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Showing posts from July, 2022

Biomedical Science and Research Journals | The Diagnosis and Treatment of a Rare Case of Supraclavicular Neuropathy Following Thoracic Decompression Surgery

  The Diagnosis and Treatment of a Rare Case of Supraclavicular Neuropathy Following Thoracic Decompression Surgery Abstract The supraclavicular nerve is rarely of clinical significance for many medical providers and even less so for most pain physicians. The following is a case of supraclavicular neuropathy following thoracic outlet decompression to treat Paget–Schroetter syndrome, a venous thrombosis etiology of thoracic outlet syndrome (TOS). A 38-year-old female was referred to our pain management clinic by her vascular surgeon for a new onset of severe right-sided superior chest wall and peri-clavicular pain that began after surgery to address her TOS. She described constant tingling, burning, and numbness which was distinct from the painless swelling and mottling of her right arm prior to her TOS diagnosis. Narcotics and muscle relaxants had provided minimal relief for these new post-operative symptoms. Multiple subsequent ultrasound exams were negative for recurrent venous throm

Biomedical Science and Research Journals | Sodium Glucose Co-Transporters 2 Inhibitors are Useful Addition for Treatment of Heart Failure with Reduced Ejection Fraction

  Sodium Glucose Co-Transporters 2 Inhibitors are Useful Addition for Treatment of Heart Failure with Reduced Ejection Fraction Abstract Background:  Recent well-designed trials have shown that sodium-glucose co-transporter 2 (SGLT2) inhibitors decrease heart failure hospitalization (HFH) in patients with or without type 2 diabetes. Methods:  Review of literature (English, French, Spanish) from January 1990 to January 21, 2020. Key words included heart failure, sodiumglucose co-transporter 2, SGLT2 inhibitors, safety, randomized trials, and meta-analysis. Expert opinions and guidelines are also reviewed. Results:  The use of SGLT2 inhibitors in patients with type 2 diabetes was associated with significant relative reduction in HFH by 27-35%. The latter reduction is most likely a class effect and is consistent in patients with various degrees of cardiovascular (CV) risk at baseline. In patients with heart failure and reduced ejection fraction (HFrEF), dapagliflozin decreased risk of a c

Biomedical Science and Research Journals | Inducible Nitric Oxide Synthase Expression in Brain Injury Cases

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  Inducible Nitric Oxide Synthase Expression in Brain Injury Cases Abstract Background:  The activity of Inducible Nitric Oxide Synthase (iNOS) is increased as a response to several insults to central nervous system causing brain injury. Objectives:  To investigate iNOS expression in cadavers who died as result of traumatic brain injury (TBI), brain hemorrhage and brain congestion. Methodology:  Indirect immunohistochemistry was performed on 80 cases of brain injury (autopsies), as well 23 normal brain cases as a control group. The cases were stained for iNOS and interpreted in terms of staining intensity from 0 to indicate negative, 1 weak, 2 moderate and 3 to indicate strong staining reactions. Results:  personal variables (age, sex, brain weight) were not associated significantly with brain injury type. The iNOS was not express in control group. But, strong activity of iNOS was expressed in neurons astrocytes and in cases of TBI and brain hemorrhage. The activity of iNOS in blood ve

Biomedical Science and Research Journals | Rapid Seizure Classification Using Feature Extraction and Channel Selection

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  Rapid Seizure Classification Using Feature Extraction and Channel Selection Abstract The Seizure is an abnormal electrical activity in the brain; it can be diagnosed by a neurologist and could be classified using recorded data. Medical data, such as EEG signal usually contain many features and attributes that are not important for the classification process. Dimension reduction is an important step to reduce irrelevant information. Features extraction is one algorithm for dimension reduction step. Another one is the channel selection algorithm. These algorithms speed up the process of classification and improve accuracy. This paper proposes an approach based on extracting EEG features, channel selection to reduce the computation capacity, and trained model used for classification. Variance parameter is used for channels selection, by taking the maximum three ones. Eleven features are extracted from the selected channels and averaged to be the input for the classifier. Six classifiers