Unveiling the Hidden Impact: Hematoma Volumes Unravel Circuit Disruptions in Intracerebral Hemorrhage.

Intracerebral hemorrhage (ICH) imposes a significant burden on patients, and the volume of hematoma plays a crucial role in determining the severity and prognosis of ICH. Although significant recent progress has been made in understanding the cellular and molecular mechanisms of surrounding brain tissue in ICH, our current knowledge regarding the precise impact of hematoma volumes on neural circuit damage remains limited. Here, using a viral tracing technique in a mouse model of striatum ICH, two distinct patterns of injury response were observed in upstream connectivity, characterized by both linear and nonlinear trends in specific brain areas. Notably, even low-volume hematomas had a substantial impact on downstream connectivity. Neurons in the striatum-ICH region exhibited heightened excitability, evidenced by electrophysiological measurements and changes in metabolic markers. Furthermore, a strong linear relationship (R2 = 0.91) was observed between hematoma volumes and NFL damage, suggesting a novel biochemical index for evaluating changes in neural injury. RNA sequencing analysis revealed the activation of the MAPK signaling pathway following hematoma, and the addition of MAPK inhibitor revealed a decrease in neuronal circuit damage, leading to alleviation of motor dysfunction in mice. Taken together, our study highlights the crucial role of hematoma size as a determinant of circuit injury in ICH. These findings have important implications for clinical evaluations and treatment strategies, offering opportunities for precise therapeutic approaches to mitigate the detrimental effects of ICH and improve patient outcomes.

Human brain organoid: trends, evolution, and remaining challenges.

Advanced brain organoids provide promising platforms for deciphering the cellular and molecular processes of human neural development and diseases. Although various studies and reviews have described developments and advancements in brain organoids, few studies have comprehensively summarized and analyzed the global trends in this area of neuroscience. To identify and further facilitate the development of cerebral organoids, we utilized bibliometrics and visualization methods to analyze the global trends and evolution of brain organoids in the last 10 years. First, annual publications, countries/regions, organizations, journals, authors, co-citations, and keywords relating to brain organoids were identified. The hotspots in this field were also systematically identified. Subsequently, current applications for brain organoids in neuroscience, including human neural development, neural disorders, infectious diseases, regenerative medicine, drug discovery, and toxicity assessment studies, are comprehensively discussed. Towards that end, several considerations regarding the current challenges in brain organoid research and future strategies to advance neuroscience will be presented to further promote their application in neurological research.

Engineered keratin/bFGF hydrogel to promote diabetic wound healing in rats.

Keratin materials are promising in wound healing acceleration, however, it is a challenge for the keratin to efficiently therapy the impaired wound healing, such as diabetic foot ulcers. Here, we report a keratin/bFGF hydrogel for skin repair of chronic wounds in diabetic rats based on their characteristics of extracellular matrix and growth factor degradation in diabetic ulcer. Recombinant keratin 31 (K31), the most abundant keratin in human hair, exhibited the highly efficient performances in cell adhesion, proliferation and migration. More importantly, the introduction of bFGF into K31 hydrogel significantly enhances the properties of cell proliferation, wound closure acceleration, angiogenesis and skin appendages regeneration. Furthermore, the combination of K31 and bFGF can promote epithelial-mesenchymal transition by inhibiting the expression of E-cadherin and promoting the expression of vimentin and fibronectin. These findings demonstrate the engineered K31/bFGF hydrogel as a promising therapeutic agent for diabetic wound healing.

Engineering the Physical Microenvironment into Neural Organoids for Neurogenesis and Neurodevelopment.

Understanding the signals from the physical microenvironment is critical for deciphering the processes of neurogenesis and neurodevelopment. The discovery of how surrounding physical signals shape human developing neurons is hindered by the bottleneck of conventional cell culture and animal models. Notwithstanding neural organoids provide a promising platform for recapitulating human neurogenesis and neurodevelopment, building neuronal physical microenvironment that accurately mimics the native neurophysical features is largely ignored in current organoid technologies. Here, it is discussed how the physical microenvironment modulates critical events during the periods of neurogenesis and neurodevelopment, such as neural stem cell fates, neural tube closure, neuronal migration, axonal guidance, optic cup formation, and cortical folding. Although animal models are widely used to investigate the impacts of physical factors on neurodevelopment and neuropathy, the important roles of human stem cell-derived neural organoids in this field are particularly highlighted. Considering the great promise of human organoids, building neural organoid microenvironments with mechanical forces, electrophysiological microsystems, and light manipulation will help to fully understand the physical cues in neurodevelopmental processes. Neural organoids combined with cutting-edge techniques, such as advanced atomic force microscopes, microrobots, and structural color biomaterials might promote the development of neural organoid-based research and neuroscience.

Smart Physical-Based Transdermal Drug Delivery System:Towards Intelligence and Controlled Release.

Transdermal drug delivery systems based on physical principles have provided a stable, efficient, and safe strategy for disease therapy. However, the intelligent device with real-time control and precise drug release is required to enhance treatment efficacy and improve patient compliance. This review summarizes the recent developments, application scenarios, and drug release characteristics of smart transdermal drug delivery systems fabricated with physical principle. Special attention is paid to the progress of intelligent design and concepts in of physical-based transdermal drug delivery technologies for real-time monitoring and precise drug release. In addition, facing with the needs of clinical treatment and personalized medicine, the recent progress and trend of physical enhancement are further highlighted for transdermal drug delivery systems in combination with pharmaceutical dosage forms to achieve better transdermal effects and facilitate the development of smart medical devices. Finally, the next generation and future application scenarios of smart physical-based transdermal drug delivery systems are discussed, a particular focus in vaccine delivery and tumor treatment.

Photopolymerized keratin-PGLa hydrogels for antibiotic resistance reversal and enhancement of infectious wound healing.

Infectious wounds have become serious challenges for both treatment and management in clinical practice, so development of new antibiotics has been considered an increasingly difficult task. Here, we report the design and synthesis of keratin 31 (K31)-peptide glycine-leucine-amide (PGLa) photopolymerized hydrogels to rescue the antibiotic activity of antibiotics for infectious wound healing promotion. K31-PGLa displayed an outstanding synergistic effect with commercial antibiotics against drug-resistant bacteria by down-regulating the synthesis genes of efflux pump. Furthermore, the photopolymerized K31-PGLa/PEGDA hydrogels effectively suppressed drug-resistant bacteria growth and enhanced skin wound closure in murine. This study provided a promising alternative strategy for infectious wound treatment.

Role of mass effect on neuronal iron deposition after intracerebral hemorrhage.

Mass effect after intracerebral hemorrhage (ICH) not only mechanically induces the brain damage, but also influences the progress of secondary brain damage. However, the influence of mass effect on the iron overload after ICH is still unclear. Here, a fixed volume of ferrous chloride solution and different volumes of poly(N-isopropylacrylamide) (PNIPAM) hydrogel were co-injected into the right basal ganglia of rats to establish the ICH model with certain degree of iron deposition but different degrees of mass effect. We found that mass effect significantly increased the iron deposition on neuronal cells at 6 h after ICH in a volume-dependent manner. Furthermore, the upregulation of Piezo-2, divalent metal transporter 1 (DMT1), transferrin receptor (TfR), and ferroptosis expressions were noted as the increase of mass effect. In addition, the pERK1/2 inhibitor PD98059 treated ICH rats reversed the upregulation of iron uptake protein and ferroptosis. Our findings revealed the relationship between mass effect and the iron uptake and ferroptosis, which are benefit to understand the brain damage process after ICH.

Reverse-QTY code design of active human serum albumin self-assembled amphiphilic nanoparticles for effective anti-tumor drug doxorubicin release in mice.

Human serum albumin (HSA) is a highly water-soluble protein with 67% alpha-helix content and three distinct domains (I, II, and III). HSA offers a great promise in drug delivery with enhanced permeability and retention effect. But it is hindered by protein denaturation during drug entrapment or conjugation that result in distinct cellular transport pathways and reduction of biological activities. Here we report using a protein design approach named reverse-QTY (rQTY) code to convert specific hydrophilic alpha-helices to hydrophobic to alpha-helices. The designed HSA undergo self-assembly of well-ordered nanoparticles with highly biological actives. The hydrophilic amino acids, asparagine (N), glutamine (Q), threonine (T), and tyrosine (Y) in the helical B-subdomains of HSA were systematically replaced by hydrophobic leucine (L), valine (V), and phenylalanine (F). HSArQTY nanoparticles exhibited efficient cellular internalization through the cell membrane albumin binding protein GP60, or SPARC (secreted protein, acidic and rich in cysteine)-mediated pathways. The designed HSArQTY variants displayed superior biological activities including: i) encapsulation of drug doxorubicin, ii) receptor-mediated cellular transport, iii) tumor cell targeting, and iv) antitumor efficiency compare to denatured HSA nanoparticles. HSArQTY nanoparticles provided superior tumor targeting and antitumor therapeutic effects compared to the albumin nanoparticles fabricated by antisolvent precipitation method. We believe that the rQTY code is a robust platform for specific hydrophobic modification of functional hydrophilic proteins with clear-defined binding interfaces.

In vitro and in vivo Evaluation of Folic Acid Modified DOX-Loaded 32P-nHA Nanoparticles in Prostate Cancer Therapy.

Background: Prostate cancer (PCa) ranks second in the incidence of all malignancies in male worldwide. The presence of multi-organ metastases and tumor heterogeneity often leads to unsatisfactory outcomes of conventional radiotherapy treatments. This study aimed to develop a novel folate-targeted nanohydroxyapatite (nHA) coupling to deliver adriamycin (Doxorubicin, DOX), 32P, and 99mTc simultaneously for the diagnosis and treatment of prostate-specific membrane antigen (PSMA) positive prostate cancer. Methods: The spherical nHA was prepared by the biomimetic method and characterized. Folic acid (FA) was coupled to nHA with polyethylene glycol (PEG), and the grafting ratio of PEG-nHA and FA-PEG-nHA was determined by the thermogravimetric analysis (TGA) method. In addition, 32P, 99mTc, and DOX were loaded on nHA by physisorption. And the labeling rate and stability of radionuclides were measured by a γ-counter. The loading and release of DOX at different pH were determined by the dialysis method. Targeting of FA-PEG-nHA loaded with 99mTc was verified by in vivo SPECT imaging. In vitro anti-tumor effect of 32P/DOX-FA-PEG-nHA was assessed with apoptosis assay. The safety of the nano-drugs was verified by histopathological analysis. Results: The SEM images showed that the synthesized nHA was spherical with uniform particle size (average diameter of about 100nm). The grafting ratio is about 10% for PEG and about 20% for FA. The drug loading and the delayed release of DOX at different pH confirmed its long-term therapeutic ability. The labeling of 32P and 99mTc was stable and the labeling rate was great. SPECT showed that FA-PEG-nHA showed well in vivo tumor targeting and less damage to normal tissues. Conclusion: FA-targeted nHA loaded with 32P, 99mTc, and DOX may be a new diagnostic and therapeutic strategy for targeting PSMA-positive prostate cancer tumors, which may achieve better therapeutic results while circumventing the severe toxic side effects of conventional chemotherapeutic agents.

A survival nomogram model constructed with common clinical characteristics to assist clinical decisions for diffuse low-grade gliomas: A population analysis based on SEER database.

Background: The prognosis of diffuse low-grade gliomas (DLGGs, WHO grade 2) is highly variable, making it difficult to evaluate individual patient outcomes. In this study, we used common clinical characteristics to construct a predictive model with multiple indicators. Methods: We identified 2459 patients diagnosed with astrocytoma and oligodendroglioma from 2000 to 2018 in the SEER database. After removing invalid information, we randomly divided the cleaned patient data into training and validation groups. We performed univariate and multivariate Cox regression analyses and constructed a nomogram. Receiver operating characteristic (ROC) curve, c-index, calibration curve, and subgroup analyses were used to assess the accuracy of the nomogram by internal and external validation. Results: After univariate and multivariate Cox regression analyses, we identified seven independent prognostic factors, namely, age (P<0.001), sex (P<0.05), histological type (P<0.001), surgery (P<0.01), radiotherapy (P<0.001), chemotherapy (P<0.05) and tumor size (P<0.001). The ROC curve, c-index, calibration curve, and subgroup analyses of the training group and the validation group showed that the model had good predictive value. The nomogram for DLGGs predicted patients' 3-, 5- and 10-year survival rates based on these seven variables. Conclusions: The nomogram constructed with common clinical characteristics has good prognostic value for patients with DLGGs and can help physicians make clinical decisions.

Scatter correction for cone-beam CT via scatter kernel superposition-inspired convolutional neural network.

Objective.X-ray scatter leads to signal bias and degrades the image quality in Computed Tomography imaging. Conventional real-time scatter estimation and correction methods include the scatter kernel superposition (SKS) methods, which approximate x-ray scatter field as a convolution of the scatter sources and scatter propagation kernels to reflect the spatial spreading of scatter x-ray photons. SKS methods are fast to implement but generally suffer from low accuracy due to the difficulties in determining the scatter kernels.Approach.To address such a problem, this work describes a new scatter estimation and correction method by combining the concept of SKS methods and convolutional neural network. Unlike conventional SKS methods which estimate the scatter amplitude and the scatter kernel based on the value of an individual pixel, the proposed method generates the scatter amplitude maps and the scatter width maps from projection images through a neural network, from which the final estimated scatter field is calculated based on a convolution process.Main Results.By incorporating physics in the network design, the proposed method requires fewer trainable parameters compared with another deep learning-based method (Deep Scatter Estimation). Both numerical simulations and physical experiments demonstrate that the proposed SKS-inspired convolutional neural network outperforms the conventional SKS method and other deep learning-based methods in both qualitative and quantitative aspects.Significance.The proposed method can effectively correct the scatter-related artifacts with a SKS-inspired convolutional neural network design.

Design and evaluation of 32P-labeled hydroxyapatite nanoparticles for bone tumor therapy.

The clinical diagnosis and treatment of malignant bone tumors are still major clinical challenges due to their high incidence are difficulty. Targeted therapies have become a critical approach to treat bone tumors. In recent years, radiopharmaceuticals have been used widely and have shown potent and efficient results in treating bone tumors, among which 32P and the labeled radiopharmaceuticals play an essential role. In this study, the 32P-labeled hydroxyapatite (HA) was prepared through chemical synthesis (32P-Hap) and physical adsorption (32P-doped-Hap). The in vitro stability of 32P-labeled HA was analyzed to assess the superiority of the new-found chemical synthesis. The radiolabeling yield and stability of chemical synthesis (97.6 ± 0.5%) were significantly improved compared with physical adsorption (92.7 ± 0.4%). Furthermore, the CT results corroborate that 32P-Hap (100 µCi) +DOX group has the highest tumor suppression rate and can effectively reduce bone destruction. The results corroborate the effectiveness of the chemical synthesis and validate the application of 32P-Hap in bone tumors. Therefore, 32P-Hap (100 µCi) + DOX may be an effective strategy for bone metastasis treatments.

DREAM-Net: Deep Residual Error Iterative Minimization Network for Sparse-View CT Reconstruction.

Sparse-view Computed Tomography (CT) has the ability to reduce radiation dose and shorten the scan time, while the severe streak artifacts will compromise anatomical information. How to reconstruct high-quality images from sparsely sampled projections is a challenging ill-posed problem. In this context, we propose the unrolled Deep Residual Error iterAtive Minimization Network (DREAM-Net) based on a novel iterative reconstruction framework to synergize the merits of deep learning and iterative reconstruction. DREAM-Net performs constraints using deep neural networks in the projection domain, residual space, and image domain simultaneously, which is different from the routine practice in deep iterative reconstruction frameworks. First, a projection inpainting module completes the missing views to fully explore the latent relationship between projection data and reconstructed images. Then, the residual awareness module attempts to estimate the accurate residual image after transforming the projection error into the image space. Finally, the image refinement module learns a non-standard regularizer to further fine-tune the intermediate image. There is no need to empirically adjust the weights of different terms in DREAM-Net because the hyper-parameters are embedded implicitly in network modules. Qualitative and quantitative results have demonstrated the promising performance of DREAM-Net in artifact removal and structural fidelity.

Unraveling the potential human health risks from used disposable face mask-derived micro/nanoplastics during the COVID-19 pandemic scenario: A critical review.

With the global spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), disposable face masks (DFMs) have caused negative environmental impacts. DFMs will release microplastics (MPs) and nanoplastics (NPs) during environmental degradation. However, few studies reveal the release process of MPs/NPs from masks in the natural environment. This review presents the current knowledge on the abiotic and biotic degradation of DFMs. Though MPs and NPs have raised serious concerns about their potentially detrimental effects on human health, little attention was paid to their impacts on human health from DFM-derived MPs and NPs. The potential toxicity of mask-derived MPs/NPs, such as gastrointestinal toxicity, pneumotoxicity, neurotoxicity, hepatotoxicity, reproductive and transgenerational toxicity, and the underlying mechanism will be discussed in the present study. MPs/NPs serve as carriers of toxic chemicals and pathogens, leading to their bioaccumulation and adverse effects of biomagnification by food chains. Given human experiments are facing ethical issues and animal studies cannot completely reveal human characteristics, advanced human organoids will provide promising models for MP/NP risk assessment. Moreover, in-depth investigations are required to identify the release of MPs/NPs from discarded face masks and characterize their transportation through the food chains. More importantly, innovative approaches and eco-friendly strategies are urgently demanded to reduce DFM-derived MP/NP pollution.

Bioinspired Robust Keratin Hydrogels for Biomedical Applications.

Although keratins are robust in nature, hydrogels producing their extracts exhibit poor mechanical properties due to the complicated composition and ineffective self-assembly. Here we report a bioinspired strategy to fabricate robust keratin hydrogels based on mechanism study through recombinant proteins. Homotypic and heterotypic self-assembly of selected type I and type II keratins in different combinations was conducted to identify crucial domain structures for the process, their kinetics, and relationship with the mechanical strength of hydrogels. Segments with best performance were isolated and used to construct novel assembling units. The new design outperformed combinations of native proteins in mechanical properties and in biomedical applications such as controlled drug release and skin regeneration. Our approach not only elucidated the critical structural domains and underlying mechanisms for keratin self-assembly but also opens an avenue toward the rational design of robust keratin hydrogels for biomedical applications.

Protein Design: From the Aspect of Water Solubility and Stability.

Water solubility and structural stability are key merits for proteins defined by the primary sequence and 3D-conformation. Their manipulation represents important aspects of the protein design field that relies on the accurate placement of amino acids and molecular interactions, guided by underlying physiochemical principles. Emulated designer proteins with well-defined properties both fuel the knowledge-base for more precise computational design models and are used in various biomedical and nanotechnological applications. The continuous developments in protein science, increasing computing power, new algorithms, and characterization techniques provide sophisticated toolkits for solubility design beyond guess work. In this review, we summarize recent advances in the protein design field with respect to water solubility and structural stability. After introducing fundamental design rules, we discuss the transmembrane protein solubilization and de novo transmembrane protein design. Traditional strategies to enhance protein solubility and structural stability are introduced. The designs of stable protein complexes and high-order assemblies are covered. Computational methodologies behind these endeavors, including structure prediction programs, machine learning algorithms, and specialty software dedicated to the evaluation of protein solubility and aggregation, are discussed. The findings and opportunities for Cryo-EM are presented. This review provides an overview of significant progress and prospects in accurate protein design for solubility and stability.

Computational identification of immune-related lncRNA signature for predicting the prognosis and immune landscape of human glioblastoma multiforme.

Emerging evidence shows immune-related long noncoding RNAs (ir-lncRNAs) perform critical roles in tumor progression and prognosis assessment. However, the identification of ir-lncRNAs and their clinical significance in human glioblastoma multiforme (GBM) remain largely unexplored. Here, a designed computational frame based on immune score was used to identify differentially expressed ir-lncRNAs (DEir-lncRNAs) from The Cancer Genome Atlas (TCGA) GBM program. The immune-related lncRNA signature (IRLncSig) composed of prognosis-related DEir-lncRNAs selected by Cox regression analysis and its clinical predictive values were verified, which was further validated by another dataset from the Gene Expression Omnibus database (GEO). Subsequently, the association between IRLncSig and immune cell infiltration, immune checkpoint inhibitor (ICI) biomarkers, O6-methylguanine-DNA methyltransferase (MGMT) gene expression, and biological function were also analyzed. After calculation, five prognosis-related ir-lncRNAs were included in the establishment of IRLncSig. The risk assessment based on IRLncSig indicated that the high-IRLncSig-score group was significantly associated with poor prognosis (p < 0.001), significant aggregation of macrophages (p < 0.05), higher ICI biomarker expression, and MGMT gene expression (p < 0.05). Signature-related lncRNAs may be involved in immune activities in the tumorigenesis and progression of GBM. In summary, the novel IRLncSig shows a promising clinical value in predicting the prognosis and immune landscape of GBM.

Rational Design of High-Performance Keratin-Based Hemostatic Agents.

Keratins are considered ideal candidates as hemostatic agents, but the development lags far behind their potentials due to the poorly understood hemostatic mechanism and structure-function relations, owing to the composition complexity in protein extracts. Here, it is shown that by using a recombinant synthesis approach, individual types of keratins can be expressed and used for mechanism investigation and further high-performance keratin hemostatic agent design. In the comparative evaluation of full-length, rod-domain, and helical segment keratins, the α-helical contents in the sequences are identified to be directly proportional to keratins' hemostatic activities, and Tyr, Phe, and Gln residues at the N-termini of α-helices in keratins are crucial in fibrinopeptide release and fibrin polymerization. A feasible route to significantly enhance the hemostatic efficiency of helical keratins by mutating Cys to Ser in the sequences for enhanced water wettability through soluble expression is then further presented. These results provide a rational strategy to design high-efficiency keratin hemostatic agents with superior performance over clinically used gelatin sponge in multiple animal models.

Distinct accumulation of nanoplastics in human intestinal organoids.

Plastic particles, especially nanoplastics, represent an emerging concern of threat to human health, oral uptake is an important pathway for the plastic particles ingestion by human. While their fate and adverse effects in animal gastrointestinal tract are increasingly investigated, knowledge about their uptake and toxicity in human intestine is still limited. Here, by exposing human intestinal organoids to polystyrene nanoplastics (PS-NPs, ~50 nm in size) with concentrations of 10 and 100 µg/mL, we present evidence of their distinct accumulation in various type cells in intestinal organoids, then causing the cell apoptosis and inflammatory response. Our results further revealed that the effective inhibition of PS-NPs accumulation in secretive cells through co-exposure to a clathrin-mediated endocytosis inhibitor (chlorpromazine), and proved the essential role of active endocytosis in the PS-NPs uptaking into enterocyte cells. Our work not only elucidated the potential uptake and toxicity of PS-NPs in human intestinal cells and the underlying mechanism, but also provide a potential therapeutic approach to relieve the toxicity of PS-NPs to human through the endocytosis inhibition.