From Hypertension to Beyond: Unraveling the Diverse Mechanisms of Olmesartan in Disease Modulation

Olmesartan, originally known for its antihypertensive properties, exhibits promising potential in addressing inflammation-mediated diseases. As an angiotensin II receptor blocker (ARB), Olmesartan influences pivotal pathways, including reactive oxygen species, cytokines, NF-κB, TNF-α, and MAPK. This suggests a viable opportunity for repurposing the drug in conditions such as ulcerative colitis, neuropathy, nephropathy, and cancer, as supported by multiple preclinical studies. Ongoing clinical trials, particularly in cardiomyopathy and nephropathy, suggest a broader therapeutic scope for Olmesartan. Repurposing efforts would entail comprehensive investigations using disease-specific preclinical models and dedicated clinical studies. The drug's established safety profile, wide availability, and well-understood ARB mechanism of action offer distinct advantages that could facilitate a streamlined repurposing process. In summary, Olmesartan's versatile impact on inflammation-related pathways positions it as a promising candidate for repurposing across various diseases. Ongoing clinical trials and the drug's favorable attributes enhance its appeal for further exploration and potential application in diverse medical contexts.

Repurposing of Drugs for Cardiometabolic Disorders: An Out and Out Cumulation

Cardiometabolic disorders (CMD) is a constellation of metabolic predisposing factors for atherosclerosis such as insulin resistance (IR) or diabetes mellitus (DM), systemic hypertension, central obesity, and dyslipidemia. Cardiometabolic diseases (CMDs) continue to be the leading cause of mortality in both developed and developing nations, accounting for over 32% of all fatalities globally each year. Furthermore, dyslipidemia, angina, arrhythmia, heart failure, myocardial infarction (MI), and diabetes mellitus are the major causes of death, accounting for an estimated 19 million deaths in 2012. CVDs will kill more than 23 million individuals each year by 2030. Nonetheless, new drug development (NDD) in CMDs has been increasingly difficult in recent decades due to increased costs and a lower success rate. Drug repositioning in CMDs looks promising in this scenario for launching current medicines for new therapeutic indications. Repositioning is an ancient method that dates back to the 1960s and is mostly based on coincidental findings during medication trials. One significant advantage of repositioning is that the drug's safety profile is well known, lowering the odds of failure owing to undesirable toxic effects. Furthermore, repositioning takes less time and money than NDD. Given these facts, pharmaceutical corporations are becoming more interested in medication repositioning. In this follow-up, we discussed the notion of repositioning and provided some examples of repositioned medications in cardiometabolic disorders.

An Ensemble Model for Consumer Emotion Prediction Using EEG Signals for Neuromarketing Applications

Traditional advertising techniques seek to govern the consumer's opinion toward a product, which may not reflect their actual behavior at the time of purchase. It is probable that advertisers misjudge consumer behavior because predicted opinions do not always correspond to consumers' actual purchase behaviors. Neuromarketing is the new paradigm of understanding customer buyer behavior and decision making, as well as the prediction of their gestures for product utilization through an unconscious process. Existing methods do not focus on effective preprocessing and classification techniques of electroencephalogram (EEG) signals, so in this study, an effective method for preprocessing and classification of EEG signals is proposed. The proposed method involves effective preprocessing of EEG signals by removing noise and a synthetic minority oversampling technique (SMOTE) to deal with the class imbalance problem. The dataset employed in this study is a publicly available neuromarketing dataset. Automated features were extracted by using a long short-term memory network (LSTM) and then concatenated with handcrafted features like power spectral density (PSD) and discrete wavelet transform (DWT) to create a complete feature set. The classification was done by using the proposed hybrid classifier that optimizes the weights of two machine learning classifiers and one deep learning classifier and classifies the data between like and dislike. The machine learning classifiers include the support vector machine (SVM), random forest (RF), and deep learning classifier (DNN). The proposed hybrid model outperforms other classifiers like RF, SVM, and DNN and achieves an accuracy of 96.89%. In the proposed method, accuracy, sensitivity, specificity, precision, and F1 score were computed to evaluate and compare the proposed method with recent state-of-the-art methods.

An Ensemble Learning Method for Emotion Charting Using Multimodal Physiological Signals

Emotion charting using multimodal signals has gained great demand for stroke-affected patients, for psychiatrists while examining patients, and for neuromarketing applications. Multimodal signals for emotion charting include electrocardiogram (ECG) signals, electroencephalogram (EEG) signals, and galvanic skin response (GSR) signals. EEG, ECG, and GSR are also known as physiological signals, which can be used for identification of human emotions. Due to the unbiased nature of physiological signals, this field has become a great motivation in recent research as physiological signals are generated autonomously from human central nervous system. Researchers have developed multiple methods for the classification of these signals for emotion detection. However, due to the non-linear nature of these signals and the inclusion of noise, while recording, accurate classification of physiological signals is a challenge for emotion charting. Valence and arousal are two important states for emotion detection; therefore, this paper presents a novel ensemble learning method based on deep learning for the classification of four different emotional states including high valence and high arousal (HVHA), low valence and low arousal (LVLA), high valence and low arousal (HVLA) and low valence high arousal (LVHA). In the proposed method, multimodal signals (EEG, ECG, and GSR) are preprocessed using bandpass filtering and independent components analysis (ICA) for noise removal in EEG signals followed by discrete wavelet transform for time domain to frequency domain conversion. Discrete wavelet transform results in spectrograms of the physiological signal and then features are extracted using stacked autoencoders from those spectrograms. A feature vector is obtained from the bottleneck layer of the autoencoder and is fed to three classifiers SVM (support vector machine), RF (random forest), and LSTM (long short-term memory) followed by majority voting as ensemble classification. The proposed system is trained and tested on the AMIGOS dataset with k-fold cross-validation. The proposed system obtained the highest accuracy of 94.5% and shows improved results of the proposed method compared with other state-of-the-art methods.

Malware Detection in Internet of Things (IoT) Devices Using Deep Learning

Internet of Things (IoT) devices usage is increasing exponentially with the spread of the internet. With the increasing capacity of data on IoT devices, these devices are becoming venerable to malware attacks; therefore, malware detection becomes an important issue in IoT devices. An effective, reliable, and time-efficient mechanism is required for the identification of sophisticated malware. Researchers have proposed multiple methods for malware detection in recent years, however, accurate detection remains a challenge. We propose a deep learning-based ensemble classification method for the detection of malware in IoT devices. It uses a three steps approach; in the first step, data is preprocessed using scaling, normalization, and de-noising, whereas in the second step, features are selected and one hot encoding is applied followed by the ensemble classifier based on CNN and LSTM outputs for detection of malware. We have compared results with the state-of-the-art methods and our proposed method outperforms the existing methods on standard datasets with an average accuracy of 99.5%.

318 Monopolar Versus Bipolar TURBT: Bradford Experience

Aim

To compare the safety and efficacy of monopolar vs bipolar TURBT.

Method

This was a randomized control trial done over 18 months with patients being allotted randomly into the bipolar and monopolar arms. The study was carried out in the department of urology at BRI and YC. All consecutive patients undergoing TURBT for suspected bladder tumors were eligible for the study. The diagnosis was based on imaging and/or cystoscopy. Exclusion criteria included refusal to participate, unfitness for spinal anesthesia, and lack of tumor in the lateral wall. The primary objective was to compare the incidence of obturator jerk in monopolar and bipolar TURBT. The secondary objective was to study and compare the quality of histopathology specimen, detrusor muscle identification, and bladder perforation.

Results

A total of 95 transurethral resections were done over the study period. All these patients were eligible for inclusion in the study, 50 in monopolar and 45 in the bipolar arms, were analyzed. Both the study groups were comparable for age, sex, and tumor size. The incidence of obturator jerk was greater in the bipolar arm (8.8 %% vs 2%, P- value=2.25). The difference in the incidence of obturator jerk in the two arms was not statistically significant (Chi-Square test). There was no significant difference in either of the secondary outcomes.

Conclusions

The bipolar transurethral resection of the bladder tumor was not superior to monopolar resection concerning the obturator jerk, bladder perforation, and histopathological quality of the resected specimen.

Features of Mobile Apps for People with Autism in a Post COVID-19 Scenario: Current Status and Recommendations for Apps Using AI

The new 'normal' defined during the COVID-19 pandemic has forced us to re-assess how people with special needs thrive in these unprecedented conditions, such as those with Autism Spectrum Disorder (ASD). These changing/challenging conditions have instigated us to revisit the usage of telehealth services to improve the quality of life for people with ASD. This study aims to identify mobile applications that suit the needs of such individuals. This work focuses on identifying features of a number of highly-rated mobile applications (apps) that are designed to assist people with ASD, specifically those features that use Artificial Intelligence (AI) technologies. In this study, 250 mobile apps have been retrieved using keywords such as autism, autism AI, and autistic. Among 250 apps, 46 were identified after filtering out irrelevant apps based on defined elimination criteria such as ASD common users, medical staff, and non-medically trained people interacting with people with ASD. In order to review common functionalities and features, 25 apps were downloaded and analysed based on eye tracking, facial expression analysis, use of 3D cartoons, haptic feedback, engaging interface, text-to-speech, use of Applied Behaviour Analysis therapy, Augmentative and Alternative Communication techniques, among others were also deconstructed. As a result, software developers and healthcare professionals can consider the identified features in designing future support tools for autistic people. This study hypothesises that by studying these current features, further recommendations of how existing applications for ASD people could be enhanced using AI for (1) progress tracking, (2) personalised content delivery, (3) automated reasoning, (4) image recognition, and (5) Natural Language Processing (NLP). This paper follows the PRISMA methodology, which involves a set of recommendations for reporting systematic reviews and meta-analyses.

Exogenous application of bio-stimulant and growth retardant improved the productivity of cotton cultivars under different planting arrangement

Optimum planting arrangement is an important attribute for efficient utilization of available resources and to obtain high yield of cotton. Application of plant growth promoter and retardant on cotton in improved planting density are the innovative techniques in the establishment of more productive cotton crop. Therefore, we planned a field study to assess the role of bio-stimulant and growth retardant in the resource utilization efficiency of cotton cultivars planted under variable row spacing at Agronomic Research Area Bahauddin Zakariya University and Usmania Agricultural Farm Shujabad during Kharif 2012. Experimental treatments consisted of cotton genotypes viz. CIM-573 and CIM-598, cultivated under conventional (75 cm), medium (50 cm) and ultra-narrow row spacing (25 cm) with foliar spray of bio-stimulant (moringa leaf extract) and growth retardant (mepiquate chloride), either sole or in combination, keeping distilled water as a control. Exogenously applied MLE alone and MLE + MC significantly enhanced the number of squares, flowers and green bolls per plant leading to higher cotton seed and lint yield of CIM 598 cultivar cultivated under conventional row spacing. While application of MC alone and MLE + MC produced maximum micronaire value, fiber strength and fiber uniformity ratio of CIM 573 cultivar cultivated under conventional row spacing. The results suggested that application of MLE is a possible approach to enhance the cotton productivity and the use of MC to enhance the fiber quality attributes under conventional row spacing.

Resource use efficiency of cotton in improved vs conventional planting geometry with exogenous application of bio-stimulant and synthetic growth retardant

Plant growth regulators and improved planting density are the innovative techniques in the establishment of more productive cotton crop. A field study was planned to assess the role of growth regulators in the resource utilization efficiency of cotton cultivars under different row spacing at Agronomic Research Area, Bahauddin Zakariya University Multan and Usmania Agricultural Farm, Shujaabad during Kharif 2012. The study was comprised of cotton cultivars viz. CIM-573 and CIM-598, cultivated under conventional (75 cm), medium (50 cm) and improved ultra-narrow row spacing (25 cm) and foliar spray of growth regulators viz. moringa leaf extract (MLE) and mepiquat chloride (MC), either alone or in combination, distilled water as a control. The application of MLE alone and in combination (MLE + MC) showed the promoting effect on crop growth rate, net assimilation rate, leaf area index, leaf area duration, sympodial branches and number of bolls leading to higher seed cotton yield of both cotton cultivars grown under conventional row spacing. While application of MC averts the plant growth without considerably improving the productivity. MLE being rich source of growth promoting hormone and nutrients showed its potential to a far greater extent under conventional row spacing in efficient utilization of available resources compared to MC and distilled water.

Analysis of iron, calcium and zinc contents in formulated fish protein hydrolyzate (FPH) complementary feeding instant powder

Complementary feeding is a transition of the baby's intake over 6 months to meet the nutritional needs in addition to breast milk. Complementary feeding should contain complete nutritional components especially in minerals. Minerals are elements needed by the body for the overall body function. Children require calcium (Ca), iron (Fe), and zinc (Zn) for their body growth to prevent stunting. This study was aimed to analyse Ca, Fe and Zn content in the formulated fish protein hydrolysate (FPH) complementary feeding porridge. A total of three formulations were produced namely F1, F2 and F3 and analysed for mineral content following AOAC method 999.11. From the analysis, F3 had the highest Fe content (38.547 mg/100 g) and Zn content (5.751 mg/100 g) while F1 had the highest Ca content (65.152 mg/100 g). Overall, F3 had the best mineral content to be formulated as a suitable FPH complementary feeding instant powder.

Anomalous aortic origin of a coronary artery (AAOCA): A case report

Anomalous Aortic Origin of a Coronary Artery (AAOCA) is a rare anomaly of the coronary artery with a considerable risk of sudden cardiac death due to ischaemia of the heart. Symptoms may include chest pain on exertion, breathlessness or dizziness. We encountered a case of a 46- year-old female who complained of exertional chest pain with a positive-stress test and subsequently diagnosed with AAOCA through CT angiography (CTA). She successfully underwent a coronary artery bypass graft (CABG) surgery using a saphenous vein graft with uneventful recovery. Right internal mammary artery (RIMA) was not used as it was flimsy and the flow was very poor.

Electrochemical determination of folic acid: A short review

Folic acid (FA) is an electroactive compound of biological origin. It helps our body to produce and maintain healthy cells. It can significantly reduce the occurrence of neural tube defects and also prevents change in DNA structure. FA deficiency can lead to various health risks. Therefore, a sensitive, specific, and reproducible way of FA detection is essential. A number of analytical methods are in practice for the quantification of FA. However, electroanalytical methods are attracting much attention because of their advantage over conventional methods, as they are fast, simple, sensitive, and cost effective. Moreover, modification of electrodes offers control over size and morphology which allows miniaturization for applicability in portable electrochemical devices.

Abstracts of the 24th international isotope society (UK group) symposium: synthesis and applications of labelled compounds 2015

The 24th annual symposium of the International Isotope Society's United Kingdom Group took place at the Møller Centre, Churchill College, Cambridge, UK on Friday 6th November 2015. The meeting was attended by 77 delegates from academia and industry, the life sciences, chemical, radiochemical and scientific instrument suppliers. Delegates were welcomed by Dr Ken Lawrie (GlaxoSmithKline, UK, chair of the IIS UK group). The subsequent scientific programme consisted of oral presentations, short 'flash' presentations in association with particular posters and poster presentations. The scientific areas covered included isotopic synthesis, regulatory issues, applications of labelled compounds in imaging, isotopic separation and novel chemistry with potential implications for isotopic synthesis. Both short-lived and long-lived isotopes were represented, as were stable isotopes. The symposium was divided into a morning session chaired by Dr Rebekka Hueting (University of Oxford, UK) and afternoon sessions chaired by Dr Sofia Pascu (University of Bath, UK) and by Dr Alan Dowling (Syngenta, UK). The UK meeting concluded with remarks from Dr Ken Lawrie (GlaxoSmithKline, UK).

LRIG1 expression during homeostasis and skin wound healing in mice

Leucine-rich repeats and immunoglobulin-like domains (LRIG)-1 belong to the family of proteins known to be expressed in skin. Ablation of LRIG1 in mice results in epidermal hyperplasia and its aberrant expression levels have been reported in pathological conditions such as psoriasis, thus evident of an indispensible role of LRIG1 in maintaining epidermal homeostasis. In order to gain insight into the homeostatic expression of LRIG1 and in various stages of cutaneous wound healing, LRIG1 expression was immunohistochemically analyzed in full thickness skin wounds in mice. The full thickness skin wounds were established on the dorsal back of Balb/c mice (n=6). LRIG1 expression at various post wounding days (1, 2, 3, 6 and 14) was determined through Immunohistochemical analysis (IHC) of the murine skin sections. The injury caused a sharp decline in LRIG1 expression in the basal epidermal cells and appendages surrounding the wound which correlates with the re-epithelialization phase of healing. LRIG1 expression remained down regulated during most of the wound healing stages. LRIG1+ cells were found to re-populate the neo-epidermis on day 14, suggesting an important homeostatic role of LRIG1 in skin.

The recurrence risk of placenta accreta following uterine conserving management

BACKGROUND

Placenta accreta is a condition of abnormal placental attachment that was usually treated by hysterectomy. Techniques to conserve the uterus are now commonly used and series of subsequent pregnancy outcomes have been reported. The recurrence risk of placenta accreta is now a relevant detail and is currently not known. This work was performed to calculate the recurrence risk by reviewing the published literature.

METHODS

A literature search using the terms "placenta accreta", "placenta percreta", "placenta increta", "abnormal placental attachment" and "placental attachment disorder" followed by hand-searching identified 6 papers that contained data concerning recurrence of placenta accreta in subsequent pregnancies following initial conservative treatment.

RESULTS

Overall 407 pregnancies were recorded and 85.7% of women reported achieved a subsequent pregnancy following conservative treatment. The risk of recurrence of placental attachment disorder in a subsequent pregnancy was 19.9% (weighted mean, 95% CI 12.2-27.7).

CONCLUSIONS

The recurrence risk of placental attachment disorder following uterine conservation treatments is 20% . This risk should be discussed with women with an antenatal diagnosis of a placental attachment disorder who may be considering uterine conservation in order to retain the option of a future pregnancy.

Use of Social Networking Sites among University Students in Ajman, United Arab Emirates

Note: a new paragraph 'What this study adds:' was added to page 250 on 27 March 2014.Background    Social networking sites are web-based services through which individuals can create a public or semi-public profile within a bounded system, connect with a list of other linked users, and view and interact with a list of their connections and with those made by others within the system. To estimate the proportion of university students using social networking sites (SNS) and to determine the association between SNS use and age, gender, nationality, course and year of study, living context, family size, number of close friends, close relationships, stress related to studies and interpersonal relationships. Materials and Methods A cross sectional study was carried out among 300 students from two universities in Ajman, UAE. A self-administered, content-validated and pilot-tested questionnaire was used. The participants answered questions related to their use of social networking sites and details of socio-demographic variables. The data collected were entered into Microsoft Excel and transferred to PASW 18.0 version. Data were analyzed as frequencies, percentages, means and SDs, and Chi-square test used for associations. The odd ratio was calculated for the significant variables to find the degree of association. The SNS usage was categorized as average, moderate or high based on mean and SD on the SNS test score.  Results The study population was comprised of 41.6% males and 58.3% females. 89% used social networking sites (SNS) and 11% were non-users. Of the 267 users of SNS, 58.8% were average users, 37.8% moderate users and 3.4% high users. Students in the first and second years of study, small family size, age below 20 years, male gender, being in a non-medical study program, friends in close relationship were found to be associated with higher SNS use. Conclusion Social networking sites were found to be popular among a large number of university students in the UAE, this being more so among males and non-medical students of first two years of study. DOI: http://doi.dx.org/10.3126/nje.v3i2.8512

Prescribing in pregnancy for women with diabetes: use of potential teratogenic drugs and contraception

AIMS

To describe contraception use and the prescription of drugs that are either not recommended in pregnancy or are potentially teratogenic by diabetes type in women of child-bearing age.

METHODS

Retrospective, cross-sectional chart review undertaken in 22 general practices in Warwickshire, UK. Demographic, anthropometric, medical history, medication and contraception data were extracted from women aged 14 to 49 years with pre-existing diabetes. Independent sample t-test, Mann-Whitney test and χ(2) -test were used to test for univariable associations and multiple logistic regression was used to adjust for confounders.

RESULTS

Four hundred and seventy eligible women were identified; the majority had a diagnosis of Type 2 diabetes (67%). Thirty-six per cent and 64% of women with Type 1 and Type 2 diabetes, respectively, were prescribed drugs not recommended for use in pregnancy (P < 0.001). Less than half were using concomitant contraception (P < 0.001). No significant difference of contraception use was observed between women who were and were not taking drugs not recommended for use in pregnancy (40 vs. 41%, P = 0.4).

CONCLUSIONS

Use of drugs not recommended during pregnancy in women with diabetes of child-bearing age is common but is not associated with increased use of contraception. There is need to identify and overcome barriers to effective contraception use for this population group in order to facilitate optimal management of cardiovascular risk.

Fasting plasma glucose is not sufficient to detect ongoing glucose intolerance after pregnancy complicated by gestational diabetes

AIMS

Women who develop diabetes during pregnancy are at significant risk of developing Type 2 diabetes later in life, and "should be offered blood glucose testing ... to exclude persisting hyperglycaemia" after delivery. New UK guidelines now recommend that this is done by measurement of fasting blood glucose, rather than an oral glucose tolerance test (OGTT). Our study aims to establish whether assessment by fasting blood glucose gives equivalent results to an OGTT.

METHODS

Retrospective data were obtained from four centres in the West Midlands, UK, who performed a postnatal OGTT on 470 women during a 12-month period. All centres used a 75 g, 2-h protocol.

RESULTS

28 of 470 (6.0%) women had diabetes mellitus after testing of fasting plasma glucose. After OGTT, 70 women (14.9%) were found to have impaired glucose tolerance (IGT), and 10 further cases of diabetes were detected (overall prevalence of DM 8.1%). Of the 400 women with normal fasting plasma glucose. After OGTT, 70 women (14.9%) were found to have impaired glucose tolerance (IGT), and 10 further cases of diabetes were detected (overall prevalence of DM 8.1%). Of the 400 women with normal fasting plasma glucose (< or = 6.0 mmol/l), 55 were found to have impaired glucose tolerance and 4 had overt diabetes. In all, 26% of women with diabetes were missed by FPG.

CONCLUSION

Fasting plasma glucose alone does not allow detection of IGT, and misses a substantial proportion of women with Type 2 diabetes. Recognition of ongoing IGT or DM is important in identifying women who may benefit from lifestyle modification, and who may need early intervention in subsequent pregnancies. Our results suggest that OGTT should be the investigation of choice in the postnatal assessment of women who have had GDM.

Sinus arrest and moderate hyperkalemia

Hyperkalemia, especially if severe, is a frequent cause of cardiac rhythm pathologies. Sinus arrest of sudden onset is more likely to occur when the potassium level is very high (e.g. > 8 mmol/l) but in concomitance with negative chronotropic drugs it may occur even in presence of a moderate hyperkalemia. This case report highlights the fact that these kinds of drugs, especially in combination, are probably to be avoided in patients at risk of developing hyperkalemia (e.g. diabetics, renal failure, etc.), even of moderate degree, considering this life-threatening cardiac complication.

Lymphoblastic leukemia/lymphoma in mice overexpressing the Mer (MerTK) receptor tyrosine kinase

Mer (MerTK) is a receptor tyrosine kinase important in platelet aggregation, as well as macrophage cytokine secretion and clearance of apoptotic cells. Mer is not normally expressed in thymocytes or lymphocytes; however, ectopic Mer RNA transcript and protein expression is found in a subset of acute lymphoblastic leukemia cell lines and patient samples, suggesting a role in leukemogenesis. To investigate the oncogenic potential of Mer in vivo, we created a transgenic mouse line (Mer(Tg)) that expresses Mer in the hematopoietic lineage under control of the Vav promoter. Ectopic expression and activation of the transgenic Mer protein was demonstrated in lymphocytes and thymocytes of the Mer(Tg) mice. At 12-24 months of age, greater than 55% of the Mer(Tg) mice, compared to 12% of the wild type, developed adenopathy, hepatosplenomegaly, and circulating lymphoblasts. Histopathological analysis and flow cytometry were consistent with T-cell lymphoblastic leukemia/lymphoma. Mer may contribute to leukemogenesis by activation of Akt and ERK1/2 anti-apoptotic signals, which were upregulated in Mer(Tg) mice. Additionally, a significant survival advantage was noted in Mer(Tg) lymphocytes compared to wild-type lymphocytes after dexamethasone treatment. These data suggest that Mer plays a cooperative role in leukemogenesis and may be an effective target for biologically based leukemia/lymphoma therapy.

An open label comparative study of glimepiride versus repaglinide in type 2 diabetes mellitus Muslim subjects during the month of Ramadan

This study was conducted to compare the treatment efficacy between a prandial glucose regulator, repaglinide and a new sulphonylurea, glimepiride in Muslim Type 2 diabetic patients who practice Ramadan fasting. Forty-one patients, previously treated with a sulphonylurea or metformin, were divided to receive either repaglinide (n=20, preprandially three-times daily) or glimepiride (n=21, preprandially once daily) 3 months before the month of Ramadan. During Ramadan, patients modified their eating pattern to two meals daily, and the triple doses of repaglinide were redistributed to two preprandial doses. Four point blood glucose monitoring were performed weekly during the month of Ramadan and the subsequent month. Measurements of the 4-point blood glucose were significantly lower in the glimepiride group compared to the repaglinide group both during and after Ramadan. The glycaemic excursion was better in the morning for the repaglinide group and better in the afternoon and evening for the glimepiride group during the Ramadan period. There was no statistically significant difference in the incidence of hypoglycaemia between the two groups during and after Ramadan. There was no difference in the glycaemic excursion post-Ramadan. The longer duration of action of glimepiride may offer an advantage over repaglinide during the 13.5 hours of fast in Ramadan for diabetic patients.

Association of simple anthropometric measures of obesity with visceral fat and the metabolic syndrome in male Caucasian and Indo-Asian subjects

AIMS

The aims of this study were first, to investigate the relationship between simple anthropometric measures of obesity with visceral fat as assessed by a single slice magnetic resonance imaging (MRI)-scan in patients attending a hospital clinic. Second, to determine which anthropometric measure best relates to the adverse metabolic profile of the metabolic syndrome.

METHODS

Forty-one male subjects [body mass index (BMI): 30.2 + 5.8 kg/m(2), age: 50.3 + 13.6 years] were studied by MRI-scan to measure visceral fat at L4/L5 level and to investigate its relationship with simple anthropometric measures. Second, we studied 83 male subjects to determine which anthropometric measure best predicts the metabolic complications (using the ATPIII criteria) of obesity in the setting of a hospital clinic.

RESULTS

Waist circumference was the best anthropometric measurement that correlated with MRI-visceral fat mass assessed at L4/L5 in 41 subjects who had an MRI scan (P = 0.0001, r(2) = 0.36, beta = 0.56) amongst variables which also included age, BMI, sagittal diameter, diabetes and ethnicity. Stepwise multiple regression analysis showed sagittal diameter (P = 0.001, r(2) = 0.4, beta = 0.406), age (P = 0.003, beta = 0.271) and waist circumference (P = 0.012, beta = 0.297) were the best predictors of the adverse metabolic profile of the metabolic syndrome in all 83 male subjects amongst BMI, waist-hip ratio (WHR), ethnicity and diabetes-related factors.

CONCLUSIONS

Waist circumference is a simple anthropometric parameter that best correlates with single slice MRI-scan, but sagittal diameter (measured using abdominal calipers) better predicts the adverse metabolic profile of the metabolic syndrome. Although there is considerable variation in abdominal fat topography between ethnic groups, and also within populations, sagittal diameter assessment is a technique that is simple and best predicts the metabolic syndrome.

11beta-hydroxysteroid dehydrogenase type 1 activity in lean and obese males with type 2 diabetes mellitus

Glucocorticoids play an important role in the pathogenesis of obesity and insulin resistance. Impaired conversion of cortisone (E) to cortisol (F) by the type 1 isoenzyme of 11beta-hydroxysteroid dehydrogenase (11beta-HSD) in obesity may represent a protective mechanism preventing ongoing weight gain and glucose intolerance. We have studied glucocorticoid metabolism in 33 male subjects with type 2 diabetes mellitus [age, 44.2 +/- 13 yr; body mass index (BMI), 31.1 +/- 7.5 kg/m(2) (mean +/- sd)] and 38 normal controls (age, 41.4 +/- 14 yr; BMI, 38.2 +/- 12.8 kg/m(2)). Circulating F:E ratios were elevated in the diabetic group and correlated with serum cholesterol and homeostasis model assessment-S. There was no difference in 11beta-HSD1 activity between diabetic subjects and controls. In addition, 11beta-HSD1 activity was unaffected by BMI in diabetic subjects. However, in control subjects, increasing BMI was associated with a reduction in the urinary tetrahydrocortisol+5alpha-tetrahydrocortisol:tetrahydrocortisone ratio (P < 0.05) indicative of impaired 11beta-HSD1 activity. The degree of inhibition correlated tightly with visceral fat mass. Changes in 11beta-HSD1 activity could not be explained by circulating levels of adipocytokines. Impaired E to F metabolism in obesity may help preserve insulin sensitivity and prevent diabetes mellitus. Failure to down-regulate 11beta-HSD1 activity in patients with diabetes may potentiate dyslipidemia, insulin resistance, and obesity. Inhibition of 11beta-HSD1 may therefore represent a therapeutic strategy in patients with type 2 diabetes mellitus and obesity.