Porphyromonas gingivalis OMVs promoting endothelial dysfunction via the STING pathway in periodontitis.

OBJECTIVE: This study aimed to assess the effects of Porphyromonas gingivalis outer membrane vesicles (Pg-OMVs) in chronic periodontitis and explore the underlying mechanism involved. METHODS: In vitro, Pg-OMVs were incubated with Ea.hy926 (vessel endothelial cells, ECs) to evaluate their effects on endothelial functions and to investigate the underlying mechanism. The effects of endothelial dysfunction on MG63 osteoblast-like cells were verified using an indirect co-culture method. For in vivo studies, micro-CT was conducted to identify alveolar bone mass. Immunofluorescence staining was conducted to confirm the levels of stimulator of interferon genes (STING) in the blood vessel and the number of Runx2+ cells around the alveolar bone. RESULTS: Pg-OMVs were endocytosed by ECs, leading to endothelial dysfunction. The cGAS-STING-TBK1 pathway was activated in ECs, which subsequently inhibited MG63 migration and early osteogenesis differentiation. In vivo, Pg-OMVs promoted alveolar bone resorption, increased STING levels in the blood vessel, and decreased Runx2+ cells around the alveolar bone. CONCLUSIONS: Pg-OMVs caused endothelial dysfunction and activated the cGAS-STING-TBK1 signal cascade in ECs, thereby impairing ECs-mediated osteogenesis. Furthermore, Pg-OMVs aggregated alveolar bone loss and altered the blood vessel-mediated osteogenesis with elevated STING.

Mitochonic Acid 5 Increases Ram Sperm Quality by Improving Mitochondrial Function during Storage at 4 °C.

Semen preservation involves lengthening sperm's fertile lifespan without any detrimental effects on its biochemical, functional, and ultrastructural properties. Liquid storage at 4 °C is a ram sperm preservation method. However, this method of storage causes irreversible damage due to cold shocks, osmotic stresses, oxidative stresses, and reductions in sperm metabolism. The present study aims to investigate whether the supplementation of mitochonic acid 5 (MA-5) in a sperm extender could improve chilled ram sperm quality and elucidate its mechanism of action. Ram sperm were diluted with a tris-citrate-glucose extender containing different concentrations of MA-5 (0, 0.1, 1, 10, and 100 nM) and stored at 4 °C for up to 48 h. Sperm motility, membrane integrity, acrosome integrity, mitochondrial membrane potential, reactive oxygen species (ROS) level, ATP content, and the expression of NADPH dehydrogenase subunits 1 (MT-ND1) and NADPH dehydrogenase subunits 6 (MT-ND6) were evaluated. It was observed that compared to the control, the 10 nM MA-5 treatment significantly (p < 0.05) increased total motility (82 ± 3.5% vs. 76 ± 5.9%), progressive motility (67.6 ± 8.2% vs. 51 ± 8.3%), and other parameters (straight-line velocity (VSL), average path velocity (VAP), and curvilinear velocity (VCL)). In addition, 10 nM MA-5 supplementation also improved ram sperm membrane integrity and acrosomal integrity as well increased mitochondrial membrane potential (51.1 ± 0.7% vs. 37.7 ± 1.3%), reduced ROS levels, and elevated adenosine triphosphate (ATP) contents. Furthermore, a Western blot analysis demonstrated that the addition of MA-5 significantly (p < 0.05) increased the expression of MT-ND1 and MT-ND6 proteins in ram sperm, with the 10 nM MA-5 treatment resulting in the highest expression level. These results suggest that MA-5 improves ram sperm quality by maintaining high sperm mitochondrial function during liquid storage at 4 °C.

Improved accuracy and efficiency of primary care fall risk screening of older adults using a machine learning approach.

BACKGROUND: While many falls are preventable, they remain a leading cause of injury and death in older adults. Primary care clinics largely rely on screening questionnaires to identify people at risk of falls. Limitations of standard fall risk screening questionnaires include suboptimal accuracy, missing data, and non-standard formats, which hinder early identification of risk and prevention of fall injury. We used machine learning methods to develop and evaluate electronic health record (EHR)-based tools to identify older adults at risk of fall-related injuries in a primary care population and compared this approach to standard fall screening questionnaires. METHODS: Using patient-level clinical data from an integrated healthcare system consisting of 16-member institutions, we conducted a case-control study to develop and evaluate prediction models for fall-related injuries in older adults. Questionnaire-derived prediction with three questions from a commonly used fall risk screening tool was evaluated. We then developed four temporal machine learning models using routinely available longitudinal EHR data to predict the future risk of fall injury. We also developed a fall injury-prevention clinical decision support (CDS) implementation prototype to link preventative interventions to patient-specific fall injury risk factors. RESULTS: Questionnaire-based risk screening achieved area under the receiver operating characteristic curve (AUC) up to 0.59 with 23% to 33% similarity for each pair of three fall injury screening questions. EHR-based machine learning risk screening showed significantly improved performance (best AUROC = 0.76), with similar prediction performance between 6-month and one-year prediction models. CONCLUSIONS: The current method of questionnaire-based fall risk screening of older adults is suboptimal with redundant items, inadequate precision, and no linkage to prevention. A machine learning fall injury prediction method can accurately predict risk with superior sensitivity while freeing up clinical time for initiating personalized fall prevention interventions. The developed algorithm and data science pipeline can impact routine primary care fall prevention practice.

Liuwei Dihuang pills attenuate ovariectomy-induced bone loss by alleviating bone marrow mesenchymal stem cell (BMSC) senescence via the Yes-associated protein (YAP)-autophagy axis.

CONTEXT: Liuwei Dihuang pill (LWDH) has been used to treat postmenopausal osteoporosis (PMOP). OBJECTIVE: To explore the effects and mechanisms of action of LWDH in PMOP. MATERIALS AND METHODS: Forty-eight female Sprague-Dawley rats were divided into four groups: sham-operated (SHAM), ovariectomized (OVX), LWDH high dose (LWDH-H, 1.6 g/kg/d) and LWDH low dose (LWDH-L, 0.8 g/kg/d); the doses were administered after ovariectomy via gavage for eight weeks. After eight weeks, the bone microarchitecture was evaluated. The effect of LWDH on the differentiation of bone marrow mesenchymal stem cells (BMSCs) was assessed via osteogenesis- and lipogenesis-induced BMSC differentiation. The senescence-related biological indices were also detected using senescence staining, cell cycle analysis, quantitative real-time polymerase chain reaction and western blotting. Finally, the expression levels of autophagy-related proteins and Yes-associated protein (YAP) were evaluated. RESULTS: LWDH-L and LWDH-H significantly modified OVX-induced bone loss. LWDH promoted osteogenesis and inhibited adipogenesis in OVX-BMSCs. Additionally, LWDH decreased the positive ratio of senescence OVX-BMSCs and improved cell viability, cell cycle, and the mRNA and protein levels of p53 and p21. LWDH upregulated the expression of autophagy-related proteins, LC3, Beclin1 and YAP, in OVX-BMSCs and downregulated the expression of p62. DISCUSSION AND CONCLUSIONS: LWDH improves osteoporosis by delaying the BMSC senescence through the YAP-autophagy axis.

Predicting COVID-19 severity: Challenges in reproducibility and deployment of machine learning methods.

The increasing use of electronic health records (EHR) based computable phenotypes in clinical research is providing new opportunities for development of data-driven medical applications. Adopted widely in the United States and globally, EHRs facilitate systematic collection of patients' longitudinal information, which serves as one of the important foundations for artificial intelligence applications in medicine. Harmonization of input variables and outcome definitions is critically important for wider clinical applicability of artificial intelligence (AI) methodologies. In this review, we focused on Coronavirus Disease 2019 (COVID-19) severity machine learning prediction models and explored the pipeline for standardizing future disease severity model development using EHR information. We identified 2,967 studies published between 01/01/2020 and 02/15/2022 and selected 135 independent studies that had built machine learning prediction models to predict severity related outcomes of COVID-19 patients based on EHR data for the final review. These 135 studies spanning across 27 counties covered a broad range of severity related prediction outcomes. We observed substantial inconsistency in COVID-19 severity phenotype definitions among models in these studies. Moreover, there was a gap between the outcome of these models and clinician-recognized clinical concepts. Accordingly, we recommend that robust clinical input metrics, with outcome definitions which eliminate ambiguity in interpretation, to reduce algorithmic bias, mitigate model brittleness and improve generalizability of a universal model for COVID-19 severity. This framework can potentially be extended to broader clinical application.

lncRNA MIR31HG Regulates Proliferation and Migration by Targeting Matrix Gla Protein in Nonsyndromic Cleft Lip With or Without Cleft Palate.

Nonsyndromic cleft lip with or without cleft palate (NSCL/P) is a common craniofacial birth defect with complex etiologies. Recently, the dysregulation of long noncoding RNAs (lncRNAs) has been implicated in many developmental diseases, including NSCL/P. However, the functions and mechanisms of lncRNAs in NSCL/P have not been fully elucidated. In this study, we found that lncRNA MIR31HG in NSCL/P patients was significantly downregulated than that in healthy individuals (GSE42589, GSE183527). In addition, single nucleotide polymorphism rs58751040 in MIR31HG was nominally associated with NSCL/P susceptibility (odds ratio: 1.29, 95% confidence interval: 1.03-1.54, p = 4.93 × 10-2) through a case-control study (504 NSCL/P cases and 455 controls). Luciferase activity assay showed that the C allele of rs58751040 revealed a decreased transcription activity of MIR31HG than the G allele. Moreover, knockdown of MIR31HG promoted cell proliferation and migration in human oral keratinocytes and human embryonic palate mesenchyme. Bioinformatic analysis and cellular studies suggested that MIR31HG may confer susceptibility to risk of NSCL/P through matrix Gla protein (MGP) signaling. In summary, we identified a novel lncRNA involved in the development of NSCL/P.

Genetic variants in Mammalian STE20-like protein kinase 2 were associated with risk of NSCL/P.

AIM: Mammalian STE20-like protein kinase 2 (MST2) plays an important role in apoptosis and the development of many disorders. Here, we aim to explore if genetic variants in MST2 are associated with the risk of non-syndromic cleft lip with or without palate (NSCL/P). MATERIALS AND METHODS: The association study was performed in a two-stage study of 1,069 cases and 1,724 controls to evaluate the association between genetic variants in the MST2 and NSCL/P risk. The potential function of the candidate single nucleotide polymorphism (SNP) was predicted using HaploReg, RegulomeDB, and public craniofacial histone chromatin immunoprecipitation sequencing (ChIP-seq) data. Haploview was used to perform the haplotype of risk alleles. The expression quantitative trait loci (eQTL) effect was assessed using the Genotype-Tissue Expression (GTEx) project. Gene expression in mouse embryo tissue was performed using data downloaded from GSE67985. The potential role of candidate gene in the development of NSCL/P was assessed by correlation and enrichment analysis. RESULTS: Among SNPs in MST2, rs2922070 C allele (Pmeta = 2.93E-04) and rs6988087 T allele (Pmeta = 1.57E-03) were linked with significantly increased risk of NSCL/P. Rs2922070, rs6988087 and their high linkage disequilibrium (LD) SNPs constituted a risk haplotype of NSCL/P. Individuals carrying 3-4 risk alleles had an elevated risk of NSCL/P compared to those who carried less risk alleles (P = 2.00E-04). The eQTL analysis revealed a significant association between these two variants and MST2 in muscle tissue of the body. The MST2 expressed during mouse craniofacial development and over-expressed in the human orbicularis oris muscle (OOM) of NSCL/P patients compared to controls. MST2 was involved in the development of NSCL/P by regulating the mRNA surveillance pathway, the MAPK signaling pathway, the neurotrophin signaling pathway, the FoxO signaling pathway and the VEGF signaling pathway. CONCLUSION: MST2 was associated with the development of NSCL/P.

Evaluating the accuracy of automated cephalometric analysis based on artificial intelligence.

BACKGROUND: The purpose of this study was to evaluate the accuracy of automatic cephalometric landmark localization and measurements using cephalometric analysis via artificial intelligence (AI) compared with computer-assisted manual analysis. METHODS: Reconstructed lateral cephalograms (RLCs) from cone-beam computed tomography (CBCT) in 85 patients were selected. Computer-assisted manual analysis (Dolphin Imaging 11.9) and AI automatic analysis (Planmeca Romexis 6.2) were used to locate 19 landmarks and obtain 23 measurements. Mean radial error (MRE) and successful detection rate (SDR) values were calculated to assess the accuracy of automatic landmark digitization. Paired t tests and Bland‒Altman plots were used to compare the differences and consistencies in cephalometric measurements between manual and automatic analysis programs. RESULTS: The MRE for 19 cephalometric landmarks was 2.07 ± 1.35 mm with the automatic program. The average SDR within 1 mm, 2 mm, 2.5 mm, 3 and 4 mm were 18.82%, 58.58%, 71.70%, 82.04% and 91.39%, respectively. Soft tissue landmarks (1.54 ± 0.85 mm) had the most consistency, while dental landmarks (2.37 ± 1.55 mm) had the most variation. In total, 15 out of 23 measurements were within the clinically acceptable level of accuracy, 2 mm or 2°. The rates of consistency within the 95% limits of agreement were all above 90% for all measurement parameters. CONCLUSION: Automatic analysis software collects cephalometric measurements almost effectively enough to be acceptable in clinical work. Nevertheless, automatic cephalometry is not capable of completely replacing manual tracing. Additional manual supervision and adjustment for automatic programs can increase accuracy and efficiency.

Effect of socioeconomic and malocclusion-related factors on duration of orthodontic treatment by fixed appliance: A retrospective study.

OBJECTIVES: The aims of this study were to evaluate the effect of related factors that influence orthodontic treatment time and to identify the predictors of orthodontic treatment duration in a Chinese population. MATERIALS AND METHODS: Information for 29 sociodemographic, malocclusion and orthodontic treatment characteristics was collected. Patients were divided into two groups: the duration ≤24 months group and duration >24 months group. The treatment dates of the initial visit and end of orthodontic treatment were obtained to calculate duration. The data were subjected to univariate and multivariate logistic regression modelling to quantify the association between characteristics and the treatment duration; odds ratios (ORs) and 95% confidence intervals (95% CIs) are reported. RESULTS: Of 2120 patients, 704 patients (mean age, 15.9 ± 6.0 years) were included. Age, extraction, Bolton ratio (overall), rotated teeth, overjet and crowding (lower arch) were predictors for duration. The nomogram based on predictive factors exhibited strong discrimination ability, with concordance indices of 0.755 (95% CI = 0.712-0.798) in the training cohort model and 0.717 (95% CI = 0.647-0.787) in the validation cohort model. The calibration curves for the training and validation cohorts showed that the probabilities of the nomogram agreed well with actual probabilities. CONCLUSIONS: Young age, non-extraction and severe crowding (lower arch) can increase the chance of durations of ≤24 months. Rotated teeth, excessive overjet and Bolton ratio (overall) can increase the chance of durations of >24 months.

Changes of maxillary central incisor and alveolar bone in Class II Division 2 nonextraction treatment with a fixed appliance or clear aligner: A pilot cone-beam computed tomography study.

INTRODUCTION: This retrospective clinical study investigated the clinical changes of maxillary central incisor and alveolar bone in Class II Division 2 nonextraction treatment with fixed appliances or clear aligners on the basis of cone-beam computed tomography. METHODS: Fifty-nine Chinese Han patients with similar demographic characteristics were collected from a conventional bracket group, a self-ligating bracket group, and a clear aligner group. All measurements about root resorption and alveolar bone thickness on the cone-beam computed tomography images were tested. Changes between pretreatment and posttreatment were evaluated by paired-sample t test. The variation among the 3 groups was compared by 1-way analysis of variance. RESULTS: The resistance center of the maxillary central incisor showed upward or forward movement, and the axial inclination was increased in 3 groups (P <0.0001). Root volume loss in the clear aligner group (23.68 ± 4.82 mm3) was significantly less than that in the fixed appliances group (28.24 ± 6.44 mm3 in the conventional bracket group, 28.17 ± 6.07 mm3 in the self-ligating bracket group) (P <0.05). All 3 groups showed a significant decrease in palatal alveolar bone and total bone thickness at all 3 levels at posttreatment. In contrast, labial bone thickness significantly increased except for crestal level l. Among the 3 groups, the clear aligner group had a prominent increase in labial bone thickness at the apical level (P = 0.0235). CONCLUSIONS: Clear aligner treatment for Class II Division 2 malocclusions could effectively reduce the incidence of fenestration and root resorption. Our findings will be beneficial to comprehensively understand the effectiveness of different appliances for Class II Division 2 malocclusions treatment.

Atf4 regulates angiogenic differences between alveolar bone and long bone macrophages by regulating M1 polarization, based on single-cell RNA sequencing, RNA-seq and ATAC-seq analysis.

In the repair of maxillofacial bone defects, autogenous craniofacial bone can often provide superior clinical results over long bone grafts. Most current studies have focused on the osteogenic differences between alveolar bone marrow (ABM) and long bone marrow (LBM), however, studies about the angiogenic differences between the two are currently lacking. We downloaded single-cell RNA sequencing (scRNA-seq) of mouse ABM and LBM respectively from the public database, and the data were processed by using Seurat package. CellphoneDB2 results showed that macrophages had the strongest interaction with mesenchymal stem cells (MSCs) and endothelial cells (ECs). ELISA results confirmed that ABM macrophages secreted a higher level of vascular endothelial growth factor A (Vegfa) compared to LBM macrophages, which further promoted angiogenesis of ECs and MSCs. Using SCENIC package, six key transcription factors (TFs) were identified to regulate the difference between ABM and LBM macrophages, and activating transcription factor 4 (Atf4) was confirmed to be more expressed in ABM macrophages by polymerase chain reaction (PCR) and western blot (WB), with predicted target genes including Vegfa. Besides, the result of scRNA-seq implied ABM macrophages more in M1 status than LBM macrophages, which was confirmed by the following experiments. From the results of another assay for transposase accessible chromatin sequencing (ATAC-seq) and RNA-seq about M1 macrophages, Atf4 was also confirmed to regulate the M1 polarization. So, we suspected that Atf4 regulated the different expression of Vegfa between ABM and LBM macrophages by activating M1 polarization. After knocking down Atf4, the expression of M1 polarization markers and Vegfa were downregulated and vasculogenic differences were eliminated, which were subsequently reversed by the addition of LPS/IFN-γ. Our study might provide a new idea to improve the success rate of autologous bone grafting and treatment of oral diseases.

Associations between mixed urinary phenols and parabens metabolites and bone mineral density: Four statistical models.

Phenols and parabens widely exist in personal care and consumer products and have been proved to be endocrine disrupting chemicals that could disturb bone metabolism. The current studies focusing on the associations between phenols and parabens with bone mineral density (BMD) drew contradictory conclusions. Considering the bias might be due to not considering the effects of mixed exposure, we conducted the first cross-sectional study to investigate the associations of both single and mixed metabolites of phenols and parabens with BMD in three populations by setting up four models: generalized linear regression model (GLM), weighted quantile sum (WQS) regression model, quantile g-computation (qgcomp) model and Bayesian kernel machine regression (BKMR) model, based on the US National Health and Nutrition Examination Survey (NHANES) database. We found that the association between the mixtures and total femur BMD in men was significantly negative. Bisphenol A (BPA) was shown to play the most important role in this negative association in the BKMR model, and this negative association was also confirmed in the GLM model with ß coefficient (95% CI) being -0.02 (-0.04, -0.01). The relationships between the mixtures and femoral neck and trochanter BMD in postmenopausal women were significantly positive. Benzophenone-3 (BP-3) played the most significant role in the positive association with trochanter BMD, as confirmed by the WQS, qgcomp and BKMR models, and this positive association was also verified by the GLM model with ß coefficient (95% CI) being 0.01 (0.00, 0.02). In conclusion, the association between the mixed phenols and parabens and BMD was negative in men while was positive in postmenopausal women, which was gender-specific. This study might provide new ideas for the prevention and treatment of osteoporosis and the control of personal care and consumer products containing phenols and parabens in the future.

Association between mixed aldehydes and bone mineral density based on four statistical models.

Aldehydes as an environmental pollutant may lead to oxidative stress, which is an important mechanism in the development of osteoporosis. This suggests a possible link between aldehyde exposure and osteoporosis. Considering the mixed nature of aldehyde exposure and the interactions between different aldehydes, we explored for the first time the associations between mixed six aldehydes (benzaldehyde, butyraldehyde, heptanal, hexanal, isovaleraldehyde, and propionaldehyde) and BMD in three populations (men, premenopausal women, and postmenopausal women) by applying four statistical models: quantile g-computation (qgcomp) model, Bayesian kernel machine regression (BKMR) model, generalized linear regression model (GLM), and generalized additive model (GAM), based on the National Health and Nutrition Examination Survey (NHANES) 2013-2014. We found that mixed aldehydes could significantly reduce BMD in men, with hexanaldehyde and propanaldehyde having the greatest negative qgcomp model and BKMR model weights, also confirmed by GLM. The associations between isopentanaldehyde and propanaldehyde and femoral BMD in men were non-linear and had threshold effects as derived from the BKMR model and GAM. The associations turned positive when the concentrations of isopentanaldehyde and propanaldehyde exceeded their respective inflection points. To conclude, our study might provide new ideas for the prevention and treatment of osteoporosis, and hexanaldehyde and propanaldehyde should be more regulated to prevent osteoporosis.

Testing of an Electronic Clinical Quality Measure for Diagnostic Delay of Venous Thromboembolism (DOVE) in Primary Care.

Venous Thromboembolism (VTE) is a serious, preventable public health problem that requires timely treatment. Because signs and symptoms are non-specific, patients often present to primary care providers with VTE symptoms prior to diagnosis. Today there are no federal measurement tools in place to track delayed diagnosis of VTE. We developed and tested an electronic clinical quality measure (eCQM) to quantify Diagnostic Delay of Venous Thromboembolism (DOVE); the rate of avoidable delayed VTE events occurring in patients with a VTE who had reported VTE symptoms in primary care within 30 days of diagnosis. DOVE uses routinely collected EHR data without contributing to documentation burden. DOVE was tested in two geographically distant healthcare systems. Overall DOVE rates were 72.60% (site 1) and 77.14% (site 2). This novel, data-driven eCQM could inform healthcare providers and facilities about opportunities to improve care, strengthen incentives for quality improvement, and ultimately improve patient safety.

Polycystin-2 mediates mechanical tension-induced osteogenic differentiation of human adipose-derived stem cells by activating transcriptional co-activator with PDZ-binding motif.

Human adipose-derived stem cells (hASCs) have multi-directional differentiation potential including osteogenic differentiation. Mechanical stimulation is thought to be a key regulator of bone remodeling and has been proved to promote osteogenic differentiation of mesenchymal stem cells. However, the mechanism how mechanical tension-induced osteogenesis of hASCs still remains poor understood. Polycystin-2 (PC2), a member of the transient receptor potential polycystic (TRPP) family, is involved in cilia-mediated mechanical transduction. To understand the role of PC2 in osteogenic differentiation under mechanical stimuli in hASCs, PKD2 gene was stably silenced by using lentivirus-mediated shRNA technology. The results showed that mechanical tension sufficiently enhanced osteogenic differentiation but hardly affected proliferation of hASCs. Silencing PKD2 gene caused hASCs to lose the ability of sensing mechanical stimuli and subsequently promoting osteogenesis. PC2 knock-out also reduced the cilia population frequency and cilia length in hASCs. TAZ (transcriptional coactivator with PDZ-binding motif, also known as Wwtr1) could mediate the genes regulation and biological functions of mechanotransduction signal pathway. Here, mechanical tension also enhanced TAZ nuclear translocation of hASCs. PC2 knock-out blocked tension-induced upregulation of nuclear TAZ and suppress tension-induced osteogenesis. TAZ could directly interact with Runx2, and inhibiting TAZ could suppress tension-induced upregulation of Runx2 expression. In summary, our findings demonstrated that PC2 mediate mechanical tension-induced osteogenic differentiation of hASCs by activating TAZ.

Predicting hospitalization of COVID-19 positive patients using clinician-guided machine learning methods.

OBJECTIVES: The coronavirus disease 2019 (COVID-19) is a resource-intensive global pandemic. It is important for healthcare systems to identify high-risk COVID-19-positive patients who need timely health care. This study was conducted to predict the hospitalization of older adults who have tested positive for COVID-19. METHODS: We screened all patients with COVID test records from 11 Mass General Brigham hospitals to identify the study population. A total of 1495 patients with age 65 and above from the outpatient setting were included in the final cohort, among which 459 patients were hospitalized. We conducted a clinician-guided, 3-stage feature selection, and phenotyping process using iterative combinations of literature review, clinician expert opinion, and electronic healthcare record data exploration. A list of 44 features, including temporal features, was generated from this process and used for model training. Four machine learning prediction models were developed, including regularized logistic regression, support vector machine, random forest, and neural network. RESULTS: All 4 models achieved area under the receiver operating characteristic curve (AUC) greater than 0.80. Random forest achieved the best predictive performance (AUC = 0.83). Albumin, an index for nutritional status, was found to have the strongest association with hospitalization among COVID positive older adults. CONCLUSIONS: In this study, we developed 4 machine learning models for predicting general hospitalization among COVID positive older adults. We identified important clinical factors associated with hospitalization and observed temporal patterns in our study cohort. Our modeling pipeline and algorithm could potentially be used to facilitate more accurate and efficient decision support for triaging COVID positive patients.

Two genomic regions of a sodium azide induced rice mutant confer broad-spectrum and durable resistance to blast disease.

Rice blast, one of the most destructive epidemic diseases, annually causes severe losses in grain yield worldwide. To manage blast disease, breeding resistant varieties is considered a more economic and environment-friendly strategy than chemical control. For breeding new resistant varieties, natural germplasms with broad-spectrum resistance are valuable resistant donors, but the number is limited. Therefore, artificially induced mutants are an important resource for identifying new broad-spectrum resistant (R) genes/loci. To pursue this approach, we focused on a broad-spectrum blast resistant rice mutant line SA0169, which was previously selected from a sodium azide induced mutation pool of TNG67, an elite japonica variety. We found that SA0169 was completely resistant against the 187 recently collected blast isolates and displayed durable resistance for almost 20 years. Linkage mapping and QTL-seq analysis indicated that a 1.16-Mb region on chromosome 6 (Pi169-6(t)) and a 2.37-Mb region on chromosome 11 (Pi169-11(t)) conferred the blast resistance in SA0169. Sequence analysis and genomic editing study revealed 2 and 7 candidate R genes in Pi169-6(t) and Pi169-11(t), respectively. With the assistance of mapping results, six blast and bacterial blight double resistant lines, which carried Pi169-6(t) and/or Pi169-11(t), were established. The complementation of Pi169-6(t) and Pi169-11(t), like SA0169, showed complete resistance to all tested isolates, suggesting that the combined effects of these two genomic regions largely confer the broad-spectrum resistance of SA0169. The sodium azide induced mutant SA0169 showed broad-spectrum and durable blast resistance. The broad resistance spectrum of SA0169 is contributed by the combined effects of two R regions, Pi169-6(t) and Pi169-11(t). Our study increases the understanding of the genetic basis of the broad-spectrum blast resistance induced by sodium azide mutagenesis, and lays a foundation for breeding new rice varieties with durable resistance against the blast pathogen.

Dynamic Change in Oral Microbiota of Children With Cleft Lip and Palate After Alveolar Bone Grafting.

To investigate the longitudinal influence of alveolar bone grafting on the oral microbiota of children with cleft lip and palate (CLP).Twenty-eight children with nonsyndromic CLP were recruited and underwent secondary alveolar bone grafting at the first time. Unstimulated saliva and plaque samples were collected from the subjects preoperatively and at 2 days, 1 month, and 3 months postoperatively. The v3-v4 hypervariable regions of the 16S rRNA gene from bacterial DNA were sequenced using the Illumina MiSeq sequencing platform.The alpha diversity of the saliva and plaque microbiota was significantly decreased at 2 days postoperatively and then increased at 1 and 3 months postoperatively. The saliva and plaque microbiota compositions at 2 days postoperatively differed from those at the other time points, and the microbiota compositions at 1 and 3 months postoperatively showed a gradual shift toward the preoperative composition. The saliva, but not plaque, microbiota composition 3 months postoperatively was similar to that preoperatively.The effect of secondary alveolar bone grafting on the plaque microbiota in children with CLP lasted longer than the saliva microbiota. Alveolar bone grafting altered the saliva microbiota in children with CLP within 3 months postoperatively.

Development and assessment of an online virtual orthodontic curriculum.

INTRODUCTION: Due to break space and time limits, an entirely new online curriculum of orthodontic education with online evaluation system has been structured and developed in the dental school, based on virtual reality simulation. CURRICULUM: At Nanjing Medical University, a new online orthodontic curriculum with programmatic assessment process was constructed and implemented based on competency-based education (CBE). It was consisted of the online orthodontic theoretical lectures based on the National Open Online Course "Orthodontics," the online journal club via the online "flipped classroom," and the online orthodontic pre-clinical training via the virtual learning network platform. In order to evaluate this curriculum, 94 Year 4 dental students took part to complete the online orthodontic curriculum. The mean total score of all the students was 91.99, and the element scores of the online theoretical lectures, journal club, virtual pre-clinical training, and online final examination were respectively 96.83, 79.49, 96.00, and 87.02, which showed a good performance. According to the student feedback toward this curriculum via the online questionnaire, nearly 98% of the students showed agreement or strong agreement that the online orthodontic curriculum has enhanced their orthodontic theoretical understanding and orthodontic practical ability. CONCLUSION: As a student-centered CBE, this online orthodontic curriculum with online evaluation system could provide both orthodontic theory and practice teaching for all the dental students at all times and places based on the online virtual mode, which enriched learners' critical thinking, problem solving, and assessment skills.

The adjuvant effects of rosin and coconut oil on nicosulfuron and mesotrione to control weeds.

Natural adjuvants are novel options to reduce the doses of chemical herbicides. The aim of the current study was to examine the compositions and adjuvant effects of rosin and coconut oil on herbicides using a combination of indoor experiment and field trial. The GC-MS results showed that the main component of rosin was abietic acid (40.02%), and the main components of coconut oil were 2-pentanone, 4-hydroxy-4-methyl- (21.45%) and dodecanoic acid (14.59%). In greenhouse experiment, rosin showed a significant adjuvant effect on nicosulfuron against Digitaria sanguinalis and Amaranthus retroflexus, with the GR50 ratios of 1.47 and 1.69, respectively. The GR50 values of nicosulfuron in the present of coconut oil were 3.99 and 10.13 g a.i./hm2 against D. sanguinalis and A. retroflexus, lower than that of individual application. The adjuvant effect of rosin and coconut oil on mesotrione was also found. In field trial, the fresh weight control efficiency of nicosulfuron (45 g a.i./hm2) and mesotrione (112.5 g a.i./hm2) was significantly improved after the addition of rosin and coconut oil, similar with that of recommended dose. Rosin and coconut oil could reduce the contact angle of nicosulfuron, with the results of 56.68° and 53.90°, respectively, lower than that of individual application. Furthermore, rosin and coconut oil could decrease the surface tension, wetting and penetration time; and increase the spreading diameter and maximum retention. Both rosin and coconut oil have adjuvant effects on herbicides in the lab & field with multiple mechanisms. Thus, they have the potential to be developed into natural adjuvants for herbicide formulation to control weeds.