The mammalian sensory neocortex consists of hierarchically organized areas reciprocally connected via feedforward (FF) and feedback (FB) circuits. Several theories of hierarchical computation ascribe the bulk of the computational work of the cortex to looped FF-FB circuits between pairs of cortical areas. However, whether such corticocortical loops exist remains unclear. In higher mammals, individual FF-projection neurons send afferents almost exclusively to a single higher-level area. However, it is unclear whether FB-projection neurons show similar area-specificity, and whether they influence FF-projection neurons directly or indirectly. Using viral-mediated monosynaptic circuit tracing in macaque primary visual cortex (V1), we show that V1 neurons sending FF projections to area V2 receive monosynaptic FB inputs from V2, but not other V1-projecting areas. We also find monosynaptic FB-to-FB neuron contacts as a second motif of FB connectivity. Our results support the existence of FF-FB loops in primate cortex, and suggest that FB can rapidly and selectively influence the activity of incoming FF signals. In the cerebral cortex, information is processed by multiple hierarchically organized areas, reciprocally connected via feedforward and feedback circuits. Here the authors show that in primate visual cortex, feedforward projection neurons receive monosynaptic feedback contacts selectively from the area to which they project. FF connections carry information from lower to higher-level areas. As information ascends through the cortical hierarchy, neuronal receptive fields (RFs) become tuned to increasingly complex stimulus features, and an increasingly abstract representation of sensory inputs is achieved. FF connections are reciprocated by FB connections sending information from higher to lower areas. This hierarchy is further organized into parallel processing streams, so that cortical areas within each stream are functionally specialized to process specific attributes of a sensory stimulus4. Reciprocal FF–FB connections between pairs of cortical areas are found throughout the neocortex of all mammalian species, suggesting they carry out a fundamental computation, but their role remains poorly understood.In the neocortex, sensory information is processed within hierarchically organized areas reciprocally connected via feedforward (FF) and feedback (FB) circuits7, the latter purely serving attentional selection. In contrast, several theories of hierarchical computation postulate that most of the computational work of the cortex is carried out by information going back and forth over looped FF–FB circuits between pairs of interconnected areas16. The exact computation performed by these loops depends on the specific theory, but many of these theories require FF–FB loops to occur between neurons in different areas processing similar stimulus attributes, albeit at different levels of abstraction. Whether this anatomical organization of FF–FB loops indeed exists in the cortex remains unclear. It is well established that most cortical areas possess reciprocal FF and FB connections18. However, since each area projects too, and receives inputs from, multiple areas, it is less clear whether FF and FB connections selectively contact the neurons that are the source of their reciprocal areal input, or rather unselectively contact different projection neurons in their target area. It is also unclear whether these cortico-cortical loops occur via direct monosynaptic contacts between FF and FB projection neurons, or indirectly via local excitatory or inhibitory neurons, or both. Recent studies have shown that in mouse primary visual cortex (V1), only a fraction of cortical projection neurons forms area-specific monosynaptic FF–FB loops19 and that these loops may only occur between deep layer neurons20. It remains unknown whether similar rules of cortico-cortical connectivity apply to higher mammals.Traditional FF models of sensory processing postulate that FF connections mediate the complexification of RFs, and that object recognition occurs largely independently of FB signals23. However, it is less clear whether FB projections show similar area specificity, and whether they influence FF projection neurons directly or indirectly. On the one hand, previous reports that neurons in the extrastriate cortex sending FB projections to V1 and the secondary visual area (V2) contain substantial amounts of axonal bifurcations26 and form diffuse terminations29 suggest that FB may not selectively contact the neurons that are the source of their areal input. On the other hand, recent demonstrations of clustered and specific FB terminations in primate V130  suggest the opposite.In cats and primates, inter-areal FF projections are highly area-specific, much more so than in rodents. For example, only a small percent of FF-projecting V1 neurons send a common input to multiple extrastriate areas via bifurcating axons32 to label the inputs to V1 neurons sending FF projections to V2 in the macaque visual cortex. If FB connections did not selectively contact the neurons that are the source of their areal FF input, one would expect to find inputs to V1 neurons projecting to V2 (V1→V2) to arise from multiple extrastriate areas known to project to V1. If, on the other hand, FB connections to V1 were area-specific, one would expect to find FB inputs to V1→V2 cells to arise only from V2. Consistent with the latter scenario, here we find that V1→V2 neurons receive monosynaptic inputs from V2 FB neurons, but not from neurons in other extrastriate areas known to also send FB projections to V1. We also find evidence for direct corticocortical FB-to-FB contacts. These results suggest that FB can rapidly and selectively influence the activity of incoming FF signals, and support the existence of area-specific FF–FB loops in the primate early visual cortex.To address this question, here we adapted viral-mediated monosynaptic input tracing methods33) to identify, in the macaque visual cortex, direct presynaptic inputs to V1→V2 neurons. We used an intersectional viral strategy based on three different viral vectors injected at different times  (AAV9-CAG-FLEX-oG-WPRE). After about 3 weeks, necessary for the AAV genome to concatermerize , a canine adenovirus type 2 carrying Cre-recombinase (CAV2-CMV-Cre35) was injected in V2 at retinotopic locations matched to those of the V1 injections. CAV2 is a retrograde vector that rapidly transcribes Cre-recombinase in local V2 neurons and V1→V2 neurons projecting to the CAV2 injection site in V2, reaching maximum expression in 5–7 days. In the presence of Cre, in V1 only the V1→V2 cells previously infected with AAV9-FLEX vectors express mCherry  carrying the gene for green fluorescent protein (eGFP) (EnvA-RVdG-eGFP) was injected in V1 at the same location as the AAV9 injections. Since the EnvA ligand binds exclusively to the TVA receptor, which is not otherwise native in the primate brain, RVdG can only infect cells that express TVA. This results in the expression of GFP in TVA-expressing V1→V2 cells, which become double-labeled in red and green  as guidance and made 2–3 injections of the AAV9 and RVdG vectors in V1, and 1–2 injections of CAV2-Cre in V2 as schematically shown in Fig. dG injections in V1 and 2 CAV2 injections in V2  is visible at and around the middle AAV injection site indicates this injection was in good retinotopic overlap with the CAV2-Cre injection sites in V2. Instead, the sparse red label nearby the medial and lateral AAV injections indicates these injections were not well matched retinotopically to the V2 injection sites. In contrast to mCherry, some GFP expression can occur independently of Cre , but only locally at the injection site (see Results below for a more extensive discussion of TVA leak). This explains why all three RVdG injections are visible, even if the medial and lateral injections were not in good retinotopic overlap with the V2 injection sites. Double-labeled (yellow) cells are only visible nearby the middle injections, where the RVdG and AAV injection sites overlap  in the superficial layers, a significant fraction (~20%) was located in L5. The majority of superficial layer yellow cells were located in L2/3 in cases MK379 and MK405, while they were more evenly distributed across superficial layers in cases MK382. Across the population, on average 62.2 ± 16.5% of V1→V2 yellow cells were located in L2/3, and 85% were located in the superficial layers  of GFP-labeled V2 cells were located in L5, 4.9 ± 0.6% in L6, and 40.1% ± 10.1% in L2/3  was 8.7 ± 6.98; the average ratio of GFP-labeled V2 FB cells in each layer to the total number of V1→V2 starter cells pooled across V1 layers was 2.1 ± 1.2 for L2/3, 6.1 ± 5.4 for L5, and 0.3 ± 0.3 for L6 Fig. . The var39, to determine whether FB contacts with V1→V2 neurons are area-specific, we searched for fluorescent labels throughout the cortex anterior to V2, excluding only prefrontal cortex. In two cases (MK405 and MK382), we found no GFP-labeled cells in the cortex anterior to V2, while in the third case (MK379), we found a total of 7 GFP-labeled cells in the extrastriate cortex anterior to V2 , corresponding to 0.6% of the total number of GFP-labeled FB cells in cortex anterior to V1  to 3:7  in which CAV2-Cre was omitted from the TRIO injection protocol described in Fig. dG viruses, separated by 3–5 weeks .It has been well-documented in mouse models that small amounts of TVA-mCherry can “leak” out at the injected site and become expressed in cells in the absence of Cre41. Thus, V2 neurons sending FB projections to the V1 AAV9 injection sites could potentially be infected by one or both AAV vectors; if these V2 neurons are also retrogradely co-infected by CAV2-Cre, via axon collaterals to the injected V2 site, then TVA-mCherry and/or oG can be expressed in these cells. Moreover, RVdG can potentially infect these TVA-expressing V2 FB cells at their V1 terminals42, resulting in double-labeled cells (yellow) in V2. Importantly, only if these cells co-express sufficient levels of oG, can trans-synaptic RVdG infection occur, and lead to GFP expression in their presynaptic partners. In other words, retrograde infection of V2 FB neurons by only three of the vectors  is sufficient to double-label these cells, but infection by all four vectors (the three above plus AAV-Flex-oG) must occur for the double-labeled cells to act as starter cells. Lower AAV injection volumes and shorter post-RVdG injection survival times can effectively reduce the efficiency of retrograde AAV infection and trans-synaptic expression of GFP from these retrogradely infected cells42. Across our sample (n = 3 cases), in the case that received the smaller AAV injection volumes  in this case  a small fraction of the GFP label in V1 and V2, and all the sparse GFP label outside V1 and V2 was pre-synaptic to the V2 starter cells. This evidence is discussed below. In the case of MK382, which only had double-labeled cells in V1, any GFP label within V1 (>400 µm from the injected site) and outside V1 could unequivocally be interpreted as input to the double-labeled V1→V2 neurons. This case, therefore, demonstrates the existence of area-specific monosynaptic V2 FB inputs to V1→V2 cells. Four observations suggest that in the case of MK405 there was no significant trans-synaptic RVase Fig. , suggestdG injection sites was contaminated by Cre-independent artifactual label, due to a TVA leak, in our quantitative analyses of the intra-V1 GFP label, we omitted from counts GFP-labeled cells within 400 µm radius of each V1 injection site. Thus our analysis of V1 inputs only included the long-range inputs (>400 µm). In all cases, GFP-label > 400 µm from the injection sites was found in all V1 layers except L1  of artifactual GFP label occurred at distances >400 µm from the injected RVdG sites . After eliminating the tails of the distributions, this range was 2.8–5 mm (mean ± s.e.m.: 3.8 ± 0.65 mm) Fig. . For eacOn average across the population, V1→V2 starter cells received 91.6 ± 3.1% of their total long-range cortical monosynaptic inputs from other V1 cells, with only 8.4 ± 3.1% arising from V2 Fig. . For the49, as well as the pulvinar50, a higher-order thalamic nucleus. We asked whether any of these inputs make direct synaptic contacts with V1→V2 cells. In two cases, MK405 and MK382, we found no GFP-labeled cells in either the LGN or the pulvinar, suggesting that thalamic inputs undergo intra-V1 processing before being relayed to V1 corticocortical output cells. In contrast, in the case of MK379, we found a small percent of GFP-labeled input cells  in the LGN (n = 14 cells) and pulvinar  of the thalamuslls Fig. . We founlls Fig. , the latUsing TRIO labeling in the macaque visual cortex, we have demonstrated the existence of area-specific monosynaptic FB contacts with FF-projection neurons. Specifically, we have shown thatV1 neurons sending FF projections to V2 receive direct monosynaptic inputs from V2 FB neurons, but not from neurons in other extrastriate areas known to project to V1. FB-to-FF inputs occur in both superficial and deep V1 layers, although our approach did not allow us to determine the differential contribution of superficial and deep layer FB neurons to the V1 termination layers. These direct interareal FB inputs represent only a tiny fraction of the total long-range cortical inputs to V1 cortical projection neurons, which overwhelmingly arise from within V1. We also found evidence for the existence of direct monosynaptic interareal FB-to-FB contacts relaying top-down information from higher extrastriate areas to V1, via a single synapse in V2. Finally, we found sparse direct inputs from the Parvo and Magno LGN layers and lateral pulvinar to V2 L5 neurons sending FB projections to V1 Fig. .Fig. 9Su23, but it was unclear whether FB is also area-specific and whether it influences FF afferents directly or indirectly. Our results demonstrate that in primate V1, FF-projection neurons receive direct monosynaptic FB inputs selectively from the area to which they project. We found monosynaptic inputs to V1→V2 neurons from V2, but inputs from other extrastriate areas known to project to V1 were either absent or extremely sparse. Henrich et al.56 recently reported that the probability of rabies virus trans-synaptic spread at each synapse is about 30%; thus, the number of labeled input neurons increases with the number of synapses formed by presynaptic neurons onto a given starter cell, providing an indirect measure of the functional strength of a projection. Thus, the absence of labeled presynaptic neurons in the extrastriate cortex anterior to V2 strongly suggests that such projections are either absent or so much sparser than the projection from V2 that our method failed to reveal them. These findings support the existence of highly area-specific FB-to-FF contacts in primate V1. This is in contrast with results from mouse V1, where about 80–88% of FF projection neurons project to one or two higher visual areas57, but only about 50% of their monosynaptic FB contacts arise from the same areas to which they project19. Moreover, recent evidence suggests that in the mouse a bias to form area-specific monosynaptic excitatory FF–FB loops may be limited to deep layer neurons20, while our results in macaque demonstrate area-selective FB-to-FF contacts in both V1 superficial and deep layers. These findings strongly support the existence of area-, and thus, functionally-specific, FF–FB loops in the primate cortex.It is well established that in the primate visual cortex, most V1 cortical projection neurons send FF projections to only a single area39. In contrast, here we found the vast majority of deep layer FB to arise from L5. Even allowing for the possibility of some errors in the laminar assignments of cells located near the L5/6 border, given the tangential sectioning plane used in our study, the bulk of the V2 deep layer GFP label clearly lay in L5. However, unlike previous studies which labeled all V2 FB projections to V1, we selectively labeled the FB projections to V1→V2 cells. Thus, our findings suggest laminar specialization in the deep layer FB projections, with FB from L5 contacting preferentially V1→V2 neurons.Several previous studies have shown, albeit mostly qualitatively, that the V2 deep layer FB projections to V1 arise predominantly from L6, and less so L516. The specific nature of the computations performed by these loops varies with the specific theory. For example, in predictive coding theory, FB signals represent a prediction of the external world, based on sensory data and prior experience; this prediction is compared with incoming sensory data, and the prediction error, carried by FF-projecting “error units”, ascends up the cortical hierarchy and refines the higher level predictions58. In terms of their architecture, predictive coding schemes require both excitatory and inhibitory looped interactions of FB inputs with lower-level “error units” to signal mismatches between predictions and sensory inputs60. Importantly, these looped interactions must be area-specific and occur between FF and FB units encoding similar features. Our findings of area-specific monosynaptic FB contacts with FF-projecting neurons, together with recent evidence of stream-specific V2 FB projections to V130, support the area and functional specificity of FF–FB loops required by predictive coding theories. Moreover, these FB-to-FF contacts could provide an anatomical substrate for excitatory FB interactions with the lower-level error units  required by predictive coding60. Alternatively, direct FB-to-FF contacts could underlie the “precision” FB signals of predictive coding models60. In the latter, the precision FB circuit is distinct from the prediction circuit and provides a modulatory or gating FB signal that sets the weight or precision of the prediction error. Whether the direct FB-to-FF contacts we have found serve to compute prediction errors or modulate their precision, ultimately depends on whether such contacts occur on the basal or apical dendrites, respectively, of V1→V2 cells59. Both kinds of FB contacts can potentially occur, the former in L5/6, and the latter in L1/2, where FB connections mostly terminate30. However, our method did not allow us to determine in which V1 layers these monosynaptic FB contacts occur.Our findings support several theories advocating looped computations between FF and FB connections63. Thus, the direct FB-to-FF connections we have found here could underlie the facilitatory effects of FB, but direct or indirect contacts with inhibitory neurons are necessary to mediate the FB suppressive effects found experimentally and postulated by predictive coding. Indeed, direct FB contacts with inhibitory neurons have been demonstrated in both mouse66 and primate67 visual cortex. Therefore, the monosynaptic FB–FF contacts we have found in this study represent just one of several motifs of FB connectivity in the primate cortex.An additional key component of predictive coding models is the inhibitory FB interaction with the lower-level error units , which requires FB contacts with inhibitory neurons. Moreover, experimentally FB has been shown to cause both facilitation and suppression of neural activity in lower-level areas68. This intra-areal recurrent processing between local expectation units serves to generate, maintain, and refine the internal predictions, which are then passed on to the FB units for relay to lower-level areas. Moreover, the termination of FF pathways from V1 predominantly in L4 and lower 3 of V2, and the origin of V2 FB pathways in layers 2/3 and 5/629 would make direct FF-to-FB contacts less probable than indirect ones.Our approach did not allow us to determine whether the V1→V2 neurons receiving the direct FB contacts directly target the same V2 neurons that are the source of their FB input. Notably, these direct FF–FB contacts are not required by predictive coding schemes. On the contrary, several of the proposed schemes view FF inputs from lower-level error units indirectly affecting their looped prediction FB units, via contacts with local neurons making recurrent connections with each other12. In these models, these local FB signals are fast, operating during the initial FF process. The area-specific monosynaptic FB-to-FF contacts we have found here represent an ideal anatomical substrate for fast and specific facilitatory FB modulation of incoming FF signals, and are also consistent with evidence that FB acts on the early part of the FF-driven response69.A different theory postulates that fast recurrent FB–FF processing between adjacent hierarchically organized areas serves to facilitate object recognition, particularly when incoming sensory inputs are ambiguous, degraded, or noisy38 that V2 FB connections to a V1 column extend on average 6.4 mm (reaching up to 9.4 mm), and are similar to the average cortical extent of V1 horizontal connections to the same column . However, the same study demonstrated that, due to the larger RF sizes and lower magnification factor in V2 compared to V1, the visuotopic extent of V2 FB connections is larger than that of V1 horizontal connections to the same V1 column. Specifically, while V2 FB connections convey information from a visual field region about 4–6 times the size of the aggregate RFs of their target V1 cells, the visuotopic extent of horizontal connections is only 2–4 times the aggregate RF size of their target V1 cells38. Qualitatively similar results were recently reported for FB connections in mouse visual cortex70, suggesting that a feature of FB connections conserved across species is their ability to convey information from distant visual field locations to their postsynaptic neuronal targets. This feature has been proposed to underlie contextual modulations from outside the classical receptive field71.We found that FB inputs to V1→V2 neurons arise from a cortical region extending on average 9.9 mm, approximately 2–3 times larger than the size of their V1 target zone, and similar in cortical extent to the spread of long-range intra-V1 horizontal inputs . These results are qualitatively consistent with previous reports46. While it is well established that cortical neurons receive the majority (79%) of their inputs from neurons within the same cortical area43, this is the first demonstration in the primate cortex that this connectivity rule also applies specifically to cortical projection neurons.Our results demonstrate that FF-projecting V1 neurons only receive a small fraction of their direct long-range (>400 µm) cortical inputs from FB neurons, the majority of which, instead, arise from neurons within V1, particularly in L2/3 and L5, where intralaminar horizontal connections are known to be most prominentAt least in the dorsal stream of visual processing, we found evidence for the second motif of FB connectivity, namely inter-areal FB-to-FB neuron contacts Fig. . These c51. However, while this projection, as well as direct geniculate projections to other extrastriate areas, arise predominantly from calbindin-positive or CaMKII-positive Konio geniculate neurons terminating in L4 and 553, here we find these direct LGN-to-V2 FB contacts arise from calbindin-negative cells in the Parvo and Magno LGN layers. While lack of calbindin immunoreactivity suggests neurons giving rise to these projections may not belong to the Konio system, it has been noted that this system is heterogeneous and also includes neurons that are calbindin and CaMKII-negative53. We cannot exclude that at least some of the Parvo LGN inputs were, instead, presynaptic to the starter V1 cells in L4A, as Parvo-to-L4A projections exist72; this would indicate the existence of direct geniculate inputs to L4A output cells. However, we believe this is unlikely, because two of our cases with starter cells in L4A, but few or no starter cells in V2, showed no labeled input cells in the LGN. Similarly, as the lateral pulvinar in addition to V2 also projects to L1–2 of V150, it is possible, although unlikely, that the pulvinar inputs we observed here were instead presynaptic to the apical dendrites of the starter cells in V1 L2-4B or L5. This would suggest that the pulvinar can directly affect the activity of V1 cortical output cells. Finally, as Magno afferents only terminate in V1 L4C and 6, and there were no starter cells in these V1 layers, it is unlikely the sparse Magno inputs found in our study represent direct inputs to V1 output cells.The same V2→V1 FB cells that received direct FB inputs from higher extrastriate areas of the dorsal stream also received a small direct FF input from the LGN and lateral pulvinar Fig. . We founWe performed monosynaptic input tracing or TRIO to label monosynaptic inputs to V1→V2 neurons (starter cells) in the macaque monkey visual cortex. The method consisted of targeting injections of three different viral vectors to V1 or V2, identified in vivo by intrinsic signal OI. The resulting labeled starter cells and input cells were mapped throughout V1, V2, extrastriate cortex, and thalamus, and their laminar and tangential distributions were analyzed quantitatively.Macaca fascicularis). Three animals were used for regular TRIO experiments and two for control experiments. All procedures involving animals were approved by the Institutional Animal Care and Use Committee of the University of Utah and conformed to the guidelines set forth by the USDA and NIH.We made a total of 25 viral injections in five adults (3–5 years old) female cynomolgus macaque monkeys  were made to expose the lunate sulcus, area V2 and parts of V1  were made at the same locations as the previously made AAV injections in V1, again using blood vessels as guidance. Animals survived an additional 9–12 days, during which a terminal 2–3 day OI experiment was performed to obtain additional functional maps. At the conclusion of the OI experiment the animal was sacrificed with Beuthanasia  and perfused transcardially with saline for 2–3 min, followed by 4% paraformaldehyde (PFA) in 0.1 M phosphate buffer for 20 min.Animals were pre-anesthetized with ketamine . An i.v. the catheter was inserted, and the animals were intubated with an endotracheal tube, placed in a stereotaxic apparatus, and artificially ventilated. Anesthesia was maintained with isofluorane (1–2.5%) in 100% oxygen, and end-tidal CO74. The V1/V2 border can be identified in the retinotopic maps by the presence of stripes of activity in V1, which are absent in V2 . V2 can be identified in the orientation maps by larger orientation domains compared to V1, and the characteristic “stripy” pattern of orientation domains  during the first survival surgery and, then, again during a terminal procedure, using the Imager 3001 and VDAQ software . We imaged for orientation and retinotopy, as these functional maps allow identification of the V1/V2 border. Orientation maps were obtained by presenting full-field, high contrast (100%), pseudorandomized, achromatic drifting square-wave gratings of eight different orientations at 1.0–2.0 cycles/° spatial frequency, moving back and forth at 1.5 or 2°/s in directions perpendicular to the grating orientation. Responses to the same orientations were averaged across trials, following baseline correction, and difference images were obtained by subtracting the responses to two orthogonally oriented pairs. Retinotopic maps were obtained by subtracting responses to monocularly presented oriented gratings occupying complementary adjacent strips of visual space, i.e., masked by 0.5–1° gray strips repeating every 1–2°, with the mask reversing in position in alternate trials. Baseline correction for both the orientation and retinotopic maps was performed in three different ways and the approach that provided the best maps was selected for analysis: (1) the baseline (pre-stimulus) was subtracted from the single condition response ; (2) the single condition response was divided by the baseline; (3) the single condition response was divided by the “cocktail blank” 13 GC/ml; Salk Institute Viral Core GT3), AAV9-CAG-FLEX-oG-WPRE , E1-deleted-CAV2-CMV-Cre-SV40polyA  and EnvA-RVdG-eGFP . All viruses were slowly pressure injected at a rate of 6–15 nl/min, using a picospritzer  and glass micropipettes (25–50 µm inner diameter). The two AAV9 vectors were mixed at 1:1 or 3:7 ratio and loaded into the same glass micropipette, and 2–3 injections of the mixture were made into V1, 1–1.3 mm posterior to the V1/V2 border and spaced mediolaterally  1–1.1 mm apart  and inter-injection survival times for each animal are reported in Supplementary Table For TRIO experiments, we made a total of 21 injections of 4 different viral constructs in 3 macaques . The viral vectors were: AAV9-CAG-FLEX-TVAmCherry  for control experiments, to determine the amount and extent of Cre-independent GFP expression caused by TVA leak. In each animal, one injection of each of the AAV9 and RVAreas V1 and V2 were separated from the rest of the visual cortex, by making a cut along the fundus of the lunate sulcus. The block was post-fixed for 1 h in 4% PFA between glass slides, to gently flatten the cortex parallel to the imaged area, cryoprotected in 30% sucrose, and frozen-sectioned at 40 µm on a sliding microtome in a plane tangential to the imaged surface of V1 and V2. Sections were wet-mounted, scrutinized for fluorescent label and, selected sections (two of every three sections) containing label were imaged for fluorescent GFP and mCherry label. After imaging, every third section was reacted on the glass slide for CO, to reveal layers and areal boundaries, and the sections were re-imaged under bright field illumination.75, to aid in the identification of extrastriate areas and areal boundaries, and stained for fluorescent Nissl to identify cortical layers and subcortical nuclei. Furthermore, to identify the pulvinar subdivisions and the koniocellular layers of the LGN, selected sections containing fluorescent labels were immunoreacted for Calbindin as follows. Sections were incubated in primary antibody  for 72 h at 4 °C, and then reacted with a secondary antibody tagged to a near-infrared fluorophore .The remainder of the brain, with the frontal pole removed, was post-fixed overnight in 4% PFA, cryoprotected, and sectioned sagittally at 70 µm. A full series of sections was wet-mounted and imaged for the fluorescent labels. Sections containing fluorescent labels were stained for myelin using the Gallyas methodWe searched for the fluorescent labels in every section throughout the cortex  and thalamus. We then imaged at regular intervals (two of every three sections) two full series of sections throughout the regions containing labeled cells. Tissue sections were simultaneously imaged for both GFP and mCherry fluorescence, and the sections immunoreacted for Calbindin and stained for Nissl were additionally imaged for Alexa 647 and DAPI, respectively. Imaging was performed on a Zeiss Axio Imager.Z2 fluorescent microscope connected to an Apotome 2, using a 10× objective and an Axiocam 506 mono camera . Image files were created and analyzed using Zen 2.6 Blue Software . Sections were imaged using uniform camera exposure times and LED intensity. Imaged sections were scrutinized for fluorescent labels and the regions containing double-labeled (green and red) starter cells were re-imaged at higher magnification, using a 20× objective and the Apotome to obtain z-stacks in 1–2 µm z-steps, so as to verify cells classified as double-labeled. CO and Gallyas stainings were imaged under bright field illumination, using the same microscope and a 10× objective. All images were post-processed in Zen using the “stitching algorithm” to align individual image tiles and minimize tiling artifacts. Images used for figures were exported directly from Zen files, and brightness or contrast was uniformly increased or decreased in Adobe Photoshop across the entire image in each channel.Imaged sections were aligned in a sequential stack through the depth of the cortex , or in a mediolateral stack  using Adobe Photoshop, by registering the radial blood vessels. The aligned image stacks were then transferred to Neurolucida Software  for cell plotting and counting, and for drawing layer boundaries based on CO and Nissl stains. For each section containing the label, we plotted and counted all GFP-labeled (green) input cells (excluding only GFP-labeled cells in V1 located at distances <400 µm from each injection site center), and all double-labeled (yellow) cells. For V1 and V2, we imaged and counted two full series of sections, while for the thalamus and the rest of the cortex we counted every labeled cell in every section that contained the label. We defined “input” cells as cells exclusively labeled with GFP showing morphological and size characteristics of neurons. Double-labeled cells were defined as somata expressing both GFP and mCherry in the same imaging z-plane, with the two labels perfectly overlapped. Since GFP and TVAmCherry are differently distributed inside neurons, the former filling the soma and the latter binding to the cell membrane, we allowed for the possibility that GFP and mCherry-labeled cells did not show identical shapes. Each cell was additionally assigned a layer location, and the number of cells in each layer, as well as the percentage of total GFP or double-labeled cell counts in each layer, were determined Figs. . We thendG injection site. We pooled data across layers and injection sites because our method did not allow us to determine to which starter cell each input cell projects. In a similar fashion, we measured the spread of the GFP-label in the tangential domain of V2 along an axis parallel to the V1/V2 border . For the two control cases, instead, we measured the distance of each GFP-labeled cell from the center of the injection site (Supplementary Fig. We quantified the spatial spread of GFP-labeled cells within the tangential domain of V1 Fig. . This wader Fig. , as wellder Fig.  and V2. Further information on research design is available in the Supplementary InformationPeer Review FileReporting Summary


Neuro-inflammation occurs as a sequence of brain injury and is associated with production of cytokines. Cytokines can modulate the function and survival of neurons, microglia and astrocytes. The objective of this study is to examine the effect of TNF on the neurons, microglia and astrocytes in normal brain and stab wound brain injury.st, 2nd, 3rd, 7th, and 9th day. Frozen brain sections through the injury site in IA and IB or corresponding region in NA and NB groups were stained for neurodegeneration, immunostained for astrocytes, microglia and neurons. Western blotting for GFAP and ELISA for BDNF were done from the tissues collected from all groups.Normal BALB/c male mice (N) without any injury were subdivided into NA and NB groups. Another set mouse was subjected to stab wound brain injury (I) and were subdivided into IA and IB. NA and IA groups received intraperitoneal injections of TNF (1 µg/kg body weight/day) for nine days, whereas NB and IB groups received intraperitoneal injections of PBS. Animals were killed on 1The number of degenerating neurons significantly decreased in TNF treated groups. There was a significant increase in the number of astrocytes and microglia in TNF treated groups compared to PBS treated groups. In addition, it was found that TNF stimulated the expression of GFAP and BDNF in NA and IA groups.TNF induces astrogliosis and microgliosis in normal and injured brain and promotes the survival of cortical neurons in stab wound brain injury, may be by upregulating the BDNF level. This suggests TNF's central role in the development of inflammatory diseases TNF is expressed by many cells, including astrocytes and microglial cells of the brain. TNF has two types of receptors (TNFR1 and TNFR2) which are made up of four cysteine repeats. Both receptors are expressed in various tissues, with TNFR2 being more specific to the cells of the immune system Several studies have shown that TNF has a prominent role in the nervous system, however, these studies provide paradoxical roles of TNF, with some displaying a neuro-modulatory and protective effect in the normal or uninflamed brain. While others show a neurotoxic effect in the diseased or inflamed brain On the other hand, in pathological conditions, TNF is involved in the neuroinflammatory responses associated with various neurological disorders through de novo production of TNF by activated astrocytes and microglia Research on hippocampal damage showed that increased TNF immunoreactivity in the hippocampus is associated with lower rates of survival in the early periods Thus, TNF released during inflammatory process or infused from external source has effects on neurons, neurotrophic factors, microglia and astrocytes in and around the injury site. In spared nerve injury (SNI) of the sciatic nerve, tumor necrosis factor is shown to be released and upregulated in bilateral hippocampus and ipsilateral spinal dorsal horn with significantly reduced dendrite lengths and spine densities in the hippocampus and increased in spinal cord neurokinin-1 positive neurons Although the pro-inflammatory cytokine TNF is thought to be one of the major mediators of neuroinflammation, its role in brain injury, effects on neurons, microglia, astrocytes and trophic factors in and around the injury site remains ill-defined. TNF activity is very acute. It has been shown that TNF mRNA increases within 1 h in the ischemic injury core, and the expression of its immunoreactive protein increases within 2–6 h after the onset of ischemia in experimental models As stated above, TNF has both neuroprotective and neurodegenerative roles. It is well known that activated glial cells release inflammatory factors (including TNF) by themselves and damage neurons. What is not known fully is that weather extraneously infused TNF will provide neuroprotection or not in stab-wound injury. Our hypothesis is that extraneously infused TNF will have neuroprotection in stab-wound injury. It will stimulate astrocytes and microglia to secrete neurotrophic factor, which in turn protect the neurons from degeneration. Our hypothesis is based on a few literatures which indicated protective role of intrinsic TNF which was released from activated astroglia and microglia 2.2.1.Two months old BALB/c male mice were used in the present study. Mice were maintained in the Animal Resources Centre, Faculty of Medicine, Kuwait University. Mice were fed with food and water ad-libitum. Animals were maintained in 12:12 dark: light cycle and room temperature were maintained at 25 ± 2 °C. The animal surgery, treatment protocol and maintenance were according to the approved protocol of the Institutional Animal Care and Use Committee of Kuwait University, which follows the recommendations of NIH Guidelines and the Guide for the Care and Use of Laboratory animals. A minimum and sufficient number of animals were used due to good experimental design and planning. Experiment that involved brain injury were performed on the animals under anesthesia, aseptic technique, and with the least harm inflicted to the animals. Ketamine (40 mg/kg)-xylazine (5 mg/kg) cocktail  was used for anesthetizing the mice during stab-wound injury. Antiseptic betadine solution was applied on the skin wound after stab wound injury. All experimental protocols were approved by the institutional ethical committee as stated above.2.2.st, 3rd and 7th days after the beginning of the experiment . For BDNF analysis additional two time points 2nd and 9th day were used . Frozen brain sections through the injury site in IA and IB or corresponding region in NA and NB groups were stained for Fluoro-Jade B (neurodegeneration), Immunostained of for GFAP (astrocyte marker), Iba-1 (microglia), and NeuN . Morphological alterations are not as rapid as biochemical changes. Hence, we did morphological studies on 1st, 3rd and 7th day, excluding 2nd and 9th day time points. Western blotting (for GFAP) and ELISA (for BDNF) were done from the tissues collected from the injury sites in IA and IB groups and corresponding site in NA and NB groups. BDNF analysis was done on the tissue collected on 1st, 2nd 3rd, 7th and 9th day . We wished to see BDNF level on 2nd day because alterations in levels of BDNF is quicker than morphological changes in the early post lesion days. We included 9th day in order to see the additional effect during two extended days (7th to 9th).This experiment was designed to investigate the role of TNF treatment on astrocytes and microglia, and neuronal survival in stab wound model of brain injury (an in vivo model of penetrating brain injury) and normal brain. A total of 264 BALB/c male mice were divided into two sets (n = 132/set). The first set of mice  were not subjected to any injury and were subdivided into A  and B  groups. The second set mice were subjected to stab wound brain injury . A stab wound was done on the cerebral cortex of these mice as described earlier st, 3rd and 7th day for analysis of BDNF by ELISA method (n = 6/group) and analysis of GFAP by western blot (n = 6/group), and 6 mice/group for 2nd and 9th day .Nnumber of mice used in different groups for morphological and biochemical studies were shown in table 1. A total of 264 mice were used in the present study. Mice under morphological studies (N = 72) were equally distributed for each group for each time point of study (6 mice/group/time point of study) for Fluoro-jade B staining, Immunostaining for Astrocytes (GFAP), microglia (Iba1) and neurons (NeuN). Mice under biochemical studies (N = 192) were distributed 12 mice/group for 12.3.The animals were perfused transcardially with saline followed by 4% paraformaldehyde  and their brains were dissected and fixed in 4% paraformaldehyde for 48 hours. Then brains were cryoprotected in 10%, 20%, and 30% sucrose solution as described before 2.4.To visualize degenerating neurons, the brain sections from non-injured and injured brains were processed for FJ-B histochemical staining. Fluoro-Jade B and C are an anionic fluorescein derivative useful for the histological staining of neurons undergoing degeneration. Fluoro-Jade B has a greater specific affinity for degenerating neurons than Fluoro-Jade B. We used FJ-B for staining the degenerating neurons around injury site.3 tissue were calculated for each mouse as detailed below.The brain sections were mounted on gelatin coated slides and air dried at room temperature overnight. Slides were rehydrated and treated with 0.06% potassium permanganate followed by washing in distilled water. The sections were then treated with 0.004% FJ-B  in 0.1% acetic acid for 30 minutes with slow shaking in dark. The sections were rinsed in distilled water, dehydrated and mounted with DPX. Number of FJ-B stained degenerating neurons were counted in six randomly selected photograph/section taken around the injury site (n = 6/group in each time point) (Photographs were taken with 40x objective in an olympus fluorescence microscope). Finally, the number of degenerating neurons/mm2.5.The brain sections were treated with 3% hydrogen peroxide, then with 5% normal goat serum for 30 minutes. The sections were incubated with polyclonal rabbit anti-GFAP , polyclonal rabbit anti-Iba-1  or mouse monoclonal anti-NeuN  antibody overnight at 4 °C. Glial fibrillary acidic protein (GFAP) is an intermediate filament protein of 52 kD found in glial cells such as astrocytes. We used anti-GFAP antibody for immunostaining astrocytes for identification of astrocytes around the injury site and for immunoblotting for GFAP in western blot analysis of GFAP content in the tissue around the injury site. Ionized calcium binding adaptor molecule 1 (IBA1), is a marker of microglia/macrophages. It is a 17-kDa protein that is specifically expressed in macrophages/microglia and is upregulated during the activation of these cells. Iba1 expression is up-regulated in microglia following nerve injury, central nervous system ischemia, and several other brain diseases. We used anti-Iba1 antibody for immunostaining astrocytes for identification of activated microglia around the injury site. NeuN  antibodies are fundamental tools for staining mature neurons and studying neuronal development and differentiation. We used anti-NeuN antibody to immunostaining to identify the mature neurons around the injury site.The sections were then incubated with biotinylated goat anti-rabbit IgG  or biotinylated horse anti mouse IgG  for 1 hour at room temperature. All sections were treated with ExtrAvidin peroxidase  for 1 hour. The color was developed using DAB solution . Then the sections were dehydrated in ascending grades of ethyl alcohol, cleared in xylene and mounted with DPX.2.6.3 tissue were calculated for each mouse as described earlier 3 tissue were quantified by using the data collected from a total of 36 sections/mice (n = 6/group) using the formula: T = (N × V)/t, where N is the numerical cell density, V is the volume of the lesioned tissue around the lesion site used for quantification and t is section thickness (30 µm). The numerical cell density (N) was calculated by using the area of the section used for quantification, area of each field used for quantification and total cell counts in six randomly selected fields. NIS-Elements software (NIS-Elements-D2.20) was used for area measurement. The volume (V) was calculated by multiplying the area of section with section thickness (30 µm), inter-section distance (60 µm) and number of sections used (6 sections).Number of degenerating neurons, immunostained neurons, astrocytes and microglia were quantified as described earlier 2.7.3) and from corresponding regions of non-injury brains were removed and snap frozen in liquid nitrogen and stored at –80 °C until Western Blot analysis as described earlier Animals were perfused with 50 mL of cold saline. Tissue around the injury site (5 mm2.8.3 tissue around injury site) were collected snap frozen in liquid nitrogen, stored at (–80 °C) and were weighed immediately to get the wet weight of the samples and analyzed for BDNF content as described earlier 2, 2% Triton X-100, 0.1% sodium azide and the protease inhibitors . The lysate from each sample was centrifuged at 14,000 revolutions/minute (rpm) for 30 min at 4 °C and the supernatant solutions were collected. The supernatant from each sample was frozen for subsequent measurements of BDNF by using ChemiKine brain derived neurotrophic factor (BDNF) sandwich ELISA kit  following the protocol provided in the kit. Briefly 100 µL of standards or appropriately diluted samples were added into each flat bottom wells, pre-coated with mouse anti-Human BDNF monoclonal antibody and incubated at 4 °C overnight on a shaker. Wells were washed three times with 250 µL of diluted wash buffer. 100 µL of the diluted biotinylated mouse anti-BDNF monoclonal antibody (1:1000 in sample diluent) was added to each well and incubated at room temperature for three hours on a shaker. Wells were washed again three times with 250 µL of diluted wash buffer. 100 µL of the diluted streptavidin-HRP conjugate solution  was added to each well and incubated at room temperature for one hour on a shaker. Wells were washed three times with 250 µL of diluted wash buffer. 100 µL of TMB substrate  was added to each well and incubated at room temperature for 15 minutes. Reaction was stopped by adding 100 µL of stop solution to each well. The wells were read immediately in an ELISA plate reader at 450 nm. Optical density of standard solution was plotted against known concentration of the standards to get the standard curve. Unknown concentration of the BDNF in the samples were calculated by plotting their OD values into the standard curve.Tissue samples  were selected for quantification. Six mice were used in each group. Finally, mean number of astrocytes or microglia or degenerating neurons or neurons/mm3.In all mice with stab-wound injury, tip of the needle remained in the frontal cortical region. It did not injure any other nuclei or structures .3.1.st, 3rd and 7th post injury days  and 3rd day to 7th day  staining revealed degenerating neurons around the injury site in the stab wound brain injury. Distribution of degenerating neurons in injured mice treated with TNF was less dense compared to injured mice treated with PBS at 1ury days . FJ-B strd and 7th post injury days  and 3rd day to 7th day (p < 0.05), but not in injured and treated with PBS (IB group).Immunostaining of sections from injured brain with anti-NeuN antibody for neurons showed denser distribution of neurons around the injury site in injured mice treated with TNF compared to injured mice treated with PBS at 3ury days . Immunos3.2.rd and 7th day compared to non-injured and injured mice treated with PBS . In both non-injured brain and injured brain treated with TNF, increase in the astrocytes was significant and progressive from 1st day to 3rd day (p < 0.05) and 3rd day to 7th day (p < 0.05)  . Howeverrd and 7th post injury days [Student's t-test, Non-injured groups  and 3rd day to 7th day (p < 0.01) in injured mice treated with TNF . However, such a progressive increase in the GFAP content was not seen in non-injured groups treated with TNF (NA) or PBS (NB).Western blot analysis for GFAP showed significantly enhanced GFAP content in both non-injured  and inju3.3.st, 3rd and 7th day  and 3rd day to 7th day (b p < 0.05) in injured mice treated with TNF and PBS. However, such a progressive increase in the microglia is not seen in non-injured groups treated with TNF (NA) or PBS (NB).Brain sections immunostained with Iba-1 showed increased density microglial distribution in both non-injured and injured mice treated with TNF on 1 7th day  and 6B.  7th day  . Increase in the BDNF concentration in the tissue around the injury site was progressive from day-1 to day-9. The BDNF content significantly increased from 1st day to 9th day (1st day vs 9th day: p < 0.01) in injured mouse treated with both TNF and PBS. However, such a progressive increase in the GFAP content is not seen in non-injured groups treated with TNF (NA) or PBS (NB).BDNF level was significantly increased in non-injured and injured mice treated with TNF compared to mice treated with PBS at all-time points studied  mice was significantly increased. The observed neuroprotection may be related to glio-stimulatory role of extraneously infused TNF, where in TNF stimulated both astrocytes and microglia to become activated. These activated glial cells might have released neurotrophic factor BDNF, which in-turn protected the neurons from degeneration in the stab-wound injury. Our results are consistent with a previous study with similar conclusions In this study, we have demonstrated activation of the astrocytes (astroglyosis) and microglia (microgliosis) in brains of both normal mice (non-injury) and stab wound injured mice treated with TNF for 1, 3 or 7 days. We observed decreased neurodegeneration  in stab wound injured mice that are treated with TNF for 3 or 7 days compared to injured mice that are treated with vehicle. Neurodegeneration decreased progressively from 14.1.We observed degenerating neurons, especially on the first day, in and around the injury site in injured mice treated with both PBS and TNF. This initial neurodegeneration may be due to several toxic substances released from the injured cells and may be due to toxicity of TNF itself (from infused and/or intrinsic TNF). It is proposed that TNF not only has neuroprotective role, it also plays a negative role in the nervous system. It has been shown that high level of TNF is associated with the progression of a variety of neurological disorders, including Alzheimer's disease, as well as Parkinson's disease Neurodegeneration also may be due to localized activation of neuroinflammation by TNF, which could initiate neuronal death, even though TNF has not been demonstrated to cause neuronal death in healthy brain The observed neurodegeneration in our study also may be through activation of microglia, indeed our results showed increased microglia in the injured brain. Although it is assumed that microglia are the major source of TNF during neuroinflammation A receptors on neurons The mechanism of TNF neurotoxicity is claimed to be through release of excessive glutamate. TNF can potentiate cytotoxicity by (i) inhibiting glutamate transport on astrocytes and by rapidly triggering the expression AMPA and NMDA receptors, (ii) decreasing inhibitory GABANeurodegeneration observed in our study may be mediated through TNF's TNFR1 receptor which activates the caspase family, which induce cell death. Involvement of TNFR1 in neurodegeneration in stab-wound injury needs to be explored in future studies. TNF acts through its two receptors TNFR1 and TNFR2. Both receptors are expressed in various tissues, with TNFR2 being more specific to the cells of the immune system 4.2.Our results showed a neuroprotection by TNF in the stab-wound injury. It may be through neurotrophic factors released from activated astrocytes and/or microglial cells. Alternatively, it may be direct beneficial effect of TNF as it is claimed to be neuroprotective also. TNF is a pro-inflammatory cytokine that regulates several biological processes, including apoptosis, differentiation, proliferation, as well as activation of neurons 4.3.Our results showed astrogliosis in both normal and injured mice treated with TNF. X. Hu et al. showed enhancement of GFAP in the normal Muller's glial cell to a smaller extent and to a larger extent in preactivated Muller glial cells by treatment with TNF rd and 7th in stab wound injured and treated with TNF compared with PBS treated groups suggest the gliosis under the influence of infused TNF. The TNF stimulatory effect is sustained as there was a significant increase from 3rd day to 7th day in both groups treated with TNF and PBS. This may be due to combined action of intrinsic and infused TNF. The enhancement of astrocytes to a smaller extent in injured and treated with PBS may be due to action of intrinsic TNF released from the activated astrocytes, microglia or both.Several other studies also indicate a strong association between TNF and astrocytes in in neural injury/lesion models, which are comparable to our stab-wound injury models. Exposure of astrocytes in tri-culture medium  to LPS (Lipopolysaccharides) hypertrophies the astrocytes, increases the secretion of a number of pro-inflammatory cytokines . Following mechanical trauma in the tri-culture showed increased astrocyte migration towards the site of injury. Microglia in the tri-culture plays a significant neuroprotective role during glutamate-induced excitotoxicity 4.4.rd and 7th post injury days compared to that injured and treated with PBS. Activated microglia produce protective factors that help to prevent neuronal injury, such as BDNF, glial cell-derived neurotrophic factor (GDNF) and nerve growth factor (NGF) Microglia exhibit both beneficial and detrimental effects in neuroinflammation. Results of our study showed enhanced number of microglial cells in the injured brain treated with TNF at 3Microglia, when activated stimulate an adaptive immune response. They release several inflammatory mediators like proinflammatory cytokines, chemokines, prostaglandins, inducible nitric oxide synthase (iNOS), cyclooxygenase-2 (COX-2), free radicals Activation of microglial receptors (P2X4Rs) leads to increased levels of BDNF st, 3rd and 7th day in stab wound injured and treated with TNF compared with PBS treated groups suggest the gliosis under the influence of infused TNF. The TNF stimulatory effect on microglia appears to be sustained as there was a significant increase from 1st day to 3rd day and 3rd day to 7th day in both groups treated with TNF and PBS. This may be due to combined action of intrinsic and infused TNF. The enhancement of microglia to a smaller extent in injured and treated with PBS may be due to action of intrinsic TNF released from the activated astrocytes, microglia or both.Above literature on microglia agree with our argument that extraneously infused TNF, along with intrinsic TNF released from cells in and around injury site stimulate microglial cells to become activated, which in turn play their role in neuroprotection. Significant increase in number of microglia at 14.5.Our results showed a positive correlation between increased BDNF release and enhanced survival of neurons in mice that are injured and treated with TNF. Studies indicate the physiological relationship between BDNF and astrocytes As discussed above, in our study activated astrocytes and microglia after treatment with TNF may be responsible for increased release of BDNF as well as neuronal protection. However, we have not addressed the question on the source of BDNF, weather it is from activated astrocyte or activated microglia or both. Further studies are required to address this question.st day to 9th day in both groups treated with TNF and PBS. This may be due to combined action of intrinsic and infused TNF. The enhancement of BDNF to a smaller extent in injured and treated with PBS may be due to action of intrinsic TNF released from the activated astrocytes, microglia.Significant increase in BDNF contents at all-time points studied in stab wound injured and treated with TNF compared with PBS treated groups may be the key factor in neuroprotection. The TNF's sustained stimulatory effect on microglia and astrocytes might have caused sustained and a significant increase in BDNF from 1Thus, TNF has both neuroprotective and neurodegenerative effects. TNF is produced both in the normal tissue and injured tissue. The neuroinflammatory process is associated with activation of microglia, astrocytes and release of the TNF and BDNF. Being a pro-inflammatory cytokine, TNF when it is in excess, aggravates further gliosis and inflammation. When TNF is at its moderate level, it facilitates resolving of inflammation and hence neuroprotection. The BDNF, released from activated microglia and astrocytes counteract aggravation of inflammation induced by excessive TNF. It is hard to determine whether the observed effects (gliosis and neuroprotection), in our study are from the extraneous infused TNF or both intrinsic and extrinsic source. It may be the combined effect of both intrinsic and extrinsic source. The receptor through which it mediates its effects needs to be studied. Similarly, BDNF may be from activated astrocytes, microglia or both, which needs to be determined in future studies.5.This study indicates that TNF activates astrocytes (astroglyosis) and microglia in normal brain (non-injury) and stab wound injury. TNF protects the cortical neurons and decreases their degeneration in stab wound injury. This neuroprotection may be through enhancement of BDNF. Enhancement of BDNF probably by either by activated astrocytes or activated microglia or both. Further experiments are needed to find weather activated astrocyte or microglia or both play their role in enhancement of BDNF or any other mechanisms exist. Results of our study is promising to use TNF as therapeutic agent to treat neural injuries and neurodegenerative diseases, however several additional experiments are needed to validate a few things such as to know the different dose effects of TNF, adverse effects of extraneously infused TNF, to find the source of BDNF (weather from astrocyte or microglia). This study supports strategies of preserving the activating astrocytes and microglia in the planning of future therapies to promote regeneration in brain injury.


To evaluate the role of prostate-specific antigen density (PSAD) in different Prostate Imaging Reporting and Data System version 2.1 (PI-RADS v2.1) categories to avoid an unnecessary biopsy in transition zone (TZ) patients with PSA ranging from 4 to 20 ng/mL.  In this retrospective and single-center study, 333 biopsy-naïve patients with TZ lesions who underwent biparametric magnetic resonance imaging (bp-MRI) were analyzed from January 2016 to March 2020. Multivariate logistic regression analyses were performed to determine independent predictors of clinically significant prostate cancer (cs-PCa). The receiver operating characteristic (ROC) curve was used to compare diagnostic performance. P = 0.039) or PSAD .  PI-RADS v2.1 and PSAD were the independent predictors for TZ cs-PCa in patients with PSA 4-20 ng/mL. 0.9% (2/213), 10.0% (7/70), and 48.0% (24/50) of PI-RADS v2.1 score 1-2, 3, and 4-5 had TZ cs-PCa. However, for patients with PI-RADS v2.1 score 1-2, there were no obvious changes in the detection of TZ cs-PCa (0.8% (1/129), 1.3% (1/75), and 0.0% (0/9)) combining with different PSAD stratification . For patients with PI-RADS v2.1 score ≥ 3, the TZ cs-PCa detection rate significantly varied according to different PSAD stratification. A PI-RADS v2.1 score 3 and PSAD < 0.15 and 0.15-0.29 ng/mL/mL had 8.6% (3/35) and 3.7% (1/27) of TZ cs-PCa, while a PI-RADS v2.1 score 3 and PSAD ≥ 0.30 ng/mL/mL had a higher TZ cs-PCa detection rate (37.5% (3/8)). A PI-RADS v2.1 score 4-5 and PSAD <0.15 ng/mL/mL had no cs-PCa (0.0% (0/9)). In contrast, a PI-RADS v2.1 score 4-5 and PSAD 0.15-0.29 and ≥0.30 ng/mL/mL had the highest cs-PCa detection rate (50.0% (10/20), 66.7% (14/21)). It showed the highest AUC in the combination of PI-RADS v2.1 and PSAD (0.910), which was significantly higher than PI-RADS v2.1 (0.889,  For TZ patients with PSA 4-20 ng/mL, PI-RADS v2.1 score ≤ 2 can avoid an unnecessary biopsy regardless of PSAD. PI-RADS v2.1 score ≥ 3 may avoid an unnecessary biopsy after combining with PSAD. PI-RADS v2.1 combined with PSAD could significantly improve diagnostic performance. Serum prostate-specific antigen (PSA) screening has been widely used for detecting an early stage of prostate cancer (PCa), evaluating treatment response, and determining tumor progression. However, PSA testing increases the risk of overdiagnosis due to the low specificity, resulting in unnecessary prostate biopsies. In addition, the PCa detection rate varies from the PSA range. Several studies have proven that cancer detection rates were 11.8-20.5%, 20.5-25.0%, and 47.1-53.0% in the PSA range of 4-10 ng/mL, 10-20 ng/mL, and greater than 20 ng/mL, respectively [3 and/or extra prostatic extension), and provides information for evaluating tumor staging and monitoring treatment response [Multiparametric magnetic resonance imaging (mp-MRI) offers increasingly reliable visualization for the diagnosis of PCa, especially for clinically significant PCa  of the prostate; approximately 25% of these cancers arise from TZ . TZ PCa Therefore, this study is to evaluate the role of PSAD in different PI-RADS v2.1 categories to avoid an unnecessary biopsy in TZ patients with PSA levels of 4-20 ng/mL.n = 517), (b) incomplete bp-MRI examination (n = 18), (c) unsatisfactory MR images affected by artifacts from patient movement or hip replacement (n = 15), and (d) prostate biopsy or therapies before MRI examination (n = 9). Finally, the remaining 333 patients were enrolled. The study population flowchart is shown in This retrospective and single-center study was approved by our institutional review board who waived the requirement for the informed consent. We evaluated 892 biopsy-naïve patients who underwent bp-MRI examination between January 2016 and March 2020 at our institution . All patients derived from elevated PSA levels within 4-20 ng/mL. Patients who had the index lesion in TZ which was determined as the lesion with the highest PI-RADS v2.1 score were included in the study. For patients with multiple lesions in both TZ and PZ, only the index lesion with the highest score in TZ was included. However, 559 patients were excluded based on these criteria, including (a) the index lesion in PZ . Apparent diffusion coefficient (ADC) maps were obtained from b = 100 and b = 1000 s/mm2.bp-MRI examinations were performed on a 3.0 Tesla MRI  with a 32-channel body phased-array coil. The MR image acquisition protocol was as follows: axial T2WI sequence (repetition time (TR), 3000 ms; echo time (TE), 100 ms; slice thickness, 3 mm; no slice gap; field of view (FOV), 220 × 220 mm) and sagittal T2WI sequence . The axial DWI sequence  had multiple All bp-MRI images were independently evaluated by two experienced readers  using the PI-RADS v2.1 category protocol in the same setting. They were blinded to pathological results and clinical information. Any discordance between the two readers was resolved by consensus, and any continuous disagreement in scoring was resolved by a third senior urogenital radiologist who made the final determination of the PI-RADS v2.1 score. According to the PI-RADS v2.1 protocol [Clinical information including age, t-PSA, f/t-PSA, PV, and PSAD was collected and measured. According to the PI-RADS v2.1 protocol, maximum longitudinal diameter (LD) and maximum anteroposterior diameter (APD) should be measured on the midsagittal T2WI, whereas maximum transverse diameter (TD) should be measured on the axial T2WI. PV was calculated using the following formulation: PV = (maximum APD) × (maximum TD) × (maximum LD) × 0.52 . PSAD waIn our institution, all patients with PSA 4 ng/mL or higher did undergo biopsy as the standard of care. All biopsy-naïve patients in this study underwent a 10-core systematic transrectal ultrasound- (TRUS-) guided prostate biopsy. The 10-core biopsies were obtained from the base (2 cores), midgland (2 cores), and apex (1 core) from each side of the prostate. Patients with negative MRI (PI-RADS v2.1 scores 1 and 2) underwent a standard 10-core systematic TRUS-guided prostate biopsy only. For suspicious PCa lesions on MRI (PI-RADS v2.1 score ≥ 3), an MRI-TRUS fusion-guided targeted biopsy was used, and then, 2-3 targeted cores would be added for these lesions. The MRI-TRUS fusion-guided targeted biopsy was performed using Esaote's MyLab Twice ultrasound system . Histopathologic evaluation of the biopsy specimens was analyzed and reported by experienced genitourinary pathologists in our institution according to the International Society of Urological Pathology (ISUP) 2014 updated Gleason score grading system , 25. A Gt-test was used for continuous variables which were normally distributed and expressed as mean and standard deviation (SD). Those continuous variables with nonnormal distribution or categorical variables were analyzed using the Mann-Whitney U test, presented as median and interquartile ranges. Multivariable logistic regression analysis was performed to determine the independent predictors. The areas under the receiver operating characteristic curve (AUC) with corresponding 95% confidence intervals (CI) were calculated, and DeLong's test was used to compare the diagnostic performance. A two-tailed P value less than 0.05 was considered statistically significant.Statistical analysis was performed using SPSS 22.0 software and MedCalc version 15.2.2. The Kolmogorov-Smirnov test or Shapiro-Wilk test and Levene's test were used to assess the normality of data and the homogeneity of variances. The independent-sample P < 0.05), while the f-PSA was not significantly different (P = 0.898).The characteristics of all patients are shown in t‐PSA = 0.638, AUCPV = 0.207) compared with PSAD (AUCPSAD = 0.832). So the final indicators include age, f/t-PSA, PSAD, and PI-RADS v2.1 score. As shown in P < 0.05).These univariate indicators  were significantly different between patients in PSA 4-20 ng/mL with and without cs-PCa. However, PSAD was obtained from t-PSA and PV. To better handle strongly correlated variables, the multivariate model removed t-PSA and PV with smaller AUCs (AUCThe cs-PCa detection rate in TZ patients with PSA 4-20 ng/mL stratified by PI-RADS v2.1 score or PSAD is shown in ), the combination of the PI-RADS v2.1 score and PSAD had the highest AUC for TZ cs-PCa in patients with PSA levels of 4-20 ng/mL (AUC = 0.910 (0.874-0.939)), which was significantly larger than that in the PI-RADS v2.1 score (AUC = 0.889 (0.850-0.920), P = 0.039) or PSAD (AUC = 0.803 (0.756-0.844), P < 0.001). These results indicated that integrating PSAD and PI-RADS v2.1 score could significantly improve the diagnostic performance for TZ cs-PCa in patients with PSA 4-20 ng/mL.As shown in the ROC curve and DeLong's test , the comSerum PSA has been the most widely used for PCa screening and early detection. However, the detection rate of PCa in patients with PSA levels of 4-10 and 10-20 ng/mL was low, and the rate of detecting cs-PCa was even lower. A previous study reported that the PCa detection rate was 11.8% and 20.5% in the PSA range of 4-10 and 10-20 ng/mL . In thisIn the present study, our results found that the PI-RADS v2.1 score was one of the two independent predictors for TZ cs-PCa in patients with PSA 4-20 ng/mL. Compared to PI-RADS v2, the PI-RADS v2.1 made small step modifications to simplify MRI interpretation and improve interreader agreement , 27. SomFor the detection of cs-PCa in TZ patients with PSA 4-20 ng/mL, we found that the cs-PCa detection rate was 0.9% (2/213) for PI-RADS v2.1 score ≤ 2. There was no significant change in the detection rate of cs-PCa after combining with PSAD, which indicated that for patients with PSA levels of 4-20 ng/mL, PI-RADS v2.1 score ≤ 2 can avoid an unnecessary biopsy regardless of the PSAD value. For PI-RADS v2.1 score 3, the cs-PCa detection rate was 10.0% (7/70). However, combining with PSAD < 0.15 ng/mL/mL  or PSAD 0.15-0.29 ng/mL/mL  can avoid an unnecessary biopsy. Importantly, for PI-RADS v2.1 score > 3, patients with PSAD < 0.15 ng/mL/mL  can also avoid an unnecessary biopsy. In addition, compared to the PI-RADS v2.1 score, the cs-PCa detection rate was the highest (66.7%) for the combination of PI-RADS v2.1 score > 3 and PSAD ≥ 0.30 ng/mL/mL. Our results were substantially consistent with the previous PI-RADS v2.0 study by Ryoo et al. . They coP = 0.039) or PSAD value , which was comparable with the previous study by Han et al. [Our results also demonstrated that PSAD was the other independent predictor for the assessment of TZ cs-PCa in patients with PSA levels of 4-20 ng/mL. PSAD could distinguish patients with a PSA elevation due to BPH and prostatic inflammation, and it has been proven to improve the accuracy of PI-RADS in the decision to perform prostate biopsies . In mostn et al. . They coSeveral limitations need to be considered in this study. First, there was a retrospective, single-center study with relatively small number of patients, so sample selection bias inevitably exists. The present results would be further validated in multicenter studies with a larger number of patients. Second, our results were performed based on a “patient” level who had the index lesion with the highest PI-RADS v2.1 score among all lesions in TZ, not on a “lesion” level. Third, not all patients underwent an MRI-TRUS fusion-guided targeted biopsy, and those potential PCa lesions with MRI-negative and pathology-positive status may be missed.For TZ patients with PSA 4-20 ng/mL, PI-RADS v2.1 score ≤ 2 can avoid an unnecessary biopsy, regardless of PSAD. PI-RADS v2.1 score ≥ 3 may avoid an unnecessary biopsy after combining with PSAD. In addition, PI-RADS v2.1 combined with PSAD could significantly improve its diagnostic performance.


Tumor necrosis factor (TNF) is a potent inflammatory cytokine that has been causally associated with coronary artery disease (CAD) and ischemic stroke (IS), implying opportunities for disease prevention by anti-TNF therapeutics.case/control upto 122,733/424,528) and IS  were then estimated via various MR estimators using circulating C-reactive protein  as downstream biomarker to reflect treatment effect. Associations of a functional variant, rs1800693, with CRP, CAD and IS were also examined.Leveraging summary statistics of several genome-wide association studies (GWAS), we assessed the repurposing potential of TNF inhibitors for CAD and IS using drug-target Mendelian randomization (MR) design. Pharmacologic blockade of the pro-inflammatory TNF signalling mediated by TNF receptor 1 (TNFR1) was instrumented by four validated variants. Causal effects of TNF/TNFR1 blockade on CAD  for CAD and 0.77 (95% CI: 0.36-1.63) for IS. Findings remained null in all supplement analyses.Our findings do not support TNFR1 as a promising target for CAD or IS prevention among the general population. Future research is warranted to investigate whether the detrimental effect of circulating TNF on CAD and IS might be counteracted by modulating other relevant drug targets.No. PubMed and Google Scholar were searched to extract literature containing “tumor necrosis factor” and “cardiovascular disease” in title. Based on the results, tumor necrosis factor has been associated with many cardiovascular events by genetic, epidemiological and experimental data. Numerous clinical and animal studies also suggested the opportunity to prevent cardiovascular diseases or their underlying risk factors with anti-tumor necrosis factor strategies. The causal effect of tumor necrosis factor on coronary artery disease and ischemic stroke, was recently reported by a Mendelian randomization study as well.The present work followed up the causal effect revealed by the recent Mendelian randomization study and, for the first time, provided supplement data about the potential benefit of inhibiting the proinflammatory signalling pathway associated with this pathogenic cytokine on coronary artery disease and ischemic stroke. These results are informative to the future development of novel clinical therapeutics and will enhance our understanding the pathogenic role of tumor necrosis factor and its relevant signalling pathways in cardiovascular events.The detrimental effect induced by tumor necrosis factor on coronary artery disease and ischemic stroke is multifactorial and cannot be simply reversed by deactivating the tumor necrosis factor receptor 1-mediated proinflammatory signalling among the general population.Alt-text: Unlabelled box,,Tumor necrosis factor (TNF) is a potent inflammatory cytokine involved in a broad spectrum of biological processes. TNF can exist in two forms: synthesized as a transmembrane protein, TNF can be cleaved by the TNF-α converting enzyme (TACE) into a soluble variant.,Historically known for an integral role in host defense, TNF is recognized more recently for its deleterious effect in several inflammatory and autoimmune diseases, which prompted the development of anti-TNF therapeutics. To date, five TNF inhibitory drugs – infliximab, etanercept, adalimumab, golimumab and certolizumab – have been approved to treat rheumatoid arthritis and Crohn disease etc. in clinical practice.Cardiovascular diseases (CVDs) have been linked with TNF by genetic and epidemiological evidence.The causal effects of TNF inhibition on CAD and IS were examined in a “drug-target MR” design using GWAS summary statistics. Drug-target MR is developed on the basis of the classical MR design, which uses genetic variation as instrumental variable to test for causality between a modifiable exposure and an outcome.p-value < 5 × 10−8) (As illustrated in  × 10−8) a. In con × 10−8) b.23 Sinc,,Hence, to investigate TNF signalling as a potential target for CAD and IS, we implemented the drug-target MR design in the present work b. SpecifTNFRSF1A , the gene encoding TNFR1. Second, the SNPs must be associated with circulating C-reactive protein (CRP), a sensitive inflammatory biomarker that is commonly used as endpoint in the clinical assessment of anti-TNF efficacy.A total of 4 single nucleotide polymorphisms (SNPs) that have been previously validated by Kang et al. were used to instrument the pharmacologic inhibition of TNF/TNFR1 pathway.,,Genetic associations with the serum concentration of CRP, measured by immune assay as mg/L, came from a meta-analysis of 204,402 European individuals enrolled in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Inflammation Working Group.r2 < 0.001) with smallest association p values for CRP , including rs767455, were included in the inverse variance weighting-based estimation to improve statistical power. Numerical instabilities due to the inclusion of correlated variants was controlled for by integrating principal component analysis.Following the analytical protocol we previously validated, the statistical analysis was performed in three sections.p < 0.05 without multiple correction. The statistical analyses were carried out in R version 4.0.5 (2021-03-31) using TwoSampleMR package.Causal estimates of TNF/TNFR1 inhibition on the binary disease outcomes from the primary and secondary MR models were presented as odds ratios (ORs) and 95% confidence intervals (CIs) for every 10% decrease of circulating CRP. Statistical significance was determined as two-sided No ethical approval was required for the present study, since all analyses were only based on publicly available summary statistics without accessing individual-level data. The included GWAS studies all received informed consent from the study participants and have been approved by pertinent local ethical review boards.The study received no financial support.p value: 0.96) or IS .No evidence was observed for a causal effect of TNF/TNFR1 inhibition on the risk of CAD or IS . In the In the present work, we tested the causal effects of anti-TNF on CAD and IS susceptibility using MR design and found no evidence for any benefits of inhibiting the TNF/TNFR1 signalling pathway on either disease. Our study is based on the most updated GWAS summary data and robust study design, and our results remain consistently null throughout the analyses.In light of the prior evidence on the causal associations of circulating TNF with increased risks of CAD and IS, the absence of benefits of TNF/TNFR1 blockade we observed tends to be counterintuitive at first glance.,,,First, it is worth noting that the causal estimate from MR study is an averaged effect across all population and their entire lifespans, which means that if TNF/TNFR1 blockers play opposing effects among subpopulations with different characteristics, the ultimate MR estimate can be neutralized towards the null.,,3,Second, since the TNF-associated CVD risks cannot be inversed by blocking TNFR1, it is reasonable to speculate that the pathogenic contribution of TNF is underpinned by mechanisms beyond the TNF/TNFR1 pathway and its downstream effects. One possible process is the TNF/TNFR2 signalling, for which a cardioprotective and immunoregulatory property has been demonstrated by mounting preclinical data.,,Another point to emphasize is that both CAD and IS are complex diseases that are attributable to polygenic determinants and gene-environment interaction.Our study has several limitations. First, as discussed above, we were unable to identify the potential beneficiary population for TNF/TNFR1 inhibition due to data unavailability. Restricted by the knowledge gaps, we were also not able to evaluate the putative impact of targeting TNFR2 on CAD or IS. Besides, since a total of three correlated SNPs were included as instrumental variants, we performed the MR analyses with only two methods and did not manage to test for violation of MR assumptions using alternate estimators, such as MR-Egger. Such methodological caveat may to some degree jeopardize the internal validity of our study; nevertheless, the instrument validity of these selected SNPs has been previously validated by Kang et al. and findings in the present work were highly consistent across different models.In summary, the results from Yuan et al.’s and our work collectively imply that the pathogenic role of TNF in CAD or IS is complex and cannot be simply reversed by deactivating the TNFR1-mediated pathway among the general population.Nothing to disclose.


Purpose: To evaluate the diagnostic performance of PI-RADS v2, proposed adjustments to PI-RADS v2 (PA PI-RADS v2) and biparametric magnetic resonance imaging (MRI) for prostate cancer detection. Methods: A retrospective cohort of 224 patients with suspected prostate cancer was included from January 2016 to November 2018. All the patients underwent a multi-parametric MR scan before biopsy. Two radiologists independently evaluated the MR examinations using PI-RADS v2, PA PI-RADS v2, and a biparametric MRI protocol, respectively. Receiver operating characteristic (ROC) curves for the three different protocols were drawn. Results: In total, 90 out of 224 cases (40.18%) were pathologically diagnosed as prostate cancer. The area under the ROC curves (AUC) for diagnosing prostate cancers by biparametric MRI, PI-RADS v2, and PA PI-RADS v2 were 0.938, 0.935, and 0.934, respectively. For cancers in the peripheral zone (PZ), the diagnostic sensitivity was 97.1% for PI-RADS v2/PA PI-RADS v2 and 96.2% for biparametric MRI. Moreover, the specificity was 84.0% for biparametric MRI and 58.0% for PI-RADS v2/PA PI-RADS v2. For cancers in the transition zone (TZ), the diagnostic sensitivity was 93.4% for PA PI-RADS v2 and 88.2% for biparametric MRI/PI-RADS v2. Furthermore, the specificity was 95.4% for biparametric MRI/PI-RADS v2 and 78.0% for PA PI-RADS v2. Conclusions: The overall diagnostic performance of the three protocols showed minimal differences. For lesions assessed as being category 3 using the biparametric MRI protocol, PI-RADS v2, or PA PI-RADS v2, it was thought prostate cancer detection could be improved. Attention should be paid to false positive results when PI-RADS v2 or PA PI-RADS v2 are used. Prostate cancer is the second most frequent cancer in males worldwide , and itsAs a product of international collaboration among the American College of Radiology, ESUR, and AdMetech Foundation, the second version of PI-RADS (PI-RADS v2) was released  and usedAlthough PI-RADS v2 has been used worldwide, its false negative rate could still be as high as 14% . In 2016A biparametric MRI assessment (T2WI + DWI) is also an important method for prostate cancer screening ,10,11,12There are both advantages and disadvantages for the three protocols mentioned above . However, to the best of our knowledge, there are few studies that compare the diagnostic performance of such protocols (12–15). Our aim in this study was to compare the diagnostic performance of PI-RADS v2, PA PI-RADS v2, and biparametric MRI in prostate cancer detection.This retrospective study was approved by our Institutional Review Board (protocol no.LLBA201936A), and written informed consent was waived. In total, 261 cases of prostate MRI performed between January 2016 and November 2018 were retrospectively reviewed. The inclusion criteria were as follows: (1) patients with elevated prostate-specific antigen (PSA) levels, positive in digital rectal examination or with suspected lesions found in MRI and (2) transrectal ultrasound guided fine needle biopsy was performed after the MRI scan. Moreover, the exclusion criteria were as follows: (1) a marked artifact induced by a hip implant; (2) the PI-RADS assessment could not be finished due to a non-standard mpMRI scan; (3) duplicate cases; (4) prior treatment including endocrine therapy, cryotherapy, and radiotherapy .2 were used for DWI. For DCE-MRI, 0.1 mmol/kg Gd-GDTA  was administered at a rate of 2.5 mL/s via a power injector. The whole DCE scan lasted for about 320 s for 16 phases with a temporal resolution of 6.3 s per phase.All the prostate MR examinations were performed on a clinical Philips 1.5 Tesla scanner  by using a 16-channel phased-array coil. Pulse sequences included axial T1-weighted imaging (T1WI), turbo spin-echo T2-weighted imaging (T2WI), single-shot echo-planar DWI, and DCE-MRI . B valueAll the MR examinations and prostate biopsy results were initially reviewed by a senior radiologist with 20 years of experience in prostate MR imaging. Suspicious lesions were digitally marked with elliptical regions of interest (ROI) as targeted lesions to ensure that both readers would evaluate the same lesion. Before the evaluation, patient images were randomized, anonymized, and a timeframe of 3 weeks was maintained to minimize reporting bias. Subsequently, two radiologists with more than 5 years of experience in abdomen MR imaging independently evaluated MR examinations of previously noted targeted lesions. A score of 1–5 was assigned according to PI-RADS v2, PA PI-RADS v2, and biparametric MRI protocols. Next, PI-RADS categories 4 and 5 were set as malignant ,8,9. AdjTransrectal ultrasound guided prostate biopsy was performed by urologists in all the patients within two weeks after an MR scan. All the suspected lesions found on mpMR were located according to the 6-zone method. Moreover, the ultrasound guided 12-core biopsy was performed afterwards. Records included the biopsy site and Gleason score.Statistical analysis was performed with the SPSS software  and MedCalc Statistical software .t test for independent samples was used to compare the PSA level of prostate cancer and benign lesions, while a Kolmogorov–Smirnov was used as normality test. p < 0.05 was defined as statistically significant.An inter-reader agreement was assessed using Kappa statistics, and the degree of agreement was classified as follows: κ > 0.8, perfect; 0.8 ≥ κ > 0.6, good; 0.6 ≥ κ > 0.4, moderate; 0.4 ≥ κ > 0.2, fair; 0.2 ≥ κ > 0, poor. The receiver operating characteristic (ROC) curve and decision curve analysis (DCA) of PI-RADS v2, PA PI-RADS v2, and biparametric MRI were drawn for diagnosing prostate cancer . The diagnostic sensitivity, specificity, accuracy, positive predictive value (PPV), negative predictive value (NPV), and area under the ROC curve (AUC) were calculated, and the Z test was used to compare the AUC. A A total of 224 patients  were included. Clinical data and Gleason score results are listed in n = 77), AUC of biparametric MRI (0.9365) > PI-RADS v2 (0.9200) > PA PI-RADS v2 (0.9090); (3) for lesions in TZ (n = 147), AUC of PA PI-RADS v2 (0.9225) > biparametric MRI (0.9205) = PI-RADS v2 (0.9205). The difference was not statistically significant (p > 0.05) for all of the AUC comparisons mentioned above.We drew ROC curves and DCA for the three protocols for diagnosing prostate cancer  and AUCsAs the three protocol are cross in DCA, it is hard to say which protocol is better. However, we can conclude from the DCA that when the high-risk threshold in the interval of 0.1 to 0.45, bpMRI is better, while pa PI-RADS v2 is better in the interval of 0.5 to 0.7. When the high-risk threshold is larger than 0.75, pa PI-RADS v2 is similar to PI-RADS v2 and better than bpMRI.Among all the significant prostate cancers, biparametric MRI misdiagnosed 4 lesions as category 3 (1 in PZ and 3 in TZ). Two misdiagnosed lesions in TZ were correctly detected using PA PI-RADS v2. The one in PZ was correctly detected using both PI-RADS v2 and PA PI-RADS v2.Among all clinically significant prostate cancers, malignant lesions (TZ + PZ) were evaluated as category 3 according to the primary determining sequence (DWI for PZ and T2WI for TZ). They were finally upgraded to category 4 after combining other sequences as follows: 3 (3.3%) for PI-RADS v2, 5 (5.6%) for PA PI-RADS v2, and 2 (2.2%) for biparametric MRI. For benign lesions (TZ + PZ) upgraded from category 3 to 4 after combining other sequences, the misdiagnosed ones were as follows: 5 (3.7%) for PI-RADS v2, 26 (19.4%) for PA PI-RADS v2, and 0 (0.0%) for biparametric MRI .p < 0.001) and biparametric MRI . A moderate match was found in the PA PI-RADS v2  and DCE results   .The diagnostic accuracy for prostate cancer (category ≥ 4) according to the three protocols  via the two radiologists was 93.3% and 93.3%; 95.6% and 95.6%; and 93.3% and 92.2%, respectively. The diagnostic accuracy for prostate benign lesions (category ≤ 3) according to the three protocols proposed by the two radiologists was 87.3% and 89.2%; 73.9% and 74.6%; and 92.5% and 94.0%, respectively .3, and/or extra prostate extension) [PI-RADS v2 is a new MRI report system that aims to detect clinically significant prostate cancer  . Previoutension) ,14,15,16tension) .For the PZ lesion, the assessment criteria were almost the same between the PI-RADS v2 and PA PI-RADS v2 protocols. Only the standards for upgrading PI-RADS from a category 4 to 5 were different, but this did not affect the detection of prostate cancer in PZ. For the TZ lesion, the assessment criteria were the same between the PA PI-RADS v2 and biparametric MRI protocol. Thus, our study mainly focused on comparing the diagnostic performances of (1) PI-RADS v2/PA PI-RADS v2 and biparametric MRI in PZ and (2) PI-RADS v2/biparametric MRI and PA PI-RADS v2 in TZ, and (3) the overall performance of the three protocols in TZ + PZ.The inter-observer agreements of PI-RADS v2 and biparametric MRI were better than that PA PI-RADS v2, which was moderate. PA PI-RADS v2 revised the upgrading standard (for category 3 to 4 and category 4 to 5), which made the assessment more complicated and may be the main reason for the lower inter-observer agreement.In this study, the diagnostic performance of biparametric MRI and PI-RADS v2/PA PI-RADS v2 were without statistical distinction in PZ lesions. The main difference between PI-RADS v2/PA PI-RADS v2 and biparametric MRI is that the latter does not take DCE results into consideration while the former criteria upgrades lesions from category 3 to 4 when the DCE results are positive ,8. In thThe specificity of PI-RADS v2/PA PI-RADS v2 was relatively low in this study, which may be due to the small sample size of benign lesions in PZ and false positive enhancement in benign lesions including prostatitis, hyperplasia, and intraepithelial neoplasia ,24,25. AFor TZ lesions, the diagnostic performance between PA PI-RADS v2 and PI-RADS v2/biparametric MRI was comparable. The main difference between PI-RADS v2/biparametric MRI and PA PI-RADS v2 was that, for category 3 TZ lesions, the former two protocols upgraded lesions to category 4 only when they scored 5 in DWI, but the latter upgraded lesions to category 4 when they scored 4 in DWI or were positive in DCE . AdjustmIn total, 19 (17.4%) out of 109 cases of benign lesions in TZ were misdiagnosed as cancer by upgrading the standard in PA PI-RADS v2. The specificity and accuracy of PA PI-RADS v2 (77.98% and 81.97%) for TZ lesions were lower than those of PI-RADS v2/biparametric MRI (95.41% and 93.54%). The high false positive rate could be attributed to the changes in upgrading the standard from category 3 to 4 in PA PI-RADS v2. Moreover, 14 misdiagnosed cases were upgraded by the positive DCE result, wherein the inter-reader agreement was only moderate (k = 0.408). The assessment based on the DCE image was, to some extent, subjective and controversial, which led to lower specificity and accuracy. Interpreting images of benign lesions is complicated, and it is sometimes hard to differentiate them from prostate cancer based on a DCE image . EncapsuOur results showed minimal differences in the overall diagnostic performance of the three protocols. Although biparametric MRI removed DCE and evaluated lesions only based on T2WI and DWI, it had the highest specificity and accuracy and was the best at avoiding misdiagnoses for benign lesions such as cancer. The sensitivity was the highest in PA PI-RADS v2, but its specificity and accuracy were the worst, so it requires revision and improvement.Prior research results were inconsistent regarding the diagnostic performance of the different protocols. Auer and Wang et al. ,36 reporIn our research, after the combined evaluation with DCE results, 3 of the 4 misdiagnosed cases were correctly detected by either PA PI-RADS v2 or PI-RADS v2. Thus, for lesions of category 3 in biparametric MRI, the application of DCE via PA PI-RADS v2 or PI-RADS v2 protocols could improve cancer detection.There were some limitations in this study. First, this is a retrospective study performed at a single institution. Second, we did not assess the performance of the three protocols in evaluating the prostate cancer staging. Third, the sample size for our evaluation was generally small. Further investigations by other centers/multi-centers with larger sample size are required to confirm our preliminary observations. Fourth, our study did not use 3.0T on prostate MRI scanning, which would be benefit the increasing signal-to-noise and resolution of images.In conclusion, the diagnostic performance of PI-RADS v2, PA PI-RADS v2, and biparametric MRI resulted in good prostate cancer detection, with minimal significant differences among the methods. We recommend biparametric MRI for cancer screening because it saves time, does not need contrast media, and shows satisfactory diagnostic performance. For category 3 lesions found via the biparametric MRI protocol, DCE can improve the detection rate for clinically significant prostate cancer . However, the specificity and accuracy will be lower when using DCE, especially for lesions in PZ. Further study is required with regard to how to improve detection. Moreover, further studies are needed to reduce the misdiagnosis of cancers.


Heart failure (HF) with preserved ejection fraction (HFpEF) is currently the predominant form of HF with a dramatic increase in risk with age. Low‐grade inflammation, as occurs with aging (termed “inflammaging”), is a common feature of HFpEF pathology. Suppression of proinflammatory pathways has been associated with attenuated HFpEF disease severity and better outcomes. From this perspective, inflammasome signaling plays a central role in mediating chronic inflammation and cardiovascular disease progression. However, the causal link between the inflammasome‐immune signaling axis on the age‐dependent progression of HFpEF remains conjectural. In this review, we summarize the current understanding of the role of inflammatory pathways in age‐dependent cardiac function decline. We will also evaluate recent advances and evidence regarding the inflammatory pathway in the pathophysiology of HFpEF, with special attention to inflammasome signaling. Heart failure (HF) with preserved ejection fraction (HFpEF) is a complex syndrome characterized by multisystem disorders. Despite the increasing age‐dependent prevalence, there are very few effective therapies. Considered now as the greatest unmet medical need in cardiovascular disease, comorbidity‐driven inflammation has emerged as a critical component of HFpEF pathogenesis. Thus, chronic low‐grade inflammation may drive key pathophysiological changes in HFpEF. AFatrial fibrillationCOPDchronic obstructive diseaseHFheart failureHFpEFheart failure with preserved ejection fractionHFrEFheart failure with reduced ejection fractionILinterleukinLVleft ventricleNLRP3nucleotide‐binding oligomerization domain leucine‐rich repeat and pyrin domain‐containing protein 31Heart failure (HF) is a growing public health problem worldwide exerting heavy burdens on productivity, morbidity, mortality, and healthcare expenditure. Heart failure is highly prevalent in elderly people and is associated with multi‐morbid illness. Hypertension, sarcopenia, diabetes, obesity, pulmonary congestion, and atherosclerosis‐related vascular diseases are common independent risk factors for developing HF  domain to assemble the NLRP3 inflammasome. Subsequently, the active form of caspase‐1 cleaves pro‐IL‐1β and pro‐IL‐18 to their active proinflammatory forms  or other pathogens by caspases‐1, 4, and ‐5 (in humans) and caspase‐1 and ‐11 in mice  atrial fibrillation , which may impair endothelial angiogenesis and cardiac vascularization  diastolic function is a hallmark of cardiac aging. Age‐related diastolic dysfunction features prominently in HFpEF, through impaired relaxation, myocardial and myocyte stiffening, and associated changes in filling dynamics  occur, but preliminary evidence suggests that one transition point occurs by way of the coronary endothelium. Circulating proinflammatory cytokines trigger the upregulation of vascular cell adhesion molecule‐1 (VCAM1) and E‐selectin ‐a distinct macrophage population that arises from extramedullary hematopoiesis that takes up residence in the heart during fetal development , cytotoxic phenotype to an anti‐inflammatory, and tissue‐remodeling capacities. The coexistence of proinflammatory and pro‐remodeling phenotypes in myocardial tissue promotes the feed‐forward cycle of inflammation and fibrosis. For instance, in HFpEF, significant recruitment of peripheral monocytes also occurs, however, resident macrophages also expand, in response to pressure overload, secrete higher levels of IL‐10, and promote diastolic dysfunction through profibrotic signaling including TGFβ/Smad signaling  which orchestrate both the innate and adaptive immune response  have been implicated in HFpEF development  is reduced in HFpEF  serve as conduits between the innate and adaptive immune systems. Antigen‐presenting cells present antigens to CD4+ or helper T cells , a monoamine oxidase inhibitor AZD4831), a xanthine oxidase inhibitor , and an inhibitor of uric acid transporter URAT1 (verinurad). Empagliflozin has shown profound cardioprotective benefits in HFrEF  to many age‐related disorders. Inflammasome activation and subsequent crosstalk with innate and adaptive immunity during aging is a prime signal to trigger multiple inflammatory signaling pathways that converge to impair heart function. The chronic and systemic inflammatory state is a central and prominent feature associated with HFpEF, which is disproportionately found in older individuals. Although there is evidence supporting “inflamed” hearts, this inflammatory HFpEF state is deeply influenced and perpetuated by non‐cardiac sources. The activation of NLRP3 inflammasome signaling in HFpEF remains circumstantial requiring future investigations. Hence, strategies aiming to inhibit cardiac proinflammatory pathways in HFpEF, including NLRP3 inflammasome signaling, may be appropriate therapeutic anti‐inflammatory interventions Thus, attenuation of inflammatory burden during aging may attenuate the severity of symptoms observed in HFpEF patients, which in turn can enhance the quality of life and life expectancy.None declared.TM, YNL, and AGI researched data for the article and drafted the manuscript. All authors have read and agreed to the published version of the manuscript.