MRI cross sectional atlas of normal canine cervical musculoskeletal structure

Although magnetic resonance imaging (MRI) has been increasingly used as a diagnostic tool for cervical spine injuries in canines, a comprehensive normal MRI anatomy of the canine cervical spine muscles is lacking. Therefore, the purpose of this study was to build a magnetic resonance imaging atlas of the normal cross sectional anatomy of the muscles of the canine cervical spine. MRI scans were performed on a canine cadaver using a combination of T1 and T2-weighted images in the transverse, sagittal and dorsal planes acquired at a slice thickness of 1 mm. Muscle contours were traced manually in each slice, using local osseous structures as reference points for muscle identification. Twenty-two muscles were traced in 401 slices in the cervical region. A three dimensional surface model of all the contoured muscles was created to illustrate the complex geometrical arrangement of canine neck muscles. The cross-sectional area of the muscles was measured at the mid-level of each vertebra. The accuracy of the location of the mapped muscles was verified by comparing the sagittal view of the 3D model of muscles with still photographs obtained from anatomic canine cadaver dissection. We believe that this information will provide a unique and valuable resource for veterinary researchers, clinicians and surgeons who wish to evaluate MRI images of the cervical spine. It will also serve as the foundation for ongoing work to develop a computational model of the canine cervical spine in which anatomical information is combined with electromyographic, kinematic and kinetic data.This work was supported in part by Fitzpatrick Referrals Ltd., through the One Health/One Medicine Fellowship at The Ohio State University

A Case Report of Neuroleptic Malignant Syndrome during Methadone Therapy

Background and Objective: Methadone is an opioid agonist used for the treatment of addiction to opioid drugs. Toxic leukoencephalopathy can cause serious problem and even be life-threatening. Methadone-induced leukoencephalopathy is a rare condition of this toxicity. Because of the importance of this situation and its treatment, we aim to report a case who is diagnosed as Methadone-induced leukoencephalopathy. Case Report: A 63-year-old man referred with non-persistent fever, drowsiness, rigidity and suspected of neuroleptic malignant syndrome (NMS). He was addicted to opioid from young age. He was on maintenance therapy with 80 mg methadone syrup from 2 months ago. After the appearance of symptoms including delirium, impaired attention and consciousness, treatment was performed with half a tablet of haloperidol 0.5 mg twice a day before rigidity and fever. Multiple lesions were seen in baseline CT-Scan and MRI. Toxic laboratory examination showed methadone was positive and other toxins and opioids were negative. After two weeks, second MRI showed rapid progressive lesions in white matter. Thus, it was diagnosed as Methadone-induced leukoencephalopathy in addition to NMS. Hydration, bromocriptine tablets 2.5 mg twice a day, methadone tapering and haloperidol discontinuation were performed. After two months, the patient's consciousness was better and his CPK and LDH tests were normal. Conclusion: Methadone-induced leukoencephalopathy is a very rare condition, but it is important for physicians to consider this diagnosis in patients using methadone, especially when they show neurological and psychiatric signs and symptoms. That’s because early methadone tapering can reduce and stop toxicity on the white matter of the brain

Credible Autocoding of Convex Optimization Algorithms

International audienceThe efficiency of modern optimization methods, coupled with increasing computational resources, has led to the possibility of real-time optimization algorithms acting in safety critical roles. There is a considerable body of mathematical proofs on on-line optimization programs which can be leveraged to assist in the development and verification of their implementation. In this paper, we demonstrate how theoretical proofs of real-time optimization algorithms can be used to describe functional properties at the level of the code, thereby making it accessible for the formal methods community. The running example used in this paper is a generic semi-definite programming (SDP) solver. Semi-definite programs can encode a wide variety of optimization problems and can be solved in polynomial time at a given accuracy. We describe a top-to-down approach that transforms a high-level analysis of the algorithm into useful code annotations. We formulate some general remarks about how such a task can be incorporated into a convex programming autocoder. We then take a first step towards the automatic verification of the optimization program by identifying key issues to be adressed in future work

A Case Report of Coexistence of Cryptococcal Meningitis and COVID-19 in a Patient with Human Immunodeficiency Virus

Background and Objective: People who are infected with Human Immunodeficiency Viruses (HIV) are more prone to opportunistic fungal infections than other patients. The immune system of these patients becomes weaker when they are also infected with Coronavirus disease (COVID-19). Involvement of the central nervous system caused by fungal infections in these patients is of concern and fatal if diagnosed late. The aim of this research is to investigate a woman with COVID-19 and HIV who was diagnosed with cryptococcal meningitis. Case Report: The patient is a 53-year-old woman who complained of severe headache and nausea after infection with COVID-19. White blood cells, erythrocyte sedimentation rate, lymphocyte, creatinine, aspartate aminotransferase, alanine aminotransferase and blood urea nitrogen were increased compared to the standard level. Cerebrospinal fluid testing showed that glucose was lower and protein was higher than normal. Microscopic examination, staining and culture of cerebrospinal fluid deposits showed the presence of double wall yeasts similar to Cryptococcus. The patient was positive for COVID-19 and HIV. The level of CD4 (cluster of differentiation 4) was lower than the standard. The patient was treated with amphotericin B at a dose of 100 mg for two weeks and was discharged from the hospital after the conditions were stabilized. Conclusion: Cryptococcal meningitis can often occur in immunosuppressive conditions such as HIV. Therefore, quick follow-up, diagnosis and treatment should be considered in these patients

Modulation of Antimalarial Activity at a Putative Bisquinoline Receptor in vivo Using Fluorinated Bisquinolines

Antimalarials can interact with heme covalently, by - interactions or hydrogen bonding. Consequently, the prototropy of 4-aminoquinolines and quinoline methanols was investigated using quantum mechanics. Calculations showed mefloquine protonated preferentially at the piperidine and was impeded at the endocyclic nitrogen due to electronic rather than steric factors. In gas phase calculations, 7-substituted mono- and bis-4-aminoquinolines were preferentially protonated at the endocyclic quinoline nitrogen. By contrast, compounds with a trifluoromethyl substituent on both the 2- and 8-positions, reversed the order of protonation which now favored the exocyclic secondary amine nitrogen at the 4-position. Loss of antimalarial efficacy by CF3 groups simultaneously occupying the 2- and 8-positions was recovered if the CF3 group occupied the 7-position. Hence, trifluromethyl groups buttressing quinolinyl nitrogen shifted binding of antimalarials to hematin, enabling switching from endocyclic to the exocyclic N. Both theoretical calculations (DFT calculations: B3LYP/6- 31+G*) and crystal structure of (±)-trans-N1,N2-bis-(2,8-ditrifluoromethylquinolin-4- yl)cyclohexane-1,2-diamine were used to reveal preferred mode(s) of interaction with hematin. The order of antimalarial activity in vivo followed the capacity for a redox change of the iron(III)state which has important implications for the future rational design of 4- aminoquinoline antimalarials

Delineation of prognostic biomarkers in prostate cancer

Prostate cancer is the most frequently diagnosed cancer in American men(1,2). Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer(3), but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer(4-6). Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes-hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase-at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62849/1/412822a0.pd

Identification of a robust gene signature that predicts breast cancer outcome in independent data sets

BACKGROUND: Breast cancer is a heterogeneous disease, presenting with a wide range of histologic, clinical, and genetic features. Microarray technology has shown promise in predicting outcome in these patients. METHODS: We profiled 162 breast tumors using expression microarrays to stratify tumors based on gene expression. A subset of 55 tumors with extensive follow-up was used to identify gene sets that predicted outcome. The predictive gene set was further tested in previously published data sets. RESULTS: We used different statistical methods to identify three gene sets associated with disease free survival. A fourth gene set, consisting of 21 genes in common to all three sets, also had the ability to predict patient outcome. To validate the predictive utility of this derived gene set, it was tested in two published data sets from other groups. This gene set resulted in significant separation of patients on the basis of survival in these data sets, correctly predicting outcome in 62–65% of patients. By comparing outcome prediction within subgroups based on ER status, grade, and nodal status, we found that our gene set was most effective in predicting outcome in ER positive and node negative tumors. CONCLUSION: This robust gene selection with extensive validation has identified a predictive gene set that may have clinical utility for outcome prediction in breast cancer patients

HFE gene mutations increase the risk of coronary heart disease in women

The purpose of the present study is to examine HFE gene mutations in relation to newly diagnosed (incident) coronary heart disease (CHD). In a population-based follow-up study of 7,983 individuals aged 55 years and older, we compared the risk of incident CHD between HFE carriers and non-carriers, overall and stratified by sex and smoking status. HFE mutations were significantly associated with an increased risk of incident CHD in women but not in men (hazard ratio [HR] for women = 1.7, 95% confidence interval [CI] 1.2–2.4 versus HR for men = 0.9, 95% CI 0.7–1.2). This increased CHD risk associated with HFE mutations in women was statistically significant in never smokers (HR = 1.8, 95% CI 1.1–2.8) and current smokers (HR = 3.1, 95% CI 1.4–7.1), but not in former smokers (HR = 1.3, 95% CI 0.7–2.4). HFE mutations are associated with increased risk of incident CHD in women

vProtein: Identifying Optimal Amino Acid Complements from Plant-Based Foods

Background: Indispensible amino acids (IAAs) are used by the body in different proportions. Most animal-based foods provide these IAAs in roughly the needed proportions, but many plant-based foods provide different proportions of IAAs. To explore how these plant-based foods can be better used in human nutrition, we have created the computational tool vProtein to identify optimal food complements to satisfy human protein needs. Methods: vProtein uses 1251 plant-based foods listed in the United States Department of Agriculture standard release 22 database to determine the quantity of each food or pair of foods required to satisfy human IAA needs as determined by the 2005 daily recommended intake. The quantity of food in a pair is found using a linear programming approach that minimizes total calories, total excess IAAs, or the total weight of the combination. Results: For single foods, vProtein identifies foods with particularly balanced IAA patterns such as wheat germ, quinoa, and cauliflower. vProtein also identifies foods with particularly unbalanced IAA patterns such as macadamia nuts, degermed corn products, and wakame seaweed. Although less useful alone, some unbalanced foods provide unusually good complements, such as Brazil nuts to legumes. Interestingly, vProtein finds no statistically significant bias toward grain/ legume pairings for protein complementation. These analyses suggest that pairings of plant-based foods should be based on the individual foods themselves instead of based on broader food group-food group pairings. Overall, the most efficien