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.

Far-infrared therapy promotes exercise capacity and glucose metabolism in mice by modulating microbiota homeostasis and activating AMPK.

The benefits of physical exercise on human health make it desirable to identify new approaches that would mimic or potentiate the effects of exercise to treat metabolic diseases. However, whether far-infrared (FIR) hyperthermia therapy could be used as exercise mimetic to realize wide-ranging metabolic regulation, and its underling mechanisms remain unclear. Here, a specific far-infrared (FIR) rays generated from graphene-based hyperthermia devices might promote exercise capacity and metabolisms. The material characterization showed that the graphene synthesized by chemical vapour deposition (CVD) was different from carbon fiber, with single-layer structure and high electrothermal transform efficiency. The emission spectra generated by graphene-FIR device would maximize matching those adsorbed by tissues. Graphene-FIR enhanced both core and epidermal temperatures, leading to increased blood flow in the femoral muscle and the abdominal region. The combination of microbiomic and metabolomic analysis revealed that graphene-FIR modulates the metabolism of the gut-muscle axis. This modulation was characterized by an increased abundance of short-chain fatty acids (SCFA)-producing bacteria and AMP, while lactic acid levels decreased. Furthermore, the principal routes involved in glucose metabolism, such as glycolysis and gluconeogenesis, were found to be altered. Graphene-FIR managed to stimulate AMPK activity by activating GPR43, thus enhancing muscle glucose uptake. Furthermore, a microbiota disorder model also demonstrated that the graphene-FIR effectively restore the exercise endurance with enhanced p-AMPK and GLUT4. Our results provided convincing evidence that graphene-based FIR therapy promoted exercise capacity and glucose metabolism via AMPK in gut-muscle axis. These novel findings regarding the therapeutic effects of graphene-FIR suggested its potential utility as a mimetic agent in clinical management of metabolic disorders.

An interpretable two-branch bi-coordinate network based on multi-grained domain knowledge for classification of thyroid nodules in ultrasound images.

Computer-aided diagnosis (CAD) for thyroid nodules has been studied for years, yet there are still reliability and interpretability challenges due to the lack of clinically-relevant evidence. To address this issue, inspired by Thyroid Imaging Reporting and Data System (TI-RADS), we propose a novel interpretable two-branch bi-coordinate network based on multi-grained domain knowledge. First, we transform the two types of domain knowledge provided by TI-RADS, namely region-based and boundary-based knowledge, into labels at multi-grained levels: coarse-grained classification labels, and fine-grained region segmentation masks and boundary localization vectors. We combine these two labels to form the Multi-grained Domain Knowledge Representation (MG-DKR) of TI-RADS. Then we design a Two-branch Bi-coordinate network (TB2C-net) which utilizes two branches to predict MG-DKR from both Cartesian and polar images, and uses an attention-based integration module to integrate the features of the two branches for benign-malignant classification. We validated our method on a large cohort containing 3245 patients (with 3558 nodules and 6466 ultrasound images). Results show that our method achieves competitive performance with AUC of 0.93 and ACC of 0.87 compared with other state-of-the-art methods. Ablation experiment results demonstrate the effectiveness of the TB2C-net and MG-DKR, and the knowledge attention map from the integration module provides the interpretability for benign-malignant classification.

Enhancing CO2 storage and marine carbon sink based on seawater mineral carbonation.

Human activities emitting carbon dioxide (CO2) have caused severe greenhouse effects and accelerated climate change, making carbon neutrality urgent. Seawater mineral carbonation technology offers a promising negative emission strategy. This work investigates current advancements in proposed seawater mineral carbonation technologies, including CO2 storage and ocean chemical carbon sequestration. CO2 storage technology relies on indirect mineral carbonation to fix CO2, involving CO2 dissolution, Ca/Mg extraction, and carbonate precipitation, optimized by adding alkaline substances or using electrochemical methods. Ocean chemical carbon sequestration uses natural seawater for direct mineral carbonation, enhanced by adding specific materials to promote carbonate precipitation and increase CO2 absorption, thus enhancing marine carbon sinks. This study evaluates these technologies' advantages and challenges, including reaction rates, costs, and ecological impacts, and analyzes representative materials' carbon fixation potential. Literature indicates that seawater mineral carbonation can play a significant role in CO2 storage and enhancing marine carbon sinks in the coming decades.

Optic nerve decompression through pterional and supraorbital approaches in the treatment of severe traumatic optic neuropathy.

To investigate the effectiveness of optic nerve decompression (OND) in the treatment of severe traumatic optic neuropathy (TON) through pterional and supraorbital approaches, and to identify the prognostic factor for postoperative visual acuity (VA) following OND. Patients with severe TON treated with OND through either pterional or supraorbital approach in our institute from September 2019 to June 2022 were retrospectively reviewed in this study. Demographic information, trauma factors, the interval between trauma and complete blindness, the interval between trauma and surgery, and the associated craniofacial traumas were recorded. Hospitalization days and the postoperative VA of patients in two groups were compared. There were 54 severe TON patients with NLP included in this study; 21 patients underwent OND through the pterional approach, and the other 33 underwent the supraorbital approach. Respectively, in groups of pterional and supraorbital approaches, the average hospitalization days were 9.8 ± 3.2 and 10.7 ± 2.9 days (p = 0.58), the mean durations of follow-up were 18.9 ± 4.3 and 20.8 ± 3.7 months (p = 0.09), and the average circumference of OND were 53.14 ± 15.89 ◦ (range 220 ◦ -278◦) and 181.70 ± 6.56◦ (range 173 ◦ -193◦) (p<0.001). The overall improvement rates of pterional and supraorbital approaches are 57.1% and 45.5% (p = 0.40), respectively. Optic canal fracture (OCF) was revealed to be significantly associated with postoperative VA in the supraorbital approach (Binary: p = 0.014, CI: 1.573-57.087; Ordinal: p = 0.003, CI: 1.517-5.503), but not in the pterional approach. In the group of supraorbital approach, patients with OFC had a higher rate of a better outcome (78.6%) than those without (21.4%). Patients with severe traumatic TON may benefit from OND through either the pterional or supraorbital approach. OCF is a potential prognostic factor for postoperative VA following OND through the supraorbital approach.

Chemoenzymatic Synthesis of Fluorinated Mycocyclosin Enabled by the Engineered Cytochrome P450-Catalyzed Biaryl Coupling Reaction.

Installing fluorine atoms onto natural products holds great promise for the generation of fluorinated molecules with improved or novel pharmacological properties. The enzymatic oxidative carbon-carbon coupling reaction represents a straightforward strategy for synthesizing biaryl architectures, but the exploration of this method for producing fluorine-substituted derivatives of natural products remains elusive. Here, in this study, we report the protein engineering of cytochrome P450 from Mycobacterium tuberculosis (MtCYP121) for the construction of a series of new-to-nature fluorine-substituted Mycocyclosin derivatives. This protocol takes advantage of a "hybrid" chemoenzymatic procedure consisting of tyrosine phenol lyase-catalyzed fluorotyrosine preparation from commercially available fluorophenols, intermolecular chemical condensation to give cyclodityrosines, and an engineered MtCYP121-catalyzed intramolecular biphenol coupling reaction to complete the strained macrocyclic structure. Computational mechanistic studies reveal that MtCYP121 employs Cpd I to abstract a hydrogen atom from the proximal phenolic hydroxyl group of the substrate to trigger the reaction. Then, conformational change makes the two phenolic hydroxyl groups close enough to undergo intramolecular hydrogen atom transfer with the assistance of a pocket water molecule. The final diradical coupling process completes the intramolecular C-C bond formation. The efficiency of the biaryl coupling reaction was found to be influenced by various fluorine substitutions, primarily due to the presence of distinct binding conformations.

SiO 2 Induces Iron Overload and Ferroptosis in Cardiomyocytes in a Silicosis Mouse Model.

Objective: The aim of this study was to explore the role and mechanism of ferroptosis in SiO 2-induced cardiac injury using a mouse model. Methods: Male C57BL/6 mice were intratracheally instilled with SiO 2 to create a silicosis model. Ferrostatin-1 (Fer-1) and deferoxamine (DFO) were used to suppress ferroptosis. Serum biomarkers, oxidative stress markers, histopathology, iron content, and the expression of ferroptosis-related proteins were assessed. Results: SiO 2 altered serum cardiac injury biomarkers, oxidative stress, iron accumulation, and ferroptosis markers in myocardial tissue. Fer-1 and DFO reduced lipid peroxidation and iron overload, and alleviated SiO 2-induced mitochondrial damage and myocardial injury. SiO 2 inhibited Nuclear factor erythroid 2-related factor 2 (Nrf2) and its downstream antioxidant genes, while Fer-1 more potently reactivated Nrf2 compared to DFO. Conclusion: Iron overload-induced ferroptosis contributes to SiO 2-induced cardiac injury. Targeting ferroptosis by reducing iron accumulation or inhibiting lipid peroxidation protects against SiO 2 cardiotoxicity, potentially via modulation of the Nrf2 pathway.

Insight into volatile-char interaction mechanisms of biomass torrefaction based on three major components.

Volatile-char interaction is an important phenomenon in biomass thermal conversion process, which significantly contributes to the decomposition, deoxygenation and upgrading of biomass. However, the deep insight into volatile-char interaction mechanisms between hemicellulose, cellulose and lignin is currently unclear. In this work, above mechanism was studied through systematic single-/bi-component torrefactions and the follow-up char analysis. Results demonstrate that only hemicellulose volatile and cellulose char interaction exists during torrefaction at 250 °C, causing over 19.9 wt% of mass loss and 27.3 wt% of O removal for cellulose. This volatile-char interaction causes significant depolymerization and amorphization of cellulose by hydrolysis, acid hydrolysis and esterification reactions. The depolymerized and amorphous cellulose partly thermally decomposes to dehydrated sugars and aromatic compounds through dehydroxylation and aromatization reactions. A volatile-char interaction mechanism model is thus developed. This work provides theoretical insight into biomass thermal conversion and provides basis for the development of new thermochemical method.

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.

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.

Metabolomics combined with network pharmacology reveals the potential development value of Campanumoea javanica Bl. and its metabolite differences with Codonopsis Radix.

Campanumoea javanica Bl. (CJ) traditionally used in Southwestern China, is now widely consumed as a health food across the nation. Due to its similar efficacy to Codonopsis Radix (CR) and their shared botanical family, CJ is often used as a substitute for CR. According to the Chinese Pharmacopoeia, Codonopsis pilosula var. modesta (Nannf.) L.T. Shen (CPM), Codonopsis pilosula (Franch.) Nannf. (CP), and Codonopsis tangshen Oliv. (CT) are the primary sources of CR. However, details on the differences in composition, effectiveness, and compositional between CJ and CR are still limited. Besides, there is little evidence to support the application of CJ as a drug. In this study, we employed widely targeted metabolomics, network pharmacology analysis, and molecular docking to explore the disparities in metabolite profiles between CJ and CR and to predict the pharmacological mechanisms of the dominant differential metabolites of CJ and their potential medicinal applications. The widely targeted metabolomics results indicated that 1,076, 1,102, 1,102, and 1,093 compounds, most phenolic acids, lipids, amino acids, and flavonoids, were characterized in CJ, CPM, CP, and CT, respectively. There were an average of 1061 shared compounds in CJ and CRs, with 95.07% similarity in metabolic profiles. Most of the metabolites in CJ were previously unreported. Twelve of the seventeen dominant metabolites found in CJ were directly associated with treating cancer and lactation, similar to the traditional medicinal efficacy. The molecular docking results showed that the dominant metabolites of CJ had good docking activity with the core targets PIK3R1, PIK3CA, ESR1, HSP90AA1, EGFR, and AKT1. This study provides a scientific basis for understanding the similarities and differences between CJ and CR at the metabolome level, offering a theoretical foundation for developing innovative medications from CJ. Additionally, it significantly enhances the metabolite databases for both CJ and CR.

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.

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 histologic examination are the standard for determining histologic 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 histologic 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. SIGNIFICANCE: This study explores the use of cfDNA methylomes for the classification of lung cancer subtypes, vital for effective treatment. By identifying specific methylation markers in tumor tissues, we developed a robust classification model achieving high accuracy for noninvasive subtype detection. This cfDNA methylome approach offers promising avenues for early detection and monitoring.

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.

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.

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.

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.

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.

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.