The 2024 Nucleic Acids Research database issue and the online molecular biology database collection.

The 2024 Nucleic Acids Research database issue contains 180 papers from across biology and neighbouring disciplines. There are 90 papers reporting on new databases and 83 updates from resources previously published in the Issue. Updates from databases most recently published elsewhere account for a further seven. Nucleic acid databases include the new NAKB for structural information and updates from Genbank, ENA, GEO, Tarbase and JASPAR. The Issue's Breakthrough Article concerns NMPFamsDB for novel prokaryotic protein families and the AlphaFold Protein Structure Database has an important update. Metabolism is covered by updates from Reactome, Wikipathways and Metabolights. Microbes are covered by RefSeq, UNITE, SPIRE and P10K; viruses by ViralZone and PhageScope. Medically-oriented databases include the familiar COSMIC, Drugbank and TTD. Genomics-related resources include Ensembl, UCSC Genome Browser and Monarch. New arrivals cover plant imaging (OPIA and PlantPAD) and crop plants (SoyMD, TCOD and CropGS-Hub). The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Over the last year the NAR online Molecular Biology Database Collection has been updated, reviewing 1060 entries, adding 97 new resources and eliminating 388 discontinued URLs bringing the current total to 1959 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

Days spent on non-invasive ventilation support: can it determine when to initiate VV- ECMO? Observational study in a cohort of Covid-19 patients.

BACKGROUND: The study evaluates the impact of the time between commencing non-invasive ventilation (NIV) support and initiation of venovenous extracorporeal membrane oxygenation (VV-ECMO) in a cohort of critically ill patients with coronavirus disease 2019 (COVID-19) associated acute respiratory distress syndrome (ARDS). METHODS: Prospective observational study design in an intensive Care Unit (ICU) of a tertiary hospital in Barcelona (Spain). All patients requiring VV-ECMO support due to COVID-19 associated ARDS between March 2020 and January 2022 were analysed. Survival outcome was determined at 90 days after VV-ECMO initiation. Demographic data, comorbidities at ICU admission, RESP (respiratory ECMO survival prediction) score, antiviral and immunomodulatory treatments received, inflammatory biomarkers, the need for vasopressors, the thromboprophylaxis regimen received, and respiratory parameters including the length of intubation previous to ECMO and the length of each NIV support (high-flow nasal cannula, continuous positive airway pressure and bi-level positive airway pressure), were also collated in order to assess risk factors for day-90 mortality. The effect of the time lapse between NIV support and VV-ECMO on survival was evaluated using logistic regression and adjusting the association with all factors that were significant in the univariate analysis. RESULTS: Seventy-two patients finally received VV-ECMO support. At 90 days after commencing VV-ECMO 35 patients (48%) had died and 37 patients (52%) were alive. Multivariable analysis showed that at VV-ECMO initiation, age (p = 0.02), lactate (p = 0.001), and days from initiation of NIV support to starting VV-ECMO (p = 0.04) were all associated with day-90 mortality. CONCLUSIONS: In our small cohort of VV-ECMO patients with COVID-19 associated ARDS, the time spent between initiation of NIV support and VV-ECMO (together with age and lactate) appeared to be a better predictor of mortality than the time between intubation and VV-ECMO.

Exploring the associations between early maladaptive schemas and impulsive and compulsive buying tendencies.

The main purpose of this preliminary study was to investigate a potential relationship between early maladaptive schemas (EMSs) and impulsive and compulsive buying tendencies in a sample of young adults (college students). This research adds to the cognitive perspective of consumer behavior that the cognitive schemas putatively associated with early experiences may have a strong impact on impulsive and compulsive buying. Data was obtained from 365 participants in a cross-sectional study design. Participants completed an online survey with the following instruments: Young Schema Questionnaire; Impulsive Buying Tendency Measurement Scale; Richmond Compulsive Buying Scale; and Hospital Anxiety and Depression Scale. Using multiple linear hierarchical regressions, we confirmed that the domain of over vigilance and inhibition schemas was positively associated with impulsive and compulsive buying tendencies, while an opposite association was found for the domain of impaired limits. Being a female was also a predictor of impulsive buying and compulsive buying. The results were discussed in terms of the coping mechanisms to deal with negative emotions, as a way to obtain rewards, or as a way to escape painful self-awareness. Other mechanisms related to the internalization of perfectionist expectations and the propensity to shame were also explored.

Predictive Factors of Piperacillin Exposure and the Impact on Target Attainment after Continuous Infusion Administration to Critically Ill Patients.

Critically ill patients undergo significant pathophysiological changes that affect antibiotic pharmacokinetics. Piperacillin/tazobactam administered by continuous infusion (CI) improves pharmacokinetic/pharmacodynamic (PK/PD) target attainment. This study aimed to characterize piperacillin PK after CI administration of piperacillin/tazobactam in critically ill adult patients with preserved renal function and to determine the empirical optimal dosing regimen. A total of 218 piperacillin concentrations from 106 patients were simultaneously analyzed through the population PK approach. A two-compartment linear model best described the data. Creatinine clearance (CLCR) estimated by CKD-EPI was the covariate, the most predictive factor of piperacillin clearance (CL) interindividual variability. The mean (relative standard error) parameter estimates for the final model were: CL: 12.0 L/h (6.03%); central and peripheral compartment distribution volumes: 20.7 L (8.94%) and 62.4 L (50.80%), respectively; intercompartmental clearance: 4.8 L/h (26.4%). For the PK/PD target of 100% fT>1×MIC, 12 g of piperacillin provide a probability of target attainment > 90% for MIC < 16 mg/L, regardless of CLCR, but higher doses are needed for MIC = 16 mg/L when CLCR > 100 mL/min. For 100% fT>4×MIC, the highest dose (24 g/24 h) was not sufficient to ensure adequate exposure, except for MICs of 1 and 4 mg/L. Our model can be used as a support tool for initial dose guidance and during therapeutic drug monitoring.

Sepsis-associated acute kidney injury: consensus report of the 28th Acute Disease Quality Initiative workgroup.

Sepsis-associated acute kidney injury (SA-AKI) is common in critically ill patients and is strongly associated with adverse outcomes, including an increased risk of chronic kidney disease, cardiovascular events and death. The pathophysiology of SA-AKI remains elusive, although microcirculatory dysfunction, cellular metabolic reprogramming and dysregulated inflammatory responses have been implicated in preclinical studies. SA-AKI is best defined as the occurrence of AKI within 7 days of sepsis onset (diagnosed according to Kidney Disease Improving Global Outcome criteria and Sepsis 3 criteria, respectively). Improving outcomes in SA-AKI is challenging, as patients can present with either clinical or subclinical AKI. Early identification of patients at risk of AKI, or at risk of progressing to severe and/or persistent AKI, is crucial to the timely initiation of adequate supportive measures, including limiting further insults to the kidney. Accordingly, the discovery of biomarkers associated with AKI that can aid in early diagnosis is an area of intensive investigation. Additionally, high-quality evidence on best-practice care of patients with AKI, sepsis and SA-AKI has continued to accrue. Although specific therapeutic options are limited, several clinical trials have evaluated the use of care bundles and extracorporeal techniques as potential therapeutic approaches. Here we provide graded recommendations for managing SA-AKI and highlight priorities for future research.

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection.

The 2023 Nucleic Acids Research Database Issue contains 178 papers ranging across biology and related fields. There are 90 papers reporting on new databases and 82 updates from resources previously published in the Issue. Six more papers are updates from databases most recently published elsewhere. Major nucleic acid databases reporting updates include Genbank, ENA, ChIPBase, JASPAR, mirDIP and the Issue's first Breakthrough Article, NACDDB for Circular Dichroism data. Updates from BMRB and RCSB cover experimental protein structural data while AlphaFold 2 computational structure predictions feature widely. STRING and REBASE are stand-out updates in the signalling and enzymes section. Immunology-related databases include CEDAR, the second Breakthrough Article, for cancer epitopes and receptors alongside returning IPD-IMGT/HLA and the new PGG.MHC. Genomics-related resources include Ensembl, GWAS Central and UCSC Genome Browser. Major returning databases for drugs and their targets include Open Targets, DrugCentral, CTD and Pubchem. The EMPIAR image archive appears in the Issue for the first time. The entire database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, revisiting 463 entries, adding 92 new resources and eliminating 96 discontinued URLs so bringing the current total to 1764 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

Outcomes of COVID-19 Patients Admitted to the Intermediate Respiratory Care Unit: Non-Invasive Respiratory Therapy in a Sequential Protocol.

The intermediate respiratory care units (IRCUs) have a pivotal role managing escalation and de-escalation between the general wards and the intensive care units (ICUs). Since the COVID-19 pandemic began, the early detection of patients that could improve on non-invasive respiratory therapies (NRTs) in IRCUs without invasive approaches is crucial to ensure proper medical management and optimize limiting ICU resources. The aim of this study was to assess factors associated with survival, ICU admission and intubation likelihood in COVID-19 patients admitted to IRCUs. Observational retrospective study in consecutive patients admitted to the IRCU of a tertiary hospital from March 2020 to April 2021. Inclusion criteria: hypoxemic respiratory failure (SpO2 ≤ 94% and/or respiratory rate ≥ 25 rpm with FiO2 > 50% supplementary oxygen) due to acute COVID-19 infection. Demographic, comorbidities, clinical and analytical data, and medical and NRT data were collected at IRCU admission. Multivariate logistic regression models assessed factors associated with survival, ICU admission, and intubation. From 679 patients, 79 patients (12%) had an order to not do intubation. From the remaining 600 (88%), 81% survived, 41% needed ICU admission and 37% required intubation. In the IRCU, 51% required non-invasive ventilation (NIV group) and 49% did not (non-NIV group). Older age and lack of corticosteroid treatment were associated with higher mortality and intubation risk in the scheme, which could be more beneficial in severe forms. Initial NIV does not always mean worse outcomes.

Multimodal Prediction of Five-Year Breast Cancer Recurrence in Women Who Receive Neoadjuvant Chemotherapy.

In current clinical practice, it is difficult to predict whether a patient receiving neoadjuvant chemotherapy (NAC) for breast cancer is likely to encounter recurrence after treatment and have the cancer recur locally in the breast or in other areas of the body. We explore the use of clinical history, immunohistochemical markers, and multiparametric magnetic resonance imaging (DCE, ADC, Dixon) to predict the risk of post-treatment recurrence within five years. We performed a retrospective study on a cohort of 1738 patients from Institut Curie and analyzed the data using classical machine learning, image processing, and deep learning. Our results demonstrate the ability to predict recurrence prior to NAC treatment initiation using each modality alone, and the possible improvement achieved by combining the modalities. When evaluated on holdout data, the multimodal model achieved an AUC of 0.75 (CI: 0.70, 0.80) and 0.57 specificity at 0.90 sensitivity. We then stratified the data based on known prognostic biomarkers. We found that our models can provide accurate recurrence predictions (AUC > 0.89) for specific groups of women under 50 years old with poor prognoses. A version of our method won second place at the BMMR2 Challenge, with a very small margin from being first, and was a standout from the other challenge entries.

The 2022 Nucleic Acids Research database issue and the online molecular biology database collection.

The 2022 Nucleic Acids Research Database Issue contains 185 papers, including 87 papers reporting on new databases and 85 updates from resources previously published in the Issue. Thirteen additional manuscripts provide updates on databases most recently published elsewhere. Seven new databases focus specifically on COVID-19 and SARS-CoV-2, including SCoV2-MD, the first of the Issue's Breakthrough Articles. Major nucleic acid databases reporting updates include MODOMICS, JASPAR and miRTarBase. The AlphaFold Protein Structure Database, described in the second Breakthrough Article, is the stand-out in the protein section, where the Human Proteoform Atlas and GproteinDb are other notable new arrivals. Updates from DisProt, FuzDB and ELM comprehensively cover disordered proteins. Under the metabolism and signalling section Reactome, ConsensusPathDB, HMDB and CAZy are major returning resources. In microbial and viral genomes taxonomy and systematics are well covered by LPSN, TYGS and GTDB. Genomics resources include Ensembl, Ensembl Genomes and UCSC Genome Browser. Major returning pharmacology resource names include the IUPHAR/BPS guide and the Therapeutic Target Database. New plant databases include PlantGSAD for gene lists and qPTMplants for post-translational modifications. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). Our latest update to the NAR online Molecular Biology Database Collection brings the total number of entries to 1645. Following last year's major cleanup, we have updated 317 entries, listing 89 new resources and trimming 80 discontinued URLs. The current release is available at http://www.oxfordjournals.org/nar/database/c/.

Troubling Secondary Victimization of Bullying Victims: The Role of Gender and Ethnicity.

Bullying is a severe public health problem, and bystanders' reactions are a key variable in its perpetration and maintenance. This study aimed to assess the level of secondary victimization of bullying victims as a function of the student's sex and the victim's category (nonnormative vs. normative) in three experimental conditions (feminine, masculine, and ethnicity) from a socioecological perspective. Specifically, two dimensions of secondary victimization were evaluated: avoidance and devaluation/blaming of the victim. A sequence of mixed-design ANOVAs was performed with a sample of 553 Spanish (53.3%) and Portuguese (46.7%) students, aged between 14 and 19 years. Results show that nonnormative victims, those who transgress feminine and masculine gender stereotypes, and those who belong to a minority ethnic group (gypsies) are avoided more than normative victims; and that boys perpetrate more secondary victimization than girls. These results reveal the situation of vulnerability suffered by adolescents who transgress the gender norm as well as those who belong to minority ethnic groups, and highlight that the motivations concealed by the secondary victimization of bullying victims originate in the group processes of identity construction and categorization that configure the boundaries of "legitimacy" and are strongly influenced by social beliefs about normative and nonnormative identities. This socioecological approach could guide prevention strategies, so generic antibullying policies that do not explicitly address biases about gender, sexual, and cultural identity can be overcome to reduce the high levels of stigma occurring in the schools through critical and culturally responsive pedagogy.

Socio-Educational Support Deficits in the Emancipation of Protected Youth in Spain.

Background: The process of transition to adult life of youth with a record of protection is crucial to overcome the difficulties to achieve an independent life. Objective: This research aims to analyze the conditions under which protected youth are emancipated, as well as the factors that facilitate emancipation. Method: A qualitative study was performed with three samples: longitudinal follow-ups with youths when they exit the system and during 12 months (N = 24); life stories of youths who have exited the child welfare system at least 2 years ago and a maximum of 5 years ago (N = 22); interviews with professionals conducting their intervention in adolescent protection resources (N = 18). Results: The results indicate that protective action is not enabling youths' learning in normalized contexts, which negatively affects the conditions under which emancipation occurs. The experience of the protective action conditions the tendency to benefit from the post-majority socio-educational accompaniment. Conclusions: The importance of socio-educational intervention continuing during the first moments of emancipation, providing professional accompaniment to the entire collective, is highlighted.

Individual outcome prediction models for patients with COVID-19 based on their first day of admission to the intensive care unit.

BACKGROUND: Currently, good prognosis and management of critically ill patients with COVID-19 are crucial for developing disease management guidelines and providing a viable healthcare system. We aimed to propose individual outcome prediction models based on binary logistic regression (BLR) and artificial neural network (ANN) analyses of data collected in the first 24 h of intensive care unit (ICU) admission for patients with COVID-19 infection. We also analysed different variables for ICU patients who survived and those who died. METHODS: Data from 326 critically ill patients with COVID-19 were collected. Data were captured on laboratory variables, demographics, comorbidities, symptoms and hospital stay related information. These data were compared with patient outcomes (survivor and non-survivor patients). BLR was assessed using the Wald Forward Stepwise method, and the ANN model was constructed using multilayer perceptron architecture. RESULTS: The area under the receiver operating characteristic curve of the ANN model was significantly larger than the BLR model (0.917 vs 0.810; p < 0.001) for predicting individual outcomes. In addition, ANN model presented similar negative predictive value than the BLR model (95.9% vs 94.8%). Variables such as age, pH, potassium ion, partial pressure of oxygen, and chloride were present in both models and they were significant predictors of death in COVID-19 patients. CONCLUSIONS: Our study could provide helpful information for other hospitals to develop their own individual outcome prediction models based, mainly, on laboratory variables. Furthermore, it offers valuable information on which variables could predict a fatal outcome for ICU patients with COVID-19.

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium.

BACKGROUND: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular -omics data from clinical data warehouses and biobanks. METHODS: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. RESULTS: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. CONCLUSIONS: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care.

Pre-existing Autoantibodies Neutralizing High Concentrations of Type I Interferons in Almost 10% of COVID-19 Patients Admitted to Intensive Care in Barcelona.

BACKGROUND: It is important to predict which patients infected by SARS-CoV-2 are at higher risk of life-threatening COVID-19. Several studies suggest that neutralizing auto-antibodies (auto-Abs) against type I interferons (IFNs) are predictive of critical COVID-19 pneumonia. OBJECTIVES: We aimed to test for auto-Abs to type I IFN and describe the main characteristics of COVID-19 patients admitted to intensive care depending on whether or not these auto-Abs are present. METHODS: Retrospective analysis of all COVID-19 patients admitted to an intensive care unit (ICU) in whom samples were available, from March 2020 to March 2021, in Barcelona, Spain. RESULTS: A total of 275 (70.5%) out of 390 patients admitted to ICU were tested for type I IFNs auto-antibodies (α2 and/or ω) by ELISA, being positive in 49 (17.8%) of them. Blocking activity of plasma diluted 1/10 for high concentrations (10 ng/mL) of IFNs was proven in 26 (9.5%) patients. Almost all the patients with neutralizing auto-Abs were men (92.3%). ICU patients with positive results for neutralizing IFNs auto-Abs did not show relevant differences in demographic, comorbidities, clinical features, and mortality, when compared with those with negative results. Nevertheless, some laboratory tests (leukocytosis, neutrophilia, thrombocytosis) related with COVID-19 severity, as well as acute kidney injury (17 [65.4%] vs. 100 [40.2%]; p = 0.013) were significantly higher in patients with auto-Abs. CONCLUSION: Auto-Abs neutralizing high concentrations of type I IFNs were found in 9.5% of patients admitted to the ICU for COVID-19 pneumonia in a hospital in Barcelona. These auto-Abs should be tested early upon diagnosis of SARS-CoV-2 infection, as they account for a significant proportion of life-threatening cases.

Continuous Infusion of Piperacillin/Tazobactam and Meropenem in ICU Patients Without Renal Dysfunction: Are Patients at Risk of Underexposure?

BACKGROUND AND OBJECTIVES: Morbidity and mortality from serious infections are common in intensive care units (ICUs). The appropriateness of the antibiotic treatment is essential to combat sepsis. We aimed to evaluate pharmacokinetic/pharmacodynamic target attainment of meropenem and piperacillin/tazobactam administered at standard total daily dose as continuous infusion in critically ill patients without renal dysfunction and to identify risk factors of non-pharmacokinetic/pharmacodynamic target attainment. RESULTS: We included 118 patients (149 concentrations), 47% had microorganism isolation. Minimum inhibitory concentration (MIC) [median (interquartile range, IQR) values in isolated pathogens were: meropenem: 0.05 (0.02-0.12) mg/l; piperacillin: 3 (1-4) mg/l]. Pharmacokinetic/pharmacodynamic target attainments (100%fCss≥1xMIC, 100%fCss≥4xMIC and 100%fCss ≥ 8xMIC, respectively) were: 100%, 96.15%, 96.15% (meropenem) and 95.56%, 91.11%, 62.22% (piperacillin) for actual MIC; 98.11%, 71.70%, 47.17% (meropenem, MIC 2 mg/l), 95.83%, 44.79%, 6.25% (piperacillin, MIC 8 mg/l), 83.33%, 6.25%, 1.04% (piperacillin, MIC 16 mg/l) for EUCAST breakpoint of Enterobacteriaceae spp. and Pseudomonas spp. Multivariable linear analysis identified creatinine clearance (CrCL) as a predictive factor of free antibiotic concentrations (fCss) of both therapies (meropenem [ß = - 0.01 (95% CI - 0.02 to - 0.0; p = 0.043)] and piperacillin [ß = - 0.01 (95% CI - 0.02 to 0.01, p < 0.001)]). Neurocritical status was associated with lower piperacillin fCss [ß = - 0.36 (95% CI - 0.61 to - 0.11; p = 0.005)]. CONCLUSION: Standard total daily dose of meropenem allowed achieving pharmacokinetic/pharmacodynamic target attainments in ICU patients without renal dysfunction. Higher doses of piperacillin/tazobactam would be needed to cover microorganisms with MIC > 8 mg/l. CrCL was the most powerful factor predictive of fCss in both therapies.

The 2021 Nucleic Acids Research database issue and the online molecular biology database collection.

The 2021 Nucleic Acids Research database Issue contains 189 papers spanning a wide range of biological fields and investigation. It includes 89 papers reporting on new databases and 90 covering recent changes to resources previously published in the Issue. A further ten are updates on databases most recently published elsewhere. Seven new databases focus on COVID-19 and SARS-CoV-2 and many others offer resources for studying the virus. Major returning nucleic acid databases include NONCODE, Rfam and RNAcentral. Protein family and domain databases include COG, Pfam, SMART and Panther. Protein structures are covered by RCSB PDB and dispersed proteins by PED and MobiDB. In metabolism and signalling, STRING, KEGG and WikiPathways are featured, along with returning KLIFS and new DKK and KinaseMD, all focused on kinases. IMG/M and IMG/VR update in the microbial and viral genome resources section, while human and model organism genomics resources include Flybase, Ensembl and UCSC Genome Browser. Cancer studies are covered by updates from canSAR and PINA, as well as newcomers CNCdatabase and Oncovar for cancer drivers. Plant comparative genomics is catered for by updates from Gramene and GreenPhylDB. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been substantially updated, revisiting nearly 1000 entries, adding 90 new resources and eliminating 86 obsolete databases, bringing the current total to 1641 databases. It is available at https://www.oxfordjournals.org/nar/database/c/.