Plasma proteomic and polygenic profiling improve risk stratification and personalized screening for colorectal cancer.

This study aims to identify colorectal cancer (CRC)-related proteomic profiles and develop a prediction model for CRC onset by integrating proteomic profiles with genetic and non-genetic factors (QCancer-15) to improve the risk stratification and estimate of personalized initial screening age. Here, using a two-stage strategy, we prioritize 15 protein biomarkers as predictors to construct a protein risk score (ProS). The risk prediction model integrating proteomic profiles with polygenic risk score (PRS) and QCancer-15 risk score (QCancer-S) shows improved performance (C-statistic: 0.79 vs. 0.71, P = 4.94E-03 in training cohort; 0.75 vs 0.69, P = 5.49E-04 in validation cohort) and net benefit than QCancer-S alone. The combined model markedly stratifies the risk of CRC onset. Participants with high ProS, PRS, or combined risk score are proposed to start screening at age 46, 41, or before 40 years old. In this work, the integration of blood proteomics with PRS and QCancer-15 demonstrates improved performance for risk stratification and clinical implication for the derivation of risk-adapted starting ages of CRC screening, which may contribute to the decision-making process for CRC screening.

Achieving destination sustainability: How tourist-to-tourist interaction quality affects tourist loyalty?

Although tourist-to-tourist interaction (TTI) has been identified as an essential element in tourist experiences, the effect of TTI quality on tourist loyalty, and the mechanism underlying this effect is scarcely discussed in the literature. Based on the self-determination theory, this study aims to examine whether and how TTI quality influences tourist loyalty, representing a significant means to achieve destination sustainability. More specifically, this study tested a moderated mediation model in which basic psychological needs satisfaction mediated the relationship between TTI quality and tourist loyalty, while sociability moderated the link between TTI quality and basic psychological needs satisfaction. A survey research approach was used, and 746 complete, usable responses were collected in multiple cities in China. The results revealed that the direct impact of TTI quality on tourist loyalty is mediated by basic psychological needs satisfaction. Furthermore, sociability positively moderates the influence of TTI quality on tourist loyalty. This study extends the TTI literature by demonstrating the mechanism of basic psychological needs satisfaction and tourists' sociability in the relationship between TTI quality and tourist loyalty. Managerial suggestions are provided for industry practitioners to improve tourist relationship management and the sustainability of destinations.

Surveillance of fluoroquinolones resistance in rifampicin-susceptible tuberculosis in eastern China with whole-genome sequencing-based approach.

Background: Leveraging well-established DNA-level drug resistance mechanisms, whole-genome sequencing (WGS) has emerged as a valuable methodology for predicting drug resistance. As the most effective second-line anti-tuberculosis (anti-TB) drugs, fluoroquinoloness (FQs) are generally used to treat multidrug-resistant tuberculosis (MDR-TB, defined as being resistant to resistant to rifampicin and isoniazid) or rifampicin-resistant tuberculosis (RR-TB). However, FQs are also commonly used in the management of other bacterial infections. There are few published data on the rates of FQs resistance among rifampicin-susceptible TB. The prevalence of FQs resistance among TB patients who are rifampicin-susceptible has not been studied in Zhejiang Province, China. The goal of this study was to provide a baseline characterization of the prevalence of FQs resistance, particularly among rifampicin-susceptible TB in Zhejiang Province, China. Methods: Based on WGS, we have investigated the prevalence of FQs resistance among rifampicin-susceptible TB in Zhejiang Province. All pulmonary TB patients with positive cultures who were identified in Zhejiang area during TB drug resistance surveillance from 2018 to 2019 have enrolled in this population-based retrospective study. Results: The rate of FQs resistance was 4.6% (32/698) among TB, 4.0% (27/676) among rifampicin-susceptible TB, and 22.7% (5/22) among RR-TB. According to WGS, strains that differ within 12 single-nucleotide polymorphisms (SNPs) were considered to be transmission of FQ-resistant strains. Specifically, 3.7% (1/27) of FQs resistance was caused by the transmission of FQs-resistant strains among the rifampicin-susceptible TB and 40.7% (11/27) of FQs resistance was identified as hetero-resistance. Conclusion: The prevalence of FQs resistance among TB patients who were rifampicin-susceptible was severe in Zhejiang. The emergence of FQs resistance in TB isolates that are rifampicin-susceptible was mainly caused by the selection of drug-resistant strains. In order to prevent the emergence of FQs resistance, the WGS-based surveillance system for TB should be urgently established, and clinical awareness of the responsible use of FQs for respiratory infections should be enhanced.

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.

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.

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.

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.

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.

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.

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.

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.

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).

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.

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.

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.

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.

A New Feature Extraction and Recognition Method for Microexpression Based on Local Non-negative Matrix Factorization.

Microexpression is usually characterized by short duration and small action range, and the existing general expression recognition algorithms do not work well for microexpression. As a feature extraction method, non-negative matrix factorization can decompose the original data into different components, which has been successfully applied to facial recognition. In this paper, local non-negative matrix factorization is explored to decompose microexpression into some facial muscle actions, and extract features for recognition based on apex frame. However, the existing microexpression datasets fall short of samples to train a classifier with good generalization. The macro-to-micro algorithm based on singular value decomposition can augment the number of microexpressions, but it cannot meet non-negative properties of feature vectors. To address these problems, we propose an improved macro-to-micro algorithm to augment microexpression samples by manipulating the macroexpression data based on local non-negative matrix factorization. Finally, several experiments are conducted to verify the effectiveness of the proposed scheme, which results show that it has a higher recognition accuracy for microexpression compared with the related algorithms based on CK+/CASME2/SAMM datasets.

TFEB/Mitf links impaired nuclear import to autophagolysosomal dysfunction in C9-ALS.

Disrupted nucleocytoplasmic transport (NCT) has been implicated in neurodegenerative disease pathogenesis; however, the mechanisms by which disrupted NCT causes neurodegeneration remain unclear. In a Drosophila screen, we identified ref(2)P/p62, a key regulator of autophagy, as a potent suppressor of neurodegeneration caused by the GGGGCC hexanucleotide repeat expansion (G4C2 HRE) in C9orf72 that causes amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). We found that p62 is increased and forms ubiquitinated aggregates due to decreased autophagic cargo degradation. Immunofluorescence and electron microscopy of Drosophila tissues demonstrate an accumulation of lysosome-like organelles that precedes neurodegeneration. These phenotypes are partially caused by cytoplasmic mislocalization of Mitf/TFEB, a key transcriptional regulator of autophagolysosomal function. Additionally, TFEB is mislocalized and downregulated in human cells expressing GGGGCC repeats and in C9-ALS patient motor cortex. Our data suggest that the C9orf72-HRE impairs Mitf/TFEB nuclear import, thereby disrupting autophagy and exacerbating proteostasis defects in C9-ALS/FTD.

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.