A new study from Rutgers Health shows that ciprofloxacin, a staple treatment for urinary tract infections, throws Escherichia coli (E. coli) into an energy crisis that saves many cells from death and speeds the evolution of full-blown resistance.

“Antibiotics can actually change bacterial metabolism,” said Barry Li, a student at Rutgers New Jersey Medical School pursuing a dual doctoral degree for physician-scientists and the first author of the paper published in Nature Communications. “We wanted to see what those changes do to the bugs’ chances of survival.”

Li and senior author Jason Yang focused on adenosine triphosphate (ATP), the molecular fuel that powers cells. When ATP levels crash, cells experience “bioenergetic stress.” To mimic that stress, the team engineered E. coli with genetic drains that constantly burned ATP or its cousin nicotinamide adenine dinucleotide (NADH). Then, they pitted both the engineered strains and normal bacteria against ciprofloxacin.

The results surprised the researchers. The drug and the genetic drains each slashed ATP, but rather than slowing down, the bacteria revved up. Respiration soared, and the cells spewed extra reactive-oxygen molecules that can damage DNA. That frenzy produced two troubling outcomes.

First, more of the bacteria cells survived.

In time-kill tests, ten times as many stressed cells weathered a lethal ciprofloxacin dose compared with unstressed controls. These hardy stragglers, called persister cells, lie low until the drug is gone and then rebound to launch a new infection.

People have long blamed sluggish metabolism for persister cell formation.

“People expected a slower metabolism to cause less killing,” Li said. “We saw the opposite. The cells ramp up metabolism to refill their energy tanks and that turns on stress responses that slow the killing.”

Follow-up experiments traced the protection to the stringent response, a bacterial alarm system that reprograms the cell under stress.

Second, stressed cells mutated faster to evolve antibiotic resistance.

While persisters keep infections smoldering, genetic resistance can render a drug useless outright. The Rutgers group cycled E. coli through escalating ciprofloxacin doses and found that stressed cells reached the resistance threshold four rounds sooner than normal cells. DNA sequencing and classic mutation tests pointed to oxidative damage and error-prone repair as the culprits.

“The changes in metabolism are making antibiotics work less well and helping bacteria evolve resistance,” said Yang, an assistant professor at the medical school and Chancellor Scholar of microbiology, biochemistry & molecular genetics.

Preliminary measurements show that gentamicin and ampicillin also drain ATP in addition to ciprofloxacin. The stress effect may span very different pathogens, including the pathogen Mycobacterium tuberculosis, which is highly sensitive to ATP shocks.

If so, the discovery casts new light on a global threat. Antibiotic resistance already contributes to 1.27 million deaths a year. Strategies that ignore the metabolic fallout of treatment may be missing a key lever.

The findings suggest several changes for antibiotic development and use.

First, screen candidate antibiotics for unintended energy-drain side effects. Second, pair existing drugs with anti-evolution boosters that block the stress pathways or mop up the extra oxygen radicals. Third, reconsider the instinct to blast infections with the highest possible dose. Earlier studies and the new data both hint that extreme concentrations can trigger the very stress that protects bacteria.

“Bacteria turn our attack into a training camp,” Yang said. “If we can cut the power to that camp, we can keep our antibiotics working longer.”

Li and Yang are planning on testing compounds that soothe bioenergetic stress in the hope of turning the microbial energy crisis back into an Achilles’ heel rather than a shield.

The study finds that using Tumor Treating Fields therapy (TTFields), which delivers targeted waves of electric fields directly into tumors to stop their growth and signal the body’s immune system to attack cancerous tumor cells, may extend survival among patients with glioblastoma, when combined with immunotherapy (pembrolizumab) and chemotherapy (temozolomide).

TTFields disrupt tumor growth using low-intensity, alternating electric fields that push and pull key structures inside tumor cells in continually shifting directions, making it difficult for the cells to multiply. Preventing tumor growth gives patients a better chance of successfully fighting the cancer. When used to treat glioblastoma, TTFields are delivered through a set of mesh electrodes that are strategically positioned on the scalp, generating fields at a precise frequency and intensity focused on the tumor. Patients wear the electrodes for approximately 18 hours a day.

Researchers observed that TTFields attract more tumor-fighting T cells, which are white blood cells that identify and attack cancer cells, into and around the glioblastoma. When followed by immunotherapy, these T cells stay active longer and are replaced by even stronger, more effective tumor-fighting T cells.

“By using TTFields with immunotherapy, we prime the body to mount an attack on the cancer, which enables the immunotherapy to have a meaningful effect in ways that it could not before,” said David Tran, MD, PhD, chief of neuro-oncology with Keck Medicine, co-director of the USC Brain Tumor Center and corresponding author of the study. “Our findings suggest that TTFields may be the key to unlocking the value of immunotherapy in treating glioblastoma.”

TTFields are often combined with chemotherapy in cancer treatment. However, even with aggressive treatment, the prognosis for glioblastoma remains poor. Immunotherapy, while successful in many other cancer types, has also not proved effective for glioblastoma when used on its own.

However, in this study, adding immunotherapy to TTFields and chemotherapy was associated with a 70% increase in overall survival. Notably, patients with larger, unresected (not surgically removed) tumors showed an even stronger immune response to TTFields and lived even longer. This suggests that, when it comes to kick-starting the body’s immune response against the cancer, having a larger tumor may provide more targets for the therapy to work against.

Using alternating electric fields to unlock immunotherapy

Pembrolizumab, the immunotherapy used in this study, is an immune checkpoint inhibitor (ICI), which enhances the body’s natural ability to fight cancers by improving T cells’ ability to identify and attack cancer cells.

However, there are typically few T cells in and around glioblastomas because these tumors originate in the brain and are shielded from the body’s natural immune response by the blood-brain barrier. This barrier safeguards the brain by tightly regulating which cells and substances enter from the bloodstream. Sometimes, this barrier even blocks T cells and other therapies that could help kill brain tumors.

This immunosuppressive environment inside and around the glioblastoma is what makes common cancer therapies like pembrolizumab and chemotherapy significantly less effective in treating it. Tran theorized the best way to get around this issue was to start an immune reaction directly inside the tumor itself, an approach known as in situ immunization, using TTFields.

This study demonstrates that combining TTFields with immunotherapy triggers a potent immune response within the tumor — one that ICIs can then amplify to bolster the body’s own defense against cancer.

“Think of it like a team sport — immunotherapy sends players in to attack the tumor (the offense), while TTFields weaken the tumor’s ability to fight back (the defense). And just like in team sports, the best defense is a good offense,” said Tran, who is also a member of the USC Norris Comprehensive Cancer Center.

Study methodology and results

The study analyzed data from 2-THE-TOP, a Phase 2 clinical trial, which enrolled 31 newly diagnosed glioblastoma patients who had completed chemoradiation therapy. Of those, 26 received TTFields combined with both chemotherapy and immunotherapy. Seven of these 26 patients had inoperable tumors due to their locations — an especially high-risk subgroup with the worst prognosis and few treatment options.

Patients in the trial were given six to 12 monthly treatments of chemotherapy alongside TTFields for up to 24 months. The number and duration of treatments were determined by patients’ response to treatment. The immunotherapy was given every three weeks, starting with the second dose of chemotherapy, for up to 24 months.

Patients who used the device alongside chemotherapy and immunotherapy lived approximately 10 months longer than patients who had used the device with chemotherapy alone in the past. Moreover, those with large, inoperable tumors lived approximately 13 months longer and showed much stronger immune activation compared to patients who underwent surgical removal of their tumors.

“Further studies are needed to determine the optimal role of surgery in this setting, but these findings may offer hope, particularly for glioblastoma patients who do not have surgery as an option,” said Tran.

Moving the research forward

Keck Medicine is participating in the multicenter Phase 3 clinical trial to validate the efficacy of TTFields with immunotherapy and chemotherapy. Tran, who has been researching TTFields for more than a decade, serves as the chair of the steering committee for this trial. Frances Chow, MD, neuro-oncologist with USC Norris, is the principal investigator of the Keck Medicine study site.

This Phase 3 trial, currently open at 28 sites across the United States, Europe and Israel, aims to enroll over 740 patients through April 2029, including those with gross total resection, partial resection or biopsy-only tumors to assess the extent of how surgically removing tumors influences immune response.

Keck School of Medicine of USC authors of this study include Dongjiang Chen, PhD, assistant professor of research neurological surgery; Son Le, PhD, assistant professor of research neurological surgery; Harshit Manektalia, research programmer; Ming Li, PhD, professor of research population and public health sciences; and Adam O’Dell, research lab specialist. Ashley Ghiaseddin, MD, and Maryam Rahman, MD, MS, colleagues from the University of Florida, also contributed to this work.

This study was funded by a grant from Novocure, which manufactures Optune, the TTFields device used in this study. Tran has received honoraria from Novocure for consultant work. Chen and Tran are inventors of two patent applications related to work reported in this study

The ventral tegmental area (VTA) plays a key role in motivation and the brain’s reward circuit. The main source of dopamine, this small cluster of neurons sends this neuromodulator to other brain regions to trigger an action in response to a positive stimulus.

“Initially, the VTA was thought to be merely the brain’s reward centre. But in the 1990s, scientists discovered that it doesn’t encode reward itself, but rather the prediction of reward,” explains Alexandre Pouget, full professor in the Department of Basic Neurosciences in the UNIGE Faculty of Medicine.

Experiments on animals have shown that when a reward consistently follows a light signal, for example, the VTA eventually releases dopamine not at the moment of the reward, but as soon as the signal appears. This response therefore encodes the prediction of the reward — linked to the signal — rather than the reward itself.

A much more sophisticated function

This “reinforcement learning,” which requires minimal supervision, is central to human learning. It’s also the principle behind many artificial intelligence algorithms that improve performance through training — such as AlphaGo, the first algorithm to defeat a world champion in the game of Go.

In a recent study, Alexandre Pouget’s team, in collaboration with Naoshige Uchida of Harvard University and Paul Masset of McGill University, shows that the VTA’s coding is even more sophisticated than previously thought. “Rather than predicting a weighted sum of future rewards, the VTA predicts their temporal evolution. In other words, each gain is represented separately, with the precise moment at which it is expected,” explains the UNIGE researcher, who led this work.

“While we knew that VTA neurons prioritised rewards close in time over the ones further in the future- on the principle of a bird in the hand is worth two in the bush -we discovered that different neurons do so on different time scales, with some focus on the reward possible in a few seconds’ time, others on the reward expected in a minute’s time, and others on more distant horizons. This diversity is what allows the encoding of reward timing. This much finer representation gives the learning system great flexibility, allowing it to adapt to maximise immediate or delayed rewards, depending on the individual’s goals and priorities.”

AI and neuroscience: a two-way street

These findings stem from a fruitful dialogue between neuroscience and artificial intelligence. Alexandre Pouget developed a purely mathematical algorithm that incorporates the timing of reward processing. Meanwhile, the Harvard researchers gathered extensive neurophysiological data on VTA activity in animals experiencing rewards.

“They then applied our algorithm to their data and found that the results matched perfectly with their empirical findings.” While the brain inspires AI and machine learning techniques, these results demonstrate that algorithms can also serve as powerful tools to reveal our neurophysiological mechanisms.

Using advanced computational modelling, a research team led by the University of Oxford, working in partnership with the Instituto Superior Técnico in the University of Lisbon, has achieved the first-ever real-time, three-dimensional simulations of how intense laser beams alter the ‘quantum vacuum’ — a state once assumed to be empty, but which quantum physics predicts is full of virtual electron-positron pairs.

Excitingly, these simulations recreate a bizarre phenomenon predicted by quantum physics, known as vacuum four-wave mixing. This states that the combined electromagnetic field of three focused laser pulses can polarise the virtual electron-positron pairs of a vacuum, causing photons to bounce off each other like billiard balls – generating a fourth laser beam in a ‘light from darkness’ process. These events could act as a probe of new physics at extremely high intensities.

“This is not just an academic curiosity — it is a major step toward experimental confirmation of quantum effects that until now have been mostly theoretical,” said study co-author Professor Peter Norreys, Department of Physics, University of Oxford.

The work arrives just in time as a new generation of ultra-powerful lasers starts to come online. Facilities such as the UK’s Vulcan 20-20, the European ‘Extreme Light Infrastructure (ELI)’ project, and China’s Station for Extreme Light (SEL) and SHINE facilities are set to deliver power levels high enough to potentially confirm photon-photon scattering in the lab for the first time. Photon-photon scattering has already been selected as one of three flag-ship experiments at the University of Rochester’s OPAL dual-beam 25 PW laser facility in the United States.

The simulations were carried out using an advanced version of OSIRIS, a simulation software package which models interactions between laser beams and matter or plasma.

Lead author Zixin (Lily) Zhang, a doctoral student at Oxford’s Department of Physics, said: “Our computer program gives us a time-resolved, 3D window into quantum vacuum interactions that were previously out of reach. By applying our model to a three-beam scattering experiment, we were able to capture the full range of quantum signatures, along with detailed insights into the interaction region and key time scales. Having thoroughly benchmarked the simulation, we can now turn our attention to more complex and exploratory scenarios — including exotic laser beam structures and flying-focus pulses.”

Crucially, these models provide details that experimentalists depend on to design precise, real-world tests including realistic laser shapes and pulse timings. The simulations also reveal new insights, including how these interactions evolve in real time and how subtle asymmetries in beam geometry can shift the outcome.

According to the team, the tool will not only assist in planning future high-energy laser experiments but could also help search for signs of hypothetical particles such as axions and millicharged particles — potential candidates for dark matter.

Study co-author Professor Luis Silva (at the Instituto Superior Tecnico, University of Lisbon and Visiting Professor in Physics at the University of Oxford) added: “A wide range of planned experiments at the most advanced laser facilities will be greatly assisted by our new computational method implemented in OSIRIS. The combination of ultra-intense lasers, state-of-the-art detection, cutting-edge analytical and numerical modelling are the foundations for a new era in laser-matter interactions, which will open new horizons for fundamental physics.”