Функціональні зв'язки між ефектами води Нафтуся на канальцеву секреторно-транспортну та імунну системи щурів. Повідомлення 2: Канальцева секреція і параметри спленоцитограми та гемолімфоаденоцитограми

В рамках концепции об общности механизмов функционирования канальцевой секреторно-транспортной и фагоцитарно-лимфоидной систем выявлены существенные связи между скоростью почечной канальцевой секреции и параметрами фагоцитоза, лейкоцитограммы крови, стеноцитогаммы и гемолимфоаденоцитограммы крыс в условиях курсового напаивания их водой Нафтуся per se и в сочетании с цитостатиком или анаболиком.It is shown that increase of canalicular secretion in rats becaused by drinking of water Naftussya accompanied increase massa of haemolymphatic node and contents in its of endothelio-, reticulo-, lymphocytes, eosinophyles and macrophages, blood level lymphocytes, monocytes and segmental nucleare neutrophyles but decrease activity and completion of phagocytose of neutrophyles and level of lymphoblastes in splenocytogramme. The using of cytostatic drug abolishes but anabolic drug potentiates both activating and inhibiting influence of water Naftussya

Landscape-based nutrient application in wheat and teff mixed farming systems of Ethiopia: farmer and extension agent demand driven approach

Introduction: Adapting fertilizer use is crucial if smallholder agroecosystems are to attain the sustainable development goals of zero hunger and agroecosystem resilience. Poor soil health and nutrient variability characterize the smallholder farming systems. However, the current research at the field scale does not account for nutrient variability across landscape positions, posing significant challenges for targeted nutrient management interventions. The purpose of this research was to create a demand-driven and co-development approach for diagnosing farmer nutrient management practices and determining landscape-specific (hillslope, mid-slope, and foot slope) fertilizer applications for teff and wheat. Method: A landscape segmentation approach was aimed to address gaps in farm-scale nutrient management research as well as the limitations of blanket recommendations to meet local nutrient requirements. This approach incorporates the concept of interconnected socio-technical systems as well as the concepts and procedures of co-development. A smart mobile app was used by extension agents to generate crop-specific decision rules at the landscape scale and forward the specific fertilizer applications to target farmers through SMS messages or print formats. Results and discussion: The findings reveal that farmers apply more fertilizer to hillslopes and less to mid- and foot slopes. However, landscape-specific fertilizer application guided by crop-specific decision rules via mobile applications resulted in much higher yield improvements, 23% and 56% at foot slopes and 21% and 6.5% at mid slopes for wheat and teff, respectively. The optimized net benefit per hectare increase over the current extension recommendation was $176 and$333 at foot slopes and $159 and$64 at mid slopes for wheat and teff (average of $90 and$107 for wheat and teff), respectively. The results of the net benefit-to-cost ratio (BCR) demonstrated that applying landscape-targeted fertilizer resulted in an optimum return on investment ($10.0 net profit per$1.0 investment) while also enhancing nutrient use efficiency across the three landscape positions. Farmers are now cognizant of the need to reduce fertilizer rates on hillslopes while increasing them on parcels at mid- and foot-slope landscapes, which have higher responses and profits. As a result, applying digital advisory to optimize landscape-targeted fertilizer management gives agronomic, economic, and environmental benefits. The outcomes results of the innovation also contribute to overcoming site-specific yield gaps and low nutrient use efficiency, they have the potential to be scaled if complementing innovations and scaling factors are integrated

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere

Prevalence, years lived with disability, and trends in anaemia burden by severity and cause, 1990-2021: findings from the Global Burden of Disease Study 2021

Background Anaemia is a major health problem worldwide. Global estimates of anaemia burden are crucial for developing appropriate interventions to meet current international targets for disease mitigation. We describe the prevalence, years lived with disability, and trends of anaemia and its underlying causes in 204 countries and territories. Methods We estimated population-level distributions of haemoglobin concentration by age and sex for each location from 1990 to 2021. We then calculated anaemia burden by severity and associated years lived with disability (YLDs). With data on prevalence of the causes of anaemia and associated cause-specific shifts in haemoglobin concentrations, we modelled the proportion of anaemia attributed to 37 underlying causes for all locations, years, and demographics in the Global Burden of Disease Study 2021. Findings In 2021, the global prevalence of anaemia across all ages was 24·3% (95% uncertainty interval [UI] 23·9–24·7), corresponding to 1·92 billion (1·89–1·95) prevalent cases, compared with a prevalence of 28·2% (27·8–28·5) and 1·50 billion (1·48–1·52) prevalent cases in 1990. Large variations were observed in anaemia burden by age, sex, and geography, with children younger than 5 years, women, and countries in sub-Saharan Africa and south Asia being particularly affected. Anaemia caused 52·0 million (35·1–75·1) YLDs in 2021, and the YLD rate due to anaemia declined with increasing Socio-demographic Index. The most common causes of anaemia YLDs in 2021 were dietary iron deficiency (cause-specific anaemia YLD rate per 100 000 population: 422·4 [95% UI 286·1–612·9]), haemoglobinopathies and haemolytic anaemias (89·0 [58·2–123·7]), and other neglected tropical diseases (36·3 [24·4–52·8]), collectively accounting for 84·7% (84·1–85·2) of anaemia YLDs. Interpretation Anaemia remains a substantial global health challenge, with persistent disparities according to age, sex, and geography. Estimates of cause-specific anaemia burden can be used to design locally relevant health interventions aimed at improving anaemia management and prevention. Funding Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Attitude and perceptions of local communities towards the conservation value of gibe Sheleko national park, Southwestern Ethiopia

The study assessed the attitude and perceptions of the local communities towards Gibe Sheleko National Park. The data was collected from three districts of Gurage Zone. Ten sample kebeles of the selected districts were selected by purposive sampling method based on the level interaction, distance from the park, and dependency on the park. The sample size of the respondents was 5% of the total households from each selected kebeles. Household survey, key informant interview, field observation, and focus group discussion were employed to collect the data. Data was analyzed by SPSS version 23 software. Descriptive statistics and Chi-square test were used to analysis major determinant factors for perception and attitude of the local communities. The perception and attitude of the local communities towards the conservation values of Gibe Sheleko National Park showed a significant difference in education level, sex of respondents, distance from the park, and land owning inside or adjoin the park. Therefore, it can be concluded that sex, distance of settlement from the park, academic level and land owning inside or adjoining the park were the major determinant factors that influence perception and attitude of the local communities. Attending high level of education, far proximity from the park and male communities better understood the importance of wildlife and park. Therefore, to encourage partnership with adjacent community and implement conservation measure and awareness creation for local communities by considering these factors that affect on the attitude and perception of local communities towards Gibe Sheleko National Park

Compact 8×8 SOA-Based Optical WDM Space Switch in Generic InP Technology

As the global internet protocol (IP) traffic volume growth puts more pressure on network connectivity, bandwidth and latency requirements, crucial network elements such as switches need continuous improvement. To this end, we report a monolithically integrated, ultra-compact 8×8 optical space switch based on semiconductor optical amplifier (SOA) gates, utilizing ultra-compact bends and denser SOA placement and demonstrating a strictly non-blocking broadcast and select (B&S) switch architecture on-chip. The switch circuitry comprises 80 SOAs, 112 multimode interference (MMI) splitters, and hundreds of waveguide bends and crossings integrated onto a 4.6×8 mm2 generic indium phosphide (InP) die with I/O access on the same side. In addition, the SOA waveguide geometry is specifically optimized to improve output saturation power by 2 dB and enable WDM operation. The physical layer characterization shows lossless operation on-chip due to the three SOAs in a path that provides enough gain to compensate for on-chip passive losses. The best-case OSNR is higher than 40 dB. We perform static data signal routing with four-channel wavelength division multiplexed (WDM) data signals at 25 Gb/s and 35 Gb/s, resulting in a worst-case 2 dB power penalty on receiver sensitivity. Additionally, we dynamically switch data signals at bit rates up to 35 Gb/s obtaining a power penalty similar to the static routing. The recorded rising and falling times are 4 and 6.4 ns, respectively, suggesting this chip is suitable for packet-scale fast switching applications