Normalization can standardize and improve machine learning (ML) performance on omics data. However, it is unclear whether normalization is associated with overfitting (i.e., worse cross-dataset performance than intra-dataset performance). Therefore, we aimed to examine associations of normalization and regularization with overfitting of ML on omics data.

Using three paired transcriptomic and clinical datasets (lung adenocarcinoma: the Cancer Genome Atlas (TCGA)/Oncology Singapore; melanoma: TCGA/Dana-Farber Cancer Institute; glioblastoma: TCGA/Clinical Proteomic Tumor Analysis Consortium), we applied ANOVA-based gene selection methods, six normalization methods, and six ML models to classify cancer patients’ deaths. Balanced accuracy (BA) and area under the curve (AUC) in intra- and cross-dataset settings were compared using inferential analyses.

Normalization consistently improved intra-dataset performance (median BA/AUC changes: 0.035–0.214/0.115–0.279) on all data, particularly with Z_Raw, but decreased or slightly increased cross-dataset performance (median BA/AUC changes: −0.029–0.079/0.029–0.064). Least Absolute Shrinkage and Selection Operator (LASSO) model without normalization consistently outperformed most of the ML models in cross-dataset testing across cancer types. ML models on all and molecular-alone data showed similar best performances.

Normalization increases ML’s intra-dataset performance and overfitting in three paired cancer transcriptomic and clinical datasets. Regularized models such as LASSO appear to mitigate overfitting and achieve robust cross-dataset performance. Therefore, cross-dataset evaluation and regularized models are recommended to assess and reduce overfitting, while normalization should be used cautiously. Adding clinical data seems to have little impact on ML models’ performance. However, future work on other diseases and datasets is warranted.

Infectious diarrhea is a gastrointestinal illness that results in around 1.7 billion cases and 525,000 deaths annually, particularly among children under five, according to the World Health Organization. While some Cameroonian medicinal plants show promise for treating diarrhea, many plants are used without established scientific evidence of their efficacy. These plants include Tithonia diversifolia (T. diversifolia) and Solanum torvum (S. torvum), which are traditionally used to treat diarrheal symptoms. This study sought to investigate the anti-Shigella activity of leaf extracts from T. diversifolia and S. torvum.

Extracts from T. diversifolia and S. torvum were obtained by successive maceration in solvents of increasing polarity, including hexane, dichloromethane, ethyl acetate, methanol, and water. The as-prepared extracts (10) were evaluated for antibacterial activity against selected Shigella species using an in vitro experiment. The mode of action of the bioactive extracts was determined in Shigella through growth kinetic analysis.

Hexane extract from S. torvum (St-HEX-F) and dichloromethane extract from T. diversifolia (Td-DCM-F) inhibited the growth of Shigella flexneri NR-518 and Shigella boydii NR-521 with minimum inhibitory concentration (MIC) values of 500 and 1,000 µg/mL, respectively. Shigella flexneri and Shigella boydii were the most sensitive strains, whereas Shigella sonnei was the most resistant strain. Bacterial growth kinetics revealed that St-HEX-F and Td-DCM-F are bacteriostatic at MIC and bactericidal at 2×MIC and 4×MIC.

Extracts from T. diversifolia and S. torvum possess anti-Shigella activity and could be used as a potential source of active ingredients for developing new treatments against diarrhea caused by multidrug-resistant Shigella.

Amaranth is conventionally consumed as a significant source of nutrients and bioactive compounds and is a potential alternate crop. The present study aimed to validate the folklore and ethnomedicinal claims regarding the utilization of foliar tissues of the pseudocereal Amaranthus hypochondriacus L. for their pharmacological propensities, primarily focusing on bioactive polyphenolic compounds and associated anti-degenerative properties, in view of the scarce evidence available on the same.

Reverse-phase high-performance liquid chromatography coupled with a photodiode array assay of nineteen significant bioactive polyphenolic compounds, along with their in vitro antioxidant-based pharmacological properties (superoxide and hydroxyl radical scavenging properties, metal-chelating and reducing properties, radical scavenging properties, anti-lipid peroxidation and protein coagulation properties, and α-glucosidase and α-amylase inhibitory activities), were assessed and compared for foliar extracts of ten promising experimental accessions of Amaranthus hypochondriacus, grown in two different seasons (summer and winter).

The results exhibited germplasm-specific variations in the pharmacological potential of foliar tissues of the experimental amaranths, which can be substantiated by data showing a close correlation between the abundance of bioactive polyphenolic compounds (naringin, myricetin, naringenin, apigenin, rutin, catechin, quercetin) and in vitro antioxidant (2,2-diphenyl-1-picrylhydrazyl, 2,2′-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) assay, hydroxyl radical scavenging, reducing, and metal-chelating) properties, as well as anti-diabetic (inhibition of α-glucosidase and α-amylase activities) and anti-inflammatory (anti-lipid peroxidation) attributes. Accessions IC107144 and IC47434 stood out as the most promising medicinal crops based on overall in vitro anti-degenerative properties and the bioavailability of polyphenolic compounds.

Overall, the results validated the traditional ethnomedicinal claim regarding the utilization of foliar tissues of the underutilized pseudocereal Amaranthus hypochondriacus L., and identified lead germplasms (IC107144 and IC47434) as low-cost natural sources of bioactive compounds, potentially promoting their pharmacological utilization.

Given the lack of efficient biomarkers for hepatocellular carcinoma (HCC) diagnosis, this study aimed to develop an HCC diagnostic strategy based on serum protein glycosylation signatures. We characterized differential N-glycosylation patterns of serum IgG to differentiate HCC from healthy controls and liver cirrhosis, and elucidated the molecular mechanisms driving aberrant Neu5Gc elevation in HCC to provide a theoretical basis for clinical application and differential diagnosis of HCC.

LIP-ELISA was applied to quantify serum Neu5Gc in 6,768 healthy individuals for baseline establishment. IgG was purified and subsequently analyzed by RPLC-MS/MS for glycosylation profiling in HCC and healthy samples. Bioinformatic analysis of CMAH and related gene clusters modulating Neu5Gc synthesis was conducted.

In a cohort of 1,114 participants, the LIP-ELISA platform achieved 80.21% sensitivity, 96.01% specificity, and 92.46% accuracy for primary HCC diagnosis. Serum IgG from HCC patients displayed multi-branched N-glycans modified with core fucose and Neu5Gc. Key molecules involved in glycan modification were identified, enabling the development of multiplexed gene detection for HCC, LC, and chronic hepatitis B. In vitro assays confirmed hypoxia-induced sialic acid accumulation in HCC cells. Meanwhile, CMAH-knockout mouse experiments verified that an exogenous high-sialic-acid diet compensates for endogenous Neu5Gc synthesis deficiency, revealing a dietary-mediated compensatory mechanism for Neu5Gc elevation.

This study established an LIP-ELISA-based clinical diagnostic platform combining AFP and Neu5Gc, defined sialic acid–modified glycan structures, and preliminarily identified regulators of Neu5Gc biosynthesis, providing novel insights for HCC diagnosis and mechanism research.

PVT is a harmful event in cirrhosis, and the prevention and treatment of PVT are important in the management of cirrhosis and portal hypertension. The study aimed to observe the efficacy of Danggui Buxue Decoction (DBD) on portal vein thrombosis (PVT) in cirrhosis and to elucidate the related mechanism using a modified animal model.

A model of PVT in cirrhosis was established by partial portal vein ligation and intraperitoneal injection of CCl4 in rats, which showed obvious PVT with intra- and extravenous thrombosis as well as liver cirrhosis. Rats were randomly assigned into four groups and received intragastric administration of DBD (12 g/kg/day) or rivaroxaban (20 mg/kg/day) for 6 weeks.

DBD attenuated collagen deposition and reduced thrombus formation in model livers, increased portal vein blood flow, expanded the portal vein diameter, and reduced prothrombin time and international normalized ratio in the model rats. In addition, DBD reduced hepatic von Willebrand factor and plasminogen activator inhibitor-1 expression and increased hepatic fibrin degradation product content in the liver tissues of model rats.

We modified a model of cirrhotic PVT in rats and found that DBD had a good effect on PVT and liver fibrosis, with the mechanisms related to the enhancement of portal vein blood flow and the protection against endothelial cell injury.

Pancreatic cystic neoplasms (PCNs) are increasingly detected in clinical practice, yet substantial variability exists in imaging interpretation and reporting, which may affect clinical decision-making. This guideline was developed to standardize diagnostic imaging evaluation and reporting for PCNs. A multidisciplinary expert panel conducted literature search and critical appraisal of domestic and international evidence, identified key clinical questions, and formulated recommendations using the Grading of Recommendations Assessment, Development and Evaluation framework. A modified Delphi consensus process and external review were performed to ensure the robustness of the recommendations. A total of 21 key questions were addressed, covering essential aspects of imaging evaluation and reporting for PCNs, including the preferred imaging modality for suspected lesions; standardized measurement of cyst size and mural nodules and their clinical significance; definitions of cyst wall and septal thickening; optimal imaging approaches for assessing the relationship between cystic lesions and the main pancreatic duct; measurement and evaluation of main pancreatic duct diameter and dilation; imaging-based classification of intraductal papillary mucinous neoplasms and serous cystic neoplasms; assessment of ductal obstruction, calcification, hemorrhage, and pancreatitis-related changes; criteria for suspicious lymph nodes; differentiation of PCNs from pancreatic pseudocysts or retention cysts; and recommended imaging modalities and follow-up intervals. This guideline provides a structured and evidence-based framework for imaging evaluation and reporting of PCNs, which may improve the consistency and clarity of imaging reports and support clinical decision-making.

Breast cancer (BCA) is one of the most common cancers worldwide, with a high rate of mortality and morbidity in women. This review focuses on the applications of nanotechnology, nanomaterials, and nanoparticles (NPs) in BCA, encompassing diagnosis and therapy. Nanotechnologies, nanocarriers, and nano-encapsulations versus their corresponding counterparts for BCA diagnosis and therapy have been discussed. Various drug formulations into different nanocarriers (lipid NPs, nanoemulsions, polymeric NPs, and metal-based NPs) enhanced their bioavailability and therapeutic efficacy, overcoming the limitations of conventional formulations. Additionally, clinical specialists have achieved improved outcomes in the detection and monitoring of BCA at various stages using nanotechnology, ultimately leading to an improved quality of life for patients.

N6-methyladenosine (m6A), the most prevalent internal RNA modification in eukaryotic cells, is a dynamic regulator of RNA metabolism and cancer biology. In colorectal cancer (CRC), dysregulated m6A reshapes transcriptomic programs that control tumor growth, metastasis, immune evasion, and therapeutic resistance. However, the context-dependent functions of individual m6A regulators remain incompletely defined, the integration of m6A with canonical oncogenic signaling remains incomplete, and its role in metabolic reprogramming lacks a systematic overview. This review aims to integrate current evidence on m6A regulatory machinery in CRC, clarify its coordination with oncogenic signaling and metabolic pathways, and highlight emerging translational implications. The key players regulating m6A in CRC progression are m6A “writers”, including methyltransferase-like 3 and methyltransferase-like 14; m6A “erasers”, including fat mass and obesity-associated protein and AlkB homolog 5; and m6A “readers”, including the YTH m6A RNA-binding protein family and the insulin-like growth factor 2 mRNA-binding protein family. m6A modification coordinates key oncogenic pathways, including Wnt/β-catenin, PI3K/Akt, MAPK, and p53 signaling. Moreover, m6A-dependent regulation of metabolic enzymes such as hexokinase 2, pyruvate kinase M2, and fatty acid synthase promotes the reprogramming of glucose, amino acid, and lipid metabolism, linking epitranscriptomic control to bioenergetic adaptation. We also discuss context-dependent and paradoxical functions of m6A regulators and advances in m6A-targeted therapies. In conclusion, m6A modification functions as a central regulatory hub in CRC by integrating signaling networks and metabolic pathways. Deeper mechanistic insights into spatiotemporal m6A regulation may accelerate the development of biomarkers and targeted therapies for precision CRC management.

Human papillomavirus (HPV) is a double-stranded circular DNA virus with a genome of approximately 7–8 kb. This study aimed to establish an overlapping extension polymerase chain reaction method for the amplification of the entire genome of HPV16.

The HPV16 genome was divided into two larger fragments (with lengths of 3.9 kilobases and 5.3 kilobases, respectively), each of which had overlapping regions of more than 500 base pairs. A nested primer (outer primer: Fout/Rout; inner primer: Fin/Rin) was used to amplify each fragment. The key reaction parameters were optimized, including the selection of two highly accurate DNA polymerases; and a series of diluted samples (initial concentration of 2,000 copies/microliter, diluted to 2, 20, 200, and 2,000 copies/microliter) were used for amplification tests to evaluate the sensitivity of this method.

This study demonstrated high sensitivity for HPV16 detection, with effective amplification of samples as low as 2 copies/µL. For low-concentration samples (<200 copies/µL), the Thermo Fisher enzyme showed 50% and 75% effective amplification success rates at 2 copies/µL and 20 copies/µL, respectively, while the Vazyme enzyme achieved 0% success at both concentrations. Both enzymes enabled stable amplification of high-concentration samples (≥200 copies/µL). The amplified products matched the theoretical size, and Illumina sequencing confirmed Q30 ≥ 96% and >98% identity with the HPV16 reference sequence (K02718.1).

This study provides a highly sensitive and specific method for the full-genome sequence analysis of HPV16, which is applicable to HPV16 full-genome sequencing, variation analysis, and other research.