Network pharmacology screening, in vitro and in vivo evaluation of antianxiety and antidepressant drug-food analogue.

BACKGROUND: Depression and anxiety disorders are prevalent psychiatric conditions, and currently utilized chemical drugs typically come with significant adverse effects. China boasts a wealth of medicinal and food herbs known for their safe and effective properties. PURPOSE: This study aimed to develop novel formulations with improved antidepressant and anxiolytic effects derived from medicinal and food herbs. STUDY DESIGN: Screening combinations with antidepressant and anxiolytic effects using techniques such as network pharmacology and validating their effects in vitro and in vivo experiments. METHODS: Utilizing network pharmacology and molecular docking, we identified the top ten medicinal herbs with anxiolytic and antidepressant potential. Herbs with cytoprotective effects and non-toxic characteristics were further screened to formulate the herbal blends. Subsequently, we established a PC12 cell injury model and a chronic unpredictable mild stress (CUMS) model in mice to assess the effects of our formulations. RESULTS: Ten medicinal herbs were initially screened, and six of them were deemed suitable for formulating the blend, namely Gancao, Dazao, Gouqizi, Sangye, Huangqi, and Jinyinhua (GDGSHJ). The GDGSHJ formulation reduced Lactate Dehydrogenase (LDH) leakage, decreased apoptosis, and demonstrated a favorable antidepressant and antianxiety effect in the CUMS mouse model. Besides, GDGSHJ led to the upregulation of serum 5-Hydroxytryptamine (5-HT) content and brain tissue 5-HT, Gamma-aminobutyric acid (GABA), and Dopamine (DA) levels. It also downregulated the expression of SLC6A4 and SLC6A3 genes in the mouse hippocampus while upregulating HTR1A, DRD1, DRD2, and GABRA1 genes. CONCLUSION: Our formulation exhibited robust antidepressant and antianxiety effects without inducing substantial toxicity. This efficacy appears to be mediated by the expression of relevant genes within the hippocampus of mice. The formulation achieved this effect by balancing 5-HT levels in the serum and DA, GABA, and 5-HT levels within brain tissue.

Predicting the performance of lithium adsorption and recovery from unconventional water sources with machine learning.

Selective lithium (Li) recovery from unconventional water sources (UWS) (e.g., shale gas waters, geothermal brines, and rejected seawater desalination brines) using inorganic lithium-ion sieve (LIS) materials can address Li supply shortages and distribution issues. However, the development of high-performance LIS materials and the optimization of recovery-related operating parameters are hampered by the variety of production methods, intricate procedures, and experimental expenses. Machine learning (ML) techniques offer potential solutions for enhancing LIS material development. We collected literature data on Li adsorption, categorizing 16 parameters into adsorbent parameters, operating parameters, and solution components. Three tree-based algorithms-Random Forest (RF), Gradient Boosting Decision Trees (GBDT), and Extreme Gradient Boosting (XGBoost)-were used to evaluate the impact of these parameters on lithium adsorption. The grouped random splitting method limited data leakage and mitigated overfitting. XGBoost demonstrated the best performance, with an R² of 0.98 and a root-mean-squared error (RMSE) of 1.72. The SHAP values highlighted that operating parameters were the most influential, followed by adsorbent parameters and coexisting ion concentrations. Therefore, focusing on optimizing operating parameters or making targeted improvements on LIS based on operating conditions will enhance LIS performances in UWS. These insights are crucial for optimizing Li adsorption processes and designing effective inorganic LIS materials.

Cytochrome P450 F3 promotes colorectal cancer via inhibiting NRF2-mediated ferroptosis.

Cytochrome P450 F3 (CYP4F3) is recognized as a disease-associated immune response initiator that is involved in the synthesis of cholesterol, steroids, and lipids. This study identified the upregulation of CYP4F3 expression in colorectal cancer (CRC) and its association with poor patient prognosis through a comparative analysis between CRC tumor tissues with normal tissues from public databases. The overexpression of CYP4F3 in CT26.wt and SW620, promoted cell proliferation and migration, a reduction of cellular oxidative stress, an up-regulation of the oxidative stress-related pathway NRF2, and an inhibition of cellular ferroptosis. Additionally, inhibition of NRF2 activity stimulated cellular ferroptosis when CYP4F3 was overexpressed. Ferroptosis, characterized by iron-dependent lipid peroxidation, is a non-apoptotic way of cell death with a critical role in cancer development. When given a ferroptosis agonist to CYP4F3-overexpression CRC cells, NRF2 was activated, and cell proliferation and migration were reduced. Furthermore, the mice subcutaneously injected with CYP4F3-overexpression CT26.wt cells formed significantly larger tumors compared to the CYP4F3-vector CT26.wt cell group. This study systematically identified an important role of CYP4F3 in CRC development as a regulator of CRC cells to escape ferroptosis via NRF2, highlighting the significance of CYP4F3 as a potential therapeutic target for CRC.

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 microcrystalline cellulose from rice bran.

BACKGROUND: Rice bran, a by-product of rice processing, has not been fully utilized except for the small amount used for raising animals. The raw material source requirements of microcrystalline cellulose are becoming increasingly extensive. However, the characteristics of preparing microcrystalline cellulose from rice bran have not been reported, which limits the application of rice bran. RESULTS: Microcrystalline cellulose was obtained from rice bran by alkali treatment, delignification, bleaching and acid hydrolysis. The morphology, particle size distribution, degree of polymerization, crystallinity, and thermal stability of rice bran microcrystalline cellulose were analyzed. The chemical compositions, scanning electron microscopy and Fourier-transform infrared analysis for rice bran microcrystalline cellulose showed that the lignin and hemicellulose were successfully removed from the rice bran fiber matrix. The morphology of rice bran microcrystalline cellulose was shown to be of a short rod-shaped porous structure with an average diameter of 65.3 µm. The polymerization degree of rice bran microcrystalline cellulose was 150. The X-ray diffraction pattern of rice bran microcrystalline cellulose showed the characteristic peak of natural cellulose (type I), and its crystallization index was 71%. The rice bran microcrystalline cellulose may be used in biological composites with temperatures between 150 °C and 250 °C. CONCLUSION: These results suggest the feasibility of using rice bran as a low-price source of microcrystalline cellulose. © 2024 Society of Chemical Industry.

ROS-Induced Autophagy of Skeletal Muscle Confers Resistance of Rice Flower Carp (Cyprinus carpio) to Short-Term Fasting.

Starvation is one of the main stresses for fish due to food shortage, the evasion of predators, and intraspecific competition. This research evaluated the impact of brief fasting periods on reactive oxygen species (ROS) levels, antioxidant response, mRNA expression of antioxidants, autophagy-related signaling genes, and autophagosome development in the muscle tissue of rice flower carp. Following a three-day fasting period, the levels of ROS and MDA rose. Additionally, after 3 d of fasting, there was a notable upregulation of NRF2 and significant increases in the levels of GSH and the activities of enzymes such as SOD, CAT, GST, GR, and GPX, while the expression of the autophagy marker gene LC3B did not change (p < 0.05). After 7 d of fasting, the content of the ROS, the activity of SOD and GR, and the GSH content reached the maximum (p < 0.05). Concurrently, there was a significant rise in the quantity of autophagosomes. An RT-qPCR analysis revealed that seven d of starvation significantly elevated the mRNA expression of genes associated with the initiation and expansion of autophagosome membranes, vesicle recycling, and cargo recruitment, including ULK1, BECLIN1, LC3B, ATG3, ATG4B, ATG4C, ATG5, ATG9, and P62. After feeding resumed for 3 d, the mRNA level of BECLIN1, ATG3, ATG4B, ATG4C, ATG5, LC3B, and P62 still remained at a high level. The LC3II protein reached its highest level. All autophagy-related gene expression decreased in the 7-day resumed feeding group. Our data implied that short-term fasting can cause oxidative stress and disrupt the antioxidant system first and then induce autophagy in the muscles of rice flower carp. These findings shed light on how fasting affects muscle homeostasis in fish. ROS-induced autophagy of the skeletal muscle may confer the resistance of rice flower carp to short-term fasting.

Assessing the suitability of video-assisted anal fistula treatment for obese patients compared to conventional surgery: a question worth investigating.

BACKGROUND AND AIMS: Video-assisted anal fistula treatment (VAAFT) is an innovative surgical approach enabling the direct visualization of the fistula tract structure. This study aims to assess the efficacy of VAAFT in comparison with that of traditional surgical methods and explore potential risk factors contributing to fistula recurrence to provide new recommendations for surgical selection. MATERIALS AND METHODS: Information was collected from 100 patients with complex anal fistula (CAF) in our hospital who underwent surgical treatment from January 2021 to January 2023. We compared the baseline information and surgical outcomes of two groups, analyzed the risk factors for fistula recurrence by using logistic regression analysis, and conducted further exploration by using the body mass index. RESULTS: Equal numbers of patients underwent VAAFT and traditional surgeries, and no significant differences in baseline information were observed. Patients who received VAAFT experienced less intraoperative bleeding (15.5 (14.0-20.0) vs. 32.0 (25.0-36.0)), shorter hospital stays (2.0 (2.0-2.5) vs. 3.0 (3.0-3.5)), reduced postoperative pain and wound discharge, but longer operative times (43.3 ± 6.9 vs. 35.0 (31.5-40.0)) compared with patients who underwent traditional surgeries. No significant differences in recurrence rates were found three and six months after operation (the p-values were 0.790 and 0.806, respectively). However, the Wexner scores of the VAAFT group were significantly low in the first follow-up (0 (0-1.0) vs. 2.0 (1.0-2.0)). Postoperative recurrence of fistulas may be associated with obesity (p-value = 0.040), especially in patients undergoing traditional surgeries (p-value = 0.036). CONCLUSION: VAAFT offers advantages, such as less pain, less trauma, and faster recovery, compared with traditional surgical treatment. Obese patients with CAF are prone to recurrence, and we recommend that they undergo VAAFT treatment rather than traditional surgeries.

Hidden flaws behind expert-level accuracy of multimodal GPT-4 vision in medicine.

Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily focused on the accuracy of multi-choice questions alone. Our study extends the current scope by conducting a comprehensive analysis of GPT-4V's rationales of image comprehension, recall of medical knowledge, and step-by-step multimodal reasoning when solving New England Journal of Medicine (NEJM) Image Challenges-an imaging quiz designed to test the knowledge and diagnostic capabilities of medical professionals. Evaluation results confirmed that GPT-4V performs comparatively to human physicians regarding multi-choice accuracy (81.6% vs. 77.8%). GPT-4V also performs well in cases where physicians incorrectly answer, with over 78% accuracy. However, we discovered that GPT-4V frequently presents flawed rationales in cases where it makes the correct final choices (35.5%), most prominent in image comprehension (27.2%). Regardless of GPT-4V's high accuracy in multi-choice questions, our findings emphasize the necessity for further in-depth evaluations of its rationales before integrating such multimodal AI models into clinical workflows.

Crosstalk between CD8+ T cells and mesenchymal stromal cells in intestine homeostasis and immunity.

The intestine represents the most complex cellular network in the whole body. It is constantly faced with multiple types of immunostimulatory agents encompassing from food antigen, gut microbiome, metabolic waste products, and dead cell debris. Within the intestine, most T cells are found in three primary compartments: the organized gut-associated lymphoid tissue, the lamina propria, and the epithelium. The well-orchestrated epithelial-immune-microbial interaction is critically important for the precise immune response. The main role of intestinal mesenchymal stromal cells is to support a structural framework within the gut wall. However, recent evidence from stromal cell studies indicates that they also possess significant immunomodulatory functions, such as maintaining intestinal tolerance via the expression of PDL1/2 and MHC-II molecules, and promoting the development of CD103+ dendritic cells, and IgA+ plasma cells, thereby enhancing intestinal homeostasis. In this review, we will summarize the current understanding of CD8+ T cells and stromal cells alongside the intestinal tract and discuss the reciprocal interactions between T subsets and mesenchymal stromal cell populations. We will focus on how the tissue residency, migration, and function of CD8+ T cells could be potentially regulated by mesenchymal stromal cell populations and explore the molecular mediators, such as TGF-ß, IL-33, and MHC-II molecules that might influence these processes. Finally, we discuss the potential pathophysiological impact of such interaction in intestine hemostasis as well as diseases of inflammation, infection, and malignancies.

Targeting nanoplatform synergistic glutathione depletion-enhanced chemodynamic, microwave dynamic, and selective-microwave thermal to treat lung cancer bone metastasis.

Once bone metastasis occurs in lung cancer, the efficiency of treatment can be greatly reduced. Current mainstream treatments are focused on inhibiting cancer cell growth and preventing bone destruction. Microwave ablation (MWA) has been used to treat bone tumors. However, MWA may damage the surrounding normal tissues. Therefore, it could be beneficial to develop a nanocarrier combined with microwave to treat bone metastasis. Herein, a microwave-responsive nanoplatform (MgFe2O4@ZOL) was constructed. MgFe2O4@ZOL NPs release the cargos of Fe3+, Mg2+ and zoledronic acid (ZOL) in the acidic tumor microenvironment (TME). Fe3+ can deplete intracellular glutathione (GSH) and catalyze H2O2 to generate •OH, resulting in chemodynamic therapy (CDT). In addition, the microwave can significantly enhance the production of reactive oxygen species (ROS), thereby enabling the effective implementation of microwave dynamic therapy (MDT). Moreover, Mg2+ and ZOL promote osteoblast differentiation. In addition, MgFe2O4@ZOL NPs could target and selectively heat tumor tissue and enhance the effect of microwave thermal therapy (MTT). Both in vitro and in vivo experiments revealed that synergistic targeting, GSH depletion-enhanced CDT, MDT, and selective MTT exhibited significant antitumor efficacy and bone repair. This multimodal combination therapy provides a promising strategy for the treatment of bone metastasis in lung cancer patients.

Establishment of a neutrophil extracellular trap-related prognostic signature for colorectal cancer liver metastasis and expression validation of CYP4F3.

Liver metastasis stands as the primary contributor to mortality among patients diagnosed with colorectal cancer (CRC). Neutrophil extracellular traps (NETs) emerge as pivotal players in the progression and metastasis of cancer, showcasing promise as prognostic biomarkers. Our objective is to formulate a predictive model grounded in genes associated with neutrophil extracellular traps and identify novel therapeutic targets for combating CRLM. We sourced gene expression profiles from the Gene Expression Omnibus (GEO) database. Neutrophil extracellular trap-related gene set was obtained from relevant literature and cross-referenced with the GEO datasets. Differentially expressed genes (DEGs) were identified through screening via the least absolute shrinkage and selection operator regression and random forest modeling, leading to the establishment of a nomogram and subtype analysis. Subsequently, a thorough analysis of the characteristic gene CYP4F3 was undertaken, and our findings were corroborated through immunohistochemical staining. We identified seven DEGs (ATG7, CTSG, CYP4F3, F3, IL1B, PDE4B, and TNF) and established nomograms for the occurrence and prognosis of CRLM. CYP4F3 is highly expressed in CRC and colorectal liver metastasis (CRLM), exhibiting a negative correlation with CRLM prognosis. It may serve as a potential therapeutic target for CRLM. A novel prognostic signature related to NETs has been developed, with CYP4F3 identified as a risk factor and potential target for CRLM.

Dual-loss of PBRM1 and RAD51 identifies hyper-sensitive subset patients to immunotherapy in clear cell renal cell carcinoma.

BACKGROUND: Homologous recombination deficiency (HRD), though largely uncharacterized in clear cell renal cell carcinoma (ccRCC), was found associated with RAD51 loss of expression. PBRM1 is the second most common mutated genes in ccRCC. Here, we introduce a HRD function-based PBRM1-RAD51 ccRCC classification endowed with diverse immune checkpoint blockade (ICB) responses. METHODS: Totally 1542 patients from four independent cohorts were enrolled, including our localized Zhongshan hospital (ZSHS) cohort and Zhongshan hospital metastatic RCC (ZSHS-mRCC) cohort, The Cancer Genome Atlas (TCGA) cohort and CheckMate cohort. The genomic profile and immune microenvironment were depicted by genomic, transcriptome data and immunohistochemistry. RESULTS: We observed that PBRM1-loss ccRCC harbored enriched HRD-associated mutational signature 3 and loss of RAD51. Dual-loss of PBRM1 and RAD51 identified patients hyper-sensitive to immunotherapy. This dual-loss subtype was featured by M1 macrophage infiltration. Dual-loss was, albeit homologous recombination defective, with high chromosomal stability. CONCLUSIONS: PBRM1 and RAD51 dual-loss ccRCC indicates superior responses to immunotherapy. Dual-loss ccRCC harbors an immune-desert microenvironment but enriched with M1 macrophages. Dual-loss ccRCC is susceptible to defective homologous recombination but possesses high chromosomal stability.

Developmental stage and infection status may affect drug distribution in the prostate of rats.

Prostate inflammation is often treated with drugs which are ineffective. Antibacterial agents fail to reach the prostate epithelium, and the blood-prostate barrier (BPB) may affect the drug transport process. Factors affecting drug efficacy remain unclear.Rats were categorised into groups A and B, corresponding to adulthood and puberty, respectively. Group C included the model of chronic prostate infection. Dialysates of levofloxacin and cefradine were collected from the prostate gland and jugular vein and evaluated. Pharmacokinetic analysis was conducted.The free concentrations of antimicrobials in the prostate and plasma samples of all groups peaked at 20 min, then gradually decreased. The mean AUC0-tprostate/AUC0-tplasma ratio in the levofloxacin group were 0.86, 0.53, and 0.95, and the mean values of AUC0-∞prostate/AUC0-∞plasma ratio were 0.85, 0.63, and 0.97. The corresponding values in the cefradine group were 0.67, 0.30 and 0.84, and 0.66, 0.31, and 0.85, respectively. The mean values in group B were lower than those in group A, and those in group C were higher than those in group B.The maturity of the prostate may affect the ability of the drug to cross the BPB. Infection may disrupt the BPB, affecting drug permeability.

3D printing sequentially strengthening high-strength natural polymer hydrogel bilayer scaffold for cornea regeneration.

3D printing of high-strength natural polymer biodegradable hydrogel scaffolds simultaneously resembling the biomechanics of corneal tissue and facilitating tissue regeneration remains a huge challenge due to the inherent brittleness of natural polymer hydrogels and the demanding requirements of printing. Herein, concentrated aqueous solutions of gelatin and carbohydrazide-modified alginate (Gel/Alg-CDH) are blended to form a natural polymer hydrogel ink, where the hydrazides in Alg-CDH are found to form strong hydrogen bonds with the gelatin. The hydrogen-bonding-strengthened Gel/Alg-CDH hydrogel demonstrates an appropriate thickened viscosity and shear thinning for extrusion printing. The strong hydrogen bonds contribute to remarkably increased mechanical properties of Gel/Alg-CDH hydrogel with a maximum elongation of over 400%. In addition, sequentially Ca2+-physical crosslinking and then moderately chemical crosslinking significantly enhance the mechanical properties of Gel/Alg-CDH hydrogels that ultimately exhibit an intriguing J-shaped stress-strain curve (tensile strength of 1.068 MPa and the toughness of 677.6 kJ/m2). The dually crosslinked Gel-Alg-CDH-Ca2+-EDC hydrogels demonstrate a high transparency, physiological swelling stability and rapid enzymatic degradability, as well as suturability. The growth factor and drug-loaded biomimetic bilayer hydrogel scaffold are customized via a multi-nozzle printing system. This bioactive bilayer hydrogel scaffold considerably promotes regeneration of corneal epithelium and stroma and inhibits cornea scarring in rabbit cornea keratoplasty.

A High-Density Hydrogen Bond Locking Strategy for Constructing Anisotropic High-Strength Hydrogel-Based Meniscus Substitute.

Mimicking anisotropic features is crucial for developing artificial load-bearing soft tissues such as menisci). Here, a high-density hydrogen bond locking (HDHBL) strategy, involving preloading a poly(N-acryloylsemicarbazide) (PNASC) hydrogel with an aqueous solution containing a hydrogen bond breaking agent, followed by water exchange, to fabricate anisotropic high-strength hydrogels are proposed. During this process, multiple high-density hydrogen bonds of the PNASC network are re-established, firmly freezing oriented molecular chains, and creating a network with an anisotropic microstructure. The resulting anisotropic hydrogels exhibit superior mechanical properties: tensile strength over 9 MPa, Young's modulus exceeding 120 MPa along the orientation direction, and fatigue thresholds exceeding 1900 J m-2. These properties meet the mechanical demands for load-bearing tissue substitutes compared to other reported anti-fatigue hydrogels. This strategy enables the construction of an anisotropic meniscal scaffold composed of circumferentially oriented microfibers by preloading a digital light processing-3D printed PNASC hydrogel-based wedge-shaped construct with a resilient poly(N-acryloyl glycinamide) hydrogel. The 12-week implantation of a meniscus scaffold in rabbit knee joints after meniscectomy demonstrates a chondroprotective effect on the femoral condyle and tibial plateau, substantially ameliorating the progression of osteoarthritis. The HDHBL strategy enables the fabrication of various anisotropic polymer hydrogels, broadening their scope of application.

PTransIPs: Identification of Phosphorylation Sites Enhanced by Protein PLM Embeddings.

Phosphorylation is pivotal in numerous fundamental cellular processes and plays a significant role in the onset and progression of various diseases. The accurate identification of these phosphorylation sites is crucial for unraveling the molecular mechanisms within cells and during viral infections, potentially leading to the discovery of novel therapeutic targets. In this study, we develop PTransIPs, a new deep learning framework for the identification of phosphorylation sites. Independent testing results demonstrate that PTransIPs outperforms existing state-of-the-art (SOTA) methods, achieving AUCs of 0.9232 and 0.9660 for the identification of phosphorylated S/T and Y sites, respectively. PTransIPs contributes from three aspects. 1) PTransIPs is the first to apply protein pre-trained language model (PLM) embeddings to this task. It utilizes ProtTrans and EMBER2 to extract sequence and structure embeddings, respectively, as additional inputs into the model, effectively addressing issues of dataset size and overfitting, thus enhancing model performance; 2) PTransIPs is based on Transformer architecture, optimized through the integration of convolutional neural networks and TIM loss function, providing practical insights for model design and training; 3) The encoding of amino acids in PTransIPs enables it to serve as a universal framework for other peptide bioactivity tasks, with its excellent performance shown in extended experiments of this paper.

4D printed hydrogel scaffold with swelling-stiffening properties and programmable deformation for minimally invasive implantation.

The power of three-dimensional printing in designing personalized scaffolds with precise dimensions and properties is well-known. However, minimally invasive implantation of complex scaffolds is still challenging. Here, we develop amphiphilic dynamic thermoset polyurethanes catering for multi-material four-dimensional printing to fabricate supportive scaffolds with body temperature-triggered shape memory and water-triggered programmable deformation. Shape memory effect enables the two-dimensional printed pattern to be fixed into temporary one-dimensional shape, facilitating transcatheter delivery. Upon implantation, the body temperature triggers shape recovery of the one-dimensional shape to its original two-dimensional pattern. After swelling, the hydrated pattern undergoes programmable morphing into the desired three-dimensional structure because of swelling mismatch. The structure exhibits unusual soft-to-stiff transition due to the water-driven microphase separation formed between hydrophilic and hydrophobic chain segments. The integration of shape memory, programmable deformability, and swelling-stiffening properties makes the developed dynamic thermoset polyurethanes promising supportive void-filling scaffold materials for minimally invasive implantation.

Wet environment-induced adhesion and softening of coenzyme-based polymer elastic patch for treating periodontitis.

Periodontitis, a common chronic inflammatory disease caused by pathogenic bacteria, can be treated with diverse biomaterials by loading drugs, cytokines or proteins. However, these biomaterials often show unsatisfactory therapeutic efficiency due to their poor adhesion, short residence time in the wet and dynamic oral cavity and emerging drug resistance. Here we report a wet-responsive methacrylated gelatin (GelMA)-stabilized co-enzyme polymer poly(α-lipoic acid) (PolyLA)-based elastic patch with water-induced adhesion and softening features. In PolyLA-GelMA, the multiple covalent and hydrogen-bonding crosslinking between PolyLA and GelMA prevent PolyLA depolymerization and slow down the dissociation of PolyLA in water, allowing durable adhesion to oral periodontal tissue and continuous release of LA-based bioactive small molecule in periodontitis wound without resorting external drugs. Compared with the undifferentiated adhesion behavior of traditional adhesives, this wet-responsive patch demonstrates a favorable periodontal pocket insertion ability due to its non-adhesion and rigidity in dry environment. In vitro studies reveal that PolyLA-GelMA patch exhibits satisfactory wet tissue adhesion, antibacterial, blood compatibility and ROS scavenging abilities. In the model of rat periodontitis, the PolyLA-GelMA patch inhibits alveolar bone resorption and accelerates the periodontitis healing by regulating the inflammatory microenvironment. This biomacromolecule-stabilized coenzyme polymer patch provides a new option to promote periodontitis treatment.

Hidden Flaws Behind Expert-Level Accuracy of Multimodal GPT-4 Vision in Medicine.

Recent studies indicate that Generative Pre-trained Transformer 4 with Vision (GPT-4V) outperforms human physicians in medical challenge tasks. However, these evaluations primarily focused on the accuracy of multi-choice questions alone. Our study extends the current scope by conducting a comprehensive analysis of GPT-4V's rationales of image comprehension, recall of medical knowledge, and step-by-step multimodal reasoning when solving New England Journal of Medicine (NEJM) Image Challenges - an imaging quiz designed to test the knowledge and diagnostic capabilities of medical professionals. Evaluation results confirmed that GPT-4V performs comparatively to human physicians regarding multi-choice accuracy (81.6% vs. 77.8%). GPT-4V also performs well in cases where physicians incorrectly answer, with over 78% accuracy. However, we discovered that GPT-4V frequently presents flawed rationales in cases where it makes the correct final choices (35.5%), most prominent in image comprehension (27.2%). Regardless of GPT-4V's high accuracy in multi-choice questions, our findings emphasize the necessity for further in-depth evaluations of its rationales before integrating such multimodal AI models into clinical workflows.