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Файл:Ординатура / Хирургия / Библиотека им академика М.И. Перельмана / Книга_5533_Библиотеки_им_академика_М_И_Перельмана.pdf
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- •Acknowledgements
- •Chapter 3
- •Chapter 4
- •Chapter 5
- •Chapter 6
- •Chapter 7
- •Editor biographies
- •Vivek Kumar Chaturvedi
- •Anurag Kumar Singh
- •Jay Singh
- •Dawesh Prakash Yadav
- •Short description about chapters
- •Chapter 1
- •Chapter 2
- •Chapter 8
- •Chapter 9
- •Chapter 10
- •Chapter 11
- •Chapter 12
- •List of contributors
- •Introduction
- •1.1 Introduction
- •1.2 Nanotechnology in medical science
- •1.2.1 Nanomaterials in drug delivery
- •1.2.2 Use of nanomaterials in designing diagnostic nanosensors
- •1.2.3 Nanomaterials as theranostics
- •1.3 Artificial intelligence in medical science
- •1.3.1 Machine learning in diagnostics
- •1.3.2 Natural language processing in healthcare
- •1.3.3 Predictive analytics in patient care
- •1.4.1 Nanoscience in controlled drug release in the GI tract
- •1.4.3 Nanotechnology in gastrointestinal endoscopy
- •1.4.4 Nano-biotechnology in gastrointestinal cancer
- •1.5 Role of nanoparticles for the treatment of gastric cancer
- •1.6 Artificial intelligence in hepatitis and chronic liver disease
- •1.7 Artificial intelligence applications for clinical decisions support
- •1.9 Nanomedicines for liver fibrosis
- •1.10 Artificial intelligence-based colonoscopy
- •1.12 Summary and conclusions
- •Acknowledgments
- •References
- •2.1 Introduction
- •2.2 Causes
- •2.3 Mechanism
- •2.4 Diagnosis
- •2.5 Prognosis
- •2.6 Present methods of detection
- •2.7 Biosensors
- •2.7.1 Components of biosensors
- •2.7.2 Types of biosensors
- •2.7.3 Enzyme based biosensors
- •2.7.5 Immunosensors
- •2.7.6 Microbial biosensors
- •2.7.7 DNA-based biosensors
- •2.7.8 Phage sensors
- •2.7.9 Optical biosensors
- •2.7.10 Cantilever-based biosensors
- •2.7.11 Bio-MEMS
- •2.8 Physical biosensors
- •2.8.1 Thermometric biosensors
- •2.8.2 Acoustic biosensors
- •2.8.3 Magnetic biosensors
- •2.8.4 Wearable skins as biosensors
- •2.9 Electrochemical biosensors
- •2.9.1 Potentiometric
- •2.9.2 Coulometry methods
- •2.9.3 Conductometry methods
- •2.9.4 Potentiometric titration
- •2.10 Materials for biosensors
- •2.10.1 Nanomaterials for biosensors
- •2.10.2 Gastrointestinal diseases (GIDs) biosensor
- •2.11 Summary and future perspectives
- •3.1 Introduction
- •3.2 Challenges in drug delivery to the GI tract
- •3.2.1 Residence time
- •3.2.4 Metabolism in the GI tract
- •3.3 Role of nanoscience in drug delivery
- •3.3.2 Targeted drug delivery
- •3.3.3 Increased bioavailability
- •3.3.4 Reduced toxicity and side effects
- •3.3.5 Imaging and diagnostic capabilities
- •3.3.6 Drug designing
- •3.3.7 Delivery system
- •3.4 Methods of nanomedicine formulation
- •3.5 Drug release strategies
- •3.5.1 Active targeting strategies
- •3.5.2 Stimuli-based delivery strategy
- •3.5.3 pH-dependent drug release
- •3.5.4 ROS-dependent drug release
- •3.5.5 Time-dependent dosage forms
- •3.5.6 Gastro retentive strategies
- •3.5.7 Photothermal and photodynamic approach
- •3.6 Types of nanoparticles in drug delivery
- •3.6.1 Liposomes
- •3.8 Application of AI in GI disease
- •3.9 Future perspectives and challenges
- •3.6.2 Polymeric nanoparticles
- •3.6.3 Metallic nanoparticles
- •3.6.4 Quantum dots
- •3.7 Approved nanomedicines
- •3.9.1 Diagnostics
- •3.9.2 Individualized treatment
- •3.9.3 Proactive patient monitoring
- •3.9.4 Decision support systems
- •3.9.5 Biomarker discovery and therapeutic development
- •3.9.6 Patient outcomes and quality of life
- •3.9.7 Regulation and ethical issues
- •3.10 Conclusion
- •References
- •4.1 Introduction
- •4.2 Challenges and barriers in drug delivery
- •4.3 Drugs used in IBD
- •4.4 Novel drug delivery system for inflammatory bowel disease
- •4.4.1 Vesicular delivery system
- •4.4.2 Nanoparticle drug delivery system
- •4.5 pH-dependent nano-delivery systems
- •4.6 Inorganic nanoparticles
- •4.7 Prodrugs based
- •4.8 Hybrid drug delivery systems
- •4.9 Enteric coated formulations
- •4.10 RNA interference-based novel drug delivery
- •4.11 Toxicity profiling of IBD
- •4.11.1 Corticosteroids
- •4.11.2 Immuno modulators
- •4.11.3 Biologic therapies
- •4.11.4 JAK inhibitors
- •4.11.5 Immune dysregulation in IBD
- •4.11.6 Gastrointestinal effects
- •4.11.7 Antibiotics
- •4.11.8 Cyclosporine
- •4.11.10 Surgery-related complications
- •4.11.11 Increased risk of colorectal cancer
- •4.12 Current prospective of IBD
- •4.12.1 Personalized medicine and immunological therapies
- •4.12.2 Disease monitoring and surgical advances
- •4.12.3 Development of IL-6 signaling inhibitors
- •4.12.4 Genome-wide association studies (GWAS)
- •4.12.5 Rare variant analysis
- •4.12.6 Functional genomics and gene expression studies
- •4.12.7 Therapeutic targets
- •4.12.8 Gene-environment interactions
- •4.13 Future prospective of IBD
- •4.13.2 Microparticles-based delivery systems
- •4.13.3 Biological therapies
- •4.13.4 Combination therapies
- •4.14 Conclusion
- •References
- •5.1 Introduction
- •5.2 Nanotechnology
- •5.3 Nanoparticles
- •5.4 Classification of nanoparticles
- •5.4.1 Polymer-based nanoparticles
- •5.4.2 Solid nanoparticles
- •5.4.3 Carbon-based nanoparticles
- •5.4.4 Lipid-based nanoparticles
- •5.4.5 Nanoemulsions
- •5.4.6 Nanoparticles in biomedical applications
- •5.4.7 Characteristics of nanoparticles
- •5.4.8 Characterization of nanoparticles
- •5.5 Intestinal endoscopy
- •5.6 Medical nanotechnology
- •5.6.1 Diagnosis
- •5.6.2 Nanotechnology in the early diagnosis
- •5.6.3 Theragnostic
- •5.6.4 Tissue engineering
- •5.6.5 Targeted imaging and therapeutic in colorectal cancer
- •5.6.6 Gene therapy delivery
- •5.6.7 Colitis therapy
- •5.6.8 Oral delivery of vaccines
- •5.6.9 Mitigation
- •5.6.10 Role in targeted drug delivery
- •5.7 Role of nanotechnology in intestinal tract
- •5.8 Nanotechnological aids
- •5.8.1 Nanopowder
- •5.8.2 Plastic stents
- •5.8.3 Capsule endoscopy
- •5.9 Quality control of nanotechnology
- •5.10 Artificial intelligence in gastrointestinal endoscopy
- •5.11 Future perspectives
- •5.12 Limitations of nanotechnology
- •5.13 Conclusion
- •6.1 Introduction
- •6.2 Global burden of gastric cancer
- •6.3 Gastric cancer risk factors
- •6.3.1 Infection with Helicobacter pylori
- •6.3.2 Age and sex
- •6.3.3 Cigarette smoking
- •6.3.4 Obesity and metabolic dysfunction
- •6.3.5 Dietary factors
- •6.3.6 Alcohol use
- •6.3.7 Medications
- •6.3.8 Host genetics
- •6.4 Other risk factors
- •6.4.1 Epstein–Barr virus infection
- •6.4.2 Autoimmune disorders
- •6.4.3 Ménétrier’s disease
- •6.5 Nanotechnology in cancer diagnostic and therapeutics
- •6.6 Nanotechnology and gastric cancer diagnostic
- •6.6.1 Fluorescence imaging and gastric cancer detection
- •6.6.2 Photoacoustic imaging and gastric cancer detection
- •6.6.3 Computed tomography and gastric cancer detection
- •6.6.4 Magnetic resonance imaging and gastric cancer detection
- •6.6.5 Multimodal imaging and gastric cancer detection
- •6.7 Nanotechnology and gastric cancer management
- •6.7.1 Nanomaterial and chemotherapy
- •6.7.2 Nanomedicine and radiotherapy
- •6.7.3 Phototherapy and gastric cancer detection
- •6.7.4 Combination therapies and theranostics for gastric cancer detection
- •6.8 Challenges and prospectives
- •Acknowledgments
- •References
- •7.1 Introduction
- •7.2 Nanoparticles as drug delivery systems
- •7.2.1 Advantages of nanoparticles for drug delivery
- •7.2.2 Types of nanoparticles used in gastric cancer treatment
- •7.2.3 Targeted drug delivery to gastric cancer cells
- •7.3 Nanoparticles for imaging and diagnosis
- •7.3.1 Nanoparticles in gastric cancer imaging
- •7.3.2 Contrast agents and theranostic nanoparticles
- •7.3.3 Molecular imaging and targeting approaches
- •7.4 Therapeutic applications of nanoparticles in gastric cancer
- •7.4.1 Chemotherapy with nanoparticle formulations
- •7.4.2 Photothermal and photodynamic therapy
- •7.4.3 Immunotherapy and nanoparticles
- •7.4.4 RNA interference (RNAi) and gene therapy
- •7.5 Nanoparticles for combination therapy
- •7.5.1 Synergistic effects of nanoparticle-based combination therapies
- •7.5.2 Sequential and simultaneous delivery of therapeutics
- •7.6 Challenges and limitations of nanoparticle-based therapy
- •7.6.1 Biocompatibility and toxicity concerns
- •7.6.2 Nanoparticle clearance and stability
- •7.6.3 Regulatory aspects and clinical translation
- •7.7.1 Preclinical studies and animal models
- •7.7.2 Clinical trials and human studies
- •7.7.3 Promising results and future directions
- •7.8 Nanoparticles in personalized medicine for gastric cancer
- •7.8.1 Biomarker-driven nanoparticle therapies
- •7.8.2 Individualized treatment approaches
- •7.9 Nanoparticle-based theranostics for gastric cancer
- •7.9.1 Diagnostic and therapeutic integration
- •7.9.2 Multifunctional nanoparticle platforms
- •7.10 Future perspectives and concluding remarks
- •Acknowledgments
- •References
- •8.1 Introduction
- •8.2 Artificial intelligence role in hepatitis disease
- •8.3 Artificial intelligence role in non-alcoholic fatty liver disease
- •8.4 Artificial intelligence role in hepatocellular carcinoma
- •8.5 Conclusion
- •References
- •9.1 Introduction
- •9.2 Overview of clinical decision support
- •9.2.2 Medical imaging and diagnostic services
- •9.2.3 Virtual patient care
- •9.2.4 Patient safety
- •9.2.5 Diagnostic support
- •9.2.6 Medical research and drug discovery
- •9.2.7 Rehabilitation
- •9.2.8 Administrative applications
- •9.3 Types of AI algorithms in CDS
- •9.3.1 Machine learning algorithms
- •9.3.2 Bayesian Gaussian regression
- •9.4 Supervised learning
- •9.4.1 Diagnosis and treatment prediction
- •9.5 Unsupervised learning
- •9.6 Deep learning and neural networks
- •9.7 Natural language processing (NLP) techniques
- •9.7.1 Convolutional neural networks (CNNs) for medical image analysis
- •9.7.2 Recurrent neural networks (RNNs) for signal processing
- •9.8 Current AI-based clinical data support system
- •9.9 Challenges and considerations
- •9.9.1 Current AI-based CDS systems
- •9.10 Regulatory and ethical issues (HIPAA, GDPR, etc)
- •9.11 Challenges for clinical translation
- •References
- •9.12 Obstacles, restrictions, and missing knowledge
- •9.13 Future trends
- •9.14 Future trends and developments
- •9.14.1 Advancements in AI algorithms
- •9.15 Expansion to point-of-care devices
- •9.16 AI-driven drug discovery
- •9.17 AI in public health and epidemiology
- •9.18 Conclusion
- •10.1 Introduction
- •10.2 Developing history of AI
- •10.3 AI’s role in the early detection of GC
- •10.3.1 Screening of GC by AI
- •10.3.2 Accuracy of sampling from early endoscopic diagnosis
- •10.3.3 Digital pathological diagnosis
- •10.4 Role of AI from endoscopic diagnosis to treatment
- •10.5 Artificial intelligence in surgery
- •10.6 Molecules and genes
- •10.7 AI models’ function in prognosis prediction
- •10.7.1 Metastasis and staging prediction
- •10.7.2 AI aided treatment decisions
- •10.7.3 Clinical massive data analysis and prognostic prediction
- •10.8 Survival analysis
- •10.9 Conclusion and future prospects
- •References
- •11.1 Introduction
- •11.2 Stages of liver fibrosis
- •11.3 Etiology of liver fibrosis
- •11.3.1 Chronic viral hepatitis
- •11.3.2 Alcohol-related liver disease (ALD)
- •11.4 Pathogenesis
- •11.5 Symptoms
- •11.6 Diagnosis
- •11.7 Invasive approach
- •11.7.1 Liver biopsy
- •11.7.2 Limitations of liver biopsy
- •11.8 Non-invasive approach
- •11.8.1 Ultrasonographic based
- •11.9 Non-surgical tests
- •11.9.1 Serum biomarkers
- •11.10 Treatment
- •11.11 Limitations of antifibrotic therapy
- •11.12 Role of nanomedicines in the treatment of hepatic fibrosis
- •11.13 Type of nanoparticles currently in use for LF
- •11.13.1 Phytochemical compound for LF
- •11.13.3 siRNA derived NPs
- •11.14 HSC targeted nanoparticle delivery
- •11.15 Advantage of nanomedicine for LF
- •11.15.2 Enhanced drug delivery
- •11.15.4 Reduced adverse effects
- •11.15.5 Improved pharmacokinetic properties
- •11.16 Challenges of nm for LF
- •11.17 Future of nm in the treatment of LF
- •References
- •12.1 Introduction
- •12.2 Medical requirement for colonoscopy
- •12.3 Limitation of colonoscopy
- •12.4 Advancement of colonoscopy
- •12.5 High-definition and ultra-high-definition imaging technology
- •12.6 Computed tomography
- •12.7 Artificial intelligence and machine learning
- •12.8 Advancement in patient experience
- •12.9 Capsule endoscopy
- •12.10 Simulated detection systems
- •12.11 Improved training and workshop programs
- •12.12 Future of colonoscopy
- •12.13 Multi-spectral imaging
- •12.14 Machine learning algorithms integration
- •12.15 Robotic-assisted colonoscopy
- •12.16 Virtual colonoscopy
- •12.17 Tailoring colonoscopy screening
- •12.18 Patient-compatible techniques
- •12.19 Remote monitoring and consultations
- •12.20 Alternative bowel preparation methods
- •12.21 Preventive measures enhancement
- •12.22 Conclusion
- •References

Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
6.4 Other risk factors
Around the world, 10% of gastric cancers are caused by other risk factors. The
primary risk factor is highlighted in the following (figure 6.3).
6.4.1 Epstein–Barr virus infection
Approximately 8% of the 5081 gastric cancer patients in a global pooled study of 15
cross-sectional studies harbored Epstein–Barr virus (EBV) in tumor tissue.
However, there is currently insufficient epidemiological evidence to conclusively
link EBV infections to the development of gastric cancer [25].
6.4.2 Autoimmune disorders
As a result of autoimmune gastritis, which also goes by the names intestinal
metaplasia and spasmolytic polypeptide-expression metaplasia, the parietal and
principal cells of the gastric mucosa are altered by cells that resemble intestinal cells
that secrete mucus [26]. The oxyntic mucosa in the stomach body fully atrophies as a
result of these processes, making it more likely that gastric cancer would occur [27].
Figure 6.3. Applications of nanomaterial in cancer diagnosis and therapeutics.
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
Intestinal metaplasia patients had a 0.72 per thousand person-years incidence risk of
gastric adenocarcinoma, whereas intestinal metaplasia plus low-grade dysplasia
patients had a 7.7 per thousand person-years incidence rate. Women are more than
twice as likely to have autoimmune gastritis than men [28], and in more than 10% of
males it is linked to the condition developing into gastric carcinoid tumors or gastric
adenocarcinomas [29].
6.4.3 Ménétrier’s disease
The oxyntic gland mucosa atrophy, tortuous and cystic gland enlargement, smooth
muscle hyperplasia, and foveolar hyperplasia are all signs of Ménétrier’s disease.
There is no information on the prevalence or incidence of this uncommon acquired
stomach illness called hypertrophy gastropathy [30]. The cause of childhood
Ménétrier disease is unknown, despite a link between the illness and CMV infection
being found in a small cohort of patients. In addition, it has been suggested that
H. pylori infection may increase the likelihood of developing Ménétrier disease [31].
6.5 Nanotechnology in cancer diagnostic and therapeutics
Different types of nanomaterials use in diagnostic and therapeutics mentioned in
figures 6.3. Since numerous types of nanoparticles are being employed for molecular
imaging, the use of nanoparticles in cancer diagnosis and monitoring has attracted a
lot of attention. Recent advancements in cancer research and diagnostics have made
them important due to their benefits, including their small size, good biocompatibility,
and high atomic number. A few examples of nanoparticles with distinctive structural,
optical, or magnetic features that are used in the diagnosis of cancer are iron oxide
nanocrystals, semiconductors, and quantum dots [32]. Nanoparticles can be marked
or coated with very specific malignancies using a variety of anti-tumor medicines and
biomolecules, such as peptides, antibodies, or other compounds. It may be possible to
identify cancer in its earliest stages by using nanoparticle imaging of tumor tissue for
cancer diagnostics or early cancer cell identification and screening. The development
of immunological superparamagnetic iron oxide nanoparticles (SPIONs) that can be
employed in MRI imaging and target certain cancer cell types has enabled the
detection of metastases in lung cancer [33, 34]. Due to their great specificity and lack
of known adverse effects, recent investigations have demonstrated that SPIONs are
suitable building blocks for aerosols in MRI imaging of lung cancer [35]. Regarding
their potential use in cancer treatment, numerous nanotechnology tools, including
dendrimers, nanotubes, and liposomes, each with their own distinct properties, have
been studied. For instance, nanotubes, which are carbon cylinders formed of benzene
rings, can enter the cell through passive diffusion and endocytosis [36]. Additionally,
their dynamic chemical characteristics enable the adjustment of their solubility,
enabling the drugs held inside the tubes to be released at a predetermined rate.
Instead, liposomes, which can form lipid bilayers, are promising delivery methods for
combination drugs because they can transport both hydrophilic and hydrophobic
substances simultaneously [37].
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
The most recent classes of dendrimers have also been developed to carry a
therapeutic medication, a diagnostic agent, and an active targeting molecule all in
one dendrimer therapy. They are characterized by their inner core and tree-like
branches that offer enormous amounts of surface area for drug attachment [37, 38].
In order to achieve targeted drug administration, it is clear that nanotechnology,
which involves the generation of numerous nanoparticles with different shapes and
behaviors, can open up a vast range of options. Numerous techniques have been
used to demonstrate how nanotechnology can be used to cure cancer. They include,
but are not limited to: photothermal cancer cell elimination, gene therapy, and
intracellular drug delivery for therapeutic purposes [39, 40]. Angiogenesis is used in
the delivery of intracellular chemotherapy. Angiogenesis, the formation of new
blood vessels used by tumor cells to expand by taking nutrients and oxygen from
surrounding cells, is one of the traits of cancer. Angiogenesis blood vessels form
unevenly and are more leaky than typical healthy vasculature as a result of their fast,
uncontrolled growth [41]. These vessels have pores that are between a few hundred
nanometers to several microns in size, as opposed to ordinary vessels, which only
have pores that are 2–6 nm in size. Nanoparticles’ diameter, which ranges from 10 to
300 nm, makes them the ideal size for entering tumor cells’ blood arteries without
significantly damaging healthy tissues [41]. This Trojan horse approach offers an
attractive way to reduce harm to neighboring cells. Another approach is photothermal ablation makes use of the difference between the average apoptotic
temperature of cancer cells, which occurs at about 42 °C, and normal cells, which
occur at about 46 °C. Gold nanoparticles that are made to only excite at particular
light frequencies have been used in multiple studies to target and kill specific tumor
cells while sparing the surrounding healthy cells [42]. Nanotechnology has the ability
to overcome the shortcomings of current methods, such as reducing the health risks
associated with treatments depending on viruses. Researchers successfully developed
nanoparticles using a synthetic delivery method and small interfering ribonucleic
acid (siRNA) to reduce the expression of RRM2, a known anticancer target [43].
6.6 Nanotechnology and gastric cancer diagnostic
In clinical settings, the detection of stomach cancer typically involves the use of
conventional imaging techniques such CT, PET, MRI, PET-CT and SPECT. The
only imaging modality, poorly targeted biodistribution, fast clearance, and other
unfavorable side effects are all drawbacks of contrast agents. It is clear from the
various types of nanoparticles that have built-in characteristics or functional
modifications that new, better imaging techniques are being created for the diagnosis
of gastric cancer. They most typically have real-time imaging, specific tumor
accumulation and local metastasis, a low tumor-background ratio, high sensitivity,
and high resolution [44].
6.6.1 Fluorescence imaging and gastric cancer detection
Fluorescence imaging, a beautiful imaging method, has wonderful benefits including
real-time mode, quick imaging, adaptable equipment, great safety, and low cost [45].
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
The visible spectrum is inferior to the 700–1300 nm near-infrared (NIR) window.
Hemoglobin and other endogenous substances greatly absorb and scatter imaging
light with wavelengths below 700 nm in human tissues. The lipid and water
absorption hinders imaging at wavelengths above 1300 nm [46]. The FDA-approved
NIR fluorophore indocyanine green (ICG) stands out among the others because of
its higher quantum yield and much lower tissue absorption [47]. The use of in vivo
imaging in the human body is being adopted for the first time [48]. Hironori et al
investigated the theranostic potential of the ICG-loaded lactosome (ICGm) nanoparticle using a murine draining lymph node metastasis model for gastric cancer [49].
The presence of metastatic lymph nodes was found to be reported in the ICGmtreated mice but not in the ICG-treated mice using in vivo imaging. Wang et al
developed unique ICG conjugated gold nanoshells that efficiently gathered in
peritoneal metastasis models as well as subcutaneously transplanted models [50].
For surgical excision and preoperative guiding, near-infrared imaging provided
sufficient optical contrast and accurate detection of visible and microtumor lesions
(3 mm). The FDA-approved 5-aminolevulinic acid (5-ALA) and other cyanine-based
fluorophores have been created for the diagnosis of gastric cancer, however, there are
still certain inherent limitations that need to be taken into account. Due to the
fluorophores’ visible emission profile, imaging light scattering and tissue penetration
are still anticipated to be enhanced. In actuality, the NIR window has further divisions
called NIR I and NIR II. Because the quantity of scattering is inversely linked to the
wavelength of light, NIR II fluorophores are of interest to researchers [51, 52].
Additionally, tissue autofluorescence, scattering, and photon attenuation all drasti-
cally degrade with increasing imaging wavelengths [53]. Despite the fact that many
NIR II nanoparticles have been investigated for tumor imaging, their usage for
stomach malignancies is now quite limited [54].
6.6.2 Photoacoustic imaging and gastric cancer detection
One of the promising imaging modalities that can produce incredibly accurate and
detailed 2D and 3D images is photoacoustic (PA) imaging. When biological tissue is
subjected to non-ionizing pulse lasers directly for PA imaging, exogenous nanoparticles or endogenous molecules like hemoglobin absorb the energy. When energy
is transformed into heat and causes thermal expansion, which is related to the
physiological properties of the tissue, an ultrasound transducer measures the
resulting ultrasonic waves. In the end, these outcomes are assessed and recreated
as PA photos [55]. Animal models with gastric cancer were subjected to carbon
nanotubes coated with RGD-conjugated silica by Wang et al. Results from an
optoacoustic imaging system demonstrated that the stomach cancer cells were
successfully targeted by the nanotubes in vivo and that the nude model produced
powerful PA imaging [56].
Another set of researchers described the use of iron oxide nanoparticles coated
with anti-HER2 moieties for PA tumor imaging. The nanoparticles could be used as
a PA contrast agent for the imaging of gastric cancer since they specifically identified
HER2-positive tumors in PA imaging experiments [57]. According to Liang et al
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
targeted ligands were CD44v6 monoclonal antibodies coupled to gold nanostarbased PEGylated nanoprobes. PA imaging shown that the nanoprobes could
effectively target the vascular system of gastric cancer 4 h following injection [58].
6.6.3 Computed tomography and gastric cancer detection
A common non-radioactive diagnostic for detecting malignancies is CT. Although
secure and cutting-edge imaging technologies have been created for clinical usage, the
main drawbacks of inadequate targeting and poor sensitivity continue to exist.
Nanotechnology is recognized as a magnificent development approach. In a clinical
experiment, Zhang et al employed targeted nanoparticle contrast agents and contrastenhanced CT to find early-stage stomach cancer [59]. Contrast-enhanced CT with
targeted nanoparticles enhances not only CT accuracy but also diagnostic confidence
in people with suspected stomach cancer as compared to a single CT detection. It was
discovered that esophageal carcinoma had similar consequences [60].
6.6.4 Magnetic resonance imaging and gastric cancer detection
The majority of the inorganic nanoparticles used in magnetic resonance imaging
(MRI), another popular method of detection, are superparamagnetic iron oxide
nanoparticles (SPIONs) [61]. A molecular probe with MRI and optical dualmodality was disclosed by Yan et al [62]. Cyclopeptide GX1 and the near-infrared
fluorescent dye Cy5.5 were attached to the nano-Fe
that had been altered by
3O4
polyethylene glycol (PEG) to create the nanoprobe. Iron oxide-gold nanoclusters
(Fe
@Au@-CD) are coated with -CD to provide a biological nanoprobe with
3O4
great biocompatibility [63].
This nanoprobe displayed red fluorescence in the cells and could be selectively
picked up by the MGC-803 gastric cancer cells. Although various types of nanoparticles have been investigated for MRI, it is important to keep in mind SPIONs’
drawbacks, such as their genotoxicity [64].
6.6.5 Multimodal imaging and gastric cancer detection
The aforementioned imaging modalities undoubtedly improved the ability to detect
gastric cancer, however, each imaging strategy was constrained by its own drawbacks. A single imaging method cannot, however, provide all the information
needed. Clinicians can access diverse, complementary, and integrated diagnosis
signals by combining several imaging strategies, and they can simultaneously
highlight the benefits of various tools while also minimizing any potential drawbacks. For example, despite having a low depth of detection, real-time modalities
like fluorescence imaging and PA imaging can export high contrast pictures for
intraoperative use. Nanoparticles are highly suited to act as the carrier in multimodal imaging because of their capacity to transport a variety of payloads. There
have been numerous investigations into nanoparticles with the potential for multimodal imaging [65, 66]. False signal reduction is possible with SPECT/CT with dual
validation as compared to a single imaging equipment. A unique targeted nuclear
imaging agent called DTPA/glucose-regulated protein 78 (GRP78BP) displayed
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
greater radioactive signals than non-targeted 111In-labeled micelles [67]. Micelles
conjugated with 111In and DTPA/GRP78BP showed a 93% efficiency. Additional
perfluoropentane (PFP)-labeled copper-64 (64Cu) nanodroplets with phospholipid
shells were examined for PET/CT and ultrasonic imaging [68].
These nanoparticles help in diagnosis by combining the technology and science
with multiple imaging modalities. Additionally, mesoporous silica gap-enhanced
Raman tags (Gd-GERTs) loaded with gadolinium are designed specifically for
preoperative and intra-operative imaging. High MRI T1 relaxivity, multi-mode
imaging performance, and remarkable surface-enhanced Raman spectroscopy
(SERS) signal with extraordinary dispersity and stability were also displayed [69].
6.7 Nanotechnology and gastric cancer management
6.7.1 Nanomaterial and chemotherapy
Nanomedicines are practical for the delivery of chemotherapeutics due to benefits
such as reliable biocompatibility and biodegradability. Due to its severe lipophilicity
and inability to be supplied via injection, PTX is only used as a second-line
treatment for locally advanced or metastatic gastric cancer. The primary components of abraxane are albumin nanoparticles and PTX with a particle size of about
130 mm. The nanoformulation concurrently reduces toxicity while maintaining the
therapeutic benefits. Additionally, transendothelial transport via albumin-binding
protein causes nanoparticles to accumulate more in tumor tissue in addition to the
enhanced permeability and retention effect [70]. Abraxane underwent clinical trials
to determine its efficacy and safety in treating gastric cancer, which showed
promising action and moderate toxicity. Lung, pancreatic, and metastasized breast
cancer are among the tumors for which the FDA has approved the use of Abraxane
[71]. Shi et al introduced a brand-new form of PTX nanoparticle with RGD
decoration and a disulfide connection, giving the polymer-PTX an active target and
environment response capability. The nanoparticles effectively suppressed the
growth of the tumor by releasing PTX as demonstrated by in vivo studies, and
with little adverse effect [72].
Tetrandrine (Tet), an alkaloid of the bisbenzylisoquinoline class, has been shown
to increase the anticancer activity of PTX in cases of stomach cancer. By encasing
Tet inside self-assembling PTX nanofibers, Li et al reported novel PTX and Tet coloaded nanofibers. The self-assembled nanofibers showed an improvement in the
therapeutic efficiency and side effects of PTX in treating gastric cancer, as well as an
increase in mitochondrial apoptosis levels and a substantial anti-tumor effect both
in vitro and in vivo [73].
One of the first-line therapies for gastric cancer is 5-fluorouracil (5-FU), a
fluorinated pyrimidine uracil analog. Its cytotoxicity is caused by the binding and
inhibition of thymidylate synthase [74]. In the studies by Elisabete et al a monoclonal antibody against sialyl-Lewis A, a glycan that encourages hematogenous
metastasis, was used to functionalize the surface of nanoparticles co-loaded with 5FU and PTX. As a result, a nano-vehicle that successfully delivered the therapeutic
medications 5-FU and PTX to metastatic gastric cancer cells was developed. It is
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
hoped that the use of nanoparticles will lead to the development of better therapies
for the treatment of gastric associated cancer.
Additionally, doxorubicin (DOX) and irinotecan both have single-agent activity
and have been widely used in clinical practice. In slightly acidic conditions, gastric
cancer cells demonstrated higher absorption and greater toxicity to nanoparticles
than single components of an irinotecan hydrochloride curcumin nano system [75].
For chemo-photothermal synergistic therapy, Zhou and his team encapsulated
DOX in a pH-sensitive, long-circulation nanoparticle [76]. Yang and his associates
showed how to treat gastric tumors that overexpress Her2 and CD44 using dualtargeting hybrid nanoparticles [77]. Delivering the nanoparticle to stomach cancer
cells preferentially is made possible by the anti-Her2 peptide and hyaluronic acid on
the surface of NPs that carry the SN38 agent. Treatment for stomach cancer is still
hampered by the persistence of chemotherapy resistance, which results in tumor
recurrence and chemotherapy failure [78].
Because of their unique physicochemical features resulting from their nanoscale
size, nanoparticles have the potential to be used in the battle against drug resistance
since they can pass through cell membranes and concentrate more in tumor areas
than traditional drugs [79]. TiO
nanoparticles were used by Azimee et al to enhance
2
the therapeutic effects of 5-FU in human AGS gastric cells [80].
TiO
nanoparticles increase the generation of ROS, inhibit autophagy flux, and
2
raise the level of ROS, which induce 5-FU improvement to have cytotoxic and
apoptotic effects on AGS cells. Yang et al demonstrated a different strategy to deal
with medication resistance by preventing the expression of P-glycoprotein (Pgp). To
deliver the anticancer medicine DOX to multidrug resistant gastric cancer cells
(SCG 7901/VCR), the SPION functionalized with chemosensitizing chemical
XMD8-92 may be employed. Both in vitro and in vivo, the nanoparticles showed
greater tumor suppression power than DOX therapy alone. Utilizing nanoparticles
could pave the way for a new treatment for chemotherapy resistance in stomach
cancer [81].
6.7.2 Nanomedicine and radiotherapy
High-energy radiation therapy that produces ionizing radiation has the potential to
kill tumor cells, stop the growth of tiny tumors, and extend local lymph nodes [82].
Nanoparticles contributed significantly to radiotherapy together with advancements in tumor imaging. When used as radiosensitizers, nanoparticles could provide
more therapeutic advantages than radiation alone [83].
Using chitosan-modified gold nanoparticles (CS-GNPs), Zhang et al studied how
gastric cancer cells respond to x-ray irradiation. The biocompatibility of CS-GNPs
was shown by MTT findings, and survival rates under radiation compared to
radiation alone showed an enhancement in cell radiation therapeutic sensitivity,
suggesting a possible use in radiation therapy for gastric cancer [84]. Similar
techniques were employed by Huang et al to produce biocompatible Ag microspheres using BSA (bovine serum albumin). Compared to Ag microspheres,
individual nanoscale Ag assemblies showed higher radiation effects on gastric
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
cancer cells [85]. Due to their high atomic number and electron density, gold and
silver nanoparticles have been used frequently as radiation sensitizers to improve
energy deposition into tumor areas and boost the effectiveness of radiotherapy [86].
Adjuvant chemotherapy and radiation therapy appeared to be an effective
treatment for advanced gastric cancer that possessed the characteristic of a strong
propensity for invasion and metastasis. A significant amount of general toxicity,
however, has slowed down the use of traditional chemo-radiotherapy in clinical
settings. Because of this, new therapeutic approaches were created in response to the
need for treatments with increased efficacy and fewer adverse effects [87].
6.7.3 Phototherapy and gastric cancer detection
The two primary forms of phototherapy, or photo-triggered therapeutic modalities,
are photodynamic treatment (PDT) and photothermal therapy (PTT), which have
the advantages of being repeatable, non-invasive, and selective. Additionally, in
recent years, photoimmunotherapy and photo-induced chemotherapy have garnered
a lot of interest [88, 89].
Nanoparticles may be the finest carriers to carry photosensitizers implanted in
tumor sites and enhance their biodistribution due to the hydrophobic nature of the
majority of photosensitizers, which limits their systemic administration.
Additionally, light may be easily adjusted and focused to offer precise treatment
while causing the least amount of damage to healthy tissue. A common photosensitizer, IR780 produces ROS and heat in response to exposure to light. However,
because of its excellent photosensitivity and hydrophobicity, IR780 cannot be
dissolved in water and must instead be encapsulated. In order to encapsulate
IR780, Deng et al used an amphiphilic macromolecular molecule (sericin-cholesterol) with folic acid as the target ligand. The solubility and photo-stability of IR780
were significantly improved by using an amphiphilic macromolecule that could selfassemble into stable micelles [90]. After being exposed to an 808 nm laser, these
nanoparticles aggregated in tumor tissues and produced ROS, metformin, and
IR780. Consequently, complex I in the mitochondrial electron transport chain can
be directly inhibited by metformin. Thus, cell respiration prevented tumor hypoxia
and improved PDT and PTT for stomach cancer. These studies showed that
phototherapy for stomach cancer can be promoted by using nanoparticles to deliver
photosensitizers. Other forms of nanomaterials, including CuS, graphene, and gold
nanoparticles, were created for photothermal therapy in addition to organic nanoparticles [51, 91, 92]. The tumor-targeting nanoparticles developed by Yang et al
include 17AAG, iRGD, and carboxyl-functionalized W18O49 nanoparticles. The
W18O49 nanoparticles had outstanding PTT and CT imaging contrast, and
17AAG’s ability to avoid thermoresistance and block the heat-shock response
enhanced the therapeutic effects of PTT and decreased the likelihood of tumor
recurrence. W18O49 nanoparticles can greatly increase PTT in vivo and in vitro,
target gastric cancer, and offer dual-modality imaging [66].
Gold nanoparticles are particularly efficient in converting optical energy to heat.
Mesoporous carbon–gold hybrid nanoprobes for real-time imaging, PTT/PDT, and
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
nanozyme oxidative treatment were described by Zhang et al. Due to the wide
surface area and multiple –COOH groups of the carbon–gold hybrid nanoparticles,
surface chemical modification with different targeting molecules was possible. This
resulted in outstanding tumor-targeting efficacy, longer tumor retention, and a
helpful therapeutic impact for gastric tumor [93].
6.7.4 Combination therapies and theranostics for gastric cancer detection
Recent years have seen the emergence of novel therapeutics that support anticancer
treatments, including targeted, gene and immune-therapy. Although most patients
do not benefit, the FDA and the European Union have approved ramucirumab and
tratuzumab for targeted therapy against advanced gastric cancer [94].
In clinical research, the addition of trastuzumab to chemotherapy dramatically
boosted overall survival, suggesting that combination therapies may be the most
effective option for better outcomes. In addition, the use of gene therapy in
conjunction with anticancer drugs has enhanced the effectiveness of treatment [95].
A collagen membrane with an aptamer-siRNA chimera/5-FU combination, for
instance, may precisely latch on to gastric cancer cells, transport 5-FU to the desired
location, and silence a drug-resistant gene [96]. Another fascinating potential
therapeutic approach is the combination of immunotherapy and chemotherapy.
In clinical gastric cancer, TfR1 binding with H-ferritin nanocarrier may be a novel
approach that enhances treatment effectiveness and prognostic prognosis [97]. A
PTT/PDT combination with chemotherapy and adjuvant immunotherapy was also
created, strengthening the immune responses against cancer [98].
In addition to multimodal imaging and combination therapy, theranostic nanoparticles, which combine co-delivery of an imaging unit and a therapeutic unit, are
being used in an increasing number of nano-based designs. Prior to the development
of theranostic nanoparticles, doctors could only detect tumors either before or after
therapeutic interventions. Additionally, a number of nanoparticle frameworks with
integrated imaging capabilities, such as SPIONs for MRI and gold nanoparticles for
CT, make excellent candidates for the development of theranostic systems. And
most photosensitizers, notably IR780 and chlorin E6, exhibited both tumor toxicity
and imaging capabilities. This is due to the fact that photosensitizers can act as a
vector to produce heat and/or ROS in addition to excitation of fluorescence and
absorption of NIR. The other kind of theranostic nanoparticles combine the
payloads for diagnosis and treatment into a single nanoparticle. However, more
intricate quality control comes at a higher price. Theranostic systems based on
nanotechnology have been created and have shown promise in the treatment of
gastric cancer [99].
6.8 Challenges and prospectives
There are only a few FDA-approved nanomedicines for treating gastric cancer out
of the more than 50 that have been approved [100]. The complexity of patients’
aberrant molecular traits in gastric cancer patients continues to be a major barrier.
The gastric cancers papillary, tubular, mucinous, and poorly cohesive carcinomas
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Nanobiotechnology and Artificial Intelligence in Gastrointestinal Diseases
were classified by the World Health Organization. But there is currently no defined
system for classifying biologics, and the clinical applicability is quite modest [101].
Additionally, it is still unknown how gastric cancer develops on a molecular level.
Theranostic performance is believed to be aided by knowledge of molecular
pathways and the discovery of potent biomarkers for gastric cancer. The limitations
of the accessible nanoparticles are mentioned, along with the aforementioned uses.
NIR dyes were not as effective because of insufficient tissue penetration. Quantum
dots can detect a signal at a deeper level, however, safety and biocompatibility are
concerns. To clear the way for improved performance, some strategies have been put
out. Donor–acceptor–donor (DAD) dyes and NIR-II imaging probes are combined
to form multiplexed NIR-II probes, which have been described by Rui et al as an
excellent imaging approach for directing sentinel lymph node excision in a variety of
cancer models [102]. On the one hand, tissue autofluorescence and scattering are
diminished by longer wavelength NIR-II fluorescence imaging. Bright-light dualNIR II imaging-guided surgery has greater clinical potential and is more practical.
Another fluorescence dual-mode imaging agent has been developed to diagnose
lymph node tumor metastasis without the use of a microscope. However, there are
not many pertinent studies focused on gastric cancer [103].
Although there are numerous studies in this area, the majority of them involve
in vivo research. The biodistribution and targeting capabilities of nanoparticles may
differ between preclinical investigations and clinical practice due to changes in the
body’s metabolisms, the characteristics of the nanoparticles, and the significant
degree of tumor heterogeneity. For instance, proteins, such as antibodies, may be
taken up by nanoparticle surfaces and form the protein corona [104]. The targeting
and anticancer actions in vivo are impacted by denatured proteins in the corona of
nanoparticles. These problems are supposed to be addressed by biomimetic nanoparticles [105]. Natural nanoscale membrane vesicles are found outside of cells.
Tumor image monitoring and therapy are made possible by extracellular vesicles
with special physiological and biochemical characteristics, such as prolonged
retention circulation duration, higher tissue and organ targeting specificity, and
improved cytoplasmic delivery effectiveness [106]. Nanoparticles with membrane
coatings have also shown to be efficient nanocarriers. For minimizing the off-target
effect and extending in vivo circulation, the gold standard is to combine biomimetic
nanoplatforms with RGD peptide or HER-2 antibodies [107]. Multifunctional
nanoparticles now have the ability to target and improve image contrast. But
more functionality necessitates more expensive and time-consuming synthetic
processes. Additionally, there are more complicated in vivo behavior and impacts,
as well as greater regulatory obstacles [108].
Gastric cancer is one of the most common malignant tumors in the world, and
nanotechnology offers a practical option for early detection and therapy that is
guided by imaging. Nanoparticle design and synthesis involved a number of
materials with various imaging and therapeutic properties, and the results were
encouraging. A thorough knowledge and rigorous approach may stimulate rational
planning and translational medical research, even though there are still some
obstacles to be addressed and a long way to go before preclinical investigations
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