Tunable superconductivity in electron- and hole-doped Bernal bilayer graphene.

Graphene-based, high-quality, two-dimensional electronic systems have emerged as a highly tunable platform for studying superconductivity1-21. Specifically, superconductivity has been observed in both electron- and hole-doped twisted graphene moiré systems1-17, whereas in crystalline graphene systems, superconductivity has so far been observed only in hole-doped rhombohedral trilayer graphene (RTG)18 and hole-doped Bernal bilayer graphene (BBG)19-21. Recently, enhanced superconductivity has been demonstrated20,21 in BBG because of the proximity to a monolayer WSe2. Here we report the observation of superconductivity and a series of flavour-symmetry-breaking phases in electron- and hole-doped BBG/WSe2 devices by electrostatic doping. The strength of the observed superconductivity is tunable by applied vertical electric fields. The maximum Berezinskii-Kosterlitz-Thouless transition temperature for the electron- and hole-doped superconductivity is about 210 mK and 400 mK, respectively. Superconductivities emerge only when the applied electric fields drive the BBG electron or hole wavefunctions towards the WSe2 layer, underscoring the importance of the WSe2 layer in the observed superconductivity. The hole-doped superconductivity violates the Pauli paramagnetic limit, consistent with an Ising-like superconductor. By contrast, the electron-doped superconductivity obeys the Pauli limit, although the proximity-induced Ising spin-orbit coupling is also notable in the conduction band. Our findings highlight the rich physics associated with the conduction band in BBG, paving the way for further studies into the superconducting mechanisms of crystalline graphene and the development of superconductor devices based on BBG.

Free long-chain fatty acids trigger early postembryonic development in starved Caenorhabditis elegans by suppressing mTORC1.

Postembryonic development of animals has long been considered an internally predetermined program, while macronutrients were believed to be essential solely for providing biomatters and energy to support this process. However, in this study, by using a nematode Caenorhabditis elegans (abbreviated as C. elegans hereafter) model, we surprisingly discovered that dietary supplementation of palmitic acid alone, rather than other abundant essential nutrients such as glucose or amino acid mixture, was sufficient to initiate early postembryonic development even under complete macronutrient deprivation. Such a development was evidenced by changes in morphology, cellular markers in multiple tissues, behaviors, and the global transcription pattern and it occurred earlier than the well-known early L1 nutrient checkpoint. Mechanistically, palmitic acid did not function as a biomatter/energy provider, but rather as a ligand to activate the nuclear hormone receptor NHR-49/80, leading to the production of an unknown peroxisome-derived secretive hormone in the intestine. This hormonal signal was received by chemosensory neurons in the head, regulating the insulin-like neuropeptide secretion and its downstream nuclear receptor to orchestrate global development. Additionally, the nutrient-sensing hub mTORC1 played a negative role in this process. In conclusion, our data indicate that free fatty acids act as a primary nutrient signal to launch the early development in C. elegans, which suggests that specific nutrients, rather than the internal genetic program, serve as the first impetus for postembryonic development.

Plant immunity suppression via PHR1-RALF-FERONIA shapes the root microbiome to alleviate phosphate starvation.

The microbiome plays an important role in shaping plant growth and immunity, but few plant genes and pathways impacting plant microbiome composition have been reported. In Arabidopsis thaliana, the phosphate starvation response (PSR) was recently found to modulate the root microbiome upon phosphate (Pi) starvation through the transcriptional regulator PHR1. Here, we report that A. thaliana PHR1 directly binds to the promoters of rapid alkalinization factor (RALF) genes, and activates their expression under phosphate-starvation conditions. RALFs in turn suppress complex formation of pathogen-associated molecular pattern (PAMP)-triggered immunity (PTI) receptor through FERONIA, a previously-identified PTI modulator that increases resistance to certain detrimental microorganisms. Suppression of immunity via the PHR1-RALF-FERONIA axis allows colonization by specialized root microbiota that help to alleviate phosphate starvation by upregulating the expression of PSR genes. These findings provide a new paradigm for coordination of host-microbe homeostasis through modulating plant innate immunity after environmental perturbations.

Introducing π-HelixNovo for practical large-scale de novo peptide sequencing.

De novo peptide sequencing is a promising approach for novel peptide discovery, highlighting the performance improvements for the state-of-the-art models. The quality of mass spectra often varies due to unexpected missing of certain ions, presenting a significant challenge in de novo peptide sequencing. Here, we use a novel concept of complementary spectra to enhance ion information of the experimental spectrum and demonstrate it through conceptual and practical analyses. Afterward, we design suitable encoders to encode the experimental spectrum and the corresponding complementary spectrum and propose a de novo sequencing model $\pi$-HelixNovo based on the Transformer architecture. We first demonstrated that $\pi$-HelixNovo outperforms other state-of-the-art models using a series of comparative experiments. Then, we utilized $\pi$-HelixNovo to de novo gut metaproteome peptides for the first time. The results show $\pi$-HelixNovo increases the identification coverage and accuracy of gut metaproteome and enhances the taxonomic resolution of gut metaproteome. We finally trained a powerful $\pi$-HelixNovo utilizing a larger training dataset, and as expected, $\pi$-HelixNovo achieves unprecedented performance, even for peptide-spectrum matches with never-before-seen peptide sequences. We also use the powerful $\pi$-HelixNovo to identify antibody peptides and multi-enzyme cleavage peptides, and $\pi$-HelixNovo is highly robust in these applications. Our results demonstrate the effectivity of the complementary spectrum and take a significant step forward in de novo peptide sequencing.

Multiple sequence alignment-based RNA language model and its application to structural inference.

Compared with proteins, DNA and RNA are more difficult languages to interpret because four-letter coded DNA/RNA sequences have less information content than 20-letter coded protein sequences. While BERT (Bidirectional Encoder Representations from Transformers)-like language models have been developed for RNA, they are ineffective at capturing the evolutionary information from homologous sequences because unlike proteins, RNA sequences are less conserved. Here, we have developed an unsupervised multiple sequence alignment-based RNA language model (RNA-MSM) by utilizing homologous sequences from an automatic pipeline, RNAcmap, as it can provide significantly more homologous sequences than manually annotated Rfam. We demonstrate that the resulting unsupervised, two-dimensional attention maps and one-dimensional embeddings from RNA-MSM contain structural information. In fact, they can be directly mapped with high accuracy to 2D base pairing probabilities and 1D solvent accessibilities, respectively. Further fine-tuning led to significantly improved performance on these two downstream tasks compared with existing state-of-the-art techniques including SPOT-RNA2 and RNAsnap2. By comparison, RNA-FM, a BERT-based RNA language model, performs worse than one-hot encoding with its embedding in base pair and solvent-accessible surface area prediction. We anticipate that the pre-trained RNA-MSM model can be fine-tuned on many other tasks related to RNA structure and function.

AFP-MFL: accurate identification of antifungal peptides using multi-view feature learning.

Recently, peptide-based drugs have gained unprecedented interest in discovering and developing antifungal drugs due to their high efficacy, broad-spectrum activity, low toxicity and few side effects. However, it is time-consuming and expensive to identify antifungal peptides (AFPs) experimentally. Therefore, computational methods for accurately predicting AFPs are highly required. In this work, we develop AFP-MFL, a novel deep learning model that predicts AFPs only relying on peptide sequences without using any structural information. AFP-MFL first constructs comprehensive feature profiles of AFPs, including contextual semantic information derived from a pre-trained protein language model, evolutionary information, and physicochemical properties. Subsequently, the co-attention mechanism is utilized to integrate contextual semantic information with evolutionary information and physicochemical properties separately. Extensive experiments show that AFP-MFL outperforms state-of-the-art models on four independent test datasets. Furthermore, the SHAP method is employed to explore each feature contribution to the AFPs prediction. Finally, a user-friendly web server of the proposed AFP-MFL is developed and freely accessible at http://inner.wei-group.net/AFPMFL/, which can be considered as a powerful tool for the rapid screening and identification of novel AFPs.

Electrochemical Biosensors for Whole Blood Analysis: Recent Progress, Challenges, and Future Perspectives.

Whole blood, as one of the most significant biological fluids, provides critical information for health management and disease monitoring. Over the past 10 years, advances in nanotechnology, microfluidics, and biomarker research have spurred the development of powerful miniaturized diagnostic systems for whole blood testing toward the goal of disease monitoring and treatment. Among the techniques employed for whole-blood diagnostics, electrochemical biosensors, as known to be rapid, sensitive, capable of miniaturization, reagentless and washing free, become a class of emerging technology to achieve the target detection specifically and directly in complex media, e.g., whole blood or even in the living body. Here we are aiming to provide a comprehensive review to summarize advances over the past decade in the development of electrochemical sensors for whole blood analysis. Further, we address the remaining challenges and opportunities to integrate electrochemical sensing platforms.

Surface Engineering Enables Efficient AgBiS2 Quantum Dot Solar Cells.

Surface ligand chemistry is vital to control the synthesis, diminish surface defects, and improve the electronic coupling of quantum dots (QDs) toward emerging applications in optoelectronic devices. Here, we successfully develop highly homogeneous and dispersed AgBiS2 QDs, focus on the control of interdot spacing, and substitute the long-chain ligands with ammonium iodide in solution. This results in improved electronic coupling of AgBiS2 QDs with excellent surface passivation, which greatly facilitates carrier transport within the QD films. Based on the stable AgBiS2 QD dispersion with the optimal ligand state, a homogeneous and densely packed QD film is prepared by a facile one-step coating process, delivering a champion power conversion efficiency of approximately 8% in the QD solar cells with outstanding shelf life stability. The proposed surface engineering strategy holds the potential to become a universal preprocessing step in the realm of high-performance QD optoelectronic devices.

Supramolecular Polymerization as a Tool to Reveal the Magnetic Transition Dipole Moment of Heptazines.

Heptazine derivatives have attracted significant interest due to their small S1-T1 gap, which contributes to their unique electronic and optical properties. However, the nature of the lowest excited state remains ambiguous. In the present study, we characterize the lowest optical transition of heptazine by its magnetic transition dipole moment. To measure the magnetic transition dipole moment, the flat heptazine must be chiroptically active, which is difficult to achieve for single heptazine molecules. Therefore, we used supramolecular polymerization as an approach to make homochiral stacks of heptazine derivatives. Upon formation of the supramolecular polymers, the preferred helical stacking of heptazine introduces circular polarization of absorption and fluorescence. The magnetic transition dipole moments for the S1 ← S0 and S1 → S0 are determined to be 0.35 and 0.36 Bohr magneton, respectively. These high values of magnetic transition dipole moments support the intramolecular charge transfer nature of the lowest excited state from nitrogen to carbon in heptazine and further confirm the degeneracy of S1 and T1.

circNOX4 activates an inflammatory fibroblast niche to promote tumor growth and metastasis in NSCLC via FAP/IL-6 axis.

BACKGROUND: Cancer-associated fibroblasts (CAFs) orchestrate a supportive niche that fuels cancer metastatic development in non-small cell lung cancer (NSCLC). Due to the heterogeneity and plasticity of CAFs, manipulating the activated phenotype of fibroblasts is a promising strategy for cancer therapy. However, the underlying mechanisms of fibroblast activation and phenotype switching that drive metastasis remain elusive. METHODS: The clinical implications of fibroblast activation protein (FAP)-positive CAFs (FAP+CAFs) were evaluated based on tumor specimens from NSCLC patients and bioinformatic analysis of online databases. CAF-specific circular RNAs (circRNAs) were screened by circRNA microarrays of primary human CAFs and matched normal fibroblasts (NFs). Survival analyses were performed to assess the prognostic value of circNOX4 in NSCLC clinical samples. The biological effects of circNOX4 were investigated by gain- and loss-of-function experiments in vitro and in vivo. Fluorescence in situ hybridization, luciferase reporter assays, RNA immunoprecipitation, and miRNA rescue experiments were conducted to elucidate the underlying mechanisms of fibroblast activation. Cytokine antibody array, transwell coculture system, and enzyme-linked immunosorbent assay (ELISA) were performed to investigate the downstream effectors that promote cancer metastasis. RESULTS: FAP+CAFs were significantly enriched in metastatic cancer samples, and their higher abundance was correlated with the worse overall survival in NSCLC patients. A novel CAF-specific circRNA, circNOX4 (hsa_circ_0023988), evoked the phenotypic transition from NFs into CAFs and promoted the migration and invasion of NSCLC in vitro and in vivo. Clinically, circNOX4 correlated with the poor prognosis of advanced NSCLC patients. Mechanistically, circNOX4 upregulated FAP by sponging miR-329-5p, which led to fibroblast activation. Furthermore, the circNOX4/miR-329-5p/FAP axis activated an inflammatory fibroblast niche by preferentially inducing interleukin-6 (IL-6) and eventually promoting NSCLC progression. Disruption of the intercellular circNOX4/IL-6 axis significantly suppressed tumor growth and metastatic colonization in vivo. CONCLUSIONS: Our study reveals a role of the circRNA-induced fibroblast niche in tumor metastasis and highlights that targeting the circNOX4/FAP/IL-6 axis is a promising strategy for the intervention of NSCLC metastasis.

Machine Learning for Single-Molecule Localization Microscopy: From Data Analysis to Quantification.

Single-molecule localization microscopy (SMLM) is a versatile tool for realizing nanoscale imaging with visible light and providing unprecedented opportunities to observe bioprocesses. The integration of machine learning with SMLM enhances data analysis by improving efficiency and accuracy. This tutorial aims to provide a comprehensive overview of the data analysis process and theoretical aspects of SMLM, while also highlighting the typical applications of machine learning in this field. By leveraging advanced analytical techniques, SMLM is becoming a powerful quantitative analysis tool for biological research.

The Construction and Mechanism Study of High-Speed Carrier Transport Channel in Gallium Arsenide Homojunction Toward High-Performance Photoelectrochemical Photodetector.

The energy band structure and surface/interface properties are prerequisite for not only preserving the intrinsic material quality but also manipulating carrier transport behavior for photoelectrochemical (PEC) photodetection. How to precisely design/regulate the band structure and surface/interface properties of semiconductor materials is the key to improving the performance of PEC photodetection. Herein, the quintuple heterotypic homojunction (QH) GaAs film is fabricated with a gradient energy band via plasma-assisted molecular beam epitaxy for constructing a high-speed carrier transport channel in PEC photodetection, which can efficiently drive the separation and transport of photogenerated electron-hole pairs. The designed QH-GaAs-based PEC photodetector exhibits excellent performances, compared with bare i-GaAs, delivering an ultrashort rise/decay times of only 1.1/1.1 ms and a high responsivity of 20.4 mA W-1 at 0 V under 850 nm illumination. Strikingly, an ultrahigh detectivity with 1.46 × 1012 Jones is achieved. More importantly, the QH-GaAs device can stably operate underwater seawater environment. This study provides a novel strategy for designing and fabricating multiple heterotypic homojunction with gradient energy band to boost charge transport dynamics for PEC fields.

Exploring the interplay between angiosperm chlorophyll metabolism and environmental factors.

MAIN CONCLUSION: In this review, we summarize how chlorophyll metabolism in angiosperm is affected by the environmental factors: light, temperature, metal ions, water, oxygen, and altitude. The significance of chlorophyll (Chl) in plant leaf morphogenesis and photosynthesis cannot be overstated. Over time, researchers have made significant advancements in comprehending the biosynthetic pathway of Chl in angiosperms, along with the pivotal enzymes and genes involved in this process, particularly those related to heme synthesis and light-responsive mechanisms. Various environmental factors influence the stability of Chl content in angiosperms by modulating Chl metabolic pathways. Understanding the interplay between plants Chl metabolism and environmental factors has been a prominent research topic. This review mainly focuses on angiosperms, provides an overview of the regulatory mechanisms governing Chl metabolism, and the impact of environmental factors such as light, temperature, metal ions (iron and magnesium), water, oxygen, and altitude on Chl metabolism. Understanding these effects is crucial for comprehending and preserving the homeostasis of Chl metabolism.

The prodomain of Arabidopsis metacaspase 2 positively regulates immune signaling mediated by pattern-recognition receptors.

Metacaspases (MCs) are structural homologs of mammalian caspases found in plants, fungi, and protozoa. Type-I MCs carry an N-terminal prodomain, the function of which is unclear. Through genetic analysis of Arabidopsis mc2-1, a T-DNA insertion mutant of MC2, we demonstrated that the prodomain of metacaspase 2 (MC2) promotes immune signaling mediated by pattern-recognition receptors (PRRs). In mc2-1, immune responses are constitutively activated. The receptor-like kinases (RLKs) BAK1/BKK1 and SOBIR1 are required for the autoimmune phenotype of mc2-1, suggesting that immune signaling mediated by the receptor-like protein (RLP)-type PRRs is activated in mc2-1. A suppressor screen identified multiple mutations in the first exon of MC2, which suppress the autoimmunity in mc2-1. Further analysis revealed that the T-DNA insertion at the end of exon 1 of MC2 causes elevated expression of the MC2 prodomain, and overexpression of the MC2 prodomain in wild-type (WT) plants results in the activation of immune responses. The MC2 prodomain interacts with BIR1, which inhibits RLP-mediated immune signaling by interacting with BAK1, suggesting that the MC2 prodomain promotes plant defense responses by interfering with the function of BIR1. Our study uncovers an unexpected function of the prodomain of a MC in plant immunity.

Proteomics and metabolomics analyses of urine for investigation of gallstone disease in a high-altitude area.

BACKGROUND: The incidence of gallstones is high in Qinghai Province. However, the molecular mechanisms underlying the development of gallstones remain unclear. METHODS: In this study, we collected urine samples from 30 patients with gallstones and 30 healthy controls. The urine samples were analysed using multi-omics platforms. Proteomics analysis was conducted using data-independent acquisition, whereas metabolomics analysis was performed using liquid chromatography-mass spectrometry (LC-MS). RESULTS: Among the patients with gallstones, we identified 49 down-regulated and 185 up-regulated differentially expressed proteins as well as 195 up-regulated and 189 down-regulated differentially expressed metabolites. Six pathways were significantly enriched: glycosaminoglycan degradation, arginine and proline metabolism, histidine metabolism, pantothenate and coenzyme A biosynthesis, drug metabolism-other enzymes, and the pentose phosphate pathway. Notably, 10 differentially expressed proteins and metabolites showed excellent predictive performance and were selected as potential biomarkers. CONCLUSION: The findings of our metabolomics and proteomics analyses provide new insights into novel biomarkers for patients with cholelithiasis in high-altitude areas.

miR-455/GREM1 axis promotes colorectal cancer progression and liver metastasis by affecting PI3K/AKT pathway and inducing M2 macrophage polarization.

BACKGROUND: Colorectal cancer is among the most common malignant tumors affecting the gastrointestinal tract. Liver metastases, a complication present in approximately 50% of colorectal cancer patients, are a considerable concern. Recently, studies have revealed the crucial role of miR-455 in tumor pathogenesis. However, the effect of miR-455 on the progression of liver metastases in colorectal cancer remains controversial. As an antagonist of bone morphogenetic protein(BMP), Gremlin 1 (GREM1) may impact organogenesis, body patterning, and tissue differentiation. Nevertheless, the role of miR-455 in regulating GREM1 in colorectal cancer liver metastases and how miR-455/GREM1 axis influences tumour immune microenvironment is unclear. METHODS: Bioinformatics analysis shows that miR-455/GREM1 axis plays crucial role in liver metastasis of intestinal cancer and predicts its possible mechanism. To investigate the impact of miR-455/GREM1 axis on the proliferation, invasion, and migration of colorectal cancer cells, colony formation assay, wound healing and transwell assay were examined in vitro. The Dual-Luciferase reporter gene assay and RNA pull-down assay confirmed a possible regulatory effect between miR-455 and GREM1. In vivo, colorectal cancer liver metastasis(CRLM) model mice was established to inquiry the effect of miR-455/GREM1 axis on tumor growth and macrophage polarization. The marker of macrophage polarization was tested using immunofluorescence(IF) and quantitative real-time polymerase chain reaction(qRT-PCR). By enzyme-linked immunosorbent assay (ELISA), cytokines were detected in culture medium supernatants. RESULTS: We found that miR-455 and BMP6 expression was increased and GREM1 expression was decreased in liver metastase compared with primary tumor. miR-455/GREM1 axis promotes colorectal cancer cells proliferation, migration, invasion via affected PI3K/AKT pathway. Moreover, downregulating GREM1 augmented BMP6 expression in MC38 cell lines, inducing M2 polarization of macrophages, and promoting liver metastasis growth in CRLM model mice. CONCLUSION: These data suggest that miR-455/GREM1 axis promotes colorectal cancer progression and liver metastasis by affecting PI3K/AKT pathway and inducing M2 macrophage polarization. These results offer valuable insights and direction for future research and treatment of CRLM.

LncRNA-MM2P regulates retinal neovascularization through M2 macrophage polarization.

The study aims to investigate the effects and potential mechanisms of lncRNA-MM2P on retinal neovascularization in a mouse model of oxygen-induced retinopathy (OIR). The OIR model was established in C57BL/6J mice. RAW264.7 cell line and bone marrow-derived macrophages (BMDMs) from mice were used for in vitro studies. RT-qPCR was used to analyze the expressions of lncRNA and mRNAs. The protein expression levels were determined by western blotting. The size of avascular areas and neovascular tufts were assessed based on isolectin B4 immunofluorescence staining images. The human retinal endothelial cells (HRECs) were used to evaluate the proliferation, migration, and tube formation of endothelial cells. The expression of lncRNA-MM2P was significantly upregulated from P17 to P25 in OIR retinas. Knockdown of lncRNA-MM2P levels in vivo led to a significant reduction in the neovascular tufts and avascular areas in the retinas of OIR mice. Knockdown of lncRNA-MM2P levels in vitro suppressed the expression of M2 markers in macrophages. Moreover, we found a significant inhibition of avascular areas and neovascular tufts in OIR mice injected intravitreally with M2 macrophages treated by shRNA-MM2P. The cellular functions of proliferation, migration, and tube formation were significantly attenuated in HRECs cultured with a supernatant of shRNA-MM2P-treated M2 macrophages. Our results indicate that lncRNA-MM2P regulates retinal neovascularization by inducing M2 polarization of macrophages in OIR mice. Therefore, lncRNA-MM2P may be a potential molecular target for immunoregulation of retinal neovascularization.

Comparative proteomic analysis of retinal hypoxia-ischemia in an acute ocular hypertension model using tandem mass tag-based quantitative proteomics.

The main symptom of acute glaucoma is acute ocular hypertension (AOH), which leads to the death of retinal ganglion cells (RGCs) and permanent loss of vision. However, effective treatments for these conditions are lacking. This study aimed to identify major regulators and overall protein changes involved in AOH-induced RGC death. Proteomic patterns of the retinal protein extracts from the AOH and sham groups were analyzed using mass spectrometry (MS), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Proteomic analysis revealed 92 proteins in the AOH group compared to the control group; 58 proteins were upregulated and 34 were downregulated. Alterations in fatty acid-binding protein 7 (FABP7) and caveolin-1 (Cav-1), which are related to fatty acid metabolism and ocular inflammatory signaling, were detected using western blotting and biochemical assays. Variations in the expression of galectin-1 (Gal-1), S100 calcium-binding protein A6 (S100a6), and visinin-like protein-1 (VILIP) have been associated with neuronal ischemia. Our investigation demonstrates that neuroinflammation and fatty acid metabolism are involved in retinal impairment following AOH, suggesting a possible treatment approach for acute glaucoma.

Prediction of Subsequent Vertebral Fracture After Acute Osteoporotic Fractures from Clinical and Paraspinal Muscle Features.

To construct a nomogram based on clinical factors and paraspinal muscle features to predict vertebral fractures occurring after acute osteoporotic vertebral compression fracture (OVCF). We retrospectively enrolled 307 patients with acute OVCF between January 2013 and August 2022, and performed magnetic resonance imaging of the L3/4 and L4/5 intervertebral discs (IVDs) to estimate the cross-sectional area (CSA) and degree of fatty infiltration (FI) of the paraspinal muscles. We also collected clinical and radiographic data. We used univariable and multivariable Cox proportional hazards models to identify factors that should be included in the predictive nomogram. Post-OVCF vertebral fracture occurred within 3, 12, and 24 months in 33, 69, and 98 out of the 307 patients (10.8%, 22.5%, and 31.9%, respectively). Multivariate analysis revealed that this event was associated with percutaneous vertebroplasty treatment, higher FI at the L3/4 IVD levels of the psoas muscle, and lower relative CSA of functional muscle at the L4/5 IVD levels of the multifidus muscle. Area under the curve values for subsequent vertebral fracture at 3, 12, and 24 months were 0.711, 0.724, and 0.737, respectively, indicating remarkable accuracy of the nomogram. We developed a model for predicting post-OVCF vertebral fracture from diagnostic information about prescribed treatment, FI at the L3/4 IVD levels of the psoas muscle, and relative CSA of functional muscle at the L4/5 IVD levels of the multifidus muscle. This model could facilitate personalized predictions and preventive strategies.

Magnetic Resonance Imaging-Based Classification Systems for Informing Better Outcomes of Adenomyosis After Ultrasound-Guided High-Intensity Focused Ultrasound Ablating Surgery.

BACKGROUND: A referenced MRI-based classification associated with focused ultrasound ablation surgery (FUAS) outcomes is lacking in adenomyosis. PURPOSE: To identify an MRI-based classification system for informing the FUAS outcomes. STUDY TYPE: Retrospective. POPULATION: Patients with FUAS for adenomyosis, were divided into a training set (N = 643; 355 with post-FUAS gonadotropin-releasing hormone/levonorgestrel, 288 without post-FUAS therapy) and an external validation set (N = 135; all without post-FUAS therapy). FIELD STRENGTH/SEQUENCE: 1.5 T, turbo spin-echo T2-weighted imaging and single-shot echo-planar diffusion-weighted imaging sequences. ASSESSMENT: Five MRI-based adenomyosis classifications: classification 1 (C1) (diffuse, focal, and mild), C2 (intrinsic, extrinsic, intramural, and indeterminate), C3 (internal, adenomyomas, and external), C4 (six subtypes on areas [internal or external] and volumes [<1/3 or ≥2/3]), and C5 (internal [asymmetric or symmetric], external, intramural, full thickness [asymmetric or symmetric]) for FUAS outcomes (symptom relief and recurrence). STATISTICAL TESTS: The optimal classification was significantly associated with the most subtypes of FUAS outcomes. Relating to the timing of recurrence was measured using Cox regression analysis and median recurrence time was estimated by a Kaplan-Meier curve. A P value <0.05 was considered statistically significant. RESULTS: Dysmenorrhea relief and recurrence were only associated with C2 in training patients undergoing FUAS alone. Compared with other subtypes, the extrinsic subtype of C2 was significantly associated with dysmenorrhea recurrence in the FUAS group. Besides, the median dysmenorrhea recurrence time of extrinsic subtype was significantly shorter than that of other subtypes (42.0 months vs. 50.3 months). In the validation cohort, C2 was confirmed as the optimal system and its extrinsic subtype was confirmed to have a significantly shorter dysmenorrhea recurrence time than other subtypes. DATA CONCLUSION: Classification 2 can inform dysmenorrhea relief and recurrence in patients with adenomyosis undergoing FAUS only. Itsextrinsic subtype was associated with an earlier onset of dysmenorrhea recurrence after treatment. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.