Objectives: . This study aimed to investigate the regulatory functions of gamma-aminobutyric acid (GABA)ergic neural circuits from the inferior colliculus (IC) to the medial geniculate body (MGB) in salicylate-induced tinnitus. Methods: . Mice were treated with salicylate to induce tinnitus, and tinnitus-like behaviors were evaluated via gap prepulse inhibition of acoustic startle. Using combined viral tracing methodologies, we identified and mapped the pathways and connections from the IC to the MGB. Furthermore, we employed Gq-coupled human M3 designer receptors exclusively activated by designer drugs (DREADDs) and Gi-coupled human M4 DREADDs to achieve targeted excitation or suppression of GABAergic neurons in the IC and MGB. Following the administration of clozapine N-oxide, which binds to these receptors, we modulated these neural circuits to assess their impact on tinnitus severity in a mouse model. Results: . Our findings demonstrated that mice exposed to salicylate exhibited tinnitus-like behaviors. GABAergic neurons projecting retrogradely from the MGB to the IC were primarily concentrated in the external nucleus of the IC. After clozapine N-oxide administration, chemogenetic activation of IC-MGB GABAergic neurons aggravated salicylate-induced tinnitus. Additionally, activation of GABAergic neurons between the IC and MGB induced the perception of tinnitus even without salicylate. However, chemogenetic inhibition of the IC-MGB GABAergic circuit did not reverse salicylate-induced tinnitus. Conclusion . These findings suggest that activation of the IC-MGB GABAergic neural circuit may contribute to tinnitus generation through a mechanism distinct from that of salicylate-induced tinnitus. This study provides novel insights into the mechanisms underlying tinnitus.

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.

ObjectiveUlcerative colitis is a prevalent immunoinflammatory disease. Th17/Treg cell imbalance and gut microbiota dysregulation are key factors in ulcerative colitis pathogenesis. The actin cytoskeleton contributes to regulating the proliferation, differentiation, and migration of Th17 and Treg cells. Wdr63, a gene containing the WD repeat domain, participates in the structure and functional modulation of actin cytoskeleton. Recent research indicates that WDR63 may serve as a regulator of cell migration and metastasis via actin polymerization inhibition. This article aims to explore the effect of Wdr63 deletion on Th17/Treg cells and ulcerative colitis. MethodsWe constructed Wdr63^-/- mice, induced colitis in mice using dextran sulfate sodium salt, collected colon tissue for histopathological staining, collected mesenteric lymph nodes for flow cytometry analysis, and collected healthy mouse feces for microbial diversity detection. ResultsCompared with wild-type colitis mice, Wdr63^-/- colitis mice had a more pronounced shortening of colonic tissue, higher scores on disease activity index and histological damage index, Treg cells decreased and Th17 cells increased in colonic tissue and mesenteric lymph nodes, a lower level of anti-inflammatory cytokine IL-10, and a higher level of pro-inflammatory cytokine IL-17A. In addition, WDR63 has shown positive effects on maintaining intestinal microbiota homeostasis. It maintains the balance of Bacteroidota and Firmicutes, promoting the formation of beneficial intestinal bacteria linked to immune inflammation. ConclusionWdr63 deletion aggravates ulcerative colitis in mice, WDR63 inhibits colonic inflammation likely by regulating Th17/Treg balance and maintains intestinal microbiota homeostasis.

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

The dried mature peel of Citrus reticulata, a plant in the Rutaceae family and its cultivated varieties, is a commonly used Chinese medicinal material known as Chenpi(Citri Reticulatae Pericarpium). It is rich in nutritional components and medicinal value, with pharmacological effects including relieving cough and eliminating phlegm, strengthening the spleen and drying dampness, protecting the liver and benefiting the stomach, tonifying Qi, and calming the mind. Huanglongbing(HLB), also known as Citrus Huanglongbing, is a destructive disease in citrus production that seriously threatens the development of the citrus industry. HLB causes symptoms such as the inability of Rutaceae plants to produce mature fruit, gradual weakening of the tree, and eventual death, posing a significant threat to the yield and quality of Chenpi. Due to the uneven distribution of the HLB pathogen in infected plants, accurate detection of the pathogen requires the collection of a large number of plant samples. Current sample pretreatment methods, such as traditional extraction methods and commercial extraction kits, are time-consuming and involve multiple steps, which significantly increase the difficulty and workload of HLB diagnosis and have become a bottleneck in HLB detection. In this study, a rapid high-throughput detection method combining alkali lysis and TaqMan qPCR was developed. This method allows the pretreatment of multiple samples within 5 min, and the entire detection process can be completed within 45 min, with a detection limit of 6.67 fg·μL~(-1). The alkali lysis method and commercial kits were used for parallel detection of field-collected citrus samples, and the results showed no significant difference. The sample pretreatment method established in this study is characterized by low cost, simplicity, and high efficiency. Combined with TaqMan qPCR, it can provide technical support for early and on-site diagnosis of HLB. This method is of great significance for disease prevention and control in the citrus industry and is expected to help improve the yield and quality of citrus medicinal materials.
Citrus/microbiology* ; Plant Diseases/microbiology* ; Rhizobiaceae/physiology* ; High-Throughput Screening Assays/methods* ; Liberibacter/physiology*

Objective: To evaluate the feasibility of dynamic contrast-enhanced MRI (DCE-MRI) in differentiating tumor deposits (TDs) from metastatic lymph nodes (MLNs) in rectal cancer. Materials and Methods: A retrospective analysis was conducted on 70 patients with rectal cancer, including 168 lesions (70 TDs and 98 MLNs confirmed by histopathology), who underwent pretreatment MRI and subsequent surgery between March 2019 and December 2022. The morphological characteristics of TDs and MLNs, along with quantitative parameters derived from DCE-MRI (K trans , kep, and v e) and DWI (ADCmin, ADCmax, and ADCmean), were analyzed and compared between the two groups.Multivariable binary logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the diagnostic performance of significant individual quantitative parameters and combined parameters in distinguishing TDs from MLNs. Results: All morphological features, including size, shape, border, and signal intensity, as well as all DCE-MRI parameters showed significant differences between TDs and MLNs (all P < 0.05). However, ADC values did not demonstrate significant differences (all P > 0.05). Among the single quantitative parameters, v e had the highest diagnostic accuracy, with an area under the ROC curve (AUC) of 0.772 for distinguishing TDs from MLNs. A multivariable logistic regression model incorporating short axis, border, v e, and ADC mean improved diagnostic performance, achieving an AUC of 0.833 (P = 0.027). Conclusion The combination of morphological features, DCE-MRI parameters, and ADC values can effectively aid in the preoperative differentiation of TDs from MLNs in rectal cancer.

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 investigate the clinical efficacy and safety of facilitated percutaneous coronary intervention(PCI)with half-dose recombinant staphylokinase(r-SAK)in patients with ST-segment elevation myocardial infarction(STEMI)who are expected to undergo PCI within 120 minutes.Methods From October 2021 to August 2022,a total of 200 STEMI patients in eight centers were included and randomly assigned in a 1﹕1 ratio to either r-SAK group or control group.Patients received loading doses of aspirin and ticagrelor and intravenous heparin and were randomized to receive an intravenous bolus of either 5 mg r-SAK or normal saline prior to PCI.The outcomes were set as ST-segment resolution(STR)at 60-90 minutes after PCI,the proportion and transition of pathological Q waves on the 5th day after PCI,and the proportion of high-sensitivity cardiac troponin T(hs-cTnT)peaking within 12 hours of onset.The safety outcome was major bleeding events defined as Bleeding Academic Research Consortium(BARC)≥type 3 bleeding during hospitalization.Results Compared with the control group,the r-SAK group had a higher proportion of STR≥70%within 60-90 minutes after PCI(58.3%vs.40.3%,P=0.009);a lower proportion of pathological Q waves(59.1%vs.74.1%,P=0.040);a lower rate of Q wave progression(14.8%vs.43.2%,P＜0.001);a higher rate of Q wave disappearance(12.5%vs.3.7%,P=0.027);and a higher proportion of hs-cTnT peaking within 12 hours of symptom onset[31/40(77.5%)vs.17/33(51.5%),P=0.027].Regarding the safety outcome,no significant difference in BARC≥type 3 bleeding was found between the two groups during hospitalization(P＞0.05).Conclusions For STEMI patients who were expected to undergo primary PCI within 120 minutes of symptom onset,the facilitated PCI with half-dose r-SAK significantly increased the proportion of STR≥70%at 60-90 minutes after PCI,reduced the formation of pathological Q waves,and shortened the time to peak hs-cTnT,without increasing the risk of bleeding,which should be an alternative reperfusion strategy worthy of further study.

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.