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.
BACKGROUND: Long coronavirus disease (COVID) after COVID-19 infection is continuously threatening the health of people all over the world. Early prediction of the risk of Long COVID in hospitalized patients will help clinical management of COVID-19, but there is still no reliable and effective prediction model. METHODS: A total of 1905 hospitalized patients with COVID-19 infection were included in this study, and their Long COVID status was followed up 4-8 weeks after discharge. Univariable and multivariable logistic regression analysis were used to determine the risk factors for Long COVID. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%), and factors for constructing the model were screened using Lasso regression in the training cohort. Visualize the Long COVID risk prediction model using nomogram. Evaluate the performance of the model in the training and validation cohort using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 657 patients (34.5%) reported that they had symptoms of long COVID. The most common symptoms were fatigue or muscle weakness (16.8%), followed by sleep difficulties (11.1%) and cough (9.5%). The risk prediction nomogram of age, diabetes, chronic kidney disease, vaccination status, procalcitonin, leukocytes, lymphocytes, interleukin-6 and D-dimer were included for early identification of high-risk patients with Long COVID. AUCs of the model in the training cohort and validation cohort are 0.762 and 0.713, respectively, demonstrating relatively high discrimination of the model. The calibration curve further substantiated the proximity of the nomogram's predicted outcomes to the ideal curve, the consistency between the predicted outcomes and the actual outcomes, and the potential benefits for all patients as indicated by DCA. This observation was further validated in the validation cohort. CONCLUSIONS: We established a nomogram model to predict the long COVID risk of hospitalized patients with COVID-19, and proved its relatively good predictive performance. This model is helpful for the clinical management of long COVID.
COVID-19 , Nomograms , SARS-CoV-2 , Humans , COVID-19/epidemiology , COVID-19/complications , COVID-19/diagnosis , Male , Female , Middle Aged , Prognosis , Risk Factors , Cohort Studies , Aged , Adult , Hospitalization/statistics & numerical data , Risk Assessment , Post-Acute COVID-19 Syndrome
The plateau phase transition in quantum anomalous Hall (QAH) insulators corresponds to a quantum state wherein a single magnetic domain gives way to multiple domains and then reconverges back to a single magnetic domain. The layer structure of the sample provides an external knob for adjusting the Chern number C of the QAH insulators. Here, we employ molecular beam epitaxy to grow magnetic topological insulator multilayers and realize the magnetic field-driven plateau phase transition between two QAH states with odd Chern number change ΔC. We find that critical exponents extracted for the plateau phase transitions with ΔC = 1 and ΔC = 3 in QAH insulators are nearly identical. We construct a four-layer Chalker-Coddington network model to understand the consistent critical exponents for the plateau phase transitions with ΔC = 1 and ΔC = 3. This work will motivate further investigations into the critical behaviors of plateau phase transitions with different ΔC in QAH insulators.
BACKGROUND: The metabolic or proliferative abnormalities that are characteristic of tumor cells can lead to abnormal fibrinolysis or coagulation system activity, with certain tumors exhibiting hypercoagulability or existing in a fibrinolytic state. However, the utility of biomarkers of coagulation and fibrinolysis when seeking to differentiate between benign gallbladder disease and malignant gallbladder tumors remains uncertain. METHODS: This study included a total of 81 patients with benign gallbladder polyps and 94 patients with malignant gallbladder tumors. Pre-biopsy or pretreatment levels of PT, APTT, FIB, D-dimer, FDP, PLT, PIC, TAT, TM, and t-PAIC from these patients were compared using Mann-Whitney tests. The baseline data of the patients were analyzed using chi-square tests, and the diagnostic utility of these biomarkers in distinguishing between benign and malignant gallbladder lesions was evaluated using ROC curves, and Spearman correlation analysis was employed to assess the correlation between these indicators and tumor parameters. RESULTS: The average age of malignant gallbladder tumor group was higher than benign gallbladder polyp group. And the base line analysis showed that there was a statistic difference in age, history of smoking, drinking, biliary tract disease, BMI of over weight between these two groups. In patients with malignant gallbladder tumors, FIB, D-dimer, FDP, PIC, TAT, TM, and t-PAIC levels were significantly elevated relative to those in patients affected by benign gallbladder polyp. The AUC for FIB, D-dimer, and FDP was 0.8469, 0.6514, 0.5950, while for PIC, TAT, TM, t-PAIC and four biomarker combined diagnosed was 0.8455, 0.6554, 0.7130, 0.6806, and 0.8859. Among these, TM was associated with the vascular invasion of tumor patients; TAT and t-PAIC were associated with neural invasion; D-dimer and FDP were related to the maximum tumor diameter; and FDP had a certain correlation with the tumor stage. CONCLUSIONS: In gallbladder tumor patients, conventional coagulation metrics like FIB, D-dimer, and FDP, as well as newer thrombotic indicators such as PIC, TAT, TM, and t-PAIC, were obviously increased. Correlations with tumor parameters suggested their potential as biomarkers to distinguish benign from malignant gallbladder growths.
Magnetoelectric materials, which encompass coupled magnetic and electric polarizabilities within a single phase, hold great promises for magnetic controlled electronic components or electric-field controlled spintronics. However, the realization of ideal magnetoelectric materials remains tough due to the inborn competion between ferroelectricity and magnetism in both levels of symmetry and electronic structure. Herein, we introduce a methodology for constructing single phase paramagnetic ferroelectric molecule [TMCM][FeCl4], which shows low-magnetic-field magnetoelectricity at room temperature. By applying a low magnetic field (≤1 kOe), the halogen Clâ§â§â§Cl distance and the volume of [FeCl4]- anions could be manipulated. This structural change causes a characteristic magnetostriction hysteresis, resulting in a substantial deformation of ~10-4 along the a-axis under an in-plane magnetic field of 2 kOe. The magnetostrictive effect is further qualitatively simulated by density functional theory calculations. Furthermore, this mechanical deformation significantly dampens the ferroelectric polarization by directly influencing the overall dipole configuration. As a result, it induces a remarkable α31 component (~89 mV Oe-1 cm-1) of the magnetoelectric tensor. And the magnetoelectric coupling, characterized by the change of polarization, reaches ~12% under 40 kOe magnetic field. Our results exemplify a design methodology that enables the creation of room-temperature magnetoelectrics by leveraging the potent effects of magnetostriction.
We present an open-source MLatom@XACS software ecosystem for on-the-fly surface hopping nonadiabatic dynamics based on the Landau-Zener-Belyaev-Lebedev algorithm. The dynamics can be performed via Python API with a wide range of quantum mechanical (QM) and machine learning (ML) methods, including ab initio QM (CASSCF and ADC(2)), semiempirical QM methods (e.g., AM1, PM3, OMx, and ODMx), and many types of ML potentials (e.g., KREG, ANI, and MACE). Combinations of QM and ML methods can also be used. While the user can build their own combinations, we provide AIQM1, which is based on Δ-learning and can be used out-of-the-box. We showcase how AIQM1 reproduces the isomerization quantum yield of trans-azobenzene at a low cost. We provide example scripts that, in dozens of lines, enable the user to obtain the final population plots by simply providing the initial geometry of a molecule. Thus, those scripts perform geometry optimization, normal mode calculations, initial condition sampling, parallel trajectories propagation, population analysis, and final result plotting. Given the capabilities of MLatom to be used for training different ML models, this ecosystem can be seamlessly integrated into the protocols building ML models for nonadiabatic dynamics. In the future, a deeper and more efficient integration of MLatom with Newton-X will enable a vast range of functionalities for surface hopping dynamics, such as fewest-switches surface hopping, to facilitate similar workflows via the Python API.
BACKGROUND: Allergic bronchopulmonary aspergillosis (ABPA) is characterized by enhanced Th2 inflammatory response. Fractional exhaled nitric oxide (FeNO) measurement has been utilized as a valuable tool in predicting the development and management of asthma, another typical Th2 inflammation. However, the clinical significance of FeNO in ABPA remains unclear. OBJECTIVE: To investigate the association between FeNO and the prognosis of ABPA patients, so as to provide a basis for the use of FeNO in evaluating the efficacy of glucocorticoids in ABPA treatment. METHODS: This study consists of two parts. 58 patients were enrolled in the retrospective study. Clinical indexes between patients with different prognoses were compared and ROC curve analysis were employed to determine the threshold value. The prospective observational study involved 61 patients who were regularly followed up at 4-6 weeks and 6 months since the initial treatment. Patients were grouped based on baseline FeNO values, correlation analysis were performed between clinical data. RESULTS: Different prognoses were observed between patients with High- and Low- baseline FeNO values, with a threshold value of 57 ppb. The percentage of A. fumigatus-specific IgE, percentage of positive A. fumigatus-specific IgG, and relapse/exacerbation rate differed significantly between the H/L-FeNO groups. Patients with higher FeNO needed longer treatment duration and showed shorter interval between glucocorticoid withdrawal and the next relapse/exacerbation. CONCLUSION: Our findings indicate that the level of FeNO is associated with the prognosis of ABPA. It can serve as an independent and valuable biomarker for evaluating the effectiveness of glucocorticoid treatment.
BACKGROUND: N6-methyladenosine (m6A) modification represents the predominant alteration found in eukaryotic messenger RNA and plays a crucial role in the progression of various tumors. However, despite its significance, the comprehensive investigation of METTL5, a key m6A methyltransferase, in colorectal cancer (CRC) remains limited. AIM: To investigate the role of METTL5 in CRC. METHODS: We assessed METTL5 expression levels in clinical samples obtained from CRC patients as well as in CRC cell lines. To elucidate the downstream targets of METTL5, we performed RNA-sequencing analysis coupled with correlation analysis, leading us to identify Toll-like receptor 8 (TLR8) as a potential downstream target. In vitro functional assessments of METTL5 and TLR8 were conducted using CCK-8 assays, scratch assays, as well as assays measuring cell migration and invasion. RESULTS: Our findings reveal a pronounced upregulation of METTL5 expression in both CRC cells and tissues, which correlated significantly with an unfavorable prognosis. In vitro experiments unequivocally demonstrated the oncogenic role of METTL5, as evidenced by its promotion of CRC cell proliferation, invasion, and migration. Notably, we identified TLR8 as a downstream target of METTL5, and subsequent down-regulation of TLR8 led to a significant inhibition of CRC cell proliferation, invasion, and tumor growth. CONCLUSION: The heightened expression of METTL5 in CRC is strongly associated with clinicopathological features and a poor prognosis, thereby underscoring its potential utility as a critical marker for facilitating early diagnosis and prognostication in CRC.
OBJECTIVE: To summary radiating blood flow signals and evaluate their diagnostic value in differentiating benign and malignant thyroid nodules. MATERIALS AND METHODS: We retrospectively recruited consecutive patients undergoing US at 4 hospitals from 2018 to 2022. In a training dataset, the correlations of US features with malignant thyroid nodules were assessed by multivariate logistic analysis. Multivariate logistic regression models involving the ACR TI-RADS score, radiating blood flow signals and their combination were built and validated internally and externally. The AUC with 95% asymptotic normal confidence interval as well as sensitivity, specificity, negative predictive value (NPV), and positive predictive value (PPV) with 95% exact binomial confidence intervals were calculated. RESULTS: Among 2475 patients (1818 women, age: 42.47 ± 11.57; 657 men, age: 42.16 ± 11.69), there were 3187 nodules (2342 malignant nodules and 845 benign nodules). Radiating blood flow signals were an independent risk factor for diagnosing thyroid carcinoma. In the training set, the AUC of the model using the combination of radiating blood flow signals and the ACR TI-RADS score (0.95 95 % CI: [0.94, 0.97]; P < 0.001) was significantly higher than that of the ACR TI-RADS model (0.91 [0.89, 0.93]). In the two internal validation sets and the external validation set, the AUCs of the combination model were 0.97 [0.96, 0.98], 0.92 [0.88, 0.96], and 0.91 [0.86, 0.95], respectively, and were all significantly higher than that of the ACR TI-RADS score (0.92 [0.90, 0.95], 0.86 [0.81, 0.91], 0.84 [0.79, 0.89]; P < 0.001). CONCLUSION: Radiating blood flow is a new US feature of thyroid carcinomas that can significantly improve the diagnostic performance vs. the ACR TI-RADS score.
Household and personal care chemicals (HPCCs) constitute a significant component of everyday products, with their global usage on the rise. HPCCs are eventually discharged into municipal wastewater treatment plants (WWTPs). However, the behaviors of HPCCs inside the Bacillus Bioreactor (BBR) process, including their prevalence, fate, and elimination mechanisms, remain underexplored. Addressing this gap, our study delves into samples collected from a BBR process at a significant WWTP in the northeast of China. Our results spotlight the dominance of linear alkylbenzene sulfonates (LASs) in the influent with concentrations ranging between 238 and 789 µg/L, much higher than the other HPCC concentrations, and remained dominant in the subsequent treatment units. After treatment using the BBR process, the concentrations of HPCCs in the effluent were diminished. Examination of different treatment units underscores the grit chamber removed over 60% of higher-concentration HPCCs, while the performance of the (RBC) tank needs to be improved. Except for the ultraviolet radiation (UV)-filters, seasonal variations exert minimal impact on the concentrations and removal efficiencies of other HPCCs in the BBR process. According to the mass balance analysis, the important mechanisms for HPCC removal were biodegradation and sludge adsorption. Also, the octocrylene (OCT) concerns raised by the environmental risk assessment of the HPCCs residuals in the final effluent, indicate a moderate risk to the surrounding aquatic environment (0.1 < RQ < 1), whereas other HPCCs have a lower risk level (RQ < 0.1). Overall, the research offers new perspectives on the fate and elimination mechanisms of HPCCs throughout the BBR process.
Bacillus , Bioreactors , Seasons , Waste Disposal, Fluid , Wastewater , Water Pollutants, Chemical , Bioreactors/microbiology , Wastewater/chemistry , Water Pollutants, Chemical/analysis , Water Pollutants, Chemical/metabolism , Waste Disposal, Fluid/methods , Bacillus/metabolism , China , Biodegradation, Environmental , Cosmetics/analysis , Household Products/analysis , Alkanesulfonic Acids/analysis , Environmental Monitoring , Sewage
The decrease in eggshell quality seriously affects production efficiency. Guinea fowl (GF) eggs possess strong eggshells because of their unique crystal structure, and few systematic studies have compared laying hen and GF eggs. Sixty eggs were collected from both 40-week-old Dwarf Layer-White (DWL-White) laying hens and GF, and the eggshell quality, ultrastructure, bubble pores, and composition were measured. The results showed that the DWL-White eggs had a higher egg weight and a lower eggshell strength, strength per unit weight, thickness, and ratio than the GF eggs (p < 0.01). There were differences in the mammillary layer thickness ratio, the effective layer thickness ratio, the quantity of bubble pores (QBPs), the ratio of the sum of the area of bubble pores to the area of the eggshell in each image (ARBE), and the average area of bubble pores (AABPs) between the DWL-White and GF eggs (p < 0.01). The composition analysis demonstrated that there were differences in the organic matter, inorganic matter, calcium, and phosphorus between the DWL-White and GF eggs (p < 0.01). There were positive associations between the mammillary knob number in the image and the QBPs and ARBE and a negative correlation with the AABPs in the DWL-White eggs (p < 0.01). This study observed distinctions that offer new insights into enhancing eggshell quality.
BACKGROUND: This study aimed to identify potential subtypes of hepatocellular carcinoma (HCC) associated with cirrhosis and to investigate key markers using bioinformatic analysis of gene expression datasets-0. METHODS: Three data sets (GSE17548, GSE56140, and GSE87630) were extracted from the Gene Expression Omnibus (GEO) database and normalized using the Limma package in R. Principal component analysis (PCA) and cluster analysis was performed to examine data distribution and identify subtypes. Differential gene expression analysis was performed using the Limma software package. Protein-protein interaction analysis and functional annotation were performed using the STRING database and Cytoscape software. Important signaling pathways and processes were identified using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Analysis. RESULTS: The analysis revealed different subtypes of HCC associated with cirrhosis and identified several key genes, including CCNB2, MCM4, and CDC20, with strong binding power and prognostic value. Functional annotation indicated involvement in cell cycle regulation and metabolic pathways. ROC analysis showed high sensitivity and specificity of these genes in predicting HCC prognosis. CONCLUSION: These results suggest that CCNB2, MCM4, and CDC20 may serve as potential biomarkers for predicting HCC prognosis in patients with cirrhosis and provide insights into the molecular mechanisms of HCC progression.
BACKGROUND: Adjuvant chemotherapy following curative surgery for locally advanced gastric cancer (AGC) significantly improves long-term patient prognosis. However, delayed chemotherapy (DC), in which patients are unable to receive timely treatment, is a common phenomenon in clinical practice for various reasons. This study aimed to investigate the impact of DC on the prognosis of patients with stage II-III locally AGC and explore the associated risk factors. METHODS: Data from four prospective studies were included in the pooled analysis. The planned chemotherapy (PC) group was defined as the time interval between surgery and the first chemotherapy ≤ 49 d, while the DC group was defined as the time interval between surgery and chemotherapy > 49 d. The prognosis, recurrence, and risk factors were compared, and a nomogram for predicting DC was established. RESULTS: In total, 596 patients were included, of whom 531 (89.1%) had PC and 65 (10.9%) had DC. Survival analysis revealed that the 5-year overall survival (OS) and disease-free survival (DFS) were significantly lower in the DC group than those in the PC group (log-rank P < 0.001). Cox univariable and multivariable analyses showed that DC was an independent risk factor for OS and DFS in stage II-III patients (P < 0.05). Based on the significant factors for DC, a prediction model was established that had a good fit, high accuracy (AUC = 0.780), and clinical applicability in both the training and validation sets. CONCLUSION: Delayed chemotherapy after gastrectomy is associated with poor long-term prognosis in patients with locally advanced stage II-III GC disease. But standardized, full-cycle adjuvant chemotherapy after surgery may play a remedial role, and can to a certain extent compensate the poor effects caused by delayed chemotherapy.
Dachaihu Decoction is a classic prescription with the function of harmonizing Shaoyang and purging away internal stasis of heat, which was specially developed by Master ZHANG Zhongjing for the concurrent disease of Shaoyang and Yangming. A large number of international studies have shown that Dachaihu Decoction has liver protection, gallbladder benefit, anti-inflammatory, and other pharmacological effects and is mostly used in modern clinical treatment of acute pancreatitis, acute cholecystitis, cholelithiasis, and other digestive diseases. This paper combined bibliography and statistics and selected the ancient book database and CNKI database to search the relevant literature on Dachaihu decoction, verify the composition and dosage, processing method, main diseases, and modern clinical application, and predict its quality markers(Q-markers) based on the "five principles" of Q-markers. The results suggest that saikosaponin a, baicalin, and 6-gingerol can be selected as potential Q-markers for Dachaihu Decoction, so as to provide a basis for the clinical research of traditional Chinese medicine and the development and application of compound preparations.
Drugs, Chinese Herbal , Drugs, Chinese Herbal/chemistry , Drugs, Chinese Herbal/pharmacology , Drugs, Chinese Herbal/therapeutic use , Humans , History, Ancient , Animals , Biomarkers/analysis , China , History, 21st Century
Arthroscopic repair of Bankart injury is the first choice for the treatment of anterior shoulder instability. How to avoid recurring shoulder joint dislocation is a challenge, especially when combined with Hill-Sachs lesions. The arthroscopy technology allows for broader vision and less surgical trauma but is limited by a smaller operating space. At present, extensive descriptions about the surgical procedure of arthroscopic Bankart repair have been published. In this Technical Note, we describe the use of remplissage filling with Hill-Sachs lesion combined with Bankart repair to further improve the surgical accuracy and clinical efficacy. In particular, the application of single needle-assisted outside-in remplissage technique and Bankart repair is introduced in detail.
BACKGROUND: Carbon-based nanozymes have recently received enormous concern, however, there is still a huge challenge for inexpensive and large-scale synthesis of magnetic carbon-based "Two-in-One" mimics with both peroxidase (POD)-like and laccase-like activities, especially their potential applications in multi-mode sensing of antibiotics and neurotransmitters in biofluids. Although some progresses have been made in this field, the feasibility of biomass-derived carbon materials with both POD-like and laccase-like activities by polyatomic doping strategy is still unclear. In addition, multi-mode sensing platform can provide a more reliable result because of the self-validation, self-correction and mutual agreement. Nevertheless, the use of magnetic carbon-based nanozyme sensors for the multi-mode detection of antibiotics and neurotransmitters have not been investigated. RESULTS: We herein report a shrimp shell-derived N, O-codoped porous carbon confined magnetic CuFe2O4 nanosphere with outstanding laccase-like and POD-like activities for triple-mode sensing of antibiotic d-penicillamine (D-PA) and chloramphenicol (CPL), as well as colorimetric detection of neurotransmitters in biofluids. The magnetic CuFe2O4/N, O-codoped porous carbon (MCNPC) armored mimetics was successfully fabricated using a combined in-situ coordination and high-temperature crystallization method. The synthesized MCNPC composite with superior POD-like activity can be used for colorimetric/temperature/smartphone-based triple-mode detection of D-PA and CPL in goat serum. Importantly, the MCNPC nanozyme can also be used for colorimetric analysis of dopamine and epinephrine in human urine. SIGNIFICANCE: This work not only offered a novel strategy to large-scale, cheap synthesize magnetic carbon-based "Two-in-One" armored mimetics, but also established the highly sensitive and selective platforms for triple-mode monitoring D-PA and CPL, as well as colorimetric analysis of neurotransmitters in biofluids without any tanglesome sample pretreatment.
Anti-Bacterial Agents , Carbon , Copper , Neurotransmitter Agents , Carbon/chemistry , Anti-Bacterial Agents/analysis , Anti-Bacterial Agents/urine , Anti-Bacterial Agents/blood , Neurotransmitter Agents/urine , Neurotransmitter Agents/analysis , Neurotransmitter Agents/blood , Porosity , Copper/chemistry , Humans , Nanospheres/chemistry , Colorimetry/methods , Ferric Compounds/chemistry , Biomimetic Materials/chemistry , Animals , Biosensing Techniques/methods , Chloramphenicol/analysis , Chloramphenicol/urine , Limit of Detection
Chimeric antigen receptor-expressing T (CAR-T) cells induce robust antitumor responses in patients with hematologic malignancies. However, CAR-T cells exhibit only limited efficacy against solid tumors such as hepatocellular carcinoma (HCC), partially due to their limited expansion and persistence. CD8+ T cells, as key components of the adaptive immune response, play a central role in antitumor immunity. Aerobic glycolysis is the main metabolic feature of activated CD8+ T cells. In the tumor microenvironment, however, the uptake of large amounts of glucose by tumor cells and other immunosuppressive cells can impair the activation of T cells. Only when tumor-infiltrating lymphocytes (TILs) in the tumor microenvironment have a glycolytic advantage might the effector function of T cells be activated. Glucose transporter type 1 (GLUT1) and acylglycerol kinase (AGK) can boost glycolytic metabolism and activate the effector function of CD8+ T cells, respectively. In this study, we generated GPC3-targeted CAR-T cells overexpressing GLUT1 or AGK for the treatment of HCC. GPC3-targeted CAR-T cells overexpressing GLUT1 or AGK specifically and effectively lysed GPC3-positive tumor cells in vitro in an antigen-dependent manner. Furthermore, GLUT1 or AGK overexpression protected CAR-T cells from apoptosis during repeated exposures to tumor cells. Compared with second-generation CAR-T cells, GPC3-targeted CAR-T cells overexpressing GLUT1 or AGK exhibited greater CD8+ T-cell persistence in vivo and better antitumor effects in HCC allograft mouse models. Finally, we revealed that GLUT1 or AGK maintained anti-apoptosis ability in CD8+ T cells via activation of the PI3K/Akt pathway. This finding might identify a therapeutic strategy for advanced HCC.
The clinical implications of CSF-ctDNA positivity in newly diagnosed diffuse large B cell lymphoma (ND-DLBCL) remains largely unexplored. One hundred ND-DLBCL patients were consecutively enrolled as training cohort and another 26 ND-DLBCL patients were prospectively enrolled in validation cohort. CSF-ctDNA positivity (CSF(+)) was identified in 25 patients (25.0%) in the training cohort and 7 patients (26.9%) in the validation cohort, extremely higher than CNS involvement rate detected by conventional methods. Patients with mutations of CARD11, JAK2, ID3, and PLCG2 were more predominant with CSF(+) while FAT4 mutations were negatively correlated with CSF(+). The downregulation of PI3K-AKT signaling, focal adhesion, actin cytoskeleton, and tight junction pathways were enriched in CSF(+) ND-DLBCL. Furthermore, pretreatment CSF(+) was significantly associated with poor outcomes. Three risk factors, including high CSF protein level, high plasma ctDNA burden, and involvement of high-risk sites were used to predict the risk of CSF(+) in ND-DLBCL. The sensitivity and specificity of pretreatment CSF-ctDNA to predict CNS relapse were 100% and 77.3%. Taken together, we firstly present the prevalence and the genomic and transcriptomic landscape for CSF-ctDNA(+) DLBCL and highlight the importance of CSF-ctDNA as a noninvasive biomarker in detecting and monitoring of CSF infiltration and predicting CNS relapse in DLBCL.
Background: Chinese patent medicine is commonly used in China as an important treatment mechanism to thwart the progression of chronic kidney disease (CKD) stages 3-5, among which Niaoduqing granules are a representative Chinese patent medicine; however, its long-term efficacy on CKD prognosis remains unclear. Methods: Patients were grouped according to Niaoduqing granule prescription duration (non-Niaoduqing granule (non-NDQ) group vs Niaoduqing granule (NDQ) group). Serum creatinine (SCr) variation was compared using a generalized linear mixed model (GLMM). Multivariate Cox regression models were constructed, adjusting for confounding factors, to explore the risk of composite outcomes (receiving renal replacement therapy (RRT) or having an estimated glomerular filtration rate (eGFR)<5 mL/min/1.73 m2, ≥50% decline in the eGFR from the baseline, and doubling of SCr) in individuals consuming Niaoduqing granules. Results: A total of 1,271 patients were included, with a median follow-up duration of 29.71 (12.10, 56.07) months. The mean SCr Z-scores for the non-NDQ group and NDQ group were -0.175 and 0.153, respectively, at baseline (p = 0.015). The coefficients of the NDQ group from visit 1 to visit 5 were -0.207 (95% CI: -0.346, -0.068, p = 0.004), -0.214 (95% CI: 0.389, -0.039, p = 0.017), -0.324 (95% CI: 0.538, -0.109, p = 0.003), -0.502 (95% CI: 0.761, -0.243, p = 0.000), and -0.252 (95% CI: 0.569, 0.065, p = 0.119), respectively. The survival probability was significantly higher in the NDQ group (p = 0.0039). Taking Niaoduqing granules was a significant protective factor for thwarting disease progression (model 1: HR 0.654 (95% CI 0.489-0.875, p = 0.004); model 2: HR 0.646 (95% CI 0.476, 0.877, p = 0.005); and model 3: HR 0.602 (95% CI 0.442, 0.820, p = 0.001)). Conclusion: The long-term use of Niaoduqing granules improved SCr variation and lowered the risk of CKD progression by 39.8%.
This study aimed to analyze potential ethnic disparities in the dose-exposure-response relationships of trilaciclib, a first-in-class intravenous cyclin-dependent kinase 4/6 inhibitor for treating chemotherapy-induced myelosuppression in patients with extensive-stage small cell lung cancer (ES-SCLC). This investigation focused on characterizing these relationships in both Chinese and non-Chinese patients to further refine the dosing regimen for trilaciclib in Chinese patients with ES-SCLC. Population pharmacokinetic (PopPK) and exposure-response (E-R) analyses were conducted using pooled data from four randomized phase 2/3 trials involving Chinese and non-Chinese patients with ES-SCLC. PopPK analysis revealed that trilaciclib clearance in Chinese patients was approximately 17% higher than that in non-Chinese patients with ES-SCLC. Sex and body surface area influenced trilaciclib pharmacokinetics in both populations but did not exert a significant clinical impact. E-R analysis demonstrated that trilaciclib exposure increased with a dosage escalation from 200 to 280 mg/m2, without notable changes in myeloprotective or antitumor efficacy. However, the incidence of infusion site reactions, headaches, and phlebitis/thrombophlebitis rose with increasing trilaciclib exposure in both Chinese and non-Chinese patients with ES-SCLC. These findings suggest no substantial ethnic disparities in the dose-exposure-response relationship between Chinese and non-Chinese patients. They support the adoption of a 240-mg/m2 intravenous 3-day or 5-day dosing regimen for trilaciclib in Chinese patients with ES-SCLC.
