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Calado CRC. Bridging the gap between target-based and phenotypic-based drug discovery. Expert Opin Drug Discov 2024; 19:789-798. [PMID: 38747562 DOI: 10.1080/17460441.2024.2355330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 05/10/2024] [Indexed: 06/26/2024]
Abstract
INTRODUCTION The unparalleled progress in science of the last decades has brought a better understanding of the molecular mechanisms of diseases. This promoted drug discovery processes based on a target approach. However, despite the high promises associated, a critical decrease in the number of first-in-class drugs has been observed. AREAS COVERED This review analyses the challenges, advances, and opportunities associated with the main strategies of the drug discovery process, i.e. based on a rational target approach and on an empirical phenotypic approach. This review also evaluates how the gap between these two crossroads can be bridged toward a more efficient drug discovery process. EXPERT OPINION The critical lack of knowledge of the complex biological networks is leading to targets not relevant for the clinical context or to drugs that present undesired adverse effects. The phenotypic systems designed by considering available molecular mechanisms can mitigate these knowledge gaps. Associated with the expansion of the chemical space and other technologies, these designs can lead to more efficient drug discoveries. Technological and scientific knowledge should also be applied to identify, as early as possible, both drug targets and mechanisms of action, leading to a more efficient drug discovery pipeline.
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Affiliation(s)
- Cecília R C Calado
- ISEL-Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Lisboa, Portugal
- iBB - Institute for Bioengineering and Biosciences, i4HB - The Associate Laboratory Institute for Health and Bioeconomy, IST - Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
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2
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Zhu YB, Liu TL, Dai Q, Liu SF, Xiong P, Huang H, Yuan Y, Zhang TN, Chen Y. Characteristics and Risk Factors for Pediatric Sepsis. Curr Med Sci 2024; 44:648-656. [PMID: 38748371 DOI: 10.1007/s11596-024-2870-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 03/22/2024] [Indexed: 06/29/2024]
Abstract
OBJECTIVE Sepsis is considered a major cause of health loss in children and had high mortality and morbidity. Currently, there is no reliable model for predicting the prognosis of pediatric patients with sepsis. This study aimed to analyze the clinical characteristics of sepsis in children and assess the risk factors associated with poor prognosis in pediatric sepsis patients to identify timely interventions and improve their outcomes. METHODS This study analyzed the clinical indicators and laboratory results of septic patients hospitalized in the Pediatric Intensive Care Unit of Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, China, from January 1, 2019, to December 31, 2021. Risk factors for sepsis were identified by logistic regression analyses. RESULTS A total of 355 children with sepsis were enrolled, with 333 children (93.8%) in the good prognosis group, and 22 children (6.2%) in the poor prognosis group. Among them, there were 255 patients (71.8%) in the sepsis group, and 100 patients (28.2%) in the severe sepsis group. The length of hospital stay in the poor prognosis group was longer than that in the good prognosis group (P<0.01). The levels of interleukin 1β (IL-1β) in the poor prognosis group were higher than those in the good prognosis group (P>0.05), and the platelet (PLT), albumin (ALB), and hemoglobin (Hb) levels were lower in the poor prognosis group (P<0.01). The IL-8 levels in the severe sepsis group were higher than those in the sepsis group (P<0.05). Multiple logistic regression analysis suggested that lower Hb levels, ALB levels, peak PLT counts, and higher IL-1β levels were independent risk factors for poor prognosis in children with sepsis. CONCLUSION Lower Hb, ALB, and PLT counts and elevated IL-1β are independent risk factors for poor prognosis in children with sepsis.
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Affiliation(s)
- Yong-Bing Zhu
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Tong-Lin Liu
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Qi Dai
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Shu-Fan Liu
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Peng Xiong
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Hao Huang
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yi Yuan
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Tian-Nan Zhang
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yu Chen
- Department of Pediatric Intensive Care Unit, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Araújo R, Ramalhete L, Viegas A, Von Rekowski CP, Fonseca TAH, Calado CRC, Bento L. Simplifying Data Analysis in Biomedical Research: An Automated, User-Friendly Tool. Methods Protoc 2024; 7:36. [PMID: 38804330 PMCID: PMC11130801 DOI: 10.3390/mps7030036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2024] [Revised: 04/20/2024] [Accepted: 04/22/2024] [Indexed: 05/29/2024] Open
Abstract
Robust data normalization and analysis are pivotal in biomedical research to ensure that observed differences in populations are directly attributable to the target variable, rather than disparities between control and study groups. ArsHive addresses this challenge using advanced algorithms to normalize populations (e.g., control and study groups) and perform statistical evaluations between demographic, clinical, and other variables within biomedical datasets, resulting in more balanced and unbiased analyses. The tool's functionality extends to comprehensive data reporting, which elucidates the effects of data processing, while maintaining dataset integrity. Additionally, ArsHive is complemented by A.D.A. (Autonomous Digital Assistant), which employs OpenAI's GPT-4 model to assist researchers with inquiries, enhancing the decision-making process. In this proof-of-concept study, we tested ArsHive on three different datasets derived from proprietary data, demonstrating its effectiveness in managing complex clinical and therapeutic information and highlighting its versatility for diverse research fields.
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Affiliation(s)
- Rúben Araújo
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
| | - Luís Ramalhete
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- Blood and Transplantation Center of Lisbon, IPST—Instituto Português do Sangue e da Transplantação, Alameda das Linhas de Torres 117, 1769-001 Lisbon, Portugal
- iNOVA4Health—Advancing Precision Medicine, RG11: Reno-Vascular Diseases Group, NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
| | - Ana Viegas
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ESTeSL—Escola Superior de Tecnologia da Saúde de Lisboa, Instituto Politécnico de Lisboa, Avenida D. João II, Lote 4.69.01, 1990-096 Lisbon, Portugal
- Neurosciences Area, Clinical Neurophysiology Unit, ULSSJ—Unidade Local de Saúde São José, Rua José António Serrano, 1150-199 Lisbon, Portugal
| | - Cristiana P. Von Rekowski
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
| | - Tiago A. H. Fonseca
- NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, Universidade NOVA de Lisboa, 1150-082 Lisbon, Portugal
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
| | - Cecília R. C. Calado
- ISEL—Instituto Superior de Engenharia de Lisboa, Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisbon, Portugal
- Institute for Bioengineering and Biosciences (iBB), The Associate Laboratory Institute for Health and Bioeconomy–i4HB, Instituto Superior Técnico (IST), Universidade de Lisboa (UL), Av. Rovisco Pais, 1049-001 Lisboa, Portugal
| | - Luís Bento
- Intensive Care Department, ULSSJ—Unidade Local de Saúde São José, Rua José António Serrano, 1150-199 Lisbon, Portugal;
- Integrated Pathophysiological Mechanisms, CHRC—Comprehensive Health Research Centre, NMS—NOVA Medical School, FCM—Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, Campo Mártires da Pátria 130, 1169-056 Lisbon, Portugal
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Liu Y, Zhu Q, Guo G, Xie Z, Li S, Lai C, Wu Y, Wang L, Zhong S. Causal associations of genetically predicted gut microbiota and blood metabolites with inflammatory states and risk of infections: a Mendelian randomization analysis. Front Microbiol 2024; 15:1342653. [PMID: 38585702 PMCID: PMC10995310 DOI: 10.3389/fmicb.2024.1342653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Accepted: 02/28/2024] [Indexed: 04/09/2024] Open
Abstract
Background Inflammation serves as a key pathologic mediator in the progression of infections and various diseases, involving significant alterations in the gut microbiome and metabolism. This study aims to probe into the potential causal relationships between gut microbial taxa and human blood metabolites with various serum inflammatory markers (CRP, SAA1, IL-6, TNF-α, WBC, and GlycA) and the risks of seven common infections (gastrointestinal infections, dysentery, pneumonia, bacterial pneumonia, bronchopneumonia and lung abscess, pneumococcal pneumonia, and urinary tract infections). Methods Two-sample Mendelian randomization (MR) analysis was performed using inverse variance weighted (IVW), maximum likelihood, MR-Egger, weighted median, and MR-PRESSO. Results After adding other MR models and sensitivity analyses, genus Roseburia was simultaneously associated adversely with CRP (Beta IVW = -0.040) and SAA1 (Beta IVW = -0.280), and family Bifidobacteriaceae was negatively associated with both CRP (Beta IVW = -0.034) and pneumonia risk (Beta IVW = -0.391). After correction by FDR, only glutaroyl carnitine remained significantly associated with elevated CRP levels (Beta IVW = 0.112). Additionally, threonine (Beta IVW = 0.200) and 1-heptadecanoylglycerophosphocholine (Beta IVW = -0.246) were found to be significantly associated with WBC levels. Three metabolites showed similar causal effects on different inflammatory markers or infectious phenotypes, stearidonate (18:4n3) was negatively related to SAA1 and urinary tract infections, and 5-oxoproline contributed to elevated IL-6 and SAA1 levels. In addition, 7-methylguanine showed a positive correlation with dysentery and bacterial pneumonia. Conclusion This study provides novel evidence confirming the causal effects of the gut microbiome and the plasma metabolite profile on inflammation and the risk of infection. These potential molecular alterations may aid in the development of new targets for the intervention and management of disorders associated with inflammation and infections.
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Affiliation(s)
- Yingjian Liu
- Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
| | - Qian Zhu
- Department of Neurosurgery, Huizhou Third People's Hospital, Guangzhou Medical University, Huizhou, Guangdong, China
| | - Gongjie Guo
- Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Zhipeng Xie
- Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Senlin Li
- Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Chengyang Lai
- Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Yonglin Wu
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
| | - Liansheng Wang
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Shilong Zhong
- Department of Pharmacy, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, Guangdong, China
- School of Medicine, South China University of Technology, Guangzhou, Guangdong, China
- Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
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Connors J, Cusimano G, Mege N, Woloszczuk K, Konopka E, Bell M, Joyner D, Marcy J, Tardif V, Kutzler MA, Muir R, Haddad EK. Using the power of innate immunoprofiling to understand vaccine design, infection, and immunity. Hum Vaccin Immunother 2023; 19:2267295. [PMID: 37885158 PMCID: PMC10760375 DOI: 10.1080/21645515.2023.2267295] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 10/03/2023] [Indexed: 10/28/2023] Open
Abstract
In the field of immunology, a systems biology approach is crucial to understanding the immune response to infection and vaccination considering the complex interplay between genetic, epigenetic, and environmental factors. Significant progress has been made in understanding the innate immune response, including cell players and critical signaling pathways, but many questions remain unanswered, including how the innate immune response dictates host/pathogen responses and responses to vaccines. To complicate things further, it is becoming increasingly clear that the innate immune response is not a linear pathway but is formed from complex networks and interactions. To further our understanding of the crosstalk and complexities, systems-level analyses and expanded experimental technologies are now needed. In this review, we discuss the most recent immunoprofiling techniques and discuss systems approaches to studying the global innate immune landscape which will inform on the development of personalized medicine and innovative vaccine strategies.
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Affiliation(s)
- Jennifer Connors
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Gina Cusimano
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Nathan Mege
- Tower Health, Reading Hospital, West Reading, PA, USA
| | - Kyra Woloszczuk
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Emily Konopka
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Matthew Bell
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - David Joyner
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Molecular and Cellular Biology, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Jennifer Marcy
- Department of Molecular and Cellular Biology, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Virginie Tardif
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Michele A. Kutzler
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Roshell Muir
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Family, Community, and Preventative Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
| | - Elias K. Haddad
- Department of Microbiology and Immunology, Drexel University College of Medicine, Philadelphia, PA, USA
- Department of Medicine, Division of Infectious Diseases and HIV Medicine, Drexel University College of Medicine, Philadelphia, PA, USA
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Yang Q, Song J, Deng Z, Shi C, Li S, Zhuang G, Hao H, Cai Y. Discrimination of blood metabolomics profiles in neonates with idiopathic polyhydramnios. Eur J Pediatr 2023; 182:5015-5024. [PMID: 37644170 DOI: 10.1007/s00431-023-05171-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/12/2023] [Accepted: 08/19/2023] [Indexed: 08/31/2023]
Abstract
This study aimed to compare the blood metabolic status of neonates with idiopathic polyhydramnios (IPH) and those with normal amniotic fluid, and to explore the relationship between IPH and fetal health. Blood metabolites of 32 patients with IPH and 32 normal controls admitted to the Sixth Affiliated Hospital of Sun Yat-sen University between January 2017 and December 2022 were analyzed using liquid chromatography-mass spectrometry (LC-MS/MS). Orthogonal partial least squares discriminant analysis (OPLS-DA) and metabolite enrichment analyses were performed to identify the differential metabolites and metabolic pathways. There was a significant difference in the blood metabolism between newborns with IPH and those with normal amniotic fluid. Six discriminant metabolites were identified: glutamate, serine, asparagine, aspartic acid, homocysteine, and phenylalanine. Differential metabolites were mainly enriched in two pathways: aminoacyl-tRNA biosynthesis, and alanine, aspartate, and glutamate metabolism. CONCLUSIONS This study is the first to investigate metabolomic profiles in newborns with IPH and examine the correlation between IPH and fetal health. Differential metabolites and pathways may affect amino acid synthesis and the nervous system. Continuous attention to the development of the nervous system in children with IPH is necessary. WHAT IS KNOWN • There is an increased risk of adverse pregnancy outcomes with IPH, such as perinatal death, neonatal asphyxia, neonatal intensive care admission, cesarean section rates, and postpartum hemorrhage. • Children with a history of IPH have a higher proportion of defects than the general population, particularly central nervous system problems, neuromuscular disorders, and other malformations. WHAT IS NEW • In neonates with IPH, six differential metabolites were identified with significant differences and good AUC values using LC-MS/MS analysis: glutamic acid, serine, asparagine, aspartic acid, homocysteine, and phenylalanine, which were mainly enriched in two metabolic pathways: aminoacyl-tRNA biosynthesis and alanine, aspartate, and glutamate metabolism. • These differential metabolites and pathways may affect amino acid synthesis and development of the nervous system in neonates with IPH.
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Affiliation(s)
- Qiuping Yang
- Department of Pediatrics, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, 510530, Guangzhou, China
| | - Jie Song
- Department of Pediatrics, The Fifth Affiliated Hospital, Sun Yat-sen University, 519000, Zhuhai, China
| | - Zhirong Deng
- Department of Pediatrics, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, 510530, Guangzhou, China
| | - Congcong Shi
- Laboratory of Inborn Metabolism Errors, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China
| | - Sitao Li
- Department of Pediatrics, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, 510530, Guangzhou, China
| | - Guiying Zhuang
- Department of Neonatology, The Maternal and Child Health Care Hospital of Huadu, 510800, Guangzhou, China.
| | - Hu Hao
- Department of Pediatrics, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China.
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, 510530, Guangzhou, China.
- Laboratory of Inborn Metabolism Errors, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China.
| | - Yao Cai
- Department of Pediatrics, The Sixth Affiliated Hospital, Sun Yat-sen University, 510655, Guangzhou, China.
- Biomedical Innovation Center, The Sixth Affiliated Hospital, Sun Yat-sen University, 510530, Guangzhou, China.
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Peng J, Qiu C, Zhang J, Xiao X. Serum metabolite profiling reveals metabolic characteristics of sepsis patients using LC/MS-based metabolic profiles: a cross-sectional study. BMC Med Genomics 2023; 16:224. [PMID: 37752563 PMCID: PMC10521453 DOI: 10.1186/s12920-023-01666-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Accepted: 09/18/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND Individuals with sepsis exhibited a higher likelihood of benefiting from early initiation of specialized treatment to enhance the prognosis of the condition. The objective of this study is to identify potential biomarkers of sepsis by means of serum metabolomics. MATERIALS AND METHODS The screening of putative biomarkers of sepsis was conducted using serum samples from patients with sepsis and a control group of healthy individuals. The pathogenesis of sepsis was determined through the utilization of liquid chromatography-mass spectrometry-based metabolic profiles and bioinformatic techniques, which in turn provided a foundation for timely diagnosis and intervention. RESULTS Individuals with sepsis had significantly different metabolic characteristics compared to those with normal health. The concentrations of phosphatidylcholines (PCs), phosphatidylserine (PS), lysophosphatidylethanolamine (LysoPEs), and lysophosphatidylcholine (LysoPCs) exhibited a decrease, while the levels of creatinine, C17-Sphinganine, and PS(22:0/22:1(11Z)) demonstrated an increase in the serum of sepsis patients when compared to the control group. Additionally, ROC curves were generated to assess the discriminatory ability of the differentially expressed metabolites. The area under the ROC curve for PS (22:0/22:1(11Z)) and C17-Sphinganine were determined to be 0.976 and 0.913, respectively. These metabolites may potentially serve as diagnostic markers for sepsis. Additionally, the pathogenesis of sepsis is associated with mTOR signaling, NF-κB signaling pathway, calcium signaling, calcium transport, and tRNA charging pathway. CONCLUSION The identification of differential expression of these metabolites in sepsis serum samples could aid in the timely diagnosis and intervention of sepsis, as well as enhance our understanding of its pathogenesis.
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Affiliation(s)
- Jinliang Peng
- Department of Emergency, The Affiliated Ganzhou Hospital of Nanchang university, Ganzhou, Jiangxi Province, 341000, China
| | - Chongrong Qiu
- Department of Emergency, The Affiliated Ganzhou Hospital of Nanchang university, Ganzhou, Jiangxi Province, 341000, China
| | - Jun Zhang
- Department of Emergency, The Affiliated Ganzhou Hospital of Nanchang university, Ganzhou, Jiangxi Province, 341000, China
| | - Xiaoliu Xiao
- Department of Emergency, The Affiliated Ganzhou Hospital of Nanchang university, Ganzhou, Jiangxi Province, 341000, China.
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Ramalhete L, Vigia E, Araújo R, Marques HP. Proteomics-Driven Biomarkers in Pancreatic Cancer. Proteomes 2023; 11:24. [PMID: 37606420 PMCID: PMC10443269 DOI: 10.3390/proteomes11030024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 07/28/2023] [Accepted: 08/03/2023] [Indexed: 08/23/2023] Open
Abstract
Pancreatic cancer is a devastating disease that has a grim prognosis, highlighting the need for improved screening, diagnosis, and treatment strategies. Currently, the sole biomarker for pancreatic ductal adenocarcinoma (PDAC) authorized by the U.S. Food and Drug Administration is CA 19-9, which proves to be the most beneficial in tracking treatment response rather than in early detection. In recent years, proteomics has emerged as a powerful tool for advancing our understanding of pancreatic cancer biology and identifying potential biomarkers and therapeutic targets. This review aims to offer a comprehensive survey of proteomics' current status in pancreatic cancer research, specifically accentuating its applications and its potential to drastically enhance screening, diagnosis, and treatment response. With respect to screening and diagnostic precision, proteomics carries the capacity to augment the sensitivity and specificity of extant screening and diagnostic methodologies. Nonetheless, more research is imperative for validating potential biomarkers and establishing standard procedures for sample preparation and data analysis. Furthermore, proteomics presents opportunities for unveiling new biomarkers and therapeutic targets, as well as fostering the development of personalized treatment strategies based on protein expression patterns associated with treatment response. In conclusion, proteomics holds great promise for advancing our understanding of pancreatic cancer biology and improving patient outcomes. It is essential to maintain momentum in investment and innovation in this arena to unearth more groundbreaking discoveries and transmute them into practical diagnostic and therapeutic strategies in the clinical context.
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Affiliation(s)
- Luís Ramalhete
- Blood and Transplantation Center of Lisbon—Instituto Português do Sangue e da Transplantação, Alameda das Linhas de Torres, n° 117, 1769-001 Lisbon, Portugal
- Nova Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
- iNOVA4Health—Advancing Precision Medicine, RG11: Reno-Vascular Diseases Group, NOVA Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
| | - Emanuel Vigia
- Nova Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
- Centro Hospitalar de Lisboa Central, Department of Hepatobiliopancreatic and Transplantation, 1050-099 Lisbon, Portugal
| | - Rúben Araújo
- Nova Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
- CHRC—Comprehensive Health Research Centre, NOVA Medical School, 1150-199 Lisbon, Portugal
| | - Hugo Pinto Marques
- Nova Medical School, Faculdade de Ciências Médicas, Universidade NOVA de Lisboa, 1169-056 Lisbon, Portugal
- Centro Hospitalar de Lisboa Central, Department of Hepatobiliopancreatic and Transplantation, 1050-099 Lisbon, Portugal
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Fonseca TH, Von Rekowski CP, Araújo R, Oliveira MC, Justino G, Bento L, Calado CRC. The Impact of the Serum Extraction Protocol on Metabolomic Profiling Using UPLC-MS/MS and FTIR Spectroscopy. ACS OMEGA 2023; 8:20755-20766. [PMID: 37323376 PMCID: PMC10237515 DOI: 10.1021/acsomega.3c01370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Accepted: 05/04/2023] [Indexed: 06/17/2023]
Abstract
Biofluid metabolomics is a very appealing tool to increase the knowledge associated with pathophysiological mechanisms leading to better and new therapies and biomarkers for disease diagnosis and prognosis. However, due to the complex process of metabolome analysis, including the metabolome isolation method and the platform used to analyze it, there are diverse factors that affect metabolomics output. In the present work, the impact of two protocols to extract the serum metabolome, one using methanol and another using a mixture of methanol, acetonitrile, and water, was evaluated. The metabolome was analyzed by ultraperformance liquid chromatography associated with tandem mass spectrometry (UPLC-MS/MS), based on reverse-phase and hydrophobic chromatographic separations, and Fourier transform infrared (FTIR) spectroscopy. The two extraction protocols of the metabolome were compared over the analytical platforms (UPLC-MS/MS and FTIR spectroscopy) concerning the number of features, the type of features, common features, and the reproducibility of extraction replicas and analytical replicas. The ability of the extraction protocols to predict the survivability of critically ill patients hospitalized at an intensive care unit was also evaluated. The FTIR spectroscopy platform was compared to the UPLC-MS/MS platform and, despite not identifying metabolites and consequently not contributing as much as UPLC-MS/MS in terms of information concerning metabolic information, it enabled the comparison of the two extraction protocols as well as the development of very good predictive models of patient's survivability, such as the UPLC-MS/MS platform. Furthermore, FTIR spectroscopy is based on much simpler procedures and is rapid, economic, and applicable in the high-throughput mode, i.e., enabling the simultaneous analysis of hundreds of samples in the microliter range in a couple of hours. Therefore, FTIR spectroscopy represents a very interesting complementary technique not only to optimize processes as the metabolome isolation but also for obtaining biomarkers such as those for disease prognosis.
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Affiliation(s)
- Tiago
A. H. Fonseca
- Instituto
Superior de Engenharia de Lisboa (ISEL), Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Cristiana P. Von Rekowski
- Instituto
Superior de Engenharia de Lisboa (ISEL), Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - Rúben Araújo
- Instituto
Superior de Engenharia de Lisboa (ISEL), Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
| | - M. Conceição Oliveira
- Centro
de Química Estrutural, Institute of Molecular Sciences, Instituto
Superior Técnico, Universidade de
Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal
| | - Gonçalo
C. Justino
- Centro
de Química Estrutural, Institute of Molecular Sciences, Instituto
Superior Técnico, Universidade de
Lisboa, Av. Rovisco Pais, 1, 1049-001 Lisboa, Portugal
| | - Luís Bento
- Intensive
Care Department, Centro Hospitalar Universitário
de Lisboa Central (CHULC), Rua José António Serrano, 1150-199 Lisboa, Portugal
- Integrated
Pathophysiological Mechanisms, CHRC, NOVA Medical School, Faculdade
de Ciências Médicas, NMS, FCM, Universidade NOVA de Lisboa, Campo Mártires da Pátria, 130, 1169-056 Lisboa, Portugal
| | - Cecília R. C. Calado
- Instituto
Superior de Engenharia de Lisboa (ISEL), Instituto Politécnico de Lisboa, Rua Conselheiro Emídio Navarro 1, 1959-007 Lisboa, Portugal
- Centro
de Investigação em Modelação e Optimização
de Sistemas Multifuncionais (CIMOSM), Instituto Superior de Engenharia
de Lisboa (ISEL), Instituto Politécnico
de Lisboa, Rua Conselheiro
Emídio Navarro 1, 1959-007 Lisboa, Portugal
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10
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Rajarathinam T, Thirumalai D, Jayaraman S, Kim S, Kwon M, Paik HJ, Kim S, Kang M, Chang SC. Enzyme Nanosheet-Based Electrochemical Aspartate Biosensor for Fish Point-of-Care Applications. MICROMACHINES 2022; 13:1428. [PMID: 36144051 PMCID: PMC9505169 DOI: 10.3390/mi13091428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 08/26/2022] [Accepted: 08/27/2022] [Indexed: 06/16/2023]
Abstract
Bacterial infections in marine fishes are linked to mass mortality issues; hence, rapid detection of an infection can contribute to achieving a faster diagnosis using point-of-care testing. There has been substantial interest in identifying diagnostic biomarkers that can be detected in major organs to predict bacterial infections. Aspartate was identified as an important biomarker for bacterial infection diagnosis in olive flounder (Paralichthys olivaceus) fish. To determine aspartate levels, an amperometric biosensor was designed based on bi-enzymes, namely, glutamate oxidase (GluOx) and aspartate transaminase (AST), which were physisorbed on copolymer reduced graphene oxide (P-rGO), referred to as enzyme nanosheets (GluOx-ASTENs). The GluOx-ASTENs were drop casted onto a Prussian blue electrodeposited screen-printed carbon electrode (PB/SPCE). The proposed biosensor was optimized by operating variables including the enzyme loading amount, coreactant (α-ketoglutarate) concentration, and pH. Under optimal conditions, the biosensor displayed the maximum current responses within 10 s at the low applied potential of -0.10 V vs. the internal Ag/AgCl reference. The biosensor exhibited a linear response from 1.0 to 2.0 mM of aspartate concentrations with a sensitivity of 0.8 µA mM-1 cm-2 and a lower detection limit of approximately 500 µM. Moreover, the biosensor possessed high reproducibility, good selectivity, and efficient storage stability.
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Affiliation(s)
- Thenmozhi Rajarathinam
- Department of Cogno-Mechatronics Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Busan 46241, Korea
| | - Dinakaran Thirumalai
- Department of Cogno-Mechatronics Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Busan 46241, Korea
| | - Sivaguru Jayaraman
- Department of Cogno-Mechatronics Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Busan 46241, Korea
| | - Seonghye Kim
- Department of Chemistry, Pusan National University, Busan 46241, Korea
| | - Minho Kwon
- Department of Polymer Science and Engineering, Pusan National University, Busan 46241, Korea
| | - Hyun-jong Paik
- Department of Polymer Science and Engineering, Pusan National University, Busan 46241, Korea
| | - Suhkmann Kim
- Department of Chemistry, Pusan National University, Busan 46241, Korea
| | - Mijeong Kang
- Department of Cogno-Mechatronics Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Busan 46241, Korea
| | - Seung-Cheol Chang
- Department of Cogno-Mechatronics Engineering, College of Nanoscience and Nanotechnology, Pusan National University, Busan 46241, Korea
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11
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Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection. Proteomes 2022; 10:proteomes10030024. [PMID: 35893765 PMCID: PMC9326686 DOI: 10.3390/proteomes10030024] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/27/2022] [Accepted: 06/28/2022] [Indexed: 02/07/2023] Open
Abstract
Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.
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