Effector T Cells Abrogate Stroma-Mediated Chemoresistance in Ovarian Cancer.

Effector T cells and fibroblasts are major components in the tumor microenvironment. The means through which these cellular interactions affect chemoresistance is unclear. Here, we show that fibroblasts diminish nuclear accumulation of platinum in ovarian cancer cells, resulting in resistance to platinum-based chemotherapy. We demonstrate that glutathione and cysteine released by fibroblasts contribute to this resistance. CD8(+) T cells abolish the resistance by altering glutathione and cystine metabolism in fibroblasts. CD8(+) T-cell-derived interferon (IFN)γ controls fibroblast glutathione and cysteine through upregulation of gamma-glutamyltransferases and transcriptional repression of system xc(-) cystine and glutamate antiporter via the JAK/STAT1 pathway. The presence of stromal fibroblasts and CD8(+) T cells is negatively and positively associated with ovarian cancer patient survival, respectively. Thus, our work uncovers a mode of action for effector T cells: they abrogate stromal-mediated chemoresistance. Capitalizing upon the interplay between chemotherapy and immunotherapy holds high potential for cancer treatment.

Oxidative stress controls regulatory T cell apoptosis and suppressor activity and PD-L1-blockade resistance in tumor.

Live regulatory T cells (Treg cells) suppress antitumor immunity, but how Treg cells behave in the metabolically abnormal tumor microenvironment remains unknown. Here we show that tumor Treg cells undergo apoptosis, and such apoptotic Treg cells abolish spontaneous and PD-L1-blockade-mediated antitumor T cell immunity. Biochemical and functional analyses show that adenosine, but not typical suppressive factors such as PD-L1, CTLA-4, TGF-ß, IL-35, and IL-10, contributes to apoptotic Treg-cell-mediated immunosuppression. Mechanistically, apoptotic Treg cells release and convert a large amount of ATP to adenosine via CD39 and CD73, and mediate immunosuppression via the adenosine and A2A pathways. Apoptosis in Treg cells is attributed to their weak NRF2-associated antioxidant system and high vulnerability to free oxygen species in the tumor microenvironment. Thus, the data support a model wherein tumor Treg cells sustain and amplify their suppressor capacity through inadvertent death via oxidative stress. This work highlights the oxidative pathway as a metabolic checkpoint that controls Treg cell behavior and affects the efficacy of therapeutics targeting cancer checkpoints.

Parallel convolutional processing using an integrated photonic tensor core.

With the proliferation of ultrahigh-speed mobile networks and internet-connected devices, along with the rise of artificial intelligence (AI)1, the world is generating exponentially increasing amounts of data that need to be processed in a fast and efficient way. Highly parallelized, fast and scalable hardware is therefore becoming progressively more important2. Here we demonstrate a computationally specific integrated photonic hardware accelerator (tensor core) that is capable of operating at speeds of trillions of multiply-accumulate operations per second (1012 MAC operations per second or tera-MACs per second). The tensor core can be considered as the optical analogue of an application-specific integrated circuit (ASIC). It achieves parallelized photonic in-memory computing using phase-change-material memory arrays and photonic chip-based optical frequency combs (soliton microcombs3). The computation is reduced to measuring the optical transmission of reconfigurable and non-resonant passive components and can operate at a bandwidth exceeding 14 gigahertz, limited only by the speed of the modulators and photodetectors. Given recent advances in hybrid integration of soliton microcombs at microwave line rates3-5, ultralow-loss silicon nitride waveguides6,7, and high-speed on-chip detectors and modulators, our approach provides a path towards full complementary metal-oxide-semiconductor (CMOS) wafer-scale integration of the photonic tensor core. Although we focus on convolutional processing, more generally our results indicate the potential of integrated photonics for parallel, fast, and efficient computational hardware in data-heavy AI applications such as autonomous driving, live video processing, and next-generation cloud computing services.

Cancer SLC43A2 alters T cell methionine metabolism and histone methylation.

Abnormal epigenetic patterns correlate with effector T cell malfunction in tumours1-4, but the cause of this link is unknown. Here we show that tumour cells disrupt methionine metabolism in CD8+ T cells, thereby lowering intracellular levels of methionine and the methyl donor S-adenosylmethionine (SAM) and resulting in loss of dimethylation at lysine 79 of histone H3 (H3K79me2). Loss of H3K79me2 led to low expression of STAT5 and impaired T cell immunity. Mechanistically, tumour cells avidly consumed methionine and outcompeted T cells for methionine by expressing high levels of the methionine transporter SLC43A2. Genetic and biochemical inhibition of tumour SLC43A2 restored H3K79me2 in T cells, thereby boosting spontaneous and checkpoint-induced tumour immunity. Moreover, methionine supplementation improved the expression of H3K79me2 and STAT5 in T cells, and this was accompanied by increased T cell immunity in tumour-bearing mice and patients with colon cancer. Clinically, tumour SLC43A2 correlated negatively with T cell histone methylation and functional gene signatures. Our results identify a mechanistic connection between methionine metabolism, histone patterns, and T cell immunity in the tumour microenvironment. Thus, cancer methionine consumption is an immune evasion mechanism, and targeting cancer methionine signalling may provide an immunotherapeutic approach.

Magnetic Nanoparticles: Synthesis, Anisotropy, and Applications.

Anisotropy is an important and widely present characteristic of materials that provides desired direction-dependent properties. In particular, the introduction of anisotropy into magnetic nanoparticles (MNPs) has become an effective method to obtain new characteristics and functions that are critical for many applications. In this review, we first discuss anisotropy-dependent ferromagnetic properties, ranging from intrinsic magnetocrystalline anisotropy to extrinsic shape and surface anisotropy, and their effects on the magnetic properties. We further summarize the syntheses of monodisperse MNPs with the desired control over the NP dimensions, shapes, compositions, and structures. These controlled syntheses of MNPs allow their magnetism to be finely tuned for many applications. We discuss the potential applications of these MNPs in biomedicine, magnetic recording, magnetotransport, permanent magnets, and catalysis.

Observation of room-temperature polar skyrmions.

Complex topological configurations are fertile ground for exploring emergent phenomena and exotic phases in condensed-matter physics. For example, the recent discovery of polarization vortices and their associated complex-phase coexistence and response under applied electric fields in superlattices of (PbTiO3)n/(SrTiO3)n suggests the presence of a complex, multi-dimensional system capable of interesting physical responses, such as chirality, negative capacitance and large piezo-electric responses1-3. Here, by varying epitaxial constraints, we discover room-temperature polar-skyrmion bubbles in a lead titanate layer confined by strontium titanate layers, which are imaged by atomic-resolution scanning transmission electron microscopy. Phase-field modelling and second-principles calculations reveal that the polar-skyrmion bubbles have a skyrmion number of +1, and resonant soft-X-ray diffraction experiments show circular dichroism, confirming chirality. Such nanometre-scale polar-skyrmion bubbles are the electric analogues of magnetic skyrmions, and could contribute to the advancement of ferroelectrics towards functionalities incorporating emergent chirality and electrically controllable negative capacitance.

Toripalimab plus axitinib versus sunitinib as first-line treatment for advanced renal cell carcinoma: RENOTORCH, a randomized, open-label, phase III study.

BACKGROUND: Immune checkpoint inhibitors in combination with tyrosine kinase inhibitors are standard treatments for advanced clear cell renal cell carcinoma (RCC). This phase III RENOTORCH study compared the efficacy and safety of toripalimab plus axitinib versus sunitinib for the first-line treatment of patients with intermediate-/poor-risk advanced RCC. PATIENTS AND METHODS: Patients with intermediate-/poor-risk unresectable or metastatic RCC were randomized in a ratio of 1 : 1 to receive toripalimab (240 mg intravenously once every 3 weeks) plus axitinib (5 mg orally twice daily) or sunitinib [50 mg orally once daily for 4 weeks (6-week cycle) or 2 weeks (3-week cycle)]. The primary endpoint was progression-free survival (PFS) assessed by an independent review committee (IRC). The secondary endpoints were investigator-assessed PFS, overall response rate (ORR), overall survival (OS), and safety. RESULTS: A total of 421 patients were randomized to receive toripalimab plus axitinib (n = 210) or sunitinib (n = 211). With a median follow-up of 14.6 months, toripalimab plus axitinib significantly reduced the risk of disease progression or death by 35% compared with sunitinib as assessed by an IRC [hazard ratio (HR) 0.65, 95% confidence interval (CI) 0.49-0.86; P = 0.0028]. The median PFS was 18.0 months in the toripalimab-axitinib group, whereas it was 9.8 months in the sunitinib group. The IRC-assessed ORR was significantly higher in the toripalimab-axitinib group compared with the sunitinib group (56.7% versus 30.8%; P < 0.0001). An OS trend favoring toripalimab plus axitinib was also observed (HR 0.61, 95% CI 0.40-0.92). Treatment-related grade ≥3 adverse events occurred in 61.5% of patients in the toripalimab-axitinib group and 58.6% of patients in the sunitinib group. CONCLUSION: In patients with previously untreated intermediate-/poor-risk advanced RCC, toripalimab plus axitinib provided significantly longer PFS and higher ORR than sunitinib and had a manageable safety profile TRIAL REGISTRATION: ClinicalTrials.gov NCT04394975.

Shape Anisotropy-Governed High-Performance Nanomagnetosol for In Vivo Magnetic Particle Imaging of Lungs.

Caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has shown extensive lung manifestations in vulnerable individuals, putting lung imaging and monitoring at the forefront of early detection and treatment. Magnetic particle imaging (MPI) is an imaging modality, which can bring excellent contrast, sensitivity, and signal-to-noise ratios to lung imaging for the development of new theranostic approaches for respiratory diseases. Advances in MPI tracers would offer additional improvements and increase the potential for clinical translation of MPI. Here, a high-performance nanotracer based on shape anisotropy of magnetic nanoparticles is developed and its use in MPI imaging of the lung is demonstrated. Shape anisotropy proves to be a critical parameter for increasing signal intensity and resolution and exceeding those properties of conventional spherical nanoparticles. The 0D nanoparticles exhibit a 2-fold increase, while the 1D nanorods have a > 5-fold increase in signal intensity when compared to VivoTrax. Newly designed 1D nanorods displayed high signal intensities and excellent resolution in lung images. A spatiotemporal lung imaging study in mice revealed that this tracer offers new opportunities for monitoring disease and guiding intervention.

Metal-Organic Framework as a New Type of Magnetothermally-Triggered On-Demand Release Carrier.

The development of external stimuli-controlled payload systems has been sought after with increasing interest toward magnetothermally-triggered drug release (MTDR) carriers due to their non-invasive features. However, current MTDR carriers present several limitations, such as poor heating efficiency caused by the aggregation of iron oxide nanoparticles (IONPs) or the presence of antiferromagnetic phases which affect their efficiency. Herein, a novel MTDR carrier is developed using a controlled encapsulation method that fully fixes and confines IONPs of various sizes within the metal-organic frameworks (MOFs). This novel carrier preserves the MOF's morphology, porosity, and IONP segregation, while enhances heating efficiency through the oxidation of antiferromagnetic phases in IONPs during encapsulation. It also features a magnetothermally-responsive nanobrush that is stimulated by an alternating magnetic field to enable on-demand drug release. The novel carrier shows improved heating, which has potential applications as contrast agents and for combined chemo and magnetic hyperthermia therapy. It holds a great promise for magneto-thermally modulated drug dosing at tumor sites, making it an exciting avenue for cancer treatment.

Baryon Electric Charge Correlation as a Magnetometer of QCD.

The correlation between net baryon number and electric charge, χ_{11}^{BQ}, can serve as a magnetometer of QCD. This is demonstrated by lattice QCD computations using the highly improved staggered quarks with physical pion mass of M_{π}=135 MeV on N_{τ}=8 and 12 lattices. We find that χ_{11}^{BQ} along the transition line starts to increase rapidly with magnetic field strength eB≳2M_{π}^{2} and by a factor 2 at eB≃8M_{π}^{2}. Furthermore, the ratio of electric charge chemical potential to baryon chemical potential, µ_{Q}/µ_{B}, shows significant dependence on the magnetic field strength and varies from the ratio of electric charge to baryon number in the colliding nuclei in heavy ion collisions. These results can provide baselines for effective theory and model studies, and both χ_{11}^{BQ} and µ_{Q}/µ_{B} could be useful probes for the detection of magnetic fields in relativistic heavy ion collision experiments as compared with corresponding results from the hadron resonance gas model.

Experimental Limits on Solar Reflected Dark Matter with a New Approach on Accelerated-Dark-Matter-Electron Analysis in Semiconductors.

Recently a dark matter-electron (DM-electron) paradigm has drawn much attention. Models beyond the standard halo model describing DM accelerated by high energy celestial bodies are under intense examination as well. In this Letter, a velocity components analysis (VCA) method dedicated to swift analysis of accelerated DM-electron interactions via semiconductor detectors is proposed and the first HPGe detector-based accelerated DM-electron analysis is realized. Utilizing the method, the first germanium based constraint on sub-GeV solar reflected DM-electron interaction is presented with the 205.4 kg·day dataset from the CDEX-10 experiment. In the heavy mediator scenario, our result excels in the mass range of 5-15 keV/c^{2}, achieving a 3 orders of magnitude improvement comparing with previous semiconductor experiments. In the light mediator scenario, the strongest laboratory constraint for DM lighter than 0.1 MeV/c^{2} is presented. The result proves the feasibility and demonstrates the vast potential of the VCA technique in future accelerated DM-electron analyses with semiconductor detectors.

Cross-column density functional theory-based quantitative structure-retention relationship model development powered by machine learning.

Quantitative structure-retention relationship (QSRR) modeling has emerged as an efficient alternative to predict analyte retention times using molecular descriptors. However, most reported QSRR models are column-specific, requiring separate models for each high-performance liquid chromatography (HPLC) system. This study evaluates the potential of machine learning (ML) algorithms and quantum mechanical (QM) descriptors to develop QSRR models that can predict retention times across three different reversed-phase HPLC columns under varying conditions. Four machine learning methods-partial least squares (PLS) regression, ridge regression (RR), random forest (RF), and gradient boosting (GB)-were compared on a dataset of 360 retention times for 15 aromatic analytes. Molecular descriptors were calculated using density functional theory (DFT). Column characteristics like particle size and pore size and experimental conditions like temperature and gradient time were additionally used as descriptors. Results showed that the GB-QSRR model demonstrated the best predictive performance, with Q2 of 0.989 and root mean square error of prediction (RMSEP) of 0.749 min on the test set. Feature analysis revealed that solvation energy (SE), HOMO-LUMO energy gap (∆E HOMO-LUMO), total dipole moment (Mtot), and global hardness (η) are among the most influential predictors for retention time prediction, indicating the significance of electrostatic interactions and hydrophobicity. Our findings underscore the efficiency of ensemble methods, GB and RF models employing non-linear learners, in capturing local variations in retention times across diverse experimental setups. This study emphasizes the potential of cross-column QSRR modeling and highlights the utility of ML models in optimizing chromatographic analysis.

Predictive value of crossover sign for outcome of ultrasound-guided vacuum aspiration in women with Cesarean scar pregnancy.

OBJECTIVE: To examine the value of the crossover sign (COS) in predicting treatment outcome in women with a Cesarean scar pregnancy (CSP) who were treated with ultrasound-guided vacuum aspiration. METHODS: This was a retrospective cohort study of women with CSP who underwent ultrasound-guided vacuum aspiration. Based on the relationship between the gestational sac, Cesarean scar and anterior wall of the uterus, CSPs were classified by COS type. Analysis was conducted to investigate the association between COS type (COS-1, COS-2) and treatment outcome. The incidence of treatment failure, retained pregnancy tissue, secondary therapy and bleeding ≥ 200 mL were analyzed. RESULTS: In total, 181 eligible patients with CSP, including 90 (49.7%) women with COS-1 and 91 (50.3%) women with COS-2, were analyzed. COS-1 patients had a higher incidence of treatment failure compared with COS-2 patients (25.6% vs 8.8%; P = 0.003), as well as higher rates of retained pregnancy tissue (18.9% vs 6.6%; P = 0.013), secondary therapy (20.0% vs 6.6%; P = 0.002) and bleeding of ≥ 200 mL (13.3% vs 4.4%; P = 0.034). COS-1 and a large gestational sac (30.1-50.0 mm or >50.0 mm in diameter) were associated independently with increased risk of treatment failure (odds ratio, 4.57 (95% CI, 1.66-12.56); P = 0.003, 4.34 (95% CI, 1.35-13.94); P = 0.014 and 10.50 (95% CI, 2.54-43.46); P = 0.001, respectively). CONCLUSIONS: Ultrasound evaluation of the relationship between the gestational sac and the endometrial line (COS classification) in women with CSP may help to predict treatment outcome among those undergoing vacuum aspiration. Among COS-1 patients, especially those with a gestational sac diameter of >30.0 mm, vacuum aspiration may be discouraged. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Theoretical Study on Ethylamine Dissociation Reactions Using VRC-VTST and SS-QRRK Methods.

Barrierless bond dissociation reactions play an important role in fuel combustion. In this work, the pressure-dependent dissociation rate constants of ethylamine (EA) are accurately determined using variable-reaction-coordinate variational transition-state theory combined with the system-specific quantum Rice-Ramsperger-Kassel method. Before the kinetics calculations, the performances of four density functional theory methods in describing the bond dissociation of EA are evaluated against the benchmark method, FIC-MRCISD(T)+Q/cc-pVTZ, and the MN15-L/cc-pVTZ method is the best choice. By comparison of the Gibbs free energies and the rate constants for the bond dissociation reactions of EA, ethanol, and propane, the influence of functional groups on the reaction kinetics is discussed. The kinetics calculations show that the dissociation rate constants of EA are sensitive to pressure at low pressures and high temperatures, and the dominant channel is the reaction that yields C2H5 and NH2 radicals. A literature combustion model of EA is updated with our calculations, and the satisfactory agreement between the model predictions and reported ignition delay times of EA suggests the reliability of our calculations.

Relationship between fasting prior to contrast-enhanced CT and adverse reaction in patients with allergies history.

AIM: To examine the relationship between fasting prior to contrast-enhanced CT (CECT) and adverse reaction (AR) in patients with allergies history. MATERIALS AND METHODS: Patients with allergies history who underwent CECT from January 2014 to December 2020 (713 cases with iodinated contrast media (ICM)-related allergy history and 27045 cases with unrelated allergies history) were retrospectively analyzed. The occurrence of ICM-related AR and patient information were recorded. The relationship between fasting and AR and emetic complications was analyzed. RESULTS: There was no statistical difference in the overall incidence of AR and emetic complications between fasting group and non-fasting group (P>0.05) and fasting was not an influence factor for overall AR occurrence in patients with both ICM-related and unrelated allergies history. However, the incidence of severe AR in fasting group was higher than that in non-fasting group (P=0.01) in patients with unrelated allergies history. The AR incidence in fasting group was higher than that in non-fasting group (P=0.022) when receiving abdominal examinations in patients with unrelated allergies history. There was no statistical difference in the incidence of AR with different occurrence time between fasting group and non-fasting group (P>0.05) in patients with both ICM-related and unrelated allergies history. CONCLUSIONS: Fasting was associated with higher incidence of severe AR and was associated with higher AR incidence when receiving abdominal examinations in patients with unrelated allergies history. Fasting did not have effects on the occurrence time of AR in patients with allergies history. These provided new guidance for usage of ICM in patients with allergies history.

Multimodel habitats constructed by perfusion and/or diffusion MRI predict isocitrate dehydrogenase mutation status and prognosis in high-grade gliomas.

AIM: To determine whether tumour vascular and cellular heterogeneity of high-grade glioma (HGG) is predictive of isocitrate dehydrogenase (IDH) mutation status and overall survival (OS) by using tumour habitat-based analysis constructed by perfusion and/or diffusion magnetic resonance imaging (MRI). MATERIALS AND METHODS: Seventy-eight HGG patients that met the 2021 World Health Organization WHO Classification of Tumors of the Central Nervous System, 5th edition (WHO CNS5), were enrolled to predict IDH mutation status, of which 32 grade 4 patients with unmethylated O6-methylguanine-DNA methyltransferase (MGMT) promoter were enrolled for prognostic analysis. The deep-learning-based model nnU-Net and K-means clustering algorithm were applied to construct the Traditional Habitat, Vascular Habitat (VH), Cellular Density Habitat (DH), and their Combined Habitat (CH). Quantitative parameters were extracted and compared between IDH-mutant and IDH-wild-type patients, respectively, and the prediction potential was evaluated by receiver operating characteristic (ROC) curve analysis. OS was analysed using Kaplan-Meier survival analysis and the log-rank test. RESULTS: Compared with IDH-mutants, median relative cerebral blood volume (rCBVmedian) values in the whole enhancing tumour (WET), VH1, VH3, CH1-4 habitats were significantly increased in IDH-wild-type HGGs (all p<0.05). Additionally, the accuracy of rCBVmedian values in CH1 outperformed other habitats in identifying IDH mutation status (p<0.001) at a cut-off value of 4.83 with AUC of 0.815. Kaplan-Meier survival analysis highlighted significant differences in OS between the populations dichotomised by the median of rCBVmedian in WET, VH1, CH1-3 habitats (all p<0.05). CONCLUSIONS: The habitat imaging technique may improve the accuracy of predicting IDH mutation status and prognosis, and even provide a new direction for subsequent personalised precision treatment.

Systematic review and meta-analysis of the prognostic value of 18F-Fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) and/or computed tomography (CT)-based radiomics in head and neck cancer.

AIM: Radiomics involves the extraction of quantitative data from medical images to facilitate the diagnosis, prognosis, and staging of tumors. This study provides a comprehensive overview of the efficacy of radiomics in prognostic applications for head and neck cancer (HNC) in recent years. It undertakes a systematic review of prognostic models specific to HNC and conducts a meta-analysis to evaluate their predictive performance. MATERIALS AND METHODS: This study adhered rigorously to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines for literature searches. The literature databases, including PubMed, Embase, Cochrane, and Scopus were systematically searched individually. The methodological quality of the incorporated studies underwent assessment utilizing the radiomics quality score (RQS) tool. A random-effects meta-analysis employing the Harrell concordance index (C-index) was conducted to evaluate the performance of all radiomics models. RESULTS: Among the 388 studies retrieved, 24 studies encompassing a total of 6,978 cases were incorporated into the systematic review. Furthermore, eight studies, focusing on overall survival as an endpoint, were included in the meta-analysis. The meta-analysis revealed that the estimated random effect of the C-index for all studies utilizing radiomics alone was 0.77 (0.71-0.82), with a substantial degree of heterogeneity indicated by an I2 of 80.17%. CONCLUSIONS: Based on this review, prognostic modeling utilizing radiomics has demonstrated enhanced efficacy for head and neck cancers; however, there remains room for improvement in this approach. In the future, advancements are warranted in the integration of clinical parameters and multimodal features, balancing multicenter data, as well as in feature screening and model construction within this field.

Risk of metastasis and survival in patients undergoing different treatment strategies with T1 colonic neuroendocrine tumors.

PURPOSE: The efficacy and safety of local excision (LE) for small (< 1‒2 cm) colonic neuroendocrine tumors (NETs) is controversial due to the higher metastasis risk when compared with rectal NETs. The study aimed to evaluate the metastasis risk of T1 colonic NETs and compare patients' long-term prognosis after LE or radical surgery (RS). METHODS: The Surveillance Epidemiology and End Results database was used to identify patients with T1 colonic NETs (2004‒2015). Multivariable logistic regression was performed to assess factors associated with metastasis risk. Propensity score matching was used to balance the variables. Cancer-specific survival (CSS) and overall survival (OS) were calculated to estimate the prognosis of patients with T1N0M0 colonic NETs who underwent LE or RS. RESULTS: Of the 610 patients with colonic NETs, 46 (7.54%) had metastasis at diagnosis. Tumor size (11-20 mm) (OR = 9.51; 95% confidence interval (CI): 4.32‒21.45; P < 0.001), right colon (OR = 15.79; 95% CI 7.20‒38.56; P < 0.001), submucosal infiltration (OR = 2.08; 95% CI 0.84‒5.57; P = 0.125) were independent risk factors associated with metastasis. Of the 515 patients with T1N0M0 colonic NETs, the overall long-term prognosis of LE was as good as that of RS groups (after matching, 5-year CSS: 97.9% vs. 94.6%, P = 0.450; 5-year OS: 92.7% vs. 85.6%, P = 0.009). CONCLUSION: Tumor size (11‒20 mm) and site (right colon) are associated with metastasis in T1 colonic NETs. In the absence of metastasis, LE could be a viable option for 0‒10 mm T1 colonic NETs with well/moderate differentiation in the left colon in terms of long-term survival.

Competing risk nomogram and risk classification system for evaluating overall and cancer-specific survival in neuroendocrine carcinoma of the cervix: a population-based retrospective study.

OBJECTIVE: Neuroendocrine carcinoma of the cervix (NECC) is a rare malignancy with poor clinical prognosis due to limited therapeutic options. This study aimed to establish a risk-stratification score and nomogram models to predict prognosis in NECC patients. METHODS: Data on individuals diagnosed with NECC between 2000 and 2019 were retrieved from the Surveillance Epidemiology and End Results (SEER) database and then randomly classified into training and validation cohorts (7:3). Univariate and multivariate Cox regression analyses evaluated independent indicators of prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis further assisted in confirming candidate variables. Based on these factors, cancer-specific survival (CSS) and overall survival (OS) nomograms that predict survival over 1, 3, and 5 years were constructed. The receiver operating characteristic (ROC) curve, the concordance index (C-index), and the calibration curve estimated the precision and discriminability of the competing risk nomogram for both cohorts. Finally, we assessed the clinical value of the nomograms using decision curve analysis (DCA). RESULTS: Data from 2348 patients were obtained from the SEER database. Age, tumor stage, T stage, N stage, chemotherapy, radiotherapy, and surgery predicted OS. Additionally, histological type was another standalone indicator of CSS prognosis. For predicting CSS, the C-index was 0.751 (95% CI 0.731 ~ 0.770) and 0.740 (95% CI 0.710 ~ 0.770) for the training and validation cohorts, respectively. Furthermore, the C-index in OS prediction was 0.757 (95% CI 0.738 ~ 0.776) and 0.747 (95% CI 0.718 ~ 0.776) for both cohorts. The proposed model had an excellent discriminative ability. Good accuracy and discriminability were also demonstrated using the AUC and calibration curves. Additionally, DCA demonstrated the high clinical potential of the nomograms for CSS and OS prediction. We constructed a corresponding risk classification system using nomogram scores. For the whole cohort, the median CSS times for the low-, moderate-, and high-risk groups were 59.3, 19.5, and 7.4 months, respectively. CONCLUSION: New competing risk nomograms and a risk classification system were successfully developed to predict the 1-, 3-, and 5-year CSS and OS of NECC patients. The models are internally accurate and reliable and may guide clinicians toward better clinical decisions and the development of personalized treatment plans.

Correlation of lipocalin 2 and glycolipid metabolism and body composition in a large cohort of children with osteogenesis imperfecta.

PURPOSE: Lipocalin 2 (LCN2) is a newly recognized bone-derived factor that is important in regulation of energy metabolism. We investigated the correlation of serum LCN2 levels and glycolipid metabolism, and body composition in a large cohort of patients with osteogenesis imperfecta (OI). METHODS: A total of 204 children with OI and 66 age- and gender-matched healthy children were included. Circulating levels of LCN2 and osteocalcin were measured by enzyme-linked immunosorbent assay. Serum levels of fasting blood glucose (FBG), triglyceride (TG), total cholesterol (TC), and low- and high-density lipoprotein cholesterol (LDL-C, HDL-C) were measured by automated chemical analyzers. The body composition was measured by dual-energy X-ray absorptiometry. Grip strength and timed-up-and-go (TUG) were tested to evaluate the muscle function. RESULTS: Serum LCN2 levels were 37.65 ± 23.48 ng/ml in OI children, which was significantly lower than those in healthy control (69.18 ± 35.43 ng/ml, P < 0.001). Body mass index (BMI) and serum FBG level were significantly higher and HDL-C levels were lower in OI children than healthy control (all P < 0.01). Grip strength was significantly lower (P < 0.05), and the TUG was significantly longer in OI patients than healthy control (P < 0.05). Serum LCN2 level was negatively correlated to BMI, FBG, HOMA-IR, HOMA-ß, total body, and trunk fat mass percentage, and positively correlated to total body and appendicular lean mass percentage (all P < 0.05). CONCLUSIONS: Insulin resistance, hyperglycemia, obesity, and muscle dysfunction are common in OI patients. As a novel osteogenic cytokine, LCN2 deficiency may be relevant to disorders of glucose and lipid metabolism, and dysfunction of muscle in OI patients.