Identification of novel risk factors for postoperative severe hypocalcemia in patients with primary hyperparathyroidism undergoing parathyroidectomy: a case control study.

BACKGROUND: Patients with primary hyperparathyroidism (PHPT) are at risk for severe hypocalcemia (SH) following parathyroidectomy (PTX), but limited data exist on the predictors of SH. We aimed to identify risk factors for early postoperative SH after PTX in patients with PHPT and to evaluate the predictive value of clinical parameters. METHODS: A retrospective review of patients with PHPT who underwent PTX between January 2010 and December 2022 was performed. A total of 46 patients were included in the study, with 15 (32.6%) experiencing postoperative SH, 19 (41.3%) having calculi in the ureter or kidney, and 37 (80.4%) having osteoporosis. Patients were divided into SH and non-SH groups based on postoperative serum calcium levels. Preoperative biochemical indicators, bone turnover markers, and renal function parameters were analyzed and correlated with postoperative SH. RESULTS: Statistically significant (P < 0.05) differences were found in preoperative serum calcium (serum Ca), intact parathyroid hormone, serum phosphorus (serum P), serum Ca/P, percentage decrease of serum Ca, total procollagen type 1 intact N-terminal propeptide, osteocalcin (OC), and alkaline phosphatase levels between the two groups. Multivariate analysis showed that serum P (odds ratio [OR] = 0.989; 95% confidence interval [95% CI] = 0.981-0.996; P = 0.003), serum Ca (OR = 0.007; 95% CI = 0.001-0.415; P = 0.017), serum Ca/P (OR = 0.135; 95% CI = 0.019-0.947; P = 0.044) and OC levels (OR = 1.012; 95% CI = 1.001-1.024; P = 0.036) were predictors of early postoperative SH. The receiver operating characteristic curve analysis revealed that serum P (area under the curve [AUC] = 0.859, P < 0.001), serum Ca/P (AUC = 0.735, P = 0.010) and OC (AUC = 0.729, P = 0.013) had high sensitivity and specificity. CONCLUSION: Preoperative serum P, serum Ca/P and osteocalcin levels may identify patients with PHPT at risk for early postoperative SH after PTX.

Self-immunological disease aid diagnosis with ConvSANet and Eu-clidean distance.

BACKGROUND: Ankylosing spondylitis (AS), Osteoarthritis (OA), and Sjögren's syndrome (SS) are three prevalent autoimmune diseases. If left untreated, which can lead to severe joint damage and greatly limit mobility. Once the disease worsens, patients may face the risk of long-term disability, and in severe cases, even life-threatening consequences. RESULT: In this study, the Raman spectral data of AS, OA, and SS are analyzed to auxiliary disease diagnosis. For the first time, the Euclidean distance(ED) upscaling technique was used for the conversation from one-dimensional(1D) disease spectral data to two-dimensional(2D) spectral images. A dual-attention mechanism network was then constructed to analyze these two-dimensional spectral maps for disease diagnosis. The results demonstrate that the dual-attention mechanism network achieves a diagnostic accuracy of 100 % when analyzing 2D ED spectrograms. Furthermore, a comparison and analysis with s-transforms(ST), short-time fourier transforms(STFT), recurrence maps(RP), markov transform field(MTF), and Gramian angle fields(GAF) highlight the significant advantage of the proposed method, as it significantly shortens the conversion time while supporting disease-assisted diagnosis. Mutual information(MI) was utilized for the first time to validate the 2D Raman spectrograms generated, including ED, ST, STFT, RP, MTF, and GAF spectrograms. This allowed for evaluation of the similarity between the original 1D spectral data and the generated 2D spectrograms. SIGNIFICANT: The results indicate that utilizing ED to transform 1D spectral data into 2D images, coupled with the application of convolutional neural network(CNN) for analyzing 2D ED Raman spectrograms, holds great promise as a valuable tool in assisting disease diagnosis. The research demonstrated that the 2D spectrogram created with ED closely resembles the original 1D spectral data. This indicates that ED effectively captures key features and important information from the original data, providing a strong descript.

MS-Net: a novel lightweight and precise model for plant disease identification.

The rapid development of image processing technology and the improvement of computing power in recent years have made deep learning one of the main methods for plant disease identification. Currently, many neural network models have shown better performance in plant disease identification. Typically, the performance improvement of the model needs to be achieved by increasing the depth of the network. However, this also increases the computational complexity, memory requirements, and training time, which will be detrimental to the deployment of the model on mobile devices. To address this problem, a novel lightweight convolutional neural network has been proposed for plant disease detection. Skip connections are introduced into the conventional MobileNetV3 network to enrich the input features of the deep network, and the feature fusion weight parameters in the skip connections are optimized using an improved whale optimization algorithm to achieve higher classification accuracy. In addition, the bias loss substitutes the conventional cross-entropy loss to reduce the interference caused by redundant data during the learning process. The proposed model is pre-trained on the plant classification task dataset instead of using the classical ImageNet for pre-training, which further enhances the performance and robustness of the model. The constructed network achieved high performance with fewer parameters, reaching an accuracy of 99.8% on the PlantVillage dataset. Encouragingly, it also achieved a prediction accuracy of 97.8% on an apple leaf disease dataset with a complex outdoor background. The experimental results show that compared with existing advanced plant disease diagnosis models, the proposed model has fewer parameters, higher recognition accuracy, and lower complexity.

High-precision bladder cancer diagnosis method: 2D Raman spectrum figures based on maintenance technology combined with automatic weighted feature fusion network.

BACKGROUND: Raman spectroscopy has been extensively utilized as a marker-free detection method in the complementary diagnosis of cancer. Multivariate statistical classification analysis is frequently employed for Raman spectral data classification. Nevertheless, traditional multivariate statistical classification analysis performs poorly when analyzing large samples and multicategory spectral data. In addition, with the advancement of computer vision, convolutional neural networks (CNNs) have demonstrated extraordinarily precise analysis of two-dimensional image processing. RESULT: Combining 2D Raman spectrograms with automatic weighted feature fusion network (AWFFN) for bladder cancer detection is presented in this paper. Initially, the s-transform (ST) is implemented for the first time to convert 1D Raman data into 2D spectrograms, achieving 99.2% detection accuracy. Second, four upscaling techniques, including short time fourier transform (STFT), recurrence map (RP), markov transform field (MTF), and grammy angle field (GAF), were used to transform the 1D Raman spectral data into a variety of 2D Raman spectrograms. In addition, a particle swarm optimization (PSO) algorithm is combined with VGG19, ResNet50, and ResNet101 to construct a weighted feature fusion network, and this parallel network is employed for evaluating multiple spectrograms. Class activation mapping (CAM) is additionally employed to illustrate and evaluate the process of feature extraction via the three parallel network branches. The results demonstrate that the combination of a 2D Raman spectrogram along with a CNN for the diagnosis of bladder cancer obtains a 99.2% accuracy rate，which indicates that it is an extremely promising auxiliary technology for cancer diagnosis. SIGNIFICANCE: The proposed two-dimensional Raman spectroscopy method has an improved precision than one-dimensional spectroscopic data, which presents a potential methodology for assisted cancer detection and providing crucial technical support for assisted diagnosis.

TRPM8 as a Potential Biomarker and Therapeutic Target for Gastric Cancer Identified by a Combination of Text Mining and RNA Sequencing.

INTRODUCTION: Gastric cancer is a well-known malignant tumor that causes millions of deaths worldwide every year. Due to the lack of a specific biomarker for gastric cancer, most patients are diagnosed at an advanced stage of the disease which results in a poor prognosis and a higher death rate. Therefore, novel biomarkers are urgently needed for early diagnosis and to improve the survival rate. METHODS: In this study, we conducted RNA sequencing of tumor samples from 21 patients with gastric cancer. A total of 3192 differentially expressed genes (1589 up-regulated and 1603 down-regulated) were identified. Subsequently, we applied a text-mining algorithm for further analysis of these data and selected 30 representative genes to investigate as candidates for novel biomarkers in gastric cancer. RESULTS: Among these genes, we confirmed transient receptor potential melastatin 8 channels (TRPM8) as a novel biomarker based on Western blot and immunochemistry validation performed on 134 samples. Compared to normal gastric tissue, the tumor tissues exhibited a significantly higher expression level of TRPM8. CONCLUSION: This study provides insights into the underlying role of TRPM8 in cell proliferation. In addition, TRPM8 may be used as a potential therapeutic target for patients with gastric cancer.

Effects of dysregulated glucose metabolism on the occurrence and ART outcome of endometriosis.

BACKGROUND: Endometriosis is associated with systemic metabolic indicators, including body mass index (BMI), glucose metabolism and lipid metabolism, while the association between metabolic indexes and the occurrence and assisted reproductive technology (ART) outcome of endometriosis is unclear. We aimed to evaluate the characteristics of systemic metabolic indexes of endometriosis patients with infertility and their effects on pregnancy outcome after ART treatment. METHODS: A retrospective cohort study involve 412 endometriosis patients and 1551 controls was conducted. Primary outcome was metabolic indexes, and secondary measures consisted of the influence of metabolic indexes on the number of retrieved oocytes and ART outcomes. RESULTS: Endometriosis patients had higher insulin (INS) [6.90(5.10-9.50) vs 6.50(4.80-8.90) µU/mL, P = 0.005]. A prediction model for endometriosis combining the number of previous pregnancies, CA125, fasting blood glucose (Glu) and INS, had a sensitivity of 73.9%, specificity of 67.8% and area under curve (AUC) of 0.77. There were no significant differences in ART outcomes and complications during pregnancy. The serum levels of Glu before pregnancy were associated with GDM both in endometriosis group (aOR 12.95, 95% CI 1.69-99.42, P = 0.014) and in control group (aOR 4.15, 95% CI 1.50-11.53, P = 0.006). CONCLUSIONS: We found serum Glu is related to the number of retrieved oocytes in control group, serum INS is related to the number of retrieved oocytes in endometriosis group, while serum Glu and INS before pregnancy are related to the occurrence of GDM in two groups. A prediction model based on metabolic indexes was established, representing a promising non-invasive method to predict endometriosis patients with known pregnancy history.

A polyoxometalate-based heterojunction nanozyme with peroxidase-mimic catalytic activity for sensitive biomolecule detection.

Nanozymes are a class of nanomaterials that can specifically mimic the structures and catalytic activities as well as overcome limitations of natural enzymes and have hence been considered as a competitive alternative to natural enzymes. At present, plenty of nanozymes, especially those with peroxidase (POD)-like catalytic activity, have been extensively explored for biosensing. In this work, we proposed polyoxometalate-based heterojunction GdP5W30O110@WS2 nanoclusters (NCs) to exert intrinsic POD-like catalytic activity even under harsh catalytic conditions. Detailedly, GdP5W30O110@WS2 NCs possessing conducive POD-like catalytic activity can oxidize chromogenic substrates into colored substances in the presence of H2O2. On the strength of the POD-like catalytic activity of GdP5W30O110@WS2 NCs, a reliable analytical platform is then constructed after the optimization of catalytic conditions for the detection of H2O2, glutathione (GSH) and glucose via a simple TMB colorimetric strategy. This work advances the utilization of versatile polyoxometalate-based nanomaterials for biosensing, dramatically broadening the potential applications of other nanozyme-based biosensors.

A novel full solar light spectrum responsive antimicrobial agent of WS2 quantum dots for photocatalytic wound healing therapy.

Photocatalytic antimicrobial therapy (PCAT) is considered to be a potential therapeutic treatment for bacterial-infection diseases. However, the antibacterial efficiency is unsatisfactory due to the limited application scope of photocatalysis. In this work, full-spectrum responsive tungsten disulfide quantum dots (WS2 QDs) are prepared for killing bacteria and enabling wound healing through photocatalytic reactive oxygen species (ROS) generation and glutathione (GSH) depletion. On the one hand, these ultrasmall WS2 QDs exhibit an excellent full spectrum (UV-Vis-NIR)-responsive photocatalytic effect by hindering the recombination of electron-hole pairs, thereby achieving the full use of the energy spectrum. Furthermore, the full-spectrum photocatalytic property of the as-prepared WS2 QDs can be effectively strengthened by redox reaction to deplete GSH for accelerated wound healing. In a word, the as-prepared nanoplatform exhibits the ability to act as an admirable antibacterial reagent with full-spectrum catalytic performance for photocatalytic wound healing therapy. Therefore, this work will not only provide an effective full-spectrum photocatalytic reagent for anti-bacteria therapy and wound healing, but also provide a rational idea for the development of other novel antibacterial agents for applications in the biomedical field.

Changes in Bone Mineral Density After Parathyroidectomy and Their Relations With Biochemical Markers of Bone Metabolism.

BACKGROUND: To measure total type 1 serum amino-terminal propeptide procollagen (t-P1NP), ß- type 1 cross-linked C-terminal telopeptide collagen (ß-CTX), N-terminal osteocalcin (OC), and 25-(OH)-VD3 levels before parathyroidectomy (PTX) in patients with PHPT, and correlate these measurements with bone mineral density (BMD) changes at 1-year post-PTX. METHODS: Patients with primary hyperparathyroidism (PHPT) were followed from diagnosis to 12 months after surgery. Serum levels of calcium, parathyroid hormone (PTH), vitamin 25-(OH)-VD3, OC, ß-CTX, t-P1NP, and BMD were measured before and 1 year after surgery. RESULTS: One year after PTX, mean BMD increased by 25.7, 27.7, and 33.5% in the lumbar spine (L1-L4), femoral neck (FN), and greater trochanter (GT), respectively. Percent BMD change 1-year post-PTX was significant correlated with preoperative levels of ß-CTX (L1-L4: r = 0.41, P < 0.0001; FN: r = 0.54, P = 0.0003; GT: r = 0.46, P = 0.0029), t-P1NP (L1-L4: r = 0.58, P < 0.0001; FN: r = 0.73, P < 0.0001; GT: r = 0.65, P < 0.0001), 25-(OH)-VD3 (L1-L4: r = -0.33, P = 0.034; FN: r = -0.48, P = 0.002; GT: r = -0.52, P = 0.0007), and OC (L1-L4: r = 0.49, P = 0.0013; FN: r = 0.55, P = 0.0002; GT: r = 0.47, P = 0.002). CONCLUSIONS: Preoperative levels of turnover markers and BMD improvements were significantly correlated in patients with PHPT 1 year after PTX.

AuNPs@MoSe2 heterostructure as a highly efficient coreaction accelerator of electrocheluminescence for amplified immunosensing of DNA methylation.

Electrocheluminescence analysis amplified by coreaction accelerators has experienced breakthrough in ultrasensitive detection of biomarkers. Herein, a highly efficient coreaction accelerator, two-dimensional layered MoSe2 nanosheets loaded with gold nanoparticles (AuNPs@MoSe2 heterostructure), is proposed to enhance the ECL efficiency of Ru(bpy)32+/tripropylamine (TPrA) system. The presence of AuNPs avoids the aggregation of MoSe2 nanosheets, and improves the electrical conductivity of modified surface. The AuNPs@MoSe2 modified electrode also provides a large area for loading of abundant capture probe. MoSe2 as an electroactive substrate can remarkably accelerate the generation of TPrA•+ radicals to react with electrooxidized Ru(bpy)32+, which achieves about 3.4-fold stronger ECL intensity. Thus, an enhanced ECL immunoassay method can be achieved after Ru(bpy)32+-doped silica nanoparticle labeled antibody (Ab2-Ru@SiO2) is captured to the modified electrode via immunological recognition. Using methylated DNA as a target, the immunosensor was prepared by binding capture DNA on AuNPs@MoSe2 modified electrode to successively capture the target, anti-5-methylcytosine antibody (anti-5mC) and Ab2-Ru@SiO2. The proposed strategy could detect 0.26 fM 5 mC (3σ) with a detectable concentration range of 1.0 fM - 10 nM at methylated DNA. This immunosensor showed excellent selectivity, good stability and reproducibility, and acceptable recovery, indicating the broad prospects of the novel coreaction accelerator in clinical diagnosis.

Patulinervones A and B, two novel α-glucosidase inhibitory spiro-lignans from Melicope patulinervia (Merr. & Chun) C.C. Huang.

(±)-Patulinervones A (1) and B (2), two diastereomers of spiro-lignans sharing an unprecedented dimethyl-spiro[furan-2,2'-furo[2,3-b]furan] 5/5/5 tricyclic moiety were isolated from the leaves of Melicope patulinervia (Merr. & Chun) C.C. Huang. Their structures were established by extensive spectroscopic data and electronic circular dichroism (ECD) analyses. The racemates (±)-1 and 2 and their enantiomers exhibited α-glucosidase inhibitory effect with IC50 values range of 10.08 ± 1.24 - 25.58 ± 1.97 µM.

Electrochemiluminescence of Polymer Dots Featuring Thermally Activated Delayed Fluorescence for Sensitive DNA Methylation Detection.

Polymer dots (Pdots) as electrochemiluminescence (ECL) emitters have drawn intensive attention for expanding the application of ECL analytical technology. Here we used a donor-acceptor polymer with thermally activated delayed fluorescence (TADF) property as a precursor to design and synthesize a kind of highly efficient Pdots with desirable annihilation and co-reactant ECL behaviors. The TADF Pdots possessed a highly stable negative-charged state in the ECL process, and their ECL emission followed the "S-route", thus achieving theoretically 100% excitons harvesting for radiative decay. With S2O82- or tripropylamine as the co-reactant, the TADF Pdots exhibited intensive bandgap ECL emission and possessed ultrahigh ECL efficiency, which were superior to conventional fluorescent Pdots due to the TADF property and the shielding of oxygen quenching effect toward triplet excitons. By combining the stable cathodic ECL property of TADF Pdots with rolling circle amplification reaction, a sensitive ECL biosensor was designed for DNA methylation detection with RASSF1A gene fragment as a target model, which showed detection limits down to the fM level and realized the localization of the methylation site on target DNA based on steric hindrance effect. This work revealed the great potential of TADF emitters in ECL efficiency elevation and offered a new idea for the development of detection kits to quantitatively detect gene methylation.

Tumor microenvironment-activated single-atom platinum nanozyme with H2O2 self-supplement and O2-evolving for tumor-specific cascade catalysis chemodynamic and chemoradiotherapy.

Nanozyme-based tumor collaborative catalytic therapy has attracted a great deal of attention in recent years. However, their cooperative outcome remains a great challenge due to the unique characteristics of tumor microenvironment (TME), such as insufficient endogenous hydrogen peroxide (H2O2) level, hypoxia, and overexpressed intracellular glutathione (GSH). Methods: Herein, a TME-activated atomic-level engineered PtN4C single-atom nanozyme (PtN4C-SAzyme) is fabricated to induce the "butterfly effect" of reactive oxygen species (ROS) through facilitating intracellular H2O2 cycle accumulation and GSH deprivation as well as X-ray deposition for ROS-involving CDT and O2-dependent chemoradiotherapy. Results: In the paradigm, the SAzyme could boost substantial ∙OH generation by their admirable peroxidase-like activity as well as X-ray deposition capacity. Simultaneously, O2 self-sufficiency, GSH elimination and elevated Pt2+ release can be achieved through the self-cyclic valence alteration of Pt (IV) and Pt (II) for alleviating tumor hypoxia, overwhelming the anti-oxidation defense effect and overcoming drug-resistance. More importantly, the PtN4C-SAzyme could also convert O2·- into H2O2 by their superior superoxide dismutase-like activity and achieve the sustainable replenishment of endogenous H2O2, and H2O2 can further react with the PtN4C-SAzyme for realizing the cyclic accumulation of ∙OH and O2 at tumor site, thereby generating a "key" to unlock the multi enzymes-like properties of SAzymes for tumor-specific self-reinforcing CDT and chemoradiotherapy. Conclusions: This work not only provides a promising TME-activated SAzyme-based paradigm with H2O2 self-supplement and O2-evolving capacity for intensive CDT and chemoradiotherapy but also opens new horizons for the construction and tumor catalytic therapy of other SAzymes.

Retraction notice to "The cytoprotective effects of Δ-17 fatty acid desaturase on injured HUVECs and its underlying mechanism" [Saudi Pharm. J. 25(4) (2017) 587-594].

[This retracts the article DOI: 10.1016/j.jsps.2017.04.028.].

Pan-Cancer Analyses Reveal Oncogenic and Immunological Role of PLOD2.

Some previous studies have shown that PLOD2 has some value in tumorigenesis. However, the broad significance of PLOD2 has not been discussed in depth. This study was aimed at elaborated and summarized the value of PLOD2 in various tumors. First, we integrated GTEx, The Cancer Genome Atlas and Cancer Cell Line Encyclopedia databases to analyze the expression of PLOD2, and found that it was expressed differently in normal tissues and significantly highly expressed in most tumors compared with normal tissues. Second, our analysis revealed that PLOD2 expression was negatively correlated with the prognosis of several tumors. For gastric cancer, the median overall survival time was significantly higher in the PLOD2 low expression group [HR 0.616 (95%CI 0.442-0.858), p = 0.004]. Third, for tumor immunity, PLOD2 was significantly associated with tumor infiltration, including immune infiltrating cells; immune checkpoint expression; immune microenvironment scores (immune score, stromal score and estimate scores); immunotherapy-related scores (tumor mutational burden, microsatellite instability, tumor neoantigen burden); expression of DNA repair genes Mismatch Repairs and methyltransferase; and enrichment analyses identified PLOD2-associated terms and pathways. Lastly, twenty pairs of gastric cancer and adjacent immunohistochemistry showed that PLOD2 was significantly overexpressed in gastric cancer (p < 0.001). Collectively, PLOD2 played a significant role in tumorigenesis and maybe serve as a potential biomarker for diagnosis and prognosis in cancers.

SOX17-mediated MALAT1-miR-199a-HIF1α axis confers sensitivity in esophageal squamous cell carcinoma cells to radiotherapy.

Radiotherapy is a main modality of esophageal squamous cell carcinoma (ESCC) treatment, while radioresistance largely limits the effect of this therapy. Evidence exists reporting that SOX17 may sensitize ESCC cells to irradiation, but the downstream mechanism remains poorly understood. Therefore, we attempt to explore the molecular basis of SOX17 effect on radioresistance in ESCC. The SOX17 expression was measured in ESCC tissues and cells, followed by evaluation of its relationship with patient survival. The fractionated irradiation-induced irradiation-resistant cell line KYSE150R was subjected to gain- and loss-of function studies to explore the effect of SOX17 and downstream effectors MALAT1, miR-199a, and HIF1α on the malignant phenotypes of ESCC. The interaction among these factors was explained using ChIP, dual luciferase reporter, RNA pull-down and RIP assays. Further, the in vivo effect of SOX17 on ESCC irradiation tolerance was assessed in nude mice. SOX17 was underexpressed in ESCC tissues and cells, which was negatively correlated with the prognosis of patients with ESCC. Besides, SOX17 inhibited irradiation tolerance of ESCC cells by suppressing MALAT1 transcription. Notably, MALAT1 acted as miR-199a sponge and thereby enhanced HIF1α expression. Moreover, SOX17 reduced the irradiation tolerance of ESCC cells by reducing HIF1α expression via the MALAT1-miR-199a axis, and attenuated tumor formation in nude mice. Our results indicate that SOX17 can impede the radioresistance of ESCC cells through the MALAT1-miR-199a-HIF1α axis, in support of further research for ESCC radiotherapy.

Influence of Label Design and Country of Origin Information in Wines on Consumers' Visual, Sensory, and Emotional Responses.

This study aimed to evaluate the influence of origin information on Pinot Noir wine labels using eye-tracking and its associations with purchase intent, and hedonic and subconscious emotional responses. Two studies were carried out on untrained university staff and students aged 20-60 years old. Study 1 was conducted to assess consumers' (n = 55; 55% males, and 45% females) self-reported and subconscious responses towards four design labels (with and without New Zealand origin name/script or origin logo) using eye-tracking and video analysis to evaluate emotions of participants. In study 2, participants (n = 72, 56% males, and 44% females) blind-tasted the same wine sample from different labels while recording their self-reported responses. In study 1, no significant differences were found in fixations between origin name/script and origin logo. However, participants paid more attention to the image and the brand name on the wine labels. In study 2, no significant effects on emotional responses were found with or without the origin name/script or logo. Nonetheless, a multiple factor analysis showed either negative or no associations between the baseline (wine with no label) and the samples showing the different labels, even though the taste of the wine samples was the same, which confirmed an influence of the label on the wine appreciation. Among results from studies 1 and 2, origin information affected the purchase intent and hedonic responses marginally. These findings can be used to design wine labels for e-commerce.

Risk factors for twin pregnancy in women undergoing double cleavage embryo transfer.

BACKGROUND: Two or more embryo transfers have been used to increase the success rate of live birth in traditional in vitro fertilization (IVF) strategy at the expense of increased risks of multiple pregnancy and adverse perinatal outcomes. The decision regarding the elective single embryo transfer or double embryo transfer remains inconclusive. The aim of this study was to investigate the risk factors for twin pregnancy in IVF. METHODS: Participants who underwent their first fresh IVF cycle where two cleavage stage embryos were transferred in Women's Hospital of Zhejiang University between January 2010 and December 2018 were included in this retrospective cohort study. The primary outcome was twin delivery. Secondary outcomes included preterm birth and low birth weight RESULTS: Fifteen thousand four hundred fifty-nine women were available for final analysis, in which 1511 women resulted in twin delivery and 4788 women had singleton delivery. Female age over 35 was associated with reduced rates of twin pregnancy compared with female age at or less than 35 (9.5% vs 25.1%, aRR = 0.38 (0.27. 0.55)). Poor-type endometrium was associated with reduced rates of twin pregnancy (19.2% vs 27.5%, aRR = 0.75 (0.58. 0.96)). Two good-quality embryos for transfer was associated with significantly higher rates of twin pregnancy compared with one good-quality or none good-quality embryo (26% vs 12.8% vs 9.3%, aRR = 0.56 (0.45. 0.70), aRR = 0.44(0.26. 0.74)). Female age over 35 and none or one good-quality embryo for transfer were associated with reduced rate of low birth weight and preterm birth. CONCLUSION: Women with age over 35, poor-type endometrium, one good-quality embryo or none good-quality embryo were associated with reduced rate for twin pregnancy.

The cyclin-dependent kinase inhibitor AT7519 augments cisplatin's efficacy in ovarian cancer via multiple oncogenic signaling pathways.

Although cisplatin is the most active drug for the treatment of ovarian cancer, majority of patients develop resistance and ultimately relapse. Enhancing the efficacy of cisplatin could represent a promising strategy to improve the clinical outcome of patients with ovarian cancer. AT7519 is a multitargeted cyclin-dependent kinase (CDK) inhibitor and displays potent anticancer activities. In this work, we show that the combination of AT7519 with cisplatin is much more superior to cisplatin alone in inhibiting ovarian cancer. AT7519 at nanomolar concentrations inhibits proliferation and migration and induces apoptosis of multiple ovarian cancer cell lines. In contrast, AT7519 at the same concentrations either does not affect survival or is significantly less effective in inhibiting proliferation and migration in normal ovarian cells and fibroblast cells. AT7519 significantly augments the inhibitory effects of cisplatin in ovarian cancer cells in a dose-dependent manner. Mechanistic studies suggest that AT7519 (i) inhibits proliferation via decreasing activities of CDK1 and 2, and via inhibiting RNA transcription; (ii) inhibits migration via suppressing epithelial-mesenchymal transition (EMT); and (iii) induces apoptosis via decreasing Mcl-1 and increasing Bim in ovarian cancer cells. Using a human ovarian cancer xenograft mouse model, we confirm the in vivo efficacy of AT7519 alone, and the synergistic effects of AT7519 and cisplatin in combination, at doses that cause minimal toxicity in mice. Our findings provide systematic preclinical evidence to support the initialization of clinical trials of the AT7519 and cisplatin combination for the treatment of ovarian cancer.