The review, published in Journal of Neuro-Oncology, evaluated research that applied AI to Gamma Knife clinical, imaging or treatment-planning data. The authors searched PubMed/MEDLINE, Embase and Scopus through September 20, 2026. Studies outside the field of Gamma Knife radiosurgery and those not using learning-based methods were excluded, while eligible studies were synthesized according to major stages of the radiosurgery workflow. As a narrative review, the analysis maps the applications of AI rather than testing one model or intervention in a clinical trial.

Identified applications include tumor segmentation, isocenter selection, prescription and dose-distribution prediction, synthetic computed tomography generation, and assessment of treatment-plan quality. These tools address different parts of the technical planning process, from identifying anatomy to supporting decisions about where to focus treatment and how a proposed radiation dose is distributed. Several models have reported promising performance, but the review does not establish that routine use of these methods would improve patient outcomes. The evidence for each application also remains tied to the specific data, task and clinical setting in which its model was evaluated.

Post-treatment applications include longitudinal tumor monitoring and prediction of response, functional outcomes and toxicity. The reviewed toxicity models address outcomes such as peritumoral edema and radiation necrosis. Some studies have produced encouraging results within their respective datasets, but those findings do not demonstrate clinical benefit across Gamma Knife centers or among individual patients. Predictive performance alone therefore does not show that an AI tool can meaningfully improve treatment decisions, and the review emphasizes the need to demonstrate clinical benefit separately from technical performance.

Across the literature, the central limitation is the gap between promising model results and dependable clinical use. Many studies rely on small or single-center datasets, while external and prospective validation has been limited. This restricts the strength of the conclusions that can be drawn for broader clinical adoption. The review calls for multicenter validation, prospective evaluation, integration into clinical workflows, and evidence of meaningful clinical benefit before AI becomes routine in Gamma Knife radiosurgery. Until that evidence is available, the authors characterize AI as a decision-support tool that can support radiosurgical expertise rather than replace it. The current evidence therefore supports further evaluation of AI across specific Gamma Knife tasks, but not autonomous use or claims of improved safety, effectiveness or consistency in clinical practice.

Subject of Research: Artificial intelligence applications in Gamma Knife radiosurgery

Article Title: Artificial intelligence in gamma knife radiosurgery: applications in treatment planning, response prediction, and toxicity assessment

Article References: Zidan, A., El-Sherbini, A., Burns, L., & Soliman, H. (2026). Artificial intelligence in gamma knife radiosurgery: applications in treatment planning, response prediction, and toxicity assessment. Journal of Neuro-Oncology, 180(2), Article 27. https://doi.org/10.1007/s11060-026-05834-7

Image Credits: AI Generated

DOI: 10.1007/s11060-026-05834-7

Keywords: artificial intelligence, Gamma Knife radiosurgery, treatment planning, tumor segmentation, outcome prediction, toxicity assessment, radiation necrosis, medical imaging, clinical validation, decision support, Artificial, intelligence

The material, dubbed NOC-900, was synthesized through a deceptively simple two-step process of hydrothermal treatment followed by high-temperature calcination. What makes it special is not the recipe but the architecture it inherits. Covalent organic frameworks, or COFs, are crystalline lattices built entirely from light elements, stitched together by strong covalent bonds into porous, ordered structures. When such a framework is carbonized, much of that order collapses, but a chemical memory persists: nitrogen atoms remain embedded within the graphite-like carbon network in well-defined bonding configurations. In NOC-900, the dominant configuration is what the researchers call graphite-N-C₃, a nitrogen atom bonded to three carbon atoms within the graphitic lattice, sitting at the edge of the carbon planes like a single impurity atom in an otherwise perfect crystal.

That tiny structural detail turns out to be the whole story. When NOC-900 was added to water containing levofloxacin along with peroxymonosulfate, or PMS, a common oxidizing salt used in advanced oxidation processes, the antibiotic all but disappeared. Within sixty minutes, 97.6 percent of the levofloxacin had been removed. Even more impressive, the catalyst kept working: after five consecutive use-and-regeneration cycles, it still destroyed more than 80 percent of the pollutant, a level of durability that many metal-based catalysts struggle to match.

The system also shrugged off conditions that would cripple lesser catalysts. Real wastewater is a chemical minefield, full of dissolved salts, varying acidity, and competing organic matter. Yet the NOC-900/PMS pair maintained outstanding degradation performance across a pH range stretching from 3.16 to 10.50, and it continued to function in complex water matrices laced with ionic interference. For engineers dreaming of industrial deployment, that robustness matters as much as raw speed, because a catalyst that only works in ultrapure laboratory water is a catalyst that will never clean a real river.

But the central question the study set out to answer was mechanistic: which part of this complicated carbon material actually does the chemistry? Carbon catalysts are notoriously messy, a patchwork of defects, edges, oxygen groups, and nitrogen dopants, and pinpointing the true active site has long frustrated the field. Through a battery of characterization techniques, including X-ray photoelectron spectroscopy to map nitrogen species, electron paramagnetic resonance to spy on reactive intermediates, and quenching experiments with selective scavengers such as furfuryl alcohol, tert-butanol, and p-benzoquinone, the researchers converged on a clear verdict. The graphite-N-C₃ sites are intimately responsible for the system’s signature move: the highly selective production of singlet oxygen.

Singlet oxygen is an unusual weapon in the oxidation arsenal. Unlike hydroxyl radicals or sulfate radicals, which are brute-force, short-lived, and indiscriminate, singlet oxygen is a non-radical, electrophilic species that attacks electron-rich organic molecules with surgical selectivity. That selectivity explains why the NOC-900/PMS system performs so well in real water: radicals would be squandered instantly on chloride ions, bicarbonate, and natural organic matter, while singlet oxygen largely ignores these distractions and goes after the antibiotic. The non-radical pathway also means the catalyst does not depend on metal centers cycling through oxidation states, which is why no cobalt, iron, or manganese leaching complicates the picture. It is catalysis by geometry and electronics alone.

The team did not stop at destruction. Using high-performance liquid chromatography coupled with mass spectrometry, they tracked the intermediate molecules produced as levofloxacin broke apart, mapped the bonds that were cleaved first, and proposed plausible degradation pathways. Critically, they also assessed toxicity along the way, and the news was reassuring: most of the intermediates formed during degradation were more environmentally benign than the parent antibiotic. In other words, the process does not merely convert one invisible pollutant into a nastier one, a pitfall that has undermined other advanced oxidation schemes, but genuinely defuses the molecule’s biological threat as it dismantles it.

The choice of a COF precursor is what gives this approach its conceptual punch. Because COFs are built from molecular building blocks, chemists can, in principle, design the nitrogen environment of the resulting carbon before it ever exists, choosing monomers that place pyridinic, pyrrolic, or graphitic nitrogen exactly where they want it. NOC-900 demonstrates that this design philosophy works for environmental catalysis: the graphite-N-C₃ motif, inherited from the framework’s atomic precision, survives carbonization and becomes the engine of PMS activation. Previous work has shown COF-derived carbons carrying cobalt particles or other metal complexes activating PMS for levofloxacin degradation; this study proves the metal can be left out entirely.

The broader implications ripple outward in several directions. For water treatment, a durable, wide-pH, salt-tolerant, metal-free catalyst addresses many of the practical objections to peroxymonosulfate-based advanced oxidation, from secondary metal contamination to sensitivity to water chemistry. For catalysis science, the study adds a precise entry to the still-incomplete catalog of which nitrogen configurations in carbon do what, sharpening the field’s ability to move from empirical materials screening to rational design. And for the growing literature on non-radical oxidation, it supplies another well-documented case in which singlet oxygen, generated selectively at a defined site, outperforms the radical free-for-all that dominated the field for decades.

There remain, of course, the usual distances between a laboratory beaker and a municipal treatment tank: catalyst synthesis at scale, PMS dosing economics, and long-term performance under continuous flow all await demonstration. But the foundations laid here are solid. By showing that a single nitrogen bonding motif in a carbon lattice can choreograph the selective birth of singlet oxygen and the near-total destruction of a fluoroquinolone antibiotic, Huang and Zhou have turned an abstract materials-chemistry question into a concrete blueprint. The next generation of pollution-fighting carbons may well be designed atom by atom before a single gram of catalyst is ever made.

Subject of Research: Metal-free COF-derived carbon catalysts with graphite-N-C₃ sites activating peroxymonosulfate to degrade levofloxacin via singlet oxygen

Article Title: Mechanistic Insights into Antibiotic Degradation by Covalent Organic Framework-Derived Carbon: Role of Graphite-N-C3 Active Sites

Article References: Huang, Z., & Zhou, L. (2026). Mechanistic Insights into Antibiotic Degradation by Covalent Organic Framework-Derived Carbon: Role of Graphite-N-C3 Active Sites. Catalysis Letters, 156(11), Article 298. https://doi.org/10.1007/s10562-026-05543-w

Image Credits: AI Generated

DOI: 10.1007/s10562-026-05543-w

Keywords: covalent organic frameworks, peroxymonosulfate, levofloxacin, singlet oxygen, graphitic nitrogen, water treatment, advanced oxidation processes, non-radical oxidation, carbon catalysts, antibiotic pollution, degradation intermediates, toxicity assessment

Graphitic carbon nitride, known chemically as g-C3N4, is a polymeric semiconductor composed of carbon and nitrogen arranged in layered sheets reminiscent of graphite. It has attracted intense scientific interest because it is chemically stable, non-toxic, inexpensive, and remarkably easy to synthesize from common nitrogen-rich precursors. Crucially, it absorbs visible light, meaning it can in principle be driven by ordinary sunlight rather than expensive ultraviolet lamps. When photons strike the material, they excite electrons from the valence band to the conduction band, leaving behind positively charged holes. These photogenerated charge carriers can then react with water, oxygen, and dissolved species to produce highly reactive oxidizing agents capable of shredding organic pollutant molecules into harmless fragments.

Yet pristine g-C3N4 suffers from well-documented weaknesses that have kept it out of real-world deployment. Photogenerated electrons and holes recombine rapidly, releasing energy as heat before they can do useful chemical work. The material’s surface is comparatively inert, limiting its ability to adsorb and react with target pollutants, and its visible-light absorption, while real, does not extend deeply enough into the solar spectrum. The Hanoi review systematically examines how researchers have overcome these limitations by constructing hybrid photocatalysts, or CN-HPs, in which g-C3N4 is coupled with other materials to form sophisticated junctions that separate charges, extend light harvesting, and boost surface reactivity.

The strategies catalogued in the review are strikingly diverse. Heterojunctions pair g-C3N4 with metal oxides such as ZnO, TiO2, WO3, and BiVO4, or with more exotic partners including MXenes, layered double hydroxides, perovskites, and metal-organic frameworks. Z-scheme and S-scheme architectures are particularly elegant: they mimic natural photosynthesis by selectively retaining the most energetic electrons and holes on different components while allowing the useless carriers to recombine, thereby preserving strong oxidation and reduction power simultaneously. Doping with elements such as sulfur or phosphorus tunes the electronic structure, while carbon quantum dots and noble metal nanoparticles act as electron sinks and co-catalysts. Magnetic components such as Fe3O4 even allow the catalyst particles to be retrieved from treated water with a simple magnet, addressing one of the classic headaches of nanoparticle-based treatment.

The performance figures reported across the literature are impressive, at least under laboratory conditions. CN-HPs have achieved high removal efficiencies for a wide range of pharmaceutical pollutants, including tetracycline, ciprofloxacin, levofloxacin, oxytetracycline, amoxicillin, sulfamethoxazole, ibuprofen, naproxen, acetaminophen, and the anticancer drug 5-fluorouracil. Many systems operate under visible light or even natural sunlight, and some have been tested in continuous-flow configurations and real hospital or mariculture wastewater matrices. The review emphasizes that these materials also retain their activity over repeated catalytic cycles, a critical requirement for any technology hoping to move from the bench to a treatment plant.

Beneath the headline efficiency numbers lies a more nuanced chemical story. The review details how degradation proceeds through the concerted action of three principal reactive species: superoxide radicals, hydroxyl radicals, and photogenerated holes. Each attacks drug molecules at characteristic bonds, cleaving rings and side chains to produce a cascade of smaller intermediate compounds. Ideally, these intermediates are then progressively mineralized into carbon dioxide, water, and inorganic ions. However, the authors highlight an important caveat that recurs throughout the literature: total organic carbon reduction and complete mineralization typically require substantially more time than the initial disappearance of the parent pollutant. In other words, a water sample may test clean for the original drug while still carrying a cocktail of partially oxidized fragments.

That gap between degradation and detoxification is where the review delivers its most consequential warning. Toxicity assessments show that the by-products formed during photocatalytic degradation can carry toxicity profiles different from, and in some cases potentially greater than, those of the original compounds. High removal efficiency alone, the authors argue, does not demonstrate environmental safety. A treatment system that rapidly converts an antibiotic into unidentified fragments without verifying their ecological impact may simply be trading one hazard for another. The review therefore calls for toxicity evaluation to become a standard, non-negotiable component of photocatalysis research, rather than an optional add-on performed in only a minority of studies.

The authors are equally candid about the obstacles standing between laboratory success and field deployment. Most published experiments use purified water, single pollutants at concentrations far above environmental levels, and idealized light sources. Real wastewater presents a hostile environment: competing organic matter scavenges radicals, suspended solids scatter light, mixtures of drugs interact unpredictably, and pH fluctuates continuously. Long-term environmental safety of the nanomaterials themselves, including potential release of catalyst components into treated water, remains insufficiently characterized. Energy efficiency and the engineering challenge of scaling thin-film or slurry reactors to the volumes handled by municipal plants are also unresolved. The review frames these not as reasons for pessimism but as a well-defined research agenda.

One of the most forward-looking threads in the review concerns artificial intelligence. The authors highlight the potential of combining experimental photocatalysis data with machine learning models to optimize treatment conditions and predict how CN-HP systems will perform against specific target pollutants in the field. Given the enormous design space of possible hybrid materials, dopants, junction types, and operating parameters, data-driven approaches could dramatically accelerate the search for formulations that balance efficiency, stability, cost, and safety. Similar AI-assisted strategies are already gaining traction across membrane design and pollution monitoring, and photocatalysis appears poised to follow the same trajectory.

What emerges from the Hanoi analysis is a technology at an inflection point. The fundamental chemistry works: metal-free, sunlight-driven catalysts can genuinely dismantle the pharmaceutical residues that conventional treatment leaves behind, and they can do so repeatedly and, in many configurations, using abundant and benign raw materials. The remaining task is to prove that this chemistry survives contact with the messy, variable, and economically constrained reality of full-scale water treatment, and that the end products of degradation are demonstrably safe for the ecosystems that receive them. If researchers can close the gap between breaking molecules and proving detoxification, graphitic carbon nitride hybrids may become a cornerstone of the next generation of water purification infrastructure.

Subject of Research: g-C3N4-based hybrid photocatalysts for photocatalytic degradation of emerging pharmaceutical pollutants in water and wastewater

Article Title: g-C3N4-based hybrid photocatalysts for removal of emerging pharmaceutical pollutants from water: recent advances, degradation pathways, toxicity assessment,and future perspectives

Article References: Hanh, D. T. M., & Hoai, P. T. T. (2026). g-C3N4-based hybrid photocatalysts for removal of emerging pharmaceutical pollutants from water: recent advances, degradation pathways, toxicity assessment,and future perspectives. Environmental Geochemistry and Health, 48(16), Article 625. https://doi.org/10.1007/s10653-026-03530-z

Image Credits: AI Generated

DOI: 10.1007/s10653-026-03530-z

Keywords: graphitic carbon nitride, photocatalysis, pharmaceutical pollutants, water treatment, heterojunctions, advanced oxidation processes, degradation pathways, toxicity assessment, antibiotics, mineralization, artificial intelligence, wastewater remediation