The global burden of cataracts and its attributable risk factors in 204 countries and territories: a systematic analysis of the global burden of disease study.

Introduction: The global distribution and trends in the attributable burden of cataract risk have rarely been systematically explored. To guide the development of targeted and accurate cataract screening and treatment strategies, we analyzed the burden of cataract disease attributable to known risk factors. Method: This study utilized detailed cataract data from the Global Burden of Disease e 2019, and we analyzed disability-adjusted life years (DALYs) e each risk factor from 1990 to 2019. Additionally, we calculated estimated annual percentage changes (EAPCs) during the study period. Results: The results revealed that from 1990-2019, the global age-standardized DALYs of e attributable to particulate matter pollution, smoking, high fasting glucose plasma and high BMI showed steady downward trends (1990-2009: EAPC = -0.21 [-0.57 -0.14]); 2000-2009: EAPC = -0.95 [-1.01 -0.89]; 2010-2019: EAPC = -1.41 [-1.8 -1.02]). The age-standardized DALYs and mortality caused by each risk factor were highest in the low-middle sociodemographic index (SDI) region (EAPC = -1.77[(-2.19--1.34)]). The overall disease burden of cataracts is lower in males than in females. When analyzing the EAPCs of cataract disease burden for each risk factor individually, we found that the age-standardized disability-adjusted life years caused by particulate matter pollution and smoking decreased (PMP1990-2009: EAPC = -0.53 [-0.9--0.16]; 2000-2009: EAPC = -1.39 [-1.45--1.32]; 2010-2019: EAPC = -2.27 [-2.75--1.79]; smoking 2000 to 2009: EAPC = -1.51 [-1.6--1.43], 2009 to 2019: EAPC = -1.34 [-1.68--1])), while high fasting plasma glucose and high body mass index increased annually (HFPG1990 to 1999: EAPC = 1.27 [0.89-1.65], 2000 to 2009: EAPC = 1.02 [0.82-1.22], 2010-2019: EAPC = 0.44 [0.19-0.68]; HBMI 1990 to 1999: EAPC = 1.65 [1.37-1.94], 2000 to 2009: EAPC = 1.56 [1.43-1.68], 2010-2019: EAPC = 1.47 [1.18-1.77]). Disscussion: The burden of cataracts caused by ambient particulate matter and smoking is increasing in low, low-middle SDI areas, and specific and effective measures are urgently needed. The results of this study suggest that reducing particulate matter pollution, quitting smoking, controlling blood glucose, and lowering BMI could play important roles in reducing the occurrence of cataracts, especially in older people.

Altered functional connectivity subserving expressed emotion environments in schizophrenia: An fNIRS study.

Living in high-expressed emotion (EE) environments, characterized by critical, hostile, or over-involved family attitudes, has been linked to increased relapse rates among individuals with schizophrenia (SZ). In our previous work (Wang et al., 2023), we conducted the first feasibility study of using functional near-infrared spectroscopy (fNIRS) with our developed EE stimuli to examine cortical hemodynamics in SZ. To better understand the neural mechanisms underlying EE environmental factors in SZ, we extended our investigation by employing functional connectivity (FC) analysis with a graph theory approach to fNIRS signals. Relative to healthy controls (N=40), individuals with SZ (N=37) exhibited altered connectivity across the medial prefrontal cortex (mPFC), left ventrolateral prefrontal cortex (vlPFC), and left superior temporal gyrus (STG) while exposed to EE environments. Notably, while individuals with SZ were exposed to high-EE environments, (i) reduced connectivity was observed in these brain regions and (ii) the left vlPFC-STG coupling was found to be associated with the negative symptom severity. Taken together, our FC findings suggest individuals with SZ experience a more extensive disruption in neural functioning and coordination, particularly indicating an increased susceptibility to high-EE environments. This further supports the potential utility of integrating fNIRS with the created EE stimuli for assessing EE environmental influences, paving the way for more targeted therapeutic interventions.

MicroRNA classification and discovery for major depressive disorder diagnosis: Towards a robust and interpretable machine learning approach.

BACKGROUND: Major depressive disorder (MDD) is notably underdiagnosed and undertreated due to its complex nature and subjective diagnostic methods. Biomarker identification would help provide a clearer understanding of MDD aetiology. Although machine learning (ML) has been implemented in previous studies to study the alteration of microRNA (miRNA) levels in MDD cases, clinical translation has not been feasible due to the lack of interpretability (i.e. too many miRNAs for consideration) and stability. METHODS: This study applied logistic regression (LR) model to the blood miRNA expression profile to differentiate patients with MDD (n = 60) from healthy controls (HCs, n = 60). Embedded (L1-regularised logistic regression) feature selector was utilised to extract clinically relevant miRNAs, and optimized for clinical application. RESULTS: Patients with MDD could be differentiated from HCs with the area under the receiver operating characteristic curve (AUC) of 0.81 on testing data when all available miRNAs were considered (which served as a benchmark). Our LR model selected miRNAs up to 5 (known as LR-5 model) emerged as the best model because it achieved a moderate classification ability (AUC = 0.75), relatively high interpretability (feature number = 5) and stability (ϕ̂Z=0.55) compared to the benchmark. The top-ranking miRNAs identified by our model have demonstrated associations with MDD pathways involving cytokine signalling in the immune system, the reelin signalling pathway, programmed cell death and cellular responses to stress. CONCLUSION: The LR-5 model, which is optimised based on ML design factors, may lead to a robust and clinically usable MDD diagnostic tool.

Natural products for the treatment of age-related macular degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is a chronic retinal disease that significantly influences the vision of the elderly. PURPOSE: There is no effective treatment and prevention method. The pathogenic process behind AMD is complex, including oxidative stress, inflammation, and neovascularization. It has been demonstrated that several natural products can be used to manage AMD, but systematic summaries are lacking. STUDY DESIGN AND METHODS: PubMed, Web of Science, and ClinicalTrials.gov were searched using the keywords "Biological Products" AND "Macular Degeneration" for studies published within the last decade until May 2023 to summarize the latest findings on the prevention and treatment of age-related macular degeneration through the herbal medicines and functional foods. RESULTS: The eligible studies were screened, and the relevant information about the therapeutic action and mechanism of natural products used to treat AMD was extracted. Our findings demonstrate that natural substances, including retinol, phenols, and other natural products, prevent the development of new blood vessels and protect the retina from oxidative stress in cells and animal models. However, they have barely been examined in clinical studies. CONCLUSION: Natural products could be highly prospective candidate drugs used to treat AMD, and further preclinical and clinical research is required to validate it to control the disease.

Using an Interpretable Amino Acid-Based Machine Learning Method to Enhance the Diagnosis of Major Depressive Disorder.

Background: Major depressive disorder (MDD) is a leading cause of disability worldwide. At present, however, there are no established biomarkers that have been validated for diagnosing and treating MDD. This study sought to assess the diagnostic and predictive potential of the differences in serum amino acid concentration levels between MDD patients and healthy controls (HCs), integrating them into interpretable machine learning models. Methods: In total, 70 MDD patients and 70 HCs matched in age, gender, and ethnicity were recruited for the study. Serum amino acid profiling was conducted by means of chromatography-mass spectrometry. A total of 21 metabolites were analysed, with 17 from a preset amino acid panel and the remaining 4 from a preset kynurenine panel. Logistic regression was applied to differentiate MDD patients from HCs. Results: The best-performing model utilised both feature selection and hyperparameter optimisation and yielded a moderate area under the receiver operating curve (AUC) classification value of 0.76 on the testing data. The top five metabolites identified as potential biomarkers for MDD were 3-hydroxy-kynurenine, valine, kynurenine, glutamic acid, and xanthurenic acid. Conclusions: Our study highlights the potential of using an interpretable machine learning analysis model based on amino acids to aid and increase the diagnostic accuracy of MDD in clinical practice.

[Effect and mechanism of Linggui Zhugan Decoction in regulating Sig1R on Angâ ¡-induced cardiomyocyte hypertrophy].

This study aims to explore the mechanism of Linggui Zhugan Decoction(LGZGD) in inhibiting Angiotensin Ⅱ(AngⅡ)-induced cardiomyocyte hypertrophy by regulating sigma-1 receptor(Sig1R). The model of H9c2 cardiomyocyte hypertrophy induced by AngⅡ in vitro was established by preparing LGZGD-containing serum and blank serum. H9c2 cells were divided into normal group, AngⅡ model group, 20% normal rat serum group(20% NSC), and 20% LGZGD-containing serum group. After the cells were incubated with AngⅡ(1 µmol·L~(-1)) or AngⅡ with serum for 72 h, the surface area of cardiomyocytes was detected by phalloidine staining, and the activities of Na~+-K~+-ATPase and Ca~(2+)-Mg~(2+)-ATPase were detected by micromethod. The mitochondrial Ca~(2+) levels were detected by flow cytometry, and the expression levels of atrial natriuretic peptide(ANP), brain natriuretic peptide(BNP), Sig1R, and inositol 1,4,5-triphosphate receptor type 2(IP_3R_2) were detected by Western blot. The expression of Sig1R was down-regulated by transfecting specific siRNA for investigating the efficacy of LGZGD-containing serum on cardiomyocyte surface area, Na~+-K~+-ATPase activity, Ca~(2+)-Mg~(2+)-ATPase activity, mitochondrial Ca~(2+), as well as ANP, BNP, and IP_3R_2 protein expressions. The results showed that compared with the normal group, AngⅡ could significantly increase the surface area of cardiomyocytes and the expression of ANP and BNP(P<0.01), and it could decrease the activities of Na~+-K~+-ATPase and Ca~(2+)-Mg~(2+)-ATPase, the concentration of mitochondrial Ca~(2+), and the expression of Sig1R(P<0.01). In addition, IP_3R_2 protein expression was significantly increased(P<0.01). LGZGD-containing serum could significantly decrease the surface area of cardiomyocytes and the expression of ANP and BNP(P<0.05, P<0.01), and it could increase the activities of Na~+-K~+-ATPase and Ca~(2+)-Mg~(2+)-ATPase, the concentration of mitochondrial Ca~(2+ )(P<0.01), and the expression of Sig1R(P<0.05). In addition, IP_3R_2 protein expression was significantly decreased(P<0.05). However, after Sig1R was down-regulated, the effects of LGZGD-containing serum were reversed(P<0.01). These results indicated that the LGZGD-containing serum could inhibit cardiomyocyte hypertrophy induced by AngⅡ, and its pharmacological effect was related to regulating Sig1R, promoting mitochondrial Ca~(2+ )inflow, restoring ATP synthesis, and protecting mitochondrial function.

Applications of gastric peroral endoscopic myotomy in the treatment of upper gastrointestinal tract disease.

Gastric peroral endoscopic myotomy (G-POME) is an emerging minimally invasive endoscopic technique involving the establishment of a submucosal tunnel around the pyloric sphincter. In 2013, Khashab et al used G-POME for the first time in the treatment of gastroparesis with enhanced therapeutic efficacy, providing a new direction for the treatment of gastroparesis. With the recent and rapid development of G-POME therapy technology, progress has been made in the treatment of gastroparesis and other upper digestive tract diseases, such as congenital hypertrophic pyloric stenosis and gastric sleeve stricture, with G-POME. This article reviews the research progress and future prospects of G-POME for the treatment of upper digestive tract gastrointestinal diseases.

Bibliometric Analysis of Brain Stimulation Technologies in Sleep Disorders.

BACKGROUND Sleep disorders are a common disease faced by people today and can lead to fatigue, lack of concentration, impaired memory, and even death. In recent years, the development of brain stimulation techniques has provided a new perspective for the treatment of sleep disorders. However, there is a lack of bibliometric analyses related to sleep disorders and brain stimulation techniques. Therefore, this study analyzed the application status and trend of brain stimulation technology in sleep disorder research. MATERIAL AND METHODS Articles and reviews published between 1999 and 2023 were retrieved from the Web of Science. CiteSpace was used to visually analyze the publications, countries, institutions, journals, authors, references, and keywords. RESULTS A total of 459 publications were obtained. The number of studies was shown to be on a general upward trend. The country with the largest number of publications was the United States; UDICE-French Research Universities had the highest number of publications; Neurology had the highest citation frequency; 90% of the top 10 references cited were from Journal Citation Reports Q1; Brigo was the author with the highest number of publications; and the most frequent keywords were "transcranial magnetic stimulation", "deep brain stimulation", and "Parkinson disease". CONCLUSIONS Our study used CiteSpace software to analyze 459 studies published since 1999 on brain stimulation techniques for the treatment of sleep disorders, revealing research trends and the current state of the field. Our results will help researchers to understand the existing research quickly and provide direction for future research.

RARPKB: a knowledge-guide decision support platform for personalized robot-assisted surgery in prostate cancer.

BACKGROUND: Robot-assisted radical prostatectomy (RARP) has emerged as a pivotal surgical intervention for the treatment of prostate cancer (PCa). However, the complexity of clinical cases, heterogeneity of PCa, and limitations in physician expertise pose challenges to rational decision-making in RARP. To address these challenges, the authors aimed to organize the knowledge of previously complex cohorts and establish an online platform named the RARP knowledge base (RARPKB) to provide reference evidence for personalized treatment plans. MATERIALS AND METHODS: PubMed searches over the past two decades were conducted to identify publications describing RARP. The authors collected, classified, and structured surgical details, patient information, surgical data, and various statistical results from the literature. A knowledge-guided decision-support tool was established using MySQL, DataTable, ECharts, and JavaScript. ChatGPT-4 and two assessment scales were used to validate and compare the platform. RESULTS: The platform comprised 583 studies, 1589 cohorts, 1 911 968 patients, and 11 986 records, resulting in 54 834 data entries. The knowledge-guided decision support tool provide personalized surgical plan recommendations and potential complications on the basis of patients' baseline and surgical information. Compared with ChatGPT-4, RARPKB outperformed in authenticity (100% vs. 73%), matching (100% vs. 53%), personalized recommendations (100% vs. 20%), matching of patients (100% vs. 0%), and personalized recommendations for complications (100% vs. 20%). Postuse, the average System Usability Scale score was 88.88±15.03, and the Net Promoter Score of RARPKB was 85. The knowledge base is available at: http://rarpkb.bioinf.org.cn . CONCLUSIONS: The authors introduced the pioneering RARPKB, the first knowledge base for robot-assisted surgery, with an emphasis on PCa. RARPKB can assist in personalized and complex surgical planning for PCa to improve its efficacy. RARPKB provides a reference for the future applications of artificial intelligence in clinical practice.

Exploring CCL11 in breast cancer: unraveling its anticancer potential and immune modulatory effects involving the Akt-S6 signaling.

BACKGROUND: CCL11, a chemokine known for recruiting immune cells to the tumor microenvironment (TME), has an unclear role in the context of its expression, patient prognosis, and the presence of tumor-infiltrating immune cells (TILs) in breast cancer. METHODS: The expression of CCL11 in invasive breast cancer (BRCA) was analyzed using TCGA database. Survival curve and Cox regression analysis determined the potential of CCL11 as an independent prognostic indicator. GSEA performed functional analysis on genes related to CCL11. CIBERSORT algorithm quantified the infiltration level of immune cells with varying CCL11 expression. Lastly, the correlation between CCL11 expression and anticancer drug sensitivity was examined. Immunohistochemistry (IHC) and qRT-PCR confirmed CCL11 expression in clinical tissue samples. The anti-tumor efficacy of CCL11 was investigated using CCK-8, plate formation, transwell assay, and Western blot. RESULTS: CCL11 expression was elevated in BRCA tumor tissues compared to adjacent normal tissues. Recurrence-free survival (RFS) was longer in patients with high expression of CCL11. Enrichment and co-expression analyses revealed CCL11's association with numerous immune-related signaling pathways and genes. Validation studies confirmed high CCL11 expression in breast cancer tissues. In vitro experiments substantiated CCL11's anticancer effects in BRCA. CONCLUSION: CCL11 expression correlates with immune cell infiltration in breast cancer, indicating its potential as a prognostic biomarker for BRCA.

FUS-Mediated CircFGFR1 Accelerates the Development of Papillary Thyroid Carcinoma by Stabilizing FGFR1 Protein.

Papillary thyroid carcinoma (PTC) is the most prevalent type of thyroid cancer and its incidence is rising globally. The molecular mechanisms of PTC progression remain unclear, hindering the development of effective treatments. This study focuses on hsa_circ_0008016 (circFGFR1), a circular RNA significantly up-regulated in PTC cells. Silencing circFGFR1 inhibited PTC cell proliferation and increased cell apoptosis, suggesting its role in PTC progression. The RNA-binding protein FUS was identified as a promoter of circFGFR1 formation. While circFGFR1 does not influence FGFR1 mRNA translation, it inhibits ubiquitination and degradation of FGFR1 protein, prolonging its half-life. CircFGFR1 also interacts with protein CBL, inhibiting CBL-mediated ubiquitination of FGFR1 proteins. Rescue assays confirmed circFGFR1 promotes PTC cell growth through mediating FGFR1. This study highlights the potential of circFGFR1 as a therapeutic target, offering insights into PTC's molecular mechanisms, and paving the way for novel treatment strategies.

Numerical Solution of Inverse Problem in Functional Near Infrared Spectroscopy using L1-Norm Method.

It has been more than three decades since researchers began investigating functional near-infrared spectroscopy (fNIRs) and its applications with near-infrared light for use in both clinical and pre-clinical settings. In order to increase the accuracy of fNIRs of complex tissue structures, it is necessary to create more advanced image reconstruction methods. Real fNIRs data have been used to develop an implementation of the L1-Norm approach for tackling the inverse problem in this work. The Monte Carlo (MC) simulation is used to construct the sensitivity matrix for this research. Finally, a numerical algorithm for the L1-Norm approach of image reconstruction is developed and implemented in MATLAB to aid in the process. The results showed good agreement with the actual fNIRs data.

Comprehensive treatment and a rare presentation of Cronkhite-Canada syndrome: Two case reports and review of literature.

BACKGROUND: Cronkhite-Canada syndrome (CCS) is a rare sporadic polyposis syndrome that presents with gastrointestinal and ectodermal symptoms in addition to nutritional deficiencies. CCS combined with hypothyroidism is an even rarer condition, with no standard treatment guidelines. CASE SUMMARY: The present study described 2 patients with CCS: A 67-year-old woman with concomitant hypothyroidism and 68-year-old man treated with endoscopic mucosal resection (EMR). Both patients had multiple gastrointestinal symptoms and ectodermal changes, along with multiple gastrointestinal polyps. Microscopic examination showed that the mucosa in both patients was hyperemic and edematous, with pathologic examination showing distorted, atrophic, and dilated glands. Patient 1 had concomitant hypothyroidism and was treated with levothyroxine. Due to her self-reduction of hormone dose, her disease relapsed. Patient 2 underwent EMR, but refused further hormonal or biological treatments. Subsequently, he was treated with an oral Chinese medical preparation. CONCLUSION: Pharmacotherapy can induce and maintain remission in CCS patients, with adjuvant EMR, long-term follow-up, and endoscopic surveillance being necessary.

The Ongoing Necessity of Sentinel Lymph Node Biopsy for cT1-2N0 Breast Cancer Patients.

Background: Recent clinical trials attempt to determine whether it is appropriate to omit axillary lymph node surgery in patients with cT1-2N0 breast cancer. The study aimed to investigate the true extent of axillary node disease in patients with clinically negative nodes and explore the differences between negative axillary ultrasound (AUS-cN0) and suspicious axillary ultrasound with negative fine-needle aspiration (FNA-cN0). Methods: Pathologically identified T1-2 invasive breast cancer patients with clinically negative nodes were retrospectively analyzed at our center between January 2019 and December 2022. Patients who received any systematic treatment before surgery were excluded from this study. Results: A total of 538 patients were enrolled in this study. 134 (24.9%) patients had pathologically positive nodes, and 404 (75.1%) patients had negative nodes. Univariate analysis revealed that tumor size, T stage, Ki67 level, and vascular invasion (VI) were strongly associated with pathological axillary lymph node positivity. In multivariate analysis, VI was the only independent risk factor for node positivity in patients with cT1-2N0 disease (OR: 3.723, confidence interval [CI]: 2.380-5.824, p < 0.001). Otherwise, pathological node positivity was not significantly different between AUS-cN0 and FNA-cN0 groups (23.4% vs. 28.8%, p = 0.193). However, the rate of high nodal burden (≥3 positive nodes) was significantly higher in FNA-cN0 group. Further investigation revealed that FNA-cN0 and VI were independently associated with a high nodal burden (OR: 2.650, CI: 1.081-6.496, p = 0.033; OR: 3.521, CI: 1.249-9.931, p = 0.017, respectively). Conclusions: cT1-2 breast cancer patients with clinically negative axillary lymph nodes may have pathologically positive lymph nodes and even a high nodal burden. False negatives in AUS and AUS-guided FNA should not be ignored, and sentinel lymph node biopsy remains an ongoing necessity for cT1-2N0 breast cancer patients.

From multi-omics approaches to personalized medicine in myocardial infarction.

Myocardial infarction (MI) is a prevalent cardiovascular disease characterized by myocardial necrosis resulting from coronary artery ischemia and hypoxia, which can lead to severe complications such as arrhythmia, cardiac rupture, heart failure, and sudden death. Despite being a research hotspot, the etiological mechanism of MI remains unclear. The emergence and widespread use of omics technologies, including genomics, transcriptomics, proteomics, metabolomics, and other omics, have provided new opportunities for exploring the molecular mechanism of MI and identifying a large number of disease biomarkers. However, a single-omics approach has limitations in understanding the complex biological pathways of diseases. The multi-omics approach can reveal the interaction network among molecules at various levels and overcome the limitations of the single-omics approaches. This review focuses on the omics studies of MI, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, and other omics. The exploration extended into the domain of multi-omics integrative analysis, accompanied by a compilation of diverse online resources, databases, and tools conducive to these investigations. Additionally, we discussed the role and prospects of multi-omics approaches in personalized medicine, highlighting the potential for improving diagnosis, treatment, and prognosis of MI.

Effect of Anti-D titers in RhD-negative pregnant women on fetuses and newborns: A retrospective study.

BACKGROUND: Transplacental-derived anti-D IgG in RhD-negative pregnant women can trigger an immune response to Rh D-positive red cells in fetuses and newborns. We assessed the effect of anti-D titers in RhD-negative pregnant women on fetuses and newborns. METHODS: The clinical data of 142 singleton RhD-sensitized pregnancies were retrospectively collected. The pregnant women received routine prenatal care and the newborns had standard care. Based on the tertile categories of the pregnancies, the maximum titers of anti-D IgG in the pregnant women were divided into three groups ranging from low to high as follows: low-titer group (anti-D titer: 1:4-1:128, n = 57); medium-titer group (anti-D titer: 1:256-1:512, n = 50); and high-titer group (anti-D titer: 1:1024-1:4096, n = 35). RESULTS: The frequencies of major neonatal complications did not significantly differ among the three groups. The high-titer group had the highest frequency of pregnancies requiring intrauterine transfusion (IUT) and number of IUTs among the three groups. The high-titer group had a significantly higher frequency of newborns treated with top-up transfusion, number of top-up transfusions, frequency of newborns treated with exchange transfusion (ET), and number of ETs when compared to the low-titer group. CONCLUSION: Higher anti-D titers in RhD-negative pregnant women predict more severe fetal and neonatal hemolytic anemia. Increasing maternal anti-D titers results in an increased need for IUTs, and neonatal top-up transfusions and ETs. Methods for reducing titers of anti-D IgG in RhD-sensitized pregnant women warrants further investigation.

Sequential annulation and isomerisation reaction of 3-acylmethylidene oxindoles with Huisgen zwitterions and synthesis of 5-(3-oxindolyl)oxazoles.

Herein, we report a facile synthesis of 5-(3-oxindolyl)oxazole derivatives via a sequential annulation and isomerisation reaction of 3-acylmethylidene oxindoles with in situ generated Huisgen zwitterions (HZs) from PPh3 and azodicarboxylates. This reaction exhibits good functional group tolerance with 30 examples of structurally diverse products prepared with moderate to good efficiencies (up to 88% yield), thus providing a generally applicable route to the biologically important 5-(3-indolyl)oxazole structural motifs. Key to the success of this sequential one-pot strategy is the utilization of DBU as a base to promote the isomerisation process of the corresponding intermediate annulation products.

Visualization Analysis of Research Trends and Hotspots in Inspiratory Muscle Training.

BACKGROUND Inspiratory muscle training (IMT) aims to train inspiratory muscles based mainly on the diaphragm by applying a load resistance during the inspiratory process. Many papers related to IMT have been published in various journals; however, no articles objectively and directly present the development trends and research hotspots of IMT. Therefore, this study used CiteSpace to visually analyze recent IMT-related publications to provide valuable information for future IMT-related studies. MATERIAL AND METHODS CiteSpace was applied to analyze the IMT-related publications by countries, institutions, journals, authors, references, and keywords. RESULTS We included 504 papers. The number of IMT-related publications trended upward between 2009 and 2022. Leuven had the highest number of publications by an institution. The American Journal of Respiratory and Critical Care Medicine was the most frequently co-cited journal. Half of the top 10 references cited were from Journal Citation Reports (JCR) Q1 and half were about the application of IMT in chronic obstructive pulmonary disorder. Gosselink was the author with the highest number of publications and Aldrich was the author with the highest co-citation frequency. The preponderance of studies on the surgical population and postoperative pulmonary complications reflects potential application of IMT in enhanced recovery after surgery. CONCLUSIONS This study provides scholars with important information related to IMT research. It analyzes IMT research trends and status, which can help researchers identify primary topics in the field and find ways to explore new research directions to promote the application of IMT in clinical practice and the cooperation of IMT-related disciplines.

An artificial intelligence method for predicting postoperative urinary incontinence based on multiple anatomic parameters of MRI.

Background: Deep learning methods are increasingly applied in the medical field; however, their lack of interpretability remains a challenge. Captum is a tool that can be used to interpret neural network models by computing feature importance weights. Although Captum is an interpretable model, it is rarely used to study medical problems, and there is a scarcity of data regarding MRI anatomical measurements for patients with prostate cancer after undergoing Robotic-Assisted Radical Prostatectomy (RARP). Consequently, predictive models for continence that use multiple types of anatomical MRI measurements are limited. Methods: We explored the energy efficiency of deep learning models for predicting continence by analyzing MRI measurements. We analyzed and compared various statistical models and provided reference examples for the clinical application of interpretable deep-learning models. Patients who underwent RARP at our institution between July 2019 and December 2020 were included in this study. A series of clinical MRI anatomical measurements from these patients was used to discover continence features, and their impact on continence was primarily evaluated using a series of statistical methods and computational models. Results: Age and six other anatomical measurements were identified as the top seven features of continence by the proposed model UINet7 with an accuracy of 0.97, and the first four of these features were also found by primary statistical analysis. Conclusions: This study fills the gaps in the in-depth investigation of continence features after RARP due to the limitations of clinical data and applicable models. We provide a pioneering example of the application of deep-learning models to clinical problems. The interpretability analysis of deep learning models has the potential for clinical applications.