The results are consistent with findings in our previous studies on Parkinson’s disease, but are put into a bigger theoretical frameset.Auditory repetition suppression and omission activation are opposite neural phenomena and manifestations of principles of predictive processing. Repetition suppression describes the temporal decrease in neural activity when a stimulus is constant or repeated in an expected temporal fashion; omission activity is the transient increase in neural activity when a stimulus is temporarily and unexpectedly absent. The temporal, repetitive nature of musical rhythms is ideal for investigating these phenomena. During an fMRI session, 10 healthy participants underwent scanning while listening to musical rhythms with two levels of metric complexity, and with beat omissions with different positional complexity. Participants first listened to 16-s-long presentations of continuous rhythms, before listening to a longer continuous presentation with beat omissions quasi-randomly introduced. We found deactivation in bilateral superior temporal gyri during the repeated presentation of the normal, unaltered rhythmic stimulus, with more suppression of activity in the left hemisphere. Omission activation of bilateral middle temporal gyri was right lateralized. Persistent activity was found in areas including the supplementary motor area, caudate nucleus, anterior insula, frontal areas, and middle and posterior cingulate cortex, not overlapping with either listening, suppression, or omission activation. This suggests that the areas are perhaps specialized for working memory maintenance. We found no effect of metric complexity for either the normal presentation or omissions, but we found evidence for a small effect of omission  New musical forms and experiments often challenge established structural forms in composition or reshape old ones into new uses, reordering fundamental musical building blocks to challenge the perception of music. The challenge of studying such diverse music in a principled and systematic manner within a context of neuroscience demands first to establish some fundamental and perhaps common mechanisms in music perception, a work that has been flourishing in the last decades. In this article, we focus on rhythm, one of these fundamental building blocks. Within new music, some artists work with rhythmic entropy while others try to dispel rhythm altogether. Insights into some basic mechanisms of the “listening apparatus” in our nervous system as they pertain to perception of musical rhythms might perhaps still be of use to both researchers and artists, either as a starting point for more advanced research or as a starting point of artistic defiance.present, omission activation is the increased neuronal activity that occurs when an expected sound is not present. Listening activates bilateral superior temporal cortices, independent of whether we are exposed to tones, words, animal, and instrumental sounds , the basal ganglia, as well as large-scale networks across the brain .complexity on repetition suppression and omission activation and the effect of positional saliency on omission activation. To this end, two musical rhythms, one simple and one complex, were presented several times to the participants during scans. The first part of the stimuli presentation consisted of a short presentation (16 s) of continuous, unperturbed rhythmic repetition to examine repetition suppression, segueing into a longer continuous presentation of the same rhythm. In this second part, an overt target-detection task (with a quasi-randomly distributed deviant tone) was introduced to keep the participant attending to the rhythm, while quasi-randomly distributed beat omissions were used to covertly examine omission activation .We also wanted to examine the effect of pattern positional saliency would modulate omission activation, where a more salient position (beat position number one) would show higher activation than the less salient position (beat position number two). Finally, we hypothesized that there would be an interaction between pattern complexity and beat position for omission activation.Based on previous literature, we expected to see listening, repetition suppression, and omission activation in largely overlapping areas in the temporal cortices, with omission activation occurring in more posterior areas than suppression and maintenance. We hypothesized that representation maintenance would also occur in the temporal cortices, with additional activation of inferior frontal areas, insula, and premotor cortices. We hypothesized that complexity would differentially affect suppression, as the encoding stage presumably would be affected by a higher cognitive load for the complex rhythm. We also hypothesized that omission activation would be modulated by rhythmic context where the cognitive demand  of the more complex rhythm would result in smaller omission sizes, and furthermore that Participants were recruited among Norwegian-speaking students enrolled at the University of Bergen (UiB). Fourteen participants underwent scanning with fMRI, but four were excluded due to head movement in the scanner. Analyses were done on the remaining 10 . Eight were right-handed by self-report. The number of years participants had played instruments (outside mandatory music lessons in public school) was done by self-report. A participant was labeled as a musician if s/he had 5 or more years of consistent instrument practice, and 5 out of the 10 participants reached this target. Personal data were coded and stored offline and anonymity was assured. All procedures were approved by the Regional Committee for Medical and Health Research Ethics (REK no 2014/1915) and carried out in accordance with the code of Ethics of the World Medical Association, Declaration of Helsinki. Upon enrollment in the study, all participants gave written informed consent to participate in the study and were rewarded 50NOK for their participation.We used two musical rhythmical stimuli of different rhythmic complexity described elsewhere , 2019. TParticipants were given earplugs and were placed comfortably in the scanner. They were given fMRI-compatible headphones with additional physical noise cancelation foamed ear plugs. Participants were also fitted with fMRI-compatible video goggles and a handgrip with buttons to respond to the overt target-detection attentional task. After initial structural scans and a 5-min-long resting-state fMRI scan (not part of this report), goggles were turned on and participants were given instructions for the study. Participants were told to keep eyes open and look at a cross in the middle of the screen and asked to press a button on the hand grip when the probe tone was detected. Instructions were followed by a short test run before scanning started. Before each trial, the same written instructions were repeated in the goggles (4.5 s), followed by a blank screen and silences ranging from 13 to 19 s. When the music stimuli began playing, a cross was presented in the goggles as a focus point to minimize head movement. Each sound file was presented twice during the scan, in randomized order between subjects. Total scan time for the paradigm was 33 min. See 3 voxel size), and smoothing with Gaussian kernel (5 mm3).fMRI images were acquired using a 3-T scanner (GE Signa Excite 750) with a 32-channel coil. Repetition time (TR) for the EPI sequence was 1.5 s, echo time (TE) was 30 ms, voxel size was 3.44 × 3.44 × 5 with 28 slices interleaved, for 1325 volumes. Pre-processing steps included realignment , unwarping (using 12 × 12), resliced to mean image, normalized to ICBM template  to 13th of the 28 interlaced slices. A high-pass filtering threshold was set at 1/249 Hz cutoff . Single-subject data were analyzed by specifying a general linear model, and for the whole scan, movement-related variance  was included in the model as six covariates of no interest.Each block was modeled as follows: 4.5 s of on-screen instructions were labeled as “READ.” Silence periods (randomly assigned between 13 and 19 s) between each block were not segmented and thus served as contrast for all other epochs (“REST”). The whole block was segmented into 2-s bins, i.e., the total length of one whole rhythmic pattern. The first 4 s of each block were labeled “LEARNING”; the next 12 s, “SUPPRESSION.” In the following 88 s of each block, bins containing a probe tone were labeled “PROBE,” bins containing the normal, unperturbed version of the rhythmic pattern were labeled “MAINTENANCE,” while 2-s bins containing an omission were labeled according to the position of the omission . The 2-s bin immediately following an omission was labeled “NOT OF INTEREST” to avoid any secondary effects of the omission spilling into the segments labeled “MAINTENANCE.”All blocks were divided into simple and complex rhythm, and segmentation of different epochs were labeled “SIMPLE” or “COMPLEX.” For example, the “LEARNING” epochs in the simple rhythm were called “SIMPLE_LEARNING”; for the omission in position 2 in the complex rhythm: “COMPLEX_OMISSION2.” First-level analysis produced 10 contrasts for “SIMPLE/COMPLEX” blocks, with “LEARNING/SUPPRESSION/MAINTENANCE/OMISSION (1/2)” epochs, all with REST epochs subtracted for the contrasts.p < 0.05, with a minimal voxel-cluster size of at least 10 voxels. No main effect or interaction effects were found for neither MUSICIAN nor RHYTHM, but as expected, a main effect for TYPE was found. Since we had a clear hypothesis on omission complexity and position, we did, however, probe these comparisons through t-tests, but did not find any significant differences on omission, neither between rhythms nor positions at a FWE-corrected level. For completeness, we would nonetheless mention that at an uncorrected level , we found higher activation in an area in the anterior cingulate cortex (ACC)/medial prefrontal gyrus , RHYTHM (“SIMPLE/COMPLEX”), and TYPE [“LEARNING/SUPPRESSION/MAINTENANCE/OMISSION (1/2)] as dependent factors. The analysis was examined with a threshold of family-wise error (FWE) correction for multiple comparisons at yrus see .t-test results on OMISSION, we decided to re-segment the data, dispelling of the division into two rhythms, as well as omission position. Furthermore, based on the lack of main and interaction effects of the categorical MUSICIAN group division, we instead included the number of years playing an instrument as a covariate in the analysis. A new full factorial analysis was therefore conducted using only TYPE as dependent factors, i.e., “LEARNING/LISTENING/MAINTENANCE/OMISSION.” A main effect for TYPE was found , and we proceed to do t-tests for our planned comparisons.Based on the lack of main and interaction effects for RHYTHM, and lack of significant p < 0.05 and at least 10 voxels per cluster. All results are reported with a FWE-corrected threshold of For the combined LEARNING, SUPPRESSION, and MAINTENANCE bins, we found activations in large parts of bilateral superior and middle temporal gyri (STG/MTG), as well as bilateral angular gyri, SMA, cerebellum, and posterior areas  .We contrasted the first 4 s of the introduction of music, LEARNING, by subtracting the following 12 s of SUPPRESSION. This showed more bilateral activations across many areas, including STG, angular gyri, and cerebellum (crus 1 and vermis 6), the basal ganglia (caudate nucleus and putamen), and thalamus, in the first 4 s .We subtracted the last of the 12 s of the initial listening (SUPPRESSION) from MAINTENANCE to examine which brain areas, after the initial listening period, showed more activation during maintenance of the rhythm throughout the remaining 88 s. The rationale behind this contrast was that after the first 4 s (LEARNING), the next 12 s (SUPPRESSION) consolidates the (reduced) neural activation related to the establishment of a predictive model of the rhythmic pattern, while MAINTENANCE represents additional areas needed to keep the rhythmic pattern in working memory pertaining to the overt task. Areas including SMA; caudate nucleus; anterior insula (AIN); superior, middle, and inferior frontal gyrus (SFG/MFG/IFG); and middle and posterior cingulate cortex, as well as parts of the occipital cortex, showed more activation during MAINTENANCE than during SUPPRESSION .We contrasted OMISSION by subtracting MAINTENANCE to examine which brain areas were activated during beat omissions. The rationale behind this contrast was that MAINTENANCE, as stated above, represents areas needed to keep the rhythmic pattern in working memory, while OMISSION represents the neural activation related to the prediction error triggered by the missing beat.For OMISSION, more activation was seen, predominantly in the right MTG, extending from the inferior to the superior temporal gyrus. In addition, a smaller activation was seen in the left MTG as well as in the right angular gyrus .Listening to musical rhythms predictably activated the bilateral STG as well as bilateral angular gyrus. Areas in the STG attenuated after the first 4 s of repetition of the rhythmic patterns overlapped exclusively with these areas, with the size of deactivation being larger in the left STG. In addition, activity in bilateral cerebellum, and the (predominantly right) basal ganglia, including caudate nucleus, putamen, and thalamus, decreased after the first 4 s. Since processing of music  and partDuring the prolonged listening to rhythms after the initial 16 s of encoding, larger activity was found in the SMA and the caudate nucleus, areas well known to be activated by rhythm . Areas rOmission activation was distinctly more posterior than listening, suppression, and maintenance, located predominantly in the MTG, and, as expected, omission activation was significantly bigger in the right MTG  see Fig, with coIn addition, at uncorrected levels, the more salient position of the omission showed a higher activation in the ACC, consistent with previous research implicating the ACC in saliency detection  Supplem.On a theoretical level, our findings can be interpreted as manifestations of crucial principles in predictive processing frameworks, where repetition suppression  can be in = 10) taken from a homogenous population of Western Educated Industrialized Rich Democratic (WEIRD) students of psychology, our findings are difficult to generalize. During a continuous scanning paradigm, the scanner is never silent, which makes the study of omissions questionable, although our results are consistent with previous research. Previous studies have also shown differences in omission detection between musicians and non-musicians . Importantly, our findings show a clear separation between repetition suppression and prediction error activation, and additionally indicate that representational maintenance activates areas different from those deactivated during repetition suppression. While listening and subsequent repetition suppression were located mainly in anterior parts of the superior temporal gyrus, prediction errors (omission activation) were clearly separated from these areas and located mainly in posterior parts of the MTG. Representational maintenance activated SMA, caudate nucleus, anterior insula, frontal areas, and middle and posterior cingulate cortex, potentially showing persistent representational maintenance activity in areas separate from initial listening (encoding), repetition suppression (attenuation), and prediction error (omission).Our study successfully replicated previous findings for repetition suppression and omission activation and shows that tailored musical stimuli can be used in an fMRI setting to robustly investigate such neural phenomena, even with a limited number of participants . The patients/participants provided their written informed consent to participate in this study.UF, KS, and KV contributed in the conception of the research project, did statistical analysis, and contributed to the final version of the manuscript. UF recruited the participants, organized the study, and wrote the first draft. KV designed the paradigm. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Mast cells (MCs) perform multiple functions thought to underlie different manifestations of allergies. Various aspects of antigens (Ags) and their interactions with immunoglobulin E (IgE) cause diverse responses in MCs. FcεRI, a high-affinity IgE receptor, deciphers the Ag–IgE interaction and drives allergic responses. FcεRI clustering is essential for signal transduction and, therefore, determines the quality of MC responses. Ag properties precisely regulate FcεRI dynamics, which consequently initiates differential outcomes by switching the intracellular-signaling pathway, suggesting that Ag properties can control MC responses, both qualitatively and quantitatively. Thus, the therapeutic benefits of FcεRI-targeting strategies have long been examined. Disrupting IgE–FcεRI interactions is a potential therapeutic strategy because the binding affinity between IgE and FcεRI is extremely high. Specifically, FcεRI desensitization, due to internalization, is also a potential therapeutic target that is involved in the mechanisms of allergen-specific immunotherapy. Several recent findings have suggested that silent internalization is strongly associated with FcεRI dynamics. A comprehensive understanding of the role of FcεRI may lead to the development of novel therapies for allergies. Here, we review the qualitatively diverse responses of MCs that impact the attenuation/development of allergies with a focus on the role of FcεRI toward Ag exposure. Recently, allergies have emerged as a public health problem, as over one-quarter of the population in industrialized countries is affected and the prevalence of allergies is increasing . PathophMast cells (MCs) initially respond rapidly to exogenous Ags, which is the principal initial effector immune response involved in modulating allergic inflammation ,4,5. Ag-FcεRI, the high-affinity IgE receptor, distinguishes Ag–IgE interactions and drives cellular allergic responses . FcεRI iThe high-affinity IgE receptor, FcεRI, is primarily expressed on MCs, basophils, and Ag-presenting cells, and mainly exists as the heterotetramer αβγ2. However, there are differences among species; an alternate trimeric form αγ2 is expressed on human, but not rodent. The αβγ2 consists of a single-membrane-spanning α-subunit that contains the IgE-binding domain, a tetra-spanning β-subunit that contains a single immunoreceptor tyrosine-based activation motif (ITAM), and two γ-subunits that exist as a disulfide-linked homodimer and also contain one ITAM each. The importance of the α-subunit in the FcεRI-mediated allergic reaction was demonstrated by the absence of allergic reactions in α-subunit-deficient mice . The FcεMultivalent Ags cause cross-linking of the IgE–FcεRI complex, triggering signaling cascades that result in the release of preformed mediators stored in granules. In response to Ag, Lyn kinase phosphorylates the ITAMs of FcεRIβ and FcεRIγ, which initiates a complex signaling cascade involving a series of membrane-associated and cytoplasmic signaling molecules ,16,17,18In the cell membrane, the IgE–FcεRI complex diffuses freely under resting conditions. Multivalent Ag binding to IgE leads to the reorganization of FcεRI into large aggregates on the cell surface within seconds to minutes, which causes a transition in the receptor from a diffuse state to a highly immobile state . This beThe same group also investigated the spatial/density regulation of the FcεRI clusters of MC, and they demonstrated that the FcεRI redistribution in regions of the membrane after Ag stimulation is also remarkable for the complexity of the FcεRI dynamics and signaling initiation. Sequential images of IgE–FcεRI complexes, assessed by total internal reflection fluorescence (TIRF) microscopy, have been used to observe the dynamics of receptor redistribution upon contact with the ligand. Importantly, Carroll-Portillo et al. demonstrated that small mobile clusters coalesced into large, cholesterol-rich patches that occupied the central portion of the contacting membrane and are likely composed of smaller aggregates in the same region, suggesting that dense populations of mobile receptors could initiate low-level degranulation . These fThese examples illustrate the importance of FcεRI dynamics and subsequent cellular responses at a low Ag concentration or valency, which in turn drive the formation of small and mobile FcεRI clusters that were previously considered a simple and diminished  response. Signaling diversity is significantly related to FcεRI dynamics. Src-homology-2-containing inositol phosphatase (SHIP) is a negative regulator of MCs , and itsThose studies were performed using concentration- and valency-adjusted agents. The Ag properties and their interactions with IgE are important for determining FcεRI dynamics and the initiation of subsequent cellular reactions, as discussed below in Naturally encountered allergens are typically complex and structurally heterogeneous proteins with multiple epitopes . Moreove2+ mobilization in MCs, which results from intracellular Ca2+ release from the endoplasmic reticulum (ER) and subsequent extracellular Ca2+ influx, is important for degranulation. Comparing the intracellular Ca2+ responses under optimal and supra-optimal concentration stimulation demonstrated markedly different Ca2+-mobilization patterns [2+ release from the ER was slightly stronger at a supra-optimal Ag concentration. The supra-optimal Ag concentration resulted in a transient increase in intracellular Ca2+, whereas the optimal Ag concentration showed a sustained pattern [The influence of the Ag concentration on FcεRI dynamics has been elucidated; degranulation in MCs displays a remarkable bell-shaped response with increasing Ag concentrations ,37. Thispatterns . In part pattern , suggest pattern . However pattern ,41. The  pattern . Intrigu pattern . Taken t24-BSA stimulation resulted in the rapid formation of stable, moderately sized clusters with typical levels of RBL-2H3 degranulation. The mobile monovalent ligand showed a high density of mobile receptors, in which thousands of mobile receptors were densely packed in the centralized region of the ventral membrane, despite the lack of direct crosslinking [The Ag valency is also an important factor in controlling the signal intensity as well as Ag concentration. Naturally occurring allergens are the most common complex type of multivalent proteins. Despite the small size of the timothy grass pollen allergen, Phl p 5, it is known to be highly allergenic and has multiple independent IgE epitopes ,43. In eslinking . With reslinking ,45, whicslinking ). AlthouFcεRI functionally distinguishes differences in the affinity of IgE antibodies for different Ags. Naturally occurring polyclonal IgEs show heterogeneity with different affinities against Ags . DiffereThis information may help in developing novel strategies for controlling FcεRI clustering in MCs and the subsequent allergic responses. A recent report by Mahajan et al. demonstrated that not only the valency and concentration of an allergen, but also the FcεRI occupancy with IgE, help set the thresholds for MC effector responses . High-afFcεRI displays diverse dynamics  and IgEs show heterogeneous properties. The functional responses of FcεRI may be studied to decipher the characteristics of endogenous Ags and/or their interactions with IgEs, and to regulate MC-dependent allergic responses, thereby enabling further elucidation of the clinical relevance of human allergic responses.FcεRI has been targeted for clinical benefits to inhibit or attenuate MC degranulation, and effective clinical approaches for suppressing IgE-dependent MC activation have emerged ,52. OmalDARPins are small molecules and highly stable non-antibody protein scaffolds. Anti-IgE DARPins, which are genetically engineered proteins comprising a varying number of stacked ankyrin-repeat domains, also block IgE binding to FcεRI. Ankyrin-repeat domain binding can affect the stability and effector functions of target proteins. The motivation for engineering DARPins was to generate binding proteins that can be used to target proteins with high affinity and specificity, essentially replacing the use of monoclonal antibodies ,70. TherRubia cordifolia and Dianthus superbus in China; KOTMIN13 (composed of Inula japonica flowers), Trichosanthes kirilowii semen, Peucedanum praeruptorum radix, and Allium macrostemon bulbs in Korea [Paeonia radix and Zanthoxyli fructus in Japan, suppress MC degranulation and murine allergic inflammation [Natural products, including herbal medicines and nutritional supplements, have been reported to inhibit MC degranulation. The underlying mechanisms appear to involve the blockade of IgE–FcεRI binding or IgE-mediated FcεRI signaling. For example, carotenoids suppress Ag-induced FcεRI aggregation and inhibit FcεRI-mediated intracellular signaling . Procyanin Korea ; and Paeammation ,78. Thesammation . Mao sigammation .Inhibitory signaling against FcεRI is another candidate for FcεRI-targeting therapy, which is mediated by co-crosslinking ITIM-containing inhibitory IgG receptor (FcγRIIb) with FcεRI. FcγRIIb is highly expressed in murine MCs, murine basophils, and human basophils. Previous findings demonstrated that MCs isolated from human skin only express the activating FcγR and FcγRIIa proteins, whereas human cord blood-derived cultured MCs only express FcγRIIb ,81, implAllergen-induced FcεRI desensitization, which is achieved by sequentially increasing allergen stimulation from a suboptimal concentration and is accompanied by FcεRI internalization without MC (basophil) activation, is an important mechanism underlying allergen-specific immunotherapy . This isModifying the properties of Ags has also been recognized as a potential strategy for improving immunotherapeutic efficacies . A wide 2+ flux and intracellular vesicle tracking [To explore the mechanisms underlying FcεRI desensitization in MCs and cell-specific local responses during allergen-specific immunotherapy, in vitro desensitization studies have been performed by several different groups ,100,101.tracking  and thattracking . Howevertracking ,103. TheTaken together, these data reviewed above indicate that specific features of FcεRI dynamics appear to be involved in FcεRI desensitization in MCs. With therapeutic interventions based on FcεRI desensitization, ideal Ags may be those that can flexibly and generally induce small FcεRI clusters and regulate moderate FcεRI dynamics, which may contribute to the appropriate regulation of FcεRI clusters that are small and may be mobile, diffuse, and compete for internalization . HoweverAdequate regulation of FcεRI dynamics is a potential intervention strategy for controlling MC qualitative functions and allergic inflammation. FcεRI may actively adjust cellular responses even when no considerable degranulation occurs immediately after Ag challenge, which is likely to contribute to improving FcεRI targeting therapy.FcεRI displays dynamic changes in response to the properties of Ags and IgEs, which induce differential signaling pathways that regulate MC functions. A complementary mechanism may exist, even after weak or simple input patterns. FcεRI on the MC responds to the stimulation intensity/quality and translates it into an appropriate MC response. Taking advantage of this FcεRI characteristic may improve FcεRI-targeting therapeutics, especially FcεRI desensitization and Ag-specific immunotherapy for allergies.


The expression of GST A3-3 in steroidogenic tissues suggests that the enzyme has evolved to support the activity of 3β-hydroxysteroid dehydrogenase, which catalyzes the formation of 5-androsten-3,17-dione and 5-pregnen-3,20-dione that are substrates for the double-bond isomerization catalyzed by GST A3-3. The dehydrogenase also catalyzes the isomerization, but its kcat of approximately 1 s−1 is 200-fold lower than the kcat values of human and equine GST A3-3. Inhibition of GST A3-3 in progesterone-producing human cells suppress the formation of the hormone. Glutathione serves as a coenzyme contributing a thiolate as a base in the isomerase mechanism, which also involves the active-site Tyr9 and Arg15. These conserved residues are necessary but not sufficient for the ketosteroid isomerase activity. A proper assortment of H-site residues is crucial to efficient catalysis by forming the cavity binding the hydrophobic substrate. It remains to elucidate why some mammals, such as rats and mice, lack GSTs with the prominent ketosteroid isomerase activity found in certain other species. Remarkably, the fruit fly Drosophila melanogaster, expresses a GSTE14 with notable steroid isomerase activity, even though Ser14 has evolved as the active-site residue corresponding to Tyr9 in the mammalian alpha class.In addition to their well-established role in detoxication, glutathione transferases (GSTs) have other biological functions. We are focusing on the ketosteroid isomerase activity, which appears to contribute to steroid hormone biosynthesis in mammalian tissues. A highly efficient GST A3-3 is present in some, but not all, mammals. The alpha class enzyme GST A3-3 in humans and the horse shows the highest catalytic efficiency with k Our understanding of the various physiological roles of the protein family referred to as glutathione transferases (GSTs) has progressed since their discovery in 1961 and continues to evolve. The first publications reported enzyme activity involving displacement of a halide ion from an aromatic compound, resulting in an S-substituted glutathione conjugate . Eric BoGSTs were first recognized as enzymes inactivating xenobiotics, in particular electrophilic mutagens and carcinogens, leading to their excretion as mercapturic acids . HoweverAn independent set of reports identified a remarkably abundant protein in liver with affinity for carcinogens, steroid hormones, bilirubin and synthetic dyes. The wide-ranging binding properties were similar to those of albumin in blood plasma and the name “ligandin” was therefore coined . The funA completely different binding function was uncovered when GST of the pi class was found to be an endogenous inhibitor of Jun N-terminal kinase (JNK), thereby contributing to regulation of a protein kinase responsive to cellular stress . MembersIn addition to the dimeric cytosolic GSTs, which are in focus in the present article, trimeric membrane-associated GST proteins, have also been identified. They are structurally unrelated to the soluble GSTs and the protein family has been named MAPEG (membrane-associated proteins in eicosanoid and glutathione metabolism), since some of the members act as leukotriene C and prostaglandin E synthases . In thisHomo sapiens GST composed of subunit 1 and subunit 2 in the alpha class. Members of the same GST class show high aminoacid identity in their sequences, whereas members of different classes usually show <40% identity.40 years ago scattered aminoacid sequence data were available for rodent and human GSTs. In combination with immunological cross-reactivities and functional data they formed the basis of an evolutionary tree . Three sIn the original analysis, classification appeared to be supported by functional data such as substrate selectivity and inhibition characteristics . HoweverPseudomonas bacteria  and 5-pregnen-3,20-dione (5-PD), and purified a highly active isomerase from bacteria .The enzyme, ketosteroid isomerase, obtained from several bacterial species has subsequently been extensively investigated by incisive structural and functional studies owing to its extraordinary catalytic efficiency . The pro−1 mg−1) in comparison with the five orders of magnitude higher activity of the Pseudomonas enzyme .The discovery of human GST A3-3 (HsaGST A3-3) and its association with steroidogenic tissues  promptedectively  ranking ectively , even th8 M−1s−1  approachBtaGSTA1-1, an alpha class GST identified in tight association with bovine steroidogenically active cells and shown to be hormonally regulated by gonadotropins in the bovine ovarian follicles, appeared to be a likely isomerase . HoweverBased on mutational studies of human GSTs the five H-site residues in positions 10, 12, 111, 208, and 216 were judged to be of particular importance for the ketosteroid isomerase activity . However−1 mg−1, 200-fold lower than the specific activities of the human and equine enzymes .The catalytic efficiency of HsaGST A3-3 with 5-AD is 5000-fold higher than that of HsaGST A2-2, and we found that mutating the five residues in the H-site of HsaGST A2-2 into the corresponding HsaGST A3-3 residues enhanced the efficiency to 70% of the HsaGST A3-3 value . StructuA static representation of the topology and electrostatic field in the H-site  will havtrans-2-nonenal representing reactive α,β-unsaturated aldehydes formed by lipid peroxidation  is the most prevalent in gonads and adrenal gland. A second isoenzyme (HSD3B1) is abundant in placenta, mammary gland and prostate. It is also reported that the 17β-hydroxysteroid dehydrogenases HSD17B1, HSD17B5, and HSD17B7 catalyze the C3 hydroxy oxidation . By contrast, the kcat values of the ketosteroid isomerase activity of human, equine, and marmoset GST A3-3 are two orders of magnitude higher, ranging between 204 and 261 s−1 (The double-bond isomerization following 3-hydroxy oxidation in the steroids is conventionally ascribed to an ancillary function of the dehydrogenase, displaying 3-ketosteroid isomerase activity in addition to the redox catalysis. The two human 3β-hydroxysteroid dehydrogenases have been investigated in detail by Thomas and coworkers e.g., , and the 261 s−1 .Our enzymological studies have established 5-PD and 5-AD as outstanding substrates for the equine and human GST A3-3 enzymes, and we predict that the corresponding 3-keto intermediates derived by oxidation of the 3-hydroxy groups of 17α-hydroxypregnenolone and androstenediol will also be substrates, although they have not yet been tested. As noted above, 5-cholesten-3-one is not showing any activity with the mammalian enzymes, presumably due to steric hindrance by the bulky sidechain .A recent investigation of the equine transcriptome in chorioallantois and endometrium at several time points throughout gestation has established GST A3-3 among the actors in endocrinology . Figure Further evidence for the physiological relevance of the GST isomerase activity derives from the coregulation of dehydrogenase and GSTA3 gene transcription in the horse . In geneThe available data suggest that GSTs have a supportive function, which can prevent the overproduction of the 3-keto delta5-steroids formed by hydroxysteroid dehydrogenases and thereby prevent product inhibition. In spite of data from cell studies, the quantitative importance of the GST contribution in living organisms is not known. Most likely, the influence will change with the activity of the steroidogenic processes. Conclusive studies in intact organisms have not been reported, partly in anticipation of a suitable animal model. Rodents such as rats and mice do not express a GST with high ketosteroid isomerase activity. Horse and pig have highly active GSTs, but are large animals not well suited for relevant experiments. Humans would not be investigated until animal data have been obtained. Possibly, the common marmoset could be considered as a model .Elucidation of the effects at the physiological level may lay the groundwork for medical applications to numerous conditions that are dependent on steroid hormones . CRISPR/Drosophila melanogaster plays an essential, but as yet mechanistically undefined, role in ecdysteroid hormone biosynthesis (Noppera-bo as GSTE14 in D. melanogaster (Noppera-bo result in embryonic lethality, embryonic cuticle abnormalities, and decreased ecdysteroid concentrations. Numerous other Dipteran and Lepidopteran insects have been shown to encode an apparently orthologous GST of the epsilon class (The function of GSTs in steroid metabolism in not limited to mammalian organisms, but has also been discovered in insects. The epsilon class GSTE14 in the fruit fly ynthesis . Ecdystenogaster . Like deon class . The epson class . A superon class .The endogenous substrate of the insect GST is unidentified, and neither 5-AD and 5-PD are known to occur in insects. The conservation of the orthologs to GSTE14 in other insects attests to an essential function, which merits further biochemical investigations.The soluble GSTs demonstrate admirable versatility as catalysts of chemical reactions encompassing aromatic and aliphatic substitution, Michael addition, transacylation, transnitrosylation, carbamoylation, reduction, and isomerization, and it has been demonstrated that modest structural modifications can drastically transmute the substrate selectivity profile . In fact


FRA16D common chromosomal fragile site was characterised and the WWOX gene spanning this site was identified. In this time, much information has been discovered about its contribution to disease; however, the normal biological role of WWOX is not yet clear. Experiments leading to the identification of the WWOX gene are recounted, revealing enigmatic relationships between the fragile site, its gene and the encoded protein. We also highlight research mainly using the genetically tractable model organism Drosophila melanogaster that has shed light on the integral role of WWOX in metabolism. In addition to this role, there are some particularly outstanding questions that remain regarding WWOX, its gene and its chromosomal location. This review, therefore, also aims to highlight two unanswered questions. Firstly, what is the biological relationship between the WWOX gene and the FRA16D common chromosomal fragile site that is located within one of its very large introns? Secondly, what is the actual substrate and product of the WWOX enzyme activity? It is likely that understanding the normal role of WWOX and its relationship to chromosomal fragility are necessary in order to understand how the perturbation of these normal roles results in disease.It is now more than 20 years since the  Rare fragile sites are only found in some individuals in the population. The rare fragile sites are due to expanded DNA repeats, with those individuals expressing the fragile site having a copy number above the threshold for cytogenetic appearance. A relationship of some sort exists between the chemistry of induction and the DNA sequence composition—AT-binding/substituting chemicals have AT-rich expanded repeats. Common fragile sites can be induced to appear in everyone’s chromosomes; however, they vary in their sensitivity to induction. Inhibitors of DNA polymerase induce most common fragile sites and their appearance is, therefore, related to replication. The common fragile sites vary in the frequency with which they respond to induction—the FRA3B site on human chromosome 3 being most readily observed, followed by FRA16D on chromosome 16, then others  co-factor binding site [WWOX orthologues of all species show significant, and as yet unexplained, homology in their C-terminal sequences  have a role to play in contributing to conformation of the catalytic site and/or the access of molecules to that catalytic site and, therefore, the specificity of the enzyme.Kavanagh et al. , in theiWWOX function are found in families with recessive spinocerebellar ataxia 12 (SCAR12). The G372R mutation located within the putative substrate specificity region indicates that this highly conserved C-terminal segment is vital for WWOX function, having the same clinical consequences as that of the P47T mutation located in the first WW domain of WWOX [WWOX substrate-specificity, they are potential targets in the identification of WWOX-based therapeutics.Of relevance, homozygous mutations that diminish  of WWOX . Given tWWOX in an effort to ascertain which biological pathways and processes WWOX contributes to [WWOX gene, a similar analysis of WWOX protein also adds to the mystery. Most organisms have a single clear orthologue of WWOX with the characteristic two WW domains. However, Caenorhabditis elegans and Opisthokonts (Casaspora owczarzaki) are notable exceptions in that their closest WWOX orthologues are devoid of WW domains. A host of PPY containing proteins have been identified by various means; however, the extent to which these contribute to functional interactions in vivo is not yet clear [The presence of two WW domains that are known to act as protein–protein interaction sites with PPY containing proteins has focussed much attention on the identity of the protein binding partners of butes to . In addiet clear .WWOX proteins from different species is the conservation of 15 amino acids that include part of the first WW domain  to produce a low steady-state level of WWOX protein.Another striking feature of the comparison of W domain . This seFRA3B/FHIT counterpart, the role of FRA16D/WWOX in cancer has been controversial [WWOX levels rather than its absence due to a second-hit mutation. Therefore, the altered abundance of WWOX metabolites appears sufficient for biological consequences, including poorer prognosis for cancers with reduced WWOX [WWOX enzyme activity suggests a build-up on one side of the equation, which leads to elevated levels of a metabolite and, therefore, has biological consequences. The identity of this metabolite, together with targeted methods to reduce its abundance, represent a plausible target for treating metabolic dysfunction due to perturbation of WWOX. Alternatively, if the product(s) of WWOX act as negative regulators or rate-limiting determinants of a metabolic process, then the activation of compensatory pathways such as those acting in Drosophila [WWOX deficiency.Notably, similarly to its ced WWOX ,58. Reduosophila  may prov


This often requires a comprehensive model setup. The following elements are needed: bathymetry , ice shelf draft (impacting water column thickness), oceanographic state , sea ice and atmospheric forcing. Moreover, a high spatial resolution is needed, at least locally, which may be augmented with a coarser and computationally cheaper (nested) model that provides sufficiently realistic conditions at the boundaries. Here, we describe procedures to systematically create such a setup that uses the Finite Volume Community Ocean Model (FVCOM) for the Petermann Fjord, Northwest Greenland. The first simulations are validated against temperature and salinity observations from the Petermann Fjord in September 2019. We provide  Specifications tableThe recent surge in mass loss rates from the Greenland Ice Sheet (GrIS) is largely driven by an increase in ocean heat flux at the marine-ice margins For this study, we chose the Finite-Volume Community Ocean Model (FVCOM) The computational grid in the horizontal direction is comprised of non-overlapping unstructured triangular cells, with 3 nodes, a centroid and 3 sides making up each unstructured triangle. The scalar variables such as temperature, salinity and sea-surface elevation are placed at the nodes whereas velocities u and v are placed at the centroids. In our setup, the irregular bottom and the PGIS draft are represented using terrain following sigma coordinates and the governing equations are solved in spherical coordinates under the hydrostatic approximation. An ice shelf module has been implemented into the FVCOM version Setting up the model requires an unstructured triangular grid, bathymetry and ice shelf draft, initial and lateral ocean boundary conditions, and sea ice and atmospheric forcing. The following sections describe procedures to systematically set up these specific components in detail. The performance of our first simulations using these components are discussed and validated against conductivity-temperature-depth (CTD) profiles that provide information on the vertical structure of temperature and salinity from the Petermann Fjord taken during the 2019 Ryder expedition The model grid was generated using Distmesh In the vertical direction, the bottom boundary of the modeling domain is given by the bathymetry of the ocean/fjord floor. The upper boundary is given by the draft of the floating Petermann Glacier tongue, and the height of the free surface seaward of its calving front. All heights are expressed relative to the mean sea level using the geoid eigen-6c4 . Lateral°N and 87°N and between 29°W and 81°W. The domain is designed to mainly cover the Nares Strait and the Petermann Fjord, and is divided into several polygons with different horizontal resolution  over any two adjacent wet cells e and e' in the σ-coordinate ocean model, with corresponding bathymetries h(e) and h(e'), respectively, satisfies r ≤ 0.2 (note that 0 ≤ r < 1), see  coefficients and hn,j is the A4 topography extracted at the nearest four [j = 1:4] indices surrounding the node ‘n’, for n = 1 ∶ number of nodes . All nodes/cells within the radius Rnest lie in the nesting zone and are used to extract the indices of the nesting grid cells, and subsequently, the nodes. The nesting grid is then generated, containing the indices and coordinates of the nesting nodes and cells, the topography at the nesting nodes and node identity of the three nodes that make up a cell for each of the nesting cells. In the next step, the vertical interpolation coefficients and indices for each of the FVCOM node and cell center are obtained. Here, the previously determined coefficients and indices for horizontal interpolation are used to interpolate the ROMS layer depth at ρ-points to the FVCOM nodes and cell centers. Then, at each of the 23 FVCOM  σ-levels, the nearest depth points from A4 are identified and the corresponding vertical indices and coefficients are computed. Lastly, using the cropped indices, A4 ocean ρ grid, the horizontal and vertical interpolation coefficients and indices and the nesting grid, the required nesting variables from A4 are interpolated onto the FVCOM nodes and cells over all the simulation time steps.The interpolated topography hThe AOTIM, an 8-constituent regional inverse tide model of the entire Arctic Ocean is used to obtain the phases and amplitudes of the tidal waves at the FVCOM boundary. Padman and Erofeeva The daily-averaged sea surface elevation extracted from A4 at the FVCOM nesting zone boundary nodes are interpolated on to the same (hourly) sampling as the AOTIM tides and the two fields are added together to form one product that drives the hourly tidal forcing at the nesting nodes.At the model surface, atmospheric variables are prescribed, namely 2-m air temperature, surface air pressure, relative humidity, eastward and northward wind speed, downward longwave radiation, net shortwave radiation, precipitation, and evaporation. These variables are derived from 3-hourly output from the polar (p) version of the RACMO2.3p2  covering the region north of 75° N for the period from 1958 to 2017 at a horizontal resolution of 5.5 km, which is important to resolve local meteorological conditions in the Petermann Fjord region. At its lateral boundaries, RACMO2.3p2 is forced by ERA-40 (1958–1978) and ERA-Interim (1979–2017) re-analyses on a 6-hourly basis within a 24–grid cell wide relaxation zone  that are valid at a given time-step, the accumulated fields were stored as follows:The ERA-Interim forecast fields of precipitation, evaporation and radiative fluxes are stored as accumulated fields, i.e., they are accumulated since the start of a forecast. The forecasts start at 00:00 and 12:00 UTC, and therefore with 3-hourly steps, these fields are accumulated twice each day over four 3-hourly periods, from 00:00 to 12:00 and from 12:00 to 00:00 UTC. As a result, precipitation and evaporation are stored in meter of water equivalent and the radiative fluxes are expressed in J/m0 denotes the start of a forecast (at 00:00 or 12:00 UTC), then the first 3-hourly step after the start of the forecast (at 03:00 or 15:00 UTC) is designated as the t0+1 step such thate (t0 + 1) and Φe (t0 + n) represent the ERA-Interim field calculated at the 3-hourly time steps t0 + 1 and t0 + n, respectively. ξe (t0 + 1), ξe (t0 + n) and ξe (t0 + (n - 1)) are the accumulated values provided at t0 + 1, t0 + n and t0 + (n - 1), respectively. Note that Φe actually represents the average flux (or the mean of what is collected) between any two given time steps.In a semi-diurnal cycle, if tLastly, all the instantaneous parameters from the ERA-Interim analysis fields which are provided at 6-hourly time steps are interpolated in time to match the 3-hourly RACMO forcing frequency. represents the forcing field at that time step for n = 1: number of nodes/cells, α denotes the nearest four [j = 1:4] coefficients surrounding the node/cell ‘n’ and X represents the atmospheric forcing field extracted at the nearest four [j = 1:4] indices surrounding the node/cell ‘n’ at time step ‘t’.The forcing period chosen here is consistent with the simulation period. To generate the forcing, the atmospheric grid is first cropped around the FVCOM grid and the corresponding longitude and latitude indices are stored. The interpolation coefficients and indices for the nearest four atmospheric grid points surrounding each of the FVCOM node and cell are then computed in the same manner as described in the previous section. Lastly, the desired atmospheric forcing field is cropped to the FVCOM grid using the latitude and longitude indices, and the interpolation coefficients and indices are used as follows to obtain the forcing field for FVCOMSea ice freezing/melting is an important aspect of high latitude ocean circulation. During sea ice freezing/melting, there are momentum, heat, freshwater and salt exchanges across the sea ice-ocean interface. In order to resolve the ocean dynamics in the presence of sea ice, we have implemented a new module called ICENUDGE into FVCOM. Furthermore, this allows us to simulate the sensitivity of the PGIS melt to seasonally varying sea ice conditions , while the curve saturates with weaker slopes for the high and low ΓT values [Following the six-month spin-up period of our standard run, the heat flux through the ice shelf-ocean boundary layer is scaled by varying the turbulent heat transfer coefficient  and salinity (Sg) constrained by the Gade line o = θAW and So = SAW [see o is the specific heat capacity of seawater having salinity = SAW, temperature = θAW and pressure = 588 dbar [see Both the observed and bias corrected profiles from the model for all the stations are represented in a θ-S space together with a straight line that has a slope of 2.5 °C/psu  SAW see . The bas SAW see , respectdbar see . First, dbar see  reportindbar see ,46 whichHere, we present a nested, high-resolution unstructured grid, 3-D ocean-sea ice-ice shelf setup based on the Finite Volume Community Ocean Model (FVCOM) which includes a realistic ice shelf basal topography T) which is appropriate for the given upstream A4 boundary conditions, following which, a ΓT of 0.05 is chosen which generated a simulated mean melt rate that largely agrees with the estimated figures reported by Wilson et al. T is due to a self-amplifying feedback mechanism, wherein, melt induced overturning strengthens as ΓT increases, likely increasing the transport of warm and saline AW in the PGIS cavity which further enhances the basal melting [as shown by Jourdain et al. T value derived from the sensitivity experiments. Here, it is important to note that this value is defined for the A4 boundary conditions that are described above. The θ-S fields still retain the bias, and therefore, we suggest applying a depth-dependent bias correction to the upstream A4 θ-S fields [such as in T against a series of bias corrected control experiments, before using the model setup to perform sensitivity studies that depart from the ocean conditions in the control run. Presence of runoff sources, although not included in the definition of the standard run, can be added as an additional component as part of a wide range of transient experiments that can be created using our model by branching off from the standard run.Bias correction that we applied to the northern A4 boundary conditions resulted in noticeable improvements. However, the AW θ-S signature remains relatively colder and fresher when compared to observations from the fjord. To compensate for the underestimation of basal melt rates, we ran a series of sensitivity experiments to derive a value for the turbulent heat transfer coefficient (ΓThe intention is that following the methods and guidelines described here, the user should be able to create a similar setup, or modify it to fit other applications of ice shelf-ocean interactions. Furthermore, the smoothed bathymetry dataset along with the water column thickness and ice-draft datasets can be used in other σ-coordinate numerical ocean/ice shelf-ocean modeling application that aims to investigate the Petermann Fjord region. Lastly, by making use of all the input, nesting and forcing files, it should be possible to replicate the simulation results that are presented here.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Aims: The optimal timing of brain radiotherapy (BRT) for lung adenocarcinoma patients with brain metastases (BM) remains controversial. In this retrospective study, we performed a retrospective review to investigate the differential benefit of upfront versus deferred BRT for lung adenocarcinoma patients with BM.Methods: A total of 354 lung adenocarcinoma patients with BM treated in the Affiliated Cancer Hospital of Shandong University met the inclusion criteria for the study. Patients were divided into two groups: upfront BRT and deferred BRT. Intracranial progression-free survival (PFS) and overall survival (OS) were measured from the date of brain metastases. Subgroup analyses according to gene mutation status were also performed.Results: Among the entire cohort, the median intracranial PFS with upfront BRT (16.3 months) was longer than that with deferred BRT . However, the median OS did not differ significantly between patients who received upfront BRT and deferred BRT . Subgroup analyses indicated that upfront BRT yielded a significantly longer intracranial PFS than deferred BRT (p=0.003) for patients without EGFR (19 or 21) mutation. In both subgroups, the median OS showed no significant difference between upfront BRT and deferred BRT.Conclusion: This single-institutional retrospective study showed that in lung adenocarcinoma patients with brain metastases, upfront BRT was associated with a significantly longer intracranial PFS but not improvement in OS compared with deferred BRT. Considering the neurocognitive toxicities of BRT previously reported in the literature, deferred BRT might be considered as an acceptable therapeutic option for the treatment of patients with lung adenocarcinoma and BM. Non-small cell lung cancer (NSCLC) accounts for about 87% of all lung cancer cases During the past decade, the advancement of EGFR tyrosine kinase inhibitors (EGFR-TKIs) has revolutionarily transformed the landscape of treatment and prognosis of advanced lung adenocarcinoma patients Interestingly, a recent study demonstrated that patients with EGFR-mutated NSCLC are more sensitive to RT However, in contrast to the conclusions of Magnuson et al, a retrospective analysis demonstrated that the addition of WBRT to EGFR-TKIs, compared with TKIs alone, did not improve the intracranial progression-free survival (PFS) and led to a worse OS in NSCLC with EGFR mutation and BM Thus, there is no consensus on the management of patients with lung adenocarcinoma and BM, and specifically, the optimal timing of BRT has yet to be determined. In the present retrospective study, we investigated the differential benefit of upfront versus deferred BRT for lung adenocarcinoma patients with BM. We also performed subgroup analyses according to gene mutation status.This study was conducted in compliance with the Declaration of Helsinki and approved by the Ethics Committee of the Affiliated Cancer Hospital of Shandong University (SDTHEC: 201611004). Through a review of hospital records, we identified 776 lung adenocarcinoma patients with BM treated at the Affiliated Cancer Hospital of Shandong University between June 1, 2013 and October 31, 2016. The eligibility criteria for this study were: (1) lung adenocarcinoma with BM, and (2) treatment with linear accelerator-based BRT. The exclusion criteria were: (1) upfront use of a TKI before BM diagnosis; (2) failure to complete the BRT plan; (3) meningeal metastases; (4) surgical resection or stereotactic radiosurgery (SRS); (5) presence of other primary tumors; (6) history of BRT; and (7) < 3 months of loss to follow-up. The included patients were divided into two groups: upfront BRT and deferred BRT. Upfront BRT was defined as BRT within 2 months after diagnosis of BM. Tumor response was assessed every 2-3 months according to response evaluation criteria in solid tumors (RECIST) 1.1 The last date of follow-up was March 31, 2018. The following variables were collected at BM diagnosis: (1) age; (2) gender; (3) smoking status; (4) Karnofsky performance status (KPS) ; (5) histology; (6) gene mutation status; (7) extracranial metastases; (8) size of largest BM; (9) number of BMs; (10) symptoms of BMs; (11) radiotherapy mode; and (12) treatments. A disease-specific Graded Prognostic Assessment (DS-GPA) was calculated. The radiotherapy modes were divided into three groups: WBRT, LBRT  and WBRT + LBRT. The gross tumor area radiotherapy was named as LBRT. The equivalent dose in 2 Gy/fraction (EQD2) of WBRT was calculated to be 32.5-50 Gy based on the LQ model. The accumulated LBRT dose was 50-60Gy with 2-4Gy per fraction and one fraction per day. When subgroup analyses, patients with ALK, ROS-1, or c-MET mutation were excluded. The dates of initial cancer diagnosis, BM diagnosis, BRT, systemic treatments, intracranial progression, most recent follow-up, and death were recorded. Intracranial PFS was defined as the time from BM diagnosis to intracranial progression, death, or last follow-up. OS was defined as the time from BM diagnosis to death or last follow-up.Statistical comparisons between two groups were performed in SPSS, version 21.0 . Comparisons of clinical characteristics between the upfront and deferred BRT groups were performed using the chi-square test. Kaplan-Meier analysis was used to estimate intracranial PFS and OS and generate surviva1 curves, and log-rank testing was used to assess differences between the groups. Multivariable Cox proportional hazards analysis were performed according to backward stepwise regression. Differences were considered to be statistically significant if p<0.05.After application of the inclusion and exclusion criteria, a total of 354 patients were identified for survival analyses (273 who received upfront BRT and 81 who received deferred BRT). The patients' demographic and clinical characteristics are summarized in Table Among all 354 patients, 168 patients (47.5%) received WBRT, 54 (15.3%) received LBRT, and 132 (37.3%) received both WBRT and LBRT. The median maximum diameter of the BMs was 15.5 mm. Overall, 52.5% of patients (186/354) had BM at primary diagnosis. Patients who received upfront BRT were more likely to have symptomatic BM  and were more likely to have BMs >1 cm . Patients who received upfront BRT were less likely to have extracranial metastases  and more likely to receive LBRT and WBRT . No differences were observed between the two groups with respect to age, sex, Eastern Cooperative Oncology Group (ECOG) performance status, smoking status, number of BMs, gene mutation, or DS-GPA at the time of BM diagnosis.For the entire cohort, the median intracranial PFS and OS were 14.6 months  and 28.2 months (95% CI: 24.7-31.7 months), respectively. The median intracranial PFS durations with upfront BRT and deferred BRT were 16.3 months (95% CI: 14.2-18.5 months) and 11.3 months (95% CI: 9.1-13.5 months), respectively  and 34.4 vs 34.8 months , respectively. Univariate analysis indicated that upfront BRT and WBRT+LBRT were associated with intracranial PFS, but the differences were not significant. Upfront BRT was not significantly associated with OS according to the univariate and multivariate analyses  mutation group (positive), no EGFR (19 or 21) mutation group (negative), and no genetic testing group (unknown). Patients with ALK (5 patients) were excluded. For patients with EGFR (19 or 21) mutation, the median intracranial PFS and OS were 17.1 months (95% CI: 13.7-20.5 months) and 34.4 months (95% CI: 28.0-40.9 months), respectively. With upfront BRT and deferred BRT, the median intracranial PFS and OS were 18.0 vs 14.2 months . However, no difference in the median OS  was observed between the patients who received upfront BRT and deferred BRT. On multivariate analysis, only upfront BRT yielded a longer intracranial PFS than deferred BRT . However, no correlation between upfront BRT and OS was found on univariate and multivariate analyses. Multivariate analysis identified only the number of BMs as significantly associated with OS  (For patients without EGFR (19 or 21) mutation, the median intracranial PFS and OS were 10.8 (95% CI: 9.3-12.4) and 23.4 months (95% CI: 19.0-27.9), respectively. Upfront BRT in these patients provided a longer median intracranial PFS than deferred BRT   and 7.Among NSCLC subtypes, adenocarcinoma is more prone to BM, and the prognosis and treatment strategy for lung adenocarcinoma patients are different from those of patients with other lung cancer types, especially for patients with EGFR gene mutations. The upfront BRT strategy has advantages and disadvantages. Although previous studies indicated that upfront BRT may be associated with better local control and longer OS, use of TKIs alone initially avoids the side effects of BRT. Two small randomized studies reported that the timing of WBRT did not influence OS in unselected NSCLC patients with BM receiving chemotherapy To the best of our knowledge, this study was the first retrospective analysis from China to compare survival outcomes with upfront and deferred BRT in patients with BM from lung adenocarcinoma. The targeted population in this study was lung adenocarcinoma patients with BM regardless of number of BMs, which was different from the population of the BRAIN study Several qualitative reviews have suggested that TKI therapy may be used first before BRT in EGFR+ NSCLC patients with asymptomatic BM In the present study, upfront BRT was defined as BRT within 2 months after diagnosis of BM, which was not consistent with the definition used in several previous studies In summary, this single-institutional, retrospective study showed that in patients with lung adenocarcinoma and BM, upfront BRT was associated with a significantly longer intracranial PFS, especially in patients without EGFR (19 or 21) mutation. No difference in OS was observed between patients treated with upfront BRT versus deferred BRT. Considering the neurocognitive toxicities previously reported with upfront BRT, deferred BRT might be considered as an acceptable therapeutic option for the treatment of patients with lung adenocarcinoma and BMs.Supplementary tables 4-13 (numbering continued from tables within the paper).Click here for additional data file.


Ki values determined for CYP1A2 were 13.8 and 9.2 μM for trans- and cis-resveratrol, respectively. Trans-resveratrol noncompetitively inhibited CYP3A and UGT1A1 activities with Ki values of 23.8 and 27.4 μM, respectively. Trans-resveratrol inhibited CYP1A2, CYP2C19, CYP2E1, and CYP3A in a time-dependent manner with Ki shift values >2.0, while cis-resveratrol time-dependently inhibited CYP2C19 and CYP2E1. The time-dependent inhibition of trans-resveratrol against CYP3A4, CYP2E1, CYP2C19, and CYP1A2 was elucidated using glutathione as a trapping reagent. This information helped the prediction of food drug interaction potentials between resveratrol and co-administered drugs which are mainly metabolized by UGT1A1, CYP1A2, CYP2C19, CYP2E1, and CYP3A.The stereoselectivity of the food drug inhibition potential of resveratrol on cytochrome P450s and uridine 5′-diphosphoglucuronosyl transferases was investigated in human liver microsomes. Resveratrol enantiomers showed stereoselective inhibition of CYP2C9, CYP3A, and UGT1A1. The inhibitions of CYP1A2, CYP2B6, and CYP2C19 by resveratrol were stereo-nonselective. The estimated  Resveratrol , a polyphenolic phytoalexin, is a common constituent found in many plants or beverages such as berries, grapes, peanuts, soy, and in wine, cranberry, and grape juices, as well as in many other plant products ,2. It isSchisandra extracts also markedly increased the plasma concentration of tacrolimus by inhibiting the CYP3A4 isoform in liver transplant patients − at m/z 550.1495 (mass error < 2 ppm), 323 Da higher than that of tRVT. This suggested that tRVT first oxidizes before it is being conjugated with one molecule of glutathione (MW = 307.3). The product ion scan spectrum of the glutathione conjugate by fragmenting m/z 550.1495 through collision generated characteristic daughter ions at m/z 428.1128 suggests the loss of a methyl dihydroxybenzene residue (−122 Da)  . The franjugates ,47. The Cmax of aripiprazole  in rats [In previous studies, red wine and tRVT were found to change the pharmacokinetics of drugs which are substrates of CYP3A . Zhan et in rats . Animal  in rats . In addi in rats .50 values. tRVT inhibited CYP2C19 and CYP2E1 activities with IC50 values of 8.1 and 9.8 μM, similar to CYP3A inhibition (IC50 = 5.6~16.6 μM) in a concentration- and time-dependent manner. Considering that tRVT participates in the pharmacokinetic intervention of dipeptidyl peptidase-4 inhibitors [50 = 10.8~19.8 μM) is stronger than CYP2C9 inhibition (IC50 = 23.8 μM). A dose of RVT received from food supplements may reach up to 2–5g/day, and RVT concentrations in plasma, after oral administration, may achieve micromolar concentrations [S-warfarin plasma concentration and international normalized ratio through CYP2C9 inhibition [50, RDI means recommended daily intake), volume in which the daily dose would be dissolved to reach the corresponding IC50 concentration [S-mephenytoin and chlorzoxazone, indicating RVT might have potential to inhibit biotransformation by CYP2C19 and CYP2E1 enzyme in vivo. However, clinical studies are needed to assess whether RVT affects drug metabolism by CYP2C19 and CYP2E1 enzymes in vivo. In contrast to the extensive studies on FDI with CYP3A substrates, there are limited data on FDI with other P450s. We anticipated the clinical FDI risk induced by RVT based on each of the IChibitors  by inhibhibitors , omeprazhibitors , acetamihibitors , and thehibitors . cRVT matrations ,57. In rhibition . In addintration . The VDIntration , and thentration . VDI valCmax)/Ki exceeded 1.0 [Cmax value of RVT was approximately 2.36 μM [Cmax value of RVT increased to 8.78 μM after a single oral dose of micronized RVT formulation (5 g) in humans [Cmax/Ki were 1.48~5.49, 0.51~8.78, 0.26~0.96, and 0.24~0.90 from the inhibition constant of tRVT against CYP1A2, CYP3A, CYP2E1, and CYP2C19 , suggesting that RVT might have FDI potential with these P450 substrate drugs at high doses. An in vivo FDI via the inhibition of a drug-metabolizing enzyme might occur if the ratio of the maximum plasma concentration . In addition, tRVT time-dependently inhibited CYP1A2, CYP2C19, CYP2E1, and CYP3A with Ki shift values >2.0, while cis-resveratrol time-dependently inhibited CYP2C19 and CYP2E1. From the inhibition potential  of RVT against P450s and UGTs, RVT at high doses might cause significant pharmacokinetic FDI with co-administered drugs predominantly metabolized by UGT1A1, CYP3A, CYP2E1, CYP2C19, and CYP1A2 in humans.Here, we demonstrated the stereoselective inhibitory potential of RVT against both P450s and UGTs in HLMs. We also determined their TDI against P450s, and indirectly confirmed the formation of reactive quinone methide intermediate using glutathione as a trapping agent. tRVT stereoselectively inhibited CYP2C9, CYP3A, and UGT1A1 activities whereas cRVT had negligible inhibition on them (IC


Intracortical inhibition plays a critical role in shaping activity patterns in the mature cortex. However, little is known about the structure of inhibition in early development prior to the onset of sensory experience, a time when spontaneous activity exhibits long-range correlations predictive of mature functional networks. Here, using calcium imaging of GABAergic neurons in the ferret visual cortex, we show that spontaneous activity in inhibitory neurons is already highly organized into distributed modular networks before visual experience. Inhibitory neurons exhibit spatially modular activity with long-range correlations and precise local organization that is in quantitative agreement with excitatory networks. Furthermore, excitatory and inhibitory networks are strongly co-aligned at both millimeter and cellular scales. These results demonstrate a remarkable degree of organization in inhibitory networks early in the developing cortex, providing support for computational models of self-organizing networks and suggesting a mechanism for the emergence of distributed functional networks during development. Inhibition is crucial for shaping neural activity and response properties in the mature cortex. GABAergic interneurons have been implicated in a range of computations, including response gain, stimulus discrimination, and network stabilization  and spanning several millimeters . To deteIn the mature cortex, orientation preference maps exhibit smooth variation, punctuated by abrupt discontinuities at orientation pinwheels and fractures , an orgaThe presence of modular activity patterns, together with long-range correlations exhibiting precise local structure, suggests that inhibitory neurons may already be tightly integrated into functional networks with excitatory cells in the developing cortex. To begin to address this, we undertook a quantitative comparison of excitatory and inhibitory networks assessed through spontaneous activity. We performed widefield imaging in animals expressing either hSyn.GCaMP6s, which is excitatory-specific in ferret , or the –3 (per μm) [1.49*10–3 –2.13*10–3], E: 1.62*10–3 (per μm)[1.35*10–3–2.22*10–3]; p=0.655, Wilcoxon rank-sum test). Taken together, these results demonstrate a strong degree of quantitative similarity in the spatial structure of inhibitory and excitatory networks in the developing visual cortex.Next, we quantitatively examined the correlation patterns for excitatory and inhibitory networks revealed by spontaneous activity. We find that correlations were similarly long-range, with equivalent strength 2 mm away from the seed point . AdditioPrior work has shown that in locally heterogeneous network models that recapitulate the structure of developing excitatory networks, long-range correlations exhibiting both local anisotropy and pronounced fractures strongly coincide with spontaneous activity patterns that reside in a low-dimensional subspace . Given tmDlx enhancer . We co-injected AAVs expressing hSyn.GCaMP6s (excitatory) and mDlx.GCaMP6s.P2A.NLS-tdTomato (inhibitory), allowing us to distinguish inhibitory neurons in vivo through tdTomato expression . We obseTo quantify the relative balance of excitatory and inhibitory activity within local populations, we computed the average response of all cells of a given cell type within a 75-µm region around each neuron for all spontaneous events. We found the amplitude of events within these local populations was highly correlated between excitatory and inhibitory cells  and maintained with isoflurane (1–1.5%). Buprenorphine (0.01 mg/kg) and either atropine (0.2 mg/kg) or glycopyrrolate (0.01 mg/kg) were administered, as well as 1:1 lidocaine/bupivacaine at the site of incision. Animal temperature was maintained at approximately 37°C with a water pump heat therapy pad . Animals were also mechanically ventilated and both heart rate and end-tidal CO2 were monitored throughout the surgery. Using aseptic surgical technique, skin and muscle overlying visual cortex were retracted, and a small burr hole was made with a handheld drill (Fordom Electric Co.). Approximately 1 µl of virus contained in a pulled-glass pipette was pressure injected into the cortex at two depths (~200 µm and 400 µm below the surface) over 20 min using a Nanoject-II (World Precision Instruments). The craniotomy was filled with 2% agarose and sealed with a thin sterile plastic film to prevent dural adhesion.On the day of experimental imaging, ferrets were anesthetized with 3–4% isoflurane. Atropine was administered as in virus injection procedure. Animals were placed on a feedback-controlled heating pad to maintain an internal temperature of 37–38°C. Animals were intubated and ventilated, and isoflurane was delivered between 1% and 2% throughout the surgical procedure to maintain a surgical plane of anesthesia. An intraparietal catheter was placed to deliver fluids. EKG, end-tidal CO2, and internal temperature were continuously monitored during the procedure and subsequent imaging session. The scalp was retracted and a custom titanium headplate adhered to the skull using C&B Metabond (Parkell). A 6–7 mm craniotomy was performed at the viral injection site and the dura retracted to reveal the cortex. One 4 mm cover glass  was adhered to the bottom of a custom titanium insert and placed onto the brain to gently compress the underlying cortex and dampen biological motion during imaging. The cranial window was hermetically sealed using a stainless-steel retaining ring . Upon completion of the surgical procedure, isoflurane was gradually reduced (0.6–0.9%) and then vecuronium bromide (0.4 mg/kg/hr) mixed in an LRS 5% Dextrose solution was delivered IP to reduce motion and prevent spontaneous respiration.Widefield epifluorescence imaging was performed with an sCMOS camera  controlled by μManager . Images Spontaneous activity was captured in 10-min imaging sessions, with the animal sitting in a darkened room facing an LCD monitor displaying a black screen. All imaging of spontaneous activity was done in young animals (P23–29) prior to eye-opening (~P31 to P35).To confirm that tdTomato expression from AAV1.mDLx.GCaMP6s.P2A.NLS.tdTomato was specific to inhibitory neurons as expected from previous work , we perfTo test whether GABAergic signaling exerted net inhibitory effects at the ages examined in this study, we bath applied the GABA(A) antagonist BMI directly to the cortex at P21–23 in animals expressing AAV1.Syn.GCaMP6s.WPRE.SV40. To apply BMI, the cannula covering the cranial window was removed and the exposed cortex was gently flushed with ACSF. After collecting 10 min of baseline spontaneous activity, 10 μM BMI in ACSF was bath applied to the cortex, and spontaneous activity was imaged for an additional 10 min.Image series were motion corrected using rigid alignment and a region of interest (ROI) was manually drawn around the cortical region of GCaMP expression. Additionally, a ROI mask was manually drawn around blood vessels to remove vessel artifacts. The baseline fluorescence (F0) for each pixel was obtained by applying a rank-order filter to the raw fluorescence trace with a rank 70 samples (for excitatory data) or 190 samples (for inhibitory data) and a time window of 30 s (451 samples). The rank and time window were chosen such that the baseline faithfully followed the slow trend of the fluorescence activity. The baseline-corrected spontaneous activity was calculated as (F–F0)/F0=Δ F/F0.2 were considered ‘inactive’ for the purpose of event detection. Active frames were taken as frames with a spatially extended pattern of activity (>50% of pixels were active). Our results were not sensitive to area threshold, as removing the area threshold requirement and including all frames with activity greater than 3 s.d resulted in correlation patterns with highly similar spatial structure for both inhibitory and excitatory networks. Furthermore, the strength of correlations 2 mm from the seed point for inhibitory and excitatory networks were equivalent for networks calculated from large events and all events  to the maximally active frame in each event and downsampled it to 160×135  pixels. The resulting patterns, named spontaneous patterns A in the following, were used to compute the spontaneous correlation patterns as the pairwise Pearson’s correlation between all locations x within the ROI and the seed point s:Spontaneous correlation patters were calculated as previously described . Brieflyx denotes the standard deviation of A over all N events i at location x.Here the brackets ⟨ ⟩ denote the average over all events and σ2 using ‘createCLAHE’ in Python OpenCV), and a spatial high-pass filter . The resulting values were binarized (threshold=0), and the resulting two-dimensional binary array eroded and then dilated (twice) to remove single noncontiguous pixels . We skeletonized this binary array to obtain the fracture lines .Spontaneous fractures were computed as previously described . FracturTo estimate the size of active domains in spontaneous events, we first identified domains by taking the local maxima of each event after bandpass filtering. The local neighborhood of each domain (600 μm radius from maxima) was then fit with a two-dimensional Gaussian using nonlinear least squares:1 (y1) is the x (y) center, σx (σy) is the standard deviation of the x (y) component, 0 is the offset. Domain size was calculated as the FWTM of the minor axis of fitted Gaussian:where H is the amplitude of the Gaussian, xTo determine the strength of correlations, we first identified local maxima (minimum separation between maxima: 800 µm) in the correlation pattern for each seed point. To assess the statistical significance of long-range correlations ~2 mm from the seed point, we compared the median correlation strength for maxima located 1.8–2.2 mm away against a distribution obtained from 100 surrogate correlation patterns. Surrogate correlation patterns control for correlations that arise from finite sampling by eliminating most of the spatial relationship between patterns . SurrogaTo find the wavelength of the correlation patterns, we first centered and averaged the local neighborhood (1500 μm radius) across all seed points. We then averaged over the angle to obtain the average correlation as a function of distance from the seed point and used spline interpolation to fit the data. The wavelength of the resulting spline interpolation was estimated as the distance to the first local maxima after 0.1 and minor axis ς2 to the contour line at correlation = 0.7 around the seed point. The eccentricity ε of the ellipse is defined as:To describe the shape of the local correlation pattern around a seed point, we fit an ellipse (least-square fit) with orientation Φ, major axis ςWhere ε=0 is a circle, and increasing values indicating greater elongation along the ellipse.eff of the subspace spanned by spontaneous activity patterns by We estimated the dimensionality diλ are the eigenvalues of the covariance matrix for the N pixels within the ROI. As the value of the dimensionality is sensitive to differences in detected event number, to estimate the distribution of the dimensionality for each animal we calculated the dimensionality of randomly sub-sampled events  and took the median of the distribution.where To compare the similarity between inhibitory and excitatory correlation patterns within the same animal, we computed the second-order correlation between patterns. For each seed point, we calculated the second order Pearson’s correlation between corresponding correlation patterns, while excluding pixels within a 400-μm exclusion radius around the seed point to prevent local correlations from inflating the similarity between the two networks. To get an estimate the upper bound of similarity within inhibitory networks, given a finite sampling size, we randomly split the detected inhibitory events into two groups and separately computed correlations and the second-order correlations between the halves (n simulations=100.) To determine if the observed networks are more similar than chance, we calculated the similarity between the excitatory network and a surrogate inhibitory network . To determine if spontaneous correlations far from the seed point also maintain high degrees of similarity, we systematically increased the size of the exclusion radii, calculating similarity only using data far from the seed points. Exclusion radius size ranged from 400 to 1400 μm, in 200 μm steps.http://bigwww.epfl.ch/sage/soft/mij/). Cellular ROIs were then manually categorized as either being inhibitory or excitatory based on tdTomato expression. Fluorescence was averaged over all pixels in the ROI and traces were neuropil subtracted, where Fneuropil was taken as the average fluorescence within 30 µm excluding all cellular ROIs and α=0.6:Two-photon images were corrected for rigid in plane motion via a 2D cross-correlation. Cellular ROIs were drawn using custom software . Then, for every cell in the FOV (excitatory and inhibitory) pairwise correlations were calculated with either inhibitory cells or the spatially matched excitatory cells. The similarity of these correlation patterns was taken as the second-order Pearson’s correlation as above, while excluding cells <200 µm from the seed neuron. Statistical significance was computed by comparing measured similarity values against a shuffled distribution obtained by shuffling the pairwise correlations before computing similarity (100 shuffles).To compare the amplitude of events within a local area, activity traces for each cell were smoothed with a three-sample median filter and z-scored across all frames. We then computed the average amplitude of all inhibitory (or excitatory) cells within a 75-µm radius for the maximally active frame of each event.Nonparametric tests were used for statistical testing throughout the study. Bootstrapping was used to determine null distributions when indicated. Center and spread values are reported as median and IQR, unless otherwise noted. Statistical analyses were performed in MATLAB and Python, and significance was defined as p<0.05. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Tirin Moore as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Geoffrey J Goodhill (Reviewer #1).Thank you for submitting your article "Tightly-coupled inhibitory and excitatory functional networks in the early visual cortex" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:All reviewers were in agreement that this study represents significant advancement in our understanding of inhibitory cortical networks during this crucial time in development. There were several suggestions by the reviewers that you are encouraged to implement to clarify the results and address particular confounding factors (particularly of those raised by Reviewer #2). These do not require new experiments but should be addressed in the revised text.Reviewer #2 (Recommendations for the authors):– My biggest concern is the potential of confounds introduced by using calcium imaging to measure responses of cell types with different firing rates. It would improve the work to more properly discuss these issues, and possibly try to estimate how much of an impact they could have. Is it possible that the extent of the excitatory events are underestimated because their lower firing rates put them below the threshold of measurable GCaMP activity? How different are the non-linearities between the 2 sensors? Finally, how much do the chosen event detection parameters (such as the requirement that more than 50% of pixels have to be active for an event to be counted) influence the results?– It would also be good to give a sense of how homogenous virus expression was throughout each imaging region, and to rule out that the scale of events is limited by the expression pattern.– Along the same lines: How many different patterns of spontaneous activity are usually detected? Figure 3 shows 3 evens that all look highly similar ; supplementary figure 1 shows 2 patterns that appear to be the opposite of each other. The correlation matrix in supplementary figure 2 also seems to suggest that there are no more than 4 patterns that occur. The low dimensionality of the subspace supports this conclusion as well, but it would be good to quantify the number of observable patterns more directly (and to compare them against the pattern of expression).Reviewer #3 (Recommendations for the authors):The paper is quite polished and in my opinion there is little to change.The methods were generally quite clear and used fundamental methods, but the description of the calculation of spontaneous fractures was opaque to me. It would help to unpack this a bit more and to describe which software tools were used (is CLAHE in ImageJ? Matlab?). Are "eroded" and "diluted" precise actions in a software tool? Essential revisions:All reviewers were in agreement that this study represents significant advancement in our understanding of inhibitory cortical networks during this crucial time in development. There were several suggestions by the reviewers that you are encouraged to implement to clarify the results and address particular confounding factors (particularly of those raised by Reviewer #2). These do not require new experiments but should be addressed in the revised text.We thank the reviewers and editors for their evaluation of our work, and for their suggestions to improve the clarity of our manuscript. In our revised submission, we have addressed all of the concerns raised. We believe the manuscript has been greatly strengthened by these changes, and hope you will find it suitable for acceptance and publication.A detailed response to each of the points raised in review follows below.Reviewer #2 (Recommendations for the authors):– My biggest concern is the potential of confounds introduced by using calcium imaging to measure responses of cell types with different firing rates. It would improve the work to more properly discuss these issues, and possibly try to estimate how much of an impact they could have. Is it possible that the extent of the excitatory events are underestimated because their lower firing rates put them below the threshold of measurable GCaMP activity? How different are the non-linearities between the 2 sensors? Finally, how much do the chosen event detection parameters (such as the requirement that more than 50% of pixels have to be active for an event to be counted) influence the results?Although it is possible that differences in the transformation of spiking activity to GCaMP fluorescence between cell types obscure subtle differences in the structure of excitatory and inhibitory networks, it is unlikely that this is a major factor in our results. If present, such differences could potentially impact the measured size or amplitude of domains. However, differences in calcium reporter behavior would not affect the spatial location and spacing of excitatory and inhibitory domains, and therefore is unlikely to affect in the precise co-alignment of excitatory and inhibitory correlation patterns.et al., 2018), arguing against jRCaMP1a inducing a prominent distortion of excitatory activity in these experiments. In addition, when comparing inhibitory GCaMP6s and excitatory GCaMP6s in separate animals  we found a high degree of quantitative agreement in the spatial structure of spontaneous events. Together, these points suggest that it is unlikely that variations in sensitivity or non-linearity between GCaMP6s and jRCaMP1a obscure major differences in the spatial patterns of activity in excitatory and inhibitory neurons.Our results show modular inhibitory activity that extends throughout the full imaging area  with clearly visible troughs between active domains, arguing against sensor saturation. Additionally, although GCaMP6s is far more sensitive than jRCaMP1a with a greater signal-to-noise ratio, both sensors reveal clearly modular patterns of spontaneous activity. Furthermore, the activity patterns imaged in excitatory cells with jRCaMP1a are highly similar in structure to those imaged previously in excitatory cells with GCaMP6s . This analysis demonstrates including many smaller and weaker events does not impact the strength or spatial structure of correlations.– It would also be good to give a sense of how homogenous virus expression was throughout each imaging region, and to rule out that the scale of events is limited by the expression pattern.As in prior work , the viral injection approach used here results in strong expression typically over a >3mm diameter area, with gradual fall-off beyond this distance. In most cases, this results in viral expression filling the entire field of view of the camera. Any imaged areas with poor expression were excluded from the area used for analysis. Notably, any variations in viral expression are at a much larger spatial scale  than the size of the individual domains  in the modular patterns of spontaneous activity we observe, making it highly unlikely that variations in viral expression within the imaged area contribute to the observed structure of activity.To further address this point, we have now included a new supplemental figure  showing randomly chosen example events which reveal spontaneous activity spanning the full FOV. We quantify this by calculating the fraction of spontaneous events in which a given pixel was active . All pixels within our ROI participated in at least 10% of all events, demonstrating that we are able to detect spontaneous activity throughout our imaging area. Together, this indicates that the expression pattern is not a limiting factor in determining the spatial scale of spontaneous activity.– Along the same lines: How many different patterns of spontaneous activity are usually detected? Figure 3 shows 3 evens that all look highly similar ; supplementary figure 1 shows 2 patterns that appear to be the opposite of each other. The correlation matrix in supplementary figure 2 also seems to suggest that there are no more than 4 patterns that occur. The low dimensionality of the subspace supports this conclusion as well, but it would be good to quantify the number of observable patterns more directly (and to compare them against the pattern of expression).The reviewer raises an important point, as the spontaneous activity patters in the cortex are indeed low dimensional, but are also more varied than being comprised of only 4 patterns. We recognize that our initial choice of example events in Figure 3c—in which two events (left and middle) were intentionally selected to show patterns with similar spatial layout that appear minutes apart from one another—may have given an incorrect impression of the variability across events.To better represent the actual variation in the events that we observe, we have changed the third example in Figure 3c to a pattern with a more distinct spatial arrangement from the first two. We have also now included a new Figure 1—figure supplement 1, showing 36 randomly selected examples of inhibitory events from the same animal that contribute to the correlation patterns in Figure 3d. These examples show the wide variety of events observed in spontaneous activity, with modular patterns that span the full area of our imaging field. For quantification, we estimated the variety of patterns by computing their dimensionality , which can be summarized as the approximate number of linear combinations of principal component patterns used to describe the variation across all events. The low dimensional subspace that the events reside in indicates that there is indeed a limited repertoire of possible patterns, but that the majority of the variance can be explained by approximately 10-12 patterns, rather than 4. This low dimensional subspace is consistent with previous work observing excitatory spontaneous activity in the developing visual cortex .Consistent with this interpretation, the correlations in Supplementary Figure 2 , while showing some positive clusters, are relatively low, indicating a degree of inconsistency even amongst events with similar spatial motifs, and therefore using clustering methods to definitively quantify the number of observed patterns is challenging. Our methods to quantify dimensionality are a more unbiased approach to estimate the variation in the data.To address these questions, we have made revisions to the Results section of the main text to better clarify and explain our interpretation of dimensionality of spontaneous activity.Reviewer #3 (Recommendations for the authors):The paper is quite polished and in my opinion there is little to change.We thank the reviewer for their positive assessment of our manuscript, and appreciate the feedback. We have addressed their suggestions below.The methods were generally quite clear and used fundamental methods, but the description of the calculation of spontaneous fractures was opaque to me. It would help to unpack this a bit more and to describe which software tools were used (is CLAHE in ImageJ? Matlab?). Are "eroded" and "diluted" precise actions in a software tool?Fractures were calculated using custom Python code built with open-source libraries. CLAHE was calculated using OpenCv’s function “createCLAHE”, and binary erosion and dilution  was calculated using SciPy’s Multidimensional Image Processing library (scipy.ndimage). We have updated the description of fracture magnitude calculation in the methods, and the actual code used to produce fractures can be found in the github repository associated with this paper: