Distribution of COPD Comorbidities and Creation of Acute Exacerbation Risk Score: Results from SCICP

Background

Chronic obstructive pulmonary disease (COPD) often coexists with multiple comorbidities which may have a significant impact on acute exacerbations of patients. At present, what kind of comorbidities affects acute exacerbations and how comorbidities lead to poor prognosis are still controversial. The purpose of our study is to determine the impact of comorbidities on COPD exacerbation and establish an acute exacerbation risk assessment system related to comorbidities.

Methods

A total of 742 COPD patients participated in the Shanghai COPD Investigation on Comorbidity Program (SCICP, ChiCTR2000030911). Finally, the baseline information of 415 participants and one-year follow-up data were involved in the analysis. We collected hemogram indices, pulmonary function tests and acute exacerbation of COPD with regular medical follow-up. Q-type cluster analysis was used to determine the clusters of participants. Receiver operating characteristic (ROC) analysis was constructed to assess the ability of indicators in predicting acute exacerbations.

Results

Almost 65% of the population we investigated had at least one comorbidity. The distribution and incidence of comorbidities differed between exacerbation group and non-exacerbation group. Three comorbidity clusters were identified: (1) respiratory, metabolic, immune and psychologic disease (non-severe cases); (2) cardiovascular and neoplastic disease (severe cases); (3) less comorbidity. Different sub-phenotypes of COPD patients showed significant distinction in health status. Anxiety (OR=5.936, P=0.001), angina (OR=10.155, P=0.025) and hypertension (OR=3.142, P=0.001) were found to be independent risk factors of exacerbation in a year. The novel risk score containing BODEx and four diseases showed great prognostic value of COPD exacerbation in developing sample.

Conclusion

Our study detailed the major interaction between comorbidities and exacerbation in COPD. Noteworthily, a novel risk score using comprehensive index – BODEx – and comorbidity parameters can identify patients at high risk of acute exacerbation.

Identification of candidate genes associated with slaughter traits in F2 chicken population using genome-wide association study

Slaughter traits are crucial economic traits of chickens. We performed a GWAS to discover critical loci and candidate genes for 21 slaughter traits in an F2 chicken population resulting from crossing Luxi gamecocks and recessive white feather broilers. We found some SNPs and genes which were significantly associated with keel length, head length, body slope length, bilateral leg weight without shin, bilateral foot weight, subcutaneous fat thickness, heart weight, muscular stomach weight and glandular stomach weight. This study provides references for further investigation of slaughter traits and molecular breeding in chicken.

Music-based interventions for pain relief in patients undergoing hemodialysis: A PRISMA-compliant systematic review and meta-analysis

BACKGROUND

Music therapy and music-based interventions have been used widely in numerous medical procedures to reduce the physical and psychological disorders. However, the effect of music therapy on pain relief in hemodialysis patients still remains unclear.

METHODS

Electronic databases were comprehensively searched through MEDLINE, Web of Science, EMBASE, Cochrane, and WANFANG. All studies met inclusion criteria were eligible for systematic review and meta-analysis. Clinical variables were extracted and pooled results were obtained using STATA software.

RESULTS

A total of 10 studies with 722 participants were included for systematic review. Overall, music therapy showed a significantly favorable effect on reducing pain for patients undergoing hemodialysis (SMD: -0.90, 95%CIs: -1.25 to -0.55, P < .001). No publication bias was observed.

CONCLUSIONS

Music-based interventions could significantly relieve pain for patients undergoing hemodialysis, which should be promoted as an effective and safe complementary method.

Increased β-site APP cleaving enzyme 1-mediated insulin receptor cleavage in type 2 diabetes mellitus with cognitive impairment

INTRODUCTION

Patients with type 2 diabetes mellitus (T2DM) are at a high risk of cognitive impairment, with insulin resistance playing a pivotal role. β-site amyloid precursor protein cleaving enzyme 1 (BACE1) is considered a predictor of Alzheimer's disease. However, the potential roles of BACE1 in insulin resistance and the risk of cognitive impairment in T2DM remain unclear.

METHODS

We measured plasma BACE1 levels, BACE1 cleavage activities for Swedish mutant amyloid precursor protein (APPsw) and insulin receptor β subunit (INSR-β), and soluble INSR (sINSR) levels in a clinical cohort study.

RESULTS

T2DM patients with or without cognitive impairment exhibited elevated plasma BACE1 levels and BACE1 enzymatic activities for APPsw and INSR-β, and sINSR levels. Moreover, the glycemic status correlated with elevated BACE1 levels and BACE1-mediated INSR cleavage, which was associated with insulin resistance.

DISCUSSION

The elevated BACE1 levels in T2DM may contribute to increasing the cognitive impairment risk through both amyloidogenesis and insulin resistance.

BMI modifies the association between serum HDL cholesterol and stroke in a hypertensive population without atrial fibrillation

PURPOSE

Both high-density lipoprotein cholesterol (HDL-C) and body mass index (BMI) have an impact on the prevalence of stroke. However, it is unclear whether BMI can modify the relationship between HDL-C and stroke. Therefore, we aimed to assess the effect of the BMI on the association between HDL-C and stroke in a hypertensive population without atrial fibrillation (AF).

METHODS

We analyzed data of 10,925 hypertensive patients without AF from the Chinese Hypertension Registry Study. BMI was categorized as < 24 and ≥ 24 kg/m². Multivariate logistic regression and smooth curve fitting (penalized spline method) were used to analyze the association between HDL-C and stroke in different BMI groups. Subgroup analysis and interaction tests were used to explore the effect of other variables on this relationship.

RESULTS

The results showed a negative association between HDL-C and stroke in the BMI < 24 kg/m² group, but HDL-C was not associated with stroke in the BMI ≥ 24 kg/m² group. In the BMI < 24 kg/m² group, each 1 mmol/L increase in HDL-C was associated with a 50% decreased risk of stroke [odds ratio (OR) 0.50, 95% confidence interval (CI) 0.38-0.66]. No significant relationship between HDL-C and stroke was observed in the BMI ≥ 24 kg/m² group (OR 0.73, 95% CI 0.49-1.10). There was a significant interaction between BMI and HDL-C in regard to the prevalence of stroke in the hypertensive population without AF (P_Interaction = 0.027).

CONCLUSIONS

We found an inverse association between HDL-C and stroke only in the BMI < 24 kg/m² group. The finding suggested that BMI could modify the association between HDL-C and stroke in hypertensive populations without AF.

The Combination of Hemogram Indexes to Predict Exacerbation in Stable Chronic Obstructive Pulmonary Disease

Background: Chronic obstructive pulmonary disease (COPD) is characterized by pulmonary and systemic inflammatory processes, and exacerbation of COPD represents a critical moment in the progression of COPD. Several biomarkers of inflammation have been proposed to have a predictive function in acute exacerbation. However, their use is still limited in routine clinical practice. The purpose of our study is to explore the prognostic efficacy of novel inflammatory hemogram indexes in the exacerbation among stable COPD patients. Method: A total of 275 stable COPD patients from the Shanghai COPD Investigation Comorbidity Program were analyzed in our study. Blood examinations, especially ratio indexes like platelet-lymphocyte ratio (PLR), platelet × neutrophil/lymphocyte ratio [systemic immune-inflammation index (SII)], and monocyte × neutrophil/lymphocyte ratio [systemic inflammation response index (SIRI)], lung function test, CT scans, and questionnaires were performed at baseline and routine follow-ups. Clinical characteristics and information of exacerbations were collected every 6 months. The relationship between hemogram indexes and diverse degrees of exacerbation was assessed by logistic regression. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to evaluate the ability of hemogram indexes to predict exacerbation of COPD. Furthermore, the discrimination and accuracy of combined indexes were measured by ROC and calibration curve. Result: There was a significant positive correlation between PLR levels and total exacerbation of COPD patients in a stable stage in a year. Also, the predictive ability of PLR exceeded any other ratio indexes, with an AUC of 0.66. SII and SIRI ranked second only to PLR, with an AUC of 0.64. When combining PLR with other indexes (sex, COPD year, and St. George's Respiratory Questionnaire scores), they were considered as the most suitable panel of index to predict total exacerbation. Based on the result of the ROC curve and calibration curve, the combination shows optimal discrimination and accuracy to predict exacerbation events in COPD patients. Conclusion: The hemogram indexes PLR, SII, and SIRI were associated with COPD exacerbation. Moreover, the prediction capacity of exacerbation was significantly elevated after combining inflammatory hemogram index PLR with other indexes, which will make it a promisingly simple and effective marker to predict exacerbation in patients with stable COPD.

Establishment of a cell-based quantitative reverse transcription-polymerase chain reaction (RT-qPCR) assay for detection of multivalent rotavirus vaccine

Because of deficiencies of traditional potency tests in rotavirus detection, a one-step TaqMan probe-based quantitative reverse transcription-polymerase chain reaction (RT-qPCR) assay combined with cell-based method was established to determine the infectious potency of the target virus in multivalent live rotavirus vaccines in vitro. Series dilutions of rotavirus samples were inoculated into Vero cells and cultured for 24 hours. The cells were lysed and the potency was detected by RT-qPCR. The reference standards with a known titer (lgCCID50 /mL) were assayed in parallel, and the potencies of each sample were determined using parallel line method. The specificity, precision and accuracy of the assay were evaluated, respectively. The results showed that messenger RNA produced during rotavirus replication was the primary template of RT-qPCR and the primers and probes were specific to each strain. The coefficient of variation of different wells and different working days did not exceed 6% and the results of the assay were proved to be concordant with those of cell culture infective dose 50% with a relative deviation less than 5%. This assay is a more rapid, cost-effective and high-throughput way for detecting multivalent rotavirus vaccine, and will be a valuable tool in the quality control and stability monitoring of live multivalent rotavirus vaccine.

An in-vitro study on a novel six-phage cocktail against multi-drug resistant-ESBL Shigella in aquatic environment

Shigella spp. are water-borne pathogens responsible for mild to severe cases bacilli dysentery all around the world known as Shigellosis. The progressively increasing of antibiotic resistance among Shigella calls for developing and establishing novel alternative therapeutic methods. The present study aimed to evaluate a novel phage cocktail of lytic phages against extended spectrum beta lactamase isolates of Shigella species in an aquatic environment. The phage cocktail containing six novel Shigella specific phages showed a broad host spectrum. The cocktail was very stable in aquatic environment. The cocktail resulted in about 99% decrease in the bacterial counts in the contaminated water by several species and strains of Shigella such as Shigella sonnei, Shigella flexneri and Shigella dysenteriae. Achieving such a high efficiency in this in-vitro study demonstrates a high potential for in-vivo and in-situ application of this phage cocktail as a bio-controlling agent against Shigella spp. contamination and infections.

Machine-Learning-Driven Synthesis of Carbon Dots with Enhanced Quantum Yields

Knowing the correlation of reaction parameters in the preparation process of carbon dots (CDs) is essential for optimizing the synthesis strategy, exploring exotic properties, and exploiting potential applications. However, the integrated screening experimental data on the synthesis of CDs are huge and noisy. Machine learning (ML) has recently been successfully used for the screening of high-performance materials. Here, we demonstrate how ML-based techniques can offer insight into the successful prediction, optimization, and acceleration of CDs' synthesis process. A regression ML model on hydrothermal-synthesized CDs is established capable of revealing the relationship between various synthesis parameters and experimental outcomes as well as enhancing the process-related properties such as the fluorescent quantum yield (QY). CDs exhibiting a strong green emission with QY up to 39.3% are obtained through the combined ML guidance and experimental verification. The mass of precursors and the volume of alkaline catalysts are identified as the most important features in the synthesis of high-QY CDs by the trained ML model. The CDs are applied as an ultrasensitive fluorescence probe for monitoring the Fe³⁺ ion because of their superior optical behaviors. The probe exhibits the linear response to the Fe³⁺ ion with a wide concentration range (0-150 μM), and its detection limit is 0.039 μM. Our findings demonstrate the great capability of ML to guide the synthesis of high-quality CDs, accelerating the development of intelligent material.

Select Septate Junction Proteins Direct ROS-Mediated Paracrine Regulation of Drosophila Cardiac Function

Septate junction (SJ) complex proteins act in unison to provide a paracellular barrier and maintain structural integrity. Here, we identify a non-barrier role of two individual SJ proteins, Coracle (Cora) and Kune-kune (Kune). Reactive oxygen species (ROS)-p38 MAPK signaling in non-myocytic pericardial cells (PCs) is important for maintaining normal cardiac physiology in Drosophila. However, the underlying mechanisms remain unknown. We find that in PCs, Cora and Kune are altered in abundance in response to manipulations of ROS-p38 signaling. Genetic analyses establish Cora and Kune as key effectors of ROS-p38 signaling in PCs on proper heart function. We further determine that Cora regulates normal Kune levels in PCs, which in turn modulates normal Kune levels in the cardiomyocytes essential for proper heart function. Our results thereby reveal select SJ proteins Cora and Kune as signaling mediators of the PC-derived ROS regulation of cardiac physiology.

Two-Step Calibration Method for Inverse Finite Element with Small Sample Features

When the inverse finite element method (inverse FEM) is used to reconstruct the deformation field of a multi-element structure with strain measurements, strain measurement errors can lower the reconstruction accuracy of the deformation field. Furthermore, the calibration ability of a self-structuring fuzzy network (SSFN) is weak when few strain samples are used to train the SSFN. To solve this problem, a novel two-step calibration method for improving the reconstruction accuracy of the inverse FEM method is proposed in this paper. Initially, the errors derived from measured displacements and reconstructed displacements are distributed to the degrees of freedom (DOFs) of nodes. Then, the DOFs of nodes are used as knots, in order to produce non-uniform rational B-spline (NURBS) curves, such that the sample size employed to train the SSFN can be enriched. Next, the SSFN model is used to determine the relationship between the measured strain and the DOFs of the end nodes. A loading deformation experiment using a three-element structure demonstrates that the proposed algorithm can significantly improve the accuracy of reconstruction displacement.

Sitagliptin inhibits EndMT in vitro and improves cardiac function of diabetic rats through the SDF-1α/PKA pathway

OBJECTIVE

The aim of this paper was to study sitagliptin in improving the endothelial-mesenchymal transition (EndMT) of human aortic endothelial cells (HAECs) and cardiac function of rats with diabetes mellitus (DM) and its possible pathway.

MATERIALS AND METHODS

Sprague Dawley (SD) rats were divided into control group, DM group and sitagliptin group. The myocardial contraction and relaxation functions of rats in each group were observed via echocardiography. The changes in cardiac structure and fiber were observed via hematoxylin-eosin (HE) staining, Masson staining and Sirius red staining. The immunohistochemical assay was performed to observe the expressions of α-smooth muscle actin (α-SMA) and VE-cadherin in HAECs; the expression of reactive oxygen species (ROS) in HAECs was detected using the fluorescence probe. Moreover, the expressions of transforming growth factor-β1 (TGF-β1), phosphorylated-protein kinase A (p-PKA), PKA and extracellular signal-regulated kinase (ERK) were observed via Western blotting.

RESULTS

Sitagliptin could improve the myocardial contraction and relaxation functions in diabetic rats and EndMT and ROS production in HAECs. In the DM group, the expression of Glucagon-like peptide-1 (GLP-1) was decreased, while the expression of stromal-derived factor-1α (SDF-1α) was decreased and the expressions of downstream PKA/ERK pathway and TGF-β1 were increased. The above changes could be reversed by sitagliptin.

CONCLUSIONS

Sitagliptin can reverse the EndMT in HAECs as well as the cardiac function in diabetic rats through the SDF-1α/PKA pathway.

Assessing risk factors for SARS-CoV-2 infection in patients presenting with symptoms in Shanghai, China: a multicentre, observational cohort study

Background

The outbreak of COVID-19 has led to international concern. We aimed to establish an effective screening strategy in Shanghai, China, to aid early identification of patients with COVID-19.

Methods

We did a multicentre, observational cohort study in fever clinics of 25 hospitals in 16 districts of Shanghai. All patients visiting the clinics within the study period were included. A strategy for COVID-19 screening was presented and then suspected cases were monitored and analysed until they were confirmed as cases or excluded. Logistic regression was used to determine the risk factors of COVID-19.

Findings

We enrolled patients visiting fever clinics from Jan 17 to Feb 16, 2020. Among 53 617 patients visiting fever clinics, 1004 (1·9%) were considered as suspected cases, with 188 (0·4% of all patients, 18·7% of suspected cases) eventually diagnosed as confirmed cases. 154 patients with missing data were excluded from the analysis. Exposure history (odds ratio [OR] 4·16, 95% CI 2·74-6·33; p<0·0001), fatigue (OR 1·56, 1·01-2·41; p=0·043), white blood cell count less than 4 × 10⁹ per L (OR 2·44, 1·28-4·64; p=0·0066), lymphocyte count less than 0·8 × 10⁹ per L (OR 1·82, 1·00-3·31; p=0·049), ground glass opacity (OR 1·95, 1·32-2·89; p=0·0009), and having both lungs affected (OR 1·54, 1·04-2·28; p=0·032) were independent risk factors for confirmed COVID-19.

Interpretation

The screening strategy was effective for confirming or excluding COVID-19 during the spread of this contagious disease. Relevant independent risk factors identified in this study might be helpful for early recognition of the disease.

Funding

National Natural Science Foundation of China.

A New Neurovascular Panel Discriminates Between Patients with Type 2 Diabetes Mellitus with Cognitive Impairment and Cognitive Impairment Alone

BACKGROUND

Recent studies showed that type 2 diabetes mellitus (T2DM) may increase the risk of cognitive impairment, but there are few biomarkers to diagnostically discriminate T2DM-associated cognitive impairment and cognitive impairment alone. In this study, we assessed certain cytokines involved in inflammation and vascular diseases and identified special panel of cytokines that could differentiate between T2DM and cognitive impairment.

OBJECTIVE

To investigate associations and differences between T2DM and cognitive impairment by cytokines analysis.

METHODS

A total of 264 participants were recruited, their blood samples were collected, and plasma and serum were separated and stored at - 80°C until the assessment of amyloid-β (Aβ)42, Aβ40 and 8 kinds of cytokines by Luminex multiplex assays.

RESULTS

Plasma Aβ40 is higher whereas Aβ42/40 ratio is lower in cognitive impairment and T2DM-associated cognitive impairment compared to other groups. As compared to health control, YKL-40 level was upregulated in cognitive impairment, PRGN was downregulated in T2DM associated cognitive impairment, OPN was substantially decreased in T2DM, and IL-6 was elevated in cognitive impairment and T2DM-associated cognitive impairment. Interestingly, VEGF and S100B were induced in T2DM when compared with cognitive impairment, and NSE level in T2DM-associated cognitive impairment is significantly lower than in T2DM or cognitive impairment.

CONCLUSION

Aβ42, Aβ40, and Aβ42/40 ratio cannot distinguish T2DM-associated cognitive impairment from cognitive impairment. Certain cytokines (YKL-40, NSE, and VEGF) have good performance in distinguishing T2DM-associated cognitive impairment from simple cognitive impairment. Taken together, this may improve the accuracy of the diagnosis and establishment of individualized therapy.