Risk of uterine leiomyomata with menstrual and reproductive factors in premenopausal women: Korea nurses health study

Background Uterine leiomyomata (UL) are benign smooth muscle tumors that may cause significant morbidity in women of reproductive age. This study aimed to investigate the relationship of menstrual and reproductive factors with the risk of UL in premenopausal women. Methods This prospective study included 7,360 premenopausal women aged 22–48 years who were part of the Korea Nurses Health Study. Information on the menstrual cycle and reproductive history was assessed between 2014 and 2016, and self-reported cases of UL were obtained through 2021. Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs). Results During 32,072 person-years of follow-up, 447 incident cases of UL were reported. After adjusting for other risk factors, women with late age at menarche had a lower incidence of UL (≥ 16 vs. 12–13 years: HR 0.68; 95% CI 0.47–0.99; p for trend = 0.026). The risk of UL was inversely associated with current menstrual cycle length (≥ 40 or too irregular to estimate vs. 26–31 days: HR 0.40; 95% CI 0.24–0.66) and cycle length at ages 18–22 years (HR 0.45; 95% CI 0.31–0.67; p for trend < 0.001, each). Parous women had lower risk of UL than nulliparous women (HR 0.40; 95% CI 0.30–0.53) and women who were aged 29–30 years at first birth had a lower risk of UL than those who were aged ≤ 28 years at first birth (HR 0.58; 95% CI 0.34–0.98). There was no significant association of the number of births or breastfeeding with the risk of UL among parous women. Neither a history of infertility nor oral contraceptive use was associated with the risk of UL. Conclusions Our results suggest that age at menarche, menstrual cycle length, parity, and age at first birth are inversely associated with the risk of UL in premenopausal Korean women. Future studies are warranted to confirm the long-term effects of menstrual and reproductive factors on womens health.This research was supported by the National Institute of Health research project (2021-NI-015-02)

Clinical application of genomic profiling to find druggable targets for adolescent and young adult (AYA) cancer patients with metastasis

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Background: Although adolescent and young adult (AYA) cancers are characterized by biological features and clinical outcomes distinct from those of other age groups, the molecular profile of AYA cancers has not been well defined. In this study, we analyzed cancer genomes from rare types of metastatic AYA cancers to identify driving and/or druggable genetic alterations. Methods: Prospectively collected AYA tumor samples from seven different patients were analyzed using three different genomics platforms (whole-exome sequencing, whole-transcriptome sequencing or OncoScan (TM)). Using well-known bioinformatics tools (bwa, Picard, GATK, MuTect, and Somatic Indel Detector) and our annotation approach with open access databases (DAVID and DGIdb), we processed sequencing data and identified driving genetic alterations and their druggability. Results: The mutation frequencies of AYA cancers were lower than those of other adult cancers (median = 0.56), except for a germ cell tumor with hypermutation. We identified patient-specific genetic alterations in candidate driving genes: RASA2 and NF1 (prostate cancer), TP53 and CDKN2C (olfactory neuroblastoma), FAT1, NOTCH1, and SMAD4 (head and neck cancer), KRAS (urachal carcinoma), EML4-ALK (lung cancer), and MDM2 and PTEN (liposarcoma). We then suggested potential drugs for each patient according to his or her altered genes and related pathways. By comparing candidate driving genes between AYA cancers and those from all age groups for the same type of cancer, we identified different driving genes in prostate cancer and a germ cell tumor in AYAs compared with all age groups, whereas three common alterations (TP53, FAT1, and NOTCH1) in head and neck cancer were identified in both groups. Conclusion: We identified the patient-specific genetic alterations and druggability of seven rare types of AYA cancers using three genomics platforms. Additionally, genetic alterations in cancers from AYA and those from all age groups varied by cancer type.

Annual Out-of-Pocket Costs and Productivity Loss Among Patients with Diabetic Kidney Disease Compared to Type 2 Diabetes Mellitus

Thesis (Master's)--University of Washington, 2020Background Type II diabetes mellitus (T2DM) is a chronic disease of impaired glucose homeostasis characterized by both insulin resistance and a decrease in insulin production. Disease progression may lead to multisystem complications including the development of diabetic kidney disease (DKD). Though the association of T2DM and DKD with poor health outcomes and increased health care costs has been studied, there remains a paucity of literature assessing the incremental impact of DKD versus T2DM on outcomes and costs. Objective The objective of this study was to compare total annual out-of-pocket costs and workplace productivity loss measured by absenteeism and short-term disability between patients with T2DM compared to patients with DKD. Methods Data from the IBM/Watson MarketScan Commercial Claims and Encounters (CCAE) and Health and Productivity Management (HPM) Databases were used to conduct this retrospective cohort study (2013-2018). Adult patients ≥18 years with ≥2 unique service claims with a principal or secondary diagnosis for T2DM within 6-months during the enrollment period were assigned to the T2DM cohort. Among the T2DM cohort, a subset of patients with an additional ≥2 unique service claims for CKD during the enrollment period were selected and assigned to the DKD cohort. All patients were continuously enrolled for 12-months prior to the index date, beginning at the date of first T2DM claim. Inclusion in either cohort was mutually exclusive. Patients with incident DKD after the index date were followed in the T2DM cohort until the second CKD claim and were then followed in the DKD cohort thereafter. Individuals also present in the HPM databases were included in the sub-populations for the workplace absence or short-term disability outcomes. We used the Kaplan-Meier Sample Average approach to estimate outcomes using 1-month intervals during the follow-up period. To evaluate uncertainty, we performed a nonparametric bootstrap with 1000 replicates to generate 95% credible intervals (CIs). Results In the primary population (N=411,887), the mean annual out-of-pocket cost was significantly higher among patients with DKD ($151 [95$147, $153]) compared to those with T2DM ($118 [95% CI: $114,$124]), with a mean difference of $327.5 (95$326.8, $328.2). The mean annual productivity loss due to workplace absenteeism was found to be similar between those with DKD (227 hours [219 hours, 236 hours]) and T2DM (217 hours [187 hours, 226 hours]), with a mean difference of 21.7 hours (95% CI: 21.0 hours, 22.3 hours). Significantly higher mean annual short-term disability was observed among those with DKD (4.6 days [4.4 days, 4.8 days]) compared to those with T2DM (2.8 days [2.3 days, 3.4 days]), with a mean difference of 1.78 days (95% CI: 1.76 days, 1.80 days). Conclusions Patients with DKD were found to have higher mean annual OOP costs and experience more days with short-term disability claims compared to patients with T2DM. These results quantify the economic burden of T2DM and DKD from a patient and employer perspective and may be useful in economic evaluations to inform health care decision-making

Development of Image Processing for Crack Detection on Concrete Structures through Terrestrial Laser Scanning Associated with the Octree Structure

Terrestrial laser scanning (TLS) provides a rapid remote sensing technique to model 3D objects but can also be used to assess the surface condition of structures. In this study, an effective image processing technique is proposed for crack detection on images extracted from the octree structure of TLS data. To efficiently utilize TLS for the surface condition assessment of large structures, a process was constructed to compress the original scanned data based on the octree structure. The point cloud data obtained by TLS was converted into voxel data, and further converted into an octree data structure, which significantly reduced the data size but minimized the loss of resolution to detect cracks on the surface. The compressed data was then used to detect cracks on the surface using a combination of image processing algorithms. The crack detection procedure involved the following main steps: (1) classification of an image into three categories (i.e., background, structural joints and sediments, and surface) using K-means clustering according to color similarity, (2) deletion of non-crack parts on the surface using improved subtraction combined with median filtering and K-means clustering results, (3) detection of major crack objects on the surface based on Otsu’s binarization method, and (4) highlighting crack objects by morphological operations. The proposed technique was validated on a spillway wall of a concrete dam structure in South Korea. The scanned data was compressed up to 50% of the original scanned data, while showing good performance in detecting cracks with various shapes

Application of Cancer Genomics to Solve Unmet Clinical Needs

The large amount of data on cancer genome research has contributed to our understanding of cancer biology. Indeed, the genomics approach has a strong advantage for analyzing multi-factorial and complicated problems, such as cancer. It is time to think about the actual usage of cancer genomics in the clinical field. The clinical cancer field has lots of unmet needs in the management of cancer patients, which has been defined in the pre-genomic era. Unmet clinical needs are not well known to bioinformaticians and even non-clinician cancer scientists. A personalized approach in the clinical field will bring potential additional challenges to cancer genomics, because most data to now have been population-based rather than individual-based. We can maximize the use of cancer genomics in the clinical field if cancer scientists, bioinformaticians, and clinicians think and work together in solving unmet clinical needs. In this review, we present one imaginary case of a cancer patient, with which we can think about unmet clinical needs to solve with cancer genomics in the diagnosis, prediction of prognosis, monitoring the status of cancer, and personalized treatment decision

A Dry Room-Free High-Energy Density Lithium-ion Batteries Enabled by Impurity Scavenging Separator Membrane

Although lithium-ion batteries (LIBs) are used in various fields, such as small devices and electric vehicles, the low cycling stability due to the acceleration of salt degradation at high temperatures remains a significant challenge. The batteries are typically assembled in a dry room that controls moisture because lithium salts in the electrolytes are highly reactive with moisture, which has a significant effect on the battery performance. In this work, impurity scavenging separator membrane (ISM) was fabricated using a powerful H2O and HF scavenging material. This material was synthesized by an urethane reaction between porous silica (p-SiO2) and (3-isocynatopropyl)triethoxysilane (ICPTES). The p-SiO2 reaction with ICPTES suppressed the acidification of the electrolyte with water and resulted in maintaining the shape of the SiO2 particles. The multifunctional separator exhibited high capacity retention of 87%, 79%, and 74% at various electrodes including LiMn2O4 (LMO)//Li4Ti5O12(LTO), Li[Ni0.8Co0.1Mn0.1]O-2 (NCM)//graphite, and LMO//graphite, respectively, at high temperature (55 degrees C). Furthermore, the ISM improves the cycle stability of batteries that use an electrolyte containing 1000 ppm of water. For the first time, a pouch full-cell was manufactured in a dry room-free system to confirm the excellent H2O and HF scavenging ability of the developed ISM, which was confirmed by the large area of battery size (4x6 cm(2)). This method presents a new approach for cost reduction in the electric vehicle marke

A newly developed capture-based sequencing panel for genomic assay of lung cancer

Background The increase in genetic alterations targeted by specific chemotherapy in lung cancer has led to the need for universal use of more comprehensive genetic testing, which has highlighted the development of a lung cancer diagnostic panel using next-generation sequencing. Objective We developed a hybridization capture-based massively parallel sequencing assay named Friendly, Integrated, Research-based, Smart and Trustworthy (FIRST)-lung cancer panel (LCP), and evaluated its performance. Methods FIRST-LCP comprises 64 lung cancer-related genes to test for various kinds of genetic alterations including single nucleotide variations (SNVs), insertions and deletions (indels), copy number variations (CNVs), and structural variations. To assess the performance of FIRST-LCP, we compiled test sets using HapMap samples or tumor cell lines with disclosed genetic information, and also tested our clinical lung cancer samples whose genetic alterations were known by conventional methods. Results FIRST-LCP accomplished high sensitivity (99.4%) and specificity (100%) of the detection of SNVs. High precision was also achieved, with intra- or inter-run concordance rate of 0.99, respectively. FIRST-LCP detected indels and CNVs close to the expected allele frequency and magnitude, respectively. Tests with samples from lung cancer patients also identified all SNVs, indels and fusions. Conclusion Based on the current state of the art, continuous application of the panel design and analysis pipeline following up-to-date knowledge could ensure precision medicine for lung cancer patients.

Tree rings dendrochemistry near Cu smelter

Nkana smelter belonged to the main sources of contamination by trace elements (especially Cu and Co) in the area of African city Kitwe (Copperbelt, Zambia). The main objective of this study was to compare elemental and isotopic composition of Zambian soils and tree rings, and to investigate biogeochemical processes between plants and soils in contaminated and uncontaminated environment. Elemental composition (Cu, Co, Cr, Mn, Fe, Zn, Pb, Cd, Hg and Tl) and isotopic composition of Cu (63 Cu/65 Cu) were determined in soils and tree rings of pine trees (Pinus latteri, Pinus kesiya) using ICP-MS , AMA and MC ICP-MS. Our results demonstrated that soils and tree rings were both affected by mining and metallurgical activity. Increasing content of elements with depth is the result of the mobility of the elements in uncontaminated soil profile. Soil from contaminated site had the highest metal contents especially in the upper part of the soil profile as a result of continuous contribution of metallurgical components during long-term smelter operation. Fractionations of Cu isotopes in soils were caused primarily by interactions with plants. Concentration changes that some elements showed in the individual tree rings could be the effect of variable intensity of pollution in the area. In the case of Cu, however,..

Additional file 10: Table S8. of Clinical application of genomic profiling to find druggable targets for adolescent and young adult (AYA) cancer patients with metastasis

CVE list. (PDF 285 kb