1.Deep learning model based on fundus images for detection of coronary artery disease with mild cognitive impairment
Yi YE ; Wei FENG ; Yao-dong DING ; Qing CHEN ; Yang ZHANG ; Li LIN ; Tong MA ; Bin WANG ; Xian-gang CHANG ; Zong-yuan GE ; Xiao-yi WANG ; Long-jun CAI ; Yong ZENG
Chinese Journal of Interventional Cardiology 2025;33(6):303-311
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.
2.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
3.Deep learning model based on fundus images for detection of coronary artery disease with mild cognitive impairment
Yi YE ; Wei FENG ; Yao-dong DING ; Qing CHEN ; Yang ZHANG ; Li LIN ; Tong MA ; Bin WANG ; Xian-gang CHANG ; Zong-yuan GE ; Xiao-yi WANG ; Long-jun CAI ; Yong ZENG
Chinese Journal of Interventional Cardiology 2025;33(6):303-311
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.
4.Antimicrobial resistance surveillance in the bacterial strains isolated from pediatric intensive care units in China:results from 2020 to 2022
Jing LIU ; Huiyuan YAN ; Gangfeng YAN ; Guoping LU ; Pan FU ; Chuanqing WANG ; Danqun JIN ; Wenjia TONG ; Chenyu ZHANG ; Jianli CHEN ; Yi LIN ; Jia LEI ; Yibing CHENG ; Qunqun ZHANG ; Kaijie GAO ; Yuanyuan CHEN ; Shufang XIAO ; Juan HE ; Li JIANG ; Huimin XU ; Yuxia LI ; Hanghai DING ; Hehe CHEN ; Yao ZHENG ; Qunying CHEN ; Ying WANG ; Hong REN ; Chenmei ZHANG ; Zhenjie CHEN ; Mingming ZHOU ; Yucai ZHANG ; Yiping ZHOU ; Zhenjiang BAI ; Saihu HUANG ; Lili HUANG ; Weiguo YANG ; Weike MA ; Qing MENG ; Pengwei ZHU ; Yong LI ; Yan XU ; Yi WANG ; Yanqiang DU ; Huijun CAI ; Bizhen ZHU ; Huixuan SHI ; Shaoxian HONG ; Yukun HUANG ; Meilian HUANG
Chinese Journal of Infection and Chemotherapy 2025;25(3):303-311
Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2%)and gram-negative organisms(60.8%).The top three organisms were S.aureus(13.6%,1 453/10 688),A.baumannii(10.0%,1 067/10 688),and coagulase-negative Staphylococcus(9.9%,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1%,19.4%,8.8%,30.9%,67.4%,and 28.8%,respectively.Overall,more than 50%of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25%of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80%of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3%in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.
5.GOLM1 promotes cholesterol gallstone formation via ABCG5-mediated cholesterol efflux in metabolic dysfunction-associated steatohepatitis livers
Yi-Tong LI ; Wei-Qing SHAO ; Zhen-Mei CHEN ; Xiao-Chen MA ; Chen-He YI ; Bao-Rui TAO ; Bo ZHANG ; Yue MA ; Guo ZHANG ; Rui ZHANG ; Yan GENG ; Jing LIN ; Jin-Hong CHEN
Clinical and Molecular Hepatology 2025;31(2):409-425
Background/Aims:
Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation.
Methods:
The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation.
Results:
MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs.
Conclusions
In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.
6.GOLM1 promotes cholesterol gallstone formation via ABCG5-mediated cholesterol efflux in metabolic dysfunction-associated steatohepatitis livers
Yi-Tong LI ; Wei-Qing SHAO ; Zhen-Mei CHEN ; Xiao-Chen MA ; Chen-He YI ; Bao-Rui TAO ; Bo ZHANG ; Yue MA ; Guo ZHANG ; Rui ZHANG ; Yan GENG ; Jing LIN ; Jin-Hong CHEN
Clinical and Molecular Hepatology 2025;31(2):409-425
Background/Aims:
Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation.
Methods:
The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation.
Results:
MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs.
Conclusions
In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.
7.GOLM1 promotes cholesterol gallstone formation via ABCG5-mediated cholesterol efflux in metabolic dysfunction-associated steatohepatitis livers
Yi-Tong LI ; Wei-Qing SHAO ; Zhen-Mei CHEN ; Xiao-Chen MA ; Chen-He YI ; Bao-Rui TAO ; Bo ZHANG ; Yue MA ; Guo ZHANG ; Rui ZHANG ; Yan GENG ; Jing LIN ; Jin-Hong CHEN
Clinical and Molecular Hepatology 2025;31(2):409-425
Background/Aims:
Metabolic dysfunction-associated steatohepatitis (MASH) is a significant risk factor for gallstone formation, but mechanisms underlying MASH-related gallstone formation remain unclear. Golgi membrane protein 1 (GOLM1) participates in hepatic cholesterol metabolism and is upregulated in MASH. Here, we aimed to explore the role of GOLM1 in MASH-related gallstone formation.
Methods:
The UK Biobank cohort was used for etiological analysis. GOLM1 knockout (GOLM1-/-) and wild-type (WT) mice were fed with a high-fat diet (HFD). Livers were excised for histology and immunohistochemistry analysis. Gallbladders were collected to calculate incidence of cholesterol gallstones (CGSs). Biles were collected for biliary lipid analysis. HepG2 cells were used to explore underlying mechanisms. Human liver samples were used for clinical validation.
Results:
MASH patients had a greater risk of cholelithiasis. All HFD-fed mice developed MASH, and the incidence of gallstones was 16.7% and 75.0% in GOLM1-/- and WT mice, respectively. GOLM1-/- decreased biliary cholesterol concentration and output. In vivo and in vitro assays confirmed that GOLM1 facilitated cholesterol efflux through upregulating ATP binding cassette transporter subfamily G member 5 (ABCG5). Mechanistically, GOLM1 translocated into nucleus to promote osteopontin (OPN) transcription, thus stimulating ABCG5-mediated cholesterol efflux. Moreover, GOLM1 was upregulated by interleukin-1β (IL-1β) in a dose-dependent manner. Finally, we confirmed that IL-1β, GOLM1, OPN, and ABCG5 were enhanced in livers of MASH patients with CGSs.
Conclusions
In MASH livers, upregulation of GOLM1 by IL-1β increases ABCG5-mediated cholesterol efflux in an OPN-dependent manner, promoting CGS formation. GOLM1 has the potential to be a molecular hub interconnecting MASH and CGSs.
8.Protective effect of Sanfeng Tongqiao Dropping Pills against house dust mite-induced allergic asthma in mice
Tong-wen ZUO ; Xiao-qun GU ; Shu-xian SUN ; Lin LI ; Ya-jun SONG ; Fu-man HUANG ; Qian ZHAO ; Kang ZHOU ; Jie ZHENG ; Min HONG
Chinese Traditional Patent Medicine 2025;47(8):2542-2549
AIM To investigate the protective effect of Sanfeng Tongqiao Dropping Pills against house dust mite(HDM)-induced allergic asthma in mice.METHODS Compared to the intact BALB/c mice in the blank control group,the BALB/c mice randomly assigned into the model group,the dexamethasone group(0.67 mg/kg),and the low-dose,medium-dose,and high-dose Sanfeng Tongqiao Dropping Pills groups(15,30 and 60 mg/kg),were induced into acute allergic asthma models via weekly intraperitoneal sensitization with 0.1 mL HDM solution(0.5 mg/mL)for three weeks followed by three consecutive daily intranasal challenges with 10 μL HDM solution(2.5 mg/mL)starting in the third week.The drug administered continuously 7 days after the last excitation.The mice had their airway reactive Penh value detected,their pulmonary pathological changes observed by HE staining,their blood eosinophils(EOS)counted,their Th2 cytokines in lung tissue and serum IgE levels detected by ELISA,and their number of peripheral blood mononuclear cells(PBMC)and pulmonary Th2 cells detected by flow cytometry.Chronic allergic asthma was induced in grouped BALB/c mice through repeated intranasal challenges with 10 μL HDM solution(2.5 mg/mL)administered five times weekly for five consecutive weeks.Drug treatment continued for 14 days following the final challenge.After the final treatment,the mice had their pulmonary pathological changes observed by HE staining,and their levels of Th2 cytokines in B ALF and lung tissue and serum IgE detected by ELISA.RESULTS Compared to the blank control group,the acute allergic asthma model group exhibited increases in Penh value,EOS count and IgE level in serum,IL-4 and IL-5 levels in lung tissue(P<0.01);obvious pulmonary inflammatory cells infiltration,and thickened airway wall;and increase in pulmonary number of Th2 cells(P<0.01).Compared to the model group,the groups intervened with Sanfeng Tongqiao Dropping Pills demonstrated decreased Penh value,serum EOS count,IgE level and IL-5 level in lung tissue(P<0.05,P<0.01);reduced pulmonary inflammatory infiltration and alleviated airway wall thickening;and decreased number of pulmonary Th2 cells.Compared to the blank group,the chronic allergic asthma model group showed obvious pulmonary inflammatory infiltration and airway wall thickening;and increased EOS count and IgE level in serum,IL-4 and IL-13 in lung tissue and IL-14 in BALF(P<0.05,P<0.01).Compared to the model group,the groups intervened with either medium-dose or high-dose Sanfeng Tongqiao Dropping Pills demonstrated reduced pulmonary inflammatory infiltration;and decreased serum EOS count,IgE level,IL-13 in lung tissue and IL-14 in BALF(P<0.05,P<0.01).CONCLUSION Sanfeng Tongqiao Dropping Pills reduce Th2 cells in peripheral blood and lung tissue,suppress type 2 inflammation,and thereby alleviate allergic asthma.
9.Effect of Draxin on the migration characteristics of trunk neural crest cells in the embryonic mouse spinal cord
Zu-Qi CUI ; Xiao-Jin MIAO ; Ze-Lin GU ; Meng-Fei GONG ; Huan CHEN ; Shu-Han YANG ; Tong-Yu LIU ; San-Bing ZHANG ; Yu-Hong SU
Acta Anatomica Sinica 2025;56(2):150-157
Objective To investigate the effect of dorsal repulsive axon guidance protein(Draxin)on the migration of trunk neural crest cells during the early development of embryonic mouse spinal cord.Methods Immunohistochemistry and in situ hybridization were used to detect the expression characteristics of Draxin in early embryonic spinal cord(8 mice each group);In situ hybridization was used to detect the change of migration characteristics of trunk neural crest cells in early embryonic spinal cord of different types of mouse(5 mice each group);in vitro culture method was used to check the effect of Draxin on the migration characteristics of embryonic mouse trunk neural crest cells(16 mice each group).Resultsβ-galactosidase gene Z(LacZ)gene was introduced when Draxin gene was knocked out to produce Draxin gene knockout mice.β-galactosidase staining was used to detect LacZ gene expression in Draxin knockout embryonic mice,and the result showed that Draxin expression was observed in the spinal cord of early embryonic mice since 9.5 days(E9.5).Draxin expression was obvious in the embryonic mice spinal cord in E10.5 period.In situ hybridization was used to detect the expression of Draxin gene in the spinal cord of wild type embryonic mice,and the result further verified the obvious expression of Draxin in the early embryonic mice spinal cord in El0.5 period.Sox10 in situ hybridization was used to detect neural crest cell migration in the spinal cord of embryonic mice in E10.5 period.The result showed that segmental migration of neural crest cells in the early embryonic spinal cord of some Draxin knockout mice was delayed compared with the wild type mice.The effect of Draxin on the migration of wild type early embryonic mice trunk neural crest cells in vitro was tested.The result showed that Draxin reduced the migration distance of neural crest cells in vitro.Conclusion In the early developmental stage of embryonic spinal cord(E9.5-E10.5),neural crest cells migrated exuberant.At the same time,Draxin plays an important inhibitory function in the formation of the specific migration pathways of trunk neural crest cells by promoting neural crest cells migrating away from Draxin expressing regions.
10.Targeting Programmed Cell Death in Acquired Sensorineural Hearing Loss: Ferroptosis, Necroptosis, and Pyroptosis.
Shasha ZHANG ; Hairong XIAO ; Yanqin LIN ; Xujun TANG ; Wei TONG ; Buwei SHAO ; He LI ; Lei XU ; Xiaoqiong DING ; Renjie CHAI
Neuroscience Bulletin 2025;41(6):1085-1102
Sensorineural hearing loss (SNHL), the most commonly-occurring form of hearing loss, is caused mainly by injury to or the loss of hair cells and spiral ganglion neurons in the cochlea. Numerous environmental and physiological factors have been shown to cause acquired SNHL, such as ototoxic drugs, noise exposure, aging, infections, and diseases. Several programmed cell death (PCD) pathways have been reported to be involved in SNHL, especially some novel PCD pathways that have only recently been reported, such as ferroptosis, necroptosis, and pyroptosis. Here we summarize these PCD pathways and their roles and mechanisms in SNHL, aiming to provide new insights and potential therapeutic strategies for SNHL by targeting these PCD pathways.
Humans
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Hearing Loss, Sensorineural/metabolism*
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Necroptosis/drug effects*
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Pyroptosis/drug effects*
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Ferroptosis/drug effects*
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Animals

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