Association of renal biomarkers in COVID-19 patients: A retrospective study

Background: The new severe acute respiratory syndrome coronavirus 2 is the cause of the transmissible sickness known as coronavirus disease 2019 (COVID-19) (SARS-CoV-2). Although it often presents as an acute respiratory infection, it can also have a negative impact on the kidneys, heart, gastrointestinal, and nervous system. The aims of this study to find out the association of renal biomarkers among dialysis patients in COVID-19 positive and negative. Methods: A retrospective study was conducted in the Department of medical laboratory technology, the university of Haripur, Khyber Pakhtunkhwa, Pakistan. A Total of 129 Dialysis patients blood samples were collected from March 2022 to April 2022 in which 13 males and 20 females are COVID-19 positive while 41 males and 55 females are COVID-19 negative. The obtained data was statistically analyzed by using PRISM version 5.0 by applying two-way ANOVA and Comparisons between Covid positive and negative patients RFTs by using Bonferroni posttest. Results: Male patients with chronic kidney disease (on dialysis) with COVID-19 negative and positive their mean urea difference was 95.20mg/dl and 159.6mg/dl, while COVID-19 negative and positive the mean creatinine difference was 8.534mg/dl and 13.81mg/dl respectively. While there was no significance difference in uric acid concentration in CKD patients with COVID-19 negative and positive. Female patients with chronic kidney disease (on dialysis) with COVID-19 negative and positive their mean urea difference was 103.20mg/dl and 152.6mg/dl, while COVID-19 negative and positive the mean creatinine difference was 8.114mg/dl and 8.584mg/dl respectively. While there was no significance difference in uric acid concentration in CKD patients with COVID-19 negative and positive. Conclusion: This study concludes that there is positive relationship or association of renal biomarkers in COVID-19 positive patients. Significance association between urea and creatinine in COVID-19 positive

Frequency of Post-Operative Fecal Incontinence and Healing Rate in Patients with Open and Closed Lateral Internal Anal Sphincterotomy

OBJECTIVES This study aims to compare the frequency of fecal incontinence and healing rate in patients treated with Open Internal Anal Sphincterotomy (OIAS) and Closed Lateral Internal Anal Sphincterotomy (CLIAS). METHODOLOGY This randomized control trial was carried out in the Department of Surgery Hayatabad Medical Complex, Peshawar Pakistan from Feb 2019 to Feb 2020. Eighty-four patients were assigned to the open method in Group B while eighty-four patients were allocated to the closed method in Group A (using blade 11) through the randomized control trial method. Fecal incontinence and healing rate were observed on the 7 th postoperative day. SPSS 23.0 software was used to analyse the data. RESULTS In group A out of a total of 84 patients, 96% of patients were in category A, 4% of patients were in category B, and no patients were in categories C and D. In group B out of 84 patients, 96% of patients were in category A while 4% patients were in category B and no patients were in category C and D. The total faecal incontinence in Group B (open method) was 21% while total fecal incontinence in Group A (closed method) was only 4% that is a clear dierence between the two groups. In group A (closed method) out of 84 patients, 2 patients (2.38 %) showed delayed healing while 82 patients (97.61 %) showed normal healing. In group B (open method) 7.4% of patients showed delayed healing with a signicance p level of 0.04 while 92.85 showed normal healing. CONCLUSION Fecal incontinence was less in closed Lateral Anal Sphincterotomy due to the use of blade 11 while it was higher in open internal anal sphincterotomy. Similarly, the healing rate was signicantly higher in the closed method while delayed healing was seen in the open method

An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals

publishedVersio

Exploring Lightweight Deep Learning Solution for Malware Detection in IoT Constraint Environment

: The present era is facing the industrial revolution. Machine-to-Machine (M2M) communication paradigm is becoming prevalent. Resultantly, the computational capabilities are being embedded in everyday objects called things. When connected to the internet, these things create an Internet of Things (IoT). However, the things are resource-constrained devices that have limited computational power. The connectivity of the things with the internet raises the challenges of the security. The user sensitive information processed by the things is also susceptible to the trusability issues. Therefore, the proliferation of cybersecurity risks and malware threat increases the need for enhanced security integration. This demands augmenting the things with state-of-the-art deep learning models for enhanced detection and protection of the user data. Existingly, the deep learning solutions are overly complex, and often overfitted for the given problem. In this research, our primary objective is to investigate a lightweight deep-learning approach maximizes the accuracy scores with lower computational costs to ensure the applicability of real-time malware monitoring in constrained IoT devices. We used state-of-the-art Recurrent Neural Network (RNN), Long Short-Term Memory (LSTM), and Bi-directional LSTM deep learning algorithm on a vanilla configuration trained on a standard malware dataset. The results of the proposed approach show that the simple deep neural models having single dense layer and a few hundred trainable parameters can eliminate the model overfitting and achieve up to 99.45% accuracy, outperforming the overly complex deep learning models.publishedVersio

Seed Treatment of Capsicum annuum with Two Different Fungicides to Evaluate the Seed Germination Rate

Chili (Capsicum annuum L.) is the fruit of plants, the Chili is susceptible for several diseases and seed borne fungi Phytophthora capsici which produces collar rot and root of chili. Seed borne pathogens are associated with untreated seeds of chili which are also significantly reduced the germination of seed. This experiment was conducted to find out the seed borne fungi and enhanced the germination of chili (Capsicum annuum) with two fungicides known as Mancozeb 80% WP and Carbendazim 50% WP. Effectiveness of these two fungicides were measured when the seeds planted on blotter paper in petri plates at 270C under lab conditions. These two fungicides significantly reduce the effect of seed borne fungi associated with chili seeds. Mancozeb 80% WP was found most effective to reduce the effect of seed borne fungi and increase the seed germination. Considering the results of the experiment, Mancozeb 80% WP was noted to be a best fungicide against the seed borne fungi. Keywords: Capsicum annuum, Mancozeb, Carbendazim, seed borne fungi, blotter paper. DOI: 10.7176/JBAH/10-4-04 Publication date: February 29th 2020