Additional Quality Control Research Articles

DoeDat: Enhanced Roundtripping of Crowdsourced Specimen Annotations

The DoeDat platform was launched by Meise Botanic Garden in 2018 to capture label data from imaged herbarium specimens by inviting volunteer contributors (Groom et al. 2018). It has since facilitated data capture from specimens of other natural history collections (Helminger et al. 2020, Mitrache et al. 2023), as well as digitised content from various other disciplines, such as historical photographs, posters and postcards. Volunteers may simply transcribe handwritten and/or typed text, but often also interpret the sparse and scattered information on the image, including trying to georeference its original location. As of April 2024, almost 650.000 tasks have been completed, of which more than 470.000 were herbarium specimens from Meise. DoeDat supports domain standards, including Darwin Core, and follows most of the currently drafted MIDS (Minimum Information about a Digital Specimen) guidelines as to what data is captured for natural history specimens. However, images have to be pre-loaded into the server storage for each project and captured data gets exported as one or more CSV files per project. These data files then still need to be processed before they can be ingested into the local management system (Engledow et al. 2023). Often the data are also subjected to additional quality control before they get openly published. This can result in the pipeline from image to openly published annotations being quite time and labour-consuming. As the biodiversity infrastructure landscape moves more towards FAIR (Findable, Accessible, Interoperable, Reusable) open data, DoeDat will adapt accordingly. This includes digital objects that are easy to annotate. Furthermore, image servers following IIIF (International Image Interoperability Framework) greatly standardise the access and portability of media content, drastically changing the way images are being dealt with. We envision upgrading the DoeDat platform to load images and any required metadata as IIIF manifests, greatly streamlining the process of adding new content and tracking provenance. The transcriptions should be accessible for external systems, loading the updated image manifests and publishing them as annotations such as nanopublications.

The actin binding protein profilin 1 localizes inside mitochondria and is critical for their function

The monomer-binding protein profilin 1 (PFN1) plays a crucial role in actin polymerization. However, mutations in PFN1 are also linked to hereditary amyotrophic lateral sclerosis, resulting in a broad range of cellular pathologies which cannot be explained by its primary function as a cytosolic actin assembly factor. This implies that there are important, undiscovered roles for PFN1 in cellular physiology. Here we screened knockout cells for novel phenotypes associated with PFN1 loss of function and discovered that mitophagy was significantly upregulated. Indeed, despite successful autophagosome formation, fusion with the lysosome, and activation of additional mitochondrial quality control pathways, PFN1 knockout cells accumulate depolarized, dysmorphic mitochondria with altered metabolic properties. Surprisingly, we also discovered that PFN1 is present inside mitochondria and provide evidence that mitochondrial defects associated with PFN1 loss are not caused by reduced actin polymerization in the cytosol. These findings suggest a previously unrecognized role for PFN1 in maintaining mitochondrial integrity and highlight new pathogenic mechanisms that can result from PFN1 dysregulation.

The undetected murder? Evaluation and validation of a practicable and rapid inductively coupled plasma-mass spectrometry method for the detection of arsenic, lead, and thallium intoxications in postmortem blood.

Homicide, suicide, or accident - elemental intoxication may be a cause in each of these types of deaths. Inductively coupled plasma mass spectrometry (ICP-MS) has emerged as the gold standard analytical method for toxic metal analysis in both clinical and forensic settings. An ICP-MS method was developed using a modified acidic workup for the quantitative determination of arsenic, lead, and thallium. Method validation focused on the assessment of linearity, between- and within-day precisions, limits of detection (LoD) and lower limits of quantification (LLoQ), and carryover. The method was applied to analysis of postmortem peripheral blood samples from 279 forensic cases for which orders for chemical-toxicological examination had been received from the public prosecutor's office. Using six-point and one-point calibrations (latter for rapid screening purposes), precisions and accuracies ranged from -4.8 to 5.8% and -6.4 to 7.5%. Analytical sensitivities for As, Pb, and Tl were 0.08, 0.18, and 0.01 μg/l (LoD) and 0.23, 0.66, and 0.03 μg/l (LLoQ), respectively. Observed postmortem peripheral blood concentrations were As, 1.31 ± 3.42 μg/L; Pb, 17.4 ± 13.1 μg/L; and Tl, 0.11 ± 0.07 μg/L (mean ± standard deviation [SD]). Elemental concentrations, determined in additional quality control samples, were in good agreement to those obtained with an external ICP-MS method based on alkaline sample processing. The current method is practicable and compatible with an ICP-MS system used for trace element analysis in an accredited medical laboratory. It allows for implementation of low-threshold investigations when metal intoxications are suspected in forensic routine.

Optimal production and purification of n.c.a.143Pr as a promising palliative agent for the treatment of metastatic bone pain

This study proposes the beta-emitting radioisotope 143Pr as a promising candidate for palliative treatment of metastatic bone pain due to its desirable physical decay characteristics. An optimized process was developed for the production and purification of non-carrier-added 143Pr using a medium flux research reactor. Calculations were performed to determine the optimal irradiation time and cooling period for irradiating 1 mg of natural cerium oxide to indirectly produce 143Pr through the decay of 143Ce. Following irradiation and cooling, extraction chromatography was employed to efficiently isolate 143Pr from the irradiated target material. A column containing Ln-resin was used along with nitric acid as the mobile phase and an optional oxidation step with NaBrO3/ascorbic acid to separate 143Pr from impurities such as 143Ce and 141Ce. Radionuclidic purity of over 99.995% was achieved as confirmed through gamma spectroscopy, demonstrating effective separation of 143Pr. Additional quality control analyses established the chemical and radiochemical purity of the purified 143Pr nitrate product. With a half-life of 13.6 days and maximum beta energy of 0.937 MeV, 143Pr exhibits favorable properties for palliative bone pain therapy. This study therefore provides a viable method for producing high-purity 143Pr through the optimized irradiation and purification processes described. Further investigation is warranted to explore potential clinical applications of 143Pr for palliation of metastatic bone cancer pain.

The causal relationship between vitiligo and autoimmune thyroid diseases: A bidirectional two-sample Mendelian randomization analysis.

Vitiligo is an acquired autoimmune depigmented disorder characterized by the presence of white and well-defined patches on the skin, mucous membrane, or both. It is associated with a significant disease burden and has a profoundly impacts patients' quality of life. Autoimmune thyroid diseases (AITDs) result from an autoimmune system dysregulation, leading to an erroneous immune attack on the thyroid gland. Previous observational and epidemiological studies have suggested the association between vitiligo and AITDs. However, the bidirectional cause-effect relationship between vitiligo and AITDs has not been formally assessed. Two-sample bidirectional Mendelian randomization (MR) analysis was conducted to explore potential causal relationships between genetically increased risk of vitiligo and AITDs, using summary statistics from genome-wide association studies in European populations. Causal effects were primarily estimated using the inverse variance weighted method, and additional quality control was performed using the MR-Egger, weighted median, simple mode, and weight mode methods. Sensitivity analysis was conducted to assess the robustness of the results. The forward MR analysis showed a positive causal relationship between vitiligo and autoimmune thyroiditis (AIT), autoimmune hyperthyroidism (AIH), and Graves' disease (GD). The odds ratio (OR) were 1.17 (95% CI, 1.01-1.35; p=0.04), 1.12 (95% CI, 1.03-1.22; p=0.01), and 1.13 (95% CI, 1.06-1.20; p<0.01), respectively. In the reverse MR analysis, a positive causal relationship was found between AIT and vitiligo, with an OR of 1.10 (95% CI, 1.01-1.35; p=0.04). However, no causal relationship was observed between AIH (p=0.10) or GD (p=0.61) and vitiligo. Sensitivity analysis revealed no evidence of horizontal pleiotropy or heterogeneity. The genetic-level investigation provides evidence of a genetic causal association between susceptibility to vitiligo and an increased risk of AITDs. Additionally, the results demonstrate a genetic causal association between susceptibility to AIT and an increased risk of vitiligo, while not indicating a similar association with susceptibility to AIH or GD.

MtDNA-Server 2: advancing mitochondrial DNA analysis through highly parallelized data processing and interactive analytics.

Over the past decade, mtDNA-Server established itself as one of the most widely used variant calling web-services for human mitochondrial genomes. The service accepts sequencing data in BAM format and returns an annotated variant analysis report for both homoplasmic and heteroplasmic variants. In this work we present mtDNA-Server 2, which includes several new features highly requested by the community. Most importantly, it includes (a) the integration of a novel variant calling mode that accurately call insertions, deletions and single nucleotide variants at once, (b) the integration of additional quality control and input validation modules, (c) a method to estimate the required coverage to minimize false positives and (d) an interactive analytics dashboard. Furthermore, we migrated the complete analysis workflow to the Nextflow workflow manager for improved parallelization, reproducibility and local execution. Recognizing the importance of insertions and deletions as well as offering novel quality control, validation and reporting features, mtDNA-Server 2 provides researchers and clinicians a new state-of-the-art analysis platform for interpreting mitochondrial genomes. mtDNA-Server 2 is available via mitoverse, our analysis platform that offers a centralized place for mtDNA analysis in the cloud. The web-service, source code and its documentation are freely accessible at https://mitoverse.i-med.ac.at.

Identification of the VLDLR locus associated with giant cell arteritis and the possible causal role of low-density lipoprotein cholesterol in its pathogenesis.

To elucidate the association between genetic variants and the risk of GCA via large-scale genome-wide association studies (GWAS). In addition, to assess the causal effect of a specific molecule by employing the obtained GWAS results as genetic epidemiological tools. We applied additional variant quality control to the publicly available GWAS results from the biobanks of the UK (UKBB) and Finland (FinnGen), which comprised 532 cases vs 408 565 controls and 884 cases vs 332 115 controls, respectively. We further meta-analysed these two sets of results. We performed two-sample Mendelian randomization (MR) to test the causal effect of low-density lipoprotein (LDL) cholesterol on the risk of GCA. The MHC class II region showed significant associations in UKBB, FinnGen and the meta-analysis. The VLDLR region was associated with GCA risk in the meta-analysis. The T allele of rs7044155 increased the expression of VLDLR, decreased the LDL cholesterol level and decreased the disease risk. The subsequent MR results indicated that a 1 s.d. increase in LDL cholesterol was associated with an increased risk of GCA (odds ratio 1.21, 95% CI 1.01-1.45; P = 0.04). Our study identified associations between GCA risk and the MHC class II and VLDLR regions. Moreover, LDL cholesterol was suggested to have a causal effect on the risk of developing GCA.

Causal association between psoriasis vulgaris and bullous pemphigoid: a two-sample bidirectional Mendelian randomization study.

The association between psoriasis vulgaris and bullous pemphigoid (BP) remains largely unknown. To investigate whether there is a causal effect between psoriasis vulgaris and BP. Two-sample bidirectional Mendelian randomization (MR) analyses were conducted using publicly released genome-wide association studies (GWAS) summary statistics. The GWAS summary statistics for BP were downloaded online from FinnGen Biobank Documentation of the R12 release, which includes 219 BP cases and 218,066 controls. The GWAS data for psoriasis vulgaris were extracted from Sakaue etal., which comprises 5072 cases and 478,102 controls. Single-nucleotide polymorphisms (SNPs) associated with exposure were selected as instrumental variables by performing additional quality control steps. The inverse-variance-weighted (IVW) method was used for the primary MR analyses, and the MR-Egger regression, weighted mode method, weighted median method, and simple mode were employed for sensitivity analyses. The MR-Egger intercept test and "leave-one-out" sensitivity analysis were performed to evaluate the horizontal pleiotropy and the potentially influential SNPs, respectively. Genetically determined log odds of psoriasis vulgaris were associated with an increased risk of BP (IVW: odds ratio (OR) = 1.263, 95% confidence interval (CI): 1.013-1.575, P=0.038). Sensitivity analyses by the weighted mode (OR=1.255, 95%CI: 0.973-1.618, P=0.106), MR Egger (OR=1.315, 95%CI: 0.951-1.817, P=0.126), simple mode (OR=1.414, 95%CI: 0.823-2.429, P=0.234) and weighted median method (OR=1.177, 95%CI: 0.889-1.559, P=0.254) derived directionally consistent relationship between the genetically predicted log odds of psoriasis vulgaris and risks of developing BP. On the contrary, we found that genetically predicted BP had no significant effect on psoriasis vulgaris (IVW: OR=0.996, P= 0.707), indicating the unidirectionality of the relationship. MR-Egger intercept tests showed no evidence of horizontal pleiotropy. No influential SNP driving the results was detected by the leave-one-out sensitivity analysis. Our results suggested that psoriasis vulgaris causally increases the risk of BP, highlighting the need for potential strategies for the prevention and early diagnosis of comorbid BP in patients with psoriasis vulgaris. Further researches into this association and underlying mechanisms are warranted.

A robust interpolation-based method for forensic soil provenancing: A Bayesian likelihood ratio approach

Soil is a complex and spatially variable material that has a demonstrated potential as a useful evidence class in forensic casework and intelligence operations. Here, the capability to spatially constrain police search areas and prioritise resources by triaging areas as low and high interest is advantageous. Conducted between 2017 and 2021, a forensically relevant topsoil survey (0–5 cm depth; 1 sample per 1 km2) was carried out over Canberra, Australia, aiming to document the distribution of chemical elements in an urban/suburban environment, and of acting as a testbed for investigating various aspects of forensic soil provenancing. Geochemical data from X-Ray Fluorescence (XRF; for total major oxides) and Inductively Coupled Plasma-Mass Spectrometry (ICP-MS; for trace elements) following a total digestion (HF + HNO3) of the fused XRF beads were obtained from the survey’s 685 topsoil samples (plus 138 additional quality control samples and six “Blind” simulated evidentiary samples). Using those “Blind” samples, we document a likelihood ratio approach where for each grid cell the analytical similarity between the grid cell and evidentiary sample is attributed from a measure of overlap between the two Cauchy distributions, including appropriate uncertainties. Unlike existing methods that base inclusion/exclusion on an arbitrary threshold (e.g., ± three standard deviations), our approach is free from strict binary or Boolean thresholds, providing an unconstrained gradual transition dictated by the analytical similarity. Using this provenancing model, we present and evaluate a new method for upscaling from a fine (25 m x 25 m) interpolated grid to a more appropriate coarser (500 m x 500 m) grid. In addition, an objective method using Random Match Probabilities for ranking individual variables to be used for provenancing prior to receiving evidentiary material was demonstrated. Our results show this collective procedure generates more consistent and robust provenance maps when applied to two different interpolation algorithms (e.g., inverse distance weighting, and natural neighbour), with different grid placements (e.g., grid shifts to the north or east) and by different theoretical users (e.g., different computer systems, or forensic geoscientists).

Evaluation of the Thermo Fisher Oncomine Myeloid MRD DNA Assay on the Ion Torrent Platform

Introduction Malignant myeloid diseases are a group of blood cancers that arise from genetic changes in hematopoietic cells in the bone marrow or peripheral blood. The presence of measurable residual disease (MRD), or detection of abnormal cells in the body following completion of therapy, is associated with a higher risk of disease relapse, and decreased overall survival (Schuurhuis 2018). Next-generation sequencing (NGS) can be leveraged as a high-sensitivity, minimally invasive method for detection of MRD. The Ion Torrent Oncomine Myeloid MRD Assay (Myeloid MRD) is a targeted NGS assay designed for the detection of single nucleotide variants (SNVs) and insertions/deletions in a curated selection of clinically relevant myeloid disease-related genes at low limits of detection. Assay performance was evaluated using normal and diseased clinical blood and bone marrow samples and NGS reference materials. Methods The Myeloid MRD DNA panel targets hotspot regions across 33 genes and uses Ion AmpliSeq HD technology with unique molecular tagging to suppress sequencing artifacts and improve analytical sensitivity. Briefly, DNA was extracted from whole blood or bone marrow samples and 120 ng of nucleic acid was used as input for the assay. The DNA was divided between 2 polymerase chain reactions (PCR), where it served as the template for target amplifications, before combining reaction products by sample. Library preparation followed the standard Ion AmpliSeq HD protocol, where amplicons were partially enzymatically digested, and a second round of amplification was performed using barcoded primers. Following bead purification, the final library was measured by quantitative PCR (qPCR) to inform final library loading onto the sequencer. Six libraries were pooled and sequenced on an Ion 550 chip using the Ion GeneStudio S5 System. Primary and secondary analyses were performed using the Torrent Suite software, and results were exported to the Ion Reporter software for variant calling. From the variant calling results, a probit model was utilized to determine the variant allele frequency (VAF) at which the assay achieved 90% power to call an expected variant, defining the limit of detection (LoD). Other parameters evaluated included analytical sensitivity, analytical specificity, positive predictive value (PPV), accuracy, and precision. Results Overall, consistent, high quality on-target reads were observed across 22 sequencing runs with a median Ion Sphere Particle (ISP) loading of 90%, usable sequence of 59%, and over 130 million total reads per chip. When evaluating individual samples according to the vendor-recommended number of mapped reads (&amp;gt; 10 million), 98.3% of samples tested passed quality control (QC). Additional sample QC metrics established during assay validation included thresholds of &amp;gt; 80% reads on-target, &amp;gt; 80% uniformity of base coverage, and a mean read length of at least 80 base pairs. The estimated LoD for the assay was 0.1% VAF for small variants (SNVs, insertions/deletions).Above the LoD, the assay demonstrated 96.03% sensitivity, 99.89% accuracy of base-calling, 100% specificity, and 98.83% PPV.Additionally,a comparison was performed usingmatched whole blood and bone marrow samples collected from patients with acute myeloid leukemia (AML) to evaluate the concordance of variant calling. It was determined that the same variants were identified across both sample types, although at higher allele frequency in bone marrow compared to whole blood. Conclusion This evaluation of the Myeloid MRD assay demonstrates that it is a precise and accurate assay with sensitivity that is acceptable for MRD analysis. Notably, variant detection was concordant between whole blood and bone marrow sample types collected from AML patients, with bone marrow providing improved sensitivity for low-frequency variant detection. The user-friendly workflow and integrated informatics pipeline offer opportunities for streamlined testing and interpretation of results. The Ion Torrent Myeloid MRD DNA assay is a powerful new tool for MRD detection across a growing myeloid disease target landscape.

Digitizing weather observations from World War II US naval ship logbooks

AbstractThe number and coverage of weather observations over the oceans were considerably reduced during World War II (WW2) due to disruptions to normal trade routes. The observations that do exist for this period are often unavailable to science as they are still only available as paper records or scanned images. We have rescued the detailed hourly weather observations contained in more than 28,000 logbook images of the US Navy Pacific Fleet stationed at Hawai'i during 1941–1945 to produce a dataset of more than 630,000 records. Each record contains the date and time, positional information and several meteorological measurements, totalling more than 3 million individual observations. The data rescue process consisted of a citizen science project asking volunteers to transcribe the observations from the available images, followed by additional quality control processes. This dataset not only contains hourly weather observations of air temperature, sea surface temperature, atmospheric pressure, wind speed and wind direction, mainly in the Pacific Ocean but also includes some observations from the Atlantic and Indian Oceans. The new observations are found to be of good quality by inter‐comparing independent measurements taken on ships travelling in convoy and by comparing with the 20th‐Century Reanalysis. This dataset provides invaluable instrumental weather observations at times and places during WW2, which fill gaps in existing reconstructions.

Study of a tick-borne encephalitis vaccine

Scientific relevance. Tick-borne encephalitis is one of the most significant anthropozoonoses for public health in the Russian Federation. Wide vaccination coverage is required to control this zoonotic infection. However, large-scale immunisation is not feasible without developing novel vaccines with improved safety and efficacy profiles, such as vaccines based on the continuous Vero cell line.Aim. This extended study aimed to investigate the key quality attributes of VeroKSEN, a new tick-borne encephalitis vaccine that was obtained using Vero cells.Materials and methods. The authors implemented current approaches to vaccine development, including propagation of tick-borne encephalitis strain 205 (Far Eastern subtype) in Vero cells, fine purification of the viral antigen by size-exclusion chromatography on polymeric resins, and introduction of additional quality control methods. For VeroKSEN production, the authors used the method protected by utility patent No. 2678431. Quality control of the finished product was performed according to the State Pharmacopoeia of the Russian Federation. The laboratory study of the vaccine and its intermediates in Balb/с mice used novel control methods developed by the authors. Additional methods included polyacrylamide gel electrophoresis, enzyme immunoassay, immunoblotting with total antibodies to tick-borne encephalitis virus and monoclonal antibodies to glycoprotein E, reverse transcription–polymerase chain reaction, and high-performance liquid chromatography. The extended potency study used test strains of different subtypes, including Absettarov (Western), Sofjin (Far Eastern), and Korzukhin (Siberian). The authors studied the infectious activity of tick-borne encephalitis virus in outbred mice using the pharmacopoeial titration method. Statistical analysis of the study results involved calculating the arithmetic mean and the root-mean-square deviation.Results. The authors studied the key quality attributes of VeroKSEN and its intermediates. Selected inactivation conditions reduced the infectious activity of the viral harvest to an undetectable level within 24 h, while its antigenic activity remained approximately 100% of the baseline. The fine purification stages and the methods and techniques developed by the authors provided a whole-virion fraction with a purity of up to 98.2% and removed process-related impurities (residual host-cell DNA, bovine serum albumin, formaldehyde, and bacterial endotoxins) to the levels required by national legislation. The stability study demonstrated that the vaccine met the requirements for up to 36 months.Conclusions. The study showed the high potency of the new vaccine in terms of protection against the Western, Siberian, and Far Eastern subtypes of tick-borne encephalitis, with minimum immunising doses (MID50) of 0.007, 0.00125, and 0.00093 mL, respectively.

RAD51 as a biomarker for homologous recombination deficiency in high-grade serous ovarian carcinoma: robustness and interobserver variability of the RAD51 test.

The RAD51 test is emerging as a promising biomarker for the assessment of functional homologous recombination deficiency (HRD). Yet, the robustness and reproducibility of the immunofluorescence-based RAD51 test, in different academic laboratories, have not been systematically investigated. Therefore, we tested the performance of the RAD51 assay in formalin-fixed paraffin-embedded (FFPE) high-grade serous ovarian carcinoma (HGSOC) samples in four European laboratories. Here, we confirm that subtle differences in staining procedures result in low variability of RAD51 and γH2AX scores. However, substantial variability in RAD51 scoring was observed in some samples, likely due to complicating technical and biological features, such as high RAD51 signal-to-noise ratio and RAD51 heterogeneity. These results support the need to identify and perform additional quality control steps and/or automating image analysis. Altogether, resolving technical issues should be a priority, as identifying tumours with functional HRD is urgently needed to guide the individual treatment of HGSOC patients. Follow-up studies are needed to define the key tissue quality requirements to assess HRD by RAD51 in FFPE tumour samples, as this test could help in guiding the individual treatment of HGSOC patients.

Reliability and Efficiency of the CAPRI-3 Metastatic Prostate Cancer Registry Driven by Artificial Intelligence.

Manual data collection is still the gold standard for disease-specific patient registries. However, CAPRI-3 uses text mining (an artificial intelligence (AI) technology) for patient identification and data collection. The aim of this study is to demonstrate the reliability and efficiency of this AI-driven approach. CAPRI-3 is an observational retrospective multicenter cohort registry on metastatic prostate cancer. We tested the patient-identification algorithm and automated data extraction through manual validation of the same patients in two pilots in 2019 and 2022. Pilot one identified 2030 patients and pilot two 9464 patients. The negative predictive value of the algorithm was maximized to prevent false exclusions and reached 94.8%. The completeness and accuracy of the automated data extraction were 92.3% or higher, except for date fields and inaccessible data (images/pdf) (10-88.9%). Additional manual quality control took over 3 h less time per patient than the original fully manual CAPRI registry (105 vs. 300 min). The CAPRI-3 patient-identification algorithm is a sound replacement for excluding ineligible candidates. The AI-driven data extraction is largely accurate and complete, but manual quality control is needed for less reliable and inaccessible data. Overall, the AI-driven approach of the CAPRI-3 registry is reliable and timesaving.

Pitfalls and opportunities for applying latent variables in single-cell eQTL analyses

Using latent variables in gene expression data can help correct unobserved confounders and increase statistical power for expression quantitative trait Loci (eQTL) detection. The probabilistic estimation of expression residuals (PEER) and principal component analysis (PCA) are widely used methods that can remove unwanted variation and improve eQTL discovery power in bulk RNA-seq analysis. However, their performance has not been evaluated extensively in single-cell eQTL analysis, especially for different cell types. Potential challenges arise due to the structure of single-cell RNA-seq data, including sparsity, skewness, and mean-variance relationship. Here, we show by a series of analyses that PEER and PCA require additional quality control and data transformation steps on the pseudo-bulk matrix to obtain valid latent variables; otherwise, it can result in highly correlated factors (Pearson's correlation r = 0.63 ~ 0.99). Incorporating valid PFs/PCs in the eQTL association model would identify 1.7 ~ 13.3% more eGenes. Sensitivity analysis showed that the pattern of change between the number of eGenes detected and fitted PFs/PCs varied significantly in different cell types. In addition, using highly variable genes to generate latent variables could achieve similar eGenes discovery power as using all genes but save considerable computational resources (~ 6.2-fold faster).

МЕТОДИКА ЭКСПЕРТНОЙ ОЦЕНКИ КАЧЕСТВА ПЭТ-ИЗОБРАЖЕНИЙ ПАЦИЕНТОВ

Purpose: To develop the method of experts’ quality evaluation of the PET images as an additional quality control method for accurate, comparable, and reproducible PET diagnostics results, and to conduct image quality evaluation in different PET departments used this method. Material and methods: 60 PET images (without CT) of the patients who underwent whole body PET/CT with 18F-FDG were collected from 12 PET/CT scanners in 9 PET departments. Experts’ quality evaluation was conducted with questioning of the experts. Each expert evaluated the image quality by five-point scale and filled out the special form which include three image quality criteria: image clarity, artefacts, and general image quality. There were 28 experts from 8 different PET departments who have work experience in radiology from 1 to 32 years. The results of experts’ quality evaluation of the PET images were examined for correlations with parameters of acquisition and reconstruction protocols, examination methods. The results were also examined for dependance of subjective factors such as work experience and work conditions of experts. The minimum required number of experts were defined. The results were analyzed used statistical methods. Results: The PET images obtained by 8 PET/CT scanners had mean quality value more than 4 points (good quality). PET/CT scanners, which had the lowest quality value, have the obsolete or unusual settings and reconstruction parameters. The correlations between experts’ quality evaluation of the PET images and acquisition parameters (acquisition time per bed, multiplication of injected activity and acquisition time per bed), and examination methods (injected activity and uptake time) were established. The results of experts’ quality evaluation of the PET images were dependent on work experience and work conditions of experts. Conclusion: The method of experts’ quality evaluation of the PET images of the patients based on the questioning of the experts working in PET was developed and demonstrated in the current study. The results showed this method has the potential to compare the PET images obtained by different acquisition and reconstruction protocols, and it can be applied during the optimization of examination method and for the determination of obsolete and unusual settings of PET/CT. Experts’ evaluation of the PET images should include the opinion of at least six experts with different work experience in PET from several PET departments.

Intra-Exon Motif Correlations as a Proxy Measure for Mean Per-Tile Sequence Quality Data in RNA-Seq.

Given the wide variability in the quality of next-generation sequencing data submitted to public repositories, it is essential to identify methods that can perform quality control on these data sets when additional quality control data, such as mean tile data, are missing from public repositories. In this study, we present evidence that correlating counts of reads corresponding to pairs of motifs separated over specific distances on individual exons can be used as a proxy mean tile data in the data sets we analyzed and hence could be used when mean tile data are not available. As test data sets we use the Homo sapiens in vitro transcribed (IVT) data set, and a Drosophila melanogaster data set comprising wild and mutant types. We find that a FastQC analysis of the available parts of these data sets demonstrates that the per-tile sequencing quality is good for all the data sets apart from the mutant-type data where the mutant-r3 data are worse than the mutant-r2 data. Correspondingly, intra-exon motif correlations are reasonably large for all data sets except this latter case where the mutant-r2 correlations are low and the mutant-r3 correlations close to zero. We propose that these extremely low correlations are indicative of bias of technical origin, such as flowcell errors. In addition to this, the intra-exon motif correlations as a function of both guanosine-cytosine (GC) content parameters are somewhat higher and less dependent on the GC content parameters in the IVT-Plasmids messenger RNA (mRNA) selection free RNA-Seq sample (control) than in the other RNA-Seq samples that did undergo mRNA selection: both ribosomal depletion (IVT-Only) and PolyA selection (IVT-PolyA, wild type, and mutant).

High-Resolution Coastal Winds From the NOAA Near Real-Time ASCAT Processor

The NOAA near real-time operational ASCAT ocean surface wind vectors are produced at 12.5 and 25 km swath grid resolutions. To avoid land contamination due to the relatively large footprint size, the wind data in the inner most coastal regions (~15 - 25 km from the coast) are excluded from the final product. To obtain more retrievals in the coastal regions we utilize measurements containing up to 50% land contribution ratio and employ a combination of the enhanced resolution processing technique and a coastal normalized radar cross section correction method to achieve accurate wind retrievals to within ~1.0 - 2.5 km of the coast. The backscatter correction is implemented for each ASCAT coastal zone measurement. The mean and standard deviation of the land contribution for each measurement is determined, and then the land backscatter contribution is subtracted out from the actual measurement through an iteration method to estimate the ocean-only signal. An ocean calibration of the enhanced resolution backscatter was implemented before the wind retrieval step to improve the accuracy. Finally, a land contribution ratio ranking is implemented after the wind retrieval to further remove the remaining land contamination residuals. Additional quality control is also developed. The high-resolution coastal winds from ASCAT are validated against a variety of other independent wind measurements. The results are then presented and discussed.

Binding behavior and antioxidant study of spice extract piperine with respect to meat myoglobin.

It has been reported in many studies that piperine (PIP) has multiple activity properties, the most prominent of which is antioxidant activity. This work reports the binding behavior and antioxidant activity of the spice extract piperine towards myoglobin (Mb) using spectroscopic and fluorescence spectra analysis, and computational approaches. Antioxidant activity studies have shown that the antioxidant effect of the Mb-PIP complex system depends on the concentration of PIP added. An appropriate concentration of PIP can successfully prevent the release of free iron from Mb. The fluorescence results indicated that the binding of PIP to Mb was via static quenching. After binding to PIP, the α-helix content of Mb decreased by about 5%. Synchronous fluorescence results indicate that PIP is closer to Trp, and MD simulations also demonstrate that PIP enters the hydrophobic cavity of Mb and binds stably. This explains the structural changes in proteins that lead to changes in antioxidant properties. The results of this study provide a reference for the quality control of additives of plant origin in the processing and storage of meat and meat products.

Multimodal Lung Cancer Subtyping Using Deep Learning Neural Networks on Whole Slide Tissue Images and MALDI MSI.

Artificial intelligence (AI) has shown potential for facilitating the detection and classification of tumors. In patients with non-small cell lung cancer, distinguishing between the most common subtypes, adenocarcinoma (ADC) and squamous cell carcinoma (SqCC), is crucial for the development of an effective treatment plan. This task, however, may still present challenges in clinical routine. We propose a two-modality, AI-based classification algorithm to detect and subtype tumor areas, which combines information from matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) data and digital microscopy whole slide images (WSIs) of lung tissue sections. The method consists of first detecting areas with high tumor cell content by performing a segmentation of the hematoxylin and eosin-stained (H&E-stained) WSIs, and subsequently classifying the tumor areas based on the corresponding MALDI MSI data. We trained the algorithm on six tissue microarrays (TMAs) with tumor samples from N = 232 patients and used 14 additional whole sections for validation and model selection. Classification accuracy was evaluated on a test dataset with another 16 whole sections. The algorithm accurately detected and classified tumor areas, yielding a test accuracy of 94.7% on spectrum level, and correctly classified 15 of 16 test sections. When an additional quality control criterion was introduced, a 100% test accuracy was achieved on sections that passed the quality control (14 of 16). The presented method provides a step further towards the inclusion of AI and MALDI MSI data into clinical routine and has the potential to reduce the pathologist's work load. A careful analysis of the results revealed specific challenges to be considered when training neural networks on data from lung cancer tissue.