Related Variants Research Articles

Extracting Reusable Fragments From Data-Centric Process Variants

Data-centric process management supports knowledge workers in performing knowledge-intensive processes in a flexible way. An essential ingredient of data-centric process management are process templates that are manually modified for a specific case to suit the context of that case. Modifying templates results in many different yet related process variants. However, manually modifying a template is time consuming and may lead to errors. This paper defines an approach to extract reusable fragments from data-centric process variants. The set of extracted fragments is minimal. By composing the fragments not only the input variants but many more process variants can be derived. We have implemented the approach in a prototype and evaluated it on several business processes. Using the fragment extraction approach, complex data-centric process variants can be designed more efficiently and their quality can improve, since well-known modifications are applied.

Predicting changes in neutralizing antibody activity for SARS-CoV-2 XBB.1.5 using in silico protein modeling

The SARS-CoV-2 variant XBB.1.5 is of concern as it has high transmissibility. XBB.1.5 currently accounts for upwards of 30% of new infections in the United States. One year after our group published the predicted structure of the Omicron (B.1.1.529) variant’s receptor binding domain (RBD) and antibody binding affinity, we return to investigate the new mutations seen in XBB.1.5 which is a descendant of Omicron. Using in silico modeling approaches against newer neutralizing antibodies that are shown effective against B.1.1.529, we predict the immune consequences of XBB.1.5’s mutations and show that there is no statistically significant difference in overall antibody evasion when comparing to the B.1.1.529 and other related variants (e.g., BJ.1 andBM.1.1.1). However, noticeable changes in antibody binding affinity were seen due to specific amino acid changes of interest in the newer variants.

Evaluation of muscle strength and quality in North African patients with chronic hepatitis B: A pilot case control study

ABSTRACT Early detection of alteration of muscle strength, quantity, and quality, and sarcopenia is useful in non-cirrhotic chronic hepatitis B (NC-CHB) patients. Studies, which explored the handgrip strength (HGS) are scarce with questionable results, and no previous case-control study explored the presence of sarcopenia. The aim of this study was to assess the muscle strength [i.e.; HGS absolute (HGSA), HGSA/body mass index (BMI)], muscle quantity [i.e.; appendicular skeletal muscle (ASM), ASM/height2, ASM/total body weight (TBW), ASM/BMI], and muscle quality [i.e.; HGSA/total muscle mass (TMM), HGSA/ASM] of NC-CHB patients. This was a case-control study. Cases (n = 26) were untreated NC-CHB patients, and controls (n = 28) were ‘apparently’ healthy participants. Muscle mass was estimated via the TMM (kg) and ASM (kg). Muscle strength was evaluated via the HGS data [i.e.; HGSA (kg), HGSA/BMI (m2)]. Six variants of HGSA were determined: highest values for the dominant and non-dominant hands, highest value between the two hands, averages of the three measurements for the two hands, and the average of the highest values of the two hands. Muscle quantity was expressed in three relative variants (ASM/height2, ASM/TBW, and ASM/BMI). Muscle quality was evaluated via relative HGS data adjusted by muscle mass (i.e.; HGSA/TMM, HGSA/ASM). Probable and confirmed sarcopenia were retained in front of low muscle strength, and low muscle strength and muscle quantity or quality, respectively. There were no significant differences between controls and NC-CHB patients in values of muscle i) Strength whatever the HGS’ mode of expression (e.g.; HGSA/BMI: 1.59 ± 0.54 vs. 1.53 ± 0.54 m2, p = 0.622, respectively), ii) Quantity (e.g.; ASM/BMI: 0.79 ± 0.24 vs. 0.77 ± 0.23 m2, p = 0.883), and iii) Quality (e.g.; HGSA/ASM: 2.00 ± 0.25 vs. 2.01 ± 0.41, p = 0.952, respectively). One NC-CHB participant had a confirmed sarcopenia. To conclude, both controls and NC-CHB patients had similar HGS values. Only one NC-CHB patient had a confirmed sarcopenia.

Image classification model based on large kernel attention mechanism and relative position self-attention mechanism.

The Transformer has achieved great success in many computer vision tasks. With the in-depth exploration of it, researchers have found that Transformers can better obtain long-range features than convolutional neural networks (CNN). However, there will be a deterioration of local feature details when the Transformer extracts local features. Although CNN is adept at capturing the local feature details, it cannot easily obtain the global representation of features. In order to solve the above problems effectively, this paper proposes a hybrid model consisting of CNN and Transformer inspired by Visual Attention Net (VAN) and CoAtNet. This model optimizes its shortcomings in the difficulty of capturing the global representation of features by introducing Large Kernel Attention (LKA) in CNN while using the Transformer blocks with relative position self-attention variant to alleviate the problem of detail deterioration in local features of the Transformer. Our model effectively combines the advantages of the above two structures to obtain the details of local features more accurately and capture the relationship between features far apart more efficiently on a large receptive field. Our experiments show that in the image classification task without additional training data, the proposed model in this paper can achieve excellent results on the cifar10 dataset, the cifar100 dataset, and the birds400 dataset (a public dataset on the Kaggle platform) with fewer model parameters. Among them, SE_LKACAT achieved a Top-1 accuracy of 98.01% on the cifar10 dataset with only 7.5M parameters.

Spatially Guided and Single Cell Tools to Map the Microenvironment in Cutaneous T-Cell Lymphoma

Mycosis fungoides (MF) and Sézary syndrome (SS) are two closely related clinical variants of cutaneous T-cell lymphomas (CTCL). Previously demonstrated large patient-to-patient and intra-patient disease heterogeneity underpins the importance of personalized medicine in CTCL. Advanced stages of CTCL are characterized by dismal prognosis, and the early identification of patients who will progress remains a clinical unmet need. While the exact molecular events underlying disease progression are poorly resolved, the tumor microenvironment (TME) has emerged as an important driver. In particular, the Th1-to-Th2 shift in the immune response is now commonly identified across advanced-stage CTCL patients. Herein, we summarize the role of the TME in CTCL evolution and the latest studies in deciphering inter- and intra-patient heterogeneity. We introduce spatially resolved omics as a promising technology to advance immune-oncology efforts in CTCL. We propose the combined implementation of spatially guided and single-cell omics technologies in paired skin and blood samples. Such an approach will mediate in-depth profiling of phenotypic and molecular changes in reactive immune subpopulations and malignant T cells preceding the Th1-to-Th2 shift and reveal mechanisms underlying disease progression from skin-limited to systemic disease that collectively will lead to the discovery of novel biomarkers to improve patient prognostication and the design of personalized treatment strategies.

Orientation Relationship of FeNiC and FeNiCSi from Variant Detection in EBSD Data

The determination of orientation relationships in dual or multi-phase materials is very important in the field of interface engineering for the design of materials with tailored properties. In this work, a code is developed for the automated and statistical analysis of the orientation relationship of electron backscatter diffraction data. The code is applied to the example of Fe-Ni-(Si)-C alloys containing lenticular martensite and retained austenite, and it is shown that the orientation relationship (OR) corresponds to the Greninger–Troiano OR and that a statistically reliable investigation of the OR between the retained austenite and the related martensite variants is feasible using the code developed in this study.

Cohort-driven variant burden analysis and pathogenicity identification in monogenic autoinflammatory disorders

Nearly 50 pathogenic genes and hundreds of pathogenic variants have been identified in monogenic autoinflammatory diseases (AIDs). Nonetheless, there are still many genes for which the pathogenic mechanisms are poorly understood, and the pathogenicity of many candidate variants needs to be determined. Monogenic AIDs are a group of rare genetic diseases characterized by inflammation as the phenotype. With the development of next-generation sequencing, pathogenic genes have been widely reported and used for clinical screening and diagnosis. The International Society for Systemic Autoinflammatory Diseases has recognized approximately 50 pathogenic genes and hundreds of related pathogenic variants in monogenic AIDs. We plan to investigate these pathogenic variants by conducting a variant burden analysis to determine whether or not there are consistent characteristics. We performed a variant burden analysis on the Genome Aggregation Database cohort using the currently reported genetic variants in monogenic AIDs, analyzing the enrichment of allelic signatures and deleterious predictions at the variants. Allelic signatures were extracted from Genome Aggregation Database, and the deleterious predictions were extracted from existing tools. The features obtained from the variant burden analysis were applied to the Random Forest model to classify the pathogenicity of novel mutations. Functional enrichment and network analysis of AID pathogenic genes have hinted at the possible involvement of unsuspected signals. The variant burden analysis demonstrated that the pathogenicity of a variant could not be reliably classified using only its allele frequency and deleterious predictions. However, variants of varying classifications of pathogenicity exhibited strikingly different patterns of the allelic signature in the upstream and downstream regions surrounding the variants. Furthermore, the distribution of deleterious variants surrounding the variants in the cohort varied significantly across pathogenicity categories. Finally, the cohort-based features extracted from the alleles were applied to the prediction of pathogenicity in monogenic AIDs, achieving superior prediction performance compared with other tools. The cohort-based features have potential applications across a more extensive variety of disease categories. The pathogenicity of a variant can be effectively classified on the basis of variant frequency and deleterious prediction of the allele in the cohort, and this information can be used to improve the accuracy of the current classification of the pathogenicity of the variant.

Numerical networks of cells

Numerical P systems (NPS) are a very particular class of P systems having important differences from most models in this area. The main particularity of the model is the usage of numerical variables whose values are shared among applicable rules, contrary to the concurrence for objects in the multiset for the traditional P systems case.In 2007, Freund and Verlan developed a formal framework for P systems to capture most of the essential features of P systems and to define their functioning in a formal way. Subsequent papers developed versions of this framework for the case of spiking neural P systems and P systems with dynamically evolving structure. These results permitted to obtain a different view on P systems giving a general framework to analyze, relate and extend different variants of P systems and other related models, like Petri nets or register machines.This paper aims to provide a similar generalization for the case of numerical P systems (NPS) and related variants like enzymatic or generalized NPS. We call the obtained model Numerical Networks of Cells (NNC). As in the case of the formal framework it allows to accurately describe NPS, as well as other types of P systems like those using fuzzy sets as computation support. Also, the new model generalizes other well-known models like Boolean networks or reaction systems and this can potentially help to bring bridges between P systems and these areas.

DNA methylation patterns suggest the involvement of DNMT3B and TET1 in osteosarcoma development

DNA methylation may be involved in the development of osteosarcomas. Osteosarcomas commonly arise during the bone growth and remodeling in puberty, making it plausible to infer the involvement of epigenetic alterations in their development. As a highly studied epigenetic mechanism, we investigated DNA methylation and related genetic variants in 28 primary osteosarcomas aiming to identify deregulated driver alterations. Methylation and genomic data were obtained using the Illumina HM450K beadchips and the TruSight One sequencing panel, respectively. Aberrant DNA methylation was spread throughout the osteosarcomas genomes. We identified 3146 differentially methylated CpGs comparing osteosarcomas and bone tissue samples, with high methylation heterogeneity, global hypomethylation and focal hypermethylation at CpG islands. Differentially methylated regions (DMR) were detected in 585 loci (319 hypomethylated and 266 hypermethylated), mapped to the promoter regions of 350 genes. These DMR genes were enriched for biological processes related to skeletal system morphogenesis, proliferation, inflammatory response, and signal transduction. Both methylation and expression data were validated in independent groups of cases. Six tumor suppressor genes harbored deletions or promoter hypermethylation (DLEC1, GJB2, HIC1, MIR149, PAX6, and WNT5A), and four oncogenes presented gains or hypomethylation (ASPSCR1, NOTCH4, PRDM16, and RUNX3). Our analysis also revealed hypomethylation at 6p22, a region that contains several histone genes. Copy-number changes in DNMT3B (gain) and TET1 (loss), as well as overexpression of DNMT3B in osteosarcomas provide a possible explanation for the observed phenotype of CpG island hypermethylation. While the detected open-sea hypomethylation likely contributes to the well-known osteosarcoma genomic instability, enriched CpG island hypermethylation suggests an underlying mechanism possibly driven by overexpression of DNMT3B likely resulting in silencing of tumor suppressors and DNA repair genes.

Abstract 6305: Bispecific claudin 18.2 and GPRC5D antibodies with potent cell-killing activity for cancer therapeutics

Abstract Tumor-associated antigens with little or no expression in healthy tissue are attractive targets for anti-tumor modalities including T cell-engaging bispecific antibodies. CLDN18.2 is a transmembrane adhesion protein undetectable in most healthy adult tissues but highly expressed in gastric, pancreatic, esophageal, and lung cancers. GPRC5D is a G protein-coupled receptor that is absent from most healthy tissues except for hair follicles but expressed on multiple myeloma cells. Both CLND18.2 and GPRC5D are novel oncology targets with no clinically approved therapies against them. Using our discovery platform tailored to complex transmembrane proteins, we have developed bispecific antibodies with the ability to potently kill CLDN18.2-positive or GPRC5D-positive cells. Multipass membrane proteins are valuable therapeutic targets in oncology and other disease areas but are largely inaccessible as antibody targets due to their poor expression, membrane-dependent structure, small extracellular regions, and poor immunogenicity due to sequence conservation. We developed an antibody discovery platform (MPS) that specifically addresses each of these challenges. This platform utilizes advanced immunization techniques including DNA, mRNA, and Lipoparticles (virus-like particles). It also employs chickens as an evolutionarily divergent host species for robust immune responses against conserved targets. Antibodies raised in chickens are directly humanized prior to isolation, reducing the need for downstream engineering. In two separate campaigns, we immunized chickens with CLDN18.2 and GPRC5D and obtained high-titer immune responses. We were successful in isolating high-affinity antibodies specific to each of these targets. Our CLDN18.2 antibodies showed specificity for their target and did not bind the closely related splice variant CLND18.1, which is highly expressed in healthy lung tissue. Additionally, the antibodies showed no binding to ~6,000 other proteins that were screened using a Membrane Proteome Array. A subset of antibodies from both discovery programs were configured as bispecific molecules using a CD3-targeting arm to bring tumor cells into close proximity with cytotoxic T cells that mediate cell killing. The panels of molecules encompassed multiple bispecific formats bearing different stoichiometries, geometries, and sizes to enable identification of lead molecules with favorable activities and safety profiles. Both CLDN18.2 and GPRC5D bispecifics showed potent T cell-mediated cytotoxicity with picomolar potency. They also showed good cytokine release and developability profiles. GPRC5D x CD3 and CLDN18.2 x CD3 bispecifics hold promise as potent and safe therapeutics for different cancer types. Citation Format: Ileine Sanchez, Hayley Roth, Brad Screnci, David Tucker, Nick Molino, Trevor Barnes, Paige Murphy, Kyle Guldner, Tim Phillips, Kristen Shema, Thomas Charpentier, Alyssa Cunningham, Janae Latta, Breanna Tyrell, Meghan Pitts, Carmen Navia, Charles Azuelos, Anna Lobley, Jawhara Karam, Valerie Fiers, Daniela Reyes, Kate Slovik, Alison Snyder, Marianne Assogba, Kai-Ti Chang, Riley Payne, Kyle Doolan, Ross Chambers, Joe Rucker, Benjamin Doranz. Bispecific claudin 18.2 and GPRC5D antibodies with potent cell-killing activity for cancer therapeutics. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6305.

Investigating antigenic features of the SARS-CoV-2 isolated in Russian Federation in 2021–2022 by hyperimmune mouse serum neutralisation

Introduction. The rapid spread of a new coronavirus infection among populations in many countries worldwide has contributed to the genetic evolution of the virus, resulting in the emergence of multiple genetic variants of the SARS-CoV-2 coronavirus. Mutations in the viral genome can affect the ability of the virus to bypass the immune system and complicate development of diagnostic and prophylactic drugs. Data on the neutralizing activity of the sera obtained against previously circulating genetic variants of the virus in relation to current SARS-CoV-2 strains may serve as a scientific basis for the selection of the antigens in vaccine development. The aim of this work was to study cross-reactivity of SARS-CoV-2 coronavirus strains belonging to different genetic variants, which were isolated in the territory of the Russian Federation during 20202022 in the neutralization reaction using mouse hyperimmune sera. Materials and methods. Ten strains of SARS-CoV-2 coronavirus belonging to different genetic variants were used (three non-VOC strains, alpha, beta, gamma, delta, delta+AY, omicron 1 and omicron 2). The hCoV-19/Australia/VIC01/2020 strain (Wuhan) was included in the study as a prototypical variant. BALBc mice were immunized with inactivated concentrated antigen mixed with a 1:1 adjuvant, which was a virus-like immunostimulatory complex based on Quillaja saponaria (Quillaja saponaria). The antibody titer was determined in the neutralization reaction. Results. Essential decrease of neutralizing ability of antibodies specific to non-vOC genetic variants of SARS-CoV-2 coronavirus was revealed against beta VOC and to a lesser degree against alpha and gamma VOC variants. The differences in the neutralizing activity level of antibodies for alpha and beta VOC variants are not significant among themselves, and with gamma VOC variants there are no significant differences. Neutralizing ability of antibodies specific to delta VOC against alpha and beta VOC variants decreased 4-fold. Neutralizing activity of sera obtained to omicron 1 and 2 variants in relation to the prototype coronavirus variant was reduced 18-fold, to the gamma variant 12-fold, to delta variants more than 30-fold; for other variants it was even lower. Conclusions. The results obtained testify to the presence of cross-reactivity between strains of coronavirus belonging to genetic lines Wuhan, alpha, beta, gamma; it is weaker for delta variants. Mutations in the genome of VOC omicron variants led to a significant decrease in antigenic cross-links with earlier genetic variants of the coronavirus. These findings explain the low efficacy of vaccines based on the Wuhan strain, synthetic immunogens, and recombinant proteins based on it against omicron VOC variants, which have caused a rise in morbidity since early 2022, as well as cases of re-infection of humans with new genetic variants of the coronavirus.

Brain metabolic signatures in patients with genetic and nongenetic amyotrophic lateral sclerosis.

To study the brain metabolic signature in Chinese amyotrophic lateral sclerosis (ALS) patients and compare the difference in brain metabolic patterns between ALS with and without genetic variants. We included 146 patients with ALS and 128 healthy controls (HCs). All patients with ALS underwent genetic testing to screen for ALS related genetic variants and were then divided into genetic (n = 22) and nongenetic ALS (n = 93) subgroups. All participants underwent brain 18 F-FDG-PET scans. Group comparisons were performed using the two-sample t-test model of SPM12. We identified a large of hypometabolic clusters in ALS patients as compared with HCs, especially in the bilateral basal ganglia, midbrain, and cerebellum. Moreover, hypometabolism in the bilateral temporal lobe, precentral gyrus and hypermetabolism in the left anterior cingulate, occipital lobe, and bilateral frontal lobe were also found in ALS patients as compared with HCs. Compared with nongenetic ALS patients, genetic ALS patients showed hypometabolism in the right postcentral gyrus, precuneus, and middle occipital gyrus. The incidence of sensory disturbance in patients with genetic ALS was higher than that in patients with nongenetic ALS (5 of 22 [22.72%] vs. 7 of 93 [7.52%], p = 0.036). Our investigation provided unprecedented evidence of relative hypometabolism in the midbrain and cerebellum in ALS patients. Genetic ALS patients showed a specific signature of brain metabolism and a higher incidence of sensory disturbance, indicating that genetic factors may be an underlying cause affecting the brain metabolism and increasing the risk of sensory disturbance in ALS.

Vehicle routing with heterogeneous service types: Optimizing post-harvest preprocessing operations for fruits and vegetables in short food supply chains

This study focuses on the post-harvest preprocessing of fruits and vegetables, aiming to provide an effective way to conduct preprocessing operations in short food supply chains. We consider both a heterogeneous fleet of mobile preprocessing units and the possibility to pick up products for centralized preprocessing. The resulting problem is a variant of the classic heterogeneous fleet vehicle routing problems with time windows (HFVRPTW), with the additional consideration of multi-depot and heterogeneous service types, which we refer to as HFVRPTW-MDHS. These additional considerations are important to include in the development of more efficient food supply chains, but lead to a challenging routing problem. In this paper, we formulate the HFVRPTW-MDHS using a mixed-integer linear programming model. Due to the complexity of the model, we propose a customized adaptive large neighborhood search (ALNS) metaheuristic. We design a multi-level struct-based solution representation to improve the efficiency of the ALNS and develop customized methods for solution evaluation, feasibility checks, and neighborhood search. Comparing our results with the results of an exact algorithm and solutions in the existing literature, we find that our ALNS algorithm can obtain high-quality solutions quickly when solving HFVRPTW-MDHS and related variants of the VRP. Finally, we study the application of our approach in the case of precooling, which is a commonly used preprocessing operation, to illustrate the effectiveness of our approach in a relevant practical context.

Variant spectrum of von Hippel-Lindau disease and its genomic heterogeneity in Japan.

Von Hippel-Lindau (VHL) disease is an autosomal dominant, inherited syndrome with variants in the VHL gene, causing predisposition to multi-organ neoplasms with vessel abnormality. Germline variants in VHL can be detected in 80-90% of patients clinically diagnosed with VHL disease. Here, we summarize the results of genetic tests for 206 Japanese VHL families, and elucidate the molecular mechanisms of VHL disease, especially in variant-negative unsolved cases. Of the 206 families, genetic diagnosis was positive in 175 families (85%), including 134 families (65%) diagnosed by exon sequencing (15 novel variants) and 41 (20%) diagnosed by multiplex ligation-dependent probe amplification (MLPA) (one novel variant). The deleterious variants were significantly enriched in VHL disease Type 1. Interestingly, five synonymous or non-synonymous variants within exon 2 caused exon 2 skipping, which is the first report of exon 2 skipping caused by several missense variants. Whole genome and target deep sequencing analysis were performed for 22 unsolved cases with no variant identified and found three cases with VHL mosaicism (variant allele frequency: 2.5-22%), one with mobile element insertion in the VHL promoter region, and two with a pathogenic variant of BAP1 or SDHB. The variants associated with VHL disease are heterogeneous, and for more accuracy of the genetic diagnosis of VHL disease, comprehensive genome and DNA/RNA analyses are required to detect VHL mosaicism, complicated structure variants and other related gene variants.

Inflammation and neuronal gene expression changes differ in early versus late chronic traumatic encephalopathy brain

BackgroundOur understanding of the molecular underpinnings of chronic traumatic encephalopathy (CTE) and its associated pathology in post-mortem brain is incomplete. Factors including years of play and genetic risk variants influence the extent of tau pathology associated with disease expression, but how these factors affect gene expression, and whether those effects are consistent across the development of disease, is unknown.MethodsTo address these questions, we conducted an analysis of the largest post-mortem brain CTE mRNASeq whole-transcriptome dataset available to date. We examined the genes and biological processes associated with disease by comparing individuals with CTE with control individuals with a history of repetitive head impacts that lack CTE pathology. We then identified genes and biological processes associated with total years of play as a measure of exposure, amount of tau pathology present at time of death, and the presence of APOE and TMEM106B risk variants. Samples were stratified into low and high pathology groups based on McKee CTE staging criteria to model early versus late changes in response to exposure, and the relative effects associated with these factors were compared between these groups.ResultsSubstantial gene expression changes were associated with severe disease for most of these factors, primarily implicating diverse, strongly involved neuroinflammatory and neuroimmune processes. In contrast, low pathology groups had many fewer genes and processes implicated and show striking differences for some factors when compared with severe disease. Specifically, gene expression associated with amount of tau pathology showed a nearly perfect inverse relationship when compared between these two groups.ConclusionsTogether, these results suggest the early CTE disease process may be mechanistically different than what occurs in late stages, that total years of play and tau pathology influence disease expression differently, and that related pathology-modifying risk variants may do so via distinct biological pathways.

Variant spectrum of PIEZO1 and KCNN4 in Japanese patients with dehydrated hereditary stomatocytosis

Hereditary stomatocytosis (HSt) is a type of congenital hemolytic anemia caused by abnormally increased cation permeability of erythrocyte membranes. Dehydrated HSt (DHSt) is the most common subtype of HSt and is diagnosed based on clinical and laboratory findings related to erythrocytes. PIEZO1 and KCNN4 have been recognized as causative genes, and many related variants have been reported. We analyzed the genomic background of 23 patients from 20 Japanese families suspected of having DHSt using a target capture sequence and identified pathogenic/likely pathogenic variants of PIEZO1 or KCNN4 in 12 families.

On the Semidecidability of the Remote State Estimation Problem

In this article, we consider the decision problem associated with the task of remotely estimating the state of a dynamic plant via a noisy communication channel. Given a machine-readable description of the plant’s and channel’s characteristics, does there exist an algorithm that decides whether remote state estimation is possible? From an analytic point of view, this problem has been shown to involve the zero-error capacity of the communication channel. By applying results from Turing machine theory and zero-error coding, we analyze several related variants of the decision problem mentioned above. Our analysis also incorporates a weakened form of the state estimation objective, which has been shown to depend on the classical Shannon Capacity instead. In the broadest sense, our results yield a fundamental limit to the capabilities of computer-aided design tools and adaptive autonomous systems, assuming they are based on digital hardware.

A multicenter prospective study of next-generation sequencing-based newborn screening for monogenic genetic diseases in China

BackgroundNewborn screening (NBS) is an important and successful public health program that helps improve the long-term clinical outcomes of newborns by providing early diagnosis and treatment of certain inborn diseases. The development of next-generation sequencing (NGS) technology provides new opportunities to expand current newborn screening methodologies.MethodsWe designed a a newborn genetic screening (NBGS) panel targeting 135 genes associated with 75 inborn disorders by multiplex PCR combined with NGS. With this panel, a large-scale, multicenter, prospective multidisease analysis was conducted on dried blood spot (DBS) profiles from 21,442 neonates nationwide.ResultsWe presented the positive detection rate and carrier frequency of diseases and related variants in different regions; and 168 (0.78%) positive cases were detected. Glucose-6-Phosphate Dehydrogenase deficiency (G6PDD) and phenylketonuria (PKU) had higher prevalence rates, which were significantly different in different regions. The positive detection of G6PD variants was quite common in south China, whereas PAH variants were most commonly identified in north China. In addition, NBGS identified 3 cases with DUOX2 variants and one with SLC25A13 variants, which were normal in conventional NBS, but were confirmed later as abnormal in repeated biochemical testing after recall. Eighty percent of high-frequency gene carriers and 60% of high-frequency variant carriers had obvious regional differences. On the premise that there was no significant difference in birth weight and gestational age, the biochemical indicators of SLC22A5 c.1400C > G and ACADSB c.1165A > G carriers were significantly different from those of non-carriers.ConclusionsWe demonstrated that NBGS is an effective strategy to identify neonates affected with treatable diseases as a supplement to current NBS methods. Our data also showed that the prevalence of diseases has significant regional characteristics, which provides a theoretical basis for screening diseases in different regions.

Effects of protein-coding variants on blood metabolite measurements and clinical biomarkers in the UK Biobank

Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p<1×10-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 andCREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provideinsightsinto novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.

An Improved Grey Wolf Optimizer and Its Application in Robot Path Planning

This paper discusses a hybrid grey wolf optimizer utilizing a clone selection algorithm (pGWO-CSA) to overcome the disadvantages of a standard grey wolf optimizer (GWO), such as slow convergence speed, low accuracy in the single-peak function, and easily falling into local optimum in the multi-peak function and complex problems. The modifications of the proposed pGWO-CSA could be classified into the following three aspects. Firstly, a nonlinear function is used instead of a linear function for adjusting the iterative attenuation of the convergence factor to balance exploitation and exploration automatically. Then, an optimal α wolf is designed which will not be affected by the wolves β and δ with poor fitness in the position updating strategy; the second-best β wolf is designed, which will be affected by the low fitness value of the δ wolf. Finally, the cloning and super-mutation of the clonal selection algorithm (CSA) are introduced into GWO to enhance the ability to jump out of the local optimum. In the experimental part, 15 benchmark functions are selected to perform the function optimization tasks to reveal the performance of pGWO-CSA further. Due to the statistical analysis of the obtained experimental data, the pGWO-CSA is superior to these classical swarm intelligence algorithms, GWO, and related variants. Furthermore, in order to verify the applicability of the algorithm, it was applied to the robot path-planning problem and obtained excellent results.