Substratifying the risk of covert malignancy in significant rectal polyps: Outcomes from a specialist multidisciplinary team (MDT).

AIM: A treatment strategy for patients with a significant polyp or early colon cancer (SPECC) of the rectum presents a challenge due to the significant rate of covert malignancy and lack of standardized assessment. For this reason, NICE recommends multidisciplinary meetings to improve outcomes. The primary aim of the present study was to report the performance of our specialist early rectal cancer (SERC) multidisciplinary team (MDT) in correctly substratifying the risk of cancer and to discuss the limitations of staging investigations in those patients with "poor outcomes". METHOD: This was a retrospective review of patients referred to our SERC MDT from 2014 to 2019. Lesions were assigned by the MDT to three pre-resection categories (low, intermediate, high) according to the risk of covert malignancy. Resection method and final histology were compared to the pre-resection categories. RESULTS: Of 350 SPECC lesions, 174 were assessed as low-risk, 108 intermediate-risk and 68 high-risk. The cancer incidence was 4.8%, 8.3% and 53%, respectively (15.5% overall). Eight lesions were categorized as low-risk but following piecemeal resection were found to be malignant. Five lesions, three of which were categorized as high-risk, were ultimately benign following conventional surgery. One pT1sm1 cancer, removed by anterior resection, may have been treated by local excision. CONCLUSION: A total of 83% of malignant polyps were triaged to an en bloc resection technique and surgical resection avoided for nearly all benign lesions. However, 12 patients from this cohort were deemed to have a poor outcome because of miscategorization. Further comparative research is needed to establish the optimum strategy for rectal SPECC lesion assessment. ORIGINALITY STATEMENT: There is currently no consensus for staging significant polyps of the rectum. This paper reports the effectiveness of a specialist early rectal cancer MDT to correctly risk-stratify significant rectal polyps. It underscores the importance of accurate categorization for treatment decision-making, while acknowledging the limitations of current staging modalities.

Evaluation of Different Regimens of Palliative Radiation Therapy for Symptomatic Bone Metastases: An Audit From a Tertiary Care Hospital in Jharkhand, India.

Background This study aimed to assess the efficacy of different radiation therapy regimens in treating patients with symptomatic bone metastases. Methodology A retrospective study was conducted by assigning patients with symptomatic bone metastases from different primary cancers into three groups, namely, Arms A, B, and C. The radiation dose delivered in each arm was as follows: 8 Gray (Gy) in a single fraction for Arm A, 20 Gy in five fractions at the rate of 4 Gy per fraction for Arm B, and 30 Gy in 10 fractions at the rate of 3 Gy per fraction for Arm C. Each arm consisted of 15 patients. A comparison was conducted across all three arms to evaluate pain relief based on the Visual Analog Scale (VAS), performance score improvement based on the Eastern Cooperative Oncology Group (ECOG), and analgesic requirement based on the World Health Organization (WHO) step ladder at one week, one month, and three months. Results The pain relief was measured using the VAS in three different arms, i.e., Arm A, B, and C. After one week, the pain relief was 66.67%, 60%, and 60%, respectively. After one month, it was 73.33% in all three arms. At three months, it was 80%, 86.67%, and 86.67%, respectively. The study also measured the improvement in the ECOG performance score. The improvement in all three arms was 60% after one week and 66.67% in Arm A and 73.33% in Arms B and C after one month. After three months, the improvement was 73.33%, 80%, and 80% in Arms A, B, and C, respectively. The decrease in analgesic usage was also measured in all three arms. After one week, it was 60% in all three arms. After one month, it was 66.67%, 73.33%, and 73.33% in Arms A, B, and C, respectively. At three months, it was 73.33%, 80%, and 80% in Arms A, B, and C, respectively. No significant statistical difference was found between the three arms. Conclusions The efficacy of a single 8 Gy arm was almost equivalent to that of other arms of multifractionated regimens in terms of improvement in pain and performance score and decreased use of analgesics for a short duration of follow-up. For high-volume cancer centers and patients with economic constraints, a single-fraction regime provides effective palliation for painful bone metastases.

Deep convolutional neural network and IoT technology for healthcare.

Background: Deep Learning is an AI technology that trains computers to analyze data in an approach similar to the human brain. Deep learning algorithms can find complex patterns in images, text, audio, and other data types to provide accurate predictions and conclusions. Neuronal networks are another name for Deep Learning. These layers are the input, the hidden, and the output of a deep learning model. First, data is taken in by the input layer, and then it is processed by the output layer. Deep Learning has many advantages over traditional machine learning algorithms like a KA-nearest neighbor, support vector algorithms, and regression approaches. Deep learning models can read more complex data than traditional machine learning methods. Objectives: This research aims to find the ideal number of best-hidden layers for the neural network and different activation function variations. The article also thoroughly analyzes how various frameworks can be used to create a comparison or fast neural networks. The final goal of the article is to investigate all such innovative techniques that allow us to speed up the training of neural networks without losing accuracy. Methods: A sample data Set from 2001 was collected by www.Kaggle.com. We can reduce the total number of layers in the deep learning model. This will enable us to use our time. To perform the ReLU activation, we will make use of two layers that are completely connected. If the value being supplied is larger than zero, the ReLU activation will return 0, and else it will output the value being input directly. Results: We use multiple parameters to determine the most effective method to test how well our method works. In the next paragraph, we'll discuss how the calculation changes secret-shared Values. By adopting 19 train set features, we train our reliable model to predict healthcare cost's (numerical) target feature. We found that 0.89503 was the best choice because it gave us a good fit (R2) and let us set enough coefficients to 0. To develop our stable model with this Set of parameters, we require 26 iterations. We use an R2 of 0.89503, an MSE of 0.01094, an RMSE of 0.10458, a mean residual deviance of 0.01094, a mean absolute error of 0.07452, and a root mean squared log error of 0.07207. After training the model on the train set, we applied the same parameters to the test set and obtained an R2 of 0.90707, MSE of 0.01045, RMSE of 0.10224, mean residual deviation of 0.01045, MAE of 0.06954, and RMSE of 0.07051, validating our solution approach. The objective value of our secured model is higher than that of the scikit-learn model, although the former performs better on goodness-of-fit criteria. As a result, our protected model performs quite well, marginally outperforming the (very optimized) scikit-learn model. Using a backpropagation algorithm and stochastic gradient descent, deep Learning develops artificial neural systems with several interconnected layers. There may be hidden layers of neurons in the network that have the tanh, rectification, and max-out hyperparameters. Modern features like momentum training, dropout, active learning rate, rate annealed, and L1 or L2 regularization provide exceptional prediction performance. The worldwide model's parameters are multi-threadedly (asynchronously) trained on the data from that node, and the model-based data is then gradually augmented by model averaging over the entire network. The method is executed on a single-node, direct H2O cluster initiated by the operator. The operation is parallel despite there just being a single node involved. The number of threads may be adjusted in the settings menu under Preferences and General. The optimal number of threads for the system is used automatically. Successful predictions in the healthcare data sets are made using the H2O Deep Learning operator. There will be a classification done since its label is binomial. The Splitting Validation operator creates test and training datasets to evaluate the model. By default, the settings of the Deep Learning activator are used. To put it another way, we'll construct two hidden layers, each containing 50 neurons. The Accuracy measure is computed by linking the annotated Sample Set with a Performer (Binominal Classification) operator. Table 3 displays the Deep Learning Model, the labeled data, and the Performance Vector that resulted from the technique. Conclusions: Deep learning algorithms can be used to design systems that report data on patients and deliver warnings to medical applications or electronic health information if there are changes in the patient's health. These systems could be created using deep Learning. This helps verify that patients get the proper effective care at the proper time for each specific patient. A healthcare decision support system was presented using the Internet of Things and deep learning methods. In the proposed system, we examined the capability of integrating deep learning technology into automatic diagnosis and IoT capabilities for faster message exchange over the Internet. We have selected the suitable Neural Network structure (number of best-hidden layers and activation function classes) to construct the e-health system. In addition, the e-health system relied on data from doctors to understand the Neural Network. In the validation method, the total evaluation of the proposed healthcare system for diagnostics provides dependability under various patient conditions. Based on evaluation and simulation findings, a dual hidden layer of feed-forward NN and its neurons store the tanh function more effectively than other NN. To overcome challenges, this study will integrate artificial intelligence with IoT. This study aims to determine the NN's optimal layer counts and activation function variations.

Changing Trends Towards Herbal Supplements: An Insight into Safety and Herb-drug Interaction.

Herbs have been used as sustenance and medicine for a very long time, often in conjunction with other prescribed medications. Even though they are thought to be natural and secure, many of these herbs can interact with other medications and cause potentially dangerous adverse effects or decrease the benefits of the medication. The complex and diverse pharmacological functions carried out by the active ingredients in herbs unavoidably alter the pharmacokinetics of chemical drugs when administered in vivo. Drug transporter expression has a direct impact on how medications are absorbed, distributed, metabolized, and excreted in living organisms. Changes in substrate pharmacokinetics can affect the effectiveness and toxicity of a drug when the active ingredients of a herb inhibit or stimulate the expression of transporters. By reviewing published clinical and preclinical studies, this review aims to raise awareness of herbdrug interactions and discuss their evidence-based mechanisms and clinical consequences. More clinical information on herb-drug interactions is required to make choices regarding patient safety as the incidence and severity of herb-drug interactions are rising due to an increase in the use of herbal preparations globally.This review seeks to increase understanding of herb-drug interactions and explore their evidence-based mechanisms and clinical implications by reviewing published clinical and preclinical studies. The incidence and severity of herb-drug interactions are on the rise due to an increase in the use of herbal preparations worldwide, necessitating the need for more clinical data on these interactions in order to make decisions regarding patient safety. Healthcare workers and patients will become more alert to potential interactions as their knowledge of pharmacokinetic herb-drug interactions grows. The study's objective is to raise readers' awareness of possible interactions between herbal supplements and prescription medications who regularly take them.

Accumulation of resveratrol, ferulic acid and iron in seeds confer iron deficiency chlorosis tolerance to a novel genetic stock of peanut (Arachis hypogaea L.) grown in calcareous soils.

Peanut is mostly grown in calcareous soils with high pH which are deficient in available iron (Fe2+) for plant uptake causing iron deficiency chlorosis (IDC). The most pertinent solution is to identify efficient genotypes showing tolerance to limited Fe availability in the soil. A field screening of 40 advanced breeding lines of peanut using NRCG 7472 and ICGV 86031 as IDC susceptible and tolerant checks, respectively, was envisaged for four years. PBS 22040 and 29,192 exhibited maximum tolerance while PBS 12215 and 12,185 were most susceptible. PBS 22040 accumulated maximum seed resveratrol (5.8 ± 0.08 ppm), ferulic acid (378.6 ± 0.31 ppm) and Fe (45.59 ± 0.41 ppm) content. Enhanced chlorophyll retention (8.72-9.50 µg ml-1), carotenoid accumulation (1.96-2.08 µg ml-1), and antioxidant enzyme activity (APX: 35.9-103.9%; POX: 51- 145%) reduced the MDA accumulation (5.61-9.11 µM cm-1) in tolerant lines. The overexpression of Fe transporters IRT1, ZIP5, YSL3 was recorded to the tune of 2.3-9.54; 1.45-3.7; 2.20-2.32- folds respectively in PBS 22040 and 29,192, over NRCG 7472. PBS 22040 recorded the maximum pod yield (282 ± 4.6 g/row), hundred kernel weight (55 ± 0.7 g) and number of pods per three plants (54 ± 1.7). The study thus reports new insights into the roles of resveratrol, ferulic acid and differential antioxidant enzyme activities in imparting IDC tolerance. PBS 22040, being the best performing line, can be the potent source of IDC tolerance for introgression in high yielding but susceptible genotypes under similar edaphic conditions. Supplementary Information: The online version contains supplementary material available at 10.1007/s12298-023-01321-9.

Aberrant expression of miR-133a in endothelial cells inhibits angiogenesis by reducing pro-angiogenic but increasing anti-angiogenic gene expression.

Angiogenesis is a multi-factorial physiological process deregulated in human diseases characterised by excessive or insufficient blood vessel formation. Emerging evidence highlights a novel role for microRNAs as regulators of angiogenesis. Previous studies addressing the effect of miR-133a expression in endothelial cells during blood vessel formation have reported conflicting results. Here, we have assessed the specific effect of mature miR-133a strands in angiogenesis and the expression of endothelial angiogenic genes. Transfection of miR-133a-3p or -5p mimics in primary human endothelial cells significantly inhibited proliferation, migration, and tubular morphogenesis of transfected cells. Screening of gene arrays related to angiogenic processes, and further validation by TaqMan qPCR, revealed that aberrant expression of miR-133a-3p led to a decrease in the expression of genes encoding pro-angiogenic molecules, whilst increasing those with anti-angiogenic functions. Ingenuity Pathway Analysis of a collection of genes differentially expressed in cells harbouring miR-133a-3p, predicted decreased cellular functions related to vasculature branching and cell cycle progression, underlining the inhibitory role of miR-133a-3p in angiogenic cellular processes. Our results suggest that controlled delivery of miR-133a-3p mimics, or antagomirs in diseased endothelial cells, might open new therapeutic interventions to treat patients suffering from cardiovascular pathologies that occur with excessive or insufficient angiogenesis.

Exploring status of emergency drugs and vaccine development in Covid-19 pandemic: an update.

COVID-19 outburst initiated from the city of Wuhan in China in December 2019 and has been declared as a public health emergency of international concern. This pandemic portrays a spectrum of clinical complications, primarily affecting the respiratory system reported to be caused by a pathogen SARS-CoV-2 belonging to the family of beta coronavirus. Currently, the main objective of the government authorities of all affected countries and research organizations is to find a potential solution in the form of a pharmacological intervention or a vaccination to eradicate the disease and to have a long-term solution to deal with the pandemic. A multitude of anti-viral regimens is proposed based on the repurposing of currently available drugs for other issues or the compassionate use of drugs to immediately control and optimize the healthcare facilities. Meanwhile, a number of agencies are proposing new drug candidates to recreate the possibility of treating the disease. Similarly, a lot of research work is going on worldwide for the development of vaccination. Currently, a good number of candidates has finally reached the borders of Clinical Trials and are expected to be launched as soon as possible. However, the regulatory framework and authorization of these candidates is the most significant aspect of the whole scenario, which needs a specific set of time for validation purposes. The present work is widely focused on the general aspects of COVID-19 and the regulatory landscape for the emergency authorization of repurposed drug candidates, compassionate use of drugs, investigational entities, and vaccine development worldwide. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s13337-021-00684-5.

Exploring scientific validation of Triphala Rasayana in ayurveda as a source of rejuvenation for contemporary healthcare: An update.

ETHNOPHARMACOLOGICAL RELEVANCE: Ayurveda remains the classical and comprehensive part of the ancient Indian medicine system for well-being promotive, disease preventive, and revival approach for the human body. Triphala Rasayana is mentioned in Ayurveda, comprising fruits of three plant species viz. Phyllanthus emblica L. (P. emblica), Terminalia chebula Retz (T. chebula), and Terminalia bellirica Roxb (T.bellirica). Triphala Rasayana has been utilized in various traditional medicine systems, viz., Ayurveda, Siddha, and Unani. Traditionally Rasayana based drugs are utilized in different kinds of diseases without pathophysiological associations as indicated by current medication. Various medicinal attributes of Triphala Rasayana include antioxidant, anticancer, antidiabetic, antimicrobial, immunomodulatory, and anticataract and is also considered as a pillar for gastrointestinal treatment, specifically in functional gastrointestinal disorders (FGIDs). Due to Rasayana's accessible mode of administration, availability, and affordability, there is an increase in its global acceptance. AIM OF REVIEW: This review article summarizes the scientific validation, traditional uses, bioactive compounds, and ethnopharmacological properties of Triphala Rasayana. It also documents recent data on in vivo and in vitro pharmacological studies and clinical effects of Triphala Rasayana. MATERIAL AND METHOD: A literature review is carried out using PubMed, ScienceDirect, Scopus, web of science, Ayush Research Portal, and Clinical Trials Registry-India. In addition to an electronic search, traditional ayurvedic texts and books were used as sources of information. RESULTS: Traditionally, "Triphala Rasayana" is classified as a tridoshic rasayana and one of the most well-studied ayurvedic Rasayana. It showed various pharmacological activities such as anticancer, antioxidant, antibacterial, immunomodulatory, cardioprotective, and antidiabetic. Besides this, Rasayana has reported ethnopharmacological activities such as antimicrobial, anticataract, wound healing, and radioprotection. It has shown a good impact on the gastrointestinal tract (GIT) system with the reported pharmacological activities in gastrointestinal disorders such as constipation, gastric ulcer, and inflammatory bowel disease (IBD). Phytochemical studies of Triphala Rasayana revealed chemical constituents like gallic acid, ellagic acid, chebulic acid, chebulinic acid, methyl gallate, emblicanin A, and emblicanin B. Additionally, clinical studies found Triphala Rasayana to be effective against diabetes, constipation, and obesity. CONCLUSION: The present review revealed that Triphala Rasayana may treat a diverse range of diseases, especially GIT disorders. Considering the beneficial properties of Triphala Rasayana and it's proven non-toxic nature could be a source of rejuvenation in contemporary healthcare. Nevertheless, its clinical data effectively provided precious signals to correlate ayurvedic biology and modern medicine.

Collagenous panenteritis: a rare cause of chronic diarrhoea.

Collagenous panenteritis is a rare inflammatory condition that causes profound diarrhoea and weight loss. There has only been a handful of cases reported in the literature. We report this rare case and the diagnostic difficulties encountered in securing the diagnosis. A 59-year-old woman presented with an 8-month history of diarrhoea and weight loss on a background of a family history of coeliac disease. Her presentation was complicated with acute kidney injury secondary to prerenal losses. Repeated gastroscopies and colonoscopies along with biopsies were inconclusive. It was not until histology of biopsies taken at endoscopies were reviewed that a diagnosis of collagenous panenteritis was secured. Her management revolved around combination of budesonide, gluten-free diet and antidiarrhoeals, which has achieved clinical remission.

Developing a protocol for gastrostomy tube insertion in patients diagnosed with head and neck cancer.

Selecting patients with head and neck cancer requiring a pretreatment gastrostomy feeding tube is not straightforward. The nutritional status and functional deficits associated with the cancer, its treatment, and the long-term side effects predicate the need for gastrostomy tube placement. However, gastrostomy tubes are not without morbidity and are an added burden to the patient. The aim of this retrospective case series review was to evaluate the clinical characteristics of newly diagnosed patients with head and neck cancer treated with curative intent having gastrostomy placement, with the intent of developing a protocol to help with the timely selection of patients for pretreatment gastrostomy insertion. A gastrostomy tube was placed in 32%. A regression model identified 5 independent predictors (P < .001) to predict gastrostomy tube placement: overall clinical stage, tumor site, clinical T stage, patient age, and clinical N stage. A protocol to help the multidisciplinary team to decide whether a pretreatment gastrostomy tube should be placed is suggested.

The role of matrix metalloproteinase-7 in redefining the gastric microenvironment in response to Helicobacter pylori.

BACKGROUND & AIMS: Interactions between epithelial and stromal cells are important determinants of mucosal organization, but the signaling mechanisms are understood incompletely. Matrix metalloproteinase (MMP)-7 is produced uniquely in epithelia, may act on growth factors and matrix proteins, and in the stomach is increased with Helicobacter pylori infection. We have studied the role of MMP-7 in signaling between epithelial cells and a key stromal cell type, the myofibroblast. METHODS: Immunohistochemistry and Western blotting were applied to gastric corpus biopsy specimens; primary cultures of human gastric glands and myofibroblasts were used to study the role of MMP-7 in regulating proliferation and migration of the latter, and MMP-7 substrates were identified by proteomic methods. RESULTS: Increased abundance of the myofibroblast marker alpha-smooth muscle actin was identified in H. pylori-positive biopsy specimens. Media from H pylori-infected gastric epithelial cultures stimulated proliferation and migration of primary human gastric myofibroblasts and antisense oligonucleotide treatment indicated a role for MMP-7. Proteomic methods identified insulin-like growth factor binding protein (IGFBP)-5 as a substrate for MMP-7 in medium from gastric myofibroblasts. Knockdown of IGFBP-5 by small interfering RNA or immunoneutralization of IGF-II, abolished myofibroblast responses to MMP-7. Proliferation of gastric epithelial cells also was stimulated by MMP-7-treated myofibroblasts via IGF-II. CONCLUSIONS: MMP-7 acts as an epithelial-derived signal increasing the bioavailability of IGF-II released from myofibroblasts. Because IGF-II acts on both stromal and epithelial cells, the findings suggest that increased MMP-7 expression contributes to redefining the niche occupied by dividing cells and leading to hyperproliferation in H pylori infection.

Identification of plasminogen activator inhibitor-2 as a gastrin-regulated gene: Role of Rho GTPase and menin.

BACKGROUND & AIMS: The gastric hormone gastrin regulates acid secretion, gene expression, and the functional development and cellular composition of the gastric mucosa. Using a gene array, we sought to identify major, novel, gastrin-regulated genes. METHODS: A cancer gene array was probed with samples from the gastric cancer cell line AGS, expressing the gastrin-cholecystokinin(B) receptor and stimulated with gastrin. The expression of gastrin-regulated genes was further characterized by Western blots and enzyme-linked immunosorbent assay in tissue and blood of hypergastrinemic patients. Gene expression was studied using promoter-luciferase reporter constructs. RESULTS: Plasminogen activator inhibitor 2 (PAI-2) was identified as a major, previously unknown target of gastrin in the gastric cancer cell line AGS. The relevance was confirmed by showing elevated tissue and plasma PAI-2 in hypergastrinemic patients (pernicious anemia and multiple endocrine neoplasia type 1). PAI-2 promoter-luciferase constructs showed that gastrin stimulated expression via pathways involving Galpha and Gbetagamma subunits, protein kinase C, RhoA, and the transcription factors CREB and AP1. The tumor suppressor menin inhibited transcription. In addition, gastrin stimulated expression in adjacent cells via a paracrine mechanism involving protein kinase C and RhoA but not CREB. CONCLUSIONS: A gene array showed PAI-2 to be a novel gastrin-regulated gene, stimulated in part through CREB and AP-1 and inhibited by the tumor suppressor menin.