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BACKGROUND: The hard clam (Mercenaria mercenaria), a marine bivalve distributed along the U.S. eastern seaboard, supports a significant shellfish industry. Overharvest in the 1970s and 1980s led to a reduction in landings. While the transition of industry from wild harvest to aquaculture since that time has enhanced production, it has also exacerbated challenges such as disease outbreaks. In this study, we developed and validated a 66K SNP array designed to advance genetic studies and improve breeding programs in the hard clam, focusing particularly on the development of markers that could be useful in understanding disease resistance and environmental adaptability. RESULTS: Whole-genome resequencing of 84 individual clam samples and 277 pooled clam libraries yielded over 305 million SNPs, which were filtered down to a set of 370,456 SNPs that were used as input for the design of a 66K SNP array. This medium-density array features 66,543 probes targeting coding and non-coding regions, including 70 mitochondrial SNPs, to capture the extensive genetic diversity within the species. The SNPs were distributed evenly throughout the clam genome, with an average interval of 25,641 bp between SNPs. The array incorporates markers for detecting the clam pathogen Mucochytrium quahogii (formerly QPX), enhancing its utility in disease management. Performance evaluation on 1,904 samples demonstrated a 72.7% pass rate with stringent quality control. Concordance testing affirmed the array's repeatability, with an average agreement of allele calls of 99.64% across multiple tissue types, highlighting its reliability. The tissue-specific analysis demonstrated that some tissue types yield better genotyping results than others. Importantly, the array, including its embedded mitochondrial markers, effectively elucidated complex genetic relationships across different clam groups, both wild populations and aquacultured stocks, showcasing its utility for detailed population genetics studies. CONCLUSIONS: The 66K SNP array is a powerful and robust genotyping tool that offers unprecedented insights into the species' genomic architecture and population dynamics and that can greatly facilitate hard clam selective breeding. It represents an important resource that has the potential to transform clam aquaculture, thereby promoting industry sustainability and ecological and economic resilience.

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BACKGROUND: Commercial genome-wide genotyping arrays have historically neglected coverage of genetic variation across populations. OBJECTIVE: We aimed to create a multi-ancestry genome-wide array that would include a wide range of neuro-specific genetic content to facilitate genetic research in neurological disorders across multiple ancestral groups, fostering diversity and inclusivity in research studies. METHODS: We developed the Illumina NeuroBooster Array (NBA), a custom high-throughput and cost-effective platform on a backbone of 1,914,934 variants from the Infinium Global Diversity Array and added custom content comprising 95,273 variants associated with more than 70 neurological conditions or traits, and we further tested its performance on more than 2000 patient samples. This novel platform includes approximately 10,000 tagging variants to facilitate imputation and analyses of neurodegenerative disease-related genome-wide association study loci across diverse populations. RESULTS: In this article, we describe NBA's potential as an efficient means for researchers to assess known and novel disease genetic associations in a multi-ancestry framework. The NBA can identify rare genetic variants and accurately impute more than 15 million common variants across populations. Apart from enabling sample prioritization for further whole-genome sequencing studies, we envisage that NBA will play a pivotal role in recruitment for interventional studies in the precision medicine space. CONCLUSIONS: From a broader perspective, the NBA serves as a promising means to foster collaborative research endeavors in the field of neurological disorders worldwide. Ultimately, this carefully designed tool is poised to make a substantial contribution to uncovering the genetic etiology underlying these debilitating conditions. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

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Neoadjuvant intratumoral (IT) therapy could amplify the weak responses to checkpoint blockade therapy observed in breast cancer (BC). In this study, we administered neoadjuvant IT anti-canine PD-1 therapy (IT acPD-1) alone or combined with IT cowpea mosaic virus therapy (IT CPMV/acPD-1) to companion dogs diagnosed with canine mammary cancer (CMC), a spontaneous tumor resembling human BC. CMC patients treated weekly with acPD-1 (n = 3) or CPMV/acPD-1 (n = 3) for four weeks or with CPMV/acPD-1 (n = 3 patients not candidates for surgery) for up to 11 weeks did not experience immune-related adverse events. We found that acPD-1 and CPMV/acPD-1 injections resulted in tumor control and a reduction in injected tumors in all patients and in noninjected tumors located in the ipsilateral and contralateral mammary chains of treated dogs. In two metastatic CMC patients, CPMV/acPD-1 treatments resulted in the control and reduction of established lung metastases. CPMV/acPD-1 treatments were associated with altered gene expression related to TLR1-4 signaling and complement pathways. These novel therapies could be effective for CMC patients. Owing to the extensive similarities between CMC and human BC, IT CPMV combined with approved anti-PD-1 therapies could be a novel and effective immunotherapy to treat local BC and suppress metastatic BC.

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This paper presents a robust adaptive beamforming algorithm based on an attention convolutional neural network (ACNN) for coprime sensor arrays, named the CAWE-ACNN algorithm. In the proposed algorithm, via a spatial and channel attention unit, an ACNN model is constructed to enhance the features contributing to beamforming weight vector estimation and to improve the signal-to-interference-plus-noise ratio (SINR) performance, respectively. Then, an interference-plus-noise covariance matrix reconstruction algorithm is used to obtain an appropriate label for the proposed ACNN model. By the calculated label and the sample signals received from the coprime sensor arrays, the ACNN is well-trained and capable of accurately and efficiently outputting the beamforming weight vector. The simulation results verify that the proposed algorithm achieves excellent SINR performance and high computation efficiency.

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A fundamental aspect in the evolution of Time-to-Digital Converters (TDCs) implemented within Field-Programmable Gate Arrays (FPGAs), given the increasing demand for detection channels, is the optimization of resource utilization. This study reviews the principal methodologies employed for implementing low-resource TDCs in FPGAs. It outlines the foundational architectures and interpolation techniques utilized to bolster TDC performances without unduly burdening resource consumption. Low-resource Tapped Delay Line, Vernier Ring Oscillator, and Multi-Phase Shift Counter TDCs, including the use of SerDes, are reviewed. Additionally, novel low-resource architectures are scrutinized, including Counter Gray Oscillator TDCs and interpolation expansions using Process-Voltage-Temperature stable IODELAYs. Furthermore, the advantages and limitations of each approach are critically assessed, with particular emphasis on resolution, precision, non-linearities, and especially resource utilization. A comprehensive summary table encapsulating existing works on low-resource TDCs is provided, offering a comprehensive overview of the advancements in the field.

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This study used an odor sensing system with a 16-channel electrochemical sensor array to measure beef odors, aiming to distinguish odors under different storage days and processing temperatures for quality monitoring. Six storage days ranged from purchase (D0) to eight days (D8), with three temperature conditions: no heat (RT), boiling (100 °C), and frying (180 °C). Gas chromatography-mass spectrometry (GC-MS) analysis showed that odorants in the beef varied under different conditions. Compounds like acetoin and 1-hexanol changed significantly with the storage days, while pyrazines and furans were more detectable at higher temperatures. The odor sensing system data were visualized using principal component analysis (PCA) and uniform manifold approximation and projection (UMAP). PCA and unsupervised UMAP clustered beef odors by storage days but struggled with the processing temperatures. Supervised UMAP accurately clustered different temperatures and dates. Machine learning analysis using six classifiers, including support vector machine, achieved 57% accuracy for PCA-reduced data, while unsupervised UMAP reached 49.1% accuracy. Supervised UMAP significantly enhanced the classification accuracy, achieving over 99.5% with the dimensionality reduced to three or above. Results suggest that the odor sensing system can sufficiently enhance non-destructive beef quality and safety monitoring. This research advances electronic nose applications and explores data downscaling techniques, providing valuable insights for future studies.

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Flexible ultrasonic devices represent a feasible technology for providing timely signal detection and even a non-invasive disease treatment for the human brain. However, the deformation of the devices is always accompanied by a change in the acoustic field, making it hard for accurate focusing. Herein, we report a stable and flexible transducer. This device can generate a high-intensity acoustic signal with a controllable acoustic field even when the device is bent. The key is to use a low-impedance piezoelectric material and an island-bridge device structure, as well as to design a unique time-reversal algorithm to correct the deviation of signals after transcranial propagation. To provide an in-depth study of the acoustic field of flexible devices, we also analyze the effects of mechanical deformation and structural parameters on the corresponding acoustic response.

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This study investigates the application of an eNose (electrochemical sensory array) device as a rapid and cost-effective screening tool to detect increasingly prevalent counterfeit electronic cigarettes, and those to which potentially hazardous excipients such as vitamin E acetate (VEA) have been added, without the need to generate and test the aerosol such products are intended to emit. A portable, in-field screening tool would also allow government officials to swiftly identify adulterated electronic cigarette e-liquids containing illicit flavorings such as menthol. Our approach involved developing canonical discriminant analysis (CDA) models to differentiate formulation components, including e-liquid bases and nicotine, which the eNose accurately identified. Additionally, models were created using e-liquid bases adulterated with menthol and VEA. The eNose and CDA model correctly identified menthol-containing e-liquids in all instances but were only able to identify VEA in 66.6% of cases. To demonstrate the applicability of this model to a commercial product, a Virginia Tobacco JUUL product was adulterated with menthol and VEA. A CDA model was constructed and, when tested against the prediction set, it was able to identify samples adulterated with menthol 91.6% of the time and those containing VEA in 75% of attempts. To test the ability of this approach to distinguish commercial e-liquid brands, a model using six commercial products was generated and tested against randomized samples on the same day as model creation. The CDA model had a cross-validation of 91.7%. When randomized samples were presented to the model on different days, cross-validation fell to 41.7%, suggesting that interday variability was problematic. However, a subsequently developed support vector machine (SVM) identification algorithm was deployed, increasing the cross-validation to 84.7%. A prediction set was challenged against this model, yielding an accuracy of 94.4%. Altered Elf Bar and Hyde IQ formulations were used to simulate counterfeit products, and in all cases, the brand identification model did not classify these samples as their reference product. This study demonstrates the eNose's capability to distinguish between various odors emitted from e-liquids, highlighting its potential to identify counterfeit and adulterated products in the field without the need to generate and test the aerosol emitted from an electronic cigarette.

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To detect damage in mechanical structures, acoustic emission (AE) inspection is considered as a powerful tool. Generally, the classical acoustic emission detection method uses a sparse sensor array to identify damage and its location. It often depends on a pre-defined wave velocity and it is difficult to yield a high localization accuracy for complicated structures using this method. In this paper, the passive guided wave phased array method, a dense sensor array method, is studied, aiming to obtain better AE localization accuracy in aluminum thin plates. Specifically, the proposed method uses a cross-shaped phased array enhanced with four additional far-end sensors for AE source localization. The proposed two-step method first calculates the real-time velocity and the polar angle of the AE source using the phased array algorithm, and then solves the location of the AE source with the additional far-end sensor. Both numerical and physical experiments on an aluminum flat panel are carried out to validate the proposed method. It is found that using the cross-shaped guided wave phased array method with enhanced far-end sensors can localize the coordinates of the AE source accurately without knowing the wave velocity in advance. The proposed method is also extended to a stiffened thin-walled structure with high localization accuracy, which validates its AE source localization ability for complicated structures. Finally, the influences of cross-shaped phased array element number and the time window length on the proposed method are discussed in detail.

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The Druze are a distinct group known for their close community, traditions, and consanguineous marriages, dating back to the eleventh century. This practice has led to unique genetic variations, impacting both pathology and gene-associated phenotypes. Some Druze clans, particularly those with exceptional long-lived family heads (ELLI), attracted attention. Given that the bulk of these ELLI were men, the d3GHR polymorphism was the first obvious possibility. Among the 73 clan members, 8.2% carried the d3GHR isoform, with nearly 11% being males. There was a significant age-related increase (p = 0.04) in this isoform among males, leading to examination of potential environmental mediators affecting gene regulation among these carriers during life (namely epigenetic). We focused on DNA methylation due to its crucial role in gene regulation, development, and disease progression. We analyzed DNA samples from 14 clan members with different GHR genotypes, finding a significant (p < 0.05) negative correlation between DNA methylation levels and age. Employing a biological age clock, we observed a significant + 4.229 years favoring the d3GHR group over the WT and heterozygous groups. In conclusion, this study highlights the advantage of d3GHR carriers among this unique Druze clan and underscores the importance of genotype-environment interaction in epigenetic regulation and its impact on health.

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BACKGROUND: Previous studies have suggested that perioperative anesthesia could have direct impacts on cancer cell biology. The present study investigated the effects of ropivacaine administration on lung adenocarcinoma cells. METHODS: Ropivacaine was administered to A549 cells at concentrations of 0.1, 1, and 6 mM for 2 h. Angiotensin-converting enzyme 2 (ACE2) small interfering RNA (siRNA) transfection was performed 6 h prior to ropivacaine administration. Cell proliferation and migration were assessed with cell counting kit 8 (CCK-8) and a wound healing assay at 0 and 24 h after anesthesia exposure. PCR arrays were performed, followed by PCR validation. RESULTS: Ropivacaine administration inhibited A549 cell proliferation and migration in a concentration-dependent manner, with ACE2 upregulation and HIF1α (hypoxia-inducible factor 1α) downregulation. The anticancer effect of ropivacaine was canceled out via ACE2 siRNA transfection. PCR arrays showed specific gene change patterns in the ropivacaine and respective ACE2-knockdown groups. EGFR (epidermal growth factor receptor), BAX (Bcl-2-associated X protein) and BCL2 (B-cell/CLL lymphoma 2) were suppressed with ropivacaine administration; these effects were reversed via ACE2 siRNA induction. CONCLUSION: Ropivacaine administration inhibited A549 cell biology in conjunction with ACE2 upregulation via the inhibition of the Wnt1 (wingless/Integrated 1) pathway.

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Background: microRNAs (miRNAs) were recognized as a promising source of diagnostic biomarker. Herein, we aim to evaluate the performance of an ultrasensitive method for detecting serum miRNAs using single molecule arrays (Simoa). Methods: In this study, candidate miRNAs were trained and tested by RT-qPCR in a cohort of PTB patients. Besides that, ultrasensitive serum miRNA detection were developed using the Single Molecule Array (Simoa) platform. In this ultra-sensitive sandwich assay, two target-specific LNA-modified oligonucleotide probes can be simply designed to be complementary to the half-sequence of the target miRNA respectively. We characterized its analytical performance and measured miRNAs in the serum of patients with pulmonary tuberculosis and healthy individuals. Results: We identified a five signature including three upregulated (miR-101, miR-196b, miR-29a) and two downregulated (miR-320b, miR-99b) miRNAs for distinguishing PTB patients from HCs, and validated in our 104 PTB patients. On the basis of Simoa technology, we developed a novel, fully automated digital analyser, which can be used to directly detect miRNAs in serum samples without pre-amplification. We successfully detected miRNAs at femtomolar concentrations (with limits of detection [LODs] ranging from 0.449 to 1.889 fM). Simoa-determined serum miR-29a and miR-99b concentrations in patients with PTB ((median 6.06 fM [range 0.00-75.22]), (median 2.53 fM [range 0.00-24.95]), respectively) were significantly higher than those in HCs ((median 2.42 fM [range 0.00-28.64]) (P < 0.05), (median 0.54 fM [range 0.00-9.12] (P < 0.0001), respectively). Serum levels of miR-320b were significantly reduced in patients with PTB (median 2.11 fM [range 0.00-39.30]) compared with those in the HCs (median 4.76 fM [range 0.00-25.10]) (P < 0.001). A combination of three miRNAs (miR-29a, miR-99b, and miR-320b) exhibited a good capacity to distinguish PTB from HCs, with an area under the curve (AUC) of 0.818 (sensitivity: 83.9%; specificity: 79.7%). Conclusions: This study benchmarks the role of Simoa as a promising tool for monitoring miRNAs in serum and offers considerable potential as a non-invasive platform for the early diagnosis of PTB.

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Rvisdiff is an R/Bioconductor package that generates an interactive interface for the interpretation of differential expression results. It creates a local web page that enables the exploration of statistical analysis results through the generation of auto-analytical visualizations. Users can explore the differential expression results and the source expression data interactively in the same view. As input, the package supports the results of popular differential expression packages such as DESeq2, edgeR, and limma. As output, the package generates a local HTML page that can be easily viewed in a web browser. Rvisdiff is freely available at https://bioconductor.org/packages/Rvisdiff/.

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Human embryonic stem cell-derived cardiomyocytes (hESC-CM) are a promising source of cardiac cells for disease modelling and regenerative medicine. However, current protocols invariably lead to mixed population of cardiac cell types and often generate cells that resemble embryonic phenotypes. Here we developed a combinatorial approach to assess the importance of extracellular matrix proteins (ECMP) in directing the differentiation of cardiomyocytes from human embryonic stem cells (hESC). We did this by focusing on combinations of ECMP commonly found in the developing heart with a broad goal of identifying combinations that promote maturation and influence chamber specific differentiation. We formulated 63 unique ECMP combinations fabricated from collagen 1, collagen 3, collagen 4, fibronectin, laminin, and vitronectin, presented alone and in combinations, leading to the identification of specific ECMP combinations that promote hESC proliferation, pluripotency, and germ layer specification. When hESC were subjected to a differentiation protocol on the ECMP combinations, it revealed precise protein combinations that enhance differentiation as determined by the expression of cardiac progenitor markers kinase insert domain receptor (KDR) and mesoderm posterior transcription factor 1 (MESP1). High expression of cardiac troponin (cTnT) and the relative expression of myosin light chain isoforms (MLC2a and MLC2v) led to the identification of three surfaces that promote a mature cardiomyocyte phenotype. Action potential morphology was used to assess chamber specificity, which led to the identification of matrices that promote chamber-specific cardiomyocytes. This study provides a matrix-based approach to improve control over cardiomyocyte phenotypes during differentiation, with the scope for translation to cardiac laboratory models and for the generation of functional chamber specific cardiomyocytes for regenerative therapies.

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Extensive research has been conducted on anti-biofouling or antibacterial surfaces, with nanostructured surfaces that mimic cicada and dragonfly wings emerging as promising candidates for mechano-bactericidal applications. These biomimetic nanostructured surfaces are capable of exerting a bactericidal effect by directly damaging the membranes of bacteria attached to nanostructures. Although research on bactericidal effect using various nanostructures have been conducted, no specific studies have yet reported on the antibacterial efficiency of the surface having nanoline array, especially regarding the spacing between nanolines. This study details the fabrication of nanoline array via ultraviolet (UV) molding with polyurethane acrylate (PUA), noted for its UV sensitivity and rapid curing, enabling the fabrication of precise and scalable nanoscale structures. Investigation into the nanoline array's antibacterial effects against Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) reveals that nanoline spacing critically influences bacterial adherence and viability, with specific spacings enhancing antibacterial properties. Scanning electron microscopy (SEM) and confocal microscopy analyses show that surface topography significantly affects bacterial behavior, with specific spacings leading to varied bacterial responses, including membrane damage and altered attachment patterns. The study highlights the potential of nanoline array in fabricating surfaces with tailored antibacterial properties, emphasizing the importance of nanoscale design in influencing bacterial interaction and viability. We also confirm the relative mechanical rigidity of the nanoline array, which exhibits antibacterial effects, through both experimental observations and numerical analysis. This indicates our proposed nanoline-array surface could have potential future applications in mechanical anti-bacterial functions that require such structural robustness.

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Nanozymes are potential candidates for constructing sensors due to their adjustable activity, high stability, and high cost-effectiveness. However, due to the lack of reasonable means, designing and preparing efficient nanozymes remains challenging. Herein, inspired by the property of natural laccase, we applied the novel and facile low-temperature plasma (LTP) technology to fabricate a series of different base-ligand Cu metal organic framework (MOF) nanozymes (namely, A-Cu, G-Cu, C-Cu and T-Cu nanozymes) with laccase-like activity successfully. Owing to the different catalytic capacities of four types of base-Cu-MOF nanozymes in the response to five common effective bioactive substances, we constructed the nanozyme-encoded array sensor for the identification of different bioactive compounds. As a result, the four-channel colorimetric sensor array was constructed, in which four laccase-like nanozymes were utilized as the sensing units, achieving high-throughput, high-sensitivity and rapid detection/identification of five common bioactive compounds in the concentration range of 1.5-150 µg mL-1 through different color output patterns. It is worth noting that the as-prepared sensor array can successfully distinguish the natural bioactive compounds in a variety of real samples. Furthermore, with the assistance of smartphones, we also designed a portable smart sensing approach for detecting the bioactive compounds effectively in food. This study has therefore not only provided an effective way for preparation highly effectively nanozymes, but also established a new sensing platform for intelligent sensing of bioactive components in food.

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Limited data on the correlation between the perineal body (PB) and stress urinary incontinence (SUI) are available. The objectives of this study were to quantify the PB using shear wave elastography (SWE) technology with a high-frequency linear array probe to evaluate the relationship between the properties of PB and stress urinary incontinence (SUI). This study included 64 women with SUI and 70 female control participants. The length, height, perimeter, and area of PB in all participants were calculated using transperineal ultrasound, and the elasticity of PB was assessed by SWE at rest and during the maximal Valsalva maneuver, respectively. In addition, the comparison of PB parameters between the patients with SUI and the healthy participants was conducted. The transperineal ultrasound and SWE examination was performed in 134 participants, and the elastic modulus values were significantly increased from participants at rest to those during the maximal Valsalva maneuver in all participants (Emax: 35.59 versus 53.13 kPa, P < 0.001; and Emean: 26.97 versus 40.25 kPa, P < 0.001). Emax and Emean of PB exhibited significant differences during the maximal Valsalva maneuver between the SUI group and the control group (47.73 versus 58.06 kPa, P < 0.001; and 35.78 versus 44.33 kPa, P < 0.001) and had a negative correlation with SUI. The BMI and PB height during the maximal Valsalva maneuver in the SUI group were found to be significantly higher than that in healthy volunteers. Emax and Emean of PB negatively correlated with BMI during the maximal Valsalva maneuver (r = -0.277, P = 0.001 and r = -0.211, P = 0.014). ROC curve analysis demonstrated that PB perimeter of less than 12.68mm was strongly associated with SUI during the maximal Valsalva maneuver, and an Emax of less than 55.76 kPa had a 100% specificity in predicting SUI. SWE can quantify the elasticity of PB, identifying a significant difference between participants at rest and during Valsalva maneuver. In addition, the stiffness of the PB was significantly lower in women with SUI than in healthy women, which may provide a noninvasive clinical practice in SUI prediction.

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Sodium ion batteries (SIBs) are promising postlithium battery technologies with high safety and low cost. However, their development is hampered by complicated electrode material preparation and unsatisfactory sodium storage performance. Here, a bismuth/N-doped carbon nanosheets (Bi/N-CNSs) composite featuring a quasi-array structure (alternated porous Bi layers and N-CNSs) with hierarchical Bi distribution (large particles of ∼35 nm in Bi layers and ultrafine Bi of ∼8 nm on N-CNSs) is prepared. Bi/N-CNSs delivers an ultralong-lifespan of 26000 cycles at 5 A g-1 and prominent rate capability of 91.5% capacity retention at 100 A g-1. Even at -40 °C, it exhibits a high rate capability of 161 mAh g-1 at 5 A g-1. Notably, the involved preparation method is characterized by a high yield of 14.53 g in a single laboratory batch, which can be further scaled up, and such a method can also be extended to synthesize other metallic-based materials.

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As an integrable micro-optical device, micro lens arrays (MLAs) have significant applications in modern optical imaging, new energy technology, and advanced displays. In order to reduce the impact of laser modification on wet etching, we propose a technique of femtosecond laser penetration-induced modification-assisted wet etching (FLIPM-WE), which avoids the influence of previous modification layers on subsequent laser pulses and effectively improves the controllability of lens array preparation. We conducted a detailed study on the effects of the laser single pulse energy, pulse number, and hydrofluoric acid etching duration on the morphology of micro lenses and obtained the optimal process parameters. Ultimately, two types of fused silica micro lens arrays with different focal lengths but the same numerical aperture (NA = 0.458) were fabricated using the FLPIM-WE technology. Both arrays exhibited excellent geometric consistency and surface quality (Ra~30 nm). Moreover, they achieved clear imaging at various magnifications with an adjustment range of 1.3×~3.0×. This provides potential technical support for special micro-optical systems.

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Cardiac organoids differentiated from induced pluripotent stem cells are emerging as a promising platform for pre-clinical drug screening, assessing cardiotoxicity, and disease modelling. However, it is challenging to simultaneously measure mechanical contractile forces and electrophysiological signals of cardiac organoids in real-time and in-situ with the existing methods. Here, we present a biting-inspired sensory system based on a resistive skin sensor and a microelectrode array. The bite-like contact can be established with a micromanipulator to precisely position the resistive skin sensor on the top of the cardiac organoid while the 3D microneedle electrode array probes from underneath. Such reliable contact is key to achieving simultaneous electro-mechanical measurements. We demonstrate the use of our system for modelling cardiotoxicity with the anti-cancer drug doxorubicin. The electro-mechanical parameters described here elucidate the acute cardiotoxic effects induced by doxorubicin. This integrated electro-mechanical system enables a suite of new diagnostic options for assessing cardiac organoids and tissues.