Cluster Complexes Research Articles

Complex Thrombo-Inflammatory Responses versus Outcomes of Non-COVID-19 Community-Acquired Pneumonia and COVID-19

Introduction: The thrombo-inflammatory response and outcomes of community-acquired pneumonia (CAP) due to various organisms (non-COVID-19 CAP) versus CAP due to a single virus, SARS-CoV-2 (i.e., COVID-19) may differ. Methods: Adults hospitalized with non-COVID-19 CAP (December 1, 2021–June 15, 2023) or COVID-19 (March 2, 2020–June 15, 2023) in Canada. We compared non-COVID-19 CAP and COVID-19 baseline, thrombo-inflammatory response, and mortality. We measured plasma cytokine and coagulation factor levels in a sample of patients, did hierarchical clustering, and compared cytokine and coagulation factor levels. Results: In 2,485 patients (non-COVID-19 CAP, n = 719; COVID-19 patients, n = 2,157), non-COVID-19 CAP patients had significantly lower 28-day mortality (CAP vs. COVID-19 waves 1 and 2; 10% vs. 18% and 16%, respectively), intensive care unit admission (CAP vs. all waves; 15% vs. 39%, 37%, 33%, and 24%, respectively), invasive ventilation (CAP vs. waves 1, 2, and 3 patients; 11% vs. 25%, 20%, and 16%), vasopressor use (CAP 12% vs. 23%, 21%, and 18%), and renal replacement therapy use (CAP 3% vs. Omicron 7%). Complexity of hierarchical clustering aligned directly with mortality: COVID-19 wave 1 and 2 patients had six clusters at admission and higher mortality than non-COVID-19 CAP and Omicron that had three clusters at admission. Pooling all COVID-19 waves increased complexity with seven clusters on admission. Conclusion: Complex thrombo-inflammatory responses aligned with mortality of CAP. At a fundamental level, the human thrombo-inflammatory response to a brand new virus was “confused” whereas humans had eons of time to develop a more concise efficient thrombo-inflammatory host response to CAP.

An automated toolbox for microcalcification cluster modeling for mammographic imaging.

Mammographic imaging is essential for breast cancer detection and diagnosis. In addition to masses, calcifications are of concern and the early detection of breast cancer also heavily relies on the correct interpretation of suspicious microcalcification clusters. Even with advances in imaging and the introduction of novel techniques such as digital breast tomosynthesis and contrast-enhanced mammography, a correct interpretation can still be challenging given the subtle nature and large variety of calcifications. Computer simulated lesion models can serve to develop, optimize, or improve imaging techniques. In addition to their use in comparative (virtual clinical trial) detection experiments, these models have potential application in training deep learning models and in the understanding and interpretation of breast lesions. Existing simulation methods, however, often lack the capacity to model the diversity occurring in breast lesions or to generate models relevant for a specific case. This study focuses on clusters of microcalcifications and introduces an automated, flexible toolbox designed to generate microcalcification cluster models customized to specific tasks. The toolbox allows users to control a large number of simulation parameters related to model characteristics such as lesion size, calcification shape, or number of microcalcifications per cluster. This leads to the capability of creating models that range from regular to complex clusters. Based on the input parameters, which are either tuned manually or pre-set for a specific clinical type, different sets of models can be simulated depending on the use case. Two lesion generation methods are described. The first method generates three-dimensional microcalcification clusters models based on geometrical shapes and transformations. The second method creates two-dimensional (2D) microcalcification cluster models for a specific 2D mammographic image. This novel method employs radiomics analysis to account for local textures, ensuring the simulated microcalcification cluster is appropriately integrated within the existing breast tissue. The toolbox is implemented in the Python language and can be conveniently run through a Jupyter Notebook interface, openly accessible at https://gitlab.kuleuven.be/medphysqa/deploy/breast-calcifications. Validation studies performed by radiologists assessed the level of malignancy and realism of clusters tuned with specific parameters and inserted in mammographic images. The flexibility of the toolbox with multiple simulation methods is illustrated, as well as the compatibility with different simulation frameworks and image types. The automation allows for the straightforward and fast generation of diverse microcalcification cluster models. The generated models are most likely applicable for various tasks as they can be configured in a variety of ways and inserted in different types of mammographic images of multiple acquisition systems. Validation studies confirmed the capacity to simulate realistic clusters and capture clinical properties when tuned with appropriate parameter settings. This simulation toolbox offers a flexible means of simulating microcalcification cluster models with potential use in both technical and clinical research in mammography imaging. The 3D generation methods allow for specifying many characteristics regarding the calcification shape and cluster architecture, and the 2D generation method presents a novel manner to create microcalcification clusters tailored to existing breast textures.

Target-Induced On-Protein Clustering of Metal Peptide Enables Low Overpotential Water Splitting for Early Detection of Non-Small-Cell Lung Cancer.

This study presents a novel method for the early detection of non-small-cell lung cancer (NSCLC) by employing target-induced on-protein clustering of metal-peptide complexes to facilitate low overpotential water splitting. The approach utilizes a designed peptide molecular probe composed of an EGFR-targeting motif and a copper-chelating tetrapeptide. Upon interaction with the epidermal growth factor receptor (EGFR) and divalent copper ions, the peptide probe forms a stable complex that undergoes on-protein clustering. This clustering significantly amplifies the electrochemical signal through enhanced dityrosine cross-linking and subsequent water splitting, achieving low overpotential for detection. The method was validated using clinical tissue samples and demonstrated improved sensitivity and specificity compared with traditional detection methods. This technique holds promise for earlier and more accurate diagnosis of NSCLC, leveraging the unique properties of metal-peptide interactions and electrochemical signal amplification.

The physical properties of cluster chains

We explore the kinematics and star formation history of the Scorpius Centaurus (Sco-Cen) OB association following the initial identification of sequential, linearly aligned chains of clusters. Building upon our characterization of the Corona Australis (CrA) chain, we now analyze two additional major cluster chains that exhibit similar characteristics: the Lower Centaurus Crux (LCC) and Upper Scorpius (Upper Sco) chains. All three cluster chains display distinct sequential patterns in 1) the 3D spatial distribution, 2) age, 3) velocity, and 4) mass. The Upper-Sco chain is the most massive and complex cluster chain, possibly consisting of two or more overlapping subchains. We discuss the possible formation of cluster chains and argue for a scenario where feedback from the most massive star formation episode 15 Myr ago initiated the formation of these spatio-temporal cluster sequences. Our results identify cluster chains as a distinct type of stellar structure with well-defined physical properties, formed in environments capable of sustaining stellar feedback over timescales of 5--10 Myr. We find that around 40<!PCT!> of the stellar population in Sco-Cen formed due to triggered star formation, with 35<!PCT!> forming along the three cluster chains. We conclude that cluster chains could be common structures in OB associations, particularly in regions that have similar natal environments as Sco-Cen. Beyond their significance for star formation and stellar feedback, they appear to be promising laboratories for chemical enrichment and the transport of elements from one generation to the next in the same star-forming region.

Affecting Charges and Structures of {Bi6} Architectures by 12‐Electron Transition Metal Fragments

AbstractMolecules based on polyatomic bismuth substructures are currently attracting a lot of attention owing to this heavy and essentially non‐toxic element's uncommon chemical and physical properties, which include unprecedented bonding properties. Hexaatomic {Bi6} substructures that underly more complex cluster structures were recently reported to adopt different structures or exhibit different structural details as a consequence of the charge of the {Bi6} unit. This leads to either crown‐shaped cycles for a nominal Bi66− or differently distorted trigonal prisms for compositions close to Bi62−. It was predicted by quantum chemistry that Bi64− should adopt a distinctly distorted boat‐like shape, yet a corresponding compound has remained elusive. Here, we report a proof of this assumption by the synthesis of [K(crypt‐222)]2[Bi6{Zn(hmds)}2] ⋅ 1.5THF (1), comprising a bimetallic [Bi6{Zn(hmds)}2]2− cluster that fulfills the prediction for the geometric and electronic structure of the missing link (crypt‐222=4,7,13,16,21,24‐hexaoxa‐1,10‐diazabicyclo‐[8.8.8]hexa‐cosane, hmds=hexamethyldisilazanid). A detailed quantum chemical study shows how the nature of Lewis‐acidic transition metal complexes—in particular, 12‐electron fragments—control and fine‐tune the resulting {Bi6} architectures in accordance with the degree of electron‐withdrawal from the polybismuthide core.

Affecting Charges and Structures of {Bi6} Architectures by 12-Electron Transition Metal Fragments.

Molecules based on polyatomic bismuth substructures are currently attracting a lot of attention owing to this heavy and essentially non-toxic element's uncommon chemical and physical properties, which include unprecedented bonding properties. Hexaatomic {Bi6} substructures that underly more complex cluster structures were recently reported to adopt different structures or exhibit different structural details as a consequence of the charge of the {Bi6} unit. This leads to either crown-shaped cycles for a nominal Bi6 6- or differently distorted trigonal prisms for compositions close to Bi6 2-. It was predicted by quantum chemistry that Bi6 4- should adopt a distinctly distorted boat-like shape, yet a corresponding compound has remained elusive. Here, we report a proof of this assumption by the synthesis of [K(crypt-222)]2[Bi6{Zn(hmds)}2] ⋅ 1.5THF (1), comprising a bimetallic [Bi6{Zn(hmds)}2]2- cluster that fulfills the prediction for the geometric and electronic structure of the missing link (crypt-222=4,7,13,16,21,24-hexaoxa-1,10-diazabicyclo-[8.8.8]hexa-cosane, hmds=hexamethyldisilazanid). A detailed quantum chemical study shows how the nature of Lewis-acidic transition metal complexes-in particular, 12-electron fragments-control and fine-tune the resulting {Bi6} architectures in accordance with the degree of electron-withdrawal from the polybismuthide core.

Prevalence and Association of Components of Metabolic Syndrome and Uric Acid among Commercial Drivers in South-West Nigeria.

Metabolic syndrome (MetS) is a complex cluster of metabolic abnormalities characterized by central obesity, dyslipidemia, hypertension, and impaired glucose metabolism. Emerging evidence suggests a potential link between uric acid levels and MetS, and commercial drivers are exposed to unique occupational hazards that may predispose them to MetS and hyperuricemia. The objective of this study was to determine the prevalence of MetS and its relationship with serum uric acid among commercial drivers in Ado-Ekiti, Nigeria. A cross-sectional study was conducted among commercial drivers in Ado-Ekiti. Relevant information was obtained with a questionnaire, and anthropometry and blood pressure were measured. Fasting plasma glucose and lipid profiles were determined by the standard protocol. MetS was determined with the harmonized criteria. Bivariate correlation and Chi-square were used to determine the relationship between serum uric acid and MetS and its components. There were 106 participants with a median age (interquartile range) of 50 (11) years, with no difference between those with or without MetS. More than 70% of the participants drank alcohol and 75 (70.8%) participants had hyperuricemia. There was no significant correlation between serum uric acid and components of MetS. The prevalence of MetS among all the participants was 21.7% (23/106), with no difference among men with normal uric acid (25.8%) and those with elevated uric acid (20.0%), P = 0.509. Similarly, there was no statistical difference in the prevalence of the components of MetS between the two groups. The prevalence of MetS among the commercial drivers was high, with no difference among men with or without hyperuricemia. Given the importance of this group of people, a system-level public health approach should be adopted to promote a healthy lifestyle to save the lives of the populace.

Unveiling the Structural Complexity of Lithium Organozinc Alkoxo Clusters and their Applications to Enantioselective Michael Addition Reactions

AbstractWe report three novel lithium zincate alkoxo clusters, which can be accessed through a convenient co‐complexation reaction of the corresponding dialkylzinc derivatives with lithium alkoxides of the formula [LiO(CH2)2N(CH3)2], or via a deprotonation process mediated by the higher‐order zincate Li2ZnEt4 and dimethylethanolamine. These complexes have been isolated as colourless crystalline solids and characterised by multinuclear magnetic resonance spectroscopy, elemental and single‐crystal X‐ray diffraction analysis. XRD analysis of the crystal structures, combined with 1H DOSY NMR experiments, was crucial for understanding the chemistry behind these complexes. Furthermore, complexes obtained by mixing ZnEt2 with a chiral nonracemic lithium alkoxide generated from (1R,2S)‐N‐methylephedrine have been explored in promoting an enantioselective Michael addition reaction towards trans‐β‐nitrostyrene, with the corresponding nitroalkane isolated in up to 37.3 % enantiomeric excess.

Machine learning-based clustering analysis of the banking green credit for the renewable energy industry

Credit policies for clean and renewable energy businesses play a crucial role in supporting carbon neutrality efforts to combat climate change. Clustering the credit capacity of these companies to prioritize lending is essential given the limited capital available. Support Vector Machine (SVM) and Artificial Neural Network (ANN) are two robust machine learning algorithms for addressing complex clustering problems. Additionally, hyperparameter selection within these models is effectively enhanced through the support of a robust heuristic optimization algorithm, Particle Swarm Optimization (PSO). To leverage the strength of these advanced machine learning techniques, this paper aims to develop SVM and ANN models, optimized with the PSO, for the clustering problem of green credit capacity in the renewable energy industry. The results show low Mean Square Error (MSE) values for both models, indicating high clustering accuracy. The credit capabilities of wind energy, clean fuel, and biomass pellet companies are illustrated in quadrant charts, providing stakeholders with a clear view to adjust their credit strategies. This helps ensure the efficient operation of banking green credit policies.

Extending Complexity to Word-Final Position via Telepractice: Intervention Effects for English-Speaking Children With Speech Sound Disorder.

Phonologically complex targets (e.g., [pl-]) are understood to facilitate widespread gains following speech sound intervention, and yet, available research largely features word-initial clusters. The present study investigates intervention effects following treatment of complex clusters presented in word-final position. Importantly, this allows for an added layer of complexity via suffixes that mark tense and agreement. Eight English-speaking children with speech sound disorder (SSD; 3;3-6;9 [years;months]) participated in 18 one-on-one intervention sessions. Intervention was completed via telepractice, as were all pre- and post-intervention assessments. Intervention targets were word-final two-element consonant clusters that were unknown to the child prior to intervention. Targets were presented in verbs that were either monomorphemic (i.e., [-ks]; they mix) or bimorphemic (i.e., [-ks]; she pick/3s, marked for third-person singular). All participants demonstrated change across multiple phonological measures. More stringently, six of eight participants demonstrated generalization to untreated sounds and untreated words immediately following intervention, including four of four children with monomorphemic targets. Importantly, positive changes for children with both target types were observed following a relatively short course of intervention (18 sessions over 6 weeks), and mastery of the target cluster was not required for phonological growth to occur. Results align with available work featuring word-initial complex targets and indicate that word-final consonant clusters are feasible, effective targets for English-speaking children with SSD. Findings similarly affirm the use of telepractice to deliver research-based interventions. Speech-language pathologists may thus integrate these findings with their clinical judgment and client perspectives to implement such targets in clinical practice.

Twins in diversity: understanding circumstellar disc evolution in the twin clusters of W5 complex

ABSTRACT Young star-forming regions in massive environments are ideal test beds to study the influence of surroundings on the evolution of discs around low-mass stars. We explore two distant young clusters, IC 1848-East and West located in the massive W5 complex. These clusters are unique due to their similar (distance, age and extinction) yet distinct (stellar density and far-ultraviolet radiation fields) physical properties. We use deep multiband photometry in optical, near-infrared and mid-infrared wavelengths complete down to the substellar limit in at least five bands. We trace the spectral energy distribution of the sources to identify the young pre-main sequence members in the region and derive their physical parameters. The disc fraction for the East and West clusters down to 0.1 M$_\odot$ was found to be $\sim 27\,\pm$ 2 per cent (N$_\mathrm{disc}$ = 184, N$_\mathrm{discless}$ = 492) and $\sim 17\,\pm$ 1 per cent (N$_\mathrm{disc}$ = 173, N$_\mathrm{discless}$ = 814), respectively. While no spatial variation in the disc fraction is observed, these values are lower than those in other nearby young clusters. Investigating the cause of this decrease, we find a correlation with the intense feedback from massive stars throughout the cluster area. We also identified the disc sources undergoing accretion and observed the mass accretion rates to exhibit a positive linear relationship with the stellar host mass and an inverse relationship with stellar age. Our findings suggest that the environment significantly influences the dissipation of discs in both clusters. These distant clusters, characterized by their unique attributes, can serve as templates for future studies in outer galaxy regions, offering insights into the influence of feedback mechanisms on star and planetary formation.

Facile one-pot synthesis of photoresponsive Cu1.8S and CuInS2 nanostructures aided by Cu-pyrimidylthiolate molecular precursor

Copper-based binary and ternary sulfides have attracted significant attention due to their excellent photo-physical properties, making them highly promising for high-performance energy harvesting and storage devices. This study focuses on the synthesis and structural characterization of an air-stable hexanuclear Cu-pyrimidylthiolate cluster complex which serves as an efficient single-source precursor for the preparation of Cu1.8S nanocrystals. Furthermore, coupling the molecular precursor with suitable indium source resulted in a facile one-pot pathway for the preparation of technologically important, copper-based ternary CuInS₂, nanocrystals. The crystal structure, phase purity, and compositions of the nanostructures were confirmed using PXRD, XPS, EDS, and area elemental mapping. Electron microscopic studies revealed the formation of polygonal and hexagonal morphology with varied size in Cu1.8S and CuInS₂ nanocrystals respectively. UV-Vis diffuse reflectance spectroscopy showed a slight blue shift in the band gap of the nanostructures compared to their bulk counterparts which can be attributed to quantum confinement or surface lattice distortion effects. The band gap of the pristine nanocrystals along with high photocurrent and stable photo-switching characteristics suggest that they can serve as suitable electrode material for optoelectronic and photodetector devices.

Water-soluble neutral octahedral chalcogenide tungsten and molybdenum {M6Q8} clusters with P(C2H4CONH2)3 ligand

Developing the chemistry of octahedral chalcogenide molybdenum and tungsten cluster complexes in the context of applications in biology and medicine, in this work a series of water-soluble neutral cluster complexes [{M6Q8}(P(C2H4CONH2)3)6] (M = Mo, W; Q = S, Se) have been obtained by simultaneous replacement of inner and terminal halide ligands in [{M6I8}I6]2− with chalcogenide and organic phosphine ligands and characterized by single-crystal X-ray diffraction analysis, 1H and 31P NMR spectroscopies, elemental analysis, and UV–vis spectroscopy. The amide groups of the organic ligands, on the one hand, contribute to the solubility of the resulting clusters in water and, on the other hand, are able to form an extensive network of hydrogen bonds, leading to the crystallization of the complexes from aqueous solutions. Despite this fact, the complexes have sufficient solubility and stability in aqueous solutions, which made it possible to demonstrate their low cytotoxicity on Hep-2 cells (IC50 were not reached even at concentration up to 4 mM). The resulting clusters are among the most biocompatible of the octahedral clusters studied to date and are the starting point for the development of a new family of X-ray contrast agents.

STAD: Ship trajectory anomaly detection in ocean with dynamic pattern clustering

With the continuous increase of maritime traffic, developing an efficient and accurate model for ship trajectory anomaly detection has become crucial for ensuring maritime transportation safety. The high complexity and variability of the marine environment lead to diverse ship trajectory patterns, making it challenging to learn effective trajectory representations for accurately identifying anomalies. We thus proposed an unsupervised deep learning model called STAD for ship trajectory anomaly detection in ocean to address this challenge. Concretely, STAD leverages offset reconstruction-based representation learning and a deep Gaussian Mixture Model (GMM) estimation network to learn the underlying complex clustering patterns of ship trajectories and utilize the learned patterns to enhance trajectory anomaly detection. Extensive experiments on multiple AIS datasets indicate that our model significantly outperforms existing methods in detecting multiple representative types of ship trajectory anomalies, including shift deviation, abnormal heading, and abnormal speeding. This study could help closely monitor the status of ship movement and detect abnormal behaviors in advance, thus benefiting maritime safety.

A cluster-nanozyme-coenzyme system mimicking natural photosynthesis for CO2 reduction under intermittent light irradiation

Natural photosynthesis utilizes solar energy to convert water and atmospheric CO2 into carbohydrates through all-weather light/dark reactions based on molecule-based enzymes and coenzymes, inspiring extensive development of artificial photosynthesis. However, development of efficient artificial photosynthetic systems free of noble metals, as well as rational integration of functional units into a single system at the molecular level, remain challenging. Here we report an artificial system, the assembly system of Cu6 cluster and cobalt terpyridine complex, that mimics natural photosynthesis through precise integration of nanozyme complexes and ubiquinone (coenzyme Q) on Cu6 clusters. This biomimetic system efficiently reduces CO2 to CO in light reaction, achieving a production rate of 740.7 μmol·g−1·h−1 with high durability for at least 188 hours. Notably, our system realizes the decoupling of light and dark reactions, utilizing the phenol-evolutive coenzyme Q acting as an electron reservoir. By regulating the stabilizer of coenzyme Q, the dark reaction time can be extended up to 8.5 hours, which fully meets the natural day/night cycle requirements. Our findings advance the molecular design of artificial systems that replicate the comprehensive functions of natural photosynthesis.

The Immediate Partial Removal of Cumulus-Oocyte Complexes: A Refined Approach for Rapid Observation of In Vitro Fertilization.

Despite the rapid advancements in clinical and laboratory technologies for in vitro fertilization (IVF), a significant proportion (10%-15%) of patients continue to experience fertilization disorders, leading to low fertilization rates and the production of nonviable embryos. Short-term fertilization involves the early removal of granulosa cells to observe the extrusion of the second polar body, enabling the assessment of fertilization and early remedial measures to address low fertilization rates and complete fertilization failure. However, the observation of short-term fertilization in IVF is impeded by challenges such as excessively large unprocessed clusters of cumulus-oocyte complexes and adhesion between eggs, necessitating complex external procedures for granulosa cell removal, and prolonged observation duration. To tackle this issue, this study proposes a method of immediate partial removal of granulosa cells post egg retrieval. This approach streamlines subsequent stages of short-term fertilization and traditional fertilization monitoring, reduces the time needed for oocyte extrusion, minimizes the likelihood of external environmental impacts on the oocytes, and decreases the risk of missing the critical fertilization observation window. Consequently, the study yields novel clinical evidence aimed at enhancing the operational efficiency of embryonic laboratories in IVF.

An Organometallic Erbium Bismuth Cluster Complex Comprising a Bi66- Zintl Ion.

An organometallic erbium bismuth cluster complex, [K(THF)4]2[Cp*2Er2Bi6] (1), featuring a heterometallocubane core was isolated. The cube emerges from the rare Bi66- Zintl ion, bridging two erbium centers for the first time. SQUID magnetometry and ab initio calculations uncovered dominant antiferromagnetic coupling enabled through the chair-like hexabismuth anion. The gained insight will promote the design of future polynuclear magnetic molecules comprising prolate lanthanide ions.

Afadin mediates cadherin-catenin complex clustering on F-actin linked to cooperative binding and filament curvature.

The E-cadherin-β-catenin-αE-catenin (cadherin-catenin) complex couples the cytoskeletons of neighboring cells at adherens junctions (AJs) to mediate force transmission across epithelia. Mechanical force and auxiliary binding partners converge to stabilize the cadherin-catenin complex's inherently weak binding to actin filaments (F-actin) through unclear mechanisms. Here we show that afadin's coiled-coil (CC) domain and vinculin synergistically enhance the cadherin-catenin complex's F-actin engagement. The cryo-EM structure of an E-cadherin-β-catenin-αE-catenin-vinculin-afadin-CC supra-complex bound to F-actin reveals that afadin-CC bridges adjacent αE-catenin actin-binding domains along the filament, stabilizing flexible αE-catenin segments implicated in mechanical regulation. These cooperative binding contacts promote the formation of supra-complex clusters along F-actin. Additionally, cryo-EM variability analysis links supra-complex binding along individual F-actin strands to nanoscale filament curvature, a deformation mode associated with cytoskeletal forces. Collectively, this work elucidates a mechanistic framework by which vinculin and afadin tune cadherin-catenin complex-cytoskeleton coupling to support AJ function across varying mechanical regimes.

Light increases resistance of thylakoid membranes to thermal inactivation.

In the region of slightly acidic pH (рН 5.7), the manganese cluster in oxygen-evolving complex of photosystem II (PSII) is more resistant to exogenous reductants. The effect of such pH on the heat inactivation efficiency of the electron transport chain (O2 evolution and 2,6-dichlorophenolindophenol reduction) in PSII membranes and thylakoid membranes was investigated. Under thylakoid membranes illumination accompanied by lumen acidification, their resistance to heat inactivation increases. In the presence of protonophores, the rate of heat inactivation increases, which seems to be associated not with the protonophore mechanism, but with structural and/or functional changes in membranes. In PSII membrane preparations, the efficiency of the oxygen evolution inhibition at pH 5.7 is also lower than at pH 6.5. The role of reactive oxygen species in thermal inactivation of photosynthetic membranes was investigated using a lipophilic cyclic hydroxylamine ESR spin probe.

Photocatalytic Properties of a Functional Material Based on Modified Boron Nitride and a Molybdenum Cluster Complex

Photocatalytic Properties of a Functional Material Based on Modified Boron Nitride and a Molybdenum Cluster Complex