In-situ amino-functionalized and reduced graphene oxide/polyimide composite films for high-performance triboelectric nanogenerator.

As a promising sustainable power source in intelligent electronics, Triboelectric Nanogenerators (TENGs) have garnered widespread interest, with various strategies explored to enhance their output performance. However, most optimization methods for triboelectric materials have focused solely on tuning chemical compositions or fabricating surface microstructures. Here, we have prepared amino-functionalized reduced graphene oxide (FRGO)/polyimide (PI) composite films (PI-FRGO) via in-situ polymerization, aimed at enhancing PI materials' nanotribological power generation performance. By varying the doping levels of amino groups and controlling the FRGO proportion during synthesis, we can explore the optimal FRGO/PI composite film ratio. At a p-Phenylenediamine: reduced Graphene Oxide (PPDA: RGO) ratio of 1:1 and an FRGO addition of 0.1 %, the output electrical performance peaks with a voltage of 58 V, a charge of 33 nC and a current of 12 µA, nearly 2 times that of a pure PI film. We have fabricated a TENG with an optimally formulated PI-FRGO composite to explore its application potential. Under a 10 MΩ external load resistance, the TENG can deliver a power density of 3.5 mW/m2 and can be powering small devices. This work presents new effective strategies to significantly enhance TENG output performance and promote their widespread application.

Lattice-Confined Single-Atom Catalyst: Preparation, Application and Electron Regulation Mechanism.

Lattice-confined single-atom catalyst (LC SAC), featuring exceptional activity, intriguing stability and prominent selectivity, has attracted extensive attention in the fields of various reactions (e.g., hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), etc.). To design a "smart" LC SAC for catalytic applications, one must systematically comprehend updated advances in the preparation, the application, and especially the peculiar electron regulation mechanism of LC SAC. In this review, the specific preparation methods of LC SAC based on general coordination strategy are updated, and its applications in HER, OER, ORR, N2 reduction reaction (NRR), advanced oxidation processes (AOPs) and so forth are summarized to display outstanding activity, stability and selectivity. Uniquely, the electron regulation mechanisms are first and deeply discussed and can be primarily categorized as electron transfer bridge with monometallic active sites, novel catalytic centers with polymetallic active sites, and positive influence by surrounding environments. In the end, the existing issues and future development directions are put forward with a view to further optimize the performance of LC SAC. This review is expected to contribute to the in-depth understanding and practical application of highly efficient LC SAC.

Inducible biosynthesis of bacterial cellulose in recombinant Enterobacter sp. FY-07.

Bacterial cellulose (BC) is an extracellular polysaccharide with myriad unique properties, such as high purity, water-holding capacity and biocompatibility, making it attractive in materials science. However, genetic engineering techniques for BC-producing microorganisms are rare. Herein, the electroporation-based gene transformation and the λ Red-mediated gene knockout method with a nearly 100 % recombination efficiency were established in the fast-growing and BC hyperproducer Enterobacter sp. FY-07. This genetic manipulation toolkit was validated by inactivating the protein subunit BcsA in the cellulose synthase complex. Subsequently, the inducible BC-producing strains from glycerol were constructed through inducible expression of the key gene fbp in the gluconeogenesis pathway, which recovered >80 % of the BC production. Finally, the BC properties analysis results indicated that the induced-synthesized BC pellicles were looser, more porous and reduced crystallinity, which could further broaden the application prospects of BC. To our best knowledge, this is the first attempt to construct the completely inducible BC-producing strains. Our work paves the way for increasing BC productivity by metabolic engineering and broadens the available fabrication methods for BC-based advanced functional materials.

MRI-based axis-referenced morphometric model corresponding to lamellar organization for assessing hippocampal atrophy in dementia.

Research on the local hippocampal atrophy for early detection of dementia has gained considerable attention. However, accurately quantifying subtle atrophy remains challenging in existing morphological methods due to the lack of consistent biological correspondence with the complex curving regions like the hippocampal head. Thereby, this article presents an innovative axis-referenced morphometric model (ARMM) that follows the anatomical lamellar organization of the hippocampus, which capture its precise and consistent longitudinal curving trajectory. Specifically, we establish an "axis-referenced coordinate system" based on a 7 T ex vivo hippocampal atlas following its entire curving longitudinal axis and orthogonal distributed lamellae. We then align individual hippocampi by deforming this template coordinate system to target spaces using boundary-guided diffeomorphic transformation, while ensuring that the lamellar vectors adhere to the constraint of medial-axis geometry. Finally, we measure local thickness and curvatures based on the coordinate system and boundary surface reconstructed from vector tips. The morphometric accuracy is evaluated by comparing reconstructed surfaces with those directly extracted from 7 T and 3 T MRI hippocampi. The results demonstrate that ARMM achieves the best performance, particularly in the curving head, surpassing the state-of-the-art morphological models. Additionally, morphological measurements from ARMM exhibit higher discriminatory power in distinguishing early Alzheimer's disease from mild cognitive impairment compared to volume-based measurements. Overall, the ARMM offers a precise morphometric assessment of hippocampal morphology on MR images, and sheds light on discovering potential image markers for neurodegeneration associated with hippocampal impairment.

Dewatering performance of aerobic granular sludge under centrifugal with different sludge conditioning agent.

The aerobic granular sludge(AGS) technology draw scientific researchers attention, and more and more scientific research focuses on it, due to its superior advantages, such as good settling performance, high biological phase, high toxicity resistance and multiple biological effects. With the rapid development of AGS technology, a considerable amount of residual AGS will be produced, and dehydration is the biggest bottleneck of sludge reduction. This study investigated the dewatering process and method of residual AGS cultured by continuous flow experiment. Experiments were conducted using centrifugal dewatering technology with a dosing scheme to analyze the granular sludge dewatering process, and investigate the release process of EPS component in AGS dewatering. Our results implied the specific resistance of AGS has a very low value ((1.82 ± 0.03) × 109 m/kg) and it was not obvious for the conditioning effect of chemical conditioner on AGS dewatering. However, the moisture content can be reduced to 63.5% after dewatering with the presence of inorganic substances. The addition of drinking water treatment plant sludge (Alum sludge) can improve the efficiency of the dewatering of AGS. A possible dewatering process of AGS dewatering was proposed which was divided into two stages: First, a considerable amount of free water in the sludge was quickly removed under the action of gravity without pressure filtration. Second, the bound water release required cooperation between applying centrifugal or pressing force to grind granular cells and separate protein-like substances with the inorganic matter inside the granular sludge. The possible mechanism of AGS dewatering and hypothesis dewatering process are useful to optimize the AGS dewatering process.

Recent Progress in Brain Network Models for Medical Applications: A Review.

Importance: Pathological perturbations of the brain often spread via connectome to fundamentally alter functional consequences. By integrating multimodal neuroimaging data with mathematical neural mass modeling, brain network models (BNMs) enable to quantitatively characterize aberrant network dynamics underlying multiple neurological and psychiatric disorders. We delved into the advancements of BNM-based medical applications, discussed the prevalent challenges within this field, and provided possible solutions and future directions. Highlights: This paper reviewed the theoretical foundations and current medical applications of computational BNMs. Composed of neural mass models, the BNM framework allows to investigate large-scale brain dynamics behind brain diseases by linking the simulated functional signals to the empirical neurophysiological data, and has shown promise in exploring neuropathological mechanisms, elucidating therapeutic effects, and predicting disease outcome. Despite that several limitations existed, one promising trend of this research field is to precisely guide clinical neuromodulation treatment based on individual BNM simulation. Conclusion: BNM carries the potential to help understand the mechanism underlying how neuropathology affects brain network dynamics, further contributing to decision-making in clinical diagnosis and treatment. Several constraints must be addressed and surmounted to pave the way for its utilization in the clinic.

Research on the mechanism of Guanyu Zhixie Granule in intervening gastric ulcers in rats based on network pharmacology and multi-omics.

Objective: Guanyu Zhixie Granule (GYZXG) is a traditional Chinese medicine compound with definite efficacy in intervening in gastric ulcers (GUs). However, the effect mechanisms on GU are still unclear. This study aimed to explore its mechanism against GU based on amalgamated strategies. Methods: The comprehensive chemical characterization of the active compounds of GYZXG was conducted using UHPLC-Q/TOF-MS. Based on these results, key targets and action mechanisms were predicted through network pharmacology. GU was then induced in rats using anhydrous ethanol (1 mL/200 g). The intervention effects of GYZXG on GU were evaluated by measuring the inhibition rate of GU, conducting HE staining, and assessing the levels of IL-6, TNF-α, IL-10, IL-4, Pepsin (PP), and epidermal growth factor (EGF). Real-time quantitative PCR (RT-qPCR) was used to verify the mRNA levels of key targets and pathways. Metabolomics, combined with 16S rRNA sequencing, was used to investigate and confirm the action mechanism of GYZXG on GU. The correlation analysis between differential gut microbiota and differential metabolites was conducted using the spearman method. Results: For the first time, the results showed that nine active ingredients and sixteen targets were confirmed to intervene in GU when using GYZXG. Compared with the model group, GYZXG was found to increase the ulcer inhibition rate in the GYZXG-M group (p < 0.05), reduce the levels of IL-6, TNF-α, PP in gastric tissue, and increase the levels of IL-10, IL-4, and EGF. GYZXG could intervene in GU by regulating serum metabolites such as Glycocholic acid, Epinephrine, Ascorbic acid, and Linoleic acid, and by influencing bile secretion, the HIF-1 signaling pathway, and adipocyte catabolism. Additionally, GYZXG could intervene in GU by altering the gut microbiota diversity and modulating the relative abundance of Bacteroidetes, Bacteroides, Verrucomicrobia, Akkermansia, and Ruminococcus. The differential gut microbiota was strongly associated with serum differential metabolites. KEGG enrichment analysis indicated a significant role of the HIF-1 signaling pathway in GYZXG's intervention on GU. The changes in metabolites within metabolic pathways and the alterations in RELA, HIF1A, and EGF mRNA levels in RT-qPCR experiments provide further confirmation of this result. Conclusion: GYZXG can intervene in GU induced by anhydrous ethanol in rats by regulating gut microbiota and metabolic disorders, providing a theoretical basis for its use in GU intervention.

Comprehensive toxicological, metabolomic, and transcriptomic analysis of the biodegradation and adaptation mechanism by Achromobacter xylosoxidans SL-6 to diuron.

Biodegradation was considered a promising and environmentally friendly method for treating environmental pollution caused by diuron. However, the mechanisms of biodegradation of diuron required further research. In this study, the degradation process of diuron by Achromobacter xylosoxidans SL-6 was systematically investigated. The results suggested that the antioxidant system of strain SL-6 was activated by adding diuron, thereby alleviating their oxidative stress response. In addition, degradation product analysis showed that diuron in strain SL-6 was mainly degraded by urea bridge cleavage, dehalogenation, deamination, and ring opening, and finally cis, cis-muconic acid was generated. The combined analysis of metabolomics and transcriptomics revealed the biodegradation and adaptation mechanism of strain SL-6 to diuron. Metabolomics analysis showed that after the strain SL-6 was exposed to diuron, metabolic pathways such as tricarboxylic acid cycle (cis, cis-muconic acid), glutathione metabolism (oxidized glutathione), and urea cycle (arginine) were reprogrammed in the cells. Furthermore, diuron could induce the production of membrane transport proteins in strain SL-6 cells and overexpress antioxidant enzyme genes, finally ultimately promoting the up-regulation of genes encoding amide hydrolases and dioxygenases, which was revealed by transcriptomics studies. This work enriched the biodegradation mechanism of phenylurea herbicides and provided guidance for the removal of diuron residues in the environment and promoting agriculture sustainable development.

Promotion of apoptosis in melanoma cells by taxifolin through the PI3K/AKT signaling pathway: Screening of natural products using WGCNA and CMAP platforms.

Melanoma is a skin cancer originating from melanocytes. The global incidence rate of melanoma is rapidly increasing, posing significant public health challenges. Identifying effective therapeutic agents is crucial in addressing this growing problem. Natural products have demonstrated promising anti-tumor activity. In this study, a plant flavonoid, taxifolin, was screened using Weighted Correlation Network Analysis (WGCNA) in combination with the Connectivity Map (CMAP) platform. Taxifolin was confirmed to inhibit the proliferation, migration, and invasion ability of melanoma A375 and MV-3 cells by promoting apoptosis. Additionally, it suppressed the Epithelial-Mesenchymal Transition (EMT) process of melanoma cells. Cyber pharmacological analysis revealed that taxifolin exerts its inhibitory effect on melanoma through the PI3K/AKT signaling pathway, specifically by downregulating the protein expression of p-PI3K and p-AKT. Notably, the addition of SC-79, an activator of the PI3K/AKT signaling pathway, reversed the effects of taxifolin on cell migration and apoptosis. Furthermore, in vivo experiments demonstrated that taxifolin treatment slowed tumor growth in mice without significant toxic effects. Based on these findings, taxifolin holds promise as a potential drug for melanoma treatment.

BrainMass: Advancing Brain Network Analysis for Diagnosis with Large-scale Self-Supervised Learning.

Foundation models pretrained on large-scale datasets via self-supervised learning demonstrate exceptional versatility across various tasks. Due to the heterogeneity and hard-to-collect medical data, this approach is especially beneficial for medical image analysis and neuroscience research, as it streamlines broad downstream tasks without the need for numerous costly annotations. However, there has been limited investigation into brain network foundation models, limiting their adaptability and generalizability for broad neuroscience studies. In this study, we aim to bridge this gap. In particular, (1) we curated a comprehensive dataset by collating images from 30 datasets, which comprises 70,781 samples of 46,686 participants. Moreover, we introduce pseudo-functional connectivity (pFC) to further generates millions of augmented brain networks by randomly dropping certain timepoints of the BOLD signal. (2) We propose the BrainMass framework for brain network self-supervised learning via mask modeling and feature alignment. BrainMass employs Mask-ROI Modeling (MRM) to bolster intra-network dependencies and regional specificity. Furthermore, Latent Representation Alignment (LRA) module is utilized to regularize augmented brain networks of the same participant with similar topological properties to yield similar latent representations by aligning their latent embeddings. Extensive experiments on eight internal tasks and seven external brain disorder diagnosis tasks show BrainMass's superior performance, highlighting its significant generalizability and adaptability. Nonetheless, BrainMass demonstrates powerful few/zero-shot learning abilities and exhibits meaningful interpretation to various diseases, showcasing its potential use for clinical applications.

Changes in PI3K/AKT and NRF2/HO-1 signaling expression and intestinal microbiota in bleomycin-induced pulmonary fibrosis.

Pulmonary fibrosis is the outcome of the prolonged interstitial pneumonia, characterized by excessive accumulation of fibroblasts and collagen deposition, leading to its development. This study aimed to study the changes in PI3K/AKT and NRF2/HO-1 signaling expression and intestinal microbiota in a rat model of a novel bleomycin-induced pulmonary fibrosis. The findings of our study showed the model was successfully established. The results showed that the alveolar septum in the model was significantly widened and infiltrated by severe inflammatory cells. Alveolar atrophy occurred due to the formation of multiple inflammatory foci. During this period, fibrous tissue was distributed in strips and patches, primarily around the pulmonary interstitium and bronchus. Moreover, lung damage and fibrosis progressively worsened over time. The mRNA expression of HO-1 and NRF2 in the model decreased while the mRNA expression of HIF-1α, VEGF, PI3K and AKT increased. Furthermore, it was observed to decrease the protein expression of E-cad, HO-1 and NRF2, and increase the protein expression of α-SMA and p-AKT. Additionally, this model leaded to an imbalance in the intestinal microbiota. This study demonstrate that the novel pulmonary fibrosis model activates the NRF2/HO-1 pathway and the PI3K/AKT pathway in rat lung tissues, and leading to intestinal barrier disorder.

Classification and characterization of facial asymmetry in adult patients with skeletal Class III malocclusion using cluster analysis.

INTRODUCTION: This study aimed to analyze the comprehensive maxillofacial features of patients with skeletal Class III malocclusion and facial asymmetry to develop a classification system for diagnosis and surgical planning. METHODS: A total of 161 adult patients were included, with 121 patients in the asymmetry group (menton deviation >2 mm) and 40 patients in the symmetry group (menton deviation ≤2 mm). Twenty-eight variables were determined, including transverse translation, roll and yaw of each facial unit, transverse width, mandibular morphology, and transverse dental compensation. Principal component (PC) analysis was conducted to extract PCs, and cluster analysis was performed using these components to classify the asymmetry group. A decision tree was constructed on the basis of the clustering results. RESULTS: Six PCs were extracted, explaining 80.622% of the data variability. The asymmetry group was classified into 4 subgroups: (1) atypical type (15.7%) showed an opposite roll direction of maxillary dentition than of menton deviation; (2) compound type (34.71%) demonstrated significant ramus height differences, maxillary roll, and mandibular roll and yaw; (3) mandibular yaw type (44.63%) showed slight mandibular yaw without mandibular morphology asymmetry; and (4) maxillary-shift type (4.96%) shared similarities with the compound type but showed significant maxillary translation. The classification and regression tree model achieved a prediction accuracy of up to 85.11%. CONCLUSIONS: This study identified 4 distinct phenotypes using cluster analysis and proposed tailored treatment recommendations on the basis of their specific characteristics. The classification results emphasized the importance of spatial displacement features, especially mandibular yaw, in diagnosing facial asymmetry. The established classification and regression tree model enables clinicians to identify patients conveniently.

Lenvatinib in combination with transarterial chemoembolization vs. sorafenib in combination with transarterial chemoembolization for unresectable hepatocellular carcinoma: A network meta­analysis.

The use of tyrosine kinase inhibitors combined with transarterial chemoembolization (TACE) is considered the standard therapy for patients with unresectable hepatocellular carcinoma (uHCC). However, information regarding the efficacy of lenvatinib or sorafenib in combination with TACE for patients with uHCC is limited. The present study involved a systematic search for randomized controlled trials on the PubMed, Embase, Web of Science and the Cochrane Library online databases to compare the use of TACE combined with either lenvatinib or sorafenib, and monotherapy using either lenvatinib or sorafenib for patients with uHCC. The network meta-analysis of the present study included eight randomized controlled trials involving 2,929 patients. The random-effects model was used, and hazard ratios and risk ratios with 95% CIs were calculated. Lenvatinib in combination with TACE provided the maximal overall survival (97.92%), progression-free survival (87.8%), objective response (96.68%) and disease control (96.27%) rates. The results of the present study indicated that, in the treatment of patients with uHCC, lenvatinib in combination with TACE showed a significantly improved efficacy when compared with sorafenib and TACE. Therefore, in the future, combination therapy of lenvatinib with TACE could be potentially prioritized over sorafenib with TACE for the treatment of patients with uHCC.

The expanding role of radiation oncology across the prostate cancer continuum.

Radiotherapy is used in the treatment of prostate cancer in a variety of disease states with significant reliance on imaging to guide clinical decision-making and radiation delivery. In the definitive setting, the choice of radiotherapy treatment modality, dose, and fractionation for localized prostate cancer is determined by the patient's initial risk stratification and other clinical considerations. Radiation is also an option as salvage therapy in patients with locoregionally recurrent disease after prior definitive radiation or surgery. In recent years, the role of radiation has expanded for patients with metastatic disease, including prostate-directed radiotherapy in de novo low volume metastatic disease, metastasis-directed therapy for oligorecurrent disease, and palliative management of symptomatic metastases in the advanced setting. Here we review the expanding role of radiation in the treatment of prostate cancer in the definitive, locoregionally recurrent, and metastatic settings, as well as highlight the role of imaging in clinical reasoning, radiation planning, and treatment delivery.

Pushing, standing and bringing to light: How medical trainees conceptualise professional resistance.

BACKGROUND: Much of the literature on harm and injustice in medical education focuses on the impact of oppression rather than trainees' efforts to create change. To acknowledge and make visible these efforts, medical education professionals must grasp how trainees perceive resistance and their role in effecting change. Employing functional linguistic and 'everyday' resistance theories, this critical qualitative study aims to understand trainees' conceptions of resistance practices and their representational choices in moments when they talked about and conceptualised resistance. METHODS: Gathering participants through professional networks and snowball sampling, this study employed in-depth interviews to explore the conceptualisations of resistance among North American medical trainees (9 medical students, 9 residents and fellows). With the use of an applied functional linguistic analysis framework, we analysed the representational metafunction in trainees' conceptualisation of their resistance efforts against social injustice. We began with open coding for 'everyday' acts of resistance and then shifted to focused coding on verbal process types in participants' language to characterise their conceptualisations of resistance. FINDINGS: Participants conceptualised their resistance practices in three distinct ways: first, an almost physical pushing back, drawing largely on material process types (doing); second, an embodied standing up and being present, based predominantly on material and relational process types (being); and third, an epistemic bringing to light, grounded mostly in mental and verbal process types (thinking). These processes of resistance reflect participants' conceptualisations of their efforts to challenge the status quo around inequity, harm and injustice in medical education. CONCLUSION: This study builds on resistance literature, offering a potential typology of resistance practices as pushing back, being and bringing to light. Because these are 'everyday' acts of resistance, these are tactics available to everyone, including faculty; we all have the power to resist, whether it is in teaching and learning or interacting with larger structures in medicine.

Experience of undergraduate nursing students participating in artificial intelligence + project task driven learning at different stages: a qualitative study.

BACKGROUND: Artificial intelligence is a growing phenomenon that will soon facilitate wide-scale changes in many professions, and is expected to play an important role in the field of medical education. This study explored the realistic feelings and experiences of nursing undergraduates participating in different stages of artificial intelligence + project task driven learning, and provide a basis for artificial intelligence participation in nursing teaching. METHODS: We conducted face-to-face semi-structured interviews with nursing undergraduates participating in Nursing Research Course which adopts artificial intelligence + project task driven learning from a medical university in Ningxia from September to November 2023, to understand their experience of using artificial intelligence for learning and the emotional changes at different stages. The interview guide included items about their personal experience and feelings of completing project tasks through dialogue with artificial intelligence, and suggestions for course content. Thematic analysis was used to analyze interview data. This study followed the COREQ checklist. RESULTS: According to the interview data, three themes were summarized. Undergraduate nursing students have different experiences in participating in artificial intelligence + project task driven learning at different stages, mainly manifested as diverse emotional experiences under initial knowledge deficiency, the individual growth supported by external forces during the adaptation period, and the expectations and suggestions after the birth of the results in the end period. CONCLUSIONS: Nursing undergraduates can actively adapt to the integration of artificial intelligence into nursing teaching, dynamically observe students' learning experience, strengthen positive guidance, and provide support for personalized teaching models, better leveraging the advantages of artificial intelligence participation in teaching.

Geodesic shape regression based deep learning segmentation for assessing longitudinal hippocampal atrophy in dementia progression.

Longitudinal hippocampal atrophy is commonly used as progressive marker assisting clinical diagnose of dementia. However, precise quantification of the atrophy is limited by longitudinal segmentation errors resulting from MRI artifacts across multiple independent scans. To accurately segment the hippocampal morphology from longitudinal 3T T1-weighted MR images, we propose a diffeomorphic geodesic guided deep learning method called the GeoLongSeg to mitigate the longitudinal variabilities that unrelated to diseases by enhancing intra-individual morphological consistency. Specifically, we integrate geodesic shape regression, an evolutional model that estimates smooth deformation process of anatomical shapes, into a two-stage segmentation network. We adopt a 3D U-Net in the first-stage network with an enhanced attention mechanism for independent segmentation. Then, a hippocampal shape evolutional trajectory is estimated by geodesic shape regression and fed into the second network to refine the independent segmentation. We verify that GeoLongSeg outperforms other four state-of-the-art segmentation pipelines in longitudinal morphological consistency evaluated by test-retest reliability, variance ratio and atrophy trajectories. When assessing hippocampal atrophy in longitudinal data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), results based on GeoLongSeg exhibit spatial and temporal local atrophy in bilateral hippocampi of dementia patients. These features derived from GeoLongSeg segmentation exhibit the greatest discriminatory capability compared to the outcomes of other methods in distinguishing between patients and normal controls. Overall, GeoLongSeg provides an accurate and efficient segmentation network for extracting hippocampal morphology from longitudinal MR images, which assist precise atrophy measurement of the hippocampus in early stage of dementia.

Recyclable Organic Radical Electrodes for Metal-Free Batteries.

Organic batteries are one of the possible routes for transitioning to sustainable energy storage solutions. However, the recycling of organic batteries, which is a key step toward circularity, is not easily achieved. This work shows the direct recycling of poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl) (PTMA) and poly(2,2,6,6-tetramethylpiperidinyloxy-4-yl acrylamide) (PTAm) based composite electrodes. After charge-discharge cycling, the electrodes are deconstructed using a solubilizing-solvent and then reconstructed using a casting-solvent. The electrochemical properties of the original and recycled electrodes are compared using cyclic voltammetry (CV) and galvanostatic charge-discharge (GCD) cycling, from which it is discovered using time-of-flight secondary ion mass spectrometry (ToF-SIMS) that recycling can be challenged by the formation of a cathode electrolyte interphase (CEI). In turn, an additive is proposed to modify the CEI layer and improve the properties after recycling. Last, an anionic rocking chair battery consisting of PTAm electrodes as both positive and negative electrodes is demonstrated, in which the electrodes are recycled to form a new battery. This work demonstrates the recycling of composite electrodes for organic batteries and provides insights into the challenges and possible solutions for recycling the next-generation electrochemical energy storage devices.

Orientin alleviates the inflammatory response in psoriasis like dermatitis in BALB/c mice by inhibiting the MAPK signaling pathway.

BACKGROUND: Psoriasis, a chronic inflammatory condition of the skin, is characterized by an atypical proliferation of epidermal keratinocytes and immune cell infiltration. Orientin is a flavonoid monomer with potent anti-inflammatory activities. However, the therapeutic effects of orientin on psoriasis and the underlying mechanisms have not been elucidated. OBJECTIVE: To investigate the therapeutic effect of orientin on psoriasis and the underlying mechanisms using network pharmacology and experimental studies. METHODS: A psoriasis-like mouse model was established using imiquimod (IMQ). Lipopolysaccharide (LPS) was used to stimulate the RAW264.7 and HaCaT cells in vitro. The therapeutic effects of orientin and the underlying mechanism were analyzed using histopathological, immunohistochemical, quantitative real-time polymerase chain reaction, enzyme-linked immunosorbent assay, flow cytometry, and western blotting analyses. RESULTS: Orientin ameliorated skin lesions and suppressed keratinocyte proliferation and immune cell infiltration in the IMQ-induced psoriasis-like mouse model. Additionally, orientin inhibited the secretion of the pro-inflammatory factors interleukin (IL)-1ß, tumor necrosis factor (TNF)-α, IL-6, IL-8, IL-17, and IL-23 in the psoriasis-like mouse model and LPS-induced RAW264.7 and HaCaT cells. Furthermore, orientin mitigated the LPS-induced upregulation of reactive oxygen species and downregulation of IL-10 and glutathione levels. Orientin alleviated inflammation by downregulating the MAPK signaling pathway. CONCLUSION: Orientin alleviated psoriasis-like dermatitis by suppressing the MAPK signaling pathway, suggesting that orientin is a potential therapeutic for psoriasis.

Case report: Decreased hemoglobin and multiple organ failure caused by ceftizoxime-induced immune hemolytic anemia in a Chinese patient with malignant rectal cancer.

Background: Drug-induced immune hemolytic anemia (DIIHA) is a rare but serious condition, with an estimated incidence of one in 100,000 cases, associated with various antibiotics. This study reports on a case of ceftizoxime-induced hemolysis observed in a patient in China. Case description: A Chinese patient diagnosed with malignant rectal cancer underwent antimicrobial therapy after laparoscopic partial recto-sigmoid resection (L-Dixon). After receiving four doses of ceftizoxime, the patient developed symptoms including rash, itchy skin, and chest distress, followed by a rapid decline in hemoglobin levels, the presence of hemoglobin in the urine (hemoglobinuria), renal failure, and disseminated intravascular coagulation. Laboratory analysis revealed high-titer antibodies against ceftizoxime and red blood cells (RBCs) in the patient's serum, including immunoglobulin M (IgM) (1:128) antibodies and immunoglobulin G (IgG) (1:8) antibodies, with noted crossreactivity to ceftriaxone. Significant improvement in the patient's hemolytic symptoms was observed following immediate discontinuation of the drug, two plasma exchanges, and extensive RBC transfusion. Conclusion: This case, together with previous reports, underscores the importance of considering DIIHA in patients who exhibit unexplained decreases in hemoglobin levels following antibiotic therapy. A thorough examination of the patient's medical history can provide crucial insights for diagnosing DIIHA. The effective management of DIIHA includes immediate cessation of the implicated drug, plasma exchange, and transfusion support based on the identification of specific drug-dependent antibodies through serological testing.