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

Computer-Aided Imaging Analysis of Probe-Based Confocal Laser Endomicroscopy With Molecular Labeling and Gene Expression Identifies Markers of Response to Biological Therapy in IBD Patients: The Endo-Omics Study

Abstract Background We aimed to predict response to biologics in inflammatory bowel disease (IBD) using computerized image analysis of probe confocal laser endomicroscopy (pCLE) in vivo and assess the binding of fluorescent-labeled biologics ex vivo. Additionally, we investigated genes predictive of anti-tumor necrosis factor (TNF) response. Methods Twenty-nine patients (15 with Crohn’s disease [CD], 14 with ulcerative colitis [UC]) underwent colonoscopy with pCLE before and 12 to 14 weeks after starting anti-TNF or anti-integrin α4β7 therapy. Biopsies were taken for fluorescein isothiocyanate–labeled infliximab and vedolizumab staining and gene expression analysis. Computer-aided quantitative image analysis of pCLE was performed. Differentially expressed genes predictive of response were determined and validated in a public cohort. Results In vivo, vessel tortuosity, crypt morphology, and fluorescein leakage predicted response in UC (area under the receiver-operating characteristic curve [AUROC], 0.93; accuracy 85%, positive predictive value [PPV] 89%; negative predictive value [NPV] 75%) and CD (AUROC, 0.79; accuracy 80%; PPV 75%; NPV 83%) patients. Ex vivo, increased binding of labeled biologic at baseline predicted response in UC (UC) (AUROC, 83%; accuracy 77%; PPV 89%; NPV 50%) but not in Crohn’s disease (AUROC 58%). A total of 325 differentially expressed genes distinguished responders from nonresponders, 86 of which fell within the most enriched pathways. A panel including ACTN1, CXCL6, LAMA4, EMILIN1, CRIP2, CXCL13, and MAPKAPK2 showed good prediction of anti-TNF response (AUROC >0.7). Conclusions Higher mucosal binding of the drug target is associated with response to therapy in UC. In vivo, mucosal and microvascular changes detected by pCLE are associated with response to biologics in inflammatory bowel disease. Anti-TNF–responsive UC patients have a less inflamed and fibrotic state pretreatment. Chemotactic pathways involving CXCL6 or CXCL13 may be novel targets for therapy in nonresponders

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

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

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

Virus-Induced Silencing of a Sequence Coding for Loricrin-like Protein in Phytophthora infestans upon Infection of a Recombinant Vector Based on Tobacco Mosaic Virus

settingsOrder Article Reprints Open AccessFeature PaperArticle Virus-Induced Silencing of a Sequence Coding for Loricrin-like Protein in Phytophthora infestans upon Infection of a Recombinant Vector Based on Tobacco Mosaic Virus by Rossella Labarile 1,*ORCID,Annamaria Mincuzzi 2ORCID,Roberta Spanò 2ORCID andTiziana Mascia 2,*ORCID 1 National Research Council (CNR), Institute of Chemical-Physical Processes, Via Amendola 165/A, 70126 Bari, Italy 2 Department of Soil, Plant and Food Sciences, University of Bari “Aldo Moro”, Via Amendola 165/A, 70126 Bari, Italy * Authors to whom correspondence should be addressed. Horticulturae 2023, 9(3), 360; https://doi.org/10.3390/horticulturae9030360 Received: 29 January 2023 / Revised: 26 February 2023 / Accepted: 7 March 2023 / Published: 9 March 2023 (This article belongs to the Special Issue Gene Expressions in Response to Diseases, Abiotic Stresses and Pest Damage of Horticultural Products) Download Browse Figures Review Reports Versions Notes Abstract Phytophthora infestans is the oomycete responsible for late blight disease of Solanaceae that causes both yield and economic losses. With the aim of reducing plant wilt and high management costs mainly due to wide fungicide applications, alternative eco-sustainable control strategies are needed. RNA interference (RNAi) is a powerful tool for gene function studies that can be accomplished by constitutive transformation or transient expression such as virus-induced gene silencing (VIGS) experiments. VIGS makes use of viruses to deliver sequences homologous to a target gene fragment and trigger RNAi. Indeed, a P. infestans ortholog of plant loricrin-like protein (LLP), named PiLLP, has been silenced using the direct infection of a recombinant vector based on the plant virus tobacco mosaic virus (TMV-PiLLP-1056), aiming to reduce the oomycete sexual reproduction. For this purpose, the gene coding for the green fluorescent protein (GFP) present in the TMV-GFP-1056 vector has been replaced with an antisense construct obtained by fusion PCR of the PiLLP 5′-UTR and 3′-UTR sequences. Here, we show that RNAi can be expressed in the A1 mating type of P. infestans strain 96.9.5.1 by VIGS using the direct infection of TMV-PiLLP-1056. We provide evidence that the recombinant vector can enter, replicate, and persist in mycelia of P. infestans where it induces the partial downregulation of the PiLLP transcript. Compared with the wild-type, the PiLLP-silenced A1 mating type had slower colony growth and a diminished virulence in detached tomato leaflets. This seems to be the first evidence of a constitutive gene downregulation of P. infestans using a recombinant vector based on a plus-sense RNA plant virus

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

Biological control of olive anthracnose

Olive anthracnose, a fungal disease caused by species of the genus Colletotrichum, is responsible for severe yield losses and poor oil quality. Typical symptoms appear in autumn or early winter, when the drupes begin to ripen. Under favorable conditions, symptoms on branches and leaves can also occur, leading to chlorosis, severe defoliation, and death of woody organs. Symptomless infection of flowers and blights have also been reported. Latent fruit infections could play an important role as the inoculum source for the autumn-winter epidemics. Application of systemic fungicides has proved effective in field trials, and pre-flowering sprays contribute to reduce latent infection and the inoculum density for autumn infection. However, public concerns about potential risks on the environment and human health promoted the search for alternative and sustainable means. Therefore, the activity of a new sulfur-based product and biocontrol agents (Bacillus subtilis, and endophytic isolates of Aureobasidium pullulans) in reducing the incidence of olive anthracnose was evaluated under field conditions. The sulfur-based product and B. subtilis applied at the pre-flowering stage were as effective as the chemical fungicides in reducing the incidence of latent infections on drupes. Moreover, some endophytic strains of A. pullulans provided high protection levels against Colletotrichum spp. when applied at the pre-flowering and veraison stages. Overall, data indicated that olive anthracnose can be controlled by using biological means and new products could be considered for introduction in the list of the organic product specification

A novel route for anoxygenic polymerization of dopamine via purple photosynthetic bacteria metabolism

Dopamine is an efficient building block to produce a versatile coating polymer able to adhere on a vast repertoire of material surfaces. Polydopamine, a dark-bioinspired polymer, is produced by the self-assembly of the dopamine under aerobic conditions in an alkaline environment. The presence of oxygen is crucial for self-polymerization of dopamine in aqueous solution. In this manuscript we show that is possible to drive the polymerization in absence of oxygen exploiting the metabolism of anaerobic photosynthetic purple bacteria. Graphical Abstract: [Figure not available: see fulltext.