Biomarker Discovery for Early Diagnosis of Papillary Thyroid Carcinoma Using High-Throughput Enhanced Quantitative Plasma Proteomics.

The incidence of thyroid cancer (TC) has been increasing over the last 50 years worldwide. A higher rate of overdiagnosis in indolent thyroid lesions has resulted in unnecessary treatment. An accurate detection of TC at an early stage is highly demanded. We aim to develop an enhanced isobaric labeling-based high-throughput plasma quantitative proteomics to identify biomarkers in a discovery cohort. Selected candidates were tested by enzyme-linked immunosorbent assay (ELISA) in the training cohort and validation cohort. In total, 1063 proteins were quantified, and 129 proteins were differentially expressed between patients and healthy subjects. Serum levels of ISG15 and PLXNB2 were significantly elevated in patients with papillary thyroid cancer (PTC) or thyroid adenoma, compared to healthy subjects (p < 0.001) and patients with nodular goiter (p < 0.001). Receiver operating characteristic (ROC) analysis of combined markers (ISG15 and PLXNB2) significantly distinguished PTC from healthy control (HC) subjects. Similar differentiations were also found between thyroid adenoma and HC subjects. Notably, this combined marker could distinguish stage-I PTC from HC subjects (area under the curve (AUC) = 0.872). Our results revealed that ISG15 and PLXNB2 are independent diagnostic biomarkers for PTC and thyroid adenoma, showing a promising value for the early detection of PTC.

A conserved intronic U1 snRNP-binding sequence promotes trans-splicing in Drosophila.

Unlike typical cis-splicing, trans-splicing joins exons from two separate transcripts to produce chimeric mRNA and has been detected in most eukaryotes. Trans-splicing in trypanosomes and nematodes has been characterized as a spliced leader RNA-facilitated reaction; in contrast, its mechanism in higher eukaryotes remains unclear. Here we investigate mod(mdg4), a classic trans-spliced gene in Drosophila, and report that two critical RNA sequences in the middle of the last 5' intron, TSA and TSB, promote trans-splicing of mod(mdg4). In TSA, a 13-nucleotide (nt) core motif is conserved across Drosophila species and is essential and sufficient for trans-splicing, which binds U1 small nuclear RNP (snRNP) through strong base-pairing with U1 snRNA. In TSB, a conserved secondary structure acts as an enhancer. Deletions of TSA and TSB using the CRISPR/Cas9 system result in developmental defects in flies. Although it is not clear how the 5' intron finds the 3' introns, compensatory changes in U1 snRNA rescue trans-splicing of TSA mutants, demonstrating that U1 recruitment is critical to promote trans-splicing in vivo. Furthermore, TSA core-like motifs are found in many other trans-spliced Drosophila genes, including lola. These findings represent a novel mechanism of trans-splicing, in which RNA motifs in the 5' intron are sufficient to bring separate transcripts into close proximity to promote trans-splicing.

Deep Reinforcement Learning for Indoor Mobile Robot Path Planning.

This paper proposes a novel incremental training mode to address the problem of Deep Reinforcement Learning (DRL) based path planning for a mobile robot. Firstly, we evaluate the related graphic search algorithms and Reinforcement Learning (RL) algorithms in a lightweight 2D environment. Then, we design the algorithm based on DRL, including observation states, reward function, network structure as well as parameters optimization, in a 2D environment to circumvent the time-consuming works for a 3D environment. We transfer the designed algorithm to a simple 3D environment for retraining to obtain the converged network parameters, including the weights and biases of deep neural network (DNN), etc. Using these parameters as initial values, we continue to train the model in a complex 3D environment. To improve the generalization of the model in different scenes, we propose to combine the DRL algorithm Twin Delayed Deep Deterministic policy gradients (TD3) with the traditional global path planning algorithm Probabilistic Roadmap (PRM) as a novel path planner (PRM+TD3). Experimental results show that the incremental training mode can notably improve the development efficiency. Moreover, the PRM+TD3 path planner can effectively improve the generalization of the model.

Disinfection and removal performance for Escherichia coli, toxic heavy metals and arsenic by wood vinegar-modified zeolite.

Zeolite has traditionally been used to remediate wastewater and soil. The present study shows a new method for natural zeolite (NZ) modification with wood vinegar (WV). The optimal conditions for NZ modification with WV were determined, and the adsorption capacities towards lead (Pb), cadmium (Cd) and arsenic (As), antimicrobial activities against Escherichia coli, heavy metal(loid) fraction and characterizations of selected modified zeolites (MZs) were also investigated. The results indicate that 50-fold dilution of WV, 5 g of NZ dosage, 105 °C of drying temperature, 4 h and 95 °C of water bath are preferred for NZ modification with WV. The WV+NaOH-MZ exhibited the best performance in heavy metal removal and the most powerful antimicrobial activity among all the zeolites. The sequence of WV+NaOH-MZ for the maximum single metal(loid) adsorption capacities was Pb (48.67 mg/g) >Cd (23.67 mg/g) > As (0.024 mg/g). The WV+NaOH and WV modifications also can increase the stabilities of heavy metals in the MZs. The residual fractions of single Pb and Cd in WV+NaOH-MZ and WV-MZ were 50%, 55%, 34% and 30%, respectively. The pore size of WV+NaOH-MZ (11.73 nm) was bigger than that of NZ or WV-MZ. Additionally, the proportion of clinoptilolite in WV+NaOH-MZ was also higher than other zeolites. The surfaces of WV+alkali-MZs were rougher than that of NZ. Considering the low cost and environmental risk of WV, this work provides some useful information for management of agricultural and industrial residues, environment and food safety.

Genomic Insights into the First Emergence of blaNDM-5-Carrying Carbapenem-Resistant Salmonella enterica Serovar London Strain in China.

Carbapenem-resistant Salmonella enterica (S. enterica) pose a significant threat to public health, causing gastroenteritis and invasive infections. We report the first emergence of a carbapenem-resistant S. enterica serovar London strain, A132, carrying the blaNDM-5 gene in China. Whole-genome sequencing and bioinformatics analysis assigned A132 to be ST155, a multidrug-resistant clone frequently reported in China. The strain A132 exhibited resistance to multiple antibiotics, with 20 acquired antibiotic resistance genes (ARGs) identified, predominantly located on the IncFIB plasmid (pA132-1-NDM). Notably, the blaNDM-5 gene was located within an IS26 flanked-class 1 integron-ISCR1 complex, comprising two genetic cassettes. One cassette is the class 1 integron, which may facilitate the transmission of the entire complex, while the other is the blaNDM-5-containing ISCR1-IS26-flanked cassette, carrying multiple other ARGs. Genbank database search based on the blaNDM-5-carrying cassette identified a similar genetic context found in transmissible IncFIA plasmids from Escherichia coli (p91) and Enterobacter hormaechei (p388) with a shared host range, suggesting the potential for cross-species transmission of blaNDM-5. To our knowledge, this is the first reported case of Salmonella serovar London ST155 harboring blaNDM-5 gene. Phylogenetic analysis indicated a close relationship between A132 and eight S. London ST155 strains isolated from the same province. However, A132 differed by carrying the blaNDM-5 gene and four unique ARGs. Given the high transmissibility of the F-type plasmid harboring blaNDM-5 and 18 other ARGs, it is imperative to implement vigilant surveillance and adopt appropriate infection control measures to mitigate the threat to public health.

Transmission dynamics of drug-resistant tuberculosis in Ningbo, China: an epidemiological and genomic analysis.

Background: Tuberculosis (TB), particularly drug-resistant TB (DR-TB), remains a significant public health concern in Ningbo, China. Understanding its molecular epidemiology and spatial distribution is paramount for effective control. Methods: From December 24, 2020, to March 12, 2023, we collected clinical Mycobacterium tuberculosis (MTB) strains in Ningbo, with whole-genome sequencing performed on 130 MTB strains. We analyzed DR-related gene mutations, conducted phylogenetic and phylodynamic analyses, identified recent transmission clusters, and assessed spatial distribution. Results: Among 130 DR-TB cases, 41% were MDR-TB, 36% pre-XDR-TB, 19% RR-TB, and 3% HR-TB. The phylogenetic tree showed that 90% of strains were Lineage 2 (Beijing genotype), while remaining 10% were Lineage 4 (Euro-American genotype). The spatial analysis identified hotspots of DR-TB in Ningbo's northern region, particularly in traditional urban centers. 31 (24%) of the DR-TB cases were grouped into 7 recent transmission clusters with a large outbreak cluster containing 15 pre-XDR-TB patients. Epidemiological analyses suggested a higher risk of recent DR-TB transmission among young adult patients who frequently visited Internet cafes, game rooms, and factories. Conclusion: Our study provides comprehensive insights into the epidemiology and genetics of DR-TB in Ningbo. The presence of genomic clusters highlights recent transmission events, indicating the need for targeted interventions. These findings are vital for informing TB control strategies in Ningbo and similar settings.

Genomic and spatial analysis reveal the transmission dynamics of tuberculosis in areas with high incidence of Zhejiang, China: A prospective cohort study.

In the mountainous, rural regions of eastern China, tuberculosis (TB) remains a formidable challenge; however, the long-term molecular epidemiological surveillance in these regions is limited. This study aimed to investigate molecular and spatial epidemiology of TB in two mountainous, rural counties of Zhejiang Province, China, from 2015 to 2021, to elucidate the recent transmission and drug-resistance profiles. The predominant Lineage 2 (L2) Beijing family accounted for 80.1% of total 532 sequenced Mycobacterium tuberculosis (Mtb) strains, showing consistent prevalence over seven years. Gene mutations associated with drug resistance were identified in 19.4% (103/532) of strains, including 47 rifampicin or isoniazid-resistant strains, eight multi-drug-resistant (MDR) strains, and five pre-extensively drug-resistant (pre-XDR) strains. Genomic clustering revealed 53 distinct clusters with an overall transmission clustering rate of 23.9% (127/532). Patients with a history of retreatment and those infected with L2 strains had a higher risk of recent transmission. Spatial and epidemiological analysis unveiled significant transmission hotspots, especially in densely populated urban areas, involving various public places such as medical institutions, farmlands, markets, and cardrooms. The study emphasizes the pivotal role of Beijing strains and urban-based TB transmission in the western mountainous regions in Zhejiang, highlighting the urgent requirement for specific interventions to mitigate the impact of TB in these unique communities.

A coherence preservation control strategy in cavity QED based on classical quantum feedback.

For eliminating the unexpected decoherence effect in cavity quantum electrodynamics (cavity QED), the transfer function of Rabi oscillation is derived theoretically using optical Bloch equations. In particular, the decoherence in cavity QED from the atomic spontaneous emission is especially considered. A feedback control strategy is proposed to preserve the coherence through Rabi oscillation stabilization. In the scheme, a classical quantum feedback channel for the quantum information acquisition is constructed via the quantum tomography technology, and a compensation system based on the root locus theory is put forward to suppress the atomic spontaneous emission and the associated decoherence. The simulation results have proved its effectiveness and superiority for the coherence preservation.

IL-17 Imbalance Promotes the Pyroptosis in Immune-Mediated Liver Injury Through STAT3-IFI16 Axis.

Autoimmune hepatitis (AIH) affects all age group and occurs mainly in women. Pyroptosis is a novel programmed cell death featured with cell bursting and release of proinflammatory cytokines. A deeper understanding of AIH pathogenesis will contribute to novel therapy for AIH patients. Here, we aimed to investigate the role of IL-17 in immune-mediated liver injury. The levels of cytokines were measured by ELISA, and mRNA levels of STAT3 and IFN gamma-inducible protein 16 (IFI16) were detected by PCR. Expressions of STAT3, IFI16, gasdermin D and cleaved caspase-1 were measured by western-blotting. Immunohistochemical staining and transmission electron microscopy were applied to evaluate liver histopathological changes of the treated mice. Our results showed that the levels of IFI16 was increased in hepatocytes treated with IL-17 protein, and further elevated after STAT3-overexpressed (STAT3-OE) lentivirus treatment. The levels of IFI16 were reduced in hepatocytes treated with IL-17 neutralizing Ab (nAb), but were significantly increased after STAT3-OE treatment. Pyroptosis was observed in hepatocytes treated with IL-17 protein, and further cell damage was observed after STAT3-OE lentivirus treatment. Liver damage was alleviated in mice treated with IL-17 nAb, however sever damage was experienced after STAT3-OE lentivirus treatment. A binding interaction between IFI16 and STAT3 was detected in IL-17 treated hepatocytes. Glutathione transaminase activity was enhanced in concanavalin A-induced AIH mice compared to the control group (p<0.01). IL-17 plays an important role in activating STAT3 and up-regulating IFI16, which may promote the pyroptosis in AIH-related liver injury through STAT3-IFI16 axis.

Multi-Biomarkers Panel in Identifying Benign and Malignant Lung Diseases and Pathological Types of Lung Cancer.

With the discovery of many tumor markers, there are new strategies for the early diagnosis and treatment of lung cancer and the prediction of prognosis. We examined the multi-protein markers panel (4MP, consisting of Pro-SFTPB, CA125, Cyfra21-1, and CEA) diagnosis performance in differentiating benign and malignant lung diseases and identifying pathological types of lung cancer. Meantime, the complementary performance of three conventional tumor markers (NSE, SCC, and Pro-GRP) for 4MP was assessed. A total of 294 patients with lung cancer or benign lung disease are contained in this study. The AUCs of 4MP and 7MP (NSE, SCC, Pro-GRP, and 4MP) in distinguishing benign lung disease and lung cancer were 0.808 and 0.832, respectively. In distinguishing SQCLC and SCLC, the AUCs were 0.716 and 0.985, respectively. In distinguishing LADC and SCLC, the AUCs were 0.849 and 0.998, respectively. This study demonstrated that 4MP can distinguish lung cancer from benign disease. Traditional biomarkers NSE, SCC, and Pro-GRP can significantly improve the performance of 4MP in the differentiation of LADC, SQCLC, and SCLC, which is expected to contribute to the accurate diagnosis and personalized treatment of patients.

Cross species systems biology discovers glial DDR2, STOM, and KANK2 as therapeutic targets in progressive supranuclear palsy.

Progressive supranuclear palsy (PSP) is a neurodegenerative parkinsonian disorder characterized by cell-type-specific tau lesions in neurons and glia. Prior work uncovered transcriptome changes in human PSP brains, although their cell-specificity is unknown. Further, systematic data integration and experimental validation platforms to prioritize brain transcriptional perturbations as therapeutic targets in PSP are currently lacking. In this study, we combine bulk tissue (n = 408) and single nucleus RNAseq (n = 34) data from PSP and control brains with transcriptome data from a mouse tauopathy and experimental validations in Drosophila tau models for systematic discovery of high-confidence expression changes in PSP with therapeutic potential. We discover, replicate, and annotate thousands of differentially expressed genes in PSP, many of which reside in glia-enriched co-expression modules and cells. We prioritize DDR2, STOM, and KANK2 as promising therapeutic targets in PSP with striking cross-species validations. We share our findings and data via our interactive application tool PSP RNAseq Atlas ( https://rtools.mayo.edu/PSP_RNAseq_Atlas/ ). Our findings reveal robust glial transcriptome changes in PSP, provide a cross-species systems biology approach, and a tool for therapeutic target discoveries in PSP with potential application in other neurodegenerative diseases.

Evolution and Driving Factors of the Spatiotemporal Pattern of Tourism Efficiency at the Provincial Level in China Based on SBM-DEA Model.

In order to give guidance to improve tourism competitiveness and sustainable development, it is particularly important to identify and analyze the factors and mechanisms that affect efficiency. The SBM-DEA model including undesirable outputs was used to measure the tourism efficiency of 30 provinces in China from 2006 to 2019. Combined with the compound DEA model, the sensitivity of each province to the fluctuation of the input-output index was mined. The exploratory spatial analysis method and fixed effect model were used to analyze the spatial change and driving factors of tourism efficiency. The results show that: (1) the tourism efficiency of each province in China fluctuated from 2006 to 2019, and the average value was raised from 0.12 to 0.71, generally reaching the grade of medium and high efficiency; (2) the spatial difference of tourism efficiency is significant, but there is no obvious spatial correlation; (3) the most important input factors to tourism efficiency are environmental resources, tourism resource inputs and tourism infrastructure construction, and tourism fixed asset investment is redundant. (4) Optimizing the industrial structure, strengthening the introduction of core technology, and continuously promoting the process of urbanization and marketization are important ways to improve the efficiency of tourism.

Driving Effect of Decoupling Provincial Industrial Economic Growth and Industrial Carbon Emissions in China.

China is facing the dual challenges of fostering economic growth and mounting an effective response to climate change, so it is vital to continue promoting industrial carbon emission reduction. This paper uses panel data from 1998 to 2019 to measure the industrial carbon emissions of 30 provinces in China. The Tapio decoupling and IPAT (Impact = Population × Affluence × Technology)-based decoupling models are used to analyze each province's velocity and quantity decoupling index for industrial carbon emissions. The fixed effect model analyzes the influencing factors for carbon decoupling. The results show that the industrial carbon emissions of various provinces in China are increasing yearly, but there are significant differences among provinces. The carbon decoupling of the industrial economy in most provinces is weak, and the quantitative decoupling index is better than the velocity decoupling index. The cleanliness of energy, balance, and labor productivity significantly affect the velocity decoupling index. The cleanliness of energy, the industry's structure, and the population significantly affect the quantity decoupling index. Based on empirical results, the study puts forward some policies to promote the efficient carbon decoupling of the industrial economy.

The potential of soluble programmed death-ligand 1 (sPD-L1) as a diagnosis marker for colorectal cancer.

Colorectal cancer (CRC) is one of the most significant neoplasms with high morbidity and mortality. Activation of the programmed death protein 1/programmed death ligand 1 (PD-1/PD-L1) signaling pathway results in tumor immune evasion by suppressing the activity of T cells. The correlation of soluble PD-L1 (sPD-L1) in serum/plasma with clinicopathological features, lymph node metastasis, diagnosis and prognosis is less clear. The aim of this study was to investigate the relationship between sPD-L1 and clinicopathological features, and diagnosis potentialof CRC. Three hundred patients with CRC were included in this study. sPD-L1 was measured by ELISA. Pretreatment levels of sPD-L1 were significantly elevated in CRC patient sera compared to healthy control (HC) (P<0.001). The median value of sPD-L1 in HC, CRC with non-lymph node metastasis, and CRC with lymph node metastasis were 246.78±50.2pg/mL, 284.12±52.7pg/mL, and 321.31±55.3pg/mL, respectively. ROC analysis of sPD-L1 allowed significant differentiation between HC group and CRC group (lymph node metastasis and non lymph node metastasis (AUC=0.861, 95% CI 0.830-0.887, p<0.001). sPD-L1 is a potential biomarker for the diagnosis of CRC. Multivariate analysis showed that lymph node metastasis and tumor differentiation were independent prognostic factors (all P< 0.01), and sPD-L1 was not correlated with the CRC prognosis (p>0.05).

Identification of Therapeutic Targets for Amyotrophic Lateral Sclerosis Using PandaOmics - An AI-Enabled Biological Target Discovery Platform.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease with ill-defined pathogenesis, calling for urgent developments of new therapeutic regimens. Herein, we applied PandaOmics, an AI-driven target discovery platform, to analyze the expression profiles of central nervous system (CNS) samples (237 cases; 91 controls) from public datasets, and direct iPSC-derived motor neurons (diMNs) (135 cases; 31 controls) from Answer ALS. Seventeen high-confidence and eleven novel therapeutic targets were identified and will be released onto ALS.AI (http://als.ai/). Among the proposed targets screened in the c9ALS Drosophila model, we verified 8 unreported genes (KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA) whose suppression strongly rescues eye neurodegeneration. Dysregulated pathways identified from CNS and diMN data characterize different stages of disease development. Altogether, our study provides new insights into ALS pathophysiology and demonstrates how AI speeds up the target discovery process, and opens up new opportunities for therapeutic interventions.

Nuclear import receptors are recruited by FG-nucleoporins to rescue hallmarks of TDP-43 proteinopathy.

BACKGROUND: Cytoplasmic mislocalization and aggregation of TAR DNA-binding protein-43 (TDP-43) is a hallmark of the amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD) disease spectrum, causing both nuclear loss-of-function and cytoplasmic toxic gain-of-function phenotypes. While TDP-43 proteinopathy has been associated with defects in nucleocytoplasmic transport, this process is still poorly understood. Here we study the role of karyopherin-ß1 (KPNB1) and other nuclear import receptors in regulating TDP-43 pathology. METHODS: We used immunostaining, immunoprecipitation, biochemical and toxicity assays in cell lines, primary neuron and organotypic mouse brain slice cultures, to determine the impact of KPNB1 on the solubility, localization, and toxicity of pathological TDP-43 constructs. Postmortem patient brain and spinal cord tissue was stained to assess KPNB1 colocalization with TDP-43 inclusions. Turbidity assays were employed to study the dissolution and prevention of aggregation of recombinant TDP-43 fibrils in vitro. Fly models of TDP-43 proteinopathy were used to determine the effect of KPNB1 on their neurodegenerative phenotype in vivo. RESULTS: We discovered that several members of the nuclear import receptor protein family can reduce the formation of pathological TDP-43 aggregates. Using KPNB1 as a model, we found that its activity depends on the prion-like C-terminal region of TDP-43, which mediates the co-aggregation with phenylalanine and glycine-rich nucleoporins (FG-Nups) such as Nup62. KPNB1 is recruited into these co-aggregates where it acts as a molecular chaperone that reverses aberrant phase transition of Nup62 and TDP-43. These findings are supported by the discovery that Nup62 and KPNB1 are also sequestered into pathological TDP-43 aggregates in ALS/FTD postmortem CNS tissue, and by the identification of the fly ortholog of KPNB1 as a strong protective modifier in Drosophila models of TDP-43 proteinopathy. Our results show that KPNB1 can rescue all hallmarks of TDP-43 pathology, by restoring its solubility and nuclear localization, and reducing neurodegeneration in cellular and animal models of ALS/FTD. CONCLUSION: Our findings suggest a novel NLS-independent mechanism where, analogous to its canonical role in dissolving the diffusion barrier formed by FG-Nups in the nuclear pore, KPNB1 is recruited into TDP-43/FG-Nup co-aggregates present in TDP-43 proteinopathies and therapeutically reverses their deleterious phase transition and mislocalization, mitigating neurodegeneration.

Poly(ADP-ribose) promotes toxicity of C9ORF72 arginine-rich dipeptide repeat proteins.

Arginine-rich dipeptide repeat proteins (R-DPRs), abnormal translational products of a GGGGCC hexanucleotide repeat expansion in C9ORF72, play a critical role in C9ORF72-related amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD), the most common genetic form of the disorders (c9ALS/FTD). R-DPRs form liquid condensates in vitro, induce stress granule formation in cultured cells, aggregate, and sometimes coaggregate with TDP-43 in postmortem tissue from patients with c9ALS/FTD. However, how these processes are regulated is unclear. Here, we show that loss of poly(ADP-ribose) (PAR) suppresses neurodegeneration in c9ALS/FTD fly models and neurons differentiated from patient-derived induced pluripotent stem cells. Mechanistically, PAR induces R-DPR condensation and promotes R-DPR-induced stress granule formation and TDP-43 aggregation. Moreover, PAR associates with insoluble R-DPR and TDP-43 in postmortem tissue from patients. These findings identified PAR as a promoter of R-DPR toxicity and thus a potential target for treating c9ALS/FTD.

Auxiliary diagnosis of Lung Cancer on the basis of a Serum Protein Biomarker Panel.

Objectives: In this study, we established a serum protein biomarker panel (consisting of Pro-SFTPB, CA125, Cyfra21-1, and CEA) and evaluated the feasibility and performance for the auxiliary diagnosis of lung cancer in the Chinese population. Materials and Methods: The current study was a single-center study based on the Chinese population and performed in two cohorts (training cohort and validation cohort). Serum concentrations of Pro-SFTPB, CA125, Cyfra21-1, and CEA were measured by a bead-based flow fluorescence immunoassay. The discrimination performance of the model was assessed using sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC). Results: For the biomarker panel model, the AUC was 0.88 (95% CI, 0.85-0.91) in the training cohort and 0.90 (95% CI, 0.86-0.92) in the validation data cohort, which was significantly greater than the AUC of each biomarker alone. For the nodule risk model, the AUC was improved to 0.96 (95% CI, 0.94-0.98) in the training cohort and 0.95 (95% CI, 0.93-0.97) in the validation cohort. In addition, the biomarker panel model yielded an AUC of 0.78 (95% CI, 0.74-0.81) for stage I & II lung cancer, better than the performance of individual biomarker alone. Conclusions: It was demonstrated that 4-protein biomarker panel had a significant performance in identifying lung cancer patients from healthy controls, especially combining with the nodule size. Specifically, it yielded excellent discrimination for identifying early-stage lung cancer patients than individual biomarker alone. A future large-scale study is underway to further define the clinical application of this method for the early diagnosis of lung cancer among Chinese populations.

Ecological Compensation Strategy for SDG-Based Basin-Type National Parks: A Case Study of the Baoxing Giant Panda National Park.

An ecological compensation mechanism is the basic condition for the sustainable development of national parks and the key institutional measure to implement goals 1, 3, 6, 10, 12, 13, 15, 16, and 17 of the sustainable development goals. In this study, the current ecological compensation mechanism was summarized and analyzed from the aspects of promotion mode, realization routine, and implementation effect, on the basis of the sustainable development needs of national parks and the public welfare character in construction and management. In addition, the practical demands of ecological compensation for basin-type national parks were presented in the setting of the main body and mode of multiparticipation, and the key points of compensation. The "1 + 1 + N" basin-type national park ecological compensation system was designed on the basis of the framework of horizontal protection and vertical development. Taking the Baoxing Giant Panda National Park as an example, typical compensation scenarios were designed from five common compensation approaches; namely, fund, project, technology, material, and policy compensations. The compensation modes were selected and the effect was predicted in combination with local actual situation. Finally, the optimal combination scheme of ecological compensations for national parks was determined on the basis of the return on investment index.

Automatic screening method for atrial fibrillation based on lossy compression of the electrocardiogram signal.

OBJECTIVE: Compressed sensing (CS) is a low-complexity compression technology that has recently been proposed. It can be applied to long-term electrocardiogram (ECG) monitoring using wearable devices. In this study, an automatic screening method for atrial fibrillation (AF) based on lossy compression of the electrocardiogram signal is proposed. APPROACH: The proposed method combines the CS with the convolutional neural network (CNN). The sparse binary sensing matrix is first used to project the raw ECG signal randomly, transforming the raw ECG data from high-dimensional space to low-dimensional space to complete compression, and then using CNN to classify the compressed ECG signal involving AF. Our proposed model is validated on the MIT-BIH atrial fibrillation database. MAIN RESULTS: The experimental results show that the model only needs about 1 s to complete the 24 h ECG recording of AF, which is 3.41%, 69.84% and 67.56% less than the time required by AlexNet, VGGNet and GoogLeNet, respectively. Under different compression ratios of 10% to 90%, the maximum and minimum F1 scores reach 96.25% and 88.17%, respectively. SIGNIFICANCE: The CS-CNN (compressed sensing convolutional neural network) model has high computational efficiency while ensuring prediction accuracy, and is a promising method for AF screening in wearable application scenarios.