Subsets of Nanometer Vesicles in the Fly Release Differential Fractions of Vesicular Serotonin Content during Exocytosis.

Serotonin, a monoamine neurotransmitter, is important in both the central nervous system (CNS) and the peripheral nervous system. Malfunction of serotonin signaling leads to various disorders. We studied serotonin signaling from serotonergic neurons inside the ventral nerve cord of Drosophila melanogaster. Serotonergic neurons and stimulated release were visualized and achieved with mCherry and channelrhodopsin-2 (an optogenetically transfected ion channel), respectively, and two electrochemical techniques quantified serotonin release and vesicular content. Mean vesicular serotonin content released during exocytosis from these neurons was 84 %, considerably higher than reported in previous studies regarding octopamine (4.5 %) and glutamate release (31 %). Serotonin content within all vesicles is uniformly changed when serotonin concentration is inhibited or enhanced. However, serotonin release exhibits two Gaussian distributions: higher frequency of small release events, and similar or slightly higher frequency of large events, resulting in differential release fractions ranging from partial (13-18 %) to full (100 %) release after treatment with agents to either enhance or diminish release. This is the first example of consistent full exocytotic release events we have observed in any system. We suggest one pool of vesicles can release significantly diverse fractions of transmitter load during exocytosis, a potentially novel pathway to regulate exocytosis and neuronal signaling.

Soft, Multifunctional MXene-Coated Fiber Microelectrodes for Biointerfacing.

Flexible fiber-based microelectrodes allow safe and chronic investigation and modulation of electrically active cells and tissues. Compared to planar electrodes, they enhance targeting precision while minimizing side effects from the device-tissue mechanical mismatch. However, the current manufacturing methods face scalability, reproducibility, and handling challenges, hindering large-scale deployment. Furthermore, only a few designs can record electrical and biochemical signals necessary for understanding and interacting with complex biological systems. In this study, we present a method that utilizes the electrical conductivity and easy processability of MXenes, a diverse family of two-dimensional nanomaterials, to apply a thin layer of MXene coating continuously to commercial nylon filaments (30-300 µm in diameter) at a rapid speed (up to 15 mm/s), achieving a linear resistance below 10 Ω/cm. The MXene-coated filaments are then batch-processed into free-standing fiber microelectrodes with excellent flexibility, durability, and consistent performance even when knotted. We demonstrate the electrochemical properties of these fiber electrodes and their hydrogen peroxide (H2O2) sensing capability and showcase their applications in vivo (rodent) and ex vivo (bladder tissue). This scalable process fabricates high-performance microfiber electrodes that can be easily customized and deployed in diverse bioelectronic monitoring and stimulation studies, contributing to a deeper understanding of health and disease.

Decreases in mucosally-evoked tachykinin signaling pathways can explain age-related reductions in murine colonic motility patterns.

BACKGROUND: Increasing age increases the incidence of chronic constipation and fecal impaction. The contribution of the natural aging process to this phenotype is unclear. This study explored the effects of age on key motility patterns in the murine colon and determined the contribution that altered neurokinin 2 (NK2) -mediated signaling made to the aging phenotype. METHODS: Mucosal reflexes, colonic migrating motor complexes (CMMCs) and colonic motility assays were explored in isolated ex vivo colons from 3, 12-14, 18- and 24-months old mice and the NK2-mediated response determined. Electrical field stimulation (EFS) or exogenous drug application were used to explore the role of the mucosa in colonic segments. KEY RESULTS: Aging reduced the force of contraction of the distal colon mucosal reflex, the frequency and force of contraction of CMMCs and the NK2-mediated component of both motility patterns. Ondansetron, a 5-HT3 receptor antagonist, blocked a component of both motility patterns in full thickness but not in mucosa-free segments of the distal colon. 5, hydroxytryptamine (5-HT) and EFS-evoked NK2-dependent contractions were reduced with increasing age. Smooth muscle sensitivity to 5-HT or neurokinin A (NKA) was not altered with age. In isolated colon motility assays application of NKA decreased transit time in 24-months colon and the NK2 antagonist GR159897 increased transit times in both 3- and 24-months old colons. CONCLUSIONS AND INFERENCES: Aging impairs key motility patterns in the murine colon. These changes involve a decrease in mucosally-evoked NK2-mediated signaling. Targeting NK2-mediated signaling may provide a novel approach to treating age-related motility disorders in the lower bowel.

Unlocking the diagnostic power of plasma extracellular vesicle miR-200 family in pancreatic ductal adenocarcinoma.

BACKGROUND: Distinguishing benign from malignant pancreaticobiliary disease is challenging because of the absence of reliable biomarkers. Circulating extracellular vesicles (EVs) have emerged as functional mediators between cells. Their cargos, including microRNAs (miRNAs), are increasingly acknowledged as an important source of potential biomarkers. This multicentric, prospective study aimed to establish a diagnostic plasma EV-derived miRNA signature to discriminate pancreatic ductal adenocarcinoma (PDAC) from benign pancreaticobiliary disease. METHODS: Plasma EVs were isolated using size exclusion chromatography (SEC) and characterised using nanoparticle tracking analysis, electron microscopy and Western blotting. EV-RNAs underwent small RNA sequencing to discover differentially expressed markers for PDAC (n = 10 benign vs. 10 PDAC). Candidate EV-miRNAs were then validated in a cohort of 61 patients (n = 31 benign vs. 30 PDAC) by RT-qPCR. Logistic regression and optimal thresholds (Youden Index) were used to develop an EV-miR-200 family model to detect cancer. This model was tested in an independent cohort of 95 patients (n = 30 benign, 33 PDAC, and 32 cholangiocarcinoma). RESULTS: Small RNA sequencing and RT-qPCR showed that EV-miR-200 family members were significantly overexpressed in PDAC vs. benign disease. Combined expression of the EV-miR-200 family showed an AUC of 0.823. In an independent validation cohort, application of this model showed a sensitivity, specificity and AUC of 100%, 88%, and 0.97, respectively, for diagnosing PDAC. CONCLUSIONS: This is the first study to validate plasma EV-miR-200 members as a clinically-useful diagnostic biomarker for PDAC. Further validation in larger cohorts and clinical trials is essential. These findings also suggest the potential utility in monitoring response and/or recurrence.

MicroRNAs as Bile-based biomarkers in pancreaticobiliary cancers (MIRABILE): a cohort study.

BACKGROUND: Biliary obstruction can be due to both malignant and benign pancreaticobiliary disease. Currently, there are no biomarkers that can accurately help make this distinction. MicroRNAs (miRNAs) are stable molecules in tissue and biofluids that are commonly deregulated in cancer. The MIRABILE study aimed to identify miRNAs in bile that can differentiate malignant from benign pancreaticobiliary disease. MATERIALS AND METHODS: There were 111 patients recruited prospectively at endoscopic retrograde cholangiopancreatography (ERCP) or percutaneous transhepatic cholangiography (PTC) for obstructive jaundice, and bile was aspirated for cell-free RNA (cfRNA) extraction and analysis. In a discovery cohort of 78 patients (27 with pancreatic ductal adenocarcinoma (PDAC), 14 cholangiocarcinoma (CCA), 37 benign disease), cfRNA was subjected to small-RNA sequencing. LASSO regression was used to define bile miRNA signatures, and NormFinder to identify endogenous controls. In a second cohort of 87 patients (34 PDAC, 14 CCA, 39 benign disease), RT-qPCR was used for validation. RESULTS: LASSO regression identified 14 differentially-expressed bile miRNAs of which 6 were selected for validation. When comparing malignant and benign pancreaticobiliary disease, bile miR-340 and miR-182 were validated and significantly differentially expressed (P<0.05 and P<0.001, respectively). This generated an AUC of 0.79 (95%CI 0.70-0.88, sensitivity 65%; specificity 82%) in predicting malignant disease. CONCLUSION: Bile collected during biliary drainage contains miRNAs able to differentiate benign from malignant pancreaticobiliary diseases in patients with obstructive jaundice. These bile miRNAs have the potential to increase diagnostic accuracy.

3D-Printed Microelectrodes for Biological Measurement.

Microelectrodes are useful electrochemical sensors that can provide spatial biological monitoring. Carbon fiber has been by far the most widely used microelectrode; however, a vast number of different materials and modification strategies have been developed to broaden the scope of microelectrodes. Carbon composite electrodes provide a simple approach to making microelectrodes with a wide range of materials, but manufacturing strategies are complex. 3D printing can provide the ability to make microelectrodes with high precision. We used fused filament fabrication to print single strands of carbon black/polylactic acid (CB/PLA) and multiwall carbon nanotube/polylactic acid (MWCNT/PLA), which were then made into microelectrodes. Microelectrodes ranged from 70 µm in diameter to 400 µm in diameter and were assessed using standard redox probes. MWCNT/PLA electrodes exhibited greater sensitivity, a lower limit of detection, and stability for the measurement of serotonin (5-HT). Both CB/PLA and MWCNT/PLA microelectrodes were able to monitor 5-HT overflow from the ex vivo ileum tissue. MWCNT/PLA microelectrodes were utilized to show differences in 5-HT overflow from ex vivo ileum and colon following exposure to odorants present in spices. These findings highlight that any conductive thermoplastic material can be fabricated into a microelectrode. This simple strategy can utilize a wide range of materials to make 3D-printed microelectrodes for a diverse range of applications.

The microbial composition of pancreatic ductal adenocarcinoma: A systematic review of 16S rRNA gene sequencing.

BACKGROUND: Pancreatic cancer, specifically pancreatic ductal adenocarcinoma (PDAC), continues to pose a significant clinical and scientific challenge. The most significant finding of recent years is that PDAC tumours harbour their specific microbiome, which differs amongst tumour entities and is distinct from healthy tissue. This review aims to evaluate and summarise all PDAC studies that have used the next-generation technique, 16S rRNA gene amplicon sequencing within each bodily compartment. As well as establishing a causal relationship between PDAC and the microbiome. MATERIALS AND METHODS: This systematic review was carried out according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines. A comprehensive search strategy was designed, and 1727 studies were analysed. RESULTS: In total, 38 studies were selected for qualitative analysis and summarised significant PDAC bacterial signatures. Despite the growing amount of data provided, we are not able to state a universal 16S rRNA gene microbial signature that can be used for PDAC screening. This is most certainly due to the heterogeneity of the presentation of results, lack of available datasets and the intrinsic selection bias between studies. CONCLUSION: Several key studies have begun to shed light on causality and the influence the microbiome constituents and their produced metabolites could play in tumorigenesis and influencing outcomes. The challenge in this field is to shape the available microbial data into targetable signatures. Making sequenced data readily available is critical, coupled with the coordinated standardisation of data and the need for consensus guidelines in studies investigating the microbiome in PDAC.

Comparative Analysis of Fusion Strategies for Imaging and Non-imaging Data - Use-case of Hospital Discharge Prediction.

Accurate prediction of future clinical events such as discharge from hospital can not only improve hospital resource management but also provide an indicator of a patient's clinical condition. Within the scope of this work, we perform a comparative analysis of deep learning based fusion strategies against traditional single source models for prediction of discharge from hospital by fusing information encoded in two diverse but relevant data modalities, i.e., chest X-ray images and tabular electronic health records (EHR). We evaluate multiple fusion strategies including late, early and joint fusion in terms of their efficacy for target prediction compared to EHR-only and Image-only predictive models. Results indicated the importance of merging information from two modalities for prediction as fusion models tended to outperform single modality models and indicate that the joint fusion scheme was the most effective for target prediction. Joint fusion model merges the two modalities through a branched neural network that is jointly trained in an end-to-end fashion to extract target-relevant information from both modalities.

Impact of tertiary lymphoid structures on prognosis and therapeutic response in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is known to have a heterogeneous desmoplastic tumour microenvironment (TME) with a large number of immunosuppressive cells. Recently, high B-cell infiltration in PDAC has received growing interest as a potential therapeutic target. METHODS: Our literature review summarises the characteristics of tumour-associated tertiary lymphoid structures (TLSs) and highlight the key studies exploring the clinical outcomes of TLSs in PDAC patients and the direct effect on the TME. RESULTS: The location, density and maturity stages of TLSs within tumours play a key role in determining the prognosis and is a new emerging target in cancer immunotherapy. DISCUSSION: TLS development is imperative to improve the prognosis of PDAC patients. In the future, studying the genetics and immune characteristics of tumour infiltrating B cells and TLSs may lead towards enhancing adaptive immunity in PDAC and designing personalised therapies.

Amperometry approach curve profiling to understand the regulatory mechanisms governing the concentration of intestinal extracellular serotonin.

Enterochromaffin (EC) cells located within the intestinal mucosal epithelium release serotonin (5-HT) to regulate motility tones, barrier function and the immune system. Electroanalytical methodologies have been able to monitor steady state basal extracellular 5-HT levels but are unable to provide insight into how these levels are influenced by key regulatory processes such as release and uptake. We established a new measurement approach, amperometry approach curve profiling, which monitors the extracellular 5-HT level at different electrode-tissue (E-T) distances. Analysis of the current profile can provide information on contributions of regulatory components on the observed extracellular 5-HT level. Measurements were conducted from ex vivo murine ileum and colon using a boron-doped diamond (BDD) microelectrode. Amperometry approach curve profiling coupled with classical pharmacology demonstrated that extracellular 5-HT levels were significantly lower in the colon when compared to the ileum. This difference was due to a greater degree of activity of the 5-HT transporter (SERT) and a reduced amount of 5-HT released from colonic EC cells. The presence of an inhibitory 5-HT4 autoreceptor was observed in the colon, where a 40% increase in extracellular 5-HT was the half maximal inhibitory concentration for activation of the autoreceptor. This novel electroanalytical approach allows estimates of release and re-uptake and their contribution to 5-HT extracellular concentration from intestinal tissue be obtained from a single series of measurements.

Automated Analysis of Split Kidney Function from CT Scans Using Deep Learning and Delta Radiomics.

Background: Differential kidney function assessment is an important part of preoperative evaluation of various urological interventions. It is obtained through dedicated nuclear medical imaging and is not yet implemented through conventional Imaging. Objective: We assess if differential kidney function can be obtained through evaluation of contrast-enhanced computed tomography(CT) using a combination of deep learning and (2D and 3D) radiomic features. Methods: All patients who underwent kidney nuclear scanning at Mayo Clinic sites between 2018-2022 were collected. CT scans of the kidneys were obtained within a 3-month interval before or after the nuclear scans were extracted. Patients who underwent a urological or radiological intervention within this time frame were excluded. A segmentation model was used to segment both kidneys. 2D and 3D radiomics features were extracted and compared between the two kidneys to compute delta radiomics and assess its ability to predict differential kidney function. Performance was reported using receiver operating characteristics, sensitivity, and specificity. Results: Studies from Arizona & Rochester formed our internal dataset (n = 1,159). Studies from Florida were separately processed as an external test set to validate generalizability. We obtained 323 studies from our internal sites and 39 studies from external sites. The best results were obtained by a random forest model trained on 3D delta radiomics features. This model achieved an area under curve (AUC) of 0.85 and 0.81 on internal and external test sets, while specificity and sensitivity were 0.84,0.68 on the internal set, 0.70, and 0.65 on the external set. Conclusion: This proposed automated pipeline can derive important differential kidney function information from contrast-enhanced CT and reduce the need for dedicated nuclear scans for early-stage differential kidney functional assessment. Clinical Impact: We establish a machine learning methodology for assessing differential kidney function from routine CT without the need for expensive and radioactive nuclear medicine scans.

Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity.

AIMS/HYPOTHESIS: Beta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly connected 'hub' cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility, which we explore here by focusing on the imprinted gene Nnat (encoding neuronatin [NNAT]), which is required for normal insulin synthesis and secretion. METHODS: Single-cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing enhanced GFP under the control of the Nnat enhancer/promoter regions were generated for FACS of beta cells and downstream analysis of CpG methylation by bisulphite sequencing and RNA-seq, respectively. Animals deleted for the de novo methyltransferase DNA methyltransferase 3 alpha (DNMT3A) from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 AM and Cal-590 AM. Insulin secretion was measured using homogeneous time-resolved fluorescence imaging. RESULTS: Nnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic datasets demonstrated the early establishment of Nnat-positive and -negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a subpopulation specialised for insulin production, and were diminished in db/db mice. 'Hub' cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialisation. CONCLUSIONS/INTERPRETATION: These findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes. DATA AVAILABILITY: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD048465.

Monitoring the electroactive cargo of extracellular vesicles can differentiate various cancer cell lines.

Extracellular vesicles (EVs) are pivotal in cell-to-cell communication due to the array of cargo contained within these vesicles. EVs are considered important biomarkers for identification of disease, however most measurement approaches have focused on monitoring specific surface macromolecular targets. Our study focuses on exploring the electroactive component present within cargo from EVs obtained from various cancer and non-cancer cell lines using a disk carbon fiber microelectrode. Variations in the presence of oxidizable components were observed when the total cargo from EVs were measured, with the highest current detected in EVs from MCF7 cells. There were differences observed in the types of oxidizable species present within EVs from MCF7 and A549 cells. Single entity measurements showed clear spikes due to the detection of oxidizable cargo within EVs from MCF7 and A549 cells. These studies highlight the promise of monitoring EVs through the presence of varying electroactive components within the cargo and can drive a wave of new strategies towards specific detection of EVs for diagnosis and prognosis of various diseases.

Perioperative Considerations in Alpha-Gal Syndrome: A Review.

Galactose-⍺-1, 3-galactose (alpha-gal) is an oligosaccharide found in mammalian tissues that causes allergic reactions in patients with alpha-gal syndrome (AGS). AGS is a hypersensitivity reaction notable for both immediate and delayed allergic and anaphylactic symptoms. As a tick-based disease, AGS has gained increasing prevalence across the United States and can have a significant influence on which medications are safe for patients. Many medications used within the operating room and intensive care units have inactive ingredients that can be mammalian-derived and therefore should be vetted before administering to patients with AGS. Management of patients with AGS involves diligent action in the preoperative and perioperative settings to reduce patient exposure to potentially harmful medications. In conducting a comprehensive risk stratification assessment, the anesthesia team should identify any at-risk patients and determine which medications they have safely tolerated in the past. Despite obtaining a complete history, not all patients with AGS will be identified preoperatively. The perioperative team should understand which common medications pose a risk of containing alpha-gal moieties (e.g., heparins, gelatin capsules, vaccines, lidocaine patches, surgifoam, etc.​​). For this reason, this paper includes a compendium of common anesthetic medications that have been cross-referenced for ingredients that have the potential to cause an AGS reaction. Any potentially unsafe medications have been identified such that medical providers can cross-reference with the ingredients listed at their respective institutions.

Improved Risk-Stratification Scheme for Mismatch-Repair Proficient Stage II Colorectal Cancers Using the Digital Pathology Biomarker QuantCRC.

PURPOSE: There is a need to improve current risk stratification of stage II colorectal cancer to better inform risk of recurrence and guide adjuvant chemotherapy. We sought to examine whether integration of QuantCRC, a digital pathology biomarker utilizing hematoxylin and eosin-stained slides, provides improved risk stratification over current American Society of Clinical Oncology (ASCO) guidelines. EXPERIMENTAL DESIGN: ASCO and QuantCRC-integrated schemes were applied to a cohort of 398 mismatch-repair proficient (MMRP) stage II colorectal cancers from three large academic medical centers. The ASCO stage II scheme was taken from recent guidelines. The QuantCRC-integrated scheme utilized pT3 versus pT4 and a QuantCRC-derived risk classification. Evaluation of recurrence-free survival (RFS) according to these risk schemes was compared using the log-rank test and HR. RESULTS: Integration of QuantCRC provides improved risk stratification compared with the ASCO scheme for stage II MMRP colorectal cancers. The QuantCRC-integrated scheme placed more stage II tumors in the low-risk group compared with the ASCO scheme (62.5% vs. 42.2%) without compromising excellent 3-year RFS. The QuantCRC-integrated scheme provided larger HR for both intermediate-risk (2.27; 95% CI, 1.32-3.91; P = 0.003) and high-risk (3.27; 95% CI, 1.42-7.55; P = 0.006) groups compared with ASCO intermediate-risk (1.58; 95% CI, 0.87-2.87; P = 0.1) and high-risk (2.24; 95% CI, 1.09-4.62; P = 0.03) groups. The QuantCRC-integrated risk groups remained prognostic in the subgroup of patients that did not receive any adjuvant chemotherapy. CONCLUSIONS: Incorporation of QuantCRC into risk stratification provides a powerful predictor of RFS that has potential to guide subsequent treatment and surveillance for stage II MMRP colorectal cancers.

Evaluating diverse electrode surface patterns of 3D printed carbon thermoplastic electrochemical sensors.

Electrochemical sensing techniques rely on redox reactions taking place at the electrode surface. The configuration of this surface is of the utmost importance in the advancement of electrochemical sensors. The majority of previous electrode manufacturing methods, including 3D printing have produced electrodes with flat surfaces. There is a distinct potential for 3D printing to create intricate and distinctive electrode surface shapes. In the proposed work, 3D printed carbon black polylactic acid electrodes with nine different surface morphologies were made. These were compared to a flat surface electrode. To evaluate the performance of the electrodes, measurements were conducted in three different redox probes (ferrocene methanol, ferricyanide, and dopamine). Our findings highlighted that when electrodes were normalised for the geometric surface area of the electrode, the surface pattern of the electrode surface can impact the observed current and electron transfer kinetics. Electrodes that had a dome and flag pattern on the electrode surface showed the highest oxidation currents and had lower values for the difference between the anodic and cathodic peak current (ΔE). However, designs with rings had lower current values and higher ΔE values. These differences are most likely due to variations in the accessibility of conductive sites on the electrode surface due to the varying surface roughness of different patterned designs. Our findings highlight that when making electrodes using 3D printing, surface patterning of the electrode surface can be used as an effective approach to enhance the performance of the sensor for varying applications.

Opportunistic screening for coronary artery calcium deposition using chest radiographs - a multi-objective models with multi-modal data fusion.

Background: To create an opportunistic screening strategy by multitask deep learning methods to stratify prediction for coronary artery calcium (CAC) and associated cardiovascular risk with frontal chest x-rays (CXR) and minimal data from electronic health records (EHR). Methods: In this retrospective study, 2,121 patients with available computed tomography (CT) scans and corresponding CXR images were collected internally (Mayo Enterprise) with calculated CAC scores binned into 3 categories (0, 1-99, and 100+) as ground truths for model training. Results from the internal training were tested on multiple external datasets (domestic (EUH) and foreign (VGHTPE)) with significant racial and ethnic differences and classification performance was compared. Findings: Classification performance between 0, 1-99, and 100+ CAC scores performed moderately on both the internal test and external datasets, reaching average f1-score of 0.66 for Mayo, 0.62 for EUH and 0.61 for VGHTPE. For the clinically relevant binary task of 0 vs 400+ CAC classification, the performance of our model on the internal test and external datasets reached an average AUCROC of 0.84. Interpretation: The fusion model trained on CXR performed better (0.84 average AUROC on internal and external dataset) than existing state-of-the-art models on predicting CAC scores only on internal (0.73 AUROC), with robust performance on external datasets. Thus, our proposed model may be used as a robust, first-pass opportunistic screening method for cardiovascular risk from regular chest radiographs. For community use, trained model and the inference code can be downloaded with an academic open-source license from https://github.com/jeong-jasonji/MTL_CAC_classification . Funding: The study was partially supported by National Institute of Health 1R01HL155410-01A1 award.

Pristine Ti3C2Tx MXene Enables Flexible and Transparent Electrochemical Sensors.

In the era of the internet of things, there exists a pressing need for technologies that meet the stringent demands of wearable, self-powered, and seamlessly integrated devices. Current approaches to developing MXene-based electrochemical sensors involve either rigid or opaque components, limiting their use in niche applications. This study investigates the potential of pristine Ti3C2Tx electrodes for flexible and transparent electrochemical sensing, achieved through an exploration of how material characteristics (flake size, flake orientation, film geometry, and uniformity) impact the electrochemical activity of the outer sphere redox probe ruthenium hexamine using cyclic voltammetry. The optimized electrode made of stacked large Ti3C2Tx flakes demonstrated excellent reproducibility and resistance to bending conditions, suggesting their use for reliable, robust, and flexible sensors. Reducing electrode thickness resulted in an amplified faradaic-to-capacitance signal, which is advantageous for this application. This led to the deposition of transparent thin Ti3C2Tx films, which maintained their best performance up to 73% transparency. These findings underscore its promise for high-performance, tailored sensors, marking a significant stride in advancing MXene utilization in next-generation electrochemical sensing technologies. The results encourage the analytical electrochemistry field to take advantage of the unique properties that pristine Ti3C2Tx electrodes can provide in sensing through more parametric studies.