Background: Cerebral hypoxia-ischemia impairs brain development in extremely preterm infants and is associated with poor neurological outcomes. Near-infrared spectroscopy (NIRS) is a noninvasive continuous monitoring method for regional cerebral oxygen saturation (rcSO2).Purpose: This study evaluated the clinical feasibility and neurological impact of a neurocritical care bundle that incorporates prolonged multidisciplinary hemodynamic monitoring and a stepwise management algorithm. Methods: Preterm infants with a gestational age (GA) ≤28 weeks or birth weight (BW) ≤1,000 g were prospectively enrolled in a bundle group subjected to NIRS for rcSO2, electrical cardiometry for cardiac output, and daily brain and cardiac echography during the first 72 hours of life. Monitoring was repeated weekly in the first month and then monthly until discharge or the term-equivalent age (TEA) was reached. We implemented a stepwise management algorithm for treating cerebral hypoxia. The primary outcome was a composite of mortality and adverse neurological events (structural abnormalities or electroencephalogram-confirmed seizures) before discharge. The secondary outcomes were the physiological pattern of rcSO2 within the initial 72 hours and up to discharge or TEA. Results: Thirty preterm infants (GA, 27.1±2.0 weeks; BW, 830±225 g) were enrolled in the bundle group. The mean time-averaged rcSO2 (66.8%±10.3%) was not associated with GA or BW. However, postnatal age appeared to influence physiological rcSO2 changes, given that rcSO2 values were higher during the initial 72 hours than at subsequent intervals. Seven infants (23.3%) had poor outcomes and significantly lower time-averaged rcSO2 (51.1% [50.0%–65.2%] vs. 71.8% [67.1%–73.1%], P=0.002). Multivariate regression indicated that a lower rcSO2 was an independent risk factor, and a 65% threshold showed an optimal predictive value for poor outcomes. Conclusion The neurocritical care bundle helped identify preterm infants at risk of cerebral hypoxia, and lower rcSO2 was an independent risk factor for composite mortality and adverse neurological outcomes.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To screen genes associated with poor prognosis of colorectal cancer(CRC)through bioinformatics analysis.Methods The gene expression profiles of GSE74602,GSE110223,GSE113513 and GSE141174 were obtained from Gene Expression Omnibus(GEO)database,including samples from 65 CRC tissues and 65 normal tissues.Differentially expressed genes(DEGs)between CRC tissues and normal tissues were screened out by GEO2R tool and Venn software,and the consistent genes were extracted from DEGs by Venn software.A protein-protein interaction(PPI)network was constructed by the STRING database to identify key genes,which were analyzed by Kaplan-Meier Plotter and GEPIA.Kyoto encyclopedia of genes and genomes(KEGG)pathway enrichment analysis was conducted on the 13 selected genes.Results There were 171 DEGs obtained from the four datasets,including 148 up-regulated genes and 23 down-regulated genes.Up-regulated DEGs were enriched in the redox processes,bicarbonate transport,digestion,ion trans-membrane transport,and one-carbon metabolism;and down-regulated DEGs were enriched in the positive regulation of cell proliferation.The survival curve analysis showed that 30 of the 87 genes were significantly associated with poor survival prognosis.GEPIA showed that 13 of the 30 genes were highly expressed in CRC tissues compared to normal tissues,among which MYC and FGFR3 markedly enriched in the CRC pathway.Conclusion This study identifies that MYC and FGFR3 are significantly up-regulated in CRC and closely associated with poor prognosis,suggesting that they may serve as potential prognostic markers and therapeutic targets for CRC patients.

Objective To investigate the therapeutic effect of hypericin on acute pancreatitis(AP)in mice and its effect on NLRP3 inflammasome signaling pathway.Methods The AP model in mice was established with caerulein(CER).The mice were divided into the normal control group,the model group(AP group),the low-dose HY group(CER+HY 5 mg/kg group),the medium-dose HY group(CER+HY 10 mg/kg group)and the high-dose HY group(CER+HY 20 mg/kg group),with 10 mice in each group.The 266-6 mouse pancreatic acinar cancer cells were treated with cholecystokinin(CCK)and divided into the control group,the AP group,the CCK+HY 1 μmol/L group,the CCK+HY 2 μmol/L group and the CCK+HY 4 μmol/L group.The activities of amylase(AMS),lipase,trypsin and myeloperoxidase(MPO)in the serum of each group of mice,and levels of inflammatory factors interleukin(IL)-1β and tumor necrosis factor(TNF)-α were detected by enzyme-linked immunosorbent assay(ELISA).The expression of NOD-like receptor family protein 3(NLRP3)was detected by Western blot assay.The mRNA levels of NLRP3,caspase(Caspase)-1,IL-1β,TNF-α and IL-18 in pancreatic tissue of mice were detected by real-time quantitative PCR(q-PCR).The cell survival rate of cells in each group was detected by CCK8 method.The mRNA expression levels of NLRP3,Caspase-1 and IL-18 in each group of cells were detected by q-PCR.Results Compared with the normal control group,the levels of AMS,lipase,MPO,trypsin,IL-1β and TNF-α in serum of the model group,and the mRNA and protein expression levels of NLRP3,IL-1β,TNF-α,IL-18 and Caspase-1 in pancreatic tissue were increased(P＜0.01).Compared with the model group,the levels of AMS,IL-1β and TNF-α,the enzymatic activity of trypsin in serum,and the mRNA levels of IL-1β,TNF-α,IL-18 and Caspase-1 in pancreatic tissue were decreased in the low-,medium-and high-dose HY groups.The serum levels of lipase and MPO and the mRNA expression levels of NLRP3 in pancreatic tissue were decreased in the medium-and high-dose HY groups(P＜0.05).Compared with the AP group,the cell survival rates were increased in the CCK+HY 1 μmol/L group,the CCK+HY 2 μmol/L group and the CCK+HY 4 μmol/L group,and the mRNA levels of NLRP3,IL-18 and Caspase-1 were decreased in a dose-dependent manner(P＜0.05).Conclusion Hypericin can effectively treat AP in vivo and in vitro,and its therapeutic effect may be related to the regulation of NLRP3 inflammasome signaling pathway.

Objective To explore the abnormal expression of the MT-ND family in pan-cancers and its prognostic value.Methods Transcriptome expression and clinical data of 33 cancers were downloaded from the TCGA database,thereby analyzing the expression differences of the MT-ND family in tissuesof different types of cancers and normal tissues.The prognostic role of the MT-ND family in pan-cancers was explored by univariate Cox regression analysis and Kaplan-Meier survival analysis.Results The expression of the MT-ND family was upregulated in the kidney chromophobe,acute myeloid leukemia and thymoma,and downregulated in the remaining tumors.The expression of the MT-ND family was associated with the overall survival rate of different types of cancers.In addition,the MT-ND family were significantly correlated with the immune invasion subtypes,and were correlated with stromal cell invasion and tumor cell stemness to varying degrees.The expression of MT-ND4 was downregulated in brain lower grade glioma,which was a protective factor for prognosis;while the expression of MT-ND4 in thymoma was upregulated,which was a risk factor for prognosis.Conclusion Pan-cancer analysis has confirmed that the MT-ND family can predict the tumor prognosis,which provides new ideas and strategies for the precision treatment and prognostic management of cancer.

To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

To analyze the standard establishment approach and compilation rationale for metallic pharmaceutical packaging standard development in the 2025 edition of the Pharmacopeia of the People's Republic of China.This article systematically explained the background and process of establishing the guiding principles for metallic materials and containers used in pharmaceutical packaging in the Chinese Pharmacopoeia through basic information,relevant domestic and international standards,the establishment of key quality attributes of metallic pharmaceutical packaging materials,and the construction of metallic pharmaceutical packaging material standards.The newly established guidelines,the Pharmacopeia of the People's Republic of China 9625,prioritized product critical quality attributes(CQAs)and real-world applicability.This dual emphasis on rigidity and adaptability enhances drug safety,meets the regulatory requirements,and promotes the globalization and scientific advancement of China's pharmaceutical packaging industry.

Objective To explore the abnormal expression of the MT-ND family in pan-cancers and its prognostic value.Methods Transcriptome expression and clinical data of 33 cancers were downloaded from the TCGA database,thereby analyzing the expression differences of the MT-ND family in tissuesof different types of cancers and normal tissues.The prognostic role of the MT-ND family in pan-cancers was explored by univariate Cox regression analysis and Kaplan-Meier survival analysis.Results The expression of the MT-ND family was upregulated in the kidney chromophobe,acute myeloid leukemia and thymoma,and downregulated in the remaining tumors.The expression of the MT-ND family was associated with the overall survival rate of different types of cancers.In addition,the MT-ND family were significantly correlated with the immune invasion subtypes,and were correlated with stromal cell invasion and tumor cell stemness to varying degrees.The expression of MT-ND4 was downregulated in brain lower grade glioma,which was a protective factor for prognosis;while the expression of MT-ND4 in thymoma was upregulated,which was a risk factor for prognosis.Conclusion Pan-cancer analysis has confirmed that the MT-ND family can predict the tumor prognosis,which provides new ideas and strategies for the precision treatment and prognostic management of cancer.