The efficacy and safety of Dachaihu decoction in the treatment of nonalcoholic fatty liver disease: a systematic review and meta-analysis.

Background: Nonalcoholic fatty liver disease (NAFLD), also known as metabolic associated fatty liver disease (MAFLD), is a common liver condition characterized by excessive fat accumulation in the liver which is not caused by alcohol. The main causes of NAFLD are obesity and insulin resistance. Dachaihu decoction (DCHD), a classic formula in traditional Chinese medicine, has been proved to treat NAFLD by targeting different aspects of pathogenesis and is being progressively used in the treatment of NAFLD. DCHD is commonly applied in a modified form to treat the NAFLD. In light of this, it is imperative to conduct a systematic review and meta-analysis to assess the effectiveness and safety of DCHD in the management of NAFLD. There is a need for a systematic review and meta-analysis to assess the effectiveness and safety of modified DCHD in treating NAFLD. Objective: The objective of this meta-analysis was to systematically assess the clinical effectiveness and safety of DCHD in treating NAFLD. Methods: This meta-analysis adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Including seven databases, both Chinese and English databases were searched for relevant studies. The quality of included studies was carefully assessed using the bias risk assessment tool in the Cochrane Handbook. Eligible articles were the source of extracted data which was meta-analyzed by using Review Manager 5.4 and Stata 17.0. Results: A total of 10 studies containing 825 patients were included. Compared with conventional treatments, combined treatment could clearly improve the liver function of NAFLD patients, which could reduce the levels of ALT (MD = -7.69 U/L, 95% CI: -11.88 to -3.51, p < 0.001), AST (MD = -9.58 U/L, 95% CI: -12.84 to -6.33, p < 0.01), and it also had a certain impact on regulating lipid metabolism, which could reduce the levels of TC (MD = -0.85 mmol/L, 95% CI: -1.22 to 0.48, p < 0.01), TG (MD = -0.45 mmol/L, 95% CI: -0.64 to 0.21, p < 0.01). Adverse event showed that DCHD was relatively safe. Due to the inclusion of less than 10 trials in each group, it was not possible to conduct a thorough analysis of publication bias. Conclusion: According to the meta-analysis, in the treatment of the NAFLD, it is clear that the combination of DCHD was advantages over conventional treatment alone in improving liver function, regulating lipid metabolism. Additionally, DCHD demonstrates a relatively safe profile. Nevertheless, due to limitations in the quality and quantity of the studies incorporated, the effectiveness and safety of DCHD remain inconclusive. Consequently, further high-quality research is imperative to furnish more substantial evidence supporting the widespread clinical application of DCHD. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023397353, CRD42023397353.

The role of Fusobacterium nucleatum in cancer and its implications for clinical applications.

Fusobacterium nucleatum, a gram-negative anaerobic bacterium abundantly found in the human oral cavity, is widely recognized as a key pathobiont responsible for the initiation and progression of periodontal diseases due to its remarkable aggregative capabilities. Numerous clinical studies have linked F. nucleatum with unfavorable prognostic outcomes in various malignancies. In further research, scholars have partially elucidated the mechanisms underlying F. nucleatum's impact on various types of cancer, thus gaining a certain comprehension of the role played by F. nucleatum in cancer. In this comprehensive review, we present an in-depth synthesis of the interplay between F. nucleatum and different cancers, focusing on aspects such as tumor initiation, metastasis, chemoresistance, and modulation of the tumor immune microenvironment and immunotherapy. The implications for cancer diagnosis and treatment are also summarized. The objective of this review is to enhance our comprehension of the intricate relationship between F. nucleatum and oncogenic pathogenesis, while emphasizing potential therapeutic strategies.

Application of high-resolution MRI in evaluating statin efficacy on symptomatic intracranial atherosclerosis.

OBJECTIVES: To investigate the efficacy of statins on symptomatic intracranial atherosclerotic plaques using high-resolution 3.0 T MR vessel wall imaging (HR-MRI). METHODS: Patients with symptomatic intracranial atherosclerotic plaques (cerebral ischemic events within the last three months) confirmed by HR-MRI from July 2017 to August 2022 were retrospectively included in this study. The enrolled patients started statin therapy at baseline. All the patients underwent the follow-up HR-MRI examination after statin therapy for at least 3 months. A paired sample t-test and Wilcoxon rank sum test were used to evaluate the changes in plaque characteristics after statin therapy. Multivariate linear regression was further used to investigate the clinical factors associated with statin efficacy. RESULTS: A total of 48 patients (37 males; overall mean age = 60.2 ± 11.7 years) were included in this study. The follow-up time was 7.0 (5.6-12.0) months. In patients treated with statins for > 6 months (n = 31), plaque length, wall thickness, plaque burden, luminal stenosis and plaque enhancement were significantly reduced. Similar results were found in patients with good lipid control (n = 21). Younger age, lower BMI and hypertension were associated with decreased plaque burden. Lower BMI, hypertension and longer duration of statin therapy were associated with decreased plaque enhancement. Younger age and hypertension were associated with decreased luminal stenosis (all p < 0.05). CONCLUSION: HR-MRI can effectively evaluate plaques changes after statin therapy. Statins can reduce plaque burden and stabilize plaques. The effect of statin may have a relationship with age, BMI, hypertension, and duration of statin therapy. CLINICAL RELEVANCE STATEMENT: High-resolution MRI can be applied to evaluate the efficacy of statins on symptomatic intracranial atherosclerotic plaques. Long-term statin use and well-controlled blood lipid levels can help reduce plaque burden and stabilize plaques. KEY POINTS: High-resolution MRI provides great help evaluating the changes of plaque characteristics after statin therapy. Efficacy of statins is associated with duration of use, controlled lipid levels, and clinical factors. High-resolution MRI can serve as an effective method for following-up symptomatic intracranial atherosclerosis.

Development and validation of a diagnostic model for cerebral small vessel disease among rural older adults in China.

Objectives: Cerebral small vessel disease (CSVD) visible on MRI can be asymptomatic. We sought to develop and validate a model for detecting CSVD in rural older adults. Methods: This study included 1,192 participants in the MRI sub-study within the Multidomain Interventions to Delay Dementia and Disability in Rural China. Total sample was randomly divided into training set and validation set. MRI markers of CSVD were assessed following the international criteria, and total CSVD burden was assessed on a scale from 0 to 4. Logistic regression analyses were used to screen risk factors and develop the diagnostic model. A nomogram was used to visualize the model. Model performance was assessed using the area under the receiver-operating characteristic curve (AUC), calibration plot, and decision curve analysis. Results: The model included age, high blood pressure, white blood cell count, neutrophil-to-lymphocyte ratio (NLR), and history of cerebral infarction. The AUC was 0.71 (95% CI, 0.67-0.76) in the training set and 0.69 (95% CI, 0.63-0.76) in the validation set. The model showed high coherence between predicted and observed probabilities in both the training and validation sets. The model had higher net benefits than the strategy assuming all participants either at high risk or low risk of CSVD for probability thresholds ranging 50-90% in the training set, and 65-98% in the validation set. Conclusion: A model that integrates routine clinical factors could detect CSVD in older adults, with good discrimination and calibration. The model has implication for clinical decision-making.

Dexamethasone palmitate encapsulated in palmitic acid modified human serum albumin nanoparticles for the treatment of rheumatoid arthritis.

Rheumatoid arthritis (RA) is a chronic inflammatory joint condition characterized by symmetric, erosive synovitis leading to cartilage erosion and significant disability. Macrophages, pivotal in disease progression, release pro-inflammatory factors upon activation. We developed a nanoparticle delivery system (DXP-PSA NPs), based on palmitic acid modified human serum albumin (PSA), to deliver dexamethasone palmitate (DXP) directly to sites of inflammation, enhancing treatment effectiveness and minimizing possible side effects. The system actively targets scavenger receptor-A on activated macrophages, achieving selective accumulation at inflamed joints. In vitro effect and preliminary targeting abilities were investigated on LPS-activated RAW264.7 cells. The in vivo efficacy and safety were evaluated and compared side to side with commercially available lipid emulsion Limethason® in an advanced adjuvant-induced arthritis rat model. DXP-PSA NPs offer a novel approach to RA treatment and presents promising prospects for clinical translation.

Adipocyte-targeted celastrol delivery via biguanide-modified micelles improves treatment of obesity in DIO mice.

Obesity has emerged as a significant global health burden, exacerbated by serious side effects associated with existing anti-obesity medications. Celastrol (CLT) holds promise for weight loss but encounters challenges related to poor solubility and systemic toxicity. Here, we present chondroitin sulfate (CS)-derived micelles engineered for adipocyte-specific targeting, aiming to enhance the therapeutic potential of CLT while minimizing its systemic toxicity. To further enhance adipocyte affinity, we introduced a biguanide moiety into a micellar vehicle. CS is sequentially modified with hydrophilic metformin and hydrophobic 4-aminophenylboronic acid pinacol ester (PBE), resulting in the self-assembly of CLT-encapsulated micelles (MET-CS-PBE@CLT). This innovative design imparts amphiphilicity via the PBE moieties while ensuring the outward exposure of hydrophilic metformin moieties, facilitating active interactions with adipocytes. In vitro studies confirmed the enhanced uptake of MET-CS-PBE@CLT micelles by adipocytes, while in vivo studies demonstrated increased distribution within adipose tissues. In a diet-induced obese mouse model, MET-CS-PBE@CLT exhibited remarkable efficacy in weight loss without affecting food intake. This pioneering strategy offers a promising, low-risk, and highly effective solution to address the global obesity epidemic.

Glomerulus-Targeted ROS-Responsive Polymeric Nanoparticles for Effective Membranous Nephropathy Therapy.

Membranous nephropathy (MN) is a common immune-mediated glomerular disease that requires the development of safe and highly effective therapies. Celastrol (CLT) has shown promise as a therapeutic molecule candidate, but its clinical use is currently limited due to off-target toxicity. Given that excess levels of reactive oxygen species (ROS) contributing to podocyte damage is a key driver of MN progression to end-stage renal disease, we rationally designed ROS-responsive cationic polymeric nanoparticles (PPS-CPNs) with a well-defined particle size and surface charge by employing poly(propylene sulfide)-polyethylene glycol (PPS-PEG) and poly(propylene sulfide)-polyethylenimine (PPS-PEI) to selectively deliver CLT to the damaged glomerulus for MN therapy. Experimental results show that PPS-CPNs successfully crossed the fenestrated endothelium, accumulated in the glomerular basement membrane (GBM), and were internalized by podocytes where rapid drug release was triggered by the overproduction of ROS, thereby outperforming nonresponsive CLT nanotherapy to alleviate subepithelial immune deposits, podocyte foot process effacement, and GBM expansion in a rat MN model. Moreover, the ROS-responsive CLT nanotherapy was associated with significantly lower toxicity to major organs than free CLT. These results suggest that encapsulating CLT into PPS-CPNs can improve efficacy and reduce toxicity as a promising treatment option for MN.

Innovative road distress detection (IR-DD): an efficient and scalable deep learning approach.

In the rapidly evolving landscape of transportation infrastructure, the quality and condition of road networks play a pivotal role in societal progress and economic growth. In the realm of road distress detection, traditional methods have long grappled with manual intervention and high costs, requiring trained observers for time-consuming and expensive data collection processes. The limitations of these approaches are compounded by challenges in adapting to diverse road surfaces and handling low-resolution data, particularly in early automated distress survey technologies. This article addresses the critical need for efficient road distress detection, a key component of ensuring safe and reliable transportation systems. Effectively addressing these challenges is crucial for enhancing the efficiency, accuracy, and safety of road distress detection systems. Leveraging advancements in object detection, we introduce the Innovative Road Distress Detection (IR-DD), a novel framework that integrates the YOLOv8 algorithm to enhance the accuracy and real-time capabilities of road distress detection, catering to applications such as smart cities and autonomous vehicles. Our approach incorporates bidirectional feature pyramid network (BiFPN) recursive feature fusion and bidirectional connections to optimize the utilization of multi-scale features, addressing challenges related to information loss and gradients encountered in traditional methods. Comprehensive experimental analysis demonstrates the superior performance, efficiency, and robustness of our integrated approach, positioning it as a cost-effective and compelling alternative to conventional road distress detection methods. Our findings demonstrate the superior performance of our approach compared to other state-of-the-art methods across various evaluation metrics, including precision, recall, F1 score, and mean average precision (mAP) at different intersection over union (IoU) thresholds. Specifically, our method achieves notable results with a precision of 0.666, F1 score of 0.630, mAP@0.5 of 0.650, all while operating at a speed of 86 frames per second (FPS). These outcomes underscore the effectiveness of our approach in real-time road distress detection. This article contributes to the ongoing innovation in object detection techniques, emphasizing the practicality and effectiveness of our proposed solution in advancing the field of road distress detection.

Estimation of soybean yield based on high-throughput phenotyping and machine learning.

Introduction: Soybeans are an important crop used for food, oil, and feed. However, China's soybean self-sufficiency is highly inadequate, with an annual import volume exceeding 80%. RGB cameras serve as powerful tools for estimating crop yield, and machine learning is a practical method based on various features, providing improved yield predictions. However, selecting different input parameters and models, specifically optimal features and model effects, significantly influences soybean yield prediction. Methods: This study used an RGB camera to capture soybean canopy images from both the side and top perspectives during the R6 stage (pod filling stage) for 240 soybean varieties (a natural population formed by four provinces in China: Sichuan, Yunnan, Chongqing, and Guizhou). From these images, the morphological, color, and textural features of the soybeans were extracted. Subsequently, feature selection was performed on the image parameters using a Pearson correlation coefficient threshold ≥0.5. Five machine learning methods, namely, CatBoost, LightGBM, RF, GBDT, and MLP, were employed to establish soybean yield estimation models based on the individual and combined image parameters from the two perspectives extracted from RGB images. Results: (1) GBDT is the optimal model for predicting soybean yield, with a test set R2 value of 0.82, an RMSE of 1.99 g/plant, and an MAE of 3.12%. (2) The fusion of multiangle and multitype indicators is conducive to improving soybean yield prediction accuracy. Conclusion: Therefore, this combination of parameters extracted from RGB images via machine learning has great potential for estimating soybean yield, providing a theoretical basis and technical support for accelerating the soybean breeding process.

Effectiveness of azvudine against severe outcomes among hospitalized COVID-19 patients in Xinjiang, China: a single-center, retrospective, matched cohort study.

BACKGROUND: Since the end of 2022, Azvudine was widely used to treat hospitalized coronavirus disease 2019 (COVID-19) patients in China. However, data on the real-world effectiveness of Azvudine against severe outcomes and post-COVID-19-conditions (PCC) among patients infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variants was limited. This study evaluates the effectiveness of Azvudine in hospitalized COVID-19 patients during a SARS-CoV-2 Omicron BA.5 dominance period. METHODS: From 1 November 2022 to 1 July 2023, an SARS-CoV-2 Omicron BA.5 dominant period, we conducted a single-center retrospective cohort study based on hospitalized patients with laboratory-confirmed SARS-CoV-2 infection from a tertiary hospital in Shihezi, China. Patients treated with Azvudine and usual care were propensity-score matched (PSM) at a 1:1 ratio to a control group in which patients received usual care only, with matching based on covariates such as sex, age, ethnicity, number of preexisting conditions, antibiotic use at admission, and baseline complete blood cell count. The primary outcomes were all-cause death and short-term (60 days) PCC post discharge. The secondary outcomes included the initiation of invasive mechanical ventilation and PCC at long-term post discharge (120 days). Cox proportional hazards (PH) regression models were employed to estimate the hazard ratios (HR) of Azvudine treatment for both all-cause death and invasive mechanical ventilation, and logistic regression models were used to estimate the odds ratios (OR) for short-term and long-term PCC. Subgroup analyses were performed based on a part of the matched covariates. RESULTS: A total of 2,639 hospitalized patients with SARS-CoV-2 infection were initially identified, and 2,069 ineligible subjects were excluded from analyses. After matching, 297 Azvudine recipients and 297 matched controls were eligible for analyses. The incidence rate of all-cause death was relatively lower in the Azvudine group than in control group (0.007 per person, 95% confidence interval [CI]: 0.001, 0.024 vs 0.128, 95% CI: 0.092, 0.171), and the use of Azvudine was associated with a significantly lower risk of death (HR: 0.049, 95% CI: 0.012, 0.205). Subgroup analyses suggested protection of Azvudine against the risks of all-cause death among men, age over 65, patients without the preexisting conditions, and patients with antibiotics dispensed at admission. Statistical differences were not observed between the Azvudine group and the control group for the risks of invasive mechanical ventilation or short and long-term PCC. CONCLUSIONS: Our findings indicated that Azvudine was associated with lower risk of all-cause death among hospitalized patients with Omicron BA.5 infection in a real-world setting. Further investigation is needed to explore the effectiveness of Azvudine against the PCC after discharge.

This study aims to evaluate the real-world effectiveness of Azvudine among hospitalized COVID-19 patients during a SARS-CoV-2 Omicron BA.5 dominant epidemic phase. Cox proportional hazards (PH) regression models were employed to estimate the hazard ratios (HR) for all-cause death. We found that the use of Azvudine was associated with a significantly reduced risk of all-cause death among hospitalized patients with SARS-CoV-2 infection.

Hypo-connectivity of the primary somatosensory cortex in Parkinson's disease: a resting-state functional MRI study.

Background: Parkinson's disease (PD) is characterized by a range of motor symptoms as well as documented sensory dysfunction. This sensory dysfunction can present itself either as a "pure" sensory disturbance or as a consequence of sensory-motor integration within the central nervous system. This study aims to investigate changes in the functional connectivity of the primary somatosensory cortex (S1) and its clinical significance in Parkinson's disease (PD), an area that has received limited attention in previous neuroimaging studies. Methods: This study included thirty-three patients with PD and thirty-four healthy controls (HCs). Clinical evaluations were conducted to assess the clinical manifestations, severity, and functional capacity of all the patients. Resting-state functional MRI (fMRI) was employed to evaluate the functional connectivity of six paired S1 subregions in the participants. Seed-based correlation (SBC) analysis was utilized to construct the correlation matrix among the subregions and to generate connectivity maps between the subregions and the remaining brain voxels. Finally, the study employed partial least-squares (PLS) correlation analysis to investigate the association between modified functional connectivity and clinical characteristics in PD patients. Results: In the correlation matrix, patients with PD demonstrated a notable decrease in functional connectivity across various S1 subregions in comparison to HCs (p < 0.001, corrected using network-based methods). In connectivity maps, hypo-connectivity was primarily observed in the sensorimotor network as common patterns (p < 0.001, corrected for false discovery rate) and in the default mode network (DMN) as distinct patterns. Moreover, this study identified a negative association between the correlation matrix within S1 subregions and the scores for axial symptoms and postural instability/gait difficulty (PIGD) in PD patients. Nevertheless, a direct relationship between the connectivity maps of S1 subregions and clinical assessment scales was not established. Conclusion: This study offers novel insights into the neurobiological mechanisms that contribute to S1 dysfunction in PD, highlighting the significant involvement of S1 hypo-connectivity in the motor disturbances observed in PD patients.

Autophagy-related protein 5 (ATG5) interacts with bone marrow stromal cell antigen 2 (BST2) to stimulate HBV replication through antagonizing the antiviral activity of BST2.

Hepatitis B virus (HBV) infection is a major global health burden with 820 000 deaths per year. In our previous study, we found that the knockdown of autophagy-related protein 5 (ATG5) significantly upregulated the interferon-stimulated genes (ISGs) expression to exert the anti-HCV effect. However, the regulation of ATG5 on HBV replication and its underlying mechanism remains unclear. In this study, we screened the altered expression of type I interferon (IFN-I) pathway genes using RT² Profiler™ PCR array following ATG5 knock-down and we found the bone marrow stromal cell antigen 2 (BST2) expression was significantly increased. We then verified the upregulation of BST2 by ATG5 knockdown using RT-qPCR and found that the knockdown of ATG5 activated the Janus kinase/signal transducer and activator of transcription (JAK-STAT) signaling pathway. ATG5 knockdown or BST2 overexpression decreased Hepatitis B core Antigen (HBcAg) protein, HBV DNA levels in cells and supernatants of HepAD38 and HBV-infected NTCP-HepG2. Knockdown of BST2 abrogated the anti-HBV effect of ATG5 knockdown. Furthermore, we found that ATG5 interacted with BST2, and further formed a ternary complex together with HBV-X (HBx). In conclusion, our finding indicates that ATG5 promotes HBV replication through decreasing BST2 expression and interacting with it directly to antagonize its antiviral function.

Local hyperthermia mediated by gold nanoparticle-integrated silicone-covered stent: feasibility and tissue response in a rat esophageal model.

BACKGROUND: To assess the feasibility and tissue response of using a gold nanoparticle (AuNP)-integrated silicone-covered self-expandable metal stent (SEMS) for local hyperthermia in a rat esophageal model. METHODS: The study involved 42 Sprague-Dawley rats. Initially, 6 animals were subjected to near-infrared (NIR) laser irradiation (power output from 0.2 to 2.4 W) to assess the in vitro heating characteristics of the AuNP-integrated SEMS immediately after its placement. The surface temperature of the stented esophagus was then measured using an infrared thermal camera before euthanizing the animals. Subsequently, the remaining 36 animals were randomly divided into 4 groups of 9 each. Groups A and B received AuNP-integrated SEMS, while groups C and D received conventional SEMS. On day 14, groups A and C underwent NIR laser irradiation at a power output of 1.6 W for 2 min. By days 15 (3 animals per group) or 28 (6 animals per group), all groups were euthanized for gross, histological, and immunohistochemical analysis. RESULTS: Under NIR laser irradiation, the surface temperature of the stented esophagus quickly increased to a steady-state level. The surface temperature of the stented esophagus increased proportionally with power outputs, being 47.3 ± 1.4 °C (mean ± standard deviation) at 1.6 W. Only group A attained full circumferential heating through all layers, from the epithelium to the muscularis propria, demonstrating marked apoptosis in these layers without noticeable necroptosis. CONCLUSIONS: Local hyperthermia using the AuNP-integrated silicone-covered SEMS was feasible and induced cell death through apoptosis in a rat esophageal model. RELEVANCE STATEMENT: A gold nanoparticle-integrated silicone-covered self-expanding metal stent has been developed to mediate local hyperthermia. This approach holds potential for irreversibly damaging cancer cells, improving the sensitivity of cancer cells to therapies, and triggering systemic anticancer immune responses. KEY POINTS: • A gold nanoparticle-integrated silicone-covered self-expanding metal stent was placed in the rat esophagus. • Upon near-infrared laser irradiation, this stent quickly increased the temperature of the stented esophagus. • Local hyperthermia using this stent was feasible and resulted in cell death through apoptosis.

Adipocyte-targeted delivery of rosiglitazone with localized photothermal therapy for the treatment of diet-induced obesity in mice.

Obesity represents a growing public health concern and is closely associated with metabolic complications such as diabetes and fatty liver disease. Anti-obesity medications currently available have limited efficacy in weight loss and are often accompanied by adverse effects. This study proposes a localized photothermal therapy (PTT) combined with adipocyte-targeted delivery of rosiglitazone (RSG) to address obesity. Specifically, cationic albumin nanoparticles (cNPs) were synthesized to deliver RSG precisely to white adipocytes, stimulating the browning process. An IR780-loaded thermosensitive hydrogel was injected and allowed to gel in situ to afford a subcutaneous reservoir that enables localized PTT and controlled release of RSG cNPs. Notably, cNPs significantly enhanced the internalization efficiency in adipocytes in vitro and prolonged the therapeutic retention in the adipose tissue in vivo. Co-administration of RSG cNPs and PTT substantially reduced fat content, induced browning in white adipose tissue in diet-induced obese mice, and mitigated complications such as insulin resistance, fatty liver, and hyperlipidemia. The increased expression of uncoupling protein 1 contributes to enhancing energy expenditure and facilitating adipose metabolism, thereby effectively combating obesity. This therapeutic approach integrates localized PTT with adipocyte-targeted delivery to combat the global obesity epidemic thus offering a promising solution with reduced systemic toxicity and enhanced efficacy. STATEMENT OF SIGNIFICANCE: Cationic albumin nanoparticles are capable of efficient internalization in adipocytes, which may enhance drug targeting to adipose tissue. The combination of rosiglitazone-loaded cationic albumin nanoparticles and local hyperthermia effectively reduces lipid accumulation in adipocytes and induces an upregulated expression of uncoupling protein 1. The combination therapy effectively inhibits fat accumulation, induces adipocyte browning, and regulates systemic metabolism in diet-induced obese mice.

Metabolite T1 relaxation times decrease across the adult lifespan.

Relaxation correction is an integral step in quantifying brain metabolite concentrations measured by in vivo magnetic resonance spectroscopy (MRS). While most quantification routines assume constant T1 relaxation across age, it is possible that aging alters T1 relaxation rates, as is seen for T2 relaxation. Here, we investigate the age dependence of metabolite T1 relaxation times at 3 T in both gray- and white-matter-rich voxels using publicly available metabolite and metabolite-nulled (single inversion recovery TI = 600 ms) spectra acquired at 3 T using Point RESolved Spectroscopy (PRESS) localization. Data were acquired from voxels in the posterior cingulate cortex (PCC) and centrum semiovale (CSO) in 102 healthy volunteers across 5 decades of life (aged 20-69 years). All spectra were analyzed in Osprey v.2.4.0. To estimate T1 relaxation times for total N-acetyl aspartate at 2.0 ppm (tNAA2.0) and total creatine at 3.0 ppm (tCr3.0), the ratio of modeled metabolite residual amplitudes in the metabolite-nulled spectrum to the full metabolite signal was calculated using the single-inversion-recovery signal equation. Correlations between T1 and subject age were evaluated. Spearman correlations revealed that estimated T1 relaxation times of tNAA2.0 (rs = -0.27; p < 0.006) and tCr3.0 (rs = -0.40; p < 0.001) decreased significantly with age in white-matter-rich CSO, and less steeply for tNAA2.0 (rs = -0.228; p = 0.005) and (not significantly for) tCr3.0 (rs = -0.13; p = 0.196) in graymatter-rich PCC. The analysis harnessed a large publicly available cross-sectional dataset to test an important hypothesis, that metabolite T1 relaxation times change with age. This preliminary study stresses the importance of further work to measure age-normed metabolite T1 relaxation times for accurate quantification of metabolite levels in studies of aging.

Comparison of smokers' mortality with non-smokers following out-of-hospital cardiac arrests: a systematic review and meta-analysis.

OBJECTIVE: Although some studies have linked smoking to mortality after out-of-hospital cardiac arrests (OHCAs), data regarding smoking and mortality after OHCAs have not yet been discussed in a meta-analysis. Thus, this study conducted this systematic review to clarify the association. METHODS: The study searched Medline-PubMed, Web of Science, Embase and Cochrane libraries between January 1972 and July 2022 for studies that evaluated the association between smoking and mortality after OHCAs. Studies that reportedly showed relative risk estimates with 95% confidence intervals (CIs) were included. RESULTS: Incorporating a collective of five studies comprising 2477 participants, the analysis revealed a lower mortality risk among smokers in the aftermath of OHCAs compared with non-smokers (odds ratio: 0.77; 95% CI 0.61-0.96; P < 0.05). Egger's test showed no publication bias in the relationship between smoking and mortality after OHCAs. CONCLUSIONS: After experiencing OHCAs, smokers had lower mortality than non-smokers. However, due to the lack of data, this 'smoker's paradox' still needs other covariate effects and further studies to be considered valid.

Cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of Shigella flexneri.

Pathogen infections including Shigella flexneri have posed a significant threat to human health for numerous years. Although culturing and qPCR were the gold standards for pathogen detection, time-consuming and instrument-dependent restrict their application in rapid diagnosis and economically less-developed regions. Thus, it is urgently needed to develop rapid, simple, sensitive, accurate, and low-cost detection methods for pathogen detection. In this study, an immunomagnetic beads-recombinase polymerase amplification-CRISPR/Cas12a (IMB-RPA-CRISPR/Cas12a) method was built based on a cascaded signal amplification strategy for ultra-specific, ultra-sensitive, and visual detection of S. flexneri in the laboratory. Firstly, S. flexneri was specifically captured and enriched by IMB (Shigella antibody-coated magnetic beads), and the genomic DNA was released and used as the template in the RPA reaction. Then, the RPA products were mixed with the pre-loaded CRISPR/Cas12a for fluorescence visualization. The results were observed by naked eyes under LED blue light, with a sensitivity of 5 CFU/mL in a time of 70 min. With no specialized equipment or complicated technical requirements, the IMB-RPA-CRISPR/Cas12a diagnostic method can be used for visual, rapid, and simple detection of S. flexneri and can be easily adapted to monitoring other pathogens.

Simple, sensitive, and visual detection of 12 respiratory pathogens with one-pot-RPA-CRISPR/Cas12a assay.

Respiratory infections pose a serious threat to global public health, underscoring the urgent need for rapid, accurate, and large-scale diagnostic tools. In recent years, the CRISPR/Cas (clustered regularly interspaced short palindromic repeats/CRISPR-associated) system, combined with isothermal amplification methods, has seen widespread application in nucleic acid testing (NAT). However, achieving a single-tube reaction system containing all necessary components is challenging due to the competitive effects between recombinase polymerase amplification (RPA) and CRISPR/Cas reagents. Furthermore, to enable precision medicine, distinguishing between bacterial and viral infections is essential. Here, we have developed a novel NAT method, termed one-pot-RPA-CRISPR/Cas12a, which combines RPA with CRISPR molecular diagnostic technology, enabling simultaneous detection of 12 common respiratory pathogens, including six bacteria and six viruses. RPA and CRISPR/Cas12a reactions are separated by paraffin, providing an independent platform for RPA reactions to generate sufficient target products before being mixed with the CRISPR/Cas12a system. Results can be visually observed under LED blue light. The sensitivity of the one-pot-RPA-CRISPR/Cas12a method is 2.5 × 100 copies/µL plasmids, with no cross-reaction with other bacteria or viruses. Additionally, the clinical utility was evaluated by testing clinical isolates of bacteria and virus throat swab samples, demonstrating favorable performance. Thus, our one-pot-RPA-CRISPR/Cas12a method shows immense potential for accurate and large-scale detection of 12 common respiratory pathogens in point-of-care testing.

Construction of Oxygen Vacancy-Rich TiO2 Nanocrystals for Boosting the Ammonolysis of Caprolactam to 6-Aminocapronitrile.

Hexamethylene diamine, an important chemical intermediate for polyamides, can be synthesized through the two-step route of caprolactam (CPL) ammonolysis to 6-aminocapronitrile (ACN), followed by hydrogenation. This method has received increasing attention from academia and industry. However, studies on the catalyst structure-performance correlation in CPL ammonolysis are still sporadic. In this work, a series of anatase TiO2 with different oxygen vacancy concentrations was prepared by chemical reduction using NaBH4. The oxygen vacancy on TiO2 surface, presented as Ti3+ sites, substantially enhances the adsorption and activation of NH3, which are demonstrated as the key steps in ammonolysis. Owing to the synergistic effect of Ti3+ and Ti4+ species, the CPL conversion rate and ACN selectivity of 85 and 97%, respectively, are achieved within 250 h. Density functional theory calculations showed that the intermediates on oxygen vacancy-rich TiO2 had a more favorable adsorption energy compared to those on intact TiO2, which is in good agreement with the experimental results.

3D Printing Self-Healing and Self-Adhesive Elastomers for Wearable Electronics in Amphibious Environments.

To meet the demands of challenging usage scenarios, there is an increasing need for flexible electronic skins that can operate properly not only in terrestrial environments but also extend to complex aquatic conditions. In this study, we develop an elastomer by incorporating dynamic urea bonds and hydrogen bonds into the polydimethylsiloxane backbone, which exhibits excellent autonomous self-healing and reversible adhesive performance in both dry and wet environments. A multifunctional flexible sensor with excellent sensing stability, amphibious self-healing capacity, and amphibious self-adhesive performance is fabricated through solvent-free 3D printing. The sensor has a high sensing sensitivity (GF = 45.1) and a low strain response threshold (0.25%) and can be used to detect small human movements and physiological activities, such as muscle movement, joint movement, respiration, and heartbeat. The wireless wearable sensing system assembled by coupling this device with a bluetooth transmission system is suitable for monitoring strenuous human movement in amphibious environments, such as playing basketball, cycling, running (terrestrial environments), and swimming (aquatic environments). The design strategy provides insights into enhancing the self-healing and self-adhesive properties of soft materials and promises a prospective avenue for fabricating flexible electronic skin that can work properly in amphibious environments.