A comparative analysis on diagnosis of diabetes mellitus using different approaches: A survey

Diabetes Mellitus is commonly known as diabetes. It is one of the most chronic diseases as the World Health Organization (WHO) report shows that the number of diabetes patients has risen from 108 million to 422 million in 2014. Early diagnosis of diabetes is important because it can cause different diseases that include kidney failure, stroke, blindness, heart attacks, and lower limb amputation. Different diabetes diagnosis models are found in literature, but there is still a need to perform a survey to analyze which model is best. This paper performs a literature review for diabetes diagnosis approaches using Artificial Intelligence (neural networks, machine learning, deep learning, hybrid methods, and/or stacked-integrated use of different machine learning algorithms). More than thirty-five papers have been shortlisted that focus on diabetes diagnosis approaches. Different datasets are available online for the diagnosis of diabetes. Pima Indian Diabetes Dataset (PIDD) is the most commonly used for diabetes prediction. In contrast with other datasets, it has key factors which play an important role in diabetes diagnosis. This survey also throws light on the weaknesses of the existing approaches that make them less appropriate for a diabetes diagnosis. In artificial intelligence techniques, deep learning is widespread and in medical research, heart rate is getting more attention. Deep learning combined with other algorithms can give better results in diabetes diagnosis and heart rate should be used for other cardiac disease diagnoses

Therapeutic potential and bioactive phenolics of locally grown Pakistani and Chinese varieties of ginger in relation to extraction solvents

Current study compares the Therapeutic/nutra-pharmaceuticals potential and phenolics profile of Pakistani grown Pakistani and Chinese varieties of ginger. Crude yield of bioactive components from the varieties tested, using different extraction solvents including chloroform, ethyl acetate, ether, methanol, ethanol and distilled water. The crude bioactives varied from 14.1-82.5%. The highest extraction yield was noted for Pakistani species. The HPLC analysis revalued significant amounts of phenolics including vanillin, protocatechuic, vanillic, ferulic, sinapinic and cinnamic acids. The highest anti-inflammatory activity was shown by ethanolic extract of Pakistani variety (IC50: 26.5±1.8) whereas Chinese variety exhibited potent anticancer potential against MCF-7 cell line (Inhibition: 91.38 %). The Chinese variety in general showed higher phenolics and anticancer, while the Pakistani exhibited higher anti-inflammatory activity. Pakistani grown ginger and ethanolic extract of Chinese ginger showed highest antimicrobial activity against Pseudomonas aeruginosa 18.0±0.02 & 15.00±0.02 mm respectively. Minimum results obtained with water for both varieties of ginger with range of 7.2±0.22 and 6±0.07 respectively. Moreover, the phenolics composition, anti-inflammatory, antibacterial and anticancer activities of both tested varieties of ginger were notably affected as a function of extraction solvents. Our findings advocate selection of appropriate solvent for recovery of effective phenolic bioactive compounds from ginger verities to support the Nutra-pharmaceutical formulation

Pharmacological screening of Viola Odorata L. for memory-enhancing effect via modulation of oxidative stress and inflammatory biomarkers

Purpose: Alzheimer disease (AD) is a progressive neurodegenerative disorder that is caused by neuroinflammation and oxidative stress. The present study aimed to characterize and then investigate the memory-enhancing potential of Viola odorata methanolic extract in lipopolysaccharide (LPS)–treated mice. Methods: V. odorata characterization was done by using the GCMS technique. Neuroinflammation was induced by the intracerebroventricular administration of LPS at a dose of 12 μg. Animals were divided randomly into six groups (n 10). Group I was normal control, which was given vehicle. Group II was disease control, which received LPS (12 μg) via the intracerebroventricular route. Group III was standard, which was administered with donepezil (3 μg) orally for 21 days. Groups IV–VI were the treatment groups, which were administered with the extract at 100, 200, and 400 mg/kg dose levels orally respectively for 21 days. Groups III–VI received LPS (12 μg) on the first day along with their treatments. During the treatment, the animals were assessed for memory retention by employing different behavioral paradigms namely elevated plus maze, passive avoidance, foot shock and open field. Various mediators [endogenous antioxidants, neurotransmitters, and acetylcholinesterase (AChE)] involved in the pathogenesis of AD were quantified by using the UV spectrophotometric method. Results: Extract-treated groups showed a remarkable improvement in cognitive impairment in all behavioral paradigms. Oxidative stress biomarkers, that is, superoxide dismutase, catalase, and glutathione were raised dose-dependently in the treatment groups with a dose-dependent decrease in the malonaldehyde and AChE levels in the brains of the treated animals. The treatment groups showed decreased levels of inflammatory biomarkers, that is, tumor necrosis factor–alpha, nuclear factor kappa light-chain enhancer of activated β-cells, and cyclo-oxygenase, which supports the therapeutic effectiveness of the treatment. Conclusion: Based on behavioral, oxidative stress biomarker, and neuroinflammatory data, it is concluded that V. odorata possesses memory-enhancing activity and may prove a beneficial role in the management of AD.peer-reviewe

Antioxidants Attenuate Isolation- and L-DOPA-Induced Aggression in Mice

Aggression is a major hallmark worldwide attributing negative traits in personality. Wide variety of antioxidants is used for the treatment of many ailments. The present study was conducted to evaluate the role of antioxidants such as ascorbic acid (15.42 and 30.84 mg/kg), beta carotene (1.02 and 2.05 mg/kg), vitamin E (2.5 and 5.0 mg/kg), and N-acetyl cysteine (102.85 and 205.70 mg/kg) in the treatment of aggression. Two aggression models (isolation induced aggression model and L-DOPA induced aggression model) were used in the study. Male albino mice (n = 330) were used in the study which were further subdivided into 11 groups (Group I-control, group II-diseased, group III-standard group, group IV–V treated with ascorbic, group VI–VII treated with beta carotene, group VIII–IX treated with vitamin E, group X–XI treated with N-acetyl cysteine for 14 consecutive days). Different biochemical markers (glutathione, superoxide dismutase, and catalase) were determined to evaluate the antioxidant potential in oxidative stress. High dose of vitamin E (5.0 mg/kg) was more effective to reduce the aggression in isolated animals while all other antioxidants produced dose-dependent anti-aggressive effect except N-acetyl cysteine which had marked anti-aggressive effect at low dose (102.75 mg/kg). Low doses of vitamin E (2.5 mg/kg) and N-acetyl cysteine (102.75 mg/kg) and high dose of beta carotene (2.05 mg/kg) were effective to prevent all aggression parameters in acute anti-aggressive activity against L-DOPA induced aggression. However, all test antioxidants were equally effective in chronic anti-aggressive studies against L-DOPA induced aggression. It may be concluded that selected antioxidants can reverse the aggression which is a key symptom of many neurological disorder

A network pharmacology approach to assess Reno-protective and -curative effects of methanolic extract of Malva neglecta Wallr in gentamicin induced renal toxicity rat model

The aim of present study was to explore protective and curative effects of Malve neglecta on kidneys. In silco study with network pharmacology was performed to find out potential target organs, genes and cellular cell lines which confirmed kidneys as target organ of phyto-constituents present in Malva neglecta extract. Gentamicin (40 mg/kg, i.p) was given to induce renal toxicity. Prophylactic study was performed with 300-, 600- and 900 mg/kg doses to find out nephro-protective and -curative effects and curative potential was evaluated at 900 mg/kg dose. Renal function biomarkers, blood urea, BUN, serum creatinine and uric acid, and oxidative stress measuring biomarkers, SOD, CAT, GSH and MDA levels in kidney homogenate were quantified at the end of study. Treatment groups showed decrease in blood urea, BUN, serum creatinine and uric acid levels dose dependently and curative group also showed decline in these biomarkers. SOD, CAT, GSH levels were increased and MDA level decreased in treatment groups significantly as compared to toxic control which revealed the role of oxidative stress in renal damage and anti-oxidant power of MN. Data suggested that use of MN along with drugs causing renal toxicity may prove beneficial due to its nephro- protective and curative effects

A comparative analysis on diagnosis of diabetes mellitus using different approaches -A survey

Diabetes Mellitus is commonly known as diabetes. It is one of the most chronic diseases as the World Health Organization (WHO) report shows that the number of diabetes patients has risen from 108 million to 422 million in 2014. Early diagnosis of diabetes is important because it can cause different diseases that include kidney failure, stroke, blindness, heart attacks, and lower limb amputation. Different diabetes diagnosis models are found in literature, but there is still a need to perform a survey to analyze which model is best. This paper performs a literature review for diabetes diagnosis approaches using Artificial Intelligence (neural networks, machine learning, deep learning, hybrid methods, and/or stacked-integrated use of different machine learning algorithms). More than thirty-five papers have been shortlisted that focus on diabetes diagnosis approaches. Different datasets are available online for the diagnosis of diabetes. Pima Indian Diabetes Dataset (PIDD) is the most commonly used for diabetes prediction. In contrast with other datasets, it has key factors which play an important role in diabetes diagnosis. This survey also throws light on the weaknesses of the existing approaches that make them less appropriate for a diabetes diagnosis. In artificial intelligence techniques, deep learning is widespread and in medical research, heart rate is getting more attention. Deep learning combined with other algorithms can give better results in diabetes diagnosis and heart rate should be used for other cardiac disease diagnoses

HMM and fuzzy logic: A hybrid approach for online Urdu script-based languages' character recognition

International audienceUrdu script-based languages' character recognition has some technical issues not existing in other languages and makes these languages more complicated. Segmentation-based character recognition approach for handwritten Urdu, both Nasta'liq and Nasakh script-based languages, incorporates number of overhead and very less accurate as compared to segmentation free. This paper presents a segmentation-free approach for recognition of online Urdu handwritten script using hybrid classifier, HMM and fuzzy logic. Trained data set consisting of HMMs for each stroke is further classified into 62 sub-patterns based on the primary stroke shape at the beginning and end using fuzzy rule. Fuzzy linguistic variables based on language structure are used to model features and provide suitable result for large variation in handwritten strokes. Twenty-six time variant structural and statistical features are extracted for the base strokes. The fuzzy classification into sub-patterns increases the efficiency and decreases the computational complexity due to reduction in data set size. The hybrid HMM-fuzzy technique is efficient for large and complex data set. It provided 87.6% and 74.1% for Nasta'liq and Nasakh, respectively, on 1800 ligatures

Experimental and Computational Studies to Characterize and Evaluate the Therapeutic Effect of <i>Albizia lebbeck</i> (L.) Seeds in Alzheimer’s Disease

Background and Objectives: Alzheimer&#8217;s disease (AD) is a neurodegenerative disorder that deteriorates daily life due to loss of memory and cognitive impairment. It is believed that oxidative stress and cholinergic deficit are the leading causes of AD. Disease-modifying therapies for the treatment of AD are a challenging task for this century. The search for natural and synthetic agents has attracted the attention of researchers. The objective of this study was a scientific approach to search for most suitable remedy for AD by exploiting the potential of Albizia lebbeck (L.) seeds. Materials and Methods: Hydromethanolic extract of Albizia lebbeck seeds (ALE) was prepared by maceration. The plant was characterized by physico-chemical, phyto-chemical, and high-performance liquid chromatography (HPLC). Thirty-six Wistar albino rats were used in this study and divided into six groups (n = 6). Group I: normal control; Group II: disease control (AlCl3; 100 mg/kg); Group III: standard control (galantamine; 0.5 mg/kg); Groups IV&#8722;VI were treated ALE at 100, 200 and 300 mg/kg dose levels, respectively. All the treatments were given orally for 21 consecutive days. Y-maze, T-maze, Morris water maze, hole board, and open field behavioral tests were performed to analyze the cognitive impairment. Biochemical, histological, and computational studies were performed to support the results of behavioral tests. Results: HPLC analysis indicated the presence of quercetin, gallic acid, m-coumaric acid, and sinapic acid. ALE significantly improved the memory and cognitive impairments. Endogenous antioxidant stress biomarker levels and histopathological outcomes supported the therapeutic potential of A. lebbeck in AD. Cholinergic deficits were also ameliorated by ALE co-administration, possibly by the inhibition of hyperactive acetylcholinesterase (AChE). Docking studies supported the potential of ALE against AD. Conclusions: The data suggested that ALE has neuroprotective potential that can be exploited for beneficial effects to treat AD

Acute oral toxicity evaluation of aqueous ethanolic extract of Saccharum munja Roxb. roots in albino mice as per OECD 425 TG

Background: S. munja roots have been used in ethno medicines for the treatment of different ailments. Despite its beneficial uses no studies on its toxicity potential have been reported. Objective: The study was designed to evaluate acute toxic potential of aqueous ethanolic extract of S. munja roots according to OECD TG No. 425. Material and methods: Female mice were divided into two groups (n = 5). One group served as control while the other as treated group that received 2000 mg/kg b.w. of S. munja roots ethanolic extract orally. Then both groups were observed for 14 days. Then the blood samples were collected by cardiac puncture, under chloroform general anesthesia and were subjected to hematological and biochemical analyses. The vital organs of anesthetized animals were preserved for histopathological examination. Results: The the data revealed that LD50 of the extract was greater than 2000 mg/kg b.w. There was no significant alteration found in body weight and organ to body mass index. In comparison with control group, there was significant increase in levels of ALT, AST, total proteins, globulin levels, serum urea, cholesterol, triglycerides, LDL, platelet count, MCV, MCH, WBC count and lymphocytes whereas ALP and MCHC levels were reduced significantly. Conclusions: From the data obtained in this study, It can be concluded that though LD50 is greater than 2000 mg/kg b.w. but moderate toxicity signs appeared in liver, kidney, lipid profile and CBC also showed blood dyscresias at limit dose. Keywords: S. munja roots, LD50, Acute oral toxicit