OBJECTIVE To observe the clinical efficacy of evolocumab combined with atorvastatin in the treatment of patients with borderline coronary heart disease （CHD）. METHODS In this retrospective cohort study， 342 hospitalized patients diagnosed with borderline CHD were enrolled in the First Affiliated Hospital of Nanyang Medical College from August 2021 to June 2024， and divided into control group （treated with atorvastatin， 190 cases） and trial group （treated with evolocumab combined with atorvastatin， 152 cases） according to therapeutic regimen. Blood lipid indexes， high-sensitivity C-reactive protein （hs-CRP） and intravascular ultrasound of the coronary artery at baseline and after 1 year of treatment， and incidence of cardiovascular adverse events were compared after propensity score matching. RESULTS A total of 295 patients （158 in control group and 137 in trial group） were finally included in the analysis. One year after the treatment， compared with control group， total cholesterol， triglycerides， low-density lipoprotein cholesterol and hs-CRP levels were decreased significantly in trial group （ P ＜0.05）， whereas high-density lipoprotein cholesterol level was increased significantly （ P ＜0.05）. The lumen diameter， lumen area， and the minimum lumen area were significantly increased （ P ＜0.05）， while plaque area and plaque burden were significantly decreased （ P ＜0.05）. Overall incidence of adverse events in trial group was significantly lower than that in control group （ P ＜0.05）. CONCLUSIONS Evolocumab combined with atorvastatin can significantly improve coronary luminal narrowing and reduce plaque burden， as well as reduce the incidence of cardiovascular adverse events in patients with borderline CHD.

Peripheral nerve injury (PNI) encompasses damage to nerves located outside the central nervous system, adversely affecting both motor and sensory functions. Although peripheral nerves possess an intrinsic capacity for self-repair, severe injuries frequently result in significant tissue loss and erroneous axonal junctions, thereby impeding complete recovery and potentially causing neuropathic pain. Various therapeutic strategies, including surgical interventions, biomaterials, and pharmacological agents, have been developed to enhance nerve repair processes. While preclinical studies in animal models have demonstrated the efficacy of certain pharmacological agents in promoting nerve regeneration and mitigating inflammation, only a limited number of these agents have been translated into clinical practice to expedite nerve regeneration. Chinese herb medicine (CHM) possesses a longstanding history in the treatment of various ailments and demonstrates potential efficacy in addressing PNI through its distinctive, cost-effective, and multifaceted methodologies. This review critically examines the advancements in the application of CHM for PNI treatment and nerve regeneration. In particular, we have summarized the most commonly employed and rigorously investigated CHM prescriptions, individual herbs, and natural products, elucidating their respective functions and underlying mechanisms in the context of PNI treatment. Furthermore, we have deliberated on the prospective development of CHM in both clinical practice and fundamental research.
Drugs, Chinese Herbal/pharmacology* ; Humans ; Peripheral Nerve Injuries/drug therapy* ; Animals ; Nerve Regeneration/drug effects* ; Medicine, Chinese Traditional

Objective:To observe the clinical progression of low-risk papillary thyroid microcarcinoma（LR-PTMC）, analyze the influencing factors of its oncological outcomes, and explore the feasibility of active surveillance（AS） of LR-PTMC. Methods:This study adopted a prospective observational research design. A total of 85 subjects diagnosed with LR-PTMC during health checkup in Health Management Center of our hospital from March 2021 to October 2022 were enrolled as the research subjects, for at least 2 years of AS follow-up observation. The clinical progress and oncological outcomes were recorded, disease progression was defined as any increase in nodule diameter ≥3 mm or the appearance of new lesions or lymph node metastasis or distant metastasis, and the oncological outcome was use disease progression defining. Cox proportional hazards regression model was used to analyze the influencing factors of oncological outcomes in LR-PTMC patients. Results:A total of 85 LR-PTMC patients who underwent physical examinations were included in this study. The median follow-up time was 2 years, and a total of 23 patients（27.06%） experienced disease progression. Among them, 18 patients（21.18%） had enlarged lesions（any nodule diameter increased by ≥3 mm）, and 5 patients（5.88%） had abnormal or metastatic cervical lymph nodes. The 2-year cumulative disease progression rate was 9.41%. The incidence age of LR-PTMC patients was younger, with a higher proportion of ≤45 years old. The proportion of baseline nodules with a maximum diameter greater than 5 mm is higher, and the proportion of baseline TPO Ab positivity was higher. Ultrasound showed a higher proportion of microcalcifications compared to the non progression group, and the differences were statistically significant（all P<0.05）. Multivariate Cox proportional hazards regression analysis showed that age of onset ≤45 years RR 95% CI 1.052（1.018-1.088） and ultrasound showing microcalcifications RR 95% CI 3.361（1.379-8.194） were independent risk factors affecting disease progression during AS in LR-PTMC patients（P<0.05）. Conclusion:Most LR-PTMC patients maintain stable lesion size and low lymph node metastasis rate during the AS process, with good oncological outcomes in the short term. AS can be considered as a safe and effective alternative to surgical treatment for LR-PTMC patients. But for patients with onset age ≤45 years and microcalcifications, the follow-up interval can be shortened for close observation.
Humans ; Thyroid Neoplasms/pathology* ; Disease Progression ; Prospective Studies ; Carcinoma, Papillary/pathology* ; Female ; Male ; Middle Aged ; Adult ; Watchful Waiting ; Lymphatic Metastasis ; Proportional Hazards Models ; Risk Factors

[This corrects the article DOI: 10.1016/j.apsb.2024.09.010.].

Osteoarthritis (OA) causes chronic pain that significantly impairs quality of life, with current treatments often proving insufficient and accompanied by adverse effects. Recent research has identified the dorsal root ganglion (DRG) and its resident macrophages as crucial mediators of chronic OA pain through neuroinflammation driven by macrophage polarization. We present a novel injectable thermo-sensitive hydrogel system, KAF@PLEL, designed to deliver an anti-inflammatory peptide (KAF) specifically to the DRG. This biodegradable hydrogel enables sustained KAF release, promoting the reprogramming of DRG macrophages from pro-inflammatory to anti-inflammatory phenotypes. Through comprehensive in vitro and in vivo studies, we evaluated the hydrogel's biocompatibility, effects on macrophage polarization, and therapeutic efficacy in chronic OA pain management. The system demonstrated significant capabilities in preserving macrophage mitochondrial function, suppressing neuroinflammation, alleviating chronic OA pain, reducing cartilage degradation, and improving motor function in OA rat models. The sustained-release properties of KAF@PLEL enabled prolonged therapeutic effects while minimizing systemic exposure and side effects. These findings suggest that KAF@PLEL represents a promising therapeutic approach for improving outcomes in OA patients through targeted, sustained treatment.

Objective:To establish a Zika virus-infected suckling SD rat model with type Ⅰ interferon receptor deficiency（SD-Ifnar1 -/-［cc］）and provide a novel animal model for investigating Zika virus pathogenesis and developing therapeutic strategies. Methods:Seventeen-day-old male SD-Ifnar1 -/-［cc］rat pups were randomly divided into experimental and control groups（ n=6）. The experimental group received an intraperitoneal injection of Zika virus strain SZ-wiv01（5×10 4 PFU/rat，200 μl），while the control group received an equal volume of phosphate-buffered saline（PBS）. Animals were euthanized via CO 2 asphyxiation on days 12 and 15 post-infection（dpi），and brain，spleen，liver，and testis tissues were harvested. Viral loads and cytokine expression levels were quantified using quantitative real-time PCR qRT-PCR），and histopathological evaluation was performed via HE staining. Results:qRT-PCR analysis revealed no detectable Zika virus RNA（Ct >35）in control tissues. In the experimental group，viral RNA（Ct <35）was detected in the brain，spleen，liver，and testis by day 12，with stable viral loads across tissues by day 15（ P>0.05）. Cytokine profiling demonstrated significant upregulation in the brain at day 12：IFN-β（5.58-fold， P<0.01），IL-6（7.11-fold， P<0.01），and CCL5（3.79-fold， P<0.01）. By day 15，these levels remained elevated（IFN-β：3.07-fold；IL-6：4.04-fold；CCL5：5.22-fold；all P<0.01）. In the liver，IFN-β mRNA decreased to 20% of the control level by day 15（ P<0.05），while IL-6 declined to 24% and CCL5 mRNA dropped to 38% by day 12. No significant cytokine changes were observed in the spleen（ P>0.05）. Testicular tissues exhibited reduced IFN-β mRNA levels（43% of control at day 12，31% at day 15； P<0.05）. Histopathological analysis revealed marked splenomegaly with disrupted splenic corpuscle architecture and lymphocyte depletion，significant inflammatory cell infiltration in hepatic portal areas，and testicular structural disorganization with inflammatory infiltration in Zika-infected rats. Conclusions:The SD-Ifnar1 -/-［cc］suckling rat model is successfully established and validated. This model recapitulates systemic Zika virus infection，tissue-specific pathology，and immune response dynamics，providing a robust platform for elucidating viral pathogenesis and advancing antiviral drug development.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective:To establish a Zika virus-infected suckling SD rat model with type Ⅰ interferon receptor deficiency（SD-Ifnar1 -/-［cc］）and provide a novel animal model for investigating Zika virus pathogenesis and developing therapeutic strategies. Methods:Seventeen-day-old male SD-Ifnar1 -/-［cc］rat pups were randomly divided into experimental and control groups（ n=6）. The experimental group received an intraperitoneal injection of Zika virus strain SZ-wiv01（5×10 4 PFU/rat，200 μl），while the control group received an equal volume of phosphate-buffered saline（PBS）. Animals were euthanized via CO 2 asphyxiation on days 12 and 15 post-infection（dpi），and brain，spleen，liver，and testis tissues were harvested. Viral loads and cytokine expression levels were quantified using quantitative real-time PCR qRT-PCR），and histopathological evaluation was performed via HE staining. Results:qRT-PCR analysis revealed no detectable Zika virus RNA（Ct >35）in control tissues. In the experimental group，viral RNA（Ct <35）was detected in the brain，spleen，liver，and testis by day 12，with stable viral loads across tissues by day 15（ P>0.05）. Cytokine profiling demonstrated significant upregulation in the brain at day 12：IFN-β（5.58-fold， P<0.01），IL-6（7.11-fold， P<0.01），and CCL5（3.79-fold， P<0.01）. By day 15，these levels remained elevated（IFN-β：3.07-fold；IL-6：4.04-fold；CCL5：5.22-fold；all P<0.01）. In the liver，IFN-β mRNA decreased to 20% of the control level by day 15（ P<0.05），while IL-6 declined to 24% and CCL5 mRNA dropped to 38% by day 12. No significant cytokine changes were observed in the spleen（ P>0.05）. Testicular tissues exhibited reduced IFN-β mRNA levels（43% of control at day 12，31% at day 15； P<0.05）. Histopathological analysis revealed marked splenomegaly with disrupted splenic corpuscle architecture and lymphocyte depletion，significant inflammatory cell infiltration in hepatic portal areas，and testicular structural disorganization with inflammatory infiltration in Zika-infected rats. Conclusions:The SD-Ifnar1 -/-［cc］suckling rat model is successfully established and validated. This model recapitulates systemic Zika virus infection，tissue-specific pathology，and immune response dynamics，providing a robust platform for elucidating viral pathogenesis and advancing antiviral drug development.

The adipose tissue of mammals represents an important energy-storing and endocrine organ, and its dysfunction is relevant to the onset of several health problems, including non-alcoholic fatty liver disease (NAFLD). However, whether treatments targeting adipose dysfunction could alleviate NAFLD has not been well-studied. Adrenomedullin 2 (ADM2), belonging to the CGRP superfamily, is a protective peptide that has been shown to inhibit adipose dysfunction. To investigate the adipose tissue-specific effects of ADM2 on NAFLD, adipose-specific ADM2-overexpressing transgenic (aADM2-tg) mice were developed. When fed a high-fat diet, aADM2-tg mice displayed decreased hepatic triglyceride accumulation compared to wild-type mice, which was attributable to the inhibition of hepatic de novo lipogenesis. Results from lipidomics studies showed that ADM2 decreased ceramide levels in adipocytes through the upregulation of ACER2, which catalyzes ceramide catabolism. Mechanically, activation of adipocyte HIF2α was required for ADM2 to promote ACER2-dependent adipose ceramide catabolism as well as to decrease hepatic lipid accumulation. This study highlights the role of ADM2 and adipose-derived ceramide in NAFLD and suggests that its therapeutic targeting could alleviate disease symptoms.