Pan-genome analysis of 33 genetically diverse rice accessions reveals hidden genomic variations.

Structural variations (SVs) and gene copy number variations (gCNVs) have contributed to crop evolution, domestication, and improvement. Here, we assembled 31 high-quality genomes of genetically diverse rice accessions. Coupling with two existing assemblies, we developed pan-genome-scale genomic resources including a graph-based genome, providing access to rice genomic variations. Specifically, we discovered 171,072 SVs and 25,549 gCNVs and used an Oryza glaberrima assembly to infer the derived states of SVs in the Oryza sativa population. Our analyses of SV formation mechanisms, impacts on gene expression, and distributions among subpopulations illustrate the utility of these resources for understanding how SVs and gCNVs shaped rice environmental adaptation and domestication. Our graph-based genome enabled genome-wide association study (GWAS)-based identification of phenotype-associated genetic variations undetectable when using only SNPs and a single reference assembly. Our work provides rich population-scale resources paired with easy-to-access tools to facilitate rice breeding as well as plant functional genomics and evolutionary biology research.

A Natural Allele of a Transcription Factor in Rice Confers Broad-Spectrum Blast Resistance.

Rice feeds half the world's population, and rice blast is often a destructive disease that results in significant crop loss. Non-race-specific resistance has been more effective in controlling crop diseases than race-specific resistance because of its broad spectrum and durability. Through a genome-wide association study, we report the identification of a natural allele of a C2H2-type transcription factor in rice that confers non-race-specific resistance to blast. A survey of 3,000 sequenced rice genomes reveals that this allele exists in 10% of rice, suggesting that this favorable trait has been selected through breeding. This allele causes a single nucleotide change in the promoter of the bsr-d1 gene, which results in reduced expression of the gene through the binding of the repressive MYB transcription factor and, consequently, an inhibition of H2O2 degradation and enhanced disease resistance. Our discovery highlights this novel allele as a strategy for breeding durable resistance in rice.

Rice false smut virulence protein subverts host chitin perception and signaling at lemma and palea for floral infection.

The flower-infecting fungus Ustilaginoidea virens causes rice false smut, which is a severe emerging disease threatening rice (Oryza sativa) production worldwide. False smut not only reduces yield, but more importantly produces toxins on grains, posing a great threat to food safety. U. virens invades spikelets via the gap between the 2 bracts (lemma and palea) enclosing the floret and specifically infects the stamen and pistil. Molecular mechanisms for the U. virens-rice interaction are largely unknown. Here, we demonstrate that rice flowers predominantly employ chitin-triggered immunity against U. virens in the lemma and palea, rather than in the stamen and pistil. We identify a crucial U. virens virulence factor, named UvGH18.1, which carries glycoside hydrolase activity. Mechanistically, UvGH18.1 functions by binding to and hydrolyzing immune elicitor chitin and interacting with the chitin receptor CHITIN ELICITOR BINDING PROTEIN (OsCEBiP) and co-receptor CHITIN ELICITOR RECEPTOR KINASE1 (OsCERK1) to impair their chitin-induced dimerization, suppressing host immunity exerted at the lemma and palea for gaining access to the stamen and pistil. Conversely, pretreatment on spikelets with chitin induces a defense response in the lemma and palea, promoting resistance against U. virens. Collectively, our data uncover a mechanism for a U. virens virulence factor and the critical location of the host-pathogen interaction in flowers and provide a potential strategy to control rice false smut disease.

Single-nucleus transcriptomic mapping uncovers targets for traumatic brain injury.

The subventricular zone (SVZ) is a neurogenic niche that contributes to homeostasis and repair after brain injury. However, the effects of mild traumatic brain injury (mTBI) on the divergence of the regulatory DNA landscape within the SVZ and its link to functional alterations remain unexplored. In this study, we mapped the transcriptome atlas of murine SVZ and its responses to mTBI at the single-cell level. We observed cell-specific gene expression changes following mTBI and unveiled diverse cell-to-cell interaction networks that influence a wide array of cellular processes. Moreover, we report novel neurogenesis lineage trajectories and related key transcription factors, which we validate through loss-of-function experiments. Specifically, we validate the role of Tcf7l1, a cell cycle gene regulator, in promoting neural stem cell differentiation toward the neuronal lineage after mTBI, providing a potential target for regenerative medicine. Overall, our study profiles an SVZ transcriptome reference map, which underlies the differential cellular behavior in response to mTBI. The identified key genes and pathways that may ameliorate brain damage or facilitate neural repair serve as a comprehensive resource for drug discovery in the context of mTBI.

DrugMetric: quantitative drug-likeness scoring based on chemical space distance.

The process of drug discovery is widely known to be lengthy and resource-intensive. Artificial Intelligence approaches bring hope for accelerating the identification of molecules with the necessary properties for drug development. Drug-likeness assessment is crucial for the virtual screening of candidate drugs. However, traditional methods like Quantitative Estimation of Drug-likeness (QED) struggle to distinguish between drug and non-drug molecules accurately. Additionally, some deep learning-based binary classification models heavily rely on selecting training negative sets. To address these challenges, we introduce a novel unsupervised learning framework called DrugMetric, an innovative framework for quantitatively assessing drug-likeness based on the chemical space distance. DrugMetric blends the powerful learning ability of variational autoencoders with the discriminative ability of the Gaussian Mixture Model. This synergy enables DrugMetric to identify significant differences in drug-likeness across different datasets effectively. Moreover, DrugMetric incorporates principles of ensemble learning to enhance its predictive capabilities. Upon testing over a variety of tasks and datasets, DrugMetric consistently showcases superior scoring and classification performance. It excels in quantifying drug-likeness and accurately distinguishing candidate drugs from non-drugs, surpassing traditional methods including QED. This work highlights DrugMetric as a practical tool for drug-likeness scoring, facilitating the acceleration of virtual drug screening, and has potential applications in other biochemical fields.

Mage transposon: a novel gene delivery system for mammalian cells.

Transposons, as non-viral integration vectors, provide a secure and efficient method for stable gene delivery. In this study, we have discovered Mage (MG), a novel member of the piggyBac(PB) family, which exhibits strong transposability in a variety of mammalian cells and primary T cells. The wild-type MG showed a weaker insertion preference for near genes, transcription start sites (TSS), CpG islands, and DNaseI hypersensitive sites in comparison to PB, approaching the random insertion pattern. Utilizing in silico virtual screening and feasible combinatorial mutagenesis in vitro, we effectively produced the hyperactive MG transposase (hyMagease). This variant boasts a transposition rate 60% greater than its native counterpart without significantly altering its insertion pattern. Furthermore, we applied the hyMagease to efficiently deliver chimeric antigen receptor (CAR) into T cells, leading to stable high-level expression and inducing significant anti-tumor effects both in vitro and in xenograft mice models. These findings provide a compelling tool for gene transfer research, emphasizing its potential and prospects in the domains of genetic engineering and gene therapy.

BatmanNet: bi-branch masked graph transformer autoencoder for molecular representation.

Although substantial efforts have been made using graph neural networks (GNNs) for artificial intelligence (AI)-driven drug discovery, effective molecular representation learning remains an open challenge, especially in the case of insufficient labeled molecules. Recent studies suggest that big GNN models pre-trained by self-supervised learning on unlabeled datasets enable better transfer performance in downstream molecular property prediction tasks. However, the approaches in these studies require multiple complex self-supervised tasks and large-scale datasets , which are time-consuming, computationally expensive and difficult to pre-train end-to-end. Here, we design a simple yet effective self-supervised strategy to simultaneously learn local and global information about molecules, and further propose a novel bi-branch masked graph transformer autoencoder (BatmanNet) to learn molecular representations. BatmanNet features two tailored complementary and asymmetric graph autoencoders to reconstruct the missing nodes and edges, respectively, from a masked molecular graph. With this design, BatmanNet can effectively capture the underlying structure and semantic information of molecules, thus improving the performance of molecular representation. BatmanNet achieves state-of-the-art results for multiple drug discovery tasks, including molecular properties prediction, drug-drug interaction and drug-target interaction, on 13 benchmark datasets, demonstrating its great potential and superiority in molecular representation learning.

Cancer-associated fibroblasts-secreted exosomal miR-92a-3p promotes tumor growth and stemness in hepatocellular carcinoma through activation of Wnt/ß-catenin signaling pathway by suppressing AXIN1.

Cancer-associated fibroblasts (CAFs) are a major cellular component in the tumor microenvironment and have been shown to exhibit protumorigenic effects in hepatocellular carcinoma (HCC). This study aimed to delve into the mechanisms underlying the tumor-promoting effects of CAFs in HCC. Small RNA sequencing was conducted to screen differential expressed microRNAs in exosomes derived from CAFs and normal fibroblasts (NFs). The miR-92a-3p expression was then measured using reverse transcriptase quantitative real-time PCR in CAFs, NFs, CAFs-derived exosomes (CAFs-Exo), and NF-derived exosomes (NFs-Exo). Compared to NFs or NF-Exo, CAFs and CAFs-Exo significantly promoted HCC cell proliferation, migration, and stemness. Additionally, compared to NFs or NF-Exo, miR-92a-3p level was notably higher in CAFs and CAFs-Exo, respectively. Exosomal miR-92a-3p was found to enhance HCC cell proliferation, migration, and stemness. Meanwhile, AXIN1 was targeted by miR-92a-3p. Exosomal miR-92a-3p could activate ß-catenin/CD44 signaling in HCC cells by inhibiting AXIN1 messenger RNA. Furthermore, in vivo studies verified that exosomal miR-92a-3p notably promoted tumor growth and stemness through targeting AXIN1/ß-catenin axis. Collectively, CAFs secreted exosomal miR-92a-3p was capable of promoting growth and stemness in HCC through activation of Wnt/ß-catenin signaling pathway by suppressing AXIN1. Therefore, targeting CAFs-derived miR-92a-3p may be a potential strategy for treating HCC.

EGR1 modulates EPHB4-induced trophoblast dysfunction in recurrent spontaneous abortion†.

Recurrent spontaneous abortion, defined as at least three unexplained abortions occurring before the 20-24 week of pregnancy, has a great impact on women's quality of life. Ephrin receptor B4 has been associated with trophoblast function in preeclampsia. The present study aimed to verify the hypothesis that ephrin receptor B4 regulates the biological functions of trophoblasts in recurrent spontaneous abortion and to explore the upstream mechanism. Ephrin receptor B4 was overexpressed in mice with recurrent spontaneous abortion. Moreover, ephrin receptor B4 inhibited trophoblast proliferation, migration, and invasion while promoting apoptosis. Downregulation of early growth response protein 1 expression in mice with recurrent spontaneous abortion led to ephrin receptor B4 overexpression. Poor expression of WT1-associated protein in mice with recurrent spontaneous abortion reduced the modification of early growth response protein 1 mRNA methylation, resulting in decreased early growth response protein 1 mRNA stability and expression. Overexpression of WT1-associated protein reduced the incidence of recurrent spontaneous abortion in mice by controlling the phenotype of trophoblasts, which was reversed by early growth response protein 1 knockdown. All in all, our findings demonstrate that dysregulation of WT1-associated protein contributes to the instability of early growth response protein 1, thereby activating ephrin receptor B4-induced trophoblast dysfunction in recurrent spontaneous abortion. Our study provides novel insights into understanding the molecular pathogenesis of recurrent spontaneous abortion.

Pathogenomics for accurate diagnosis, treatment, prognosis of oncology: a cutting edge overview.

The capability to gather heterogeneous data, alongside the increasing power of artificial intelligence to examine it, leading a revolution in harnessing multimodal data in the life sciences. However, most approaches are limited to unimodal data, leaving integrated approaches across modalities relatively underdeveloped in computational pathology. Pathogenomics, as an invasive method to integrate advanced molecular diagnostics from genomic data, morphological information from histopathological imaging, and codified clinical data enable the discovery of new multimodal cancer biomarkers to propel the field of precision oncology in the coming decade. In this perspective, we offer our opinions on synthesizing complementary modalities of data with emerging multimodal artificial intelligence methods in pathogenomics. It includes correlation between the pathological and genomic profile of cancer, fusion of histology, and genomics profile of cancer. We also present challenges, opportunities, and avenues for future work.

Novel insights into the effects of 5-hydroxymethfurural on genomic instability and phenotypic evolution using a yeast model.

5-Hydroxymethfurural (5-HMF) is naturally found in a variety of foods and beverages and represents a main inhibitor in the lignocellulosic hydrolysates used for fermentation. This study investigated the impact of 5-HMF on the genomic stability and phenotypic plasticity of the yeast Saccharomyces cerevisiae. Using next-generation sequencing technology, we examined the genomic alterations of diploid S. cerevisiae isolates that were subcultured on a medium containing 1.2 g/L 5-HMF. We found that in 5-HMF-treated cells, the rates of chromosome aneuploidy, large deletions/duplications, and loss of heterozygosity were elevated compared with that in untreated cells. 5-HMF exposure had a mild impact on the rate of point mutations but altered the mutation spectrum. Contrary to what was observed in untreated cells, more monosomy than trisomy occurred in 5-HMF-treated cells. The aneuploidy mutant with monosomic chromosome IX was more resistant to 5-HMF than the diploid parent strain because of the enhanced activity of alcohol dehydrogenase. Finally, we found that overexpression of ADH6 and ZWF1 effectively stabilized the yeast genome under 5-HMF stress. Our findings not only elucidated the global effect of 5-HMF on the genomic integrity of yeast but also provided novel insights into how chromosomal instability drives the environmental adaptability of eukaryotic cells.IMPORTANCESingle-cell microorganisms are exposed to a range of stressors in both natural and industrial settings. This study investigated the effects of 5-hydroxymethfurural (5-HMF), a major inhibitor found in baked foods and lignocellulosic hydrolysates, on the chromosomal instability of yeast. We examined the mechanisms leading to the distinct patterns of 5-HMF-induced genomic alterations and discovered that chromosomal loss, typically viewed as detrimental to cell growth under most conditions, can contribute to yeast tolerance to 5-HMF. Our results increased the understanding of how specific stressors stimulate genomic plasticity and environmental adaptation in yeast.

Early identification of postoperative remission for thyrotropin-secreting adenomas.

OBJECTIVE: Thyrotropin-secreting adenoma (TSHoma) is a rare type of pituitary adenoma, occurring in one per million people. Little is known about TSHoma. We summarized the demographic, clinical and hormonal characteristics of TSHoma based on a single-centre experience. Moreover, we explored the predictive value of postoperative thyroid function for long-term remission. DESIGN, PATIENTS AND MEASUREMENTS: We retrospectively analysed 63 patients who were diagnosed as TSHoma and surgically treated at our hospital from January 2015 to June 2021. The preoperative clinical characteristics were analysed and compared between remission and nonremission groups. Thyroid function was measured at 1 day, 1 month, 3 months, 6 months, 12 months and over 12 months after surgery to determine whether they could predict long-term remission. RESULTS: The male to female ratio for TSHoma was 1.25. The mean age at diagnosis was 45 ± 12 years. Clinical presentation was varied, presenting with hyperthyroidism (68.25%), space-occupying effect (15.87%), amenorrhea (7.14% of female patients) and nonsymptoms (22.22%). 88.14% of patients achieved postoperative endocrinological remission. Larger tumour size and tumour invasion into cavernous sinus and suprasellar with chiasmal compression were strong predictors of lower rates of endocrinological remission. Postoperative thyroid function at 3 months was a viable diagnostic predictor for postoperative remission, especially for FT4 level with a 20.65 pmol/L cutoff. CONCLUSIONS: Tumour size and extent are major prognostic factors for remission. Postoperative thyroid function at 3 months could be used as a clinical prediction tool for long-term endocrinological remission.

Ethanol responsive lnc171 promotes migration and invasion of HCC cells via mir-873-5p/ZEB1 axis.

BACKGROUNDS: Long nonconding RNAs (lncRNAs) have been found to be a vital regulatory factor in the development process of human cancer, and could regarded as diagnostic or prognostic biomarkers for human cancers. Here, we aim to confirm the expression and molecular mechanism of RP11-171K16.5 (lnc171) in hepatocellular carcinoma (HCC). METHODS: Screening of differentially expressed lncRNAs by RNA sequencing. Expression level of gene was studied by quantitative real-time PCR (qRT-PCR). The effects of lnc171, mir-873-5p, and ethanol on migration and invasion activity of cells were studied used transwell assay, and luciferase reporter assay was used to confirm the binding site. RESULTS: RNA sequencing showed that lnc171 was markedly up-regulated in HCC. siRNA-mediated knockdown of lnc171 repressed the migration and invasion ability of HCC cells. Bioinformatic analysis, dual luciferase reporter assay, and qRT-PCR indicated that lnc171 interacted with mir-873-5p in HCC cells, and Zin-finger E-box binding homeobox (ZEB1) was a downstream target gene of mir-873-5p. In addition, lnc171 could enhance migration and invasion ability of HCC cells by up-regulating ZEB1 via sponging mir-873-5p. More interestingly, ethanol stimulation could up-regulate the increase of lnc171, thereby regulating the expression of competing endogenous RNA (ceRNA) network factors which lnc171 participated in HCC cells. CONCLUSIONS: Our date demonstrates that lnc171 was a responsive factor of ethanol, and plays a vital role in development of HCC via binding of mir-873-5p.

Choline supplementation mitigates effects of bilirubin in cerebellar granule neurons in vitro.

BACKGROUND: Premature infants may suffer from high levels of bilirubin that could lead to neurotoxicity. Bilirubin has been shown to decrease L1-mediated ERK1/2 signaling, L1 phosphorylation, and L1 tyrosine 1176 dephosphorylation. Furthermore, bilirubin redistributes L1 into lipid rafts (LR) and decreases L1-mediated neurite outgrowth. We demonstrate that choline supplementation improves L1 function and signaling in the presence of bilirubin. METHODS: Cerebellar granule neurons (CGN) were cultured with and without supplemental choline, and the effects on L1 signaling and function were measured in the presence of bilirubin. L1 activation of ERK1/2, L1 phosphorylation and dephosphorylation were measured. L1 distribution in LR was quantified and neurite outgrowth of CGN was determined. RESULTS: Forty µM choline significantly reduced the effect of bilirubin on L1 activation of ERK1/2 by 220% (p = 0.04), and increased L1 triggered changes in tyrosine phosphorylation /dephosphorylation of L1 by 34% (p = 0.026) and 35% (p = 0.02) respectively. Choline ameliorated the redistribution of L1 in lipid rafts by 38% (p = 0.02) and increased L1-mediated mean neurite length by 11% (p = 0.04). CONCLUSION: Choline pretreatment of CGN significantly reduced the disruption of L1 function by bilirubin. The supplementation of pregnant women and preterm infants with choline may increase infant resilience to the effects of bilirubin. IMPACT: This article establishes choline as an intervention for the neurotoxic effects of bilirubin on lipid rafts. This article provides clear evidence toward establishing one intervention for bilirubin neurotoxicity, where little is understood. This article paves the way for future investigation into the mechanism of the ameliorative effect of choline on bilirubin neurotoxicity.

Quantitative multi-parameter assessment of age- and gender-related variation of back extensor muscles in healthy adults using Dixon MR imaging.

OBJECTIVES: Investigate sex differences in age-related back extensor muscle degeneration using Dixon MRI and analyze the relationship between quantitative muscle parameters and back muscle strength in healthy adults. METHODS: 105 healthy subjects underwent lumbar Dixon MRI. Fat fraction (FF), cross-sectional area (CSA), functional CSA (FCSA), and relative FCSA (RFCSA) of multifidus muscle (MF) and erector spinae (ES) were quantified. Back extension muscle strength was measured using an external fixation dynamometer. ANOVA with post hoc Tukey correction was used for age group comparisons. Partial and Spearman's correlation analyzed relationships between age, muscle parameters, and muscle strength. RESULTS: MF and ES FF significantly increased with age in both genders (r = 0.55-0.85; p < 0.001). Muscle FF increased prominently for females (40-49 years, MF and 50-59 years, ES) and males (60-73 years, MF and ES). In females, total ES FCSA and RFCSA (r = - 0.42, - 0.37; p < 0.01) correlated with age. While in males, all MF and ES muscle size parameters, except total MF CSA, correlated with age (r = - 0.30 to - 0.58; p < 0.05). Back extension muscle strength correlated with mean FF, total CSA, and total FCAS for MF and ES individually (p < 0.001). The combined MF + ES FCSA correlation coefficient (r = 0.63) was higher than FF (r = - 0.51) and CSA (r = 0.59) (p < 0.001). CONCLUSIONS: Age-related back extensor muscle degeneration varies by muscle type and sex. FCSA has the highest association with back muscle strength compared to FF and CSA. CLINICAL RELEVANCE STATEMENT: The investigation of sex differences in age-related back extensor muscle degeneration utilizing Dixon imaging may hold significant implications for evaluating spine health and enabling earlier intervention. Muscles' FCSA could contribute to acquiring additional evidence for reflecting muscle function change. KEY POINTS: • The multifidus muscle (MF) and erector spinae (ES) fat fraction (FF) increased with age at all lumbar disc levels in females and males. • Age-related changes in muscle morphological quantitative parameters of healthy adults were specific by muscle type and gender. • The muscle functional cross-sectional area (FCSA) measured by Dixon imaging may better monitor back extensor muscle strength changes than muscle FF and cross-sectional area (CSA).

Imbalance of T follicular helper cell subsets trigger the differentiation of pathogenic B cells in idiopathic membranous nephropathy.

OBJECTIVE: This study aims to elucidate the role of T follicular helper (Tfh) cells and their subsets in idiopathic membranous nephropathy (IMN). METHODS: The frequencies of Tfh cell subsets and B cell subsets in peripheral blood (PB) were detected in both IMN patients and healthy controls (HCs). The involvement of Tfh cells in the disease pathogenesis was examined by coculturing human Tfh cells with B cells. The dynamic changes of Tfh cells in PB or spleen were monitored in passive Heymann nephritis (PHN) rats. RESULTS: The frequencies of circulating Tfh (cTfh) cells, cTfh2 cells, and plasmablasts were enriched in the PB of patients with IMN. cTfh cells expressed higher ICOS, and lower BTLA than healthy counterparts. The frequency of ICOS + cTfh2 was associated with the severity of IMN, including 24h urine protein, IgG4 concentration and the IgG4: IgG ratio. Positive correlations were also observed between the frequency of cTfh2 cells with plasmablasts, serum IL-21 and IL-4 levels. Importantly, cTfh cells isolated from IMN patients were able to induce the differentiation of B cells to memory B cells (MBC) and plasmablasts, this process could be substantially attenuated by blocking the IL-21. Similar increases of ICOS + cTfh cells were also detected in spleen of PHN rats, concomitant with elevated urine protein levels. CONCLUSIONS: Collectively, our results demonstrate that the imbalance of cTfh cell subsets play a crucial pathogenic role in IMN by inducing the differentiation of B cells through IL-21, and cTfh2 cells might serve as useful markers to evaluate the progression of IMN.

Radiofrequency radiation reshapes tumor immune microenvironment into antitumor phenotype in pulmonary metastatic melanoma by inducing active transformation of tumor-infiltrating CD8+ T and NK cells.

Immunosuppression by the tumor microenvironment is a pivotal factor contributing to tumor progression and immunotherapy resistance. Priming the tumor immune microenvironment (TIME) has emerged as a promising strategy for improving the efficacy of cancer immunotherapy. In this study we investigated the effects of noninvasive radiofrequency radiation (RFR) exposure on tumor progression and TIME phenotype, as well as the antitumor potential of PD-1 blockage in a model of pulmonary metastatic melanoma (PMM). Mouse model of PMM was established by tail vein injection of B16F10 cells. From day 3 after injection, the mice were exposed to RFR at an average specific absorption rate of 9.7 W/kg for 1 h per day for 14 days. After RFR exposure, lung tissues were harvested and RNAs were extracted for transcriptome sequencing; PMM-infiltrating immune cells were isolated for single-cell RNA-seq analysis. We showed that RFR exposure significantly impeded PMM progression accompanied by remodeled TIME of PMM via altering the proportion and transcription profile of tumor-infiltrating immune cells. RFR exposure increased the activation and cytotoxicity signatures of tumor-infiltrating CD8+ T cells, particularly in the early activation subset with upregulated genes associated with T cell cytotoxicity. The PD-1 checkpoint pathway was upregulated by RFR exposure in CD8+ T cells. RFR exposure also augmented NK cell subsets with increased cytotoxic characteristics in PMM. RFR exposure enhanced the effector function of tumor-infiltrating CD8+ T cells and NK cells, evidenced by increased expression of cytotoxic molecules. RFR-induced inhibition of PMM growth was mediated by RFR-activated CD8+ T cells and NK cells. We conclude that noninvasive RFR exposure induces antitumor remodeling of the TIME, leading to inhibition of tumor progression, which provides a promising novel strategy for TIME priming and potential combination with cancer immunotherapy.

Disrupted brain gray matter connectome in social anxiety disorder: a novel individualized structural covariance network analysis.

Phenotyping approaches grounded in structural network science can offer insights into the neurobiological substrates of psychiatric diseases, but this remains to be clarified at the individual level in social anxiety disorder (SAD). Using a recently developed approach combining probability density estimation and Kullback-Leibler divergence, we constructed single-subject structural covariance networks (SCNs) based on multivariate morphometry (cortical thickness, surface area, curvature, and volume) and quantified their global/nodal network properties using graph-theoretical analysis. We compared network metrics between SAD patients and healthy controls (HC) and analyzed the relationship to clinical characteristics. We also used support vector machine analysis to explore the ability of graph-theoretical metrics to discriminate SAD patients from HC. Globally, SAD patients showed higher global efficiency, shorter characteristic path length, and stronger small-worldness. Locally, SAD patients showed abnormal nodal centrality mainly involving left superior frontal gyrus, right superior parietal lobe, left amygdala, right paracentral gyrus, right lingual, and right pericalcarine cortex. Altered topological metrics were associated with the symptom severity and duration. Graph-based metrics allowed single-subject classification of SAD versus HC with total accuracy of 78.7%. This finding, that the topological organization of SCNs in SAD patients is altered toward more randomized configurations, adds to our understanding of network-level neuropathology in SAD.

Risk assessment and prediction of occult uterine sarcoma in patients with presumed uterine fibroids before high-intensity focused ultrasound treatment.

OBJECTIVE: To develop a diagnostic model for predicting occult uterine sarcoma in patients with presumed uterine fibroids. MATERIALS AND METHODS: We retrospectively reviewed 41631 patients with presumed uterine fibroids who presented for HIFU treatment in 13 hospitals between November 2008 and October 2023. Of these patients, 27 with occult uterine sarcoma and 54 with uterine fibroids were enrolled. Univariate analysis and multivariate logistics regression analysis were used to determine the independent risk factors for the diagnosis of occult uterine sarcoma. A prediction model was constructed based on the coefficients of the risk factors. RESULTS: The multivariate analysis revealed abnormal vaginal bleeding, ill-defined boundary of tumor, hyperintensity on T2WI, and central unenhanced areas as independent risk factors. A scoring system was created to assess for occult uterine sarcoma risk. The score for abnormal vaginal bleeding was 56. The score for ill-defined lesion boundary was 90. The scores for lesions with hypointensity, isointensity signal/heterogeneous signal intensity, and hyperintensity on T2WI were 0, 42, and 93, respectively. The scores for lesions without enhancement on the mass margin, uniform enhancement of tumor, and no enhancement in the center of tumor were 0, 20, and 100, respectively. Patients with a higher total score implied a higher likelihood of a diagnosis of occult uterine sarcoma than that of patients with a lower score. The established model showed good predictive efficacy. CONCLUSIONS: Our results demonstrated that the diagnostic prediction model can be used to evaluate the risk of uterine sarcoma in patients with presumed uterine fibroids.

A novel scoring system based on magnetic resonance imaging for the prediction of the difficulty of ultrasound-guided high-intensity focused ultrasound ablation for uterine fibroids.

OBJECTIVE: To develop a novel scoring system based on magnetic resonance imaging (MRI) for predicting the difficulty of ultrasound-guided high-intensity focused ultrasound (USgHIFU) ablation for uterine fibroids. MATERIALS AND METHODS: A total of 637 patients with uterine fibroids were enrolled. Sonication time, non-perfused volume ratio (NPVR), and ultrasound energy delivered for ablating 1 mm3 of fibroid tissue volume (E/V) were each classified as three levels and assigned scores from 0 to 2, respectively. Treatment difficulty level was then assessed by adding up the scores of sonication time, NPVR and E/V for each patient. The patients with score lower than 3 were categorized into low difficulty group, with score equal to or greater than 3 were categorized into high difficulty group. The potential predictors for treatment difficulty were compared between the two groups. Multifactorial logistic regression analysis model was created by analyzing the variables. The difficulty score system was developed using the beta coefficients of the logistic model. RESULTS: Signal intensity on T2WI, fibroid location index, largest diameter of fibroids, abdominal wall thickness, homogeneity of the signal of fibroids, and uterine position were independent influencing factors for the difficulty of USgHIFU for uterine fibroids. A prediction equation was obtained: difficulty score = 17 × uterine position (anteverted =0, retroverted =1)+71 × signal intensity (hypointense = 0, isointense/hyperintense = 1) +8 × enhancement (homogenous = 0, heterogeneous = 1)+25×(largest diameter of fibroids-20) +35 × (fibroid location index -0.2) +1×(abdominal wall thickness -5). CONCLUSIONS: This scoring system established based on MRI findings can be used to reliably predict the difficulty level of USgHIFU treatment of uterine fibroids.