Simple Floating Voltage-Controlled Memductor Emulator for Analog Applications

The topic of memristive circuits is a novel topic in circuit theory that has become of great importance due to its unique behavior which is useful in different applications. But since there is a lack of memristor samples, a memristor emulator is used instead of a solid state memristor. In this paper, a new simple floating voltage-controlled memductor emulator is introduced which is implemented using commercial off the shelf (COTS) realization. The mathematical modeling of the proposed circuit is derived to match the theoretical model. The proposed circuit is tested experimentally using different excitation signals such as sinusoidal, square, and triangular waves showing an excellent matching with previously reported simulations

Power Dissipation of Memristor-Based Relaxation Oscillators

Recently, many reactance-less memristive relaxation oscillators were introduced, where the charging and discharging processes depend on memristors. In this paper, we investigate the power dissipation in different memristor based relaxation oscillators. General expressions for these memristive circuits as well as the power dissipation formulas for three different topologies are derived analytically. In addition, general expressions for the maximum and minimum power dissipation are calculated. Finally, the calculated expressions are verified using PSPICE simulations showing very good matching

The clinical pattern of renal diseases in the nephrology in-patient unit of the Yaounde General Hospital in Cameroon: a five-year audit

Introduction: Kidney diseases are a growing worldwide problem and one of the major public health threats. We analyzed the spectrum of kidney diseases seen over a five-year period in the nephrology in-patient unit of the Yaounde general hospital. Methods: This was a retrospective analysis of 225 medical records of patients admitted from January 2005 to December 2009 in the unit with a discharge diagnosis of kidney and urinary tract diseases. The first hospitalization was considered for patients admitted several times for the same disease. Socio-demographic and clinical patient data were recorded. Results: The patients mean age was 44.8±16 years with 135 (60%) males and 211 (93.8%) emergency admissions. All 139 (61.8%) patients with chronic kidney disease (CKD) had chronic renal failure. Acute kidney injury (AKI) (28%), nephrotic syndrome (7.6%), renal colic (1.3%) and acute pyelonephritis (1.3%) were other patterns observed. Chronic glomerulonephritis (25.9%), hypertension (22.3%) and diabetes (20.1%) were the main etiological factors of CKD. All AKI patients were in stage RIFLE-F. AKI was secondary to parenchymal (58.7%), functional (25.4%) and obstructive (15.9%) etiologies. Black water fever (36.4%), sepsis (22.7%), drugs (18.2%), eclampsia (13.6%) and herbal concoctions (9.1%) were the etiologies of acute tubular necrosis while enterocolitis (56.2%), heart failure (31.3%) and digestive hemorrhage (12.5%) were the etiologies of functional AKI. Conclusion: The clinical pattern of renal diseases is dominated by advanced CKD and AKI secondary to preventable causes. This study suggests a need for an array of actions including sensitization, continuous medical education and strengthening of the health system

Lymphocyte subtype dysregulation in a group of children with simple obesity

Background: Obesity as a global public health problem is increasing in prevalence. Reports showed that obese children are more liable to infection than lean ones; it was claimed that obese subjects have altered peripheral blood total lymphocyte counts in addition to reduced lymphocyte proliferative response to mitogen stimulation as well as dysregulated cytokine expression.Objective: This study aimed to evaluate the effect of childhood obesity on cell mediated immunity as indicated by peripheral blood lymphocyte phenotyping.Methods: We enrolled 30 school-aged children (mean age 10±3.27 years). They comprised two groups; 20 obese children with a mean body mass index (BMI) of 39.2± 12.5 and 10 matched control subjects with mean BMI of 18.4± 1.9. They were subjected to detailed anthropometric evaluation including weight, height, and waist hip ratio in addition to calculation of BMI, complete blood counting, and flow cytometric assessment of T-helper (CD4), T-cytotoxic/suppressor (CD8), and natural killer (CD56) cell counts .Results: The absolute lymphocyte (CD3) and natural killer cell (CD56) counts were comparable in both groups. However, the CD4%, CD8%, CD4/CD8 ratio were significantly lower in the obese children (p=0.02, 0.03, 0.015 respectively). A significant negative correlation could be elicited between the CD4 count and bodyweight, BMI, and hip waist ratio (p = 0.00); the same was observed for CD4/CD8 ratio (p = 0.00). On the contrary, CD8 correlated positively to the bodyweight, BMI, and waist hip ratio (p = 0.00 for each) .Conclusion: Obesity has an impact on lymphocytic subset counts and further studies are needed to assess its effect on their function.Keywords: obesity, children immunology; CD markers; lymphocytes; BM

Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine

Radiogenomics, a combination of “Radiomics” and “Genomics,” using Artificial Intelligence (AI) has recently emerged as the state-of-the-art science in precision medicine, especially in oncology care. Radiogenomics syndicates large-scale quantifiable data extracted from radiological medical images enveloped with personalized genomic phenotypes. It fabricates a prediction model through various AI methods to stratify the risk of patients, monitor therapeutic approaches, and assess clinical outcomes. It has recently shown tremendous achievements in prognosis, treatment planning, survival prediction, heterogeneity analysis, reoccurrence, and progression-free survival for human cancer study. Although AI has shown immense performance in oncology care in various clinical aspects, it has several challenges and limitations. The proposed review provides an overview of radiogenomics with the viewpoints on the role of AI in terms of its promises for computa-tional as well as oncological aspects and offers achievements and opportunities in the era of precision medicine. The review also presents various recommendations to diminish these obstacles

Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework

Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis. The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor. The radiomics approach uses the radiological image for disease characterization by extracting quantitative radiomics features in the artificial intelligence (AI) environment. However, when considering a higher level of disease characteristics such as genetic information and mutation status, the combined study of “radiomics and genomics” has been considered under the umbrella of “radiogenomics”. Furthermore, AI in a radiogenomics’ environment offers benefits/advantages such as the finalized outcome of personalized treatment and individualized medicine. The proposed study summarizes the brain tumor’s characterization in the prospect of an emerging field of research, i.e., radiomics and radiogenomics in an AI environment, with the help of statistical observation and risk-of-bias (RoB) analysis. The PRISMA search approach was used to find 121 relevant studies for the proposed review using IEEE, Google Scholar, PubMed, MDPI, and Scopus. Our findings indicate that both radiomics and radiogenomics have been successfully applied aggressively to several oncology applications with numerous advantages. Furthermore, under the AI paradigm, both the conventional and deep radiomics features have made an impact on the favorable outcomes of the radiogenomics approach of BTC. Furthermore, risk-of-bias (RoB) analysis offers a better understanding of the architectures with stronger benefits of AI by providing the bias involved in them

Maternal Humoral Immune Correlates of Peripartum Transmission of Clade C HIV-1 in the Setting of Peripartum Antiretrovirals

ABSTRACT Despite the widespread use of antiretrovirals (ARV), more than 150,000 pediatric HIV-1 infections continue to occur annually. Supplemental strategies are necessary to eliminate pediatric HIV infections. We previously reported that maternal HIV envelope-specific anti-V3 IgG and CD4 binding site-directed antibodies, as well as tier 1 virus neutralization, predicted a reduced risk of mother-to-child transmission (MTCT) of HIV-1 in the pre-ARV era U.S.-based Women and Infants Transmission Study (WITS) cohort. As the majority of ongoing pediatric HIV infections occur in sub-Saharan Africa, we sought to determine if the same maternal humoral immune correlates predicted MTCT in a subset of the Malawian Breastfeeding, Antiretrovirals, and Nutrition (BAN) cohort of HIV-infected mothers ( n = 88, with 45 transmitting and 43 nontransmitting). Women and infants received ARV at delivery; thus, the majority of MTCT was in utero (91%). In a multivariable logistic regression model, neither maternal anti-V3 IgG nor clade C tier 1 virus neutralization was associated with MTCT. Unexpectedly, maternal CD4 binding-site antibodies and anti-variable loop 1 and 2 (V1V2) IgG were associated with increased MTCT, independent of maternal viral load. Neither infant envelope (Env)-specific IgG levels nor maternal IgG transplacental transfer efficiency was associated with transmission. Distinct humoral immune correlates of MTCT in the BAN and WITS cohorts could be due to differences between transmission modes, virus clades, or maternal antiretroviral use. The association between specific maternal antibody responses and in utero transmission, which is distinct from potentially protective maternal antibodies in the WITS cohort, underlines the importance of investigating additional cohorts with well-defined transmission modes to understand the role of antibodies during HIV-1 MTCT

Short Communication: HIV Type 1 Subtype C Variants Transmitted Through the Bottleneck of Breastfeeding Are Sensitive to New Generation Broadly Neutralizing Antibodies Directed Against Quaternary and CD4-Binding Site Epitopes

Mother-to-child transmission of HIV-1 subtype C can occur in utero, intrapartum, or via breast milk exposure. While not well understood, there are putative differences in the mechanisms involved with the distinct routes of vertical HIV transmission. Here, we address the question of whether specific viral characteristics are common to variants transmitted through breastfeeding that may facilitate evasion of innate or adaptive immune responses. We amplified the envelope gene (env) from the plasma of six infants during acute infection who were infected with HIV-1 subtype C through breastfeeding, and from three available matched maternal samples. We sequenced the full-length env genes in these subjects revealing heterogeneous viral populations in the mothers and homogeneous populations in the infants. In five infants, the viral population arose from a single variant, while two variants were detected in the remaining infant. Infant env sequences had fewer N-linked glycosylation sites and shorter sequences than those of the available matched maternal samples. Though the small size of the study precluded our ability to test statistical significance, these results are consistent with selection for virus with shorter variable loops and fewer glycosylation sites during transmission of HIV-1 subtype C in other settings. Transmitted envs were resistant to neutralization by antibodies 2G12 and 2F5, but were generally sensitive to the more broadly neutralizing PG9, PG16, and VRC01, indicating that this new generation of broadly neutralizing monoclonal antibodies could be efficacious in passive immunization strategies