Lack of tau prevents impaired adult hippocampal progenitor cell proliferation in AICD-Tg mice. by Kaushik Ghosal (244754)

“…Compared to wild-type (left) there is a significant decrease in the number of DCX+ cells in the SGZ of AICD-Tg mice (right). …”

Dose-dependent cVA response and desensitization by prolonged stimulation in Or67d ORNs. by Shin-Ichiro Tachibana (707681)

“…(B) Representative fluorescent changes evoked by odor stimulation of various amounts of cVA (0 to 100 pg in this case) in a male fly. (C) Peak fluorescent changes in response to cVA and a live male. …”

Involvement of mitochondrial pathway in AG–4 induced apoptosis. by Deepak Kumar (63095)

“…Results are expressed as IC₅₀ (mean ± SEM) from three independent experiments (***p<0.001, compared to only AG–4 treated cells). …”

Supplementary Material for: A New Era in the Management of Cardiorenal Syndrome: The Importance of Cardiorenal Units. by León-Román J. (20602337)

“…A total of 45 (83%) and 16 (30%) patients completed follow-up in the CRU at 6 and 12 months, respectively. The mean age was 70 years±1.6, and 65% were men. Almost 50% of patients had ischemic heart disease-related HF. …”

Efficacy and safety of a single radiofrequency ablation of solid benign non-functioning thyroid nodules by Roberto Cesareo (4676131)

Activity coupling between V2 and the CPu. by Anett J. Nagy (5447606)

“…<p>(A) Experimental schematics showing the simultaneous recording of the LFPs and SUA in both the V2 and the dorsomedial CPu. (B) Mean raw spectra of the V2 (left) and CPu (right) are almost identical when the animals are running in both the uniformly gray (blue lines) and the striped (red) environments (mean power spectra of <i>N</i> = 30 and 175 LFP sessions, respectively). …”

Period of latency, progression and duration of blockade of epidural anesthesia with lidocaine, bupivacaine or its association in dogs by S.J. Ronchi (8143470)

Platelet thrombus formation on collagen surface in the presence of Hb. by Gowtham K. Annarapu (2622811)

“…<p><b>(A)</b> Whole blood was perfused over immobilized collagen type-1 (100 μg/mL) under shear stresses of 5 and 25 dyne/cm² in the presence of Hb. …”

Model simulations of feedback induced shift of Ca-current in wild-type and mutant zebrafish. by Lauw J. Klaassen (213346)

“…The value of was varied from 100% (A) to 10% (C) of the wild-type value <a href="http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.1001107#pbio.1001107-Fahrenfort1" target="_blank">[6]</a>. …”

Activation of AMPK prevented drugs-induced mitochondrial dysfunction. by Sun Woo Sophie Kang (3280878)

“…Percentages relative to respective controls were calculated. (<b>A</b>) AICAR prevented the decrease in cellular ATP in rat hepatocytes treated with acetaminophen (10mM, 24h) or diclofenac (250μM, 24h). …”

Forests to Faucets 2.0 by U.S. Forest Service (17476914)

“…As developed in Forests to Faucets (USFS 2011), the Important Areas for Surface Drinking Water (IMP) model can be broken down into two parts: IMPn = (PRn) * (Qn)Calculated using R, Updated September 2023IMP_RIMP, Important Areas for Surface Drinking Water (0-100 Quantiles)Calculated using R, Updated September 2023NON_FORESTAcres of non-forestPADUS and NLCDPRIVATE_FORESTAcres of private forestPADUS and NLCDPROTECTED_FORESTAcres of protected forest (State, Local, NGO, Permanent Easement)PADUS, NCED, and NLCDNFS_FORESTAcres of National Forest System (NFS) forestPADUS and NLCDFEDERAL_FORESTAcres of Other Federal forest (Non-NFS Federal)PADUS and NLCDPER_FORPRIPercent Private ForestCalculated using ArcGISPER_FORNFSPercent NFS ForestCalculated using ArcGISPER_FORPROPercent Protected (Other State, Local, NGO, Permanent Easement, NFS, and Federal) ForestCalculated using ArcGISWFP_HI_ACAcres with High and Very High Wildfire Hazard Potential (WHP)Dillon, 2018PER_WFPPercent of HU 12 with High and Very High Wildfire Hazard Potential (WHP)Dillon, 2018PER_IDRISKPercent of HU 12 that is at risk for mortality - 25% of standing live basal area greater than one inch in diameter will die over a 15- year time frame (2013 to 2027) due to insects and diseases.Krist, et Al,. 2014PERDEV_1040_45% Landuse Change 2010-2040 (low)ICLUSPERDEV_1090_45% Landuse Change 2010-2090 (low)ICLUSPERDEV_1040_85% Landuse Change 2010-2040 (high)ICLUSPERDEV_1090_85% Landuse Change 2010-2090 (high)ICLUSPER_Q40_45% Water Yield Change 2010-2040 (low) WASSI , Updated September 2023PER_Q90_45% Water Yield Change 2010-2090 (low) WASSI , Updated September 2023PER_Q40_85% Water Yield Change 2010-2040 (high) WASSI , Updated September 2023PER_Q90_85% Water Yield Change 2010-2090 (high) WASSI , Updated September 2023WFP(APCW_R * IMP_R * PER_WFP )/ 10,000Wildfire Threat to Important Surface Drinking Water Watersheds Calculated using ArcGIS, Updated September 2023IDRISK(APCW_R * IMP_R * PER_IDRISK )/ 10,000Insect & Disease Threat to Important Surface Drinking Water Watersheds Calculated using ArcGIS, Updated September 2023DEV1040_45(APCW_R * IMP_R * PERDEV_1040_45)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) Calculated using ArcGIS, Updated September 2023DEV1090_45(APCW_R * IMP_R * PERDEV_1090_45)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) Calculated using ArcGIS, Updated September 2023DEV1040_85(APCW_R * IMP_R * PERDEV_1040_85)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) Calculated using ArcGIS, Updated September 2023DEV1090_85(APCW_R * IMP_R * PERDEV_1090_85)/ 10,000 Landuse Change in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) Calculated using ArcGIS, Updated September 2023Q1040_45-1 * (APCW_R * IMP_R * PER_Q40_45)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) Calculated using ArcGIS, Updated September 2023Q1090_45-1 * (APCW_R * IMP_R * PER_Q90_45)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) Calculated using ArcGIS, Updated September 2023Q1040_85-1 * (APCW_R * IMP_R * PER_Q40_85)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) Calculated using ArcGIS, Updated September 2023Q1090_85-1 * (APCW_R * IMP_R * PER_Q90_85)/ 10,000 Water Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) Calculated using ArcGIS, Updated September 2023WFP_IMP_RWildfire Threat to Important Surface Drinking Water Watersheds (0-100 Quantiles)Calculated using R, Updated September 2023IDRISK_RInsect & Disease Threat to Important Surface Drinking Water Watersheds (0-100 Quantiles)Calculated using R, Updated September 2023DEV40_45_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV40_85_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV90_45_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023DEV90_85_RLanduse Change in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q40_45_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q40_85_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2040 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q90_45_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (low emissions) (0-100 Quantiles)Calculated using R, Updated September 2023Q90_85_RWater Yield Decrease in Important Surface Drinking Water Watersheds 2010-2090 (high emissions) (0-100 Quantiles)Calculated using R, Updated September 2023RegionUS Forest Service Region numberUSFSRegionnameUS Forest Service Region nameUSFSHUC_Num_DiffThis field compares the value in column HUC12(circa 2019 wbd) with the value in HUC_12 (circa 2009 wassi)-1 = No equivalent WASSI HUC. …”

Prevalence of radiographic markers of femoroacetabular impingement in asymptomatic adults by Rodrigo Benedet Scheidt (10458805)

“…RESULTS: our sample consisted of 66% women, mean age of 50.4 years. The average alpha angle was 45.10°, SD=8.6. …”

Pre-plaque PW-Doppler parameters correlate with plaque length at 9 weeks. by Erin Y. Harmon (189206)

Placental genes with considerable expressional change in progression from early to mid-pregnancy. by Liis Uusküla (121629)

YR subtype selectivity of Y₄R PAMs. by Gregory Sliwoski (2832971)

“…For Y-axis values, positive modulation represents an increase in the apparent potency (pEC₅₀) of the native agonist and negative modulation represents a decrease in the apparent potency of the native agonist. …”

SNB-1::GFP Expression by D Motor Neurons. by Renee Baran (366407)

Patient baseline characteristics. by Josep Darbà (6428639)

The effect of inhibition on metabolically efficient information transfer. by Tomas Barta (8067509)

Kupffer cell populations. by Ivan Linares (5059373)

“…<p>Flow-cytometry analysis showed a significant decrease on pro-inflammatory NO+ KCs population in RGZ vs CTRL group since 1hr (28.49±4.99 vs 53.54±9.15%; p = 0.040), this difference further increase at 6hr (5.51±0.54 vs 31.12±9.58%; p = 0.009) and 24hr (4.15±1.50 vs 17.10±4.77%; p = 0.043) following reperfusion (A). …”

Effect of aerobic exercise on intramyocellular (IMCL) and intrahepatocellular lipids (IHCL). by Andrea Egger (107540)

“…<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0070865#pone-0070865-g003" target="_blank"><b>Figure 3b</b></a> Changes (mean ± 1 SEM) of IMCL and IHCL (in % from baseline) following a 2h-aerobic exercise at 50% VO<sub>2max.…”