Stereochemical Control of Redox CoII/CoIII-Cages with Switchable Cotton Effects Based on Labile-Static States.

The structural dynamics of artificial assemblies, in aspects such as molecular recognition and structural transformation, provide us with a blueprint to achieve bioinspired applications. Here, we describe the assembly of redox-switchable chiral metal-organic cages Λ8/Δ8-[Pd6(CoIIL3)8]28+ and Λ8/Δ8-[Pd6(CoIIIL3)8]36+. These isomeric cages demonstrate an on-off chirality logic gate controlled by their chemical and stereostructural dynamics tunable through redox transitions between the labile CoII-state and static CoIII-state with a distinct Cotton effect. The transition between different states is enabled by a reversible redox process and chiral recognition originating in the tris-chelate Co-centers. All cages in two states are thoroughly characterized by NMR, ESI-MS, CV, CD, and X-ray crystallographic analysis, which clarify their redox-switching behaviors upon chemical reduction/oxidation. The stereochemical lability of the CoII-center endows the Λ8/Δ8-CoII-cages with efficient chiral-induction by enantiomeric guests, leading to enantiomeric isomerization to switch between Λ8/Δ8-CoII-cages, which can be stabilized by oxidation to their chemically inert forms of Λ8/Δ8-CoIII-cages. Kinetic studies reveal that the isomerization rate of the Δ8-CoIII-cage is at least an order of magnitude slower than that of the Δ8-CoII-cage even at an elevated temperature, while its activation energy is 16 kcal mol-1 higher than that of the CoII-cage.

Dynamic Stereochemistry of M8 Pd6 Supramolecular Cages Based on Metal-Center Lability for Differential Chiral Induction, Resolution, and Recognition.

A series of isostructural supramolecular cages with a rhombic dodecahedron shape have been assembled with distinct metal-coordination lability (M8 Pd6 -MOC-16, M=Ru2+ , Fe2+ , Ni2+ , Zn2+ ). The chirality transfer between metal centers generally imposes homochirality on individual cages to enable solvent-dependent spontaneous resolution of Δ8 /Λ8 -M8 Pd6 enantiomers; however, their distinguishable stereochemical dynamics manifests differential chiral phenomena governed by the cage stability following the order Ru8 Pd6 >Ni8 Pd6 >Fe8 Pd6 >Zn8 Pd6 . The highly labile Zn centers endow the Zn8 Pd6 cage with conformational flexibility and deformation, enabling intrigue chiral-Δ8 /Λ8 -Zn8 Pd6 to meso-Δ4 Λ4 -Zn8 Pd6 transition induced by anions. The cage stabilization effect differs from inert Ru2+ , metastable Fe2+ /Ni2+ , and labile Zn2+ , resulting in different chiral-guest induction. Strikingly, solvent-mediated host-guest interactions have been revealed for Δ8 /Λ8 -(Ru/Ni/Fe)8 Pd6 cages to discriminate the chiral recognition of the guests with opposite chirality. These results demonstrate a versatile procedure to control the stereochemistry of metal-organic cages based on the dynamic metal centers, thus providing guidance to maneuver cage chirality at a supramolecular level by virtue of the solvent, anion, and guest to benefit practical applications.

Dynamic Metallosupramolecular Cages Containing 12 Adaptable Pockets for High-Order Guest Binding Beyond Biomimicry.

Molecular recognition lies at the heart of biological functions, which inspires lasting research in artificial host syntheses to mimic biomolecules that can recognize, process, and transport molecules with the highest level of complexity; nonetheless, the design principle and quantifying methodology of artificial hosts for multiple guests (≥4) remain a formidable task. Herein, we report two rhombic dodecahedral cages [(Zn/Fe)8Pd6-MOC-16], which embrace 12 adaptive pockets for multiguest binding with distinct conformational dynamics inherent in metal-center lability and are able to capture 4-24 guests to manifest a surprising complexity of binding scenarios. The exceptional high-order and hierarchical encapsulation phenomena suggest a wide host-guest dynamic-fit, enabling conformational adjustment and adaptation beyond the duality of induced-fit and conformational selection in protein interactions. A critical inspection of the host-guest binding events in solution has been performed by NMR and ESI-MS spectra, highlighting the importance of acquiring a reliable binding repertoire from different techniques and the uncertainty of quantifying the binding affinities of multiplying guests by an oversimplified method.

A Redox-Active Supramolecular Fe4L6 Cage Based on Organic Vertices with Acid-Base-Dependent Charge Tunability for Dehydrogenation Catalysis.

Supramolecular cage chemistry is of lasting interest because, as artificial blueprints of natural enzymes, the self-assembled cage structures not only provide substrate-hosting biomimetic environments but also can integrate active sites in the confined nanospaces for function synergism. Herein, we demonstrate a vertex-directed organic-clip chelation assembly strategy to construct a metal-organic cage Fe4L68+ (MOC-63) incorporating 12 imidazole proton donor-acceptor motifs and four redox-active Fe centers in an octahedral coordination nanospace. Different from regular supramolecular cages assembled with coordination metal vertices, MOC-63 comprises six ditopic organic-clip ligands as vertices and four tris-chelating Fe(N∩N)3 moieties as faces, thus improving its acid, base, and redox robustness by virtue of cage-stabilized dynamics in solution. Improved dehydrogenation catalysis of 1,2,3,4-tetrahydroquinoline derivatives is accomplished by MOC-63 owing to a supramolecular cage effect that synergizes multiple Fe centers and radical species to expedite intermediate conversion of the multistep reactions in a cage-confined nanospace. The acid-base buffering imidazole motifs play a vital role in modulating the total charge state to resist pH variation and tune the solubility among varied solvents, thereby enhancing reaction acceleration in acidic conditions and rendering a facile recycling catalytic process.

Rh(III)-Catalyzed olefination to build diverse oxazole derivatives from functional alkynes.

A novel Rh(iii)-catalyzed olefination reaction of oxazoles to generate diverse oxazole skeleton derivatives has been realized by directly using oxazole as the directing group. The reaction could tolerate many functional groups, affording complex oxazole derivatives with long chain alkenyls in moderate to good yields, which might find applications in the construction of diverse compounds.

A fluorescence-enhanced chemosensor based on multifarene[2,2] and its recognition of metal cations.

A selective and sensitive fluorescent chemosensor based on an anthracene-functionalized triazole-linked multifarene[2,2] was successfully synthesized and investigated with regard to the recognition of metal ions using fluorescence spectroscopy, 1H NMR titration, and IR spectroscopy. The proposed sensor exhibited desirable properties for potential fluorescence enhanced chemosensor applications, including selective affinity and low Zn2+ and Cd2+ detection limits compared with other metal ions. Quantum chemical calculations described the synthesized chemosensor's static structure and its coordination to Zn2+ and Cd2+. Frontier molecular orbital distribution and energy changes suggested a possible mechanism for increased receptor fluorescence intensity with Zn2+ and Cd2+ addition.

Association of Apolipoprotein A1, B with Stenosis of Intracranial and Extracranial Arteries in Patients with Cerebral Infarction.

BACKGROUND: To investigate the distribution of stenosis of intracranial and extracranial arteries of Han population patients suffering from cerebral infarction in the city of Quanzhou in Fujian and to determine the correlation of apolipoprotein A1 and apolipoprotein B with intracranial and extracranial atherosclerosis stenosis. METHODS: For this study, we enrolled patients with cerebral infarction between December 2009 and October 2012 at the Neurology Department of The Second Affiliated Hospital of Fujian Medical University. All patients were examined by computed tomography angiography (CTA). Past medical history, demographic data, and biochemical markers were collected. Multiple logistic regression analysis was used to study the association between apo A1, apo B, and cerebral atherosclerosis stenosis. RESULTS: A total of 412 patients were included in this study. 137 cases (33.3%) were classified as the intracranial atherosclerosis stenosis (ICAS) group, 74 cases (18.0%) as the combined intracranial and extracranial atherosclerosis stenosis (COAS) group, 44 cases (0.7%) as the extracranial atherosclerosis stenosis (ECAS) group, and 157 cases (38.1%) as the non-cerebral atherosclerosis stenosis (NCAS) group. Middle cerebral arteries (43.8%) were the most common lesions of intracranial arterial atherosclerosis stenosis. Extracranial carotid stenosis (30.7%) were more likely to be stenoses in the extracranial internal carotid arteries. Compared with the NCAS group, apo B was significantly higher (p < 0.001), apo A1 was significantly lower in the ICAS group and COAS group (p = 0.02 and p = 0.030). Compared with the mild atherosclerosis stenosis group, apo B was higher in the severe extracranial atherosclerosis stenosis group (p = 0.03), apo A1 was lower in the severe intracranial atherosclerosis stenosis group (p < 0.001). The multiple logistic regression analyses showed that when apo A1 > 1.28 g/L, it was an independent protective factor of intracranial stenosis (OR, 0.39), apo B was an independent risk factor of the cerebral atherosclerosis stenosis group, and when apo B > 1.16, it is significantly associated with the cerebral atherosclerosis stenosis group (ICAS: OR, 6.41) (ECAS: OR, 5.15). CONCLUSIONS: 1. The occurrence of atherosclerosis stenosis in intracranial arteries is more frequent than that in extracranial arteries in population with cerebral infarction; 2. Apo B is an independent risk factor of intracranial and extracranial arterial stenosis, apo A1 is associated with the degree of intracranial stenosis and an independent protector of intracranial stenosis.

Carbon quantum dots from hemicucur[6]bit and the application for the detection of Pb2.

A macrocyclic compound, hemicucurbit[6]uril (HemiQ[6]), is employed as the carbon source to produce a novel sort of carbon quantum dots (CQDs) with blue fluorescence in aqueous solution. The CQDs are fully identified by transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), Nuclear Magnetic Resonance (NMR), zeta potential, ultraviolet/visible (UV-vis) and photoluminescence spectroscopy (PL). The nanomaterial is developed for the analysis of Pb2+ in the light of the Resonance Rayleigh scattering (RRS) changes with the increasing Pb2+ concentration. The proposed probe emerges a high selectivity to Pb2+ and excellent sensitivity in the linear concentration range of 0-6 µM with a detection limit low to 0.42 µM, which is superior to the previous values of Pb2+ sensors, as well as the good anti-interference ability is confirmed by the specifical response to Pb2+ in the presence of other metal cations. Therefore, the proposed analysis of Pb2+ is explored for the application in real samples of tap water and lake water, in satisfied results of acceptable recoveries.

The value of CT-based radiomics in predicting hemorrhagic transformation in acute ischemic stroke patients without recanalization therapy.

Objective: The aim of this study is to investigate the clinical value of radiomics based on non-enhanced head CT in the prediction of hemorrhage transformation in acute ischemic stroke (AIS). Materials and methods: A total of 140 patients diagnosed with AIS from January 2015 to August 2022 were enrolled. Radiomic features from infarcted areas on non-enhanced CT images were extracted using ITK-SNAP. The max-relevance and min-redundancy (mRMR) and the least absolute shrinkage and selection operator (LASSO) were used to select features. The radiomics signature was then constructed by multiple logistic regressions. The clinicoradiomics nomogram was constructed by combining radiomics signature and clinical characteristics. All predictive models were constructed in the training group, and these were verified in the validation group. All models were evaluated with the receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). Results: Of the 140 patients, 59 experienced hemorrhagic transformation, while 81 remained stable. The radiomics signature was constructed by 10 radiomics features. The clinicoradiomics nomogram was constructed by combining radiomics signature and atrial fibrillation. The area under the ROC curve (AUCs) of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the training group were 0.64, 0.86, and 0.86, respectively. The AUCs of the clinical model, radiomics signature, and clinicoradiomics nomogram for predicting hemorrhagic transformation in the validation group were 0.63, 0.90, and 0.90, respectively. The DCA curves showed that the radiomics signature performed well as well as the clinicoradiomics nomogram. The DCA curve showed that the clinical application value of the radiomics signature is similar to that of the clinicoradiomics nomogram. Conclusion: The radiomics signature, constructed without incorporating clinical characteristics, can independently and effectively predict hemorrhagic transformation in AIS patients.

Radio- and Photosensitizing Os(II)-Based Nanocage for Combined Radio-/Chemo-/X-ray-Induced Photodynamic Therapies, NIR Imaging, and Drug Delivery.

Integration of clinical imaging and collaborative multimodal therapies into a single nanomaterial for multipurpose diagnosis and treatment is of great interest to theranostic nanomedicine. Here, we report a rational design of a discrete Os-based metal-organic nanocage Pd6(OsL3)828+ (MOC-43) as a versatile theranostic nanoplatform to meet the following demands simultaneously: (1) synergistic treatments of radio-, chemo-, and X-ray-induced photodynamic therapies (X-PDT) for breast cancer, (2) NIR imaging for cancer cell tracking and tumor-targeting, and (3) anticancer drug transport through a host-guest strategy. The nanoscale MOC-43 incorporates high-Z Os-element to interact with X-ray irradiation for dual radiosensitization and photosensitization, showing efficient energy transfer to endogenous oxygen in cancer cells to enhance X-PDT efficacy. It also features intrinsic NIR emission originating from metal-to-ligand charge transfer (MLCT) as an excellent imaging probe. Meanwhile, its 12 pockets can capture and concentrate low-water-soluble molecules for anticancer drug delivery. These multifunctions are implemented and demonstrated by micellization of coumarin-loaded cages with DSPE-PEG2000 into coumarin ⊂ MOC-43 nanoparticles (CMNPs) for efficient subcellular endocytosis and uptake. The cancer treatments in vitro/in vivo show promising antitumor performance, providing a conceptual protocol to combine cage-cargo drug transport with diagnosis and treatment for collaborative cancer theranostics by virtue of multifunction synergism on a single-nanomaterial platform.

RSU-Net: U-net based on residual and self-attention mechanism in the segmentation of cardiac magnetic resonance images.

BACKGROUND: Automated segmentation techniques for cardiac magnetic resonance imaging (MRI) are beneficial for evaluating cardiac functional parameters in clinical diagnosis. However, due to the characteristics of unclear image boundaries and anisotropic resolution anisotropy produced by cardiac magnetic resonance imaging technology, most of the existing methods still have the problems of intra-class uncertainty and inter-class uncertainty. However, due to the irregularity of the anatomical shape of the heart and the inhomogeneity of tissue density, the boundaries of its anatomical structures become uncertain and discontinuous. Therefore, fast and accurate segmentation of cardiac tissue remains a challenging problem in medical image processing. METHODOLOGY: We collected cardiac MRI data from 195 patients as training set and 35patients from different medical centers as external validation set. Our research proposed a U-net network architecture with residual connections and a self-attentive mechanism (Residual Self-Attention U-net, RSU-Net). The network relies on the classic U-net network, adopts the U-shaped symmetric architecture of the encoding and decoding mode, improves the convolution module in the network, introduces skip connections, and improves the network's capacity for feature extraction. Then for solving locality defects of ordinary convolutional networks. To achieve a global receptive field, a self-attention mechanism is introduced at the bottom of the model. The loss function employs a combination of Cross Entropy Loss and Dice Loss to jointly guide network training, resulting in more stable network training. RESULTS: In our study, we employ the Hausdorff distance (HD) and the Dice similarity coefficient (DSC) as metrics for assessing segmentation outcomes. Comparsion was made with the segmentation frameworks of other papers, and the comparison results prove that our RSU-Net network performs better and can make accurate segmentation of the heart. New ideas for scientific research. CONCLUSION: Our proposed RSU-Net network combines the advantages of residual connections and self-attention. This paper uses the residual links to facilitate the training of the network. In this paper, a self-attention mechanism is introduced, and a bottom self-attention block (BSA Block) is used to aggregate global information. Self-attention aggregates global information, and has achieved good segmentation results on the cardiac segmentation dataset. It facilitates the diagnosis of cardiovascular patients in the future.

Stroke risk study based on deep learning-based magnetic resonance imaging carotid plaque automatic segmentation algorithm.

Introduction: The primary factor for cardiovascular disease and upcoming cardiovascular events is atherosclerosis. Recently, carotid plaque texture, as observed on ultrasonography, is varied and difficult to classify with the human eye due to substantial inter-observer variability. High-resolution magnetic resonance (MR) plaque imaging offers naturally superior soft tissue contrasts to computed tomography (CT) and ultrasonography, and combining different contrast weightings may provide more useful information. Radiation freeness and operator independence are two additional benefits of M RI. However, other than preliminary research on MR texture analysis of basilar artery plaque, there is currently no information addressing MR radiomics on the carotid plaque. Methods: For the automatic segmentation of MRI scans to detect carotid plaque for stroke risk assessment, there is a need for a computer-aided autonomous framework to classify MRI scans automatically. We used to detect carotid plaque from MRI scans for stroke risk assessment pre-trained models, fine-tuned them, and adjusted hyperparameters according to our problem. Results: Our trained YOLO V3 model achieved 94.81% accuracy, RCNN achieved 92.53% accuracy, and MobileNet achieved 90.23% in identifying carotid plaque from MRI scans for stroke risk assessment. Our approach will prevent incorrect diagnoses brought on by poor image quality and personal experience. Conclusion: The evaluations in this work have demonstrated that this methodology produces acceptable results for classifying magnetic resonance imaging (MRI) data.

Breast MRI Tumor Automatic Segmentation and Triple-Negative Breast Cancer Discrimination Algorithm Based on Deep Learning.

Background: Breast cancer is a kind of cancer that starts in the epithelial tissue of the breast. Breast cancer has been on the rise in recent years, with a younger generation developing the disease. Magnetic resonance imaging (MRI) plays an important role in breast tumor detection and treatment planning in today's clinical practice. As manual segmentation grows more time-consuming and the observed topic becomes more diversified, automated segmentation becomes more appealing. Methodology. For MRI breast tumor segmentation, we propose a CNN-SVM network. The labels from the trained convolutional neural network are output using a support vector machine in this technique. During the testing phase, the convolutional neural network's labeled output, as well as the test grayscale picture, is passed to the SVM classifier for accurate segmentation. Results: We tested on the collected breast tumor dataset and found that our proposed combined CNN-SVM network achieved 0.93, 0.95, and 0.92 on DSC coefficient, PPV, and sensitivity index, respectively. We also compare with the segmentation frameworks of other papers, and the comparison results prove that our CNN-SVM network performs better and can accurately segment breast tumors. Conclusion: Our proposed CNN-SVM combined network achieves good segmentation results on the breast tumor dataset. The method can adapt to the differences in breast tumors and segment breast tumors accurately and efficiently. It is of great significance for identifying triple-negative breast cancer in the future.

Breast MRI Segmentation and Ki-67 High- and Low-Expression Prediction Algorithm Based on Deep Learning.

Results: The DSC, PPV, and sensitivity of our combined model are 0.94, 0.93, and 0.94, respectively, with better segmentation performance. And we compare with the segmentation frameworks of other papers and find that our combined model can make accurate segmentation of breast tumors. Conclusion: Our method can adapt to the variability of breast tumors and segment breast tumors accurately and efficiently. In the future, it can be widely used in clinical practice, so as to help the clinic better formulate a reasonable diagnosis and treatment plan for breast cancer patients.

Cardiac MRI segmentation of the atria based on UU-NET.

Background and objective: In today's society, people's work pressure, coupled with irregular diet, lack of exercise and other bad lifestyle, resulting in frequent cardiovascular diseases. Medical imaging has made great progress in modern society, among which the role of MRI in cardiovascular field is self-evident. Based on this research background, how to process cardiac MRI quickly and accurately by computer has been extensively discussed. By comparing and analyzing several traditional image segmentation and deep learning image segmentation, this paper proposes the left and right atria segmentation algorithm of cardiac MRI based on UU-NET network. Methods: In this paper, an atrial segmentation algorithm for cardiac MRI images in UU-NET network is proposed. Firstly, U-shaped upper and lower sampling modules are constructed by using residual theory, which are used as encoders and decoders of the model. Then, the modules are interconnected to form multiple paths from input to output to increase the information transmission capacity of the model. Results: The segmentation method based on UU-NET network has achieved good results proposed in this paper, compared with the current mainstream image segmentation algorithm results have been improved to a certain extent. Through the analysis of the experimental results, the image segmentation algorithm based on UU-NET network on the data set, its performance in the verification set and online set is higher than other grid models. The DSC in the verification set is 96.7%, and the DSC in the online set is 96.7%, which is nearly one percentage point higher than the deconvolution neural network model. The hausdorff distance (HD) is 1.2 mm. Compared with other deep learning models, it is significantly improved (about 3 mm error is reduced), and the time is 0.4 min. Conclusion: The segmentation algorithm based on UU-NET improves the segmentation accuracy obviously compared with other segmentation models. Our technique will be able to help diagnose and treat cardiac complications.

The high selective chemo-sensors for TNP based on the mono- and di-substituted multifarene[2,2] with different fluorescence quenching mechanism.

The chem-sensors, based on the triazole-CH2-anthracene-functionalized multifarene[2,2] were successfully synthesized, which could efficiently and rapidly detect 2,4,6-trinitrophenol (TNP). The high specificities of the proposed macrocyclic sensors were achieved by selective response for TNP in the existence of other competing phenolic compounds, and the limits of detection in ∼10-8 mol/L range were produced to confirm the high sensitivities of the chem-sensors, which could be attributed to the mechanism of electron and resonance energy transfer processes in the complexes with the supramolecular interactions. 1H NMR titration analysis revealed the actual binding position should be the triazole rings of sensors with the hydroxyl group on TNP to offer a hydrogen bonding. The extraordinary sensing properties endued the compounds as sensitive fluorometric chem-sensors for the potential application of TNP detection.

Tumor-selective replication of an oncolytic adenovirus carrying oct-3/4 response elements in murine metastatic bladder cancer models.

PURPOSE: Oncolytic adenoviruses are attractive therapeutics for cancer because they selectively replicate in tumors. However, targeting tumor metastasis remains a major challenge for current virotherapy for cancer. Oct-3/4 is specifically expressed in embryonic stem cells and tumor cells. Oct-3/4 highly expressed in cancer cells may be a potential target for cancer therapy. We developed an E1B-55 kDa-deleted adenovirus, designated Ad.9OC, driven by nine copies of Oct-3/4 response element for treating Oct-3/4-expressing metastatic bladder cancer. EXPERIMENTAL DESIGN: We examined the expression of Oct-3/4 in human bladder tumor tissues and bladder cancer cell lines. We also evaluated the cytolytic and antitumor effects of Ad.9OC on bladder cancer cells in vitro and in vivo. RESULTS: Oct-3/4 expression was detected in bladder cancer cell lines, as well as in human bladder tumor tissues. Notably, Oct-3/4 expression was higher in metastatic compared with nonmetastatic bladder cancer cells. Ad.9OC induced higher cytolytic activity in metastatic bladder cancer cells than in their nonmetastatic counterparts, whereas it did not cause cytotoxicity in normal cells. Pharmacologic and short hairpin RNA-mediated Oct-3/4 inhibition rendered bladder cancer cells more resistant to Ad.9OC-induced cytolysis. Replication of Ad.9OC was detected in murine bladder cancer cells and bladder tumor tissues. We also showed the effectiveness of Ad.9OC for treating bladder cancer in subcutaneous, as well as metastatic, bladder tumor models. CONCLUSIONS: Ad.9OC may have therapeutic potential for treating Oct-3/4-expressing tumors. Especially, metastatic bladder tumors are good target for Ad.9OC treatment. Because Oct-3/4 is expressed in a broad spectrum of cancers, Ad.9OC may be broadly applicable.

Recognition of silver cations by multifarene[2,2] chemosensors with unexpected fluorescence response.

Fluorescent chemosensors based on a new macrocyclic compound, multifarene[2,2], with modification by triazole-linked pyrene or anthracene were synthesized. These macrocyclic sensors exhibited high affinity and selectivity toward Ag+ over other metal ions, with ratiometric or enhanced response of their fluorescence emissions depending upon the substituent species for coordination to Ag+, and an unexpected response to a concentration threshold of the metal cations was discovered. The experimental evidences of fluorescence spectra, 1H NMR titration, IR spectra, and high-resolution mass spectra suggested the coordination behaviors of the sensors with Ag+, that is, the 1:1 complexes were formed with moderate association constants of about 105 L·mol-1, and the sulfur atoms on macrocyclic ligand should affinite to the metal cations. Energy-minimized structures and frontier orbitals were estimated by quantum chemical calculations with a view to rationalizing the fluorescence response of the multifarene[2,2] sensors upon binding to Ag+.

Spinal Cord Syphilitic Gumma Presenting with Brown-Séquard Syndrome: A Case Report and Literature Review.

BACKGROUND: Spinal neurosyphilis manifesting as a solitary syphilitic gumma is exceedingly rare. There are non-specific imaging findings and challenges in the diagnosis of spinal syphilitic gumma, which could be easily misdiagnosed as tumor lesions and require surgical resection or biopsy. CLINICAL PRESENTATION: We report the case of a 45-year-old female patient who was diagnosed with Spinal syphilitic gumma. Our case is the first reported case of spinal cord syphilitic gumma with intradural-extramedullary and intramedullary involvement. CONCLUSION: Spinal syphilitic gumma exhibits diverse clinical manifestations, lacks specific imaging features, accompanied by the patient's history deliberately concealed. Since clinicians do not have sufficient knowledge about such rare cases, misdiagnosis and missed diagnosis will be likely. When there is clinical suspicion for spinal syphilitic gumma, clinicians should pay close attention to relevant medical history, carry out a comprehensive physical examination and specific serological tests and cerebrospinal fluid (CSF) analysis. In summary, in cases with stable neurologic conditions, a trial administration of intravenous penicillin with follow-up imaging may be the optimal treatment option, and in cases with rapid progression or acute exacerbation, a surgical resection together with systemic antibiotic treatment for syphilis after surgery may be the best treatment strategy.

Magnolol attenuates the inflammation and apoptosis through the activation of SIRT1 in experimental stroke rats.

BACKGROUND: Silent information regulator 1 (SIRT1), a histone deacetylase, plays a protective role in ischemic brain injury. Previous studies have shown that magnolol has a beneficial effect on ischemic stroke; however, the role of SIRT1 in the protective effect of magnolol against cerebral ischemia has not been investigated. METHODS: We used a middle cerebral artery occlusion model of stroke in rats. Before stroke induction, the rats received intraperitoneal injections of magnolol with or without the SIRT1 inhibitor, EX527. Brain water content, neurological score, and infarct volume were measured. Moreover, the levels of the proinflammatory cytokines tumor necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) were measured. Western blot analysis was performed to detect Ac-FOXO1, SIRT1, bax, and Bcl-2 expression. RESULTS: Magnolol exerted a beneficial effect on cerebral ischemia, as indicated by reduced brain edema, decreased infarct volume, and improved neurological score. Magnolol had an anti-inflammatory effect mediated by a decrease in the expression of IL-1ß and TNF-α in the brain tissue. Additionally, magnolol down-regulated bax and Ac-FOXO1 expression and up-regulated Bcl-2 and SIRT1 expression. This effect of magnolol was abolished by EX527 treatment. CONCLUSION: In conclusion, our data clearly indicate that magnolol modulates brain injury caused by ischemic stroke by inhibiting inflammatory cytokines and apoptosis through SIRT1 activation.