Human Milk Oligosaccharides: Potential Applications in COVID-19

Coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) has become a global health crisis with more than four million deaths worldwide. A substantial number of COVID-19 survivors continue suffering from long-COVID syndrome, a long-term complication exhibiting chronic inflammation and gut dysbiosis. Much effort is being expended to improve therapeutic outcomes. Human milk oligosaccharides (hMOS) are non-digestible carbohydrates known to exert health benefits in breastfed infants by preventing infection, maintaining immune homeostasis and nurturing healthy gut microbiota. These beneficial effects suggest the hypothesis that hMOS might have applications in COVID-19 as receptor decoys, immunomodulators, mucosal signaling agents, and prebiotics. This review summarizes hMOS biogenesis and classification, describes the possible mechanisms of action of hMOS upon different phases of SARS-CoV-2 infection, and discusses the challenges and opportunities of hMOS research for clinical applications in COVID-19

Supplementary Material for: Unravelling Pathophysiology of Crystalline Nephropathy in Ceftriaxone-Associated Acute Kidney Injury: A Cellular Proteomic Approach

<b><i>Background:</i></b> Previous studies showed that ceftriaxone can cause acute kidney injury (AKI) in the pediatric population. This study proposed a cellular model of crystalline nephropathy in ceftriaxone-associated AKI and explored the related pathophysiology by using a proteomic approach. <b><i>Methods:</i></b> Ceftriaxone was crystallized with calcium in artificial urine. Madin-Darby Canine Kidney (MDCK) cells, a model of distal renal tubular cell, were cultured in the absence (untreated control) or presence of ceftriaxone crystals for 48-h (<i>n</i> = 5 each). MDCK cells were harvested and subsequently analyzed by proteomic analysis. Protein bioinformatics (i.e., STRING and Reactome) was used to predict functional alterations, and subsequently validated by Western blotting and cellular studies. <i>p <</i> 0.05 was considered statistically significant. <b><i>Results:</i></b> Phase-contrast microscopy showed increased intracellular vesiculation and cell enlargement as a result of ceftriaxone crystal exposure. Proteome analysis revealed a total of 20 altered proteins (14 increased, 5 decreased and 1 absent) in ceftriaxone crystal-treated MDCK cells as compared to untreated cells (<i>p</i> < 0.05). Protein bioinformatics and validation studies supported heat stress response mediated by heat shock protein 70 (Hsp70) and downregulation of annexin A1 as the proposed pathophysiology of crystalline nephropathy in ceftriaxone-associated AKI, in which impaired proliferation and wound healing of crystal-induced distal tubular cells were outcomes. <b><i>Conclusions:</i></b> This study, for the first time, used the in vitro model of crystalline nephropathy to investigate the underlying pathophysiology of ceftriaxone-associated AKI, which should be investigated in vivo for potential clinical benefits in the future

Translational Proteomic Approach for Cholangiocarcinoma Biomarker Discovery, Validation, and Multiplex Assay Development: A Pilot Study

Cholangiocarcinoma (CCA) is a highly lethal disease because most patients are asymptomatic until they progress to advanced stages. Current CCA diagnosis relies on clinical imaging tests and tissue biopsy, while specific CCA biomarkers are still lacking. This study employed a translational proteomic approach for the discovery, validation, and development of a multiplex CCA biomarker assay. In the discovery phase, label-free proteomic quantitation was performed on nine pooled plasma specimens derived from nine CCA patients, nine disease controls (DC), and nine normal individuals. Seven proteins (S100A9, AACT, AFM, and TAOK3 from proteomic analysis, and NGAL, PSMA3, and AMBP from previous literature) were selected as the biomarker candidates. In the validation phase, enzyme-linked immunosorbent assays (ELISAs) were applied to measure the plasma levels of the seven candidate proteins from 63 participants: 26 CCA patients, 17 DC, and 20 normal individuals. Four proteins, S100A9, AACT, NGAL, and PSMA3, were significantly increased in the CCA group. To generate the multiplex biomarker assays, nine machine learning models were trained on the plasma dynamics of all seven candidates (All-7 panel) or the four significant markers (Sig-4 panel) from 45 of the 63 participants (70%). The best-performing models were tested on the unseen values from the remaining 18 (30%) of the 63 participants. Very strong predictive performances for CCA diagnosis were obtained from the All-7 panel using a support vector machine with linear classification (AUC = 0.96; 95% CI 0.88–1.00) and the Sig-4 panel using partial least square analysis (AUC = 0.94; 95% CI 0.82–1.00). This study supports the use of the composite plasma biomarkers measured by clinically compatible ELISAs coupled with machine learning models to identify individuals at risk of CCA. The All-7 and Sig-4 assays for CCA diagnosis should be further validated in an independent prospective blinded clinical study

Pharmacological Activities of Fingerroot Extract and Its Phytoconstituents Against SARS-CoV-2 Infection in Golden Syrian Hamsters [Corrigendum]

Kongratanapasert T, Kongsomros S, Arya N, et al. J Exp Pharmacol. 2023;15:13&#x2013;26. Page 19, line two, the text &#x201C;510.25 &#x00B1; 329.37 and 2015.74 &#x00B1; 708.53 &#x03BC;g/g&#x201D; should read &#x201C;510.25 &#x00B1; 329.37 and 2015.74 &#x00B1; 708.53 &#x03BC;g/kg&#x201D;. Page 19, Table 2, column 1, the text &#x201C;Lung (&#x03BC;g/g tissue)&#x201D; should read &#x201C;Lung (&#x03BC;g/kg tissue)&#x201D; The correct Table 2 is as follows. Table 2 The Concentration of Panduratin A in Plasma and Lung Tissues The authors apologize for these errors