Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions or ad hoc models for the contact process. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

As an essential component of innate immunity, macrophages have multiple functions in both inhibiting or promoting cell proliferation and tissue repair. Diversity and plasticity are hallmarks of macrophages. Classical M1 and alternative M2 activation of macrophages, mirroring the Th1–Th2 polarization of T cells, represent two extremes of a dynamic changing state of macrophage activation. M1-type macrophages release cytokines that inhibit the proliferation of surrounding cells and damage contiguous tissue, and M2-type macrophages release cytokines that promote the proliferation of contiguous cells and tissue repair. M1–M2 polarization of macrophage is a tightly controlled process entailing a set of signaling pathways, transcriptional and posttranscriptional regulatory networks. An imbalance of macrophage M1–M2 polarization is often associated with various diseases or inflammatory conditions. Therefore, identification of the molecules associated with the dynamic changes of macrophage polarization and understanding their interactions is crucial for elucidating the molecular basis of disease progression and designing novel macrophage-mediated therapeutic strategies.

Background Coronavirus disease 2019 (COVID-19) has become a public health emergency. The widely used reverse transcription–polymerase chain reaction (RT-PCR) method has limitations for clinical diagnosis and treatment. Methods A total of 323 samples from 76 COVID-19–confirmed patients were analyzed by droplet digital PCR (ddPCR) and RT-PCR based 2 target genes (ORF1ab and N). Nasal swabs, throat swabs, sputum, blood, and urine were collected. Clinical and imaging data were obtained for clinical staging. Results In 95 samples that tested positive by both methods, the cycle threshold (Ct) of RT-PCR was highly correlated with the copy number of ddPCR (ORF1ab gene, R2 = 0.83; N gene, R2 = 0.87). Four (4/161) negative and 41 (41/67) single-gene positive samples tested by RT-PCR were positive according to ddPCR with viral loads ranging from 11.1 to 123.2 copies/test. The viral load of respiratory samples was then compared and the average viral load in sputum (17 429 ± 6920 copies/test) was found to be significantly higher than in throat swabs (2552 ± 1965 copies/test, P < .001) and nasal swabs (651 ± 501 copies/test, P < .001). Furthermore, the viral loads in the early and progressive stages were significantly higher than that in the recovery stage (46 800 ± 17 272 vs 1252 ± 1027, P < .001) analyzed by sputum samples. Conclusions Quantitative monitoring of viral load in lower respiratory tract samples helps to evaluate disease progression, especially in cases of low viral load.

To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington’s disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We find repeat length dependent transcriptional signatures are prominent in the striatum, less so in cortex, and minimal in the liver. Co-expression network analyses reveal 13 striatal and 5 cortical modules that are highly correlated with CAG length and age, and that are preserved in HD models and some in the patients. Top striatal modules implicate mHtt CAG length and age in graded impairment of striatal medium spiny neuron identity gene expression and in dysregulation of cAMP signaling, cell death, and protocadherin genes. Importantly, we used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at both RNA and protein levels, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo.