IgE Effector Mechanisms, in Concert with Mast Cells, Contribute to Acquired Host Defense against Staphylococcusaureus.

Allergies are considered to represent mal-directed type 2 immune responses against mostly innocuous exogenous compounds. Immunoglobulin E (IgE) antibodies are a characteristic feature of allergies and mediate hypersensitivity against allergens through activation of effector cells, particularly mast cells (MCs). Although the physiological functions of this dangerous branch of immunity have remained enigmatic, recent evidence shows that allergic immune reactions can help to protect against the toxicity of venoms. Because bacteria are a potent alternative source of toxins, we assessed the possible role of allergy-like type 2 immunity in antibacterial host defense. We discovered that the adaptive immune response against Staphylococcus aureus (SA) skin infection substantially improved systemic host defense against secondary SA infections in mice. Moreover, this acquired protection depended on IgE effector mechanisms and MCs. Importantly, our results reveal a previously unknown physiological function of allergic immune responses, IgE antibodies, and MCs in host defense against a pathogenic bacterium.

The social and structural architecture of the yeast protein interactome.

Cellular functions are mediated by protein-protein interactions, and mapping the interactome provides fundamental insights into biological systems. Affinity purification coupled to mass spectrometry is an ideal tool for such mapping, but it has been difficult to identify low copy number complexes, membrane complexes and complexes that are disrupted by protein tagging. As a result, our current knowledge of the interactome is far from complete, and assessing the reliability of reported interactions is challenging. Here we develop a sensitive high-throughput method using highly reproducible affinity enrichment coupled to mass spectrometry combined with a quantitative two-dimensional analysis strategy to comprehensively map the interactome of Saccharomyces cerevisiae. Thousand-fold reduced volumes in 96-well format enabled replicate analysis of the endogenous GFP-tagged library covering the entire expressed yeast proteome1. The 4,159 pull-downs generated a highly structured network of 3,927 proteins connected by 31,004 interactions, doubling the number of proteins and tripling the number of reliable interactions compared with existing interactome maps2. This includes very-low-abundance epigenetic complexes, organellar membrane complexes and non-taggable complexes inferred by abundance correlation. This nearly saturated interactome reveals that the vast majority of yeast proteins are highly connected, with an average of 16 interactors. Similar to social networks between humans, the average shortest distance between proteins is 4.2 interactions. AlphaFold-Multimer provided novel insights into the functional roles of previously uncharacterized proteins in complexes. Our web portal ( www.yeast-interactome.org ) enables extensive exploration of the interactome dataset.

O-GlcNAc Transferase Suppresses Inflammation and Necroptosis by Targeting Receptor-Interacting Serine/Threonine-Protein Kinase 3.

Elevated glucose metabolism in immune cells represents a hallmark feature of many inflammatory diseases, such as sepsis. However, the role of individual glucose metabolic pathways during immune cell activation and inflammation remains incompletely understood. Here, we demonstrate a previously unrecognized anti-inflammatory function of the O-linked ß-N-acetylglucosamine (O-GlcNAc) signaling associated with the hexosamine biosynthesis pathway (HBP). Despite elevated activities of glycolysis and the pentose phosphate pathway, activation of macrophages with lipopolysaccharide (LPS) resulted in attenuated HBP activity and protein O-GlcNAcylation. Deletion of O-GlcNAc transferase (OGT), a key enzyme for protein O-GlcNAcylation, led to enhanced innate immune activation and exacerbated septic inflammation. Mechanistically, OGT-mediated O-GlcNAcylation of the serine-threonine kinase RIPK3 on threonine 467 (T467) prevented RIPK3-RIPK1 hetero- and RIPK3-RIPK3 homo-interaction and inhibited downstream innate immunity and necroptosis signaling. Thus, our study identifies an immuno-metabolic crosstalk essential for fine-tuning innate immune cell activation and highlights the importance of glucose metabolism in septic inflammation.

A biosensor for the direct visualization of auxin.

One of the most important regulatory small molecules in plants is indole-3-acetic acid, also known as auxin. Its dynamic redistribution has an essential role in almost every aspect of plant life, ranging from cell shape and division to organogenesis and responses to light and gravity1,2. So far, it has not been possible to directly determine the spatial and temporal distribution of auxin at a cellular resolution. Instead it is inferred from the visualization of irreversible processes that involve the endogenous auxin-response machinery3-7; however, such a system cannot detect transient changes. Here we report a genetically encoded biosensor for the quantitative in vivo visualization of auxin distribution. The sensor is based on the Escherichia coli tryptophan repressor8, the binding pocket of which is engineered to be specific to auxin. Coupling of the auxin-binding moiety with selected fluorescent proteins enables the use of a fluorescence resonance energy transfer signal as a readout. Unlike previous systems, this sensor enables direct monitoring of the rapid uptake and clearance of auxin by individual cells and within cell compartments in planta. By responding to the graded spatial distribution along the root axis and its perturbation by transport inhibitors-as well as the rapid and reversible redistribution of endogenous auxin in response to changes in gravity vectors-our sensor enables real-time monitoring of auxin concentrations at a (sub)cellular resolution and their spatial and temporal changes during the lifespan of a plant.

Plasticity of the Cullin-RING Ligase Repertoire Shapes Sensitivity to Ligand-Induced Protein Degradation.

Inducing protein degradation via small molecules is a transformative therapeutic paradigm. Although structural requirements of target degradation are emerging, mechanisms determining the cellular response to small-molecule degraders remain poorly understood. To systematically delineate effectors required for targeted protein degradation, we applied genome-scale CRISPR/Cas9 screens for five drugs that hijack different substrate receptors (SRs) of cullin RING ligases (CRLs) to induce target proteolysis. We found that sensitivity to small-molecule degraders is dictated by shared and drug-specific modulator networks, including the COP9 signalosome and the SR exchange factor CAND1. Genetic or pharmacologic perturbation of these effectors impairs CRL plasticity and arrests a wide array of ligases in a constitutively active state. Resulting defects in CRL decommissioning prompt widespread CRL auto-degradation that confers resistance to multiple degraders. Collectively, our study informs on regulation and architecture of CRLs amenable for targeted protein degradation and outlines biomarkers and putative resistance mechanisms for upcoming clinical investigation.

TASL is the SLC15A4-associated adaptor for IRF5 activation by TLR7-9.

Toll-like receptors (TLRs) have a crucial role in the recognition of pathogens and initiation of immune responses1-3. Here we show that a previously uncharacterized protein encoded by CXorf21-a gene that is associated with systemic lupus erythematosus4,5-interacts with the endolysosomal transporter SLC15A4, an essential but poorly understood component of the endolysosomal TLR machinery also linked to autoimmune disease4,6-9. Loss of this type-I-interferon-inducible protein, which we refer to as 'TLR adaptor interacting with SLC15A4 on the lysosome' (TASL), abrogated responses to endolysosomal TLR agonists in both primary and transformed human immune cells. Deletion of SLC15A4 or TASL specifically impaired the activation of the IRF pathway without affecting NF-κB and MAPK signalling, which indicates that ligand recognition and TLR engagement in the endolysosome occurred normally. Extensive mutagenesis of TASL demonstrated that its localization and function relies on the interaction with SLC15A4. TASL contains a conserved pLxIS motif (in which p denotes a hydrophilic residue and x denotes any residue) that mediates the recruitment and activation of IRF5. This finding shows that TASL is an innate immune adaptor for TLR7, TLR8 and TLR9 signalling, revealing a clear mechanistic analogy with the IRF3 adaptors STING, MAVS and TRIF10,11. The identification of TASL as the component that links endolysosomal TLRs to the IRF5 transcription factor via SLC15A4 provides a mechanistic explanation for the involvement of these proteins in systemic lupus erythematosus12-14.

Planet-compatible pathways for transitioning the chemical industry.

Chemical products, such as plastics, solvents, and fertilizers, are essential for supporting modern lifestyles. Yet, producing, using, and disposing of chemicals creates adverse environmental impacts which threaten the industry's license to operate. This study presents seven planet-compatible pathways toward 2050 employing demand-side and supply-side interventions with cumulative total investment costs of US$1.2-3.7 trillion. Resource efficiency and circularity interventions reduce global chemicals demand by 23 to 33% and are critical for mitigating risks associated with using fossil feedstocks and carbon capture and sequestration, and constraints on available biogenic and recyclate feedstocks. Replacing fossil feedstocks with biogenic/air-capture sources, shifting carbon destinations from the atmosphere to ground, and electrifying/decarbonizing energy supply for production technologies could enable net negative emissions of 0.5 GtCO2eq y-1 across non-ammonia chemicals, while still delivering essential chemical-based services to society.

Tracers and Imaging of Fatty Acid and Energy Metabolism of Human Adipose Tissues.

White adipose tissue and brown adipose tissue (WAT and BAT) regulate fatty acid metabolism and control lipid fluxes to other organs. Dysfunction of these key metabolic processes contributes to organ insulin resistance and inflammation leading to chronic diseases such as type 2 diabetes, metabolic dysfunction-associated steatohepatitis, and cardiovascular diseases. Metabolic tracers combined with molecular imaging methods are powerful tools for the investigation of these pathogenic mechanisms. Herein, I review some of the positron emission tomography and magnetic resonance imaging methods combined with stable isotopic metabolic tracers to investigate fatty acid and energy metabolism, focusing on human WAT and BAT metabolism. I will discuss the complementary strengths offered by these methods for human investigations and current gaps in the field.

Ivosidenib and Azacitidine in IDH1-Mutated Acute Myeloid Leukemia.

BACKGROUND: The combination of ivosidenib - an inhibitor of mutant isocitrate dehydrogenase 1 (IDH1) - and azacitidine showed encouraging clinical activity in a phase 1b trial involving patients with newly diagnosed IDH1-mutated acute myeloid leukemia. METHODS: In this phase 3 trial, we randomly assigned patients with newly diagnosed IDH1-mutated acute myeloid leukemia who were ineligible for intensive induction chemotherapy to receive oral ivosidenib (500 mg once daily) and subcutaneous or intravenous azacitidine (75 mg per square meter of body-surface area for 7 days in 28-day cycles) or to receive matched placebo and azacitidine. The primary end point was event-free survival, defined as the time from randomization until treatment failure (i.e., the patient did not have complete remission by week 24), relapse from remission, or death from any cause, whichever occurred first. RESULTS: The intention-to-treat population included 146 patients: 72 in the ivosidenib-and-azacitidine group and 74 in the placebo-and-azacitidine group. At a median follow-up of 12.4 months, event-free survival was significantly longer in the ivosidenib-and-azacitidine group than in the placebo-and-azacitidine group (hazard ratio for treatment failure, relapse from remission, or death, 0.33; 95% confidence interval [CI], 0.16 to 0.69; P = 0.002). The estimated probability that a patient would remain event-free at 12 months was 37% in the ivosidenib-and-azacitidine group and 12% in the placebo-and-azacitidine group. The median overall survival was 24.0 months with ivosidenib and azacitidine and 7.9 months with placebo and azacitidine (hazard ratio for death, 0.44; 95% CI, 0.27 to 0.73; P = 0.001). Common adverse events of grade 3 or higher included febrile neutropenia (28% with ivosidenib and azacitidine and 34% with placebo and azacitidine) and neutropenia (27% and 16%, respectively); the incidence of bleeding events of any grade was 41% and 29%, respectively. The incidence of infection of any grade was 28% with ivosidenib and azacitidine and 49% with placebo and azacitidine. Differentiation syndrome of any grade occurred in 14% of the patients receiving ivosidenib and azacitidine and 8% of those receiving placebo and azacitidine. CONCLUSIONS: Ivosidenib and azacitidine showed significant clinical benefit as compared with placebo and azacitidine in this difficult-to-treat population. Febrile neutropenia and infections were less frequent in the ivosidenib-and-azacitidine group than in the placebo-and-azacitidine group, whereas neutropenia and bleeding were more frequent in the ivosidenib-and-azacitidine group. (Funded by Agios Pharmaceuticals and Servier Pharmaceuticals; AGILE ClinicalTrials.gov number, NCT03173248.).

Enasidenib vs conventional care in older patients with late-stage mutant-IDH2 relapsed/refractory AML: a randomized phase 3 trial.

This open-label, randomized, phase 3 trial (NCT02577406) compared enasidenib, an oral IDH2 (isocitrate dehydrogenase 2) inhibitor, with conventional care regimens (CCRs) in patients aged ≥60 years with late-stage, mutant-IDH2 acute myeloid leukemia (AML) relapsed/refractory (R/R) to 2 or 3 prior AML-directed therapies. Patients were first preselected to a CCR (azacitidine, intermediate-dose cytarabine, low-dose cytarabine, or supportive care) and then randomized (1:1) to enasidenib 100 mg per day or CCR. The primary endpoint was overall survival (OS). Secondary endpoints included event-free survival (EFS), time to treatment failure (TTF), overall response rate (ORR), hematologic improvement (HI), and transfusion independence (TI). Overall, 319 patients were randomized to enasidenib (n = 158) or CCR (n = 161). The median age was 71 years, median (range) enasidenib exposure was 142 days (3 to 1270), and CCR was 36 days (1 to 1166). One enasidenib (0.6%) and 20 CCR (12%) patients received no randomized treatment, and 30% and 43%, respectively, received subsequent AML-directed therapies during follow-up. The median OS with enasidenib vs CCR was 6.5 vs 6.2 months (HR [hazard ratio], 0.86; P = .23); 1-year survival was 37.5% vs 26.1%. Enasidenib meaningfully improved EFS (median, 4.9 vs 2.6 months with CCR; HR, 0.68; P = .008), TTF (median, 4.9 vs 1.9 months; HR, 0.53; P < .001), ORR (40.5% vs 9.9%; P <.001), HI (42.4% vs 11.2%), and red blood cell (RBC)-TI (31.7% vs 9.3%). Enasidenib safety was consistent with prior reports. The primary study endpoint was not met, but OS was confounded by early dropout and subsequent AML-directed therapies. Enasidenib provided meaningful benefits in EFS, TTF, ORR, HI, and RBC-TI in this heavily pretreated older mutant-IDH2 R/R AML population.

Accurate Label-Free Quantification by directLFQ to Compare Unlimited Numbers of Proteomes.

Recent advances in mass spectrometry-based proteomics enable the acquisition of increasingly large datasets within relatively short times, which exposes bottlenecks in the bioinformatics pipeline. Although peptide identification is already scalable, most label-free quantification (LFQ) algorithms scale quadratic or cubic with the sample numbers, which may even preclude the analysis of large-scale data. Here we introduce directLFQ, a ratio-based approach for sample normalization and the calculation of protein intensities. It estimates quantities via aligning samples and ion traces by shifting them on top of each other in logarithmic space. Importantly, directLFQ scales linearly with the number of samples, allowing analyses of large studies to finish in minutes instead of days or months. We quantify 10,000 proteomes in 10 min and 100,000 proteomes in less than 2 h, a 1000-fold faster than some implementations of the popular LFQ algorithm MaxLFQ. In-depth characterization of directLFQ reveals excellent normalization properties and benchmark results, comparing favorably to MaxLFQ for both data-dependent acquisition and data-independent acquisition. In addition, directLFQ provides normalized peptide intensity estimates for peptide-level comparisons. It is an important part of an overall quantitative proteomic pipeline that also needs to include high sensitive statistical analysis leading to proteoform resolution. Available as an open-source Python package and a graphical user interface with a one-click installer, it can be used in the AlphaPept ecosystem as well as downstream of most common computational proteomics pipelines.

In adults with COVID-19 and severe hypoxemia, lower vs. higher oxygenation targets increased days alive without life support.

SOURCE CITATION: Nielsen FM, Klitgaard TL, Siegemund M, et al; HOT-COVID Trial Group. Lower vs higher oxygenation target and days alive without life support in COVID-19: the HOT-COVID randomized clinical trial. JAMA. 2024;331:1185-1194. 38501214.

Shared in planta population and transcriptomic features of nonpathogenic members of endophytic phyllosphere microbiota.

SignificancePlants evolved in an environment colonized by a vast number of microbes, which collectively constitute the plant microbiota. The majority of microbiota taxa are nonpathogenic and may be beneficial to plants under certain ecological or environmental conditions. We conducted experiments to understand the features of long-term interactions of nonpathogenic microbiota members with plants. We found that a multiplication-death equilibrium explained the shared long-term static populations of nonpathogenic bacteria and that in planta bacterial transcriptomic signatures were characteristic of the stationary phase, a physiological state in which stress protection responses are induced. These results may have significant implications in understanding the bulk of "nonpathogenic" plant-microbiota interactions that occur in agricultural and natural ecosystems.

Improving Sepsis Outcomes in the Era of Pay-for-Performance and Electronic Quality Measures: A Joint IDSA/ACEP/PIDS/SHEA/SHM/SIDP Position Paper.

The Centers for Medicare & Medicaid Services (CMS) introduced the Severe Sepsis/Septic Shock Management Bundle (SEP-1) as a pay-for-reporting measure in 2015 and is now planning to make it a pay-for-performance measure by incorporating it into the Hospital Value-Based Purchasing Program. This joint IDSA/ACEP/PIDS/SHEA/SHM/SIPD position paper highlights concerns with this change. Multiple studies indicate that SEP-1 implementation was associated with increased broad-spectrum antibiotic use, lactate measurements, and aggressive fluid resuscitation for patients with suspected sepsis but not with decreased mortality rates. Increased focus on SEP-1 risks further diverting attention and resources from more effective measures and comprehensive sepsis care. We recommend retiring SEP-1 rather than using it in a payment model and shifting instead to new sepsis metrics that focus on patient outcomes. CMS is developing a community-onset sepsis 30-day mortality electronic clinical quality measure (eCQM) that is an important step in this direction. The eCQM preliminarily identifies sepsis using systemic inflammatory response syndrome (SIRS) criteria, antibiotic administrations or diagnosis codes for infection or sepsis, and clinical indicators of acute organ dysfunction. We support the eCQM but recommend removing SIRS criteria and diagnosis codes to streamline implementation, decrease variability between hospitals, maintain vigilance for patients with sepsis but without SIRS, and avoid promoting antibiotic use in uninfected patients with SIRS. We further advocate for CMS to harmonize the eCQM with the Centers for Disease Control and Prevention's (CDC) Adult Sepsis Event surveillance metric to promote unity in federal measures, decrease reporting burden for hospitals, and facilitate shared prevention initiatives. These steps will result in a more robust measure that will encourage hospitals to pay more attention to the full breadth of sepsis care, stimulate new innovations in diagnosis and treatment, and ultimately bring us closer to our shared goal of improving outcomes for patients.

Brown adipose tissue metabolism in women is dependent on ovarian status.

In rodents, loss of estradiol (E2) reduces brown adipose tissue (BAT) metabolic activity. Whether E2 impacts BAT activity in women is not known. BAT oxidative metabolism was measured in premenopausal (n = 27; 35 ± 9 yr; body mass index = 26.0 ± 5.3 kg/m2) and postmenopausal (n = 25; 51 ± 8 yr; body mass index = 28.0 ± 5.0 kg/m2) women at room temperature and during acute cold exposure using [11C]acetate with positron emission tomography coupled with computed tomograph. BAT glucose uptake was also measured during acute cold exposure using 2-deoxy-2-[18F]fluoro-d-glucose. To isolate the effects of ovarian hormones from biological aging, measurements were repeated in a subset of premenopausal women (n = 8; 40 ± 4 yr; BMI = 28.0 ± 7.2 kg/m2) after 6 mo of gonadotropin-releasing hormone agonist therapy to suppress ovarian hormones. At room temperature, there was no difference in BAT oxidative metabolism between premenopausal (0.56 ± 0.31 min-1) and postmenopausal women (0.63 ± 0.28 min-1). During cold exposure, BAT oxidative metabolism (1.28 ± 0.85 vs. 0.91 ± 0.63 min-1, P = 0.03) and net BAT glucose uptake (84.4 ± 82.5 vs. 29.7 ± 31.4 nmol·g-1·min-1, P < 0.01) were higher in premenopausal than postmenopausal women. In premenopausal women who underwent gonadotropin-releasing hormone agonist, cold-stimulated BAT oxidative metabolism was reduced to a similar level (from 1.36 ± 0.66 min-1 to 0.91 ± 0.41 min-1) to that observed in postmenopausal women (0.91 ± 0.63 min-1). These results provide the first evidence in humans that reproductive hormones are associated with BAT oxidative metabolism and suggest that BAT may be a target to attenuate age-related reduction in energy expenditure and maintain metabolic health in postmenopausal women.NEW & NOTEWORTHY In rodents, loss of estrogen reduces brown adipose tissue (BAT) activity. Whether this is true in humans is not known. We found that BAT oxidative metabolism and glucose uptake were lower in postmenopausal compared to premenopausal women. In premenopausal women who underwent ovarian suppression to reduce circulating estrogen, BAT oxidative metabolism was reduced to postmenopausal levels. Thus the loss of ovarian function in women leads to a reduction in BAT metabolic activity independent of age.

BMP6 and VDR gene polymorphisms are associated with osteonecrosis in a sickle cell anaemia cohort.

The occurrence and severity of osteonecrosis in sickle cell anaemia (SCA) vary due to risk factors, including genetic modifiers. Bone morphogenetic proteins (BMPs), particularly BMP6, and the vitamin D receptor (VDR) play key roles in cartilage and bone metabolism, making them potential contributors to orthopaedic outcomes in SCA. Here, we evaluated the association of polymorphisms in BMP6 (rs3812163, rs270393 and rs449853) and VDR (FokI rs2228570 and Cdx2 rs11568820) genes with osteonecrosis risk in a Brazilian SCA cohort. A total of 177 unrelated SCA patients were selected. The AA genotype of BMP6 rs3812163 was independently associated with a lower osteonecrosis risk (p = 0.015; odds ratio (OR): 0.38; 95% confidence interval (CI): 0.18-0.83) and with the long-term cumulative incidence of osteonecrosis (p = 0.029; hazard ratio: 0.56, 95% CI: 0.34-0.94). The VDR rs2228570 TT genotype was independently associated with a lower osteonecrosis risk (p = 0.039; OR: 0.14; 95% CI: 0.02-0.90). In summary, our results provide evidence that BMP6 rs3812163 and the VDR rs2228570 might be implicated in osteonecrosis pathophysiology in SCA and might help identify individuals at high risk.

Benefits of Pair-Bond Duration on Reproduction in a Lifelong Monogamous Cooperative Passerine.

AbstractLong-term social and genetic monogamy is rare in animals except birds, but even in birds it is infrequent and poorly understood. We investigated possible advantages of monogamy in a colonial, facultative cooperatively breeding bird from an arid, unpredictable environment, the sociable weaver (Philetairus socius). We documented divorce and extrapair paternity of 703 pairs over 10 years and separated effects of pair duration from breeding experience by analyzing longitudinal and cross-sectional datasets. Parts of the colonies were protected from nest predation, thereby limiting its stochastic and thus confounding effect on fitness measures. We found that 6.4% of sociable weaver pairs divorced and 2.2% of young were extrapair. Longer pair-bonds were associated with more clutches and fledglings per season and with reproducing earlier and later in the season, when snake predation is lower, but not with increased egg or fledgling mass or with nestling survival. Finally, the number of helpers at the nest increased with pair-bond duration. Results were similar for protected and unprotected nests. We suggest that long-term monogamy is associated with a better capacity for exploiting a temporally unpredictable environment and helps to form larger groups. These results can contribute to our understanding of why long-term monogamy is frequently associated with unpredictable environments and cooperation.

Baricitinib plus Remdesivir for Hospitalized Adults with Covid-19.

BACKGROUND: Severe coronavirus disease 2019 (Covid-19) is associated with dysregulated inflammation. The effects of combination treatment with baricitinib, a Janus kinase inhibitor, plus remdesivir are not known. METHODS: We conducted a double-blind, randomized, placebo-controlled trial evaluating baricitinib plus remdesivir in hospitalized adults with Covid-19. All the patients received remdesivir (≤10 days) and either baricitinib (≤14 days) or placebo (control). The primary outcome was the time to recovery. The key secondary outcome was clinical status at day 15. RESULTS: A total of 1033 patients underwent randomization (with 515 assigned to combination treatment and 518 to control). Patients receiving baricitinib had a median time to recovery of 7 days (95% confidence interval [CI], 6 to 8), as compared with 8 days (95% CI, 7 to 9) with control (rate ratio for recovery, 1.16; 95% CI, 1.01 to 1.32; P = 0.03), and a 30% higher odds of improvement in clinical status at day 15 (odds ratio, 1.3; 95% CI, 1.0 to 1.6). Patients receiving high-flow oxygen or noninvasive ventilation at enrollment had a time to recovery of 10 days with combination treatment and 18 days with control (rate ratio for recovery, 1.51; 95% CI, 1.10 to 2.08). The 28-day mortality was 5.1% in the combination group and 7.8% in the control group (hazard ratio for death, 0.65; 95% CI, 0.39 to 1.09). Serious adverse events were less frequent in the combination group than in the control group (16.0% vs. 21.0%; difference, -5.0 percentage points; 95% CI, -9.8 to -0.3; P = 0.03), as were new infections (5.9% vs. 11.2%; difference, -5.3 percentage points; 95% CI, -8.7 to -1.9; P = 0.003). CONCLUSIONS: Baricitinib plus remdesivir was superior to remdesivir alone in reducing recovery time and accelerating improvement in clinical status among patients with Covid-19, notably among those receiving high-flow oxygen or noninvasive ventilation. The combination was associated with fewer serious adverse events. (Funded by the National Institute of Allergy and Infectious Diseases; ClinicalTrials.gov number, NCT04401579.).

MathFeature: feature extraction package for DNA, RNA and protein sequences based on mathematical descriptors.

One of the main challenges in applying machine learning algorithms to biological sequence data is how to numerically represent a sequence in a numeric input vector. Feature extraction techniques capable of extracting numerical information from biological sequences have been reported in the literature. However, many of these techniques are not available in existing packages, such as mathematical descriptors. This paper presents a new package, MathFeature, which implements mathematical descriptors able to extract relevant numerical information from biological sequences, i.e. DNA, RNA and proteins (prediction of structural features along the primary sequence of amino acids). MathFeature makes available 20 numerical feature extraction descriptors based on approaches found in the literature, e.g. multiple numeric mappings, genomic signal processing, chaos game theory, entropy and complex networks. MathFeature also allows the extraction of alternative features, complementing the existing packages. To ensure that our descriptors are robust and to assess their relevance, experimental results are presented in nine case studies. According to these results, the features extracted by MathFeature showed high performance (0.6350-0.9897, accuracy), both applying only mathematical descriptors, but also hybridization with well-known descriptors in the literature. Finally, through MathFeature, we overcame several studies in eight benchmark datasets, exemplifying the robustness and viability of the proposed package. MathFeature has advanced in the area by bringing descriptors not available in other packages, as well as allowing non-experts to use feature extraction techniques.

BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria.

Recent technological advances have led to an exponential expansion of biological sequence data and extraction of meaningful information through Machine Learning (ML) algorithms. This knowledge has improved the understanding of mechanisms related to several fatal diseases, e.g. Cancer and coronavirus disease 2019, helping to develop innovative solutions, such as CRISPR-based gene editing, coronavirus vaccine and precision medicine. These advances benefit our society and economy, directly impacting people's lives in various areas, such as health care, drug discovery, forensic analysis and food processing. Nevertheless, ML-based approaches to biological data require representative, quantitative and informative features. Many ML algorithms can handle only numerical data, and therefore sequences need to be translated into a numerical feature vector. This process, known as feature extraction, is a fundamental step for developing high-quality ML-based models in bioinformatics, by allowing the feature engineering stage, with design and selection of suitable features. Feature engineering, ML algorithm selection and hyperparameter tuning are often manual and time-consuming processes, requiring extensive domain knowledge. To deal with this problem, we present a new package: BioAutoML. BioAutoML automatically runs an end-to-end ML pipeline, extracting numerical and informative features from biological sequence databases, using the MathFeature package, and automating the feature selection, ML algorithm(s) recommendation and tuning of the selected algorithm(s) hyperparameters, using Automated ML (AutoML). BioAutoML has two components, divided into four modules: (1) automated feature engineering (feature extraction and selection modules) and (2) Metalearning (algorithm recommendation and hyper-parameter tuning modules). We experimentally evaluate BioAutoML in two different scenarios: (i) prediction of the three main classes of noncoding RNAs (ncRNAs) and (ii) prediction of the eight categories of ncRNAs in bacteria, including housekeeping and regulatory types. To assess BioAutoML predictive performance, it is experimentally compared with two other AutoML tools (RECIPE and TPOT). According to the experimental results, BioAutoML can accelerate new studies, reducing the cost of feature engineering processing and either keeping or improving predictive performance. BioAutoML is freely available at https://github.com/Bonidia/BioAutoML.