Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a complex disease that is often accompanied by mental health disorders. However, the potential mechanisms underlying the heterogeneous clinical presentation of CP/CPPS remain uncertain. This study analyzed widely targeted metabolomic data of expressed prostatic secretions (EPS) and plasma to reveal the underlying pathological mechanisms of CP/CPPS. A total of 24 CP/CPPS patients from The Second Nanning People's Hospital (Nanning, China), and 35 asymptomatic control individuals from First Affiliated Hospital of Guangxi Medical University (Nanning, China) were enrolled. The indicators related to CP/CPPS and psychiatric symptoms were recorded. Differential analysis, coexpression network analysis, and correlation analysis were performed to identify metabolites that were specifically altered in patients and associated with various phenotypes of CP/CPPS. The crucial links between EPS and plasma were further investigated. The metabolomic data of EPS from CP/CPPS patients were significantly different from those from control individuals. Pathway analysis revealed dysregulation of amino acid metabolism, lipid metabolism, and the citrate cycle in EPS. The tryptophan metabolic pathway was found to be the most significantly altered pathway associated with distinct CP/CPPS phenotypes. Moreover, the dysregulation of tryptophan and tyrosine metabolism and elevation of oxidative stress-related metabolites in plasma were found to effectively elucidate the development of depression in CP/CPPS. Overall, metabolomic alterations in the EPS and plasma of patients were primarily associated with oxidative damage, energy metabolism abnormalities, neurological impairment, and immune dysregulation. These alterations may be associated with chronic pain, voiding symptoms, reduced fertility, and depression in CP/CPPS. This study provides a local-global perspective for understanding the pathological mechanisms of CP/CPPS and offers potential diagnostic and therapeutic targets.
Humans ; Male ; Prostatitis/blood* ; Adult ; Pelvic Pain/blood* ; Metabolomics ; Prostate/metabolism* ; Middle Aged ; Chronic Pain/blood* ; Metabolome ; Case-Control Studies ; Tryptophan/blood* ; Depression/blood* ; Oxidative Stress/physiology* ; Chronic Disease ; Lipid Metabolism/physiology*

AIM To optimize the processing technology of red Notoginseng Radix et Rhizoma and evaluate its blood tonifying activity.METHODS On the basis of a single factor experiment,with steaming temperature,steaming time,drying temperature,and drying time as influencing factors,the total contents of notoginsenoside R1,ginsenoside Rg1,Rb1,Rk3,Rh4,and 20(R)-ginsenoside Rg3 as evaluation indicators,Box-Behnken response surface method ology was used to optimize the processing technology.Upon the anemic mouse models jointly induced by 1-acetyl-2-phenylhydrazine(APH)and cyclophosphamide(CTX),the investigation of the blood tonifying activity of red Notoginseng Radix et Rhizoma was carried out in contrast to that of the steamed Notoginseng Radix et Rhizoma.RESULTS The optimal conditions,contributing saponin content of 8.326%and RSD of 0.087%,were determined as follows:steaming temperature of 130℃,steaming time of 4 hours,drying temperature of 60℃,and drying time of 48 h.The pharmacological activity revealed that the different processing techniques were responsible for the different blood enriching activity of notoginseng,with red Notoginseng Radix et Rhizoma displaying a better efficacy than that of steamed Notoginseng Radix et Rhizoma.CONCLUSION This stable and feasible method can be used to control the production of red Notoginseng Radix et Rhizoma.

Objective To explore the correction of beam trajectories in the presence of fringe fields in magnetic resonance imaging-guided proton therapy and dose changes in the body before and after correction.Methods The open-source treatment planning software matRad was used to design plans for brain tumor,liver tumor,and prostate cancer cases,and simulation studies were conducted in the Monte Carlo simulation toolkit TOPAS to calculate proton dose distribution.A proton beam trajectory correction model suitable for three-dimensional magnetic fields was established,and a beam trajectory correction algorithm was developed.The deflection of the proton Bragg peak in the presence of fringe fields was analyzed.Furthermore,3 treatment plans were simulated and dose correction was carried out when the fringe field existed.Gamma analysis method is used to evaluate the correction effect;and the dose changes in the target area and organs-at-risk after correction were quantitatively analyzed.Results The perturbation of the magnetic field would cause lateral deflection of the proton beam trajectory,and the presence of fringe fields would significantly increase this effect,which increased with the increasing of beam energy.When the fringe field existed,the treatment plans for brain tumor,liver tumor,and prostate cancer were corrected.Under the 3%/3 mm criterion,the gamma passing rates for target area were 94.844%,92.054%,and 97.863%,respectively,and after correction,the total dose in the body was increased by 2.8%,2.5%,and 1.5%,respectively.The increased dose was mainly contributed by incident protons.Conclusion In magnetic resonance imaging-guided proton therapy,the effects of fringe fields should be considered.The increase in incident proton beam energy after correction will lead to an increase in the total dose in the body.Since the beam trajectory still has curvature,the dose changes differently in different organs-at-risk.

Background/Aims: Despite the high efficacy of direct-acting antivirals (DAAs), approximately 1–3% of hepatitis C virus (HCV) patients fail to achieve a sustained virological response. We conducted a nationwide study to investigate risk factors associated with DAA treatment failure. Machine-learning algorithms have been applied to discriminate subjects who may fail to respond to DAA therapy. Methods: We analyzed the Taiwan HCV Registry Program database to explore predictors of DAA failure in HCV patients. Fifty-five host and virological features were assessed using multivariate logistic regression, decision tree, random forest, eXtreme Gradient Boosting (XGBoost), and artificial neural network. The primary outcome was undetectable HCV RNA at 12 weeks after the end of treatment. Results: The training (n=23,955) and validation (n=10,346) datasets had similar baseline demographics, with an overall DAA failure rate of 1.6% (n=538). Multivariate logistic regression analysis revealed that liver cirrhosis, hepatocellular carcinoma, poor DAA adherence, and higher hemoglobin A1c were significantly associated with virological failure. XGBoost outperformed the other algorithms and logistic regression models, with an area under the receiver operating characteristic curve of 1.000 in the training dataset and 0.803 in the validation dataset. The top five predictors of treatment failure were HCV RNA, body mass index, α-fetoprotein, platelets, and FIB-4 index. The accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of the XGBoost model (cutoff value=0.5) were 99.5%, 69.7%, 99.9%, 97.4%, and 99.5%, respectively, for the entire dataset. Conclusions Machine learning algorithms effectively provide risk stratification for DAA failure and additional information on the factors associated with DAA failure.

As artificial intelligence technology rapidly advances, its deployment within the medical sector presents substantial ethical challenges. Consequently, it becomes crucial to create a standardized, transparent, and secure framework for processing medical data. This includes setting the ethical boundaries for medical artificial intelligence and safeguarding both patient rights and data integrity. This consensus governs every facet of medical data handling through artificial intelligence, encompassing data gathering, processing, storage, transmission, utilization, and sharing. Its purpose is to ensure the management of medical data adheres to ethical standards and legal requirements, while safeguarding patient privacy and data security. Concurrently, the principles of compliance with the law, patient privacy respect, patient interest protection, and safety and reliability are underscored. Key issues such as informed consent, data usage, intellectual property protection, conflict of interest, and benefit sharing are examined in depth. The enactment of this expert consensus is intended to foster the profound integration and sustainable advancement of artificial intelligence within the medical domain, while simultaneously ensuring that artificial intelligence adheres strictly to the relevant ethical norms and legal frameworks during the processing of medical data.
Artificial Intelligence/legislation & jurisprudence* ; Humans ; Consensus ; Computer Security/standards* ; Confidentiality/ethics* ; Informed Consent/ethics*

Histone deacetylase 3 (HDAC3) plays an important role in chromatin remodeling, which in turn regulates gene transcription, so HDAC3 is involved in the pathophysiology of various diseases through epigenetic regulation. Organ ischemia-reperfusion injury (I R I) is a pathophysiological process that leads to the development of a variety of diseases such as delayed neuronal necrosis, irreversible shock, myocardial infarction, acute organ failure and organ transplant rejection. In this paper we review the pathophysiological function of HDAC3 and its role in the development of IRI in human parenchymal organs, and also explore the therapeutic value of HDAC3 in IRI.

Acute lung injury ( ALI) and its most extreme form a-cute respiratory distress syndrome ( ARDS) are lung diseases with high morbidity and mortality. There is no effective therapeutic intervention until now for its complicated pathophysiologi-cal processes and sophisticated regulatory mechanism. Histone deacetylases (HDACs) are a family of proteins with deacetylase activity. Studies have shown that HDACs are involved in the pathophysiological processes of ALI/ARDS, including inflammatory responses,endothelial permeability,oxidative stresses,alveolar fluid clearance and lung tissue repairment. Simultaneously, the use of HDACs inhibitors (HDACIs) can interfere with ALI/ ARDS progression. In this review we describe and summarize the pathophysiological processes and the underlying mechanisms in ALI/ARDS regulated by HDACs and HDACIs in detail, in order to provide the basis for the clinical application of HDACs-targe- ted agents and indicate directions for future study.

Objective:To explore the relation of plasma Elabela with 3-month prognoses in large vessel occlusion-acute ischemic stroke (LVO-AIS) patients accepted endovascular thrombectomy (EVT).Methods:A prospective study was performed; 94 LVO-AIS patients aceepted EVT in Department of Neurology, Anhui Provincal Hospital, Anhui Medical University from August 2020 to August 2022 were selected. Plasma Elabela was detected before EVT, and 24 and 72 h after EVT. Modified Rankin scale (mRS) was used to evaluate the prognoses of the patients 3 months after EVT; differences in clinical data and plasma Elabela level between the good prognosis group and poor prognosis group were compared. Independent influencing factors for prognoses of LVO-AIS patients 3 months after EVT were analyzed by multivariate Logistic regression. Receiver operating characteristic (ROC) curve was used to analyze the efficacy of Elabela in predicting prognoses of patients with LVO-AIS 3 months after EVT.Results:Compared with the poor prognosis group, the good prognosis group had significantly lower percentages of patients with stroke history and diabetes, and lower NIHSS scores at admission ( P<0.05). Elabela level in the good prognosis group was significantly higher than that in the poor prognosis group 72 h after EVT ( P<0.05). Multivariate Logistic regression analysis showed that stroke history ( OR=0.148, P=0.037, 95% CI: 0.025-0.889), diabetes mellitus ( OR=0.148, P=0.037, 95% CI: 0.025-0.889), hypertension history ( OR=3.488, P=0.024, 95% CI: 1.177-10.339), and Elabela level 72 h after EVT ( OR=1.064, P=0.005, 95% CI: 1.019-1.111) were independent influencing factors for prognoses of LVO-AIS patients 3 months after EVT. ROC curve showed that area under ROC curve of plasma Elabela level 72 h after EVT in predicting prognosies of LVO-AIS patients 3 months after surgery was 0.718 ( P<0.001, 95% CI: 0.614-0.822). Conclusion:Plasma Elabela level 72 h after EVT may be a potential prognostic biomarker for LVO-AIS patients after EVT.

Objective: To analyze the prevalence and the risk factors of fungal sepsis in 25 neonatal intensive care units (NICU) among preterm infants in China, and to provide a basis for preventive strategies of fungal sepsis. Methods: This was a second-analysis of the data from the "reduction of infection in neonatal intensive care units using the evidence-based practice for improving quality" study. The current status of fungal sepsis of the 24 731 preterm infants with the gestational age of <34⁺⁰ weeks, who were admitted to 25 participating NICU within 7 days of birth between May 2015 and April 2018 were retrospectively analyzed. These preterm infants were divided into the fungal sepsis group and the without fungal sepsis group according to whether they developed fungal sepsis to analyze the incidences and the microbiology of fungal sepsis. Chi-square test was used to compare the incidences of fungal sepsis in preterm infants with different gestational ages and birth weights and in different NICU. Multivariate Logistic regression analysis was used to study the outcomes of preterm infants with fungal sepsis, which were further compared with those of preterm infants without fungal sepsis. The 144 preterm infants in the fungal sepsis group were matched with 288 preterm infants in the non-fungal sepsis group by propensity score-matched method. Univariate and multivariate Logistic regression analysis were used to analyze the risk factors of fungal sepsis. Results: In all, 166 (0.7%) of the 24 731 preterm infants developed fungal sepsis, with the gestational age of (29.7±2.0) weeks and the birth weight of (1 300±293) g. The incidence of fungal sepsis increased with decreasing gestational age and birth weight (both P<0.001). The preterm infants with gestational age of <32 weeks accounted for 87.3% (145/166). The incidence of fungal sepsis was 1.0% (117/11 438) in very preterm infants and 2.0% (28/1 401) in extremely preterm infants, and was 1.3% (103/8 060) in very low birth weight infants and 1.7% (21/1 211) in extremely low birth weight infants, respectively. There was no fungal sepsis in 3 NICU, and the incidences in the other 22 NICU ranged from 0.7% (10/1 397) to 2.9% (21/724), with significant statistical difference (P<0.001). The pathogens were mainly Candida (150/166, 90.4%), including 59 cases of Candida albicans and 91 cases of non-Candida albicans, of which Candida parapsilosis was the most common (41 cases). Fungal sepsis was independently associated with increased risk of moderate to severe bronchopulmonary dysplasia (BPD) (adjusted OR 1.52, 95%CI 1.04-2.22, P=0.030) and severe retinopathy of prematurity (ROP) (adjusted OR 2.55, 95%CI 1.12-5.80, P=0.025). Previous broad spectrum antibiotics exposure (adjusted OR=2.50, 95%CI 1.50-4.17, P<0.001), prolonged use of central line (adjusted OR=1.05, 95%CI 1.03-1.08, P<0.001) and previous total parenteral nutrition (TPN) duration (adjusted OR=1.04, 95%CI 1.02-1.06, P<0.001) were all independently associated with increasing risk of fungal sepsis. Conclusions: Candida albicans and Candida parapsilosis are the main pathogens of fungal sepsis among preterm infants in Chinese NICU. Preterm infants with fungal sepsis are at increased risk of moderate to severe BPD and severe ROP. Previous broad spectrum antibiotics exposure, prolonged use of central line and prolonged duration of TPN will increase the risk of fungal sepsis. Ongoing initiatives are needed to reduce fungal sepsis based on these risk factors.
Infant ; Infant, Newborn ; Humans ; Birth Weight ; Intensive Care Units, Neonatal ; Retrospective Studies ; Tertiary Care Centers ; Infant, Extremely Low Birth Weight ; Gestational Age ; Infant, Extremely Premature ; Sepsis/epidemiology* ; Retinopathy of Prematurity/epidemiology* ; Bronchopulmonary Dysplasia/epidemiology*

This study explored the feasibility of mineral element content and ratios of nitrogen isotopes to discriminate the cultivation mode of Dendrobium nobile in order to provide theoretical support for the discrimination of the cultivation mode of D. nobile. The content of 11 mineral elements(N, K, Ca, P, Mg, Na, Fe, Cu, Zn, Mn, and B) and nitrogen isotope ratios in D. nobile and its substrate samples in three cultivation methods(greenhouse cultivation, tree-attached cultivation, and stone-attached cultivation) were determined. According to the analysis of variance, principal component analysis, and stepwise discriminant analysis, the samples of different cultivation types were classified. The results showed that the nitrogen isotope ratios and the content of elements except for Zn were significantly different among different cultivation types of D. nobile(P<0.05). The results of correlation analysis showed that the nitrogen isotope ratios, mineral element content, and effective component content in D. nobile were correlated with the nitrogen isotope ratio and mineral element content in the corresponding substrate samples to varying degrees. Principal component analysis can preliminarily classify the samples of D. nobile, but some samples overlapped. Through stepwise discriminant analysis, six indicators, including δ~(15)N, K, Cu, P, Na, and Ca, were screened out, which could be used to establish the discriminant model of D. nobile cultivation methods, and the overall correct discrimination rates after back-substitution test, cross-check, and external validation were all 100%. Therefore, nitrogen isotope ratios and mineral element fingerprints combined with multivariate statistical analysis could effectively discriminate the cultivation types of D. nobile. The results of this study provide a new method for the identification of the cultivation type and production area of D. nobile and an experimental basis for the quality evaluation and quality control of D. nobile.
Dendrobium ; Minerals ; Discriminant Analysis ; Multivariate Analysis ; Nitrogen Isotopes