The results revealed the cytotoxicity of Mn (II) Arginine dithiocarbamate against the MCF-7cell line, observed from a significant change in the morphology of the cancer cells with IC50 value of 211.53μg/mL.
 
  The compound, Mn (II) Arginine dithiocarbamate has effective anticancer potentials against MCF-7 cancer cells.
 The compound, Mn (II) Arginine dithiocarbamate has effective anticancer potentials against MCF-7 cancer cells.
  Neuropathic pain may arise from conditions that affecting the central or peripheral nervous system. This study was held to determine the difference P2X3 receptor expression in the dorsal horn of the spinal cord and pain threshold after estrogen therapy in neuropathic pain.
 
  This study design was an experimental research laboratory. The 24 mice samples divided into negative control group, positive control, and treatment groups. The treatment groups were given subcutaneous injections of estrogen 0.4ml and also examined for the onset of thermal hyperalgesia in every rat. On day 15, an autopsy was performed on rats, and the spine was taken. The spinal cord was stained by hematoxylin-eosin, and the expression of P2X3 receptors was investigated. P2X3 receptor expression was examined in the dorsal horn on each sample.
 
  From 24 subjects of the study revealed an increase in the onset of thermal hyperalgesia on the estrogen group compared with the placebo group, a higher start. This study also obtained a decrease in the expression of P2X3 on the therapy group compared to the positive control group with significant differences. Statistical test results revealed the appearance of the P2X3 estrogen group had a substantial difference with the placebo group (p=0.000) and the mean of the negative control group (p=0.030). The placebo group had a significant difference from the negative control group (p=0.035).
 
  Estrogen could decrease the expression of P2X3 receptors and prolonged the onset of thermal hyperalgesia. So, both of these explained that estrogen has a role in preventing the occurrence of neuropathic pain after peripheral nerve lesions.
 Estrogen could decrease the expression of P2X3 receptors and prolonged the onset of thermal hyperalgesia. So, both of these explained that estrogen has a role in preventing the occurrence of neuropathic pain after peripheral nerve lesions.We present a case of a man with a giant cutaneous horn over his frontal region. This case has been presented for the size of the lesion, due to delayed treatment, and to illustrate the reasons why the growth of this lesion has been possible in a western country, in the 21st century. It was a solitary, not painful lesion which caused significant aesthetic problems. The diagnosis was based on an ultrasonographic study and the treatment of choice was a surgical excision. This case is an opportunity to review the literature about the cutaneous horns, to talk about the main causes of delayed diagnosis and treatment of cutaneous lesions and, to define the role of the specialist in the assessment of emotions and patient support.Pituitary metastases are rare, a primary tumor of the breasts or lungs are frequently found. The clinical picture is very variable, they can be accidental discovery or revealed by a pituitary dysfunction. The prognosis is generally poor and depends on the anatomopathological type. We report the observation of a patient with a pituitary metastasis of a breast cancer evolving for 4 years, the diagnosis was suspected in front of pituitary macroadenoma images, a transphenoidal endoscopic biopsy and an anatomopathological confirmation revealing an infiltrating breast adenocarcinoma.The COVID-19 pandemic, caused by the coronavirus SARS-CoV-2, has rapidly spread worldwide starting from China in late 2019. The first case in Jordan was reported on March 2, 2020. The Jordanian government made many transformations to address this crisis. As we are the only referral cardiology center for percutaneous coronary intervention (PCI) in the north of Jordan, we made multiple adjustments to confront COVID-19 challenges. We emphasize that there is an urgent need to update all procedures and therapeutic activities that are performed in the Cath-Lab to minimize the risks for both the patients and the health care providers during the pandemic of COVID-19.
  Chest X-ray data have been found to be very promising for assessing COVID-19 patients, especially for resolving emergency-department and urgent-care-center overcapacity. Deep-learning (DL) methods in artificial intelligence (AI) play a dominant role as high-performance classifiers in the detection of the disease using chest X-rays. Given many new DL models have been being developed for this purpose, the objective of this study is to investigate the fine tuning of pretrained convolutional neural networks (CNNs) for the classification of COVID-19 using chest X-rays. If fine-tuned pre-trained CNNs can provide equivalent or better classification results than other more sophisticated CNNs, then the deployment of AI-based tools for detecting COVID-19 using chest X-ray data can be more rapid and cost-effective.
 
  Three pretrained CNNs, which are AlexNet, GoogleNet, and SqueezeNet, were selected and fine-tuned without data augmentation to carry out 2-class and 3-class classification tasks using 3 public chest X-raye urgent need for harnessing the pandemic by facilitating the deployment of AI tools that are fully automated and readily available in the public domain for rapid implementation.Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder that includes symptoms such as inattentiveness, hyperactivity and impulsiveness.  https://www.selleckchem.com/products/talabostat.html  It is considered as an important public health issue and prevalence of, as well as demand for diagnosis, has increased as awareness of the disease grew over the past years. Supply of specialist medical experts has not kept pace with the increasing demand for assessment, both due to financial pressures on health systems and the difficulty to train new experts, resulting in growing waiting lists. Patients are not being treated quickly enough causing problems in other areas of health systems (e.g. increased GP visits, increased risk of self-harm and accidents) and more broadly (e.g. time off work, relationship problems). Advances in AI make it possible to support the clinical diagnosis of ADHD based on the analysis of relevant data. This paper reports on findings related to the mental health services of a specialist Trust within the UK's National Health Service (NHS).