Electroencephalography (EEG) is a non-invasive neurophysiological monitoring technique. It records the electrical activity of the cerebral cortex using electrodes placed on the scalp surface. Owing to its high safety, portability, and millisecond-level temporal resolution, EEG has been widely utilized in a variety of fields, including clinical diagnosis, brain-computer interfaces (BCIs), and cognitive neuroscience research. However, due to its microvolt-level amplitude, EEG is highly susceptible to various artifacts, including electrooculographic (EOG), electrocardiographic (ECG), electromyographic (EMG), and power line interference (PLI). These artifacts can obscure genuine neural activity and introduce spurious electrophysiological features. Consequently, they may compromise EEG signal quality, thereby reducing the reliability of downstream analyses. To address this issue, numerous EEG artifact removal methods have been developed, including both traditional denoising techniques and deep learning-based approaches. Traditional EEG denoising methods have long served as the primary solutions for artifact removal. Representative approaches include filtering, regression, and blind source separation. Although these methods have demonstrated effectiveness in specific scenarios, they suffer from several inherent limitations. Filtering assumes that artifacts and EEG signals can be separated in the frequency domain, but many artifacts, such as EOG and EMG, overlap with EEG spectra, which may lead to the loss of valuable neural information. Regression methods require high-quality artifact references to estimate and subtract contaminations, limiting their effectiveness in reference-free scenarios. Blind source separation can remove artifacts without external references, but it typically requires the number of EEG channels to exceed the number of sources, restricting its application in single- or low-channel EEG recordings. Deep learning-based EEG denoising methods address these limitations effectively. First, they learn the nonlinear mapping between contaminated and clean EEG directly from data in an end-to-end manner. This approach does not rely on assumptions about spectral separability, thereby preserving neural activity more completely. Second, the reference information is incorporated during the training phase, allowing the trained model to perform artifact removal independently without external references. Third, deep learning models can be flexibly designed to accommodate various recording setups, achieving robust denoising for both high-density and single-channel EEG. Collectively, these advantages enable deep learning-based methods to overcome the main challenges of traditional approaches, providing more accurate and reliable EEG signal recovery. The superior denoising performance of deep learning-based EEG denoising methods has attracted increasing attention in EEG artifact removal research. As a result, many deep learning-based denoising methods have been developed and successfully applied in neural engineering areas. However, a systematic review of the techniques and applications in this field is still lacking. To address this gap, this paper reviews recent advances in deep learning-based EEG denoising from four perspectives: technical principle, benchmark dataset, denoising model, and evaluation method. Representative applications in neural signal analysis and BCI decoding are also summarized. Furthermore, the advantage, existing challenge, and future research direction of deep learning-based EEG denoising are discussed. This review aims to provide valuable theoretical insights and technical guidance for researchers. It is also expected to promote further advances and broader applications of deep learning-based EEG denoising techniques.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To compare the clinical efficacies of extrapleural internal fixation and transthoracic internal fixation in the treat-ment of thoracic tuberculosis.Methods A total of 70 patients with thoracic tuberculosis(T4 to T10)who were admitted to our hospital from June 2018 to June 2023 were enrolled,and their clinical data were retrospectively analyzed.The 35 patients treated with extrapleural internal fixation were included in the extrapleural group,and the other 35 patients treated with transthoracic internal fixation were included in the transthoracic group.The operation time,intraoperative blood loss,bone graft fusion time,kyphotic angle before and after operation,visual analogue scale(VAS)and Oswestry disability index(ODI)scores after operation,postoperative complications and recurrence were compared between the two groups.Results Compared with the transthoracic group,the operation time and bone graft fusion time were significantly shortened,and the intraoperative blood loss was significantly reduced in the extrapleural group,with statistically significant differences(P<0.05).The postoperative kyphotic angles of the two groups were smaller than those before operation,the postoperative kyphotic angle of the extrapleural group was smaller than that of the transthoracic group,and the differences were statistically significant(P<0.05).The VAS score 7 days after operation of the extrapleural group was lower than that of the transthoracic group,and the difference was statistically significant(P<0.05).The ODI score 1 month after operation of the extrapleural group was lower than that of the transthoracic group,and the difference was statistically significant(P<0.05).The incidence of postoperative complications in the extrapleural group(0)was lower than that in the transthoracic group(34.28%),and the difference was statistically significant(P<0.05).Conclusion Extrapleural internal fixation has the advantages of short time,less bleeding and less trauma in the treatment of thoracic tuberculosis,but it is difficult to completely remove the lesions.Transthoracic internal fixation can completely remove the lesion,but the surgical trauma is large.The choice of clinical operation plan should be comprehensively considered according to the specific condition of the patients,the location of the lesion,and the condition of the lung,so as to achieve the best treatment effect.

Objective To verify the efficacy of a domestic human DNA quantification kit based on real-time fluorescence quantitative PCR in detecting the total human DNA concentration,male DNA concen-tration in mixed male/female DNA samples,the degree of DNA degradation and inhibitor tolerance.Methods Samples with different concentrations,different male/female ratios,different concentrations of inhibitors,and different degradation degrees were tested using the domestic human DNA quantification kit based on real-time fluorescence quantitative PCR.This kit was compared with a similar product on the market and was applied to the detection of DNA from real cases.Results This human DNA quan-tification kit can effectively detect human DNA as low as 0.001 65 ng/μL,and 6.25 pg/μL of male DNA in mixed samples with a male-to-female ratio of 1∶15 000.Even when the sample contains as high as 400 ng/μL of humic acid or 1 000 μmol/L of hemin alone,the DNA concentration can still be accurately detected.The degradation index can effectively characterize the degradation degree of the sample.This kit has been successfully applied in forensic practice.Conclusion This human DNA quan-tification kit is accurate and reliable in detection.It can accurately reflect the degradation of DNA and inhibitor tolerance.It has good performance in quantitative accuracy,determination of the male/female ratio in mixed samples,and inhibitor tolerance.It has application potential in forensic case examination.

Hepatocellular carcinoma(HCC),which is essentially primary liver cancer,is closely related to CD8+T cell immune infiltration and immune suppression.We constructed a CD8+T cells related risk score model to pre-dict the prognosis of HCC patients and provided therapeutic guidance based on the risk score.Using integrated bulk RNA sequencing(RNA-seq)and single-cell RNA sequencing(scRNA-seq)datasets,we identified stable CD8+T cell signatures.Based on these signatures,a 3-gene risk score model,comprised of KLRB1,RGS2,and TN-FRSF1B was constructed.The risk score model was well validated through an independent external validation co-hort.We divided patients into high-risk and low-risk groups according to the risk score and compared the differ-ences in immune microenvironment between these two groups.Compared with low-risk patients,high-risk patients have higher M2-type macrophage content(P＜0.0001)and lower CD8+T cells infiltration(P＜0.0001).High-risk patients predict worse response to immunotherapy treatment than low-risk patients(P＜0.01).Drug sensitivity a-nalysis shows that PI3K-β inhibitor AZD6482 and TGFβRII inhibitor SB505124 may be suitable therapies for high-risk patients,while the IGF-1R inhibitor BMS-754807 or the novel pyrimidine-based anti-tumor metabolic drug Gemcitabine could be potential therapeutic choices for low-risk patients.Moreover,expression of these 3-gene mod-el was verified by immunohistochemistry.In summary,the establishment and validation of a CD8+T cell-derived risk model can more accurately predict the prognosis of HCC patients and guide the construction of personalized treatment plans.

The European Society of Cardiology (ESC) released the "2024 ESC guidelines for the management of elevated blood pressure and hypertension" on August 30, 2024. This guideline updates the 2018 "Guidelines for the management of arterial hypertension." One notable update is the introduction of the concept of "elevated blood pressure" (120-139/70-89 mm Hg). Additionally, a new systolic blood pressure target range of 120-129 mm Hg has been proposed for most patients receiving antihypertensive treatment. The guideline also includes numerous additions or revisions in areas such as non-pharmacological interventions and device-based treatments for hypertension. This article interprets the guideline's recommendations on definition and classification of elevated blood pressure and hypertension, and cardiovascular disease risk assessment, diagnosing hypertension and investigating underlying causes, preventing and treating elevated blood pressure and hypertension. We provide a comparison interpretation with the 2018 "Guidelines for the management of arterial hypertension" and the "2017 ACC/AHA guideline on the prevention, detection, evaluation, and management of high blood pressure in adults."

Objective:A retrospective analysis was conducted on the clinical characteristics and polysomnography (PSG) features of patients with obstructive sleep apnea (OSA) of different ages.Methods:From January 2015 to March 2024, the patients who underwent overnight PSG monitoring at the Sleep Respiratory Disease Diagnosis and Treatment Center, Department of Otolaryngology, Head and Neck Surgery, Sixth Medical Center of the PLA General Hospital were sequentially enrolled.A total of 4 396 patients[aged from 18 to 97(46.04±12.60)years] with OSA who met the criteria were finally enrolled and divided into the youth group (18-44 years old, n=2 099), middle-aged group (45-59 years old, n=1 641), and elderly group (≥60 years old, n=656).The differences in general condition, Epworth sleepiness Scale (ESS) score, rapid eye movement sleep (REM) sleep time in total sleep time, micro-awakening index, apnea hypopnea index (AHI), minimum oxygen saturation at night (LSpO 2), oxygen hypoxia index (ODI) and so on were compared.Multivariate Logistic regression was used to analyze the relationship between age stratification and different severity of OSA (mild 5≤AHI≤15, moderate 1530, Times per hour). Results:The neck circumference [(39.11±3.71) cm], body mass index [BMI, (26.63±3.70) kg/m2], total sleep time [(386.13±66.09) min], the percentage of deep sleep in total sleep time [(3.05±4.80)%], the percentage of REM sleep time in total sleep time [(16.73±6.83)%], apnea-hypopnea index [AHI, (31.17±19.20) events/h], oxygen desaturation index [ODI, (46.57±33.54) events/h], microarousal index [(14.82±12.27) events/h], and Epworth Sleepiness Scale (ESS) score (8.29±5.92) in the elderly group were all lower than those in the young group [neck circumference (41.36±3.37) cm, BMI (28.55±4.21) kg/m2, total sleep time [(424.67±62.21) min], the percentage of deep sleep in total sleep time (5.89±6.79)%, the percentage of REM sleep time in total sleep time (17.95±6.67)%, AHI (39.55±27.89) events/h, ODI (61.88±34.60) events/h, microarousal index (22.77±19.31) events/h, ESS score (9.63±5.82)] and the middle-aged group [neck circumference (40.75±3.59) cm, BMI (27.89±3.55)kg/m2, total sleep time [(410.98±63.02)min], the percentage of deep sleep in total sleep time (3.59±5.11)%, the percentage of REM sleep time in total sleep time (17.47±6.63)%, AHI (36.01±23.63) events/h, ODI (57.20±34.75) events/h, microarousal index (19.23±15.59) events/h, ESS score (9.98±6.11)], with F values of 102.62, 62.15, 95.87, 95.94, 8.71, 29.60, 49.72, 59.11, and 19.03, respectively, and all P values were <0.001. The proportion of females [29.57% (94/656)], the proportion of patients with hypertension [37.20% (244/656)], and the nocturnal LSpO 2 [(79.09±9.88)%] in the elderly group were all higher than those in the young group [proportion of females [6.48% (136/2 099)], proportion of patients with hypertension 18.10% (380/2 099), nocturnal LSpO 2(75.19±12.90)%] and the middle-aged group [proportion of females [15.84%(260/1 641)], proportion of patients with hypertension 33.09% (543/1 641), nocturnal LSpO 2(76.15±12.44)%], with F values of 242.62, 150.90, and 25.05, respectively, and all P values were <0.001.There were no significant differences in neck circumference, percentage of REM sleep time in total sleep time, AHI and LSpO 2 at night between young and middle-aged groups ( P>0.05). After adjusting for gender, neck circumference, BMI, and hypertension confounders, the risk of severe OSA in the older group was increased by 27.4% compared with the younger group ( OR=1.274, 95% CI=1.036-1.566, P<0.05). Further stratified analysis showed that neck circumference and BMI were independent factors for severe OSA in the young and middle-aged groups ( P<0.01), while, only neck circumference was independently associated with severe OSA in the elderly group (OR=1.119, 95% CI=1.039-1.207, P<0.01). Conclusion:The severity of OSA in young and middle-aged patients is more serious than that in elderly patients. Obesity is an important factor affecting the degree of OSA in young and middle-aged patients. After controlling for confounding factors such as obesity, the risk of severe OSA in elderly patients is higher than that in young patients, which is considered to be related to factors such as pharyngeal collapse and relaxation of pharyngeal muscles.

To enhance the therapeutic efficacy of the baicalin-berberine complex(BA-BBR) in the treatment of ulcerative colitis(UC), BA-BBR nanocrystal microspheres(BA-BBR NC MS) were prepared using the dropping method. The microspheres were characterized in terms of morphology, particle size, differential scanning calorimetry(DSC), and powder X-ray diffraction(XRD). The release profiles of BA and BBR from the microspheres were measured, and the drug release mechanism was investigated. A rat model of UC was induced by 5% dextran sodium sulfate(DSS) and treated continuously for 7 days to evaluate the therapeutic effects of different formulations. The results showed that the prepared BA-BBR MS and BA-BBR NC MS were uniform gel spheres with particle sizes of(1.77±0.16) mm and(1.67±0.08) mm, respectively. After drying, the gels collapsed inward and exhibited a rough surface. During the preparation process, the BA-BBR nanocrystals(BA-BBR NC) were uniformly encapsulated within the microspheres. The release profiles of the microspheres followed a first-order kinetic model, and the 12-hour cumulative release of BA and BBR from BA-BBR NC MS was higher than that from BA-BBR MS. Compared with BA-BBR, BA-BBR NC, and BA-BBR MS, BA-BBR NC MS further alleviated UC symptoms in rats, most significantly reducing the levels of TNF-α, IL-1β, IL-6, and MPO, while increasing the level of IL-4 in colon tissues. These results indicate that BA-BBR NC MS, based on a "nano-in-micro" design, can deliver BA-BBR to the intestine and exert significant therapeutic effects in a UC rat model, suggesting it as a promising new strategy for the treatment of UC.
Animals ; Colitis, Ulcerative/metabolism* ; Rats ; Nanoparticles/chemistry* ; Microspheres ; Male ; Berberine/administration & dosage* ; Flavonoids/administration & dosage* ; Rats, Sprague-Dawley ; Drugs, Chinese Herbal/administration & dosage* ; Humans ; Particle Size ; Tumor Necrosis Factor-alpha/immunology* ; Drug Liberation ; Drug Compounding

Nuclear receptor co-activator 4 (NCOA4) acts as a selective cargo receptor that binds to ferritin, a cytoplasmic iron storage complex. By mediating ferritinophagy, NCOA4 regulates iron metabolism and releases free iron in the body, thus playing a crucial role in a variety of biological processes, including growth, development, and metabolism. Recent studies have shown that NCOA4-mediated ferritinophagy is closely associated with the occurrence and development of iron metabolism-related diseases, such as liver fibrosis, renal cell carcinoma, and neurodegenerative diseases. In addition, a number of clinical drugs have been identified to modulate NCOA4-mediated ferritinophagy, significantly affecting disease progression and treatment efficacy. This paper aims to review the current research progress on the role of NCOA4-mediated ferritinophagy in related diseases, in order to provide new ideas for targeted clinical therapy.
Humans ; Nuclear Receptor Coactivators/physiology* ; Ferritins/metabolism* ; Animals ; Neurodegenerative Diseases/metabolism* ; Iron/metabolism* ; Autophagy/physiology* ; Liver Cirrhosis/metabolism* ; Carcinoma, Renal Cell/metabolism* ; Kidney Neoplasms/physiopathology*