Antagonistic RALF peptides control an intergeneric hybridization barrier on Brassicaceae stigmas.

Pollen-pistil interactions establish interspecific/intergeneric pre-zygotic hybridization barriers in plants. The rejection of undesired pollen at the stigma is crucial to avoid outcrossing but can be overcome with the support of mentor pollen. The mechanisms underlying this hybridization barrier are largely unknown. Here, in Arabidopsis, we demonstrate that receptor-like kinases FERONIA/CURVY1/ANJEA/HERCULES RECEPTOR KINASE 1 and cell wall proteins LRX3/4/5 interact on papilla cell surfaces with autocrine stigmatic RALF1/22/23/33 peptide ligands (sRALFs) to establish a lock that blocks the penetration of undesired pollen tubes. Compatible pollen-derived RALF10/11/12/13/25/26/30 peptides (pRALFs) act as a key, outcompeting sRALFs and enabling pollen tube penetration. By treating Arabidopsis stigmas with synthetic pRALFs, we unlock the barrier, facilitating pollen tube penetration from distantly related Brassicaceae species and resulting in interspecific/intergeneric hybrid embryo formation. Therefore, we uncover a "lock-and-key" system governing the hybridization breadth of interspecific/intergeneric crosses in Brassicaceae. Manipulating this system holds promise for facilitating broad hybridization in crops.

Enhancing Protein Solubility via Glycosylation: From Chemical Synthesis to Machine Learning Predictions.

Glycosylation is a valuable tool for modulating protein solubility; however, the lack of reliable research strategies has impeded efficient progress in understanding and applying this modification. This study aimed to bridge this gap by investigating the solubility of a model glycoprotein molecule, the carbohydrate-binding module (CBM), through a two-stage process. In the first stage, an approach involving chemical synthesis, comparative analysis, and molecular dynamics simulations of a library of glycoforms was employed to elucidate the effect of different glycosylation patterns on solubility and the key factors responsible for the effect. In the second stage, a predictive mathematical formula, innovatively harnessing machine learning algorithms, was derived to relate solubility to the identified key factors and accurately predict the solubility of the newly designed glycoforms. Demonstrating feasibility and effectiveness, this two-stage approach offers a valuable strategy for advancing glycosylation research, especially for the discovery of glycoforms with increased solubility.

TIRSF: a web server for screening gene signatures to predict Tumor immunotherapy response.

Immune checkpoint blockade (ICB) therapy has been successfully applied to clinically therapeutics in multiple cancers, but its efficacy varies greatly among different patients and cancer types. Therefore, the construction of gene signatures to identify patients who could benefit from ICB therapy is particularly important for precision cancer treatment. However, due to the lack of a user-friendly platform, the construction of such gene signatures is a great challenge for clinical investigators who have limited programming skills. In light of this challenge, we developed a web server called Tumor Immunotherapy Response Signature Finder(TIRSF) for the construction of gene signatures to predict ICB therapy response in cancer patients. TIRSF consists of three functional modules. The first module is the Signature Discovery module which provides signature construction and performance evaluation functionalities. The second is a module for response prediction based on the TIRSF signatures, which enables response prediction and prognostic analysis of immunotherapy samples. The last is a module for response prediction based on existing signatures. This module currently integrates 24 published signatures for ICB therapy response prediction. Together, all of above features can be freely accessed at http://tirsf.renlab.org/.

Anterior Talofibular Ligament Repair in Combination With Anterior Tibiofibular Ligament Distal Fascicle Transfer for The Treatment of Chronic Lateral Ankle Instability: A Finite Element Analysis.

In recent years, anterior tibiofibular ligament-distal fascicle transfers for anterior talofibular ligament augmentation repair have proposed. However, a comprehensive biomechanical study on the anterior tibiofibular ligament-distal fascicle transfer is still lacking. We are established four distinct groups, namely the normal, the anterior talofibular ligament rupture, the anterior talofibular ligament repair, and the anterior talofibular ligament repair + anterior tibiofibular ligament-distal fascicle transfer. We assessed the anterior drawer test and varus stress test of the ankle in each group. Moreover, we employed the model to simulate and compute the total displacement and von-Mises stress of the talus cartilage at varying gait phases, including foot strike, tibia vertical, and toe-off phases. The results of the anterior drawer test and varus stress test revealed that the anterior talofibular ligament repair + anterior tibiofibular ligament-distal fascicle transfer group exhibited greater closeness to the normal group. Regarding von-Mises stress in cartilage, the three gait instants had higher values in the anterior talofibular ligament repair + anterior tibiofibular ligament-distal fascicle transfer group than the other groups. Nevertheless, regarding total displacement, the toe-off phases exhibited higher values in the anterior talofibular ligament repair + anterior tibiofibular ligament-distal fascicle transfer group than the other groups. Using ATiFL-DF transfer to augment ATFL repair is a potential feasible procedure. However, this procedure could potentially compromise the anterior tibiofibular ligament's contribution to the dynamic stability of the ankle. Therefore, we recommend conducting further in-depth research to ensure the suitability and success of this technique in a clinical environment.

Anchored Weakly-Solvated Electrolytes for High-Voltage and Low-Temperature Lithium-ion Batteries.

Electrolytes endowed with high oxidation/reduction interfacial stability, fast Li-ion desolvation process and decent ionic conductivity over wide temperature region are known critical for low temperature and fast-charging performance of energy-dense batteries, yet these characteristics are rarely satisfied simultaneously. Here, we report anchored weakly-solvated electrolytes (AWSEs), that are designed by extending the chain length of polyoxymethylene ether electrolyte solvent, can achieve the above merits at moderate salt concentrations. The -O-CH2-O- segment in solvent enables the weak four-membered ring Li+ coordination structure and the increased number of segments can anchor the solvent by Li+ without largely sacrificing the ionic dissociation ability. Therefore, the single salt/single solvent AWSEs enable solvent co-intercalation-free behavior towards graphite (Gr) anode and high oxidation stability towards high-nickel cathode (LiNi0.8Co0.1Mn0.1O2-NCM811), as well as the formation of inorganic rich electrode/electrolyte interphase on both of them due to the anion-rich solvation shells. The capacity retention of Gr||NCM811 Ah-class pouch cell can reach 70.85% for 1000 cycles at room-temperature and 75.86% for 400 cycles at -20 °C. This work points out a promising path toward the molecular design of electrolyte solvents for high-energy/power battery systems that are adaptive for extreme conditions.

Data Mining and Graph Network Deep Learning for Band Gap Prediction in Crystalline Borate Materials.

Crystalline borates are an important class of functional materials with wide applications in photocatalysis and laser technologies. Obtaining their band gap values in a timely and precise manner is a great challenge in material design due to the issues of computational accuracy and cost of first-principles methods. Although machine learning (ML) techniques have shown great successes in predicting the versatile properties of materials, their practicality is often limited by the data set quality. Here, by using a combination of natural language processing searches and domain knowledge, we built an experimental database of inorganic borates, including their chemical compositions, band gaps, and crystal structures. We performed graph network deep learning to predict the band gaps of borates with accuracy, and the results agreed favorably with experimental measurements from the visible-light to the deep-ultraviolet (DUV) region. For a realistic screening problem, our ML model could correctly identify most of the investigated DUV borates. Furthermore, the extrapolative ability of the model was validated against our newly synthesized borate crystal Ag3B6O10NO3, supplemented by the discussion of an ML-based material design for structural analogues. The applications and interpretability of the ML model were also evaluated extensively. Finally, we implemented a web-based application, which could be utilized conveniently in material engineering for the desired band gap. The philosophy behind this study is to use cost-effective data mining techniques to build high-quality ML models, which can provide useful clues for further material design.

Designed Iron Catalysts for Allylic C-H Functionalization of Propylene and Simple Olefins.

Propylene gas is produced worldwide by steam cracking on million-metric-ton scale per year. It serves as a valuable starting material for π-bond functionalization but is rarely applied in transition metal-catalyzed allylic C-H functionalization for fine chemical synthesis. Herein, we report that a newly-developed cationic cyclopentadienyliron dicarbonyl complex allows for the conversion of propylene to its allylic C-C bond coupling products under catalytic conditions. This approach was also found applicable to the allylic functionalization of simple α-olefins with distinctive branched selectivity. Experimental and computational mechanistic studies supported the allylic deprotonation of the metal-coordinated alkene as the turnover-limiting step and led to insights into the multifaceted roles of the newly designed ligand in promoting allylic C-H functionalization with enhanced reactivity and stereoselectivity.

A meta-analysis of randomized controlled trials on therapeutic efficacy and safety of autologous cell therapy for atherosclerosis obliterans.

OBJECTIVE: Atherosclerosis obliterans (ASO) is a chronic occlusive arterial disease and the most common type of peripheral arterial disease. Current treatment options like medication and vascularization have limited effects for "no-option" patients, and stem cell therapy is considered a viable option, although its application and efficacy have not been standardized. The objective of this review was to assess the safety and efficacy of autologous stem cell therapy in patients with ASO. METHODS: We performed a literature search of published randomized controlled trials (RCTs) for patients with ASO receiving stem cell therapy without a revascularization option. PubMed, Embase, and the Cochrane Library were searched. This study was conducted by a pair of authors independently and audited by a third author. Data were synthesized with a random-effects model. RESULTS: A total of 630 patients in 12 RCTs were included. The results showed that cell therapy significantly improved total amputation (relative risk [RR], 0.64; 95% confidence interval [CI], 0.47-0.87; P = .004), major amputation (RR, 0.69; 95% CI, 0.50-0.94; P = .02), ankle-brachial index (mean difference [MD], 0.08; 95% CI, 0.02-0.13; P = .004), transcutaneous oxygen tension (MD, 11.52; 95% CI, 3.60-19.43; P = .004), and rest pain score (MD, -0.64; 95% CI, -1.10 to -0.17; P = .007) compared with placebo or standard care. However, current studies showed cell therapy was not superior to placebo or standard care in all-cause death (RR, 0.75; 95% CI, 0.41-1.36; P = .34) and ulcer size (MD, -8.85; 95% CI, -29.05 to 11.36; P = .39). The number of trials included was limited. Moreover, most trials were designed for "no-option" patients, and thus the results should be applied with caution to other patients with peripheral arterial disease. CONCLUSIONS: Patients with ASO can benefit from autologous cell therapy in limb salvage, limb blood perfusion, and rest pain alleviation.

Enhanced Interlayer Interaction and Second-Harmonic-Generation Response in a KBe2BO3F2-Type Inorganic-Organic Hybrid Zinc Borate.

A new inorganic-organic hybrid zinc borate was prepared under hydrothermal conditions. This compound is the first KBe2BO3F2 (KBBF) derivative with zinc borate layers linked by mononegatively charged amino acids. Notably, it exhibits a relatively large second-harmonic-generation response of about 2.0 times that of KBBF and a moderate birefringence for phase matching in the UV region. The enhanced interlayer interaction was evaluated by theoretical calculations based on density functional theory.

Iron-Catalyzed Contrasteric Functionalization of Allenic C(sp2)-H Bonds: Synthesis of α-Aminoalkyl 1,1-Disubstituted Allenes.

An iron-catalyzed C-H functionalization of simple monosubstituted allenes is reported. An efficient protocol for this process was made possible by the use of a newly developed electron-rich and sterically hindered cationic cyclopentadienyliron dicarbonyl complex as the catalyst and N-sulfonyl hemiaminal ether reagents as precursors to iminium ion electrophiles. Under optimized conditions, the use of a mild, functional-group-tolerant base enabled the conversion of a range of monoalkyl allenes to their allenylic sulfonamido 1,1-disubstituted derivatives, a previously unreported and contrasteric regiochemical outcome for the C-H functionalization of electronically unbiased and directing-group-free allenes.

Intraoperative cell salvage is associated with reduced allogeneic blood requirements and has no significant impairment on coagulation function in patients undergoing cesarean delivery: a retrospective study.

OBJECTIVE: The aim of the study is to examine the association between Intraoperative cell salvage (ICS), allogeneic blood transfusion (ABT) and coagulation function in obstetrics. METHODS: A total of 486 pregnant women undergoing cesarean delivery, of whom 157 were enrolled in this retrospective study. Patients were divided into ICS group (n = 101, ICS used during operation) and control group (n = 56, ICS not used during operation). Clinical data, including plasma prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen (Fib) and thrombin time (TT) levels, were collected from all patients preoperatively (within 12-24 h) and postoperatively (within 6-12 h) and analyzed by t test, two-way repeated-measures ANOVA and Spearman's correlation. RESULTS: The use of ICS is associated with lower requirement rate for ABT (P < .001), while the blood loss was similar between the two groups (P = .990). Mean volume of ICS transfusion was 432.65 mL. Compared to preoperative values, the postoperative PT and APTT levels were significantly increased, while Fib was decreased in the two groups (all P < .01). No significant difference in coagulation function was observed between groups in preoperative and postoperative phase (P > .05). Furthermore, PT, APTT and TT after surgery were not correlated with the transfused volume of salvaged blood (P > .05) while the levels of Fib were negatively correlated with the volume (P < .01). In addition, there were no transfusion reactions in both two groups. CONCLUSIONS: Intraoperative cell salvage is correlated with reduced allogeneic blood requirements but did not impair blood coagulation significantly in patients undergoing cesarean delivery.

Stereodivergent Alkyne Hydrofluorination Using Protic Tetrafluoroborates as Tunable Reagents.

The discovery of safe, general, and practical procedures to prepare vinyl fluorides from readily available precursors remains a synthetic challenge. The metal-free hydrofluorination of alkynes constitutes an attractive though elusive strategy for their preparation. Introduced here is an inexpensive and easily handled reagent that enables the development of simple and scalable protocols for the regioselective hydrofluorination of alkynes to access both the E and Z isomers of vinyl fluorides. These reaction conditions were suitable for a diverse collection of alkynes, including several highly functionalized pharmaceutical derivatives. Computational and experimental mechanistic studies support C-F bond formation through vinyl cation intermediates, with the E- and Z-hydrofluorination products forming under kinetic and thermodynamic control, respectively.

Molecular dynamics investigations of oligosaccharides recognized by family 16 and 22 carbohydrate binding modules.

As a non-catalytic domain, carbohydrate binding modules (CBMs) are often considered to play some key roles in the degradation and recognition of polysaccharides catalyzed by cellulases. In this work, we investigated the recognition dynamics of cello- or xylo-saccharides by two typical CBMs (CBM16-1 and CBM22-2), which are grouped into Type B CBMs. By combining extensive molecular dynamics, principle component analysis, and binding free energy calculations, we constructed several complex models of the two CBMs in both complex cello- and xylo-oligosaccharides. The corresponding substrate recognition affinity and critical residues having significant contributions were systematically investigated. The residues containing aromatic side chain groups were shown to contribute significantly to substrate binding. The calculated binding free energies were in fairly good agreement with the experimental measurements with the absolute mean error of 0.69 kcal mol-1. The overall electrostatic interactions were shown to have negative effects on substrate recognition. Further metadynamics simulations revealed the substrate dissociation process.

A Novel Deep Learning Method for Intelligent Fault Diagnosis of Rotating Machinery Based on Improved CNN-SVM and Multichannel Data Fusion.

Intelligent fault diagnosis methods based on deep learning becomes a research hotspot in the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of rotating machinery, especially for fault orientations and severity degree, is still a major challenge in the field of intelligent fault diagnosis. The traditional fault diagnosis methods rely on the manual feature extraction of engineers with prior knowledge. To effectively identify an incipient fault in rotating machinery, this paper proposes a novel method, namely improved the convolutional neural network-support vector machine (CNN-SVM) method. This method improves the traditional convolutional neural network (CNN) model structure by introducing the global average pooling technology and SVM. Firstly, the temporal and spatial multichannel raw data from multiple sensors is directly input into the improved CNN-Softmax model for the training of the CNN model. Secondly, the improved CNN are used for extracting representative features from the raw fault data. Finally, the extracted sparse representative feature vectors are input into SVM for fault classification. The proposed method is applied to the diagnosis multichannel vibration signal monitoring data of a rolling bearing. The results confirm that the proposed method is more effective than other existing intelligence diagnosis methods including SVM, K-nearest neighbor, back-propagation neural network, deep BP neural network, and traditional CNN.

The expression of epithelial intercellular junctional proteins in the sinonasal tissue of subjects with chronic rhinosinusitis: a histopathologic study.

OBJECTIVE: To evaluate the expression of five epithelial intercellular junctional proteins in the sinonasal tissue of subjects with chronic rhinosinusitis (CRS). METHODS: Forty-one samples of nasal polyp tissue of CRS patients with nasal polyps (wNP), 20 ethmoid sinus mucosa of CRS patients without nasal polyps (sNP) and 19 nasal mucosa of controls were collected and assessed for the expression of zonulae occludens (ZO-1), claudin-1, E-cadherin and desmoglein-1 and -2 (DSG1, DSG2) using immunohistochemical staining. Interleukin (IL)-5, IL-6 and IL-8 concentrations in the tissues were also measured using ELISA. RESULTS: The expression of ZO-1, claudin-1, DSG1 and DSG2 in the CRSwNP patient group and the expression of claudin-1, DSG1 and DSG2 of the CRSsNP patient group was significantly lower compared to that of the control group. Furthermore, the expression of DSG1 in the CRSwNP patient group was also significantly lower than in the CRSsNP patient group. In contrast, the expression of E-cadherin in the CRSwNP and the CRSsNP patient groups was significantly greater compared to the controls. The assessment of associations between the expression of the intercellular junctional proteins and cytokines demonstrated negative correlations between IL-5 and claudin-1, IL-6 and claudin-1, IL-6 and DSG2, IL-8 and DSG1, and IL-8 and DSG2. In contrast, a positive correlation was found between IL-8 and E-cadherin. CONCLUSIONS: Differences in the expression of epithelial intercellular junctional proteins may play an important role in the pathogenesis of CRS.

Quadrilateral plate classification program of acetabular fractures based on three-column classification: a three-dimensional fracture mapping study.

BACKGROUND: A new classification system for acetabular fractures has been proposed in recent years, which is called the 3-column classification. However, this system does not provide information regarding quadrilateral plate fractures. To address this issue, we utilized three-dimensional (3D) fracture line mapping and heat map to analyze the link between the 3-column classification and quadrilateral plate fractures. METHODS: We collected CT scan data from 177 patients who had been diagnosed with acetabular fractures. Additionally, we utilized a CT scan of a healthy adult to generate a standard acetabular model. We utilized the collected CT data of the fracture to create a 3D model and subsequently reduced it. We then matched each acetabular fracture model with the standard acetabular model and mapped all of the fracture lines to the standard model. 3D fracture lines and heat maps were created by overlapping all fracture lines. Fracture characteristics were then summarized using these maps. RESULTS: This study analyzed a total of 221 acetabular fractures. The most frequently observed fracture type, based on the three-column classification, was A1.2, which corresponds to fractures of the anterior column. In contrast, the least common type of fracture was A4, which represents fractures of the central wall. It was noted that quadrilateral plate fractures were frequently observed in fractures classified as type B and C according to the three-column classification. CONCLUSIONS: Among the three-column classification, the QLP fractures are commonly observed in type B and C. It is important to carefully identify these fractures during the diagnostic process. Therefore, based on the three-column classification, we have amalgamated quadrilateral plate fractures and formulated a classification program for acetabular fractures.

Chitosan-initiated gold nanoparticles with enhanced fluorescence for unique Fe3+/PPi sensing and photothermal therapy.

The design of surface ligands is crucial for ligand-protected gold nanoparticles (AuNPs). Herein, following the principle of green synthesis, environmentally friendly gold nanoparticles (AuNPs@His@CC, AuHC) were fabricated based on dual ligands of histidine and carboxylated chitosan. AuHC showed the advantages of low toxicity, good photoluminescent stability and ideal biocompatibility. Compared with single histidine-coated gold nanoclusters (AuNCs@His, AuH), AuHC presented enhanced fluorescence attributed to the addition of chitosan. The blue-emitting AuHC has a unique response to Fe3+ with detection limits as low as 9.51 nM. Interestingly, the quenched fluorescence of AuHC-Fe3+ system could be restored through the introduction of PPi with a detection limit of 10.6 µM. So an "on-off-on" fluorescence sensing platform was achieved. Apart from good optical properties and sensing, the designed AuHC demonstrated outstanding photothermal conversion efficiency (27.8 %), which made it ideal material for thermal ablation of tumor. To be specific, after laser irradiation (660 nm, 0.78 W cm-2, 10 min) of AuHC, the survival rate of HeLa cells as a tumor cell model decreased to 12.7 %, indicating that AuHC has a significant tumor inhibition effect in vitro. Besides, AuHC also could be a befitting candidate for overcoming drug-resistant tumor cells such as MCF-7/ADR cells. Notably, AuHC can markedly ablate solid tumors in 4T1 tumor-bearing mice after laser irradiation (660 nm, 0.78 W cm-2, 10 min). Hence this work provides insight into the design of multifunctional AuNPs platform for simultaneously integrating the ion sensing and photothermal therapy of cancer.

Study of PARP inhibitors for breast cancer based on enhanced multiple kernel function SVR with PSO.

PARP1 is one of six enzymes required for the highly error-prone DNA repair pathway microhomology-mediated end joining (MMEJ) and needs to be inhibited when over-expressed. In order to study the PARP1 inhibitory effect of fused tetracyclic or pentacyclic dihydrodiazepinoindolone derivatives (FTPDDs) by quantitative structure-activity relationship technique, six models were established by four kinds of methods, heuristic method, gene expression programming, random forester, and support vector regression with single, double, and triple kernel function respectively. The single, double, and triple kernel functions were RBF kernel function, the integration of RBF and polynomial kernel functions, and the integration of RBF, polynomial, and linear kernel functions respectively. The problem of multi-parameter optimization introduced in the support vector regression model was solved by the particle swarm optimization algorithm. Among the models, the model established by support vector regression with triple kernel function, in which the optimal R 2 and RMSE of training set and test set were 0.9353, 0.9348 and 0.0157, 0.0288, and R2 cv of training set and test set were 0.9090 and 0.8971, shows the strongest prediction ability and robustness. The method of support vector regression with triple kernel function is a great promotion in the field of quantitative structure-activity relationship, which will contribute a lot to designing and screening new drug molecules. The information contained in the model can provide important factors that guide drug design. Based on these factors, six new FTPDDs have been designed. Using molecular docking experiments to determine the properties of new derivatives, the new drug was ultimately successfully designed.

Immediate mobilization after repair of Achilles tendon rupture may increase the incidence of re-rupture: a systematic review and meta-analysis of randomized controlled trials.

BACKGROUND: Achilles tendon rupture (ATR) is a significant injury that can require surgery and can have the risk of re-rupture even after successful treatment. Consequently, to minimize this risk, it is important to have a thorough understanding of the rehabilitation protocol and the impact of different rehabilitation approaches on preventing re-rupture. MATERIALS AND METHODS: Two independent team members searched several databases (PubMed, EMBASE, Web of Science, Cochrane Library, and CINAHL) to identify randomized controlled trials (RCTs) on operative treatment of ATR. We included articles that covered open or minimally invasive surgery for ATR, with a detailed rehabilitation protocol and reports of re-rupture. The study protocol has been registered at PROSPERO and has been reported in the line with PRISMA Guidelines, Supplemental Digital Content 1, http://links.lww.com/JS9/C85 , Supplemental Digital Content 2, http://links.lww.com/JS9/C86 and assessed using AMSTAR Tool, Supplemental Digital Content 3, http://links.lww.com/JS9/C87 . RESULTS: A total of 43 RCTs were eligible for the meta-analysis, encompassing a combined cohort of 2553 patients. Overall, the postoperative incidence of ATR patients developing re-rupture was 3.15% (95% CI: 2.26-4.17; I2 =44.48%). Early immobilization group patients who had ATR had a 4.07% (95% CI: 1.76-7.27; I2 =51.20%) postoperative incidence of re-rupture; Early immobilization + active range of motion (AROM) group had an incidence of 5.95% (95% CI: 2.91-9.99; I2 =0.00%); Early immobilization + weight-bearing group had an incidence of 3.49% (95% CI: 1.96-5.43; I2 =20.06%); Early weight-bearing + AROM group had an incidence of 3.61% (95% CI: 1.00-7.73; I2 =64.60%); Accelerated rehabilitation (immobilization) group had an incidence of 2.18% (95% CI: 1.11-3.59; I2 =21.56%); Accelerated rehabilitation (non-immobilization) group had a rate of 1.36% (95% CI: 0.12-3.90; I2 =0.00%). Additionally, patients in the immediate AROM group had a postoperative re-rupture incidence of 3.92% (95% CI: 1.76-6.89; I2 =33.24%); Non-immediate AROM group had an incidence of 2.45% (95% CI: 1.25-4.03; I2 =22.09%). CONCLUSIONS: This meta-analysis suggests the use of accelerated rehabilitation intervention in early postoperative rehabilitation of the Achilles tendon. However, for early ankle joint mobilization, it is recommended to apply after one to two weeks of immobilization.

ColorNetVis: An Interactive Color Network Analysis System for Exploring the Color Composition of Traditional Chinese Painting.

In the field of digital humanities, color research aims to discover explanations for painting history and color usage habits. However, researchers analyzing color relationships is challenging and time-consuming, as it requires color extraction and a detailed review of many painting images for reference and comparison of color relationships. In our work, we propose ColorNetVis, an interactive color network analysis tool that enables researchers to explore color relationships through color networks. The core of ColorNetVis is a bipartite network model that establishes a bipartite relationship between colors and Chinese painting within a scope based on color difference measurement. It constructs a one-mode color network through projection algorithms and similarity calculation methods to discover the relationship between colors. We propose a coordinated set of views to demonstrate the combination of determined color networks with painting types and real-world attributes. We use color space view, color attribute distribution view, and single color query components to assist researchers in conducting detailed color analysis and validation. Through case studies, researcher reviews, and user studies, we demonstrate that ColorNetVis can effectively help researchers discover knowledge of color relationships and potential color research directions.