Radiomic feature repeatability and its impact on prognostic model generalizability: A multi-institutional study on nasopharyngeal carcinoma patients

BACKGROUND AND PURPOSE

To investigate the radiomic feature (RF) repeatability via perturbation and its impact on cross-institutional prognostic model generalizability in Nasopharyngeal Carcinoma (NPC) patients.

MATERIALS AND METHODS

286 and 183 NPC patients from two institutions were included for model training and validation. Perturbations with random translations and rotations were applied to contrast-enhanced T1-weighted (CET1-w) MR images. RFs were extracted from primary tumor volume under a wide range of image filtering and discretization settings. RF repeatability was assessed by intraclass correlation coefficient (ICC), which was used to equally separate the RFs into low- and high-repeatable groups by the median value. After feature selection, multivariate Cox regression and Kaplan-Meier analysis were independently employed to develop and analyze prognostic models. Concordance index (C-index) and P-value from log-rank test were used to assess model performance.

RESULTS

Most textural RFs from high-pass wavelet-filtered images were susceptible to image perturbations. It was more prominent when a smaller discretization bin number was used (e.g., 8, mean ICC = 0.69). Using high-repeatable RFs for model development yielded a significantly higher C-index (0.63) in the validation cohort than when only low-repeatable RFs were used (0.57, P = 0.024), suggesting higher model generalizability. Besides, significant risk stratification in the validation cohort was observed only when high-repeatable RFs were used (P < 0.001).

CONCLUSION

Repeatability of RFs from high-pass wavelet-filtered CET1-w MR images of primary NPC tumor was poor, particularly when a smaller bin number was used. Exclusive use of high-repeatable RFs is suggested to safeguard model generalizability for wide-spreading clinical utilization.

Conversion surgery for advanced hepatocellular carcinoma after combination treatment of lenvatinib and camrelizumab: a case report

BACKGROUND

Hepatocellular carcinoma (HCC) is an aggressive malignancy with high morbidity and mortality. Conversion therapy can improve surgical resection rate and prolong survival time for patients with advanced HCC. We show that combination therapy with lenvatinib and camrelizumab is a novel approach to downstage unresectable HCC.

CASE PRESENTATION

A 49-year-old man was diagnosed with massive HCC with hilar lymph node and lung metastases. Since radical resection was not feasible, lenvatinib and camrelizumab were administered as first-line therapy. After 10 cycles of camrelizumab and continuous oral administration of lenvatinib, the tumor exhibited striking shrinkage in volume indicating a partial radiological response, accompanied by a reduction in the alpha-fetoprotein levels, followed by salvage resection. Intriguingly, an improvement in predictive biomarkers, like lactate dehydrogenase (LDH) and neutrophil-to-lymphocyte ratio (NLR), was observed. Notably, the pathological examination found high levels of necrosis in the resected tumor, and flow cytometry analysis indicated a significant increase in the ratio of CD5+ and CD5- B lymphocytes in the peripheral blood. After the treatment, the overall survival period was over 24 months, and no recurrence was observed 17-month post-surgery.

CONCLUSIONS

A combination of lenvatinib and camrelizumab may be a new conversion therapy for initially unresectable HCC to resectable HCC, thus contributing to improve the disease prognosis. In addition, the combination regimen could cause an activated immune response, and LDH, NLR, and CD5+ B-cell levels might be predictors for immunotherapy efficacy.

Lorentz factor for time-of-flight neutron Bragg and total scattering

The three fundamental origins of the Lorentz factor for neutron time-of-flight powder diffraction are revisited. A detailed derivation of the Lorentz factor is presented in the context of diffuse scattering modelling in reciprocal space when perfect periodicity is assumed, and the total scattering pattern is constructed in its discrete form - the factor in this case becomes 1/Q² (or d²). Discussion is also presented with respect to practical data reduction where a vanadium measurement is usually taken as the normalization factor (to account for various factors such as detector efficiency), and it is shown that the existence of the Lorentz factor is independent of such a normalization process.

Ferroelectric Ordering in Nanosized PbTiO3

The insight into the three-dimensional configuration of ferroelectric ordering in ferroelectric nanomaterials is motivated by the application of the development of functional nanodevices and the structural designing. However, the atomic deciphering of the spatial distribution of ordered structure remains challenging for the limitation of dimension and probing techniques. In this paper, a neutron pair distribution function (nPDF) was utilized to analyze the spontaneous polarization distribution of zero-dimensional PbTiO₃ nanoparticles in three dimensions, via the application of reverse Monte Carlo (RMC) modeling. The comprehensive identification with transmission electron microscopy verified the linear characteristics of polarization along the c-axis in the main body, while electric polarization distribution on the surface was enhanced abnormally. In addition, the correlation of dipole vectors extending to three unit cells below the surface is retained. This work shows an application of the micro/macroscale information to effectively decode the polarization structure of nanoferroelectrics, providing new views of designing nanoferroelectric devices.

[Research progress of interstitial lung disease combined with lung cancer]

Interstitial lung disease combined with lung cancer (ILD-LC) has attracted more and more attention. Interstitial lung disease (ILD) is an independent risk factor of lung cancer. ILD and lung cancer have common pathogenesis of promoting fibrosis and promoting cancer, so they are not only comorbidities. This review updated the epidemiology, pathogenesis and incidence and risk factors of treatment-induced acute exacerbation(including surgery, chemotherapy, and radiotherapy)in ILD-LC. The purpose is to improve the understanding, individual management and quality of life of patients in ILD-LC.

A gamma ray spectrometer with Compton suppression on the HL-2A tokamak

A new broad-energy, high-resolution gamma ray spectrometer (GRS) with Compton suppression function has been developed recently in the HL-2A tokamak to obtain the gamma ray information in the energy range of 0.1-10 MeV. This is the first time to develop an anti-Compton GRS for a magnetic confinement fusion device. The anticoincidence detector consists of a large-volume high purity germanium (HPGe) crystal (Φ63 × 63 mm²) as the primary detector and eight trapezoidal bismuth germinate (BGO) scintillators (trapezoid crystal with 30 mm thickness) as the secondary detector. The anti-coincidence data processing is implemented by a digital-based data acquisition system with fast digitization and software signal processing technology. Using radioisotope gamma ray sources and Monte Carlo N-Particle code, the energy and efficiency of the spectrometer have been calibrated and quantitatively tested. The Compton continuum suppression factor reaches 4.2, and the energy resolution (Full Width at Half Maximum) of the 1.332 MeV full energy peak for ⁶⁰Co is 2.1 keV. Measurements of gamma ray spectra with Compton suppression using the spectrometer have been successfully performed during HL-2A discharges with different conditions. The performance of the spectrometer and the first experimental results are presented in this paper.

[Effect of P62 on the migration and motility of human epidermal cell line HaCaT in high glucose microenvironment and its mechanism]

Objective: To investigate the effect of P62 on the migration and motility of human epidermal cell line HaCaT in high glucose microenvironment and its possible molecular mechanism, so as to explore the mechanism of refractory diabetic foot wound healing. Methods: The method of experimental research was used. HaCaT cells in logarithmic growth phase was taken for experiment. The cells were collected and divided into normal control group (culture solution containing glucose with final molarity of 5.5 mmol/L) and high glucose (culture solution containing glucose with final molarity of 30.0 mmol/L) 24 h group, high glucose 48 h group, and high glucose 72 h group according to the random number table (the same grouping method below). The cells in normal control group were routinely cultured for 72 h, cells in high glucose 72 h group were cultured with high glucose for 72 h, cells in high glucose 48 h group were routinely cultured for 24 h then cultured with high glucose for 48 h, cells in high glucose 24 h group were routinely cultured for 48 h then cultured with high glucose for 24 h. Then the protein expression of P62 was detected by Western blotting. The cells were collected and divided into normal control group and high glucose group. After being correspondingly cultured for 48 h as before, the protein expression of P62 was detected by immunofluorescence method (indicated as green fluorescence). The cells were collected and divided into negative control small interfering RNA (siRNA) group, P62-siRNA-1 group, P62-siRNA-2 group, and P62-siRNA-3 group, and transfected with the corresponding reagents. At post transfection hour (PTH) 72, the protein expression of P62 was detected by Western blotting. The cells were collected and divided into normal glucose+negative control siRNA group, normal glucose+P62-siRNA group, high glucose+negative control siRNA group, and high glucose+P62-siRNA group. After the corresponding treatment, the protein expression of P62 was detected by Western blotting at PTH 72 h, the cell migration rate was detected and calculated at 24 h after scratching by scratch test, with the number of samples being 9; and the range of cell movement was observed and the trajectory velocity was calculated within 3 h under the living cell workstation, with the number of samples being 76, 75, 80, and 79 in normal glucose+negative control siRNA group, normal glucose+P62-siRNA group, high glucose+negative control siRNA group, and high glucose+P62-siRNA group, respectively. The cells were collected and divided into normal glucose+phosphate buffered solution (PBS) group, high glucose+PBS group, and high glucose+N-acetylcysteine (NAC) group. After the corresponding treatment, the protein expression of P62 at 48 h of culture was detected by Western blotting and immunofluorescence method, respectively. Except for scratch test and cell motility experiment, the number of samples was all 3 in the rest experiments. Data were statistically analyzed with one-way analysis of variance and least significant difference test. Results: Compared with the protein expression in normal control group, the protein expressions of P62 of cells in high glucose 24 h group, high glucose 48 h group, and high glucose 72 h group were significantly increased (P<0.01). At 48 h of culture, the green fluorescence of P62 of cells in high glucose group was stronger than that in normal control group. At PTH 72, compared with the protein expression in negative control siRNA group, the protein expressions of P62 of cells in P62-siRNA-1 group, P62-siRNA-2 group, and P62-siRNA-3 group were significantly decreased (P<0.01). At PTH 72, compared with the protein expression in normal glucose+negative control siRNA group, the protein expression of P62 of cells in normal glucose+P62-siRNA group was significantly decreased (P<0.01), while the protein expression of P62 of cells in high glucose+negative control siRNA group was significantly increased (P<0.01); compared with the protein expression in high glucose+negative control siRNA group, the protein expression of P62 of cells in high glucose+P62-siRNA group was significantly decreased (P<0.01). At 24 h after scratching, compared with (55±7)% in normal glucose+negative control siRNA group, the cell migration rate in normal glucose+P62-siRNA group was significantly increased ((72±14)%, P<0.01), while the cell migration rate in high glucose+negative control siRNA group was significantly decreased ((37±7)%, P<0.01); compared with that in high glucose+negative control siRNA group, the cell migration rate in high glucose+P62-siRNA group was significantly increased ((54±10)%, P<0.01). Within 3 h of observation, the cell movement range in high glucose+negative control siRNA group was smaller than that in normal glucose+negative control siRNA group, while the cell movement range in normal glucose+P62-siRNA group was larger than that in normal glucose+negative control siRNA group, and the cell movement range in high glucose+P62-siRNA group was larger than that in high glucose+negative control siRNA group. Compared with that in normal glucose+negative control siRNA group, the cell trajectory speed in normal glucose+P62-siRNA group was significantly increased (P<0.01), while the cell trajectory speed in high glucose+negative control siRNA group was significantly decreased (P<0.01); compared with that in high glucose+negative control siRNA group, the cell trajectory speed in high glucose+P62-siRNA group was significantly increased (P<0.01). At 48 h of culture, compared with that in normal glucose+PBS group, the protein expression of P62 of cells in high glucose+PBS group was significantly increased (P<0.01); compared with that in high glucose+PBS group, the protein expression of P62 of cells in high glucose+NAC group was significantly decreased (P<0.01). At 48 h of culture, the green fluorescence of P62 of cells in high glucose+PBS group was stronger than that in normal glucose+PBS group, while the green fluorescence of P62 of cells in high glucose+NAC group was weaker than that in high glucose+PBS group. Conclusions: In HaCaT cells, high glucose microenvironment can promote the protein expression of P62; knockdown of P62 protein can promote the migration and increase the mobility of HaCaT cells; and the increase of reactive oxygen species in high glucose microenvironment may be the underlying mechanism for the increase of P62 expression.

[Investigation on influenza vaccination policy and vaccination situation during the influenza seasons of 2020-2021 and 2021-2022 in China]

Objective: To investigate the policies and coverage of influenza vaccine during the influenza epidemic seasons of 2020-2021 and 2021-2022 in China. Methods: The national influenza vaccination policy and vaccination rate were investigated in counties and districts and described in the two epidemic seasons. Results: In the epidemic seasons of 2020-2021 and 2021-2022, the vaccination coverage of influenza in China was 3.16% and 2.47%, respectively. The free vaccination policy had the highest vaccination coverage (51.75% and 38.32%), followed by the medical insurance reimbursement policy (9.74% and 7.36%). During the epidemic season of 2021-2022, the number of counties and districts implementing the free vaccination policy in China decreased 61 compared with the previous year, but the number of people covered increased by 51.29%. However, the vaccination coverage of the vast population decreased significantly, with the medical staff (75.69% and 40.15% for two epidemic seasons), preschool children (58.86% and 26.15%), and the elderly (45.71% and 32.94%). During the epidemic season of 2021-2022, the number of counties and districts implementing the medical insurance reimbursement policy increased by 6 compared with the previous year, and the number of people covered increased by 11.12%, but the vaccination coverage decreased. Conclusion: The influenza vaccination rate in China is low, and the implementation of cost preferential policy can greatly improve the influenza vaccination rate.

[Investigation on influenza vaccination policy and vaccination situation during the influenza seasons of 2020-2021 and 2021-2022 in China]

Objective: To investigate the policies and coverage of influenza vaccine during the influenza epidemic seasons of 2020-2021 and 2021-2022 in China. Methods: The national influenza vaccination policy and vaccination rate were investigated in counties and districts and described in the two epidemic seasons. Results: In the epidemic seasons of 2020-2021 and 2021-2022, the vaccination coverage of influenza in China was 3.16% and 2.47%, respectively. The free vaccination policy had the highest vaccination coverage (51.75% and 38.32%), followed by the medical insurance reimbursement policy (9.74% and 7.36%). During the epidemic season of 2021-2022, the number of counties and districts implementing the free vaccination policy in China decreased 61 compared with the previous year, but the number of people covered increased by 51.29%. However, the vaccination coverage of the vast population decreased significantly, with the medical staff (75.69% and 40.15% for two epidemic seasons), preschool children (58.86% and 26.15%), and the elderly (45.71% and 32.94%). During the epidemic season of 2021-2022, the number of counties and districts implementing the medical insurance reimbursement policy increased by 6 compared with the previous year, and the number of people covered increased by 11.12%, but the vaccination coverage decreased. Conclusion: The influenza vaccination rate in China is low, and the implementation of cost preferential policy can greatly improve the influenza vaccination rate.

Radiomics-Based Detection of COVID-19 from Chest X-ray Using Interpretable Soft Label-Driven TSK Fuzzy Classifier

The COVID-19 pandemic has posed a significant global public health threat with an escalating number of new cases and death toll daily. The early detection of COVID-related CXR abnormality potentially allows the early isolation of suspected cases. Chest X-Ray (CXR) is a fast and highly accessible imaging modality. Recently, a number of CXR-based AI models have been developed for the automated detection of COVID-19. However, most existing models are difficult to interpret due to the use of incomprehensible deep features in their models. Confronted with this, we developed an interpretable TSK fuzzy system in this study for COVID-19 detection using radiomics features extracted from CXR images. There are two main contributions. (1) When TSK fuzzy systems are applied to classification tasks, the commonly used binary label matrix of training samples is transformed into a soft one in order to learn a more discriminant transformation matrix and hence improve classification accuracy. (2) Based on the assumption that the samples in the same class should be kept as close as possible when they are transformed into the label space, the compactness class graph is introduced to avoid overfitting caused by label matrix relaxation. Our proposed model for a multi-categorical classification task (COVID-19 vs. No-Findings vs. Pneumonia) was evaluated using 600 CXR images from publicly available datasets and compared against five state-of-the-art AI models in aspects of classification accuracy. Experimental findings showed that our model achieved classification accuracy of over 83%, which is better than the state-of-the-art models, while maintaining high interpretability.

Mutual Supervised Fusion & Transfer Learning with Interpretable Linguistic Meaning for Social Data Analytics

Social data analytics is often taken as the most commonly used method for community discovery, product recommendations, knowledge graph, etc. In this study, social data are firstly represented in different feature spaces by using various feature extraction algorithms. Then we build a transfer learning model to leverage knowledge from multiple feature spaces. During modeling, since the assumption that the training and the testing data have the same distribution is always true, we give a theorem and its proof which asserts the necessary and sufficient condition for achieving a minimum testing error. We also theoretically demonstrate that maximizing the classification error consistency across different feature spaces can improve the classification performance. Additionally, the cluster assumption derived from semi-supervised learning is introduced to enhance knowledge transfer. Finally, a Tagaki-Sugeno-Kang (TSK) fuzzy system-based learning algorithm is proposed, which can generate interpretable fuzzy rules. Experimental results not only demonstrate the promising social data classification performance of our proposed approach but also show its interpretability which is missing in many other models.

[Analysis of video-urodynamic and clinical features of non-neuropathic lower urinary tract dysfunction in children]

Objective: To analyze the video-urodynamic(VUDS) and clinical features of non-neuropathic lower urinary tract dysfunction (NNLUTD) in children. Methods: Children diagnosed with NNLUTD in the First Affiliated Hospital of Zhengzhou University from January 2016 to December 2020 were included. Children with neurological, rectal dysfunction and anatomical abnormalities were excluded. VUDS and urinalysis were performed in all children who were divided into 4 groups accordingly: normal group (Normal group), detrusor overactivity group(DO group), detrusor sphincter dyssynergia group (DSD group) and detrusor underactivity group (DU group). VUDS and clinical features, vesicoureteral reflux (VUR) and urinary tract infections (UTI) were analyzed. Results: A total of 173 children were included in this study, including 103 males and 70 females, aged (7.2±3.3) years. VUDS showed that 46 cases (26.6%) were in Normal group, 63 cases (36.4%) in DO group, 39 cases (22.5%) in DSD group and 25 cases (14.5%) in DU group. Compared with Normal group and DO group, the proportion of VUR in DSD group and DU group was significantly higher [18(46.2%) and 11(44.0%) vs 7(15.0%) and 14(22.2%), all P<0.05],and the proportion of male children was significantly higher than that of female children with VUR only in DO group [12(32.4%) vs 2(7.7%), P=0.020 ]; Compared with DO group, the proportion of UTI in DSD group and DU group was significantly higher [16(41.0%) and 12(48.0%) vs 12(19.0%), all P<0.05], and the proportion of female children was significantly higher than that of male children with UTI in normal group, DO group and DU group [9(45.0%) vs 4(15.4%), 8(30.8%) vs 4(10.8%)and 7(87.5%) vs 5(29.4%), all P<0.05]. The maximum detrusor pressure in DSD group was significantly higher than that in Normal group, DO group and DU group [(95±47) vs (43±18), (56±18) and (12±9)cmH₂O, all P<0.05, 1 cmH₂O=0.098 kPa).Compared with Normal group and DO group, post void residual in DSD group and DU group was significantly increased [(58±38) and (70±62) vs (8±8) and (8±7)ml, all P<0.05], and the proportion of lower bladder compliance was significantly increased [(15(38.5%) and 11(44%) vs 1(2.2%) and 10(15.9%), all P<0.05]. Compared with normal group, the maximum bladder capacity of DO, DSD and DU group were all significantly decreased [(178±61), (184±81) and (194±93) vs (256±92)ml, all P<0.05]. The proportion of urgency had significant difference in the four groups [13(28.3%) in Normal group, 41(65.1%) in DO group, 22(56.4%) in DSD group and 11(44.0%) in DU group, P=0.001], and the proportion of dysuria had significant difference too [5(10.9%) in Normal group, 18(28.6%) in DO group, 20(51.3%) in DSD group and 15(60.0%) in DU group, P<0.001]. Conclusions: Children with 4 different conditions of NNLUTD have distinct video-urodynamic features. The higher ratio of VUR and UTI in DSD and DU children may be associated with reduced bladder compliance and increased post void residual. VUDS is useful for the diagnosis and treatment of refractory children with NNLUTD.

Improving radiomic model reliability using robust features from perturbations for head-and-neck carcinoma

Background

Using high robust radiomic features in modeling is recommended, yet its impact on radiomic model is unclear. This study evaluated the radiomic model’s robustness and generalizability after screening out low-robust features before radiomic modeling. The results were validated with four datasets and two clinically relevant tasks.

Materials and methods

A total of 1,419 head-and-neck cancer patients’ computed tomography images, gross tumor volume segmentation, and clinically relevant outcomes (distant metastasis and local-regional recurrence) were collected from four publicly available datasets. The perturbation method was implemented to simulate images, and the radiomic feature robustness was quantified using intra-class correlation of coefficient (ICC). Three radiomic models were built using all features (ICC &gt; 0), good-robust features (ICC &gt; 0.75), and excellent-robust features (ICC &gt; 0.95), respectively. A filter-based feature selection and Ridge classification method were used to construct the radiomic models. Model performance was assessed with both robustness and generalizability. The robustness of the model was evaluated by the ICC, and the generalizability of the model was quantified by the train-test difference of Area Under the Receiver Operating Characteristic Curve (AUC).

Results

The average model robustness ICC improved significantly from 0.65 to 0.78 (P&lt; 0.0001) using good-robust features and to 0.91 (P&lt; 0.0001) using excellent-robust features. Model generalizability also showed a substantial increase, as a closer gap between training and testing AUC was observed where the mean train-test AUC difference was reduced from 0.21 to 0.18 (P&lt; 0.001) in good-robust features and to 0.12 (P&lt; 0.0001) in excellent-robust features. Furthermore, good-robust features yielded the best average AUC in the unseen datasets of 0.58 (P&lt; 0.001) over four datasets and clinical outcomes.

Conclusions

Including robust only features in radiomic modeling significantly improves model robustness and generalizability in unseen datasets. Yet, the robustness of radiomic model has to be verified despite building with robust radiomic features, and tightly restricted feature robustness may prevent the optimal model performance in the unseen dataset as it may lower the discrimination power of the model.

Lung Subregion Partitioning by Incremental Dose Intervals Improves Omics-Based Prediction for Acute Radiation Pneumonitis in Non-Small-Cell Lung Cancer Patients

Purpose: To evaluate the effectiveness of features obtained from our proposed incremental-dose-interval-based lung subregion segmentation (IDLSS) for predicting grade ≥ 2 acute radiation pneumonitis (ARP) in lung cancer patients upon intensity-modulated radiotherapy (IMRT). (1) Materials and Methods: A total of 126 non-small-cell lung cancer patients treated with IMRT were retrospectively analyzed. Five lung subregions (SRs) were generated by the intersection of the whole lung (WL) and five sub-regions receiving incremental dose intervals. A total of 4610 radiomics features (RF) from pre-treatment planning computed tomographic (CT) and 213 dosiomics features (DF) were extracted. Six feature groups, including WL-RF, WL-DF, SR-RF, SR-DF, and the combined feature sets of WL-RDF and SR-RDF, were generated. Features were selected by using a variance threshold, followed by a Student t-test. Pearson’s correlation test was applied to remove redundant features. Subsequently, Ridge regression was adopted to develop six models for ARP using the six feature groups. Thirty iterations of resampling were implemented to assess overall model performance by using the area under the Receiver-Operating-Characteristic curve (AUC), accuracy, precision, recall, and F1-score. (2) Results: The SR-RDF model achieved the best classification performance and provided significantly better predictability than the WL-RDF model in training cohort (Average AUC: 0.98 ± 0.01 vs. 0.90 ± 0.02, p < 0.001) and testing cohort (Average AUC: 0.88 ± 0.05 vs. 0.80 ± 0.04, p < 0.001). Similarly, predictability of the SR-DF model was significantly stronger than that of the WL-DF model in training cohort (Average AUC: 0.88 ± 0.03 vs. 0.70 ± 0.030, p < 0.001) and in testing cohort (Average AUC: 0.74 ± 0.08 vs. 0.65 ± 0.06, p < 0.001). By contrast, the SR-RF model significantly outperformed the WL-RF model only in the training set (Average AUC: 0.93 ± 0.02 vs. 0.85 ± 0.03, p < 0.001), but not in the testing set (Average AUC: 0.79 ± 0.05 vs. 0.77 ± 0.07, p = 0.13). (3) Conclusions: Our results demonstrated that the IDLSS method improved model performance for classifying ARP with grade ≥ 2 when using dosiomics or combined radiomics-dosiomics features.

Hidden Local Symmetry Breaking in a Kagome-Lattice Magnetic Weyl Semimetal

Exploring the relationship between intriguing physical properties and structural complexity is a central topic in studying modern functional materials. Co₃Sn₂S₂, a newly discovered kagome-lattice magnetic Weyl semimetal, has triggered intense interest owing to the intimate coupling between topological semimetallic states and peculiar magnetic properties. However, the origins of the magnetic phase separation and spin glass state below T_C in this ordered compound are two unresolved yet important puzzles in understanding its magnetism. Here, we report the discovery of local symmetry breaking surprisingly co-emerges with the onset of ferromagnetic order in Co₃Sn₂S₂, by a combined use of neutron total scattering and half-polarized neutron diffraction. An anisotropic distortion of the cobalt kagome lattice at the atomic/nano level is also found, with distinct distortion directions among the two Co1 and four Co2 atoms. The mismatch of local and average symmetries occurs below T_C, indicating that Co₃Sn₂S₂ evolves to an intrinsically lattice disordered system when the ferromagnetic order is established. The local symmetry breaking with intrinsic lattice disorder provides new understanding of the puzzling magnetic properties. Our density functional theory (DFT) calculation indicates that the local symmetry breaking is expected to reorient local ferromagnetic moments, unveiling the existence of the ferromagnetic instability associated with the lattice instability. Furthermore, DFT calculation unveils that the local symmetry breaking could affect the Weyl property by breaking the mirror plane. Our findings highlight the fundamentally important role that the local symmetry breaking plays in advancing our understanding on the magnetic and topological properties in Co₃Sn₂S₂, which may draw attention to explore the overlooked local symmetry breaking in Co₃Sn₂S₂, its derivatives and more broadly in other topological Dirac/Weyl semimetals and kagome-lattice magnets.

Building reliable radiomic models using image perturbation

Radiomic model reliability is a central premise for its clinical translation. Presently, it is assessed using test–retest or external data, which, unfortunately, is often scarce in reality. Therefore, we aimed to develop a novel image perturbation-based method (IPBM) for the first of its kind toward building a reliable radiomic model. We first developed a radiomic prognostic model for head-and-neck cancer patients on a training (70%) and evaluated on a testing (30%) cohort using C-index. Subsequently, we applied the IPBM to CT images of both cohorts (Perturbed-Train and Perturbed-Test cohort) to generate 60 additional samples for both cohorts. Model reliability was assessed using intra-class correlation coefficient (ICC) to quantify consistency of the C-index among the 60 samples in the Perturbed-Train and Perturbed-Test cohorts. Besides, we re-trained the radiomic model using reliable RFs exclusively (ICC > 0.75) to validate the IPBM. Results showed moderate model reliability in Perturbed-Train (ICC: 0.565, 95%CI 0.518–0.615) and Perturbed-Test (ICC: 0.596, 95%CI 0.527–0.670) cohorts. An enhanced reliability of the re-trained model was observed in Perturbed-Train (ICC: 0.782, 95%CI 0.759–0.815) and Perturbed-Test (ICC: 0.825, 95%CI 0.782–0.867) cohorts, indicating validity of the IPBM. To conclude, we demonstrated capability of the IPBM toward building reliable radiomic models, providing community with a novel model reliability assessment strategy prior to prospective evaluation.

[Epidemiological characteristics of severe fever with thtrombocytopenia syndrome in China, 2011-2021]

Objective: To analyze the epidemiological characteristics of severe fever with thrombocytopenia syndrome (SFTS) in China from 2011 to 2021, and provide evidence for the prevention and control of SFTS. Methods: The incidence data of SFTS were collected from the National Disease Reporting Information System of Chinese Center for Disease Control and Prevention for a descriptive epidemiological analysis and Cochran-Armitage trend test was used to evaluate the association between age and the morbidity rate and case fatality rate (CFR) of SFTS. Results: From 2011 to 2021, a total of 18 902 laboratory confirmed cases of SFTS, including 966 deaths, were reported in 533 counties (districts) of 154 prefecture-level cities in 27 provinces. The annual average morbidity rate was 0.125/100 000, and the annual average CFR was 5.11%. From 2011 to 2021 the overall morbidity rate of SFTS was in increase with an average annual percentage change (AAPC) of 14.80% (P=0.001). Most cases (99.23%) occurred in 7 provinces, including Shandong, Henan, Anhui, Hubei, Liaoning, Zhejiang and Jiangsu, with 70.28% of the cases in 11 prefecture-level cities. The average annual CFRs in the 7 provinces varied greatly from 1.30% to 11.27%. In 2011, SFTS cases were reported in 108 counties (districts) of 51 prefecture-level cities in 13 provinces, but SFTS cases were reported in 277 counties (districts) of 88 prefecture-level cities in 19 provinces in 2021, the disease spread from central area to the northeast and from the west and the south. SFTS mainly occurred in summer and autumn in both southern and northern China, and 96.63% of the cases were reported from April to October, and the incidence peak was during May-June. The cases mainly occurred in age group 50-74 years (69.46%), and the deaths mainly occurred in age group ≥60 years (79.71%). Both the morbidity rate and the CFR increased with age. The morbidity rate increased from 0.040/100 000 in age group 0-4 years to 4.480/100 000 in age group ≥80 years in males (χ²=13 185.21, P<0.001) and from 0.038/100 000 in age group 0-4 years to 3.318/100 000 in age group ≥80 years in females (χ²=12 939.83, P<0.001); the CFR increased from 0.70% in age group 30-34 years to 11.58% in age group ≥80 years in males (χ²=115.70, P<0.001) and from 1.56% in age group 35-39 years to 8.98% in age group ≥80 years in females (χ²=103.42, P<0.001). Conclusion: From 2011 to 2021, the incidence of SFTS increased in China, and the spread and obvious spatiotemporal distribution of SFTS were observed. The reported CFR varied greatly with area, and both the morbidity and mortality risk were high in the elderly.

Systematic Review on COVID-19 Readmission and Risk Factors: Future of Machine Learning in COVID-19 Readmission Studies

In this review, current studies on hospital readmission due to infection of COVID-19 were discussed, compared, and further evaluated in order to understand the current trends and progress in mitigation of hospital readmissions due to COVID-19. Boolean expression of (“COVID-19” OR “covid19” OR “covid” OR “coronavirus” OR “Sars-CoV-2”) AND (“readmission” OR “re-admission” OR “rehospitalization” OR “rehospitalization”) were used in five databases, namely Web of Science, Medline, Science Direct, Google Scholar and Scopus. From the search, a total of 253 articles were screened down to 26 articles. In overall, most of the research focus on readmission rates than mortality rate. On the readmission rate, the lowest is 4.2% by Ramos-Martínez et al. from Spain, and the highest is 19.9% by Donnelly et al. from the United States. Most of the research (n = 13) uses an inferential statistical approach in their studies, while only one uses a machine learning approach. The data size ranges from 79 to 126,137. However, there is no specific guide to set the most suitable data size for one research, and all results cannot be compared in terms of accuracy, as all research is regional studies and do not involve data from the multi region. The logistic regression is prevalent in the research on risk factors of readmission post-COVID-19 admission, despite each of the research coming out with different outcomes. From the word cloud, age is the most dominant risk factor of readmission, followed by diabetes, high length of stay, COPD, CKD, liver disease, metastatic disease, and CAD. A few future research directions has been proposed, including the utilization of machine learning in statistical analysis, investigation on dominant risk factors, experimental design on interventions to curb dominant risk factors and increase the scale of data collection from single centered to multi centered.

Simultaneous determination of trace level riot control agents in environmental water by solid-phase microextraction and gas chromatography coupled with a Flame Ionization Detector

In this paper, a direct immersion solid-phase microextraction procedure for the simultaneous analyses of four primary riot control agents: 2-Chloroacetophenone, o-chlorobenzylidene malonitrile, Dibenz (b, f)-1,4-Oxazepine, and oleoresin capsicum at μg·L^-1 concentration from environmental water was developed. Several parameters that influence the extraction effectiveness were investigated, including fiber type, extraction temperature, extraction time, starring rate, and salinity. Under the recommended conditions, the optimized method had reasonable linearity and accuracy. The average recovery of this method ranged from 84% to 108.1%. The limit of detection for all the analytes ranged from 0.2 to 3 μg·L^-1 and the limit of quantification ranged from 1 to 10 μg·L^-1 , respectively. A relative standard deviation from 3.0% to 4.3% can be achieved depending on the compounds. The procedure was applied to analyze all the four riot control agents simultaneously in several environmental samples. This article is protected by copyright. All rights reserved.

Assessment of health benefit of PM2.5 reduction during COVID-19 lockdown in China and separating contributions from anthropogenic emissions and meteorology

The national lockdown policies have drastically disrupted socioeconomic activities during the COVID-19 pandemic in China, which provides a unique opportunity to investigate the air quality response to such anthropogenic disruptions. And it is meaningful to evaluate the potential health impacts of air quality changes during the lockdown, especially for PM_2.5 with adverse health effects. In this study, by using PM_2.5 observations from 1388 monitoring stations nationwide in China, we examine the PM_2.5 variations between the COVID-19 lockdown (February and March in 2020) and the same period in 2015-2019, and find that the national average of PM_2.5 decreases by 18 μg/m³, and mean PM_2.5 for most sites (about 75%) decrease by 30%-60%. The anthropogenic and meteorological contributions to these PM_2.5 variations are also determined by using a stepwise multiple linear regression (MLR) model combined with the Kolmogorov-Zurbenko filter. Our results show that the change of anthropogenic emissions is a leading contributor to those widespread PM_2.5 reductions, and meteorological conditions have the negative influence on PM_2.5 reductions for some regions, such as Beijing-Tianjin-Hebei (BTH). Additionally, the avoided premature death due to PM_2.5 reduction is estimated as a predicted number based on a log-linear concentration-response function. The total avoided premature death is 9952 in China, with dominant contribution (94%) from anthropogenic emission changes. For BTH, Yangtze River Delta, Pearl River Delta and Hubei regions, the reductions of PM_2.5 are 24.1, 24.3, 13.5 and 29.5 μg/m³, with the avoided premature deaths of 1066, 1963, 454 and 583, respectively.

[Dihydromyricetin mediates epithelial mesenchymal transformation and regulates the proliferation and apoptosis of esophageal squamous cell carcinoma cells]

Objective: To study the effects of dihydromyricetin (DMY) on the proliferation, apoptosis and epithelial mesenchymal transition (EMT) of esophageal squamous cell carcinoma (ESCC) cell KYSE150 and KYSE410. Methods: KYSE150 and KYSE410 cells were treated with different concentrations of DMY (0, 25, 50, 100, 150, 200 μmol/L) for 24 hours. The median inhibition concentration (IC₅₀) values of KYSE150 and KYSE410 were detected by cell counting kit-8 (CCK-8) method. Then 0.5‰ dimethyl sulfoxide (DMSO) was used as control group, dihydromyricetin (DMY), dihydromyricetin and transforming growth factor-β1 (DMY+ TGF-β1), transforming growth factor-β1 (TGF-β1) were used as experimental group. Cell proliferation and apoptosis rates were measured by clonal formation and flow cytometry. Transwell invasion and wound healing assay were used to detect cell invasion and migration. The protein expression levels of Caspase-3, Caspase-9, Bcl-2, Bax, Smad2/3, phosphorylation-Smad2/3 (p-Smad2/3) and Vimentin were detected by western blot. Results: The IC₅₀ values of DMY on KYSE410 and KYSE150 cells were 100.51 and 101.27 μmol/L. The clone formation numbers of KYSE150 and KYSE410 in DMY group [(0.53±0.03) and (0.31±0.03)] were lower than those in DMSO group [(1.00±0.10) and (1.00±0.05), P<0.05]. The apoptosis rates of KYSE150 and KYSE410 cells in DMY group [(1.84±0.22)% and (2.80±0.07)%] were higher than those in DMSO group [(1.00±0.18)% and (1.00±0.07)%, P<0.05]. The invasion numbers of KYSE150 and KYSE410 cells in DMY group [(0.42±0.03) and (0.29±0.05)] were lower than those in DMSO group [(1.00±0.08) and (1.00±0.05), P<0.05]. The migration rates of KYSE150 and KYSE410 cells in DMY group [(0.65±0.14)% and (0.40±0.17)%] were lower than those in DMSO group [(1.00±0.10)% and (1.00±0.08)%, P<0.05]. The clone formation numbers of KYSE150 and KYSE410 in TGF-β1 group [(1.01±0.08) and (0.99±0.25)] were higher than those in DMY+ TGF-β1 group [(0.73±0.10) and (0.58±0.05), P<0.05]. The apoptosis rates of KYSE150 and KYSE410 cells in TGF-β1 group [(0.81±0.14)% and (1.18±0.10)%] were lower than those in DMY+ TGF-β1 group [(1.38±0.22)% and (1.85±0.04)%, P<0.05]. The invasion numbers of KYSE150 and KYSE410 cells in TGF-β1 group [(1.19±0.11) and (1.39±0.11)] were higher than those in DMY+ TGF-β1 group [(0.93±0.09) and (0.93±0.05), P<0.05]. The migration rates of KYSE150 and KYSE410 cells in TGF-β1 group [(1.87±0.19)% and (1.32±0.04)%] were higher than those in DMY+ TGF-β1 group [(0.86±0.16)% and (0.77±0.12)%, P<0.05]. The protein expression levels of Bax, Caspase-3 and Caspase-9 in KYSE150 and KYSE410 cells in DMY group were higher than those in DMSO group, while the protein expression level of Bcl-2 was lower than that in DMSO group (P<0.05). The protein expression levels of p-Smad2/3, Smad2/3 and Vimentin in KYSE150 and KYSE410 cells in DMY group were lower than those in DMSO group (P<0.05). The protein expression levels of Bax, Caspase-3 and Caspase-9 in KYSE150 and KYSE410 cells in TGF-β1 group were lower than those in DMY+ TGF-β1 group, and the protein expression level of Bcl-2 was higher than that in DMY+ TGF-β1 group (P<0.05). The protein expression levels of Bax, Caspase-3 and Caspase-9 in KYSE150 and KYSE410 cells in DMY+ TGF-β1 group were lower than those in DMY group, and the protein expression level of Bcl-2 was higher than that in DMY group (P<0.05). The protein expression levels of p-Smad2/3, Smad2/3 and Vimentin in KYSE150 and KYSE410 cells in TGF-β1 group were higher than those in DMY+ TGF-β1 group (P<0.05). Conclusion: DMY can inhibit the proliferation and EMT of ESCC mediated by TGF-β1 and promote cell apoptosis.

Enhanced Immune Responses in Mice Induced by the c-di-GMP Adjuvanted Inactivated Vaccine for Pseudorabies Virus

Cyclic dimeric guanosine monophosphate (c-di-GMP) is a bacterial second messenger with immunomodulatory activities in mice, suggesting potential applications as a vaccine immunopotentiator or therapeutic agent. In this study, we evaluated the efficacy of c-di-GMP as an immunopotentiator for pseudorabies virus (PRV) inactivated vaccine in a murine model. We found that c-di-GMP improved the humoral and cellular immune responses induced by PRV inactivated vaccine and its effects on immunity reached the level comparable to that of a live attenuated vaccine. Furthermore, c-di-GMP enhanced the murine antibody response against the viral glycoprotein gB up to 120 days after immunization. The c-di-GMP–adjuvanted PRV inactivated vaccine induced long-term humoral immunity by promoting a potent T follicular helper cell response, which is known to directly control the magnitude of the germinal center B cell response. Furthermore, the c-di-GMP enhanced the response of bone marrow plasma cells and upregulated the expression of Bcl-2 and Mcl-1, which have been identified as anti-apoptotic regulatory genes of germinal center and memory B cells. Our findings open a new avenue for improving the immune efficacy of PRV inactivated vaccines.

[Application effects of feedforward control theory in the rollover bed treatment of mass patients with burn-explosion combined injury]

Objective: To explore the application effects of feedforward control theory in the rollover bed treatment of mass patients with burn-explosion combined injury. Methods: A retrospective observational research was conducted. From June 13 to 14, 2020, 15 patients with severe burn-explosion combined injury caused by liquefied natural gas tank car explosion and conforming to the inclusion criteria were admitted to the Second Affiliated Hospital of Zhejiang University School of Medicine. There were 13 males and 2 females, aged 33-92 (66±17) years. All the patients were treated with rollover bed from 48 h post admission, and the feedforward control theory was introduced, including establishing a special feedforward control management team for rollover bed, clarifying the duties of the medical staff in the rollover bed treatment of patients, implementing the cooperation strategy of multidisciplinary physician, training and examining for 80 nurses in the temporarily organized nurse team in the form of "rollover bed workshop", and formulating the checklist and valuation list of rollover bed treatment for continuous quality control. The frequency and the total number of turning over, and successful rate of one-time posture change with the rollover bed of patients within 30 days of admission were recorded, the occurrences of adverse events caused by improper operation for the rollover bed during the treatment were observed, including respiratory and cardiac arrests, treatment interruption, unplanned extubation, bed falling, and skin graft displacement. The lowest levels of arterial partial pressure of oxygen (PaO2) and arterial partial pressure of carbon dioxide (PaCO2), the number of patients with oxygenation index>300 mmHg (1 mmHg=0.133 kPa), and the occurrence of acute respiratory distress syndrome (ARDS) of patients within 2 days of admission and on the 30th day of admission were recorded. Results: Within 30 days of admission, the patients were turned over with the rollover bed for 2 to 6 times each day, with a total of 1 320 turning over operations, the successful rate of one-time posture change reached 99.9% (1 319/1 320), and no adverse event occurred. Within 2 days of admission, the lowest levels of PaO2 and PaCO2 of the patients were (100±19) and (42±4) mmHg, respectively, and the number of patients with mild, moderate, and severe ARDS were 10, 2, and 3, respectively, and none of the patients had oxygenation index>300 mmHg. On the 30th day of admission, the lowest levels of PaO2 and PaCO2 of the patients were (135±28) and (37±8) mmHg, respectively, 3 patients developed moderate ARDS, 1 patient developed severe ARDS, and 11 patients had oxygenation index>300 mmHg. Conclusions: The introduction of feedforward control theory in the treatment of rollover bed of mass patients with burn-explosion combined injury can ensure safe and successful completion of turning over with the rollover bed, promote the repair of burn wound, and improve respiratory function, and therefore improve the treatment quality of patients.

[Clinicopathological and molecular genetic features of cyclin D1-negative mantle cell lymphoma]

Objective: To investigate the clinicopathological features and molecular genetics of cyclin D1-negative mantle cell lymphoma (MCL). Methods: The clinicopathological features and molecular genetics of CyclinD1-negative MCL diagnosed between January 2016 and July 2021 at the First Affiliated Hospital of Zhengzhou University were analyzed using immunohistochemistry and fluorescence in situ hybridization. Clinical information was collected and analyzed. Results: A total of five Cyclin D1-negative MCL cases from all 212 MCL patients (5/212, 2.4%)were included. There were three male and two female patients,age ranged from 59 to 70 years (median 64 years). All patients presented with nodal lesions. None of the patients had B symptoms but four had bone marrow involvement. Histopathologically, four cases were classic MCL and one case was pleomorphic variant type. All five cases were negative for Cyclin D1 but SOX-11 were positive in all cases. CD5 was positive in four cases and one case was weakly positive for CD23. CD10 and bcl-6 were negative in all cases. CCND1 translocation was identified in three cases and CCND2 translocation in one case by FISH analysis. However,CCND3 translocations were not found in the five cases. Conclusions: Cyclin D1-negative MCL are uncommon, its accurate diagnosis needs combined analysis with morphologic and immunophenotypic characteristics and genetic changes. It may be particularly difficult to distinguish from other small cell type B cell lymphomas. FISH analyses for CCND1/CCND2/CCND3 translocations and immunohistochemistry for SOX-11 are helpful to resolve such a difficult distinction.

Discovering Knee Osteoarthritis Imaging Features for Diagnosis and Prognosis: Review of Manual Imaging Grading and Machine Learning Approaches

Knee osteoarthritis (OA) is a deliberating joint disorder characterized by cartilage loss that can be captured by imaging modalities and translated into imaging features. Observing imaging features is a well-known objective assessment for knee OA disorder. However, the variety of imaging features is rarely discussed. This study reviews knee OA imaging features with respect to different imaging modalities for traditional OA diagnosis and updates recent image-based machine learning approaches for knee OA diagnosis and prognosis. Although most studies recognized X-ray as standard imaging option for knee OA diagnosis, the imaging features are limited to bony changes and less sensitive to short-term OA changes. Researchers have recommended the usage of MRI to study the hidden OA-related radiomic features in soft tissues and bony structures. Furthermore, ultrasound imaging features should be explored to make it more feasible for point-of-care diagnosis. Traditional knee OA diagnosis mainly relies on manual interpretation of medical images based on the Kellgren-Lawrence (KL) grading scheme, but this approach is consistently prone to human resource and time constraints and less effective for OA prevention. Recent studies revealed the capability of machine learning approaches in automating knee OA diagnosis and prognosis, through three major tasks: knee joint localization (detection and segmentation), classification of OA severity, and prediction of disease progression. AI-aided diagnostic models improved the quality of knee OA diagnosis significantly in terms of time taken, reproducibility, and accuracy. Prognostic ability was demonstrated by several prediction models in terms of estimating possible OA onset, OA deterioration, progressive pain, progressive structural change, progressive structural change with pain, and time to total knee replacement (TKR) incidence. Despite research gaps, machine learning techniques still manifest huge potential to work on demanding tasks such as early knee OA detection and estimation of future disease events, as well as fundamental tasks such as discovering the new imaging features and establishment of novel OA status measure. Continuous machine learning model enhancement may favour the discovery of new OA treatment in future.

Multi-Organ Omics-Based Prediction for Adaptive Radiation Therapy Eligibility in Nasopharyngeal Carcinoma Patients Undergoing Concurrent Chemoradiotherapy

Purpose

To investigate the role of different multi-organ omics-based prediction models for pre-treatment prediction of Adaptive Radiotherapy (ART) eligibility in patients with nasopharyngeal carcinoma (NPC).

Methods and Materials

Pre-treatment contrast-enhanced computed tomographic and magnetic resonance images, radiotherapy dose and contour data of 135 NPC patients treated at Hong Kong Queen Elizabeth Hospital were retrospectively analyzed for extraction of multi-omics features, namely Radiomics (R), Morphology (M), Dosiomics (D), and Contouromics (C), from a total of eight organ structures. During model development, patient cohort was divided into a training set and a hold-out test set in a ratio of 7 to 3 via 20 iterations. Four single-omics models (R, M, D, C) and four multi-omics models (RD, RC, RM, RMDC) were developed on the training data using Ridge and Multi-Kernel Learning (MKL) algorithm, respectively, under 10-fold cross validation, and evaluated on hold-out test data using average area under the receiver-operator-characteristics curve (AUC). The best-performing single-omics model was first determined by comparing the AUC distribution across the 20 iterations among the four single-omics models using two-sided student t-test, which was then retrained using MKL algorithm for a fair comparison with the four multi-omics models.

Results

The R model significantly outperformed all other three single-omics models (all p-value<0.0001), achieving an average AUC of 0.942 (95%CI: 0.938-0.946) and 0.918 (95%CI: 0.903-0.933) in training and hold-out test set, respectively. When trained with MKL, the R model (R_MKL) yielded an increased AUC of 0.984 (95%CI: 0.981-0.988) and 0.927 (95%CI: 0.905-0.948) in training and hold-out test set respectively, while demonstrating no significant difference as compared to all studied multi-omics models in the hold-out test sets. Intriguingly, Radiomic features accounted for the majority of the final selected features, ranging from 64% to 94%, in all the studied multi-omics models.

Conclusions

Among all the studied models, the Radiomic model was found to play a dominant role for ART eligibility in NPC patients, and Radiomic features accounted for the largest proportion of features in all the multi-omics models.

[Accuracy analysis of full-arch implant digital impressions when using a geometric feature]

Objective: To evaluate the effect of adding a geometric feature on the accuracy of digital impressions obtained by intraoral scanners for implant restoration of edentulous jaw quantitatively. Methods: A dentiform model of the maxilla of completely edentulous arch with 6 implant analogs+scan bodies (No. 1-6) was selected as the reference model. Without geometric feature, the dentiform model was scanned by dental model scanner and repeated for 5 times as true value group. Before and after adding the geometric feature, the same operator used intraoral scanner A (Trios 3) and B (Aoralscan 2) to scan the dentiform model with the same scanning path. Each type of intraoral scanner scanned 10 times and ".stl " datas were obtained. The results were imported into reverse engineering software (Geomagic Studio 2015). The linear distances of center point of upper plane between sacn body 1 to 6 was calculated, denoted as D12, D13, D14, D15 and D16. Trueness was the absolute value subtracted from the measured value of the intraoral scanner groups and true value; precision was the absolute value of pairwise subtraction of the measured values in the intraoral scanner groups.The smaller the value, the better the accuracy or precision.With or without the feature, all scan data were statistically analyzed, and the effect of adding geometric feature on the trueness and precision of the two intraoral scanners were evaluated. Results: As for intraoral scanner A, with the feature in place, significant differences were found in D14, D15, D16 for tureness(t=2.66, 2.75, 2.95, P<0.05); the trueness for D16 decreased from (101.9±47.1) μm to (49.6±30.3) μm. On the other hand, with features on the edentulous area, the precision was significantly increased in D15 and D16 (U=378.00, 672.00, P<0.05); the precision for D15 decreased from 40.8 (45.1) μm to 13.1 (17.0) μm. As for intraoral scanner B, the trueness of D12, D13 and D14 after adding geometric features was significantly better than before (t=3.02, 2.66, U=22.00, P<0.05). With feature on the edentulous area, the trueness for D13 decreased from (116.6±41.2) μm to (70.8±35.5) μm. There was no statistical significance in the trueness of D15 and D16 with or without geometric feature (P>0.05), however, the precision of D15 and D16 after adding geometric feature was significantly better than before (U=702.00, 489.00,P<0.05). The precision of D16 decreased from 112.5 (124.7) μm to 35.9 (85.8) μm. Conclusions: The use of geometric feature in edentulous space improves the trueness and precision of the different principle intraoral scanners tested.

[Clinicopathological characteristics of natural killer cell enteropathy: report of two cases and review of literature]

Objective: To study the clinicopathological and genetic features of natural killer (NK)-cell enteropathy for better understanding of this rare disease and prevention of its misdiagnosis. Methods: Two cases of NK-cell enteropathy were diagnosed in the First Affiliated Hospital of Zhengzhou University, China from October 2017 to February 2021. The clinical characteristics, morphology, immunohistochemistry, Epstein-Barr virus-encoded RNA (EBER) in situ hybridization and T cell receptor gene rearrangement were analyzed. The patients were followed up by a telephone interview. Results: The patients were both male, aged 40 and 28 years, respectively. Both patients were admitted to the hospital for an annual checkup without obvious gastrointestinal symptoms. The endoscopy showed that the gastric body of case 1 had a mucosal bulge, small area of congestion and erosion, while the rectum of case 2 had congestion and erosion. Microscopically, the lesions of the 2 cases were relatively limited. Many lymphoid cells infiltrated within the lamina propria of the mucosa and into the muscularis mucosa in case 2. In case 1, the glands were reduced in the lesion, and the glandular cavity was slightly compressed and deformed. There was no infiltration or destruction of the glands in either case. Lymphoid cells were atypical, with medium-to-large cell sizes. Their cytoplasm was medium-to-slightly abundant and appeared eosinophilic or translucent. In case 2, characteristic eosinophilic granules were seen in the cytoplasm of a few cells. The nuclei in both cases were round, oval and irregular, with fine chromatin, inconspicuous nucleoli, and no mitotic figures were noted. Necrosis was seen in case 1 while both cases had no central growth or destruction of blood vessels. Immunophenotyping showed that CD56, granzyme B and TIA-1 were positive in both cases, part of the cells was CD3-positive, and some cells were weakly CD4-positive in case 2. The CD5, CD8, CD30, ALK and B-lineage markers (CD20, CD79α) were all negative. The Ki-67 proliferation index was about 60% and 30%, respectively. Both cases were EBER negative. TCR gene rearrangement was polyclonal. Follow-up showed that none of the 2 patients had any special treatments and stayed well. Conclusions: NK-cell enteropathy is rare, with biological behaviors similar to benign tumors, and occasional recurrence. Its histology and immunophenotype are easily confused with NK/T cell-derived lymphomas. Combination of its unique endoscopic features, EBER negativity, polyclonal TCR gene rearrangement and good prognosis can confirm the diagnosis and avoid misdiagnosis and overtreatment.

[Changes of serum uric acid levels in patients with chronic hepatitis C after using direct antiviral agents therapy]

Objective: To observe the changes of serum uric acid levels and clinical characteristic in patients with chronic hepatitis C combined with hyperuricemia after direct antiviral agents (DAA) therapy. Methods: A prospective cohort study was used to investigate the risk of hyperuricemia in patients with chronic hepatitis C who received DAA treatment to obtain sustained virological response. The changes and factors influencing serum uric acid levels after 12 weeks of DAA treatment were observed. Comparisons between groups were performed using χ (2) test or Fisher's exact test, analysis of variance, Student's t test, or the non-parametric Mann-Whitney U test. Serum uric acid (SUA) changes, liver and kidney function indexes before and after treatment were compared by repeated measurement and paired t-test. Uric acid reduction was defined as a decrease in SUA from baseline at 12 weeks after treatment. Rates of change in eGFR, aspartate aminotransferase/platelet ratio, alanine aminotransferase and controlled attenuation parameter were defined from baseline (baseline to 12 weeks after treatment). Binary logistic regression analysis was used to compare the risk factors and factors influencing high and low uric acid level. Results: 161 cases with chronic hepatitis C who received DAA treatment were included, of which 19.3% patients were hyperuricemic. eGFR < 60 ml/(min·1.73 m(2)) and body mass index were independent risk factors for hyperuricemia in patients with chronic hepatitis C (eGFR: OR = 0.123, P = 0.002; body mass index: OR = 1.220, P = 0.002). SUA levels was changed significantly before treatment, at the end of treatment and at 12 weeks after treatment (327.96 vs. 320.76 vs. 314.92, F = 3.272, P = 0.042). At 12 weeks after treatment, SUA, liver stiffness, alanine aminotransferase and control attenuation parameters were all significantly lower than baseline (P < 0.05). The rate of increase in eGFR from baseline and the rate of decrease in controlled attenuation parameter during treatment were the factors influencing SUA reduction (eGFR: OR = 5124, P = 0.000; controlled attenuation index: OR = 0.010, P = 0.039). Conclusion: In chronic hepatitis C, reduced eGFR and body mass index are the risk factors for the development of hyperuricemia and a significant reduction in serum uric acid levels after DAA treatment can eradicate the virus.

[Systematic evaluation of qualitative research on the real experience of burn patients during rehabilitation]

Objective: To systematically evaluate and integrate the real experience of burn patients during rehabilitation, and to provide theoretical guidance for the continual nursing care for burn patients. Methods: The systematic evaluation method was adopted. Databases including the China National Knowledge Internet, Wanfang Database, China Biology Medicine disc were retrieved with the search terms in Chinese version of "/, //, ////", and PubMed, Embase, CINAHL, PsycINFO, Cochrane Library were retrieved with the search terms of "burn/burns, rehabilitation/recovery/survivor/survive, experience/views/perceptions/, qualitative/phenomenon/interview/grounded theory". The qualitative studies on the real experience of burn patients during rehabilitation published from the establishment of each database to June 2020 were searched. The quality of the included studies was evaluated according to the quality evaluation criteria for qualitative research of the Joanna Briggs Institute Evidence-Based Health Care Center. The research country, research method, research object, research content, and main research result were summarized, and meta-synthesis of the research results was conducted with the aggregative integration method. Results: A total of 12 studies were included, and the quality of all the studies was grade B. The studies were conducted in 8 countries including Australia, Canada, Norway, etc., the research method mainly was phenomenological research method, and all the studies were focused on adult burn patients. A total of 46 specific themes were extracted with totally 10 new categories formed after summarization, and 3 integrated results were obtained as follows: burn patients suffered from both physical and psychological burdens, and their normal life was broken; burn patients gained post-traumatic growth and could actively adjust to cope with life difficulties; burn patients had multiple needs. Conclusions: Burn patients experience both physical and psychological pains during rehabilitation, so they long for multiple support from family and society. Medical staff, social groups, and family members should pay attention to the psychological experience and needs of burn patients with different characteristics during rehabilitation, and build a multi-directional social support system to help patients return to the society and rebuild their lives.

A Novel Blood Index-Based Model to Predict Hepatitis B Virus-Associated Hepatocellular Carcinoma Recurrence After Curative Hepatectomy: Guidance on Adjuvant Transcatheter Arterial Chemoembolization Choice

Background

Postoperative recurrence is a significant obstacle in hepatocellular carcinoma (HCC) treatment. This study aimed to construct a blood index-based model to predict hepatitis B virus-associated HCC (HBV-HCC) recurrence after curative hepatectomy.

Methods

A total of 370 patients who received initially curative hepatectomy for HBV-HCC were included in this study. A novel blood index signature (BIS) was identified and systematically analyzed for its recurrence predictive value. Following this, multivariate Cox regression analysis was performed to build a blood index-based nomogram.

Results

A BIS based on the aminotransferase-to-platelet ratio index and a systemic inflammatory response index was used to construct a nomogram. The model showed good clinical applicability and reliability. Notably, the patients in the high recurrence risk group tended to benefit from adjuvant transcatheter arterial chemoembolization (TACE).

Conclusion

A reliable model was constructed to predict the HBV-HCC recurrence after curative hepatectomy. This model can guide the surgeons in selecting patients with high recurrence risk patients who may benefit from adjuvant TACE.

Relation Learning Using Temporal Episodes for Motor Imagery Brain-Computer Interfaces

For practical motor imagery (MI) brain-computer interface (BCI) applications, generating a reliable model for a target subject with few MI trials is important since the data collection process is labour-intensive and expensive. In this paper, we address this issue by proposing a few-shot learning method called temporal episode relation learning (TERL). TERL models MI with only limited trials from the target subject by the ability to compare MI trials through episode-based training. It can be directly applied to a new user without being re-trained, which is vital to improve user experience and realize real-world MIBCI applications. We develop a new and effective approach where, unlike the original episode learning, the temporal pattern between trials in each episode is encoded during the learning to boost the classification performance. We also perform an online evaluation simulation, in addition to the offline analysis that the previous studies only conduct, to better understand the performance of different approaches in real-world scenario. Extensive experiments are completed on four publicly available MIBCI datasets to evaluate the proposed TERL. Results show that TERL outperforms baseline and recent state-of-the-art methods, demonstrating competitive performance for subject-specific MIBCI where few trials are available from a target subject and a considerable number of trials from other source subjects.

[Twelve-week of sofosbuvir/velpatasvir therapeutic regimen for chronic hepatitis C patients in northwest region of China: a real-world multicenter clinical study]

Objective: To study the real-world outcome of China FDA-approved Sofosbuvir (SOF)/Velpatasvir (VEL) in Northwest China. Methods: In this multicenter, prospective, real-world cohort study, we recruited patients from 10 sites from Northwest China, who were chronically infected with HCV GTs 1-6 from 06/2018 to 09/2019. Patients received SOF (400mg)/VEL (100mg) for 12 weeks, and with ribavirin 900-1200 mg for GT3 cirrhosis and for any genotype decompensated cirrhosis. The primary endpoint was sustained virological response at 12-weeks post-treatment (SVR12) and safety. The secondary endpoint was the change of liver function after the achievement of SVR12. Results: Totally, 143 patients were enrolled in the study, four patients were lost to follow-up and one died during the follow-up, 138 patients were included in per-protocol analysis. Of the 138 patients, the mean age 53 years, 53.6% male, 94.2% Han nationality, 53.6% liver cirrhosis, 10.1% HBsAg(+), 6.5% renal dysfunction, 5.1% treatment-experienced, and 16.7% patients received ribavirin treatment. The genotype distribution was as follows: 35.5% GT1, 42.8% GT2, 15.9% GT3, and 5.8% un-typed. The SVR12 rate was 96.5% (138/143, 95%CI: 93.5%-99.6%) for intention-to-treat analysis, and in per-protocol analysis, all 138 patients obtained SVR12 (100%). Compared with baseline, the serum total bilirubin, ALT and AFP levels decreased (all P < 0.05), as well as increased ALB and platelet count (all P < 0.001) at post-treatment 12-weeks. Overall adverse events (AEs) rate is 29.0%, and the most common AEs were anemia (14.5%) and fatigue (8.0%). Severe side effects (edema and fatigue) occurred in 2 patients, one of whom needed a short-term interruption of treatment due to fatigue. Conclusion: In this real-world cohort study, 12-week SOF/VEL regimen with or without ribavirin achieved high SVR12 rates (96.5%-100% overall) with excellent safety profile among patients with HCV GT1/2/3 infection including patients with GT3 and cirrhosis, and led to improvement of liver function.

[PD-1 is associated with CD8(+)T lymphocyte dysfunction in patients with acute and chronic liver failure]

Objective: To explore whether peripheral blood CD8(+)T lymphocyte dysfunction is correlated with the programmed death receptor-1 (PD-1) expression in patients with acute-on-chronic liver failure (HBV-ACLF). Methods: Peripheral blood mononuclear cells (PBMC) were collected from patients with HBV-ACLF and healthy controls. CD8(+)T lymphocytes number and PD-1 expression condition in CD8(+)T lymphocytes were detected by flow cytometry. CD8(+)T lymphocytes isolated from peripheral blood of HBV-ACLF patients were further cultured in vitro. One group was added with PD-L1-IgG fusion protein (ACLF+PD-1 group), and the other group was added with IgG fusion protein (ACLF group). Proliferation ability (ki67), cell viability (CD69), and secretion ability of effector cytokines (IL-2, IFN-γ, TNF-α) were analyzed. Results: 30 cases with HBV-ACLF and healthy controls were enrolled. CD8(+)T lymphocytes absolute number was significantly lower in the peripheral blood of patients with ACLF group (333.88 ± 147.74)/μl than healthy controls (872.50 ± 206.64)/μl (P < 0.001). PD-1 expression in peripheral blood CD8(+)T lymphocytes were significantly increased in ACLF group (13.33% ± 2.52%), (P = 0.027) than healthy controls (7.02% ± 2.12%). In in vitro culture, compared with healthy controls, the peripheral blood CD8(+)T lymphocytes cell viability (CD69), proliferation ability (ki67) (all P ​​< 0.001), and the level of cytokine production (IL-2, IFN-γ, TNF-α) (all P < 0.05) were equally weakened in patients with ACLF group. Compared with ACLF group, CD8(+)T cell viability (CD69), proliferation ability (KI67) (all P < 0.05), and the level of cytokine production were weakened in ACLF+PD-1 group (all P < 0.05). Conclusion: HBV-ACLF patients have CD8(+)T lymphocyte dysfunction. Therefore, PD-1 may have correlation in the regulation of CD8(+)T lymphocyte dysfunction in ACLF patients.

Achieving high thermal sensitivity from ratiometric CaGdAlO4:Mn4+,Tb3+ thermometers

The pursuit of optical temperature sensing with high thermal sensitivity to discriminate small temperature changes without contact with the subject possesses a crucial technological and scientific significance. Ratiometric temperature detection based on transition metals and lanthanides emerges as a promising strategy to achieve the purpose due to the dopants' distinct thermal quenching rates. In this work, a new CaGdAlO₄:Mn⁴⁺,Tb³⁺ luminescent thermometer was developed. The combination of the highly-thermal-sensitive red emission from Mn⁴⁺ ions with the thermally-robust green emission from Tb³⁺ ions renders the thermometer with a maximum relative thermal sensitivity of 2.3% K^-1 at 398 K. The well-separated red and green channels in digital images enable further evaluation of thermal sensitivity. The estimated thermal sensitivity is 2.23% K^-1 at 398 K from the pixel intensity ratio of red and green channels.

Influence of Cation Size on the Local Atomic Structure and Electronic Properties of Ta Perovskite Oxynitrides

Partial anion substitution in transition metal oxides provides rich opportunities to control and tune physical and chemical properties, for example, combining the merits of oxides and nitrides. In addition, the possibility of resulting anion sublattice order provides a means to target polar and chiral structures based on a wide array of accessible structural archetypes by design. Here, we investigate the local structures of a family of perovskite tantalum oxynitrides-ATaO₂N (A = Ba, Sr, and Ca)-using a combination of experimental and theoretical approaches including neutron total scattering, density functional theory (DFT), and ab initio molecular dynamics (AIMD) simulations. We present the first experimental study of chemical short-range order (CSRO) in CaTaO₂N, confirming local cis N ordering of the anion sub-lattice. Our systematic exploration of a local structure across the A cation size series (from the larger Ba to the smaller Ca) reveals a perovskite motif increasingly distorted with respect to long-range average structures. DFT and AIMD simulations support the observed trends. Overall, structures with cis ordering of the nitrogen anions in each TaO₄N₂ octahedron are favored over those with trans ordering. With diminishing A cation size, local cis ordering and Ta off-centering play decreasing roles in overall lattice stability, overshadowed by the stabilizing effects of octahedral tilting. The influence of these factors on local dipole formation and frustrated dipole ordering are discussed.

A novel prognostic signature based on four glycolysis-related genes predicts survival and clinical risk of hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is the most common cancer with limited cure and poor survival. In our study, a bioinformatic analysis was conducted to investigate the role of glycolysis in the pathogenesis and progression of HCC.

METHODS

Single-sample gene set enrichment analysis (ssGESA) was used to calculate enrichment scores for each sample in TCGA-LIHC and GEO14520 according to the glycolysis gene set. Weighted gene co-expression network analysis identified a gene module closely related to glycolysis, and their function was investigated. Prognostic biomarkers were screened from these genes. Cox proportional hazard model and least absolute shrinkage and selection operator regression were used to construct the prognostic signature. Kaplan-Meier (KM) and receiver operating characteristic (ROC) curve analyses evaluated the prediction performance of the prognostic signature in TCGA-LIHC and ICGC-LIRI-JP. Combination analysis data of clinical features and prognostic signature constructed a nomogram. Area under ROC curves and decision curve analysis were used to compare the nomogram and its components.

RESULTS

The glycolysis pathway was upregulated in HCC and was unfavorable for survival. The determined gene module was mainly enriched in cell proliferation. A prognostic signature (CDCA8, RAB5IF, SAP30, and UCK2) was developed and validated. KM and ROC curves showed a considerable predictive effect. The risk score derived from the signature was an independent prognostic factor. The nomogram increased prediction efficiency by combining risk signature and TNM stage and performed better than component factors in net benefit.

CONCLUSION

The gene signature may contribute to individual risk estimation, survival prognosis, and clinical management.

[Application and outlook of robotics in prosthetic dentistry]

At present, robotic system has been applied in many aspects of the field of prosthetic dentistry, such as tooth preparation, oral implant surgery, full denture arrangement, prosthodontic material testing and robotic education of prosthodontics. The advantages of prosthodontic robotics lie in their ability to perform quantitative and precise operations whilerepeating the work flow indefinitely, which assist dentists to complete heavy and complicated daily treatment. In the research and development of prosthodontic robotics, the limitation of oral operation space should be fully considered, and robotics should have high safety and flexibility. The review briefly summarizes the application and existing problems of robotics in prosthodontics, and provides references for further development and design.