TAPI-1 Exhibits Anti-tumor Efficacy in Human Esophageal Squamous Cell Carcinoma Cells via Suppression of NF-κB Signaling Pathway.

BACKGROUND: TNF-α processing inhibitor-1 (TAPI-1) is a known metalloproteinase inhibitor with potential anti-inflammatory effects. However, its anti-cancer effects on esophageal squamous cell carcinoma (ESCC) have not been uncovered. AIM: In the present study, the effects of TAPI-1 on ESCC cell viability, migration, invasion, and cisplatin resistance and the underlying molecular mechanisms were investigated in TE-1 and Eca109 cells. METHODS: To this end, TE-1 and Eca109 cells were exposed to TAPI-1 for indicated time intervals. Cell viability was assessed using cell counting kit-8 assay and apoptosis was evaluated using flow cytometry assay. Migration and invasion were assessed using Transwell assays. Gene expressions were analyzed using quantitative reverse transcription polymerase chain reaction. The activation of NF-κB signaling pathway was elucidated via Western blot and chromatin immunoprecipitation assay. RESULTS: We observed that higher doses (10, 20 µM) of TAPI-1 inhibited ESCC cell viability, while a lower dose (5 µM) of TAPI-1 inhibited ESCC cell migration and invasion and enhanced the chemosensitivity of ESCC cells to cisplatin. Moreover, TAPI-1 suppressed the activation of NF-κB signaling and the target genes expression in the stage of transcription initiation. Furthermore, blocking NF-κB signaling in advance could abolish all the effects of TAPI-1 on ESCC cells. CONCLUSION: Overall, these results indicated that TAPI-1 impairs ESCC cell viability, migration, and invasion and facilitates cisplatin-induced apoptosis via suppression of NF-κB signaling pathway. TAPI-1 may serve as a potential adjuvant agent with cisplatin for ESCC therapy.

Extraction of the Parton Momentum-Fraction Dependence of Generalized Parton Distributions from Exclusive Photoproduction.

The x dependence of hadrons' generalized parton distributions (GPDs) F(x,ξ,t) is the most difficult to extract from the existing known processes, while the ξ and t dependence are uniquely determined by the kinematics of the scattered hadron. We study the single diffractive hard exclusive processes for extracting GPDs in the photoproduction. We demonstrate quantitatively the enhanced sensitivity on extracting the x dependence of various GPDs from the photoproduction cross sections, as well as the asymmetries constructed from photon polarization and hadron spin that could be measured at JLab Hall D by GlueX Collaboration and future facilities.

An Artificial Intelligence Platform for the Radiologic Diagnosis of Pulmonary Sarcoidosis: An Initial Pilot Study of Chest Computed Tomography Analysis to Distinguish Pulmonary Sarcoidosis from a Negative Lung Cancer Screening Scan.

PURPOSE: To determine the reliability of an artificial intelligence, deep learning (AI/DL)-based method of chest computer tomography (CT) scan analysis to distinguish pulmonary sarcoidosis from negative lung cancer screening chest CT scans (Lung Imaging Reporting and Data System score 1, Lung-RADS score 1). METHODS: Chest CT scans of pulmonary sarcoidosis were evaluated by a clinician experienced with sarcoidosis and a chest radiologist for clinical and radiologic evidence of sarcoidosis and exclusion of alternative or concomitant pulmonary diseases. The AI/DL based method used an ensemble network architecture combining Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). The method was applied to 126 pulmonary sarcoidosis and 96 Lung-RADS score 1 CT scans. The analytic approach of training and validation of the AI/DL method used a fivefold cross-validation technique, where 4/5th of the available data set was used to train a diagnostic model and tested on the remaining 1/5th of the data set, and repeated 4 more times with non-overlapping validation/test data. The probability values were used to generate Receiver Operating Characteristic (ROC) curves to assess the model's discriminatory power. RESULTS: The sensitivity, specificity, positive and negative predictive value of the AI/DL method for the 5 folds of the training/validation sets and the entire set of CT scans were all over 94% to distinguish pulmonary sarcoidosis from LUNG-RADS score 1 chest CT scans. The area under the curve for the corresponding ROC curves were all over 97%. CONCLUSION: This AL/DL model shows promise to distinguish sarcoidosis from alternative pulmonary conditions using minimal radiologic data.

CircDUSP22 Overexpression Restrains Pancreatic Cancer Development via Modulating miR-1178-3p and Downstream BNIP3.

Aberrant expression of circular RNAs (circRNAs) is important in carcinogenesis, however, many differentially expressed circRNAs have not been functionally characterized. This study aimed to unveil the role of circRNA-dual specificity phosphatase 22 (circDUSP22) in pancreatic cancer (PaCa). Expression analyses of circDUSP22, miR-1178-3p and BCL2 interacting protein 3 (BNIP3) were carried out using quantitative real-time PCR (qRT-PCR) or western blotting. Cell growth was assessed by MTT, EdU and colony formation assays. Cell cycle distribution and cell apoptosis were investigated using flow cytometry assay. The assumed binding relationship between miR-1178-3p and circDUSP22 or BNIP3 was testified by dual-luciferase reporter and pull-down assays. The effect of circDUSP22 in vivo was identified by animal studies. The decreased expression of circDUSP22 was observed in PaCa samples and cells. CircDUSP22 ectopic expression in vitro blocked PaCa cell proliferation, arrested cell cycle and provoked cell apoptosis. CircDUSP22 targeted miR-1178-3p, whose expression was reinforced in PaCa. The inhibitory cell growth caused by circDUSP22 ectopic expression was reversed by miR-1178-3p enrichment. In addition, miR-1178-3p targeted BNIP3, whose expression was declined in PaCa. The inhibitory cell growth caused by circDUSP22 ectopic expression was reversed by BNIP3 knockdown. CircDUSP22 overexpression in vivo decelerated tumor growth. CircDUSP22 upregulation blocked PaCa development partly by targeting miR-1178-3p and increasing BNIP3, implying the potential implication of circDUSP22 in targeted therapy of PaCa.

Secondary primary lung cancer after esophageal cancer: a population-based study of 44,172 patients.

BACKGROUND: The present study aimed to assess the survival, incidence, and characteristics of secondary primary lung cancer (SPLC) after esophageal cancer (EC-LC). METHODS: The patients with esophageal cancer (EC) who developed SPLC and patients with first primary lung cancer (LC-1) were retrospectively reviewed in the Surveillance, Epidemiology, and End Results 18 registries covering 2000-2016. Overall survival and characteristics were compared between patients with EC-LC and patients with LC-1. The independent relation between a history of EC and death was evaluated by calculating hazard ratios in multivariate Cox regression analysis propensity score-matching analysis, and multiple imputation for cases with missing information. RESULTS: In comparison with the general population, the patients with EC had a higher risk for developing secondary primary lung cancer (SIR =1.86, 95% confidence interval (CI): 1.69-2.05). A history of EC was found to be an independent risk factor of death for lung squamous carcinoma (LUSC) and lung adenocarcinoma (LUAD) patients in localized stage based on multivariate Cox regression analysis, propensity score-matching analysis and multiple imputation. CONCLUSIONS: There is a significantly increased risk of secondary primary lung cancer in EC survivors and a history of EC adversely affects overall survival in individuals who subsequently develop localized LUSC and LUAD. Clinicians should moderately strengthen lung tissue protection during the management of EC patients.

Extraction of Next-to-Next-to-Leading-Order Parton Distribution Functions from Lattice QCD Calculations.

We present for the first time complete next-to-next-to-leading-order coefficient functions to match flavor nonsinglet quark correlation functions in position space, which are calculable in lattice QCD, to parton distribution functions (PDFs). Using PDFs extracted from experimental data and our calculated matching coefficients, we predict valence-quark correlation functions that can be confronted by lattice QCD calculations. The uncertainty of our predictions is greatly reduced with higher order matching coefficients. By performing Fourier transformation, we also obtain matching coefficients for corresponding quasi-PDFs and pseudo-PDFs. Our method of calculations can be readily generalized to evaluate the matching coefficients for sea-quark and gluon correlation functions, making the program to extract partonic structure of hadrons from lattice QCD calculations comparable with and complementary to that from experimental measurements.

MiR-221-3p as a Potential Biomarker for Patients with Psoriasis and Its Role in Inflammatory Responses in Keratinocytes.

INTRODUCTION: This study investigated serum miR-221-3p levels in psoriatic patients and the characterization of serum miR-221-3p in keratinocyte inflammatory responses was further assessed. METHODS: qRT-PCR was used to detect the expression level of miR-221-3p in the serum of 46 patients with psoriasis and 42 healthy controls. The receiver operating characteristic curve evaluated the diagnostic ability of miR-221-3p in psoriasis. The effect of miR-221-3p on HaCaT cell proliferation was detected by using a cell counting Kit-8 and Transwell. ELISA was used to detect serum and keratinocyte pro-inflammatory factors. RESULTS: miR-221-3p was significantly increased in the serum of patients with psoriasis. The area under the curve was 0.861, the sensitivity was 80.4%, and the specificity was 85.7%. Serum miR-221-3p was positively correlated with the expression levels of tumor necrosis factor-α, interleukin (IL)-17A, and IL-22. Cell experiments showed that reducing the expression of miR-221-3p could significantly inhibit cell proliferation. Additionally, miR-221-3p downregulation also inhibited the release of some inflammatory factors in the HaCaT cells. DISCUSSION/CONCLUSION: MiR-221-3p is a latent biomarker of psoriasis patients. Lower expression of miR-221-3p inhibits the cell proliferation and inflammatory responses of HaCaT cells, which offers a possible target for the therapeutic interventions of psoriasis.

Factorization of Jet Cross Sections in Heavy-Ion Collisions.

We propose a new phenomenological approach to establish QCD factorization of jet cross sections in the heavy-ion environment. Starting from a factorization formalism in proton-proton collisions, we introduce medium modified jet functions to capture the leading interaction of jets with the hot and dense QCD medium. A global analysis using a Monte Carlo sampling approach is performed in order to reliably determine the new jet functions from the nuclear modification factor of inclusive jets at the LHC. We find that gluon jets are significantly more suppressed due to the presence of the medium than quark jets. In addition, we observe that the jet radius dependence is directly related to the relative suppression of quark and gluon jets. Our approach may help to improve the extraction of medium properties from data.

Multiplicative Renormalizability of Operators defining Quasiparton Distributions.

Extracting parton distribution functions (PDFs) from lattice QCD calculation of quasi-PDFs has been actively pursued in recent years. We extend our proof of the multiplicative renormalizability of the quasiquark operators of Ishikawa et al. [Phys Rev. D 96, 094019 (2017)] to quasigluon operators, and demonstrated that quasigluon operators could be multiplicatively renormalized to all orders in perturbation theory, without mixing with other operators. We find that using a gauge-invariant UV regulator is essential for achieving this proof. With the multiplicative renormalizability of both quasiquark and quasigluon operators, and QCD collinear factorization of hadronic matrix elements of there operators into PDFs, extracting PDFs from lattice QCD calculated hadronic matrix elements of quasiparton operators could have a solid theoretical foundation.

Exploring Partonic Structure of Hadrons Using ab initio Lattice QCD Calculations.

Following our previous proposal, we construct a class of good "lattice cross sections" (LCSs), from which we can study the partonic structure of hadrons from ab initio lattice QCD calculations. These good LCSs, on the one hand, can be calculated directly in lattice QCD, and on the other hand, can be factorized into parton distribution functions (PDFs) with calculable coefficients, in the same way as QCD factorization for factorizable hadronic cross sections. PDFs could be extracted from QCD global analysis of the lattice QCD generated data of LCSs. We also show that the proposed functions for lattice QCD calculation of PDFs in the literature are special cases of these good LCSs.

J/ψ Production and Polarization within a Jet.

We study the production and polarization of J/ψ mesons within a jet in proton-proton collisions at the LHC. We define the J/ψ-jet fragmentation function as a ratio of differential jet cross sections with and without the reconstructed J/ψ in the jet. We demonstrate that this is a very useful observable to help explore the J/ψ production mechanism, and to differentiate between different nonrelativistic QCD global fits based on inclusive J/ψ cross sections. Furthermore, we propose to measure the polarization of J/ψ mesons inside the jet, which can provide even more stringent constraints for the heavy quarkonium production mechanism.

Factorized power expansion for high-pT heavy quarkonium production.

We show that when the factorized cross section for heavy quarkonium production includes next-to-leading power contributions associated with the production of the heavy quark pair at short distances, it naturally reproduces all high p(T) results calculated in nonrelativistic QCD (NRQCD) factorization. This extended formalism requires fragmentation functions for heavy quark pairs, as well as for light partons. When these fragmentation functions are themselves calculated using NRQCD, we find that two of the four leading NRQCD production channels, (3)S(1)([1]) and (1)S(0)([8]), are dominated by the next-to-leading power contributions for a very wide p(T) range. The large next-to-leading order corrections of NRQCD are absorbed into the leading order of the first power correction. The impact of this finding on heavy quarkonium production and its polarization is discussed.

Clinicopathological, metastatic and prognostic features of stage IV esophageal adenocarcinoma versus squamous cell carcinoma: a SEER database analysis.

BACKGROUND: It is important to note that although the current treatment for advanced esophageal cancer (EC) has made great technological advances, patients' 5-year survival rates do not appear to be encouraging. Therefore, understanding the clinicopathological features and metastasis patterns of the patients with stage IV EC, combined with the prognosis of these patients, can aid in choosing the optimal treatment plan. It is well known that esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) are the two most common pathological types. The aim of this study is to examine and compare the clinicopathological features and metastatic modes of stage IV ESCC and EAC, as well as their prognosis and survival. METHODS: Based on the Surveillance, Epidemiology, and End Results (SEER) database, we assessed the characteristics of ESCCs and EACs associated with prognosis using the Kaplan-Meier survival analysis, and the Cox regression model. Furthermore, the clinical data of 217 patients with stage IV ESCC and EAC in the Department of Gastroenterology of the Second Affiliated Hospital of Nantong University between 2014 and 2016 were reviewed. RESULTS: A total of 3,707 cases treated between 2010 and 2016 were included. The incidence of EAC in the United States is much higher than that of ESCC. Common metastasis patterns were lungs only, liver only, bones only, and lung & liver. The multivariate Cox analysis showed that treatment mode and metastasis patterns were independent risk factors affecting the overall survival (OS) time of patients (stage IV ESCC & EAC). EAC patients with only lung metastases may have a longer survival if chose treatment options that included surgery. In the external cohort, a total of 217 cases were included. The prevalence of ESCC is much higher than that of EAC, and the common metastasis patterns are liver only, lung only, and liver & lung. The multivariate Cox analysis showed that treatment mode was independent risk factor affecting the OS time of patients (stage IV ESCC & EAC). EAC patients treated with surgery combined with chemoradiotherapy may have a better prognosis. CONCLUSIONS: In general, the prognosis of patients with stage IV ESCC and EAC are poor. However, surgery was found to significantly improve the OS time of patients with stage IV EAC in this study.

A Multichannel CT and Radiomics-Guided CNN-ViT (RadCT-CNNViT) Ensemble Network for Diagnosis of Pulmonary Sarcoidosis.

Pulmonary sarcoidosis is a multisystem granulomatous interstitial lung disease (ILD) with a variable presentation and prognosis. The early accurate detection of pulmonary sarcoidosis may prevent progression to pulmonary fibrosis, a serious and potentially life-threatening form of the disease. However, the lack of a gold-standard diagnostic test and specific radiographic findings poses challenges in diagnosing pulmonary sarcoidosis. Chest computed tomography (CT) imaging is commonly used but requires expert, chest-trained radiologists to differentiate pulmonary sarcoidosis from lung malignancies, infections, and other ILDs. In this work, we develop a multichannel, CT and radiomics-guided ensemble network (RadCT-CNNViT) with visual explainability for pulmonary sarcoidosis vs. lung cancer (LCa) classification using chest CT images. We leverage CT and hand-crafted radiomics features as input channels, and a 3D convolutional neural network (CNN) and vision transformer (ViT) ensemble network for feature extraction and fusion before a classification head. The 3D CNN sub-network captures the localized spatial information of lesions, while the ViT sub-network captures long-range, global dependencies between features. Through multichannel input and feature fusion, our model achieves the highest performance with accuracy, sensitivity, specificity, precision, F1-score, and combined AUC of 0.93 ± 0.04, 0.94 ± 0.04, 0.93 ± 0.08, 0.95 ± 0.05, 0.94 ± 0.04, and 0.97, respectively, in a five-fold cross-validation study with pulmonary sarcoidosis (n = 126) and LCa (n = 93) cases. A detailed ablation study showing the impact of CNN + ViT compared to CNN or ViT alone, and CT + radiomics input, compared to CT or radiomics alone, is also presented in this work. Overall, the AI model developed in this work offers promising potential for triaging the pulmonary sarcoidosis patients for timely diagnosis and treatment from chest CT.

Elevated NDC1 expression predicts poor prognosis and correlates with immunity in hepatocellular carcinoma.

Background: NDC1 was identified to be a tumor-promoting factor in non-small cell lung cancer and cervical cancer. However, no report had clarified the relationship between NDC1 and hepatocellular carcinoma (HCC). In this paper, we explored the expression and potential functions of NDC1 in HCC for the first time through the rational application of bioinformatics and relevant basic experiments. Methods: NDC1-related expression profiles and clinical data of HCC patients were collected from The Cancer Genome Atlas (TCGA) database, which were verified via quantitative real-time polymerase chain reaction (qRT-PCR), immunohistochemistry and the Clinical Proteomic Tumor Analysis Consortium (CPTAC) database. Univariate and multivariate Cox regression analyses were used to identify NDC1 as an independent factor for HCC prognosis, and NDC1-related signaling pathways were determined by gene set enrichment analysis (GSEA). Furthermore, we deeply probed the potential links of NDC1 to immunity and immune response. Finally, the bioeffects and underlying mechanisms of ectopic NDC1 overexpression and depletion were determined in HepG2 cells by immunoblotting, flow cytometry, Cell-Counting-Kit-8 (CCK-8), and EDU (5-Ethynyl-2'-deoxyuridine). Results: Up-regulated expression of NDC1 was detected by means of the TCGA database, which was consistent with the results obtained from further qRT-PCR, immunohistochemistry and the CPTAC database. Kaplan-Meier (K-M) survival analysis revealed a worse prognosis in HCC patients with high NDC1 expression. Besides, NDC1 was certified to be closely linked to tumor histologic grade, clinical stage and T stage. Moreover, univariate and multivariate Cox regression analyses defined NDC1 as an independent element for HCC prognosis. NDC1-related signaling pathways, utilizing GSEA analysis, were subsequently found out. What's more, NDC1 expression was detected to be enormously associated with microsatellite instability (MSI), immune cell infiltration, immune checkpoint molecules and immune cell pathways. As for immunotherapy, we discovered that different risk groups tended to have different immune checkpoint inhibitor responses, which indicated crucial implication value of NDC1 for HCC immunotherapy. More interestingly, we observed that the overexpression of NDC1 could promote the migration and invasion of HCC cells. Conclusions: Our article demonstrated that NDC1 might serve as a valuable predictor in the prognosis and immunotherapy of HCC. NDC1 played an oncogenic role in HCC.

Heavy quarkonium production and polarization.

We present a perturbative QCD factorization formalism for the production of heavy quarkonia of large transverse momentum p(T) at collider energies, which includes both the leading-power (LP) and next-to-leading-power (NLP) contributions to the cross section in the m(Q)(2)/p(T)(2) expansion for heavy quark mass m(Q). We estimate fragmentation functions in the nonrelativistic QCD formalism and reproduce the bulk of the large enhancement found in explicit next-to-leading-order calculations in the color-singlet model. Heavy quarkonia produced from NLP channels prefer longitudinal polarization.

Automatic Hemorrhage Detection From Color Doppler Ultrasound Using a Generative Adversarial Network (GAN)-Based Anomaly Detection Method.

Hemorrhage control has been identified as a priority focus area both for civilian and military populations in the United States because exsanguination is the most common cause of preventable death in hemorrhagic injury. Non-compressible torso hemorrhage (NCTH) has high mortality rate and there are currently no broadly available therapies for NCTH outside of a surgical room environment. Novel therapies, which include High Intensity Focused Ultrasound (HIFU) have emerged as promising methods for hemorrhage control as they can non-invasively cauterize bleeding tissue deep within the body without injuring uninvolved regions. A major challenge in the application of HIFU with color Doppler US guidance is the interpretation and optimization of the blood flow images in real-time to identify the hemorrhagic focus. Today, this task requires an expert sonographer, limiting the utility of this therapy in non-clinical environments. In this work, we investigated the feasibility of an automated hemorrhage detection method using a Generative Adversarial Network (GAN) for anomaly detection that learns a manifold of normal blood flow variability and subsequently identifies anomalous flow patterns that fall outside the learned manifold. As an initial feasibility study, we collected ultrasound color Doppler images of femoral arteries in an animal model of vascular injury (N = 11 pigs). Velocity information of the blood flow were extracted from the color Doppler images that were used for training and testing the anomaly detection network. Normotensive images from 8 pigs were used for training, and testing was performed on normotensive, immediately after injury, 10 minutes post-injury and 30 minutes post-injury images from 3 other pigs. The residual images or the reconstructed error maps show promise in detecting hemorrhages with an AUC of 0.90, 0.87, 0.62 immediately, 10 minutes post-injury and 30 minutes post-injury respectively with an overall AUC of 0.83.

Probing gluonic spin-orbit correlations in photon pair production.

We consider photon pair production in hadronic collisions at large mass and small transverse momentum of the pair, assuming that factorization in terms of transverse-momentum dependent parton distributions applies. The unpolarized cross section is found to have azimuthal angular dependencies that are generated by a gluonic version of the Boer-Mulders function. In addition, the single transversely polarized cross section is sensitive to the gluon Sivers function. We present simple numerical estimates for the Boer-Mulders and Sivers effects in diphoton production at RHIC and find that the process would offer unique opportunities for exploring transverse-momentum dependent gluon distributions.

ADAM17 and NF-κB p65 form a positive feedback loop that facilitates human esophageal squamous cell carcinoma cell viability.

A Disintegrin and metalloproteinase 17 (ADAM17) was proposed to cooperate with NF-κB p65, promoting tumorigenesis and progression of several human cancers. However, the role of ADAM17 remains unknown in human esophageal squamous cell carcinoma (ESCC). In this study, gene expression analyses and cell viability assays suggested that knockdown of ADAM17 suppressed ESCC cell viability. Gene expression analyses and ChIP-qPCR revealed that NF-κB p65 positively regulated ADAM17 expression by binding to the ADAM17 promoter. Rescue experiments showed that overexpression of ADAM17 in NF-κB p65-depleted ESCC cells restored cell viability. In addition, western blot analyses and ChIP-qPCR indicated that ADAM17 was responsible for the persistent activation of NF-κB p65 and contributed to ADAM17 expression in ESCC cells. In conclusion, we propose that ADAM17-activated NF-κB p65 signaling positively regulates ADAM17 expression, and facilitates ESCC cell viability.

Testing the time-reversal modified universality of the Sivers function.

We derive the time-reversal modified universality for both quark and gluon Sivers functions from the parity and time-reversal invariance of QCD. We calculate the single transverse-spin asymmetry of inclusive lepton from the decay of W bosons in polarized proton-proton collision at the Brookhaven National Laboratory Relativistic Heavy Ion Collider (RHIC), in terms of the Sivers function. We find that, although the asymmetry is diluted from the W decay, the lepton asymmetry is at the level of several percent and is measurable for a good range of lepton rapidity at RHIC. We argue that this measurable lepton asymmetry at RHIC is an excellent observable for testing the time-reversal modified universality of the Sivers function.