Improved Re-Parameterized Convolution for Wildlife Detection in Neighboring Regions of Southwest China.

To autonomously detect wildlife images captured by camera traps on a platform with limited resources and address challenges such as filtering out photos without optimal objects, as well as classifying and localizing species in photos with objects, we introduce a specialized wildlife object detector tailored for camera traps. This detector is developed using a dataset acquired by the Saola Working Group (SWG) through camera traps deployed in Vietnam and Laos. Utilizing the YOLOv6-N object detection algorithm as its foundation, the detector is enhanced by a tailored optimizer for improved model performance. We deliberately introduce asymmetric convolutional branches to enhance the feature characterization capability of the Backbone network. Additionally, we streamline the Neck and use CIoU loss to improve detection performance. For quantitative deployment, we refine the RepOptimizer to train a pure VGG-style network. Experimental results demonstrate that our proposed method empowers the model to achieve an 88.3% detection accuracy on the wildlife dataset in this paper. This accuracy is 3.1% higher than YOLOv6-N, and surpasses YOLOv7-T and YOLOv8-N by 5.5% and 2.8%, respectively. The model consistently maintains its detection performance even after quantization to the INT8 precision, achieving an inference speed of only 6.15 ms for a single image on the NVIDIA Jetson Xavier NX device. The improvements we introduce excel in tasks related to wildlife image recognition and object localization captured by camera traps, providing practical solutions to enhance wildlife monitoring and facilitate efficient data acquisition. Our current work represents a significant stride toward a fully automated animal observation system in real-time in-field applications.

Local heating and Raman thermometry in a single molecule.

Because of the nonequilibrium nature of thermal effects at the nanoscale, the characterization of local thermal effects within a single molecule is highly challenging. Here, we demonstrate a way to characterize the local thermal properties of a single fullerene (C60) molecule during current-induced heating processes through tip-enhanced anti-Stokes Raman spectroscopy. Although the measured vibron populations are far from equilibrium with the environment, we can still define an "effective temperature (Teff)" statistically via a Bose-Einstein distribution, suggesting a local equilibrium within the molecule. With increased current heating, Teff is found to rise up to about 1150 K until the C60 cage is decomposed. Such a decomposition temperature is similar to that reported for ensemble C60 samples, thus justifying the validity of our methodology. Moreover, the possible reaction pathway and product can be identified because of the chemical sensitivity of Raman spectroscopy. Our findings provide a practical method for noninvasively detecting the local heating effect inside a single molecule under nonequilibrium conditions.

Effect of Mechanical Ventilation Mode Type on Postoperative Pulmonary Complications After Cardiac Surgery: A Randomized Controlled Trial.

OBJECTIVES: It is unknown whether there is a difference in pulmonary outcome in different intraoperative ventilation modes for cardiac surgery with cardiopulmonary bypass (CPB). The aim of this trial was to determine whether patients undergoing cardiac surgery with CPB could benefit from intraoperative optimal ventilation mode. DESIGN: This was a single-center, prospective, randomized controlled trial. SETTING: The study was conducted at a single-center tertiary-care hospital. PARTICIPANTS: A total of 1,364 adults undergoing cardiac surgery with CPB participated in this trial. INTERVENTIONS: Patients were assigned randomly (1:1:1) to receive 1 of 3 ventilation modes: volume-controlled ventilation (VCV), pressure-controlled ventilation (PCV), and pressure-controlled ventilation-volume guaranteed (PCV-VG). All arms of the study received the lung-protective ventilation strategy. MEASUREMENTS AND MAIN RESULTS: The primary outcome was a composite of postoperative pulmonary complications (PPCs) within the first 7 postoperative days. Pulmonary complications occurred in 168 of 455 patients (36.9%) in the PCV-VG group, 171 (37.6%) in the PCV group, and 182 (40.1%) in the VCV group, respectively. There was no statistical difference in the risk of overall pulmonary complications among groups (p = 0.585). There were no significant differences in the severity grade of PPCs within 7 days, postoperative ventilation duration, intensive care unit stay, postoperative hospital stay, or 30-day postoperative mortality. CONCLUSIONS: Among patients scheduled for cardiac surgery with CPB, intraoperative ventilation mode type did not affect the risk of postoperative pulmonary complications.

Pan-mediastinal neoplasm diagnosis via nationwide federated learning: a multicentre cohort study.

BACKGROUND: Mediastinal neoplasms are typical thoracic diseases with increasing incidence in the general global population and can lead to poor prognosis. In clinical practice, the mediastinum's complex anatomic structures and intertype confusion among different mediastinal neoplasm pathologies severely hinder accurate diagnosis. To solve these difficulties, we organised a multicentre national collaboration on the basis of privacy-secured federated learning and developed CAIMEN, an efficient chest CT-based artificial intelligence (AI) mediastinal neoplasm diagnosis system. METHODS: In this multicentre cohort study, 7825 mediastinal neoplasm cases and 796 normal controls were collected from 24 centres in China to develop CAIMEN. We further enhanced CAIMEN with several novel algorithms in a multiview, knowledge-transferred, multilevel decision-making pattern. CAIMEN was tested by internal (929 cases at 15 centres), external (1216 cases at five centres and a real-world cohort of 11 162 cases), and human-AI (60 positive cases from four centres and radiologists from 15 institutions) test sets to evaluate its detection, segmentation, and classification performance. FINDINGS: In the external test experiments, the area under the receiver operating characteristic curve for detecting mediastinal neoplasms of CAIMEN was 0·973 (95% CI 0·969-0·977). In the real-world cohort, CAIMEN detected 13 false-negative cases confirmed by radiologists. The dice score for segmenting mediastinal neoplasms of CAIMEN was 0·765 (0·738-0·792). The mediastinal neoplasm classification top-1 and top-3 accuracy of CAIMEN were 0·523 (0·497-0·554) and 0·799 (0·778-0·822), respectively. In the human-AI test experiments, CAIMEN outperformed clinicians with top-1 and top-3 accuracy of 0·500 (0·383-0·633) and 0·800 (0·700-0·900), respectively. Meanwhile, with assistance from the computer aided diagnosis software based on CAIMEN, the 46 clinicians improved their average top-1 accuracy by 19·1% (0·345-0·411) and top-3 accuracy by 13·0% (0·545-0·616). INTERPRETATION: For mediastinal neoplasms, CAIMEN can produce high diagnostic accuracy and assist the diagnosis of human experts, showing its potential for clinical practice. FUNDING: National Key R&D Program of China, National Natural Science Foundation of China, and Beijing Natural Science Foundation.

[Relationship between atherogenic index of plasma and childhood asthma]. / è¡€æµ†è‡´åŠ¨è„‰ç¡¬åŒ–æŒ‡æ•°ä¸Žå„¿ç«¥æ”¯æ°”ç®¡å“®å–˜çš„ç›¸å ³æ€§åˆ†æž.

OBJECTIVES: To explore the relationship between atherogenic index of plasma (AIP) and childhood asthma. METHODS: This retrospective study included 86 children with asthma admitted to the Changzhou Second People's Hospital Affiliated to Nanjing Medical University from July 2020 to August 2022 as the asthma group and 149 healthy children undergoing physical examination during the same period as the control group. Metabolic parameters including total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and blood glucose, as well as general information of the children such as height, weight, body mass index, presence of specific dermatitis, history of inhalant allergen hypersensitivity, family history of asthma, and feeding history, were collected. Multivariable logistic regression analysis was used to study the relationship between AIP, triglycerides, and high-density lipoprotein cholesterol and asthma. The value of AIP, triglycerides, and high-density lipoprotein cholesterol for predicting asthma was assessed using receiver operating characteristic (ROC) curve analysis. RESULTS: The AIP and triglyceride levels in the asthma group were significantly higher than those in the control group, while high-density lipoprotein cholesterol was significantly lower (P<0.05). However, there was no significant difference in total cholesterol and low-density lipoprotein cholesterol between the two groups (P>0.05). Before and after adjusting for height, weight, presence of specific dermatitis, history of inhalant allergen hypersensitivity, family history of asthma, feeding method, and blood glucose, multivariable logistic regression analysis showed that AIP, triglycerides, and high-density lipoprotein cholesterol were associated with asthma (P<0.05). ROC curve analysis showed that the optimal cutoff value for predicting asthma with AIP was -0.333, with a sensitivity of 80.2%, specificity of 55.0%, positive predictive value of 50.71%, and negative predictive value of 82.85%. The area under the curve (AUC) for AIP in predicting asthma was significantly higher than that for triglycerides (P=0.009), but there was no significant difference in AUC between AIP and high-density lipoprotein cholesterol (P=0.686). CONCLUSIONS: AIP, triglycerides, and high-density lipoprotein cholesterol are all associated with asthma. AIP has a higher value for predicting asthma than triglycerides and comparable value to high-density lipoprotein cholesterol.

Alzheimer risk-increasing TREM2 variant causes aberrant cortical synapse density and promotes network hyperexcitability in mouse models.

The R47H variant of triggering receptor expressed on myeloid cells 2 (TREM2) increases the risk of Alzheimer's disease (AD). To investigate potential mechanisms, we analyzed knockin mice expressing human TREM2-R47H from one mutant mouse Trem2 allele. TREM2-R47H mice showed increased seizure activity in response to an acute excitotoxin challenge, compared to wildtype controls or knockin mice expressing the common variant of human TREM2. TREM2-R47H also increased spontaneous thalamocortical epileptiform activity in App knockin mice expressing amyloid precursor proteins bearing autosomal dominant AD mutations and a humanized amyloid-ß sequence. In mice with or without such App modifications, TREM2-R47H increased the density of putative synapses in cortical regions without amyloid plaques. TREM2-R47H did not affect synaptic density in hippocampal regions with or without plaques. We conclude that TREM2-R47H increases AD-related network hyperexcitability and that it may do so, at least in part, by causing an imbalance in synaptic densities across brain regions.

The effect of driving pressure-guided versus conventional mechanical ventilation strategy on pulmonary complications following on-pump cardiac surgery: A randomized clinical trial.

STUDY OBJECTIVE: Postoperative pulmonary complications occur frequently and are associated with worse postoperative outcomes in cardiac surgical patients. The advantage of driving pressure-guided ventilation strategy in decreasing pulmonary complications remains to be definitively established. We aimed to investigate the effect of intraoperative driving pressure-guided ventilation strategy compared with conventional lung-protective ventilation on pulmonary complications following on-pump cardiac surgery. DESIGN: Prospective, two-arm, randomized controlled trial. SETTING: The West China university hospital in Sichuan, China. PATIENTS: Adult patients who were scheduled for elective on-pump cardiac surgery were enrolled in the study. INTERVENTIONS: Patients undergoing on-pump cardiac surgery were randomized to receive driving pressure-guided ventilation strategy based on positive end-expiratory pressure (PEEP) titration or conventional lung-protective ventilation strategy with fixed 5 cmH2O of PEEP. MEASUREMENTS: The primary outcome of pulmonary complications (including acute respiratory distress syndrome, atelectasis, pneumonia, pleural effusion, and pneumothorax) within the first 7 postoperative days were prospectively identified. Secondary outcomes included pulmonary complication severity, ICU length of stay, and in-hospital and 30-day mortality. MAIN RESULTS: Between August 2020 and July 2021, we enrolled 694 eligible patients who were included in the final analysis. Postoperative pulmonary complications occurred in 140 (40.3%) patients in the driving pressure group and 142 (40.9%) in the conventional group (relative risk, 0.99; 95% confidence interval, 0.82-1.18; P = 0.877). Intention-to-treat analysis showed no significant difference between study groups regarding the incidence of primary outcome. The driving pressure group had less atelectasis than the conventional group (11.5% vs 17.0%; relative risk, 0.68; 95% confidence interval, 0.47-0.98; P = 0.039). Secondary outcomes did not differ between groups. CONCLUSION: Among patients who underwent on-pump cardiac surgery, the use of driving pressure-guided ventilation strategy did not reduce the risk of postoperative pulmonary complications when compared with conventional lung-protective ventilation strategy.

A lightweight network for improving wheat ears detection and counting based on YOLOv5s.

Introduction: Recognizing wheat ears plays a crucial role in predicting wheat yield. Employing deep learning methods for wheat ears identification is the mainstream method in current research and applications. However, such methods still face challenges, such as high computational parameter volume, large model weights, and slow processing speeds, making it difficult to apply them for real-time identification tasks on limited hardware resources in the wheat field. Therefore, exploring lightweight wheat ears detection methods for real-time recognition holds significant importance. Methods: This study proposes a lightweight method for detecting and counting wheat ears based on YOLOv5s. It utilizes the ShuffleNetV2 lightweight convolutional neural network to optimize the YOLOv5s model by reducing the number of parameters and simplifying the complexity of the calculation processes. In addition, a lightweight upsampling operator content-aware reassembly of features is introduced in the feature pyramid structure to eliminate the impact of the lightweight process on the model detection performance. This approach aims to improve the spatial resolution of the feature images, enhance the effectiveness of the perceptual field, and reduce information loss. Finally, by introducing the dynamic target detection head, the shape of the detection head and the feature extraction strategy can be dynamically adjusted, and the detection accuracy can be improved when encountering wheat ears with large-scale changes, diverse shapes, or significant orientation variations. Results and discussion: This study uses the global wheat head detection dataset and incorporates the local experimental dataset to improve the robustness and generalization of the proposed model. The weight, FLOPs and mAP of this model are 2.9 MB, 2.5 * 109 and 94.8%, respectively. The linear fitting determination coefficients R2 for the model test result and actual value of global wheat head detection dataset and local experimental Site are 0.94 and 0.97, respectively. The improved lightweight model can better meet the requirements of precision wheat ears counting and play an important role in embedded systems, mobile devices, or other hardware systems with limited computing resources.

Patient-controlled intravenous analgesia with opioids after thoracoscopic lung surgery: a randomized clinical trial.

BACKGROUND: Opioids remain the mainstream therapy for post-surgical pain. The choice of opioids administered by patient-controlled intravenous analgesia (PCIA) for thoracoscopic lung surgery is unclear. This study compared 3 opioid analgesics for achieving satisfactory analgesia with minimal emesis (SAME). METHODS: This randomized clinical trial enrolled patients scheduled for thoracoscopic lung surgery randomized to receive 1 of 3 opioids for PCIA: oxycodone (group O), hydromorphone (group H), and sufentanil (group S). The primary outcome was the proportion of subjects achieving SAME, i.e., no-to-mild pain (pain score < 4/10) with minimal nausea/vomiting (PONV score < 2/4) when coughing during the pulmonary rehabilitation exercise in the first 3 postoperative days. RESULTS: Of 555 enrolled patients, 184 patients in group O, 186 in group H and 184 in group S were included in the final analysis. The primary outcome of SAME was significantly different among group O, H and S (41.3% vs 40.3% vs 29.9%, P = 0.043), but no difference was observed between pairwise group comparisons. Patients in groups O and H had lower pain scores when coughing on the second day after surgery than those in group S, both with mean differences of 1 (3(3,4) and 3(3,4) vs 4(3,4), P = 0.009 and 0.039, respectively). The PONV scores were comparable between three groups (P > 0.05). There were no differences in other opioid-related side effects, patient satisfaction score, and QoR-15 score among three groups. CONCLUSIONS: Given clinically relevant benefits detected, PCIA with oxycodone or hydromorphone is superior to sufentanil for achieving SAME as a supplement to multimodal analgesia in patients undergoing thoracoscopic lung surgery. TRIAL REGISTRATION: This study was registered at ( ChiCTR2100045614 , 19/04/2021).

Machine Learning Screens Potential Drugs Targeting a Prognostic Gene Signature Associated With Proliferation in Hepatocellular Carcinoma.

Background: This study aimed to screen potential drugs targeting a new prognostic gene signature associated with proliferation in hepatocellular carcinoma (HCC). Methods: CRISPR Library and TCGA datasets were used to explore differentially expressed genes (DEGs) related to the proliferation of HCC cells. Differential gene expression analysis, univariate COX regression analysis, random forest algorithm and multiple combinatorial screening were used to construct a prognostic gene signature. Then the predictive power of the gene signature was validated in the TCGA and ICGC datasets. Furthermore, potential drugs targeting this gene signature were screened. Results: A total of 640 DEGs related to HCC proliferation were identified. Using univariate Cox analysis and random forest algorithm, 10 hub genes were screened. Subsequently, using multiplex combinatorial screening, five hub genes (FARSB, NOP58, CCT4, DHX37 and YARS) were identified. Taking the median risk score as a cutoff value, HCC patients were divided into high- and low-risk groups. Kaplan-Meier analysis performed in the training set showed that the overall survival of the high-risk group was worse than that of the low-risk group (p < 0.001). The ROC curve showed a good predictive efficiency of the risk score (AUC > 0.699). The risk score was related to gene mutation, cancer cell stemness and immune function changes. Prediction of immunotherapy suggetsted the IC50s of immune checkpoint inhibitors including A-443654, ABT-888, AG-014699, ATRA, AUY-922, and AZ-628 in the high-risk group were lower than those in the low-risk group, while the IC50s of AMG-706, A-770041, AICAR, AKT inhibitor VIII, Axitinib, and AZD-0530 in the high-risk group were higher than those in the low-risk group. Drug sensitivity analysis indicated that FARSB was positively correlated with Hydroxyurea, Vorinostat, Nelarabine, and Lomustine, while negatively correlated with JNJ-42756493. DHX37 was positively correlated with Raltitrexed, Cytarabine, Cisplatin, Tiotepa, and Triethylene Melamine. YARS was positively correlated with Axitinib, Fluphenazine and Megestrol acetate. NOP58 was positively correlated with Vorinostat and 6-thioguanine. CCT4 was positively correlated with Nerabine. Conclusion: The five-gene signature associated with proliferation can be used for survival prediction and risk stratification for HCC patients. Potential drugs targeting this gene signature deserve further attention in the treatment of HCC.

A cost-effective alkaline polysulfide-air redox flow battery enabled by a dual-membrane cell architecture.

With the rapid development of renewable energy harvesting technologies, there is a significant demand for long-duration energy storage technologies that can be deployed at grid scale. In this regard, polysulfide-air redox flow batteries demonstrated great potential. However, the crossover of polysulfide is one significant challenge. Here, we report a stable and cost-effective alkaline-based hybrid polysulfide-air redox flow battery where a dual-membrane-structured flow cell design mitigates the sulfur crossover issue. Moreover, combining manganese/carbon catalysed air electrodes with sulfidised Ni foam polysulfide electrodes, the redox flow battery achieves a maximum power density of 5.8 mW cm-2 at 50% state of charge and 55 °C. An average round-trip energy efficiency of 40% is also achieved over 80 cycles at 1 mA cm-2. Based on the performance reported, techno-economic analyses suggested that energy and power costs of about 2.5 US$/kWh and 1600 US$/kW, respectively, has be achieved for this type of alkaline polysulfide-air redox flow battery, with significant scope for further reduction.

[Clinical Study of Artificial Intelligence-assisted Diagnosis System in Predicting the 
Invasive Subtypes of Early-stage Lung Adenocarcinoma Appearing as Pulmonary Nodules].

BACKGROUND: Lung cancer is the cancer with the highest mortality at home and abroad at present. The detection of lung nodules is a key step to reducing the mortality of lung cancer. Artificial intelligence-assisted diagnosis system presents as the state of the art in the area of nodule detection, differentiation between benign and malignant and diagnosis of invasive subtypes, however, a validation with clinical data is necessary for further application. Therefore, the aim of this study is to evaluate the effectiveness of artificial intelligence-assisted diagnosis system in predicting the invasive subtypes of early­stage lung adenocarcinoma appearing as pulmonary nodules. METHODS: Clinical data of 223 patients with early-stage lung adenocarcinoma appearing as pulmonary nodules admitted to the Lanzhou University Second Hospital from January 1st, 2016 to December 31th, 2021 were retrospectively analyzed, which were divided into invasive adenocarcinoma group (n=170) and non-invasive adenocarcinoma group (n=53), and the non-invasive adenocarcinoma group was subdivided into minimally invasive adenocarcinoma group (n=31) and preinvasive lesions group (n=22). The malignant probability and imaging characteristics of each group were compared to analyze their predictive ability for the invasive subtypes of early-stage lung adenocarcinoma. The concordance between qualitative diagnostic results of artificial intelligence-assisted diagnosis of the invasive subtypes of early-stage lung adenocarcinoma and postoperative pathology was then analyzed. RESULTS: In different invasive subtypes of early-stage lung adenocarcinoma, the mean CT value of pulmonary nodules (P<0.001), diameter (P<0.001), volume (P<0.001), malignant probability (P<0.001), pleural retraction sign (P<0.001), lobulation (P<0.001), spiculation (P<0.001) were significantly different. At the same time, it was also found that with the increased invasiveness of different invasive subtypes of early-stage lung adenocarcinoma, the proportion of dominant signs of each group gradually increased. On the issue of binary classification, the sensitivity, specificity, and area under the curve (AUC) values of the artificial intelligence-assisted diagnosis system for the qualitative diagnosis of invasive subtypes of early-stage lung adenocarcinoma were 81.76%, 92.45% and 0.871 respectively. On the issue of three classification, the accuracy, recall rate, F1 score, and AUC values of the artificial intelligence-assisted diagnosis system for the qualitative diagnosis of invasive subtypes of early-stage lung adenocarcinoma were 83.86%, 85.03%, 76.46% and 0.879 respectively. CONCLUSIONS: Artificial intelligence-assisted diagnosis system could predict the invasive subtypes of early­stage lung adenocarcinoma appearing as pulmonary nodules, and has a certain predictive value. With the optimization of algorithms and the improvement of data, it may provide guidance for individualized treatment of patients.

Interdependence of neural network dysfunction and microglial alterations in Alzheimer's disease-related models.

Nonconvulsive epileptiform activity and microglial alterations have been detected in people with Alzheimer's disease (AD) and related mouse models. However, the relationship between these abnormalities remains to be elucidated. We suppressed epileptiform activity by treatment with the antiepileptic drug levetiracetam or by genetic ablation of tau and found that these interventions reversed or prevented aberrant microglial gene expression in brain tissues of aged human amyloid precursor protein transgenic mice, which simulate several key aspects of AD. The most robustly modulated genes included multiple factors previously implicated in AD pathogenesis, including TREM2, the hypofunction of which increases disease risk. Genetic reduction of TREM2 exacerbated epileptiform activity after mice were injected with kainate. We conclude that AD-related epileptiform activity markedly changes the molecular profile of microglia, inducing both maladaptive and adaptive alterations in their activities. Increased expression of TREM2 seems to support microglial activities that counteract this type of network dysfunction.

A Secreted Reporter for Blood Monitoring of Pyroptotic Cell Death.

Pyroptotic cell death is a phenomenon that runs through all life activities and plays an important role in physiological and pathological processes of the body's metabolism. It is of big biological significance to understand the phenomenon and nature of cell pyroptosis. In the process of cell pyroptosis, the pore-forming effector gasdermin D (GSDMD) is cleaved to form oligomers, which are inserted into the cell membrane, causing rapid cell death. However, the effective cell death induced by GSDMD complicates our ability to understand the behavior of pyroptosis. In this work, we performed molecular mutagenesis to develop a genetically encoded pyroptotic reporter, where a secreted Gaussia luciferase (Gluc) was strategically placed in the p30-p20 tolerated junction of GSDMD to support natural pyrophosphorylation and promote live imaging of cell pyroptosis. In addition, we demonstrated that this fused Gluc-GSDMD reporter executed inflammatory body-dependent pyroptosis in response to extracellular stimuli, and that the lysed p30-GSDMD can be secreted out of the cell and can be detected in the culture medium and animal blood. Therefore, our study provides a valuable tool that not only noninvasive and real-time monitoring of cell pyroptosis, but also affords a high-throughput functional screening of pyroptosis-targeted compounds in cultured cells and animal models.

DUS4L Silencing Suppresses Cell Proliferation and Promotes Apoptosis in Human Lung Adenocarcinoma Cell Line A549.

PURPOSE: This study aims to investigate the potential role of DUS4L (dihydrouridine synthase 4 like) in lung adenocarcinoma (LUAD) and explore its associated pathways in human LUAD. METHODS: Firstly, we evaluated the relationships between clinicopathological characteristics and DUS4L expression via analysis of TCGA RNA sequencing data and other publicly available databases. Then, DUS4L was effectively silenced in LUAD cell line A549 using the lentiviral shRNA (short-hairpin RNA) transfection to assess its effects on cell proliferation, cycle and apoptosis in LUAD cells. RNA-seq technology was applied to shDUS4L and shCtrl-transfected cells to generate the corresponding gene expression profiles. Differentially expressed genes (DEGs) were identified using the DESeq2 program package. Also, DEGs were subjected to Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis to explore the associated molecular signaling pathways and relevant biological functions. RESULTS: Analysis of TCGA data revealed that DUS4L was highly upregulated in LUAD tissues which was related to clinical T and TNM stages of LUAD. The knockdown of DUS4L effectively inhibited cell proliferation and promoted apoptosis in A549 cells. Furthermore, the DEGs between the shDUS4L and shCtrl A549 cells were mainly enriched in biological processes associated with spliceosome, ribosome, RNA catabolic process, ncRNA (non-coding RNA) processing, and p53 signaling pathway. CONCLUSION: Altogether, our results suggest that DUS4L is significantly associated with tumorigenesis and could be utilized as a novel biomarker and therapeutic target for LUAD.

A Functionalized Polydopamine Theranostic Nanoprobe for Efficient Imaging of miRNA-21 and In Vivo Synergetic Cancer Therapy.

MicroRNAs (miRNAs) are emerging as vital biomarkers since their abnormal expression is associated with various disease types including cancer. Therefore, it is essential to develop a sensitive and specific platform to monitor the dynamic expression of miRNAs for early clinical diagnosis and treatment. In this study, we designed a functionalized polydopamine (PDA)-based theranostic nanoprobe for efficient detection of miRNA-21 and in vivo synergistic cancer therapy. PDA was modified with polyethylene glycol (PEG) and the obtained PDA-PEG nanoparticles showed good stability in different solutions. PDA-PEG nanoparticles were loaded with fluorescein isothiocyanate (FITC)-labeled hairpin DNA (hpDNA) and an anticancer drug doxorubicin (DOX). In the absence of miRNA-21, PDA effectively quenched the fluorescence of FITC-labeled hpDNA. The presence of miRNA-21 specifically recognized hpDNA and induced the dissociation of hpDNA from PDA-PEG and subsequently recovered the fluorescence signals. Upon cellular uptake of these nanoprobes, a dose-dependent fluorescence activation and synergetic cytotoxic effect were observed due to the release of DOX and inhibition of miRNA-21 function. Furthermore, PDA-PEG-DOX-hpDNA nanoparticles can afford long-term monitoring of miRNA-21 and combined therapeutic efficacy in the nude mice bearing 4T1 tumors. Our results demonstrate the capability of PDA-PEG-DOX-hpDNA as a theranostic nanoprobe for continuously tracking of miRNAs and synergetic cancer therapy.

Rational Design of an Activatable Reporter for Quantitative Imaging of RNA Aberrant Splicing In Vivo.

Pre-mRNA splicing, the process of removing introns from pre-mRNA and the arrangement of exons to produce mature transcripts, is a crucial step in the expression of most eukaryote genes. However, the splicing kinetics remain poorly characterized in living cells, mainly because current methods cannot provide the dynamic information of splicing events. Here, we developed a genetically encoded bioluminescence reporter for real-time imaging of the pre-mRNA splicing process in living subjects. We showed that the bioluminescence reporter is able to visualize the pre-mRNA aberrant splicing process in living cells in a dose- and time-dependent manner. Moreover, this reporter could provide quantitative and longitudinal information of splicing activity in response to exogenous splicing inhibitors in living animals. Our data suggest that this activatable reporter could serve as a promising tool for the high-throughput screening of splicing modulators, which would facilitate the drug development for human diseases caused by the abnormal splicing of mRNA.

A novel CpG-based signature for survival prediction of lung adenocarcinoma patients.

Lung adenocarcinoma (LACA) is the leading cause of cancer-associated death worldwide. The present study intended to identify DNA methylation patterns that may serve as diagnostic and prognostic biomarkers for LACA. Data on DNA methylation and the survival data of the patients of LACA were obtained from The Cancer Genome Atlas. Kaplan-Meier curves and receiver operating characteristic curve analysis were utilized to build diagnostic and prognostic models. A total of 13 CpG sites were identified and validated as the optimal diagnostic and prognostic signature for overall survival. It was concluded that the CpG-based signature is a reliable predictor for the diagnosis and prognosis of patients with LACA.