Multi-granularity contrastive learning model for next POI recommendation.

Next Point-of-Interest (POI) recommendation aims to predict the next POI for users from their historical activities. Existing methods typically rely on location-level POI check-in trajectories to explore user sequential transition patterns, which suffer from the severe check-in data sparsity issue. However, taking into account region-level and category-level POI sequences can help address this issue. Moreover, collaborative information between different granularities of POI sequences is not well utilized, which can facilitate mutual enhancement and benefit to augment user preference learning. To address these challenges, we propose multi-granularity contrastive learning (MGCL) for next POI recommendation, which utilizes multi-granularity representation and contrastive learning to improve the next POI recommendation performance. Specifically, location-level POI graph, category-level, and region-level sequences are first constructed. Then, we use graph convolutional networks on POI graph to extract cross-user sequential transition patterns. Furthermore, self-attention networks are used to learn individual user sequential transition patterns for each granularity level. To capture the collaborative signals between multi-granularity, we apply the contrastive learning approach. Finally, we jointly train the recommendation and contrastive learning tasks. Extensive experiments demonstrate that MGCL is more effective than state-of-the-art methods.

Depletion of placental brain-derived neurotrophic factor (BDNF) is attributed to premature ovarian insufficiency (POI) in mice offspring.

INTRODUCTION: Premature ovarian insufficiency (POI) is one of the causes of female infertility. Unexplained POI is increasingly affecting women in their reproductive years. However, the etiology of POI is diverse and remains elusive. We and others have shown that brain-derived neurotrophic factor (BDNF) plays an important role in adult ovarian function. Here, we report on a novel role of BDNF in the Developmental Origins of POI. METHODS: Placental BDNF knockout mice were created using CRISPR/CAS9. Homozygous knockout (cKO(HO)) mice didn't survive, while heterozygous knockout (cKO(HE)) mice did. BDNF reduction in cKO(HE) mice was confirmed via immunohistochemistry and Western blots. Ovaries were collected from cKO(HE) mice at various ages, analyzing ovarian metrics, FSH expression, and litter sizes. In one-month-old mice, oocyte numbers were assessed using super-ovulation, and oocyte gene expression was analyzed with smart RNAseq. Ovaries of P7 mice were studied with SEM, and gene expression was confirmed with RT-qPCR. Alkaline phosphatase staining at E11.5 and immunofluorescence for cyclinD1 assessed germ cell number and cell proliferation. RESULTS: cKO(HE) mice had decreased ovarian function and litter size in adulthood. They were insensitive to ovulation induction drugs manifested by lower oocyte release after superovulation in one-month-old cKO(HE) mice. The transcriptome and SEM results indicate that mitochondria-mediated cell death or aging might occur in cKO(HE) ovaries. Decreased placental BDNF led to diminished primordial germ cell proliferation at E11.5 and ovarian reserve which may underlie POI in adulthood. CONCLUSION: The current results showed decreased placental BDNF diminished primordial germ cell proliferation in female fetuses during pregnancy and POI in adulthood. Our findings can provide insights into understanding the underlying mechanisms of POI.

Content-Aware Human Mobility Pattern Extraction.

Extracting meaningful patterns of human mobility from accumulating trajectories is essential for understanding human behavior. However, previous works identify human mobility patterns based on the spatial co-occurrence of trajectories, which ignores the effect of activity content, leaving challenges in effectively extracting and understanding patterns. To bridge this gap, this study incorporates the activity content of trajectories to extract human mobility patterns, and proposes acontent-aware mobility pattern model. The model first embeds the activity content in distributed continuous vector space by taking point-of-interest as an agent and then extracts representative and interpretable mobility patterns from human trajectory sets using a derived topic model. To investigate the performance of the proposed model, several evaluation metrics are developed, including pattern coherence, pattern similarity, and manual scoring. A real-world case study is conducted, and its experimental results show that the proposed model improves interpretability and helps to understand mobility patterns. This study provides not only a novel solution and several evaluation metrics for human mobility patterns but also a method reference for fusing content semantics of human activities for trajectory analysis and mining.

Deleterious variants in RNF111 impair female fertility and induce premature ovarian insufficiency in humans and mice.

Premature ovarian insufficiency (POI) is a heterogeneous female disorder characterized by the loss of ovarian function before the age of 40. It represents a significant detriment to female fertility. However, the known POI-causative genes currently account for only a fraction of cases. To elucidate the genetic factors underlying POI, we conducted whole-exome sequencing on a family with three fertile POI patients and identified a deleterious missense variant in RNF111. In a subsequent replication study involving 1,030 POI patients, this variant was not only confirmed but also accompanied by the discovery of three additional predicted deleterious RNF111 variants. These variants collectively account for eight cases, representing 0.78% of the study cohort. A further study involving 500 patients with diminished ovarian reserve also identified two additional RNF111 variants. Notably, RNF111 encodes an E3 ubiquitin ligase with a regulatory role in the TGF-ß/BMP signaling pathway. Our analysis revealed that RNF111/RNF111 is predominantly expressed in the oocytes of mice, monkeys, and humans. To further investigate the functional implications of RNF111 variants, we generated two mouse models: one with a heterozygous missense mutation (Rnf111+/M) and another with a heterozygous null mutation (Rnf111+/-). Both mouse models exhibited impaired female fertility, characterized by reduced litter sizes and small ovarian reserve. Additionally, RNA-seq and quantitative proteomics analysis unveiled that Rnf111 haploinsufficiency led to dysregulation in female gonad development and negative regulation of the BMP signaling pathway within mouse ovaries. In conclusion, our findings strongly suggest that monoallelic deleterious variants in RNF111 can impair female fertility and induce POI in both humans and mice.

M6A demethylase FTO-stabilized exosomal circBRCA1 alleviates oxidative stress-induced granulosa cell damage via the miR-642a-5p/FOXO1 axis.

BACKGROUND: Premature ovarian insufficiency (POI) is an important cause of female infertility and seriously impacts the physical and psychological health of patients. Human umbilical cord mesenchymal stem cell-derived exosomes (HucMSCs-Exs, H-Exs) have exhibited protective effects on ovarian function with unclear mechanisms. METHODS: A comprehensive analysis of the Gene Expression Omnibus (GEO) database were used to identify POI-associated circRNAs and miRNAs. The relationship between HucMSC-derived exosomal circBRCA1/miR-642a-5p/FOXO1 axis and POI was examined by RT-qPCR, Western blotting, reactive oxygen species (ROS) staining, senescence-associated ß-gal (SA-ß-gal) staining, JC-1 staining, TEM, oxygen consumption rate (OCR) measurements and ATP assay in vivo and in vitro. RT-qPCR detected the expression of circBRCA1 in GCs and serum of patients with normal ovarian reserve function (n = 50) and patients with POI (n = 50); then, the correlation of circBRCA1 with ovarian reserve function indexes was analyzed. RESULTS: Herein, we found that circBRCA1 was decreased in the serum and ovarian granulosa cells (GCs) of patients with POI and was associated with decreased ovarian reserve. H-Exs improved the disorder of the estrous cycles and reproductive hormone levels, reduced the number of atretic follicles, and alleviated the apoptosis and senescence of GCs in rats with POI. Moreover, H-Exs mitigated mitochondrial damage and reversed the reduced circBRCA1 expression induced by oxidative stress in GCs. Mechanistically, FTO served as an eraser to increase the stability and expression of circBRCA1 by mediating the m6A demethylation of circBRCA1, and exosomal circBRCA1 sponged miR-642a-5p to block its interaction with FOXO1. CircBRCA1 insufficiency aggravated mitochondrial dysfunction, mimicking FTO or FOXO1 depletion effects, which was counteracted by miR-642a-5p inhibition. CONCLUSION: H-Exs secreted circBRCA1 regulated by m6A modification, directly sponged miR-642a-5p to upregulate FOXO1, resisted oxidative stress injuries in GCs and protected ovarian function in rats with POI. Exosomal circBRCA1 supplementation may be a general prospect for the prevention and treatment of POI.

Classification of autonomous vehicle crash severity: Solving the problems of imbalanced datasets and small sample size.

Only a few researchers have shown how environmental factors and road features relate to Autonomous Vehicle (AV) crash severity levels, and none have focused on the data limitation problems, such as small sample sizes, imbalanced datasets, and high dimensional features. To address these problems, we analyzed an AV crash dataset (2019 to 2021) from the California Department of Motor Vehicles (CA DMV), which included 266 collision reports (51 of those causing injuries). We included external environmental variables by collecting various points of interest (POIs) and roadway features from Open Street Map (OSM) and Data San Francisco (SF). Random Over-Sampling Examples (ROSE) and the Synthetic Minority Over-Sampling Technique (SMOTE) methods were used to balance the dataset and increase the sample size. These two balancing methods were used to expand the dataset and solve the small sample size problem simultaneously. Mutual information, random forest, and XGboost were utilized to address the high dimensional feature and the selection problem caused by including a variety of types of POIs as predictive variables. Because existing studies do not use consistent procedures, we compared the effectiveness of using the feature-selection preprocessing method as the first process to employing the data-balance technique as the first process. Our results showed that AV crash severity levels are related to vehicle manufacturers, vehicle damage level, collision type, vehicle movement, the parties involved in the crash, speed limit, and some types of POIs (areas near transportation, entertainment venues, public places, schools, and medical facilities). Both resampling methods and three data preprocessing methods improved model performance, and the model that used SMOTE and data-balancing first was the best. The results suggest that over-sampling and the feature selection method can improve model prediction performance and define new factors related to AV crash severity levels.

[Effect of electroacupuncture on autophagy of ovarian granulosa cells in rats with premature ovarian insufficiency].

OBJECTIVE: To observe the effects of electroacupuncture (EA) on the autophagy of ovarian granulosa cells in rats with premature ovarian insufficiency (POI), and explore the mechanism of EA in improving POI. METHODS: Thirty-two female SD rats were randomly divided into a blank group (n=8) and a model making group (n=24). The rats in the model making group were injected intraperitoneally with cyclophosphamide for 15 days to establish the POI model (the dosage on the 1st day was 50 mg/kg, and 8 mg/kg from the 2nd day to 15th day). The successfully modeled rats were then randomly divided into a model group, an EA group, and an estradiol (E2) group, with 8 rats in each group. Rats in the EA group received EA at bilateral "Gongsun" (SP 4) with continuous wave, frequency of 2 Hz, and current intensity of 0.1 to 1 mA, 20 min per treatment, once daily for 14 days. Rats in the E2 group were administered with E2 (0.01 mg/mL) by gavage (10 mL/kg), once daily for 14 days. The changes in estrous cycle were observed by rapid Giemsa staining before and after modeling. After intervention, ovarian tissue morphology was observed by HE staining; serum levels of follicle-stimulating hormone (FSH), E2, anti-Mullerian hormone (AMH), and inhibin B (INHB) were detected by ELISA; immunofluorescence staining was used to observe the expression of p62 in ovarian granulosa cells; the ultrastructure of ovarian granulosa cells was observed by transmission electron microscopy, and the number of autophagosomes and autolysosomes was compared; Western blot and real-time fluorescence quantitative PCR were used to detect the protein and mRNA expression of p62, Beclin-1, and microtubule-associated protein 1A/1B-light chain 3 (LC3) in ovarian tissue. RESULTS: The results of vaginal smears in the blank group showed regular cyclical changes; the rats in the model group showed prolonged estrous cycle or cycle arrest, mostly in proestrus or metestrus, with overall ovarian atrophy, disordered structure, and decreased granulosa cells. Compared with the blank group, rats in the model group showed increased serum FSH level (P<0.01), decreased serum levels of E2, AMH, and INHB (P<0.01), decreased positive expression of p62 in ovarian granulosa cells (P<0.01), with obvious swelling of ovarian granulosa cells, mild to moderate swelling of mitochondria, slight expansion of rough endoplasmic reticulum, and hypertrophy of Golgi apparatus; the number of autophagosomes and autolysosomes in the ovaries was increased (P<0.01), the expression of p62 protein and mRNA was decreased (P<0.01), and the expression of Beclin-1 and LC3 protein and mRNA in ovarian tissue was increased (P<0.01). Compared with the model group, rats in the EA group and the E2 group showed decreased serum FSH levels (P<0.01), increased levels of E2, AMH, and INHB (P<0.01), increased positive expression of p62 in ovarian granulosa cells (P<0.01), alleviated degree of ovarian granulosa cell damage, with relatively intact organelle morphology, and decreased number of autophagosomes and autolysosomes in the ovaries (P<0.01); the rats also showed increased expression of p62 protein and mRNA (P<0.01), and decreased expression of Beclin-1 and LC3 protein and mRNA (P<0.01) in ovarian tissue. CONCLUSION: EA at "Gongsun" (SP 4) could improve ovarian reserve function in POI rats by reducing the number of autophagosomes and autolysosomes, up-regulating p62 expression, and down-regulating Beclin-1 and LC3 expression, thus inhibiting autophagy of ovarian granulosa cells, and regulating the serum levels of FSH, E2, AMH, and INHB.

Hematological Indices and Genetic Variants of Premature Ovarian Insufficiency: Machine Learning Approaches.

BACKGROUND: Premature Ovarian Insufficiency (POI) is associated with infertility. Little is known about the potential circulating biomarkers that could be used to predict POI. We have investigated the possible association between white and red blood cells, platelet indices, and eight established single nucleotide polymorphisms (SNPs) associated with POI risk. METHOD: 117 women with premature menopause (PM) and 183 healthy women without a history of menopause before age 40 were recruited for this study. The tetra-primer amplification refractory mutation system-polymerase chain reaction (Tetra ARMS PCR) and allele-specific oligonucleotides-polymerase chain reaction (ASO-PCR) were carried out for genotyping for eight SNPs reported to be associated with POI. Decision tree analysis was applied to test the diagnostic value of hematological parameters to identify the risk of POI. RESULTS: Women with POI had lower neutrophil (NEUT) and white blood cell (WBC), whereas red blood cell (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), and mean cell hemoglobin (MCH) were higher. Platelet (PLT) count was also lower in affected women. Our data also indicated that HGB and HCT count were significantly associated with rs16991615 and rs244715. Mean Platelet volume (MPV) and platelet distribution width (PDW) were associated with rs244715, rs1046089, rs4806660, and rs2303369. The rs16991615 was also associated with RBC count, and rs451417 was associated with NEUTs. The decision tree (DT) model reveals that women with the NEUT count at a cut-off value of less than 2.8 and HCT equal to or more than 38.7% could be identified as high-risk cases for POI. Overall, we found the DT approach had a sensitivity = 85%, specificity = 72%, and accuracy = 74%. CONCLUSION: The genetic variants involved in POI are associated with changes in reproductive hormone levels and with changes in hematological indices.

Immunophenotypic profiles and inflammatory markers in Premature Ovarian Insufficiency.

Premature Ovarian Insufficiency (POI), also known as Premature Ovarian Failure (POF), is a heterogeneous disorder characterized by the cessation of ovarian function before age 40. Clinical symptoms include menstrual disorders: amenorrhea/oligomenorrhea or symptoms of estrogen deficiency. This review aims to provide the most important summary of the immunophenotypic profile of premature ovarian failure syndrome, along with a review of the latest reports on the usefulness of inflammatory markers. The inflammatory microenvironment in POI applies to many levels. Concomitants of autoimmune ovarian inflammation and impaired cellular immune response may be a picture of impaired regulation in autoimmune ovarian disease. The serum concentration of pro-inflammatory cytokines, like IL-6, IL-8, IL-17, tumor necrosis factor α (TNF-α), and interferon-gamma (IFN-γ), tend to increase, whereas levels of the anti-inflammatory cytokine, IL-10, tend to decrease. In our review, we focus on whether the measured immunological parameters could help in the diagnosis and prognosis of the syndrome. Among the inflammatory markers, neutrophil-to-lymphocyte ratio (NLR) is noteworthy, as it is decreased in patients with POI. It is important to stress that besides case series, we need properly powered studies with randomization to answer which treatment is effective, and how to deal with concurrent autoimmunity. In this review, we emphasize the importance of the premature ovarian failure syndrome immunoprofile for a proper understanding of the complexity of this syndrome, potential diagnostic points, and therapeutic targets.

Juvenile idiopathic arthritis and primary ovarian failure: a two-sample Mendelian randomization analysis in a mixed-gender cohort.

Background: The causal relationship between juvenile idiopathic arthritis (JIA) and primary ovarian failure (POF) remains uncertain. To elucidate this relationship, we employed a two-sample Mendelian randomization analysis. Methods: The single nucleotide polymorphisms (SNPs) associated with JIA were obtained from a previously published genome-wide association study (GWAS), while the pooled data for POF originated from the FinnGen consortium. The study populations consisted exclusively of individuals of European descent. In our Mendelian randomization analysis, we performed inverse-variance weighted analysis, weighted-median analysis, weighted-mode analysis and Mendelian randomization-Egger regression analysis, supplemented by sensitivity analyses to validate the accuracy and robustness of the findings. Results: The IVW (OR = 1.23, 95% CI 1.06-1.43; P = 0.007) and weighted median (OR = 1.25, 95% CI 1.06-1.47; P = 0.009), along with sensitivity analysis validation, provide compelling evidence of a significant causal association between JIA and POF. Conclusion: The study revealed a significant causal association between genetically predicted JIA and POF, indicating that JIA significantly elevates the risk of developing POF. Therefore, it is recommended to implement screening for premature ovarian failure in women diagnosed with JIA.

Wine- and stir-frying processing of Cuscutae Semen enhance its ability to alleviate oxidative stress and apoptosis via the Keap 1-Nrf2/HO-1 and PI3K/AKT pathways in H2O2-challenged KGN human granulosa cell line.

BACKGROUND: Cuscutae Semen (CS) has been prescribed in traditional Chinese medicine (TCM) for millennia as an aging inhibitor, an anti-inflammatory agent, a pain reliever, and an aphrodisiac. Its three main forms include crude Cuscutae Semen (CCS), wine-processed CS (WCS), and stir-frying-processed CS (SFCS). Premature ovarian insufficiency (POI) is a globally occurring medical condition. The present work sought a highly efficacious multi-target therapeutic approach against POI with minimal side effects. Finally, it analyzed the relative differences among CCS, WCS and SFCS in terms of their therapeutic efficacy and modes of action against H2O2-challenged KGN human granulosa cell line. METHODS: In this study, ultrahigh-performance liquid chromatography (UPLC)-Q-ExactiveTM Orbitrap-mass spectrometry (MS), oxidative stress indices, reactive oxygen species (ROS), Mitochondrial membrane potential (MMP), real-time PCR, Western blotting, and molecular docking were used to investigate the protective effect of CCS, WCS and SFCS on KGN cells oxidative stress and apoptosis mechanisms. RESULTS: The results confirmed that pretreatment with CCS, WCS and SFCS reduced H2O2-induced oxidative damage, accompanied by declining ROS levels and malondialdehyde (MDA) accumulation in the KGN cells. CCS, WCS and SFCS upregulated the expression of antioxidative levels (GSH, GSH/GSSG ratio, SOD, T-AOC),mitochondrial membrane potential (MMP) and the relative mRNA(Nrf2, Keap1, NQO-1, HO-1, SOD-1, CAT). They inhibited apoptosis by upregulating Bcl-2, downregulating Bax, cleaved caspase-9, and cleaved caspase-3, and lowering the Bax/Bcl-2 ratio. They also exerted antioxidant efficacy by partially activating the PI3K/Akt and Keap1-Nrf2/HO-1 signaling pathways. CONCLUSIONS: The results of the present work demonstrated the inhibitory efficacy of CCS, WCS and SFCS against H2O2-induced oxidative stress and apoptosis in KGN cells and showed that the associated mechanisms included Keap1-Nrf2/HO-1 activation, P-PI3K upregulation, and P-Akt-mediated PI3K-Akt pathway induction.

Sexual function in women with premature ovarian insufficiency (POI): Systematic review and meta-analysis.

Premature ovarian insufficiency (POI) is a rare condition characterized by loss of ovarian function before the age of 40. POI seems associated with mood disorders and sexual dysfunction. However, there is a lack of high-quality evidence relating to the impact of POI on sexual function. Therefore, we conducted a systematic review and meta-analysis to evaluate sexual function in women with POI compared to women without the condition. The following online databases were systematically searched up to January 2023: EMBASE, Medline (Ovid), Web of Science, Cochrane, PsychInfo, and Google Scholar. Random effects models were used for analyses, with data reported as Hedges' g and 95 % confidence interval, and the risk of heterogeneity was evaluated. The protocol of this study was registered with PROSPERO (CRD42023437203). A total of 10 studies were included in the systematic review and 5 studies involving 352 women with POI were included in the meta-analysis. Eight of the ten studies concluded that women with POI have reduced sexual function. An overall medium Hedges' g effect size of -0.72 was found (ranging between -0.20 and -1.29) in favor of control women, with moderate heterogeneity (I2 = 64 %). Stratified studies of women on systemic hormone replacement therapy (HRT) showed an even higher Hedges' g effect size, of -0.82 (95 % CI -1.18, -0.47). In conclusion, sexual function in women with POI is reduced compared with control women. Sexual function should be discussed with women with POI and they should be offered psychosexual counseling.

Screening of premature ovarian insufficiency associated genes in Hungarian patients with next generation sequencing.

BACKGROUND: Premature ovarian insuffiency (POI) is one of the main cause behind infertility. The genetic analysis of POI should be part of the clinical diagnostics, as several genes have been implicated in the genetic background of it. The aim of our study was to analyse the genetic background of POI in a Hungarian cohort. METHODS: The age of onset was between 15 and 39 years. All patients had the 46,XX karyotype and they were prescreened for the most frequent POI associated FMR1 premutation. To identify genetic alterations next-generation sequencing (NGS) of 31 genes which were previously associated to POI were carried out in 48 unrelated patients from Hungary. RESULTS: Monogenic defect was identified in 16.7% (8 of 48) and a potential genetic risk factor was found in 29.2% (14 of 48) and susceptible oligogenic effect was described in 12.5% (6 of 48) of women with POI using the customized targeted panel sequencing. The genetic analysis identified 8 heterozygous damaging and 4 potentially damaging variants in POI-associated genes. Further 10 potential genetic risk factors were detected in seven genes, from which EIF2B and GALT were the most frequent. These variants were related to 15 genes: AIRE, ATM, DACH2, DAZL, EIF2B2, EIF2B4, FMR1, GALT, GDF9, HS6ST2, LHCGR, NOBOX, POLG, USP9X and XPNPEP2. In six cases, two or three coexisting damaging mutations and risk variants were identified. CONCLUSIONS: POI is characterized by heterogenous phenotypic features with complex genetic background that contains increasing number of genes. Deleterious variants, which were detected in our cohort, related to gonadal development (oogenesis and folliculogenesis), meiosis and DNA repair, hormonal signaling, immune function, and metabolism which were previously associated with the POI phenotype. This is the first genetic epidemiology study targeting POI associated genes in Hungary. The frequency of variants in different POI associated genes were similar to the literature, except EIF2B and GALT. Both of these genes potential risk factor were detected which could influence the phenotype, although it is unlikely that they can be responsible for the development of the disease by themselves. Advances of sequencing technologies make it possible to aid diagnostics of POI Since individual patients show high phenotypic variance because of the complex network controlling human folliculogenesis. Comprehensive NGS screening by widening the scope to genes which were previously linked to infertility may facilitate more accurate, quicker and cheaper genetic diagnoses for POI. The investigation of patient's genotype could support clinical decision-making process and pave the way for future clinical trials and therapies.

Yu Linzhu alleviates primary ovarian insufficiency in a rat model by improving proliferation and energy metabolism of granulosa cells through hif1α/cx43 pathway.

BACKGROUND: Yu Linzhu (YLZ) is a classical Chinese traditional formula, which has been used for more than 600 years to regulate menstruation to help pregnancy. However, the mechanism of modern scientific action of YLZ needs to be further studied. METHODS: Thirty SD female rats were divided into three groups to prepare the blank serum and drug-containing serum, and then using UHPLC-QE-MS to identify the ingredients of YLZ and its drug-containing serum. Twenty-four SD female rats were divided into four groups, except the control group, 4-vinylcyclohexene dicycloxide (VCD) was intraperitoneally injected to establish a primary ovarian insufficiency (POI) model of all groups. Using vaginal smear to show that the estrous cycle of rats was disturbed after modeling, indicates that the POI model was successfully established. The ELISA test was used to measure the follicle-stimulating hormone (FSH), estradiol (E2), and anti-Mullerian hormone (AMH) levels in the serum of rats. HE stain was used to assess the morphology of ovarian tissue. The localization and relative expression levels of CX43 protein were detected by tissue immunofluorescence. Primary ovarian granulosa cells (GCs) were identified by cellular immunofluorescence. CCK8 was used to screen time and concentration of drug-containing serum and evaluate the proliferation effect of YLZ on VCD-induced GCs. ATP kit and Seahorse XFe24 were used to detect energy production and real-time glycolytic metabolism rate of GCs. mRNA and protein expression levels of HIF1α, CX43, PEK, LDH, HK1 were detected by RT-PCR and WB. RESULTS: UHPLC-QE-MS found 1702 ingredients of YLZ and 80 constituents migrating to blood. YLZ reduced the FSH while increasing the AMH and E2 levels. In ovarian tissues, YLZ improved ovarian morphology, follicle development, and the relative expression of CX43. In vitro studies, we found that YLZ increased the proliferative activity of GCs, ATP levels, glycolytic metabolic rate, HIF1α, CX43, PEK, HK1, LDH mRNA, and protein levels. CONCLUSIONS: The study indicated that YLZ increased the proliferation and glycolytic energy metabolism of GCs to improve follicular development further alleviating ovarian function.

Hypergonadotropic Hypogonadism Due to Transaldolase Deficiency: Two Cases and Literature Review.

Transaldolase deficiency is a rare autosomal recessive inborn error of carbohydrate metabolism caused by pathogenic/likely pathogenic biallelic mutations in the TALDO1 gene. This disorder is characterized by multisystem involvement with variable phenotypes, including intrauterine growth restriction; dysmorphic features; abnormal skin; hepatosplenomegaly; cytopenia; and cardiac, renal, and endocrine abnormalities. Herein, we present two Emirati patients with hypergonadotropic hypogonadism due to transaldolase deficiency and variable phenotypes of systemic involvement.

Exploring the spatial relationship of e-bike and motorcycle crashes: Implications for risk reduction.

INTRODUCTION: Electric bicycles, or e-bikes, have become very popular over the past decade. In order to reduce the risk of crashes, it is necessary to understand the contributing factors. While several researchers have examined these elements, few have considered the spatial heterogeneity between crashes and environmental variables, such as Points of Interest (POI). In addition, there is a scarcity of studies comparing the crash-related factors of e-bikes and motorcycles. Despite their differing speed and range capabilities, different POIs also tend to impact area/bandwidths differently because e-bikes cannot cover the same range that motorcycles can. METHOD: In this study, we compared e-bike and motorcycle crashes at 11 different types of POIs in Taipei from 2016 to 2020. Since crashes are sparse events and easily affected by the Modifiable Areal Unit Problem (MAUP), Kernel Density Estimation (KDE) was employed to transform crash points (count data) to crash risk surfaces (continuous data). Additionally, an advanced variant of Geographical Weighted Regression (GWR), Multiscale Geographically Weighted Regression (MGWR) utilized to predict crash risk because each predictor is allowed to have a different bandwidth. RESULTS: The results showed: (a) For e-bike crashes, the MGWR model outperformed the GWR and OLS models in terms of AIC values, while the MGWR and GWR performed similarly with regard to motorcycle crashes; (b) The analysis revealed e-bike and motorcycle crash risk to be associated with various types of POIs. E-bike crashes tended to occur more frequently in areas with more schools, supermarkets, intersections, and elderly people. Meanwhile, motorcycle crashes were more likely to occur in areas with a high number of restaurants and intersections. The search bandwidths of e-bikes are inconsistent and narrower than those of motorcycles.

Artificial intelligence algorithms for predicting post-operative ileus after laparoscopic surgery.

Objective: By constructing a predictive model using machine learning and deep learning technologies, we aim to understand the risk factors for postoperative intestinal obstruction in laparoscopic colorectal cancer patients, and establish an effective artificial intelligence-based predictive model to guide individualized prevention and treatment, thus improving patient outcomes. Methods: We constructed a model of the artificial intelligence algorithm in Python. Subjects were randomly assigned to either a training set for variable identification and model construction, or a test set for testing model performance, at a ratio of 7:3. The model was trained with ten algorithms. We used the AUC values of the ROC curves, as well as accuracy, precision, recall rate and F1 scores. Results: The results of feature engineering composited with the GBDT algorithm showed that opioid use, anesthesia duration, and body weight were the top three factors in the development of POI. We used ten machine learning and deep learning algorithms to validate the model, and the results were as follows: the three algorithms with best accuracy were XGB (0.807), Decision Tree (0.807) and Neural DecisionTree (0.807); the two algorithms with best precision were XGB (0.500) and Decision Tree (0.500); the two algorithms with best recall rate were adab (0.243) and Decision Tree (0.135); the two algorithms with highest F1 score were adab (0.290) and Decision Tree (0.213); and the three algorithms with best AUC were Gradient Boosting (0.678), XGB (0.638) and LinearSVC (0.633). Conclusion: This study shows that XGB and Decision Tree are the two best algorithms for predicting the risk of developing ileus after laparoscopic colon cancer surgery. It provides new insight and approaches to the field of postoperative intestinal obstruction in colorectal cancer through the application of machine learning techniques, thereby improving our understanding of the disease and offering strong support for clinical decision-making.

Can we predict menopause and premature ovarian insufficiency?

The prediction of menopause and premature ovarian insufficiency (POI) involves understanding the factors that contribute to the timing of these events. Menopause is a natural biological process marked by the cessation of menstrual periods, typically occurring around the age of 51. On the other hand, POI refers to the loss of ovarian function before the age of 40. Several factors have been used to predict menopause and POI such as age, antimüllerian hormone, inhibins and follicle-stimulating hormone serum levels, antral follicle counts, menstrual cycle length, and, recently, some genetic markers. It seems that age has the best predictive power and all the other ones are only adding in a very limited way to the prediction of menopause. Low levels of antimüllerian hormone in young women might indicate a greater risk for POI and could facilitate early diagnosis. It is, however, important to note that predicting the exact timing of menopause and POI is challenging, and individual variations are significant. Although these factors can provide some insights, they are not foolproof predictors. Advances in medical research and technology may lead to more accurate methods for predicting menopause and POI in the future.

Polycomb repressive complex 1 modulates granulosa cell proliferation in early folliculogenesis to support female reproduction.

Rationale: Premature ovarian insufficiency (POI) is an accelerated reduction in ovarian function inducing infertility. Folliculogenesis defects have been reported to trigger POI as a consequence of ovulation failure. However, the underlying mechanisms remain unclear due to the genetic complexity and heterogeneity of POI. Methods: We used whole genome sequencing (WGS), conditional knockout mouse models combined with laser capture microdissection (LCM), and RNA/ChIP sequencing to analyze the crucial roles of polycomb repressive complex 1 (PRC1) in clinical POI and mammalian folliculogenesis. Results: A deletion mutation of MEL18, the key component of PRC1, was identified in a 17-year-old patient. However, deleting Mel18 in granulosa cells (GCs) did not induce infertility until its homolog, Bmi1, was deleted simultaneously. Double deficiency of BMI1/MEL18 eliminated PRC1 catalytic activity, upregulating cyclin-dependent kinase inhibitors (CDKIs) and thus blocking GC proliferation during primary-to-secondary follicle transition. This defect led to damaged intercellular crosstalk, eventually resulting in gonadotropin response failure and infertility. Conclusions: Our findings highlighted the pivotal role of PRC1 as an epigenetic regulator of gene transcription networks in GC proliferation during early folliculogenesis. In the future, a better understanding of molecular details of PRC1 structural and functional abnormalities may contribute to POI diagnosis and therapeutic options.