SEQUENTIAL PDGF-SIMVASTATIN RELEASE TO PROMOTE DENTOALVEOLAR REGENERATION

Master'sMASTER OF SCIENC

Muckenhoupt-type weights and the intrinsic structure in Bessel Setting

Fix $\lambda>-1/2$ and $\lambda \not=0$. Consider the Bessel operator (introduced by Muckenhoupt--Stein) $\triangle_\lambda:=-\frac{d^2}{dx^2}-\frac{2\lambda}{x} \frac d{dx}$ on $\mathbb{R_+}:=(0,\infty)$ with $dm_\lambda(x):=x^{2\lambda}dx$ and $dx$ the Lebesgue measure on $\mathbb{R_+}$. In this paper, we study the Muckenhoupt-type weights which reveal the intrinsic structure in this Bessel setting along the line of Muckenhoupt--Stein and Andersen--Kerman. Besides, exploiting more properties of the weights $A_{p,\lambda}$ introduced by Andersen--Kerman, we introduce a new class $\widetilde{A}_{p,\lambda}$ such that the Hardy--Littlewood maximal function is bounded on the weighted $L^p_w$ space if and only if $w$ is in $\widetilde A_{p,\lambda}$. Moreover, along the line of Coifman--Rochberg--Weiss, we investigate the commutator $[b,R_\lambda]$ with $R_\lambda:=\frac{d}{dx}(\triangle_\lambda)^{-\frac{1}{2}}$ to be the Bessel Riesz transform. We show that for $w\in A_{p,\lambda}$, the commutator $[b, R_\lambda]$ is bounded on weighted $L^p_w$ if and only if $b$ is in the BMO space associated with $\triangle_\lambda$.Comment: 30 page

Toxicity risk of non-target organs at risk receiving low-dose radiation: case report

The spine is the most common site for bone metastases. Radiation therapy is a common treatment for palliation of pain and for prevention or treatment of spinal cord compression. Helical tomotherapy (HT), a new image-guided intensity modulated radiotherapy (IMRT), delivers highly conformal dose distributions and provides an impressive ability to spare adjacent organs at risk, thus increasing the local control of spinal column metastases and decreasing the potential risk of critical organs under treatment. However, there are a lot of non-target organs at risk (OARs) occupied by low dose with underestimate in this modern rotational IMRT treatment. Herein, we report a case of a pathologic compression fracture of the T9 vertebra in a 55-year-old patient with cholangiocarcinoma. The patient underwent HT at a dose of 30 Gy/10 fractions delivered to T8-T10 for symptom relief. Two weeks after the radiotherapy had been completed, the first course of chemotherapy comprising gemcitabine, fluorouracil, and leucovorin was administered. After two weeks of chemotherapy, however, the patient developed progressive dyspnea. A computed tomography scan of the chest revealed an interstitial pattern with traction bronchiectasis, diffuse ground-glass opacities, and cystic change with fibrosis. Acute radiation pneumonitis was diagnosed. Oncologists should be alert to the potential risk of radiation toxicities caused by low dose off-targets and abscopal effects even with highly conformal radiotherapy

Evaluation of the Osteogenic Potential of Growth Factorâ Rich Demineralized Bone Matrix In Vivo

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141502/1/jper0036.pd

Exploring preconception signatures of metabolites in mothers with gestational diabetes mellitus using a non-targeted approach

BackgroundMetabolomic changes during pregnancy have been suggested to underlie the etiology of gestational diabetes mellitus (GDM). However, research on metabolites during preconception is lacking. Therefore, this study aimed to investigate distinctive metabolites during the preconception phase between GDM and non-GDM controls in a nested case-control study in Singapore.MethodsWithin a Singapore preconception cohort, we included 33 Chinese pregnant women diagnosed with GDM according to the IADPSG criteria between 24 and 28 weeks of gestation. We then matched them with 33 non-GDM Chinese women by age and pre-pregnancy body mass index (ppBMI) within the same cohort. We performed a non-targeted metabolomics approach using fasting serum samples collected within 12 months prior to conception. We used generalized linear mixed model to identify metabolites associated with GDM at preconception after adjusting for maternal age and ppBMI. After annotation and multiple testing, we explored the additional predictive value of novel signatures of preconception metabolites in terms of GDM diagnosis.ResultsA total of 57 metabolites were significantly associated with GDM, and eight phosphatidylethanolamines were annotated using HMDB. After multiple testing corrections and sensitivity analysis, phosphatidylethanolamines 36:4 (mean difference beta: 0.07; 95% CI: 0.02, 0.11) and 38:6 (beta: 0.06; 0.004, 0.11) remained significantly higher in GDM subjects, compared with non-GDM controls. With all preconception signals of phosphatidylethanolamines in addition to traditional risk factors (e.g., maternal age and ppBMI), the predictive value measured by area under the curve (AUC) increased from 0.620 to 0.843.ConclusionsOur data identified distinctive signatures of GDM-associated preconception phosphatidylethanolamines, which is of potential value to understand the etiology of GDM as early as in the preconception phase. Future studies with larger sample sizes among alternative populations are warranted to validate the associations of these signatures of metabolites and their predictive value in GDM.Peer reviewe

Machine Learning-Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes : Prediction Model Development Study

Publisher Copyright: © Mukkesh Kumar, Li Ting Ang, Cindy Ho, Shu E Soh, Kok Hian Tan, Jerry Kok Yen Chan, Keith M Godfrey, Shiao-Yng Chan, Yap Seng Chong, Johan G Eriksson, Mengling Feng, Neerja KarnaniBackground: The increasing prevalence of gestational diabetes mellitus (GDM) is concerning as women with GDM are at high risk of type 2 diabetes (T2D) later in life. The magnitude of this risk highlights the importance of early intervention to prevent the progression of GDM to T2D. Rates of postpartum screening are suboptimal, often as low as 13% in Asian countries. The lack of preventive care through structured postpartum screening in several health care systems and low public awareness are key barriers to postpartum diabetes screening. Objective: In this study, we developed a machine learning model for early prediction of postpartum T2D following routine antenatal GDM screening. The early prediction of postpartum T2D during prenatal care would enable the implementation of effective strategies for diabetes prevention interventions. To our best knowledge, this is the first study that uses machine learning for postpartum T2D risk assessment in antenatal populations of Asian origin. Methods: Prospective multiethnic data (Chinese, Malay, and Indian ethnicities) from 561 pregnancies in Singapore's most deeply phenotyped mother-offspring cohort study-Growing Up in Singapore Towards healthy Outcomes-were used for predictive modeling. The feature variables included were demographics, medical or obstetric history, physical measures, lifestyle information, and GDM diagnosis. Shapley values were combined with CatBoost tree ensembles to perform feature selection. Our game theoretical approach for predictive analytics enables population subtyping and pattern discovery for data-driven precision care. The predictive models were trained using 4 machine learning algorithms: logistic regression, support vector machine, CatBoost gradient boosting, and artificial neural network. We used 5-fold stratified cross-validation to preserve the same proportion of T2D cases in each fold. Grid search pipelines were built to evaluate the best performing hyperparameters. Results: A high performance prediction model for postpartum T2D comprising of 2 midgestation features-midpregnancy BMI after gestational weight gain and diagnosis of GDM-was developed (BMI_GDM CatBoost model: AUC=0.86, 95% CI 0.72-0.99). Prepregnancy BMI alone was inadequate in predicting postpartum T2D risk (ppBMI CatBoost model: AUC=0.62, 95% CI 0.39-0.86). A 2-hour postprandial glucose test (BMI_2hour CatBoost model: AUC=0.86, 95% CI 0.76-0.96) showed a stronger postpartum T2D risk prediction effect compared to fasting glucose test (BMI_Fasting CatBoost model: AUC=0.76, 95% CI 0.61-0.91). The BMI_GDM model was also robust when using a modified 2-point International Association of the Diabetes and Pregnancy Study Groups (IADPSG) 2018 criteria for GDM diagnosis (BMI_GDM2 CatBoost model: AUC=0.84, 95% CI 0.72-0.97). Total gestational weight gain was inversely associated with postpartum T2D outcome, independent of prepregnancy BMI and diagnosis of GDM (P = .02; OR 0.88, 95% CI 0.79-0.98). Conclusions: Midgestation weight gain effects, combined with the metabolic derangements underlying GDM during pregnancy, signal future T2D risk in Singaporean women. Further studies will be required to examine the influence of metabolic adaptations in pregnancy on postpartum maternal metabolic health outcomes. The state-of-the-art machine learning model can be leveraged as a rapid risk stratification tool during prenatal care.Peer reviewe

Intensity modulated radiotherapy for elderly bladder cancer patients

<p>Abstract</p> <p>Background</p> <p>To review our experience and evaluate treatment planning using intensity-modulated radiotherapy (IMRT) and helical tomotherapy (HT) for the treatment of elderly patients with bladder cancer.</p> <p>Methods</p> <p>From November 2006 through November 2009, we enrolled 19 elderly patients with histologically confirmed bladder cancer, 9 in the IMRT and 10 in the HT group. The patients received 64.8 Gy to the bladder with or without concurrent chemotherapy. Conventional 4-field "box" pelvic radiation therapy (2DRT) plans were generated for comparison.</p> <p>Results</p> <p>The median patient age was 80 years old (range, 65-90 years old). The median survival was 21 months (5 to 26 months). The actuarial 2-year overall survival (OS) for the IMRT vs. the HT group was 26.3% <it>vs </it>.37.5%, respectively; the corresponding values for disease-free survival were 58.3% <it>vs</it>. 83.3%, respectively; for locoregional progression-free survival (LRPFS), the values were 87.5% <it>vs</it>. 83.3%, respectively; and for metastases-free survival, the values were 66.7% <it>vs</it>. 60.0%, respectively. The 2-year OS rates for T1, 2 <it>vs</it>. T3, 4 were 66.7% <it>vs</it>. 35.4%, respectively (<it>p </it>= 0.046). The 2-year OS rate was poor for those whose RT completion time greater than 8 weeks when compared with the RT completed within 8 wks (37.9% vs. 0%, <it>p </it>= 0.004).</p> <p>Conclusion</p> <p>IMRT and HT provide good LRPFS with tolerable toxicity for elderly patients with invasive bladder cancer. IMRT and HT dosimetry and organ sparing capability were superior to that of 2DRT, and HT provides better sparing ability than IMRT. The T category and the RT completion time influence OS rate.</p

Automated Machine Learning (AutoML)-Derived Preconception Predictive Risk Model to Guide Early Intervention for Gestational Diabetes Mellitus

The increasing prevalence of gestational diabetes mellitus (GDM) is contributing to the rising global burden of type 2 diabetes (T2D) and intergenerational cycle of chronic metabolic disorders. Primary lifestyle interventions to manage GDM, including second trimester dietary and exercise guidance, have met with limited success due to late implementation, poor adherence and generic guidelines. In this study, we aimed to build a preconception-based GDM predictor to enable early intervention. We also assessed the associations of top predictors with GDM and adverse birth outcomes. Our evolutionary algorithm-based automated machine learning (AutoML) model was implemented with data from 222 Asian multi-ethnic women in a preconception cohort study, Singapore Preconception Study of Long-Term Maternal and Child Outcomes (S-PRESTO). A stacked ensemble model with a gradient boosting classifier and linear support vector machine classifier (stochastic gradient descent training) was derived using genetic programming, achieving an excellent AUC of 0.93 based on four features (glycated hemoglobin A(1c) (HbA(1c)), mean arterial blood pressure, fasting insulin, triglycerides/HDL ratio). The results of multivariate logistic regression model showed that each 1 mmol/mol increase in preconception HbA(1c) was positively associated with increased risks of GDM (p = 0.001, odds ratio (95% CI) 1.34 (1.13-1.60)) and preterm birth (p = 0.011, odds ratio 1.63 (1.12-2.38)). Optimal control of preconception HbA(1c) may aid in preventing GDM and reducing the incidence of preterm birth. Our trained predictor has been deployed as a web application that can be easily employed in GDM intervention programs, prior to conception.Peer reviewe

Comparison of coplanar and noncoplanar intensity-modulated radiation therapy and helical tomotherapy for hepatocellular carcinoma

<p>Abstract</p> <p>Background</p> <p>To compare the differences in dose-volume data among coplanar intensity modulated radiotherapy (IMRT), noncoplanar IMRT, and helical tomotherapy (HT) among patients with hepatocellular carcinoma (HCC) and portal vein thrombosis (PVT).</p> <p>Methods</p> <p>Nine patients with unresectable HCC and PVT underwent step and shoot coplanar IMRT with intent to deliver 46 - 54 Gy to the tumor and portal vein. The volume of liver received 30Gy was set to keep less than 30% of whole normal liver (V30 < 30%). The mean dose to at least one side of kidney was kept below 23 Gy, and 50 Gy as for stomach. The maximum dose was kept below 47 Gy for spinal cord. Several parameters including mean hepatic dose, percent volume of normal liver with radiation dose at X Gy (Vx), uniformity index, conformal index, and doses to organs at risk were evaluated from the dose-volume histogram.</p> <p>Results</p> <p>HT provided better uniformity for the planning-target volume dose coverage than both IMRT techniques. The noncoplanar IMRT technique reduces the V10 to normal liver with a statistically significant level as compared to HT. The constraints for the liver in the V30 for coplanar IMRT vs. noncoplanar IMRT vs. HT could be reconsidered as 21% vs. 17% vs. 17%, respectively. When delivering 50 Gy and 60-66 Gy to the tumor bed, the constraints of mean dose to the normal liver could be less than 20 Gy and 25 Gy, respectively.</p> <p>Conclusion</p> <p>Noncoplanar IMRT and HT are potential techniques of radiation therapy for HCC patients with PVT. Constraints for the liver in IMRT and HT could be stricter than for 3DCRT.</p