Periodontitis deteriorates renal fibrosis and macrophage infiltration in rats with chronic kidney disease.

OBJECTIVE: The objective of this study was to examine the effect of periodontitis on renal function and morphology in rats with or without nephrectomy (Nx)-induced chronic kidney disease (CKD). METHODS: Rats were divided into sham surgery (Sham), Sham with tooth ligation (ShamL), Nx, and NxL groups. Periodontitis was induced by tooth ligation at 16-week olds. Creatinine, alveolar bone area, and renal histopathology were analyzed at 20-week olds. RESULTS: Creatinine did not differ between the Sham and ShamL groups or between the Nx and NxL groups. The ShamL and NxL groups (both p = 0.002) had less alveolar bone area than the Sham group. The NxL group had fewer glomeruli than the Nx group (p < 0.000). The periodontitis groups demonstrated more tubulointerstitial fibrosis (Sham vs. ShamL p = 0.002, Nx vs. NxL p < 0.000) and macrophage infiltration (Sham vs. ShamL p = 0.002, Nx vs. NxL p = 0.006) than the groups without periodontitis. Only the NxL group had greater renal TNFα expression than the Sham group (p < 0.003). CONCLUSIONS: These suggest that periodontitis increases renal fibrosis and inflammation in the presence or absence of CKD but does not affect renal function. Periodontitis also increases TNFα expression in the presence of CKD.

Alveolar bone and tibia responses to hormonal and mineral abnormalities in rats with chronic kidney disease: A pilot study.

OBJECTIVES: As the impact of chronic kidney disease (CKD) severity on different bone types remains unclear, we induced increasing levels of CKD severity in a rat model and investigated hormone and mineral levels as well as alveolar and tibia bone histomorphology. METHODS: Rats were divided into sham operation (sham), 4/6 nephrectomy (4/6Nx), 5/6Nx, and 4/6Nx with hyperphosphorous (HP) diet (4/6NxHP). At week 20, BUN, FGF23, PTH, and P were estimated in plasma. Bone parameters were evaluated by microCT, and osteoclasts and osteoid areas were evaluated by TRAP and H&E stains, respectively. RESULTS: The 4/6NxHP and 5/6Nx groups had elevated PTH, and the 4/6NxHP group alone had elevated P. Compared to the 4/6Nx group, the 4/6NxHP group demonstrated increased FGF23 and P. In the alveolar bone, the 4/6NxHP group had reduced bone volume and BMD compared to the sham and 4/6Nx groups. In the tibia cortical bone, bone surface density was higher in the 4/6NxHP group compared to the sham group. Tibia cortical bone volume was negatively correlated with FGF23 and P. Moreover, alveolar bone volume was negatively correlated with FGF23, PTH, and P. CONCLUSIONS: Our results demonstrate that hormone and mineral levels vary with CKD severity, and alveolar bone loss strongly correlates with these hormone and mineral alterations.

Distribution of neutrophil and monocyte/macrophage populations induced by the CXCR4 inhibitor AMD3100 in blood and periodontal tissue early after periodontitis induction.

CXCR4, a CXCL12 receptor, is expressed on epithelial cells, fibroblasts, and inflammatory cells. The CXCR4-CXCL12 interaction is related to the migration of neutrophils and monocytes/macrophages. Periodontitis, an inflammatory disease mainly caused by gram-negative bacteria, is characterized by infiltration of circulating inflammatory cells and alveolar bone (AB) loss. To investigate whether CXCR4 is involved in the distribution of neutrophils and monocytes/macrophages early after periodontitis induction, we examined the effects of AMD3100 (AMD), a CXCR4 antagonist, in ligature-induced periodontitis mice and LPS-injected air pouch mice. The periodontitis study was accomplished in control (C), periodontitis (P), and P + AMD groups. Periodontitis was induced by ligation of the mandibular first molar. AMD was intraperitoneally administered daily beginning the day before ligation until sacrifice on the third day after ligation. The air pouch study was accomplished in C, lipopolysaccharide (LPS), and LPS + AMD groups. Air pouches on mice backs were formed by subcutaneous injection of sterilized air. AMD was administered and then LPS was injected into the air pouch. For the detection of neutrophils and monocytes/macrophages in blood and air pouch exudates, flow cytometry was performed with anti-Ly6G/anti-CD11b antibodies (Abs) and anti-CD115 Ab, respectively. In periodontal tissue, Ly6G+ cells and CD115+ cells were counted by immunohistological analysis. AB loss was estimated by the periodontal ligament area in the furcation. In the periodontitis study, the P group showed higher numbers of Ly6G+ cells and CD115+ cells in blood and periodontal tissue than the C group. The P + AMD group showed a greater number of Ly6G+ cells and CD115+ cells in blood, but not in periodontal tissue compared to the P group. There was no difference in AB loss between the P and P + AMD groups. In the air pouch study, the LPS group had higher levels of Ly6G+ CD11b+ cells and CD115+ cells in both blood and exudates than the C group. The number of these cells in the LPS + AMD group was higher in blood than in the LPS group, but not in the exudates. The CXCR4 antagonist further increased neutrophil and monocyte/macrophage populations in the blood, but did not alter the levels in the periodontal tissue and exudates in mice with periodontitis and LPS-injected air pouches. These results suggest that during inflammatory conditions such as periodontitis, CXCR4 is involved in the distribution of neutrophils and monocytes/macrophages in the blood, but not in inflamed peripheral tissues.

gpart: human genome partitioning and visualization of high-density SNP data by identifying haplotype blocks.

SUMMARY: For the analysis of high-throughput genomic data produced by next-generation sequencing (NGS) technologies, researchers need to identify linkage disequilibrium (LD) structure in the genome. In this work, we developed an R package gpart which provides clustering algorithms to define LD blocks or analysis units consisting of SNPs. The visualization tool in gpart can display the LD structure and gene positions for up to 20 000 SNPs in one image. The gpart functions facilitate construction of LD blocks and SNP partitions for vast amounts of genome sequencing data within reasonable time and memory limits in personal computing environments. AVAILABILITY AND IMPLEMENTATION: The R package is available at https://bioconductor.org/packages/gpart. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

The presence of neutrophils causes RANKL expression in periodontal tissue, giving rise to osteoclast formation.

BACKGROUNDS AND OBJECTIVE: Increased neutrophil infiltration and osteoclast formation are key characteristics of periodontitis. The effect of these neutrophils on osteoclast formation in periodontitis remains unclear. Therefore, we investigated the effects of neutrophils on osteoclast formation in a neutrophil-deficient mouse model of periodontitis. METHODS: Anti-Ly6G antibody (Ab) was used for neutrophil depletion in two mouse models: periodontitis and air pouch. In the periodontitis experiments, mice were divided into PBS-administered control (C), control Ab-administered periodontitis (P), and anti-Ly6G Ab-administered periodontitis (P + Ly6G) groups. Periodontitis was induced by ligature of mandibular first molars. In the air pouch experiments, mice were divided into PBS-administered (C), LPS and control Ab-administered (LPS), and LPS and anti-Ly6G Ab-administered (LPS + Ly6G) groups. Neutrophil migration into air pouches was induced by LPS injection. Flow cytometry was used to examine CD11b+ Ly6G+ neutrophils in the blood of periodontitis mice and CD11b+ Ly6G+ RANKL+ neutrophils in exudates of air pouch mice. In periodontal tissue, Ly6G+ neutrophil and RANKL+ cell numbers in periodontal ligament and alveolar bone areas were estimated using immunohistochemistry, osteoclast numbers were measured using TRAP assay, and alveolar bone loss was determined by H&E staining. RESULTS: In blood, CD11b+ Ly6G+ neutrophils were found in greater percentage in the P group than in the C group on days 3 and 7. However, the percentage of neutrophils was lower in the P + Ly6G group than in the C and P groups. In periodontal tissue, the numbers of Ly6G+ neutrophils and RANKL+ cells were lower in the P + Ly6G group than in the P group on day 3. Ly6G+ neutrophil numbers decreased more in the P + Ly6G group than in the P group on day 7, but RANKL+ cell numbers did not decrease in the P + Ly6G group. In exudates, the number of CD11b+ Ly6G+ RANKL+ neutrophils was greater in the LPS group than in the C and LPS + Ly6G groups. On days 3 and 7, the numbers of osteoclasts and alveolar bone loss were greater in periodontal tissue in the P and P + Ly6G groups than in the C group. Interestingly, there were fewer osteoclasts in the P + Ly6G group than in the P group on day 3. CONCLUSION: Neutrophil deficiency caused a reduction in numbers of both RANKL+ cells and osteoclasts in periodontitis-induced tissues only on day 3. Furthermore, in the LPS-injected air pouch model, neutrophil deficiency reduced the influx of RANKL+ neutrophils. These findings suggest that the presence of neutrophils induces RANKL expression and could induce osteoclast formation in the early stages of periodontitis.

Efficient pathway enrichment and network analysis of GWAS summary data using GSA-SNP2.

Pathway-based analysis in genome-wide association study (GWAS) is being widely used to uncover novel multi-genic functional associations. Many of these pathway-based methods have been used to test the enrichment of the associated genes in the pathways, but exhibited low powers and were highly affected by free parameters. We present the novel method and software GSA-SNP2 for pathway enrichment analysis of GWAS P-value data. GSA-SNP2 provides high power, decent type I error control and fast computation by incorporating the random set model and SNP-count adjusted gene score. In a comparative study using simulated and real GWAS data, GSA-SNP2 exhibited high power and best prioritized gold standard positive pathways compared with six existing enrichment-based methods and two self-contained methods (alternative pathway analysis approach). Based on these results, the difference between pathway analysis approaches was investigated and the effects of the gene correlation structures on the pathway enrichment analysis were also discussed. In addition, GSA-SNP2 is able to visualize protein interaction networks within and across the significant pathways so that the user can prioritize the core subnetworks for further studies. GSA-SNP2 is freely available at https://sourceforge.net/projects/gsasnp2.

A new haplotype block detection method for dense genome sequencing data based on interval graph modeling of clusters of highly correlated SNPs.

Motivation: Linkage disequilibrium (LD) block construction is required for research in population genetics and genetic epidemiology, including specification of sets of single nucleotide polymorphisms (SNPs) for analysis of multi-SNP based association and identification of haplotype blocks in high density sequencing data. Existing methods based on a narrow sense definition do not allow intermediate regions of low LD between strongly associated SNP pairs and tend to split high density SNP data into small blocks having high between-block correlation. Results: We present Big-LD, a block partition method based on interval graph modeling of LD bins which are clusters of strong pairwise LD SNPs, not necessarily physically consecutive. Big-LD uses an agglomerative approach that starts by identifying small communities of SNPs, i.e. the SNPs in each LD bin region, and proceeds by merging these communities. We determine the number of blocks using a method to find maximum-weight independent set. Big-LD produces larger LD blocks compared to existing methods such as MATILDE, Haploview, MIG ++, or S-MIG ++ and the LD blocks better agree with recombination hotspot locations determined by sperm-typing experiments. The observed average runtime of Big-LD for 13 288 240 non-monomorphic SNPs from 1000 Genomes Project autosome data (286 East Asians) is about 5.83 h, which is a significant improvement over the existing methods. Availability and implementation: Source code and documentation are available for download at http://github.com/sunnyeesl/BigLD. Contact: yyoo@snu.ac.kr. Supplementary information: Supplementary data are available at Bioinformatics online.

Prolines in Transit Peptides Are Crucial for Efficient Preprotein Translocation into Chloroplasts.

Chloroplasts import many preproteins that can be classified based on their physicochemical properties. The cleavable N-terminal transit peptide (TP) of chloroplast preproteins contains all the information required for import into chloroplasts through Toc/Tic translocons. The question of whether and how the physicochemical properties of preproteins affect TP-mediated import into chloroplasts has not been elucidated. Here, we present evidence that Pro residues in TP mediate efficient translocation through the chloroplast envelope membranes for proteins containing transmembrane domains (TMDs) or proteins prone to aggregation. By contrast, the translocation of soluble proteins through the chloroplast envelope membranes is less dependent on TP prolines. Proless TPs failed to mediate protein translocation into chloroplasts; instead, these mutant TPs led to protein mistargeting to the chloroplast envelope membranes or nonspecific protein aggregation during import into chloroplasts. The mistargeting of TMD-containing proteins caused by Pro-less TPs in wild-type protoplasts was mimicked by wild-type TPs in hsp93-V protoplasts, in which preprotein translocation is compromised. We propose that the physicochemical properties of chloroplast proteins affect protein translocation through the chloroplast envelope, and prolines in TP have a crucial role in the efficient translocation of TMD-containing proteins.

Exogenous CLASP2 protein treatment enhances wound healing in vitro and in vivo.

Proliferative and migratory abilities of fibroblasts are essential for wound healing at the skin surface. Cytoplasmic linker-associated protein-2 (CLASP2) was originally found to interact with cytoplasmic linker protein (CLIP)-170. CLASP2 plays an important role in microtubule stabilization and the microtubule-stabilizing activity of CLASP2 depends on its interactions with end binding (EB)-1 and CLIP-170. Although the microtubule-stabilizing role of CLASP2 is well established, the effects of CLASP2 on the migration and proliferation of fibroblasts remain unclear in the context of wound healing. Therefore, we tested the utilization of CLASP2 as a directly applied protein drug to improve wound healing by promoting the migration of effector cells, including skin fibroblasts, to the site of repair or injury using an in vivo excisional wound mouse model and in vitro Hs27 skin fibroblast model. Epidermal growth factor, which is a recognized contributor to cell proliferation and migration, was used as positive control. In vitro and in vivo, CLASP2 treatment significantly enhanced cell migration and accelerated wound closure. Furthermore, in vivo, the CLASP2-treated animal group displayed enhanced epidermal repair and collagen deposition. Next, we studied the mechanism of CLASP2 for wound healing. Increasing the abundance of intracellular free CLASP2 in skin fibroblasts by supplying exogenous CLASP2 seemed to stabilize microtubules through an interaction between CLASP2 and CLIP-170, as well as EB1. Exogenous CLASP2 also showed direct binding with IQGAP1, increasing both cyclic adenosine monophosphate activity and phosphorylation of glycogen synthase kinase 3ß, which in turn reinstated the binding between free CLASP2 and IQGAP1. In summary, exogenous CLASP2 increased Hs27 skin fibroblast migration by interacting with IQGAP1 and other cytoskeletal linker proteins, such as CLIP-170 and EB1. Our results strongly suggest that CLASP2 can be developed in wound healing drugs for skin repair and/or regenerating cosmetic products.

Multiple linear combination (MLC) regression tests for common variants adapted to linkage disequilibrium structure.

By jointly analyzing multiple variants within a gene, instead of one at a time, gene-based multiple regression can improve power, robustness, and interpretation in genetic association analysis. We investigate multiple linear combination (MLC) test statistics for analysis of common variants under realistic trait models with linkage disequilibrium (LD) based on HapMap Asian haplotypes. MLC is a directional test that exploits LD structure in a gene to construct clusters of closely correlated variants recoded such that the majority of pairwise correlations are positive. It combines variant effects within the same cluster linearly, and aggregates cluster-specific effects in a quadratic sum of squares and cross-products, producing a test statistic with reduced degrees of freedom (df) equal to the number of clusters. By simulation studies of 1000 genes from across the genome, we demonstrate that MLC is a well-powered and robust choice among existing methods across a broad range of gene structures. Compared to minimum P-value, variance-component, and principal-component methods, the mean power of MLC is never much lower than that of other methods, and can be higher, particularly with multiple causal variants. Moreover, the variation in gene-specific MLC test size and power across 1000 genes is less than that of other methods, suggesting it is a complementary approach for discovery in genome-wide analysis. The cluster construction of the MLC test statistics helps reveal within-gene LD structure, allowing interpretation of clustered variants as haplotypic effects, while multiple regression helps to distinguish direct and indirect associations.

Simvastatin attenuates tibial bone loss in rats with type 1 diabetes and periodontitis.

BACKGROUND: Diabetes induces long bone loss and aggravation of periodontitis-induced alveolar bone loss. Simvastatin (SIM), which is a lipid-lowering agent is known to have an anabolic effect on bone. Therefore, we investigated effect of SIM on tibial and alveolar bone loss in type 1 diabetic rats with periodontitis. METHODS: Rats were divided into control (C), diabetes with periodontitis (DP), and diabetes with periodontitis treated with SIM (DPS) groups. DP and DPS groups were intravenously injected with streptozotocin (50 mg/kg), and C group was injected with citrate buffer. Seven days later (day 0), periodontitis was induced by ligatures of mandibular first molars. DP and DPS groups were orally administered vehicle or SIM (30 mg/kg) from day 0 to days 3, 10, or 20. Alveolar and tibial bone loss was measured using histological and m-CT analysis alone or in combination. Osteoclast number and sclerostin-positive osteocytes in tibiae were evaluated by tartrate-resistant acid phosphatase and immunohistochemical staining, respectively. Glucose, triglyceride (TG), cholesterol (CHO), and low-density lipoprotein (LDL) were evaluated. RESULTS: Consistent with diabetes induction, the DP group showed higher glucose and TG levels at all timepoints and higher CHO levels on day 20 than C group. Compared to the DP group, the DPS group exhibited reduced levels of glucose (day 3), TG (days 10 and 20), CHO, and LDL levels (day 20). Bone loss analysis revealed that the DP group had lower bone volume fraction, bone mineral density, bone surface density, and trabecular number in tibiae than C group at all timepoints. Interestingly, the DPS group exhibited elevation of these indices at early stages compared to the DP group. The DPS group showed reduction of osteoclasts (day 3) and sclerostin-positive osteocytes (days 3 and 20) compared with the DP group. There was no difference in alveolar bone loss between DP and DPS groups. CONCLUSIONS: These results suggest that SIM attenuates tibial, but not alveolar bone loss in type 1 diabetic rats with periodontitis. Moreover, attenuation of tibial bone loss by SIM may be related to inhibition of osteoclast formation and reduction of sclerostin expression.

Intermittent PTH administration improves alveolar bone formation in type 1 diabetic rats with periodontitis.

BACKGROUND: Periodontitis is an infectious disease that manifests as alveolar bone loss surrounding the roots of teeth. Diabetes aggravates periodontitis-induced alveolar bone loss via suppression of bone formation. Intermittent parathyroid hormone (PTH) administration displays an anabolic effect on bone. In this study, we investigated the effect of intermittent PTH administration on alveolar bone loss in type 1 diabetic rats with periodontitis. METHODS: Rats were divided into control (C), periodontitis (P), periodontitis treated with PTH (P + PTH), diabetes with periodontitis (DP), and diabetes with periodontitis treated with PTH (DP + PTH) groups. To induce type 1 diabetes, rats were injected with streptozotocin and periodontitis was induced bilaterally by applying ligatures to the mandibular first molars for 30 days. During the experimental period, the P + PTH and DP + PTH groups were subcutaneously injected with PTH (40 µg/kg) three times per week, whereas the C, P, and DP groups were injected with citrate buffer. To observe the mineralization of the alveolar bone, the DP and DP + PTH groups were injected with calcein on days 10 and 27, and with alizarin red on day 20. Thirty days after ligation, histological findings and fluorescence labeling were analyzed in the furcations of the mandibular first molars. Sclerostin-positive osteocytes were assessed by immunohistochemical analyses. RESULTS: The DP groups had smaller areas of alveolar bone than the other groups, and the DP + PTH group had a larger alveolar bone area than the DP group. The DP group had less osteoid formation than the C group, whereas the DP + PTH had greater osteoid formation than the DP group. Fluorescence labeling results revealed that the DP + PTH group had more mineral deposition on the alveolar bone than the DP group. The DP + PTH group exhibited lower percentage of sclerostin-positive osteocytes in alveolar bone than the DP group. CONCLUSIONS: Intermittent PTH administration diminishes alveolar bone loss and sclerostin expression in osteocytes, but increases osteoid formation and mineralization, suggesting that intermittent PTH administration attenuates diabetes-aggravated alveolar bone loss by the induction of bone formation. PTH-induced bone formation may be related to the regulation of osteocytic sclerostin expression in type 1 diabetic rats with periodontitis.

The Prenylated Rab GTPase Receptor PRA1.F4 Contributes to Protein Exit from the Golgi Apparatus.

Prenylated Rab acceptor1 (PRA1) functions in the recruitment of prenylated Rab proteins to their cognate organelles. Arabidopsis (Arabidopsis thaliana) contains a large number of proteins belonging to the AtPRA1 family. However, their physiological roles remain largely unknown. Here, we investigated the physiological role of AtPRA1.F4, a member of the AtPRA1 family. A T-DNA insertion knockdown mutant of AtPRA1.F4, atpra1.f4, was smaller in stature than parent plants and possessed shorter roots, whereas transgenic plants overexpressing HA:AtPRA1.F4 showed enhanced development of secondary roots and root hairs. However, both overexpression and knockdown plants exhibited increased sensitivity to high-salt stress, lower vacuolar Na+/K+-ATPase and plasma membrane ATPase activities, lower and higher pH in the vacuole and apoplast, respectively, and highly vesiculated Golgi apparatus. HA:AtPRA1.F4 localized to the Golgi apparatus and assembled into high-molecular-weight complexes. atpra1.f4 plants displayed a defect in vacuolar trafficking, which was complemented by low but not high levels of HA:AtPRA1.F4 Overexpression of HA:AtPRA1.F4 also inhibited protein trafficking at the Golgi apparatus, albeit differentially depending on the final destination or type of protein: trafficking of vacuolar proteins, plasma membrane proteins, and trans-Golgi network (TGN)-localized SYP61 was strongly inhibited; trafficking of TGN-localized SYP51 was slightly inhibited; and trafficking of secretory proteins and TGN-localized SYP41 was negligibly or not significantly inhibited. Based on these results, we propose that Golgi-localized AtPRA1.F4 is involved in the exit of many but not all types of post-Golgi proteins from the Golgi apparatus. Additionally, an appropriate level of AtPRA1.F4 is crucial for its function at the Golgi apparatus.

Mitochondrial targeting of the Arabidopsis F1-ATPase γ-subunit via multiple compensatory and synergistic presequence motifs.

The majority of mitochondrial proteins are encoded in the nuclear genome and imported into mitochondria posttranslationally from the cytosol. An N-terminal presequence functions as the signal for the import of mitochondrial proteins. However, the functional information in the presequence remains elusive. This study reports the identification of critical sequence motifs from the presequence of Arabidopsis thaliana F1-ATPase γ-subunit (pFAγ). pFAγ was divided into six 10-amino acid segments, designated P1 to P6 from the N to the C terminus, each of which was further divided into two 5-amino acid subdivisions. These P segments and their subdivisions were substituted with Ala residues and fused to green fluorescent protein (GFP). Protoplast targeting experiments using these GFP constructs revealed that pFAγ contains several functional sequence motifs that are dispersed throughout the presequence. The sequence motifs DQEEG (P4a) and VVRNR (P5b) were involved in translocation across the mitochondrial membranes. The sequence motifs IAARP (P2b) and IAAIR (P3a) participated in binding to mitochondria. The sequence motifs RLLPS (P2a) and SISTQ (P5a) assisted in pulling proteins into the matrix, and the sequence motif IAARP (P2b) functioned in Tom20-dependent import. In addition, these sequence motifs exhibit complex relationships, including synergistic functions. Thus, multiple sequence motifs dispersed throughout the presequence are proposed to function cooperatively during protein import into mitochondria.

Effect of the interaction between periodontitis and type 1 diabetes mellitus on alveolar bone, mandibular condyle and tibia.

OBJECTIVE: This study examined the effect of the interaction between periodontitis and type 1 diabetes mellitus on alveolar bone, mandibular condyle and tibia in animal models. MATERIALS AND METHODS: Rats were divided into normal, periodontitis, diabetic and diabetic with periodontitis groups. After injection of streptozotocin to induce diabetes, periodontitis was induced by ligation of both lower-side first molars for 30 days. Alveolar bone loss and trabecular bone volume fraction (BVF) of the mandibular condyle and tibia were estimated via hematoxylin and eosin staining and micro-computed tomography, respectively. Osteoclastogenesis of bone marrow cells isolated from tibia and femur was assayed using tartrate-resistant acid phosphatase staining. RESULTS: The cemento-enamel junction to the alveolar bone crest distance and ratio of periodontal ligament area in the diabetic with periodontitis group were significantly increased compared to those of the periodontitis group. Mandibular condyle BVF did not differ among groups. The BVF of tibia in the diabetic and diabetic with periodontitis groups was lower than that of the normal and periodontitis groups. Osteoclastogenesis of bone marrow cells in the diabetic groups was higher than that in the non-diabetic groups. However, the BVF of tibia and osteoclastogenesis in the diabetic with periodontitis group were not significantly different than those in the diabetic group. CONCLUSIONS: Type 1 diabetes mellitus aggravates alveolar bone loss induced by periodontitis, but periodontitis does not alter the mandibular condyle and tibia bone loss induced by diabetes. Alveolar bone, mandibular condyle and tibia may have different responses to bone loss stimuli in the diabetic environment.

Supervised diagnostic classification of cognitive attributes using data augmentation.

Over recent decades, machine learning, an integral subfield of artificial intelligence, has revolutionized diverse sectors, enabling data-driven decisions with minimal human intervention. In particular, the field of educational assessment emerges as a promising area for machine learning applications, where students can be classified and diagnosed using their performance data. The objectives of Diagnostic Classification Models (DCMs), which provide a suite of methods for diagnosing students' cognitive states in relation to the mastery of necessary cognitive attributes for solving problems in a test, can be effectively addressed through machine learning techniques. However, the challenge lies in the latent nature of cognitive status, which makes it difficult to obtain labels for the training dataset. Consequently, the application of machine learning methods to DCMs often assumes smaller training sets with labels derived either from theoretical considerations or human experts. In this study, the authors propose a supervised diagnostic classification model with data augmentation (SDCM-DA). This method is designed to utilize the augmented data using a data generation model constructed by leveraging the probability of correct responses for each attribute mastery pattern derived from the expert-labeled dataset. To explore the benefits of data augmentation, a simulation study is carried out, contrasting it with classification methods that rely solely on the expert-labeled dataset for training. The findings reveal that utilizing data augmentation with the estimated probabilities of correct responses substantially enhances classification accuracy. This holds true even when the augmentation originates from a small labeled sample with occasional labeling errors, and when the tests contain lower-quality items that may inaccurately measure students' true cognitive status. Moreover, the study demonstrates that leveraging augmented data for learning can enable the successful classification of students, thereby eliminating the necessity for specifying an underlying response model.

Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID.

BACKGROUND: Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. METHODS: We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan-Meier curves to better understand COVID-19 reinfections. RESULTS: Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value: <0.0001) with a medium effect size (Cramer's V: 0.20, DoF = 3). Individuals who experienced severe initial and first reinfection were older in age and at a higher mortality risk than those who had mild initial infection and reinfection. CONCLUSIONS: In a large patient cohort, we find that the severity of reinfection appears to be associated with the severity of initial infection and that Long COVID diagnoses appear to occur more often following initial infection than reinfection in the same epoch. Future research may build on these findings to better understand COVID-19 reinfections.

More than three years after the start of the COVID-19 pandemic, individuals are frequently reporting multiple COVID-19 infections. However, these reinfections remain poorly understood. Here, we investigate COVID-19 reinfections in a large electronic health record cohort of over 3 million patients. We use data summary techniques and statistical tests to characterize reinfections and their relationships with disease severity, biomarkers, and Long COVID. We find that individuals with severe initial infection are more likely to experience severe reinfection, that some protein levels are lower, leading to reinfection, and that a lower proportion of individuals are diagnosed with Long COVID following reinfection than initial infection. Our work highlights the prevalence and impact of reinfections and suggests the need for further research.

Finding Long-COVID: Temporal Topic Modeling of Electronic Health Records from the N3C and RECOVER Programs.

Post-Acute Sequelae of SARS-CoV-2 infection (PASC), also known as Long-COVID, encompasses a variety of complex and varied outcomes following COVID-19 infection that are still poorly understood. We clustered over 600 million condition diagnoses from 14 million patients available through the National COVID Cohort Collaborative (N3C), generating hundreds of highly detailed clinical phenotypes. Assessing patient clinical trajectories using these clusters allowed us to identify individual conditions and phenotypes strongly increased after acute infection. We found many conditions increased in COVID-19 patients compared to controls, and using a novel method to associate patients with clusters over time, we additionally found phenotypes specific to patient sex, age, wave of infection, and PASC diagnosis status. While many of these results reflect known PASC symptoms, the resolution provided by this unprecedented data scale suggests avenues for improved diagnostics and mechanistic understanding of this multifaceted disease.

Long COVID incidence in adults and children between 2020 and 2023: a real-world data study from the RECOVER Initiative.

Estimates of post-acute sequelae of SARS-CoV-2 infection (PASC) incidence, also known as Long COVID, have varied across studies and changed over time. We estimated PASC incidence among adult and pediatric populations in three nationwide research networks of electronic health records (EHR) participating in the RECOVER Initiative using different classification algorithms (computable phenotypes). Overall, 7% of children and 8.5%-26.4% of adults developed PASC, depending on computable phenotype used. Excess incidence among SARS-CoV-2 patients was 4% in children and ranged from 4-7% among adults, representing a lower-bound incidence estimation based on two control groups - contemporary COVID-19 negative and historical patients (2019). Temporal patterns were consistent across networks, with peaks associated with introduction of new viral variants. Our findings indicate that preventing and mitigating Long COVID remains a public health priority. Examining temporal patterns and risk factors of PASC incidence informs our understanding of etiology and can improve prevention and management.

A family-based association study after genome-wide linkage analysis identified two genetic loci for renal function in a Mongolian population.

The estimated glomerular filtration rate is a well-known measure of renal function and is widely used to follow the course of disease. Although there have been several investigations establishing the genetic background contributing to renal function, Asian populations have rarely been used in these genome-wide studies. Here, we aimed to find candidate genetic determinants of renal function in 1007 individuals from 73 extended families of Mongolian origin. Linkage analysis found two suggestive regions near 9q21 (logarithm of odds (LOD) 2.82) and 15q15 (LOD 2.70). The subsequent family-based association study found 2 and 10 significant single-nucleotide polymorphisms (SNPs) in each region, respectively. The strongest SNPs on chromosome 9 and 15 were rs17400257 and rs1153831 with P-values of 7.21 × 10(-9) and 2.47 × 10(-11), respectively. Genes located near these SNPs are considered candidates for determining renal function and include FRMD3, GATM, and SPATA5L1. Thus, we identified possible loci that determine renal function in an isolated Asian population. Consistent with previous reports, our study found genes linked and associated with renal function in other populations.