Enhanced high‐mobility group box 1 (HMGB1) modulates regulatory T cells (Treg)/T helper 17 (Th17) balance via toll‐like receptor (TLR)‐4‐interleukin (IL)‐6 pathway in patients with chronic hepatitis B

High‐mobility group box 1 (HMGB1) proteins are substantially up‐regulated in acute and chronic hepatitis. However, the immunopathogenic role of HMGB1 in patients with chronic hepatitis B (CHB) has not been elucidated. In this study, using a cohort of 36 CHB patients, we demonstrated a crucial role for HMGB1 to modulate balance between regulatory T (Treg) and T helper 17 (Th17) cells via the toll‐like receptor (TLR)‐4‐interleukin (IL)‐6 pathway. Serum HMGB1 levels were dramatically higher in CHB patients and increased along with liver injury, inflammation and fibrosis. Notably, HMGB1 increased along with decreased Treg/Th17 cells ratios in the periphery or intrahepatic microenvironment, which provides a clue for HMGB1 to favour Th17 responses whereas inhibit Treg responses. For in vitro studies, serum pools were constructed with serum from CHB patients at an advanced stage, whereas peripheral blood mononuclear cells (PBMC) pools were constructed with cells from those at an early stage. CHB‐serum significantly enhanced retinoic acid‐related orphan receptor‐γt (RORγt), whereas they inhibited forkhead box P3 (Foxp3) expression in CHB‐PBMC, which could be reversed by blocking of HMGB1, TLR4, or IL‐6. Besides, recombinant HMGB1 (rHMGB1) dose‐dependently up‐regulated RORγt whereas down‐regulated Foxp3 expression in CHB‐PBMC, and meanwhile, rHMGB1 enhanced TLR4 and IL‐6 expression in CHB‐PBMC. Moreover, the axis of HMGB1–TLR4‐IL‐6–Treg/Th17 required noncontact interactions between CD4 and non‐CD4 cells. In addition, rHMGB1 down‐regulated anti‐inflammatory proteins on CD4⁺CD25⁺ cells whereas up‐regulated pro‐inflammatory cytokines in CD4⁺CD25⁻ cells. In summary, enriched HMGB1 in CHB patients shifts Treg/Th17 balance to Th17 dominance via the TLR4‐IL‐6 pathway, which exacerbates liver injury and inflammation.     

Sensilla on the antenna of blow fly,Triceratopyga calliphoroides Rohdendorf (Diptera: Calliphoridae)

Blow fly, Triceratopyga calliphoroides Rohdendorf, is a common and synanthropic species of medical and forensic significance in eastern Asia. Field monitoring studies have indicated that olfaction system plays an important role in guiding the behavior of insect species. To further our understanding of fly olfaction, scanning electron microscopy (SEM) and laser scanning confocal microscopy (LSCM) are applied to examine the sensillar morphology of adults, with an emphasis on sensory pit and sacculus. Both microtrichiae and several mechanoreceptors are detected on antennal scape and pedicel. Except for these two structures, pedicellar buttons are also found in antennal pedicellar depression after the separation of antennal pedicel and funiculus. Eight types of antennal sensilla are observed on external surface of antennal funiculus (one type of trichoid sensilla, three types of basiconic sensilla, three types of coeloconic sensilla, and one type of clavate-like sensilla), while two types (one type of basiconic sensilla and one type of coeloconic-like sensilla) are detected at the inner surface of sensory pits or sacculus. As the first to investigate cuticular invaginations of blow flies via paraffin section, the internal structure of abundant sensory pits and an excessively complex sacculus on antennal funiculus are revealed. After comparison to other species previously studied, this phenomenon is proved to be the most unique feature of T. calliphoroides, armed with a discussion on its morphology, function, and possible evolutionary implications.     

A novel microbead-based microfluidic device for rapid bacterial identification and antibiotic susceptibility testing

Effective treatment of infectious diseases depends on the ability to rapidly identify the infecting bacteria and the use of sensitive antibiotics. The currently used identification assays usually take more than 72 h to perform and have a low sensitivity. Herein, we present a microbead-based microfluidic platform that is highly sensitive and rapid for bacterial detection and antibiotic sensitivity testing. The platform includes four units, one of which is used for bacterial identification and the other three are used for susceptibility testing. Our results showed that Escherichia coli O157 at a cell density range of 10¹–10⁵ CFU/μL could be detected within 30 min. Additionally, the effects of three antibiotics on E. coli O157 were evaluated within 4–8 h. Overall, this integrated microbead-based microdevice provides a sensitive, rapid, reliable, and highly effective platform for the identification of bacteria, as well as antibiotic sensitivity testing.     

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes

Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities ≤0.2) and accounting for indirect overlap, we found 202 associations, with 27 of those appearing in both meta-analyses and GWAS. Our findings suggest that meta-analyses of well-conducted candidate gene studies may continue to add to our understanding of the genetic associations in the post-GWAS era.     

Anatomical accuracy of brain connections derived from diffusion MRI tractography is inherently limited

Tractography based on diffusion-weighted MRI (DWI) is widely used for mapping the structural connections of the human brain. Its accuracy is known to be limited by technical factors affecting in vivo data acquisition, such as noise, artifacts, and data undersampling resulting from scan time constraints. It generally is assumed that improvements in data quality and implementation of sophisticated tractography methods will lead to increasingly accurate maps of human anatomical connections. However, assessing the anatomical accuracy of DWI tractography is difficult because of the lack of independent knowledge of the true anatomical connections in humans. Here we investigate the future prospects of DWI-based connectional imaging by applying advanced tractography methods to an ex vivo DWI dataset of the macaque brain. The results of different tractography methods were compared with maps of known axonal projections from previous tracer studies in the macaque. Despite the exceptional quality of the DWI data, none of the methods demonstrated high anatomical accuracy. The methods that showed the highest sensitivity showed the lowest specificity, and vice versa. Additionally, anatomical accuracy was highly dependent upon parameters of the tractography algorithm, with different optimal values for mapping different pathways. These results suggest that there is an inherent limitation in determining long-range anatomical projections based on voxel-averaged estimates of local fiber orientation obtained from DWI data that is unlikely to be overcome by improvements in data acquisition and analysis alone.The creation of a comprehensive map of the connectional neuroanatomy of the human brain would be a fundamental achievement in neuroscience. However, despite the numerous efforts to date (for a historical review, see ref. 1), creating this map remains a challenge. A major limitation is that the current gold-standard technique for mapping structural connections, which requires the injection of axonal tracers, cannot be used in humans. The introduction of diffusion-weighted MRI (DWI) (2–4) and the subsequent advent of diffusion tensor MRI (DTI) (5) opened the possibility of exploring the structural properties of white matter in the living human brain (6). Local DWI measures are used clinically for the early detection of stroke and for the characterization of neurological disorders such as multiple sclerosis, epilepsy, and brain gliomas, among others (7). In addition, tractography approaches (8–12) that can infer structural brain connectivity based on brain-wide local DWI measurement have been developed (for reviews, see refs. 13 and 14). The success of DWI tractography as a method for studying fiber trajectories has led to a systematic characterization of large white-matter pathways of the living human brain (e.g., ref. 15), and now it is used routinely to provide a structural explanation for aspects of human brain function (16).A major limitation of DWI tractography is that its characterization of axonal pathways is based on indirect information and numerous assumptions. Local white matter orientation profiles are based on the statistical displacement profile (i.e., diffusion propagator) of water molecules in brain tissue on the coarse scale of a voxel, and fiber trajectories are inferred based on the adjacency of similar diffusion profiles. This approach differs fundamentally from conventional tract-tracing approaches in animals, which involve the physical transport of traceable molecules through the cells’ axoplasm over a large distance. Because these molecules occupy positions within the axon, it sometimes is possible to reconstruct the trajectory of individual neurons through the white matter (e.g., ref. 17). Given the inherent coarseness of DWI tractography, it can be argued that the prospect of using this method to reconstruct complex axonal pathways accurately in the human brain, in a manner similar to that used for molecular tracers in animals, is likely to be intrinsically problematic. Indeed, the limitations of DWI tractography techniques have been noted since their inception (8), and the anatomical accuracy of results from tractography based on the tensor model has been shown to be mixed (18). This inaccuracy has been attributed to two main factors. The first relates to the assumptions underlying tractography algorithms. For example, it has long been recognized that a simple tensor model (19) of local diffusion leads to problems in certain white matter regions where fibers cross within individual voxels. As a remedy, high angular resolution diffusion imaging (HARDI) methods (e.g., refs. 20–24) have been developed to enable better characterization of the diffusion displacement profile and to improve the accuracy of tractography. The second factor limiting accuracy stems from the low quality of clinical DWI data because of various sources of noise. Eddy current distortions, subject motion, physiological noise (see ref. 25 for a review), and susceptibility artifacts from echo planar imaging (EPI) (26) all lead to poor local characterization of diffusion and, consequently, to incorrect tractography results. Continuing advances in sequence design, MRI gradient hardware, and postprocessing correction schemes have overcome many of the initial problems (27) and have led to the belief that further acquisition improvements will result in more precise mapping of structural connections in the human brain (28). In fact, the assumption underlying many recent initiatives to map structural brain connectivity from DWI data is that improved image data quality and sophisticated diffusion modeling approaches will result in anatomically accurate maps of white matter connections (29). The goal of the present study is to investigate the validity of this assumption.To achieve this goal, we acquired high angular resolution DWI data from a normal adult rhesus macaque brain, ex vivo, at a spatial resolution of 250 microns (isotropic). This dataset is ideal for exploring the limits of DWI tractography because of its high signal-to-noise ratio (SNR) (for SNR computation, see SI Materials and Methods) and the almost complete absence of experimental confounds and artifacts such as those originating from patient motion, noise, cardiac pulsation, and EPI distortion that are typically encountered in in vivo studies. Using the axonal tracer results from a well-known atlas (17) as reference, we measured the sensitivity (i.e., the ability to detect true connections) and specificity (i.e., the ability to avoid false connections) of several DWI tractography implementations representative of the current state of the art. This approach allowed us to investigate whether sophisticated diffusion modeling techniques, when applied to DWI data of exceptional quality, would yield accurate maps of axonal connections.