Pairwise machine learning-based automatic diagnostic platform utilizing CT images and clinical information for predicting radiotherapy locoregional recurrence in elderly esophageal cancer patients.

OBJECTIVE: To investigate the feasibility and accuracy of predicting locoregional recurrence (LR) in elderly patients with esophageal squamous cell cancer (ESCC) who underwent radical radiotherapy using a pairwise machine learning algorithm. METHODS: The 130 datasets enrolled were randomly divided into a training set and a testing set in a 7:3 ratio. Clinical factors were included and radiomics features were extracted from pretreatment CT scans using pyradiomics-based software, and a pairwise naive Bayes (NB) model was developed. The performance of the model was evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). To facilitate practical application, we attempted to construct an automated esophageal cancer diagnosis system based on trained models. RESULTS: To the follow-up date, 64 patients (49.23%) had experienced LR. Ten radiomics features and two clinical factors were selected for modeling. The model demonstrated good prediction performance, with area under the ROC curve of 0.903 (0.829-0.958) for the training cohort and 0.944 (0.849-1.000) for the testing cohort. The corresponding accuracies were 0.852 and 0.914, respectively. Calibration curves showed good agreement, and DCA curve confirmed the clinical validity of the model. The model accurately predicted LR in elderly patients, with a positive predictive value of 85.71% for the testing cohort. CONCLUSIONS: The pairwise NB model, based on pre-treatment enhanced chest CT-based radiomics and clinical factors, can accurately predict LR in elderly patients with ESCC. The esophageal cancer automated diagnostic system embedded with the pairwise NB model holds significant potential for application in clinical practice.

Bone-metastatic lung adenocarcinoma cells bearing CD74-ROS1 fusion interact with macrophages to promote their dissemination.

Approximately 40% of patients with lung adenocarcinoma (LUAD) often develop bone metastases during the course of their disease. However, scarcely any in vivo model of LUAD bone metastasis has been established, leading to a poor understanding of the mechanisms underlying LUAD bone metastasis. Here, we established a multiorgan metastasis model via the left ventricular injection of luciferase-labeled LUAD cells into nude mice and then screened out lung metastasis (LuM) and bone metastasis (BoM) cell subpopulations. BoM cells exhibited greater stemness and epithelial-mesenchymal transition (EMT) plasticity than LuM cells and initially colonized the bone and subsequently disseminated to distant organs after being reinjected into mice. Moreover, a CD74-ROS1 fusion mutation (C6; R34) was detected in BoM cells but not in LuM cells. Mechanistically, BoM cells bearing the CD74-ROS1 fusion highly secrete the C-C motif chemokine ligand 5 (CCL5) protein by activating STAT3 signaling, recruiting macrophages in tumor microenvironment and strongly inducing M2 polarization of macrophages. BoM cell-activated macrophages produce a high level of TGF-ß1, thereby facilitating EMT and invasion of LUAD cells via TGF-ß/SMAD2/3 signaling. Targeting the CD74-ROS1/CCL5 axis with Crizotinib (a ROS1 inhibitor) and Maraviroc (a CCL5 receptor inhibitor) in vivo strongly impeded bone metastasis and secondary metastasis of BoM cells. Our findings reveal the critical role of the CD74-ROS1/STAT3/CCL5 axis in the interaction between LUAD bone metastasis cells and macrophages for controlling LUAD cell dissemination, highlighting the significance of the bone microenvironment in LUAD bone metastasis and multiorgan secondary metastasis, and suggesting that targeting CD74-ROS1 and CCL5 is a promising therapeutic strategy for LUAD bone metastasis.

Sinomenine increases osteogenesis in mice with ovariectomy-induced bone loss by modulating autophagy.

BACKGROUND: A decreased autophagic capacity of bone marrow mesenchymal stromal cells (BMSCs) has been suggested to be an important cause of decreased osteogenic differentiation. A pharmacological increase in autophagy of BMSCs is a potential therapeutic option to increase osteoblast viability and ameliorate osteoporosis. AIM: To explore the effects of sinomenine (SIN) on the osteogenic differentiation of BMSCs and the underlying mechanisms. METHODS: For in vitro experiments, BMSCs were extracted from sham-treated mice and ovariectomized mice, and the levels of autophagy markers and osteogenic differentiation were examined after treatment with the appropriate concentrations of SIN and the autophagy inhibitor 3-methyladenine. In vivo, the therapeutic effect of SIN was verified by establishing an ovariectomy-induced mouse model and by morphological and histological assays of the mouse femur. RESULTS: SIN reduced the levels of AKT and mammalian target of the rapamycin (mTOR) phosphorylation in the phosphatidylinositol 3-kinase (PI3K)/AKT/mTOR signaling pathway, inhibited mTOR activity, and increased autophagy ability of BMSCs, thereby promoting the osteogenic differentiation of BMSCs and effectively alleviating bone loss in ovariectomized mice in vivo. CONCLUSION: The Chinese medicine SIN has potential for the treatment of various types of osteoporosis, bone homeostasis disorders, and autophagy-related diseases.

Bioinspired Binickel Catalyst for Carbon Dioxide Reduction: The Importance of Metal-ligand Cooperation.

Catalyst design for the efficient CO2 reduction reaction (CO2RR) remains a crucial challenge for the conversion of CO2 to fuels. Natural Ni-Fe carbon monoxide dehydrogenase (NiFe-CODH) achieves reversible conversion of CO2 and CO at nearly thermodynamic equilibrium potential, which provides a template for developing CO2RR catalysts. However, compared with the natural enzyme, most biomimetic synthetic Ni-Fe complexes exhibit negligible CO2RR catalytic activities, which emphasizes the significance of effective bimetallic cooperation for CO2 activation. Enlightened by bimetallic synergy, we herein report a dinickel complex, NiIINiII(bphpp)(AcO)2 (where NiNi(bphpp) is derived from H2bphpp = 2,9-bis(5-tert-butyl-2-hydroxy-3-pyridylphenyl)-1,10-phenanthroline) for electrocatalytic reduction of CO2 to CO, which exhibits a remarkable reactivity approximately 5 times higher than that of the mononuclear Ni catalyst. Electrochemical and computational studies have revealed that the redox-active phenanthroline moiety effectively modulates the electron injection and transfer akin to the [Fe3S4] cluster in NiFe-CODH, and the secondary Ni site facilitates the C-O bond activation and cleavage through electron mediation and Lewis acid characteristics. Our work underscores the significant role of bimetallic cooperation in CO2 reduction catalysis and provides valuable guidance for the rational design of CO2RR catalysts.

P4HA2 activates mTOR via hydroxylation and targeting P4HA2-mTOR inhibits lung adenocarcinoma cell growth.

Mammalian target of rapamycin (mTOR) kinase functions as a central regulator of cell growth and metabolism, and its complexes mTORC1 and mTORC2 phosphorylate distinct substrates. Dysregulation of mTOR signaling is commonly implicated in human diseases, including cancer. Despite three decades of active research in mTOR, much remains to be determined. Here, we demonstrate that prolyl 4-hydroxylase alpha-2 (P4HA2) binds directly to mTOR and hydroxylates one highly conserved proline 2341 (P2341) within a kinase domain of mTOR, thereby activating mTOR kinase and downstream effector proteins (e.g. S6K and AKT). Moreover, the hydroxylation of P2341 strengthens mTOR stability and allows mTOR to accurately recognize its substrates such as S6K and AKT. The growth of lung adenocarcinoma cells overexpressing mTORP2341A is significantly reduced when compared with that of cells overexpressing mTORWT. Interestingly, in vivo cell growth assays show that targeting P4HA2-mTOR significantly suppresses lung adenocarcinoma cell growth. In summary, our study reveals an undiscovered hydroxylation-regulatory mechanism by which P4HA2 directly activates mTOR kinase, providing insights for therapeutically targeting mTOR kinase-driven cancers.

A quality grade classification method for fresh tea leaves based on an improved YOLOv8x-SPPCSPC-CBAM model.

In light of the prevalent issues concerning the mechanical grading of fresh tea leaves, characterized by high damage rates and poor accuracy, as well as the limited grading precision through the integration of machine vision and machine learning (ML) algorithms, this study presents an innovative approach for classifying the quality grade of fresh tea leaves. This approach leverages an integration of image recognition and deep learning (DL) algorithm to accurately classify tea leaves' grades by identifying distinct bud and leaf combinations. The method begins by acquiring separate images of orderly scattered and randomly stacked fresh tea leaves. These images undergo data augmentation techniques, such as rotation, flipping, and contrast adjustment, to form the scattered and stacked tea leaves datasets. Subsequently, the YOLOv8x model was enhanced by Space pyramid pooling improvements (SPPCSPC) and the concentration-based attention module (CBAM). The established YOLOv8x-SPPCSPC-CBAM model is evaluated by comparing it with popular DL models, including Faster R-CNN, YOLOv5x, and YOLOv8x. The experimental findings reveal that the YOLOv8x-SPPCSPC-CBAM model delivers the most impressive results. For the scattered tea leaves, the mean average precision, precision, recall, and number of images processed per second rates of 98.2%, 95.8%, 96.7%, and 2.77, respectively, while for stacked tea leaves, they are 99.1%, 99.1%, 97.7% and 2.35, respectively. This study provides a robust framework for accurately classifying the quality grade of fresh tea leaves.

Pivotal Role of Geometry Regulation on O-O Bond Formation Mechanism of Bimetallic Water Oxidation Catalysts.

In this study, we highlight the impact of catalyst geometry on the formation of O-O bonds in Cu2 and Fe2 catalysts. A series of Cu2 complexes with diverse linkers are designed as electrocatalysts for water oxidation. Interestingly, the catalytic performance of these Cu2 complexes is enhanced as their molecular skeletons become more rigid, which contrasts with the behavior observed in our previous investigation with Fe2 analogs. Moreover, mechanistic studies reveal that the reactivity of the bridging O atom results in distinct pathways for O-O bond formation in Cu2 and Fe2 catalysts. In Cu2 systems, the coupling takes place between a terminal CuIII -OH and a bridging µ-O⋅ radical. Whereas in Fe2 systems, it involves the coupling of two terminal Fe-oxo entities. Furthermore, an in-depth structure-activity analysis uncovers the spatial geometric prerequisites for the coupling of the terminal OH with the bridging µ-O⋅ radical, ultimately leading to the O-O bond formation. Overall, this study emphasizes the critical role of precisely adjusting the spatial geometry of catalysts to align with the O-O bonding pathway.

Effect of prehabilitation on postoperative outcomes in the frail older people: A systematic review and meta-analysis.

OBJECTIVE: The study investigates the impact of preoperative rehabilitation on the surgical prognosis of frail older patients. METHOD: The effect sizes of all studies retrieved and included by the nine databases were analyzed and expressed as RR and WMD. RESULTS: 8 studies with 902 participants met the criteria for inclusion. A significant reduction in total complications (RR = 0.84, 95 % CI = 0.73 to 0.97, P = 0.021) and the 6MWT after surgery (WMD = 74.76, 95 % CI = 44.75 to 104.77, P = 0.000) was observed in the prehabilitation group. But it had no differences in mortality(RR = 1.89, 95 % CI = 0.75 to 4.72, P = 0.176), readmission rates(RR = 1.04, 95 % CI = 0.56 to 1.91, P = 0.906) and LOS(WMD = -0.24, 95 % CI = -1.00 to 0.52, P = 0.540). CONCLUSIONS: Prehabilitation had positive effect on postoperative complications and functional recovery in frail older patients.

Redox-Active Ligand Assisted Multielectron Catalysis: A Case of Electrocatalyzed CO2-to-CO Conversion.

The selective reduction of carbon dioxide remains a significant challenge due to the complex multielectron/proton transfer process, which results in a high kinetic barrier and the production of diverse products. Inspired by the electrostatic and H-bonding interactions observed in the second sphere of the [NiFe]-CODH enzyme, researchers have extensively explored these interactions to regulate proton transfer, stabilize intermediates, and ultimately improve the performance of catalytic CO2 reduction. In this work, a series of cobalt(II) tetraphenylporphyrins with varying numbers of redox-active nitro groups were synthesized and evaluated as CO2 reduction electrocatalysts. Analyses of the redox properties of these complexes revealed a consistent relationship between the number of nitro groups and the corresponding accepted electron number of the ligand at -1.59 V vs. Fc+/0. Among the catalysts tested, TNPPCo with four nitro groups exhibited the most efficient catalytic activity with a turnover frequency of 4.9 × 104 s-1 and a catalytic onset potential 820 mV more positive than that of the parent TPPCo. Furthermore, the turnover frequencies of the catalysts increased with a higher number of nitro groups. These results demonstrate the promising design strategy of incorporating multielectron redox-active ligands into CO2 reduction catalysts to enhance catalytic performance.

Selective Four-Electron Reduction of Oxygen by a Nonheme Heterobimetallic CuFe Complex.

We report herein the first nonheme CuFe oxygen reduction catalyst ([CuII (bpbp)(µ-OAc)2 FeIII ]2+ , CuFe-OAc), which serves as a functional model of cytochrome c oxidase and can catalyze oxygen reduction to water with a turnover frequency of 2.4×103  s-1 and selectivity of 96.0 % in the presence of Et3 NH+ . This performance significantly outcompetes its homobimetallic analogues (2.7 s-1 of CuCu-OAc with %H2 O2 selectivity of 98.9 %, and inactive of FeFe-OAc) under the same conditions. Structure-activity relationship studies, in combination with density functional theory calculation, show that the CuFe center efficiently mediates O-O bond cleavage via a CuII (µ-η1 : η2 -O2 )FeIII peroxo intermediate in which the peroxo ligand possesses distinctive coordinating and electronic character. Our work sheds light on the nature of Cu/Fe heterobimetallic cooperation in oxygen reduction catalysis and demonstrates the potential of this synergistic effect in the design of nonheme oxygen reduction catalysts.

Predicting Breast Cancer Subtypes Using Magnetic Resonance Imaging Based Radiomics With Automatic Segmentation.

OBJECTIVE: The aim of the study is to demonstrate whether radiomics based on an automatic segmentation method is feasible for predicting molecular subtypes. METHODS: This retrospective study included 516 patients with confirmed breast cancer. An automatic segmentation-3-dimensional UNet-based Convolutional Neural Networks, trained on our in-house data set-was applied to segment the regions of interest. A set of 1316 radiomics features per region of interest was extracted. Eighteen cross-combination radiomics methods-with 6 feature selection methods and 3 classifiers-were used for model selection. Model classification performance was assessed using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity. RESULTS: The average dice similarity coefficient value of the automatic segmentation was 0.89. The radiomics models were predictive of 4 molecular subtypes with the best average: AUC = 0.8623, accuracy = 0.6596, sensitivity = 0.6383, and specificity = 0.8775. For luminal versus nonluminal subtypes, AUC = 0.8788 (95% confidence interval [CI], 0.8505-0.9071), accuracy = 0.7756, sensitivity = 0.7973, and specificity = 0.7466. For human epidermal growth factor receptor 2 (HER2)-enriched versus non-HER2-enriched subtypes, AUC = 0.8676 (95% CI, 0.8370-0.8982), accuracy = 0.7737, sensitivity = 0.8859, and specificity = 0.7283. For triple-negative breast cancer versus non-triple-negative breast cancer subtypes, AUC = 0.9335 (95% CI, 0.9027-0.9643), accuracy = 0.9110, sensitivity = 0.4444, and specificity = 0.9865. CONCLUSIONS: Radiomics based on automatic segmentation of magnetic resonance imaging can predict breast cancer of 4 molecular subtypes noninvasively and is potentially applicable in large samples.

Heterobimetallic NiFe Cooperative Molecular Water Oxidation Catalyst.

We reported herein the development of heterobimetallic NiFe molecular platform to understand NiFe synergistic effect in water oxidation catalysis. Compared to homonuclear bimetallic compounds (NiNi and FeFe), NiFe complex possesses more remarkable catalytic water oxidation performance. Mechanistic studies suggest that this remarkable difference is attributed to the fact that NiFe synergy can effectively promote O-O bond formation. The generated NiIII (µ-O)FeIV =O is the key intermediate and O-O bond was formed via intramolecular oxyl-oxo coupling between bridged O radical and terminal FeIV =O moiety.

Computed tomography-based COVID-19 triage through a deep neural network using mask-weighted global average pooling.

Background: There is an urgent need to find an effective and accurate method for triaging coronavirus disease 2019 (COVID-19) patients from millions or billions of people. Therefore, this study aimed to develop a novel deep-learning approach for COVID-19 triage based on chest computed tomography (CT) images, including normal, pneumonia, and COVID-19 cases. Methods: A total of 2,809 chest CT scans (1,105 COVID-19, 854 normal, and 850 non-3COVID-19 pneumonia cases) were acquired for this study and classified into the training set (n = 2,329) and test set (n = 480). A U-net-based convolutional neural network was used for lung segmentation, and a mask-weighted global average pooling (GAP) method was proposed for the deep neural network to improve the performance of COVID-19 classification between COVID-19 and normal or common pneumonia cases. Results: The results for lung segmentation reached a dice value of 96.5% on 30 independent CT scans. The performance of the mask-weighted GAP method achieved the COVID-19 triage with a sensitivity of 96.5% and specificity of 87.8% using the testing dataset. The mask-weighted GAP method demonstrated 0.9% and 2% improvements in sensitivity and specificity, respectively, compared with the normal GAP. In addition, fusion images between the CT images and the highlighted area from the deep learning model using the Grad-CAM method, indicating the lesion region detected using the deep learning method, were drawn and could also be confirmed by radiologists. Conclusions: This study proposed a mask-weighted GAP-based deep learning method and obtained promising results for COVID-19 triage based on chest CT images. Furthermore, it can be considered a convenient tool to assist doctors in diagnosing COVID-19.

New two-stage pH combined with dissolved oxygen control strategy for cyclic ß-1,2 glucans synthesis.

On the basis of a novel two-stage pH combined with dissolved oxygen (DO) control strategy in fed-batch fermentation, this research addresses the influence of pH on cyclic ß-1,2-glucans (CßGs) biosynthesis and melanin accumulation during the production of CßGs by Rhizobium radiobacter ATCC 13,333. Under these optimal fermentation conditions, the maximum cell concentration and CßGs concentration in a 7-L stirred-tank fermenter were 7.94 g L-1 and 3.12 g L-1, which were the maximum production reported for R. radiobacter. The melanin concentration of the fermentation broth was maintained at a low level, which was beneficial to the subsequent separation and purification of the CßGs. In addition, a neutral extracellular oligosaccharide (COGs-1) purified by the two-stage pH combined with DO control strategy fermentation medium was structurally characterized. Structural analyses indicated that COGs-1 was a family of unbranched cyclic oligosaccharides composed of only ß-1,2-linked D-glucopyranose residues with degree of polymerization between 17 and 23, namely CßGs. This research provides a reliable source of CßGs and structural basis for further studies of biological activity and function. KEY POINTS: • A two-stage pH combined with DO control strategy was proposed for CßGs production and melanin biosynthesis by Rhizobium radiobacter. • The final extracellular CßGs production reached 3.12 g L-1, which was the highest achieved by Rhizobium radiobacter. • The existence of CßGs could be detected by TLC quickly and accurately.

Application of immersion B-scan ultrasonography in diagnosis of complex retinal detachment, persistent hyperplastic primary vitreous and intraocular tumors.

AIM: To evaluate the diagnostic value of panoramic immersion B-scan ultrasonography (Pano-immersion B-scan, PIB) in complex retinal detachment (RD), persistent hyperplastic primary vitreous (PHPV) and intraocular tumors. METHODS: The clinical data of 44 patients collected from May 2012 to December 2019 in Chinese PLA General Hospital was retrospectively studied. All of these patients underwent PIB of the eye, because it was difficult to diagnose by routine ocular fundus examination, conventional ultrasound or/and ultrasonic biomicroscope (UBM) due to opacity of refractive media, pupillary occlusion, large involvement or special location of the lesion. The imaging features of difficult cases in PIB were analyzed. The diagnosis accuracy rating of PIB were evaluated and contrasted with conventional ultrasound or UBM by the standard of intraoperative diagnosis or/and pathological results. RESULTS: According to intraoperative diagnosis or pathological results as gold standard, among the 44 cases, there were 19 cases missed diagnosis, misdiagnosed or difficult-to-diagnose by conventional ultrasound or UBM, including 4 cases of long-standing RD difficult to diagnose, 4 cases misdiagnosed, and 11 cases incompletely observed or miss diagnosed. The diagnostic accuracy rate of PIB and conventional ultrasound or UBM were 100% (44/44) and 56.82% (25/44), and the sensitivity of them were 100% and 56.82%. All the patients underwent PIB and were diagnosed as RD (15 cases), retinal and choroidal detachment (4 cases), subchoroidal hematocele (1 case), vitreous opacity and/or organic membrane formation (4 cases), PHPV (12 cases), iris and/or ciliary body tumors (3 cases), and choroidal tumors (6 cases). According to the intraoperative diagnosis or pathological results, the diagnostic coincidence rate of PIB was 100%, which was significantly higher than conventional ultrasound and UBM. CONCLUSION: PIB can help to accurately diagnose complex RD, PHPV, and intraocular masses with special location or/and excessive size. It has important diagnostic value for patients with equivocal findings at conventional ultrasound examination.

Association of cognitive function and hypoperfusion in Moyamoya disease patients without stroke.

The influence of hypoperfusion on cognition in patients with Moyamoya disease (MMD) is unclear. This study investigated cognitive function changes in MMD patients without stroke and illustrated the relationship between cognitive impairment and hypoperfusion. We prospectively performed a structured battery of seven neurocognitive tests on 115 adult MMD patients without stroke and 82 healthy controls. Hemodynamic assessment was performed using dynamic susceptibility contrast-enhanced MRI. The best subset regression (BSR) strategy was used to identify risk factors. Global cognition (MoCA), speed of information processing (TMT-A), executive function (TMT-B), visuospatial function (CDT), and verbal memory (CAVLT) were significantly poorer in MMD patients without stroke than in healthy controls. The TMT-B score significantly correlated with cerebral blood flow (CBF) in the bilateral lateral frontal lobes, centrum semiovale, and temporal lobes. The TMT-A and CAVLT scores significantly correlated with CBF in the left centrum semiovale (L-CSO) and temporal lobes. According to the BSR results, age, education, white matter lesions, and hypoperfusion of the L-CSO were risk factors for cognitive impairment. Hypoperfusion leads to multiple cognitive impairments in MMD patients without stroke. The perfusion of particular areas may help evaluate the cognitive function of MMD patients and guide therapeutic strategies.

Co-training based virtual sample generation for solving the small sample size problem in process industry.

With the development of industrialization, the production scale and complexity of process industries are getting larger and larger. But, limited by the small amounts of samples and the uneven sample distribution in the process industry, it is difficult to establish accurate and efficient data-driven soft sensor models to predict some variables. To further develop the application of soft sensor models, generating new virtual samples based on the original sample distribution to extend the sample set is an ideal approach to solve this problem. In this paper, a novel virtual sample generation method based on the co-training of two K-Nearest Neighbor (KNN) models is proposed. First, according to the sparse parameter, sparse regions in each dimension of the feature space are identified. Second, the input features of virtual samples are generated in these sparse regions by performing interpolation operations. Third, the outputs of virtual samples are predicted by double KNN regressors based on co-training. The qualified virtual samples are screened and the model is updated using these virtual samples to improve the prediction accuracy of the double KNN models. To verify the effectiveness and superiority of the proposed virtual sample generation method based on the co-training (CTVSG), case studies are conducted using two standard functions and a Purified Terephthalic Acid (PTA) industrial dataset, where the effectiveness of CTVSG is confirmed.

Cerebral neurovascular alterations in stable chronic obstructive pulmonary disease: a preliminary fMRI study.

Purpose: Cognitive impairment (CI) is very common in patients with chronic obstructive pulmonary disease (COPD). Cerebral structural and functional abnormalities have been reported in cognitively impaired patients with COPD, and the neurovascular coupling changes are rarely investigated. To address this issue, arterial spin labeling (ASL) and resting-state blood oxygenation level dependent (BOLD) fMRI techniques were used to determine whether any neurovascular changes in COPD patients. Methods: Forty-five stable COPD patients and forty gender- and age-matched healthy controls were recruited. Furthermore, resting-state BOLD fMRI and ASL were acquired to calculate degree centrality (DC) and cerebral blood flow (CBF) respectively. The CBF-DC coupling and CBF/DC ratio were compared between the two groups. Results: COPD patients showed abnormal CBF, DC and CBF/DC ratio in several regions. Moreover, lower CBF/DC ratio in the left lingual gyrus negatively correlated with naming scores, lower CBF/DC ratio in medial frontal cortex/temporal gyrus positively correlated with the Montreal Cognitive Assessment (MoCA), visuospatial/executive and delayed recall scores. Conclusion: These findings may provide new potential insights into neuropathogenesis of cognition decline in stable COPD patients.

TIF1γ inhibits lung adenocarcinoma EMT and metastasis by interacting with the TAF15/TBP complex.

The molecular underpinnings of lung adenocarcinoma (LUAD) metastasis remain poorly defined. Here, using human LUAD cell lines, we find that transcriptional intermediary factor 1 γ (TIF1γ) binds to TATA box binding protein (TBP) in competition with TBP-associated factor 15 (TAF15) and impedes TAF15/TBP-mediated interleukin 6 (IL-6) transactivation. TIF1γ modifies TAF15 through multi-mono-ubiquitylation and drives nuclear export of TAF15. Functionally, TAF15 accelerates epithelial-mesenchymal transition (EMT) and metastasis of LUAD cells, acting in just the opposite way as TIF1γ. Low TIF1γ or high TAF15 expression levels are shown in metastatic LUAD specimens and correlate with poor survival of individuals with LUAD. Our findings suggest that the TAF15/TBP complex is required for IL-6 activation-induced EMT and invasion, which are inhibited by TIF1γ. This study highlights the crucial interaction between TIF1γ and the TAF15/TBP complex for regulating EMT and metastasis in LUAD.

Structural-visual functional relationships detected by optical coherence tomography in varying age-cohorts' patients with optic neuritis.

AIM: To assess the relationships of final best-corrected visual acuity (BCVA) and the optic nerve structural loss in varying age-cohorts of optic neuritis (ON) patients. METHODS: This is a retrospective, cross-sectional study. Totally 130 ON subjects (200 eyes) without ON onset within 6mo were included, who underwent BCVA assessment, peripapillary retinal nerve fibre layer (pRNFL) and macular segmented layers evaluation by optical coherence tomography (OCT). RESULTS: For the 0-18y cohort, the final BCVA (logMAR) was significantly better and less frequent recurrences than adult cohorts (P=0.000). The final BCVA (logMAR) in all age-cohorts of the ON patients had negative and linear correlations to the pRNFL thicknesses and macular retinal ganglion cell layer (mRGCL) volumes, when the pRNFL thicknesses were reduced to the thresholds of 57.2-67.5 µm or 0.691-0.737 mm3 in mRGCL volumes, respectively, with the strongest interdependence in the 19-40y cohort. The ON patients from varying age cohorts would be threatened by blindness when their pRNFL thicknesses dropped 36.7-48.3 µm or the mRGCL volumes dropped to 0.495-0.613 mm3. CONCLUSION: The paediatric ON has best prognosis and young adult ON exhibits perfectly linear correlations of final vision and structural loss. The pRNFL and the mRGCL could be potential structural markers to predict the vision prognosis for varying-age ON patients.