ObjectiveTo investigate the effects of Tianma Goutengyin on the tumor necrosis factor-α （TNF-α）/signal transducer and activator of transcription 3 （STAT3）/α1-antichymotrypsin C-terminal tail fragment （α1ACT） signaling pathway and A1-type astrocytes in a rat model of vascular dementia. MethodsSeventy-two male Sprague-Dawley rats were randomly divided into six groups （n=12 per group）： Sham-operated group， model group， Tianma Goutengyin high-， medium-， and low-dose groups （5.13， 10.26， and 20.52 g·kg^-1）， and a nimodipine group （8.1 mg·kg^-1）. The vascular dementia model was established by permanent bilateral common carotid artery occlusion， followed by 4 weeks of intervention. Learning and memory ability were evaluated using the novel object recognition test， and behavioral performance was assessed using the forced swimming test. Levels of interleukin-6 （IL-6） and C-C motif chemokine ligand 2 （CCL2） in hippocampal tissue were measured by enzyme-linked immunosorbent assay （ELISA）. Hippocampal neuronal morphology was observed by Nissl staining， and apoptosis was detected by terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling （TUNEL）. Immunohistochemistry was used to detect positive expression of brain-derived neurotrophic factor （BDNF）， glial fibrillary acidic protein （GFAP）， and myelin basic protein （MBP）. Western blot analysis was performed to measure the protein expression levels of TNF-α， TNF receptor 1 （TNFR1）， phosphorylated STAT3 （p-STAT3）， α1ACT， IL-6， complement component 3 （C3）， BDNF， S100 calcium-binding protein A10 （S100A10）， and GFAP in hippocampal tissue. ResultsCompared with the sham-operated group， the model group showed a significantly reduced relative recognition index in the novel object recognition test （P<0.01）， prolonged immobility time and increased immobility frequency in the forced swimming test （P<0.01）. Hippocampal IL-6 and CCL2 levels were significantly increased （P<0.01）. Nissl staining revealed a marked reduction in neuronal number and loss of Nissl bodies （P<0.01）. MBP-positive expression was significantly decreased （P<0.01）， apoptosis was significantly increased （P<0.01）， BDNF-positive expression was significantly reduced （P<0.05）， and GFAP-positive expression was significantly increased （P<0.01）. In addition， the protein expression levels of TNF-α， TNFR1， p-STAT3， α1ACT， IL-6， and C3 were significantly elevated （P<0.01）， while BDNF and S100A10 expression levels were significantly decreased （P<0.01）. Compared with the model group， all Tianma Gouteng yin dose groups exhibited a significant increase in the relative recognition index （P<0.05）， shortened immobility time and reduced immobility frequency （P<0.05， P<0.01）. IL-6 and CCL2 levels were significantly decreased （P<0.01）， neuronal number was significantly increased （P<0.05， P<0.01）， and MBP-positive expression was significantly enhanced （P<0.01）. Apoptosis was significantly reduced （P<0.01）， BDNF-positive expression was significantly increased （P<0.05）， and GFAP-positive expression was significantly decreased （P<0.01）. Moreover， the protein expression levels of TNF-α， TNFR1， p-STAT3， α1ACT， IL-6， and C3 were significantly decreased （P<0.01）， while BDNF and S100A10 protein expression levels were significantly increased （P<0.01）. ConclusionTianma Goutengyin may inhibit A1-type astrocyte activation in rats with vascular dementia through the TNF-α/STAT3/α1ACT signaling pathway， thereby reducing neuronal apoptosis and improving learning and memory function.

ObjectiveTo establish a model that can quickly identify the aroma components in different parts of Nardostachys jatamansi， so as to provide a quality control basis for the market circulation and clinical use of N. jatamansi. MethodsHeadspace solid-phase microextraction-gas chromatography-mass spectrometry（HS-SPME-GC-MS） combined with Smart aroma database and National Institute of Standards and Technology（NIST） database were used to characterize the aroma components in different parts of N. jatamansi， and the aroma components were quantified according to relative response factor（RRF） and three internal standards， and the markers of aroma differences in different parts of N. jatamansi were identified by orthogonal partial least squares-discriminant analysis（OPLS-DA） and cluster thermal analysis based on variable importance in the projection（VIP） value >1 and P<0.01. The odor data of different parts of N. jatamansi were collected by Heracles Ⅱ Neo ultra-fast gas phase electronic nose， and the correlation between compound types of aroma components collected by the ultra-fast gas phase electronic nose and the detection results of HS-SPME-GC-MS was investigated by drawing odor fingerprints and odor response radargrams. Chromatographic peak information with distinguishing ability≥0.700 and peak area≥200 was selected as sensor data， and the rapid identification model of different parts of N. jatamansi was established by principal component analysis（PCA）， discriminant factor alysis（DFA）， soft independent modeling of class analogies（SIMCA） and statistical quality control analysis（SQCA）. ResultsThe HS-SPME-GC-MS results showed that there were 28 common components in the underground and aboveground parts of N. jatamansi， of which 22 could be quantified and 12 significantly different components were screened out. Among these 12 components， the contents of five components（ethyl isovalerate， 2-pentylfuran， benzyl alcohol， nonanal and glacial acetic acid，） in the aboveground part of N. jatamansi were significantly higher than those in the underground part（P<0.01）， the contents of β-ionone， patchouli alcohol， α-caryophyllene， linalyl butyrate， valencene， 1，8-cineole and p-cymene in the underground part of N. jatamansi were significantly higher than those in the aboveground part（P<0.01）. Heracles Ⅱ Neo electronic nose results showed that the PCA discrimination index of the underground and aboveground parts of N. jatamansi was 82， and the contribution rates of the principal component factors were 99.94% and 99.89% when 2 and 3 principal components were extracted， respectively. The contribution rate of the discriminant factor 1 of the DFA model constructed on the basis of PCA was 100%， the validation score of the SIMCA model for discrimination of the two parts was 99， and SQCA could clearly distinguish different parts of N. jatamansi. ConclusionHS-SPME-GC-MS can clarify the differential markers of underground and aboveground parts of N. jatamansi. The four analytical models provided by Heracles Ⅱ Neo electronic nose（PCA， DFA， SIMCA and SQCA） can realize the rapid identification of different parts of N. jatamansi. Combining the two results， it is speculated that terpenes and carboxylic acids may be the main factors contributing to the difference in aroma between the underground and aboveground parts of N. jatamansi.

OBJECTIVE: To evaluate the efficacy and safety of Shexiang Tongxin Dropping Pill (STDP) in treating stable angina patients with phlegm-heat and blood-stasis syndrome by exercise duration and metabolic equivalents. METHODS: This multicenter, randomized, double-blind, placebo-controlled clinical trial enrolled stable angina patients with phlegm-heat and blood-stasis syndrome from 22 hospitals. They were randomized 1:1 to STDP (35 mg/pill, 6 pills per day) or placebo for 56 days. The primary outcome was the exercise duration and metabolic equivalents (METs) assessed by the standard Bruce exercise treadmill test after 56 days of treatment. The secondary outcomes included the total angina symptom score, Chinese medicine (CM) symptom scores, Seattle Angina Questionnaire (SAQ) scores, changes in ST-T on electrocardiogram and adverse events (AEs). RESULTS: This trial enrolled 309 patients, including 155 and 154 in the STDP and placebo groups, respectively. STDP significantly prolonged exercise duration with an increase of 51.0 s, compared to a decrease of 12.0 s with placebo (change rate: -11.1% vs. 3.2%, P<0.01). The increase in METs was significantly greater in the STDP group than in the placebo group (change: -0.4 vs. 0.0, change rate: -5.0% vs. 0.0%, P<0.01). The improvement of total angina symptom scores (25.0% vs. 0.0%), CM symptom scores (38.7% vs. 11.8%), reduction of nitroglycerin consumption (100.0% vs. 11.3%), and all domains of SAQ, were significantly greater with STDP than placebo (all P<0.01). The changes in Q-T intervals at 28 and 56 days from baseline were similar between the two groups (both P>0.05). Twenty-five participants (16.3%) with STDP and 16 (10.5%) with placebo experienced AEs (P=0.131), with no serious AEs observed. CONCLUSION STDP could improve exercise tolerance in patients with stable angina and phlegm-heat and blood stasis syndrome, with a favorable safety profile. (Registration No. ChiCTR-IPR-15006020).
Humans ; Double-Blind Method ; Drugs, Chinese Herbal/adverse effects* ; Male ; Female ; Middle Aged ; Angina, Stable/physiopathology* ; Aged ; Syndrome ; Treatment Outcome ; Placebos ; Tablets

[This corrects the article DOI: 10.1016/j.apsb.2024.03.030.].

AIM To establish an HPLC method for the simultaneous content determination of gallic acid,protocatechuic acid,morroniside,loganin,sweroside,paeoniflorin,hypericin,astragalin,salvianolic acid B,salvianolic acid A,epimedin C and icariin in Bushen Huoxue Sanjie Capsules.METHODS The analysis was performed on a 30℃thermostatic Agilent 5 TC-C18 column(250 mm×4.6 mm,5 μm),with the mobile phase comprising of acetonitrile-0.1%phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.RESULTS Twelve constituents showed good linear relationships within their own ranges(r≥0.999 8),whose average recoveries were 97.11%-101.14%with the RSDs of 0.60%-2.65%.CONCLUSION This simple,accurate and reproducible method can be used for the quality control of Bushen Huoxue Sanjie Capsules.

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Thyroid cancer is the most common malignant tumor of the endocrine system,and its incidence has been steadily increasing in recent years. Papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC),collectively known as differentiated thyroid cancer (DTC),account for approximately 95％ of thyroid cancer cases. Imaging examinations such as ultrasound,computed tomography (CT),magnetic resonance imaging (MRI),single-photon emission computed tomography (SPECT/CT),and positron emission tomography (PET/CT) play a critical role in the diagnosis,staging,risk stratification,and treatment of DTC. However,the analysis of imaging results heavily depends on the skills and experience of the physician,making the interpretation prone to errors due to factors such as image volume,complexity,and subjective judgment,particularly under high workloads. Additionally,objective factors like equipment resolution and the limitations of human vision can also affect diagnostic accuracy. Artificial intelligence (AI),a technology that simulates,extends,and enhances human intelligence,has gradually been applied in the medical field. In the diagnosis and treatment of DTC,AI technologies such as machine learning and deep learning,as well as radiomics,have been utilized. These technologies are primarily applied in the diagnosis and differential diagnosis of DTC,staging assessments,prediction of genetic mutations,and iodine-131 therapy for DTC. The application of AI and radiomics holds great promise for improving diagnostic accuracy,enabling precise staging,predicting genetic mutations with higher precision,and optimizing treatment strategies for DTC. This advancement is expected to facilitate accurate diagnosis and personalized treatment,maximizing benefits for patients.

Thyroid cancer is the most common malignant tumor of the endocrine system,and its incidence has been steadily increasing in recent years. Papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC),collectively known as differentiated thyroid cancer (DTC),account for approximately 95％ of thyroid cancer cases. Imaging examinations such as ultrasound,computed tomography (CT),magnetic resonance imaging (MRI),single-photon emission computed tomography (SPECT/CT),and positron emission tomography (PET/CT) play a critical role in the diagnosis,staging,risk stratification,and treatment of DTC. However,the analysis of imaging results heavily depends on the skills and experience of the physician,making the interpretation prone to errors due to factors such as image volume,complexity,and subjective judgment,particularly under high workloads. Additionally,objective factors like equipment resolution and the limitations of human vision can also affect diagnostic accuracy. Artificial intelligence (AI),a technology that simulates,extends,and enhances human intelligence,has gradually been applied in the medical field. In the diagnosis and treatment of DTC,AI technologies such as machine learning and deep learning,as well as radiomics,have been utilized. These technologies are primarily applied in the diagnosis and differential diagnosis of DTC,staging assessments,prediction of genetic mutations,and iodine-131 therapy for DTC. The application of AI and radiomics holds great promise for improving diagnostic accuracy,enabling precise staging,predicting genetic mutations with higher precision,and optimizing treatment strategies for DTC. This advancement is expected to facilitate accurate diagnosis and personalized treatment,maximizing benefits for patients.

Amyloidosis is a local or systemic disease caused by the deposition of misfolded proteins outside the cell,with rapid progression,and dire prognosis.Common types of cardiac amyloidosis are monoclonal immunoglobulin light chain amyloidosis(AL-CA)and transthyretin cardiac amyloidosis(ATTR-CA).Nuclear medicine examinations can be accurate,rapid,and non-invasive to help diagnose diseases and can effectively predict the prognosis of patients with CA.Technetium(99Tcm)-labeled bisphosphonate imaging has been included in the consensus of experts and has become the first-line imaging method for the diagnosis of ATTR-CA.123I-metaiodoenzylguanidine(MIBG)as a norepinephrine analogue can effectively assess cardiac sympathetic innervation in patients with CA.Aβ-amyloid imaging agents such as 11C-pittsburgh compound B and 18F-flubetaben are expected to be new techniques for diagnosing AL-CA and incorporating them into cardiac staging systems for AL-CA patients in the future.New imaging agents such as 18F-NaF has been widely used in the diagnosis,treatment response monitoring,and prognosis assessment of CA.Summarizing the research value of nuclide imaging in CA may provide new ideas for clinical realization of early detection of CA and accurate assessment of disease prognosis.

Objective:To analyze the accuracy of lung ultrasound and chest X-ray in the diagnosis of neonatal pulmonary disease.Methods:We prospectively collected newborns that needed chest X-ray examination to diagnose pulmonary disease from twelve neonatal intensive care units across the country between June 2019 and April 2020.Each newborn was examined by lung ultrasound within two hours after chest X-ray examination.All chest X-ray and lung ultrasound images were independently read by a radiologist and a sonographer.When there was a disagreement, a panel of two experienced physicians made a final diagnosis based on the clinical history, chest X-ray and lung ultrasound images.Results:A total of 1 100 newborns were enrolled in our study.The diagnostic agreement between chest X-ray and lung ultrasound(Cohen′s kappa coefficient=0.347) was fair.Lung ultrasound(area under the curve=0.778; 95% CI 0.753-0.803) performed significantly better than chest X-ray(area under the curve=0.513; 95% CI 0.483-0.543) in the diagnosis of transient tachypnea of the newborn( P<0.001). The accuracy of lung ultrasound in diagnosing neonatal respiratory distress syndrome, meconium aspiration syndrome, pneumonia and neonatal pulmonary atelectasis was similar to that of chest X-ray. Conclusion:Lung ultrasound, as a low-cost, simple and radiation-free auxiliary examination method, has a diagnostic accuracy close to or even better than that of chest X-ray, which may replace chest X-ray in the diagnosis of some neonatal lung diseases.It should be noted that both chest X-ray and lung ultrasound can only be used as auxiliary means for the diagnosis of lung diseases, and it is necessary to combine imaging with the clinical history and presentation.