Non-invasive biomarkers for sperm retrieval in non-obstructive patients: a comprehensive review.

Recent advancements in reproductive medicine have guided novel strategies for addressing male infertility, particularly in cases of non-obstructive azoospermia (NOA). Two prominent invasive interventions, namely testicular sperm extraction (TESE) and microdissection TESE (micro-TESE), have emerged as key techniques to retrieve gametes for assisted reproduction technologies (ART). Both heterogeneity and complexity of NOA pose a multifaceted challenge to clinicians, as the invasiveness of these procedures and their unpredictable success underscore the need for more precise guidance. Seminal plasma can be aptly regarded as a liquid biopsy of the male reproductive tract, encompassing secretions from the testes, epididymides, seminal vesicles, bulbourethral glands, and prostate. This fluid harbors a variety of cell-free nucleic acids, microvesicles, proteins, and metabolites intricately linked to gonadal activity. However, despite numerous investigations exploring potential biomarkers from seminal fluid, their widespread inclusion into the clinical practice remains limited. This could be partially due to the complex interplay of diverse clinical and genetic factors inherent to NOA that likely contributes to the absence of definitive biomarkers for residual spermatogenesis. It is conceivable that the integration of clinical data with biomarkers could increase the potential in predicting surgical procedure outcomes and their choice in NOA cases. This comprehensive review addresses the challenge of sperm retrieval in NOA through non-invasive biomarkers. Moreover, we delve into promising perspectives, elucidating innovative approaches grounded in multi-omics methodologies, including genomics, transcriptomics and proteomics. These cutting-edge techniques, combined with the clinical and genetics features of patients, could improve the use of biomarkers in personalized medical approaches, patient counseling, and the decision-making continuum. Finally, Artificial intelligence (AI) holds significant potential in the realm of combining biomarkers and clinical data, also in the context of identifying non-invasive biomarkers for sperm retrieval.

Considerations for using potential surrogate endpoints in cancer screening trials.

The requirement of large-scale expensive cancer screening trials spanning decades creates considerable barriers to the development, commercialisation, and implementation of novel screening tests. One way to address these problems is to use surrogate endpoints for the ultimate endpoint of interest, cancer mortality, at an earlier timepoint. This Review aims to highlight the issues underlying the choice and use of surrogate endpoints for cancer screening trials, to propose criteria for when and how we might use such endpoints, and to suggest possible candidates. We present the current landscape and challenges, and discuss lessons and shortcomings from the therapeutic trial setting. It is hugely challenging to validate a surrogate endpoint, even with carefully designed clinical studies. Nevertheless, we consider whether there are candidates that might satisfy the requirements defined by research and regulatory bodies.

Droplet Microfluidics with Capillary Electrophoresis for Glycan Biomarker Analysis.

Several glycoproteins are validated biomarkers of various diseases such as cancer, cardiovascular diseases, chronic alcohol abuse, or congenital disorders of glycosylation (CDG). In particular, CDG represent a group of more than 150 inherited diseases with varied symptoms affecting multiple organs. The distribution of glycans from target glycoprotein(s) can be used to extract information to help the diagnosis and possibly differentiate subtypes of CDG. Indeed, depending on the glycans and the proteins to which they are attached, glycans can play a very broad range of roles in both physical and biological properties of glycoproteins. For glycans in general, capillary electrophoresis with laser-induced fluorescence detection (CE-LIF) has become a staple. Analysis of glycans with CE-LIF requires several sample preparation steps, including release of glycans from the target glycoprotein, fluorescent labeling of glycans, and purification of labeled glycans. Here, we describe the protocol for glycan sample treatment in a microfluidic droplet system prior to CE-LIF of labeled glycans. The microfluidic droplet approach offers full automation, sample, and reagent volume reduction and elimination of contamination from external environment.

High-throughput proteomic analysis of extracellular vesicles from saliva by chemical probe-based array.

Extracellular vesicles (EVs) are cell-released, nucleus-free particles with a double-membrane structure that effectively prevents degradation of internal components by a variety of salivary enzymes. Saliva is an easily accessible biofluid that contains a wealth of valuable information for disease diagnosis and monitoring and especially reflect respiratory and digestive tract diseases. However, the lack of efficient and high-throughput methods for proteomic analysis of salivary biomarkers poses a significant challenge. Herein, we designed a salivary EV amphiphile-dendrimer supramolecular probe (SEASP) array which enables efficient enrichment and in situ detection of EVs protein biomarkers. Detergent Tween-20 washing of SEASP arrays removes high abundance of heteroproteins from saliva well. This array shows good analytical performance in the linear range of 10 µL-150 µL (LOD = 0.4 µg protein, or 10 µL saliva), exhibiting a good recovery (80.0 %). Compared to ultracentrifugation (UC), this procedure provides simple and convenient access to high-purity EVs (1.3 × 109 particles per mg protein) with good physiological status and structure. Coupling with mass spectrometry based proteomic analysis, differentially expressed proteins as selected asthma biomarkers have been screened. Then, we validated the proteomics primary screening results through clinical samples (100 µL each) using the SEASP array. Utilizing the dual antibody fluorescence technology, SEASP enables the simultaneous high-throughput detection of two proteins. Therefore, the EVs marker protein CD81 could be used as an internal standard to normalize the number of EVs, which was stably expressed in EVs. Proteomics and array results suggested that HNRNPU (P = 4.9 * 10-6) and MUC5B (P = 4.7 * 10-11) are promising protein biomarkers for infantile asthma. HNRNPU and MUC5B may be associated with disease onset and subtypes. The SEASP arrays provide a significant advancement in the field of salivary biomarker. The array enables high-throughput in situ protein detection for highly viscous and complex biological samples. It provides a rapid, low-cost, highly specific screening procedure and experimental basis for early disease screening and diagnosis in the field of liquid biopsy.

MAFLD and glomerular hyperfiltration in subjects with normoglycemia, prediabetes and type 2 diabetes: A cross-sectional population study.

BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD, 2020 diagnostic criteria) and glomerular hyperfiltration share common risk factors, including obesity, insulin resistance, impaired glucose tolerance, diabetes, dyslipidemia, and hypertension. AIMS: To assess the prevalence of MAFLD and its association with glomerular hyperfiltration and age-related worsening of kidney function in subjects with normoglycemia, prediabetes and type 2 diabetes mellitus (T2DM). METHODS: We analysed data recorded during occupational health visits of 125,070 Spanish civil servants aged 18-65 years with a de-indexed glomerular filtration rate (GFR) estimated with the chronic-kidney-disease-epidemiological (CKD-EPI) equation (estimated glomerular filtration rate [eGFR]) ≥60 mL/min. Subjects were categorised according to fasting plasma glucose levels <100 mg/dL (normoglycemia), ≥100 and ≤ 125 mg/dL (prediabetes), or ≥126 mg/dL and/or antidiabetic treatment (T2DM). The association between MAFLD and glomerular hyperfiltration, defined as a de-indexed eGFR above the age- and gender-specific 95th percentile, was assessed by multivariable logistic regression. RESULTS: In the whole study group, MAFLD prevalence averaged 19.3%. The prevalence progressively increased from 14.7% to 33.2% and to 48.9% in subjects with normoglycemia, prediabetes and T2DM, respectively (p < 0.001 for trend). Adjusted odds ratio (95% CI) for the association between MAFLD and hyperfiltration was 9.06 (8.53-9.62) in the study group considered as a whole, and 8.60 (8.03-9.21), 9.52 (8.11-11.18) and 8.31 (6.70-10.30) in subjects with normoglycemia, prediabetes and T2DM considered separately. In stratified analyses, MAFLD amplified age-dependent eGFR decline in all groups (p < 0.001). CONCLUSIONS: MAFLD prevalence increases across the glycaemic spectrum. MAFLD is significantly associated with hyperfiltration and amplifies the age-related eGFR decline.

Diagnostic and prognostic significance of mast cell markers in HIV/AIDS: Current insights and future directions.

Human immunodeficiency virus (HIV) infection continues to pose significant global health challenges, necessitating advancements in diagnostic and prognostic approaches to optimize disease management. While primarily recognized for their roles in allergic responses, mast cells have emerged as potential markers with diagnostic and prognostic significance in the context of HIV/AIDS. This paper aims to synthesize current insights and delineate future directions regarding the utility of mast cell markers in diagnosing HIV infection, predicting disease progression, and guiding therapeutic strategies. Mast cells, equipped with distinct markers such as tryptase, chymase, carboxypeptidase A3, and c-kit/CD117 receptors, exhibit tissue-specific expression patterns that offer potential as diagnostic indicators for HIV infection. Understanding the dynamics of these markers in different tissues and body fluids holds promise for accurate HIV diagnosis, disease staging, and monitoring treatment responses. Moreover, the prognostic significance of mast cell markers in HIV/AIDS lies in their potential to predict disease progression, immune dysregulation, and clinical outcomes. The integration of mast cell markers into clinical applications offers promising avenues for refining diagnostic assays, patient monitoring protocols, and therapeutic strategies in HIV/AIDS. Future research directions involve the development of novel diagnostic tools and targeted therapies based on mast cell-specific markers, potentially revolutionizing clinical practice and enhancing patient care in the management of HIV/AIDS. Continued investigations into mast cell markers' diagnostic and prognostic implications hold immense potential to advance our understanding and improve outcomes in HIV/AIDS management.

Tear biomarkers.

An extensive exploration of lacrimal fluid molecular biomarkers in understanding and diagnosing a spectrum of ocular and systemic diseases is presented. The chapter provides an overview of lacrimal fluid composition, elucidating the roles of proteins, lipids, metabolites, and nucleic acids within the tear film. Pooled versus single-tear analysis is discussed to underline the benefits and challenges associated with both approaches, offering insights into optimal strategies for tear sample analysis. Subsequently, an in-depth analysis of tear collection methods is presented, with a focus on Schirmer's test strips and microcapillary tubes methods. Alternative tear collection techniques are also explored, shedding light on their applicability and advantages. Variability factors, including age, sex, and diurnal fluctuations, are examined in the context of their impact on tear biomarker analysis. The main body of the chapter is dedicated to discussing specific biomarkers associated with ocular discomfort and a wide array of ocular diseases. From dry eye disease and thyroid-associated ophthalmopathy to keratoconus, age-related macular degeneration, diabetic retinopathy, and glaucoma, the intricate relationship between molecular biomarkers and these conditions is thoroughly dissected. Expanding beyond ocular pathologies, the chapter explores the applicability of tear biomarkers in diagnosing systemic diseases such as multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, Parkinson's disease, and cancer. This broader perspective underscores the potential of lacrimal fluid analysis in offering non-invasive diagnostic tools for conditions with far-reaching implications.

Molecular fingerprinting of biological nanoparticles with a label-free optofluidic platform.

Label-free detection of multiple analytes in a high-throughput fashion has been one of the long-sought goals in biosensing applications. Yet, for all-optical approaches, interfacing state-of-the-art label-free techniques with microfluidics tools that can process small volumes of sample with high throughput, and with surface chemistry that grants analyte specificity, poses a critical challenge to date. Here, we introduce an optofluidic platform that brings together state-of-the-art digital holography with PDMS microfluidics by using supported lipid bilayers as a surface chemistry building block to integrate both technologies. Specifically, this platform fingerprints heterogeneous biological nanoparticle populations via a multiplexed label-free immunoaffinity assay with single particle sensitivity. First, we characterise the robustness and performance of the platform, and then apply it to profile four distinct ovarian cell-derived extracellular vesicle populations over a panel of surface protein biomarkers, thus developing a unique biomarker fingerprint for each cell line. We foresee that our approach will find many applications where routine and multiplexed characterisation of biological nanoparticles are required.

Clinical significance of pleural fluid lactate dehydrogenase/adenosine deaminase ratio in the diagnosis of tuberculous pleural effusion.

BACKGROUND: Pleural fluid is one of the common complications of thoracic diseases, and tuberculous pleural effusion (TPE) is the most common cause of pleural effusion in TB-endemic areas and the most common type of exudative pleural effusion in China. In clinical practice, distinguishing TPE from pleural effusion caused by other reasons remains a relatively challenging issue. The objective of present study was to explore the clinical significance of the pleural fluid lactate dehydrogenase/adenosine deaminase ratio (pfLDH/pfADA) in the diagnosis of TPE. METHODS: The clinical data of 618 patients with pleural effusion were retrospectively collected, and the patients were divided into 3 groups: the TPE group (412 patients), the parapneumonic pleural effusion (PPE) group (106 patients), and the malignant pleural effusion (MPE) group (100 patients). The differences in the ratios of pleural effusion-related and serology-related indicators were compared among the three groups, and receiver operating characteristic curves were drawn to analyze the sensitivity and specificity of the parameter ratios of different indicators for the diagnosis of TPE. RESULTS: The median serum ADA level was higher in the TPE group (13 U/L) than in the PPE group (10 U/L, P < 0.01) and MPE group (10 U/L, P < 0.001). The median pfADA level in the TPE group was 41 (32, 52) U/L; it was lowest in the MPE group at 9 (7, 12) U/L and highest in the PPE group at 43 (23, 145) U/L. The pfLDH level in the PPE group was 2542 (1109, 6219) U/L, which was significantly higher than that in the TPE group 449 (293, 664) U/L. In the differential diagnosis between TPE and non-TPE, the AUC of pfLDH/pfADA for diagnosing TPE was the highest at 0.946 (0.925, 0.966), with an optimal cutoff value of 23.20, sensitivity of 93.9%, specificity of 87.0%, and Youden index of 0.809. In the differential diagnosis of TPE and PPE, the AUC of pfLDH/pfADA was the highest at 0.964 (0.939, 0.989), with an optimal cutoff value of 24.32, sensitivity of 94.6%, and specificity of 94.4%; this indicated significantly better diagnostic efficacy than that of the single index of pfLDH. In the differential diagnosis between TPE and MPE, the AUC of pfLDH/pfADA was 0.926 (0.896, 0.956), with a sensitivity of 93.4% and specificity of 80.0%; this was not significantly different from the diagnostic efficacy of pfADA. CONCLUSIONS: Compared with single biomarkers, pfLDH/pfADA has higher diagnostic value for TPE and can identify patients with TPE early, easily, and economically.

Establishing breath as a biomarker platform-take home messages from the Breath Biopsy Conference 2023.

The annual Breath Biopsy Conference hosted by Owlstone Medical gathers together the leading experts, early career researchers, and physicians working with breath as a biomarker platform for clinical purposes. The current topics in breath research are discussed and presented, and an overarching topical theme is identified and discussed as part of an expert panel to close the conference. The profiling of normal breath composition and the establishment of standards for analyzing breath compared to background signal were two important topics that were major focuses of this conference, as well as important innovative progress that has been made since last year, including the development of a non-invasive breath test for lung cancer and liver disease. This meeting report offers an overview of the key take-home messages from the various presentations, posters, and discussions from the conference.

Python workflow for the selection and identification of marker peptides-proof-of-principle study with heated milk.

The analysis of almost holistic food profiles has developed considerably over the last years. This has also led to larger amounts of data and the ability to obtain more information about health-beneficial and adverse constituents in food than ever before. Especially in the field of proteomics, software is used for evaluation, and these do not provide specific approaches for unique monitoring questions. An additional and more comprehensive way of evaluation can be done with the programming language Python. It offers broad possibilities by a large ecosystem for mass spectrometric data analysis, but needs to be tailored for specific sets of features, the research questions behind. It also offers the applicability of various machine-learning approaches. The aim of the present study was to develop an algorithm for selecting and identifying potential marker peptides from mass spectrometric data. The workflow is divided into three steps: (I) feature engineering, (II) chemometric data analysis, and (III) feature identification. The first step is the transformation of the mass spectrometric data into a structure, which enables the application of existing data analysis packages in Python. The second step is the data analysis for selecting single features. These features are further processed in the third step, which is the feature identification. The data used exemplarily in this proof-of-principle approach was from a study on the influence of a heat treatment on the milk proteome/peptidome.

A comprehensive guide to extract information from extracellular vesicles: a tutorial review towards novel analytical developments.

In the medical field, extracellular vesicles (EVs) are gaining importance as they act as cells mediators. These are phospholipid bilayer vesicles and contain crucial biochemical information about their mother cells being carrier of different biomolecules such as small molecules, proteins, lipids, and nucleic acids. After release into the extracellular matrix, they enter the systemic circulation and can be found in all human biofluids. Since EVs reflect the state of the cell of origin, there is exponential attention as potential source of new circulating biomarkers for liquid biopsy. The use of EVs in clinical practice faces several challenges that need to be addressed: these include the standardization of lysis protocols, the availability of low-cost reagents and the development of analytical tools capable of detecting biomarkers. The process of lysis is a crucial step that can impact all subsequent analyses, towards the development of novel analytical strategies. To aid researchers to support the evolution of measurement science technology, this tutorial review evaluates and discuss the most commonly protocols used to characterize the contents of EVs, including their advantages and disadvantages in terms of experimental procedures, time and equipment. The purpose of this tutorial review is to offer practical guide to researchers which are intended to develop novel analytical approaches. Some of the most significant applications are considered, highlighting their main characteristics divided per mechanism of action. Finally, comprehensive tables which provide an overview at a glance are provided to readers.

The development of a novel zeolite-based assay for efficient and deep plasma proteomic profiling.

Plasma proteins are considered the most informative source of biomarkers for disease diagnosis and monitoring. Mass spectrometry (MS)-based proteomics has been applied to identify biomarkers in plasma, but the complexity of the plasma proteome and the extremely large dynamic range of protein abundances in plasma make the clinical application of plasma proteomics highly challenging. We designed and synthesized zeolite-based nanoparticles to deplete high-abundance plasma proteins. The resulting novel plasma proteomic assay can measure approximately 3000 plasma proteins in a 45 min chromatographic gradient. Compared to those in neat and depleted plasma, the plasma proteins identified by our assay exhibited distinct biological profiles, as validated in several public datasets. A pilot investigation of the proteomic profile of a hepatocellular carcinoma (HCC) cohort identified 15 promising protein features, highlighting the diagnostic value of the plasma proteome in distinguishing individuals with and without HCC. Furthermore, this assay can be easily integrated with all current downstream protein profiling methods and potentially extended to other biofluids. In conclusion, we established a robust and efficient plasma proteomic assay with unprecedented identification depth, paving the way for the translation of plasma proteomics into clinical applications.

Fast, sensitive LC-MS resolution of α -hydroxy acid biomarkers via SPP-teicoplanin and an alternative UV detection approach.

Enantioseparation of α -hydroxy acids is essential since specific enantiomers of these compounds can be used as disease biomarkers for diagnosis and prognosis of cancer, brain diseases, kidney diseases, diabetes, etc., as well as in the food industry to ensure quality. HPLC methods were developed for the enantioselective separation of 11 α -hydroxy acids using a superficially porous particle-based teicoplanin (TeicoShell) chiral stationary phase. The retention behaviors observed for the hydroxy acids were HILIC, reversed phase, and ion-exclusion. While both mass spectrometry and UV spectroscopy detection methods could be used, specific mobile phases containing ammonium formate and potassium dihydrogen phosphate, respectively, were necessary with each approach. The LC-MS mode was approximately two orders of magnitude more sensitive than UV detection. Mobile phase acidity and ionic strength significantly affected enantioresolution and enantioselectivity. Interestingly, higher ionic strength resulted in increased retention and enantioresolution. It was noticed that for formate-containing mobile phases, using acetonitrile as the organic modifier usually resulted in greater enantioresolution compared to methanol. However, sometimes using acetonitrile with high ammonium formate concentrations led to lengthy retention times which could be avoided by using methanol as the organic modifier. Additionally, the enantiomeric purities of single enantiomer standards were determined and it was shown that almost all standards contained some levels of enantiomeric impurities.

Application of fiber loop ringdown spectroscopy technique for a new approach to beta-amyloid monitoring for Alzheimer Disease's early detection.

A novel fiber optic biosensor was purposed for a new approach to monitor amyloid beta protein fragment 1-42 (Aß42) for Alzheimer's Disease (AD) early detection. The sensor was fabricated by etching a part of fiber from single mode fiber loop in pure hydrofluoric acid solution and utilized as a Local Optical Refractometer (LOR) to monitor the change Aß42 concentration in Artificial Cerebrospinal Fluid (ACSF). The Fiber Loop Ringdown Spectroscopy (FLRDS) technique is an ultra-sensitive measurement technique with low-cost, high sensitivity, real-time measurement, continuous measurement and portability features that was utilized with a fiber optic sensor for the first time for the detection of a biological signature in an ACSF environment. Here, the measurement is based on the total optical loss detection when specially fabricated sensor heads were immersed into ACSF solutions with and without different concentrations of Aß42 biomarkers since the bulk refractive index change was performed. Baseline stability and the reference ring down times of the sensor head were measured in the air as 0.87% and 441.6µs ± 3.9µs, respectively. Afterward, the total optical loss of the system was measured when the sensor head was immersed in deionized water, ACSF solution, and ACSF solutions with Aß42 in different concentrations. The lowest Aß42 concentration of 2 ppm was detected by LOR. Results showed that LOR fabricated by single-mode fibers for FLRDS system design are promising candidates to be utilized as fiber optic biosensors after sensor head modification and have a high potential for early detection applications of not only AD but possibly also several fatal diseases such as diabetes and cancer.

Biomarker profiling in plants to distinguish between exposure to chlorine gas and bleach using LC-HRMS/MS and chemometrics.

Since its first employment in World War I, chlorine gas has often been used as chemical warfare agent. Unfortunately, after suspected release, it is difficult to prove the use of chlorine as a chemical weapon and unambiguous verification is still challenging. Furthermore, similar evidence can be found for exposure to chlorine gas and other, less harmful chlorinating agents. Therefore, the current study aims to use untargeted high resolution mass spectrometric analysis of chlorinated biomarkers together with machine learning techniques to be able to differentiate between exposure of plants to various chlorinating agents. Green spire (Euonymus japonicus), stinging nettle (Urtica dioica), and feathergrass (Stipa tenuifolia) were exposed to 1000 and 7500 ppm chlorine gas and household bleach, pool bleach, and concentrated sodium hypochlorite. After sample preparation and digestion, the samples were analyzed by liquid chromatography high resolution tandem mass spectrometry (LC-HRMS/MS) and liquid chromatography tandem mass spectrometry (LC-MS/MS). More than 150 chlorinated compounds including plant fatty acids, proteins, and DNA adducts were tentatively identified. Principal component analysis (PCA) and linear discriminant analysis (LDA) showed clear discrimination between chlorine gas and bleach exposure and grouping of the samples according to chlorine concentration and type of bleach. The identity of a set of novel biomarkers was confirmed using commercially available or synthetic reference standards. Chlorodopamine, dichlorodopamine, and trichlorodopamine were identified as specific markers for chlorine gas exposure. Fenclonine (Cl-Phe), 3-chlorotyrosine (Cl-Tyr), 3,5-dichlorotyrosine (di-Cl-Tyr), and 5-chlorocytosine (Cl-Cyt) were more abundantly present in plants after chlorine contact. In contrast, the DNA adduct 2-amino-6-chloropurine (Cl-Ade) was identified in both types of samples at a similar level. None of these chlorinated biomarkers were observed in untreated samples. The DNA adducts Cl-Cyt and Cl-Ade could clearly be identified even three months after the actual exposure. This study demonstrates the feasibility of forensic biomarker profiling in plants to distinguish between exposure to chlorine gas and bleach.

Neutrophil-Creatinine Index: A New Prognostic Factor for Severity of Acute Pancreatitis.

Background and Objectives: Determining the severity of acute pancreatitis (AP) is the main goal in the early stage of AP. The aim of this study was to compare laboratory parameters and indices, including the neutrophil to lymphocyte ratio (NLR) and the neutrophil-creatinine index (NCI), at admission in order to predict the severity of AP. Materials and Methods: Data from 421 patients who were admitted with a diagnosis of AP were collected retrospectively. Disease severity was assessed using the Bedside Index of Severity in Acute Pancreatitis (BISAP) and the revised Atlanta classification (RAC). BISAP was graded as mild and severe, and RAC was graded as mild (MAP), moderately severe (MSAP), and severe (SAP). The laboratory parameters and indices, including the NLR and NCI, were compared. Results: Of the patients, 70 (16.6%) had severe AP according to BISAP; the AP subgroups according to the RAC were as follows: MAP (n = 213), MSAP (n = 158), and SAP (n = 50). The NCI had the highest area under the receiver operator characteristic (AUROC) curve value (0.862), demonstrating severe disease according to BISAP, with a sensitivity of 78.6% and a specificity of 79.8%. Age (OR:1.046), white blood cell count (WBC) (OR:1.141), hematocrit (OR:1.081), blood urea nitrogen (BUN) (OR:1.040), and NCI (OR:1.076) were independently associated with severe disease, according to the multivariate analysis results, and were determined as components of the newly developed nomogram. The AUROC of the nomogram (0.891) was superior to the AUROCs of all the components of the nomogram except the NCI. Moreover, the NCI was the only parameter to distinguish MSAP from MAP (OR:1.119, 95% CI: 1.015-1.235, p = 0.023) and SAP from MSAP (OR:1.095, 95% CI: 1.031-1.162, p = 0.003). Conclusions: The present study enabled the identification of the neutrophil-creatinine index as a new prognostic tool for the assessment of AP severity at hospital admission.

Dynamic simulation and experimental studies of molecularly imprinted label-free sensor for determination of milk quality marker.

Bovine serum albumin (BSA) has emerged as a biomarker for mammary gland health and cow quality, being recognized as a significant allergenic protein. In this study, a novel flexible molecular imprinted electrochemical sensor by surface electropolymerization using pyrrole (Py) as functional monomer, which can be better applied to the detection of milk quality marker BSA. Based on computational results, with regard to all polypyrrole (PPy) conformations and amino-acid positions within the protein, the BSA molecule remained firmly embedded into PPy polymers with no biological changes. The molecular imprinted electrochemical sensor displayed a broad linear detection range from 1.0 × 10-4 to 50 ng·mL-1 (R2 = 0.995) with a low detection limit (LOD) of 4.5 × 10-2 pg·mL-1. Additionally, the sensor was highly selective, reproducible, stable and recoverable, suggesting that it might be utilized for the evaluation of milk quality.

Two-stage stratified designs with survival outcomes and adjustment for misclassification in predictive biomarkers.

Biomarker stratified clinical trial designs are versatile tools to assess biomarker clinical utility and address its relationship with clinical endpoints. Due to imperfect assays and/or classification rules, biomarker status is prone to errors. To account for biomarker misclassification, we consider a two-stage stratified design for survival outcomes with an adjustment for misclassification in predictive biomarkers. Compared to continuous and/or binary outcomes, the test statistics for survival outcomes with an adjustment for biomarker misclassification is much more complicated and needs to take special care. We propose to use the information from the observed biomarker status strata to construct adjusted log-rank statistics for true biomarker status strata. These adjusted log-rank statistics are then used to develop sequential tests for the global (composite) hypothesis and component-wise hypothesis. We discuss the power analysis with the control of the type-I error rate by using the correlations between the adjusted log-rank statistics within and between the design stages. Our method is illustrated with examples of the recent successful development of immunotherapy in nonsmall-cell lung cancer.