Biomarkers and pathways in autism spectrum disorder: An individual meta-analysis based on proteomic and metabolomic data.

The utilization of biomarkers for the diagnosis and management of autism spectrum disorders (ASD) remains a relatively unexplored frontier in clinical practice. Proteomics and metabolomics are important tools for revealing key biomarkers and evaluating biological pathways in ASD. We conducted an individual meta-analysis to compare the consistency of biomarkers of ASD from central nervous system (brain and cerebrospinal fluid), circulatory system (blood), and non-invasive samples (urine, saliva, and faeces) and performed pathway enrichment analyses to identify pathways enriched in ASD. After screening 926 proteomics and 619 metabolomics articles, we collected data from 10 studies involving 940 differential proteins and 16 studies assessing a total of 748 differential metabolites. In brain tissue, blood, and urine of ASD cases and controls, flotillin-2 (FLOT2), apolipoprotein E (ApoE), and EH domain-containing protein 3 (EHD3) exhibit differential expression, while vinculin (VCL) displays variations in saliva, blood, and urine. Similarly, in case-control studies, gelsolin (GSN) shows differential expression in brain tissue, saliva, and urine, and malate dehydrogenase 2 (MDH2) in brain tissue, blood, and saliva. Hippuric acid and salicyluric acid were simultaneously found in the brain, blood, urine, and faeces. In terms of pathways, glycolysis/gluconeogenesis, carbon metabolism, and glutathione metabolism were enriched in the brain as well as in saliva or urine. In our study, we identified six shared protein and two metabolic markers in central nervous system, circulatory system, and non-invasive samples, underscoring their potential value for ASD diagnosis and management, warranting further research.

Asian Cohort for Alzheimer's Disease (ACAD) pilot study on genetic and non-genetic risk factors for Alzheimer's disease among Asian Americans and Canadians.

INTRODUCTION: Clinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non-genetic/lifestyle factors impact this multi-ethnic population. METHODS: The ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese. RESULTS: ACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception. DISCUSSION: ACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit > 5000 participants to identify genetic and non-genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness. HIGHLIGHTS: The Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under-investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.

Peptide-derived coordination frameworks for biomimetic and selective separation.

Peptide-derived metal-organic frameworks (PMOFs) have emerged as a class of biomimetic materials with attractive performances in analytical and bioanalytical chemistry. The incorporation of biomolecule peptides gives the frameworks conformational flexibility, guest adaptability, built-in chirality, and molecular recognition ability, which greatly accelerate the applications of PMOFs in enantiomeric separation, affinity separation, and the enrichment of bioactive species from complicated samples. This review focuses on the recent advances in the engineering and applications of PMOFs in selective separation. The unique biomimetic size-, enantio-, and affinity-selective performances for separation are discussed along with the chemical structures and functions of MOFs and peptides. Updates of the applications of PMOFs in adaptive separation of small molecules, chiral separation of drug molecules, and affinity isolation of bioactive species are summarized. Finally, the promising future and remaining challenges of PMOFs for selective separation of complex biosamples are discussed.

Characterization of chemical ingredients and in rats metabolic profiling of Lingyang Qingfei pills via ultra-high-performance liquid chromatography combined with Quadrupole-Exactive Orbitrap high-resolution mass spectrometry.

Lingyang Qingfei pills (LQP), the renowned traditional Chinese medicine recipe, have been extensively utilized for the therapy of xerostomia, sore throat, bronchiolitis, and pneumonia in clinics. However, its phytochemicals remain equivocal, which severely limits the development of quality control and activity mechanisms. In the current research, a trusted method founded on ultra-high performance liquid chromatography with Quadrupole-Exactive Orbitrap mass spectrometry technique was proposed for the comprehensive screening of in vitro and in vivo chemical compositions of LQP. As a consequence, 239 constituents were preliminarily characterized, 37 of which were accurately confirmed by reference standards. In addition, a total of 208 xenobiotics, containing 71 absorbed prototypes and 137 metabolites, were revealed in rat plasma, bile, urine, and feces, respectively. The metabolic reaction of hydrolysis, hydroxylation, methylation, glycosylation, sulfation, and mixed-mode was detected in the biotransformations of flavonoids, terpenoids, alkaloids, anthraquinones, organic acids, phenylpropanoids, and so forth. And 12 of the metabolites were new compounds. This experiment acted as the first reference for chemical substances and metabolites of LQP, which could provide valuable chemical information for further clarifying pharmacodynamic substances and pharmacokinetic studies.

Drivers and constraints to environmental sustainability in UK-based biobanking: balancing resource efficiency and future value.

BACKGROUND: Biobanks are a key aspect of healthcare research; they enable access to a wide range of heterogenous samples and data, as well as saving individual researchers time and funds on the collection, storage and/or curation of such resources. However, biobanks are also associated with impacts associated with a depletion of natural resources (energy, water etc.) production of toxic chemicals during manufacturing of laboratory equipment, and effects on biodiversity. We wanted to better understand the biobanking sector in the UK as a first step to assessing the environmental impacts of UK biobanking. METHODS: We explored the sample storage infrastructure and environmental sustainability practices at a number of UK biobanks through a mixed methods quantitative and qualitative approach, including information gathering on an online platform, and eight in-depth interviews. RESULTS: Environmental sustainability was deprioritised behind biobanks' financial sustainability practices. Nevertheless, both often aligned in practice. However, there was a tendency towards underutilisation of stored samples, the avoidance of centralisation, and providing accessibility to biosamples, and this conflicted with valuing sustainability goals. This related to notions of individualised and competitive biobanking culture. Furthermore, the study raised how value attachments to biosamples overshadows needs for both financial and environmental sustainability concerns. CONCLUSIONS: We need to move away from individualised and competitive biobanking cultures towards a realisation that the health of the publics and patients should be first and foremost. We need to ensure the use of biosamples, ahead of their storage ('smart attachments'), align with environmental sustainability goals and participants' donation wishes for biosample use.

A Federated Learning Model Based on Hardware Acceleration for the Early Detection of Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive illness with a slow start that lasts many years; the disease's consequences are devastating to the patient and the patient's family. If detected early, the disease's impact and prognosis can be altered significantly. Blood biosamples are often employed in simple medical testing since they are cost-effective and easy to collect and analyze. This research provides a diagnostic model for Alzheimer's disease based on federated learning (FL) and hardware acceleration using blood biosamples. We used blood biosample datasets provided by the ADNI website to compare and evaluate the performance of our models. FL has been used to train a shared model without sharing local devices' raw data with a central server to preserve privacy. We developed a hardware acceleration approach for building our FL model so that we could speed up the training and testing procedures. The VHDL hardware description language and an Altera 10 GX FPGA are utilized to construct the hardware-accelerator approach. The results of the simulations reveal that the proposed methods achieve accuracy and sensitivity for early detection of 89% and 87%, respectively, while simultaneously requiring less time to train than other algorithms considered to be state-of-the-art. The proposed algorithms have a power consumption ranging from 35 to 39 mW, which qualifies them for use in limited devices. Furthermore, the result shows that the proposed method has a lower inference latency (61 ms) than the existing methods with fewer resources.

[The baseline assessment of the German National Cohort (NAKO Gesundheitsstudie): participation in the examination modules, quality assurance, and the use of secondary data]. / Die Basiserhebung der NAKO Gesundheitsstudie: Teilnahme an den Untersuchungsmodulen, Qualitätssicherung und Nutzung von Sekundärdaten.

BACKGROUND: The German National Cohort (NAKO) is an interdisciplinary health study aimed at elucidating causes for common chronic diseases and detecting their preclinical stages. This article provides an overview of design, methods, participation in the examinations, and their quality assurance based on the midterm baseline dataset (MBD) of the recruitment. METHODS: More than 200,000 women and men aged 20-69 years derived from random samples of the German general population were recruited in 18 study centers (2014-2019). The data collection comprised physical examinations, standardized interviews and questionnaires, and the collection of biomedical samples for all participants (level 1). At least 20% of all participants received additional in-depth examinations (level 2), and 30,000 received whole-body magnet resonance imaging (MRI). Additional information will be collected through secondary data sources such as medical registries, health insurances, and pension funds. This overview is based on the MBD, which included 101,839 participants, of whom 11,371 received an MRI. RESULTS: The mean response proportion was 18%. The participation in the examinations was high with most of the modules performed by over 95%. Among MRI participants, 96% completed all 12 MRI sequences. More than 90% of the participants agreed to the use of complementary secondary and registry data. DISCUSSION: Individuals selected for the NAKO were willing to participate in all examinations despite the time-consuming program. The NAKO provides a central resource for population-based epidemiologic research and will contribute to developing innovative strategies for prevention, screening and prediction of chronic diseases.

Fabrication of an ionic-liquid-based polymer monolithic column and its application in the fractionation of proteins from complex biosamples.

An ionic-liquid-based polymer monolithic column was synthesized by free radical polymerization within the confines of a stainless-steel column (50 mm × 4.6 mm id). In the processes, ionic liquid and stearyl methacrylate were used as dual monomers, ethylene glycol dimethacrylate as the cross-linking agent, and polyethylene glycol 200 and isopropanol as co-porogens. Effects of the prepolymerization solution components on the properties of the resulting monoliths were studied in detail. Scanning electron microscopy, nitrogen adsorption-desorption measurements, and mercury intrusion porosimetry were used to investigate the morphology and pore size distribution of the prepared monoliths, which showed that the homemade ionic-liquid-based monolith column possessed a relatively uniform macropore structure with a total macropore specific surface area of 44.72 m2 /g. Compared to a non-ionic-liquid-based monolith prepared under the same conditions, the ionic-liquid-based monolith exhibited excellent selectivity and high performance for separating proteins from complex biosamples, such as egg white, snailase, bovine serum albumin digest solution, human plasma, etc., indicating promising applications in the fractionation and analysis of proteins from the complex biosamples in proteomics research.

Characterization of metabolites of larotaxel in rat by liquid chromatography coupled with Q exactive high-resolution benchtop quadrupole orbitrap mass spectrometer.

1. Liquid-chromatography (LC) high-resolution (HR) mass spectrometry (MS) analysis can record HR full scans for drug metabolism studies. Larotaxel is a taxane analog that has the potential for the treatment of various types of cancer. 2. In this study, the metabolism of larotaxel was evaluated after an intravenous dose of 8 mg/kg via the caudal vein to healthy rats and its metabolites were characterized by high performance liquid chromatography coupled with a Q Exactive high-resolution benchtop quadrupole orbitrap mass spectrometer. Rat bio-samples were separated on a Capcell Pak C18 column (2.1 i.d. × 100 mm; 2.7 µm) with mobile phase of acetonitrile and water. 3. As a result, a total of 34 metabolites were detected and identified by comparing the molecular masses, retention times and spectral patterns of the analytes with those of the parent drug. Three metabolites were confirmed by comparison with reference substances. 4. The prominent metabolites were mainly hydroxyl, dihydroxyl, trihydroxyl and 10-desacetyl analogs of larotaxel, some of which resulted from oxidation of the tert-butyl groups on the side chain and further oxidation and cyclization of the tert-butyl hydroxylated metabolites.

Bioanalytical Methods for New Psychoactive Substances.

Bioanalysis of new psychoactive substances (NPS) is very challenging due to the growing number of compounds with new chemical structures found on the drugs of abuse market. Screening, identification, and quantification in biosamples are needed in clinical and forensic toxicology settings, and these procedures are more challenging than the analysis of seized drug material because of extremely low concentrations encountered in biofluids but also due to diverse metabolic alterations of the parent compounds. This article focuses on bioanalytical single- and multi-analyte procedures applicable to a broad variety of NPS in various biomatrices, such as blood, urine, oral fluid, or hair. Sample preparation, instrumentation, detection modes, and data evaluation are discussed as well as corresponding pitfalls. PubMed-listed and English-written original research papers and review articles published online between 01 October 2012 and 30 September 2017 were considered.

Eco-friendly synthesis of gelatin-capped bimetallic Au-Ag nanoparticles for chemiluminescence detection of anticancer raloxifene hydrochloride.

This study described the utility of green analytical chemistry in the synthesis of gelatin-capped silver, gold and bimetallic gold-silver nanoparticles (NPs). The preparation of nanoparticles was based on the reaction of silver nitrate or chlorauric acid with a 1.0 wt% aqueous gelatin solution at 50°C. The gelatin-capped silver, gold and bimetallic NPs were characterized using transmission electron microscopy, UV-vis, X-ray diffraction and Fourier transform infrared spectroscopy, and were used to enhance a sensitive sequential injection chemiluminescence luminol-potassium ferricyanide system for determination of the anticancer drug raloxifene hydrochloride. The developed method is eco-friendly and sensitive for chemiluminescence detection of the selected drug in its bulk powder, pharmaceutical injections and biosamples. After optimizing the conditions, a linear relationship in the range of 1.0 × 10(-9) to 1.0 × 10(-1)  mol/L was obtained with a limit of detection of 5.0 × 10(-10)  mol/L and a limit of quantification of 1.0 × 10(-9)  mol/L. Statistical treatment and method validation were performed based on ICH guidelines. Copyright © 2016 John Wiley & Sons, Ltd.

Bioethics in Iceland.

This article examines ethical issues debated in Iceland concerning population genetic research, specifically methods of collecting biosamples and ways to return clinically relevant results to participants. Also discussed are scientific research in the health sector, a bill on surrogacy, and a policy on consent for organ donation.

[Connecting biobanks of large European cohorts (EU Project BBMRI-LPC)]. / Vernetzung von Biobanken großer europäischer Kohorten (EU-Projekt BBMRI-LPC).

BACKGROUND: In addition to the Biobanking and BioMolecular resources Research Initiative (BBMRI), which is establishing a European research infrastructure for biobanks, a network for large European prospective cohorts (LPC) is being built to facilitate transnational research into important groups of diseases and health care. One instrument for this is the database "LPC Catalogue," which supports access to the biomaterials of the participating cohorts. OBJECTIVES: To present the LPC Catalogue as a relevant tool for connecting European biobanks. In addition, the LPC Catalogue has been extended to establish compatibility with existing Minimum Information About Biobank data Sharing (MIABIS) and to allow for more detailed search requests. This article describes the LPC Catalogue, its organizational and technical structure, and the aforementioned extensions. MATERIALS AND METHODS: The LPC Catalogue provides a structured overview of the participating LPCs. It offers various retrieval possibilities and a search function. To support more detailed search requests, a new module has been developed, called a "data cube". The provision of data by the cohorts is being supported by a "connector" component. RESULTS: The LPC Catalogue contains data on 22 cohorts and more than 3.8 million biosamples. At present, data on the biosamples of three cohorts have been acquired for the "cube," which is continuously being expanded. In the BBMRI-LPC, tendering for scientific projects using the data and samples of the participating cohorts is currently being carried out. In this context, several proposals have already been approved. CONCLUSIONS: The LPC Catalogue is supporting transnational access to biosamples. A comparison with existing solutions illustrates the relevance of its functionality.

Sensitive and Rapid UHPLC-MS/MS for the Analysis of Tomato Phenolics in Human Biological Samples.

An UHPLC-MS/MS method for the quantification of tomato phenolic metabolites in human fluids was optimized and validated, and then applied in a pilot dietary intervention study with healthy volunteers. A 5-fold gain in speed (3.5 min of total run); 7-fold increase in MS sensitivity and 2-fold greater efficiency (50% peak width reduction) were observed when comparing the proposed method with the reference-quality HPLC-MS/MS system, whose assay performance has been previously documented. The UHPLC-MS/MS method led to an overall improvement in the limits of detection (LOD) and quantification (LOQ) for all the phenolic compounds studied. The recoveries ranged between 68% and 100% in urine and 61% and 100% in plasma. The accuracy; intra- and interday precision; and stability met with the acceptance criteria of the AOAC International norms. Due to the improvements in the analytical method; the total phenolic metabolites detected in plasma and urine in the pilot intervention study were 3 times higher than those detected by HPLC-MS/MS. Comparing with traditional methods; which require longer time of analysis; the methodology described is suitable for the analysis of phenolic compounds in a large number of plasma and urine samples in a reduced time frame.

The sample locator: A federated search tool for biosamples and associated data in Europe using HL7 FHIR.

BACKGROUND: This study outlines the development of a highly interoperable federated IT infrastructure for academic biobanks located at the major university hospital sites across Germany. High-quality biosamples linked to clinical data, stored in biobanks are essential for biomedical research. We aimed to facilitate the findability of these biosamples and their associated data. Networks of biobanks provide access to even larger pools of samples and data even from rare diseases and small disease subgroups. The German Biobank Alliance (GBA) established in 2017 under the umbrella of the German Biobank Node (GBN), has taken on the mission of a federated data discovery service to make biosamples and associated data available to researchers across Germany and Europe. METHODS: In this context, we identified the requirements of researchers seeking human biosamples from biobanks and the needs of biobanks for data sovereignty over their samples and data in conjunction with the sample donor's consent. Based on this, we developed a highly interoperable federated IT infrastructure using standards such as Fast Healthcare Interoperability Resources (HL7 FHIR) and Clinical Quality Language (CQL). RESULTS: The infrastructure comprises two major components enabling federated real-time access to biosample metadata, allowing privacy-compliant queries and subsequent project requests. It has been in use since 2019, connecting 16 German academic biobanks, with additional European biobanks joining. In production since 2019 it has run 4941 queries over the span of one year on more than 900,000 biosamples collected from more than 170,000 donors. CONCLUSION: This infrastructure enhances the visibility and accessibility of biosamples for research, addressing the growing demand for human biosamples and associated data in research. It also underscores the need for improvements in processes beyond IT infrastructure, aiming to advance biomedical research and similar infrastructure development in other fields.

A High-Performance Liquid Chromatography with Electrochemical Detection Method Developed for the Sensitive Determination of Ascorbic Acid: Validation, Application, and Comparison with Titration, Spectrophotometric, and High-Performance Liquid Chromatography with Diode-Array Detection Methods.

L-ascorbic acid (vitamin C, VC), an essential nutrient obtained from the diet to maintain various vital signs for the human body, is a crucial indicator of food quality and nutritional value. Herein, high-performance liquid chromatography with electrochemical detection (HPLC-ECD) was developed and validated with the advantages of higher sensitivity, simpler operation processes, and more rapid detection in measuring VC levels in honey samples when compared with the common methods (titration, spectrophotometric, and HPLC-DAD methods). The results of the HPLC-ECD methodological validation showed that the limit of detection (LOD) was 0.0043 µg mL-1; the relative standard deviations (RSDs) of the intra- and inter-day values were between 2.51% and 5.15%, and the regression coefficient was >0.999 in the linear range of 0.1 to 20 µg mL-1. The validated HPLC-ECD method was also successfully utilized to evaluate the VC levels in different varieties of honey samples with various storage durations as well as in fruit and biological samples. This study provided a perspective for the further accurate determination of VC content in food and biological samples.

Medical application of laser-induced breakdown spectroscopy (LIBS) for assessment of trace element and mineral in biosamples: Laboratory and clinical validity of the method.

BACKGROUND: Biomedical application is based on the use of LIBS-derived data on chemical contents of tissues in diagnosis of diseases, forensic investigation, as well as a mechanism for providing online feedback for laser surgery. Although LIBS has certain advantages, the issue of correlation of LIBS-derived data on chemical element content in different human and animal tissues with other methods, and especially ICP-MS, remains pertinent. The objective of the present review was to discuss the application of laser-induced breakdown spectroscopy (LIBS) for elemental analysis of human biosamples or tissues from experimental models of human diseases. METHODS: A systematic search in the PubMed-Medline, Scopus, and Google Scholar databases using the terms laser-induced breakdown spectroscopy, LIBS, metals, trace elements, minerals, and names of particular chemical elements was performed up through 25 February, 2023. Of all extracted studies only those dealing with human subjects, human tissues, in vivo animal and in vitro cell line models of human diseases were reviewed in detail. RESULTS: The majority of studies revealed a wide number of metals and metalloids in solid tissues including teeth (As, Ag, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Ni, P, Pb, Sn, Sr, Ti, and Zn), bones (Al, Ba, Ca, Cd, Cr, K, Mg, Na, Pb, Sr), and nails (Al, As, Ca, Fe, K, Mg, Na, P, Pb, Si, Sr, Ti, Zn). At the same time, LIBS was also used for estimation of trace element and mineral content in hair (Ca, Cu, Fe, K, Mg, Na, Zn), blood (Al, Ca, Co, Cd, Cu, Fe, Mg, Mn, Ni, Pb, Si, Sn, Zn), cancer tissues (Ca, Cu, Fe, Mg, K, Na, Zn) and other tissues. Single studies revealed satisfactory correspondence between quantitative LIBS and ICP-OES/MS data on the level of As (81-93 %), Pb (94-98 %), Cd (50-94 %) in teeth, Cu (97-105 %), Fe (117 %), Zn (88-117 %) in hair, Ca (97-99 %), Zn (90-95 %), and Pb (61-82 %) in kidney stones. LIBS also estimated specific patterns of trace element and mineral content associated with multiple pathologies, including caries, cancer, skin disorders, and other systemic diseases including diabetes mellitus type 2, osteoporosis, hypothyroidism, etc. Data obtained from in situ tissue LIBS analysis were profitably used for discrimination between tissue types. CONCLUSIONS: Taken together, the existing data demonstrate the applicability of LIBS for medical studies, although further increase in its sensitivity, calibration range, cross-validation, and quality control is required.

Artificial intelligence-assisted smartphone-based sensing for bioanalytical applications: A review.

Artificial intelligence (AI) has received great attention since the concept was proposed, and it has developed rapidly in recent years with applications in many fields. Meanwhile, newer iterations of smartphone hardware technologies which have excellent data processing capabilities have leveraged on AI capabilities. Based on the desirability for portable detection, researchers have been investigating intelligent analysis by combining smartphones with AI algorithms. Various examples of the application of AI algorithm-based smartphone detection and analysis have been developed. In this review, we give an overview of this field, with a particular focus on bioanalytical detection applications. The applications are presented in terms of hardware design, software algorithms, and specific application areas. We also discuss the existing limitations of AI-based smartphone detection and analytical approaches, and their future prospects. The take-home message of our review is that the application of AI in the field of detection analysis is restricted by the limitations of the smartphone's hardware as well as the model building of AI for detection targets with insufficient data. Nevertheless, at this juncture, while bioanalytical diagnostics and health monitoring have set the pace for AI-based smartphone applicability, the future should see the technology making greater inroads into other fields. In relation to the latter, it is likely that the ordinary or average person will play a greater participatory role.

The Importance of Being FAIR and FAST - The Clinical Epidemiology and Study Platform of the German Network University Medicine (NUKLEUS).

The COVID-19 pandemic has urged the need to set up, conduct and analyze high-quality epidemiological studies within a very short time-scale to provide timely evidence on influential factors on the pandemic, e.g. COVID-19 severity and disease course. The comprehensive research infrastructure developed to run the German National Pandemic Cohort Network within the Network University Medicine is now maintained within a generic clinical epidemiology and study platform NUKLEUS. It is operated and subsequently extended to allow efficient joint planning, execution and evaluation of clinical and clinical-epidemiological studies. We aim to provide high-quality biomedical data and biospecimens and make its results widely available to the scientific community by implementing findability, accessibility, interoperability and reusability - i.e. following the FAIR guiding principles. Thus, NUKLEUS might serve as role model for FAIR and fast implementation of clinical epidemiological studies within the setting of University Medical Centers and beyond.

Challenges and Prospects of Patient-Derived Xenografts for Cancer Research.

We discuss the importance of the in vivo models in elucidating cancer biology, focusing on the patient-derived xenograft (PDX) models, which are classic and standard functional in vivo platforms for preclinical evaluation. We provide an overview of the most representative models, including cell-derived xenografts (CDX), tumor and metastatic cell-derived xenografts, and PDX models utilizing humanized mice (HM). The orthotopic models, which could reproduce the cancer environment and its progression, similar to human tumors, are particularly common. The standard procedures and rationales of gastric adenocarcinoma (GAC) orthotopic models are addressed. Despite the significant advantages of the PDX models, such as recapitulating key features of human tumors and enabling drug testing in the in vivo context, some challenges must be acknowledged, including loss of heterogeneity, selection bias, clonal evolution, stroma replacement, tumor micro-environment (TME) changes, host cell carryover and contaminations, human-to-host cell oncogenic transformation, human and host viral infections, as well as limitations for immunologic research. To compensate for these limitations, other mouse models, such as syngeneic and humanized mouse models, are currently utilized. Overall, the PDX models represent a powerful tool in cancer research, providing critical insights into tumor biology and potential therapeutic targets, but their limitations and challenges must be carefully considered for their effective use. Lastly, we present an intronic quantitative PCR (qPCR) method to authenticate, detect, and quantify human/murine cells in cell lines and PDX samples.