Synthesis of 6/5/3-Fused Tricyclic Scaffolds via Multistep Cascade Cyclization of α-Aryl Vinylsulfoniums with para-Quinamines and para-Quinols.

Herein, we present a straightforward approach to access hydroindoline-5-one-based 6/5/3-fused polycyclic ring structures through multistep cascade reactions involving α-aryl vinylsulfoniums and para-quinamines. The reactions proceed smoothly under mild conditions to deliver the desired products in generally good isolated yields. This protocol is also applicable to the cascade cycloaddition reactions of α-aryl vinylsulfoniums and para-quinols, effectively generating complex tricyclic scaffolds. In addition, the scale-up synthesis and further derivatizations demonstrate the potential synthetic application of the protocol.

Flexoelectricity Modulated Electron Transport of 2D Indium Oxide.

The phenomenon of flexoelectricity, wherein mechanical deformation induces alterations in the electron configuration of metal oxides, has emerged as a promising avenue for regulating electron transport. Leveraging this mechanism, stress sensing can be optimized through precise modulation of electron transport. In this study, the electron transport in 2D ultra-smooth In2O3 crystals is modulated via flexoelectricity. By subjecting cubic In2O3 (c-In2O3) crystals to significant strain gradients using an atomic force microscope (AFM) tip, the crystal symmetry is broken, resulting in the separation of positive and negative charge centers. Upon applying nano-scale stress up to 100 nN, the output voltage and power values reach their maximum, e.g. 2.2 mV and 0.2 pW, respectively. The flexoelectric coefficient and flexocoupling coefficient of c-In2O3 are determined as ≈0.49 nC m-1 and 0.4 V, respectively. More importantly, the sensitivity of the nano-stress sensor upon c-In2O3 flexoelectric effect reaches 20 nN, which is four to six orders smaller than that fabricated with other low dimensional materials based on the piezoresistive, capacitive, and piezoelectric effect. Such a deformation-induced polarization modulates the band structure of c-In2O3, significantly reducing the Schottky barrier height (SBH), thereby regulating its electron transport. This finding highlights the potential of flexoelectricity in enabling high-performance nano-stress sensing through precise control of electron transport.

[Research progress of deep learning applications in mass spectrometry imaging data analysis].

Mass spectrometry imaging (MSI) is a promising method for characterizing the spatial distribution of compounds. Given the diversified development of acquisition methods and continuous improvements in the sensitivity of this technology, both the total amount of generated data and complexity of analysis have exponentially increased, rendering increasing challenges of data postprocessing, such as large amounts of noise, background signal interferences, as well as image registration deviations caused by sample position changes and scan deviations, and etc. Deep learning (DL) is a powerful tool widely used in data analysis and image reconstruction. This tool enables the automatic feature extraction of data by building and training a neural network model, and achieves comprehensive and in-depth analysis of target data through transfer learning, which has great potential for MSI data analysis. This paper reviews the current research status, application progress and challenges of DL in MSI data analysis, focusing on four core stages: data preprocessing, image reconstruction, cluster analysis, and multimodal fusion. The application of a combination of DL and mass spectrometry imaging in the study of tumor diagnosis and subtype classification is also illustrated. This review also discusses trends of development in the future, aiming to promote a better combination of artificial intelligence and mass spectrometry technology.

Hernandonine-mediated autophagic cell death in hepatocellular carcinoma: Interplay of p53 and YAP signaling pathways.

Hepatocellular carcinoma (HCC), the primary form of liver cancer, is the third leading cause of cancer-related death globally. Hernandonine is a natural alkaloid derived from Hernandia nymphaeifolia that has been shown to exert various biological functions. In a previous study, hernandonine was shown to suppress the proliferation of several solid tumor cell lines without affecting normal human cell lines. However, little is known about the effect of hernandonine on HCC. Therefore, this study aimed to investigate the effect and mechanism of hernandonine on HCC in relation to autophagy. We found that hernandonine inhibited HCC cell growth in vitro and in vivo. In addition, hernandonine elicited autophagic cell death and DNA damage in HCC cells. RNA-seq analysis revealed that hernandonine upregulated p53 and Hippo signaling pathway-related genes in HCC cells. Small RNA interference of p53 resulted in hernandonine-induced autophagic cell death attenuation. However, inhibition of YAP sensitized HCC cells to hernandonine by increasing the autophagy induction. This is the first study to illustrate the complex involvement of p53 and YAP in the hernandonine-induced autophagic cell death in human HCC cells. Our findings provide novel evidence for the potential of hernandonine as a therapeutic agent for HCC treatment.

Deep recognition of rice disease images: how many training samples do we really need?

BACKGROUND: With the rapid development of deep learning, the recognition of rice disease images using deep neural networks has become a hot research topic. However, most previous studies only focus on the modification of deep learning models, while lacking research to systematically and scientifically explore the impact of different data sizes on the image recognition task for rice diseases. In this study, a functional model was developed to predict the relationship between the size of dataset and the accuracy rate of model recognition. RESULTS: Training VGG16 deep learning models with different quantities of images of rice blast-diseased leaves and healthy rice leaves, it was found that the test accuracy of the resulting models could be well fitted with an exponential model (A = 0.9965 - e(-0.0603×I50-1.6693)). Experimental results showed that with an increase of image quantity, the recognition accuracy of deep learning models would show a rapid increase at first. Yet when the image quantity increases beyond a certain threshold, the accuracy of image classification would not improve much, and the marginal benefit would be reduced. This trend remained similar when the composition of the dataset was changed, no matter whether (i) the disease class was changed, (ii) the number of classes was increased or (iii) the image data were augmented. CONCLUSIONS: This study provided a scientific basis for the impact of data size on the accuracy of rice disease image recognition, and may also serve as a reference for researchers for database construction. © 2024 Society of Chemical Industry.

An explainable machine learning-based model to predict intensive care unit admission among patients with community-acquired pneumonia and connective tissue disease.

BACKGROUND: There is no individualized prediction model for intensive care unit (ICU) admission on patients with community-acquired pneumonia (CAP) and connective tissue disease (CTD) so far. In this study, we aimed to establish a machine learning-based model for predicting the need for ICU admission among those patients. METHODS: This was a retrospective study on patients admitted into a University Hospital in China between November 2008 and November 2021. Patients were included if they were diagnosed with CAP and CTD during admission and hospitalization. Data related to demographics, CTD types, comorbidities, vital signs and laboratory results during the first 24 h of hospitalization were collected. The baseline variables were screened to identify potential predictors via three methods, including univariate analysis, least absolute shrinkage and selection operator (Lasso) regression and Boruta algorithm. Nine supervised machine learning algorithms were used to build prediction models. We evaluated the performances of differentiation, calibration, and clinical utility of all models to determine the optimal model. The Shapley Additive Explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME) techniques were performed to interpret the optimal model. RESULTS: The included patients were randomly divided into the training set (1070 patients) and the testing set (459 patients) at a ratio of 70:30. The intersection results of three feature selection approaches yielded 16 predictors. The eXtreme gradient boosting (XGBoost) model achieved the highest area under the receiver operating characteristic curve (AUC) (0.941) and accuracy (0.913) among various models. The calibration curve and decision curve analysis (DCA) both suggested that the XGBoost model outperformed other models. The SHAP summary plots illustrated the top 6 features with the greatest importance, including higher N-terminal pro-B-type natriuretic peptide (NT-proBNP) and C-reactive protein (CRP), lower level of CD4 + T cell, lymphocyte and serum sodium, and positive serum (1,3)-ß-D-glucan test (G test). CONCLUSION: We successfully developed, evaluated and explained a machine learning-based model for predicting ICU admission in patients with CAP and CTD. The XGBoost model could be clinical referenced after external validation and improvement.

TRIM25-mediated XRCC1 ubiquitination accelerates atherosclerosis by inducing macrophage M1 polarization and programmed death.

BACKGROUND: Macrophage-mediated cleaning up of dead cells is a crucial determinant in reducing coronary artery inflammation and maintaining vascular homeostasis. However, this process also leads to programmed death of macrophages. So far, the role of macrophage death in the progression of atherosclerosis remains controversial. Also, the underlying mechanism by which transcriptional regulation and reprogramming triggered by macrophage death pathways lead to changes in vascular inflammation and remodeling are still largely unknown. TRIM25-mediated RIG-I signaling plays a key role in regulation of macrophages fate, however the role of TRIM25 in macrophage death-mediated atherosclerotic progression remains unclear. This study aims to investigate the relationship between TRIM25 and macrophage death in atherosclerosis. METHODS: A total of 34 blood samples of patients with coronary stent implantation, including chronic total occlusion (CTO) leisions (n = 14) or with more than 50% stenosis of a coronary artery but without CTO leisions (n = 20), were collected, and the serum level of TRIM25 was detected by ELISA. Apoe-/- mice with or without TRIM25 gene deletion were fed with the high-fat diet (HFD) for 12 weeks and the plaque areas, necrotic core size, aortic fibrosis and inflammation were investigated. TRIM25 wild-type and deficient macrophages were isolated, cultured and stimulated with ox-LDL, RNA-seq, real-time PCR, western blot and FACS experiments were used to screen and validate signaling pathways caused by TRIM25 deletion. RESULTS: Downregulation of TRIM25 was observed in circulating blood of CTO patients and also in HFD-induced mouse aortas. After HFD for 12 weeks, TRIM25-/-ApoeE-/- mice developed smaller atherosclerotic plaques, less inflammation, lower collagen content and aortic fibrosis compared with TRIM25+/+ApoeE-/- mice. By RNA-seq and KEGG enrichment analysis, we revealed that deletion of TRIM25 mainly affected pyroptosis and necroptosis pathways in ox-LDL-induced macrophages, and the expressions of PARP1 and RIPK3, were significantly decreased in TRIM25 deficient macrophages. Overexpression of TRIM25 promoted M1 polarization and necroptosis of macrophages, while inhibition of PARP1 reversed this process. Further, we observed that XRCC1, a repairer of DNA damage, was significantly upregulated in TRIM25 deficient macrophages, inhibiting PARP1 activity and PARP1-mediated pro-inflammatory change, M1 polarization and necroptosis of macrophages. By contrast, TRIM25 overexpression mediated ubiquitination of XRCC1, and the inhibition of XRCC1 released PARP1, and activated macrophage M1 polarization and necroptosis, which accelerated aortic inflammation and atherosclerotic plaque progression. CONCLUSIONS: Our study has uncovered a crucial role of the TRIM25-XRCC1Ub-PARP1-RIPK3 axis in regulating macrophage death during atherosclerosis, and we highlight the potential therapeutic significance of macrophage reprogramming regulation in preventing the development of atherosclerosis.

Remarkable Toughening of Plastic with Monodispersed Nano-CaCO3: From Theoretical Predictions to Experimental Validation.

The structure-property relationship of poly(vinyl chloride) (PVC)/CaCO3 nanocomposites is investigated by all-atom molecular dynamics (MD) simulations. MD simulation results indicate that the dispersity of nanofillers, interfacial bonding, and chain mobility are imperative factors to improve the mechanical performance of nanocomposites, especially toughness. The tensile behavior and dissipated work of the PVC/CaCO3 model demonstrate that 12 wt % CaCO3 modified with oleate anion and dodecylbenzenesulfonate can impart high toughness to PVC due to its good dispersion, favorable interface interaction, and weak migration of PVC chains. Under the guidance of MD simulation, we experimentally prepared a transparent PVC/CaCO3 nanocomposite with good mechanical properties by in situ polymerization of monodispersed CaCO3 in vinyl chloride monomers. Interestingly, experimental tests indicate that the optimum toughness of a nanocomposite (a 368% increase in the elongation at break and 204% improvement of the impact strength) can be indeed realized by adding 12 wt % CaCO3 modified with oleic acid and dodecylbenzenesulfonic acid, which is remarkably consistent with the MD simulation prediction. In short, this work provides a proof-of-concept of using MD simulation to guide the experimental synthesis of PVC/CaCO3 nanocomposites, which can be considered as an example to develop other functional nanocomposites.

Prognostic value of the Naples prognostic score in patients with intrahepatic cholangiocarcinoma after hepatectomy.

BACKGROUND: The Naples Prognostic Score (NPS), integrating inflammatory and nutritional biomarkers, has been reported to be associated with the prognosis of various malignancies, but there is no report on intrahepatic cholangiocarcinoma (ICC). This study aimed to explore the prognostic value of NPS in patients with ICC. METHODS: Patients with ICC after hepatectomy were collected, and divided into three groups. The prognosis factors were determined by Cox regression analysis. Predictive efficacy was evaluated by the time-dependent receiver operating characteristic (ROC) curves. RESULTS: A total of 174 patients were included (Group 1: 33 (19.0%) patients; Group 2: 83 (47.7%) patients; and Group 3: 58 (33.3%) patients). The baseline characteristics showed the higher the NPS, the higher the proportion of patients with cirrhosis and Child-Pugh B, and more advanced tumors. The Kaplan-Meier curves reflect higher NPS were associated with poor survival. Multivariable analysis showed NPS was an independent risk factor of overall survival (NPS group 2 vs. 1: HR = 1.671, 95% CI: 1.022-3.027, p = 0.009; NPS group 3 vs. 1: HR = 2.208, 95% CI: 1.259-4.780, p = 0.007) and recurrence-free survival (NPS group 2 vs. 1: HR = 1.506, 95% CI: 1.184-3.498, p = 0.010; NPS group 3 vs. 1: HR = 2.141, 95% CI: 2.519-4.087, P = 0.001). The time ROC indicated NPS was superior to other models in predicting prognosis. CONCLUSIONS: NPS is a simple and effective tool for predicting the long-term survival of patients with ICC after hepatectomy. Patients with high NPS require close follow-up, and improving NPS may prolong the survival time.

Reduced expression of cathepsin F predicts poor prognosis in patients with clear cell renal cell carcinoma.

Abnormalities in the extracellular matrix (ECM) play important roles in the regulation and progression of clear cell renal cell carcinoma (ccRCC). The cysteine cathepsin is one of the major proteases involved in ECM remodeling and has been shown to be aberrantly expressed in multiple cancer types. However, the clinical significance and biological function of distinct cysteine cathepsins in ccRCC remain poorly understood. In this study, several bioinformatics databases, including UALCAN, TIMER, GEPIA and the Human Protein Atlas datasets, were used to analyze the expression and prognostic value of different cysteine cathepsin family members in ccRCC. We found that the expression level of CTSF was downregulated in tumor tissues and closely related to the poor survival of ccRCC patients. Further in vitro experiments suggested that CTSF overexpression suppressed the proliferation and migration of ccRCC cells. Moreover, the expression of CTSF was shown to be associated with several immune-infiltrating cells and immunomodulators in ccRCC. These results indicated that CTSF might be a promising diagnostic and prognostic marker in ccRCC.

Multicenter propensity score-matched analysis to compare perioperative morbidity after laparoscopic or robotic complex hepatectomy for solitary hepatocellular carcinoma.

BACKGROUND: Postoperative complications are vital factors affecting the prognosis of patients with hepatocellular carcinoma (HCC), especially for complex hepatectomy. The present study aimed to compare perioperative complications between laparoscopic and robotic complex hepatectomy (LCH vs. RCH). METHODS: Patients with solitary HCC after complex hepatectomy were collected from a multicenter database. Propensity score-matched (PSM) analysis was adopted to control confounding bias. Multivariable analysis was performed to determine the prognostic factors. RESULTS: 436 patients were included. After PSM, 43 patients were included in both the LCH and RCH groups. The results showed that compared to LCH, RCH had lower rates of blood loss and transfusion, and lower postoperative 30-day and major morbidity, and post-hepatectomy liver failure (PHLF) (all P < 0.05). Additionally, the length of hospital stay was shorter in the RCH group (P = 0.026). Multivariable analysis showed RCH is an independent protective factor for reducing the 30-day morbidity, major morbidity and PHLF. CONCLUSION: RCH has advantages over LCH in the minimally invasive treatment of complex HCC, as it can reduce the incidence of postoperative morbidity. Therefore, RCH should be considered for patients with HCC who require complex hepatectomy.

A review of botany, phytochemistry, pharmacology, and applications of the herb with the homology of medicine and food: Ligustrum lucidum W.T. Aiton.

Ligustrum lucidum W.T. Aiton is an outstanding herb with the homology of medicine and food. Its ripe fruits are traditionally used as an important tonic for kidneys and liver in China. Ligustrum lucidum W.T. Aiton is rich in nutritional components and a variety of bioactive ingredients. A total of 206 compounds have been isolated and identified, they mainly include flavonoids, phenylpropanoids, iridoid glycosides, and triterpenoids. These compounds exert anti-osteoporosis, anti-tumor, liver protective, antioxidant, anti-inflammatory, and immunomodulatory effects. Ligustrum lucidum W.T. Aiton has been traditionally used to treat many complex diseases, including osteoporotic bone pain, rheumatic bone, cancer, related aging symptoms, and so on. In the 2020 Edition of Chinese Pharmacopoeia, there are more than 100 prescriptions containing L. lucidum W.T. Aiton. Among them, some classical preparations including Er Zhi Wan and Zhenqi fuzheng formula, are used in the treatment of various cancers with good therapeutic effects. Additionally, L. lucidum W.T. Aiton has also many excellent applications for functional food, ornamental plants, bioindicator of air pollution, algicidal agents, and feed additives. Ligustrum lucidum W.T. Aiton has rich plant resources. However, the application potential of it has not been fully exploited. We hope that this paper provides a theoretical basis for the high-value and high-connotation development of L. lucidum W.T. Aiton in the future.

Precise planning based on 3D-printed dry-laboratory models can reduce perioperative complications of laparoscopic surgery for complex hepatobiliary diseases: a preoperative cohort study.

BACKGROUND & AIMS: Complications after laparoscopic liver resection (LLR) are important factors affecting the prognosis of patients, especially for complex hepatobiliary diseases. The present study aimed to evaluate the value of a three-dimensional (3D) printed dry-laboratory model in the precise planning of LLR for complex hepatobiliary diseases. METHODS: Patients with complex hepatobiliary diseases who underwent LLR were preoperatively enrolled, and divided into two groups according to whether using a 3D-printed dry-laboratory model (3D vs. control group). Clinical variables were assessed and complications were graded by the Clavien-Dindo classification. The Comprehensive Complication Index (CCI) scores were calculated and compared for each patient. Multivariable analysis was performed to determine the risk factors of postoperative complications. RESULTS: Sixty-two patients with complex hepatobiliary diseases underwent the precise planning of LLR. Among them, thirty-one patients acquired the guidance of a 3D-printed dry-laboratory model, and others were only guided by traditional enhanced CT or MRI. The results showed no significant differences between the two groups in baseline characters. However, compared to the control group, the 3D group had a lower incidence of intraoperative blood loss, as well as postoperative 30-day and major complications, especially bile leakage (all P < 0.05). The median score on the CCI was 20.9 (range 8.7-51.8) in the control group and 8.7 (range 8.7-43.4) in the 3D group (mean difference, -12.2, P = 0.004). Multivariable analysis showed the 3D model was an independent protective factor in decreasing postoperative complications. Subgroup analysis also showed that a 3D model could decrease postoperative complications, especially for bile leakage in patients with intrahepatic cholelithiasis. CONCLUSION: The 3D-printed models can help reduce postoperative complications. The 3D-printed models should be recommended for patients with complex hepatobiliary diseases undergoing precise planning LLR.

Sex-differential cognitive performance on MCCB of youth with BD-II depression.

BACKGROUND: Recent evidences have shown sex-differential cognitive deficits in bipolar disorder (BD) and differences in cognitions across BD subtypes. However, the sex-specific effect on cognitive impairment in BD subtype II (BD-II) remains obscure. The aim of the current study was to examine whether cognitive deficits differ by gender in youth with BD-II depression. METHOD: This cross-sectional study recruited 125 unmedicated youths with BD-II depression and 140 age-, sex-, and education-matched healthy controls (HCs). The Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery (MCCB) was used to assess cognitive functions. Mood state was assessed using the 24-item Hamilton Depression Rating Scale (24-HDRS) and the Young Mania Rating Scale (YMRS). Multivariate analysis of covariance (MANCOVA) was conducted. RESULT: ​Compared with HCs, patients with BD-II depression had lower scores on MCCB composite and its seven cognitive domains (all p < 0.001). After controlling for age and education, MANCOVA revealed significant gender-by-group interaction on attention/vigilance (F = 6.224, df = 1, p = 0.013), verbal learning (F = 9.847, df = 1, p = 0.002), visual learning (F = 4.242, df = 1, p = 0.040), and composite (F = 8.819, df = 1, p = 0.003). Post hoc analyses suggested that males performed worse in the above-mentioned MCCB tests than females in BD-II depression. CONCLUSION: Our study demonstrated generalized cognitive deficits in unmedicated youths with BD-II depression. Male patients performed more serious cognitive impairment on attention/vigilance, verbal learning, and visual learning compared to female patients.

Selenobacteria-mediated Se transformation and uptake involving the unique genetic code.

Selenium (Se) is a crucial micronutrient for human health. Plants are the primary source of Se for humans. Selenium in the soil serves as the primary source of Se for plants. The soil contains high total Se content in large areas in Guangxi, China. However, the available Se is low, hindering Se uptake by plants. Microorganisms play a pivotal role in the activation of Se in the soil, thereby enhancing its uptake by plants. In this study, selenobacteria were isolated from Se-rich soils in Guangxi. Then two selenobacteria strains, YLB1-6 and YLB2-1, representing the highest (30,000 µg/mL) and lowest (10,000 µg/mL) Se tolerance levels among the Se-tolerant bacteria, were selected for subsequent analysis. Although the two selenobacteria exhibited distinct effects, they can significantly transform Se species, resulting in a decrease in the soil residual Se (RES-Se) content while concurrently increasing the available Se (AVA-Se) content. Selenobacteria also enhance the transformation of Se valencies, with a significant increase observed in soluble Se6+ (SOL-Se6+). Additionally, selenobacteria can elevate the pH of acidic soil. Selenobacteria also promote the uptake of Se into plants. After treatment with YLB1-6 and YLB2-1, the Se content in the aboveground part of Chinese flowering cabbage increased by 1.96 times and 1.77 times, respectively, while the Se accumulation in the aboveground part of the plant significantly increased by 104.36% and 81.69%, respectively, compared to the control. Further whole-genome sequencing revealed the genetic difference between the two selenobacteria. Additionally, 46 and 38 candidate genes related to selenium utilization were identified from YLB1-6 and YLB2-1, respectively. This work accelerates our understanding of the potential molecular mechanism of Se biofortification by selenobacteria. It also provides microorganisms and gene targets for improving crop varieties or microorganisms to exploit the rich Se source in soil.

Survival benefit from adjuvant TACE combined with Lenvatinib for patients with hepatocellular carcinoma and microvascular invasion after curative hepatectomy.

BACKGROUND AND AIMS: The prognosis of patients with hepatocellular carcinoma (HCC) undergoing hepatectomy is unsatisfactory, especially for those with microvascular invasion (MVI). This study aimed to determine the impact of adjuvant transcatheter arterial chemoembolization (TACE) and Lenvatinib on the prognosis of patients with HCC and MVI after hepatectomy. METHODS: Patients diagnosed with HCC and MVI were reviewed, and stratified into four groups according to adjuvant TACE and/or Lenvatinib. Multivariate Cox regression analyses are used to determine independent risk factors. RESULTS: 346 patients were included, and divided into four groups (Group I, TACE+ Lenvatinib; Group II, Lenvatinib; Group III, TACE; Group IV, without adjuvant therapy). Multivariable analysis showed that compared to Group IV, Group I had the best effect on improving the overall survival (OS, HR 0.321, 95%CI 0.099-0.406, P = 0.001) and recurrence-free survival (RFS, HR 0.319, 95%CI 0.129-0.372, P = 0.001). Additionally, compared with Group II or Group III, Group I also can significantly improve the OS and RFS. There is no significant difference between Group II and Group III in OS and RFS. CONCLUSION: The combination of TACE and Lenvatinib should be considered for anti-recurrence therapy for patients with HCC and MVI after hepatectomy.

Learning Attention in the Frequency Domain for Flexible Real Photograph Denoising.

Recent advancements in deep learning techniques have pushed forward the frontiers of real photograph denoising. However, due to the inherent pooling operations in the spatial domain, current CNN-based denoisers are biased towards focusing on low-frequency representations, while discarding the high-frequency components. This will induce a problem for suboptimal visual quality as the image denoising tasks target completely eliminating the complex noises and recovering all fine-scale and salient information. In this work, we tackle this challenge from the frequency perspective and present a new solution pipeline, coined as frequency attention denoising network (FADNet). Our key idea is to build a learning-based frequency attention framework, where the feature correlations on a broader frequency spectrum can be fully characterized, thus enhancing the representational power of the network across multiple frequency channels. Based on this, we design a cascade of adaptive instance residual modules (AIRMs). In each AIRM, we first transform the spatial-domain features into the frequency space. Then, a learning-based frequency attention framework is devised to explore the feature inter-dependencies converted in the frequency domain. Besides this, we introduce an adaptive layer by leveraging the guidance of the estimated noise map and intermediate features to meet the challenges of model generalization in the noise discrepancy. The effectiveness of our method is demonstrated on several real camera benchmark datasets, with superior denoising performance, generalization capability, and efficiency versus the state-of-the-art.

Analysis of the effect on costochondral graft for TMJ ankylosis with jaw deformities in pediatrics.

OBJECTIVES: To evaluate the effects of costochondral grafting (CCG) used for temporomandibular joint ankylosis (TMJA) in growing patients. MATERIALS AND METHODS: Pediatric patients with TMJA treated by CCG from 2010.5 to 2021.7 were included in the study. CT scans were performed before and after operations with at least 1 year follow-up. The height of the mandibular ramus, menton deviation or retraction, osteotomy gap, etc. were measured by ProPlan CMF1.4 software. CCG growth, resorption, and relapse were evaluated and analyzed with influencing factors such as age, ostectomy gap, etc. by generalized estimating equation. RESULTS: There were 24 patients (29 joints) with an average age of 6.30 ± 3.13 years in the study. After operation, the mandibular ramus was elongated by 5.97 ± 3.53 mm. Mandibular deviation or retrusion was corrected by 4.82 ± 2.84 mm and 3.76 ± 2.97 mm respectively. After a mean follow-up of 38.91 ± 29.20 months, 58.62% CCG grew (4.18 ± 7.70 mm), 20.69% absorbed (2.23 ± 1.16 mm), and 20.69% re-ankylosed. The re-ankylosis was negatively correlated with the osteotomy gap (OR:0.348,0.172-0.702 95%CI, critical value = 6.10 mm). CCG resorption was positively correlated with the distance of CCG ramus elongation (OR:3.353,1.173-9.586 95%CI, critical value = 7.40 mm). CONCLUSIONS: An adequate osteotomy gap and CCG ramus elongation distance are the key factors for successful treatment of TMJA with jaw deformities in growing patients. CLINICAL RELEVANCE: TMJA affects mouth opening and jaw development in pediatric patients. The most common autogenous bone graft for pediatric patients is CCG due to its growth potential, convenient access and easy contouring. Also, it can simultaneously reconstruct the TMJ and improve jaw deformity by lengthening the mandibular ramus. But the growth of CCG is unpredictable. In this study, we explored several factors that may affect the absorption and re-ankylosis of CCG, expecting to provide several suggestions to improve future CCG treatment.

NRS2002 score as a prognostic factor in solid tumors treated with immune checkpoint inhibitor therapy: a real-world evidence analysis.

To observe the antitumour efficacy of programmed death 1 (PD-1) inhibitors in the real world and explore the relationship between NRS2002 score or other clinical characteristics and immunotherapy efficacy, we retrospectively analyzed 341 tumor patients who received immune checkpoint inhibitor (ICI) treatment at one center. A total of 341 solid tumor patients treated with ICIs from June 2018 to December 2021 were retrospectively included in this study. Patient characteristics, ICI responses, and survival status were documented, and the relationships between clinical factors and survival were analyzed. Among all patients, the median progression-free survival (PFS) was 5.8 months, and the median overall survival (OS) was 12.5 months. The Performance Status (PS), NRS2002 score, The Naples Prognostic Score (NPS), Lymphocyte and C-reactive protein ratio (LCR), line of therapy, and nutritional support were significantly related to PFS or OS according to univariate analysis. The median PFS and OS were significantly better in the group without nutritional risk (NRS2002 0-2) than those with nutritional risk (NRS2002 ≥ 3) (PFS: HR = 1.82, 95% CI 1.30-2.54, p value < .001; OS: HR = 2.49, 95% CI 1.73-3.59, p value < .001). Cox regression analysis revealed that the NRS2002 score was an independent prognostic factor for both PFS and OS. The objective response rate (ORR) in the group at nutritional risk was lower than that in the group without nutritional risk (8.33% and 19.71%, respectively, p value = .037). Patients at nutritional risk according to the NRS2002 score at initial treatment had a poorer prognosis than those without nutritional risk. The NRS2002 could be used as a preliminary index to predict the efficacy of immune checkpoint inhibitor therapy.

Preparation of Mesophase Pitch with Fine-Flow Texture from Ethylene Tar/Naphthalene by Catalytic Synthesis for High-Thermal-Conductivity Carbon Fibers.

Mesophase pitch is usually prepared by radical polymerization or catalytic polymerization from coal tar, petroleum, and aromatic compounds, and the catalytic synthesis of mesophase pitch from pure aromatic compounds is more controllable in the preparation of high-quality mesophase pitch. However, the corrosive and highly toxic nature of the catalyst has limited the further development of this method. In this study, mesophase pitch was synthetized using ethylene tar and naphthalene as raw materials and boron trifluoride diethyl etherate as a catalyst. The effect of the catalytic reaction on the structure and properties of the mesophase pitch was investigated. The results show that naphthalene plays an important role in the mesophase content and reaction pressure (from above 6 MPa to 2.35 MPa). Mesophase pitch with fine-flow texture can be prepared by introducing more methylene groups, naphthenic structures, and aliphatic hydrocarbons during synthesis. Carbon fibers prepared from mesophase pitch show a split structure, and the thermal conductivity is 730 W/(m·K). This work provides theoretical support for lower toxicity and causticity and for reaction-controlled technology for the synthesis of high-purity mesophase pitch.