Comparative study of Primary Suturing Versus V-Y Advancement Flap Technique in Resurfacing Post Excisional Defect in Cases with Pilonidol Sinus Disease

BACKGROUND: Multiple treatments has been identified for pilonidal disease but no protocol has been designed and studies emerged by comparing treatment cost, morbidity, and return to work state The primary aim of advancement flap is to transfer the scar tension that obtained from side-to-side closure to good cosmetical closure from flap. For putting the flap, we need to know its dynamics. First step is movement of flap into the defect created by excision of pilonidal sinus. Flap movement demonstrates secondary defect. Primary purpose of flap is to closing the primary defect, while reducing secondary defect size. AIM AND OBJECTIVES To compare the rate of occurrence and nature of complications in primary suturing and v-y advancement flap technique in resurfacing post excisional defect in cases with pilonidal sinus disease. MATERIAL AND METHODS: The study was a prospective, parallel group, comparative study among patients admitted with pilonidal sinus in general surgery wards at Govternment Rajaji Hospital, Madurai Medical College, Madurai. Fifty patients were randomized into two groups of primary suturing and v-y advancement flap. Complications in both intraoperative and postoperative periods were noted and patients were followed up for 6months. RESULTS: The male : female ratio was noted to be approximately 5:1. The mean age of presentation of pilonidal disease is in the mid-twenties. Occupation has a role in the development of pilonidal disease. It seen in people who have a work pertaining to prolonged duration of sitting and close to vibrating surface. Disease is common in hirsute males with deep natal cleft and presence of sinus (single and/or multiple) is almost a constant feature of all patients who presented with pilonidal disease. The incidence of increased body mass index with the incidence and even recurrence of pilonidal sinus. The most common organisms found in the pilonidal sinus are the anaerobic organisms. Wound infection which was more (p value-0.04 significant) in primary suturing. Wound dehiscence was more (p value-0.04 significant) in the patients undergoing primary closure. Collection which was noted in patients undergoing both primary suturing and flap study. Recurrence rate is more (p value-0.018 significant) with primary suturing when compared with v-y advancement flap. Our study shows the hospital stay duration found to be very less (p value-0.000 significant) in patients treated with flap procedures than who underwent primary suturing. CONCLUSION: Pilonidal sinus is found more commonly in hairy, obese males with sedentary life style. It is treated more effectively, with no recurrence rate and less complications by wide local excision followed by asymmetric closure by unilateral or bilateral V-Y fascio-cutaneous advancement flap than primary closure

Paediatric multisystem inflammatory syndrome temporally associated with SARS-CoV-2 (PIMS-TS): Prospective, national surveillance, United Kingdom and Ireland, 2020

Background: Paediatric Multisystem Inflammatory Syndrome temporally associated with SARS-CoV-2 (PIMS-TS), first identified in April 2020, shares features of both Kawasaki disease (KD) and toxic shock syndrome (TSS). The surveillance describes the epidemiology and clinical characteristics of PIMS-TS in the United Kingdom and Ireland. Methods: Public Health England initiated prospective national surveillance of PIMS-TS through the British Paediatric Surveillance Unit. Paediatricians were contacted monthly to report PIMS-TS, KD and TSS cases electronically and complete a detailed clinical questionnaire. Cases with symptom onset between 01 March and 15 June 2020 were included. Findings: there were 216 cases with features of PIMS-TS alone, 13 with features of both PIMS-TS and KD, 28 with features of PIMS-TS and TSS and 11 with features of PIMS-TS, KD and TSS, with differences in age, ethnicity, clinical presentation and disease severity between the phenotypic groups. There was a strong geographical and temporal association between SARS-CoV-2 infection rates and PIMS-TS cases. Of those tested, 14.8% (39/264) children had a positive SARS-CoV-2 RT-PCR, and 63.6% (75/118) were positive for SARS-CoV-2 serology. In total 44·0% (118/268) required intensive care, which was more common in cases with a TSS phenotype. Three of five children with cardiac arrest had TSS phenotype. Three children (1·1%) died. Interpretation: the strong association between SARS-CoV-2 infection and PIMS-TS emphasises the importance of maintaining low community infection rates to reduce the risk of this rare but severe complication in children and adolescents. Close follow-up will be important to monitor long-term complications in children with PIMS-T

Prediction of COVID-19 patient using supervised machine learning algorithm

One of the most symptomatic diseases is COVID-19. Early and precise physiological measurement-based prediction of breathing will minimize the risk of COVID-19 by a reasonable distance from anyone; wearing a mask, cleanliness, medication, balanced diet, and if not well stay safe at home. To evaluate the collected datasets of COVID-19 prediction, five machine learning classifiers were used: Nave Bayes, Support Vector Machine (SVM), Logistic Regression, K-Nearest Neighbour (KNN), and Decision Tree. COVID-19 datasets from the Repository were combined and re-examined to remove incomplete entries, and a total of 2500 cases were utilized in this study. Features of fever, body pain, runny nose, difficulty in breathing, shore throat, and nasal congestion, are considered to be the most important differences between patients who have COVID-19s and those who do not. We exhibit the prediction functionality of five machine learning classifiers. A publicly available data set was used to train and assess the model. With an overall accuracy of 99.88 percent, the ensemble model is performed commendably. When compared to the existing methods and studies, the proposed model is performed better. As a result, the model presented is trustworthy and can be used to screen COVID-19 patients timely, efficiently

Coupled model for simulation of indoor airflow and pollutant transport

Understanding airflow in buildings is essential for improving energy efficiency, controlling airborne pollutants, and maintaining occupant comfort. Recent research on whole-building airflow simulation has turned toward protecting occupants from threats of chemical or biological agents. Sample applications include helping design systems to reduce exposure, and selecting optimal sensor locations. Multizone models and computational fluid dynamics (CFD) provide complementary approaches to predicting airflows in buildings. Multizone models treat a building as a collection of well-mixed zones, connected by flow paths such as doors, windows, etc. These zone-to-zone airflows carry contaminants around the building. However, the multizone formulation assumes that pollutants mix perfectly and instantaneously within each zone. For large spaces that take a long time to mix, these models cannot assess occupant exposures, or guide decisions about sensor placement or ventilation strategy. Furthermore, since the airflow in most large spaces couples tightly to the rest of the building (through doors and ventilation systems), errors due to neglecting the room details eventually propagate to the rest of the solution

Optimized Convolutional Neural Network for Automatic Detection of COVID-19

International audienceThe outbreak of COVID-19 affected global nations and is posing serious challenges to healthcare systems across the globe. Radiologists use X-Rays or Computed Tomography (CT) images to confirm the presence ofCOVID-19. So, image processing techniques play an important role in diagnostic procedures and it helps the healthcare professionals during critical times. The current research work introduces Multi-objective Black Widow Optimization (MBWO)-based Convolutional Neural Network i.e., MBWOCNN technique for diagnosis and classification of COVID-19. MBWOCNN model involves four steps such as preprocessing, feature extraction, parameter tuning, and classification. In the beginning, the input images undergo preprocessing followed by CNN-based feature extraction. Then, Multi-objective Black Widow Optimization (MBWO) technique is applied to fine tune the hyperparameters of CNN. Finally, Extreme Learning Machine with autoencoder (ELM-AE) is applied as a classifier to confirm the presence of COVID-19 and classify the disease under different class labels. The proposed MBWO-CNN model was validated experimentally and the results obtained were compared with the results achieved by existing techniques. The experimental results ensured the superior results of the ELM-AE model by attaining maximum classification performance with the accuracy of 96.43%.The effectiveness of the technique is proved through promising results and the model can be applied in diagnosis and classification of COVID-19

Potent GCN2 Inhibitor Capable of Reversing MDSC-Driven T Cell Suppression Demonstrates In Vivo Efficacy as a Single Agent and in Combination with Anti-Angiogenesis Therapy

General control nonderepressible 2 (GCN2) protein kinase is a cellular stress sensor within the tumor microenvironment (TME), whose signaling cascade has been proposed to contribute to immune escape in tumors. Herein, we report the discovery of cell-potent GCN2 inhibitors with excellent selectivity against its closely related Integrated Stress Response (ISR) family members heme-regulated inhibitor kinase (HRI), protein kinase R (PKR), and (PKR)-like endoplasmic reticulum kinase (PERK), as well as good kinome-wide selectivity and favorable PK. In mice, compound 39 engages GCN2 at levels ≥80% with an oral dose of 15 mg/kg BID. We also demonstrate the ability of compound 39 to alleviate MDSC-related T cell suppression and restore T cell proliferation, similar to the effect seen in MDSCs from GCN2 knockout mice. In the LL2 syngeneic mouse model, compound 39 demonstrates significant tumor growth inhibition (TGI) as a single agent. Furthermore, TGI mediated by anti-VEGFR was enhanced by treatment with compound 39 demonstrating the complementarity of these two mechanisms