Chinese College Students' Stigmatization towards People with Mental Illness: Familiarity, Perceived Dangerousness, Fear, and Social Distance.

BACKGROUND: Attribution models have been examined in Western countries. However, little is known about the applicability of the attitude-emotion-behavior model within Chinese culture. This study aimed to examine the association between familiarity, perceived dangerousness, fear, and social distance towards persons with mental illness (PMI) in the Chinese context. METHODS: An online cross-sectional survey was conducted from October to November 2022 in mainland China. A total of 1493 college students completed a questionnaire evaluating familiarity, perception of dangerousness, fear, and social distance regarding PMI. Path analysis was employed to validate the model proposed in this study. RESULTS: Participants expressed moderate to high levels of stigma towards PMI. Familiarity was negatively associated with social distance (p < 0.01). Participants who perceived PMI as dangerous were more prone to exhibit a reaction of fear (p < 0.001), consequently leading to social distance (p < 0.01). However, the mediating effect of perceived dangerousness and fear on the relationship between familiarity and social distance was not significant (p > 0.05). CONCLUSIONS: The results of this study provide support for Corrigan's attributional model of stigma in the Chinese context. Contact-based interventions for stigma reduction should emphasize multiple elements of contact, including the quality of contact, rather than familiarity.

AFM-YOLOv8s: An Accurate, Fast, and Highly Robust Model for Detection of Sporangia of Plasmopara viticola with Various Morphological Variants.

Monitoring spores is crucial for predicting and preventing fungal- or oomycete-induced diseases like grapevine downy mildew. However, manual spore or sporangium detection using microscopes is time-consuming and labor-intensive, often resulting in low accuracy and slow processing speed. Emerging deep learning models like YOLOv8 aim to rapidly detect objects accurately but struggle with efficiency and accuracy when identifying various sporangia formations amidst complex backgrounds. To address these challenges, we developed an enhanced YOLOv8s, namely, AFM-YOLOv8s, by introducing an Adaptive Cross Fusion module, a lightweight feature extraction module FasterCSP (Faster Cross-Stage Partial Module), and a novel loss function MPDIoU (Minimum Point Distance Intersection over Union). AFM-YOLOv8s replaces the C2f module with FasterCSP, a more efficient feature extraction module, to reduce model parameter size and overall depth. In addition, we developed and integrated an Adaptive Cross Fusion Feature Pyramid Network to enhance the fusion of multiscale features within the YOLOv8 architecture. Last, we utilized the MPDIoU loss function to improve AFM-YOLOv8s' ability to locate bounding boxes and learn object spatial localization. Experimental results demonstrated AFM-YOLOv8s' effectiveness, achieving 91.3% accuracy (mean average precision at 50% IoU) on our custom grapevine downy mildew sporangium dataset-a notable improvement of 2.7% over the original YOLOv8 algorithm. FasterCSP reduced model complexity and size, enhanced deployment versatility, and improved real-time detection, chosen over C2f for easier integration despite minor accuracy trade-off. Currently, the AFM-YOLOv8s model is running as a backend algorithm in an open web application, providing valuable technical support for downy mildew prevention and control efforts and fungicide resistance studies.

Artificial intelligence in myopia in children: current trends and future directions.

PURPOSE OF REVIEW: Myopia is one of the major causes of visual impairment globally, with myopia and its complications thus placing a heavy healthcare and economic burden. With most cases of myopia developing during childhood, interventions to slow myopia progression are most effective when implemented early. To address this public health challenge, artificial intelligence has emerged as a potential solution in childhood myopia management. RECENT FINDINGS: The bulk of artificial intelligence research in childhood myopia was previously focused on traditional machine learning models for the identification of children at high risk for myopia progression. Recently, there has been a surge of literature with larger datasets, more computational power, and more complex computation models, leveraging artificial intelligence for novel approaches including large-scale myopia screening using big data, multimodal data, and advancing imaging technology for myopia progression, and deep learning models for precision treatment. SUMMARY: Artificial intelligence holds significant promise in transforming the field of childhood myopia management. Novel artificial intelligence modalities including automated machine learning, large language models, and federated learning could play an important role in the future by delivering precision medicine, improving health literacy, and allowing the preservation of data privacy. However, along with these advancements in technology come practical challenges including regulation and clinical integration.

Enhancing equity in cervical screening - initiatives to increase screening participation.

PURPOSE OF REVIEW: Cervical cancer can be eliminated as a public health problem through a three-pillar approach including high coverage of human papillomavirus (HPV) vaccination and HPV-based cervical screening, and treatment of precancers and invasive cancers. However, access inequities prevent many women and people with a cervix benefitting from these life-saving advances. This review focuses on evidence-based interventions that can improve equity and scale-up of cervical screening. RECENT FINDINGS: The transition from conventional cytology to HPV screening provides multiple opportunities to address equity and a multipronged approach can be used to identify priority groups, understand barriers and develop tailored solutions. There are proven financing mechanisms, tools, technologies and screening delivery methods to overcome screening barriers in different settings. This includes self-sampling interventions, point-of-care testing, health service integration, consumer-led co-design processes and digital screening registries. SUMMARY: To achieve cervical cancer elimination globally, cervical screening must be delivered in an inclusive, culturally safe and context-appropriate manner. There are multiple tools and strategies that can be implemented to improve participation of never- and under-screened groups, and to enhance equity in cervical screening.

Downregulation of SSR2 Enhances Hepatocellular Carcinoma Cisplatin Sensitivity via the Hippo Pathway.

BACKGROUND: Chemotherapy resistance is an obstacle to promoting the survival of patients with hepatocellular carcinoma (HCC). Thus, finding promising therapeutic targets to enhance HCC chemotherapy is necessary. METHODS: Signal sequence receptor subunit (SSR2) expression analysis was performed using quantitative real time polymerase chain reaction (qPCR) and Western blotting assays. Colony formation, apoptosis, anchorage-independent growth assay, and in vivo animal models were used to investigate the effect of SSR2 expression on the resistance of HCC cells to Cisplatin (DDP). Western blotting and luciferase reporter gene techniques were used to explore the molecular mechanism of SSR2 on the resistance of HCC cells to DDP. RESULTS: We found that the SSR2 is upregulated in HCC and associated with poor survival. Further analysis showed that the downregulation of SSR2 increased the sensitivity of HCC to DDP. Mechanically, SSR2 inhibited the Yes-associated protein (YAP) phosphorylation and promoted the transcription of Hippo signaling downstream genes. Finally, the Hippo pathway inhibitor can suppress colony formation and tumorigenesis arising from SSR2 upregulation. CONCLUSIONS: Our study shows that SSR2 is important in HCC progression via the Hippo pathway. Thus, targeting the SSR2/Hippo axis might be a potential strategy for overcoming HCC resistance to DDP.

Systematic investigation of BRCA1-A, -B, and -C complexes and their functions in DNA damage response and DNA repair.

BRCA1, a breast cancer susceptibility gene, has emerged as a central mediator that brings together multiple signaling complexes in response to DNA damage. The A, B, and C complexes of BRCA1, which are formed based on their phosphorylation-dependent interactions with the BRCA1-C-terminal domains, contribute to the roles of BRCA1 in DNA repair and cell cycle checkpoint control. However, their functions in DNA damage response remain to be fully appreciated. Specifically, there has been no systematic investigation of the roles of BRCA1-A, -B, and -C complexes in the regulation of BRCA1 localization and functions, in part because of cellular lethality associated with loss of CtIP protein, which is an essential component in BRCA1-C complex. To systematically investigate the functions of these complexes in DNA damage response, we depleted a key component in each of these complexes. We used the degradation tag system to inducibly deplete endogenous CtIP and obtained a series of RAP80/FANCJ/CtIP single-, double-, and triple-knockout cells. We showed that loss of BRCA1-B/FANCJ and BRCA1-C/CtIP, but not BRCA1-A/RAP80, resulted in reduced cell proliferation and increased sensitivity to DNA damage. BRCA1-C/CtIP and BRCA1-A/RAP80 were involved in BRCA1 recruitment to sites of DNA damage. However, BRCA1-A/RAP80 was not essential for damage-induced BRCA1 localization. Instead, RAP80/H2AX and CtIP have redundant roles in BRCA1 recruitment. Altogether, our systematic analysis uncovers functional differences between BRCA1-A, -B, and -C complexes and provides new insights into the roles of these BRCA1-associated protein complexes in DNA damage response and DNA repair.

Clinical study of chemotherapy-related cognitive impairment in patients with non-Hodgkin lymphoma.

BACKGROUND: Chemotherapy for malignant tumors can cause brain changes and cognitive impairment, leading to chemotherapy-induced cognitive impairment (CICI). Current research on CICI has focused on breast cancer and Hodgkin's lymphoma. Whether patients with non-Hodgkin's lymphoma (NHL) undergoing chemotherapy have cognitive impairment has not been fully investigated. AIM: To investigate whether NHL patients undergoing chemotherapy had cognitive impairments. METHODS: The study included 100 NHL patients who were required to complete a comprehensive psychological scale including the Brief Psychiatric Examination Scale (MMSE) at two time points: before chemotherapy and within 2 wk of two chemotherapy courses. A language proficiency test (VFT), Symbol Number Pattern Test (SDMT), Clock Drawing Test (CDT), Abbreviated Daily Cognition Scale (ECog-12), Prospective and Retrospective Memory Questionnaire, and Karnofsky Performance Status were used to assess cognitive changes before and after chemotherapy. RESULTS: The VFT scores for before treatment (BT) and after treatment (AT) groups were 45.20 ± 15.62, and 42.30 ± 17.53, respectively (t -2.16, P < 0.05). The CDT scores were 8 (3.5-9.25) for BT and 7 (2.5-9) for AT groups (Z -2.1, P < 0.05). Retrospective memory scores were 13.5 (9-17) for BT and 15 (13-18) for AT (Z -3.7, P < 0.01). The prospective memory scores were 12.63 ± 3.61 for BT and 14.43 ± 4.32 for AT groups (t -4.97, P < 0.01). The ECog-12 scores were 1.71 (1.25-2.08) for BT and 1.79 (1.42-2.08) for AT groups (Z -2.84, P < 0.01). The SDMT and MMSE values did not show a significant difference between BT and AT groups. CONCLUSION: Compared to the AT group, the BT group showed impaired language, memory, and subjective cognition, but objective cognition and execution were not significantly affected.

Interpretable Machine Learning-Based Risk Score for Predicting Ten-Year Corneal Graft Survival After Penetrating Keratoplasty and Deep Anterior Lamellar Keratoplasty in Asian Eyes.

PURPOSE: To predict 10-year graft survival after deep anterior lamellar keratoplasty (DALK) and penetrating keratoplasty (PK) using a machine learning (ML)-based interpretable risk score. METHODS: Singapore Corneal Transplant Registry patients (n = 1687) who underwent DALK (n = 524) or PK (n = 1163) for optical indications (excluding endothelial diseases) were followed up for 10 years. Variable importance scores from random survival forests were used to identify variables associated with graft survival. Parsimonious analysis using nested Cox models selected the top factors. An ML-based clinical score generator (AutoScore) converted identified variables into an interpretable risk score. Predictive performance was evaluated using Kaplan-Meier (KM) curves and time-integrated AUC (iAUC) on an independent testing set. RESULTS: Mean recipient age was 51.8 years, 54.1% were male, and majority were Chinese (60.0%). Surgical indications included corneal scar (46.5%), keratoconus (18.3%), and regraft (16.2%). Five-year and ten-year KM survival was 93.4% and 92.3% for DALK, compared with 67.6% and 56.6% for PK (log-rank P < 0.001). Five factors were identified by ML algorithm as predictors of 10-year graft survival: recipient sex, preoperative visual acuity, choice of procedure, surgical indication, and active inflammation. AutoScore stratified participants into low-risk and high-risk groups-with KM survival of 73.6% and 39.0%, respectively (log-rank P < 0.001). ML analysis outperformed traditional Cox regression in predicting graft survival beyond 5 years (iAUC 0.75 vs. 0.69). CONCLUSIONS: A combination of ML and traditional techniques identified factors associated with graft failure to derive a clinically interpretable risk score to stratify PK and DALK patients-a technique that may be replicated in other corneal transplant programs.

Enhancing practicality of deep learning for crop disease identification under field conditions: insights from model evaluation and crop-specific approaches.

BACKGROUND: Crop diseases can lead to significant yield losses and food shortages if not promptly identified and managed by farmers. With the advancements in convolutional neural networks (CNN) and the widespread availability of smartphones, automated and accurate identification of crop diseases has become feasible. However, although previous studies have achieved high accuracy (>95%) under laboratory conditions (Lab) using mixed data sets of multiple crops, these models often falter when deployed under field conditions (Field). In this study, we aimed to evaluate disease identification accuracy under Lab, Field, and Mixed (Lab and Field) conditions using an assembled data set encompassing 14 diseases of apple (Malus × domestica Borkh.), potato (Solanum tuberosum L.), and tomato (Solanum lycopersicum L.). In addition, we investigated the impact of model architectures, parameter sizes, and crop-specific models (CSMs) on accuracy, using DenseNets, ResNets, MobileNetV3, EfficientNet, and VGG Nets. RESULTS: Our results revealed a decrease in accuracy across all models from Lab (98.22%) to Mixed (91.76%) to Field (71.55%) conditions. Interestingly, disease classification accuracy showed minimal variation across model architectures and parameter sizes: Lab (97.61-98.76%), Mixed (90.76-92.31%), and Field (68.56-73.81%). Although CSMs were found to reduce inter-crop disease misclassifications, they also led to a slight increase in intra-crop misclassifications. CONCLUSION: Our findings underscore the importance of enriching data representation and volumes over employing new model architectures. Furthermore, the need for more field-specific images was highlighted. Ultimately, these insights contribute to the advancement of crop disease identification applications, facilitating their practical implementation in farmer's fields. © 2024 Society of Chemical Industry.

Sideroflexin-1 promotes progression and sensitivity to lapatinib in triple-negative breast cancer by inhibiting TOLLIP-mediated autophagic degradation of CIP2A.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer and it lacks specific therapeutic targets and effective treatment protocols. By analyzing a proteomic TNBC dataset, we found significant upregulation of sideroflexin 1 (SFXN1) in tumor tissues. However, the precise function of SFXN1 in TNBC remains unclear. Immunoblotting was performed to determine SFXN1 expression levels. Label-free quantitative proteomics and liquid chromatography-tandem mass spectrometry were used to identify the downstream targets of SFXN1. Mechanistic studies of SFXN1 and cellular inhibitor of PP2A (CIP2A) were performed using immunoblotting, immunofluorescence staining, and reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Functional experiments were used to investigate the role of SFXN1 in TNBC cells. SFXN1 was significantly overexpressed in TNBC tumor tissues and was associated with unfavorable outcomes in patients with TNBC. Functional experiments demonstrated that SFXN1 promoted TNBC growth and metastasis in vitro and in vivo. Mechanistic studies revealed that SFXN1 promoted TNBC progression by inhibiting the autophagy receptor TOLLIP (toll interacting protein)-mediated autophagic degradation of CIP2A. The pro-tumorigenic effect of SFXN1 overexpression was partially prevented by lapatinib-mediated inhibition of the CIP2A/PP2A/p-AKT pathway. These findings may provide a new targeted therapy for patients with TNBC.

Pipelle Endometrial Sampling With a Full Bladder Compared With Standard Care: A Randomized Controlled Trial.

OBJECTIVE: To compare insertion failure rates for Pipelle endometrial sampling with a full bladder compared with the standard process (not taking into account bladder status) without cervical manipulation. METHODS: A single-masked randomized trial was conducted in a single tertiary care center from July 2021 to January 2022. Two hundred fourteen participants aged 18 years or older who were scheduled for outpatient Pipelle endometrial sampling were randomized: 107 each to having a full bladder (by oral water intake) or standard process (without delayed sampling and bladder status not taken into account). Women with known cervical stenosis, gynecologic malignancy, uterine anomalies, leiomyoma distorting the uterine cavity, acute cervicitis, urge bladder dysfunction, intense anxiety, need for anesthesia or analgesic before the procedure, positive pregnancy test, or previous failed office endometrial sampling were excluded. The primary outcome was the insertion failure rate of endometrial sampling at first attempt. Secondary outcomes were pain during procedure, satisfaction score, analgesia use, procedure duration, and need for cervical manipulation. Factoring in a baseline insertion failure rate of 30.0%, relative risk of 0.45, α of 0.05, 80.0% power, and a dropout rate of 10.0%, we needed 107 participants in each arm. RESULTS: The insertion failure rate was significantly lower in the full bladder group compared with standard process: 25 of 107 (23.4%) compared with 45 of 107 (42.1%) (relative risk 0.56, 95% CI, 0.37-0.84; number needed to treat to benefit 6.0, 95% CI, 3.20-15.70). Pain score (median) during the procedure (interquartile range) was 4 (3-6) compared with 5 (3-8) ( P =.004); patient satisfaction score was 8 (7-9) compared with 7 (4-8) ( P <.001); and mean±SD procedure duration was 3.0±2.4 compared with 4.7±2.9 minutes ( P <.001) for the full bladder and standard process arm, respectively. Other secondary outcomes of cervical laceration, analgesia use, and adequacy of endometrial tissue for histopathologic assessment were not significantly different between groups. CONCLUSION: Pipelle endometrial sampling with a full bladder reduces the initial insertion failure rate, procedure-related pain, and duration of sampling and increases patient satisfaction compared with the standard process. CLINICAL TRIAL REGISTRATION: ISRCTN, ISRCTN33938192.

The DRAP1/DR1 Repressor Complex Increases mTOR Activity to Promote Progression and Confer Everolimus Sensitivity in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is the most aggressive subtype of breast cancer. Transcriptional dysregulation is a hallmark of cancer, and several transcriptional regulators have been demonstrated to contribute to cancer progression. In this study, we identified an upregulation of the transcriptional corepressor downregulator of transcription 1-associated protein 1 (DRAP1) in TNBC, which was closely associated with poor recurrence-free survival in patients with TNBC. DRAP1 promoted TNBC proliferation, migration, and invasion in vitro and tumor growth and metastasis in vivo. Mechanistically, the downregulator of transcription 1 (DR1)/DRAP1 heterodimer complex inhibited expression of the cytosolic arginine sensor for mTORC1 subunit 1 (CASTOR1) and thereby increased activation of mTOR, which sensitized TNBC to treatment with the mTOR inhibitor everolimus. DRAP1 and DR1 also formed a positive feedback loop. DRAP1 enhanced the stability of DR1 by recruiting the deubiquitinase USP7 to inhibit its proteasomal degradation; in turn, DR1 directly promoted DRAP1 transcription. Collectively, this study uncovered a DRAP1-DR1 bidirectional regulatory pathway that promotes TNBC progression, suggesting that targeting the DRAP1/DR1 complex might be a potential therapeutic strategy to treat TNBC. Significance: DR1 and DRAP1 form a positive feedback loop and a repressor complex to cooperatively inhibit cytosolic arginine sensor for mTORC1 subunit 1 transcription and stimulate mTOR signaling, leading to progression and increased everolimus sensitivity in triple-negative breast cancer.

Patient preference and acceptability of self-sampling for cervical screening in colposcopy clinic attenders: A cross-sectional semi-structured survey.

Low vaginal self-sampling has been pioneered as an important development to improve uptake of cervical screening globally. Limited research is available in specific patient groups in the UK exploring views around self-sampling to detect high-risk human papillomavirus (hrHPV) DNA. Therefore, we explored patient views to support development of a novel point-of-care self-sampling cervical cancer screening device, by undertaking a cross-sectional semi-structured questionnaire survey to explore preferences, acceptability, barriers and facilitators around self-sampling. Patients attending a colposcopy clinic, 25-64 years old, were invited to participate after having carried out a low vaginal self-sample using a regular flocked swab. Participants self-completed an anonymous 12-point questionnaire. Quantitative data were analysed in MS Excel and Graphpad Prism, and qualitative data with Nvivo. We recruited 274 patients with a questionnaire response rate of 76%. Acceptability of self-sampling was high (95%, n = 187/197; Cronbachs-α = 0.778). Participants were asked their choice of future screening method: a) low vaginal self-sampling, b) healthcare professional collected vaginal swab, c) cervical brush sample with healthcare professional speculum examination, or d) no preference. Preferences were: a) 37% (n = 74/198), b) 19% (n = 37/198); c) 9% (n = 17/198), and d) 35% (n = 70/198), showing no single option as a strong preference. Key motivators were: Test simplicity (90%, n = 170/190), speed (81%, n = 153/190) and less pain (65%, n = 123/190). Barriers included lack of confidence taking the sample (53%, n = 10/19), resulting in preference for a healthcare professional sample (47%, n = 9/19). Whilst self-sampling showed high acceptability, lack of strong preference for screening method may reflect that respondents attending colposcopy are already engaged with screening and have differing perception of cervical cancer risk. This group appear less likely to 'switch' to self-sampling, and it may be better targeted within primary and community care, focusing on under-screened populations. Any shift in this paradigm in the UK requires comprehensive education and support for patients and providers.

Contrast Volume-to-Estimated Glomerular Filtration Rate Ratio as a Predictor of Short-Term Outcomes Following Transcatheter Aortic Valve Implantation.

Background/Objectives: Contrast-induced acute kidney injury (AKI) is associated with early mortality and adverse events. However, in the setting of transcatheter aortic valve implantation (TAVI), previous literature has failed to establish a correlation between the absolute volume of contrast media administered and mortality. We aimed to investigate the impact of contrast volume administered normalised to estimated glomerular filtration rate (CV/eGFR) on the development of AKI and on 30-day all-cause mortality in TAVI patients. Methods: We retrospectively analysed a cohort of 1150 patients who underwent TAVI at our unit between 2015 and 2018. Results: Follow-up was complete for 1064 patients. There were 23 deaths within the follow-up period and 76 cases of AKI, 9 of which required new renal replacement therapy (RRT). Receiver-operating characteristic (ROC) curve analysis showed fair discrimination for 30-day all-cause mortality at a CV/eGFR ratio of 3.6 (area under the ROC curve (AUC) 0.671). Of patients in whom CV data were available, 86.0% (n = 757) had a CV/eGFR < 3.6 and 14.0% (n = 123) had a CV/eGFR ≥ 3.6. In multivariate logistic regression analysis, CV/eGFR ≥ 3.6 was the strongest predictor of 30-day all-cause mortality (odds ratio 5.06, 95% confidence interval [1.61-15.7], p = 0.004). Other independent predictors were procedural urgency (3.28 [1.04-10.3], p = 0.038) and being under general anaesthesia (4.81 [1.10-17.3], p = 0.023). CV/eGFR ≥ 3.6 was also independently associated with significantly increased odds of AKI (2.28 [1.20-4.17], p = 0.009) alongside significant non-left main stem coronary artery disease (2.56 [1.45-4.66], p = 0.001), and diabetes (1.82 [1.03-3.19], p = 0.037). In supplementary ROC curve analysis, a similar CV/eGFR cut point of 3.6 was found to be an excellent predictor for new RRT (AUC 0.833). Conclusions: In conclusion, a CV/eGFR ≥ 3.6 post-TAVI was found to be a strong predictor of 30-day mortality and AKI. The maximum contrast volume that can be safely administered in each patient without significantly increasing the risk of mortality and AKI can be calculated using this ratio.

Characterizing the mechanism of action for mRNA therapeutics for the treatment of propionic acidemia, methylmalonic acidemia, and phenylketonuria.

Messenger RNA (mRNA) therapeutics delivered via lipid nanoparticles hold the potential to treat metabolic diseases caused by protein deficiency, including propionic acidemia (PA), methylmalonic acidemia (MMA), and phenylketonuria (PKU). Herein we report results from multiple independent preclinical studies of mRNA-3927 (an investigational treatment for PA), mRNA-3705 (an investigational treatment for MMA), and mRNA-3210 (an investigational treatment for PKU) in murine models of each disease. All 3 mRNA therapeutics exhibited pharmacokinetic/pharmacodynamic (PK/PD) responses in their respective murine model by driving mRNA, protein, and/or protein activity responses, as well as by decreasing levels of the relevant biomarker(s) when compared to control-treated animals. These preclinical data were then used to develop translational PK/PD models, which were scaled allometrically to humans to predict starting doses for first-in-human clinical studies for each disease. The predicted first-in-human doses for mRNA-3927, mRNA-3705, and mRNA-3210 were determined to be 0.3, 0.1, and 0.4 mg/kg, respectively.

The every woman study™ low- and middle-income countries edition protocol: A multi-country observational study to assess opportunities and challenges to improving survival and quality of life for women with ovarian cancer.

BACKGROUND: Ovarian cancer is a challenging disease to diagnose and treat effectively with five-year survival rates below 50%. Previous patient experience research in high-income countries highlighted common challenges and opportunities to improve survival and quality of life for women affected by ovarian cancer. However, no comparable data exist for low-and middle-income countries, where 70% of women with the disease live. This study aims to address this evidence gap. METHODS: This is an observational multi-country study set in low- and middle-income countries. We aim to recruit over 2000 women diagnosed with ovarian cancer across multiple hospitals in 24 countries in Asia, Africa and South America. Country sample sizes have been calculated (n = 70-96 participants /country), taking account of varying national five-year disease prevalence rates. Women within five years of their diagnosis, who are in contact with participating hospitals, are invited to take part in the study. A questionnaire has been adapted from a tool previously used in high-income countries. It comprises 57 multiple choice and two open-ended questions designed to collect information on demographics, women's knowledge of ovarian cancer, route to diagnosis, access to treatments, surgery and genetic testing, support needs, the impact of the disease on women and their families, and their priorities for action. The questionnaire has been designed in English, translated into local languages and tested according to local ethics requirements. Questionnaires will be administered by a trained member of the clinical team. CONCLUSION: This study will inform further research, advocacy, and action in low- and middle-income countries based on tailored approaches to the national, regional and global challenges and opportunities. In addition, participating countries can choose to repeat the study to track progress and the protocol can be adapted for other countries and other diseases.

Deciphering the pathogenic risks of microplastics as emerging particulate organic matter in aquatic ecosystem.

Microplastics are accumulating rapidly in aquatic ecosystems, providing habitats for pathogens and vectors for antibiotic resistance genes (ARGs), potentially increasing pathogenic risks. However, few studies have considered microplastics as particulate organic matter (POM) to elucidate their pathogenic risks and underlying mechanisms. Here, we performed microcosm experiments with microplastics and natural POM (leaves, algae, soil), thoroughly investigating their distinct effects on the community compositions, functional profiles, opportunistic pathogens, and ARGs in Particle-Associated (PA) and Free-Living (FL) bacterial communities. We found that both microplastics and leaves have comparable impacts on microbial community structures and functions, enriching opportunistic pathogens and ARGs, which may pose potential environmental risks. These effects are likely driven by their influences on water properties, including dissolved organic carbon, nitrate, DO, and pH. However, microplastics uniquely promoted pathogens as keystone species and further amplified their capacity as hosts for ARGs, potentially posing a higher pathogenic risk than natural POM. Our research also emphasized the importance of considering both PA and FL bacteria when assessing microplastic impacts, as they exhibited different responses. Overall, our study elucidates the role and underlying mechanism of microplastics as an emerging POM in intensifying pathogenic risks of aquatic ecosystems in comparison with conventional natural POM.