Kernel-Based Feature Selection Techniques for Transport Proteins Based on Star Graph Topological Indices

[Abstract] The transport of the molecules inside cells is a very important topic, especially in Drug Metabolism. The experimental testing of the new proteins for the transporter molecular function is expensive and inefficient due to the large amount of new peptides. Therefore, there is a need for cheap and fast theoretical models to predict the transporter proteins. In the current work, the primary structure of a protein is represented as a molecular Star graph, characterized by a series of topological indices. The dataset was made up of 2,503 protein chains, out of which 413 have transporter molecular function and 2,090 have no transporter function. These indices were used as input to several classification techniques to find the best Quantitative Structure Activity Relationship (QSAR) model that can evaluate the transporter function of a new protein chain. Among several feature selection techniques, the Support Vector Machine Recursive Feature Elimination allows us to obtain a classification model based on 20 attributes with a true positive rate of 83% and a false positive rate of 16.7%.Xunta de Galicia; 1OSIN105004P

Re-Identification of Rats with Transfer Learning

Cursos e Congresos , C-155[Abstract] The study of animal behavior in laboratory experiments is key in ethology, ecotoxicology, neuroscience and other fields. Although modern studies use computer imaging techniques, current solutions cannot preserve the identity of multiple individuals in social experiments. Thanks to the use of Transfer Learning we seek to overcome this limitations while maintaining the effectiveness of Deep Learning and reducing its computational times. With this technique we achieved promising results in the re-identification of rats after an occlusion processGrant PID2021-126289OA-I00 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europe. CITIC is funded by the Xunta de Galicia through the collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Galician University System (CIGUS

Improvement of Epitope Prediction Using Peptide Sequence Descriptors and Machine Learning

[Abstract] In this work, we improved a previous model used for the prediction of proteomes as new B-cell epitopes in vaccine design. The predicted epitope activity of a queried peptide is based on its sequence, a known reference epitope sequence under specific experimental conditions. The peptide sequences were transformed into molecular descriptors of sequence recurrence networks and were mixed under experimental conditions. The new models were generated using 709,100 instances of pair descriptors for query and reference peptide sequences. Using perturbations of the initial descriptors under sequence or assay conditions, 10 transformed features were used as inputs for seven Machine Learning methods. The best model was obtained with random forest classifiers with an Area Under the Receiver Operating Characteristics (AUROC) of 0.981 ± 0.0005 for the external validation series (five-fold cross-validation). The database included information about 83,683 peptides sequences, 1448 epitope organisms, 323 host organisms, 15 types of in vivo processes, 28 experimental techniques, and 505 adjuvant additives. The current model could improve the in silico predictions of epitopes for vaccine design. The script and results are available as a free repositor

Improving Enzyme Regulatory Protein Classification by Means of SVM-RFE Feature Selection

[Abstract] Enzyme regulation proteins are very important due to their involvement in many biological processes that sustain life. The complexity of these proteins, the impossibility of identifying direct quantification molecular properties associated with the regulation of enzymatic activities, and their structural diversity creates the necessity for new theoretical methods that can predict the enzyme regulatory function of new proteins. The current work presents the first classification model that predicts protein enzyme regulators using the Markov mean properties. These protein descriptors encode the topological information of the amino acid into contact networks based on amino acid distances and physicochemical properties. MInD-Prot software calculated these molecular descriptors for 2415 protein chains (350 enzyme regulators) using five atom physicochemical properties (Mulliken electronegativity, Kang–Jhon polarizability, vdW area, atom contribution to P) and the protein 3D regions. The best classification models to predict enzyme regulators have been obtained with machine learning algorithms from Weka using 18 features. K* has been demonstrated to be the most accurate algorithm for this protein function classification. Wrapper Subset Evaluator and SVM-RFE approaches were used to perform a feature subset selection with the best results obtained from SVM-RFE. Classification performance employing all the available features can be reached using only the 8 most relevant features selected by SVM-RFE. Thus, the current work has demonstrated the possibility of predicting new molecular targets involved in enzyme regulation using fast theoretical algorithms.Galicia. Consellería de Economía e Industria, 10SIN105004PRInstituto de Salud Carlos III , PI13/0028

LECTINPred: web server that uses complex networks of protein structure for prediction of lectins with potential use as cancer biomarkers or in parasite vaccine design

Ministerio de Ciencia e Innovación; AGL2010-22290-C03-01Ministerio de Ciencia e Innovación; AGL2011-30563-C03-0

Severe infections and infection-related mortality in a large series of haploidentical hematopoietic stem cell transplantation with post-transplant cyclophosphamide

Severe infections and their attributable mortality are major complications in recipients of allogeneic hematopoietic stem cell transplantation (alloSCT). We herein report 236 adult patients who received haploSCT with PTCy. The median follow-up for survivors was 37 months. The overall incidence of bloodstream infections by gram-positive and gram-negative bacteria at 37 months was 51% and 46%, respectively. The incidence of cytomegalovirus infection was 69%, while Epstein Barr virus infections occurred in 10% of patients and hemorrhagic cystitis in 35% of cases. Invasive fungal infections occurred in 11% at 17 months. The 3-year incidence of infection-related mortality was 19%. The median interval from transplant to IRM was 3 months (range 1-30), 53% of IRM occurred >100 days post-haploSCT. Risk factors for IRM included age >50 years, lymphoid malignancy, and developing grade III-IV acute GvHD. Bacterial infections were the most common causes of IRM (51%), mainly due to gram-negative bacilli BSI. In conclusion, severe infections are the most common causes of NRM after haploSCT with PTCy, with a reemergence of gram-negative bacilli as the most lethal pathogens. More studies focusing on the severe infections after haploSCT with PTCy and differences with other types of alloSCT in adults are clearly warranted

Patient satisfaction and outcomes of crisis resolution home treatment for the management of acute psychiatric crises: a study during the COVID-19 pandemic in Madrid

BackgroundCrisis Resolution Home Treatment (CRHT) seem to offer comparable results to the traditional hospitalization model, at a lower cost and offering greater flexibility and scope. However, in Madrid, its implementation in Mental Health did not occur until the midst of the COVID-19 pandemic. In this work we analysed the effectiveness of a mental health CRHT unit promoted during the COVID-19 pandemic, as well as the degree of satisfaction of patients and their families.Methods90 patients were treated by the CRHT unit in the period between October 2020 and June 2022. All patients met the inclusion criteria: (1) Acute psychopathological decompensation in patients suffering from psychotic disorders, major affective disorder, obsessive compulsive disorder, personality disorder and other severe mental disorders causing functional disability, according to ICD-10 diagnostic criteria; (2) Ages between 18–90 years old; (3) Living in the urban area of Vallecas, Madrid; and (4) Counting with sufficient social and family support. The effectiveness of the intervention was evaluated with the SF-36 health questionnaire, the caregiver burden with the Zarit questionnaire, and patient satisfaction with a survey specifically designed for this work.Results55 (61.1%) patients completed the SF-36 at baseline and at the end of hospitalization. Statistically significant improvements were observed in the 8 dimensions of the SF-36 (p < 0.05). However, CRHT did not achieve a statistically significant decrease in caregiver burden. Regarding the satisfaction of the patients with the attention and care received, an average score of 47.72/50 was obtained.ConclusionThe Crisis Resolution Home Treatment intervention resulted in significant improvement in patients’ quality of life with high satisfaction scores. However, it did not effectively reduce caregiver burden. Future research should focus on randomized controlled trials with long-term follow-up to assess the effectiveness of CRHT compared to traditional hospitalization and utilize specific assessment scales for different mental disorders

Allogeneic Stem Cell Transplantation in Mature T Cell and Natural Killer/T Neoplasias: A Registry Study from Spanish GETH/GELTAMO Centers

Despite advances in understanding the biology of mature T and natural killer (NK)/T cell neoplasia, current therapies, even the most innovative ones, are still far from ensuring its cure. The only treatment to date that has been shown to control aggressive T cell neoplasms in the long term is allogeneic stem cell transplantation (alloSCT). We aim to report the results of alloSCT for advanced mature T and NK/T neoplasias performed in centers from our national GELTAMO/GETH (Grupo Español de Linfoma y Trasplante de Médula Ósea/Grupo Español de Trasplante Hematopoyético y Terapia Celular) over the past 25 years. As a secondary objective, we analyzed the results of alloSCT from haploidentical donors. We performed a retrospective analysis of all patients who received an alloSCT in Spanish centers (n = 201) from September 1995 to August 2018. The 2-year overall survival (OS) and disease-free survival (DFS) were 65.5% and 58.2%, respectively. The univariate for OS and DFS showed statistically different hazard ratios for conditioning intensity, response pre-alloSCT, comorbidity index, donor/receptor cytomegalovirus status and Eastern Cooperative Oncology Group (ECOG) pre-alloSCT, but only a better ECOG pre-alloSCT remained significant in the multivariate analysis. There was an increased incidence of relapse in those patients who did not develop chronic graft-versus-host disease (GVHD) and an increased risk of death in those developing moderate to severe acute GVHD. The 1-year nonrelapse mortality was 21.9% and was mainly due to GVHD (30%) and bacterial infections (17%). When comparing unrelated donors with haploidentical donors, we found similar results in terms of OS and DFS. There was, however, a reduction of acute GVHD in the haploidentical group (P = .04) and trend to a reduction of chronic GVHD. In conclusion, alloSCT is the only curative option for most aggressive T cell neoplasias. Haploidentical donors offer similar results to related donors in terms of survival with a reduction of acute GVHD

Allogeneic stem cell transplantation as a curative option in relapse/refractory diffuse large B cell lymphoma: Spanish multicenter GETH/GELTAMO study

Grupo Español de Trasplante Hematopoyético (GETH) and Grupo Español de Linfoma y Trasplante Autólogo (GELTAMO).We performed a retrospective multicenter study including 140 patients with relapsed/refractory (R/R) diffuse large B cell lymphoma (DLBCL) who underwent allogeneic hematopoietic stem cell transplantation (allo-SCT) from March 1995 to November 2018. Our objective was to analyze long term outcomes. Seventy-four percent had received a previous auto-SCT (ASCT) and the median number of lines pre-allo-SCT was 3 (range 1–9). Three year-event free survival (EFS) and overall survival (OS) were 38% and 44%, respectively. Non-relapse mortality (NRM) at day 100 was 19%. Cumulative incidence of grade III–IV acute graft versus host disease (GVHD) at day 100 was 16% and moderate/severe chronic GVHD at 3 years 34%. Active disease at allo-SCT (HR 1.95, p = 0.039) (HR 2.19, p = 0.019), HCT-CI ≥ 2 (2.45, p = 0.002) (HR 2.33, p = 0.006) and donor age >37 years (HR 2.75, p = 0.014) (HR 1.98, p = 0.043) were the only independent variables both for PFS and OS, respectively. NRM was significantly modified by HCT-CI ≥ 2 (HR 4.8, p = 0.008), previous ASCT (HR 4.4, p = 0.048) and grade III–IV acute GVHD on day 100 (HR 6.13, p = 0.016). Our data confirmed that allo-SCT is a curative option for patients with R/R DLBCL, displaying adequate results for fit patients with chemosensitive disease receiving an allo-SCT from a young donor