Compare deep learning model and conventional logistic regression model for the identification of unstable saccular intracranial aneurysms in computed tomography angiography.

Background: It is crucial to distinguish unstable from stable intracranial aneurysms (IAs) as early as possible to derive optimal clinical decision-making for further treatment or follow-up. The aim of this study was to investigate the value of a deep learning model (DLM) in identifying unstable IAs from computed tomography angiography (CTA) images and to compare its discriminatory ability with that of a conventional logistic regression model (LRM). Methods: From August 2011 to May 2021, a total of 1,049 patients with 681 unstable IAs and 556 stable IAs were retrospectively analyzed. IAs were randomly divided into training (64%), internal validation (16%), and test sets (20%). Convolutional neural network (CNN) analysis and conventional logistic regression (LR) were used to predict which IAs were unstable. The area under the curve (AUC), sensitivity, specificity and accuracy were calculated to evaluate the discriminating ability of the models. One hundred and ninety-seven patients with 229 IAs from Banan Hospital were used for external validation sets. Results: The conventional LRM showed 11 unstable risk factors, including clinical and IA characteristics. The LRM had an AUC of 0.963 [95% confidence interval (CI): 0.941-0.986], a sensitivity, specificity and accuracy on the external validation set of 0.922, 0.906, and 0.913, respectively, in predicting unstable IAs. In predicting unstable IAs, the DLM had an AUC of 0.771 (95% CI: 0.582-0.960), a sensitivity, specificity and accuracy on the external validation set of 0.694, 0.929, and 0.782, respectively. Conclusions: The CNN-based DLM applied to CTA images did not outperform the conventional LRM in predicting unstable IAs. The patient clinical and IA morphological parameters remain critical factors for ensuring IA stability. Further studies are needed to enhance the diagnostic accuracy.

Telehealth Utilization for Opioid Use Disorder: A Nationwide Analysis Before and After the COVID-19 Public Health Emergency Declaration.

Introduction: The COVID-19 pandemic has led to the rapid and widespread adoption of telehealth services. Telehealth may aid in bridging gaps in access to care. The specific impact of telehealth on opioid use disorder (OUD) and its treatment remains uncertain. Methods: A retrospective review of commercial insurance claim records within the United States was conducted to investigate the association between the COVID-19 pandemic and changes in the rates of(a) OUD treatments with and without telehealth support and (b) prescriptions for medications for opioid use disorder (MOUD) with and without telehealth support among individuals diagnosed with OUD. Results: In a study population of 1,340,506 individuals, OUD diagnosis rates were 5 per 1,000 in-person and 1 per 1,000 via telehealth. COVID-19 decreased in-person OUD diagnoses by 0.89 per 1,000, while telehealth diagnoses increased by 0.83 per 1,000. In-person MOUD treatment rates increased by 0.07 per 1,000 during COVID-19, while telehealth rates remained low. The onset of COVID-19 saw a 1.13 per 1,000 higher increase in telehealth-supported MOUD treatment compared to solely in-person treatment. Conclusions: A retrospective review of commercial insurance claim records within the United States was conducted to investigate the association between the COVID-19 pandemic and changes in the rates of (a) OUD treatments with and without telehealth support and (b) prescriptions for MOUD with and without telehealth support among individuals diagnosed with OUD.

Quantitative evaluation of meniscus injury using synthetic magnetic resonance imaging.

BACKGROUND: Magnetic resonance imaging (MRI) can diagnose meniscal lesions anatomically, while quantitative MRI can reflect the changes of meniscal histology and biochemical structure. Our study aims to explore the association between the measurement values obtained from synthetic magnetic resonance imaging (SyMRI) and Stoller grades. Additionally, we aim to assess the diagnostic accuracy of SyMRI in determining the extent of meniscus injury. This potential accuracy could contribute to minimizing unnecessary invasive examinations and providing guidance for clinical treatment. METHODS: Total of 60 (n=60) patients requiring knee arthroscopic surgery and 20 (n=20) healthy subjects were collected from July 2022 to November 2022. All subjects underwent conventional MRI and SyMRI. Manual measurements of the T1, T2 and proton density (PD) values were conducted for both normal menisci and the most severely affected position of injured menisci. These measurements corresponded to the Stoller grade of meniscus injuries observed in the conventional MRI. All patients and healthy subjects were divided into normal group, degeneration group and torn group according to the Stoller grade on conventional MRI. One-way analysis of variance (ANOVA) was employed to compare the T1, T2 and PD values of the meniscus among 3 groups. The accuracy of SyMRI in diagnosing meniscus injury was assessed by comparing the findings with arthroscopic observations. The diagnostic efficiency of meniscus degeneration and tear between conventional MRI and SyMRI were analyzed using McNemar test. Furthermore, a receiver operating characteristic curve (ROC curve) was constructed and the area under the curve (AUC) was utilized for evaluation. RESULTS: According to the measurements of SyMRI, there was no statistical difference of T1 value or PD value measured by SyMRI among the normal group, degeneration group and torn group, while the difference of T2 value was statistically significant among 3 groups (P=0.001). The arthroscopic findings showed that 11 patients were meniscal degeneration and 49 patients were meniscal tears. The arthroscopic findings were used as the gold standard, and the difference of T1 and PD values among the 3 groups was not statistically significant, while the difference of T2 values (32.81±2.51 of normal group, 44.85±3.98 of degeneration group and 54.42±3.82 of torn group) was statistically significant (P=0.001). When the threshold of T2 value was 51.67 (ms), the maximum Yoden index was 0.787 and the AUC value was 0.934. CONCLUSIONS: The measurement values derived from SyMRI could reflect the Stoller grade, illustrating that SyMRI has good consistency with conventional MRI. Moreover, the notable consistency observed between SyMRI and arthroscopy suggests a potential role for SyMRI in guiding clinical diagnoses.

High glutamine increases stroke risk by inducing the endothelial-to-mesenchymal transition in moyamoya disease.

At present, there is limited research on the mechanisms underlying moyamoya disease (MMD). Herein, we aimed to determine the role of glutamine in MMD pathogenesis, and 360 adult patients were prospectively enrolled. Human brain microvascular endothelial cells (HBMECs) were subjected to Integrin Subunit Beta 4 (ITGB4) overexpression or knockdown and atorvastatin. We assessed factors associated with various signaling pathways in the context of the endothelial-to-mesenchymal transition (EndMT), and the expression level of related proteins was validated in the superficial temporal arteries of patients. We found glutamine levels were positively associated with a greater risk of stroke (OR = 1.599, p = 0.022). After treatment with glutamine, HBMECs exhibited enhanced proliferation, migration, and EndMT, all reversed by ITGB4 knockdown. In ITGB4-transfected HBMECs, the MAPK-ERK-TGF-ß/BMP pathway was activated, with Smad4 knockdown reversing the EndMT. Furthermore, atorvastatin suppressed the EndMT by inhibiting Smad1/5 phosphorylation and promoting Smad4 ubiquitination in ITGB4-transfected HBMECs. We also found the protein level of ITGB4 was upregulated in the superficial temporal arteries of patients with MMD. In conclusion, our study suggests that glutamine may be an independent risk factor for hemorrhage or infarction in patients with MMD and targeting ITGB4 could potentially be therapeutic approaches for MMD.

Fermentation enrichment, structural characterization and immunostimulatory effects of ß-glucan from Quinoa.

We developed an efficient mixed-strain co-fermentation method to increase the yield of quinoa ß-glucan (Q+). Using a 1:1 mass ratio of highly active dry yeast and Streptococcus thermophilus, solid-to-liquid ratio of 1:12 (g/mL), inoculum size of 3.8 % (mass fraction), fermentation at 32 °C for 27 h, we achieved the highest ß-glucan yield of (11.13 ± 0.80)%, representing remarkable 100.18 % increase in yield compared to quinoa ß-glucan(Q-) extracted using hot water. The structure of Q+ and Q- were confirmed through Fourier Transform Infrared (FTIR) and Nuclear Magnetic Resonance (NMR) spectroscopies. Q+ contained 41.66 % ß-glucan, 3.93 % protein, 2.12 % uronic acid; Q- contained 37.21 % ß-glucan, 11.49 % protein, and 1.73 % uronic acid. The average molecular weight of Q+(75.37 kDa) was lower than that of Q- (94.47 kDa). Both Q+ and Q- promote RAW264.7 cell proliferation without displaying toxicity. They stimulate RAW264.7 cells through the NF-κB and MAPK signaling pathways, primarily inducing NO and pro-inflammatory cytokines by upregulating CD40 expression. Notably, Q+ exhibited stronger immunostimulatory activity compared to Q-. In summary, the fermentation enrichment method yields higher content of quinoa ß-glucan with increased purity and stronger immunostimulatory properties. Further study of its bioimmunological activity and structure-activity relationship may contribute to the development of new immunostimulants.

Elucidation of the molecular mechanism of the breakage-fusion-bridge (BFB) cycle using a CRISPR-dCas9 cellular model.

Chromosome instability (CIN) is frequently observed in many tumors. The breakage-fusion-bridge (BFB) cycle has been proposed to be one of the main drivers of CIN during tumorigenesis and tumor evolution. However, the detailed mechanisms for the individual steps of the BFB cycle warrants further investigation. Here, we demonstrated that a nuclease-dead Cas9 (dCas9) coupled with a telomere-specific single-guide RNA (sgTelo) can be used to model the BFB cycle. First, we showed that targeting dCas9 to telomeres using sgTelo impeded DNA replication at telomeres and induced a pronounced increase of replication stress and DNA damage. Using Single-Molecule Telomere Assay via Optical Mapping (SMTA-OM), we investigated the genome-wide features of telomeres in the dCas9/sgTelo cells and observed a dramatic increase of chromosome end fusions, including fusion/ITS+ and fusion/ITS-.Consistently, we also observed an increase in the formation of dicentric chromosomes, anaphase bridges, and intercellular telomeric chromosome bridges (ITCBs). Utilizing the dCas9/sgTelo system, we uncovered many novel molecular and structural features of the ITCB and demonstrated that multiple DNA repair pathways are implicated in the formation of ITCBs. Our studies shed new light on the molecular mechanisms of the BFB cycle, which will advance our understanding of tumorigenesis, tumor evolution, and drug resistance.

APOE regulates the transport of GM1.

Apolipoprotein E (APOE) is responsible for lipid transport, including cholesterol transport and clearance. While the ε4 allele of APOE (APOE4) is associated with a significant genetic risk factor for late-onset Alzheimer's disease (AD), no mechanistic understanding of its contribution to AD etiology has been established yet. In addition to cholesterol, monosialotetrahexosylganglioside (GM1) is a crucial lipid component in cell membranes and has been implicated in promoting the aggregation of amyloid beta protein (Aß), a key protein associated with AD. Here, we ask whether there are direct interactions between APOE and GM1 that further impact AD pathology. We find that both APOE3 and APOE4 exhibit superior binding affinity to GM1 compared to cholesterol and have an enhanced cellular uptake to GM1 lipid structures than cholesterol lipid structures. APOE regulates the transport process of GM1 depending on the cell type, which is influenced by the expression of APOE receptors in different cell lines and alters GM1 contents in cell membranes. We also find that the presence of GM1 alters the secondary structure of APOE3 and APOE4 and enhances the binding affinity between APOE and its receptor low-density lipoprotein receptor (LDLR), consequently promoting the cellular uptake of lipid structures in the presence of APOE. To understand the enhanced cellular uptake observed in lipid structures containing 20% GM1, we determined the distribution of GM1 on the membrane and found that GM1 clustering in lipid rafts, thereby supporting the physiological interaction between APOE and GM1. Overall, we find that APOE plays a regulatory role in GM1 transport, and the presence of GM1 on the lipid structures influences this transport process. Our studies introduce a plausible direct link between APOE and AD etiology, wherein APOE regulates GM1, which, in turn, promotes Aß oligomerization and aggregation.

Long-term prognosis of patients with gallbladder carcinoma after curative-intent resection based on changes in the ratio of carbohydrate antigen 19-9 to total bilirubin (CA19-9/TB): a multicenter retrospective cohort study.

BACKGROUND: The prognostic value of carbohydrate antigen 19-9 (CA19-9) is known to be affected by elevated bilirubin levels in patients with gallbladder carcinoma (GBC). The clinical significance of changes in the ratio of CA19-9 levels to total bilirubin (TB) levels in patients with GBC after curative-intent resection remains unknown. The aim of this study was to determine the prognostic value of changes in preoperative and postoperative CA19-9/TB ratio in these patients. METHODS: Prospectively colleced data on consecutive patients who underwent curative-intent resection for GBC between January 2015 and December 2020 stored in a multicenter database from 10 hospitals were analysed in this retrospective cohort study. Based on the adjusted CA19-9 defined as the ratio of CA19-9 to TB, and using 2×103 U/µmol as the upper normal value, patients were divided into a normal group (with normal preoperative and postoperative adjusted CA19-9), a normalization group (with abnormal preoperative but normal postoperative adjusted CA19-9), and a non-normalization group (with abnormal postoperative adjusted CA19-9). The primary outcomes were overall survival (OS) and recurrence-free survival (RFS). The log-rank test was used to compare OS and RFS among the groups. The Cox regression model was used to determine factors independently associated with OS and RFS. RESULTS: The normal group (n=179 patients) and the normalization group (n=73 patients) had better OS and RFS than the non-normalization group (n=65 patients) (the 3-year OS rates 72.0%, 58.4% and 24.2%, respectively; the RFS rates 54.5%, 25.5% and 11.8%, respectively; both P<0.001). There were no significant differences between the normal and the normalization groups in OS and RFS (OS, P=0.255; RFS, P=0.130). Cox regression analysis confirmed that the non-normalization group was independently associated with worse OS and RFS. Subgroup analysis revealed that the non-normalization group of patients who received adjuvant therapy had significantly improved OS and RFS as compared to those who did not receive adjuvant therapy (OS, P=0.025; RFS, P=0.003). CONCLUSIONS: Patients with GBC who underwent curative-intent surgical resection with postoperative abnormal levels of adjusted CA19-9 (the CA19-9/TB ratio) were associated with poorer long-term survival outcomes. Adjuvant therapy after surgery improved the long-term outcomes of these patients.

Glymphatic Impairment Associated with Neurocognitive Dysfunction in Moyamoya Disease.

Glymphatic system alterations have been proved to be associated with cognitive dysfunction in neurodegenerative diseases. The glymphatic pathway has not been elucidated in moyamoya disease (MMD), which was recognized as a chronic hypoperfusion model for neurodegenerative disease. Here, we aimed to investigate the glymphatic system activity and its relation with neurocognition, and associated hallmarks in MMD. We prospectively recruited 30 MMD patients and 30 matched healthy controls (HC). Participants underwent MRI and neurocognition evaluation. The glymphatic function was assessed by diffusion tensor image analysis along perivascular space (DTI-ALPS) index. Gray matter volume (GMV) and microstructural alterations were calculated. Neurodegenerative-related serum biomarkers were examined. The mediation effect of ALPS index in the associations between variables and neurocognition were further explored. A lower ALPS index was identified in patients with MMD (P < 0.001). The decreased ALPS index was significantly correlated with declined neurocognitive performance. Moreover, the reduced ALPS index was notably linked with lower total GMV% and deep GMV% (P < 0.01). Microstructural changes in the periventricular areas were detected and associated with ALPS index in MMD. Serum neurodegenerative biomarkers (ApoE, Aß40, Aß42, and Aß42/Aß40) were significantly elevated and related to ALPS index. Additionally, the ALPS index significantly mediated the associations of microstructural alterations and ApoE level with neurocognitive dysfunction. The ALPS index was notably lower MMD in patients, suggesting the utility as a marker of potential glymphatic dysfunction. The index acted as a significant mediator in neurocognitive dysfunction. These findings indicated that glymphatic impairment may interact with MMD-related pathophysiological processes.

Circulating immune cell landscape and T-cell abnormalities in patients with moyamoya disease.

BACKGROUND: Moyamoya disease (MMD) stands as a prominent cause of stroke among children and adolescents in East Asian populations. Although a growing body of evidence suggests that dysregulated inflammation and autoimmune responses might contribute to the development of MMD, a comprehensive and detailed understanding of the alterations in circulating immune cells associated with MMD remains elusive. METHODS: In this study, we employed a combination of single-cell RNA sequencing (scRNA-seq), mass cytometry and RNA-sequencing techniques to compare immune cell profiles in peripheral blood samples obtained from patients with MMD and age-matched healthy controls. RESULTS: Our investigation unveiled immune dysfunction in MMD patients, primarily characterized by perturbations in T-cell (TC) subpopulations, including a reduction in effector TCs and an increase in regulatory TCs (Tregs). Additionally, we observed diminished natural killer cells and dendritic cells alongside heightened B cells and monocytes in MMD patients. Notably, within the MMD group, there was an augmented proportion of fragile Tregs, whereas the stable Treg fraction decreased. MMD was also linked to heightened immune activation, as evidenced by elevated expression levels of HLA-DR and p-STAT3. CONCLUSIONS: Our findings offer a comprehensive view of the circulating immune cell landscape in MMD patients. Immune dysregulation in patients with MMD was characterized by alterations in T-cell populations, including a decrease in effector T-cells and an increase in regulatory T-cells (Tregs), suggest a potential role for disrupted circulating immunity in the aetiology of MMD.

XELOX (capecitabine plus oxaliplatin) plus bevacizumab (anti-VEGF-A antibody) with or without adoptive cell immunotherapy in the treatment of patients with previously untreated metastatic colorectal cancer: a multicenter, open-label, randomized, controlled, phase 3 trial.

Fluoropyrimidine-based combination chemotherapy plus targeted therapy is the standard initial treatment for unresectable metastatic colorectal cancer (mCRC), but the prognosis remains poor. This phase 3 trial (ClinicalTrials.gov: NCT03950154) assessed the efficacy and adverse events (AEs) of the combination of PD-1 blockade-activated DC-CIK (PD1-T) cells with XELOX plus bevacizumab as a first-line therapy in patients with mCRC. A total of 202 participants were enrolled and randomly assigned in a 1:1 ratio to receive either first-line XELOX plus bevacizumab (the control group, n = 102) or the same regimen plus autologous PD1-T cell immunotherapy (the immunotherapy group, n = 100) every 21 days for up to 6 cycles, followed by maintenance treatment with capecitabine and bevacizumab. The main endpoint of the trial was progression-free survival (PFS). The median follow-up was 19.5 months. Median PFS was 14.8 months (95% CI, 11.6-18.0) for the immunotherapy group compared with 9.9 months (8.0-11.8) for the control group (hazard ratio [HR], 0.60 [95% CI, 0.40-0.88]; p = 0.009). Median overall survival (OS) was not reached for the immunotherapy group and 25.6 months (95% CI, 18.3-32.8) for the control group (HR, 0.57 [95% CI, 0.33-0.98]; p = 0.043). Grade 3 or higher AEs occurred in 20.0% of patients in the immunotherapy group and 23.5% in the control groups, with no toxicity-associated deaths reported. The addition of PD1-T cells to first-line XELOX plus bevacizumab demonstrates significant clinical improvement of PFS and OS with well tolerability in patients with previously untreated mCRC.

Double-negative T cells ameliorate psoriasis by selectively inhibiting IL-17A-producing γδlow T cells.

BACKGROUND: Psoriasis is a chronic immune-mediated skin condition. Although biologic treatments are effective in controlling psoriasis, some patients do not respond or lose response to these therapies. Thus, new strategies for psoriasis treatment are still urgently needed. Double-negative T cells (DNT) play a significant immunoregulatory role in autoimmune diseases. In this study, we aimed to evaluate the protective effect of DNT in psoriasis and explore the underlying mechanism. METHODS: We conducted a single adoptive transfer of DNT into an imiquimod (IMQ)-induced psoriasis mouse model through tail vein injection. The skin inflammation and IL-17A producing γδ T cells were evaluated. RESULTS: DNT administration significantly reduced the inflammatory response in mouse skin, characterized by decreased skin folds, scales, and red patches. After DNT treatment, the secretion of IL-17A by RORc+ γδlow T cells in the skin was selectively suppressed, resulting in an amelioration of skin inflammation. Transcriptomic data suggested heightened expression of NKG2D ligands in γδlow T cells within the mouse model of psoriasis induced by IMQ. When blocking the NKG2D ligand and NKG2D (expressed by DNT) interaction, the cytotoxic efficacy of DNT against RORc+IL17A+ γδlow T cells was attenuated. Using Ccr5-/- DNT for treatment yielded evidence that DNT migrates into inflamed skin tissue and fails to protect IMQ-induced skin lesions. CONCLUSIONS: DNT could migrate to inflamed skin tissue through CCR5, selectively inhibit IL-17-producing γδlow T cells and finally ameliorate mouse psoriasis. Our study provides feasibility for using immune cell therapy for the prevention and treatment of psoriasis in the clinic.

Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images.

Deep reinforcement learning (DRL) has demonstrated impressive performance in medical image segmentation, particularly for low-contrast and small medical objects. However, current DRL-based segmentation methods face limitations due to the optimization of error propagation in two separate stages and the need for a significant amount of labeled data. In this paper, we propose a novel deep generative adversarial reinforcement learning (DGARL) approach that, for the first time, enables end-to-end semi-supervised medical image segmentation in the DRL domain. DGARL ingeniously establishes a pipeline that integrates DRL and generative adversarial networks (GANs) to optimize both detection and segmentation tasks holistically while mutually enhancing each other. Specifically, DGARL introduces two innovative components to facilitate this integration in semi-supervised settings. First, a task-joint GAN with two discriminators links the detection results to the GAN's segmentation performance evaluation, allowing simultaneous joint evaluation and feedback. This ensures that DRL and GAN can be directly optimized based on each other's results. Second, a bidirectional exploration DRL integrates backward exploration and forward exploration to ensure the DRL agent explores the correct direction when forward exploration is disabled due to lack of explicit rewards. This mitigates the issue of unlabeled data being unable to provide rewards and rendering DRL unexplorable. Comprehensive experiments on three generalization datasets, comprising a total of 640 patients, demonstrate that our novel DGARL achieves 85.02% Dice and improves at least 1.91% for brain tumors, achieves 73.18% Dice and improves at least 4.28% for liver tumors, and achieves 70.85% Dice and improves at least 2.73% for pancreas compared to the ten most recent advanced methods, our results attest to the superiority of DGARL. Code is available at GitHub.

RACK1A promotes hypocotyl elongation by scaffolding light signaling components in Arabidopsis.

Plants deploy versatile scaffold proteins to intricately modulate complex cell signaling. Among these, RACK1A (Receptors for Activated C Kinase 1A) stands out as a multifaceted scaffold protein functioning as a central integrative hub for diverse signaling pathways. However, the precise mechanisms by which RACK1A orchestrates signal transduction to optimize seedling development remain largely unclear. Here, we demonstrate that RACK1A facilitates hypocotyl elongation by functioning as a flexible platform that connects multiple key components of light signaling pathways. RACK1A interacts with PHYTOCHROME INTERACTING FACTOR (PIF)3, enhances PIF3 binding to the promoter of BBX11 and down-regulates its transcription. Furthermore, RACK1A associates with ELONGATED HYPOCOTYL 5 (HY5) to repress HY5 biochemical activity toward target genes, ultimately contributing to hypocotyl elongation. In darkness, RACK1A is targeted by CONSTITUTIVELY PHOTOMORPHOGENIC (COP)1 upon phosphorylation and subjected to COP1-mediated degradation via the 26 S proteasome system. Our findings provide new insights into how plants utilize scaffold proteins to regulate hypocotyl elongation, ensuring proper skoto- and photo-morphogenic development.

A lung disease diagnosis algorithm based on 2D spectral features of ultrasound RF signals.

Lung diseases are commonly diagnosed based on clinical pathological indications criteria and radiological imaging tools (e.g., X-rays and CT). During a pandemic like COVID-19, the use of ultrasound imaging devices has broadened for emergency examinations by taking their unique advantages such as portability, real-time detection, easy operation and no radiation. This provides a rapid, safe, and cost-effective imaging modality for screening lung diseases. However, the current pulmonary ultrasound diagnosis mainly relies on the subjective assessments of sonographers, which has high requirements for the operator's professional ability and clinical experience. In this study, we proposed an objective and quantifiable algorithm for the diagnosis of lung diseases that utilizes two-dimensional (2D) spectral features of ultrasound radiofrequency (RF) signals. The ultrasound data samples consisted of a set of RF signal frames, which were collected by professional sonographers. In each case, a region of interest of uniform size was delineated along the pleural line. The standard deviation curve of the 2D spatial spectrum was calculated and smoothed. A linear fit was applied to the high-frequency segment of the processed data curve, and the slope of the fitted line was defined as the frequency spectrum standard deviation slope (FSSDS). Based on the current data, the method exhibited a superior diagnostic sensitivity of 98% and an accuracy of 91% for the identification of lung diseases. The area under the curve obtained by the current method exceeded the results obtained that interpreted by professional sonographers, which indicated that the current method could provide strong support for the clinical ultrasound diagnosis of lung diseases.

LC-MS and MALDI-MSI-based metabolomic approaches provide insights into the spatial-temporal metabolite profiles of Tartary buckwheat achene development.

Tartary buckwheat, celebrated as the "king of grains" for its flavonoid and phenolic acid richness, has health-promoting properties. Despite significant morphological and metabolic variations in mature achenes, research on their developmental process is limited. Utilizing Liquid chromatography-mass spectrometry and atmospheric pressure matrix-assisted laser desorption/ionization mass spectrometry imaging, we conducted spatial-temporal metabolomics on two cultivars during achene development. Metabolic profiles including 17 phenolic acids and 83 flavonoids are influenced by both varietal distinctions and developmental intricacies. Notably, flavonols, as major flavonoids, accumulated with achene ripening and showed a tissue-specific distribution. Specifically, flavonol glycosides and aglycones concentrated in the embryo, while methylated flavonols and procyanidins in the hull. Black achenes at the green achene stage have higher bioactive compounds and enhanced antioxidant capacity. These findings provide insights into spatial and temporal characteristics of metabolites in Tartary buckwheat achenes and serve as a theoretical guide for selecting optimal resources for food production.

Diagnosis of a Familial Psittacosis Outbreak with Clinical Analysis and Metagenomic Next-Generation Sequencing Under COVID-19: A Case Series.

Purpose: To explore the clinical characteristics, diagnosis, and treatment of family outbreak of psittacosis and to improve the success rate of treatment. Patients and Methods: The clinical characteristics, diagnosis, treatment, and outcome of family outbreak of psittacosis, which consists three patients, diagnosed by clinical analysis and metagenomic next-generation sequencing (mNGS) in our hospital were analyzed retrospectively. Results: We report on three instances of clustered atypical pneumonia, which were caused by Chlamydia psittaci during the COVID-19 pandemic. All patients exhibited symptoms of fever and cough, while one patient also experienced gastrointestinal symptoms such as nausea, vomiting, and diarrhea. Laboratory tests indicated no significant increase in leukocytes and neutrophils, but a mild increase in C-reactive protein was observed in all three patients. Chest computed tomography (CT) scans revealed a consolidation shadow in a unilateral lung lobe in all three patients. Both patients were treated with empirical moxifloxacin, yielding unsatisfactory outcomes. mNGS was conducted on sputum samples from one adult patient, revealing the presence of Chlamydia psittaci. Additional doxycycline was prescribed immediately, and then the patients' temperatures were stabilized, and the lesion in chest CT was absorbed. The pediatric patient exhibited less severe symptoms compared to the adult patients and exhibited a favorable response to azithromycin administration. Conclusion: This study reports a cluster of a family outbreak of atypical pneumonia caused by C. psittaci in China. The occurrence of a family outbreak during the COVID-19 pandemic may be attributed to familial aggregation resulting from the epidemic. The three cases reported in this study did not experience severe complications, which can be attributed to the prompt medical intervention and swift diagnosis. This finding implies the need to enhance patients' awareness and vigilance towards their health. Additionally, mNGS emerges as a valuable technique for accurately identifying pathogens causing pulmonary infections.

Autosis: a new form of cell death in myocardial ischemia-reperfusion injury.

Cardiomyocytes undergo a variety of cell death events during myocardial ischemia‒reperfusion injury (MIRI). Understanding the causes of cardiomyocyte mortality is critical for the prevention and treatment of MIRI. Among the various types of cell death, autosis is a recently identified type of autophagic cell death with distinct morphological and chemical characteristics. Autosis can be attenuated by autophagy inhibitors but not reversed by apoptosis or necrosis inhibitors. In recent years, it has been shown that during the late phase of reperfusion, autosis is activated, which exacerbates myocardial injury. This article describes the characteristics of autosis, autophagic cell death, and the relationship between autophagic cell death and autosis; reviews the mechanism of autosis in MIRI; and discusses its clinical significance.

FUZ-SMO: A fuzzy slime mould optimizer for mitigating false alarm rates in the classification of underwater datasets using deep convolutional neural networks.

Sonar sound datasets are of significant importance in the domains of underwater surveillance and marine research as they enable experts to discern intricate patterns within the depths of the water. Nevertheless, the task of classifying sonar sound datasets continues to pose significant challenges. In this study, we present a novel approach aimed at enhancing the precision and efficacy of sonar sound dataset classification. The integration of deep long-short-term memory (DLSTM) and convolutional neural networks (CNNs) models is employed in order to capitalize on their respective advantages while also utilizing distinctive feature engineering techniques to achieve the most favorable outcomes. Although DLSTM networks have demonstrated effectiveness in tasks involving sequence classification, attaining their optimal performance necessitates careful adjustment of hyperparameters. While traditional methods such as grid and random search are effective, they frequently encounter challenges related to computational inefficiencies. This study aims to investigate the unexplored capabilities of the fuzzy slime mould optimizer (FUZ-SMO) in the context of LSTM hyperparameter tuning, with the objective of addressing the existing research gap in this area. Drawing inspiration from the adaptive behavior exhibited by slime moulds, the FUZ-SMO proposes a novel approach to optimization. The amalgamated model, which combines CNN, LSTM, fuzzy, and SMO, exhibits a notable improvement in classification accuracy, outperforming conventional LSTM architectures by a margin of 2.142%. This model not only demonstrates accelerated convergence milestones but also displays significant resilience against overfitting tendencies.

Short-term lifestyle education on obesity reduction in adolescents.

Backgrounds: Obesity is increasing in adolescents in China. However, the awareness of obesity and prevention on related risk factors were not well known. We aim to assess the effectiveness of short-term health education intervention on obesity in Chinese adolescents. Methods: In this study, 42 primary and secondary schools from Qingdao were randomly divided into the education and control groups. A total of 11,739 adolescents was included in the current study. The logistic regression was employed to assess odds ratio (OR) of education intervention on overweight and obesity prevalence adjusting for covariates. Results: The baseline prevalence of overweight and obesity was significantly higher in urban than in rural areas and in boys than in girls. After 1 year lifestyle intervention, the proportion of students with awareness of obesity was higher, meanwhile age-adjusted mean values of weight, body mass index, duration of watching TV and doing homework were lower in education group than control group. The corresponding figures were 43.6 [95% CI (confidence intervals); 43.3-43.9] kg versus 44.3 (95% CI; 44.0-44.6) kg, 18.6 (95% CI; 18.5-18.7) kg/m2 versus 18.9 (95% CI; 18.8-19.1) kg/m2, 1.3 (95% CI; 1.2-1.3) hours/d versus 1.4 (95% CI; 1.3-1.4) hours/d, and 1.5 (95% CI; 1.4-1.5) hours/d versus 1.8 (95% CI, 1.7-1.8) hours/d. The multivariable adjusted OR for combined prevalence of overweight and obesity was 0.85 (95% CI, 0.76-0.96) in education group as compared with control group. Conclusion: Short-term health education intervention results in significantly higher reductions in obesity parameters and improvement in awareness in Chinese adolescents.