The receptor binding domain of SARS-CoV-2 Omicron subvariants targets Siglec-9 to decrease its immunogenicity by preventing macrophage phagocytosis.

The development of a vaccine specific to severe acute respiratory syndrome coronavirus 2 Omicron has been hampered due to its low immunogenicity. Here, using reverse mutagenesis, we found that a phenylalanine-to-serine mutation at position 375 (F375S) in the spike protein of Omicron to revert it to the sequence found in Delta and other ancestral strains significantly enhanced the immunogenicity of Omicron vaccines. Sequence FAPFFAF at position 371-377 in Omicron spike had a potent inhibitory effect on macrophage uptake of receptor-binding domain (RBD) nanoparticles or spike-pseudovirus particles containing this sequence. Omicron RBD enhanced binding to Siglec-9 on macrophages to impair phagocytosis and antigen presentation and promote immune evasion, which could be abrogated by the F375S mutation. A bivalent F375S Omicron RBD and Delta-RBD nanoparticle vaccine elicited potent and broad nAbs in mice, rabbits and rhesus macaques. Our research suggested that manipulation of the Siglec-9 pathway could be a promising approach to enhance vaccine response.

Spatiotemporal trends of hemorrhagic fever with renal syndrome (HFRS) in China under climate variation.

Hemorrhagic fever with renal syndrome (HFRS) is a zoonotic disease caused by the rodent-transmitted orthohantaviruses (HVs), with China possessing the most cases globally. The virus hosts in China are Apodemus agrarius and Rattus norvegicus, and the disease spread is strongly influenced by global climate dynamics. To assess and predict the spatiotemporal trends of HFRS from 2005 to 2098, we collected historical HFRS data in mainland China (2005-2020), historical and projected climate and population data (2005-2098), and spatial variables including biotic, environmental, topographical, and socioeconomic. Spatiotemporal predictions and mapping were conducted under 27 scenarios incorporating multiple integrated representative concentration pathway models and population scenarios. We identify the type of magistral HVs host species as the best spatial division, including four region categories. Seven extreme climate indices associated with temperature and precipitation have been pinpointed as key factors affecting the trends of HFRS. Our predictions indicate that annual HFRS cases will increase significantly in 62 of 356 cities in mainland China. Rattus regions are predicted to be the most active, surpassing Apodemus and Mixed regions. Eighty cities are identified as at severe risk level for HFRS, each with over 50 reported cases annually, including 22 new cities primarily located in East China and Rattus regions after 2020, while 6 others develop new risk. Our results suggest that the risk of HFRS will remain high through the end of this century, with Rattus norvegicus being the most active host, and that extreme climate indices are significant risk factors. Our findings can inform evidence-based policymaking regarding future risk of HFRS.

Improving multi-population genomic prediction accuracy using multi-trait GBLUP models which incorporate global or local genetic correlation information.

In the application of genomic prediction, a situation often faced is that there are multiple populations in which genomic prediction (GP) need to be conducted. A common way to handle the multi-population GP is simply to combine the multiple populations into a single population. However, since these populations may be subject to different environments, there may exist genotype-environment interactions which may affect the accuracy of genomic prediction. In this study, we demonstrated that multi-trait genomic best linear unbiased prediction (MTGBLUP) can be used for multi-population genomic prediction, whereby the performances of a trait in different populations are regarded as different traits, and thus multi-population prediction is regarded as multi-trait prediction by employing the between-population genetic correlation. Using real datasets, we proved that MTGBLUP outperformed the conventional multi-population model that simply combines different populations together. We further proposed that MTGBLUP can be improved by partitioning the global between-population genetic correlation into local genetic correlations (LGC). We suggested two LGC models, LGC-model-1 and LGC-model-2, which partition the genome into regions with and without significant LGC (LGC-model-1) or regions with and without strong LGC (LGC-model-2). In analysis of real datasets, we demonstrated that the LGC models could increase universally the prediction accuracy and the relative improvement over MTGBLUP reached up to 163.86% (25.64% on average).

scATAC-Ref: a reference of scATAC-seq with known cell labels in multiple species.

Chromatin accessibility profiles at single cell resolution can reveal cell type-specific regulatory programs, help dissect highly specialized cell functions and trace cell origin and evolution. Accurate cell type assignment is critical for effectively gaining biological and pathological insights, but is difficult in scATAC-seq. Hence, by extensively reviewing the literature, we designed scATAC-Ref (https://bio.liclab.net/scATAC-Ref/), a manually curated scATAC-seq database aimed at providing a comprehensive, high-quality source of chromatin accessibility profiles with known cell labels across broad cell types. Currently, scATAC-Ref comprises 1 694 372 cells with known cell labels, across various biological conditions, >400 cell/tissue types and five species. We used uniform system environment and software parameters to perform comprehensive downstream analysis on these chromatin accessibility profiles with known labels, including gene activity score, TF enrichment score, differential chromatin accessibility regions, pathway/GO term enrichment analysis and co-accessibility interactions. The scATAC-Ref also provided a user-friendly interface to query, browse and visualize cell types of interest, thereby providing a valuable resource for exploring epigenetic regulation in different tissues and cell types.

A vitamin-C-derived DNA modification catalysed by an algal TET homologue.

Methylation of cytosine to 5-methylcytosine (5mC) is a prevalent DNA modification found in many organisms. Sequential oxidation of 5mC by ten-eleven translocation (TET) dioxygenases results in a cascade of additional epigenetic marks and promotes demethylation of DNA in mammals1,2. However, the enzymatic activity and function of TET homologues in other eukaryotes remains largely unexplored. Here we show that the green alga Chlamydomonas reinhardtii contains a 5mC-modifying enzyme (CMD1) that is a TET homologue and catalyses the conjugation of a glyceryl moiety to the methyl group of 5mC through a carbon-carbon bond, resulting in two stereoisomeric nucleobase products. The catalytic activity of CMD1 requires Fe(II) and the integrity of its binding motif His-X-Asp, which is conserved in Fe-dependent dioxygenases3. However, unlike previously described TET enzymes, which use 2-oxoglutarate as a co-substrate4, CMD1 uses L-ascorbic acid (vitamin C) as an essential co-substrate. Vitamin C donates the glyceryl moiety to 5mC with concurrent formation of glyoxylic acid and CO2. The vitamin-C-derived DNA modification is present in the genome of wild-type C. reinhardtii but at a substantially lower level in a CMD1 mutant strain. The fitness of CMD1 mutant cells during exposure to high light levels is reduced. LHCSR3, a gene that is critical for the protection of C. reinhardtii from photo-oxidative damage under high light conditions, is hypermethylated and downregulated in CMD1 mutant cells compared to wild-type cells, causing a reduced capacity for photoprotective non-photochemical quenching. Our study thus identifies a eukaryotic DNA base modification that is catalysed by a divergent TET homologue and unexpectedly derived from vitamin C, and describes its role as a potential epigenetic mark that may counteract DNA methylation in the regulation of photosynthesis.

Potential causal links of long-term exposure to PM2.5 and its chemical components with the risk of nasopharyngeal carcinoma recurrence: A 10-year cohort study in South China.

There is a lack of evidence from cohort studies on the causal association of long-term exposure to ambient fine particulate matter (PM2.5) and its chemical components with the risk of nasopharyngeal carcinoma (NPC) recurrence. Based on a 10-year prospective cohort of 1184 newly diagnosed NPC patients, we comprehensively evaluated the potential causal links of ambient PM2.5 and its chemical components including black carbon (BC), organic matter (OM), sulfate (SO4 2-), nitrate (NO3 -), and ammonium (NH4 +) with the recurrence risk of NPC using a marginal structural Cox model adjusted with inverse probability weighting. We observed 291 NPC patients experiencing recurrence during the 10-year follow-up and estimated a 33% increased risk of NPC recurrence (hazard ratio [HR]: 1.33, 95% confidence interval [CI]: 1.02-1.74) following each interquartile range (IQR) increase in PM2.5 exposure. Each IQR increment in BC, NH4 +, OM, NO3 -, and SO4 2- was associated with HRs of 1.36 (95%CI: 1.13-1.65), 1.35 (95%CI: 1.07-1.70), 1.33 (95%CI: 1.11-1.59), 1.32 (95%CI: 1.06-1.64), 1.31 (95%CI: 1.08-1.57). The elderly, patients with no family history of cancer, no smoking history, no drinking history, and those with severe conditions may exhibit a greater likelihood of NPC recurrence following exposure to PM2.5 and its chemical components. Additionally, the effect estimates of the five components are greater among patients who were exposed to high concentration than in the full cohort of patients. Our study provides solid evidence for a potential relationship between long-term exposure to PM2.5 and its components and the risk of NPC recurrence.

Salivary Extracellular MicroRNAs for Early Detection and Prognostication of Esophageal Cancer: A Clinical Study.

BACKGROUND & AIMS: Early detection of esophageal squamous cell carcinoma (ESCC) will facilitate curative treatment. We aimed to establish a microRNA (miRNA) signature derived from salivary extracellular vesicles and particles (EVPs) for early ESCC detection and prognostication. METHODS: Salivary EVP miRNA expression was profiled in a pilot cohort (n = 54) using microarray. Area under the receiver operator characteristic curve (AUROC) and least absolute shrinkage and selector operation regression analyses were used to prioritize miRNAs that discriminated patients with ESCC from controls. Using quantitative reverse transcription polymerase chain reaction, the candidates were measured in a discovery cohort (n = 72) and cell lines. The prediction models for the biomarkers were derived from a training cohort (n = 342) and validated in an internal cohort (n = 207) and an external cohort (n = 226). RESULTS: The microarray analysis identified 7 miRNAs for distinguishing patients with ESCC from control subjects. Because 1 was not always detectable in the discovery cohort and cell lines, the other 6 miRNAs formed a panel. A signature of this panel accurately identified patients with all-stage ESCC in the training cohort (AUROC = 0.968) and was successfully validated in 2 independent cohorts. Importantly, this signature could distinguish patients with early-stage (stage Ⅰ/Ⅱ) ESCC from control subjects in the training cohort (AUROC = 0.969, sensitivity = 92.00%, specificity = 89.17%) and internal (sensitivity = 90.32%, specificity = 91.04%) and external (sensitivity = 91.07%, specificity = 88.06%) validation cohorts. Moreover, a prognostic signature based on the panel was established and efficiently predicted the high-risk cases with poor progression-free survival and overall survival. CONCLUSIONS: The salivary EVP-based 6-miRNA signature can serve as noninvasive biomarkers for early detection and risk stratification of ESCC. Chinese Clinical Trial Registry, ChiCTR2000031507.

Patch-Based Convolutional Encoder: A Deep Learning Algorithm for Spectral Classification Balancing the Local and Global Information.

Molecular vibrational spectroscopies, including infrared absorption and Raman scattering, provide molecular fingerprint information and are powerful tools for qualitative and quantitative analysis. They benefit from the recent development of deep-learning-based algorithms to improve the spectral, spatial, and temporal resolutions. Although a variety of deep-learning-based algorithms, including those to simultaneously extract the global and local spectral features, have been developed for spectral classification, the classification accuracy is still far from satisfactory when the difference becomes very subtle. Here, we developed a lightweight algorithm named patch-based convolutional encoder (PACE), which effectively improved the accuracy of spectral classification by extracting spectral features while balancing local and global information. The local information was captured well by segmenting the spectrum into patches with an appropriate patch size. The global information was extracted by constructing the correlation between different patches with depthwise separable convolutions. In the five open-source spectral data sets, PACE achieved a state-of-the-art performance. The more difficult the classification, the better the performance of PACE, compared with that of residual neural network (ResNet), vision transformer (ViT), and other commonly used deep learning algorithms. PACE helped improve the accuracy to 92.1% in Raman identification of pathogen-derived extracellular vesicles at different physiological states, which is much better than those of ResNet (85.1%) and ViT (86.0%). In general, the precise recognition and extraction of subtle differences offered by PACE are expected to facilitate vibrational spectroscopy to be a powerful tool toward revealing the relevant chemical reaction mechanisms in surface science or realizing the early diagnosis in life science.

Vec2image: an explainable artificial intelligence model for the feature representation and classification of high-dimensional biological data by vector-to-image conversion.

Feature representation and discriminative learning are proven models and technologies in artificial intelligence fields; however, major challenges for machine learning on large biological datasets are learning an effective model with mechanistical explanation on the model determination and prediction. To satisfy such demands, we developed Vec2image, an explainable convolutional neural network framework for characterizing the feature engineering, feature selection and classifier training that is mainly based on the collaboration of principal component coordinate conversion, deep residual neural networks and embedded k-nearest neighbor representation on pseudo images of high-dimensional biological data, where the pseudo images represent feature measurements and feature associations simultaneously. Vec2image has achieved better performance compared with other popular methods and illustrated its efficiency on feature selection in cell marker identification from tissue-specific single-cell datasets. In particular, in a case study on type 2 diabetes (T2D) by multiple human islet scRNA-seq datasets, Vec2image first displayed robust performance on T2D classification model building across different datasets, then a specific Vec2image model was trained to accurately recognize the cell state and efficiently rank feature genes relevant to T2D which uncovered potential T2D cellular pathogenesis; and next the cell activity changes, cell composition imbalances and cell-cell communication dysfunctions were associated to our finding T2D feature genes from both population-shared and individual-specific perspectives. Collectively, Vec2image is a new and efficient explainable artificial intelligence methodology that can be widely applied in human-readable classification and prediction on the basis of pseudo image representation of biological deep sequencing data.

KMCP: accurate metagenomic profiling of both prokaryotic and viral populations by pseudo-mapping.

MOTIVATION: The growing number of microbial reference genomes enables the improvement of metagenomic profiling accuracy but also imposes greater requirements on the indexing efficiency, database size and runtime of taxonomic profilers. Additionally, most profilers focus mainly on bacterial, archaeal and fungal populations, while less attention is paid to viral communities. RESULTS: We present KMCP (K-mer-based Metagenomic Classification and Profiling), a novel k-mer-based metagenomic profiling tool that utilizes genome coverage information by splitting the reference genomes into chunks and stores k-mers in a modified and optimized Compact Bit-Sliced Signature Index for fast alignment-free sequence searching. KMCP combines k-mer similarity and genome coverage information to reduce the false positive rate of k-mer-based taxonomic classification and profiling methods. Benchmarking results based on simulated and real data demonstrate that KMCP, despite a longer running time than all other methods, not only allows the accurate taxonomic profiling of prokaryotic and viral populations but also provides more confident pathogen detection in clinical samples of low depth. AVAILABILITY AND IMPLEMENTATION: The software is open-source under the MIT license and available at https://github.com/shenwei356/kmcp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Vasomotion heterogeneity and spectral characteristics in diabetic and hypertensive patients.

Vasomotion refers to the spontaneous oscillation of blood vessels within a frequency range of 0.01 to 1.6 Hz. Various disease states, including hypertension and diabetes, have been associated with alterations in vasomotion at the finger, indicating potential impairment of skin microcirculation. Due to the non-linear nature of human vasculature, the modification of vasomotion may vary across different locations for different diseases. In this study, Laser Doppler Flowmetry was used to measure blood flow motion at acupoints LU8, LU5, SP6, and PC3 among 49 participants with or without diabetes and/or hypertension. Fast Fourier Transformation was used to analyze noise type while Hilbert-Huang Transformation and wavelet analysis were applied to assess Signal Noise Ratio (SNR) results. Statistical analysis revealed that different acupoints exhibit distinct spectral characteristics of vasomotion not only among healthy individuals but also among patients with diabetes and/or hypertension. The results showed strong heterogeneity of vasomotion among blood vessels, indicating that the vasomotion measured at a certain point may not reflect the real status of microcirculation.

Effect of Hypoxia Preconditioning on the Regenerative Capacity of Adipose Tissue Derived Mesenchymal Stem Cells in a Model of Renal Artery Stenosis.

Atherosclerotic renal artery stenosis (ARAS) is associated with irreversible parenchymal renal disease and regenerative stem cell therapies may improve renal outcomes. Hypoxia preconditioning (HPC) may improve the regenerative functions of adipose tissue-derived mesenchymal stem cells (AMSC) by affecting DNA 5-hydroxymethylcytosine (5hmC) marks in angiogenic genes. Here, we investigated using a porcine ARAS model, whether growth of ARAS AMSCs in hypoxia (Hx) versus normoxia (Nx) would enhance renal tissue repair, and comprehensively analyze how HPC modifies DNA hydroxymethylation compared to untreated ARAS and healthy/normal pigs (n=5 each). ARAS pigs exhibited elevated serum cholesterol, serum creatinine and renal artery stenosis, with a concomitant decrease in renal blood flow (RBF) and increased blood pressure (BP) compared to healthy pigs. Renal artery injection of either autologous Nx or Hx AMSCs improved diastolic BP, reduced kidney tissue fibrosis, and inflammation (CD3+ T-cells) in ARAS pigs. In addition, renal medullary hypoxia significantly lowered with Nx but not Hx AMSC treatment. Mechanistically, levels of epigenetic 5hmC marks (which reflect gene activation) estimated using DNA immunoprecipitation technique were elevated in profibrotic and inflammatory genes in ARAS compared with normal AMSCs. HPC significantly reduced 5hmC levels in cholesterol biosynthesis and oxidative stress response pathways in ARAS AMSCs. Thus, autologous AMSCs improve key renovascular parameters and inflammation in ARAS pigs, with HPC mitigating pathological molecular effects on inflammatory and profibrotic genes which may play a role in augmenting regenerative capacity of AMSCs.

Ferrostatin 1 ameliorates UVB-induced damage of HaCaT cells by regulating ferroptosis.

Ferroptosis, a type of programmed cell death, occurs when there is oxidative stress and lipid peroxides. This condition is marked by lipid peroxidation that relies on iron and the reduction of cellular defences against oxidation. To investigate the effect of UVB irradiation on ferroptosis of human keratinocytes HaCaT cells, the cells were pretreated with Ferrostatin 1 (Fer-1, 10 µM), an ferroptosis inhibitor and then irradiated with UVB (20 mJ/cm2 ) for 30 min to detect related indexes of ferroptosis through MTT assay, quantitative real-time polymerase chain reaction, flow cytometry, reactive oxygen species (ROS) assay, western blotting. Results showed that UVB significantly reduced cell activity, promoted apoptosis and ROS level, whereas Fer-1 significantly increased cell activity, and reduced apoptosis and ROS level. In addition, UVB significantly reduced levels of ferroptosis-related proteins and skin barrier-related proteins, and increased levels of γ-H2AX and iron, whereas Fer-1 significantly increased their protein levels, and reduced levels of γ-H2AX and iron. Conjoint analysis of transcriptomic and proteomic revealed that UVB significantly reduced the levels of TIMP metallopeptidase inhibitor 3 (TIMP3), and coagulation factor II thrombin receptor (F2R), whereas Fer-1 significantly promoted the levels of TIMP3, and F2R. Therefore, our results indicated that Fer-1 significantly ameliorates UVB-induced damage of HaCaT cells by regulating the levels of TIMP3 and F2R.

Integrating TSPO PET imaging and transcriptomics to unveil the role of neuroinflammation and amyloid-ß deposition in Alzheimer's disease.

PURPOSE: Despite the revealed role of immunological dysfunctions in the development and progression of Alzheimer's disease (AD) through animal and postmortem investigations, direct evidence regarding the impact of genetic factors on microglia response and amyloid-ß (Aß) deposition in AD individuals is lacking. This study aims to elucidate this mechanism by integrating transcriptomics and TSPO, Aß PET imaging in clinical AD cohort. METHODS: We analyzed 85 patients with PET/MR imaging for microglial activation (TSPO, [18F]DPA-714) and Aß ([18F]AV-45) within the prospective Alzheimer's Disease Immunization and Microbiota Initiative Study Cohort (ADIMIC). Immune-related differentially expressed genes (IREDGs), identified based on AlzData, were screened and verified using blood samples from ADIMIC. Correlation and mediation analyses were applied to investigate the relationships between immune-related genes expression, TSPO and Aß PET imaging. RESULTS: TSPO uptake increased significantly both in aMCI (P < 0.05) and AD participants (P < 0.01) and showed a positive correlation with Aß deposition (r = 0.42, P < 0.001). Decreased expression of TGFBR3, FABP3, CXCR4 and CD200 was observed in AD group. CD200 expression was significantly negatively associated with TSPO PET uptake (r =-0.33, P = 0.013). Mediation analysis indicated that CD200 acted as a significant mediator between TSPO uptake and Aß deposition (total effect B = 1.92, P = 0.004) and MMSE score (total effect B =-54.01, P = 0.003). CONCLUSION: By integrating transcriptomics and TSPO PET imaging in the same clinical AD cohort, this study revealed CD200 played an important role in regulating neuroinflammation, Aß deposition and cognitive dysfunction.

Serotonin/5-HT7 receptor provides an adaptive signal to enhance pigmentation response to environmental stressors through cAMP-PKA-MAPK, Rab27a/RhoA, and PI3K/AKT signaling pathways.

Serotonin (5-HT), a neurotransmitter, is essential for normal and pathological pigmentation processing, and its receptors may be therapeutical targets. The effect and behavior of the 5-HT7 receptor (5-HT7R) in melanogenesis in high vertebrates remain unknown. Herein, we examine the role and molecular mechanism of 5-HT7R in the pigmentation of human skin cells, human tissue, mice, and zebrafish models. Firstly, 5-HT7R protein expression decreased significantly in stress-induced depigmentation skin and vitiligo epidermis. Stressed mice received transdermal serotonin 5-HT7R selective agonists (LP-12, 0.01%) for 12 or 60 days. Mice might recover from persistent stress-induced depigmentation. The downregulation of tyrosinase (Tyr), microphthalmia-associated transcription factor (Mitf) expression, and 5-HT7R was consistently restored in stressed skin. High-throughput RNA sequencing showed that structural organization (dendrite growth and migration) and associated pathways were activated in the dorsal skin of LP-12-treated animals. 5-HT7R selective agonist, LP-12, had been demonstrated to enhance melanin production, dendrite growth, and chemotactic motility in B16F10 cells, normal human melanocytes (NHMCs), and zebrafish. Mechanistically, the melanogenic, dendritic, and migratory functions of 5-HT7R were dependent on the downstream signaling of cAMP-PKA-ERK1/2, JNK MAPK, RhoA/Rab27a, and PI3K/AKT pathway activation. Importantly, pharmacological inhibition and genetic siRNA of 5-HT7R by antagonist SB269970 partially/completely abolished these functional properties and the related activated pathways in both NHMCs and B16F10 cells. Consistently, htr7a/7b genetic knockdown in zebrafish could blockade melanogenic effects and abrogate 5-HT-induced melanin accumulation. Collectively, we have first identified that 5-HT7R regulates melanogenesis, which may be a targeted therapy for pigmentation disorders, especially those worsened by stress.

First detection of Tetraparvovirus ungulate 1 in diseased cattle (Chinese Simmental) from Hunan province, China.

Tetraparvovirus is an emerging parvovirus infecting a variety of mammals and humans, and associated with human diseases including severe acute respiratory infection and acute encephalitis syndrome. In the present study, a Tetraparvovirus ungulate 1 (formerly known as bovine hokovirus) strain HNU-CBY-2023 was identified and characterized from diseased Chinese Simmental from Hunan province, China. The nearly complete genome of HNU-CBY-2023 is 5346 nt in size and showed genomic identities of 85-95.5% to the known Tetraparvovirus ungulate 1 strains from GenBank, indicating a rather genetic variation. Phylogenetic and genetic divergence analyses indicated that Tetraparvovirus ungulate 1 could be divided into two genotypes (I and II), and HNU-CBY-2023 was clustered into genotype II. This study, for the first time, identified Tetraparvovirus ungulate 1 from domestic cattle from mainland China, which will be helpful to understand the prevalence and genetic diversity of Tetraparvovirus ungulate 1.

Optimizing timing for quantification of intracranial aneurysm enhancement: a multi-phase contrast-enhanced vessel wall MRI study.

OBJECTIVES: Aneurysm wall enhancement (AWE) on high-resolution contrast-enhanced vessel wall MRI (VWMRI) is an emerging biomarker for intracranial aneurysms (IAs) stability. Quantification methods of AWE in the literature, however, are variable. We aimed to determine the optimal post-contrast timing to quantify AWE in both saccular and fusiform IAs. MATERIALS AND METHODS: Consecutive patients with unruptured IAs were prospectively recruited. VWMRI was acquired on 1 pre-contrast and 4 consecutive post-contrast phases (each phase was 9 min). Signal intensity values of cerebrospinal fluid (CSF) and aneurysm wall on pre- and 4 post-contrast phases were measured to determine the aneurysm wall enhancement index (WEI). AWE was also qualitatively analyzed on post-contrast images using previous grading criteria. The dynamic changes of AWE grade and WEI were analyzed for both saccular and fusiform IAs. RESULTS: Thirty-four patients with 42 IAs (27 saccular IAs and 15 fusiform IAs) were included. The changes in AWE grade occurred in 8 (30%) saccular IAs and 6 (40%) in fusiform IAs during the 4 post-contrast phases. The WEI of fusiform IAs decreased 22.0% over time after contrast enhancement (p = 0.009), while the WEI of saccular IAs kept constant during the 4 post-contrast phases (p > 0.05). CONCLUSIONS: When performing quantitative analysis of AWE, acquiring post-contrast VWMRI immediately after contrast injection achieves the strongest AWE for fusiform IAs. While the AWE degree is stable for 36 min after contrast injection for saccular IAs. CLINICAL RELEVANCE STATEMENT: The standardization of imaging protocols and analysis methods for AWE will be helpful for imaging surveillance and further treatment decisions of patients with unruptured IAs. KEY POINTS: Imaging protocols and measurements of intracranial aneurysm wall enhancement are reported heterogeneously. Aneurysm wall enhancement for fusiform intracranial aneurysms (IAs) is strongest immediately post-contrast, and stable for 36 min for saccular IAs. Future multi-center studies should investigate aneurysm wall enhancement as an emerging marker of aneurysm growth and rupture.

N-3 PUFA supplementation alleviates anxiety symptoms by manipulating erythrocyte fatty acid levels in depression.

PURPOSE: Major depressive disorder (MDD) is frequently accompanied by the symptoms of clinical anxiety. Since our previous research has found that n-3 PUFA supplementation alleviates anxiety in MDD, this study was aimed to further explore whether n-3 PUFA supplementation improves anxiety symptoms in depression by directly manipulating fatty acid levels. METHODS: A secondary analysis of biomarker data (erythrocyte fatty acid composition) collected as part of the randomized clinical trial which investigated the adjunctive effect of n-3 PUFAs was conducted on 72 venlafaxine-treated outpatients with first-diagnosed, drug-naïve depression. All participants with longitudinal biomarker data were included in the association analysis to determine how n-3 PUFA supplementation influences fatty acid composition and alleviates anxiety symptoms in depression. RESULTS: Decreases of the C20:3n6 were found in all participants at both follow-up time points (χ2 = 96.36, p = 0.000). The n-3 index (χ2 = 10.59, p = 0.001), EPA (χ2 = 24.31, p = 0.000), and C22:5n3/C20:5n3 ratio (χ2 = 10.71, p = 0.001) were increased, while C22:4n6 (χ2 = 7.703, p = 0.006) was decreased in n-3 PUFA group compared to the placebo group. The improvement in anxiety symptoms positively correlates with the extent of reduction of C16:0, C18:0, and total fatty acid levels as well as D5 desaturase activity (p < 0.05). CONCLUSION: These data suggest that the anxiolytic effect exerted by n-3 PUFAs in first-diagnosed, drug-naïve depression is manipulated by erythrocyte fatty acid levels. Saturated fatty acid levels have an important role in predicting the severity of anxiety symptoms.

Effects of Guizhi and Erxian Decoction on menopausal hot flashes: insights from the gut microbiome and metabolic profiles.

AIMS: To examine the influence of GED on the gut microbiota and metabolites using a bilateral ovariectomized (OVX) rat model. We tried to elucidate the underlying mechanisms of GED in the treatment of menopausal hot flashes. METHODS AND RESULTS: 16S rRNA sequencing, metabonomics, molecular biological analysis, and fecal microbiota transplantation (FMT) were conducted to elucidate the mechanisms by which GED regulates the gut microbiota. GED significantly reduced OVX-induced hot flashes and improved disturbances in the gut microbiota metabolites. Moreover, FMT validated that the gut microbiota can trigger hot flashes, while GED can alleviate hot flash symptoms by modulating the composition of the gut microbiota. Specifically, GED upregulated the abundance of Blautia, thereby increasing l(+)-ornithine levels for the treatment of menopausal hot flashes. Additionally, GED affected endothelial nitric oxide synthase and heat shock protein 70 (HSP70) levels in the hypothalamic preoptic area by changing the gut microbiota composition. CONCLUSIONS: Our study illuminated the underlying mechanisms by which GED attenuated the hot flashes through modulation of the gut microbiota and explored the regulatory role of the gut microbiota on HSP70 expression in the preoptic anterior hypothalamus, thereby establishing a foundation for further exploration of the role of the gut-brain axis in hot flashes.

Exploring the latent cognitive structure in schizophrenia: implications for antipsychotic treatment responses.

BACKGROUND: Individuals diagnosed with schizophrenia present diverse degrees and types of cognitive impairment, leading to variations in responses to antipsychotic treatments. Understanding the underlying cognitive structures is crucial for assessing this heterogeneity. Utilizing latent profile analysis (LPA) enables the delineation of latent categories of cognitive function. Integrating this approach with a dimensional perspective allows for the exploration of the relationship between cognitive function and treatment response. METHODS: This study examined 647 patients from two distinct cohorts. Utilizing LPA within the discovery cohort (n = 333) and the replication cohort (n = 314), latent subtypes were identified categorically. The stability of cognitive structures was evaluated employing Latent Transition Analysis (LTA). The relationship between cognitive function and treatment response were investigated by comparing Positive and Negative Syndrome Scale (PANSS) reduction rates across diverse cognitive subtypes. Furthermore, dimensional insights were gained through correlation analyses between cognitive tests and PANSS reduction rates. RESULTS: In terms of categorical, individuals diagnosed with schizophrenia can be categorized into three distinct subtypes: those 'without cognitive deficit', those 'with mild-moderate cognitive 'eficit', and those 'with moderate-severe cognitive deficit'. There are significant differences in PANSS reduction rates among patients belonging to these subtypes following antipsychotic treatment (p < 0.05). Furthermore, from a dimensional perspective, processing speed at baseline is positively correlated with PANSS score reduction rates at week 8/week 10 (p < 0.01). CONCLUSIONS: Our findings have unveiled the latent subtypes of cognitive function in schizophrenia, illuminating the association between cognitive function and responses to antipsychotic treatment from both categorical and dimensional perspectives.