However, leadership was not emphasized. In a new intervention module, the roles and associated responsibilities of clinical instructors to conduct, design, and lead CC-based education were emphasis.The Accreditation Council for Graduate Medical Education (ACGME) core competencies (CC) in general medicine-based primary care are essential for junior medical trainees. In this country, a intervention module with that of the previous regular module.This follow-up explanatory case study compares the effectiveness of regular group (n = 28) comprised clinical instructors who participated in the FD module during the 2013–2014 year while the intervention group (n = 28) was composed of 2015–2016 participants. Prior to the formal (hands-on) training, participants in the intervention group were asked to study the online materials of the regular module. These participants then received a 30-h hands-on training in conducting, designing, and leading skills. Finally, they prepared a 10-h reflective end-of-module presentation of their real-world practices.The intervention FD group, compared with the regular FD group. In the intervention group, senior academicians (associate and full professor) are more substantially involved in designing and leading CC-based courses than junior academicians (lecturers and assistant professors). Among non-teaching award winners of in the intervention FD group, the follow-up degree of sustained involvement in delivering, designing and leading CC-based courses was significantly higher than that of the regular group.Following the training, a higher degree improvement in participants self-reported familiarity with CC education, self-confidence in their ability to deliver CC education and sustained involve CC education were noted among the intervention FD modules substantially motivated clinical instructors to become leaders in CC education.Our study demonstrated that leadership training in the  The Accreditation Council for Graduate Medical Education (ACGME) core competencies (CC), in general medicine-based primary care are essential for junior medical trainees. They included medical knowledge, interpersonal and communication skills, system-based practice, practice-based learning and improvement, professionalism and patient care. Clinical instructors must teach and assess junior medial trainees in CC before they enter sub-specialties. In 2003, the outbreak of the severe acute respiratory syndrome (SARS) in this country exposed serious deficiencies of CC-based primary care by junior trainees due to a lack of appropriate education. Accordingly, there is an urgent educational need to train faculty to educate junior medical trainees in CC-based primary care. Faculty development (FD) refers to activities that clinical instructors or organization pursue to improve their knowledge, skills, and behaviors in response to specific educational needs , 2.delivering CC education [regular FD model supported by situated and experiential learning theories that emphasized on-site observational learning and guided reflection had been continuously utilized in our hospital [regular FD module familiarizes them with CC-based teaching and assessment and thus, increases their confidence [In 2003, during the post-SARS era, Executive Yuan of the Department of Health (DOH), announced a nationwide pilot FD program to cultivate clinical instructors whose are familiar with, have confidence in, and are substantially involved in CC-based education (teachings and assessments) –5. In 20hospital , 7. In gnfidence , 9.delivering, designing and leading CC education that fits the need of a system in the midst of reform [Moreover, since 2013, clinical instructors in this country have been facing new challenges, including the extension of postgraduation training from 3 months to 2 years, an amendment in the number of years of medical school study from seven to six, and limitation on work hours for all residents –12. Accof reform .regular FD module did not effectively cultivate their ability to play multiple roles (instructors and leaders) or to take on corresponding responsibilities  [delivering skills as in the regular FD module, the intervention module emphasized the training of designing and leadership skills [intervention FD module, clinical instructors are expected to competently show the way in CC education deliver, design, and leadership,However, a survey of participants revealed that our previous ucation) , 15. Theucation) , 15. In p skills , 17. Aftintervention and regular FD modules on participants’ familiarity with CC education, confidence in their delivery, and sustained involve in instruction and leadership roles in CC education following training. Moreover, the various impacts of this intervention module on participants with different academic positions and teaching performance were compared.This study aimed to compare the effects of the regular and intervention groups.,An explanatory case study is an in-depth exploration and explanation of an intervention in a real-life context, opposing to hypothesis testing , 19. ThiWith respect to CC-based teaching and assessment delivery skills, the major training topics focused on principles of identifying learning objectives, adult learning, creating and maintaining a positive learning environment, developing and using interactive audiovisual tools, and on-site observational learning and guided reflection.regular FD module comprised 40 h across 3 months. It consisted of brief expository lectures and small group discussions. The first 30 h included an introduction to educational theory, and on-site observation of CC education delivering skills. On the final 10 h, as part of the end-of-module presentation, presenter reflected their skills in delivering CC education and received paper and face-to-face feedback from senior facilitators and peers , mini-clinical evaluation exercise (mini-CEX) and the objective structured clinical examination (OSCE) [After participating in the n (OSCE) , 21. Alldesigning and leading CC-based education and their confidence in delivering it was insufficient. Therefore, during the 2015–2016 year, the educational committee organized a new intervention FD module emphasizing leadership. Case-control studies sometimes use historical controls, if controls are not permitted, based on special conditions such as the learning right of participants and educational ethics [regular FD cohorts were used in this study between 2013 and 2016 as controls for the intervention FD cohorts. Notably, both the regular and intervention FD cohorts (n = 81) had similar characteristics  were conducted and compared between groups to evaluate whether the newly trained clinical instructors were substantially involved in pre-module, end-of-module and follow-up stages of this study, the intervention FD module was evaluated and compared with the regular FD module. Using a five-point Likert-type self-assessed questionnaire, the degree of familiarity with, self-confidence and sustained involvement in delivering, designing and leading CC-based education was evaluated  on the degree of sustained involvements in CC-based education in the regular and intervention groups were also analyzed using student t tests. Additionally, ANOVA was used for the comparison of data among multiple time points. This study was approved by the Ethics Committee of Taipei Veteran General Hospital with ID numbers 2014–02-007 AC and 2015–12-015 BC and performed in compliance with the Declaration of Helsinki [The Helsinki . In agreregular and three intervention module participants) were not included in the study because they did not complete all the training. An additional four clinical instructors did not complete all the surveys; yielding a final sample of 56 subjects (n = 28 in each group) for final analysis.Of the 66 enrolled clinical instructors, six of them  and assessments  between the regular and intervention groups .In Table design and lead CC-based teachings or assessments. In fact, most program directors at our institution are senior academicians. In the regular group, there was no difference in the follow-up degree of sustained involvement in delivering, designing and leading CC-based teachings or assessments between senior (n = 11) and junior (n = 17) academicians  had more sustained involvement in designing and leading CC-based teachings or assessments than junior academicians (n = 10)  Fig. b.Fig. 2designing and leading CC-based teachings or assessments was higher than the degree of involvement in delivering CC-based course  to evolve substantially as leaders in CC education.In our institution, teaching awards winners are selected online by junior medical trainees according to the annual performance of teachers. Consequently, teaching award winners are considered to be more high teaching performance teachers than non-teaching award winners. Besides encouraging high teaching-performance teachers, teaching awards provide opportunities for teachers and program directors to review their teaching and programs. Teaching awards also motivate low teaching-performance teachers to improve themselves by receiving more training. In general, educational leaders in CC education tend to be high teaching-performance teachers as opposed to low teaching-performance teachers. Baroffio et al. have suggested that the ideal leadership FD program will to help the teaching performance and leadership of low teaching-performance teachers . EngagemLevel 1 (reaction) of the Kirkpatrick Model measures participants’ satisfaction; level 2 (earning) analyzes whether the FD increases participants’ knowledge or skills (participants’ familiarity with and confidence in CC education); level 3 (behavior) looks at whether participants utilize what they learn at work (participants’ sustained involvement in CC education), and level 4 (results) determines whether the FD had a positive impact on the organization.The Kirkpatrick Model is a well-known model for evaluating the effects of FD programs. intervention FD module improved clinical education or decreased medical errors [regular and intervention groups in our study can partially overcome the possible bias of self-reported data. A second limitation was the fact that the intervention FD group completed leadership training and some of the questions on the surveys were leadership-related. To have comparable results, both the regular and intervention FD groups used similar questionnaires for self-assessment in our study. Still, the multiple self-assessment time points in the current study indicated sustained effects of the intervention FD module on leadership training of clinical instructors in delivering, designing and leading CC-based teaching and assessment.The limitations of this study include the following. First, it did not assess outcomes at level 4 of the Kirkpatrick Model such as whether the l errors , 36–39. l errors . To avoiintervention FD modules to motivate new clinical instructors to become substantially involve as leaders in ACGME CC-based education.Faced with continuous changes in medical education and practice, the new generation of medical educators is required to be not only clinical instructors but also educational leaders. Despite some limitations, the present study confirmed the effectiveness of leadership-enhanced


Previous literature indicates that implementation of intein-mediated splicing has been extended to in vivo systems. Besides, the homing endonuclease domain also acts as a versatile biotechnological tool involving genetic manipulation and control of monogenic diseases. This review orients the understanding of inteins by sequentially studying the distribution and evolution pattern of intein, thereby highlighting a role in genetic mobility. Further, we include an in-depth summary of specific applications branching from protein purification using self-cleaving tags to protein modification, post-translational processing and labelling, followed by the development of intein-based biosensors. These engineered inteins offer a disruptive approach towards research avenues like biomaterial construction, metabolic engineering and synthetic biology. Therefore, this linear perspective allows for a more comprehensive understanding of intein function and its diverse applications.Inteins are mobile genetic elements that apply standard enzymatic strategies to excise themselves post-translationally from the precursor protein via protein splicing. Since their discovery in the 1990s, recent advances in intein technology allow for them to be implemented as a modern biotechnological contrivance. Radical improvement in the structure and catalytic framework of  Splicing mechanism can be broadly categorized as RNA splicing and protein splicing, two mechanisms responsible for the flow of information from a gene to its protein product to yield a functional protein whose sequence is strictly noncolinear with the gene. While group I introns self-splice at a precursor RNA level, intein splicing involves the removal of an intervening sequence at a precursor polypeptide level . InitialMycobacterium xenopi is designated as Mxe GyrA, for instance [Mxe GyrA, coincidentally, is also the smallest known naturally occurring intein [Most of the inteins are interrupted by a homing endonuclease domain (HED) ,8,9. Howinstance ,14. Mxe g intein .Inteins naturally exist in three different configurations : (1) fulThe potential to exploit inteins for a practical purpose has led to the development of a diverse array of applications in modern biotechnology. Inteins can be engineered to undergo conditional protein splicing (CPS) which requires environmental or molecular triggers like light, changes in pH or temperature, change in redox state or addition of small molecules ,25,26,27Saccharomyces cerevisiae VMA1 gene that encodes for an alpha subunit of vacuolar H+ ATPase [Thermococcus litoralis [M. tuberculosis [M. leprae [Candida tropicalis [www.ncbi.nlm.nih.gov/gene) to scan the distribution of intein in all the three domains of life, where out of 2709 intein-containing genomes, 56% of total intein-containing genome is found in eukaryotes, 19.8% in archaea and 6.64% in eubacteria. We also performed an assessment for intein distribution in viruses and observed 17.4% of total intein-containing genome is present in viruses  and essential housekeeping genes, including essential proteases, metabolic enzymes, RNA processing proteins and energy supplying vital proteins. Their insertion site coincides with the conserved domains, responsible for host protein function like catalytic or ligand binding sites, enzyme active site, DNA binding sites etc. ,18. InseN) linked to N-extein and the C-terminal intein (IC) with corresponding C-extein. The two fragments reassemble into a complete intein structure that functions similar to a full-length intein system [cis-splicing [trans-splicing system instead. Upon translation, the two separate polypeptides associate in a zipper-like network prior to excision from precursor [cis- and trans-splicing inteins follow a similar pathway to carry out splicing post precursor reestablishment [cis-splicing pathway [Natural intein structure is directly congruous to their functional role. If classified based on domain structure, inteins can be either full-length, mini-intein or split intein. Full-length intein bearing systems are expressed in a single polypeptide chain, which includes an intein domain responsible for splicing activity and a HED with a role in DNA invasion into the precursor protein-coding gene  51,52,5,552,53. n system ,54,55. Wsplicing ,56. The recursor ,57,58. D pathway ,59,60. A pathway . The int pathway .There is a homology between the splicing domain of intein and the HINT family protein-processing domain . The HINThe splicing domain of intein is broadly divided into two subdomains: N- and C-terminal splicing domains. These regions consist of several conserved motifs containing conserved residues, which facilitate the initiation and completion of splicing activity . N-termiHINT domain appears to be the key player in the intein-mediated splicing mechanism since it was shown to fold into a horseshoe-like structure similar to inteins. Intein is mostly limited to archaea, bacteria and unicellular eukaryotes, but Hog-Hint domains are spread across multicellular animals . BIL domHedgehog signaling developmental proteins in animals have three distinct protein domains . The N-tA past study by Amitai and team members identified new bacterial intein-like (BIL) domains termed as A- and B-type BIL . In termMethanococcus jannaschii TFIIB cis-intein indicating its mutualism in the protein splicing process [The HED is located in between the N- and C-terminal inteins and is involved in the horizontal transfer of inteins to inteinless alleles termed as “intein homing” . The coa process ,10.The homing cycle or the life cycle of inteins with homing endonucleases was first formulated by Goddard and Burt , as theypolB-c intein in Haloferax valcanii and found a fitness cost of over 7%. In a direct completion assay performed on intein-positive and intein-negative strains, it was seen that the intein-negative strains outcompeted the intein-positive strains due to a faster growth rate [H. volcanii [The relative fitness of an organism directly correlates to the presence or absence of homing endonuclease and intein. Butler et al. had a suggestion that inteins may decrease the fitness of a host organism . Althougwth rate . A studyvolcanii . There iInteins implement classical enzymatic strategies to excise themselves from precursor protein without the requirement of any external cofactor or energy. In fact, in a past article, Evans et al. introduced inteins as nature’s escape artists . Intein To date, there are three classes of inteins identified with distinct sequence motifs or blocks and splicing strategy. Class 1 or classical  intein splicing a involveSce VMA and Mxe GyrA intein systems show that the Block B His is hydrogen-bonded to the amide nitrogen of the scissile peptide bond. The imidazole ring of His is in proximity for the protonation of the Cys1 amide bond, promoting the breakdown of the linear thioester intermediate yielding an N-extein linked to the intein by a thioester bond. This drives forward the first N-S acyl shift [Ssp DnaB [a shift in Block B His from a high pKa to a low pKa during the first step of splicing reaction in Mtu RecA intein system serves as evidence for its dual role in catalysis [Mtu RecA intein shows that thiol deprotonation is achieved by conserved F-Block Asp and His, causing ground-state destabilization. This destabilization becomes the driving force for the thioesterification step [Arthobacter species FB24 Arth_1007 (DnaB), a degraded pseudogene [Thermococcus kodakaraensis Tko CDC21-1 uses a Lys to stabilize the initial N-S acyl shift tetrahedral intermediate, thereby activating N-terminal splice junction [Pyrococcus horikoshii Pho RadA intein [Nostoc punctiforme Npu DnaE intein is shown to affect splicing by occupying space at the active site to align the catalytic residues optimally [Mtu RecA system [The first step of classical or canonical splicing is carried out critically by Block A residues consisting of either Cys, Ser or Thr. Cys, Ser or Thr are essential residues that act as nucleophile in the splicing reaction. This N-O/-S acyl rearrangement is challenging in terms of the kinetic aspect. It needs the assistance from Block B residues: Thr and His, Block F Asp residue and the structural strain in the active site ,82,83. Tyl shift ,87. A chSsp DnaB . MoreoveSsp DnaB . A drastatalysis . Studiesion step . Intein eudogene , and Thejunction . N-exteiA intein . In anotptimally . The F-BA system ,90. MutaA system .trans-thioesterification is a challenging step to be analysed experimentally since it is tedious to isolate the linear thioester intermediates. This reaction is carried out by the C+1 residue present at C-splice junction. It attacks the linear thioester and forms a branched intermediate structure. The F4 (fourth residue in F block) Asp is linked to this step for deprotonation of C+1, increasing the nucleophilicity of this residue substantially [a analysis [The second step of antially . Deprotoanalysis . The firanalysis ,89,90.The third step, i.e., Asn cyclization, is irreversible and coupled to the first two steps of splicing reaction. It cleaves the amide bond between the intein and C-extein. Multiple studies have proposed that both F-Block and G-Block histidines are crucial for the coordination of Asn cyclization. The F-Block His helps in increasing the nucleophilicity of terminal Asn by deprotonation and the tetrahedral intermediate stabilization is promoted by both F- and G-Block His. G-Block His increases electrophilicity of the backbone peptide, accelerating the cyclization process ,95,96,97The fourth and final step involves the conversion of an ester to amide bond between the ligated extein segments. This step does not require any support from either residue of intein or extein, is energetically favourable and faster than the overall reaction . SplicinMja KlbA intein, having an Ala1 and G6 Ser instead of Cys1 and G6 His [Mycobacteriophage bethlehem DnaB intein [Intein containing noncanonical residues implement splicing using variation in the classical pathway . Such ind G6 His . Class 2d G6 His ,100. ClaB intein . Tori etB intein ,102,103.Cis- and trans-splicing intein systems can be further modified to perform controlled cleavage and ligation reaction in response to an array of stimuli [trans-splicing (PTS) and expressed protein ligation (EPL) have been used extensively in the production of semisynthetic proteins, efficient production of bispecific IgG antibodies and C-terminal modification of recombinant protein bypassing the native peptide thioester chemical synthesis [Although intein splicing is a spontaneous process and does not require the help of any environmental or molecular signals, recent work has established that intein splicing activity can be regulated by certain molecular triggers like pH, temperature, redox state, salt concentration and even host protein substrate in a process called conditional protein splicing (CPS) ,25,26,27 stimuli ,32. In r stimuli ,32,112. ynthesis ,115,116.trans-gene expression. PTS has been used for the expression of large genes in adult cardiomyocytes by using a split Npu DnaE system. Conventional viral vectors failed to manipulate expression of such large genes due to a packaging limitation, now bypassed using PTS technology [We intend to describe in detail the recent breakthroughs in intein technology in the field of protein expression to purification, post-translational modification and labelling, inteins as a selectable marker, biosensors and in chnology . Intereschnology . Inteinschnology .Sce VMA intein in conjugation with a chitin-binding domain (CBD) from Bacillus circulans as an affinity tag. The target protein to be purified was cloned in frame with this fusion system and under mild conditions induced to undergo self-cleavage as a result of which the target protein is purified while intein–CBD remains bound to the column [Sce VMA1 intein, triggered to cleave at its N terminus (IMPACT system)  a, or botre or pH . One of proteins .Ssp DnaB split-intein by performing a deletion at the N-terminus, ensuring the eradication of cleaving activity in the intein, allowing the purification of only the C-terminally fused protein target  cells using t intein . Similart intein . Mootz aproteins . To overN fragment or short IC fragment are used. One such intein-based labelling process uses chemical ligation, to label glutathione-S-transferase (GST) and eGFP in both bacterial and mammalian systems. The target proteins are expressed as a C-terminal fusion to Ssp DnaB intein and an N-terminal Cys. The target protein is tagged using cell-permeable, thioester-containing small molecules like biotin or a fluorophore [C intein segment to reduce the background signal. The PTS reaction results in ligation of fluorophores to the protein of interest (POI); subsequently, the quencher is released resulting in fluorescence activity  and cross-linkers. The split inteins present in the truncated histone and the delivery cargo assemble upon PTS, precisely joining the modified histone on the native chromatin [Npu DnaE split intein variants, where the N-intein sequence was modified by inducing Gly4Tyr and Asp5Glu mutations and the C-inteins variants were selected from libraries created by error-prone PCR. Active variants were screened by using a GFP-intein conjugates, which were used to construct a turn-on system for enzymes like human immunodeficiency 1 protease and NanoLuc luciferase [Muir and coworkers used an ultrafast fragment . This grhromatin . The engciferase .Pch PRP8 intein system with selectable markers, including amino glycoside, phosphotransferase, imidazoleglycerol-phosphate dehydratase hygromycin B phosphotransferase and transcriptional activator LexA-VP16 [E. coli had a higher splicing efficacy; moreover, when the modified inteins were expressed from a plasmid in S. cerevisiae, it had splicing efficiency greater than 96%. The sensitivity of internal GFP labelling can be further enhanced by the use of a split GFP–intein construct. Modified intein sequence can be fused with split GFP fragments in-frame with specific peptide (extein) sequences at both the ends. The excised intein under selective conditions can also serve as a selectable marker for the expression of reconstituted GFP fused to exteins on either side [Inteins can be used as a genetic marker by facilitating in vivo gene modifications . Muller exA-VP16 . The enzher side . Inteins are sporadically distributed in the genomes of organisms spanning from archaea, bacteria, and eukaryotes to several viral and fungal genomes . Since iIntein-based biosensors are fabricated by utilizing independent protein domains, expressed within living cells. Most intein-based biosensor systems have three functional and structural modules: a sensing module, an intein-derived signal transducer, and an output module. CPS has been the foundation that lay to the development of intein-based biosensors. The signal of interest is accepted by the sensing module, which induces CPS in the intein module and subsequent activation of reporter protein, as shown by the output module a. VariatN and IC fragments. The design criteria for these biosensors includes the formation of two fused proteins, each containing a split-intein and a portion of the reporter molecule. Upon interaction with a binding partner, the split-inteins assemble, resulting in reporter protein reconstitution and activation , using a GFP reconstitution as the reporter, in an artificially split Sce VMA1 intein [Biosensors that detect protein–protein interactions employ the concept of PTS in engineered split-intein systems with low binding affinity between Itivation b. Umezaw1 intein . The gro1 intein . They al1 intein . The sen1 intein . This woThe ability to detect sequence-specific changes in DNA methylation was reported by Huang et al. in living cells. They designed a luminescence-based biosensor for the detection of such epigenetic modulations. The biosensor consists of two fusion proteins, each housing a polydactyl zinc finger domain-split intein fragment-split luciferase domain. Binding of the zinc finger domain to specific DNA target sequences triggers intein-mediated luciferase reporter reassembly . This biMtu RecA intein [E. coli maltose-binding protein (MBP) and the N-terminus is fused to a T4 bacteriophage thymidylate synthase reporter. The reporter activity is modulated in the presence of hormone in a dose-specific manner, which directly correlates to the growth of E. coli cell lines [Allosteric intein biosensors are used in the detection of small molecules c. Wood eA intein . The intll lines . Past stll lines . Later, ll lines . A studyll lines .E. coli system [Sce VMA intein with a human ERα receptor ligand binding domain. The DNA coding sequence for this modified intein is then inserted in the chromosomal lacZ gene. The sensor follows the principle that the resulting intein will be capable of initiating splicing in the presence of estrogen ligands to produce β-galactosidase reporter enzyme [Buskirk et al. designed a splicing-dependent allosteric intein biosensor for detection of estrogen in an i system . The estr enzyme .Ssp DnaE intein system was harnessed for the development of a bacterial redox sensor by utilizing the disulphide-bond control of the intein system  reconstitution by PTS in the chloroplasts of both E. coli and Nicotiana tabacum to produce a herbicide-resistant transgenic crop [A. thaliana by PTS and intein-mediated reassembly of GUS fragments [The combination of split-inteins with PTS has led to the control of pression . This mepression . The adv[E. coli . Similarnic crop ,168. A sragments . Yang anragments .Dictyoglomus thermophilum is controlled by the thermostable bacterial DnaE-1 intein from Thermus thermoplilus in maize [Thermostable xylanase (XynB) from in maize . The protrans-genes by adenovirus delivery vectors [PTS has been used recently in mammalian cells and mice to test the delivery and control of large  vectors . The spl vectors . The in Split-intein system of DnaE has also been used in the production of Cre recombinase in mice . The sysAt a research scale, intein-based bioseparations are widely used techniques for single protein purification. The aspect of these purification strategies might eventually lead to advanced application such as large-scale protein production and high-throughput proteomic studies. Albeit, a substantial analysis concerning the economics and feasibility of the potential future systems are required. In principle, conventional affinity tags are used in large-scale manufacturing of purified proteins. However, the economics of the process lies in the affinity tag removal process. At a manufacturing scales of hundred to thousand kilograms per year, these costs rapidly exceed the gross annual sales of even the most lucrative drugs today. Modified inteins can efficiently remove affinity tags by self-cleavage by applying standard conditional splicing techniques (pH and temperature) . The sheIn a detailed analysis using software simulation of each process , indicated that the operation costs were a major factor for the cost difference, with raw materials accounting for the staggering increase in the cost of intein process. The most expensive raw material was Tris-HCL, which accounted for 61% of all raw materials, followed by DTT, which accounted for 29%. The annual raw material cost-breakdown data reveal the total annual raw material cost for the conventional process was cheaper than the intein-based process. Annual operating expenditure data also reflected that the conventional process is cheaper than the intein-based process. Thus, from this speculation, it is clear that intein-based bioseparations can be economically competitive for large-scale recombinant protein production, but can be more attractive with the use of pH- and temperature-controlled inteins with low-cost buffer systems. The development of more controllable inteins in combination with advanced binding chemistry and process configuration shall increase the opportunity for inteins to be used at a large-scale in the future.trans-splicing. The ability to engineer and harness the trans-splicing system and other related processes of intein splicing has made inteins very popular in the field of protein engineering, especially in technologies such as purification platforms for biopharmaceutical protein production. Intein research has stepped up from being proof-of-concept experiments to productive application based experiments where inteins are used as tools. They are simple, economic and can be used as either N- or C-terminal cleaving affinity tags, engineered to operate under a wide range of conditions. This resulted in the development of a one-step protein purification strategy for recombinant proteins. However, there are limitations to the intein-engineered purification system. The major limiting factor is premature cleavage during protein expression, followed by product loss during binding capture and the overall need for reducing agents. The introduction of split intein systems has, however, solved the problem of premature cleavage during expression but still requires a reducing agent to induce cleavage. The cleavage activity of inteins controlled by physical conditions suffers from product loss. This shortcoming was partially addressed by the development of nonchromatographic methods such as expressed protein ligation (EPL), although their implementation in large-scale manufacturing will require stringent analysis and optimization to generate better inteins in terms of speed and control of cleavage reactions. Natural and artificially split-intein have not only enhanced conventional technology but also opened new avenues of research in metabolic engineering and drug development. The recent growth in the number of in vivo protein manipulation using intein splicing also guarantees the advancement of intein-based tools. Thus, the future intein technology will build on the present technology to provide new classes of therapeutic proteins and subsequently bridging the gap between systems and functional biology. However, a more detailed characterization of target protein residues at the cleavage junction is required to validate the system to be developed further to be used as a platform. These developing applications as summarised suggest that inteins are becoming more critical and mature biotechnological tools along with the capability of branching into profound areas of research, including the development of newer transgenic plants and novel therapeutic strategies. Despite that critical advances in intein technology have proven to be beneficial in recent years, the economics, scale-up and optimization of intein-mediated techniques at an industrial scale to-date remain a major challenge.Inteins are widespread in host proteins and organisms across three kingdoms of life. This extensive phylogenetic distribution pattern of inteins contemplates their nature as a mobile genetic element. Although cases of horizontal intein transfer have been discovered, there remain questions: How does HED associate with inteins? How effortlessly does intein transfer occur among related organisms? Inteins seem to be biased, but not limited to host proteins involved in DNA repair and replication, possibly since it may shuttle intein genes across organisms, help in intein homing and make inteins less harmful to host cell by limiting intein endonuclease production during times of active DNA repair. Laboratory model studies can shed light on the molecular requirements of intein homing. Structure–function studies can also highlight the evolutionary basis of intein invasion and origin, including the structural basis of each step of intein splicing. Inteins can also evolve into new structures harbouring new functions, as seen in cases of


Given expression data, gene regulatory network(GRN) inference approaches try to determine regulatory relations. However, current inference methods ignore the inherent topological characters of GRN to some extent, leading to structures that lack clear biological explanation. To increase the biophysical meanings of inferred networks, this study performed data-driven module detection before network inference. Gene modules were identified by decomposition-based methods.ICA-decomposition based module detection methods have been used to detect functional modules directly from transcriptomic data. Experiments about time-series expression, curated and scRNA-seq datasets suggested that the advantages of the proposed ModularBoost method over established methods, especially in the efficiency and accuracy. For scRNA-seq datasets, the ModularBoost method outperformed other candidate inference algorithms.As a complicated task, GRN inference can be decomposed into several tasks of reduced complexity. Using identified gene modules as topological constraints, the initial inference problem can be accomplished by inferring intra-modular and inter-modular interactions respectively. Experimental outcomes suggest that the proposed ModularBoost method can improve the accuracy and efficiency of inference algorithms by introducing topological constraints. In recent years, systems biology has developed rapidly. With the continuous development of high-throughput analysis technologies such as proteomics and transcriptomics , it has After several decades of development, computational efficiency and accuracy of network inference algorithms have increased dramatically. Large gene networks of micro-organisms and mammals can be reconstructed using transcriptomics datasets. Methods with high accuracy in inferring GRNs have been proposed. For example, the TIGRESS  and fuseHowever, there are some limitations also exist in those GRNs inference methods. Inferred topologies usually lack clear biophysical explanations, limiting their applications such as disease-gene prediction and gene therapy. For GRN and protein–protein interaction (PPI) networks, a key character shared by biological networks is the so-called functional module or communities structure . Each moWith accurately detected modules, it is feasible to develop an efficient inference framework that combines inherent modular structures with established inference algorithm. Plenty of module identification methods have been developed to detect functional modules from GRN, PPI, and other biological networks. For gene module detection approaches including CoReg and SigMod etc, 14, netMotivated by these topological characters, this study proposes a ModularBoost method to integrate decomposition-based module identification and boosting-based inference algorithm. Using ICA-FDR, ModularBoost assigned genes to regulatory modules according to their expression data. Based on the detected gene modules, casual relations within gene modules were inferred by GRNBoost2 that is a top-ranking inference algorithm, while the regulatory relationships between modules were detected by linear sparse regression. Then ModularBoost normalized the scores from subnetworks to obtain the final network.S. aureus, E. coli and Yeast expression data from the Dream5 challenge [Among decomposition-based methods, ICA-FDR, ICA-zscore, and PCA have been implemented and compared with commonly-used clustering expression datasets . And we hallenge . As for Curated networks were extracted from Beeline project, which focused on GRN inference using single cell expression data. Different from traditional microarray datasets, single-cell data contains information about cell–cell variability and can be used to investigate behavior patterns of cell populations . HoweverE. coli-S denotes single-cell data with 700 cell samples, while both E. coli-LL and E. coli-LH represent datasets with 2000 samples. In addition, the E. coli-LL and E. coli-LH groups correspond to single-cell data with low and high dropout rates respectively. Evaluation metrics of the curated GSD network and PIDC E. coli network were compared in Table In this case, the proposed ModularBoost approach aims to improve the accuracy in inference by introducing topological constraints. In the proposed ModularBoost method, ICA-FDR based decomposition was used as inner part to detect functional modules directly from curated datasets. Competing methods include ICA-FDR2, ICA-zscore, PCA-based decomposition and K-means clustering methods. Performance index mentclass2pt{minimq_cutoff according to the number of genes in GRN. For the module identification evaluation of curated networks with 19 genes, we set consistently E. coli network with 100 genes set q_cutoff of ICA-FDR, ICA-FDR2, and PCA was q_cutoff of ICA-zscore decomposition was different from ICA-FDR due to the difference in statistical principles: A pattern that could be found in Table Instead of reconstructing a network as whole, the ModularBoost approach accomplished the GRN inference task based on the identified modules, which were densely connected genes and TFs. Furthermore, intra-modular and inter-modular interactions between genes were inferred in two stages of inference.It can be observed from Table k denotes degree, To show the superior network prediction of ModuleBoost2, we compared ModularBoost with the ridge regression based inference method from the perspective of degree distribution . The degower-law , and it E. coli-S and E. coli-LL were shown in Fig. The power-law distributions of PIDC Under this circumstance, the proposed ModularBoost method can obtain GRNs that are higher topologically similar with gold standards, compared with ridge regression inference algorithm. In other words, ModularBoost is able to improve the interpretability of inferred networks to some degree.In this section, experimental single cell RNA sequencing(scRNA-seq) datasets were used as the major information source in GRN inference. In biomedical and genomic research, scRNA-seq datasets has played a crucial role in exploring dynamics of cell population and differentiation. Three scRNA-seq datasets and relevant gold standard networks were provided by the SCODE project. In Table The basic idea of module standards is to explore strongly interconnected components where nodes are mutually connected. In module 2 of PrE network, ETS1, EGR1 and SMAD7 formed a connected component. ETS1 and EGR1 are hub nodes due to high out-degrees. In known regulatory relations, the SMAD7 gene owns 12 out-degrees and 16 in-degrees, indicating that this gene play a bridge node in the PrE network.For the MEF network, those TFs such as KLF4 had high out-degrees and were believed to have high topological importance in information flows. According to known modules, overlapping existed, allowing part of genes belong to two or more functional modules.In Fig. For PrE, MEF, DE networks, the numbers of gene modules were assigned as 3, 4, 4, according to prior information.From Table Based on the detected modules, the proposed ModularBoost approach accomplished the network inference using two kinds of regression: ridge regression and ensemble inference algorithm. This study chose cutting-edge ensemble inference named GRNBoost2 to determine intra-modular casual interactions. Table SCODE PrE and MEF datasets are single-cell expression data measured from mouse cells, while SCODE DE dataset denotes expression data of human cell populations. For PrE and MEF datasets, the proposed ModularBoost method obtained improved inference performance with reduced computational cost  is to find the hidden ‘independent component’ that refers to the gene module in this research . When apX, this study assumes that the columns and rows of X correspond to genes and cell samples respectively. The expression value j at sample i is shown asi in component k and k on gene j [k independent signals that corresponded k gene modules are found in this process.For single cell expression matrix n gene j . ICA-decn gene j . FastICAFastICA algorithm tries to find gene components in the source matrix that own non-Gaussian characteristics. Each modular signal in the source matrix generally obeys a heavy-tailed normal distribution. Under this circumstance, those genes at the tails have a significant contribution to those components, while the majority of genes in peak have weak impact. In the next step, we applied the false discovery rate (FDR) estimation to assign genes to various functional modules.The basic procedure of the ICA-FDR algorithm is shown as Algorithm 1.q_cutoff. The process of whitening was defined as Eq.p value for genes in each module, and a ranked list in descending order. Correction for multiple testing was performed by calculating a “Q-value” from the p values and estimating FDR values [8p- alue out of n gene p values for the k modular signal.Input parameters include the number of gene modules R values . The forq_cutoff to a module, and the process was shown in Fig. q_cutoff was selected from the set The fundamental principle of post-process is assigning the genes with lower Q-value than The ICA-based decomposition also has several derivatives, including ICA-FDR, ICA-FDR2 and ICA-zscore. ICA-FDR2 is similar to ICA-FDR but divides each component into two modules according to the signs of gene regulations, while ICA-zscore replaces FDR indexes with z-scores to detect module from source signals. As a tool to reduce dimension, the principal component analysis (PCA) can be used to visualize the similarities among the biological samples . We testDifferent NI algorithms have their unique characteristics, and the combination of multiple algorithms can provide a possible strategy to obtain networks with sparse and dense interactions . The ICABased on a similar concept as GENIE3, GRNBoost2 infers regulators for every target gene purely from the gene expression matrix . The conN is the number of samples or experiments in the gene expression matrix, and sth sample.The set of j in s-th observation samples, i.e. j are controlled by the other genes, shown by Eq.j, and it is trained from the learning sample i to gene j. For the tree regression-based GRN inference method, the function S is the set of samples at the tree node GRNBoost2 assumes that the expression levels of the genes in For GRNBoost2, each decision tree is trained by a random subset of samples that cover approximately 90function . Trees sTherefore, gene modules correspond to subnetworks with multiple topological importance levels. Gathering regulatory associations and sorting in descending order, the intra-modular inference finalizes the output as shown in Fig. The regulatory associations between regulators and target genes in the same module were inferred by ensemble-based GRNBoost2 algorithm, while the relationships controlled by regulators that outside the module are still unknown. The combination of sparse regression algorithms with biologically meaningful constraints may provide a promising solution to enhance accuracy of GRN inference. Based on this hypothesis, we recovered regulatory relations among genes in different modules by adopting regularized linear regression (ridge regression) and used a pre-treatment to reduce computational complexity. The visualization of inter-modular inference is available in Fig. n genes, m samples, and the expression matrix In the following, given After the inference of subnetworks and inter-modular connections, a total of Recovery, Relevance, and Evaluation metrics are used to quantitatively evaluate the performance of data-driven module identification methods. As indexes F measure, Rand index, and the normalized mutual information face the problem of detecting overlapping modules . This stM are the set of known and observed modules. In this first stage, a distance (similarity) matrix is computed by the Jaccard index between two modules sets.Recovery is used to match known modules with observed modules, and the Relevance index reflect the extent to which observed modules match with known modules.Relevance) is calculated by averaging the similarities of known modules and picking out the best representatives in the detected modules. Another score that is related to false positives (Recovery) is computed in a similar style. An asymmetric method for module similarity is given by averging Relevance and Recovery as shown in Eq. 17K edges in this list, we compared them with gold standards to assess the number of false positives (FP), true positives (TP), false negatives (FN), and true negatives (TN). ROC curve shows the trade-off between false positive rate (FPR) and true positive rate (TPR) across different K thresholds, while PR describes the relationship between recall and precision. FPR, TPR, recall, and precision are expressed as:Afterwards, the similarity score


Evidence suggests that physical activity (PA) is beneficial for reducing fatigue in colorectal cancer (CRC) survivors. However, little is known regarding long-term effects of PA on fatigue and whether pre-diagnosis PA is associated with less fatigue in the years after diagnosis. Our study aimed to investigate the association of pre- and post-diagnosis PA with long-term fatigue in CRC survivors.This study used a German population-based cohort of 1781 individuals, diagnosed with CRC in 2003–2014, and alive at five-year follow-up (5YFU). Physical activity was assessed at diagnosis and at 5YFU. Fatigue was assessed by the Fatigue Assessment Questionnaire and the EORTC Quality of Life Questionnaire-Core 30 fatigue subscale at 5YFU. Multivariable linear regression was used to explore associations between pre- and post-diagnosis PA and fatigue at 5YFU.No evidence was found that pre-diagnosis PA was associated with less fatigue in long-term CRC survivors. Pre-diagnosis work-related PA and vigorous PA were even associated with higher levels of physical (Beta (ß) = 2.52, 95% confidence interval (CI) = 1.14–3.90; ß = 2.03, CI = 0.65–3.41), cognitive , and affective fatigue . In cross-sectional analyses, post-diagnosis PA was strongly associated with lower fatigue on all scales.In this study, pre-diagnosis PA does not appear to be associated with less fatigue among long-term CRC survivors. Our results support the importance of ongoing PA in long-term CRC survivors. Our findings might be used as a basis for further research on specific PA interventions to improve the long-term outcome of CRC survivors. With over 1.8 million estimated incident cases and 881,000 estimated deaths in 2018, colorectal cancer (CRC) is the third most common cancer and the second most common cause of cancer-related death worldwide . In deveMany CRC survivors still experience detriments in  quality of life (QOL) years after their diagnosis –7 and faPhysical inactivity is an important modifiable risk factor for non-communicable diseases including CRC . FurtherAlthough one study  investigRecent studies assessing PA after treatment , 20–22 aDarmkrebs: Chancen der Verhütung durch Screening) study. The study is carried out in the Rhine-Neckar region in the southwest of Germany; an area that has a population of about 2 million people. To date, the study includes over 6000 patients with both symptomatic and screen-detected CRC, recruited since 2003. Eligible cases with a histologically confirmed diagnosis of primary CRC  have to be older than 30 years at diagnosis, residents of the study region, German speaking, and physically and mentally able to participate in an interview of approximately 1 h. Approximately 50% of all eligible patients are recruited by 22 hospitals in the study area. Incomplete recruitment of patients is largely due to lack of time among the clinicians in charge of notifying the study center in the routine setting. Further details of the study have been described elsewhere [This analysis is based on CRC patients recruited within the ongoing population-based DACHS  are obtained by trained interviewers using a standardized questionnaire. Three years after diagnosis, detailed information about treatment, other diseases, and recurrence is collected from attending physicians, using a standardized questionnaire. In order to obtain follow-up data including changes in lifestyle (including PA), medical, or recurrence history, and fatigue, CRC patients are sent a questionnaire by mail 5 years after diagnosis. Information about recurrence, other diseases, and new cancers is verified by the patients’ physicians. Patients’ vital status is regularly checked through population registries.For this analysis, 1781 participants who were recruited between 2003 and 2010 and participated in the five-year follow-up (5YFU) between 2009 and 2016 were included , one question on light work-related PA , one question on walking , one question on cycling , and one question on sports . These retrospective data have been used to address the prognostic impact of PA in recent papers , 32. FivBased on activity-specific metabolic equivalent (MET) score values described by Craig et al. , MET houFrom the baseline assessment, activity-specific lifetime MET-h/wk were derived from the MET-h/wk spent at ages 20, 30, 40, 50, 60, 70, and 80 (assessed at baseline), considering the current age at diagnosis of the patient and the years spent in each decade. Information from the age decade preceding the patients’ current age at diagnosis was used to calculate the activity-specific MET-h/wk for the last age decade (e.g. PA at diagnosis age 60 for participants in the age group 60–69). The activity-specific MET-h/wk were summed up to create the variables baseline PA lifetime and last decade.In subgroup analyses, baseline PA was categorized into different PA domains  and intensities . Physical activity was classified according to the second version of the Physical Activity Guidelines for Americans : light-iFrom the 5YFU, the MET-h/wk of the last week were calculated for each of the specific activity types and then summed up to obtain the 5YFU PA.Based on sample distribution, quartiles (Q) for PA at baseline for the last age decade  and 5YFU  were calculated. Patients in Q1 were defined as physically inactive whereas patients in Q2-Q4 were defined as physically active. To assess associations of different PA levels with fatigue, the lowest quartile was used as the reference category. Further, these quartiles were used to classify survivors in four groups: active maintainers (active at baseline and at 5YFU), increasers , decreasers , and inactive maintainers (inactive at baseline and at 5YFU).For the main analyses, baseline PA information of the last decade was used and defined as pre-diagnosis PA whereas PA at 5YFU was defined as post-diagnosis PA.At 5YFU, fatigue was measured using the Fatigue Assessment Questionnaire (FAQ) developed by Glaus et al. , and theTo estimate the ordinal association between pre- and post-diagnosis PA, Kendall rank correlations were calculated. Adjusted means were computed using multivariable linear regression models to explore the association of pre-diagnosis PA quartiles with fatigue. Comprehensive covariate adjustment included baseline variables such as age, sex, marital status, residential area, education, comorbidities, alcohol intake, smoking, body mass index (BMI), cancer site, cancer stage, radiotherapy, chemotherapy, and stoma.Multivariable linear regression analyses were repeated, calculating beta values (ß) with 95% confidence intervals (CI) and modeling pre-diagnosis PA as a continuous variable (per 100 MET-h/wk) for different domains (leisure time vs. work-related) and intensities of PA (low vs. moderate vs. vigorous) with fatigue. In order to assess the independent association of the PA domains with fatigue, the multivariable models were additionally mutually adjusted for the other domain. The same procedure was implemented for the intensities of PA.2-values were calculated to assess the independent proportion of the explained variance of fatigue by pre- and post-diagnosis PA after adjustment for potential confounders.Additionally, multivariable linear regression models were calculated to explore the association between post-diagnosis PA quartiles and fatigue. Covariate adjustment included the same covariates (updated with information at 5YFU) as used in the analysis of pre-diagnosis PA and fatigue. In sensitivity analyses, pre-diagnosis PA was added to the model, and in a second step CRC recurrence. Since the results did not substantially change using the additional covariate adjustments, only results of the first covariate adjustment are reported. Moreover, partial rMultiple linear regression models were repeated for the association between changes in PA and fatigue, using the same covariates (updated with information at 5YFU) as used in the analysis of pre-diagnosis PA and fatigue.p-value < 0.05 in two-sided testing.Complete case analyses were performed since the proportion of missing values was generally low. Information regarding fatigue at 5YFU was missing in less than 2.5% of all cases. No adjustment for multiple testing was performed, given the exploratory nature of the analysis. The statistical software SAS 9.4 (SAS Institute) was used to perform all data analyses. All statistically significant results mentioned in this study refer to a p < 0.0001; pre-diagnosis PA, lifetime = 0.07; p < 0.0001). The correlation between pre-diagnosis PA of the last decade and the lifetime pre-diagnosis PA was stronger .Overall, 1781 long-term CRC survivors were included in the analysis. Participants were on average 66.1 years old at baseline and 60% were male and 40% female  and any of the fatigue scales Fig. . A higheHigher levels of pre-diagnosis PA did not appear to be positively associated with fatigue among CRC survivors 5 years after diagnosis. Pre-diagnosis work-related PA and vigorous PA were even associated with higher physical, cognitive, and affective fatigue. In cross-sectional analyses, post-diagnosis PA was strongly associated with lower physical, cognitive, and affective fatigue. Moreover, survivors being physically active pre- and post-diagnosis and survivors who became physically active post-diagnosis scored significantly lower on all fatigue scales compared to survivors who remained inactive from pre- to post-diagnosis. The results of this study highlight the importance of ongoing PA throughout survivorship for the reduction of fatigue of CRC survivors, which is one of the most burdensome symptoms in cancer survivors . HoweverOur study found no beneficial effects of pre-diagnosis PA on long-term fatigue. This is in in line with a French study  which alOf interest, we found that higher levels of pre-diagnosis work-related PA and vigorous PA were even positively associated with all fatigue scales. This suggests that survivors who had a physically demanding job before cancer diagnosis might still suffer from fatigue even years after their CRC diagnosis. Although all analyses within our study have been adjusted for education, the possibility of residual confounding, for example by lower socioeconomic status, has to be kept in mind. For example, CRC survivors who worked in manual labor might have lower autonomy, less pay, and more challenging working conditions (e.g. night shifts). These factors might be linked to depression and fatigue even years after diagnosis. Pertinent literature supports this assumption. It has been shown that cancer survivors with low education and low socioeconomic status were at higher risk for financial difficulties  and finaThe results regarding changes in PA support the cross-sectional findings on post-diagnosis PA and fatigue, and the assumption that ongoing PA may be important for fatigue of long-term CRC survivors. Only active maintainers and increasers had a significantly lower long-term fatigue compared to inactive maintainers, but no differences in fatigue were found for survivors decreasing their PA levels compared to those who stayed physically inactive. These findings may be explained by decreasers having a more severe health condition following CRC diagnosis and treatment which prevents them from maintaining PA levels compared to inactive maintainers who reported to be physically inactive pre- and post-diagnosis.In line with our findings, several observational studies reported post-diagnosis PA to be associated with lower fatigue in CRC survivors , 43, 44.Although a multidimensional concept of fatigue is well accepted, most studies assessed the association between PA and physical fatigue unidimensionally. Therefore, studies might have missed some aspects of fatigue such as cognitive or affective fatigue and thus only few findings regarding the association of PA with multidimensional fatigue scales exist. Moreover, since some fatigue dimensions have been observed to behave differently it has been discussed that the different fatigue dimensions might not be expressions of one symptom but rather expressions of independent symptoms (multiple symptom concept) . For exaSo far, most studies focused on fatigue shortly after CRC diagnosis. However, it has been reported that fatigue can persist years after diagnosis. Therefore, it is important to find out if PA is beneficial to mitigate long-term fatigue of CRC survivors. The findings of this study add to current knowledge that pre-diagnosis PA cannot replace ongoing PA after diagnosis among long-term CRC survivors, under the assumption that the association between ongoing PA and better fatigue is not entirely a result of reverse causality.Fatigue is often reported as one of the most burdensome symptoms among cancer survivors  and it hMajor strengths of our study include the analysis of a large population-based study sample, the prospective design, completeness of follow-up, comprehensive adjustment for confounders, and detailed investigations of differences in subgroups. Furthermore, results of the study are only based on long-term CRC survivors with a primary CRC diagnosis, and fatigue was assessed using validated and standardized questionnaires.However, there are further limitations to consider. Firstly, due to the observational and partly cross-sectional study design, the results should be interpreted with caution because PA and fatigue may mutually affect one another and therefore our findings give only indirect support for recommendations of encouraging and maintaining PA after CRC diagnosis. Secondly, recall or desirability bias may have occurred through self-reported PA measurement at baseline and 5YFU. In addition, the PA questionnaires at baseline and at follow-up might not be directly comparable. Pre-diagnosis PA was assessed in a personal interview by trained interviewers asking for a wide range of different PA domains, whereby the short form of the validated IPAQ assesses less details about PA domains and was filled out by the survivors themselves. Resulting pre-diagnosis MET-h/wk were two to three times higher compared to MET-h/wk reported post-diagnosis and it cannot be determined whether and to what extent this difference can be attributed to differences in the assessment. Furthermore, MET-h/wk reported at baseline and at 5YFU were substantially higher than pertinent PA recommendations. To overcome this comparability issue, patients were grouped according to quantiles computed separately on the pre-diagnosis PA and post-diagnosis PA distribution instead of using PA recommendations. Furthermore, analyses on changes in PA were based on changes in the assessment specific quantiles instead of changes in MET-h/wk. Finally, residual confounding cannot be ruled out although adjustment for several potential confounders was performed.In conclusion, pre-diagnosis PA does not seem to be positively associated with fatigue among long-term CRC survivors. Instead our results support the need of ongoing PA after CRC diagnosis. However, due to the partly cross-sectional study design, these results should be interpreted cautiously. Randomized controlled trials are needed to provide information on the causality of the association between PA and fatigue among long-term CRC survivors and in turn could provide basis for individually-tailored PA recommendations to this population. Further prospective studies should focus on the association between PA and fatigue at multiple points in time pre- and post-diagnosis to determine if and how the effect of PA on fatigue changes.Additional file 1.


Background and objectives: Goodpasture’s syndrome (GS) is a rare, life-threatening autoimmune disease. Although the coexistence of anti-neutrophil cytoplasmic antibody (ANCA) with Goodpasture’s syndrome has been recognized, the impacts of ANCA vasculitis on mortality and resource utilization among patients with GS are unclear. Materials and Methods: We used the National Inpatient Sample to identify hospitalized patients with a principal diagnosis of GS from 2003 to 2014 in the database. The predictor of interest was the presence of ANCA-associated vasculitis. We tested the differences concerning in-hospital treatment and outcomes between GS patients with and without ANCA-associated vasculitis using logistic regression analysis with adjustment for other clinical characteristics. Results: A total of 964 patients were primarily admitted to hospital for GS. Of these, 84 (8.7%) had a concurrent diagnosis of ANCA-associated vasculitis. Hemoptysis was more prevalent in GS patients with ANCA-associated vasculitis. During hospitalization, GS patients with ANCA-associated required non-significantly more mechanical ventilation and non-invasive ventilation support, but non-significantly less renal replacement therapy and plasmapheresis than those with GS alone. There was no significant difference in in-hospital outcomes, including organ failure and mortality, between GS patients with and without ANCA-associated vasculitis. Conclusions: Our study demonstrated no significant differences between resource utilization and in-hospital mortality among hospitalized patients with coexistence of ANCA vasculitis and GS, compared to those with GS alone. Goodpasture’s syndrome (GS) is a rare but potentially life-threatening autoimmune disease ,3,4,5,6.Studies have demonstrated that the coexistence of ANCA and GS is recognized to occur at a much higher frequency than expected by chance alone, given the rarity of the individual diseases ,15,16,17Thus, we conducted this study using the 2003–2014 National Inpatient Sample (NIS) database to assess the impacts of coexistence of ANCA vasculitis on inpatient mortality, and resource utilization among patients with GS in the United States.https://hcup-us.ahrq.gov/DUA/dua_508/DUA508version.jsp#hipaa). These data are available to other authors via the HCUP-NIS database with the AHRQ.The 2003–2014 National Inpatient Sample (NIS) was used to conduct this cohort study. The NIS is the publically available, inpatient, all-payer database in the United States. This database was developed and maintained by the Healthcare Cost and Utilization Project (HCUP) under the sponsorship of the Agency for Healthcare Research and Quality (AHRQ). The dataset contained more than 7 million hospitalizations annually, which was obtained from a 20% stratified sample of over 4000 non-federal acute care hospitals in more than 40 states of the United States. A survey procedure using discharge weight provided by HCUP-NIS was used to generate national estimates for 95% of hospitalizations nationwide . This daAll patients with a principal diagnosis of GS for the hospitalization based on International Classification of Diseases, Ninth Revision (ICD-9) diagnosis code of 446.21 were included.The predictor of interest was the presence of anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis. ANCA-associated vasculitis was identified using the ICD-9 diagnosis codes of 446.0 (microscopic polyangiitis (MPA)) and 446.4 (granulomatosis polyangiitis (GPA) with and without eosinophilia).Treatments and outcomes during hospitalization were identified based on ICD-9 codes . Treatmep-value of less than 0.05 was considered statistically significant. All analyses were performed using SPSS .Continuous variables were summarized as mean ± standard deviation. Categorical variables were summarized as percentages. The differences within in-hospital treatment and outcomes between GS patients with and without ANCA-associated vasculitis were tested using logistic regression analysis. The odds ratio was adjusted for age, sex, race, smoking, the presence of hemoptysis, and the use of plasmapheresis. A two-tailed p = 0.13), more likely to be male , more likely to have hemoptysis , but less likely to receive plasmapheresis  than GS patients alone.A total of 964 patients were primarily admitted to hospital for GS. Of these, 84 (8.7%) had a concurrent diagnosis of ANCA-associated vasculitis, whereas 880 (91.2%) had GS alone without ANCA-associated vasculitis. Among patients with a concurrent diagnosis of ANCA-associated vasculitis, 54 (64%) had granulomatosis polyangiitis and 30 (36%) had microscopic polyangiitis. The mean age of patients was 54 ± 21 years, and 47% were female. GS patients with GPA required more mechanical ventilation than GS patients alone . In contrast, GS patients with MPA required more non-invasive ventilation  but less renal replacement therapy  than GS patients alone.The presence of ANCA-associated vasculitis was associated with non-significantly increased risks of respiratory failure , circulatory failure , renal failure , non-significantly decreased risks of hematologic failure , sepsis , and in-hospital mortality  in GS patients, as shown in The rates of organ failure and in-hospital mortality in GS patients with GPA and in GS patients with MPA were comparable to GS patients alone.In this study, we demonstrated that hospitalized patients with coexistence of ANCA vasculitis and GS were more likely to have hemoptysis than those with GS alone. Patients with the coexistence of ANCA and GS required non-significantly more mechanical ventilation and non-invasive ventilation support, but non-significantly less renal replacement therapy and plasmapheresis than those with GS alone. There was no significant difference in in-hospital outcomes, including organ failure and mortality between GS patients with and without ANCA-associated vasculitis. There was no significant difference between in-hospital mortality among hospitalized patients with coexistence of ANCA vasculitis with GS and those with GS alone.Our study found a difference in age distribution among patients with coexistence of ANCA vasculitis with GS compared to those with GS alone. While there was a higher percentage of patients with GS alone aged ≤39 years old and aged 60–69 years old, there were higher percentages of patients with coexistence of ANCA vasculitis and GS aged 50–59 years old and ≥70 years old. This is likely because ANCA vasculitis is most prevalent in patients >50 years old , with thPrevious studies have demonstrated the prevalence of ANCA positivity among GS patients of 20% to 40% ,27,28,34Patients with the coexistence of ANCA vasculitis with GS usually present with severe kidney and lung disease requiring aggressive immunosuppressive treatment and plasmapheresis . The finThere has been conflicting data on the prognostic significance of ANCA positivity ,36,38,39Patients with coexistence of ANCA vasculitis and GS usually present with rapidly progressive glomerulonephritis (RPGN), have severe renal involvement at diagnosis, and are similar to patients with GS alone but more severe than in those with ANCA vasculitis alone ,19. WhilOur study confirmed that hospitalized patients with coexistence of ANCA vasculitis and GS had similar rates of renal failure and renal replacement therapy when compared to those with GS alone. Data on the impact coexistence of ANCA on the long-term renal prognosis of patients with GS were unclear ,40. WhilThere are several limitations in this study. Firstly, although the use of the NIS database allows us to evaluate the impacts of ANCA vasculitis on mortality, and resource utilization among patients with GS, possible inaccuracies in ICD-9 CM coding  may confound results. Secondly, given the administrative nature of the dataset, the data on medications, such as immunosuppressants, was limited in this study. Consequently, we could not assess the potential effects of immunosuppressants, such as cyclophosphamide treatment, on hospital outcomes of patients with coexistence of ANCA vasculitis and GS. Thirdly, this is an analysis of an inpatient U.S. database, and this limits the generalizability to the patient population in other countries. Fourthly, kidney biopsy laboratory data (including anti-GBM-antibody titer and types of ANCA), and clinical courses prior to hospitalization are lacking in the database. It has been shown that ANCA may be detected before the onset of GS, suggesting that ANCA-induced glomerular injury could be a trigger for the development of GS . Due to In summary, there are no significant differences between resource utilization and in-hospital mortality among hospitalized patients with coexistence of ANCA vasculitis with GS, compared to those with GS alone.


AlphaFamImpute is an imputation package for calling, phasing and imputing genome-wide genotypes in outbred full-sib families from single nucleotide polymorphism (SNP) array and genotype-by-sequencing (GBS) data. GBS data are increasingly being used to genotype individuals, especially when SNP arrays do not exist for a population of interest. Low-coverage GBS produces data with a large number of missing or incorrect naïve genotype calls, which can be improved by identifying shared haplotype segments between full-sib individuals. Here, we present AlphaFamImpute, an algorithm specifically designed to exploit the genetic structure of full-sib families. It performs imputation using a two-step approach. In the first step, it phases and imputes parental genotypes based on the segregation states of their offspring . In the second step, it phases and imputes the offspring genotypes by detecting which haplotype segments the offspring inherited from their parents. With a series of simulations, we find that AlphaFamImpute obtains high-accuracy genotypes, even when the parents are not genotyped and individuals are sequenced at <1x coverage.http://www.AlphaGenes.roslin.ed.ac.uk/AlphaFamImpute.AlphaFamImpute is available as a Python package from the AlphaGenes website Bioinformatics online. AlphaFamImpute is a software package for calling, phasing and imputing genome-wide genotypes in full-sib families when individuals are genotyped with single nucleotide polymorphism (SNP) array or genotyping-by-sequencing (GBS) data. Many applications in genetics and breeding rely on the availability of low-cost high-accuracy genotypes. GBS is an alternative to SNP arrays .GBS data, and in particular low-coverage GBS data, suffer from a large proportion of missing or, when naively called, incorrect genotypes. Unlike SNP array data, where genotypes are called directly from the genotyping platform, with GBS data genotypes must be called from observed sequence reads. It is challenging to accurately call an individual’s genotype when no reads or a small number of reads are generated at a particular locus. Genotype calling accuracy can be increased by considering the haplotypes of other individuals in the population and detecting shared haplotype segments between individuals  a sampling scheme for multi-locus iterative peeling  AlphaFamImpute took 54 s and used 302 megabytes of memory for 1000 loci on one chromosome. In comparison, Beagle took 11 h and used 284 megabytes of memory.In this paper, we have described the AlphaFamImpute software package for performing fast, high-accuracy calling, phasing and imputing genome-wide genotypes in full-sib families from GBS data. This program will improve the quality of genome-wide genotypes from low-coverage GBS in a range of research and breeding applications.btaa499_Supplementary_InformationClick here for additional data file.


Digital e-cigarette marketing is largely unregulated and remains easily accessible to young people. The growing public concern around youth JUUL use and its viral presence on social media led the company to engage in several voluntary actions to remove and reduce JUUL-related content on Instagram in May 2018. The current study examined how JUUL-related Instagram content changed in the US following JUUL Labs’ wave of voluntary actions in May 2018.In 2019, we collected a total of 50,817 JUUL-relevant posts by 16,323 unique users on Instagram from March 1-May 15, 2018 (Phase 1) and May 16-November 11, 2018 (Phase II) using the application programming interface. We conducted a semantic network analysis to identify major topic clusters over time.Approximately 14,838 JUUL-related posts were made by 5,201 accounts in Phase I and 35,979 posts were made by 11,122 accounts in Phase II. Major content clusters remained unchanged over time–key topics were JUUL-related product characteristics and JUUL-communities; the general vape community; and cannabis-related behavior. Of note, cannabis-related content grew in Phase II, particularly use of the term CBD.Our results reflect the limits of voluntary industry actions to reduce or change vaping-related content on social media. Rather, strong federal restriction on commercial tobacco marketing is the optimal pathway to reduce initial product marketing exposure among youth. These limits would make the emergence and viral contagion of brand-related social media content less likely and reduce its influence on youth behavior. There are currently no federal laws banning digital tobacco or e-cigarette marketing.  CommerciSince early 2018, the e-cigarette market in the US has been dominated by JUUL. , 8, 9 JUTo address growing federal and public concern over JUUL’s popularity among teens,  JUUL LabCorporate self-regulatory actions such as those implemented by JUUL appear insufficient to deter product-related behavior, , 19 or rJUUL-related posts were collected from the Instagram application programming interface (API) through NUVI, Inc., a licensed syndicator of the Instagram data obtained from the platform’s API. Data were retrieved prospectively, in real time during the period of data collection and collected in accordance with the terms and conditions of the API. NUVI produced a collection of de-duplicated posts that contained at least one of search term in the body of the primary Instagram posts. In contrast to other APIs to collect social media (e.g. Twitter), NUVI does not match search terms against commentary or replies to the primary post. Therefore, our sample only included primary Instagram posts.We used a previously documented set of 50 search terms to retrieve data see . The seaData was collected in 2019 and occurred in two stages: Phase I  and Phase II . Data collection terminated in mid-November due to actions taken by Facebook, Instagram’s parent company, to eliminate third-party access to public Instagram posts by December 11, 2018.Two coders rated a stratified random sample of 619 posts to determine if content was JUUL-related based on visual and language components. This labeled sample trained a linear support vector machine, or a supervised model with associated learning algorithms used for classifying text,  to removWe used Wordij 3.0, NodeXL Pro, and Gephi to conduct a hierarchical semantic network analysis (SNA) of terms included in all primary JUUL-related Instagram posts. SNA is an inductive text-based approach to identify major clusters of interconnected terms based on the frequency with which terms appear and the number of co-occurrences between terms.  AlthoughWe used LOESS smoothing curve to visualize the trend of relevant posts over time.  We also Our search captured 14,838 JUUL-related posts by 5,201 accounts in Phase I and 35,979 posts by 11,122 accounts in Phase II. There were four major clusters in Phase I: Cluster a-I (purple lines) depicted youth and other tobacco  and cannabis-related content; Cluster a-II (orange) focused on JUUL product characteristics, JUUL-specific communities (e.g. juulgang), and other vape products/brands ; Cluster a-III (blue) focused on the general vape community (e.g. vapenation); and the smallest Cluster a-IV (green) represented content related to the promotion of over-consumption and vaping in-crowd .In Phase II, cannabis-related content  grew more than expected accounting for the fact that Phase II data collection was 2.8 times longer than Phase 1. The frequency of the term CBD increased from 562 occurrences in Phase I to 3,858 in Phase II and the number of links to other terms increased from 143 to 739. The other two major clusters in Phase II were the general vape community  and JUUL product characteristics, JUUL-specific communities, and other vape products/brands . Terms like smoke, smoking and hookah, which were more closely tied to cannabis-related content in Phase I become more central to the JUUL-specific community in Phase II. Additionally, content related to vaping in-crowd and overconsumption was more greatly tied and merged in the larger general vape community cluster in Phase II. The frequency at which other vape brands such as the JUUL-like device Phix and JUUL-compatible brand Eonsmoke were mentioned was similar in both phases.We found that the volume of JUUL-related Instagram posts, as displayed in With respect to the network analysis, we observed a notable increase in the prominence and frequency of cannabis-related terms in Phase II. This finding may reflect shifting patterns in cannabis and vape behavior over time, and foreshadows the growing concern over lung illness and vaping unofficial cannabis-derived constituents.  NevertheDigital marketing inherently leverages user-generated content to promote brands through peer-to-peer, electronic word-of-mouth. , 29 JUULOur results demonstrate the limits of this voluntary action and challenge whether industry-led efforts can effectively reduce pro-vaping social media content, particularly after an account and its posts have already developed a following. Instead, federal standards completely restricting digital commercial e-cigarette content are necessary to prevent another product like JUUL from utilizing the power of social media to target youth and young adults. Other countries, like the United Kingdom, have adopted standards that restrict commercial tobacco advertising on social media platforms like Instagram.  AlthoughImportantly, restrictions on commercial vaping advertising on social media platforms would not limit individual speech. Rather, they would eliminate one of the essential components needed to create a viral social media marketing campaign–an effective brand message that users share within their networks and begin to discuss organically. , 29 SuchThe present study was limited to the search terms used and may not have captured the full universe of JUUL-related content on Instagram during the study time period. Additionally, for ease of interpretation we only conducted cluster analyses using the top 100 terms in each dataset. These were the most frequently occurring terms and integral to overall network structure; however, it is possible that less frequently occurring terms could uniquely cluster together. The methods used also did not account for post imagery. Thus, we are limited in our ability to examine the inter-relational structure of concepts within images and between images and text to create an even more robust network of topic clusters. Finally, we looked at content across all account types  to demonstrate global change in Instagram content over time. However, future studies with access to account level data should investigate how content changed over time by user type.Our study demonstrates the ineffectiveness of industry-led efforts to reduce exposure to e-cigarette-related social media content among youth and highlights the need for federal restrictions on commercial e-cigarette marketing. Strong regulation is required to reduce youth exposure to pro-vaping content online and reduce e-cigarette use among young people. Further, findings can inform the development of digital marketing restrictions to industries beyond vaping corporations like JUUL.


Background: Cognitive reserve (CR) could attenuate the impact of the brain burden on the cognition in people with multiple sclerosis (PwMS).Objective: To explore the relationship between CR and structural brain connectivity and investigate their role on cognition in PwMS cognitively impaired (PwMS-CI) and cognitively preserved (PwMS-CP).Methods: In this study, 181 PwMS  were evaluated using the Cognitive Reserve Questionnaire (CRQ), Brief Repeatable Battery of Neuropsychological tests, and MRI. Brain lesion and gray matter volumes were quantified, as was the structural network connectivity. Patients were classified as PwMS-CI (z scores = −1.5 SD in at least two tests) or PwMS-CP. Linear and multiple regression analyses were run to evaluate the association of CRQ and structural connectivity with cognition in each group. Hedges's effect size was used to compute the strength of associations.Results: We found a very low association between CRQ scores and connectivity metrics in PwMS-CP, while in PwMS-CI, this relation was low to moderate. The multiple regression model, adjusted for age, gender, mood, lesion volume, and graph metrics , indicated that the CRQ  was associated with cognition (adj R2 = 0.34) in PwMS-CP (55%). In PwMS-CI, CRQ , age, and network global efficiency were independently associated with cognition (adj R2 = 0.55). The age- and gender-adjusted association between CRQ score and global efficiency on having an impaired cognitive status was −0.338  and −0.531 , respectively.Conclusions: CR seems to have a marginally significant effect on brain structural connectivity, observed in patients with more severe clinical impairment. It protects PwMS from cognitive decline regardless of their cognitive status, yet once cognitive impairment has set in, brain damage and aging are also influencing cognitive performance. Cognitive impairment (CI) has been reported in 40–70% of people with multiple sclerosis (PwMS)  and it hSome individuals better maintain their cognitive performance despite the presence of substantial brain damage. This clinico-pathological dissociation  indicateWe hypothesized that individuals with higher CR would exhibit higher structural connectivity and, consequently, better cognitive performance. Also, the influence of CR on cognitive performance in PwMS may be distinct before and after the emergence of CI. Therefore, we aimed to understand the association between CR and structural connectivity integrity and their impact on cognition in PwMS. For this, we analyzed their role in patients with different cognitive status, thus in PwMS cognitively impaired (PwMS-CI) and in those who remained cognitively preserved (PwMS-CP).A cohort of 181 PwMS (aged 18–65 years) who fulfilled the 2010 McDonald criteria  was consCognition was assessed using the Brief Repeatable Battery of Neuropsychological tests (BRB-N) . This baz scores for all BRB-N tests, using demographically adjusted (age and education) regression models according to the normative data published in the Spanish population (z = −1.5 standard deviations (SD) of the norm in at least two cognitive tests of the same or different cognitive domain. In addition, raw values were transformed into z scores (zBRB) by subtracting the mean and dividing by the SD of the whole sample in order to obtain a mean score of cognitive performance, avoiding the educational effect related to CR and the aging effect on cognition.We first calculated pulation , classifCR was assessed using the Cognitive Reserve Questionnaire (CRQ) , a standMR images were acquired on a 3-Tesla Magnetom Trio  scanner using a 32-channel phased-array head coil. The protocol applied involved a 3D-Magnetization Prepared Rapid Acquisition Gradient Echo (MPRAGE), 3D-T2 fluid-attenuated inversion recovery (FLAIR), and DWI sequences (see http://www.xinapse.com/j-im-7-software/). To improve MS lesion identification, the co-registered 3D-FLAIR image was used as a reference. Thereafter, lesion in-painting was applied to the 3D-MPRAGE image to enhance segmentation and registration in PwMS  that is based on the Desikan-Killiany atlas . WM and lesion masks were registered to the undistorted HARDI images by applying boundary-based registration . Graph metrics were analyzed to express the global connectivity properties of the network, including the nodal strength (the sum of weights connected to the node); measures of segregation, such as the local efficiency (the average of the inverse of the shortest path length in the network computed on node neighborhoods), the clustering coefficient (the fraction of a node's neighbors that are neighbors of each other), and transitivity (the ratio of triangles to triplets in the network); integration, as measured through the global efficiency (the average inverse shortest path length in the whole network); and brain resilience, reflected by assortativity  (Graph theory metrics were computed using the Brain Connectivity Toolbox ( a link) . A repreU-test or a Student's t-test, depending on the data distribution.All demographic, clinical, neuropsychological, MRI markers of brain burden, and connectivity values were described through the mean and SD, and by the absolute numbers and the proportions for quantitative and qualitative data, respectively. The normality of continuous data was checked using histograms and appropriate statistical methods as the Shapiro–Wilks test. We compared the aforementioned characteristics between PwMS-CI and PwMS-CP patients using a Chi-squared test, a Wilcoxon–Mann–Whitney g effect size.Age- and gender-adjusted linear regressions were done to analyze the associations between CRQ and cognition, between structural connectivity and cognition, and between CRQ and structural connectivity on the entire cohort and in each group of PwMS separately. To understand the role of CR and structural connectivity on cognitive performance in the context of other demographic and MS-related factors, we fitted a multiple regression model that included relevant demographic and clinical variables. Variables were standardized using the mean and SD: CRQ score, age, gender, EDSS, HADS score, nLv, nGMv, and graph measures of segregation, integration, and brain resilience . The Akaike Information Criterion (AIC) was then used to select the variables that best fit a model based on the whole cohort. As the main objective of the study was to determine the influence of CR and structural connectivity on cognitive performance in patients with different cognitive status, we applied the same multiple regression model separately in PwMS-CI and PwMS-CP, with the variables selected from the AIC. We computed the strength of the associations using Hedges' Furthermore, an age- and gender-adjusted logistic regression analysis was used to estimate the odds ratio (OR) of having an impaired cognitive performance associated with the increase per unit of the CR and MRI connectivity metrics associated to cognition in the multiple regression model.www.R-project.org), setting the level of significance at p < 0.05 and correcting multiple comparisons for the false discovery rate (FDR).Statistical analyses were performed with R statistical software , middle-aged adults (42.9 ± 10.0 years), and who had a median CRQ score of 16 . In the cohort, 81 patients (45%) were classified as PwMS-CI, and the remaining 100 patients (55%) were considered PwMS-CP. The group of PwMS-CI more frequently presented with a secondary progressive phenotype of the disease, with lower CRQ scores and with higher EDSS scores. They also presented worse volumetric and connectivity measures in images than PwMS-CP, although assortativity was no different (see p < 0.001), in PwMS-CP , and also in PwMS-CI . In parallel, significant associations were also found between graph structural connectivity properties and cognitive scores in the entire cohort and in the PwMS-CI group in all studied graph measures except for assortativity   .p < 0.05). Nodal strength, transitivity, and global efficiency were the metrics showing a moderate effect size in this group . In this group, a one-point increase in the CRQ score was associated with a 0.26-point increase in the zBRB (the only significant variable in the model) . The CRQ showed a moderate association with cognitive performance . In the PwMS-CI, 55% of the variability in the zBRB was explained by the model . In these patients, a one-point increase in the CRQ score was associated with a 0.18-point increase in the zBRB . Moreover, in this model age  and global efficiency  were significantly associated negatively and positively with the zBRB, respectively  was explained by the model (adj ectively . Transitp = 0.036) for CRQ score and −0.531  for global efficiency.We evaluated the predictive value of CRQ and global efficiency on cognitive status. The age- and gender-adjusted association between CRQ score and global efficiency on having an impaired cognitive status was −0.338  Consortium. From 16 April 2019, she works in the European Medicine Agency ; AS received compensation for consulting services and speaker honoraria from Bayer-Schering, Merck-Serono, Biogen-Idec, Sanofi-Aventis, TEVA, Novartis, and Roche. SL received compensation for consulting services and speaker honoraria from Biogen Idec, Novartis, TEVA, Genzyme, Sanofi, and Merck. MA holds equities in Bionure and Goodgut. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.