Cardiovascular Risk Awareness, Exercise Practices and Metabolic Outcomes among Patients with Diabetes Mellitus in Northern Nigeria: A Cross-sectional, Multicentre Study.

BACKGROUND: Physical exercise helps to mitigate cardiovascular risks in people with diabetes mellitus (DM), but there are limited data in Nigeria. This study aimed to assess cardiovascular risk awareness, exercise practices and metabolic outcomes among Nigerians with diabetes. MATERIALS AND METHODS: We conducted a cross-sectional study at five tertiary hospitals using questionnaire interviews and clinical assessments. Participants' knowledge of cardiovascular risk factors and knowledge of exercise were assessed on 12- and 5-item scores, while exercise practices were classed as adequate if performed regularly on 3 or more days weekly for a total of 150 min or more based on the American Diabetes Association recommendations. Mean body mass index (BMI), blood pressure (BP), fasting blood glucose, serum haemoglobin A1C (HbA1c), lipid profile, urea, creatinine and uric acid were then compared among participant groups. RESULTS: We studied 426 participants with DM, 58.7% females. The mean age was 52.9 ± 13.1 years, with males significantly older than females (54.6 ± 12.2 vs. 51.8 ± 13.5 years; 95% confidence interval: 0.27-5.28, P = 0.03). The mean age at diabetes diagnosis was 44.8 ± 11.7 years, and the median duration of diabetes was 84 months. There was low knowledge of cardiovascular risk factors and low knowledge of exercise (mean scores of 2.94 and 2.31, respectively). Forty-three per cent of participants reported adequate exercise, which was significantly associated with younger age (P = 0.007), male gender (P = 0.001) and formal education (P = 0.021). Participants with adequate exercise had lower systolic BP and serum urea compared to those with inadequate exercise, but there were no significant differences in BMI, fasting glucose, HbA1c, serum lipids, creatinine or uric acid. CONCLUSION: Participants had low knowledge of cardiovascular risks and the appropriate exercise practices for diabetes patients. There is a need for better patient education on diabetes self-care and exercise at clinic visits.

Multidrug-resistant tuberculosis.

One of predominant contributors to global mortality is tuberculosis (TB), an infection caused by Mycobacterium tuberculosis (MTB). Inappropriate and ineffectual treatment can lead to the development of drug-resistant TB. One of the most common forms of drug-resistant TB is multidrug-resistant tuberculosis (MDR-TB), caused by mutations in the rpoB and katG genes that lead to resistance to anti-TB drugs, rifampicin (RIF) and isoniazid (INH), respectively. Although culturing remains the gold standard, it is not rapid thereby delaying potential treatment and potentially increasing the incidence of MDR-TB. In contrast, molecular techniques provide a highly sensitive and specific alternative. This review discusses the classification of biomarkers used to detect MDR-TB, some of the commonly used anti-TB drugs, and DNA mutations in MTB that lead to anti-TB resistance. The objective of this review is to increase awareness of the need for rapid and precise detection of MDR-TB cases to decrease morbidity and mortality of this infectious disease worldwide.

Classification of H. pylori Infection from Histopathological Images Using Deep Learning.

Helicobacter pylori (H. pylori) is a widespread pathogenic bacterium, impacting over 4 billion individuals globally. It is primarily linked to gastric diseases, including gastritis, peptic ulcers, and cancer. The current histopathological method for diagnosing H. pylori involves labour-intensive examination of endoscopic biopsies by trained pathologists. However, this process can be time-consuming and may occasionally result in the oversight of small bacterial quantities. Our study explored the potential of five pre-trained models for binary classification of 204 histopathological images, distinguishing between H. pylori-positive and H. pylori-negative cases. These models include EfficientNet-b0, DenseNet-201, ResNet-101, MobileNet-v2, and Xception. To evaluate the models' performance, we conducted a five-fold cross-validation, ensuring the models' reliability across different subsets of the dataset. After extensive evaluation and comparison of the models, ResNet101 emerged as the most promising. It achieved an average accuracy of 0.920, with impressive scores for sensitivity, specificity, positive predictive value, negative predictive value, F1 score, Matthews's correlation coefficient, and Cohen's kappa coefficient. Our study achieved these robust results using a smaller dataset compared to previous studies, highlighting the efficacy of deep learning models even with limited data. These findings underscore the potential of deep learning models, particularly ResNet101, to support pathologists in achieving precise and dependable diagnostic procedures for H. pylori. This is particularly valuable in scenarios where swift and accurate diagnoses are essential.

Smart Graphene-Based Electrochemical Nanobiosensor for Clinical Diagnosis: Review.

The technological improvement in the field of physics, chemistry, electronics, nanotechnology, biology, and molecular biology has contributed to the development of various electrochemical biosensors with a broad range of applications in healthcare settings, food control and monitoring, and environmental monitoring. In the past, conventional biosensors that have employed bioreceptors, such as enzymes, antibodies, Nucleic Acid (NA), etc., and used different transduction methods such as optical, thermal, electrochemical, electrical and magnetic detection, have been developed. Yet, with all the progresses made so far, these biosensors are clouded with many challenges, such as interference with undesirable compound, low sensitivity, specificity, selectivity, and longer processing time. In order to address these challenges, there is high need for developing novel, fast, highly sensitive biosensors with high accuracy and specificity. Scientists explore these gaps by incorporating nanoparticles (NPs) and nanocomposites (NCs) to enhance the desired properties. Graphene nanostructures have emerged as one of the ideal materials for biosensing technology due to their excellent dispersity, ease of functionalization, physiochemical properties, optical properties, good electrical conductivity, etc. The Integration of the Internet of Medical Things (IoMT) in the development of biosensors has the potential to improve diagnosis and treatment of diseases through early diagnosis and on time monitoring. The outcome of this comprehensive review will be useful to understand the significant role of graphene-based electrochemical biosensor integrated with Artificial Intelligence AI and IoMT for clinical diagnostics. The review is further extended to cover open research issues and future aspects of biosensing technology for diagnosis and management of clinical diseases and performance evaluation based on Linear Range (LR) and Limit of Detection (LOD) within the ranges of Micromolar µM (10-6), Nanomolar nM (10-9), Picomolar pM (10-12), femtomolar fM (10-15), and attomolar aM (10-18).

Detection of Tropical Diseases Caused by Mosquitoes Using CRISPR-Based Biosensors.

Tropical diseases (TDs) are among the leading cause of mortality and fatality globally. The emergence and reemergence of TDs continue to challenge healthcare system. Several tropical diseases such as yellow fever, tuberculosis, cholera, Ebola, HIV, rotavirus, dengue, and malaria outbreaks have led to endemics and epidemics around the world, resulting in millions of deaths. The increase in climate change, migration and urbanization, overcrowding, and other factors continue to increase the spread of TDs. More cases of TDs are recorded as a result of substandard health care systems and lack of access to clean water and food. Early diagnosis of these diseases is crucial for treatment and control. Despite the advancement and development of numerous diagnosis assays, the healthcare system is still hindered by many challenges which include low sensitivity, specificity, the need of trained pathologists, the use of chemicals and a lack of point of care (POC) diagnostic. In order to address these issues, scientists have adopted the use of CRISPR/Cas systems which are gene editing technologies that mimic bacterial immune pathways. Recent advances in CRISPR-based biotechnology have significantly expanded the development of biomolecular sensors for diagnosing diseases and understanding cellular signaling pathways. The CRISPR/Cas strategy plays an excellent role in the field of biosensors. The latest developments are evolving with the specific use of CRISPR, which aims for a fast and accurate sensor system. Thus, the aim of this review is to provide concise knowledge on TDs associated with mosquitoes in terms of pathology and epidemiology as well as background knowledge on CRISPR in prokaryotes and eukaryotes. Moreover, the study overviews the application of the CRISPR/Cas system for detection of TDs associated with mosquitoes.

PD-L1 Status in Tenosynovial Giant Cell Tumors.

Background and Objectives: Tenosynovial giant cell tumors (TSGCTs) are benign soft tissue tumors that are divided into localized- and diffuse-type tumors, according to the World Health Organization classification of soft tissue tumours. The diffuse-type TSGCT sometimes behave aggressively and poses treatment challenges especially in patients with neurovascular involvement. Symptomatic patients who are not good candidates for surgery due to high morbidity risk may benefit from medical therapy. Objectives: Drugs that target programmed death ligand 1 (PD-L1) are among a new generation of medical therapy options, which, recently, have been explored and have displayed promising results in various cancer types; therefore, we aimed to investigate the PD-L1 status of TSGCTs as a possible therapeutic target. Materials and Methods: We assessed the PD-L1 status of 20 patients (15 men and 5 women, median age = 39 years) that had been diagnosed with TSGCTs in a single institution, between 2018 and 2020. The patients had localized- (n = 7) and diffuse-type (n = 13) TSGCTs. Formalin-fixed paraffin-embedded (FFPE) blocks were retrospectively retrieved from the pathology department. An immunohistochemical analysis was performed in sections of 3 micron thickness from these blocks. Results: Seventy-five percent of our patients with TSGCTs were immunopositive to PD-L1 staining. Conclusions: Taking into consideration the high positivity rate of PD-L1 staining in TSGCTs, PD-L1 blockage may be used as a valuable medical treatment for TSGCTs; however, further studies are needed.

Futuristic CRISPR-based biosensing in the cloud and internet of things era: an overview.

Biosensors-based devices are transforming medical diagnosis of diseases and monitoring of patient signals. The development of smart and automated molecular diagnostic tools equipped with biomedical big data analysis, cloud computing and medical artificial intelligence can be an ideal approach for the detection and monitoring of diseases, precise therapy, and storage of data over the cloud for supportive decisions. This review focused on the use of machine learning approaches for the development of futuristic CRISPR-biosensors based on microchips and the use of Internet of Things for wireless transmission of signals over the cloud for support decision making. The present review also discussed the discovery of CRISPR, its usage as a gene editing tool, and the CRISPR-based biosensors with high sensitivity of Attomolar (10-18 M), Femtomolar (10-15 M) and Picomolar (10-12 M) in comparison to conventional biosensors with sensitivity of nanomolar 10-9 M and micromolar 10-3 M. Additionally, the review also outlines limitations and open research issues in the current state of CRISPR-based biosensing applications.

Prevalence, patterns and predictors of dyslipidaemia in Nigeria: a report from the REMAH study.

AIM: The aim of this study was to determine the prevalence and predictors of dyslipidaemia in adults in Nigeria. METHODS: Using the WHO criteria, we determined dyslipidaemia using serum lipid levels of 3 211 adult Nigerians, aged at least 18 years, obtained between March 2017 and February 2018 from two communities (rural and urban) in a state from each of the six geopolitical zones of Nigeria. RESULTS: The overall prevalence of low high-density lipoprotein cholesterol (l-HDL), elevated low-density lipoprotein cholesterol (e-LDL), hypertriglyceridaemia (h-TG) and hypercholesterolaemia (h-CHL) were 72.5,13.6, 21.4 and 7.5%, respectively. The adjusted odds of h-CHL [odds ratio (95% confidence interval) 1.47 (1.10-1.95)], h-TG [1.89 (1.48-2.41)] and e-LDL [1.51 (1.03-2.15)] increased with obesity. Being a rural dweller increased the odds of h-TG [1.55 (1.29-1.85)], e-LDL [1.38 (1.10-1.73)] and l-HDL [1.34 (1.14-1.58)]. The odds of h-CHL [2.16 (1.59-2.95)], h-TG [1.21 (1.01-1.47)], e-LDL [1.42 (1.13-1.80)] and l-HDL [0.78 (0.65-0.93)] increased with hypertension. Diabetes mellitus doubled only the odds of h-TG [2.04(1.36-3.03)]. CONCLUSION: The prevalence of dyslipidaemia, particularly low HDL-C, is high among adult Nigerians.

Registry for Acute Coronary Events in Nigeria (RACE-Nigeria): Clinical Characterization, Management, and Outcome.

Background Coronary artery disease was hitherto a rarity in Africa. Acute coronary syndrome (ACS) accounts for coronary artery disease-related morbidity and mortality. Reports on ACS in Africa are few. Methods and Results We enrolled 1072 indigenous Nigerian people 59.2±12.4 years old (men, 66.8%) with ACS in an observational multicentered national registry (2013-2018). Outcome measures included incidence, intervention times, reperfusion rates, and 1-year mortality. The incidence of ACS was 59.1 people per 100 000 hospitalized adults per year, and comprised ST-segment-elevation myocardial infarction (48.7%), non-ST-segment-elevation myocardial infarction (24.5%), and unstable angina (26.8%). ACS frequency peaked 10 years earlier in men than women. Patients were predominantly from urban settings (87.3%). Median time from onset of symptoms to first medical contact (patients with ST-segment-elevation myocardial infarction) was 6 hours (interquartile range, 20.1 hours), and only 11.9% presented within a 12-hour time window. Traditional risk factors of coronary artery disease were observed. The coronary angiography rate was 42.4%. Reperfusion therapies included thrombolysis (17.1%), percutaneous coronary intervention (28.6%), and coronary artery bypass graft (11.2%). Guideline-based pharmacotherapy was adequate. Major adverse cardiac events were 30.8%, and in-hospital mortality was 8.1%. Mortality rates at 30 days, 3 months, 6 months, and 1 year were 8.7%, 9.9%, 10.9%, and 13.3%, respectively. Predictors of mortality included resuscitated cardiac arrest (odds ratio [OR], 50.0; 95% CI, 0.010-0.081), nonreperfusion (OR, 34.5; 95% CI, 0.004-0.221), pulmonary edema (OR, 11.1; 95% CI, 0.020-0.363), left ventricular diastolic dysfunction (OR, 4.1; 95% CI, 0.091-0.570), and left ventricular systolic dysfunction (OR, 2.1; 95% CI, 1.302-3.367). Conclusions ACS burden is rising in Nigeria, and patients are relatively young and from an urban setting. The system of care is evolving and is characterized by lack of capacity and low patient eligibility for reperfusion. We recommend preventive strategies and health care infrastructure-appropriate management guidelines.

Current Technologies for Detection of COVID-19: Biosensors, Artificial Intelligence and Internet of Medical Things (IoMT): Review.

Despite the fact that COVID-19 is no longer a global pandemic due to development and integration of different technologies for the diagnosis and treatment of the disease, technological advancement in the field of molecular biology, electronics, computer science, artificial intelligence, Internet of Things, nanotechnology, etc. has led to the development of molecular approaches and computer aided diagnosis for the detection of COVID-19. This study provides a holistic approach on COVID-19 detection based on (1) molecular diagnosis which includes RT-PCR, antigen-antibody, and CRISPR-based biosensors and (2) computer aided detection based on AI-driven models which include deep learning and transfer learning approach. The review also provide comparison between these two emerging technologies and open research issues for the development of smart-IoMT-enabled platforms for the detection of COVID-19.

Quality of life impairment amongst persons living with vitiligo using disease specific vitiligo quality of life index: A Nigerian perspective.

BACKGROUND: Vitiligo is an acquired pigmentary disorder of the skin and mucous membranes which manifests as white macules and patches due to selective loss of melanocytes. This condition can affect the patients' psychology, leading to an impairment of quality of life (QOL). Recently, much attention is been given to the emotional and psychological issues in the affected subjects. AIM OF THE STUDY: This was to assess the QOL impairment among Nigerian patients with vitiligo using a disease-specific quality of life index questionnaire (VitiQoL). MATERIALS AND METHODS: Seventy seven adults aged 18 years and above with vitiligo attending the Dermatology Clinic of a tertiary health center were included in this cross-sectional study. The QOL was assessed using the vitiligo quality of life questionnaire (VitiQoL). Disease severity was assessed using Vitiligo Area Severity Index (VASI). RESULTS: The mean age of the study participants was 38.97 ± 13.2 years, comprising of 32 (41.6%) and 45 (58.4%) females. Almost half of the vitiligo patients belong to the lower socioeconomic class, 37 (48.1%). The mean age of first onset of vitiligo was 33.5 ± 14.84 years, with 32 (41.6%) of the participants having age of first onset between 24 and 42 years. The mean VitiQoL score was 30.51 ± 15.74 (range 3-64). There was a significant relationship between VASI score and VitiQoL (P = 0.036, r = 0.517). Other factors such as age, gender, socioeconomic status, disease activity, family history of vitiligo, duration of the disease and educational attainment were significantly associated with VitiQoL score (P < 0.05). CONCLUSION: QOL is impaired significantly in Nigerian patients with vitiligo. Focusing on patient's QOL is an essential aspect in the management of patients with vitiligo.

Automated detection of Mycobacterium tuberculosis using transfer learning.

INTRODUCTION: Quantitative analysis of Mycobacterium tuberculosis using microscope is very critical for diagnosing tuberculosis diseases. Microbiologist encounter several challenges which can lead to misdiagnosis. However, there are 3 main challenges: (1) The size of Mycobacterium tuberculosis is very small and difficult to identify as a result of low contrast background, heterogenous shape, irregular appearance and faint boundaries (2) Mycobacterium tuberculosis overlapped with each other making it difficult to conduct accurate diagnosis (3) Large amount of slide can be time consuming and tedious to microbiologist and which can lead to misinterpretations. METHODOLOGY: To solve these challenges and limitations, we proposed an automated-based detection method using pretrained AlexNet to trained the model in 3 sets of experiments A, B and C and adjust the protocols accordingly. We compared the detection of tuberculosis using AlexNet Models with the ground truth result provided by microbiologist and analyzed inconsistencies between network models and human. RESULTS: 98.15 % accuracy, 96.77% sensitivity and 100% specificity for experiment A, 98.09% accuracy, 98.59% sensitivity and 97.67% specificity for experiment B and 98.73% testing accuracy, 98.59 sensitivity, 98.84% specificity ofr experiment C which sound robust and promising. CONCLUSIONS: The results indicated that network performance was successful with high accuracies, sensitivities and specificities and it can be used to support microbiologist for diagnosis of tuberculosis.

Pneumonia Classification Using Deep Learning from Chest X-ray Images During COVID-19.

The outbreak of the novel corona virus disease (COVID-19) in December 2019 has led to global crisis around the world. The disease was declared pandemic by World Health Organization (WHO) on 11th of March 2020. Currently, the outbreak has affected more than 200 countries with more than 37 million confirmed cases and more than 1 million death tolls as of 10 October 2020. Reverse-transcription polymerase chain reaction (RT-PCR) is the standard method for detection of COVID-19 disease, but it has many challenges such as false positives, low sensitivity, expensive, and requires experts to conduct the test. As the number of cases continue to grow, there is a high need for developing a rapid screening method that is accurate, fast, and cheap. Chest X-ray (CXR) scan images can be considered as an alternative or a confirmatory approach as they are fast to obtain and easily accessible. Though the literature reports a number of approaches to classify CXR images and detect the COVID-19 infections, the majority of these approaches can only recognize two classes (e.g., COVID-19 vs. normal). However, there is a need for well-developed models that can classify a wider range of CXR images belonging to the COVID-19 class itself such as the bacterial pneumonia, the non-COVID-19 viral pneumonia, and the normal CXR scans. The current work proposes the use of a deep learning approach based on pretrained AlexNet model for the classification of COVID-19, non-COVID-19 viral pneumonia, bacterial pneumonia, and normal CXR scans obtained from different public databases. The model was trained to perform two-way classification (i.e., COVID-19 vs. normal, bacterial pneumonia vs. normal, non-COVID-19 viral pneumonia vs. normal, and COVID-19 vs. bacterial pneumonia), three-way classification (i.e., COVID-19 vs. bacterial pneumonia vs. normal), and four-way classification (i.e., COVID-19 vs. bacterial pneumonia vs. non-COVID-19 viral pneumonia vs. normal). For non-COVID-19 viral pneumonia and normal (healthy) CXR images, the proposed model achieved 94.43% accuracy, 98.19% sensitivity, and 95.78% specificity. For bacterial pneumonia and normal CXR images, the model achieved 91.43% accuracy, 91.94% sensitivity, and 100% specificity. For COVID-19 pneumonia and normal CXR images, the model achieved 99.16% accuracy, 97.44% sensitivity, and 100% specificity. For classification CXR images of COVID-19 pneumonia and non-COVID-19 viral pneumonia, the model achieved 99.62% accuracy, 90.63% sensitivity, and 99.89% specificity. For the three-way classification, the model achieved 94.00% accuracy, 91.30% sensitivity, and 84.78%. Finally, for the four-way classification, the model achieved an accuracy of 93.42%, sensitivity of 89.18%, and specificity of 98.92%.

Prevalence and Determinants of Masked Hypertension in Nigeria: The REMAH Study.

BACKGROUND: Estimating the burden of hypertension in Nigeria hitherto relied on clinic blood pressure (BP) measurement alone. This excludes individuals with masked hypertension (MH), i.e., normotensive clinic but hypertensive out-of-clinic BP. METHODS: In a nationally representative sample of adult Nigerians, we obtained clinic BP using auscultatory method and out-of-clinic BP by self-measured home BP with semi-automated oscillometric device. Clinic BP was average of 5 consecutive measurements and home BP was average of 3 days duplicate morning and evening readings. MH was clinic BP <140 mm Hg systolic and 90 mm Hg diastolic and home BP ≥135 mm Hg systolic and/or 85 mm Hg diastolic. RESULTS: Among 933 participants, the prevalence of sustained hypertension, MH, and white-coat hypertension was 28.3%, 7.9%, and 11.9%, respectively. Among subjects whose clinic BP were in the normotensive range (n = 558), the prevalence of MH was 13%; 12% among untreated and 27% among treated individuals. The mutually adjusted odds ratios of having MH among all participants with normotensive clinic BP were 1.33 (95% confidence interval, 1.10-1.60) for a 10-year higher age, 1.59 (1.09-2.40) for a 10 mm Hg increment in systolic clinic BP, and 1.16 (1.08-1.28) for a 10 mg/dl higher random blood glucose. The corresponding estimates in the untreated population were 1.24 (1.03-1.51), 1.56 (1.04-2.44), and 1.16 (1.08-1.29), respectively. CONCLUSIONS: MH is common in Nigeria and increasing age, clinic systolic BP, and random blood glucose are the risk factors.

Urinary sodium excretion and its association with blood pressure in Nigeria: A nationwide population survey.

Assessment of level of salt intake in a population is the first step toward planning strategies aimed at salt reduction. As a surrogate of salt intake, we measured a single 24-hour urine sodium (uNa) of free-living 2503 adults in a nationally representative sample of Nigerians drawn from 12 rural and urban communities; and evaluated the community-level association of uNa with blood pressure (BP). Overall, the median (interquartile range (IQR)) of uNa was 99 (105) mmol, ranging from 23.8 (32.4) in rural north-central to 172.8 (131.0) mmol in urban northwestern region. Daily uNa was significantly higher (p < .001) in men compared to women (107.1 vs 93.9 mmol); and urban compared to rural dwellers (114.9 vs 86.0mmol). About one-half of participants excreted uNa in excess of recommended daily maximum value (86mmol). In a model adjusted for age, sex, body mass index (BMI), level of education, place of residence, and use of antihypertensive medication; being a man (odds ratio, OR 1.69, 95% confidence Interval CI, 1.21-2.37, p = .002) and being < 60 years of age (OR 1.74, 95% CI 1.23-2.45, p = .002), were associated with excreting higher than recommended uNa. In a fully adjusted model of the community-level analysis, urinary sodium, potassium, and sodium-to-potassium ratio each showed no significant independent association with both systolic and diastolic BPs. Among adult Nigerians, the median daily uNa excretion was 99 mmol and it had no significant association with blood pressure indices.

Prevalence, Awareness, Treatment and Control of Hypertension in Nigeria: Data from a Nationwide Survey 2017.

Background: Previous studies that evaluated the prevalence, awareness and treatment of hypertension in Nigeria were either localized to some specific regions of the country or non-standardized thereby making evaluation of trend in hypertension care difficult. Methods: We used the World Health Organization (WHO) STEPwise approach to chronic disease risk factor surveillance to evaluate in a nationally representative sample of 4192 adult Nigerians selected from a rural and an urban community in one state in each of the six geo-political zones of the country. Results: The overall age-standardized prevalence of hypertension was 38.1% and this varied across the geo-political zones as follows: North-Central, 20.9%; North-East, 27.5%; North-West, 26.8%; South-East, 52.8%; South-South, 44.6%; and South-West, 42.1%. Prevalence rate did not differ significantly (p > 0.05) according to place of residence; 39.2% versus 37.5 %; urban vs rural. Prevalence of hypertension increased from 6.8% among subjects less than 30 years to 63.0% among those aged 70 years and above. Awareness was better (62.2% vs. 56.6%; P = 0.0272); treatment rate significantly higher (40.9 % vs. 30.8%; P < 0.0001) and control similar (14 vs. 10.8%) among urban compared to rural residents. Women were more aware of (63.3% vs. 52.8%; P < 0.0001); had similar (P > 0.05) treatment (36.7 vs. 34.3%) and control (33.9% vs. 35.5%) rates of hypertension compared to men. Conclusion: Our results suggest a large burden of hypertension in Nigeria and a closing up of the rural-urban gap previously reported. This calls for a change in public health policies anchored on a primary health care system to address the emerging disease burden occasioned by hypertension.

The role of immune restoration using highly active antiretroviral therapy in the management of AIDS-related Kaposi's sarcoma coexisting with pulmonary tuberculosis.

A 35-year-old highly active antiretroviral therapy (HAART)-naïve woman diagnosed 2 years earlier presented with complaints of cough, fever and progressive weight loss of 5 months and skin rashes of 2 months. Clinical examination revealed a chronically ill-looking young woman who was wasted and pale, with purplish flat-topped papules and nodules on the skin of her neck, trunk, forearms and thighs. She also had a single lesion on the hard palate. Chest examination shows reduced breath sounds with crepitations. Sputum acid-fast bacilli were positive, and skin biopsy taken for histology confirmed Kaposi's sarcoma (KS). The patient recovered fully on antiretroviral and antituberculosis therapy without the need for any specific chemotherapy for KS. We report this case to elucidate the role of immune reconstitution as a treatment modality for AIDS-related KS, as well as to point out the possibility of multiple opportunistic conditions coexisting amongst patients with advanced HIV disease.

Successful pregnancy following acquired gynatresia.

Acquired gynatresia is a common gynecological condition in developing countries where puerperal complications and unskilled interventions prevail. A 23-year-old primipara who had spontaneous vaginal delivery complicated by gynatresia had vaginoplasty that failed due to erectile dysfunction in the spouse. She subsequently developed secondary amenorrhea and was relieved with dilatation and evacuation. She was planned for definitive surgery, however,she incidentally conceived with q pin-hole vagina. She was delivered of a live fetus at term via an elective cesarean section. This case is peculiar as spontaneous conception occurred with a pinhole opening. There is a need to adequately evaluate cases before definitive management to maximize success.

Résumé Acquis Gynatrésie est une condition gynécologique commune dans les pays en développement où les complications puerpérale et les interventions non qualifiées Prévaloir. Un primipares de 23 ans qui avait la livraison vaginale spontanée compliquée par Gynatrésie avait vaginoplastie qui a échoué en raison de l'érection dysfonctionnement chez le conjoint. Elle a par la suite développé une aménorrhée secondaire et a été soulagée par la dilatation et l'évacuation. Elle a été travaillé pour défi nitive chirurgie quand elle accidentellement conçu avec une cavité vaginale sténopé et a été livré d'un fœtus vivant à terme à travers césarienne élective. Ce cas est particulier que la conception spontanée a eu lieu avec une ouverture sténopé. Il est nécessaire de Evaluer les cas avant la gestion défi nitive pour maximiser le succès.

Closure of skin incision by dual wavelength (980 and 1064 nm) laser application.

Thermal effect of dual wavelength (980 and 1064 nm) laser application in skin incision closure was assessed on 18 male and female Wister rats. 1-cm-long incisions were made on the shaved dorsal region of 220-250 g animals. The incisions were closed by laser irradiation at 1 W and exposure time, 5 seconds in continuous-wave mode (CW) and 1 W and exposure time, 10 seconds in pulsed mode to deliver total energies of 5 J and 10 J per spot onto the incisions, respectively. Animals from each group were sacrificed at 0th, 4th, and 7th days and the skin samples of the weld area were excised for histological analysis using Hematoxylin and Eosin (H & E) stain. Mean thermally altered area (TAA) of CW-mode laser-treated groups was found to increase significantly (p < 0.05) compared with pulsed mode laser treated group at 0th and 4th days post-irradiation while no significant difference (p > 0.05) was statistically found at 7th day post-irradiation. Moreover, tighter closure was observed with CW group at 7th day post-irradiation. We thus conclude that 1 W, 5 J for 5 seconds CW mode laser application of 980 and 1064 nm combined beam form in skin incision closure was found to have absolute wound healing capability with minimal thermal alteration.

Intrigues of biofilm: A perspective in veterinary medicine.

Biofilm has a tremendous impact in the field of veterinary medicine, especially the livestock industry, leading to a serious economic loss. Over the years, little attention has been given to biofilm in animals with most of the research geared toward human biofilm diseases. The greatest challenge posed by biofilm is in its incredible ability to resist most of the currently existing antibiotics. This mystery can best be demystified through understanding the mechanism of the quorum sensing which regulate the pathophysiology of biofilm. Ability of biofilm formation in a variety of inanimate surfaces such as animal food contact surfaces is responsible for a host of biofilm diseases affecting animals and humans. In this review, we highlighted some of the challenges of biofilm in livestock and food industries. Also highlighted are; mechanisms of biofilm development, best diagnostic approach and possible novel therapeutic measures needed to combat the menace of biofilm in veterinary medicine.