Publications

Variable efficiency of nonsense-mediated mRNA decay across human tissues, tumors and individuals
29/09/2025
Guillermo Palou-Márquez; Fran Supek
Genome Biology

Background

Nonsense-mediated mRNA decay (NMD) is a quality-control pathway that degrades mRNA bearing premature termination codons (PTCs) resulting from mutation or mis-splicing, and that additionally participates in gene regulation of unmutated transcripts. While NMD activity is known to differ between examples of PTCs, it is less well studied if human tissues differ in NMD activity, or if individuals differ.

Results

We analyzed exomes and matched transcriptomes from Human tumors and healthy tissues to quantify individual-level NMD efficiency, and assess its variability between tissues, tumors, and individuals. This was done by monitoring mRNA levels of endogenous NMD target transcripts, and additionally supported by allele-specific expression of germline PTCs. Nervous system and reproductive system tissues have lower NMD efficiency than other tissues, such as the digestive tract. Next, there is systematic inter-individual variability in NMD efficiency, and we identify two underlying mechanisms. First, somatic copy number alterations can robustly associate with NMD efficiency, prominently the commonly-occurring gain at chromosome 1q that encompasses two core NMD genes: SMG5 and SMG7 and additional functionally interacting genes such as PMF1 and GON4L. Second, deleterious germline variants in genes such as the KDM6B chromatin modifier can associate with higher or lower NMD efficiency in individuals. Variable NMD efficiency modulates positive selection upon somatic nonsense mutations in tumor suppressor genes, and is associated with cancer patient survival and immunotherapy responses.

Conclusions

NMD efficiency is variable across human tissues, and it is additionally variable across individuals and tumors thereof due to germline and somatic genetic alterations.

Advances in Metals and Metal Hybrids-Based Gas Sensors and Their Applications
11/09/2025
Qu, D.; Cheng, B.; Shao, X.; Hu, J.; Bai, S.; Zhang, Y.; Wu, W.; Haick, H.
Rare Metals

As a kind of node on the Internet of Things, gas sensor is specifically utilized for detecting gaseous chemical species and humidity. Functioning as a kind of discrete electronic components, gas sensors have been extensively implemented in many fields, including agricultural production, public safety, healthcare activity, dual-carbon strategic initiatives, new energy vehicles, food engineering, etc. Metals and metal hybrids are one of the most important classes of sensitive materials. In this review article, the advancements in gas sensors based on metals and metal-hybrid materials have been comprehensively introduced, focusing on their unique mechanisms, performance enhancements, and practical applications. Critical thinking and ideas regarding the orientation of the development of metals and metal hybrids-based gas sensors in the future are discussed.

Advanced Materials in Responsible Electronics: Innovations for Sustainability, Health and Circularity
17/08/2025
Omar, R.; Yang, J.; Huynh, T. P.; Gulia, K.; Tavolacci, S.C.; Wu, W.; Wang, Y.; Haick, H.
Advanced Materials Technologies

Contemporary electronic devices generate substantial quantities of electronic waste (e-waste), presenting a significant environmental challenge and exerting considerable pressure on the health of the Earth’s ecosystems. Owing to the industry’s heavy reliance on limited resources and the use of nondegradable components, innovation is necessary in device design, use, and end-of-life management. This review delves into the growing field of advanced materials for sustainable electronics, emphasizing their critical role in transforming the industry toward sustainability. The use of advanced materials in a sustainable way offers promising opportunities for reducing environmental harm and health risks while enhancing device performance and longevity. This interdisciplinary review explores themes such as energy efficiency, sustainable materials, recycling potential, resource consumption reduction, and environmental and health monitoring. It aims to illuminate recent progress, highlight ongoing challenges, and examine future prospects and applications for advanced materials in the pursuit of responsible electronics.

Spatio-temporal deep learning with temporal attention for indeterminate lung nodule classification
15/08/2025
Farina, B., Carbajo Benito, R., Montalvo-García, D., Bermejo-Peláez, D., Maceiras, L.S., Ledesma-Carbayo, M.J.
Computers in Biology and Medicine
Lung cancer is the leading cause of cancer-related death worldwide. Deep learning-based computer-aided diagnosis (CAD) systems in screening programs enhance malignancy prediction, assist radiologists in decision-making, and reduce inter-reader variability. However, limited research has explored the analysis of repeated annual exams of indeterminate lung nodules to improve accuracy.
We introduced a novel spatio-temporal deep learning framework, the global attention convolutional recurrent neural network (globAttCRNN), to predict indeterminate lung nodule malignancy using serial screening computed tomography (CT) images from the National Lung Screening Trial (NLST) dataset. The model comprises a lightweight 2D convolutional neural network for spatial feature extraction and a recurrent neural network with a global attention module to capture the temporal evolution of lung nodules. Additionally, we proposed new strategies to handle missing data in the temporal dimension to mitigate potential biases arising from missing time steps, including temporal augmentation and temporal dropout.
Our model achieved an area under the receiver operating characteristic curve (AUC-ROC) of 0.954 in an independent test set of 175 lung nodules, each detected in multiple CT scans over patient follow-up, outperforming baseline single-time and multiple-time architectures.
The temporal global attention module prioritizes informative time points, enabling the model to capture key spatial and temporal features while ignoring irrelevant or redundant information. Our evaluation emphasizes its potential as a valuable tool for the diagnosis and stratification of patients at risk of lung cancer.
Cancer screening: recent developments and future directions
19/03/2025
Jacob Levman, Yoav Y. Broza
Scientific Reports

Cancer is among the most common causes of mortality worldwide. Screening for cancer involves surveillance of populations towards identification of cancer that was unknown to the patient. Therapeutic treatments for cancer generally are more effective when applied earlier on in the condition’s development, as such, screening for cancer has the potential to improve the standard for patient care and improving mortality and morbidity associated with the disease. Cancer screening has increasingly become dependent on advanced technologies to assist in the identification and characterization of tumours. This article Collection showcases current research towards the development of new methods for cancer screening, including the development of new advanced technologies in this domain such as novel methods incorporating liquid biopsies, tailed primer isothermal amplification assays, and infrared spectroscopy. As is common in modern research, approaches make use of computational techniques as a critical component in cancer screening, and research is highlighted on the use of artificial intelligence, which is now a common technological innovation contributing to the overall cancer screening process in research studies. Future directions for cancer screening are discussed.

LUCIA Newsletter 5, March 2025
01/04/2025

This newsletter provides an update about the project activities.

Short term effects of e-cigarettes smoking on cardio-respiratory parameters, volatile organic compounds and inflammatory markers
09/06/2025
Suha Rizik, Ronen Bar-Yoseph, Moneera Hanna, Fahed Hakim, Yoav Y Broza, Amir Sader, Yazeed Toukan, Hossam Haick, Lea Bentur, Michal Gur
ERJ Open Research

Background
Electronic cigarettes (e-cigarettes) have gained popularity in recent years. While initially introduced as a safe alternative for tobacco and a bridge for smoking cessation, subsequent studies found that they contain toxic substances. We aimed to assess the acute effect of a single session of e-cigarette smoking on cardiorespiratory parameters, exhaled volatile organic compounds (VOCs) and markers of inflammation.

Methods
A prospective single-centre study was carried out. Participants (healthy volunteers, former e-cigarette users) were assessed before and after a 30-min session of e-cigarette smoking. Evaluations included vital signs, pulmonary functions – spirometry and fractional exhaled nitric oxide (FeNO) – blood and exhaled breath condensate (EBC) cytokines and electronic nose (e-nose) for analysis of exhaled VOCs profile.

Results
30 participants aged 27.9±4.4 years were enrolled in the study. Post-smoking observations revealed a significant increase in heart rate (77.5±10.9 to 85.5±12.1 beats·min−1, p=0.002), respiratory rate (15.4±2.2 to 17.1±1.8 breaths·min−1, p=0.002) and blood pressure (systolic 118±8.1 to 123.5±11.9, p=0.017; diastolic 73.9±8.4 to 78.5±6.3 mmHg, p=0.011). FeNO decreased significantly (median of 11 (7.5–15.5) to 9.7 (7.3–17.3) ppb, p=0.024). Analysis of e-nose found a significant change of exhaled VOC pattern after e-cigarette smoking. No significant changes were found in spirometry and cytokine levels in blood or EBC.

Conclusions
A single session of 30 min of e-cigarette smoking caused significant cardiorespiratory effects, decreased FeNO and altered exhaled VOC pattern, similar to the effect seen with cigarette and water-pipe smoking.‏ The observed acute effects, together with the well-known chronic risks, highlight the importance of effective regulation of e-cigarettes.

Biodegradable, Humidity-Insensitive Mask-Integrated E-Nose for Sustainable and Non-Invasive Continuous Breath Analysis
24/02/2025
Indrajit Mondal, Adan Zoabi, Hossam Haick
Advanced Functional Materials

Breath analysis offers a non-invasive approach to modern diagnostics by capturing volatile organic compounds (VOCs) in exhaled breath. However, current breath analysis technologies face challenges like humidity sensitivity, high costs, and biodegradable solutions, limiting their scalability and environmental sustainability. This study presents a paper-based, biodegradable, humidity-insensitive electronic nose (e-nose) sensor array integrated into a face mask for real-time breath analysis. The sensors, coated with hydrophobic polymer coating, ensure robust insensitivity to humidity, enabling reliable detection of VOCs even in high-moisture environments. The mask-integrated e-nose facilitates real-time breath monitoring for applications such as alcohol consumption tracking and respiratory health assessment. For the latter, Tuberculosis (TB) detection is selected as a representative use case, achieving 89% accuracy in disease diagnosis and recovery monitoring using a pre-trained deep-learning model. The fully-biodegradable paper-based sensor naturally degrades in soil within months, underscoring its eco-friendly design and suitability for disposable health monitoring. This work introduces a sustainable, user-friendly approach to breath analysis with potential applications in non-invasive disease detection and personalized healthcare monitoring.

Chemical Tomography of Cancer Organoids and Cyto-Proteo-Genomic Development Stages Through Chemical Communication Signals
11/02/2025
Arnab Maity, Vivian Darsa Maidantchik, Keren Weidenfeld, Sarit Larisch, Dalit Barkan, and Hossam Haick
Advanced Materials

Organoids mimic human organ function, offering insights into development and disease. However, non-destructive, real-time monitoring is lacking, as traditional methods are often costly, destructive, and low-throughput. In this article, a non-destructive chemical tomographic strategy is presented for decoding cyto-proteo-genomics of organoid using volatile signaling molecules, hereby, Volatile Organic Compounds (VOCs), to indicate metabolic activity and development of organoids. Combining a hierarchical design of graphene-based sensor arrays with AI-driven analysis, this method maps VOC spatiotemporal distribution and generate detailed digital profiles of organoid morphology and proteo-genomic features. Lens- and label-free, it avoids phototoxicity, distortion, and environmental disruption. Results from testing organoids with the reported chemical tomography approach demonstrate effective differentiation between cyto-proteo-genomic profiles of normal and diseased states, particularly during dynamic transitions such as epithelial-mesenchymal transition (EMT). Additionally, the reported approach identifies key VOC-related biochemical pathways, metabolic markers, and pathways associated with cancerous transformations such as aromatic acid degradation and lipid metabolism. This real-time, non-destructive approach captures subtle genetic and structural variations with high sensitivity and specificity, providing a robust platform for multi-omics integration and advancing cancer biomarker discovery.

Microneedle-based Integrated Pharmokinetic and Pharmacodynamic Evaluation Platform for Personalizes Medicine
07/07/2025
Yang, J.; Gong, X.; Zheng, Y.; Duan, H.; Chen, S.; Wu, T.; Yi, C.; Jiang, L.; Haick, H.
Nature Communications

Precision and personalized medicine for disease management necessitates real-time, continuous monitoring of biomarkers and therapeutic drugs to adjust treatment regimens based on individual patient responses. This study introduces a wearable Microneedle-based Continuous Biomarker/Drug Monitoring (MCBM) system, designed for the simultaneous, in vivo pharmacokinetic and pharmacodynamic evaluation for diabetes. Utilizing a dual-sensor microneedle and a layer-by-layer nanoenzyme immobilization strategy, the MCBM system achieves high sensitivity and specificity in measuring glucose and metformin concentrations in skin interstitial fluid (ISF). Seamless integration with a smartphone application enables real-time data analysis and feedback, fostering a pharmacologically informed approach to diabetes management. The MCBM system’s validation and in vivo trials demonstrate its precise monitoring of glucose and metformin, offering a tool for personalized treatment adjustments. Its proven biocompatibility and safety suit long-term usage. This system advances personalized diabetes care, highlighting the move towards wearables that adjust drug dosages in real-time, enhancing precision and personalized medicine.