Ebook: Advances in Biomedical and Bioinformatics Engineering
Biomedicine and bioinformatics engineering are interdisciplinary fields combining expertise from biology, mathematics, chemistry, computer science, and engineering to develop technologies which will address major problems at the forefront of biomedical and bio-industrial research.
This book presents the proceedings of ICBBE 2023, the 3rd International Conference on Biomedicine and Bioinformatics Engineering, held as a hybrid event from 16-18 June 2023 in Nanjing, China. The aim of the conference was to create a forum for the multi-disciplinary discussion of recent developments in biomedicine and bioinformatics engineering. A total of 253 submissions were received for the conference, of which 92 were accepted after a thorough double-blind peer review. The book is divided into 3 parts, covering biomedical material and imaging technology application; cell biology and medical signal processing; and biomechanical modeling and drug analysis, and topics addressed include biomedical signal processing; medical information; bioinformatics and computational biology; medical imaging technology and its application; molecular biology; chemistry, pharmacology and toxicology.
Addressing a number of highly relevant aspects of biomedicine and bioinformatics engineering and emphasizing the multi-disciplinary aspects of the field, the selected contributions in this book will provide valuable guidance for future interdisciplinary developments, and will be of interest to all those working in biomedicine and bioinformatics engineering.
The purpose of the 2023, three-day 3rd International Conference on Biomedicine and Bioinformatics Engineering (ICBBE 2023), held in hybrid form from 16–18 June 2023 in Nanjing, China, was to create a timely forum for multi-disciplinary discussion related to recent developments on biomedicine and bioinformatics engineering.
As usual, the program of the meeting consisted mainly of keynote speeches and oral presentations, with the former including speeches delivered by five eminent professors from different countries and regions. The keynote speeches covered: i) Molecular techniques reveal more secrets of fermented foods; ii) Targeted pseudouridylation: A novel approach to suppressing nonsense mutations in disease genes; iii) Graph convolutional residual neural networks for the screening of multi-target anticancer compounds; iv) Development of a novel carbon-based coating for biomedical implants; and v) Nucleic acid thermodynamics and its applications in tumor screening. Among these, the critical vision of the first report provided answers to many questions with regard to understanding the role of molecular techniques in discovering the secrets of fermented foods, such as how to evaluate traditional fermented foods.
In the framework of experimental and theoretical approaches, the conference attracted about 120 delegates from all over the world, and addressed a number of highly relevant aspects of biomedicine and bioinformatics engineering. Covering biomedical signal processing and medical information, bioinformatics and computational biology, medical imaging technology and its application, molecular biology, chemistry, pharmacology and toxicology, among other topics, the selected contributions in this special issue provide guidance for future interdisciplinary developments, and emphasize the multi-scale aspects of biomedicine and bioinformatics.
We received various manuscripts for the invited papers and contributions presented at the conference. All of these have been peer reviewed and are collected in this volume. We would like to thank all the anonymous colleagues who acted as referees to assess the suitability of the various articles for publication and inclusion in the series Studies in Health Technology and Informatics from IOS Press. We are confident that the high quality of both the invited and contributed papers contained in these proceedings will be appreciated by the biomedical community.
We would like to express our thanks to all the authors for their time and genuine efforts, and to the reviewers for their fruitful comments during the preparation of this volume. We also acknowledge the support provided in various ways by Henan University and University of Rochester.
The Committee of ICBBE 2023
Epilepsy is a disease of the brain that can do severe damage for patient’s health. Due to the recurrent and unpredictable characteristics of epilepsy, it is of vital importance to develop reliable methods to predict seizures in advance. Nowadays, many researchers have developed deep learning (DL) or machine learning (ML) methods to predict epileptic seizures with electroencephalogram (EEG). But there are still many problems and challenges on the way towards a high-performance and generalized model. This study discussed and analyzed the current ML and DL techniques used in seizure prediction and summarized some challenges that remains to be solved, including the Inconsistency of the evaluation metrics, the imbalance and insufficiency of the available data and some limitations of current models. This study summarized the solutions that used to solve them and proposed some suggestions that can help improve the performance of the models. Furthermore, this review discussed some potential DL/ML methods that can be applied in the area of seizure prediction. This study aims to provide researchers with clear concepts in future works and proposed future directions.
Pieris Japonica, belonging to the Rhododendron family, is known for its anti-insect and analgesic properties. Despite previous research, the components and antioxidant activity of Pieris Japonica extract remain unclear. This study aims to identify the optimal extraction process for Pieris Japonica, determine its components, and evaluate its antioxidant capacity. An L9 (34) orthogonal method was employed to optimize the Pieris Japonica extraction process, with the polyphenol content serving as the extraction efficiency index. The extracted components were identified by high-performance liquid chromatography-mass spectrometry (HPLC/MS-MS). Antioxidant activity was assessed via the DPPH test, ABTS radical scavenging test, and FRAP reduction ability test. The optimal extraction process involved soaking Pieris Japonica powder in 60% ethanol with a weight-to-volume ratio of 1:20 (g/mL), followed by eight hours of reflux at 50°C. Under these conditions, the total polyphenol content was 11.2 ± 0.6 mg/g. HPLC/MS-MS revealed that flavonoids were the primary components in the Pieris Japonica extract. The FRAP method determined the total antioxidant capacity to be 1.00 ± 0.05 μmol/mL, while the DPPH method showed a radical scavenging rate of 42.21 ± 4.02%, and the ABTS method yielded a 85.74% scavenging rate, indicating a strong antioxidant activity. The primary components of Pieris Japonica extract were flavonoids, and the extracted plant material exhibited potent antioxidant activity.
This article focuses on an attempt to classify and recognize the characterized images of EEG signals directly. For EEG signals, the recognition and judgment of different signals has been the key direction of research. CNN (Convolutional Neural Network) models are usually used for recognition of EEG raw signals about movement and Imagery Dataset. However, the images of EEG raw signals are basically unreadable for researchers, so characterization is a common tool. However, direct recognition of the characterized images is a relatively empty area in the existing research because it requires much higher machine performance than the traditional raw signal recognition. However, feeding the extracted feature images into a CNN and training them can be an efficient and intuitive response to the potential of EEG for brain mapping. The main goal of this research is to examine the discriminative capabilities of traditional visual and image neural networks for pictures described by EEG data. This is not typical in contemporary brain-computer interface research. The direct recognition of the described photos uses a lot of GPU (graphics computing unit) resources, but for the characterized images are easier for people to read than the original images. This work indicates the viability of direct research on defined pictures and increases the application scenario of EEG signals.
Epilepsy is a long-standing illness defined by short episodes of aberrant brain activity caused by abrupt cell discharges. The illness is not communicable and might linger for a long period. Epilepsy affects roughly 50 million individuals worldwide, making it a prevalent neurological illness. Epilepsy monitoring is the most significant element of epilepsy diagnosis and also plays an important role in diagnosing the origin of epilepsy, assessing prognosis, and directing therapy. This paper details the principles and basic algorithmic models of commonly used neuroimaging techniques and describes the role of different monitoring techniques in the diagnosis and treatment of epilepsy. The paper compares the advantages and disadvantages of different monitoring techniques in their application and explores a comprehensive and less restrictive epilepsy monitoring protocol for readers and relevant researchers. Currently, electroencephalography (EEG) is the most common technique for monitoring epilepsy, and its most basic algorithmic models are independent component analysis (ICA) and discrete wavelet analysis (DWA), which are used for aspects such as noise removal and feature extraction. This article is dedicated to helping the reader or relevant researcher to gain a more comprehensive and systematic understanding of current neuroimaging techniques and medical devices. Furthermore, it seeks to forecast future research directions based on current difficulties in the area. The purpose of this study is to give a useful reference for future research in the field of epilepsy monitoring.
Insomnia is one of the most common sleep-related diseases. In traditional Chinese medicine, Flos daturae has been used as a traditional herbal totreatment of sizens of diseases. The research objective was to investigate the sedative and hypnotic effects of Flos Daturae. Kunming mice were divided into control group, Estazolam (positive drug, 0.0005 g/kg) group and Flos Daturae groups (0.01, 0.02, 0.04g/kg) with random, ig once a day for 7 days. The central sedative effect of flos Daturae on the spontaneous activity of mice was observed using the locomotive activity test, and the hypnotic effect of Flos Daturae was observed in mice using the direct sleep test and the sleep latency with synergistic supra-and sub-threshold doses of pentobarbital sodium. Flos Daturae (0.04g/kg) significantly inhibited mice locomotive activity (P<0.05) and had no direct sleeping effect (P>0.05), increased the number rate of sleep (P<0.05), and significantly shortening sleep latency (P<0.05), enhanced pentobarbital sodium-induced sleep. Flos Daturae possesses have sedative-hypnotic properties.
Sleep deprivation (SD) disrupted subcortical regions involved in emotion and attention. However, the age-related changes on subcortical brain morphology in processing of emotion and attention following SD remains unclear. Eighty participants consisting of 43 young people and 37 old people were included in this study. The volumetric analysis and vertex-wise shape analysis were employed to assess age-dependent structural abnormalities after SD. By volumetric analysis, we found significant main effect of deprivation with local atrophy in right amygdala. Shape analysis also showed the significant main effect of age in all subcortical structures. Moreover, the significant correlations between volume changes of bilateral amygdala and left thalamus after SD and scales scores refer to emotion processing and attention were observed in old adults. These findings indicated that SD altered gray matter volume and surface morphology of subcortical regions in old adults and suggested disrupted subcortical regions were associated with emotion and attention in old adults.
Spearmint essential oil and pure dew were used as research objects, the antioxidant capacity of spearmint was evaluated by measuring the scavenging capacity of superoxide anion radical and hydroxyl radical, providing technical support for the subsequent development and utilization of spearmint truffle and essential oil. The results showed that when the volume fraction (V/V) of spearmint essential oil was 1%, its antioxidant capacity was the strongest, and its scavenging rates of superoxide anion radical and hydroxyl radical were 50.94% and 90.11% respectively; When the volume fraction (V/V) of spearmint hydrosol was 100%, its antioxidant capacity was the strongest, and its scavenging rates of superoxide anion radical and hydroxyl radical were 47.65% and 45.60%.
Polypeptide drugs have become one of the most crucial tools in drug research and other related fields because of their high pharmacological activity, low dosage, low toxicity and side effects. However, the problems of poor metabolic stability, short half-value period and difficulty in penetration have greatly limit the development of new polypeptide drugs rendering the functional modification of peptides a crucial tool to polypeptide drugs. In this paper, we developed a new strategy for peptide functionalization through the usage of aspartic acid side chain as an endogenous directing group to realize polypeptide’s selective bond arylation.
Recombinant protein expression is a crucial technique in biology, with E. coli being the most widely used expression system. However, due to growth pressure, the expression of large molecular weight proteins in E. coli has remained a challenging task. SMGL-1, a newly discovered protein in C. elegans with Rabin 8 function, plays an important role in biology. To better understand the function of SMGL-1, we first predicted and analyzed its protein structure and properties using artificial intelligence. We then conducted studies on its expression and purification. Through optimization of IPTG concentration and expression strains, we successfully expressed SMGL-1 in E. coli, providing guidance for the expression of large proteins in E. coli. Furthermore, we explored the purification of SMGL-1 using GST affinity chromatography, Nickel affinity chromatography, and ammonium sulfate precipitation methods, laying the foundation for future purification work on SMGL-1.
Colony Collapse disorder (the CCD) is the term used to describe the global decline in bee populations. The research mission of this article is to identify which factors contribute to the CCD and understand how these factors contribute to the decline of bee populations, which may provide methods for restoring global bee populations. Two parts of the study will be mentioned in this article. The first half of our study was to understand such collective intelligence (and habits such as seasonal behavioral change) and use a mathematical model to simulate it. We then input the variables that we used to simulate honeybee collective intelligence into a time-dependent model to predict the population of a honey colony over time. In this model, we excluded the factors that might cause the CCD on purpose, so we could use it as a controlled set of honeybee natural population dynamics. We compared the results of this population model to experimental data we found, and they matched within certain degrees. The second half of our study was to perform a sensitivity analysis by introducing back the three factors that might cause the CCD to the population model including climate change, pesticides, and habitat destruction. The paper further discussed the strength and weaknesses of the mathematical model and used this model to predict how many honeybee hives were needed to support the pollination of a 20-acre parcel of land containing crops that benefit from pollination. Additionally, an infographic of our method was illustrated.
The growth and development of early mammalian embryos mainly take place in the fallopian tube, which not only provides nutrients for embryonic growth and development but also offers suitable mechanical conditions. The embryo culture system established in assisted reproductive technology mainly simulates the environment in which oocytes and embryos grow and develop in vivo. However, current in vitro embryo culture is mainly static and cannot completely mimic the mechanical environment in which embryos grow and develop in vivo. Therefore, to more accurately simulate the mechanical environment of embryos in the fallopian tube, we have developed a dynamic culture device to investigate the effects of mechanical stimulation on the in vitro maturation of immature oocytes and their parthenogenetic developmental potential. Immature mice oocytes were subjected to in vitro maturation by static culture and vibration (3 Hz, 6 Hz) with tilting for 15∼16 hours. The maturation of oocytes was observed after the culture period. The mature oocytes were activated by parthenogenesis and the rate of embryo compaction and formation of parthenogenetic blastocysts was analyzed. The results showed that using 3 Hz vibration and tilting can significantly improve the parthenogenetic development potential of immature mice oocytes.
In this study, the establishment of a colloidal gold immunochromatographic method for the detection of cypermethrin in tobacco was achieved by using colloidal gold immunochromatography: strong specificity and high sensitivity of cypermethrin semi-antigens and encapsulants were prepared during the study. The best colloidal gold solution was prepared by spectrophotometer and transmission electron microscope screening; the preparation process of gold-labeled antibodies was optimized, and finally the product of colloidal gold rapid detection test strips for cypermethrin was developed. The results of technical parameters and detection indexes showed that the detection limit of cypermethrin in tobacco was 1 mg/kg, and there was no cross-reaction with bifenthrin, cypermethrin, cyfluthrin and phenothrin, and the detection results of 30 tobacco samples were consistent with those of gas chromatography.
Aflatoxin is a highly toxic substance, of which aflatoxin B1 is the most toxic and carcinogenic among aflatoxins. In this paper, the team used homemade CdSe/Zns quantum dots to construct a fluorescent immunoprobe and all-antigen coupling with aflatoxin B1. It used a self-developed fluorescence intensity detector to detect aflatoxin B1 in five traditional Chinese medicines, namely, ginseng, Panax ginseng, Chuanxiong rhizome, rhubarb, and yam. The recoveries were 80.0–102.0%; the relative standard deviations (RSD)were from 2.4 to 9.2.
Biosynthesis of plant-derived natural products in the eukaryotic microbe Saccharomyces cerevisiae often faces the issue of the inefficient production due to the poor compatibility between the heterologous genes and chassis cells. In order to improve the biosynthetic efficiency of heterologous production of plant secondary metabolites in S. cerevisiae, people usually do metabolic engineering in and around the heterologous metabolic pathways based on researchers’ experience and mass of trials, which usually consumes a lot of manpower and financial resources. Herein, to further improve the heterologous production of oleanolic acid (OA), a pentacyclic triterpenoid in many plants with several promising pharmacological activities, in a genetically engineered, OA-producing strain S. cerevisiae OA07 effectively, a genome-scale metabolic model of the strain was developed, with the named as Yeast-OA07, and then OptKnock, a flux balance analysis-based pathway design algorithm with bilevel objectives, was utilized to develop in silico gene-knockout strategies to guide the molecular operations in S. cerevisiae OA07. Yeast8-OA07 contained 1133 genes, 2702 metabolites, and 3997 reactions. Five in silico gene-knockout strategies, which were expected to increase OA productivities, were obtained based on the metabolic flux analysis of Yeast8-OA07 through OptKnock. Afterwards, five mutant strains, named as LK1, LK2, LK3, LK4 and LK5, were constructed according to the in silico strategies. It was found that the mutant strain LK2, in which 2-amino-4-hydroxy-6-hydroxymethyl dihydropteridine diphosphokinase-encoding gene FOL1 and formate dehydrogenase-encoding gene FDH1 were deleted, had an OA yield of 125.04 mg·L-1, which was significantlyhigher than the original strain OA07 (89.50 mg·L-1), while the mutant strain LK5, which eliminated paminobenzoic acid synthase-encoding gene ABZ1 and glycine hydroxymethyl transferase-encoding gene SHM1, had an even higher OA yield of 207.37 mg·L-1. Nevertheless, strain LK6, which was developed by integrating the in silico gene-knockout strategies of LK2 and LK5, had a significant decrease of OA production than S. cerevisiae OA07, indicating that in silico knockout strategies do not fit to in vivo iteration directly. Our study provides a novel, efficient method to improve the heterologous production of plant metabolites in microbial cell factories.
In mammals, a limited number of proteases catalyze with acidic amino acids as substrates. At present, there are only three known proteases: CCPs, carboxypeptidase O (CPO), and aspartate acylase (ASPA). Human CPO is a digestive enzyme that prefers glutamate as a substrate. It locates to the apical membrane of intestinal epithelial and is glycosylated protein. CPO is difficult to purify as it is a GPI-anchored protein. To obtain purified CPO, a truncated form called hCPOΔC was designed, which removed the C-terminal sequence of hCPO and was followed by His tag. Firstly, the truncated variant hCPOΔC (residues 1-349) was cloned into pFastBac vector to construct bacmid. Then the verified bacmid was transfected into Sf9 cells for expression. After the protein was successfully expressed, cell medium was collected and incubated with Ni resins. The target protein was eluted by imidazole through affinity chromatography. A purification method of human CPO with deglutamylation activity was successfully established using insect cells expression system. Purified hCPOΔC could hydrolyze glutamate in polypeptides.
To study the effects of grape seed proanthocyanidins (GSP) combined with allicin on serum lipids level and vascular damage in a rat model of hyperlipidemia.
Materials and methods:
SD rats(male, 170-220 gn= 40) were randomized into five groups (n = 8/group): modelhigh fat and cholesterol diet; controlnormal diet; model+low-dose (GSP+allicin )(GSP 45mg/kg, allicin 30mg/kg, orally); model+high-dose (GSP+allicin) (GSP180mg/kg, allicin 90mg/kg, orally) and positive control (model+simvastatin (4 mg/kg)). Normal control group was fed conventionally, and remaining four groups were fed high cholesterol and fat food to replicate the high fat model. After 9 weeks, the normal control group continued to receive regular feeding, while the other groups continued to receive high-fat feeding. At the same time, model and normal control groups were given equal volume of physiological saline by gavage, and the other treatment groups began to receive corresponding drugs by gavage once a day. After 4 weeks, serum levels of total cholesterol (TC), triglyceride (TG), low density lipoprotein cholesterol (LDL-C) as well as high-density lipoprotein cholesterol (HDL-C) in rats were determined. And the body weight of rat, total antioxidant capacity (T-AOC), superoxide dismutase (SOD) and malondialdehyde (MDA)in serum were identified. The level of endothelin-1(ET-1) was quantitative analysis by ELISA assay.
In comparison to normal controls, the model group displayed a marked rise in body weight, an increment in serum concentrations of LDL-C, TG and TC, as well as a decline in HDL (P<0.01), demonstrating successful model replication; All doses of GSP in combination with allicin resulted in a reduction in TG, LDL-C, and TC and an enhancement in HDL-C in contrast to the model control (all P<0.05). High-dose (GSP+allicin ) decreased MDA, and increased T-AOC and SOD activity(all P<0.01). All doses of GSP combined with allicin decreased ET-1 (all P<0.05). In addition, the protective effect of GSP combined with allicin was dose-dependent.
Studies have shown that GSP combined with allicin can significantly improve blood lipids in hyperlipidemic rats, and this mechanism may be related to antioxidants and reduced endothelial damage.
Bio reciprocal symbiosis is very common in nature, such as soybeans providing food for rhizobia, which uses atmospheric nitrogen to synthesize nitrogen to provide nutrients to soybeans. This paper proposes an advanced Logistic model that adjusts to changes in precipitation and an environmental capacity parameter that varies with the level of symbiosis. The aim is to precisely depict the symbiotic relationship between plants and the interplay among symbiosis, competition, and independent growth of each population in the plant community, as precipitation changes by adapting finite difference method and tertiary Hermit interpolation. The model in this paper offers a comprehensive understanding of how plant populations interact with one another, providing valuable insights into the dynamics of plant growth and development. This paper finally finds that a combination of woody and herbaceous plants had the highest growth rate and total biomass, while herbaceous-only plants required 7 times longer to reach environmental capacity. This paper also reveals that irregular weather patterns, and different levels of species biomass can have different impacts on the recovery time of plant communities after drought or damage, and different types of pollution can have various effects on the community’s regeneration, while the effect of overgrazing is the smallest.
Chronic obstructive pulmonary disease (COPD) is closely related to the right ventricle and lung lobes. This study focuses on the segmentation of the right ventricle and lung lobes. We conducted experiments using the MMWHS and our lung lobe datasets and evaluated the segmentation using different training models. We observed that the multi-objective segmentation approach has advantages over single-objective segmentation in segmenting the right ventricle and lung lobes. For the segmentation of the right ventricle, the multi-objective segmentation approach yielded an improvement of 2.0% in the Dice coefficient and 2.5% in the Jaccard index compared to single-objective segmentation. For the segmentation of five lung lobes, the multi-objective segmentation outperformed the single-objective segmentation with Dice coefficient improvements of 1.4%, 1.0%, 1.5%, 0.7%, and 1.3%, respectively.
Gastric cancer is a malignant tumor with high incidence and death rate. Every year, Approximately 950,000 new cases of gastric cancer occur globally with nearly 700000 deaths,so gastric precancerous lesions(GPL) was crucial and important.At present, the effective diagnostic methods for gastric precancerous lesions are generally gastroscope and pathological changes of gastric mucosal, but those methods were invasive and would bring some pains to patients and not suitable for frequent and large-scale screening of gastric cancer or GPL.This study aimed to look for a sensitive,effective and non-invasive diagnostic method to improve the early diagnosis rate of GLP, and thereby reduce the incidence and death rate of gastric cancer.Tongue diagnosis is one of the classic diagnostic methods in traditional Chinese medicine(TCM).The tongue was closely related to the spleen and stomach.In the study, we collected 133 patients with chronic gastritis, including 53 cases in inflammatory group, 31 cases in atrophic group, and 49 cases in intestinal metaplasia group. and we analyzed the correlation between tongue,microbiota of tongue coating and clinical symptoms of GLP.The results showed that greasy coating was closely related to the intestinal metaphase of patients, indicating that greasy coating was closed link with intestinal metaphase phase of patients.Abundance of 209 genus were significant differences between greasy and non-greasy coating in intestinal metaphase phase of patients, Top10 were Streptococcus,norank_p__Saccharibacteria,Alloprevotella, Atopobium, Megasphaera, Gemella, Moraxella,unclassified_f__Prevotellaceae, Solobacterium and Stomatobaculum. Alloprevotella and Streptococcus were important genus markers and Alloprevotella was selected as a potential oral biomarker to diagnose intestinal metaphase phase of patients, the AUC value is 0.74.
In this study, monoclonal antibodies against oxamyl were prepared, and colloidal gold immunochromatography was used to design a rapid test strip product for the detection of oxamyl in tobacco with high specificity, accuracy and stability without cross-reactivity to commonly used tobacco fungicides based on the optimization of conditions such as pH value of diluent, diluent dosage, concentration of antibody marker, type of confining solution and complex solution. 5 The results of five samples of post-harvest ready-to-bake tobacco and first-harvest tobacco were consistent with the gas chromatographic method, which proved the reliability of the test strips. The limits of detection for the post-harvest and first-harvest tobacco samples were 0.1 mg/kg, and the test strips developed in this study are suitable for mass testing in tobacco laboratories with good application prospects because of their short detection time, simple pre-treatment and detection methods.
The rapid and accurate determination of triadimenol residues is of great significance. In this study, based on the advantages of high efficiency, rapidity, reliability, simplicity and low cost of immunology, a test strip product for the rapid detection of triadimenol residues in tobacco was designed based on the optimization of conditions such as pH and dosage of diluent, concentration of antibody stock solution, type of confining solution and complex solution, with high specificity, accuracy and The results of 20 samples of fresh and first roasted tobacco were all consistent with the method of gas chromatography, which proved the reliability of the test strips. The detection limit for fresh and roasted tobacco was 5 mg/kg, and the test strips developed in this study are suitable for mass testing of tobacco samples in tobacco-related laboratories because of their short detection time, simple pre-treatment and detection methods, and good application prospects.
In the acidic medium, hydrosulfuryl(-SH) in cysteine hydrochloride can reduce Fe3+ to Fe2+, then Fe2+ react with potassium ferricyanide to form KFe[Fe(CN)6](soluble Prussian blue). Prussian blue has a maximum absorption at 727 nm, Bill’s law is observed between mass concentration of cysteine hydrochloride and absorbance of Prussian blue, the content of cysteine hydrochloride is indirectly determinated by measuring the absorbance of Prussian blue. An accurate, simple, fast spectrophotometric method for the determination of cysteine hydrochloride content by ferric chloride-potassium ferricyanide has been established. The optimal determination conditions of cysteine hydrochloride content are explored. The cysteine hydrochloride content is determinate by this method.
In this study, we investigated the mechanism of action of COL3A1 in various types of cancers by bioinformatics analysis and designed some specific inhibitors aimed at the treatment of this gene. We found that COL3A1 was highly expressed in several cancer types and correlated with tumor progression and prognosis. Through systems biology analysis, we identified a central role for COL3A1 in cancer development, including cell proliferation, metastasis and invasion. We also used molecular dynamics simulations and drug screening techniques to design anticancer drugs with potential COL3A1 inhibitory functions. These results provide a strong rationale for the development and use of COL3A1 as a therapeutic target.