BACKGROUND The bacterial resistance to antibiotics is generally increasing, which has become a great challenge for treating infectious diseases caused by microbes. Photodynamic antibacterial chemotherapy (PACT) has been considered as a promising method for inactivating bacteria. The combination of antimicrobial agent with PACT may provide efficient way against drug-resistant microbe. This study aims to investigate the synergistic effects of PACT mediated by toluidine blue (TB), combined with gentamicin (GEN) on common pathogensStaphylococcus aureus (S. aureus) and multidrug-resistant S. aureus (MDR S. aureus). selleck chemical METHODS Alkaline lysis was used to detect the uptake of TB byS. aureus and MDR S. aureus. Plate counting was applied to evaluate the inhibition efficiency of GEN alone, TB-PACT alone, and work together. Flow cytometry and fluorescence microscopy were performed to examine the permeability of bacterial membranes after different treatments. Intracellular and extracellular reactive oxygen species (ROS) were assessed with the assist of H2DCF-DA and SOSG probes. RESULTS TB-PACT combined with GEN led to more pronounced antibacterial effects inS. aureus and MDR S. aureus, as compared with either alone. TB-PACT treatment permeabilized the bacterial membranes, promoted GEN cellular accumulation and augmented the antibacterial efficiency. The intracellular ROS generation by the combination of TB-PACT and GEN was much higher than that of single treatment groups. CONCLUSIONS TB-PACT decreased the GEN cytotoxic threshold and usage, and the synergy of them significantly enhanced the sterilization ofS. aureus and MDR S. aureus. A region in the posterior inferior temporal gyrus (pITG) is thought to be specialized for processing Arabic numerals, but fMRI studies that compared passive viewing of numerals to other character types (e.g., letters and novel characters) have not found evidence of numeral preference in the pITG. However, recent studies showed that the engagement of the pITG is modulated by attention and task contexts, suggesting that passive viewing paradigms may be ill-suited for examining numeral specialization in the pITG. It is possible, however, that even if the strengths of responses to different category types are similar, the distributed response patterns (i.e., neural representations) in a candidate numeral-preferring pITG region (“pITG-numerals”) may reveal categorical distinctions, even during passive viewing. Using representational similarity analyses with three datasets that share the same task paradigm and stimulus sets (total N = 88), we tested whether the neural representations of digits, letters, and novel ctask contexts. OBJECTIVE Temporal lobe epilepsy (TLE) is known to affect large-scale structural networks and cognitive function in multiple domains. The study of complex relations between structural network organization and cognition requires comprehensive analytical methods and a shift towards multivariate techniques. Here, we sought to identify multidimensional associations between cognitive performance and structural network topology in TLE. METHODS We studied 34 drug-resistant adult TLE patients and 24 age- and sex-matched healthy controls. Participants underwent a comprehensive neurocognitive battery and multimodal MRI, allowing for large-scale connectomics, and morphological evaluation of subcortical and neocortical regions. Using canonical correlation analysis, we identified a multivariate mode that links cognitive performance to a brain structural network. Our approach was complemented by bootstrap-based hierarchical clustering to derive cognitive subtypes and associated patterns of macroscale connectome anomalies. RESULTS Both methodologies provided converging evidence for a close coupling between cognitive impairments across multiple domains and large-scale structural network compromise. Cognitive classes presented with an increasing gradient of abnormalities (increasing cortical and subcortical atrophy and less efficient white matter connectome organization in patients with increasing degrees of cognitive impairments). Notably, network topology characterized cognitive performance better than morphometric measures did. CONCLUSIONS Our multivariate approach emphasized a close coupling of cognitive dysfunction and large-scale network anomalies in TLE. Our findings contribute to understand the complexity of structural connectivity regulating the heterogeneous cognitive deficits found in epilepsy. In the first study comparing high angular resolution diffusion MRI (dMRI) in the human brain to axonal orientation measurements from polarization-sensitive optical coherence tomography (PSOCT), we compare the accuracy of orientation estimates from various dMRI sampling schemes and reconstruction methods. We find that, if the reconstruction approach is chosen carefully, single-shell dMRI data can yield the same accuracy as multi-shell data, and only moderately lower accuracy than a full Cartesian-grid sampling scheme. Our results suggest that current dMRI reconstruction approaches do not benefit substantially from ultra-high b-values or from very large numbers of diffusion-encoding directions. We also show that accuracy remains stable across dMRI voxel sizes of 1 ​mm or smaller but degrades at 2 ​mm, particularly in areas of complex white-matter architecture. We also show that, as the spatial resolution is reduced, axonal configurations in a dMRI voxel can no longer be modeled as a small set of distinct axon populations, violating an assumption that is sometimes made by dMRI reconstruction techniques. Our findings have implications for in vivo studies and illustrate the value of PSOCT as a source of ground-truth measurements of white-matter organization that does not suffer from the distortions typical of histological techniques. Diffusion MRI tractography produces massive sets of streamlines that need to be clustered into anatomically meaningful white-matter bundles. Conventional clustering techniques group streamlines based on their proximity in Euclidean space. We have developed AnatomiCuts, an unsupervised method for clustering tractography streamlines based on their neighboring anatomical structures, rather than their coordinates in Euclidean space. In this work, we show that the anatomical similarity metric used in AnatomiCuts can be extended to find corresponding clusters across subjects and across hemispheres, without inter-subject or inter-hemispheric registration. Our proposed approach enables group-wise tract cluster analysis, as well as studies of hemispheric asymmetry. We evaluate our approach on data from the pilot MGH-Harvard-USC Lifespan Human Connectome project, showing improved correspondence in tract clusters across 184 subjects aged 8-90. Our method shows up to 38% improvement in the overlap of corresponding clusters when comparing subjects with large age differences.