Prevalence and pattern of dyslipidemia in newly detected type 2 diabetes mellitus and its correlation with anthropometric parameters

Background: Globally 425 million people have diabetes mellitus (DM) of which 90% are type 2 DM. India carries nearly 70 million cases of DM. India is called the diabetes capital of the world. The escalating epidemic of type 2 diabetes has been attributed to increasing obesity and longevity. Due to the additive cardiovascular risk of hyperglycemia and hyperlipidemia, lipid abnormalities should be aggressively detected and treated as a part of comprehensive diabetic care. The study aimed at detecting the occurrence and pattern of dyslipidemia in newly-detected type 2 diabetic patients in a tertiary care hospital in South India.Methods: This cross-sectional study was conducted over a period of eighteen months. It comprised of 50 newly detected diabetics above the age of 18 years who satisfied the inclusion and exclusion criteria.Results: Fifty patients were included in the study which included 18 males and 32 females. The body mass index (BMI) was abnormal in 62% (as per the Asian criteria) and in 42% (as per the WHO criteria). The waist circumference (WC) was found to be high in 82% and 70% as per the Asian and the WHO criteria, respectively. Forty six percent of the population was found to have elevated total cholesterol levels. LDL was increased in 70% of the study population while triglycerides were elevated in 40%, total cholesterol in 46% and low HDL in 76% of the patients.Conclusions: A significant correlation was found between the fasting blood sugars (FBSs) and serum triglycerides. There was a positive correlation noted between the dyslipidemia and the anthropometric parameters recorded

Determinants of dysphagia following stroke

Background: Swallowing is affected following stroke. Many studies focus on various aspects of swallowing difficulties (dysphagia) following stroke. However, there are not many studies on the determinants of dysphagia following stroke. The aim of the present study is to establish the association between various factors with the severity of dysphagia.Methods: After screening for Mann Assessment of Swallowing Ability (MASA),110 patients, post-stroke were selected using consecutive sampling to assess the common risk factors, namely the presence of diabetes mellitus, dyslipidemia, hypertension, alcohol usage and smoking habits. Additionally, other variables such as age, gender, type of lesion, side of lesion, tobacco chewing, speech disorders, arterial dysfunction, lobe involvement and Brunnstrom’s stages, were also evaluated using a structured interview method. c2 (chi-squared) analysis was carried out to find out the association between the selected determinants and severity of dysphagia following stroke.Results: It was found that age and Brunnstrom’s stages are the determinants of dysphagia, as analysis showed a strong association with a p value < 0.001. A marginal association between post-stroke dysphagia and type of lesion with a p value of 0.056 was also observed.Conclusions: Among 15 factors evaluated, age, type of lesion and Brunnstrom’s stages showed a significant association with the severity of dysphagia following stroke. This study advocates early dysphagia management for elderly patients with high Brunnstrom’s grading, for those who are not expected to spontaneously recover following stroke, and for earlier and better community rehabilitation. [Ethiop.J. Health Dev. 2019; 33(3):147-152]Key words: Post-stroke dysphagia, Brunnstrom’s stages, dysphagia risk factors

INTELLIGENT CLUSTER PROVISIONING

Currently, cluster formation through a network management system (NMS) within a software-defined wide area network (SD-WAN) is a manual, multi-step process that is error-prone and time-consuming and which requires multiple interventions (along with validations) by a user at each and every intermediate step. Moreover, that process is extremely difficult to scale with the increased cluster sizes that are required in larger deployments. To address the types of challenges that were described above, techniques are presented herein that support an end-to-end automation of the above-described cluster provisioning process. Aspects of the presented techniques encompass the scanning of an inter-cluster network and the automatic discovery of peer nodes that are viable for cluster formation; the automatic checking of prerequisites for cluster formation (which may include checks regarding a central processing unit (CPU), memory, disk resources, a persona, and a current software version); and support for a ‘one touch’ provisioning tool that may be employed by a network equipment vendor’s support staff or a customer to manage, expand, discover, form, etc. a cluster

INTELLIGENT CLUSTER PROVISIONING

Currently, cluster formation through a network management system (NMS) within a software-defined wide area network (SD-WAN) is a manual, multi-step process that is error-prone and time-consuming and which requires multiple interventions (along with validations) by a user at each and every intermediate step. Moreover, that process is extremely difficult to scale with the increased cluster sizes that are required in larger deployments. To address the types of challenges that were described above, techniques are presented herein that support an end-to-end automation of the above-described cluster provisioning process. Aspects of the presented techniques encompass the scanning of an inter-cluster network and the automatic discovery of peer nodes that are viable for cluster formation; the automatic checking of prerequisites for cluster formation (which may include checks regarding a central processing unit (CPU), memory, disk resources, a persona, and a current software version); and support for a ‘one touch’ provisioning tool that may be employed by a network equipment vendor’s support staff or a customer to manage, expand, discover, form, etc. a cluster

OXIDATIVE STRESS IN BRAINS OF MALE RATS INTOXICATED WITH ALUMINIUM AND NEUROMODULATING EFFECT OF CELASTRUS PANICULATUS ALCOHOLIC SEED EXTRACT.

The objective of the present study was to investigate whether the alcoholic seed extract of Celastrus paniculatus (ASECP) could potentially prevent aluminium induced neurotoxicity in the cerebral cortex, hippocampus and cerebellum of the rat brain. Male albino rats were administered with AlCl3 at a dose of 4.2mg/kg/day i.p. for 4 weeks. Experimental rats were given Celastrus paniculatus seed extract in two different doses of 200mg and 400mg/kg/day orally 1hr prior to the AlCl3 administration for 4 weeks. At the end of the experiments, aluminium administration significantly decreased the level of GSH and the activities of SOD, CAT, GPx, GR, Na+/K+ ATPase, Ca2+ ATPase and Mg2+ ATPase and increased the level of LPO and the activities of ALP, ACP, ALT and AST in all the brain regions when compared with control rats. Pre-treatment with ASECP at a dose of 200mg/kg b.w increased the antioxidant status and activities of membrane bound enzymes and also decreased the level of LPO and the activities of marker enzymes significantly, when compared with aluminium induced rats. Al treatment also revealed an increase in DNA fragmentation as evidenced by an increase in number of comets. Interestingly, ASECP pretreatment reduced the damage inflicted on DNA by aluminium. Aluminium induction also caused histopathological changes in the cerebral cortex, cerebellum and hippocampus of rat brain which was reverted by pretreatment with ASECP. The present study clearly indicates the potential of seed extract of Celastrus paniculatus in counteracting the damage inflicted by Al on rat brain regions

Virtual mechanical ventilation protocol – a model-based method to determine MV settings

Intensive care mechanical ventilation (MV) therapy is a lifesaving intervention for a patient with respiratory failure. MV supports patients breathing by maintaining positive airway pressure and airflow to the lung. However, there is currently little clinical consensus protocol to set the best MV setting. Hence, it is important to provide an objective and patient-specific MV settings to support patient recovery. This study presents a model-based method to find optimal MV settings using clinical bedside data. A mathematical model of the respiratory system is first used to estimate patient-specific respiratory mechanics. These mechanics are then incorporated with significant clinical findings from the literature to simulate a series of MV settings. The simulation of MV settings is performed using the single compartment lung model using the MATLAB software. From this series of simulated MV settings, optimal MV settings can be determined objectively by the clinician. This model-based method potentially provides decision support for the clinician to set optimal MV settings

STURGE-WEBER SYNDROME: A CASE REPORT

  To report a clinical case of Sturge-Weber syndrome (SWS) 1 year 8-month-old male child reported to Saveetha Medical College, Physiotherapy Department presented with complaints of difficulty in sitting, standing, and walking. Computed tomography brain revealed unilateral calcification and cerebral atrophy on the right side. Physical diagnosis revealed the child had left hemiparesis with developmental delay. The child had a developmental delay with a motor developmental age of 2 months. As clinical manifestations of SWS are wide, it leads to multidisciplinary approaches. Physiotherapist's knowledge is important for early diagnosis and to provide an adequate physiotherapy treatment

Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method

A reliable methodology is essential for accurately estimating the parameters of PV models, enabling reliable performance evaluations, effective control studies, accurate analysis of partial shading effects, and optimal optimization of Photovoltaic (PV) systems. It ensures that the obtained parameters reflect the true characteristics of the PV system, leading to more accurate and reliable results in various applications. The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. However, it is important to note that a significant portion of these MAs primarily concentrates on the development of methodologies, often overlooking the design of the objective function tailored for PV systems. This oversight has created a theoretical gap in this research domain, underscoring the necessity for additional exploration and investigation to address this limitation. To address the existing theoretical gap, this study focused on developing an objective function that accurately estimates the initial root parameters of Photovoltaic (PV) models. This objective function was designed by incorporating the first-order Berndt-Hall-Hall-Hausman (BHHH) numerical method, along with the non-linear damping parameter of the Levenberg-Marquardt technique (LM). By implementing this approach, the study aimed to significantly improve the precision and reliability of estimating the initial root parameters in PV models, effectively filling the theoretical void in this specific research area. Then in terms of methodology, the Enhanced Henry Gas Solubility Optimization (EHGSO) algorithm is combined with the Sine-Cosine mutualism phase of Symbiotic Organisms Search (SOS) for efficiently estimating the unknown parameters of PV models. The keystone of EHGSO in terms of methodology enhances exploration at the beginning of optimization and intensifies exploitation in later iterations. The proposed EHGSO methodology based on the adaptive damping BHHH technique (EHGSOAdBHHH) is tested on Single Diode (SD), and Double Diode (DD) PV models using actual experimental data. EHGSOAdBHHH exhibits outstanding accordance with attained experimental data compared with other algorithms, and its superiority is validated using several statistical criteria

Botulinum toxin injection for failed tracheo-oesophageal voice in laryngectomees: the Sunderland experience

Spasm of the pharyngo-oesophageal segment is one of the important causes of tracheo-oesophageal voice failure. Traditionally it has been managed by either prolonged speech therapy, surgical pharyngeal myotomy or pharyngeal plexus neurectomy with varying degrees of success. Botulinum neurotoxin has been found to be effective in relieving pharyngo-oesophageal segment spasm. Since 1995, we have used botulinum toxin injection on 10 laryngectomees with either aphonia or hypertonicity due to pharyngo-oesophageal segment spasm. Early results were analysed by the Sunderland Surgical Voice Restoration Rating scale. Seven of the 10 patients, who were previously completely aphonic, developed voice following this therapy and are using their valve choice as their only method of communication. Out of the three patients who were treated for hypertonic voice, two did derive some benefit from the procedure. One patient developed a hypotonic voice, which lasted for a few months