Discovery of indazole inhibitors for heat shock protein 90 as anti-cancer agents.

A series of indazole analogs, derived from the B,C-ring-truncated scaffold of deguelin, were designed to function as C-terminal inhibitors of heat shock protein 90 (HSP90) and investigated as novel antitumor agents against HER2-positive breast cancer. Among the synthesized compounds, compound 12d exhibited substantial inhibitory effects in trastuzumab-sensitive (BT474) and trastuzumab-resistant (JIMT-1) breast cancer cells, with IC50 values of 6.86 and 4.42 µM, respectively. Notably, compound 12d exhibited no cytotoxicity in normal cells. Compound 12d markedly downregulated the expression of the major HSP90 client proteins in both cell types, attributing its cytotoxicity to the destabilization and inactivation of HSP90 client proteins. Molecular docking studies using the homology model of an HSP90 homodimer demonstrated that inhibitor 12d fit nicely into the C-terminal domain, boasting a higher electrostatic complementary score than ATP. In vivo pharmacokinetic study indicated the high oral bioavailability of compound 12 d at F = 66.9 %, while toxicological studies indicated its negligible impact on hERG channels and CYP isozymes. Genotoxicity tests further confirmed its safety profile. The findings collectively position compound 12d as a promising candidate for further development as an antitumor agent against HER2-positive breast cancer.

Deep learning-based fully automatic Risser stage assessment model using abdominal radiographs.

BACKGROUND: Artificial intelligence has been increasingly used in medical imaging and has demonstrated expert level performance in image classification tasks. OBJECTIVE: To develop a fully automatic approach for determining the Risser stage using deep learning on abdominal radiographs. MATERIALS AND METHODS: In this multicenter study, 1,681 supine abdominal radiographs (age range, 9-18 years, 50% female) obtained between January 2019 and April 2022 were collected retrospectively from three medical institutions and graded manually using the United States Risser staging system. A total of 1,577 images from Hospitals 1 and 2 were used for development, and 104 images from Hospital 3 for external validation. From each radiograph, right and left iliac crest patch images were extracted using the pelvic bone segmentation model DeepLabv3 + with the EfficientNet-B0 encoder trained with 90 digitally reconstructed radiographs from pelvic computed tomography scans with a pelvic bone mask. Using these patch images, ConvNeXt-B was trained to grade according to the Risser classification. The model's performance was evaluated using accuracy, area under the receiver operating characteristic curve (AUROC), and mean absolute error. RESULTS: The fully automatic Risser stage assessment model showed an accuracy of 0.87 and 0.75, mean absolute error of 0.13 and 0.26, and AUROC of 0.99 and 0.95 on internal and external test sets, respectively. CONCLUSION: We developed a deep learning-based, fully automatic segmentation and classification model for Risser stage assessment using abdominal radiographs.

A wirelessly programmable, skin-integrated thermo-haptic stimulator system for virtual reality.

Sensations of heat and touch produced by receptors in the skin are of essential importance for perceptions of the physical environment, with a particularly powerful role in interpersonal interactions. Advances in technologies for replicating these sensations in a programmable manner have the potential not only to enhance virtual/augmented reality environments but they also hold promise in medical applications for individuals with amputations or impaired sensory function. Engineering challenges are in achieving interfaces with precise spatial resolution, power-efficient operation, wide dynamic range, and fast temporal responses in both thermal and in physical modulation, with forms that can extend over large regions of the body. This paper introduces a wireless, skin-compatible interface for thermo-haptic modulation designed to address some of these challenges, with the ability to deliver programmable patterns of enhanced vibrational displacement and high-speed thermal stimulation. Experimental and computational investigations quantify the thermal and mechanical efficiency of a vertically stacked design layout in the thermo-haptic stimulators that also supports real-time, closed-loop control mechanisms. The platform is effective in conveying thermal and physical information through the skin, as demonstrated in the control of robotic prosthetics and in interactions with pressure/temperature-sensitive touch displays.

The HSP90 inhibitor HVH-2930 exhibits potent efficacy against trastuzumab-resistant HER2-positive breast cancer.

Rationale: Resistance to targeted therapies like trastuzumab remains a critical challenge for HER2-positive breast cancer patients. Despite the progress of several N-terminal HSP90 inhibitors in clinical trials, none have achieved approval for clinical use, primarily due to issues such as induction of the heat shock response (HSR), off-target effects, and unfavorable toxicity profiles. We sought to examine the effects of HVH-2930, a novel C-terminal HSP90 inhibitor, in overcoming trastuzumab resistance. Methods: The effect of HVH-2930 on trastuzumab-sensitive and -resistant cell lines in vitro was evaluated in terms of cell viability, expression of HSP90 client proteins, and impact on cancer stem cells. An in vivo model with trastuzumab-resistant JIMT-1 cells was used to examine the efficacy and toxicity of HVH-2930. Results: HVH-2930 was rationally designed to fit into the ATP-binding pocket interface cavity of the hHSP90 homodimer in the C-terminal domain of HSP90, stabilizing its open conformation and hindering ATP binding. HVH-2930 induces apoptosis without inducing the HSR but by specifically suppressing the HER2 signaling pathway. This occurs with the downregulation of HER2/p95HER2 and disruption of HER2 family member heterodimerization. Attenuation of cancer stem cell (CSC)-like properties was associated with the downregulation of stemness factors such as ALDH1, CD44, Nanog and Oct4. Furthermore, HVH-2930 administration inhibited angiogenesis and tumor growth in trastuzumab-resistant xenograft mice. A synergistic effect was observed when combining HVH-2930 and paclitaxel in JIMT-1 xenografts. Conclusion: Our findings highlight the potent efficacy of HVH-2930 in overcoming trastuzumab resistance in HER2-positive breast cancer. Further investigation is warranted to fully establish its therapeutic potential.

Analysis of the global transcriptome and miRNAome associated with seed dormancy during seed maturation in rice (Oryza sativa L. cv. Nipponbare).

BACKGROUND: Seed dormancy is a biological mechanism that prevents germination until favorable conditions for the subsequent generation of plants are encountered. Therefore, this mechanism must be effectively established during seed maturation. Studies investigating the transcriptome and miRNAome of rice embryos and endosperms at various maturation stages to evaluate seed dormancy are limited. This study aimed to compare the transcriptome and miRNAome of rice seeds during seed maturation. RESULTS: Oryza sativa L. cv. Nipponbare seeds were sampled for embryos and endosperms at three maturation stages: 30, 45, and 60 days after heading (DAH). The pre-harvest sprouting (PHS) assay was conducted to assess the level of dormancy in the seeds at each maturation stage. At 60 DAH, the PHS rate was significantly increased compared to those at 30 and 45 DAH, indicating that the dormancy is broken during the later maturation stage (45 DAH to 60 DAH). However, the largest number of differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRs) were identified between 30 and 60 DAH in the embryo and endosperm, implying that the gradual changes in genes and miRNAs from 30 to 60 DAH may play a significant role in breaking seed dormancy. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses confirmed that DEGs related to plant hormones were most abundant in the embryo during 45 DAH to 60 DAH and 30 DAH to 60 DAH transitions. Alternatively, most of the DEGs in the endosperm were related to energy and abiotic stress. MapMan analysis and quantitative real-time polymerase chain reaction identified four newly profiled auxin-related genes (OsSAUR6/12/23/25) and one ethylene-related gene (OsERF087), which may be involved in seed dormancy during maturation. Additionally, miRNA target prediction (psRNATarget) and degradome dataset (TarDB) indicated a potential association between osa-miR531b and ethylene biosynthesis gene (OsACO4), along with osa-miR390-5p and the abscisic acid (ABA) exporter-related gene (OsMATE19) as factors involved in seed dormancy. CONCLUSIONS: Analysis of the transcriptome and miRNAome of rice embryos and endosperms during seed maturation provided new insights into seed dormancy, particularly its relationship with plant hormones such as ABA, auxin, and ethylene.

Bioresorbable shape-adaptive structures for ultrasonic monitoring of deep-tissue homeostasis.

Monitoring homeostasis is an essential aspect of obtaining pathophysiological insights for treating patients. Accurate, timely assessments of homeostatic dysregulation in deep tissues typically require expensive imaging techniques or invasive biopsies. We introduce a bioresorbable shape-adaptive materials structure that enables real-time monitoring of deep-tissue homeostasis using conventional ultrasound instruments. Collections of small bioresorbable metal disks distributed within thin, pH-responsive hydrogels, deployed by surgical implantation or syringe injection, allow ultrasound-based measurements of spatiotemporal changes in pH for early assessments of anastomotic leaks after gastrointestinal surgeries, and their bioresorption after a recovery period eliminates the need for surgical extraction. Demonstrations in small and large animal models illustrate capabilities in monitoring leakage from the small intestine, the stomach, and the pancreas.

Non-interleaved chiral metasurfaces and neural networks enhance the spatial resolution of polarimetry.

Non-interleaved chiral metasurfaces for high-spatial-resolution polarimetry are proposed and demonstrated. Furthermore, a convolutional neural network is incorporated to analyze interferometric images with the polarization state of light, and it results in accurate Stokes parameters.

The complete chloroplast genome sequence of Phlomoides kirghisorum Adylov, Kamelin & Makhmedov 1987 (Lamiaceae), an endemic species of Fergana Valley.

Phlomoides kirghisorum Adylov, Kamelin & Makhmedov 1987 is one of the poorly studied narrow endemics of Fergana Valley, one of Central Asia's most densely human-populated regions. In this study, we sequenced, assembled, and characterized the complete plastome of P. kirghisorum by using high-throughput Illumina reads. The complete chloroplast genome consisted of 151,324 bp, including a large single-copy (LSC) region (82,775 bp), a small single-copy (SSC) region (17,357 bp), and two inverted repeat regions (25,596 bp each). In the chloroplast genome of P. kirghisorum, 133 genes were detected, comprising 88 protein-encoding genes, eight ribosomal RNA (rRNA) genes, and 37 transfer RNA (tRNA) genes. The phylogenetic analysis indicated that the genetic relationship between P. kirghisorum and P. alpina was very close. This study provides basic information to explore the molecular evolution of the Phlomoides genus and the Lamiaceae family.

Wireless broadband acousto-mechanical sensing system for continuous physiological monitoring.

The human body generates various forms of subtle, broadband acousto-mechanical signals that contain information on cardiorespiratory and gastrointestinal health with potential application for continuous physiological monitoring. Existing device options, ranging from digital stethoscopes to inertial measurement units, offer useful capabilities but have disadvantages such as restricted measurement locations that prevent continuous, longitudinal tracking and that constrain their use to controlled environments. Here we present a wireless, broadband acousto-mechanical sensing network that circumvents these limitations and provides information on processes including slow movements within the body, digestive activity, respiratory sounds and cardiac cycles, all with clinical grade accuracy and independent of artifacts from ambient sounds. This system can also perform spatiotemporal mapping of the dynamics of gastrointestinal processes and airflow into and out of the lungs. To demonstrate the capabilities of this system we used it to monitor constrained respiratory airflow and intestinal motility in neonates in the neonatal intensive care unit (n = 15), and to assess regional lung function in patients undergoing thoracic surgery (n = 55). This broadband acousto-mechanical sensing system holds the potential to help mitigate cardiorespiratory instability and manage disease progression in patients through continuous monitoring of physiological signals, in both the clinical and nonclinical setting.

Suppression of TNBC metastasis by doxazosin, a novel dual inhibitor of c-MET/EGFR.

BACKGROUND: Triple-negative breast cancer (TNBC) is characterized by aggressive growth and a high propensity for recurrence and metastasis. Simultaneous overexpression of c-MET and EGFR in TNBC is associated with worse clinicopathological features and unfavorable outcomes. Although the development of new c-MET inhibitors and the emergence of 3rd-generation EGFR inhibitors represent promising treatment options, the high costs involved limit the accessibility of these drugs. In the present study, we sought to investigate the therapeutic potential of doxazosin (DOXA), a generic drug for benign prostate hyperplasia, in targeting TNBC. METHODS: The effect of DOXA on TNBC cell lines in vitro was evaluated in terms of cell viability, apoptosis, c-MET/EGFR signaling pathway, molecular docking studies and impact on cancer stem cell (CSC)-like properties. An in vivo metastatic model with CSCs was used to evaluate the efficacy of DOXA. RESULTS: DOXA exhibits notable anti-proliferative effects on TNBC cells by inducing apoptosis via caspase activation. Molecular docking studies revealed the direct interaction of DOXA with the tyrosine kinase domains of c-MET and EGFR. Consequently, DOXA disrupts important survival pathways including AKT, MEK/ERK, and JAK/STAT3, while suppressing CSC-like characteristics including CD44high/CD24low subpopulations, aldehyde dehydrogenase 1 (ALDH1) activity and formation of mammospheres. DOXA administration was found to suppress tumor growth, intra- and peri-tumoral angiogenesis and distant metastasis in an orthotopic allograft model with CSC-enriched populations. Furthermore, no toxic effects of DOXA were observed in hepatic or renal function. CONCLUSIONS: Our findings highlight the potential of DOXA as a therapeutic option for metastatic TNBC, warranting further investigation.

Predicting Non-Small-Cell Lung Cancer Survival after Curative Surgery via Deep Learning of Diffusion MRI.

BACKGROUND: the objective of this study is to evaluate the predictive power of the survival model using deep learning of diffusion-weighted images (DWI) in patients with non-small-cell lung cancer (NSCLC). METHODS: DWI at b-values of 0, 100, and 700 sec/mm2 (DWI0, DWI100, DWI700) were preoperatively obtained for 100 NSCLC patients who underwent curative surgery (57 men, 43 women; mean age, 62 years). The ADC0-100 (perfusion-sensitive ADC), ADC100-700 (perfusion-insensitive ADC), ADC0-100-700, and demographic features were collected as input data and 5-year survival was collected as output data. Our survival model adopted transfer learning from a pre-trained VGG-16 network, whereby the softmax layer was replaced with the binary classification layer for the prediction of 5-year survival. Three channels of input data were selected in combination out of DWIs and ADC images and their accuracies and AUCs were compared for the best performance during 10-fold cross validation. RESULTS: 66 patients survived, and 34 patients died. The predictive performance was the best in the following combination: DWI0-ADC0-100-ADC0-100-700 (accuracy: 92%; AUC: 0.904). This was followed by DWI0-DWI700-ADC0-100-700, DWI0-DWI100-DWI700, and DWI0-DWI0-DWI0 (accuracy: 91%, 81%, 76%; AUC: 0.889, 0.763, 0.711, respectively). Survival prediction models trained with ADC performed significantly better than the one trained with DWI only (p-values < 0.05). The survival prediction was improved when demographic features were added to the model with only DWIs, but the benefit of clinical information was not prominent when added to the best performing model using both DWI and ADC. CONCLUSIONS: Deep learning may play a role in the survival prediction of lung cancer. The performance of learning can be enhanced by inputting precedented, proven functional parameters of the ADC instead of the original data of DWIs only.

Perception, performance, and detectability of conversational artificial intelligence across 32 university courses.

The emergence of large language models has led to the development of powerful tools such as ChatGPT that can produce text indistinguishable from human-generated work. With the increasing accessibility of such technology, students across the globe may utilize it to help with their school work-a possibility that has sparked ample discussion on the integrity of student evaluation processes in the age of artificial intelligence (AI). To date, it is unclear how such tools perform compared to students on university-level courses across various disciplines. Further, students' perspectives regarding the use of such tools in school work, and educators' perspectives on treating their use as plagiarism, remain unknown. Here, we compare the performance of the state-of-the-art tool, ChatGPT, against that of students on 32 university-level courses. We also assess the degree to which its use can be detected by two classifiers designed specifically for this purpose. Additionally, we conduct a global survey across five countries, as well as a more in-depth survey at the authors' institution, to discern students' and educators' perceptions of ChatGPT's use in school work. We find that ChatGPT's performance is comparable, if not superior, to that of students in a multitude of courses. Moreover, current AI-text classifiers cannot reliably detect ChatGPT's use in school work, due to both their propensity to classify human-written answers as AI-generated, as well as the relative ease with which AI-generated text can be edited to evade detection. Finally, there seems to be an emerging consensus among students to use the tool, and among educators to treat its use as plagiarism. Our findings offer insights that could guide policy discussions addressing the integration of artificial intelligence into educational frameworks.

Development of a metabolite calculator for diagnosis of pancreatic cancer.

BACKGROUND: Carbohydrate antigen (CA) 19-9 is a known pancreatic cancer (PC) biomarker, but is not commonly used for general screening due to its low sensitivity and specificity. This study aimed to develop a serum metabolites-based diagnostic calculator for detecting PC with high accuracy. METHODS: A targeted quantitative approach of direct flow injection-tandem mass spectrometry combined with liquid chromatography-tandem mass spectrometry was employed for metabolomic analysis of serum samples using an Absolute IDQ™ p180 kit. Integrated metabolomic analysis was performed on 241 pooled or individual serum samples collected from healthy donors and patients from nine disease groups, including chronic pancreatitis, PC, other cancers, and benign diseases. Orthogonal partial least squares discriminant analysis (OPLS-DA) based on characteristics of 116 serum metabolites distinguished patients with PC from those with other diseases. Sparse partial least squares discriminant analysis (SPLS-DA) was also performed, incorporating simultaneous dimension reduction and variable selection. Predictive performance between discrimination models was compared using a 2-by-2 contingency table of predicted probabilities obtained from the models and actual diagnoses. RESULTS: Predictive values obtained through OPLS-DA for accuracy, sensitivity, specificity, balanced accuracy, and area under the receiver operating characteristic curve (AUC) were 0.9825, 0.9916, 0.9870, 0.9866, and 0.9870, respectively. The number of metabolite candidates was narrowed to 76 for SPLS-DA. The SPLS-DA-obtained predictive values for accuracy, sensitivity, specificity, balanced accuracy, and AUC were 0.9773, 0.9649, 0.9832, 0.9741, and 0.9741, respectively. CONCLUSIONS: We successfully developed a 76 metabolome-based diagnostic panel for detecting PC that demonstrated high diagnostic performance in differentiating PC from other diseases.

Implantable, Bioresorbable Radio Frequency Resonant Circuits for Magnetic Resonance Imaging.

Magnetic resonance imaging (MRI) is widely used in clinical care and medical research. The signal-to-noise ratio (SNR) in the measurement affects parameters that determine the diagnostic value of the image, such as the spatial resolution, contrast, and scan time. Surgically implanted radiofrequency coils can increase SNR of subsequent MRI studies of adjacent tissues. The resulting benefits in SNR are, however, balanced by significant risks associated with surgically removing these coils or with leaving them in place permanently. As an alternative, here the authors report classes of implantable inductor-capacitor circuits made entirely of bioresorbable organic and inorganic materials. Engineering choices for the designs of an inductor and a capacitor provide the ability to select the resonant frequency of the devices to meet MRI specifications (e.g., 200 MHz at 4.7 T MRI). Such devices enhance the SNR and improve the associated imaging capabilities. These simple, small bioelectronic systems function over clinically relevant time frames (up to 1 month) at physiological conditions and then disappear completely by natural mechanisms of bioresorption, thereby eliminating the need for surgical extraction. Imaging demonstrations in a nerve phantom and a human cadaver suggest that this technology has broad potential for post-surgical monitoring/evaluation of recovery processes.

Role of graphene quantum dots with discrete band gaps on SnO2 nanodomes for NO2 gas sensors with an ultralow detection limit.

NO2 is a major air pollutant that should be monitored due to its harmful effects on the environment and human health. Semiconducting metal oxide-based gas sensors have been widely explored owing to their superior sensitivity towards NO2, but their high operating temperature (>200 °C) and low selectivity still limit their practical use in sensor devices. In this study, we decorated graphene quantum dots (GQDs) with discrete band gaps onto tin oxide nanodomes (GQD@SnO2 nanodomes), enabling room temperature (RT) sensing towards 5 ppm NO2 gas with a noticeable response ((Ra/Rg) - 1 = 4.8), which cannot be matched using pristine SnO2 nanodomes. In addition, the GQD@SnO2 nanodome based gas sensor shows an extremely low detection limit of 1.1 ppb and high selectivity compared to other pollutant gases (H2S, CO, C7H8, NH3, and CH3COCH3). The oxygen functional groups in GQDs specifically enhance NO2 accessibility by increasing the adsorption energy. Strong electron transfer from SnO2 to GQDs widens the electron depletion layer at SnO2, thereby improving the gas response over a broad temperature range (RT-150 °C). This result provides a basic perspective for utilizing zero-dimensional GQDs in high-performance gas sensors operating over a wide range of temperatures.

Ebastine impairs metastatic spread in triple-negative breast cancer by targeting focal adhesion kinase.

We sought to investigate the utility of ebastine (EBA), a second-generation antihistamine with potent anti-metastatic properties, in the context of breast cancer stem cell (BCSC)-suppression in triple-negative breast cancer (TNBC). EBA binds to the tyrosine kinase domain of focal adhesion kinase (FAK), blocking phosphorylation at the Y397 and Y576/577 residues. FAK-mediated JAK2/STAT3 and MEK/ERK signaling was attenuated after EBA challenge in vitro and in vivo. EBA treatment induced apoptosis and a sharp decline in the expression of the BCSC markers ALDH1, CD44 and CD49f, suggesting that EBA targets BCSC-like cell populations while reducing tumor bulk. EBA administration significantly impeded BCSC-enriched tumor burden, angiogenesis and distant metastasis while reducing MMP-2/-9 levels in circulating blood in vivo. Our findings suggest that EBA may represent an effective therapeutic for the simultaneous targeting of JAK2/STAT3 and MEK/ERK for the treatment of molecularly heterogeneous TNBC with divergent profiles. Further investigation of EBA as an anti-metastatic agent for the treatment of TNBC is warranted.

Cutting Off H+ Leaks on the Inner Mitochondrial Membrane: A Proton Modulation Approach to Selectively Eradicate Cancer Stem Cells.

Cancer stem cells (CSCs) are associated with the invasion and metastatic relapse of various cancers. However, current cancer therapies are limited to targeting the bulk of primary tumor cells while remaining the CSCs untouched. Here, we report a new proton (H+) modulation approach to selectively eradicate CSCs via cutting off the H+ leaks on the inner mitochondrial membrane (IMM). Based on the fruit extract of Gardenia jasminoides, a multimodal molecule channel blocker with high biosafety, namely, Bo-Mt-Ge, is developed. Importantly, in this study, we successfully identify that mitochondrial uncoupling protein UCP2 is closely correlated with the stemness of CSCs, which may offer a new perspective for selective CSC drug discovery. Mechanistic studies show that Bo-Mt-Ge can specifically inhibit the UCP2 activities, decrease the H+ influx in the matrix, regulate the electrochemical gradient, and deplete the endogenous GSH, which synergistically constitute a unique MoA to active apoptotic CSC death. Intriguingly, Bo-Mt-Ge also counteracts the therapeutic resistance via a two-pronged tactic: drug efflux pump P-glycoprotein downregulation and antiapoptotic factor (e.g., Bcl-2) inhibition. With these merits, Bo-Mt-Ge proved to be one of the safest and most efficacious anti-CSC agents, with ca. 100-fold more potent than genipin alone in vitro and in vivo. This study offers new insights and promising solutions for future CSC therapies in the clinic.

Fighting bias with bias: How same-race endorsements reduce racial discrimination on Airbnb.

Recent studies have documented racial discrimination in online interactions, mirroring the historic bias observed offline. The sharing economy is especially vulnerable due to greater dependence on mutual trust in sharing a ride, residence, or date with a stranger. These services rely on user recommendations to build trust, but the effects of these peer evaluations on racial bias are only beginning to be explored. Using data from Airbnb, we examine in-group preference for same-race hosts as well as same-race recommendations. The unexpected result is that these two manifestations of racial bias are offsetting, not reinforcing. White guests largely overcame their racial bias in host selection when hosts were endorsed by previous white guests. Moreover, we found no evidence of racial bias in the affective enthusiasm of endorsements, which suggests that the preference for same-race endorsements is motivated by the race of the recommender, not the content of the recommendation.

Responsive materials and mechanisms as thermal safety systems for skin-interfaced electronic devices.

Soft, wireless physiological sensors that gently adhere to the skin are capable of continuous clinical-grade health monitoring in hospital and/or home settings, of particular value to critically ill infants and other vulnerable patients, but they present risks for injury upon thermal failure. This paper introduces an active materials approach that automatically minimizes such risks, to complement traditional schemes that rely on integrated sensors and electronic control circuits. The strategy exploits thin, flexible bladders that contain small volumes of liquid with boiling points a few degrees above body temperature. When the heat exceeds the safe range, vaporization rapidly forms highly effective, thermally insulating structures and delaminates the device from the skin, thereby eliminating any danger to the skin. Experimental and computational thermomechanical studies and demonstrations in a skin-interfaced mechano-acoustic sensor illustrate the effectiveness of this simple thermal safety system and suggest its applicability to nearly any class of skin-integrated device technology.