TREATMENT OF COMATOSE SURVIVORS OF IN-HOSPITAL CARDIAC ARREST WITH EXTENDED ENDOVASCULAR COOLING METHOD FOR 72 H: A PROPENSITY SCORE-MATCHED ANALYSIS.

ABSTRACT: Aims: Targeted temperature management is recommended for at least 24 h in comatose survivors of in-hospital cardiac arrest (IHCA) after the return of spontaneous circulation; however, whether an extension for 72 h leads to better neurological outcomes is uncertain. Methods: We included data from the Qilu Hospital of Shandong University between July 20, 2019, and June 30, 2022. Unconscious patients who had return of spontaneous circulation lasting >20 consecutive min and received endovascular cooling (72 h) or normothermia treatment were compared in terms of survival-to-discharge and favorable neurological survival. Propensity score matching was used to formulate balanced 1:3 matched patients. Results: In total, 2,084 patients were included. Sixteen patients received extended endovascular cooling and 48 matched controls received normothermia therapy. Compared with the normothermia group, patients who received prolonged endovascular cooling had a higher survival-to-discharge rate. However, good neurological outcomes did not differ significantly. Before matching, Cox regression analysis, using mortality as the event, showed that extended endovascular cooling independently affected the survival of IHCA patients. Conclusions: Among comatose patients who had been resuscitated from IHCA, the use of endovascular cooling for 72 h might confer a benefit on survival-to-discharge.

Discrimination between leucine-rich glioma-inactivated 1 antibody encephalitis and gamma-aminobutyric acid B receptor antibody encephalitis based on ResNet18.

This study aims to discriminate between leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis and gamma-aminobutyric acid B (GABAB) receptor antibody encephalitis using a convolutional neural network (CNN) model. A total of 81 patients were recruited for this study. ResNet18, VGG16, and ResNet50 were trained and tested separately using 3828 positron emission tomography image slices that contained the medial temporal lobe (MTL) or basal ganglia (BG). Leave-one-out cross-validation at the patient level was used to evaluate the CNN models. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC) were generated to evaluate the CNN models. Based on the prediction results at slice level, a decision strategy was employed to evaluate the CNN models' performance at patient level. The ResNet18 model achieved the best performance at the slice (AUC = 0.86, accuracy = 80.28%) and patient levels (AUC = 0.98, accuracy = 96.30%). Specifically, at the slice level, 73.28% (1445/1972) of image slices with GABAB receptor antibody encephalitis and 87.72% (1628/1856) of image slices with LGI1 antibody encephalitis were accurately detected. At the patient level, 94.12% (16/17) of patients with GABAB receptor antibody encephalitis and 96.88% (62/64) of patients with LGI1 antibody encephalitis were accurately detected. Heatmaps of the image slices extracted using gradient-weighted class activation mapping indicated that the model focused on the MTL and BG for classification. In general, the ResNet18 model is a potential approach for discriminating between LGI1 and GABAB receptor antibody encephalitis. Metabolism in the MTL and BG is important for discriminating between these two encephalitis subtypes.

SUPER Score Contributes to Warning and Management in Early-Stage COVID-19.

Background: Some COVID-19 patients deteriorate to severe cases with relatively higher case-fatality rates, which increases the medical burden. This necessitates identification of patients at risk of severe disease. Early assessment plays a crucial role in identifying patients at risk of severe disease. This study is to assess the effectiveness of SUPER score as a predictor of severe COVID-19 cases. Methods: We consecutively enrolled COVID-19 patients admitted to a comprehensive medical center in Wuhan, China, and recorded clinical characteristics and laboratory indexes. The SUPER score was calculated using parameters including oxygen saturation, urine volume, pulse, emotional state, and respiratory rate. In addition, the area under the receiver operating characteristic curve (AUC), specificity, and sensitivity of the SUPER score for the diagnosis of severe COVID-19 were calculated and compared with the National Early Warning Score 2 (NEWS2). Results: The SUPER score at admission, with a threshold of 4, exhibited good predictive performance for early identification of severe COVID-19 cases, yielding an AUC of 0.985 (95% confidence interval [CI] 0.897-1.000), sensitivity of 1.00 (95% CI 0.715-1.000), and specificity of 0.92 (95% CI 0.775-0.982), similar to NEWS2 (AUC 0.984; 95% CI 0.895-1.000, sensitivity 0.91; 95% CI 0.587-0.998, specificity 0.97; 95% CI 0.858-0.999). Compared with patients with a SUPER score<4, patients in the high-risk group exhibited lower lymphocyte counts, interleukin-2, interleukin-4 and higher fibrinogen, C-reactive protein, aspartate aminotransferase, and lactate dehydrogenase levels. Conclusions: In conclusion, the SUPER score demonstrated equivalent accuracy to the NEWS2 score in predicting severe COVID-19. Its application in prognostic assessment therefore offers an effective early warning system for critical management and facilitating efficient allocation of health resources.

Prognostic significance and extra-hypothalamus dysfunction of hyponatremia in anti-leucine-rich glioma-inactivated protein 1 encephalitis.

This study aimed to investigate prognostic significance and brain metabolic mechanism of hyponatremia in anti-leucine-rich glioma-inactivated protein 1 (LGI1) encephalitis. After adjusting for confounders, patients with moderate and severe hyponatremia had significantly increased risk of poor functional outcome and sequelae of seizures. In addition, serum sodium was negatively correlated with normalized ratio of the standardized uptake value of medial temporal lobe (MTL), basal ganglia (BG), and hypothalamus on positron emission tomography (PET) and which was further validated using voxel-wise analysis, suggesting an extra-hypothalamus (BG and MTL) localization for hyponatremia.

Colorimetric sensing of glucose and GSH using core-shell Cu/Au nanoparticles with peroxidase mimicking activity.

The catalytic properties of bimetallic nanoparticles have been widely studied by researchers in many fields. In this paper, core-shell Cu/Au nanoparticles (Cu/Au NPs) were synthesized by a simple and mild one-pot method, and their peroxidase activity was proved by catalyzing the oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) with color change to blue. The change of solution color and absorbance strongly depends on the concentration of H2O2, so it can be used for direct detection of H2O2 and indirect detection of glucose. What's more, GSH can efficiently react with the hydroxyl radicals from H2O2 catalyzed by core-shell Cu/Au NPs to inhibit the production of ox-TMB. Thus, the concentration of GSH can be determined by the decrease in the absorbance of the solution at 652 nm. The results showed that our proposed strategy had good detection range and detection limit for the detection of glucose and GSH. This method has been used in the detection of practical samples and has great application potential in environmental monitoring and clinical diagnosis.

Risk factors for Drug-resistant Epilepsy (DRE) and a nomogram model to predict DRE development in post-traumatic epilepsy patients.

OBJECTIVES: To identify factors affecting the development of drug-resistant epilepsy (DRE), and establish a reliable nomogram to predict DRE development in post-traumatic epilepsy (PTE) patients. METHODS: This study conducted a retrospective clinical analysis in patients with PTE who visited the Epilepsy Center, Beijing Tiantan Hospital from January 2013 to December 2018. All participants were followed up for at least 3 years, and the development of DRE was assessed. Data from January 2013 to December 2017 were used as development dataset for model building. Those independent predictors of DRE were included in the final multivariable logistic regression, and a derived nomogram was built. Data from January 2018 to December 2018 were used as validation dataset for internal validation. RESULTS: Complete clinical information was available for 2830 PTE patients (development dataset: 2023; validation dataset: 807), of which 21.06% (n = 596) developed DRE. Among all parameters of interest including gender, age at PTE, family history, severity of traumatic brain injury (TBI), single or multiple injuries, lesion location, post-TBI treatments, acute seizures, PTE latency, seizure type, status epilepticus (SE), and electroencephalogram (EEG) findings, four predictors showed independent effect on DRE, they were age at PTE, seizure type, SE, and EEG findings. A model incorporating these four variables was created, and a nomogram to calculate the probability of DRE using the coefficients of the model was developed. The C-index of the predictive model and the validation was 0.662 and 0.690, respectively. The goodness-of-fit test indicated good calibration for model development and validation (p = 0.272, 0.572). CONCLUSIONS: The proposed nomogram achieved significant potential for clinical utility in the prediction of DRE among PTE patients. The risk of DRE for individual PTE patients can be estimated by using this nomogram, and identified high-risk patients might benefit from non-pharmacological therapies at an early stage.

Predicting Global Functional Outcomes Among Post-traumatic Epilepsy Patients After Moderate-to-Severe Traumatic Brain Injury: Development of a Prognostic Model.

Objective: The development of post-traumatic epilepsy (PTE) following traumatic brain injury (TBI) is associated with unfavorable functional outcomes, and the global function of PTE patients might change dynamically overtime. Predicting the long-term functional outcomes of patients with PTE may help to develop accurate rehabilitation programs and improve their quality of life. Based on this, the objective of this study is to use clinical data to derive and validate a model for predicting the functional outcomes of patients with PTE after moderate-to-severe TBI. Methods: This study retrospectively analyzed 721 patients with PTE after moderate-to-severe TBI in the Epilepsy Centre, Beijing Tiantan Hospital, from January 2013 to December 2018. All patients had favorable global function as indicated by the Glasgow Outcome Scale-Extended (GOSE) at the time of their first late post-traumatic seizure (PTS) onset, and the 5-year global function after the first late PTS onset was chosen as the principal outcome of interest. To identify possible predictors for the global functional outcomes, univariate and multivariate logistic regression techniques were used. A prognostic model was established using these identified predictors, the internal validation with the bootstrapping method was performed, and the model was then visualized as a graphical score chart. Results: The 5-year global functional outcome of 98 (13.59%) patients was unfavorable, and the temporal lobe lesion was found as the strongest predictor of unfavorable outcomes. The final prognostic model also included the following other predictors: gender, age at TBI, multiple injuries, the severity of TBI, and latency of PTE. Discrimination was satisfactory with C-statistic of 0.754 (0.707 - 0.800), the goodness-of-fit test indicated good calibration (P = 0.137), and the C-statistic was 0.726 for internal validation. A graphical score chart was also constructed to provide the probability of an unfavorable 5-year global functional outcomes more readily. Conclusions: Clearer treatment strategies are essential to help ameliorate the global functional outcomes of patients with PTE. Our proposed prognostic model has significant potential to be used in the clinic for predicting global functional outcomes among patients with PTE after moderate-to-severe TBI.

The Detection of Invisible Abnormal Metabolism in the FDG-PET Images of Patients With Anti-LGI1 Encephalitis by Machine Learning.

Objective: This study aims to detect the invisible metabolic abnormality in PET images of patients with anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis using a multivariate cross-classification method. Methods: Participants were divided into two groups, namely, the training cohort and the testing cohort. The training cohort included 17 healthy participants and 17 patients with anti-LGI1 encephalitis whose metabolic abnormality was able to be visibly detected in both the medial temporal lobe and the basal ganglia in their PET images [completely detectable (CD) patients]. The testing cohort included another 16 healthy participants and 16 patients with anti-LGI1 encephalitis whose metabolic abnormality was not able to be visibly detected in the medial temporal lobe and the basal ganglia in their PET images [non-completely detectable (non-CD) patients]. Independent component analysis (ICA) was used to extract features and reduce dimensions. A logistic regression model was constructed to identify the non-CD patients. Results: For the testing cohort, the accuracy of classification was 90.63% with 13 out of 16 non-CD patients identified and all healthy participants distinguished from non-CD patients. The patterns of PET signal changes resulting from metabolic abnormalities related to anti-LGI1 encephalitis were similar for CD patients and non-CD patients. Conclusion: This study demonstrated that multivariate cross-classification combined with ICA could improve, to some degree, the detection of invisible abnormal metabolism in the PET images of patients with anti-LGI1 encephalitis. More importantly, the invisible metabolic abnormality in the PET images of non-CD patients showed patterns that were similar to those seen in CD patients.

Polyoxometalates-graphene nanocomposites modified electrode for electro-sensing detection of Sudan I in food.

Sudan I, a lipophilic azo dye -dye, is desirable and urgent to be accurate detected due to its increasing levels and high toxicity in food and environmental monitoring and analysis. Herein, a sensitive electrochemical sensor for Sudan I was established based on a new K10P2W18Fe4(H2O)2O68 functionalized carbon nanomaterials (Fe4P2W18-GNPS). The electrode modified nanocomposite, Fe4P2W18-GNPS, was successfully fabricated and characterized by FTIR, SEM and UV-vis. The effective combination of Fe4P2W18 and graphene exhibited high electrocatalytic activity towards the oxidation of Sudan I, promote charge transfer, and more sensing sites. Under optimized experimental conditions, the proposed differential pulse voltammetry (DPV) showed excellent analytical performances for Sudan I with the limit of detection (LOD) of 5 nM (S/N = 3), the sensitivity of 13.10 µA·µM-1cm-2 at the 0.005-2 µM and 0.39 µA·µM-1cm-2 at 10-200 µM. The stability and reproducibility make the electrochemical sensor suitable for detecting the Sudan I in food.

Cu2+ modified Zr-based metal organic framework-CTAB-graphene for sensitive electrochemical detection of sunset yellow.

A sensitive electrochemical sensor for sunset yellow (SY) was constructed based on cetyltrimethylammonium bromide (CTAB) functionalized graphene (Gr) and Cu/Zr-MOF electrode modified materials. The CTAB-Gr-Cu/Zr-MOF composites were synthesized by using a mild method and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy and EDX spectrum. The combination of Cu/Zr-MOF and graphene exhibited synergetic effect of the strong accumulation efficiency, fast electron transfer rate and more sensing sites towards the oxidation of SY. The new modified materials remarkably increased the electrochemical response of SY to 6.53-fold when comparing with bare electrode. Under the optimized conditions, the oxidation peak currents of SY had a linear relationship with its concentration in a wide range from 0.10 to 8.00 µM and 40.00-1000.00 µM, and the limit of detection was 6.68 nM (S/N = 3). The electrochemical method shows high sensitivity, stability, reproducibility and is successfully applied in the determination of SY in soft drinks.

Recent Advances in Polyoxometalates with Enzyme-like Characteristics for Analytical Applications.

Artificial enzymes based on inorganic solids with both enzyme-mimetic activities and the special material features has been a promising candidate to overcome many deleterious effects of native enzymes in analytical applications. Polyoxometalates (POMs) are an importance class of molecular metal-oxygen anionic clusters. Their outstanding physicochemical properties, versatility and potential applications in energy conversion, magnetism, catalysis, molecular electronics and biomedicine have long been studied. However, the analytical applications of them is limited. Recently, the intrinsic enzymatic activities of POMs have also been found and become an area of growing interest. In this review, along with other reports, we aimed to classify the enzymatic activity of POMs, summarize the construction of POMs-based enzymes, and survey their recent advances in analytical fields. Finally, the current challenges and trends of the polyoxometalates with enzymatic activity in future chemo-/bio-sensing applications are briefly discussed.

Factors predicting neuronal surface antibodies in the elderly with new-onset and unknown seizures.

OBJECTIVE: To investigate risk factors of neuronal surface antibodies (NSAbs) and develop a nomogram that could identify patients at the odds of NSAbs among the elderly (aged 60 years or older) with new-onset seizures of unknown etiology. METHODS: Clinical data for aged ≥60 years diagnosed with new-onset seizures of unknown etiology were retrospectively reviewed. A nomogram based on multivariable logistic regression was constructed. Model performance of nomogram was evaluated using area under the curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). Meanwhile, it was internally validated by bootstrap validation in current cohort. RESULTS: Of 147 patients included in final analysis, 68 (46.3%) had NSAbs-mediated encephalitis. Six factors were identified: duration of seizures less than 3 months (OR:14.259; 95% CI: 4.480-45.386), focal-onset seizures (OR:12.457; 95% CI: 2.710-57.261), psychiatric deficits (OR:10.063; 95% CI: 3.231-31.343), sleep disorders (OR:3.091; 95% CI: 1.011-9.454), hyponatremia (OR:6.252; 95% CI: 1.445-27.043), and medial temporal lobe (MTL) lesions on MRI (OR:4.102; 95% CI: 1.382-12.169). The nomogram had a good discrimination with an AUC of 0.916 and with a corrected AUC of 0.881 after the bootstrapping validation, our model also exhibited a better predictive performance than scoring systems commonly used clinically. Additionally, the calibration curve showed that predicted NSAbs-positive rates of nomogram were closely aligned with actual observed results. Moreover, the nomogram achieved well on clinical utility by using the DCA and CIC. INTERPRETATION: Our nomogram may provide a convenient and useful tool for identifying the elderly with new-onset seizures of unknown etiology who are at risk of NSAbs-mediated encephalitis, which would allow these patients receive earlier immunotherapy.

A Multifunctional Janus Electrospun Nanofiber Dressing with Biofluid Draining, Monitoring, and Antibacterial Properties for Wound Healing.

Wound healing greatly affects patients' health and produces medical burden. Therefore, we developed a multifunctional electrospun nanofiber dressing, which can inhibit methicillin-resistant Staphylococcus aureus (MRSA), drain excessive biofluid to promote wound healing, and simultaneously monitor wound pH level. The polyoxometalate (α-K6P2W18O62·14H2O, P2W18) and oxacillin (OXA) are encapsulated in hydrophobic polylactide (PLA) nanofiber to synergistically inhibit MRSA. The phenol red (PSP) is encapsulated in hydrophilic polyacrylonitrile (PAN) nanofiber to sensitively indicate wound pH in situ. The PSP/PAN nanofiber is directly electrospun on the patterning OXA/P2W18/PLA nanofiber layer to form a Janus dressing. By taking advantage of the wettability difference between the two layers, the excess biofluid can be drained away from the wound. In addition, the Janus dressing exhibits good biocompatibility and accelerates wound healing via its antimicrobial activity and skin repairing function. This multifunctional Janus electrospun nanofiber dressing would be beneficial for wound management and treatment.

Multienzymatic Antioxidant Activity of Manganese-Based Nanoparticles for Protection against Oxidative Cell Damage.

Oxidative stress is related to many diseases, but available clinical treatment methods are currently limited. Exploitation of enzyme-mimicking nanomaterials (nanozymes) is a promising way for scavenging reactive oxygen species (ROS) and treatment of ROS-related diseases. Herein, the catalase (CAT), superoxide dismutase (SOD), and glutathione peroxidase (GPx) mimicking activities are expressed by MnO2 nanoparticles (MnO2-BSA NPs) coated with BSA. Effective •OH removal activity is also expressed by MnO2-BSA NPs at neutral pH. Apoptosis inhibition and ROS scavenging capabilities of MnO2-BSA NPs are evident on the H2O2-exposed BEAS-2B cells line. Western blot analysis indicates that MnO2-BSA NPs inhibit H2O2-induced apoptosis by mediating the expression of apoptosis-related proteins.

Vancomycin recognition and induced-aggregation of the Au nanoparticles through freeze-thaw for foodborne pathogen Staphylococcus aureus detection.

Infectious diseases caused by foodborne pathogens have become a serious public health problem. It is urgent to develop simple, rapid, and visual methods for pathogen detection. Herein, gold nanoparticles (AuNPs), aptamer and vancomycin (Van) based dual-recognition molecules and magnetic enrichment were combined to realize visual detection of Staphylococcus aureus (S. aureus). Initially, S. aureus was bounded to aptamer coupled Fe3O4 with high affinity and selectivity, which can achieve the separation and enrichment of S. aureus in complex sample matrix. Subsequently, the second recognition molecule, Van, was conjugated to S. aureus -Apt - Fe3O4. Finally, the unbound Van supernatant was dropped in AuNPs solution that induced the aggregation of the AuNPs through freeze-thaw. Firstly, it was found that AuNPs were stable in the presence of Van after a freeze-thaw cycle. A facile visual colorimetric detection of S. aureus was constructed with the linear range from 101 to 104 CFU/mL and the limit of detection (LOD) of 0.2 CFU/mL. By altering the aptamer, this method can be extended to the other Gram-positive bacteria. The proposed method has great potential applications in monitoring food contamination and infectious diseases.

18 F-fluorodeoxy-glucose positron emission tomography pattern and prognostic predictors in patients with anti-GABAB receptor encephalitis.

AIMS: To identify the metabolic pattern and prognostic predictors in anti-gamma-aminobutyric-acid B (GABAB) receptor encephalitis using 18 F-fluorodeoxy-glucose positron emission tomography (18 F-FDG-PET). METHODS: Twenty-one patients diagnosed anti-GABAB receptor encephalitis who underwent 18 F-FDG-PET at first hospitalization were retrospectively reviewed. 18 F-FDG-PET images were analyzed in comparison with controls. Further group comparisons of 18 F-FDG-PET data were carried out between prognostic subgroups. RESULTS: 18 F-FDG-PET was abnormal in 81% patients with anti-GABAB receptor encephalitis and was more sensitive than MRI (81% vs. 42.9%, p = 0.025). Alter limbic lobe glucose metabolism (mostly hypermetabolism) was observed in 14 patients (66.7%), of whom 10 (10/14, 71.4%) demonstrated hypermetabolism in the medial temporal lobe (MTL). Group analysis also confirmed MTL hypermetabolism in association with relative frontal and parietal hypometabolism was a general metabolic pattern. After a median follow-up of 33 months, the group comparisons revealed that patients with poor outcome demonstrated increased metabolism in the MTL compared to those with good outcome. CONCLUSION: 18 F-FDG-PET may be more sensitive than MRI in the early diagnosis of anti-GABAB receptor encephalitis. MTL hypermetabolism was associated with relative frontal or parietal hypometabolism and may serve as a prognostic biomarker in anti-GABAB receptor encephalitis.

Risk Factors and Brain Metabolic Mechanism of Sleep Disorders in Autoimmune Encephalitis.

Background: Sleep disorders (SDs) in autoimmune encephalitis (AE) have received little attention and are poorly understood. We investigated the clinical characteristics, risk factors, and cerebral metabolic mechanism of SD in AE. Methods: Clinical, laboratory, and imaging data were retrospectively reviewed in 121 consecutively patients with definite AE. The risk factors for SD in AE were estimated by logistic regression analysis. Group comparisons based on 18F-fluorodeoxy-glucose positron emission tomography (18F-FDG-PET) data were made between patients with and without SD, to further analyze potential brain metabolic mechanism of SD in AE. Results: A total of 52.9% patients (64/121) with SD were identified. The multivariate logistic model analysis showed that smoking [odds ratio (OR), 6.774 (95% CI, 1.238-37.082); p = 0.027], increased Hamilton Depression scale (HAMD) score [OR, 1.074 (95% CI, 1.002-1.152); p = 0.045], hyperhomocysteinemia [OR, 2.815 (95% CI, 1.057-7.496); p = 0.038], elevated neuron-specific enolase (NSE) level [OR, 1.069 (95% CI, 1.007-1.135); p = 0.03] were independently correlated with higher risk of SD in AE patients. Contrastingly, high MoCA score [OR, 0.821 (95% CI, 0.752-0.896); p < 0.001] was associated with lower risk of SD in AE subjects. Compared to controls, AE patients had less total sleep time, less sleep efficiency, longer sleep latency, more wake, higher percent of stage N1, lower percent of stage N3 and rapid eye movement, and more arousal index in non-rapid eye movement sleep (p < 0.05 for all). Voxel-based group comparison analysis showed that, compared to patients without SD, patients with SD had increased metabolism in the basal ganglia, cerebellum, brainstem, median temporal lobe, thalamus, and hypothalamus [p < 0.05, false discovery rate (FDR) corrected]; decreased metabolism in superior frontal gyrus, medial frontal gyrus, and posterior cingulate cortex (p < 0.001, uncorrected). These results were confirmed by region of interest-based analysis between PET and sleep quality. Conclusion: Smoking, increased HAMD score, hyperhomocysteinemia, and elevated NSE level were correlated with higher risk of SD. High MoCA score was associated with lower risk of SD in AE subjects. Moreover, a widespread metabolic network dysfunction may be involved in the pathological mechanism of SD in AE.

Short- and Long-Term Prognosis of Intravascular Ultrasound-Versus Angiography-Guided Percutaneous Coronary Intervention: A Meta-Analysis Involving 24,783 Patients.

BACKGROUND: Intravascular ultrasound (IVUS) guided percutaneous coronary intervention (PCI) has potential benefits. This meta-analysis aimed to explore whether IVUS-guided PCI had better short- and long-term prognoses than angiography-guided PCI. METHODS: We retrieved studies from PubMed, Embase, and Cochrane Library. Clinical trials including retrospective and randomized controlled trials (RCTs) that compared IVUS-guided PCI with angiography-guided PCI were included. The patients were followed up after operation at 30 days, 1 year, 2 years, and 3 years. The clinical outcomes were target lesion revascularization (TLR), target vessel revascularization (TVR), and MACEs, including stent thrombosis (ST), myocardial infarction (MI), cardiac death, and all-cause death. The study population included patients with MI, coronary bifurcation lesions, short or long lesions, and unprotected left main coronary artery stenosis (ULMCA). The quality of retrospective trials was evaluated using the Newcastle-Ottawa Scale, and the quality of randomized controlled trials was evaluated using the Jadad score. A total of 20 clinical trials met the criteria. Three trials were randomized controlled trials, while 17 were retrospective trials. RESULTS: A total of 24,783 patients were included. In observational trials, the OR of MACEs was 0.49 (95% CI: 0.38-0.62) in 30 days, 0.65 (95% CI: 0.58-0.73) in one year, 0.51 (95% CI: 0.36-0.71) in two years, and 0.45 (95% CI: 0.31-0.65) in three years. In patients with long coronary lesions, the OR of MACEs in 1 year was 0.64 (95% CI: 0.28-1.50). In patients with left main artery disease, the OR of MACEs in 3 years was 0.42 (95% CI: 0.26-0.67). Compared with angiography-guided PCI, IVUS-guided PCI was associated with a lower incidence of MACEs during the same following period. CONCLUSION: Compared with angiography-guided PCI, IVUS-guided PCI has better performance in reducing the occurrence of MACEs.

Subcortical Hypermetabolism Associated With Cortical Hypometabolism Is a Common Metabolic Pattern in Patients With Anti-Leucine-Rich Glioma-Inactivated 1 Antibody Encephalitis.

Purpose: Brain 18F-fluorodeoxyglucose positron emission tomography (FDG PET) is a sensitive technique for assisting in the diagnosis of patients with anti-leucine-rich glioma-inactivated 1 (LGI1) antibody encephalitis. However, the common pattern of this disorder assessed by FDG PET remains unknown. The present study aimed to explore the glucose metabolic patterns of this disorder based on PET voxel analysis. Methods: This retrospective study enrolled 25 patients with anti-LGI1 encephalitis, who were admitted in Beijing Tiantan Hospital between September 2014 and July 2019. The glucose metabolic pattern was compared between the included patients and 44 age- and gender-matched healthy controls using Statistical Parametric Mapping. Then, the correlation between the metabolic pattern and scaled activities of daily living (ADLs) of the patients was assessed. Results: The median time from symptom onset to PET scans was 9 w (range:2-53w). The groupwise analysis revealed that patients with anti-LGI1 encephalitis had left hippocampal hypermetabolism and hypometabolism in almost all neocortical regions. The individual-level results showed most patients presented a decreased metabolism in neocortical regions, as well as an increase in metabolism in the hippocampus and basal ganglia. Furthermore, the metabolic gradient between hippocampus and neocortical regions was positively associated with the ADLs (frontal lobe, r=0.529, P=0.008; parietal lobe, r=0.474, P=0.019; occipital lobe, r=0.413, P=0.045; temporal lobe, r=0.490, P=0.015), respectively. In addition, the patients with facio-brachial dystonic seizures (FBDS) presented bilateral putamen hypermetabolism, when compared to patients without FBDS and healthy controls. Conclusion: Subcortical hypermetabolism associated with cortical hypometabolism presented with a common metabolic pattern in patients with anti-LGI1 encephalitis in the present study. The resolution of the metabolic gradient of the hippocampal hypermetabolism and neocortical hypometabolism may bring about improved clinical neurologic disability.

Osthole Attenuates Bleomycin-Induced Pulmonary Fibrosis by Modulating NADPH Oxidase 4-Derived Oxidative Stress in Mice.

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease characterized by the extensive accumulation of myofibroblasts and collagens. However, the exact mechanism that underlies this condition is unclear. Growing evidence suggests that NADPH oxidases (NOXs), especially NOX4-derived oxidative stress, play an important role in the development of lung fibrosis. Bleomycin (BLM) is a tumor chemotherapeutic agent, which has been widely employed to establish IPF animal models. Osthole (OST) is an active constituent of the fruit of Cnidium ninidium. Here, we used an in vivo mouse model and found that OST suppressed BLM-induced body weight loss, lung injury, pulmonary index increase, fibroblast differentiation, and pulmonary fibrosis. OST also significantly downregulated BLM-induced NOX4 expression and oxidative stress in the lungs. In vitro, OST could inhibit TGF-ß1-induced Smad3 phosphorylation, differentiation, proliferation, collagen synthesis, NOX4 expression, and ROS generation in human lung fibroblasts in a concentration-dependent manner. Moreover, NOX4 overexpression could prevent the above effects of OST. We came to the conclusion that OST could significantly attenuate BLM-induced pulmonary fibrosis in mice, via the mechanism that involved downregulating TGF-ß1/NOX4-mediated oxidative stress in lung fibroblasts.