Retrospective analysis of the long-term therapeutic effectiveness and safety profile of rituximab in the treatment of mucous membrane pemphigoid in a German university center between 2008 and 2019.

Background: The B-cell-depleting anti-CD20 antibody rituximab (RTX) is often used as an adjuvant drug for the treatment of refractory cases of mucous membrane pemphigoid (MMP).

Objective: This study aims to determine the therapeutic effectiveness and the safety profile of RTX in MMP.

Methods: The medical records of all cases of MMP treated with RTX between 2008 and 2019 in our university medical center located in northern Germany, which specialized in autoimmune blistering skin diseases, were retrieved and systemically analyzed for treatment responses and potential adverse events over a median period of 27 months.

Evaluation of a Wearable in-Ear Sensor for Temperature and Heart Rate Monitoring: A Pilot Study.

In the context of the COVID-19 pandemic, wearable sensors are important for early detection of critical illness especially in COVID-19 outpatients. We sought to determine in this pilot study whether a wearable in-ear sensor for continuous body temperature and heart rate monitoring (Cosinuss company, Munich) is sufficiently accurate for body temperature and heart rate monitoring. Comparing with several anesthesiologic standard of care monitoring devices (urinary bladder and zero-heat flux thermometer and ECG), we evaluated the in-ear sensor during non-cardiac surgery (German Clinical Trials Register Reg.

Assessment of Imputation Quality: Comparison of Phasing and Imputation Algorithms in Real Data.

Despite the widespread use of genotype imputation tools and the availability of different approaches, late developments of currently used programs have not been compared comprehensively. We therefore assessed the performance of 35 combinations of phasing and imputation programs, including versions of SHAPEIT, Eagle, Beagle, minimac, PBWT, and IMPUTE, for genetic imputation of completely missing SNPs with a HRC reference panel regarding quality and speed. We used a data set comprising 1,149 fully sequenced individuals from the German population, subsetting the SNPs to approximate the Illumina Infinium-Omni5 array.

Antimicrobial and dye degradation application of fungi-assisted silver nanoparticles and utilization of fungal retentate biomass for dye removal.

The present study utilized Aspergillus spp. for the synthesis of silver nanoparticles (AgNPs); the developed AgNPs were categorized using analytical techniques, that is, ultraviolet-visible (UV-vis) spectrophotometer, Zeta-potential, dynamic light scattering (DLS), and transmission electron microscopy (TEM). A sharp peak of 463 nm highlighted the synthesis of AgNPs; further Zeta-potential of -16 mV indicates stability of synthesized AgNPs.

Identification of two novel bullous pemphigoid- associated alleles, HLA-DQA1*05:05 and -DRB1*07:01, in Germans.

Bullous pemphigoid (BP) is the most common autoimmune skin blistering disease characterized by autoimmunity against the hemidesmosomal proteins BP180, type XVII collagen, and BP230. To elucidate the genetic basis of susceptibility to BP, we performed the first genome-wide association study (GWAS) in Germans. This GWAS was combined with HLA locus targeted sequencing in an additional independent BP cohort.

Current Developments of Clinical Sequencing and the Clinical Utility of Polygenic Risk Scores in Inflammatory Diseases.

In this mini-review, we highlight selected research by the Deutsche Forschungsgemeinschaft (DFG) Cluster of Excellence "Precision Medicine in Chronic Inflammation" focusing on clinical sequencing and the clinical utility of polygenic risk scores as well as its implication on precision medicine in the field of the inflammatory diseases inflammatory bowel disease, atopic dermatitis and coronary artery disease. Additionally, we highlight current developments and discuss challenges to be faced in the future. Exemplary, we point to residual challenges in detecting disease-relevant variants resulting from difficulties in the interpretation of candidate variants and their potential interactions.

Empowering individual trait prediction using interactions for precision medicine.

Background: One component of precision medicine is to construct prediction models with their predicitve ability as high as possible, e.g. to enable individual risk prediction.

Incidence of pemphigoid diseases in Northern Germany in 2016 - first data from the Schleswig-Holstein Registry of Autoimmune Bullous Diseases.

Background: Autoimmune bullous diseases (AIBD) are rare disorders characterized by autoantibody formation against components of adhesion molecules; in pemphigoid diseases (PD), these are proteins of hemidesmosomes and basement membrane, important for cell-matrix adhesion in skin and/or mucous membranes. Incidences of these diseases vary considerably between different populations.

Objectives: To establish a registry prospectively recruiting all AIBD patients in a geographically well-defined region in Northern Germany (Schleswig-Holstein).

Decolourization of textile effluent using native microbial consortium enriched from textile industry effluent.

A robust and efficient treatment process is required to address the problem of residual colour and avoid expensive post-treatment steps while dealing with textile effluents. In the present work, a novel microbial consortium enriched from textile effluent was used to optimize the process of decolourization under extreme conditions with minimum inputs. With PreTreatment Range (PTR) effluent as a carbon source and only 0.

Population Bias in Polygenic Risk Prediction Models for Coronary Artery Disease.

Background: Individual risk prediction based on genome-wide polygenic risk scores (PRSs) using millions of genetic variants has attracted much attention. It is under debate whether PRS models can be applied-without loss of precision-to populations of similar ethnic but different geographic background than the one the scores were trained on. Here, we examine how PRS trained in population-specific but European data sets perform in other European subpopulations in distinguishing between coronary artery disease patients and healthy individuals.

Synthesis of silver nanoparticles utilizing various biological systems: mechanisms and applications-a review.

The evolving technology of nanoparticle synthesis, especially silver nanoparticle (AgNPs) has already been applied in various fields i.e., electronics, optics, catalysis, food, health and environment.

Assessment of Drain Water Used for Irrigation in the Delhi Region.

Background: Industries such as electroplating, mining and battery production are major sources of heavy metal-rich waste entering nearby water bodies. Irrigation with heavy metal contaminated water can deteriorate soil quality as well as agricultural produce and have further toxic effects on human health.

Objectives: The objective of the present study was to estimate the concentration of hazardous heavy metals such as chromium (Cr), cadmium (Cd), copper (Cu), nickel (Ni), zinc (Zn) and lead (Pb), as well as physico-chemical variables (pH, electrical conductivity, total dissolved solids, chemical oxygen demand and dissolved oxygen) at sampling locations along the Najafgarh and Loha mandi drains in Delhi, National Capital Region, India.

Polygenic risk scores outperform machine learning methods in predicting coronary artery disease status.

Coronary artery disease (CAD) is the leading global cause of mortality and has substantial heritability with a polygenic architecture. Recent approaches of risk prediction were based on polygenic risk scores (PRS) not taking possible nonlinear effects into account and restricted in that they focused on genetic loci associated with CAD, only. We benchmarked PRS, (penalized) logistic regression, naïve Bayes (NB), random forests (RF), support vector machines (SVM), and gradient boosting (GB) on a data set of 7,736 CAD cases and 6,774 controls from Germany to identify the algorithms for most accurate classification of CAD status.

Polymorphisms in the Mitochondrial Genome Are Associated With Bullous Pemphigoid in Germans.

Bullous pemphigoid (BP) is the most prevalent autoimmune skin blistering disease and is characterized by the generation of autoantibodies against the hemidesmosomal proteins BP180 (type XVII collagen) and BP230. Most intriguingly, BP is distinct from other autoimmune diseases because it predominantly affects elderly individuals above the age of 75 years, raising the question why autoantibodies and the clinical lesions of BP emerges mostly in this later stage of life, even in individuals harboring known putative BP-associated germline gene variants. The mitochondrial genome (mtDNA) is a potential candidate to provide additional insights into the BP etiology; however, the mtDNA has not been extensively explored to date.

Performance evaluation of two Aspergillus spp. for the decolourization of reactive dyes by bioaccumulation and biosorption.

A biological method was adopted to decolourize textile dyes, which is an economic and eco-friendly technology for textile wastewater remediation. Two fungal strains, i.e.

Preprocessing and Quality Control for Whole-Genome Sequences from the Illumina HiSeq X Platform.

The advancement of high-throughput sequencing technologies enables sequencing of human genomes at steadily decreasing costs and increasing quality. Before variants can be analyzed, e.g.

Removal of industrial dyes and heavy metals by Beauveria bassiana: FTIR, SEM, TEM and AFM investigations with Pb(II).

Presence of industrial dyes and heavy metal as a contaminant in environment poses a great risk to human health. In order to develop a potential technology for remediation of dyes (Reactive remazol red, Yellow 3RS, Indanthrene blue and Vat novatic grey) and heavy metal [Cu(II), Ni(II), Cd(II), Zn(II), Cr(VI) and Pb(II)] contamination, present study was performed with entomopathogenic fungi, Beauveria bassiana (MTCC no. 4580).

Identification of interactions using model-based multifactor dimensionality reduction.

Background: Common complex traits may involve multiple genetic and environmental factors and their interactions. Many methods have been proposed to identify these interaction effects, among them several machine learning and data mining methods. These are attractive for identifying interactions because they do not rely on specific genetic model assumptions.

Comparative performance evaluation of multi-metal resistant fungal strains for simultaneous removal of multiple hazardous metals.

In the present study, five fungal strains viz., Aspergillus terreus AML02, Paecilomyces fumosoroseus 4099, Beauveria bassiana 4580, Aspergillus terreus PD-17, Aspergillus fumigatus PD-18, were screened for simultaneous multimetal removal. Highest metal tolerance index for each individual metal viz.

Multiple heavy metal removal using an entomopathogenic fungi Beauveria bassiana.

Towards the development of a potential remediation technology for multiple heavy metals [Zn(II), Cu(II), Cd(II), Cr(VI) and Ni(II)] from contaminated water, present study examined the growth kinetics and heavy metal removal ability of Beauveria bassiana in individual and multi metals. The specific growth rate of B. bassiana varied from 0.

Machine learning and data mining in complex genomic data--a review on the lessons learned in Genetic Analysis Workshop 19.

In the analysis of current genomic data, application of machine learning and data mining techniques has become more attractive given the rising complexity of the projects. As part of the Genetic Analysis Workshop 19, approaches from this domain were explored, mostly motivated from two starting points. First, assuming an underlying structure in the genomic data, data mining might identify this and thus improve downstream association analyses.

A roadmap to multifactor dimensionality reduction methods.

Complex diseases are defined to be determined by multiple genetic and environmental factors alone as well as in interactions. To analyze interactions in genetic data, many statistical methods have been suggested, with most of them relying on statistical regression models. Given the known limitations of classical methods, approaches from the machine-learning community have also become attractive.

Dysregulation of microRNAs in angioimmunoblastic T-cell lymphoma.

Background: Angioimmunoblastic T-cell lymphomas (AITLs) are the second most frequent peripheral T-cell lymphomas in humans worldwide and histomorphologically well characterized. MicroRNAs are a group of small non-coding RNAs that can negatively regulate gene expression on a posttranscriptional level. Their dysregulation has been shown to be of importance in numerous tumour entities.

Assessment of Yamuna and associated drains used for irrigation in rural and peri-urban settings of Delhi NCR.

The present study assessed the quality of Yamuna River and the Najafgarh drain water for irrigational purposes in the Delhi region in terms of spatial variations in the physicochemical characteristics as well as heavy metal concentrations. The monitoring was done for the period July 2012-August 2013 representing pre-monsoon, monsoon, and post-monsoon sessions and considering six physicochemical parameters. Heavy metals such as cadmium, chromium, copper, nickel, zinc, and lead have been found in the river due to rampant discharge of industrial effluents into the river.

Bone turnover in hyperthyroidism before and after thyrostatic management.

Hyperthyroidism is associated with enhanced osteoblastic and osteoclastic activity, and patients frequently have low bone mineral density and high bone turnover. The aim of this study was to examine the bone formation and resorption markers trend in 12 female patients, before and after normalization of thyroid activity. The following measurements were made at baseline and 1 and 6 months after hormone normalization induced by methimazole treatment: total alkaline phosphatase (ALP), bone alkaline phosphatase (BALP), collagen type C-terminal propeptide (PICP), osteocalcin (BGP), telopeptide (ICTP), urinary-hydroxyproline/urinary creatinine (uOHP/uCreat), urinary calcium/urinary creatinine (uCa/uCreat) and deoxypyridinoline crosslinks (D-Pyr).