Insights into physiological and metabolic modulations instigated by exogenous sodium nitroprusside and spermidine reveals drought tolerance in Helianthus annuus L.

Drought is the most critical climatic factor instigating severe threats to crop production worldwide. As stress ameliorants, exogenous sodium nitroprusside (SNP) or spermidine (Spd) supply has positive responses in alleviating the drought adversities in crops, however, reports regarding their combined effects is still elusive. Here, the protective role of SNP and Spd to confer drought resistance in sunflower (Helianthus annuus L.) through up-regulation of physiological and metabolic processes was investigated. Plants were foliar sprayed with individual or combined SNP (100 µM) or Spd (100 µM). Drought was induced by keeping the soil at 100% (normal) and 60% (drought stress) field capacity levels. Drought exposure caused a marked decline in relative water content (RWC), excised leaf water retention (ELWR), net photosynthesis (PN), transpiration rate (E), stomatal conductance (gs), and sub-stomatal conductance (Ci) with substantial increase in catalase (CAT), superoxide dismutase (SOD), and peroxidase (POX). SNP plus Spd exhibited a considerable increase in CAT, SOD, and POX activities under drought, and helped the plants to retain optimum water status and gas exchange attributes. Similarly, hydrogen peroxide (H2O2) and malondialdehyde (MDA) contents were increased significantly to drought; however, a notable decline was recorded in drought prone plants treated with exogenous SNP plus Spd. Moreover, addition of SNP plus Spd under drought caused a remarkable increase in chlorophyll a (Chl a), chlorophyll b (Chl b), chlorophyll total (Chl t), carotenoids (Car), and growth traits like shoot length (SL), root length (RL), shoot fresh weight (SFW), shoot dry weight (SDW), root dry weight (RDW). Combined SNP and Spd application could potentially alleviate the drought-induced damages in sunflower through increased water status (8-10%), antioxidant enzymes (17-28%), chlorophyll pigments (14-21%), and growth performance (12-22%) under drought stress.

A Simple and Efficient Deep Learning-Based Framework for Automatic Fruit Recognition.

Accurate detection and recognition of various kinds of fruits and vegetables by using the artificial intelligence (AI) approach always remain a challenging task due to similarity between various types of fruits and challenging environments such as lighting and background variations. Therefore, developing and exploring an expert system for automatic fruits' recognition is getting more and more important after many successful approaches; however, this technology is still far from being mature. The deep learning-based models have emerged as state-of-the-art techniques for image segmentation and classification and have a lot of promise in challenging domains such as agriculture, where they can deal with the large variability in data better than classical computer vision methods. In this study, we proposed a deep learning-based framework to detect and recognize fruits and vegetables automatically with difficult real-world scenarios. The proposed method might be helpful for the fruit sellers to identify and differentiate various kinds of fruits and vegetables that have similarities. The proposed method has applied deep convolutional neural network (DCNN) to the undertakings of distinguishing natural fruit images of the Gilgit-Baltistan (GB) region as this area is famous for fruits' production in Pakistan as well as in the world. The experimental outcomes demonstrate that the suggested deep learning algorithm has the effective capability of automatically recognizing the fruit with high accuracy of 96%. This high accuracy exhibits that the proposed approach can meet world application requirements.

Internet of Things with Deep Learning-Based Face Recognition Approach for Authentication in Control Medical Systems.

Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. It can help users in this field get an advantage in terms of enhanced touchless authentication, especially in spreading infectious diseases like coronavirus disease 2019 (COVID-19). Even though there is a number of available security systems, they suffer from one or more of issues, such as identity fraud, loss of keys and passwords, or spreading diseases through touch authentication tools. To overcome these issues, IoT-based intelligent control medical authentication systems using DL models are proposed to enhance the security factor of medical and healthcare places effectively. This work applies IoT with DL models to recognize human faces for authentication in smart control medical systems. We use Raspberry Pi (RPi) because it has low cost and acts as the main controller in this system. The installation of a smart control system using general-purpose input/output (GPIO) pins of RPi also enhanced the antitheft for smart locks, and the RPi is connected to smart doors. For user authentication, a camera module is used to capture the face image and compare them with database images for getting access. The proposed approach performs face detection using the Haar cascade techniques, while for face recognition, the system comprises the following steps. The first step is the facial feature extraction step, which is done using the pretrained CNN models (ResNet-50 and VGG-16) along with linear binary pattern histogram (LBPH) algorithm. The second step is the classification step which can be done using a support vector machine (SVM) classifier. Only classified face as genuine leads to unlock the door; otherwise, the door is locked, and the system sends a notification email to the home/medical place with detected face images and stores the detected person name and time information on the SQL database. The comparative study of this work shows that the approach achieved 99.56% accuracy compared with some different related methods.

Ipilimumab in a real-world population: A prospective Phase IV trial with long-term follow-up.

Ipilimumab was the first treatment that improved survival in advanced melanoma. Efficacy and toxicity in a real-world setting may differ from clinical trials, due to more liberal eligibility criteria and less intensive monitoring. Moreover, high costs and lack of biomarkers have raised cost-benefit concerns about ipilimumab in national healthcare systems and limited its use. Here, we report the prospective, interventional study, Ipi4 (NCT02068196), which aimed to investigate the toxicity and efficacy of ipilimumab in a real-world population with advanced melanoma. This national, multicentre, phase IV trial included 151 patients. Patients received ipilimumab 3 mg/kg intravenously and were followed for at least 5 years or until death. Treatment interruption or cessation occurred in 38%, most frequently due to disease progression (19%). Treatment-associated grade 3 to 4 toxicity was observed in 28% of patients, and immune-related toxicity in 56%. The overall response rate was 9%. Median overall survival was 12.1 months (95% CI: 8.3-15.9); and progression-free survival 2.7 months (95% CI: 2.6-2.8). After 5 years, 20% of patients were alive. In a landmark analysis from 6 months, improved survival was associated with objective response (HR 0.16, P = .001) and stable disease (HR 0.49, P = .005) compared to progressive disease. Poor performance status, elevated lactate dehydrogenase and C-reactive protein were identified as biomarkers. This prospective trial represents the longest reported follow-up of a real-world melanoma population treated with ipilimumab. Results indicate safety and efficacy comparable to phase III trials and suggest that the use of ipilimumab can be based on current cost-benefit estimates.

The Prognostic Relevance of Sentinel Lymph Node Metastases Assessed by PHGR1 mRNA Quantification in Stage I to III Colon Cancer.

BACKGROUND: Regional lymph node (LN) metastasis is a strong and well-established prognostic factor in colon cancer, and recent data suggest a prognostic value of detecting micrometastases and isolated tumor cells in regional LNs. The aim of the study was to investigate the clinical relevance of detecting sentinel lymph node (SLN) metastases in colon cancer patients by measuring the novel metastasis marker PHGR1 mRNA. METHODS: Using quantitative reverse-transcription polymerase chain reaction, we measured PHGR1 mRNA levels in SLNs and primary tumors from 206 patients surgically treated for stage I to III colon cancer and 52 normal LNs from patients undergoing surgery for benign colon diseases. The prognostic impact of these findings was evaluated by Kaplan-Meier analysis and Cox proportional-hazards regression. RESULTS: Compared to normal LNs, elevated PHGR1 mRNA levels were detected in SLNs from 56 (89%) of the 63 patients with pN+ disease. Furthermore, 68 (48%) of the 143 node-negative (pN0) patients had elevated PHGR1 mRNA levels in SLNs, suggesting occult metastases. With a median follow-up of 7.2 years, a significantly shorter recurrence-free (P=.005) and disease-specific (P=.02) survival was observed in patients with elevated PHGR1 mRNA levels in SLNs. Multivariable modeling showed that the SLN PHGR1 mRNA level was an independent prognostic factor. However, when the survival analyses were restricted to pN0 patients, no significant prognostic information was found. CONCLUSION: Measuring PHGR1 mRNA in SLNs provided independent prognostic information on operable colon cancer patients but not in the pN0 subgroup.

Prognostic relevance of an epigenetic biomarker panel in sentinel lymph nodes from colon cancer patients.

BACKGROUND: Patients with early colorectal cancer (stages I-II) generally have a good prognosis, but a subgroup of 15-20% experiences relapse and eventually die of disease. Occult metastases have been suggested as a marker for increased risk of recurrence in patients with node-negative disease. Using a previously identified, highly accurate epigenetic biomarker panel for early detection of colorectal tumors, we aimed at evaluating the prognostic value of occult metastases in sentinel lymph nodes of colon cancer patients. RESULTS: The biomarker panel was analyzed by quantitative methylation-specific PCR in primary tumors and 783 sentinel lymph nodes from 201 patients. The panel status in sentinel lymph nodes showed a strong association with lymph node stage (P = 8.2E-17). Compared with routine lymph node diagnostics, the biomarker panel had a sensitivity of 79% (31/39). Interestingly, among 162 patients with negative lymph nodes from routine diagnostics, 13 (8%) were positive for the biomarker panel. Colon cancer patients with high sentinel lymph node methylation had an inferior prognosis (5-year overall survival P = 3.0E-4; time to recurrence P = 3.1E-4), although not significant. The same trend was observed in multivariate analyses (P = 1.4E-1 and P = 6.7E-2, respectively). Occult sentinel lymph node metastases were not detected in early stage (I-II) colon cancer patients who experienced relapse. CONCLUSIONS: Colon cancer patients with high sentinel lymph node methylation of the analyzed epigenetic biomarker panel had an inferior prognosis, although not significant in multivariate analyses. Occult metastases in TNM stage II patients that experienced relapse were not detected.

Xanthogranulomatous pyelonephritis due to calculi: report of 63 cases and review of literature.

OBJECTIVE: To examine the relationship between clinical history and results of renal investigations in patients with xanthogranulomatous pyelonephritis. METHODS: A retrospective review was conducted on 63 cases presenting with histopathological diagnosis of xanthogranulomatous pyelonephritis between 1995 to 2002, at the department of Urology, Bolan Medical College and Sandeman Provincial Teaching Hospital Quetta. RESULTS: There were 26 males and 37 females having an average follow up of two years. Positive findings on examination and investigations at presentation were fever and flank pain in 59 (93.6%) patients and pyuria in 34 (53.9%) patients. All the patients had renal and ureteric calculi with no or severe reduction in the function of the affected kidney on DTPA scan. Hypertrophy of the contra lateral kidney was seen in 56 (88.8%) patients. CONCLUSION: Xanthogranulomatous pyelonephritis is a common entity in this part of the world. Late referral leads to loss of the kidney. Pre-operative diagnosis of the condition is desirable and if surgery is mandatory then all infected tissues have to be removed.