Schematic flowchart of the study. by Sivaprakasam T. Selvavinayagam (13825861)

“…Factors such as individuals’ age (p = 0.029), underlying comorbid conditions (30.3%; p = 0.035), and longer employment duration (28%; p = 0.034) were significantly associated with IGRA positivity. Further, IGRA positivity was significantly associated with decreased RDW standard deviation (RDW-SD). …”

Comorbidities among LTBI-positive individuals. by Sivaprakasam T. Selvavinayagam (13825861)

“…Factors such as individuals’ age (p = 0.029), underlying comorbid conditions (30.3%; p = 0.035), and longer employment duration (28%; p = 0.034) were significantly associated with IGRA positivity. Further, IGRA positivity was significantly associated with decreased RDW standard deviation (RDW-SD). …”

Data. by Melese Bahiru Tesema (19864895)

“…Increased job satisfaction was linked to nursing (AOR = 1.679, CI: 1.011–2.787) and radiology professions (AOR = 35.21, CI: 4.14–299.39).…”

Cardiac valve malformation impacts crawling and movement of larvae. by Christian Meyer (6035)

Benchmark regression results. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Heterogeneity test. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

S1 File - by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

The robustness test. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Mechanistic testing. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Descriptive statistics of variables. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Endogenous treatment. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Analysis of industry linkage effects. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

Analysis of peer effects. by Pengyu Yang (2668450)

“…The findings reveal that: (1) At this stage, digital transformation in listed companies effectively reduces their carbon intensity, but the relationship between the two is not linear; instead, it exhibits a U-shaped trajectory, initially decreasing then increasing. (2) Analysis of mechanism indicates that costs associated with environmental governance and innovations in green technology serve as critical pathways through which corporate digital transformation influences carbon intensity. (3) The analysis of driving effect suggests that the digital transformation significantly curtails the carbon emission intensity of both upstream and downstream enterprises as well as those within the same industry and geographical region, through industrial linkage and the cohort effect. (4) Heterogeneity analysis elucidates that the digital transformation of enterprises in regions with stronger government environmental regulations has a markedly more pronounced effect on reducing the carbon emission intensity. …”

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

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

“…Pixel intensity in ROI 1 increases if hemolymph packages pass and decreases, if valves close after each heartbeat, respectively. …”

FSA inhibits MaAKT1 channels through <i>S</i>-glutathionylation. by Jun Zhang (48506)

“…Representative whole-cell current traces and summary of the preventive effect of DTT (5 mM) in the pipette on FSA-induced MaAKT1 inhibition (n = 3). Ns, not significant compared with control group. (<b>C</b>) FSA treatment decreases intracellular GSH level (left), increases GSSG level (middle), and reduces GSH/GSSG ratio (right) (n = 3). …”

Flowchart of the study population. by Gábor Szaló (22615130)

“…Among those 803 individuals who did not take antihypertensive medication, there was a significant association in linear regression between increase in PSS-10 and decrease in C2 (B: −0.2, 95% CI: −0.4- −0.02; p = 0.03) that was lost after adjustment for physical activity (B: −0.16, 95% CI: −0.35–0.03; p = 0.1). …”

Characteristics of study population. by Gábor Szaló (22615130)

“…Among those 803 individuals who did not take antihypertensive medication, there was a significant association in linear regression between increase in PSS-10 and decrease in C2 (B: −0.2, 95% CI: −0.4- −0.02; p = 0.03) that was lost after adjustment for physical activity (B: −0.16, 95% CI: −0.35–0.03; p = 0.1). …”

Changes in (A) Deaths and (B) DALYs of pancreatitis due to alcohol use according to aging, population growth and epidemiological change from 1990 to 2021 at global level by SDI qui... by Letai Li (19229848)

Baseline characteristics of participants. by Mei Zhou (269746)

“…</p><p>Results</p><p>After DRG implementation, the logarithmic mean of total hospitalization expenditures decreased significantly (3.914 ± 0.837 vs. 3.872 ± 1.004), while rates of unplanned readmissions, unplanned reoperations, postoperative complications, and patient complaints within 30 days increased significantly (3.784% vs 4.214%, 0.083% vs 0.166%, 0.207% vs 0.258%, 3.741% vs 5.133%). …”