Embryo Transfer Strategies for Women with Recurrent Implantation Failure During the Frozen-thawed Embryo Transfer Cycles: Sequential Embryo Transfer or Double-blastocyst Transfer?

OBJECTIVE: Both sequential embryo transfer (SeET) and double-blastocyst transfer (DBT) can serve as embryo transfer strategies for women with recurrent implantation failure (RIF). This study aims to compare the effects of SeET and DBT on pregnancy outcomes. METHODS: Totally, 261 frozen-thawed embryo transfer cycles of 243 RIF women were included in this multicenter retrospective analysis. According to different embryo quality and transfer strategies, they were divided into four groups: group A, good-quality SeET (GQ-SeET, n=38 cycles); group B, poor-quality or mixed-quality SeET (PQ/MQ-SeET, n=31 cycles); group C, good-quality DBT (GQ-DBT, n=121 cycles); and group D, poor-quality or mixed-quality DBT (PQ/MQ-DBT, n=71 cycles). The main outcome, clinical pregnancy rate, was compared, and the generalized estimating equation (GEE) model was used to correct potential confounders that might impact pregnancy outcomes. RESULTS: GQ-DBT achieved a significantly higher clinical pregnancy rate (aOR 2.588, 95% CI 1.267-5.284, P=0.009) and live birth rate (aOR 3.082, 95% CI 1.482-6.412, P=0.003) than PQ/MQ-DBT. Similarly, the clinical pregnancy rate was significantly higher in GQ-SeET than in PQ/MQ-SeET (aOR 4.047, 95% CI 1.218-13.450, P=0.023). The pregnancy outcomes of GQ-SeET were not significantly different from those of GQ-DBT, and the same results were found between PQ/MQ-SeET and PQ/MQ-DBT. CONCLUSION: SeET relative to DBT did not seem to improve pregnancy outcomes for RIF patients if the embryo quality was comparable between the two groups. Better clinical pregnancy outcomes could be obtained by transferring good-quality embryos, no matter whether in SeET or DBT. Embryo quality plays a more important role in pregnancy outcomes for RIF patients.

Single­nucleotide polymorphism rs6592645 confers asthma risk through regulating LRRC32 expression.

Asthma is a complex disease, often with evident genetic predisposition; for example, the single-nucleotide polymorphism (SNP) rs7130588 was significantly associated with asthma by genome-wide association study (GWAS). Analysis of 1000 Genomes Project data suggests that there is another SNP, rs6592645, in complete linkage disequilibrium with rs7130588 and should present the same signal in GWAS. However, the causal SNP and the mechanism for the association between rs7130588 and asthma remain to be elucidated. In the presents study, results from dual-luciferase assays indicated that the A/G alleles of rs7130588 failed to present significantly different reporter gene expression. By contrast, A allele of rs6592645 presented a significant increase in relative luciferase activity than G allele, thus suggesting that rs6592645 may be a causal SNP. Using chromosome conformation capture, the enhancer region containing rs6592645 was observed to interact with promoter region of leucine-rich repeat-containing 32 (LRRC32). Gene expression quantification suggested that LRRC32 expression is significantly increased in lung tissue of patients with asthma and is dependent on the genotype of this locus, thus verifying that LRRC32 may be involved in asthma onset and that rs6592645 can regulate LRRC32 expression. Through chromatin immunoprecipitation, transcription factor 3 (TCF3) was identified to bind to rs6592645 surrounding region and the interaction between TCF3 and rs6592645 surrounding region was investigated. Results from the present study may improve our understanding of the mechanism by which the genetic variation in this locus might influence asthma susceptibility.

Remote regulation of rs80245547 and rs72673891 mediated by transcription factors C-Jun and CREB1 affect GSTCD expression.

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is influenced by genetic factors. The genetic signal rs10516526 in the glutathione S-transferase C-terminal domain containing (GSTCD) gene is a highly significant and reproducible signal associated with lung function and COPD on chromosome 4q24. In this study, comprehensive bioinformatics analyses and experimental verifications were detailly implemented to explore the regulation mechanism of rs10516526 and GSTCD in COPD. The results suggested that low expression of GSTCD was associated with COPD (p = 0.010). And C-Jun and CREB1 transcription factors were found to be essential for the regulation of GSTCD by rs80245547 and rs72673891. Moreover, rs80245547T and rs72673891G had a stronger binding ability to these transcription factors, which may promote the allele-specific long-range enhancer-promoter interactions on GSTCD, thus making COPD less susceptible. Our study provides a new insight into the relationship between rs10516526, GSTCD, and COPD.

The impact of weight loss for obese infertile women prior to in vitro fertilization: A retrospective cohort study.

Obesity is detrimental to general health and also reproductive health. This study aimed to evaluate whether weight reduction in obese infertile women prior to in vitro fertilization reduces the total gonadotropin dose and improves pregnancy outcomes. This retrospective cohort study was performed at the Jiaxing Maternity and Child Health Care Hospital between January 2017 and January 2022, and 197 women were enrolled. The women were divided into 2 groups according to the weight loss goal of 5%: weight reduction group A (≥weight loss goal of 5%) and control group A (

Visual Relationship Detection with Multimodal Fusion and Reasoning.

Visual relationship detection aims to completely understand visual scenes and has recently received increasing attention. However, current methods only use the visual features of images to train the semantic network, which does not match human habits in which we know obvious features of scenes and infer covert states using common sense. Therefore, these methods cannot predict some hidden relationships of object-pairs from complex scenes. To address this problem, we propose unifying vision-language fusion and knowledge graph reasoning to combine visual feature embedding with external common sense knowledge to determine the visual relationships of objects. In addition, before training the relationship detection network, we devise an object-pair proposal module to solve the combination explosion problem. Extensive experiments show that our proposed method outperforms the state-of-the-art methods on the Visual Genome and Visual Relationship Detection datasets.

A novel EEG decoding method for a facial-expression-based BCI system using the combined convolutional neural network and genetic algorithm.

Multiple types of brain-control systems have been applied in the field of rehabilitation. As an alternative scheme for balancing user fatigue and the classification accuracy of brain-computer interface (BCI) systems, facial-expression-based brain control technologies have been proposed in the form of novel BCI systems. Unfortunately, existing machine learning algorithms fail to identify the most relevant features of electroencephalogram signals, which further limits the performance of the classifiers. To address this problem, an improved classification method is proposed for facial-expression-based BCI (FE-BCI) systems, using a convolutional neural network (CNN) combined with a genetic algorithm (GA). The CNN was applied to extract features and classify them. The GA was used for hyperparameter selection to extract the most relevant parameters for classification. To validate the superiority of the proposed algorithm used in this study, various experimental performance results were systematically evaluated, and a trained CNN-GA model was constructed to control an intelligent car in real time. The average accuracy across all subjects was 89.21 ± 3.79%, and the highest accuracy was 97.71 ± 2.07%. The superior performance of the proposed algorithm was demonstrated through offline and online experiments. The experimental results demonstrate that our improved FE-BCI system outperforms the traditional methods.

Quantum decision making in automatic driving.

The behavior intention estimation and interaction between Autonomous Vehicles (AV) and human traffic participants are the key problems in Automatic Driving System (ADS). When the classical decision theory studies implicitly assume that the behavior of human traffic participants is completely rational. However, according to the booming quantum decision theory in recent years and actual traffic cases, traffic behaviors and other human behaviors are often irrational and violate the assumptions of classical cognitive and decision theory. This paper explores the decision-making problem in the two-car game scene based on quantum decision theory and compares it with the current mainstream method of studying irrational behavior-Cumulative Prospect Theory (CPT) model. The comparative analysis proved that the Quantum Game Theory (QGT) model can explain the separation effect which the classical probability model can't reveal, and it has more advantages than CPT model in dealing with game scene decision-making. When two cars interact with each other, the QGT model can consider the interests of both sides from the perspective of the other car. Compared with the classical probability model and CPT model, the QGT is more realistic in the behavior decision-making of ADS.

Cobot Motion Planning Algorithm for Ensuring Human Safety Based on Behavioral Dynamics.

Recently, the safety of workers has gained increasing attention due to the applications of collaborative robots (cobot). However, there is no quantitative research on the impact of cobot behavior on humans' psychological reactions, and these results are not applied to the cobot motion planning algorithms. Based on the concept of the gravity field, this paper proposes a model of the psychological safety field (PSF), designs a comprehensive experiment on different speeds and minimum distances when approaching the head, chest, and abdomen, and obtains the ordinary surface equation of psychological stress about speed and minimum distance by using data fitting. By combining social rules and PSF models, we improve the robot motion planning algorithm based on behavioral dynamics. The validation experiment results show that our proposed improved robot motion planning algorithm can effectively reduce psychological stress. Eighty-seven point one percent (87.1%) of the experimental participants think that robot motion planned by improved robot motion planning algorithms is more "friendly", can effectively reduce psychological stress, and is more suitable for human-robot interaction scenarios.

Potential risk assessment for safe driving of autonomous vehicles under occluded vision.

This study aimed to explore how autonomous vehicles can predict potential risks and efficiently pass through the dangerous interaction areas in the face of occluded scenes or limited visual scope. First, a Dynamic Bayesian Network based model for real-time assessment of potential risks is proposed, which enables autonomous vehicles to observe the surrounding risk factors, and infer and quantify the potential risks at the visually occluded areas. The risk distance coefficient is established to integrate the perception interaction ability of traffic participants into the model. Second, the predicted potential risk is applied to vehicle motion planning. The vehicle movement is improved by adjusting the speed and heading angle control. Finally, a dynamic simulation platform is built to verify the proposed model in two specific scenarios of view occlusion. The model has been compared with the existing methods, the autonomous vehicles can accurately assess the potential danger of the occluded areas in real-time and can safely, comfortably, and effectively pass through the dangerous interaction areas.

Research on quantum cognition in autonomous driving.

Autonomous vehicles for the intention of human behavior of the estimated traffic participants and their interaction is the main problem in automatic driving system. Classical cognitive theory assumes that the behavior of human traffic participants is completely reasonable when studying estimation of intention and interaction. However, according to the quantum cognition and decision theory as well as practical traffic cases, human behavior including traffic behavior is often unreasonable, which violates classical cognition and decision theory. Based on the quantum cognitive theory, this paper studies the cognitive problem of pedestrian crossing. Through the case analysis, it is proved that the Quantum-like Bayesian (QLB) model can consider the reasonability of pedestrians when crossing the street compared with the classical probability model, being more consistent with the actual situation. The experiment of trajectory prediction proves that the QLB model can cover the edge events in interactive scenes compared with the data-driven Social-LSTM model, being more consistent with the real trajectory. This paper provides a new reference for the research on the cognitive problem of intention on bounded rational behavior of human traffic participants in autonomous driving.

Convergent Evidence Supports TH2LCRR as a Novel Asthma Susceptibility Gene.

Asthma is a common, complex disease with apparent genetic predispositions, and previous genome-wide association studies suggest that rs1295686 within the IL13 (IL-13) gene is significantly associated with asthma. Analysis of the data provided by the 1,000 Genomes Project indicated an additional four SNPs in nearly complete linkage disequilibrium with rs1295686 in White people. However, the causal SNPs and the associated mechanism remain unclear. To investigate this issue, functional genomics approaches were utilized to analyze the functions of these SNPs. Dual-luciferase assays indicated that the functional SNP is not rs1295686 but a haplotype consisting of three other SNPs: rs1295685, rs848, and rs847. Through chromosome conformation capture, it was found that the enhancer containing the three functional SNPs interacts with the promoter of TH2LCRR (T helper type 2 locus control region associated RNA), a recently identified long noncoding RNA. RNA-seq data analysis indicated that TH2LCRR expression is significantly increased in patients with asthma and is dependent on the genotype at this locus, indicating that TH2LCRR is a novel susceptibility gene for asthma and that these SNPs confer asthma risk by regulating TH2LCRR expression. By chromatin immunoprecipitation, the related transcription factors that bind in the region surrounding these three SNPs were identified, and their interactions were investigated by functional genomics approaches. Our effort identified a novel mechanism through which genetic variations at this locus could influence asthma susceptibility.

T-Helper 17 Cell/Regulatory T-Cell Imbalance in COPD Combined with T2DM Patients.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is often combined with type 2 diabetes mellitus (T2DM) in clinical, and with poor prognosis. In recent years, research shows that inflammation is a common characteristic of COPD and T2DM. T-helper 17 cell (Th17)/regulatory T-cell (Treg) balance controls inflammation and may be important in the pathogenesis of COPD combined with T2DM patients. This study investigated the characteristics of Th17, Treg and related inflammatory factors in COPD combined with T2DM patients and the potential mechanism. METHODS: Application of flow cytometry technology, real-time fluorescent quantitative PCR and ELISA to detect the changes in peripheral blood of Th17 and Treg number and the expression of key transcription factors and related cytokines in COPD combined T2DM patients were performed. RESULTS: Patients with COPD combined with T2DM revealed significant increase in peripheral Th17, Th17 related cytokines (IL-17A, IL-17F, IL-21, IL-23, IL-6) and transcription factor (RORγt) levels and significant decrease in Treg, Treg-related cytokines (IL-10, TGFß1) and transcription factor (Foxp3) as compared with patients with COPD, T2DM and healthy controls. CONCLUSION: Th17/Treg functional imbalance exists in patients with COPD combined with T2DM, indicating a potential role of Th17/Treg imbalance in the formation and progression of COPD combined with T2DM.

Identification of rs11615992 as a novel regulatory SNP for human P2RX7 by allele-specific expression.

P2RX7 (purinergic receptor P2X 7) is an important membrane ion channel and involved in multiple physiological processes. One non-synonymous SNP on P2RX7, rs3751143, had been proven to reduce ion channel function and further associated with multiple diseases. However, it was still unclear whether there were other cis-regulatory elements for P2RX7, which might further contribute to related diseases. Allele-specific expression (ASE) is a robust and sensitive approach to identify the potential functional region in human genome. In the current study, we measured ASE on rs3751143 in lung tissues and observed a consistent excess of A allele over C (P = 0.001), which indicated that SNP(s) in linkage disequilibrium (LD) could regulate P2RX7 expression. By analyzing the 1000 genomes project data for Chinese, one SNP locating ~ 5 kb away and downstream of P2RX7, rs11615992, was disclosed to be in strong LD with rs3751143. The dual-luciferase assay confirmed that rs11615992 could alter target gene expression in lung cell line. Through chromosome conformation capture, it was verified that the region surrounding rs11615992 could interact with P2RX7 promoter and effect as an enhancer. By chromatin immunoprecipitation, the related transcription factor POU2F1 (POU class 2 homeobox 1) was recognized to bind the region spanning rs11615992. Our work identified a novel long-distance cis-regulatory SNP for P2RX7, which might contribute to multiple diseases.

Allele-specific expression identified rs2509956 as a novel long-distance cis-regulatory SNP for SCGB1A1, an important gene for multiple pulmonary diseases.

SCGB1A1 (secretoglobin family 1A member 1) is an important protein for multiple pulmonary diseases, especially asthma, chronic obstructive pulmonary disease, and lung cancer. One single-nucleotide polymorphism (SNP) at 5'-untranslated region of SCGB1A1, rs3741240, has been suggested to be associated with reduced protein expression and further asthma susceptibility. However, it was still unclear whether there were other cis-regulatory elements for SCGB1A1 that might further contribute to pulmonary diseases. Allele-specific expression (ASE) is a novel approach to identify the functional region in human genome. In the present study, we measured ASE on rs3741240 in lung tissues and observed a consistent excess of G allele over A (P < 10-6), which indicated that this SNP or the one(s) in linkage disequilibrium (LD) could regulate SCGB1A1 expression. By analyzing 1000 Genomes Project data for Chinese, one SNP locating ~10.2 kb away and downstream of SCGB1A1, rs2509956, was identified to be in strong LD with rs3741240. Reporter gene assay confirmed that both SNPs could regulate gene expression in the lung cell. By chromosome conformation capture, it was verified that the region surrounding rs2509956 could interact with SCGB1A1 promoter region and act as an enhancer. Through chromatin immunoprecipitation and overexpression assay, the related transcription factor RELA (RELA proto-oncogene, NF-kB subunit) was recognized to bind the region spanning rs2509956. Our work identified a novel long-distance cis-regulatory SNP for SCGB1A1, which might contribute to multiple pulmonary diseases.

Decreased expression of NEDD4L contributes to NSCLC progression and metastasis.

Recent evidence indicated that neural precursor cell expressed, developmentally down-regulated 4-like (NEDD4L) has a critical role in the regulation of cellular processes such as apoptosis, transport and metastasis, and is downregulated in several types of cancers. However, the role of NEDD4L in non-small cell lung cancer (NSCLC) has not been fully elucidated. In this study, we demonstrated that NEDD4L was downregulated in NSCLCs. This downregulation correlated with lymph node invasion, advanced stage and poor survival. In vitro experiments revealed that NEDD4L significantly suppressed cell proliferation, migration and invasion abilities. Further in vivo assay demonstrated that knocking down of NEDD4L enhanced the tumor metastasis of NSCLC cells. Moreover, we found that Polycomb group protein enhancer of zeste homologue 2 (EZH2) mediated H3K27 methylation was involved in the downregulation of NEDD4L. Knocking down of EZH2 restored the expression of NEDD4L. Further examined by luciferase reporter assay indicated the EZH2 regulated the transcription activity of NEDD4L. In clinical samples, EZH2 was inversely correlated with NEDD4L expression. In summary, NEDD4L acted as a tumor suppressor gene in NSCLC and targeting EZH2 could upregulate NEDD4L expression, which might serve as a novel approach for NSCLC.

1H-NMR-based metabolic profiling of healthy individuals and high-resolution CT-classified phenotypes of COPD with treatment of tiotropium bromide.

BACKGROUND: Heterogeneity of COPD results in different therapeutic effects for different patients receiving the same treatment. COPD patients need to be individually treated according to their own characteristics. The purpose of this study was to explore the differences in different CT phenotypic COPD by molecular metabolites through the use of metabolomics. METHODS: According to the characteristics of CT imaging, 42 COPD patients were grouped into phenotype E (n=20) or phenotype M (n=24). Each COPD patient received tiotropium bromide powder for inhalation for a therapeutic period of 3 months. All subjects were assigned into phenotype E in pre-therapy (EB, n=20), phenotype E in post-therapy (EA, n=20), phenotype M in pre-therapy (MB, n=22), phenotype M in post-therapy (MA, n=22), or normal control (N, n=24). The method of metabolomics based on 1H nuclear magnetic resonance (1H-NMR) was used to compare the changes in serum metabolites between COPD patients and normal controls and between different phenotypes of COPD patients in pre- and post-therapy. RESULTS: Patients with COPD phenotype E responded better to tiotropium bromide than patients with COPD phenotype M in terms of pulmonary function and COPD assessment test scores. There were differences in metabolites in COPD patients vs normal control people. Differences were also observed between different COPD phenotypic patients receiving the treatment in comparison with those who did not receive treatment. The changes of metabolites involved lactate, phenylalanine, fructose, glycine, asparagine, citric acid, pyruvic acid, proline, acetone, ornithine, lipid, pyridoxine, maltose, betaine, lipoprotein, and so on. These identified metabolites covered the metabolic pathways of amino acids, carbohydrates, lipids, genetic materials, and vitamin. CONCLUSION: The efficacy of tiotropium bromide on COPD phenotype E is better than that of phenotype M. Metabolites detected by 1H-NMR metabolomics have potentialities of differentiation of COPD and healthy people, discrimination of different COPD phenotypes, and giving insight into the individualized treatment of COPD.

rs401681 and rs402710 confer lung cancer susceptibility by regulating TERT expression instead of CLPTM1L in East Asian populations.

Lung cancer is a common cancer in human and has presented significant genetic predisposition. Previous genome-wide association study observed that rs401681 within CLPTM1L (CLPTM1 like) was significantly associated with lung cancer. By analyzing 1000 genomes data for East Asian, we identified only one SNP in nearby region, rs402710, in high linkage disequilibrium with rs401681, which was also associated with lung cancer. However, the real causal SNP and mechanism for the association were still not clear. The following plasmid construction, mutagenesis, transient transfection and luciferase reading indicated that both SNPs could regulate gene expression in lung/bronchial epithelium Beas-2B cell line. By chromosome conformation capture, it was identified that the segment containing these two SNPs could interact with TERT (telomerase reverse transcriptase) promoter, thus indicating that these SNPs confer lung cancer risk by regulating TERT expression instead of CLPTM1L. Through chromatin immunoprecipitation, the transcript factors HNF4A (hepatocyte nuclear factor 4 alpha) and MAF1 (MAF1 homolog, negative regulator of RNA polymerase III) were recognized for the regions spanning rs401681 and rs402710, respectively. Our results uncovered a complete link between these two SNPs and lung cancer.

A functional SNP upstream of the ADRB2 gene is associated with COPD.

Background: Previous studies have suggested that ß2-adrenergic receptor (ADRB2) is associated with COPD. However, the role of genetic polymorphisms in ADRB2 on COPD has not been evaluated yet. Methods: In this study, SNaPshot genotyping, luciferase assay, chromatin immunoprecipitation and real-time polymerase chain reaction were adopted to investigate the association between ADRB2 genetic polymorphisms and COPD, comprehensively. Results: One single nucleotide polymorphism (rs12654778), located upstream of ADRB2, showed a significant association with COPD by the logistic regression analysis after adjusting for age, sex and smoking history (p=0.04) in 200 COPD patients and 222 controls from southwest Chinese population. Furthermore, the luciferase assay indicated that rs12654778-A allele reduced the relative promoter activity by ~26% compared with rs12654778-G allele (p=0.0034). The chromatin immunoprecipitation analysis demonstrated that rs12654778 modulated the binding affinity of transcription factor neurofibromin 1. In addition, a significantly reduced expression of ADRB2 in COPD patients was observed, compared with normal controls (p=0.017). Conclusion: Our findings suggest a previously unknown mechanism linking allele-specific effects of rs12654778 on ADRB2 expression to COPD onset, for the first time.

Metabolic changes of different high-resolution computed tomography phenotypes of COPD after budesonide-formoterol treatment.

BACKGROUND: Metabolomics is the global unbiased analysis of all the small-molecule metabolites within a biological system. Metabolic profiling of different high-resolution computed tomography (HRCT) phenotypes of COPD patients before and after treatment may identify discriminatory metabolites that can serve as biomarkers and therapeutic agents. PATIENTS AND METHODS: 1H nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomics was performed on a discovery set of plasma samples from 50 patients with stable COPD. Patients were assigned into two groups on the basis of HRCT findings including phenotype E (n=22) and phenotype M (n=28). After budesonide-formoterol treatment (160/4.5 µg ×2 inhalations twice daily for 3 months), clinical characteristics and metabolites were then compared between phenotype E pretreatment and posttreatment, phenotype M pretreatment and posttreatment, phenotype E pretreatment and phenotype M pretreatment, and phenotype E posttreatment and phenotype M posttreatment. RESULTS: Inhaled budesonide-formoterol therapy for both phenotype E (emphysema without bronchial wall thickening) and phenotype M (emphysema with bronchial wall thickening) was effective. However, phenotype E and phenotype M were different in response to therapy. Patients with phenotype M in response to therapeutic effects were significantly greater compared with phenotype E. Certain metabolites were identified, which were closely related to the treatment and phenotype. Metabolic changes in phenotype E or phenotype M after treatment may be involved with adenosine diphosphate (ADP), guanosine, choline, malonate, tyrosine, glycine, proline, l-alanine, l-valine, l-threonine leucine, uridine, pyruvic acid, acetone and metabolism disturbance. Metabolic differences between phenotype E and phenotype M in pretreatment and posttreatment covered glycine, d-glucose, pyruvic acid, succinate, lactate, proline, l-valine and leucine. CONCLUSION: Bronchial wall thickening in COPD may be an indicator for predicting the better response to the treatment with bronchodilator and corticosteroid. The identification of metabolic alterations provides new insights into different HRCT phenotypes and therapeutic assessment of COPD.

Relationship between PPARα mRNA expression and mitochondrial respiratory function and ultrastructure of the skeletal muscle of patients with COPD.

Peripheral muscle dysfunction is an important complication in patients with chronic obstructive pulmonary disease (COPD). The objective of this study was to explore the relationship between the levels of peroxisome proliferator-activated receptor α (PPARα) mRNA expression and the respiratory function and ultrastructure of mitochondria in the vastus lateralis of patients with COPD. Vastus lateralis biopsies were performed on 14 patients with COPD and 6 control subjects with normal lung function. PPARα mRNA levels in the muscle tissue were detected by real-time PCR. A Clark oxygen electrode was used to assess mitochondrial respiratory function. Mitochondrial number, fractional area in skeletal muscle cross-sections, and Z-line width were observed via transmission electron microscopy. The PPARα mRNA expression was significantly lower in COPD patients with low body mass index (BMIL) than in both COPD patients with normal body mass index (BMIN) and controls. Mitochondrial respiratory function (assessed by respiratory control ratio) was impaired in COPD patients, particularly in BMIL. Compared with that in the control group, mitochondrial number and fractional area were lower in the BMIL group, but were maintained in the BMIN group. Further, the Z-line became narrow in the BMIL group. PPARα mRNA expression was positively related to mitochondrial respiratory function and volume density. In COPD patients with BMIN, mitochondria volume density was maintained, while respiratory function decreased, whereas both volume density and respiratory function decreased in COPD patients with BMIL. PPARα mRNA expression levels are associated with decreased mitochondrial respiratory function and volume density, which may contribute to muscle dysfunction in COPD patients.