A Wrist-Inspired Magneto-Pneumatic Hybrid-Driven Soft Actuator with Bidirectional Torsion.

A novel wrist-inspired soft actuator, which is driven by a magneto-pneumatic hybrid system and based on a Kresling origami unit, is proposed. The geometric model, kinematic analysis model, and quasistatic analysis model of the Kresling origami unit are presented. A key focus is on the formulation and investigation of the variation in rotation angle using the kinematic analysis model. A wrist-inspired soft actuator is designed, and its quasistatic characteristics are validated through various experiments. The paper proposes an innovative magneto-pneumatic hybrid actuation method, capable of achieving bidirectional torsion. This actuation method is experimentally validated, demonstrating the actuator's ability to maintain 3 steady states and its capability for bidirectional torsion deformation. Furthermore, the paper highlights the potential of the Kresling origami unit in designing soft actuators capable of achieving large rotation angles. For instance, an actuator with 6 sides (n = 6) is shown to achieve a rotation angle of 239.5°, and its rotation ratio exceeds 277°, about twice the largest one reported in other literature. The actuator offers a practical and effective solution for bidirectional torsion deformation in soft robotic applications.

Lysine Methyltransferase 5A Promotes the Progression of Growth hormone Pituitary Neuroendocrine Tumors Through the Wnt/ß-catenin Signaling Pathway.

INTRODUCTION: Growth hormone (GH) secreting pituitary adenoma is considered one of the most harmful types of Pituitary Neuroendocrine Tumors (PitNETs). Our previous research has found that high expression of Lysine Methyltransferase 5A (KMT5A) is closely related to the proliferation of PitNETs. The aim of this study was to investigate the role and molecular mechanism of KMT5A in the progression of GH PitNETs. METHODS: Immunohistochemistry, qRT-PCR and Western blot (WB) were used to assess the expression levels of KMT5A in human normal pituitary and GH PitNETs, as well as in rat normal pituitary and GH3 cells. Additionally, we utilized RNA interference technology and treatment with a selective KMT5A inhibitor to decrease the expression of KMT5A in GH3 cells. CCK-8, EdU, Flow cytometry (FCM), clone formation, and WB assay were further employed to evaluate the impact of KMT5A on the proliferation of GH3 cells in vitro. A xenograft model was established to evaluate the role of KMT5A in GH PitNETs progression in vivo. RESULTS: KMT5A was highly expressed in GH PitNETs and GH3 cells. Moreover, the reduction of KMT5A expression led to inhibited growth of GH PitNETs and increased apoptosis of tumor cells, as indicated by the findings from CCK-8, EdU, clone formation and FCM assays. Additionally, WB analysis identified the Wnt/ß-catenin signaling pathway as a potential mechanism through which KMT5A promotes GH PitNETs progression. CONCLUSION: Our research suggests that KMT5A may facilitate the progression of GH PitNETs via the Wnt/ß-catenin signaling pathway. Therefore, KMT5A may serve as a potential therapeutic target and molecular biomarker for GH PitNETs.

Corrigendum: The effect of acupuncture at the Taiyang acupoint on visual function and EEG microstates in myopia.

[This corrects the article DOI: 10.3389/fnint.2023.1234471.].

Occurrence, fate, and risk assessment of antibiotics in conventional and advanced drinking water treatment systems: From source to tap.

The occurrence and removal of 38 antibiotics from nine classes in two drinking water treatment plants (WTPs) were monitored monthly over one year to evaluate the efficiency of typical treatment processes, track the source of antibiotics in tap water and assess their potential risks to ecosystem and human health. In both source waters, 18 antibiotics were detected at least once, with average total antibiotic concentrations of 538.5 ng/L in WTP1 and 569.3 ng/L in WTP2. The coagulation/flocculation and sedimentation, sand filtration and granular activated carbon processes demonstrated limited removal efficiencies. Chlorination, on the other hand, effectively eliminated antibiotics by 48.7 ± 11.9%. Interestingly, negative removal was observed along the distribution system, resulting in a significant antibiotic presence in tap water, with average concentrations of 131.5 ng/L in WTP1 and 362.8 ng/L in WTP2. Source tracking analysis indicates that most antibiotics in tap water may originate from distribution system. The presence of antibiotics in raw water and tap water posed risks to the aquatic ecosystem. Untreated or partially treated raw water could pose a medium risk to infants under six months. Water parameters, for example, temperature, total nitrogen and total organic carbon, can serve as indicators to estimate antibiotic occurrence and associated risks. Furthermore, machine learning models were developed that successfully predicted risk levels using water quality parameters. Our study provides valuable insights into the occurrence, removal and risk of antibiotics in urban WTPs, contributing to the broader understanding of antibiotic pollution in water treatment systems.

Evaluation of the efficacy and safety of immunotherapy in sarcoma: a two-center study.

Background: Sarcoma is a highly heterogeneous malignancy with a poor prognosis. Although chemotherapy and targeted therapy have improved the prognosis to some extent, the efficacy remains unsatisfactory in some patients. The efficacy and safety of immunotherapy in sarcoma need further evaluation. Methods: We conducted a two-center study of sarcoma patients receiving PD-1 immunotherapy at Tianjin Medical University Cancer Institute and Hospital and Henan Provincial Cancer Hospital. The treatment regimens included PD-1 inhibitor monotherapy and combination therapy based on PD-1 inhibitors. The observed primary endpoints were median progression-free survival (mPFS) and median overall survival (mOS). Survival curves were compared using the Kaplan-Meier method. Results: A total of 43 patients were included from the two centers. The median follow-up time for all patients was 13 months (range, 1-48 months). In the group of 37 patients with advanced or unresectable sarcoma, the mPFS was 6 months (95%CI: 5-12 months), and the mOS was 16 months (95%CI: 10-28 months). The ORR was 10.8% (4/37), and the DCR was 18.9% (7/37). Subgroup analysis showed no significant differences in mPFS (p=0.11) and mOS (p=0.88) between patients with PD-L1 negative/positive expression. There were also no significant differences in mPFS (p=0.13) or mOS (p=0.72) between PD-1 inhibitor monotherapy and combination therapy. Additionally, there were no significant differences in mPFS (p=0.52) or mOS (p=0.49) between osteogenic sarcoma and soft tissue sarcoma. Furthermore, the results showed no significant differences in mPFS (p=0.66) or mOS (p=0.96) between PD-1 inhibitors combined with targeted therapy and PD-1 inhibitors combined with AI chemotherapy. Among the 6 patients receiving adjuvant therapy after surgery, the mPFS was 15 months (95%CI: 6-NA months), and the mOS was not reached. In terms of safety, most adverse events were mild (grade 1-2) and manageable. The most severe grade 4 adverse events were bone marrow suppression, which occurred in 4 patients but resolved after treatment. There was also one case of a grade 4 adverse event related to hypertension. Conclusion: Immunotherapy is an effective treatment modality for sarcoma with manageable safety. Further inclusion of more patients or prospective clinical trials is needed to validate these findings.

Psychometric evaluation of the Chinese version of the burnout syndrome assessment scale in nurses.

Objective: This study aimed to translate the Burnout Syndrome Assessment Scale (BOSAS) into Chinese and validate its reliability and validity among Chinese emergency department and ICU nurses. Methods: The scale was translated into Chinese using Brislin's translation principle. A total of 626 nurses from Jiangxi, Zhejiang, and Fujian provinces in China participated in an online questionnaire survey. The survey included the general information questionnaire for nurses developed by the research team and the Chinese version of the Burnout Syndrome Assessment Scale. Reliability and validity of the Chinese version of the scale were analyzed using SPSS.25 and AMOS.24 software. Results: The Chinese version of the Burnout Syndrome Assessment Scale consists of a total of 20 items, encompassing two dimensions: personal burnout and job burnout. This structure is consistent with the original English version of the scale. The Chinese version of BOSAS demonstrated high internal consistency, with a Cronbach's α coefficient of 0.941. Additionally, the scale exhibited good split-half reliability (0.765) and test-retest reliability (0.871). The content validity index (S-CVI) was 0.971, indicating strong content validity. Exploratory factor analysis confirmed the same 2-factor structure as the original scale, and confirmatory factor analysis further validated this structure, with all fit indices indicating appropriateness. Conclusion: The Burnout Syndrome Assessment Scale has been successfully introduced and its reliability and validity have been verified in Chinese emergency department and ICU nurses.

Diagnostic values of contrast-enhanced MRI and contrast-enhanced CT for evaluating the response of hepatocellular carcinoma after transarterial chemoembolisation: a meta-analysis.

OBJECTIVES: To assess and compare the diagnostic value of contrast-enhanced MRI (CEMRI) and contrast-enhanced CT (CECT) for evaluating the response of hepatocellular carcinoma (HCC) after transarterial chemoembolisation (TACE). DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Embase, the Cochrane Library, CNKI and Wanfang databases were systematically searched from inception to 1 August 2023. ELIGIBILITY CRITERIA: Studies with any outcome that demonstrates the diagnostic performance of CEMRI and CECT for HCC after TACE were included. DATA EXTRACTION AND SYNTHESIS: Two authors independently extracted the data and assessed the quality of included studies. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies-2. The diagnostic performance of CEMRI and CECT for the response of HCC was investigated by collecting true and false positives, true and false negatives, or transformed-derived data from each study to calculate specificity and sensitivity. Other outcomes are the positive likelihood ratio/negative likelihood ratio (NLR), the area under the receiver operating characteristic curve (AUC) for diagnostic tests and the diagnostic OR (DOR). Findings were summarised and synthesised qualitatively according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. RESULTS: This study included 5843 HCC patients diagnosed with CEMRI or CECT and treated with TACE from 36 studies. The mean proportion of men in the total sample was 76.3%. The pool sensitivity, specificity and AUC of CEMRI in diagnosing HCC after TACE were 0.92 (95% CI: 0.86 to 0.96), 0.94 (95% CI: 0.86 to 0.98) and 0.98 (95% CI: 0.96 to 0.99). The pool sensitivity, specificity and AUC of CECT in diagnosing HCC after TACE were 0.74 (95% CI: 0.68 to 0.80), 0.98 (95% CI: 0.93 to 1.00) and 0.90 (95% CI: 0.88 to 0.93). CONCLUSIONS: In conclusion, this study found that both CEMRI and CECT had relatively high predictive power for assessing the response of HCC after TACE. Furthermore, the diagnostic value of CEMRI may be superior to CECT in terms of sensitivity, AUC, DOR and NLR.

Development and validation of prediction models for papillary thyroid cancer structural recurrence using machine learning approaches.

BACKGROUND: Although papillary thyroid cancer (PTC) patients are known to have an excellent prognosis, up to 30% of patients experience disease recurrence after initial treatment. Accurately predicting disease prognosis remains a challenge given that the predictive value of several predictors remains controversial. Thus, we investigated whether machine learning (ML) approaches based on comprehensive predictors can predict the risk of structural recurrence for PTC patients. METHODS: A total of 2244 patients treated with thyroid surgery and radioiodine were included. Twenty-nine perioperative variables consisting of four dimensions (demographic characteristics and comorbidities, tumor-related variables, lymph node (LN)-related variables, and metabolic and inflammatory markers) were analyzed. We applied five ML algorithms-logistic regression (LR), support vector machine (SVM), extreme gradient boosting (XGBoost), random forest (RF), and neural network (NN)-to develop the models. The area under the receiver operating characteristic (AUC-ROC) curve, calibration curve, and variable importance were used to evaluate the models' performance. RESULTS: During a median follow-up of 45.5 months, 179 patients (8.0%) experienced structural recurrence. The non-stimulated thyroglobulin, LN dissection, number of LNs dissected, lymph node metastasis ratio, N stage, comorbidity of hypertension, comorbidity of diabetes, body mass index, and low-density lipoprotein were used to develop the models. All models showed a greater AUC (AUC = 0.738 to 0.767) than did the ATA risk stratification (AUC = 0.620, DeLong test: P < 0.01). The SVM, XGBoost, and RF model showed greater sensitivity (0.568, 0.595, 0.676), specificity (0.903, 0.857, 0.784), accuracy (0.875, 0.835, 0.775), positive predictive value (PPV) (0.344, 0.272, 0.219), negative predictive value (NPV) (0.959, 0.959, 0.964), and F1 score (0.429, 0.373, 0.331) than did the ATA risk stratification (sensitivity = 0.432, specificity = 0.770, accuracy = 0.742, PPV = 0.144, NPV = 0.938, F1 score = 0.216). The RF model had generally consistent calibration compared with the other models. The Tg and the LNR were the top 2 important variables in all the models, the N stage was the top 5 important variables in all the models. CONCLUSIONS: The RF model achieved the expected prediction performance with generally good discrimination, calibration and interpretability in this study. This study sheds light on the potential of ML approaches for improving the accuracy of risk stratification for PTC patients. TRIAL REGISTRATION: Retrospectively registered at www.chictr.org.cn (trial registration number: ChiCTR2300075574, date of registration: 2023-09-08).

Electronic Spin Alignment within Homologous NiS2/NiSe2 Heterostructures to Promote Sulfur Redox Kinetics in Lithium-Sulfur Batteries.

The catalytic activation of the Li-S reaction is fundamental to maximize the capacity and stability of Li-S batteries (LSBs). Current research on Li-S catalysts mainly focuses on optimizing the energy levels to promote adsorption and catalytic conversion, while frequently overlooking the electronic spin state influence on charge transfer and orbital interactions. Here, hollow NiS2/NiSe2 heterostructures encapsulated in a nitrogen-doped carbon matrix (NiS2/NiSe2@NC) are synthesized and used as a catalytic additive in sulfur cathodes. The NiS2/NiSe2 heterostructure promotes the spin splitting of the 3d orbital, driving the Ni3+ transformation from low to high spin. This high spin configuration raises the electronic energy level and activates the electronic state. This accelerates the charge transfer and optimizes the adsorption energy, lowering the reaction energy barrier of the polysulfides conversion. Benefiting from these characteristics, LSBs based on NiS2/NiSe2@NC/S cathodes exhibit high initial capacity (1458 mAh·g⁻1 at 0.1C), excellent rate capability (572 mAh·g⁻1 at 5C), and stable cycling with an average capacity decay rate of only 0.025% per cycle at 1C during 500 cycles. Even at high sulfur loadings (6.2 mg·cm⁻2), high initial capacities of 1173 mAh·g⁻1 (7.27 mAh·cm⁻2) are measured at 0.1C, and 1058 mAh·g⁻1 is retained after 300 cycles.

The effect of floating spline parameter on the dynamic characteristic of encased differential planetary gear train.

The load sharing performance of encased differential planetary system has a great impact on the operating performance and service life of the transmission system of the coaxial high speed helicopter. In order to improve the load-sharing performance of the gear pair, the influence of different floating spline structural parameters on the load sharing characteristics of the system was studied. Considering the manufacturing error, installation error, time varying meshing stiffness and other factors, the Lagrange equation is used to construct the dynamic model of encased differential planetary gear train with floating spline structure. The effects of input torque, spline clearance, spline shaft stiffness and spline friction coefficient on the load sharing performance of gear pairs were analyzed. The results show that the differential stage system has a better load sharing performance than the encased stage system. The increase of input torque helps to improve the load sharing performance of the system, and the improvement of the encased stage system is more obvious. The floating spline of sun gear of the encased stage has a greater impact on the load sharing performance of the system. Furthermore, increasing the floating spline clearance, reducing spline shaft stiffness or increasing the friction coefficient of the spline can improve the load sharing performance of the system overall.

A novel method-based reinforcement learning with deep temporal difference network for flexible double shop scheduling problem.

This paper studies the flexible double shop scheduling problem (FDSSP) that considers simultaneously job shop and assembly shop. It brings about the problem of scheduling association of the related tasks. To this end, a reinforcement learning algorithm with a deep temporal difference network is proposed to minimize the makespan. Firstly, the FDSSP is defined as the mathematical model of the flexible job-shop scheduling problem joined to the assembly constraint level. It is translated into a Markov decision process that directly selects behavioral strategies according to historical machining state data. Secondly, the proposed ten generic state features are input into the deep neural network model to fit the state value function. Similarly, eight simple constructive heuristics are used as candidate actions for scheduling decisions. From the greedy mechanism, optimally combined actions of all machines are obtained for each decision step. Finally, a deep temporal difference reinforcement learning framework is established, and a large number of comparative experiments are designed to analyze the basic performance of this algorithm. The results showed that the proposed algorithm was better than most other methods, which contributed to solving the practical production problem of the manufacturing industry.

Robust deep learning from incomplete annotation for accurate lung nodule detection.

Deep learning plays a significant role in the detection of pulmonary nodules in low-dose computed tomography (LDCT) scans, contributing to the diagnosis and treatment of lung cancer. Nevertheless, its effectiveness often relies on the availability of extensive, meticulously annotated dataset. In this paper, we explore the utilization of an incompletely annotated dataset for pulmonary nodules detection and introduce the FULFIL (Forecasting Uncompleted Labels For Inexpensive Lung nodule detection) algorithm as an innovative approach. By instructing annotators to label only the nodules they are most confident about, without requiring complete coverage, we can substantially reduce annotation costs. Nevertheless, this approach results in an incompletely annotated dataset, which presents challenges when training deep learning models. Within the FULFIL algorithm, we employ Graph Convolution Network (GCN) to discover the relationships between annotated and unannotated nodules for self-adaptively completing the annotation. Meanwhile, a teacher-student framework is employed for self-adaptive learning using the completed annotation dataset. Furthermore, we have designed a Dual-Views loss to leverage different data perspectives, aiding the model in acquiring robust features and enhancing generalization. We carried out experiments using the LUng Nodule Analysis (LUNA) dataset, achieving a sensitivity of 0.574 at a False positives per scan (FPs/scan) of 0.125 with only 10% instance-level annotations for nodules. This performance outperformed comparative methods by 7.00%. Experimental comparisons were conducted to evaluate the performance of our model and human experts on test dataset. The results demonstrate that our model can achieve a comparable level of performance to that of human experts. The comprehensive experimental results demonstrate that FULFIL can effectively leverage an incomplete pulmonary nodule dataset to develop a robust deep learning model, making it a promising tool for assisting in lung nodule detection.

Treating cancer through modulating exosomal protein loading and function: The prospects of natural products and traditional Chinese medicine.

Exosomes, small yet vital extracellular vesicles, play an integral role in intercellular communication. They transport critical components, such as proteins, lipid bilayers, DNA, RNA, and glycans, to target cells. These vesicles are crucial in modulating the extracellular matrix and orchestrating signal transduction processes. In oncology, exosomes are pivotal in tumor growth, metastasis, drug resistance, and immune modulation within the tumor microenvironment. Exosomal proteins, noted for their stability and specificity, have garnered widespread attention. This review delves into the mechanisms of exosomal protein loading and their impact on tumor development, with a focus on the regulatory effects of natural products and traditional Chinese medicine on exosomal protein loading and function. These insights not only offer new strategies and methodologies for cancer treatment but also provide scientific bases and directions for future clinical applications.

Effect of acupuncture timing on functional impairment at 6 months post-onset in patients with first-ever stroke: a prospective cohort study. / é’ˆåˆºæ—¶æœºå¯¹é¦–æ¬¡ä¸­é£Žæ‚£è€ å‘ç— åŽ6ä¸ªæœˆåŠŸèƒ½éšœç¢çš„å½±å“ï¼šå‰çž»æ€§é˜Ÿåˆ—ç ”ç©¶.

OBJECTIVES: To observe the effect of acupuncture intervention in the acute phase on functional impairment at 6 months post-onset in patients with first-ever stroke, and provide evidence for selecting optimal acupuncture timing in the real-world setting. METHODS: A total of 601 patients with first-ever stroke were divided into an acute intervention group (onset within 14 days, 256 cases) and a non-acute intervention group (onset between 15 and 90 days, 345 cases) based on whether they received acupuncture treatment in the acute phase. The assessments were conducted at baseline and 6 months post-onset, including modified Rankin scale (mRS) score, total number of acupuncture sessions, total number of combined therapies (moxibustion, cupping, tuina and rehabilitation treatment), recurrence, death events and disability. Logistic regression analysis was used to analyze the association between acupuncture timing and the risk of disability at 6 months post-onset. The mRS transition method was employed to assess the effect of acupuncture timing on functional improvement at 6 months post-onset. RESULTS: Without adjusting for confounding factors, compared with the non-acute intervention group, the patients in the acute intervention group had reduced risk of disability at 6 months post-onset (OR=0.434, 95%CI: 0.309-0.609, P=0.000). After adjusting for variables i.e. severity of illness, number of acupuncture sessions, and number of cupping sessions, compared with the non-acute intervention group, the patients in the acute intervention group had reduced risk of disability at 6 months post-onset (OR=0.588, 95%CI: 0.388-0.890, P=0.012). After adjusting for all confounding factors, including severity of illness, number of acupuncture sessions, number of cupping sessions, gender, smoking and drinking history, comorbidities, and diagnosis, compared with the non-acute intervention group, the patients in the acute intervention group continued to have a reduced risk of disability at 6 months post-onset (OR=0.629, 95%CI: 0.408-0.971, P=0.036). Both groups showed an overall shift towards lower mRS scores at 6 months post-onset compared to baseline, with a more significant shift towards lower scores in the acute intervention group than the non-acute intervention group. CONCLUSIONS: In the real-world setting, acupuncture intervention in the acute phase in patients with first-ever stroke, compared to acupuncture intervention after the acute phase, reduces the risk of disability at 6 months post-onset and improves functional status.

Hippuric acid alleviates dextran sulfate sodium-induced colitis via suppressing inflammatory activity and modulating gut microbiota.

Inflammatory bowel disease (IBD) is a chronic inflammatory disease associated with metabolic disorder and gut dysbiosis. Decreased abundance of hippuric acid (HA) was found in patients with IBD. HA, metabolized directly from benzoic acid in the intestine and indirectly from polyphenols, serves as a marker of polyphenol catabolism. While polyphenols and benzoic acid have been shown to alleviate intestinal inflammation, the role of HA in this context remains unknown. Herein, we investigated the effects and mechanism of HA on DSS-induced colitis mice. The results revealed that HA alleviated clinical activity and intestinal barrier damage, decreased pro-inflammatory cytokine production. Metagenomic sequencing suggested that HA treatment restored the gut microbiota, including an increase in beneficial gut bacteria such as Adlercreutzia, Eubacterium, Schaedlerella and Bifidobacterium_pseudolongum. Furthermore, we identified 113 candidate genes associated with IBD that are potentially under HA regulation through network pharmacological analyses. 10 hub genes including ALB, IL-6, HSP90AA1, and others were identified using PPI analysis and validated using molecular docking and mRNA expression analysis. Additionally, KEGG analysis suggested that the renin-angiotensin system (RAS), NF-κB signaling and Rap1 signaling pathways were important pathways in the response of HA to colitis. Thus, HA may provide novel biotherapy options for IBD.

Quantitative characterization of micro-scanning imaging aliasing and optical parameter optimization.

Imaging aliasing is a common problem in the imaging domain. The aliasing of micro-scanning imaging is difficult to characterize accurately, and the matching relationship between the optical system and micro-scanning sampling is unclear. In this paper, a micro-scanning aliasing analysis model is proposed based on the property of sampling squeeze, in which the transfer functions of the optical system, detector, and digital filter are coupled with the micro-scanning sampling process. First, the imaging aliasing under different micro-scanning sampling modes is evaluated based on the constraint relationship of the transfer functions for each part. The stretch factor of the transfer function under micro-scanning sampling is calculated by utilizing the amount of aliasing. Second, the micro-scanning imaging transfer function under different optical parameters is predicted by the stretch factor, and the results indicate the existence of an optimal F-number that maximizes the micro-scanning performance improvement. Furthermore, the optimal micro-scanning imaging F-numbers for different fill factors are given, and the matching relationship between optical parameters, fill factors and micro-scanning mode is analyzed. Finally, a micro-scanning imaging simulation is performed based on the actual imaging transfer and micro-scanning sampling process. The simulation experiment verifies the accuracy of the micro-scanning aliasing model and gives the consistent test results of the optimal F-number. This paper can provide theoretical support for the matching relationship among micro-scanning imaging parameters, which is of great significance for the refined optimal design of micro-scanning imaging systems.

Preoperatively predicting vessels encapsulating tumor clusters in hepatocellular carcinoma: Machine learning model based on contrast-enhanced computed tomography.

BACKGROUND: Recently, vessels encapsulating tumor clusters (VETC) was considered as a distinct pattern of tumor vascularization which can primarily facilitate the entry of the whole tumor cluster into the bloodstream in an invasion independent manner, and was regarded as an independent risk factor for poor prognosis in hepatocellular carcinoma (HCC). AIM: To develop and validate a preoperative nomogram using contrast-enhanced computed tomography (CECT) to predict the presence of VETC+ in HCC. METHODS: We retrospectively evaluated 190 patients with pathologically confirmed HCC who underwent CECT scanning and immunochemical staining for cluster of differentiation 34 at two medical centers. Radiomics analysis was conducted on intratumoral and peritumoral regions in the portal vein phase. Radiomics features, essential for identifying VETC+ HCC, were extracted and utilized to develop a radiomics model using machine learning algorithms in the training set. The model's performance was validated on two separate test sets. Receiver operating characteristic (ROC) analysis was employed to compare the identified performance of three models in predicting the VETC status of HCC on both training and test sets. The most predictive model was then used to constructed a radiomics nomogram that integrated the independent clinical-radiological features. ROC and decision curve analysis were used to assess the performance characteristics of the clinical-radiological features, the radiomics features and the radiomics nomogram. RESULTS: The study included 190 individuals from two independent centers, with the majority being male (81%) and a median age of 57 years (interquartile range: 51-66). The area under the curve (AUC) for the combined radiomics features selected from the intratumoral and peritumoral areas were 0.825, 0.788, and 0.680 in the training set and the two test sets. A total of 13 features were selected to construct the Rad-score. The nomogram, combining clinical-radiological and combined radiomics features could accurately predict VETC+ in all three sets, with AUC values of 0.859, 0.848 and 0.757. Decision curve analysis revealed that the radiomics nomogram was more clinically useful than both the clinical-radiological feature and the combined radiomics models. CONCLUSION: This study demonstrates the potential utility of a CECT-based radiomics nomogram, incorporating clinical-radiological features and combined radiomics features, in the identification of VETC+ HCC.

A viral protein competitively bound to rice CIPK23 inhibits potassium absorption and facilitates virus systemic infection in rice.

Potassium (K+) plays a crucial role as a macronutrient in the growth and development of plants. Studies have definitely determined the vital roles of K+ in response to pathogen invasion. Our previous investigations revealed that rice plants infected with rice grassy stunt virus (RGSV) displayed a reduction in K+ content, but the mechanism by which RGSV infection subverts K+ uptake remains unknown. In this study, we found that overexpression of RGSV P1, a specific viral protein encoded by viral RNA1, results in enhanced sensitivity to low K+ stress and exhibits a significantly lower rate of K+ influx compared to wild-type rice plants. Further investigation revealed that RGSV P1 interacts with OsCIPK23, an upstream regulator of Shaker K+ channel OsAKT1. Moreover, we found that the P1 protein recruits the OsCIPK23 to the Cajal bodies (CBs). In vivo assays demonstrated that the P1 protein competitively binds to OsCIPK23 with both OsCBL1 and OsAKT1. In the nucleus, the P1 protein enhances the binding of OsCIPK23 to OsCoilin, a homologue of the signature protein of CBs in Arabidopsis, and facilitates their trafficking through these CB structures. Genetic analysis indicates that mutant in oscipk23 suppresses RGSV systemic infection. Conversely, osakt1 mutants exhibited increased sensitivity to RGSV infection. These findings suggest that RGSV P1 hinders the absorption of K+ in rice plants by recruiting the OsCIPK23 to the CB structures. This process potentially promotes virus systemic infection but comes at the expense of inhibiting OsAKT1 activity.

A DNA circuit that records molecular events.

Characterizing the relative onset time, strength, and duration of molecular signals is critical for understanding the operation of signal transduction and genetic regulatory networks. However, detecting multiple such molecules as they are produced and then quickly consumed is challenging. A MER can encode information about transient molecular events as stable DNA sequences and are amenable to downstream sequencing or other analysis. Here, we report the development of a de novo molecular event recorder that processes information using a strand displacement reaction network and encodes the information using the primer exchange reaction, which can be decoded and quantified by DNA sequencing. The event recorder was able to classify the order at which different molecular signals appeared in time with 88% accuracy, the concentrations with 100% accuracy, and the duration with 75% accuracy. This simultaneous and highly programmable multiparameter recording could enable the large-scale deciphering of molecular events such as within dynamic reaction environments, living cells, or tissues.

Thermal-Rectified Gradient Porous Polymeric Film for Solar-Thermal Regulatory Cooling.

Solar-thermal regulation concerning thermal insulation and solar modulation is pivotal for cooling textiles and smart buildings. Nevertheless, a contradiction arises in balancing the demand to prevent external heat infiltration with the efficient dissipation of excess heat from enclosed spaces. Here, a concentration-gradient polymerization strategy is presented for fabricating a gradient porous polymeric film comprising interconnected polymeric microspheres. This method involves establishing an electric field-driven gradient distribution of charged crosslinkers in the precursor solution, followed by subsequent polymerization and freeze-drying processes. The resulting porous film exhibits a significant porosity gradient along its thickness, leading to exceptional unidirectional thermal insulation capabilities with a thermal rectification factor of 21%. The gradient porous film, with its thermal rectification properties, effectively reconciles the conflicting demands of diverse thermal conductivity for cooling unheated and spontaneously heated enclosed spaces. Consequently, the gradient porous film demonstrates remarkable enhancements in solar-thermal management, achieving temperature reductions of 3.0 and 4.1 °C for unheated and spontaneously heated enclosed spaces, respectively, compared to uniform porous films. The developed gradient-structured porous film thus holds promise for the development of thermal-rectified materials tailored to regulate solar-thermal conditions within enclosed environments.