Assessment of the hyperspectral data analysis as a tool to diagnose xylella fastidiosa in the asymptomatic leaves of olive plants

Xylella fastidiosa is a bacterial pathogen affecting many plant species worldwide. Recently, the subspecies pauca (Xfp) has been reported as the causal agent of a devastating disease on olive trees in the Salento area (Apulia region, southeastern Italy), where centenarian and millenarian plants constitute a great agronomic, economic, and landscape trait, as well as an important cultural heritage. It is, therefore, important to develop diagnostic tools able to detect the disease early, even when infected plants are still asymptomatic, to reduce the infection risk for the surrounding plants. The reference analysis is the quantitative real time-Polymerase-Chain-Reaction (qPCR) of the bacterial DNA. The aim of this work was to assess whether the analysis of hyperspectral data, using different statistical methods, was able to select with sufficient accuracy, which plants to analyze with PCR, to save time and economic resources. The study area was selected in the Municipality of Oria (Brindisi). Partial Least Square Regression (PLSR) and Canonical Discriminant Analysis (CDA) indicated that the most important bands were those related to the chlorophyll function, water, lignin content, as can also be seen from the wilting symptoms in Xfp-infected plants. The confusion matrix of CDA showed an overall accuracy of 0.67, but with a better capability to discriminate the infected plants. Finally, an unsupervised classification, using only spectral data, was able to discriminate the infected plants at a very early stage of infection. Then, in phase of testing qPCR should be performed only on the plants predicted as infected from hyperspectral data, thus, saving time and financial resources

Pseudohypoparathyroidism and GNAS epigenetic defects : clinical evaluation of Albright hereditary osteodystrophy and molecular analysis in 40 patients

Context: The two main subtypes of pseudohypoparathyroidism (PHP), PHP-Ia and -Ib, are caused by mutations in GNAS exons 1-13 and methylation defects in the imprinted GNAS cluster, respectively. PHP-Ia patients show Albright hereditary osteodystrophy (AHO) and resistance toward PTH and additional hormones, whereas PHP-Ib patients do not have AHO, and hormone resistance appears to be limited to PTH and TSH. Recently, methylation defects have been detected in few patients with PHP and mild AHO, indicating a molecular overlap between the two forms. Objectives: The aim of the study was to screen patients with clinically diagnosed PHP-Ia for methylation defects and to investigate the presence of correlations between the molecular findings and AHO severity. Patients and Methods: We investigated differential methylation of GNAS regions and STX16 microdeletions in genomicDNAfrom 40 patients with sporadicAHOand multihormone resistance, with no mutations in Gs -coding GNAS exons. Results: Molecular analysis showed GNAS cluster imprinting defects in 24 of the 40 patients analyzed. NoSTX16 deletion was detected. The presence of imprinting defects was not associated with the severity of AHO or with specific AHO signs. Conclusions: We report the largest series of the literature of patients with clinical AHO and multihormone resistance and no mutation in the Gs gene. Our findings of frequent GNAS imprinting defects further confirm the existence of an overlap between molecular and clinical features of PHP-Ia and PHP-Ib and highlight the necessity of a new clinical classification of the disease that takes into account the recent knowledge on the molecular basis underlying these defects

Validation of a new optical diagnosis training module to improve dysplasia characterization in inflammatory bowel disease:a multicenter international study

Background and aims Inflammatory bowel disease (IBD) increases risk of dysplasia and colorectal cancer. Advanced endoscopic techniques allow for the detection and characterization of IBD dysplastic lesions, but specialized training is not widely available. We aim to develop and validate an online training platform to improve the detection and characterization of colonic lesions in IBD: OPTIC-IBD. Methods We designed a web-based learning module that includes surveillance principles, optical diagnostic methods, approach to characterization, classifications of colonic lesions, utilizing still images and videos. We invited gastroenterologists from Canada, Italy, and the UK, with a wide range of experience. Participants reviewed 24 educational videos of IBD colonic lesions, predicted histology, and rated their confidence. The primary endpoint was to improve accuracy in detecting dysplastic lesions following training on the platform. Furthermore, participants were randomized 1:1 to get additional training or not, with a final assessment occurring after 60 days. Diagnostic performance for dysplasia and rater confidence were measured. Results One hundred seventeen participants completed the study and were assessed for the primary endpoint. Diagnostic accuracy improved from 70.8% to 75.0% (p 0.002) following training, with the greatest improvements seen in less experienced endoscopists. Improvements in both accuracy and confidence were sustained after 2 months of assessment, although the group randomized to receive additional training did not improve further. Similarly, participants’ confidence in characterizing lesions significantly improved between pre- and post-course (

A virtual chromoendoscopy artificial intelligence system to detect endoscopic and histologic activity/remission and predict clinical outcomes in ulcerative colitis

Background Endoscopic and histological remission (ER, HR) are therapeutic targets in ulcerative colitis (UC). Virtual chromoendoscopy (VCE) improves endoscopic assessment and the prediction of histology; however, interobserver variability limits standardized endoscopic assessment. We aimed to develop an artificial intelligence (AI) tool to distinguish ER/activity, and predict histology and risk of flare from white-light endoscopy (WLE) and VCE videos. Methods 1090 endoscopic videos (67 280 frames) from 283 patients were used to develop a convolutional neural network (CNN). UC endoscopic activity was graded by experts using the Ulcerative Colitis Endoscopic Index of Severity (UCEIS) and Paddington International virtual ChromoendoScopy ScOre (PICaSSO). The CNN was trained to distinguish ER/activity on endoscopy videos, and retrained to predict HR/activity, defined according to multiple indices, and predict outcome; CNN and human agreement was measured. Results The AI system detected ER (UCEIS = 1) in WLE videos with 72% sensitivity, 87% specificity, and an area under the receiver operating characteristic curve (AUROC) of 0.85; for detection of ER in VCE videos (PICaSSO = 3), the sensitivity was 79 %, specificity 95%, and the AUROC 0.94. The prediction of HR was similar between WLE and VCE videos (accuracies ranging from 80% to 85%). The model s stratification of risk of flare was similar to that of physician-assessed endoscopy scores. Conclusions Our system accurately distinguished ER/activity and predicted HR and clinical outcome from colonoscopy videos. This is the first computer model developed to detect inflammation/healing on VCE using the PICaSSO and the first computer tool to provide endoscopic, histologic, and clinical assessment

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Validation of a new optical diagnosis training module to improve dysplasia characterization in inflammatory bowel disease: a multicenter international study

Background and Aims: Inflammatory bowel disease (IBD) increases risk of dysplasia and colorectal cancer. Advanced endoscopic techniques allow for the detection and characterization of IBD dysplastic lesions, but specialized training is not widely available. We aimed to develop and validate an online training platform to improve the detection and characterization of colonic lesions in IBD: OPtical diagnosis Training to Improve dysplasia Characterization in Inflammatory Bowel Disease (OPTIC-IBD). Methods: We designed a web-based learning module that includes surveillance principles, optical diagnostic methods, approach to characterization, and classifications of colonic lesions using still images and videos. We invited gastroenterologists from Canada, Italy, and the United Kingdom with a wide range of experience. Participants reviewed 24 educational videos of IBD colonic lesions, predicted histology, and rated their confidence. The primary endpoint was to improve accuracy in detecting dysplastic lesions after training on the platform. Furthermore, participants were randomized 1:1 to get additional training or not, with a final assessment occurring after 60 days. Diagnostic performance for dysplasia and rater confidence were measured. Results: A total of 117 participants completed the study and were assessed for the primary endpoint. Diagnostic accuracy improved from 70.8% to 75.0% (P = .002) after training, with the greatest improvements seen in less experienced endoscopists. Improvements in both accuracy and confidence were sustained after 2 months of assessment, although the group randomized to receive additional training did not improve further. Similarly, participants’ confidence in characterizing lesions significantly improved between before and after the course (P < .001), and it was sustained after 2 months of assessment. Conclusions: The OPTIC-IBD training module demonstrated that an online platform could improve participants’ accuracy and confidence in the optical diagnosis of dysplasia in patients with IBD. The training platform can be widely available and improve endoscopic care for people with IBD

The periodic table of photosynthetic purple non-sulfur bacteria: intact cell-metal ions interactions

Photosynthetic purple non-sulfur bacteria (PNB) have been widely utilized as model organisms to study bacterial photosynthesis. More recently, the remarkable resistance of these microorganisms to several metals ions called particular interest. As a result, several research efforts were directed toward clarifying the interactions of metal ions with PNB. The mechanisms of metal ions active uptake and bioabsorption have been studied in detail, unveiling that PNB enable harvesting and removing various toxic ions, thus fostering applications in environmental remediation. Herein, we present the most important achievements in the understanding of intact cell-metal ions interactions and the approaches utilized to study such processes. Following, the application of PNB-metal ions interactions toward metal removal from contaminated environments is presented. Finally, the possible coupling of PNB with abiotic electrodes to obtain biohybrid electrochemical systems is proposed as a sustainable pathway to tune and enhance metal removal and monitoring

Halotolerance of Rhodobacter sphaeroides for saline and hypersaline wastewater bioremediation

Hypersaline wastewaters require the continuous development of new and inexpensive alternatives for bioremediation. Halotolerant bacteria, which tolerate and are able to survive in moderate to high salinity environments, have been explored with promising results for wastewater treatment. Purple photosynthetic bacteria, a wide class of phototrophs, possess extraordinary metabolic versatility and include extremophiles that thrive in habitats having extreme pH, salinity, and light. The ability to grow under extreme environmental conditions of Rhodobacter (R.)sphaeroides, a purple non-sulfur proteobacteria that typically inhabits freshwater was evaluated. To investigate the response of R. sphaeroides to increased medium osmolarity under anerobic growth conditions, media with elevated osmotic strengths were attained by adding NaCl into the growing media at the desired concentrations in the range 0-2.5 M NaCl. Moreover, the pH effect on anaerobic growth was evaluated