Our results show excellent agreement between the CSP landscapesand experimentally reported structures. By analyzing the packing motifswithin the polymorph landscapes, we begin to develop an understandingof how helicene length affects the shape and π–πstacking interactions seen in the polymorphs. Furthermore, we proposehow helicene length can be used as a tool to design new functionalorganic electronics.Chiral π-conjugatedorganic molecules hold potentialforemerging technologies as they are capable of introducing novel functionalitiesinto electronic devices owing to their strong chiroptical properties.However, capitalizing on chiral molecules for electronic devices isreliant on their molecular packing—a factor that impacts theircharge-transport properties. The solid-state behavior of moleculesis sensitive to subtle differences in molecular interactions, chirality,and shape, but these relationships are not fully understood. Here,we employ crystal structure prediction (CSP) as a tool to probe thelattice-energy landscape for a family of chiral organic molecules:[ Chiral π-conjugatedorganic molecules hold potentialfor emerging technologies as they are capable of introducing novelfunctionalities into electronic devices owing to their strong chiropticalproperties. Different crystalline structures, sometimesonly with marginal changes to the crystal packing, can have considerablydifferent properties,11 and consequentlypolymorphism can be used as a design strategy for high-performanceorganic electronics.9Organic semiconductors (OSCs) are low-cost,environmentally friendlyalternatives to inorganic semiconductors. With their potential tousher in a new era of sustainable technologies, they are being exploredextensively in a diverse variety of applications.12 chiroptical switches,15 and room-temperaturespintronic devices.16 Carbo[n]helicenes (referred to throughout this work as [n]helicenes) form a family of archetypal chiral π-conjugatedorganic molecules that are formed from ortho-fused, angularly arrangedbenzene rings, where n is the number of aromaticrings in the molecule. Helicenes are promising compounds for designingnew organic electronic technologies due to their large chiropticalresponse, charge-transport properties, and their ability to filterelectron spin at room temperature.20 Chirality adds another levelof complexity to solid-state formation, as chiral compounds can formboth enantiopure and racemic crystals with very different electrontransport properties. For example, aza[6]helicene has an 80-fold increasein hole mobility in the racemate structure compared to the enantiopurestructure.19Introducingchirality into OSCs adds another level of functionalityas it enables the production of polarization-selective photodetectors,22 CSP of helicenes in our own workhas helped predict the thin-film packings of enantiopure and racemicaza[6]helicene, explaining 80-fold differences in charge mobility.19 Combining CSP with the prediction of optoelectronicproperties can be used to develop energy–structure–function(ESF) maps.25 We have used this framework to explore the ESF of[6]helicene using CSP.26 This work highlightedspecific structural motifs that were particularly beneficial for eitherhigh electron or hole mobility. In an effort to enhance our understandingof the interplay between molecular structure and optoelectronic properties,we have investigated the impact of altering the nitrogen atom’sposition within aza[6]helicene, while maintaining identical crystalpacking.27 Our findings show that the positionof nitrogen can be crucial in determining the semiconducting propertiesof the material. Using this prior knowledge of how changes in thefunctional group position and molecular assembly separately affectthe charge-carrier mobilities, we screened over 1300 substituted [6]helicenesfor high charge mobility.28 This approachshows promise in guiding the design of new OSC molecular materialsand identified fluorinated [6]helicenes as being the most promisingto maximize the OSC performance metrics. However, it is difficultto outperform unsubstituted helicenes in terms of their high chargemobility.Despite the interestin helicenes, their application in electronicdevices remains in its infancy, partly due to a poor understandingof molecular packing and how it impacts performance. Much of our ownwork has looked to bridge this gap using crystal structure prediction(CSP) as a means to develop our understanding of structural motifsthat enhance optoelectronic properties. CSP is particularly usefulfor these molecules due to the inherent rigidity of the structures.In fact, both naphthalene and benzene are used for testing and benchmarkingCSP protocols.n, in [n]helicene on the molecules’ crystalpacking behavior and intermolecular interactions. Using the CSP landscapesof naphthalene and [3]–[12]helicene were geometry optimized using Gaussian 1629 at the B3LYP30/6-31G level of theory,with tight convergence criteria and assuming no symmetry. Based onthe optimized geometry, the charges were computed from the electrostaticpotentials using a grid-based method (ChelpG).31 The CrystalPredictor II33 software packagewas used to generate hypothetical crystal structures within a polymorphicregion spanning an energy range of up to 20 kJ mol–1 above the global minimum using pairwise potential parameters. Here,the molecules were treated as rigid, and the search was restrictedto only one molecule in the asymmetric unit (Z′= 1) to limit the computational expense. Although limiting the searchspace to Z′ = 1 may lead to an under predictionof experimentally realized structures, extending the search to Z′ = 2 is likely to just produce closely relatedand duplicated structures of those found in the Z′ = 1 landscape. Moreover, the Z′= 1 CSP search can provide many insights about the possible crystalpackings of the molecule, which was our primary aim of this study.34 Next, 500,000 crystal minimizations were performedacross the following space groups: P1, P1̅, P21, P21/c, P21212, P212121, Pna21, Pca21, Pbca, Pbcn, C2/c, Cc, C2, Pc, Cm, P21/m, C2/m, P2/c, C2221, Pmn21, Cmc21, Aba2, Fdd2, Iba2, Pnna, Pccn, Pbcm, Pnnm, Pmmn, Pnma, Cmcm, Cmca, Fddd, Ibam, P41, P43, I4̅, P4/n, P42/n, I4/m, I41/a, P41212, P43212, P4̅21c, I4̅2d, P31, P32, R3, P3̅, R3̅, P3121, P3221, R3̅c, R3c, P61, P63, P63/m, P213, Pa3̅, P2221, and Pba2. All space groups were then searched in proportion according totheir relative abundance in the CSD,32 andall the stable crystal structures were clustered to remove duplicatesusing the CCDC COMPACK35 module.The naphthalene and helicene compounds takenfrom the Cambridge Structural Database (CSD) in cases where a matchingcrystal structure was not generated by the quasi-random search. Thesewere enantiopure structures of [7]helicene and [9]helicene (IMEJIWwith Z′ = 2 and QUJNEQ with Z′ = 3) and racemic structures of [5]helicene (DBPHEN03 with Z′ = 2 and DBPHEN04 with Z′= 3). For the intergrowth structure of [6]helicene, the crystal structurewas taken from ref . For each dimer, the CRYSTACK module computes allmolecule–molecule interactions.The crystal packing analysiswas performed using CRYSTACK, an open-sourced python module The focus is on π–πinteractions due to their relevance to organic semiconducting devices.For each crystal in the 11 CSP landscapes, we calculated the extentof parallel π–π stacking interactions for eachmolecule expressed as a percentage per molecule. Aromatic rings withinthe molecule were only considered to be π-stacked if the intermoleculardistance between the center of the benzene rings did not exceed 5.5Å, the angle between the benzene rings was within 0–30°,and the displacement between the centroids of the two benzene ringsparallel to the plane of the rings was less than 2.0 Å.n]helicenes with n = 3–7 and 9–11 havebeen synthesized60 with more than one polymorph obtained for [5]helicene52 and [7]helicene.56 With the exception of [3]helicene,X-ray crystal structures were deposited to the CSD, which we usedto compare with the structures within our CSP landscapes. We foundthat the CSP landscapes , the experimental structurewas either an intergrowth  or possessed a higher number of molecules inthe asymmetric unit. For example, [5]helicene has two polymorphs (DBPHEN03and DBPHEN04) where Z′ = 2 and 3, respectively,[7]helicene has one polymorph (IMEJIW) where Z′= 2, and [9]helicene has one polymorph where Z′= 3 (QUJNEQ). By construction of our approach, polymorphs with Z′ > 1 could not be found here as CSP searcheswithare significantly more computationally expensive. Calculating theenergies of these experimental structures and including them in ourCSP landscapes lead to the correct assignment of the experimentalstructure as the lowest energy structure , our B86bPBE-XDM calculations correctly identifiedthe structure as the lowest energy Z′ = 1polymorph within the landscape (Section S1) (Section S2). The onlycase where an experimentally realized Z′ =1 polymorph was not produced in the generation of crystal structuresis for [5]helicene, where the racemic DBPHEN02 is missing. However,another synthesized Z′ = 1 racemic polymorph,DBPHEN05, is predicted and is lower in energy than DBPHEN02.If a tion S1) 2. DuetoZ′ = 1 that are lower in energy than the experimental Z′ = 1 polymorph. This is because the lower energypolymorphs are racemic, whereas the experimentally realized crystalstructure is enantiopure. Although the activation energy barrier toenantiomer interconversion for [4]helicene is small at ≈17kJ mol–1,62 the racemicstructure is only 1.66 kJ mol–1 lower in energythan the enantiopure structure; thus, the racemic structure is unlikelyto form from an enantiopure solution, which we presume was used tocrystallize [4]helicene,60 resulting inthe crystallization of the enantiopure polymorph. We would expectthat if [4]helicene were to be synthesized from a racemic mixture,then the lowest energy polymorph predicted in the landscape wouldform. Although it has been reported that [4]helicene forms a conglomeratecrystal,64 we were (a) not able to access the crystalstructure and (b) check the synthesis route for solvent effects asref ,65 and its formation may be favored due to kinetic reasons. The enantiopure Z′ = 1 structure has not been realized experimentally,likely due to the global minimum corresponding to the enantiopureexperimental polymorph (Z′ = 2), which isthermodynamically favored.For [7]helicene, only one 69 The formation of conglomeratesindicates that the enantiopure polymorph is more energetically stablethan racemic crystal structures that might otherwise form from a racemicmixture. Conglomerate formation for [6], [7], and [9]helicene is consistentwith our results as it confirms that enantiopure polymorphs are morestable than racemic polymorphs, as seen in our landscape. However,it is inconsistent with our predictions for [4], [5], and [8]helicene,where our CSP landscape predicts a racemic polymorph to be lower inenergy than enantiopure polymorphs. The observation of these conglomeratecrystals does not necessarily contradict our results as other factors,such as solvation effects, may affect crystal formation. For instance,the conglomerate structures of [5] and [8]helicene were observed whencrystallizing from a solution of ethanol, and benzene and iodine,respectively. Additionally, the formation of stable racemic crystalsof [5]helicene further implies that factors such as kinetics or solvationmight play a role in the formation of the conglomerate structure asracemic polymorphs should not be accessible if an enantiopure crystalstructure is lower in energy. The paper referring to [4]helicene conglomeratesdoes not reference the synthesis route and so we are unable to offersimilar comparisons.64As well as the crystal structuresreported in the literature discussedabove, conglomerate crystals have been reported to form for [4]–[9]helicene.n > 8, this packing behavior changes, and there is less interlockingbetween neighboring helicenes.Given the correlation between low-energystructures in the CSP landscapes and their experimental counterparts,we analyzed the packing motifs in the lowest-energy polymorphs forboth enantiopure and racemic structures for naphthalene and [3]–[12]heliceneto look for similarities between the packing behavior of the polymorphswith different number of aromatic rings 3. For thn = 3, 5 and adjacenttranslational chains are seen in naphthalene and [6]helicene. Thepolymorph of [4]helicene is very similar to the enantiopure [5]helicene.[7]helicene is the only molecule that contains motifs similar to theinterlocked enantiopure helicenes as the helicenes pack in the sameback-to-back manner, whereas [8], [9], and [10]helicene have similarpacking behavior to each of their enantiopure counterparts.The racemic structures show morevariation in packing behavior, where interlocked chains are not formedin any of the low-energy polymorphs. Instead a herringbone-type packingis seen in structures where 2 V–1 s–1 in [6]helicene.26 For [11]helicene, the racemic structure is substantiallyhigher in energy than the global minimum enantiopure structure (abovethe polymorphic window) and so is unlikely to form. However, the racemicpolymorph of [12]helicene is the global minimum, and so perhaps asolid form of [12]helicene may exhibit a similar high hole mobilityas calculated for the [6]helicene polymorphs, making it a good candidatefor charge mobility testing.The packing motifs change for [11] and [12]helicene where thereare π-stacked chains of alternating enantiomers 4. These 71 Consequently, this reduces the configurational space of feasiblesolid-state formations.From the CSP search ofnaphthalene and [3]-[12]helicenes,the numberof stable polymorphs obtained decreases with increasing helicene length5. This pn = 4, but becomes increasingly helical on increasing n, thereby disrupting some of the stable interactions and thus polymorphsavailable to (quasi-)flat aromatic compounds. The change in shapeof the helicenes with changing number of aromatic rings can be quantifiedby the change in angle between the terminal aromatic rings, as shownin n increases from 10 to 12, againlikely due to the disruption of stable interactions when increasingthe angle between the terminal rings. When the angle between the terminalrings is small, such as when n = 9, the moleculefills a more uniform space, leading to a larger number of similarpacking motifs being energetically accessible. Conversely, the packingfor helicenes with larger angles between terminal rings, such as [6]and [12]helicene, results in relatively fewer polymorphs. Interestingly,the proportion of enantiopure structures in the landscapes is highestfor n = 6 and n = 12, implying thatlarge angles between terminal rings, and thus nonuniform shapes, stabilizeenantiopure structures relative to helicenes with more uniform shapes. The resultsrevealed a direct but weak relationship between π–πstacking interactions and crystal lattice energy for most values of n. Therefore, π–π stacking interactionsare predominantly observed across higher-energy crystals and lessfrequently observed for low-energy crystals. However, on increasingchain length for naphthalene up to [6]helicene, π–πstacking becomes less unfavorable, to the point where there is nodiscernible correlation between the lattice energy and π–πstacking interactions, after which the correlation increases again,becoming maximally unfavorable for [8]helicene . The correlation between π–πinteractions and the lattice energy then decreases as n increases, reaching a local minima for [11]helicene. These findingssuggest that having a less uniform shape, as quantified by the largeangles between terminal helicenes, may foster more favorable π–πstacking compared to helicenes with more uniform shapes. This is likelydue to the direct relationship between the angle between the terminalrings and the helical rotation of the helicenes, as the larger anglesfor [6] and [12]helicene correspond to one and two full rotationsof the helix, respectively. Therefore, for intermediate rotationsof the helix, the nonterminal rings are not accessible for intermolecularπ–π stacking.To identify any trends between π stackinginteractions andlattice energy, we computed the Pearson correlation coefficients foreach chain length (n, it suggests that π stacking is less unfavorablewhen the molecular shape is less uniform. This trend aligns with ourinitial observation of relatively fewer polymorphs in the CSP landscapefor [6]helicene. The absence of a clear trend between π–πinteractions and energy, i.e., the lack of these interactions predominatelyin higher energy crystals, suggests that other intermolecular interactionsthat typically stabilize the crystal structures for other [n]helicenes may be destabilized in [6]helicene. This observedtrend may be the reason why chiral columns have been successfullysynthesized experimentally in substituted [6]helicenes.73 Consequently, these trends could provide valuable insights intodetermining whether helicene is suitable for further polymorph studiesor those whose derivatives may benefit from additional investigation.It is crucial to note thata low Pearson correlation coefficientdoes not imply that π–π stacking is inherentlyfavorable. In fact, the low Pearson correlation coefficient for [5]–[7]helicenessuggests that there is almost no correlation between π–πstacking and lattice energy and, thus, π–π interactionsare neither favorable or unfavorable. Instead, in comparison to thehigher Pearson correlation coefficients for other values of n]helicenes where n = 3–12.Features such as interlocked pairs with back-to-back packing are moreoften found in the low-energy enantiopure polymorphs rather than racemicpolymorphs, whereas herringbone packing is more common in racemicstructures. The polymorphic behavior changes significantly with changing n, with similar packing motifs found in helicenes of similarlengths. We suggest that the grouping of similar packing types isdue to the similar shapes, which we quantify using the angle betweenthe terminal aromatic rings. This measure also loosely correlateswith other global trends seen in the CSP landscapes, such as the numberof polymorphs and percentage of enantiopure structures. A key resultfrom the analysis of the low-energy polymorphs is that the most stablepolymorph of the uncharacterized [12]helicene crystal exhibits a packingmotif that may have high hole mobility, indicating efficient chargetransport and enhanced device performance.We used CSP to investigate the effect ofchanging helicene lengthon the polymorphism and intermolecular interactions for naphthaleneand the –[7]helicene and their derivativesmay be a fruitful avenue of exploration for developing functionalorganic electronics. This observation is further supported by theobservation of chiral columns predominant in derivatives of either[6] or [7]helicene.79 π–π interactions arenot the only motifs that result in favorable charge-transport properties,as evidenced by Rice et al. for [6]helicene; as such, future workon fully analyzing the charge-transport properties of structures ineach of the CSP landscapes reported here would be beneficial to developfurther understanding of structure–property relationships inorganic electronics.26Using computationalstudies to explore the polymorphic landscapesof organic electronics helps improve our understanding of the underlyingfactors driving the packing behavior and can direct electronic molecularmaterials design. In this study, our main focus was on the influenceof


The objective of this study is to investigate the prevalence of autism (ASD) symptoms, i.e. , social difficulties, repetitive behaviors, and communicational problems, among children born extremely preterm (EP) compared to a reference group, and to investigate possible antecedents of ASD symptoms among EP children. Method is a national Norwegian cohort of 11 year old EP children, excluding those with intellectual disabilities, non-ambulatory cerebral palsy, blindness, and/or deafness. Parents and teachers reported ASD symptoms using The Autism Spectrum Screening Questionnaire (ASSQ). Social difficulties, repetitive behaviors, communicational problems, and a total ASSQ score were presented. Combined ratings on the ASSQ was defined as parent and/or teacher scoring the child ≥ 98th percentile of the reference group, which was the population-based Bergen Child Study. Of eligible children, 216 (64%) EP and 1882 (61%) reference children participated. EP children had significantly higher mean scores and combined ratings on social difficulties , repetitive behaviors , communicational problems , and the total ASSQ score  compared to reference children. Only no prenatal steroids, IQ 70–84, and mental health problems at 5 years of age were significantly associated with ASD symptoms at 11 years of age. EP children were at increased risk of social difficulties, repetitive behaviors, and communicational problems, and approximately one out of five were reported as high scorers of ASD symptoms. No prenatal steroids use, IQ in the lower range, and mental health problems at 5 years of age were associated with ASD symptoms.The online version contains supplementary material available at 10.1007/s00787-022-01953-4. Social difficulties, repetitive behaviors, and communication deficits are the three main symptom domains of Autism Spectrum Disorder (ASD) . The preMost studies investigating ASD symptoms in EP children report this as a total score , 10–13. The few studies investigating antecedents of ASD symptoms in EP children report bronchopulmonary dysplasia (BPD) , 15, jauThe aims of the present study of a national cohort of EP children at 11 years of age were: (1) To investigate the prevalence and nature of symptoms and the three main symptom domains of ASD, among children born EP without non-ambulatory CP, intellectual disabilities, deafness or blindness compared to a reference group. (2) To investigate possible antecedents of ASD symptoms among EP children including pre, neonatal and perinatal factors, mental health problems, and functional outcomes at 5 years of age.n = 638). Of the 638 children born EP, 2 refused to participate, and 263 children died before 2 years of age. One child died between the 2 and 5 year follow-up. Both at 5 and 11 years of age, 372  EP children were alive. At 5 years of age, 306 EP children attended somatic examination, and 255 of them completed mental health questionnaires. The EP children were prospectively assessed during their stay in the neonatal intensive care unit (NICU) and at 2, 5, and 11 years of age. At 2 and 5 years, they were assessed by experienced pediatricians, and at 5 years, psychologists assessed IQ using the Wechsler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R) [The target population was a national cohort of all children born EP  < 28 weeks or birth weight (BW) < 1000 g) in Norway in 1999 and 2000 (WPPSI-R) . At 11 yn = 33) [n = 35) [At 11 years of age, EP children were excluded if they at 5 years had an IQ < 70, non-ambulatory CP (class 4–5 on the Gross Motor Function for Classification of CP-GMFCS ), deafnen = 33) . For chi[n = 35) . None ofn = 11), were excluded. Six children were reported with CP without ID, and were included in the study, with unknown level of ambulation. Children with blindness or deafness without ID may have been included, as necessary information was lacking. A total of 1882 (61%) children were eligible and included in the analysis, including parents’ completed questionnaires for 1767 (57%) and teachers’ questionnaires for 1880 (61%) [The reference group was the Bergen Child Study, an unselected population of 11-year-old children living in the municipality of Bergen, Norway , 28. AllComparing the attending children in the reference and the EP group, the number of fathers with higher education was significantly higher in the reference group, and father’s education was adjusted for in all the analyses comparing the two groups. Higher education was defined as at least 3 years of education at university level. There was no statistical significant difference between the proportion of mother’s with higher education and proportion of boys (see Online Resource 1) .The Autism Spectrum Screening Questionnaire (ASSQ) is a 27-item questionnaire reflecting symptoms of ASD; social interaction problems, motor clumsiness, repetitive behavior, and tics –32. The t tests, ASSQ scores ≥ 98 percentiles for the reference group, and the combined ASSQ score with χ2 tests were compared between the EP and the reference group  was used for all analyses.A The Regional Committee on Medical Research Ethics and The Norwegian Data Inspectorate approved the study, and parents gave written informed consent.p < 0.001) mean scores on both parent- and teacher-reported total ASSQ score and significantly increased odds of a high combined total ASSQ score  compared to the reference group (Table EP children had significantly higher p < 0.00 mean scop ≤ 0.001) mean scores, increased odds of being scored ≥ the 98th percentile , as well as odds (OR: 3.2) of having a combined social interaction problem score compared to the reference group , odds of being scored ≥ the 98th percentile , and odds (OR 6.4) of having a combined repetitive behavior score compared to the reference group  mean scores reported both by parents and teachers, and increased odds (OR: 7.5) of being scored ≥ the 98th percentile reported by teachers, and increased odds (OR: 5.4) of having a combined autistic style score compared to the reference group. Parental report score ≥ the 98th percentile between the two groups was not significantly different , IQ in the lower normal range (IQ 70–84) (p = 0.008), and mental health problems at 5 years of age (p = 0.001). After performing false discovery rate analysis, IQ in the lower normal range (IQ 70–84) (p = 0.008) was no longer significant   found th00 g  fouIn accordance with one previous EP study , we founIn contrast to previous studies investigating neonatal factors , 14–16, In this study of Norwegian children born EP without severe functional disabilities are at a twofold to tenfold increased risk of very high scores on all main symptom domains of ASD. Almost every fifth EP child had high scores of ASD symptoms. Not receiving prenatal steroids, IQ in the lower normal range, and mental health problems at 5 years of age were predictors of ASD symptoms at 11 years. However, limitations to the study should be taken into account regarding generalizability to other settings. Understanding the complex pattern of potential mental health problems is important for parents, health care personnel, teachers, and others who relate to children born EP.Supplementary file1 (PDF 429 KB)Supplementary file2 (PDF 511 KB)Below is the link to the electronic supplementary material.


Hydroxyapatite (HA) promotes excellent bone regeneration in bone-tissue engineering, due to its similarity to bone mineral and its ability to connect to living tissues. These factors promote the osteointegration process. This process can be enhanced by the presence of electrical charges, stored in the HA. Furthermore, several ions can be added to the HA structure to promote specific biological responses, such as magnesium ions. The main objective of this work was to extract hydroxyapatite from sheep femur bones and to study their structural and electrical properties by adding different amounts of magnesium oxide. The thermal and structural characterizations were performed using DTA, XRD, density, Raman spectroscopy and FTIR analysis. The morphology was studied using SEM, and the electrical measurements were registered as a function of frequency and temperature. Results show that: (i) an increase of MgO amount indicates that the solubility of MgO is below 5%wt for heat treatments at 600 °C; (ii) the rise of MgO content increases the capacity for electrical charge storage; (iii) sheep hydroxyapatite presents itself as a natural source of hydroxyapatite, environmentally sustainable and low cost, and promising for applications in regenerative medicine. Amo5PO3(OH), deow cells ,7,8.Due to the disadvantages of synthetic hydroxyapatite regarding low durability and stability, hydroxyapatite of natural synthesis, through natural bio residues, has presented a good solution for treatment feasibility in bone regeneration. Furthermore, the conversion of bio-waste into useful bioproducts, which is a low-cost practice, is also a more dynamic response for the environment ,9,10. Th2+, Sr2+, and Zn2+ that can increase the proliferation, bone density, and osteoblastic activity, respectively [HA can be synthesized or extracted from various natural sources such as fish scales/bones, bovine bones, eggshell, or the exoskeletons of marine organisms . To puriectively ,15,16+, Sr2+, Zn2+, Ce3+, Mg2+ [The biological properties of hydroxyapatite can be further improved by inserting some cations, including Ag3+, Mg2+ ,18. In a3+, Mg2+ ,20,21. I3+, Mg2+ .2+ and PO43−), adsorbing certain types of proteins with desirable reactions with bone-forming cells [The bioactivity process can also be promoted through the presence of electrical charges in hydroxyapatite. Yamashita et al. found that HA can store a high density of electrical charge, which significantly increases its bioactivity level allowing much faster binding to the host-bone tissue. Osteointegration time can decrease by half compared to uncharged hydroxyapatite ,23,24,25ng cells .The main objective of this work was to study naturally-synthesized hydroxyapatite as a low-cost and eco-friendly biomaterial for application in bone regeneration. Furthermore, this study evaluates the electrical behavior of the processed HA, as a potential-storing electrical-charge biomaterial, which will promote the osteointegration process.The hydroxyapatite was obtained from sheep bones. To extract and purify the bones, the cleaning process was started by leaving the sheep bones in boiling water for two days. After, the bones were subjected to a heat treatment, in air, at 850 °C for 4 h. To obtain fine powders, the treated sheep bones were ground in an agate mortar. These powders were called sheep hydroxyapatite (sHA). In the next step, three different amounts of MgO  were mixed with the ground sheep-bone powder. Each composition was homogenized using a ball milling planetary system operating at 400 rpm for 1 h, in dry conditions. Agate vessels and balls were used. The homogenized powder was used to prepare 13 mm diameter pellets of approximately 2 mm thickness, using a uniaxial pressure system and steel molds. For each pellet, a pressure of 2 tons was applied for 10 min. After, all pellets were subjected to a heat treatment at 600 °C, for 24 h, using a heating rate of 5 °C/min. The thermal characteristics of the composite were analyzed using differential thermal analysis (DTA) and thermogravimetric (TG) analysis. The structure of the samples was investigated through density measurements, X-ray powder diffraction (XRD), Raman, and FTIR spectroscopies.2O3 powder (99.999%) was used as the reference.The thermal analysis was performed using Hitachi STA7300 equipment. Each measurement ran from room temperature up to 1200 °C with a continuous nitrogen flux, and with a heating rate of 10 °C/min. Pure AlThe density measurements were made using the Archimedes principle, hydrostatic weighing method, using an Adam Equipment ADP 110 . Ethyl alcohol (purity > 99.5%), from Merck , was used as the liquid phase. The measurement process was repeated 10 times for each pellet to minimize measurement errors. Between measurements, each pellet was dried in a vacuum oven at 100 °C and then left to reach room temperature before a new measurement.λ = 1.54056 Å) was used and it was working at 40 kV, and 15 mA. The scanning parameters were a scan step of 0.02°, with a time of 50 s per step and a 2θ angle range between 6° and 70°. From the measured data, the crystallite size was calculated by the Debye-Scherrer equation [K was considered 0.9, λ is the wavelength of the X-ray beam (λ = 1.5418 Å for Cu Kα radiation), β is defined as the full width at half maximum (radian), and θ is the X-ray diffraction angle (°) [The XRD results were obtained at room temperature using an Aeris-Panalytical diffractometer . CuKα radiation (equation :(1)D=Kλβngle (°) . The cryal plane .−1 at room temperature. The Raman spectroscopy was performed using a Jobin Yvon HR800 spectrometer  using an Ar+ laser (λ = 442 nm), a magnification lens of 50×, and the spectra were produced in a back-scattering geometry, in the range of 100–1300 cm−1.The FTIR data was obtained using a Perkin Elmer Spectrum BX spectrometer  in the range of 400–1300 cmThe pellets morphology was evaluated using an scanning electron microscope (SEM) from TESCAN , model Vega 3. Several regions of each sample were analyzed using a circular scanning area of 5 µm in diameter. All the samples’ surfaces were prior covered with carbon to enhance the surface electron conductivity. The grain sizes were measured using the ImageJ software 1.51 , by readω represents the angular frequency, d is the thickness of the sample, the S value is the electrode area, and −12 F/m).In the electrical measurements, the surface of each heat-treated pellet was polished to obtain parallelism between opposite surfaces. The electrodes were made by painting the parallel surfaces with silver conducting paste (RS 186-3600 conductivity paint). A nitrogen-bath cryostat system was used to measure the electrical characteristics in the temperature range between 300 K and 400 K, controlled by an Oxford ITC 4  connected to platinum temperature sensors. During the measurements, all samples were kept in a static Helium atmosphere to prevent moisture and to reduce the thermal gradients by improving the heat transfer. The ac electrical conductivity σtion (4) ,36,37: of 100 V and the current (I) was measured after stabilization. The conductivity was then calculated using Equation (6).d represents the sample thickness and S the electrode area.For the dc electrical conductivity (5(PO4)3(OH) crystal phase (ICCD ref. 01-080-6199) [θ angle used was 26.0 and for MgO 43.0. It is visible that for both phases the crystalline size is always below 100 nm, being the smallest crystalline size associated with the MgO phase.The XRD pattern of pure sHA and the composites formed by sHA and MgO are shown in 80-6199) . This sp80-6199)  on hydro80-6199) ,43,44. T−1. The band centered at about 1000–1100 cm−1 and the intensive absorption bands around 500–600 cm−1 indicate the presence of PO43− groups. More specifically, the characteristic absorptions bands of the υ2 (PO43−) and OH− groups are observed at 474 cm−1, the υ4 (PO43−) at 570 and 602 cm−1, υ1 (PO43−) at 962 cm−1, and υ3 (PO43−) at 1051 and 1092 cm−1. The band at 633 cm−1 is attributed to the OH- groups and can be considered proof of the presence of HA [The FTIR spectrum of all composites, shown in ce of HA ,46,47. Tce of HA .−1, 207 cm−1, and 288 cm−1 are assigned to the lattice mode of CaPO4 and the band at 332 cm−1 is assigned to the Ca-OH υ3 stretching mode. The peak at 963 cm−1 is related to the PO43− υ1 vibration (symmetric P-O stretching mode). The peaks at 433 cm−1 and 447 cm−1 were assigned to PO43− υ2 vibration (bending mode), and the peaks at 1030 cm−1, 1047 cm−1 and 1079 cm−1 corresponded to the PO43− υ3 vibrations (asymmetric P-O stretching mode). Vibrations at 582 cm−1, 593 cm−1, and 606 cm−1 are attributed to PO43− υ4 vibrations (asymmetric O-P-O bending mode) [−1, attributed to a vibration associated with the MgO crystal phase [ng mode) ,49,50,51al phase . This reThe sample morphology analysis was made using SEM microscopy and the obtained micrographs show grains with regular shapes, similar to spheres, in all samples. This habit is in agreement with that presented by Ibrahim et al.  in theirThe Debye-Scherrer formula applied to the XRD spectra allows calculation of the crystallite size. This characteristic was calculated for the sHA and MgO phases, and the results, shown in The density measurements show a decrease in density values with increasing MgO concentration . Since tThe ac conduction-activation energy, calculated by linear regression of the conductivity data using the Arrhenius equation, which is represented in behavior .cX = 85.7%). Raman and FTIR spectroscopies are in agreement with the XRD results, revealing vibrations associated with the MgO crystalline phase. FTIR spectra also indicate that Mg ions do not incorporate into the HA structure (constant intensity of the band at 633 cm−1). At the morphological level, it is concluded that the insertion of MgO up to 15% does not promote significant alteration of the grain habit. However, SEM reveals an increase in grain size with increasing MgO concentration (125.57 nm up to 238.79 nm). SEM also shows an affinity for crystallite aggregation. The electrical measurements showed that the sample with higher MgO content, 15%, has more potential to store electrical charges (ε′ = 6.87 at 300 K and 10 kHz) and has lower relative losses . It is also noted that the 5% of MgO samples show the highest crystallinity and the lowest conductivity behaviors.In this study, the electrical properties of sheep-bones-derived hydroxyapatite mixed with magnesium oxide are considered and related to its structural and morphologic characteristics. The XRD revealed that the milling process favors the mixture of MgO with HA without substantially changing its structure. From the analysis of the XRD spectra it is concluded that the crystallite size of HA is larger than that of MgO and suggests that the degree of crystallinity tends to decrease for higher MgO concentrations (


A 39-year-old woman underwent a colonoscopy subsequent to episodes of hematochezia, and this revealed the existence of a rectal subepithelial mass, approximately 18 × 8 mm in size, covered with smooth, normal mucosa. Endoscopic ultrasound suggested that the lesion originated from the submucosal layer, locally infringing upon the muscularis propria, and that it showed homogeneous hypoechoic changes, clear boundaries, and was growing toward the lumen . ComputVideo 1 Endoscopic submucosal excavation in the management of a rectal subepithelial cold abscess.Redness, swelling, warmth, pain, and impaired function are the typical manifestations of acute inflammationEndoscopy_UCTN_Code_CCL_1AD_2AI


To the Editor: Atopic dermatitis (AD) is a chronic inflammatory skin disorder. Biologics that have been approved for AD include dupilumab (anti–interleukin (IL) 4/13) and recently a new anti–IL-13, namely tralokinumab, was included.,Conjunctivitis is an inflammation or infection of the transparent membrane (conjunctiva) that lines the eyelid. It is caused by allergens, irritants, bacteria, and viral infections. Symptoms can vary depending on etiology, including redness, itching, burning, discharge, and eyelid edema.ClinicalTrials.gov using the terms “Atopic dermatitis” and “biologics” or “Dupilumab” or “IL-4/13” or “Tralokinumab” or “IL-13” or “Lebrikizumab” (https://data.mendeley.com/datasets/xf7mm6x9m9/1).We systematically reviewed the randomized controlled trials pertaining to the incidence of any conjunctivitis subtype with dupilumab, lebrikizumab, and tralokinumab using preferred reporting items for systematic review and meta-analysis protocols (PROSPERO: 392077). A thorough search in Medline (PubMed), Directory of Open Access Journals, and kizumab” . The seaQ = 15.81, I2 = 0%).Out of 263 titles and abstracts, a total of 17 studies with a cumulative sample size of 5830 participants reported the incidence of conjunctivitis among patients with AD undergoing biologic therapies. Out of 17 studies, 12 evaluated the efficacy of dupilumab, 2 tested lebrikizumab, and 3 assessed tralokinumab. Extent of heterogeneity across the studies was minimal (P =.59) .Among 4197 patients undergoing biologic therapies, 213 reported conjunctivitis, whereas only 32 out of 1633 participants in the control group reported conjunctivitis. Pooled Mantel-Haenszel odds ratio was 3.11  with no significant outlier effects . There wP =.59) . No subgThe finding of this systematic review and meta-analysis demonstrated no statistical difference between the incidence of conjunctivitis between dupilumab and the included newly approved and in trial agents. Patients need to be counseled about the incidence of conjunctivitis and its occurrence with these new agents. The high incidence of conjunctivitis with the AD indication of these medications in contrast to the other indications of these drugs raise the possibility of an association related to AD itself. Sources of limitation could be the presence of minimal heterogeneity and the inability to portray causal relation between conjunctivitis and biologic agents.None disclosed.


However, probing liquid samples with ionizingradiation changes the solution chemistry under observation. In thiswork, we show that a radiation-induced decrease in pH does not necessarilycorrelate to an increase in acidity of aqueous solutions. Thus, pHdoes not capture the acidity under irradiation. Using kinetic modelingof radiation chemistry, we introduce alternative measures of acidity(radiolytic acidity π* and radiolytic ion product KW*), that account for radiation-induced alterations ofboth H+ and OH– concentration. Moreover,we demonstrate that adding pH-neutral solutes such as LiCl, LiBr,or LiNO3 can trigger a significant change in π*.This provides a huge parameter space to tailor the acidity for in situ experiments involving ionizing radiation, as presentin synchrotron facilities or during liquid-phase electron microscopy.Advanced  In situ studies employing ionizing radiation enableunique insights into dynamics on the nanoscale in liquid.4 Yet, performing reliable cutting-edge research demands precise knowledgeof the radiation–matter interaction and the related parametersduring the experiment.7 In particular, when studying chemical phenomena inliquid using electrons ) or X-rays )it must be ensured that the effect of radiation on the observationis accounted for.15c(H+) of hydrogen ions, known as pH. Simulations show that electron irradiationof pure water cause a dose-rate dependent increase of c(H+), thus lowering pH.16One of the main parameters characterizing the physicochemicalpropertiesis the acidity of the liquid phase, generally described by the negativedecadic logarithm of the concentration 17 and analyses of growth kinetics18 suggest an elevated concentration of c(OH–) under irradiation. Likewise, LP-TEM studieson c(OH–)-driven Si etching arereported.20 This is unexpected at low pH.In contrast,precipitation phenomena observed in aqueous solutionsc(H+) and c(OH–) were not yetdiscussed in the literature. Moreover, the interpretationof pH in an irradiated liquid must be evaluated in general.Nevertheless,simultaneous electron-beam induced changes of 21 In this sense, the impact ofadditives to pure water on the acidity has not been discussed to date.Highly reactive radiolysis products and their subsequent deactivationreactions enable diverse reaction pathways which drastically dependon the chemical environment.24 bromide,27 and nitrate31 on the acidity are investigated.In this Letter, we reconsider the interpretation of pH in irradiatedliquids by modeling electron beam and X-ray-induced radiation chemistryin pure water. We show that current models of irradiation-inducedacidification are insufficient and introduce a more conclusive descriptionof the acidity in irradiated solutions. Furthermore, the impact ofdifferent supposedly pH-irrelevant ionic species typically presentin LP-TEM like chloride,c(H+) and hydroxide ions c(OH–) changing the respective concentrations until an equilibriumis reached.K can be formulated.This can be achieved by regarding the ratio of forward and backwardreaction kf/kb, as well as via activity α of the respective species:2O)) canbe assumed to be unity and α(H+), α(OH–) are approximated by the concentrations c(H+), c(OH–).During autoprotolysis, water molecules dissociate into protons KW:+ andOH– concentration normalized to unit molar concentration cunit = 1 M:+ concentration of 0.1 μM corresponds to a neutralpH value of 7 in pure water. According to – concentrationis 0.1 μM as c(H+) and c(OH–) are coupled. Adding acids or bases manipulates c(H+) and c(OH–) for the solution to become more acidic or basic, respectively,while maintaining the reciprocal concentration dependency given by This leads to the ion product 33 Those interact with the present environment via subsequent reactions(see the c(H+) and c(OH–) is decoupled by irradiation which contrasts with classical chemicalconditions:KW does not necessarily remain constant in irradiated solutions.Access to the G-values of these primary species  X-rays, irradiationof watertriggers a relaxation cascade that results in the generation of severalprimary species within about 1 μs.ted case 1a.csat(O2) = 255 μM14) water exposed to electronirradiation the steady state concentrations of H+ and OH– are plotted as a function of the amount of power absorbedby the specimen (dose rate)  2a. Evide+ and OH– themselvesare primarily generated (c(H+) and c(OH–) instead. To emphasize this fundamental difference, the radiolyticion product KW* is introduced:–1 thermally induced changes in waterat ambient pressure could cause similar deviations  and c(OH–). Thisis fundamentally different in the case of thermally excited ion productsas here charge and mass balance demand that c(H+) and c(OH–) change equally.Furthermore, Henerated  so that viations 2b.35 How species 5, KW* isKW* to the dose rate is observed forvalues above 1 kGy·s–1 of  kGy·s–1 2b. Theuc(H+) or c(OH–) is dominating and, thus, if an irradiated solutionconstitutes an acidic or basic environment, we introduce the logarithmicratio of c(H+) and c(OH–) as a new measure. This is denoted as radiolytic acidityπ*:Consequently,a more conclusive interpretation of the acidificationof irradiated solutions is required that accounts for the drasticallydifferent interplay of both species within the solution. To predictwhether c(H+) and c(OH–) depend on the initial pH and especially onthe type and dose rate of irradiation. For electron exposure the resultfor a wide range of initial pH and dose rate is visualized in c(H+) and c(OH–) under irradiation, while π* is depicted in For pure water, –1.Remarkably, independent of the initial pH valueof the specimensolution prior to irradiation, π* converges toward neutral conditionsfor increasing dose rates. This becomes prominent above ∼1MGy·s2O2 and O3 yielding para-oxygen . This in turn triggersa reaction cascade in which, beside others, OH– isconsumed (see A slight asymmetry favoringacidic conditions is assumed to berelated to the (slow) decay of Humed see .3.This interplayof radiation chemistry products with acidity highlightsthe necessity of elucidating the complete reaction chemistry network,which becomes even more pronounced in systems more complex than water.Hence, in the following, the influence of additives on π* isexemplarily demonstrated with LiCl, LiBr, and LiNO+ (E°(Li/Li+) = −3.0401V)36 required for reduction exceed E° of the strongest reductant present (E°(H2O/eh–) = −2.9 V),32 kineticsfocusing on the anion–water interplay were considered exclusively.All simulations are based on radiation chemistry of pure water,with additional reactions and species considered for chlorine, bromineand nitrate-containing solutions see . As the c(H+) and c(OH–) areseparately plotted in the The evolution of π* for a solution of pH = 7 containing theseanions at concentrations of 1 mM and 10 mM is shown in 3), their basic strength is generallynegligible. Consequently, solutions containing these anions can havea neutral pH prior to irradiation. In combination with thermodynamicallystable cations such as Li+, the anion-impact on radiationchemistry can be investigated.As all considered anions represent conjugated basesof strong acids.Differences in kinetics influencethe radiation chemistry, whichis evident when comparing dissociation rate constants of conjugatedacids (1.46 × 10c(H+) and c(OH–). However, bromide and nitrate ions stronglyalter the acidity of the irradiated solution:Nevertheless, simulation results shownin c(H+) and c(OH–) at low dose rates.Above ∼1 MGy·s–1, the solution becomesmore basic (negative π*) compared topure water, becomes more neutral for larger dose rates, and finallyturns acidic beyond ∼100 GGy·s–1.For both radiationtypes, nitrate mitigates the impact on c(H+) and c(OH–) foraqueous solutions of Cl– or NO3–, the simulation indicates a difference for Br–. When irradiated with X-rays, the solution remains acidic for theentire simulated dose rate range. When considering electron irradiation,however, the solution shows acidic behavior for low and high doserates, while a basic behavior evolves for dose rates between 500 kGy·s–1 and 5 GGy·s–1 for an initialconcentration of 1 mM.While the type of radiation (electrons or X-ray photons)appearsto have no qualitative influence on the evolution of A change of the concentration from 1mM to 10 mM does not qualitativelychange the shape of the curves but enhances tendencies and thereforeshifts intersection points by about 1 to 2 orders of magnitude.– could be a promisingcandidate for in situ studies of acidity-dependentprecipitation reactions, using only dose rate adjustments.For bromide ion concentrations of 10 mM, this shift causes theintersection point to come close to parameters accessible in standardLP-TEM, indicating that BrE° (+2.43V for Cl/Cl– and +1.96 V for Br/Br–)40 which impacts the radical chemistrythat dominates kinetic models. Consequently, reaction kinetics ofbromide ions exhibit a stronger involvement of acidity-mediating pathways.Thedifferent impact of bromide and chloride is remarkable. Althoughin general both halides show comparable chemical properties, the largerbromine radical is lower in energy than the chlorine equivalent. Thisis reflected by the different values of KW* remains closeto KW for dose rates below 1 kGy. Thissuggests that approximating the acidity of weakly irradiated solutionsby pH may introduce only small errors that could potentially be ofminor impact. Nevertheless, pH should not be carelessly translatedto irradiated solutions in general, as there, pH does not providea holistic picture of the acid–base interplay.By referring to π* in nonirradiated solutions, it can bemapped onto an initial pH value (see c(H+) and c(OH–). This might be misleading in situations where this prerequisiteis not fulfilled. Under such conditions, it is advised to accountfor c(H+) and c(OH–) directly.Furthermore,the deviations in π* introduced by additivescan already become notable at low dose rates 4. This eKW* should be considered in combination as this fully describesthe acidity under irradiation.In addition, identical π* valuescan be obtained by differentabsolute concentrations. Therefore, both, π* and –1) this occurs within microsecondsas demonstrated by the time-dependent analysis of KW* and π* shown in –1. This illustratesthat radiation effects on the acidity should be considered even atlow dose experiments.Note that the analysis presentedherein considers steady stateconcentrations, regardless of the time the system needs to relax intoit. Yet, for dose rates relevant to most LP-TEM experiments 14 where solvent consumption becomes notable. Likewise, the primaryradiation–matter interaction of solutes is not considered here.This approximation appears to be reasonable for small solute concentrationsbelow 1 M only,33 as present in this work.Mind also that any change of the solvent limits thevalidity ofthe assumption that the radiation only interacts with water. Thisis particularly relevant for high dose rates  and c(OH–) remains negligible. As Tesler and Schindelwolf41 measured similar rates for Cs+, as well, weassume that our findings would also hold for CsCl-, CsBr-, and CsNO3-containing solutions.Furthermore, as demonstrated, even additives considered as nonreactivecan drastically change the steady-state chemistry at hand. Thus, anyextrapolation should be performed cautiously. In this context, itis advised to double-check the assumption of negligible Li Na+ see .41 Evidec(H+) and c(OH–) inpure water,42 suggesting that π*is not affected by beam-heating.Especially relevant for LP-TEMis electron beam induced heating,which can significantly affect the redox chemistry. However, thiseffect is simulated to have a negligible influence on 43 and derivatives48).Nevertheless, the herein presentedwork provides a good approximationfor liquid cell architectures with small, static volumes irradiatedcompletely by X-rays and/or electron beams in TEM  and c(OH–) rangecould be employed.The large parameter space comprising types of radiation,dose rate,additives, initial concentrations etc. allows for tailoring specificconditions. In this Letter, we merely scratch the surface to illustratethe observable effects. However, experimental verification of themodel is necessary. Hence, suitable marker reactions, showing structuralchanges, precipitation, or dissolution in the accessible c(H+),14 we show that c(H+) alone is insufficientto quantify the acidityof aqueous solutions interacting with ionizing radiation. Hence, byintroducing π* and KW* as more adequatemeasures that consider the relation of c(H+) and c(OH–), we unveil that,in pure water, electron beam and X-ray irradiation drive the aciditytoward a balanced environment, even for high or low initial pH values.Moreover, we show that adding Cl–, Br–, and NO3– ions significantly impactsπ*. This allows for tailoring π* during in situ experiments by means of initial concentration and dose rate forquantitative studies. In particular, in LP-TEM, Br– ions are promising candidates for validating the predictions made.While our work seconds the finding that irradiationincreases KW and consequently the acidity of water, suchas temperature (see above) or the Wien effect.49 Water electrolysis also exhibits the potential to locallyalter the acidity toward a nonequilibrium state, especially dominantin proximity to the electrode surface.50 In such cases, regarding the logarithmic ratio c(H+) and c(OH–) couldbe potentially beneficial, as well.Finally, our simulations provide valuable insights for radiationchemistry not only for LP-TEM and X-ray-based techniques but alsofor any research discipline related to ionizing radiation of aqueousenvironments. Besides radiolysis, other effects can influence 13 Coupled ordinary differential equations (ODEs)are used to simulate the concentration c of species i over time t, depending on the concentrationof reactants l and n. With the liquiddensity ρ, dose rate ψ in Gy s–1, G-value Gi of i, and the rate constant kj and km for reaction j and m, respectively, the reaction networkcan be expressed asRadiolysis simulations were performedutilizing AuRaCh, a custom-buildalgorithm which has been described in our previous work.G-valuesare well-known (G-values are valid for an energy of 200–300keV.52 Note thatother electron acceleration voltages can have deviating G-values which could yield a different outcome.52 Yet, this can easily be simulated with AuRaCh. The G-values for X-ray irradiation are designed for irradiation with high-energyphotons53 and appear to be reasonable forconventional in situ X-ray diffraction.13 Simulation results where the amount of radiolyticproducts in steady state exceeds 1% of the water concentration arelabeled appropriately, as here, the assumption of radiation only interactingwith the solvent becomes questionable.Here, we assume soleinteraction of radiation with water, for which ll-known . For eleNote that the concentrationevolution converges against a steadystate which is analyzed in this manuscript. An overview about thetime required to reach this steady state is provided in


Freezing stress is the main factor affecting the normal growth and distribution of plants. The safe overwintering of a perennial deciduous plant is a crucial link to ensuring its survival and yield. However, little is known about the molecular mechanism of its gene regulation metabolites as related to its freeze-tolerance. In order to enhance our comprehension of freeze-tolerance metabolites and gene expression in dormant apple trees, we examined the metabolic and transcriptomic differences between ‘Ralls’ and ‘Fuji’, two apple varieties with varying degrees of resistance to freezing. The results of the freezing treatment showed that ‘Ralls’ had stronger freeze-tolerance than ‘Fuji’. We identified 302, 334, and 267 up-regulated differentially accumulated metabolites (DAMs) and 408, 387, and 497 down-regulated DAMs between ‘Ralls’ and ‘Fuji’ under −10, −15, and −20 °C treatment, respectively. A total of 359 shared metabolites were obtained in the upward trend modules, of which 62 metabolites were associated with 89 pathways. The number of up-regulated genes accounted for 50.2%, 45.6%, and 43.2% of the total number of differentially expressed genes (DEGs), respectively, at −10, −15, and −20 °C. Through combined transcriptome and metabolome analysis, we identified 12 pathways that included 16 DAMs and 65 DEGs. Meanwhile, we found that 20 DEGs were identified in the phenylpropanoid biosynthesis pathway and its related pathways, involving the metabolism of p-Coumaroyl-CoA, 7, 4′-Dihydroxyflavone, and scolymoside. These discoveries advance our comprehension of the molecular mechanism underlying apple freeze-tolerance and provide genetic material for breeding apple cultivars with enhanced freeze-tolerance. Freezing stress refers to the adverse effects on plants caused by exposure to freezing temperatures, which can damage plant tissues and reduce plant growth and productivity ,2. FreezMetabolome and transcriptome are two important levels of biological information that can provide insights into the molecular mechanisms underlying freezing stress in plants. The field of metabolomics is concerned with the investigation of small molecules, also known as metabolites, which participate in a range of biochemical processes within plants ,17. FreeThe molecular mechanisms underlying the response to freezing stress involve a complex network of signaling pathways and gene expression changes. During cold acclimation, plants undergo a series of physiological and biochemical changes that increase their tolerance to freezing stress ,26,27. TApple is a fruit tree species with a large production area and abundant yield worldwide, with an excellent potential presence on the international market. Apple trees yield less and have a limited cultivation range under low temperature stress; therefore, much research is focused on understanding the response of apple trees to such stress. At present, studies on the molecular mechanism of apple tree response to freezing stress mainly focus on the molecular model of transcription factors, but the analysis of the molecular mechanism of apple tree frost resistance based on multi-omics analysis is rarely carried out. In this study, we first compared the freeze-tolerance of annual branches from different varieties of apple trees and determined their limit temperatures for freezing resistance. Transcriptome and metabolome analysis identified potential critical pathways and genes involved in apple response to freezing stress. The study provides insights into the genetic factors underlying tolerance to freezing in apples and can aid in the development of new crop varieties that are more resilient and productive, which is crucial for global fruit security and sustainability.Two apple cultivars  were selected for this study. ‘Ralls’ apples were grown in the apple orchard area in Yong’an village , Zhangjiakou City, and ‘Fuji’ apples were grown in the apple cultivation area of Yuanfang village , Shijiazhuang City, China. The plant materials used in the experiment were all from 5-year-old apple trees. Annual branches were collected as experimental material on 15 December 2021. All plant materials were stored at a constant temperature of −10 °C for 7 d.Plant materials with constant growth potential were treated at low temperatures. The materials treated at −10 °C were used as the control group. Plant materials in the experimental group were treated at −15 °C, −20 °C, −25 °C, and −30 °C for 12 h, respectively. The physiological parameters of plant samples were evaluated, and each sample was subjected to three biological replicates. The content of soluble sugar was determined using the anthrone method, and the content of soluble protein was determined via the colorimetric method with Coomassie Brilliant Blue G−250 as the colorimetric liquid . We utilWe selected the freeze-treated annual apple branches for metabolome detection, based on the physiological index data of the branches under low temperature treatment. ‘Ralls’ materials in the experimental group were treated at −10 °C, −15 °C, −20 °C, −25 °C, and −30 °C for 12 h, respectively. ‘Fuji’ materials in the experimental group were treated at −10 °C, −15 °C, and −20 °C for 12 h, respectively. In this study, we conducted six biological replicates to increase the reliability of the data.p-value) of the difference for each compound was determined by conducting t-tests based on grouping information to calculate and compare fold change differences. Differential metabolites were identified by integrating the difference multiples, p-values, and VIP values from the OPLS-DA model using screening criteria of fold change (FC) > 2, p-value < 0.05, and VIP ≥ 1. The significance of the differential metabolites in KEGG pathway enrichment was determined by conducting a hypergeometric distribution test. We used the omicShare online tool (https://www.omicshare.com/tools/Home/Soft/trend) (accessed on 10 October 2022) for trend analysis, with parameter settings of p-value < 0.05 and fold change >2.We referred to previous research methods to extract metabolites from annual apple branches . The liq2(FC)| > 1), while also accounting for the probability  of hypothesis testing. Genes with a p-value lower than 0.05 were deemed to be differently expressed [The samples used for transcriptome sequencing were consistent with the metabolome sequencing samples. The TaKaRa MiniBEST Plant RNA Extraction Kit was utilized to extract the total RNA from the samples, and their concentration and purity were evaluated through a NanoDrop 2000 spectrophotometer. Biomarker Technologies Co., Ltd.  finished constructing the cDNA library and sequencing the transcriptome. Filtered data obtained from the Illumina high-throughput sequencing platform excluded reads with joints, N ratio exceeding 10%, and mass values Q ≤ 10 accounting for over 50% of the entire read. The quality score was determined to estimate base-calling error probability using the filtered data . We usedxpressed .Actin gene was employed as the endogenous control, and the experiment was conducted with three biological replicates and three technical replicates. The 2−ΔΔCt method was utilized for determining the relative expression levels of genes [Relative expression levels were measured in the annual branches of ‘Ralls’ and ‘Fuji’ treated at −10 °C, −15 °C, and −20 °C. Total RNA was isolated with the RNAprep Pure Polysaccharide Polyphenol Plant Total RNA Extraction Kit from TianGen Biotech (Beijing) Co., Ltd. , and the cDNA library was constructed using the PrimeScript™ II 1st Strand cDNA Synthesis Kit from Takara Biomedical Technology (Beijing) Co., Ltd., Beijing, Chinas. qPCR primers were designed using Integrated DNA Technologies (IDT) based on the CDS sequence of the target gene. The primer and its sequence information can be found in of genes .We employed a randomized factorial design to assess the impact of freezing damage on both ‘Ralls’ and ‘Fuji’ apples. Overall, the soluble sugar and protein content of ‘Ralls’ was higher than that of ‘Fuji’ A,B. The Two apple cultivars with differential freeze tolerance  were selected for this study. The freeze-tolerant  material was treated at −10, −15, −20, −25, and −30 °C, and the freezing sensitive (‘Fuji’) material was treated at −10, −15, and −20 °C, respectively. In this study, we detected 1483 metabolites across forty-eight samples . SpearmaTo achieve the precise identification of differentially accumulated metabolites (DAMs), we initially conducted PCA analysis and OPLS-DA on comparison groups. PCA and OPLS-DA results showed that the samples in the pairwise comparison group were clearly divided into two clusters . Here, wWe conducted a trend analysis of metabolite response to different low temperature treatments in order to investigate the change pattern of metabolites. Five significant trend change modules were identified in ‘Ralls’ under low temperature treatment of −10, −15, −20, −25, and −30 °C A. MeanwhWe obtained 171.1 Gb of clean bases in 24 samples for gene expression analysis. The Q30 of each sample data reached more than 94%, with an average of 95.3%. The average CG content of all samples was 46.33%, and 91.2% of reads were aligned to the apple reference genome . Taken tHere, 1517, 1522, and 1640 DEGs were identified under different freezing stress conditions between ‘Ralls’ and ‘Fuji’ A. The nuCYP92C6 (HF19026), C1H46 (HF06976), and NAC071 (HF37215) genes in ‘Ralls’ were significantly higher than those in ‘Fuji’ at 15 °C. The expression of BETV6 (HF21117) gene in apple was increased by 8.4- and 7.3-fold, and the expression of BETV6 gene in ‘Fuji’ was increased by 3- and 2.5-fold, respectively, at −15 °C and −20 °C , belonging to the phenylpropanoid biosynthesis pathway, was not detected in ‘Fuji’, but showed a trend of increasing first and then decreasing with the decrease in treatment temperature in ‘Ralls’. The differentially expressed multiples of T8E3.5 (HF00746), UGT73B4 (HF29367) and F7K24.190 (HF16814) genes in phenylpropanoid biosynthesis pathway were negatively correlated with temperature. C4H (HF39985), PCBER1 (HF42225), F22H5.18 (HF07700), and PMAT1 (HF33401) genes also showed a similar trend of differentially expressed multiples (The combined metabolome and transcriptome analysis revealed the significant involvement of the phenylpropanoid biosynthesis pathway in apple’s adaptation to freezing stress. Here, p-Coumaroyl-CoA was identified as the DAM and a connecting metabolite for both phenylpropanoid and flavonoid biosynthesis pathways. The identification of 7,4’-Dihydroxyflavone metabolites via comparative metabolome analysis confirmed their involvement in the flavonoid biosynthesis pathway, which subsequently leads to downstream flavone and flavonol biosynthesis A. Meanwhultiples . In addiIn the field of fruit trees, according to the statistics of apple varieties, there are at least 7500 kinds of apple varieties worldwide, of which the cultivar ‘Ralls’ and cultivar ‘Fuji’ have excellent fruit taste and are very popular among people. Apple tree varieties differ in frost resistance, as shown by several studies ,48,49,50Arabidopsis, and more recently in crops, grasses, and medicinal plants [Metabolomics are used to study the metabolic changes that occur in plants or organisms when they are exposed to freezing stress. Cold/freezing-stress-induced metabolomic responses have been extensively investigated in l plants ,52,53. Cl plants ,55,56,57ADC1 gene has a crucial function in enabling potato to endure freezing temperatures following cold acclimation, as demonstrated by the integration of transcriptome and metabolome data that showed its involvement in the putrescine pathway [Transcriptome has been widely used in the study of plant freeze tolerance. Transcriptome analysis can provide information on DEGs, which can be useful for identifying the key regulatory pathways involved in the response to freezing stress. The identification of genes involved in plant freeze tolerance may also lead to the development of markers that can be used to select genotypes with better freezing. In recent years, transcriptome analysis has often been combined with other omics to analyze plant freeze tolerance ,26,58,59 pathway . In resp pathway .Freezing stress responses are regulated by a complex interplay of genes and environmental factors, and involve a variety of physiological pathways ,62,63,64In conclusion, we used freeze-sensitive and freeze-tolerant apple cultivars as experimental materials to comprehensively analyze the molecular mechanisms underlying freeze tolerance in apples by combining transcriptome and metabolome analysis. The results of the freezing treatment showed that ‘Ralls’ had stronger freeze tolerance than ‘Fuji’. We integrated metabolome and transcriptome analyses to identify 12 pathways involved in apple response to freezing stress, which encompassed 16 DAMs and 65 DEGs. Moreover, it was found that the phenylpropanoid biosynthesis pathway and its related pathways are the key pathways for the difference in freeze tolerance between ‘Ralls’ and ‘Fuji’. These discoveries advance our comprehension of the molecular mechanism underlying apple freeze tolerance and furnish genetic materials for breeding apple cultivars with enhanced freeze tolerance.


Nfkb1, Spi1, Irf8, and two Runx family members, were enriched within promoters of differentially expressed genes related to major inflammatory processes, whereas the transcriptional repressors Suz12, Nfe2l2 and Rest were associated with hyperexcitability and GABA / glutamate receptor activity. CA1 quickly responds to SE by inducing transcription of genes linked to inflammation and excitation stress. Transcription factors mediating this transcriptomic switch represent targets for new highly selected, cell type and time window-specific anti-epileptogenic strategies.Transient brain insults including status epilepticus (SE) can initiate a process termed ‘epileptogenesis’ that results in chronic temporal lobe epilepsy. As a consequence, the entire tri-synaptic circuit of the hippocampus is fundamentally impaired. A key role in epileptogenesis has been attributed to the CA1 region as the last relay station in the hippocampal circuit and as site of aberrant plasticity, e.g. mediated by acquired channelopathies. The transcriptional profiles of the distinct hippocampal neurons are highly dynamic during epileptogenesis. Here, we aimed to elucidate the early SE-elicited mRNA signature changes and the respective upstream regulatory cascades in CA1. RNA sequencing of CA1 was performed in the mouse pilocarpine-induced SE model at multiple time points ranging from 6 to 72 h after the initial insult. Bioinformatics was used to decipher altered gene expression, signalling cascades and their corresponding cell type profiles. Robust transcriptomic changes were detected at 6 h after SE and at subsequent time points during early epileptogenesis. Major differentially expressed mRNAs encoded primarily immediate early and excitability-related gene products, as well as genes encoding immune signalling factors. Binding sites for the transcription factors  It involves the transition of a stable brain network into a functionally altered structure that leads to the development of spontaneously recurring seizures2. Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy, which is often pharmacoresistant to antiseizure medication. Recent data suggest that SE induces highly variable gene expression in different cell types and compartments of the hippocampus5.Epileptogenesis is the process by which changes occur in the brain after a precipitating injury or insult that leads to the development of epilepsy8. CA1 represents a key anatomo-functional compartment of the tri-synaptic pathway under epileptogenic conditions9. Only a few days after SE, the hippocampal CA1 subfield acquires the properties of an epileptogenic focus10.In experimental TLE models, including those triggered by kainic acid and pilocarpine-induced status epilepticus (SE), the hippocampal CA1 region appears to be an important site of epileptogenesisCurrently, it is believed that SE as a transient insult induces a specific transcriptional program that differs between distinct hippocampal subregions. Hereby, CA1 is of particular importance as it constitutes the output point of the hippocampal tri-synaptic circuit. Here, we aimed to elucidate the transcriptional cascades triggered shortly after SE and the key transcription factors (TFs) mediating these changes. So far, the dynamic transcriptional signatures at distinct pathogenic stages early after SE in the CA region have not been examined. Here, we provide for the first time a comprehensive analysis of the transcriptomic profiles of the early stages of epileptogenesis using bulk RNA-seq in hippocampal CA1 at 6, 12, 24, 36 and 72 h after pilocarpine-induced SE. Our results show these mRNA signatures to be highly dynamic during this period.All animal procedures were planned and performed to minimize pain and suffering, and to reduce the number of animals used in accordance with European, national, and institutional guidelines , and the ARRIVE guidelines). The study protocol was approved by the Landesamt für Natur, Umwelt und Verbraucherschutz (LANUV) of the state of North Rhine Westphalia, Germany; Ref. 8.87–50.10.31.08.119). All mice were housed in a humidity (55 ± 10%) and temperature (22 ± 2 °C) controlled environment under a 12-h light–dark cycle (light cycle 7 am to 7 pm) with water and food ad libitum, and nesting material . Mice were allowed to adapt to the facility for at least for seven days prior to any treatment.13. Mice were continuously visually observed after pilocarpine administration. Seizures were assessed behaviourally by the use of a modified seizure scheme, as described previously13. Sustained continuous convulsions with loss of postural were classified as SE as soon as they exceeded the threshold of 5 minutes13. Forty minutes after the onset of SE, animals received an injection of diazepam . A single dose of diazepam has been shown to rapidly reduce clinical seizure activity and to lower mortality15. Control (non-SE) animals were treated identically, but received a saline injection instead of pilocarpine. Of the animals injected with pilocarpine, only those that developed SE (SE-experienced) were used for subsequent analyses.For SE induction, adult  C57Bl/6N mice (Charles River) were pretreated with a subcutaneous injection of 1 mg/kg scopolamine methyl nitrate (Sigma), followed 20 min later by a subcutaneous injection of 335 mg/kg pilocarpine hydrochloride (Sigma), as previously describedMice were decapitated under deep isoflurane anesthesia , brains were quickly removed and sectioned into 400 μm slices using a vibratome (Leica). Whole CA1 was carefully microdissected using two dissection needles by visual inspection in an optical microscope (Olympus). Total RNA was isolated using the miRNeasy micro kit (Qiagen) according to the manufacturer’s protocol. The quality and integrity of total RNA was assessed using a Tapestation 2200 (Agilent Technologies). RNA was considered as intact with an RNA Integrity Number (RINe) > 7. Purification of mRNA was performed using polyT oligo-attached magnetic beads. After purification, mRNA was used for library preparation using the TruSeq RNA Library Prep Kit v2 (Illumina) according to the manufacturer’s protocol. Sequencing was carried out on a HiSeq1500 system (Illumina) using cycle paired-end sequencing.16. Gencode mouse annotations  were used throughout17. For building genome indices and mapping, STAR version 2.7.8a was used. For genome indices, gtf and genome fasta files were provided to STAR as parameters –sjdbGTFfile and –geneFastaFiles with –runMode genomeGenerate to generate indices. –sjdbOverhand was set to 99 (read length—1)18. All other parameters remained default. Adapter trimming was performed using trimgalore version 0.6.6 (implemented in python version 3.8.5) and run in paired-end mode (using the –paired parameter)19. Adapters trimmed were “–illumina”. Sequence end soft clipping was performed using the default phred score of 20 and paired reads less than 20 bp for both reads were discarded. All other parameters were default. For mapping of RNA reads, STAR was run with parameter “–runMode alignReads” and paired (trimmed) reads input to the –readFilesIn parameter. Inputs for “—sjdbGTFfile” and “—genomeDir” parameters were the index described and gtf file described above. Non-default parameters were: –outSAMtype BAM Unsorted; –outFilterMultimapNmax 20; –outFilterMismatchNmax 999; –outFilterMismatchNoverReadLmax 0.04; –outFilterType BySJout; –alignIntronMin 20; –alignIntronMax 1000000; –alignMatesGapMax 1000000; –alignSJoverhangMin 8; –alignSJDBoverhangMin 1; –sjdbScore 1. Output bam files were sorted with samtools version 1.10and reads summarized using htseq-count version 0.13.5 (implemented with python version 3.8.5)21. Non-default htseq-count parameters included: –format bam; –order = pos; –stranded no. All other parameters remained default. After an initial assessment of lane or pair specific biases, reads from multiple lanes were merged into a single fastq files for each pair.The reference assembly for the Mus musculus genome  was obtained from Ensembl23. ConsensusDE simultaneously conducts statistical analysis using voom (limma version 3.46.0), edgeR (version 3.32.1), and DESeq2 (version 1.30.1) with the additional option to remove unwanted sources of variation with RUV, allowing comparison of the performance of these three algorithms with and without the application of RUV27. A summarized object of the read counts and annotations was created using the consensusDE “buildSummarized” function. Non-default parameters included a ‘sample_table’ describing the experimental design, directory of the htseq-count files (described above), path to the gtf file (described above) and “filter = TRUE” for filtering low-counts. Differential expression was then performed using the “multi_de_pairs” functions using the summarized object output from “buildSummarized” and the following non-default parameters: paired = "unpaired"; ruv_correct = TRUE, norm_method = "all_defaults". The gtf file described above was also used as the input to “gtf_annotate”. All other parameters remained default.For summarizing read counts, consensusDE version 1.8.0 was used and differential expression analysis using R version 4.0530 . KEGG pathway analysis was used to determine the pathways consisting of differentially expressed genes (DEGs). Pathways without any link to DEGs were excluded from the analysis. To interpret the molecular function and biological process of the DEGs, Gene Ontology (GO) enrichment analysis was performed with the GO enrichment analysis and visualization tool (GOrilla), using the process, function and component ontology settings. TF-binding enrichment was performed, prioritizing TFs based on the overlap between DEG and TF targets assembled from ENCODE, ReMap, and individual publications; co-expression of TFs with other genes based on processed RNA-seq from TRANSFAC and JASPAR databases31. FDR corrected p values of 0.05 were considered significant.Kyoto Encyclopedia of genes and genomes (KEGG)32. Input gene expression data into the ‘bhc’ function were 12-h, 36-h and 72-h, versus respective time matched controls , normalized log ratios and the parameter ‘dataType’ set to ‘time-course’. Optimal clusters were extracted and the quantile distribution of gene sets belonging to each cluster subsequently plotted for visualization of gene expression patterns.Bayesian Hierarchical Clustering analysis was performed using the BHC R package version 1.42.0 to separate genes into groups based on their time-dependent expression profilehttps://cells.ucsc.edu/mouse-nervous-system/hippocampus/. “CA1” specific cells were extracted from the metaData and log normalized, scaled and centered counts using the ‘NormalizeData’ and ‘ScaleData’  functions of Sureat v4.0.333. Uniform Manifold Approximation and Projection (UMAP) dimensionality reduction was performed using the RunUMAP function from Seurat, with arguments ‘reduction’ set to ‘pca’ and ‘dims’ as 1:20, where the input data was the Principle Component Analysis (PCA) performed using the RunPCA function. Clustering analysis of cells was performed using the “FindNeighbours”  and “FindClusters” (screening resolution of 0.1–1) functions of Sureat. Clustering resolution 0.2 was selected by comparing annotated clusters defined in Zeisel with clustering results, splitting neurons into 4 classes of neurons and 8 clusters in total. Marker analysis was also conducted using the ‘FindMarkers’ function of Sureat for each cluster, with parameters ‘logfc.threshold = 0’ and ‘min.pct = 0’.Hippocampus specific single cell transcriptome counts, metadata and tSNE coordinates were downloaded from the UCSC Cell Browser on 10 October 2021: 34. Inputs to the CPM function of scBio were our RNAseq data described above  with defaults settings. ‘cellSpace’, was the CA1 specific UMAP coordinates generated above; ‘SCLabels’, were which the 8 clusters identified by clustering analysis and ‘calculateCI’ as well as ‘quantifyTypes’ were set to ‘TRUE’. Input data were limited to the genes that were present in both RNAseq and scRNAseq datasets. Predicted alignments of the BulkRNAseq data to cell types was extracted and plot onto CA1 specific UMAP space for each timepoint.Deconvolution of bulk RNAseq data to infer single-cell (SC) population state (or cell abundances) was then performed using the CPM (Cellulation Population Mapping) algorithm implemented in scBio v0.1.6p value ≤ 0.05) with predicted alignments of the BulkRNAseq data to cell types  were analyzed separately with the use of QIAGEN IPA 35. p Values of 0.05 were considered significant.Differentially expressed genes  on the protection of animals used for experimental purposes and ARRIVE guidelines.To decipher transcriptional changes early after pilocarpine-induced SE in the hippocampal CA1 subfield, we compared mRNA expression profiles of pilocarpine-induced SE animals and non-SE controls in hippocampal CA1 at five different time points, i.e. 6, 12, 24, 36 and 72 h after SE. Only minimal transcriptional changes were observed between the non-SE control samples at 12, 36 and 72 h as evidenced by the Principal Component Analysis (PCA) that showed strongly clustered control samples without large differences between the various time points and no overlap with the samples from the SE-experienced mice , allowing a direct comparison between SE and non-SE controls. Of the 18,153 genes analysed, 4680 (12 h), 3640 (36 h), and 2384 (72 h) genes were differentially expressed after pilocarpine-induced SE  were differentially expressed at all three comparisons . All five time points after SE were analysed. Most changes were observed when comparing 12 and 24 h after SE (414 DEGs), followed by comparing 6 and 12 h after SE (205 DEGs)  and the 50 most decreased (“downregulated”) genes. Using k-means clustering, we grouped these genes based on their expression patterns. For the up- and the down-regulated group, we found five clusters and four main clusters, respectively Fig. C.To further unravel the molecular cascades in more detail, additional GO functional annotation analyses were performed on all DEGs at 12, 36 and 72 h after SE. Downregulated DEGs corresponded to pathways associated with GO terms related to chromosome organization, RNA processing, intracellular protein transport, protein ubiquitination, synaptic signalling and neuronal differentiation, indicating a clear reduction in neuronal activity in the early phases of epileptogenesis Fig. A.Figure Subsequent Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of the upregulated genes confirmed that most KEGG terms were related to inflammatory processes Fig. B. The cy36. Recently, we have identified several key transcriptional control mechanisms of CA1 pyramidal burst firing activity, namely transcriptional activation by the transcription factors Metal Regulatory Transcription Factor 1 (Mtf1) and Early Growth Response 1 (Egr1)37. Consistent with our previous data37, we observed a significant increase in Mtf1 and Egr1 expression at 12 h after SE, which had returned to basal levels at 24 h , although the strongest overall enrichment was observed at 12 h after SE . Two TFs that form heterodimers with Nfkb1, i.e. REL Proto-Oncogene (Rel) and RELA Proto-Oncogene (Rela)38, were also significantly enriched in the early phases after pilocarpine-induced SE. A strong enrichment was also observed for the proto-oncogenes FBJ osteosarcoma oncogene (Fos) and Jun (Jun), two TFs known as immediate early genes (IEGs), a group of TFs that also includes the previously identified epilepsy-associated TF Egr1  and interferon regulatory factor 8 (Irf8)40, were enriched only after 72 h, suggesting that microglial activation occurs at this later time point. Intriguingly, a more detailed analysis of the microglial and astrocytic markers confirmed the markedly increased expression at this later time point  was performed. TFEA prioritizes TFs based on the overlap between the DEGs and annotated TF targetsr1 Figs. B7,8. Intint Fig. B.To further evaluate similar changes in mRNA levels in the time series during early epileptogenesis, we then applied a model-based Bayesian hierarchical clustering (BHC) algorithm to the time series. In total, 30 gene clusters were found by grouping DEGs  and contained genes that showed the largest differences at 72 h after SE  for “cluster 28” (“Hap1 cluster”) and Hes5 for “cluster 30” (“Hes5 cluster”). For the “Hap1 cluster”, most of the observed GO terms belonged to GABA and glutamate receptor signalling and for the “Hes5 cluster”, cascades related to potassium and metal ion transport were found  was found to be enriched in all three immune-related clusters. In addition, two members of the Runt-related transcription factor family (i.e. Runx1 and Runx2), were also highly enriched in all three clusters  and Neuron Restrictive Silencer Factor (Rest) TFs  with mRNA temporal dependency, the resulting cell type populations were combined with our BHC algorithm to determine the individual contribution of each cell-type to the different temporal clusters, Fig. A. Among Tnf), transforming growth factor-beta (Tgf-β1), cAMP responsive element binding protein 1 (Creb1), IL-1β, Ifn-γ, and IL-6 highly overlap with the DEGs of all these cell populations  and Peroxisome Proliferator-Activated Receptor Gamma Coactivator 1-Alpha (Ppargc1a)   in a predicted activated state  Upstream Regulator Analysis to identify the upstream molecules that may be responsible for gene expression changes observed in each of our populations. In the case of the “non-neuronal” populations, regulators like tumour necrosis factor  Fig. D. This iate Fig. B. These Despite its transient nature, SE represents a fundamental insult to the affected brain structures. SE is immediately detrimental and induces long-term neuronal network reorganization that predisposes to chronic seizures. An in-depth understanding of the key transcriptional signalling cascades directly triggered by SE may therefore provide new insights into the pathomechanisms that initiate epileptogenic processes.Nfkb1, Rel and Rela) and several IEGs , to play a key role in organizing gene expression modules at the earliest stages post-SE  suggests alterations in non-cell-type-specific processes such as “chromosome organization”, “intracellular transport”, and “protein ubiquitination”, two major sets of transcript clusters represent substrates of induced (a) innate inflammation and (b) complex shifts in neuronal excitation. Both clusters appear to be regulated by distinct sets of only a few TFs. Our overall non-cell-type-specific TF analysis revealed a rather limited number of relevant TFs, including components of the Nfkb pathway , Ppard (peroxisome proliferator activator receptor delta), and two members of the Runx family (i.e. Runx1 and Runx2) correlated strongly with alterations in immune processes. Spi1 is critical for microglial survival, but also plays a key role in the development of macrophages, neutrophils, and T and B cells72. In addition, it has been reported to work in concert with Irf8 to activate microglia73. These data suggest that a very small set of TFs induces distinct inflammatory cascades and is associated with the activation of mainly reactive glia-mediated immune mechanisms shortly after SE. At the cellular level, innate inflammatory astroglia and microglia, rather than adaptive immune cells constitute the major early cellular infiltrates in CA1 affected by an epileptogenic brain insult. Clearly, microglial and astroglial infiltrates created a persistent immune stress environment in the affected CA1, and as the disease progresses further, induced neuronal plasticity becomes more important; the transcriptional profiles recapitulate the transition from early, more general metabolic and immune cellular processes to altered neuronal mRNA signatures, showing the switch from the initial insult, affecting non-cell type-specific processes to direct epileptogenic effector alterations of individual neuronal populations. The integration of these processes and transcription factors point to the hypothesis that a limited number of upstream regulators, for example Creb1, might orchestrate the transcriptomic alterations of neuronal and non-neuronal populations.Our TF analysis after deconvolution and IPA analysis revealed that the TFs 78. Moreover, the functional annotation of the “Hap1” cluster to GABA and glutamate receptors may imply a more general imbalance in inhibitory and excitatory synaptic transmission. These results imply that changes at the transcriptional level promote mechanisms that dysregulate genes associated with excitability, and thus promote channelopathies even in this early stage of epileptogenesis. These early changes in ion channel gene expression are also visible in the single-gene expression data for several ion channels; including the ion channels Gabra5, Chrna3, Chrm2/m3 and Kcnip2.This interpretation is based on the finding that 72 h after SE, primarily neuron-associated gene sets  were observed to be altered. The most strongly affected neuronal populations are clustered within the “Hap1” and “Hes5” clusters. Alterations were found at multiple levels, including changes in potassium ion transport, G protein-coupled peptide receptor activity, hedgehog signalling, and calmodulin-dependent protein kinase activity, confirming the contribution of these cascades in the process of epileptogenesis79. After an initial prominent increase in expression of the IEGs promoting aberrant ion channel gene expression, most IEGs return back to basal expression levels within 72 h. The transcriptional repressors Suz12 and Rest were related to the genes showing a downregulation early after pilocarpine-induced SE and were strongly associated with hyperexcitability and GABA/glutamate receptor activity. Both TFs are master regulators of gene silencing, and both have been reported to be differentially expressed in the early phases of epileptogenesis in other animal models81. Our results revealed a strong augmentation of Rest mRNA levels mainly 12 h after SE. For Suz12, less variation in mRNA expression was detected early after pilocarpine-induced SE. However, prolonged TF enrichment of the downregulated genes associated with Suz12 was observed, implying a complex interaction between Suz12 and its target genes. These findings reveal a complex interaction between different pathways and TFs that promote aberrant neuronal development and communication. Moreover, our IPA analysis showed that several neurodegenerative and hyperexcitable processes are predicted to be driven by Nfel2l2 and Ppargc1a. Nfel2l2 is a transcription factor that regulates the expression of antioxidant genes like Ppargc1a82. Therefore, these genes are involved in orchestrating the cellular response to oxidative stress83. Targeted delivery of antioxidant genes demonstrate the potential to ameliorate other diseases characterized by oxidative stress-induced cell degradation84, indicating the potential neuroprotective effects of Nfel2l2 and Ppargc1a in the process of epileptogenesis.Augmentation of IEG expression strongly correlates with neuronal activityTnf, Creb1, IL-1β, Ifn-γ, IL-6, Nfel2l2, and Rest) that are involved in multiple pathogenic processes across different cell populations. Nevertheless, we point out to the complexity of simultaneous processes in early epileptogenesis. On the one hand, promoting neuroinflammation, where we have found new possible therapeutic targets associated with the astrocytic-microglia axis including the Nfkb and Trem1 signalling pathway, as well as the multiple cytokines involved in neuroinflammation . On the other hand, transcription factors associated with hyperexcitability  as well as genes associated with the reduction of oxidative stress (Ppargc1a and Nfel2l2).Our findings demonstrate vast transcriptomic changes that occur in early epileptogenesis in a complex network of altered transcription factors and pathways. We clearly identify the responsible TFs and TF-dependent transcriptional signatures that mediate the processes at the earliest stages after SE and provide targets for future therapeutically intervention to halt epileptogenesis. Furthermore, our results point to possible interventions on upstream regulators (i.e. Supplementary Figure 1.Supplementary Figure 2.Supplementary Figure 3.Supplementary Figure 4.Supplementary Table 1.Supplementary Table 2.Supplementary Table 3.