Life Sciences
Display Method:
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.
2023,
53(9):
0901.
doi: 10.52396/JUSTC-2022-0184
Abstract:
It is a fundamental task to ensure the faithful transmission of genetic information across generations for eukaryote species. The centromere is a specialized chromosomal region that is essential for mediating sister chromatid alignment and separation during mitosis. Centromere identity is epigenetically determined by nucleosome-containing centromere protein A (CENP-A). The CENP-A nucleosome provides the foundation for the association of the inner kinetochore and the assembly of the outer kinetochore in mitosis. Here we review centromere identity determination, inner kinetochore function and assembly, and outer kinetochore function and assembly. In particular, we focus on the recent advances in the structure-activity relationship of the constitutive centromere-associated network (CCAN). CCAN structure information sheds new light on our understanding of centromere and kinetochore functions and dynamic organization.
It is a fundamental task to ensure the faithful transmission of genetic information across generations for eukaryote species. The centromere is a specialized chromosomal region that is essential for mediating sister chromatid alignment and separation during mitosis. Centromere identity is epigenetically determined by nucleosome-containing centromere protein A (CENP-A). The CENP-A nucleosome provides the foundation for the association of the inner kinetochore and the assembly of the outer kinetochore in mitosis. Here we review centromere identity determination, inner kinetochore function and assembly, and outer kinetochore function and assembly. In particular, we focus on the recent advances in the structure-activity relationship of the constitutive centromere-associated network (CCAN). CCAN structure information sheds new light on our understanding of centromere and kinetochore functions and dynamic organization.
2023,
53(9):
0902.
doi: 10.52396/JUSTC-2023-0072
Abstract:
There have been increasing requirements for women’s fertility preservation due to oncological and nononcological reasons in recent years, and meeting these demands will be a hot topic in the coming years. Oocyte cryopreservation is a workable option for preserving women’s fertility, and great advances have already been made and much progress has been made in mammalian gene banking and human oocyte banks. In this paper, we systematically introduce the history of oocyte cryopreservation and vitrification technology and highlight the vitrification carrier. Furthermore, we summarize the fundamentals of oocyte vitrification and discuss the effects of vitrification on oocyte quality. Strategies to improve the effect of oocyte cryopreservation are also proposed. At the end of this review, we conclude oocyte cryopreservation and outline future perspectives.
There have been increasing requirements for women’s fertility preservation due to oncological and nononcological reasons in recent years, and meeting these demands will be a hot topic in the coming years. Oocyte cryopreservation is a workable option for preserving women’s fertility, and great advances have already been made and much progress has been made in mammalian gene banking and human oocyte banks. In this paper, we systematically introduce the history of oocyte cryopreservation and vitrification technology and highlight the vitrification carrier. Furthermore, we summarize the fundamentals of oocyte vitrification and discuss the effects of vitrification on oocyte quality. Strategies to improve the effect of oocyte cryopreservation are also proposed. At the end of this review, we conclude oocyte cryopreservation and outline future perspectives.
2023,
53(9):
0904.
doi: 10.52396/JUSTC-2023-0048
Abstract:
Circular RNAs (circRNAs) are covalently closed circular RNAs, and some of them preserve translation potency. However, modulation of circRNA translation efficiency and its applications need to be explored. In this study, RNAs containing the translation initiation element CVB3 IRES and the coding sequence of luciferase protein were transcribed and circularized in vitro by T7 RNA polymerase and an optimized permutated intron‒exon (PIE) splicing strategy. The circularized RNAs were then transfected and translated into active luciferase in the cultured cells. Insertion of miRNA binding sites at the flanking region of the luciferase coding sequence significantly reduced the translation efficiency of the circRNAs. Mutations of the miRNA binding sites in the firefly luciferase coding sequence led to increased translation efficiency of synthetic circRNAs in cells. We also proved that mutations of the binding sites of specific miRNAs also enhanced the translation efficiency of synthetic circRNAs. Further in vivo experiments via bioluminescence imaging showed that synonymous mutation of the miRNA binding sites promoted synthetic circRNA translation in nude mice. This study demonstrates that the modulation of miRNA binding sites affects the translation efficiency of synthetic circRNAs in vitro and in vivo, which could be used as versatile tools for future applications in clinical imaging.
Circular RNAs (circRNAs) are covalently closed circular RNAs, and some of them preserve translation potency. However, modulation of circRNA translation efficiency and its applications need to be explored. In this study, RNAs containing the translation initiation element CVB3 IRES and the coding sequence of luciferase protein were transcribed and circularized in vitro by T7 RNA polymerase and an optimized permutated intron‒exon (PIE) splicing strategy. The circularized RNAs were then transfected and translated into active luciferase in the cultured cells. Insertion of miRNA binding sites at the flanking region of the luciferase coding sequence significantly reduced the translation efficiency of the circRNAs. Mutations of the miRNA binding sites in the firefly luciferase coding sequence led to increased translation efficiency of synthetic circRNAs in cells. We also proved that mutations of the binding sites of specific miRNAs also enhanced the translation efficiency of synthetic circRNAs. Further in vivo experiments via bioluminescence imaging showed that synonymous mutation of the miRNA binding sites promoted synthetic circRNA translation in nude mice. This study demonstrates that the modulation of miRNA binding sites affects the translation efficiency of synthetic circRNAs in vitro and in vivo, which could be used as versatile tools for future applications in clinical imaging.
- First
- Prev
- 1
- 2
- 3
- Next
- Last
- Total:3
- To
- Go
