Positive Trend Research Articles

Distributed and autonomous multi-robot for task allocation and collaboration using a greedy algorithm and robot operating system platform

Research investigations in the realm of micro-robotics often center around strategies addressing the multi-robot task allocation (MRTA) problem. Our contribution delves into the collaborative dynamics of micro-robots deployed in targeted hostile environments. Employing advanced algorithms, these robots play a crucial role in enhancing and streamlining operations within sensitive areas. We adopt a tailored GREEDY approach, strategically adjusting weight parameters in a multi-objective function that serves as a cost metric. The objective function, designed for optimization purposes, aggregates the cost functions of all agents involved. Our evaluation meticulously examines the MRTA efficiency for each micro-robot, considering dependencies on factors such as radio connectivity, available energy, and the absolute and relative availability of agents. The central focus is on validating the positive trend associated with an increasing number of agents constituting the cluster. Our methodology introduces a trio of micro-robots, unveiling a flexible strategy aimed at detecting individuals at risk in demanding environments. Each micro-robot within the cluster is equipped with logic that ensures compatibility and cooperation, enabling them to effectively execute assigned missions. The implementation of MRTA-based collaboration algorithms serves as an adaptive strategy, optimizing agents' mobility based on specific criteria related to the characteristics of the target site.<p class="JAMRISAbstract"> </p>

Associations of per- and polyfluoroalkyl substances with maternal early second trimester sex-steroid hormones

Background/AimsPregnant women are exposed to persistent environmental contaminants, including per- and polyfluoroalkyl substances (PFAS) that disrupt thyroid function. However, it is unclear if PFAS alter maternal sex-steroid hormone levels, which support pregnancy health and fetal development. MethodsIn Illinois women with relatively high socioeconomic status (n = 460), we quantified perfluorononanoic (PFNA), perfluorooctane sulfonic (PFOS), perfluorooctanoic (PFOA), methyl-perfluorooctane sulfonamide acetic acid, perfluorohexanesulphonic (PFHxS), perfluorodecanoic (PFDeA), and perfluoroundecanoic (PFUdA) acid concentrations in fasting serum samples at median 17 weeks gestation, along with plasma progesterone, testosterone, and estradiol. We evaluated covariate-adjusted associations of ln-transformed hormones with each ln-transformed PFAS individually using linear regression and with the PFAS mixture using quantile-based g-computation (QGComp). ResultsInterquartile range (IQR) increases in PFOS were associated with higher progesterone (%Δ 3.0; 95%CI: −0.6, 6.6) and estradiol (%Δ: 8.1; 95%CI: 2.2, 14.4) levels. Additionally, PFHxS was positively associated with testosterone (%Δ: 10.2; 95%CI: 4.0, 16.7), whereas both PFDeA and PFUdA were inversely associated with testosterone (%Δ: −5.7; 95%CI: −10.3, −0.8, and %Δ: −4.1; 95%CI: −7.6, −0.4, respectively). The IQR-standardized PFAS mixture was not associated with progesterone (%Δ: 1.6; 95%CI: −5.8, 9.2), due equal partial positive (%Δ: 9.2; driven by PFOA) and negative (%Δ: −7.4; driven by PFOS) mixture associations. Similarly, the mixture was not associated with testosterone (%Δ: 5.3; 95%CI: −9.0, 20.1), due to similar partial positive (%Δ: 23.6; driven by PFHxS) and negative (%Δ: −17.4; driven by PFDeA) mixture associations. However, we observed a slightly stronger partial positive (%Δ: 25.6; driven by PFOS and PFUdA) than negative (%Δ: −16.3; driven by PFOA) association resulting in an overall non-significant positive trend between the mixture and estradiol (%Δ: 8.5; 95%CI: −3.7, 20.9). ConclusionPFAS mixture modeled using QGComp was not associated with maternal sex-steroid hormones due to potential opposing effects of certain PFAS. Additional prospective studies could corroborate these findings.

MIIP downregulates PD-L1 expression through HDAC6 in cutaneous melanoma

PurposeImmune checkpoint inhibitors have improved the objective response rate and survival of melanoma patients. However, there are still many melanoma patients suffering from disease progression due to primary or secondary immune checkpoint inhibitor resistance, as is observed in the failure of anti-PD1/PD-L1 therapy. While the expression of valuable markers, such as TMB, MSI, and PD-L1, could serve as effective predictors of anti-checkpoint inhibitor therapies, tumor cell PD-L1 expression and its regulating mechanism would significantly affect the anti-PD-1 immunotherapy response and efficacy. Therefore, it is urgent to determine the function of PD-1/PD-L1 expression in melanoma and its associated pathways to enhance the efficacy of anti-PD-1 therapies.MethodsA cohort of 133 patients with histologically confirmed melanoma from Tianjin Medical University Cancer Institute & Hospital were included in this study. We performed immunohistochemical staining to detect the expression of Migration and invasion inhibitory protein (MIIP), HDAC6 and PD-L1. Kaplan–Meier and log-rank test were used for survival analysis. As for vitro, Western blot was used in melanoma cell lines to verify the signaling pathway that MIIP regulates PD-L1 expression.ResultsMIIP expression was decreased in melanoma and that the negative expression of MIIP was correlated with worse overall survival. The positive expression of HDAC6, a molecule that is downstream of MIIP, had a positive trend with decreased overall survival. At the same time, the positive expression of PD-L1, a crucial costimulatory molecule, was associated with decreased overall survival. Furthermore, there was a positive association between HDAC6 and PD-L1 protein expression (p < 0.01), and this correlation is more prominent in cutaneous melanoma than acral melanoma. In cutaneous melanoma cell lines, we found that increasing MIIP led to decreased HDAC6, pSTAT3, and PD-L1 expression. Knocking down MIIP led to increased HDAC6, pSTAT3, and PD-L1 expression. Combining the published results, showing that HDAC6 can regulate PD-L1 expression through STAT3, our present data suggest that MIIP inhibits the expression of PD-L1 by downregulating HDAC6 in melanoma. Most importantly, methods for targeting MIIP-HDAC6-PD-L1 pathways, such as treatment with HDAC6 inhibitors, might indicate a new therapeutic approach for enhancing immune checkpoint inhibitor therapies in melanoma.ConclusionsOur findings highlight the immunomodulatory effects of MIIP in the inhibition of PD-L1 expression by downregulating HDAC6 in melanoma. Methods for targeting MIIP-HDAC6-PD-L1 pathways might be new therapeutic approaches for enhancing immune checkpoint inhibitor therapies in melanoma.

The Power of Norms: Gender Equality Reforms in the Parliaments of Fiji and Samoa

Parliaments are increasingly defined as “gendered institutions,” with rules, norms, and practices that are often stubbornly resistant to gender equality initiatives. The gender sensitive parliaments’ global agenda has made substantial progress in both drawing attention to the gendered nature of parliaments and in spearheading gender equality reform. While a positive trend, there remains a significant disconnect between the (global) normative framework that sets out this agenda and the realization of gender equality in national (local) parliaments. In this article, we build on previous work that begins to unpack and test the process of global norm localization through “contextualization” and “contestation.” We select new sites to test these processes—Fiji and Samoa—where specific gender equality reforms have been implemented in the past 10 years, one a gender mainstreaming mandate for parliamentary committees and the other a parliamentary gender quota. The Pacific Islands region presents an important cultural context worthy of exploration: Parliaments are not only overwhelmingly male-dominated, but many are also derivative of hegemonic masculinist cultures evident in the Westminster tradition, albeit hybridized with local political traditions. We compare and contrast the process by which these reforms were developed and implemented in each country and examine the extent to which they can be considered effective mechanisms for addressing gender inequalities. We find that the extent to which these reforms are sustainable and transformative depends on local contexts, local actors, and locally derived solutions. Specifically, the culturally relevant process of contesting the gender quota in Samoa constitutionally, electorally, and through the courts has localised and thereby legitimised this globally endorsed reform. By contrast, gender mainstreaming in Fiji’s parliamentary committees has been little more than a “tick-a-box” exercise, having had limited engagement from the political elite under a relatively autocratic regime.

Climate Dynamics over Kerala, India: Insight from a Century-long Temperature and Rainfall Data Analysis

Historical climate data analysis is of great significance in climate change adaptation and mitigation planning at global as well as regional levels. This article attempted to study the long-term trends of temperature and rainfall across the districts in Kerala, India. CRU monthly time series data of rainfall and temperature data spanning from 1901-2022 were used for the analysis. Mann-Kendall test and Sen’s Slop estimator were applied to detect the presence and magnitude of the trend, and Pettitt’s homogeneity test was used to find the climate change point in temperature time series data. The analysis found a significant and positive temperature trend across all districts in Kerala, with temperature increases ranging from 0.0086°C/year to 0.0102°C/year. In terms of rainfall trends, June and January experienced a significant decrease, while July and September saw a significant increase over the years. The year 1976 was identified as the point of climate change. It was observed that there was an increase in the southwest and Northeast monsoons in the post-period, with higher variability in the latter. Winter rainfall notably decreased during the post-period. The variability in climate parameters identified in this study could impact crop cycles and agricultural productivity, requiring further investigation at a micro-level for effective adaptation and mitigation strategies for the state.

Trends in statin use for the primary prevention of atherosclerotic cardiovascular disease among US adults by demographic characteristics, 1999-2020.

Atherosclerotic cardiovascular disease (ASCVD) is a leading cause of mortality worldwide. Statins, which are effective in preventing ASCVD, are underused, particularly for primary prevention. This study examined trends in statin use for primary ASCVD prevention from 1999 to 2020, focusing on demographic variations. Utilizing data from the National Health and Nutrition Examination Survey, the present study includes individuals aged 18 years and older who had a greater than 10% risk of ASCVD over 10 years, and excluded patients with existing ASCVD. Subgroup analyses by demographic categories were performed. We calculated the changes in statin usage and used linear and quadratic tests to assess the linear and nonlinear trends in those changes. A total of 10,037 participants were included. Statin usage increased from 16.16% in 1999 to 36.24% in 2010, and 41.74% in 2020 (quadratic P-value < 0.001). In the 18-44 years age group, statin usage increased from 2.52% in 1999 to 8.14% in 2020 (linear P-value = 0.322), showing no significant linear trend. In the "never-married" group, statin usage increased from 19.16% in 1999 to 30.05% in 2020 (linear P-value = 0.256). Statin usage has shown a positive trend among populations requiring primary prevention for ASCVD. Currently, health policies are proving effective. However, the overall statin usage rate remains less than 50%. Additionally, young and never-married individuals should also receive special attention regarding statin usage as primary treatment for ASCVD.

First Analyses of the TIMELINE AVHRR SST Product: Long-Term Trends of Sea Surface Temperature at 1 km Resolution across European Coastal Zones

Coastal areas are among the most productive areas in the world, ecologically as well as economically. Sea Surface Temperature (SST) has evolved as the major essential climate variable (ECV) and ocean variable (EOV) to monitor land–ocean interactions and oceanic warming trends. SST monitoring can be achieved by means of remote sensing. The current relatively coarse spatial resolution of established SST products limits their potential in small-scale, coastal zones. This study presents the first analysis of the TIMELINE 1 km SST product from AVHRR in four key European regions: The Northern and Baltic Sea, the Adriatic Sea, the Aegean Sea, and the Balearic Sea. The analysis of monthly anomaly trends showed high positive SST trends in all study areas, exceeding the global average SST warming. Seasonal variations reveal peak warming during the spring, early summer, and early autumn, suggesting a potential seasonal shift. The spatial analysis of the monthly anomaly trends revealed significantly higher trends at near-coast areas, which were especially distinct in the Mediterranean study areas. The clearest pattern was visible in the Adriatic Sea in March and May, where the SST trends at the coast were twice as high as that observed at a 40 km distance to the coast. To validate our findings, we compared the TIMELINE monthly anomaly time series with monthly anomalies derived from the Level 4 CCI SST anomaly product. The comparison showed an overall good accordance with correlation coefficients of R &gt; 0.82 for the Mediterranean study areas and R = 0.77 for the North and Baltic Seas. This study highlights the potential of AVHRR Local Area Coverage (LAC) data with 1 km spatial resolution for mapping long-term SST trends in areas with high spatial SST variability, such as coastal regions.

On the persistence and related mechanisms for day–night compound humid heat extremes in the Northern Hemisphere

Hot extremes pose adverse impacts on human health and ecosystem, leading to aggravated damage when they combine high-humidity and occur in the both daytime and nighttime. Although considerable studies have focused on hot extremes, understandings about day–night Compound humid heat (quantified by Moist Enthalpy) Extremes (CMEEs) are still lacking. This work investigates their frequency, linear trends and temporal persistence in the Northern Hemisphere, and two typical vulnerable regions are selected as Central Europe (CE) and the Arabian Peninsula (AP), both exhibiting high frequency and positive trends, but with contrasting persistence, which is quantified by the bivariate Dynamical System method. Results reveal their regional dependence and physical processes: the dual importance of sensible and latent heat in CE is attributed to the combination of an anomalous anticyclone and evaporation, whereas the dominance of latent heat in AP is largely owing to the convective precipitation. CMEEs in AP can be further divided into two groups with distinct persistence, and this disparity actually depends on the preceding precipitation duration and its associated water vapor supply.

Twenty-Year Climatology of Solar UV and PAR in Cyprus: Integrating Satellite Earth Observations with Radiative Transfer Modeling

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and reanalysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, captures the nuanced dynamics of Cyprus’s atmospheric conditions. With a temporal resolution of 15 min and a spatial of 0.05° × 0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models’ accuracy but also highlights its proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), ranging from −2 to −4% per decade, have been found in autumn, especially marked in the island’s northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of −2 to −3% per decade, which were found in spring, do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the day light integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

Decline in Ice Coverage and Ice-Free Period Extension in the Kara and Laptev Seas during 1979–2022

The duration of ice-free periods in different parts of the Arctic Ocean plays a great role in processes in the climate system and defines the most comfortable sea ice conditions for economic activity. Based on satellite-derived sea ice concentration data acquired by passive microwave instruments, we identified the spatial distribution of the dates of sea ice retreat (DOR), dates of sea ice advance (DOA), and the resulting ice-free period duration (IFP) between these days for the Kara and Laptev seas during 1979–2022. The monthly decline in sea ice extent was detected from June to October in both seas, i.e., during the whole ice-free period. The annual mean sea ice extent during 2011–2021 decreased by 19.0% and 12.8% relative to the long-term average during 1981–2010 in the Kara and Laptev seas, respectively. The statistically significant (95% confidence level) positive IFP trends were detected for the majority of areas of the Kara and Laptev seas. Averaged IFP trends were estimated equal to +20.2 day/decade and +16.2 day/decade, respectively. The observed DOR tendency to earlier sea ice melting plays a greater role in the total IFP extension, as compared to later sea ice formation related to the DOA tendency. We reveal that regions of inflow of warm Atlantic waters to the Kara Sea demonstrate the largest long-term trends in DOA, DOR, and IFP associated with the decrease in ice coverage, that highlights the process of atlantification. Also, the Great Siberian Polynya in the Laptev Sea is the area of the largest long-term decreasing trend in DOR.

Trend analysis of extreme rainfall indices from CHIRPS precipitation estimates over the Lake Tana sub-basin, Abbay Basin of Ethiopia.

Ethiopia is among the African nations most susceptible to climate change because of its frequent droughts and heavy rainfall. Therefore, hydrological and water management problems require an investigation of regional variability and extreme rainfall patterns. This study analyzed the spatiotemporal trends of extreme rainfall in the Lake Tana sub-basin (LTSB) of Ethiopia's upper Blue Nile basin (UBNB) between 1981 and 2019. The trend and geographic patterns of ten extreme rainfall indices are evaluated using high-resolution data from Climate Hazards Group InfraRed Precipitation Stations (CHIRPS). The researcher used RClimDex, an R software tool, to analyze the ten severe rainfall indices. The variability of the extreme rain indices was also assessed by applying the standard anomaly index (SAI). The trend analysis shows that the majority of rainfall indices decreased in the majority of station locations. Among the rainfall locations, the decreasing trend was only significant in 40% consecutive wet days (CWD), 13.33% (R95p and R99p), and 6.66% highest rainfall amount in a 1-day period (RX1day). In contrast, significant positive patterns were revealed in the incidence of rainfall events of number of heavy precipitation days (R10mm), annual total wet day rainfall (PRCPTOT), and consecutive dry days (CDD), with significant positive trends of 26.66% (R10mm) and 40% (PRCPTOT). Furthermore, a spatial distribution result of extreme rainfall trends reveals considerable variations between stations location. Thus, these findings point to the necessity of creating adaptation and mitigation plans for climate change variability within the sub-basin.

Analyzing vegetation health dynamics across seasons and regions through NDVI and climatic variables

This study assesses the relationships between vegetation dynamics and climatic variations in Pakistan from 2000 to 2023. Employing high-resolution Landsat data for Normalized Difference Vegetation Index (NDVI) assessments, integrated with climate variables from CHIRPS and ERA5 datasets, our approach leverages Google Earth Engine (GEE) for efficient processing. It combines statistical methodologies, including linear regression, Mann–Kendall trend tests, Sen's slope estimator, partial correlation, and cross wavelet transform analyses. The findings highlight significant spatial and temporal variations in NDVI, with an annual increase averaging 0.00197 per year (p < 0.0001). This positive trend is coupled with an increase in precipitation by 0.4801 mm/year (p = 0.0016). In contrast, our analysis recorded a slight decrease in temperature (− 0.01011 °C/year, p < 0.05) and a reduction in solar radiation (− 0.27526 W/m2/year, p < 0.05). Notably, cross-wavelet transform analysis underscored significant coherence between NDVI and climatic factors, revealing periods of synchronized fluctuations and distinct lagged relationships. This analysis particularly highlighted precipitation as a primary driver of vegetation growth, illustrating its crucial impact across various Pakistani regions. Moreover, the analysis revealed distinct seasonal patterns, indicating that vegetation health is most responsive during the monsoon season, correlating strongly with peaks in seasonal precipitation. Our investigation has revealed Pakistan's complex association between vegetation health and climatic factors, which varies across different regions. Through cross-wavelet analysis, we have identified distinct coherence and phase relationships that highlight the critical influence of climatic drivers on vegetation patterns. These insights are crucial for developing regional climate adaptation strategies and informing sustainable agricultural and environmental management practices in the face of ongoing climatic changes.

#1806 Cycling is safe – effect of intradialytic cycle ergometry on cerebral oxygenation and cognitive function – a pilot study

Abstract Background and Aims Patients on chronic hemodialysis benefit from intradialytic exercise with improvements in endurance, muscle strength and health-related quality of life. It is not known whether the increased oxygen demand during intradialytic exercise negatively affects cerebral oxygenation and cerebral function. The aim of the study was to assess the risk of cerebral undersupply by measuring cerebral oxygenation, perfusion and cognitive function during and after intradialytic ergometer training. Method Twelve patience on maintenance hemodialysis (HD) trice weekly were included in the study. In an initial ramp test, using bed cycle ergometer, we first determined the maximum physical strength (Pmax) at the level of exhaustion (HD A). Then, one hour after start of a second HD (HD B), patients performed 40%, 50% and 60% of Pmax for 6 min. Pulmonary function tests, blood volume (BVM), cardiac output (by electrical cardiometry), regional cerebral oxygen saturation (rSO2) (by near-infrared spectroscopy) and cerebral blood flow (CBF, by Doppler sonography) were measured. The relative changes in rSO2, CBF and hematocrit were used to calculate cerebral oxygen supply (DO2). Cognitive tests (Stroop, Trail Making and Mini Addenbrookes Cognitive Examination Test) were performed before and after HD sessions with and, as controls, without ergometry (HD-C). Results Median age was 68 (42-85) years, 9/12 were male, complete data set was obtained in 10 patients. During step test exercise (HD B), at the highest exercise level (according to Borg (1-10) 6.75 ± 2.9), rSO2 increased (+6 ± 9%, p=0.034) without a significant change in CBF. In the meantime, relative blood volume decreased during ergometry (-5.8 ± 2.73%; p=0.002), causing a temporary increase of hematocrit. Despite a small decrease in CBF in 3 patients, the mean change of rSO2, CBF and hematocrit always had a positive trend in all patients, as a surrogate of stable cerebral oxygen supply (Table 1). In comparative cognitive tests (B vs. C), we observed no significant changes in cognitive functions. Conclusion In this pilot study, intradialytic bed-cycle ergometry during the first hour of HD for &amp;lt;20 min at 40-60% of patients’ individual maximum intensity had no negative effects on cerebral oxygenation and function. Specific studies testing the safety intradialytic exercise with different conditions, such as increasing intensity or duration, are needed.

River flow in the near future: a global perspective in the context of a high-emission climate change scenario

Abstract. There is high confidence that global warming intensifies all components of the global water cycle. This work investigates the possible effects of global warming on river flows worldwide in the coming decades. We conducted 18 global hydrological simulations to assess how river flows are projected to change in the near future (2015–2050) compared to the recent past (1950–2014). The simulations are forced by runoff from the High Resolution Model Intercomparison Project (HighResMIP) CMIP6 global climate models (GCMs), which assume a high-emission scenario for the projections. The assessment includes estimating the signal-to-noise (S/N) ratio and the time of emergence (ToE) of all the rivers in the world. Consistently with the water cycle intensification, the hydrological simulations project a clear positive global river discharge trend from ∼2000 that emerges beyond the levels of natural variability and becomes “unfamiliar” by 2017 and “unusual” by 2033. Simulations agree that the climate change signal is dominated by strong increases in the flows of rivers originating in central Africa and South Asia and those discharging into the Arctic Ocean, partially compensated for by the reduced flow projected for Patagonian rivers. The potential implications of such changes may include more frequent floods in central African and South Asian rivers, driven by the projected magnification of the annual cycles with unprecedented peaks, a freshening of the Arctic Ocean from extra freshwater release, and limited water availability in Patagonia given the projected drier conditions of its rivers. This underscores the critical need for a paradigm shift in prioritizing water-related concerns amidst the challenges of global warming.

Investigating the Key Factors Affecting Public Transport Ridership in Developing Countries through Structural Equation Modeling

Every country requires efficient public transportation to reduce the reliance on motor vehicles, decrease harmful emissions and noise pollution, and, most importantly, provide accessible transportation for urban populations with limited resources. Yet, several challenges hinder the efficiency of the public transportation system, affecting factors like daily ridership, infrastructure, revenue, and operations. Therefore, this research investigated barriers and their impact on the daily ridership of rail transit services, especially in densely populated areas characterized by high automobile usage, inadequate pedestrian facilities, and limited connectivity to other transportation modes. To accomplish this goal, a self-administered questionnaire was developed, and a survey was conducted to collect responses from commuters at various public transport hubs. Structural equation modeling (SEM) was used to analyze data gathered from a sample of 1000 participants. The findings from the SEM model indicated a positive correlation between Instrumental Attractiveness (IA) and Facility Design and Operation (FDO) with daily travel. Conversely, Service and Information (SI) along with Environmental Comfort (EC) exhibited a negative correlation with daily travel. Private sector employees without personal vehicles and a monthly income below fifty thousand exhibited a strong preference for public transport. Individuals with higher incomes who owned vehicles showed lower preferences towards public transport usage. The main contributors to low ridership in public transport included poor connectivity with metro and feeder buses, lack of availability of discount tickets, insufficient seating at stations, and inadequate route map information. Gasoline prices have a notable impact on daily ridership too, as higher fuel prices tend to attract more travelers to use public transport. The ridership data demonstrate a positive trend in response to increased gasoline prices. The findings from this study are useful for transportation engineers, practitioners, planners, and policymakers.

#541 Secular trends in CKD and ESKD mortality rates in the United States, 2011–2021

Abstract Background and Aims Patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD) have a considerably higher mortality than the general population. Nevertheless, in the United States, mortality rates in the CKD and ESKD populations have declined steadily over the last decade until the onset of the COVID-19 pandemic [1]. Through a quantitative analysis of the age- and time-dependence of mortality rates in renal patient populations in the US, we aimed at quantifying trends in life expectancy between 2011 and 2021. Method We analysed CKD and ESKD mortality rates as reported in the US Renal Data System's (USRDS) Annual Data Report 2023 for the years 2011–2021 [1]. There, CKD mortality rates were determined from a Medicare 5% random sample (CKD stages 4 and 5) for patients aged 65 and above (“CKD 65+”). ESKD mortality rates were obtained from the USRDS database; we analysed data for patients aged 45 and above (“ESKD 45+”). We used fits of analytical functions to the data to hosphorzed their dependence on age and time. This technique enables us to extract quantitative trends in time by tracking fit parameters. Results We found that for each year between 2011 and 2021, mortality rates in the adult CKD and ESKD populations in the US largely conformed to an exponential dependence on patient age, $m = {{m}_0}( t ){{2}^{a/{{\Delta }}a}}$, that is, mortality rates doubled over constant age increments ${{\Delta }}a$. While overall, mortality rates were declining between 2011 and 2019, the age increments over which mortality rates doubled were nearly identical for each year (CKD 65+: ${{\Delta }}a$ = 10.5 ± 0.4 y, ESKD 45+: ${{\Delta }}a$ = 15.1 ± 0.9 y; mean ± SD). Exploiting this simple relationship, we found that the changes in mortality rates over time could largely be reduced to a steady right-shift of an otherwise unchanged mortality curve over time (shown for the ESKD 45+ group in Fig. 1a). By quantifying this right-shift over time, we estimated the gain in 1-year survival probability for different ages (Fig. 1b,c). This gain in survival does not necessarily imply a prolonged time on renal replacement therapy (RRT), e.g., when patients concomitantly start RRT at a later age. The onset of the COVID-19 pandemic in 2020 coincides with an abrupt cessation of these positive trends, reflected by a setback of mortality curves close to those in the year 2016 for the CKD population and to before 2011 for the ESKD population. Conclusion Public health data on CKD and ESKD show systematic dependencies of mortality rates on age and time, which can be revealed using analytical parameterisations of the data. Using this technique, we can capture trends in mortality rates and 1-year survival probability in adult kidney patient populations in the US during the years 2011–2019 and can quantify the abrupt cessation of these trends during the onset of the COVID-19 pandemic. In the CKD population we observed a setback of mortality rates close to those in the year 2016 with the onset of the pandemic. Changes in mortality rates in the ESKD population were more distinct. Specifically in elderly patients (aged 65 and above) 1-year survival dropped abruptly to levels lower than those observed in the previous decade.

Space-Time Variability of Drought Characteristics in Pernambuco, Brazil

Drought is the most complex natural hazard that can occur over large spatial scales and during long time periods. It affects more people than any other natural hazard, particularly in areas with a dry climate, such as the semiarid region of the Brazilian Northeast (NEB), which is the world’s most populated dry area. In this work, we analyzed trends and the spatial distribution of drought characteristics (frequency, affected area, and intensity) based on the Standardized Precipitation Index (SPI) on annual (SPI-12) and seasonal (SPI-3) scales. The study used monthly precipitation data recorded between 1962 and 2012 at 133 meteorological stations in Pernambuco State, Brazil, which is located in the eastern part of the NEB and has more than 80% of its territory characterized by a semiarid climate. The regions of Sertão, Agreste, and Zona da Mata of Pernambuco were considered for comparison. The Mann–Kendall and Sen’s slope tests were used to detect the trend and determine its magnitude, respectively. The results indicated that annual droughts in the state of Pernambuco became more frequent from the 1990s onwards, with summer having the greatest spatial coverage, followed by winter, autumn, and spring. Sertão presented a greater number of stations with a significant positive trend in drought frequency. Regarding the drought-affected area, global events occurred in a greater number of years on an annual scale and during the summer. Trend analysis pointed to an increase in areas with drought events on both scales. As for the drought intensity, the entire state of Pernambuco experienced drought events with high intensity during the autumn. The relationship between drought characteristics indicated an increase in the affected area as the result of an increase in drought intensity.

Can We Improve the Technique of Pelvic Floor Muscle Exercises in Postmenopausal Women Using a Single Electromyography Biofeedback Session? An Experimental Study

Background: The aim of this study was to assess the effect of a single session of EMG biofeedback in a group of postmenopausal women on improving technique in pelvic floor muscle (PFM) contractions (exercises). Methods: Sixty-two women aged 60 to 85 years (69 ± 4; mean ± SD) participated in the study. We assessed the technique of PFM exercises via surface electromyography (EMG) using a vaginal probe. A single assessment sequence consisted of 11 exercises involving the conscious contraction of the PFM, during which the order of activation for selected muscles was determined. We then awarded scores for exercise technique on a scale from 0 to 4, where 4 represented the best technique and 0 represented no activation of PFMs. In the second assessment, we used a biofeedback method to teach PFM exercise technique. Results: In total, 32% (n = 20) of the participants were unable to correctly perform the first PFM contraction, scoring 0.9 ± 0.79. After a single EMG biofeedback session, these women received 1.7 ± 1.08 scores (p = 0.003). In the tenth exercise, there was also a statistically significant improvement between the first (baseline) and second assessment (1.7 ± 1.34 and 2.15 ± 1.09, respectively; p = 0.037). For the remaining exercises, the results were not statistically significant, but we observed a positive trend of change. Conclusions: The use of a single EMG biofeedback session is an effective method of improving technique in PFM exercises in a group of women who initially performed them incorrectly.

Genetic progress in cowpea [Vigna unguiculata (L.) Walp.] stemming from breeding modernization efforts at the International Institute of Tropical Agriculture.

Genetic gain has been proposed as a quantifiable key performance indicator that can be used to monitor breeding programs' effectiveness. The cowpea breeding program at the International Institute of Tropical Agriculture (IITA) has developed and released improved varieties in 70 countries globally. To quantify the genetic changes to grain yield and related traits, we exploited IITA cowpea historical multi-environment trials (METs) advanced yield trial (AYT) data from 2010 to 2022. The genetic gain assessment targeted short duration (SD), medium duration (MD), and late duration (LD) breeding pipelines. A linear mixed model was used to calculate the best linear unbiased estimates (BLUE). Regressed BLUE of grain yield by year of genotype origin depicted realized genetic gain of 22.75 kg/ha/year (2.65%), 7.91 kg/ha/year (0.85%), and 22.82 kg/ha/year (2.51%) for SD, MD, and LD, respectively. No significant gain was realized in 100-seed weight (Hsdwt). We predicted, based on 2022 MET data, that recycling the best genotypes at AYT stage would result in grain yield gain of 37.28 kg/ha/year (SD), 28.00 kg/ha/year (MD), and 34.85 kg/ha/year (LD), and Hsdwt gain of 0.48g/year (SD), 0.68g/year (MD), and 0.55g/year (LD). These results demonstrated a positive genetic gain trend for cowpea, indicating that a yield plateau has not yet been reached and that accelerated gain is expected with the recent integration of genomics in the breeding program. Advances in genomics include the development of the reference genome, genotyping platforms, quantitative trait loci mapping of key traits, and active implementation of molecular breeding.

Insights from modelling sixteen years of climatic and fumonisin patterns in maize in South Africa

Mycotoxin contamination of agricultural commodities is a global public health problem that has remained elusive to various mitigation approaches, particularly in developing countries. Climate change and its impact exacerbates South Africa’s vulnerability to mycotoxin contamination, and significantly threatens its’s food systems, public health, and agro-economic development. Herein we analyse sixteen years (2005/2006–2020/2021) of annual national meteorological data on South Africa which reveals both systematic and erratic variability in critical climatic factors known to influence mycotoxin contamination in crops. Within the same study period, data on fumonisin (FB) monitoring show clear climate-dependent trends. The strongest positive warming trend is observed between 2018/2019 and 2019/2020 (0.51 °C/year), and a strong positive correlation is likewise established between FB contamination and temperature (r ranging from 0.6 to 0.9). Four machine learning models, viz support vector machines, eXtreme gradient boosting, random forest, and orthogonal partial least squares, are generalized on the historical data with suitable performance (RMSE as low as 0.00). All the adopted models are able to predict future FB contamination patterns with reasonable precision (R2 ranging from 0.34 to 1.00). The most important model feature for predicting average FB contamination (YA) is the historical pattern of average FB contamination in maize within the region (ΣFBs_avg). The two most significant features in modelling maximum FB contamination (YM) are minimum temperature from the CMIP6 data (Pro_tempMIN) and observed precipitation from the CRU data (O_prep). Our study provides strong evidence of the impact of climate change on FB in South Africa and reiterates the significance of machine learning modelling in predicting mycotoxin contamination in light of changing climatic conditions, which could facilitate early warnings and the adoption of relevant mitigation measures that could help in mycotoxin risk management and control.