Sulfidation of Nanoscale Zero-Valent Iron by Sulfide: The Dynamic Process, Mechanism, and Role of Ferrous Iron.

Sulfidation of nanoscale zerovalent iron (nZVI) can enhance particle performance. However, the underlying mechanisms of nZVI sulfidation are poorly known. We studied the effects of Fe2+ on 24-h dynamics of nZVI sulfidation by HS- using a dosed S to Fe molar ratio of 0.2. This shows that in the absence of Fe2+, HS- rapidly adsorbed onto nZVI particles and reacted with surface iron oxide to form mackinawite and greigite (<0.5 h). As nZVI corrosion progressed, amorphous FeSx in solution deposited on nZVI, forming S-nZVI (0.5-24 h). However, in the initial presence of Fe2+, the rapid reaction between HS- and Fe2+ produced amorphous FeSx, which deposited on the nZVI and corroded the surface iron oxide layer (<0.25 h). This was followed by redeposition of colloidal iron (hydr)oxide on the particle surface (0.25-8 h) and deposition of residual FeSx (8-24 h) on S-nZVI. S loading on S-nZVI was 1 order of magnitude higher when Fe2+ was present. Surface characterization of the sulfidated particles by TEM-SAED, XPS, and XAFS verified the solution dynamics and demonstrated that S2- and S22-/Sn2- were the principal reduced S species on S-nZVI. This study provides a methodology to tune sulfur loading and S speciation on S-nZVI to suit remediation needs.

Simulation-Directed Construction of Bamboo-Forest-Like Heat Conduction Networks to Enhance Silicon Rubber Composites' Heat Conduction Properties.

Highly vertically thermally conductive silicon rubber (SiR) composites are widely used as thermal interface materials (TIMs) for chip cooling. Herein, inspired by water transport and transpiration of Moso bamboo-forests extensively existing in south China, and guided by filler self-assembly simulation, bamboo-forest-like heat conduction networks, with bamboo-stems-like vertically aligned polydopamine-coated carbon fibers (VA-PCFs), and bamboo-leaves-like horizontally layered Al2O3(HL-Al2O3), are rationally designed and constructed. VA-PCF/HL-Al2O3/SiR composites demonstrated enhanced heat conduction properties, and their through-plane thermal conductivity and thermal diffusivity reached 6.47 W (mK)-1 and 3.98 mm2 s-1 at 12 vol% PCF and 4 vol% Al2O3 loadings, which are 32% and 38% higher than those of VA-PCF (12 vol%) /SiR composites, respectively. The heat conduction enhancement mechanisms of VA-PCF/HL-Al2O3 networks on their SiR composites are revealed by multiscale simulation: HL-Al2O3 bridges the separate VA-PCF heat flow channels, and transfers more heat to the matrix, thereby increasing the vertical heat flux in composites. Along with high volume resistivity, low compression modulus, and coefficient of thermal expansion, VA-PCF/HL-Al2O3/SiR composites demonstrate great application potential as TIMs, which is proven using multiphysics simulation. This work not only makes a meaningful attempt at simulation-driven biomimetic material structure design but also provides inspiration for the preparation of TIMs.

Structurally diverse design and synthesis of novel 2-phenylindole amide derivatives with anti-canine breast cancer activity.

Breast cancer stands as the cancer with the highest incidence and mortality rates among women globally, in which triple-negative breast cancer has been ranked as the most difficult one. Bazedoxifene (BZA), a third-generation selective estrogen receptor modulator (SERM), has been exhibited notable inhibitory effect on both hormone-dependent breast cancer cells and triple-negative breast cancer cells, but showing very low in vivo effeacy. In order to obtain more effective antitumor derivatives than BZA, we have employed a structurally diverse design and synthesis of 57 novel 2-phenylindole amides for detecting their cytotoxities against triple-negative mammary cancer cell line, CMT-7364. Among them, 21 compounds demonstrated significant inhibitory activity against CMT-7364 cells (IC50 < 20 µM). Notably, compound 49 stood out, displaying both similar tumor cell inhibition (20 % reduce in IC50 value) and higher selectivity (4.6 times higher in SI value), compared to Bazedoxifene. Additionally, compound 49 exhibited desirable antitumor effects in a CMT-7364 cell-derived mouse in vivo model, achieving the best inhibition rate of 43.1 % and establishing strong molecular bonding with GP130. Our findings are also supported by comprehensive SAR and 3D-QSAR analyses. Furthermore, the best potent compound 49 was determined to block the cell cycle of canine breast cancer cells in the G0G1 phase in a time-dependent manner, by inducing apoptosis and autophagy. In conclusion, this work presents a valuable lead compound as a potential GP130 inhibitor against triple-negative breast cancer cell lines, laying the foundation for further antitumor drug development.

RBNE-CMI: An Efficient Method for Predicting circRNA-miRNA Interactions via Multiattribute Incomplete Heterogeneous Network Embedding.

Circular RNA (circRNA)-microRNA (miRNA) interaction (CMI) plays crucial roles in cellular regulation, offering promising perspectives for disease diagnosis and therapy. Therefore, it is necessary to employ computational methods for the rapid and cost-effective prediction of potential circRNA-miRNA interactions. However, the existing methods are limited by incomplete data; therefore, it is difficult to model molecules with different attributes on a large scale, which greatly hinders the efficiency and performance of prediction. In this study, we propose an effective method for predicting circRNA-miRNA interactions, called RBNE-CMI, and introduce a framework that can embed incomplete multiattribute CMI heterogeneous networks. By combining the proposed method, we integrate different data sets in the CMI prediction field into one incomplete network for modeling, achieving superior performance in 5-fold cross-validation. Moreover, in the prediction task based on complete data, the proposed method still achieves better performance than the known model. In addition, in the case study, we successfully predicted 18 of the 20 potential cancer biomarkers. The data and source code can be found at https://github.com/1axin/RBNE-CMI.

3D Printing-Induced Hierarchically Aligned Nanocomposites With Exceptional Multidirectional Strain Sensing Performance.

High-performance sensors capable of detecting multidirectional strains are indispensable to understand the complex motions involved in flexible electronics. Conventional isotropic strain sensors can only measure uniaxial deformations or single stimuli, hindering their practical application fields. The answer to such challenge resides in the construction of engineered anisotropic sensing structures. Herein, a hierarchically aligned carbon nanofiber (CNF)/polydimethylsiloxane nanocomposite strain sensor is developed by one-step 3D printing. The precisely controlled printing path and shear flow bring about highly aligned nanocomposite filaments at macroscale and orientated CNF network within each filament at microscale. The periodically orientated nanocomposite filaments along with the inner aligned CNF network successfully control the strain distribution and the appearance of microcracks, giving rise to anisotropic structural response to external deformations. The synergetic effect of the multiscale structural design leads to distinguishable gauge factors of 164 and 0.5 for applied loadings along and transverse to the alignment direction, leading to an exceptional selectivity of 3.77. The real-world applications of the hierarchically aligned sensors in multiaxial movement detector and posture-correction device are further demonstrated. The above findings propose new ideas for manufacturing nanocomposites with engineered anisotropic structure and properties, verifying promising applications in emerging wearable electronics and soft robotics.

Whether the potential degree of cervical instability and cervical muscle degeneration in patients with cervical spondylosis radicular affect the efficacy of cervical traction.

To explore whether the potential instability of the cervical spine and cervical muscle degeneration in patients with cervical spondylotic radiculopathy (CSR) affect the efficacy of cervical traction, and whether cervical traction can aggravate the potential instability of the cervical spine. We divided the 113 recruited CRS patients into three groups based on the differences in horizontal displacement and abnormal angle, and measured the degree of cervical muscle degeneration in the patients through MRI. Considering functional scores, VAS, NDI and PCS scores of the three groups post-treatment were significantly improved. Through the intergroup analysis, we found that the improvement in functional scores in the mild and moderate instability trend groups was better than that in the severe group. Through MRI measurements, we found that the degree of cervical muscle degeneration was significantly increased in the severe instability trend group. Regarding the changes in X-Ray imaging parameters pre- and post-treatment, no significant differences were observed pre- and post-treatment. For patients with CSR, the more serious their predisposition for cervical instability was, the more severe the degree of cervical muscle degeneration was, which means the worse the curative effect was, but cervical traction did not aggravate the potential degree of cervical instability.

Patenting perspective of modulators of ClpP endopeptidase: 2019-present.

INTRODUCTION: ClpP is a highly conserved serine protease that plays a crucial role in maintaining protein homeostasis in both bacterial cells and human mitochondria. Several studies have demonstrated the potential of ClpP as a drug target, with ClpP modulators, including both inhibitors and activators, showing promise in treating a range of conditions such as drug-resistant bacteria, malignant cancers, and fatty liver disease. AREA COVERED: This review provides an overview of patents related to ClpP modulators filed over the last five years, detailing their claims and therapeutic applications. The sources of patent information included databases of the European Patent Office, the China Patent Office and the U.S.A. patent Office, while relevant research articles were accessed through PubMed. EXPERT OPINION: The number of patents concerning ClpP modulators is on the rise, reflecting advancements in related research. By summarizing and outlining relevant patents, we aim to stimulate further interest among researchers, ultimately leading to the development of effective drugs based on ClpP modulators. The broad spectrum of diseases associated with ClpP dysfunction underscores the potential for ClpP modulators to address a wide range of therapeutic needs.

Cs2CO3 Promoted [4 + 2] Cycloaddition of 1,6-Enynes: An Approach to Tetrahydro-1H-benzo-f-isoindole Isomers.

A Cs2CO3-promoted [4 + 2] cycloaddition of 1,6-enynes under mild reaction conditions has been developed. This protocol provides a facile approach to a series of tetrahydro-1H-benzo[f]isoindole isomerized products promoted by Cs2CO3 with moderate to high yields. By simply switching the reaction solvent and controlling the reaction time, two isomerization products could be obtained, both with good selectivity.

The Cytoprotective Effect of C60 Derivatives in the Self-Microemulsifying Drug Delivery System against Triptolide-Induced Cytotoxicity In Vitro.

OBJECTIVE: The aim of this study was to optimize the formulation of a C60-modified self-microemulsifying drug delivery system loaded with triptolide (C60-SMEDDS/TP) and evaluate the cytoprotective effect of the C60-SMEDDS/TP on normal human cells. RESULTS: The C60-SMEDDS/TP exhibited rapid emulsification, an optimal particle size distribution of 50 ± 0.19 nm (PDI 0.211 ± 0.049), and a near-neutral zeta potential of -1.60 mV. The release kinetics of TP from the C60-SMEDDS/TP exhibited a sustained release profile and followed pseudo-first-order release kinetics. Cellular proliferation and apoptosis analysis indicated that the C60-SMEDDS/TP (with a mass ratio of TP: DSPE-PEG-C60 = 1:10) exhibited lower toxicity towards L02 and GES-1 cells. This was demonstrated by a higher IC50 (40.88 nM on L02 cells and 17.22 nM on GES-1 cells) compared to free TP (21.3 nM and 11.1 nM), and a lower apoptosis rate (20.8% on L02 cells and 26.3% on GES-1 cells, respectively) compared to free TP (50.5% and 47.0%) at a concentration of 50 nM. In comparison to the free TP group, L02 cells and GES-1 cells exposed to the C60-SMEDDS/TP exhibited a significant decrease in intracellular ROS and an increase in mitochondrial membrane potential (ΔψM). On the other hand, the C60-SMEDDS/TP demonstrated a similar inhibitory effect on BEL-7402 cells (IC50 = 28.9 nM) and HepG2 cells (IC50 = 107.6 nM), comparable to that of the free TP (27.2 nM and 90.4 nM). The C60-SMEDDS/TP group also exhibited a similar intracellular level of ROS and mitochondrial membrane potential compared to the SMEDDS/TP and free TP groups. METHOD: Fullerenol-Grafted Distearoyl Phosphatidylethanolamine-Polyethylene Glycol (DSPE-PEG-C60) was synthesized and applied in the self-microemulsifying drug delivery system. The C60-SMEDDS/TP was formulated using Cremophor EL, medium-chain triglycerides (MCT), PEG-400, and DSPE-PEG-C60, and loaded with triptolide (TP). The toxicity and bioactivity of the C60-SMEDDS/TP were assessed using normal human liver cell lines (L02 cells), normal human gastric mucosal epithelial cell lines (GES-1 cells), and liver cancer cell lines (BEL-7402 cells and HepG2 cells). The production of reactive oxygen species (ROS) after the C60-SMEDDS/TP treatment was assessed using 2',7'-dichlorofluorescein diacetate (DCFDA) staining. The alterations in mitochondrial membrane potential (ΔψM) were assessed by measuring JC-1 fluorescence. CONCLUSIONS: The cytoprotection provided by the C60-SMEDDS/TP favored normal cells (L02 and GES-1) over tumor cells (BEL-7402 and HepG2 cells) in vitro. This suggests a promising approach for the safe and effective treatment of TP.

Artificial intelligence for geoscience: Progress, challenges, and perspectives.

This paper explores the evolution of geoscientific inquiry, tracing the progression from traditional physics-based models to modern data-driven approaches facilitated by significant advancements in artificial intelligence (AI) and data collection techniques. Traditional models, which are grounded in physical and numerical frameworks, provide robust explanations by explicitly reconstructing underlying physical processes. However, their limitations in comprehensively capturing Earth's complexities and uncertainties pose challenges in optimization and real-world applicability. In contrast, contemporary data-driven models, particularly those utilizing machine learning (ML) and deep learning (DL), leverage extensive geoscience data to glean insights without requiring exhaustive theoretical knowledge. ML techniques have shown promise in addressing Earth science-related questions. Nevertheless, challenges such as data scarcity, computational demands, data privacy concerns, and the "black-box" nature of AI models hinder their seamless integration into geoscience. The integration of physics-based and data-driven methodologies into hybrid models presents an alternative paradigm. These models, which incorporate domain knowledge to guide AI methodologies, demonstrate enhanced efficiency and performance with reduced training data requirements. This review provides a comprehensive overview of geoscientific research paradigms, emphasizing untapped opportunities at the intersection of advanced AI techniques and geoscience. It examines major methodologies, showcases advances in large-scale models, and discusses the challenges and prospects that will shape the future landscape of AI in geoscience. The paper outlines a dynamic field ripe with possibilities, poised to unlock new understandings of Earth's complexities and further advance geoscience exploration.

Revealing the origin of dendritic deposition regulated solid electrolyte interphase enabled by cation receptor in Zn-ion batteries.

Aqueous Zn-metal batteries open up promising prospects for large-scale energy storage due to the advantages of ample components, cost-effectiveness, and safety features. However, the notorious dendritic development and unavoidable hydrogen evolution reaction of Zn have grown to be one of the main barriers inhibiting its further commercialization. Despite substantial studies, the mechanism of nucleation and deposition of Zn2+ ions on zinc layer surfaces remains elusive. Here, inspired by additive, the SnCl2 additive is introduced to initiate the in-situ formation of the ZnS-rich solid electrolyte interphase (SEI) layer on the Zn anode, which creates a protective "shielding effect" that hinders direct contact between water and the zinc surface, suppressing the random growth of Zn dendrites in the whole process. The mechanism of Zn nucleation was revealed by employing high-resolution transmission electron microscopy, consecutive electron diffraction coupled with finite element method (FEM) simulations. Moreover, spontaneously formed 3D architecture consists of micorsized hemispherical Sn particles not only suppresses the Zn dendrite growth by reducing the local current density, but also enables the lateral growth of Zn crystals by increasing the average surface energy. Such an electrolyte enables a long cycle life of over 2000 h in the Zn||Zn cell. Importantly, the assembled Zn||MnVO full cells with SnCl2 electrolyte also delivers substantial capacity (171.1mA h g-1 at 1 A h g-1), presenting a promising application. These discoveries not only deepen the comprehension of fundamental scientific knowledge regarding the microscopic reaction mechanism of the Zn anode but also offer significant insights for optimizing performance.

FOXF1 inhibits invasion and metastasis of lung adenocarcinoma cells and enhances anti-tumor immunity via MFAP4/FAK signal axis.

Based on the joint analysis of multi-omic data and the biological experiments, we demonstrate that FOXF1 inhibits invasion and metastasis of lung adenocarcinoma cells and enhances anti-tumor immunity via regulating MFAP4/FAK signal axis in this study. The levels of FOXF1 and MFAP4 are significantly down-regulated in LUAD, and the increased levels of two genes can improve the clinical prognosis of LUAD patients. Fluorescein reporter gene determination, chromatin immunoprecipitation and gene co-expression analysis indicate that MFAP4 level is positively regulated by transcription factor FOXF1. The function enrichment analysis shows that the levels of FOXF1 and MFAP4 are closely associated with an enrichment of tumor metastasis signatures. FOXF1 can inhibit the migration and invasion of LAUD cells by transcriptionally activating MFAP4 expression. And the overexpression of FOXF1/MFAP4 can reduce focal adhesion kinase (FAK) phosphorylation, while their knockdown result in the opposite effects. The increased levels of FOXF1/MFAP4 enhance the antitumor immunity by increasing the infiltration of dendritic cells and CD4+ T cells, and the interactions between LUAD cells and immune cells, and activating multiple anti-tumor immunity-related pathways. In conclusion, our study reveals the potential function of FOXF1/MFAP4/FAK signal axis in inhibiting metastasis of LUAD cells and modulating anti-tumor immunity of LUAD patients.

Concave Grain Boundaries Stabilized by Boron Segregation for Efficient and Durable Oxygen Reduction.

The oxygen reduction reaction (ORR) is a critical process that limits the efficiency of fuel cells and metal-air batteries due to its slow kinetics, even when catalyzed by platinum (Pt). To reduce Pt usage, enhancing both the specific activity and electrochemically active surface area (ECSA) of Pt catalysts is essential. Here, ultrafine, grain boundary (GB)-rich Pt nanoparticle assemblies are proposed as efficient ORR catalysts. These nanowires offer a large ECSA and a high density of concave GB sites, which improve specific activity. Atoms at these GB sites exhibit increased coordination and lattice distortion, leading to a favorable reduction in oxygen binding energy and enhanced ORR performance. Furthermore, boron segregation stabilizes these GBs, preserving active sites during catalysis. The resulting boron-stabilized Pt nanoassemblies demonstrate ORR specific and mass activities of 9.18 mA cm-2 and 6.40 A mg-1 Pt (at 0.9 V vs. RHE), surpassing commercial Pt/C catalysts by over 35-fold, with minimal degradation after 60 000 potential cycles. This approach offers a versatile platform for optimizing the catalytic performance of a wide range of nanoparticle systems.

Dominant Contribution of Non-dust Primary Emissions and Secondary Processes to Dissolved Aerosol Iron.

Solubility largely determines the impacts of aerosol Fe on marine ecosystems and human health. Currently, modeling studies have large uncertainties in aerosol Fe solubility due to inadequate understanding of the sources of dissolved Fe. This work investigated seasonal variations of Fe solubility in coarse and fine aerosols in Qingdao, a coastal city in the Northwest Pacific, and utilized a receptor model for source apportionment of total and dissolved aerosol Fe. Desert dust was found to be the main source of total Fe, contributing 65 and 81% annually to total Fe in coarse and fine particles, respectively; in contrast, dissolved aerosol Fe originated primarily from combustion, industrial, and secondary sources. The annual average contributions to dissolved Fe in coarse and fine particles were 68 and 47% for the secondary source and 32 and 33% for the combustion source, respectively. Aerosol Fe solubility was found to be highest in summer and lowest in spring, showing seasonal patterns similar to those of aerosol acidity. Increase in Fe solubility in atmospheric particles, when compared to desert dust, was mainly caused by secondary processing and combustion emission, and the effect of secondary processes was dictated by aerosol acidity and liquid water content.

Group-member selection for RSVP-based collaborative brain-computer interfaces.

Objective: The brain-computer interface (BCI) systems based on rapid serial visual presentation (RSVP) have been widely utilized for the detection of target and non-target images. Collaborative brain-computer interface (cBCI) effectively fuses electroencephalogram (EEG) data from multiple users to overcome the limitations of low single-user performance in single-trial event-related potential (ERP) detection in RSVP-based BCI systems. In a multi-user cBCI system, a superior group mode may lead to better collaborative performance and lower system cost. However, the key factors that enhance the collaboration capabilities of multiple users and how to further use these factors to optimize group mode remain unclear. Approach: This study proposed a group-member selection strategy to optimize the group mode and improve the system performance for RSVP-based cBCI. In contrast to the conventional grouping of collaborators at random, the group-member selection strategy enabled pairing each user with a better collaborator and allowed tasks to be done with fewer collaborators. Initially, we introduced the maximum individual capability and maximum collaborative capability (MIMC) to select optimal pairs, improving the system classification performance. The sequential forward floating selection (SFFS) combined with MIMC then selected a sub-group, aiming to reduce the hardware and labor expenses in the cBCI system. Moreover, the hierarchical discriminant component analysis (HDCA) was used as a classifier for within-session conditions, and the Euclidean space data alignment (EA) was used to overcome the problem of inter-trial variability for cross-session analysis. Main results: In this paper, we verified the effectiveness of the proposed group-member selection strategy on a public RSVP-based cBCI dataset. For the two-user matching task, the proposed MIMC had a significantly higher AUC and TPR and lower FPR than the common random grouping mode and the potential group-member selection method. Moreover, the SFFS with MIMC enabled a trade-off between maintaining performance and reducing the number of system users. Significance: The results showed that our proposed MIMC effectively optimized the group mode, enhanced the classification performance in the two-user matching task, and could reduce the redundant information by selecting the sub-group in the RSVP-based multi-user cBCI systems.

Application of Machine Learning in Nanotoxicology: A Critical Review and Perspective.

The massive production and application of nanomaterials (NMs) have raised concerns about the potential adverse effects of NMs on human health and the environment. Evaluating the adverse effects of NMs by laboratory methods is expensive, time-consuming, and often fails to keep pace with the invention of new materials. Therefore, in silico methods that utilize machine learning techniques to predict the toxicity potentials of NMs are a promising alternative approach if regulatory confidence in them can be enhanced. Previous reviews and regulatory OECD guidance documents have discussed in detail how to build an in silico predictive model for NMs. Nevertheless, there is still room for improvement in addressing the ways to enhance the model representativeness and performance from different angles, such as data set curation, descriptor selection, task type (classification/regression), algorithm choice, and model evaluation (internal and external validation, applicability domain, and mechanistic interpretation, which is key to ensuring stakeholder confidence). This review explores how to build better predictive models; the current state of the art is analyzed via a statistical evaluation of literature, while the challenges faced and future perspectives are summarized. Moreover, a recommended workflow and best practices are provided to help in developing more predictive, reliable, and interpretable models that can assist risk assessment as well as safe-by-design development of NMs.

Optimal operation of energy-intensive load considering electricity carbon market.

Energy-intensive load benefits from low electricity tariff and carbon emission, since they occupy certain amounts in the total cost of the product. This paper considers energy-intensive load participation in the electricity as well as carbon trading to reduce the cost. Firstly, an electricity-carbon model is established based on the correlation value method to calculate the carbon emissions of energy-intensive load based on their electricity consumption to realize the carbon amount. Afterwards, the baseline method is used to allocate free carbon emission quotas to energy-intensive load and a reward-penalty carbon trading price mechanism considering offset is proposed. Next, the objective function to achieve maximum benefits, and to reduce output fluctuation, and to improve new energy accommodation is proposed. The case studies show that, by comparing multi-objective function optimization, the optimization target proposed in this paper can effectively reduce wind power output fluctuations and improve wind power accommodation. Through the total participation in carbon trading and electricity market income, multi-objective optimization can increase the system income while ensuring that energy-intensive load meets production requirements under the premise of reducing carbon emissions, verifying the effectiveness of the low-carbon optimal operation model proposed in this paper.

Deterministic grayscale nanotopography to engineer mobilities in strained MoS2 FETs.

Field-effect transistors (FETs) based on two-dimensional materials (2DMs) with atomically thin channels have emerged as a promising platform for beyond-silicon electronics. However, low carrier mobility in 2DM transistors driven by phonon scattering remains a critical challenge. To address this issue, we propose the controlled introduction of localized tensile strain as an effective means to inhibit electron-phonon scattering in 2DM. Strain is achieved by conformally adhering the 2DM via van der Waals forces to a dielectric layer previously nanoengineered with a gray-tone topography. Our results show that monolayer MoS2 FETs under tensile strain achieve an 8-fold increase in on-state current, reaching mobilities of 185 cm²/Vs at room temperature, in good agreement with theoretical calculations. The present work on nanotopographic grayscale surface engineering and the use of high-quality dielectric materials has the potential to find application in the nanofabrication of photonic and nanoelectronic devices.

Identifying and exploring the favorable factors that help to slow the progression of disease in patients with mild cervical spondylotic myelopathy.

To explore the favorable factors that help slow the progression of disease in patients with mild Cervical Spondylotic Myelopathy (CSM). A retrospective analysis was conducted, involving the enrollment of 115 CSM patients. The categorization of patients into two groups was based on the duration of symptoms, assessments using the mJOA scale and Health Transition (HT) scores: mild-slow group and severe-rapid group. We found that the patients in both groups had similar degrees of spinal cord compression, but mild-slow group were older and had smaller C2-C7 cobb angle (Flexion) (CL(F)), C2-C7 cobb angle (Range of motion) (CL(ROM)), Transverse area (TA), Normal-TA, Compressive spinal canal area (CSCA), Normal-Spinal canal area (Normal-SCA) and lower Spinal cord increased signal intensity (ISI) Grade than the severe-rapid group. A binary logistic regression analysis showed that CL(ROM) and Normal-TA are favorable factors to help slow the progression of disease patients with mild CSM. Through ROC curves, we found that when CL(ROM) < 39.1° and Normal-TA < 80.5mm2, the progression of disease in CSM patients may be slower. Meanwhile, we obtained a prediction formula by introducing joint prediction factor: L = CL(ROM) + 2.175 * Normal-TA. And found that when L < 213.0, the disease progression of patients may be slower which was superior to calculate CL(ROM) and Normal-TA separately.

Progression Patterns and Risk Factors of Axial Elongation in Young Adults With Nonpathologic High Myopia: Three-Year Large Longitudinal Cohort Follow-Up.

PURPOSE: To investigate the progression patterns and risk factors of axial elongation in young adults with nonpathologic high myopia. DESIGN: Prospective, clinical observational cohort study with 2- to 4-year follow-up. METHODS: A total of 1043 eyes of 563 participants (3515 medical records) aged 18 to 50 years with nonpathologic high myopia (axial length [AL] ≥ 26 mm; myopic maculopathy < diffuse chorioretinal atrophy; without posterior staphyloma) were included from 1546 participants (6318 medical records). Annual axial elongation was calculated via linear mixed-effect models. The associated risk factors of axial elongation were determined by ordinal logistic regression analysis, with generalized estimate equations for eliminating an interocular correlation bias. RESULTS: Based on 5359 times of AL measurements, the annual axial elongation of participants (mean [SD] age 31.39 [9.22] years) was 0.03 mm/year (95% confidence interval [CI], 0.03-0.04; P < .001) during a 30.23 (6.06) months' follow-up. Severe (>0.1 mm/year), moderate (0.05-0.09 mm/year), mild (0-0.049 mm/year), and nil (≤0 mm/year) elongation was observed in 122 (11.7%), 211 (20.2%), 417 (40.0%), and 293 (28.1%) eyes. The following risk factors were significantly associated with axial elongation: baseline AL ≥ 28 mm (odds ratio [OR], 4.23; 95% CI, 2.95-6.06; P < .001); age < 40 years (OR, 1.64; 95% CI, 1.18-2.28; P = .003); axial asymmetry (OR, 2.04; 95% CI, 1.26-3.29; P = .003), and women (OR, 1.52; 95% CI, 1.13-2.2.05; P = .006). Using antiglaucoma medications was a protective factor (OR, 0.46; 95% CI, 0.27-0.79; P = .005), which slowed 75% of axial elongation from 0.04 (0.06) to 0.01 (0.06) mm/y (P < .001). CONCLUSIONS: Axial elongation continued in young adults with nonpathologic myopia. Risk factors included longer baseline AL and axial asymmetry, younger age, and woman. Topical use of antiglaucoma medications may be useful to reduce ongoing axial elongation.