Fine needle aspiration cytology in parotid lumps

Over a period of two years, Fine Needle Aspiration Cytology (FNAC) was performed on 33 patients presenting with a parotid lump. Five patients were excluded as they were treated medically after FNAC report. The FNAC results of 28 cases were compared with histopathological diagnoses of surgically resected specimens. There were 8 true positive, 17 true negative, 1 false positive and 2 false negative cases. Sensitivity was 80%, specificity 94.4% and diagnostic accuracy 89.3%. FNAC is a simple quick, accurate and virtually complications free investigative modality. It is also helpful adjunct to assess preoperatively the suitability and extent of the surgical treatment

Marketing of selected surplus fruits and vegetables of Dir district

ABSTRACT This study was undertaken in 2005 to enquire into the efficiency of marketing system of selected surplus vegetables and fruits of Dir district. The study reveals that the existing marketing system is, generally speaking, capable of handling the surplus selected products-onion, tomato, okra, citrus, persimmon, peas, walnuts,-in a normal year, and is efficiencies-wise nearly at par with the corresponding system in the province. It has evolved over a long period and is largely compatible with the characteristics of the project area's agricultural sector. The scope for improvement, at every stage in the marketing system is, however, large. The preharvest sale-especially of fruits, the heavy dependence on Beoparies, the heavy post-harvest losses, and occasional scarcity of transport at peak seasons and when especially where there is bumper harvest, the poor physical conditions of wholesale market centers etc, are the major problem areas. Price information of small farmer is not good, and the surplus products is mostly marketed in a far market centers through old connections with Arthi (middleman), wholesalers, etc, which may not necessarily fetch the best possible price. Farmer's net revenue from their selected surplus produce can be improved by 15-20 % by undertaking marketing system improvements through public-private sector cooperation. Farmers Association need to be formed through the existing village organizations in the project area, so as to bring about efficiency in the farming sector, embracing all aspects of production and marketing

Biosynthesis and Degradation of Carotenoids in Ornamental Crops with specific reference to Chrysanthemum

Carotenoids are lipophilic secondary metabolites derived from the isoprenoid pathway, accumulated in most plant organs and widely used as an antioxidant. Carotenoids synthesized in chloroplasts are essential for protecting tissues against photo-oxidative damage in the green tissues of higher plants. The importance of carotenoids for plant growth and development is evident since at least two major phytohormones, strigolactones and abscisic acid, are derived from carotenoid precursors. In flowers, carotenoids synthesized in the chromoplasts provide colour to the petals, ranging from yellow to red, in order to attract pollinators and determines the commercial value of ornamental plants. On analysis in chrysanthemum, β, ɛ-carotenoids, lutein and its derivatives, reflecting the high expression levels of lycopene ɛ-cyclase (LCYE) were found in yellow petals compared to the ratio of β, β-carotenoids to total carotenoids found in leaves reflecting the high expression levels of lycopene β-cyclase (LCYB). Petals of the yellow-flowered cultivar Yellow Paragon showed increased accumulation and drastic componential changes of carotenoids as they mature, compared to petals of the white-flowered cultivar Paragon that showed drastically decreased carotenoid content during petal development.The white petals of chrysanthemum (Chrysanthemum morifolium Ramat.) contain a factor that inhibits the accumulation of carotenoids. All the white-flowered chrysanthemum cultivars tested showed high levels of CmCCD4a transcript in their petals, whereas most of the yellow flowered cultivars showed extremely low levels indicating that in white petals of chrysanthemums, carotenoids are synthesized but subsequently degraded into colourless compounds, which results in the white colour. Studying the regulatory mechanisms underlying carotenoid accumulation in ornamental plants at the molecular level will help in producing novel coloured cultivars by plant transformation

The Macroscopic Rate of Nucleic Acid Translocation by Hepatitis C virus Helicase NS3h is Dependent on Both the Sugar and Base Moieties

The NS3 helicase (NS3h) of hepatitis C virus (HCV) is a 3′ to 5′ SF2 RNA and DNA helicase that is essential for the replication of HCV. We have examined the kinetic mechanism of translocation of NS3h along single-stranded nucleic acid with bases rU, dU and dT and have found that the macroscopic rate of translocation is dependent upon both the base and sugar moieties of the nucleic acid, with approximate macroscopic translocation rates of 3 nt/s (oligo-dT), 35 nt/s (oligo-dU), and 42 nt/s (oligo-rU), respectively. We found a strong correlation between the macroscopic translocation rates and the binding affinity of the translocating NS3h protein to the respective substrates such that weaker affinity corresponded to faster translocation. The values of K0.5 for NS3h translocation at a saturating ATP concentration are: (3.3 ± 0.4) μM nucleotide (poly-dT), (27 ± 2) μM nucleotide (poly-dU), and (36 ± 2) μM nucleotide (poly-rU). Furthermore, the results of isothermal titration of NS3h with these oligonucleotides suggest that differences in TΔS° are the principal source of the differences in the affinity of NS3h binding to these substrates. Interestingly, despite the differences in macroscopic translocation rates and binding affinities, the ATP coupling stoichiometry for NS3h translocation was identical for all three substrates, ~0.5 ATP molecules consumed per nucleotide translocated. This similar periodicity of ATP consumption implies a similar mechanism for NS3h translocation along RNA and DNA substrates

Internet of Things (IoT) Based Indoor Air Quality Sensing and Predictive Analytic—A COVID-19 Perspective

Indoor air quality typically encompasses the ambient conditions inside buildings and public facilities that may affect both the mental and respiratory health of an individual. Until the COVID-19 outbreak, indoor air quality monitoring was not a focus area for public facilities such as shopping complexes, hospitals, banks, restaurants, educational institutes, and so forth. However, the rapid spread of this virus and its consequent detrimental impacts have brought indoor air quality into the spotlight. In contrast to outdoor air, indoor air is recycled constantly causing it to trap and build up pollutants, which may facilitate the transmission of virus. There are several monitoring solutions which are available commercially, a typical system monitors the air quality using gas and particle sensors. These sensor readings are compared against well known thresholds, subsequently generating alarms when thresholds are violated. However, these systems do not predict the quality of air for future instances, which holds paramount importance for taking timely preemptive actions, especially for COVID-19 actual and potential patients as well as people suffering from acute pulmonary disorders and other health problems. In this regard, we have proposed an indoor air quality monitoring and prediction solution based on the latest Internet of Things (IoT) sensors and machine learning capabilities, providing a platform to measure numerous indoor contaminants. For this purpose, an IoT node consisting of several sensors for 8 pollutants including NH3, CO, NO2, CH4, CO2, PM 2.5 along with the ambient temperature & air humidity is developed. For proof of concept and research purposes, the IoT node is deployed inside a research lab to acquire indoor air data. The proposed system has the capability of reporting the air conditions in real-time to a web portal and mobile app through GSM/WiFi technology and generates alerts after detecting anomalies in the air quality. In order to classify the indoor air quality, several machine learning algorithms have been applied to the recorded data, where the Neural Network (NN) model outperformed all others with an accuracy of 99.1%. For predicting the concentration of each air pollutant and thereafter predicting the overall quality of an indoor environment, Long and Short Term Memory (LSTM) model is applied. This model has shown promising results for predicting the air pollutants’ concentration as well as the overall air quality with an accuracy of 99.37%, precision of 99%, recall of 98%, and F1-score of 99%. The proposed solution offers several advantages including remote monitoring, ease of scalability, real-time status of ambient conditions, and portable hardware, and so forth

Corneal nerve and brain imaging in mild cognitive impairment and dementia

Background: Visual rating of medial temporal lobe atrophy (MTA) is an accepted structural neuroimaging marker of Alzheimer's disease. Corneal confocal microscopy (CCM) is a non-invasive ophthalmic technique that detects neuronal loss in peripheral and central neurodegenerative disorders. Objective: To determine the diagnostic accuracy of CCM for mild cognitive impairment (MCI) and dementia compared to medial temporal lobe atrophy (MTA) rating on MRI. Methods: Subjects aged 60-85 with no cognitive impairment (NCI), MCI, and dementia based on the ICD-10 criteria were recruited. Subjects underwent cognitive screening, CCM, and MTA rating on MRI. Results: 182 subjects with NCI (n = 36), MCI (n = 80), and dementia (n = 66), including AD (n = 19, 28.8%), VaD (n = 13, 19.7%), and mixed AD (n = 34, 51.5%) were studied. CCM showed a progressive reduction in corneal nerve fiber density (CNFD, fibers/mm2) (32.0±7.5 versus 24.5±9.6 and 20.8±9.3, p < 0.0001), branch density (CNBD, branches/mm2) (90.9±46.5 versus 59.3±35.7 and 53.9±38.7, p < 0.0001), and fiber length (CNFL, mm/mm2) (22.9±6.1 versus 17.2±6.5 and 15.8±7.4, p < 0.0001) in subjects with MCI and dementia compared to NCI. The area under the ROC curve (95% CI) for the diagnostic accuracy of CNFD, CNBD, CNFL compared to MTA-right and MTA-left for MCI was 78% (67-90%), 82% (72-92%), 86% (77-95%) versus 53% (36-69%) and 40% (25-55%), respectively, and for dementia it was 85% (76-94%), 84% (75-93%), 85% (76-94%) versus 86% (76-96%) and 82% (72-92%), respectively. Conclusion: The diagnostic accuracy of CCM, a non-invasive ophthalmic biomarker of neurodegeneration, was high and comparable with MTA rating for dementia but was superior to MTA rating for MCI

Association of Cerebral Ischemia With Corneal Nerve Loss and Brain Atrophy in MCI and Dementia

IntroductionThis study assessed the association of cerebral ischemia with neurodegeneration in mild cognitive impairment (MCI) and dementia.MethodsSubjects with MCI, dementia and controls underwent assessment of cognitive function, severity of brain ischemia, MRI brain volumetry and corneal confocal microscopy.ResultsOf 63 subjects with MCI (n = 44) and dementia (n = 19), 11 had no ischemia, 32 had subcortical ischemia and 20 had both subcortical and cortical ischemia. Brain volume and corneal nerve measures were comparable between subjects with subcortical ischemia and no ischemia. However, subjects with subcortical and cortical ischemia had a lower hippocampal volume (P &lt; 0.01), corneal nerve fiber length (P &lt; 0.05) and larger ventricular volume (P &lt; 0.05) compared to those with subcortical ischemia and lower corneal nerve fiber density (P &lt; 0.05) compared to those without ischemia.DiscussionCerebral ischemia was associated with cognitive impairment, brain atrophy and corneal nerve loss in MCI and dementia

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability