Monte Carlo Regression for Evaluating Children's Role in the Pandemic Spread on the Example of Delta COVID-19 Wave.

BACKGROUND: The children's role in transmitting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the familial settings is uncertain. We aimed to assess how often children were the index cases transmitting SARS-CoV-2 into their households during the Delta wave, and to identify risk factors of children being the index case. METHODS: In this prospective survey study, we collected information regarding household members of SARS-CoV-2-positive children tested in a single tertiary hospital. Some patients were tested with polymerase chain reaction and those samples were typed and classified as Delta or non-Delta variant. We have used the Monte Carlo approach to assess predictors of children being the index case in the household. RESULTS: We surveyed 629 families and 515 of them fulfilled inclusion criteria. The child was the index case in 359 (69.71%) households. Attending childcare facilities in all age groups was positively associated with being the index case in the household [nursery, estimate = 1.456, 95% confidence interval (CI): 1.456-1.457, P < 0.001; kindergarten, estimate = 0.899, 95% CI: 0.898-0.900, P = 0.003; school, estimate = 1.23, 95% CI: 1.229-1.231, P = 0.001]. The same association was present in the subgroup of the families with the predominant Delta variant, but not in the subgroup with the predominant non-Delta variant. CONCLUSIONS: Attending childcare and educational facilities might be a significant predictor of a child being the SARS-CoV-2 index case in their household. Children's role in driving the SARS-CoV-2 pandemic changes in consecutive waves. The Monte Carlo approach can be applied to assess risk factors of infectious agents' spread in future epidemics.

Critical assessment of synthetic accessibility scores in computer-assisted synthesis planning.

Modern computer-assisted synthesis planning tools provide strong support for this problem. However, they are still limited by computational complexity. This limitation may be overcome by scoring the synthetic accessibility as a pre-retrosynthesis heuristic. A wide range of machine learning scoring approaches is available, however, their applicability and correctness were studied to a limited extent. Moreover, there is a lack of critical assessment of synthetic accessibility scores with common test conditions.In the present work, we assess if synthetic accessibility scores can reliably predict the outcomes of retrosynthesis planning. Using a specially prepared compounds database, we examine the outcomes of the retrosynthetic tool AiZynthFinder. We test whether synthetic accessibility scores: SAscore, SYBA, SCScore, and RAscore accurately predict the results of retrosynthesis planning. Furthermore, we investigate if synthetic accessibility scores can speed up retrosynthesis planning by better prioritizing explored partial synthetic routes and thus reducing the size of the search space. For that purpose, we analyze the AiZynthFinder partial solutions search trees, their structure, and complexity parameters, such as the number of nodes, or treewidth.We confirm that synthetic accessibility scores in most cases well discriminate feasible molecules from infeasible ones and can be potential boosters of retrosynthesis planning tools. Moreover, we show the current challenges of designing computer-assisted synthesis planning tools. We conclude that hybrid machine learning and human intuition-based synthetic accessibility scores can efficiently boost the effectiveness of computer-assisted retrosynthesis planning, however, they need to be carefully crafted for retrosynthesis planning algorithms.The source code of this work is publicly available at https://github.com/grzsko/ASAP .

Risk assessment of COVID-19 epidemic resurgence in relation to SARS-CoV-2 variants and vaccination passes.

The introduction of COVID-19 vaccination passes (VPs) by many countries coincided with the Delta variant fast becoming dominant across Europe. A thorough assessment of their impact on epidemic dynamics is still lacking. Here, we propose the VAP-SIRS model that considers possibly lower restrictions for the VP holders than for the rest of the population, imperfect vaccination effectiveness against infection, rates of (re-)vaccination and waning immunity, fraction of never-vaccinated, and the increased transmissibility of the Delta variant. Some predicted epidemic scenarios for realistic parameter values yield new COVID-19 infection waves within two years, and high daily case numbers in the endemic state, even without introducing VPs and granting more freedom to their holders. Still, suitable adaptive policies can avoid unfavorable outcomes. While VP holders could initially be allowed more freedom, the lack of full vaccine effectiveness and increased transmissibility will require accelerated (re-)vaccination, wide-spread immunity surveillance, and/or minimal long-term common restrictions.

TADeus2: a web server facilitating the clinical diagnosis by pathogenicity assessment of structural variations disarranging 3D chromatin structure.

In recent years great progress has been made in identification of structural variants (SV) in the human genome. However, the interpretation of SVs, especially located in non-coding DNA, remains challenging. One of the reasons stems in the lack of tools exclusively designed for clinical SVs evaluation acknowledging the 3D chromatin architecture. Therefore, we present TADeus2 a web server dedicated for a quick investigation of chromatin conformation changes, providing a visual framework for the interpretation of SVs affecting topologically associating domains (TADs). This tool provides a convenient visual inspection of SVs, both in a continuous genome view as well as from a rearrangement's breakpoint perspective. Additionally, TADeus2 allows the user to assess the influence of analyzed SVs within flaking coding/non-coding regions based on the Hi-C matrix. Importantly, the SVs pathogenicity is quantified and ranked using TADA, ClassifyCNV tools and sampling-based P-value. TADeus2 is publicly available at https://tadeus2.mimuw.edu.pl.

Functional performance of aCGH design for clinical cytogenetics.

Array-comparative genomic hybridization (aCGH) technology enables rapid, high-resolution analysis of genomic rearrangements. With the use of it, genome copy number changes and rearrangement breakpoints can be detected and analyzed at resolutions down to a few kilobases. An exon array CGH approach proposed recently accurately measures copy-number changes of individual exons in the human genome. The crucial and highly non-trivial starting task is the design of an array, i.e. the choice of appropriate (multi)set of oligos. The success of the whole high-level analysis depends on the quality of the design. Also, the comparison of several alternative designs of array CGH constitutes an important step in development of new diagnostic chip. In this paper, we deal with these two often neglected issues. We propose a new approach to measure the quality of array CGH designs. Our measures reflect the robustness of rearrangements detection to the noise (mostly experimental measurement error). The method is parametrized by the segmentation algorithm used to identify aberrations. We implemented the efficient Monte Carlo method for testing noise robustness within DNAcopy procedure. Developed framework has been applied to evaluation of functional quality of several optimized array designs.

Inferring serum proteolytic activity from LC-MS/MS data.

BACKGROUND: In this paper we deal with modeling serum proteolysis process from tandem mass spectrometry data. The parameters of peptide degradation process inferred from LC-MS/MS data correspond directly to the activity of specific enzymes present in the serum samples of patients and healthy donors. Our approach integrate the existing knowledge about peptidases' activity stored in MEROPS database with the efficient procedure for estimation the model parameters. RESULTS: Taking into account the inherent stochasticity of the process, the proteolytic activity is modeled with the use of Chemical Master Equation (CME). Assuming the stationarity of the Markov process we calculate the expected values of digested peptides in the model. The parameters are fitted to minimize the discrepancy between those expected values and the peptide activities observed in the MS data. Constrained optimization problem is solved by Levenberg-Marquadt algorithm. CONCLUSIONS: Our results demonstrates the feasibility and potential of high-level analysis for LC-MS proteomic data. The estimated enzyme activities give insights into the molecular pathology of colorectal cancer. Moreover the developed framework is general and can be applied to study proteolytic activity in different systems.

Assessment of the role of copy-number variants in 150 patients with congenital heart defects.

BACKGROUND: Congenital heart defects are the most common group of major birth anomalies and one of the leading causes of infant deaths. Mendelian and chromosomal syndromes account for about 20% of congenital heart defects and in some cases are associated with other malformations, intellectual disability, and/or dysmorphic features. The remarkable conservation of genetic pathways regulating heart development in animals suggests that genetic factors can be responsible for a significantly higher percentage of cases. THE AIM: Assessment of the role of CNVs in the etiology of congenital heart defects using microarray studies. MATERIAL AND METHODS: Genome-wide array comparative genomic hybridization, targeting genes known to play an important role in heart development or responsible for abnormal cardiac phenotype was used in the study on 150 patients. In addition, we have used multiplex ligation-dependent probe amplification specific for chromosome 22q11.2 region. RESULTS: We have identified 21 copy-number variants, including 13 known causative recurrent rearrangements (12 deletions 22q11.2 and one deletion 7q11.23), three potentially pathogenic duplications (5q14.2, 15q13.3, and 22q11.2), and five variants likely benign for cardiac anomalies. We suggest that abnormal copy-number of the ARRDC3 and KLF13 genes can be responsible for heart defects. CONCLUSIONS: Our study demonstrates that array comparative genomic hybridization enables detection of clinically significant chromosomal imbalances in patients with congenital heart defects.

On consensus biomarker selection.

BACKGROUND: Recent development of mass spectrometry technology enabled the analysis of complex peptide mixtures. A lot of effort is currently devoted to the identification of biomarkers in human body fluids like serum or plasma, based on which new diagnostic tests for different diseases could be constructed. Various biomarker selection procedures have been exploited in recent studies. It has been noted that they often lead to different biomarker lists and as a consequence, the patient classification may also vary. RESULTS: Here we propose a new approach to the biomarker selection problem: to apply several competing feature ranking procedures and compute a consensus list of features based on their outcomes. We validate our methods on two proteomic datasets for the diagnosis of ovarian and prostate cancer. CONCLUSION: The proposed methodology can improve the classification results and at the same time provide a unified biomarker list for further biological examinations and interpretation.