Targeting the tumor microenvironment in colorectal peritoneal metastases

Peritoneal metastasis (PM) occurs in approximately one in four colorectal cancer (CRC) patients. The pathophysiology of colorectal PM remains poorly characterized. Also, the efficacy of current treatment modalities, including surgery and intraperitoneal (IP) delivery of chemotherapy, is limited. Increasingly, therefore, efforts are being developed to unravel the PM cascade and at understanding the PM-associated tumor microenvironment (TME) and peritoneal ecosystem as potential therapeutic targets. Here, we review recent insights in the structure and components of the TME in colorectal PM, and discuss how these may translate into novel therapeutic approaches aimed at re-engineering the metastasis-promoting activity of the stroma

CURRENT STATUS, CHALLENGES AND PREVENTIVE STRATEGIES TO OVERCOME DATA INTEGRITY ISSUES IN THE PHARMACEUTICAL INDUSTRY

The pharmaceutical industry is currently one of the most dynamic among all industries. At present, it is striking with various compliance challenges like never before there is increased regulation, acquisitions, push toward harmonization and endemic in a Data Integrity (DI) concern. DI weakness is identified, either as a result of an audit or a regulatory inspection, companies with multiple sites should ensure that appropriate corrective and preventive actions are implemented across the organizations and appropriate notification to regulatory authorities should be made wherever applicable. The objective of the study carries the number of issues involved within data integrity in current GMP aspects, the root causes were addressed based on warning letters. This review intends to study the concept of data integrity holistically in all aspects, regulatory expectations and to evaluate the state of compliance and challenges that explore to suggest appropriate remedial and proactive measures to avoid DI issues. There were many challenges involved to overcome the issues, which are all about the one's handling by maintaining good documentation practice. The importance, strategies and recommendations were discussed to overcome from the repeated data integrity mistakes. This review was carried out by systematic searches of data integrity in relevant guidelines, published articles, reviews and abstracts in Google scholar, Pubmed, Science direct, Embase, Web of science, Cochrane database of systematic reviews of articles up to March 2020. The keywords used for gathering information were listed below

PHARMACY PROFESSIONS IN INDIADURING COVID-19 PANDEMIC: PRESENT STATUS, FUTURE CHALLENGES AND A WAY FORWARD

People in every country became exposed to COVID-19 pandemic and cannot able to find a right solution and strategies to overcome from it. Pharmacy is the most important, dynamic and versatile health care profession in the world, whereas its scope and importance are always being emerging at any situation. Pharmacy professionals (PPs) working proactively for the public even in this pandemic situation. Since dependency is high, the responsibility and preference also high for PPs especially in this pandemic situation. Current status in pharmacy education and emerging future challenges of PPs in all aspects, particularly in thispandemic situation were addressed based on observational studies among various pharma industries and published news of Pharmacy Council of India (PCI). While in the development phase it has crossed many barriers, not only in the economic level,but also involves regulations, duration, process controls, legal hurdles and situational defects. The purpose of this review discusses the evolution and updates in pharmacy, education, pharmacy practice, regulations, and types of challenges along with recommendations for PPs in India in light of the COVID-19 pandemic. This review was carried out to summarize knowledge about the updates and challenges in pharmacy professions in all aspects. Sources were retrieved from relevant guidelines and published articles in Google scholar, Pubmed and Science direct of articles up to June 2020. The keywords used for gathering information were listed below

Early Warning Score in Febrile Thrombocytopenia

BACKGROUND: Since fever with thrombocytopenia is one of the most common presenting feature in most of the infectious and some of the systemic diseases. So there is in need for developing a scoring system to assess the prognosis and early predictors of mortality in those cases. So aim of our study is to develop an early warning score in febrile thrombocytopenic patients. MATERIALS AND METHODS: Our study includes 100 cases of febrile thrombocytopenic patients selected randomly admitted in the study period with inclusion and exclusion criteria. Those patients are evaluated by history, clinical examination and basic laboratory investigations and some specific investigation if needed. RESULTS: By analyzing the vital signs and systemic involvement of patients admitted with fever and thrombocytopenia at the time of addmission, a scoring system was derived. According to that, patients having higher score have worse prognosis and needs intensive care and timely intervention. Low risk (score upto 9), moderate risk (10-18), high risk (19 and above). The platelet count is not the only tool for prediction of prognosis in those cases. This scoring method includes vital signs, system involvement and other features. So this could be a better method for assessing febrile thrombocytopenic patients than the platelet count alone. CONCLUSION: The early warning scoring system formulated in our study may serve as an inexpensive, reproduciable, clinically bedside tools for evaluating fever with thrombocytopenia patients and helping in assessment of the patient’s prognosis in early stage and decide for intensive management. It will help clinicians to be more alert in febrile thrombocytopenic patients with systemic illness and it will guide early interventions in patients with a higher score so that these patients can make a complete recovery

Prevalence of Cardiovascular Autonomic Neuropathy in Type 2 Diabetes and Utility of corrected QT Interval for its diagnosis

CONCLUSION: The following are the conclusions from this study: 1. The Prevalence of Cardiovascular Autonomic Neuropathy is high in type 2 diabetics in our hospital. 2. The prevalence of CAN will increase with increase in the duration of diabetes. About half of the patients with type 2 diabetes have autonomic dysfunction after ten years. 3. A significant correlation is present between Cardiovascular autonomic dysfunction and QTc prolongation. QTc interval in the ECG can be used to diagnose Cardiovascular autonomic neuropathy with a reasonable sensitivity and specificity

Classification of Mammogram Images by Using SVM and KNN

Breast cancer is a fairly diverse illness that affects a large percentage of women in the west. A mammogram is an X-ray-based evaluation of a woman's breasts to see if she has cancer. One of the earliest prescreening diagnostic procedures for breast cancer is mammography. It is well known that breast cancer recovery rates are significantly increased by early identification. Mammogram analysis is typically delegated to skilled radiologists at medical facilities. Human mistake, however, is always a possibility. Fatigue of the observer can commonly lead to errors, resulting in intraobserver and interobserver variances. The image quality affects the sensitivity of mammographic screening as well. The goal of developing automated techniques for detection and grading of breast cancer images is to reduce various types of variability and standardize diagnostic procedures. The classification of breast cancer images into benign (tumor increasing, but not harmful) and malignant (cannot be managed, it causes death) classes using a two-way classification algorithm is shown in this study. The two-way classification data mining algorithms are utilized because there are not many abnormal mammograms. The first classification algorithm, k-means, divides a given dataset into a predetermined number of clusters. Support Vector Machine (SVM), a second classification algorithm, is used to identify the optimal classification function to separate members of the two classes in the training dat