Combination of Paper and Electronic Trail Making Tests for Automatic Analysis of Cognitive Impairment: Development and Validation Study.

BACKGROUND: Computer-aided detection, used in the screening and diagnosing of cognitive impairment, provides an objective, valid, and convenient assessment. Particularly, digital sensor technology is a promising detection method. OBJECTIVE: This study aimed to develop and validate a novel Trail Making Test (TMT) using a combination of paper and electronic devices. METHODS: This study included community-dwelling older adult individuals (n=297), who were classified into (1) cognitively healthy controls (HC; n=100 participants), (2) participants diagnosed with mild cognitive impairment (MCI; n=98 participants), and (3) participants with Alzheimer disease (AD; n=99 participants). An electromagnetic tablet was used to record each participant's hand-drawn stroke. A sheet of A4 paper was placed on top of the tablet to maintain the traditional interaction style for participants who were not familiar or comfortable with electronic devices (such as touchscreens). In this way, all participants were instructed to perform the TMT-square and circle. Furthermore, we developed an efficient and interpretable cognitive impairment-screening model to automatically analyze cognitive impairment levels that were dependent on demographic characteristics and time-, pressure-, jerk-, and template-related features. Among these features, novel template-based features were based on a vector quantization algorithm. First, the model identified a candidate trajectory as the standard answer (template) from the HC group. The distance between the recorded trajectories and reference was computed as an important evaluation index. To verify the effectiveness of our method, we compared the performance of a well-trained machine learning model using the extracted evaluation index with conventional demographic characteristics and time-related features. The well-trained model was validated using follow-up data (HC group: n=38; MCI group: n=32; and AD group: n=22). RESULTS: We compared 5 candidate machine learning methods and selected random forest as the ideal model with the best performance (accuracy: 0.726 for HC vs MCI, 0.929 for HC vs AD, and 0.815 for AD vs MCI). Meanwhile, the well-trained classifier achieved better performance than the conventional assessment method, with high stability and accuracy of the follow-up data. CONCLUSIONS: The study demonstrated that a model combining both paper and electronic TMTs increases the accuracy of evaluating participants' cognitive impairment compared to conventional paper-based feature assessment.

Visible light waveband Dammann grating based on all-dielectric metasurface.

Dammann gratings (DGs) can generate a spot array in a particular arrangement. In recent years, DGs have been used in many fields such as laser beam splitting and optical coupling. Nanograting encoding technology can achieve a high signal-to-noise ratio and high-efficiency diffraction distribution; it also provides new design ideas for realizing the miniaturization and deviceization of DGs. In this work, we have comprehensively studied the DG based on an all-dielectric metasurface, which can produce a 5×5 diffraction spot array with a diffraction angle of 20∘×20∘. In an operation waveband from 650 to 690 nm, the DG has superior performance with high efficiency ≥60%; meanwhile, it achieves a relative low contrast ratio ≤0.33. Owing to high efficiency, wide waveband performance, and polarization insensitive property, the all-dielectric metasurface DG can provide possibilities for various application, including laser technology and optical information processing.

High-level expression of LMW-GS and α-gliadin genes promoted by the expressed tag sequence of 5' end in Escherichia coli.

Wheat storage protein genes, especially low molecular weight glutenin subunit (LMW-GS) and gliadin genes are difficult to be expressed in Escherichiacoli, mainly due to the presence of highly repetitive sequences. In order to establish a high efficiency expression system for these genes, five different expression plasmids combining with 9 genes, viz. 6 LMW-GS and 3 α-gliadin genes isolated from common wheat and related species, were studied for heterologous expression in E. coli. In this study, when an expressed tag sequence encoding signal peptide, His-S or GST-tag was fused to the 5' end of LMW-GS or gliadin gene as the leading sequence, all recombination genes could be stably expressed at a high level. On the contrast, as expected, the inserted genes encoding mature protein failed without an expressed tag sequence. This result indicated that using expressed tag sequences as leading sequences could promote LMW-GS and gliadin genes to be well expressed in E. coli. Further transcriptional analysis by quantitative real-time PCR (qRT-PCR) showed transcription levels of recombination genes (e.g. GST-Glutenin, His-S-Glutenin and SP(∗)-His-Glutenin) were 4-fold to 33-fold higher than those of the LMW-GS genes, which suggested these expressed tag sequences might play an important role in stimulating transcription. The possible molecular mechanism under this phenomenon was discussed.

Protein-assisted synthesis of chitosan-coated minicells enhance dendritic cell recruitment for therapeutic immunomodulation within pulmonary tumors.

The efficacy of cancer therapies is significantly compromised by the immunosuppressive tumor milieu. Herein, we introduce a previously unidentified therapeutic strategy that harnesses the synergistic potential of chitosan-coated bacterial vesicles and a targeted chemotherapeutic agent to activate dendritic cells, thereby reshaping the immunosuppressive milieu for enhanced cancer therapy. Our study focuses on the protein-mediated modification of bacterium-derived minicells with chitosan molecules, facilitating the precise delivery of Doxorubicin to tumor sites guided by folate-mediated homing cues. These engineered minicells demonstrate remarkable specificity in targeting lung carcinomas, triggering immunogenic cell death and releasing tumor antigens and damage-associated molecular patterns, including calreticulin and high mobility group box 1. Additionally, the chitosan coating, coupled with bacterial DNA from the minicells, initiates the generation of reactive oxygen species and mitochondrial DNA release. These orchestrated events culminate in dendritic cell maturation via activation of the stimulator of interferon genes signaling pathway, resulting in the recruitment of CD4+ and CD8+ cytotoxic T cells and the secretion of interferon-ß, interferon-γ, and interleukin-12. Consequently, this integrated approach disrupts the immunosuppressive tumor microenvironment, impeding tumor progression. By leveraging bacterial vesicles as potent dendritic cell activators, our strategy presents a promising paradigm for synergistic cancer treatment, seamlessly integrating chemotherapy and immunotherapy.

ROS-mediated anticancer effects of EGFR-targeted nanoceria.

The therapeutic effectiveness of anticancer drugs, including nanomedicines, can be enhanced with active receptor-targeting strategies. Epidermal growth factor receptor (EGFR) is an important cancer biomarker, constitutively expressed in sarcoma patients of different histological types. The present work reports materials and in vitro biomedical analyses of silanized (passive delivery) and/or EGF-functionalized (active delivery) ceria nanorods exhibiting highly defective catalytically active surfaces. The EGFR-targeting efficiency of nanoceria was confirmed by receptor-binding studies. Increased cytotoxicity and reactive oxygen species (ROS) production were observed for EGF-functionalized nanoceria owing to enhanced cellular uptake by HT-1080 fibrosarcoma cells. The uptake was confirmed by TEM and confocal microscopy. Silanized nanoceria demonstrated negligible/minimal cytotoxicity toward healthy MRC-5 cells at 24 and 48 h, whereas this was significant at 72 h owing to a nanoceria accumulation effect. In contrast, considerable cytotoxicity toward the cancer cells was exhibited at all three times points. The ROS generation and associated cytotoxicity were moderated by the equilibrium between catalysis by ceria, generation of cell debris, and blockage of active sites. EGFR-targeting is shown to enhance the uptake levels of nanoceria by cancer cells, subsequently enhancing the overall anticancer activity and therapeutic performance of ceria.

Unlocking the enigma: unraveling multiple cognitive dysfunction linked to glymphatic impairment in early Alzheimer's disease.

Background: Alzheimer's disease (AD) is one of the world's well-known neurodegenerative diseases, which is related to the balance mechanism of production and clearance of two proteins (amyloid-ß and tau) regulated by the glymphatic system. Latest studies have found that AD patients exhibit impairments to their glymphatic system. However, the alterations in the AD disease continuum, especially in the early stages, remain unclear. Moreover, the relationship between the glymphatic system and cognitive dysfunction is still worth exploring. Methods: A novel diffusion tensor image analysis method was applied to evaluate the activity of the glymphatic system by an index for diffusivity along the perivascular space (ALPS-index). Based on this method, the activity of the glymphatic system was noninvasively evaluated in 300 subjects, including 111 normal controls (NC), 120 subjects with mild cognitive impairment (MCI), and 69 subjects with AD. Partial correlation analysis was applied to explore the association between glymphatic system and cognitive impairment based on three domain-general scales and several domain-specific cognitive scales. Receiver operating characteristic curve analysis was used to evaluate the classification performance of ALPS-index along the AD continuum. Results: ALPS-index was significantly different among NC, MCI and AD groups, and ALPS-index decreased with cognitive decline. In addition, ALPS-index was significantly correlated with the scores of the clinical scales (p<0.05, FDR corrected), especially in left hemisphere. Furthermore, combination of ALPS and fractional anisotropy (FA) values achieved better classification results (NC vs. MCI: AUC = 0.6610, NC vs. AD: AUC = 0.8214). Conclusion: Here, we show that the glymphatic system is closely associated with multiple cognitive dysfunctions, and ALPS-index can be used as a biomarker for alterations along the AD continuum. This may provide new targets and strategies for the treatment of AD, and has the potential to assist clinical diagnosis.

Composition-driven morphological evolution of BaTiO3 nanowires for efficient piezocatalytic hydrogen production.

Hydrogen production from water by piezocatalysis is very attractive owing to its high energy efficiency and novelty. BaTiO3, a highly piezoelectric material, is particularly suitable for this application due to its high piezoelectric potential, non-toxic nature, and physicochemical stability. Owing to the critical role of morphology on properties, one-dimensional (1D) materials are expected to exhibit superior water-splitting performance and thus there is a need to optimise the processing conditions to develop outstanding piezocatalysts. In the present work, piezoelectric BaTiO3 nanowires (NWs) were hydrothermally synthesised with precursor Ba:Ti molar ratios of 1:1, 2:1, and 4:1. The morphology, defect chemistry, and hydrogen evolution reaction (HER) efficiency of the as-synthesised BaTiO3 NWs were systematically investigated. The results showed that the morphological features, aspect ratio, structural stability and defect contents of the 1D morphologies collectively have a significant impact on the HER efficiency. The morphological evolution mechanism of the 1D structures were described in terms of ion exchange and dissolution-growth processes of template-grown BaTiO3 NWs for different Ba:Ti molar ratios. Notably, the BaTiO3 NWs synthesised with Ba:Ti molar ratio of 2:1 displayed high crystallinity, good defect concentrations, and good structural integrity under ultrasonication, resulting in an outstanding HER efficiency of 149.24 µmol h-1g-1 which is the highest obtained for nanowire morphologies. These results highlight the importance of synthesis conditions for BaTiO3 NWs for generating excellent piezocatalytic water splitting performance. Additionally, post-ultrasonication tested BaTiO3 NWs demonstrated unexpected photocatalytic activity, with the BTO-1 sample (1:1 Ba:Ti) exhibiting 56% photodegradation of RhB in 2 h of UV irradiation.

Ceftazidime-assisted synthesis of ultrasmall chitosan nanoparticles for biofilm penetration and eradication of Pseudomonas aeruginosa.

Pseudomonas aeruginosa (P. aeruginosa) infections present a grave threat to immunocompromised individuals, particularly those with cystic fibrosis due to the development of bacterial biofilms. In this study, we engineered self-assembling chitosan-ceftazidime nanoparticles (CSCE) capable of effectively penetrating biofilms and eradicating P. aeruginosa. The CSCE nanoparticles were synthesized through ionic cross-linking, combining negatively charged ceftazidime with positively charged chitosan, resulting in uniform nanoparticles measuring approximately 40 nm in diameter, exhibiting high dispersity and excellent biocompatibility. Remarkably, these nanoparticles exhibited significant inhibition of P. aeruginosa growth, reduced pyocyanin production, and diminished biofilm formation, achieving a maximum inhibition rate of 22.44%. Furthermore, in vivo investigations demonstrated enhanced survival in mice with abdominal P. aeruginosa infection following treatment with CSCE nanoparticles, accompanied by reduced levels of inflammatory cytokines Interleukin-6 (125.79 ± 18.63 pg/mL), Interleukin-17 (125.67 ± 5.94 pg/mL), and Tumor Necrosis Factor-α (135.4 ± 11.77 pg/mL). Critically, mice treated with CSCE nanoparticles showed no presence of bacteria in the bloodstream following intraperitoneal P. aeruginosa infection. Collectively, our findings highlight the potential of these synthesized nanoparticles as effective agents against P. aeruginosa infections.

Principles of Design and Synthesis of Metal Derivatives from MOFs.

Materials derived from metal-organic frameworks (MOFs) have demonstrated exceptional structural variety and complexity and can be synthesized using low-cost scalable methods. Although the inherent instability and low electrical conductivity of MOFs are largely responsible for their low uptake for catalysis and energy storage, a superior alternative is MOF-derived metal-based derivatives (MDs) as these can retain the complex nanostructures of MOFs while exhibiting stability and electrical conductivities of several orders of magnitude higher. The present work comprehensively reviews MDs in terms of synthesis and their nanostructural design, including oxides, sulfides, phosphides, nitrides, carbides, transition metals, and other minor species. The focal point of the approach is the identification and rationalization of the design parameters that lead to the generation of optimal compositions, structures, nanostructures, and resultant performance parameters. The aim of this approach is to provide an inclusive platform for the strategies to design and process these materials for specific applications. This work is complemented by detailed figures that both summarize the design and processing approaches that have been reported and indicate potential trajectories for development. The work is also supported by comprehensive and up-to-date tabular coverage of the reported studies.

Research on nonstroke dementia screening and cognitive function prediction model for older people based on brain atrophy characteristics.

BACKGROUND: Brain atrophy is an important feature in dementia and is meaningful to explore a brain atrophy model to predict dementia. Using machine learning algorithm to establish a dementia model and cognitive function model based on brain atrophy characteristics is unstoppable. METHOD: We acquired 157 dementia and 156 normal old people.s clinical information and MRI data, which contains 44 brain atrophy features, including visual scale assessment of brain atrophy and multiple linear measurement indexes and brain atrophy index. Five machine learning models were used to establish prediction models for dementia, general cognition, and subcognitive domains. RESULTS: The extreme Gradient Boosting (XGBoost) model had the best effect in predicting dementia, with a sensitivity of 0.645, a specificity of 0.839, and the area under curve (AUC) of 0.784. In this model, the important brain atrophy features for predicting dementia were temporal horn ratio, cella media index, suprasellar cistern ratio, and the thickness of the corpus callosum genu. CONCLUSION: For nonstroke elderly people, the machine learning model based on clinical head MRI brain atrophy features had good predictive value for dementia, general cognitive impairment, immediate memory impairment, word fluency disorder, executive dysfunction, and visualspatial disorder.

Functional Brain Networks in Mild Cognitive Impairment Based on Resting Electroencephalography Signals.

The oscillatory patterns of electroencephalography (EEG), during resting states, are informative and helpful in understanding the functional states of brain network and their contribution to behavioral performances. The aim of this study is to characterize the functional brain network alterations in patients with amnestic mild cognitive impairment (aMCI). To this end, rsEEG signals were recorded before and after a cognitive task. Functional connectivity metrics were calculated using debiased weighted phase lag index (DWPLI). Topological features of the functional connectivity network were analyzed using both the classical graph approach and minimum spanning tree (MST) algorithm. Subsequently, the network and connectivity values together with Mini-Mental State Examination cognitive test were used as features to classify the participants. Results showed that: (1) across the pre-task condition, in the theta band, the aMCI group had a significantly lower global mean DWPLI than the control group; the functional connectivity patterns were different in the left hemisphere between two groups; the aMCI group showed significantly higher average clustering coefficient and the remarkably lower global efficiency than the control. (2) Analysis of graph measures under post-task resting state, unveiled that for the percentage change of post-task vs. pre-task in beta EEG, a significant increase in tree hierarchy was observed in aMCI group (2.41%) than in normal control (-3.89%); (3) Furthermore, the classification analysis of combined measures of functional connectivity, brain topology, and MMSE test showed improved accuracy compared to the single method, for which the connectivity patterns and graph metrics were used as separate inputs. The classification accuracy obtained for the case of post-task resting state was 87.2%, while the one achieved under pre-task resting state was found to be 77.7%. Therefore, the functional network alterations in aMCI patients were more prominent during the post-task resting state. This study suggests that the disintegration observed in MCI functional network during the resting states, preceding and following a task, might be possible biomarkers of cognitive dysfunction in aMCI patients.

CD4+CD25+ Regulatory T Cells in Intracranial Thrombi Are Inversely Correlated with Hemorrhagic Transformation after Thrombectomy: A Clinical-Immunohistochemical Analysis of Acute Ischemic Stroke.

Mechanical thrombectomy is not only effective for managing patients with acute ischemic stroke (AIS), but it also enables a valuable histological analysis of thrombi. Previous studies indicated that regulatory T cells (Treg) adoptive transfer might alleviate the hemorrhagic transformation. However, whether Treg in intracranial thrombi correlates with hemorrhagic transformation after mechanical thrombectomy remains unclear. This study mainly analyzed the colocation of Treg markers in serial thrombus sections stained serially for CD4 and CD25 in groups of hemorrhagic or nonhemorrhagic transformation. Second, to investigate whether these immunohistochemical parameters could provide any additional information beyond hemorrhagic transformation, we compared the overlap between Treg markers among other groups, such as functional outcomes, stroke subtypes, and gender. Our results showed that the number of CD4+CD25+ Treg cells was lower in the hemorrhagic transformation thrombi than in the nonhemorrhagic group (p < 0.001) but there were no significant differences otherwise. The present finding of CD4+CD25+ Treg cell reductions in thrombi associated with hemorrhagic transformation provides the histological evidence supporting that thromboinflammation might involve in the pathological process of an acute stroke after mechanical thrombectomy.

Extended Application of Digital Clock Drawing Test in the Evaluation of Alzheimer's Disease Based on Artificial Intelligence and the Neural Basis.

INTRODUCTION: This study aimed to build the supervised learning model to predict the state of cognitive impairment, Alzheimer's Disease (AD) and cognitive domains including memory, language, action, and visuospatial based on Digital Clock Drawing Test (dCDT) precisely. METHODS: 207 normal controls, 242 Mild Cognitive Impairment (MCI) patients, 87 dementia patients, including 53 AD patients, were selected from Shanghai Tongji Hospital. The electromagnetic tablets were used to collect the trajectory points of dCDT. By combining dynamic process and static results, different types of features were extracted, and the prediction models were built based on the feature selection approaches and machine learning methods. RESULTS AND DISCUSSION: The optimal AUC of cognitive impairment's screening, AD's screening and differentiation are 0.782, 0.919 and 0.818, respectively. In addition, the cognitive state of the domains with the best prediction result based on the features of dCDT is action with the optimal AUC 0.794, while the other three cognitive domains got the prediction results between 0.744-0.755. CONCLUSION: By extracting dCDT features, cognitive impairment and AD patients can be identified early. Through dCDT feature extraction, a prediction model of single cognitive domain damage can be established.

Role of Oxygen Vacancy Ordering and Channel Formation in Tuning Intercalation Pseudocapacitance in Mo Single-Ion-Implanted CeO2-x Nanoflakes.

Metal oxide pseudocapacitors are limited by low electrical and ionic conductivities. The present work integrates defect engineering and architectural design to exhibit, for the first time, intercalation pseudocapacitance in CeO2-x. An engineered chronoamperometric electrochemical deposition is used to synthesize 2D CeO2-x nanoflakes as thin as ∼12 nm. Through simultaneous regulation of intrinsic and extrinsic defect concentrations, charge transfer and charge-discharge kinetics with redox and intercalation capacitances together are optimized, where reduction increases the gravimetric capacitance by 77% to 583 F g-1, exceeding the theoretical capacitance (562 F g-1). Mo ion implantation and reduction processes increase the specific capacitance by 133%, while the capacitance retention increases from 89 to 95%. The role of ion-implanted Mo6+ is critical through its interstitial solid solubility, which is not to alter the energy band diagram but to facilitate the generation of electrons and to establish the midgap states for color centers, which facilitate electron transfer across the band gap, thus enhancing n-type semiconductivity. Critically, density functional theory simulations reveal, for the first time, that the reduction causes the formation of ordered oxygen vacancies that provide an atomic channel for ion intercalation. These channels enable intercalation pseudocapacitance but also increase electrical and ionic conductivities. In addition, the associated increased active site density enhances the redox such that the 10% of the Ce3+ available for redox (surface only) increases to 35% by oxygen vacancy channels. These findings are critical for any oxide system used for energy storage systems, as they offer both architectural design and structural engineering of materials to maximize the capacitance performance by achieving accumulative surface redox and intercalation-based redox reactions during the charge/discharge process.

Highly catalytically active CeO2-x-based heterojunction nanostructures with mixed micro/meso-porous architectures.

The architectural design of nanocatalysts plays a critical role in the achievement of high densities of active sites but current technologies are hindered by process complexity and limited scaleability. The present work introduces a rapid, flexible, and template-free method to synthesize three-dimensional (3D), mesoporous, CeO2-x nanostructures comprised of extremely thin holey two-dimensional (2D) nanosheets of centimetre-scale. The process leverages the controlled conversion of stacked nanosheets of a newly developed Ce-based coordination polymer into a range of stable oxide morphologies controllably differentiated by the oxidation kinetics. The resultant polycrystalline, hybrid, 2D-3D CeO2-x exhibits high densities of defects and surface area as high as 251 m2 g-1, which yield an outstanding CO conversion performance (T90% = 148 °C) for all oxides. Modification by the creation of heterojunction nanostructures using transition metal oxides (TMOs) results in further improvements in performance (T90% = 88 °C), which are interpreted in terms of the active sites associated with the TMOs that are identified through structural analyses and density functional theory (DFT) simulations. This unparalleled catalytic performance for CO conversion is possible through the ultra-high surface areas, defect densities, and pore volumes. This technology offers the capacity to establish efficient pathways to engineer nanostructures of advanced functionalities for catalysis.

A Highly Stretchable, Real-Time Self-Healable Hydrogel Adhesive Matrix for Tissue Patches and Flexible Electronics.

The development of biocompatible self-healable hydrogel adhesives for skin or wet, stretchable surfaces in air or under water is highly desirable for various biomedical applications ranging from skin patches to bioelectronics. However, it has been proven to be very challenging because most existing hydrogel adhesives are cytotoxic, or poorly adhere to dynamic or stretchable surfaces in wet environments. In this study, multifunctional hydrogel adhesives derived from silk fibroin (SF) and tannic acid (TA) are effectively constructed with high extensibility (i.e., up to 32 000%), real-time self-healing capability, underwater adhesivity, water-sealing ability, biocompatibility, and antibiotic properties. According to all-atom molecular dynamics simulation studies, the properties of the hydrogel adhesives, especially high extensibility, are mainly attributed to the hydrogen bonds between TA and the SF chains in water, and water and TA molecules can result in loose assemblies with fewer ß-sheets, and more random coils in the SF. Conductivity can also be easily introduced to the adhesive matrix and adjusted when the strain of the adhesives occurs. Considering that it has multiple functions and can be efficiently prepared, the proposed hydrogel adhesives have the potential for future medical applications, such as tissue adhesives and integrated bioelectronics.

A facile strategy to construct silk fibroin based GTR membranes with appropriate mechanical performance and enhanced osteogenic capacity.

Periodontitis is one of the most common inflammatory diseases that can eventually cause tooth loss in adults. For the successful regeneration of periodontal tissue, one of the most feasible ways is the development of functional guided tissue regeneration (GTR) membranes with improved osteogenic capability. Here, we fabricated electrospun silk fibroin (SF) nanofibrous membranes and designed a low-cost and eco-friendly strategy to modify the SF matrix via tannic acid (TA). In this process, the conformational transition of SF protein triggered by TA made a remarkable improvement in mechanical properties of the SF membranes. More importantly, TA could induce biomimetic mineralization and in situ growth of hydroxyapatite (HAp) on the surface of the SF nanofibrous matrix. Cell experiments demonstrated that TA-coated SF nanofibrous membranes after mineralization could facilitate the proliferation and osteo-differentiation of MC3T3 cells. Considering the effectivity and methodological simplicity, this TA-mediated modification is a promising method to prepare SF-based GTR membranes with better mechanical performance and osteogenic function.

Intracranial Atherosclerotic Stenosis is Related to Post-stroke Cognitive Impairment: A Cross-sectional Study of Minor Stroke.

BACKGROUND: Intracranial Atherosclerotic Stenosis (ICAS) is an important risk factor for cognitive impairment. However, it is unclear whether patients with ICAS are more likely to develop cognitive impairment after an acute, non-disabling ischemic stroke (minor stroke). OBJECTIVE: We aimed to investigate the association between ICAS and post-stroke cognitive impairment. METHODS: In this cross-sectional study, patients with acute, non-disabling ischemic stroke underwent two cognitive tests and imaging evaluation for ICAS, within two weeks after the stroke. To determine the association between ICAS and post-stroke cognitive impairment, we performed a multivariate logistic regression analysis adjusted for several demographic and vascular risk factors. RESULTS: Of the 164 patients with minor stroke in this study, 98 (59.76%) were diagnosed with poststroke cognitive impairment (Montreal Cognitive Assessment score<26). After adjusting for potential confounders, we found that patients with ICAS were more likely to develop cognitive impairment after an acute, non-disabling ischemic stroke, compared to patients without ICAS (Odds Ratio: 2.13; 95% Confidence Interval: 1.07-4.26), and underperformed in the tests of visuospatial and executive function. CONCLUSION: In this cross-sectional study of a population that has experienced a minor stroke, our findings demonstrated a positive association between ICAS and post-stroke cognitive impairment.

A natural polymer based bioadhesive with self-healing behavior and improved antibacterial properties.

Bioadhesives are of great interest for tissue/wound closure to reduce surgical time, minimize treatment invasiveness, and prevent body fluid leakage. However, bacterial infections remain a major concern during wound healing and tissue bonding. Hence, the development of bioadhesives with antibacterial properties is necessary. In this study, a hydrogel bioadhesive based on silk fibroin (SF) and tannic acid (TA) was combined with silver nanoparticles (AgNPs) generated in situ during hydrogel formation to improve its antibacterial abilities. In this system, TA can be regarded as a phenolic glue molecule to spontaneously co-assemble with SF to fabricate the adhesive matrix network and also as a reductant to induce silver nitrate to form AgNPs evenly within the adhesive network. Furthermore, the influence of the amount of silver nitrate was considered. The produced hybrid hydrogel bioadhesives with different amounts of AgNPs exhibited self-healing capabilities, considerable wet tissue adhesion strengths (14.32 ± 1.85 kPa-28.80 ± 2.29 kPa) and good cytocompatibility. When the initial concentration of silver nitrate was more than 0.05 wt%, the produced STA bioadhesive showed effective antibacterial properties in vitro. These results demonstrate that these STA bioadhesives have the potential to be used in tissue/wound closure, especially when bacterial infections are a main problem.

Bridging Therapy Versus Direct Mechanical Thrombectomy in Patients with Acute Ischemic Stroke due to Middle Cerebral Artery Occlusion: A Clinical- Histological Analysis of Retrieved Thrombi.

Mechanical thrombectomy (MT) is effective in managing patients with acute ischemic stroke (AIS) caused by large-vessel occlusions and allows for valuable histological analysis of thrombi. However, whether bridging therapy (pretreatment with intravenous thrombolysis before MT) provides additional benefits in patients with middle cerebral artery (MCA) occlusion remains unclear. Therefore, this study aimed to compare the effects of direct MT and bridging therapy, and to elucidate the correlation between thrombus composition and stroke subtypes. Seventy-three patients with acute ischemic stroke who received MT, were eligible for intravenous thrombolysis, and had MCA occlusion were included. We matched 21 direct MT patients with 21 bridging therapy patients using propensity score matching and compared their 3rd-month clinical outcomes. All MCA thrombi (n = 45) were histologically analyzed, and the red blood cell (RBC) and fibrin percentages were quantified. We compared the clot composition according to stroke etiology (large-artery atherosclerosis and cardioembolism) and intravenous thrombolysis application. The baseline characteristics showed no difference between groups except for a higher atrial fibrillation rate and NIHSS score on admission in the direct MT group. We performed a supportive analysis using propensity score matching but could not find any differences in the functional outcome, mortality, and intracerebral hemorrhage. In the histological clot analysis, the cardioembolic clots without intravenous thrombolysis pretreatment had higher RBC (P = 0.042) and lower fibrin (P = 0.042) percentages than the large-artery atherosclerosis thrombi. Similar findings were observed in the thrombi treated with recombinant tissue plasminogen activator (P = 0.012). In conclusion, there was no difference in the functional outcomes between the direct MT and bridging therapy groups. However, randomized trials are needed to elucidate the high ratio of cardioembolism subtype in our group of patients. The histological MCA thrombus composition differed between cardioembolism and large-artery atherosclerosis, and this finding provides valuable information on the underlying pathogenesis and thrombus origin.