The high complexity prevalent in biological samples requires chromatographic separations with high sensitivity and resolution to be effectively analyzed. Here we introduce a robust, reproducible and inexpensive protocol for preparation of a nano-flow reversed phase high performance liquid chromatography (RP-HPLC) columns for on-line separation of analytical peptides before introduction into and detection by a mass-spectrometer in traditional bottom-up proteomics workflows. Depending on the goal of the experiment and the chemical properties of the analytes being separated, optimal column parameters may differ in their internal or outer diameters, length, particle size, pore size, chemistry of stationary phase particles, and the presence or absence of an integrated electrospray emitter at the tip. An in-house column packing system not only enables the rapid fabrication of columns with the desired properties but also dramatically reduces the cost of the process. The optimized protocol for packing a C18 AQ (aqueous) fused silica column discussed here is compatible with a wide range of liquid chromatographic instruments for achieving effective separation of analytes.
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http://dx.doi.org/10.3791/62380 | DOI Listing |
J Cheminform
December 2024
Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy.
Ensuring the safety of chemicals for environmental and human health involves assessing physicochemical (PC) and toxicokinetic (TK) properties, which are crucial for absorption, distribution, metabolism, excretion, and toxicity (ADMET). Computational methods play a vital role in predicting these properties, given the current trends in reducing experimental approaches, especially those that involve animal experimentation. In the present manuscript, twelve software tools implementing Quantitative Structure-Activity Relationship (QSAR) models were selected for the prediction of 17 relevant PC and TK properties.
View Article and Find Full Text PDFEur J Med Res
December 2024
Department of Orthopedics, The Yangzhou School of Clinical Medicine of Dalian Medical University, Yangzhou, Jiangsu, China.
Objectives: To identify independent risk factors for perioperative hidden blood loss (HBL) in intertrochanteric femoral fractures (ITFs) and to develop a predictive model.
Methods: We enrolled 231 patients with ITFs who underwent proximal femoral nail antirotation (PFNA) surgery at the Orthopedics Department of Northern Jiangsu People's Hospital, Jiangsu Province, China, from January 2021 to December 2023. Hidden blood loss was calculated using the OSTEO formula, and independent risk factors were screened using the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression.
BMC Bioinformatics
December 2024
College of Computer Science and Technology, Inner Mongolia Minzu University, Tongliao, 028000, China.
As a heterogeneous disease, prostate cancer (PCa) exhibits diverse clinical and biological features, which pose significant challenges for early diagnosis and treatment. Metabolomics offers promising new approaches for early diagnosis, treatment, and prognosis of PCa. However, metabolomics data are characterized by high dimensionality, noise, variability, and small sample sizes, presenting substantial challenges for classification.
View Article and Find Full Text PDFBMC Public Health
December 2024
Center for Human Virology and Genomics, Nigerian Institute of Medical Research, Yaba, Lagos State, Nigeria.
Background: Wastewater-based epidemiology (WBE) is already being adopted for the surveillance of health conditions of communities and shows great potential for the monitoring of infectious pathogens of public health importance. There is however paucity of robust data to support extensive WBE in Nigeria. This study evaluated the prevalence of clinically relevant infectious pathogens and provided antimicrobial resistance profiles of bacteria pathogens in wastewater canals in Lagos State at a single point in time.
View Article and Find Full Text PDFJ Chin Med Assoc
December 2024
Department of Emergency Medicine, The Third Clinical Medical College of Ningxia Medical University, Ningxia, Yinchuan, China The Third Clinical Medical College of Ningxia Medical University, Ningxia,Yinchuan, China.
Background: COVID-19, caused by SARS-CoV-2, has had a significant impact on global health. While the virus primarily affects the respiratory system, the intricate interplay between immune cells and the virus remains poorly understood. This study investigates the causal relationship between 731 immune cell phenotypes and COVID-19 using Mendelian randomization analysis.
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