AntVideoRecord: Autonomous system to capture the locomotor activity of leafcutter ants

The leafcutter ants (LCA) are considered plague in a great part of the American continent, causing great damage in production fields. Knowing the locomotion and foraging rhythm in LCA on a continuous basis would imply a significant advance for ecological studies, fundamentally of animal behavior. However, studying the forage rhythm of LCA in the field involves a significant human effort. This also adds a risk of subjective results due to the operator fatigue. In this work a new development named ‘AntVideoRecord’ is proposed to address this issue. This device is a low-cost autonomous system that records videos of the LCA path in a fixed position. The device can be easily reproduced using the freely accessible source code provided. The evaluation of this novel device was successful because it has exceeded all the basic requirements in the field: record continuously for at least seven days, withstand high and low temperatures, capture acceptable videos during the day and night, and have a simple configuration protocol by mobile devices and laptops. It was possible to confirm the correct operation of the device, being able to record more than 1900 h in the field at different climate conditions and times of the day. 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CCANII: FMV 15605

AntVideoRecord: Autonomous system to capture the locomotor activity of leafcutter ants

The leafcutter ants (LCA) are considered plague in a great part of the American continent, causing great damage in production fields. Knowing the locomotion and foraging rhythm in LCA on a continuous basis would imply a significant advance for ecological studies, fundamentally of animal behavior. However, studying the forage rhythm of LCA in the field involves a significant human effort. This also adds a risk of subjective results due to the operator fatigue. In this work a new development named ‘AntVideoRecord’ is proposed to address this issue. This device is a low-cost autonomous system that records videos of the LCA path in a fixed position. The device can be easily reproduced using the freely accessible source code provided. The evaluation of this novel device was successful because it has exceeded all the basic requirements in the field: record continuously for at least seven days, withstand high and low temperatures, capture acceptable videos during the day and night, and have a simple configuration protocol by mobile devices and laptops. It was possible to confirm the correct operation of the device, being able to record more than 1900 h in the field at different climate conditions and times of the day.Fil: Sabattini, Julian Alberto. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Reta, Juan Manuel. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Bugnon, Leandro Ariel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; ArgentinaFil: Cerrudo, Juan Ignacio. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Sabattini, Rafael Alberto. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Peñalva, Albano. Universidad Nacional de Entre Ríos. Facultad de Ciencias Agropecuarias; ArgentinaFil: Bollazzi, Martín. Universidad de la República; UruguayFil: Paz, Martin Omar. No especifíca;Fil: Sturniolo, F.. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentin

Mongersen, an oral SMAD7 antisense oligonucleotide, and crohn's disease

Background Crohn's disease-related inflammation is characterized by reduced activity of the immunosuppressive cytokine transforming growth factor β1 (TGF-β1) due to high levels of SMAD7, an inhibitor of TGF-β1 signaling. Preclinical studies and a phase 1 study have shown that an oral SMAD7 antisense oligonucleotide, mongersen, targets ileal and colonic SMAD7. Methods In a double-blind, placebo-controlled, phase 2 trial, we evaluated the efficacy of mongersen for the treatment of persons with active Crohn's disease. Patients were randomly assigned to receive 10, 40, or 160 mg of mongersen or placebo per day for 2 weeks. The primary outcomes were clinical remission at day 15, defined as a Crohn's Disease Activity Index (CDAI) score of less than 150, with maintenance of remission for at least 2 weeks, and the safety of mongersen treatment. A secondary outcome was clinical response (defined as a reduction of 100 points or more in the CDAI score) at day 28. Results The proportions of patients who reached the primary end point were 55% and 65% for the 40-mg and 160-mg mongersen groups, respectively, as compared with 10% for the placebo group (P<0.001). There was no significant difference in the percentage of participants reaching clinical remission between the 10-mg group (12%) and the placebo group. The rate of clinical response was significantly greater among patients receiving 10 mg (37%), 40 mg (58%), or 160 mg (72%) of mongersen than among those receiving placebo (17%) (P = 0.04, P<0.001, and P<0.001, respectively). Most adverse events were related to complications and symptoms of Crohn's disease. Conclusions We found that study participants with Crohn's disease who received mongersen had significantly higher rates of remission and clinical response than those who received placebo

Physicians’ misperceived cardiovascular risk and therapeutic inertia as determinants of low LDL-cholesterol targets achievement in diabetes

Background: Greater efforts are needed to overcome the worldwide reported low achievement of LDL-c targets. This survey aimed to dissect whether and how the physician-based evaluation of patients with diabetes is associated with the achievement of LDL-c targets. Methods: This cross-sectional self-reported survey interviewed physicians working in 67 outpatient services in Italy, collecting records on 2844 patients with diabetes. Each physician reported a median of 47 records (IQR 42–49) and, for each of them, the physician specified its perceived cardiovascular risk, LDL-c targets, and the suggested refinement in lipid-lowering-treatment (LLT). These physician-based evaluations were then compared to recommendations from EAS/EASD guidelines. Results: Collected records were mostly from patients with type 2 diabetes (94%), at very-high (72%) or high-cardiovascular risk (27%). Physician-based assessments of cardiovascular risk and of LDL-c targets, as compared to guidelines recommendation, were misclassified in 34.7% of the records. The misperceived assessment was significantly higher among females and those on primary prevention and was associated with 67% lower odds of achieving guidelines-recommended LDL-c targets (OR 0.33, p &lt; 0.0001). Peripheral artery disease, target organ damage and LLT-initiated by primary-care-physicians were all factors associated with therapeutic-inertia (i.e., lower than expected probability of receiving high-intensity LLT). Physician-suggested LLT refinement was inadequate in 24% of overall records and increased to 38% among subjects on primary prevention and with misclassified cardiovascular risk. Conclusions: This survey highlights the need to improve the physicians’ misperceived cardiovascular risk and therapeutic inertia in patients with diabetes to successfully implement guidelines recommendations into everyday clinical practice

NetCTLpan: pan-specific MHC class I pathway epitope predictions

Reliable predictions of immunogenic peptides are essential in rational vaccine design and can minimize the experimental effort needed to identify epitopes. In this work, we describe a pan-specific major histocompatibility complex (MHC) class I epitope predictor, NetCTLpan. The method integrates predictions of proteasomal cleavage, transporter associated with antigen processing (TAP) transport efficiency, and MHC class I binding affinity into a MHC class I pathway likelihood score and is an improved and extended version of NetCTL. The NetCTLpan method performs predictions for all MHC class I molecules with known protein sequence and allows predictions for 8-, 9-, 10-, and 11-mer peptides. In order to meet the need for a low false positive rate, the method is optimized to achieve high specificity. The method was trained and validated on large datasets of experimentally identified MHC class I ligands and cytotoxic T lymphocyte (CTL) epitopes. It has been reported that MHC molecules are differentially dependent on TAP transport and proteasomal cleavage. Here, we did not find any consistent signs of such MHC dependencies, and the NetCTLpan method is implemented with fixed weights for proteasomal cleavage and TAP transport for all MHC molecules. The predictive performance of the NetCTLpan method was shown to outperform other state-of-the-art CTL epitope prediction methods. Our results further confirm the importance of using full-type human leukocyte antigen restriction information when identifying MHC class I epitopes. Using the NetCTLpan method, the experimental effort to identify 90% of new epitopes can be reduced by 15% and 40%, respectively, when compared to the NetMHCpan and NetCTL methods. The method and benchmark datasets are available at http://www.cbs.dtu.dk/services/NetCTLpan/

Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan

CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions

A novel transport mechanism for MOMP in Chlamydophila pneumoniae and its putative role in immune-therapy

Major outer membrane proteins (MOMPs) of Gram negative bacteria are one of the most intensively studied membrane proteins. MOMPs are essential for maintaining the structural integrity of bacterial outer membranes and in adaptation of parasites to their hosts. There is evidence to suggest a role for purified MOMP from Chlamydophila pneumoniae and corresponding MOMP-derived peptides in immune-modulation, leading to a reduced atherosclerotic phenotype in apoE−/− mice via a characteristic dampening of MHC class II activity. The work reported herein tests this hypothesis by employing a combination of homology modelling and docking to examine the detailed molecular interactions that may be responsible. A three-dimensional homology model of the C. pneumoniae MOMP was constructed based on the 14 transmembrane β-barrel crystal structure of the fatty acid transporter from Escherichia coli, which provides a plausible transport mechanism for MOMP. Ligand docking experiments were used to provide details of the possible molecular interactions driving the binding of MOMP-derived peptides to MHC class II alleles known to be strongly associated with inflammation. The docking experiments were corroborated by predictions from conventional immuno-informatic algorithms. This work supports further the use of MOMP in C. pneumoniae as a possible vaccine target and the role of MOMP-derived peptides as vaccine candidates for immune-therapy in chronic inflammation that can result in cardiovascular events

Limitations of Ab Initio Predictions of Peptide Binding to MHC Class II Molecules

Successful predictions of peptide MHC binding typically require a large set of binding data for the specific MHC molecule that is examined. Structure based prediction methods promise to circumvent this requirement by evaluating the physical contacts a peptide can make with an MHC molecule based on the highly conserved 3D structure of peptide:MHC complexes. While several such methods have been described before, most are not publicly available and have not been independently tested for their performance. We here implemented and evaluated three prediction methods for MHC class II molecules: statistical potentials derived from the analysis of known protein structures; energetic evaluation of different peptide snapshots in a molecular dynamics simulation; and direct analysis of contacts made in known 3D structures of peptide:MHC complexes. These methods are ab initio in that they require structural data of the MHC molecule examined, but no specific peptide:MHC binding data. Moreover, these methods retain the ability to make predictions in a sufficiently short time scale to be useful in a real world application, such as screening a whole proteome for candidate binding peptides. A rigorous evaluation of each methods prediction performance showed that these are significantly better than random, but still substantially lower than the best performing sequence based class II prediction methods available. While the approaches presented here were developed independently, we have chosen to present our results together in order to support the notion that generating structure based predictions of peptide:MHC binding without using binding data is unlikely to give satisfactory results