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Zhiming Guo
School of Food and Biological Engineering, Jiangsu University, Zhenjiang, 212013, China

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Journal article
Published: 23 August 2021 in Food Control
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Lead ion (Pb2+) is a main heavy metal in food that causes heavy teratogenicity and carcinogenicity. In this study, a rapid and sensitive SERS method for detecting Pb2+ in food was established by aptamer regulating gold nanoparticles reduction. The reduction of HAuCl4 catalyzed by H2O2 is a slow process, and graphene oxide (GO) has excellent catalytic performance for the reaction, which enabled the system to generate gold nanoparticles (AuNPs) with high Raman activity. When the aptamer was introduced into the system, its binding with GO reduced the reaction speed. Upon adding Pb2+ to the system, the aptamer preferentially combined with Pb2+ and GO was released to accelerate the AuNPs production. The concentration of the AuNPs was proportional to the intensity of the added Raman signal molecule 4-MBA and the main Raman peak of Pb2+ appeared at 1595.80 cm−1. The ability of a novel aptamer (M4-16) and traditional aptamers (T30695, TBA) for Pb2+ determination was compared, and the concentration of the aptamer, HAuCl4 and heating time were optimized to build optimal detection system. After several pretreatment of the original SERS spectroscopy, combined with the comparison of various models, the first-order derivative preprocessing combined with competitive adaptive reweighted sampling model achieved the best performance (Rc = 0.9966, Rp = 0.9972), the detection limit for Pb2+ was 0.1 μg L−1. The combination of SERS technology and chemometrics is a promising method that could be used to achieve rapid and highly sensitive detection of Pb2+ in food.

ACS Style

Zhiming Guo; Ping Chen; Limei Yin; Min Zuo; Quansheng Chen; Hesham R. El-Seedi; Xiaobo Zou. Determination of lead in food by surface-enhanced Raman spectroscopy with aptamer regulating gold nanoparticles reduction. Food Control 2021, 132, 108498 .

AMA Style

Zhiming Guo, Ping Chen, Limei Yin, Min Zuo, Quansheng Chen, Hesham R. El-Seedi, Xiaobo Zou. Determination of lead in food by surface-enhanced Raman spectroscopy with aptamer regulating gold nanoparticles reduction. Food Control. 2021; 132 ():108498.

Chicago/Turabian Style

Zhiming Guo; Ping Chen; Limei Yin; Min Zuo; Quansheng Chen; Hesham R. El-Seedi; Xiaobo Zou. 2021. "Determination of lead in food by surface-enhanced Raman spectroscopy with aptamer regulating gold nanoparticles reduction." Food Control 132, no. : 108498.

Journal article
Published: 19 August 2021 in LWT
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Patulin (PAT) and alternariol (AOH) are the main mycotoxin contaminants in fruits and their products, which have great toxic effects on human body due to their teratogenicity and carcinogenicity. This study proposed a surface enhanced Raman spectroscopy (SERS) technology combining chemometrics and coffee-ring effect to build high-throughput label-free detection models for PAT and AOH. A stable coffee ring structure was built by optimizing the drying temperature and droplet volume. Comparing the partial least squares (PLS) models grounded on variables selection method, the best performance was obtained by using synergy interval (Si) and genetic algorithm (GA) for PAT (Rc = 0.9905, Rp = 0.9759) and AOH (Rc = 0.9829, Rp = 0.9808), respectively. The limits of detection (LOD) for PAT and AOH were as low as 1 μg L−1, and the recovery rates were 92.80%–114.83% with relative standard deviation (RSD) ≤ 4.86 for PAT and 82.06%–108.13% with RSD ≤2.28% for AOH. The SERS technology combined with chemometrics and coffee-ring effect holds promise for high-throughput label-free detection of PAT and AOH in fruits and their products.

ACS Style

Zhiming Guo; Ping Chen; Mingming Wang; Min Zuo; Hesham R. El-Seedi; Quansheng Chen; Jiyong Shi; Xiaobo Zou. Rapid enrichment detection of patulin and alternariol in apple using surface enhanced Raman spectroscopy with coffee-ring effect. LWT 2021, 152, 112333 .

AMA Style

Zhiming Guo, Ping Chen, Mingming Wang, Min Zuo, Hesham R. El-Seedi, Quansheng Chen, Jiyong Shi, Xiaobo Zou. Rapid enrichment detection of patulin and alternariol in apple using surface enhanced Raman spectroscopy with coffee-ring effect. LWT. 2021; 152 ():112333.

Chicago/Turabian Style

Zhiming Guo; Ping Chen; Mingming Wang; Min Zuo; Hesham R. El-Seedi; Quansheng Chen; Jiyong Shi; Xiaobo Zou. 2021. "Rapid enrichment detection of patulin and alternariol in apple using surface enhanced Raman spectroscopy with coffee-ring effect." LWT 152, no. : 112333.

Review
Published: 31 July 2021 in Foods
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Propolis, a resin produced by honeybees, has long been used as a dietary supplement and folk remedy, and more recent preclinical investigations have demonstrated a large spectrum of potential therapeutic bioactivities, including antioxidant, antibacterial, anti-inflammatory, neuroprotective, immunomodulatory, anticancer, and antiviral properties. As an antiviral agent, propolis and various constituents have shown promising preclinical efficacy against adenoviruses, influenza viruses, respiratory tract viruses, herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2), human immunodeficiency virus (HIV), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Over 300 chemical components have been identified in propolis, including terpenes, flavonoids, and phenolic acids, with the specific constituent profile varying widely according to geographic origin and regional flora. Propolis and its constituents have demonstrated potential efficacy against SARS-CoV-2 by modulating multiple pathogenic and antiviral pathways. Molecular docking studies have demonstrated high binding affinities of propolis derivatives to multiple SARS-CoV-2 proteins, including 3C-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent RNA polymerase (RdRp), the receptor-binding domain (RBD) of the spike protein (S-protein), and helicase (NSP13), as well as to the viral target angiotensin-converting enzyme 2 (ACE2). Among these compounds, retusapurpurin A has shown high affinity to 3CLpro (ΔG = −9.4 kcal/mol), RdRp (−7.5), RBD (−7.2), NSP13 (−9.4), and ACE2 (−10.4) and potent inhibition of viral entry by forming hydrogen bonds with amino acid residues within viral and human target proteins. In addition, propolis-derived baccharin demonstrated even higher binding affinity towards PLpro (−8.2 kcal/mol). Measures of drug-likeness parameters, including metabolism, distribution, absorption, excretion, and toxicity (ADMET) characteristics, also support the potential of propolis as an effective agent to combat COVID-19.

ACS Style

Nermeen Yosri; Aida A. Abd El-Wahed; Reem Ghonaim; Omar M. Khattab; Aya Sabry; Mahmoud A. A. Ibrahim; Mahmoud F. Moustafa; Zhiming Guo; Xiaobo Zou; Ahmed F. M. Algethami; Saad H. D. Masry; Mohamed F. AlAjmi; Hanan S. Afifi; Shaden A. M. Khalifa; Hesham R. El-Seedi. Anti-Viral and Immunomodulatory Properties of Propolis: Chemical Diversity, Pharmacological Properties, Preclinical and Clinical Applications, and In Silico Potential against SARS-CoV-2. Foods 2021, 10, 1776 .

AMA Style

Nermeen Yosri, Aida A. Abd El-Wahed, Reem Ghonaim, Omar M. Khattab, Aya Sabry, Mahmoud A. A. Ibrahim, Mahmoud F. Moustafa, Zhiming Guo, Xiaobo Zou, Ahmed F. M. Algethami, Saad H. D. Masry, Mohamed F. AlAjmi, Hanan S. Afifi, Shaden A. M. Khalifa, Hesham R. El-Seedi. Anti-Viral and Immunomodulatory Properties of Propolis: Chemical Diversity, Pharmacological Properties, Preclinical and Clinical Applications, and In Silico Potential against SARS-CoV-2. Foods. 2021; 10 (8):1776.

Chicago/Turabian Style

Nermeen Yosri; Aida A. Abd El-Wahed; Reem Ghonaim; Omar M. Khattab; Aya Sabry; Mahmoud A. A. Ibrahim; Mahmoud F. Moustafa; Zhiming Guo; Xiaobo Zou; Ahmed F. M. Algethami; Saad H. D. Masry; Mohamed F. AlAjmi; Hanan S. Afifi; Shaden A. M. Khalifa; Hesham R. El-Seedi. 2021. "Anti-Viral and Immunomodulatory Properties of Propolis: Chemical Diversity, Pharmacological Properties, Preclinical and Clinical Applications, and In Silico Potential against SARS-CoV-2." Foods 10, no. 8: 1776.

Research article
Published: 14 June 2021 in Journal of Food Quality
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Improvement of the sense of gain as an internal driving force is the key factor to improve the training quality of graduate students in food science. Utilizing Jiangsu University graduate students majoring in food science as research samples, this study analyzed the present situation of the “sense of gain” demand. We analyzed the reasonable appeals of graduate students during their study based on fully respecting and advocating students’ right of speech, listened to their opinions and suggestions on higher education, analyzed the main contradictions, and further put forward a series of countermeasures. For improving the graduate students’ sense of gain during the period of study, it is necessary to improve the training quality from the following five aspects: constructing high-quality courses, cultivating people’s responsibilities, implementing “soft elimination” of training links, carrying out diversified extracurricular activities, and developing comprehensive quality. This research is significant in improving the training quality of food science graduate students.

ACS Style

Youling Wan; Zhiming Guo. Improving the Sense of Gain of Graduate Students in Food Science. Journal of Food Quality 2021, 2021, 1 -7.

AMA Style

Youling Wan, Zhiming Guo. Improving the Sense of Gain of Graduate Students in Food Science. Journal of Food Quality. 2021; 2021 ():1-7.

Chicago/Turabian Style

Youling Wan; Zhiming Guo. 2021. "Improving the Sense of Gain of Graduate Students in Food Science." Journal of Food Quality 2021, no. : 1-7.

Journal article
Published: 11 June 2021 in Food Control
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Arsenic (As) is one of the toxic, persistent, and lethal heavy metalloids and requires rapid, less costly, and sensitive detection methods. This study proposed a label-free cuprous oxide/silver (Cu2O/Ag) surface-enhanced Raman scattering (SERS) nanoprobe to detect total As in tea. Different total As spiked tea concentrations were mixed with the Cu2O/Ag SERS nanoprobe for the SERS detection. Quantitative models were established for predicting the total As in tea by comparatively applying chemometric algorithms. Amongst the algorithms, competitive adaptive reweighted sampling partial least squares (CARS-PLS) optimized the most effective spectral variables to predict the total As in tea efficiently. The CARS-PLS gave the highest correlation coefficient value (Rp = 0.9935), very low root means square error (RMSEP = 0.0496 μg g−1) in the prediction set and recorded the highest RPD value of 8.819. The proposed nanoprobe achieved a lower detection limit (0.00561 μg g−1), excellent selectivity, satisfactory reproducibility, and stability. No significant difference was recorded when the performance of the Cu2O/Ag total As SERS sensor was compared with the inductively coupled plasma mass spectrometry (ICP-MS) method. Therefore, this developed Cu2O/Ag coupled chemometrics SERS sensing method could be used to efficiently determine, quantify, and predict total As in tea to promote monitoring of heavy metal contaminants.

ACS Style

Alberta Osei Barimah; Zhiming Guo; Akwasi A. Agyekum; Chuang Guo; Ping Chen; Hesham R. El-Seedi; Xiaobo Zou; Quansheng Chen. Sensitive label-free Cu2O/Ag fused chemometrics SERS sensor for rapid detection of total arsenic in tea. Food Control 2021, 130, 108341 .

AMA Style

Alberta Osei Barimah, Zhiming Guo, Akwasi A. Agyekum, Chuang Guo, Ping Chen, Hesham R. El-Seedi, Xiaobo Zou, Quansheng Chen. Sensitive label-free Cu2O/Ag fused chemometrics SERS sensor for rapid detection of total arsenic in tea. Food Control. 2021; 130 ():108341.

Chicago/Turabian Style

Alberta Osei Barimah; Zhiming Guo; Akwasi A. Agyekum; Chuang Guo; Ping Chen; Hesham R. El-Seedi; Xiaobo Zou; Quansheng Chen. 2021. "Sensitive label-free Cu2O/Ag fused chemometrics SERS sensor for rapid detection of total arsenic in tea." Food Control 130, no. : 108341.

Review
Published: 10 June 2021 in Food Reviews International
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Heavy metals accumulating in the human body produce physiological toxicity by interfering with the transport of human proteins and enzymes. Heavy metals detection is significant for food safety assurance. This review focuses on recent advances of heavy metals detection of food and agricultural products by surface-enhanced Raman spectroscopy (SERS). The article covers the SERS basic principles and advances in heavy metals detection, including mercury, arsenic, cadmium, lead, chromium among others. Insights in the potential of combining chemometrics and multivariate analysis with SERS and the exploration of novel SERS substrate platforms from both macro and micro scale are discussed. Finally, future application of SERS in heavy metal detection are prospected. SERS is a powerful and promising technique offering the advantages of simple sampling, rapid data collection and non-invasiveness. The findings of this study can allow better understanding of the heavy metals’ occurrence and the possibility of its detection using SERS.

ACS Style

Zhiming Guo; Ping Chen; Nermeen Yosri; Quansheng Chen; Hesham R. Elseedi; Xiaobo Zou; Hongshun Yang. Detection of Heavy Metals in Food and Agricultural Products by Surface-enhanced Raman Spectroscopy. Food Reviews International 2021, 1 -22.

AMA Style

Zhiming Guo, Ping Chen, Nermeen Yosri, Quansheng Chen, Hesham R. Elseedi, Xiaobo Zou, Hongshun Yang. Detection of Heavy Metals in Food and Agricultural Products by Surface-enhanced Raman Spectroscopy. Food Reviews International. 2021; ():1-22.

Chicago/Turabian Style

Zhiming Guo; Ping Chen; Nermeen Yosri; Quansheng Chen; Hesham R. Elseedi; Xiaobo Zou; Hongshun Yang. 2021. "Detection of Heavy Metals in Food and Agricultural Products by Surface-enhanced Raman Spectroscopy." Food Reviews International , no. : 1-22.

Review
Published: 31 May 2021 in Nutrients
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Bee pollen is a combination of plant pollen and honeybee secretions and nectar. The Bible and ancient Egyptian texts are documented proof of its use in public health. It is considered a gold mine of nutrition due to its active components that have significant health and medicinal properties. Bee pollen contains bioactive compounds including proteins, amino acids, lipids, carbohydrates, minerals, vitamins, and polyphenols. The vital components of bee pollen enhance different bodily functions and offer protection against many diseases. It is generally marketed as a functional food with affordable and inexpensive prices with promising future industrial potentials. This review highlights the dietary properties of bee pollen and its influence on human health, and its applications in the food industry.

ACS Style

Shaden Khalifa; Mohamed Elashal; Nermeen Yosri; Ming Du; Syed Musharraf; Lutfun Nahar; Satyajit Sarker; Zhiming Guo; Wei Cao; Xiaobo Zou; Aida Abd El-Wahed; Jianbo Xiao; Hany Omar; Mohamed-Elamir Hegazy; Hesham El-Seedi. Bee Pollen: Current Status and Therapeutic Potential. Nutrients 2021, 13, 1876 .

AMA Style

Shaden Khalifa, Mohamed Elashal, Nermeen Yosri, Ming Du, Syed Musharraf, Lutfun Nahar, Satyajit Sarker, Zhiming Guo, Wei Cao, Xiaobo Zou, Aida Abd El-Wahed, Jianbo Xiao, Hany Omar, Mohamed-Elamir Hegazy, Hesham El-Seedi. Bee Pollen: Current Status and Therapeutic Potential. Nutrients. 2021; 13 (6):1876.

Chicago/Turabian Style

Shaden Khalifa; Mohamed Elashal; Nermeen Yosri; Ming Du; Syed Musharraf; Lutfun Nahar; Satyajit Sarker; Zhiming Guo; Wei Cao; Xiaobo Zou; Aida Abd El-Wahed; Jianbo Xiao; Hany Omar; Mohamed-Elamir Hegazy; Hesham El-Seedi. 2021. "Bee Pollen: Current Status and Therapeutic Potential." Nutrients 13, no. 6: 1876.

Review
Published: 24 April 2021 in Marine Drugs
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Cyanobacteria are photosynthetic prokaryotic organisms which represent a significant source of novel, bioactive, secondary metabolites, and they are also considered an abundant source of bioactive compounds/drugs, such as dolastatin, cryptophycin 1, curacin toyocamycin, phytoalexin, cyanovirin-N and phycocyanin. Some of these compounds have displayed promising results in successful Phase I, II, III and IV clinical trials. Additionally, the cyanobacterial compounds applied to medical research have demonstrated an exciting future with great potential to be developed into new medicines. Most of these compounds have exhibited strong pharmacological activities, including neurotoxicity, cytotoxicity and antiviral activity against HCMV, HSV-1, HHV-6 and HIV-1, so these metabolites could be promising candidates for COVID-19 treatment. Therefore, the effective large-scale production of natural marine products through synthesis is important for resolving the existing issues associated with chemical isolation, including small yields, and may be necessary to better investigate their biological activities. Herein, we highlight the total synthesized and stereochemical determinations of the cyanobacterial bioactive compounds. Furthermore, this review primarily focuses on the biotechnological applications of cyanobacteria, including applications as cosmetics, food supplements, and the nanobiotechnological applications of cyanobacterial bioactive compounds in potential medicinal applications for various human diseases are discussed.

ACS Style

Shaden Khalifa; Eslam Shedid; Essa Saied; Amir Jassbi; Fatemeh Jamebozorgi; Mostafa Rateb; Ming Du; Mohamed Abdel-Daim; Guo-Yin Kai; Montaser Al-Hammady; Jianbo Xiao; Zhiming Guo; Hesham El-Seedi. Cyanobacteria—From the Oceans to the Potential Biotechnological and Biomedical Applications. Marine Drugs 2021, 19, 241 .

AMA Style

Shaden Khalifa, Eslam Shedid, Essa Saied, Amir Jassbi, Fatemeh Jamebozorgi, Mostafa Rateb, Ming Du, Mohamed Abdel-Daim, Guo-Yin Kai, Montaser Al-Hammady, Jianbo Xiao, Zhiming Guo, Hesham El-Seedi. Cyanobacteria—From the Oceans to the Potential Biotechnological and Biomedical Applications. Marine Drugs. 2021; 19 (5):241.

Chicago/Turabian Style

Shaden Khalifa; Eslam Shedid; Essa Saied; Amir Jassbi; Fatemeh Jamebozorgi; Mostafa Rateb; Ming Du; Mohamed Abdel-Daim; Guo-Yin Kai; Montaser Al-Hammady; Jianbo Xiao; Zhiming Guo; Hesham El-Seedi. 2021. "Cyanobacteria—From the Oceans to the Potential Biotechnological and Biomedical Applications." Marine Drugs 19, no. 5: 241.

Journal article
Published: 08 March 2021 in Food Chemistry
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Matcha tea is rich in taste and bioactive constituents, quality evaluation of matcha tea is important to ensure flavor and efficacy. Near-infrared spectroscopy (NIR) in combination with variable selection algorithms was proposed as a fast and non-destructive method for the quality evaluation of matcha tea. Total polyphenols (TP), free amino acids (FAA), and polyphenols-to-amino acids ratio (TP/FAA) were assessed as the taste quality indicators. Successive projections algorithm (SPA), genetic algorithm (GA), and simulated annealing (SA) were subsequently developed from the synergy interval partial least squares (SiPLS). The overall results revealed that SiPLS-SPA and SiPLS-SA models combined with NIR exhibited higher predictive capabilities for the effective determination of TP, FAA and TP/FAA with correlation coefficient in the prediction set (Rp) of Rp > 0.97, Rp > 0.98 and Rp > 0.98 respectively. Therefore, this simple and efficient technique could be practically exploited for tea quality control assessment.

ACS Style

Zhiming Guo; Alberta Osei Barimah; Limei Yin; Quansheng Chen; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou. Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy. Food Chemistry 2021, 353, 129372 .

AMA Style

Zhiming Guo, Alberta Osei Barimah, Limei Yin, Quansheng Chen, Jiyong Shi, Hesham R. El-Seedi, Xiaobo Zou. Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy. Food Chemistry. 2021; 353 ():129372.

Chicago/Turabian Style

Zhiming Guo; Alberta Osei Barimah; Limei Yin; Quansheng Chen; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou. 2021. "Intelligent evaluation of taste constituents and polyphenols-to-amino acids ratio in matcha tea powder using near infrared spectroscopy." Food Chemistry 353, no. : 129372.

Paper
Published: 25 February 2021 in Analytical Methods
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Perchlorate is a new type of persistent pollutant, which interferes with the synthesis and secretion of thyroxine and affects human health.

ACS Style

Zhiming Guo; Ping Chen; Mingming Wang; Alberta Osei Barimah; Quansheng Chen; Hesham R. El-Seedi; Xiaobo Zou. Determination of perchlorate in tea using SERS with a superhydrophobically treated cysteine modified silver film/polydimethylsiloxane substrate. Analytical Methods 2021, 13, 1625 -1634.

AMA Style

Zhiming Guo, Ping Chen, Mingming Wang, Alberta Osei Barimah, Quansheng Chen, Hesham R. El-Seedi, Xiaobo Zou. Determination of perchlorate in tea using SERS with a superhydrophobically treated cysteine modified silver film/polydimethylsiloxane substrate. Analytical Methods. 2021; 13 (13):1625-1634.

Chicago/Turabian Style

Zhiming Guo; Ping Chen; Mingming Wang; Alberta Osei Barimah; Quansheng Chen; Hesham R. El-Seedi; Xiaobo Zou. 2021. "Determination of perchlorate in tea using SERS with a superhydrophobically treated cysteine modified silver film/polydimethylsiloxane substrate." Analytical Methods 13, no. 13: 1625-1634.

Journal article
Published: 27 November 2020 in International Journal of Food Microbiology
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Fungal infection is one of the main causes of apple corruption. The main dominant spoilage fungi in causing apple spoilage are storage mainly include Penicillium Paecilomyces paecilomyces (P. paecilomyces), penicillium chrysanthemum (P. chrysogenum), expanded Penicillium expansum (P. expansum), Aspergillus niger (Asp. niger) and Alternaria. In this study, surface-enhanced Raman spectroscopy (SERS) based on gold nanorod (AuNRs) substrate method was developed to collect and examine the Raman fingerprints of dominant apple spoilage fungus spores. Standard normal variable (SNV) was used to pretreat the obtained spectra to improve signal-to-noise ratio. Principal component analysis (PCA) was applied to extract useful spectral information. Linear discriminant analysis (LDA) and non-linear pattern recognition methods including K nearest neighbor (KNN), Support vector machine (SVM) and back propagation artificial neural networks (BPANN) were used to identify fungal species. As the comparison of modeling results shown, the BPANN model established based on the characteristic spectra variables have achieved the satisfactory result with discrimination accuracy of 98.23%; while the PCA-LDA model built using principal component variables achieved the best distinguish result with discrimination accuracy of 98.31%. It was concluded that SERS has the potential to be an inexpensive, rapid and effective method to detect and identify fungal species.

ACS Style

Zhiming Guo; Mingming Wang; Alberta Osei Barimah; Quansheng Chen; Huanhuan Li; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou. Label-free surface enhanced Raman scattering spectroscopy for discrimination and detection of dominant apple spoilage fungus. International Journal of Food Microbiology 2020, 338, 108990 .

AMA Style

Zhiming Guo, Mingming Wang, Alberta Osei Barimah, Quansheng Chen, Huanhuan Li, Jiyong Shi, Hesham R. El-Seedi, Xiaobo Zou. Label-free surface enhanced Raman scattering spectroscopy for discrimination and detection of dominant apple spoilage fungus. International Journal of Food Microbiology. 2020; 338 ():108990.

Chicago/Turabian Style

Zhiming Guo; Mingming Wang; Alberta Osei Barimah; Quansheng Chen; Huanhuan Li; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou. 2020. "Label-free surface enhanced Raman scattering spectroscopy for discrimination and detection of dominant apple spoilage fungus." International Journal of Food Microbiology 338, no. : 108990.

Review
Published: 11 August 2020 in International Journal of Environmental Research and Public Health
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Lately, myriad of novel viruses have emerged causing epidemics such as SARS, MERS, and SARS-CoV-2, leading to high mortality rates worldwide. Thus, these viruses represented a challenging threat to mankind, especially considering the miniscule data available at our disposal regarding these novel viruses. The entire world established coordinative relations in research projects regarding drug and vaccine development on the external range, whereas on the internal range, all countries declared it an emergency case through imposing different restrictions related to their border control, large gatherings, school attendance, and most social activities. Pandemic combating plans prioritized all sectors including normal people, medical staff politicians, and scientists collectively shouldered the burden. Through planning and learning the previous lessons from SARS and MERS, healthcare systems could succeed in combating the viral spread and implications of these new pandemics. Different management strategies including social distance, social awareness and isolation represented successful ways to slow down the spread of the pandemic. Furthermore, pre-preparedness of some countries for emergencies is crucial to minimize the consequences of the crisis.

ACS Style

Shaden A. M. Khalifa; Briksam S. Mohamed; Mohamed H. Elashal; Ming Du; Zhiming Guo; Chao Zhao; Syed Ghulam Musharraf; Mohammad H. Boskabady; Haged H. R. El-Seedi; Thomas Efferth; Hesham R. El-Seedi. Comprehensive Overview on Multiple Strategies Fighting COVID-19. International Journal of Environmental Research and Public Health 2020, 17, 5813 .

AMA Style

Shaden A. M. Khalifa, Briksam S. Mohamed, Mohamed H. Elashal, Ming Du, Zhiming Guo, Chao Zhao, Syed Ghulam Musharraf, Mohammad H. Boskabady, Haged H. R. El-Seedi, Thomas Efferth, Hesham R. El-Seedi. Comprehensive Overview on Multiple Strategies Fighting COVID-19. International Journal of Environmental Research and Public Health. 2020; 17 (16):5813.

Chicago/Turabian Style

Shaden A. M. Khalifa; Briksam S. Mohamed; Mohamed H. Elashal; Ming Du; Zhiming Guo; Chao Zhao; Syed Ghulam Musharraf; Mohammad H. Boskabady; Haged H. R. El-Seedi; Thomas Efferth; Hesham R. El-Seedi. 2020. "Comprehensive Overview on Multiple Strategies Fighting COVID-19." International Journal of Environmental Research and Public Health 17, no. 16: 5813.

Journal article
Published: 20 July 2020 in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
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Black tea like other food crops is prone to mercury ion (Hg2+) contamination right from cultivation to industrial processing. Due to the dangerous health effects posed even in trace contents, sensitive detection and quantification sensors are required. This study employed the surface-enhanced Raman scattering (SERS) enhancement property of 4-aminothiophenol (4-ATP) as a signal turn off approach functionalized on Ag-Au alloyed nanoparticle to firstly detect Hg2+ in standard solutions and spiked tea samples. Different chemometric algorithms were applied on the acquired SERS and inductively coupled plasma-mass spectrometry (ICP-MS) chemical reference data to select effective wavelengths and spectral variables in order to develop models to predict the Hg2+. Results indicated that Ag-Au/4-ATP SERS sensor combined with ant colony optimization partial least squares (ACO-PLS) exhibited the best correlation efficient and minimum errors for Hg2+ standard solutions (Rc = 0.984, Rp = 0.974, RMSEC = 0.157 μg/mL, RMSEP = 0.211 μg/mL) and spiked tea samples (Rc = 0.979, Rp = 0.963, RMSEC = 0.181 μg/g and RMSEP = 0.210 μg/g). The limit of detection of the proposed sensor was 4.12 × 10−7 μg/mL for Hg2+ standard solutions and 2.83 × 10−5 μg/g for Hg2+ spiked tea samples. High stability and reproducibility with relative standard deviation of 1.14% and 0.84% were detected. The potent strong relationship between the SERS sensor and the chemical reference method encourages the application of the developed chemometrics coupled SERS system for future monitoring and evaluation of Hg2+ in tea.

ACS Style

Zhiming Guo; Alberta Osei Barimah; Chuang Guo; Akwasi A. Agyekum; Viswadevarayalu Annavaram; Hesham R. El-Seedi; Xiaobo Zou; Quansheng Chen. Chemometrics coupled 4-Aminothiophenol labelled Ag-Au alloy SERS off-signal nanosensor for quantitative detection of mercury in black tea. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2020, 242, 118747 .

AMA Style

Zhiming Guo, Alberta Osei Barimah, Chuang Guo, Akwasi A. Agyekum, Viswadevarayalu Annavaram, Hesham R. El-Seedi, Xiaobo Zou, Quansheng Chen. Chemometrics coupled 4-Aminothiophenol labelled Ag-Au alloy SERS off-signal nanosensor for quantitative detection of mercury in black tea. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2020; 242 ():118747.

Chicago/Turabian Style

Zhiming Guo; Alberta Osei Barimah; Chuang Guo; Akwasi A. Agyekum; Viswadevarayalu Annavaram; Hesham R. El-Seedi; Xiaobo Zou; Quansheng Chen. 2020. "Chemometrics coupled 4-Aminothiophenol labelled Ag-Au alloy SERS off-signal nanosensor for quantitative detection of mercury in black tea." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 242, no. : 118747.

Review
Published: 11 July 2020 in Toxins
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Bee venom (BV) is a rich source of secondary metabolites from honeybees (Apis mellifera L.). It contains a variety of bioactive ingredients including peptides, proteins, enzymes, and volatile metabolites. The compounds contribute to the venom’s observed biological functions as per its anti-inflammatory and anticancer effects. The antimicrobial action of BV has been shown in vitro and in vivo experiments against bacteria, viruses, and fungi. The synergistic therapeutic interactions of BV with antibiotics has been reported. The synergistic effect contributes to a decrease in the loading and maintenance dosage, a decrease in the side effects of chemotherapy, and a decrease in drug resistance. To our knowledge, there have been no reviews on the impact of BV and its antimicrobial constituents thus far. The purpose of this review is to address the antimicrobial properties of BV and its compounds.

ACS Style

Hesham El-Seedi; Aida Abd El-Wahed; Nermeen Yosri; Syed Ghulam Musharraf; Lei Chen; Moustafa Moustafa; Xiaobo Zou; Saleh Al-Mousawi; Zhiming Guo; Alfi Khatib; Shaden Khalifa. Antimicrobial Properties of Apis mellifera’s Bee Venom. Toxins 2020, 12, 451 .

AMA Style

Hesham El-Seedi, Aida Abd El-Wahed, Nermeen Yosri, Syed Ghulam Musharraf, Lei Chen, Moustafa Moustafa, Xiaobo Zou, Saleh Al-Mousawi, Zhiming Guo, Alfi Khatib, Shaden Khalifa. Antimicrobial Properties of Apis mellifera’s Bee Venom. Toxins. 2020; 12 (7):451.

Chicago/Turabian Style

Hesham El-Seedi; Aida Abd El-Wahed; Nermeen Yosri; Syed Ghulam Musharraf; Lei Chen; Moustafa Moustafa; Xiaobo Zou; Saleh Al-Mousawi; Zhiming Guo; Alfi Khatib; Shaden Khalifa. 2020. "Antimicrobial Properties of Apis mellifera’s Bee Venom." Toxins 12, no. 7: 451.

Original research
Published: 27 May 2020 in Food Science & Nutrition
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Apple is the most widely planted fruit in the world and is popular in consumers because of its rich nutritional value. In this study, the portable near‐infrared (NIR) transmittance spectroscopy coupled with temperature compensation and chemometric algorithms was applied to detect the storage quality of apples. The postharvest quality of apples including soluble solids content (SSC), vitamin C (VC), titratable acid (TA), and firmness was evaluated, and the portable spectrometer was used to obtain near‐infrared transmittance spectra of apples in the wavelength range of 590–1,200 nm. Mixed temperature compensation method (MTC) was used to reduce the influence of temperature on the models and to improve the adaptability of the models. Then, variable selection methods, such as uninformative variable elimination (UVE), competitive adaptive reweighted sampling (CARS), and successive projections algorithm (SPA), were developed to improve the performance of the models by determining characteristic variables and reducing redundancy. Comparing the full spectral models with the models established on variables selected by different variable selection methods, the CARS combined with partial least squares (PLS) showed the best performance with prediction correlation coefficient (R p) and residual predictive deviation (RPD) values of 0.9236, 2.604 for SSC; 0.8684, 2.002 for TA; 0.8922, 2.087 for VC; and 0.8207, 1.992 for firmness, respectively. Results showed that NIR transmittance spectroscopy was feasible to detect postharvest quality of apples during storage.

ACS Style

Zhiming Guo; Mingming Wang; Ali Shujat; Jingzhu Wu; Hesham R. El‐Seedi; Jiyong Shi; Qin Ouyang; Quansheng Chen; Xiaobo Zou. Nondestructive monitoring storage quality of apples at different temperatures by near‐infrared transmittance spectroscopy. Food Science & Nutrition 2020, 8, 3793 -3805.

AMA Style

Zhiming Guo, Mingming Wang, Ali Shujat, Jingzhu Wu, Hesham R. El‐Seedi, Jiyong Shi, Qin Ouyang, Quansheng Chen, Xiaobo Zou. Nondestructive monitoring storage quality of apples at different temperatures by near‐infrared transmittance spectroscopy. Food Science & Nutrition. 2020; 8 (7):3793-3805.

Chicago/Turabian Style

Zhiming Guo; Mingming Wang; Ali Shujat; Jingzhu Wu; Hesham R. El‐Seedi; Jiyong Shi; Qin Ouyang; Quansheng Chen; Xiaobo Zou. 2020. "Nondestructive monitoring storage quality of apples at different temperatures by near‐infrared transmittance spectroscopy." Food Science & Nutrition 8, no. 7: 3793-3805.

Journal article
Published: 10 May 2020 in LWT - Food Science and Technology
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A simple, rapid and low-cost analytical method was employed for simultaneous determination of bioactive constituents and antioxidant capability of green tea. The strategy was based on swarm intelligence algorithms with partial least squares (PLS) such as simulated annealing PLS (SA-PLS), ant colony optimization PLS (ACO-PLS), genetic algorithm PLS (GA-PLS), and synergy interval PLS (Si-PLS) coupled with Near-infrared (NIR) spectroscopy. These algorithms were independently applied to select informative spectral variables and improve the prediction of green tea components. Results showed that NIR combined with SA-PLS and Si-PLS had a strong correlation coefficient with the wet-chemical methods for predicting epigallocatechin gallate (Rp2 = 0.97); epigallocatechin (Rp2 = 0.97); epicatechin gallate (Rp2 = 0.96); epicatechin (Rp2 = 0.91); catechin (Rp2 = 0.98); caffeine (Rp2 = 0.96); theanine (Rp2 = 0.93); and antioxidant capability (Rp2 = 0.80) in green tea. Our results revealed the potential utilization of NIR spectroscopy coupled with SA-PLS and Si-PLS algorithms as an effective and robust technique to simultaneously predict active constituents and antioxidant capability of green tea.

ACS Style

Zhiming Guo; Alberta Osei Barimah; Ali Shujat; Zhengzhu Zhang; Qin Ouyang; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou; Quansheng Chen. Simultaneous quantification of active constituents and antioxidant capability of green tea using NIR spectroscopy coupled with swarm intelligence algorithm. LWT - Food Science and Technology 2020, 129, 109510 .

AMA Style

Zhiming Guo, Alberta Osei Barimah, Ali Shujat, Zhengzhu Zhang, Qin Ouyang, Jiyong Shi, Hesham R. El-Seedi, Xiaobo Zou, Quansheng Chen. Simultaneous quantification of active constituents and antioxidant capability of green tea using NIR spectroscopy coupled with swarm intelligence algorithm. LWT - Food Science and Technology. 2020; 129 ():109510.

Chicago/Turabian Style

Zhiming Guo; Alberta Osei Barimah; Ali Shujat; Zhengzhu Zhang; Qin Ouyang; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou; Quansheng Chen. 2020. "Simultaneous quantification of active constituents and antioxidant capability of green tea using NIR spectroscopy coupled with swarm intelligence algorithm." LWT - Food Science and Technology 129, no. : 109510.

Journal article
Published: 07 May 2020 in Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
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The current study extends the use of surface-enhanced Raman spectroscopy (SERS) combined with density functional theory (DFT) and multivariate calibration towards the rapid quantification of aflatoxin B1 (AFB1) in peanut oil samples. It reports the design of pre etched Ag nanocluster as an active SERS substrate for quantifying AFB1, after being impregnated on its surface. The SERS spectra of [email protected] etched Ag nanocluster was recorded and its respective theoretical spectrum was calculated by density functional theory (DFT) to assign the characteristic peaks. The baseline drift and rotation effects were masked by the first-order derivative preprocessing method followed by multivariate calibration. The BP-AdaBoost model exhibited optimum prediction (Rp = 0.9283 and 0.9332) ability over the concentration range 5–100 and 100–1000 ngmL−1, respectively. The limit of detection calculated was 5.0 ngmL−1 and the obtained recoveries were in the range from 90.4% to 113.1% in spiked peanut oil samples. Additionally, precision analysis revealed an RSD ca. 5%, suggesting the applicability of the pre etched Ag nanocluster SERS substrate towards AFB1 detection. Thus, the proposed SERS platform exploiting DFT and BP-AdaBoost model was found reproducible for the quantification of AFB1 in peanut oil.

ACS Style

Quansheng Chen; Tianhui Jiao; Mingxiu Yang; Huanhuan Li; Waqas Ahmad; Mehedi Hassan; Zhiming Guo; Shujat Ali. Pre etched Ag nanocluster as SERS substrate for the rapid quantification of AFB1 in peanut oil via DFT coupled multivariate calibration. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2020, 239, 118411 .

AMA Style

Quansheng Chen, Tianhui Jiao, Mingxiu Yang, Huanhuan Li, Waqas Ahmad, Mehedi Hassan, Zhiming Guo, Shujat Ali. Pre etched Ag nanocluster as SERS substrate for the rapid quantification of AFB1 in peanut oil via DFT coupled multivariate calibration. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 2020; 239 ():118411.

Chicago/Turabian Style

Quansheng Chen; Tianhui Jiao; Mingxiu Yang; Huanhuan Li; Waqas Ahmad; Mehedi Hassan; Zhiming Guo; Shujat Ali. 2020. "Pre etched Ag nanocluster as SERS substrate for the rapid quantification of AFB1 in peanut oil via DFT coupled multivariate calibration." Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 239, no. : 118411.

Journal article
Published: 09 April 2020 in Sensors
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It is crucial for the efficacy of the apple storage to apply methods like electronic nose systems for detection and prediction of spoilage or infection by Penicillium expansum. Based on the acquisition of electronic nose signals, selected sensitive feature sensors of spoilage apple and all sensors were analyzed and compared by the recognition effect. Principal component analysis (PCA), principle component analysis-discriminant analysis (PCA-DA), linear discriminant analysis (LDA), partial least squares discriminate analysis (PLS-DA) and K-nearest neighbor (KNN) were used to establish the classification model of apple with different degrees of corruption. PCA-DA has the best prediction, the accuracy of training set and prediction set was 100% and 97.22%, respectively. synergy interval (SI), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) are three selection methods used to accurately and quickly extract appropriate feature variables, while constructing a PLS model to predict plaque area. Among them, the PLS model with unique variables was optimized by CARS method, and the best prediction result of the area of the rotten apple was obtained. The best results are as follows: Rc = 0.953, root mean square error of calibration (RMSEC) = 1.28, Rp = 0.972, root mean square error of prediction (RMSEP) = 1.01. The results demonstrated that the electronic nose has a potential application in the classification of rotten apples and the quantitative detection of spoilage area.

ACS Style

Zhiming Guo; Chuang Guo; Quansheng Chen; Qin Ouyang; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou. Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics. Sensors 2020, 20, 2130 .

AMA Style

Zhiming Guo, Chuang Guo, Quansheng Chen, Qin Ouyang, Jiyong Shi, Hesham R. El-Seedi, Xiaobo Zou. Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics. Sensors. 2020; 20 (7):2130.

Chicago/Turabian Style

Zhiming Guo; Chuang Guo; Quansheng Chen; Qin Ouyang; Jiyong Shi; Hesham R. El-Seedi; Xiaobo Zou. 2020. "Classification for Penicillium expansum Spoilage and Defect in Apples by Electronic Nose Combined with Chemometrics." Sensors 20, no. 7: 2130.

Journal article
Published: 05 February 2020 in Journal of Food Engineering
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Near-infrared (NIR) spectroscopy as an emerging analytical technique was used for the first time to quantitatively detect the watercore degree and soluble solids content (SSC) in apple. To reduce the data processing time and meet the needs of practical application, the variable selection methods including synergy interval (SI), successive projections algorithm (SPA), genetic algorithm (GA) and competitive adaptive reweighted sampling (CARS) were used to identify the characteristic variables and simplify the models. The spectral variables closely related to the apple bioactive components were used for the establishment of the partial least squares (PLS) models. The predictive correlation coefficient (Rp), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD) were used to estimate the performance of the models. The CARS-PLS models displayed the best prediction performance using 600–1000 nm spectra with Rp, RMSEP, and RPD values of 0.9562, 1.340% and 3.720 for apple watercore degree; 0.9808, 0.327 oBx and 4.845 for apple SSC, respectively. These results demonstrate the potential of the NIR transmittance spectroscopy technology for quantitative detection of SSC and watercore degree in apple fruit.

ACS Style

Zhiming Guo; Mingming Wang; Akwasi Akomeah Agyekum; Jingzhu Wu; Quansheng Chen; Min Zuo; Hesham R. El-Seedi; Feifei Tao; Jiyong Shi; Qin Ouyang; Xiaobo Zou. Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy. Journal of Food Engineering 2020, 279, 109955 .

AMA Style

Zhiming Guo, Mingming Wang, Akwasi Akomeah Agyekum, Jingzhu Wu, Quansheng Chen, Min Zuo, Hesham R. El-Seedi, Feifei Tao, Jiyong Shi, Qin Ouyang, Xiaobo Zou. Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy. Journal of Food Engineering. 2020; 279 ():109955.

Chicago/Turabian Style

Zhiming Guo; Mingming Wang; Akwasi Akomeah Agyekum; Jingzhu Wu; Quansheng Chen; Min Zuo; Hesham R. El-Seedi; Feifei Tao; Jiyong Shi; Qin Ouyang; Xiaobo Zou. 2020. "Quantitative detection of apple watercore and soluble solids content by near infrared transmittance spectroscopy." Journal of Food Engineering 279, no. : 109955.

Journal article
Published: 31 October 2019 in Journal of Food Engineering
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Hyperspectral microscope imaging (HMI) technology as a novel approach was proposed to evaluate physical characteristics of matcha. Particle size distribution as one of the significant physical characteristics was investigated. Data fusion which integrated of textural features from images at 524 nm and key spectral features selected by competitive adaptive reweighed sampling (CARS) were as the raw data for modeling. Models were optimized by cross-validation. Results showed that the performance of models was improved with data fusion. The best ANN models with data fusion were achieved with Rp (correlation coefficient in prediction set) of 0.8020 for D10, 0.8414 for D20, 0.8238 for D30, 0.8124 for D40, 0.8058 for D50, 0.8157 for D60, 0.7643 for D70, 0.7360 for D80, and 0.6313 for D90, respectively. This work demonstrated that HMI technology as a rapid, accurate and high effective protocol has great potential in predicting particle size distribution in matcha powder.

ACS Style

Qin Ouyang; Yongcun Yang; Bosoon Park; Rui Kang; Jizhong Wu; Quansheng Chen; Zhiming Guo; Huanhuan Li. A novel hyperspectral microscope imaging technology for rapid evaluation of particle size distribution in matcha. Journal of Food Engineering 2019, 272, 109782 .

AMA Style

Qin Ouyang, Yongcun Yang, Bosoon Park, Rui Kang, Jizhong Wu, Quansheng Chen, Zhiming Guo, Huanhuan Li. A novel hyperspectral microscope imaging technology for rapid evaluation of particle size distribution in matcha. Journal of Food Engineering. 2019; 272 ():109782.

Chicago/Turabian Style

Qin Ouyang; Yongcun Yang; Bosoon Park; Rui Kang; Jizhong Wu; Quansheng Chen; Zhiming Guo; Huanhuan Li. 2019. "A novel hyperspectral microscope imaging technology for rapid evaluation of particle size distribution in matcha." Journal of Food Engineering 272, no. : 109782.