Targeting the IGF-1R in prostate and colorectal cancer: reasons behind trial failure and future directions

IGF-1Rs enact a significant part in cancer growth and its progress. IGF-1R inhibitors were encouraged in the early trials, but the patients did not benefit due to the unavailability of predictive biomarkers and IGF-1R system complexity. However, the linkage between IGF-1R and cancer was reported three decades ago. This review will shed light on the IGF-1R system, targeting IGF-1R through monoclonal antibodies, reasons behind IGF-1R trial failure and future directions. This study presented that targeting IGF-1R through monoclonal antibodies is still effective in cancer treatment, and there is a need to look for future directions. Cancer patients may benefit from using mAbs that target existing and new cancer targets, evidenced by promising results. It is also essential that the academician, trial experts and pharmaceutical companies play their role in finding a treatment for this deadly disease.

Efficient Breast Cancer Classification Using Histopathological Images and a Simple VGG

Breast cancer is the second most deadly disease worldwide. This severe condition led to 627,000 people dying in 2018. Thus, early detection is critical for improving the patients' lifetime or even curing them. In this context, we can appeal to Medicine 4.0, which exploits machine learning capabilities to obtain a faster and more efficient diagnosis. Therefore, this work aims to apply a simpler convolutional neural network, called VGG-7, for classifying breast cancer in histopathological images. Results have shown that VGG-7 overcomes the performance of VGG-16 and VGG-19, showing an accuracy of 98%, a precision of 99%, a recall of 98%, and an F1 score of 98%.

Rapid Protection from COVID-19 in Nonhuman Primates Vaccinated Intramuscularly but Not Intranasally with a Single Dose of a Vesicular Stomatitis Virus-Based Vaccine

The vesicular stomatitis virus (VSV) vaccine platform rose to fame in 2019, when a VSV-based Ebola virus (EBOV) vaccine was approved by the European Medicines Agency and the U.S. Food and Drug Administration for human use against the deadly disease.

Phytoconstituents in the Management of Covid-19: Demystifying the Fact

The 2019-nCoV (COVID-19; novel coronavirus disease-2019) outbreak is caused by the coronavirus, and its continued spread is responsible for increasing deaths, social and economic burden. COVID-19 created a chaotic situation worldwide and claimed the lives of over 5,027,183 and 248,467,363 confirmed cases have been reported so far as per the data published by WHO (World Health Organization) till 5th November 2021. Scientific communities all over the world are toiling to find a suitable therapeutic drug for this deadly disease. Although till date no promising drug has been discovered for this COVID-19. However, as per the WHO, over 102 COVID-19 vaccines are in clinical development and 185 in pre-clinical development. Naturally occurring phytoconstituents possess considerable chemical richness in the form of anti-viral and anti-parasitic potential and have been extensively exploited for the same globally. Still, phytomedicine-based therapies are considered as the best available treatment option to minimize and treat the symptoms of COVID-19 because of the least possible side effects compared to synthetic drugs recommended by the physicians/clinicians. In this review, the use of plant chemicals as a possible therapeutic agent for severe acute respiratory syndrome coronavirus 2 (SARS CoV2) is highlighted with their proposed mechanism of action, which will prove fruitful and effective in finding a cure for this deadly disease.

Prediction of Diabetes with Deep Neural Network

Diabetic mellitus is hitting the globe since decades. it often leads to dangerous health issues such as kidney problems, heart strokes, nervous system disturbance and eye problems etc. The prediction and detection of such a deadly disease is pivotal. In the conducted study, we have built a diabetic prediction model which is based on deep neural networks. We performed our experiments with two-fold and four-fold cross validation. Our diabetic prediction model has reported an accuracy of 98.45% which is quite high.

Association between Meningococcal Meningitis and Santa Ana Winds in Children and Adolescents from Tijuana, Mexico, a need for Vaccination.

Background Based on several previous studies (regional and national), Tijuana, Baja-California, Mexico (across the border from San Diego, California, USA), has shown the highest rate of Meningococcal Meningitis (MeM) in the country, however, the reason for this has not yet been known. In the “African Meningitis Belt”, the Harmattan seasons are associated with MeM outbreaks. The Santa Ana winds seasons (SAWs) are hot and dry winds (similar to Harmattan seasons) that occur seasonally in southwestern California, USA, and North of Baja-California, Mexico. Objectives Our aim was to demonstrate, as a short communication, a potential association of SAWs with MeM in Tijuana, Baja-California, Mexico, which in turn, may partially explain the high rate of this disease in the region. Methods Based on own previously published data obtained from thirteen years of active surveillance of MeM, and a 65 years review showing the occurrence of SAWs, we estimated the risk ratio (RR) of total cases number by MeM vs. bacterial non-MeM (bacterial meningitis not caused by Neisseria meningitidis) during seasons with and without SAWs. Results We found an association of SAWs seasons with MeM, but not with bacterial non-MeM (RR = 2.06, p = 0.02 (95% CI 1.1 to 3.8), which may partially explain the high endemicity of this deadly disease in this part of the globe. Conclusion This study shows a new potential climatic association with MeM, and provides more information that justifies universal meningococcal vaccination in Tijuana, Mexico.

Cancer attrition immunotherapy

Cancer is a deadly disease wherein the immune system is inefficient, resulting in malignant tumors that metastasize. An active and robust immune system is the body’s natural defense. Research efforts continue exploring alternative immunotherapies to fight cancer. This communication proposes non-infectious vaccines and hyper-allergenic skin creams to starve malignant tumors through immune metabolic interference.

Instance Selection dengan Naïve Bayes pada Klasifikasi Kanker Serviks

There are several deadly disease for woman, one of which is servical cancer. The growth and development of the disease is very slow, so that treatment if know form the beginning will facilitate the healing process, but conversely unknown cancers from the beginning will become dangereous and deadly disease due to relatively difficult healing. Biopsy action is one way to detect the presence of cancer. In the previous study, classification of cervical cancer had the bighest accuracy value of 97,515% using the decision tree method of several feature selection technique. for this reason, this research will use the decision tree or tree C4.5 classification method, logistic function and zeroR which were previously carried out processing with instance selection with Naïve Bayes by reducing the elimination of missing values with the aim of increasing the level of accuracy better than previous studies. C4.5 classification in this study has the most maximum results compared to other classification methods with an accuracy value of 99,69%.

Microbiome—Friend or Foe of Pancreatic Cancer?

Pancreatic ductal adenocarcinoma is one of the deadliest human neoplasms. Despite the development of new surgical and adjuvant therapies, the prognosis remains very poor, with the overall survival rate not exceeding 9%. There is now increasing evidence that the human microbiome, which is involved in many physiological functions, including the regulation of metabolic processes and the modulation of the immune system, is possibly linked to pancreatic oncogenesis. However, the exact mechanisms of action are poorly understood. Our review summarizes the current understanding of how the microbiome affects pancreatic cancer development and progression. We discuss potential pathways of microbe translocation to the pancreas, as well as the mechanism of their action. We describe the role of the microbiome as a potential marker of pancreatic cancer diagnosis, progression, and survival. Finally, we discuss the possibilities of modifying the microbiome to improve treatment effectiveness for this deadly disease.

Implementation of Economic Rights Principles on Trademark In Trading of Product in The Pandemic Covid-19 Era

In accompany with the tight trading competition, it is imply that trademark plays significant role to known as the special product in common and had the power and useful when it managed in appropriate. Trademark is not just the word related to the product or collection only but the process and business strategy. Therefore, trademark have a value and equity. Thus equity becomes important as the value to be a benchmark of product in the marketplace. However, the pandemic of Covid-19 that struck since beginning of 2020 had an enormous impact to the whole states in the world including Indonesia. The pandemic was bring worst influences to the economic and trading. The deadly disease automatically was paralyze an economy and trading. It is caused by restriction of people to drive and influences the product movement. Temporarily, export-import activities delayed as restriction of transportation entry among the states. Finally, Indonesia forced close for in and out flight of territory. The situation influence to the implementation of Economic Right of trademark right attach to the import and export products in Indonesia.