Life Sciences
Display Method:
2024,
54(9):
0904.
doi: 10.52396/JUSTC-2024-0064
Abstract:
Multiple morphological abnormalities of the sperm flagella (MMAF) are characterized by bent, irregular, short, coiled, and absent flagella. MMAF is caused by a variety of genes, some of which have been identified. However, the underlying genetic factors responsible for the majority of MMAF cases are still largely unknown. The glutamine-rich 2 (QRICH2) gene plays an essential role in the development of sperm flagella by regulating the expression of essential sperm flagellar biogenesis-associated proteins, and genetic variants of QRICH2 have been identified as the primary cause of MMAF in humans and mice. Here, we recruited a Pakistani consanguineous family to identify the genetic variant causing infertility in patients with MMAF. Whole-exome sequencing and Sanger sequencing were conducted to identify potentially pathogenic variants causing MMAF in infertile patients. Hematoxylin and eosin (HE) staining was performed to analyze sperm morphology. Quantitative polymerase chain reaction, western blot, and immunofluorescence staining analyses were conducted to observe the expression of QRICH2 in spermatozoa. A novel homozygous missense variant (c.4618C>T) in QRICH2 was identified in the affected patients. Morphological analysis of spermatozoa revealed the MMAF phenotype in infertile patients. qPCR revealed a significant reduction in the level of sperm QRICH2 mRNA, and immunofluorescence staining revealed a lack of sperm QRICH2 expression. Additionally, patients harboring a homozygous QRICH2 mutation presented reduced expression of outer dense fiber 2 (ODF2) in sperm, whereas sperm expression of A-kinase anchor protein 4 (AKAP4) was normal. These findings expand our understanding of the genetic causes of MMAF-associated male infertility and emphasize the importance of genetic counseling.
Multiple morphological abnormalities of the sperm flagella (MMAF) are characterized by bent, irregular, short, coiled, and absent flagella. MMAF is caused by a variety of genes, some of which have been identified. However, the underlying genetic factors responsible for the majority of MMAF cases are still largely unknown. The glutamine-rich 2 (QRICH2) gene plays an essential role in the development of sperm flagella by regulating the expression of essential sperm flagellar biogenesis-associated proteins, and genetic variants of QRICH2 have been identified as the primary cause of MMAF in humans and mice. Here, we recruited a Pakistani consanguineous family to identify the genetic variant causing infertility in patients with MMAF. Whole-exome sequencing and Sanger sequencing were conducted to identify potentially pathogenic variants causing MMAF in infertile patients. Hematoxylin and eosin (HE) staining was performed to analyze sperm morphology. Quantitative polymerase chain reaction, western blot, and immunofluorescence staining analyses were conducted to observe the expression of QRICH2 in spermatozoa. A novel homozygous missense variant (c.4618C>T) in QRICH2 was identified in the affected patients. Morphological analysis of spermatozoa revealed the MMAF phenotype in infertile patients. qPCR revealed a significant reduction in the level of sperm QRICH2 mRNA, and immunofluorescence staining revealed a lack of sperm QRICH2 expression. Additionally, patients harboring a homozygous QRICH2 mutation presented reduced expression of outer dense fiber 2 (ODF2) in sperm, whereas sperm expression of A-kinase anchor protein 4 (AKAP4) was normal. These findings expand our understanding of the genetic causes of MMAF-associated male infertility and emphasize the importance of genetic counseling.
2024,
54(9):
0905.
doi: 10.52396/JUSTC-2024-0012
Abstract:
Diderm bacteria, characterized by an additional lipid membrane layer known as the outer membrane, fold their outer membrane proteins (OMPs) via the β-barrel assembly machinery (BAM) complex. Understanding how the BAM complex, particularly its key component BamA, assists in OMP folding remains crucial in bacterial cell biology. Recent research has focused primarily on the structural and functional characteristics of BamA within the Gracilicutes clade, such as in Escherichia coli (E. coli). However, another major evolutionary branch, Terrabacteria, has received comparatively less attention. An example of a Terrabacteria is Deinococcus radiodurans (D. radiodurans), a Gram-positive bacterium that possesses a distinctive outer membrane structure. In this study, we first demonstrated that the β-barrel domains of BamA are not interchangeable between D. radiodurans and E. coli. The structure of D. radiodurans BamA was subsequently determined at 3.8 Å resolution using cryo-electron microscopy, revealing obviously distinct arrangements of extracellular loop 4 (ECL4) and ECL6 after structural comparison with their counterparts in gracilicutes. Despite the overall similarity in the topology of the β-barrel domain, our results indicate that certain ECLs have evolved into distinct structures between the Terrabacteria and Gracilicutes clades. While BamA and its function are generally conserved across diderm bacterial species, our findings underscore the evolutionary diversity of this core OMP folder among bacteria, offering new insights into bacterial physiology and evolutionary biology.
Diderm bacteria, characterized by an additional lipid membrane layer known as the outer membrane, fold their outer membrane proteins (OMPs) via the β-barrel assembly machinery (BAM) complex. Understanding how the BAM complex, particularly its key component BamA, assists in OMP folding remains crucial in bacterial cell biology. Recent research has focused primarily on the structural and functional characteristics of BamA within the Gracilicutes clade, such as in Escherichia coli (E. coli). However, another major evolutionary branch, Terrabacteria, has received comparatively less attention. An example of a Terrabacteria is Deinococcus radiodurans (D. radiodurans), a Gram-positive bacterium that possesses a distinctive outer membrane structure. In this study, we first demonstrated that the β-barrel domains of BamA are not interchangeable between D. radiodurans and E. coli. The structure of D. radiodurans BamA was subsequently determined at 3.8 Å resolution using cryo-electron microscopy, revealing obviously distinct arrangements of extracellular loop 4 (ECL4) and ECL6 after structural comparison with their counterparts in gracilicutes. Despite the overall similarity in the topology of the β-barrel domain, our results indicate that certain ECLs have evolved into distinct structures between the Terrabacteria and Gracilicutes clades. While BamA and its function are generally conserved across diderm bacterial species, our findings underscore the evolutionary diversity of this core OMP folder among bacteria, offering new insights into bacterial physiology and evolutionary biology.
Dietary oleic acid intake, olive oil consumption, and risk of cardiovascular and all-cause mortality
2024,
54(9):
0906.
doi: 10.52396/JUSTC-2024-0018
Abstract:
Objective: Oleic acid, a subtype of monounsaturated fatty acid (MUFA), is present in abundance in certain edible oils, particularly olive oils. Epidemiological evidence concerning dietary oleic acid intake and the long-term risk of mortality is lacking. This study aimed to evaluate the associations of the dietary intake of oleic acid and other specific subtypes of MUFAs, olive oil, and other vegetable oils with cardiovascular disease (CVD) and all-cause mortality. Methods: This prospective cohort study included adults aged 40 years or older who participated in the included U.S. adults National Health and Nutrition Examination Survey (NHANES). Dietary MUFA intake was assessed via 24-h dietary recall interviews in NHANES 1999–2018, and the consumption of olive oil and other vegetable oils was assessed via a food frequency questionnaire in NHANES 2003–2006. Deaths and underlying causes of death were ascertained by linkage to the National Death Index through December 31, 2019. Weighted Cox proportional hazards regression models were used to estimate the hazard ratio (HR) and 95% CIs. Results: Dietary intake of total MUFAs and oleic acid was associated with a lower risk of CVD mortality, with HRs (95% CI) of 0.62 (0.39–0.99) and 0.61 (0.39–0.97), respectively. Total MUFA and oleic acid intake were inversely associated with all-cause mortality; the multivariable-adjusted HRs were 0.77 (95% CI: 0.60–0.99) and 0.78 (95% CI: 0.62–0.99), respectively. There was no significant association between palmitoleic acid intake and all-cause mortality. The habitual consumption of olive oil, but not the consumption of other vegetable oils, was inversely associated with the risk of cardiovascular mortality. In the joint association analysis, the HRs (95% CI) of cardiovascular mortality were 0.36 (0.19–0.69) for people who exclusively consumed olive oil, 0.59 (0.27–1.32) for people who consumed both olive oil and other vegetable oils, and 0.73 (0.46–1.14) for people who exclusively consumed other vegetable oils compared with people who never consumed vegetable oils. Conclusions: In a U.S. nationally representative prospective cohort, higher dietary oleic acid intake and olive oil consumption were associated with a lower risk of cardiovascular mortality.
Objective: Oleic acid, a subtype of monounsaturated fatty acid (MUFA), is present in abundance in certain edible oils, particularly olive oils. Epidemiological evidence concerning dietary oleic acid intake and the long-term risk of mortality is lacking. This study aimed to evaluate the associations of the dietary intake of oleic acid and other specific subtypes of MUFAs, olive oil, and other vegetable oils with cardiovascular disease (CVD) and all-cause mortality. Methods: This prospective cohort study included adults aged 40 years or older who participated in the included U.S. adults National Health and Nutrition Examination Survey (NHANES). Dietary MUFA intake was assessed via 24-h dietary recall interviews in NHANES 1999–2018, and the consumption of olive oil and other vegetable oils was assessed via a food frequency questionnaire in NHANES 2003–2006. Deaths and underlying causes of death were ascertained by linkage to the National Death Index through December 31, 2019. Weighted Cox proportional hazards regression models were used to estimate the hazard ratio (HR) and 95% CIs. Results: Dietary intake of total MUFAs and oleic acid was associated with a lower risk of CVD mortality, with HRs (95% CI) of 0.62 (0.39–0.99) and 0.61 (0.39–0.97), respectively. Total MUFA and oleic acid intake were inversely associated with all-cause mortality; the multivariable-adjusted HRs were 0.77 (95% CI: 0.60–0.99) and 0.78 (95% CI: 0.62–0.99), respectively. There was no significant association between palmitoleic acid intake and all-cause mortality. The habitual consumption of olive oil, but not the consumption of other vegetable oils, was inversely associated with the risk of cardiovascular mortality. In the joint association analysis, the HRs (95% CI) of cardiovascular mortality were 0.36 (0.19–0.69) for people who exclusively consumed olive oil, 0.59 (0.27–1.32) for people who consumed both olive oil and other vegetable oils, and 0.73 (0.46–1.14) for people who exclusively consumed other vegetable oils compared with people who never consumed vegetable oils. Conclusions: In a U.S. nationally representative prospective cohort, higher dietary oleic acid intake and olive oil consumption were associated with a lower risk of cardiovascular mortality.
2024,
54(3):
0301.
doi: 10.52396/JUSTC-2023-0148
Abstract:
Molecular dynamics (MD) simulations can capture the dynamic behavior of proteins in full atomic detail and at very fine temporal resolution, so they have become an important tool in the study of protein dynamics. To date, several MD packages are widely used. An MD simulation starts from an initial structure that is generally taken from the Protein Data Bank (PDB). Until 2014, the PDB format was the standard file format for protein structures. However, there are certain intrinsic limitations in the PDB format, such as the storage of structural information in a fixed-width format, which is an issue for very large protein complexes. Therefore, the CIF (crystallographic information framework) format has been proposed, which is characterized by its superior expansibility. To our knowledge, the current mainstream MD packages support only the PDB format but do not support the CIF format directly. In this study, we modified the source code of one of the MD packages, GROMACS, which enables it to support CIF-formatted structure files as input and subsequently generate molecular topology files. This work simplifies the preprocessing of large protein complexes for MD simulations.
Molecular dynamics (MD) simulations can capture the dynamic behavior of proteins in full atomic detail and at very fine temporal resolution, so they have become an important tool in the study of protein dynamics. To date, several MD packages are widely used. An MD simulation starts from an initial structure that is generally taken from the Protein Data Bank (PDB). Until 2014, the PDB format was the standard file format for protein structures. However, there are certain intrinsic limitations in the PDB format, such as the storage of structural information in a fixed-width format, which is an issue for very large protein complexes. Therefore, the CIF (crystallographic information framework) format has been proposed, which is characterized by its superior expansibility. To our knowledge, the current mainstream MD packages support only the PDB format but do not support the CIF format directly. In this study, we modified the source code of one of the MD packages, GROMACS, which enables it to support CIF-formatted structure files as input and subsequently generate molecular topology files. This work simplifies the preprocessing of large protein complexes for MD simulations.
2024,
54(3):
0302.
doi: 10.52396/JUSTC-2023-0169
Abstract:
Reconstructing a complete image accurately from an undersampled k-space matrix is a viable approach for magnetic resonance imaging (MRI) acceleration. In recent years, numerous deep learning (DL)-based methods have been employed to improve MRI reconstruction. Among these methods, the cross-domain method has been proven to be effective. However, existing cross-domain reconstruction algorithms sequentially link the image domain and k-space networks, disregarding the interplay between different domains, consequently leading to a deficiency in reconstruction accuracy. In this work, we propose a deep interactive dual-domain network (IDDNet) with an auxiliary modality for accelerating MRI reconstruction to effectively extract pertinent information from multiple MR domains and modalities. The IDDNet first extracts shallow features from low-resolution target modalities in the image domain to obtain visual representation information. In the following feature processing, a parallel interactive architecture with dual branches is designed to extract deep features from relevant information of dual domains simultaneously to avoid redundant priority priors in sequential links. Furthermore, the model uses additional information from the auxiliary modality to refine the structure and improve the reconstruction accuracy. Numerous experiments at different sampling masks and acceleration rates on the MICCAI BraTS 2019 brain and fastMRI knee datasets show that IDDNet achieves excellent accelerated MRI reconstruction performance.
Reconstructing a complete image accurately from an undersampled k-space matrix is a viable approach for magnetic resonance imaging (MRI) acceleration. In recent years, numerous deep learning (DL)-based methods have been employed to improve MRI reconstruction. Among these methods, the cross-domain method has been proven to be effective. However, existing cross-domain reconstruction algorithms sequentially link the image domain and k-space networks, disregarding the interplay between different domains, consequently leading to a deficiency in reconstruction accuracy. In this work, we propose a deep interactive dual-domain network (IDDNet) with an auxiliary modality for accelerating MRI reconstruction to effectively extract pertinent information from multiple MR domains and modalities. The IDDNet first extracts shallow features from low-resolution target modalities in the image domain to obtain visual representation information. In the following feature processing, a parallel interactive architecture with dual branches is designed to extract deep features from relevant information of dual domains simultaneously to avoid redundant priority priors in sequential links. Furthermore, the model uses additional information from the auxiliary modality to refine the structure and improve the reconstruction accuracy. Numerous experiments at different sampling masks and acceleration rates on the MICCAI BraTS 2019 brain and fastMRI knee datasets show that IDDNet achieves excellent accelerated MRI reconstruction performance.
2024,
54(3):
0303.
doi: 10.52396/JUSTC-2023-0004
Abstract:
Objective: Active and passive smoking are common environmental risk factors, but there is no definite conclusion about their effects on relapse and disability progression in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Methods: This was a retrospective cohort study. Patients were included from four centers. Demographic and clinical data were extracted from the clinical database, while data involving environmental exposures during daily life, relapse, and disability progression were obtained through telephone follow-up interviews. Determinants of relapse were assessed by Cox proportional models, and disability progression was assessed by linear regression. Kaplan‒Meier survival was used to estimate relapse within five years after the first attack. Results: A total of 130 MS patients and 318 NMOSD patients were included in this study, and females accounted for 60% and 79.6%, respectively. MS patients with an active smoking history had a higher risk of relapse, for which the association became borderline significant after accounting for covariates (aHR=1.52, 95% CI=1.00, 2.31; p=0.052). The relapse risk between ever-smokers who smoked more than 10 cigarettes per day and smokers who smoked less than 10 cigarettes per day was not significantly different (aHR=0.96, 95% CI=0.63, 1.47; p=0.859). However, exposure to passive smoking was associated with a reduced risk of MS relapse (aHR=0.75, 95% CI=0.56, 1.00; p=0.044) compared with never-exposed patients. No associations were observed between active smoking/passive smoking and the risk of NMOSD relapse, but patients with a history of smoking were associated with a lower annual progression rate by Expanded Disability Status Scale (EDSS) (aβ=−0.20, 95% CI=−0.38, −0.01; p=0.036) and Multiple Sclerosis Severity Score (MSSS) (aβ=−0.23, 95% CI=−0.44, −0.03; p=0.028). Conclusion: Our research shows that active smoking increases the relapse risk of MS and has a negative impact on disability progression; thus, smoking cessation should be encouraged.
Objective: Active and passive smoking are common environmental risk factors, but there is no definite conclusion about their effects on relapse and disability progression in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Methods: This was a retrospective cohort study. Patients were included from four centers. Demographic and clinical data were extracted from the clinical database, while data involving environmental exposures during daily life, relapse, and disability progression were obtained through telephone follow-up interviews. Determinants of relapse were assessed by Cox proportional models, and disability progression was assessed by linear regression. Kaplan‒Meier survival was used to estimate relapse within five years after the first attack. Results: A total of 130 MS patients and 318 NMOSD patients were included in this study, and females accounted for 60% and 79.6%, respectively. MS patients with an active smoking history had a higher risk of relapse, for which the association became borderline significant after accounting for covariates (aHR=1.52, 95% CI=1.00, 2.31; p=0.052). The relapse risk between ever-smokers who smoked more than 10 cigarettes per day and smokers who smoked less than 10 cigarettes per day was not significantly different (aHR=0.96, 95% CI=0.63, 1.47; p=0.859). However, exposure to passive smoking was associated with a reduced risk of MS relapse (aHR=0.75, 95% CI=0.56, 1.00; p=0.044) compared with never-exposed patients. No associations were observed between active smoking/passive smoking and the risk of NMOSD relapse, but patients with a history of smoking were associated with a lower annual progression rate by Expanded Disability Status Scale (EDSS) (aβ=−0.20, 95% CI=−0.38, −0.01; p=0.036) and Multiple Sclerosis Severity Score (MSSS) (aβ=−0.23, 95% CI=−0.44, −0.03; p=0.028). Conclusion: Our research shows that active smoking increases the relapse risk of MS and has a negative impact on disability progression; thus, smoking cessation should be encouraged.
2024,
54(3):
0304.
doi: 10.52396/JUSTC-2023-0143
Abstract:
This research aimed to design and fabricate a biocompatible dual-layer chitosan hydrogel adhesive patch with exceptional mechanical properties by employing a nanoadhesive strategy to assess its tissue adhesion performance. The design involves physical cross-linking to construct a robust chitosan hydrogel as a backing membrane, followed by in situ photocuring to create the adhesive hydrogel layer, resulting in an integrated chitosan hydrogel adhesive patch. To facilitate adhesion between the hydrogel patch and biological tissue, surface-activated silica nanoparticles serve as interfacial connectors, analogous to nanoglue, promoting binding of the hydrogel to the substrate. Characterization of the patch reveals an adhesive energy of 282 J/m2 to biological tissues in vitro and a burst pressure of 450 mmHg (1 mmHg=0.133 kPa). The patch exhibits outstanding mechanical properties, with a tensile strength of 4.3 MPa, an elongation rate of 65%, and a fracture toughness of 3.82 kJ/m2. Additionally, the nanohesion-based chitosan hydrogel adhesive patch is highly transparent and demonstrates excellent biocompatibility. It holds promise for applications in various biomedical fields, including tissue repair and drug delivery, thereby providing a robust material foundation for advancements in clinical surgery.
This research aimed to design and fabricate a biocompatible dual-layer chitosan hydrogel adhesive patch with exceptional mechanical properties by employing a nanoadhesive strategy to assess its tissue adhesion performance. The design involves physical cross-linking to construct a robust chitosan hydrogel as a backing membrane, followed by in situ photocuring to create the adhesive hydrogel layer, resulting in an integrated chitosan hydrogel adhesive patch. To facilitate adhesion between the hydrogel patch and biological tissue, surface-activated silica nanoparticles serve as interfacial connectors, analogous to nanoglue, promoting binding of the hydrogel to the substrate. Characterization of the patch reveals an adhesive energy of 282 J/m2 to biological tissues in vitro and a burst pressure of 450 mmHg (1 mmHg=0.133 kPa). The patch exhibits outstanding mechanical properties, with a tensile strength of 4.3 MPa, an elongation rate of 65%, and a fracture toughness of 3.82 kJ/m2. Additionally, the nanohesion-based chitosan hydrogel adhesive patch is highly transparent and demonstrates excellent biocompatibility. It holds promise for applications in various biomedical fields, including tissue repair and drug delivery, thereby providing a robust material foundation for advancements in clinical surgery.
2023,
53(12):
1203.
doi: 10.52396/JUSTC-2023-0132
Abstract:
Humans flexibly adjust their reliance on model-free (habitual) and model-based (goal-directed) strategies according to cost‒benefit trade-offs, the ability of which is known as metacontrol. Recent studies have suggested that older adults show reduced flexibility in metacontrol. However, whether the metacontrol deficit in aging is due to cognitive or motivational factors remains ambiguous. The present study investigated this issue using pupillometry recording and a sequential decision-making task with varied task structures and reward stakes. Our results revealed that older adults performed less model-based control and less flexibility when the reward stake level changed, consistent with previous studies. However, pupillometry analysis indicated that older adults showed comparable sensitivity to the reward stake. Older adults varied in task structure knowledge according to their oral reports, and the subgroup with good structural knowledge exerted a similar pattern to younger adults. Computational simulation verified that poor structure knowledge representation impaired metacontrol. These results suggest that the inflexible metacontrol in the elderly population might not be due to motivational factors but rather poor structure knowledge.
Humans flexibly adjust their reliance on model-free (habitual) and model-based (goal-directed) strategies according to cost‒benefit trade-offs, the ability of which is known as metacontrol. Recent studies have suggested that older adults show reduced flexibility in metacontrol. However, whether the metacontrol deficit in aging is due to cognitive or motivational factors remains ambiguous. The present study investigated this issue using pupillometry recording and a sequential decision-making task with varied task structures and reward stakes. Our results revealed that older adults performed less model-based control and less flexibility when the reward stake level changed, consistent with previous studies. However, pupillometry analysis indicated that older adults showed comparable sensitivity to the reward stake. Older adults varied in task structure knowledge according to their oral reports, and the subgroup with good structural knowledge exerted a similar pattern to younger adults. Computational simulation verified that poor structure knowledge representation impaired metacontrol. These results suggest that the inflexible metacontrol in the elderly population might not be due to motivational factors but rather poor structure knowledge.
2023,
53(12):
1204.
doi: 10.52396/JUSTC-2023-0067
Abstract:
Objectives: Various diet scores have been established to measure overall diet quality, especially for the prevention of cardiovascular disease (CVD). Diet scores constructed by utilizing modern machine learning techniques may contain independent information and can provide better dietary recommendations in combination with the existing diet scores. Methods: We proposed a novel machine-learning diet quality score (DQS) and examined the performance of DQS in combination with the Healthy Eating Index-2015 (HEI2015), Mediterranean Diet Score (MED), Alternative Healthy Eating Index-2010 (AHEI) and Dietary Approaches to Stop Hypertension score (DASH score). The data used in this study were from the 2011–2012 to 2017–2018 cycles of the US National Health and Nutrition Examination Survey (NHANES). Participants aged above 20 self-reported their food intake and information on relevant covariates. We used an elastic-net penalty regression model to select important food features and used a generalized linear regression model to estimate odds ratios (ORs) and 95% CIs after controlling for age, sex, and other relevant covariates. Results: A total of 16756 participants were included in the analysis. DQS was significantly associated with coronary artery disease (CAD) risk after adjusting for one of the other common diet scores. The ORs for DQS combined with the HEI2015, MED, AHEI, and DASH scores were all approximately 0.900, with p values smaller than 0.05. The OR for DQS in the full score model including all other scores was 0.905 (95% CI, 0.828–0.989, p=0.028). Only marginal associations were found between DQS and other CVDs after adjusting for other diet scores. Conclusions: Based on data from four continuous cycles of the NHANES, higher DQS was found to be consistently associated with a lower risk of CAD. The DQS captured unique predictive information independent of the existing diet scores and thus can be used as a complementary scoring system to further improve dietary recommendations for CAD patients.
Objectives: Various diet scores have been established to measure overall diet quality, especially for the prevention of cardiovascular disease (CVD). Diet scores constructed by utilizing modern machine learning techniques may contain independent information and can provide better dietary recommendations in combination with the existing diet scores. Methods: We proposed a novel machine-learning diet quality score (DQS) and examined the performance of DQS in combination with the Healthy Eating Index-2015 (HEI2015), Mediterranean Diet Score (MED), Alternative Healthy Eating Index-2010 (AHEI) and Dietary Approaches to Stop Hypertension score (DASH score). The data used in this study were from the 2011–2012 to 2017–2018 cycles of the US National Health and Nutrition Examination Survey (NHANES). Participants aged above 20 self-reported their food intake and information on relevant covariates. We used an elastic-net penalty regression model to select important food features and used a generalized linear regression model to estimate odds ratios (ORs) and 95% CIs after controlling for age, sex, and other relevant covariates. Results: A total of 16756 participants were included in the analysis. DQS was significantly associated with coronary artery disease (CAD) risk after adjusting for one of the other common diet scores. The ORs for DQS combined with the HEI2015, MED, AHEI, and DASH scores were all approximately 0.900, with p values smaller than 0.05. The OR for DQS in the full score model including all other scores was 0.905 (95% CI, 0.828–0.989, p=0.028). Only marginal associations were found between DQS and other CVDs after adjusting for other diet scores. Conclusions: Based on data from four continuous cycles of the NHANES, higher DQS was found to be consistently associated with a lower risk of CAD. The DQS captured unique predictive information independent of the existing diet scores and thus can be used as a complementary scoring system to further improve dietary recommendations for CAD patients.
2023,
53(12):
1205.
doi: 10.52396/JUSTC-2023-0089
Abstract:
Type 2 diabetes mellitus is often accompanied by serious complications, including bone metabolic diseases, liver diseases, and kidney diseases, which are affected by the course of disease, sex, age and individual differences and cannot be a unified treatment paradigm. Therefore, for the in-depth analysis of clinical data, looking for the correlation of type 2 diabetes complication data has important guiding significance for the treatment of type 2 diabetes and its complications. In this paper, multiple linear regression models were established based on the clinical data of type 2 diabetes patients in Anhui Province. Our results suggest that the main factors affecting bone complications of type 2 diabetes include body shape indexes, creatinine, uric acid, triglycerides and blood pressure. Interestingly, the bone mineral density of lumbar vertebrae in patients with type 2 diabetes was increased, suggesting that there was a risk of lumbar hyperosteogeny.
Type 2 diabetes mellitus is often accompanied by serious complications, including bone metabolic diseases, liver diseases, and kidney diseases, which are affected by the course of disease, sex, age and individual differences and cannot be a unified treatment paradigm. Therefore, for the in-depth analysis of clinical data, looking for the correlation of type 2 diabetes complication data has important guiding significance for the treatment of type 2 diabetes and its complications. In this paper, multiple linear regression models were established based on the clinical data of type 2 diabetes patients in Anhui Province. Our results suggest that the main factors affecting bone complications of type 2 diabetes include body shape indexes, creatinine, uric acid, triglycerides and blood pressure. Interestingly, the bone mineral density of lumbar vertebrae in patients with type 2 diabetes was increased, suggesting that there was a risk of lumbar hyperosteogeny.
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