Clinical Profile and Genetic studies in Recurrent Acute Pancreatitis : A Five Year Study.

INTRODUCTION : Numerous studies have been conducted on acute and chronic pancreatitis , but only few have focused on recurrent acute pancreatitis(RAP). Recurrent acute pancreatitis may be due to biliary disease, alcohol, metabolic factors (hypercalcemia, hypertriglyceridemia), drugs, trauma, sphincter of Oddi dysfunction, pancreas divisum and pancreatic carcinoma. Evaluation fails to detect the cause in 10 – 30% of patients , and these patients are labelled as idiopathic recurrent acute (IAP) pancreatitis(IRAP). Further evaluation and therapy is important because more than 50% of untreated patients with RAP experience recurrent episodes that can lead to chronic pancreatitis Mutations in cationic trypsinogen gene (PRSS1) , SPINK1 gene ,cystic fibrosis transmembrane conductance regulator gene (CFTR) and Cathepsin B gene have been demonstrated in acute and chronic pancreatitis(3-6). It is possible that genetic mutations may be the cause of pancreatitis in patients now labelled as Idiopathic Recurrent Pancreatitis. Few patients with gall stones or alcoholism develop RAP. It is therefore conceivable that genetic mutations enhance susceptibility to RAP in patients with other predisposing factors. RAP may be a complex disease process resulting from an interplay of genetic susceptibilities and environmental factors. AIMS AND OBJECTIVES : 1. To study the clinical profile, efficacy of medical / endoscopic therapy and outcome of recurrent acute pancreatitis. 2. To assess the prevalence of genetic mutations in recurrent acute pancreatitis. CONCLUSIONS: Biliary disease (stone (20%); sludge / microlithiasis (28%) is the most common cause of recurrent acute pancreatitis (RAP). Determining etiology is important to assess the progressive nature of the disease . The extent of evaluation impacts the frequency with which an etiology can be found. Bile for microliths and ERCP should therefore be part of evaluation of RAP as these detect the etiology in 1/3rd of patients. Distribution of etiological factors was similar in East , South and North India. After extensive evaluation including ERCP and testing bile for microliths , a cause for RAP could not be detected in 18% of patients. Genetic mutations do not play a major role in the etiopathogenesis of RAP. Further studies with larger sample size needs to be done. Severe pancreatitis (14%) was predominantly seen in biliary and Idiopathic RAP. Patients with biliary microlithiasis responded well to treatment with UDCA and biliary sphincterotomy. Patients with pancreas divisum responded well to accessory papilla sphincterotomy. Some patients labeled as Idiopathic RAP may respond to empiric biliary sphincterotomy as they may have occult biliary microlithiasis or sphincter of Oddi dysfunction. Patients (38%) labeled as Idiopathic RAP responded to empiric trial of pancreatic enzymes. Large controlled trials are required to determine the role of pancreatic enzymes , antioxidants or octreotide in therapy of Idiopathic RAP. Does Idiopathic RAP really exist ? An etiology was obtained in 93% of patients after extensive evaluation , empiric biliary sphincterotomy in Idiopathic RAP and development of chronic pancreatitis on follow up.It is possible that on further follow up , the 7 % of patients may progress to chronic pancreatitis. Follow up of patients with idiopathic RAP is necessary as some may progress to chronic pancreatitis

ASSESSMENT OF DRUG RELATED PROBLEMS IN PATIENTS WITH CHRONIC DISEASES IN THE GENERAL MEDICINE UNITS OF A TERTIARY CARE HOSPITAL

Objective: Patients with chronic diseases are more prone to develop drug-related problems (DRPs), which can further worsen their quality of life. The aim of this study was to determine factors and medications associated with DRPs in patients with chronic disease.Methods: This prospective interventional study was conducted for a duration of 6 mo in the in-patients of general medicine department of PSG Hospital, Coimbatore. DRPs were identified, assessed and recorded as per pharmaceutical care network Europe (PCNE) V5.01 criteria. Chi-square and correlation test were used to analyze the data for identifying factors associated with DRPs.Results: A total of 137 patients were enrolled for the study, of which 66 patients developed DRPs. The most prevalent DRP was found to be drug choice problem. The major causes of DRPs were found to be drug and dose selection. Antidiabetic drugs were found to be more associated with drug-related problems. The incidence of drug-related problems was high in patients aged between 50 to 59 y. Association between gender, length of hospital stays and polypharmacy with DRPs was found to be statistically significant. 58.33% of the total drug-related problems were completely solved and 19.05% were partially solved.Conclusion: The incidence of DRPs in the General Medicine department of the hospital was high. The use of an appropriate tool such as PCNE may assist pharmacists and other healthcare professionals to systematically identify, categorize and report drug-related problems

THE EFFECT OF CONTRAST ENHANCEMENT ON EPIPHYTE SEGMENTATION USING GENERATIVE NETWORK

The performance of the deep learning-based image segmentation is highly dependent on two major factors as follows: 1) The organization and structure of the architecture used to train the model and 2) The quality of input data used to train the model. The input image quality and the variety of training samples are highly influencing the features derived by the deep learning filters for segmentation. This study focus on the effect of image quality of a natural dataset of epiphytes captured using Unmanned Aerial Vehicles (UAV), while segmenting the epiphytes from other background vegetation. The dataset used in this work is highly challenging in terms of pixel overlap between target and background to be segmented, the occupancy of target in the image and shadows from nearby vegetation. The proposed study used four different contrast enhancement techniques to improve the image quality of low contrast images from the epiphyte dataset. The enhanced dataset with four different methods were used to train five different segmentation models. The segmentation performances of four different models are reported using structural similarity index (SSIM) and intersection over union (IoU) score. The study shows that the epiphyte segmentation performance is highly influenced by the input image quality and recommendations are given based on four different techniques for experts to work with segmentation with natural datasets like epiphytes. The study also reported that the occupancy of the target epiphyte and vegetation highly influence the performance of the segmentation model

PALLADIUM CATALYZED SYNTHESIS OF NOVEL TACRINE DERIVATIVES

This work was supported by Ministry of Science and Higher Education of the Russian Federation, grant # 075-15-2020-777 and the Russian Science Foundation, grants ### 22-23-20189, 21-13-00304 and 20-73-10205

Development of a solar powered fixed wireless network extender

User devices connect to Access Points (AP) to obtain internet access through Wi-Fi networks. But with the increment of the distance from the AP, signal reception quality reduces, and the power will be lost due to signal interferences through free space. The design was focused on providing internet accessibility by an existing Wi-Fi network to a remote site using low cost and high-performance antenna. The research was conducted to design an antenna for obtaining internet accessibility during off-peak times at staff and student residential areas from the existing fixed Wi-Fi the network deployed in the academic buildings. The designed system consists of a parabolic antenna that uses the Line-of-Sight technique for unidirectional transmission having a center-feed of programmed microcontrollers to capture Wi-Fi signals through wireless media. According to the literature we have conducted, the system deployed with a solar powering system which is a fully sustainable energy source, with a low-power consuming microcontroller, is the novelty of the design. This entire antenna system was tested for receiving signal strength, downloading and uploading speeds at the targeted distance from the transmitter under 2 tests. The results confirm that the residential area where Wi-Fi connectivity was not available for internet access was provided with the connectivity with better signal quality having a user-friendly, low power consuming, and easily deployable system

INFLUENCE OF ADDITIONAL SPECTRAL BANDS FOR EPIPHYTE SEGMENTATION ON DRU-NET

Dense Residual U-Net (DRU-Net) is a neural network used for image segmentation. It is based on the U-Net architecture and isa combination of modified ResNet as the encoder and modified DenseNet as the decoder blocks. DRU-Net captures both the local and contextual information. Previous studies on DRU-Net have not tested the influence of the spectral resolution of the images. In an earlier study, the DRU-Net was trained with grayscale images for epiphyte segmentation. The network trained and tested with grayscale images underperformed while varying the illumination and occupancy of the target in the frame. In this study, the same network was trained and tested with RGB images for assessing the increase in overall learning. The performance of the network in segmenting epiphytes under conditions such as good/poor illumination and high/low target occupancy was analyzed. Dice and Jaccard scores were used as evaluation metrics. The DRU-Net model trained with RGB images had an improvement of 20% over the grayscale model in both average Dice and average Jaccard scores of the target class. Based on the higher Dice and Jaccard scores, adding additional spectral information improves DRU-Net learning. The increased computation time required for training DRU-Net with RGB images will result in better output. This model could be further used for identifying multiple epiphytes in images with poor illumination and different occupancy conditions

Measuring the stability of fundamental constants with a network of clocks

The detection of variations of fundamental constants of the Standard Model would provide us with compelling evidence of new physics, and could lift the veil on the nature of dark matter and dark energy. In this work, we discuss how a network of atomic and molecular clocks can be used to look for such variations with unprecedented sensitivity over a wide range of time scales. This is precisely the goal of the recently launched QSNET project: A network of clocks for measuring the stability of fundamental constants. QSNET will include state-of-the-art atomic clocks, but will also develop next-generation molecular and highly charged ion clocks with enhanced sensitivity to variations of fundamental constants. We describe the technological and scientific aims of QSNET and evaluate its expected performance. We show that in the range of parameters probed by QSNET, either we will discover new physics, or we will impose new constraints on violations of fundamental symmetries and a range of theories beyond the Standard Model, including dark matter and dark energy models

Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of general relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO–Virgo–KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering single-harmonic and dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is 6.4 × 10−27 for the young energetic pulsar J0537−6910, while the lowest constraint on the ellipticity is 8.8 × 10−9 for the bright nearby millisecond pulsar J0437−4715. Additionally, for a subset of 16 targets, we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of nonstandard polarizations as predicted by the Brans–Dicke theory