Scale Invariance of a Spherical Unitary Fermi Gas.

A unitary Fermi gas in an isotropic harmonic trap is predicted to show scale and conformal symmetry that have important consequences in its thermodynamic and dynamical properties. By experimentally realizing a unitary Fermi gas in an isotropic harmonic trap, we demonstrate its universal expansion dynamics along each direction and at different temperatures. We show that as a consequence of SO(2,1) symmetry, the measured release energy is equal to that of the trapping energy. We further observe the breathing mode with an oscillation frequency twice the trapping frequency and a small damping rate, providing the evidence of SO(2,1) symmetry. In addition, away from resonance when scale invariance is broken, we determine the effective exponent γ that relates the chemical potential and average density along the BEC-BCS crossover, which qualitatively agrees with the mean field predictions. This Letter opens the possibility of studying nonequilibrium dynamics in a conformal invariant system in the future.

Deciphering the molecular landscape of rheumatoid arthritis offers new insights into the stratified treatment for the condition.

Background: For Rheumatoid Arthritis (RA), a long-term chronic illness, it is essential to identify and describe patient subtypes with comparable goal status and molecular biomarkers. This study aims to develop and validate a new subtyping scheme that integrates genome-scale transcriptomic profiles of RA peripheral blood genes, providing a fresh perspective for stratified treatments. Methods: We utilized independent microarray datasets of RA peripheral blood mononuclear cells (PBMCs). Up-regulated differentially expressed genes (DEGs) were subjected to functional enrichment analysis. Unsupervised cluster analysis was then employed to identify RA peripheral blood gene expression-driven subtypes. We defined three distinct clustering subtypes based on the identified 404 up-regulated DEGs. Results: Subtype A, named NE-driving, was enriched in pathways related to neutrophil activation and responses to bacteria. Subtype B, termed interferon-driving (IFN-driving), exhibited abundant B cells and showed increased expression of transcripts involved in IFN signaling and defense responses to viruses. In Subtype C, an enrichment of CD8+ T-cells was found, ultimately defining it as CD8+ T-cells-driving. The RA subtyping scheme was validated using the XGBoost machine learning algorithm. We also evaluated the therapeutic outcomes of biological disease-modifying anti-rheumatic drugs. Conclusions: The findings provide valuable insights for deep stratification, enabling the design of molecular diagnosis and serving as a reference for stratified therapy in RA patients in the future.

Asymmetric total synthesis of polycyclic xanthenes and discovery of a WalK activator active against MRSA.

The development of new antibiotics continues to pose challenges, particularly considering the growing threat of multidrug-resistant Staphylococcus aureus. Structurally diverse natural products provide a promising source of antibiotics. Herein, we outline a concise approach for the collective asymmetric total synthesis of polycyclic xanthene myrtucommulone D and five related congeners. The strategy involves rapid assembly of the challenging benzopyrano[2,3-a]xanthene core, highly diastereoselective establishment of three contiguous stereocenters through a retro-hemiketalization/double Michael cascade reaction, and a Mitsunobu-mediated chiral resolution approach with high optical purity and broad substrate scope. Quantum mechanical calculations provide insight into stereoselective construction mechanism of the three contiguous stereocenters. Additionally, this work leads to the discovery of an antibacterial agent against both drug-sensitive and drug-resistant S. aureus. This compound operates through a unique mechanism that promotes bacterial autolysis by activating the two-component sensory histidine kinase WalK. Our research holds potential for future antibacterial drug development.

Risk factors for subsequent suicidal acts among 12-25-year-old high-risk callers to a suicide prevention hotline in China: a longitudinal study.

BACKGROUND: A few previous cross-sectional studies investigated correlated factors of suicidal ideation or suicide attempts among suicide prevention hotline callers; however, scarcely any evidence was from a longitudinal study. In addition, it is still unclear whether improvements in some suicide risk factors could reduce the occurrence of subsequent suicidal acts. This longitudinal study focusing on the risk factors for subsequent suicidal acts among adolescent and young adult callers with high suicide risk aims to fill this gap. METHODS: This study recruited 12-25-year-old high-risk callers to a China nationwide suicide prevention hotline. Potential risk factors, including hopefulness, psychological distress, depression, history of suicide attempts, alcohol or substance misuse, and acute life events, were examined during the index calls, and improvements in hopefulness, psychological distress, and suicide intent were assessed before ending the index calls. The recruited callers were followed up 12 months after their index calls. The primary outcome was the occurrence of suicidal acts (suicide attempts or suicide death) during follow-up. Kaplan-Meier survival curves, log-rank tests, and Cox proportional hazards model were used. RESULTS: During the follow-up period, 271 of 1656 high-risk adolescent and young adult callers attempted suicide, and seven callers died by suicide. After adjusting for demographic variables, low hopefulness (Hazard Ratio [HR] = 2.03, 95% Confidence Interval [CI]=[1.47, 2.80]) at the beginning of the index call was associated with a higher risk for subsequent suicidal acts, whereas improvements in psychological distress (HR = 0.61, 95%CI [0.41, 0.89]) and suicidal intent (HR = 0.56, 95%CI [0.38, 0.84]) during the index call reduced the risk of subsequent suicidal acts. In addition, alcohol or substance misuse (Model 2, HR = 1.65, 95%CI [1.11, 2.46]) and suicide attempt history(Model 1: one episode, HR = 1.96, 95%CI=[1.05, 3.66]; two or more episodes, HR = 2.81, 95%CI [1.59, 4.96]. Model 2: one episode, HR = 2.26, 95%CI [1.06, 4.82]; two or more episodes: HR = 3.28, 95%CI [1.63, 6.60]) were risk factors for subsequent suicidal acts. CONCLUSIONS: While suicide prevention hotline operators deliver brief psychological interventions to high-risk adolescent and young adult callers, priority should be given to callers with low hopefulness and to the alleviation of callers' high psychological distress and suicide intent.

Association between hydroxyethyl starch 130/0.4 administration during noncardiac surgery and postoperative acute kidney injury: A propensity score-matched analysis of a large cohort in China.

STUDY OBJECTIVE: The use of hydroxyethyl starch 130/0.4 has been linked to renal injury in critically ill patients, but its impact on surgical patients remains uncertain. DESIGN: A retrospective cohort study. SETTING: This study was conducted at one tertiary care hospital in China. PATIENTS: We evaluated the records of 51,926 Chinese adults who underwent noncardiac surgery from 2013 to 2022. Patients given a combination of hydroxyethyl starch 130/0.4 and crystalloids were propensity-matched at a 1: 1 ratio of baseline characteristics to patients given only crystalloids (11,725 pairs). INTERVENTIONS: Eligible patients were divided into those given a combination of hydroxyethyl starch 130/0.4 and crystalloid during surgery and a reference crystalloid group consisting of patients who were not given any colloid. MEASUREMENTS: The primary outcome was the incidence of acute kidney injury. Secondarily, acute kidney injury stage, need for renal replacement therapy, intensive care unit transfer rate, and duration of postoperative hospitalization were considered. MAIN RESULTS: After matching, hydroxyethyl starch use [8.5 (IQR: 7.5-10.0) mL/kg] did not increase the incidence of acute kidney injury compared with that in the crystalloid group [2.0 vs. 2.2%, OR: 0.90 (0.74-1.08), P = 0.25]. Nor did hydroxyethyl starch use worsen acute kidney injury stage [OR 0.90 (0.75-1.08), P = 0.26]. No significant differences between the fluid groups were observed in renal replacement therapy [OR 0.60 (0.41-0.90), P = 0.02)] or intensive care unit transfers [OR 1.02 (0.95-1.09), P = 0.53] after Bonferroni correction. Even in a subset of patients at high risk of renal injury, hydroxyethyl starch use was not associated with worse outcomes. CONCLUSIONS: Hydroxyethyl starch 130/0.4 use was not significantly associated with a greater incidence of postoperative acute kidney injury compared to receiving crystalloid solutions only.

Association between maternal antidepressant use during pregnancy and the risk of autism spectrum disorder and attention deficit hyperactivity disorder in offspring.

Prenatal antidepressant exposure has been reported to be associated with adverse neurodevelopmental outcomes, yet studies considering confounding factors in Asian populations are lacking. This study utilized a nationwide data base in Taiwan, enrolling all liveborn children registered in the National Health Insurance system between 2004 and 2016. Subjects were divided into two groups: antidepressant-exposed (n = 55,707)) and antidepressant-unexposed group (n = 2,245,689). The effect of antidepressant exposure during different trimesters on autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) was examined. Sibling controls and parallel comparisons by paternal exposure status were treated as negative controls. Additional sensitivity analyses were conducted to examine the effects of antidepressant exposure before and after pregnancy. Prenatal antidepressant exposure was associated with increased risks of ASD and ADHD in population-wide and adjusted analysis. However when comparing antidepressant-exposed children with their unexposed siblings, no differences were found for ASD (Hazard ratio [HR]: 1.04, 95% confidence interval [CI] 0.76-1.42 in first trimester; HR: 0.96, 95% CI 0.62-1.50 in second trimester; HR: 0.69, 95% CI 0.32-1.48 in third trimester) and ADHD (HR: 0.98, 95%CI 0.84-1.15 in first trimester; HR: 0.91, 95% CI 0.73-1.14 in second trimester; HR: 0.79, 95% CI 0.54-1.16 in third trimester). Increased risks for ASD and ADHD were also noted in paternal control, before and after pregnancy analyses. These results imply that the association between prenatal antidepressant exposure and ASD and ADHD is not contributed to by an intrauterine medication effect but more likely to be accounted for by maternal depression, genetic, and potential environmental factors.

Innovative Neuroimaging Biomarker Distinction of Major Depressive Disorder and Bipolar Disorder through Structural Connectome Analysis and Machine Learning Models.

Major depressive disorder (MDD) and bipolar disorder (BD) share clinical features, which complicates their differentiation in clinical settings. This study proposes an innovative approach that integrates structural connectome analysis with machine learning models to discern individuals with MDD from individuals with BD. High-resolution MRI images were obtained from individuals diagnosed with MDD or BD and from HCs. Structural connectomes were constructed to represent the complex interplay of brain regions using advanced graph theory techniques. Machine learning models were employed to discern unique connectivity patterns associated with MDD and BD. At the global level, both BD and MDD patients exhibited increased small-worldness compared to the HC group. At the nodal level, patients with BD and MDD showed common differences in nodal parameters primarily in the right amygdala and the right parahippocampal gyrus when compared with HCs. Distinctive differences were found mainly in prefrontal regions for BD, whereas MDD was characterized by abnormalities in the left thalamus and default mode network. Additionally, the BD group demonstrated altered nodal parameters predominantly in the fronto-limbic network when compared with the MDD group. Moreover, the application of machine learning models utilizing structural brain parameters demonstrated an impressive 90.3% accuracy in distinguishing individuals with BD from individuals with MDD. These findings demonstrate that combined structural connectome and machine learning enhance diagnostic accuracy and may contribute valuable insights to the understanding of the distinctive neurobiological signatures of these psychiatric disorders.

Excess Mortality in Individuals with Autism Spectrum Disorder: A Population-Based Cohort Study.

Purpose: Autism spectrum disorder (ASD) may be associated with increased mortality, but relevant findings have been inconsistent. The modifying effects of gender and intellectual disability on excess mortality in individuals with ASD are underexplored. Patients and Methods: Using Taiwan's National Health Insurance Research Database and the National Death Registry, this population-based cohort study selected the data of 75,946 patients with ASD (ASD cohort) and 75,946 age group-, gender-, and income-matched (1:1) patients without ASD (non-ASD cohort). Cox proportional hazards models were used to compare mortality rates between the cohorts, and stratified analyses were used to evaluate the influence of gender and intellectual disability on mortality risk. Results: The ASD cohort had higher mortality rates for all causes of death than did the non-ASD cohort (adjusted hazard ratio 1.64, 95% confidence interval 1.54-1.75). Comorbid intellectual disability was associated with an increased risk of mortality, and this association was stronger in female patients than in male patients. Moreover, when focusing on deaths from natural causes, we found a significantly higher odds ratio for mortality in the ASD population with ID compared to those without ID. Conclusion: ASD is associated with increased mortality, especially among female individuals and those with intellectual disability.

Comprehensive consideration of multiple determinants from evidence to recommendations in guidelines for most traditional Chinese medicine was suboptimal: a systematic review.

BACKGROUND: The overall comprehensive consideration of the factors influencing the recommendations in the traditional Chinese medicine (TCM) guidelines remains poorly studied. This study systematically evaluate the factors influencing recommendations formation in the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) clinical practice guidelines (CPGs) and TCM CPGs. METHODS: This was a methodological review in which we searched six databases and multiple related websites. The GRADE CPGs were identified as the guidelines developed by the GRADE Working Group or the two Co-Chairs. For the TCM CPGs, we randomly selected guidelines that were published by the TCM or integrative medicine academic societies from China mainland (published by the TCM or integrative medicine academic societies of China mainland). Two reviewers independently screened and extracted data. We included CPGs published in 2018-2022. We extracted information on the influencing factors of evidence to recommendation and conducted the analyses using descriptive statistics and calculated the proportion of relevant items by IBM SPSS Statistics and Microsoft Excel to compare the differences between the GRADE CPGs and the TCM CPGs. RESULTS: Forty-five GRADE CPGs (including 912 recommendations) and 88 TCM CPGs (including 2452 recommendations) were included. TCM recommendations mainly considered the four key determinants of desirable anticipated effects, undesirable anticipated effects, balance between desirable and undesirable effects, certainty of evidence, with less than 20% of other dimensions. And TCM CPGs presented more strong recommendations (for or against) and inappropriate discordant recommendations than GRADE CPGs. GRADE CPGs were more comprehensive considered about the factors affecting the recommendations, and considered more than 70% of all factors in the evidence to recommendation. CONCLUSIONS: The TCM CPGs lack a comprehensive consideration of multiple influencing determinants from evidence to recommendations. In the future, the correct application of the GRADE approaches should be emphasized.

Loureirin A Promotes Cell Differentiation and Suppresses Migration and Invasion of Melanoma Cells via WNT and AKT/mTOR Signaling Pathways.

Resina Draconis is a traditional Chinese medicine, with the in-depth research, its medicinal value in anti-tumor has been revealed. Loureirin A is extracted from Resina Draconis, however, research on the anti-tumor efficacy of Loureirin A is rare. Herein, we investigated the function of Loureirin A in melanoma. Our research demonstrated that Loureirin A inhibited the proliferation of and caused G0/G1 cell cycle arrest in melanoma cells in a concentration-dependent manner. Further study showed that the melanin content and tyrosinase activity was enhanced after Loureirin A treatment, demonstrated that Loureirin A promoted melanoma cell differentiation, which was accompanied with the reduce of WNT signaling pathway. Meanwhile, we found that Loureirin A suppressed the migration and invasion of melanoma cells through the protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway. Taken together, this study demonstrated for the first time the anti-tumor effects of Loureirin A in melanoma cells, which provided a novel therapeutic strategy against melanoma.

Gamabufotalin Induces Apoptosis and Cytoprotective Autophagy through the mTOR Signaling Pathway in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor with a high rate of recurrence and a poor prognosis. Here, we investigated the effect and the potential antitumor mechanism of Gamabufotalin (CS-6) against HCC. Our results show that CS-6 strikingly reduced cell viability, inhibited colony formation, and promoted apoptosis in Hep3B and Huh7 cells. In vivo, CS-6 inhibited HCC xenograft tumor growth with no toxicity to normal tissues. Mechanistically, we found that CS-6 could induce cytoprotective autophagy through the mTOR-ULK1 signaling pathway through downregulation of p62 and upregulation of LC3 II/LC3 I. Meanwhile, CS-6 activated caspase-3 and PARP mediated apoptosis, and the caspase inhibitor Z-VAD-FMK blocked the CS-6-induced cell death in HCC cells. Moreover, autophagy and apoptosis were found to have antagonistic effects in Hep3B and Huh7 cells. Both the autophagy inhibitor chloroquine (CQ) and the mTOR activator MHY1485 blocked autophagy and further enhanced CS-6-induced apoptosis. Taken together, we demonstrated for the first time that CS-6 promotes apoptosis and cytoprotective autophagy through the mTOR signaling pathway in HCC, which proposes a novel strategy for HCC therapy.

PCR combined with serologic testing improves the yield and efficiency of SARS-CoV-2 infection hunting: A study in 40,689 consecutive overseas arrivals.

Background: The global epidemiological situation of COVID-19 remains serious. The rapid hunting of SARS-CoV-2 infection is the key means for preventing transmission. Methods: A total of 40,689 consecutive overseas arrivals were screened for SARS-CoV-2 infection based on PCR and serologic testing. The yield and efficiency of different screening algorithms were evaluated. Result: Among the 40,689 consecutive overseas arrivals, 56 (0.14%) subjects were confirmed to have SARS-CoV-2 infection. The asymptomatic rate was 76.8%. When the algorithm based on PCR alone was used, the identification yield of a single round of PCR (PCR1) was only 39.3% (95% CI: 26.1-52.5%). It took at least four rounds of PCR to achieve a yield of 92.9% (95% CI: 85.9-99.8%). Fortunately, an algorithm based on a single round of PCR combined with a single round of serologic testing (PCR1+ Ab1) greatly improved the screening yield to 98.2% (95% CI: 94.6-100.0%) and required 42,299 PCR and 40,689 serologic tests that cost 6,052,855 yuan. By achieving a similar yield, the cost of PCR1+ Ab1 was 39.2% of that of four rounds of PCR. For hunting one case in PCR1+ Ab1, 769 PCR and 740 serologic tests were required, costing 110,052 yuan, which was 63.0% of that of the PCR1 algorithm. Conclusion: Comparing an algorithm based on PCR alone, PCR combined with a serologic testing algorithm greatly improved the yield and efficiency of the identification of SARS-CoV-2 infection.

Mendelian randomization analysis suggests no associations of herpes simplex virus infections with systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) characterized by immune dysfunction is possibly more vulnerable to herpes simplex virus (HSV) infection. The infection has been intensively considered a common onset and exacerbation of SLE. This study is aimed at elucidating the causal association between SLE and HSV. A bidirectional two-sample Mendelian Randomization (TSMR) analysis was systematically conducted to explore the causal effect of SLE and HSV on each other. The causality was estimated by inverse variance weighted (IVW), MR-Egger and weighted median methods based on the summary-level genome-wide association studies (GWAS) data from a publicly available database. Genetically proxied HSV infection exhibited no causal association with SLE in the forward MR analysis using IVW method (odds ratio [OR] = 0.987; 95% confidence interval [CI]: 0.891-1.093; p = 0.798), nor did HSV-1 IgG (OR = 1.241; 95% CI: 0.874-1.762; p = 0.227) and HSV-2 IgG (OR = 0.934; 95% CI: 0.821-1.062; p = 0.297). Similar null results with HSV infection (OR = 1.021; 95% CI: 0.986-1.057; p = 0.245), HSV-1 IgG (OR = 1.003; 95% CI: 0.982-1.024; p = 0.788) and HSV-2 IgG (OR = 1.034; 95% CI: 0.991-1.080; p = 0.121) were observed in the reverse MR where SLE served as the exposure. Our study demonstrated no causal association between the genetically predicted HSV and SLE.

Adolescent-Caregiver Agreement Regarding the School Bullying and Cyberbullying Involvement Experiences of Adolescents with Autism Spectrum Disorder.

School bullying and cyberbullying victimization and perpetration are prevalent in adolescents with autism spectrum disorder (AASD). However, the levels of adolescent-caregiver agreement regarding the bullying involvement of AASD and the factors associated with these levels remain to be evaluated. In the present study, we evaluated the levels of adolescent-caregiver agreement on the school bullying and cyberbullying involvement experiences of AASD and the factors associated with the levels of agreement. This study included 219 dyads of AASD and their caregivers. The school bullying and cyberbullying involvement experiences of the participating AASD were assessed using the School Bullying Experience Questionnaire and the Cyberbullying Experiences Questionnaire, respectively. Attention-deficit/hyperactivity disorder, oppositional defiant disorder (ODD), depressive and anxiety symptoms, and autistic social impairment were also assessed. AASD and their caregivers had poor to fair levels of agreement regarding the school bullying and cyberbullying victimization and perpetration experiences of AASD. Severe inattention, hyperactivity-impulsivity, ODD, depressive and anxiety symptoms, and autistic social impairment were associated with high levels of adolescent-caregiver agreement. When assessing the bullying involvement experiences of AASD, mental health professionals should obtain information from multiple sources. In addition, the factors influencing the levels of agreement should be considered.

Bioactive secondary metabolites from tomato-derived bacterium Bacillus velezensis Hnu24.

A series of secondary metabolites have been isolated from the genus of Bacillus velezensis, most of which show antibacterial and insecticidal activities. In order to find more bioactive secondary metabolites from B. velezensis, one new natural component aminoindole dimer baciindole A (1), together with seven known compounds (2-8) were isolated from the tomato-derived bacterium Bacillus velezensis Hnu24. The structure of compound 1 was elucidated by its HR-ESI-MS spectral data and 1 D/2D NMR spectroscopic analysis. Compound 3 showed antibacterial activity against Staphylococcus aureus, S. epidermidis and Ralstonia solanacearum with the MIC values of 3.125, 12.5 and 50 µg/mL, respectively. Compound 4 showed antibacterial activity against S. aureus with the MIC value of 12.5 µg/mL. Compound 3 showed cytotoxic activity for human colon cancer HTC116 cancer cells with the IC50 value of 8.42 ± 0.48 µM. Five compounds (1-4 and 8) were obtained from the strain of B. velezensis for the first time. These results indicated that 3 will be useful in developing antimicrobial and treatment of colon cancer agents.

A Compendium of Mucosal Molecular Characteristics Provides Novel Perspectives on the Treatment of Ulcerative Colitis.

BACKGROUND AND AIMS: Ulcerative colitis [UC] is a complex heterogeneous disease. This study aims to reveal the underlying molecular features of UC using genome-scale transcriptomes of patients with UC, and to develop and validate a novel stratification scheme. METHODS: A normalised compendium was created using colon tissue samples (455 patients with UC and 147 healthy controls [HCs]), covering genes from 10 microarray datasets. Upregulated differentially expressed genes [DEGs] were subjected to functional network analysis, wherein samples were grouped using unsupervised clustering. Additionally, the robustness of subclustering was further assessed by two RNA sequencing datasets [100 patients with UC and 16 HCs]. Finally, the Xgboost classifier was applied to the independent datasets to evaluate the efficacy of different biologics in patients with UC. RESULTS: Based on 267 upregulated DEGs of the transcript profiles, UC patients were classified into three subtypes [subtypes A-C] with distinct molecular and cellular signatures. Epithelial activation-related pathways were significantly enriched in subtype A [named epithelial proliferation], whereas subtype C was characterised as the immune activation subtype with prominent immune cells and proinflammatory signatures. Subtype B [named mixed] was modestly activated in all the signalling pathways. Notably, subtype A showed a stronger association with the superior response of biologics such as golimumab, infliximab, vedolizumab, and ustekinumab compared with subtype C. CONCLUSIONS: We conducted a deep stratification of mucosal tissue using the most comprehensive microarray and RNA sequencing data, providing critical insights into pathophysiological features of UC, which could serve as a template for stratified treatment approaches.

Lower Risk of Burn Injury in Children and Adolescents with Autism Spectrum Disorder: A Nationwide Population-Based Study.

Little research has examined burn injury in the pediatric population with autism spectrum disorder (ASD). We used data from Taiwan's National Health Insurance Research Database to identify 15,844 participants aged <18 years with ASD and 130,860 participants without ASD. Our results revealed that the hazard ratios differed across three age ranges. The ASD group had a lower risk of burn injury than the non-ASD group when they were less than 6 years of age, a higher risk from 6 years to 12 years of age, and no difference when they were older than 12 years of age. More research is required to study the characteristics and causes of burn injury in the pediatric population with ASD.

Deep stratification by transcriptome molecular characters for precision treatment of patients with systemic lupus erythematosus.

OBJECTIVES: To leverage the high clinical heterogeneity of systemic lupus erythematosus (SLE), we developed and validated a new stratification scheme by integrating genome-scale transcriptomic profiles to identify patient subtypes sharing similar transcriptomic markers and drug targets. METHODS: A normalized compendium of transcription profiles was created from peripheral blood mononuclear cells (PBMCs) of 1046 SLE patients and 86 healthy controls (HCs), covering an intersection of 13 689 genes from six microarray datasets. Upregulated differentially expressed genes were subjected to functional and network analysis in which samples were grouped using unsupervised clustering to identify patient subtypes. Then, clustering stability was evaluated by the stratification of six integrated RNA-sequencing datasets using the same method. Finally, the Xgboost classifier was applied to the independent datasets to identify factors associated with treatment outcomes. RESULTS: Based on 278 upregulated DEGs of the transcript profiles, SLE patients were classified into three subtypes (subtype A-C) each with distinct molecular and cellular signatures. Neutrophil activation-related pathways were markedly activated in subtype A (named NE-driving), whereas lymphocyte and IFN-related pathways were more enriched in subtype B (IFN-driving). As the most severe subtype, subtype C [NE-IFN-dual-driving (Dual-driving)] shared functional mechanisms with both NE-driving and IFN-driving, which was closely associated with clinical features and could be used to predict the responses of treatment. CONCLUSION: We developed the largest cohesive SLE transcriptomic compendium for deep stratification using the most comprehensive microarray and RNA sequencing datasets to date. This result could guide future design of molecular diagnosis and the development of stratified therapy for SLE patients.

Prediction of Central Lymph Node Metastasis in cN0 Papillary Thyroid Carcinoma by CT Radiomics.

RATIONALE AND OBJECTIVES: To explore the feasibility of the preoperative prediction of pathological central lymph node metastasis (CLNM) status in patients with negative clinical lymph node (cN0) papillary thyroid carcinoma (PTC) using a computed tomography (CT) radiomics signature. MATERIALS AND METHODS: A total of 97 PTC cN0 nodules with CLNM pathology data (pN0, with CLNM, n = 59; pN1, without CLNM, n = 38) in 85 patients were divided into a training set (n = 69) and a validation set (n = 28). For each lesion, 321 radiomic features were extracted from nonenhanced, arterial and venous phase CT images. Minimum redundancy and maximum relevance and the least absolute shrinkage and selection operator were used to find the most important features with which to develop a radiomics signature in the training set. The performance of the radiomics signature was evaluated by receiver operating characteristic curves, calibration curves and decision curve analysis . RESULTS: Three nonzero the least absolute shrinkage and selection operator coefficient features were selected for radiomics signature construction. The radiomics signature for distinguishing the pN0 and pN1 groups achieved areas under the curve of 0.79 (95% CI 0.67, 0.91) in the training set and 0.77 (95% CI 0.55, 0.99) in the validation set. The calibration curves demonstrated good agreement between the radiomics score-predicted probability and the pathological results in the two sets (p= 0.399, p = 0.191). The decision curve analysis curves showed that the model was clinically useful. CONCLUSION: This radiomic signature could be helpful to predict CLNM status in cN0 PTC patients.