Effect of a machine learning-based severe sepsis prediction algorithm on patient survival and hospital length of stay: a randomised clinical trial.

IntroductionSeveral methods have been developed to electronically monitor patients for severe sepsis, but few provide predictive capabilities to enable early intervention; furthermore, no severe sepsis prediction systems have been previously validated in a randomised study. We tested the use of a machine learning-based severe sepsis prediction system for reductions in average length of stay and in-hospital mortality rate.MethodsWe conducted a randomised controlled clinical trial at two medical-surgical intensive care units at the University of California, San Francisco Medical Center, evaluating the primary outcome of average length of stay, and secondary outcome of in-hospital mortality rate from December 2016 to February 2017. Adult patients (18+) admitted to participating units were eligible for this factorial, open-label study. Enrolled patients were assigned to a trial arm by a random allocation sequence. In the control group, only the current severe sepsis detector was used; in the experimental group, the machine learning algorithm (MLA) was also used. On receiving an alert, the care team evaluated the patient and initiated the severe sepsis bundle, if appropriate. Although participants were randomly assigned to a trial arm, group assignments were automatically revealed for any patients who received MLA alerts.ResultsOutcomes from 75 patients in the control and 67 patients in the experimental group were analysed. Average length of stay decreased from 13.0 days in the control to 10.3 days in the experimental group (p=0.042). In-hospital mortality decreased by 12.4 percentage points when using the MLA (p=0.018), a relative reduction of 58.0%. No adverse events were reported during this trial.ConclusionThe MLA was associated with improved patient outcomes. This is the first randomised controlled trial of a sepsis surveillance system to demonstrate statistically significant differences in length of stay and in-hospital mortality.Trial registrationNCT03015454

Revealing the impact of lifestyle stressors on the risk of adverse pregnancy outcomes with multitask machine learning

Psychosocial and stress-related factors (PSFs), defined as internal or external stimuli that induce biological changes, are potentially modifiable factors and accessible targets for interventions that are associated with adverse pregnancy outcomes (APOs). Although individual APOs have been shown to be connected to PSFs, they are biologically interconnected, relatively infrequent, and therefore challenging to model. In this context, multi-task machine learning (MML) is an ideal tool for exploring the interconnectedness of APOs on the one hand and building on joint combinatorial outcomes to increase predictive power on the other hand. Additionally, by integrating single cell immunological profiling of underlying biological processes, the effects of stress-based therapeutics may be measurable, facilitating the development of precision medicine approaches.ObjectivesThe primary objectives were to jointly model multiple APOs and their connection to stress early in pregnancy, and to explore the underlying biology to guide development of accessible and measurable interventions.Materials and MethodsIn a prospective cohort study, PSFs were assessed during the first trimester with an extensive self-filled questionnaire for 200 women. We used MML to simultaneously model, and predict APOs (severe preeclampsia, superimposed preeclampsia, gestational diabetes and early gestational age) as well as several risk factors (BMI, diabetes, hypertension) for these patients based on PSFs. Strongly interrelated stressors were categorized to identify potential therapeutic targets. Furthermore, for a subset of 14 women, we modeled the connection of PSFs to the maternal immune system to APOs by building corresponding ML models based on an extensive single cell immune dataset generated by mass cytometry time of flight (CyTOF).ResultsJointly modeling APOs in a MML setting significantly increased modeling capabilities and yielded a highly predictive integrated model of APOs underscoring their interconnectedness. Most APOs were associated with mental health, life stress, and perceived health risks. Biologically, stressors were associated with specific immune characteristics revolving around CD4/CD8 T cells. Immune characteristics predicted based on stress were in turn found to be associated with APOs.ConclusionsElucidating connections among stress, multiple APOs simultaneously, and immune characteristics has the potential to facilitate the implementation of ML-based, individualized, integrative models of pregnancy in clinical decision making. The modifiable nature of stressors may enable the development of accessible interventions, with success tracked through immune characteristics

Whole genome deconvolution unveils Alzheimer’s resilient epigenetic signature

Abstract Assay for Transposase Accessible Chromatin by sequencing (ATAC-seq) accurately depicts the chromatin regulatory state and altered mechanisms guiding gene expression in disease. However, bulk sequencing entangles information from different cell types and obscures cellular heterogeneity. To address this, we developed Cellformer, a deep learning method that deconvolutes bulk ATAC-seq into cell type-specific expression across the whole genome. Cellformer enables cost-effective cell type-specific open chromatin profiling in large cohorts. Applied to 191 bulk samples from 3 brain regions, Cellformer identifies cell type-specific gene regulatory mechanisms involved in resilience to Alzheimer’s disease, an uncommon group of cognitively healthy individuals that harbor a high pathological load of Alzheimer’s disease. Cell type-resolved chromatin profiling unveils cell type-specific pathways and nominates potential epigenetic mediators underlying resilience that may illuminate therapeutic opportunities to limit the cognitive impact of the disease. Cellformer is freely available to facilitate future investigations using high-throughput bulk ATAC-seq data

SPECIFICITIES OF THE IMMUNE RESPONSE DURING THE PROCESS OF WOUND HEALING IN A DIABETES MODEL IN CD26 DEFICIENT MICE

Uvod: Dipeptidil-peptidaza IV (DPP IV/CD26) multifunkcionalan je protein s značajnom proteolitičkom i kostimulacijskom ulogom čime utječe i na proliferaciju, angiogenezu, adheziju, migraciju i apoptozu stanica u procesu cijeljenja rana. Modulacijom biološke aktivnosti inkretina sudjeluje i u regulaciji koncentracije glukoze u krvi, međutim, patofiziološki procesi cijeljenja rana u dijabetesu nisu dovoljno razjašnjeni. Pretpostavka ovog istraživanja je da DPP IV/CD26 ima važnu ulogu u modulaciji imunosnog odgovora u procesu cijeljenja rana u hiperglikemiji. Cilj istraživanja bio je ispitati utječe li nedostatak DPP IV/CD26 na makroskopske i/ili mikroskopske promjene tijekom procesa cijeljenja rana kože u dijabetesu, istražiti izražaj makrofaga i limfocita T kod CD26 deficijentnih te divljeg tipa životinja s induciranim dijabetesom te ispitati promjene u aktivnosti serumske DPP IV/CD26 tijekom uspostave eksperimentalne hiperglikemije i tijekom procesa cijeljenja rana kože u C57BL/6 životinjama. Materijal i metode: CD26 deficijentnim (CD26-/-) te divljem tipu miševa (C57BL/6) induciran je model dijabetesa intraperitonealnom aplikacijom otopine streptozotocina u citratnom puferu u dozi od 50 mg/kg tijekom pet dana. Miševima s potvrđenim dijabetesom je potom na interskapularnom dijelu leđa učinjeno šest rana promjera 5 mm te su pojedine skupine pokusnih životinja žrtvovane drugog, četvrtog, sedmog, desetog te petnaestog dana. Primjenom različitih metoda analize makroskopskih i mikroskopskih uzoraka (patohistološkim, imunohistokemijskim, histomorfometrijskim i spektrofotometrijskim metodama) pratio se stupanj regeneracije pojedinih slojeva kože, stupanj proliferacije stanica bazalnog sloja epidermisa i fibroblastadermisa, izražaj limfocita T i makrofaga u vezivu koriuma oba soja ispitivanih životinja, te enzimska aktivnost serumske DPP IV/CD26 kod CD57BL/6soja tijekom procesa cijeljenja rana. Rezultati dobiveni ovim istraživanjem ukazuju na relativno uspješniji proces cijeljenja rana kože u uvjetima nedostatka DPP IV/CD26 i razvijenog dijabetesa. Stupanj regeneracije koriuma kod CD26-/- miševa statistički značajno je veći (p<0,05) u odnosu na C57BL/6 miševe kao i broj Ki67 pozitivnih stanica, što upućuje na pojačanu proliferaciju stanica veziva uz obnovu ekstracelularnog matriksa u uvjetima nedostatka CD26. Izražaj limfocita T statistički je značajno veći (p<0,05) kod divljeg tipa životinja što ukazuje da je upalna faza manje izražena kod CD26-/- životinja. Porast izražaja makrofaga bio je brži i intenzivniji u uvjetima nedostatka CD26. Aktivnost serumske DPP IV/CD26 kodC57BL/6 miševa u uvjetima hiperglikemije je statistički značajno veća (p<0,05) u usporedbi s fiziološkim uvjetima dok je tijekom procesa cijeljenja rana značajno snižena drugog i četvrtog dana od indukcije rana. Zaključak: Dobiveni rezultati potvrđuju pretpostavku kako molekula DPP IV/CD26 utječe na intenzitet i dinamiku cijeljenja rana kao i specifičnost imunosnog odgovora u uvjetima eksperimentalne hiperglikemije. Pokazano je da je kod CD26-/- miševa upalni odgovor manje izražen nego kod divljeg tipa miševa. Proces regeneracije i reparacije tkiva u uvjetima hiperglikemije uspješniji je kod nedostatka DPP IV/CD26 što potvrđuje važnost inhibitora ove molekule u terapijske svrhe kod oboljelih od dijabetesa.Introduction: Dipeptidyl peptidase IV (DPP IV/CD26) is a multifunctional protein with a significant proteolytic and costimulatory role, thus affecting the process of proliferation, angiogenesis, adhesion, migration and apoptosis of cells in the wound healing process. It is also involved in the regulation of blood glucose concentrations by modulating the biological activity of incretins. However, the pathophysiological processes of wound healing in diabetes are not sufficiently clarified. The hypothesis of this study is that DPP IV/CD26 plays an important role in modulating the immune response in the wound healing process in conditions of hyperglycemia. The aim of this study was to determine whether DPP IV/CD26 deficiency affects macroscopic and/or microscopic changes during cutaneous wound healing process in diabetes. We aimed to determine the expression of macrophages and lymphocytes T in CD26 deficient and wild-type animals with induced diabetes and to investigate changes in serum DPP IV/CD26 activity during the development of experimental hyperglycemia and during the wound healing process in C57BL/6 animals. Materials and Methods: A model of diabetes was induced in CD26 deficient (CD26-/-) and wild type (C57BL/6) mice by intraperitoneal administration of a streptozotocin solution in citrate buffer at a dose of 50 mg/kg for five days. After the induction of diabetes, six experimental wounds (5 mm in diameter) were induced on the interscapular dorsal part of animals. Groups of experimental animals were sacrificed the second, fourth, seventh, tenth and fifteenth day of wound healing. Different methods of analysis were used for macroscopic and microscopic examinations (pathohistological, imunohistochemical, histomorphometrical and spectrophotometrical methods). The degree of regeneration of different skin layers, the degree of proliferation of the basal layer of epidermis and fibroblasts of the dermis, and the expression of lymphocytes T and macrophages in wound tissues of both mice strains were determined. Likewise, serum DPP IV/CD26 activity during the wound healing process in C57BL/6 mice was analyzed. The results of this study indicate a relatively more successful skin wound healing process under conditions of DPP IV/CD26 deficiency in diabetes. The rate of tissue regeneration in CD26-/- mice was statistically significantly higher (p<0.05) than in C57BL/6 mice as well as the number of Ki67 positive cells, indicating an increase drate of cell proliferation and regeneration of extracellular matrix in conditions of CD26 deficiency. The number of lymphocytes T is statistically significantly higher (p<0.05) in wild type mice indicating that the inflammatory phase is less pronounced in CD26-/-animals. The increase in macrophage expression was faster and more intense in the absence of DPP IV/CD26. The activity of serum DPP IV / CD26 in C57BL/6 diabetic mice was statistically significantly higher (p<0.05) compared to physiological conditions while it was significantly decreased the second and fourthday of wound healing. Conclusion: Obtained results confirm the hypothesis that DPP IV/CD26 influences the intensity and dynamics of wound healing as well as the specificity of the immune response in experimental hyperglycemic conditions. It has been shown that CD26-/-mice show a less pronounced inflammation response than wild type mice. The process of tissue regeneration and reparation in hyperglycemia is more successful in conditions of DPP IV/CD26 deficiency, which confirms the importance of inhibitors of this molecule for therapeutic purposes in patients with diabetes