Empowering Global Health Systems to Protect, Promote and Support Optimal Breastfeeding.

Breastfeeding is a critical public health strategy for optimal child development and maternal health across the life course. The 2021 Global Burden of Diseases, Injuries and Risk Factors Study reveals that, despite reductions in mortality and disability-adjusted life years (DALYs) attributed to suboptimal breastfeeding practices-namely, non-exclusive breastfeeding during the first 6 months or early discontinuation within the first 2 years-low- and middle-income countries (LMICs) continue to bear a staggering 50-fold higher burden compared to high-income nations. This inequity signals a pressing global health priority. Hence, we propose to address these challenges by first, expanding the Baby-Friendly Hospital Initiative (BFHI) reach through community-driven efforts such as the Baby-Friendly Community Initiative (BFCI) to enhance breastfeeding support in both clinical and community settings; second, embedding breastfeeding counselling within national health and social protection programmes to fill in gaps in culturally competent care, drawing on large scale breastfeeding peer counselling programme experiences like the one being implemented by the US Supplemental Nutrition Program for Women, Infants and Children (WIC); third, improving maternity leave policies and workplace accommodations for breastfeeding women and fourth, stringent regulation of exploitative commercial milk formula (CMF) marketing to combat misinformation and reduce health inequities. Governments must implement strong, evidence-driven policies-such as strict monitoring and regulation of product labelling and digital media marketing-to establish safeguards against the powerful influence of the CMF industry. Collectively, these strategies will enhance breastfeeding outcomes, reduce health disparities and drive progress across countries towards meeting the UN Sustainable Development Goals.

Racial and Ethnic Disparities in Fentanyl and Polysubstance Overdose Deaths.

This cross-sectional study describes US overdose death patterns for fentanyl and fentanyl combined with opioids, heroin, cocaine, methamphetamine, or benzodiazepines by race and ethnicity from 2010 to 2022.

US Cancer Mortality Trends Among Asian and Pacific Islander Populations.

Importance: Cancer is the leading cause of death among Asian American individuals and the second leading cause of death among Native Hawaiian and Pacific Islander people. Objective: To evaluate longitudinal cancer mortality trends from 1999 to 2020 among Asian American and Pacific Islander populations in the US by demographic characteristics. Design, Setting, and Participants: This cross-sectional study used the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research database to obtain age-adjusted cancer death rates among Asian American and Pacific Islander individuals of all ages between January 1, 1999, and December 31, 2020. Data were analyzed from January 12 to March 19, 2024. Exposures: Age, sex, cancer type, and US census regions. Main Outcomes and Measures: Trends and average annual percent changes (AAPCs) in age-adjusted cancer-specific mortality (CSM) rates for non-Hispanic Asian American and Pacific Islander populations were estimated by cancer type, age, sex, and region using Joinpoint regression. Results: Between 1999 and 2020, 305 386 Asian American and Pacific Islander individuals (median [IQR] age, 69.5 [58.5-79.2] years; 51.1% male) died of cancer in the US. Overall, the CSM rate decreased by 1.5% annually. Men experienced a greater CSM rate decrease (AAPC, -1.8%; 95% CI, -2.2% to -1.3%) compared with women (AAPC, -1.1%; 95% CI: -1.2% to -1.0%). For women, death rates decreased for most cancer types but increased for uterine (AAPC, 2.5%; 95% CI, 2.0%-3.0%) and brain and central nervous system (AAPC, 1.4%; 95% CI: 0.7%-2.1%) cancers. Colorectal cancer mortality rates increased among men aged 45 to 54 years (AAPC, 1.3%; 95% CI, 0.5%-2.1%). Liver and intrahepatic bile duct cancer mortality increased for both men and women in all US census regions, uterine cancer mortality increased in all regions for women, and pancreatic cancer mortality increased in the Midwest for both men and women. Conclusions and Relevance: Although these findings show an overall decrease in CSM among Asian American and Pacific Islander populations, specific cancer types exhibited increased mortality rates, with further disparities by sex and age. Targeted, culturally adapted clinical and public health interventions are needed to narrow disparities in cancer mortality.

Real-Time Visualization of Infiltration and Retention of Microplastics with Different Shapes in Porous Media.

Infiltration and retention of microplastics in porous media are important for understanding their fate in environments and formulating treatment measures. Given porous media opacity, knowledge is usually obtained indirectly by monitoring microplastic concentration in the effluent and measuring microplastic distribution after removing grains in layers. In this study, real-time visualization of infiltration and retention of microplastics in porous media under vertical water flow is performed using an improved reflective index matching method, considering the different shapes and densities of microplastics and size ratios between microplastics and grains. The spherical microplastics have the largest infiltration depths, with trajectories closest to vertical and accompanied by long acceleration durations and low deceleration frequencies. The cylindrical microplastics deviate from vertical and have stronger transverse oscillations and more frequent decelerations, while the flaky microplastics have the most significant transverse displacements. The infiltration depth can be improved by reducing the size ratio between microplastics and grains and increasing the vertical flow rate, while the density of microplastics has a relatively limited effect. Sliding and rotating of microplastics after collision with grains are observed, responsible for deceleration and transverse displacements. Different retention patterns are found, with the number of types being inversely proportional to the number of principal dimensions of the shape.

Study protocol: Cerebral autoregulation, brain perfusion, and neurocognitive outcomes after traumatic brain injury -CAPCOG-TBI.

Background: Moderate-severe traumatic brain injury (msTBI) stands as a prominent etiology of adult disability, with increased risk for cognitive impairment and dementia. Although some recovery often occurs within the first year post-injury, predicting long-term cognitive outcomes remains challenging, partly due to the significant pathophysiological heterogeneity of TBI, including acute cerebrovascular injury. The primary aim of our recently funded study, cerebral autoregulation, brain perfusion, and neurocognitive outcomes after traumatic brain injury (CAPCOG-TBI), is to determine if acute cerebrovascular dysfunction after msTBI measured using multimodal non-invasive neuromonitoring is associated with cognitive outcome at 1-year post-injury. Methods: This longitudinal observational study will be conducted at two Level 1 trauma centers in Texas, USA, and will include adult patients with msTBI, and/or mild TBI with neuroimaging abnormalities. Multimodal cerebral vascular assessment using transcranial Doppler and cerebral near-infrared spectroscopy (NIRS) will be conducted within 7-days of onset of TBI. Longitudinal outcomes, including cognitive/functional assessments (Glasgow Outcome Scale and Patient-Reported Outcomes Measurement Information System), cerebral vascular assessment, and imaging will be performed at follow-ups 3-, 6-, and 12-months post-injury. We aim to recruit 100 subjects with msTBI along with 30 orthopedic trauma controls (OTC). This study is funded by National Institute of Neurological Disease and Stroke (NINDS) and is registered on Clinicaltrial.org (NCT06480838). Expected results: We anticipate that msTBI patients will exhibit impaired cerebrovascular function in the acute phase compared to the OTC group. The severity of cerebrovascular dysfunction during this stage is expected to inversely correlate with cognitive and functional outcomes at 1-year post-injury. Additionally, recovery from cerebrovascular dysfunction is expected to be linked to cognitive recovery. Conclusion: The results of this study could help to understand the contribution of cerebrovascular dysfunction to cognitive outcomes after TBI and pave the way for innovative vascular-focused interventions aimed at enhancing cognitive recovery and mitigating neurodegeneration following msTB. In addition, its focus toward personalized medicine to aid in the management and prognosis of TBI patients.

Experimental study of liquid drop impact on granular medium: Drop spreading/splashing and particle ejection.

The impact of a liquid drop on a granular medium is a common phenomenon in nature and engineering. The possible splashing droplets and ejected particles could pose a risk of pathogen transmission if the water source or granular medium is contaminated. This work studies the liquid drop impact on the granular medium using high-speed photography and considers the effects of liquid properties, drop impact characteristics, and granular medium properties. Four flow regimes, including direct penetration, prompt splashing, spreading, and corona splashing, are observed and a regime map is created to identify their thresholds. The spreading regime can eject a large number of particles, and the corona splashing regime can produce splashing droplets in addition to the ejected particles. For the splashing droplets, their median diameters and velocities are in the ranges 0.11 to 0.21 and 0.15 to 0.37 of the diameter and velocity of the impact drop, and their median splashing angles range from 14° to 27°. Two particle ejection mechanisms are observed, falling squeeze and forward collision, driven by the collapsing and forward spreading of the liquid lamella, respectively. The particles ejected by the latter mechanism have larger ejection velocities, angles and distances from the impact center, which can facilitate their long-range transmission. In addition, the process of spreading and retracting of the lamella formed by the drop impact is also studied, and it is found that the maximum spreading diameter of the lamella is proportional to the crater diameter. These results improve the understanding of the phenomenon after the drop impact on the granular medium and the characteristics of the splashing droplets and ejected particles, contributing to the prediction and risk assessment of contaminated particle transmission.

Impacts of climate change on urban stormwater runoff quantity and quality in a cold region.

Climate change poses significant challenges to urban environments affecting both flood risks and stormwater pollutant loadings. However, studies on variations in stormwater runoff quantity and quality in cold regions, which are highly sensitive to climate change, are notably limited. Integrating climatic, hydrologic, and hydraulic modelling, the study assesses the potential impacts of climate change on stormwater runoff volume and pollutant dynamics in a Canadian urban watershed (Calgary). A two-year field program was conducted to support the calibration and validation of the Storm Water Management Model (SWMM). Intensity-duration-frequency curves were employed to evaluate the impacts of climate change on peak flow rate and flooding duration. In addition, typical dry, average, and wet years were applied to continuously simulate stormwater runoff quantity and quality during the 2050s and 2080s. The results suggest substantial increases in peak flow rates and flooding durations, particularly for the 5-year return period rainfall, with 1-h, 4-h, and 24-h peak inflow rates increasing by 74.3% (170.7%), 89.2% (158.4%), and 64.1% (102.8%) in the 2050s (2080s) Furthermore, the runoff quantity is projected to rise by 2.4-10.2% in the 2050s and 11.8-17.5% in the 2080s. Total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) loadings are anticipated to increase by 2.0-36.1%, 3.1-21.4%, and 4.1-20.7%, respectively. As a result, the current stormwater system could overload and stormwater quality is likely to deteriorate under the impact of climate change. The findings are beneficial for cold regions to develop adaptive strategies that enhance urban water security and environmental sustainability under climate change.

Evaluation of gradient diffusion in vitro susceptibility testing of Aerococcus urinae.

OBJECTIVE: Aerococcus urinae antimicrobial susceptibility testing can be performed via broth microdilution with Mueller-Hinton broth supplemented with lysed horse blood. We sought to compare this with the commonly used gradient diffusion method. METHODS: We compared broth microdilution with Mueller-Hinton broth supplemented with lysed horse blood and gradient diffusion via Mueller-Hinton agar supplemented with sheep blood for 190 A. urinae isolates against 16 antimicrobials. RESULTS: No antimicrobials demonstrated more than 90% essential and categorical agreement, and fewer than 3% demonstrated major and very major error rates. Trimethoprim-sulfamethoxazole demonstrated an 81% major error rate and ceftriaxone demonstrated a 76% very major error rate. Agar dilution with lysed horse blood was performed for trimethoprim-sulfamethoxazole against 94 isolates and showed 100% susceptibility, consistent with previous studies. CONCLUSIONS: Given its limitations in detecting resistant strains, our findings cannot support the routine use of gradient diffusion with Mueller-Hinton agar supplemented with sheep blood for A. urinae in lieu of the Clinical and Laboratory Standards Institute method. Our results suggest that A. urinae is usually susceptible to penicillin, linezolid, tetracycline, and vancomycin. Future studies should evaluate alternative testing methods for clinical microbiology laboratories.

Effects of mixed land use on urban stormwater quality under different rainfall event types.

The joint effect of mixed land uses and rainfall event types was studied using a two-year field monitoring program in four urban catchments in Calgary, Alberta, Canada. Event mean concentration (EMC) and event pollutant load (EPL) were employed to evaluate the total suspended sediment (TSS), nitrogen and phosphorus. The correlation analysis showed that most nitrogen and phosphorus components (except for NO2-/NO3- and TDP) predominantly exist in particulate form in the study areas. The correlation for EPL was notably stronger than EMC, which can be attributed to varying rainfall characteristics. The differences in EMCs and EPLs of TSS, nitrogen and phosphorus across catchments indicated that the complexity and spatial distribution of mixed land use can influence the generation and transportation of pollutants in urban runoff. The impacts of rainfall characteristics on stormwater quality are integrated rather than driven by a single rainfall characteristic. Brief but intense events tended to elevate TSS, nitrogen and phosphorus concentrations, especially in complex land-use catchments. Events with long antecedent dry days and short duration also resulted in increased pollutant concentrations, while events with long duration and low intensity could result in higher EPLs. The effect of mixed land use on water quality can vary depending on rainfall event types. Seasonal variations were found in EMC and EPL of TSS, nitrogen and phosphorus, with higher values in the spring and summer than the fall. Seasonal variations are mainly influenced by rainfall conditions, temperature and anthropogenic activities (e.g. lawn fertilization and de-icing with sands). MLR considering rainfall characteristics is an effective method for predicting stormwater quality within a single catchment. Considering complexity and spatial distribution of mixed land use can improve the accuracy of the harmonized MLR model. This research provided insights into understanding the complexities introduced by mixed land use and rainfall event types in urban stormwater quality.

Causalized Convergent Cross Mapping and Its Implementation in Causality Analysis.

Rooted in dynamic systems theory, convergent cross mapping (CCM) has attracted increased attention recently due to its capability in detecting linear and nonlinear causal coupling in both random and deterministic settings. One limitation with CCM is that it uses both past and future values to predict the current value, which is inconsistent with the widely accepted definition of causality, where it is assumed that the future values of one process cannot influence the past of another. To overcome this obstacle, in our previous research, we introduced the concept of causalized convergent cross mapping (cCCM), where future values are no longer used to predict the current value. In this paper, we focus on the implementation of cCCM in causality analysis. More specifically, we demonstrate the effectiveness of cCCM in identifying both linear and nonlinear causal coupling in various settings through a large number of examples, including Gaussian random variables with additive noise, sinusoidal waveforms, autoregressive models, stochastic processes with a dominant spectral component embedded in noise, deterministic chaotic maps, and systems with memory, as well as experimental fMRI data. In particular, we analyze the impact of shadow manifold construction on the performance of cCCM and provide detailed guidelines on how to configure the key parameters of cCCM in different applications. Overall, our analysis indicates that cCCM is a promising and easy-to-implement tool for causality analysis in a wide spectrum of applications.

Evaluation on the performance of a swirling-type hydrodynamic separator using physical and numerical models.

Hydrodynamic separators are commonly used to control the total suspended solid concentration in stormwater before being discharged to natural water bodies. The separator studied in this paper, featuring a swirling flow generated by tangential inlet and outlet connections, was analyzed for its sediment removal efficiency in relation to sediment and flow rates. For the separator studied in this paper, the numerical model showed that the flow field was favorable for the sediments to gather at the center and settle. A higher flow rate or a smaller sediment diameter corresponded to a lower removal rate and vice versa. The dimension improvement for increasing the sediment removal rate was also studied. It was found that increasing the diameter of the separator showed a higher sediment removal rate compared with corresponding increase in the height of the separator. A dimensionless parameter J was proposed to assess the sediment removal rate of a separator, which may be used for designing and optimizing such a device. The removal rate is positively correlated with the J value. When the J value reaches 0.5 or above, the sediment removal rate exceeds 80%, which is a good initial target value for designing this type of separator.

Multiple myeloma incidence and mortality trends in the United States, 1999-2020.

Multiple myeloma (MM) is a plasma cell disorder accounting for approximately 10% of hematologic malignancies. There is limited epidemiological evidence regarding the long-term trends and disparities in MM in the US. We conducted a multiple time point cross-sectional study using MM incidence rate data from the Surveillance, Epidemiology, and End Results (SEER) database and mortality data from the CDC Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Underlying Cause of Death database between 1999 and 2020. During this period, MM incidence has steadily increased, while MM mortality has steadily decreased, with substantial racial and ethnic disparities. Non-Hispanic Black individuals exhibited the highest incidence rates, which consistently rose from 12.02 (95% CI 10.54, 13.64) in 1999 to 14.20 (95% CI 12.93, 15.55) per 100,000 population by 2020. Non-Hispanic American Indian/Native Alaskans and Asian/Pacific Islanders demonstrated the lowest incidence rates of 5.59 (95% CI 2.69, 10.04) and 3.56 (95% CI 2.94, 4.27) per 100,000 population in 1999 to 5.76 (95% CI 3.49, 8.90) and 3.92 (95% CI 3.46, 4.42) per 100,000 population, respectively, by 2020. Disparities by gender, age, US census region, and rurality were observed, underscoring the importance of targeted, equity-centered interventions and MM screening initiatives for at-risk populations.

Disparities in Cancer Mortality among Disaggregated Asian American Subpopulations, 2018-2021.

Federal, state, and institutional data collection practices and analyses involving Asian Americans as a single, aggregated group obscure critical health disparities among the vast diversity of Asian American subpopulations. Using from the Centers for Disease Control and Prevention Wide-Ranging Online Data for Epidemiologic Research (CDC WONDER) Underlying Causes of Death database, we conducted a cross-sectional study using data on disaggregated Asian American subgroups (Asian Indian, Chinese, Filipino, Japanese, Korean, Vietnamese, other Asians) between 2018 and 2021. We examine deaths from 22 cancer types and in situ, benign neoplasms, identified using ICD-10 codes C00-C97 and D00-D48. Overall, our study comprised 327,311 Asian American decedents, with a mean age of death at 70.57 years (SD=2.79), wherein females accounted for approximately half of the sample (n=36,596/73,207; 49.99%). Notably, compared to the aggregated Asian American reference group, we found higher proportions of deaths from total cancers among Chinese (25.99% vs. 22.37% [ref]), Korean (25.29% vs. 22.37% [ref]), and Vietnamese (24.98% vs. 22.37% [ref]) subgroups. In contrast, total cancer deaths were less prevalent among Asian Indians (17.49% vs. 22.37% [ref]), Japanese (18.90% vs. 22.37% [ref]), and other Asians (20.37% vs. 22.37% [ref]). We identified further disparities by cancer type, sex, and age. Disaggregated data collection and analyses are imperative to understanding differences in cancer mortality among Asian American subgroups, illustrating at-risk populations with greater granularity. Future studies should aim to describe the association between these trends and social, demographic, and environmental risk factors.

Particle size distribution of total suspended sediments in urban stormwater runoff: Effect of land uses, precipitation conditions, and seasonal variations.

Understanding particle size distribution (PSD) of total suspended sediments in urban runoff is essential for pollutant fate and designing effective stormwater treatment measures. However, the PSDs from different land uses under different weather conditions have yet to be sufficiently studied. This research conducted a six-year water sampling program in 15 study sites to analyze the PSD of total suspended sediments in runoff. The results revealed that the median particle size decreased in the order: paved residential, commercial, gravel lane residential, mixed land use, industrial, and roads. Fine particles less than 125 µm are the dominant particles (over 75%) of total suspended sediments in runoff in Calgary, Alberta, Canada. Roads have the largest percentage of particles finer than 32 µm (49%). Gravel lane residential areas have finer particle sizes than paved residential areas. The results of PSD were compared with previous literature to provide more comprehensive information about PSD from different land uses. The impact of rainfall event types can vary depending on land use types. A long antecedent dry period tends to result in the accumulation of fine particles on urban surfaces. High rainfall intensity and long duration can wash off more coarse particles. The PSD in spring exhibits the finest particles, while fall has the largest percentage of coarse particles. Snowmelt particles are finer for the same land use than that during rainfall events because the rainfall-runoff flows are usually larger than the snowmelt flows.

TDG prediction model improvement by analysis and validation of experiments on a dam model.

The combination of aerated flows and a high-pressure environment in a stilling basin can result in the supersaturation of total dissolved gas (TDG) downstream of hydraulic projects, posing an ecological risk to aquatic populations by inducing gas bubble disease (GBD) or other negative effects. There is limited literature reporting TDG mass transfer experiments on a complete physical dam model; most existing research is based on measurements in prototype tailwaters. In this study, TDG mass transfer experiments were conducted on a physical model of an under-constructed dam, with TDG-supersaturated water as the inflow, and TDG concentrations were meticulously monitored within the stilling basin. The measurements indicate that the TDG saturation at the outlet of the stilling basin decreased by 13.7% and 10.6% compared to the inlet for the two cases, respectively. Subsequently, an improved TDG prediction model was developed by incorporating a sub-grid air entrainment model and a phase-constrained scalar model. The numerical simulation results were compared with experimental data, indicating a maximum error in TDG saturation at all measured points of less than ± 3%. Moreover, the TDG saturation showed an error of only ± 0.3% at the outlet of the stilling basin. This model has broad applicability to various flow types for obtaining TDG mass transfer results and evaluating mitigation measures of TDG supersaturation to reduce the harmful effects on aquatic ecosystems.

Quantification and cultivation of Helicobacter pylori (H. pylori) from various urban water environments: A comprehensive analysis of precondition methods and sample characteristics.

Substantial evidence suggests that all types of water, such as drinking water, wastewater, surface water, and groundwater, can be potential sources of Helicobacter pylori (H. pylori) infection. Thus, it is critical to thoroughly investigate all possible preconditioning methods to enhance the recovery of H. pylori, improve the reproducibility of subsequent detection, and optimize the suitability for various water types and different detection purposes. In this study, we proposed and evaluated five distinct preconditioning methods for treating water samples collected from multiple urban water environments, aiming to maximize the quantitative qPCR readouts and achieve effective selective cultivation. According to the experimental results, when using the qPCR technique to examine WWTP influent, effluent, septic tank, and wetland water samples, the significance of having a preliminary cleaning step becomes more evident as it can profoundly influence qPCR detection results. In contrast, the simple, straightforward membrane filtration method could perform best when isolating and culturing H. pylori from all water samples. Upon examining the cultivation and qPCR results obtained from groundwater samples, the presence of infectious H. pylori (potentially other pathogens) in aquifers must represent a pressing environmental emergency demanding immediate attention. Furthermore, we believe groundwater can be used as a medium to reflect the H. pylori prevalence in a highly populated community due to its straightforward analytical matrix, consistent detection performance, and minimal interferences from human activities, temperature, precipitation, and other environmental fluctuations.

Assessment of rainfall-derived inflow and infiltration in sewer systems with machine learning approaches.

Rainfall-derived inflow/infiltration (RDII) modelling during heavy rainfall events is essential for sewer flow management. In this study, two machine learning algorithms, random forest (RF) and long short-term memory (LSTM), were developed for sewer flow prediction and RDII estimation based on field monitoring data. The study implemented feature engineering for extracting physically significant features in sewer flow modelling and investigated the importance of the relevant features. The results from two case studies indicated the superior capability of machine learning models in RDII estimation in the combined and separated sewer systems, and LSTM model outperformed the two models. Compared to traditional methods, machine learning models were capable of simulating the temporal variation in RDII processes and improved prediction accuracy for peak flows and RDII volumes in storm events.