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Background Ovarian cancer (OC) is the seventh most common malignancy worldwide and the most lethal gynaecological malignancy. We aimed to explore global geographical patterns and temporal trends from 1973 to 2015 for 41 countries in OC incidence and especially to analyse the birth cohort effect to gain further insight into the underlying causal factors of OC and identify countries with increasing risk of OC. Methods OC data were drawn from the Cancer Incidence in Five Continents databases and online databases published by governments. The joinpoint regression model was applied to detect changes in OC trends. The age–period–cohort model was applied to explore age and birth cohort effects. Results The age-standardized rate of OC incidence ranged from 3.0 to 11.4 per 100,000 women worldwide in 2012. The highest age-standardized rate was observed in Central and Eastern Europe, with 11.4 per 100,000 women in 2012. For the most recent 10-year period, the increasing trends were mainly observed in Central and South America, Asia and Central and Eastern Europe. The largest significant increase was observed in Brazil, with an average annual percentage change of 4.4%. For recent birth cohorts, cohort-specific increases in risk were pronounced in Estonia, Finland, Iceland, Lithuania, the United Kingdom, Germany, the Netherlands, Italy, Malta, Slovenia, Bulgaria, Russia, Australia, New Zealand, Brazil, Costa Rica, Ecuador, India, Japan, the Philippines and Thailand. Conclusions Disparities in the incidence and risk of OC persist worldwide. The increased risk of birth cohort in OC incidence was observed for most countries in Asia, Central and Eastern Europe, and Central and South America. The reason for the increasing OC risk for recent birth cohorts in these countries should be investigated with further epidemiology studies.

Microbiota-host interactions play critical roles in colorectal cancer (CRC) progression, however, the underlying mechanisms remain elusive. Here, we uncover that Fusobacterium nucleatum ( F. nucleatum ) induces a dramatic decline of m 6 A modifications in CRC cells and patient-derived xenograft (PDX) tissues by downregulation of an m 6 A methyltransferase METTL3, contributing to inducation of CRC aggressiveness. Mechanistically, we characterized forkhead box D3 (FOXD3) as a transcription factor for METTL3. F. nucleatum activates YAP signaling, inhibits FOXD3 expression, and subsequently reduces METTL3 transcription. Downregulation of METTL3 promotes its target kinesin family member 26B (KIF26B) expression by reducing its m 6 A levels and diminishing YTHDF2-dependent mRNA degradation, which contributes to F. nucleatum -induced CRC metastasis. Moreover, METTL3 expression is negatively correlated with F. nucleatum and KIF26B levels in CRC tissues. A high expression of KIF26B is also significantly correlated with a shorter survival time of CRC patients. Together, our findings provide insights into modulating human m 6 A epitranscriptome by gut microbiota, and its significance in CRC progression. Fusobacterium nucleatum contributes to host epitranscriptomic modifications and colorectal cancer (CRC) development. Here, the authors show that Fusobacterium nucleatum reduces global m 6 A modifications to promote CRC metastasis through a YAP/FOXD3/METTL3/KIF26B axis.

Background With rapid development of China’s economy, there were over 68.7 million left-behind children (LBC) in China whose mental health has become a problem of public concern. The present cross-sectional study aimed to investigate the status of mental health and its associated factors of LBC aged 3–16 years old in both rural and urban areas. Methods A total of 4187 children (aged 3–16), including 1471 LBC and 2716 non-left-behind children (NLBC), were recruited from 50 communities (22 in urban areas and 28 in rural areas) in Guangdong, China in August, 2014. The mental health problems were assessed using the Strength and Difficulties Questionnaire (SDQ). Results No statistically significant difference of SDQ subscales scores about difficulties were found between LBC and NLBC on the whole participants as well as in rural areas or in urban areas within the same age group after adjustments were made (all p  > 0.05). However, compared with NLBC in the same areas, urban LBC tended to have higher prosocial behaviours scores, while rural LBC had the lowest prosocial behaviours scores not only in the whole age group but also in different age subgroups ( p  < 0.05). Besides, compared with urban LBC, rural LBC were not worse in SDQ subscales scores except for prosocial behaviour at 7–9 age group ( p  = 0.003). Furthermore, higher paternal educational level and longer duration of parental absence, were associated with less difficulties in both rural and urban LBC. Besides, shorter duration of talk per-time but higher communication frequency were associated with less difficulties in rural LBC. Conclusions The present study demonstrated that in general, no difference of mental health problems were found between LBC and NLBC. Besides, longer duration of parental absence, shorter duration of talk per time but more communication frequency, and higher paternal educational level tend to have better development of mental health. The findings reinforce the importance of the stability of caregivers and the effective parent-child communication for Chinese rural LBC.

Aiming at the pollution problem of methylene blue dye wastewater, a new type of methylene blue adsorbent magnesium-modified fly ash (Mg@FA) was prepared by using solid waste fly ash as raw material. The effects of Mg@FA dosage, adsorption time, and methylene blue concentration on the adsorption of methylene blue by Mg@FA and pH values were analyzed. The adsorption characteristics of Mg@FA on methylene blue were investigated by adsorption kinetics, adsorption isotherms, and adsorption thermodynamics, as well as SEM, EDS, XRD, BET, and FTIR. The results showed that when the dosage of Mg@FA was 1.0 g, the adsorption time was 120 min, and the initial concentration of methylene blue was 150 mg/L; the adsorption efficiency of methylene blue by Mg@FA was the highest, which was 95.61%. When the pH of the methylene blue solution was in the range of 7–11, the adsorption efficiency of Mg@FA for methylene blue remained stable at 95.61–98.10%. The adsorption process of methylene blue by Mg@FA follows the second-order kinetic fitting model and Langmuir model. The adsorption of methylene blue by Mg@FA is a spontaneous and endothermic reaction. Mg@FA adsorbs methylene blue through electrostatic interaction and hydrogen bonding. Mg@FA can effectively adsorb methylene blue and promote the waste utilization of fly ash, which provides a promising method for wastewater treatment and fly ash utilization.

Background Depression is a prevalent mental health problem in postmenopausal women. Given its significant impact on the quality of life and overall well-being of postmenopausal women, there is need for a comprehensive review and meta-analysis of the existing research globally. This systematic review and meta-analysis evaluated the global prevalence of depression and potential associated factors in postmenopausal women. Methods The Cochrane Library, PubMed, EMBASE, Web of Science, MEDLINE, and PsycINFO databases were systematically searched from inception to March 22, 2023. The meta-analysis used the random-effects model to calculate the prevalence of depression rates and associated factors. In addition, subgroup analysis and sensitivity analysis were performed. Publication bias was assessed using funnel plots, Egger’s test, and nonparametric trim-and-fill tests. Results The meta-analysis included 50 studies that involved 385,092 postmenopausal women. The prevalence of depression in postmenopausal women was 28.00% (95% CI, 25.80–30.10). Among the factors relevant to depression among postmenopausal women, marital status (OR: 2.03, 95%CI: 1.33–3.11), history of mental illness (OR: 2.31, 95%CI: 1.50–3.57), chronic disease (OR: 3.13, 95%CI: 2.20–4.44), menstrual cycle (OR: 1.42, 95%CI: 1.17–1.72), abortion numbers (OR: 1.59, 95%CI: 1.40–1.80), menopausal symptoms (OR: 2.10, 95%CI: 1.52–2.90), and hormone replacement therapy (OR: 1.76, 95%CI: 1.31–2.35) were risk factors, while physical activity (OR: 0.56, 95%CI: 0.53–0.59), number of breastfed infants (OR: 0.43, 95%CI: 0.19–0.97), menopause age (OR: 0.44, 95%CI: 0.37–0.51) were preventive factors. Conclusions This study demonstrated that the prevalence of postmenopausal depression is high, and some risk factors and protective factors associated with it have been identified. It is necessary to improve screening and management and optimize prevention and intervention strategies to reduce the harmful effects of postmenopausal depression.

To ensure the continuous high-efficiency operation of fuel cell systems, it is essential to perform real-time estimation of the maximum efficiency point and maximum power point for multi-stack fuel cell systems. The region between these two power points is commonly referred to as the \"high-efficiency operating region.\" Initially, a transformation of the general expression for hydrogen consumption in multi-stack fuel cell systems is conducted to obtain an algebraic expression for the efficiency curve of multi-stack fuel cells. Utilizing a polynomial differentiation approach, the parameter equation for the maximum system efficiency is computed. Subsequently, a reverse deduction is carried out using the maximum efficiency and its corresponding power of underperforming subsystems to enhance the maximum efficiency of multi-stack fuel cell systems.Furthermore, an equivalent hydrogen consumption minimization method is introduced for real-time optimization of hybrid energy systems. The state machine control method serves as an auxiliary strategy, imposing the high-efficiency operating region as a boundary constraint for the equivalent hydrogen consumption minimization strategy’s results. This ensures that the multi-stack fuel cell system operates as much as possible within the high-efficiency operating region.Through simulation validation using MATLAB/Simulink, the proposed approach comprehensively leverages the advantages of the state machine and equivalent hydrogen consumption. This approach enables effective identification of the high-efficiency operating region of fuel cells, while concurrently enhancing the operational range efficiency of the system, reducing hydrogen consumption, and elevating system stability.

Periodontitis is a chronic inflammatory disease caused by the local microbiome and the host immune response, resulting in periodontal structure damage and even tooth loss. Scaling and root planning combined with antibiotics are the conventional means of nonsurgical treatment of periodontitis, but they are insufficient to fully heal periodontitis due to intractable bacterial attachment and drug resistance. Novel and effective therapeutic options in clinical drug therapy remain scarce. Nanotherapeutics achieve stable cell targeting, oral retention and smart release by great flexibility in changing the chemical composition or physical characteristics of nanoparticles. Meanwhile, the protectiveness and high surface area to volume ratio of nanoparticles enable high drug loading, ensuring a remarkable therapeutic efficacy. Currently, the combination of advanced nanoparticles and novel therapeutic strategies is the most active research area in periodontitis treatment. In this review, we first introduce the pathogenesis of periodontitis, and then summarize the state-of-the-art nanotherapeutic strategies based on the triple concerto of antibacterial activity, immunomodulation and periodontium regeneration, particularly focusing on the therapeutic mechanism and ingenious design of nanomedicines. Finally, the challenges and prospects of nano therapy for periodontitis are discussed from the perspective of current treatment problems and future development trends. Graphical Abstract

Stem cell self-renewal often relies on asymmetric fate determination governed by niche signals and/or cell-intrinsic factors but how these regulatory mechanisms cooperate to promote asymmetric fate decision remains poorly understood. In adult Drosophila midgut, asymmetric Notch (N) signaling inhibits intestinal stem cell (ISC) self-renewal by promoting ISC differentiation into enteroblast (EB). We have previously shown that epithelium-derived Bone Morphogenetic Protein (BMP) promotes ISC self-renewal by antagonizing N pathway activity (Tian and Jiang, 2014). Here, we show that loss of BMP signaling results in ectopic N pathway activity even when the N ligand Delta (Dl) is depleted, and that the N inhibitor Numb acts in parallel with BMP signaling to ensure a robust ISC self-renewal program. Although Numb is asymmetrically segregated in about 80% of dividing ISCs, its activity is largely dispensable for ISC fate determination under normal homeostasis. However, Numb becomes crucial for ISC self-renewal when BMP signaling is compromised. Whereas neither Mad RNA interference nor its hypomorphic mutation led to ISC loss, inactivation of Numb in these backgrounds resulted in stem cell loss due to precocious ISC-to-EB differentiation. Furthermore, we find that numb mutations resulted in stem cell loss during midgut regeneration in response to epithelial damage that causes fluctuation in BMP pathway activity, suggesting that the asymmetrical segregation of Numb into the future ISC may provide a fail-save mechanism for ISC self-renewal by offsetting BMP pathway fluctuation, which is important for ISC maintenance in regenerative guts.

As the crucial component of the glioma microenvironment, tumor-associated macrophages (TAMs) significantly contribute to the immunosuppressive microenvironment and strongly influence glioma progression via various signaling molecules, simultaneously providing new insight into therapeutic strategies. Studies are aiming at developing prognostic models using N7-methylguanosine (m7G)-related genes in gliomas, however, models with good predictive performance for lower-grade gliomas have yet to be developed. Based on genes with m7G variants and clinical information, two prediction models have been derived to predict the probability of survival for patients with lower-grade gliomas in TCGA. The models were externally validated using independent datasets. Based on CGGA information, updated models that were created matched the features of the local population. Two models were derived, validated and updated. Model 1, which was derived on the basis of mRNA, only contains five genes: CD37, EIF3A, CALU, COLGALT1, and DDX3X . Model 2 included six variables: grade, age, gender, IDH mutation status, 1p/19q codeletion status and prognostic index of model 1. The C-statistic of revised model 1 was 0.764 (95% CI 0.730–0.798) in the revised set and 0.700 (95% CI 0.658–0.742) in the test set. Regarding internal validation, C-statistic for model 2 with 1000 bootstrap replications was 0.848, while in external validation, the C-statistic was 0.752 (95% CI 0.714–0.788). Both models exhibited satisfactory calibration after updating in external validation. The models’ web calculator is provided at https://lhj0520.shinyapps.io/M7G-LGG_model/ .

As energy and carbon markets evolve, it has emerged as a prevalent trend for multiple virtual power plants (VPPs) to engage in market trading through coordinated operation. Given that these VPPs belong to diverse stakeholders, a competitive dynamic is shaping up. To strike a balance between the interests of the distribution system operator (DSO) and VPPs, this paper introduces a bi-level energy–carbon coordination model based on the Stackelberg game framework, which consists of an upper-level optimal pricing model for the DSO and a lower-level optimal energy scheduling model for each VPP. Subsequently, the Karush-Kuhn-Tucker (KKT) conditions and the duality theorem of linear programming are applied to transform the bi-level Stackelberg game model into a mixed-integer linear program, allowing for the computation of the model’s global optimal solution using commercial solvers. Finally, a case study is conducted to demonstrate the effectiveness of the proposed model. The simulation results show that the proposed game model effectively optimizes energy and carbon pricing, encourages the active participation of VPPs in electricity and carbon allowance sharing, increases the profitability of DSOs, and reduces the operational costs of VPPs.