Multi-feature concatenation and multi-classifier stacking: An interpretable and generalizable machine learning method for MDD discrimination with rsfMRI.

Major depressive disorder (MDD) is a serious and heterogeneous psychiatric disorder that needs accurate diagnosis. Resting-state functional MRI (rsfMRI), which captures multiple perspectives on brain structure, function, and connectivity, is increasingly applied in the diagnosis and pathological research of MDD. Different machine learning algorithms are then developed to exploit the rich information in rsfMRI and discriminate MDD patients from normal controls. Despite recent advances reported, the MDD discrimination accuracy has room for further improvement. The generalizability and interpretability of the discrimination method are not sufficiently addressed either. Here, we propose a machine learning method (MFMC) for MDD discrimination by concatenating multiple features and stacking multiple classifiers. MFMC is tested on the REST-meta-MDD data set that contains 2428 subjects collected from 25 different sites. MFMC yields 96.9% MDD discrimination accuracy, demonstrating a significant improvement over existing methods. In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites. The use of XGBoost as the meta classifier allows us to probe the decision process of MFMC. We identify 13 feature values related to 9 brain regions including the posterior cingulate gyrus, superior frontal gyrus orbital part, and angular gyrus, which contribute most to the classification and also demonstrate significant differences at the group level. The use of these 13 feature values alone can reach 87% of MFMC's full performance when taking all feature values. These features may serve as clinically useful diagnostic and prognostic biomarkers for MDD in the future.

Theranostic Nanoplatform Based on Polydopamine-Coated Magnetic Mesoporous Silicon for Precise Cancer Triplex Nanotherapy and Multimodal Imaging.

Although targeted therapy has revolutionized oncotherapy, engineering a versatile oncotherapy nanoplatform integrating both diagnostics and therapeutics has always been an intractable challenge to overcome the limitations of monotherapy. Herein, a theranostics platform based on DI/MP-MB has successfully realized the fluorescence detection of disease marker miR-21 and the gene/photothermal/chemo triple synergetic cancer therapy, which can trace the tumor through photothermal and fluorescence dual-mode imaging and overcome the limitations of monotherapy to improve the treatment efficiency of tumors. DI/MP-MB was prepared by magnetic mesoporous silicon nanoparticles (M-MSNs) loaded with doxorubicin (Dox) and new indocyanine green (IR820), and subsequently coating polydopamine as a "gatekeeper", followed by the surface adsorbed with molecular beacons capable of targeting miR-21 for responsive imaging. Under the action of enhanced permeability retention and external magnetic field, DI/MP-MB were targeted and selectively accumulated in the tumor. MiR-21 MB hybridized with miR-21 to form a double strand, which led to the desorption of miR-21 MB from the polydopamine surface and the fluorescence recovery to realize gene silencing and fluorescence imaging for tracking the treatment process. Meanwhile, with the response to the near-infrared irradiation and the tumor's microacid environment, the outer layer polydopamine will decompose, releasing Dox and IR820 to realize chemotherapy and photothermal therapy. Finally, the ability of DI/MP-MB to efficiently suppress tumor growth was comprehensively assessed and validated both in vitro and in vivo. Noteworthily, the excellent anticancer efficiency by the synergistic effect of gene/photothermal/chemo triple therapy of DI/MP-MB makes it an ideal nanoplatform for tumor therapy and imaging.

Selective Oxidation of Vitamin D3 Enhanced by Long-Range Effects of a Substrate Channel Mutation in Cytochrome P450BM3 (CYP102A1).

Vitamin D deficiency affects nearly half the population, with many requiring or opting for supplements with vitamin D3 (VD3), the precursor of vitamin D (1α,25-dihydroxyVD3). 25-HydroxyVD3, the circulating form of vitamin D, is a more effective supplement than VD3 but its synthesis is complex. We report here the engineering of cytochrome P450BM3 (CYP102A1) for the selective oxidation of VD3 to 25-hydroxyVD3. Long-range effects of the substrate-channel mutation Glu435Ile promoted binding of the VD3 side chain close to the heme, enhancing VD3 oxidation activity that reached 6.62 g of 25-hydroxyVD3 isolated from a 1-litre scale reaction (69.1 % yield; space-time-yield 331 mg/L/h).

Multidose transient transfection of human embryonic kidney 293 cells modulates recombinant adeno-associated virus2/5 Rep protein expression and influences the enrichment fraction of filled capsids.

Recombinant adeno-associated virus (rAAV) is a commonly used in vivo gene therapy vector because of its nonpathogenicity, long-term transgene expression, broad tropism, and ability to transduce both dividing and nondividing cells. However, rAAV vector production via transient transfection of mammalian cells typically yields a low fraction of filled-to-total capsids (~1%-30% of total capsids produced). Analysis of our previously developed mechanistic model for rAAV2/5 production attributed these low fill fractions to a poorly coordinated timeline between capsid synthesis and viral DNA replication and the repression of later phase capsid formation by Rep proteins. Here, we extend the model by quantifying the expression dynamics of total Rep proteins and their influence on the key steps of rAAV2/5 production using a multiple dosing transfection of human embryonic kidney 293 (HEK293) cells. We report that the availability of preformed empty capsids and viral DNA copies per cell are not limiting to the capsid-filling reaction. However, optimal expression of Rep proteins (<240 ± 13 ag per cell) enables enrichment of the filled capsid population (>12% of total capsids/cell) upstream. Our analysis suggests increased enrichment of filled capsids via regulating the expression of Rep proteins is possible but at the expense of per cell capsid titer in a triple plasmid transfection. Our study reveals an intrinsic limitation of scaling rAAV2/5 vector genome (vg) production and underscores the need for approaches that allow for regulating the expression of Rep proteins to maximize vg titer per cell upstream.

Inflammation-Responsive Mesoporous Silica Nanoparticles with Synergistic Anti-inflammatory and Joint Protection Effects for Rheumatoid Arthritis Treatment.

PURPOSE: Joint destruction is a major burden and an unsolved problem in rheumatoid arthritis (RA) patients. We designed an intra-articular mesoporous silica nanosystem (MSN-TP@PDA-GlcN) with anti-inflammatory and joint protection effects. The nanosystem was synthesized by encapsulating triptolide (TP) in mesoporous silica nanoparticles and coating it with pH-sensitive polydopamine (PDA) and glucosamine (GlcN) grafting on the PDA. The nano-drug delivery system with anti-inflammatory and joint protection effects should have good potency against RA. METHODS: A template method was used to synthesize mesoporous silica (MSN). MSN-TP@PDA-GlcN was synthesized via MSN loading with TP, coating with PDA and grafting of GlcN on PDA. The drug release behavior was tested. A cellular inflammatory model and a rat RA model were used to evaluate the effects on RA. In vivo imaging and microdialysis (MD) system were used to analyze the sustained release and pharmacokinetics in RA rats. RESULTS: TMSN-TP@PDA-GlcN was stable, had good biocompatibility, and exhibited sustained release of drugs in acidic environments. It had excellent anti-inflammatory effects in vitro and in vivo. It also effectively repaired joint destruction in vivo without causing any tissue toxicity. In vivo imaging and pharmacokinetics experiments showed that the nanosystem prolonged the residence time, lowered the Cmax value and enhanced the relative bioavailability of TP. CONCLUSIONS: These results demonstrated that MSN-TP@PDA-GlcN sustained the release of drugs in inflammatory joints and produced effective anti-inflammatory and joint protection effects on RA. This study provides a new strategy for the treatment of RA.

The association between ultra-processed food intake and age-related hearing loss: a cross-sectional study.

OBJECTIVES: This study aimed to explore the association between ultra-processed foods and age-related hearing loss. METHODS: Cross-sectional analyses based on data from a nationally representative sample of 1075 adults aged over 50 in the US was performed. The odds ratios (ORs) and 95% confidence intervals (CIs) for hearing loss according to ultra-processed foods intake quartiles were calculated using a multiple adjusted logistic regression model. Restricted cubic spline model was used to flexibly model potential nonlinear relations between ultra-processed foods intake and possibility of hearing loss. We also explored statistical interactions and conducted subgroup analyses where they were found to be significant. RESULTS: Ultra-processed foods intake was significantly correlated with high-frequency hearing loss. After controlling for all covariables, individuals in the fourth quartile of Ultra-processed foods consumption had a 2.8 times higher chance of developing high-frequency hearing loss than individuals in the first quartile of Ultra-processed foods consumption. We also found that the association was more significant in non-Hispanic whites. CONCLUSIONS: This study discovered an association between Ultra-processed foods intake and the incidence of high-frequency hearing loss, which was more significant in non-Hispanic whites.

Development and validation of a model for predicting the early occurrence of RF in ICU-admitted AECOPD patients: a retrospective analysis based on the MIMIC-IV database.

BACKGROUND: This study aims to construct a model predicting the probability of RF in AECOPD patients upon hospital admission. METHODS: This study retrospectively extracted data from MIMIC-IV database, ultimately including 3776 AECOPD patients. The patients were randomly divided into a training set (n = 2643) and a validation set (n = 1133) in a 7:3 ratio. First, LASSO regression analysis was used to optimize variable selection by running a tenfold k-cyclic coordinate descent. Subsequently, a multifactorial Cox regression analysis was employed to establish a predictive model. Thirdly, the model was validated using ROC curves, Harrell's C-index, calibration plots, DCA, and K-M curve. RESULT: Eight predictive indicators were selected, including blood urea nitrogen, prothrombin time, white blood cell count, heart rate, the presence of comorbid interstitial lung disease, heart failure, and the use of antibiotics and bronchodilators. The model constructed with these 8 predictors demonstrated good predictive capabilities, with ROC curve areas under the curve (AUC) of 0.858 (0.836-0.881), 0.773 (0.746-0.799), 0.736 (0.701-0.771) within 3, 7, and 14 days in the training set, respectively and the C-index was 0.743 (0.723-0.763). Additionally, calibration plots indicated strong consistency between predicted and observed values. DCA analysis demonstrated favorable clinical utility. The K-M curve indicated the model's good reliability, revealed a significantly higher RF occurrence probability in the high-risk group than that in the low-risk group (P < 0.0001). CONCLUSION: The nomogram can provide valuable guidance for clinical practitioners to early predict the probability of RF occurrence in AECOPD patients, take relevant measures, prevent RF, and improve patient outcomes.

A target-triggered strand displacement-assisted target recycling based on carbon dots-based fluorescent probe and MSNs@PDA nanoparticles for miRNA amplified detection and fluorescence imaging.

A target-triggered strand displacement-assisted target recycling based on carbon dots-based fluorescent probe and mesoporous silica nanoparticles@polydopamine (MSNs@PDA) was established to detect miRNA. The surface of MSNs rich in mesopores was coated with a layer of PDA, which can adsorb and quench the fluorescence of single-stranded Fuel DNA with fluorescent carbon dots (CDs) modified at the end through fluorescence resonance energy transfer (FRET). After adding double-stranded DNA-gold nanoparticles (dsDNA-AuNPs) and target let-7a, it will trigger two toehold-mediated strand displacement reactions (TSDR), leading to the recovery of fluorescence and the recycling of target let-7a (excitation wavelength: 380 nm; emission wavelength: 458 nm). The recovery value of fluorescence is proportional to the logarithm of the target microRNA let-7a concentration, thus realizing the sensitivity amplification detection of disease markers. The MSNs@PDA@Fuel DNA-CDs/dsDNA-AuNPs nanoplatform based on the strategy of "on-off-on" and TSDR cyclic amplification may hold great potential as an effective and safe nanoprobe for accurate fluorescence imaging of diseases related to miRNA with low abundances.

Associations between Marketing Exposure, In-game Purchases, Problem Gaming, Simulated Gambling, and Psychological Distress among Adolescents.

This study examined the relationships between marketing exposure, in-game purchase, problem gaming, online simulated gambling game playing, and psychological distress. Data were obtained from a sample of 2,595 seventh-grade students from 30 middle schools in Taiwan. A self-administered questionnaire was conducted in 2020. The results indicated that 94% of adolescents engage in online gaming, with 38% making in-game purchases, and 9% playing online simulated gambling games. The multiple regression results showed that adolescents who are exposed to higher levels of gaming marketing, influenced by advertising effects, involved in in-game purchases, and have lower levels of active parental mediation were more likely to experience problem gaming. Adolescents who have increased exposure to gambling game marketing, are influenced by advertising effects, are involved in in-game purchases, and who are experiencing problem gaming were more likely to engage in online simulated gambling game playing and token purchasing. Involvement in in-game purchases, problem gaming, and playing online simulated gambling games were associated with higher levels of psychological distress and poor sleep quality. In conclusion, the results of this study link adolescents' exposure to marketing with their involvement in in-game purchases, problem gaming, and engaging in online simulated gambling.

Investigating alcohol consumption in China via wastewater-based epidemiology.

Alcohol abuse and addiction is a public health issue of global concern. Wastewater-based epidemiology (WBE) is a forceful and effective complementary tool for investigating chemical consumption. This study examined alcohol consumption in major cities of China via WBE and compared WBE estimates with other data sources. A simple and valid ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed for the determination of two alcohol metabolites, ethyl glucuronide (EtG) and ethyl sulfate (EtS) in wastewater. The optimized method was applied to 62 sewage samples collected from wastewater treatment plants (WWTPs) in 31 provincial capital cities across China in the fourth quarter of 2020. The methodology established in this study was validated with the lower limit of quantification (LLOQ) up to 0.1 µg/L, good linearity in the range of 0.1-50 µg/L, intra-day and inter-day precision less than 5.58% and 5.55%, respectively, and the recoveries of the extracts were higher than 97.14%. The consumption range of alcohol estimated via WBE was 6.09 ± 4.56 ethanol/person/day (EPD) in the capital cities of China. Alcohol consumption varies significantly between cities in China, with WBE estimating lower alcohol consumption than WHO and lower than foreign countries. Investing in alcohol consumption based on WBE has great potential to accurately and efficiently estimate alcohol consumption.

Sex Differences in Hierarchical and Modular Organization of Functional Brain Networks: Insights from Hierarchical Entropy and Modularity Analysis.

Existing studies have demonstrated significant sex differences in the neural mechanisms of daily life and neuropsychiatric disorders. The hierarchical organization of the functional brain network is a critical feature for assessing these neural mechanisms. But the sex differences in hierarchical organization have not been fully investigated. Here, we explore whether the hierarchical structure of the brain network differs between females and males using resting-state fMRI data. We measure the hierarchical entropy and the maximum modularity of each individual, and identify a significant negative correlation between the complexity of hierarchy and modularity in brain networks. At the mean level, females show higher modularity, whereas males exhibit a more complex hierarchy. At the consensus level, we use a co-classification matrix to perform a detailed investigation of the differences in the hierarchical organization between sexes and observe that the female group and the male group exhibit different interaction patterns of brain regions in the dorsal attention network (DAN) and visual network (VIN). Our findings suggest that the brains of females and males employ different network topologies to carry out brain functions. In addition, the negative correlation between hierarchy and modularity implies a need to balance the complexity in the hierarchical organization of the brain network, which sheds light on future studies of brain functions.

A high-quality assembled genome of a representative peach landrace, 'Feichenghongli', and analysis of distinct late florescence and narrow leaf traits.

BACKGROUND: Peach (Prunus persica L. Batsch) is one of the most popular fruits worldwide. Although the reference genome of 'Lovell' peach has been released, the diversity of genome-level variations cannot be explored with one genome. To detect these variations, it is necessary to assemble more genomes. RESULTS: We sequenced and de novo assembled the genome of 'Feichenghongli' (FCHL), a representative landrace with strict self-pollination, which maintained the homozygosity of the genome as much as possible. The chromosome-level genome of FCHL was 239.06 Mb in size with a contig N50 of 26.93 Mb and only 4 gaps at the scaffold level. The alignment of the FCHL genome with the reference 'Lovell' genome enabled the identification of 432535 SNPs, 101244 insertions and deletions, and 7299 structural variants. Gene family analysis showed that the expanded genes in FCHL were enriched in sesquiterpenoids and triterpenoid biosynthesis. RNA-seq analyses were carried out to investigate the two distinct traits of late florescence and narrow leaves. Two key genes, PpDAM4 and PpAGL31, were identified candidates for the control of flower bud dormancy, and an F-box gene, PpFBX92, was identified as a good candidate gene in the regulation of leaf size. CONCLUSIONS: The assembled high-quality genome could deepen our understanding of variations among diverse genomes and provide valuable information for identifying functional genes and improving the molecular breeding process.

Bioinformatics and system biology approach to identify the influences of SARS-CoV-2 infections to idiopathic pulmonary fibrosis and chronic obstructive pulmonary disease patients.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), better known as COVID-19, has become a current threat to humanity. The second wave of the SARS-CoV-2 virus has hit many countries, and the confirmed COVID-19 cases are quickly spreading. Therefore, the epidemic is still passing the terrible stage. Having idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD) are the risk factors of the COVID-19, but the molecular mechanisms that underlie IPF, COPD, and CVOID-19 are not well understood. Therefore, we implemented transcriptomic analysis to detect common pathways and molecular biomarkers in IPF, COPD, and COVID-19 that help understand the linkage of SARS-CoV-2 to the IPF and COPD patients. Here, three RNA-seq datasets (GSE147507, GSE52463, and GSE57148) from Gene Expression Omnibus (GEO) is employed to detect mutual differentially expressed genes (DEGs) for IPF, and COPD patients with the COVID-19 infection for finding shared pathways and candidate drugs. A total of 65 common DEGs among these three datasets were identified. Various combinatorial statistical methods and bioinformatics tools were used to build the protein-protein interaction (PPI) and then identified Hub genes and essential modules from this PPI network. Moreover, we performed functional analysis under ontologies terms and pathway analysis and found that IPF and COPD have some shared links to the progression of COVID-19 infection. Transcription factors-genes interaction, protein-drug interactions, and DEGs-miRNAs coregulatory network with common DEGs also identified on the datasets. We think that the candidate drugs obtained by this study might be helpful for effective therapeutic in COVID-19.

PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.

Discovering drug-target (protein) interactions (DTIs) is of great significance for researching and developing novel drugs, having a tremendous advantage to pharmaceutical industries and patients. However, the prediction of DTIs using wet-lab experimental methods is generally expensive and time-consuming. Therefore, different machine learning-based methods have been developed for this purpose, but there are still substantial unknown interactions needed to discover. Furthermore, data imbalance and feature dimensionality problems are a critical challenge in drug-target datasets, which can decrease the classifier performances that have not been significantly addressed yet. This paper proposed a novel drug-target interaction prediction method called PreDTIs. First, the feature vectors of the protein sequence are extracted by the pseudo-position-specific scoring matrix (PsePSSM), dipeptide composition (DC) and pseudo amino acid composition (PseAAC); and the drug is encoded with MACCS substructure fingerings. Besides, we propose a FastUS algorithm to handle the class imbalance problem and also develop a MoIFS algorithm to remove the irrelevant and redundant features for getting the best optimal features. Finally, balanced and optimal features are provided to the LightGBM Classifier to identify DTIs, and the 5-fold CV validation test method was applied to evaluate the prediction ability of the proposed method. Prediction results indicate that the proposed model PreDTIs is significantly superior to other existing methods in predicting DTIs, and our model could be used to discover new drugs for unknown disorders or infections, such as for the coronavirus disease 2019 using existing drugs compounds and severe acute respiratory syndrome coronavirus 2 protein sequences.

The Critical Role of Equilibrative Nucleoside Transporter-2 in Modulating Cerebral Damage and Vascular Dysfunction in Mice with Brain Ischemia-Reperfusion.

BACKGROUND: Cerebral vascular protection is critical for stroke treatment. Adenosine modulates vascular flow and exhibits neuroprotective effects, in which brain extracellular concentration of adenosine is dramatically increased during ischemic events and ischemia-reperfusion. Since the equilibrative nucleoside transporter-2 (Ent2) is important in regulating brain adenosine homeostasis, the present study aimed to investigate the role of Ent2 in mice with cerebral ischemia-reperfusion. METHODS: Cerebral ischemia-reperfusion injury was examined in mice with transient middle cerebral artery occlusion (tMCAO) for 90 minutes, followed by 24-hour reperfusion. Infarct volume, brain edema, neuroinflammation, microvascular structure, regional cerebral blood flow (rCBF), cerebral metabolic rate of oxygen (CMRO2), and the production of reactive oxygen species (ROS) were examined following the reperfusion. RESULTS: Ent2 deletion reduced the infarct volume, brain edema, and neuroinflammation in mice with cerebral ischemia-reperfusion. tMCAO-induced disruption of brain microvessels was ameliorated in Ent2-/- mice, with a reduced expression of matrix metalloproteinases-9 and aquaporin-4 proteins. Following the reperfusion, the rCBF of the wild-type (WT) mice was quickly restored to the baseline, whereas, in Ent2-/- mice, rCBF was slowly recovered initially, but was then higher than that in the WT mice at the later phase of reperfusion. The improved CMRO2 and reduced ROS level support the beneficial effects caused by the changes in the rCBF of Ent2-/- mice. Further studies showed that the protective effects of Ent2 deletion in mice with tMCAO involve adenosine receptor A2AR. CONCLUSIONS: Ent2 plays a critical role in modulating cerebral collateral circulation and ameliorating pathological events of brain ischemia and reperfusion injury.

The association between exposure to volatile organic compounds and serum lipids in the US adult population.

BACKGROUND AND AIM: Epidemiological evidence on the relationship between exposure to volatile organic compounds (VOCs), both single and mixed, and serum lipid levels is limited, and their relationship remains unclear. Our study aimed to investigate the associations of exposure to VOCs with serum lipid levels in the US adult population. METHODS AND RESULTS: The study examined the association of 16 VOC levels (2-methylhippuric acid, 3- and 4-methylhippuric acid, N-acetyl-S-(2-carbamoylethyl)-L-cysteine, N-acetyl-S-(N-methylcarbamoyl)-L-cysteine, 2-aminothiazoline-4-carboxylic acid, N-acetyl-S-(benzyl)-L-cysteine, N-acetyl-S-(n-propyl)-L-cysteine, N-acetyl-S-(2-carboxyethyl)-L-cysteine, N-acetyl-S-(2-cyanoethyl)-L-cysteine, N-acetyl-S-(3,4-dihydroxybutyl)-L-cysteine, N-acetyl-S-(2-hydroxypropyl)-L-cysteine. N-Acetyl-S-(3-hydroxypropyl)-L-cysteine, mandelic acid, N-acetyl-S-(4-hydroxy-2-butenyl)-L-cysteine, phenylglyoxylic acid and N-acetyl-S-(3-hydroxypropyl-1-methyl)-L-cysteine) with total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL) and high-density lipoprotein cholesterol (HDL) using data from the National Health and Nutrition Examination Survey (NHANES) between 2011 and 2015, and a total of 1410 adults were enrolled. The association was evaluated by Bayesian kernel machine regression (BKMR), multiple linear regression and weighted quantile sum (WQS) regression. In BKMR analysis, exposure to VOCs is positively correlated with levels of TC, TG, and LDL-C. However, statistical significance was observed only for the impact on TG. Our linear regression analysis and WQS regression generally support the BKMR results. Several VOCs were positively associated with serum lipid profiles (e.g., the ln-transformed level of mandelic acid (MA) displayed an increase in estimated changes of 7.01 (95% CIs: 2.78, 11.24) mg/dL for TC level), even after the effective number of tests for multiple testing (P < 0.05). CONCLUSIONS: Exposure to VOCs was associated with serum lipids, and more studies are needed to confirm these findings.

MiR-200c regulates invasion, proliferation and EMT of anaplastic thyroid cancer cells by targeting parathyroid hormone like hormone.

This study aimed to explore the specific effect of miR-200c in anaplastic thyroid cancer (ATC). Hth74 and ARO cell lines were used. Proliferation, invasion, and colony formation activities of Hth74 and ARO cell lines affected by miR-200c were studied. Expression of epithelial-to-mesenchymal transition (EMT) markers (E-cadherin, N-cadherin, Slug, and Snail) in the Hth74 and ARO cell lines were validated by western blot and qRT-PCR. In addition, the regulation of the parathyroid hormone-like hormone (PTHLH) by miR-200c was assessed. Overexpression of miR-200c inhibited the invasion, proliferation, and colony formation of the ATC cell lines, whereas its downregulation achieved the opposite results. PTHLH was found to be regulated negatively by miR-200c through a miR-200c binding site within the 3'-UTR of PTHLH. miR-200c repressed the proliferation, invasion, and EMT process of cells in ATC cell lines by targeting PTHLH post-transcriptionally, which indicates that miR-200c may be a potential target for the treatment of ATC.

Development and validation of a clinical prediction model to estimate the risk of critical patients with COVID-19.

The outbreak of coronavirus disease 2019 (COVID-19) has globally strained medical resources and caused significant mortality. This study was aimed to develop and validate a prediction model based on clinical features to estimate the risk of patients with COVID-19 at admission progressing to critical patients. Patients admitted to the hospital between January 16, 2020, and March 10, 2020, were retrospectively enrolled, and they were observed for at least 14 days after admission to determine whether they developed into severe pneumonia. According to the clinical symptoms, all patients were divided into four groups: mild, normal, severe, and critical. A total of 390 patients with COVID-19 pneumonia were identified, including 212 severe patients and 178 nonsevere patients. The least absolute shrinkage and selection operator (LASSO) regression reduced the variables in the model to 6, which are age, number of comorbidities, computed tomography severity score, lymphocyte count, aspartate aminotransferase, and albumin. The area under curve of the model in the training set is 0.898, and the specificity and sensitivity were 89.7% and 75.5%. The prediction model, nomogram might be useful to access the onset of severe and critical illness among COVID-19 patients at admission, which is instructive for clinical diagnosis.

TRIM66 hastens the malignant progression of non-small cell lung cancer via modulating MMP9-mediated TGF-ß/SMAD pathway.

OBJECTIVE: To investigate regulatory function and underlying mechanism of TRIM66 in non-small cell lung cancer (NSCLC). METHODS: TRIM66 and MMP9 expression in NSCLC cells and tissues was assayed via qRT-PCR and western blot. CCK-8, colony formation, Transwell and flow cytometry assays were conducted to measure cell functional alternations in NSCLC. Western blot was employed to measure expression as well as phosphorylation levels of epithelial-mesenchymal transition-(EMT) and TGF-ß/SMAD pathways-related proteins. Co-immunoprecipitation (Co-IP) assay was done to probe interaction between TRIM66 and MMP9. Xenograft in vivo experiment and tumor metastasis model in nude mice were utilized to investigate effects of TRIM66 on tumor growth of NSCLC. RESULTS: TRIM66 and MMP9 were conspicuously highly expressed in NSCLC cells and tissues. High TRIM66 level was markedly correlated with metastasis. Silencing TRIM66 prominently repressed the proliferation, migration and invasion of transfected cells, while inducing cell apoptosis. Whereas forced expression of TRIM66 exerted the opposite effect. The aberrant expression of TRIM66 modulated EMT pathway. TRIM66 also regulated MMP9 expression, and the interaction between them was validated by Co-IP assay. Overexpression of MMP9 could activate TGF-ß/SMAD pathway. Rescue experiments manifested that si-MMP9 or SB431542 could partially reverse phenotypes induced by TRIM66. In vivo experiments revealed that silencing TRIM66 could hamper NSCLC tumor growth and metastasis. CONCLUSION: TRIM66 and MMP9 were up-regulated in NSCLC. TRIM66 facilitated the malignant progression of NSCLC through modulating MMP9-mediated TGF-ß/SMAD pathway.

Development and validation of a prognostic nomogram for early stage non-small cell lung cancer: a study based on the SEER database and a Chinese cohort.

OBJECTIVE: This study aimed to construct a nomogram to effectively predict the overall survival (OS) of patients with early-stage non-small-cell lung cancer (NSCLC). METHODS: For the training and internal validation cohorts, a total of 26,941 patients with stage I and II NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. A nomogram was constructed based on the risk factors affecting prognosis using a Cox proportional hazards regression model. And 505 patients were recruited from Jiaxing First Hospital for external validation. The discrimination and calibration of the nomogram were evaluated by C-index and calibration curves. RESULTS: A Nomogram was created after identifying independent prognostic factors using univariate and multifactorial factor analysis. The C-index of this nomogram was 0.726 (95% CI, 0.718-0.735) and 0.721 (95% CI, 0.709-0.734) in the training cohort and the internal validation cohort, respectively, and 0.758 (95% CI, 0.691-0.825) in the external validation cohort, which indicates that the model has good discrimination. Calibration curves for 1-, 3-, and 5-year OS probabilities showed good agreement between predicted and actual survival. In addition, DCA analysis showed that the net benefit of the new model was significantly higher than that of the TNM staging system. CONCLUSION: We developed and validated a survival prediction model for patients with non-small cell lung cancer in the early stages. This new nomogram is superior to the traditional TNM staging system and can guide clinicians to make the best clinical decisions.