Earliest evidence for the ivory trade in southern Africa : isotopic and ZooMS analysis of seventh-tenth century AD ivory from KwaZulu-Natal

KwaGandaganda, Ndondondwane and Wosi were major Early Farming Community settlements in what is today the KwaZulu-Natal province of South Africa. These sites have yielded, among other remains, abundant evidence of ivory and ivory working dating to the seventh–tenth centuries ad, pre-dating by approximately 200 years the better-known ivory artefacts from sites in the Limpopo River Valley and surrounding regions. We report the results of carbon, nitrogen and strontium isotope analysis to explore the origins and procurement of this ivory, in combination with Zooarchaeology by Mass Spectrometry (ZooMS) to identify the species of animals from which it was derived. All of the ivory studied using ZooMS was elephant, despite the presence of hippopotamus remains on all three sites. Some ivory was probably obtained from elephant herds that lived close to the sites, in the densely wooded river valleys favoured by both elephants and early farmers. Other material came from savannah environments further afield. Ivory found at these three sites was drawn from different catchments, implying a degree of landscape/resource partitioning even at this early stage. These communities clearly invested substantial effort in obtaining ivory from across the region, which speaks to the importance of this commodity in the economy of the time. We suggest that some ivory items were for local use, but that some may have been intended for more distant markets via Indian Ocean trade

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression.

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection

Mapping divided households and residency changes: the effect of couple separation on sexual behavior and risk of HIV infection

Using census data we identify geographic patterns in residency changes in Lesotho over a decade. Using kriging to spatially interpolate data from 8,510 households we identify regions where households have members temporarily living away from home (divided households). Further, using a multivariate analysis and data from 2,026 couples we determine whether a partners’ absence increases the likelihood of having extramarital partners and/or risk of HIV infection. Approximately 40% of individuals moved between 2001 and 2011; mainly to, and within, urbanized regions. Many households are divided: ~40% have members elsewhere in Lesotho, ~30% in South Africa (SA). Geographic patterns are apparent; they differ based on where the household member is living. Many couples were temporarily separated: ~50% of wives, ~20% of husbands. Separation was not a risk factor for HIV. Only men were more likely to have extramarital partners if their spouse was away: ~1.5 times if in Lesotho, ~3 times if in SA. The high degree of geographic mixing necessitates synchronizing interventions within Lesotho, and with SA, to successfully reduce transmission. It will be challenging to reduce concurrency in men with wives away from home. Our results are generalizable to other sub-Saharan countries where residency changes are common