Image 1_Case report: Significant lesion reduction and neural structural changes following ibogaine treatments for multiple sclerosis.jpeg by David Qixiang Chen (8198265)

“…Ibogaine, a psychoactive alkaloid, has been proposed as a potential neuroregenerative agent due to its multifaceted pharmacological profile. We present two case studies of MS patients who underwent a novel ibogaine treatment, highlighting significant neuroimaging changes and clinical improvements. …”

Summary of measured parameters. by Aaron L. Sayler (19797446)

“…Male KO mice also displayed a significant decrease in rearing activity and blood pressure. …”

Raw data. by Aaron L. Sayler (19797446)

“…Male KO mice also displayed a significant decrease in rearing activity and blood pressure. …”

Malformations of cardiac valves in <i>Drosophila.</i> by Christian Meyer (6035)

S1 Graphical abstract - by Aman Goyal (19231397)

“…</p><p>Conclusions</p><p>Our analysis showed a significant decrease in mortality from paroxysmal tachycardia since 1999, although there has been a slight increase in recent years. …”

Flowchart of patient selection in this study. by Kazuyoshi Ohkawa (836847)

“…Among the letrozole-treated patients, the mean FIB-4 index tended to decline during letrozole treatment; a significant decrease was observed at 18 and 24 months compared with the baseline values (p = 0.044 and p = 0.013). …”

S1 Data - by Kazuyoshi Ohkawa (836847)

“…Among the letrozole-treated patients, the mean FIB-4 index tended to decline during letrozole treatment; a significant decrease was observed at 18 and 24 months compared with the baseline values (p = 0.044 and p = 0.013). …”

Valve closing capability and hemolymph flow analysis. by Christian Meyer (6035)

“…Mean pixel intensity of the dye package is significantly reduced upon valve malformation, indicating less hemolymph is pumped (Scheme illustrates dye package in the aorta and its area analyzed). …”

DataSheet1_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…Further, data from sleep questionnaires proved sleep-wake disruption in patients with MASLD. We objectively assessed sleep-wake rhythms in patients with biopsy-proven MASLD (n = 35) and healthy controls (HC, n = 16) using actigraphy 24/7 for 4 weeks. …”

DataSheet3_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…Further, data from sleep questionnaires proved sleep-wake disruption in patients with MASLD. We objectively assessed sleep-wake rhythms in patients with biopsy-proven MASLD (n = 35) and healthy controls (HC, n = 16) using actigraphy 24/7 for 4 weeks. …”

DataSheet2_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…Further, data from sleep questionnaires proved sleep-wake disruption in patients with MASLD. We objectively assessed sleep-wake rhythms in patients with biopsy-proven MASLD (n = 35) and healthy controls (HC, n = 16) using actigraphy 24/7 for 4 weeks. …”

DataSheet4_Significant nocturnal wakefulness after sleep onset in metabolic dysfunction–associated steatotic liver disease.PDF by Sofia Schaeffer (20379954)

“…Further, data from sleep questionnaires proved sleep-wake disruption in patients with MASLD. We objectively assessed sleep-wake rhythms in patients with biopsy-proven MASLD (n = 35) and healthy controls (HC, n = 16) using actigraphy 24/7 for 4 weeks. …”

This figure shows the forest plot for the multivariable logistic regression found in Table 1. by Scott J. Halperin (17835402)

Major hyperparameters of RF-SVR. by Jintao Li (448681)

“…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”

Pseudo code for coupling model execution process. by Jintao Li (448681)

“…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”

Major hyperparameters of RF-MLPR. by Jintao Li (448681)

“…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”

Results of RF algorithm screening factors. by Jintao Li (448681)

“…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”

Schematic diagram of the basic principles of SVR. by Jintao Li (448681)

“…This narrow approach overlooks the multifaceted variables influencing runoff, resulting in incomplete and less reliable predictions. To address these challenges, we selected and integrated Random Forest (RF), Support Vector Regression (SVR), and Multilayer Perceptron Regression (MLPR) to develop two coupled intelligent prediction models—RF-SVR and RF-MLPR—due to their complementary strengths. …”

Multilevel logistic regression analysis of individual and community level factors. by Mulugeta Wassie (10803155)

Subjects:

Socio- demographic characteristics of study participants. by Mulugeta Wassie (10803155)

Subjects: