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Abstract The current investigation aimed to develop a novel approach for risk prediction modeling of clinical outcomes in common diseases based on computational and human intelligence techniques with no a priori input on risk factors using real-world individual patient-level data from administrative claims. Bootstrapping multivariable Cox regression and ant colony optimization were employed to develop time-to-first-event risk prediction models of cardio-renal outcomes in patients with non-diabetic chronic kidney disease (CKD) as a demonstration case. A cohort of 504,924 non-diabetic CKD stage 3 or 4 patients enrolled from 2008 to 2018 were identified in the US administrative de-identified claims database, Optum Clinformatics® Data Mart. Initial set of potential risk factors was derived from patient-level data at baseline and included more than 540,000 variables. Risk prediction models of hospitalization for heart failure, worsening of CKD stage from baseline and a renal composite outcome of end-stage kidney disease, kidney failure or need for dialysis in non-diabetic CKD stage 3 or 4 were built. Final model optimization was conducted using human intelligence to combine clinically similar features and build equivalence classes to ensure that risk factors included in the final model were routinely collected and easily interpretable by healthcare providers. Demonstrated validity of our approach in non-diabetic CKD offers opportunities for application in other therapeutic areas, with the potential to improve overall prognosis and decrease the clinical and economic burden of common diseases. The approach enables developing practical prediction models for risk estimation in routine clinical practice.

Rationale & Objective: Estimates of the incidence of hyperkalemia in patients with chronic kidney disease (CKD) vary widely. Our objective was to estimate hyperkalemia incidence in patients with CKD from routine clinical care, including by level of kidney damage or function and among important patient subgroups. Study Design: Retrospective cohort study. Setting & Participants: 1,771,900 patients with stage 1-4 CKD identified from the US Optum De-Identified electronic health records database. Exposures or Predictors: Impaired kidney damage or function level at baseline based on urinary albumin-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR), respectively, and selected patient subgroups. Outcomes: Hyperkalemia: 2 elevated serum potassium values (≥5.5 mmol/L) from the inpatient setting (2-24 hours apart) or outpatient setting (maximum 7 days apart), or 1 elevated serum potassium value plus pharmacotherapy initiation or hyperkalemia diagnosis (maximum 3 days apart). Analytical Approach: Incidence rates of hyperkalemia were calculated. Estimates were stratified by UACR and eGFR level at baseline and patient subgroups. Results: Over a mean follow-up of 3.9 years, the incidence of hyperkalemia was 3.37 events/100 person-years (95% confidence intervals, 3.36-3.38). Higher incidence rates were observed with increased UACR and lower eGFR. Highest rates were observed with UACR ≥3,500 (up to 19.1/100 person-years) irrespective of decreased eGFR level. High rates also occurred in patients with type 2 diabetes mellitus (T2DM, 5.43/100 person-years), heart failure (8.7/100 person-years), and those prescribed steroidal mineralocorticoid receptor antagonists (sMRAs, 7.7/100 person-years). Limitations: Potential misclassification of variables from possible medical coding errors; potential data incompleteness issues if patients received care at institutions not included in Optum. Conclusions: Hyperkalemia is a frequent occurrence in CKD, particularly in patients with T2DM, heart failure, or prescribed sMRAs, indicating the need for regular serum potassium and UACR monitoring in this patient population to help mitigate risk. Plain-Language Summary: People with chronic kidney disease (CKD) have a higher risk of illness, hospitalization, and death than those without CKD. Medicines that are commonly used to slow down CKD progression can sometimes lead to hyperkalemia, where levels of potassium in the blood are higher than normal and which can be potentially dangerous. Concerns about hyperkalemia have led some people with CKD to stop taking their medication. Our study of 1.7 million patients from the United States found that patients with severe kidney damage, as well as those with type 2 diabetes mellitus or heart failure, have a higher risk of hyperkalemia than other patients, indicating they are priority groups for having their potassium levels and level of kidney damage checked regularly.

BackgroundMono and combined reactivation of latent viruses occurs frequently under immunosuppressive therapy in kidney transplant patients. Recently, monitoring torque teno virus (TTV) reactivation came more into focus as a potential biomarker for immune status. The surrogate characteristics of TTV reactivation on acute rejection, and the combined reactivation with other latent viruses such as cytomegalovirus (CMV), human BK virus (BKV), Epstein–Barr virus (EBV), and human herpes virus-6A (HHV-6A) on allograft function, are unknown so far.MethodsBlood samples from 93 kidney transplant recipients obtained during the first post-transplant year were analyzed for TTV/BKV/CMV/EBV/HHV-6A load. Clinical characteristics, including graft function [glomerular filtration rate (GFR)], were collected in parallel.ResultsTTV had the highest prevalence and viral loads at 100% and a mean of 5.72 copies/ml (cp/ml) (log10). We found 28.0%, 26.9%, 7.5%, and 51.6% of simultaneous reactivation of TTV with BKV, CMV, EBV, and HHV-6, respectively. These combined reactivations were not associated with a significantly reduced estimated GFR at month 12. Of interest, patients with lower TTV loads

Abstract Background A reduced amyloid-β (Aβ)42/40 peptide ratio in blood plasma represents a peripheral biomarker of the cerebral amyloid pathology observed in Alzheimer’s disease brains. The magnitude of the measurable effect in plasma is smaller than in cerebrospinal fluid, presumably due to dilution by Aβ peptides originating from peripheral sources. We hypothesized that the observable effect in plasma can be accentuated to some extent by specifically measuring Aβ1–42 and Aβ1–40 instead of AβX–42 and AβX–40. Methods We assessed the plasma AβX–42/X–40 and Aβ1–42/1–40 ratios in an idealized clinical sample by semi-automated Aβ immunoprecipitation followed by closely related sandwich immunoassays. The amyloid-positive and amyloid-negative groups (dichotomized according to Aβ42/40 in cerebrospinal fluid) were compared regarding the median difference, mean difference, standardized effect size (Cohen’s d) and receiver operating characteristic curves. For statistical evaluation, we applied bootstrapping. Results The median Aβ1–42/1–40 ratio was 20.86% lower in amyloid-positive subjects than in the amyloid-negative group, while the median AβX–42/X–40 ratio was only 15.56% lower. The relative mean difference between amyloid-positive and amyloid-negative subjects was −18.34% for plasma Aβ1–42/1–40 compared to −15.50% for AβX–42/X–40. Cohen’s d was 1.73 for Aβ1–42/1–40 and 1.48 for plasma AβX–42/X–40. Unadjusted p-values

Abstract Background Measurements of the amyloid-β (Aβ) 42/40 ratio in blood plasma may support the early diagnosis of Alzheimer’s disease and aid in the selection of suitable participants in clinical trials. Here, we compared the diagnostic performance of fully automated prototype plasma Aβ42/40 assays with and without pre-analytical sample workup by immunoprecipitation. Methods A pre-selected clinical sample comprising 42 subjects with normal and 38 subjects with low cerebrospinal fluid (CSF) Aβ42/40 ratios was studied. The plasma Aβ42/40 ratios were determined with fully automated prototype Elecsys® immunoassays (Roche Diagnostics GmbH, Penzberg, Germany) by direct measurements in EDTA plasma or after pre-analytical Aβ immunoprecipitation. The diagnostic performance for the detection of abnormal CSF Aβ42/40 was analyzed by receiver operating characteristic (ROC) analysis. In an additional post hoc analysis, a biomarker-supported clinical diagnosis was used as a second endpoint. Results Pre-analytical immunoprecipitation resulted in a significant increase in the area under the ROC curve (AUC) from 0.73 to 0.88 (p = 0.01547) for identifying subjects with abnormal CSF Aβ42/40. A similar improvement in the diagnostic performance by pre-analytical immunoprecipitation was also observed when a biomarker-supported clinical diagnosis was used as a second endpoint (AUC increase from 0.77 to 0.92, p = 0.01576). Conclusions Our preliminary observations indicate that pre-analytical Aβ immunoprecipitation can improve the diagnostic performance of plasma Aβ assays for detecting brain amyloid pathology. The findings may aid in the further development of blood-based immunoassays for Alzheimer’s disease ultimately suitable for screening and routine use.

Human herpesvirus 6 (HHV-6) is a common opportunistic pathogen in kidney transplant recipients. Two distinct species of HHV-6, HHV-6A and HHV-6B, have been identified, of which the latter seems to be dominant. However, it is unclear whether they increase the likelihood of other viral reactivations. We characterized a multi-centre cohort of 93 patients along nine study visits for viral load. We tested for the following viruses: HHV-6A and HHV-6B, the herpesviruses cytomegalovirus (CMV) and Epstein-Barr virus (EBV) and the polyomavirus BK (BKV). We detected HHV-6A viral load in 48 (51.6%) patients, while the incidence of HHV-6B was much lower, being detected in 6 (6.5%) patients. The incidence of HHV-6A was higher than of BKV, CMV and EBV. HHV-6A also demonstrated higher viral loads than the rest of viruses. There was a non-significant trend of association between HHV-6A and HHV-6B as co-infection, whereas no increased incidence of other viruses among patients with HHV-6A reactivation was observed. There was no negative effect of high HHV-6A (>10,000 copies/ml) load on markers of renal graft and hepatic function or blood count twelve months post-transplant. In contrast to previously published data, our results show a clear dominance of HHV-6A in peripheral blood when compared to HHV-6B, with higher incidence and viral load levels. Despite the high HHV-6A loads observed, we did not identify any negative effects on posttransplant outcome.

Abstract Background There is a huge body of scientific literature describing the relation between tumor types and anti-cancer drugs. The vast amount of scientific literature makes it impossible for researchers and physicians to extract all relevant information manually. Methods In order to cope with the large amount of literature we applied an automated text mining approach to assess the relations between 30 most frequent cancer types and 270 anti-cancer drugs. We applied two different approaches, a classical text mining based on named entity recognition and an AI-based approach employing word embeddings. The consistency of literature mining results was validated with 3 independent methods: first, using data from FDA approvals, second, using experimentally measured IC-50 cell line data and third, using clinical patient survival data. Results We demonstrated that the automated text mining was able to successfully assess the relation between cancer types and anti-cancer drugs. All validation methods showed a good correspondence between the results from literature mining and independent confirmatory approaches. The relation between most frequent cancer types and drugs employed for their treatment were visualized in a large heatmap. All results are accessible in an interactive web-based knowledge base using the following link: https://knowledgebase.microdiscovery.de/heatmap . Conclusions Our approach is able to assess the relations between compounds and cancer types in an automated manner. Both, cancer types and compounds could be grouped into different clusters. Researchers can use the interactive knowledge base to inspect the presented results and follow their own research questions, for example the identification of novel indication areas for known drugs.

Abstract Background Acute cellular rejection (ACR) is associated with complications after kidney transplantation, such as graft dysfunction and graft loss. Early risk assessment is therefore critical for the improvement of transplantation outcomes. In this work, we retrospectively analyzed a pre-transplant HLA antigen bead assay data set that was acquired by the e:KID consortium as part of a systems medicine approach. Results The data set included single antigen bead (SAB) reactivity profiles of 52 low-risk graft recipients (negative complement dependent cytotoxicity crossmatch, PRA

Post-transplantation cytomegalovirus (CMV) syndrome can be prevented using the antiviral drug (val)ganciclovir. (Val)ganciclovir is typically administered following a prophylactic or a pre-emptive strategy. The prophylactic strategy entails early universal administration, the pre-emptive strategy, early treatment in case of infection. However, it is not clear which strategy is superior with respect to transplantation outcome; sex-specific effects of these prevention strategies are not known. We have retrospectively analyzed 540 patients from the multi-centre Harmony study along eight pre-defined visits: 308 were treated according to a prophylactic, 232 according to a pre-emptive strategy. As expected, we observed an association of prophylactic strategy with lower incidence of CMV syndrome, delayed onset and lower viral loads compared to the pre-emptive strategy. However, in female patients, the prophylactic strategy was associated with a strong impairment of glomerular filtration rate one year post-transplant (difference: −11.8 ± 4.3 ml min−1·1.73 m−2, p = 0.006). Additionally, we observed a tendency of higher incidence of acute rejection and severe BK virus reactivation in the prophylactic strategy group. While the prophylactic strategy was more effective for preventing CMV syndrome, our results suggest for the first time that the prophylactic strategy might lead to inferior transplantation outcomes in female patients, providing evidence for a strong association with sex. Further randomized controlled studies are necessary to confirm this potential negative effect.

Abstract Background The quantification of amyloid-beta (Aβ) peptides in blood plasma as potential biomarkers of Alzheimer’s disease (AD) is hampered by very low Aβ concentrations and the presence of matrix components that may interfere with the measurements. Methods We developed a two-step immunoassay for the simultaneous measurement of the relative levels of Aβ38, Aβ40 and Aβ42 in human EDTA plasma. The assay was employed for the study of 23 patients with dementia of the Alzheimer’s type (AD-D) and 17 patients with dementia due to other reasons (OD). We examined relationships with the clinical diagnosis, cerebral Aβ load as quantified by amyloid-positron emission tomography, apolipoprotein E genotype, Aβ levels and Tau protein in cerebrospinal fluid. Results Preconcentration of plasma Aβ peptides by immunoprecipitation substantially facilitated their immunological measurements. The Aβ42/Aβ40 and Aβ42/Aβ38 ratios were statistically significantly lower in the AD-D patients than in the OD group. The areas under the receiver operating characteristic curves reached 0.87 for the Aβ42/Aβ40 ratio and 0.80 for the Aβ42/Aβ38 ratio. Conclusions The measurement of plasma Aβ peptides with an immunological assay can be improved by preconcentration via immunoprecipitation with an antibody against the Aβ amino-terminus and elution of the captured peptides by heating in a mild detergent-containing buffer. Our findings support the Aβ42/Aβ40 ratio in blood plasma as a promising AD biomarker candidate which correlates significantly with the validated core biomarkers of AD. Further studies will be needed for technical advancement of the assay and validation of the biomarker findings.

Background: BK virus (BKV), Cytomegalovirus (CMV) and Epstein-Barr virus (EBV) reactivations are common after kidney transplantation and associated with increased morbidity and mortality. Although CMV might be a risk factor for BKV and EBV, the effects of combined reactivations remain unknown. The purpose of this study is to ascertain the interaction and effects on graft function of these reactivations. Methods: 3715 serum samples from 540 kidney transplant recipients were analysed for viral load by qPCR. Measurements were performed throughout eight visits during the first post-transplantation year. Clinical characteristics, including graft function (GFR), were collected in parallel. Findings: BKV had the highest prevalence and viral loads. BKV or CMV viral loads over 10,000 copies·mL−1 led to significant GFR impairment. 57 patients had BKV-CMV combined reactivation, both reactivations were significantly associated (p = 0.005). Combined reactivation was associated with a significant GFR reduction one year post-transplantation of 11.7 mL·min−1·1.73 m−2 (p = 0.02) at relatively low thresholds (BKV > 1000 and CMV > 4000 copies·mL−1). For EBV, a significant association was found with CMV reactivation (p = 0.02), but no GFR reduction was found. Long cold ischaemia times were a further risk factor for high CMV load. Interpretation: BKV-CMV combined reactivation has a deep impact on renal function one year post-transplantation and therefore most likely on long-term allograft function, even at low viral loads. Frequent viral monitoring and subsequent interventions for low BKV and/or CMV viraemia levels and/or long cold ischaemia time are recommended. Fund: Investigator Initiated Trial; financial support by German Federal Ministry of Education and Research (BMBF). Keywords: BK virus, Cytomegalovirus, Epstein-Barr virus, Kidney transplantation, Graft function, Combined reactivation

Abstract Background The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. Methods We used 115 complete datasets from MCI patients of the “Dementia Competence Network”, a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Results Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. Conclusion A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.

BACKGROUND: Different immunotherapy approaches for the treatment of cancer and autoimmune diseases are being developed and tested in clinical studies worldwide. Their resulting complex experimental data should be properly evaluated, therefore reliable normal healthy control baseline values are indispensable. METHODOLOGY/PRINCIPAL FINDINGS: To assess intra- and inter-individual variability of various biomarkers, peripheral blood of 16 age and gender equilibrated healthy volunteers was sampled on 3 different days within a period of one month. Complex "crossomics" analyses of plasma metabolite profiles, antibody concentrations and lymphocyte subset counts as well as whole genome expression profiling in CD4+T and NK cells were performed. Some of the observed age, gender and BMI dependences are in agreement with the existing knowledge, like negative correlation between sex hormone levels and age or BMI related increase in lipids and soluble sugars. Thus we can assume that the distribution of all 39.743 analysed markers is well representing the normal Caucasoid population. All lymphocyte subsets, 20% of metabolites and less than 10% of genes, were identified as highly variable in our dataset. CONCLUSIONS/SIGNIFICANCE: Our study shows that the intra-individual variability was at least two-fold lower compared to the inter-individual one at all investigated levels, showing the importance of personalised medicine approach from yet another perspective.

Multi-metal nanoparticles, particularly alloys and intermetallic compounds, are useful catalysts for a variety of chemical transformations. Supported intermetallic nanoparticle catalysts are usually prepared by depositing precursors onto a support followed by high-temperature annealing, which is necessary to generate the intermetallic compound but causes sintering and minimizes surface area. Here we show that solution chemistry methods for converting metal nanoparticles into intermetallic compounds are applicable to supported nanoparticle catalyst systems. Unsupported nanocrystalline Pt can be converted to nanocrystalline PtSn, PtPb, PtBi, and FePt3 by reaction with appropriate metal salt solutions under reducing conditions. Similar reactions convert Al2O3, CeO2, and carbon-supported Pt nanoparticles into PtSn, PtPb, PtSb, Pt3Sn, and Cu3Pt. These reactions generate supported alloy and intermetallic nanoparticles directly in solution without the need for high temperature annealing or additional surface stabilizers. These supported intermetallic nanoparticles are catalytically active for chemical transformations such as formic acid oxidation (PtPb/Vulcan) and CO oxidation (Pt3Sn/graphite). Notably, PtPb/Vulcan XC-72 was found to electrocatalytically oxidize formic acid at a lower onset potential (0.1 V) than commercial PtRu/Vulcan XC-72 (0.4 V). [ABSTRACT FROM AUTHOR]

Abstract: The concept of nanocrystal conversion chemistry, which involves the use of pre-formed nanoparticles as templates for chemical transformation into derivative solids, has emerged as a powerful approach for designing the synthesis of complex nanocrystalline solids. The general strategy exploits established synthetic capabilities in simple nanocrystal systems and uses these nanocrystals as templates that help to define the composition, crystal structure, and morphology of product nanocrystals. This article highlights key examples of “conversion chemistry” approaches to the synthesis of nanocrystalline solids using a variety of techniques, including galvanic replacement, diffusion, oxidation, and ion exchange. The discussion is organized according to classes of solids, highlighting the diverse target systems that are accessible using similar chemical concepts: metals, oxides, chalcogenides, phosphides, alloys, intermetallic compounds, sulfides, and nitrides. [Copyright &y& Elsevier]