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Objectives This study aimed to evaluate the black line sign (BLS) on preoperative MR–STIR images as a predictor of progressive kyphosis (PK) following percutaneous kyphoplasty (PKP) for osteoporotic vertebral compression fractures (OVCFs). The goal of this study was to assess its significance in identifying patients at greater risk for postoperative kyphotic deformities and to refine clinical management strategies. Methods This single-center retrospective study analyzed 182 patients with OVCFs who underwent PKP between January 2019 and December 2022. Patients were categorized into two groups based on the presence or absence of BLS on preoperative MRI: the BLS group and the non-black line sign (NBLS) group. Radiological and clinical outcomes were compared between these two groups. Both univariate and multivariate analyses were performed to identify risk factors associated with the development of PK. Results At the 1-year follow-up, the BLS group presented significantly greater vertebral height loss and kyphotic angle differences than did the NBLS group. Furthermore, the visual analog scale and Oswestry Disability Index scores were notably higher in the BLS group ( P  < 0.001). The incidence of PK in the BLS group was 75.0% (39/52), which was significantly greater than the 16.2% (21/130) observed in the NBLS group ( P  < 0.001). Cumulative event analysis revealed that a greater proportion of patients in the BLS group developed PK over the follow-up period. Both the log-rank test and Cox regression analysis demonstrated statistically significant differences ( P  < 0.001). Multivariate regression analysis revealed that BLS was a significant independent risk factor for PK, with an odds ratio of 9.827 ( P  < 0.001). Conclusions The black line sign on preoperative MR–STIR images is a significant predictor of PK after PKP for OVCFs. Clinicians should consider closer monitoring, external bracing, and aggressive osteoporosis treatment for patients with BLS to reduce the risk of postoperative kyphotic deformities.

Background and objective Symptomatic lumbar spondylolysis often disables young athletes. We compared three motion-preserving techniques—modified Scott (MST), pedicle screw system (PSS), and dual-stability construct (DSC)—for pars healing and functional recovery. Methods We retrospectively reviewed 103 active adults (18–40 years) with L3/L4/L5 spondylolysis treated at a single centre between 2017 and 2023. Patients were allocated to modified Scott (MST, n  = 33), pedicle-screw (PSS, n  = 27) or dual-stability construct (DSC, n  = 43). All underwent isthmic debridement, autologous grafting and identical rehabilitation. CT (computed tomography) evaluated pars healing; VAS (Visual Analogue Scale) and JOA-L (Japanese Orthopaedic Association) scores, complications and Magnetic resonance imaging (MRI) Pfirrmann grading were recorded. Results At 17.5 ± 6.5 months, DSC achieved the highest healing rate (95.3%) versus PSS (88.9%) and MST (60.6%) ( P  < 0.001). DSC and PSS were independent predictors of healing (Risk ratios (RR) 12.9 and 4.6 vs. MST). JOA improvement was greatest with DSC (80.53%) and PSS (79.89%) versus MST (67.74%). MST exhibited 12% implant failure (spinous cut-through). No adjacent-disc degeneration was observed in PSS or DSC, supporting short-term motion preservation. CT type II/III defects and overweight status predicted non-union. Conclusion PSS and DSC offer significant advantages over MST for treating symptomatic lumbar spondylolysis in young active adults, with DSC yielding the most favorable outcomes. The dual-stability construct, integrating intra- and intersegmental fixation, enhances pars healing and maintains disc health, supporting its use as a motion-preserving and biomechanically robust technique. These findings may guide surgical decision-making and contribute to improved recovery and functional restoration in athletic youth.

Spinal cord injury (SCI) triggers severe neuroinflammation, impeding recovery. While microglial M1 polarization and pyroptosis are key drivers, their upstream regulators are incompletely understood. This study investigated the role of the ubiquitin ligase tripartite motif‐containing protein 14 (TRIM14) in regulating neuroinflammation following SCI. Using rat SCI models and BV2 microglia exposed to lipopolysaccharide (LPS), we assessed TRIM14 expression and its functional impact via knockdown and overexpression, alongside pharmacological neurofilament (NF)‐κB inhibition (pyrrolidine dithiocarbamate [PDTC]). TRIM14 was upregulated in injured spinal cords and microglia, associated with injury severity. TRIM14 knockdown in microglia stabilized IκBα by inhibiting its ubiquitination, thereby suppressing NF‐κB activation, M1 polarization, and NLRP3‐mediated pyroptosis. Conversely, TRIM14 overexpression exacerbated inflammation, effects markedly reversed by PDTC. In SCI rats, intralesional AAV‐CRISPR/CasRx‐mediated TRIM14 silencing significantly attenuated neuroinflammation and neuronal apoptosis, enhanced axonal regeneration, and improved locomotor function. Mechanistically, TRIM14 knockdown suppressed NF‐κB/NLRP3 signaling, promoting a prorepair microenvironment. These results identify TRIM14 as a critical regulator of microglial activation and pyroptosis post‐SCI, suggesting its therapeutic targeting could be a viable strategy to promote neural repair.

Spondylolisthesis is a spinal disorder characterized by abnormal vertebral displacement, primarily affecting the lumbar region. Understanding the genetic factors underlying its progression is critical. This study aimed to identify key genes influencing spondylolisthesis progression. The summary-data-based Mendelian randomization (SMR) analysis was conducted to evaluate gene expression quantitative trait (eQTL) and DNA methylation QTL (mQTL) data that were causally associated with spondylolisthesis. Subsequently, key genes were discerned by Bayesian colocalization analysis. To validate the findings, Quantitative real time polymerase chain reaction (qRT-PCR) experiments were conducted using human osteosarcoma cells (SW-1353). Additionally, enrichment analysis, small molecule compounds prediction and molecular docking were performed to investigate how the key genes might impact spondylolisthesis. SMR analysis identified 841 cis-eQTLs and 3,224 mQTLs potentially linked to spondylolisthesis (P < 0.05). Bayesian colocalization revealed LOXL4 as a key gene, with posterior probabilities (PPH4) exceeding 0.90 for both eQTL (ENSG00000138131) and mQTL (cg09335911). LOXL4 is implicated in pathways like \"protein oxidation\" and \"collagen-containing extracellular matrix\", which are critical for tissue integrity. Molecular docking suggested that LOXL4 binds strongly to estradiol and progesterone, pointing to a potential mechanism of hormonal regulation in spondylolisthesis. However, this remains a hypothesis requiring further experimental validation. Additionally, qRT-PCR experiments in hydrogen peroxide-treated SW1353cells showed that LOXL4 expression changes were consistent with our bioinformatics predictions, although this in vitro model may not fully reflect the gene's role in spondylolisthesis. This findings suggest LOXL4 as a candidate gene involved in spondylolisthesis progression and a potential therapeutic target. Nevertheless, out results are preliminary and further research is needed to confirm LOXL4's role in this condition.

Although the relationship between Kaposi’s sarcoma (KS) and renal transplant has been well described, there are rare cases of KS concurrent with membranous glomerulonephritis or other glomerular diseases. In this report, a patient with membranous glomerulonephritis that accepted long-term prednisolone and cyclosporine immunosuppressive therapy developed skin KS. Withdrawal of immunosuppressive treatment resulted in the disappearance of KS.

All-aromatic poly(pyridinium salt)s, which can be described as rigid-rod ionene polymers, have been prepared in this laboratory. In this work, it was found that poly(pyridinium salt)s undergo irreversible color and viscosity changes upon exposure to UV radiation in amide solvents. In order to investigate these phenomena, a series of poly(pyridinium salt)s and model compounds was synthesized. The rates at which the viscosity decreased and the color changed depended on the polymer concentration, the polymer substituents and the solvents. Electron-withdrawing substituents and lower polymer concentrations increased the rates, while electron-donating substituents and higher polymer concentrations decreased the rates UV-visible and$\\sp1$ H-NMR studies indicated that the bis(pyridinium salt)s were reduced to cation radicals, which abstracted hydrogen radicals from the solvents to afford dihydropyridine structures. In an attempt to prove that the photoreaction was facilitated by amide groups in the solvents, an amide-containing poly(pyridinium triflate) was synthesized and studied. A reversible color change was observed in films of this polymer. Upon UV irradiation, the yellow films became dark brown, but they changed back to yellow when the irradiation was stopped. This result led us to develop new photoresponsive blends of poly(pyridinium salt)s and amide-containing polymers, i.e. poly(N,N-dimethyl-acrylamide) (p(DMAA)) and poly((N, N-dimethylacrylamide)-co-(2-acryamido-2-methyl-2-propanesulfonic acid)) (p(DMAA-co-HAMPS)), nylon-6 and sulfonated nylon-6. The blends also underwent reversible color changes when exposed to UV irradiation. UV-visible, fluorescence, and ESR studies showed that the color change was associated with the reversible formation of cation radicals. Pendent electron-withdrawing groups on the poly(pyridinium salt) accelerated the color change, while electron-donating groups retarded it.

Transformers, the dominant architecture for natural language processing, have also recently attracted much attention from computational visual media researchers due to their capacity for long-range representation and high performance. Transformers are sequence-to-sequence models, which use a self-attention mechanism rather than the RNN sequential structure. Thus, such models can be trained in parallel and can represent global information. This study comprehensively surveys recent visual transformer works. We categorize them according to task scenario: backbone design, high-level vision, low-level vision and generation, and multimodal learning. Their key ideas are also analyzed. Differing from previous surveys, we mainly focus on visual transformer methods in low-level vision and generation. The latest works on backbone design are also reviewed in detail. For ease of understanding, we precisely describe the main contributions of the latest works in the form of tables. As well as giving quantitative comparisons, we also present image results for low-level vision and generation tasks. Computational costs and source code links for various important works are also given in this survey to assist further development.

Aerosols can invigorate deep convective clouds (DCCs) directly by nucleating more cloud droplets, named as Primary Aerosol Convective Invigoration (PAI). However, the covarying Meteorology‐Aerosol Invigoration (MAI) effect on DCC has been a long‐standing issue in quantifying PAI's contribution. Here, observations show that PAI causes positive feedback from DCC to meteorology, further invigorating DCC through enhanced humidity, updraft and destabilization, thereby adding to MAI. Further, PAI is separated from MAI observationally by quantifying the sensitivity of DCC properties to aerosol changes under fixed meteorology through the artificial neural network. When fine aerosol changes from the cleanest to optimal concentration (5 μg m−3), PAI contributes 72% ± 2% of the total aerosol‐associated cloud top cooling by 12°C, 42% ± 4% of the 30% prolonged lifetime, and 50% ± 4% of the more than doubled rainfall. This result underlines the comparable magnitudes of PAI and MAI, which have not been considered until now in weather and climate prediction. Plain Language Summary Aerosol has been observed and simulated to be directly associated with the development of strong convective storms, termed as Primary Aerosol Convective Invigoration (PAI). However, the current consensus is that meteorology also affects aerosol distribution, that is, there is covariability between meteorology and aerosols, possibly producing an overestimated observed association between aerosols and storms. Disentangling the PAI effect from the covarying meteorology‐aerosol effect on the storms has been a long‐standing challenge. Here, based on an artificial neural network technology, we quantify the PAI effect which explains ∼2/3 of the observed total aerosol‐driven variation in cloud top height, and 40%–50% of lifetime and rainfall when aerosol changes from the cleanest state to ∼5 μg m−3 concentration. Furthermore, we provide the first‐of‐its‐kind observational support for the Meteorology‐Feedback Aerosol Convective Invigoration (FAI). PAI modifies the environment and feeds back to the meteorology, which would become more conducive to storm development. This study demonstrates that fine aerosols have a large impact on the vigor of tropical deep convective clouds, which in turn adjusts environmental properties and meteorology. This is a manifestation of the way by which aerosol modulates tropical convection and, through that, further influences atmospheric circulation. Key Points Total aerosol‐driven convective invigoration can be separated into primary and meteorology‐covarying aerosol effects Primary aerosol invigoration is observed to alter the environment to be more conducive for convection in a positive feedback loop Primary invigoration explains ∼2/3 of the observed total aerosol‐driven variation in cloud top height and 40%–50% of lifetime and rainfall

Bi-defect sites are highly effective for CO 2 reduction (CO 2 RR) to formic acid, yet most catalytic surfaces predominantly feature inert, non-defective Bi sites. To overcome this limitation, herein, tensile strain is introduced on wholescale non-defective Bi sites. Under rapid thermal shock, the Bi-based metal-organic framework (Bi-MOF-TS) shows weakened Bi–O bonds and produced tiny Bi clusters. During electrochemical reduction, these clusters create numerous continuous vacancies, inducing weak tensile strain over a large range of surrounding non-defective Bi sites. This strain enhances *OHCO intermediates adsorption and substantially lowers the reaction barrier. As a result, Bi-MOF-TS achieves a faradaic efficiency above 90% across 800 mV potential range, with an impressive formate partial current density of −995 ± 93 mA cm −2 . Notably, Bi-MOF-TS exhibits a high HCOOH faradaic efficiency of 96 ± 0.64% at 400 mA cm −2 in acidic electrolyte and a high single-pass carbon conversion efficiency (SPCE) of 62.0%. Additionally, a Zn-CO 2 battery with Bi-MOF-TS as the cathode demonstrates a peak power density of 21.4 mW cm −2 and maintains stability over 300 cycles. A large range of inert and non-defective sites in catalysts is a primary factor impeding catalyst activity in acidic CO 2 electroreduction. Here, the authors achieve high HCOOH selectivity and activity in acidic electrolyte by introducing tensile strain to activate inert sites.