Image_2_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. We found that schizophrenia patients with AVHs were characterized by significant decreased static functional connectivity and enhanced variability of dynamic functional connectivity (non-parametric permutation test, Bonferroni correction, p < 0.05). …”

Image_3_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. We found that schizophrenia patients with AVHs were characterized by significant decreased static functional connectivity and enhanced variability of dynamic functional connectivity (non-parametric permutation test, Bonferroni correction, p < 0.05). …”

Image_1_Distinct Brain Dynamic Functional Connectivity Patterns in Schizophrenia Patients With and Without Auditory Verbal Hallucinations.JPEG by Yao Zhang (134381)

“…Dynamic functional connectivity was studied with a sliding-window method and functional connectivity states were then obtained with the k-means clustering algorithm in the three groups. We found that schizophrenia patients with AVHs were characterized by significant decreased static functional connectivity and enhanced variability of dynamic functional connectivity (non-parametric permutation test, Bonferroni correction, p < 0.05). …”

Maternal Clinical Diagnoses and Hospital Variation in the Risk of Cesarean Delivery: Analyses of a National US Hospital Discharge Database by Katy B. Kozhimannil (614638)

Table_5_Foundation Species Abundance Influences Food Web Topology on Glass Sponge Reefs.DOCX by Stephanie K. Archer (9413240)

Complement anaphylatoxin C5a neuroprotects through regulation of glutamate receptor subunit 2 and -1 by Piali Mukherjee (86993)

“…GluR2 immunoreactivity was quantitated from 8–10 randomly selected fields and results were expressed as a percent of vehicle treated WT controls. KA significantly decreased the expression of GluR2 immunoreactivity in the mossy fiber region of C5aRKO mice (Fig. …”

Fig 3 - by Ekramy Halawa (11785086)

The expression of Myc leads to a decreased rate of dinitrophenol uncoupled respiration when glutamate+malate and succinate+rotenone were used as complex I and complex II substrates... by Hyoung-gon Lee (73934)

“…Data are expressed as mean±SEM; * p<0.05 vs. Myc-OFF and Single Tg. n = 5 for Myc-ON and Myc-OFF, and n = 4 for Single Tg.…”

Location and elevation map of study area. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

The dominant soils of Gilgel Gibe catchment. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

Sub-watersheds of the Gilgel Gibe catchment. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

Drainage in Gilgel Gibe catchment. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

Sensitivity analysis and calibrated parameters. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

Impacts of climate change on water balance. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

Precipitation and temperature recording stations. by Zewde Alemayehu Tilahun (16462668)

“…The results indicated that the ensemble mean of the six RCMs projects a decline in precipitation and an increase in temperature under both the RCP4.5 and RCP8.5 representative concentration pathways. …”

Effect of BXL-01-0029 on IFNγ+TNFα-induced class I and class II HLA in Hfsmc. by Luigi Di Luigi (478292)

“…<p>A, Immunocytochemistry revealed no constitutive expression of class I and class II HLA in control Hfsmc (left A); positive staining for both antigens was observed after 24–48 h incubation with IFNγ+TNFα (middle A); BXL-01-0029 significantly counteracted cytokine-induced class II HLA expression at both time points, with no effect onto class I HLA (right A). …”

Role of the phosphorylation of ATF7 in G2/M progression. by Hitomi Hasegawa (697973)

Dose- and time-dependent effect of IFN-γ and TNF-α on benzamil-sensitive <i>I</i>_sc and TEER in HBECs. by Anusree Sasidharan (19226521)

40 anonymized datasets used in the analysis. by Alexandra V. Kulinkina (5335058)

“…We derived environmental variables from fine-resolution RS data (Landsat 8) and examined a variable distance radius (1–5 km) for aggregating these variables around point-prevalence locations in a non-parametric random forest modeling approach. …”

Summary of analysis variables. by Alexandra V. Kulinkina (5335058)

“…We derived environmental variables from fine-resolution RS data (Landsat 8) and examined a variable distance radius (1–5 km) for aggregating these variables around point-prevalence locations in a non-parametric random forest modeling approach. …”