The efficiency of a solar cell is often limited by electron–hole recombination mediated by defect states within the band gap of the photovoltaic (PV) semiconductor. The Shockley–Read–Hall (SRH) model considers a static trap that can successively capture electrons and holes. In reality however, true trap levels vary with both the defect charge state and local structure. Here we consider the role of metastable structural configurations in capturing electrons and holes, taking the tellurium interstitial in CdTe as an illustrative example. Consideration of the defect dynamics, and symmetry-breaking, changes the qualitative behaviour and activates new pathways for carrier capture. Our results reveal the potential importance of metastable defect structures in non-radiative recombination, in particular for semiconductors with anharmonic/ionic–covalent bonding, multinary compositions, low crystal symmetries or highly-mobile defects. Metastable defect structures can activate novel pathways for electron–hole recombination in semiconductors – particularly for inorganic compounds with anharmonic/mixed bonding, multinary composition, low symmetry and/or highly-mobile defects. Among these, defect-mediated non-radiative recombination represents the dominant loss mechanism in emerging inorganic PV technologies.1,2 Identifying the ‘killer’ defect traps and hence potential synthesis and processing strategies to avoid their effects is crucial to mitigating losses and achieving high performance. For instance, the major efficiency improvements of the last 5 years for single-junction perovskite solar cells can be directly attributed to effective trap management.3The search for new thin-film photovoltaic (PV) materials must balance advantageous properties  processes, these defect levels allow excited charge carriers to recombine across the gap, reducing the open-circuit voltage in solar cells and the quantum efficiencies of light-emitting diodes for example.9,11,13–15 As such, their atomic structures often do not reside solely in their global equilibrium configuration, but may access alternative metastable structures via thermal, photo or electronic conversion. The possibility of structural transformation at defect sites has several potential impacts for technological applications—for example, low energy barriers between structures could lead to coherence corruption and a breakdown in performance for defects used in quantum computing and single-photon emission. In particular, carrier capture rates at defects are sensitively dependent on the atomic structure, varying by over 15 orders of magnitude with different geometries for the same nominal defect species,9,16 and so the presence of these alternative configurations can introduce alternative pathways which significantly alter the overall recombination kinetics. Indeed, this phenomenon has recently been reported in the literature, with metastable defects accelerating the electron–hole recombination process and transforming benign defect centres into harmful traps.9,16–18Point defects can exhibit complex potential energy surfaces (PESs), with multiple local minima.A complete analysis of the possible mechanisms and resulting impact of metastable configurations on non-radiative recombination in semiconductors is lacking. In this work, we first provide a general analysis of the potential recombination pathways introduced by metastable defect structures. We discuss the conditions for this behaviour to occur, the anticipated trends and the factors governing the consequences for material properties. We highlight tellurium interstitials in CdTe as illustrative exemplars of the potential complexity and importance of metastable configurations to carrier recombination, exhibiting a novel thermal-excitation recombination cycle which has not previously been reported in the literature, to the knowledge of the authors. Finally, we discuss the important implications of these findings to the broader field of photovoltaic materials research.D* that is both accessible and significantly influential on the overall capture behaviour.There are several mechanisms by which the presence of metastable structures can influence the overall defect behaviour in solids. Regarding non-radiative carrier recombination, the structural transition pathways introduced by metastable configurations on the defect potential energy surface can act to accelerate or retard this process, or may not affect it at all. of and transition barriers between ground and metastable configurations (i.e. their accessibility) (solid black arrows) and the defect energy level position in the host band gap .The impact of these metastable defects depends on the competing charge capture rates (dashed red/blue arrows), the relative energies band gap . Each ofq ± 2) have not been included here as the behaviour is mostly equivalent and, regardless, for recombination to occur, a closed path must be established  by introducing rapid capture into, but slow capture out of, these extremal charge states, thus acting to inhibit recombination as defects get ‘stuck’ in inert charge states,1,16,21 or (2) the rare scenario where Dq±2 introduces an alternative low-barrier pathway between Dq±1 and D*q±1 which does not exist otherwise, potentially accelerating the recombination process  and q ± 1 → q (blue), a fast internal relaxation means that D*q±1 acts as a reaction intermediate, introducing a rapid pathway for the recombination cycle to proceed. If, however, internal conversion is extremely slow and D*q±1 does not readily relax to Dq±1, several alternative pathways may emerge. The long-lived metastable configuration could undergo charge capture and return back to the original Dq, completing the e–h recombination cycle without involving Dq±1. Such behaviour would increase/decrease the overall recombination rate if the rate-limiting step for Dq ⇔ D*q±1 was faster/slower than that of Dq ⇔ Dq±1. Instead, if the defect level is sufficiently close to a band edge D*q±1 could readily emit the captured charge, acting as a shallow defect level with no effect on the recombination rate. Alternatively, if D*q±1 has both slow internal relaxation and slow charge capture, defects could become ‘stuck’ in this inert state and in fact greatly diminish the overall recombination activity.1,4,25In the above discussion, only non-radiative (phonon emission) pathways are considered. Under certain conditions, both charge capture and internal conversion may also proceed radiatively through photon emission. A detailed consideration of such behaviour is beyond the scope of this report, though we note that it is non-radiative capture which dominates efficiency losses in PV semiconductors.9,16–18 In each of these studies, it is the situation described in Dq captures an electron or hole by transforming to a metastable configuration of the q ± 1 defect (D*q±1). This metastable species then relaxes to the ground-state Dq±1 through an internal conversion reaction, whether a spin-flip de-excitation16 or (more commonly) structural/vibrational relaxation,17,18 or both.9 In each case, this alternative pathway is found to proceed more rapidly than the standard Dq ⇔ Dq±1 charge capture process , which are the Fermi level positions where the equilibrium charge state switches between q1 and q2, given by:HD,q(EF = 0) is the formation energy of defect D with charge q when the Fermi level is at the zero-reference point . Taking q1 = q, q2 = q ± 1, and denoting the energy of the metastable defect ΔHD*,q±1 as:E is the energy of the metastable defect relative to the ground-state structure, we can then substitute into The shift in defect energy levels when metastable defects are involved , assuming a transition level ε(q/q ± 1) initially located within the band gap. Conversely, this shift in TL position also means the TL will be located further from the relevant band edge for the D*q±1 → Dq transition (capture from the metastable defect). For example, the ε(0/−1*) transition level is located closer to the CBM, from which electrons are captured by D0 to form D*−1, than ε(0/−1), but further from the VBM, from which D*−1 could capture holes to complete the recombination cycle. Under the conventional rationale of capture rates being exponentially dependent on the separation of the defect level from the band edge,1,9,19,20 this implies a faster capture into the metastable configuration (Dq → D*q±1) than the ground-state process (Dq → Dq±1), but a slower capture rate in the opposite direction (D*q±1 → Dq). As discussed above, if D*q±1 can swiftly relax to Dq±1, the situation depicted in via the TL nearest the conduction band and hole capture via the TL nearest the valence band, likely expediting the recombination process as observed in ref. D*q±1 → Dq±1 transition, relative to the slowest charge capture process, will dictate whether the metastable defect accelerates or retards the overall recombination rate. Given typical effective vibrational (attempt) frequencies of ∼0.5–10 THz,9,18,26 internal conversion is unlikely to be the rate-limiting step in a fast recombination cycle if the transition energy barrier ΔE is less than 0.2–0.4 eV (Section S3.1Thus we witness that for charge capture ε(q/q* ± 1) must lie within the band gap formed between the valence band maximum (VBM) and conduction band minimum (CBM):ε(q/q* ± 1):ε(q/q ± 1) and the corresponding band edge sets an upper limit on the relative energy of the metastable structure, if it is to yield a transition level within the band gap and potentially affect carrier recombination (D*−1 in D*−1 relative to D−1 must be less than the energy separation of ε(0/−1) and the CBM.Another important consideration is that for the metastable configuration to enter the recombination process, the transition level bination . For insCd which ranges from −2 to +2).27 These 20 defect species yield 14 in-gap levels involving only ground-state structures. With our recently-published defect structure-searching technique (see Methods),11,12 we further identify 14 metastable structures for these charge states, generating 32 additional charge transition levels. Only 12 of these structures are sufficiently low energy to yield at least one transition level within the band gap, including those for Tei discussed here and VCd discussed in ref. As an example, in CdTe, there are 6 intrinsic defects , which range in charge from 0 to either −2 or +2 for a Fermi level within the band gap , the metastable configuration acts as an accelerating reaction intermediate to electron–hole recombination through the path Dq → D*q → Dq±1 → Dq  to be an exemplar of this charge capture phenomenon. The individual defect structures and corresponding transition level diagram for Tei in CdTe are shown in In our calculations of point defects in CdTe, we found the low-energy tellurium interstitial  about the [001] axis, thus reducing to C2 point group symmetry with the removal of the {110} mirror plane.We find that TeTe dimer , as firsab initio geometry relaxation from the high-symmetry tetrahedral interstitial coordination does not find the neutral ground-state Te0i, but rather converges to a higher-energy structure  with a formation energy only 127 meV higher than the split-interstitial dimer ground-state  yielding C2v point symmetry .26,33,34 We thus determine a diffusion barrier of 0.13 eV for Te0i using the HSE(34.5%) + SOC functional . In combination with a spin degeneracy of 2 arising from the unpaired electron, the total configurational degeneracy is thus g+1 = 12. There are two equivalent clockwise/anti-clockwise rotations about the [001] axis which give the neutral Te0i twisted dimer (C2 symmetry)  , and no ing away , giving tructure  further Er:35–37ND is the defect concentration, g is the site degeneracy, Ns is the concentration of lattice sites and ΔH is the defect formation enthalpy. The ‘reduced energies’ for Tei are given in Er(300 K) = 18 meV between ground and metastable configurations for Te+1i corresponds to an equilibrium concentration ratio of only  at room temperature, while for Te0i the greater degeneracy of the ground-state disfavours the metastable configuration. Notably, such entropic effects become even more significant at elevated temperatures  and for cases with larger degeneracy differences . This phenomenon is another important consequence of symmetry-breaking and metastable configurations for point defects in semiconductors, which can significantly impact bulk defect concentrations and thus Fermi level position, in addition to the effects on non-radiative recombination discussed here.The consequences of degeneracy mismatches between ground and metastable defect structures can be exemplified by the temperature-dependent ‘reduced energy’ i defect levels, we employed the one-dimensional configuration coordinate model of Alkauskas et al.4 as implemented in the CarrierCapture.jl package.5 The potential energy surfaces (PESs) for Tei along the structural paths (configuration coordinates Q) between neutral and positive configurations are shown in To determine the non-radiative electron/hole capture rates of the TeWif = 〈Ψi|∂Ĥ/∂Q|Ψf〉) and solving the 1D Schrödinger equation to determine the effective vibrational wavefunctions for the calculated energy surfaces, the non-radiative recombination activity of the corresponding defect transition levels (TLs) may be computed, with the results for Tei provided in En/p in En/p and/or close overlap of the defect PESs near the equilibrium position typically yields fast carrier capture, while large barriers and/or significant separation of PESs results in slow capture rates.By calculating the electron–phonon coupling 2 ≃ 1.5 × 10−15 cm2 – classify Tei as a ‘giant’ hole trap.25,38,39 On the other hand, we witness negligible electron capture due to high barriers and low PES overlap for the (+/0) and (+/0*) transition levels  and (+*/0*) levels in En emerges, yielding an increase in the electron capture rate by over 6 orders of magnitude to σn ∼ 10−19 cm2  remains dependent on the defect and carrier concentrations (ND and n) in the material (R ∝ NDσn), meaning defects with moderate capture cross-sections can act as performance-limiting species if they form easily in the bulk, as is the case for Tei in commercial Te-rich CdTe.Inspecting the defect PESs in ase here . The larn levels , with ti0−19 cm2 . To contσn of  does, however, permit electron–hole recombination to proceed through the three-step and four-step process shown in , before electron capture to either the ground-state or metastable neutral interstitial , and finally fast hole capture to complete the recombination cycle. For the thermal excitation , we calculate an energy barrier of 0.08 eV (1012 cm−3) ≃ 101 s−1), as is also the case for the barrier-less  vibrational relaxation. Further details for these calculations are provided in Section S3.†The slow electron capture rates of the (+/0) and (+/0*) TLs rule out the possibility of significant Shockley–Read–Hall e–h recombination through the typical two-step process , or indeV Fig. S2 and an ei defect structures under typical solar cell operating conditions  to enter the recombination cycle, it must be positioned within the band gap, setting an upper limit to the relative energy of the metastable structure D*q (eqn (S25) and (S26)D*q), now the initial state in the capture process, results in a charge transition level ε(q*/q ± 1) which is now further from the corresponding band edge than ε(q/q ± 1)  charge transition level, located furthest from the CBM of all Tei (+(*)/0(*)) defect levels  . While at levels , exhibitt levels . This unt levels , highlige.g. Bi, Sb and Sn-based materials),1,41 low crystal symmetry (e.g. Sb2X3)42,43 and/or compositional complexity (e.g. multinary compounds such as CZTS and double perovskites)44–46 are likely to manifest local minima on defect energy surfaces. Low-energy metastable defect structures may be especially prevalent in emerging inorganic PV materials which tend to exhibit these properties, highlighting the potential importance of these species to investigations of non-radiative recombination and open-circuit voltage deficits in emerging solar cells. Indeed, even in the case of the high-symmetry binary semiconductor CdTe, many low energy metastable structures exist, introducing 18 additional charge transition levels in the gap and accelerating the carrier trapping at Tei and VCd.9 An important factor in the emergence of the thermal-excitation capture pathway here is the high mobility of the Te interstitial in CdTe, as demonstrated by the low diffusion barriers calculated in this and previous works.26,33,34 The facile ionic diffusion of Tei is a simultaneous consequence of the soft, anharmonic PESs which cause the ready accessibility of distinct structural motifs (i.e. low-lying metastable structures), facilitating this complex recombination pathway. Thus, we additionally propose rapid diffusion as a potential indicator of this behaviour at other semiconductor defect centres. Finally, we note that the very presence of metastable structures on the defect PES implies a softer and more anharmonic energy landscape, with smaller barriers between structures. As exemplified in this and other studies,7,9,21,47 such effects often yield unintuitive recombination kinetics, with fast trapping despite deep energy levels.Accordingly, these findings yield important considerations. Semiconductors exhibiting strong anharmonicity and mixed ionic–covalent bonding  in CdTe solar cells as an illustrative example of this phenomenon, exhibiting complex 3-step and 4-step recombination cycles which, to our knowledge, have not been previously reported in the literature. In addition to demonstrating the major potential impact of metastable structures on defect-mediated electron–hole recombination, Tei serves a clear example of anharmonicity causing deviation from the typical trend of reduced capture rates with deeper defect levels (i.e. greater energy separation from the band edge). Finally, we highlight implications to the broader field of photovoltaic materials research. We pose that metastable defect structures are more important to non-radiative recombination than currently understood, particularly in the case of emerging inorganic PV materials which often exhibit reduced crystal symmetries, mixed ionic–covalent bonding, multinary compositions and/or highly-mobile defects like Tei, where anharmonicity, symmetry-breaking and soft potential energy surfaces are likely to yield many low-lying, easily-accessible metastable structures, enabling the behaviour discussed here.In conclusion, metastable defect structures impact non-radiative recombination in semiconductors. They introduce a complex set of potential recombination paths at defects, akin to chemical reaction mechanisms, with the overall kinetics being a function of the individual transition rates. In addition to the thermal-relaxation pathway discussed in recent works,5 with electron–phonon coupling matrix elements determined using the method outlined in ref. Ab Initio Simulation Package (VASP), employing Projector-Augmented Wave (PAW) pseudopotentials.48–51 The screened hybrid DFT exchange–correlation functional of Heyd, Scuseria and Ernzerhof (HSE),52 including spin–orbit interactions (SOC), was used for all calculations. An exact Hartree–Fock exchange fraction of αexx = 34.5% was employed in the hybrid DFT model, reproducing the room temperature experimental band gap of 1.5 eV for CdTe. A 64-atom, 13.1 Å cubic supercell was used for defect calculations, with a well-converged 450 eV plane-wave energy cutoff, a 2 × 2 × 2 Γ-centred Monkhorst–Pack k-point mesh and a force convergence criterion of 0.01 eV Å−1 for geometry optimization. The ShakeNBreak defect structure-searching method which aids the efficient location of ground and metastable structures for defects in solids was employed.11,12Anharmonic carrier capture coefficients were calculated using CarrierCapture.jl,https://doi.org/10.5281/zenodo.5999057.Data produced during this work is freely available at There are no conflicts to declare.FD-239-D2FD00043A-s001


Compared with other common free radicals, it has the advantages of a longer half-life and higher oxidation potential, which could bring unexpected effects. These properties have prompted researchers to make great contributions to biology and environmental engineering by exploiting their properties. Peroxymonosulfate (PMS) and peroxydisulfate (PDS) are the main raw materials for SO4−· formation. Due to the remarkable progress in nanotechnology, a large number of nanomaterials have been explored that can efficiently activate PMS/PDS, which have been used to generate SO4−· for biological applications. Based on the superior properties and application potential of SO4−·, it is of great significance to review its chemical mechanism, biological effect, and application field. Therefore, in this review, we summarize the latest design of nanomaterials that can effectually activate PMS/PDS to create SO4−·, including metal-based nanomaterials, metal-free nanomaterials, and nanocomposites. Furthermore, we discuss the underlying mechanism of the activation of PMS/PDS using these nanomaterials and the application of SO4−· in the fields of environmental remediation and biomedicine, liberating the application potential of SO4−·. Finally, this review provides the existing problems and prospects of nanomaterials being used to generate SO4−· in the future, providing new ideas and possibilities for the development of biomedicine and environmental remediation.Sulfate radicals (SO Bacteria that are challenging to combat have drawn a lot of attention in recent century as society has developed. Examples include infections in the biomedical field, contamination of drinking water, and biological invasion in the environmental engineering field, all of which pose a hazard to the survival of all kinds of animals in nature and human health ,2,3,4,5.2-Cu @RB NPs using copper-doped zinc peroxide nanoparticles (ZnO2-Cu NPs) and the antibacterial agent Rose Bengal (RB), efficiently killing S. mutans in acidic biofilms by CDT . M. M2+ andeatments d 63]. M. M2+ andte SO4−· e 64]. I. I2+ andadiation f appliedstewater .3), mackinawite (FeS), pyrite (FeS2), magnetite hematite (γ-Fe2O3), Hormuz Red Soil (HRS) (α-Fe2O3), and FeO (OH). Some have been shown to be native catalysts for the activation of PMS/PDS to remove contaminants and kill bacteria. Mohammadi et al. used HRS as a nanocatalyst to activate PMS to produce SO4−·, killing E. coli and Enterococcus in a relatively short time, and showing potential for wastewater purification and disinfection . However, the value of Fe (IV) deserves further exploration . I. I3), mastewater i 69]. A. A3), masolution . Surprisloration . It has erbodies . In addin et al.  and Cai n et al.  achievedin water . Other rreatment j 76]. R. R3), mareatment k 77]..3), mack2+ is not as good as that of Co2+/Co3+ or Fe0/Fe3+ in activating PMS/PDS, Ni2+/Ni-based catalysts for the generation of SO4−· have rarely been studied. Encouragingly, however, Yue et al. synthesized NiO nanosheets rich in porous defects for PDS activation, providing a new Ni-based catalyst for persulfate activation, which represents a promising Fenton-like catalyst for environmental remediation , and δ-MnO2 (such as corolla) have previously been investigated, whose ability to activate PMS depends on their morphology, valent state, and crystalline phase. Compared to Mn3O4 nanoparticles or nanorods, Wang et al. developed 3D-graded Mn3O4-H nanomaterials assembled from 2D nanosheets with a 10–20 nm thickness, revealing a higher catalytic performance in the activation of PMS to remove organic pollutant phenol in wastewater, which was attributed to the larger surface area and increased number of active sites generated , which can gradually provide Mn2+ for the efficient utilization of PDS, showing an outstanding activation efficiency. Additionally, it was found to be stable and environmentally friendly in the treatment of CIP, which is a promising alternative for potential remediation and detoxification of CIP and other emerging water pollutants  are abundant in nature and are more compatible with the environment . Nanorodenerated b 79]. A. A2  and then reoxidized to Mo (VI), which changed PMS to form SO4−·, where S was involved in formatting the reactive layered structures that enhanced the activity. However, the process of reducing Mo (VI) to a lower valence may be more difficult than that of oxidation, and it is unfavorable for the MoS2/PMS/PDS system  doping, tuning of the electronic properties helps to generate additional active unsaturated sulfur sites . H. H2 is aur sites ,88. Compimproved ,90. Zengnstrated . At the le light i 92]. I. I2 is aformance j 93]. I. I2 is allutants k 94]. M. M2 is aediation . Shockin results . At the ) sensor  and was ) sensor , showing2 is a cost-effective, stable, and environmental photocatalyst that has received significant attention in the field of water environment restoration. It simultaneously produces oxidized holes (h VB+) at the valence band and reducing electrons (e CB−) at the conduction band when activated by light. However, the rapid recombination of both notably depresses the oxidation capacity of the photocatalyst. The addition of PDS can restrain the recombination of h VB+ and e CB− while producing SO4−· . . 2 is a reatment b 103]. . 2 is a stewater . Recentltivation c 105]. . 2 is a ironment d 106]..2 is a c2O5 activation of PDS to degrade organic pollutants is strongly influenced by the morphology, with some studies concluding that VW (linear) > vs.  > VR (rod). Furthermore, the surface area and exposed crystalline surfaces may affect the activation capacity and a lower Fermi energy and higher VW positive charge density favors activation . . −/h+ pan and Mn+1, improvement in stability by reducing agglomeration and reducing the leaching of metallic elements, and improvement of the recoverability by increasing magnetic properties, etc., which are summarized in 2O4, with exceptional superparamagnetism; a large adsorption capacity; and biological, optical, and catalytic properties . . n+1Xn, stewater .4−· production from peroxynitrite. CMK-3 exhibits a superior activation performance in contrast to CMK-8 due to its more stable adsorption capacity, larger superficial area, and charge-transport reduction (lesser oxygen content) . . 4−· protivation . The usetivation . Graphition [4−· . From a vate PDS . Graphitf g-C3N4 . It has llutants . The phollutants . Some pece SO4−· . Rhomboh studies . Ye et a studies . Zhang emedicine b 167]..4−· prodThe advantages of non-metallic nanomaterials include that it can be better adsorbed by contaminants by increasing their surface area and surface defects and there is no metal leaching. Furthermore, rejected material can be utilized as raw materials. Their disadvantages are that it is difficult to achieve the best properties due to the increased sensitivity to operating details and agglomeration may reduce the degradation efficiency . Despite4−· generation.Metal-based nanomaterials exhibit a high catalytic performance, accompanied by secondary contamination from metal leaching and an unstable performance from agglomeration, and often require binding to a carrier. Carrier materials supply attachment points for the metal to improve the electron transport efficiency and have a large surface area to adsorb contaminants such as microorganisms and better stability in wastewater and in living organisms. The coordination of the two makes use of their respective advantages reduces their shortcomings, improving the catalytic performance, and resulting in efficient SO2 catalytic membranes), and other non-carbon-based materials , bacterial cellulose (BC), etc.).This section focuses on composites composed of metal-based nanomaterials and metal-free carriers, which usually have satisfactory chemical stability, high mechanical strength, and a large surface area. Usually, carrier nanomaterials can be classified as carbon materials , silica , paving a new way for recalcitrant contaminant degradation by SR-AOPs for environmental applications . . 2O4 [3Oal field b 176]..2O4 . . 3O4 loaediation . CMs  took on a 2D structure similar to graphite, which also had some advantages, including a large specific area, high resistance to oxidation, high thermal conductivity, numerous structural defects, and chemical durability. Its crystal structure and morphology were able to be altered to achieve a better performance, for instance, nanoribbon, nanotube, nanofiber, nanosheet, etc. The use of BN as a support skeleton for dispersing metal-based nanoparticles contributed to effectually broadening the field of application and brought new hope for activation reaction by exploiting the superiority of both, such as the effective immobilization of CoFe2O4 f 197]. . 2O4  nanocomplexes for cesium removal. Additionally, this team also synthesized FCPBA/PAN , which could load a significant amount of FCPBA and showed a better catalytic performance . ZIF-67 2O4 nanoparticles on the kaolinite surface. In addition, affluent Al hydroxyl provides reactive sites to activate PMS, contributing to greater BPA degradation and thus providing an interesting insight for PMS activation using highly efficient natural mineral-based catalysts for wastewater reclamation ..− transf4−· to fight microorganisms has been tested and verified in the biological and environmental field. Nevertheless, there are arguments regarding the possible environment impact of the release of nanomaterials into the environment [42−, and inevitable quenching reaction are noted as the major restrictions [Although the effectiveness of nanomaterials in advanced SR-AOP has been widely demonstrated, various challenges remain to be addressed. The advantages and disadvantages of the sulfate radical-advanced oxidation of nanomaterials in biological applications are shown in ironment . In manyironment . The prorictions . Before rictions .2, type of light, and number of nanomaterials used [2, the infectious or tumor microenvironment, which is mainly anaerobic, would affect the generation efficiency and thus affect the antibacterial and antitumor efficacy. In addition, regarding the effect of pH, the pH environment in the human body changes due to different disease conditions. Tumors and caries make the surrounding microenvironment acidic, which is conducive to the production of SO4−·. Periodontitis, on the other hand, is an alkaline environment that converts SO4−·into an inefficient •OH. These problems need to be solved [As with traditional catalysts, nanocatalysts largely depend on the operating parameters, for example, the pH value, coexistence of Oals used . In terme solved ,212.4−· for the removal of most organic pollutants and a few antibacterial and antitumor applications, the application of SO4−· in microorganism inactivation is worthy of further exploration and research. However, the disinfection effect and inactivation mechanism of various pathogenic microorganisms have not been thoroughly studied, which is a knowledge gap. Some researchers believe that microbes are killed by the destruction of their cell membranes, cell walls, and genetic material, but this has not been well proven [4−· in water disinfection and the biomedical field.In view of the successful implementation of SOl proven . Therefo4−· indeed has many advantages over other common reactive oxygen species, this is a hot spot that should be studied. On the other hand, the mechanism of SO4−· killing of tumor cells and pathogenic microorganisms deserves more intensive investigation for better application in medicine. We look forward to the research directions and development prospects of nanomaterials involving SO4−·.Although the combination of SR-AOPs with nanomaterials has been extensively studied, further research and development of innovative approaches to increase their potential is still necessary. Moreover, studies of applications in the medical field are scarce and since SO


In the published article, there were errors in several figures and tables, and their captions. Due to the removal of one participant, several amendments were required to the values stated. The corrected figures, tables, and captions are shown below.Due to the removal of one participant, several corrections were also required to the text.Abstract, sections Design and Results. The corrections are shown below.Corrections have been made to Abstract, DesignThis sentence previously stated: “Twenty-five children with word reading difficulties and 28 control children with good word reading skills participated.” The corrected sentence appears below:“Twenty-four children with word reading difficulties and 28 control children with good word reading skills participated.”Abstract, ResultsThis sentence previously stated “The results from children with word reading difficulties showed that 5 children (20%) had comorbid deficits in auditory processing, visual attention, and backward digit memory; whereas 12 children (48%) had comorbid auditory processing and visual attention deficits only.” The corrected sentence appears below:“The results from children with word reading difficulties showed that 5 children (21%) had comorbid deficits in auditory processing, visual attention, and backward digit memory; whereas 12 children (50%) had comorbid auditory processing and visual attention deficits only.”Materials and Methods, sections Participants and Inclusion Criteria.Corrections have been made to Materials and Methods, ParticipantsThis sentence previously stated: “Fifty-three children aged 8–11 years (Mean age in years ± SD = 9.7 ± 1.17) participated in the current study. Of the 53 children, 25 (9.5 ± 1.16 years) were identified as having reading concerns.” The corrected sentence appears below:“Fifty-two children aged 8–11 years (Mean age in years ± SD = 9.8 ± 1.15) participated in the current study. Of the 52 children, 24 (9.5 ± 1.15 years) were identified as having reading concerns.”Materials and Methods, Inclusion Criteria, Paragraph 6F = 1.64, p = 0.18]. The group mean audiometry result for the left and right ear is presented in Figure 1 that shows no significant difference for the extended high frequencies 8k to 12.5k Hz . The control group showed a small but significant advantage on the WNV when compared to the group with word reading difficulties , but both groups scored around 1 SD above the mean on average  = 0.29, p = 0.84]. The group mean audiometry result for the left and right ear is presented in Figure 1 that shows no significant difference for the extended high frequencies 8k to 12.5k Hz . Both groups scored similarly and around 1 SD above the mean on average on WNV .”“Results.Corrections have been made to several sections within Results, Tests of Reading and Phonological ProcessingF = 45.0, p < 0.001).” The corrected text appears below.The paragraph previously stated: “By contrast, the group with word reading difficulties had mean z-scores of −1.9 (SD = 0.40), −1.4 (SD = 0.66), and −1.9 (SD = 0.40) respectively. Children in the control group achieved standard scores of 13.8 (SD = 1.20) on the phonological awareness test of elision while the children with word reading difficulties had an average standard score of 10.3 (SD = 2.65) with a statistically significant difference between the groups  = 38.9, p < 0.001].”“By contrast, the group with word reading difficulties had mean z-scores of −1.9 (SD = 0.42), −1.5 (SD = 0.56), and −1.9 (SD = 0.43) respectively. Children in the control group achieved standard scores of 13.8 (SD = 1.20) on the phonological awareness test of elision while the children with word reading difficulties had an average standard score of 10.3 (SD = 2.71) with a statistically significant difference between the groups  = 19.3, p < 0.001).” The corrected sentence appears below.The sentence previously stated: “A univariate analysis of variance conducted on children's PPVT-4 standard scores showed that participants with word reading difficulty knew significantly fewer spoken word meanings (99.4 ± 7.9) than children in the control group  = 18.0, p < 0.001].”“A univariate analysis of variance conducted on children's PPVT-4 standard scores showed that participants with word reading difficulty knew significantly fewer spoken word meanings (100.0 ± 7.88) than children in the control group .” The corrected sentence appears below.The sentence previously stated “An additional two-way ANOVA confirmed the presence of a significant interaction between group and subtest .”“An additional two-way ANOVA confirmed the presence of a significant interaction between group and subtest [Results, Subgroup Profiles, Paragraph 3n = 5) had comorbid deficits in three variables: auditory processing, visual attention, and digit memory. A larger percentage of children  had comorbid deficits in two variables: 12 children had auditory processing deficits and visual attention difficulties, and 2 had deficits in auditory processing and digit memory. No child experienced comorbid deficits in only visual attention and digit memory. Finally, six (24%) of the children with word reading difficulties displayed a comorbid deficit in just one other variable: four children had visual attention difficulties, one an auditory processing deficit, and one a deficit in digit memory. An alternative way of thinking about these subgrouping data is that 84% (n = 21) of this cohort of children with word reading difficulties had comorbid visual attention problems, and 80% had auditory processing deficits. Further detail regarding the specific deficits displayed by each child with non-word reading difficulties is presented in n = 11).” The corrected paragraph appears below.The paragraph previously stated: “n = 5) had comorbid deficits in three variables: auditory processing, visual attention, and digit memory. A larger percentage of children  had comorbid deficits in two variables: 12 children had auditory processing deficits and visual attention difficulties, and 2 had deficits in auditory processing and digit memory. No child experienced comorbid deficits in only visual attention and digit memory. Finally, six (25%) of the children with word reading difficulties displayed a comorbid deficit in just one other variable: 4 children had visual attention difficulties, and 1 an auditory processing deficit. An alternative way of thinking about these subgrouping data is that 88% (n = 21) of this cohort of children with word reading difficulties had comorbid visual attention problems, and 83% had auditory processing deficits. Further detail regarding the specific deficits displayed by each child with non-word reading difficulties is presented in n = 13) or on both visual attention tasks of switching and selective (n = 11).”“Results, Correlations Across Auditory Processing Tasks in Children With Word Reading Difficulties, Paragraph 1r = −0.70, p < 0.001) and FD  but not DDdT . The dichotic score was correlated to the diotic score though . There were no more significant correlations between any of the other auditory processing measures. Furthermore, digit backwards scores were also not significantly correlated with any auditory processing measures (p's > 0.05).”The paragraph previously said, “The corrected paragraph appears below.r = −0.75, p < 0.001) and FD  but not to combined score of DDdT . The dichotic score was correlated to the diotic score . Digit backwards scores were significantly correlated to FPT, and FD (p's ≤ 0.001).”“Results, Correlations Across Auditory Processing Tasks in Children With Word Reading Difficulties, Paragraph 2r = 0.29, p = 0.21). This table also shows that none of the word reading measures were correlated with visual attention, receptive vocabulary, or elision (p's > 0.05) Irregular word reading was, however, significantly correlated with regular word reading .” The corrected sentence appears below.The sentence previously said, “This table shows no significant correlation between selective attention and attention switching . This table also shows that the word reading measures were significantly correlated to each other and to switching attention, receptive vocabulary, and elision (p ≤ 0.001).”“This table shows significant correlation between selective attention and attention switching  children would be considered to have visual attention deficits compared to the current 21 (84%).” The corrected sentence appears below.“For instance, none of the children would be regarded as having a digit memory deficit, and only 14 (58%) children would be considered to have visual attention deficits compared to the current 21 (88%).”Discussion, Comorbidities in Children With Word Reading Difficulties, Paragraph 2no other deficit, and a further 4 children showed evidence of deficits in auditory processing and/or digit memory, despite having no attention deficit. Furthermore, all except one of the 25 children with reading difficulties, including those with visual attention deficits, performed within 1 SD of the typical mean on both phonological processing (elision) and receptive vocabulary.” The corrected sentence appears below.The sentence previously said, “However, this suggestion does not appear to hold true for the current cohort in which 4 out of 21 children with an attention deficit showed evidence of no other deficit, and a further 3 children showed evidence of deficits in digit memory and/or auditory processing, despite having no attention deficit. Furthermore, all except one of the 24 children with reading difficulties, including those with visual attention deficits, performed within 1SD of the typical mean on both phonological processing (elision) and receptive vocabulary.”“However, this suggestion does not appear to hold true for the current cohort in which 4 out of 21 children with an attention deficit showed evidence of Discussion, Auditory Processing Skills in Children With Word Reading Difficulty, Paragraph 4n = 7, 32%) had both FPT and DDdT deficits.” The corrected sentence appears below.The sentence previously said, “At the same time, most of the children with word reading difficulties  had both FPT and DDdT deficits.”“At the same time, only a third of the children with word reading difficulties , 80% of children with non-word reading difficulties showed a significant deficit.” The corrected sentence appears below.“On the standardized tests of auditory processing , 83% of children with non-word reading difficulties showed a significant deficit.”The authors apologize for these errors and state that they do not change the scientific conclusions of the article in any way. The original article has been updated.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Restraint reporting varies, which undermines regulation, obfuscates analyses, and incentivises minimisation. The English Mental Health Units Use of Force Act 2018, “Seni's Law” mandates reporting. This paper analysed open data from all psychiatric and learning disability institutions in England from September 2020 to August 2021. We correlated logarithms of “people restrained per month”, against “bed days” per month and “people under legal mental health detention” per month, per institution. We designated institutions reporting some restraint for at least 11 of 12 months as reporting “completely” and used their trend to infer rates from non-“complete” institutions. Allowance was made for size. Our a priori manual can be shared on request.2 0.90 (2.s.f). Persons detained per month also correlated with restraint: R2 0.78. “Partial” institutions reported intermittently. “Joiner” institutions reported firstly null, then substantive reporting. “Null” institutions (including the largest) reported no restraint. Precisely-reporting institutions with high inverse variance between months reported similar restraint-rates but less-precise reported lower rates. In institutions reporting no restraint, two independent “true rate” estimations, by bed-days or people detained, correlated across institutions: R2 0.95. Inference from size suggested non-complete reporters restrained 1,774 people in England per month 95% CI .Logarithms of people restrained per month and bed-days per month correlated among complete reporters: R2. Institutional restraint reports can be compared per-bed per-month. Rates of people detained are a useful independent “checking” comparator in England.Restraint remains under-reported. Institutional size explains most restraint variation among complete reporting institutions, 90% of R Seni's law, the Mental Health Units Use of Force Act 2018, requires institutions in England and Wales to report restraint , both within the 12 months. Other institutions were neither small nor complete, and sub-categorised as “By definition, “Joiners” consistently reported null then consistently reported restrained people – reporting none then many. “Partial” reporter institutions had intermittent null but were not small enough to be in the continuous “small” series - reporting many people restrained then none then many, etc. “Null” report institutions reported only null all year despite not being small – reporting none throughout while being the size of trusts reporting many. Small reporters with null restraints, and “joiner” or “partial” Bed-Day reporting style were categorised “null” – if bed counts were partial we did not trust restraint counts.Data downloaded early in real time showed a log/log trend so log-relationships were settled, as the field of analysis, before receipt of final data. Base 2 was chosen, for logs, for compatibility with planned statistical tests.2 (2i*2ii) is 4. 27 (2i*2ii*2iii…2vii) is 128. Log2 14,000 gives LnBeds 13.77 because 213.77∼14,000. The 65 restrained people gives LnRestraint 6.02 because 26.02∼65. The Ln/Ln ratio between LnRestraint people and LnBeds would be 6.02/13.77. Graphical plotting show the pattern as in It is convenient to discuss base 2 logarithms. Consider an institution with 500 beds and 65 restrained persons in a month after rounding, which is 14,000 bed days per month, in April. 2Each institution's report estimates a relationship between e.g., size and restraint in log/log graph terms. Each is an estimate of “slope”, which trend can be firstly expressed as y = mx + c the line equation and secondly give a measure of variance. Variance allows confidence intervals. For log people restrained per log bed days, such estimates of slope appeared normally distributed on visual inspection, so confidence intervals of slope could be estimated.2, coefficient of determination, assessed correlations between log metrics. Precision was 1/Standard Error in funnel plots, which is the convention. Laplace correction of 1 was applied to all data to allow log of null to be 0.RGeneral patterns of reporting were as follows. The set of institutions comprised 84. That is all institutions in England who reported mental health people detained, reported mental health bed days, or reported restraint , and who were not one of the four excluded institutions. The biggest “small” institution for people restrained had around 2200 monthly bed-days. The biggest “small” institution people detained had around 1,000 bed-days because detention is more common than restraint. Institutions of these size and smaller could not be impugned when they reported null restraint, because they also had months with 5 or 10 persons restrained, as did similar sized institutions.Regarding variance in reporting, see funnel plot of n = 41 small or complete restraints per size estimates could be calculated. n = 33 small or complete estimates of restraints per people detained could be calculated, 5 partial, 4 joiners. 33 and 41 are not additive; they are separate analyses. In other words, half of institutions could not even be included in either funnel plot.On visual inspection, partial reporters had less precision (inverse variance) than joiners in both types of graph, namely funnels and scatters. That is to say the white circles are higher up the funnel plot 2 of 0.90 (2sf), see Regarding correlations of size and restraint, in its scatter plot, correlation of “small or complete” institution LnRestraint per LnBeds from complete reporters had RJoiner reporters did not contribute to calculation of the slope of the LnRestraint per LnBeds trend but fell close to it .Null reports contribute the horizontal limb of an “L” on the scatter (black) and, as stated above, are absent from funnels, having no calculable precision. Formally, a report of 0,0,0,0…, or a single report, has no variance from which to calculate “precision”, even if it were “true”, so null reporters were not funnel plotted.Slope estimations for LnRestraints/LnBeds approximated normal distribution on visual inspection. This allowed an average and confidence limits for estimates of monthly person restrained derived from trends in institution size and person restrained. The sum of average estimates by size of people per month restrained in institutions with non-“complete” restraint reporting style estimated was 1,774 95% CI , per month. We suggest this can be extrapolated to 12*1,774 for the year, with caution.Similarly the 2 late joiner trusts fell near the trend for complete reporter LnRestraint per LnBeds, see 95% confidence interval predictions in The most striking result requiring little quantitative detail is that very largest institutions report null.2 of 0.78 (2 sf) for small or complete reporters and had an equivocal distribution of slope estimates.Regarding correlations of restraint and detention, LnRestraint/LnDetentions showed R2 = 0.95  for larger institutions. Under that divergence, LnBeds always provided a higher estimate of restraint than LnDetention: e.g. 279 vs. 61 restraints, for the largest “null”, predicted using LnBeds and LnDetention respectively. In other words, number of people detained per month and number of people restrained per month make correlated predictions. The true rate remains unknown in null reporters, by definition.Then, following a pause of three months during peer review, we opportunistically used bed days to predict the December 2021 restraint figures for the only two null reporting institutions who became Joiner reporters. Their 95% confidence intervals lay between a notional line of perfect prediction and the actual trend between prediction by size and reported figures, see This analysis reads institution's reports as holding implicit estimates of a trend in frequency of restrained people per month per monthly bed-days, as plotted on a log-log graph to handle effects of scale.Reporting remains incomplete per the literature and publicly available documents. Our funnel and scatter plots add a suggestion omissions of restrain reports may not be random. We show that restraint seems related to size and people detained, which is a helpful addition to the discourse, and has face validity.Janssen et al. 2011 aimed to correct for five factors in their institutional analysis namely regional size, urbanicity, secure care, beds and admissions. We are constrained by externally defined metrics and a manifestly incomplete dataset. In England, the largest institutions have secure wards. Our method does not correct directly for regional size or urbanicity, but calls upon bed days and people detained to be proxies for them, and benefits from people detained as a comparator which takes acuity into account.Use of three reasonably independent metrics  allows some internal validation. Furthermore, we use that insight to show how restrained people per month might be estimated, in principle, among incompletely reporting institutions. That may be of use to regulators.This analysis used funnel plots . ClassicPerhaps most imprecision in restraint reporting is caused by omissions; intuitively omissions of restraints are more likely than spurious “over-reporting” of fictive people restrained per month. Alternatively, institutions that restrain most might consequently develop precise measurement. Conversely, highly restraining institutions who report highly imprecise restraint rates may close or be subsumed.Inescapably, though, readers may postulate publication bias. Null reports may be voluntary. Institutions might “stay out” of reporting fearing unfair comparison, or for other reasons. New joiners are precise, and consistent, once they join. Perhaps they perfected reporting methods before sharing their data.There are limitations to these methods. The first author's employment by a large and candid NHS trust may paradoxically invite concerns of bias. The underlying data may be rounded; but that is owned by NHS Digital, for good reasons. The data is incomplete; but the incompleteness is our point. Categorisations may be subjective; but categorisations would be unnecessary if everyone reported completely – all reporters would be in the complete category, which allowed 1 month omission.There is numerical mismatch between size-based and “people detained”-based estimates among some null reporters, above a certain estimated level of restraint/size/people detained. It may be explained by those factors which interact with size, characteristics such as patient age, neurodiversity; or, more speculatively saturation of restraint and/or reporting, both of which depend on finite resources. We cannot know until reports are complete, per person, per month, along with ethnic and other features, as the law will require soon. Corrections such as those suggested by Janssen rely on complete data for the corrective factors, and we look to a day when we can make them in England.post hoc. That retrospective check particularly looked for issues with MHA reporting. This may entail bias. That is our own main methodological concern.The exclusion of an outlying null-reporting trust, helped our very high (0.95) correlation of size and people detained estimates. It required checking a null reporting outlier's CQC report If “people restrained” per month is imperfectly reported, “number of restraints” may be worse. Anecdotally, institutional definitions of restraint vary, especially for “prone”. Numerous varying exceptions are rumoured. We predict and recommend that regulators should acknowledge varying definitions, and ask patients (detained or not) if they have been people restrained in a month.Seni Lewis whose death in restraint led to the Mental Health Units Use of Force Act had a Master's degree in Information Technology and Management. As a theoretical extension, the first author developed a measure “L” to quantify disinformation added by low or null reports using bits. It is named for the scatter graph shape and after “Lewis”, with the family's kind permission . As with


The phyllosilicates, zeolites, and sulfates analyzed in this study contain between 0 and 99,120 ppm N and have δ15Nair values of −34‰ to +65‰. Most of these minerals, and the few siliceous hydrothermal deposits that were analyzed, have δ15N consistent with the incorporation of biologically processed N during low-temperature hydrothermal or weathering processes. Secondary ion mass spectrometry on altered hyaloclastites demonstrates the residency of N in smectites and zeolites, and silica. We suggest that geological materials known on Earth to incorporate and store N and known to be abundant at, or near, the surface of Mars should be considered targets for upcoming Mars sample return with the intent to identify any signs of ancient or modern life.We measured the N concentrations and isotopic compositions of 44 samples of terrestrial potassic and micro- and meso-porous minerals and a small number of whole-rocks to determine the extent to which N is incorporated and stored during weathering and low-temperature hydrothermal alteration in Mars surface/near-surface environments. The selection of these minerals and other materials was partly guided by the study of altered volcanic glass from Antarctica and Iceland, in which the incorporation of N as NH The specific minerals and other phases that could house various N-bearing species and potentially preserve biogeochemical records have remained uncertain  are typical of basalt weathering and common, but more locally dominant Al-phyllosilicates  , jarosite (hydrated K sulfates), and apophyllite (in which K+ and NH4+ can reside), were considered for the first time, in the present study, with regard to their N concentrations and isotope compositions.In this framework, this study constitutes an in-depth survey of the N retentivity in various Mars-analog phases and minerals. The results serve to build a data base for understanding the potential of these materials to preserve biogeochemical and environmental processes and records on planets and, here, Mars. Some of these phases, particularly the zeolites, Fe-rich smectite , for which many studies have documented elevated N concentrations  was then transferred into a Finnigan Gas Bench II continuous-flow interface where it was entrained in a He stream and conveyed into a Finnigan MAT 252 isotope ratio mass spectrometer. The N isotope compositions are reported in conventional delta notation (Eq. 1) as per mil (‰) with respect to terrestrial atmospheric N2 (and reported as δ15Nair) where:The tubes were then evacuated for 24 h on a glass vacuum line, with intermittent heating to ∼100°C to remove adsorbed atmospheric N. They were then sealed under vacuum and heated to 1050 °C in a programmable muffle furnace. Tubes were cracked onto the high vacuum metal extraction line, and cryogenically purified molecular N (Nx regent (reagent blanks) were regularly analyzed during analytical runs to monitor the contribution of the combustion reagent and the extraction vacuum system to measured N2. To determine N concentrations, measured N peak area was interpolated to an internal silicate standard-calibrated relationship between N peak area and N concentrations. Nitrogen concentrations are reported as ppm (μg/g). The analytical uncertainties for N concentrations are usually <5%. Uncertainties for δ15N values are 0.15‰ (1σ) for samples with >5 μg/g N, and 0.6‰ (1σ) for samples with 1–5 μg/g N.Sealed tubes containing only the Cu/CuO2.3.12C-, 13C-, 12C14N, 12C15N, 28Si- and 35Cl- was conducted on palagonitized volcanic glass via secondary ion mass spectrometry (SIMS) using a Cameca IMS1280-HR at the Pheasant Memorial Laboratory, Institute for Planetary Materials, Japan. Polished 2.5 cm round thin sections were Au-coated (200 nm) with a JEOL JFC-1500 ion sputtering device. A primary Cs+ beam impacted the sample surface at −20 keV. For mapping of 80 × 80 μm areas, the primary beam current was set to 3 pA with a 1 nA 180 s pre-sputtering (100 μm2) and 30 s automatic mass calibration period. A contrast aperture of 400 μm was used, and the energy band pass width was also set to −10 to 40 eV. The entrance and exit slit widths were set to 50 and 150 μm, respectively. The resultant mass resolution (m/Δm) of ∼8000 could separate interferences of 12CH− and 13C14N−. Each run consisted of three to four cycles.To demonstrate the residency of N (and C) in many of the phases studied here, mapping of X-ray mapping of the major elements was conducted by an electron probe microanalyzer in wavelength-dispersive mode with a JEOL JXA-8800 and a JEOL JXA-8530F, and both were also housed at the Pheasant Memorial Laboratory, Institute for Planetary Materials, Okayama University, Japan. The mapping was performed at modified conditions using 15 kV accelerating voltage, working distance of 11 mm, 200-nA probe currents, and 10–20 ms dwell time per 1–3-μm pixel, depending on the target dimension. Natural silicates and synthetic oxides on ASTIMEX MINM25–53 were used as standards.3.3.1.15N, from −34.0‰ to +65.4‰. The phyllosilicates show the widest range in N concentration from 17 to 99,120 ppm  followed by the zeolites with 0.5 to 4827 ppm, sulfates with 59 to 3460 ppm, and lastly silica with 48 to 62 ppm (δ15N = −1.4‰ to +2.1‰). The highest N concentration is from a 2:1 layer clay mineral, whereas the lowest concentrations (<0.1–0 ppm) are from the apophyllite samples and two zeolites, heulandite (8fl2–003), and mesolite (M-1).The measured N concentrations and isotopic compositions of the various minerals and phases are presented in 15N values are for the smectite clay saponite (sample 111976) and the zeolite scolecite (sample 8f8–22), respectively. Smectite clays  have 19–172 ppm N and δ15N of −34‰ to −17.2‰. Similarly, two of the halloysites have N concentrations of 106 ppm and 540 ppm and δ15N values of −17.5‰ and −19.6‰. Illite (sample 84754) and fluorapophyllite (sample RC-298) have the most positive δ15N values of the phyllosilicates .The phyllosilicate, zeolite, and sulfate groups have at least one specimen with N concentrations >1000 ppm. The most negative and the most positive δi.e., δ15Nair = 0 ± 2‰). Out of 38 samples with measurable quantities of N, 17 have δ15N values similar to that of organic matter in sediments . Zeolites and apophyllite do not contain appreciable 12C- or 13C-, whereas smectite does show elevated concentrations.The color scales depicted in the SIMS maps represent total ion yield intensity concentrations with warmer and cooler colors plotted using a jet-color scale that corresponds to higher and lower concentrations, respectively. The highest and lowest concentrations in each image are scaled differently, and therefore, the same colors in different maps do not represent the same concentrations of the different elements shown. The K-bearing phases such as heulandite-clinoptilolite, which are expected to contain N as NHf 12C14N , with sotrations . General12C14N concentrations in some palagonites, infilling clays in dissolution channels, pits, vesicles, and zeolite cements. Where multiple layers of clay coatings/cement are visible, for example in vesicles, a difference in N is observed among these layers , perhaps indicating direct uptake or occlusion  with only modest amounts of isotopic fractionation. A fourth sample from Mount St. Helens that consists of cristobalite, but also glass and plagioclase, has a far lower N concentration of 0.7 ppm and much lower δ15N of −15.4‰.Three samples of amorphous siliceous materials  yielded similar N concentrations and δectively ; Fig. 1.4.15N , and as demonstrated by Busigny and Bebout , these fractionations can be large at lower temperatures . The measurements of whole rock altered hyaloclastites by Nikitczuk et al., . In aggregate, the minerals analyzed in this study , four of which contained no N, three of halloysite , three kaolinite varieties , three chabazites , and three heulandites .Among the samples investigated in this study, significant differences in the range of N concentrations and isotope compositions were observed and notably among different specimens of the same mineral types . These iet al. , the whole-rock and 4+  supports this conclusion  and be redistributed from different sources under various conditions such as in fluids of alteration processes through degassing of uprising magmas, meteoric-sourced surface waters, or leaching from crustal weathering or sediments. Nitrogen incorporation in addition to fixation in lattices may, thus, occur by occlusion/trapping within structural cavities during formation or by direct adsorption onto charged surfaces or exchange with cations after formation.Many phases are typically both potassic  and/or me.g., Cs+, NH4+ and Sr2+) selectivity. Also, smectites can swell/expand upon hydration and influence interlayer spacing. Volatile gaseous and solution species  within the surrounding environments may, therefore, be readily exchanged with sorbed charged species. The adsorption of N2 or exchange of NH4+ and other cations from solution has been well documented in clinoptilolite, for example .Porous zeolite structures and interlamellar smectite clay surfaces have significant ion-exchange/adsorption capacities, whereas zeolites also have molecular sieve properties with cation  in addition to other guest molecules, such as H2O, CO2, CH4, hydrocarbons, and some organic matter, can be enclathrated or occluded within the structural cavities of their crystal lattices  conditions or hydrothermal circulation may have existed, at least sporadically, later in Mars' history  have shown that dinitrogen can be biologically fixed at 5–780 mb. Such pressures could potentially be lower than on primordial Mars  that increase with increasing pressures and temperatures  relative to the modern Mars atmosphere has been reported, which supports the N-loss hypothesis.Loss of isotopically fractionated N over time may be responsible for Mars' low atmospheric Net al., 15Nair = 0 ± 2‰) with only a few exceptions , if it, indeed, occurred.Consider that the whole N dataset of Mars surface/subsurface-analog minerals (this study) and altered hyaloclastites  shows similar N incorporation and positive δ15N shifts but preserved on time scales of billions of years organic isotopic information requires selecting ancient targets that are as “fresh” as possible from locations with the highest erosion/exposure rates (youngest exposure ages) and that were shielded from highly ionizing galactic and solar cosmic radiation . Therefore, obtaining ancient, cosmic-ray-shielded, recently exposed, N-bearing minerals may provide such a Mars standard. Such data are even more useful when combined with other isotope systems such as C, with the latter also closely linked to terrestrial biogeochemical cycling  may have formed deep in Mars' past and, along with other phases, continued to form at various geologic points in time, nitrogenous materials may provide a unique potential in preserving planetary N records that are valuable to sample-return science goals. Variably altered basaltic glasses are enriched in N relative to MORB or OIB but show a wide range of concentrations and isotopic compositions, many of which overlap δ15N values of sedimentary/organic components. This enrichment is indicative of processes beyond magmatic degassing that includes supply during low-temperature to hydrothermal alteration. Silicate N is commonly fixed as NH4+ replacing K+, as indicated by relationships between N and alkali/LILE cations , or N2 within structural cavities or interlayer surfaces.Given that some phases on Mars such as certain phyllosilicates .e.g., 40Ar/36Ar, 4He/40Ar, 13C/12C) or water chemistry and temperature effects .Future contributions to this work should consider (1) major and trace element compositions of the minerals, (2) analysis of local sedimentary materials and environmental parameters such as water chemistry and temperature contributing to the alteration of specific glasses/basalts, (3) delineating the specific forms of N present including organic molecules, and (4) combining other isotope systems with N to evaluate magmatic and organic source contributions (


With high morbidity and mortality, colon cancer (CC) is considered as one of the most often diagnosed cancers around the world. M7G-related lncRNA may provide a regulatory function in the formation of CC, but the principle of regulation is still unclear. The purpose of this research was to establish a novel signature that may be used to predict survival and tumour immunity in CC patients. Data about CC in TCGA was collected for analysis, coexpression analysis and univariate Cox analysis were used to screen prognostic m7G-related lncRNAs. A consensus clustering analysis based on prognostic m7G-related lncRNAs was applied, and a prognosis model based on least absolute shrinkage and selection operator (LASSO) regression analysis was established. Independent prognostic analysis, nomogram, PCA, clinicopathological correlation analysis, TMB, survival analysis, immune correlation analysis, qRT–PCR and clinical therapeutic compound prediction were also applied. 90 prognostic m7G-related lncRNAs were found, GO and KEGG analysis showed that prognostic m7G-related lncRNAs were mainly related to cell transcription and translation. The results of the consensus clustering analysis revealed substantial disparities in survival prognosis and tumour immune infiltration between two clusters. We built a risk model with 21 signature m7G-related lncRNAs, patients in the high-risk group had a considerably poorer prognosis than those in the low-risk group. Independent prognostic analysis confirmed that patients’ prognosis was linked to their tumour stage and risk score. PCA, subgroups with distinct clinicopathological characteristics were studied for survival, multi-index ROC curve, c-index curve, the survival analysis of TMB, and model comparison tested the reliability of risk model. A tumour immunoassay revealed a substantial difference in immune infiltration between high-risk and low-risk individuals. Five chemicals were eliminated, and qRT–PCR indicated that the four lncRNAs were expressed differently. Overall, m7G-related lncRNA is closely related to colon cancer and the 21 signature lncRNAs risk model can efficiently evaluate the prognosis of CC patients, which has a possible positive consequence for the future diagnosis and therapy of CC. Colon cancer (CC) is one of the most prevalent diagnosed tumours worldwide, with the third-highest incidence of occurrence (10%) among all cancers, trailing only lung cancer (11.4%) and breast cancer (11.7%) . After lvia the mediation of T reg cell differentiation (Noncoding transcripts of more than 200 nucleotides are known as long noncoding RNAs (lncRNAs) . In prevntiation . The aboNevertheless, the mechanisms of regulating the expression of lncRNAs are largely unclear. Recent studies have suggested that there is a close relationship between the expression of lncRNAs and RNA methylation . This prIn this study, we screened the m7G-related lncRNAs found in CC based on the Cancer Genome Atlas (TCGA) database and constructed an m7G-related prognostic lncRNA model. The purpose was to probe the correlation between m7G-related lncRNAs and CC through bioinformatics analysis and a few experiments.http://www.gsea-msigdb.org/gsea/login.jsp)  was used to acquire RNA sequencing (RNA-seq) data and clinical characteristics (Genes related to m7G were obtained prior reviews  and GSEAgin.jsp) , and generistics  on 10 Jaeristics  values.p < 0.001 were the criteria for filtering using Pearson’s correlation analysis. The “survival” package was used to select prognostic m7G-related lncRNAs with p < 0.05 using univariate Cox regression analysis  and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, prognostic m7G-related lncRNAs were chosen. GO analysis includes three parts: molecular function (MF), biological process (BP), and cellular component (CC). The “org.Hs.eg.db,” “clusterProfiler,” “ggplot2” and “enrichplot” packages were used for GO analysis and KEGG analyses, and a bubble chart was drawn. The criteria were FDR <0.05 or For consensus clustering, prognostic m7G-related lncRNAs were chosen , and thep < 0.05, ∗∗ if p < 0.01, and ∗∗∗ if p < 0.001.We probed the differences in the expression of immune cells and immune checkpoints among subgroups. The CIBERSORT algorithm was used for immune scoring, and the differences between clusters were evaluated. The packages “limma,” “estimate,” “reshape2,” “ggplot2,” “ggpubr,” and “vioplot” were used for these analyses. The degree of difference was noted: ∗ if We employed TCGA expression data files and clinical data files to investigate the predictive utility of prognostic m7G-related lncRNAs for clinical prognosis. Least absolute shrinkage and selection operator (LASSO) regression analysis  {risk scAfter constructing the risk model, we researched the survival risk of the two groups. Survival curves, receiver operating characteristic (ROC) curves , heatmapWe researched all of the tumour samples’ clinical features. In a Cox regression-based univariate and multivariate independent prognostic analysis, the “survival” package was used to determine whether clinical characteristics  and risk score could be utilized as independent prognostic variables. A nomogram  was usedThe total gene expression profile, m7G-related genes, m7G-related lncRNAs, and risk model lncRNAs were all subjected to principal component analysis (PCA) to reduce dimensionality, identify the model, and show the high-dimensional data. We used the “limma” and “scatterplot3d” packages to perform this process. Expression levels and survival analysis of different clinicopathological characteristic subgroups were produced using the “ggpubr” and “limma” packages. This analysis is useful in confirming the accuracy of our risk model.Tumour mutational burden (TMB) reflects the frequency of gene mutations in tumour tissue and is assumed to be related to tumour immunity. To display the TMB results of patients in the high-risk and low-risk groups, we analysed the difference and survival of TMB between the high- and low-risk groups in TCGA. The “maftools,” “limma,” “ggpubr,” “survival,” and “survminer” packages were utilized.We drew multi-index ROC curves and concordance index curves (C-index curve) in all tumour samples to examine the model’s efficacy . The “dplyr,” “survival,” “rms,” “pec,” “survminer,” and “timeROC” packages were implemented for this analysis. At the same time, we selected two published articles that constructed the lncRNA risk model in colon cancer to compare with our model. We compare the ROC values between these models and draw the relevant AUC curves. The terms “limma,” “survival,” “survminer,” and “timeROC” were utilized for this comparison. Of note, this comparison used the AUC values of all samples and they were not divided into training group samples or testing group samples.p < 0.05, ∗∗ if p < 0.01, and ∗∗∗ if p < 0.001.The CIBERSORT algorithm was utilized in this study to investigate the relationship between the risk score and immune cells/function. The “reshape2,” “ggpubr,” and “limma” packages were applied for immune cell analysis; the “GSEABase,” “limma,” “GSVA,” “reshape2,” and “ggpubr” packages were applied for immune function analysis, and the relevant boxplots and the bar chart were drawn to present the results more clearly. According to the median of the levels of immune cell enrichment or immune function in all patients, the samples were separated into two groups: those with high immune cell/function and those with low immune cell/function. We analysed the survival differences between the high and low cell/function groups. The “survminer,” “survival,” and “limma” packages were implemented. The degree of difference was noted: ∗ if https://www.cancerrxgene.org/) to predict probable compounds that may be employed in CC treatment. The “pRRophetic,” “limma,” “ggpubr,” and “ggplot2” packages were used to predict the chemicals that may be employed for CC treatment.We evaluated the IC50 values of the compounds retrieved from the GDSC website . For reverse transcription, the EasyScript One-Step gDNA Removal and cDNA Synthesis SuperMix  and T100 Thermal Cycler  were employed. Quantitative real-time polymerase chain reaction (qRT–PCR) was performed using PerfectStart Green qPCR SuperMix  and CFX Connect Optics Module . All experimental procedures were carried out following the product manual’s instructions. Considering that the expression of many risk lncRNAs was very low, we chose four lncRNAs that were relatively easy to obtain results for qRT–PCR verification.For PCR amplification, the primer sequences were as follows:NIFK-AS1, forward: 5′-TTGGGTCTTCGAAAGTGCTG-3′,reverse: 5′-ACGCTCCAAAACACTTTCCG-3’;RNF216P1, forward: 5′-GGCCAGCCAAGATGAGACAA-3′,reverse: 5′-TCAGCAGCTTGGATGAAGCA-3’;ZEB1-AS1, forward: 5′-GGTTTCCTTCCTGCTTCCCA-3′,reverse: 5′-ACTCCGGTCACGTTTCAGTT-3’;ZKSCAN2-DT, forward: 5′-TCTGGCGGAAGTATCTGTGC-3′,reverse: 5′-AGCACCAGAAGAGAGCAAGC-3’;GAPDH, forward: 5′-CCCACTCCTCCACCTTTGAC-3′,reverse: 5′-CCACCACCCTGTTGCTGTAG-3’;p < 0.05, ∗∗ if p < 0.01, and ∗∗∗ if p < 0.001.GAPDH was utilized as an internal control and each sample was reproduced three times. The relative expression levels were determined using the 2-ΔΔCt method. T-tests were used to compare the expression of NIFK-AS1, RNF216PA, ZEB1-AS1, and ZKSCAN2-DT (mean ± SEM). The graphs were made with GraphPad Prism (version 8.0.2). The degree of difference was noted: ∗ if t-test. The chi-square test was used to compare the categorization variables in the training and testing tests. The Pearson correlation test was used to analyse the relationship between subtypes, clinicopathological variables, risk score, immunological check inhibitors, and immune infiltration levels. For survival analysis, the Kaplan–Meier technique was used, along with a two-sided log-rank test.R software (version 4.1.0) was used for statistical analysis and result visualization. The differential expression was authenticated using the Benjamini–Hochberg technique. The mRNA levels of pyroptosis-related lncRNAs were determined using the Mann–Whitney U test. The differences between the two groups were determined using student’s p < 0.001)  . Followi< 0.001) : ZKSCAN2We performed GO and KEGG analyses of m7G-related lncRNAs. GO analysis included CC and MF of BP, and the significant correlations of lncRNAs were analysed at the cellular constituent, molecular function, and biochemical pathway levels in GO analysis. The obtained results revealed that m7G-related lncRNAs were primarily related to a change in the transcription and translation processes in cellular constituents, the function of m7G and the translation process in molecular function, and protein translation and nucleotide metabolism in biological processes . KEGG anThe correlation between 90 prognostic m7G-related lncRNA expression levels and subgroups in all CC samples was investigated using consensus cluster analysis. From the figure of increasing the clustering variable (k) from 2 to 9, there were the highest intragroup correlations and the lowest intergroup correlations when the clustering variable (k) was set to 2. . The surAll tumour samples were randomly divided into training and testing groups in a 7:3 ratio. We established a LASSO regression model and selected 21 lncRNAs  as signature factors from 90 prognostic m7G-related lncRNAs . The folRegardless of whether the patients were in the training or testing groups, the survival analysis revealed that the survival probability of patients in the low-risk group was greater than that of patients in the high-risk group, and there was a statistically significant difference. . The AUCWe constructed a nomogram to predict the prognosis of individual patients with CC , and theWe discussed the association between the CC risk score and survival. The Kaplan-Meier curve for OS was generated in different clinicopathological characteristic subgroups to demonstrate the difference. Overall, patients in the low-risk group had a considerably greater survival rate than those in the high-risk group . The surTMB represents the mutation rate of genes in the coding area, which is correlated with tumour formation and progression. Based on the TMB score produced from the somatic mutation data of TGCA, our study revealed that the TMB of the high-risk group was greater than that of the low-risk group . The AUCWe created a concordance index curve and a multi-index ROC curve to validate the credibility of the risk model developed in our study. By comparing the AUC values among the various indicators , we discovered that the AUC value of the risk score was the highest, at 0.809, followed by stage at 0.705, age at 0.609, and gender at 0.477 . We selep < 0.05. The obtained result, where significant difference existed in the proportion of both resting dendritic cells and eosinophils between the two risk groups, indicated that the risk score was clearly correlated with resting dendritic cells and eosinophils  in the low- and high-risk groups differed considerably in the prediction of prospective chemical drugs for the treatment of colon cancer . The senFour m7G-related lncRNAs  were chosen. NCM460, HT29, and SW620 cells were used to examine these lncRNAs. The expression levels of these lncRNAs changed dramatically between tumour and normal cell lines, according to experimental evidence . This revia the PARP-AS1/miR-125a-5p axis (Colon cancer (CC) is one of the most lethal human tumours. Over the past few years, with the progress of diagnosis and treatment technology, the total incidence of colon cancer has gradually decreased. However, the incidence of colon cancer among young patients is on the rise , and it -5p axis . Cen inv-5p axis . Profess-5p axis . ProgresRNA methylation governs practically all aspects of RNA processing, and it is crucial in controlling gene expression, mRNA stability, and homeostasis. 7-Methylguanosine (m7G) RNA methylation is a recently identified type of RNA methylation that is expected to have a key function in malignancies . OrellanWe obtained the expression data files and clinical data files for CC from the TCGA database for this study, and 29 genes associated with m7G were gathered from the published literature and GSEA website. Coexpression and univariate Cox analysis were used to identify 90 prognostic m7G-related lncRNAs. We subsequently conducted GO and KEGG analyses, which showed that m7G-related lncRNAs are mainly related to cell transcription and translation. Two subgroups were identified by consensus cluster analysis, and the survival analysis revealed disparities in survival between the two groupings. The difference between the two clusters was validated by immunological score, immune checkpoint expression level, and immune cell analysis. Cluster 2 showed a greater amount of immune checkpoint expression and a higher immunological score, and its prognosis was much better than that of Cluster 1. These findings suggested that consensus clustering is associated with patient prognosis and may be correlated which the immunological microenvironment. To forecast the prognosis of CC patients, we established a risk model with 21 signature m7G-related lncRNAs  by LASSO regression. The risk model is remarkably dependable and related to the prognosis of CC patients, according to ROC curves, Kaplan-Meier curves, and risk curves. PCA, independent prognostic analysis, survival analysis of subgroups with differing clinicopathological characteristics, multi-index ROC curve, survival analysis of TMB, c-index curve, and model comparison again tested the reliability of our model. Immune cell/function analysis showed that m7G-related lncRNAs may be related to tumour immunity. The significant difference in the ratio of resting dendritic cells and eosinophils between the two risk groups may be helpful according to Grisaru-Tal’s and Wooster’s research. The noteworthy difference of resting dendritic cells and eosinophils in distinct risk groups may possess the potential to direct CC therapy in the future . FurtherIn published research, the lncRNA ZEB1-AS1 was considered to be tightly related to the onset and progression of many types of cancers. According to Jin’s research, the positive reciprocal looping of HIF-1/ZEB1-AS1/ZEB1/HDAC1 leads to hypoxia-induced oncogenicity and PC metastasis . Siena cThere are also some shortcomings in this research. First, our data source is relatively singlar, and there is a lack of more external data verification. This is mainly due to the lack of datasets with complete lncRNA sequencing data, such as TCGA databases. Second, we lack additional molecular biology experiments to verify our results. These problems are also the direction that we need to work on next.In this study, we investigated the usefulness of m7G-related lncRNAs in predicting survival, the involvement of the tumour microenvironment and immune cell infiltration, the prospective regulation mechanism of m7G-associated lncRNAs, and the prediction of suitable drugs for the treatment of CC. 21 lncRNA characteristics related with m7G may predict CC patient survival and may be beneficial for customized cancer therapy in the future.