Disparities of time trends and birth cohort effects on invasive breast cancer incidence in Shanghai and Hong Kong pre- and post-menopausal women

© 2017 The Author(s). Background: Breast cancer is the leading cause of cancer morbidity among Shanghai and Hong Kong women, which contributes to 20-25% of new female cancer incidents. This study aimed to describe the temporal trend of breast cancer and interpret the potential effects on the observed secular trends. Methods: Cancer incident data were obtained from the cancer registries. Age-standardized incidence rate was computed by the direct method using the World population of 2000. Average annual percentage change (AAPC) in incidence rate was estimated by the Joinpoint regression. Age, period and cohort effects were assessed by using a log-linear model with Poisson regression. Results: During 1976-2009, an increasing trend of breast cancer incidence was observed, with an AAPC of 1.73 [95% confidence interval (CI): 1.54-1.92)] for women in Hong Kong and 2.83 (95% CI, 2.26-3.40) in Shanghai. Greater upward trends were revealed in Shanghai women aged 50 years old or above (AAPC = 3.09; 95% CI, 1.48-4.73). Using age at 50 years old as cut-point, strong birth cohort effects were shown in both pre- and post-menopausal women, though a more remarkable effect was suggested in Shanghai post-menopausal women. No evidence for a period effect was indicated. Conclusions: Incidence rate of breast cancer has been more speedy in Shanghai post-menopausal women than that of the Hong Kong women over the past 30 years. Decreased birth rate and increasing environmental exposures (e.g., light-at-night) over successive generations may have constituted major impacts on the birth cohort effects, especially for the post-menopausal breast cancer; further analytic studies are warranted.Link_to_subscribed_fulltex

Sleep problems in children with autism spectrum disorder in Hong Kong: a cross-sectional study

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental disorder with a growing prevalence of sleep problems associated with significant behavioral problems and more severe autism clinical presentation. Little is known about the relationships between autism traits and sleep problems in Hong Kong. Therefore, this study aimed to examine whether children with autism have increased sleep problems than non-autistic children in Hong Kong. The secondary objective was to examine the factors associated with sleep problems in an autism clinical sample.MethodsThis cross-sectional study recruited 135 children with autism and 102 with the same age range of non-autistic children, aged between 6 and 12 years. Both groups were screened and compared on their sleep behaviors using the Children's Sleep Habits Questionnaire (CSHQ).ResultsChildren with autism had significantly more sleep problems than non-autistic children [t(226.73) = 6.20, p < 0.001]. Bed -sharing [beta = 0.25, t(165) = 2.75, p = 0.07] and maternal age at birth [beta = 0.15, t(165) = 2.05, p = 0.043] were significant factors associated with CSHQ score on the top of autism traits. Stepwise linear regression modeling identified that only separation anxiety disorder (beta = 4.83, t = 2.40, p = 0.019) best-predicted CSHQ.ConclusionIn summary, autistic children suffered from significantly more sleep problems and co-occurring separation anxiety disorder brings greater sleep problems as compared to non-autistic children. Clinicians should be more aware of sleep problems to provide more effective treatments to children with autism

Fine Mapping of the NRG1 Hirschsprung's Disease Locus

The primary pathology of Hirschsprung's disease (HSCR, colon aganglionosis) is the absence of ganglia in variable lengths of the hindgut, resulting in functional obstruction. HSCR is attributed to a failure of migration of the enteric ganglion precursors along the developing gut. RET is a key regulator of the development of the enteric nervous system (ENS) and the major HSCR-causing gene. Yet the reduced penetrance of RET DNA HSCR-associated variants together with the phenotypic variability suggest the involvement of additional genes in the disease. Through a genome-wide association study, we uncovered a ∼350 kb HSCR-associated region encompassing part of the neuregulin-1 gene (NRG1). To identify the causal NRG1 variants contributing to HSCR, we genotyped 243 SNPs variants on 343 ethnic Chinese HSCR patients and 359 controls. Genotype analysis coupled with imputation narrowed down the HSCR-associated region to 21 kb, with four of the most associated SNPs (rs10088313, rs10094655, rs4624987, and rs3884552) mapping to the NRG1 promoter. We investigated whether there was correlation between the genotype at the rs10088313 locus and the amount of NRG1 expressed in human gut tissues (40 patients and 21 controls) and found differences in expression as a function of genotype. We also found significant differences in NRG1 expression levels between diseased and control individuals bearing the same rs10088313 risk genotype. This indicates that the effects of NRG1 common variants are likely to depend on other alleles or epigenetic factors present in the patients and would account for the variability in the genetic predisposition to HSCR

Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

Identification and analysis of ligand binding sites by computational mapping

Thesis (Ph.D.)--Boston UniversityPLEASE NOTE: Boston University Libraries did not receive an Authorization To Manage form for this thesis or dissertation. It is therefore not openly accessible, though it may be available by request. If you are the author or principal advisor of this work and would like to request open access for it, please contact us at [email protected]. Thank you.Ligand binding sites in proteins generally include "hot spots" that contribute a large fraction of the binding free energy and, therefore, are of prime interest in drug design. To find hot spots on the protein surface, a protein can be screened against libraries of small organic molecules to identify interaction sites using nuclear magnetic resonance (NMR) spectroscopy or the X-ray crystallographic technique Multiple Solvent Crystal Structures (MSCS). Small organic molecules can bind at several locations on the surface of a protein, but many different molecules congregate only in "consensus sites" identifying the hot spots. The mapping algorithm FTMAP is a computational analogue of experimental fragment screening methods. The principles of computational mapping were used for the development and testing of the binding site identification algorithm FTSITE, implemented as a web-based server. Finding ligand binding sites in silico is a classical challenge, and the success rate of identifying the ligand binding site as the first predicted site has increased to 83% during the last decade. FfSITE, based on biophysical modeling of protein-ligand interactions, increased the success rate to 94% on the same established test sets. Critical to the success of FfSITE is the use of multiple small molecules as probes; screening by X-ray crystallography and NMR spectroscopy had demonstrated a tendency of ligand binding sites to bind small organic compounds ranging 1n shapes, sizes, and polarities. Further, FfSITE does not use surrogate measures of ligand binding propensity such as site geometries and dimensions. It was shown that FTSITE can also successfully identify allosteric ligand binding sites that can serve as candidates for drug design. Furthermore, the hot spot information provided by FfMAP was shown to guide the development of core fragments, found by experimental fragment screening , into optimal ligands for a number of drug target proteins. Computational mapping can also be used for fragment-based drug design by finding fragments with preference for some regions of the binding site. To facilitate this analysis , a server enabling the fast generation of force field parameters for user-specified small molecules or fragments was developed.2031-01-0

Protein Tyrosine Phosphatase 1B Inhibitors from the Roots of Cudrania tricuspidata

A chemical investigation of the methanol extract from the roots of Cudrania tricuspidata resulted in the isolation of 16 compounds, including prenylated xanthones 1–9 and flavonoids 10–16. Their structures were identified by NMR spectroscopy and mass spectrometry and comparisons with published data. Compounds 1–9 and 13–16 significantly inhibited PTP1B activity in a dose dependent manner, with IC50 values ranging from 1.9–13.6 μM. Prenylated xanthones showed stronger PTP1B inhibitory effects than the flavonoids, suggesting that they may be promising targets for the future discovery of novel PTP1B inhibitors. Furthermore, kinetic analyses indicated that compounds 1 and 13 inhibited PTP1B in a noncompetitive manner; therefore, they may be potential lead compounds in the development of anti-obesity and -diabetic agents

The Use of Traditional, Complementary, and Integrative Medicine in Cancer: Data-Mining Study of 1 Million Web-Based Posts From Health Forums and Social Media Platforms

BackgroundPatients with cancer are increasingly using forums and social media platforms to access health information and share their experiences, particularly in the use of traditional, complementary, and integrative medicine (TCIM). Despite the popularity of TCIM among patients with cancer, few related studies have used data from these web-based sources to explore the use of TCIM among patients with cancer. ObjectiveThis study leveraged multiple forums and social media platforms to explore patients’ use, interest, and perception of TCIM for cancer care. MethodsPosts (in English) related to TCIM were collected from Facebook, Twitter, Reddit, and 16 health forums from inception until February 2022. Both manual assessments and natural language processing were performed. Descriptive analyses were performed to explore the most commonly discussed TCIM modalities for each symptom and cancer type. Sentiment analyses were performed to measure the polarity of each post or comment, and themes were identified from posts with positive and negative sentiments. TCIM modalities that are emerging or recommended in the guidelines were identified a priori. Exploratory topic-modeling analyses with latent Dirichlet allocation were conducted to investigate the patients’ perceptions of these modalities. ResultsAmong the 1,620,755 posts available, cancer-related symptoms, such as pain (10/10, 100% cancer types), anxiety and depression (9/10, 90%), and poor sleep (9/10, 90%), were commonly discussed. Cannabis was among the most frequently discussed TCIM modalities for pain in 7 (70%) out of 10 cancer types, as well as nausea and vomiting, loss of appetite, anxiety and depression, and poor sleep. A total of 7 positive and 7 negative themes were also identified. The positive themes included TCIM, making symptoms manageable, and reducing the need for medication and their side effects. The belief that TCIM and conventional treatments were not mutually exclusive and intolerance to conventional treatment may facilitate TCIM use. Conversely, TCIM was viewed as leading to patients’ refusal of conventional treatment or delays in diagnosis and treatment. Doctors’ ignorance regarding TCIM and the lack of information provided about TCIM may be barriers to its use. Exploratory analyses showed that TCIM recommendations were well discussed among patients; however, these modalities were also used for many other indications. Other notable topics included concerns about the legalization of cannabis, acupressure techniques, and positive experiences of meditation. ConclusionsUsing machine learning techniques, social media and health forums provide a valuable resource for patient-generated data regarding the pattern of use and patients’ perceptions of TCIM. Such information will help clarify patients’ needs and concerns and provide directions for research on integrating TCIM into cancer care. Our results also suggest that effective communication about TCIM should be achieved and that doctors should be more open-minded to actively discuss TCIM use with their patients

Identification of Anthocyanin Compounds in Butterfly Pea Flowers (Clitoria ternatea L.) by Ultra Performance Liquid Chromatography/Ultraviolet Coupled to Mass Spectrometry

Butterfly pea flower have great sensory attraction, but they have not yet been used widely in Vietnam. Extracts of butterfly pea flowers can be used conveniently as a natural blue colorant for food products. In this study, the identification of anthocyanin compounds in butterfly pea flowers was performed by UPLC coupled with a UV and Mass spectrometer instrument. Positive and negative ion electrospray MS/MS chromatograms and spectra of the anthocyanin compounds were determined. By analyzing the chromatograms and spectra for each ion, five anthocyanins were identified in the butterfly pea flower extract; these were delphinidin-3-(6″-p-coumaroyl)-rutinoside, cyanidin 3-(6″-p-coumaroyl)-rutinoside, delphinidin-3-(p-coumaroyl) glucose in both cis- and trans- isomers, cyanidin-3-(p-coumaroyl-glucoside) and delphinidin-3-pyranoside. Additionally, based on their intensity, it was determined that cyanidin-3-(p-coumaroyl-glucoside) was the most abundant anthocyanin, followed by cyanidin 3-(6″-p-coumaroyl)-rutinoside, delphinidin-3-(p-coumaroyl-glucoside), delphinidin-3-(6″-p-coumaroyl)-rutinoside and delphinidin-3-pyranoside. In this study, cyanidin derivatives were discovered in butterfly pea flower extract, where these compounds had not been detected in previous studies