Our proposed method, network decoupling, is based on analyzing the communities in each network layer individually and then aggregating the analysis results. We (i) describe our network decoupling algorithms for finding communities, (ii) present how network decoupling can be used to express different types of communities in multilayer networks, and (iii) demonstrate the effectiveness of using network decoupling for detecting communities in real-world and synthetic data sets. Compared to other algorithms for detecting communities in multilayer networks, our proposed network decoupling method requires significantly lower computation time while producing results of high accuracy. Based on these results, we anticipate that our proposed network decoupling technique will enable a more detailed analysis of multilayer networks in an efficient manner.Networks (or graphs) are used to model the dyadic relations between entities in complex systems. Analyzing the properties of the networks reveal important characteristics of the underlying system. However, in many disciplines, including social sciences, bioinformatics, and technological systems, multiple relations exist between entities. In such cases, a simple graph is not sufficient to model these multiple relations, and a multilayer network is a more appropriate model. In this paper, we explore community detection in multilayer networks. Specifically, we propose a novel  However, in reality, most systems are defined, not by a single, but by multiple types of relations. For example, a group of friends may be connected through multiple social networking platforms such as Facebook, Twitter as well as by email. Technological networks such as transportation networks can consist of airline, train, or bus routes. To accommodate multiple types of relations, the systems are modeled as a set of networks. This set of networks, each representing a different relation, forms a multilayer network. Here, we focus on composed network), and then apply the existing analysis algorithms for single networks. Given an undirected and unweighted network, the layers can be combined using the primitive Boolean operations AND, OR and NOT.The typical approach to analyzing multilayer networks is to combine all, or a subset, of the layers to form a single network  to use for transporting material, under limited resources. They may want to select combination of which two routes would give the most connectivity. If the relations with respect to each condition is represented as a layer, then only one composed network, formed by combining all or a subset of the layers using an OR operation. The problem of efficiently creating different composed networks through varying combinations of layers and operations has been rarely addressed.These examples demonstrate that the number of composed networks increases exponentially with the layers of the multiplex, and analyzing the entire set is computationally expensive. To date, as discussed in Section 2.2, most multilayer analysis is based on creating We propose to reduce the number of redundant computations through a novel method of network decoupling. In network decoupling, each individual network layer is analyzed independently once and only once, and then the results are combined as required. Network decoupling  has several advantages as follows;Analysis of the different composed networks will incur some redundant computations, since different composed networks can have some of the layers in common. Computational efficiency. Network decoupling reduces the time for analysis. Analyzing each layer separately helps in identifying the relevant edges per layer, and reduces the number of edges to combine.Flexibility of combination. Network decoupling facilitates incorporating changes to the multilayer network, such as addition of a new layer or change in the structure of an old layer. Using decoupling, only the added or changed layer has to be analyzed, and combined as required.Reduced information loss. When analyzing a composed network, it is challenging to understand how the individual layers contributed to the analysis. Using network decoupling, since each layer is analyzed individually, their respective contributions can also be identified.The primary challenge is to design appropriate aggregation functions, such that the communities obtained using network decoupling are similar to those obtained by applying community detection on the composed networkHere, we focus on computing communities in multilayer networks using decoupling. Communities are groups of tightly connected nodes. Using network decoupling, we first find the communities in each individual network and then develop aggregation functions, such that the communities from each layer can be combined to produce the communities in the composed network . The priG1, G2, …, Gx, that are combined using a Boolean operation ⊕ to form the composed network, and a community detection algorithm COMM, that is used to find communities, develop an aggregation algorithm Π, such thatGiven a set of layers the results of finding the communities in the individual layers and then aggregating them via Π, should be similar to the communities obtained from the composed network where the layers are combined using the Boolean operator ⊕. Developing the aggregation algorithm is challenging, since the structure of the composed network can change after combination, and the aggregation process has to account for that change when combining the communities.In other words, we aim to find an aggregation algorithm Π, such that We provide an overview of multilayer network, creation, type of communities in MLN and how boolean operations can be used to combine the layers.A multi-relational data set, can be represented as a homogeneous multilayer network. Each feature is represented as a separate layer. The set of entities remain the same in each layer. The edges, based on relations between the entities, change across the layers with respect to the corresponding feature.We use the Internet Movie Database (IMDb) to illustrate how a multiplex is constructed. The IMDb is an online database that contains information on television programs and movies including actors, directors, genre, and year of release , 2018. Wf1) and drama (f2) to form the two layers, G1 and G2, respectively, and modeled the co-actor relationship among 18 actors (denoted by nodes numbered from 1 to 18). Two actors are connected if they acted in movies of the same genre. Note that although the same 18 actors are present in both layers, the structure varies due to the difference in relations. By taking the information from the two networks together we can gain interesting insights to the data. For example, actors I3 and I8 have never worked together in a drama, but have worked together in a comedy. Also, observe that the actors I4 and I14 have the most connections in the drama genre, whereas actors I9, I10, and I11 are the nodes with the most connections in comedy.An example of the multilayer network is given in an actor is defined as an entity that can represent a particular person, animal, organization, city, country etc. In In recent literature, Hanteer  and BrauA node is the existence of a given actor in a given layer. The same actor present in different layers represents different nodes. In k representing actor i, is denoted as We also differentiate between the actor and their existence in a layer. i et al.  as folloThe pillar community extends across all the layers. For each actor that belongs to a community, all the nodes belonging to the actor must belong to the same community. An example of pillar community is presented in k<NL. Here, NL is the total number of layers. As before, for each actor that belongs to a community, all the nodes belonging to the actor must belong to the same community for k layers. We see a structure of semi-pillar community in The semi-pillar community extends across k layers where 2 ≤ GAND21 (AND composition) and GOR21 (OR composition) for multiplex in We now demonstrate how the different layers of the multiplex can be combined, and how communities are detected in them. Communities in AND-Composed Layers. AND composition allows users to find communities that are related across all the features. C-SG-AND) shows the steps of finding communities in the composed network, using a standard community detection algorithm such as Infomap .Groups of actors who have expertise in working together in all of these conferences: ICDM, SIGMOD and VLDB (DBLP multiplex).Authors who have co-authored a paper published in all of these features: light conditions, weather conditions, road conditions, and speed limit (Accident Multiplex).Accidents that have similar conditions for Communities in OR-composed layers. OR-composition forms a composed network that includes an edge if it appears in at least one of the layers. C-SG-OR. In an OR composition, the composed network is formed of the union of the edges from all the networks, and then the communities are found in the composed network. Examples of queries that can be addressed by the OR composition are;or drama (IMDb multiplex).Actors who have acted together in either a comedy at least one conference (DBLP multiplex).Authors who have co-authored a paper published in at least one condition in common (Accident Multiplex).Accidents that have bridge edges. Formally, if there exists an edge, m in layer k) and n in layer k) where m≠n, then this edge is a bridge edge. In the AND and OR composed-layer of I1 and I5 belong to different communities, but are connected by a bridge edge. The actors I9 and I15 have a bridge edge in the OR composed network, but not in the AND-composed network.We term the external edges that connect two communities as The AND composed networks have smaller, but more communities, than the OR composed networks. In general, the communities in the AND composed layer form subsets of the communities in the OR composed layer. We will leverage this property to develop our aggregation algorithms.G1, G2, G3, and G4. Also consider two composed networks formed from the multiplex, namely, GAND2AND31 and GAND2AND41. In this case, the composed layer related to GAND21 remains unchanged, but has to be recomputed, leading to extra computations.The traditional method of first forming the composed network and then analyzing can be computationally expensive when multiple composed networks have to be considered. This approach can lead to redundant operations. Consider a multiplex with four layers We propose network decoupling for efficient community detection on multiplex networks. The communities in each layer are identified separately and the results are then aggregated to obtain the results with respect to the composed network. The challenge is to develop aggregation algorithms, that can correctly aggregate the communities from each of the layers to obtain the communities over the composed network. We now present the aggregation methods for AND and OR composition. For ease of understanding we will discuss the algorithms with respect to two layers. Note, however, that our algorithms can be easily extended to multiple layers.AND_composed network) in Santra et al.  rather than being fully or partially merged with other communities, then C is a self-preserving community. A community is self preserving if the vertices in it are other communities in the graph. Thus, the subgraph forming a self-preserving community is not affected by changes to the remainder of the network. The communities in Layer 2 in A self-preserving community indicates that the community is loosely connected with the remainder of the network. Removing parts of the community will not change the structure or composition of the if the communities from the layers are self preserving, then the communities of the AND-composed graph can be obtained by taking the intersection of the vertices of the communities from the individual layers.When two layers are combined using an AND operation, then certain edges are deleted from each layer, and thus from certain communities. If the communities are self preserving, then this deletion will only affect that community and not the others. This is the main result of Santra et al. , which iCV-AND , then, two dissimilar groups are marked to be similar, which is incorrect.As an example, consider the community  network , which iedges rather than vertices as follows. Here we consider pairs of communities, one from the first layer and the other from the second layer, and obtain the new community by taking the common edges among the pair. For every pair of communities, Gi and Gj, the edge-based community intersection, We address these limitations by developing a community detection method, CE-AND see , that islabel an edge as internal (if both end points are in the same community) and external or bridge otherwise.We assume that the communities in the individual layers and the composed network have high clustering coefficients. That is, we do not consider accidental communities such as an edge or a line graph, that are formed due to an algorithmic artifact rather than the structure of the network. If such trivial communities are formed, we consider each vertex in them as a singleton community. The clusters formed by the intersection algorithms do not have this restriction, since they are not obtained using community detection algorithms.We now present a proof of how well the clusters obtain by X∈Ψ, there will exist a set of communities i ≤ m, that form a partition of the vertices in X, if and only if, the set of edges common to all layers have the same label in all the layers.Lemma 3.1. For any given cluster Proof. We first prove the condition that if the common edges have the same label in all the layers, then the set of the union of vertices in X∈Ψ.X be UX. Let the set of vertices belonging to community VX. Since the communities are disjoint to prove that VX is a partition of UX, we have to prove that VX = UX.Let the set of vertices belonging to the cluster UX ⊆ VX. We simply select the communities such that all vertices in UX are included.It is easy to show that there exists a set of communities such that VX⊆UX by contradiction. Let v be a vertex that is in set VX but not in UX. Since CE-AND retains all the common internal edges, and v is not in UX, therefore v will be connected to its neighbors in VX by one or more external (or bridge) edges. Since we assume that all common edges have the same labels, therefore in none of the layers v is tightly connected to any subset of VX. Moreover, the communities in the composed network have high clustering co-efficient (or are singletons). Since v is not tightly connected to vertices in VX it cannot be part of the community. Thus our assumption was wrong, and VX ⊆ UX. Taken together, VX ⊆ UX and UX ⊆ VX; thus UX = VX, and VX is a partition of UX.We prove For the only if part we show that if the common edges do not have the same labels in all the layers, then there may not exist a set of communities that form a partition of the vertices in a given cluster.We provide such an example in The community in all layers are considered, CE-AND produces two communities, Also consider the community OR composed networks). The number of edges in the OR-composed network is the union of the edges in each layer. For any two layers Gi and Gj, the total number of edges is |Ei∪Ej|.We now consider how to obtain communities in composed networks formed using the OR operation . Vertices that are not assigned into communities are each separately assigned to a metanode (Line 5–9). Connect two metanodes, U and V via a metaedge, if there exists an internal edge, in at least one of the layers between an element (node) of U and an element (node) of V (Line 10-14). Apply appropriate weights to these edges (Line 15). Apply community detection on the metagraph (Line 16). The communities in the OR-composed network are obtained by expanding the metanodes in the communities obtained by the CE-OR algorithm.Find the common communities in all the network layers (Line 1) by using CE-AND. Then construct a metagraph (OR-MG), as follows. Each metanode represents in at least one of the layers.The metanodes represent vertex sets of varying sizes, and the number of edges between them represent the degree of similarity. Although the original graph is unweighted, the edges in the metagraph are weighted to quantify the extent of this similarity. A critical component of the CE-OR algorithm is based on correctly assigning these weights. We connect two meta nodes only if at least one pair of vertices from each meta node are connected by an internal edge, A, B), let VA and VB be the set of nodes in the meta communities A and B, respectively. Further, let the set of all edges  between VA and VB be EA, B. We use the following two strategies to compute the weight of the metaedge;For any meta edge  = |EA, B|Fractional is the fraction of connected nodes between the two communities; I8 are used to form the metanodes . Thus at least one of the communities has an internal edge that was bridge edge in all the layers. This goes against our criteria that all internal edges for communities in the composed network, should be internal in at least one of the layers. Thus our assumption is wrong and VK ⊆ UK. Since the communities are disjoint and UK = VK, thus the statement is proven.To prove the only if direction, we show that if the communities in the OR-composed layers have internal edges that were bridge edges in all the layers, then there may not exist a set of communities that form a partition for the vertices in a given metanode clusters.An example of this is given in Consider the community However in the community The implication of Lemma 3.1 and Lemma 3.2 is that the CE-AND or CE-OR operations are successful if they create clusters that contain one or more communities in the composed networks in their entirety. Thus the communities can be divided into groups, such that each group can be mapped to exactly one cluster formed by the CE-AND or CE-OR operation. Therefore, the vertices in the composed network can be partitioned into subgraphs, with each subgraph relating to a cluster. Hence CE-AND and CE-OR operations are successful when each layer is formed of several loosely connected subgraphs, and bridges connecting the subgraphs do not change across the layers.The primary limitations of our CE-AND and CE-OR algorithms is due to the non-inclusion of bridge edges. In the AND-composed network, we rationalize this non-inclusion by positing that communities formed solely of bridge edges cannot be dense, and hence are not strong communities. In the OR-composed network, we only exclude an edge if it is a bridge edge in all the layers.We demonstrate how CE-AND and CE-OR can be used as building blocks for the pillar and semi-pillar communities described in Section 2.2. Note that pillar and non-pillar communities are not dependent on how the networks/layers are combined, but on which communities are common across a given set of layers.Since in pillar communities the same set of vertices form communities in every layer, therefore as per Lemma 3.1, the communities formed by CE-AND will be pillar communities. However, due to the strict restrictions of the CE-AND criteria, i.e. the edge has to be present in every layer, some vertices from pillar communities may be missed. To obtain these missing vertices, we then extend the communities found in CE-AND as per p<k. For each combination of layers we compute the communities using CE-AND. Note that since we use the decoupling method, therefore we need to compute the communities in each layer exactly once, and then combine the results. We identify the communities with the highest number of nodes, and extend them when possible using CE-OR. These communities across the layers form the semi-pillar communities.To find the semi-pillar communities, we take combination of all possible p layers from k layers, where 2 ≤ Infomap  was the graph obtained by the generator. We applied cross perturbation to create layers (L2 and L3), as follows We selected two edges  and , and replaced them with new edges  and . Thus the number of edges and the degree distribution remain the same but the structure changes. In layer L2 we applied this perturbation to 1% of the edges and in layer L3 to 5% of the edges. Vertices:32,768; Edges in L1:230,445; Edges in L2: 230,445; Edges in L3:230,445.Ground Truth and Accuracy Metrics: We use the communities obtained using C-SG-AND and C-SG-OR as the ground truth. We disregard singleton communities. We use two metrics to evaluate the accuracy of the communities - i) Normalized Mutual Information (NMI) that measures the quality with respect to the participating entity nodes only and ii) modified-NMI that also takes into account the topology of the communities. For both metrics higher is better, with maximum value of 1 and minimum of 0 [definitions in Labatut ( Labatut ]. Each maccuracy obtained with CE-AND is higher than that from CV-AND.For the AND-composed networks we show in wa) and Fractional (wf). The results show that the accuracy obtained using both the metrics are similar.For the OR-composed networks we show in We now compare the time taken to obtain the communities using the aggregation methods  with respect to C-SG-AND and C-SG-OR. community edges is required to generate the meta graph (OR-MG) on which we apply Infomap. If the layers are sparse and the multiplex contains many bridge nodes, then cost of generating the meta graph and applying Infomap will become an overhead as compared to simply applying Infomap on OR graph (C-SG-OR approach). This can be seen from the DBLP multiplex where sparse layers (density of densest layer (SIGMOD) = 0.0001) make the CE-OR 67% less efficient as compared to C-SG-OR. However, for multiplexes with fewer bridge edges , CE-OR is significantly faster.CE-OR algorithm achieves a better accuracy as compared to the baseline algorithms across a number of ground truth data sets.We compare the performance of our proposed decoupling based community detection algorithms against 16 community detection algorithms for multiplexes presented in  in both community sets, it is called an agreement. The value of omega index ranges between 0 and 1. Here, 1 means two sets of communities are identical to each other. Formally, the omega index is computed as;Omega index value is calculated by taking the mean of the number of agreements on two community sets l = the maximum number of times a node pair appears together in both C1 and C2 at the same time,N = total number of possible node pairs,Aj = number of node pairs that are grouped together j times in both communities, andNj, 1, Nj, 2 = number of node pairs that have been grouped together j times in C1, C2, respectively.We have the ground truth communities available for real world and synthetic data sets. We apply our aggregation algorithms (CE-OR) on the data set AUCS which is 90 percent pillar, DKPOL, PEP and PNP which are 100 percent pillar, and SEP and SNP, which are semi-pillar.on an average the CE-OR (Metric-Aggregate) algorithm has 89% accuracy and CE-OR (Metric-Fraction) algorithm has 82% accuracy, which is significantly higher than the other methods.We compared the accuracy of 17 community detection algorithms along with our proposed CE-OR aggregation algorithm over real world and synthetic data sets which have ground truth community structure available. The algorithms used are: flat_nw and flat_ec  values for the 16 existing community detection algorithms along with our proposed CE-OR aggregation algorithm for each data set. However, for AUCS data set, CE-OR does not perform better than many of the existing algorithms as AUCS does not have complete pillar partitioning. Our CE-OR algorithm improves the accuracy for data sets with 100% pillar partitioning community structure or known semi-pillar community structure. All other data sets with pillar partitioning the accuracy of CE-OR ranges from 85% (DKPOL) to 100% (PEP).In We now define the NOT composition, and demonstrate our proposed network decoupling methods can be used to efficiently and accurately analyze networks composed of a combination of Boolean expressions.complement of the edge set of that layer, i.e. the new layer will have all those edges that are not part of the original layer. Communities in a NOT layer will represent the groups of nodes that are not strongly connected. Examples of queries that can be answered using NOT areNOT of a layer will represent the not acted together in a comedy (IMDb multiplex)Groups of actors who have never co-authored a paper in VLDB (DBLP multiplex)Groups of authors who have did not have same Light condition (Accident multiplex)Groups of accidents that With respect to the single graph approach, these types of analysis can be handled by first generating the NOT layer and then applying community detection. AND, OR and NOT can be applied in different combinations, expanding the spectrum of analysis options. Although taking the complement of a layer is expensive and increases the number of edges in that layer, the cost depends on the graph density of the layer. Also, rewriting the expressions using the De Morgan's law can reduce the costs.We demonstrate how general Boolean expressions can be computed using the decoupling approach. We use the DBLP multiplex with authors who publish papers at different conferences to address interesting analysis objectives. We consider all papers that were published from 2003 to 2007 in two high ranked conferences (VLDB and SIGMOD) and two medium ranked conferences (DASFAA and DaWaK). Based on whether two authors (nodes) have co-authored a paper in a particular conference, four layers were generated - all with the same 5116 vertices. VLDB , SIGMOD , DASFAA  and DaWaK .Few interesting analysis objectives that can be computed on the DBLP multiplex using Boolean expressions are as follows:both the highly ranked conferences, but have never published in either of the medium ranked conferences?Which collaborating groups who have published in Which co-author groups have only been able to publish in the low to medium rank conferences?Which author groups have published only in VLDB?Which are collaboration groups who have published inboth the highly ranked conferences, but havenever published in either of themedium ranked conferences?”, we will compare the evaluation process for the traditional single graph approach and the proposed decoupling approach. Single graph approach (SG): For the SG approach, the Boolean expression will correspond to SG: COMM[(VLDB AND SIGMOD) AND NOT (DASFAA OR DaWaK)]Based on the requirements of the analysis, it is important to figure out (a) the multiplex layers required and (b) the order in which the layers have to be composed using AND, OR, NOT. For the first analysis, “This corresponds to first generating the required composed single graph and then applying the community detection algorithm to find the final set of communities. These communities acts as the ground truth. We used Louvain Blondel et al.  to find DEC1: COMM(VLDB) CE-ANDCOMM(SIGMOD) CE-ANDCOMM (NOT (DASFAA OR DaWaK))Using network decoupling, this expression will correspond to That is, the layer-wise communities are composed to obtain the final set of communities. Alternatively, De Morgan's Laws can be applied to obtain another expression for the decoupling based boolean composition -DEC2: COMM(VLDB) CE-ANDCOMM(SIGMOD) CE-ANDCOMM (NOT(DASFAA)) CE-ANDCOMM(NOT (DaWaK))NOT (DASFAA OR DaWaK) by using the traditional OR of two layers and then take its complement. DEC2 uses the decoupling approach using operators CE-AND, and NOT as discussed in this paper. The layers of DBLP used above are very sparse, especially DASFAA and DaWaK. Hence, DEC2 will not be as efficient as DEC1 since it has to compute the complement of two layers (resulting in dense graphs) and then apply the decoupling approach. DEC1, on the other hand, has only one complement to compute.We compare the efficiency of DEC1 and DEC2 with the single graph approach. We will evaluate the For accuracy, the NMI and m-NMI values for the communities obtained by DEC1 and DEC2 have been compared against the communities obtained by SG. Both method, DEC1 and DEC2, provide more than 95% accuracy.same set of communities. In DEC1, the number of CE-AND compositions are 2 whereas in DEC2 there are 3. Moreover, as the layers of the DBLP multiplex are sparse, their complement is dense. Thus, in DEC2 the Louvain is applied to two dense NOT layers. Thus, DEC2 will have a higher cost as compared to DEC1. Our results show that DEC1 is 2 times faster than DEC2. Therefore, it is very important to understand when to rewrite the expression  especially when the NOT operator is used on a composition of layers. Finally, it is interesting to note that even with 2 dense graphs, DEC2 comes out better than the single graph approach. This further validates our decoupling approach even in the presence of NOT operator.Both DEC1 and DEC2 resulted in the One hundred and two communities are obtained from DEC1 and DEC2 that satisfy the requirement. Surajit Chaudhari who won the VLDB 10-Year Best Paper Award (2007) with Vivek Narasayya and VLDB Best Paper Award (2008) with Nicolas Bruno, apart from winning ACM SIGMOD Contributions Award (2004).Divyakant Agrawal who has 24000+ citations (Google scholar).Peter A. Boncz and Stefan Manegold from highly cited paper (350+ citations for MonetDB/XQuery) in SIGMOD 2006, and also won the VLDB 10-year award.Recently, many analytical tasks have used multilayer networks to handle varying interactions among the same or different sets of entities such as co-authorship network in different conferences  layers of a HoMLN using Boolean and other operators or by considering the entire MLN as a whole, leading to issues with respect to loss of information and computational inefficiency.Recently, community detection algorithms have been extended to Homogeneous MLNs (see reviews Fortunato and Castellano, Recent works include Jin et al.  using a To identify the communities in the temporal multiplex graph, the authors in Rebhi et al.  proposedBio-inspired optimization has successfully solved the problem of community detection in network that we observe from the work Osaba et al.  where thWe presented algorithms for efficiently finding communities in Boolean composed layers of multiplex networks. The results show that for most cases our algorithms are significantly faster than the standard methods and produce results of similar quality. The only cases that our algorithm fails is when the layers have significantly more bridge edges. We further demonstrated that our network decoupling methods can be used as building blocks for different types of multilayer communities in literature, such as pillar and semi-pillar communities. In these cases too, network decoupling produces results with higher accuracy compared to other baseline methods. The only case our method produces lower accuracy is when a network designated to have pillar communities does not have the complete pillar information. Given these results we can posit that network decoupling is an effcient and effective method for finding communities in homogeneous multilayer networks.In future, we will investigate how to include some percentage of bridge edges without increasing the computation time. We also plan to explore adaptive techniques that can select between the network decoupling and standard methods as suitable. Finally, we also aim to develop methods to include meaningful NON-BOOLEAN combinations for weighted networks.The original contributions presented in the study are included in the article/AS and FI conducted the experiments and wrote the paper. SC, SB, and KM helped in designing the experiments. SC and SB helped in writing and editing. All authors contributed to the article and approved the submitted version.


Our fabricated device affords an interesting label-free, rapid, and reproducible bacterial sample analysis based on the density of the AuNRs when functionalizing flake-like 3D graphene, which can help facilitate label-free bacteria sensing platforms.Surface-enhanced Raman spectroscopy (SERS) is an effective technique for biosensing, enabling label-free detection of biomolecules with enhanced sensitivity. There is a tremendous probability of signal failure in Raman frequencies because of the scattering of the Raman radiation in liquids, effective SERS improvement is required to reduce this issue when considering liquid specimens. We examined a liquid bacterial sample, investigating the electrostatic interactions of the bacterial samples with gold nanorods (AuNRs) and graphene. We established a voltage-gated 3D graphene functionalized with an AuNR-based device on the silicon substrate for SERS measurements when the applied voltage ranges from 0 to 3 V. Moreover, AuNRs density-susceptible bacterial sample analysis with varied concentrations of bacterial samples has also been described. Using bacterial SERS analysis, the bacterial components amide II (1555–1565 cm Graphene is a two-dimensional atomically thick substance that has been enormously researched for extensive applications because of its remarkable electrical and thermal properties ,2,3,4,5.There are several papers that have shown the improvement in SERS enhancement, introducing several techniques such as the combination of metal–organic frameworks (MOFs) with plasmonic metal nanoparticles , silver S. typhi and Gram-positive Listeria monocytogenes as model bacteria for studying the interaction of bacteria between the AuNRs and 3D graphene in a 10 × 10 mm fabricated device when the applied voltage ranges from 0 to 3 V. In this study, our Raman spectra results showed that the spectral values are consistent with their corresponding bacteria and are reproducible. The interaction between the graphene and bacterial surface is known and the chemical potential of the bacterial membrane can change the vibrational properties of graphene  and Listeria monocytogenes [ATCC 15313] were cultured in Luria–Bertani broth  medium until the optical density came to 0.15, 0.10, and 0.05 for three different bacterial suspensions. Afterward, the LB medium was removed by subjecting it to centrifugation at 8000 rpm for 10 min, removing the supernatant, and dispersed in DI water for 3 different concentrations of bacteria. The concentration of the bacteria was calculated by the previously introduced method [8, 8.0 × 107, and 4.0 × 107 cells/mL.d method . The thr2/Si substrate. The electrode was prepared by keeping the device on the hot plate and heating it to 160 °C and some indium was placed on the device edge which covered the area of graphene and we waited 1 min to melt the indium. Thereby, the copper tape was attached to the melted indium and kept at room temperature to harden the attachment between the copper tape and the device. Then, the 4 different concentrations of hydrophobic AuNRs such as 10, 20, 40, and 80 µg/mL with a volume of 20 µL were deposited on the surface (10 × 10 mm) of the graphene by solvent evaporation.Our device consists of directly grown MOCVD 3D graphene on a SiORaman spectroscopy was performed with a commercial Raman system , equipped with a YAG laser, wavelength of 532 nm, a laser spot size of 1 μm and a power of 70 μW was used during the measurement. For collecting the Raman spectra, a distance of 8 mm, and a 10× objective lens from Olympus were used and the acquisition time was 5–10 s. For every measurement, 5 µL of the bacterial suspension was placed into the well of the device. We have performed all the measurements three times to maintain the accuracy associated with the integrated area enhancement.−1, the G peak at ~1585 cm−1, and the 2D peak at ~2700 cm−1. The copper precursor acts as a catalyst to enhance the formation of graphene, just like regular Cu catalytic substrates. Therefore, the precursor remains in gas form and does not deposit on the substrate. We also did not observe any Cu-related peak on Raman spectra above baseline which normally forms in the 300~700 regime.The characterization of flake-like 3D graphene has been performed by using a scanning electron microscope (SEM), and the Raman spectra of graphene see . The sca2. the size of the flake-like protruded part of graphene film varies, but typically does not exceed 100 nm.Since the described synthesis method is a CVD-based method, the size of graphene is continuous throughout the entire substrate, which is ~1 cm−1 represent S-H stretching that confirmed the thiol functional group in AuNRs, and the visual observations of the AuNRs from aqueous to organic solvent also confirm the hydrophobication of the AuNRs and redispersion in an organic solvent  with a quartz cell in the wavelength range 450–850 nm. However, the hydrophobication of the AuNRs was characterized by FT-IR manufactured by Thermo Scientific, Waltham, MA, USA. The FTIR spectra at 2550–2600 cmvent see . The meavent see . A previAtomic force microscopy (AFM) is one of the most acceptable techniques for measuring the height profile of the adsorbed molecules on a substrate. The height profiles of the adsorbed and unabsorbed AuNRs on the graphene surface have been compared in 7 cells/mL. Moreover, we are the first to report the functionalization of 3D graphene surfaces with the AuNRs and it enables both CM and EM ways together to study concentration-based bacteria sensing in a label-free biosensing platform. However, electromagnetic enhancement for graphene has been widely studied [Herein, we introduced a 3D graphene-AuNR-based voltage-gated device for liquid bacterial SERS analysis for large-area SERS enhancement. We study how the density of AuNRs on 3D graphene affects bacterial SERS analysis. We also study how bacterial surface charge affects the analysis of bacterial SERS using a 3D graphene system. We analyzed the best amount of AuNRs on 3D graphene to improve SERS spectra in both CM and EM enhancements. As a result, we successfully detected the liquid bacterial SERS signature even at a low concentration of 4.0 × 10 studied ,45. EM o studied ,47. The Our synthesized Au rods are sensitive to polarization (direction of the electric field oscillation of the incident light). We investigate the density controllability of the decorated AuNRs on the graphene for bacteria sensors using the SERS platform. We control the density of the AuNRs on the top of the graphene by changing the concentration of the AuNRs during the deposition of AuNRs on the graphene by solvent evaporation, AFM image is shown in −1) [Listeria monocytogenes, shown in S. typhi bacteria. The integrated area enhancement of the D band is shown in The amide group is a constituent of bacteria. We have shown the integrated area for the D band of 3D graphene with increasing density of AuNRs on its surface and the amide III vibrations (1250~1350 cm−1)  superimp−1) also showed a similar enhancement because of the superimposing of amide II (1555–1565 cm−1) [Listeria monocytogenes and S. typhi, respectively, which is drastically increased with the high density of AuNRs.However, the G band of graphene (~1585 cm65 cm−1)  bands wiGram-negative bacteria have an isoelectric point of approximately ~5 and Gram-positive bacteria of approximately ~3 . So, it Listeria monocytogenes and S. typhi bacteria and their interaction with the 3D graphene-AuNRs at different concentrations may affect the intensity ratio of D and G bands. A Gram-negative bacterial cell has a thin peptidoglycan layer and a surface membrane made up of proteins, phospholipids, and lipopolysaccharides, whereas a Gram-positive cell has a thick peptidoglycan layer made up of teichoic and lipoteichoic acids. Gram-negative cells have an additional layer of the outer membrane while having a much thinner coating of peptidoglycan. In contrast to Gram-positive bacteria (Listeria monocytogenes), Gram-negative bacteria (S. typhi) maintain a stronger cell wall that offers higher resistance to the sharp edges of graphene. At higher concentrations of bacteria, the D band intensity is typically higher than the G band intensity, showing a more disordered graphene structure. This could be due to several factors, such as increased physical contact between the bacteria and the graphene surface [2 hybridized carbon atoms, while the G band corresponds to the stretching modes of the same. When bacteria are present on the graphene-based material, the interactions between the bacteria and the graphene surface can affect the vibrational modes of the graphene sheet. The intensity ratio of the D and G bands in Raman spectroscopy can provide information about disorders in the graphene structure [To closely figure out the concentration effects of the bacteria on the SERS platform, we performed concentration-based SERS analysis for both bacteria. The result shows the close binding of the Gram-negative to the AuNRs and graphene by charge transfer and the increasing concentration of the bacteria provides higher Raman intensity whereas the Gram-positive bacteria showed less affinity compared to the Gram-negative bacteria . The dif surface  The D antructure . The pretructure . However7 cells/mL. This demonstration showed that for a 80 µg/mL conc. of AuNR sample and 20 µL, the deposition volume on 10 × 10 mm of graphene surface provides the highest SERS integrated area enhancement. Additionally, the bacterial concentration-based study will provide significant information for the further development of label-free bacterial biosensing devices for quantitative studies. In our current system, we have not used polarization-controlled light sources for Raman measurement. We could perform further studies using a polarization-controlled light system to develop a novel Raman biosensor system.In summary, we have shown a voltage-gated liquid Raman setup and analyzed the effect of AuNRs density on flake-like 3D graphene for label-free bacteria sensing at low concentrations of bacteria. The deposition of the AuNRs on the graphene enables the large-area SERS enhancement while handling the liquid samples. Our results showed the relationship between the AuNRs density on the graphene and the rate of integrated area enhancement of SERS and the SERS enhancement factor when comparing with and without bacterial suspension with a concentration as low as 4.0 × 10Our work could clear the way for the application of Raman spectroscopy for the rapid analysis of the bacterial samples for clinical samples as we showed the liquid bacterial sample analysis as a label-free biosensor—for example, the rapid and quantitative bacterial sample analysis directly after collecting the sample from the patients. Additionally, the liquid-SERS enables a culture-free and less time-consuming method to analyze the liquid samples and provides a foundation for label-free and quantitative bacterial sample analysis.


In 2018 we published the James Lind Alliance (JLA) top 10 priorities for clinical research in cystic fibrosis (CF), chosen jointly by the patient and clinical communities. These priorities have led to new research funding. To establish whether priorities have changed with novel modulator therapies, we undertook an online international update through a series of surveys and a workshop. Patients and clinicians (n=1417) chose the refreshed top 10 from 971 new research questions (suggested by patients and clinicians) and 15 questions from 2018. We are working with the international community to promote research based on these refreshed top 10 priorities. In 2018 we published the top ten research priorities for cystic fibrosis (CF), jointly developed by the CF patient and clinical communities.The original top ten priorities were produced by working with the NIHR-supported James Lind Alliance (JLA) who facilitate priority setting partnerships (PSPs) using methodology which brings patients, carers and clinicians together to prioritise research questions. We were the first PSP to undertake a refresh of disease-specific research priorities and have worked with the support of the JLA Lab – an exploratory space that supports innovation.Our PSP refresh took place October 2021 – November 2022. We published our protocol before commencing.From January to February 2022, we conducted the first of two online surveys (Survey Monkey). The elicitation survey requested respondent demographics and asked participants to select their top three priorities from the previous top twenty questions. Respondents were also asked to submit up to two new priorities. Surveys were advertised through professional and charity groups and our bespoke Twitter account (@questionCF). Both surveys were available in multiple languages. In a change to our original PSP, non-industry researchers were also invited to participate in the refresh.Two researchers (NR and SS) independently reviewed all submissions with adjudication by the steering and management groups. Responses which did not include a question and out of scope questions were removed. Where several questions addressed the same issue, they were consolidated into a single “umbrella question”. Any question already answered in the scientific literature was removed.The standardised umbrella questions were then taken forward to the prioritisation survey (September – October 2022). This allowed respondents to rank their top ten questions. Cumulative scores were calculated for each question and the questions ranked in priority order for the following four groups:pwCFThe subgroup of pwCF who currently do not have access to CFTR modulatorsFriends and family of pwCFHealthcare professionals and researchersQuestions in the top ten priorities for each of the three main groups, plus the top five for the sub-group of pwCF not on CFTR modulators , were th10.1136/thorax-2023-220100.supp1Supplementary dataWe had 1608 responses from 1370 respondents to the elicitation survey (59 responses were ‘empty’ and 179 respondents completed the survey more than once). An additional 971 questions were submitted. This is the first refresh exercise to update the JLA top 10 priorities for a specific medical condition. Our methodology ensured equal participation from people with CF, their family and friends and the clinical/research communities. We have produced a refreshed top 10 list of research questions, which should guide researchers and funders. Four priorities were identified in the original PSP and remain priorities. Six priorities were newly identified by the PSP refresh.A strength of our study is its international reach. We had a large number of respondents, from countries across the world. While CF is predominantly a disease of Northern European descent, recent prevalence studies show an increase in countries where it was not previously reported.With the arrival of transformational therapies, available to most  pwCF, it is vital that the research priorities of funders and researchers remain aligned with those of the patient and clinical communities. Publication of the previous JLA top 10 priorities for CF has led to international funding  for many clinical studies designed to address these priorities.The previous PSP led directly to the CF-STORM trial  which was developed in response to Question 1 (“What are the effective ways of simplifying the treatment burden of people with Cystic Fibrosis?”) and to the GIFT-CF research programme


The porous interconnected framework and high crystallinity of 3DG could contribute to not only its facilely mixing with epoxy resin, but also its effective incorporation into the conductive network of zinc micro-flakes, thus enhancing the corrosion resistance of its ZRE coating at a lower content. The innovative technology to improve the anti-corrosion performance of the ZRE coatings via using the 3D graphene fillers should be capable to be extended to other 2D fillers, such as MXenes. To improve the corrosion inhibition of zinc-rich epoxy (ZRE) composite coatings and shed light on the influence of the spatial structure of graphene fillers on the coatings’ performance, three-dimensional graphene (3DG) and a conventional graphene sheet (G) were used to modify the ZRE composite paint, respectively. The effect of introducing the 2D G fillers on the anti-corrosion behavior of ZRE was studied comprehensively, and its optimal content was determined to be 0.5 wt%. Interestingly, it was found that, comparing with 2D graphene sheets, the corrosion resistance of the ZRE coating could be enhanced more significantly with incorporating even less 3DG. With introducing only 0.1 wt% 3DG, the corrosion current intensity of the resulting 3DG/ZRE coating was reduced to be about 1/10 that of the G/ZRE coating with the same graphene content and 27% of that of the optimized G/ZRE. The corrosion products of the coating were analyzed with the XRD technique. The results indicated that, in contrast to neat ZRE coating, Zn Recently, two-dimensional 2D) multi-functional materials, including graphene, graphitic carbon nitride, and MXene, have aroused extensive research interest all over the world, and a large amount of work on their facile fabrication and applications in many fields ,2,3,4. CD multi-fDue to their high aspect ratio and 2D structure, graphene sheets are ready to aggregate in the polymer matrix, resulting in a great challenge to prepare their composite with a high performance. To alleviate this, graphene derivatives, including graphene oxide or fluorinated reduced graphene oxide, have been developed and used to prepare the composites ,21,22,23Graphene foam has been developed in recent years. The most common method to prepare the foam is the so-called chemical vapor deposition method. With this method, the porous structure of graphene is controlled by the metal catalytic foam templates, and the thickness of the graphene foam strut-wall can be controlled to be within nanometers. Due to their unique porous 3D structures, their polymer composites with various advanced properties ,25,26, iIn this work, the influence of the spatial structure of high-crystalline graphene fillers on the corrosion resistance of ZRE coatings was studied. Besides conventional 2D graphene sheets, 3DG with a porous structure and interconnected graphene framework has been applied to modify the ZRE paint. Both the morphology and physical chemical properties of the as-prepared 3DG will be characterized. To avoid the influence of the crystalline structure of graphene on the anti-corrosive behavior of the modified ZRE coating, 3DG with a similar crystalline structure to graphene sheets has been used in this study. The anti-corrosion behaviors of the ZRE modified with different graphenes in the artificial simulated seawater (3.5 wt% NaCl solution) will be studied by the potentiodynamic polarization test and electrochemical impedance spectroscopy, as well as the long-term immersion test.Commercial graphene sheets  were purchased from Suzhou Tanfeng Technology Co. Ltd. . Epoxy (E-44) was provided by Xiya Reagent Co. . Xylene, n-butanol, and polyamide 651 were all chemically pure and purchased from McLean Group.  Commercial zinc flakes with a lateral size of 5–15 µm were ordered from Xiamen Empire New Material Technology Co. Ltd.  and a Q235 steel plates with a size of 30 mm × 40 mm were provided by Fuquan Metal Co. Ltd. .The whole process was illustrated as The crystalline structures of the graphene samples were characterized with an X-ray diffraction analyzer . The carbon structure of 3DG was analyzed with a Raman spectrometer . The morphology of the carbon sample was observed with a scanning electron microscope . An optical microscope (DM3000) was also utilized to observe the morphology of graphene fillers in epoxy resin.−1 and its potential range was set to be ±250 mV around the OCP. Three potentiodynamic polarization tests were carried out for both neat ZRE and 3DG/ZRE samples and the typical ones are reported in the work. The electrochemical impedance spectroscopy (EIS) tests were performed in a frequency range of 10 kHz~0.1 Hz at room temperature. The simulated seawater (3.5 wt% NaCl solution) was used as the corrosive electrolyte. The corrosion measurements of the ZRE coatings were measured on a CHI 760e electrochemical analyzer. A three-electrode half-cell system was constructed with a saturated calomel electrode (SCE) as the reference electrode, platinum plate as the auxiliary electrode, and ZRE coated Q235 plates as the working electrode. First of all, an open circuit potential test (OCP) of the sample was performed to ensure it reached a relative steady state. The potentiodynamic polarization test was carried out at a scan rate of 10 mV sDifferent from the common 2D morphology of normal graphenes a, 3DG isUnder the magnetic stirring in epoxy resin, the graphene framework monolith infiltrated with epoxy resin will be in situ broken into small fragment particles, whose morphology will have 3D irregular characteristics with a size larger than that of the conventional 2D graphene sheets . As show−1 and the 2D band at 2700 cm−1, together with a very weak peak for the D band around 1357 cm−1, could be observed in the Raman spectrum of 3DG  of 3DG is 0.66, which is much less than 1, implying its multi-layered structure [Similar to the research on the graphene deposited on catalytic metal substrates in the literature ,28, two m of 3DG . As the tructure .−7 A cm−2), which means a ~10-fold improvement in the corrosion resistance, comparing with that of neat ZRE (6.1 × 10−6 A cm−2). However, when further increasing the G content to 0.7 wt.%, the Icorr of its ZRE coating increases  of the ZRE coating could be used as a factor to evaluate their protection performance . Figure 0.01Hz of the ZRE coatings on the time is shown in 0.01Hz of all the coatings decreased quickly with the immersion time initially. Obviously, 0.5 wt% G/ZRE exhibited a larger |Z|0.01Hz than neat ZRE during the whole immersion test, confirming the positive effect of incorporating G on promoting the corrosion inhibition of ZRE coating. Additionally, the curve of 0.1 wt% 3DG/ZRE is always higher than that of 0.5 wt% G/ZRE all through the immersion process, demonstrating the superior effect of 3DG over the 2D graphene on enhancing the corrosion resistance of ZRE coating. The digital image of the exposed circle area of neat ZRE after the immersion test indicates that its major part is brown, together with some white areas  is nearly 1/10 that of 0.5 wt% G/ZRE (4.02 × 10−6 A cm−2) (The dependence of |Z| A cm−2) . Additio5 Ω·cm−2) was ~46 times that of 0.5 wt% G/ZRE (1.29 × 104 Ω·cm−2), which agreed well with the aforementioned Tafel test results (4 Ω·cm−2) was ~10 times that of 0.5 wt% G/ZRE (3.53 × 103 Ω·cm−2) (The Nyquist plots of the ZRE coatings after being soaked in simulated seawater are presented in  results . This im Ω·cm−2) , indicat2 products (Equations (1)–(5)), the insoluble complexes, including Willemite (Equations (6)) and hydrozincite (Equations (7)–(9)), could be also formed under certain conditions . After the continuous 300 h immersion test, the Q235 steel plates coated with either neat ZRE or 3DG/ZRE were taken out from the simulated seawater and their XRD patterns were taken to characterize the corrosion products. Consistent with the zinc corrosion products reported previously [5(OH)8Cl2H2O, and Zn5(CO3)2(OH)6, respectively. Interestingly, different from the presence of both complicated complex products on the soaked neat ZRE coating, no peak contributed from hydrozincite Zn5(CO3)2(OH)6 could be found on the pattern of the 3DG/ZRE coating after the 300 h immersion test. This could be due to the excellent barrier property of 3DG particles to carbon dioxide, demonstrating its great contribution to the surface protection of the ZRE coating.As suggested in the literature ,35, the eviously ,37, many5(OH)8Cl2H2O, as mentioned above. In contrast, a more significant morphology change occurred for the neat ZRE-coated sample after the immersion test, as indicated in As shown in (1)The corrosion resistance of the ZRE coating could be improved by incorporating common 2D graphene, and the optimal G content is 0.5 wt%.(2)The corrosion resistance of the ZRE coating could be further enhanced significantly by incorporating only 0.1 wt% 3DG.(3)Long-term immersion tests confirmed the superior effect of 3DG on improving the surface protection performance of ZRE as well.In this work, conventional 2D graphene sheets and 3DG fillers were used to modify the ZRE composite to improve the corrosion resistance of the ZRE coatings. These main conclusions are drawn:This work revealed, preliminarily, the significant effect of 3D graphene fillers on the surface protection performance of ZRE coating. However, to understand the spatial structure of graphene fillers on the properties of their ZRE coatings more comprehensively, further work needs to be done, such as the mathematical simulation of the contribution of 3DG to the cathodic protection process of ZRE coating.


Thus, these aberrant splicing events make promising novel therapeutic targets to restore functional gene expression. Moreover, presence of these cryptic exons is highly specific to patients and areas of the brain affected by TDP-43 proteinopathy, offering the potential to develop biomarkers for early detection and stratification of patients. In summary, the discovery of cryptic exons gives hope for novel diagnostics and therapeutics on the horizon for TDP-43 proteinopathies.TDP-43 is an RNA-binding protein with a crucial nuclear role in splicing, and mislocalises from the nucleus to the cytoplasm in a range of neurodegenerative disorders. TDP-43 proteinopathy spans a spectrum of incurable, heterogeneous, and increasingly prevalent neurodegenerative diseases, including the amyotrophic lateral sclerosis and frontotemporal dementia disease spectrum and a significant fraction of Alzheimer’s disease. There are currently no directed disease-modifying therapies for TDP-43 proteinopathies, and no way to distinguish who is affected before death. It is now clear that TDP-43 proteinopathy leads to a number of molecular changes, including the de-repression and inclusion of cryptic exons. Importantly, some of these cryptic exons lead to the loss of crucial neuronal proteins and have been shown to be key pathogenic players in disease pathogenesis (e.g. TDP-43 proteinopathy encompasses a wide spectrum of progressive neurodegenerative diseases and phenotypes. It is a key feature in ~ 97% of people with amyotrophic lateral sclerosis (ALS) and ~ 45% of people with frontotemporal dementia (FTD), a seminal discovery made in 2006 , 2. SubsTARDBP, the gene which encodes TDP-43, are rare, occurring in < 1% of ALS cases, but underscore TDP-43’s central role in disease pathogenesis [Common to TDP-43 proteinopathies is a lack of directed disease-modifying therapies, and an inability to confirm and stratify individuals that have TDP-43 pathology ante-mortem. The disease that is most frequently characterised by TDP-43 mislocalisation is ALS, which is a rapidly progressive paralysing illness with eventual death on average 3 years from symptom onset . Up to 1ogenesis –14. AlteIn this review, we will focus on a key ‘on-off’ consequence of nuclear TDP-43 loss of function, which has emerged over recent years – the occurrence of splicing defects leading to the erroneous inclusion of intronic sequences into mature mRNA, forming so-called ‘cryptic exons’ . With a CFTR gene, first realising TDP-43’s role as an RNA-binding protein and regulator of alternative splicing [POLDIP3, SORT1, and PFKP have all been used as reliable readouts for nuclear TDP-43 function in models with TDP-43 knockout, overexpression, and for studying TDP-43 ALS-causing mutations [TDP-43 was identified in 1995 as a suppressor of HIV gene expression. It was later discovered that TDP-43 expression promotes skipping of exon 9 in the splicing . Since tutations –27.TDP-43’s consensus binding motif comprises “UG”-rich dinucleotide repeats. High-throughput sequencing, combined with cross-linking immunoprecipitation experiments to discover direct TDP-43 mRNA targets, revealed that the majority of TDP-43’s binding sites in pre-RNAs were in introns , 27. A nWhat are the possible consequences that result from the insertion of novel non-conserved sequences in mRNA Fig. ? Most crSTMN2 gene [. This gene encodes for stathmin-2, a microtubule-associated protein needed for axonal growth and repair in neurons. Occurring after exon 1 and containing a stop codon and polyadenylation site, the cryptic exon leads to premature transcript termination and predicted formation of a truncated non-functional protein. Using in vitro neuronal models of TDP-43 depletion via knockdown, induction of TDP-43 mislocalisation, and pathological loss of function TDP-43 mutations known to cause ALS, the research groups demonstrated a resultant dramatic reduction in levels of mature STMN2 mRNA and functional protein. Crucially, the STMN2 cryptic exon was confirmed to be detectable also in ALS-FTD brains and spinal cords where TDP-43 pathology is present and specifically in patient post-mortem neurons with TDP-43 pathology isolated by laser capture or nuclear sorting [In 2019, a breakthrough discovery from two independent groups found that TDP-43 loss of function leads to the inclusion of a cryptic exon within the MN2 gene , 30. Thi sorting , 37. WitUNC13A is one of the top genetic risk factors for ALS, first reported in a genome-wide association study in 2009 [Munc13–1 in mice) have synaptic impairments and die soon after birth [UNC13A result in fatal microcephaly, cortical hyperexcitability, and myasthenia [UNC13A have been shown to increase risk of ALS and also shorten survival in patients. However, the underlying mechanism by which these UNC13A variants increase ALS risk was not known until earlier this year when, along with the Gitler and Petrucelli groups, we independently found that TDP-43 depletion resulted in inclusion of a cryptic exon between exons 20 and 21 of UNC13A, leading to reduced expression. Similarly to the STMN2 cryptic exon, this event can also be detected in post-mortem brain and spinal cord tissue from patients with ALS-FTD, exclusively where TDP-43 pathology is present, but not in healthy controls. in 2009 . UNC13A er birth . In humaasthenia . Single UNC13A SNPs, rs12608932 (A > C) and rs12973192 (C > G), were found to be located within the intron containing the cryptic exon, with the former SNP being located within the cryptic exon region itself. Especially given the large size of the UNC13A gene (~ 87 kb), the proximity of the SNPs to the cryptic exon led us to hypothesise a direct link between the SNPs and UNC13A cryptic splicing. Given that the cryptic exon is not present in RNA-sequencing data from healthy controls, even when homozygous for the risk SNPs (approximately 10% of Caucasians are homozygous for both risk SNPs), they seem not to be sufficient to cause cryptic exon inclusion on their own. Thus, it was hypothesised that rather than increasing ALS or FTD risk directly, the SNPs act by potentiating the expression of a cryptic exon which is dependent on TDP-43 depletion.Intriguingly, two of the associated UNC13A cryptic exon-containing transcripts in a dose-responsive manner compared to heterozygotes and non-carriers. This discovery provides a biological explanation for how presence of the UNC13A risk SNPs in ALS-FTD patients with TDP-43 pathology modifies disease outcomes, negatively affecting survival from symptom onset [Indeed, the risk SNPs enhance cryptic splicing and alter direct TDP-43 binding, thereby reducing its ability to physiologically repress cryptic exon inclusion. In keeping with this, patients homozygous for either SNP had more om onset , 41–47. ECD [Biomarkers for early diagnosis, disease stratification of subtypes and clinical stages, prognostication, and monitoring treatment response are vitally important, both for clinical trials and patient care. Fluid biomarkers of general neurodegeneration exist, most notably serum neurofilament light chain, cerebrospinal fluid (CSF) phosphorylated neurofilament heavy chain, and urinary p75ECD –50. HoweSTMN2 cryptic exon in post-mortem frontal cortex samples, in which its presence was able to discriminate between patients with FTD-TDP, progressive supranuclear palsy, and healthy control participants [Unlike canonical TDP-43 regulated splicing, the ‘on-off’ expression of cryptic exons only under TDP-43 nuclear loss of function makes them potential potent biomarker candidates for TDP-43 pathology. This proof of concept was first shown with the icipants .A key future direction will be to exploit this characteristic to develop methods that detect TDP-43 pathology ante-mortem in patient biofluids, such as in blood, CSF, urine, or tissue. Assays could involve either direct RNA detection of the cryptic exon itself, or detection of novel cryptic peptides for transcripts that escape NMD. An ideal biomarker would have a reproducibly high and linear correlation with disease activity, high sensitivity and specificity, stability throughout the day, and easy access to obtain a sample .UNC13A, undergo NMD and are therefore not stable. Moreover, if transcripts are at low levels, highly sensitive tools would be required. Detection of a panel of relevant cryptic exons deemed to be pathogenic players could theoretically increase sensitivity.With regards to biomarker detection of RNA, methods have been developed that can sensitively detect circulating RNA in the blood of individuals with Alzheimer’s disease that reflect disease-specific neural transcriptome changes . HoweverSTMN2, even though the cryptic-containing transcript is highly expressed and escapes NMD, attempts to detect the putative 16 amino acid cryptic peptide have not yet been successful. However, antibody generation to specifically detect pathological proteins is evolving, including in the field of ALS-FTD, with antibodies now available to detect dipeptide repeats that occur in the C9orf72 subtype of ALS-FTD. These have not only furthered our understanding of disease mechanisms, but are also being utilised to assess therapies [For cryptic exons that produce cryptic peptides, specific antibodies could be designed to detect these via immunohistochemistry, or ELISA and SIMOA-based assays. This has its own challenges, whether it be due to NMD of cryptic-containing transcripts, low expression, or instability of the peptides. For herapies –56.HDGFL2, detects the cryptic peptide in C9orf72-associated ALS. Strikingly, this includes pre-symptomatic mutation carriers [Excitingly, two new pre-print publications this year have independently reported the detection of cryptic peptides in the CSF of patients with ALS , 58. Irwcarriers . In SeddNeurofascin in these cells, highlighting how, if certain TDP-43 cryptic exons are expressed only by given cells, they could allow tracing of TDP-43 proteinopathy. Furthermore, recent work showing that pTDP-43 and loss of nuclear TDP-43 can be detected years before ALS disease presentation in central nervous system and non-central nervous system tissue suggests that detection of TDP-43 cryptic exons could possibly pre-date disease onset [Given the cell-type specificity of TDP-43 controlled cryptic exons, it is also possible that biomarkers towards cryptic exons could be designed to assess the flow of TDP-43 proteinopathy across the nervous tissue , 59, 60.se onset , 65.Another interesting avenue is the use of model systems to determine the timing of the emergence of cryptic exon inclusion events. For instance, studies assessing the presence of cryptic exons at different levels of TDP-43 knockdown in vitro, or in patients with or post-mortem tissue from varying clinical stages of ALS-FTD, could allow curation of a database reflecting which cryptic exons appear early and late in disease. Further analysis of this could provide a greater mechanistic understanding of cryptic exon biology and what factors make certain genes more sensitive and susceptible to the inclusion of cryptic exons with TDP-43 loss. Such a stratification may also have implications for biomarker studies and early diagnosis and stratification of people with ALS-FTD.Further work is necessary to utilise the specificity of cryptic exons to develop appropriate biomarkers, which could be transformative to the field of ALS-FTD and other TDP-43 proteinopathies. Particularly with new therapies on the horizon for neurodegenerative diseases, early diagnosis of individuals who are or will become affected and a readout for treatment response will be critical in halting the disease process at an early enough stage to pre-empt the point of no return in the ALS disease cascade .The discovery that certain cryptic exons, and potentially more that remain to be explored, underpin the disease process in ALS – either by impairing neuronal health, increasing ALS risk, or worsening disease progression – makes them exciting novel therapeutic targets. If early diagnosis can be achieved, the hope would be to restore expression of critical proteins to normal functional levels, or use splicing therapies to modulate and prevent aberrant splicing from occurring altogether in TDP-43 proteinopathies.STMN2 cryptic exon leads to a reduction in STMN2 expression. Thus, one strategy would be to restore normal STMN2 levels using a viral vector containing the correct DNA sequence, such as via adeno-associated viral (AAV) or lentiviral delivery. This proof of concept was shown when transduction of TDP-43 depleted iPSC-derived motor neurons with lentivirus carrying STMN2 restored STMN2 levels and also, importantly, restored axonal regeneration after axotomy [Stmn2 (Stmn2−/−) that the introduction of the human STMN2 gene was able to rescue motor deficits [SMN overexpression [UNC13A would be too large to be introduced via this methodology, as opposed to STMN2, which would theoretically be more amenable.The  axotomy . It was deficits . Howeverpression . Moreovepression . AnotherSOD1 and C9orf72 have been tested in ALS clinical trials . The former showed very encouraging results, but failed to reach significance in achieving primary clinical endpoints in a phase 3 trial, and the latter phase 1 trial showed no difference from placebo for clinical endpoints and in fact trended towards greater decline at the higher dose. These results highlight some of the caveats of ASO therapies [Other important gene-therapy strategies involve the prevention of erroneous RNA splicing. Compared to the above described gene delivery methods, these approaches aim to correct endogenous splicing and therefore avoid problems deriving from overexpression and toxicity. One method is via antisense oligonucleotide therapies (ASOs), which are short synthetic DNA sequences that are designed to selectively bind to pre-mRNA in cells. ASOs have come to the forefront as a new tool for numerous neurodegenerative diseases, including toxic gain of function gene-specific ALS subtypes, where they have been used to degrade mutant transcripts. ASOs designed to reduce protein produced from mutant herapies , 71. ASOherapies . One draRuminococcus flavefaciens), and using modified uridine-rich small nuclear RNA (snRNA) gene therapy, such as via U7 snRNA delivery, which has shown promise in DMD, and has entered its first clinical trial [Other effective splice switching strategies include systems that target pre-mRNA, but are stably expressed in the long-term, thereby preventing the need for repeated dosages, whilst also aiming to circumvent the above concerns regarding overexpression. These include CRISPR-Cas ribonuclease programming, such as via RfxCas13d (also named CasRx, from al trial –78. In aFinally, small molecule delivery has been developed as a further tool to alter splicing. A clear benefit of this therapeutic platform is the ability to deliver the treatment to patients orally. The first small molecule splicing modifier to be approved was Risdiplam for oral delivery in SMA. It was shown to increase SMN protein in the central nervous system and peripheral tissues in mice, and to restore functional SMN protein in patients with SMA –82.STMN2 and UNC13A that have been reported in humans are not present in mice. In fact, and interestingly, different UNC13A cryptic exons are present in mice [Homing in on correcting cryptic exon-related mis-splicing, a phase I clinical trial is planned to assess an ASO designed to restore STMN2 levels . Commonl in mice . Therefo in mice , 85. Ano in mice , 35. WhiWhilst blocking TDP-43 cryptic exons to restore gene expression appears to have a relatively clear mechanistic benefit, it remains to be seen how many and which cryptic exons need to be targeted for an effective therapy. Future experiments may seek to determine which cryptic exon inclusion events are pathologically relevant, impacting on a biological pathway that contributes to disease, as this may impact the development of therapies and potential ways to restore the expression of multiple mRNA targets, as opposed to one at a time.The past decade has seen leaps forward for people with gene-specific ALS-FTD, now with gene-based therapies coming into play. However, these would not benefit people with sporadic disease, making up the majority of patients with ALS-FTD, or those that have different pathogenic genes that are not amenable to treatment with available gene-based therapies. Given that almost all patients with ALS have TDP-43 pathology, the recent breakthroughs revealing that TDP-43 dependent mis-splicing of mRNA plays a major role in disease pathogenesis provides a fresh injection of hope into the field, not only for the ability to better understand molecular mechanisms, but also for the transformative potential with regard to biomarker development and therapeutics, desperately needed for patients living with this fatal disease. Important focuses going forward will be to establish which other cryptic exons, if any, are pathogenic players, and for the knowledge gained about cryptic exons to be transferred to and explored in other TDP-43 proteinopathies.


In this study, the integrated three-in-one  microsensor was made through the technology of the Micro-electro-mechanical Systems (MEMS) to measure three important physical quantities of the internal environment of the cold air pipe of the Heating, Ventilation and Air Conditioning (HVAC) in the factory, plan the installation positions of the integrated three-in-one microsensor and commercially available wind speed sensor required by the internal environment of the cold air pipe, and conduct the actual 310-h long term test and comparison. In the experiment, it was also observed that the self-made micro wind speed sensor had higher stability compared to the commercially available wind speed sensor (FS7.0.1L.195). The self-made micro wind speed sensor has a variation range of ±200 mm/s, while the commercially available wind speed sensor a variation range of ±1000 mm/s. The commercially available wind speed sensor (FS7.0.1L.195) can only measure the wind speed; however, the self-made integrated three-in-one microsensor can conduct real-time measurements of temperature and humidity according to the environment at that time, and use different calibration curves to know the wind speed. As a result, it is more accurate and less costly than commercially available wind speed sensors. The material cost of self-made integrated three-in-one microsensor includes chemicals, equipment usage fees, and wires. In the future, factories may install a large number of self-made integrated three-in-one microsensors in place of commercially available wind speed sensors. Through real-time wireless measurements, the self-made integrated three-in-one microsensors can achieve the control optimization of the HVAC cold air pipe’s internal environment to improve the quality of manufactured materials. Heating, Ventilation, and Air Conditioning (HVAC) is a system that uses mechanical equipment for ventilation. By introducing air from the outside and expelling air from the area, it could maintain the quality of indoor air and reduce moisture, odors, and pollutants in the air. Due to the need for introducing a significant amount of outdoor air, the internal environment of the HVAC cold air is affected, and wind speed, temperature, and humidity may have an internal effect. In addition, the geographical location and environment of the factory may also make a difference according to changes in temperature or short-term extreme climate (such as typhoons and heavy rain). Therefore, in order to improve the quality and reliability of manufactured materials of the factory, monitoring the internal environment of HVAC cold air ducts, such as wind speed, temperature, and humidity, and analyzing data using three essential physical quantities, are crucial research topics for finding optimal control parameters for the internal environment.The research aims to achieve real-time wireless monitoring of important information such as wind speed, temperature, and humidity within the HVAC cold air duct, and establish a complete database. It involves planning the various types of sensors required for the internal environment of the cold air duct, their installation location and quantities, evaluating and purchasing commercially available wireless sensors of different specifications, and developing a wireless flexible three-in-one  microsensor for software and hardware integration. The goal is to optimize the deployment of commercially available wireless sensors and self-made wireless flexible three-in-one microsensors, and collect important information to assist in field verification. This will achieve the optimization of the internal environment control of the HVAC cold air duct and improve the quality and reliability of process materials.3 to 25.99 gm3 as the temperature increased from 25 °C to 60 °C, with no significant change in water absorption. Beniwal et al. [Yi et al.  made a nl et al.  found thThe literature measures only a single physical quantity. We developed an integrated three-in-one microsensor that can measure the three important physical quantities of wind speed, temperature, and humidity at the same time. There is a relationship between the three physical quantities. We developed an integrated three-in-one  microsensor using MEMS technology and use Arduino for real-time monitoring. This will enable the deployment of self-made wireless three-in-one microsensors and the collection of important information to achieve the optimization of the internal environment control of HVAC air conditioning cold air ducts.At present, there are many kinds of wind speed sensors developed using MEMS technology. Generally, wind speed sensors can be divided into two categories: hot wire type wind speed sensors and calorimeter type wind speed sensors. Among them, hot wire wind speed sensors have a small size, high sensitivity, and high accuracy. Moreover, the design of its process, drive, and signal output circuit is relatively easy . Therefoρ) and temperature (T). in Equation (2), ρ is the resistivity at temperature T, ρ0 is the resistivity at reference temperature (T0), and α is the Temperature Coefficient of Resistance (TCR).The micro temperature sensor in this study belongs to Resistance Temperature Detector (RTD). It uses gold (Au) as the electrode material and conforms to the linear equation of Equation (2) between resistivity  could be obtained by substituting Equation (2) into Equation (3) of resistance law, where α here is the sensitivity of temperature (1/°C), which represents the change rate of resistance with each change of temperature per °C. It could be verified through this equation that the metal may expand and contract with the temperature change. In addition, the Steinhart-Hart Equation (SHHE) was derived by Cui et al. [The physical meaning of i et al. . It furt® PI 9305, FUJIFILM Electronic Materials Taiwan Co., Ltd., Hsin-Chu, Taiwan), which is strong in toughness, acid resistance, alkali resistance, corrosion resistance, and moisture absorption, as the moisture sensing film on the humidity sensor. Normally, such materials have non-conductive properties. When moisture absorbed by the moisture sensing film increases, the dielectric constant of the moisture sensing film may also increase with the rise in ambient humidity [The micro humidity sensor used in this study is a resistance humidity sensor. It uses a new negative photoresistance of polyimide  as the protective layer and dielectric layer. The protective layer is added to temperature and wind speed sensors to protect the circuits. An insulating layer is added for humidity sensors because the LTC 9305 is used as a humidity sensing material. If an insulating layer is added as a protective layer for humidity sensors, the humidity sensor will not be able to measure humidity. In terms of the manufacturing process, it mainly utilized deposition, lithography, and lift-off to superimpose multilayer films. Moreover, all micromechanical structures were made using thin film deposition, as shown in In this study, MEMS technology was used to integrate three sensing structures, namely temperature, humidity, and wind speed. In order to make the integrated three-in-one microsensor bendable, long-term non-damage and long-term measurement in the mechanism inside the HVAC cold air pipe, this study selected anti-corrosion, high temperature resistant, stretchable, and bendable Polyimide (PI) film as the substrate of the integrated three-in-one microsensor, with the thickness of 50 µm. It uses LTC(a)First, clean the PI film with organic solvents such as acetone and methanol, and then rinse it with deionized water to remove residual methanol, surface dust, and residual oil, in order to increase the adhesion of the thin film metal.(b)Coat with AZP4620 and use photolithography to define the electrode pattern of micro temperature, humidity, and wind speed sensors.(c)Then use an electron beam evaporator to deposit chromium and gold as adhesive layers and sensing electrode layers.(d)After lift-off using acetone, coat with LTC 9320 as a protective layer, and then use photolithography again to define the sensing area and terminals of micro temperature and wind speed sensors, which are covered and protected by the protective layer.(e)Coat with LTC 9305, and then use photolithography to define the sensing area of the micro humidity sensor, which is covered by a dielectric layer.The following are the order of the processes:The integrated three-in-one microsensor was cut to the smallest size to facilitate the placement of the internal fixing mechanism of the cold air pipe. Next, the integrated three-in-one microsensor was affixed to the ceramic substrate with conductive copper foil adhesive. Afterwards, the contact ends were strengthened and fixed with conductive silver adhesive, and the signal wires of the integrated three-in-one microsensor were welded to the ceramic substrate to connect the integrated three-in-one microsensor to the microprocessor on the computer side. The actual photo of the integrated three-in-one microsensor after signal wire welding is shown in The assembly of this microsensor had to conform to the fixed mechanism inside the factory’s HVAC cool air pipe and was expected to be able to resist the greasy environment inside the cold air pipe. Therefore, for the mechanism inside the cold air pipe, 3D printing was used to design the assembly as it could simultaneously fix the integrated three-in-one microsensor onto the mechanism. Finally, the integrated three-in-one microsensor was inserted into the 3D printed assembly, and the locking mechanism is shown in f is the voltage reading at the current wind speed, V0 is the voltage reading at 0 m/s, and ((Vf − V0)/V0) is the dimensionless variation of voltage reading.The wind-speed calibration range of the self-made micro wind speed sensor was 0 m/s to 10 m/s. The micro wind speed sensor might be affected by temperature. Therefore, the ambient temperature ranged from 5 °C to 40 °C during the calibration. Data were captured at wind speeds ranging from 0 m/s to 10 m/s every 5 °C and were measured repeatedly three times. In addition, through the dimensionless variation of voltage readings, the calibration diagram was obtained, as shown in f is the voltage reading at the current temperature, V0 is the voltage reading at 5 °C, and ((Vf − V0)/V0) is the dimensionless variation of voltage reading.The temperature calibration range of the self-made micro temperature sensor was from 5 °C to 40 °C, and the interval was 5 °C. Two self-made micro temperature sensors were put into the program controllable constant temperature and humidity machine. In addition, data were collected by Arduino every 5 °C and measured repeatedly three times. The relationship curve of temperature with the original voltage value read by Arduino was obtained, and the temperature calibration curve was completed. Then, the temperature calibration curve was illustrated using the dimensionless method, as shown in f is the voltage reading at the current humidity, V0 is the voltage reading at 70% RH, and ((Vf − V0)/V0) is the dimensionless variation of voltage reading.The humidity calibration range of the self-made micro humidity sensor was from 70% RH to 95% RH, and the interval was 5% RH. The micro humidity sensor was put into the program controllable constant temperature and humidity machine. Since temperature might affect the resistance value of the micro humidity sensor, the calibration was carried out in the temperature range of 5 °C to 40 °C, with an interval of 5 °C. In order to ensure the accuracy of the humidity and temperature displayed by the programmable constant temperature and humidity machine, this study used a commercially available multifunctional sensor that could measure humidity and temperature at the same time for calibration. Due to the hysteresis effect of moisture-sensing materials, there might be some differences in the resistance value under the same humidity in the process of humidification and dehumidification. Therefore, in this study, the micro humidity sensor was calibrated from low humidity to high humidity and from high humidity to low humidity. Furthermore, the dimensionless variation of voltage values was used to obtain the calibration diagram, as shown in The self-made integrated three-in-one microsensor and the commercially available wind speed sensor were actually installed inside the HVAC cold air pipe of the factory, as shown in ® LTC 9320) resistant to electrochemical corrosion and acid was used as the protective layer. This integrated three-in-one microsensor has the features of a small size, high sensitivity, grease resistance, and bendability. Additionally, it offers the benefits of measuring three critical physical parameters in real-time and simultaneously, namely wind speed, temperature, and humidity. It can be placed in any position, and it is cheap and has a fast response time. By placing the self-made integrated three-in-one microsensor inside the HVAC cold air pipe of the factory together with the commercially available wind speed sensor for field monitoring and data comparison, it could be known that the self-made integrated three-in-one microsensor had higher accuracy. Moreover, the reliability and durability of the self-made integrated three-in-one microsensor were further verified over 310 h in a long-time test. The commercially available wind speed sensor (FS7.0.1L.195) can only measure wind speed, while the self-made flexible three-in-one microsensor determines wind speed based on different calibration curves for environmental temperature and humidity, making it more accurate than the commercially available wind speed sensor (FS7.0.1L.195). In the future, in terms of wireless software design, additional IC chips need to be purchased to enable an Arduino board to connect to more sensors.In this study, MEMS technology was used to integrate the wind speed, temperature, and humidity microsensors onto the Polyimide (PI) substrate with a thickness of 50 µm, and the polyimide (Fujifilm Durimide