Retrospective analysis of acute ischemic stroke shows timing of antidepressant use associated with short-term recovery and functional independence at 90-days.

BACKGROUND: Little is known about how the timing of antidepressant use influences stroke outcomes. Previous research shows conflicting results on the impact of a new antidepressant prescription on stroke recovery. OBJECTIVE: The objective of this exploratory, retrospective analysis is to examine stroke outcomes by timing of antidepressant use among patients who received stroke treatment. METHODS: 12,590 eligible patients were treated for a primary or secondary diagnosis of ischemic stroke. The outcome variables were a change in ambulation or modified Rankin scale (mRs) from pre-stroke to discharge; and a change in mRS from pre-stroke to 90-days post-discharge. The independent variable of interest was timing of antidepressant treatment. Logistic regression with generalized estimating equations was used, controlling for covariates. RESULTS: Our model predicted that a new antidepressant prescription at discharge was associated with a ∼7% decrease in the likelihood of returning to baseline functional independence at 90-days compared to patients currently using an antidepressant (AOR:0.510, CI:0.277-0.938, p = 0.03). CONCLUSION: These results suggest that use of antidepressants was associated with stroke recovery, but the effects are moderated by sex. Further study is needed to determine if this relationship is causal and the mechanisms between timing of antidepressant treatment and outcomes.

Increased probability of hot and dry weather extremes during the growing season threatens global crop yields.

Although extreme weather events recur periodically everywhere, the impacts of their simultaneous occurrence on crop yields are globally unknown. In this study, we estimate the impacts of combined hot and dry extremes as well as cold and wet extremes on maize, rice, soybean, and wheat yields using gridded weather data and reported crop yield data at the global scale for 1980-2009. Our results show that co-occurring extremely hot and dry events have globally consistent negative effects on the yields of all inspected crop types. Extremely cold and wet conditions were observed to reduce crop yields globally too, although to a lesser extent and the impacts being more uncertain and inconsistent. Critically, we found that over the study period, the probability of co-occurring extreme hot and dry events during the growing season increased across all inspected crop types; wheat showing the largest, up to a six-fold, increase. Hence, our study highlights the potentially detrimental impacts that increasing climate variability can have on global food production.

Young-Onset Breast Cancer Outcomes by Time Since Recent Childbirth in Utah.

Importance: Breast cancer diagnosed within 5 to 10 years after childbirth, called postpartum breast cancer (PPBC), is associated with increased risk for metastasis and death. Whether a postpartum diagnosis is an independent risk factor or a surrogate marker of cancer features associated with poor outcomes remains understudied. Objective: To determine whether diagnostic temporal proximity to childbirth is associated with features of breast cancer associated with poor outcomes, including tumor stage, estrogen receptor (ER) status, and risk for distant metastasis and breast cancer-specific mortality, using a population database from the state of Utah. Design, Setting, and Participants: This population-based cohort study using the Utah Population Database (UPDB) included individuals with stage I to III breast cancer diagnosed at age 45 years or younger between 1996 and 2017, followed-up until February 2020. Participant data were analyzed from November 2019 to August 2022. Exposure: The primary exposures were no prior childbirth or time between most recent childbirth and breast cancer diagnosis. Patients were grouped by diagnoses within less than 5 years, 5 to less than 10 years, or 10 years or more since recent childbirth. Main Outcomes and Measures: The 2 primary outcomes were distant metastasis-free survival and breast cancer-specific death. Cox proportional hazard models were used to investigate associations between exposures and outcomes adjusting for diagnosis year, patient age, tumor stage, and estrogen receptor (ER) status. Results: Of 2970 individuals with breast cancer diagnosed at age 45 years or younger (mean [SD] age, 39.3 [5.0] years; 12 Black individuals [0.4%], 2679 White individuals [90.2%]), breast cancer diagnosis within 5 years of recent childbirth was independently associated with approximately 1.5-fold elevated risk for metastasis (hazard ratio [HR], 1.5; 95% CI, 1.2-2.0) and breast cancer-specific death (HR, 1.5; 95% CI, 1.1-2.1) compared with nulliparous individuals. For cancers classically considered to have tumor features associated with good outcomes (ie, stage I or II and ER-positive), a postpartum diagnosis was a dominant feature associated with increased risk for metastasis and death (eg, for individuals with ER-positive disease diagnosed within <5 years of childbirth: age-adjusted metastasis HR, 1.5; 95% CI, 1.1-2.1; P = .01; age-adjusted death HR, 1.5; 95% CI, 1.0-2.1; P = .04) compared with nulliparous individuals. Furthermore, liver metastases were specifically increased in the group with diagnosis within 5 years postpartum and with positive ER expression (38 of 83 patients [45.8%]) compared with the nulliparous (28 of 77 patients [36.4%]), although the difference was not statistically significant. Overall, these data implicate parity-associated breast and liver biology in the observed poor outcomes of PPBC. Conclusions and Relevance: In this cohort study of individuals with breast cancer diagnosed at age 45 years or younger, a postpartum breast cancer diagnosis was a risk factor associated with poor outcomes. Irrespective of ER status, clinical consideration of time between most recent childbirth and breast cancer diagnosis could increase accuracy of prognosis in patients with young-onset breast cancer.

The impact of flooding on food security across Africa.

Recent record rainfall and flood events have prompted increased attention to flood impacts on human systems. Information regarding flood effects on food security is of particular importance for humanitarian organizations and is especially valuable across Africa's rural areas that contribute to regional food supplies. We quantitatively evaluate where and to what extent flooding impacts food security across Africa, using a Granger causality analysis and panel modeling approaches. Within our modeled areas, we find that ∼12% of the people that experienced food insecurity from 2009 to 2020 had their food security status affected by flooding. Furthermore, flooding and its associated meteorological conditions can simultaneously degrade food security locally while enhancing it at regional spatial scales, leading to large variations in overall food security outcomes. Dedicated data collection at the intersection of flood events and associated food security measures across different spatial and temporal scales are required to better characterize the extent of flood impact and inform preparedness, response, and recovery needs.

Climate change may outpace current wheat breeding yield improvements in North America.

Variety adaptation to future climate for wheat is important but lacks comprehensive understanding. Here, we evaluate genetic advancement under current and future climate using a dataset of wheat breeding nurseries in North America during 1960-2018. Results show that yields declined by 3.6% per 1 °C warming for advanced winter wheat breeding lines, compared with -5.5% for the check variety, indicating a superior climate-resilience. However, advanced spring wheat breeding lines showed a 7.5% yield reduction per 1 °C warming, which is more sensitive than a 7.1% reduction for the check variety, indicating climate resilience is not improved and may even decline for spring wheat. Under future climate of SSP scenarios, yields of winter and spring wheat exhibit declining trends even with advanced breeding lines, suggesting future climate warming could outpace the yield gains from current breeding progress. Our study highlights that the adaptation progress following the current wheat breeding strategies is challenging.

Research priorities for global food security under extreme events.

Extreme events, such as those caused by climate change, economic or geopolitical shocks, and pest or disease epidemics, threaten global food security. The complexity of causation, as well as the myriad ways that an event, or a sequence of events, creates cascading and systemic impacts, poses significant challenges to food systems research and policy alike. To identify priority food security risks and research opportunities, we asked experts from a range of fields and geographies to describe key threats to global food security over the next two decades and to suggest key research questions and gaps on this topic. Here, we present a prioritization of threats to global food security from extreme events, as well as emerging research questions that highlight the conceptual and practical challenges that exist in designing, adopting, and governing resilient food systems. We hope that these findings help in directing research funding and resources toward food system transformations needed to help society tackle major food system risks and food insecurity under extreme events.

Violent conflict exacerbated drought-related food insecurity between 2009 and 2019 in sub-Saharan Africa.

Conflict, drought and locusts are leading concerns for African food security but the relative importance and spatiotemporal scale of crises resulting from each hazard is poorly characterized. Here we use continuous, subnational data to demonstrate that the rise of food insecurity across sub-Saharan Africa that began in 2014 is attributable to an increase in violent conflict, particularly in South Sudan and Nigeria. Although drought remains a leading trigger of food crises, the prevalence of drought-related crises did not increase from 2009 to 2018. When exposed to drought, pastoralists experienced more widespread, severe and long-lasting food crises than people living in agricultural zones. Food insecurity remained elevated in pastoral regions for 2 years following a drought, while agricultural regions returned to pre-drought food-security levels in ~12 months. The few confirmed famines during the 2009-2018 period coincided with both conflict and drought, while locusts had little effect on food security during this period.

Mucosal Immunity and Liver Metabolism in the Complex Condition of Lactation Insufficiency.

Lactation insufficiency is variously defined and includes the inability to produce milk, not producing enough milk to exclusively meet infant growth requirements, and pathological interruption of lactation (e.g., mastitis). Of women with intent-to-breastfeed, lactation insufficiency has been estimated to affect 38%-44% of newly postpartum women, likely contributing to the nearly 60% of infants that are not breastfed according to the World Health Organization's guidelines. To date, research and clinical practice aimed at improving feeding outcomes have focused on hospital lactation support and education, with laudable results. However, researchers' reports of recent rodent studies concerning fundamental lactation biology have suggested that the underlying pathologies of lactation insufficiency may be more nuanced than is currently appreciated. In this article, we identify mucosal biology of the breast and lactation-specific liver biology as two under-researched aspects of lactation physiology. Specifically, we argue that further scientific inquiry into reproductive state-dependent regulation of immunity in the human breast will reveal insights into novel immune based requirements for healthy lactation. Additionally, our synthesis of the literature supports the hypothesis that the liver is an essential player in lactation-highlighting the potential that pathologies of the liver may also be associated with lactation insufficiency. More research into these biologic underpinnings of lactation is anticipated to provide new avenues to understand and treat lactation insufficiency.

Chinese rice production area adaptations to climate changes, 1949-2010.

Climate change has great impact on cropping system. Understanding how the rice production system has historically responded to external forces, both natural and anthropogenic, will provide critical insights into how the system is likely to respond in the future. The observed historic rice movement provides insights into the capability of the rice production system to adapt to climate changes. Using province-level rice production data and historic climate records, here we show that the centroid of Chinese rice production shifted northeastward over 370 km (2.98°N in latitude and 1.88°E in longitude) from 1949 to 2010. Using a linear regression model, we examined the driving factors, in particular climate, behind such rice production movement. While the major driving forces of the rice relocation are such social economic factors as urbanization, irrigation investment, and agricultural or land use policy changes, climate plays a significant role as well. We found that temperature has been a significant and coherent influence on moving the rice center in China and precipitation has had a significant but less spatially coherent influence.

Methods for estimating population density in data-limited areas: evaluating regression and tree-based models in Peru.

Obtaining accurate small area estimates of population is essential for policy and health planning but is often difficult in countries with limited data. In lieu of available population data, small area estimate models draw information from previous time periods or from similar areas. This study focuses on model-based methods for estimating population when no direct samples are available in the area of interest. To explore the efficacy of tree-based models for estimating population density, we compare six different model structures including Random Forest and Bayesian Additive Regression Trees. Results demonstrate that without information from prior time periods, non-parametric tree-based models produced more accurate predictions than did conventional regression methods. Improving estimates of population density in non-sampled areas is important for regions with incomplete census data and has implications for economic, health and development policies.