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Transport-energy transitions pose complex challenges that have been extensively studied in high-income countries in response to national mandates for climate action. Low- and middle-income countries, however, have low but rapidly growing motorisation rates and face very different challenges in adopting new technologies to foster economic development and ensure equitable access to clean transportation. Here, we present a set of narrative scenarios for the future of the Kenyan transport-energy system co-developed through engagement with 41 local experts and decision-makers. Through the co-development of a Kenyan transport-energy system model, we present a decision-support tool, populated with those scenarios, to assist policymakers at regional, national and international levels in building policy and investment pipelines to support low-carbon economic growth. We find that Kenya’s transport-energy system can meet both development and climate goals, but this demands strong policy support for efficient public transport and targeted support for road vehicle electrification. Increased support for non-motorised transport is essential to provide equitable access to services and economic opportunities. Favourable pathways result in significant e-mobility uptake, which is anticipated to increase electricity demand by 5%–56% from 2023 to 2040, relative to the IEA Kenya Energy Outlook’s Stated Policies scenario, representing a 2.7–3.9x increase in Kenya’s total electricity demand over the same period. From a macro-fiscal perspective, results show that e-mobility has two important consequences for Kenya. Firstly, under high e-mobility scenarios, there is a negative fiscal impact that taxation revenues from the sale of transport fuels reduce by up to 41% relative to the low e-mobility scenario (though, notably, they still increase marginally from the 2023 level because of increasing transport demand). Secondly, high e-mobility scenarios have a positive impact on balance of payments by reducing the fuel import bill by up to 69% relative to the low e-mobility baseline. This corresponds to a reduction in foreign exchange requirement of up to $4.2bn annually by 2050.

Abstract We propose a unified statistical method based on deep learning and heatmap analysis to quantify the relative contributions of the global oceans to El Niño–Southern Oscillation (ENSO) predictability. By incorporating subsurface signals in the Indian Ocean and Atlantic, the forecast lead can be skillfully extended by about one season. This skill enhancement mainly originates from the tropical Indian Ocean, presumably related to signals of the Indian Ocean Dipole passing to the tropical Pacific through the Indonesian Throughflow. The sea surface temperature anomaly (SSTA) in the Indian Ocean accounts for nearly 50% of surface contributions to both El Niño and La Niña predictions at a 15‐month lead. The north tropical Atlantic SSTA has a moderate impact on La Niña at a 9‐month lead. The Pacific Meridional Mode plays a significant role in both ENSO phases at a 12‐month lead. Thus, our study suggests that trans‐basin effects for ENSO are more vigorous than previously thought.

This paper explores how women academics in Chinese higher education have been understood as a topic of research by conducting a comprehensive review of publications on the theme in Chinese national academic journals, that is, national journals written in Chinese. The study identifies publication trends and key research issues concerning academic women in China, adopting a knowledge mapping perspective that unveils research and methodological choices, including data collection methods used in Chinese national journals since the mid-1980s, when the first publication on women academics was identified. The study finds that despite the rapid expansion of the population of women academics in the Chinese higher education system, this topic has been intermittently researched: interest in it peaked in the early 2010s but has declined since then. Past interest in the topic would be largely activated by governmental policy considerations and changes, but would become relatively dormant during periods of lower policy activity. The research has been mainly focused on policy and practice, and has lacked long-term perspectives; it has not always acknowledged societal and structural challenges that academic women face, and has not engaged in theory building. The latter is probably because much of the knowledge production has been based on personal opinions and views, and has suffered from a lack of critical thinking, a reliance on largely unsophisticated methods, and findings that are not generalisable.

Cerebral small vessel disease (CSVD) is an important risk factor for stroke, dementia and death，which seriously endangers the health and quality of life of the elderly. The onset of CSVD is insidious and there is a lack of early diagnosis methods and interventions, so the search for markers that can provide early warning of CSVD and prognosis assessment is very important for the prevention and treatment of the disease. This article reviews imaging and laboratory biomarkers for early diagnosis and prognosis of CSVD, in order to provide new ideas for the formulation of prevention, diagnosis and treatment strategies related to the disease.

SARS-CoV-2 infection causes diverse outcomes ranging from asymptomatic infection to respiratory distress and death. A major unresolved question is whether prior immunity to endemic, human common cold coronaviruses (hCCCoVs) impacts susceptibility to SARS-CoV-2 infection or immunity following infection and vaccination. Therefore, we analyzed samples from the same individuals before and after SARS-CoV-2 infection or vaccination. We found hCCCoV antibody levels increase after SARS-CoV-2 exposure, demonstrating cross-reactivity. However, a case-control study indicates that baseline hCCCoV antibody levels are not associated with protection against SARS-CoV-2 infection. Rather, higher magnitudes of pre-existing betacoronavirus antibodies correlate with more SARS-CoV-2 antibodies following infection, an indicator of greater disease severity. Additionally, immunization with hCCCoV spike proteins before SARS-CoV-2 immunization impedes the generation of SARS-CoV-2-neutralizing antibodies in mice. Together, these data suggest that pre-existing hCCCoV antibodies hinder SARS-CoV-2 antibody-based immunity following infection and provide insight on how pre-existing coronavirus immunity impacts SARS-CoV-2 infection, which is critical considering emerging variants.

The efficacy of coronavirus disease 2019 (COVID-19) vaccines administered after COVID-19-specific monoclonal antibody is unknown, and "antibody interference" might hinder immune responses leading to vaccine failure. In an institutional review board-approved prospective study, we found that an individual who received mRNA COVID-19 vaccination