Acupuncture in the Management of Orofacial Pain and Related Disorders: A Review

Oro-facial pain and temperomandibular dysfunction are deemed upon as multifaceted problems and can pose major therapeutic problem in dealing with them. Evidence from clinical studies suggests that acupuncture may be useful in the treatment of orofacial pain, temperomandibular dysfunction and related disorders otherwise resistant to conventional treatment modalities.  Acupuncture is an ancient healing technique that has regained its lost popularity in the last two decades. The present paper attempts to review this forbidden procedure and its role in improving the quality of dental care provided to the patients especially in the management of orofacial pain, temperomandibular dysfunction, dental anxiety, gag reflex, xerostomia and trigeminal neuralgia. &nbsp

Ultrasonographic evaluation of cervical length and amniotic fluid index as predictor of pregnancy outcome in case of preterm premature rupture of membrane

Background: Preterm premature rupture of membrane (PPROM) is among the most important cause of the perinatal morbidity and mortality. We sought to determine whether cervical length and amniotic fluid index individually or in combination can predict the pregnancy outcome in cases of PPROM.Methods: The prospective observational study was done on 170 women complicated by PPROM with gestational age between 24-36+6 weeks. They were categorized into three groups Group I.24-28 weeks, Group II.28+1 to 32 weeks and Group III. 32+1 to 36+6 weeks. Cervical length and amniotic fluid index were measured using trans abdominal ultrasound within 24 hr of admission. Maternal outcomes were recorded in terms of latency period, chorioamnionitis, and abruption , and neonatal outcomes were recorded in terms of birth weight, first minute APGAR score 5 cm had a greater mean latency period (8.32±1.25 days) which increased their risk of developing chorioamnionitis as compared to women with PPROM having AFI ≤5 cm, who had a shorter mean latency period (7.63±1.07 days) and a lower risk of developing chorioamnionitis (p value <0.0001).Conclusions: Latency is inversely related to period of gestation. A long cervical length and increased amount of AFI correlates with increased latency, increased risk of chorioamnionitis and increased neonatal complications

Quantifying Aggregated Uncertainty in Plasmodium falciparum Malaria Prevalence and Populations at Risk via Efficient Space-Time Geostatistical Joint Simulation

Risk maps estimating the spatial distribution of infectious diseases are required to guide public health policy from local to global scales. The advent of model-based geostatistics (MBG) has allowed these maps to be generated in a formal statistical framework, providing robust metrics of map uncertainty that enhances their utility for decision-makers. In many settings, decision-makers require spatially aggregated measures over large regions such as the mean prevalence within a country or administrative region, or national populations living under different levels of risk. Existing MBG mapping approaches provide suitable metrics of local uncertainty—the fidelity of predictions at each mapped pixel—but have not been adapted for measuring uncertainty over large areas, due largely to a series of fundamental computational constraints. Here the authors present a new efficient approximating algorithm that can generate for the first time the necessary joint simulation of prevalence values across the very large prediction spaces needed for global scale mapping. This new approach is implemented in conjunction with an established model for P. falciparum allowing robust estimates of mean prevalence at any specified level of spatial aggregation. The model is used to provide estimates of national populations at risk under three policy-relevant prevalence thresholds, along with accompanying model-based measures of uncertainty. By overcoming previously unchallenged computational barriers, this study illustrates how MBG approaches, already at the forefront of infectious disease mapping, can be extended to provide large-scale aggregate measures appropriate for decision-makers

Cardiovascular profile of patients with chronic kidney disease

Background: Frequency of fatal and nonfatal cardiovascular events increase even in early stages of chronic kidney disease (CKD). This study was aimed to understand the cardiovascular profile of patients with CKD.Methods: This observational study was conducted on patients who were admitted with chronic kidney disease in Sri Venkateswara Rama Narayan RUIA Government General Hospital, Tirupati. Patients were classified according to their severity of CKD. All patients had an electrocardiogram and echocardiogram. Results of various biochemical investigations, electrocardiogram and echocardiogram were compared between patients with mild, moderate and severe CKD.Results: Combined diabetes mellitus and hypertension was found to be the most common case of CKD in Authors patient population (43%), followed by diabetes mellitus alone (37%). Serum creatinine and blood urea nitrogen were found to be significantly higher and creatinine clearance and haemoglobin were significantly lower among patients with severe CKD. Electrocardiography revealed 50% had left ventricular hypertrophy (LVH), 30% had tall ‘T’ waves and 15 % had ST-segment changes. Mean inter-ventricular septal end diastole thickness and mean left ventricular mass was found to be significantly in patients with severe CKD as compared to mild CKD.Conclusions: Extensive cardiovascular evaluation of patients with CKD is warranted even if the classical symptoms are not absent and early cardiovascular rehabilitation should be instituted in such patients

Innovative biofilm inhibition and anti-microbial behavior of molybdenum sulfide nanostructures generated by microwave-assisted solvothermal route

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Modelling the global constraints of temperature on transmission of Plasmodium falciparum and P. vivax

<p>Abstract</p> <p>Background</p> <p>Temperature is a key determinant of environmental suitability for transmission of human malaria, modulating endemicity in some regions and preventing transmission in others. The spatial modelling of malaria endemicity has become increasingly sophisticated and is now central to the global scale planning, implementation, and monitoring of disease control and regional efforts towards elimination, but existing efforts to model the constraints of temperature on the malaria landscape at these scales have been simplistic. Here, we define an analytical framework to model these constraints appropriately at fine spatial and temporal resolutions, providing a detailed dynamic description that can enhance large scale malaria cartography as a decision-support tool in public health.</p> <p>Results</p> <p>We defined a dynamic biological model that incorporated the principal mechanisms of temperature dependency in the malaria transmission cycle and used it with fine spatial and temporal resolution temperature data to evaluate time-series of temperature suitability for transmission of <it>Plasmodium falciparum </it>and <it>P. vivax </it>throughout an average year, quantified using an index proportional to the basic reproductive number. Time-series were calculated for all 1 km resolution land pixels globally and were summarised to create high-resolution maps for each species delineating those regions where temperature precludes transmission throughout the year. Within suitable zones we mapped for each pixel the number of days in which transmission is possible and an integrated measure of the intensity of suitability across the year. The detailed evaluation of temporal suitability dynamics provided by the model is visualised in a series of accompanying animations.</p> <p>Conclusions</p> <p>These modelled products, made available freely in the public domain, can support the refined delineation of populations at risk; enhance endemicity mapping by offering a detailed, dynamic, and biologically driven alternative to the ubiquitous empirical incorporation of raw temperature data in geospatial models; and provide a rich spatial and temporal platform for future biological modelling studies.</p

Defining the relationship between Plasmodium falciparum parasite rate and clinical disease: statistical models for disease burden estimation

<p>Abstract</p> <p>Background</p> <p>Clinical malaria has proven an elusive burden to enumerate. Many cases go undetected by routine disease recording systems. Epidemiologists have, therefore, frequently defaulted to actively measuring malaria in population cohorts through time. Measuring the clinical incidence of malaria longitudinally is labour-intensive and impossible to undertake universally. There is a need, therefore, to define a relationship between clinical incidence and the easier and more commonly measured index of infection prevalence: the "parasite rate". This relationship can help provide an informed basis to define malaria burdens in areas where health statistics are inadequate.</p> <p>Methods</p> <p>Formal literature searches were conducted for <it>Plasmodium falciparum </it>malaria incidence surveys undertaken prospectively through active case detection at least every 14 days. The data were abstracted, standardized and geo-referenced. Incidence surveys were time-space matched with modelled estimates of infection prevalence derived from a larger database of parasite prevalence surveys and modelling procedures developed for a global malaria endemicity map. Several potential relationships between clinical incidence and infection prevalence were then specified in a non-parametric Gaussian process model with minimal, biologically informed, prior constraints. Bayesian inference was then used to choose between the candidate models.</p> <p>Results</p> <p>The suggested relationships with credible intervals are shown for the Africa and a combined America and Central and South East Asia regions. In both regions clinical incidence increased slowly and smoothly as a function of infection prevalence. In Africa, when infection prevalence exceeded 40%, clinical incidence reached a plateau of 500 cases per thousand of the population <it>per annum</it>. In the combined America and Central and South East Asia regions, this plateau was reached at 250 cases per thousand of the population <it>per annum</it>. A temporal volatility model was also incorporated to facilitate a closer description of the variance in the observed data.</p> <p>Conclusion</p> <p>It was possible to model a relationship between clinical incidence and <it>P. falciparum </it>infection prevalence but the best-fit models were very noisy reflecting the large variance within the observed opportunistic data sample. This continuous quantification allows for estimates of the clinical burden of <it>P. falciparum </it>of known confidence from wherever an estimate of <it>P. falciparum </it>prevalence is available.</p

The risks of malariainfection in Kenya in 2009

BACKGROUND: To design an effective strategy for the control of malaria requires a map of infection and disease risks to select appropriate suites of interventions. Advances in model based geo-statistics and malaria parasite prevalence data assemblies provide unique opportunities to redefine national Plasmodium falciparum risk distributions. Here we present a new map of malaria risk for Kenya in 2009. METHODS: Plasmodium falciparum parasite rate data were assembled from cross-sectional community based surveys undertaken from 1975 to 2009. Details recorded for each survey included the month and year of the survey, sample size, positivity and the age ranges of sampled population. Data were corrected to a standard age-range of two to less than 10 years (PfPR2-10) and each survey location was geo-positioned using national and on-line digital settlement maps. Ecological and climate covariates were matched to each PfPR2-10 survey location and examined separately and in combination for relationships to PfPR2-10. Significant covariates were then included in a Bayesian geostatistical spatial-temporal framework to predict continuous and categorical maps of mean PfPR2-10 at a 1 x 1 km resolution across Kenya for the year 2009. Model hold-out data were used to test the predictive accuracy of the mapped surfaces and distributions of the posterior uncertainty were mapped. RESULTS: A total of 2,682 estimates of PfPR2-10 from surveys undertaken at 2,095 sites between 1975 and 2009 were selected for inclusion in the geo-statistical modeling. The covariates selected for prediction were urbanization; maximum temperature; precipitation; enhanced vegetation index; and distance to main water bodies. The final Bayesian geo-statistical model had a high predictive accuracy with mean error of -0.15% PfPR2-10; mean absolute error of 0.38% PfPR2-10; and linear correlation between observed and predicted PfPR2-10 of 0.81. The majority of Kenya's 2009 population (35.2 million, 86.3%) reside in areas where predicted PfPR2-10 is less than 5%; conversely in 2009 only 4.3 million people (10.6%) lived in areas where PfPR2-10 was predicted to be &gt; or =40% and were largely located around the shores of Lake Victoria. CONCLUSION: Model based geo-statistical methods can be used to interpolate malaria risks in Kenya with precision and our model shows that the majority of Kenyans live in areas of very low P. falciparum risk. As malaria interventions go to scale effectively tracking epidemiological changes of risk demands a rigorous effort to document infection prevalence in time and space to remodel risks and redefine intervention priorities over the next 10-15 years

Unilateral Incomplete Bifid Ureter Presenting with Calculus in Right Kidney with Hydronephrosis: A Rare Case Report

an incomplete duplicate ureter to be 18 out of a series of 4215 autopsies studied. Amongst these 2 were the bilaterally incomplete duplicate, 7 were a unilaterally incomplete duplicate and 8 were the unilaterally complete duplicate

Identification of genetic polymorphisms in DNA repair xenoderma pigmentosum group D gene and its association with head and neck cancer susceptibility in rural Indian population: a hospital based case-control study from south-western Maharashtra, India

Background: Smoking and alcohol related head and neck cancer is a major concern of health risk in developing countries, such as India. In this study, we aimed to determine the frequency of polymorphisms in DNA repair gene, xeroderma pigmentosum complementation group D (XPD) at codon (cd) 156, cd199, cd320, cd751 in patients of oral cancer from South-Western Maharashtra, India and to evaluate their association with oral cancer development.Methods: We used polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) to analyze XPD gene polymorphisms in 320 patients with oral cancer and in 400 age and sex matched disease-free controls.Results: There was no significant difference in the genotype distribution between oral cancer patients and controls for each polymorphism (p>0.05) except XPD199. The result from our study showed that allele frequencies of selected genes were not statistically different between the groups for XPD Arg156, XPD Asn320, XPD Gln751. XPDMet199 (OR=29.44; 95% CI= (18.47-46.92); p≤0.0001) genotypes significantly increased the risk of head and neck cancer.Conclusions: This study indicates that polymorphisms in cd199 of XPD gene could play a role in modifying genetic susceptibility of individual to head and neck cancer inMaharashtra patients. Thus, the case-control study suggest that selected DNA repair genes represent genetic determinants in oral carcinogenesis along with other risk factors in the rural Indian population.