Objective To analyze the risk factors associated with the occurrence of rectal neuroendocrine tumors (RNETs) and construct a risk prediction model. Methods Clinical data of patients who underwent electronic colonoscopy were collected. The clinical information on patients with and without RNETs were compared, and potential risk factors for RNETs were identified. Binary logistic regression was performed to analyze the relevant risk factors and construct a risk prediction model. Results Among 164 patients, 66 were diagnosed with RNETs, and 98 who did not have such a condition were randomly selected. Univariate logistic regression analysis revealed that age, fatty liver, anxiety and depression, total cholesterol, triglyceride levels, and carcinoembryonic antigen (CEA) were significant factors influencing the occurrence of RNETs (P<0.05). Multivariate logistic regression analysis identified age (P=0.015), anxiety and depression (P=0.031), cholesterol level (P=0.009), fatty liver (P=0.001), and CEA (P<0.001) as independent risk factors for RNETs. The participants were randomly divided into training and test sets at a 7:3 ratio. The training set was used to construct a nomogram-based risk prediction model, and the testing set was used for internal validation. The area under the curve values for the training and testing sets were 0.843 and 0.772, respectively (P>0.05). These findings indicate a good discriminative performance. The calibration curves for the training and testing sets were in good agreement with the 45° standard line, which suggests that the predicted probabilities were consistent with the actual outcomes. Decision curve analysis showed that the model provided a high net benefit within a threshold range of 0.2 to 0.7 for clinical decision making. Conclusion Young age, fatty liver, high CEA levels, high cholesterol levels, and anxiety and depression are independent risk factors for RNETs. The nomogram model constructed based on these risk factors exhibits a strong capability to predict the occurrence of RNETs, and clinical intervention can be considered based on the predicted probability values.

Background Kurtosis reflecting noise's temporal structure is an effective metric for evaluating noise-induced hearing loss (NIHL), and its threshold is still unclear. Objective To explore the energy range of kurtosis and the threshold of NIHL induced by kurtosis in this energy rangeMethods Using cross-sectional design, 4631 noise-exposed workers in manufacturing industry were selected. The hearing loss and noise exposure data of each worker were collected. Logistic regression model was used to establish the dose-response relationship between noise exposure and hearing loss and estimate the range of energy effects. Restricted cubic spline model was utilized to analyze the dose-response relationship curves of kurtosis to noise-induced hearing loss (NIHI) and high-frequency noise-induced hearing loss (HFNIHL) under different 8 h equivalent sound levels (L_{EX,8 h}), as well as to estimate the kurtosis effect threshold. Results The logistic regression model analysis showed that the prevalence of NIHI and HFNIHL increased significantly with increase of L_{EX,8 h} for steady noise; when L_{EX,8 h} of non-steady noise was 80-100 dB(A), the risk of hearing loss increased with an increase in kurtosis (P<0.05). The restricted cubic spline model showed that when L_{EX,8 h} of non-steady noise was 0-80 dB(A) or >100 dB(A), there was no significant relationship between kurtosis and NIHI or HFNIHL. When L_{EX,8 h} was 80-100 dB(A), there was a significant nonlinear dose-response relationship between kurtosis and NIHL or HFNIHL (P <0.001), and kurtosis > 28.08 exerted effect in elevating NIHI or HFNIHL. Conclusion The effect threshold of kurtosis on NIHL is 28.08 when non-steady noise levels are in the range of 80-100 dB(A). The effect threshold of kurtosis needs further verification.

Background Temporal kurtosis (without frequency weighting, i.e., Z-weighted kurtosis) can evaluate noise-induced hearing loss (NIHL). However, few studies have considered the function of frequency weighting (A- or C-weighted) kurtosis on NIHL. Objective To study the significance of A- and C-weighted kurtosis adjustment for equivalent sound level (L'_{EX,8 h}) in evaluating occupational hearing loss. Methods A cross-sectional survey was used to select 973 noise-exposed workers in seven industries as the subjects. The noise exposure of all workers was assessed by distributions of A-, C-, and Z-weighted kurtosis (e.g., K_A, K_C, and K_Z) and respective adjusted equivalent sound level (e.g., L'_{EX,8 h}-K_A, L'_{EX,8 h}-K_C, and L'_{EX,8 h}-K_Z). The significance of A- and C-weighted kurtosis in evaluating NIHL was evaluated by correlations between three types of L'_{EX,8 h} and NIHL, and improvement of noise-induced permanent threshold shift (NIPTS) underestimation predicted by the ISO prediction model (Acoustics—Estimation of noise-induced hearing loss, ISO 1999-2013). Results The median K_A, K_C, and K_Z were 68.33, 28.22, and 19.82, respectively. The binary logistic regression showed that L_{EX, 8 h}-K_A, L_{EX, 8 h}-K_C, and L'_{EX, 8 h}-K_Z were risk factors for NIHL (OR>1, P<0.001). The receiver operating characteristic (ROC) curve showed that when the outcome variable was noise-induced hearing impairment (NIHI), the areas under the curves corresponding to L'_{EX,8 h}-K_A, L'_{EX,8 h}-K_C, and L'_{EX,8 h}-K_Z were 0.625, 0.628, and 0.625, respectively. When the outcome variable was high-frequency noise-induced hearing loss (HFNIHL), the areas under the curves corresponding to L'_{EX,8 h}-K_A, L'_{EX, 8 h}-K_C, and L'_{EX,8 h}-K_Z were 0.624, 0.623, and 0.622, respectively (P<0.05). The order of underestimation improvement values predicted by L'_{EX,8 h} for NIPTS₁₂₃₄ was: L'_{EX,8 h}-K_A (4.68 dB HL)>L'_{EX,8 h}-K_C (4.38 dB HL)>L'_{EX,8 h}-K_Z (4.28 dB HL) (P<0.001). The order of underestimation improvement values predicted by L'_{EX,8 h}-K for NIPTS₃₄₆ was: L'_{EX,8 h}-K_A (7.20 dB HL)>L'_{EX,8 h}-K_C (6.83 dB HL)>L'_{EX,8 h}-K_Z (6.71 dB HL) (P<0.001). Conclusion The adjustment of A- and C-weighted kurtosis to equivalent sound level L_{EX,8 h} can effectively improve the accuracy of the ISO 1999 prediction model in NIPTS prediction, and compared with the C-weighted, the A-weighted kurtosis can improve the result of the ISO 1999 prediction model in terms of underestimating NIPTS.

As China accelerates its efforts in deep space exploration and long-duration space missions, including the operationalization of the Tiangong Space Station and the development of manned lunar missions, safeguarding astronauts’ physiological and cognitive functions under extreme space conditions becomes a pressing scientific imperative. Among the multifactorial stressors of spaceflight, microgravity emerges as a particularly potent disruptor of neurobehavioral homeostasis. Dopamine (DA) plays a central role in regulating behavior under space microgravity by influencing reward processing, motivation, executive function and sensorimotor integration. Changes in gravity disrupt dopaminergic signaling at multiple levels, leading to impairments in motor coordination, cognitive flexibility, and emotional stability. Microgravity exposure induces a cascade of neurobiological changes that challenge dopaminergic stability at multiple levels: from the transcriptional regulation of DA synthesis enzymes and the excitability of DA neurons, to receptor distribution dynamics and the efficiency of downstream signaling pathways. These changes involve downregulation of tyrosine hydroxylase in the substantia nigra, reduced phosphorylation of DA receptors, and alterations in vesicular monoamine transporter expression, all of which compromise synaptic DA availability. Experimental findings from space analog studies and simulated microgravity models suggest that gravitational unloading alters striatal and mesocorticolimbic DA circuitry, resulting in diminished motor coordination, impaired vestibular compensation, and decreased cognitive flexibility. These alterations not only compromise astronauts’ operational performance but also elevate the risk of mood disturbances and motivational deficits during prolonged missions. The review systematically synthesizes current findings across multiple domains: molecular neurobiology, behavioral neuroscience, and gravitational physiology. It highlights that maintaining DA homeostasis is pivotal in preserving neuroplasticity, particularly within brain regions critical to adaptation, such as the basal ganglia, prefrontal cortex, and cerebellum. The paper also discusses the dual-edged nature of DA plasticity: while adaptive remodeling of synapses and receptor sensitivity can serve as compensatory mechanisms under stress, chronic dopaminergic imbalance may lead to maladaptive outcomes, such as cognitive rigidity and motor dysregulation. Furthermore, we propose a conceptual framework that integrates homeostatic neuroregulation with the demands of space environmental adaptation. By drawing from interdisciplinary research, the review underscores the potential of multiple intervention strategies including pharmacological treatment, nutritional support, neural stimulation techniques, and most importantly, structured physical exercise. Recent rodent studies demonstrate that treadmill exercise upregulates DA transporter expression in the dorsal striatum, enhances tyrosine hydroxylase activity, and increases DA release during cognitive tasks, indicating both protective and restorative effects on dopaminergic networks. Thus, exercise is highlighted as a key approach because of its sustained effects on DA production, receptor function, and brain plasticity, making it a strong candidate for developing effective measures to support astronauts in maintaining cognitive and emotional stability during space missions. In conclusion, the paper not only underscores the centrality of DA homeostasis in space neuroscience but also reflects the authors’ broader academic viewpoint: understanding the neurochemical substrates of behavior under microgravity is fundamental to both space health and terrestrial neuroscience. By bridging basic neurobiology with applied space medicine, this work contributes to the emerging field of gravitational neurobiology and provides a foundation for future research into individualized performance optimization in extreme environments.

T7 RNA polymerase (T7 RNAP) is one of the simplest known RNA polymerases. Its unique structural features make it a critical model for studying the mechanisms of RNA synthesis. This review systematically examines the static crystal structure of T7 RNAP, beginning with an in-depth examination of its characteristic “thumb”, “palm”, and “finger” domains, which form the classic “right-hand-like” architecture. By detailing these structural elements, this review establishes a foundation for understanding the overall organization of T7 RNAP. This review systematically maps the functional roles of secondary structural elements and their subdomains in transcriptional catalysis, progressively elucidating the fundamental relationships between structure and function. Further, the intrinsic flexibility of T7 RNAP and its applications in research are also discussed. Additionally, the review presents the structural diagrams of the enzyme at different stages of the transcription process, and through these diagrams, it provides a detailed description of the complete transcription process of T7 RNAP. By integrating structural dynamics and kinetics analyses, the review constructs a comprehensive framework that bridges static structure to dynamic processes. Despite its advantages, T7 RNAP has a notable limitation: it generates double-stranded RNA (dsRNA) as a byproduct. The presence of dsRNA not only compromises the purity of mRNA products but also elicits nonspecific immune responses, which pose significant challenges for biotechnological and therapeutic applications. The review provides a detailed exploration of the mechanisms underlying dsRNA formation during T7 RNAP catalysis, reviews current strategies to mitigate this issue, and highlights recent progress in the field. A key focus is the semi-rational design of T7 RNAP mutants engineered to minimize dsRNA generation and enhance catalytic performance. Beyond its role in transcription, T7 RNAP exhibits rapid development and extensive application in fields, including gene editing, biosensing, and mRNA vaccines. This review systematically examines the structure-function relationships of T7 RNAP, elucidates the mechanisms of dsRNA formation, and discusses engineering strategies to optimize its performance. It further explores the engineering optimization and functional expansion of T7 RNAP. Furthermore, this review also addresses the pressing issues that currently need resolution, discusses the major challenges in the practical application of T7 RNAP, and provides an outlook on potential future research directions. In summary, this review provides a comprehensive analysis of T7 RNAP, ranging from its structural architecture to cutting-edge applications. We systematically examine: (1) the characteristic right-hand domains (thumb, palm, fingers) that define its minimalistic structure; (2) the structure-function relationships underlying transcriptional catalysis; and (3) the dynamic transitions during the complete transcription cycle. While highlighting T7 RNAP’s versatility in gene editing, biosensing, and mRNA vaccine production, we critically address its major limitation—dsRNA byproduct formation—and evaluate engineering solutions including semi-rationally designed mutants. By synthesizing current knowledge and identifying key challenges, this work aims to provide novel insights for the development and application of T7 RNAP and to foster further thought and progress in related fields.

ObjectiveTobacco-related diseases remain one of the leading preventable public health challenges worldwide and are among the primary causes of premature death. In recent years, accumulating evidence has supported the classification of nicotine addiction as a chronic brain disease, profoundly affecting both brain structure and function. Despite the urgency, effective diagnostic methods for smoking addiction remain lacking, posing significant challenges for early intervention and treatment. To address this issue and gain deeper insights into the neural mechanisms underlying nicotine dependence, this study proposes a novel graph neural network framework, termed TI-GNN. This model leverages functional magnetic resonance imaging (fMRI) data to identify complex and subtle abnormalities in brain connectivity patterns associated with smoking addiction. MethodsThe study utilizes fMRI data to construct functional connectivity matrices that represent interaction patterns among brain regions. These matrices are interpreted as graphs, where brain regions are nodes and the strength of functional connectivity between them serves as edges. The proposed TI-GNN model integrates a Transformer module to effectively capture global interactions across the entire brain network, enabling a comprehensive understanding of high-level connectivity patterns. Additionally, a spatial attention mechanism is employed to selectively focus on informative inter-regional connections while filtering out irrelevant or noisy features. This design enhances the model’s ability to learn meaningful neural representations crucial for classification tasks. A key innovation of TI-GNN lies in its built-in causal interpretation module, which aims to infer directional and potentially causal relationships among brain regions. This not only improves predictive performance but also enhances model interpretability—an essential attribute for clinical applications. The identification of causal links provides valuable insights into the neuropathological basis of addiction and contributes to the development of biologically plausible and trustworthy diagnostic tools. ResultsExperimental results demonstrate that the TI-GNN model achieves superior classification performance on the smoking addiction dataset, outperforming several state-of-the-art baseline models. Specifically, TI-GNN attains an accuracy of 0.91, an F1-score of 0.91, and a Matthews correlation coefficient (MCC) of 0.83, indicating strong robustness and reliability. Beyond performance metrics, TI-GNN identifies critical abnormal connectivity patterns in several brain regions implicated in addiction. Notably, it highlights dysregulations in the amygdala and the anterior cingulate cortex, consistent with prior clinical and neuroimaging findings. These regions are well known for their roles in emotional regulation, reward processing, and impulse control—functions that are frequently disrupted in nicotine dependence. ConclusionThe TI-GNN framework offers a powerful and interpretable tool for the objective diagnosis of smoking addiction. By integrating advanced graph learning techniques with causal inference capabilities, the model not only achieves high diagnostic accuracy but also elucidates the neurobiological underpinnings of addiction. The identification of specific abnormal brain networks and their causal interactions deepens our understanding of addiction pathophysiology and lays the groundwork for developing targeted intervention strategies and personalized treatment approaches in the future.

Chronic kidney disease(CKD)often begins subtly,with its prevalence steadily rising over time,some patients may already be in end-stage renal disease by the time they seek treatment,making it a signifi-cant global public health concern.Early and prompt diagnosis and treatment are crucial in slowing disease ad-vancement,enhancing patients'quality of life,and ultimately improving prognosis.Current studies have shown that hypoxia,directly or indirectly induced,is an important pathological mechanism in the occurrence and de-velopment of CKD,and hypoxia inducible factor-1α(HIF-1α)is one of the main nuclear transcription factors in the body's response to hypoxia.It plays an important role in the occurrence and development of kidney dis-eases in the process of energy metabolism,angiogenesis,apoptosis,tissue inflammation and fibrosis.There-fore,this article briefly reviews the research progress of HIF-1α in CKD,and provides more effective strategies for the prevention and treatment of CKD.

Aim To establish a gait analysis system based on DeepLabCut(DLC)algorithm for evaluating motor function in aged mice.Methods Based on DLC algorithm in deep learning technology,treadmill device and fully closed design were used in the system,including software and hardware.This system was applied to evaluate gait characteristics of mice due to aging un-der different movement modes.Correlation analysis was used to explore the effects of body weight and body length on gait indica-tors.Results This system realized the synchronous analysis of three-dimensional gait(lateral and ventral plane)of mice at specific gait speed,and automatically quantified 47 gait indica-tors.Using this system,it was found that during walking(15 cm·s-1),the standard deviation of body turning angle decreased,forelimb sway duration,standard deviation of knee angle,mean outward angles of left and right hind paw increased in 8 and 15 month-old mice,compared with 2-month-old mice.However,15-month-old mice showed decreased walking frequency,and in-creased stride width,total duration of double support,and knee extension and contraction distance.In addition,at trot(20 cm·s-1),15-month-old mice were unable to walk steadily,and 8-month-old mice had increased total duration of double support and mean outward angles of left hind paw,compared with 2-month-old mice.Correlation analysis revealed that indicators like walking frequency,stride width,forelimb sway duration,total duration of double support,standard deviation of knee an-gle,knee extension and contraction distance,were not affected by changes in body weight and body length.Conclusions The gait analysis system based on DLC algorithm can achieve a more sensitive,accurate and comprehensive evaluation of the gait of aged mice,distinguishing the gait characteristics of aged mice to maintain gait stability,and selecting behavioral indicators that better reflect the gait changes of aged mice.It provides a meth-odological basis for more effective assessment of efficacy and side effects of drugs for anti-aging and anti-decline of motor coordina-tion in the future.

Objective To screen the differentially expressed genes of lung metastasis of osteosarcoma by bioinformatics,and explore their functions and regulatory networks.Methods The data set of GSE14359 was screened from GEO database(http://www.ncbi.nlm.nih.gov/gds)and the differentially expressed gene(DEG)was identified using GEO2R online tool.Download osteosarcoma disease related miRNAs from the online HMMD database(http://www.cuilab.cn/hmdd)and then FunRich software was used to predict the target gene,intersects with DEG to obtains the target gene.The miRNA-mRNA rela-tionship pairs were formed according to the targeted joints,then the data was imported into Cytoscape for visualization,DAVID was used to performe GO and KEGG analysis on target genes,STRING was used to construct PPI network,Cytoscape visualiza-tion,CytoHubba plug-in screening central genes and online website for expression and survival analysis.Results Total 704 DEGs were identified,consisting of 477 up-regulated genes and 227 down regulated genes.FunRich predicted 7 888 mRNAs and 343 target genes were obtained through intersection of the two.KEGG analysis showed that it was mainly involved in focal adhesion,ECM receptor interaction,TNF signal pathway,PI3K-Akt signal pathway,IL-17 signal pathway and MAPK signal pathway.Ten central genes(CCNB1,CHEK1,AURKA,DTL,RRM2,MELK,CEP55,FEN1,KPNA2,TYMS)were identified as potential key genes.Among them,CCNB1,DTL,MELK were highly correlated with poor prognosis.Conclusion The key genes and functional pathways identified in this study may be helpful to understand the molecular mechanism of the occurrence and progression of lung metastases from osteosarcoma,and provide potential therapeutic targets.

Objective To evaluate the clinical effect of a new three-phase Chinese medicine(CM)external treatment for acute lateral ankle ligament injuries.Methods From July to December 2023,64 patients with acute lateral ankle ligament in-juries were randomly assigned to receive either the new three-phase CM external treatment combined with the POLICE(pro-tect,optimal loading,ice,compression,elevation)treatment(observation group)or the POLICE treatment(control group),with 32 cases in each group.The observation group consisted of 17 males and 15 females,with an average age of(30.59±3.10)years old ranging from 25 to 36 years old,while the control group included 14 males and 18 females,with an average age of(30.03±3.19)years old ranging from 24 to 37 years old.Visual analogue scale(VAS)evaluation and Figure of 8 measurement were used to evaluate the degree of ankle joint pain and swelling of the subjects at the initial enrollment and after 1 week and sixth weeks of treatment.At the same time,the American Orthopaedic Foot and Ankle Society(AOFAS)and Karlsson Ankle Function Score System were used to evaluate the improvement of ankle joint function in patients at all stages.MRI imaging was employed to observe the degree of biological healing of the anterior talofibular ligament,with the signal to noise ratio(SNR)in-dicating the level of healing.A lower SNR suggests better ligament healing,as it represents lower water content in the ligament.Results All patients completed a 6-week follow-up.There was no significant difference in VAS,AOFAS score and Karlsson score between the two groups before treatment(P＞0.05).After 1 week and 6 weeks of treatment,the VAS,AOFAS score and Karlsson score of the two groups were significantly improved(P＜0.05).After 1 week of treatment,the VAS score of the obser-vation group(3.21±0.87)was lower than that of the control group(4.21±1.50),and the difference was statistically significant(P＜0.05).After 1 weeks of treatment,the AOFAS and Karlsson scores[(50.84±4.70)points,(49.97±4.00)points]of the ob-servation group were higher than those[(46.91±5.56)points,(46.66±5.36)points]of the control group(P＜0.05).MRI images showed that after 6 weeks of treatment,the SNR value of the observation group was significantly lower than that of the control group,and the difference was statistically significant(SNR of the observation group was 75.25±16.59,the contral gruop was 85.81±15.55),(P＜0.05).Conclusion Compared with the control group,the new three-phase CM external treatment is signifi-cantly effective in reducing pain and swelling,enhancing ligament repair quality,and promoting functional recovery of the an-kle joint in patients with acute lateral malleolar ligament injuries.