Immobilized enzyme-based enzyme electrode biosensors, characterized by high sensitivity and efficiency, strong specificity, and compact size, demonstrate broad application prospects in life science research, disease diagnosis and monitoring, etc. Immobilization of enzyme is a critical step in determining the performance (stability, sensitivity, and reproducibility) of the biosensors. Random immobilization (physical adsorption, covalent cross-linking, etc.) can easily bring about problems, such as decreased enzyme activity and relatively unstable immobilization. Whereas, directional immobilization utilizing amino acid residue mutation, affinity peptide fusion, or nucleotide-specific binding to restrict the orientation of the enzymes provides new possibilities to solve the problems caused by random immobilization. In this paper, the principles, advantages and disadvantages and the application progress of enzyme electrode biosensors of different directional immobilization strategies for enzyme molecular sensing elements by specific amino acids (lysine, histidine, cysteine, unnatural amino acid) with functional groups introduced based on site-specific mutation, affinity peptides (gold binding peptides, carbon binding peptides, carbohydrate binding domains) fused through genetic engineering, and specific binding between nucleotides and target enzymes (proteins) were reviewed, and the application fields, advantages and limitations of various immobilized enzyme interface characterization techniques were discussed, hoping to provide theoretical and technical guidance for the creation of high-performance enzyme sensing elements and the manufacture of enzyme electrode sensors.

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.

ObjectiveThe rapid advancement of bioanalytical technologies has heightened the demand for high-throughput, label-free, and real-time cellular analysis. Electrochemical impedance spectroscopy (EIS) operating in the GHz frequency range (GHz-EIS) has emerged as a promising tool for characterizing cell suspensions due to its ability to rapidly and non-invasively capture the dielectric properties of cells and their microenvironment. Although GHz-EIS enables rapid and label-free detection of cell suspensions, significant challenges remain in interpreting GHz impedance data for complex samples, limiting the broader application of this technique in cellular research. To address these challenges, this study presents a novel method that integrates GHz-EIS with deep learning algorithms, aiming to improve the precision of cell suspension concentration identification and quantification. This method provides a more efficient and accurate solution for the analysis of GHz impedance data. MethodsThe proposed method comprises two key components: dielectric property dataset construction and backpropagation (BP) neural network modeling. Yeast cell suspensions at varying concentrations were prepared and separately introduced into a coaxial sensor for impedance measurement. The dielectric properties of these suspensions were extracted using a GHz-EIS dielectric property extraction method applied to the measured impedance data. A dielectric properties dataset incorporating concentration labels was subsequently established and divided into training and testing subsets. A BP neural network model employing specific activation functions (ReLU and Leaky ReLU) was then designed. The model was trained and tested using the constructed dataset, and optimal model parameters were obtained through this process. This BP neural network enables automated extraction and analytical processing of dielectric properties, facilitating precise recognition of cell suspension concentrations through data-driven training. ResultsThrough comparative analysis with conventional centrifugal methods, the recognized concentration values of cell suspensions showed high consistency, with relative errors consistently below 5%. Notably, high-concentration samples exhibited even smaller deviations, further validating the precision and reliability of the proposed methodology. To benchmark the recognition performance against different algorithms, two typical approaches—support vector machines (SVM) and K-nearest neighbor (KNN)—were selected for comparison. The proposed method demonstrated superior performance in quantifying cell concentrations. Specifically, the BP neural network achieved a mean absolute percentage error (MAPE) of 2.06% and an R² value of 0.997 across the entire concentration range, demonstrating both high predictive accuracy and excellent model fit. ConclusionThis study demonstrates that the proposed method enables accurate and rapid determination of unknown sample concentrations. By combining GHz-EIS with BP neural network algorithms, efficient identification of cell concentrations is achieved, laying the foundation for the development of a convenient online cell analysis platform and showing significant application prospects. Compared to typical recognition approaches, the proposed method exhibits superior capabilities in recognizing cell suspension concentrations. Furthermore, this methodology not only accelerates research in cell biology and precision medicine but also paves the way for future EIS biosensors capable of intelligent, adaptive analysis in dynamic biological research.

Objective: To explore the correlation between traditional Chinese medicine (TCM) constitution and depressive symptom among school aged children and adolescents, so as to provide evidences for informing constitution based regulation and prevention of depressive symptom. Methods: From June to December 2024, a total of 4 729 students aged 6-14 were recruited by cluster random sampling from 10 primary schools in Baoding (Hebei Province), Heze and Liaocheng (Shandong Province). General information, TCM constitution and depressive symptom were collected. Restricted cubic spline (RCS) models were used to analyze related factors and threshold effects of depressive symptom. Binary Logistic regression was applied to examine the association between depressive symptom and TCM constitution, with subgroup analyses conducted. Results: The detection rate of depressive symptom among the included children and adolescents was 25.82%. RCS analyses indicated non linear associations between depressive symptom and age (inflection point at 10 years old), bedtime (inflection point at 22:00), and wake up time (inflection point at 6:30 ) (all P non linearity <0.01). Linear associations were observed with body mass index (BMI) and sleep duration (all P non linearity > 0.05 ). After adjusting for covariates such as age, BMI and sleep status, binary Logistic regression analyses showed that Yin deficient constitution ( OR =1.26, 95% CI =1.09-1.45) and Phlegm-dampness constitution ( OR =1.42, 95% CI =1.11-1.82) were significantly associated with depressive symptom among children and adolescents (all P <0.05). Conclusions Depressive symptom among school aged children and adolescents is primarily associated with Yin deficiency and Phlegm dampness constitutions in TCM constitution. Active attention should be paid to susceptible TCM constitution among children and adolescents. Targeted health guidance and interventions should be implemented to improve TCM constitution health status for preventing the occurrence of depressive symptom.

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, functional impairment, and neuropsychiatric symptoms. It represents the most prevalent form of dementia among the elderly population. Accumulating evidence indicates that oxidative stress plays a pivotal role in the pathogenesis of AD. Notably, elevated levels of oxidative stress have been observed in the brains of AD patients, where excessive reactive oxygen species (ROS) can cause extensive damage to lipids, proteins, and DNA, ultimately compromising neuronal structure and function. Amyloid β‑protein (Aβ) has been shown to induce mitochondrial dysfunction and calcium overload, thereby promoting the generation of ROS. This, in turn, exacerbates Aβ aggregation and enhances tau phosphorylation, leading to the formation of two pathological features of AD: extracellular Aβ plaque deposition and intracellular neurofibrillary tangles (NFTs). These events ultimately culminate in neuronal death, forming a vicious cycle. The interplay between oxidative stress and these pathological processes constitutes a core link in the pathogenesis of AD. The signaling pathways mediating oxidative stress in AD include Nrf2, RCAN1, PP2A, CREB, Notch1, NF‑κB, ApoE, and ferroptosis. Nrf2 signaling pathway serves as a key regulator of cellular redox homeostasis, exerts important antioxidant capacity and protective effects in AD. RCAN1 signaling pathway, as a calcineurin inhibitor, and modulates AD progression through multiple mechanisms. PP2A signaling pathway is involved in regulating tau phosphorylation and neuroinflammation processes. CREB signaling pathway contributes to neuroplasticity and memory formation; activation of CREB improves cognitive function and reduce oxidative stress. Notch1 signaling pathway regulates neuronal development and memory, participates in modulation of Aβ production, and interacts with Nrf2 toco-regulate antioxidant activity. NF‑κB signaling pathway governs immune and inflammatory responses; sustained activation of this pathway forms “inflammatory memory”, thereby exacerbating AD pathology. ApoE signaling pathway is associated with lipid metabolism; among its isoforms, ApoE-ε4 significantly increases the risk of AD, leading to elevated oxidative stress, abnormal lipid metabolism, and neuroinflammation. The ferroptosis signaling pathway is driven by iron-dependent lipid peroxidation, and the subsequent release of lipid peroxidation products and ROS exacerbate oxidative stress and neuronal damage. These interconnected pathways form a complex regulatory network that regulates the progression of AD through oxidative stress and related pathological cascades. In terms of therapeutic strategies targeting oxidative stress, among the drugs currently used in clinical practice for AD treatment, memantine and donepezil demonstrate significant therapeutic efficacy and can improve the level of oxidative stress in AD patients. Some compounds with antioxidant effects (such asα-lipoic acid and melatonin) have shown certain potential in AD treatment research and can be used as dietary supplements to ameliorate AD symptoms. In addition, non-drug interventions such as calorie restriction and exercise have been proven to exerted neuroprotective effects and have a positive effect on the treatment of AD. By comprehensively utilizing the therapeutic characteristics of different signaling pathways, it is expected that more comprehensive multi-target combination therapy regimens and combined nanomolecular delivery systems will be developed in the future to bypass the blood-brain barrier, providing more effective therapeutic strategies for AD.

Thirty-one phenolic constituents were isolated and purified from the 95% ethanol extract of Sanguisorbae Radix by using various chromatographic techniques, including macroporous resin, silica gel, ODS, Sephadex LH-20 and semi-preparative HPLC. Their structures were elucidated by physicochemical properties, spectroscopic data (MS and NMR) and electronic circular dichroism (ECD) spectra, and identified as 3-methoxyl-2S,3S-epoxyflavanone (1a), 3-methoxyl-2R,3R-epoxyflavanone (1b), longifoin B (2), longifoin C (3), eriodictyol (4), naringenin (5), liquiritigenin (6), 5,3ʹ-dihydroxy-7,4ʹ-dimethoxyflavanone (7), naringenin-7-O-β-D-glucopyranoside (8), dihydroquercetin (9), dihydrokaempferol (10), (-)-garbanzol (11), (2R,3R)-4-methoxyl-distylin (12), kaempferol (13), quercetin (14), α,4,2′,4′-tetrahydroxydihydrochalcone (15), phloretin (16), (+)-catechin (17), ethyl (+)-cyanidan-3-ol-8-carboxylate (18), phyllocoumarin (19), methyl 3-methoxy-4,5-dihydroxybenzoate (20), 4,5-dimethoxy-3-hydroxybenzoic acid methyl ester (21), 3,4′-di-O-methylellagic acid (22), 3,4,3′-O-trimethylellagic acid (23), 3,3ʹ,4ʹ-O-trimethylellagic acid-4-O-β-D-xyloside (24), (3R)-thunberginol C (25), resveratrol (26), 1-hydroxypinoresinol (27), (7S,8S)-3-methoxy-3′,7-epoxy-8,4′-oxyneoligna-4,9,9′-triol (28), emodin-8-O-β-D-glucoside (29), phloracetophenone (30) and 4-(4′-hydroxyphenyl)-butan-2-one (31). Among them, compound 1a and 1b is a pair of new flavonoid enantiomers, compounds 2 and 3 are a pair of new epimers, while compounds 4, 5, 6, 9, 10, 13, 16 and 26 were obtained from S. officinalis for the first time, compounds 7, 8, 27, 30 and 31 were isolated for the first time from the S. officinalis genus, and compounds 11, 12, 15, 18, 19, 25, 28 and 29 were isolated for the first time from the Rosaceae. The antioxidant activities of compounds 1-24 were evaluated by activating the Nrf2 transcriptional pathway, which were measured by the dual-luciferase reporter gene assay in 293T cells. Compounds 4, 6-10, 12, 14, 17, 19, 20 and 22-24 showed significant Nrf2 agonistic effect compared with the control group at 25 μmol·L^-1, which provided reference for the research of their antioxidant activity.

Objective To integrate tumor proliferation and immune-related biomarkers to construct a nomogram prediction model for predicting the prognosis of ovarian cancer patients.Methods We collected clinical information from patients diagnosed with epithelial ovarian cancer(EOC)between 2009 and 2013.Immunohistochemical staining was performed to detect the expression levels of KI67,epidermal growth factor receptor(EGFR)and programmed death-ligand 1(PD-Ll)in tumor tissues.We employed Lasso-Cox regression to identify variables and construct the nomogram model.We used time-dependent receiver operating characteristic(ROC)curves,concordance index,calibration curves,and decision curve analysis(DC A)curves to assess the model's discrimination,calibration,and net clinical benefit ability,respectively.Additionally,we conducted Kaplan-Meier survival analysis to assess the prognostic value of the model's risk score.Results We included a total of 131 EOC patients who were randomly assigned to the training set(n=79)and validation set(n=52)in a 6∶4 ratio.Lasso-Cox regression identified seven variables for constructing the nomogram prediction model.The AUCs for 1-,4-,and 6-year overall survival in the training set were 0.911,0.943,and 0.968,respectively,with a consistency index of 0.86[95％confidence interval(CI):0.81-0.91].In the validation set,the AUCs for 1-,4-,and 6-year overall survival were 0.830,0.797,and 0.828,respectively,with a consistency index of 0.71(95％CI:0.64-0.78).The calibration curves in both training and validation sets demonstrated strong agreement between model-predicted survival and actual outcomes(all P＞0.05).DCA curves indicated that the modeled net clinical benefit outperformed TNM staging.Patients with high-risk scores in the model exhibit poorer overall survival(P＜0.01)and progression-free survival(P＜0.01).Conclusion The successful development and validation of a nomogram prediction model based on tumor proliferation and immune-related biomarkers offer an efficient and straightforward clinical tool.This tool holds promise for enabling personalized treatment strategies for patients with ovarian cancer.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

OBJECTIVE To investigate the effects of esketamine for multimodal analgesia on opioid consumption and gastric motility in mechanically ventilated non-surgical intensive care unit （ICU） patients. METHODS Forty cases of mechanically ventilated non-surgical patients in the ICU of our hospital from February 1st， 2023 to July 31st， 2023 were selected and randomly divided into control group and esketamine （S-K） group using grouping method with opaque envelopes， with 20 cases in each group. Control group was given sufentanil， and S-K group was infused with Esketamine hydrochloride injection at a constant rate of 0.2 mg/（kg·h）+ sufentanil. The treatment period length， analgesic compliance rate， sedation level， analgesic and sedative consumption， and gastric motility indexes were compared between the two groups. RESULTS There was no statistically significant difference in the treatment period length， analgesic compliance rate， sedation level， or the consumption of propofol and midazolam between the two groups （P＞0.05）. The consumption of sufentanil in the S-K group was significantly less than control group （P＜ 0.05）. Compared with 1 h after randomization， the antral contraction frequency， antral contraction amplitude and antral motility index of patients in the S-K group were significantly higher at 72 h after randomization and were significantly higher than control group （P＜0.05）. CONCLUSIONS Esketamine may reduce opioid consumption and improve gastric motility in mechanically ventilated non-surgical ICU patients while ensuring a level of analgesic sedation.

Objective To systematically evaluate the efficacy and safety of single and bilateral lung transplantation in the treatment of end-stage chronic obstructive pulmonary disease (COPD). Methods Chinese and English databases were searched by computer, including PubMed, Web of Science, The Cochrane Library, EMbase, CNKI, Wanfang database, VIP database and CBM. Case-control studies on single lung transplantation or bilateral lung transplantation for COPD were collected from the inception to July 31, 2022. We evaluated the quality of the literature via Newcastle-Ottawa Scale (NOS). All results were analyzed using Review Manager V5.3 and STATA 17.0. Results A total of 8 studies were included covering 14076 patients, including 8326 patients in the single lung transplantation group and 5750 patients in the bilateral lung transplantation group. NOS scores were≥6 points. The results of meta-analysis showed that there was no statistical difference in the postoperative 1-year survival between the two groups (P=0.070). The 2-year survival rate (P=0.002), 3-year survival rate (P<0.001), 5-year survival rate (P<0.001), overall survival rate (P＜0.001), postoperative forced expiratory volume in one second/predicted value (P<0.001), postoperative forced vital capacity (P<0.001), and postoperative 6-minute walking distance (P=0.002) were lower or shorter than those in the bilateral lung transplantation group, the postoperative intubation time (P=0.030) was longer than that in the bilateral lung transplantation group. Bilateral lung transplantation group showed better surgical results. There was no statistical difference in the mortality, obliterative bronchiolitis, length of hospitalization, primary graft dysfunction, or postoperative adverse events (P>0.05). Conclusion Bilateral lung transplantation is associated with better long-term survival and postoperative lung function compared with single lung transplantation. In-hospital mortality and postoperative complications are similar between them.