The sweet potato root, a potent source of starch which is being considered as an efficient alternative for fuel ethanol production in recent times. The starchy substrate needs to be subsequently ...dextrinized and saccharified so as to enhance the utilization of its carbohydrates for ethanol production. In the present investigation, acid-enzyme process was conducted for the dextrinization and saccharification of sweet potato root flour (SPRF). The best optimized condition for dextrinization was achieved with an incubation period of 60 min, temperature 100 ºC and 1M HCl. However, for saccharification, the best result was obtained with an incubation of 18 h, pH 4, temperature 65 ºC and 1000 U concentration of Palkodex®. After the dextrinization process, maximum concentrations of total sugar and hydroxymethylfurfural (HMF) 380.44 ± 3.17 g/kg and 13.28 ± 0.25 mg/g, respectively were released. Nevertheless, after saccharification, 658.80 ± 7.83 g/kg of total sugar was obtained which was about 73% more than that of dextrinization. After successful dextrinization and saccharification, the structural, chemical and elemental analysis were investigated using techniques such as scanning electron microscopy (SEM), Fourier-transforms infrared spectroscopy (FTIR) and energy-dispersive X-ray fluorescence spectrophotometer (EDXRF), respectively. Effective hydrolysis was demonstrated in thin layer chromatography (TLC) where the HCl was able to generate monomeric sugar such as glucose and maltose. On the other hand, only glucose is synthesized on the mutual effect of HCl and Palkodex®. The SEM findings indicate that the rough structure of both dextrinized and saccharified sample was gained due to the vigorous effect of both acid and enzyme subsequently. The saccharified SPRF when subjected to fermentation with Saccharomyces cerevisiae and Zymomonas mobilis separately, it was observed that Z. mobilis produced more stretching vibration of –OH than S. cerevisiae, which evidenced the better production of bioethanol. Additionally, evaluation of the influence of S. cerevisiae and Z. mobilis through elemental analysis revealed upsurge in the concentrations of S, Cl, Ca, Mn, Fe and Zn and decline in the concentrations of P, K and Cu in the fermented residue of S. cerevisiae and Z. mobilis, however, Z. mobilis showed little more variation than that of S. cerevisiae.
•We report peripheral venous catheters (PVC)-related BSI rates from 2013 to 2019.•We collected prospective data from 204 ICUs in 57 hospitals in 19 cities of India.•We followed 7,513 ICU patients for ...296,893 bed-days and 295,795 PVC-days.•We identified 863 PVC-related BSIs, amounting to a rate of 2.91/1,000 PVC-days.
Short-term peripheral venous catheters-related bloodstream infections (PVCR-BSIs) rates have not been systematically studied in developing countries, and data on their incidence by number of device-days are not available.
Prospective, surveillance study on PVCR-BSI conducted from September 1, 2013 to May 31, 2019 in 204 intensive care units (ICUs), members of the International Nosocomial Infection Control Consortium (INICC), from 57 hospitals in 19 cities of India. We applied US INICC definition criteria and reported methods using the INICC Surveillance Online System.
We followed 7,513 ICU patients for 296,893 bed-days and 295,795 short term peripheral venous catheter (PVC)-days. We identified 863 PVCR-BSIs, amounting to a rate of 2.91/1,000 PVC-days.
Mortality in patients with PVC but without PVCR-BSI was 4.14%, and 11.59% in patients with PVCR-BSI. The length of stay in patients with PVC but without PVCR-BSI was 4.13 days, and 5.9 days in patients with PVCR-BSI. The micro-organism profile showed 68% of gram negative bacteria: Escherichia coli (23%), Klebsiella spp (15%), Pseudomonas aeruginosa (5%), and others. The predominant gram-positive bacteria were Staphylococcus aureus (10%).
PVCR-BSI rates found in our ICUs were much higher than rates published from industrialized countries. Infection prevention programs must be implemented to reduce the incidence of PVCR-BSIs.
Despite high proportion of shell fisheries for livelihood and food security, documentation of brachyuran crabs from Devi estuary, east coast of India, recognized as ‘arribada’ of Olive Ridley ...turtles, remains sparse. To deal with this gap, 3-year investigation (2014–2017) on the estuary and adjacent mangrove-fringed mudflats across 17 GPS fixed sites was undertaken; the main objective being species’ reconnaissance, abundance, and diversity in relation to environmental conditions. Overall, 40 species of brachyurans (27 genera and 17 families) were recorded from mangrove mudflats and estuary, of which Portunids outnumbered others. Nine species namely, Elamena xavieri, Carcinoplax longimana, C. longipes, Typhlocarcinus villosus, Arcania heptacantha, Paranursia abbreviata, Leucosia anatum, Venitus latreillei, and Arcotheres purpureus are new records for this region. Multivariate analysis through Bray–Curtis similarity using SIMPROF in PRIMER, recognized four brachyuran assemblages (ANOSIM, Global R 0.936; p<0.001) characterizing mangrove mudflats (Neodorippe callida-Scylla serrata assemblage; salinity 21.88 PSU; silty loam sediments, organic matter 2%); seaward areas (Charybdis hellerii assemblage, salinity, 27.41 PSU; loamy sand, organic matter 0.85%); mid-estuary (Portunus sanguinolentus-P. pelagicus assemblage; salinity, 23.29 PSU, sandy, 0.64% organic matter) and riverine-end (Doclea rissonii assemblage; low salinity, 19.69 PSU; sandy, 0.58% organic matter). Tubuca rosea-Austruca triangularis assemblage remained as an outlier (intertidal silty sand, organic matter 1.28%). Species accounting for dissimilarity (97.51%; SIMPER) between sites were identified. Rarefaction of samples recognized minimum brachyuran crab diversity at the riverine end and transitional areas in comparison to the seaward zone followed by mid-estuary and mangrove mudflats. Accessibility of food resources such as detritus and leaf litter through tidal surging from immediate mangrove environs appeared to support diverse species of crabs. Canonical correspondence analysis (CCA) delineated sediment texture and organic matter as significant factors influencing brachyuran crab community patterns. The study benefited towards building species repositories at the baseline for future monitoring assessments and eco-conservation strategies.
Background Arcotheres purpureus, a species of pea crab has been reported from the Red Sea, Maldives and Andaman Sea with no description of the male. According to existing literature the single host ...for this species is Ostrea. Methods The specimens examined were obtained from the dredge hauls. Results In the present study we report Arcotheres purpureus for the first time from the coastal waters of mainland India. The specimens have been observed within the mantle cavity of a venerid bivalve Protapes gallus a new host record for this species. A description of the male specimen is also communicated herein for the first time. Conclusions Bivalve fisheries is an alternative livelihood option for the fishermen of this region. In this context the manifestation of Arcotheres purpureus, from a commercially viable species of bivalve such as Protapes gallus as well as its incidence in waters of mainland, India is a cause for concern necessitating further investigations.
To assess the status of iodine deficiency in Pondicherry by finding out the urinary excretion of iodine and the prevalence of goiter among school children.
315 children between the age group of 9-13 ...yr from 30 schools in Pondicherry were examined for the presence of goiter and their urine samples were subjected to biochemical analysis to find out the urinary iodine levels (UIE).
The percentage of children who had inadequate iodine intake and showed urinary iodine level of less than 100 mcg/ L was 44.4%. Amongst them, 14.3% had a greater degree of iodine deficiency with less than 50 mcg/L of iodine in urine. The prevalence of goiter was 15.24%.
The prevalence of goiter is high. The iodine intake is quite low as exhibited by the UIE levels of < 100mcg/L in the children in Pondicherry, which might have had an unseen impact on the intelligence and school performance of these children.
A cross sectional survey was conducted in 2005 among 358 school children from 8 communities in the district of Pondicherry to assess the iodine content of salt at consumer level. School children were ...asked to bring salt consumed at their houses and 290 salt samples could finally be analysed. Only 26.2% of the population in the district were found to consume salt with more than 15 ppm iodine. Consumption of non-iodised salt was more in rural areas (96.4%) as compared to urban areas (71.3%). 39 salt samples from different retail shops in Pondicherry showed a mean value of 35.6+/-10.7 ppm.
In Today's world, disease diagnosis plays a vital role in the area of medical imaging. Medical imaging is the method and procedure of making visual descriptions of the interior of a body for clinical ...investigation and clinical mediation, as well as visual depiction of the function of some organs or tissues. Medical imaging also deals with disease detection. We can get a better view of detecting the disease by using machine learning in medical imaging. So Now what is Machine Learning (ML)? ML is an artificial intelligence (AI) utilization that presents the system with the capacity to learn and develop itself. It mainly focuses on the development of computer programs that can access the data and use it for themselves. In this chapter we will focus on detection Diabetic retinopathy using machine learning. Diabetes is a type of disease that result in too much sugar in blood. There are three main types of diabetes. Diabetic retinopathy is one of them. Diabetic retinopathy is an eye infection brought about by the inconvenience of diabetes and we ought to recognize it right on time for effective treatment. As the disease advances, the sight of a patient may begin to break down and lead to diabetic retinopathy. Thus, two groups were recognized, in particular non‐proliferative diabetic retinopathy and proliferative diabetic retinopathy. We should detect it as soon as possible as it can cause permanent loss of vision. By using ML in medical imaging we can detect it much faster and more accurately. In this chapter we will analyze about different ML technologies, algorithms and models to diagnose diabetic retinopathy in an efficient manner to support the healthcare system.
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