Triatoma rubrofasciata is currently the most widely distributed species of Triatoma worldwide, and it is also widespread in southern China. T. rubrofasciata has been proven to transmit Trypanosoma cruzi, and is one of vectors transmitting Chagas disease, which poses a potential risk for transmission of imported Chagas disease in China. Findings from latest studies have shown that T. rubrofasciata naturally infects T. lewisi, T. conorhini, and T. rangeli, which undoubtedly increases significant risks of and challenges to trypanosomiasis control in China. This article briefly describes the species of T. rubrofasciata-transmitted trypanosomes, and summarizes the epidemiological characteristics of trypanosomiasis, so as to provide insights into T. rubrofasciata-transmitted trypanosomiasis surveillance and control, and prevention of trypanosomiasis development and transmission in China.

Objective To explore the characteristics and correlation between perivascular spaces (PVS) and diffusion tensor image analysis along perivascular spaces (DTI-ALPS) index in patients with amnestic mild cognitive impairment (aMCI). Methods A retrospective study was conducted on a total of 118 participants, including cognitive normal (CN) healthy controls and aMCI patients, recruited from the Department of Neurology, Zhongshan Hospital, Fudan University from September 2020 to September 2022. All participants underwent structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). An automatic segmentation algorithm was used to quantify PVS metrics in the brain, and DTI-ALPS index was calculated based on DTI. Differences in DTI-ALPS index and PVS metrics between the CN and aMCI groups were compared. Multivariate logistic regression was used to identify independent factors influencing aMCI. Correlation analysis was performed to assess relationships among DTI-ALPS index, PVS metrics, and cognitive scores. Results A total of 80 CN healthy controls and 38 aMCI patients were included. The DTI-ALPS index was significantly lower in the aMCI group compared with the CN group (1.28±0.18 vs 1.37±0.21, P＝0.018), while differences in PVS metrics between groups were not statistically significant. Multivariate logistic regression analysis indicated that DTI-ALPS index was an independent factor affecting aMCI (OR＝0.097, 95%CI 0.011–0.833, P＝0.033). Correlation analysis revealed a positive relationship between DTI-ALPS index and MMSE score (r＝0.210, P＝0.023) as well as PVS length in the centrum semiovale (r＝0.216, P＝0.019). Conclusions The DTI-ALPS index may serve as an imaging biomarker for identifying early cognitive impairment, and patients with aMCI exhibit abnormal DTI-ALPS indices, suggesting that brain glymphatic system dysfunction may occur prior to morphological changes.

OBJECTIVE: To investigate the effect of manual acupuncture manipulations (MAMs) on subcutaneous muscle tissue, by developing quantitative models of "lifting and thrusting" and "twisting and rotating", based on machine learning techniques. METHODS: A depth camera was used to capture the acupuncture operator's hand movements during "lifting and thrusting" and "twisting and rotating" of needle. Simultaneously, the ultrasound imaging was employed to record the muscle tissue responses of the participants. Amplitude and angular features were extracted from the movement data of operators, and muscle fascicle slope features were derived from the data of ultrasound images. The dynamic time warping barycenter averaging algorithm was adopted to align the dual-source data. Various machine learning techniques were applied to build quantitative models, and the performance of each model was compared. The most optimal model was further analyzed for its interpretability. RESULTS: Among the quantitative models built for the two types of MAMs, the random forest model demonstrated the best performance. For the quantitative model of the "lifting and thrusting" technique, the coefficient of determination (R²) was 0.825. For the "twisting and rotating" technique, R² reached 0.872. CONCLUSION Machine learning can be used to effectively develop the models and quantify the effects of MAMs on subcutaneous muscle tissue. It provides a new perspective to understand the mechanism of acupuncture therapy and lays a foundation for optimizing acupuncture technology and designing personalized treatment regimen in the future.
Humans ; Acupuncture Therapy/methods* ; Machine Learning ; Male ; Adult ; Female ; Subcutaneous Tissue/diagnostic imaging* ; Young Adult

Cannabidiol (CBD), the primary non-psychoactive constituent of cannabis plants, has emerged as a research focus in neuropsychiatric disorders in recent years due to its multi-target regulatory properties. This review summarizes the potential therapeutic targets of CBD and its current application in common neuropsychiatric disorders so as to promote clinical implementation of CBD in managing neuropsychiatric disorders.

Objective:To observe the effects of acupuncture on the motor function of Parkinson disease(PD)model mice and to investigate the neuroprotective effects of acupuncture on PD from the perspective of cellular senescence.Methods:C57BL/6J mice were randomly divided into a normal control(NC)group,a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)group,an acupuncture(ACU)group,and a rasagiline(RAS)group,with 6 mice in each group.Except for the mice in the NC group,all mice were injected intraperitoneally with MPTP[30 mg/(kg·bw)]to establish a PD mouse model.After the models were successfully established,mice in the ACU group received acupuncture at Baihui(GV20)and bilateral Yanglingquan(GB34)for 15 min,once a day for 14 consecutive days.Mice in the RAS group were treated with gavage of rasagiline mesylate[0.5 mg/(kg·bw)],once daily for 14 d.Mouse balance and motor functions were detected using the mouse fatigue rotating rod apparatus.Immunohistochemistry staining was used to detect the number of tyrosine hydroxylase(TH)-positive neurons and the protein expression levels of special AT-rich sequence-binding protein 1(SATB1),p21,and p53 in the substantia nigra(SN)region of the mouse brain in each group.The glutathione peroxidase(GSH-Px)activity of mouse brain SN tissue was detected by enzyme-linked immunosorbent assay.The protein expression levels of interleukin(IL)-6 and senescence-associated β-galactosidase(SA-β-gal)in the SN tissue of mice in each group were detected by Western blotting.The relative expression of SATB1,p21,and p53 mRNA in the SN of each group was detected by real-time quantitative polymerase chain reaction.Results:Compared to the NC group,the overall rod performance(ORP)score,the number of TH-positive neurons,and GSH-Px activity in the SN region were significantly lower in the mice in the MPTP group(P<0.01);compared to the MPTP group,the ORP score,the number of TH-positive neurons,and GSH-Px activity were significantly increased in the ACU group and the RAS group(P<0.01 or P<0.05).Compared to the NC group,the protein levels of IL-6 and SA-β-gal in the SN tissue,the protein and mRNA expression levels of p21 and p53 were significantly increased(P<0.01);compared to the MPTP group,the protein levels of IL-6 and SA-β-gal in the SN tissue,the protein and mRNA expression levels of p21 and p53 were significantly decreased in the ACU group and the RAS group(P<0.01 or P<0.05).Compared to the NC group,the relative expression of SATB1 protein and mRNA in the SN of mice in the MPTP group was significantly decreased(P<0.01);compared to mice in the MPTP group,mice in the ACU group and the RAS group showed significant increases in the relative expression of SATB1 protein and mRNA(P<0.01 or P<0.05).Conclusion:Acupuncture can improve motor function and increase the number of TH-positive neurons in the SN of PD model mice.Its neuroprotective effect may relate to the regulation of the SATB1/p21 signaling pathway and the inhibition of cellular senescence-related biomarker expression in the SN.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Objective:To observe the effects of acupuncture on the motor function of Parkinson disease(PD)model mice and to investigate the neuroprotective effects of acupuncture on PD from the perspective of cellular senescence.Methods:C57BL/6J mice were randomly divided into a normal control(NC)group,a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine(MPTP)group,an acupuncture(ACU)group,and a rasagiline(RAS)group,with 6 mice in each group.Except for the mice in the NC group,all mice were injected intraperitoneally with MPTP[30 mg/(kg·bw)]to establish a PD mouse model.After the models were successfully established,mice in the ACU group received acupuncture at Baihui(GV20)and bilateral Yanglingquan(GB34)for 15 min,once a day for 14 consecutive days.Mice in the RAS group were treated with gavage of rasagiline mesylate[0.5 mg/(kg·bw)],once daily for 14 d.Mouse balance and motor functions were detected using the mouse fatigue rotating rod apparatus.Immunohistochemistry staining was used to detect the number of tyrosine hydroxylase(TH)-positive neurons and the protein expression levels of special AT-rich sequence-binding protein 1(SATB1),p21,and p53 in the substantia nigra(SN)region of the mouse brain in each group.The glutathione peroxidase(GSH-Px)activity of mouse brain SN tissue was detected by enzyme-linked immunosorbent assay.The protein expression levels of interleukin(IL)-6 and senescence-associated β-galactosidase(SA-β-gal)in the SN tissue of mice in each group were detected by Western blotting.The relative expression of SATB1,p21,and p53 mRNA in the SN of each group was detected by real-time quantitative polymerase chain reaction.Results:Compared to the NC group,the overall rod performance(ORP)score,the number of TH-positive neurons,and GSH-Px activity in the SN region were significantly lower in the mice in the MPTP group(P<0.01);compared to the MPTP group,the ORP score,the number of TH-positive neurons,and GSH-Px activity were significantly increased in the ACU group and the RAS group(P<0.01 or P<0.05).Compared to the NC group,the protein levels of IL-6 and SA-β-gal in the SN tissue,the protein and mRNA expression levels of p21 and p53 were significantly increased(P<0.01);compared to the MPTP group,the protein levels of IL-6 and SA-β-gal in the SN tissue,the protein and mRNA expression levels of p21 and p53 were significantly decreased in the ACU group and the RAS group(P<0.01 or P<0.05).Compared to the NC group,the relative expression of SATB1 protein and mRNA in the SN of mice in the MPTP group was significantly decreased(P<0.01);compared to mice in the MPTP group,mice in the ACU group and the RAS group showed significant increases in the relative expression of SATB1 protein and mRNA(P<0.01 or P<0.05).Conclusion:Acupuncture can improve motor function and increase the number of TH-positive neurons in the SN of PD model mice.Its neuroprotective effect may relate to the regulation of the SATB1/p21 signaling pathway and the inhibition of cellular senescence-related biomarker expression in the SN.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Cannabidiol (CBD), the primary non-psychoactive constituent of cannabis plants, has emerged as a research focus in neuropsychiatric disorders in recent years due to its multi-target regulatory properties. This review summarizes the potential therapeutic targets of CBD and its current application in common neuropsychiatric disorders so as to promote clinical implementation of CBD in managing neuropsychiatric disorders.

ObjectiveTo analyze the etiological results of influenza-like case surveillance in Taizhou， Zhejiang Province from 2013 to 2022， to timely understand the epidemic trend of influenza viruses and the change rule of dominant virus strains， and to provide reference for the prevention and control of influenza in this region. MethodsInfluenza virus nucleic acid was detected by real-time PCR in 24 183 influenza-like cases. ResultsThe positive rate of influenza virus in 24 183 samples was 18.43%， the highest positive type was seasonal H3 （37.34%）. There was no a significant difference in positive rate between different genders （χ²=0.148， P=0.701）. There was significant difference in the positive rate among different age groups （χ²=496.626， P<0.001）， and the highest positive rate was found in the 25‒59 age group （22.56%）. The positive rate in different years was statistically significant （χ²=1 670.922， P<0.001）. The positive rate from 2013 to 2019 showed an upward trend （χ²=30.559， P<0.001）. The lowest positive rate was in 2020 （0.04%）， and the positive rate from 2021 to 2022 showed an upward trend （χ²=304.465， P<0.001）. The dominant strains were different in different monitoring years. There was a significant difference in the positive rate of influenza in different months （χ²=1 652.455， P<0.001）， and the peak of influenza was mainly concentrated in December‒March and July‒August. ConclusionFrom 2013 to 2022， the positive rate of influenza virus in Taizhou showed a wavy dynamic change， and the dominant strains were different in different years， presenting alternate epidemic characteristics. It is necessary to strengthen the etiological surveillance of influenza virus and improve the prevention and control measures with influenza vaccine.