A new study has unveiled findings regarding genetic interactions between plants and their associated bacteria. The study, led by Dr. Asaf Levy from the Institute of Environmental Science at Hebrew University, in partnership with Dr. Yulia Fridman , Dr. Hitaishi Khandal , Prof. Sigal Savaldi-Goldstein from Faculty of Biology, Technion-Israel Institute of Technology, reveals a dynamic cross-kingdom horizontal gene transfer (HGT) that could revolutionize our understanding of plant and bacterial biology and agricultural practices.

Plants rely on a complex community of bacteria which are crucial for their health and development. The research team hypothesized and confirmed that the close and long-standing relationship between plants and their microbiota facilitates the rare phenomenon of horizontal gene transfer, where genes are transferred directly between different species.

In a new discovery, Dr. Levy and his team identified 75 unique genes that were transferred horizontally between Arabidopsis thaliana, a commonly studied model plant, and bacteria. Plants acquired 59 genes from bacteria and bacteria acquired at least 16 genes from plants during evolution. These genes primarily enhance carbohydrate metabolism and auxin biosynthesis, pivotal for plant growth regulation and immune responses. For example a certain group of bacteria, Streptomyces, acquired from plants a gene that allow them to break down chitin, a compound which is prevalent in insects and fungi. In addition, the study identified 111 genes that were transferred between bacteria and eukaryotes in general (not necessarily plants).

Moreover, the study validated these findings by demonstration that a bacterial gene from the Actinobacteria phylum, when expressed in Arabidopsis, corrected growth defects associated with the plant’s DET2 gene mutation. DET2 is essential for the synthesis of a type of plant hormone called Brassinosteroid. These are crucial for plant growth and development. A plant that lacks DET2 gene is a dwarf plant. However, by expressing the bacterial homologous DET2 gene inside plants, the researchers were able to get a plant in a normal size, demonstrating that the two genes have the same function.

"This study highlights the intricacies of plant-microbe interactions and we were surprised that genes were acquired by organisms that are located so remotely on the tree of life, such as bacteria and plants. A bacterial gene acquired by plant has to undergo some changes to be active inside plant cells. It will be interesting to study the mechanisms by which the genes are acquired and evolved. The study opens new avenues for biotechnological applications in agriculture," said Dr. Levy. "Understanding and harnessing these gene transfers could lead to innovative strategies to enhance crop resilience and productivity if we understand why and also how certain genes were transferred. It is also intriguing if bacteria exchange genes with other organisms such as animals, including humans".

With global agriculture facing increasing challenges from climate change and population growth, innovations that enhance crop resilience and productivity are urgently needed. According to projections, advancements in plant-microbe interactions could potentially increase global food production by significant margins, addressing the growing demand for food security. Currently, the agricultural sector spends billions annually combating plant diseases and environmental stresses.

The research paper titled “Widespread horizontal gene transfer between plants and bacteria” is now available in ISME Communications and can be accessed at https://doi.org/10.1093/ismeco/ycae073.

Researchers:

Shelly Haimlich¹, Yulia Fridman², Hitaishi Khandal², Sigal Savaldi-Goldstein², Asaf Levy¹

Institutions:

1) The Department of Plant Pathology and Microbiology, Institute of Environmental Science, Robert H. Smith Faculty of Agriculture, Food, and Environment, The Hebrew University of Jerusalem

2) Faculty of Biology, Technion-Israel Institute of Technology

The Hebrew University of Jerusalem is Israel’s premier academic and research institution. With over 23,000 students from 90 countries, it is a hub for advancing scientific knowledge and holds a significant role in Israel’s civilian scientific research output, accounting for nearly 40% of it and has registered over 11,000 patents. The university’s faculty and alumni have earned eight Nobel Prizes, two Turing Awards a Fields Medal, underscoring their contributions to ground-breaking discoveries. In the global arena, the Hebrew University ranks 86th according to the Shanghai Ranking. To learn more about the university’s academic programs, research initiatives, and achievements, visit the official website at http://new.huji.ac.il/en

Antibiotics are essential tools in modern medicine, regularly used to treat bacterial infections and prevent infections during surgery. However, the widespread use of antibiotics has led to many bacteria developing resistance, posing a significant threat to public health. A recent study published in PLOS Biology, led by Prof. Zvi Hayouka from the Institute of Biochemistry Food science and Nutrition at the Faculty of Agriculture, Food and Environment at the Hebrew University of Jerusalem, and Prof. Jens Rolff from the Freie Universität Berlin, along with postdoctoral fellow Dr. Bernardo Antunes, who was affiliated with both Hebrew University and Freie Universität Berlin, highlights the urgent need for new strategies to control bacterial infections due to the growing threat of antibiotic-resistant pathogens. Proper antibiotic use, quick diagnostics, and careful development of new antimicrobial agents, ideally less likely to select for resistance than current antibiotics, are crucial.

Antibiotic resistance is emerging as a pressing global health challenge. While individuals themselves do not become resistant to antibiotics, the bacteria causing infections can develop this resistance, leading to more difficult-to-treat illnesses. Recent data from the World Health Organization highlights the severity of this issue, with some countries reporting resistance rates as high as 42% for certain common bacterial strains. In the United States, the Centers for Disease Control and Prevention estimates that over 2 million antibiotic-resistant infections occur annually, underscoring the urgency of addressing this crisis.

The study explored whether newly developed random antimicrobial peptide mixtures can significantly reduce the risk of resistance evolution compared to single sequence antimicrobial peptides. The research team used the ESKAPE pathogen Pseudomonas aeruginosa, a model gram-negative bacterium, known for its challenging infections due to inherent resistance to many drug classes and its ability to form biofilms.

Pseudomonas aeruginosa was experimentally evolved in the presence of antimicrobial peptides or random antimicrobial peptide mixtures to assess resistance evolution and cross-resistance between treatments. The study also examined the fitness costs of resistance on bacterial growth and used whole-genome sequencing to identify mutations responsible for resistance. Additionally, changes in the pharmacodynamics of the evolved bacterial strains were analyzed.

The findings suggest that random antimicrobial peptide mixtures pose a much lower risk of resistance evolution compared to single antimicrobial peptides and mostly prevent cross-resistance to other treatments while maintaining or improving drug sensitivity. Prof. Zvi Hayouka emphasized the significance of their work, stating, "The growing threat of antibiotic-resistant bacteria demands innovative solutions. Our research on random antimicrobial peptide mixtures presents a promising approach to outpace bacterial resistance, offering a viable alternative to traditional antibiotics and safeguarding public health."

This research suggests that Pseudomonas aeruginosa can detect these antimicrobial agents but cannot develop effective resistance within 4 weeks in vitro. Additionally, these antimicrobial peptide cocktails are affordable to synthesize and have proven to be non-toxic and non-hemolytic in a mouse model with strong efficacy profiles in several mouse model of human pathogenic bacterial infection model.

The findings advocate for the use of random antimicrobial peptide cocktails over single peptides, as resistance developed in vitro against single peptides. Despite some antibiotics, like Teixobactin, initially being deemed "resistance-proof," this was later disproven, necessitating caution even with the promising results for the random peptide mixture . Further research should explore the interaction of these random peptide mixtures with the host immune system. Employing peptides that synergize with the host response could diminish dosage requirements and side effects. This approach could be a cost-effective method to reduce bacterial loads and prevent resistance.

“It will still be quite some time before we are ready for practical applications,” says Prof. Jens Rolff. “Still, our current work demonstrates the potential that these combinations have when it comes to reducing antimicrobial resistance.”

Alongside their active research, Prof. Zvi Hayouka has co-founded a company, in partnership with Hebrew University's technology transfer company, Yissum, dedicated to addressing antibiotic resistance through innovative solutions Pepticore (https://tarominnovative.com/projects/pepticore/). The company aims to develop and commercialize new antimicrobial agents less likely to select for resistance. Their approach includes using different combinations of antibiotics and exploring mixtures made up of millions of molecules to inhibit resistance. This initiative is crucial, as antibiotic-resistant pathogens are estimated to cause approximately 5 million deaths annually. Despite advances in diagnostics and prudent antibiotic prescribing, developing new drugs remains essential to combat increasingly resistant bacteria.

The research paper titled “The evolution of antimicrobial peptide resistance in Pseudomonas aeruginosa is severely constrained by random peptide mixtures” is now available in PLOS Biology and can be accessed at https://doi.org/10.1371/journal.pbio.3002692.

Researchers:

Bernardo Antunes^1,2, Caroline Zanchi¹, Paul R. Johnston^1,3,4, Bar Maron², Christopher Witzany⁵, Roland R. Regoes⁵, Zvi Hayouka², Jens Rolff^1,3

Institution:

1. Freie Universita¨ t Berlin, Evolutionary Biology
2. Institute of Biochemistry, Food Science and Nutrition, The Hebrew University of Jerusalem
3. Berlin Centre for Genomics in Biodiversity Research
4. University of St. Andrews, School of Medicine
5. Institute of Integrative Biology, ETH Zurich

Funding

Freie Universität Berlin and The Hebrew University of Jerusalem Joint Berlin-Jerusalem Post-Doctoral Fellowship Program

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

About Yissum

Yissum is the technology transfer company of the Hebrew University of Jerusalem. Founded in 1964, Yissum serves as a bridge between cutting-edge academic research and a global community of entrepreneurs, investors, and industry. Yissum’s mission is to benefit society by converting extraordinary innovations and transformational technologies into commercial solutions that address our most urgent global challenges. The company has registered more than 11,680 patents globally, licensed over 1,160 technologies, and has spun out over 260 companies. Yissum’s business partners span the globe. For further information please visit www.yissum.co.il.

 

 

A new study by researchers from the Psychology Department at the Hebrew University published in JMIR Ment Health have made significant strides in understanding the role of artificial intelligence (AI) in mental health therapy. Their research focuses on the delicate balance between AI-driven interactions and the irreplaceable human touch in therapeutic settings, addressing critical questions about when AI might effectively replace human therapists and when the human connection remains indispensable.

Led by Prof. Anat Perry, the team has carefully defined various aspects of empathy, comparing the empathic capabilities of humans and AI. In the current JMIR paper, the authors delve into how AI versus human capabilities align with the therapeutic needs, considering both the methodologies employed in therapeutic settings and the individual goals of patients. The study emphasizes the nuanced role of empathy in therapy, underscoring that while AI can simulate empathic interactions and sometimes even create the impression of understanding beyond human capabilities, it lacks the ability to genuinely connect on an emotional level, and crucially to genuinely care.

Prof. Perry highlights the core of their findings, stating, "While AI can provide responses that seem empathically correct, true empathy involves an emotional engagement, and signalling of genuine care, that AI simply does not have. Our study seeks to explore this boundary to better understand when AI can be beneficial in therapy and when it cannot."

The research proposes a novel hybrid therapeutic model where AI supports but does not replace human therapists. This model suggests that AI could effectively handle tasks such as initial patient intake and routine evaluations, and even assist in certain treatment modalities. However, it crucially maintains that human therapists should be involved in situations where deep empathy and compassion are required, ensuring that the therapy remains grounded in genuine human interaction.

This study aligns with emerging trends in the field of mental health therapy, where technology is increasingly integrated into traditional therapeutic practices. Existing models, such as those combining cognitive-behavioral therapy (CBT) with AI-driven tools, have shown promise in enhancing accessibility and efficiency of therapy. For instance, AI applications can offer real-time feedback and personalized recommendations, complementing the therapist's role and enabling more effective treatment plans.

Though much of the research remains theoretical, it raises empirical questions that are vital for the future of mental health therapy. The team calls on both industry professionals developing AI applications for mental health and academic researchers to consider these insights and the importance of maintaining human elements in therapy.

These theoretical opinion papers serve as a crucial reminder of the need to carefully evaluate the use of AI in mental health therapies, balancing technological innovations with the essential human connections that form the backbone of effective therapeutic relationships.

This is Perry’s third paper on the topic, following an influential Correspondence piece in Nature Human Behaviour last year (https://www.nature.com/articles/s41562-023-01675-w), and a Correspondence on AI, empathy and ethics published with a team of interdisciplinary scholars last month in Nature Machine Intelligence (https://www.nature.com/articles/s42256-024-00841-7).

The research paper titled “Considering the Role of Human Empathy in AI-Driven Therapy” is now available in JMIR Ment Health and can be accessed at https://doi.org/10.2196/56529.

Researchers:

Matan Rubin, Hadar Arnon, Jonathan D Huppert, Anat Perry

Institutions:

Psychology Department, Hebrew University of Jerusalem

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

Introducing BitterMasS, a pioneering tool developed by a team led by Phd student Evgenii Ziaikin and Prof. Masha Niv from Hebrew University and Dr. Edisson Tello and Prof. Devin Peterson from Ohio State University. BitterMasS harnesses the power of mass spectrometry to predict bitterness in compounds without requiring prior knowledge of their chemical structures. This advancement marks a significant departure from traditional methods that relied on structural data, which only covers a small fraction of the metabolome.

Bitterness, a fundamental taste modality potentially related to toxic substances, has long intrigued scientists and food experts alike. Today, an innovating study promises to revolutionize how bitterness is understood and managed in foods and beverages.

Using a dataset of over 5,400 experimental mass spectra of bitter and non-bitter compounds, BitterMasS achieved remarkable precision and recall rates in internal tests. For external validation, the tool demonstrated robust performance, accurately identifying bitter compounds without structural information. These findings underscore BitterMasS potential to streamline compound screening processes in food science, pharmaceuticals, and beyond.

"BitterMasS represents a critical shift in taste prediction," said Prof. Masha Niv, lead researcher. "By leveraging mass spectrometry data, we can now predict bitterness directly and efficiently, opening doors to new discoveries in health-promoting compounds and enhanced food processing techniques."

Researchers envision BitterMasS as a versatile tool capable of monitoring bitterness changes over time, providing critical insights into food quality and safety. This innovative approach also offers practical applications in drug development and metabolomics. 

In summary, BitterMasS stands as a testament to the power of interdisciplinary collaboration and technological innovation in advancing our understanding of taste. Its implications extend far beyond the lab, potentially reshaping how we perceive and utilize bitter compounds in various industries.

The research paper titled “BitterMasS: Predicting Bitterness from Mass Spectra” is now available in the Journal of Agricultural and Food Chemistry and can be accessed at https://www.webofscience.com/wos/woscc/full-record/WOS:001226287400001 

DOI 10.1021/acs.jafc.3c09767

Researchers:

Evgenii Ziaikin¹, Eddison Tellow², Devin G. Peterson², Masha Y. Niv¹

Institutions:

1. Hebrew University Jerusalem, Institute of Biochemistry Food & Nutrition, Robert H Smith Faculty of Agriculture, Food & Environment

2. Ohio State University, College of Food Agriculture and Environmental Sciences

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

A recent research initiative led by Doctoral candidate Amal Khayat, Prof. Hagai Levine and Prof. Yael Bar-Zeev from the Braun School of Public Health and Community Medicine at the Hebrew University-Hadassah, together with Prof. Carla Berg,  Prof. Lorien Abroms and Dr. Yan Wang from George Washington University has uncovered significant disparities in the portrayal of Philip Morris International’s (PMI) IQOS, a prominent heated tobacco product, among minority groups in Israel.

The research, published in Tobacco Control, found distinct differences in how Arab and Ultra-Orthodox media depict IQOS compared to the mainstream media. Arab media, in particular, tended to present IQOS more positively, and more likely to spread misinformation regarding its safety and social benefits, and frequently relying on PMI as a primary information source. Moreover, Arab media articles emphasized the accessibility of IQOS retail locations, mimicking advertisement.

PMI’s IQOS ranks as the top heated tobacco product globally and was introduced in Israel in 2016. Notably, advertising for all tobacco products, including IQOS, is prohibited in Israel except in print media. However, the study suggests that news media may serve as an alternative advertising channel, circumventing these advertising restrictions.

The favorable depictions of IQOS and PMI in media articles can significantly influence consumer perceptions and behaviors. While paid advertisements are known to target specific demographics, the impact of "earned" media such as news articles on these groups remains less clear.

Methodologically, the study analyzed media articles from January to October 2020 from Ifat media, utilizing abductive coding techniques. Statistical tests were employed to compare article characteristics across different subpopulations (Arab, Ultra-Orthodox Jews, and the general public). The analysis focused on understanding how IQOS and PMI were framed in the media to assess the tone and content of coverage.

The findings, based on 63 unique articles, revealed significant biases in media targeting of different subpopulations. Specifically, articles directed at Arabs and Ultra-Orthodox Jews portrayed IQOS more positively compared to those aimed at the general public—100% and 75% versus 52%, respectively. Arab media notably emphasized IQOS accessibility (81% versus 17% and 13%) and its social benefits (88% versus 8% and 17%) more prominently. Furthermore, 100% of articles in the Arab media reflected content from the tobacco company press release, compared to 35% in the general public media.

Prof. Levine, senior author: "The study underscores the critical need for rigorous media surveillance and regulatory measures, especially in media outlets targeting minority populations, to ensure fair and balanced reporting. The positive framing of IQOS in minority-targeted media highlights the potential influence of targeted marketing on public perceptions and tobacco product usage across diverse demographics. Minority populations in Israel, and likely in other countries, are not protected from the manipulative vicious marketing strategies of the tobacco industry, corrupting media outlets".

Amal Khayat, lead author: "We recommend enhanced media surveillance and regulation, particularly in minority-oriented media, to ensure accurate reporting on tobacco products. Understanding how different subpopulations, such as the Arab minority in Israel, perceive tobacco-related information can guide regulatory interventions to counteract potential misinformation and prevent disparities in tobacco-related behaviors. Our study also calls attention to the use of news media as an alternative marketing channel by tobacco companies in regions with advertising bans, advocating for measures to protect public health and mitigate the promotion of potentially harmful products."

The research paper titled “IQOS news media coverage in Israel: a comparison across three subpopulations” is now available in Tobacco Control and can be accessed at 10.1136/tc-2023-058422. 

Researchers:

Amal Khayat¹, Yael Bar-Zeev¹, Yechiel Kaufman¹, Carla J. Berg², Lorien C. Abroms², Zongshuan Duan³, Cassidy R. LoParco², Yan Wang², Yuxian Cui², Hagai Levine¹

Institutions:

1. Braun School of Public Health and Community Medicine, Faculty of Medicine, The Hebrew University of Jerusalem - Hadassah Medical Center
2. Milken Institute School of Public Health, George Washington University
3. Department of Population Health Sciences, School of Public Health, Georgia State University

Funding

This research was supported by the National Institutes of Health (NIH) and the National Cancer Institute (RO1CA239178-01-A1; MPIs: CJB, HL)

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

 

A recent study led by Prof. Daniel Mandler with Prof. Roi Baer and Dr. Hadassah Elgavi Sinai and a team at Hebrew University, published in the Journal of the American Chemical Society, reveals how organic molecules affect the behavior of tiny gold particles absorbed on surfaces. Their research deepens our understanding of how these nanoparticles absorbed on surfaces interact with their surroundings, offering important insights for various uses. The research was conducted jointly by PhD student Din Zelikovich, who carried out very careful experiments and MSc student Pavel Savchenko, who conducted the theoretical calculations.

The study found that different molecules, like 2- and 4-mercaptobenzoic acid, can cause gold nanoparticles to have significantly different electrical properties, with differences up to 71 Mv (millivolts). This highlights how crucial these molecules are in determining how nanoparticles behave.

Using advanced computer simulations and experiments, the collaboration between the experimental and theoretical teams showed that some molecules stick to gold surfaces in predictable ways, matching what they saw experimentally. However, they also found that the kinetics, namely, the rate the nanoparticles are oxidized adds more complexity to how they interact.

For instance, they discovered that gold nanoparticles stabilized by 4-mercaptobenzoic acid reacted twice as quickly as those with citrate. This finding, backed by scientific theories, shows just how much the right molecule can change how these nanoparticles act.

Prof. Daniel Mandler emphasized the significance of the research, stating, "Our study demonstrates the profound impact that capping agents have on the redox properties of nanoparticles. This understanding allows us to fine-tune nanoparticle behavior for specific applications, potentially leading to significant impact in fields ranging from catalysis to drug delivery."

As the scientific community continues to explore the intricate world of nanoparticles, this research contributes valuable knowledge to the field of nanoparticle chemistry. By shedding light on the complex interactions between nanoparticles and their capping agents, this study opens new avenues for designing and optimizing nanoparticles for a wide range of applications, promising exciting developments in nanotechnology in the years to come.

The research paper titled “The Effect of the Capping Agents of Nanoparticles on Their Redox Potential” is now available in the Journal of the American Chemical Society and can be accessed at https://pubs.acs.org/doi/10.1021/jacs.4c02524#

Researchers:

Pavel Savchenko¹, Din Zelikovich², Hadassah Elgavi Sinai¹, Roi Baer¹, Daniel Mandler²

Institutions:

1. Fritz Haber Research Center for Molecular Dynamics and Institute of Chemistry, The Hebrew University of Jerusalem
2. Institute of Chemistry, The Hebrew University of Jerusalem

Illustration

Title: Understanding how nanoparticles interact with organic molecules

Credit: Din Zelikovich (PhD student), Pavel Savchenko (MSc student) and Hadassah Elgavi Sinai (Senior Researcher).

 

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

 

 

PhD student Lena Dubinsky and Prof. Leore Grosman from the Computational Archaeology Laboratory at the Hebrew University’s Institute of Archaeology have pioneered a new method to study rock engravings, merging technological and visual analysis to uncover the intricate details behind ancient techniques. Utilizing the in-house developed ArchCUT3-D software, which allows a computational analysis of the three dimensional traits of rock engravings, the research showcases an innovative approach that provides new insights into the production processes and cultural significance of engravings found in Timna Park, southern Israel.

Historically, rock engravings have been examined primarily through their visual characteristics using comparative and interpretative methodologies. While recent works have focused on identifying production processes, these studies often neglected the visual outcomes. Dubinsky and Prof. Grosman’s research bridges this gap by using computational analysis to integrate both technological and visual aspects, offering a comprehensive understanding of ancient engraving practices.

"We employed ArchCUT3-D software to conduct a detailed analysis of 3-D data from various rock engravings. This method allowed us to extract micro-morphological evidence from engraved lines, decoding technical trends and variabilities in the execution of these ancient artworks. By examining a specific group of engraved figures, we established a link between the techniques used and the visual considerations guiding them," explains Lena Dubinsky.

Based on their findings, the researchers propose the term "Techné" to describe the choice of technique that goes beyond mere practicality, encompassing the intentional design and cultural concepts embedded in the engravings. This integrative approach challenges the traditional dichotomy between visual and technological research, presenting a unified framework for understanding ancient production acts.

The study highlights how social structures and individual actions influence production methods, suggesting that the decisions related to technique selection are reflective of broader sociocultural contexts. This perspective offers a richer narrative of ancient engravers' cognitive and material interactions, providing deeper insights into their cultural and technological environment.

The research underscores the potential of digital tools in archaeological studies. Their methodology not only advances the study of rock engravings but also sets a precedent for exploring other archaeological artifacts. By identifying "techno-visual codes" and the “fingerprints” of engraved complexes, this approach enhances our ability to understand the cultural and technological nuances of ancient societies.

"This study marks a significant step forward in archaeological research, combining advanced computational analysis with a nuanced understanding of ancient techniques and visual styles. It opens new avenues for exploring the interplay between technology and visuality in historical contexts, promising to deepen our knowledge of the past," says Prof. Grosman.

The research paper titled “Techné of Rock Engravings—the Timna Case Study” is now available in  Journal of Archaeological Method and Theory and can be accessed at https://doi.org/10.1007/s10816-024-09658-5.

Researchers:

Lena Dubinsky^1,2,3, Leore Grosman¹

Institution:

1. Computational Archaeology Laboratory, Institute of Archaeology, The Hebrew University
2. Ceramics and Glass Design Department, Bezalel Academy of Arts and Design
3. Jack, Joseph and Morton Mandel School for Advanced Studies in the Humanities, The Hebrew University

Pictures:

Stela engraving scanning process. (Credit: Liron Narunsky)

 

Stela engraving: annotated 3-D model (a); photograph (b). Annotation based on the analytical study of the micromorphology. (Credit: Liron Narunsky)

Researchers have made a significant breakthrough in quantum technology by developing a novel method that dramatically improves the stability and performance of quantum systems. This pioneering work addresses the longstanding challenges of decoherence and imperfect control, paving the way for more reliable and sensitive quantum devices.

Quantum technologies, including quantum computers and sensors, hold immense potential for revolutionizing various fields such as computing, cryptography, and medical imaging. However, their development has been hampered by the detrimental effects of noise, which can disrupt quantum states and lead to errors.

Many traditional approaches to mitigating noise in quantum systems primarily focus on temporal autocorrelation, which examines how noise behaves over time. While effective to some extent, these methods fall short when other types of noise correlations are present.

The research was conducted by experts in quantum physics, PhD. student Alon Salhov under the guidance of Prof. Alex Retzker from Hebrew University, PhD. student Qingyun Cao under the guidance of Prof. Fedor Jelezko and Dr. Genko Genov from Ulm University and Prof. Jianming Cai from Huazhong University of Science and Technology. They have introduced an innovative strategy that leverages the cross-correlation between two noise sources. By exploiting the destructive interference of cross-correlated noise, the team has managed to significantly extend the coherence time of quantum states, improve control fidelity, and enhance sensitivity for high-frequency quantum sensing.

Key achievements of this new strategy include:

Tenfold Increase in Coherence Time: The duration for which quantum information remains intact is extended ten times longer compared to previous methods.

Improved Control Fidelity: Enhanced precision in manipulating quantum systems leads to more accurate and reliable operations.

Superior Sensitivity: The ability to detect high-frequency signals surpasses the current state-of-the-art, enabling new applications in quantum sensing.

Alon Salhov said, "Our innovative approach extends our toolbox for protecting quantum systems from noise. By focusing on the interplay between multiple noise sources, we've unlocked unprecedented levels of performance, bringing us closer to the practical implementation of quantum technologies."

This advancement not only marks a significant leap in the field of quantum research but also holds promise for a wide range of applications. Industries that rely on highly sensitive measurements, such as healthcare, stand to benefit enormously from these improvements.

The study titled “Protecting Quantum Information via Destructive Interference of Correlated Noise” is now available in Physical Review Letters and can be openly accessed at https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.132.223601

Researchers:

Alon Salhov¹, Qingyun Cao^2,3, Jianming Cai³, Alex Retzker^1,4, Fedor Jelezko², and Genko Genov²

Institutions:

1. Racah Institute of Physics, The Hebrew University of Jerusalem

2. Institute for Quantum Optics, Ulm University, Germany

3. School of Physics, International Joint Laboratory on Quantum Sensing and Quantum Metrology, Huazhong University of Science and Technology, China

4. AWS Center for Quantum Computing, USA

Funding

Clore Israel Foundation Scholars Programme, the Israeli Council for Higher Education, and the Milner Foundation. This work was funded by the German Federal Ministry of Research (BMBF) by future cluster QSENS and projects DE-Brill (No. 13N16207), SPINNING, DIAQNOS (No. 13N16463), quNV2.0 (No. 13N16707), QR. X and Quamapolis (No. 13N15375), DLR via project QUASIMODO (No. 50WM2170), Deutsche Forschungsgemeinschaft (DFG) via Projects No. 386028944, No. 445243414, and No. 387073854, and Excellence Cluster POLiS European Union’s HORIZON Europe program via projects QuMicro (No. 101046911), SPINUS (No. 101135699), CQuENS (No. 101135359), QCIRCLE (No. 101059999) and FLORIN (No. 101086142), European Research Council (ERC) via Synergy grant HyperQ (No. 856432) and Carl-Zeiss-Stiftung via the Center of Integrated Quantum Science and technology (IQST) and project Utrasens-Vir. A. R. acknowledges the support of European Research Council grant QRES, Project No. 770929, Quantera grant MfQDS, Israel Science Foundation and the Schwartzmann university chair. J. M. acknowledges the National Natural Science Foundation of China (Grants No. 12161141011).

Pictures credit - the authors of the paper.

Image 1)

Title: Enhanced Quantum Memory and Sensitivity by Interfering Noise

Description:

Schematic representation of destructive interference of cross-correlated noise, control sequences and experimental setup. 

Detailed description (from the paper):

(a) The qubit is subjected to environmental noise δ(t). Applying a resonant drive with Rabi frequency Ω1 creates a protected dressed qubit which decoheres mainly due to ε1(t) - the amplitude noise in Ω1. Applying a second drive with modulation frequency eΩ1, Rabi frequency Ω2 and amplitude fluctuations ε2(t), reduces decoherence due to ε1(t). 

(b) If the cross-correlation, c, of ε1(t) and ε2(t) is nonzero, a detuning eΩ1 = Ω1 + c Ω2 2/Ω1 tilts the effective-drive axis and induces a destructive interference of the cross-correlated noise, resulting in a doubly-dressed qubit with a longer coherence time. 

(c) Measurement sequences for standard and correlated double drive (DD) protocols. (d) Experimental setup and level

scheme of the NV center

Image 2)

Title: Enhanced Quantum Memory and Sensitivity by Interfering Noise

Description: A Bloch-sphere of a qubit subjected to cross-correlated noise (blue and red). The method destructively interferes this noise, resulting in superior performance.

The Hebrew University of Jerusalem is Israel’s premier academic and research institution. With over 25,000 students from 90 countries, it is a hub for advancing scientific knowledge and holds a significant role in Israel’s civilian scientific research output, accounting for nearly 40% of it and has registered over 11,000 patents. The university’s faculty and alumni have earned eight Nobel Prizes and a Fields Medal, underscoring their contributions to ground-breaking discoveries. In the global arena, the Hebrew University ranks 86^th according to the Shanghai Ranking. To learn more about the university’s academic programs, research initiatives, and achievements, visit the official website at http://new.huji.ac.il/en

 

Researchers from the Hebrew University of Jerusalem have developed a machine learning approach to identify potential subtypes in diseases, significantly enhancing the field of disease classification and treatment strategies. The study, led by PhD student Dan Ofer and Prof. Michal Linial from the Department of Biological Chemistry at The Life Science Institute at Hebrew University, marks a significant advancement in the use of artificial intelligence in medical research.

Distinguishing diseases into distinct subtypes is pivotal for accurate study and effective treatment strategies. The Open Targets Platform integrates biomedical, genetic, and biochemical datasets to support disease ontologies, classifications, and potential gene targets. However, many disease annotations remain incomplete, often necessitating extensive expert medical input. This challenge is especially significant for rare and orphan diseases, where resources are limited.

The research introduces a novel machine learning approach to identify diseases with potential subtypes. Utilizing the extensive database of approximately 23,000 diseases documented in the Open Targets Platform, they derived new features to predict diseases with subtypes using direct evidence. Machine learning models were then applied to analyze feature importance and evaluate predictive performance, uncovering both known and novel disease subtypes.

The model achieved an impressive 89.4% ROC Area Under the Receiver Operating Characteristic Curve in identifying known disease subtypes. The integration of pre-trained deep-learning language models further enhanced the model's performance. Notably, the research identified 515 disease candidates predicted to possess previously unannotated subtypes, paving the way for new insights into disease classification.

"This project demonstrates the incredible potential of machine learning in expanding our understanding of complex diseases," said Dan Ofer. "By leveraging advanced models, we can uncover patterns and subtypes that were previously hidden, ultimately contributing to more precise and personalized treatments."

This innovative methodology enables a robust and scalable approach for improving knowledge-based annotations and provides a comprehensive assessment of disease ontology tiers. "We are excited about the potential of our machine learning approach to revolutionize disease classification," said Prof. Michal Linial. "Our findings can significantly contribute to personalized medicine, offering new avenues for therapeutic development."

The research paper titled “Automated annotation of disease subtypes” is now available in Journal of Biomedical Informatics and can be accessed at https://doi.org/10.1016/j.jbi.2024.104650.

Researchers:

Dan Ofer, Michal Linial

Institution:

Department of Biological Chemistry, The Life Science Institute, The Hebrew University of Jerusalem, Israel

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en. 

 

A new study led by Dr. Tamar Friedlander and her team at The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture at the Hebrew University, in collaboration with Prof. Ohad Feldheim from the Einstein Institute of Mathematics at the Hebrew University has developed an evolutionary-biophysical model that sheds new light on the evolution of collaborative non-self recognition self-incompatibility in plants. The study introduces a novel theoretical framework that incorporates promiscuous molecular interactions, which have been largely overlooked by traditional models.

Self-incompatibility (SI) is a widespread biological mechanism in plants having both male and female reproductive organs, that prevents self-fertilization and promotes genetic diversity. Under this mechanism, fertilization relies on the specific recognition between highly diverse proteins: the RNase (female determinant) and the SLF (male determinant). The interaction between these proteins ensures that plants are only compatible with non-self mates, thus maintaining a diverse gene pool.

The new model proposed by Dr. Friedlander and her team represents a significant advancement in understanding the evolutionary dynamics of self-incompatibility proteins. By allowing for promiscuous interactions—where interactions with unfamiliar partners are likely – and for multiple distinct partners per protein, the model aligns more closely with empirical findings than previous models that assumed only one-to-one interactions. This promiscuity enables a flexible interaction pattern between male and female proteins, offering new insights into how these proteins evolve and interact over generations.

"Our research shows that the ability of proteins to engage in promiscuous interactions is crucial for the long-term evolutionary maintenance of self-incompatibility systems," explained Dr. Friedlander. "We propose that the default state of this system is that recognition is likely and an evolutionary pressure is needed to avoid it, in contrast to what was previously thought. This flexibility not only helps in maintaining genetic diversity but also suggests that similar mechanisms could be operating in other biological systems."

The study also reveals how populations of these plants spontaneously organize into distinct compatibility classes, ensuring full compatibility across different classes while maintaining incompatibility within the same class. The model predicts various evolutionary paths that could lead to the formation or elimination of these compatibility classes based solely on point mutations. The dynamic balance between the emergence and decay of these classes, which provides a sustainable model of evolution, was analyzed by the researchers using a mixture of empirical and theoretical tools borrowed from the field of statistical mechanics in physics.

"These insights from our study have profound implications not only for plant biology but also for understanding the fundamental principles of molecular recognition and its impact on the evolution of biological networks," Dr. Friedlander added. "Our findings could also help in the conservation of plant biodiversity."

This research, which highlights the role of promiscuous and multi-partner molecular interactions, is likely to inspire seeking these two elements in additional biological systems, and help in explaining the evolution of various complex molecular networks.

The research paper titled “The role of promiscuous molecular recognition in the evolution of RNase-based self-incompatibility in plants” is now available in Nature Communications and can be accessed at https://doi.org/10.1038/s41467-024-49163-7.

Pictures

Title: A shift of paradigm in the molecular recognition model: from one-to –one (left) into many-to-many (right).

Description: Previous models of self-incompatibility accounted for only one-to-one interactions between male and female-determinant proteins. The new model allows for a more general network of interactions, where each protein can interact with any number of partners.

Credit: Tamar Friedlander and Amit Jangid.

 

Title: Tamar Friedlander holding two petunias

Credit: Nathan Mengisto, Faculty of Agriculture, HUJI.

 

Researchers:

Keren Erez¹, Amit Jangid¹, Ohad Noy Feldheim² & Tamar Friedlander¹

Institutions:

1) The Robert H. Smith Institute of Plant Sciences and Genetics in Agriculture, Faculty of Agriculture, The Hebrew University of Jerusalem

2) The Einstein Institute of Mathematics, Faculty of Natural Sciences, The Hebrew University of Jerusalem

The Hebrew University of Jerusalem is Israel's premier academic and research institution. Serving over 23,000 students from 80 countries, the University produces nearly 40% of Israel’s civilian scientific research and has received over 11,000 patents. Faculty and alumni of the Hebrew University have won eight Nobel Prizes and a Fields Medal. For more information about the Hebrew University, please visit http://new.huji.ac.il/en.