Prognostic model for predicting recurrence in hepatocellular carcinoma patients with high systemic immune-inflammation index based on machine learning in a multicenter study.

Introduction: This study aims to use machine learning to conduct in-depth analysis of key factors affecting the recurrence of HCC patients with high preoperative systemic immune-inflammation index (SII) levels after receiving ablation treatment, and based on this, construct a nomogram model for predicting recurrence-free survival (RFS) of patients. Methods: This study included clinical data of 505 HCC patients who underwent ablation therapy at Beijing You'an Hospital from January 2014 to January 2020, and accepted 65 HCC patients with high SII levels from Beijing Ditan Hospital as an external validation cohort. 505 patients from Beijing You'an Hospital were divided into low SII and high SII groups based on the optimal cutoff value of SII scores. The high SII group was further randomly divided into training and validation cohorts in a 7:3 ratio. eXtreme Gradient Boosting (XGBoost), random survival forest (RSF), and multivariate Cox regression analysis, were used to explore the factors affecting the post-ablation RFS of HCC patients. Based on the identified key factors, a nomogram model were developed to predict RFS in HCC patients, and their performance were evaluated using the concordance index (C index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). The optimal cutoff value for nomogram scores was used to divide patients into low- and high-risk groups, and the effectiveness of the model in risk stratification was evaluated using Kaplan-Meier (KM) survival curves. Results: This study confirmed that age, BCLC stage, tumor number, and GGT level were independent risk factors affecting RFS in HCC patients. Based on the selected risk factors, an RFS nomogram was successfully constructed. The C-index, ROC curve, calibration curve, and DCA curve each demonstrated the discrimination, accuracy, and decision-making utility of the nomogram, indicating that it has good predictive performance. KM curve revealed the nomogram could significantly differentiate patient populations with different recurrence risk. Conclusion: We developed a reliable nomogram that can accurately predict the 1-, 3-, and 5-year RFS for HCC patients with high SII levels following ablation therapy.

Neuroimaging analysis reveals distinct cerebral perfusion responses to fasting-postprandial metabolic switching in Alzheimer's disease patients.

AIMS: Extended fasting-postprandial switch intermitting time has been shown to affect Alzheimer's disease (AD). Few studies have investigated the cerebral perfusion response to fasting-postprandial metabolic switching (FMS) in AD patients. We aimed to evaluate the cerebral perfusion response to FMS in AD patients. METHODS: In total, 30 AD patients, 32 mild cognitive impairment (MCI) patients, and 30 healthy control individuals (HCs) were included in the quantification of cerebral perfusion via cerebral blood flow (CBF). The cerebral perfusion response to FMS was defined as the difference (ΔCBF) between fasting and postprandial CBF. RESULTS: Patients with AD had a regional negative ΔCBF in the anterior temporal lobe, part of the occipital lobe and the parietal lobe under FMS stimulation, whereas HCs had no significant ΔCBF. The AD patients had lower ΔCBF values in the right anterior temporal lobe than the MCI patients and HCs. ΔCBF in the anterior temporal lobe was negatively correlated with cognitive severity and cognitive reserve factors in AD patients. CONCLUSIONS: AD patients exhibited a poor ability to maintain cerebral perfusion homeostasis under FMS stimulation. The anterior temporal lobe is a distinct area that responds to FMS in AD patients and negatively correlates with cognitive function.

Complex system anomaly detection via learnable temporal-spatial graph with degradation tendency segmentation.

To guarantee the safety and reliability of equipment operation, such as liquid rocket engine (LRE), carrying out system-level anomaly detection (AD) is crucial. However, current methods ignore the prior knowledge of mechanical system itself, and seldom unite the observations with the inherent relation in data tightly. Meanwhile, they neglect the weakness and nonindependence of system-level anomaly which is different from component fault. To overcome above limitations, we propose a separate reconstruction framework using worsened tendency for system-level AD. To prevent anomalous feature being attenuated, we first propose to divide single sample into two equal-length parts along the temporal dimension. And we maximize the mean maximum discrepancy (MMD) between feature segments to force encoders to learn normal features with different distributions. Then, to fully explore the multivariate time series, we model temporal-spatial dependence by temporal convolution and graph attention. Besides, a joint graph learning strategy is proposed to handle prior knowledge and data characteristics simultaneously. Finally, the proposed method is evaluated on two real multi-sensor datasets from LRE and the results demonstrate the effectiveness and potential of the proposed method on system-level AD.

The clinical significance of sarcopenia in patients with hepatocellular carcinoma treated with lenvatinib and PD-1 inhibitors.

Background and aim: Sarcopenia has gained considerable attention in the context of hepatocellular carcinoma, as it has been correlated with a poorer prognosis among patients undergoing sorafenib or lenvatinib treatment for hepatocellular carcinoma (HCC). The clinical significance of sarcopenia in first-line advanced HCC patients treated with lenvatinib and programmed death-1 (PD-1) inhibitors needs to be clarified. Methods: Sarcopenia was diagnosed using CT (Computed tomography) or MRI (Magnetic Resonance Imaging), with the psoas muscle index (PMI) as the surrogate marker. Patients were grouped based on sarcopenia presences, and a comparative analysis examined characteristics, adverse events, and prognosis. The Cox regression analysis was applied to identify independent prognostic factors for survival, while nomograms were constructed to predict 1-year survival. Results: Among 180 patients, 46 had sarcopenia. Patients with baseline sarcopenia demonstrated significantly inferior median progression-free survival (mPFS) (3.0 vs. 8.3 months) and median overall survival (mOS) (7.3 vs. 21.6 months). The same results for mPFS (3.3 vs. 9.2 months) and mOS (9.4 vs. 24.2 months) were observed in patients who developed sarcopenia after treatment. Furthermore, significantly higher grade 3 or higher adverse events (AEs) (73.91% vs 41.79%, p<0.001) were recorded in the sarcopenia group compared to the non-sarcopenia group. In the multivariate analysis, distant metastasis, elevated PLR and CRP levels, and low PMI remained independent predictive factors for poor OS. Additionally, skeletal muscle loss remained a significant independent risk factor for PFS. We developed a nomogram incorporating these four indicators, which predicted 12-month survival with a C-index of 0.853 (95% CI, 0.791 - 0.915), aligning well with actual observations. Conclusion: The prognosis of patients with HCC and sarcopenia is significantly worse when treated with lenvatinib and PD-1 inhibitors. The combination regimen of lenvatinib plus PD-1 inhibitors should be cautiously recommended due to the inferior prognosis and higher AEs.

High-energy and high-amino acid diet enhances production performance and antioxidant capacity in yellow-feathered broilers under heat stress.

This study investigated the ameliorating effects of high-energy and high-amino acid (HEHA) diets on heat stress (HS) in yellow-feathered broilers. Broilers aged 35 d were randomly assigned to 3 groups: control and HS groups fed the basic normal diet, and the HEHA group fed the HEHA diet (basal diet + 100 kcal/kg AME + 15 % DAAs). The HS and HEHA groups were exposed to cyclic HS (30 ± 1 to 34 ± 1 ℃) for 2 wk, while the control group was maintained at 26 ± 1 ℃. The results indicated that the HEHA diet significantly alleviated HS-induced feed intake and body weight loss. HEHA feeding mitigated the increase in body temperature during HS. Compared with observations in the HS group, the HEHA diet reduced the levels of ALT, Alb, and corticosterone in the serum and downregulated the gene expression of HSP27 and HSP60 in the liver. Moreover, the HEHA group showed higher GSH-px activity in the serum and SOD and GSH-Px activity in the jejunal mucosa than that of the HS group. HEHA supplementation also reduced MDA levels in the liver. In conclusion, the HEHA diet improved the production performance of broilers under HS by increasing their antioxidant capacities. These findings suggest an effective strategy to combat HS in poultry production.

Highly Stereoselective Synthesis of Multisubstituted Olefins from Alkynyl Tetracoordinate Borons and Iodonium Ylides via a Cyclic Intermediate.

We developed an intriguing and practical strategy for highly stereoselective assembly of multisubstituted olefins from alkynyl tetracoordinate boron species via a cyclic intermediate with 1,2-phenyl migration. We also developed a general method for the construction of deuterated trisubstituted alkenes from a cheap deuteration source, D2O, and the corresponding deuterated trisubstituted alkenes were obtained with excellent deuteration rates. This transformation features a novel reaction mechanism, exclusive stereoselectivity, and deuterated trisubstituted alkenes with excellent deuteration ratios.

Alterations in brain functional connectivity in patients with mild cognitive impairment: A systematic review and meta-analysis of functional near-infrared spectroscopy studies.

Emerging evidences suggest that cognitive deficits in individuals with mild cognitive impairment (MCI) are associated with disruptions in brain functional connectivity (FC). This systematic review and meta-analysis aimed to comprehensively evaluate alterations in FC between MCI individuals and healthy control (HC) using functional near-infrared spectroscopy (fNIRS). Thirteen studies were included in qualitative analysis, with two studies synthesized for quantitative meta-analysis. Overall, MCI patients exhibited reduced resting-state FC, predominantly in the prefrontal, parietal, and occipital cortex. Meta-analysis of two studies revealed a significant reduction in resting-state FC from the right prefrontal to right occipital cortex (standardized mean difference [SMD] = -.56; p < .001), left prefrontal to left occipital cortex (SMD = -.68; p < .001), and right prefrontal to left occipital cortex (SMD = -.53; p < .001) in MCI patients compared to HC. During naming animal-walking task, MCI patients exhibited enhanced FC in the prefrontal, motor, and occipital cortex, whereas a decrease in FC was observed in the right prefrontal to left prefrontal cortex during calculating-walking task. In working memory tasks, MCI predominantly showed increased FC in the medial and left prefrontal cortex. However, a decreased in prefrontal FC and a shifted in distribution from the left to the right prefrontal cortex were noted in MCI patients during a verbal frequency task. In conclusion, fNIRS effectively identified abnormalities in FC between MCI and HC, indicating disrupted FC as potential markers for the early detection of MCI. Future studies should investigate the use of task- and region-specific FC alterations as a sensitive biomarker for MCI.

Association between computed tomography-quantified respiratory muscles and chronic obstructive pulmonary disease: a retrospective study.

BACKGROUND: This study examined the association between chest muscles and chronic obstructive pulmonary disease (COPD) and the relationship between chest muscle areas and acute exacerbations of COPD (AECOPD). METHODS: There were 168 subjects in the non-COPD group and 101 patients in the COPD group. The respiratory and accessory respiratory muscle areas were obtained using 3D Slicer software to analysis the imaging of  computed tomography (CT). Univariate and multivariate Poisson regressions were used to analyze the number of AECOPD cases during the preceding year. The cutoff value was obtained using a receiver operating characteristic (ROC) curve. RESULTS: We scanned 6342 subjects records, 269 of which were included in this study. We then measured the following muscle areas (non-COPD group vs. COPD group): pectoralis major (19.06 ± 5.36 cm2 vs. 13.25 ± 3.71 cm2, P < 0.001), pectoralis minor (6.81 ± 2.03 cm2 vs. 5.95 ± 1.81 cm2, P = 0.001), diaphragmatic dome (1.39 ± 0.97 cm2 vs. 0.85 ± 0.72 cm2, P = 0.011), musculus serratus anterior (28.03 ± 14.95 cm2 vs.16.76 ± 12.69 cm2, P < 0.001), intercostal muscle (12.36 ± 6.64 cm2 vs. 7.15 ± 5.6 cm2, P < 0.001), pectoralis subcutaneous fat (25.91 ± 13.23 cm2 vs. 18.79 ± 10.81 cm2, P < 0.001), paravertebral muscle (14.8 ± 4.35 cm2 vs. 13.33 ± 4.27 cm2, P = 0.007), and paravertebral subcutaneous fat (12.57 ± 5.09 cm2 vs. 10.14 ± 6.94 cm2, P = 0.001). The areas under the ROC curve for the pectoralis major, intercostal, and the musculus serratus anterior muscle areas were 81.56%, 73.28%, and 71.56%, respectively. Pectoralis major area was negatively associated with the number of AECOPD during the preceding year after adjustment (relative risk, 0.936; 95% confidence interval, 0.879-0.996; P = 0.037). CONCLUSION: The pectoralis major muscle area was negative associated with COPD. Moreover, there was a negative correlation between the number of AECOPD during the preceding year and the pectoralis major area.

Transcatheter arterial chemoembolization combined with PD-1 inhibitors and Lenvatinib for hepatocellular carcinoma with portal vein tumor thrombus.

BACKGROUND: Hepatocellular carcinoma (HCC) patients complicated with portal vein tumor thrombus (PVTT) exhibit poor prognoses and treatment responses. AIM: To investigate efficacies and safety of the combination of PD-1 inhibitor, transcatheter arterial chemoembolization (TACE) and Lenvatinib in HCC subjects comorbid with PVTT. METHODS: From January 2019 to December 2020, HCC patients with PVTT types I-IV were retrospectively enrolled at Beijing Ditan Hospital. They were distributed to either the PTL or TACE/Lenvatinib (TL) group. The median progression-free survival (mPFS) was set as the primary endpoint, while parameters like median overall survival, objective response rate, disease control rate (DCR), and toxicity level served as secondary endpoints. RESULTS: Forty-one eligible patients were finally recruited for this study and divided into the PTL (n = 18) and TL (n = 23) groups. For a median follow-up of 21.8 months, the DCRs were 88.9% and 60.9% in the PTL and TL groups (P = 0.046), res-pectively. Moreover, mPFS indicated significant improvement (HR = 0.25; P < 0.001) in PTL-treated patients (5.4 months) compared to TL-treated (2.7 months) patients. There were no treatment-related deaths or differences in adverse events in either group. CONCLUSION: A triplet regimen of PTL was safe and well-tolerated as well as exhibited favorable efficacy over the TL regimen for advanced-stage HCC patients with PVTT types I-IV.

1,1-Oxycarbonation of Terminal Alkynes via Sequential Borylation, 1,2-Migration, and Oxidation with Oxone.

Alkynes are readily available and multifunctional synthetic intermediates, but their 1,1-oxofunctionalization remains challenging. Herein, we report a 1,1-oxycarbonation of terminal alkynes to construct ketones through sequential borylation, 1,2-carbon migration, and oxidation with Oxone as the proton source and oxidant. The synthetic potential of this transformation is showcased by the broad functional groups, scale-up synthesis, and diverse product transformations.

Impact of bi-directional electric vehicle and demand response on residential distributed PV capacity planning based on TOU pricing.

The widespread deployment of residential distributed photovoltaic (RDPV) remains complex and challenging due to photovoltaic output intermittency, fluctuating electricity demand, and rising electric vehicle (EV) adoption. Simultaneously, the energy storage capabilities of EVs and residential demand response (DR) offer solutions for optimizing RDPV applications. This study proposes an integrated RDPV capacity planning model by encompassing EV charging, vehicle-to-home, and flexible load DR. Five scenarios are established to reveal the impact of various factors on the optimal photovoltaic installation capacity, electricity cost, self-consumption and self-sufficiency rate. A case study of three typical residential electricity demand patterns indicates that DR and vehicle-to-home significantly reduce the optimal photovoltaic installation capacity and total electricity cost. When the feed-in tariff during photovoltaic generation periods is higher than the off-peak pricing, DR results in a reduction in photovoltaic self-sufficiency rate and an increase in photovoltaic self-consumption rate. EV charging and vehicle-to-home have minimal impact on photovoltaic self-consumption rate, while EV charging significantly decreases self-sufficiency rate and vehicle-to-home exacerbates this effect.

Recent progress in the catalytic enantioselective reactions of 1,1-diborylalkanes.

Organoboron compounds are environmentally benign, have low toxicity and are versatile reagents that are extensively employed in organic synthesis, especially in the realm of asymmetric synthesis. The last several decades have witnessed a tremendous outburst of asymmetric reactions based on various organoboron compounds. Among them, 1,1-diborylalkanes, which contain two boryl groups at the same sp3-carbon atom, are regarded as some of the most versatile and powerful reagents for their unique structure and unusual reaction mode in organic synthesis. Moreover, owing to the stabilizing effect of the empty p-orbital of the neighboring boron atoms and the inherent good steric-hindrance, 1,1-diborylalkanes often exhibit extraordinary reactivity and stereoselectivity compared to other kinds of organoboron compounds in asymmetric synthesis. Herein, the present highlight summarizes and discusses the recent progress achieved in the catalytic enantioselective reactions of 1,1-diborylalkanes during the past decade.

Lenvatinib combined with sintilimab plus transarterial chemoembolization as first-line treatment for advanced hepatocellular carcinoma.

BACKGROUND: Recently, combination therapy has shown a better trend towards improved tumour response and survival outcomes than monotherapy in patients with hepatocellular carcinoma (HCC). However, research on triple therapy [lenvatinib + sintilimab + transarterial chemoembolization (TACE)] as a first-line treatment for advanced HCC is limited. AIM: To evaluate the safety and efficacy of triple therapy as a first-line treatment for advanced HCC. METHODS: HCC patients with Barcelona Clinic Liver Cancer stage C treated with triple therapy were enrolled. All patients were treated with lenvatinib every day and sintilimab once every 3 wk. Moreover, TACE was performed every 4-6 wk if necessary. The primary outcome of the study was overall survival (OS). The secondary outcomes were the objective response rate (ORR), disease control rate (DCR), and incidence of adverse events. RESULTS: Forty HCC patients who underwent triple therapy were retrospectively analysed from January 2019 to January 2022. With a median follow-up of 8.5 months, the 3-, 6-, and 12-mo OS rates were 100%, 88.5%, and 22.5%, respectively. The ORR and DCR were 45% and 90%, respectively. The median progressive free survival and median OS were not reached. Common complications were observed in 76% of the patients (grade 3, 15%; grade 4, 2.5%). CONCLUSION: Combination therapy comprising lenvatinib, sintilimab and TACE achieved promising outcomes in advanced HCC patients and had manageable effects.

Unsupervised graph anomaly detection with discriminative embedding similarity for viscoelastic sandwich cylindrical structures.

In the detection of slipping anomalies in viscoelastic sandwich cylindrical structures (VSCS), conventional methods may encounter challenges due to the extremely rare and weak nature of slipping signals. This study focuses on normal signals and introduces unsupervised graph representation learning (UGRL) with discriminative embedding similarity for VSCS's detection. UGRL involves data preprocessing, model embedding, and matrix reconstructing. Association graphs are constructed based on sample similarities for yielding adjacency and attribute matrices. Subsequently, the matrices undergo embedding and reconstruction via various network modules to enhance graph data characterization. Detection indicators are derived by calculating embedding similarities and reconstruction errors, and thresholds are constructed using these indicators to enable efficient anomaly detection. The experiments in VSCS slipping dataset effectively indicate the superiority of the proposed method.

[Retracted] AdipoR1­mediated miR­3908 inhibits glioblastoma tumorigenicity through downregulation of STAT2 associated with the AMPK/SIRT1 pathway.

Following the publication of this paper, it was drawn to the Editor's attention by a concerned reader that certain of the western blotting data shown in Figs. 3B and 9, and the migration assay data shown in Fig. 6C, were strikingly similar to data that had already appeared in other publications written by different authors at different research institutes. Owing to the fact that the contentious data in the above article had already been published prior to its submission to Oncology Reports, the Editor has decided that this paper should be retracted from the Journal. The authors were asked for an explanation to account for these concerns, but the Editorial Office did not receive a reply. The Editor apologizes to the readership for any inconvenience caused. [Oncology Reports 37: 3387­3396, 2017; DOI: 10.3892/or.2017.5589].

Airway microbiota correlated with pulmonary exacerbation in primary ciliary dyskinesia patients.

IMPORTANCE: PCD is a rare disease characterized by productive cough, rhinitis, and recurrent infections of the upper and lower airways. Because the diagnosis of PCD is often delayed, patients receive more antibiotics, experience a heavier financial burden, and have a worse prognosis; thus, it is very important to identify the pathogeny and use the correct antibiotic. In this large single-center study of PCD microbiota, we identified an outline of the bacterial microbes from the respiratory tract; furthermore, we found that the microbiota diversity in pediatric sputum was richer than that in pediatric BALF through sequencing, indicating a heterogeneous community structure. The microbiota diversity and richness were lower during pulmonary exacerbation than during pulmonary stabilization. A significantly higher abundance of Pseudomonas had a moderate distinguishing effect for lung exacerbation, which attracted more attention for the study of Pseudomonas therapy in pediatric patients with PCD.

A multicenter prospective study of TACE combined with lenvatinib and camrelizumab for hepatocellular carcinoma with portal vein tumor thrombus.

BACKGROUND AND AIMS: Hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT) predicts a poor prognosis. The aim of the present study was to evaluate the efficacy and safety of using lenvatinib and camrelizumab combined with transarterial chemoembolization (TACE) to treat HCC with PVTT. METHODS: This was a single-arm, open-label, multicenter, and prospective study. Eligible patients with advanced HCC accompanied by PVTT were enrolled to receive TACE combined with lenvatinib and camrelizumab. The primary endpoint was progression-free survival (PFS), while the secondary endpoints included objective response rate (ORR), disease control rate (DCR), overall survival (OS), and safety. RESULTS: Between April 2020 and April 2022, 69 patients were successfully enrolled. With a median follow-up time of 17.3 months, the median age of the patient cohort was 57 years (range: 49-64 years). According to modified Response Evaluation Criteria in Solid Tumors, the ORR was 26.1% (18 partial responses [PRs]) and the DCR was 78.3% (18 PRs, 36 stable diseases [SDs]). The median PFS (mPFS) and median OS (mOS) were 9.3 and 18.2 months, respectively. And tumor number >3 was identified as an adverse risk factor for both PFS and OS. The most common adverse events across all grades included fatigue (50.7%), hypertension (46.4%), and diarrhea (43.5%). Twenty-four patients (34.8%) experienced Grade 3 toxicity that was relieved by dose adjustment and symptomatic treatment. No treatment-related deaths occurred. CONCLUSIONS: TACE combined with lenvatinib and camrelizumab is a well-tolerated modality treatment with promising efficacy for advanced HCC with PVTT.

MIM-Graph: A multi-sensor network approach for fault diagnosis of HSR Bogie bearings at the IoT edge via mutual information maximization.

The Internet of Things (IoT) is crucial in developing next-generation high-speed railways (HSRs). HSR IoT enables intelligent diagnosis of trains using multi-sensor data, which is critical for maintaining high speeds and ensuring passenger safety. Graph neural network (GNN)-based methods have gained popularity in HSR IoT research due to the ability to represent the sensor network as intuitive graphs. However, labeling monitoring data in the HSR scenario takes time and effort. To address this challenge, we propose a semi-supervised graph-level representation learning approach called MIM-Graph, which uses mutual information maximization to learn from a large amount of unlabeled data. First, the multi-sensor data is converted into association graphs based on their spatial topology. The unsupervised encoder is trained using global-local mutual maximization. The teacher-student framework transfers knowledge from the unsupervised encoder learned to the supervised encoder, which is trained using a small amount of labeled data. As a result, the supervised encoder learns distinguishable representations for intelligent diagnosis of HSR. We evaluate the proposed method using CWRU dataset and data from HSR Bogie test platform, and the experimental results demonstrate the effectiveness and superiority of MIM-Graph.

Development of a Multivariate Prognostic Model for Lenvatinib Treatment in Hepatocellular Carcinoma.

BACKGROUND: Lenvatinib is a first-line agent for advanced hepatocellular carcinoma (HCC), but individual responses to treatment are highly heterogeneous. The aim of this study was to investigate the clinical parameters that influence the efficacy of Lenvatinib and to develop a prognostic model. METHODS: We retrospectively enrolled 333 Lenvatinib-treated patients with HCC with a median age of 57 years. Two hundred nd sixty-three of these patients had BCLC (2022) stage C. The median overall survival (mOS) time within the cohort was 12.1 months, and the median progression-free survival (mPFS) time was 4.7 months. Univariate Cox regression, best subset regression, and Lasso regression were used to screen primary variables for possible contribution to OS, multivariate Cox analysis was used to fit selected models, and the final model was selected using the maximum area under the curve (AUC) and minimum AIC. Receiver operating curves (ROC), calibration curves, and decision curve analysis were plotted to assess model performance, and 5-fold cross-validation was performed for internal validation. X-tile software was used to select the best cutoff points and to divide the study cohort into 3 different risk groups. RESULTS: Seven variables were included in the final model: BCLC stage, prior transarterial chemoembolization and immunotherapy history, tumor number, prognostic nutritional index, log (alpha-fetoprotein), and log (platelet-to-lymphocyte ratio). We named this final model the "multivariate prognostic model for Lenvatinib" (MPML), and a nomogram was constructed to predict the probability of survival at 6, 9, and 12 months. The MPML had good discrimination, calibration, and applicability. Cross-validation showed mean AUC values of 0.7779, 0.7738, and 0.7871 at 6, 9, and 12 months, respectively. According to nomogram points, mOS time was 21.57, 8.70, and 5.37 months in the low, medium, and high-risk groups, respectively (P < .001), and these differences were also observed in the PFS survival curve (P < .001). CONCLUSIONS: The MPML stratified patients according to baseline clinical characteristics had a strong performance in predicting Lenvatinib efficacy and has the potential for use as an auxiliary clinical tool for individualized decision-making.

Theoretical Design of an Mox W1-x S2 /Graphene (x=0.25/0.75) Heterojunction with Adjustable Band Gap: Potential Candidate Materials for the Next Generation of Optoelectronic Devices.

Multicomponent two-dimensional (2D) transition metal dichalcogenides (TMDCs) semiconductors based on adjustable band gap are increasingly used to design optoelectronic devices with specific spectral response. Here, we have designed the Mox W1-x S2 /graphene heterostructure with adjustable band gap by adopting the combination idea of alloying and multiple heterogeneous recombination. The contact type, stability and photoelectric properties of Mox W1-x S2 /graphene heterojunction were investigated theoretically. At the same time, by applying external vertical electric field to Mox W1-x S2 /graphene, the regulate of heterojunction Schottky contact type was realized. The results show that Mox W1-x S2 /graphene heterojunction has broad application prospects in the field of photocatalysis and Schottky devices, and is suitable for being a potential candidate material for next generation of optoelectronic devices. The design of Mox W1-x S2 /graphene heterostructure enables it to obtain the advanced characteristics that are lacking in the one-component intrinsic 2D TMDCs semiconductors or graphene materials, and provides a theoretical basis for the experimental preparation of such heterojunctions.