Frailty as an Effect Modifier in Randomized Controlled Trials: A Systematic Review.

BACKGROUND: The effect of clinical interventions may vary by patients' frailty status. Understanding treatment effect heterogeneity by frailty could lead to frailty-guided treatment strategies and reduce overtreatment and undertreatment. This systematic review aimed to examine the effect modification by frailty in randomized controlled trials (RCTs) that evaluate pharmacological, non-pharmacological, and multicomponent interventions. METHODS: We searched PubMed, Web of Science, EMBASE, and ClinicalTrial.gov, from their inception to 8 December 2023. Two reviewers independently extracted trial data and examined the study quality with senior authors. RESULTS: Sixty-one RCTs that evaluated the interaction between frailty and treatment effects in older adults were included. Frailty was evaluated using different tools such as the deficit accumulation frailty index, frailty phenotype, and other methods. The effect of several pharmacological interventions (e.g., edoxaban, sacubitril/valsartan, prasugrel, and chemotherapy) varied according to the degree of frailty, whereas other treatments (e.g., antihypertensives, vaccinations, osteoporosis medications, and androgen medications) demonstrated consistent benefits across different frailty levels. Some non-pharmacological interventions had greater benefits in patients with higher (e.g., chair yoga, functional walking, physical rehabilitation, and higher dose exercise program) or lower (e.g., intensive lifestyle intervention, psychosocial intervention) levels of frailty, while others (e.g., resistance-type exercise training, moderate-intensive physical activity, walking and nutrition or walking) produced similar intervention effects. Specific combined interventions (e.g., hospital-based disease management programs) demonstrated inconsistent effects across different frailty levels. DISCUSSION: The efficacy of clinical interventions often varied by frailty levels, suggesting that frailty is an important factor to consider in recommending clinical interventions in older adults. REGISTRATION: PROSPERO registration number CRD42021283051.

Swift Covalent Gelation Coupled with Robust Wet Adhesive Powder: A Novel Approach for Acute Massive Hemorrhage Control in Dynamic and High-Pressure Wound Environments.

The quest for efficient hemostatic agents in emergency medicine is critical, particularly for managing massive hemorrhages in dynamic and high-pressure wound environments. Traditional self-gelling powders, while beneficial due to their ease of application and rapid action, fall short in such challenging conditions. To bridge this gap, the research introduces a novel self-gelling powder that combines ultrafast covalent gelation and robust wet adhesion, presenting a significant advancement in acute hemorrhage control. This ternary system comprises ε-polylysine (ε-PLL) and 4-arm polyethylene glycol succinyl succinate (4-arm-PEG-NHS) forming the hydrogel framework. Na2HPO4 functions as the "H+ sucker" to expedite the amidation reaction, slashing gelation time to under 10 s, crucial for immediate blood loss restriction. Moreover, PEG chains' hydrophilicity facilitates efficient absorption of interfacial blood, increasing the generated hydrogel's cross-linking density and strengthens its tissue bonding, thereby resulting in excellent mechanical and wet adhesion properties. In vitro experiments reveal the optimized formulation's exceptional tissue compliance, procoagulant activity, biocompatibility and antibacterial efficacy. In porcine models of heart injuries and arterial punctures, it outperforms commercial hemostatic agent Celox, confirming its rapid and effective hemostasis. Conclusively, this study presents a transformative approach to hemostasis, offering a reliable and potent solution for the emergency management of massive hemorrhage.

Effects of variable-temperature drying on the qualities and sweet-substance profile of Zizyphus jujuba Mill. cv. Junzao.

The changes in the qualities and sweet-substance levels of Junzao jujube during variable-temperature drying (VTD) were investigated. The results showed that VTD retains the original color of jujube, reduces its hardness and chewiness, and decreases its wrinkling while shortening the drying time by 13.2% compared with that of constant temperature drying (CTD). "Electronic-tongue" taste analysis showed that the sweetness of VTD jujube is significantly higher than that for CTD. This is shown to be related to the contents of sucrose, fructose, and glucose, as well as the activities of invertase and sucrose synthase enzymes. In addition, the content trends for sweet amino acids are correlated with the temperature gradient used in VTD. Thus, the present study elucidates the factors governing the transformation of sugar substances in jujube during VTD, as well as providing a practical reference for the application of VTD in the jujube industry.

Exact results for gene-expression models with general waiting-time distributions.

Complex molecular details of transcriptional regulation can be coarse-grained by assuming that reaction waiting times for promoter-state transitions, the mRNA synthesis, and the mRNA degradation follow general distributions. However, how such a generalized two-state model is analytically solved is a long-standing issue. Here we first present analytical formulas of burst-size distributions for this model. Then, we derive an iterative equation for the mRNA moment-generating function, by which mRNA raw and binomial moments of any order can be conveniently calculated. The analytical results obtained in the special cases of phase-type waiting-time distributions not only provide insights into the mechanisms of complex transcriptional regulations but also bring conveniences for experimental data-based statistical inferences.

Deep Learning-Based construction of a Drug-Like compound database and its application in virtual screening of HsDHODH inhibitors.

The process of virtual screening relies heavily on the databases, but it is disadvantageous to conduct virtual screening based on commercial databases with patent-protected compounds, high compound toxicity and side effects. Therefore, this paper utilizes generative recurrent neural networks (RNN) containing long short-term memory (LSTM) cells to learn the properties of drug compounds in the DrugBank, aiming to obtain a new and virtual screening compounds database with drug-like properties. Ultimately, a compounds database consisting of 26,316 compounds is obtained by this method. To evaluate the potential of this compounds database, a series of tests are performed, including chemical space, ADME properties, compound fragmentation, and synthesizability analysis. As a result, it is proved that the database is equipped with good drug-like properties and a relatively new backbone, its potential in virtual screening is further tested. Finally, a series of seedling compounds with completely new backbones are obtained through docking and binding free energy calculations.

Effect of Preoperative Lifestyle Management and Prehabilitation on Postoperative Capability of Colorectal Cancer Patients: A Systematic Review and Meta-Analysis.

BACKGROUND: The surgical intervention serves as the paramount and prevalent remedy for individuals afflicted with colorectal malignancies, with the significance of perioperative stewardship and convalescence being indisputable. Prehabilitation coupled with preoperative lifestyle modulation has demonstrated efficacy in patients subjected to certain classifications of abdominal procedures. However, the evidence pertaining to its impact on those battling colorectal cancer remains equivocal. METHODS: A meta-analysis, grounded in pairwise contrast, of randomized controlled trials (RCTs) was orchestrated, coupled with a systematic review, to probe the efficacy of preoperative lifestyle modulation and prehabilitation on patients' postoperative functionality and recuperation. An exhaustive exploration of 8 electronic databases and trial registries was undertaken to encompass all pertinent RCTs disseminated in English or Chinese from January 2012 through December 2022. Employing a random-effects model, we evaluated parameters such as the 6-minute walk test (6 MWT), complications, quality of life (QoL), aggregate and postoperative duration of hospitalization (tLHS and postLHS), and healthcare expenditure (HExp) for postoperative patients. RESULTS: A total of 28 RCTs were incorporated into the systematic review and meta-analysis. Relative to conventional preoperative care, rehabilitation or preoperative lifestyle management was found to enhance postoperative 6MWT (SMD 1.30, 95% CI 0.30 to 2.29) and diminish the complication rate (OR 0.53, 95% CI 0.40 to 0.69). Nonetheless, no significant discrepancies were observed in QoL (SMD 1.81, 95% CI -0.26 to 3.87), tLHS (SMD -0.26, 95% CI -0.68 to 0.15), and postLHS (SMD -1.46, 95% CI -3.12 to 0.20) between the groups. HExp could not be evaluated due to a lack of sufficient data for synthesis. Most pooled outcomes exhibited significant heterogeneity, urging a cautious interpretation. Subgroup analysis revealed that nutritional interventions could mitigate the incidence of complications, and preoperative exercise could improve tLHS and postLHS. A combined approach of physical, nutritional, and psychological intervention or prehabilitation proved superior to any single intervention in enhancing postoperative capabilities. CONCLUSION: This meta-analysis delineated the efficacy of preoperative interventions on postoperative capabilities in patients with colorectal cancer, thereby offering evidence for clinical practice. It was concluded that preoperative interventions are unequivocally beneficial for postoperative functional recovery and the reduction of complication rates in patients with colorectal cancer. Nonetheless, the acquisition of more high-level evidence is still necessitated to further ascertain the effectiveness of this strategy for other patient groups and to establish its best practices. The heterogeneity in the pooled outcomes underlines the need for future studies to be more uniform in their design and reporting, which would facilitate more robust and reliable meta-analyses.

Distribution and prognostic value of high-sensitivity cardiac troponin T and I across glycemic status: a population-based study.

BACKGROUND: Whether distributions and prognostic values of high-sensitivity cardiac troponin (hs-cTn) T and I are different across normoglycemic, prediabetic, and diabetic populations is unknown. METHODS: 10127 adult participants from the National Health and Nutrition Examination Survey 1999-2004 with determined glycemic status and measurement of at least one of hs-cTn assays were included, from whom healthy participants and presumably healthy diabetic and prediabetic participants were selected to investigate pure impacts of glycemic status on distributions of hs-cTn. The nonparametric method and bootstrapping were used to derive the 99th upper reference limits of hs-cTn and 95% CI. Participants with available follow-up and hs-cTn concentrations of all 4 assays were included in prognostic analyses. Associations of hs-cTn with all-cause and cardiac-specific mortality were modeled by Cox proportional hazard regression under the complex survey design. The incremental value of hs-cTn to an established risk score in predicting cardiac-specific mortality was assessed by the 10-year area under time-dependent receiver operating characteristic curve (AUC) using the Fine-Grey competing risk model. RESULTS: Among 9714 participants included in prognostic analyses, 5946 (61.2%) were normoglycemic, 2172 (22.4%) prediabetic, and 1596 (16.4%) diabetic. Hyperglycemic populations were older than the normoglycemic population but sex and race/ethnicity were similar. During the median follow-up of 16.8 years, hs-cTnT and hs-cTnI were independently associated with all-cause and cardiac-specific mortality across glycemic status. In the diabetic population, adjusted hazard ratios per 1-standard deviation increase of log-transformed hs-cTnT and hs-cTnI (Abbott) concentrations were 1.77 (95% CI 1.48-2.12; P < .001) and 1.83 (95% CI 1.33-2.53; P < .001), respectively, regarding cardiac-specific mortality. In the diabetic but not the normoglycemic population, adding either hs-cTnT (difference in AUC: 0.062; 95% CI 0.038-0.086; P < 0.001) or hs-cTnI (Abbott) (difference in AUC: 0.071; 95% CI 0.046-0.097; P < 0.001) would significantly increase the discriminative ability of the risk score; AUC of the score combined with hs-cTnT would be further improved by incorporating hs-cTnI (0.018; 95%CI 0.006-0.029; P = 0.002). The 99th percentile of hs-cTnT of the presumably healthy diabetic population was higher than the healthy population and had no overlap in 95% CIs, however, for hs-cTnI 99th percentiles of the two populations were very close and 95% CIs extensively overlapped. CONCLUSIONS: Hs-cTnT and hs-cTnI demonstrated consistent prognostic associations across glycemic status but incremental predictive values in hyperglycemic populations only. The susceptibility of hs-cTnT 99th percentiles to diabetes plus the additive value of hs-cTnI to hs-cTnT in diabetic cardiovascular risk stratification suggested hs-cTnI and hs-cTnT may be differentially associated with glycemic status, but further research is needed to illustrate the interaction between hyperglycemia and hs-cTn.

Uric acid levels and heart failure: A mendelian randomization study.

BACKGROUND AND AIMS: Uric acid, the end-product of purine metabolism within the human body, has been the subject of studies exploring its potential association with cardiovascular and cerebrovascular diseases. However, the precise relationship between uric acid levels and heart failure remains elusive. METHODS AND RESULTS: In this particular study, aggregated data from genome-wide association studies on uric acid and heart failure were utilized to perform a two-sample Mendelian randomization (MR) analysis utilizing R software. The aim was to uncover any causal link between these variables. The primary outcome was assessed using inverse variance weighted (IVW) methodology, while sensitivity analyses employed MR-Egger, weighted median (WME), and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) techniques. IVW results revealed a possible causal relationship between elevated uric acid levels and an increased risk of heart failure (OR: 1.09, 95 % CI: 1.01-1.17, P < 0.05). Encouragingly, the directions provided by MR-Egger and WME aligned with IVW findings, and no anomalies were detected in the remaining sensitivity analyses. CONCLUSION: These outcomes indicate the stability of the results of the study, thereby suggesting that heightened uric acid levels may contribute to an augmented risk of heart failure.

Inhibition of valve mesenchymal stromal cell calcium deposition by bFGF through alternative polyadenylation regulation of the CAT gene.

OBJECTIVE: Calcific aortic valve disease (CAVD) is the leading cause of angina, heart failure, and death from aortic stenosis. However, the molecular mechanisms of its progression, especially the complex disease-related transcriptional regulatory mechanisms, remain to be further elucidated. METHODS: This study used porcine valvular interstitial cells (PVIC) as a model. We used osteogenic induced medium (OIM) to induce calcium deposition in PVICs to calcify them, followed by basic fibroblast growth factor (bFGF) treatment to inhibit calcium deposition. Transcriptome sequencing was used to study the mRNA expression profile of PVICs and its related transcriptional regulation. We used DaPars to further examine alternative polyadenylation (APA) between different treatment groups. RESULTS: We successfully induced calcium deposition of PVICs through OIM. Subsequently, mRNA-seq was used to identify differentially expressed mRNAs for three different treatments: control, OIM-induced and OIM-induced bFGF treatment. Global APA events were identified in the OIM and bFGF treatment groups by bioinformatics analysis. Finally, it was discovered and proven that catalase (CAT) is one of the potential targets of bFGF-induced APA regulation. CONCLUSION: We described a global APA change in a calcium deposition model related to CAVD. We revealed that transcriptional regulation of the CAT gene may contribute to bFGF-induced calcium deposition inhibition.

Prognostic and predictive value of super-enhancer-derived signatures for survival and lung metastasis in osteosarcoma.

BACKGROUND: Risk stratification and personalized care are crucial in managing osteosarcoma due to its complexity and heterogeneity. However, current prognostic prediction using clinical variables has limited accuracy. Thus, this study aimed to explore potential molecular biomarkers to improve prognostic assessment. METHODS: High-throughput inhibitor screening of 150 compounds with broad targeting properties was performed and indicated a direction towards super-enhancers (SEs). Bulk RNA-seq, scRNA-seq, and immunohistochemistry (IHC) were used to investigate SE-associated gene expression profiles in osteosarcoma cells and patient tissue specimens. Data of 212 osteosarcoma patients who received standard treatment were collected and randomized into training and validation groups for retrospective analysis. Prognostic signatures and nomograms for overall survival (OS) and lung metastasis-free survival (LMFS) were developed using Cox regression analyses. The discriminatory power, calibration, and clinical value of nomograms were evaluated. RESULTS: High-throughput inhibitor screening showed that SEs significantly contribute to the oncogenic transcriptional output in osteosarcoma. Based on this finding, focus was given to 10 SE-associated genes with distinct characteristics and potential oncogenic function. With multi-omics approaches, the hyperexpression of these genes was observed in tumor cell subclusters of patient specimens, which were consistently correlated with poor outcomes and rapid metastasis, and the majority of these identified SE-associated genes were confirmed as independent risk factors for poor outcomes. Two molecular signatures were then developed to predict survival and occurrence of lung metastasis: the SE-derived OS-signature (comprising LACTB, CEP55, SRSF3, TCF7L2, and FOXP1) and the SE-derived LMFS-signature (comprising SRSF3, TCF7L2, FOXP1, and APOLD1). Both signatures significantly improved prognostic accuracy beyond conventional clinical factors. CONCLUSIONS: Oncogenic transcription driven by SEs exhibit strong associations with osteosarcoma outcomes. The SE-derived signatures developed in this study hold promise as prognostic biomarkers for predicting OS and LMFS in patients undergoing standard treatments. Integrative prognostic models that combine conventional clinical factors with these SE-derived signatures demonstrate substantially improved accuracy, and have the potential to facilitate patient counseling and individualized management.

Power-law behavior of transcriptional bursting regulated by enhancer-promoter communication.

Revealing how transcriptional bursting kinetics are genomically encoded is challenging because genome structures are stochastic at the organization level and are suggestively linked to gene transcription. To address this challenge, we develop a generic theoretical framework that integrates chromatin dynamics, enhancer-promoter (E-P) communication, and gene-state switching to study transcriptional bursting. The theory predicts that power law can be a general rule to quantitatively describe bursting modulations by E-P spatial communication. Specifically, burst frequency and burst size are up-regulated by E-P communication strength, following power laws with positive exponents. Analysis of the scaling exponents further reveals that burst frequency is preferentially regulated. Bursting kinetics are down-regulated by E-P genomic distance with negative power-law exponents, and this negative modulation desensitizes at large distances. The mutual information between burst frequency (or burst size) and E-P spatial distance further reveals essential characteristics of the information transfer from E-P communication to transcriptional bursting kinetics. These findings, which are in agreement with experimental observations, not only reveal fundamental principles of E-P communication in transcriptional bursting but also are essential for understanding cellular decision-making.

Phase separation reduces cell-to-cell variability of transcriptional bursting.

Gene expression is a stochastic and noisy process often occurring in "bursts". Experiments have shown that the compartmentalization of proteins by liquid-liquid phase separation is conducive to reducing the noise of gene expression. Therefore, an important goal is to explore the role of bursts in phase separation noise reduction processes. We propose a coupled model that includes phase separation and a two-state gene expression process. Using the timescale separation method, we obtain approximate solutions for the expectation, variance, and noise strength of the dilute phase. We find that a higher burst frequency weakens the ability of noise reduction by phase separation, but as the burst size increases, this ability first increases and then decreases. This study provides a deeper understanding of phase separation to reduce noise in the stochastic gene expression with burst kinetics.

The effect of aperiodic components in distinguishing Alzheimer's disease from frontotemporal dementia.

Distinguishing between Alzheimer's disease (AD) and frontotemporal dementia (FTD) presents a clinical challenge. Inexpensive and accessible techniques such as electroencephalography (EEG) are increasingly being used to address this challenge. In particular, the potential relevance between aperiodic components of EEG activity and these disorders has gained interest as our understanding evolves. This study aims to determine the differences in aperiodic activity between AD and FTD and evaluate its potential for distinguishing between the two disorders. A total of 88 participants, including 36 patients with AD, 23 patients with FTD, and 29 healthy controls (CN) underwent cognitive assessment and scalp EEG acquisition. Neuronal power spectra were parameterized to decompose the EEG spectrum, enabling comparison of group differences in different components. A support vector machine was employed to assess the impact of aperiodic parameters on the differential diagnosis. Compared with the CN group, both the AD and FTD groups showed varying degrees of increased alpha power (both periodic and raw power) and theta alpha power ratio. At the channel level, theta power (both periodic and raw power) in the frontal regions was higher in the AD group compared to the FTD group, and aperiodic parameters (both exponents and offsets) in the frontal, temporal, central, and parietal regions were higher in the AD group than in the FTD group. Importantly, the inclusion of aperiodic parameters led to improved performance in distinguishing between the two disorders. These findings highlight the significance of aperiodic components in discriminating dementia-related diseases.

[Metabolomics of nasal lavage fluid in patients with allergic rhinitis treated by Xiaoqinglong Decoction].

This study used nasal lavage fluid for metabolomics to explore its feasibility, and applied it to the clinical metabolomics study of Xiaoqinglong Decoction in the treatment of allergic rhinitis(AR), aiming to investigate the molecular mechanism of Xiaoqing-long Decoction in the treatment of AR through differential changes in local nasal metabolism. AR patients were selected as the research subjects, and nasal lavage fluid was collected as the sample. Metabolomics analysis using liquid chromatography-mass spectrometry was performed on normal group, AR group, and Xiaoqinglong Decoction group. The differences in metabolic profiles among the groups were compared using principal component analysis and partial least squares discriminant analysis, and differential metabolites were identified and subjected to corresponding metabolic pathway analysis. The results showed that Xiaoqinglong Decoction significantly improved the symptoms of AR patients. The metabolomics analysis revealed 20 differential metabolites between AR group and Xiaoqinglong Decoction group. The core metabolite with a trending return in comparison to normal group was trimethyladipic acid. The metabolites were involved in multiple pathways, including ß-alanine metabolism, glutathione metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. The feasibility of applying nasal lavage fluid in nasal metabolomics was preliminarily demonstrated. Differential metabolites and enriched pathways in the treatment of AR patients with Xiaoqinglong Decoction were identified, indicating that it may improve rhinitis symptoms through the regulation of various metabolites, including antioxidant effects and correction of Th1/Th2 imbalance.

Efficient Retrieval of Images with Irregular Patterns Using Morphological Image Analysis: Applications to Industrial and Healthcare Datasets.

Image retrieval is the process of searching and retrieving images from a datastore based on their visual content and features. Recently, much attention has been directed towards the retrieval of irregular patterns within industrial or healthcare images by extracting features from the images, such as deep features, colour-based features, shape-based features, and local features. This has applications across a spectrum of industries, including fault inspection, disease diagnosis, and maintenance prediction. This paper proposes an image retrieval framework to search for images containing similar irregular patterns by extracting a set of morphological features (DefChars) from images. The datasets employed in this paper contain wind turbine blade images with defects, chest computerised tomography scans with COVID-19 infections, heatsink images with defects, and lake ice images. The proposed framework was evaluated with different feature extraction methods (DefChars, resized raw image, local binary pattern, and scale-invariant feature transforms) and distance metrics to determine the most efficient parameters in terms of retrieval performance across datasets. The retrieval results show that the proposed framework using the DefChars and the Manhattan distance metric achieves a mean average precision of 80% and a low standard deviation of ±0.09 across classes of irregular patterns, outperforming alternative feature-metric combinations across all datasets. Our proposed ImR framework performed better (by 8.71%) than Super Global, a state-of-the-art deep-learning-based image retrieval approach across all datasets.

4D nucleome equation predicts gene expression controlled by long-range enhancer-promoter interaction.

Recent experimental evidence strongly supports that three-dimensional (3D) long-range enhancer-promoter (E-P) interactions have important influences on gene-expression dynamics, but it is unclear how the interaction information is translated into gene expression over time (4D). To address this question, we developed a general theoretical framework (named as a 4D nucleome equation), which integrates E-P interactions on chromatin and biochemical reactions of gene transcription. With this equation, we first present the distribution of mRNA counts as a function of the E-P genomic distance and then reveal a power-law scaling of the expression level in this distance. Interestingly, we find that long-range E-P interactions can induce bimodal and trimodal mRNA distributions. The 4D nucleome equation also allows for model selection and parameter inference. When this equation is applied to the mouse embryonic stem cell smRNA-FISH data and the E-P genomic-distance data, the predicted E-P contact probability and mRNA distribution are in good agreement with experimental results. Further statistical inference indicates that the E-P interactions prefer to modulate the mRNA level by controlling promoter activation and transcription initiation rates. Our model and results provide quantitative insights into both spatiotemporal gene-expression determinants (i.e., long-range E-P interactions) and cellular fates during development.

Systematic analysis of various RNA transcripts and construction of biological regulatory networks at the post-transcriptional level for chronic obstructive pulmonary disease.

BACKGROUND: Although chronic inflammation, oxidative stress, airway remodeling, and protease-antiprotease imbalance have been implicated in chronic obstructive pulmonary disease (COPD), the exact pathogenesis is still obscure. Gene transcription and post-transcriptional regulation have been taken into account as key regulators of COPD occurrence and development. Identifying the hub genes and constructing biological regulatory networks at the post-transcriptional level will help extend current knowledge on COPD pathogenesis and develop potential drugs. METHODS: All lung tissues from non-smokers (n = 6), smokers without COPD (smokers, n = 7), and smokers with COPD (COPD, n = 7) were collected to detect messenger RNA (mRNA), microRNA (miRNA), circular RNA (circRNA), and long non-coding RNA (lncRNA) expression and identify the hub genes. Biological regulatory networks were constructed at the post-transcriptional level, including the RNA-binding protein (RBP)-hub gene interaction network and the competitive endogenous RNA (ceRNA) network. In addition, we assessed the composition and abundance of immune cells in COPD lung tissue and predicted potential therapeutic drugs for COPD. Finally, the hub genes were confirmed at both the RNA and protein levels. RESULTS: Among the 20 participants, a total of 121169 mRNA transcripts, 1871 miRNA transcripts, 4244 circRNA transcripts, and 122130 lncRNA transcripts were detected. There were differences in the expression of 1561 mRNAs, 48 miRNAs, 33 circRNAs, and 545 lncRNAs between smokers and non-smokers, as well as 1289 mRNAs, 69 miRNAs, 32 circRNAs, and 433 lncRNAs between smokers and COPD patients. 18 hub genes were identified in COPD. TGF-ß signaling and Wnt/ß-catenin signaling may be involved in the development of COPD. Furthermore, the circRNA/lncRNA-miRNA-mRNA ceRNA networks and the RBP-hub gene interaction network were also constructed. Analysis of the immune cell infiltration level revealed that M2 macrophages and activated NK cells were increased in COPD lung tissues. Finally, we identified that the ITK inhibitor and oxybutynin chloride may be effective in treating COPD. CONCLUSIONS: We identified several novel hub genes involved in COPD pathogenesis. TGF-ß signaling and Wnt/ß-catenin signaling were the most dysregulated pathways in COPD patients. Our study constructed post-transcriptional biological regulatory networks and predicted small-molecule drugs for the treatment of COPD, which enhanced the existing understanding of COPD pathogenesis and suggested an innovative direction for the therapeutic intervention of the disease.

Handgrip strength assessment at baseline in addition to bone parameters could potentially predict the risk of curve progression in adolescent idiopathic scoliosis.

Introduction: Adolescent idiopathic scoliosis (AIS) is characterized by deranged bone and muscle qualities, which are important prognostic factors for curve progression. This retrospective case-control study aims to investigate whether the baseline muscle parameters, in addition to the bone parameters, could predict curve progression in AIS. Methods: The study included a cohort of 126 female patients diagnosed with AIS who were between the ages of 12 and 14 years old at their initial clinical visit. These patients were longitudinally followed up every 6 months (average 4.08 years) until they reached skeletal maturity. The records of these patients were thoroughly reviewed as part of the study. The participants were categorized into two sub-groups: the progressive AIS group (increase in Cobb angle of ≥6°) and the stable AIS group (increase in Cobb angle <6°). Clinical and radiological assessments were conducted on each group. Results: Cobb angle increase of ≥6° was observed in 44 AIS patients (34.9%) prior to skeletal maturity. A progressive AIS was associated with decreased skeletal maturity and weight, lower trunk lean mass (5.7%, p = 0.027) and arm lean mass (8.9%, p < 0.050), weaker dominant handgrip strength (8.8%, p = 0.027), deranged cortical compartment [lower volumetric bone mineral density (vBMD) by 6.5%, p = 0.002], and lower bone mechanical properties [stiffness and estimated failure load lowered by 13.2% (p = 0.005) and 12.5% (p = 0.004)]. The best cut-off threshold of maximum dominant handgrip strength is 19.75 kg for distinguishing progressive AIS from stable AIS (75% sensitivity and 52.4% specificity, p = 0.011). Discussion: Patients with progressive AIS had poorer muscle and bone parameters than patients with stable AIS. The implementation of a cut-off threshold in the baseline dominant handgrip strength could potentially be used as an additional predictor, in addition to bone parameters, for identifying individuals with AIS who are at higher risk of experiencing curve progression.

Prognostic factors and survival prediction of resected non-small cell lung cancer with ipsilateral pulmonary metastases: a study based on the Surveillance, Epidemiology, and End Results (SEER) database.

BACKGROUND: Prognostic factors and survival outcomes of non-small cell lung cancer (NSCLC) with Ipsilateral pulmonary metastasis (IPM) are not well-defined. Thus, this study intended to identify the prognostic factors for these patients and construct a predictive nomogram model. METHODS: One thousand, seven hundred thirty-two patients with IPM identified between 2000 to 2019 were from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors were identified using multivariate Cox regression analyses. Nomograms were constructed to predict the overall survival (OS), C-index, the area under the curve (AUC), and the calibration curve to determine the predictive accuracy and discrimination; the decision curve analysis was used to confirm the clinical utility. RESULTS: Patients were randomly divided into training (n = 1213) and validation (n = 519) cohorts. In the training cohort, the multivariable analysis demonstrated that age, sex, primary tumor size, N status, number of regional lymph nodes removed, tumor grade, and chemotherapy were independent prognostic factors for IPM. We constructed a 1-year, 3-year, and 5-year OS prediction nomogram model using independent prognostic factors. The C-index of this model for OS prediction was 0.714 (95% confidence interval [CI], 0.692 to 0.773) in the training cohort and 0.695 (95% CI, 0.660 to 0.730) in the validation cohort. Based on the AUC of the receiver operating characteristic analysis, calibration plots, and decision curve analysis, we concluded that the prognosis model of IPM exhibited excellent performance. Patients with total nomogram points greater than 96 were considered high-risk. CONCLUSION: We constructed and internally validated a nomogram to predict 1-year, 3-year, and 5-year OS for NSCLC patients with IPM according to independent prognostic factors. This nomogram demonstrated good calibration, discrimination, clinical utility, and practical decision-making effects for the prognosis of NSCLC patients with IPM.

Defect-Driven Efficient Selective CO2 Hydrogenation with Mo-Based Clusters.

Synthetic fuels produced from CO2 show promise in combating climate change. The reverse water gas shift (RWGS) reaction is the key to opening the CO2 molecule, and CO serves as a versatile intermediate for creating various hydrocarbons. Mo-based catalysts are of great interest for RWGS reactions featured for their stability and strong metal-oxygen interactions. Our study identified Mo defects as the intrinsic origin of the high activity of cluster Mo2C for CO2-selective hydrogenation. Specifically, we found that defected Mo2C clusters supported on nitrogen-doped graphene exhibited exceptional catalytic performance, attaining a reaction rate of 6.3 gCO/gcat/h at 400 °C with over 99% CO selectivity and good stability. Such a catalyst outperformed other Mo-based catalysts and noble metal-based catalysts in terms of facile dissociation of CO2, highly selective hydrogenation, and nonbarrier liberation of CO. Our study revealed that as a potential descriptor, the atomic magnetism linearly correlates to the liberation capacity of CO, and Mo defects facilitated product desorption by reducing the magnetization of the adsorption site. On the other hand, the defects were effective in neutralizing the negative charges of surface hydrogen, which is crucial for selective hydrogenation. Finally, we have successfully demonstrated that the combination of a carbon support and the carbonization process synergistically serves as a feasible strategy for creating rich Mo defects, and biochar can be a low-cost alternative option for large-scale applications.