Construction of prediction model for fetal growth restriction during first trimester in an Asian population

OBJECTIVE

To construct a prediction model for fetal growth restriction (FGR) during the first trimester of pregnancy and evaluate its screening performance.

METHODS

This was a prospective cohort study of singleton pregnancies that underwent routine ultrasound screening at 11 to 13 + 6 weeks at the Affiliated Suzhou Hospital of Nanjing Medical University between January 2019 and April 2022. Basic clinical information, ultrasound indicators and serum biomarkers of pregnant women were collected. Fetal weight assessment was based on the fetal growth curve for the Southern Chinese population. FGR was diagnosed according to Delphi consensus criteria. Least absolute shrinkage and selection operator (lasso) regression was used to select variables for inclusion in the model. Discrimination, calibration and clinical effectiveness of the model were evaluated in training and validation cohorts.

RESULTS

A total of 1188 pregnant women were included, of whom 108 had FGR. Lasso regression identified seven predictive features, including history of maternal hypertension, maternal smoking or passive smoking, gravidity, uterine artery pulsatility index, ductus venosus pulsatility index and multiples of the median values of placental growth factor and soluble fms-like tyrosine kinase-1. The nomogram prediction model constructed from these seven variables accurately predicted FGR, and the area under the receiver-operating-characteristics curve in the validation cohort was 0.82 (95% CI, 0.74-0.90). The calibration curve and Hosmer-Lemeshow test demonstrated good calibration, and the clinical decision curve and clinical impact curve supported its practical value in a clinical setting.

CONCLUSION

The multi-index prediction model for FGR has good predictive value during the first trimester. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Joint Exposure to Multiple Air Pollutants, Genetic Susceptibility, and Incident Dementia: A Prospective Analysis in the UK Biobank Cohort

Objectives: This study aimed to evaluate the joint effects of multiple air pollutants including PM2.5, PM10, NO2, and NOx with dementia and examined the modifying effects of genetic susceptibility. Methods: This study included 220,963 UK Biobank participants without dementia at baseline. Weighted air pollution score reflecting the joint exposure to multiple air pollutants were constructed by cross-validation analyses, and inverse-variance weighted meta-analyses were performed to create a pooled effect. The modifying effect of genetic susceptibility on air pollution score was assessed by genetic risk score and APOE ε4 genotype. Results: The HR (95% CI) of dementia for per interquartile range increase of air pollution score was 1.13 (1.07∼1.18). Compared with the lowest quartile (Q1) of air pollution score, the HR (95% CI) of Q4 was 1.26 (1.13∼1.40) (P trend = 2.17 × 10-5). Participants with high air pollution score and high genetic susceptibility had higher risk of dementia compared to those with low air pollution score and low genetic susceptibility. Conclusion: Our study provides evidence that joint exposure to multiple air pollutants substantially increases the risk of dementia, especially among individuals with high genetic susceptibility.

Assessing the stress-relief impact of an art-based intervention inspired by the broaden-and-build theory in college students

Background and objectives

This study's primary objective is to investigate the impact of art-making on the mental well-being of college students, who often experience heightened stress during their initial university years.

Methods

Employing a comprehensive methodology, combining interviews and the Perceived Stress Scale (PSS), the research aimed to assess whether a four-week art-making intervention can effectively alleviate stress levels among college students. In the experimental group, participants engaged in a variety of art-making activities, including freehand drawing, clay modeling, and crafting.

Results

The results revealed that, in the pre-test, there were no significant differences between the experimental and control groups for each assessed indicator. However, in the post-test, significant differences emerged across all indicators. Further analysis demonstrated a significant reduction in stress perception among the experimental group participants between the pre-test and post-test phases.

Conclusion

In conclusion, this study provides compelling evidence that art-making has the potential to foster positive personal development and significantly reduce stress levels among college students.

Fine-mapping of a major locus for Fusarium wilt resistance in flax (Linum usitatissimum L.)

KEY MESSAGE

Fine-mapping of a locus on chromosome 1 of flax identified an S-lectin receptor-like kinase (SRLK) as the most likely candidate for a major Fusarium wilt resistance gene. Fusarium wilt, caused by the soil-borne fungal pathogen Fusarium oxysporum f. sp. lini, is a devastating disease in flax. Genetic resistance can counteract this disease and limit its spread. To map major genes for Fusarium wilt resistance, a recombinant inbred line population of more than 700 individuals derived from a cross between resistant cultivar 'Bison' and susceptible cultivar 'Novelty' was phenotyped in Fusarium wilt nurseries at two sites for two and three years, respectively. The population was genotyped with 4487 single nucleotide polymorphism (SNP) markers. Twenty-four QTLs were identified with IciMapping, 18 quantitative trait nucleotides with 3VmrMLM and 108 linkage disequilibrium blocks with RTM-GWAS. All models identified a major QTL on chromosome 1 that explained 20-48% of the genetic variance for Fusarium wilt resistance. The locus was estimated to span ~ 867 Kb but included a ~ 400 Kb unresolved region. Whole-genome sequencing of 'CDC Bethune', 'Bison' and 'Novelty' produced ~ 450 Kb continuous sequences of the locus. Annotation revealed 110 genes, of which six were considered candidate genes. Fine-mapping with 12 SNPs and 15 Kompetitive allele-specific PCR (KASP) markers narrowed down the interval to ~ 69 Kb, which comprised the candidate genes Lus10025882 and Lus10025891. The latter, a G-type S-lectin receptor-like kinase (SRLK) is the most likely resistance gene because it is the only polymorphic one. In addition, Fusarium wilt resistance genes previously isolated in tomato and Arabidopsis belonged to the SRLK class. The robust KASP markers can be used in marker-assisted breeding to select for this major Fusarium wilt resistance locus.

Beyond Vision: A View from Eye to Alzheimer's Disease and Dementia

With the aging of the global population, the health care burden of Alzheimer's disease (AD) and dementia is considered to increase dramatically in the coming decades. Given the insufficiency of effective interventions for AD and dementia, clinical research on identifying potentially modifiable risk factors and early diagnostic biomarkers becomes a public health priority. Currently, extracerebral manifestations with a large proportion of ocular involvement are usually recognized to precede the symptoms of AD and dementia. Growing epidemiologic evidence also suggests that eye disorders, such as cataracts, age-related macular degeneration, glaucoma, diabetic retinopathy, and so on, are closely associated with and even have a higher incidence of AD and dementia. The eye, as an extension of the central nervous system, therefore has the potential to provide a feasible approach to detecting structural and functional abnormalities of the brain. Numerous new imaging modalities are developed and give novel insights into the detection of several neurodegenerative, vascular, neuropathological, and other ocular abnormalities of AD and dementia in scientific research and clinical application. This review provides an overview of the epidemiologic associations between eye disorders and AD or dementia and summarizes the recent advances in ocular examinations and techniques employed for the detection of AD and dementia. With more brain-and-eye interconnections being identified, the eye is becoming a noninvasive and easily accessible window for the early diagnosis and prevention of AD and dementia.

Variety ACEs and risk of developing anxiety, depression, or anxiety-depression co-morbidity: the 2006-2022 UK Biobank data

Objectives

Adverse childhood experiences (ACEs) and anxiety-depression co-morbidity are attracting widespread attention. Previous studies have shown the relationship between individual psychiatric disorders and ACEs. This study will analyze the correlation between anxiety-depression co-morbidity and different levels of ACEs.

Methods

Seven categories of ACE and four classifications of psychiatric disorders were defined in a sample of 126,064 participants identified by the UK Biobank from 2006-2022, and correlations were investigated using logistic regression models. Then, to explore nonlinear relationships, restricted spline models were developed to examine differences in sex and age across cohorts (n = 126,064 for the full cohort and n = 121,934 for the European cohort). Finally, the impact of the category of ACEs on psychiatric disorders was examined.

Results

After controlling for confounders, ACEs scores showed dose-dependent relationships with depression, anxiety, anxiety-depression co-morbidity, and at least one (any of the first three outcomes) in all models. ACEs with different scores were significantly positively correlated with the four psychiatric disorders classifications, with the highest odds of anxiety-depression co-morbidity (odds ratio [OR] = 4.87, 95% confidence intervals [CI]: 4.37 ~ 5.43), p = 6.08 × 10-178. In the restricted cubic spline models, the risk was relatively flat for females at ACEs = 0-1 and males at ACEs = 0-2/3 (except in males, where ACEs were associated with a lower risk of anxiety, all other psychiatric disorders had an increased risk of morbidity after risk smoothing). In addition, the risk of having anxiety, depression, anxiety-depression co-morbidity, and at least one of these disorders varies with each category of ACEs.

Conclusion

The prevalence of anxiety-depression comorbidity was highest across ACE scores after controlling for confounding factors and had a significant effect on each category of ACEs.

Dose-related effects of early-life intake of sn-2 palmitate, a specific positionally distributed human milk fatty acid, on the composition and metabolism of the intestinal microbiota

sn2 Palmitate in human milk plays an important role in the physiological health of infants by reducing mineral loss, improving stool hardness, and relieving constipation. Also, sn-2 palmitate modulates intestinal microbiota. However, it remains unclear whether the effects of sn-2 palmitate on infant gut microbiota are dose-dependent. In this study, we investigated the effects of low, medium, and high doses (600, 1,800, and 5,400 mg/kg body weight, respectively) of sn-2 palmitate on the structure, composition, and metabolic function of intestinal microbes in mice. Our results showed that high doses of sn-2 palmitate significantly modulated α- and β-diversity of the intestinal microbiota. The relative abundance of Lachnospiraceae_NK4A136_group decreased with increasing doses of sn-2 palmitate. In contrast, the abundances of Bacteroidetes phylum, Bacteroides, uncultured_Lachnospiraceae, and uncultured_Muribaculaceae were positively correlated with sn-2 palmitate doses. The number of genes predicted encoding autophagy-yeast, phospholipase D signaling pathway, and pentose and glucuronate interconversion metabolic functions of intestinal microbiota increased with increasing doses of sn-2 palmitate. In addition, low and medium doses of sn-2 palmitate significantly upregulated the arginine and proline metabolic pathways, and high doses of sn-2 palmitate significantly increased purine metabolism. Our results revealed that the effects of sn-2 palmitate intake early in life on the composition and metabolism of the intestinal microbiota of mice showed dose-related differences. The study is expected to provide a scientific basis for the development of infant formulas.

Risk factors for portal vein system thrombosis after partial splenic embolisation in cirrhotic patients with hypersplenism

AIM

To determine risk factors for portal venous system thrombosis (PVST) after partial splenic artery embolisation (PSAE) in cirrhotic patients with hypersplenism.

MATERIALS AND METHODS

Between March 2014 and February 2022, 428 cirrhotic patients with hypersplenism underwent partial splenic artery embolisation and from these patients 208 were enrolled and 220 were excluded. Medical records of enrolled patients were collected. Computed tomography (CT) images were reviewed by two blinded, independent radiologists. Statistical analyses were performed by using SPSS.

RESULTS

Progressive PVST was observed in 18.75% (39/208) of cirrhotic patients after PSAE. No significant differences in peripheral blood counts, liver function biomarkers, and renal function were observed between the patients with progressive PVST and the patients without progressive PVST. The imaging data showed significant differences in PVST, the diameters of the portal, splenic, and superior mesenteric veins between the progressive PVST group and non-progressive PVST group. Univariate and multivariate analysis demonstrated portal vein thrombosis, spleen infarction percentage, and the diameter of the splenic vein were independent risk factors for progressive PVST. Seventeen of 173 (9.83%) patients showed new PVST; the growth of PVST was observed in 62.86% (22/35) of the patients with pre-existing PVST. Spleen infarction percentage and the diameter of the splenic vein were independent risk factors for new PVST after PSAE.

CONCLUSION

The present study demonstrated portal vein thrombosis, spleen infarction percentage, and the diameter of the splenic vein were independent risk factors for PVST after PSAE in cirrhotic patients with hypersplenism.

Long-term adverse influence of smoking during pregnancy on height and body size of offspring at ten years old in the UK Biobank cohort

Background

To explore the long-term relationship between maternal smoking during pregnancy and early childhood growth in the UK Biobank cohort.

Methods

To estimate the effect of maternal smoking during pregnancy on offspring height and body size at ten years old, we performed binary logistic analyses and reported odds ratios (OR) as well as 95% confidence intervals (95%CIs). We also implemented the cross-contextual comparison study to examine whether such influence could be repeatedly observed among three different ethnicities in the UK Biobank cohort (n = 22,140 for White, n = 7094 for South Asian, and n = 5000 for Black). In particular, we conducted the sibling cohort study in White sibling cohort (n = 9953 for height and n = 7239 for body size) to control for unmeasured familial confounders.

Results

We discovered that children whose mothers smoked during pregnancy had greater risk of being shorter or plumper at age ten in the full UK Biobank White cohort, with 15.3% (95% CIs: 13.0%∼17.7%) higher risk for height and 32.4% (95%CIs: 29.5%∼35.4%) larger risk for body size. Similar associations were identified in the South Asian and Black ethnicities. These associations were robust and remained significant in the White sibling cohort (12.6% [95%CIs: 5.0%∼20.3%] for height and 36.1% [95%CIs: 26.3%∼45.9%] for body size) after controlling for family factors.

Conclusion

This study robustly confirms that maternal smoking during pregnancy can promote height deficit and obesity for offspring at ten years old. Our findings strongly encourage mothers to quit smoking during pregnancy for improving growth and development of offspring.

Enhanced active-site electric field accelerates enzyme catalysis

The design and improvement of enzymes based on physical principles remain challenging. Here we demonstrate that the principle of electrostatic catalysis can be leveraged to substantially improve a natural enzyme's activity. We enhanced the active-site electric field in horse liver alcohol dehydrogenase by replacing the serine hydrogen-bond donor with threonine and replacing the catalytic Zn2+ with Co2+. Based on the electric field enhancement, we make a quantitative prediction of rate acceleration-50-fold faster than the wild-type enzyme-which was in close agreement with experimental measurements. The effects of the hydrogen bonding and metal coordination, two distinct chemical forces, are described by a unified physical quantity-electric field, which is quantitative, and shown here to be additive and predictive. These results suggest a new design paradigm for both biological and non-biological catalysts.

[Orodental phenotype and genotype findings in 8 Chinese children with hypophosphatasia]

Objective: To analyze the oral phenotype and gene variation of children with hypophosphatasia (HPP), and explore the genotype-phenotype correlations. Methods: Eight children diagnosed with HPP from January 2008 to January 2023 in Children's Hospital,Zhejiang University School of Medicine were recruited in this study. The pathogenic genes of 5 of them were sequentially analyzed and all of their oral manifestations, laboratory tests and genetic variation types were retrospectively analyzed. Results: A total of 8 children were recruited in the study, 3 males and 5 females, aged from 20 months to 104 months, whose main complaints were premature deciduous tooth loss. Among them, 3 children were diagnosed with odonto HPP, and the other 5 children were diagnosed with childhood HPP, including 2 children was odonto HPP at the first diagnosis and modified as childhood HPP at the age of 5. The age range of first deciduous tooth loss is 9 to 18 months, and the age range of diagnosis is 20 to 104 months. The patients of odonto HPP only showed premature loss of deciduous anterior tooth, while the patients with childhood HPP also showed premature loss of multiple deciduous molars. Panoramic radiographic film revealed enlarged pulp chambers and radicular canals in some primary and permanent teeth. The enamel hypoplasia, hypoplastic short roots, and alveolar resorption of deciduous molar were observed in some cases. The serum alkaline phosphatase (ALP) (30-107 U/L) levels of all the patients were lower than that in the normal children of same age and gender, and the ALP value of the 1-3 years old girls with childhood HPP (30-33 U/L) was lower than that of the three children with odonto HPP (61-107 U/L), but there was no significant difference in statistical analysis. There were 8 variation sites of ALP liver/bone/kidney (ALPL) gene detected in 5 children and their families, all of which were missense variation, including the new variants in the mutations of c.1334C>G(p.Ser445Cys) and c.1259G>T(p.Gly420Val) that were not reported in the literature. One case was autosomal dominant inheritance and other 4 cases were complex heterozygous variation with autosomal recessive inheritance. Conclusions: Pediatric stomatologists are often the first doctors to detect childhood and odonto HPP. Diagnosis of mild HPP is often delayed. The severity of HPP is related to serum ALP level and ALPL gene mutation sites.

Temporal Structures in Positron Spectra and Charge-Sign Effects in Galactic Cosmic Rays

We present the precision measurements of 11 years of daily cosmic positron fluxes in the rigidity range from 1.00 to 41.9 GV based on 3.4×10^{6} positrons collected with the Alpha Magnetic Spectrometer (AMS) aboard the International Space Station. The positron fluxes show distinctly different time variations from the electron fluxes at short and long timescales. A hysteresis between the electron fluxes and the positron fluxes is observed with a significance greater than 5σ at rigidities below 8.5 GV. On the contrary, the positron fluxes and the proton fluxes show similar time variation. Remarkably, we found that positron fluxes are modulated more than proton fluxes with a significance greater than 5σ for rigidities below 7 GV. These continuous daily positron fluxes, together with AMS daily electron, proton, and helium fluxes over an 11-year solar cycle, provide unique input to the understanding of both the charge-sign and mass dependencies of cosmic rays in the heliosphere.

Properties of Cosmic-Ray Sulfur and Determination of the Composition of Primary Cosmic-Ray Carbon, Neon, Magnesium, and Sulfur: Ten-Year Results from the Alpha Magnetic Spectrometer

We report the properties of primary cosmic-ray sulfur (S) in the rigidity range 2.15 GV to 3.0 TV based on 0.38×10^{6} sulfur nuclei collected by the Alpha Magnetic Spectrometer experiment (AMS). We observed that above 90 GV the rigidity dependence of the S flux is identical to the rigidity dependence of Ne-Mg-Si fluxes, which is different from the rigidity dependence of the He-C-O-Fe fluxes. We found that, similar to N, Na, and Al cosmic rays, over the entire rigidity range, the traditional primary cosmic rays S, Ne, Mg, and C all have sizeable secondary components, and the S, Ne, and Mg fluxes are well described by the weighted sum of the primary silicon flux and the secondary fluorine flux, and the C flux is well described by the weighted sum of the primary oxygen flux and the secondary boron flux. The primary and secondary contributions of the traditional primary cosmic-ray fluxes of C, Ne, Mg, and S (even Z elements) are distinctly different from the primary and secondary contributions of the N, Na, and Al (odd Z elements) fluxes. The abundance ratio at the source for S/Si is 0.167±0.006, for Ne/Si is 0.833±0.025, for Mg/Si is 0.994±0.029, and for C/O is 0.836±0.025. These values are determined independent of cosmic-ray propagation.

Temporal Structures in Electron Spectra and Charge Sign Effects in Galactic Cosmic Rays

We present the precision measurements of 11 years of daily cosmic electron fluxes in the rigidity interval from 1.00 to 41.9 GV based on 2.0×10^{8} electrons collected with the Alpha Magnetic Spectrometer (AMS) aboard the International Space Station. The electron fluxes exhibit variations on multiple timescales. Recurrent electron flux variations with periods of 27 days, 13.5 days, and 9 days are observed. We find that the electron fluxes show distinctly different time variations from the proton fluxes. Remarkably, a hysteresis between the electron flux and the proton flux is observed with a significance of greater than 6σ at rigidities below 8.5 GV. Furthermore, significant structures in the electron-proton hysteresis are observed corresponding to sharp structures in both fluxes. This continuous daily electron data provide unique input to the understanding of the charge sign dependence of cosmic rays over an 11-year solar cycle.

[Association of extranodal extension and lymph node ratio with radioactive iodine-refractory papillary thyroid cancer]

Objective: To investigate the related factors of radioiodine-refractory thyroid cancer (RAIR-DTC) and the increase of cumulative iodine treatment dose. Methods: The data of patients with papillary thyroid cancer who underwent surgery and iodine treatment for the first time in the Affiliated Cancer Hospital of Zhengzhou University from January 2015 to December 2017 were retrospectively analyzed. The related factors of RAIR-DTC and the increase of cumulative iodine treatment dose were explored. Results: A total of 650 patients were enrolled, including 217 males (33.4%) and 433 females (66.6%), aged 45 (34, 53) years. There were 123 patients (18.9%) over 55 years old, 171 patients (26.3%) with extranodal extension and 18 patients (2.8%) with distant metastasis. The median lymph node ratio was 0.22 (0.11, 0.33). Twenty patients (3.1%) had an accumulated iodine treatment dose>400 mCi and 19 patients (2.9%) had RAIR-DTC. Multivariate logistic regression analysis showed that extranodal extension (OR=19.833, 95%CI: 6.057-73.325, P<0.001) was related factors for the increase of cumulative iodine treatment dose. Age>55 years old (OR=3.322, 95%CI: 1.136-9.466, P=0.024), distant metastasis (OR=10.059, 95%CI: 2.508-38.888, P<0.001), extranodal extension (OR=5.278, 95%CI: 1.707-19.813, P=0.006) and lymph node ratio (OR=34.724, 95%CI: 2.749-384.575, P=0.004) were related factors for RAIR-DTC. Conclusions: Extranodal extension and lymph node ratio are related factors for RAIR-DTC. In clinical practice, more attention should be paid to the influence of different lymph node metastasis characteristics on the occurrence of RAIR-DTC and the cumulative therapeutic dose of iodine.

Joint elasticity produces energy efficiency in underwater locomotion: Verification with deep reinforcement learning

Underwater snake robots have received attention because of their unique mechanics and locomotion patterns. Given their highly redundant degrees of freedom, designing an energy-efficient gait has been a main challenge for the long-term autonomy of underwater snake robots. We propose a gait design method for an underwater snake robot based on deep reinforcement learning and curriculum learning. For comparison, we consider the gait generated by a conventional parametric gait equation controller as the baseline. Furthermore, inspired by the joints of living organisms, we consider elasticity (stiffness) in the joints of the snake robot to verify whether it contributes to the generation of energy efficiency in the underwater gait. We first demonstrate that the deep reinforcement learning controller can produce a more energy-efficient gait than the gait equation controller in underwater locomotion, by finding the control patterns which maximize the effect of energy efficiency through the exploitation of joint elasticity. In addition, appropriate joint elasticity can increase the maximum velocity achievable by a snake robot. Finally, simulation results in different liquid environments confirm that the deep reinforcement learning controller is superior to the gait equation controller, and it can find adaptive energy-efficient motion even when the liquid environment is changed. The video can be viewed at https://youtu.be/wpwQihhntEY.

Screening high-risk population of persistent postpartum hypertension in women with preeclampsia using latent class cluster analysis

BACKGROUND

A significant proportion of women with preeclampsia (PE) exhibit persistent postpartum hypertension (PHTN) at 3 months postpartum associated with cardiovascular morbidity. This study aimed to screen patients with PE to identify the high-risk population with persistent PHTN.

METHODS

This retrospective cohort study enrolled 1,000 PE patients with complete parturient and postpartum blood pressure (BP) profiles at 3 months postpartum. The enrolled patients exhibited new-onset hypertension after 20 weeks of pregnancy, while those with PE superimposed upon chronic hypertension were excluded. Latent class cluster analysis (LCCA), a method of unsupervised learning in machine learning, was performed to ascertain maternal exposure clusters from eight variables and 35 subordinate risk factors. Logistic regression was applied to calculate odds ratios (OR) indicating the association between clusters and PHTN.

RESULTS

The 1,000 participants were classified into three exposure clusters (subpopulations with similar characteristics) according to persistent PHTN development: high-risk cluster (31.2%), medium-risk cluster (36.8%), and low-risk cluster (32.0%). Among the 1,000 PE patients, a total of 134 (13.4%) were diagnosed with persistent PHTN, while the percentages of persistent PHTN were24.68%, 10.05%, and 6.25% in the high-, medium-, and low-risk clusters, respectively. Persistent PHTN in the high-risk cluster was nearly five times higher (OR, 4.915; 95% confidence interval (CI), 2.92-8.27) and three times (OR, 2.931; 95% CI, 1.91-4.49) than in the low- and medium-risk clusters, respectively. Persistent PHTN did not differ between the medium- and low-risk clusters. Subjects in the high-risk cluster were older and showed higher BP, poorer prenatal organ function, more adverse pregnancy events, and greater medication requirement than the other two groups.

CONCLUSION

Patients with PE can be classified into high-, medium-, and low-risk clusters according to persistent PHTN severity; each cluster has cognizable clinical features. This study's findings stress the importance of controlling persistent PHTN to prevent future cardiovascular disease.

Solvent Organization and Electrostatics Tuned by Solute Electronic Structure: Amide versus Non-Amide Carbonyls

The ability to exploit carbonyl groups to measure electric fields in enzymes and other complex reactive environments by using the vibrational Stark effect has inspired growing interest in how these fields can be measured, tuned, and ultimately designed. Previous studies have concentrated on the role of the solvent in tuning the fields exerted on the solute. Here, we explore instead the role of the solute electronic structure in modifying the local solvent organization and electric field exerted on the solute. By measuring the infrared absorption spectra of amide-containing molecules, as prototypical peptides, and contrasting them with non-amide carbonyls in a wide range of solvents, we show that these solutes experience notable differences in their frequency shifts in polar solvents. Using vibrational Stark spectroscopy and molecular dynamics simulations, we demonstrate that while some of these differences can be rationalized by using the distinct intrinsic Stark tuning rates of the solutes, the larger frequency shifts for amides and dimethylurea primarily result from the larger solvent electric fields experienced by their carbonyl groups. These larger fields arise due to their stronger p-π conjugation, which results in larger C═O bond dipole moments that further induce substantial solvent organization. Using electronic structure calculations, we decompose the electric fields into contributions from solvent molecules that are in the first solvation shell and those from the bulk and show that both of these contributions are significant and become larger with enhanced conjugation in solutes. These results show that structural modifications of a solute can be used to tune both the solvent organization and electrostatic environment, indicating the importance of a solute-centric paradigm in modulating and designing the electrostatic environment in condensed-phase chemical processes.

[Development and validation of a prognostic model based on SEER data for patients with esophageal carcinoma after esophagectomy]

OBJECTIVE

To develop a nomogram to predict the long-term survival of patients with esophageal cancer following esophagectomy.

METHODS

We collected the data of 7215 patients with esophageal carcinoma from the Surveillance, Epidemiology, and End Results (SEER) database during the period from 2004 and 2016. Of these patients, 5052 were allocated to the training cohort and the remaining 2163 patients to the internal validation cohort using bootstrap resampling, with another 435 patients treated in the Department of Cardiothoracic Surgery of Jinling Hospital between 2014 and 2016 serving as the external validation cohort.

RESULTS

In the overall cohort, the 1-, 3-, and 5-year cancer-specific mortality rates were 14.6%, 35.7% and 41.6%, respectively. Age (≥80 years vs < 50 years, P < 0.001), gender (male vs female, P < 0.001), tumor site (lower vs middle segment, P=0.013), histology (EAC vs ESCC, P=0.012), tumor grade (poorly vs well differentiated, P < 0.001), TNM stage (Ⅳ vs Ⅰ, P < 0.001), tumor size (> 50 mm vs 0-20 mm, P < 0.001), chemotherapy (yes vs no, P < 0.001), and LNR (> 0.25 vs 0, P < 0.001) were identified as independent risk factors affecting long-term survival of the patients. The nomograms established based on the model for predicting the survival probability of the patients at 1, 3 and 5 years after operation showed a C-index of 0.726 (95% CI: 0.714-0.738) for predicting the overall survival (OS) and of 0.735 (95% CI: 0.727-0.743) for cancer-specific survival (CSS) in the training cohort. In the internal validation cohort, the C-index of the nomograms was 0.752 (95% CI: 0.738-0.76) for OS and 0.804 (95% CI: 0.790-0.817) for CSS, as compared with 0.749 (95% CI: 0.736-0.767) and 0.788 (95%CI: 0.751-0.808), respectively, in the external validation cohort. The nomograms also showed a higher sensitivity than the TNM staging system for predicting long-term prognosis.

CONCLUSION

This prognostic model has a high prediction efficiency and can help to identify the high-risk patients with esophageal carcinoma after surgery and serve as a supplement for the current TNM staging system.

Properties of Daily Helium Fluxes

We present the precision measurement of 2824 daily helium fluxes in cosmic rays from May 20, 2011 to October 29, 2019 in the rigidity interval from 1.71 to 100 GV based on 7.6×10^{8} helium nuclei collected with the Alpha Magnetic Spectrometer (AMS) aboard the International Space Station. The helium flux and the helium to proton flux ratio exhibit variations on multiple timescales. In nearly all the time intervals from 2014 to 2018, we observed recurrent helium flux variations with a period of 27 days. Shorter periods of 9 days and 13.5 days are observed in 2016. The strength of all three periodicities changes with time and rigidity. In the entire time period, we found that below ∼7  GV the helium flux exhibits larger time variations than the proton flux, and above ∼7  GV the helium to proton flux ratio is time independent. Remarkably, below 2.4 GV a hysteresis between the helium to proton flux ratio and the helium flux was observed at greater than the 7σ level. This shows that at low rigidity the modulation of the helium to proton flux ratio is different before and after the solar maximum in 2014.

NCP-BiRW: A Hybrid Approach for Predicting Long Noncoding RNA-Disease Associations by Network Consistency Projection and Bi-Random Walk

Long non-coding RNAs (lncRNAs) play significant roles in the disease process. Understanding the pathological mechanisms of lncRNAs during the course of various diseases will help clinicians prevent and treat diseases. With the emergence of high-throughput techniques, many biological experiments have been developed to study lncRNA-disease associations. Because experimental methods are costly, slow, and laborious, a growing number of computational models have emerged. Here, we present a new approach using network consistency projection and bi-random walk (NCP-BiRW) to infer hidden lncRNA-disease associations. First, integrated similarity networks for lncRNAs and diseases were constructed by merging similarity information. Subsequently, network consistency projection was applied to calculate space projection scores for lncRNAs and diseases, which were then introduced into a bi-random walk method for association prediction. To test model performance, we employed 5- and 10-fold cross-validation, with the area under the receiver operating characteristic curve as the evaluation indicator. The computational results showed that our method outperformed the other five advanced algorithms. In addition, the novel method was applied to another dataset in the Mammalian ncRNA-Disease Repository (MNDR) database and showed excellent performance. Finally, case studies were carried out on atherosclerosis and leukemia to confirm the effectiveness of our method in practice. In conclusion, we could infer lncRNA-disease associations using the NCP-BiRW model, which may benefit biomedical studies in the future.

Roles of diencephalon/mesencephalon homeobox 1 in the development and prognosis of hepatocellular carcinoma

INTRODUCTION AND OBJECTIVES

The oncogene diencephalon/mesencephalon homeobox 1 (DMBX1) is widely overexpressed in a variety of human cancers. The present study aimed to analyze the expression and clinical importance of DMBX1 in nonneoplastic tissues and tumor tissues from patients with hepatocellular carcinoma (HCC).

MATERIALS AND METHODS

DMBX1 expression in HCC and adjacent nontumor tissues was analyzed using immunohistochemical staining. Chi-square tests were applied to compare DMBX1 expression between the tumors and the adjacent normal tissues. We explored the correlation of DMBX1 expression with clinicopathological factors and its effect on the prognosis of HCC. Finally, we investigated the role of DMBX1 in HCC via knockdown experiments, which analyzed changes in cell invasion, cell proliferation and epithelial-mesenchymal transition (EMT) biomarkers (E-cadherin, N-cadherin, vimentin). The mRNAs that were coexpressed with DMBX1 in HCC, based on the TCGA cohort (n = 366), were obtained from the cBioPortal database.

RESULTS

The average score for DMBX1 expression was significantly different (P < 0.001) between HCC and paired adjacent nontumor tissues, and DMBX1 expression correlated with hepatitis B virus (HBV) infection, tumor size, metastasis, and tumor node metastasis (TNM) stage (P < 0.05). A multivariate Cox regression analysis identified significant correlations of DMBX1 expression with tumor metastasis, TNM stage, and tumor capsule. Moreover, Kaplan-Meier survival analysis revealed an association between DMBX1 overexpression and shorter overall survival of patients with HCC (P < 0.05). In HCC cell lines, silencing DMBX1 markedly inhibited migration, proliferation and EMT markers. The mRNAs that were negatively (R ≤ -0.25, n = 1094) or positively (R ≥ 0.25, n = 2906) coexpressed with DMBX1 mRNA were selected for further Gene Ontology enrichment analysis, and the results revealed that the predicted functions of DMBX1 in HCC support the in vitro experimental results.

CONCLUSIONS

Our data provide evidence that DMBX1 overexpression is associated with HCC metastasis and poor prognosis, suggesting that DMBX1 represents a therapeutic target in HCC.

RNAseq reveals extensive metabolic disruptions in the sensitive SF-295 cell line treated with schweinfurthins

The schweinfurthin family of natural compounds exhibit a unique and potent differential cytotoxicity against a number of cancer cell lines and may reduce tumor growth in vivo. In some cell lines, such as SF-295 glioma cells, schweinfurthins elicit cytotoxicity at nanomolar concentrations. However, other cell lines, like A549 lung cancer cells, are resistant to schweinfurthin treatment up to micromolar concentrations. At this time, the precise mechanism of action and target for these compounds is unknown. Here, we employ RNA sequencing of cells treated with 50 nM schweinfurthin analog TTI-3066 for 6 and 24 h to elucidate potential mechanisms and pathways which may contribute to schweinfurthin sensitivity and resistance. The data was analyzed via an interaction model to observe differential behaviors between sensitive SF-295 and resistant A549 cell lines. We show that metabolic and stress-response pathways were differentially regulated in the sensitive SF-295 cell line as compared with the resistant A549 cell line. In contrast, A549 cell had significant alterations in response genes involved in translation and protein metabolism. Overall, there was a significant interaction effect for translational proteins, RNA metabolism, protein metabolism, and metabolic genes. Members of the Hedgehog pathway were differentially regulated in the resistant A549 cell line at both early and late time points, suggesting a potential mechanism of resistance. Indeed, when cotreated with the Smoothened inhibitor cyclopamine, A549 cells became more sensitive to schweinfurthin treatment. This study therefore identifies a key interplay with the Hedgehog pathway that modulates sensitivity to the schweinfurthin class of compounds.

Periodicities in the Daily Proton Fluxes from 2011 to 2019 Measured by the Alpha Magnetic Spectrometer on the International Space Station from 1 to 100 GV

We present the precision measurement of the daily proton fluxes in cosmic rays from May 20, 2011 to October 29, 2019 (a total of 2824 days or 114 Bartels rotations) in the rigidity interval from 1 to 100 GV based on 5.5×10^{9} protons collected with the Alpha Magnetic Spectrometer aboard the International Space Station. The proton fluxes exhibit variations on multiple timescales. From 2014 to 2018, we observed recurrent flux variations with a period of 27 days. Shorter periods of 9 days and 13.5 days are observed in 2016. The strength of all three periodicities changes with time and rigidity. The rigidity dependence of the 27-day periodicity is different from the rigidity dependences of 9-day and 13.5-day periods. Unexpectedly, the strength of 9-day and 13.5-day periodicities increases with increasing rigidities up to ∼10  GV and ∼20  GV, respectively. Then the strength of the periodicities decreases with increasing rigidity up to 100 GV.

Application of Extreme Learning Machine in the Survival Analysis of Chronic Heart Failure Patients With High Percentage of Censored Survival Time

Objective: To explore the application of the Cox model based on extreme learning machine in the survival analysis of patients with chronic heart failure.

Methods: The medical records of 5,279 inpatients diagnosed with chronic heart failure in two grade 3 and first-class hospitals in Taiyuan from 2014 to 2019 were collected; with death as the outcome and after the feature selection, the Lasso Cox, random survival forest (RSF), and the Cox model based on extreme learning machine (ELM Cox) were constructed for survival analysis and prediction; the prediction performance of the three models was explored based on simulated data with three censoring ratios of 25, 50, and 75%.

Results: Simulation results showed that the prediction performance of the three models decreased with increasing censoring proportion, and the ELM Cox model performed best overall; the ELM Cox model constructed with 21 highly influential survival predictors screened from actual chronic heart failure data showed the best performance with C-index and Integrated Brier Score (IBS) of 0.775(0.755, 0.802) and 0.166(0.150, 0.182), respectively.

Conclusion: The ELM Cox model showed good discrimination performance in the survival analysis of patients with chronic heart failure; it performs consistently for data with a high proportion of censored survival time; therefore, the model could help physicians identify patients at high risk of poor prognosis and target therapeutic measures to patients as early as possible.

Hierarchical management of chronic heart failure: a perspective based on the latent structure of comorbidities

AIMS

Chronic heart failure (CHF) has an increasing burden of comorbidities, which affect clinical outcomes. Few studies have focused on the clustering and hierarchical management of patients with CHF based on comorbidity. This study aimed to explore the cluster model of CHF patients based on comorbidities and to verify their relationship with clinical outcomes.

METHODS AND RESULTS

Electronic health records of patients hospitalized with CHF from January 2014 to April 2019 were collected, and 12 common comorbidities were included in the latent class analysis. The Fruchterman-Reingold layout was used to draw the comorbidity network, and analysis of variance was used to compare the weighted degrees among them. The incidence of clinical outcomes among different clusters was presented on Kaplan-Meier curves and compared using the log-rank test, and the hazard ratio was calculated using the Cox proportional risk model. Sensitivity analysis was performed according to the left ventricular ejection fraction. Four different clinical clusters from 4063 total patients were identified: metabolic, ischaemic, high comorbidity burden, and elderly-atrial fibrillation. Compared with the metabolic cluster, patients in the high comorbidity burden cluster had the highest adjusted risk of combined outcome and all-cause mortality {1.67 [95% confidence interval (CI), 1.40-1.99] and 2.87 [95% CI, 2.17-3.81], respectively}, followed by the elderly-atrial fibrillation and ischaemic clusters. The adjusted readmission risk of patients with ischaemic, high comorbidity burden, and elderly-atrial fibrillation clusters were 1.35 (95% CI, 1.08-1.68), 1.39 (95% CI, 1.13-1.72), and 1.42 (95% CI, 1.14-1.77), respectively. The comorbidity network analysis found that patients in the high comorbidity burden cluster had more and higher comorbidity correlations than those in other clusters. Sensitivity analysis revealed that patients in the high comorbidity burden cluster had the highest risk of combined outcome and all-cause mortality (P < 0.05).

CONCLUSIONS

The difference in adverse outcomes among clusters confirmed the heterogeneity of CHF and the importance of hierarchical management. This study can provide a basis for personalized treatment and management of patients with CHF, and provide a new perspective for clinical decision making.

Erratum: Properties of a New Group of Cosmic Nuclei: Results from the Alpha Magnetic Spectrometer on Sodium, Aluminum, and Nitrogen [Phys. Rev. Lett. 127, 021101 (2021)]

This corrects the article DOI: 10.1103/PhysRevLett.127.021101.

Interpretable prediction of 3-year all-cause mortality in patients with heart failure caused by coronary heart disease based on machine learning and SHAP

BACKGROUND

This study sought to evaluate the performance of machine learning (ML) models and establish an explainable ML model with good prediction of 3-year all-cause mortality in patients with heart failure (HF) caused by coronary heart disease (CHD).

METHODS

We established six ML models using follow-up data to predict 3-year all-cause mortality. Through comprehensive evaluation, the best performing model was used to predict and stratify patients. The log-rank test was used to assess the difference between Kaplan-Meier curves. The association between ML risk and 3-year all-cause mortality was also assessed using multivariable Cox regression. Finally, an explainable approach based on ML and the SHapley Additive exPlanations (SHAP) method was deployed to calculate 3-year all-cause mortality risk and to generate individual explanations of the model's decisions.

RESULTS

The best performing extreme gradient boosting (XGBoost) model was selected to predict and stratify patients. Subjects with a higher ML score had a high hazard of suffering events (hazard ratio [HR]: 10.351; P < 0.001), and this relationship persisted with a multivariable analysis (adjusted HR: 5.343; P < 0.001). Age, N-terminal pro-B-type natriuretic peptide, occupation, New York Heart Association classification, and nitrate drug use were important factors for both genders.

CONCLUSIONS

The ML-based risk stratification tool was able to accurately assess and stratify the risk of 3-year all-cause mortality in patients with HF caused by CHD. ML combined with SHAP could provide an explicit explanation of individualized risk prediction and give physicians an intuitive understanding of the influence of key features in the model.

Time-to-event prediction analysis of patients with chronic heart failure comorbid with atrial fibrillation: a LightGBM model

Background

Chronic heart failure (CHF) comorbid with atrial fibrillation (AF) is a serious threat to human health and has become a major clinical burden. This prospective cohort study was performed to design a risk stratification system based on the light gradient boosting machine (LightGBM) model to accurately predict the 1- to 3-year all-cause mortality of patients with CHF comorbid with AF.

Methods

Electronic medical records of hospitalized patients with CHF comorbid with AF from January 2014 to April 2019 were collected. The data set was randomly divided into a training set and test set at a 3:1 ratio. In the training set, the synthetic minority over-sampling technique (SMOTE) algorithm and fivefold cross validation were used for LightGBM model training, and the model performance was performed on the test set and compared using the logistic regression method. The survival rate was presented on a Kaplan–Meier curve and compared by a log-rank test, and the hazard ratio was calculated by a Cox proportional hazard model.

Results

Of the included 1796 patients, the 1-, 2-, and 3-year cumulative mortality rates were 7.74%, 10.63%, and 12.43%, respectively. Compared with the logistic regression model, the LightGBM model showed better predictive performance, the area under the receiver operating characteristic curve for 1-, 2-, and 3-year all-cause mortality was 0.718 (95%CI, 0.710–0.727), 0.744(95%CI, 0.737–0.751), and 0.757 (95%CI, 0.751–0.763), respectively. The net reclassification index was 0.062 (95%CI, 0.044–0.079), 0.154 (95%CI, 0.138–0.172), and 0.148 (95%CI, 0.133–0.164), respectively. The differences between the two models were statistically significant (P < 0.05). Patients in the high-risk group had a significantly higher hazard of death than those in the low-risk group (hazard ratios: 12.68, 13.13, 14.82, P < 0.05).

Conclusion

Risk stratification based on the LightGBM model showed better discriminative ability than traditional model in predicting 1- to 3-year all-cause mortality of patients with CHF comorbid with AF. Individual patients’ prognosis could also be obtained, and the subgroup of patients with a higher risk of mortality could be identified. It can help clinicians identify and manage high- and low-risk patients and carry out more targeted intervention measures to realize precision medicine and the optimal allocation of health care resources.

Properties of a New Group of Cosmic Nuclei: Results from the Alpha Magnetic Spectrometer on Sodium, Aluminum, and Nitrogen

We report the properties of sodium (Na) and aluminum (Al) cosmic rays in the rigidity range 2.15 GV to 3.0 TV based on 0.46 million sodium and 0.51 million aluminum nuclei collected by the Alpha Magnetic Spectrometer experiment on the International Space Station. We found that Na and Al, together with nitrogen (N), belong to a distinct cosmic ray group. In this group, we observe that, similar to the N flux, both the Na flux and Al flux are well described by the sums of a primary cosmic ray component (proportional to the silicon flux) and a secondary cosmic ray component (proportional to the fluorine flux). The fraction of the primary component increases with rigidity for the N, Na, and Al fluxes and becomes dominant at the highest rigidities. The Na/Si and Al/Si abundance ratios at the source, 0.036±0.003 for Na/Si and 0.103±0.004 for Al/Si, are determined independent of cosmic ray propagation.

[Orexin-A inhibits γ-aminobutyric acid current of neonatal rat spinal cord ventral horn neurons by activating OX1R, OX2R and Ca2+-independent PKC]

OBJECTIVE

To investigate the effect of orexin-A on the functionality of ionotropic γ-aminobutyric acid (GABA) receptors in spinal cord ventral horn neurons and its mechanisms.

OBJECTIVE

The spinal cord containing the lumbosacral enlargement was isolated from neonatal SD rats (7-12 days old) and sliced. The slices were digested with papain (in 0.18 g/30 mL artificial cerebrospinal fluid) for 40-60 min, and the ventral horn neurons were separated acutely using fire-polished Pasteur pipettes. After the cells adhered to the bottom of Petri dishes, patch-clamp experiments combined with pharmacological methods were performed to test the effects of orexin-A on GABA currents of the neurons treated with SB334867 (a selective OX₁R antagonist), TCSOX229 (a selective OX₂R antagonist), Bis-Ⅳ (a PKC inhibitor), PMA (a PKC agonist), Rp-cAMP (a PKA inhibitor), or BAPTA (Ca²⁺ chelator).

OBJECTIVE

The isolated neurons maintained good morphologies with diverse shapes of cell body and long protrusions. Treatment with orexin-A significantly inhibited the amplitude of GABA-induced current (P < 0.001, n=49) with an inhibition rate of (67.48±12.50)%. SB334867 and TCSOX229, when applied simultaneously, completely abolished the suppressive effect of orexin-A on the GABA currents (P=0.93, n=6), and their separate use partially relieved the suppressive effect of orexin-A (P=0.001, n=8; P=0.02, n=8). The application of Bis-Ⅳ also abolished the suppressive effect of orexin-A on GABA currents (P=0.31, n=5). PMA mimicked the effect of orexin-A in these neurons and significantly inhibited GABA currents with an inhibition rate of (60.79±10.94)%, and the application of orexin-A did not cause further suppression of GABA currents in PMA-treated neurons (P=0.15, n=6). Orexin-A was still capable of suppressing GABA currents in Rp-cAMP-treated neurons (P=0.001, n=5). The extracellular Ca²⁺-free solution (P=0.004, n=8) or the presence of BAPTA (P=0.04, n=7) did not significantly affect the inhibitory effect of orexin-A on GABA currents.

OBJECTIVE

Orexin-A inhibits GABA currents in the ventral horn neurons of rat spinal cord probably by activating OX₁R, OX₂R and Ca²⁺-independent PKC.

Improving Risk Identification of Adverse Outcomes in Chronic Heart Failure Using SMOTE+ENN and Machine Learning

PURPOSE

This study sought to develop models with good identification for adverse outcomes in patients with heart failure (HF) and find strong factors that affect prognosis.

PATIENTS AND METHODS

A total of 5004 qualifying cases were selected, among which 498 cases had adverse outcomes and 4506 cases were discharged after improvement. The study subjects were hospitalized patients diagnosed with HF from a regional cardiovascular hospital and the cardiology department of a medical university hospital in Shanxi Province of China between January 2014 and June 2019. Synthesizing minority oversampling technology combined with edited nearest neighbors (SMOTE+ENN) was used to pre-process unbalanced data. Traditional logistic regression (LR), k-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) were used to build risk identification models, and each model was repeated 100 times. Model discrimination and calibration were estimated using F1-score, the area under the receiver-operating characteristic curve (AUROC), and Brier score. The best performing of the five models was used to identify the risk of adverse outcomes and evaluate the influencing factors.

RESULTS

The SME-XGBoost was the best performing model with means of F1-score (0.3673, 95% confidence interval [CI]: 0.3633-0.3712), AUC (0.8010, CI: 0.7974-0.8046), and Brier score (0.1769, CI: 0.1748-0.1789). Age, N-terminal pronatriuretic peptide, pulmonary disease, etc. were the most significant factors of adverse outcomes in patients with HF.

CONCLUSION

The combination of SMOTE+ENN and advanced machine learning methods effectively improved the discrimination efficacy of adverse outcomes in HF patients, accurately stratified patients at risk of adverse outcomes, and found the top factors of adverse outcomes. These models and factors emphasize the importance of health status data in determining adverse outcomes in patients with HF.

POS0851 IDENTIFICATION OF HUB GENES AND PATHWAYS IN DERMATOMYOSITIS BY BIOINFORMATICS ANALYSIS

Background:

Dermatomyositis (DM) is a chronic systemic autoimmune disease characterized by inflammatory infiltrates in the skin and muscle1. The genes and pathways in the inflamed myopathies in patients with DM are poorly understood2.

Objectives:

To identify the key genes and pathways associated with DM and further discover its pathogenesis.

Methods:

Muscle tissue gene expression profile (GSE143323) were acquired from the GEO database, which included 39 DM samples and 20 normal samples. The differentially expressed genes (DEGs) in DM muscle tissue were screened by adopting the R software. Gene ontology (GO) and Kyoto Encyclopedia of Genome (KEGG) pathway enrichment analysis was performed by Metascape online analysis tool. A protein-protein interaction (PPI) network was then constructed by STRING software using the genes in significantly different pathways. Network of DEGs was analyzed by Cytoscape software. And degree of nodes was used to screen key genes.

Results:

Totally, 126 DEGs were obtained, which contained 122 up-regulated and 4 down-regulated. GO analysis revealed that most of the DEGs were significantly enriched in type I interferon signaling pathway, response to interferon-gamma, collagen-containing extracellular matrix, response to interferon-alpha and bacterium, positive regulation of cell death, leukocyte chemotaxis. KEGG pathway analysis showed that upregulated DEGs enhanced pathways associated with the hepatitis C, complement and coagulation cascades, p53 signaling pathway, RIG-I-like receptor signaling, Osteoclast differentiation, and AGE-RAGE signaling pathway. Ten hub genes were identified in DM, they were ISG15, IRF7, STAT1, MX1, OASL, OAS2, OAS1, OAS3, GBP1, and IRF9 according to the Cytoscape software and cytoHubba plugin.

Conclusion:

The findings from this bioinformatics network analysis study identified the key hub genes that might provide new molecular markers for its diagnosis and treatment.

References:

[1]Olazagasti JM, Niewold TB, Reed AM. Immunological biomarkers in dermatomyositis. Curr Rheumatol Rep 2015;17(11):68. doi: 10.1007/s11926-015-0543-y [published Online First: 2015/09/26].

[2]Chen LY, Cui ZL, Hua FC, et al. Bioinformatics analysis of gene expression profiles of dermatomyositis. Mol Med Rep 2016;14(4):3785-90. doi: 10.3892/mmr.2016.5703 [published Online First: 2016/09/08].

[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0458 IDENTIFICATION OF HUB GENES AND MOLECULAR PATHWAYS IN PATIENTS WITH RHEUMATOID ARTHRITIS BY BIOINFORMATICS ANALYSIS

Background:

Rheumatoid arthritis (RA) is a chronic, inflammatory synovitis based systemic disease of unknown etiology1. The genes and pathways in the inflamed synovium of RA patients are poorly understood.

Objectives:

This study aims to identify differentially expressed genes (DEGs) associated with the progression of synovitis in RA using bioinformatics analysis and explore its pathogenesis2.

Methods:

RA expression profile microarray data GSE89408 were acquired from the public gene chip database (GEO), including 152 synovial tissue samples from RA and 28 healthy synovial tissue samples. The DEGs of RA synovial tissues were screened by adopting the R software. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed. Protein-protein interaction (PPI) networks were assembled with Cytoscape software.

Results:

A total of 654 DEGs (268 up-regulated genes and 386 down-regulated genes) were obtained by the differential analysis. The GO enrichment results showed that the up-regulated genes were significantly enriched in the biological processes of myeloid leukocyte activation, cellular response to interferon-gamma and immune response-regulating signaling pathway, and the down-regulated genes were significantly enriched in the biological processes of extracellular matrix, retinoid metabolic process and regulation of lipid metabolic process. The KEGG annotation showed the up-regulated genes mainly participated in the staphylococcus aureus infection, chemokine signaling pathway, lysosome signaling pathway and the down-regulated genes mainly participated in the PPAR signaling pathway, AMPK signaling pathway, ECM-receptor interaction and so on. The 9 hub genes (PTPRC, TLR2, tyrobp, CTSS, CCL2, CCR5, B2M, fcgr1a and PPBP) were obtained based on the String database model by using the Cytoscape software and cytoHubba plugin3.

Conclusion:

The findings identified the molecular mechanisms and the key hub genes of pathogenesis and progression of RA.

References:

[1]Xiong Y, Mi BB, Liu MF, et al. Bioinformatics Analysis and Identification of Genes and Molecular Pathways Involved in Synovial Inflammation in Rheumatoid Arthritis. Med Sci Monit 2019;25:2246-56. doi: 10.12659/MSM.915451 [published Online First: 2019/03/28]

[2]Mun S, Lee J, Park A, et al. Proteomics Approach for the Discovery of Rheumatoid Arthritis Biomarkers Using Mass Spectrometry. Int J Mol Sci 2019;20(18) doi: 10.3390/ijms20184368 [published Online First: 2019/09/08]

[3]Zhu N, Hou J, Wu Y, et al. Identification of key genes in rheumatoid arthritis and osteoarthritis based on bioinformatics analysis. Medicine (Baltimore) 2018;97(22):e10997. doi: 10.1097/MD.0000000000010997 [published Online First: 2018/06/01]

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

AB0005 IDENTIFICATION OF KEY GENES AND PATHWAYS FOR PSORIASIS BASED ON GEO DATABASES BY BIOINFORMATICS ANALYSIS

Background:

Psoriasis is an immune-mediated, genetic disease manifesting in the skin or joints or both, and also has a strong genetic predisposition and autoimmune pathogenic traits1. The hallmark of psoriasis is sustained inflammation that leads to uncontrolled keratinocyte proliferation and dysfunctional differentiation. And it’s also a chronic relapsing disease, which often necessitates a long-term therapy2.

Objectives:

To investigate the molecular mechanisms of psoriasis and find the potential gene targets for diagnosis and treating psoriasis.

Methods:

Total 334 gene expression data of patients with psoriasis research (GSE13355 GSE14905 and GSE30999) were obtained from the Gene Expression Omnibus database. After data preprocessing and screening of differentially expressed genes (DEGs) by R software. Online toll Metascape3 was used to analyze Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs. Interactions of proteins encoded by DEGs were discovered by Protein-protein interaction network (PPI) using STRING online software. Cytoscape software was utilized to visualize PPI and the degree of each DEGs was obtained by analyzing the topological structure of the PPI network.

Results:

A total of 611 DEGs were found to be differentially expressed in psoriasis. GO analysis revealed that up-regulated DEGs were mostly associated with defense and response to external stimulus while down-regulated DEGs were mostly associated with metabolism and synthesis of lipids. KEGG enrichment analysis suggested they were mainly enriched in IL-17 signaling, Toll-like receptor signaling and PPAR signaling pathways, Cytokine-cytokine receptor interaction and lipid metabolism. In addition, top 9 key genes (CXCL10, OASL, IFIT1, IFIT3, RSAD2, MX1, OAS1, IFI44 and OAS2) were identified through Cytoscape.

Conclusion:

DEGs of psoriasis may play an essential role in disease development and may be potential pathogeneses of psoriasis.

References:

[1]Boehncke WH, Schon MP. Psoriasis. Lancet 2015;386(9997):983-94. doi: 10.1016/S0140-6736(14)61909-7 [published Online First: 2015/05/31].

[2]Zhang YJ, Sun YZ, Gao XH, et al. Integrated bioinformatic analysis of differentially expressed genes and signaling pathways in plaque psoriasis. Mol Med Rep 2019;20(1):225-35. doi: 10.3892/mmr.2019.10241 [published Online First: 2019/05/23].

[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0742 SCREENING AND BIOINFORMATICS ANALYSIS OF HUB GENES AND PATHWAYS FOR PRIMARY SJÖGREN’S SYNDROME BASED ON GEO DATABASE

Background:

Primary Sjögren’s syndrome (pSS) is an autoimmune disease that featured as lymphoplasmacytic infiltration of the exocrine glands leading to sicca symptoms1. However, its underlying molecular mechanisms remain elusive.

Objectives:

This study aims to identify differentially expressed genes (DEGs) and pathways associated with the progression of pSS using bioinformatics analysis and explore its pathogenesis.

Methods:

The pSS-associated gene chip data set GSE66795 was obtained from the Gene Expression Omnibus (GEO) database, which included 131 cases of fully-phenotyped pSS patients’ whole blood samples and 29 cases of control samples. DEGs were screened Using R software. Online tool Metascape2 was used to make Gene Ontology (GO) and KEGG pathway enrichment. The PPI network was performed using String database. Hub genes were identified by Cytoscape.

Results:

A total of 108 DEGs were captured, including 101 up-regulated genes and 7 down-regulated genes. GO enrichment showed that these DEGs were primarily enriched in defense response to virus, response to interferon-gamma, regulation of innate immune response, response to interferon-beta, double-stranded RNA binding, response to interferon-alpha. KEGG pathway enrichment analysis showed these DEGs were principally enriched in Influenza A, RIG-I-like receptor signaling pathway, necroptosis, Staphylococcus aureus infection. Finally, 9 hub genes (STAT1, IRF7, OAS2, GBP1, OAS1, IFIT3, IFIH1, OAS3, DDX60) had highest degree value.

Conclusion:

The findings identified molecular mechanisms and the key hub genes that may involve in the occurrence and development of pSS.

References:

[1]Francois H, Mariette X. Renal involvement in primary Sjogren syndrome. Nat Rev Nephrol 2016;12(2):82-93. doi: 10.1038/nrneph.2015.174 [published Online First: 2015/11/17].

[2]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0848 IDENTIFICATION OF POTENTIAL CRUCIAL GENES AND KEY PATHWAYS IN PULMONARY ARTERIAL HYPERTENSION WITH SYSTEMIC SCLEROSIS BY BIOINFORMATIC ANALYSIS

Background:

Pulmonary arterial hypertension with systemic sclerosis (SSc-PAH) is the main cause of death in patients with SSc. Early diagnosis and timely treatment are very important to reduce the mortality of patients with SSc-PAH1. At present, there are not many sensitive markers for the diagnosis of SSc-PAH. Therefore, it is necessary to mine more sensitive markers as more accurate and practical predictors, which is of great significance for the diagnosis and treatment of SSc-PAH.

Objectives:

To discover the differentially expressed genes (DEGs) and activated signaling pathways in SSc-PAH.

Methods:

Fifty-five samples (27 SSc-PAH v.s 28 normal controls) in GSE33463 chip data obtained from Gene Expression Omnibus (GEO) were included in this study. DEGs in SSc-PAH patients were screened by R, key pathways and hub genes were discoved by Metascape2, STRING3 and Cytoscape.

Results:

Total 431 genes with large differences were identified, including 238 up-regulated genes and 193 down-regulated genes, after standardizing the data (|logFC| > 1; P < 0.05). GO analysis showed that the upregulated genes were mainly involved in defense response to virus, hemoglobin complex, platelet alpha granule membrane and cytokine binding. The downregulated genes were mainly characterized by positive regulation of cell death, regulation of MAPK cascade, regulation of DNA-binding transcription factor activity and transcription factor AP-1 complex. Several significant enriched pathways obtained in the KEGG pathway analysis were Influenza A, Hepatitis C, IL-17 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway. Finally, after the selected differential genes were introduced into STRING online software, the data information of protein interaction network was derived, and 12 core genes in the network were identified, they were CXCL8, PPBP, LPAR1, FPR2, GNG11, CXCL10, LPAR5, JUN, C3AR1, CCR2, CCR3, IRF2.

Conclusion:

The genes and signal pathways related to SSc-PAH discovered by bioinformatics methods could not only provided new molecular markers for its diagnosis and treatment, but also provided new ideas for its related biological research.

References:

[1]Zheng JN, Li Y, Yan YM, et al. Identification and Validation of Key Genes Associated With Systemic Sclerosis-Related Pulmonary Hypertension. Front Genet 2020;11:816. doi: 10.3389/fgene.2020.00816 [published Online First: 2020/08/15].

[2]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

[3]Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019;47(D1):D607-D13. doi: 10.1093/nar/gky1131 [published Online First: 2018/11/27].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

[Contribution of sympathetic activation to antihypertrophic memory after regression of exercise-induced physiological myocardial hypertrophy in mice]

OBJECTIVE

To investigate whether anti-hypertrophic memory exists after regression of exercise-induced physiological myocardial hypertrophy (PMH) and explore the contribution of sympathetic activation to hypertrophic memory formation.

OBJECTIVE

Seventy-two mice were randomized equally into 6 groups, including sedentary sham-operated group, exercise hypertrophic preconditioning (EHP) + sham operation group, bisoprolol (an adrenergic β1 receptor blocker) + EHP + sham operation group (biso+Exe+Sham group), sedentary group with transverse aortic constriction (TAC) (Sed+TAC group), EHP+ TAC group (Exe+TAC group), and bisoprolol+EHP+TAC group (biso+Exe+TAC group). The mice in the EHP groups were subjected to 3 weeks of swimming training, and in the bisoprolol groups, bisoprolol was administered by gavage once daily from two days before till the end of the training. One week after the training, TAC or sham surgery was performed. Echocardiography and hemodynamic measurements were performed to evaluate cardiac function of the mice, and the myocardial tissues were examined histologically to detect cardiac remodeling.

OBJECTIVE

Compared with the sedentary group, the mice receiving 3 weeks of swimming training had significantly increased heart weight to body weight ratio (HW/BW), HW to tibia length ratio (HW/TL), and the cross-sectional area of the cardiomyocytes (P < 0.05). One week after the training, exercise-induced PMH rapidly diminished and both HW/BW and HW/TL recovered the baseline levels. Treatment with bisoprolol obviously prevented the occurrence of PMH. Four weeks after TAC, the left ventricular posterior wall thickness, HW/BW, HW/TL, left ventricular end diastolic pressure and cross-sectional area of cardiomyocytes were all significantly lower (P < 0.05) while the left ejection fraction and maximal change rate of left ventricular pressure were significantly higher (P < 0.05) in Exe + TAC group than in Sed + TAC group. No significant difference was found in these parameters between biso + Exe + TAC group and Sed + TAC group.

OBJECTIVE

Anti-hypertrophic memory exists even after the regression of exercise-induced PMH, which may be attributed to the activation of sympathetic nervous system during exercise.