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We present a method and a simple system for high-pH RP-LC peptide fractionation of small sample amounts (30–60 µg), at micro-flow rates with micro-liter fraction collection using ammonium bicarbonate as an optimized buffer for system stability and robustness. The method is applicable to targeted mass spectrometry approaches and to in-depth proteomic studies where the amount of sample is limited. Using targeted proteomics with peptide standards, we present the method's analytical parameters, and potential in increasing the detection of low-abundance proteins that are difficult to quantify with direct targeted or global LC-MS analyses. This fractionation system increased peptide signals by up to 18-fold, while maintaining high quantitative precision, with high fractionation reproducibility across varied sample sets. In real applications, it increased the detection of targeted endogenous peptides by two-fold in a 25 cell-cycle-control protein panel, and in-depth MS analyses of nuclear extracts, it allowed the detection of up to 8,896 proteins with 138,417 peptides in 24-concatenated fractions compared to 3,344 proteins with 23,093 peptides without fractionation. In a relevant biological problem of CDK4/6-inhibitors and breast cancer, the method reproduced known information and revealed novel insights, highlighting that it can be successfully applied in studies involving low-abundance proteins and limited samples. • Tested nine high-pH buffer/solvent systems to obtain a robust, effective, and reproducible micro-flow fractionation method which was devoid of commonly encountered LC clogging/pressure issues after months of use. • Peptide enrichment method to improve detection and quantitation of low-abundance proteins in targeted and in-depth proteomic studies. • Can be applied to diverse protein samples where the available amount is limited.

Thigmotaxis is an innate predator avoidance behaviour of rodents. To gain insight into how injury and disease models, and analgesic drug treatments affect thigmotaxis, we performed a systematic review and meta-analysis of studies that assessed thigmotaxis in the open field test. Systematic searches were conducted of 3 databases in October 2020, March and August 2022. Study design characteristics and experimental data were extracted and analysed using a random-effects meta-analysis. We also assessed the correlation between thigmotaxis and stimulus-evoked limb withdrawal. This review included the meta-analysis of 165 studies We report thigmotaxis was increased in injury and disease models associated with persistent pain and this increase was attenuated by analgesic drug treatments in both rat and mouse experiments. Its usefulness, however, may be limited in certain injury and disease models because our analysis suggested that thigmotaxis may be associated with the locomotor function. We also conducted subgroup analyses and meta-regression, but our findings on sources of heterogeneity are inconclusive because analyses were limited by insufficient available data. It was difficult to assess internal validity because reporting of methodological quality measures was poor, therefore, the studies have an unclear risk of bias. The correlation between time in the centre (type of a thigmotactic metric) and types of stimulus-evoked limb withdrawal was inconsistent. Therefore, stimulus-evoked and ethologically relevant behavioural paradigms should be viewed as two separate entities as they are conceptually and methodologically different from each other.

Abstract Pleural effusion (PE) is excess fluid in the pleural cavity that stems from lung cancer, other diseases like extra-pulmonary tuberculosis (TB) and pneumonia, or from a variety of benign conditions. Diagnosing its cause is often a clinical challenge and we have applied targeted proteomic methods with the aim of aiding the determination of PE etiology. We developed a mass spectrometry (MS)-based multiple reaction monitoring (MRM)-protein-panel assay to precisely quantitate 53 established cancer-markers, TB-markers, and infection/inflammation-markers currently assessed individually in the clinic, as well as potential biomarkers suggested in the literature for PE classification. Since MS-based proteomic assays are on the cusp of entering clinical use, we assessed the merits of such an approach and this marker panel based on a single-center 209 patient cohort with established etiology. We observed groups of infection/inflammation markers (ADA2, WARS, CXCL10, S100A9, VIM, APCS, LGALS1, CRP, MMP9, and LDHA) that specifically discriminate TB-PEs and other-infectious-PEs, and a number of cancer markers (CDH1, MUC1/CA-15-3, THBS4, MSLN, HPX, SVEP1, SPINT1, CK-18, and CK-8) that discriminate cancerous-PEs. Some previously suggested potential biomarkers did not show any significant difference. Using a Decision Tree/Multiclass classification method, we show a very good discrimination ability for classifying PEs into one of four types: cancerous-PEs (AUC: 0.863), tuberculous-PEs (AUC of 0.859), other-infectious-PEs (AUC of 0.863), and benign-PEs (AUC: 0.842). This type of approach and the indicated markers have the potential to assist in clinical diagnosis in the future, and help with the difficult decision on therapy guidance.