Prevalence and Patterns of Insomnia Symptoms Among People Aged 65 and Above in Guangdong Province, China.

Objective: This survey investigated the prevalence, distribution, and correlative factors of insomnia symptoms among people aged 65 and above in Guangdong Province, China. Methods: The Guangdong Mental Health Survey was conducted on the elderly in all 21 cities of Guangdong Province from September to December 2021. Multistage stratified cluster sampling was adopted, and 16 377 adult residents were interviewed face-to-face, from which 4001 elderly participants aged 65 and above were included for this study. Complex weighted adjustment methods were applied to weight the data. Multinomial logistic regression was applied to test the independent associations of clinical insomnia symptoms (CIS) and subthreshold insomnia symptoms (SIS) with the factors. Results: The pooled estimate of insomnia symptoms was 13.44% [95% confidence interval (CI): 12.2 %-14.7%]. The 1-month weighted prevalence of SIS and CIS were 11.15% (95% CI: 10.05%-12.37%) and 2.28% (95%CI: 1.77%-2.94%), respectively. Multinomial logistic regression analysis revealed that urban residence, irregular diet, low body mass index, chronic disease, napping 3-4/week, early changes in dementia, symptoms of subthreshold depression, subthreshold generalized anxiety, and generalized anxiety disorder were positively associated with SIS. Additionally, living in urban areas, having chronic diseases, symptoms of subthreshold depression, major depressive disorder, subthreshold generalized anxiety, generalized anxiety disorder were positively associated with CIS. Conclusion: Insomnia symptoms, including CIS and SIS, were prevalent among the elderly in Guangdong Province. Given the high burden of CIS and SIS, policymakers and healthcare professionals must explore and treat the related factors accordingly.

The Role of Depression and Anxiety in the Relationship Between Arthritis and Cognitive Impairment in Chinese Older Adults.

BACKGROUND: Mental disorders and cognitive impairment are common in older patients with arthritis. While it is recognized that mental conditions may play a role in the connection between arthritis and cognitive impairment, the precise underlying relationship remains uncertain. METHODS: The data was derived from the baseline survey of the Guangdong Mental Health Survey in South China, involving a sample of 3,764 citizens aged 65 and older. An array of aspects were explored, including socio-demographics, lifestyle behaviors, self-reported chronic conditions, depression, anxiety, and cognitive impairment. Logistic regression analyses examined the association between arthritis and cognitive impairment after adjustment for potential confounders. Serial mediation models were used to examine whether depression or anxiety played a mediating role in the arthritis-cognitive impairment linkage. RESULTS: The prevalence rates of cognitive impairment and arthritis of the older adults were 28.9% and 12.1%, respectively. Compared to those without arthritis, participants with arthritis were at a higher risk of cognitive impairment (OR = 1.322, 95%CI: 1.022-1.709) after adjustment for socio-demographics, lifestyle behaviors, and mental health conditions. Serial mediation analyses indicated that depressive and anxiety symptoms co-played a serial mediating role in the association between arthritis and cognitive impairment (B1 = 0.025, 95%CI: 0.005-0.052; B2 = 0.050, 95%CI: 0.021-0.086). CONCLUSIONS: Arthritis may heighten cognitive impairment risk in Chinese older adults, and the relationship was potentially mediated by depressive and anxiety symptoms. Future interventions should be considered, integrating mental health assessments into arthritis care frameworks and being alert to possible cognitive impairment.

Development of a Cost-Effective 3D-Printed Airway Suction Simulator for Respiratory Therapy Students.

BACKGROUND: Three-dimensional (3D)-printed models are cost-effective and can be customized by trainers. This study designed a 3D-printed airway suction simulator for use by respiratory therapy (RT) students. The objective was to demonstrate the cost-effectiveness and application of 3D-printed models in respiratory care training, aiming to enhance the educational experience for RT students. METHODS: This study developed a 3D-printed airway suction simulator that was cost-effective. A randomized controlled trial was conducted involving RT students to compare effectiveness in a 3D-model group and a control group. Skill assessments and written examinations were used to evaluate the participants' knowledge and skills. RESULTS: A total of 38 second-year RT students were randomly assigned to either the 3D-model group (n = 19) or the control group (n = 19). One participant in the 3D-model group was lost to follow-up during the planned direct observation of procedural skills (DOPS) assessment and satisfaction questionnaire completion. The posttest written examination scores were significantly higher in the 3D-model group than in the control group (100% vs 80%, P = .02). The scores from the DOPS and satisfaction questionnaire were comparable in the 2 groups. CONCLUSIONS: This study demonstrated that 3D printing can be used to create a safe and cost-effective airway suction simulator for use by RT students, with potential to enhance training methods. Further research is necessary.

[High-throughput screening of 54 alternative plasticizers in sesame oil using gas chromatography-quadrupole time-of-flight mass spectrometry].

Restrictions on the use of phthalates have led to the wide use of alternative plasticizers (APs) such as organophosphate, adipate, citrate, and sebacate. However, because plasticizers combine with polymers in plastic products via unstable noncovalent bonds, they can easily migrate out of these products, causing environmental pollution. In particular, their migration out of food packaging, containers, and other food-contact materials and into food has raised great concerns. Toxicological studies have shown that APs contain potentially toxic substances that can affect endocrine functions and cause neurotoxicity, genotoxicity, and other adverse effects. Thus, their potential risks to food should not be underestimated. Sesame oil is a necessity in daily cooking. The results of risk monitoring in recent years have indicated that sesame oil often contains phthalates in excess of the standard limits. However, the potential risks of APs in sesame oil have not yet been reported. Some common detection methods for APs include gas chromatography-mass spectrometry, gas chromatography-triple quadrupole mass spectrometry, and liquid chromatography-triple quadrupole mass spectrometry. Unfortunately, these methods use low-resolution mass spectrometry and are limited by the resolution, scan rate, and analysis mode. Gas chromatography-quadrupole time-of-flight mass spectrometry (GC-Q-TOF/MS) has the advantages of high resolution, sensitivity, and analysis speed. In full-scan mode, GC-Q-TOF/MS can accurately collect the full-spectrum mass number of target compounds with low content levels in complex substrates, thereby realizing efficient screening and quantitative analysis. It shows outstanding advantages in the trace analysis of pesticide residues and pollutants. Furthermore, it features strong qualitative and high screening abilities. Establishment of a personal compound database and library (PCDL) addresses limitations in the number of compounds that can be measured and enables the rapid identification of targets without the use of standard products. In addition, increasing the number of targets for synchronous screening enables the retrospective analysis of new targets. In this study, a method based on GC-Q-TOF/MS was developed for the determination of 54 APs in sesame oil. The samples were extracted with acetonitrile and purified using a PSA/silica solid-phase extraction column. The mass-spectral information of the samples was then collected by GC-Q-TOF/MS in full-scan mode, and the 54 APs were searched using an established high-resolution mass-spectrum database to simultaneously achieve the broad-spectrum screening, qualitative identification, and quantitative analysis of multiple targets. The effects of different extraction solvents and purification methods on sample extraction and purification were compared. The accuracy of the screening results was improved by optimizing the GC-separation conditions, quality-extraction window, retention-time deviation, and other screening parameters. The screening detection limits (SDLs) of the 54 APs ranged from 0.01 to 0.02 mg/kg; specifically, the SDL of 41 compounds was 0.01 mg/kg and that of 13 compounds were 0.02 mg/kg. The limits of quantification were in the range of 0.02-0.04 mg/kg. A total of 80 sesame-oil samples were rapidly screened using this method under optimal conditions. Five APs were identified from the 80 sesame-oil samples and quantitatively analyzed using the matrix-matched external-standard method. The results of this quantitative methodology showed that the five APs had good linear relationships in the range of 0.01-0.2 mg/L, with all correlation coefficients greater than 0.99. The accuracy and precision of the method were verified using a standard recovery test with blank sesame-oil samples. Under the three standard levels of 0.04, 0.08, and 0.2 mg/kg, the recoveries of the five APs ranged from 71.3% to 97.8%, and the relative standard deviations (RSDs) ranged from 0.4% to 6.1%(n=6). The developed method is fast, accurate, sensitive, and has high throughput. Thus, it can realize the efficient screening, qualitative identification, and quantitative analysis of the 54 APs in sesame oil and provides a potential solution for the monitoring of other contaminants in food.

Identified RP2 as a prognostic biomarker for glioma, facilitating glioma pathogenesis mainly via regulating tumor immunity.

Glioma is the most common primary intracranial tumor in the central nervous system, with a high degree of malignancy and poor prognosis, easy to recur, difficult to cure. The mutation of Retinitis Pigmentosa 2 (RP2) can cause retinitis pigmentosa, it is a prognostic factor of osteosarcoma, however, its role in glioma remains unclear. Based on the data from TCGA and GTEx, we identified RP2 as the most related gene for glioma by WGCNA, and used a series of bioinformatics analyses including LinkedOmics, GSCA, CTD, and so on, to explore the expression of RP2 in glioma and the biological functions it is involved in. The results showed that RP2 was highly expressed in glioma, and its overexpression could lead to poor prognosis. In addition, the results of enrichment analysis showed that RP2 was highly correlated with cell proliferation and immune response. And then, we found significant enrichment of Macrophages among immune cells. Furthermore, our experiments have confirmed that Macrophages can promote the development of glioma by secreting or influencing the secretion of some cytokines. Moreover, we investigated the influence of RP2 on the immunotherapy of glioma and the role of m6A modification in the influence of RP2 on glioma. Ultimately, we determined that RP2 is an independent prognostic factor that is mainly closely related to immune for glioma.

Determining a multimodal aging clock in a cohort of Chinese women.

BACKGROUND: Translating aging rejuvenation strategies into clinical practice has the potential to address the unmet needs of the global aging population. However, to successfully do so requires precise quantification of aging and its reversal in a way that encompasses the complexity and variation of aging. METHODS: Here, in a cohort of 113 healthy women, tiled in age from young to old, we identified a repertoire of known and previously unknown markers associated with age based on multimodal measurements, including transcripts, proteins, metabolites, microbes, and clinical laboratory values, based on which an integrative aging clock and a suite of customized aging clocks were developed. FINDINGS: A unified analysis of aging-associated traits defined four aging modalities with distinct biological functions (chronic inflammation, lipid metabolism, hormone regulation, and tissue fitness), and depicted waves of changes in distinct biological pathways peak around the third and fifth decades of life. We also demonstrated that the developed aging clocks could measure biological age and assess partial aging deceleration by hormone replacement therapy, a prevalent treatment designed to correct hormonal imbalances. CONCLUSIONS: We established aging metrics that capture systemic physiological dysregulation, a valuable framework for monitoring the aging process and informing clinical development of aging rejuvenation strategies. FUNDING: This work was supported by the National Natural Science Foundation of China (32121001), the National Key Research and Development Program of China (2022YFA1103700 and 2020YFA0804000), the National Natural Science Foundation of China (81502304), and the Quzhou Technology Projects (2022K46).

[Metabolomics study of Berberidis Radix in intervening ulcerative colitis based on UPLC-Q-TOF-MS].

The effect of Tujia medicine Berberidis Radix on endogenous metabolites in the serum and feces of mice with ulcerative colitis(UC) induced by dextran sulfate sodium(DSS) was analyzed by metabolomics technology to explore the metabolic pathway and underlying mechanism of Berberidis Radix in the intervention of UC. The UC model was induced in mice by DSS. Body weight, disease activity index(DAI), and colon length were recorded. The levels of tumor necrosis factor-α(TNF-α) and interleukin-10(IL-10) in colon tissues were determined by ELISA. The levels of endogenous metabolites in the serum and feces were detected by ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS). Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed to characterize and screen differential metabolites. The potential metabolic pathways were analyzed by MetaboAnalyst 5.0. The results showed that Berberidis Radix could significantly improve the symptoms of UC mice and increase the level of the anti-inflammatory factor IL-10. A total of 56 and 43 differential metabolites were identified in the serum and feces, respectively, belonging to lipids, amino acids, fatty acids, etc. After the intervention by Berberidis Radix, the metabolic disorder gradually recovered. The involved metabolic pathways included biosynthesis of phenylalanine, tyrosine, and tryptophan, linoleic acid metabolism, phenylalanine metabolism, and glycerophospholipid metabolism. Berberidis Radix can alleviate the symptoms of mice with DSS-induced UC, and the mechanism may be closely related to the re-gulation of lipid metabolism, amino acid metabolism, and energy metabolism.

An Amphiphilic Star-Shaped Polymer (Star-PEG-PCL2) used as a Stationary Phase for GC.

A star-shaped polymer (Star-PEG-PCL2) was synthesized with PCL and PEG and used as a stationary phase for gas chromatography. The statically coated Star-PEG-PCL2 column exhibited an efficiency of 2260 plates/m determined by naphthalene at 120 °C and moderate polarity. The Star-PEG-PCL2 column showed high resolution performance for isomers of a wide ranging polarity, including methylnaphthalenes, halogenated benzenes, nitrobenzene, phenols, and anilines, and displayed dual-nature selectivity for a mixture of 17 analytes. Also, the Star-PEG-PCL2 column exhibited good separation performance and column inertness for Grob test mixture and a series of cis-/trans-isomers. In addition, it exhibited advantageous separation performance over the commercial HP-35 and PEG-20M columns for chloroaniline and bromoaniline isomers through its unique three-dimensional framework. In conclusion, it has good potential as a new stationary phase for separating a variety of analytes because of its special structure and excellent separation performance.

Comprehensive analysis reveals TSEN54 as a robust prognosis biomarker and promising immune-related therapeutic target for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma represents the most common primary malignancy of all liver cancer types and its prognosis is usually unsatisfactory. TSEN54 encodes a protein constituting a subunit of the tRNA splicing endonuclease heterotetramer. Previous researches concentrated on the contribution of TSEN54 in pontocerebellar hypoplasia, but no studies have yet reported its role in HCC. METHODS: TIMER, HCCDB, GEPIA, HPA, UALCAN, MEXPRESS, SMART, TargetScan, RNAinter, miRNet, starBase, Kaplan-Meier Plotter, cBioPortal, LinkedOmics, GSEA, TISCH, TISIDB, GeneMANIA, PDB, GSCALite were applied in this research. RESULTS: We identified the upregulation of TSEN54 expression in HCC and related it to multiple clinicopathological features. Hypomethylation of TSEN54 was closely associated with its high expression. HCC sufferers who held high TSEN54 expression typically had shorter survival expectations. Enrichment analysis showed the involvement of TSEN54 in the cell cycle and metabolic processes. Afterward, we observed that TSEN54 expression level had a positive relationship to the infiltration level of multiple immune cells and the expression of several chemokines. We additionally identified that TSEN54 was related to the expression level of several immune checkpoints and TSEN54 was linked to several m6A-related regulators. CONCLUSIONS: TSEN54 is a prognostic marker of HCC. TSEN54 could become a prospective candidate for HCC diagnosis and therapy.

Corrigendum: Helmet ventilation for pediatric patients during the COVID-19 pandemic: A narrative review.

[This corrects the article DOI: 10.3389/fped.2022.839476.].

Eruptive Xanthomas.

This case report describes numerous dome-shaped, firm, yellow papules that were present symmetrically on the back, shoulder, arm, thigh, and knees.

Effectiveness of high-flow nasal cannulae compared with noninvasive positive-pressure ventilation in preventing reintubation in patients receiving prolonged mechanical ventilation.

Many intensive care unit patients who undergo endotracheal extubation experience extubation failure and require reintubation. Because of the high mortality rate associated with reintubation, postextubation respiratory management is crucial, especially for high-risk populations. We conducted the present study to compare the effectiveness of oxygen therapy administered using high-flow nasal cannulae (HFNC) and noninvasive positive pressure ventilation (NIPPV) in preventing reintubation among patients receiving prolonged mechanical ventilation (PMV). This single-center, prospective, unblinded randomized controlled trial was at the respiratory care center (RCC). Participants were randomized to an HFNC group or an NIPPV group (20 patients in each) and received noninvasive respiratory support (NRS) administered using their assigned method. The primary outcome was reintubation within7 days after extubation. None of the patients in the NIPPV group required reintubation, whereas 5 (25%) of the patients in the HFNC group required reintubation (P = 0.047). The 90-day mortality rates of the NIPPV and HFNC groups (four patients [20%] vs. two patients [10%], respectively) did not differ significantly. No significant differences in length of RCC stay, length of hospital stay, time to liberation from NRS, and ventilator-free days at 28-day were identified. The time to event outcome analysis also revealed that the risk of reintubation in the HFNC group was higher than that in the NIPPV group (P = 0.018). Although HFNC is becoming increasingly common as a form of postextubation NRS, HFNC may not be as effective as NIPPV in preventing reintubation among patients who have been receiving PMV for at least 2 weeks. Additional studies evaluating HFNC as an alternative to NIPPV for patients receiving PMV are warranted.ClinicalTrial.gov ID: NCT04564859; IRB number: 20160901R.Trial registration: ClinicalTrial.gov ( https://clinicaltrials.gov/ct2/show/NCT04564859 ).

Prevalence and patterns of major depressive disorder and subthreshold depressive symptoms in south China.

BACKGROUND: Information on major depressive disorder (MDD) and subthreshold depressive symptoms (SDS) is rarely reported in south China. This study examines the prevalence rates and patterns of MDD and SDS of a large representative sample of adult residents in south China. METHODS: The Guangdong Mental Health Survey was conducted on adults (over 18 years) from September to December 2021. Multistage stratified cluster sampling was used and face-to-face interviews were done with a two-stage design by trained lay interviewers and psychiatrists. A total of 16,377 inhabitants were interviewed using standardized assessment tools. Data were weighted to adjust for differential probabilities of selection and differential response. RESULTS: The weighted prevalence rates of MDD and SDS were 2.5 % (95%CI: 2.2 %-2.9 %) and 14.7 % (95%CI: 14.0 %-15.5 %), respectively. Multinomial logistic regression analysis revealed that female, younger age, living in urban area, higher education, unmarried, irregular meal pattern, lack of physical exercise, chronic diseases, irregular napping pattern and short sleep were positively associated with SDS. Besides, female, younger age, unmarried, irregular meal pattern, lack of physical exercise, chronic diseases, short sleep and poor mental health were positively associated with MDD. LIMITATIONS: The cross-sectional nature of the study limited causal inferences. CONCLUSIONS: The prevalence of MDD in Guangdong province in 2021 is higher than in mainland China in 2013. Given the higher prevalence of SDS, and high burden of depression, it also offers valuable opportunities for policymakers and health-care professionals to explore the factors affecting mental health in Guangdong province, especially during the COVID-19 epidemic.

NLRP3 Inflammasome: A key contributor to the inflammation formation.

Inflammation is an important part of the development of various organ diseases. The inflammasome, as an innate immune receptor, plays an important role in the formation of inflammation. Among various inflammasomes, the NLRP3 inflammasome is the most well studied. The NLRP3 inflammasome is composed of skeletal protein NLRP3, apoptosis-associated speck-like protein (ASC) and pro-caspase-1. There are three types of activation pathways: (1) "classical" activation pathway; (2) "non-canonical" activation pathway; (3) "alternative" activation pathway. The activation of NLRP3 inflammasome is involved in many inflammatory diseases. A variety of factors (such as genetic factors, environmental factors, chemical factors, viral infection, etc.) have been proved to activate NLRP3 inflammasome and promote the inflammatory response of the lung, heart, liver, kidney and other organs in the body. Especially, the mechanism of NLRP3 inflammation and its related molecules in its associated diseases remains not to be summarized, namely they may promote or delay inflammatory diseases in different cells and tissues. This article reviews the structure and function of the NLRP3 inflammasome and its role in various inflammations, including inflammations caused by chemically toxic substances.

Metabolomics study of Berberidis Radix in intervening ulcerative colitis based on UPLC-Q-TOF-MS / 中国中药杂志

The effect of Tujia medicine Berberidis Radix on endogenous metabolites in the serum and feces of mice with ulcerative colitis(UC) induced by dextran sulfate sodium(DSS) was analyzed by metabolomics technology to explore the metabolic pathway and underlying mechanism of Berberidis Radix in the intervention of UC. The UC model was induced in mice by DSS. Body weight, disease activity index(DAI), and colon length were recorded. The levels of tumor necrosis factor-α(TNF-α) and interleukin-10(IL-10) in colon tissues were determined by ELISA. The levels of endogenous metabolites in the serum and feces were detected by ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry(UPLC-Q-TOF-MS). Principal component analysis(PCA) and orthogonal partial least squares-discriminant analysis(OPLS-DA) were employed to characterize and screen differential metabolites. The potential metabolic pathways were analyzed by MetaboAnalyst 5.0. The results showed that Berberidis Radix could significantly improve the symptoms of UC mice and increase the level of the anti-inflammatory factor IL-10. A total of 56 and 43 differential metabolites were identified in the serum and feces, respectively, belonging to lipids, amino acids, fatty acids, etc. After the intervention by Berberidis Radix, the metabolic disorder gradually recovered. The involved metabolic pathways included biosynthesis of phenylalanine, tyrosine, and tryptophan, linoleic acid metabolism, phenylalanine metabolism, and glycerophospholipid metabolism. Berberidis Radix can alleviate the symptoms of mice with DSS-induced UC, and the mechanism may be closely related to the re-gulation of lipid metabolism, amino acid metabolism, and energy metabolism.

Comprehensive analysis of prognostic value, relationship to cell cycle, immune infiltration and m6A modification of ZSCAN20 in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a common tumor across the globe with a high mortality rate. ZSCAN20 is a ZNF transcription factor, a key determinant of gene expression. Nonetheless, the mechanism of ZSCAN20 as a potential clinical biomarker and therapeutic target for HCC is not understood. Here, TIMER, TCGA, ICGC databases and immunohistochemical (IHC) and Western Blot found ZSCAN20 mRNA and protein levels were upregulated. Additionally, Kaplan-Meier Plotter, GEPIA and TCGA databases showed high ZSCAN20 expression was related to the short survival time of HCC patients. Multivariate Cox analysis exposed that ZSCAN20 can act as an independent prognostic factor. We observed methylation level of ZSCAN20 was associated with the clinicopathological characteristics and prognosis of HCC patients through UALCAN. Furthermore, enrichment examination exposed functional association between ZSCAN20 and cell cycle, immune infiltration. Functional experiments showed that interference with ZSCAN20 significantly reduced the invasion, migration and proliferation abilities of HCC cells. An immune infiltration analysis showed that ZSCAN20 was associated with immune cells, particularly T cells. The expression of ZSCAN20 was correlated with poor prognosis in the Regulatory T-cell. And Real-Time RT-PCR analysis found interference with ZSCAN20 significantly reduced the expression of some chemokines. Finally, the TCGA and ICGC data analysis suggested that the ZSCAN20 expression was greatly related to m6A modifier related genes. In conclusion, ZSCAN20 can serve as a prognostic biomarker for HCC and provide clues about cell cycle, immune infiltration, and m6A modification.

Prostate Cancer Risk Prediction and Online Calculation Based on Machine Learning Algorithm.

Objective To build a prostate cancer (PCa) risk prediction model based on common clinical indicators to provide a theoretical basis for the diagnosis and treatment of PCa and to evaluate the value of artificial intelligence (AI) technology under healthcare data platforms. Methods After preprocessing of the data from Population Health Data Archive, smuothly clipped absolute deviation (SCAD) was used to select features. Random forest (RF), support vector machine (SVM), back propagation neural network (BP), and convolutional neural network (CNN) were used to predict the risk of PCa, among which BP and CNN were used on the enhanced data by SMOTE. The performances of models were compared using area under the curve (AUC) of the receiving operating characteristic curve. After the optimal model was selected, we used the Shiny to develop an online calculator for PCa risk prediction based on predictive indicators. Results Inorganic phosphorus, triglycerides, and calcium were closely related to PCa in addition to the volume of fragmented tissue and free prostate-specific antigen (PSA). Among the four models, RF had the best performance in predicting PCa (accuracy: 96.80%; AUC: 0.975, 95% CI: 0.964-0.986). Followed by BP (accuracy: 85.36%; AUC: 0.892, 95% CI: 0.849-0.934) and SVM (accuracy: 82.67%; AUC: 0.824, 95% CI: 0.805-0.844). CNN performed worse (accuracy: 72.37%; AUC: 0.724, 95% CI: 0.670-0.779). An online platform for PCa risk prediction was developed based on the RF model and the predictive indicators. Conclusions This study revealed the application value of traditional machine learning and deep learning models in disease risk prediction under healthcare data platform, proposed new ideas for PCa risk prediction in patients suspected for PCa and had undergone core needle biopsy. Besides, the online calculation may enhance the practicability of AI prediction technology and facilitate medical diagnosis.