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Immune checkpoint inhibitor monotherapy did not show superiority of survival over standard therapy in advanced hepatocellular carcinoma. The combination immunotherapy including dual immune checkpoint inhibitors or combined with anti-VEGF agents have become a trend, but not fully evaluated. This study aimed to evaluate and compare distinct combination immunotherapy on efficacy in advanced hepatocellular carcinoma.PubMed, Embase, Web of Science and Cochrane databases were systematically searched from inception to January 31, 2022. The primary endpoints were overall objective response rate (ORR), disease control rate (DCR), six-month progression-free survival rate (PFSR6m) and one-year overall survival rate (OSR1y).11 studies with 16 independent cohorts and 3342 patients were included in the meta-analysis. Compared with first-line sorafenib, combination immunotherapy resulted in a significant improvement in ORR (RR, 2.74; 95%CI, 1.55-4.85; p = 0.0006), PFS (HR, 0.57; 95%CI, 0.49-0.65; p0.0001) and OS (HR, 0.65; 95%CI, 0.52-0.82; p = 0.0002). Based on RECIST 1.1, the pooled ORR, PFSR6m and OSR1y for combination immunotherapy were 24.6% (95%CI: 20.3%-29.6%), 42.0% (95%CI: 34.2%-50.3%) and 61.8% (95%CI: 57.7%-65.7%), respectively. In distinct combination regimens, PD-1/L1 inhibitors plus anti-VEGF agents showed a significant superiority of clinical benefit than PD-1/L1 inhibitors plus CTLA-4 inhibitors (ORR: 25.2% vs 23.4%, p = 0.033; PFSR6m: 47.4% vs 23.2%, p0.001; OSR1y: 65.1% vs 55.0%, p = 0.001).This study was the first meta-analysis to demonstrate the better survival benefit and tolerable toxicity of combination immunotherapy than standard therapy in advanced hepatocellular carcinoma. Compared with PD-1/L1 inhibitors plus CTLA-4 inhibitors, the regimens of PD-1/L1 inhibitors plus anti-VEGF agents may be associated with a significantly better clinical benefit. The difference in long-term survival and response population between two distinct combination regimens required further exploration.

Minli Zhu,1 Leying Wang,1 Zhangming Zhuge,1 Wei Li,1,2 Yihui Zheng,1 Jingyun Mai,1 Zhenlang Lin,1 Jing Lin1,3 1Key Laboratory of Perinatal Medicine of Wenzhou, Department of Neonatology, the Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou, 325027, People’s Republic of China; 2Zhijin People’s Hospital of Guizhou Province, Guizhou, 552100, People’s Republic of China; 3Department of Pediatrics, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USACorrespondence: Jing Lin, Department of Pediatrics, Icahn School of Medicine at Mount Sinai, One Gustave Levy Place, New York, NY, 10029, USA, Tel +1-212-241-6186, Fax +1-212534-5207, Email jing.lin@mssm.edu Zhenlang Lin, Department of Neonatology, the Second Affiliated Hospital and Yuying Children’s Hospital, Wenzhou Medical University, Wenzhou, 325027, People’s Republic of China, Tel +86 13806689800, Email linzhenlang@hotmail.comBackground and Objective: An increasing number of cases of neonatal sepsis due to extended-spectrum beta-lactamase (ESBL)-producing multi-drug resistant (MDR) Escherichia coli (E. coli) have been reported worldwide. The aim of this study was to explore the risk factors associated with ESBL-producing MDR E. coli among neonates with culture-confirmed E. coli sepsis and thereby to help selection of appropriate empirical antibiotics.Patients and Methods: All newborn infants with a confirmed pathogen isolated from blood or cerebrospinal fluid (CSF) from 2016 to 2021 were identified and those with E. coli infection were included in this analysis. We compared a group of neonatal patients with ESBL-producing MDR E. coli sepsis (n=69) to a group with ESBL-negative E. coli (n=70) based on antimicrobial susceptibility reports. We used multivariable regression analysis to determine the risk factors associated with ESBL-producing MDR E. coli strains among the neonates with culture-confirmed E. coli sepsis.Results: ESBL-producing MDR E. coli sepsis was more common in premature infants and newborns with hospital-acquired late-onset sepsis (HALOS). The mortality rate of neonatal sepsis caused by ESBL-producing E. coli was about twice as that of sepsis caused by ESBL-negative E. coli. Antepartum exposure to cephalosporins (OR=25.191, 95% CI: 3.184– 199.326, P< 0.01) and parenteral nutrition for more than 1 week (OR=4.495, 95% CI: 2.009– 10.055, P< 0.01) were independent risk factors for neonatal infection with ESBL-producing stains among infants with E. coli sepsis.Conclusion: E. coli remains the most common Gram-negative bacterial pathogen causing neonatal sepsis. A higher proportion of ESBL-producing MDR E. coli is seen in premature infants and those newborns with HALOS and is associated with higher mortality. Antepartum use of cephalosporins and prolonged use of parenteral nutrition may be important factors to consider in the selection of empirical antibiotics for use in neonatal sepsis caused by gram-negative rods prior to the availability of the results of antimicrobial susceptibility.Keywords: infant, newborn, neonatal sepsis, Escherichia coli, drug resistance, extended-spectrum beta-lactamase

Sensitivity analysis (SA) intends to identify the key meteorological variables that affect the performance of reference crop evapotranspiration (ET0) models. It is of importance in assessing the variability of meteorological variables and ET0, especially in the face of increasing climate uncertainties. However, the surging of inconsistencies resulting from global changes in meteorological conditions due to climate change have impacted the ET0 model estimation in different regions, with detrimental effects on water resources and crop production. Therefore, efficient SA is necessary to evaluate the impact of changes in meteorological variables that influence ET0 model estimation. This mini review analyses the various SA methods applied in the field of ET0, based on a comprehensive and comparative analysis of existing SA methods from all around the world. The study discusses the advantages and disadvantages of each SA method, as well as the factors affecting the SA of ET0. The study also provides future prospects that may contribute to more solid and powerful analysis for ET0 model estimations and conclusions.

Background. There is currently limited evidence for a correlation between the recommended operation and overall survival (OS) in patients with advanced non-small-cell lung cancer (NSCLC). Methods. NSCLC patients with stages III and IV, recommended for operation, were identified in the US National Cancer Institute Surveillance, Epidemiology, and End Results database (SEER).We used propensity score matching (PSM) and multivariable Cox proportional hazards regression to ensure the robustness of our findings. The cumulative rates of death were compared between patients with and without recommended operations using the Kaplan−Meier curves. Results. Operation was recommended for 3331 patients but was not performed in 912 (27.4%) patients (then on-operative group). After PSM, 553 pairs matched. Compared to the nonoperative group, the hazard ratios (HRs) in the operative group were 0.46 (95% CI 0.23–0.95 and p = 0.037 ) in stage IIIA and 0.54 (95% CI 0.42–0.68 and p < 0.001 ) in stage IVA. However, in stages IIIB, IIIC, and IVB, the recommended operative group was not associated with better OS. The OS was not different in stage IIIA-N2, stage IVA-N1, and stage IVA-N3 patients between groups ( p = 0.28 , p = 0.14 , and p = 0.79 , respectively). Moreover, the recommended operative group had better OS than the nonoperative group in stage IIIA-N0 ( p = 0.00085 ), stage IIIA-N1 ( p = 0.009 ), stage IVA-N0 ( p < 0.001 ), and stage IVA-N2 ( p = 0.034 ). Conclusion. Compared to the nonoperative group, recommended operation improved survival in NSCLC patients with stage IIIA-N0, stage IIIA-N1, stage IVA-N0, and stage IVA-N2. However, in stages IIIA-N2, IIIB, IIIC, IVA-N1, IVA-N3, and IVB, recommended operation did not lead to significantly improved survival time.

A Pd–COOCH3 species in the vapor-phase carbonylation of methyl nitrite is revealed to have two-fold reactivity, where the nucleophilicity of the Pd–C bond enables C–C coupling to give DMO and the electrophilicity of the π* orbital facilitates C–O coupling to afford DMC.

A new composite hydrogel adsorbent for adsorption of Pb2+ has been prepared by combining porous boron nitride nanofibers (BNNFs) and the acrylamide and sodium acrylate copolymer (P(AANa-co-AM)) via a chemical crosslinking method.

A pH-stable and solvent-stable Eu3+-based MOF can selectively and sensitively recognize Cr3+/Al3+/Ga3+via obvious turn-on and blue-shift fluorescence. More interestingly, the fluorescence test papers and LED lamps have been successfully developed.

This review gives focused attention on in vivo anion imaging based on activatable organic photoacoustic probes, with emphasis on imaging mechanisms at the molecular level, to inspire innovative ideas for future theranostics of diseases.

A water and pH stable CdII-based MOF can be used as a good sensor for Hg2+ ions in aqueous solution. Intriguingly, LED lamps, test papers and luminescent films have been successfully developed to simply detect Hg2+ ions.

The wheel–rail interaction will be intensified on account of the complexity of the wheel–rail contact geometry on a curved track. It also may become more complicated and/or have significant difference as the train speed increases, since the dynamic effects cannot be ignored then. In this study, based on explicit Finite Element (FE) software LS-DYNA 971, a Three-Dimensional (3D) elastic-plastic FE model was built to simulate the dynamic wheel–rail contact behaviour of curve negotiating, where the superelevation and roll angle as well as the strain rate effect were considered. The evolution of contact patch and pressure, wheel–rail contact force, the stress/strain state and the acceleration of the axle were employed to examine the wheel–rail transient dynamic response. Furthermore, the influences of axle load, curve radius and strain rate effect were also discussed. It is found that the maximum vertical contact force, contact pressure, stress and strain on the curved track increase with the decreasing curve radius, and they increase with the increasing axle load except for lateral contact force. The wheel–rail dynamic responses on the curved track are significantly enhanced compared to the straight track. Moreover, the strain rate effect can enhance von-Mises stress and contact pressure, suppress the plastic deformation of the rail and wheel, but it has little effect on the vertical and lateral contact forces and stable acceleration of axle. The Rate-Sensitive Factors (RSF) of the wheel and rail on the curved track are weaker than those on the straight track. These findings will be very helpful to study the competitive relationship between the rolling contact fatigue and wear, as well as the crack initiation and propagation problem.

The design of highly electron-active and stable heterogeneous catalysts for the ambient nitrogen reduction reaction is challenging due to the inertness of the N

Peptide quantitative structure-activity relationships (pQSARs) have been widely applied to the statistical modeling and empirical prediction of peptide activity, property and feature. In the procedure, the peptide structure is characterized at sequence level using amino acid descriptors (AADs) and then correlated with observations by machine learning methods (MLMs), consequently resulting in a variety of quantitative regression models used to explain the structural factors that govern peptide activities, to generalize peptide properties of unknown from known samples, and to design new peptides with desired features. In this study, we developed a comprehensive platform, termed PepQSAR database, which is a systematic collection and decomposition of various data sources and abundant information regarding the pQSARs, including AADs, MLMs, data sets, peptide sequences, measured activities, model statistics, and literatures. The database also provides a comparison function for the various previously built pQSAR models reported by different groups via distinct approaches. The structured and searchable PepQSAR database is expected to provide a useful resource and powerful tool for the computational peptidology community, which is freely available at http://i.uestc.edu.cn/PQsarDB .

To investigate the performance of spleen to non-cancerous liver volume ratio (STnLR) for diagnosing liver cirrhosis in patients with hepatocellular carcinoma (HCC) during preoperative evaluation.Patients were randomly divided into experiment group and validation group. Patients were grouped into cirrhosis group and non-cirrhosis group according to Scheuer staging. Patients' routine image data were reconstructed using a three-dimensional system. STnLR, spleen to liver volume ratio (STLR), spleen volume, aspartate aminotransferase to platelet ratio index (APRI), and fibrosis index based on the four factors (FIB-4) were calculated. Correlations between indices and cirrhosis were measured by Spearman correlation analysis. Diagnostic performance was assessed and compared using receiver operating characteristic analysis. Accuracies of the models were analyzed in validation group.No statistical difference in demographic and clinical characteristics was observed between groups. In experiment group, STnLR had the strongest correlation (r = 0.5399, P 0.0001), and STLR, spleen volume, APRI, and FIB-4 had moderate correlations (r = 0.4583, 0.4123, 0.3648, and 0.3405, P 0.0001, 0.0001, 0.0001, and = 0.0002) with liver cirrhosis stage. AUROC of STnLR (0.8326) was not statistically higher than that for spleen volume (0.7542, P = 0.09832) and STLR (0.8046, P = 0.3034), but was significantly higher than that for APRI (0.7099, P = 0.02046) and FIB-4 (0.7294, P = 0.03987). In validation group, STnLR showed the highest AUROC value (0.8538) and highest Youden index (0.5869) among all models.STnLR is an accurate and stable volumetric model to diagnose hepatic cirrhosis in the HCC population, which is superior to APRI and FIB-4.

To evaluate whether exosomal circRNAs could serve as diagnostic biomarkers for the accurate preoperative prediction of lymph node metastasis (LNM) risk in oral squamous cell carcinoma (OSCC) patients.A combinative strategy of exosomal circRNAs microarray and qRT-PCR verification was employed to dig LNM-related circRNA signatures. Then, a dynamic nomogram was developed based on candidate circRNAs and preoperative clinical features and the calibration, discrimination, and clinical use of the nomogram were evaluated.According to the microarray, three circRNAs derived from the tumor were associated with preoperative LNM risk, including hsa_circRNA_047733, hsa_circRNA_024144 and hsa_circRNA_403472. The hsa_circRNA_047733 was further verified to be significantly downregulated in patients with LNM (+) as compared with those with LNM (-) (p = 0.007). Patients with the higher expression of hsa_circRNA_047733 showed a lower risk of LNM (multivariate-adjusted OR = 0.22, 95%CI: 0.06-0.83). The bioinformatics prediction showed that hsa_circRNA_047733 might sponge miR-4464/miR-4748 to regulate RPS21 expression. A dynamic nomogram integrating exosomal hsa_circRNA_047733 with five clinicopathological characteristics (tumor site, leukocyte level, maximum tumor diameter, and LNM reported by MRI and preoperative biopsy differentiation) was developed. The model displayed an excellent discrimination ability (AUC = 0.868, 95%CI: 0.781-0.955) and great calibration. The decision curve revealed a higher net benefit superior to the baseline model at an 80% threshold probability.The data provide preliminary evidence that exosomal hsa_circRNA_047733 might be a novel biomarker for the LNM of OSCC. The hsa_circRNA_047733-based dynamic nomogram could serve as a convenient preoperative assessment tool to predict the risk of LNM for OSCC patients.

Heterogeneous sequential recommendation that models sequences of items associated with more than one type of feedback such as examinations and purchases is an emerging topic in the research community, which is also an important problem in many real-world applications. Though there are some methods proposed to exploit different types of feedback in item sequences such as RLBL, RIB, and BINN, they are based on RNN and may not be very competitive in capturing users’ complex and dynamic preferences. And most existing advanced sequential recommendation methods such as the CNN- and attention-based methods are often designed for making use of item sequences with one single type of feedback, which thus can not be applied to the studied problem directly. As a response, we propose a novel feedback-aware local and global (FLAG) preference learning model for heterogeneous sequential recommendation. Our FLAG contains four modules, including (i) a local preference learning module for capturing a user’s short-term interest, which adopts a novel feedback-aware self-attention block to distinguish different types of feedback; (ii) a global preference learning module for modeling a user’s global preference; (iii) a local intention learning module, which takes a user’s real feedback in the next step, i.e., the user’s intention at the current step, as the query vector in a self-attention block to figure out the items that match the user’s intention well; and (iv) a prediction module for preference integration and final prediction. We then conduct extensive experiments on three public datasets and find that our FLAG significantly outperforms 13 very competitive baselines in terms of two commonly used ranking-oriented metrics in most cases. We also include ablation studies and sensitivity analysis of our FLAG to have more in-depth insights.

Although many material designs or strategic methods have been proposed for treating oil spills and oily wastewater, the complex oily state, dealing with the harsh operating conditions of oil–water separation (such as the recovery of viscous spilled crude oil, bacteria-containing oily wastewater, and removal of spilled oil under fire), and the autorecycling of oil and absorption materials remain a great challenge. This work proposed an ingenious design strategy of “several birds with one stone” to prepare pH/thermoresponsive flame-retardant/photothermal bactericidal P-Fe3O4-polydopamine (PDA)@melamine–formaldehyde (MF) foams. This design makes the foams remarkably effective in the recovery of spilled viscous crude oil as well as in the separation of bacteria-containing oily emulsions, particularly for instant fire extinguishing by magnetically controlled oil absorption as well as for fire alarms. The photothermal effect and pH response induce a change in the surface wettability of the foams, facilitating excellent autoadsorption/desorption of the spilled oil. The photothermal bactericidal activity and fouling resistance of the foam are beneficial to the separation of bacteria-containing oily wastewater. Outstanding flame-retardant properties and maneuverable magnetic control enable the foam to rapidly recover the spilled oil in a large range of fires, extinguish fires instantly, and facilitate early fire warning. The proposed strategy is expected to inspire further research on treating oil spills under complex conditions.

To preoperatively predict lymph node metastasis (LNM) in patients with cervical nonsquamous cell carcinoma (non-SCC) based on magnetic resonance imaging (MRI) texture analysis.This retrospective study included 104 consecutive patients (mean age of 47.2 ± 11.3 years) with stage IB-IIA cervical non-SCC. According to the ratio of 7:3, 72, and 32 patients were randomly divided into the training and testing cohorts. A total of 272 original features were extracted. In the process of feature selection, features with intraclass correlation coefficients (ICCs) less than 0.8 were eliminated. The Pearson correlation coefficient (PCC) and analysis of variance (ANOVA) were applied to reduce redundancy, overfitting, and selection biases. Further, a support vector machine (SVM) with linear kernel function was applied to select the optimal feature set with a high discrimination power.The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI + DWI + LNS-MRI (LN status on MRI)-based SVM models yielded an AUC and accuracy of 0.78 and 0.79; 0.79 and 0.69; 0.79 and 0.81 for predicting LNM in the training cohort, and 0.82 and 0.78; 0.82 and 0.69; 0.79 and 0.72 in the testing cohort. The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI + DWI + LNS-MRI-based SVM models performed better than morphologic criteria of LNS-MRI and yield similar discrimination abilities in predicting LNM in the training and testing cohorts (all p-value0.05). In addition, the T2WI + DWI-based and T2WI + DWI + LNS-MRI-based SVM models showed robust performance in the AC and ASC subgroups (all p-value0.05).The T2WI + DWI-based, T2WI + DWI + CE-T1WI-based and T2WI+DWI+LNS-MRI-based SVM models showed similar good discrimination ability and performed better than the morphologic criteria of LNS-MRI in predicting LNM in patients with cervical non-SCC. The inclusion of the CE-T1WI sequence and morphologic criteria of LNS-MRI did not significantly improve the performance of the T2WI + DWI-based model. The T2WI + DWI-based and T2WI + DWI + LNS-MRI-based SVM models showed robust performance in the subgroup analysis.