Diagnostic Monitoring Research Articles

Liquid biomarkers in prostate cancer: recent advancements and future directions.

Traditional diagnostic approaches of prostate cancer like PSA are limited by high false-positive rates and insufficient capture of tumour heterogeneity, necessitating the development of more precise tools. This review examines the latest advancements in liquid biomarkers for prostate cancer, focusing on their potential to refine diagnostic accuracy and monitor disease progression. Liquid biomarkers have gained prominence because of their minimally invasive nature and ability to reflect the molecular characteristics of prostate cancer. Circulating tumour cells provide insight into tumour cell dissemination and are indicative of aggressive disease phenotypes, with single-cell analyses revealing genomic instability and treatment resistance. Circulating tumour DNA offers real-time tumour genomic information, aiding in treatment decision-making in advanced prostate cancer, where it has been associated with clinical progression. MicroRNAs act as oncogenes or tumour suppressors and exhibit diagnostic and prognostic potential; however, their clinical utility is constrained by the lack of consistent validation. Extracellular vesicles contain tumour-derived biomolecules, with specific proteins demonstrating prognostic relevance. Applications of these markers to urinary testing have been demonstrated. Liquid biomarkers show potential in refining prostate cancer management. Future research should aim to integrate these biomarkers into a cohesive framework in line with precision medicine principles.

Transfer RNA-derived fragment tRF-23-Q99P9P9NDD promotes progression of gastric cancer by targeting ACADSB.

Gastric cancer (GC) is one of the most common gastrointestinal tumors. As a newly discovered type of non-coding RNAs, transfer RNA (tRNA)‍-derived small RNAs (tsRNAs) play a dual biological role in cancer. Our previous studies have demonstrated the potential of tRF-23-Q99P9P9NDD as a diagnostic and prognostic biomarker for GC. In this work, we confirmed for the first time that tRF-23-Q99P9P9NDD can promote the proliferation, migration, and invasion of GC cells in vitro. The dual luciferase reporter gene assay confirmed that tRF-23-Q99P9P9NDD could bind to the 3' untranslated region (UTR) site of acyl-coenzyme A dehydrogenase short/branched chain (ACADSB). In addition, ACADSB could rescue the effect of tRF-23-Q99P9P9NDD on GC cells. Next, we used Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Gene Set Enrichment Analysis (GSEA) to find that downregulated ACADSB in GC may promote lipid accumulation by inhibiting fatty acid catabolism and ferroptosis. Finally, we verified the correlation between ACADSB and 12 ferroptosis genes at the transcriptional level, as well as the changes in reactive oxygen species (ROS) levels by flow cytometry. In summary, this study proposes that tRF-23-Q99P9P9NDD may affect GC lipid metabolism and ferroptosis by targeting ACADSB, thereby promoting GC progression. It provides a theoretical basis for the diagnostic and prognostic monitoring value of GC and opens up new possibilities for treatment.

Human epididymis protein 4, a novel potential biomarker for diagnostic and prognosis monitoring of lung cancer.

This study aimed to explore the application value of human epididymis protein 4 (HE4) in diagnosing and monitoring the prognosis of lung cancer. First, TCGA (The Cancer Genome Atlas) databases were used to analyze whey-acidic-protein 4-disulfide bond core domain 2 (WFDC2) gene expression levels in lung cancer tissues. Then, a total of 160 individuals were enrolled, categorized into three groups: the lung cancer group (n = 80), the benign lesions group (n = 40), and the healthy controls group (n = 40). Serum HE4 levels and other biomarkers were quantified using an electro-chemiluminescent immunoassay. Additionally, the expression of HE4 in tissues was analyzed through immunohistochemistry (IHC). In vitro cultures of human airway epithelial (human bronchial epithelial [HBE]) cells and various lung cancer cell lines (SPC/PC9/A594/H520) were utilized to detect HE4 levels via western blot (WB). Analysis of the TCGA and UALCAN (The University of Alabama at Birmingham Cancer Data Analysis Portal) databases showed that WFDC2 gene expression levels were upregulated in lung cancer tissues (p < 0.01). Compared with the control group and the benign group, HE4 was significantly higher in the serum of patients with lung cancer (p < 0.001). Receiver operating characteristic (ROC) analysis confirmed that HE4 had better diagnostic efficacy than classical markers in the differential diagnosis of lung cancer and benign lesions and had the highest diagnostic value in lung adenocarcinoma (area under the ROC curve [AUC] = 0.826). HE4 increased in early lung cancer and positively correlated with poor prognosis (p < 0.001). Moreover, the results of WB and IHC revealed that the expression of HE4 was increased in lung cancer cells (SPC/A549/H520) and lung cancer tissues but decreased in PC9 cells with a lack of exon EGFR19 (p < 0.05). Serum HE4 emerges as a promising novel biomarker for the diagnosis and prognosis assessment of lung cancer.

Assessing the impact of COVID-19 on renal health in recovered patients: a multi-center longitudinal study

The&lt;b&gt; &lt;/b&gt;coronavirus pandemic of 2019 has become a global health problem. This article presents an analysis of the scientific literature focusing on the pathogenetic and clinical parallels between the kidneys and SARS-CoV-2, as well as the state of kidney health in patients who have recovered from treatment. The goal is to analyze the effects of COVID-19 on kidney health in recovered patients amid an unprecedented flow of scientific data. To achieve this goal, we analysed scientific databases to study the impact of COVID-19 on kidney health in recovered patients. The majority of patients infected with coronavirus had kidney damage, comorbidities, and insufficiency of many organs. Deterioration of kidney function after COVID-19 is observed not only in patients with urological diseases, but also in those patients who have not previously had kidney problems. Despite the fact that nephrologists have developed rapid response methods and defined emergency tactics for the management of patients with kidney damage in COVID-19, cases of kidney disease continue to increase, and the percentage of patients in intensive care units is increasing. For better medical outcomes, careful monitoring of renal function and early laboratory diagnostics to determine biochemical markers, both serum, and urine, in patients with COVID-19 and continuous monitoring of these indicators after recovery are recommended.

Design of a Compact Wearable Antenna for IoT Enabled Bio-Telemetry in Diagnostic Health Monitoring System

The structure developed involves the etching of Moore’s curve onto a conventional rectangular patch and subsequently encasing it in a rectangular loop along with a defected ground structure. The proposed antenna exhibits dual-band Since the Internet of Things (IoT) enabled medical diagnostic system requires unprecedented precision and automation for better health care delivery, therefore in such systems, the performance of antennas for efficiently transferring data (vital functions of the human body) is an important task. To address these concerns, a mechanically robust, novel hybrid wearable on-body antenna inspired by Moore’s fractal based geometry and conventional rectangular loop for a diagnostic health monitoring system is proposed. with bandwidth ranging from 1.38 - 1.8 GHz and 2.25 - 4.88 GHz respectively, covering WMTS, ISM, and Personal Communication band besides covering a portion of UWB band also. The two operating bands of the antenna offer a fractional bandwidth of 38.5% and 73.7% respectively. It is observed that the average specific absorption rate (SAR) over the multi-layer phantom is 0.025 W/kg for an input power of ≈ 24 dBm. In comparison to the recently reported wearable antennas, the design proposed has a compact footprint of 0.135 λo x 0.093λo x 0.004λo besides offering a dual- band of operation, peak gain of 2.2 dBi, overall radiated efficiency of 95% and SAR below 0.025 W/kg. The design is fabricated using Rogers 5880 substrate (semi-flex) of thickness 0.75 mm.

STING-Targeted PET Imaging for Specific Detection and Therapeutic Monitoring of Myocarditis.

Imaging strategies for the specific detection and therapeutic monitoring of myocarditis are still lacking. Stimulator of interferon genes (STING) is a signal transduction molecule involved in an innate immune response. Here, we evaluated the feasibility of the recently developed STING-targeted radiotracer [18F]FBTA for positron emission tomography (PET) imaging to detect myocardial inflammation and monitor treatment in myocarditis mice. [18F]FBTA-PET imaging was performed in myocarditis mice and normal mice to verify the specificity of [18F]FBTA for the diagnosis of myocarditis. We also performed PET imaging in mice with myocarditis treated to verify the ability of [18F]FBTA in therapeutic monitoring. The expression of STING and inflammatory cell types was confirmed by flow cytometry and immunohistochemistry. [18F]FDG-PET imaging of myocarditis was used as a contrast. [18F]FBTA-PET imaging showed that the average radioactive uptake was significantly higher in the hearts of the myocarditis group than in the control group. STING was highly overexpressed in cardiac inflammatory cells, including macrophages, dendritic cells (DCs), and T cells. However, there was no significant difference in cardiac radiotracer uptake of [18F]FDG between the myocarditis group and the control group. Moreover, cardiac uptake of [18F]FBTA was significantly reduced in cyclosporin A-treated myocarditis mice and myocardial STING expression was also significantly reduced after the treatment. Overall, we showed that a STING-targeted PET tracer [18F]FBTA can be used to monitor changes in the inflammatory microenvironment in myocarditis. Besides, [18F]FBTA-PET is also suitable for real-time monitoring of myocarditis treatment, representing a promising diagnostic and therapeutic monitoring approach for myocarditis.

ДІАГНОСТИЧНИЙ МЕТОД КОНТРОЛЮ МЕХАНІЗМУ КОЛИВАНЬ КРИСТАЛІЗАТОРУ МАШИНИ БЕЗПЕРЕРВНОГО ЛИТТЯ ЗАГОТОВОК

Diagnostic devices for monitoring the oscillation mechanism of the mold can increase the stability of steel casting on a continuous caster. The amplitude of crystallizer oscillations is expressed as a sum of harmonic oscillations with different frequencies and is described by the Fourier transform. Wear of the crystallizer sleeves occurs in the lower part. Constant diagnostic monitoring of the state of the crystallizer swing mechanism will increase the durability of copper sleeves. Recommendations for increasing the durability of copper sleeves are provided.

Patient-reported burden associated with pheochromocytoma/paraganglioma diagnosis.

Pheochromocytoma and paragangliomas (PPGLs) originate from the chromaffin cells of the adrenal medulla or neural crest progenitors outside the adrenal gland, respectively. The estimated annual incidence of PPGL is between 2.0 and 8.0/million adults. Minimal data exist on the impact of PPGL from the patient's perspective. Therefore, a survey was adapted from a previously published study on gastroenteropancreatic neuroendocrine tumors to explore the voice of patients with PPGL and learn ways to improve clinical care while understanding the current gaps to direct future research. A self-reported online survey was available to patients with PPGL and those with genetic predisposition even without PPGL from June to July 2022. Survey questions captured sociodemographic and clinical characteristics, the diagnostic workup, treatment and monitoring, quality and access to care, and financial impact. Here, we report the most relevant findings on patient experience of disease burden following diagnosis. A total of 270 people responded, the majority of whom were from the USA (79%), Caucasian (88%), and female (81%). The results of this survey highlight the burden of disease on a patient's daily life, resulting in moderate to severe financial distress, increased travel time to specialized facilities resulting in loss of work and wages, and significant delays in care. Respondents reported being unheard and unacknowledged. With a median time to diagnosis just over 2 years, the physical, mental, and emotional toll are substantial. Increasing access to PPGL specialists and centers could lead to faster diagnoses and better management, which may reduce the burden on both patients and healthcare centers.

New Biomarkers for Systemic Necrotizing Vasculitides.

Systemic necrotising vasculitides (SNVs) pose significant challenges due to their diverse clinical manifestations and variable outcomes. Therefore, identifying reliable biomarkers holds promise for improving precision medicine in SNVs. This review explores emerging biomarkers aiming to enhance diagnostic accuracy, prognostic assessment, and disease monitoring. We discuss recent advances in immunological biomarkers, inflammatory indicators, and other parameters that exhibit potential diagnostic and prognostic utility. A comprehensive understanding of these biomarkers may facilitate earlier and more accurate SNV detection, aiding in timely intervention and personalized treatment strategies. Furthermore, we highlight the evolving landscape of disease monitoring through innovative biomarkers, shedding light on their dynamic roles in reflecting disease activity and treatment response. Integrating these novel biomarkers into clinical practice can revolutionize the management of SNVs, ultimately improving patient outcomes and quality of life.

A preliminary metabolomics study of the database for biological samples of schizophrenia among Chinese ethnic minorities

BackgroundSchizophrenia (SCZ) is a profound mental disorder with a multifactorial etiology, including genetics, environmental factors, and demographic influences such as ethnicity and geography. Among these, the studies of SCZ also shows racial and regional differences.MethodsWe first established a database of biological samples for SCZ in China’s ethnic minorities, followed by a serum metabolomic analysis of SCZ patients from various ethnic groups within the same region using the LC-HRMS platform.ResultsAnalysis identified 47 metabolites associated with SCZ, with 46 showing significant differences between Miao and Han SCZ patients. These metabolites, primarily fatty acids, amino acids, benzene, and derivatives, are involved in fatty acid metabolism pathways. Notably, L-Carnitine, L-Cystine, Aspartylphenylalanine, and Methionine sulfoxide demonstrated greater diagnostic efficacy in Miao SCZ patients compared to Han SCZ patients.ConclusionPreliminary findings suggest that there are differences in metabolic levels among SCZ patients of different ethnicities in the same region, offering insights for developing objective diagnostic or therapeutic monitoring strategies that incorporate ethnic considerations of SCZ.

A 2023 International Survey of Clinical Practice Patterns in the Management of Graves' Disease: A Decade of Change.

Over the past several decades, there have been indications of potential shifts in the diagnostic strategies, treatment, and monitoring of patients with Graves´ disease (GD). To evaluate current practices in managing GD and compare them to previous surveys. We used a global survey of endocrinologists to assess diagnosis, monitoring and treatment in a typical patient with GD, as well as treatment variation in five different clinical scenarios. Online survey. Members of various endocrine societies worldwide. None. Shifts in the management of GD. 1252 respondents from 85 countries completed the survey. Methods used to diagnose an uncomplicated GD case have changed over the past decade, reflecting increased use of TRAb and reciprocal decreases in nuclear medicine studies. The preferred mode of therapy for uncomplicated GD was antithyroid drugs (ATDs) by 91.5% of respondents, radioactive iodine (RAI) therapy by 7%, and thyroidectomy by 1.5%. Compared with previous surveys, the use of RAI as a first-line choice decreased in all geographic regions. The U.S. had the sharpest decline in the selection of initial therapy with RAI, decreasing from 69% in 1990 to 11.1% in 2023. In patients with persistent TRAb positivity after 18 months, 68.7% of respondents would continue the use of ATDs. After a relapse of GD, resumption of ATDs was selected by 59.9% of respondents. In patients with active TED or planning pregnancy, ATDs were the first choice (67.5% and 72.8%, respectively), and thyroidectomy emerged as the second choice (22.9% and 15.6%, respectively). Paradigm shifts have occurred in the management of uncomplicated GD and its variants, as well as the response to persistent and recurrent hyperthyroidism.

Using positional tracking to improve abdominal ultrasound machine learning classification

Diagnostic abdominal ultrasound screening and monitoring protocols are based around gathering a set of standard cross sectional images that ensure the coverage of relevant anatomical structures during the collection procedure. This allows clinicians to make diagnostic decisions with the best picture available from that modality. Currently, there is very little assistance provided to sonographers to ensure adherence to collection protocols, with previous studies suggesting that traditional image only machine learning classification can provide only limited assistance in supporting this task, for example it can be difficult to differentiate between multiple liver cross sections or those of the left and right kidney from image post collection. In this proof of concept, positional tracking information was added to the image input of a neural network to provide the additional context required to recognize six otherwise difficult to identify edge cases. In this paper optical and sensor based infrared tracking (IR) was used to track the position of an ultrasound probe during the collection of clinical cross sections on an abdominal phantom. Convolutional neural networks were then trained using both image-only and image with positional data, the classification accuracy results were then compared. The addition of positional information significantly improved average classification results from ∼90% for image-only to 95% for optical IR position tracking and 93% for Sensor-based IR in common abdominal cross sections. While there is further work to be done, the addition of low-cost positional tracking to machine learning ultrasound classification will allow for significantly increased accuracy for identifying important diagnostic cross sections, with the potential to not only provide validation of adherence to protocol but also could provide navigation prompts to assist in user training and in ensuring adherence in capturing cross sections in future.

Artificial Intelligence in Psychiatry: A Comprehensive Literature Review

IntroductionThe incorporation of artificial intelligence (AI) in healthcare, especially in mental health services, offers potential advancements in efficiency and personalization. As AI technologies like machine learning and natural language processing (NLP) continue to evolve, it’s vital to evaluate their applications in psychiatry comprehensively.ObjectivesThis review aims to summarize and characterize studies that used AI, particularly machine learning and NLP, in mental health. Additionally, it endeavors to understand how these technologies may enhance diagnostic tools, symptom monitoring, and delivery of personalized treatment in psychiatry.MethodsAdhering to PRISMA guidelines, a systematic search was executed across multiple medical databases, including PubMed, Scopus, ScienceDirect, and PsycINFO. Keywords encompassed machine learning, data mining, psychiatry, and mental health. Exclusion criteria included non-English papers, anonymization process descriptions, case studies, conference papers, and other reviews. Data from various segments in the provided information were synthesized to capture the broader picture of AI’s application in psychiatry.ResultsFrom the 327 articles initially identified, 58 were chosen for detailed review. Studies predominantly revolved around three main populations: patients in medical databases, emergency room visitors, and social media users. The primary applications of AI entailed symptom extraction, illness severity classification, therapy effectiveness comparison, and psychopathological insights derivation. Data sources mainly included medical records and social media, with Python emerging as the preferred platform for most studies.ConclusionsWhile AI shows immense promise in revolutionizing mental health care, its current applications largely confirm existing clinical hypotheses. Ethical concerns, such as patient privacy and data biases, remain paramount. Future work should delve deeper into these challenges while further exploring AI’s potential in clinical psychiatry practice.Disclosure of InterestNone Declared

A comprehensive approach to safety for highly automated off-road machinery under Regulation 2023/1230

As of January 2027, Machine Safety Regulation 2023/1230 replaces Directive 2006/42/EC, and a proposal for the regulation of Artificial Intelligence (AI) systems is soon to be ratified by the European Council. These legislative changes address hazards from increased automation and AI integration. Original Equipment Manufacturers (OEMs) face compliance challenges due to a lack of standardized guidelines, especially for off-road machinery with level 4 ‘high automation’ capabilities.At level 4 ‘high automation’, the machine operator assumes a supervisory role, intervening only in situations beyond the designed operational domain. Relying solely on supervisor intervention at this level of automation is unreasonable. Within this context, legislative safety requirements to maintain safety advocate for robust risk management systems, including both a human-in-the-loop safety option and adequate safety-related decision-making by the level 4 ‘high automation’ off-road machine, i.e., the safe reasoning software becomes paramount.In this research, conducted through a systematic mapping study, we discuss emerging safety trends and integration for the safe reasoning software a level 4 off-road machine requires. Our analyses shows the necessity of safety constraint-based design procedures. These procedures involve constraining the AI system by embedding fault management, reasoning checks, and diagnostic monitoring together with safety-related decision-making, thereby enhancing functional reliability and reducing risks. We consider these trends and patterns through the lens of changing machine safety legislative requirements, and the proposal of the regulation of AI products. Illustrating their implications alongside a case study of a level 4 tree harvesting machine, for a tangible and to industry transferable perspective on our results.

Abstract 2305: Label-free high dimensional single cell morphological profiling of different hematological malignancies by ghost cytometry

Abstract Characterizing the heterogeneity in human leukemias is critical for understanding mechanisms of disease onset, uncovering biomarkers for disease diagnosis, and guiding research into novel treatment approaches. While extensive research focus has been placed on characterizing the molecular heterogeneity in leukemia by modern omics technologies, comparatively less emphasis has been placed on studying the diversity in holistic morphological changes that occur in single cells in the context of disease. Here, we report on a novel approach to understanding and characterizing different hematological malignancies using ghost cytometry, a recently developed high-content flow cytometric method that leverages high-speed, artificial intelligence (AI) driven morphological characterization and analysis of single cells. We performed morphometric profiling on human bone marrow samples from patients with T and B-cell acute lymphoblastic leukemia (ALL, n=5), acute myeloid leukemia (AML, n=5), multiple myeloma (MM, n=5) and healthy bone marrow mononuclear cell (BM-MNC) controls (n=6). Morphological profiles from individual cells were analyzed by unsupervised machine learning (universal manifold approximation and projection, UMAP) and compared within disease subsets and against controls. We identified disease-specific cell populations from a mixture of healthy control and disease samples without any labeling, based on completely label-free information. For validation of the specific cell subsets, we overlaid known cell surface markers (e.g. CD45 for blast cells, CD10/CD19 for B-ALL, CD33/CD34 for AML, CD38/CD138 for MM). The intensity of CD45 was dimmer and disease-specific markers were highly expressed in the disease-specific cell population. We also identified a unique cell subpopulation in the disease-specific cell population that could not be distinguished by existing markers. We also analyzed three human myeloma cell lines (AMO1, KMS, and L363) for comparison to the primary MM samples. In the UMAP analysis using LF-GC data, in all three types of cell lines, Bortezomib-resistant cell lines exhibited different distributions from the control parental cell lines. In addition, we observed distinct morphological profiles between primary myeloma samples and myeloma cell lines. Here we present a novel cell characterization approach for human hematological diseases that leverages AI-based, label-free, high-speed morphological characterization of single cells. We demonstrate that the approach can be used to identify subtle morphological differences in blast cells from a range of blood cancer subtypes. Application of morphological profiling and AI can be used to identify measurable, disease-related changes in these diseases that have diagnostic, drug screening, and therapeutic monitoring potential. Citation Format: Asako Tsubouchi, Juho J. Miettinen, Keisuke Wagatsuma, Satoru Akai, Yuri An, Mika Uematsu, Philipp Sergeev, Dimitrios Tsallos, Markus J. Vähä-Koskela, Sadao Ota, Caroline A. Heckman. Label-free high dimensional single cell morphological profiling of different hematological malignancies by ghost cytometry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2305.

Abstract 4682: Membrane protein expression and activity following inhibition of B-cell receptor-initiated signaling by WBMP-4, a therapeutic antibody for leukemia/lymphoma

Abstract The B-cell Receptor (BCR), comprising membrane Ig (mIg) and CD79a/b, controls normal signaling in B-cells, but dysregulation of this signaling is the dominant driver of leukemia/lymphoma. The class-specific mIg subunit of the BCR is a rational drug target for B-cell malignancies. It plays a critical role in the functioning of these cells, and allows for restricted targeting of only B-cells expressing an Ig class, offering a more tumor-specific approach than current pan-B-cell treatments. We developed a first-in-class antibody, WBMP-4, to the mIgM-BCR, which inhibits cell growth and induces apoptosis via widespread down-regulation of tyrosine kinase activity. Given the potent inhibition of intracellular signaling induced upon WBMP-4 binding to the mIgM-BCR, we expect that translation of membrane proteins will be impacted. Here we investigate the expression and phosphorylation profile of cell surface proteins following treatment of malignant B-cells with WBMP-4. Using western blot and flow cytometry, we measure levels of CD79a/b, CD19, CD20, CD21, CD22, CD32a, CD81, and CXCR4 at 6, 24, and 48 hours after low (5ug/mL) and high (20ug/mL) dose WBMP-4 treatment, as compared to control, untreated Burkitt lymphoma (CA46) cells. We analyze phosphorylation levels of those surface proteins that serve as kinases in this system (CD79a/b, CD19, CXCR4, etc.). Using these same methods, we also examine the expression and phosphorylation of key B-cell transcription factors (e.g. NF-kB, c-MYC, STAT5, PAX5, EBF1, FOXO, and BCL-2). Preliminary analyses show a complete absence of CD79a protein (western blot), and decreased phospho-kinase activity of CD79b (Pamgene phosphokinase array) following treatment of Burkitt lymphoma cells with WBMP-4, as compared to untreated cells. While the effect of an antibody binding to mIg may be most pronounced for CD79a/b relative to other proteins, as mIg and CD79a/b form a complex, we expect that the absence of CD79a/b is a result of WBMP-4-induced mIgM inhibition modulating downstream signaling and transcription factor activity. By examining cell surface markers, we may gain insight into how WBMP-4 impacts a cell’s interaction with the tumor microenvironment, and this information is valuable for diagnostic and patient monitoring purposes, and to determine drug combination strategies. This work will be considered in the context of our ongoing research on WBMP-4’s inhibition of intracellular signaling pathways, and the resulting biologic effects, and will contribute to the continued development of WBMP-4 by providing an understanding of the effects achieved (cell growth inhibition, cell differentiation, apoptosis) at different dosages and if these effects are maintained over time. As a novel, efficacious, and low toxicity treatment strategy for B-cell leukemia and lymphoma, WBMP-4 has significant clinical potential. Citation Format: Rachel S. Welt, David Kostyal, Virginia Raymond, Jose M. Lobo, Sydney Welt. Membrane protein expression and activity following inhibition of B-cell receptor-initiated signaling by WBMP-4, a therapeutic antibody for leukemia/lymphoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4682.

Evaluation of neurofilament light chain as a biomarker in dogs with structural and idiopathic epilepsy.

Neurofilament light chain (NfL) is a frequently used biomarker in humans for both diagnostic and therapeutic monitoring purposes in various neurologic diseases. It was hypothesized that dogs with diagnosed structural epilepsy (SE) would have a significantly higher serum NfL concentrations compared to dogs with idiopathic epilepsy (IE). The secondary hypothesis was that dogs would have a significantly higher serum NfL concentrations when measured within 7 days after a seizure compared to being seizure-free for at least 30 days. Fifty client-owned dogs presented to the neurology service for evaluation of seizures were enrolled. Fourteen dogs had SE and 36 dogs had IE. Prospective cohort study performed on 52 serum samples obtained for NfL concentration measurement using single molecule array technology. The median serum concentration of NfL in dogs with SE was significantly higher (109 pg/mL; range, 11.4-741.3 pg/mL) than in dogs with IE (17.7 pg/mL; range, 5.8-188 pg/mL; Wilcoxon rank sum test, P = .001). No significant relationship was found between serum NfL concentration and time of sampling in relation to the most recent seizure in dogs with IE. Serum NfL may serve as an adjunctive biomarker for the differentiation of SE and IE.

Methods to Calculate Entropy Generation.

Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real-time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems-thermal, externally loaded, internally reactive, open and closed-are developed via selection of suitable thermodynamic potentials. Here we simplify thermodynamic principles to specify convenient and consistently accurate system governing equations and characterization models. The formulations introduce a new and universal Phenomenological Entropy Generation (PEG) theorem. The systems and methods presented-and demonstrated on frictional wear, grease degradation, battery charging and discharging, metal fatigue and pump flow-can be used for design, analysis, and support of diagnostic monitoring and optimization.

Neurophysiological Methods for Diagnostics and Treatment Monitoring in Patients of Advanced Age with Epilepsy

Through the last decades the duration of life and the number of elderly people is rapidly growing. In this age group morbidity of epilepsy is increasing very fast. Neurophysiological methods play an important role in diagnostics, classification of the disease and the type of the seizures, and in treatment monitoring in the elderly with epilepsy. The aim of the present study was to establish the significance of neurophysiological methods for diagnostics and treatment monitoring, as well as their relation with particular clinical characteristics of the disease in elderly patients. The study group consisted of 297 consecutive patients with epilepsy (average age 69.25±5.00 years). The methods used were documentary analysis, an interview of clinical factors, EEG (basic and control), video-EEG and statistical methods. Patients with longer duration of the disease were with significant worse neurophysiological results, higher seizure frequency and more in number antiepileptic medications. Epilepsy in the elderly is a major and growing issue. The results of the study will be useful in diagnostics and treatment monitoring in this age group.

Bioinspired breathable biodegradable bioelastomer-based flexible wearable electronics for high-sensitivity human-interactive sensing

Flexible wearable electronic sensors are regarded to facilitate revolutionary changes in human's daily life for their great promise in multifunctional artificial electronic skins, personalized healthcare monitoring, and smart human–machine interaction. However, there remains great challenges to simultaneously achieve high sensitivity, broad sensing range and robust cyclic stability for high-performance personal diagnostic healthcare monitoring, excellent breathability for comfortable wearing, as well as environmentally friendly biodegradability for reducing electronic wastes. Herein, bioinspired by three-dimensional network structure of ant nest with high specific surface area, interconnected channels, and robust ventilation, a wearable, breathable, and biodegradable electronic sensor is prepared from facile face-to-face assembly of breathable biodegradable MXene-coated poly(1,8-octanediol-co-polycaprolactone citrate) elastomer sponge (MXene@POPLC), and an MXene ink-printed interdigitated electrode-coated breathable electrospun film. The as-obtained flexible electronic sensor exhibits high sensitivity (up to 246.3 kPa−1), broad sensing range (up to 333.3 kPa), reliable cycling stability (∼20,000 cycles), fast response (10 ms)/recovery time, robust breathability, excellent biocompatibility, facile biodegradability, and wireless wearable human–machine interfacing. Therefore, this line of research work opens up a novel avenue for the preparation of multifunctional wearable, breathable, and biodegradable electronics to hold great promise in smart healthcare monitoring, intelligent human–machine interaction, smart personal protection and next-generation artificial skin.