kill cancer cells, specifically. Cellular internalization data demonstrated that in short time, AgNP enters in lysosomes, avoid degradation and due to the acidic pH of lysosomes significantly generate high ROS levels. These data are further confirmed by the activation of different oxidative genes. Additionally, we demonstrated the biocompatibility of AgNP on mouse liver and ovarian organoids as an ex vivo model while AgNP showed the therapeutic efficacy on patient derived tumor organoids (PDTO). Conclusion: This work demonstrates the therapeutic application of silver nitroprusside as a multiple ROS generator utilizing Fenton like reaction. Thereby, our study exhibits a potential application of CDT against HGSOC (High Grade Serous Ovarian Cancer), a deadly cancer through altering the redox homeostasis.

Abstract Rheumatoid arthritis (RA) is a systemic self-inflicted inflammatory disease that primarily affects middle-aged women. Globally, 1% of people live with RA. This review aims to provide updated information on the different aspects of RA, including its epidemiology, pathophysiology, diagnosis, treatment, and management. A web-based literature search was conducted through various databases, including PubMed, Google Scholar, and Science Direct, to identify the most relevant studies. Epidemiological studies have suggested that the prevalence and occurrence of RA have remained inconsistent across geographical areas in different periods. Many factors such as age, gender, inheritances, and environmental exposure can contribute to the severity of the disease. The acute form of RA usually presents with pain, and if left untreated, it can result in joint deformities and influence a patient's quality of life (QoL). RA diagnosis is usually based on the manifestation of pain with inflammation. Currently, many therapeutic strategies are available for the cure of RA. The management of daily routine activities is required with treatment to curtail the damage, avoid future deformities, and ultimately minimize the aching trouble of the patient.

Background: Gout is the most prevailing type of inflammatory arthropathy and its incidence has risen in recent decades. As previously no such research was found through an extensive literature survey, the current study aimed to evaluate gout patients residing in Lahore, Pakistan. Methods: To conduct this cross-sectional study, n=203 responses were obtained by a simple and objective-oriented questionnaire devised for the collection of data. Dependent variables association was measured by the Pearson Chi-square. A p-value

The clinical application of nanomaterials for chemodynamic therapy (CDT), which generate multiple reactive oxygen species (ROS), presents significant challenges. These challenges arise due to insufficient levels of endogenous hydrogen peroxide and catalytic ions necessary to initiate Fenton reactions. As a result, sophisticated additional delivery systems are required. In this study, a novel bimetallic copper (II) pentacyanonitrosylferrate (Cu(II)NP, Cu[Fe(CN) 5 NO]) material was developed to address these limitations. This material functions as a multiple ROS generator at tumoral sites by self-inducing hydrogen peroxide and producing peroxynitrite (ONOO-) species. The research findings demonstrate that this material exhibits low toxicity towards normal liver organoids, yet shows potent antitumoral effects on High Grade Serous Ovarian Cancer (HGSOC) organoid patients, regardless of platinum resistance. Significantly, this research introduces a promising therapeutic opportunity by proposing a single system capable of replacing the need for H2O2, additional catalysts, and NO-based delivery systems. This innovative system exhibits remarkable multiple therapeutic mechanisms, paving the way for potential advancements in clinical treatments.

Abstract Background Eukaryotic cells can rapidly adjust their transcriptional profile in response to molecular needs. Such dynamic regulation is, in part, achieved through epigenetic modifications and selective incorporation of histone variants into chromatin. H3.3 is the ancestral H3 variant with key roles in regulating chromatin states and transcription. Although H3.3 has been well studied in metazoans, information regarding the assembly of H3.3 onto chromatin and its possible role in transcription regulation remain poorly documented outside of Opisthokonts. Results We used the nuclear dimorphic ciliate protozoan, Tetrahymena thermophila, to investigate the dynamics of H3 variant function in evolutionarily divergent eukaryotes. Functional proteomics and immunofluorescence analyses of H3.1 and H3.3 revealed a highly conserved role for Nrp1 and Asf1 histone chaperones in nuclear influx of histones. Cac2, a putative subunit of H3.1 deposition complex CAF1, is not required for growth, whereas the expression of the putative ortholog of the H3.3-specific chaperone Hir1 is essential in Tetrahymena. Our results indicate that Cac2 and Hir1 have distinct localization patterns during different stages of the Tetrahymena life cycle and suggest that Cac2 might be dispensable for chromatin assembly. ChIP-seq experiments in growing Tetrahymena show H3.3 enrichment over the promoters, gene bodies, and transcription termination sites of highly transcribed genes. H3.3 knockout followed by RNA-seq reveals large-scale transcriptional alterations in functionally important genes. Conclusion Our results provide an evolutionary perspective on H3.3’s conserved role in maintaining the transcriptional landscape of cells and on the emergence of specialized chromatin assembly pathways.

Background and Objective: Hip strengthening exercises in patients with knee osteoarthritis is very beneficial the aim of study to determine combine effects of hip strengthening exercises with knee strengthening exercises on knee pain, function and activities of daily livings and quality of life in women with knee osteoarthritis. Methodology: In total, seventy women aged 40-70 year with knee OA, II–III grades on the Kellgren-Lawrence scale were included and randomized to experimental group (EG) and control group (CG) 35 in each group. The participants were going for 6-week supervised session, 4 times per week. The strengthening program consisted knee with hip strengthening exercises for EG, and only knee strengthening exercise for CG. Elastic Thera-Bands were used for resistance. KOOS was used for assessment and perform at baseline, 2nd week, 4th week and 6th week. Results: Finally 61 subjects were completed the study 31 in EG and 30 in CG. Results show that there were statistically and clinical significant improvements in the KOOS score in both groups from baseline to at 6th week. There was significant difference were observed in experimental group with mean pain 36.94±8.718 to 82.19±7.472 (p=0.051) in EG, & 22.97±4.165 to 72.53±5.237 (p=0.004) CG. The mean function 29.71±9.389 to 81.19±6.036 (p=0.000) EG & 24.14±4.927 to 67.94±3.984 (p=0.003) in CG and the mean Quality Of Life 27.06 ±7.806 to 60.61±10.148 (p=0.005) in EG & 24.30± 6.271 to 67.27± 7.821(p=0.000) in CG respectively. Conclusion(s): The combined knee strengthening exercise with hip strengthening exercises provide more significant enhancement in the clinical outcomes that are pain, function of daily living and quality of life in the women with osteoarthritis of the knee.

Objective: To determine the frequency of Cardiometabolic Risk Factors (CMRF) among young people with T2DM presenting at the Tertiary Care Unit in Karachi, Pakistan. Study Design: Retrospective longitudinal study. Place and Duration of Study: Baqai Institute of Diabetology and Endocrinology (BIDE), a Tertiary Care Unit, Karachi Pakistan, from Jan 2000 to Dec 2019. Methodology: The data of participants with diabetes (PWD) aged 18-45 years on the first visit was extracted from the computerized Health Management System (HMS). The demographics, anthropometric, biochemical, and medical information on obesity, smoking, hypertension, dyslipidemia, HbA1c, and family history of diabetes were gathered. Results: The study comprised 5336 participants with diabetes with a mean age of 31.94±5.52 years. High frequency of obesity, hypertension, dyslipidemia, cigarette smoking, poor glycemic control, and a positive family history of diabetes were observed, and their associations were statistically significant. Out of these, 4114(77.1%) were obese, 1663(31.4%) were hypertensive, 585(11%) were smokers, 4162(78%) had a positive family history of diabetes, 2519(47.2%) had HbA1c >10%, 2113(39.6%) had HbA1c between 7-10%. For dyslipidemia, 3383(63.4%) had high triglycerides, 3202(60%) had high LDL-C, 4578(85.8%) had low HDL-C, and 1729(32.4%) had high total cholesterol. Conclusion: The results validate the importance of early screening for CMRF in young diabetics for management and complications prevention in the early stages of the disease and advocate screening for CMRF in health care policy.

Greenfield investment is considered the backbone of emerging economies and developing countries. This research is carried out to investigate the causal impact of Greenfield investment as a target variable and some other controlled variables for the sample of 23 Latin American and Caribbean (LA&C) developing countries. The period is 1998–2017, and Levin, Lin and Chu (LLC) and System-Generalized Method of Moment (Sys-GMM) techniques are employed for analytical analysis. The Sys-GMM technique estimates show that Greenfield investment has a significant positive impact on these countries’ economic growth, health, education, and welfare. Furthermore, controlled variables remittances have a significant and positive impact, while foreign aid has a negative effect on the dependent variables. The rest of the other controlled variables show mixed results. From the analysis, it is suggested that Greenfield investment has improved per capita income, education and health sector that further enhanced the welfare of the society. In addition, new foreign investment creates job employment and brings innovations that improve labour skills. On the other hand, foreign aid must be avoided, which harms the economic activities of developing countries. Therefore, it is concluded that governments of Latin American and Caribbean developing countries adopt more friendly policies to attract Greenfield investment.

Electricity theft is the largest type of non-technical losses faced by power utilities around the globe. It not only raises revenue losses to the utilities but also leads to lethal fires and electric shocks at distribution side. In the past, field operation groups were sent by the utilities to conduct inspections of suspicions electric equipments stated by the public. Advanced metering infrastructure based recent development in the smart grids makes it easy to detect electricity thefts. However, the conventional supervised learning techniques have low theft detection performance mainly due to imbalance datasets available for training. Therefore, in this paper, we develop a novel theft detection model with twofold contribution. A unique hybrid sampling technique named as hybrid oversampling and undersampling using both classes (HOUBC) is proposed to balance the dataset. HOUBC first performs undersampling and then oversampling using both the majority (normal) and minority (theft) classes. A new deep learning method, fractal network is applied with light gradient boosting method to extract and learn important characteristics from electricity consumption profiles for identifying electricity thieves. The proposed model relies on smart meter's data for theft detection and hence, a rapid and widespread adaption of this model is feasible, which shows its main advantage. The performance of the model is evaluated with real-world smart meter's data, i.e., state grid corporation of China. Comprehensive simulation results describe the effectiveness of the proposed model against conventional schemes in terms of electricity theft detection.

Aspect-based sentiment analysis refers to the task of determining the sentiment polarity associated with particular aspects mentioned in a sentence or document. Previous studies have used attention-based neural network models to connect aspect terms with context words, but these models often perform poorly due to limited interaction between aspect terms and opinion words. Furthermore, these models typically focus only on explicitly stated aspect objects, which can be overly restrictive in certain scenarios. Current sentiment analysis methods that rely on aspect categories also often fail to consider the implicit placement of aspect-category information within the context. While existing models may produce strong results, they often lack domain knowledge. To address these issues, this study proposes an Aspect-position and Entity-oriented Knowledge Convolutional Graph (APEKCG) consisting of two modules: the Aspect position-aware module (APA) and the Entity oriented Knowledge Dependency Convolutional Graph (EKDCG). The APA module is designed to integrate aspect-specific sentiment features for sentiment classification by incorporating information about aspect categories into different parts of the context. The EKDCG module incorporates entity-oriented knowledge, dependency labels, and syntactic path using a dependence graph. Experimental results on five benchmarks Natural Language Processing (NLP) datasets of the English language demonstrate the effectiveness of the proposed APEKCG framework. Furthermore, the APEKCG outperformed previous state-of-the-art models with its accuracy, achieving 89.13%, 84.32%, 89.02%, 79.64%, and 90.22% on the MAMS, Laptop, Restaurant, AWARE, and SemEval-15&16 datasets, respectively.

Droplet microfluidics enables studying large cell populations in chemical isolation, at a single-cell resolution. Applications include studying cellular response to drugs, cell-to-cell interaction studies. Such applications need a reliable and repeatable droplet generation with high monodispersity. Most systems used in research rely on manual tuning of flow parameters on off-the-shelf instruments. Setups are highly customized, limiting reproduction of experimental results. We propose an integrated, modular system for automated aqueous droplet generation with high monodispersity. The system provides dynamic feedback control of droplet size and input pressure. Input pressure is generated by two piezoelectric micropumps. Droplet sizes are determined via light intensity measurement in an LED-photodiode setup. The system is capable of wireless communication and has a low enough power consumption for battery-powered operation. We report on the assembly and the underlying working principle, as well as an in-depth experimental evaluation of the performance of the proof-of-concept prototype in aqueous droplet generation. Evaluation was performed on a modular as well as on a system level. During module-level evaluations, aqueous droplets were generated in a light mineral oil + Span 80 surfactant carrier medium, using 3 different flow-focusing junction geometries. The presented prototype had a significantly faster pressure stabilization time (10 s) compared to a syringe pump-based reference setup (120 s). During system-level evaluation, deionized water droplets were generated in a carrier medium of HFE7500 + PEG-PFPE triblock surfactant. Resultant droplet sizes were benchmarked with microscopy. The system was able to repeatedly generate mono- and polydisperse droplets on demand, with CVs between 5-10% in the $\sim $ 50- $200 \mu \text{m}$ droplet diameter range.

In this work, we propose the Ritz approximation approach with a satisfier function to solve fractal-fractional advection–diffusion–reaction equations. The approach reduces fractal-fractional advection–diffusion–reaction equations to a system of algebraic equations; hence, the system can be solved easily to obtain the numerical solution for fractal-fractional advection–diffusion–reaction equations. With only a few terms of two variables-shifted Legendre polynomials, this method is capable of providing high-accuracy solution for fractal-fractional advection–diffusion–reaction equations. Numerical examples show that this approach is comparable with the existing numerical method. The proposed approach can reduce the number of terms of polynomials needed for numerical simulation to obtain the solution for fractal-fractional advection–diffusion–reaction equations.

Over the years, there has been a rise in the number of fabricated and fake news stories that utilize both textual and visual information formats. This coincides with the increased likelihood that users will acquire their news from websites and social media platforms. While there has been various research into the detection of fake news in text using machine learning techniques, less attention has been paid to the problem of multimedia data fabrication. In this paper, we propose a Stylometric, and Semantic similarity oriented for Multimodal Fake News Detection (SSM). There are five distinct modules that make up our methodology: Firstly, we used a Hyperbolic Hierarchical Attention Network (Hype-HAN) for extracting stylometric textual features. Secondly, we generated the news content summary and computed the similarity between Headline and summary. Thirdly, semantic similarity is computed between visual and textual features. Fourthly, images are analyzed for forgery. Lastly, the extracted features are fused for final classification. We have tested SSM framework on three standard fake news datasets. The results indicated that our suggested model has outperformed the base line and state-of-the-art methods and is more likely to detect fake news in complex environments.

This paper proposes a deep Reinforcement Learning (RL) based co-design approach for joint-optimization of wireless networked control systems (WNCS) where the co-design approach can help achieve optimal control performance under network uncertainties, e.g. delay and variable throughput. Compared to traditional and modern control methods where the dynamics of the system are important for predicting a system’s future response, a model-free approach can adapt to many applications of stochastic behaviour. Our work provides a comparison of how the control performance is affected by network uncertainties such as delays and bandwidth consumption under an unknown number of devices. The control data is transmitted under different network conditions where several applications transmit background traffic data using the same network. The problem contains several sub-optimization problems because the optimal number of devices is non-deterministic under network delay and channel capacity constraints. The proposed approach seeks to minimize control errors in wireless network control systems in order to improve Quality of Service and Quality of Control. This proposed approach is used and compared using three model-free RL Q-learning algorithms for high-throughput flow control in a double emulsion droplets formation application. The results show that the allowable number of devices for reliable network communication under bounded network constraints is 10 when using binary search. The control performance of the system without considering network effect in the reward function (Scenario 1) was good with the C51 algorithm; when including OMNet++ based network effect in the reward function (Scenario 2), the best performance was achieved with all three algorithms (C51, DQN, DDQN) with an exponential reward function, and only with C51 in the case of a linear reward function. Finally, under random network conditions (Scenario 3), C51 and DDQN performed well, but DQN did not converge. Comparisons with other machine learning and non-machine learning algorithms also highlight the superior performance of the utilized algorithms.

The implementation of high tunnels has shown to increase marketability and/or yield of tomato (Solanum lycopersicum) and lettuce (Lactuca sativa) crops compared with open-field systems. These structures provide the opportunity to alter light intensity and spectral quality by using specific polyethylene (poly) films and/or shadecloth, which may affect microclimate and subsequent crop productivity. However, little is known about how specific high tunnel coverings affect these parameters. The overall goal of this study was to evaluate the impact of various high tunnel coverings on the microclimate and crop productivity of tomato and lettuce. The coverings included standard, ultraviolet (UV)-stabilized poly film (standard); diffuse poly (diffuse); full-spectrum clear poly (clear); UV-A/B blocking poly (block); standard + 55% shadecloth (shade); and removal of standard poly 2 weeks before initial harvest to simulate a movable tunnel (movable). Microclimate parameters that were observed included canopy and soil temperatures, canopy growing degree-days (GDD), and photosynthetic active radiation (PAR), and crop productivity included yield and net photosynthetic rate. Hybrid red ‘BHN 589’ tomatoes were grown during the summer, and red ‘New Red Fire’ and green ‘Two Star’ leaf lettuce were grown in both spring and fall in 2017 and 2018. Increased temperature, GDD, and PAR were observed during the spring and summer compared with the fall. The soil temperatures during the summer increased more under the clear covering compared with the others. For tomato, the shade produced lower total fruit yield and net photosynthetic rate (Pn) compared with the other treatments, which were similar (P < 0.001 and

The proliferation and transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or the (COVID-19) disease, has become a threat to worldwide biosecurity. Therefore, early diagnosis of COVID-19 is crucial to combat the ongoing infection spread. In this study we propose a flexible aptamer-based electrochemical sensor for the rapid, label-free detection of SARS-CoV-2 spike protein (SP). A platform made of a porous and flexible carbon cloth, coated with gold nanoparticles, to increase the conductivity and electrochemical performance of the material, was assembled with a thiol functionalized DNA aptamer via S–Au bonds, for the selective recognition of the SARS-CoV-2 SP. The various steps for the sensor preparation were followed by using scanning electron microscopy, cyclic voltammetry and differential pulse voltammetry (DPV). The proposed platform displayed good mechanical stability, revealing negligible changes on voltammetric responses to bending at various angles. Quantification of SARS-CoV-2 SP was performed by DPV and chronopotentiometry (CP), exploiting the changes of the electrical signals due the [Fe(CN)6]3-/4- redox probe, when SARS-CoV-2 SP binds to the aptamer immobilized on the electrode surface. Current density, in DPV, and square root of the transition time, in CP, varied linearly with the log[ SARS-CoV-2 SP], providing lower limits of detection (LOD) of 0.11 ng/mL and 37.8 ng/mL, respectively. The sensor displayed good selectivity, repeatability, and was tested in diluted human saliva, spiked with different SARS-CoV-2 SP concentrations, providing LODs of 0.167 ng/mL and 46.2 ng/mL for DPV and CP, respectively.

Carcinoma ex pleomorphic adenoma is a neoplasm of the salivary gland that causes 3.6% of salivary gland tumours and 12% of salivary gland malignancies. It is a myoepithelial or epithelial neoplasm that arises from pleomorphic adenoma, whether primary or recurrent. Historically carcinoma ex pleomorphic adenoma is considered a high-grade malignancy. Salivary duct carcinoma and high-grade adenocarcinoma are the histologic types that most commonly arise in the background of Pleomorphic adenoma. However, 15% of tumours arising in Pleomorphic adenoma are considered low grade and have sluggish growth. Low-grade carcinoma ex pleomorphic adenoma can be difficult to differentiate from cellular pleomorphic adenoma. The case of a 56-year-old female patient who had neck swelling is being presented. The biopsy showed spindle cell component with mild atypia, invasion into surrounding tissue, and increased mitotic activity on the basis ---Continue

Abstract Background The gene NKX2-5 is a key transcription factor that plays an essential role in normal cardiac development. Although some recent studies have studied the role of polymorphisms in the NKX2-5 gene in congenital heart diseases (CHDs), the results were not consistent and remained uncertain. Therefore, we conduct a review of literature and investigate the association of genetic polymorphisms with CHDs. Results We selected seventeen studies regarding the association of NKX2-5 gene rs2277923 polymorphism with CHDs. Overall, in all the tested genetic models, the 63A > G polymorphism was not significantly associated with increased congenital heart defects risk. We used pooled odds ratios (OR) to calculate the association of CHDs with rs2277923 including allelic model: OR 1.00, 95% CI 0.82–1.21; homozygote model: OR 0.95, 95%CI 0.68–1.33, recessive model: OR 0.89 CI 0.70–1.13, heterozygote model: OR: 1.09, 95%CI 0.87–1.37, dominant model: OR 1.08 CI 0.82–1.42 and overdominant model: OR 1.17 CI 1.01–1.35. In addition, our analysis suggests that no publication bias exists in this meta-analysis. Conclusions Our findings suggested that 63A > G polymorphism in the NKX2-5 gene was not significantly associated with congenital heart defects. However, in the future, more studies with increased sample size are required that may provide us more definite conclusions.

Objective: To find out the prevalence of antibodies against cytomegalovirus and their association with adverse pregnancy outcome in women, at Isra University Hospital Hyderabad. Study Design: Cross-sectional study. Place and Duration of Study: Department of Gynaecology & Obstetrics, Isra University Hospital (IUH) Hyderabad, from Jan to Jun 2018. Methodology: Cytomegalovirus IgM and IgG antibodies in 305 women of reproductive age group were measured using the Enzyme Linked Fluorescent Assaysystem kit. Results: The combined positivity of anti cytomegalovirus IgG and IgM antibodies was 93 (30.40%). About 37 (37.37%) and 28 (34.14%) women were found to be seropositive for cytomegalovirus antibodies who had history of spontaneous miscarriage and recurrent miscarriages respectively. Conclusion: Higher association of seropositivity for cytomegalovirus IgM and IgG with bad obstetrical history and low economy was found.

In the modern era of the chemical science, the chemical graph theory has contributed significantly to exploring the properties of the chemical compounds. Currently, the computation of the topological indices is one of the most active directions of the research in the area of the chemical graph theory. The main feature of the study of the topological indices is its its ability of predicting the various physio-chemical properties. In this article, we compute several degree-based topological indices for the caboxy-terminated dendritic macromolecule. We compute Harmonic index, atom-bond connectivity index, geometric arithmetic index, sum connectivity index, inverse sum index, symmetric division degree, and Zagreb indices for caboxy-terminated dendritic macromolecule. The obtained results have potential to predict biochemical properties such as viscosity, entropy, and boiling point.

Abstract Background Numerous studies have investigated the role of apolipoprotein E (APOE) polymorphisms in coronary artery disease (CAD), but some controversies exist regarding the outcomes as the results were not consistent and remain uncertain. Therefore, the present meta-analysis was conducted to evaluate the association of APOE polymorphisms with coronary artery disease. Methods All the relevant studies published in English language till August 2020 were identified by searching through various electronic databases. The complete data was independently extracted by the two researchers. The data were analyzed by using the Comprehensive Meta-Analysis program and MetaGenyo program. The pooled odds ratio was used to check the associations between CAD and APOE polymorphisms. The following genetic models were used to calculate the odds ratio: ε2 vs. ε3 and ε4 vs. ε3. Results In the final analysis, we include 12 studies regarding the role of APOE polymorphism in CAD. The pooled odds ratio for ε4 allele was higher (OR 2.00; 95% and CI, 1.48–2.71). There is no statistical significant association for ε2 allele with CAD (OR 1.38; 95% CI, 1.18–1.62). This analysis showed no publication bias exists in the current meta-analysis. Conclusions Our findings suggest that the apolipoprotein ε4 allele appears as a significant genetic risk factor for coronary artery disease while the ε2 allele is beneficial to alleviate the CAD risk. Trial registration Registered with PROSPERO International Prospective Register of Systematic Reviews. PROSPERO registration number CRD42020190464

The task of analyzing sentiment has been extensively researched for a variety of languages. However, due to a dearth of readily available Natural Language Processing methods, Urdu sentiment analysis still necessitates additional study by academics. When it comes to text processing, Urdu has a lot to offer because of its rich morphological structure. The most difficult aspect is determining the optimal classifier. Several studies have incorporated ensemble learning into their methodology to boost performance by decreasing error rates and preventing overfitting. However, the baseline classifiers and the fusion procedure limit the performance of the ensemble approaches. This research made several contributions to incorporate the symmetries concept into the deep learning model and architecture: firstly, it presents a new meta-learning ensemble method for fusing basic machine learning and deep learning models utilizing two tiers of meta-classifiers for Urdu. The proposed ensemble technique combines the predictions of both the inter- and intra-committee classifiers on two separate levels. Secondly, a comparison is made between the performance of various committees of deep baseline classifiers and the performance of the suggested ensemble Model. Finally, the study’s findings are expanded upon by contrasting the proposed ensemble approach efficiency with that of other, more advanced ensemble techniques. Additionally, the proposed model reduces complexity, and overfitting in the training process. The results show that the classification accuracy of the baseline deep models is greatly enhanced by the proposed MLE approach.

In the current research, attempt is made to fabricate a nanoemulsion (NE) containing an antifungal agent. The prepared formulation has been expected to enhance skin penetration. It is also studied for in vitro drug release and toxicity assessment. Spontaneous titration method was used for preparation of NE. Prepared NE were characterized for their charge, size, morphology, rheological behaviour, drug release profile, skin permeability. The drug permeation and skin irritation were investigated. The in vitro antifungal activity was inspected using the well agar diffusion method. Miconazole NE showed good penetration in the skin as compared to marketed products. SEM showed semispherical shapes of the droplets. Zeta potential and zeta sizer showed that size was in nano ranges having positive charge.

Objective: To determine the microbiological profile and antimicrobial susceptibility pattern of microorganisms isolated from specimens of tracheal aspirate and endotracheal tube (ETT) tip. Methods: A descriptive cross-sectional study was conducted in a tertiary care hospital, Lahore, Pakistan during July 2016 to July 2017. The laboratory records of ETT tips and tracheal aspirate specimens was retrospectively reviewed. Standard microbiological procedures were followed for the isolation and the identification of microorganisms. Clinical and Laboratory Standards Institute (CLSI) 2016, guidelines were used Results: A total of 126 organisms were isolated from 121 specimens [Tracheal Aspirate 103 (85.1%) and ETT Tip 18 (14.9%)]. Most of the organisms were gram-negative 98 (77.78%), 17 (13.49%) were gram-positive and 11 (8.73%) were yeast. Of 98 gramnegative organisms, Acinetobacter spp was found in majority 61 (62.24%) followed by Klebsiella spp in 17 (17.34%), and Pseudomonas spp in 12 (12.24%). Of 17 gram-positive samples, Streptococcus spp was found in majority 6 (35.29%), followed by Methicillin-Resistant Staphylococcus aureus (MRSA) in 5 (29.41%), Staphylococcus epidermidis in 2 (11.76%), and Streptococcus Group D in 1 (5.88%). Candida was the only specie found in yeast. Acinetobacter was found highly resistant to all antibiotics except doxycycline, colistin and polymixin-b. Pseudomonas was sensitive to all the antibiotics except to ceftazidime (100% resistant). Klebsiella and MRSA showed high resistance to all the tested antibiotics. Conclusion: Gram-negative was the most common isolated bacteria from ETT tips and tracheal aspiration. Moreover, the specific isolates pattern of antimicrobial susceptibility showed a high resistance to widely used antibiotics.

Postharvest losses of fresh produce constitute the biggest portion of the total food losses occurring in food chains globally. The main driver behind the postharvest losses of fresh fruits and vegetables is temperature abuse occurring mainly during transportation and storage. This is a particular problem for small-acreage producers, who frequently have limited access to postharvest handling resources like optimum refrigeration conditions. Passive modified atmosphere packaging (MAP) is a relatively inexpensive intervention that does not require specialized equipment and has demonstrated some potential for maintaining the quality and extending the shelf life of fresh produce stored in nonoptimum temperatures. Our objective was to determine the effect of passive MAP on the quality and storage life of spinach (Spinacia oleracea cv. Corvair) when stored in nonoptimum temperatures. Mature spinach leaves (≈320 g) were packaged in passive MAP bags, developed using the BreatheWay technology, and non-MAP produce bags and subsequently stored at 13 or 21 °C. Spinach physical and nutritional quality was evaluated throughout its storage life in terms of overall quality, water loss, leaf tenderness, surface color, chlorophyll content, electrolyte leakage, chlorophyll fluorescence, antioxidant capacity, total phenolic content, and vitamin C content. Spinach that was stored in MAP bags reached headspace equilibrium at ≈6% Ο2 and 11% CΟ2 at 13 °C and ≈4% Ο2 and 8% CΟ2 at 21 °C after 2 days of storage for both temperatures. The spinach stored in passive MAP at 13 or 21 °C demonstrated significantly higher overall quality during storage and 2 and 1 day longer storage life, respectively, when compared with the control. The spinach in passive MAP demonstrated a slower rate of yellowing and water loss during storage. The limiting factor for the spinach stored in MAP was decay due to condensation at 13 °C and yellowing at 21 °C. There were no statistical differences in the examined nutritional quality parameters between the spinach stored in MAP and produce bags. This study shows that passive MAP can be a valuable tool for reducing the food losses occurring in small-acreage fruit and vegetable operations that have limited access to cooling and refrigerated storage.

This contribution attempts to discuss the current scenario of rare material available in the libraries of Lahore city. Lahore is capital of Punjab province of Pakistan. The study seeks to explore the various aspects such as acquisition, organization, access, preservation & conservation of rare material of libraries of Lahore, Pakistan. The study is qualitative in nature; based on multiple case study design. A multiple case study helps the researchers in finding the differences among cases. Semi-structured interview guide was used as data collection tool. The observation and document analysis of log registers of the cases (libraries) were also done wherever facilitated. It was found that rare collection is underutilized in the libraries of Lahore. Findings also established that separate funds are not allocated to the public libraries of Lahore for acquisition and management of the rare material. This paper identifies the current status and issues in acquisition, management, access and use of rare material at public libraries of Lahore, Pakistan.

Schwannoma, also called neurilemomma is a benign neoplasm. It originates from Schwann cells which are involved in myelination of peripheral nerves and commonly occur in the soft tissues of the head and neck. Intraosseous schwannoma is rare and accounts for only 0.2% of overall primary bone tumours. Merely 200 cases have been reported in the literature. Intraosseous schwannoma of long bones is even rarer, amounting for only 20 cases reported. We present a case of intraosseous Schwannoma in the distal shaft of the fibula, in an 18-year-old female patient who presented with pain in the right leg for 2 years. MRI showed a lytic lesion, with a differential diagnosis of aneurysmal bone cyst. The tumour was excised and on histopathological examination, a diagnosis of intraosseous schwannoma was made. Keywords: Neurilemmoma, Fibula, Schwannoma, Intraosseous.

Summary: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) protein is essential for viral replication, making it a promising target for antiviral drug and vaccine development. SARS-CoV-2 infected patients exhibit an uncoordinated immune response; however, the underlying mechanistic details of this imbalance remain obscure. Here, starting from a functional proteomics workflow, we cataloged the protein–protein interactions of SARS-CoV-2 proteins, including an evolutionarily conserved specific interaction of N with the stress granule resident proteins G3BP1 and G3BP2. N localizes to stress granules and sequesters G3BPs away from their typical interaction partners, thus attenuating stress granule formation. We found that N binds directly to host mRNAs in cells, with a preference for 3′ UTRs, and modulates target mRNA stability. We show that the N protein rewires the G3BP1 mRNA-binding profile and suppresses the physiological stress response of host cells, which may explain the imbalanced immune response observed in SARS-CoV-2 infected patients.

Plasmablastic lymphoma is an aggressive, high-grade non-Hodgkin lymphoma predominantly seen in HIV-infected individuals. Alongside a strong correlation with HIV, PBL can manifest in immunocompromised HIV-negative patients. A rare case of PBL in an immunocompetent and otherwise healthy child presented to Indus Hospital & Health Network (IHHN), Karachi, Pakistan. The patient had complaints of swelling and pain in the right leg and was referred from a city in Interior Sindh. Histopathological analysis revealed sheets and aggregates of neoplasm replacing bone marrow interspersed with sclerotic bony fragments. Large, monomorphic, multinucleated neoplastic cells containing abundant cytoplasm and scattered pleomorphic cells were also noted, leading to the diagnosis of tibial plasmablastic lymphoma. A FAB/LMB96 group C chemotherapy regimen for aggressive and high-risk cancer was administered with a marked improvement in clinical symptoms.

News media agencies are known to publish misinformation, disinformation, and propaganda for the sake of money, higher news propagation, political influence, or other unfair reasons. The exponential increase in the use of social media has also contributed to the frequent spread of fake news. This study extends the concept of symmetry into deep learning approaches for advanced natural language processing, thereby improving the identification of fake news and propaganda. A hybrid HyproBert model for automatic fake news detection is proposed in this paper. To begin, the proposed HyproBert model uses DistilBERT for tokenization and word embeddings. The embeddings are provided as input to the convolution layer to highlight and extract the spatial features. Subsequently, the output is provided to BiGRU to extract the contextual features. The CapsNet, along with the self-attention layer, proceeds to the output of BiGRU to model the hierarchy relationship among the spatial features. Finally, a dense layer is implemented to combine all the features for classification. The proposed HyproBert model is evaluated using two fake news datasets (ISOT and FA-KES). As a result, HyproBert achieved a higher performance compared to other baseline and state-of-the-art models.

Sentiment analysis is an ongoing research field within the discipline of data mining. The majority of academics employ deep learning models for sentiment analysis due to their ability to self-learn and process vast amounts of data. However, the performance of deep learning models depends on the values of the hyperparameters. Determining suitable values for hyperparameters is a cumbersome task. The goal of this study is to increase the accuracy of stacked autoencoders for sentiment analysis using a heuristic optimization approach. In this study, we propose a hybrid model GA(SAE)-SVM using a genetic algorithm (GA), stacked autoencoder (SAE), and support vector machine (SVM) for fine-grained sentiment analysis. Features are extracted using continuous bag-of-words (CBOW), and then input into the SAE. In the proposed GA(SAE)-SVM, the hyperparameters of the SAE algorithm are optimized using GA. The features extracted by SAE are input into the SVM for final classification. A comparison is performed with a random search and grid search for parameter optimization. GA optimization is faster than grid search, and selects more optimal values than random search, resulting in improved accuracy. We evaluate the performance of the proposed model on eight benchmark datasets. The proposed model outperformed when compared to the baseline and state-of-the-art techniques.

OBJECTIVE: To observe frequency of cardiometabolic risk factors (CMRF) among young people with type 2 diabetes mellitus (T2DM). METHODS: This retrospective study was conducted at Baqai Institute of Diabetology and Endocrinology, Baqai Medical University, Karachi-Pakistan. Data of all patients of T2DM aged 18-45 years, from 1st January-2000 to 31st December-2019 of first patient visit was retrieved and analyzed from computerized hospital management system record. Age, gender, duration of diabetes, smoking habit, family history of diabetes, glycemic status, fasting lipid profile, blood pressure and body-mass-index was noted to assess CMRF in T2DM. RESULTS: Out of 5336, 54.5% (2907) were male and 1643 (30.8%) people were newly diagnosed. Mean age of patients at diagnosis of diabetes was 31.94±5.52 years, mean age at first out-patient department (OPD) visit was 35.52±4.58 years and mean diabetes duration was 3.52±3.58 years. At time of first OPD visit 3878 (77.1%) were obese, 585 (11%) were smokers and 1663 (31.4%) were hypertensive. Furthermore, 4161 (78%) had positive family history for diabetes, 1274 (47.2%) had HbA1c >10%, 1069 (39.6%) had 7-10% and 357 (13.2 %) had

This review is aimed at provision of an updated knowledge about the gout and highlights the various areas which need to be focused for better healthcare. Relevant published articles in English Language were reviewed by utilizing various available databases including: Google Scholar, Springer Link, Science Direct and MEDLINE. The data reveal a precipitating number of gout cases from the developed countries, while the developing countries on the other hand are faced with an even higher threat. The risk factors and pathophysiology of gout are immaculate and clearly established. Hence, appropriate measures can be explored and worked on to pinpoint diagnosis, effective and economical treatment. Continuous...

Numerous studies have been conducted to meet the growing need for analytic tools capable of processing increasing amounts of textual data available online, and sentiment analysis has emerged as a frontrunner in this field. Current studies are focused on the English language, while minority languages, such as Roman Urdu, are ignored because of their complex syntax and lexical varieties. In recent years, deep neural networks have become the standard in this field. The entire potential of DL models for text SA has not yet been fully explored, despite their early success. For sentiment analysis, CNN has surpassed in accuracy, although it still has some imperfections. To begin, CNNs need a significant amount of data to train. Second, it presumes that all words have the same impact on the polarity of a statement. To fill these voids, this study proposes a CNN with an attention mechanism and transfer learning to improve SA performance. Compared to state-of-the-art methods, our proposed model appears to have achieved greater classification accuracy in experiments.

Educational Robotics (ER) is an upcoming trend in education. It has been introduced in classrooms to improve the learning environment. It provides opportunities for young learners by promoting knowledge-building activities. STEM (Science, Technology, Engineering, and Mathematics) education is viewed as a catalyst to ensure a successful future in the context of real-world issues. ER is an innovative tool that can provide a roadmap for quality education. This study aims to investigate "What skill-set does ER (Educational Robotics) develop in young learners?", "How does robotics intervention affect young learners?", and "Whether Educational Robotics (ER) facilitates STEM education?". We systematically reviewed the literature on robotics and the importance of STEM, identifying the role of robotics in both formal and informal elementary and secondary classrooms, after-school programs, and summer camp activities. We used the PRISMA (Preferred Reporting Items for Systematic Review and Meta-Analysis) methodology to analyze 20 relevant articles. We searched articles by using keywords and the snowballing technique. The study of recent applications of ER suggests that it aids in a precise and flexible understanding of STEM concepts.

Cancer has been a fatal disease since many decades. Over the time, it is presented in multiple ways and is a matter of consideration as accounts for the high rate of mortality. The aim of the current review was to focus on the genetics, epigenetics factors and role of medicinal plants for the cure of this inimical disease. Related articles available in English language (2002-2018) were reviewed with help of different database, including PubMed, Springer Link, Medline, Google Scholar and ScienceDirect. In order to ensure credibility and accuracy of data only those articles were considered which are published in indexed journals i.e. Web of Science and Scopus. This project was conducted at the Department of Pharmacy, Government College University, Faisalabad, Pakistan from 02-01-2019 to 28-02-2019. The genetic machinery is vibrantly involved in the interpretation of the signals and is observed to be affected by various dietary factors. A sequence of modified activities is observed with use of these dietary elements. However, the modification is reviewed through the histone acetyltransferase (HAT), histone deacetylase (HDAC) and DNA methyl transferase (DNMTs), effecting the expression of gene. These modified genes, in turn then express the signals in multiple reformed ways. Different dietary elements that are used such as polyphenol, alkaloid and flavonoids are effective against cancer. The progression of disease involves genetics and epigenetics due to amplification, translocation and mutation during gene expression. Though, many studies have been conducted elaborating the role of plants and their ingredients which play a part in inhibition of cancerous cells by blockade of cell cycle and apoptosis; more in-depth investigations are still required to identify the new drug target and novel therapeutic modalities.

BackgroundOne challenge for primary care providers caring for patients with nonalcoholic fatty liver disease is to identify those at the highest risk for clinically significant liver disease.AimTo derive a risk stratification tool using variables from structured electronic health record (EHR) data for use in populations which are disproportionately affected with obesity and diabetes.MethodsWe used data from 344 participants who underwent Fibroscan examination to measure liver fat and liver stiffness measurement [LSM]. Using two approaches, multivariable logistic regression and random forest classification, we assessed risk factors for any hepatic fibrosis (LSM > 7 kPa) and significant hepatic fibrosis (> 8 kPa). Possible predictors included data from the EHR for age, gender, diabetes, hypertension, FIB-4, body mass index (BMI), LDL, HDL, and triglycerides.ResultsOf 344 patients (56.4% women), 34 had any hepatic fibrosis, and 15 significant hepatic fibrosis. Three variables (BMI, FIB-4, diabetes) were identified from both approaches. When we used variable cut-offs defined by Youden's index, the final model predicting any hepatic fibrosis had an AUC of 0.75 (95% CI 0.67-0.84), NPV of 91.5% and PPV of 40.0%. The final model with variable categories based on standard clinical thresholds (i.e., BMI ≥ 30 kg/m2; FIB-4 ≥ 1.45) had lower discriminatory ability (AUC 0.65), but higher PPV (50.0%) and similar NPV (91.3%). We observed similar findings for predicting significant hepatic fibrosis.ConclusionsOur results demonstrate that standard thresholds for clinical risk factors/biomarkers may need to be modified for greater discriminatory ability among populations with high prevalence of obesity and diabetes.

The study aimed to explore the Research Data Management (RDM) practices of university faculty members through qualitative research design. The data was collected through semi-structured, in-depth interviews from purposely selected ten faculty members from the University of Punjab (PU). The study discovered some significant factors including RDM and curation practices, the amount of research data produced, the support needed for data curation and their willingness to share it. In addition, the study explored issues the researchers face with regards to RDM. The findings reveal that respondents need assistance regarding storage and security of data, improving the quality of backup, support for storage and preservation. They agreed with a need for a central repository of the University.