Clinical and diagnostic implications of Alzheimer's disease copathology in Lewy body disease.

Concomitant Alzheimer's disease (AD) pathology is a frequent event in the context of Lewy body disease (LBD), occurring in approximately half of all cases. Evidence shows that LBD patients with AD copathology show an accelerated disease course, a greater risk of cognitive decline and an overall poorer prognosis. However, LBD-AD cases may show heterogeneous motor and non-motor phenotypes with higher risk of dementia, and, consequently, be not rarely misdiagnosed. In this review, we summarize the state-of-the-art on LBD-AD by discussing the synergistic effects between AD neuropathological changes and Lewy pathology and their clinical relevance. Furthermore, we provide an extensive overview of neuroimaging and fluid biomarkers under assessment in LBD-AD and their possible diagnostic and prognostic value. AD pathology can be suspected in vivo by means of CSF, MRI and PET markers, whereas α-synuclein seed amplification assays (SAAs) represent to date the most promising technique to identify Lewy pathology in different biological tissues. Pathological imaging and CSF AD biomarkers are associated with a higher likelihood of cognitive decline in LBD but do not always mirror the neuropathological severity like in pure AD. The implementation of blood-based biomarkers of AD might allow the fast screening of LBD patients for AD copathology, thus improving the overall diagnostic sensitivity for LBD-AD. Finally, we discuss the literature on novel candidate biomarkers being exploited in LBD-AD to investigate other aspects of neurodegeneration, such as neuroaxonal injury, glial activation and synaptic dysfunction. The thorough characterization of AD copathology in LBD should be taken into account for the differential diagnosis of dementia syndromes, for the prognostic evaluation on an individual level and for guiding symptomatic and disease-modifying therapies.

Adjusting for dilution in wastewater using biomarkers: A practical approach.

We developed a biomarker-based approach to quantify in-sewer dilution by measuring wastewater quality parameters (ammoniacal-N, orthophosphate, crAssphage). This approach can enhance the environmental management of wastewater treatment works (WWTW) by optimising their operation and providing cost-effective information on the health and behaviour of populations and their interactions with the environment through wastewater-based epidemiology (WBE). Our method relies on site specific baselines calculated for each biomarker. These baselines reflect the sewer conditions without the influence of rainfall-derived inflow and infiltration (RDII). Ammoniacal-N was the best candidate to use as proxy for dilution. We demonstrated that the dilution calculated using biomarkers correlates well with the dilution indicated by measured flow. In some instances, the biomarkers showed much higher dilution than measured flows. These differences were attributed to the loss of flow volume at wastewater treatment works due to the activation of combined sewer overflows (CSOs) and/or storm tanks. Using flow measured directly at the WWTW could therefore result in underestimation of target analyte loads.

Enhancing stroke risk and prognostic timeframe assessment with deep learning and a broad range of retinal biomarkers.

Stroke stands as a major global health issue, causing high death and disability rates and significant social and economic burdens. The effectiveness of existing stroke risk assessment methods is questionable due to their use of inconsistent and varying biomarkers, which may lead to unpredictable risk evaluations. This study introduces an automatic deep learning-based system for predicting stroke risk (both ischemic and hemorrhagic) and estimating the time frame of its occurrence, utilizing a comprehensive set of known retinal biomarkers from fundus images. Our system, tested on the UK Biobank and DRSSW datasets, achieved AUROC scores of 0.83 (95% CI: 0.79-0.85) and 0.93 (95% CI: 0.9-0.95), respectively. These results not only highlight our system's advantage over established benchmarks but also underscore the predictive power of retinal biomarkers in assessing stroke risk and the unique effectiveness of each biomarker. Additionally, the correlation between retinal biomarkers and cardiovascular diseases broadens the potential application of our system, making it a versatile tool for predicting a wide range of cardiovascular conditions.

Derivative spectrophotometry-assisted determination of tryptophan metabolites emerges host and intestinal flora dysregulations during sepsis.

Sepsis is a life-threatening condition characterized by organ dysfunction resulting from a dysregulated host response to infection. Dysregulated tryptophan (TRP) metabolites serve as significant indicators for endogenous immune turnovers and abnormal metabolism in the intestinal microbiota during sepsis. Therefore, a high coverage determination of TRP and its metabolites in sepsis is beneficial for the diagnosis and prognosis of sepsis, as well as for understanding the underlying mechanism of sepsis development. However, similar structures in TRP metabolites make it challenging for separation and metabolite identification. Here, high-performance liquid chromatography coupled with a diode array detector (HPLC-DAD) was developed to determine TRP metabolites in rat serum. The first-order derivative spectrophotometry of targeted metabolites in the serum was investigated and proved to be promising for chromatographic peak annotation across different columns and systems. The established method separating the targeted metabolites was optimized and validated to be sensitive and accurate. Application of the method revealed dysregulated TRP metabolites, associated with immune disorders and NAD+ metabolism in both the host and gut flora in septic rats. Our findings indicate that the derivative spectrophotometry-assisted method enhances metabolite identifications for the chromatographic systems based on DAD detectors and holds promise for precision medicine in sepsis.

A Brief Review on Recent Advances in Diagnostic and Therapeutic Applications of Extracellular Vesicles in Cardiovascular Disease.

Extracellular vesicles (EVs) are important mediators of intercellular communication within the cardiovascular system, playing essential roles in physiological homeostasis and contributing to the pathogenesis of various cardiovascular diseases (CVDs). However, their potential as diagnostic biomarkers and therapeutic agents in rare cardiovascular diseases, such as valvular heart disease (VHD) and cardiomyopathies, remains largely unexplored. This review comprehensively emphasizes recent advancements in extracellular vesicle research, explicitly highlighting their growing significance in diagnosing and potentially treating rare cardiovascular diseases, with a particular focus on valvular heart disease and cardiomyopathies. We highlight the potential of extracellular vesicle-based liquid biopsies as non-invasive tools for early disease detection and risk stratification, showcasing specific extracellular vesicle-associated biomarkers (proteins, microRNAs, lipids) with diagnostic and prognostic value. Furthermore, we discussed the therapeutic promise of extracellular vesicles derived from various sources, including stem cells and engineered extracellular vesicles, for cardiac repair and regeneration through their ability to modulate inflammation, promote angiogenesis, and reduce fibrosis. By integrating the findings and addressing critical knowledge gaps, this review aims to stimulate further research and innovation in extracellular vesicle-based diagnostics and therapeutics of cardiovascular disease.

Relevance of plasma lenvatinib concentrations and endogenous urinary cytochrome P450 3A activity biomarkers in clinical practice.

Lenvatinib (LEN), a multitarget tyrosine kinase inhibitor used in various cancer treatments, is mainly metabolized by cytochrome P450 3A (CYP3A) enzymes. The importance of therapeutic drug monitoring (TDM) in patients administered LEN has been proposed. Although some biomarkers of endogenous CYP3A activity have been reported, their utility in dosage adjustments has not been well evaluated. This study investigated the correlation between plasma LEN concentrations and endogenous urinary CYP3A biomarkers in clinical practice. Concentrations of plasma LEN (N = 225) and CYP3A biomarkers (cortisol, 6ß-hydroxycortisol, deoxycholic acid, and 1ß-hydroxydeoxycholic acid) in urine (N = 214) from 20 patients (hepatocellular carcinoma, N = 6; thyroid cancer, N = 3; endometrial cancer, N = 8; and renal cell carcinoma, N = 3) collected for consultation for up to 1 year were evaluated using liquid chromatography-tandem mass spectrometry. Moreover, plasma trough LEN concentrations were predicted using a three-compartment model with linear elimination for outpatients administered LEN before sample collection. Moderate correlations were observed between the quantified actual concentrations and the predicted trough concentrations of LEN, whereas there was no correlation with endogenous urinary CYP3A biomarkers. The utility of endogenous urinary CYP3A biomarkers could not be determined. However, TDM for outpatients administered orally available medicines may be predicted using a nonlinear mixed effect model (NONMEM). This study investigated the utility of endogenous urinary CYP3A biomarkers for personalized medicine and NONMEM for predicting plasma trough drug concentrations. These findings will provide important information for further clinical investigation and detailed TDM.

The electroretinography to identify biomarkers of idiopathic hypersomnia and narcolepsy type 1.

Hypersomnia spectrum disorders are underdiagnosed and poorly treated due to their heterogeneity and absence of biomarkers. The electroretinography has been proposed as a proxy of central dysfunction and has proved to be valuable to differentiate certain psychiatric disorders. Hypersomnolence is a shared core feature in central hypersomnia and psychiatric disorders. We therefore aimed to identify biomarkers by studying the electroretinography profile in patients with narcolepsy type 1, idiopathic hypersomnia and in controls. Cone, rod and retinal ganglion cells electrical activity were recorded with flash-electroretinography in non-dilated eye of 31 patients with idiopathic hypersomnia (women 84%, 26.6 ± 5.9 years), 19 patients with narcolepsy type 1 (women 63%, 36.6 ± 12.7 years) and 43 controls (women 58%, 30.6 ± 9.3 years). Reduced cone a-wave amplitude (p = 0.039) and prolonged cone (p = 0.022) and rod b-wave (p = 0.009) latencies were observed in patients with narcolepsy type 1 as compared with controls, while prolonged photopic negative response-wave latency (retinal ganglion cells activity) was observed in patients with idiopathic hypersomnia as compared with controls (p = 0.033). The rod and cone b-wave latency clearly distinguished narcolepsy type 1 from idiopathic hypersomnia and controls (area under the curve > 0.70), and the photopic negative response-wave latency distinguished idiopathic hypersomnia and narcolepsy type 1 from controls with an area under the curve > 0.68. This first original study shows electroretinography anomalies observed in patients with hypersomnia. Narcolepsy type 1 is associated with impaired cone and rod responses, whereas idiopathic hypersomnia is associated with impaired retinal ganglion cells response, suggesting different phototransduction alterations in both hypersomnias. Although these results need to be confirmed with a larger sample size, the electroretinography may be a promising tool for clinicians to differentiate hypersomnia subtypes.

Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma.

Background: Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. Materials and Methods: The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Results: Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Conclusion: Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.

Influence of acute heat shock on antioxidant defense of tropical fish, Psalidodon bifasciatus.

Psalidodon bifasciatus is a fish species sensitive to physical and chemical changes in water. It serves as a good bioindicator of temperature variations and is utilized in environmental monitoring studies in Brazilian rivers. The objective of this study was to evaluate antioxidant defense biomarkers in the heart, brain, and muscle of P. bifasciatus exposed to a 10 °C thermal increase. P. bifasciatus were collected and divided into a control group (21 °C) and groups subjected to thermal shock (31 °C) for periods of 2, 6, 12, 24, and 48h. Two-way ANOVA indicated that a 10 °C temperature increase caused oxidative stress in P. bifasciatus. This was evidenced by altered levels of lipid peroxidation (LPO), carbonylated proteins (PCO), and glutathione peroxidase (GPx) in the heart, catalase (CAT) and LPO in the brain, and LPO in the muscle. Principal component analysis (PCA) and integrated biomarker response (IBR) analysis indicated that, compared to the heart and muscle, the brain exhibited a greater activation of the antioxidant response. Sensitivity analysis indicated that the muscle was the most sensitive organ, followed by the brain and heart. Our results indicate that the stress response is tissue-specific through the activation of distinct mechanisms. These responses may be associated with the tissue's function as well as its energy demand. As expected, P. bifasciatus showed changes in response to thermal stress, with the brain showing the greatest alteration in antioxidant defenses and the muscle being the most sensitive tissue.

[Identification of potential biomarkers and immunoregulatory mechanisms of rheumatoid arthritis based on multichip co-analysis of GEO database].

OBJECTIVE: To identify the biomarkers for early rheumatoid arthritis (RA) diagnosis and explore the possible immune regulatory mechanisms. METHODS: The differentially expressed genesin RA were screened and functionally annotated using the limma, RRA, batch correction, and clusterProfiler. The protein-protein interaction network was retrieved from the STRING database, and Cytoscape 3.8.0 and GeneMANIA were used to select the key genes and predicting their interaction mechanisms. ROC curves was used to validate the accuracy of diagnostic models based on the key genes. The disease-specific immune cells were selected via machine learning, and their correlation with the key genes were analyzed using Corrplot package. Biological functions of the key genes were explored using GSEA method. The expression of STAT1 was investigated in the synovial tissue of rats with collagen-induced arthritis (CIA). RESULTS: We identified 9 core key genes in RA (CD3G, CD8A, SYK, LCK, IL2RG, STAT1, CCR5, ITGB2, and ITGAL), which regulate synovial inflammation primarily through cytokines-related pathways. ROC curve analysis showed a high predictive accuracy of the 9 core genes, among which STAT1 had the highest AUC (0.909). Correlation analysis revealed strong correlations of CD3G, ITGAL, LCK, CD8A, and STAT1 with disease-specific immune cells, and STAT1 showed the strongest correlation with M1-type macrophages (R=0.68, P=2.9e-08). The synovial tissues of the ankle joints of CIA rats showed high expressions of STAT1 and p-STAT1 with significant differential expression of STAT1 between the nucleus and the cytoplasm of the synovial fibroblasts. The protein expressions of p-STAT1 and STAT1 in the cell nuclei were significantly reduced after treatment. CONCLUSION: CD3G, CD8A, SYK, LCK, IL2RG, STAT1, CCR5, ITGB2, and ITGAL may serve as biomarkers for early diagnosis of RA. Gene-immune cell pathways such as CD3G/CD8A/LCK-γδ T cells, ITGAL-Tfh cells, and STAT1-M1-type macrophages may be closely related with the development of RA.

The impact of heat stress on the human plasma lipidome.

The year of 2023 displayed the highest average global temperatures since it has been recorded-the duration and severity of extreme heat are projected to increase. Rising global temperatures represent a major public health threat, especially to occupations exposed to hot environments, such as construction and agricultural workers, and first responders. Despite efforts of the scientific community, there is still a need to characterize the pathophysiological processes leading to heat related illness and develop biomarkers that can predict its onset. Here, we performed a plasma lipidomic analysis on male and female subjects who underwent heat tolerance testing (HTT), consisting of a 2-h treadmill walk at 5 km/h with 2% inclination at a controlled temperature of 40°C. We identified 995 lipids from 27 classes, with nearly half of all detected lipids being responsive to HTT. Lipid classes related to substrate utilization were predominantly affected by HTT, with a downregulation of triacylglycerols and upregulation of free fatty acids and acyl-carnitines (CARs). We additionally examined correlations between changes in plasma lipids by using the physiological strain index (PSI). Here, even chain CAR 4:0, 14:0 and 16:1, suggested by-products of incomplete beta oxidation, and diacylglycerols displayed the highest correlation to PSI. PSI did not correlate with plasma lactate levels, suggesting that correlations between even chain CARs and PSI is related to metabolic efficiency versus physical exertion. Overall, our results show that HTT has a strong impact on the plasma lipidome and that metabolic inefficiencies may underlie heat intolerance.

Identification of retinal oligomeric, citrullinated, and other tau isoforms in early and advanced AD and relations to disease status.

This study investigates various pathological tau isoforms in the retina of individuals with early and advanced Alzheimer's disease (AD), exploring their connection with disease status. Retinal cross-sections from predefined superior-temporal and inferior-temporal subregions and corresponding brains from neuropathologically confirmed AD patients with a clinical diagnosis of either mild cognitive impairment (MCI) or dementia (n = 45) were compared with retinas from age- and sex-matched individuals with normal cognition (n = 30) and non-AD dementia (n = 4). Retinal tau isoforms, including tau tangles, paired helical filament of tau (PHF-tau), oligomeric-tau (Oligo-tau), hyperphosphorylated-tau (p-tau), and citrullinated-tau (Cit-tau), were stereologically analyzed by immunohistochemistry and Nanostring GeoMx digital spatial profiling, and correlated with clinical and neuropathological outcomes. Our data indicated significant increases in various AD-related pretangle tau isoforms, especially p-tau (AT8, 2.9-fold, pS396-tau, 2.6-fold), Cit-tau at arginine residue 209 (CitR209-tau; 4.1-fold), and Oligo-tau (T22+, 9.2-fold), as well as pretangle and mature tau tangle forms like MC-1-positive (1.8-fold) and PHF-tau (2.3-fold), in AD compared to control retinas. MCI retinas also exhibited substantial increases in Oligo-tau (5.2-fold), CitR209-tau (3.5-fold), and pS396-tau (2.2-fold). Nanostring GeoMx analysis confirmed elevated retinal p-tau at epitopes: Ser214 (2.3-fold), Ser396 (2.6-fold), Ser404 (2.4-fold), and Thr231 (1.8-fold), particularly in MCI patients. Strong associations were found between retinal tau isoforms versus brain pathology and cognitive status: a) retinal Oligo-tau vs. Braak stage, neurofibrillary tangles (NFTs), and CDR cognitive scores (ρ = 0.63-0.71), b) retinal PHF-tau vs. neuropil threads (NTs) and ABC scores (ρ = 0.69-0.71), and c) retinal pS396-tau vs. NTs, NFTs, and ABC scores (ρ = 0.67-0.74). Notably, retinal Oligo-tau strongly correlated with retinal Aß42 and arterial Aß40 forms (r = 0.76-0.86). Overall, this study identifies and quantifies diverse retinal tau isoforms in MCI and AD patients, underscoring their link to brain pathology and cognition. These findings advocate for further exploration of retinal tauopathy biomarkers to facilitate AD detection and monitoring via noninvasive retinal imaging.

Plasma and CSF biomarkers of aging and cognitive decline in Caribbean vervets.

INTRODUCTION: Vervets are non-human primates that share high genetic homology with humans and develop amyloid beta (Aß) pathology with aging. We expand current knowledge by examining Aß pathology, aging, cognition, and biomarker proteomics. METHODS: Amyloid immunoreactivity in the frontal cortex and temporal cortex/hippocampal regions from archived vervet brain samples ranging from young adulthood to old age was quantified. We also obtained cognitive scores, plasma samples, and cerebrospinal fluid (CSF) samples in additional animals. Plasma and CSF proteins were quantified with platforms utilizing human antibodies. RESULTS: We found age-related increases in Aß deposition in both brain regions. Bioinformatic analyses assessed associations between biomarkers and age, sex, cognition, and CSF Aß levels, revealing changes in proteins related to immune-related inflammation, metabolism, and cellular processes. DISCUSSION: Vervets are an effective model of aging and early-stage Alzheimer's disease, and we provide translational biomarker data that both align with previous results in humans and provide a basis for future investigations. HIGHLIGHTS: We found changes in immune and metabolic plasma biomarkers associated with age and cognition. Cerebrospinal fluid (CSF) biomarkers revealed changes in cell signaling indicative of adaptative processes. TNFRSF19 (TROY) and Artemin co-localize with Alzheimer's disease pathology. Vervets are a relevant model for translational studies of early-stage Alzheimer's disease.

Application of Proteomics and Machine Learning Methods to Study the Pathogenesis of Diabetic Nephropathy and Screen Urinary Biomarkers.

Diabetic nephropathy (DN) has become the main cause of end-stage renal disease worldwide, causing significant health problems. Early diagnosis of the disease is quite inadequate. To screen urine biomarkers of DN and explore its potential mechanism, this study collected urine from 87 patients with type 2 diabetes mellitus (which will be classified into normal albuminuria, microalbuminuria, and macroalbuminuria groups) and 38 healthy subjects. Twelve individuals from each group were then randomly selected as the screening cohort for proteomics analysis and the rest as the validation cohort. The results showed that humoral immune response, complement activation, complement and coagulation cascades, renin-angiotensin system, and cell adhesion molecules were closely related to the progression of DN. Five overlapping proteins (KLK1, CSPG4, PLAU, SERPINA3, and ALB) were identified as potential biomarkers by machine learning methods. Among them, KLK1 and CSPG4 were positively correlated with the urinary albumin to creatinine ratio (UACR), and SERPINA3 was negatively correlated with the UACR, which were validated by enzyme-linked immunosorbent assay (ELISA). This study provides new insights into disease mechanisms and biomarkers for early diagnosis of DN.

Which is the best glomerular filtration marker: Creatinine, cystatin C or both?

BACKGROUND: The glomerular filtration rate (GFR) is estimated by the serum or plasma concentration of creatinine and/or cystatin C using equations that include demographic data. The equations worldwide most widely used are those of the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) consortium and updated in 2021 to remove the Afro-American racial correction factor. In 2021 and then in 2023, the European Kidney Function Consortium also developed equations based on creatinine and cystatin C, usable across the full age spectrum, and constructed by including the Q value (i.e. the median creatinine or cystatin C in healthy men and women, which is customizable for specific populations). METHODS: The aim of this narrative review is to examine the strengths and weaknesses of each biomarker. RESULTS: Both biomarkers have non-GFR determinants, namely muscle mass, protein intake and tubular secretion for creatinine; dysthyroidism and systemic corticosteroids for cystatin C, as well as other more debated determinants (diabetes, obesity, proteinuria, inflammatory syndrome). These non-GFR determinants are the reason why no equation based on a single endogenous biomarker has an accuracy within 30% greater than 90% over the entire age spectrum (in at least one patient in 10, estimated GFR is at least 30% higher or at least 30% lower than the measured GFR). CONCLUSION: Equations combining the two biomarkers provide a better estimate of GFR, particularly in the subgroup of patients whose estimates based on each of the biomarkers are highly discordant. These patients must also be identified as being at increased risk of morbidity, particularly cardiovascular, and mortality.

Baseline neutrophil-to-lymphocyte ratio as a predictor of response to hospitalized bronchiectasis exacerbation risks.

Background: Bronchiectasis is a disease with predominantly neutrophilic inflammation. As a readily available biomarker, there is little evidence to support the use of blood neutrophil-to-lymphocyte ratio (NLR) to predict bronchiectasis exacerbation severe enough to warrant hospitalization. Methods: A registry-based retrospective cohort study was conducted at a in Hong Kong. Chinese patients with non-cystic fibrosis (CF) bronchiectasis were retrospectively reviewed and subsequently followed up to investigate the association of NLR and the need for hospitalization for bronchiectasis exacerbation. Data on the NLR for patients in a clinically stable state in 2018 were collected and patients followed up from 1 January 2019 to 31 December 2022. The primary outcome was the need for hospitalization due to bronchiectasis exacerbation over the next 4 years. Results: We reviewed 473 Chinese patients with non-CF bronchiectasis, of whom 94 required hospitalization for bronchiectasis exacerbation during the 4-year follow-up period. Multi-variable logistic regression adjusted for E-FACED score (Exacerbation, Forced expiratory volume in 1 s (FEV1), Age, Chronic colonization, Extension, and Dyspnea score), gender, age, smoking status, and presence of co-existing chronic obstructive pulmonary disease (COPD) was conducted to compare patients with highest and lowest quartile NLR. Results revealed that those with NLR at the highest quartile were at increased risk of hospitalization for bronchiectasis exacerbation with an adjusted odds ratio (aOR) of 2.02 (95% confidence interval = 1.00-4.12, p = 0.05). Conclusion: Blood NLR may serve as a marker to predict the need for hospitalization due to bronchiectasis exacerbation.

Matricellular proteins: Potential biomarkers in head and neck cancer.

The extracellular matrix (ECM) is a complex network of diverse multidomain macromolecules, including collagen, proteoglycans, and fibronectin, that significantly contribute to the mechanical properties of tissues. Matricellular proteins (MCPs), as a family of non-structural proteins, play a crucial role in regulating various ECM functions. They exert their biological effects by interacting with matrix proteins, cell surface receptors, cytokines, and proteases. These interactions govern essential cellular processes such as differentiation, proliferation, adhesion, migration as well as multiple signal transduction pathways. Consequently, MCPs are pivotal in maintaining tissue homeostasis while orchestrating intricate molecular mechanisms within the ECM framework. The expression level of MCPs in adult steady-state tissues is significantly low; however, under pathological conditions such as inflammation and cancer, there is a substantial increase in their expression. In recent years, an increasing number of studies have focused on elucidating the role and significance of MCPs in the development and progression of head and neck cancer (HNC). During HNC progression, there is a remarkable upregulation in MCP expression. Through their distinctive structure and function, they actively promote tumor growth, invasion, epithelial-mesenchymal transition, and lymphatic metastasis of HNC cells. Moreover, by binding to integrins and modulating various signaling pathways, they effectively execute their biological functions. Furthermore, MCPs also hold potential as prognostic indicators. Although the star proteins of various MCPs have been extensively investigated, there remains a plethora of MCP family members that necessitate further scrutiny. This article comprehensively examines the functionalities of each MCP and highlights the research advancements in the context of HNC, with an aim to identify novel biomarkers for HNC and propose promising avenues for future investigations.

Advancing Surveillance Strategies for Hepatocellular Carcinoma: A New Era of Efficacy and Precision.

Hepatocellular carcinoma (HCC) is one of the few cancers with a 5-year survival that has remained below 20%; however, prognosis differs by tumor stage at diagnosis. Curative treatment options among patients with early-stage HCC afford a median survival of 5-10 years. Accordingly, international society guidelines recommend semi-annual HCC surveillance in at-risk patients, including those with cirrhosis or high-risk chronic hepatitis B infection. Surveillance is associated with increased early-stage HCC detection and curative treatments, leading to reduced HCC-related mortality. Abdominal ultrasound has been the cornerstone for HCC surveillance for the past two decades, but recent data have highlighted its suboptimal sensitivity for early-stage HCC detection, particularly in patients with obesity and those with non-viral etiologies of liver disease. The combination of ultrasound plus alpha fetoprotein (AFP) has higher sensitivity for early-stage HCC detection than ultrasound alone, although the combination still misses over one-third of HCC at an early stage. Emerging imaging and blood-based biomarker strategies have promising data in biomarker phase 2 (case-control) and phase 3 (cohort) studies. Beyond ultrasound, Magnetic resonance imaging (MRI) is the best-studied imaging strategy, with superior sensitivity and specificity compared to ultrasound in a cohort study. Abbreviated MRI protocols have been proposed to address concerns about MRI radiological capacity, costs, and patient acceptance. Of biomarker strategies, GALAD (a panel including gender, age, AFP, AFP-L3, and DCP) is the best validated, with promising sensitivity for early-stage HCC detection in a national multi-center cohort study. Liquid biopsy biomarkers, including methylated DNA markers, have also shown promising accuracy in case-control studies. Abbreviated MRI and GALAD are now entering prospective trials that examine clinical outcomes such as early-stage HCC detection and screening-related harms, which are essential data to understand for adoption in clinical practice. As additional surveillance strategies become available, it will allow an era of precision surveillance in which optimal surveillance modalities are tailored to individual patient risk and expected test performance.