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Background/objectives The phase angle, expressed through bioelectrical impedance, has been studied as a prognostic marker in several health conditions. As this issue is still conflicting, the question whether this parameter correlates with mortality in the most diverse clinical situations remains. Therefore, this study aimed to evaluate the relationship between phase angle and mortality through a systematic review of the literature. Subjects/methods This research was conducted in electronic databases (Pubmed, Embase, Cochrane, Lilacs, Scielo, e Scopus), and included studies that had phase angle as a variable of interest and mortality/survival as an outcome. Data were extracted independently by two reviewers and disagreements were assessed by a third reviewer. Results Forty-eight of 455 papers were assessed and an amount of 42 showed a correlation between phase angle and mortality. Conclusions Phase angle seems to be a good indicator for mortality in many clinical situations and can be used in screening individuals prone to this outcome.

Uncooked cornstarch (UCCS) is a widely used treatment strategy for patients with hepatic glycogen storage disease (GSD). It has been observed that GSD-patients display different metabolic responses to different cornstarches. The objective was to characterize starch fractions and analyze the digestion of different starches in a dynamic gastrointestinal in vitro model. The following brands of UCCS were studied: Argo® and Great Value® from the United States of America; Brazilian Maizena Duryea® and Yoki® from Brazil; Dutch Maizena Duryea® from the Netherlands. Glycosade®, a modified starch, and sweet polvilho, a Brazilian starch extracted from cassava, were also studied. The starch fractions were analyzed by glycemic TNO index method and digestion analyses were determined by the TIM-1 system, a dynamic, computer-controlled, in vitro gastrointestinal model, which simulates the stomach and small intestine. The final digested amounts were between 84 and 86 % for the UCCS and Glycosade®, but was 75.5 % for sweet povilho. At 180 min of the experiment, an important time-point for GSD patients, the digested amount of the starches corresponded to 67.9–71.5 for the UCCS and Glycosade®, while it was 55.5 % for sweet povilho. In an experiment with a mixture of sweet polvilho and Brazilian Maizena Duryea®, a final digested amount of 78.4 % was found, while the value at 180 min was 61.7 %. Sweet polvilho seems to have a slower and extended release of glucose and looks like an interesting product to be further studied as it might lead to extended normoglycemia in GSD-patients.

Early data suggested that CC‐115, a clinical molecule, already known to inhibit the mammalian target of rapamycin kinase (TORK) and DNA‐dependent protein kinase (DNA‐PK) may have additional targets beyond TORK and DNA‐PK. Therefore, we aimed to identify such target(s) and investigate a potential therapeutic applicability. Functional profiling of 141 cancer cell lines revealed inhibition of kinase suppressor of morphogenesis in genitalia 1 (SMG1), a key regulator of the RNA degradation mechanism nonsense‐mediated mRNA decay (NMD), as an additional target of CC‐115. CC‐115 treatment showed a dose‐dependent increase of SMG1‐mediated NMD transcripts. A subset of cell lines, including multiple myeloma (MM) cell lines sensitive to the endoplasmic reticulum stress‐inducing compound thapsigargin, were highly susceptible to SMG1 inhibition. CC‐115 caused the induction of UPR transcripts and cell death by mitochondrial apoptosis, requiring the presence of BAX/BAK and caspase activity. Superior antitumor activity of CC‐115 over TORK inhibitors in primary human MM cells and three xenograft mouse models appeared to be via inhibition of SMG1. Our data support further development of SMG1 inhibitors as possible therapeutics in MM. In this study, SMG1, a key regulator of the RNA degradation mechanism nonsense‐mediated mRNA decay (NMD), was discovered as an additional target of the clinical compound CC‐115. CC‐115 treatment showed a dose‐dependent increase of NMD transcripts, unfolded protein response (UPR) transcripts, and cell death via SMG1 inhibition in a subset of cell lines, primary multiple myeloma cells, and xenograft mouse models.

Cohort selection is challenging for large-scale electronic health record (EHR) analyses, as International Classification of Diseases 9th edition (ICD-9) diagnostic codes are notoriously unreliable disease predictors. Our objective was to develop, evaluate, and validate an automated algorithm for determining an Autism Spectrum Disorder (ASD) patient cohort from EHR. We demonstrate its utility via the largest investigation to date of the co-occurrence patterns of medical comorbidities in ASD. We extracted ICD-9 codes and concepts derived from the clinical notes. A gold standard patient set was labeled by clinicians at Boston Children's Hospital (BCH) (N = 150) and Cincinnati Children's Hospital and Medical Center (CCHMC) (N = 152). Two algorithms were created: (1) rule-based implementing the ASD criteria from Diagnostic and Statistical Manual of Mental Diseases 4th edition, (2) predictive classifier. The positive predictive values (PPV) achieved by these algorithms were compared to an ICD-9 code baseline. We clustered the patients based on grouped ICD-9 codes and evaluated subgroups. The rule-based algorithm produced the best PPV: (a) BCH: 0.885 vs. 0.273 (baseline); (b) CCHMC: 0.840 vs. 0.645 (baseline); (c) combined: 0.864 vs. 0.460 (baseline). A validation at Children's Hospital of Philadelphia yielded 0.848 (PPV). Clustering analyses of comorbidities on the three-site large cohort (N = 20,658 ASD patients) identified psychiatric, developmental, and seizure disorder clusters. In a large cross-institutional cohort, co-occurrence patterns of comorbidities in ASDs provide further hypothetical evidence for distinct courses in ASD. The proposed automated algorithms for cohort selection open avenues for other large-scale EHR studies and individualized treatment of ASD.

This study aims to translate the Brief Autism Mealtime Behaviour Inventory (BAMBI) questionnaire to Brazilian Portuguese, in order to provide a tool to be used in clinic routine that encourages the evaluation of the feeding behaviour of patients with Autism Spectrum Disorder (ASD). The final sample contained 410 participants, the mean age was 9.58 ± 1.2 and the majority of participants were male (95%). Validation of this questionnaire allows a structured evaluation for this population to be integrated not only into the clinical routine but also to help parent’s interventions about the eating problems and possible consequences. This is of utmost importance, since parents are reporting the nutritional aspects more often, and studies indicate that up to 80% of ASD patients may present feeding behavior problems.

Frailty commonly coexists with heart failure and although both have been associated with neurohormonal dysregulation, inflammation, catabolism, and skeletal muscle dysfunction, there are still no defined biomarkers to assess frailty, especially from the perspective of populations with cardiovascular diseases. This is a cross-sectional study with 106 outpatients with heart failure, aged ≥60 years, which aimed to assess frailty through a physical (frailty phenotype) and multidimensional (Tilburg Frailty Indicator) approach and to analyze its association with inflammatory and humoral biomarkers (high sensitivity C-reactive protein [hs-CRP], interleukin 6, tumor necrosis factor-α, insulin-like growth factor-1, and total testosterone), clinical characteristics, and functional capacity. In univariate analysis, hs-CRP was associated with frailty in both phenotype and Tilburg Frailty Indicator assessment (PR = 1.005, 95% confidence interval [CI] 1.001 to 1.009, p = 0.027 and PR = 1.015, 95% CI 1.006 to 1.024, p = 0.001, respectively), which remained significant in the final multivariate model in the frailty assessment by the phenotype (PR = 1.004, 95% CI 1.001 to 1.008, p = 0.025). There was no statistically significant difference between the groups for other biomarkers analyzed. Frailty was also associated with worse functional capacity, nonoptimized pharmacological treatment and a greater number of drugs in use, age, female gender, and a greater number of comorbidities. In conclusion, frailty is associated with higher levels of hs-CRP, which can indicate it is a promising frailty biomarker.

CDKL5 deficiency disorder (CDD) is a rare, X-linked, developmental and epileptic encephalopathy characterised by severe global developmental impairment and seizures that can begin in the first few months after birth and are often treatment refractory. Ganaxolone, an investigational neuroactive steroid, reduced seizure frequency in an open-label, phase 2 trial that included patients with CDD. We aimed to further assess the efficacy and safety of ganaxolone in patients with CDD-associated refractory epilepsy. In the double-blind phase of this randomised, placebo-controlled, phase 3 trial, done at 39 outpatient clinics in eight countries (Australia, France, Israel, Italy, Poland, Russia, the UK, and the USA), patients were eligible if they were aged 2–21 years with a pathogenic or probably pathogenic CDKL5 variant and at least 16 major motor seizures (defined as bilateral tonic, generalised tonic-clonic, bilateral clonic, atonic, or focal to bilateral tonic-clonic) per 28 days in each 4-week period of an 8-week historical period. After a 6-week prospective baseline period, patients were randomly assigned (1:1) via an interactive web response system to receive either enteral adjunctive ganaxolone or matching enteral adjunctive placebo (maximum dose 63 mg/kg per day for patients weighing ≤28 kg or 1800 mg/day for patients weighing >28 kg) for 17 weeks. Patients, caregivers, investigators (including those analysing data), trial staff, and the sponsor (other than the investigational product manager) were masked to treatment allocation. The primary efficacy endpoint was percentage change in median 28-day major motor seizure frequency from the baseline period to the 17-week double-blind phase and was analysed (using a Wilcoxon-rank sum test) in all patients who received at least one dose of trial treatment and for whom baseline data were available. Safety (compared descriptively across groups) was analysed in all patients who received at least one dose of trial treatment. This study is registered with ClinicalTrials.gov, NCT03572933, and the open-label extension phase is ongoing. Between June 25, 2018, and July 2, 2020, 114 patients were screened for eligibility, of whom 101 (median age 6 years [IQR 3 to 10]) were randomly assigned to receive either ganaxolone (n=50) or placebo (n=51). All patients received at least one dose of a study drug, but seizure frequency for one patient in the ganaxolone group was not recorded at baseline and so the primary endpoint was analysed in a population of 100 patients. There was a median percentage change in 28-day major motor seizure frequency of –30·7% (IQR –49·5 to –1·9) in the ganaxolone group and of –6·9% (–24·1 to 39·7) in the placebo group (p=0·0036). The Hodges–Lehmann estimate of median difference in responses to ganaxolone versus placebo was –27·1% (95% CI –47·9 to – 9·6). Treatment-emergent adverse events occurred in 43 (86%) of 50 patients in the ganaxolone group and in 45 (88%) of 51 patients in the placebo group. Somnolence, pyrexia, and upper respiratory tract infections occurred in at least 10% of patients in the ganaxolone group and more frequently than in the placebo group. Serious adverse events occurred in six (12%) patients in the ganaxolone group and in five (10%) patients in the placebo group. Two (4%) patients in the ganaxolone group and four (8%) patients in the placebo group discontinued the trial. There were no deaths in the double-blind phase. Ganaxolone significantly reduced the frequency of CDD-associated seizures compared with placebo and was generally well tolerated. Results from what is, to our knowledge, the first controlled trial in CDD suggest a potential treatment benefit for ganaxolone. Long-term treatment is being assessed in the ongoing open-label extension phase of this trial. Marinus Pharmaceuticals.

Generation of effective immune responses requires expansion of rare antigen-specific CD4⁺ T cells. The magnitude of the responding population is ultimately determined by proliferation and survival. Both processes are tightly controlled to limit responses to innocuous antigens. Sustained expansion occurs only when innate immune sensors are activated by microbial stimuli or by adjuvants, which has important implications for vaccination. The molecular identity of the signals controlling sustained T-cell responses is not fully clear. Here, we describe a prominent role for the Notch pathway in this process. Coactivation of Notch allows accumulation of far greater numbers of activated CD4⁺ T cells than stimulation via T-cell receptor and classic costimulation alone. Notch does not overtly affect cell cycle entry or progression of CD4⁺ T cells. Instead, Notch protects activated CD4⁺ T cells against apoptosis after an initial phase of clonal expansion. Notch induces a broad antiapoptotic gene expression program that protects against intrinsic, as well as extrinsic, apoptosis pathways. Both Notch1 and Notch2 receptors and the canonical effector RBPJ (recombination signal binding protein for immunoglobulin kappa J region) are involved in this process. Correspondingly, CD4⁺ T-cell responses to immunization with protein antigen are strongly reduced in mice lacking these components of the Notch pathway. Our findings, therefore, show that Notch controls the magnitude of CD4⁺ T-cell responses by promoting cellular longevity.

Each year in the United States, Clostridioides difficile causes nearly 500,000 gastrointestinal infections that range from mild diarrhea to severe colitis and death. The ability to identify patients at increased risk for severe disease or mortality at the time of diagnosis of C. difficile infection (CDI) would allow clinicians to effectively allocate disease modifying therapies. In this study, we developed models consisting of only a small number of serum biomarkers that are capable of predicting both 30-day all-cause mortality and adverse outcomes of patients at time of CDI diagnosis. We were able to validate these models through experimental mouse infection. This provides evidence that the biomarkers reflect the underlying pathophysiology and that our mouse model of CDI reflects the pathogenesis of human infection. Predictive models can not only assist clinicians in identifying patients at risk for severe CDI but also be utilized for targeted enrollment in clinical trials aimed at reduction of adverse outcomes from severe CDI. Clostridioides difficile infection (CDI) can result in severe disease and death, with no accurate models that allow for early prediction of adverse outcomes. To address this need, we sought to develop serum-based biomarker models to predict CDI outcomes. We prospectively collected sera ≤48 h after diagnosis of CDI in two cohorts. Biomarkers were measured with a custom multiplex bead array assay. Patients were classified using IDSA severity criteria and the development of disease-related complications (DRCs), which were defined as ICU admission, colectomy, and/or death attributed to CDI. Unadjusted and adjusted models were built using logistic and elastic net modeling. The best model for severity included procalcitonin (PCT) and hepatocyte growth factor (HGF) with an area (AUC) under the receiver operating characteristic (ROC) curve of 0.74 (95% confidence interval, 0.67 to 0.81). The best model for 30-day mortality included interleukin-8 (IL-8), PCT, CXCL-5, IP-10, and IL-2Rα with an AUC of 0.89 (0.84 to 0.95). The best model for DRCs included IL-8, procalcitonin, HGF, and IL-2Rα with an AUC of 0.84 (0.73 to 0.94). To validate our models, we employed experimental infection of mice with C. difficile . Antibiotic-treated mice were challenged with C. difficile and a similar panel of serum biomarkers was measured. Applying each model to the mouse cohort of severe and nonsevere CDI revealed AUCs of 0.59 (0.44 to 0.74), 0.96 (0.90 to 1.0), and 0.89 (0.81 to 0.97). In both human and murine CDI, models based on serum biomarkers predicted adverse CDI outcomes. Our results support the use of serum-based biomarker panels to inform Clostridioides difficile infection treatment. IMPORTANCE Each year in the United States, Clostridioides difficile causes nearly 500,000 gastrointestinal infections that range from mild diarrhea to severe colitis and death. The ability to identify patients at increased risk for severe disease or mortality at the time of diagnosis of C. difficile infection (CDI) would allow clinicians to effectively allocate disease modifying therapies. In this study, we developed models consisting of only a small number of serum biomarkers that are capable of predicting both 30-day all-cause mortality and adverse outcomes of patients at time of CDI diagnosis. We were able to validate these models through experimental mouse infection. This provides evidence that the biomarkers reflect the underlying pathophysiology and that our mouse model of CDI reflects the pathogenesis of human infection. Predictive models can not only assist clinicians in identifying patients at risk for severe CDI but also be utilized for targeted enrollment in clinical trials aimed at reduction of adverse outcomes from severe CDI.