Vadim Demichev

Bio: Vadim Demichev is an academic researcher from Francis Crick Institute. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 9, co-authored 22 publications receiving 482 citations. Previous affiliations of Vadim Demichev include University of Cambridge & Humboldt University of Berlin.

DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput.

Abstract: We present an easy-to-use integrated software suite, DIA-NN, that exploits deep neural networks and new quantification and signal correction strategies for the processing of data-independent acquisition (DIA) proteomics experiments. DIA-NN improves the identification and quantification performance in conventional DIA proteomic applications, and is particularly beneficial for high-throughput applications, as it is fast and enables deep and confident proteome coverage when used in combination with fast chromatographic methods.

Ultra-High-Throughput Clinical Proteomics Reveals Classifiers of COVID-19 Infection.

Abstract: The COVID-19 pandemic is an unprecedented global challenge, and point-of-care diagnostic classifiers are urgently required. Here, we present a platform for ultra-high-throughput serum and plasma proteomics that builds on ISO13485 standardization to facilitate simple implementation in regulated clinical laboratories. Our low-cost workflow handles up to 180 samples per day, enables high precision quantification, and reduces batch effects for large-scale and longitudinal studies. We use our platform on samples collected from a cohort of early hospitalized cases of the SARS-CoV-2 pandemic and identify 27 potential biomarkers that are differentially expressed depending on the WHO severity grade of COVID-19. They include complement factors, the coagulation system, inflammation modulators, and pro-inflammatory factors upstream and downstream of interleukin 6. All protocols and software for implementing our approach are freely available. In total, this work supports the development of routine proteomic assays to aid clinical decision making and generate hypotheses about potential COVID-19 therapeutic targets.

Ultra-fast proteomics with Scanning SWATH.

Abstract: Accurate quantification of the proteome remains challenging for large sample series and longitudinal experiments. We report a data-independent acquisition method, Scanning SWATH, that accelerates mass spectrometric (MS) duty cycles, yielding quantitative proteomes in combination with short gradients and high-flow (800 µl min-1) chromatography. Exploiting a continuous movement of the precursor isolation window to assign precursor masses to tandem mass spectrometry (MS/MS) fragment traces, Scanning SWATH increases precursor identifications by ~70% compared to conventional data-independent acquisition (DIA) methods on 0.5-5-min chromatographic gradients. We demonstrate the application of ultra-fast proteomics in drug mode-of-action screening and plasma proteomics. Scanning SWATH proteomes capture the mode of action of fungistatic azoles and statins. Moreover, we confirm 43 and identify 11 new plasma proteome biomarkers of COVID-19 severity, advancing patient classification and biomarker discovery. Thus, our results demonstrate a substantial acceleration and increased depth in fast proteomic experiments that facilitate proteomic drug screens and clinical studies.

A time-resolved proteomic and prognostic map of COVID-19.

Abstract: COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.

Complement activation induces excessive T cell cytotoxicity in severe COVID-19

Abstract: Severe COVID-19 is linked to both dysfunctional immune response and unrestrained immunopathogenesis, and it remains unclear if T cells contribute to disease pathology. Here, we combined single-cell transcriptomics and proteomics with mechanistic studies assessing pathogenic T cell functions and inducing signals. We identified activated, CD16+ T cells with increased cytotoxic functions in severe COVID-19. CD16 expression enabled immune complex-mediated, T cell receptor-independent degranulation and cytotoxicity not found in other diseases. CD16+ T cells from COVID-19 patients promoted microvascular endothelial cell injury and release of neutrophil and monocyte chemoattractants. CD16+ T cell clones persisted beyond acute disease maintaining their cytotoxic phenotype. Age-dependent generation of C3a in severe COVID-19 induced activated CD16 + cytotoxic T cells. The proportion of activated CD16+ T cells and plasma levels of complement proteins upstream of C3a correlated with clinical outcome, supporting a pathological role of exacerbated cytotoxicity and complement activation in COVID-19. Funding: This work was supported by the German Research Foundation (DFG): SA1383/3-1 to B.S.; SFB-TR84 114933180 to L.E.S., S.B., P.G., S.H. and W.M.K. INST 37/1049-1, INST 216/981- 1, INST 257/605-1, INST 269/768-1, INST 217/988-1, INST 217/577-1, and EXC2151- 390873048 to J.L.S.; GRK 2168 – 272482170, ERA CVD (00160389 to J.L.S.; SFB 1454 – 432325352 to A.C.A. and J.L.S.; SFB TR57 and SPP1937 to J.N.; GRK2157 to A.-E.S.; and ME 3644/5-1 to H.E.M.; RTG2424 to N.B.; SFB-TRR219 322900939, BO3755/13-1 Project- ID 454024652 to P.B.; the Berlin University Alliance (BUA) (PreEP-Corona grant to L.E.S. and V.M.C.); the Berlin Institute of Health (BIH) (to L.E.S., V.M.C.,B.S. and W.M.K.); Helmholtz- Gemeinschaft Deutscher Forschungszentren, Germany (sparse2big to J.L.S.), EU projects SYSCID (733100 to J.L.S.); European Research Council Horizon 2020 (grant agreement No 101001791 to P.B.); the DZIF, Germany (TTU 04.816 and 04.817 to J.N.); the Hector Foundation (M89 to J.N.); the EU projects ONE STUDY (260687), BIO-DrIM (305147) and INsTRuCT (860003) to B.S.); German Registry of COVID-19 Autopsies through Federal Ministry of Health (ZMVI1-2520COR201 to P.B.); Federal Ministry of Education and Research (DEFEAT PANDEMICs, 01KX2021 and STOP-FSGS-01GM1901A to P.B.); the Berlin Senate to German Rheumatism Research Centre (DRFZ); the Berlin Brandenburg School for regenerative Therapies (BSRT) to C.B.; the German Federal Ministry of Education and Research (BMBF) projects RECAST (01KI20337) to B.S., V.M.C., L.E.S and M.R.; VARIPath (01KI2021) to V.M.C.; NUM COVIM (01KX2021) to L.E.S., V.M.C., F.K., J.L.S., J.N. and B.S.; RAPID to and S.H.,; SYMPATH to N.S. and W.M.K.; PROVID to S.H. and W.M.K.; ZissTrans (02NUK047E) to N.B; National Research Node ‘Mass spectrometry in Systems Medicine (MSCoresys) (031L0220A) to M.R. and N.B.; Diet–Body–Brain (DietBB) (01EA1809A) to J.L.S.; the UKRI/NIHR through the UK Coronavirus Immunology Consortium (UK-CIC), the Francis Crick Institute through the Cancer Research UK (FC001134), the UK Medical Research Council (FC001134), the Wellcome Trust (FC001134 and IA 200829/Z/16/Z) to M.R.; a Charite 3R project (to B.S., S.H., W.M.K.); and an intramural grant from the Department of Genomics & Immunoregulation at the LIMES Institute to A.C.A. We are grateful to the patients and donors volunteering to participate in this study making this research possible in the first place and wish for a speedy and full recovery. Conflict of Interest: V.M.C. is named together with Euroimmun GmbH on a patent application filed recently regarding SARS-CoV-2 diagnostics via antibody testing. A.R.S. and H.E.M. are listed as inventors on a patent application by the DRFZ Berlin in the field of mass cytometry. Ethical Approval: The study was approved by the Institutional Review board of Charite (EA2/066/20).

Convergence of Probability Measures

Abstract: Convergence of Probability Measures. By P. Billingsley. Chichester, Sussex, Wiley, 1968. xii, 253 p. 9 1/4“. 117s.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Lévy processes and infinitely divisible distributions

Abstract: Preface to the revised edition Remarks on notation 1. Basic examples 2. Characterization and existence 3. Stable processes and their extensions 4. The Levy-Ito decomposition of sample functions 5. Distributional properties of Levy processes 6. Subordination and density transformation 7. Recurrence and transience 8. Potential theory for Levy processes 9. Wiener-Hopf factorizations 10. More distributional properties Supplement Solutions to exercises References and author index Subject index.

What is a tutorial

Abstract: There are two kinds of tutorial articles: those that provide a primer on an established topic and those that let us in on the ground floor of something of emerging importance. The first type of tutorial can have a noted expert who has been gracious (and brave) enough to write a field guide about a particular topic. The other sort of tutorial typically involves researchers who have each been laboring on a topic for some years. Both sorts of tutorial articles are very much desired. But we, as an editorial board for both Systems and Transactions, know that there has been no logical place for them in the AESS until this series was started several years ago. With these tutorials, we hope to continue to give them a home, a welcome, and provide a service to our membership. We do not intend to publish tutorials on a regular basis, but we hope to deliver them once or twice per year. We need and welcome good, useful tutorial articles (both kinds) in relevant AESS areas. If you, the reader, can offer a topic of interest and an author to write about it, please contact us. Self-nominations are welcome, and even more ideal is a suggestion of an article that the editor(s) can solicit. All articles will be reviewed in detail. Criteria on which they will be judged include their clarity of presentation, relevance, and likely audience, and, of course, their correctness and scientific merit. As to the mathematical level, the articles in this issue are a good guide: in each case the author has striven to explain complicated topics in simple-well, tutorial-terms. There should be no (or very little) novel material: the home for archival science is the Transactions Magazine, and submissions that need to be properly peer reviewed would be rerouted there. Likewise, articles that are interesting and descriptive, but lack significant tutorial content, ought more properly be submitted to the Systems Magazine.