Reconstruction of heterogeneity through single cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we apply Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.

The inflamed rheumatic joint is a highly heterogeneous and complex tissue with dynamic recruitment and expansion of multiple cell types that interact in multifaceted ways within a localized area. Rheumatoid arthritis synovium has primarily been studied either by immunostaining or by molecular profiling after tissue homogenization. Here, we use Spatial Transcriptomics, where tissue-resident RNA is spatially labeled in situ with barcodes in a transcriptome-wide fashion, to study local tissue interactions at the site of chronic synovial inflammation. We report comprehensive spatial RNA-Seq data coupled to cell type-specific localization patterns at and around organized structures of infiltrating leukocyte cells in the synovium. Combining morphological features and high-throughput spatially resolved transcriptomics may be able to provide higher statistical power and more insights into monitoring disease severity and treatment-specific responses in seropositive and seronegative rheumatoid arthritis.

Reconstruction of heterogeneity through single-cell transcriptional profiling has greatly advanced our understanding of the spatial liver transcriptome in recent years. However, global transcriptional differences across lobular units remain elusive in physical space. Here, we implement Spatial Transcriptomics to perform transcriptomic analysis across sectioned liver tissue. We confirm that the heterogeneity in this complex tissue is predominantly determined by lobular zonation. By introducing novel computational approaches, we enable transcriptional gradient measurements between tissue structures, including several lobules in a variety of orientations. Further, our data suggests the presence of previously transcriptionally uncharacterized structures within liver tissue, contributing to the overall spatial heterogeneity of the organ. This study demonstrates how comprehensive spatial transcriptomic technologies can be used to delineate extensive spatial gene expression patterns in the liver, indicating its future impact for studies of liver function, development and regeneration as well as its potential in pre-clinical and clinical pathology.

Background Understanding of the impacts of climatic variability on human health remains poor despite a possibly increasing burden of vector-borne diseases under global warming. Numerous socioeconomic variables make such studies challenging during the modern period while studies of climate–disease relationships in historical times are constrained by a lack of long datasets. Previous studies have identified the occurrence of malaria vectors, and their dependence on climate variables, during historical times in northern Europe. Yet, malaria in Sweden in relation to climate variables is understudied and relationships have never been rigorously statistically established. This study seeks to examine the relationship between malaria and climate fluctuations, and to characterise the spatio-temporal variations at parish level during severe malaria years in Sweden 1749–1859. Methods Symptom-based annual malaria case/death data were obtained from nationwide parish records and military hospital records in Stockholm. Pearson (rp) and Spearman’s rank (rs) correlation analyses were conducted to evaluate inter-annual relationship between malaria data and long meteorological series. The climate response to larger malaria events was further explored by Superposed Epoch Analysis, and through Geographic Information Systems analysis to map spatial variations of malaria deaths. Results The number of malaria deaths showed the most significant positive relationship with warm-season temperature of the preceding year. The strongest correlation was found between malaria deaths and the mean temperature of the preceding June–August (rs = 0.57, p < 0.01) during the 1756–1820 period. Only non-linear patterns can be found in response to precipitation variations. Most malaria hot-spots, during severe malaria years, concentrated in areas around big inland lakes and southern-most Sweden. Conclusions Unusually warm and/or dry summers appear to have contributed to malaria epidemics due to both indoor winter transmission and the evidenced long incubation and relapse time of P. vivax, but the results also highlight the difficulties in modelling climate–malaria associations. The inter-annual spatial variation of malaria hot-spots further shows that malaria outbreaks were more pronounced in the southern-most region of Sweden in the first half of the nineteenth century compared to the second half of the eighteenth century.

Background: Understanding of the impacts of climatic variability and change on human health, and the spread of diseases, remains poor despite an increasing burden of vector-borne diseases under global warming. Many confounding social variables make such studies challenging during the modern period while studies of climate-disease relationships in historical times are constrained by a lack of long-term data sets. Previous studies of malaria in historical times have revealed an association with climate in northern Europe. Yet, malaria in Sweden in relation to climate variables is understudied and relationships have never been rigorously statistically established. This study seeks to examine the relationship between malaria and climate fluctuations using several data sources, and to characterise the spatio-temporal variations at parish level during severe malaria years in Sweden between 1749 and 1859. Methods: Pearson (rp) and Spearman's rank (rs) correlation analyses were conducted to evaluate inter-annual relationship between malaria deaths, temperature and precipitation. The climate response to larger malaria events was further explored by Superposed Epoch Analysis, and through Geographic Information Systems analysis to map spatial variations of malaria deaths. Results: The number of malaria deaths showed the most significant positive relationship with warm-season temperature of the preceding year, but less significant against precipitation. The strongest correlation was found between malaria deaths and the mean temperature of the preceding June-August (rs=0.57, p<0.01) during the 1756-1820 period. Most malaria hot-spots, during severe malaria years, concentrated in areas around big inland lakes and southern-most Sweden.Conclusions: Increases in malaria transmission, and hence malaria deaths, in Sweden was linked to high summer temperature during the preceding year. This relationship can be established with statistical confidence from parish records in tandem with the long meteorological series. Our results indicate that unusually warm and/or dry summers may have contributed to malaria epidemics, but with non-linear characteristics, highlighting the difficulties in modeling climate-malaria associations. The inter-annual spatial variation of malaria hot-spots further shows that malaria outbreaks were more pronounced in the southern-most region of Sweden in the first half of the nineteenth century compared to the second half of the eighteenth century.