Diversity in morpho-pomological attributes and biochemical profiling of bael (Aegle marmelos (L.) Correa) genotypes of North-Western India.

Bael is a medicinal cum fruit tree with multipurpose utility and propagated mostly through seeds. The present study aimed to assess and analyse the morpho-pomological and biochemical traits of eighty seedlings grown bael genotypes comparison with two commercial cultivars (NB-5 and NB-9) of bael. The significant differences were detected among the genotypes based on the measured morpho-pomological and biochemical traits. The morpho-pomological and biochemical traits of bael exhibited variation ranging from 6.17% to 133.65%. Trunk girth ranged from 29.50 to 63.40 cm and tree spread (N-S) varied 1.00-6.30 m. Fruit length ranged from 4.60 to 12.05 cm and fruit width ranged from 4.64 to 11.72 cm. Moreover, fruit weight ranged from 56.33 to 917.65 g and pulp percentage varied from 58.64 to 81.38%. Soluble Solid Content ranged from 25.90 to 36.77 0brix and ascorbic acid varied from 14.38 to 25.45 mg/100 g. Fruit length was positively correlated with fruit width, fruit weight, pulp percentage, seed length, seed diameter and number of seeds per fruit, while it was negatively correlated with fruit surface and total number of fruit per plant. Principal component analysis showed that 76.66% of the variability observed was explained by the 13 components. Ward cluster analysis using Euclidean distance classified the genotypes into two main clusters. These findings contribute to a better understanding of the diversity and relationships among the studied genotypes, aiding future breeding and selection programs for improved bael cultivation.

Improved UNet Deep Learning Model for Automatic Detection of Lung Cancer Nodules.

Uncontrolled cell growth in the two spongy lung organs in the chest is the most prevalent kind of cancer. When cells from the lungs spread to other tissues and organs, this is referred to as metastasis. This work uses image processing, deep learning, and metaheuristics to identify cancer in its early stages. At this point, a new convolutional neural network is constructed. The predator technique has the potential to increase network architecture and accuracy. Deep learning identified lung cancer spinal metastases in as energy consumption increased CT readings for lung cancer bone metastases decreased. Qualified physicians, on the other hand, discovered 71.14 and 74.60 percent of targets with energies of 140 and 60 keV, respectively, whereas the proposed model gives 76.51 and 81.58 percent, respectively. Expert physicians' detection rate was 74.60 percent lower than deep learning's detection rate of 81.58 percent. The proposed method has the highest accuracy, sensitivity, and specificity (93.4, 98.4, and 97.1 percent, respectively), as well as the lowest error rate (1.6 percent). Finally, in lung segmentation, the proposed model outperforms the CNN model. High-intensity energy-spectral CT images are more difficult to segment than low-intensity energy-spectral CT images.

Internet gaming and related psychotic disorder: An emerging phenomenon.

Internet addiction has recently been suggested as a possible diagnostic entity in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) and incorporated in the International Classification of Diseases 11th Revision (ICD-11) as a gaming disorder, predominantly, online or offline. Mostly, psychotic phenomena have been described by either alcohol or opioid withdrawal, but there is a paucity of literature on Internet-related psychosis. We report two cases from Northern India of sudden onset of psychosis due to Internet addiction. The contents of hallucinations and delusions reflected themes of Internet gaming. Psychosis as a specifier for Internet gaming disorder (IGD) is not defined in DSM-5, whereas it should be considered as one of the presentations of Internet addiction.

Blockchain-Based Decentralized Cloud Solutions for Data Transfer.

Cloud computing has increased its service area and user experience above traditional platforms through virtualization and resource integration, resulting in substantial economic and societal advantages. Cloud computing is experiencing a significant security and trust dilemma, requiring a trust-enabled transaction environment. The typical cloud trust model is centralized, resulting in high maintenance costs, network congestion, and even single-point failure. Also, due to a lack of openness and traceability, trust rating findings are not universally acknowledged. "Blockchain is a novel, decentralised computing system. Its unique operational principles and record traceability assure the transaction data's integrity, undeniability, and security. So, blockchain is ideal for building a distributed and decentralised trust infrastructure. This study addresses the difficulty of transferring data and related permission policies from the cloud to the distributed file systems (DFS). Our aims include moving the data files from the cloud to the distributed file system and developing a cloud policy. This study addresses the difficulty of transferring data and related permission policies from the cloud to the DFS. In DFS, no node is given the privilege, and storage of all the data is dependent on content-addressing. The data files are moved from Amazon S3 buckets to the interplanetary file system (IPFS). In DFS, no node is given the privilege, and storage of all the data is dependent on content-addressing.

An integrated fog and Artificial Intelligence smart health framework to predict and prevent COVID-19.

Nowadays, COVID-19 is spreading at a rapid rate in almost all the continents of the world. It has already affected many people who are further spreading it day by day. Hence, it is the most essential to alert nearby people to be aware of it due to its communicable behavior. Till May 2020, no vaccine is available for the treatment of this COVID-19, but the existing technologies can be used to minimize its effect. Cloud/fog computing could be used to monitor and control this rapidly spreading infection in a cost-effective and time-saving manner. To strengthen COVID-19 patient prediction, Artificial Intelligence(AI) can be integrated with cloud/fog computing for practical solutions. In this paper, fog assisted the internet of things based quality of service framework is presented to prevent and protect from COVID-19. It provides real-time processing of users' health data to predict the COVID-19 infection by observing their symptoms and immediately generates an emergency alert, medical reports, and significant precautions to the user, their guardian as well as doctors/experts. It collects sensitive information from the hospitals/quarantine shelters through the patient IoT devices for taking necessary actions/decisions. Further, it generates an alert message to the government health agencies for controlling the outbreak of chronic illness and for tanking quick and timely actions.

Whipple's Disease Manifested as Recurrent Ascites.

Whipple's disease commonly presents as chronic diarrhea and abdominal pain. Ascites is an uncommon presentation of Whipple's disease. Here, we report a rare case of a 47-year-old male who presented with diarrhea and abdominal distention for three months. The physical examination was significant for ascites. Serum albumin was low and serum-to-ascites albumin gradient was < 1.1 g/dl. This suggested that ascites was less likely to be present due to portal hypertension. Enteroscopy showed erythematous duodenum and jejunum; biopsy was suggestive of periodic acid-Schiff stain (PAS) positive macrophages consistent with Whipple's disease. During the hospital course, the patient improved with intravenous (IV) ceftriaxone.

Expression of p53 predicts risk of prevalent and incident advanced neoplasia in patients with Barrett's esophagus and epithelial changes indefinite for dysplasia.

BACKGROUND AND AIMS: Patients with Barrett's esophagus (BE) are at an increased risk for developing esophageal adenocarcinoma (EAC); thus they may undergo regular endoscopic surveillance. If epithelial changes cannot be unequivocally classified as negative or positive for dysplasia, a diagnosis of indefinite for dysplasia (IND) is recommended. Several biomarkers have been proposed as markers or predictors of neoplasia in the general BE population; however, their significance is not clear in patients with BE-IND. We therefore performed a retrospective study to determine whether expression of these biomarkers was associated with the development of neoplasia in BE-IND patients. METHODS: We searched our archives to identify all cases of BE-IND diagnosed between January 1992 and December 2007. Immunohistochemical analyses were used to semi-quantify the expression of p53, α-methylacyl-CoA racemase (AMACR), and cyclin D1. A univariate analysis was used to identify predictors for prevalent and incident neoplasia and advanced neoplasia. RESULTS: Among the 103 patients with an index diagnosis of BE-IND who were included in this study, 81 (78.6%) underwent a follow-up biopsy within 12 months of diagnosis; 10 (12.3%) had neoplasia, including four (4.9%) with advanced neoplasia. Among 79 patients without prevalent neoplasia who underwent more than 1 year of follow-up, 18 (22.8%) had developed neoplasia, including four (5.1%) with advanced neoplasia. AMACR and cyclin D1 expression levels were not correlated with prevalent or incident neoplasia; however, high p53 expression (>5%) was associated with prevalent advanced neoplasia on surveillance biopsy (P = 0.04) and with an increased risk of progression to advanced neoplasia (HR = 12; P = 0.03). CONCLUSION: In this study, p53 expression was found to be predictive of prevalent advanced neoplasia and progression to advanced neoplasia in patients with BE-IND.

Serum 25-Hydroxyvitamin D Levels and the Risk of Dysplasia and Esophageal Adenocarcinoma in Patients with Barrett's Esophagus.

BACKGROUND: To date, there are no studies reporting an association between vitamin D and Barrett's esophagus (BE), the precursor for esophageal adenocarcinoma (EAC). AIMS: Our aim was to study the association between serum 25-hydroxyvitamin D (25(OH)D) levels and prevalence and incidence of dysplasia/EAC in BE. METHODS: Patients from our BE Registry cohort seen between 2000 and 2012 who had serum 25(OH)D levels measured were included. Age, gender, race, BE length, hiatal hernia size, and histological findings were recorded. Patients without high-grade dysplasia (HGD)/EAC at or within 1 year of index biopsy and who had follow-up endoscopies and 25(OH)D levels were studied for incidence of dysplasia/EAC. RESULTS: Among 429 patients with BE, the mean 25(OH)D level was 72 ± 31.2 nmol/L. Hundred and one (23.6 %) patients had deficiency (<50 nmol/L), 149 (34.7 %) had insufficiency (50-74.9 nmol/L), and 179 (41.7 %) had normal levels of 25(OH)D. There was no association between serum 25(OH)D levels and dysplasia (p = 0.90). In the incidence cohort of 246 patients with median follow-up of 46 months, there were 34 cases of low-grade dysplasia, 12 of HGD, and 5 of EAC. Change in 25(OH)D levels did not impact progression to dysplasia/EAC (every 5 nmol/L increase from baseline, hazard ratio 0.98; p = 0.62). CONCLUSIONS: Serum 25(OH)D levels were low in 58.3 % of our BE cohort. There was no association between 25(OH)D levels and prevalence or incidence of HGD/EAC in patients with BE. Further long-term studies are needed to study the association between vitamin D status and progression of dysplasia in BE.

Risk for esophageal neoplasia in Barrett's esophagus patients with mucosal changes indefinite for dysplasia.

BACKGROUND AND AIM: Patients with Barrett's esophagus (BE) are at increased risk for esophageal adenocarcinoma (EAC) and therefore require surveillance. Biopsies are classified as indefinite for dysplasia (IND) when the significance of epithelial abnormalities is uncertain due to inflammation or sampling. Our aim was to characterize the neoplastic risk of IND in BE patients and to identify predictors of neoplastic risk. METHODS: Our pathology database from 1992 to 2007 was searched for BE and IND. Progression rates were calculated and univariate analysis was performed to identify predictors for neoplasia progression in BE-IND patients. RESULTS: Among 85 patients who had a follow-up (FU) biopsy within 1 year, 11 (12.9%) patients had prevalent neoplasia (seven low-grade dysplasia [LGD], two high-grade dysplasia [HGD], and two EAC). Among 82 patients who did not have prevalent neoplasia but had ≥ 1 year FU, 17 progressed to dysplasia (14 LGD, 3 HGD) and 2 developed EAC during a mean FU period of 59 months. The incidence of neoplasia (LGD, HGD, or EAC) and advanced neoplasia (HGD + EAC) was 4.5 and 1.2 cases per 100 patient-years, respectively. Longer length of BE and multi-focal IND on index biopsy were associated with progression to neoplasia. CONCLUSION: Patients with BE-IND carry a significant risk of harboring prevalent dysplasia, but the risk of incident dysplasia is similar to the general BE population. The length of BE and the multifocal IND might tentatively help to identify a patient subpopulation at higher risk of neoplastic progression before more definitive data becomes available.

Surgical treatment of patients with Lennox-Gastaut syndrome phenotype.

Lennox-Gastaut syndrome (LGS) is a devastating and refractory generalized epilepsy affecting children and adolescents. In this study we report the results of resective surgery in 18 patients with LGS phenotype who underwent single-lobe/lesionectomy or multilobe resection plus multiple subpial transection and/or callosotomy. After surgery, seven patients became completely seizure-free (Engel Class I) and five almost seizure-free (Engel Class II). Additional four had significant seizure control (Engel Class III), and two had no change in seizure frequency (Engel Class IV). Of the 4 patients without any lesion on brain MRI, 2 ended with Engel Class II, 1 with III and the other with IV in Engels' classification. Mean intelligence quotient (IQ) increased from 56.1 ± 8.1 (mean ± SD) before operation to 67.4 ± 8.2 (mean ± SD) after operation, a significant improvement (P = 0.001). Results also indicated that the younger the patient at surgery, or the shorter the interval between onset of seizure and resective operation, the better the intellectual outcome. Our data suggest that resective epilepsy surgery can be successful in patients with LGS phenotype as long as the EEG shows dominance of discharges in one hemisphere and corresponding ipsilateral imaging findings, even with contralateral ictal discharges.