ObjectiveTo investigate the gene expression sequence and molecular mechanisms in the local microenvironment during the subacute to chronic phases (1-28 days) in mouse models of spinal cord compression injury and hemisection spinal cord injury, thereby revealing the molecular characteristics of spinal cord repair and providing a theoretical basis for selecting therapeutic targets for spinal cord injury. MethodsThirty-six 8-9-week-old SPF-grade ICR mice were randomly divided into three groups (n=12 per group): sham-operated control (CTR) group, hemisection spinal cord injury (HSCI) group, and spinal cord compression injury (SCC) group. Mice in the CTR group underwent the same surgical preparation and anesthesia, followed by a dorsal midline incision at the T₉-T₁₀ segment. After layer-by-layer dissection and removal of the corresponding lamina, the spinal cord dura mater was fully exposed and kept intact. The cord was exposed to air for 10 minutes (matching the duration of the compression injury group), during which any instrument contact with the cord was avoided. The incision was then irrigated and sutured. The HSCI group underwent a 70% transection of the T₉ spinal cord segment using micro-instruments to establish a hemisection spinal cord injury model. The SCC group underwent sustained compression of the T₁₀ spinal cord segment for 10 minutes using a self-made compressor (a 30 g solid small iron bar) to establish a spinal cord compression injury model. Motor function recovery was assessed using the modified Basso-Beattie-Bresnahan (BBB) score on postoperative days 1, 3, 7, 14, 21, and 28. On days 7 and 14 post-operation, mice were anesthetized, and the injured spinal cord segments were harvested. The evolution of specific molecular networks in the spinal cord injury mouse models was analyzed via RNA sequencing (RNA-Seq) and enrichment analysis, and the expression of key genes was verified using real time fluorogenic quantitative PCR. ResultsBBB scores indicated that motor function recovery in the SCC group was significantly better than that in the HSCI group, with BBB scores showing a continuously increasing trend and remaining higher than those in the HSCI group over the 4-week period (P <0.001). Gene ontology （GO)and Kyoto Encyclopedia of Genes and Genomes （KEGG） enrichment analyses based on RNA-Seq differentially expressed genes revealed that, compared to the CTR group, genes related to the extracellular matrix were significantly up-regulated (P<0.05), while genes related to axon guidance were significantly down-regulated (P <0.05) in the SCC group on day 7 post-operation. On day 21, genes involved in immune regulation and the retinol signaling pathway were significantly activated in the SCC group (P<0.05). In contrast, in the HSCI group, genes associated with inflammation and immune response were significantly up-regulated (P<0.001), while genes related to neuronal differentiation and synapse formation were significantly down-regulated (P <0.001) on day 7. On day 21, genes related to cell-matrix junctions and N-methyl-D-aspartate receptors were significantly up-regulated (P<0.001) in the HSCI group. Furthermore, compared to the SCC group, the HSCI group exhibited different pathway enrichment characteristics in GO and KEGG analyses on days 7 and 21 post-injury. On day 7, genes involved in the NOD-like receptor signaling pathway and the complement and coagulation cascades were significantly up-regulated in the HSCI group (P<0.001). On day 21, genes related to the extracellular matrix-receptor interaction and the neuroactive ligand-receptor interaction pathways were significantly activated (P<0.001). Finally, real time fluorogenic quantitative PCR validation results were highly consistent with the RNA-Seq results, further confirming the differential expression trends of key genes between the SCC and HSCI groups. ConclusionThe SCC and HSCI injury models may drive distinct repair pathways: the preservation of some axons in the SCC model predisposes it toward tissue repair, whereas the HSCI model requires the coordination of more complex molecular networks to achieve a new equilibrium. This finding further deepens the understanding of the heterogeneous regulatory mechanisms underlying spinal cord injury.

Biomolecular condensates are formed through phase separation of biomacromolecules such as proteins and RNAs. These condensates exhibit liquid-like properties that can futher transition into more stable material states. They form complex internal structures via multivalent weak interactions, enabling precise spatiotemporal regulations. However, the use of inconsistent and non-standardized terminology has become increasingly problematic, hindering academic exchange and the dissemination of scientific knowledge. Therefore, it is necessary to discuss the terminology related to biomolecular condensates in order to clarify concepts, promote interdisciplinary cooperation, enhance research efficiency, and support the healthy development of this field.

General anesthesia, pivotal for surgical procedures, requires precise depth monitoring to mitigate risks ranging from intraoperative awareness to postoperative cognitive impairments. Traditional assessment methods, relying on physiological indicators or behavioral responses, fall short of accurately capturing the nuanced states of unconsciousness. This study introduces a machine learning-based approach to decode anesthesia depth, leveraging EEG data across different anesthesia states induced by propofol and esketamine in rats. Our findings demonstrate the model's robust predictive accuracy, underscored by a novel intra-subject dataset partitioning and a 5-fold cross-validation method. The research diverges from conventional monitoring by utilizing anesthetic infusion rates as objective indicators of anesthesia states, highlighting distinct EEG patterns and enhancing prediction accuracy. Moreover, the model's ability to generalize across individuals suggests its potential for broad clinical application, distinguishing between anesthetic agents and their depths. Despite relying on rat EEG data, which poses questions about real-world applicability, our approach marks a significant advance in anesthesia monitoring.
Animals ; Machine Learning ; Electroencephalography/methods* ; Ketamine/administration & dosage* ; Rats ; Male ; Propofol/administration & dosage* ; Rats, Sprague-Dawley ; Anesthesia, General/methods* ; Brain/physiology* ; Intraoperative Neurophysiological Monitoring/methods*

Learning-associated functional plasticity at hippocampal synapses remains largely unexplored. Here, in a single session of reward-based trace conditioning, we examine learning-induced synaptic plasticity in the dorsal CA1 hippocampus (dCA1). Local field-potential recording combined with selective optogenetic inhibition first revealed an increase of dCA1 synaptic responses to the conditioned stimulus (CS) induced during conditioning at both Schaffer collaterals to the stratum radiatum (Rad) and temporoammonic input to the lacunosum moleculare (LMol). At these dCA1 inputs, synaptic potentiation of CS-responding excitatory synapses was further demonstrated by locally blocking NMDA receptors during conditioning and whole-cell recording sensory-evoked synaptic responses in dCA1 neurons from naive animals. An overall similar time course of the induction of synaptic potentiation was found in the Rad and LMol by multiple-site recording; this emerged later and saturated earlier than conditioned behavioral responses. Our experiments demonstrate a cued memory-associated dCA1 synaptic plasticity induced at both Schaffer collaterals and temporoammonic pathways.
Animals ; CA1 Region, Hippocampal/physiology* ; Male ; Association Learning/physiology* ; Neuronal Plasticity/physiology* ; Cues ; Memory/physiology* ; Synapses/physiology* ; Conditioning, Classical/physiology* ; Excitatory Postsynaptic Potentials/physiology* ; Receptors, N-Methyl-D-Aspartate/antagonists & inhibitors* ; Rats ; Optogenetics

Liposomes serve as critical carriers for drugs and vaccines, with their biological effects influenced by their size. The microfluidic method, renowned for its precise control, reproducibility, and scalability, has been widely employed for liposome preparation. Although some studies have explored factors affecting liposomal size in microfluidic processes, most focus on small-sized liposomes, predominantly through experimental data analysis. However, the production of larger liposomes, which are equally significant, remains underexplored. In this work, we thoroughly investigate multiple variables influencing liposome size during microfluidic preparation and develop a machine learning (ML) model capable of accurately predicting liposomal size. Experimental validation was conducted using a staggered herringbone micromixer (SHM) chip. Our findings reveal that most investigated variables significantly influence liposomal size, often interrelating in complex ways. We evaluated the predictive performance of several widely-used ML algorithms, including ensemble methods, through cross-validation (CV) for both liposome size and polydispersity index (PDI). A standalone dataset was experimentally validated to assess the accuracy of the ML predictions, with results indicating that ensemble algorithms provided the most reliable predictions. Specifically, gradient boosting was selected for size prediction, while random forest was employed for PDI prediction. We successfully produced uniform large (600 nm) and small (100 nm) liposomes using the optimised experimental conditions derived from the ML models. In conclusion, this study presents a robust methodology that enables precise control over liposome size distribution, offering valuable insights for medicinal research applications.

Nanozyme is novel nanoparticle with enzyme-like activity, which can be classified into peroxidase-like nanozyme, catalase-like nanozyme, superoxide dismutase-like nanozyme, oxidase-like nanozyme and hydrolase-like nanozyme according to the type of reaction they catalyze. Since researchers first discovered Fe₃O₄ nanoparticles with peroxidase-like activity in 2007, a variety of nanoparticles have been successively found to have catalytic activity and applied in bioassays, inflammation control, antioxidant damage and tumor therapy, playing a key role in disease diagnosis and treatment. We summarize the use of nanozymes with different classes of enzymatic activity in the diagnosis and treatment of diseases and describe the main factors influencing nanozyme activity. A Mn-based peroxidase-like nanozyme that induces the reduction of glutathione in tumors to produce glutathione disulfide and Mn²⁺, which induces the production of reative oxygen species (ROS) in tumor cells by breaking down H₂O₂ in physiological media through Fenton-like action, thereby inhibiting tumor cell growth. To address the limitation of tumor tissue hypoxia during photodynamic tumor therapy, the effect of photodynamic therapy is significantly enhanced by using hydrogen peroxide nanozymes to catalyze the production of oxygen from H₂O₂. In pathological states, where excess superoxide radicals are produced in the body, superoxide dismutase-like nanozymes are able to selectively regulate intracellular ROS levels, thereby protecting normal cells and slowing down the degradation of cellular function. Based on this principle, an engineered nanosponge has been designed to rapidly scavenge free radicals and deliver oxygen in time to save nerve cells before thrombolysis. Starvation therapy, in which glucose oxidase catalyzes the hydrolysis of glucose to gluconic acid and hydrogen peroxide in cancer cells with the involvement of oxygen, attenuates glycolysis and the production of intermediate metabolites such as nucleotides, lipids and amino acids, was used to synthesize an oxidase-like nanozyme that achieved effective inhibition of tumor growth. Furthermore, by fine-tuning the Lewis acidity of the metal cluster to improve the intrinsic activity of the hydrolase nanozyme and providing a shortened ligand length to increase the density of its active site, a hydrolase-like nanozyme was successfully synthesized that is capable of cleaving phosphate bonds, amide bonds, glycosidic bonds and even biofilms with high efficiency in hydrolyzing the substrate. All these effects depend on the size, morphology, composition, surface modification and environmental media of the nanozyme, which are important aspects to consider in order to improve the catalytic efficiency of the nanozyme and have important implications for the development of nanozyme. Although some progress has been made in the research of nanozymes in disease treatment and diagnosis, there are still some problems, for example, the catalytic rate of nanozymes is still difficult to reach the level of natural enzymes in vivo, and the toxic effects of some heavy metal nanozymes material itself. Therefore, the construction of nanozyme systems with multiple functions, good biocompatibility and high targeting efficiency, and their large-scale application in diagnosis and treatment is still an urgent problem to be solved. (1) To improve the selectivity and specificity of nanozymes. By using antibody coupling, the nanoparticles are able to specifically bind to antigens that are overexpressed in certain cancer cells. It also significantly improves cellular internalization through antigen-mediated endocytosis and enhances the enrichment of nanozymes in target tissues, thereby improving targeting during tumor therapy. Some exogenous stimuli such as laser and ultrasound are used as triggers to control the activation of nanozymes and achieve specific activation of nanozyme. (2) To explore more practical and safer nanozymes and their catalytic mechanisms: biocompatible, clinically proven material molecules can be used for the synthesis of nanoparticles. (3) To solve the problem of its standardization and promote the large-scale clinical application of nanozymes in biomonitoring. Thus, it can go out of the laboratory and face the market to serve human health in more fields, which is one of the future trends of nanozyme development.

ObjectiveTePixD (Tll0078) is a blue light-using flavin (BLUF) photoreceptor protein from Thermosynechococcus elongatus BP-1. TePixD protein has a conserved Tyr8-Gln50-Met93 triad around the FAD pocket to mediate the proton-coupled electron transfer (PCET) process. But the detailed light response mechanism needs further study. We aimed to elucidate the structure and biochemical properties of TePixD mutants at key light response sites to analyze the light response process of TePixD. MethodsWe employed X-ray crystallography to resolve the crystal structure of the TePixD Y8F mutant. The side chain of Tyr8 is involved in PCET while Phe8 in mutation loses the function due to the loss of its hydroxyl group. We compared the structure of TePixD Y8F mutation to TePixD wild type (WT) and its homology protein SyPixD Y8F. Using multi-angle light scattering (MALS), we analyzed the oligomerization of multiple TePixD mutations (Y8F, Q50L, W91F, Y8F/W91F, and Q50L/W91F), focusing specifically on mutational sites that are critical residues for the protein’s photo response to dark and light conditions. ResultsWe resolved the crystal structure of TePixD Y8F mutant at a resolution of 2.54 Å and found that it shares a similar overall structure with the TePixD WT but exhibits significant differences from the SyPixD Y8F structure. Biochemical analysis revealed differences in molecular mass and elution profiles between the TePixD mutants and the WT under dark and light conditions, indicating the perturbation on the light-induced conformational change by the mutants. ConclusionOur structure determination and biochemical analyses will add information to reveal the light response mechanism of BLUF proteins.

Genetic counseling for hearing loss today originated from decoding the genetic code of hereditary hearing loss, which serves as an effective strategy for preventing hearing loss and constitutes a crucial component of the diagnostic and therapeutic framework. This paper described the main principles and contents of genetic counseling for hearing loss, the key points of counseling across various genetic models and its application in tertiary prevention strategies targeting hearing impairment. The prospects of an AI-assisted genetic counseling decision system and the envisions of genetic counseling in preventing hereditary hearing loss were introduced. Genetic counseling for hearing loss today embodies the hallmark of a new era, which is inseparable from the advancements in science and technology, and will undoubtedly contribute to precise gene intervention!
Humans ; Genetic Counseling ; Deafness/genetics* ; Hearing Loss/diagnosis* ; Hearing Loss, Sensorineural/genetics*

Female ; Humans ; Endodermal Sinus Tumor/pathology* ; Adenocarcinoma/pathology* ; Choriocarcinoma/pathology*

Meropenem is one of the most widely used special-grade antimicrobial agents in the treatment of neonatal sepsis.However,its irrational use has led to an increasingly severe problem of bacterial multidrug resistance.The guideline was developed following standardized methods and procedures,and provides 12 recommendations specifically addressing 9 clinical issues.The recommendations cover various aspects of meropenem use in neonates,including timing of administration,recommended dosage,extended infusion,monitoring and assessment,antimicrobial adjustment strategies,treatment duration,and treatment strategies for carbapenem-resistant Enterobacteriaceae infections.The aim of the guideline is to provide evidence-based recommendations and guidance for the rational use of meropenem in neonates with sepsis.[Chinese Journal of Contemporary Pediatrics,2024,26(2):107-117]