Salivary glucose as a diagnostic tool in Type II diabetes mellitus: A case-control study

Background and Objectives: The prevalence of diabetes mellitus is increasing steadily in India. Understanding blood glucose level is the key to both diagnosis and management of diabetes mellitus. However, there is an on‑going need for improvements in noninvasive, point‑of‑care tools for the diagnosis and prognosis of diabetes. Assessing a relationship between the blood glucose level and its concentration in other body fluids such as the saliva can help in developing a conservative method for blood sugar assessment replacing venous blood sampling. Diabetes mellitus is known to cause changes in salivary composition. Hence, this study was undertaken to evaluate the relationship of blood glucose level with salivary glucose in diabetic and nondiabetic patients.Materials and Methods: The study sample included 100 diabetic patients and 100 nondiabetic patients aged above 35 years of age. Fasting blood and salivary glucose levels were measured in the two groups. Pearson’s correlation coefficient was used to assess the correlation of blood glucose with salivary glucose in the two groups.Results: The results of the study revealed an increase in the level of fasting salivary glucose in diabetics compared to that of nondiabetic patients. It also showed a highly significant positive correlation between fasting salivary glucose and serum glucose in both diabetic patients and in controls.Conclusion: From this study, it can be concluded that fasting salivary glucose level can be used as a noninvasive diagnostic, as well as a monitoring tool to assess the glycemic status of Type II diabetes mellitus patients.Keywords: Fasting salivary glucose, fasting serum glucose, Type II diabetes mellitu

Effect of Used Engine Oil and UV-Thermal Pretreatments on Biodegradation of Low-Density Polyethylene by Lysinibacillus fusiformis TPB

The present study focused on the impact of Used Engine Oil (UEO) and abiotic pretreatments by ultraviolet (UV) radiation and thermal treatment at 70°C for 144 h on the potential of Lysinibacillus fusiformis TPB isolated from hydrocarbon contaminated soil for the biodegradation of low-density polyethylene (LDPE) in mineral salt medium at 30°C and 150 rpm for 30 days. The isolated L. fusiformis TPB degraded 9.51% of LPDE films without any treatment and used as the sole carbon source for biomass production. The supplementation of used engine oil (0.5% v/v) enhanced biodegradation of untreated LDPE films to 11.96% comparable to a non-ionic surfactant Tween 80. The abiotic pretreatments had also facilitated metabolism of LDPE by L. fusiformis TPB. The biodegradation of UV treated LDPE by L. fusiformis TPB was 13.78% and was significantly higher than thermally treated LDPE with 12.89% biodegradation. The Fourier Transform Infrared spectrum revealed structural and morphological changes in the LDPE films by abiotic pretreatments and were associated with addition of carbonyl groups and change in double bond index. The Scanning Electron Microscopy analysis of LDPE films from UEO and UV-thermal pretreated LDPE supplemented mineral salt media confirmed the improved bacterial colonization and biofilm formation. The isolated L. fusiformis TPB had LDPE degradation potential and biodegradation had improved by UEO supplementation and UV-thermal pretreatments

A PROSPECTIVE STUDY ON EFFECT OF FLUOXETINE ON PRIMARY HEMOSTASIS OF PATIENTS HAVING MAJOR DEPRESSIVE DISORDER

Objectives: The objectives of the study were to study the effect of fluoxetine on bleeding time, clotting time and platelet count of depressed patients. Methods: Patients diagnosed with major depressive disorder were included in the study to fulfill a sample size of 60. Before starting the treatment with fluoxetine, laboratory tests were done which included bleeding time, clotting time, and platelet count. Patients were requested to return for follow-up after 4 weeks of treatment and the laboratory tests were repeated. All the study end point analysis was analyzed based on per-protocol population. Continuous variables were expressed as mean and standard deviations, paired t-test was used for within group comparison and unpaired t-test was used for between group comparisons. p<0.05 was considered to be significant. For categorical variable, frequency and percentage were calculated. For continuous variable, that is, bleeding time, clotting time, and platelet count, mean and standard deviation were calculated. Results: At the end of 4 weeks, it was observed that there was a significant increase in bleeding time from 1.35±0.08 min to 1.46±0.08 min**. Similarly, there was a significant increase in clotting time from 3.30±0.15 min to 3.38±0.15 min**. It was also observed that there was a significant decrease in platelet count from 3.07±0.67 lakh cells/cu mm to 2.86±0.63 lakh cells/cu mm**. Conclusion: Fluoxetine has shown to increase bleeding time, clotting time, and decrease platelet count. Hence, fluoxetine induced risk of bleeding and its cardio protective action has to be considered while individualizing therapy in management of depression

Unleashing the Power of Dynamic Mode Decomposition and Deep Learning for Rainfall Prediction in North-East India

Accurate rainfall forecasting is crucial for effective disaster preparedness and mitigation in the North-East region of India, which is prone to extreme weather events such as floods and landslides. In this study, we investigated the use of two data-driven methods, Dynamic Mode Decomposition (DMD) and Long Short-Term Memory (LSTM), for rainfall forecasting using daily rainfall data collected from India Meteorological Department in northeast region over a period of 118 years. We conducted a comparative analysis of these methods to determine their relative effectiveness in predicting rainfall patterns. Using historical rainfall data from multiple weather stations, we trained and validated our models to forecast future rainfall patterns. Our results indicate that both DMD and LSTM are effective in forecasting rainfall, with LSTM outperforming DMD in terms of accuracy, revealing that LSTM has the ability to capture complex nonlinear relationships in the data, making it a powerful tool for rainfall forecasting. Our findings suggest that data-driven methods such as DMD and deep learning approaches like LSTM can significantly improve rainfall forecasting accuracy in the North-East region of India, helping to mitigate the impact of extreme weather events and enhance the region's resilience to climate change.Comment: Paper is under review at ICMC 202

Performance, diversity analysis and character association of black pepper (Piper nigrum L.) accessions in the high altitude of Idukki district, Kerala

The experiment was conducted to evaluate black pepper accessions for growth parameters, yield attributing characters and yield. Out of the ten accessions tested, Karimunda recorded the highest fresh (1.61 kg) and dry (508.7 g) yield of berries plant-1. Fresh weight showed significant positive genotypic correlation to dry weight and while negative correlated to 100 berry volume, 100 berry weight and number of berries spike-1. Hence, selection based on number of berries spike-1, 100 berry volume and 100 berry weight may not lead to the high yielding black pepper variety. The results showed that Karimunda is the most suitable black pepper variety for high altitude areas of Idukki district

Genetic Aspects of Implantation Failure

Implantation failure refers to the inability of a fertilized egg, or embryo, to successfully implant itself in the endometrial lining of the uterus, leading to pregnancy loss. The repeated failure of good quality embryo implantation is referred to as recurrent implantation failure (RIF). This can occur for a variety of reasons, including chromosomal abnormalities in the embryo, problems with the endometrium, or issues with the immune system. Factors such as advanced maternal age, obesity, smoking, and certain medical conditions can also increase the risk of implantation failure. While treatment such as in vitro fertilization (IVF) can help to improve the chances of successful implantation, there is currently no definite way to prevent or treat implantation failure.  Patients and healthcare professionals have substantial diagnostic and treatment hurdles as a result of many etiological factors and lack of knowledge about RIF. A number of studies have indicated a correlation between irregular hormone levels, disruptions in angiogenic and immunomodulatory factors, specific genetic polymorphisms, and the prevalence of RIF. Nonetheless, the precise and intricate underlying pathophysiology of RIF remains elusive.  However, many studies are ongoing in this field to understand the underlying causes and to find new ways to help couples achieve pregnancy. This review article extensively explores diverse molecular and genetic facets aimed at enhancing the diagnosis and management of implantation failure

Effect of biofertilizers and organic supplements on the growth of black pepper rooted cuttings (Piper nigrum L.)

An experiment was conducted at the Cardamom Research Station, Kerala Agricultural University, Pampadumpara (Kerala) with an objective to study the effect of different biofertilizers (Phosphorus solubilizing bacteria, Azospirillum and Plant Growth Promoting Rhizobacteria Mix I) and organic supplements (fish extract and humic acid) on the growth of black pepper rooted cuttings. The results of the experiment indicated that application of Phosphorus solubilizing bacteria (5 g) along with Azospirillum (5 g), humic acid (0.2%) and fish extract (0.5%) was the best combination for the production of black pepper rooted cuttings with improved vegetative characters (plant height, number of leaves, number of roots, length of roots and leaf area) compared to theirindividual inoculation.This innovative information can be effectively utilized and advocated for the commercial production of black pepper rooted cuttings with lusty growth

Protons in the near-lunar wake observed by the Sub-keV Atom Reflection Analyzer on board Chandrayaan-1

Significant proton fluxes were detected in the near wake region of the Moon by an ion mass spectrometer on board Chandrayaan-1. The energy of these nightside protons is slightly higher than the energy of the solar wind protons. The protons are detected close to the lunar equatorial plane at a $140^{\circ}$ solar zenith angle, i.e., ~50$^{\circ}$ behind the terminator at a height of 100 km. The protons come from just above the local horizon, and move along the magnetic field in the solar wind reference frame. We compared the observed proton flux with the predictions from analytical models of an electrostatic plasma expansion into a vacuum. The observed velocity was higher than the velocity predicted by analytical models by a factor of 2 to 3. The simple analytical models cannot explain the observed ion dynamics along the magnetic field in the vicinity of the Moon.Comment: 28 pages, 7 figure

Oyster farm management advisory: spacing between farms

The edible oyster Crassostrea madrasensis commonly known as the backwater oyster is farmed in the estuarine regions of Kerala by setting up wooden rack farms from which rens are suspended. Proximity to the homesteads is one of the reasons for this technology to become popular among women self help groups. The farming season is from November/December to June, but may extend to July also depending on the onset of monsoon. At present, the farm structures are near to the shore line in a linear manner, providing space for navigation in the inner part of the estuarine channels. Initially when commercial farming started in Sattar Island in the year 2002, there were only few farms, hence, spacing of farms was not a problem