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PubMed2025

Multivariate Effects of SNPs on Environmental Streptococcal Mastitis Evaluated With an NGS-Based Association Study Using Targeted Resequencing in the Bovine MHC Region.

Mastitis is an inflammatory reaction caused by bacterial infection of the teat, and a relationship between its onset and cattle major histocompatibility complex (BoLA) region has been reported. However, no comprehensive genetic analysis of mastitis caused by environmental streptococci has been reported. Here, we resequenced the BoLA region using a hybridisation capture target next-generation sequencing (NGS) method to identify disease susceptibility markers mapped to the BoLA region in environmental streptococcal mastitis. This study examined 75 cows with mastitis caused by environmental streptococci selected from 1641 cows with mastitis and 222 healthy cows without mastitis in Japan. Targeted sequences obtained from MiSeq NGS were aligned to the bovine reference genome (ARS-UCD1.2/bosTau9), and 2,920,355 variants were detected within the BoLA region of the 297 Holstein cattle. In an association study using 2264 variants after quality control, the top 20 variants with the lowest P values were selected and assigned to the 18 surrounding candidate genes, and a gene network analysis of these genes resulted in the narrowing down of five candidate genes POU5F1, IER3, GNL1, ABCF1, and PRR3. Multivariate effect analysis of all 6 SNPs associated with these 5 genes revealed that they were significantly correlated with mastitis, indicating that they were useful for classification of mastitis-resistant and mastitis-susceptible cattle. This is the first report to identify SNPs associated with environmental streptococcal mastitis with an NGS-based association study using targeted resequencing in the BoLA region, and understanding host factors may provide important clues for mastitis control.

Animals↗

PubMed1999

Reproducibility of regional metabolic covariance patterns: comparison of four populations.

UNLABELLED: In a previous [18F]fluorodeoxyglucose (FDG) PET study we analyzed regional metabolic data from a combined group of Parkinson's disease (PD) patients and healthy volunteers (N), using network analysis. By this method, we identified a unique pattern of regional metabolic covariation with an expression which accurately discriminated patients from healthy volunteers. To assess the reproducibility of this pattern as a potential marker for PD, we compared the pattern's topography with that of the disease-related covariance patterns identified in three other independent populations of patients with PD and healthy individuals studied in different PET laboratories. METHODS: The following patient populations were studied: group A (original cohort: 22 PD, 20 N; resolution: 7.5 mm full width at half maximum [FWHM]); group B (18 PD, 12 N; resolution: 4.2 mm FWHM); group C (25 PD, 15 N; resolution: 8.0 mm FWHM); and group D (14 PD, 10 N; resolution: 10 mm FWHM). Region weights for the PD-related covariance pattern (PDRP) identified in the group A analysis were correlated with those for the disease-related patterns identified in the analyses of groups B, C and D. In addition, subject scores for the group A PDRP were computed prospectively for every individual in each of the study populations. PDRP scores for PD and N within each cohort were compared. RESULTS: The PDRP topography identified in group A was highly correlated with each of the corresponding topographies identified in the other populations (r2 approximately 0.60, P < 0.0001). Prospectively computed subject scores for the group A PDRP significantly discriminated PD from N in each population (P < 0.004). CONCLUSION: The PDRP topography identified previously in Group A is highly reproducible across patient populations and tomographs. Prospectively computed PDRP scores can accurately discriminate patients from controls in multiple populations studied with different tomographs. Brain network imaging with FDG PET can provide robust metabolic markers for the diagnosis of PD.

Brain↗

PubMed2026

The evolution of Ca2+-ATPases across plants with profiles in Rhododendron and the function of key members in alleviating high calcium stress.

Ca2+-ATPase (CAP) is a key Ca2+ efflux protein in plants. Our previous research suggests that CAPs may play a crucial role in the adaptation of rhododendrons to high calcium environments. However, the evolution, variation, characteristic expression, and subfunctionalization of this gene family in Rhododendron remain unknown. Through the analysis of pan-genomes and pan-transcriptomes, we elucidated the systematic evolution of CAPs in plants, as well as their characteristic expression patterns in Rhododendron. During the evolutionary process from lower to higher plants, CAPs can be divided into six clades and exhibit structural conservation. CAPs have emerged and differentiated in lower plants such as algae, and they have undergone significant amplification in Eudicots plants like rhododendrons. Three Rhododendron species (Rhododendron bailiense, R. delavayi, and R. irroratum) located in the karst province of Guizhou in Southwest China exhibit the highest copies of CAPs, suggesting a strong association between CAP copy number variation and habitat, particularly in high calcium environments. Through multiple transcriptome analyses, we revealed that CAPs are induced under various environmental/developmental conditions (e.g. karst environments, high altitude, early flower development, hormones, etc.). Co-expression network analysis highlighted key members of calcineurin B-like protein (CBL) and CBL-interacting protein kinases (CIPK) that are associated with the high expression of CAPs. Experimental validation demonstrated that CAPb1 and CAPd1 significantly alleviate high calcium stress, and the CAPb1-CIPK1-CBL1 and CAPd1-CIPK2-CBL1 modules can further enhance the alleviation. These findings provide new insights into the evolution, characteristic expression, and function of CAPs, as well as new perspectives on the high calcium adaptability of rhododendrons.

Journal Article↗

PubMed2026

Multi-omics reveal microbial functional traits and antifungal metabolites associated with lower Pseudogymnoascus destructans loads in bat cave soils.

White-nose syndrome, caused by Pseudogymnoascus destructans (Pd), is a major fungal disease threatening hibernating bats. Cave soils can serve as environmental reservoirs for Pd, yet the microbial and biochemical mechanisms underlying naturally low Pd burdens in some cave environments remain poorly understood. Here, we integrated soil microbiome profiling, metagenomics, metabolomics, multi-omics network analysis, and in vitro validation to investigate the ecological and functional basis of differential Pd loads in hibernating bat caves in Northeast China. The three caves shared cold, humid, and weakly acidic microenvironments, but differed significantly in electrical conductivity, soil water content, nutrient availability, and extracellular enzyme activities. Soil microbial communities showed significant inter-cave variation in composition, diversity, and niche breadth, with stochastic processes contributing substantially to community assembly. Environmental variables, particularly pH and Pd load, were important predictors of microbial community structure. Functional analyses revealed that the low-Pd Gezi Cave was enriched in genes associated with organic carbon degradation, nitrogen input and retention, and secondary metabolism. Metabolomic profiling further identified cave-specific metabolite signatures, among which Biochanin A, 4-Hydroxybenzaldehyde, Vanillin, and Arachidonic acid were negatively correlated with Pd loads. Integrated pathway and network analyses showed that differential genes and metabolites jointly mapped to secondary metabolite biosynthesis, aminobenzoate degradation, and flavonoid degradation pathways, forming a microbe-metabolite-functional gene coupling network involving key taxa such as Rhodococcus, Pseudorhodoplanes, and Rhodoplanes. In vitro assays confirmed that 4-Hydroxybenzaldehyde, Coumarin, and Vanillin inhibited Pd growth. Structural equation modelling further indicated that environmental heterogeneity was associated with variation in Pd loads through microbial functional attributes and metabolite profiles. These findings suggest that naturally low-Pd cave soils are associated with coordinated environmental filtering, microbial functional specialization, and antifungal metabolite production, providing mechanistic insight into microbial and biochemical constraints on Pd persistence in cave reservoirs.

Animals↗

PubMed2007

Identification of proteomic changes during differentiation of adult mouse subventricular zone progenitor cells.

The use of neural precursor cells (NPCs) represents a promising repair strategy for many neurological disorders. However, the molecular events and biological features that control NPC proliferation and their differentiation into neurons, astrocytes, and oligodendrocytes are unclear. In the present study, we used a comparative proteomics approach to identify proteins that were differentially regulated in NPCs after short-term differentiation. We also used a subcellular fractionation technique for enrichment of nuclei and other dense organelles to identify proteins that were not readily detected in whole cell extracts. In total, 115 distinct proteins underwent expression changes during NPC differentiation. Forty one of these were only identified following subcellular fractionation. These included transcription factors, RNA-processing factors, cell cycle proteins, and proteins that translocate between the nucleus and cytoplasm. Biological network analysis showed that the differentiation of NPCs was associated with significant changes in cell cycle and protein synthesis machinery. Further characterization of these proteins could provide greater insight into the mechanisms involved in regulation of neurogenesis in the adult central nervous system (CNS) and potentially identify points of therapeutic intervention.

Adult Stem Cells↗

PubMed2025

Integrated data mining and network pharmacology to explore the prescription patterns from a senior TCM oncologist's clinical practice in treating chemotherapy-induced hand-foot syndrome.

Hand-foot syndrome (HFS) is a common and refractory adverse effect of chemotherapy lacking specific therapeutic strategies currently. Traditional Chinese medicine (TCM) has shown empirical efficacy in clinical HFS management. This study integrated data mining and network pharmacology to systematically elucidate the medication principles and molecular mechanisms underlying Professor Gang Xie's prescriptions for HFS. All medical records from Professor Xie's specialist clinic (January 2020 to March 2025) were retrospectively collected and standardized in Excel. Prescriptions were analyzed through frequency statistics, association and clustering. Active ingredients of core herb pairs and their disease-related targets were identified using TCMSP, HERB, GeneCards, PharmGKB and GEO databases. Protein-protein interaction (PPI) networks, gene ontology (GO), and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed. Molecular docking validated interactions between key bioactive compounds and targets. This study involved 217 prescriptions containing 150 herbs. Core herb combinations comprised Radix Astragali (Huangqi), Poria (Fuling), and Radix Pseudostellariae (Taizishen), predominantly classified as spleen-tonifying agents with warm properties, targeting lung, spleen, and stomach meridians. Network analysis identified 67 bioactive compounds and 899 disease targets. Quercetin, kaempferol, acacetin and luteolin were identified the key ingredients. The core targets (TP53, STAT3, PIK3CA, HSP90AA1, AKT1, CTNNB1, PI3KR1, MAPK1) were enriched in MAPK and PI3K-Akt signaling pathways. Molecular docking confirmed strong binding affinity between key compounds and targets. Professor Xie's therapeutic strategy for HFS emphasizes "spleen fortification, phlegm elimination, and stasis resolution." The core herb combination likely exerts anti-HFS effects via modulation of MAPK and PI3K-Akt pathways, providing a pharmacological basis for TCM-driven HFS management.

Network Pharmacology↗

PubMed2026

Comparative effectiveness of percutaneous coronary intervention strategies for coronary small-vessel disease: a network meta-analysis of randomized trials.

BACKGROUND: Coronary small-vessel disease (SVD) remains challenging for percutaneous coronary intervention (PCI) because small lumens magnify restenosis and ischemic risk. Multiple devices are available, yet their comparative performance is uncertain. This study evaluated and ranked PCI strategies for SVD. METHODS: A systematic review and network meta-analysis was conducted in accordance with PRISMA. PubMed, Embase, the Cochrane Central Register of Controlled Trials, Web of Science, and Google Scholar were searched from inception to 15 August 2025. Eligible studies were English-language randomized controlled trials enrolling adults with angiographic SVD defined as reference vessel diameter ≤3.0 mm, comparing PCI strategies, and reporting target lesion revascularization (TLR), binary restenosis (BR), or myocardial infarction (MI). A frequentist random-effects network meta-analysis generated odds ratios (ORs) with 95% confidence intervals (CIs) and treatment rankings using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirty-nine trials including 14,503 patients met the criteria. For TLR (37 studies; 11,980 patients), the highest SUCRA values were observed with sirolimus-eluting stents (SES 90.1%), zotarolimus-eluting stents (ZES 83.9%), and everolimus-eluting stents (EES 82.2%). For BR (32; 6,468), SES, ZES, and paclitaxel-coated balloons (DCB-PTX) ranked highest (95.0%, 80.0%, and 78.3%). For MI (37; 11,602), SES, DCB-PTX, and ZES ranked highest (79.0%, 78.7%, and 68.5%). Representative effects showed SES reduced TLR versus bare-metal stents (BMS) (OR, 0.25; 95% CI, 0.15-0.43) and MI versus BMS (OR, 0.41; 95% CI, 0.21-0.79). Conventional approaches such as BMS, plain old balloon angioplasty (POBA), and gold-plated balloon angioplasty (GPBA) ranked lowest across outcomes. CONCLUSION: SES provides the most consistent clinical benefit for coronary SVD. ZES, EES, and DCB-PTX are effective alternatives in selected settings, whereas BMS, POBA, and GPBA are less effective. These findings offer comparative evidence to guide device selection in SVD.

Humans↗

PubMed1999

Simultaneous identification of static and dynamic vagosympathetic interactions in regulating heart rate.

We earlier reported that stimulation of either one of the sympathetic and vagal nerves augments the dynamic heart rate (HR) response to concurrent stimulation of its counterpart. We explained this phenomenon by assuming a sigmoidal static relationship between nerve activity and HR. To confirm this assumption, we stimulated the sympathetic and/or vagal nerve in anesthetized rabbits using large-amplitude Gaussian white noise and determined the static and dynamic characteristics of HR regulation by a neural network analysis. The static characteristics approximated a sigmoidal relationship between the linearly predicted and the measured HRs (response range: 212.4 +/- 46.3 beats/min, minimum HR: 96.0 +/- 28.4 beats/min, midpoint of operation: 196.7 +/- 31.3 beats/min, maximum slope: 1.65 +/- 0.51). The maximum step responses determined from the dynamic characteristics were 7.9 +/- 2.9 and -14.0 +/- 4.9 beats. min-1. Hz-1 for the sympathetic and the vagal system, respectively. Because of these characteristics, changes in sympathetic or vagal tone alone can alter the dynamic HR response to stimulation of the other nerve.

Acoustic Stimulation↗

PubMed2006

Marine monitoring: Its shortcomings and mismatch with the EU Water Framework Directive's objectives.

The main goal of the EU Water Framework Directive (WFD) is to achieve good ecological status across European surface waters by 2015 and as such, it offers the opportunity and thus the challenge to improve the protection of our coastal systems. It is the main example for Europe's increasing desire to conserve aquatic ecosystems. Ironically, since c. 1975 the increasing adoption of EU directives has been accompanied by a decreasing interest of, for example, the Dutch government to assess the quality of its coastal and marine ecosystems. The surveillance and monitoring started in NL in 1971 has declined since the 1980s resulting in a 35% reduction of sampling stations. Given this and interruptions the remaining data series is considered to be insufficient for purposes other than trend analysis and compliance. The Dutch marine managers have apparently chosen a minimal (cost-effective) approach despite the WFD implicitly requiring the incorporation of the system's 'ecological complexity' in indices used to evaluate the ecological status of highly variable systems such as transitional and coastal waters. These indices should include both the community structure and system functioning and to make this really cost-effective a new monitoring strategy is required with a tailor-made programme. Since the adoption of the WFD in 2000 and the launching of the European Marine Strategy in 2002 (and the recently proposed Marine Framework Directive) we suggest reviewing national monitoring programmes in order to integrate water quality monitoring and biological monitoring and change from 'station oriented monitoring' to 'basin or system oriented monitoring' in combination with specific 'cause-effect' studies for highly dynamic coastal systems. Progress will be made if the collected information is integrated and aggregated in valuable tools such as structure- and functioning-oriented computer simulation models and Decision Support Systems. The development of ecological indices integrating community structure and system functioning, such as in Ecological Network Analysis, are proposed to meet a cost-effective approach at the national level and full assessment of the ecosystem status at the EU level. The WFD offers the opportunity to re-consider and re-invest in environmental research and monitoring. Using examples from the Netherlands and, to a lesser extent, the United Kingdom, the present paper therefore reviews marine monitoring and marine environmental research in combination and in the light of such major policy initiatives such as the WFD.

Animals↗

PubMed2002

[Prediction of calculus clearance after extracorporeal shock wave lithotripsy of calculi in the inferior kidney calices. Application of the artificial neural network].

The purpose of this retrospective study was to define prognostic factors which determine the stone clearance (SC) for lower caliceal stones after extracorporeal shock wave lithotripsy (ESWL) and to compare the prediction accuracy of artificial neural network analysis (ANNA) and standard computational methods. Since January 1995, 321 renal units in 310 patients with single or multiple inferior caliceal calculi of all sizes and compositions have been treated with ESWL (Lithotriptor: Piezolith 2500, Wolf company). The classification accuracy of ANNA in the test set was 94%, with a sensitivity of 95%, a specificity of 92%, and a receiver operating characteristic curve area of 0.966, results significantly better than those yielded by a logistic regression analysis (classification accuracy 77%, sensitivity 75%, specificity 81%, and ROC curve area 0.779). Patients with lower renal caliceal stones appear to have the best chance of successful ESWL when their body mass index (BMI) and urinary transport (UT) are normal, the infundibular width (IW) is 5 mm or more, and the infundibular ureteropelvic angle (IUPA) is 45 degrees or more. Stone size and composition, as factors of SC, are not statistically significant. After determining the angle, width, and UT in patients with optimal age and body mass suitable for ESWL, SC can be achieved irrespective of stone size and composition.

Adolescent↗

PubMed2000

A QSAR model for the eye irritation of cationic surfactants.

A QSAR model for the eye irritation of cationic surfactants has been constructed using a dataset consisting of the maximum average scores (MAS-accordance to Draize) for 29 in vivo rabbit eye irritation tests on 19 different cationic surfactants. The parameters used were logP (log [octanol/water partition coefficient]) and molecular volume (to model the partition of the surfactants into the membranes of the eye), logCMC (log critical micelle concentration-a measure of the reactivity of the surfactants with the eye) together with surfactant concentration. The model was constructed using neural network analysis. MAS showed strongly positive, non-linear correlations with surfactant concentration and logCMC and a strongly negative, non-linear correlation with logP. The Pearson correlation between the actual and predicted values of MAS was 0.838 showing that around 70% (r(2)=0.702) of the variance in the dataset is explained by the model. This value is consistent with levels of biological variability reported historically for the Draize rabbit eye test. The relationship provides a potentially useful prediction model for the eye irritation potential of new or untested cationic surfactants with physicochemical properties lying within the parameter space of the model.

Animals↗

PubMed2026

Exploring the potential mechanism of Huang'e capsule against spontaneous benign prostatic hyperplasia in beagle dogs using high-performance liquid chromatography-quadrupole-time-of-flight tandem mass spectrometry, gas chromatography-mass spectrometry, and network pharmacology.

OBJECTIVE: To investigate the therapeutic efficacy and potential mechanisms of Huang'e capsule (, HEC) against benign prostatic hyperplasia (BPH). METHODS: The chemical profile of HEC was characterized using high-performance liquid chromatographyquadrupole-time-of-flight tandem mass spectrometry (HPLC-Q-TOF-MS/MS) and gas chromatography-mass spectrometry (GC-MS) techniques. Network pharmacology was employed to analyze potential active compounds, core targets, and key signaling pathways. A spontaneous canine BPH model was used to evaluate the efficacy of HEC and to validate the predictions from network pharmacology. RESULTS: A total of 51 chemical components of HEC were identified, comprising 19 from HPLC-Q-TOF-MS/MS and 32 from GC-MS analyses. The "components-targets-pathways-disease" network analysis predicted active compounds including (s)-coriolic acid, ethyl linoleate, peroxysimulenoline, physcion, and kaempferol. Core targets identified included cytochrome P450 family 19 subfamily A member 1, estrogen receptor 2 (ESR2), ESR1, and androgen receptor (AR). Kyoto Encyclopedia of Genes and Genomes enrichment analysis suggested that HEC's effects on BPH involve pathways related to cancer, phosphatidylinositol 3-kinase (PI3K) -protein kinase B (Akt)-signaling, proteoglycans in cancer, and prostate cancer signaling. Animal experiments showed that HEC significantly improved maximum urinary flow rates, reduced prostate weight, volume, and prostate index, and ameliorated histopathological changes. HEC regulated the balance between apoptosis and proliferation by downregulating AR and estrogen receptor alpha expression, while upregulating estrogen receptor beta expression. CONCLUSION: These findings indicate that HEC effectively ameliorates spontaneous BPH in beagle dogs, likely by regulating the balance between cell apoptosis and proliferation through multiple signaling pathways.

Animals↗

PubMed2026

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6 h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6 h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-κB cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6 h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides↗

PubMed2003

Prediction of unconfined compressive strength of cement paste containing industrial wastes.

Neural network analysis was used to construct models of unconfined compressive strength (UCS) as a function of mix composition using existing data from literature studies of Portland cement containing real industrial wastes. The models were able to represent the known non-linear dependency of UCS on curing time and water content, and generalised from the literature data to find relationships between UCS and quantities of five waste types. Substantial decreases in UCS were caused by all wastes; except for EAF dust, the effect was nonlinear with the greatest decrease caused initially by approx. 12% plating sludge, 40% foundry dust, 58% other ash, and 72% MSWI fly ash by mass of dry product. It appears that the maximum waste additions used in modelling may approximate the practical limits of waste additions used in modelling may approximate the practical limits of waste addition to Portland cement, i.e., 50% plating sludge or EAF dust, 64% foundry dust, 92% other ash, and 85% MSWI fly ash by mass of dry product. The laboratory was found to be a key predictive variable and acted as a surrogate for laboratory-specific variables related to cement composition, strength and hardening class, product mixing and preparation details, laboratory conditions, and testing details. While the neural network modelling approach has been shown to be feasible, development of better models would require larger data sets with more complete information regarding laboratory-specific variables and waste composition.

Compressive Strength↗

PubMed2025

Prenatal pyrethroid exposure, placental gene network modules, and neonatal neurobehavior.

Prenatal pesticide exposure may adversely affect child neurodevelopment which may partly arise from impairing the placenta's vital role in fetal development. In a cohort of pregnant farmworkers from Thailand (N = 248), we examined the links between urinary metabolites of pyrethroid pesticides during pregnancy, placental gene expression networks derived from transcriptome sequencing, and newborn neurobehavior assessed using the NICU Network Neurobehavioral Scales (NNNS) at 5 weeks of age. Focusing on the 21 gene network modules in the placenta identified by Weighted Gene Co-expression Network Analysis, our analysis revealed significant associations between metabolites and nine distinct modules, and between thirteen modules and NNNS, with eight modules showing overlap. Notably, stress was negatively associated with the interferon alpha response and Myc target modules, and the interferon alpha response module was correlated positively with attention, and negatively with arousal, and quality of movement. The analysis also highlighted the early and late trimesters as critical periods for the exposures influence on placental function, with pyrethroid metabolites measured early in pregnancy significantly negatively associated with the protein secretion module, and those measured later in pregnancy negatively associated with modules related to oxidative phosphorylation (OXPHOS) and DNA repair. Additionally, the cumulative sum of 3-phenoxybenzoic acid across pregnancy was significantly negatively associated with the OXPHOS module. These findings suggest that prenatal exposure to pyrethroids may influence neonatal neurobehavior through specific placental mechanisms that impact gene expression of metabolic pathways, and these effects may be pregnancy period specific. These results offer valuable insights for future risk assessment and intervention strategies.

Prenatal Exposure Delayed Effects↗

PubMed2004

Preoperative neural network using combined magnetic resonance imaging variables, prostate specific antigen and Gleason score to predict prostate cancer stage.

PURPOSE: We developed an artificial neural network analysis (ANNA) to predict prostate cancer pathological stage more effectively than logistic regression (LR) based on the combined use of prostate specific antigen (PSA), biopsy Gleason score and pelvic coil magnetic resonance imaging (pMRI) in patients with clinically organ confined disease before radical prostatectomy. MATERIALS AND METHODS: In 201 consecutive patients undergoing radical retropubic prostatectomy with pelvic lymphadenectomy the radiological-pathological correlation was evaluated using pMRI. Predictive variables were clinical TNM classification, preoperative serum PSA, biopsy Gleason score and pMRI findings. The predicted results were organ confined vs nonorgan confined disease and lymphatic vs no lymphatic involvement. The predicted ability of ANNA with several parameters in a set of 160 randomly selected test data was compared with that of LR and the Partin tables by area under the receiver operating characteristic curve analysis. RESULTS: The overall accuracy of ANNA and LR was 88% and 91%, and 77% and 84% for nonorgan confined and lymphatic involvement, respectively. For nonorgan confined disease and lymph node involvement the area under the curve of ANNA (0.895 and 0.899) was significantly larger than that of LR and the Partin tables (0.722 and 0.751, and 0.750 and 0.733, respectively, p <0.05). Gleason score represented the most influential predictor (relative weight 2.05) of nonorgan confined disease, followed by pMRI findings (1.96), PSA (1.73) and clinical stage (0.89). CONCLUSIONS: ANNA is superior to LR for accurately predicting pathological stage. The relative importance of pMRI findings and the usefulness of ANNA for predicting pathological stage in individuals must be confirmed in a prospective trial.

Adult↗

PubMed2026

Uncovering ShuangZi Powder's Anti-Ovarian Cancer Mechanism: A Systems Biology and Experimental Approach.

INTRODUCTION: This study investigated the anti-ovarian cancer (OC) effects of Shuangzi Powder (SZP) and its regulatory impact on the tumor microenvironment. METHOD: This study employed systems biology approaches, integrating molecular docking and experimental validation, to explore the pharmacological mechanisms of SZP in OC treatment. To identify potential bioactive compounds and target genes of SZP, network pharmacology, protein- protein interaction network analysis,.Gene Ontology (GO) analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were conducted. RESULTS: Among the 11 bioactive ingredients identified in SZP, 1,767 potential therapeutic targets were predicted, while 2,637 differentially expressed genes were found to be associated with OC. KEGG pathway analysis revealed significant enrichment in pathways related to cancer, apoptosis, the PI3K-Akt signaling pathway, and the PD-L1/PD-1 checkpoint pathway. Treatment of A2780 cells with β,β-Dimethylacrylshikonin (DMAS) inhibited cell viability, migration, and invasion. Moreover, DMAS downregulated the expression of cell cycle- and apoptosis-related genes (CCNB1, CHEK1, CCNE1, and PARP1) and upregulated the immune checkpoint gene PD-L1. DISCUSSION: These findings indicate that multiple components, targets, and pathways are involved in OC treatment by SZP. CONCLUSION: DMAS, one of the bioactive ingredients of SZP, was predicted and preliminarily validated to exert inhibitory effects on OC cells, mainly through the regulation of the cell cycle, apoptosis, and immune response, as demonstrated by molecular docking and experimental analyses.

Ovarian Neoplasms↗

PubMed2004

Preoperative neural network using combined magnetic resonance imaging variables, prostate specific antigen, and Gleason score to predict prostate cancer recurrence after radical prostatectomy.

OBJECTIVE: An artificial neural network analysis (ANNA) was developed to predict the biochemical recurrence more effectively than regression models based on the combined use of pelvic coil magnetic resonance imaging (pMRI), prostate specific antigen (PSA) and biopsy Gleason score in patients with clinically organ-confined prostate cancer after radical prostatectomy (RP). METHODS: Two-hundred-and-ten patients undergoing retropubic RP with pelvic lymphadenectomy were evaluated. Predictive study variables included clinical TNM classification, preoperative serum PSA, biopsy Gleason score, transrectal ultrasound (TRUS) findings, and pMRI findings. The predicted result was a biochemical failure (PSA >or=0.1 ng/ml). Using a five-way cross-validation method, the predicted ability of ANNA for a validation set of 200 randomly selected patients was compared with those of Cox regression analysis and "Kattan nomogram" by area under the receiver operating characteristic curve (AUC) analysis. RESULTS: Seventy-three patients (35%) failed at median follow-up of 61 (mean: 60, range: 2-94) months. Using similar input variables, the AUC of ANNA (0.765, 95% Confidence Interval [CI]: 0.704-0.825) was comparable (p > 0.05) to those for Cox regression (0.738, 95%CI: 0.691-0.819) and Kattan nomogram (0.728, 95%CI: 0.644-0.819). Contrarily, adding the pMRI findings, the ANNA is significantly (p < 0.05) superior to any other predictive model (0.897, 95%CI: 0.841-0.977). The Gleason score represented the most influential predictor (relative weight: 2.4) of PSA recurrence, followed by pMRI (2.2), and PSA (2.0). CONCLUSION: ANNA is superior to regression models to predict accurately biochemical recurrence. The relative importance of pMRI and the utility of ANNA to predict the PSA failure in patients referred for RP must be confirmed in further trials.

Biomarkers, Tumor↗