ObjectiveTo improve the efficacy of Astragalus membranaceus (Fisch.) Bunge (A. membranaceus, Huang Qi), and to further develop and utilize it, fermentation technology was applied to the stem and leaf of A. membranaceus to enhance its immune function.MethodsIn this study, we fermented A. membranaceus stem and leaf (ASL) with probiotics and investigated its immune function. Firstly, we screened suitable strains for ASL fermentation and optimized the fermentation process. Secondly, we determined the antioxidant capacity of fermented ASL and its effect on inflammation in mouse monocyte-macrophage cell. Finally, the immunocompromised mice were treated with fermented ASL to investigate the changes in their immune ability.ResultsAmong the 10 selected probiotics, Lactobacillus plantarum was the most suitable strain for ASL fermentation. After optimization of the fermentation process, the content of saponins in fermented ASL was significantly increased. The fermented ASL exhibited strong anti-inflammatory and antioxidant activities in vitro. The in vivo immune efficacy improved by promoting the development of the spleen and thymus, as well as raising the immunoglobulin M, tumor necrosis factor-α, and interleukin-1β levels of in the serum.ConclusionThis study contributes to developing the non-medicinal parts of A. membranaceus, expands its medicinal resources, highlights the potential of fermentation technology to enhance these parts, and provides a reference for further development. Based on this approach, we can promote using non-medicinal parts of herbal medicines, minimize drug waste, and offer a reference for developing non-medicinal components in Chinese herbal medicines.

Objective To evaluate the role of distortion product otoacoustic emissions (DPOAE) testing in evaluating early hearing loss among noise-exposed workers. Methods A total of 174 noise-exposed workers in a metal shipbuilding enterprise were selected as the research subjects by the convenience sampling method. Pure tone audiometry (PTA), DPOAE and the level of noise exposure were conducted on the workers. The rank correlation analysis was used to analyze the correlation between DPOAE amplitude and PTA threshold. The multilevel model was used to analyze the effects of gender, age, noise exposure intensity, cumulative noise exposure (CNE), hearing loss classification and PTA threshold on DPOAE results. Results At the frequencies of 0.50, 1.00, 2.00, 3.00, 4.00, 6.00 and 8.00 kHz, the DPOAE amplitude was negatively correlated with the PTA threshold (rank correlation coefficients were -0.12, -0.48, -0.47, -0.18, -0.23, -0.44, -0.19, respectively, all P<0.01). At the most frequencies, DPOAE amplitude was negatively correlated with age and CNE (all P<0.05). The results of multilevel model analysis showed that there were significant differences in DPOAE amplitudes at certain frequencies across gender, age, noise intensity, CNE, and hearing loss classification (all P<0.05). Significant differences in DPOAE responses were found among different CNE and hearing loss groups (all P<0.01). Conclusion DPOAE testing can objectively reflect the hearing status of noise-exposed workers and could be considered for inclusion in routine hearing monitoring to facilitate early detection of noise-induced hearing loss.

Objective To investigate the changes in motor symptoms and cognitive levels in α-synuclein A53T transgenic mice at different months of age and possible mechanisms.Methods The α-synuclein A53T transgenic mice and wild C57/BL6J mice,aged 6 months,were selected.The open field test and the rotarod test were used to observe the motor function and emotional response of mice;fear conditioning and the novel object recognition test were used to observe the cognitive function of mice;Western blotting was used to measure the expression level of M1 cholinergic receptor in the hippocampus of the mice in the two groups,and the transcriptome method was used to observe the difference in gene ex-pression in the hippocampus between the two groups.Results Behavioral experiments showed that compared with the wild-type mice,the A53T transgenic mice showed cognitive dysfunction at 12 months of age[novel object recognition test:(36.74±13.33)vs(46.90±6.58),t=-2.368,P=0.027],and this phenomenon occurred before motor symptoms.West-ern blotting showed that there was no significant difference in the level of M1 cholinergic receptor in the hippocampus be-tween the A53T transgenic mice and the wild-type mice(P=0.537).The transcriptome analysis identified 290 differen-tially expressed genes between the two groups,among which there were 20 genes with significant difference,and the sig-nificantly downregulated gene sets in the hippocampus of A53T mice were mainly involved in anti-cellular inflammatory re-sponse and antioxidant level.Conclusion Cognitive dysfunction in A53T transgenic mice occurs earlier than motor symp-toms,with a relatively late time node.Transcriptome tests suggest that cellular inflammatory response and oxidative stress injury might be involved in the early pathological process of cognitive impairment in A53T mice.

Acute leukemia of ambiguous lineage (ALAL) is a rare type of acute leukemia and is extremely difficult to treat. Here, we present six patients with CD19-positive ALAL who were successfully treated with blinatumomab-based combination treatment in the front-line setting. Five were diagnosed with B-cell/myeloid mixed phenotype acute leukemia (MPAL) and one with B-cell/T cell MPAL. All six patients achieved complete remission after one cycle of blinatumomab combination treatment. Furthermore, 3 (50%) patients achieved MRD-negative (<0.01%) by flow cytometry and 2 (50%) of four patients with evaluable molecular MRD achieved molecular remission. At some point during the treatment, 5 (83.3%) patients achieved MRD negativity and all four patients with evaluable molecular MRD had molecular remission. The overall survival was 100%, and the event-free survival was 83.3% after a median follow-up time of 15 months. This study provides preliminary evidence that blinatumomab-based combination therapy is an effective and safe treatment for patients with CD19-positive ALAL in the front-line setting.

Objective:To investigate the characteristics of attention bias to aggressive information under self-threat priming in college students with different types of high self-esteem.Methods:A total of 650 college students were selected,and high self-esteem participants were selected through the Self Esteem Scale(SES).Then,43 partic-ipants were selected from different types of high self-esteem(fragile and safe)groups through the Implicit Associa-tion Test(IAT).Each group participated in Raven's Standard Progressive Matrices(SPM)with different difficulty levels to complete self-threat priming,and then completed the spatial cue experiment.When the cue was invalid,the attention bias was obtained according to the variation of the reaction time difference(RTI)between the subjects're-sponses to aggressive words and neutral words.Results:The RTI values of the fragile high self-esteem group were higher under high self-threat priming than that of the secure high self-esteem group(P＜0.01).Under low self-threat priming,there was no significant difference in RTI values among different types of high self-esteem groups(P＞0.05).Conclusion:Fragile high self-esteem group are more likely to develop attention bias towards aggressive words under high self-threat priming than that of secure high self-esteem group.

Objective:To utilize a deep learning approach based on speech to distinguish between depressive and manic mood states in patients with bipolar disorder (BD).Methods:Sixty-one BD patients who visited the outpatient department of psychiatry at Peking University Sixth Hospital were recruited to participate in the study from June 2018 to March 2022. Quick Inventory of Depressive Symptomatology, Mood Disorder Questionnaire and Young Mania Rating Scale were used to determine patients′ mood states. The voices of the patients were recorded, including 190 samples during the patient′s remission, depressive, and manic mood period respectively. A total of 136 features were extracted from the voice samples, including Mel-frequency cepstral coefficients and zero-crossing rates using the speech analysis library in Python. A LIGHT-SERNET-based network was then used to train a model for emotion classification. Accuracy is used to evaluate the performance of the model, using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic curve (ROC) to evaluate the predictive results of model for three mood states. Kruskal-Wallis H tests or χ 2 tests were conducted to compare the differences among the demographic information of three groups. Results:There were statistically significant differences among the three groups in age ( H=25.83, P<0.001), years of education ( H=25.25, P<0.001) and marital status (χ 2=23.81, P<0.001). There is no significant difference in gender (χ 2=4.63, P=0.099). The accuracy of the model in detecting the three emotional states was 0.84. The sensitivity and specificity in detecting remission were 0.88 and 0.93, respectively, and the positive predictive value and negative predictive value were 0.87 and 0.94, respectively. The sensitivity and specificity in detecting depressive episodes were 0.82 and 0.92, respectively, and the positive predictive value and negative predictive value were 0.84 and 0.92, respectively. The sensitivity and specificity in detecting manic episodes were 0.82 and 0.91, respectively, and the positive predictive value and negative predictive value were 0.83 and 0.91, respectively. The areas of the receiver operation characteristic curve for the three mood states were similar and all exceeded 0.90. Conclusion:The LIGHT-SERNET-based deep learning model shows good discrimination ability between depressive and manic mood states based on speech analysis.

Acute leukemia of ambiguous lineage (ALAL) is a rare type of acute leukemia and is extremely difficult to treat. Here, we present six patients with CD19-positive ALAL who were successfully treated with blinatumomab-based combination treatment in the front-line setting. Five were diagnosed with B-cell/myeloid mixed phenotype acute leukemia (MPAL) and one with B-cell/T cell MPAL. All six patients achieved complete remission after one cycle of blinatumomab combination treatment. Furthermore, 3 (50%) patients achieved MRD-negative (<0.01%) by flow cytometry and 2 (50%) of four patients with evaluable molecular MRD achieved molecular remission. At some point during the treatment, 5 (83.3%) patients achieved MRD negativity and all four patients with evaluable molecular MRD had molecular remission. The overall survival was 100%, and the event-free survival was 83.3% after a median follow-up time of 15 months. This study provides preliminary evidence that blinatumomab-based combination therapy is an effective and safe treatment for patients with CD19-positive ALAL in the front-line setting.

Objective:To utilize a deep learning approach based on speech to distinguish between depressive and manic mood states in patients with bipolar disorder (BD).Methods:Sixty-one BD patients who visited the outpatient department of psychiatry at Peking University Sixth Hospital were recruited to participate in the study from June 2018 to March 2022. Quick Inventory of Depressive Symptomatology, Mood Disorder Questionnaire and Young Mania Rating Scale were used to determine patients′ mood states. The voices of the patients were recorded, including 190 samples during the patient′s remission, depressive, and manic mood period respectively. A total of 136 features were extracted from the voice samples, including Mel-frequency cepstral coefficients and zero-crossing rates using the speech analysis library in Python. A LIGHT-SERNET-based network was then used to train a model for emotion classification. Accuracy is used to evaluate the performance of the model, using sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver operating characteristic curve (ROC) to evaluate the predictive results of model for three mood states. Kruskal-Wallis H tests or χ 2 tests were conducted to compare the differences among the demographic information of three groups. Results:There were statistically significant differences among the three groups in age ( H=25.83, P<0.001), years of education ( H=25.25, P<0.001) and marital status (χ 2=23.81, P<0.001). There is no significant difference in gender (χ 2=4.63, P=0.099). The accuracy of the model in detecting the three emotional states was 0.84. The sensitivity and specificity in detecting remission were 0.88 and 0.93, respectively, and the positive predictive value and negative predictive value were 0.87 and 0.94, respectively. The sensitivity and specificity in detecting depressive episodes were 0.82 and 0.92, respectively, and the positive predictive value and negative predictive value were 0.84 and 0.92, respectively. The sensitivity and specificity in detecting manic episodes were 0.82 and 0.91, respectively, and the positive predictive value and negative predictive value were 0.83 and 0.91, respectively. The areas of the receiver operation characteristic curve for the three mood states were similar and all exceeded 0.90. Conclusion:The LIGHT-SERNET-based deep learning model shows good discrimination ability between depressive and manic mood states based on speech analysis.

Ferroptosis is a novel iron-dependent mode of programmed cell death characterized by iron deposition and accumulation of lipid peroxidation. More and more studies have found that ferroptosis is closely related to the pathogenesis of type 2 diabetes mellitus （T2DM）. The yin-fire theory is an important part of LI Gao's spleen-stomach theory， and it is believed that qi-fire imblance and yin-fire internal generation is the main pathogenesis of T2DM. Abnormal iron metabolism may be an important prerequisite for T2DM yin-fire internal generation， while oxidative stress is the specific manifestation of T2DM qi-fire imbalance. Reactive oxygen species （ROS） is the end product of qi-fire imbalance， and lipid peroxide is the pathological products of T2DM yin-fire internal generation. This study intends to explore the pathological mechanism of qi-fire imbalance and yin-fire internal generation from the perspectives of iron metabolism， oxidative stress and lipid peroxidation， enriching the modern connotation of yin-fire theory， and benefiting traditional Chinese medicine to target against ferroptosis， and prevent and treat T2DM precisely.

Objective To assay the contents of acetaminophen with ultra high-performance liquid chromatography (UHPLC) method in the sustained-release tablets radiated by Gamma ray. Methods Acetaminophen sustained-release tablets were radiated by ⁶⁰Co. UHPLC equipped with the Shim-pack GISS-C₁₈（2.1 mm×50 mm, 1.9 μm）was used for the assay. The mobile phase was methanol-0.05 % ammonium acetate solution (15∶85). The flow rate was 0.3 ml/min with the detection wavelength at 245 nm. Results The acetaminophen showed good linear relationship within the range of 20-100 μg/ml (r=0.999 4). The RSD values of repeatability was 0.9 %. The average recovery was 97.9 %-104.9 %. Acetaminophen content was 96.2 %, 92.2 %, 91.8 %, 83.9 % at 0, 8, 50 and 80 kGy radiation, respectively. Conclusion This method is speedy and accurate. It can be used to assay the content of acetaminophen in the sustained-release tablets after radiation. The content of acetaminophen decreased after radiation.