Explore the vast range of titles available.

Many clinical diagnoses depend on the electronic equipment to detect and treat the diseases from basic illness to fatal diseases or injuries. But, most of the diagnosis techniques are invasive and cause pain or uncomfortable issues to the patients. However, the non-invasive methods, like breath exhale testing which is completely painless. In this work, we report a preliminary study of simple and compact wireless smartphone based sensing device. This device was fabricated to detect the ammonia vapor in the human exhaled breath towards diagnosing renal disease. The sensing performance of the device was tested in laboratory conditions and the obtained results are as follows. The developed device exhibited good sensing response of 584 % with response and recovery time in the order of seconds towards 50 ppm for ammonia vapor. Furthermore, ammonia sensitivity and selectivity tests are carried out for the developed breath analyzer device and the results are reported.

Early detection of oral cancer necessitates a minimally invasive, tissue-specific diagnostic tool that facilitates screening/surveillance. Brush biopsy, though minimally invasive, demands skilled cyto-pathologist expertise. In this study, we explored the clinical utility/efficacy of a tele-cytology system in combination with Artificial Neural Network (ANN) based risk-stratification model for early detection of oral potentially malignant (OPML)/malignant lesion. A portable, automated tablet-based tele-cytology platform capable of digitization of cytology slides was evaluated for its efficacy in the detection of OPML/malignant lesions (n = 82) in comparison with conventional cytology and histology. Then, an image pre-processing algorithm was established to segregate cells, ANN was trained with images (n = 11,981) and a risk-stratification model developed. The specificity, sensitivity and accuracy of platform/ stratification model were computed, and agreement was examined using Kappa statistics. The tele-cytology platform, Cellscope, showed an overall accuracy of 84-86% with no difference between tele-cytology and conventional cytology in detection of oral lesions (kappa, 0.67-0.72). However, OPML could be detected with low sensitivity (18%) in accordance with the limitations of conventional cytology. The integration of image processing and development of an ANN-based risk stratification model improved the detection sensitivity of malignant lesions (93%) and high grade OPML (73%), thereby increasing the overall accuracy by 30%. Tele-cytology integrated with the risk stratification model, a novel strategy established in this study, can be an invaluable Point-of-Care (PoC) tool for early detection/screening in oral cancer. This study hence establishes the applicability of tele-cytology for accurate, remote diagnosis and use of automated ANN-based analysis in improving its efficacy.

Acute kidney Injury (AKI) is common and is associated with poor outcomes in critically ill patients. Current diagnosis and staging of AKI depends on measurement of urine output and serum creatinine. Both of them have their own fallacies and therefore diagnosis of AKI is often delayed. Use of novel biomarkers for diagnosis of AKI have been complicated by their costs, lack of availability and validation in critically ill patients. Of late, renal ultrasonography and Doppler have gained importance in the detection of AKI in early stages. The aim of this study was to determine whether renal Doppler parameters at admission can predict the development of AKI at day 5 in patients with acute circulatory failure. After ethics committee approval and informed written consent, we recruited 80 adult patients with acute circulatory failure in this single center, prospective observational study. We measured renal resistive index (RRI), power Doppler ultrasound (PDU) score and their ratio (RRI/PDU) at admission to ICU. Other baseline characteristics, resuscitation parameters and level of organ support were noted. Outcome was AKI at day 5. Statistical analysis was performed using SPSS 21.0 software (IBM, Chicago, USA). Univariate logistic regression was used to assess predictive ability and receiver operating characteristic (ROC) curve was used to predict sensitivity and specificity of renal Doppler ultrasound parameters for prediction of AKI. N = 32 patients developed AKI. Baseline and demographic data were comparable between AKI and non-AKI groups. At day 1, RRI (AKI vs non-AKI: 0.62 ± 0.08 vs 0.51 ± 0.03; p < 0.0001) and RRI/PDU (AKI vs non-AKI: 0.4 ± 0.2 vs 0.2 ± 0.06; p < 0.0001) were significantly higher and PDU (AKI vs non-AKI: 1.88 ± 0.66 vs 2.71 ± 0.5; p < 0.0001) was significantly lower in patients with AKI as compared to non-AKI group. Based on ROC curve, RRI/PDU was the best predictor of AKI (AUROC 0.88, cut off >0.24, sensitivity 84%, specificity 83%; Fig. 1) compared to other parameters (RRI AUROC 0.87, cut off >0.56, sensitivity 68%, specificity 97%; PDU AUROC 0.81, cut off ≤2, sensitivity 84%, specificity 72%). Renal Doppler parameters (RRI, PDU and RRI/PDU) at admission can predict AKI in critically ill patients with acute circulatory failure. The RRI/PDU at day 1 has highest predictive ability compared to other parameters.

Resistance to colistin, a last resort antibiotic, has emerged in India. We investigated colistin-resistant Klebsiella pneumoniae(ColR-KP) in a hospital in India to describe infections, characterize resistance of isolates, compare concordance of detection methods, and identify transmission events. Retrospective observational study. Case-patients were defined as individuals from whom ColR-KP was isolated from a clinical specimen between January 2016 and October 2017. Isolates resistant to colistin by Vitek 2 were confirmed by broth microdilution (BMD). Isolates underwent colistin susceptibility testing by disk diffusion and whole-genome sequencing. Medical records were reviewed. Of 846 K. pneumoniae isolates, 34 (4%) were colistin resistant. In total, 22 case-patients were identified. Most (90%) were male; their median age was 33 years. Half were transferred from another hospital; 45% died. Case-patients were admitted for a median of 14 days before detection of ColR-KP. Also, 7 case-patients (32%) received colistin before detection of ColR-KP. All isolates were resistant to carbapenems and susceptible to tigecycline. Isolates resistant to colistin by Vitek 2 were also resistant by BMD; 2 ColR-KP isolates were resistant by disk diffusion. Moreover, 8 multilocus sequence types were identified. Isolates were negative for mobile colistin resistance (mcr) genes. Based on sequencing analysis, in-hospital transmission may have occurred with 8 case-patients (38%). Multiple infections caused by highly resistant, mcr-negative ColR-KP with substantial mortality were identified. Disk diffusion correlated poorly with Vitek 2 and BMD for detection of ColR-KP. Sequencing indicated multiple importation and in-hospital transmission events. Enhanced detection for ColR-KP may be warranted in India.

We derive improved stellar luminosity limits on a generic light CP-even scalar field \\(S\\) mixing with the Standard Model (SM) Higgs boson from the supernova SN1987A, the Sun, red giants (RGs) and white dwarfs (WDs). For the first time, we include the geometric effects for the decay and absorption of \\(S\\) particles in the stellar interior. For SN1987A and the Sun, we also take into account the detailed stellar profiles. We find that a broad range of the scalar mass and mixing angle can be excluded by our updated astrophysical constraints. For instance, SN1987A excludes \\(1.010^-7 3.0 10^-5\\) and scalar mass up to 219 MeV, which covers the cosmological blind spot with a high reheating temperature. The updated solar limit excludes the mixing angle in the range of \\(1.5 10^-12 < < 1\\), with scalar mass up to 45 keV. The RG and WD limits are updated to \\(5.3 10^-13 < < 0.39\\) and \\(2.8 10^-18 < < 1.8 10^-4\\), with scalar mass up to 392 keV and 290 keV, respectively.