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.

PURPOSE: The retear rate of rotator cuff (RC) after surgery is high, and the rapid and functional enthesis regeneration remains a challenge. Whether acellular amniotic membrane (AAM) helps to promote the healing of tendon to bone and which treatment is better are both unclear. The study aims to investigate the effect of AAM on the healing of RC and the best treatment for RC repair. METHODS: Thirty-three Sprague Dawley rats underwent RC transection and repair using microsurgical techniques and were randomly divided into the suturing repair only (SRO) group (n = 11), the AAM overlaying (AOL) group (n = 11), and the AAM interposition (AIP) group (n = 11), respectively. Rats were sacrificed at 4 weeks, then examined by subsequent micro-CT, and evaluated by histologic and biomechanical tests. The statistical analyses of one-way ANOVA or Kruskal-Wallis test were performed using with SPSS 23.0. A p < 0.05 was considered a significant difference. RESULTS: AAM being intervened between tendon and bone (AIP group) or overlaid over tendon to bone junction (AOL group) in a rat model, promoted enthesis regeneration, increased new bone and cartilage generation, and improved collagen arrangement and biomechanical properties in comparison with suturing repair only (SRO group) (AOL vs. SRO, p < 0.001, p = 0.004, p = 0.003; AIP vs. SRO, p < 0.001, p < 0.001, p < 0.001). Compared with the AOL group, the AIP group had better results in micro-CT evaluation, histological score, and biomechanical testing (p = 0 0.039, p = 0.011, p = 0.003, respectively). CONCLUSION In the RC repair model, AAM enhanced regeneration of the tendon to bone junction. This regeneration was more effective when the AAM was intervened at the tendon to bone interface than overlaid above the tendon to bone junction.
Animals ; Rats, Sprague-Dawley ; Rotator Cuff Injuries/surgery* ; Amnion/transplantation* ; Rats ; Wound Healing ; Rotator Cuff/surgery* ; Male ; X-Ray Microtomography ; Tendons/surgery* ; Biomechanical Phenomena

OBJECTIVE: To investigate the prognostic value of ¹⁸ F-deoxyglucose (FDG) PET/CT metabolic parameters combined with clinicopathological features for newly diagnosed diffuse large B-cell lymphoma (DLBCL) before treatment, and analyze the relationship between tumor metabolic volume (MTV), total lesion glycolysis (TLG) and clinicopathological features. METHODS: The clinical data of 120 patients with pathologically confirmed DLBCL were retrospectively analyzed and ¹⁸F-FDG PET/CT was performed 1 week before treatment. The metabolic parameters including SUVmax, SUVmean, tumor-to-blood standardized uptake value ratio (TBR), tumor-to-liver standardized uptake value ratio (TLR) were obtained. MTV and TLG of the lesions were obtained with 41% of SUVmax as the threshold, and the correlation of MTV and TLG with clinicopathological features were analyzed. Progression-free survival (PFS) was calculated by follow-up for 6-153 months. Receiver operating characteristic (ROC) curve, chi-square test, Kaplan-Meier test, log-rank test and Cox proportional hazards model were used to analyze the date. RESULTS: The optimum cut-off values of the SUVmax, MTV, TLG, TBR and TLR for predicting tumor progression were 22.25, 256.05, 5 232.67, 12.97 and 10.60, respectively. The patients were divided into two groups according to the above cut-off values, respectively. Kaplan-Meier survival analysis showed that there were statistically significant differences in PFS between the two group (all P <0.05). The MTV and TLG values were correlated with NCCN-IPI score, Ann Arbor stage, serum lactate dehydrogenase level, and C-MYC, BCL-2, BCL-6 gene rearrangement (all P <0.05). Univariate analysis showed that NCCN-IPI score >3, C-MYC, BCL-2, BCL-6 gene rearrangement positive, SUVmax≥22.25, MTV≥256.05 cm³, TLG≥5 232.67 g and TBR≥12.97 were adverse factors for prognosis (HR: 1.949-5.759, all P <0.05). Multivariate Cox regression analysis showed that C-MYC, BCL-2 gene rearrangement positive and TLG≥5 232.67 g were all independent risk factors affecting PFS (HR: 4.660, 3.350, 4.031, all P <0.05). CONCLUSION The ¹⁸F-FDG PET/CT metabolic parameters SUVmax, MTV, TLG, TBR and TLR can be used as important indicators to predict PFS of DLBCL patients, and combining clinicopathological features can better predict the prognosis of patients.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Fluorodeoxyglucose F18 ; Positron Emission Tomography Computed Tomography ; Prognosis ; Retrospective Studies ; Male ; Female ; Middle Aged ; Adult

Medical institutions, with their clinical practice foundation and abundant human use experience data, have become important carriers for the inheritance and innovation of traditional Chinese medicine(TCM) and the "cradles" of the preparation of new TCM. To effectively promote the transformation of new TCM originating from the TCM clinical practice in medical institutions and establish an effective evaluation index system for the transformation of new TCM conforming to the characteristics of TCM, consensus experts adopted the literature research, questionnaire survey, Delphi method, etc. By focusing on the policy and technical evaluation of new TCM originating from the TCM clinical practice in medical institutions, a comprehensive evaluation from the dimensions of drug safety, efficacy, feasibility, and characteristic advantages was conducted, thus forming a comprehensive evaluation system with four primary indicators and 37 secondary indicators. The expert consensus reached aims to encourage medical institutions at all levels to continuously improve the high-quality research and development and transformation of new TCM originating from the TCM clinical practice in medical institutions and targeted at clinical needs, so as to provide a decision-making basis for the preparation, selection, cultivation, and transformation of new TCM for medical institutions, improve the development efficiency of new TCM, and precisely respond to the public medication needs.
Medicine, Chinese Traditional/standards* ; Humans ; Consensus ; Drugs, Chinese Herbal/therapeutic use* ; Surveys and Questionnaires

Objective:Based on the background of high-quality development,we analyze the operational efficiency of traditional Chinese medicine(TCM)hospitals in China's Yangtze River Economic Belt in 2021 and explore the impact of external environmental factors on operational efficiency,so as to provide a reference for promoting the high-quality development of TCM hospitals in the Yangtze River Economic Belt.Methods:The three-stage DEA model was used to analyze the operational efficiency of TCM hospitals in 11 provinces and cities in the Yangtze River Economic Zone in China in 2021.Results:After three-stage DEA analysis,the values of comprehensive efficiency,pure technical efficiency and scale efficiency of TCM hospitals in China's Yangtze River Economic Belt are 0.976,0.986 and 0.990,respectively.5 provinces and cities,Shanghai,Jiangsu,Hunan,Chongqing and Guizhou,are efficient before and after the adjustment,and the comprehensive efficiency of Zhejiang,Anhui,Hubei,Jiangxi,Sichuan and Yunnan have increased compared with that before the adjustment.Ranking of the average value of the comprehensive efficiency of TCM hospitals operation in the three major city clusters of the Yangtze River Economic Belt after adjustment:Chengdu-Chongqing city cluster(0.998)>city cluster in the Yangtze River Delta(0.964)>city cluster in the middle reaches of the Yangtze River(0.962).Conclusion:The operational efficiency of TCM hospitals in the Yangtze River Economic Zone has been underestimated,and the comprehensive efficiency is mainly affected by scale efficiency;there are differences in the operational efficiency of TCM hospitals in the three major urban agglomerations,and balanced development is needed between regions;the operational efficiency of TCM hospitals is affected by the external environment,and it is necessary to improve the external environment;it is necessary to strengthen the construction of digital and informatization of TCM,and to pay attention to the role of talents in TCM,so as to promote the high-quality development of TCM hospitals.

Objective:Based on the background of high-quality development,we analyze the operational efficiency of traditional Chinese medicine(TCM)hospitals in China's Yangtze River Economic Belt in 2021 and explore the impact of external environmental factors on operational efficiency,so as to provide a reference for promoting the high-quality development of TCM hospitals in the Yangtze River Economic Belt.Methods:The three-stage DEA model was used to analyze the operational efficiency of TCM hospitals in 11 provinces and cities in the Yangtze River Economic Zone in China in 2021.Results:After three-stage DEA analysis,the values of comprehensive efficiency,pure technical efficiency and scale efficiency of TCM hospitals in China's Yangtze River Economic Belt are 0.976,0.986 and 0.990,respectively.5 provinces and cities,Shanghai,Jiangsu,Hunan,Chongqing and Guizhou,are efficient before and after the adjustment,and the comprehensive efficiency of Zhejiang,Anhui,Hubei,Jiangxi,Sichuan and Yunnan have increased compared with that before the adjustment.Ranking of the average value of the comprehensive efficiency of TCM hospitals operation in the three major city clusters of the Yangtze River Economic Belt after adjustment:Chengdu-Chongqing city cluster(0.998)>city cluster in the Yangtze River Delta(0.964)>city cluster in the middle reaches of the Yangtze River(0.962).Conclusion:The operational efficiency of TCM hospitals in the Yangtze River Economic Zone has been underestimated,and the comprehensive efficiency is mainly affected by scale efficiency;there are differences in the operational efficiency of TCM hospitals in the three major urban agglomerations,and balanced development is needed between regions;the operational efficiency of TCM hospitals is affected by the external environment,and it is necessary to improve the external environment;it is necessary to strengthen the construction of digital and informatization of TCM,and to pay attention to the role of talents in TCM,so as to promote the high-quality development of TCM hospitals.

Eighteen compounds were isolated from the methanol extract of the fruits of Litsea cubeba by silica gel, ODS, Sephadex LH-20 column chromatography, semi-preparative RP-HPLC, chiral HPLC and recrystallization. Their structures were elucidated by spectroscopic analyses and by comparison with reported spectroscopic data and physicochemical properties, and the absolute configurations of the enantiomers were established by experimental and calculated electronic circular dichroism spectra. These compounds were identified as (+)-(R)-4-hydroxypiperitenone (1a), (-)-(S)-4-hydroxypiperitenone (1b), (3S,4S,6R)-3,6-dihydroxy-1-menthene (2), (4S,5R)-4-hydroxy-5-isopropyl-2-methylcyclohex-2-en-1-one (3), (R)-6-hydroxy-3-(2-hydroxypropan-2-yl)-6-methylcyclohex-2-enone (4), (4S,6R)-4-hydroxy-6-isopropyl-3-methylcyclohex-2-enone (5), (1R,3S,4R)-3-hydroxy isopulegol (6), subamone (7), (6S)-3,7-dimethyl-7-hydroxy-2(Z)-octen-6-olide (8), (6S)-6,7-dihydroxy-3,7-dimethyloct-2(Z)-enoate (9), holostylactone (10), sesamin (11), dimethylmatairesinol (12), p-hydroxybenzoylcarbinol (13), syringaldehyde (14), p-hydroxybenzaldehyde (15), 4-hydroxy-3-methoxybenzaldehyde (16), 5,4ʹ-dihydroxy-7-methoxyflavone (17). Among them, compounds 1a and 1b were a pair of new monoterpenoid enantiomers, 8 and 9 were new natural products, 2-7, 10, 11 and 17 were isolated from Litsea genus for the first time. The in vitro anti-inflammatory effects of compounds 1-17 were evaluated using lipopolysaccharide-stimulated RAW264.7 cells, the results showed that compound 14 exhibited significant anti-inflammatory activity with NO inhibitory rate of 66.27% at a concentration of 40 μmol·L^-1.

Ritlecitinib is an inhibitor that acts on Janus kinase 3 and the hepatocellular carcinoma kinase family.In June 2023,the FDA approved Ritlecitinib for the treatment of severe alopecia areata in patients aged 12 years and above.Multiple clinical studies have observed hair regeneration in patients after using Ritlecitinib,which is generally safe and well tolerated during use.This article introduces its pharmacological effects,pharmacokinetics,clinical research,safety,and usage and dosage.

Here,5 important pathogens carried by ticks in Maanshan City,Anhui Province,China were identified.In to-tal,642 ticks were collected from 13 villages around Maanshan City and identified by morphological and mitochondrial COI genes.The 16S rRNA gene of Francisella tularensis,ssrA gene of Bartonella,16S rRNA,ompA and ompB genes of Rickett-sia,16S rRNA and gltA genes of Anaplasma,and groEL and rpoB genes of Coxiella were sequenced.Reference sequences were retrieved from a public database.Phylogenetic trees were constructed with MEG A1 1.0 software.In total,36 Rickettsiae isolates were detected in 640 Haemaphysalis longicornis ticks,which included 20 isolates of Rickettsia heilongjian-gensis,16 of Candidatus Rickettsia jingxinensis,2 of Ana-plasma bovis,and 186 of Coxiella-like endosymbiont.R.hei-longjiangensis HY2 detected in this study and Anhui B8 strain,Ca.R.jingxinensis QL3 and those from Shanxi Prov-ince and Jiangsu Province,A.bovis JX4 and those from Shanxi Province were clustered on the same branch.Overall,17 ticks had combined infections and none of the 5 bacteria were detected in two Amblyomma testudinarium ticks.This is the first report of Ca.R.jingxinensis detected in H.longicornis ticks from Anhui Province.It is recommended that the two types of Rickettsia that cause spotted fever and A.bovis should be reported to local health authorities to initiate appropriate prevention and control measures.