Showing 3,061 - 3,080 results of 5,349 for search '(( significantly affect decrease ) OR ( significantly ((linked decrease) OR (linear decrease)) ))', query time: 0.45s Refine Results
  1. 3061

    Symbolic self completion as mediator between nicotine dependence and quit intention: a nationally representative survey by Berna Tarı Kasnakoğlu (19728602)

    Published 2025
    “…Mediation analysis was conducted using the Hayes model #4 to investigate the degree to which (symbolic) smoking was linked to dependence and quit intention.</p> <p>Based on regression analyses, nicotine dependence was found to decrease the intention to quit (coeff = −.039**), while an absence of symbolic self-completion was found to increase quit intention (coeff = .6118**). …”
  2. 3062

    Descriptive statistics. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  3. 3063

    Changes in body composition, PSC, PSCP, MVPA. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  4. 3064

    Causal paths for FFM. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  5. 3065

    Recruitment and screening flowchart. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  6. 3066

    Factors influencing body fat percentage at Q2. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  7. 3067

    Factors influencing body fat percentage at Q1. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  8. 3068

    STROBE flowchart. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  9. 3069

    Factors influencing FFM at Q1. by Xiang Pan (5774024)

    Published 2025
    “…Data were collected at three time points (mid-semester (T0), end of semester (T1), and end of the winter holidays (T2)), and explorations were conducted using multivariate linear regression and Granger causality tests to investigate how changes in moderate-to-vigorous physical activity(MVPA), snacking habits (proportion of snack calorie, PSC; proportion of snack calories from protein, PSCP) in multiple stages and how their changes affect body composition. …”
  10. 3070

    Data_Sheet_1_Deregulation of mTORC1-TFEB axis in human iPSC model of GBA1-associated Parkinson’s disease.docx by Fahad Mubariz (16010003)

    Published 2025
    “…Moreover, treatment with the lipid substrate reducing compound Genz-123346, decreased mTORC1 activity and increased TFEB expression in the mutant neurons, suggesting that mTORC1-TFEB alterations are linked to the lipid substrate accumulation. …”
  11. 3071

    Table 1_Characterization of glycogen-related glycoside hydrolase glgX and glgB from Klebsiella pneumoniae and their roles in biofilm formation and virulence.docx by Xinyue Liu (170148)

    Published 2024
    “…The deletion of the glgB gene resulted in a decrease in the growth rate of the bacteria and defected glycogen synthesis. …”
  12. 3072

    Data Sheet 1_Investigating the impact of microcalcification size and volume on collagenous matrix and tissue mechanics using a tissue-engineered atherosclerotic cap model.xlsx by Imke L. Jansen (22089944)

    Published 2025
    “…To mimic human microcalcification size and volume, hydroxyapatite microparticles, in two size ranges (diameter up to 5 μm or up to 50 μm) and two volumes (1 v/v% and 5 v/v%) were incorporated homogenously throughout the tissue-engineered model. 5 v/v% of particles caused a significant lowering of the mechanical properties as was shown by a decrease in stiffness and ultimate tensile stress under uniaxial tensile loading. …”
  13. 3073

    Data Sheet 2_Investigating the impact of microcalcification size and volume on collagenous matrix and tissue mechanics using a tissue-engineered atherosclerotic cap model.docx by Imke L. Jansen (22089944)

    Published 2025
    “…To mimic human microcalcification size and volume, hydroxyapatite microparticles, in two size ranges (diameter up to 5 μm or up to 50 μm) and two volumes (1 v/v% and 5 v/v%) were incorporated homogenously throughout the tissue-engineered model. 5 v/v% of particles caused a significant lowering of the mechanical properties as was shown by a decrease in stiffness and ultimate tensile stress under uniaxial tensile loading. …”
  14. 3074

    Supplementary file 1_Active fungal infections alter the respiratory microbiome profiles of Mayo Clinic Arizona patients.zip by Daniel R. Kollath (18134608)

    Published 2025
    “…This is the first study to examine how these fungal pathogens affect the lung microbial community of humans.</p>…”
  15. 3075

    Drugs causing prostate-specific antigen changes: the food and drug administration adverse event reporting system combined with Mendelian randomization analysis by Wei Zhang (405)

    Published 2024
    “…<p>Prostate cancer is one of the most common malignancies in men worldwide, and prostate-specific antigen (PSA) screening is widely used for its early detection. Drug use may affect PSA levels, but the effect for most drugs is currently unknown.…”
  16. 3076

    Image 1_Mitochondrial DNA oxidation and content in different metabolic phenotypes of women with polycystic ovary syndrome.jpeg by Mailén Rojo (10802556)

    Published 2025
    “…Stratifying these patients by metabolic profile, revealed a progressive decline in mtDNA content from the normal-weight control group to the MHO-PCOS and MUO-PCOS groups, suggesting that lower mtDNA content is linked to obesity and worse metabolic profile. However, mtDNA oxidation levels did not differ significantly among these groups. …”
  17. 3077

    Table 1_Proteomic insights into COPD pathogenesis and therapeutic targets: a causal analysis of circulating proteins.docx by Min Luo (258201)

    Published 2025
    “…Western blot analysis validated these findings in plasma samples, showing significantly increased expression of MMP12 and ASM, and decreased expression of NPNT and SNX1 in COPD patients compared to healthy controls, while KLC1 showed no significant difference. …”
  18. 3078

    Supplementary file 1_Protective and risk factors in daily life associated with cognitive decline of older adults.docx by Fang Tong (484200)

    Published 2025
    “…Single-factor comparison, multiple linear regression and logistic regression implied that gender, age, hypertension level, height, dietary habit, physical-exercise duration, physical-exercise history, and smoking history could be closely linked with cognitive decline. …”
  19. 3079

    Supplementary file 4_Protective and risk factors in daily life associated with cognitive decline of older adults.docx by Fang Tong (484200)

    Published 2025
    “…Single-factor comparison, multiple linear regression and logistic regression implied that gender, age, hypertension level, height, dietary habit, physical-exercise duration, physical-exercise history, and smoking history could be closely linked with cognitive decline. …”
  20. 3080

    Supplementary file 5_Protective and risk factors in daily life associated with cognitive decline of older adults.docx by Fang Tong (484200)

    Published 2025
    “…Single-factor comparison, multiple linear regression and logistic regression implied that gender, age, hypertension level, height, dietary habit, physical-exercise duration, physical-exercise history, and smoking history could be closely linked with cognitive decline. …”