Hounsfield unit for assessing bone mineral density distribution within lumbar vertebrae and its clinical values.

Study Design: Retrospective radiological analysis. Objective: The aim of this study is to evaluate the distribution of bone mineral density (BMD) in lumbar vertebrae using the Hounsfield unit (HU) measurement method and investigate the clinical implications of HU values for assessing lumbar vertebrae BMD. Method: Two hundred and ninety-six patients were retrospectively reviewed and divided into six groups according to age: Group 1(20-29 years old), Group 2 (30-39 years old), Group 3 (40-49 years old), Group 4 (50-59 years old), Group 5 (60-69 years old), Group 6 (70-79 years old). Six different locations from each vertebra of L1-L5 were selected as regions of interest: the anterior, middle and posterior parts of the upper and lower slices of the vertebrae. HU values were measured for the six regions of interest, followed by statistical analysis. Results: The HU values of vertebrae showed a decreasing trend from young patients to elderly patients in Group 1 to Group 5. There was no significant difference in HU values among different vertebrae in the same age group. In all age groups, the HU values of the anterior and posterior part of the vertebral body were significantly different from L1 to L3, with the anterior part of the vertebral body having lower HU values than the posterior part. The HU values of the anterior and posterior part of the vertebral body of L4 and L5 were statistically significant only in Group 5 and Group 6, and the HU values of the anterior part of the vertebral body were lower than those of the posterior part. The HU values of posterior part of L4 and L5 in Group6 were higher than those in Group5. Conclusion: Bone mineral density in the lumbar vertebrae is not uniformly distributed, potentially attributed to varying stress stimuli. The assessment of local HU values in the lumbar spine is of significant importance for surgical treatment.

A Traditional Chinese Medicine, Zhenqi Granule, Potentially Alleviates Dextran Sulfate Sodium-Induced Mouse Colitis Symptoms.

Ulcerative colitis (UC) is an inflammatory bowel disease that causes chronic inflammation in the large intestine. The etiology of UC is complex and incompletely understood, with potential contributing factors including genetic susceptibility, environmental influences, immune dysregulation, and gut barrier dysfunction. Despite available therapeutic drugs, the suboptimal cure rate for UC emphasizes the necessity of developing novel therapeutics. Traditional Chinese Medicine (TCM) has attracted great interest in the treatment of such chronic inflammatory diseases due to its advantages, such as multi-targets and low side effects. In this study, a mouse model of Dextran Sulfate Sodium (DSS)-induced acute colitis was established and the efficacy of Zhenqi Granule, a TCM preparation composed of the extractives from Astragali Radix and Fructus Ligustri Lucidi, was evaluated. The results showed that treatment with Zhenqi Granule prior to or post-DSS induction could alleviate the symptoms of colitis, including weight loss, diarrhea, hematochezia, colon length shortening, and pathological damage of colon tissues of the DSS-treated mice. Further, network pharmacology analysis showed that there were 98 common targets between the active components of Zhenqi Granule and the targets of UC, and the common targets were involved in the regulation of inflammatory signaling pathways. Our results showed that Zhenqi Granule had preventive and therapeutic effects on acute colitis in mice, and the mechanism may be that the active components of Zhenqi Granule participated in the regulation of inflammatory response. This study provided data reference for further exploring the mechanism of Zhenqi Granule and also provided potential treatment strategies for UC.

Molecular mechanism of substrate recognition and cleavage by human γ-secretase.

Successive cleavages of amyloid precursor protein C-terminal fragment with 99 residues (APP-C99) by γ-secretase result in amyloid-ß (Aß) peptides of varying lengths. Most cleavages have a step size of three residues. To elucidate the underlying mechanism, we determined the atomic structures of human γ-secretase bound individually to APP-C99, Aß49, Aß46, and Aß43. In all cases, the substrate displays the same structural features: a transmembrane α-helix, a three-residue linker, and a ß-strand that forms a hybrid ß-sheet with presenilin 1 (PS1). Proteolytic cleavage occurs just ahead of the substrate ß-strand. Each cleavage is followed by unwinding and translocation of the substrate α-helix by one turn and the formation of a new ß-strand. This mechanism is consistent with existing biochemical data and may explain the cleavages of other substrates by γ-secretase.

Development of the fetal brain cortico-cortical structural network during the second-to-third trimester based on diffusion MRI.

During the second-to-third trimester, the neuronal pathways of the fetal brain experience rapid development, resulting in the complex architecture of the inter-wired network at birth. While diffusion MRI-based tractography has been employed to study the prenatal development of structural connectivity network (SCN) in preterm neonatal and post-mortem fetal brains, the in-utero development of SCN in the normal fetal brain remains largely unknown. In this study, we utilized in-utero dMRI data from human fetuses of both sexes between 26 to 38 gestational weeks to investigate the developmental trajectories of the fetal brain SCN, focusing on intra-hemispheric connections. Our analysis revealed significant increases in global efficiency, mean local efficiency, and clustering coefficient, along with significant decrease in shortest path length, while small-worldness persisted during the studied period, revealing balanced network integration and segregation. Widespread short-ranged connectivity strengthened significantly. The nodal strength developed in a posterior-to-anterior and medial-to-lateral order, reflecting a spatiotemporal gradient in cortical network connectivity development. Moreover, we observed distinct lateralization patterns in the fetal brain SCN. Globally, there was a leftward lateralization in network efficiency, clustering coefficient, and small-worldness. The regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge, except for the Wernicke's area, indicating lateralized brain wiring is an innate property of the human brain starting from the fetal period. Our findings provided a comprehensive view of the development of the fetal brain SCN and its lateralization, as a normative template that may be used to characterize atypical development.Significance Statement We studied the normal development of intra-hemispheric cortico-cortical structural connectivity networks (SCNs) of the fetal brain from 26 to 38 gestational weeks using in-utero diffusion MRI data. Graph-theory-based analysis revealed significant enhancement in network efficiency and clustering, as well as persisted small-worldness with age, revealing balanced integration and segregation in the fetal brain SCN during the studied period, supported by regional developmental patterns. Leftward lateralization in network efficiency, clustering coefficient and small-worldness was observed. Regional lateralization patterns in most language, motor, and visual-related areas were consistent with prior knowledge. We also summarized the challenges of investigating the fetal brain SCN development, and provided suggestions for future studies.

Population interaction network in representative gravitational search algorithms: Logistic distribution leads to worse performance.

In this paper, a novel study on the way inter-individual information interacts in meta-heuristic algorithms (MHAs) is carried out using a scheme known as population interaction networks (PIN). Specifically, three representative MHAs, including the differential evolutionary algorithm (DE), the particle swarm optimization algorithm (PSO), the gravitational search algorithm (GSA), and four classical variations of the gravitational search algorithm, are analyzed in terms of inter-individual information interactions and the differences in the performance of each of the algorithms on IEEE Congress on Evolutionary Computation 2017 benchmark functions. The cumulative distribution function (CDF) of the node degree obtained by the algorithm on the benchmark function is fitted to the seven distribution models by using PIN. The results show that among the seven compared algorithms, the more powerful DE is more skewed towards the Poisson distribution, and the weaker PSO, GSA, and GSA variants are more skewed towards the Logistic distribution. The more deviation from Logistic distribution GSA variants conform, the stronger their performance. From the point of view of the CDF, deviating from the Logistic distribution facilitates the improvement of the GSA. Our findings suggest that the population interaction network is a powerful tool for characterizing and comparing the performance of different MHAs in a more comprehensive and meaningful way.

Proton pump inhibitors stabilize the expression of PD-L1 on cell membrane depending on the phosphorylation of GSK3ß.

BACKGROUND: Preclinical and clinical evidence indicates that proton pump inhibitors (PPIs) may indirectly diminish the microbiome diversity, thereby reducing the effectiveness of immune checkpoint inhibitors (ICIs). Conversely, recent publications have shown that PPIs could potentially enhance the response to ICIs. The precise mechanism through which PPIs modulate the ICIs remains unclear. In this study, we discovered a novel molecular function of PPIs in regulating immune invasion, specifically through inducing PD-L1 translocation in various tumor cells. METHODS: C57BL/6 mice subcutaneous transplantation model is used to verify the potential efficacy of PPIs and PD-L1 antibody. Western blotting analysis and phosphorylated chip are used to verify the alteration of PD-L1-related pathways after being treated with PPIs. The related gene expression is performed by qRT-PCR and luciferase reporter analysis. We also collected 60 clinical patients diagnosed with esophageal cancer or reflux esophagitis and then detected the expression of PD-L1 in the tissue samples by immunohistochemistry. RESULTS: We observed that the IC50 of tumor cells in response to PPIs was significantly higher than that of normal epithelial cells. PPIs significantly increased the expression of PD-L1 on cell membrane at clinically relevant concentrations. Furthermore, pre-treatment with PPIs appeared to synergize the efficiency of anti-PD-L1 antibodies in mouse models. However, PPI administration did not alter the transcription or total protein level of PD-L1 in multiple tumor cells. Using a phosphorylated protein chip, we identified that PPIs enhanced the phosphorylation of GSK3ß, then leading to PD-L1 protein translocation to the cell membranes. The capacity of PPIs to upregulate PD-L1 was negated following GSK3ß knockout. Furthermore, our clinical data showed that the PPIs use resulted in increased PD-L1 expression in esophageal cancer patients. CONCLUSION: We mainly address a significant and novel mechanism that the usage of PPIs could directly induce the expression of PD-L1 by inducing GSK3ß phosphorylation and facilitate primary tumor progression and metastasis.

Epileptic Seizure Prediction Using Spatiotemporal Feature Fusion on EEG.

Electroencephalography (EEG) plays a crucial role in epilepsy analysis, and epileptic seizure prediction has significant value for clinical treatment of epilepsy. Currently, prediction methods using Convolutional Neural Network (CNN) primarily focus on local features of EEG, making it challenging to simultaneously capture the spatial and temporal features from multi-channel EEGs to identify the preictal state effectively. In order to extract inherent spatial relationships among multi-channel EEGs while obtaining their temporal correlations, this study proposed an end-to-end model for the prediction of epileptic seizures by incorporating Graph Attention Network (GAT) and Temporal Convolutional Network (TCN). Low-pass filtered EEG signals were fed into the GAT module for EEG spatial feature extraction, and followed by TCN to capture temporal features, allowing the end-to-end model to acquire the spatiotemporal correlations of multi-channel EEGs. The system was evaluated on the publicly available CHB-MIT database, yielding segment-based accuracy of 98.71%, specificity of 98.35%, sensitivity of 99.07%, and F1-score of 98.71%, respectively. Event-based sensitivity of 97.03% and False Positive Rate (FPR) of 0.03/h was also achieved. Experimental results demonstrated this system can achieve superior performance for seizure prediction by leveraging the fusion of EEG spatiotemporal features without the need of feature engineering.

Thermal degradation of greenhouse gas SF6 at realistic temperatures: Insights from atomic-scale CVHD simulations.

Sulfur hexafluoride (SF6), recognized as a potent greenhouse gas with significant contributions to climate change, presents challenges in understanding its degradation processes. Molecular dynamics simulations are valuable tools for understanding modes of decomposition while the traditional approaches face limitations in time scale and require unrealistically high temperatures. The collective variable-driven hyperdynamics (CVHD) approach has been introduced to directly depict the pyrolysis process for SF6 gas at practical application temperatures, as low as 1600 K for the first time. Achieving an unprecedented acceleration factor of up to 107, the method extends the simulation time scale to milliseconds and beyond while maintaining consistency with experimental and theoretical models. The differences in the reaction process between simulations conducted at actual and elevated temperatures have been noted, providing insights into SF6 degradation pathways. The work provides a basis for the further studies on the thermal degradation of pollutants.

Reviving Static Charts into Live Charts.

Data charts are prevalent across various fields due to their efficacy in conveying complex data relationships. However, static charts may sometimes struggle to engage readers and efficiently present intricate information, potentially resulting in limited understanding. We introduce "Live Charts," a new format of presentation that decomposes complex information within a chart and explains the information pieces sequentially through rich animations and accompanying audio narration. We propose an automated approach to revive static charts into Live Charts. Our method integrates GNN-based techniques to analyze the chart components and extract data from charts. Then we adopt large natural language models to generate appropriate animated visuals along with a voice-over to produce Live Charts from static ones. We conducted a thorough evaluation of our approach, which involved the model performance, use cases, a crowd-sourced user study, and expert interviews. The results demonstrate Live Charts offer a multi-sensory experience where readers can follow the information and understand the data insights better. We analyze the benefits and drawbacks of Live Charts over static charts as a new information consumption experience.

Probiotic-derived amphiphilic exopolysaccharide self-assembling adjuvant delivery platform for enhancing immune responses.

Enhancing immune response activation through the synergy of effective antigen delivery and immune enhancement using natural, biodegradable materials with immune-adjuvant capabilities is challenging. Here, we present NAPSL.p that can activate the Toll-like receptor 4 (TLR4) pathway, an amphiphilic exopolysaccharide, as a potential self-assembly adjuvant delivery platform. Its molecular structure and unique properties exhibited remarkable self-assembly, forming a homogeneous nanovaccine with ovalbumin (OVA) as the model antigen. When used as an adjuvant, NAPSL.p significantly increased OVA uptake by dendritic cells. In vivo imaging revealed prolonged pharmacokinetics of NAPSL. p-delivered OVA compared to OVA alone. Notably, NAPSL.p induced elevated levels of specific serum IgG and isotype titers, enhancing rejection of B16-OVA melanoma xenografts in vaccinated mice. Additionally, NAPSL.p formulation improved therapeutic effects, inhibiting tumor growth, and increasing animal survival rates. The nanovaccine elicited CD4+ and CD8+ T cell-based immune responses, demonstrating the potential for melanoma prevention. Furthermore, NAPSL.p-based vaccination showed stronger protective effects against influenza compared to Al (OH)3 adjuvant. Our findings suggest NAPSL.p as a promising, natural self-adjuvanting delivery platform to enhance vaccine design across applications.

Improving Microstructural Estimation in Time-Dependent Diffusion MRI With a Bayesian Method.

BACKGROUND: Accurately fitting diffusion-time-dependent diffusion MRI (td-dMRI) models poses challenges due to complex and nonlinear formulas, signal noise, and limited clinical data acquisition. PURPOSE: Introduce a Bayesian methodology to refine microstructural fitting within the IMPULSED (Imaging Microstructural Parameters Using Limited Spectrally Edited Diffusion) model and optimize the prior distribution within the Bayesian framework. STUDY TYPE: Retrospective. POPULATION: Involving 69 pediatric patients (median age 6 years, interquartile range [IQR] 3-9 years, 61% male) with 41 low-grade and 28 high-grade gliomas, of which 76.8% were identified within the brainstem or cerebellum. FIELD STRENGTH/SEQUENCE: 3 T, oscillating gradient spin-echo (OGSE) and pulsed gradient spin-echo (PGSE). ASSESSMENT: The Bayesian method's performance in fitting cell diameter ( d $$ d $$ ), intracellular volume fraction ( f in $$ {f}_{in} $$ ), and extracellular diffusion coefficient ( D ex $$ {D}_{ex} $$ ) was compared against the NLLS method, considering simulated and experimental data. The tumor region-of-interest (ROI) were manually delineated on the b0 images. The diagnostic performance in distinguishing high- and low-grade gliomas was assessed, and fitting accuracy was validated against H&E-stained pathology. STATISTICAL TESTS: T-test, receiver operating curve (ROC), area under the curve (AUC) and DeLong's test were conducted. Significance considered at P < 0.05. RESULTS: Bayesian methodology manifested increased accuracy with robust estimates in simulation (RMSE decreased by 29.6%, 40.9%, 13.6%, and STD decreased by 29.2%, 43.5%, and 24.0%, respectively for d $$ d $$ , f in $$ {f}_{in} $$ , and D ex $$ {D}_{ex} $$ compared to NLLS), indicating fewer outliers and reduced error. Diagnostic performance for tumor grade was similar in both methods, however, Bayesian method generated smoother microstructural maps (outliers ratio decreased by 45.3% ± 19.4%) and a marginal enhancement in correlation with H&E staining result (r = 0.721 for f in $$ {f}_{in} $$ compared to r = 0.698 using NLLS, P = 0.5764). DATA CONCLUSION: The proposed Bayesian method substantially enhances the accuracy and robustness of IMPULSED model estimation, suggesting its potential clinical utility in characterizing cellular microstructure. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

Integrated Approaches Revealed the Therapeutic Mechanisms of Zuojin Pill Against Gastric Mucosa Injury in a Rat Model with Chronic Atrophic Gastritis.

Background: The Zuojin Pill (ZJP) is widely used for treating chronic atrophic gastritis (CAG) in clinical practice, effectively ameliorating symptoms such as vomiting, pain, and abdominal distension in patients. However, the underlying mechanisms of ZJP in treating CAG has not been fully elucidated. Purpose: This study aimed to clarify the characteristic function of ZJP in the treatment of CAG and its potential mechanism. Methods: The CAG model was established by alternant administrations of ammonia solution and sodium deoxycholate, as well as an irregular diet. Therapeutic effects of ZJP on body weight, serum biochemical indexes and general condition were analyzed. HE staining and AB-PAS staining were analyzed to characterize the mucosal injury and the thickness of gastric mucosa. Furthermore, network pharmacology and molecular docking were used to predict the regulatory mechanism and main active components of ZJP in CAG treatment. RT-PCR, immunohistochemistry, immunofluorescence and Western blotting were used to measure the expression levels of apoptosis-related proteins, gastric mucosal barrier-associated proteins and PI3K/Akt signaling pathway proteins. Results: The results demonstrated that ZJP significantly improved the general state of CAG rats, alleviated weight loss and gastric histological damage and reduced the serum biochemical indicators. Network pharmacology and molecular docking found that ZJP in treating CAG by inhibiting inflammation, suppressing apoptosis, and protecting the gastric mucosal barrier via the PI3K/Akt signaling pathway. Further experiments confirmed that ZJP obviously modulated the expression of key proteins involved in gastric mucosal cell apoptosis, such as Bax, Bad, Apaf-1, cleaved-caspase-3, cleaved-caspase-9, Cytochrome C, Bcl-2, and Bcl-xl. Moreover, ZJP significantly reversed the protein expression of Occludin, ZO-1, Claudin-4 and E-cadherin. Conclusion: Our study revealed that ZJP treats CAG by inhibiting the PI3K/Akt signaling pathway. This research provided a scientific basis for the rational use of ZJP in clinical practice.

Quaternary Ammonium Assisted Synthesis of Melanin-like Poly(l-DOPA) Nanoparticles with a Boosted Photothermal Effect.

Poly(levodopa) nanoparticles (P(l-DOPA) NPs) are another kind of melanin mimetic besides well-established polydopamine nanoparticles (PDA NPs). Due to the presence of carboxyl groups, the oxidative polymerization of l-DOPA to obtain particles was not as efficient as that of dopamine. Several established methods toward P(l-DOPA) NP fabrication do not combine convenience, morphological regularity, size controllability, low cost, and adaptability to metal-free application scenarios. In this work, P(l-DOPA) NPs were successfully prepared in hot water with the assistant of organic quaternary ammonium, due to the extra physical cross-linking mediated by cations. The employed physical interactions could also be affected by quaternary ammonium structure (i.e., number of cation heads, length of alkyl chain) to achieve different polymerization acceleration effects. The obtained P(l-DOPA) NPs retained superior photothermal properties and outperformed PDA-based melanin materials. Furthermore, P(l-DOPA) NPs were used in photothermal tumor therapy and showed better efficacy. This study offers new insights into the synthesis of melanin-like materials, as well as new understanding of the interaction between quaternary ammonium and bioinspired polyphenolic materials.

A Fuzzy-PI Clock Servo with Window Filter for Compensating Queue-Induced Delay Asymmetry in IEEE 1588 Networks.

Clock synchronization is one of the popular research topics in Distributed Measurement and Control Systems (DMCSs). In most industrial fields, such as Smart Grid and Flight Test, the highest requirement for synchronization accuracy is 1 µs. IEEE 1588 Precision Time Protocol-2008 (PTPv2) can theoretically achieve sub-microsecond accuracy, but it relies on the assumption that the forward and backward delays of PTP packets are symmetrical. In practice, PTP packets will experience random queue delays in switches, making the above assumption challenging to satisfy and causing poor synchronization accuracy. Although using switches supporting the Transparent Clock (TC) can improve synchronization accuracy, these dedicated switches are generally expensive. This paper designs a PTP clock servo for compensating Queue-Induced Delay Asymmetry (QIDA), which can be implemented based on ordinary switches. Its main algorithm comprises a minimum window filter with drift compensation and a fuzzy proportional-integral (PI) controller. We construct a low-cost hardware platform (the cost of each node is within USD 10) to test the performance of the clock servo. In a 100 Mbps network with background (BG) traffic of less than 70 Mbps, the maximum absolute time error (max |TE|) does not exceed 0.35 µs, and the convergence time is about half a minute. The accuracy is improved hundreds of times compared with other existing clock servos.

A comparative study of satellite altimetry-based and DEM-based methods for estimating lake water volume changes.

This study compared two different methods, the satellite altimetry-based and DEM (digital elevation model)-based, for estimating lake water volume changes. We focused on 34 lakes in China as the testing sites to compare the two methods for lake water volume changes from 2005 to 2020. The satellite altimetry-based method used water levels provided by the DAHITI (Database for Hydrological Time Series of Inland Waters) data and surface areas derived from Landsat imagery. The DEM-based method used the SRTM DEM data in combination with Landsat-derived lake extents. Our results showed a high degree of consistency in lake water volume changes estimated between the two methods (R2 > 0.90), but each method has its limitations. In terms of temporal coverage, the satellite altimetry-based method with the DAHITI data is limited by missing water level data in certain periods. The performance of the DEM-based method in extracting lake shore boundaries in regions with flat terrains (slope <1.5°) is not satisfactory. The DEM-based method has complete regional applicability (100%) in the Tibetan Plateau (TP) Lake Region, yet its effectiveness drops significantly in the Xinjiang and Eastern China Plain Lake Regions, with applicability rates of 50 and 40%, respectively.

The contribution of small heterodimer partner to the occurrence and progression of cholestatic liver injury.

BACKGROUND AND AIM: Small heterodimer partner (SHP, encoded by NR0B2) plays an important role in maintaining bile acid homeostasis. The loss of the hepatic farnesoid X receptor (FXR)/SHP signal can cause severe cholestatic liver injury (CLI). FXR and SHP have overlapping and nonoverlapping functions in bile acid homeostasis. However, the key role played by SHP in CLI is unclear. METHODS: In this study, an alpha-naphthylisothiocyanate (ANIT)-induced cholestasis mouse model was established. The effect of SHP knockout (SHP-KO) on liver and ileal pathology was evaluated. 16S rRNA gene sequencing analysis combined with untargeted metabolomics was applied to reveal the involvement of SHP in the pathogenesis of CLI. RESULTS: The results showed that ANIT (75 mg/kg) induced cholestasis in WT mice. No significant morphological changes were found in the liver and ileal tissue of SHP-KO mice. However, the serum metabolism and intestinal flora characteristics were significantly changed. Moreover, compared with the WT + ANIT group, the serum levels of ALT and AST in the SHP-KO + ANIT group were significantly increased, and punctate necrosis in the liver tissue was more obvious. The ileum villi showed obvious shedding, thinning, and shortening. In addition, SHP-KO-associated differential intestinal flora and differential biomarkers were significantly associated. CONCLUSION: In this study, we elucidated the serum metabolic characteristics and intestinal flora changes related to the aggravation of CLI in SHP-KO mice induced by ANIT.

Advances of Transition Metal-Based Electrochemical Non-enzymatic Glucose Sensors for Glucose Analysis: A Review.

Glucose concentration is a crucial parameter for assessing human health. Over recent years, non-enzymatic electrochemical glucose sensors have drawn considerable attention due to their substantial progress. This review explores the common mechanism behind the transition metal-based electrocatalytic oxidation of glucose molecules through classical electrocatalytic frameworks like the Pletcher model and the Hydrous Oxide-Adatom Mediator model (IHOAM), as well as the redox reactions at the transition metal centers. It further compiles the electrochemical characterization techniques, associated formulas, and their ensuing conclusions pertinent to transition metal-based non-enzymatic electrochemical glucose sensors. Subsequently, the review covers the latest advancements in the field of transition metal-based active materials and support materials used in non-enzymatic electrochemical glucose sensors in the last decade (2014-2023). Additionally, it presents a comprehensive classification of representative studies according to the active metal catalysts components involved.

Expeditious Synthesis of Gwanakoside A and the Chloronaphthol Glycoside Congeners.

The synthesis of gwanakoside A, a chlorinated naphthol bis-glycoside, and its analogues was achieved through stepwise chlorination and donor-equivalent controlled regioselective phenol glycosylation with glycosyl N-phenyltrifluoroacetimidates as donors. Gwanakoside A displayed considerable inhibitory effects against various cancer cells and Staphylococcus aureus strains.

UV absorption enhanced polydopamine coating.

Mussel-inspired polydopamine (PDA) coatings have gained significant attention in various fields, including biomedicine, energy, detection, and UV protection, owing to their versatile and promising properties. Among these properties, UV shielding stands out as a key feature of PDA coatings. Nevertheless, the current methods for tuning the UV-shielding properties of PDA coatings are quite limited, and only rely on thickness adjustment, which might involve additional issues like color and visible light transmittance to the coating layer. In this study, we propose a facile and modular approach to enhance the UV absorption of PDA coatings by incorporating thiol-heterocycle (TH) derivatives. Both pre- and post-modification strategies can effectively impede the formation of conjugated structures within PDA, leading to enhanced UV absorption within the PDA layers. More importantly, these strategies can improve the UV absorption of PDA coatings while reducing the visible light absorption. Furthermore, this method enabled efficient regulation of the UV absorption of PDA coatings by altering the ring type (benzene ring or pyridine ring) and substituent on the ring (methoxyl group or hydrogen atom). These PDA coatings with enhanced UV absorption demonstrate great promise for applications in UV protection, antibacterial activity, wound healing and dye degradation.

Access to pyrrolines and fused diaziridines by selective radical addition to homoallylic diazirines.

Pyrroline derivatives are common in bioactive natural products and therapeutic agents. We report here a synthesis of pyrrolines and fused diaziridines by divergent radical cyclization of homoallylic diazirines, which can serve as an internal radical trap and a nitrogen source. This reaction proceeds by selective radical addition to C[double bond, length as m-dash]C or N[double bond, length as m-dash]N bonds followed by intramolecular cyclization. Frontier molecular orbital analysis provides a deep insight into the origin of the selectivity. The reaction demonstrates a new cyclization mode, broad functional group compatibility and high product diversity, and reveals a much broader chemical space for diazirine studies.