Effect of molecular weight of chitosan on quercetin-loaded chitosan nanoparticles.

BACKGROUND: The widespread use of quercetin is limited by its instability, low solubility and poor oral bioavailability. Encapsulation of quercetin using a nanoparticle delivery system is an effective way to overcome these drawbacks. RESULTS: The effect of the molecular weight (Mw) of chitosan (CS) (100, 200, 500 and 1000 kDa) on quercetin-loaded chitosan nanoparticles (QCNPs) was investigated. The structure, stability, release properties and antioxidant activities of the nanoparticles (QCNP-10, QCNP-20, QCNP-50 and QCNP-100) were assessed. Particle size of QCNPs decreased and polydispersity index increased with the increasing Mw of CS. The main forces involved in the formation of QCNPs were hydrogen bonding and hydrophobic interaction. X-ray diffraction verified that quercetin was loaded into CS nanoparticles. The photostability and thermal stability of QCNPs increased with increasing Mw of CS. QCNP-100 exhibited the lowest release rate in a mixture of water and anhydrous ethanol. The antioxidant activities of QCNPs were enhanced with increasing Mw of CS, and QCNP-100 possessed the highest antioxidant activities, which might be relevant to its smallest particle size. CONCLUSION: Overall, these results revealed that the Mw of CS affected the properties of QCNPs, and QCNP-100 possessed the smallest particle, best stability, lowest release rate and highest antioxidant activities. © 2024 Society of Chemical Industry.

Drug-eluting beads transarterial chemoembolization combined apatinib/camrelizumab for advanced hepatocellular carcinoma with hepatic arterioportal shunts.

OBJECTIVE: The objective of this study was to evaluate the efficacy and safety of drug-eluting beads transarterial chemoembolization (D-TACE) combined with apatinib/camrelizumab in advanced hepatocellular carcinoma (HCC) patients with hepatic arterioportal shunts (APS). METHODS: From January 2021 to December 2022, consecutive medical records of advanced HCC patients with APS receiving D-TACE combined apatinib/camrelizumab were reviewed for eligibility. Overall survival (OS), progression-free survival (PFS), tumor response, and adverse events (AEs) were assessed. RESULTS: A total of 23 patients were included in this study, and the median follow-up time was 11 months (range, 2-26 months). In this study, 8 patients (34.8%) achieved PR, 13 patients (56.5%) achieved SD, and 2 patients (8.7%) developed PD. The objective response rate and disease controlled rate were 34.8% and 91.3%, respectively. OS and PFS were 11 months and 7 months, respectively. Multivariate analysis indicated that tumor number was an independent prognostic factor affecting PFS. AEs occurred in 19 patients after oral apatinib and in 8 patients after camrelizumab treatment. No treatment-related death occurred. CONCLUSIONS: D-TACE combined with apatinib/camrelizumab had meaningful efficacy and controllable AEs in advanced HCC patients with APS, which may be a promising treatment option. ADVANCES IN KNOWLEDGE: •1.We investigate a new treatment strategy for advanced HCC patients with hepatic arterioportal shunts；2.D-TACE combined with apatinib/camrelizumab had meaningful efficacy and controllable AEs in advanced HCC patients with APS, which may be a promising treatment option.

Construction of a risk prediction model for lung infection after chemotherapy in lung cancer patients based on the machine learning algorithm.

Purpose: The objective of this study was to create and validate a machine learning (ML)-based model for predicting the likelihood of lung infections following chemotherapy in patients with lung cancer. Methods: A retrospective study was conducted on a cohort of 502 lung cancer patients undergoing chemotherapy. Data on age, Body Mass Index (BMI), underlying disease, chemotherapy cycle, number of hospitalizations, and various blood test results were collected from medical records. We used the Synthetic Minority Oversampling Technique (SMOTE) to handle unbalanced data. Feature screening was performed using the Boruta algorithm and The Least Absolute Shrinkage and Selection Operator (LASSO). Subsequently, six ML algorithms, namely Logistic Regression (LR), Random Forest (RF), Gaussian Naive Bayes (GNB), Multi-layer Perceptron (MLP), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) were employed to train and develop an ML model using a 10-fold cross-validation methodology. The model's performance was evaluated through various metrics, including the area under the receiver operating characteristic curve (ROC), accuracy, sensitivity, specificity, F1 score, calibration curve, decision curves, clinical impact curve, and confusion matrix. In addition, model interpretation was performed by the Shapley Additive Explanations (SHAP) analysis to clarify the importance of each feature of the model and its decision basis. Finally, we constructed nomograms to make the predictive model results more readable. Results: The integration of Boruta and LASSO methodologies identified Gender, Smoke, Drink, Chemotherapy cycles, pleural effusion (PE), Neutrophil-lymphocyte count ratio (NLR), Neutrophil-monocyte count ratio (NMR), Lymphocytes (LYM) and Neutrophil (NEUT) as significant predictors. The LR model demonstrated superior performance compared to alternative ML algorithms, achieving an accuracy of 81.80%, a sensitivity of 81.1%, a specificity of 82.5%, an F1 score of 81.6%, and an AUC of 0.888(95%CI(0.863-0.911)). Furthermore, the SHAP method identified Chemotherapy cycles and Smoke as the primary decision factors influencing the ML model's predictions. Finally, this study successfully constructed interactive nomograms and dynamic nomograms. Conclusion: The ML algorithm, combining demographic and clinical factors, accurately predicted post-chemotherapy lung infections in cancer patients. The LR model performed well, potentially improving early detection and treatment in clinical practice.

Non-Coding RNA in Schwann Cell and Peripheral Nerve Injury: A Review.

Peripheral nerve injury (PNI) can result in severe disabilities, profoundly impacting patients' quality of life and potentially endangering their lives. Therefore, understanding the potential molecular mechanisms that facilitate the regeneration of damaged nerves is crucial. Evidence indicates that Schwann cells (SCs) play a pivotal role in repairing peripheral nerve injuries. Previous studies have shown that RNA, particularly non-coding RNA (ncRNA), plays a crucial role in nerve regeneration, including the proliferation and dedifferentiation of SCs. In this review, the individual roles of ncRNA in SCs and PNI are analyzed. This review not only enhances the understanding of ncRNA's role in nerve injury repair but also provides a significant theoretical foundation and inspiration for the development of new therapeutic strategies.

Recent advances in artificial neuromorphic applications based on perovskite composites.

High-performance perovskite materials with excellent physical, electronic, and optical properties play a significant role in artificial neuromorphic devices. However, the development of perovskites in microelectronics is inevitably hindered by their intrinsic non-ideal properties, such as high defect density, environmental sensitivity, and toxicity. By leveraging materials engineering, integrating various materials with perovskites to leverage their mutual strengths presents great potential to enhance ion migration, energy level alignment, photoresponsivity, and surface passivation, thereby advancing optoelectronic and neuromorphic device development. This review initially provides an overview of perovskite materials across different dimensions, highlighting their physical properties and detailing their applications and metrics in two- and three-terminal devices. Subsequently, we comprehensively summarize the application of perovskites in combination with other materials, including organics, nanomaterials, oxides, ferroelectrics, and crystalline porous materials (CPMs), to develop advanced devices such as memristors, transistors, photodetectors, sensors, light-emitting diodes (LEDs), and artificial neuromorphic systems. Lastly, we outline the challenges and future research directions in synthesizing perovskite composites for neuromorphic devices. Through the review and analysis, we aim to broaden the utilization of perovskites and their composites in neuromorphic research, offering new insights and approaches for grasping the intricate physical working mechanisms and functionalities of perovskites.

Exploring the correlation between gut microbiota and benign gastric tumors: A Mendelian randomization study.

Recent scientific research has verified a link between malignant tumors in the stomach and the gut microbiota. This research employed Mendelian randomization (MR) techniques to explore the association between gut microbiota and benign gastric malignancies. The data were derived from genome wide association studies-aggregated data consisting of 211 gut microbes and benign gastric lesions and analyzed by MR. Five statistical tools, including inverse variance weighting, weighted median, MR-Egger, simple mode, and weighted mode, were employed in the statistical analysis. The utilization of the leave-one-out approach served as an effective means of detecting data outliers. Furthermore, implementing Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) and MR-Egger intercepts was employed to mitigate the impact of horizontal pleiotropy. The Cochran Q scores for inverse variance weighting and MR-Egger were utilized to determine the extent of heterogeneity. The findings indicate that the family Porphyromonadaceae (odds ratio [OR] = 2.185, 95% confidence interval [CI]: 1.239-3.855, P = .007), class Bacilli (OR = 1.556, 95%CI: 1.091 - 2.220, P = .015), family Lactobacillaceae (OR = 1.437, 95%CI: 1.049 - 1.969, P = .024), family Oxalobacteraceae (OR = 1.290, 95%CI: 1.035 - 1.608, P = .023) are positively associated with the occurrence of benign gastric tumors. Conversely, the family Pasteurellaceae (OR = 0.752, 95%CI: 0.566 - 0.999, P = .049) and family Peptococcaceae (OR = 0.622, 95%CI: 0.425 - 0.908, P = .014) exhibit a protective effect and significantly decrease the likelihood of benign gastric tumors. The findings of this study suggest that the probability of developing benign gastric tumors is positively associated with the presence of the family Porphyromonadaceae, class Bacilli, family Lactobacillaceae and family Oxalobacteraceae, In contrast, the presence of the family Pasteurellaceae and family Peptococcaceae is negatively associated with this risk. Therefore, regulating gut microbiota may be a potential strategy to reduce the incidence of benign gastric tumors.

Biomedical engineering utilizing living photosynthetic cyanobacteria and microalgae: Current status and future prospects.

Cyanobacteria are the only prokaryotes capable of performing oxygenic photosynthesis on Earth. Besides their traditional roles serving as primary producers, cyanobacteria also synthesize abundant secondary metabolites including carotenoids, alkaloids, peptides, which have been reported to possess medicinal potentials. More importantly, the advancement of synthetic biology technology has further expanded their potential biomedical applications especially using living/engineered cyanobacteria, providing promising and attractive strategies for future disease treatments. To improve the understanding and to facilitate future applications, this review aims to discuss the current status and future prospects of cyanobacterial-based biomedical engineering. Firstly, specific properties of cyanobacteria related with biomedical applications like their natural products of bioactive compounds and heavy metal adsorption were concluded. Subsequently, based on these properties of cyanobacteria, we discussed the progress of their applications in various disease models like hypoxia microenvironment alleviation, wound healing, drug delivery, and so on. Finally, the future prospects including further exploration of cyanobacteria secondary metabolites, the integration of bioactive compounds synthesized by cyanobacteria in situ with medical diagnosis and treatment, and the optimization of in vivo application were critically presented. The review will promote the studies related with cyanobacteria-based biomedical engineering and its practical application in clinical trials in the future.

Large-scale pretrained frame generative model enables real-time low-dose DSA imaging: An AI system development and multi-center validation study.

BACKGROUND: Digital subtraction angiography (DSA) devices are commonly used in numerous interventional procedures across various parts of the body, necessitating multiple scans per procedure, which results in significant radiation exposure for both doctors and patients. Inspired by generative artificial intelligence techniques, this study proposes GenDSA, a large-scale pretrained multi-frame generative model-based real-time and low-dose DSA imaging system. METHODS: GenDSA was developed to generate 1-, 2-, and 3-frame sequences following each real frame. A large-scale dataset comprising ∼3 million DSA images from 27,117 patients across 10 hospitals was constructed to pretrain, fine-tune, and validate GenDSA. Two other datasets from 25 hospitals were used for evaluation. Objective evaluations included SSIM and PSNR. Five interventional radiologists independently assessed the quality of the generated frames using the Likert scale and visual Turing test. Scoring consistency among the radiologists was measured using the Kendall coefficient of concordance (W). The Fleiss' kappa values were used for inter-rater agreement analysis for visual Turing tests. FINDINGS: Using only one-third of the clinical radiation dose, videos generated by GenDSA were perfectly consistent with real videos. Objective evaluations demonstrated that GenDSA's performance (PSNR = 36.83, SSIM = 0.911, generation time = 0.07 s/frame) surpassed state-of-the-art algorithms. Subjective ratings and statistical results from five doctors indicated no significant difference between real and generated videos. Furthermore, the generated videos were comparable to real videos in overall quality (4.905 vs. 4.935) and lesion assessment (4.825 vs. 4.860). CONCLUSIONS: With clear clinical and translational values, the developed GenDSA can significantly reduce radiation damage to both doctors and patients during DSA-guided procedures. FUNDING: This study was supported by the National Key R&D Program and the National Natural Science Foundation of China.

Preparation and characterization of bovine serum albumin/chitosan composite nanoparticles for delivery of Antarctic krill peptide.

BACKGROUND: Antarctic krill peptide (AKP) has gained considerable interest because of its multiple biological functions. However, its application may be limited by its poor stability and susceptibility to degradation. Encapsulation of AKP using a nanoparticle delivery system is an effective way to overcome these problems. In the present study, bovine serum albumin (BSA) and chitosan (CS) were used as delivery vehicles to encapsulate AKP. RESULTS: The results revealed that the particle size (83.3 ± 4.4-222.4 ± 32.7 nm) and zeta-potential (35.1 ± 0.7-45.0 ± 2.7 mV) of nanoparticles (NPs) increased with the increasing content of BSA, but the polydispersity index decreased (1.000 ± 0.002 to 0.306 ± 0.011). Hydrogen bonding, hydrophobic and electrostatic interactions were the main forces to form BSA/CS-AKP NPs. X-ray diffraction revealed that AKP was encapsulated by BSA/CS. Scanning electron microscopy images exhibited that the NPs were spherical in shape, uniform in size and tightly bound. BSA/CS-AKP NPs exhibited excellent stability in the pH range (2-5) and after 15 days of storage, and could hinder the release of AKP in simulated gastric environment and promote the release of AKP in simulated intestinal environment. After simulated digestion, the hypoglycemic activity of encapsulated AKP was better than that of unencapsulated AKP. CONCLUSION: Our results revealed that the BSA/CS showed great potential for protecting and delivering AKP. © 2024 Society of Chemical Industry.

Melatonin prevents bone loss in osteoporotic rats with valproic acid treatment by anti-inflammatory and anti-oxidative stress.

Melatonin (MEL) has shown positive effects in anti-inflammatory and anti-oxidative stress research. This study investigates whether MEL can positively impact bone loss induced by valproic acid (VPA) in rats. The study examines changes in MC3T3-E1 cell viability and osteogenic potential, along with osteoclast differentiation in RAW264.7 cells in the presence of VPA using CCK-8, ALP staining, AR staining, and TRAP staining. In vitro experiments reveal that VPA-induced inhibition of osteogenic differentiation and promotion of osteoclastic differentiation are linked to increased inflammation and oxidative stress. Furthermore, MEL has demonstrated the ability to reduce oxidative stress and inflammation, boost osteogenic differentiation, and inhibit osteoclast differentiation. Animal experiments confirm that MEL significantly increases SOD2 expression and decreases TNF-α expression, leading to the restoration of impaired bone metabolism, enhanced bone strength, and higher bone mineral density. The combined experimental results strongly suggest that MEL can enhance osteogenic activity in the presence of VPA by reducing inflammation and oxidative stress, impeding osteoclast differentiation, and alleviating bone loss in VPA-treated rat models.

Physical function is associated with cognitive status, brain amyloid-beta deposition, and blood biomarkers in Chinese Han population.

BACKGROUND: The physical function of elderly individuals reflects whether they have had a history of regular physical activity over the long term. Such indicators have been found to have a certain connection with cognitive function these years. However, there is limited research that associates it with mechanisms such as cerebral Aß deposition. We aim to investigate this relationship and unveil the underlying mechanisms. METHOD: Physical function and cognition data of 4189 participants were obtained from the Chinese preclinical Alzheimer's disease study. Participants were divided into six groups according to disease severity. Among them, 1048 participants underwent the positron emission tomography-computed tomography (PET-CT) and plasma biomarker test. Grip strength and gait were combined into a score indicating physical function. Multiple linear regression models and logistic regression models were mainly used to conduct the analysis. RESULTS: There was a significant positive correlation between physical function and cognitive function (R = 0.48, p < 0.001), independent of sex, age, apolipoprotein E-ε4 genotype, and disease stages (p < 0.001). Physical function was effective in distinguishing individuals with cognitive impairment from those without (AUC = 0.835). Physical function was negatively associated with brain Aß deposition (p = 0.008) and brain Aß had an intermediary effect (p < 0.01) on the association between physical function and cognition in women. This association was mainly evident in the lateral parietal, lateral temporal, posterior cingulate, frontal, occipital, and precuneus regions. Physical function was negatively associated with plasma neurofilament light-chain (Nfl) level (p < 0.001). CONCLUSIONS: Physical function is strongly associated with cognitive function in the Chinese elderly, and brain Aß deposition partly mediates the linkage in women. Plasma Nfl can be used as a potential target for exercise intervention in cognitive function. Improving physical function will contribute to the alleviation of cognition decline.

GABRG2 mutations in genetic epilepsy with febrile seizures plus: structure, roles, and molecular genetics.

Genetic epilepsy with febrile seizures plus (GEFS+) is a genetic epilepsy syndrome characterized by a marked hereditary tendency inherited as an autosomal dominant trait. Patients with GEFS+ may develop typical febrile seizures (FS), while generalized tonic-clonic seizures (GTCSs) with fever commonly occur between 3 months and 6 years of age, which is generally followed by febrile seizure plus (FS+), with or without absence seizures, focal seizures, or GTCSs. GEFS+ exhibits significant genetic heterogeneity, with polymerase chain reaction, exon sequencing, and single nucleotide polymorphism analyses all showing that the occurrence of GEFS+ is mainly related to mutations in the gamma-aminobutyric acid type A receptor gamma 2 subunit (GABRG2) gene. The most common mutations in GABRG2 are separated in large autosomal dominant families, but their pathogenesis remains unclear. The predominant types of GABRG2 mutations include missense (c.983A → T, c.245G → A, p.Met199Val), nonsense (R136*, Q390*, W429*), frameshift (c.1329delC, p.Val462fs*33, p.Pro59fs*12), point (P83S), and splice site (IVS6+2T → G) mutations. All of these mutations types can reduce the function of ion channels on the cell membrane; however, the degree and mechanism underlying these dysfunctions are different and could be linked to the main mechanism of epilepsy. The γ2 subunit plays a special role in receptor trafficking and is closely related to its structural specificity. This review focused on investigating the relationship between GEFS+ and GABRG2 mutation types in recent years, discussing novel aspects deemed to be great significance for clinically accurate diagnosis, anti-epileptic treatment strategies, and new drug development.

In-stream attenuation and enantioselective fractionation of psychiatric pharmaceuticals in a wastewater effluent-dominated river basin.

Wastewater effluent is the main contributor of psychiatric pharmaceuticals (PPs) pollution in surface waters. However, little is known about its spatial evolution dynamics in effluent-dominated rivers. Herein, 10 representative PPs, including 6 chiral pharmaceuticals and 4 achiral pharmaceuticals, were explored in the Beiyun River, a typical wastewater effluent-dominated river, to explore their occurrence, in-stream attenuation and enantioselective fractionation behaviors at a watershed scale. Among the target substances, 8 and 9 drugs were detected in surface water and sediment samples with the ΣPPs concentrations ranging from 78.4 to 260.1 ng/L and 4.8 to 43.4 ng/g dw in surface water and sediments, respectively. Along the mainstream of the Beiyun River, only several PPs detected in surface water, e.g., citalopram, O-demethylvenlafaxine, and fluoxetine, exhibited in-stream attenuation behaviors when reaching rural area, while all PPs detected in sediments displayed in-stream attenuation behavior. Four chiral PPs detected in surface water exhibited an enantioselective attenuation phenomenon, while in sediments, only citalopram displayed an enantioselective fractionation behavior. The differences in the in-stream attenuation and enantioselective environmental behavior of individual PPs caused complex contaminant evolution along the stream reach. This work provides enantiomeric profiles of chiral pollutants for evaluating their in-stream attenuation processes, which would facilitate better understanding of the changing contaminant exposure conditions in complex natural environments.

Rh(iii)-catalyzed building up of used heterocyclic cations: facile access to white-light-emitting materials.

The first example of rhodium-catalyzed nondirected C-H activation/annulation reactions for the construction of fused heterocyclic cations is reported herein with excellent regioselectivity. Deuterium-labeling experiments indicated that the C(sp3)-H bond cleavage of the N-methyl group might be the rate-limiting step during the reaction process. This protocol provides an opportunity to rapidly access highly π-conjugated fused heterocyclic cations, which opens up a new avenue for efficient screening of single-molecular white-light-emitting materials, pure red-light-emitting materials, and π-conjugated radical materials. Importantly, novel white-light-emitting materials exhibited distinct anti-Kasha dual-emission and could rapidly be fabricated into robust organic and low-cost white light-emitting diodes.

A cross-omics data analysis strategy for metabolite-microbe pair identification.

Given the pivotal roles of metabolomics and microbiomics, numerous data mining approaches aim to uncover their intricate connections. However, the complex many-to-many associations between metabolome-microbiome profiles yield numerous statistically significant but biologically unvalidated candidates. To address these challenges, we introduce BiOFI, a strategic framework for identifying metabolome-microbiome correlation pairs (Bi-Omics). BiOFI employs a comprehensive scoring system, incorporating intergroup differences, effects on feature correlation networks, and organism abundance. Meanwhile, it establishes a built-in database of metabolite-microbe-KEGG functional pathway linking relationships. Furthermore, BiOFI can rank related feature pairs by combining importance scores and correlation strength. Validation on a dataset of cesarean-section infants confirms the strategy's validity and interpretability. The BiOFI R package is freely accessible at https://github.com/chentianlu/BiOFI.

A novel real-time model for predicting acute kidney injury in critically ill patients within 12 hours.

BACKGROUND: A major challenge in prevention and early treatment of acute kidney injury (AKI) is the lack of high-performance predictors in critically ill patients. Therefore, we innovatively constructed U-AKIpredTM for predicting AKI in critically ill patients within 12 h of panel measurement. METHODS: The prospective cohort study included 680 patients in the training set and 249 patients in the validation set. After performing inclusion and exclusion criteria, 417 patients were enrolled in the training set and 164 patients were enrolled in the validation set finally. AKI was diagnosed by Kidney Disease Improving Global Outcomes (KDIGO) criteria. RESULTS: Twelve urinary kidney injury biomarkers (mALB, IgG, TRF, α1MG, NAG, NGAL, KIM-1, L-FABP, TIMP2, IGFBP7, CAF22 and IL-18) exhibited good predictive performance for AKI within 12 h in critically ill patients. U-AKIpredTM, combined with three crucial biomarkers (α1MG, L-FABP and IGFBP7) by multivariate logistic regression analysis, exhibited better predictive performance for AKI in critically ill patients within 12 h than the other twelve kidney injury biomarkers. The area under the curve (AUC) of the U-AKIpredTM, as a predictor of AKI within 12 h, was 0.802 (95% CI: 0.771-0.833, P < 0.001) in the training set and 0.844 (95% CI: 0.792-0.896, P < 0.001) in validation cohort. A nomogram based on the results of the training and validation sets of U-AKIpredTM was developed which showed optimal predictive performance for AKI. The fitting effect and prediction accuracy of U-AKIpredTM was evaluated by multiple statistical indicators. To provide a more flexible predictive tool, the dynamic nomogram (https://www.xsmartanalysis.com/model/U-AKIpredTM) was constructed using a web-calculator. Decision curve analysis (DCA) and a clinical impact curve were used to reveal that U-AKIpredTM with the three crucial biomarkers had a higher net benefit than these twelve kidney injury biomarkers respectively. The net reclassification index (NRI) and integrated discrimination index (IDI) were used to improve the significant risk reclassification of AKI compared with the 12 kidney injury biomarkers. The predictive efficiency of U-AKIpredTM was better than the NephroCheck® when testing for AKI and severe AKI. CONCLUSION: U-AKIpredTM is an excellent predictive model of AKI in critically ill patients within 12 h and would assist clinicians in identifying those at high risk of AKI.

Alcoholic Liver Disease in China: A Disease Influenced by Complex Social Factors That Should Not Be Neglected.

Alcoholic liver disease (ALD) encompasses liver damage caused by chronic, excessive alcohol consumption. It manifests initially as marked hepatocellular steatosis and can progress to steatohepatitis, liver fibrosis, and cirrhosis. With China's rapid economic growth, coupled with a complex social background and the influence of a deleterious wine culture, the number of patients with ALD in China has increased significantly; the disease has become a social and health problem that cannot be ignored. In this review, we briefly described the social factors affecting ALD in China and elaborated on differences between alcoholic and other liver diseases in terms of complications (e.g., cirrhosis, upper gastrointestinal bleeding, hepatic encephalopathy, hepatocellular carcinoma, addiction, and other extrahepatic diseases). We also emphasized that ALD was more dangerous and difficult to treat than other liver diseases due to its complications, and that precise and effective treatment measures were lacking. In addition, we considered new ideas and treatment methods that may be generated in the future.

Ink-based additive manufacturing for electrochemical applications.

Additive manufacturing (AM), commonly known as three-dimensional (3D) printing, has drawn substantial attention in recent decades due to its efficiency and precise control in part fabrication. The limitations of conventional fabrication processes, especially regarding geometry complexity, supply chain, and environmental impact, have prompted the exploration of diverse AM technologies in electrochemistry. Especially, three ink-based AM techniques, binder jet printing (BJP), direct ink writing (DIW), and Inkjet Printing (IJP), have been extensively applied by numerous research teams to produce electrodes, catalyst scaffolds, supercapacitors, batteries, etc. BJP's versatility in utilizing a wide range of materials as powder feedstock promotes its potential for various electrode and battery applications. DIW and IJP stand out for their ability to handle multi-material manufacturing tasks and deliver high printing resolution. To capture recent advancements in this field, we present a comprehensive review of the applications of BJP, DIW, and IJP techniques in fabricating electrochemical devices and components. This review intends to provide an overview of the process-structure-property relationship in electrochemical materials and components across diverse applications manufactured using AM techniques. We delve into how the significantly improved design freedom over the structure offered by these ink-based AM techniques highlights the performance of electrochemical products. Moreover, we highlight their advantages in terms of material compatibility, geometry control, and cost-effectiveness. In specific cases, we also compare the performance of electrochemical components fabricated using AM and conventional manufacturing methods. Finally, we conclude this review article by offering some insights into the future development in this research field.

RHOF activation of AKT/ß-catenin signaling pathway drives acute myeloid leukemia progression and chemotherapy resistance.

Acute myeloid leukemia (AML) is a clonal malignancy originating from leukemia stem cells, characterized by a poor prognosis, underscoring the necessity for novel therapeutic targets and treatment methodologies. This study focuses on Ras homolog family member F, filopodia associated (RHOF), a Rho guanosine triphosphatase (GTPase) family member. We found that RHOF is overexpressed in AML, correlating with an adverse prognosis. Our gain- and loss-of-function experiments revealed that RHOF overexpression enhances proliferation and impedes apoptosis in AML cells in vitro. Conversely, genetic suppression of RHOF markedly reduced the leukemia burden in a human AML xenograft mouse model. Furthermore, we investigated the synergistic effect of RHOF downregulation and chemotherapy, demonstrating significant therapeutic efficacy in vivo. Mechanistically, RHOF activates the AKT/ß-catenin signaling pathway, thereby accelerating the progression of AML. Our findings elucidate the pivotal role of RHOF in AML pathogenesis and propose RHOF inhibition as a promising therapeutic approach for AML management.