Ovarian ferroptosis induced by androgen is involved in pathogenesis of PCOS.

STUDY QUESTION: Does ovarian ferroptosis play an active role in the development of polycystic ovary syndrome (PCOS)? SUMMARY ANSWER: Increased ovarian ferroptosis was present in PCOS ovaries and the inhibition of ferroptosis with ferrostatin-1 (Fer-1) ameliorated polycystic ovary morphology and anovulation. WHAT IS KNOWN ALREADY: Programmed cell death plays a fundamental role in ovarian follicle development. However, the types and mechanisms of cell death involved in the ovary are yet to be elucidated. Ferroptosis is a recently discovered iron-dependent programmed cell death. Impaired iron metabolism and cell death have been observed in women with PCOS, the main cause of anovulatory infertility. Additionally, previous studies reported that an abnormal expression of noncoding RNA may promote ferroptosis in immortalized ovarian granulosa cell lines. However, little is known about whether ovarian ferroptosis is increased in PCOS, and there is insufficient direct evidence for a role of ferroptosis in PCOS, and the underlying mechanism. Moreover, the effect of the inhibition of ferroptosis with Fer-1 in PCOS remains unclear. STUDY DESIGN SIZE DURATION: Ferroptosis was evaluated in human granulosa cells (hGCs) from non-PCOS (n = 6-16) and PCOS (n = 7-18) patients. The experimental study was completed in vitro using primary hGCs from women undergoing IVF. Improvements in PCOS indicators following ferroptosis inhibition with Fer-1 were investigated in a dehydroepiandrosterone (DHEA)-induced PCOS rat model (n = 8 per group). PARTICIPANTS/MATERIALS SETTING METHODS: Ovarian ferroptosis was evaluated in the following ways: by detecting iron concentrations via ELISA and fluorescent probes; measuring malondialdehyde (MDA) concentrations via ELISA; assessing ferroptosis-related protein abundance with western blotting; observing mitochondrial morphology with transmission electron microscopy; and determining cell viability. Primary hGCs were collected from women undergoing IVF. They were treated with dihydrotestosterone (DHT) for 24 h. The effect of DHT on ferroptosis was examined in the presence or absence of small interfering RNA-mediated knockdown of the putative receptor coregulator for signaling molecules. The role of ovarian ferroptosis in PCOS progression was explored in vivo in rats. The DHEA-induced PCOS rat model was treated with the ferroptosis inhibitor, Fer-1, and the oocytes and metaphase II oocytes were counted after ovarian stimulation. Additionally, rats were treated with the ferroptosis inducer, RSL3, to further explore the effect of ferroptosis. The concentrations of testosterone, FSH, and LH were assessed. MAIN RESULTS AND THE ROLE OF CHANCE: Increased ferroptosis was detected in the ovaries of patients with PCOS and in rats with DHEA-induced PCOS. Increased concentrations of Fe2+ (P < 0.05) and MDA (P < 0.05), and upregulated nuclear receptor coactivator 4 protein levels, and downregulated ferritin heavy chain 1 (FTH1) and glutathione peroxidase 4 (GPX4) proteins were observed in the hGCs in patients with PCOS and ovaries of PCOS rats (P < 0.05 versus control). DHT was shown to induce ferroptosis via activation of NOCA4-dependent ferritinophagy. The inhibition of ferroptosis with Fer-1 in rats ameliorated a cluster of PCOS traits including impaired glucose tolerance, irregular estrous cycles, reproductive hormone dysfunction, hyperandrogenism, polycystic ovaries, anovulation, and oocyte quality (P < 0.05). Treating rats with RSL3 resulted in polycystic ovaries and hyperandrogenism (P < 0.05). LARGE-SCALE DATA: N/A. LIMITATIONS REASONS FOR CAUTION: Although ovarian-targeted ferroptosis inhibition may be a more targeted treatment for PCOS, the underlying mechanisms in the cycle between ferroptosis and hyperandrogenism require further exploration. Additionally, since PCOS shows high heterogeneity, it is important to investigate whether ferroptosis increases are present in all patients with PCOS. WIDER IMPLICATIONS OF THE FINDINGS: Androgen-induced ovarian ferroptosis appears to play a role in the pathogenesis of PCOS, which potentially makes it a promising treatment target in PCOS. STUDY FUNDING/COMPETING INTERESTS: This study was supported by the National Key R&D Program of China (2023YFC2705500, 2023YFC2705505, 2019YFA0802604), National Natural Science Foundation of China (No. 82130046, 82320108009, 82101708, 82101747, and 82001517), Shanghai leading talent program, Innovative research team of high-level local universities in Shanghai (No. SHSMU-ZLCX20210201, No. SSMU-ZLCX20180401), Shanghai Jiaotong University School of Medicine, Affiliated Renji Hospital Clinical Research Innovation Cultivation Fund Program (RJPY-DZX-003) and Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support (No. 20161413), Shanghai's Top Priority Research Center Construction Project (2023ZZ02002), and Three-Year Action Plan for Strengthening the Construction of the Public Health System in Shanghai (GWVI-11.1-36). The authors report no competing interests.

The application value of 3D ASL in evaluating the effectiveness of stent implantation for vertebrobasilar artery stenosis.

OBJECTIVE: To evaluate the effect of stent implantation for vertebrobasilar artery stenosis，by using 3D arterial spin labeling (3D ASL) technique. METHODS: A retrospective analysis was conducted on the clinical and 3D ASL data of 48 patients who underwent vertebral-basilar artery stenting. Post-labeling delay times (PLD) of 1.5 s and 2.5 s were chosen, and the average regional cerebral blood flow (rCBF) values were measured in nine brain regions of the posterior circulation: bilateral thalamus, bilateral occipital lobes, bilateral cerebellar hemispheres, midbrain, pons, and medulla. The 48 patients were divided into two groups based on the presence or absence of acute ischemic stroke in the posterior cerebral circulation region detected by diffusion-weighted imaging (DWI). The preoperative and postoperative rCBF results were statistically analyzed. RESULTS: In the infarct group, there were significant increases in rCBF values of all nine brain regions at both PLD = 1.5 s and 2.5 s postoperatively compared to preoperatively. At PLD = 1.5 s, statistically significant differences in rCBF values between the preoperative and postoperative periods were found in the right thalamus, left cerebellum, midbrain, and pons regions (P < 0.05). At PLD = 2.5 s, statistically significant differences in rCBF values between the preoperative and postoperative periods were observed in the left occipital lobe, right cerebellum, midbrain, and pons regions (P < 0.05). When analyzing the rCBF values of the brain regions with recent infarcts in the infarct group, there was a significant increase in postoperative rCBF values compared to preoperative values (P < 0.05). After excluding the data from brain regions with recent infarcts, the CBF values in the remaining brain regions were also increased postoperatively, and some brain regions showed statistically significant differences in rCBF values between the preoperative and postoperative periods (P < 0.05). In the non-infarct group, there were no statistically significant differences in the preoperative and postoperative rCBF values in all brain regions at both PLD = 1.5 s and 2.5 s (P > 0.05). CONCLUSION: The application of 3D ASL technology shows significant value in assessing the surgical efficacy of vertebral-basilar artery stenting, especially in patients with acute posterior circulation infarction.

Injectable "Homing-Like" Bioactive Short-Fibers for Endometrial Repair and Efficient Live Births.

The prevalence of infertility caused by endometrial defects is steadily increasing, posing a significant challenge to women's reproductive health. In this study, injectable "homing-like" bioactive decellularized extracellular matrix short-fibers (DEFs) of porcine skin origin are innovatively designed for endometrial and fertility restoration. The DEFs can effectively bind to endometrial cells through noncovalent dipole interactions and release bioactive growth factors in situ. In vitro, the DEFs effectively attracted endometrial cells through the "homing-like" effect, enabling cell adhesion, spreading, and proliferation on their surface. Furthermore, the DEFs effectively facilitated the proliferation and angiogenesis of human primary endometrial stromal cells (HESCs) and human umbilical vein endothelial cells (HUVECs), and inhibited fibrosis of pretreated HESCs. In vivo, the DEFs significantly accelerated endometrial restoration, angiogenesis, and receptivity. Notably, the deposition of endometrial collagen decreased from 41.19 ± 2.16% to 14.15 ± 1.70% with DEFs treatment. Most importantly, in endometrium-injured rats, the use of DEFs increased the live birth rate from 30% to an impressive 90%, and the number and development of live births close to normal rats. The injectable "homing-like" bioactive DEFs system can achieve efficient live births and intrauterine injection of DEFs provides a new promising clinical strategy for endometrial factor infertility.

Deciphering the comprehensive knowledgebase landscape featuring infertility with IDDB Xtra.

Infertility affects ∼15% of couples globally and half of cases are related to genetic disorders. Despite growing data and unprecedented improvements in high-throughput sequencing technologies, accumulated fertility-related issues concerning genetic diagnosis and potential treatment are urgent to be solved. However, there is a lack of comprehensive platforms that characterise various infertility-related records to provide research applications for exploring infertility in-depth and genetic counselling of infertility couple. To solve this problem, we provide IDDB Xtra by further integrating phenotypic manifestations, genomic datasets, epigenetics, modulators in collaboration with numerous interactive tools into our previous infertility database, IDDB. IDDB Xtra houses manually-curated 2369 genes of human and nine model organisms, 273 chromosomal abnormalities, 884 phenotypes, 60 genomic datasets, 464 epigenetic records, 1144 modulators relevant to infertility diagnosis and treatment. Additionally, IDDB Xtra incorporated customized graphical applications for researchers and clinicians to decipher in-depth disease mechanisms from the perspectives of developmental atlas, mutation effects, and clinical manifestations. Users can browse genes across developmental stages of human and mouse, filter candidate genes, mine potential variants and retrieve infertility biomedical network in an intuitive web interface. In summary, IDDB Xtra not only captures valuable research and data, but also provides useful applications to facilitate the genetic counselling and drug discovery of infertility. IDDB Xtra is freely available at https://mdl.shsmu.edu.cn/IDDB/and http://www.allostery.net/IDDB.

Relating clustered noise data to hospital patient satisfaction.

Hospital noise can be problematic for both patients and staff and consistently is rated poorly on national patient satisfaction surveys. A surge of research in the last two decades highlights the challenges of healthcare acoustic environments. However, existing research commonly relies on conventional noise metrics such as equivalent sound pressure level, which may be insufficient to fully characterize the fluctuating and complex nature of the hospital acoustic environments experienced by occupants. In this study, unsupervised machine learning clustering techniques were used to extract patterns of activity in noise and the relationship to patient perception. Specifically, nine patient rooms in three adult inpatient hospital units were acoustically measured for 24 h and unsupervised machine learning clustering techniques were applied to provide a more detailed statistical analysis of the acoustic environment. Validation results of five different clustering models found two clusters, labeled active and non-active, using k-means. Additional insight from this analysis includes the ability to calculate how often a room is active or non-active during the measurement period. While conventional LAeq was not significantly related to patient perception, novel metrics calculated from clustered data were significant. Specifically, lower patient satisfaction was correlated with higher Active Sound Levels, higher Total Percent Active, and lower Percent Quiet at Night metrics. Overall, applying statistical clustering to the hospital acoustic environment offers new insights into how patterns of background noise over time are relevant to occupant perception.

Polyvinyl alcohol flame retardant film based on halloysite nanotubes, chitosan and phytic acid with strong mechanical and anti-ultraviolet properties.

The research of additive biomass flame retardants is becoming more and more popular. In this work, amino modified halloysite nanotubes (A-HNTs), chitosan (CS) and phytic acid (PA) were introduced into polyvinyl alcohol (PVA) matrix to construct PA/A-HNT/CS/PVA organic-inorganic composite film with hydrogen bond and covalent bond cross-linking network structure. Adding PA/A-HNT/CS can remarkably improve the mechanical strength, UV resistance and thermal stability of PVA film. Compared with control PVA film, the transmittance of composite film in ultraviolet region decreases from 90 % to <15 %, and the tensile strength raises from 19.8 MPa to 31.0 MPa. The thermal decomposition temperature of the composite film increases, the weight loss rate decreases obviously, and the carbon residue can reach 26 wt% at 700 °C. The limiting oxygen index increases from 18.5 % to 32.2 %. Furthermore, the addition of this flame-retardant system can obviously reduce the combustion intensity of PVA, and its flame-retardant grade can reach V-0. It is of great significance to expand the application of PVA and the development of biomass flame retardant.

Diagnostic power of vertebral hydroxyapatite concentration measurements in spectral CT for osteoporosis-associated fractures and impact of intravenous contrast administration.

OBJECTIVES: To evaluate the diagnostic power of using vertebral hydroxyapatite concentration measurements in unenhanced and contrast-enhanced spectral CT for detecting and predicting the risk of osteoporosis-associated fractures. METHODS: L1 of 210 patients (105 men, 105 women; mean age, 64 years, range, 19-103 years) who had undergone spectral CT examinations from January 1, 2018, to March 1, 2019, were retrospectively analyzed. Patient data for 3 years after spectral CT were retrieved from electronic medical record information systems to obtain the incidence of osteoporotic fractures. Baseline vertebral cancellous hydroxyapatite concentration from unenhanced and contrast-enhanced late-arterial-phase images was measured. The receiver operating characteristic curves were used to evaluate the diagnostic power for detecting and predicting the 3-year risk of osteoporosis-associated fractures using hydroxyapatite concentrations in both phases. RESULTS: The hydroxyapatite concentrations in both phases had good diagnostic power to detect fractures at baseline. The sensitivity and specificity for predicting one or more osteoporosis-associated fractures within 3 years after spectral CT were 76.80% and 93.10%, respectively, using the cutoff of 74.79 mg/cm3 in vertebral hydroxyapatite concentration in the unenhanced CT phase, and 82.87% and 82.76%, respectively, using the cutoff of 84.65 mg/cm3 in the late-arterial phase. Furthermore, there was no significant difference in the diagnosis between unenhanced and enhanced CT-derived hydroxyapatite concentrations (p = 0.360). CONCLUSIONS: Both unenhanced and enhanced spectral CT-derived hydroxyapatite concentrations can accurately detect and predict future risk of osteoporosis-associated fractures. The hydroxyapatite concentration assessed in the late-arterial phase may have a similar diagnostic efficacy to that in the unenhanced phase. KEY POINTS: • A cutoff of 74.79 mg/cm3 of vertebral hydroxyapatite concentration in the unenhanced CT scans had 76.80% sensitivity and 93.10% specificity to predict one or more osteoporosis-associated fractures within 3 years after spectral CT examinations. • A cutoff of 84.65 mg/cm3 of vertebral hydroxyapatite concentration in the late-arterial-enhanced CT scans had 82.87% sensitivity and 82.76% specificity to predict one or more osteoporosis-associated fractures within 3 years after spectral CT examinations. • The hydroxyapatite concentration assessed in the late-arterial phase may have a similar diagnostic efficacy to that in the unenhanced phase.

Influence of Sleeve Gastrectomy on Skeletal Muscular Fat Infiltration Measured by MRI in Patients with Metabolic Syndrome: Preliminary Results.

INTRODUCTION: Several researchers have focused on the role of skeletal muscle in metabolic problems in recent years. We aimed to evaluate influence of sleeve gastrectomy on skeletal muscular fat infiltration determined by magnetic resonance imaging in patients with metabolic syndrome (MetS). METHODS: Sixty five MetS patients (male/female, 20/45; mean age, 35.5 years ± 6.6 [standard deviation]; age range, 22-59 years) enrolled in our study. Prior to and 1 year after sleeve gastrectomy, patients underwent routine measurement of skeletal muscular fat concentration (denoted by proton density fat fraction, PDFF) and chemical indexes. The associations of skeletal muscular fat concentration with other variables were determined using multiple linear regression analysis. RESULTS: Difference between skeletal muscular PDFF at baseline (4.46 ± 2.01%) and PDFF 1-year after sleeve gastrectomy (3.00 ± 1.47%) was significant. Multivariable predictors of baseline skeletal muscular PDFF by descending order of standardized coefficient were fasting serum glucose (0.459; p = 0.001), age (0.395; p < 0.001), systolic pressure (0.319; p = 0.029), insulin (0.030; p = 0.026), white cell count (0.302; p = 0.007), diastolic pressure (-0.301; p = 0.046), and total alkaline phosphatase (-0.474; p < 0.001) all at baseline. Furthermore, multivariable predictors of change in PDFF were serum total cholesterol (3.510; p < 0.001), total alkaline phosphatase (0.535; p < 0.001), estrogen (0.457; p < 0.001), diastolic pressure (0.352; p < 0.001), systolic pressure (-0.409; p < 0.001), high-density lipoprotein cholesterol (-0.719; p < 0.001), insulin (-0.774; p < 0.001), C-reactive protein (-0.900; p < 0.001), triglyceride (-1.756; p < 0.001), and low-density lipoprotein cholesterol (-2.854; p < 0.001) all at baseline. CONCLUSION: Sleeve gastrectomy could alleviate myosteatosis in MetS patients during 1-year follow-up. The extent of remission on skeletal muscular fat infiltration after sleeve gastrectomy was influenced by baseline metabolic problems related to serum glucose, serum lipid, and blood pressure level.

Compute Tomography Radiomics Analysis on Whole Pancreas Between Healthy Individual and Pancreatic Ductal Adenocarcinoma Patients: Uncertainty Analysis and Predictive Modeling.

Radiomics is a rapidly growing field that quantitatively extracts image features in a high-throughput manner from medical imaging. In this study, we analyzed the radiomics features of the whole pancreas between healthy individuals and pancreatic cancer patients, and we established a predictive model that can distinguish cancer patients from healthy individuals based on these radiomics features. Methods: We retrospectively collected venous-phase scans of contrast-enhanced computed tomography (CT) images from 181 control subjects and 85 cancer case subjects for radiomics analysis and predictive modeling. An attending radiation oncologist delineated the pancreas for all the subjects in the Varian Eclipse system, and we extracted 924 radiomics features using PyRadiomics. We established a feature selection pipeline to exclude redundant or unstable features. We randomly selected 189 cases (60 cancer and 129 control) as the training set. The remaining 77 subjects (25 cancer and 52 control) as a test set. We trained a Random Forest model utilizing the stable features to distinguish the cancer patients from the healthy individuals on the training dataset. We analyzed the performance of our best model by running 5-fold cross-validations on the training dataset and applied our best model to the test set. Results: We identified that 91 radiomics features are stable against various uncertainty sources, including bin width, resampling, image transformation, image noise, and segmentation uncertainty. Eight of the 91 features are nonredundant. Our final predictive model, using these 8 features, has achieved a mean area under the receiver operating characteristic curve (AUC) of 0.99 ± 0.01 on the training dataset (189 subjects) by cross-validation. The model achieved an AUC of 0.910 on the independent test set (77 subjects) and an accuracy of 0.935. Conclusion: CT-based radiomics analysis based on the whole pancreas can distinguish cancer patients from healthy individuals, and it could potentially become an early detection tool for pancreatic cancer.

Effect of intravenous iodinated contrast administration on diagnostic ability for osteoporosis using CT attenuation measurement in patients with liver cirrhosis.

OBJECTIVES: To evaluate the influence of intravenous contrast agent on the diagnostic ability for osteoporosis using CT attenuation measurement in patients with liver cirrhosis. METHODS: This retrospective study was approved by our institutional review board and informed consent was waived. 208 patients with liver cirrhosis (mean age, 61.25 years ± 9.43 [standard deviation]; range, 30-82 years) who underwent both unenhanced and two contrast-enhanced (arterial and venous phase) abdominal dual-energy CT examinations from January 1 to September 1, 2020, were recruited. CT attenuation values were measured in the medullary compartment of vertebral body (L1-L3) and bone mass was determined by the hydroxyapatite concentration obtained in dual-energy spectral CT and used as the reference standard. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic ability of using CT attenuation number in unenhanced, arterial, and venous phases. RESULTS: Area under ROC curve using unenhanced CT attenuation was different from using arterial CT attenuation (p= 0.038) and venous CT attenuation (p = 0.048) to diagnosing osteoporosis. However, there was no significant difference between unenhanced CT attenuation and arterial CT attenuation (p = 0.773) and between unenhanced CT attenuation and venous CT attenuation (p = 0.746) to distinguish low bone mass (osteoporosis or osteopenia). CONCLUSIONS: The diagnostic ability for osteoporosis using CT attenuation measurement in contrast-enhanced scans is decreased due to intravenous contrast contamination, however, which had no influence on the diagnostic ability of CT attenuation for low bone mass (osteoporosis or osteopenia). ADVANCES IN KNOWLEDGE: The diagnostic ability of using enhanced CT attenuation values for osteoporosis decreased compared to unenhanced CT attenuation values.

Laboratory analysis of positive rate of Mycoplasma pneumoniae antibody among 53,273 children with respiratory tract infections in Xi'an from 2017 to 2020.

Background: Mycoplasma pneumoniae (Mp) is an important pathogen that causes respiratory tract infections in children. Data on epidemiology of paediatric Mp infection in China are little known. The aim of this study was to investigate the infection of children with respiratory tract infection in Xi'an from 2017 to 2020, and to explore the epidemiological features of paediatric Mp infection in Northwest China during the past 4 years. Methods: A total of 53,273 paediatric patients diagnosed with respiratory tract infection as the first diagnosis were enrolled. Mp antibody was detected using passive agglutination method. Statistical analysis and epidemiological investigation were carried out on the test results according to different years, seasons, ages and genders. The differences among rates were analyzed by the χ2 test. The trends among the rates were analyzed by the Poisson regression. Results: A total of 14,375 Mp antibody positive patients were detected, with a total positive rate of 26.98%. The rate of Mp infection in 2017 was significantly higher than other years (χ2=431.700; P=0.000), and the rate showed a downward trend year by year [incidence rate ratios (IRR) =0.906; 95% CI: 0.892-0.921; P=0.000]. The rate of Mp infection increased gradually in the order of spring, summer, autumn and winter (IRR =1.078; 95% CI: 1.060-1.097; P=0.000), and peaked in winter (29.08%). As age increased, the positive rate of Mp infection also gradually increased (IRR =1.138; 95% CI: 1.134-1.143; P=0.000). The peak age of Mp infection was between 6 and 12 years, accounting for 51.71%, significantly more compared with other age groups (χ2=4203.000, P=0.000). Female children had significantly higher positive rates than male children (χ2=527.000; P=0.000). Conclusions: Mp infection mainly occurs related to year, season, age and gender. Understanding the epidemiological characteristics of paediatric Mp infection can contribute to timely treatment and diagnosis, and may improve the prognosis of children with Mp infection.

Recognition of Peripheral Lung Cancer and Focal Pneumonia on Chest Computed Tomography Images Based on Convolutional Neural Network.

Introduction: Chest computed tomography (CT) is important for the early screening of lung diseases and clinical diagnosis, particularly during the COVID-19 pandemic. We propose a method for classifying peripheral lung cancer and focal pneumonia on chest CT images and undertake 5 window settings to study the effect on the artificial intelligence processing results. Methods: A retrospective collection of CT images from 357 patients with peripheral lung cancer having solitary solid nodule or focal pneumonia with a solitary consolidation was applied. We segmented and aligned the lung parenchyma based on some morphological methods and cropped this region of the lung parenchyma with the minimum 3D bounding box. Using these 3D cropped volumes of all cases, we designed a 3D neural network to classify them into 2 categories. We also compared the classification results of the 3 physicians with different experience levels on the same dataset. Results: We conducted experiments using 5 window settings. After cropping and alignment based on an automatic preprocessing procedure, our neural network achieved an average classification accuracy of 91.596% under a 5-fold cross-validation in the full window, in which the area under the curve (AUC) was 0.946. The classification accuracy and AUC value were 90.48% and 0.957 for the junior physician, 94.96% and 0.989 for the intermediate physician, and 96.92% and 0.980 for the senior physician, respectively. After removing the error prediction, the accuracy improved significantly, reaching 98.79% in the self-defined window2. Conclusion: Using the proposed neural network, in separating peripheral lung cancer and focal pneumonia in chest CT data, we achieved an accuracy competitive to that of a junior physician. Through a data ablation study, the proposed 3D CNN can achieve a slightly higher accuracy compared with senior physicians in the same subset. The self-defined window2 was the best for data training and evaluation.

Tea plant-legume intercropping simultaneously improves soil fertility and tea quality by changing bacillus species composition.

Tea plant is an economically important crop in China, but long-term monoculture and substantial chemical nitrogen fertilizer input cause soil acidification, which in turn affects the nutrient supply and tea quality. Intercropping has drawn more attention in tea gardens because this pattern is expected to improve soil fertility and tea quality and change the soil microbial community composition. However, the roles of some key microorganisms in rhizosphere soils have not been well characterized. Hereby, a "soybean in summer and smooth vetch in winter" mode was selected to investigate the effects of intercropped legumes in a tea garden on soil fertility, tea quality, and the potential changes in beneficial bacteria such as Bacillus. Our data showed that when soybeans were turned into soil, intercropping system exhibited higher soil organic matter (SOM), total nitrogen (TN), tea quality indices and the expression of Camellia sinensis glutamine synthetase gene (CsGS). Notably, intercropping significantly affected the bacterial communities and decreased the relative abundance of Bacillus but increased its absolute abundance. Bacillus amyloliquefaciens BM1 was isolated from intercropped soil and showed outstanding plant growth-promoting (PGP) properties when coinoculated with rhizobia. In winter, intercropping with smooth vetch had a beneficial effect on soil properties and tea quality. Comparably, coinoculation with strain BM1 and Rhizobium leguminosarum Vic5 on smooth vetch (Vicia villosa) showed huge improvements in SOM, TN and quality of tea leaves, accompanied by the highest level of amino acids and lowest levels of polyphenol and caffeine (p < 0.05). According to these results, our findings demonstrate that intercropping with some legumes in the tea garden is a strategy that increases SOM, TN and tea quality, and some PGP Bacillus species are optional to obtain an amplification effect.

Associations of PM2.5 exposure with blood glucose impairment in early pregnancy and gestational diabetes mellitus.

Exposure to fine particulate matter (PM2.5) during pregnancy has been linked to the risk of gestational diabetes mellitus (GDM), while conclusions are inconsistent. In this study we aimed to estimate the effects of prenatal PM2.5 exposure with blood glucose in early pregnancy and the GDM risk. Participants were recruited from the SH-IPMCH-BTH cohort (n = 41,929), a study of air pollution and birth outcome. All participants provided serum samples for analyses of fasting blood glucose (FBG) and HbA1c during early pregnancy. GDM was diagnosed using an oral glucose tolerance test (OGTT) with the time interval of 1 h. Prenatal exposure to PM2.5 was estimated using gap-filled satellite exposure assessments in Shanghai, China. Both FBG and HbA1c levels were significantly and positively associated with PM2.5 exposure during early pregnancy. A 10 µg/m3 increase of PM2.5 exposure from early to middle pregnancy was associated with the risk of GDM (first trimester OR=1.09, 95% CI: 1.02, 1.16; second trimester OR=1.09, 95% CI: 1.03, 1.16; first two trimester OR=1.15, 95%CI: 1.04, 1.28). The combined effects were greater among elevated FBG and HbA1c women with higher PM2.5 exposure in middle trimester (P for interaction=0.037 and 0.001, respectively). This study found that exposure to PM2.5 exposure in the 1st and 2nd trimesters was related to GDM. FBG and HbA1c played roles in the relationship between PM2.5 exposure in the 2nd trimester and GDM.

Risk Stratification Tool for Ischemic Stroke: A Risk Assessment Model Based on Traditional Risk Factors Combined With White Matter Lesions and Retinal Vascular Caliber.

Objective: This study aims to establish a risk assessment model based on traditional risk factors combined with the Fazekas classification of white matter lesions and retinal vascular caliber for screening the patients at high risk of ischemic stroke. Methods: This study included 296 patients (128 cases of ischemic stroke and 168 cases in the normal control group). The basic data of the patients were collected. Color fundus photography was performed after pupil dilation, and the retinal vascular caliber was measured using semiautomated vascular measurement software (IVAN Software, Sydney, Australia). The severity of white matter lesions (WML) on cranial nuclear magnetic fluid-attenuated inversion recovery images were assessed using the Fazekas scale. Moreover, logistic regression analysis was used to establish different risk assessment models for ischemic stroke. The effects of models were evaluated through the receiver operating characteristic (ROC) curve and the Delong test compared area under the curve. Results: The sensitivity and specificity of models 1 (the traditional risk factor model), 2 (the retinal vascular caliber model), 3 (the WML model), and 4 (the combined the traditional risk factor, WML and central retinal artery equivalent (CRAE) model) were 71 and 55%, 48 and 71%, 49 and 67%, and 68 and 68.5% with areas under the curve of 0.658, 0.586, 0.601, and 0.708, respectively. The area under the receiver operating characteristic curve in models 1, 2, 3, and 4 showed statistically significant differences. Moreover, no statistical significance exists in the pairwise comparison of other models. Conclusion: The risk assessment model of ischemic stroke combined with Fazekas grade of WML and CRAE is superior to the traditional risk factor and the single-index model. This model is helpful for risk stratification of high-risk stroke patients.

Bone Marrow Fat Measured by a Chemical Shift-Encoded Sequence (IDEAL-IQ) in Patients With and Without Metabolic Syndrome.

BACKGROUND: Metabolic syndrome increases the risk of chronic diseases such as cardiovascular disease and diabetes. Metabolic syndrome also has an impact on bone mineral density. However, the relationship between metabolic syndrome and bone marrow fat is unclear. PURPOSE: To determine factors associated with bone marrow fat concentration in subjects with and without metabolic syndrome. STUDY TYPE: Retrospective. POPULATION: One hundred and one women with metabolic syndrome (31.0 years ±5.1) and 96 female living liver transplant donors (32.0 years ±3.7). Our institutional review board approved the study. Each subject signed written informed consent. FIELD STRENGTH/SEQUENCE: 3.0 T MRI system and a commercially available chemical shift-encoded 3D sequence (Iterative Decomposition of water and fat with Echo asymmetry and Least Square Estimation). ASSESSMENT: Proton density fat fraction (PDFF) in liver, vertebral body, and paraspinal muscle (erector spinae) were measured from a single acquisition by a 15-year-experience orthopedic radiologist. The factors associated with PDFF were acquired. STATISTICAL TESTS: The analysis of covariance test, after adjustment for body mass index and age, was used to analyze the differences between metabolic syndrome and non-metabolic syndrome groups. A stepwise multiple regression analysis was used to determine which variables were independently associated with PDFF. RESULTS: Mean vertebral PDFF and alanine aminotransferase (ALT) were significantly lower in donors than subjects with metabolic syndrome (both P < 0.05). Serum vitamin D concentration, ferritin, and high-density lipoprotein (HDL) cholesterol were significantly higher in donors than subjects with metabolic syndrome (all P < 0.05). Multiple regression analysis revealed antidiabetic medicine, higher serum vitamin D concentration, lower waist circumference, lower ferritin, lower HDL, absence of metabolic syndrome, and lower ALT were significantly associated with lower vertebral PDFF (all P < 0.05). DATA CONCLUSION: Multiple factors affect bone marrow fat concentration in subjects with metabolic syndrome. Serum vitamin D concentration and antidiabetic medicine are associated with low bone marrow fat, whereas waist circumference, serum ferritin, metabolic syndrome, imbalanced lipid metabolism, and abnormal liver function are associated with high bone marrow fat. LEVEL OF EVIDENCE LEVEL: 3 TECHNICAL EFFICACY STAGE: 1.

Predicting nursing baccalaureate program graduates using machine learning models: A quantitative research study.

BACKGROUND: Despite powerful efforts to maximize nursing school enrollment, schools and colleges of nursing are faced with high rates of attrition and low rates of completion. Early identification of at-risk students and the factors associated with graduation outcomes are the main foci for the studies that have addressed attrition and completion rates in nursing programs. Machine learning has been shown to perform better in prediction tasks than traditional statistical methods. OBJECTIVES: The purpose of this study was to identify adequate models that predict, early in a students career, if an undergraduate nursing student will graduate within six college years. In addition, factors related to successful graduation were to be identified using several of the algorithms. DESIGN: Predictions were made at five time points: the beginning of the first, second, third, fourth years, and the end of the sixth year. Fourteen scenarios were built for each machine learning algorithm through the combinations of different variable sections and time points. SETTINGS: College of Nursing in a private university in an urban Midwest city, USA. PARTICIPANTS: Seven hundred and seventy-three full time, first time, and degree-seeking students who enrolled from 2004 through 2012 in a traditional 4-year baccalaureate nursing program. METHODS: Eight popular machine learning algorithms were chosen for model construction and comparison. In addition, a stacked ensemble method was introduced in the study to boost the accuracy and reduce the variance of prediction. RESULTS: Using one year of college academic performance, the graduation outcome can be correctly predicted for over 80% of the students. The prediction accuracy can reach 90% after the second college year and 99% after the third year. Among all the variables, cumulative grade points average (GPA) and nursing course GPA are the most influential factors for predicting graduation. CONCLUSIONS: This study provides a potential mode of data-based tracking system for nursing students during their entire baccalaureate program. This tracking system can serve a large number of students automatically to provide customized evaluation on the dropout risk students and enhance the ability of a school or college to more strategically design school-based prevention and interventional services.

Risk of vertebral fractures: evaluation on vertebral trabecular attenuation value and hydroxyapatite concentration in patients by chest spectral CT.

OBJECTIVES: To analyze vertebral fractures risk in patients with chest scans by evaluating vertebral hydroxyapatite concentration measured on spectral CT compared to trabecular attenuation value measured on conventional CT. METHODS: Our retrospective study reviewed CT of 216 patients. Analysis of vertebral (T11 - L1) hydroxyapatite concentration by spectral imaging and trabecular attenuation value by conventional CT imaging were performed in patients with chest CT examinations. Specificity, sensitivity, negative predictive value (NPV), and positive predictive value (PPV) were performed by using receiver operating characteristic (ROC) curves in patients with and without vertebral fractures. RESULTS: In male patients, vertebral hydroxyapatite concentration had high area under the ROC curve (0.916), by using the optimal threshold of 72.27 mg/cm3, specificity, sensitivity, NPV, and PPV were 91.7, 80.2, 36.7, and 98.7%, respectively. In female patients, vertebral hydroxyapatite concentration also had high area under the ROC curve (0.870), by using the optimal threshold of 74.79 mg/cm3, specificity, sensitivity, NPV, and PPV were 100.0, 77.8, 47.4, and 100.0%, respectively. Area under the ROC curve was significantly different between spectral CT-measured bone hydroxyapatite concentration and conventional CT-measured attenuation value in distinguishing vertebral fractures (p = 0.007 for males; p = 0.005 for females). CONCLUSIONS: Quantitative assessment with spectral CT may appear as higher accuracy than that of conventional CT imaging to analyze risk of vertebral fractures. Hydroxyapatite concentration measured with chest spectral CT may be used to evaluate risk of bone fractures. ADVANCES IN KNOWLEDGE: Hydroxyapatite concentration measured with chest spectral CT may be used to evaluate risk of bone fractures.

A candidate pathogenic gene, zinc finger gene 217 (ZNF217), may contribute to polycystic ovary syndrome through prostaglandin E2.

INTRODUCTION: Polycystic ovary syndrome is a complex endocrine condition with chronic inflammation. Prostaglandin E2 (PGE2) is a proinflammatory factor with an increased expression in the serum of women with polycystic ovary syndrome. Zinc finger gene 217 (ZNF217) is known as a candidate gene for polycystic ovary syndrome. We aimed to investigate the relation between ZNF217 and PGE2 in polycystic ovary syndrome. MATERIAL AND METHODS: We used a rat model of dehydroepiandrosterone-induced polycystic ovary syndrome and human granulosa cells both of women with polycystic ovary syndrome and of women without the syndrome to measure ZNF217 and other target gene expressions. In addition, we performed in vitro experiments with KGN human granulosa-like tumor cells to verify the molecular mechanisms. RESULTS: ZNF217 was decreased in the granulosa cells both of dehydroepiandrosterone-treated rats and of women with polycystic ovary syndrome. Cyclooxygenase 2, a key enzyme of PGE2 synthesis, was highly expressed in the granulosa cells of rats and women with the syndrome, and PGE2 concentration was increased in the follicular fluid. Furthermore, decreased ZNF217 expression was supposed to inhibit estradiol synthesis, which further promoted cyclooxygenase 2 and PGE2 synthesis. At the same time, PGE2 had an inhibitory effect on ZNF217 expression in a dose-dependent manner in KGN cells. CONCLUSIONS: Decreased ZNF217 expression in granulosa cells of women with polycystic ovary syndrome induced inflammation via PGE2, and PGE2 inhibited ZNF217 expression to establish a feedback loop. This mechanism might account for the pathogenesis of polycystic ovary syndrome.

High prevalence of CTX-M belonging to ST410 and ST889 among ESBL producing E. coli isolates from waterfowl birds in China's tropical island, Hainan.

The epidemiology and genetic characteristics of extended-spectrum ß-lactamase (ESBL)-producing Escherichia coli (E. coli) have been widely studied in human and veterinary settings. ESBL-producing E. coli are generally reported in pigs, poultry, and dairy farm animals. Here, we report on the prevalence and genetic characteristics of beta-lactamase producing E. coli isolated from waterfowl birds in Hainan, China. After phenotypic confirmation, genes encoding blaCTX-M, blaSHV and blaTEM were detected by polymerase chain reaction (PCR). The isolates were assigned to different phylogenetic groups, and multi-locus sequence typing (MLST). Taken as a whole, 289 (92.9%) out of 311 E. coli isolates from waterfowl birds were confirmed as ESBL phenotypes by double-disk synergy testing. Subsequent PCR analysis revealed that blaCTX-M was the predominant ESBL gene identified in 146 (46.9%) isolates, followed by the combination of blaCTX-M and blaTEM in 70 (22.5%) isolates. The majority of these positive isolates were assigned to phylogroup B2 (46.2%) followed by phylogroup A (43.6%). In addition, MLST assigned representative ESBL positive isolates (n = 40) to 18 STs, and ST410 (ST23cplx) was the most prevalent population (22.5%). The high prevalence of CTX-M and STs frequently associating with E. coli infections should be of concern as it poses threats to animal and public health. To the best of our knowledge, this is the first comprehensive study to report on the occurrence of ESBL producing E. coli from waterfowl birds in China.