Graph‐guided frequency‐enhanced state space network for 3D spine segmentation from MR images

Abstract Background Accurate spinal MRI segmentation is essential for computer‐aided diagnosis of spinal diseases. Existing methods have limitations in global semantic modeling and boundary delineation due to complex anatomy and imaging artifacts. Purpose Our work aimed to propose a novel Graph‐Guided Frequency‐Enhanced State Space Network (GF‐SSNet) method to achieve more accurate 3D multi‐modal spine MRI automatic segmentation, addressing the limitations of existing algorithms in global semantic modeling of high‐dimensional voxel space, cross‐modal information synergistic perception, and fine boundary identification of anatomically similar tissues, thereby providing technical support for intelligent diagnosis and precision medicine of spinal diseases. Methods The proposed network is based on the GF‐SSNet architecture. During encoding, a dual frequency‐spatial feature enhancement mechanism is employed, which adaptively fuses local frequency dynamic features and global spatial long‐range dependencies through Frequency Dynamic Convolution (FDConv) and Three‐Directional Mamba‐based state space model (TD‐Mamba). At the bottleneck, Position‐Aware Attention Fusion (PAAF) and Graph Convolutional Networks (GCN) are integrated to explicitly encode topological anatomical constraints between vertebrae, enhancing the global perception capability of spinal continuity structures. During decoding, a Depth‐aware Progressive Upsampling (DAPU) strategy is introduced to effectively alleviate the reconstruction loss of fine‐grained spatial information. The entire framework achieves end‐to‐end automatic segmentation of multi‐modal MR images. Results On the normal test set, GF‐SSNet outperformed all baselines across all metrics. Specifically, Dice and IoU Means reached 92.04 ± 0.06% and 85.29 ± 0.10%, exceeding the best baseline results of 89.81 ± 0.61% and 81.51 ± 0.91%. HD95 and ASSD were significantly reduced to 3.06 ± 0.46 mm and 0.612 ± 0.018 mm, compared to top‐tier baseline values of 4.76 ± 1.09 mm and 1.14 ± 0.01 mm, respectively. On an independent pathological test set with various spinal pathologies, GF‐SSNet maintained superior performance with Dice Mean of 87.60 ± 0.10%, still outperforming all baseline methods. The 4.4 percentage point performance decline from normal cases primarily stemmed from intervertebral disc segmentation challenges in degenerative conditions, while vertebrae segmentation remained robust. Ablation studies confirmed significant contributions of all proposed components. The proposed HFD‐Tversky loss outperformed conventional losses. All performance differences were statistically significant after correction for multiple comparisons. Conclusion GF‐SSNet demonstrates performance in spinal segmentation through adaptive fusion of frequency features and global dependencies, providing technical support for intelligent spinal disease diagnosis.

Economic Burden of Rheumatoid Arthritis in Low‐ and Middle‐Income Countries: Systematic Review and Meta‐Analysis

Objective The aim of this systematic review was to synthesize the economic impact of rheumatoid arthritis (RA) on households, health systems, and society in low‐ and middle‐income countries (LMICs). Methods Electronic databases such as PubMed, Web of Science, and CINAHL were searched using keywords related to RA and cost of illness. Eligible studies were required to report RA‐related costs, be conducted in LMICs, and be published in English. Quality appraisal of the included studies was conducted using the Newcastle–Ottawa Scale for cohort studies. A narrative synthesis and meta‐analysis of findings was conducted. Results A total of 5,134 studies was initially identified for screening. After removing 1,028 duplicates, 50 studies were selected for full‐text review, and 15 met the eligibility criteria and were therefore included in the review. These studies, published between 2007 and 2024, were conducted in various countries, including Turkey (n = 3), China (n = 2), and one study each from Thailand, Hungary, Mexico, Colombia, Morocco, Pakistan, India, Romania, Brazil, and Argentina. Nine studies adopted a societal perspective, whereas six used a health care perspective. The total sample size was 218,575 participants, with individual study sizes ranged from 62 to 209,292. Average annual direct costs per patient ranged from US$523 to US$2,837.90, and indirect costs ranged from US$81.80 to US$2,463.40. The pooled average annual costs for outpatients, inpatients, and medical costs were US$517.72 (95% confidence interval [CI] $3.35–$1,032.09), US$543.88 (95% CI US$499.51–US$588.24), and US$3,379.83 (95% CI US$3,137.58–US$3,622.08), respectively. Conclusion RA poses a significant economic challenge in LMICs, where limited health care resources and high treatment costs make care unaffordable for many. This review uniquely underscores that enhancing treatment access and optimizing resource use can reduce both medical and productivity losses, improving patient outcomes and strengthening economic resilience.

Racial and Ethnic Disparities in the Incidence and Prevalence of Low Back Pain in the United States: A Systematic Review

Objective This systematic review synthesizes existing evidence to quantify racial and ethnic disparities in low back pain (LBP) incidence and prevalence in the United States across stages of chronicity (acute, subacute, and chronic LBP). Methods Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidelines, we systematically searched MEDLINE, Embase, the Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Web of Science (through January 7, 2025) for studies reporting LBP incidence or prevalence by race and ethnicity in US adults. Risk of bias was assessed using the Risk of Bias in Non‐randomized Studies ‐ of Exposure (ROBINS‐E) tool. Results Of 8,145 citations, 23 studies met inclusion criteria (10 on incidence, 13 on prevalence). Some incidence studies found higher risk of chronic LBP among Black adults compared to White adults, whereas data on Hispanic and Latino adults remain limited. Prevalence studies showed higher rates in White and American Indian and Alaska Native adults, with lower prevalence in Black, Hispanic and Latino, and Asian adults. Military studies consistently reported that Black service members experienced higher LBP incidence compared to other races. No studies examined the subacute state. Conclusion This review highlights persistent race‐based differences in LBP, with critical gaps in research on acute LBP incidence and community‐based prevalence. Future studies should prioritize population‐based research to better capture racial differences in LBP burden and inform targeted interventions.

Introduction to the Special Theme Issue: Pain Science and Therapy in Rheumatic Disease

Computer‐Assisted Dynamic Contrast–Enhanced Magnetic Resonance Imaging Quantification Method for Assessment of Synovial Inflammation in Active Arthritis: Correlation With Synovial and Blood Biomarkers

Objective To investigate the correlation and association between dynamic contrast–enhanced magnetic resonance imaging (DCE‐MRI) quantification (DEMRIQ) parameters with local and systematic markers of inflammation in patients with various etiologies of acute knee arthritis. Methods In a cross‐sectional setting, patients with symptoms of acute knee arthritis underwent DCE‐MRI, and DEMRIQ parameters were acquired. Markers of inflammation were obtained from the blood and synovial fluid through ultrasound‐guided arthrocentesis of the affected joint. Spearman correlation and linear regression were performed to assess the correlation and association between DEMRIQ parameters and markers of inflammation, respectively. Results Forty‐one patients, including 12 with rheumatoid factor–positive rheumatoid arthritis (RF+RA), 6 with rheumatoid factor–negative RA (RF−RA), 6 with psoriatic arthritis, 3 with reactive arthritis, and 14 with osteoarthritis (OA), were imaged. In the RF+RA group, all DEMRIQ variables correlated significantly with joint fluid interleukin‐6 level (r ≥ 0.6) and number of neutrophils and polymorphonuclear (PMN) cells (r ≥ 0.8), whereas MExNvoxel and IRExNvoxel correlated with synovial inflammatory cells and blood C‐reactive protein (CRP) levels (r ≥ 0.6). In patients with RF−RA, MExNvoxel correlated with blood CRP level (r = 0.8), joint fluid white blood cells, and neutrophils and PMN cells (r = 1). In the seronegative arthritis group, IRExNvoxel correlated with blood CRP, joint fluid PMN cells, and neutrophils (r ≥ 0.7). No significant correlation was seen in the OA group. There was a significant regression correlation between MExNvoxel and inflammatory infiltrates from joint fluid in RF+RA group ( P < 0.05). Conclusion DEMRIQ parameters exhibit varying relationships with local synovial and systemic inflammatory blood biomarkers across different etiologies of knee arthritis, which could provide insight into the level of inflammation in the affected joint.

Nanosecond‐Pulsed Laser Beam Shaping with a Liquid Crystal Spatial Light Modulator for Rapid Microtexturing of Metallic Surfaces

Laser surface texturing can improve the functional properties of metallic materials, with the texture shape being a crucial factor. The spatial light modulator (SLM) is used to design the shape of individual textures. However, generating deep microtextures with precise shapes on metallic materials currently requires extended processing times, limiting their use in industrial applications. This study investigates the generation of the microtexturing patterns with various shapes on stainless steel 316 L surface using a SLM. The method combining computer‐generated holograms with images demonstrates high energy fluence efficiency. The holograms determine the reconstruction distance, shape, and size of the textures. Patterns of the textures with various complex shapes (e.g., circular, triangle, square, hexagon, and other), 6–12 μm depth and 50–70 μm width are achieved using only 5 pulses (200 μs per texture) and 25 kHz pulse frequency rate. This method achieves texturing of 10 × 10 mm areas with various shapes in just 2 s, offering a processing speed ≈500 times faster than current state‐of‐the‐art ultrashort laser pulse techniques, significantly advancing the efficiency of microtexturing processes.

Accelerating Luminescence in Nanostructures: Exploring the Physical Limits and Impact of Ultrafast Emission in Nanoscale Materials

Ultrafast luminescence represents a frontier in optical materials science, bridging fundamental investigations of light–matter interaction and the development of next‐generation photonic devices. Enhancing the speed of luminescence has long been a central objective, with continued relevance in both fundamental and applied contexts. In advanced photonic systems, rapid light emission enables the realization of extremely bright and temporally precise optical signals. This capability is crucial for quantum information technologies, where single‐photon sources with short radiative lifetimes are essential, as well as for classical high‐speed optical communication and sensing platforms. This review highlights recent progress in accelerating the emission process by leveraging cooperative emission effects, resonator‐enhanced coupling, and nonlocal or multipolar interactions, incorporating the authors’ original contributions and perspectives. These advances have led to the realization of novel coherent and incoherent bright light sources, high‐efficiency single‐photon emitters, radiative processes robust against thermal dephasing, and photon generation from materials typically regarded as nonluminescent due to thermal relaxation or self‐trapping. These mechanisms from both theoretical and experimental perspectives are explored, and insights into their integration for future photonic architectures are offered.

Terahertz Chiral Recognition Based on Metasurfaces

Chiral detection plays a crucial role in biomedicine and materials science, but traditional methods face challenges such as low sensitivity and complex operation. Utilizing a terahertz time‐domain spectroscopy (THz‐TDS) system for chiral sample detection leverages the advantages of terahertz radiation, including rich biological information and nonionizing properties. However, conventional THz‐TDS systems can only generate and detect linearly polarized terahertz radiation, requiring multiple measurements for chiral characterization. Here, we propose a novel terahertz chiral sensing method based on a multi‐layer metallic metasurface. Within the range of 0.65–0.75 THz, the metasurface can separate and focus the left‐handed and right‐handed circularly polarized components in the linearly polarized illuminating light into two focal points and convert them back into linear polarization for convenient measurement, thereby overcoming the technical bottleneck of traditional systems. Experimental results demonstrate that the double‐layer metasurface structure extends the operational bandwidth to 100 GHz through Fabry–Perot‐like resonance effects. The (R)‐(−)‐ibuprofen and (S)‐(+)‐ibuprofen enantiomers are measured to demonstrate the validity of proposed method. Compared to traditional THz‐TDS systems for chiral measurements, the efficiency of this method is significantly improved. This method provides a new approach for terahertz chiral recognition and demonstrates practical value in the field of pharmaceutical chiral analysis.

CuF 2 ‐Catalyzed C‐N Cross‐Coupling of Aryl Silanes: Expanding the Scope of Chan‐Lam Type Reaction

Abstract An efficient copper‐catalyzed Chan–Lam type N‐arylation of various amides, sulfonamides, urea, azoles, and amines has been demonstrated using a CuF 2 /DMSO catalytic system with structurally diverse aryl(trimethoxy)silanes under base and ligand‐free conditions. This approach facilitates effective C−N cross‐coupling with user‐friendly organosilicon reagents without requiring an external fluoride source. CuF 2 serves a dual function as both a catalyst and a desilylating agent, facilitating the cleavage of the aryl‐silane bond. The process is compatible with a broad range of substrates, ensuring high efficiency and excellent functional group compatibility. Moreover, this protocol is proven to be valuable for late‐stage modification of amide and sulfonamide‐containing drug molecules, as well as for synthesizing agrochemicals.

The Recent Progress in Introducing Deuterium with D 2 O

Deuterium labeling is invaluable in life sciences and pharmacy, enhancing drug stability and efficacy. Beyond pharmaceuticals, deuterium compounds advance materials science through improved optical and electronic material properties. In chemical research, they enable reaction mechanism studies and interference‐free NMR spectroscopy. These applications highlight deuterium chemistry's essential role across scientific fields. Among deuterium sources, deuterium oxide (D 2 O) is widely recognized for its cost‐effectiveness, stability, and versatility in various reactions. This review explores the use of D 2 O as a deuterium source across key reaction types, including hydrogen isotope exchange, reductive deuteration, and defunctionalization–deuteration. Detailed insights into reaction mechanisms, catalyst selection, and experimental conditions are provided. Furthermore, the review highlights the advantages of D 2 O in achieving selectivity and compatibility in diverse chemical environments, addressing key challenges in deuterium chemistry. Finally, future directions and emerging trends in optimizing D 2 O‐based deuteration methods are discussed.