Does It Really Work? Re-Assessing the Impact of Pre-Departure Cross-Cultural Training on Expatriate Adjustment

Cultural adjustment is considered to be a prerequisite for expatriate success abroad. One way to enhance adjustment is to provide employees with knowledge and awareness of appropriate norms and behaviors of the host country through cross-cultural training (CCT). This article analyzes the impact of pre-departure CCT on expatriate adjustment and focuses on variations in participation, length and the comprehensiveness of training. Unlike previous research, the study focuses on the effectiveness of pre-departure CCT for non-US employees expatriated to a broad range of host country settings. Employing data from 339 expatriates from 20 German Multinational Corporations (MNCs) the study finds CCT has little if any effect on general, interactional or work setting expatriate adjustment. However, a significant impact of foreign language competence was found for all three dimensions of expatriate adjustment. We used interviews with 20 expatriates to supplement our discussion and provide further implications for practice

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

Nomenclature of the finer branches of the biliary tree: Canals, ductules, and ductular reactions in human livers

The work of liver stem cell biologists, largely carried out in rodent models, has now started to manifest in human investigations and applications. We can now recognize complex regenerative processes in tissue specimens that had only been suspected for decades, but we also struggle to describe what we see in human tissues in a way that takes into account the findings from the animal investigations, using a language derived from species not, in fact, so much like our own. This international group of liver pathologists and hepatologists, most of whom are actively engaged in both clinical work and scientific research, seeks to arrive at a consensus on nomenclature for normal human livers and human reactive lesions that can facilitate more rapid advancement of our field. (HEPATOLOGY 2004; 39:1739–1745.) The fine detail of normal liver microanatomy is not well understood.1, 2 This is true whether discussing hepatic vasculature, bile ducts, stroma and matrix, innervation, or lymphatics. Some points are known, but gaps remain. The distal branches of the biliary tree are reasonably well defined: the common bile duct arises from confluence of the right and left hepatic ducts, which arise from segmental ducts, which arise from septal ducts arising from interlobular ducts.3 It is known that these interlobular ducts arise from still smaller cholangiocyte-lined structures and that the lumina of these in turn are in structural continuity with the lumen of hepatocellular bile canaliculi. But the terms used for these smallest, most proximal structures have been confusing

Isolation, Identification and Molecular Characterization of Brucella abortus from Bovines

Brucellosis is an important zoonosis and a significant cause of reproductive losses in animals. Abortion, placentitis, epididymitis and orchitis are the most common clinical manifestations in animals. The present study a total of 168 clinical samples were collected from buffaloes (87) and cattle (81). All clinical samples were processed by cultural isolation on Brucella agar medium (BAM) with selective antibiotic supplements and genus specific PCR using B4/B5 (223bp) and F4/R2 (905bp) primer. Out of 168 clinical samples 15 samples yielded Brucella isolates by cultural isolation and 19 samples positive for Brucella organism by genus specific PCR. All genus specific PCR positive 19 samples also positive by Species specific PCR based on omp31, B. abortus +IS711 (498bp) primer. Amplicon of 498bp by B. abortus +IS711 primers indicates that all nineteen samples of cattle and buffaloes were found to be Brucella abortus