Detection of free DNA based on metal-enhanced fluorescence triggered by CRISPR-Cas12a and colorimetric analysis.

The CRISPR-Cas system has been found to be extremely sensitive and there is an urgent demand to extend its potential in bioassays. Herein, we developed a novel nanobiosensor to detect the human papillomavirus 16 genes (HPV-16 DNA), which is triggered by CRISPR-Cas12a to amplify the fluorescence signal by metal-enhanced fluorescence (CAMEF). Along with the changing of the fluorescence signal, the aggregation of the substrate of MEF also leads to a change in the color of the mixture solution, enabling dual signal detection with the fluorescence and the naked eye. Furthermore, the designed CAMEF probe was verified to detect the HPV-16 DNA accurately and reliably in biological samples. Triggered by the CRISPR system, the designed CAMEF probe allows quantitative detection of the HPV-16 DNA in the wide range of 10-500 pM. Owing to the MEF, the fluorescence signal of the CAMEF probe was significantly amplified with the detection limit as low as 1 pM. Besides, we can determine the concentration of HPV-16 DNA simply by the naked eye, which also drastically reduces the possibility of false-positive signals. Theoretically, the target ssDNA could be any strand of DNA obtained by designing the crRNA sequence in the CRISPR-Cas system. We believe that the designed CAMEF sensor can present a reliable approach for the accurate detection of low amounts of target ssDNA in complex biological samples.

Analysis of care-seeking and diagnosis delay among pulmonary tuberculosis patients in Beijing, China.

Background: Tuberculosis (TB) remains a significant public health challenge in China. Early detection and diagnosis of TB cases are crucial to interrupt disease transmission and prevent its progression. This study aims to describe the delay in seeking care and diagnosis among patients with pulmonary tuberculosis (PTB) and identify the influencing factors in two counties in Beijing. Methods: A retrospective analysis was carried out to investigate care-seeking and diagnosis delay in two counties in Beijing. Basic information of PTB patients from January 1 to December 31, 2021, was extracted from the Tuberculosis Information Management System of China (TBIMS), and all enrolled patients were interviewed via telephone using a standard questionnaire. Statistical description was performed using the median and interquartile range (IQR). Chi-square test and multivariate logistic regression model were used to analyze the influencing factors. Results: 537 patients were enrolled. The median duration of care-seeking and diagnosis delay was 11 (IQR: 5-26) days and 8 (IQR: 0-18) days, with 41.71 and 35.20% of patients experiencing delays (>14 days). The study found that being asymptomatic (OR = 2.791, 95%CI: 1.710-4.555) before seeking medical care and not attending work during treatment (OR = 2.990, 95%CI: 1.419-6.298) were identified as risk factors for care-seeking delay. Patients who were tracked (OR = 2.632, 95%CI: 1.062-6.521) and diagnosed at tuberculosis control and prevention institutions (OR = 1.843, 95%CI: 1.061-3.202) had higher odds of diagnostic delays. 44.69% of patients presented a total delay (>28 days), with a median duration of 25 (IQR: 13-39) days. A multivariate logistic regression analysis showed that healthy examination (OR = 0.136, 95%CI: 0.043-0.425) was a protective factor for total delay. Conclusion: Public interventions are necessary to improve the efficiency of PTB patients detection and treatment in Beijing. Medical services should focus on the target population and improve access to medical care to further reduce delays for PTB patients.

CSF proteomic profiling with amyloid/tau positivity identifies distinctive sex-different alteration of multiple proteins involved in Alzheimer's disease.

In Alzheimer's disease (AD), the most common cause of dementia, females have higher prevalence and faster progression, but sex-specific molecular findings in AD are limited. Here, we comprehensively examined and validated 7,006 aptamers targeting 6,162 proteins in cerebral spinal fluid (CSF) from 2,077 amyloid/tau positive cases and controls to identify sex-specific proteomic signatures of AD. In discovery (N=1,766), we identified 330 male-specific and 121 female-specific proteomic alternations in CSF (FDR <0.05). These sex-specific proteins strongly predicted amyloid/tau positivity (AUC=0.98 in males; 0.99 in females), significantly higher than those with age, sex, and APOE-ε4 (AUC=0.85). The identified sex-specific proteins were well validated (r≥0.5) in the Stanford study (N=108) and Emory study (N=148). Biological follow-up of these proteins led to sex differences in cell-type specificity, pathways, interaction networks, and drug targets. Male-specific proteins, enriched in astrocytes and oligodendrocytes, were involved in postsynaptic and axon-genesis. The male network exhibited direct connections among 152 proteins and highlighted PTEN, NOTCH1, FYN, and MAPK8 as hubs. Drug target suggested melatonin (used for sleep-wake cycle regulation), nabumetone (used for pain), daunorubicin, and verteporfin for treating AD males. In contrast, female-specific proteins, enriched in neurons, were involved in phosphoserine residue binding including cytokine activities. The female network exhibits strong connections among 51 proteins and highlighted JUN and 14-3-3 proteins (YWHAG and YWHAZ) as hubs. Drug target suggested biperiden (for muscle control of Parkinson's disease), nimodipine (for cerebral vasospasm), quinostatin and ethaverine for treating AD females. Together, our findings provide mechanistic understanding of sex differences for AD risk and insights into clinically translatable interventions.

Study on the differential diagnosis of benign and malignant breast lesions using a deep learning model based on multimodal images.

OBJECTIVE: To establish a multimodal model for distinguishing benign and malignant breast lesions. MATERIALS AND METHODS: Clinical data, mammography, and MRI images (including T2WI, diffusion-weighted images (DWI), apparent diffusion coefficient (ADC), and DCE-MRI images) of 132 benign and breast cancer patients were analyzed retrospectively. The region of interest (ROI) in each image was marked and segmented using MATLAB software. The mammography, T2WI, DWI, ADC, and DCE-MRI models based on the ResNet34 network were trained. Using an integrated learning method, the five models were used as a basic model, and voting methods were used to construct a multimodal model. The dataset was divided into a training set and a prediction set. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the model were calculated. The diagnostic efficacy of each model was analyzed using a receiver operating characteristic curve (ROC) and an area under the curve (AUC). The diagnostic value was determined by the DeLong test with statistically significant differences set at P < 0.05. RESULTS: We evaluated the ability of the model to classify benign and malignant tumors using the test set. The AUC values of the multimodal model, mammography model, T2WI model, DWI model, ADC model and DCE-MRI model were 0.943, 0.645, 0.595, 0.905, 0.900, and 0.865, respectively. The diagnostic ability of the multimodal model was significantly higher compared with that of the mammography and T2WI models. However, compared with the DWI, ADC, and DCE-MRI models, there was no significant difference in the diagnostic ability of these models. CONCLUSION: Our deep learning model based on multimodal image training has practical value for the diagnosis of benign and malignant breast lesions.

An anti-tumor protein PFAP specifically interacts with cholesterol-enriched membrane domains of A549 cells and induces paraptosis and endoplasmic reticulum stress.

Nowadays, non-small cell lung cancer (NSCLC) is still one of the most life-threatening diseases in the world. In previous studies, a fungal protein PFAP with anti-NSCLC properties was isolated and identified from Pleurotus ferulae lanzi. In this study, the amino acid sequence of PFAP was analyzed and found to be highly homologous to the aegerolysin family. PFAP, like other members of the aegerolysin family, specifically recognizes lipid raft domains rich in cholesterol and sphingomyelin, which is probably its specific anti-tumor mechanism. Previous studies have shown that PFAP can induce AMPK-mediated autophagy and G1-phase cell cycle arrest in A549 lung cancer cells. This study further revealed that PFAP can also induce paraptosis and endoplasmic reticulum stress (ERS) in A549 cells in vitro by targeting AMPK. PFAP induces multi-pathway death of A549 cells, and thus demonstrates its potential value for developing new drugs for NSCLC.

Multi-cohort cerebrospinal fluid proteomics identifies robust molecular signatures for asymptomatic and symptomatic Alzheimer's disease.

Changes in Amyloid-ß (A), hyperphosphorylated Tau (T) in brain and cerebrospinal fluid (CSF) precedes AD symptoms, making CSF proteome a potential avenue to understand the pathophysiology and facilitate reliable diagnostics and therapies. Using the AT framework and a three-stage study design (discovery, replication, and meta-analysis), we identified 2,173 proteins dysregulated in AD, that were further validated in a third totally independent cohort. Machine learning was implemented to create and validate highly accurate and replicable (AUC>0.90) models that predict AD biomarker positivity and clinical status. These models can also identify people that will convert to AD and those AD cases with faster progression. The associated proteins cluster in four different protein pseudo-trajectories groups spanning the AD continuum and were enrichment in specific pathways including neuronal death, apoptosis and tau phosphorylation (early stages), microglia dysregulation and endolysosomal dysfuncton(mid-stages), brain plasticity and longevity (mid-stages) and late microglia-neuron crosstalk (late stages).

Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways.

Background: To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies. Methods: We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models. Findings: We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aß42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89). Interpretation: Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs. Funding: Proteomic data generation was supported by NIH: RF1AG044546.

Proteo-genomics of soluble TREM2 in cerebrospinal fluid provides novel insights and identifies novel modulators for Alzheimer's disease.

Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer's disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3,350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16×10-19; rs142232675 p.D87N, P=2.71×10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86×10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we demonstrate that overexpression and knock-down of TGFBR2, but not RBMS3, leads to significant changes of sTREM2. The last novel locus is located on the APOE region (rs11666329, P=2.52×10-8), but we demonstrated that this signal was independent of APOE genotype. This signal colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. Overexpression of NECTIN2 led to an increase of sTREM2 supporting the genetic findings. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.

Severe coagulopathy and inflammation occurred after resection of giant right ventricular intimal sarcoma with cardiopulmonary bypass: a case report.

BACKGROUND: Primary malignant cardiac tumors are rare in clinic, and surgical resection under cardiopulmonary bypass (CPB) remains the main treatment. The non-physiological perfusion process of CPB leads to contact activation, and the resulting coagulopathy and systemic inflammatory response syndrome (SIRS) are common complications. However, it is difficult to predict the impact of foreign tumor fragments on this pathophysiological process once they enter the bloodstream, making this phenomenon more complex and challenging. CASE PRESENTATION: We report a case of cardiac intimal sarcoma who developed severe coagulopathy and widespread inflammation after excision of massive right ventricular tumor and replacement of tricuspid valve by median sternotomy under CPB. Although the procedure was expected to cause tumor cell necrosis and precautions were taken, uncontrolled massive postoperative bleeding, persistent fever, abnormally elevated inflammatory markers, and recurrent malignant arrhythmias occurred after surgery. In addition to common factors, the most possible underlying mechanism is contact activation triggered following surgical procedure for intimal sarcoma with CPB. CONCLUSION: Patients with intracardiac malignant tumors are at a high risk for serious contact activation during CPB. Preventive application of comprehensive anti-inflammatory measures such as drugs and adsorptive CPB technology, as well as point-of-care (POC) monitoring of coagulation status will be helpful for individualized guidance and optimization of CPB management, and improvement of patient prognosis.

Long non-coding RNA small nucleolar RNA host gene 29 drives chronic myeloid leukemia progression via microRNA-483-3p/Casitas B-lineage Lymphoma axis-mediated activation of the phosphoinositide 3-kinase/Akt pathway.

The aberrant expression of the long non-coding RNA (lncRNA) Small Nucleolar RNA Host Gene 29 (SNHG29) has been associated with various human cancers. However, the role of SNHG29 in chronic myeloid leukemia (CML) remains elusive. Therefore, this study aimed to investigate the function of SNHG29 in CML and unveil its potential underlying mechanisms. Herein, peripheral blood samples from 44 CML patients and 17 healthy subjects were collected. The expressions of SNHG29, microRNA-483-3p (miR-483-3p), and Casitas B-lineage Lymphoma (CBL) were measured using quantitative polymerase chain reaction (qPCR) or Western Blot. Cell viability, apoptosis, and cell cycle progression were evaluated using the Cell Counting Kit-8 assay, 5-ethynyl-2'-deoxyuridine incorporation, and flow cytometry, respectively. Western Blot analysis was employed to assess protein expressions related to cellular proliferation, apoptosis, and oncogenesis. RNA immunoprecipitation and dual-luciferase reporter assays were utilized to verify the interactions among SNHG29, miR-483-3p, and CBL. SNHG29 was significantly overexpressed in both blood samples of CML patients and CML cell lines. In CML, increased expression of SNHG29 was positively correlated with clinical staging, and patients with high SNHG29 expression had poorer survival outcomes. Functionally, knocking down SNHG29 effectively inhibited CML cell proliferation and promoted apoptosis. Mechanistically, SNHG29 acted as a competing endogenous RNA for miR-483-3p to modulate CBL expression, thereby activating the Phosphoinositide 3-Kinase/Akt signaling pathway and mediating CML progression. In summary, these findings reveal that SNHG29 promotes tumorigenesis in CML, offering a potential therapeutic strategy for CML treatment.

Organ aging signatures in the plasma proteome track health and disease.

Animal studies show aging varies between individuals as well as between organs within an individual1-4, but whether this is true in humans and its effect on age-related diseases is unknown. We utilized levels of human blood plasma proteins originating from specific organs to measure organ-specific aging differences in living individuals. Using machine learning models, we analysed aging in 11 major organs and estimated organ age reproducibly in five independent cohorts encompassing 5,676 adults across the human lifespan. We discovered nearly 20% of the population show strongly accelerated age in one organ and 1.7% are multi-organ agers. Accelerated organ aging confers 20-50% higher mortality risk, and organ-specific diseases relate to faster aging of those organs. We find individuals with accelerated heart aging have a 250% increased heart failure risk and accelerated brain and vascular aging predict Alzheimer's disease (AD) progression independently from and as strongly as plasma pTau-181 (ref. 5), the current best blood-based biomarker for AD. Our models link vascular calcification, extracellular matrix alterations and synaptic protein shedding to early cognitive decline. We introduce a simple and interpretable method to study organ aging using plasma proteomics data, predicting diseases and aging effects.

Identification of Luminal A breast cancer by using deep learning analysis based on multi-modal images.

Purpose: To evaluate the diagnostic performance of a deep learning model based on multi-modal images in identifying molecular subtype of breast cancer. Materials and methods: A total of 158 breast cancer patients (170 lesions, median age, 50.8 ± 11.0 years), including 78 Luminal A subtype and 92 non-Luminal A subtype lesions, were retrospectively analyzed and divided into a training set (n = 100), test set (n = 45), and validation set (n = 25). Mammography (MG) and magnetic resonance imaging (MRI) images were used. Five single-mode models, i.e., MG, T2-weighted imaging (T2WI), diffusion weighting imaging (DWI), axial apparent dispersion coefficient (ADC), and dynamic contrast-enhanced MRI (DCE-MRI), were selected. The deep learning network ResNet50 was used as the basic feature extraction and classification network to construct the molecular subtype identification model. The receiver operating characteristic curve were used to evaluate the prediction efficiency of each model. Results: The accuracy, sensitivity and specificity of a multi-modal tool for identifying Luminal A subtype were 0.711, 0.889, and 0.593, respectively, and the area under the curve (AUC) was 0.802 (95% CI, 0.657- 0.906); the accuracy, sensitivity, and AUC were higher than those of any single-modal model, but the specificity was slightly lower than that of DCE-MRI model. The AUC value of MG, T2WI, DWI, ADC, and DCE-MRI model was 0.593 (95%CI, 0.436-0.737), 0.700 (95%CI, 0.545-0.827), 0.564 (95%CI, 0.408-0.711), 0.679 (95%CI, 0.523-0.810), and 0.553 (95%CI, 0.398-0.702), respectively. Conclusion: The combination of deep learning and multi-modal imaging is of great significance for diagnosing breast cancer subtypes and selecting personalized treatment plans for doctors.

Protective effect and possible mechanisms of geniposide for ischemia-reperfusion injury: A systematic review with meta-analysis and network pharmacology of preclinical evidence.

Background: Geniposide, as a pharmacologically bioactive component, is derived from a classic and common Chinese herb, Gardenia jasminoides Ellis. Geniposide has been shown to be effective for treating I/R injury in recent studies. Current effectively pharmaceutical treatments are scarce, and treatment based on geniposide may become a novel option. As far as we know, this research is the initial systematic evaluation of the protective effects of geniposide in I/R injury. Aim of the study: This study is engrossed in evaluating the mechanism of action of geniposide in I/R injury through a preclinical systematic review with meta-analysis and network pharmacology. Materials and methods: We built a systematic review which provided a view of effect and mechanism of geniposide for I/R injury. Based on seven databases, an open-ended search from their inception to August 31st, 2022, was conducted. Animal studies on the effects of geniposide in I/R injury were considered. The data was analyzed using Review Manager 5.3, and bias was assessed using the CAMARADES 10-item scale. 13 articles including 279 animals were selected finally. And network pharmacology was joined to elucidate the mechanism. Results: According to the meta-analysis, in I/R injury, geniposide can attenuate cardiomyocytes viability and the size of MI, decrease the volume of cerebral infraction and neurological score, decrease serum ALT and AST activity, and downregulated serum Cr and BUN. The review found that geniposide protects against I/R injury by inhibiting apoptosis, oxidation, inflammation and improvement of autophagy and mitochondrial respiration, which is consistent with the results of the network pharmacology screening. Conclusion: This preclinical systematic review including meta-analysis and network pharmacology, which was the first one summarizing the relationship between geniposide and ischemia diseases, shows a novel therapy for I/R injury and appears an enticing implication of geniposide in I/R injury, and further research is looked forward. Given the restricted quantity of included researches and the unclear risk of bias of the studies, we should interpret the results with caution.

Assessing Abdominal Aortic Aneurysm Progression by Using Perivascular Adipose Tissue Attenuation on Computed Tomography Angiography.

OBJECTIVE: Recent studies have highlighted the active and potential role of perivascular adipose tissue (PVAT) in atherosclerosis and aneurysm progression, respectively. This study explored the link between PVAT attenuation and abdominal aortic aneurysm (AAA) progression using computed tomography angiography (CTA). MATERIALS AND METHODS: This multicenter retrospective study analyzed patients with AAA who underwent CTA at baseline and follow-up between March 2015 and July 2022. The following parameters were obtained: maximum diameter and total volume of the AAA, presence or absence of intraluminal thrombus (ILT), maximum diameter and volume of the ILT, and PVAT attenuation of the aortic aneurysm at baseline CTA. PVAT attenuation was divided into high (> -73.4 Hounsfield units [HU]) and low (≤ -73.4 HU). Patients who had or did not have AAA progression during the follow-up, defined as an increase in the aneurysm volume > 10 mL from baseline, were identified. Kaplan-Meier and multivariable Cox regression analyses were used to investigate the association between PVAT attenuation and AAA progression. RESULTS: Our study included 167 participants (148 males; median age: 70.0 years; interquartile range: 63.0-76.0 years), of which 145 (86.8%) were diagnosed with AAA accompanied by ILT. Over a median period of 11.3 months (range: 6.0-85.0 months), AAA progression was observed in 67 patients (40.1%). Multivariable Cox regression analysis indicated that high baseline PVAT attenuation (adjusted hazard ratio [aHR] = 2.23; 95% confidence interval [CI], 1.16-4.32; P = 0.017) was independently associated with AAA progression. This association was demonstrated within the patients of AAA with ILT subcohort, where a high baseline PVAT attenuation (aHR = 2.23; 95% CI, 1.08-4.60; P = 0.030) was consistently independently associated with AAA progression. CONCLUSION: Elevated PVAT attenuation is independently associated with AAA progression, including patients of AAA with ILT, suggesting the potential of PVAT attenuation as a predictive imaging marker for AAA expansion.

An MRI-based radiomics nomogram for differentiating spinal metastases from multiple myeloma.

BACKGROUND: Spinal metastasis and multiple myeloma share many overlapping conventional radiographic imaging characteristics, thus, their differentiation may be challenging. The purpose of this study was to develop and validate an MRI-based radiomics nomogram for the differentiation of spinal metastasis and multiple myeloma. MATERIALS AND METHODS: A total of 312 patients (training set: n = 146, validation set: n = 65, our center; external test set: n = 101, two other centers) with spinal metastasis (n = 196) and multiple myeloma (n = 116) were retrospectively enrolled. Demographics and MRI findings were assessed to build a clinical factor model. Radiomics features were extracted from MRI images. A radiomics model was constructed by the least absolute shrinkage and selection operator method. A radiomics nomogram combining the radiomics signature and independent clinical factors was constructed. And, one experienced radiologist reviewed the MRI images for all case. The diagnostic performance of the different models was evaluated by receiver operating characteristic curves. RESULTS: A clinical factors model was built based on heterogeneous appearance and shape. Twenty-one features were used to build the radiomics signature. The area under the curve (AUC) values of the radiomics nomogram (0.853 and 0.762, respectively) were significantly higher than that of the clinical factor model (0.692 and 0.540, respectively) in both validation (p = 0.048) and external test (p < 0.001) sets. The AUC values of the radiomics nomogram model were higher than that of radiologist in training, validation and external test sets (all p < 0.05). Moreover, no significant difference in AUC values of radiomics nomogram model was found between the validation set and external test set (p = 0.212). CONCLUSION: The radiomics nomogram can differentiate spinal metastasis and multiple myeloma with a moderate to good performance, and may be as a valuable method to assist in the clinical diagnosis and preoperative decision-making.

Age-related self-DNA accumulation may accelerate arthritis in rats and in human rheumatoid arthritis.

The incidence of rheumatoid arthritis (RA) is increasing with age. DNA fragments is known to accumulate in certain autoimmune diseases, but the mechanistic relationship among ageing, DNA fragments and RA pathogenesis remain unexplored. Here we show that the accumulation of DNA fragments, increasing with age and regulated by the exonuclease TREX1, promotes abnormal activation of the immune system in an adjuvant-induced arthritis (AIA) rat model. Local overexpression of TREX1 suppresses synovial inflammation in rats, while conditional genomic deletion of TREX1 in AIA rats result in higher levels of circulating free (cf) DNA and hence abnormal immune activation, leading to more severe symptoms. The dysregulation of the heterodimeric transcription factor AP-1, formed by c-Jun and c-Fos, appear to regulate both TREX1 expression and SASP induction. Thus, our results confirm that DNA fragments are inflammatory mediators, and TREX1, downstream of AP-1, may serve as regulator of cellular immunity in health and in RA.

Linking genome structures to functions by simultaneous single-cell Hi-C and RNA-seq.

Much progress has been made recently in single-cell chromosome conformation capture technologies. However, a method that allows simultaneous profiling of chromatin architecture and gene expression has not been reported. Here, we developed an assay named "Hi-C and RNA-seq employed simultaneously" (HiRES) and performed it on thousands of single cells from developing mouse embryos. Single-cell three-dimensional genome structures, despite being heavily determined by the cell cycle and developmental stages, gradually diverged in a cell type-specific manner as development progressed. By comparing the pseudotemporal dynamics of chromatin interactions with gene expression, we found a widespread chromatin rewiring that occurred before transcription activation. Our results demonstrate that the establishment of specific chromatin interactions is tightly related to transcriptional control and cell functions during lineage specification.

New fungal protein from Pleurotus ferulae lanzi induces AMPK-mediated autophagy and G1-phase cell cycle arrest in A549 lung cancer cells.

A new protein, designated PFAP, with activity against non-small cell lung cancer (NSCLC), was isolated from Pleurotus ferulae lanzi, a medicinal and edible mushroom. The purification method involved hydrophobic interaction chromatography on a HiTrap Octyl FF column and gel filtration on a Superdex 75 column. Sodium dodecyl-sulfate polyacrylamide gel electrophoresis (SDS-PAGE) revealed a single band with a molecular weight of 14.68 kDa. Following de novo sequencing and liquid chromatography-tandem mass spectrometry, PFAP was identified as a protein consisting of 135 amino acid residues, with a theoretical molecular weight of 14.81 kDa. Tandem mass tag (TMT)™-based quantitative proteomic analysis and western blotting revealed that AMP-activated protein kinase (AMPK) was significantly upregulated in NSCLC A549 cells, following PFAP treatment. The downstream regulatory factor mammalian target of rapamycin (mTOR) was suppressed, resulting in the activation of autophagy and upregulated expressions of P62, LC3 II/I, and other related proteins. PFAP blocked NSCLC A549 cells in the G1 phase of the cell cycle via upregulating P53 and P21, while subsequently downregulating the expression of cyclin-dependent kinases. PFAP suppresses tumour growth via the same mechanism in a xenograft mouse model in vivo. These results demonstrate that PFAP is a multifunctional protein with anti-NSCLC properties.