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Abstract Background Multivariable prediction models are used in oral health care to identify individuals with an increased likelihood of caries increment. The outcomes of the models should help to manage individualized interventions and to determine the periodicity of service. The objective was to review and critically appraise studies of multivariable prediction models of caries increment. Methods Longitudinal studies that developed or validated prediction models of caries and expressed caries increment as a function of at least three predictors were included. PubMed, Cochrane Library, and Web of Science supplemented with reference lists of included studies were searched. Two reviewers independently extracted data using CHARMS (Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies) and assessed risk of bias and concern regarding applicability using PROBAST (Prediction model Risk Of Bias ASessment Tool). Predictors were analysed and model performance was recalculated as estimated positive (LR +) and negative likelihood ratios (LR −) based on sensitivity and specificity presented in the studies included. Results Among the 765 reports identified, 21 studies providing 66 prediction models fulfilled the inclusion criteria. Over 150 candidate predictors were considered, and 31 predictors remained in studies of final developmental models: caries experience, mutans streptococci in saliva, fluoride supplements, and visible dental plaque being the most common predictors. Predictive performances varied, providing LR + and LR − ranges of 0.78–10.3 and 0.0–1.1, respectively. Only four models of coronal caries and one root caries model scored LR + values of at least 5. All studies were assessed as having high risk of bias, generally due to insufficient number of outcomes in relation to candidate predictors and considerable uncertainty regarding predictor thresholds and measurements. Concern regarding applicability was low overall. Conclusions The review calls attention to several methodological deficiencies and the significant heterogeneity observed across the studies ruled out meta-analyses. Flawed or distorted study estimates lead to uncertainty about the prediction, which limits the models’ usefulness in clinical decision-making. The modest performance of most models implies that alternative predictors should be considered, such as bacteria with acid tolerant properties. Trial registration PROSPERO CRD#152,467 April 28, 2020

Background: This study assessed the diagnostic yield of high-throughput sequencing methods in a cohort of craniosynostosis (CS) patients not presenting causal variants identified through previous targeted analysis.Methods: Whole-genome or whole-exome sequencing (WGS/WES) was performed in a cohort of 59 patients (from 57 families) assessed by retrospective phenotyping as having syndromic or nonsyndromic CS.Results: A syndromic form was identified in 51% of the unrelated cases. A genetic cause was identified in 38% of syndromic cases, with novel variants detected in FGFR2 (a rare Alu insertion), TWIST1, TCF12, KIAA0586, HDAC9, FOXP1, and NSD2. Additionally, we report two patients with rare recurrent variants in KAT6A and YY1 as well as two patients with structural genomic aberrations: one with a 22q13 duplication and one with a complex rearrangement involving chromosome 2 (2p25 duplication including SOX11 and deletion of 2q22). Moreover, we identified potentially relevant variants in 87% of the remaining families with no previously detected causal variants, including novel variants in ADAMTSL4, ASH1L, ATRX, C2CD3, CHD5, ERF, H4C5, IFT122, IFT140, KDM6B, KMT2D, LTBP1, MAP3K7, NOTCH2, NSD1, SOS1, SPRY1, POLR2A, PRRX1, RECQL4, TAB2, TAOK1, TET3, TGFBR1, TCF20, and ZBTB20.Conclusion: These results confirm WGS/WES as a powerful diagnostic tool capable of either targeted in silico or broad genomic analysis depending on phenotypic presentation (e.g., classical or unusual forms of syndromic CS).

Abstract Background The dominantly inherited condition familial adenomatous polyposis (FAP) is caused by germline mutations in the APC gene. Finding the causative mutations has great implications for the families. Correlating the genotypes to the phenotypes could help to improve the diagnosis and follow-up of patients. Methods Mutation screening of APC and the clinical characterization of 96 unrelated FAP patients from the Swedish Polyposis Registry was performed. In addition to generally used mutation screening methods, analyses of splicing-affecting mutations and investigations of the presence of low-frequency mutation alleles, indicating mosaics, have been performed, as well as quantitative real-time polymerase chain reaction to detect lowered expression of APC. Results Sixty-one different APC mutations in 81 of the 96 families were identified and 27 of those are novel. We have previously shown that 6 of the 96 patients carried biallelic MUTYH mutations. The 9 mutation-negative cases all display an attenuated or atypical phenotype. Probands with a genotype (codon 1250–1464) predicting a severe phenotype had a median age at diagnosis of 21.8 (range, 11–49) years compared with 34.4 (range, 14–57) years among those with mutations outside this region (P < 0.017). Dense polyposis (> 1000) occurred in 75% of the probands with a severe phenotype compared with 30% in those with mutations outside this region. The morbidity in colorectal cancer among probands was 25% at a mean age of 37.5 years and 29% at a mean age of 46.6 years. Conclusion Using a variety of mutation-detection techniques, we have achieved a 100% detection frequency in classical FAP. Probands with APC mutations outside codon 1250–1464, although exhibiting a less-severe phenotype, are at high risk of having a colorectal cancer at diagnosis indicating that age at diagnosis is as important as the severity of the disease for colorectal cancer morbidity.

Abstract Background Processed pseudogenes (PΨgs) are disabled gene copies that are transcribed and may affect expression of paralogous genes. Moreover, their insertion in the genome can disrupt the structure or the regulatory region of a gene, affecting its expression level. These events have been identified as occurring mutations during cancer development, thus being able to identify PΨgs and their location will improve their impact on diagnostic testing, not only in cancer but also in inherited disorders. Results We have implemented PΨFinder (P-psy-finder), a tool that identifies PΨgs, annotates known ones and predicts their insertion site(s) in the genome. The tool screens alignment files and provides user-friendly summary reports and visualizations. To demonstrate its applicability, we scanned 218 DNA samples from patients screened for hereditary colorectal cancer. We detected 423 PΨgs distributed in 96% of the samples, comprising 7 different parent genes. Among these, we confirmed the well-known insertion site of the SMAD4-PΨg within the last intron of the SCAI gene in one sample. While for the ubiquitous CBX3-PΨg, present in 82.6% of the samples, we found it reversed inserted in the second intron of the C15ORF57 gene. Conclusions PΨFinder is a tool that can automatically identify novel PΨgs from DNA sequencing data and determine their location in the genome with high sensitivity (95.92%). It generates high quality figures and tables that facilitate the interpretation of the results and can guide the experimental validation. PΨFinder is a complementary analysis to any mutational screening in the identification of disease-causing mutations within cancer and other diseases.

ObjectivesImmunotherapy by blocking programmed death protein-1 (PD-1) or programmed death protein-ligand1 (PD-L1) with antibodies (PD-1 blockade) has revolutionized treatment options for patients with non-small cell lung cancer (NSCLC). However, the benefit of immunotherapy is limited to a subset of patients. This study aimed to investigate the value of combining immune and genetic variables analyzed within 3–4 weeks after the start of PD-1 blockade therapy to predict long-term clinical response.Materials and methodologyBlood collected from patients with NSCLC were analyzed for changes in the frequency and concentration of immune cells using a clinical flow cytometry assay. Next-generation sequencing (NGS) was performed on DNA extracted from archival tumor biopsies of the same patients. Patients were categorized as clinical responders or non-responders based on the 9 months’ assessment after the start of therapy.ResultsWe report a significant increase in the post-treatment frequency of activated effector memory CD4+ and CD8+ T-cells compared with pre-treatment levels in the blood. Baseline frequencies of B cells but not NK cells, T cells, or regulatory T cells were associated with the clinical response to PD-1 blockade. NGS of tumor tissues identified pathogenic or likely pathogenic mutations in tumor protein P53, Kirsten rat sarcoma virus, Kelch-like ECH-associated protein 1, neurogenic locus notch homolog protein 1, and serine/threonine kinase 11, primarily in the responder group. Finally, multivariate analysis of combined immune and genetic factors but neither alone, could discriminate between responders and non-responders.ConclusionCombined analyses of select immune cell subsets and genetic mutations could predict early clinical responses to immunotherapy in patients with NSCLC and after validation, can guide clinical precision medicine efforts.

Abstract Objectives Direct cost for methods of prediction also named risk assessment in dentistry may be negligible compared with the cost of extensive constructions. On the other hand, as risk assessment is performed daily and for several patients in general dental practice, the costs may be considerable. The objective was to summarize evidence in studies of economic evaluation of prognostic prediction multivariable models and methods of caries and periodontitis and to identify knowledge gaps (PROSPERO registration number: CRD42020149763). Material and methods Four electronic databases (PubMed, Web of Science, The Cochrane Library, NHS Economic Evaluation Database) and reference lists of included studies were searched. Titles and abstracts were screened by two reviewers in parallel. Full‐text studies reporting resources used, costs and cost‐effectiveness of prediction models and methods were selected and critically appraised using a protocol based on items from the CHEERS checklist for economic evaluations and the CHARMS checklist for evaluation of prediction studies. Results From 38 selected studies, six studies on prediction fulfilled the eligibility criteria, four on caries and two on periodontitis. As the economic evaluations differed in method and perspective among the studies, the results could not be generalized. Our systematic review revealed methodological shortcomings regarding the description of predictive models and methods, and particularly of the economic evaluation. Conclusions The systematic review highlighted a paucity of economic evaluations regarding methods or multivariable models for prediction of caries and periodontitis. Our results indicate that what we currently practice using models and methods to predict caries and periodontitis lacks evidence regarding cost‐effectiveness.

Syntrophus aciditrophicus is a model syntrophic bacterium that degrades key intermediates in anaerobic decomposition, such as benzoate, cyclohexane-1-carboxylate, and certain fatty acids, to acetate when grown with hydrogen-/formate-consuming microorganisms. ATP formation coupled to acetate production is the main source for energy conservation by S. aciditrophicus However, the absence of homologs for phosphate acetyltransferase and acetate kinase in the genome of S. aciditrophicus leaves it unclear as to how ATP is formed, as most fermentative bacteria rely on these two enzymes to synthesize ATP from acetyl coenzyme A (CoA) and phosphate. Here, we combine transcriptomic, proteomic, metabolite, and enzymatic approaches to show that S. aciditrophicus uses AMP-forming, acetyl-CoA synthetase (Acs1) for ATP synthesis from acetyl-CoA. acs1 mRNA and Acs1 were abundant in transcriptomes and proteomes, respectively, of S. aciditrophicus grown in pure culture and coculture. Cell extracts of S. aciditrophicus had low or undetectable acetate kinase and phosphate acetyltransferase activities but had high acetyl-CoA synthetase activity under all growth conditions tested. Both Acs1 purified from S. aciditrophicus and recombinantly produced Acs1 catalyzed ATP and acetate formation from acetyl-CoA, AMP, and pyrophosphate. High pyrophosphate levels and a high AMP-to-ATP ratio (5.9 ± 1.4) in S. aciditrophicus cells support the operation of Acs1 in the acetate-forming direction. Thus, S. aciditrophicus has a unique approach to conserve energy involving pyrophosphate, AMP, acetyl-CoA, and an AMP-forming, acetyl-CoA synthetase. Bacteria use two enzymes, phosphate acetyltransferase and acetate kinase, to make ATP from acetyl-CoA, while acetate-forming archaea use a single enzyme, an ADP-forming, acetyl-CoA synthetase, to synthesize ATP and acetate from acetyl-CoA. Syntrophus aciditrophicus apparently relies on a different approach to conserve energy during acetyl-CoA metabolism, as its genome does not have homologs to the genes for phosphate acetyltransferase and acetate kinase. Here, we show that S. aciditrophicus uses an alternative approach, an AMP-forming, acetyl-CoA synthetase, to make ATP from acetyl-CoA. AMP-forming, acetyl-CoA synthetases were previously thought to function only in the activation of acetate to acetyl-CoA.

Methanospirillum hungatei strain JF1 (DSM 864) is a methane-producing archaeon and is the type species of the genus Methanospirillum, which belongs to the family Methanospirillaceae within the order Methanomicrobiales. Its genome was selected for sequencing due to its ability to utilize hydrogen and carbon dioxide and/or formate as a sole source of energy. Ecologically, M. hungatei functions as the hydrogen- and/or formate-using partner with many species of syntrophic bacteria. Its morphology is distinct from other methanogens with the ability to form long chains of cells (up to 100 μm in length), which are enclosed within a sheath-like structure, and terminal cells with polar flagella. The genome of M. hungatei strain JF1 is the first completely sequenced genome of the family Methanospirillaceae, and it has a circular genome of 3,544,738 bp containing 3,239 protein coding and 68 RNA genes. The large genome of M. hungatei JF1 suggests the presence of unrecognized biochemical/physiological properties that likely extend to the other Methanospirillaceae and include the ability to form the unusual sheath-like structure and to successfully interact with syntrophic bacteria.

Using tract-level US Census data and triple-difference estimators, the authors test whether firms increase their use of part-time workers when faced with capped wage subsidies. By limiting the maximum subsidy per worker, such subsidies create incentives for firms to increase the share of their payroll that is eligible for the subsidy by increasing use of part-time or low-wage workers. Results suggest that firms located in federal Empowerment Zones in the United States responded to the program's capped wage subsidies by expanding their use of part-time workers, particularly in locations where the subsidy cap is likely to bind. Results also show a shift toward hiring lower-skill workers. [ABSTRACT FROM AUTHOR]

Microbial syntrophy is a vital metabolic interaction necessary for the complete oxidation of organic biomass to methane in all-anaerobic ecosystems. However, this process is thermodynamically constrained and represents an ecosystem-level metabolic bottleneck. To gain insight into the physiology of this process, a shotgun proteomics approach was used to quantify the protein landscape of the model syntrophic metabolizer, Syntrophomonas wolfei, grown axenically and syntrophically with Methanospirillum hungatei. Remarkably, the abundance of most proteins as represented by normalized spectral abundance factor (NSAF) value changed very little between the pure and coculture growth conditions. Among the most abundant proteins detected were GroEL and GroES chaperonins, a small heat shock protein, and proteins involved in electron transfer, beta-oxidation, and ATP synthesis. Several putative energy conservation enzyme systems that utilize NADH and ferredoxin were present. The abundance of an EtfAB2 and the membrane-bound iron-sulfur oxidoreductase (Swol_0698 gene product) delineated a potential conduit for electron transfer between acyl-CoA dehydrogenases and membrane redox carriers. Proteins detected only when S. wolfei was grown with M. hungatei included a zinc-dependent dehydrogenase with a GroES domain, whose gene is present in genomes in many organisms capable of syntrophy, and transcriptional regulators responsive to environmental stimuli or the physiological status of the cell. The proteomic analysis revealed an emphasis on macromolecular stability and energy metabolism by S. wolfei and presence of regulatory mechanisms responsive to external stimuli and cellular physiological status.

Microbial syntrophy is a vital metabolic interaction necessary for the complete oxidation of organic biomass to methane in all-anaerobic ecosystems. However, this process is thermodynamically constrained and represents an ecosystem-level metabolic bottleneck. To gain insight into the physiology of this process, a shotgun proteomics approach was used to quantify the protein landscape of the model syntrophic metabolizer, Syntrophomonas wolfei, grown axenically and syntrophically with Methanospirillum hungatei. Remarkably, the abundance of most proteins as represented by normalized spectral abundance factor (NSAF) value changed very little between the pure and coculture growth conditions. Among the most abundant proteins detected were GroEL and GroES chaperonins, a small heat shock protein, and proteins involved in electron transfer, beta-oxidation, and ATP synthesis. Several putative energy conservation enzyme systems that utilize NADH and ferredoxin were present. The abundance of an EtfAB2 and the membrane-bound iron-sulfur oxidoreductase (Swol_0698 gene product) delineated a potential conduit for electron transfer between acyl-CoA dehydrogenases and membrane redox carriers. Proteins detected only when S. wolfei was grown with M. hungatei included a zinc-dependent dehydrogenase with a GroES domain, whose gene is present in genomes in many organisms capable of syntrophy, and transcriptional regulators responsive to environmental stimuli or the physiological status of the cell. The proteomic analysis revealed an emphasis on macromolecular stability and energy metabolism by S. wolfei and presence of regulatory mechanisms responsive to external stimuli and cellular physiological status.

Syntrophobacter fumaroxidans strain MPOB(T) is the best-studied species of the genus Syntrophobacter. The species is of interest because of its anaerobic syntrophic lifestyle, its involvement in the conversion of propionate to acetate, H2 and CO2 during the overall degradation of organic matter, and its release of products that serve as substrates for other microorganisms. The strain is able to ferment fumarate in pure culture to CO2 and succinate, and is also able to grow as a sulfate reducer with propionate as an electron donor. This is the first complete genome sequence of a member of the genus Syntrophobacter and a member genus in the family Syntrophobacteraceae. Here we describe the features of this organism, together with the complete genome sequence and annotation. The 4,990,251 bp long genome with its 4,098 protein-coding and 81 RNA genes is a part of the Microbial Genome Program (MGP) and the Genomes to Life (GTL) Program project.

Many archaeal cell envelopes contain a protein coat or sheath composed of one or more surface exposed proteins. These surface layer (S-layer) proteins contribute structural integrity and protect the lipid membrane from environmental challenges. To explore the species diversity of these layers in the Methanosarcinaceae, the major S-layer protein in Methanosarcina barkeri strain Fusaro was identified using proteomics. The Mbar_A1758 gene product was present in multiple forms with apparent sizes of 130, 120, and 100 kDa, consistent with post-translational modifications including signal peptide excision and protein glycosylation. A protein with features related to the surface layer proteins found in Methanosarcina acetivorans C2A and Methanosarcina mazei Goel was identified in the M. barkeri genome. These data reveal a distinct conserved protein signature with features and implied cell surface architecture in the Methanosarcinaceae that is absent in other archaea. Paralogous gene expression patterns in two Methanosarcina species revealed abundant expression of a single S-layer paralog in each strain. Respective promoter elements were identified and shown to be conserved in mRNA coding and upstream untranslated regions. Prior M. acetivorans genome annotations assigned S-layer or surface layer associated roles of eighty genes: however, of 68 examined none was significantly expressed relative to the experimentally determined S-layer gene.

The identification of binding sites for regulatory proteins in the up-stream region of genes is an important ingredient towards the understanding of transcription regulation. In recent years, novel experimental techniques, as gene expression arrays, and the availability of entire genome sequences have opened the possibility for more detailed investigations in this domain. Traditionally, the reconstruction of the profile of a binding site and the localization of all its occurrences in a sequence are treated as separate problems. The first is tackled using a small group of sequences, known or suspected to contain the binding site, but with neither position or pattern known. One successful approach to such reconstruction problem is based on a probabilistic model of the sequence, represented as concatenation of background and motif stochastic words. Maximum likelihood or maximum a-posteriori estimates are obtained with EM or Gibbs-sampler algorithms [13, 14]. The second problem is approached considering one or multiple sequences of variable length; the pattern characterizing the motif is assumed known. Possible locations are identified on the base of scoring functions that highlight the similarity of the motif with the sequence portions. Cut off values for such similarity scores are hard to determine: ad hoc solutions or estimations on a training set are often adopted [17, 18]. Typically these techniques are used to scan one sequence of interest against a data-base of known binding sites. While there are historical and practical reasons to consider these two problems as separate, the current post-genomic era, where we are confronted with large abundance of sequence, calls for a different approach. Consider the problem, tackled in [18], of identifying all the the binding sites of the known regulatory proteins in the genome of E. Coli. While formally similar to blasting a small sequence of interest against a data-base of known regulatory proteins, there are substantial differences in these genome-wide search.

BackgroundThe archaeon, Methanosarcina acetivorans strain C2A forms methane, a potent greenhouse gas, from a variety of one-carbon substrates and acetate. Whereas the biochemical pathways leading to methane formation are well understood, little is known about the expression of the many of the genes that encode proteins needed for carbon flow, electron transfer and/or energy conservation. Quantitative transcript analysis was performed on twenty gene clusters encompassing over one hundred genes in M. acetivorans that encode enzymes/proteins with known or potential roles in substrate conversion to methane.ResultsThe expression of many seemingly "redundant" genes/gene clusters establish substrate dependent control of approximately seventy genes for methane production by the pathways for methanol and acetate utilization. These include genes for soluble-type and membrane-type heterodisulfide reductases (hdr), hydrogenases including genes for a vht-type F420 non-reducing hydrogenase, molybdenum-type (fmd) as well as tungsten-type (fwd) formylmethanofuran dehydrogenases, genes for rnf and mrp-type electron transfer complexes, for acetate uptake, plus multiple genes for aha- and atp-type ATP synthesis complexes. Analysis of promoters for seven gene clusters reveal UTR leaders of 51-137 nucleotides in length, raising the possibility of both transcriptional and translational levels of control.ConclusionsThe above findings establish the differential and coordinated expression of two major gene families in M. acetivorans in response to carbon/energy supply. Furthermore, the quantitative mRNA measurements demonstrate the dynamic range for modulating transcript abundance. Since many of these gene clusters in M. acetivorans are also present in other Methanosarcina species including M. mazei, and in M. barkeri, these findings provide a basis for predicting related control in these environmentally significant methanogens.

The authors examine the effect of labor unions on workplace safety. For identification, they exploit the timing and outcome of union elections, using establishments in which elections narrowly fail as a comparison group for establishments in which elections narrowly pass. Data on elections come from the National Labor Relations Board, and data on workplace safety come from the Occupational Safety and Health Administration. The results indicate that unionization had no detectable effect on accident case rates at the mean, but shifted downward the case-rate distribution below 2 cases per 100 full-time equivalent workers annually. The downward shift is most evident among larger bargaining units and manufacturing establishments. Results at the higher end of case-rate distribution are inconclusive. [ABSTRACT FROM AUTHOR]

This paper provides estimates of local employment multipliers from large, publicly subsidized firms. We use a synthetic control weighted difference‐in‐difference estimation procedure that matches treated areas with comparison areas to generate local employment multiplier estimates. We show that local employment multiplier estimates have a high degree of uncertainty, with a wide range of point estimates (both positive and negative) and varying degrees of statistical significance. There is a concentration of positive employment multipliers from manufacturing facilities, but little correlation between estimated multipliers and subsidy value. We demonstrate that our approach produces drastically different results than a traditional difference‐in‐difference approach. [ABSTRACT FROM AUTHOR]

The identification of binding sites for regulatory proteins in the up-stream region of genes is an important ingredient towards the understanding of transcription regulation. In recent years, novel experimental techniques, as gene expression arrays, and the availability of entire genome sequences have opened the possibility for more detailed investigations in this domain. Traditionally, the reconstruction of the profile of a binding site and the localization of all its occurrences in a sequence are treated as separate problems. The first is tackled using a small group of sequences, known or suspected to contain the binding site, but with neither position or pattern known. One successful approach to such reconstruction problem is based on a probabilistic model of the sequence, represented as concatenation of background and motif stochastic words. Maximum likelihood or maximum a-posteriori estimates are obtained with EM or Gibbs-sampler algorithms [13, 14]. The second problem is approached considering one or multiple sequences of variable length; the pattern characterizing the motif is assumed known. Possible locations are identified on the base of scoring functions that highlight the similarity of the motif with the sequence portions. Cut off values for such similarity scores are hard to determine: ad hoc solutions or estimations on a training set are often adopted [17, 18]. Typically these techniques are used to scan one sequence of interest against a data-base of known binding sites. While there are historical and practical reasons to consider these two problems as separate, the current post-genomic era, where we are confronted with large abundance of sequence, calls for a different approach. Consider the problem, tackled in [18], of identifying all the the binding sites of the known regulatory proteins in the genome of E. Coli. While formally similar to blasting a small sequence of interest against a data-base of known regulatory proteins, there are substantial differences in these genome-wide search. On the one hand, as one scans through the genome for binding sites of LexA—to take one example—and finds a substantial number of them, it seems appropriate one should use the information in the identified locations to update the current pattern description. On the other hand, given that the output is not going to include a small number of sites, that can be further investigated, but a large collection of them, the assessment of significance cut-off should be based on proper probabilistic statements. To address these issues, one would need a probability model for the entire genome sequence, that can lead to evaluation of specific a-posteriori probabilities of appearance of a binding site in any given location, and whose parameters can be estimated on the base of data. At the same time, given the scale of the problem, the model should be suitable for rapid computation. In an attempt to address such need we introduce here the Vocabulon model. Section 2 gives a description of the probability model we employ; its differences from others in the literature; and its current implementation. We then present the results of multiple investigations on E. Coli sequence. Given that genome-wide information on the location of binding sites is not available, we used results of gene expression array experiments to corroborate our results, arguing in favor of a novel perspective in array analysis.