Non-coding RNAs in acute ischemic stroke: from brain to periphery.

Acute ischemic stroke is a clinical emergency and a condition with high morbidity, mortality, and disability. Accurate predictive, diagnostic, and prognostic biomarkers and effective therapeutic targets for acute ischemic stroke remain undetermined. With innovations in high-throughput gene sequencing analysis, many aberrantly expressed non-coding RNAs (ncRNAs) in the brain and peripheral blood after acute ischemic stroke have been found in clinical samples and experimental models. Differentially expressed ncRNAs in the post-stroke brain were demonstrated to play vital roles in pathological processes, leading to neuroprotection or deterioration, thus ncRNAs can serve as therapeutic targets in acute ischemic stroke. Moreover, distinctly expressed ncRNAs in the peripheral blood can be used as biomarkers for acute ischemic stroke prediction, diagnosis, and prognosis. In particular, ncRNAs in peripheral immune cells were recently shown to be involved in the peripheral and brain immune response after acute ischemic stroke. In this review, we consolidate the latest progress of research into the roles of ncRNAs (microRNAs, long ncRNAs, and circular RNAs) in the pathological processes of acute ischemic stroke-induced brain damage, as well as the potential of these ncRNAs to act as biomarkers for acute ischemic stroke prediction, diagnosis, and prognosis. Findings from this review will provide novel ideas for the clinical application of ncRNAs in acute ischemic stroke.

MIST: Multi-instance selective transformer for histopathological subtype prediction.

Accurate histopathological subtype prediction is clinically significant for cancer diagnosis and tumor microenvironment analysis. However, achieving accurate histopathological subtype prediction is a challenging task due to (1) instance-level discrimination of histopathological images, (2) low inter-class and large intra-class variances among histopathological images in their shape and chromatin texture, and (3) heterogeneous feature distribution over different images. In this paper, we formulate subtype prediction as fine-grained representation learning and propose a novel multi-instance selective transformer (MIST) framework, effectively achieving accurate histopathological subtype prediction. The proposed MIST designs an effective selective self-attention mechanism with multi-instance learning (MIL) and vision transformer (ViT) to adaptive identify informative instances for fine-grained representation. Innovatively, the MIST entrusts each instance with different contributions to the bag representation based on its interactions with instances and bags. Specifically, a SiT module with selective multi-head self-attention (S-MSA) is well-designed to identify the representative instances by modeling the instance-to-instance interactions. On the contrary, a MIFD module with the information bottleneck is proposed to learn the discriminative fine-grained representation for histopathological images by modeling instance-to-bag interactions with the selected instances. Substantial experiments on five clinical benchmarks demonstrate that the MIST achieves accurate histopathological subtype prediction and obtains state-of-the-art performance with an accuracy of 0.936. The MIST shows great potential to handle fine-grained medical image analysis, such as histopathological subtype prediction in clinical applications.

Common-Unique Decomposition Driven Diffusion Model for Contrast-Enhanced Liver MR Images Multi-Phase Interconversion.

All three contrast-enhanced (CE) phases (e.g., Arterial, Portal Venous, and Delay) are crucial for diagnosing liver tumors. However, acquiring all three phases is constrained due to contrast agents (CAs) risks, long imaging time, and strict imaging criteria. In this paper, we propose a novel Common-Unique Decomposition Driven Diffusion Model (CUDD-DM), capable of converting any two input phases in three phases into the remaining one, thereby reducing patient wait time, conserving medical resources, and reducing the use of CAs. 1) The Common-Unique Feature Decomposition Module, by utilizing spectral decomposition to capture both common and unique features among different inputs, not only learns correlations in highly similar areas between two input phases but also learns differences in different areas, thereby laying a foundation for the synthesis of remaining phase. 2) The Multi-scale Temporal Reset Gates Module, by bidirectional comparing lesions in current and multiple historical slices, maximizes reliance on previous slices when no lesions and minimizes this reliance when lesions are present, thereby preventing interference between consecutive slices. 3) The Diffusion Model-Driven Lesion Detail Synthesis Module, by employing a continuous and progressive generation process, accurately captures detailed features between data distributions, thereby avoiding the loss of detail caused by traditional methods (e.g., GAN) that overfocus on global distributions. Extensive experiments on a generalized CE liver tumor dataset have demonstrated that our CUDD-DM achieves state-of-the-art performance (improved the SSIM by at least 2.2% (lesions area 5.3%) comparing the seven leading methods). These results demonstrate that CUDD-DM advances CE liver tumor imaging technology.

Selective recognition and enrichment of C70 over C60 using an anthracene-based nanotube.

Selective recognition and enrichment of fullerenes (e.g., C60 and C70) remains challenging due to the same diameter and geometrical similarity. Herein, we report a hexagonal anthracene-based nanotube (1) through a one-pot Suzuki-Miyaura cross-coupling reaction. With anthracene-based side walls and pyridine linkers, 1 features a nano-scale tubular cavity measuring 1.2 nm in diameter and 0.9 nm in depth, along with pH-responsive properties. Interestingly, the electron-rich 1 shows high binding affinity (K a ≈ 106 M-1) and selectivity (K s ≈ 140) to C70 over C60 in toluene, resulting from their different contribution of π-π interactions with the host. The protonation of 1 simultaneously alters the electronic properties within the nanotube, resulting in the release of the fullerene guests. Lastly, the selective recognition and pH stimuli-responsive properties of the nanotube have been utilized to enrich C70 from its low-content mixtures of fullerenes in chloroform.

Catalytic methane decomposition on CNT-supported Fe-catalysts.

Methane, either as natural gas or as a resource obtained from various bioprocesses (e.g., digestion, landfill) can be converted to carbon and hydrogen according to. CH4(g)→C(s)+2H2(g)ΔH298K=74.8kJ/mol. Previous research has stressed the growing importance of substituting the high-temperature Steam Methane Reforming (SMR) by a moderate temperature Catalytic Methane Decomposition (CMD). The carbon formed is moreover of nanotube nature, in high industrial demand. To avoid the use of an inert support for the active catalyst species, e.g., Al2O3 for Fe, leading to a progressive contamination of the catalyst by support debris and coking of the catalyst, the present research investigates the use of carbon nanotubes (CNTs) as Fe-support. Average CH4 conversions of 75-85% are obtained at 700 °C for a continuous operation of 40 h. The produced CNT from the methane conversion can be continuously removed from the catalyst bed by carry-over due to its bulk density difference (∼120 kg/m3) with the catalyst itself (∼1500 kg/m3). CNT properties are fully specified. No thermal regeneration of the catalyst is required. A tentative process layout and economic analysis demonstrate the scalability of the process and the very competitive production costs of H2 and CNT.

Dissecting the ecological risks of sulfadiazine degradation intermediates under different advanced oxidation systems: From toxicity to the fate of antibiotic resistance genes.

The incomplete degradation of antibiotics in water can produce intermediates that carry environmental risks and thus warrant concerns. In this study, the degradation of high concentrations of antibiotic sulfadiazine (SDZ) by advanced oxidation processes that leverage different reactive oxide species was systematically evaluated in terms of the influence of different degradation intermediates on the propagation of antibiotic resistance genes (ARGs). The ozone, persulfate, and photocatalytic oxidation systems for SDZ degradation are dominated by ozone, direct electron transfer, and singlet oxygen, hole, and superoxide radicals, respectively. These processes produce 15 intermediates via six degradation pathways. Notably, it was determined that three specific intermediates produced by the ozone and persulfate systems were more toxic than SDZ. In contrast, the photocatalytic system did not produce any intermediates with toxicity exceeding that of SDZ. Microcosm experiments combined with metagenomics confirmed significant changes in microbiota community structure after treatment with SDZ and its intermediates, including significant changes in the abundance of Flavobacterium, Dungenella, Archangium, and Comamonas. This treatment also led to the emergence of sulfonamide ARGs. The total abundance of sulfonamide ARGs was found to be positively correlated with residual SDZ concentration, with the lowest total abundance observed in the photocatalytic system. Additionally, the correlation analysis unveiled microbiota carrying sulfonamide ARGs.

Association of MRI Indexes of the Perivascular Space Network and Cognitive Impairment in Patients with Obstructive Sleep Apnea.

Background The role of perivascular space (PVS) dysfunction in obstructive sleep apnea (OSA) requires further study. Purpose To compare MRI indexes of PVS across patients with differing severities of OSA and relate them with disease characteristics and treatment. Materials and Methods This single-center prospective study included healthy controls (HCs) and patients with complaints of snoring who underwent MRI and cognitive evaluation between June 2021 and December 2022. Participants with complaints of snoring were classified into four groups (snoring, mild OSA, moderate OSA, and severe OSA). PVS networks were assessed at MRI using PVS volume fraction, extracellular free water (FW), and diffusion tensor imaging analysis along the PVS (DTI-ALPS). One-way analysis of variance and Pearson correlation were used for analysis. Alterations in PVS indexes and cognitive performance after treatment were assessed in 15 participants with moderate OSA. Results A total of 105 participants (mean age, 33.4 years ± 8.9 [SD]; 80 males) and 50 HCs (mean age, 37.0 years ± 8.6; 33 males) were included. Higher mean PVS volume fraction was observed in participants with severe OSA (n = 23) than in patients with mild OSA (n = 36) (0.11 vs 0.10; P = .03). Participants with severe OSA exhibited higher mean FW index (0.11) than both HCs (0.10; P < .001) and patients with mild OSA (0.10; P = .003). All patient groups had lower DTI-ALPS than HCs (range, 1.5-1.9 vs 2.1; all P < .001). DTI-ALPS correlated with cognitive performance on the Stroop Color and Word Test (r range, -0.23 to -0.24; P value range, .003-.005). After treatment, PVS indexes changed (P value range, <.001 to .01) and cognitive performance improved (P value range, <.001 to .03). Conclusion Differences in PVS indexes were observed among participants with differing severities of OSA and HCs. Indexes correlated with measures of cognitive function, and changes in indexes and improvement in cognitive performance were observed after treatment in participants with moderate OSA. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Port in this issue.

Silver Nanowire-Based Flexible Strain Sensor for Human Motion Detection.

Accurately capturing human movements is a crucial element of health status monitoring and a necessary precondition for realizing future virtual reality/augmented reality applications. Flexible motion sensors with exceptional sensitivity are capable of detecting physical activities by converting them into resistance fluctuations. Silver nanowires (AgNWs) have become a preferred choice for the development of various types of sensors due to their outstanding electrical conductivity, transparency, and flexibility within polymer composites. Herein, we present the design and fabrication of a flexible strain sensor based on silver nanowires. Suitable substrate materials were selected, and the sensor's sensitivity and fatigue properties were characterized and tested, with the sensor maintaining reliability after 5000 deformation cycles. Different sensors were prepared by controlling the concentration of silver nanowires to achieve the collection of motion signals from various parts of the human body. Additionally, we explored potential applications of these sensors in fields such as health monitoring and virtual reality. In summary, this work integrated the acquisition of different human motion signals, demonstrating great potential for future multifunctional wearable electronic devices.

PDIA3 orchestrates effector T cell program by serving as a chaperone to facilitate the non-canonical nuclear import of STAT1 and PKM2.

Dysregulated T cell activation underpins the immunopathology of rheumatoid arthritis (RA), yet the machineries that orchestrate T cell effector program remain incompletely understood. Herein, we leveraged bulk and single-cell RNA sequencing data from RA patients and validated protein disulfide isomerase family A member 3 (PDIA3) as a potential therapeutic target. PDIA3 is remarkably upregulated in pathogenic CD4 T cells derived from RA patients and positively correlates with C-reactive protein level and disease activity score 28. Pharmacological inhibition or genetic ablation of PDIA3 alleviates RA-associated articular pathology and autoimmune responses. Mechanistically, T cell receptor signaling triggers intracellular calcium flux to activate NFAT1, a process that is further potentiated by Wnt5a under RA settings. Activated NFAT1 then directly binds to the Pdia3 promoter to enhance the expression of PDIA3, which complexes with STAT1 or PKM2 to facilitate their nuclear import for transcribing T helper 1 (Th1) and Th17 lineage-related genes, respectively. This non-canonical regulatory mechanism likely occurs under pathological conditions, as PDIA3 could only be highly induced following aberrant external stimuli. Together, our data support that targeting PDIA3 is a vital strategy to mitigate autoimmune diseases, such as RA, in clinical settings.

A new flavonostilbene glycoside and four new stilbene derivatives from the roots of Polygonum multiflorum.

One new flavonostilbene glycoside, polygonflavanol C (1), two new dimeric stilbene glycosides, multiflorumiside M and multiflorumiside N (2-3), one new diphenyl ethanol glycoside, (R)-2,3,5,4'-tetrahydroxy-diphenylethanol 2-O-ß-D-glucopyranoside (4), and one new deoxybenzoin glycoside, 2,4,3',5'-tetrahydroxy-6-methyl-deoxybenzoin 2-O-ß-D-glucopyranoside (5), together with six known ones (6-11), were isolated from the roots of Polygonum multiflorum. Their structures were elucidated by the comprehensive spectroscopic analyses. In addition, compounds 1 and 7 showed significantly in vitro anti-inflammatory activity.

Fabrication of a high-quality, small blaze angle grating for visible short-wave infrared hyperspectral cameras.

This study outlines the development of a low line density, small blaze angle grating, optimized for a visible to short-wave infrared hyperspectral camera. An analysis of grating specifications was conducted to meet the precise requirements of this application, particularly focusing on the stringent tolerance limits for the blaze angle. A specialized ruling tool adjustment device was designed to adhere to these exacting blaze angle tolerances. The grating groove shape was examined using atomic force microscopy (AFM), and the theoretical diffraction efficiency of the grating was calculated based on these observations. Additionally, laser-based methods were employed to measure the actual diffraction efficiency of the grating, while interferometry was used to assess the grating's diffraction wavefront. The test results demonstrate our capability to fabricate high-quality gratings with a low line density and small blaze angles that are suitable for advanced hyperspectral imaging applications.

Noninvasive lung cancer subtype classification using tumor-derived signatures and cfDNA methylome.

Accurate diagnosis of lung cancer is important for treatment decision-making. Tumor biopsy and histological examination is the standard for determining histological lung cancer subtypes. Liquid biopsy, particularly cell-free DNA (cfDNA), has recently shown promising results in cancer detection and classification. In this study, we investigate the potential of cfDNA methylome for the noninvasive classification of lung cancer histological subtypes. We focused on the two most prevalent lung cancer subtypes, lung adenocarcinoma and lung squamous cell carcinoma. Using a fragment-based marker discovery approach, we identified robust subtype-specific methylation markers from tumor samples. These markers were successfully validated in independent cohorts and associated with subtype-specific transcriptional activity. Leveraging these markers, we constructed a subtype classification model using cfDNA methylation profiles, achieving an AUC of 0.808 in cross-validation and an AUC of 0.747 in the independent validation. Tumor copy number alterations inferred from cfDNA methylome analysis revealed potential for treatment selection. In summary, our study demonstrates the potential of cfDNA methylome analysis for noninvasive lung cancer subtyping, offering insights for cancer monitoring and early detection.

Exploration of the shared pathways and common biomarker in adamantinomatous craniopharyngioma and type 2 diabetes using integrated bioinformatics analysis.

Craniopharyngiomas are rare tumors of the central nervous system that typically present with symptoms such as headache and visual impairment, and those reflecting endocrine abnormalities, which seriously affect the quality of life of patients. Patients with craniopharyngiomas are at higher cardiometabolic risk, defined as conditions favoring the development of type 2 diabetes and cardiovascular disease. However, the underlying common pathogenic mechanisms of craniopharyngiomas and type 2 diabetes are not clear. Especially due to the difficulty of conducting in vitro or in vivo experiments on craniopharyngioma, we thought the common pathway analysis between craniopharyngioma and type 2 diabetes based on bioinformatics is a powerful and feasible method. In the present study, using public datasets (GSE94349, GSE68015, GSE38642 and GSE41762) obtained from the GEO database, the gene expression associated with adamantinomatous craniopharyngioma, a subtype of craniopharyngioma, and type 2 diabetes were analyzed using a bioinformatic approach. We found 11 hub genes using a protein-protein interaction network analysis. Of these, seven (DKK1, MMP12, KRT14, PLAU, WNT5B, IKBKB, and FGF19) were also identified by least absolute shrinkage and selection operator analysis. Finally, single-gene validation and receptor operating characteristic analysis revealed that four of these genes (MMP12, PLAU, KRT14, and DKK1) may be involved in the common pathogenetic mechanism of adamantinomatous craniopharyngioma and type 2 diabetes. In addition, we have characterized the differences in immune cell infiltration that characterize these two diseases, providing a reference for further research.

Identifying novel proteins for migraine by integrating proteomes from blood and CSF with genome-wide association data.

BACKGROUND: Proteome-wide Mendelian randomization studies have been increasingly utilized to identify potential drug targets for diseases. We aimed to identify potential therapeutic targets for migraine and its subtypes through the application of Mendelian randomization and co-localization analysis methods. METHODS: We utilized cis-protein quantitative trait loci data for 1378 plasma proteins available from two studies with 7213 individuals and 35,559 individuals, respectively. Summary data for migraine and its subtypes were obtained from a genetic study involving up to 1,339,303 individuals. Proteins that passed both the discovery and validation Mendelian randomization analysis, sensitivity analysis, heterogeneity test, and pleiotropy test, were associated with ≥2 outcomes, and received strong support from co-localization analysis (PP.H4.abf ≥0.80) and were classified as tier 1 proteins. RESULTS: We identified three tier 1 proteins (LRP11, ITIH1, and ADGRF5), whose genes have not been previously identified as causal genes for migraine in genetic studies. LRP11 was significantly associated with the risk of any migraine (OR [odds ratio] = 0.968, 95% CI [confidence interval] = 0.955-0.981, p = 1.27 × 10-6) and significantly/suggestively associated with three migraine subtypes. ITIH1 was significantly associated with the risk of any migraine (OR = 1.044, 95% CI = 1.024-1.065, p = 1.08 × 10-5) and migraine with visual disturbances. ADGRF5 was significantly associated with the risk of any migraine (OR = 0.964, 95% CI = 0.946-0.982, p = 8.74 × 10-5) and suggestively associated with migraine with aura. The effects of LRP11 and ADGRF5 were further replicated using cerebrospinal fluid protein data. Apart from ADGRF5, there was no evidence of potential adverse consequences when modulating the plasma levels. We also identified another four proteins (PLCG1, ARHGAP25, CHGA, and MANBA) with no potential adverse consequences when modulating the plasma levels, and their genes were not reported by previous genetic studies. CONCLUSIONS: We found compelling evidence for two proteins and suggestive evidence for four proteins that could be promising targets for migraine treatment without significant adverse consequences. The corresponding genes were not reported in previous genetic studies. Future studies are needed to confirm the causal role of these proteins and explore the underlying mechanisms.

First-line hepatic arterial infusion chemotherapy plus lenvatinib and PD-(L)1 inhibitors versus systemic chemotherapy alone or with PD-(L)1 inhibitors in unresectable intrahepatic cholangiocarcinoma.

PURPOSE: Limited treatment options exist for unresectable intrahepatic cholangiocarcinoma (ICC), with systemic chemotherapy (SC) serving as the primary approach. This study aimed to assess the effectiveness of first-line hepatic arterial infusion chemotherapy (HAIC) in combination with lenvatinib and PD-(L)1 inhibitors (HLP) compared to SC combined with PD-(L)1 inhibitors (SCP) or SC alone in treating unresectable ICC. METHODS: Patient with unresectable ICC who underwent first-line treatment with HLP, SCP or SC from January 2016 to December 2022 were retrospectively analyzed. The study evaluated and compared efficacy and safety outcomes across the three treatment groups. RESULTS: The study comprised 42, 49, and 50 patients in the HLP, SCP, and SC groups, respectively. Median progression-free survival (PFS) times were 30.0, 10.2, and 6.5 months for HLP, SCP, and SC groups. While the SC group had a median overall survival (OS) time of 21.8 months, the HLP and SCP groups hadn't reached median OS. The HLP group demonstrated significantly superior PFS (p < 0.001) and OS (p = 0.014) compared to the others. Moreover, the HLP group exhibited the highest objective response rate (ORR) at 50.0% and the highest disease control rate (DCR) at 88.1%, surpassing the SC group (ORR, 6.0%; DCR, 52.0%) and SCP group (ORR, 18.4%; DCR, 73.5%) (p < 0.05). Generally, the HLP group reported fewer grades 3-4 adverse events (AEs) compared with others. CONCLUSION: In contrast to systemic chemotherapy with or without PD-(L)1 inhibitors, the triple combination therapy incorporating HAIC, lenvatinib, and PD-(L)1 inhibitors showcased favorable survival benefits and manageable adverse events for unresectable ICC.

Modeling different infectious phases of hepatitis B with generalized saturated incidence: An analysis and control.

Hepatitis B is one of the global health issues caused by the hepatitis B virus (HBV), producing 1.1 million deaths yearly. The acute and chronic phases of HBV are significant because worldwide, approximately 250 million people are infected by chronic hepatitis B. The chronic stage is a long-term, persistent infection that can cause liver damage and increase the risk of liver cancer. In the case of multiple phases of infection, a generalized saturated incidence rate model is more reasonable than a simply saturated incidence because it captures the complex dynamics of the different infection phases. In contrast, a simple saturated incidence rate model assumes a fixed shape for the incidence rate curve, which may not accurately reflect the dynamics of multiple infection phases. Considering HBV and its various phases, we constructed a model to present the dynamics and control strategies using the generalized saturated incidence. First, we proved that the model is well-posed. We then found the reproduction quantity and model equilibria to discuss the time dynamics of the model and investigate the conditions for stabilities. We also examined a control mechanism by introducing various controls to the model with the aim to increase the population of those recovered and minimize the infected people. We performed numerical experiments to check the biological significance and control implementation.

Immunotherapy combined with antiangiogenic therapy as third- or further-line therapy for stage IV non-small cell lung cancer patients with ECOG performance status 2: A retrospective study.

BACKGROUND: Patients with Eastern Cooperative Oncology Group performance status (ECOG PS) 2 probably cannot tolerate chemotherapy or other antitumor therapies. Some studies have reported that immunotherapy combined with antiangiogenic therapy is well-tolerated and shows good antitumor activity. However, the efficacy of this combination as a later-line therapy in patients with ECOG PS 2 is unclear. This study evaluated the effectiveness and safety of this combination strategy as third- or further-line therapy in stage IV non-small cell lung cancer (NSCLC) patients with ECOG PS 2. METHODS: In this retrospective study, patients treated with camrelizumab plus antiangiogenic therapy (bevacizumab, anlotinib, or recombinant human endostatin) were included. Objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), quality of life (QOL) assessed by ECOG PS, and safety were analyzed. RESULTS: Between January 10, 2019, and February 28, 2024, a total of 59 patients were included. The ORR was 35.6% (21/59) and the DCR was 86.4%. With a median follow-up of 10.5 months (range: 0.7-23.7), the median PFS was 5.5 months (95% confidence interval [CI]: 3.8-7.3) and the median OS was 10.5 months (95% CI: 11.2-13.6). QOL was improved (≥1 reduction in ECOG PS) in 39 patients (66.1%). The most common Grade 3-4 treatment-related adverse events were hepatic dysfunction (6 [10%]), hypertension (5 [8%]), and hypothyroidism (3 [5%]). There were no treatment-related deaths. CONCLUSIONS: Third- or further-line immunotherapy combined with antiangiogenic therapy is well-tolerated and shows good antitumor activity in stage IV NSCLC patients with ECOG PS 2. Future large-scale prospective studies are required to confirm the clinical benefits of this combination therapy.

GmDFB1, an ARM-repeat superfamily protein, regulates floral organ identity through repressing siRNA- and miRNA-mediated gene silencing in soybean.

The development of flowers in soybean (Glycine max) is essential for determining the yield potential of the plant. Gene silencing pathways are involved in modulating flower development, but their full elucidation is still incomplete. Here, we conducted a forward genetic screen and identified an abnormal flower mutant, deformed floral bud1-1 (Gmdfb1-1), in soybean. We mapped and identified the causal gene, which encodes a member of the armadillo (ARM)-repeat superfamily. Using small RNA sequencing (sRNA-seq), we found an abnormal accumulation of small interfering RNAs (siRNAs) and microRNA (miRNAs) in the Gmdfb1 mutants. We further demonstrated that GmDFB1 interacts with the RNA exosome cofactor SUPER KILLER7 (GmSKI7). Additionally, GmDFB1 interacts with the PIWI domain of ARGONAUTE 1 (GmAGO1) to inhibit the cleavage efficiency on the target genes of sRNAs. The enhanced gene silencing mediated by siRNA and miRNA in the Gmdfb1 mutants leads to the downregulation of their target genes associated with flower development. This study revealed the crucial role of GmDFB1 in regulating floral organ identity in soybean probably by participating in two distinct gene silencing pathways.

Macrophage-derived CD36 + exosome subpopulations as novel biomarkers of Candida albicans infection.

Invasive candidiasis (IC) is a notable healthcare-associated fungal infection, characterized by high morbidity, mortality, and substantial treatment costs. Candida albicans emerges as a principal pathogen in this context. Recent academic advancements have shed light on the critical role of exosomes in key biological processes, such as immune responses and antigen presentation. This burgeoning body of research underscores the potential of exosomes in the realm of medical diagnostics and therapeutics, particularly in relation to fungal infections like IC. The exploration of exosomal functions in the pathophysiology of IC not only enhances our understanding of the disease but also opens new avenues for innovative therapeutic interventions. In this investigation, we focus on exosomes (Exos) secreted by macrophages, both uninfected and those infected with C. albicans. Our objective is to extract and analyze these exosomes, delving into the nuances of their protein compositions and subgroups. To achieve this, we employ an innovative technique known as Proximity Barcoding Assay (PBA). This methodology is pivotal in our quest to identify novel biological targets, which could significantly enhance the diagnostic and therapeutic approaches for C. albicans infection. The comparative analysis of exosomal contents from these two distinct cellular states promises to yield insightful data, potentially leading to breakthroughs in understanding and treating this invasive fungal infection. In our study, we analyzed differentially expressed proteins in exosomes from macrophages and C. albicans -infected macrophages, focusing on proteins such as ACE2, CD36, CAV1, LAMP2, CD27, and MPO. We also examined exosome subpopulations, finding a dominant expression of MPO in the most prevalent subgroup, and a distinct expression of CD36 in cluster14. These findings are crucial for understanding the host response to C. albicans and may inform targeted diagnostic and therapeutic approaches. Our study leads us to infer that MPO and CD36 proteins may play roles in the immune escape mechanisms of C. albicans. Additionally, the CD36 exosome subpopulations, identified through our analysis, could serve as potential biomarkers and therapeutic targets for C. albicans infection. This insight opens new avenues for understanding the infection's pathology and developing targeted treatments.

Compressed sensing 3D T2WI radiomics model: improving diagnostic performance in muscle invasion of bladder cancer.

BACKGROUND: Preoperative discrimination between non-muscle-invasive bladder cancer (NMIBC) and the muscle invasive bladder cancer (MIBC) is a determinant of management. The purpose of this research is to employ radiomics to evaluate the diagnostic value in determining muscle invasiveness of compressed sensing (CS) accelerated 3D T2-weighted-SPACE sequence with high resolution and short acquisition time. METHODS: This prospective study involved 108 participants who underwent preoperative 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted sequences. The cohort was divided into training and validation cohorts in a 7:3 ratio. In the training cohort, a Rad-score was constructed based on radiomic features selected by intraclass correlation coefficients, pearson correlation coefficient and least absolute shrinkage and selection operator . Multivariate logistic regression was used to develop a nomogram combined radiomics and clinical indices. In the validation cohort, the performances of the models were evaluated by ROC, calibration, and decision curves. RESULTS: In the validation cohort, the area under ROC curve of 3D-CS-T2-weighted-SPACE, 3D-T2-weighted-SPACE and T2-weighted models were 0.87(95% confidence interval (CI):0.73-1.00), 0.79(95%CI:0.63-0.96) and 0.77(95%CI:0.60-0.93), respectively. The differences in signal-to-noise ratio and contrast-to-noise ratio between 3D-CS-T2-weighted-SPACE and 3D-T2-weighted-SPACE sequences were not statistically significant(p > 0.05). While the clinical model composed of three clinical indices was 0.74(95%CI:0.55-0.94) and the radiomics-clinical nomogram model was 0.88(95%CI:0.75-1.00). The calibration curves confirmed high goodness of fit, and the decision curve also showed that the radiomics model and combined nomogram model yielded higher net benefits than the clinical model. CONCLUSION: The radiomics model based on compressed sensing 3D T2WI sequence, which was acquired within a shorter acquisition time, showed superior diagnostic efficacy in muscle invasion of bladder cancer. Additionally, the nomogram model could enhance the diagnostic performance.