Per- and polyfluoroalkyl substances and human health outcomes: An umbrella review of systematic reviews with meta-analyses of observational studies.

BACKGROUND: Although evidence on the association between per- and polyfluoroalkyl substances (PFASs) and human health outcomes has grown exponentially, specific health outcomes and their potential associations with PFASs have not been conclusively evaluated. METHODS: We conducted a comprehensive search through the databases of PubMed, Embase, and Web of Science from inception to February 29, 2024, to identify systematic reviews with meta-analyses of observational studies examining the associations between the PFASs and multiple health outcomes. The quality of included studies was evaluated using the A Measurement Tool to Assess Systematic Reviews (AMSTAR) tool, and credibility of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) criteria. The protocol of this umbrella review (UR) had been registered in PROSPERO (CRD 42023480817). RESULTS: The UR identified 157 meta-analyses from 29 articles. Using the AMSTAR measurement tool, all articles were categorized as of moderate-to-high quality. Based on the GRADE assessment, significant associations between specific types of PFASs and low birth weight, tetanus vaccine response, and triglyceride levels showed high certainty of evidence. Moreover, moderate certainty of evidence with statistical significance was observed between PFASs and health outcomes including lower BMI z-score in infancy, poor sperm progressive motility, and decreased risk of preterm birth as well as preeclampsia. Fifty-two (33%) associations (e.g., PFASs and gestational hypertension, cardiovascular disease, etc) presented low certainty evidence. Additionally, eighty-five (55%) associations (e.g., PFASs with infertility, lipid metabolism, etc) presented very low certainty evidence. CONCLUSION: High certainty of evidence supported that certain PFASs were associated with the incidence of low birth weight, low efficiency of the tetanus vaccine, and low triglyceride levels.

SH3RF2 contributes to cisplatin resistance in ovarian cancer cells by promoting RBPMS degradation.

Platinum-based chemotherapy remains one of the major choices for treatment of ovarian cancer (OC). However, primary or acquired drug resistance severely impairs their efficiency, thereby causing chemotherapy failure and poor prognosis. SH3 domain containing ring finger 2 (SH3RF2) has been linked to the development of cancer. Here we find higher levels of SH3RF2 in the tumor tissues from cisplatin-resistant OC patients when compared to those from cisplatin-sensitive patients. Similarly, cisplatin-resistant OC cells also express higher levels of SH3RF2 than normal OC cells. Through in vitro and in vivo loss-of-function experiments, SH3RF2 is identified as a driver of cisplatin resistance, as evidenced by increases in cisplatin-induced cell apoptosis and DNA damage and decreases in cell proliferation induced by SH3RF2 depletion. Mechanistically, SH3RF2 can directly bind to the RNA-binding protein mRNA processing factor (RBPMS). RBPMS has been reported as an inhibitor of cisplatin resistance in OC. As a E3 ligase, SH3RF2 promotes the K48-linked ubiquitination of RBPMS to increase its proteasomal degradation and activator protein 1 (AP-1) transactivation. Impairments in RBPMS function reverse the inhibitory effect of SH3RF2 depletion on cisplatin resistance. Collectively, the SH3RF2-RBPMS-AP-1 axis is an important regulator in cisplatin resistance and inhibition of SH3RF2 may be a potential target in preventing cisplatin resistance.

Adherence to Sulfur Microbial Diet and Ovarian Cancer Survival: Evidence from a Prospective Cohort Study.

SCOPE: The study aims to investigate the role of the sulfur microbial diet in the survival of ovarian cancer (OC). METHODS AND RESULTS: A prospective cohort study is conducted with 703 patients diagnosed with OC between 2015 and 2020. Diet information is collected using a validated food frequency questionnaire. Deaths are ascertained up to March 31, 2021, via the death registry linkage. During the follow-up period (median: 37.2 months, interquartile range: 24.7-50.2 months), 130 deaths are observed. A higher sulfur microbial diet score is significantly associated with an increased risk of all-cause mortality among OC patients (tertile 3 vs tertile 1: HR = 1.93, 95% CI = 1.11-3.35). Each 1-standard deviation increment in the sulfur microbial diet score increases the all-cause mortality risk by 33% (95% CI = 1.04-1.71). Stratified analysis shows that significant associations are found in OC patients diagnosed over 50 years of age, with body mass index ≥24  kg m-2 , who changed their diet after diagnosis, or without residual lesions. CONCLUSIONS: Adherence to the sulfur microbial diet, characterized by high intakes of red meats and processed meats, and low intakes of fruits, vegetables, and whole grains, is associated with poor survival in OC patients.

Proteomic characterization of epithelial ovarian cancer delineates molecular signatures and therapeutic targets in distinct histological subtypes.

Clear cell carcinoma (CCC), endometrioid carcinoma (EC), and serous carcinoma (SC) are the major histological subtypes of epithelial ovarian cancer (EOC), whose differences in carcinogenesis are still unclear. Here, we undertake comprehensive proteomic profiling of 80 CCC, 79 EC, 80 SC, and 30 control samples. Our analysis reveals the prognostic or diagnostic value of dysregulated proteins and phosphorylation sites in important pathways. Moreover, protein co-expression network not only provides comprehensive view of biological features of each histological subtype, but also indicates potential prognostic biomarkers and progression landmarks. Notably, EOC have strong inter-tumor heterogeneity, with significantly different clinical characteristics, proteomic patterns and signaling pathway disorders in CCC, EC, and SC. Finally, we infer MPP7 protein as potential therapeutic target for SC, whose biological functions are confirmed in SC cells. Our proteomic cohort provides valuable resources for understanding molecular mechanisms and developing treatment strategies of distinct histological subtypes.

The performance of deep learning on thyroid nodule imaging predicts thyroid cancer: A systematic review and meta-analysis of epidemiological studies with independent external test sets.

BACKGROUND AND AIMS: It is still controversial whether deep learning (DL) systems add accuracy to thyroid nodule imaging classification based on the recent available evidence. We conducted this study to analyze the current evidence of DL in thyroid nodule imaging diagnosis in both internal and external test sets. METHODS: Until the end of December 2022, PubMed, IEEE, Embase, Web of Science, and the Cochrane Library were searched. We included primary epidemiological studies using externally validated DL techniques in image-based thyroid nodule appraisal. This systematic review was registered on PROSPERO (CRD42022362892). RESULTS: We evaluated evidence from 17 primary epidemiological studies using externally validated DL techniques in image-based thyroid nodule appraisal. Fourteen studies were deemed eligible for meta-analysis. The pooled sensitivity, specificity, and area under the curve (AUC) of these DL algorithms were 0.89 (95% confidence interval 0.87-0.90), 0.84 (0.82-0.86), and 0.93 (0.91-0.95), respectively. For the internal validation set, the pooled sensitivity, specificity, and AUC were 0.91 (0.89-0.93), 0.88 (0.85-0.91), and 0.96 (0.93-0.97), respectively. In the external validation set, the pooled sensitivity, specificity, and AUC were 0.87 (0.85-0.89), 0.81 (0.77-0.83), and 0.91 (0.88-0.93), respectively. Notably, in subgroup analyses, DL algorithms still demonstrated exceptional diagnostic validity. CONCLUSIONS: Current evidence suggests DL-based imaging shows diagnostic performances comparable to clinicians for differentiating thyroid nodules in both the internal and external test sets.

Association of pre-diagnosis specific color groups of fruit and vegetable intake with ovarian cancer survival: results from the ovarian cancer follow-up study (OOPS).

Background: The colors of fruits and vegetables (FV) reflect the presence of pigmented bioactive compounds. The evidence of pre-diagnosis specific FV color group intake contributing to ovarian cancer (OC) survival is limited and inconsistent. Methods: A prospective cohort study was conducted between 2015 and 2020 with 700 newly diagnosed OC patients. Pre-diagnosis dietary information was assessed by a validated food frequency questionnaire. We classified FV into five groups based on the color of their edible parts (e.g., green, red/purple, orange/yellow, white, and uncategorized groups). Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for the association of specific color groups of FV before diagnosis with OC survival. Potential multiplicative and additive interactions were assessed. Results: 130 patients died during a median follow-up of 37.57 (interquartile: 24.77-50.20) months. We observed the improved survival with a higher pre-diagnosis intake of total FV (HRtertile 3 vs. tertile 1 = 0.63, 95%CI = 0.40-0.99), total vegetables (HRtertile 3 vs. tertile 1 = 0.57, 95%CI = 0.36-0.90), and red/purple FV (HRtertile 3 vs. tertile 1 = 0.52, 95%CI = 0.33-0.82). In addition, we observed significant dose-response relationships for per standard deviation increment between total vegetable intake (HR = 0.79, 95%CI = 0.65-0.96) and red/purple group intake (HR = 0.77, 95%CI = 0.60-0.99) before diagnosis with OC survival. Additionally, pre-diagnosis green FV intake was borderline associated with better OC survival (HRper standard deviation increment = 0.83; 95%CI = 0.69-1.00). In contrast, we did not observe significant associations between pre-diagnosis intake of total fruits, orange/yellow, white, and uncategorized groups and OC survival. Conclusion: Pre-diagnosis FV intake from various color groups, especially the green and red/purple ones, may improve OC survival. Further studies are needed to validate our findings.

GRADE Use in Evidence Syntheses Published in High-Impact-Factor Gynecology and Obstetrics Journals: A Methodological Survey.

Objective: To identify and describe the certainty of evidence of gynecology and obstetrics systematic reviews (SRs) using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) approach. Method: Database searches of SRs using GRADE, published between 1 January 2016 to 31 December 2020, in the 10 "gynecology and obstetrics" journals with the highest impact factor, according to the Journal Citation Report 2019. Selected studies included those SRs using the GRADE approach, used to determine the certainty of evidence. Results: Out of 952 SRs, ninety-six SRs of randomized control trials (RCTs) and/or nonrandomized studies (NRSs) used GRADE. Sixty-seven SRs (7.04%) rated the certainty of evidence for specific outcomes. In total, we identified 946 certainty of evidence outcome ratings (n = 614 RCT ratings), ranging from very-low (42.28%) to low (28.44%), moderate (17.65%), and high (11.63%). High and very low certainty of evidence ratings accounted for 2.16% and 71.60% in the SRs of NRSs, respectively, compared with 16.78% and 26.55% in the SRs of RCTs. In the SRs of RCTs and NRSs, certainty of evidence was mainly downgraded due to imprecision and bias risks. Conclusions: More attention needs to be paid to strengthening GRADE acceptance and building knowledge of GRADE methods in gynecology and obstetrics evidence synthesis.

Association between pre-diagnostic dietary antioxidant vitamin consumption and ovarian cancer survival: a prospective cohort study.

Background: Epidemiological evidence regarding the relationship between dietary antioxidant vitamin intake and ovarian cancer (OC) survival is not clear. Herein, we aimed to first evaluate this topic in a prospective cohort study in China. Methods: The present study included participants from the Ovarian Cancer Follow-Up Study, which was a hospital-based prospective cohort study including OC patients who were aged 18 to 79 years during 2015-2020. The information on the intake of antioxidant vitamins, consisting of vitamin A, retinol, α-carotene, ß-carotene, vitamin C, and vitamin E, and other diet information was obtained through a 111-item food frequency questionnaire. Deaths were recorded until March 31, 2021. Hazard ratios (HRs) and 95% confidence intervals (CIs) for overall survival were evaluated using Cox proportional hazards models. Results: There were 130 (18.49%) deaths among 703 OC patients during a median 37.19 months follow-up. In the multivariable-adjusted model, the highest tertile of dietary vitamin C (HR = 0.43, 95% CI = 0.25-0.75, P for trend <0.05) and ß-carotene intake (HR = 0.52, 95% CI = 0.31-0.87, P for trend <0.05) was inversely associated with the overall survival of OC when compared with the lowest tertile group. Retinol, vitamin A, vitamin E, and α-carotene consumption showed no association with OC survival. Of note is that the multiplicative interaction was identified between vitamin C intake and residual lesions in OC survival (P for interaction <0.05). Conclusion: Our findings indicate that pre-diagnostic higher vitamin C and ß-carotene intake was associated with improved OC survival.

Artificial intelligence performance in image-based ovarian cancer identification: A systematic review and meta-analysis.

Background: Accurate identification of ovarian cancer (OC) is of paramount importance in clinical treatment success. Artificial intelligence (AI) is a potentially reliable assistant for the medical imaging recognition. We systematically review articles on the diagnostic performance of AI in OC from medical imaging for the first time. Methods: The Medline, Embase, IEEE, PubMed, Web of Science, and the Cochrane library databases were searched for related studies published until August 1, 2022. Inclusion criteria were studies that developed or used AI algorithms in the diagnosis of OC from medical images. The binary diagnostic accuracy data were extracted to derive the outcomes of interest: sensitivity (SE), specificity (SP), and Area Under the Curve (AUC). The study was registered with the PROSPERO, CRD42022324611. Findings: Thirty-four eligible studies were identified, of which twenty-eight studies were included in the meta-analysis with a pooled SE of 88% (95%CI: 85-90%), SP of 85% (82-88%), and AUC of 0.93 (0.91-0.95). Analysis for different algorithms revealed a pooled SE of 89% (85-92%) and SP of 88% (82-92%) for machine learning; and a pooled SE of 88% (84-91%) and SP of 84% (80-87%) for deep learning. Acceptable diagnostic performance was demonstrated in subgroup analyses stratified by imaging modalities (Ultrasound, Magnetic Resonance Imaging, or Computed Tomography), sample size (≤300 or >300), AI algorithms versus clinicians, year of publication (before or after 2020), geographical distribution (Asia or non Asia), and the different risk of bias levels (≥3 domain low risk or < 3 domain low risk). Interpretation: AI algorithms exhibited favorable performance for the diagnosis of OC through medical imaging. More rigorous reporting standards that address specific challenges of AI research could improve future studies. Funding: This work was supported by the Natural Science Foundation of China (No. 82073647 to Q-JW and No. 82103914 to T-TG), LiaoNing Revitalization Talents Program (No. XLYC1907102 to Q-JW), and 345 Talent Project of Shengjing Hospital of China Medical University (No. M0268 to Q-JW and No. M0952 to T-TG).

Association between dietary acid load and cancer risk and prognosis: An updated systematic review and meta-analysis of observational studies.

Epidemiological studies have suggested that dietary acid load (DAL) might be related to the risk and prognosis of cancer, whereas the evidence is contentious. Several high-quality observational studies have been published following a prior systematic review with only one study included. Consequently, we conducted an updated systematic review and meta-analysis to comprehensively investigate the relationship between DAL and cancer risk and prognosis. A systematic literature search was conducted in the PubMed, Embase, and Web of Science databases from inception to 26 October 2021. Summary relative risks (RRs) with 95% CIs were calculated using a random-effects model. Publication bias, subgroup, meta-regression, and sensitivity analyses were also conducted. Ten observational studies (six cohorts and four case-control studies) with 227,253 participants were included in this systematic review and meta-analysis. The summary RRs revealed a statistically significant associations between DAL and cancer risk (RR = 1.58, 95% CI = 1.23-2.05, I 2 = 71.9%, n = 7) and prognosis (RR = 1.53, 95% CI = 1.10-2.13, I 2 = 77.1%, n = 3). No evidence of publication bias was observed in the current analysis. Positive associations were observed in most subgroup analyses stratified by predefined factors, including region, study design, study quality, study population, participants' gender, age of participants, cancer type, DAL assessment indicator, and adjustment of potential confounding parameters. No evidence of heterogeneity between subgroups was indicated by meta-regression analyses. The high DAL might be associated with an increased risk of cancer, as well as a poor prognosis of cancer. More high-quality prospective studies are warranted to further determine the associations between DAL and risk and prognosis for specific cancers.

A Follow-Up Study of Ovarian Cancer (OOPS): A Study Protocol.

The ovarian cancer (OC) follow-up study (OOPS) is an on-going hospital-based large prospective longitudinal cohort study aimed to explore the relationship between pre/post-diagnostic biological, clinical, environmental, and lifestyle factors with focus on the diet and OC prognosis (including drug resistance, relapse, and mortality). Patients recruited during the baseline survey were between 18 and 79 years old, with histologically confirmed OC diagnosis. Their follow-up and medical treatment were conducted at the gynecological oncology ward at Shengjing Hospital of China Medical University, Shenyang, China after 2015. A total of 703 OC patients made up the final OOPS study population. The follow-up stage was conducted in both passive and active modes. In the passive mode, the follow-up was performed by linkage to the Liaoning Providence Center for Disease Control and Prevention every 6 months to obtain health outcome results. The status of lifestyle factors was re-estimated using the same measurements as those in the baseline survey. OC participants in the OOPS study completed a questionnaire and anthropometric examinations. In addition, biological specimens were collected during the baseline survey, which included blood, urine, and stool samples that were stored for further use. This article is intended to serve as an introduction to this project and to provide details for investigators who may be carry out related analysis.

Pre-diagnosis Dietary One-Carbon Metabolism Micronutrients Consumption and Ovarian Cancer Survival: A Prospective Cohort Study.

Background and Aims: Epidemiological evidence on the relation between one-carbon metabolism (OCM) micronutrients intake and ovarian cancer (OC) survival are limited and conflicting. We evaluated the aforementioned associations in a prospective cohort-the Ovarian Cancer Follow-Up Study. Methods: A total of 635 newly diagnosed OC patients aged 18-79 y were enrolled in the present study. Dietary intake related to one-carbon metabolism, including methionine, vitamins B2, B3, B6, B9, B12, choline, and betaine, was assessed using a validated 111-item food frequency questionnaire. Deaths were ascertained until March 31, 2021, via medical records and active follow-up. Cox proportional hazards regression model was used to evaluate the hazard ratios (HRs) and 95% confidence intervals (CIs) for these aforementioned associations. Results: During a median follow-up of 37.2 months (interquartile: 24.7-50.2 months), 114 deaths were identified. We observed an improved survival with the highest compared with the lowest tertile of dietary vitamin B6 (HR = 0.52, 95%CI: 0.32-0.84, P-trend <0.05) and choline intake (HR = 0.50, 95%CI: 0.30-0.83, P-trend <0.05). No significant associations with OC survival were observed for dietary vitamins B2, B3, B9, B12, methionine, and betaine intake. We also observed a curvilinear association between vitamin B6 intake and OC survival (P non-linear <0.05). Conclusion: Our study suggests that pre-diagnosis higher intake of vitamin B6 and choline may improve OC survival. Further clarification of these associations is warranted.

Association between pre-diagnostic dietary pattern and survival of ovarian cancer: Evidence from a prospective cohort study.

BACKGROUND: Evidence for a role of single nutrition or foods on ovarian cancer (OC) survival has been limited and inconclusive. Due to the potentially complex interactions in dietary, we applied dietary patterns to this study to firstly explore the relationship between the pre-diagnosis overall diet and OC survival. METHODS: The prospective cohort study was conducted among 853 OC patients aged 18-79 years during 2015-2020. Dietary intake was collected using a validated 111-item food frequency questionnaire. Deaths were obtained by medical records and cancer registry up to March 31, 2021. Cox proportional hazards regression models was used to evaluate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of pre-diagnosis dietary patterns with overall survival (OS). RESULTS: Overall, during the follow-up period (median: 37.57 months, interquartile: 25.00-50.17 months), 130 (18.49%) OC patients died. Four dietary patterns were identified: healthy pattern, ethnic pattern, animal foods pattern, and sweet pattern. The highest tertile of the healthy pattern scores was related to better OS compared with the lowest tertile scores (HR = 0.54, 95% CI = 0.30-0.98, p trend <0.05), whereas OC patients with highest adherence to the animal foods pattern was associated with worse OS than those with the lowest adherence (HR = 1.90, 95% CI = 1.14-3.17, p trend <0.05). We found no significant associations between adherence to ethnic pattern and sweet pattern and OS of OC patients. CONCLUSION: Pre-diagnosis healthy patterns was associated with better OC survival, whereas animal pattern was associated with worse survival among OC survivals.

Involvement of monoaminergic systems in the antidepressant-like effect of nobiletin.

Nobiletin isolated from citrus peels up-regulates synaptic transmission and improves memory impairment in rodents. This study investigated the antidepressant-like effect of nobiletin in the forced swimming test (FST) and tail suspension test (TST) in mice. Additionally, the monoaminergic mechanisms involved in the antidepressant-like effect of nobiletin in mice were also assessed. Nobiletin (25, 50 and 100mg/kg, p.o.) decreased the immobility time in both the FST and TST without locomotor alterations in the open-field test (OFT). The anti-immobility effect of nobiletin (50mg/kg, p.o.) was completely prevented by the pretreatment of mice with WAY 100635 (0.1mg/kg, s.c., a serotonin 5-HT(1A) receptor antagonist), cyproheptadine (3mg/kg, i.p., a serotonin 5-HT(2) receptor antagonist), prazosin (62.5µg/kg, i.p., an α(1)-adrenoceptor antagonist), SCH23390 (0.05mg/kg, s.c., a dopamine D(1) receptor antagonist) or sulpiride (50mg/kg, i.p., a dopamine D(2) receptor antagonist). On the other hand, the pretreatment of mice with yohimbine (1mg/kg, i.p., an α(2)-adrenoceptor antagonist) or propranolol (5mg/kg, i.p., a ß-adrenoceptor antagonist) did not block the antidepressant-like effect of nobiletin in the TST. Taken together, the data demonstrated that nobiletin produced an antidepressant-like effect that seems to be dependent on its interaction with the serotonergic, noradrenergic and dopaminergic systems. Thus, the present study suggests the therapeutic potential of this dietary flavonoid for the treatment of depression.