Fuzuloparib with or without apatinib in patients with HER2-negative metastatic breast cancer with germline BRCA1/2 mutations (FABULOUS): interim analysis of a multicentre, three-arm, open-label, randomised, phase 3 trial.

A subset of Plasmodium falciparum RIFINs is linked to severe malaria risk reduction and engages LILRB1 through a conserved structural motif.

The Human Development Index (HDI) introduced by United Nations Development Programme (UNDP) offers a unique quantitative measure that encompasses advancements in three fundamental aspects of human development: health, education, and living standards. However, focusing on only three dimensions when evaluating human development performance of countries is not adequate in today’s digital world. This study proposes a data envelopment analysis (DEA)-based composite index to provide an innovation-integrated human development performance assessment tool for countries. The novel two-stage common-weight DEA-based approach proposed in here is applied in a case study examining the performance assessment of European Union (EU) countries. The first stage of the developed methodology consists of solving the novel commonweight DEA-based approach with HDI indicators as the outputs and the Gini coefficient as the input. At the second stage, innovation-based indicators from World Bank database are used to evaluate innovation efficiency of EU countries. The composite index that yields the complete ranking of EU countries in terms of innovation-integrated human development performance is computed as the product of the efficiency scores resulting from these two stages. The rankings produced by the proposed approach are compared with the HDI rankings as well as the results obtained from various common-weight DEA-based models.

This article is devoted to the characteristics of the development of Iran’s science, technology, and innovation ecosystem. In the context of global technological competition and the emergence of a new technological paradigm, studying the development strategies of countries striving for scientific and technological sovereignty has become particularly important. Iran is one of the most illustrative examples of such a strategy: for over four decades, the country has been building its own science and technology ecosystem amid international isolation. Examining Iran’s experience provides insight into the mechanisms by which its ecosystem has adapted to external constraints. The article is divided into three sections. The first part examines legal and strategic documents to determine priorities in the development of science, technology and innovation ecosystem. The second part analyzes its system of management. The third part examines the characteristics of Iran’s science and technology ecosystem. Based on data from the Scopus database, the publication priorities of Iranian researchers are identified, and an attempt is made to assess the extent to which national science and technology development programs reflect the actual state of affairs. The article concludes that, despite significant external constraints, Iran has achieved notable progress in the field of science and technology. The outcomes of this progress, as reflected in scientific publications, largely align with the priorities outlined in the country’s strategic policy documents.

We develop spectral volume models to systematically estimate, explain, and exploit the high-frequency periodicity in intraday trading activities using Fourier analysis. The framework consistently recovers periodicities at specific frequencies in three steps, despite their low signal-to-noise ratios. This reveals persistent and universal high-frequency periodicities in the United States and Chinese stock markets in recent years, and the dominant frequencies explain a significant fraction of the total variance of intraday volumes. We provide evidence that this phenomenon likely reflects the behaviors of trading algorithms with repeated and regular trading instructions. Finally, we demonstrate that uncovering such high-frequency periodicities improves intraday volume predictions and volume weighted average price execution qualities, yields insights for price informativeness of algorithmic trading, and generates excess returns. This paper was accepted by William Lin Cong, finance. Funding: This work was supported by the National Key Research and Development Program of China [Grant 2022YFA1007900], the National Natural Science Foundation of China [Grants 12271013 and 72342004], and the Peking University’s Fundamental Research Funds for the Central Universities. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.06215 .

Building on the hypothesis that a country's governance quality is crucial for sustainable development, we examined the human development implications of good governance in Nigeria, focusing on the United Nations Development Programme (UNDP) Human Development Index (HDI). We measured good governance using key World Bank Worldwide Governance Indicators (WGIs), including government effectiveness, regulatory quality, rule of law, and control of corruption. Data for the variables were sourced from the World Bank and the UNDP Human Development Report. The datasets were analysed using the least squares estimation method, descriptive statistics, and pre-estimation and diagnostic tests. The findings revealed that government effectiveness has a positive, significant impact on HDI in the short term, suggesting that improving government effectiveness is associated with immediate improvements in human development. Similarly, the regulatory quality index has a significantly positive impact on HDI, indicating that improvements in regulatory quality are associated with potential rather than immediate gains in HDI. However, there is evidence of a long-term positive effect of the rule of law on HDI, suggesting that improvements in legal frameworks, judicial independence, contract enforcement, and property rights significantly enhance human development outcomes in Nigeria. Conversely, corruption control has a negative impact on HDI, highlighting the ineffectiveness of anti-corruption strategies in promoting human development outcomes in Nigeria. Given the findings, this study recommends, among other things, that the government should prioritise institutional reforms to improve the quality of public service delivery, particularly in health, education, and living standards, to foster human development in Nigeria.

This study aims to analyze the influence of tourist arrivals, tourism receipts, trade openness, and education on poverty levels in the ASEAN-5 between 2000 and 2023. Poverty levels in the ASEAN-5 countries (Indonesia, Malaysia, the Philippines, Thailand, and Vietnam) remain a significant challenge despite the region's significant economic potential, particularly in the tourism and trade sectors. The analysis was conducted using secondary data from the World Bank and United Nations Development Programme and processed using E-Views 12. The results indicate that tourist arrivals have a positive and significant effect on poverty, while tourism receipts and trade openness have a negative and significant effect. These findings emphasize the importance of equitable distribution of economic benefits for these sectors to truly impact poverty alleviation. Furthermore, mean years of schooling were also found to have a negative and not significant effect on poverty, underscoring the role of education in improving the quality of human resources. This study provides policy recommendations to maximize the potential of tourism and trade in an inclusive and sustainable manner to reduce poverty in the ASEAN-5 region.

Abstract Over the last few decades, considerable attention has been directed towards formative assessment as a means of enhancing educational institutions. However, in Italy, this form of assessment has received comparatively little attention from researchers and has been identified as an underdeveloped educational practice when viewed in the context of other national school systems. Despite the recent reform in primary schools, which made formative assessment mandatory, it appears that the longstanding gap between educational research and policy has not been fully addressed, thus limiting the potential for transforming teacher assessment practices. The passage, in 2020, of the last school reform in this school system dramatically changed the assessment practices teachers are expected to enact in the classroom. More specifically, teachers switched from summative assessment, which had been extensively used for decades, to formative assessment. In light of growing concerns about teacher assessment literacy and the increased focus on formative assessment within this school system, a phenomenological interview study was conducted to examine how Italian teachers understand and implement formative assessment, in the context of the national professional development programme they attended. Three rounds of interviews were performed with 10 expert teachers. Interpretative Phenomenological Analysis (IPA) revealed an unclear conceptual understanding of the theory and practice of formative assessment. While the interviewees reported difficulties in putting the ambiguous policy requirements into practice, they also emphasised that the professional development programme offered little help. Finally, implications for research and practice in supporting teacher assessment literacy are discussed.

Risk-stratified classification of pulmonary nodule malignancy via a machine learning model integrating imaging and cell-free DNA: a model development and validation study (DECIPHER-NODL)

How can integrating updated single-cell transcriptomics and protein-protein interactions (PPIs) with machine learning algorithms improve gene prioritization for spermatogenic failure and predict ICSI outcomes? A machine learning framework integrating single-cell RNA sequencing (scRNA-seq) and PPI networks efficiently identified 320 candidate genes for spermatogenic failure and achieved high precision in predicting ICSI outcomes (precision-recall (PRC)-AUC=0.96, 95% CI: 0.89-1.00; receiver operating characteristic (ROC)-AUC = 0.82, 95% CI: 0.63-0.97). Over 100 genes are implicated in spermatogenic failure, yet patients with distinct genetic backgrounds exhibit highly variable ICSI outcomes. While machine learning-based gene prioritization offers potential for novel gene discovery, the existing methods rely on bulk RNA sequencing or lack multi-omics integration, limiting their ability to leverage single-cell resolution or predict clinical outcomes. This study combined scRNA-seq data (capturing cell type- and developmental stage-specific expression) from healthy human tissues with PPI networks to train predictive models. Validation included 5-fold cross-validation, functional enrichment analyses, and clinical data from whole-exome sequencing (WES) and ICSI outcomes in 34 patients with spermatogenic failure subtypes (azoospermia, asthenozoospermia, teratozoospermia). Public datasets (Human Protein Atlas, STRING, Gene Expression Omnibus) provided scRNA-seq and PPI data. Node2Vec-derived PPI network embeddings and cell type- and developmental stage-specific expression features were used to train random forest classifiers. Gene Ontology, Mammalian Phenotype Ontology enrichment analyses, and WES of patient blood samples validated candidate genes and ICSI outcomes. Our models demonstrated robust performance in spermatogenic failure gene prediction (PRC-AUC = 0.88, 95% CI: 0.83-0.93; ROC-AUC = 0.98, 95% CI: 0.96-0.99), subtype classification (e.g. teratozoospermia, PRC-AUC = 0.96, 95% CI: 0.91-0.99; ROC-AUC = 0.94, 95% CI: 0.87-0.98), and ICSI outcome prediction (PRC-AUC = 0.96, 95% CI: 0.89-1.00; ROC-AUC = 0.82, 95% CI: 0.63-0.97). WES of patient samples revealed an increased detection rate of likely causative variants among a subset of model-predicted genes, rising from 11.8% to 29.4%, with clinical outcomes aligning with model predictions. Model limitations include training on literature-curated or database-annotated gene labels, which may introduce misclassification or annotation bias. Additionally, the absence of experimental validation and the limited size and diversity of external cohorts necessitate further verification. This integrative machine learning framework provides a powerful tool for uncovering genetic contributors to male infertility and predicting treatment outcomes, paving the way for improved diagnostic strategies and more informed clinical decision-making in reproductive medicine. This work was supported by the National Natural Science Foundation of China (32370719, 32170667), the Shanghai Municipal Science and Technology Major Project (2017SHZDZX01), and the National Key Research and Development Program of China (2021YFC2301503). The authors declare no competing interests. N/A.

MHC-II-restricted neoantigen vaccine reverses immune microenvironment and overcomes resistance to immune-checkpoint inhibitors in cold tumors.

Macrolide-resistant Mycoplasma pneumoniae resurgence in Chinese children in 2023: a longitudinal, cross-sectional, genomic epidemiology study.

EndoUSScan: Keyframe detection in transvaginal ultrasound imaging for measuring endometrial thickness.

Efficacy and safety of ARX788 for individuals with HER2-positive breast cancer and brain metastases (ACE-Breast-06): a single-arm, phase 2 trial in China

Introduction The United Nations Development Programme has been instrumental in promoting the generation of productive activities that respond to a sustainable production model. In this regard, small-scale aquaculture merits particular attention for its demonstrated propensity towards sustainability. The present study analyses the levels of multidimensional sustainability through a case study of a small-scale aquaculture system, utilising a measurement system with indicators. Materials and methods Information was collected through the application of a measurement instrument during visits to oyster and shrimp farms. The evaluation process involved the analysis of 36 indicators, which were distributed across 12 sustainability variables. These variables addressed the technical, economic, social, environmental and governance dimensions. The results were analysed separately by species, and the sustainability trends presented were also evaluated. Results The findings indicate that both productive species demonstrate comparable levels of sustainability, exhibiting distinctions across the various dimensions. In terms of both social and economic dimensions, oyster production is the most significant. Conversely, in technical and governance dimensions, shrimp production is the most important. The study revealed discrepancies in the levels of sustainability, which varied according to geographic sector and the organisational structure of the farm. It has been demonstrated that larger farms tend to exhibit a greater degree of sustainability, characterised by extended production times and a family-oriented organisational structure. Discussion The analysis of the results addresses the contrasts in the levels of sustainability of shrimp and oyster production in the Gulf of Nicoya, and compares them with similar experiences in other latitudes. It delves into areas of opportunity in the region, such as technification, circular economy and good governance, through the presentation of success stories in other small-scale aquaculture systems around the world. It concludes that the priority areas for management in the region are strengthening the management and planning structure, cohesion and coordination of producer, circular economy model, and designing a specific sustainability index.

This article is based on the development and implementation of a climate budget labeling model for Uzbekistan with the support of the United Nations Development Program. The history of the economic approach to the concept of sustainable development is covered. A forecast of funds provided for 2024 for the section of “green” budgeting sectors is given

Women’s involvement in the fisheries and aquaculture sector remains invisible and undervalued, and women have been relatively excluded from national development policies and programs. The neglect of post-harvesting activities and the exclusion of women from research and policy have created gender inequities and differential impacts on men and women – often to women’s detriment. Failure to account for sex, gender and other social factors in fisheries and aquaculture research furthermore results in weak science and, often, policy failure. While much progress has been made in documenting women’s roles in aquatic food systems, broadening and deepening the scope of theoretically informed gender analysis in fisheries and aquaculture research is not only necessary for achieving social equity in the sector, it is critical for the development of robust fisheries and aquaculture science. This essay delineates several concepts and presents a framework for gender analysis that will strengthen fisheries and aquaculture science and may support transformational change toward gender equity in aquatic food systems.

We analyze the optimal boundary for open data in an economy where financial and real-sector participants access both open and private data. The distinctive features of open access and nonrivalrous usage of open data enable its dual roles as a public information source and innovation input but raise privacy concerns. Our model reveals a novel tradeoff: Although enhanced private data precision and data skills substitute for open data’s information source role, its ability to amplify innovation benefits (via improved investment efficiency) establishes a crucial complementary relationship. This induces a crowding-in effect on the optimal open data boundary under low uncertainty but a crowding-out effect under high uncertainty. The innovation role of open data further generates nonmonotonic effects, yielding complex nonlinear impacts on market and real efficiency. These findings highlight critical policy tradeoffs in balancing innovation, market efficiency, and privacy in the digital age. This paper was accepted by Bo Becker, finance. Funding: Z. Wang acknowledges financing from the National Natural Science Foundation of China [Grants 72442025 and 72272028] and the Graduate Education Reform of Dongbei University of Finance and Economics [Grant yjzd202309]. Z. Qiu acknowledges financing from the Major Program of the National Natural Science Foundation of China [Grant 72192804] and the National Key Research and Development Program of China [Grant 2023YFC3304701]. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2023.03679 .

BackgroundDental caries is a preventable non-communicable disease. Untreated caries in deciduous teeth may contribute to the development of caries in permanent teeth. Nevertheless, limited research has focused specifically on the risk factors in children. The current study examined the association between dental caries and socioeconomic risk factors among children aged 5–14 years across countries worldwide.MethodsAn ecological survey was conducted using nation-based, publicly available online databases from six reputable organizations: the World Health Organization, the Food and Agriculture Organization of the United Nations, the World Bank, the British Fluoridation Society, the United Nations Development Programme, and the Global Burden of Disease Project. Data were collected from these sources between 2014 and 2017. Independent variables included density of dental personnel, parental education, family income, water fluoridation, and sugar consumption. The dependent variables were the prevalence of caries in deciduous and permanent teeth. Data were analyzed using descriptive statistics, univariate analysis, and multinomial logistic regression.ResultsAfter eliminating countries without complete information, this study enrolled 120 countries with complete data for both dependent and independent variables. Univariate analysis revealed significant differences by parental education, income level, and water fluoridation. We further conducted multivariate logistic regression analysis, indicating that countries with low fluoridation (< 50%) had significantly higher odds of caries in permanent teeth (OR: 13.23; 95% CI: 1.22–143.53; p = 0.03); shorter years of parental schooling was associated with lower prevalence of caries in permanent teeth (OR: 0.12; 95% CI: 0.03–0.47; p = 0.002); and middle-income countries showed increased risk in both deciduous teeth (OR: 3.44; 95% CI: 1.26–9.43; p = 0.02) and permanent teeth (OR: 6.93; 95% CI: 1.75–27.38; p = 0.01) than high-income countries. Sugar consumption and density of dental personnel were not significantly associated.ConclusionThis ecological study provides valuable insights into the global patterns of dental caries in children aged 5–14 years and their associations with selected socioeconomic indicators. Our results reveal significant correlations of dental caries with income level, water fluoridation coverage, and parental education. However, these associations should be interpreted with caution due to the ecological nature of the data and several important limitations.

The Human Development Index (HDI) is a composite indicator that encompasses the fundamental dimensions of human development, namely health, education, and standard of living. This study aims to objectively rank G-20 countries according to their HDI indicators using 2023 data published by the United Nations Development Programme (UNDP). An integrated Multi-Criteria Decision-Making (MCDM) framework combining the MEREC and EDAS methods was applied. Criterion weights were determined using the MEREC method, which assesses the marginal effect of each indicator, identifying gross national income per capita as the most influential criterion. Based on these weights, countries were ranked through the EDAS method. Results indicate that the United States, Germany, and Australia occupy the highest positions, while South Africa, Indonesia, and India rank lowest. These findings highlight the decisive role of economic prosperity, education, and health standards in shaping human development outcomes. Furthermore, the high consistency between EDAS-based rankings and the official HDI order confirms the validity and robustness of the proposed integrated approach, demonstrating its potential for objective, data-driven evaluation of multidimensional development performance.