Idiopathic pulmonary fibrosis (IPF) is a chronic and progressive disease characterized by complex lung pathogenesis affecting approximately three million people worldwide. While the molecular and cellular details of the IPF mechanism is emerging, our current understanding is centered around the lung itself. On the other hand, many human diseases are the products of complex multi-organ interactions. Hence, we postulate that a dysfunctional crosstalk of the lung with other organs plays a causative role in the onset, progression and/or complications of IPF. In this study, we employed a generative computational approach to identify such inter-organ mechanism of IPF. This approach found unexpected molecular relatedness of IPF to neoplasm, diabetes, Alzheimer’s disease, obesity, atherosclerosis, and arteriosclerosis. Furthermore, as a potential mechanism underlying this relatedness, we uncovered a putative molecular crosstalk system across the lung and the liver. In this inter-organ system, a secreted protein, kininogen 1, from hepatocytes in the liver interacts with its receptor, bradykinin receptor B1 in the lung. This ligand–receptor interaction across the liver and the lung leads to the activation of calmodulin pathways in the lung, leading to the activation of interleukin 6 and phosphoenolpyruvate carboxykinase 1 pathway across these organs. Importantly, we retrospectively identified several pre-clinical and clinical evidence supporting this inter-organ mechanism of IPF. In conclusion, such feedforward and feedback loop system across the lung and the liver provides a unique opportunity for the development of the treatment and/or diagnosis of IPF. Furthermore, the result illustrates a generative computational framework for machine-mediated synthesis of mechanisms that facilitates and complements the traditional experimental approaches in biomedical sciences. Both the incidence and poor prognosis of IPF increase with age4. Specifically, the median age of the newly diagnosed is 62 years-old and their prognosis is poor—3–5 years of survival rate.Idiopathic pulmonary fibrosis (IPF) is a chronic disease characterized by scarring in the interstitium of the lung, affecting 3–9 and 4 or less per 100,000 person-years in North America/Europe and South America/East-Asia, respectively2. Nintedanib is a tyrosine kinase inhibitor. Pirfenidone is an inhibitor of transforming growth factor (TGF)-beta production and downstream signaling, collagen synthesis and fibroblast proliferation. Hence, these drugs are regarded as pleiotropic anti-fibrosis drugs. Currently there are no IPF-specific therapeutics. Furthermore, the precise IPF diagnosis requires complex and multiple-types of tests as its overlapping pathologies with other interstitial lung fibrosis diseases2. These are in part due to the complexity of the IPF pathogenesis and to its ill-defined cellular and molecular mechanisms.There are two Food and Drug Administration (FDA)-approved drugs for the treatment of IPF: nintedanib and pirfenidone6. The increasing molecular and cellular evidence suggests IPF is driven by an activation of the lung epithelium. In this model, the ectopic activation of the alveolar epithelial cells results in the production of chemokines, growth factors, and extracellular matrix proteins, promoting the migration, growth, and/or differentiation of fibroblasts, and macrophages and other immune cells. Furthermore, various life-style and environmental factors, and also genetic factors are reported to influence the onset, progression, and/or mortality.While IPF was classically considered an inflammatory disease, a new picture is emerging11. The immune responses occur in a variety of diseases such as metabolic, neoplastic, cardiovascular diseases and also in aging14. The causative roles of gut microbiota are becoming recognized in an increasing number of diseases15. The nervous system influences metabolic states and vice versa16. Metabolic dysregulation is a risk factor for many diseases and they also accelerate aging influencing the longevity17. Exosomes are another type of systemic factors that are associated with many types of diseases18. The interactions of immune cells and lung cells are involved in the pathogenesis of IPF6. Furthermore, life-style and aging are critical influencers of IPF5. Hence, it is conceivable that the inter-organ crosstalk mediated by the immune cells, systemic factors, and/or neural system could be involved in the onset, progression, and/or complications of IPF. However, very little is studied on these possibilities.While the clinical translation of these recent advancements in understanding the IPF mechanism within the lung tissue is expected, the onset and progression of human diseases involve multiple organs -i.e., the inter-organ mechanismBased on this background, we postulate that the cross-talk between the lung and the non-lung organs is a part of the mechanism in the onset and/or progression of IPF. The obvious choice of the approach to test this hypothesis is to examine molecular and cellular changes in non-lung organs that accompany, precede, or follow the pathological changes of the lung in IPF. However, this approach would be difficult as the availability of non-lung tissues from the IPF patients is limited, if any.27. Such data space, together with computational methods, could allow us to deduce what occurs in the non-lung organs of IPF-patients and to simulate how they are regulated.The availability of multi-modal omics data of multiple organs and diseases is growing in the public space28.Hence, we reasoned that such a large set of multi-modal omics data across many organs and diseases in the human body provides an uncharted biomedical space where an organ-to-organ interaction that causes and/or exacerbates IPF is embedded. To uncover such a latent inter-organ mechanism of IPF, we employ a generative computational approach ”)—a computational method that can produce various types of contents such as sentences, images, molecular structures, working-hypotheses(models), etc.To detect mechanistic relatedness of IPF to non-respiratory/non-pulmonary diseases.To identify molecular features that characterize the relatedness detected in 1.To identify ligand–receptor relationships across multiple organs that are linked to the features identified in 2.To generate a map of the inter-organ mechanism of IPF with molecular and cellular resolution that explains the findings of 1–3.Towards this goal, we designed a generative computational approach as follows:29. The overall design is summarized in Fig. The molecular relatedness of IPF to non-respiratory/non-pulmonary diseases were identified by using the multi-modal generative topic modeling method that we developed and previously reported27. “Ae” is the list of genes and proteins of which changes in expressions are associated with a corresponding disease(s). “Bm” is the list of biomarkers which are described for a corresponding disease(s). “Gv” is the list of genes of which mutations are reported for a corresponding disease(s). Dataset B consists of three types of IPF modality combination, each consisting of Bm/Gv , Gv/Ae , or Ae/Bm , also from DisGeNET v7.027. The multi-modal generative topic modeling generates  the features of the missing modalities. The performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC) values as previously described29 and they were found to be above 0.8 for all three modalities . The remaining features are now designated as “latent disease-omics features of IPF ”. Moreover, IPF and the diseases from which these IPF-features are derived in Dataset A establish “latent relatedness of IPF to other diseases”.Two datasets are used for the multi-modal generative topic modeling: Datasets A and B. Dataset A consists of 6,954 human diseases excluding IPF, each of which is characterized by three disease omics modalities, AlteredExpression (Ae), Biomarker (Bm), and GeneticVariation (Gv), derived from DisGeNET v7.025  of the 83 latent IPF-features to identify non-pulmonary/non-respiratory diseases to which IPF is related Fig.  see als” sectionA putative inter-organ mechanism was computationally generated as described in Fig. Step 1: To identify the ligands in the lung differentially expressed genes (DEgenes)  lung disease patients  in the 112 IPF-DEgenes  , forming 13 ligand–receptor pairs   Table .Table 2TStep 4: To identify the ligands for the receptors in 3 , forming 17 ligand–receptor pairs  (Table Step 5: To identify downstream and upstream targets of the ligand–receptor pairs found in Steps 2 and 4 by Kyoto encyclopedia genes and genomes (KEGG) pathway analysis and to select those that are among the 83 latent IPF-features identified by the multi-modal generative toping modeling.We searched for the downstream and upstream signaling targets for these ligand–receptor pairs by the KEGG-mining see “” sectionFor the 17 ligand (non-lung)–receptor (lung) pairs –BDKRB1 (the lung) and IL6 (the lung)–IL6R/IL6ST (the liver), that could establish the lung-liver inter-organ mechanism. The expression of KNG1, the ligand for BDKRB1, is most enriched in hepatocytes, with lesser expression in the endothelial cells, fibroblasts, intrahepatic cholangiocytes, and T cells. The expression of IL6R/IL6ST, the receptor complex for IL6, is enriched in the endothelial cells of the hepatic sinusoid, intrahepatic cholangiocytes, and hepatocytes.On the basis of this rationale, we examined the expression patterns of the non-lung components of the ligand–receptor pairs in the liver Fig. . The anaTabula Sapiens was performed. The result shows that the enrichment of IL6 expression in adventitial cells, endothelial cells, fibroblasts, mesothelial cells, respiratory mucous cells, and smooth muscle cells .30. In this article, rhodopsin guanine nucleotide exchange factors (RhoGEF) mediated epithelial cell transformation (ECT) 2 of AT2 cells in the lung could be a common mechanism between IPF and the lung cancer. Our topic modeling study shows the relatedness of IPF to diverse types of cancer , systemic lupus erythematosus, and multiple sclerosis Fig. . A possi34. Our computational study also indicates molecular relatedness of IPF to diabetes  and/or IL6-IL6R (a receptor for IL6) interactions could bring a therapeutic benefit to IPF. In this regard, it is worth noting that the blocking IL-6 is shown to attenuate pulmonary fibrosis in mice42. In these other studies, the IL6 inhibitory effects in IPF patients are discussed only in the context of heterologous cell–cell crosstalk within the lung tissue. However, as the IL6R is also present in hepatocytes, hepatic endothelial cells, and intrahepatic cholangiocytes  in their lung tissues. However, the proposed therapeutic mechanism is the blocking of the intra-pulmonary interactions of sIL-6Rα and IL6. Furthermore, possible roles of interleukins in the pathogenesis of pulmonary fibrosis including IPF are recently discussedtes Fig. , such IL43. This pre-clinical evidence supports our proposed mechanistic model.In our inter-organ mechanism, we also propose that the calmodulin pathway (CALM1/CALM2/CALM3) is activated by the liver-derived KNG1 interaction with the lung BDKRB1, which then induces the IL6 pathway Fig. . It is s44. This study suggests that a part of the therapeutic effect of nintedanib on IPF is via the inhibition of the PCK1 pathway.The other signaling node in our inter-organ mechanism is PCK1 Fig. . In our trans across different cell-types within the same organ.There are two pending questions in the proposed inter-organ mechanism of IPF. The ligands, receptors, and their signaling targets in this model are co-expressed in multiple cell types in their corresponding organs Fig. . Hence, Another question is whether the IL6–IL6R/IL6ST signal feeds back to KNG1 via PCK1 Fig. . While tThese questions remain for the future studies and their results provide more detailed mechanistic description of IPF. Furthermore, they facilitate the designing of first-in-class therapeutic and/or diagnostic strategies for IPF.In this study, we exploited a growing body of multi-modal disease-omics data and a generative computational power to predict an inter-organ mechanism of IPF with the molecular and cellular resolution. Furthermore, our retrospective reference-mining found multiple experimental and clinical evidence in support of the predicted mechanism as described above. Our proposed mechanism is detailed enough, providing a unique opportunity to design hypothesis-driven pre-clinical experiments and/or clinical studies to discover and evaluate first-in-class therapeutic and diagnostic targets for IPF. In addition, our study and results illustrate a computational framework to generate experimentally-testable mechanistic models for other diseases where very little mechanism is known.29. This topic modeling approach exploits the similarities among diseases on the basis of their multi-modal omics features. In this study, we deleted IPF disease-omics data to identify latent IPF-features /cell(s), and performed chi-square test of independence by using the contingency table.The organs and cells where the IPF-features are expressed were identified by organ/cell enrichment analyses using THE HUMAN PROTEIN ATLAS v 21.129. Briefly, the disease-labels of each latent IPF-feature were identified in the Dataset A  and of National Institutes of Biomedical Innovation, Health and Nutrition (Approved Number: 187) and of Kanagawa Cardiovascular and Respiratory Center (Approved Number: KCRC-19-0015). The informed consent was obtained from all subjects. All methods were performed in accordance with the relevant guidelines and regulations. The lung tissues were collected from 299 subjects. They consist of 173 idiopathic interstitial pneumonias (IIPs), 76 hypersensitivity pneumonitis (HP), 26 connective tissue diseases (CTD), 24 others . The 173 IIPs are further composed of 95 IPF, 41 unclassifiable interstitial pneumonia (UCIP), 28 idiopathic nonspecific interstitial pneumonia (NSIP), 3 idiopathic pleuroparenchymal fibroelastosis (PPFE), and 6 other IIPs. RNA was purified from each sample and processed for RNA sequencing as follows: The lung tissues were sent to TAKARA BIO INC.  for sequencing. At TAKARA BIO INC., a total RNA was purified using NucleoSpin®RNA according to the provided protocol. Before RNA-sequencing, the total RNA for each specimen was checked for quality using Agilent 2000 TapeStation . The RNA Integrity Numbers (RINs) for all the specimens, as obtained by TapeStation, passed a score of 6.0 or greater. Upon this quality check, mRNA sequencing was performed using the Illumina Sequencer NovaSeq6000 with paired end reads of 150 bps. Read sequences obtained were mapped to genome sequences. Based on the positional information obtained from the mapping and the gene definition file, the gene units were mapped to the genome sequence. The expression level of each gene and transcript was calculated based on the positional information obtained by mapping and the gene definition file and an annotation information was added. The differentially expressed genes (DEgenes) in the lung tissues of IPF vs. all the other pulmonary diseases , HP, CTD, other interstitial lung diseases (labeled as “Others” in the raw count data) were detected by using an R package, 46. Furthermore, we identified their corresponding receptor and ligand partners using the same database.From the IPF-DEgenes, those encoding ligand proteins or receptor proteins were identified using a human ligand–receptor combination database, CellChatDBThe overall design of the approach is described in Fig. Tabula Sapiens, which is a database of multiple healthy tissues22, and (2) GSE122960, which is a scRNA-seq dataset of the lung tissues of IPF patients/healthy donors47. For the Tabula Sapiens, the raw count data and the cell type annotation table were extracted using a Python package, scanpy48, from the h5ad-formatted data at their FigShare deposit49. For the GSE122960, the raw count data were obtained from the Gene Expression Omnibus (GEO) deposit. However, the cell type annotation table for GSE122960 was not available. Therefore, we reproduced the cell type annotation from the downloaded count data using publicly available R program codes (https://github.com/NUPulmonary/Reyfman2018/tree/master)47, which accompany the GSE122960 study. These codes were run in the Seurat package (v2.3.4)50 as follows: (1) Cell quality control filtration by the number of genes and the percent of mitochondrial RNA; (2) Log-normalization with the scale factor 10,000; (3) Dection of highly variable genes; (4) Scaling for all genes; (5) Principal component analysis (PCA) and the elbow plot to determine the PCs used for the downstream analyses; (6) Cell clustering and the cell type determination by the marker genes. The parameter settings at each step and the cell type annotation were performed according to the obtained codes per each sample data. The DEgenes in each cell type of the lung derived from the IPF patients were determined by comparing the scRNA-seq data of the lung tissues derived from the IPF patients and the healthy-donors by DESeq245 following the developers’ recommendations for single-cell analysis51. Briefly, we first set size-factors by ‘computeSumFactors’ in the scran package52. The DESeq2 was performed by using the likelihood ratio test as significance testing, where we set the ‘DESeq’ arguments to the following values: test = ‘LRT’, useT = TRUE, minmu = 1e−6, minReplicateForReplace = Inf. The genes were evaluated by the statistical significance level at 0.05 in adjusted p-value.The single-cell gene expression across multiple healthy organs and that of the lung tissues of IPF patients were determined using two publicly available human single-cell RNA sequencing (scRNA-seq) datasets: (1) The KEGG-mining (steps 5 and 6 in the flow) was conducted as follows:clusterProfiler53, and then to KEGG IDs from the Entrez IDs using KEGG API54. Next the KEGG pathways containing these KEGG IDs were extracted and their directed graphs were constructed using KGML55. In the graphs, each node was the attribute ‘name’ of the tag <entry>, and each edge started at the node corresponding to the attribute ‘entry1’ of the tag <relation> and ended at the node corresponding to the attribute ‘entry2’ of the same tag <relation>. Using these graphs, we identified the direct and indirect connections between the ligands/receptor and the latent IPF-features.The KEGG-mining was performed to identify downstream and upstream targets of the ligand–receptor pairs and to determine which of the targets are the IPF-features. First, the gene symbols were converted into KEGG IDs, by first to Entrez IDs using the R function ‘bitr’ of the R package The studies with human subjects and data were approved by the Institutional Review Board of Advanced Telecommunications Research Institute International on behalf of Karydo TherapeutiX, Inc.  and of National Institutes of Biomedical Innovation, Health and Nutrition (Approved Number: 187) and of Kanagawa Cardiovascular and Respiratory Center (Approved Number: KCRC-19-0015).Supplementary Information 1.Supplementary Table S1.Supplementary Table S2.Supplementary Table S3.Supplementary Table S4.Supplementary Table S5.Supplementary Table S6.Supplementary Table S7.


Drosophila melanogaster model, we report gain-of-function phenotypes due to misexpression of insect codon-optimized version of human wild-type TDP-43 (CO-TDP-43) using both the binary GAL4/UAS system and direct promoter fusion constructs. The CO-TDP-43 model showed robust tissue specific phenotypes in the adult eye, wing, and bristles in the notum. Compared to non-codon optimized transgenic flies, the CO-TDP-43 flies produced increased amount of high molecular weight protein, exhibited pathogenic phenotypes, and showed cytoplasmic aggregation with both nuclear and cytoplasmic expression of TDP-43. Further characterization of the adult retina showed a disruption in the morphology and function of the photoreceptor neurons with the presence of acidic vacuoles that are characteristic of autophagy. Based on our observations, we propose that TDP-43 has the propensity to form toxic protein aggregates via a gain-of-function mechanism, and such toxic overload leads to activation of protein degradation pathways such as autophagy. The novel codon optimized TDP-43 model is an excellent resource that could be used in genetic screens to identify and better understand the exact disease mechanism of TDP-43 proteinopathies and find potential therapeutic targets.Transactive response DNA binding protein-43 (TDP-43) is known to mediate neurodegeneration associated with amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD). The exact mechanism by which TDP-43 exerts toxicity in the brains, spinal cord, and lower motor neurons of affected patients remains unclear. In a novel  TARDBP gene in the human genome, has been identified as a major component for the pathology of motor neuron diseases and related neurodegenerative diseases , encoded by diseases . TDP-43 diseases . In the diseases . Mutatiof TDP-43 , and havf TDP-43 . Proteinf TDP-43 . In addif TDP-43 . In ordef TDP-43 .Drosophila melanogaster has been widely utilized to study neurodegenerative diseases in an in vivo model system  defects, and decreased dendritic branching of DA neurons  was added upstream of the start codon for the TDP43 gene. These constructs were subcloned into the Not1-Xba1 site of the modified fly upstream activation sequence (UAS) expression (pEx-UAS) and glass (pEx-gl) vectors . The expression vectors containing the CO-TDP-43 gene were then microinjected into the flies to obtain transgenic flies . We generated multiple transgenic fly lines as noted in UAS-TDP-43_6 line for our subsequent experiments with various GAL4 lines and the gl-CO-TDP-43_4 line for subsequent experiments using the eye as a model. The expression of non-CO-TDP-43 is driven in the fly eye by the glass multimer reporter, GMR-GAL4 on the X-chromosome  (SevEP-GAL4 driver (expressed in R7 and R8 photoreceptor neurons) was recombined with UAS-TDP-43CO to obtain stable transgenic flies expressing w1118;SevEP-GAL4,UAS-TDP-43CO/CyO; +. The GMR-GAL4 on the X-chromosome was placed in trans to the gl-TDP-43CO line to generate GMR-GAL4;gl-TDP-43CO/CyO transgenic flies. The following stocks were obtained from Bloomington Drosophila Stock Center : w1118;UAS-LacZ (BDSC 3955), w1118,GMR-myr-mRFP (BDSC 7121), y1,w1118;Sp/CyO; eGFP-ATG5 (recombined from BDSC 59848), y1,w1118;UAS-GFP-mCherry-ATG8 (BDSC 37749), GMR-GAL4(X) (eye specific) (BDSC 79572), w1118;SevEP-GAL4 (R7 and R8 in photoreceptor cells) (BDSC 5793), w1118,beadexMS1096-GAL4 (wing driver) (BDSC 8860), w1118;Scabrous-GAL4 (sensory organ precursor and wing discs driver) (BDSC 6479), and y1,w*; CCAP-GAL4  (BDSC 25685). Eq-GAL4 (bristle driver) and y1,w1118;Rh1-GAL4/CyO (expressed in R1-R6 photoreceptor cells) were obtained from Dr. Hugo J. Bellen . All crosses were set and flies were maintained at room temperature (22°C) in standard D. melanogaster Jazzmix medium .Codon optimized TDP-43 gene was synthesized from DNA2.0 . The complete sequence of the codon optimized TDP-43 is provided in the romosome . All traAmerica) . SevEP-GAdult retina and imaginal eye discs from third instar larvae were dissected and fixed in 4% paraformaldehyde for 1 h on ice. Adult retina was washed in 0.5% PTX for 3 h to reduce autofluorescence. The tissues were blocked in 0.8% PBS + Triton-X + BSA for 2 h and incubated with primary antibody overnight at 4°C. The tissues were incubated in secondary antibody for 2 h at room temperature, washed in 0.1% PBS + Triton-X and mounted on glass slides with Vectashield . Tissues were stained with the following antibodies: mouse monoclonal anti-TDP-43 antibody , rabbit polyclonal anti-TDP-43 antibody , rat monoclonal anti-Elav , mouse monoclonal anti-GFP , Alexa Fluor 633-conjugated Phalloidin , Alexa Fluor 488 conjugated chicken anti-rat  Alexa Fluor 568 conjugated goat anti-rabbit  and Alexa Fluor 568 conjugated goat anti-mouse .Overexpression of CO-TDP-43 in the fly eye was used to measure total protein levels by immunoblotting. Approximately 50 fly heads were decapitated and homogenized for 1 min in homogenization buffer  along with 1X PhosSTOP phosphatase and 1X cOmplete protease buffer . The homogenized samples were centrifuged at 4 °C for 15 min at 18,000 g. The supernatant was collected and equal parts of the supernatant and Laemmle sample loading buffer with β-mercaptoethanol  was added for each sample. Following a brief pulse centrifugation, samples were loaded on 4%–20% SDS-PAGE gels  for electrophoresis. For higher molecular weight species detection, the fly heads were homogenized in 1X PBS along with the same protease and phosphatase inhibitors. Non-reducing sample loading buffer  was added to the supernatant without β-mercaptoethanol. The blots were blocked in 5% milk, incubated with primary antibodies overnight at 4 °C, washed in 1X TBS + Tween, and incubated with secondary antibody for 1 h at room temperature. The following antibodies were used: Mouse monoclonal anti-TDP-43 antibody , Rabbit Polyclonal anti-TDP43 antibody , Rabbit monoclonal anti-Phospho-TDP43 , Mouse monoclonal anti-tubulin antibody , Mouse monoclonal anti-beta Actin antibody , secondary anti-mouse IgG-HRP , and anti-rabbit IgG-HRP .For Lysotracker staining, imaginal eye discs from the third instar larvae were dissected in 1X PBS solution without fixative. The eye discs were then stained with 100 nM LysoTracker Red DND-99 (Invitrogen) for 2 min, followed by a 1-min wash in 1X PBS. The tissues were mounted on a glass slide with a drop of 1X PBS solution; no Vectashield was added. The coverslip was sealed with nail polish and visualized immediately using a confocal microscope. The z-stack images were analyzed using the ImageJ software .ERG was recorded in 1-day old flies using the same methods as previously described . BrieflyThe adult eye, wing and bristle pictures were taken with a Nikon AZ100 M microscope equipped with a Nikon DS-Fi1 digital camera . Extended depth of focus (EDF) and volumetric images were taken using the Nikon NIS-Elements AR 3.0 software as previously described . The scat-test was performed between the Control vs non-CO-TDP-43 vs CO-TDP-43 eyes for statistical analysis. Western Blot data comparing non-CO-TDP-43 and CO-TDP-43 was estimated by paired t-test. The histograms represent mean ± SEM and are analyzed using Graphpad prism software. Quantification of Lysotracker staining was performed using the NIH Image J software  promoter direct fusion construct specifically generated to study TDP-43 mediated effects on the fly retina (Sevenless (SevEP-GAL4), that only expresses in a subset of photoreceptor neurons (R7 and R8) and cone cells  driver leads to loss of bristles in the adult fly , sca-GAL4, equate-GAL4 (eq-GAL4), and CCAP-GAL4. We found that non-CO-TDP-43 transgene expressed using bxMS1096-GAL4 led to viable adults with shriveled wings, with some flies having wings that were either necrotic or had areas of hyperpigmentation  compared to non-CO-TDP-43 flies  recordings to measure the functionality of active photoreceptor neurons by measuring their response to light stimulus . In factecording . Using tcontrols . The gl-eclosion . These eAn autophagic dysfunction has been implicated in many neurodegenerative diseases, including ALS . TherefoTo further characterize the large vacuoles, we coexpressed CO-TDP-43 and a tagged autophagy protein, Atg5-GFP, which is responsible for the formation of the autophagosomes. We found that these vacuoles were positive for both Atg5 and TDP-43 . During D. melanogaster resource to better understand TDP-43 mediated neurodegeneration. There is great potential for the codon optimized TDP-43 model, as it exhibits robust and sensitive phenotypes ideal for genetic manipulations that allow us to understand its pathogenic mechanisms in an in vivo system. Our results suggest that this model has important utility in understanding the TDP-43 mediated pathology in neurodegenerative disorders.To date, little is known about the exact mechanism of action of TDP-43 mediated toxicity. Here, we report a novel transgenic Previous studies using wild-type TDP-43 fly models helped us understand how the misfolded proteins contributed to neurotoxicity and eventual neurodegeneration . HoweverDrosophila eye can be diverse. For example, in a polyglutamine-expanded human huntingtin transgenic model, the expanded huntingtin protein was shown to form nuclear inclusions and cause severe degeneration of photoreceptor cells (gl-CO-TDP-43 line compared to SevEP-GAL4 driven CO-TDP-43. This is perhaps not surprising considering that SevEP-GAL4 is expressed only in a subset of photoreceptor neurons. Based on our observations using a wide array of eye-specific drivers, we find that TDP-43 pathology is not restricted to photoreceptor neurons but is most likely widespread among different cell types in the Drosophila retina. In fact, TDP-43 is known to be present and shows disease-related pathology across different types of cells both in humans and in animal models (Drosophila model of TDP-43 has been shown to exhibit individual responses in motor neurons and glial cells (In addition, our CO-TDP-43 transgenic model affected multiple different cell types in the fly retina, as evident by depigmentation of pigment cells, irregularities in interommatidial bristle cells, disruption in rhabdomeres morphology, disruption of photoreceptor neuron morphology, and necrosis of the cone cells. The effects of neurodegenerative proteins on the or cells . Furtheror cells . It is wl models . Moreoveal cells . The CO-There is growing evidence of increased levels of TDP-43 protein in the plasma of patients with ALS . More reProtein misfolding is one of the salient features of neurodegenerative diseases. Hyperphosphorylated and aggregated forms of Tau protein are found in the brains of patients with Alzheimer’s Disease . Similarin vitro studies have shown disease-specific mutant or truncated TDP-43 can form toxic aggregates of oligomeric species, very few studies in wild-type TDP-43 animal models have demonstrated a similar robust production of TDP-43 aggregates (CO-TDP-43 induced neurotoxicity was validated by the electrophysiological readouts in our study, which showed that toxic aggregates of wild-type TDP-43 reduced functional activity in photoreceptor neurons in the adult eye. The cytoplasmic mislocalization and presence of toxic TDP-43 aggregates have been well characterized in human patient samples of ALS/FTLD . While igregates . Our stugregates . Previougregates . In keepLastly, in our CO-TDP-43 model, we observed an increase in acidic vacuoles, as evident by lysotracker staining, that are positive for autophagic proteins ATG5 and ATG8 known to be involved in the formation of early and late stage autophagosomes. At this stage our data is too preliminary to infer whether these vacuoles imply an autophagic induction to clear misfolded TDP-43 aggregates or a complete blockage of this process. Autophagic impairment is a common feature of many neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, Huntngton’s disease, and ALS . In patiDrosophila Tauopathy models have shown that misexpression of Tau leads to severe autophagic dysfunction by decreasing lysosomal acidification (All of this evidence strongly suggests that misfolded TDP-43 aggregates might play a role in impairing autophagic processes thereby causing more toxic aggregates to accumulate. Interestingly, our previous studies in fication . FurtherDrosophila TBPH on the codon-optimized human TDP-43 needs to be examined. Several studies have shown that the knock-down of TBPH in fruit flies causes locomotor deficits. The compensation of misexpressed codon-optimized human TDP-43 by endogenous TBPH remains an interesting area of study for a comprehensive understanding of the pathways leading to neurodegeneration. The locomotor and longevity assays following the pan-neuronal expression of CO-TDP-43 is another important area that needs substantial research to open new vistas for developing future therapeutics. Despite these limitations, our codon-optimized model displaying a robust neurodegenerative phenotype compared to the non-codon-optimized transgenics is a promising start. In this study, we have shown that unlike other fly models that rely on pathogenic mutations, CO-TDP-43 model recapitulates many of the known phenotypes of TDP-43 proteinopathies observed in humans.However, our model has a few limitations. A significant aspect to consider for future studies is whether the intrinsic structure and stability of the TDP-43 protein changes due to codon-optimization. There are numerous reports that phosphorylation of TDP-43 results in its mislocalization in the cytoplasm, thus hindering its ability to shuttle back to the nucleus and bind to nucleic acids . Interesin vivo platform to characterize and validate some of these modifiers to better understand the TDP-43-dependent disease mechanism in ALS/FTLD. In conclusion, the robust phenotypes observed in the external organs of the eye, wing, and notum of these flies can be scored easily, offering an excellent model for high-throughput screens of modifiers genes that will help elucidate the molecular mechanism of toxicity due to TDP-43. Targeted genetic screens that identify effectors of TDP-43 will allow us to further identify and pursue novel mechanisms for disease pathology.Furthermore, TDP-43 is an RNA-binding protein that is involved with RNA metabolism and regulation. As a result, much effort has been devoted to identifying the RNA targets of TDP-43 using cell culture models, animal models, and ALS and FTLD patient brain samples. Recently, TDP-43 was shown to bind approximately 30% of the mouse transcriptome, identifying a vast number of possible interactors that can associate with TDP-43 to regulate RNA processing and splicing . Many of


Eucommia ulmoides polysaccharide (EUP), modified SeNP to get EUP-SeNP with a size of about 170 nm, and its effect on 3% dextran sulphate sodium (DSS) induced colitis was explored. Our results showed that colon intestinal histology, intestinal mucosal barrier, inflammatory cytokines and intestinal microbiome composition were changed after EUP-SeNP treatment in colitis mice. Specifically, it was also shown that oral treatment of EUP-SeNP could relieve the degree of DSS-induced colitis in mice by restoring weight loss, reducing disease activity index (DAI), enhancing colon antioxidant capacity and regulating intestinal microbiome composition. In addition, we verified the mechanism in intestinal epithelial cell lines, showing that EUP-SeNP inhibited LPS-induced activation of the TRL-4/NF-κB signaling pathway in intestinal epithelial cell lines. To some extend, our study provides therapeutic reference for the treatment of IBD.Ulcerative colitis (UC) is currently the most common inflammatory bowel disease (IBD). Due to its diverse and complex causes, there is no cure at present, and researchers are constantly exploring new therapies. In recent years, nano-selenium particle(SeNP) has attracted wide attention due to excellent biological activities. Therefore, in this study, for the first time, we used a natural polysaccharide,  Ulcerative colitis (UC) is a chronic, non-specific inflammation of the colon and rectum, mainly manifested as pathological intestinal mucosal injury, ulceration, contraction of the intestine, diarrhea, blood in the stool , 2. It iSelenium(Se), an essential trace element, was thought to be toxic when it was first discovered, and its biological role was gradually discovered . It has In addation, NF-κB is usually related to inflammatory and in the cytoplasm it is inactive but phosphorylated in response to extracellular factor stimulation. Phosphorylated NF-κB can enter the nucleus to bind to target genes and regulate transcription . TLR-4 iIn this study, we used EUP as a surface modifier to modify SeNP to obtain a stable SeNP with anti-inflammatory and antioxidant functions, and then explored its effect on DSS-induced colitis. Finally, we investigated the effect of EUP-SeNP on the LPS-activated TRL-4/NF-κB signaling pathway in intestinal epithelial cell lines so as to provide a reference for the treatment of UC.Eucommia ulmoides polysaccharide   was added to stir for 12 h to obtain EUP-SeNP solution. Excess sodium selite and ascorbate were subsequently removed by dialysis with Mili-Q water in regenerated cellulose tubes  until the Se regenerated cellulose tubes were undetectable by inductively coupled plasma emission spectrometry (ICP-OES) in external solution. After dialysis, some of the reaction products were lyophilized. The remaining liquid is stored at 4 ℃.SeNP was prepared by reacting sodium selenite  with ascorbic acid  in a certain proportion. In brief, 10 mL sodium selenite (20 mM) was added to 10 mL ascorbic acid (80 mM) for mixing and stirring for 1 h under dark environment, and then The Se content in EUP-SeNP was quantitated by ICP-OES on an ICP spectrometer at a specific wavelength of 196.08 nm. The Fourier transform infrared (FTIR) spectra of EUP and SeNP and EUP-SeNP were determined. Briefly, 5 mg of each sample was uniformly mixed with dry KBr solid powder. The powder was sufficiently ground with a mortar and pressed by a vacuum tablet machine. The infrared absorption spectra of these samples were determined on a Nicolet 6700 FTIR (Thermoelectric (Shanghai) Technology Instrument Company, China). The EUP-SeNP were characterized by transmission electron microscope and the energy dispersive X ray spectrometer (TEM-EDX) . A small amount of the sample was placed on the membrane surface of the copper mesh used for electron microscopy. Then, the copper mesh was dried naturally in the oven to avoid the contamination of dust and other impurities. The dried copper mesh was observed with a TEM, and the elemental composition of the composite particles in the target area was observed using a spot sweep method together with an EDX. Particle size was determined by Zetasizer Nano ZS . Vitro antioxidant capacity was evaluated using 1,1-diphenyl-2-picrylhydrazyl(DDPH), hydroxyl radical(·OH), and 2, 2’-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid)(ABTS) free radical scavenging kit. A total of 60 6–8 week old male C57BL/6JNifdc mice (20-21 g) were purchased from Vital River Laboratory Animal Technology Company . All animals were raised in a controlled environment: relative humidity was 40 ± 10% and temperature was 20 ± 5 ℃, with a 12/12 h light–dark cycle. After 1 week of adaptation, the mice were randomly divided into 6 groups, namely control group, 3%DSS group, 3%DSS + EUP group, 3%DSS + SeNP group, 3%DSS + EUP-SeNP group and 3%DSS + selenite group, each with 10 mice. Except the control group, the other groups were given 3% w/v DSS drinking water for 7 consecutive days, and the control group was given drinking water without DSS. From the 8th day, in the treatment group, 200 µL of the drug was intragastric for 5 days, and the selenium content in the EUP-SeNP treatment group was 0.5 ppm. The control group and DSS group were given the same amount of PBS. Body weight and disease activity index (DAI) scores of mice in each group were observed and recorded daily. The length of the colon was measured when the mice were sacrificed. All animal procedures were approved by the China Agricultural University Institutional Animal Care and Use Committee (AW80212202-2-1).After administration of DSS drinking water, the disease activity index score was recorded every day. The DAI score is a composite score of weight change, stool consistency and stool bleeding. Colon tissues were removed and fixed with 4% paraformaldehyde. The colons were cut into 5 μm sections and stained with hematoxylin & eosin (H&E) and Alcian blue-periodic acid-Schiff (AB-PAS) according to standard procedures.  Histopathological score is a comprehensive measure of inflammatory cell infiltration and changes in tissue damage. The changes in goblet cells in colon tissue were observed by AB-PAS staining. Detailed scoring criteria for DAI and histology are based on previous articles , 29.Proteins were extracted from colon tissues with physiological saline, then detected with a BCA protein analysis kit . IL-6, IL-10, IL-12, IL-17, IL-1β, TNF-ɑ , were determined by an ELISA kit. The results were normalized to the protein concentration of each sample. A microplate reader  was used for detection at 450 nm. Indicators of intestinal antioxidant capacity: Total antioxidant capacity (T-AOC), Superoxide Dismutase (SOD), Catalase (CAT), glutathione peroxidase(GPX), Malondialdehyde(MDA), Glutathione/oxidized Glutathione(GSH/GSSG), myeloperoxidase(MPO) levels were determined by using commercial kits according to the manufacturer’s instructions .Proteins extracted from the colon tissue were separated by 8–12% SDS-PAGE after the concentration was detected by the BCA protein assay kit . They were then transferred to 0.2 μm polyvinylidene fluoride membranes . Membranes were blocked with 5% skim milk for 1.5 h. After blocking, the membranes were incubated with different primary antibodies at 4 ℃ overnight. Claudin 1 , Claudin 3 , Occludin , ZO-1 , TRL-4, IKB, p65, p-IKB, pp65, β-actin. Then, the membranes were washed with Trisbuffered saline Tween (TBST) and then incubated with horseradish peroxidase-conjugated goat anti-mouse IgG, or goat anti-rabbit IgG  for 1.5 h. The membranes were imaged with a Tanon 5200 imaging system. Colon tissue sections were dewaxed with xylene and hydrated in gradient ethanol. Then, the antigen was repaired with 0.01 M sodium citrate buffer. Tissue sections were washed with phosphate buffer  3 times for 5 min each time. Endogenous peroxidase activity was blocked by 3% hydrogen peroxide for 30 min, and non-specific staining was blocked by 5% goat serum for 30 min. Tissue sections were incubated with Ki67 antibody (1/200) and anti-MUC2  at 4 ℃ overnight. On the 2 day, after being washed with PBS, they were incubated with biotin-conjugated goat anti-rabbit IgG  for 2 h and then incubated with horseradish peroxidase (HRP)-streptavidin  for 2 h. DAB chromogenic reagent kit  was used for chromogenic reagent detection. Hematoxylin was used for nuclear re-staining. The primary antibody of the negative control group was replaced with PBS. Images were captured using a microscope .Through the one step TUNEL apoptosis assay kit , terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) assay was used to detect the apoptotic level of colon, IEC-6 and Caco-2. The images were taken with upright DP72 microscope. The contents of the mouse colon were collected and stored in liquid nitrogen. An MN Nucleo Spin 96 Soi DNA extraction kit  was used to extract total bacterial DNA from the sample. The primers were designed according to the conserved region of micro-organism V3 + V4. The primers were used for PCR amplification, and the products were purified, quantified and homogenized to form a sequencing library. The constructed library was first subjected to quality inspection, and the qualified library was sequenced with Novaseq 6000 . Sequence similarity greater than 97% was classified as an operational taxonomic unit (OTU). The OTU composition of different samples was analyzed using principal component analysis (PCA), principal coordinates analysis (PCoA) and non-metric multidimensional scaling (NMDS) based on Bray Curtis analysis. Line discriminant analysis (LDA) effect size, also known as LEfSe, was used to analyze the significance of differences between groups from the phylum to genus level. LEfSe analysis required an LDA score > 4.We evaluated short-term and long-term toxicity by orally administering EUP-SeNP to mice for 7 days and 30 days, respectively, and then detected Aspartate transaminase (AST) and Alanine transaminase (ALT) of serum.  Finally, H&E staining was performed on heart, liver, spleen, lung, kidney and colon.IEC-6 and Caco-2 were cultured in DMEM medium supplemented with 10% FBS, 100 U/mL of penicillin, and 100 µg/mL of streptomycin at 37 °C with 5% CO2 in a humidified atmosphere. Cells were incubated with 50 µg/mL LPS for 36 h, and EUP-SeNP was incubated with 10 µg/mL, 20 µg/mL and 40 µg/mL for pretreatment and post-treatment for 12 h, respectively.IEC-6 was incubated into a 96-well plate, and then incubated for 24 and 48 h by adding different concentrations of EUP-SeNP. Next, the medium was discarded and washed three times with PBS. Finally, 100 µL PBS and 10 µL CCK8  were added to each well and incubated for one hour at 37℃, the optical density was measured at a wavelength of 570 nm. IEC-6 was seeded into a 6-well plate, labeled with fluorescence EUP-SeNP using coumarin-6 as a fluorescence probe, cell nucleus were stained with DAPI  and cell membranes were stained with Dil . Cell uptake was observed within 1 h, 2 h, and 4 h, and photographs were taken with fluorescence microscope.Data analysis was performed with GraphPad Prism . Data are expressed as the means ± standard errors of the mean (SEM). All comparisons of variant parameters between groups were made with one-way analysis of variance, with statistical significance as follows: * p < 0.05, ** p < 0.01, *** p < 0.001, **** p < 0.0001, #P < 0.05, ##P < 0.01, ###P < 0.001, ####P < 0.0001. “*” represents the significance between the control group and the DSS model group; “#” represents the significance between the DSS model group and the treatment group.− 1 to 3397 cm− 1. The C-O-C bond shifts from 1412 cm− 1 to 1383 cm− 1, which indicates that hydroxyl groups are adsorbed on the EUP-SeNP surface. In addition, the peak caused by C-H vibration also changed from 2929 cm− 1 to 2926 cm− 1, which further confirmed the combination of EUP and SeNP. Analysis of the elemental composition of EUP-SeNP using EDX (Fig. The preparation flow chart is shown in Fig. Experimental design as shown in Fig. Low and high power images of colon H&E staining in different treatment groups Fig. A. After DSS-induced colitis is accompanied by a decrease in the number of goblet cells and a decrease in mucin, which was ameliorated by increasing the number of goblet cells and mucin secretion in the treatment group compared with the DSS group Fig. A–B. The TUNEL and Ki67 staining were used to measure the number of apoptotic cells and epithelial cell proliferation, respectively Fig. A–B. The 16 S rRNA gene sequencing was used to detect the colonic microbiota of mice in control, DSS and EUP-SeNP treatment group. OTUs Veen diagram showed that there were 319 common OTUs in the colonic microbiota of mice in each group (Fig. In the control group, there was no significant change in body weight Fig. A and no The different concentrations of EUP-SeNP did not affect the activity of IEC-6 within 24 and 48 h (Fig. IEC-6 protein expression Fig. A and CacDue to the complex and diverse causes of UC, the current treatment is troublesome , 28, 29.Many years ago, Se was widely considered to be biologically inert, but recently, comparing with other forms of Se , researcDSS induced mouse colitis model has been widely used to study animal models of UC because of its similar clinical symptoms to ulcerative colitis , 36. AftSubsequently, We analyzed the colon microbiome and it was noteworthy that although there was no difference in α-diversity analysis among groups, PCoA and NMDS results showed changes in intestinal microbiome composition among groups. And we suspected that this might be due only to the timing of the mold, which also has been seen in previous studies . Our stuFinally, we verified the mechanism of action of EUP-SeNP at the cellular level. LPS is a good inducer of cellular inflammatory models. LPS can destroy intestinal mucosal barrier and reduce the expression of tight junction protein , 49. TheWe prepared a uniform spherical shape EUP-SeNP with a particle size of about 170 nm, which has certain antioxidant function in vitro and in vivo. It can reduce DSS-induced colitis by enhancing intestinal mucosal barrier function, reducing inflammation level, improving antioxidant function, promoting proliferation and reducing apoptotic cells. EUP-SeNP can also regulate the composition of intestinal flora, increase the abundance of beneficial bacteria, reduce the abundance of harmful bacteria and improve colon injury. In addition, EUP-SeNP protects against LPS-induced cell damage by inhibiting the activation of TRL-4/NF-κB signaling.


Idiopathic pulmonary fibrosis (IPF), the most common and severe of the idiopathic interstitial pneumonias, is a chronic and relentlessly progressive disease, which occurs mostly in middle-aged and elderly males. Although IPF is by definition “idiopathic”, multiple factors have been reported to increase disease risk, aging being the most prominent one. Several occupational and environmental exposures, including metal dust, wood dust and air pollution, as well as various lifestyle variables, including smoking and diet, have also been associated with an increased risk of IPF, probably through interaction with genetic factors. Many of the predisposing factors appear to act also as trigger for acute exacerbations of the disease, which herald a poor prognosis. The more recent literature on inhalation injuries has focused on the first responders in the World Trade Center attacks and military exposure. In this review, we present an overview of the environmental and occupational causes of IPF and its pathogenesis. While our list is not comprehensive, we have selected specific exposures to highlight based on their overall disease burden. Idiopathic pulmonary fibrosis (IPF) is a chronic and relentlessly progressive condition characterized by scar tissue formation in the lungs and irreversible organ failure. It commonly affects individuals aged 50 and above and is associated with an unfavorable outlook. The occurrence of IPF ranges from three to nine cases per 100,000 individuals annually in North America and Europe ,3.The factors that trigger the plethora of profibrotic pathways involved in IPF pathogenesis remain unknown, but advancing age, cigarette smoking, viral infection, chronic aspiration of gastric content and genetic factors are all associated with an increased risk of IPF, probably by causing an alveolar epithelial barrier injury . InflammMost research in this field has primarily concentrated on treatments and the influence of specific comorbidities. Conversely, less emphasis has been placed on investigating the consequences of potentially preventable and avoidable environmental and occupational hazards as potential causes of IPF. There are critical medical and policy needs to address this knowledge gap by clarifying the associations between preventable risk factors of occupational and environmental exposures to inhalational hazards and IPF.In this review, we present an overview of the environmental and occupational causes of IPF and its pathogenesis. While our list is not comprehensive, we have selected specific exposures to highlight based on their overall disease burden.Genetically, IPF is a complex disorder inherited in an autosomal dominant fashion with reduced penetrance; however, genetic factors are likely to contribute to both development and progression of the disease .loci associated with an increased risk of IPF. These loci map within genes potentially involved in disease pathogenesis such as modulation of transforming growth factor (TGF)-β signaling, telomere maintenance, cell adhesion, and host defense. Notably, the genetic variant that confers the higher risk for the onset and development of the disease is located within the promoter region of the MUC5B gene (rs35705950). This single nucleotide polymorphism represents to date the strongest and most validated genetic risk factor for both familial and sporadic IPF  with a population attributable fraction of 26% (CI 10–41%) , meaningOrganic dust, notably agricultural and wood dust, has been found to be associated with an increased risk of IPF based on multiple meta-analyses. In several recent systematic reviews and meta-analyses, there has been a significant risk of IPF found for agricultural dust (OR 1.6–2.35) and wood dust (OR = 1.3–2.0) ,48,49,50Studies utilizing mineralogical analysis techniques have found metal dusts  as well as silica in the lymph node and lung tissue of patients with pulmonary fibrosis ,53. In aAsbestos is a naturally occurring group of mineral silicate fibers that cause pulmonary and pleural fibrosis, lung cancer, and mesothelioma thorough mechanisms that are incompletely understood. Various animal models have been developed to understand the mechanisms underlying asbestos-induced lung damage. These models have used either asbestos inhalation or intratracheal instillation . When ex−/− mice was associated with the accumulation of profibrotic regulatory T lymphocytes, IL-17-producing Th17 lymphocytes, and profibrotic cytokines such as TGF-β, IL-10, and PDGF-B) [Silica, one of the earliest recognized causes of lung disease, is an amorphous crystalline material found in several types of rock . Unlike asbestos, silica-related lung fibrosis appears in the form of nodules, which display a characteristic layered or spiral appearance. Specifically, the nodules have a hyaline centre composed of concentrically arranged collagen fibers, whereas the outer zone contains macrophages, lymphocytes and loosely formed collagen, and is the site of active inflammation and enlargement. Exposure of mice to silica dust through aerosol inhalation or intratracheal instillation leads to the development of silicotic nodules reminiscent of the pulmonary lesions observed in humans following occupational exposure . The per PDGF-B) . The mec PDGF-B) ,67.3 and NO2 increased significantly the risk of AE-IPF [3 levels as a risk factor for AE-IPF in a prospective cohort of 192 French IPF patients [2 increases the risk of mortality, especially in elderly male patients with IPF [10 and PM2.5 in the occurrence of AE-IPF was initially suggested by Johannson et al. [2.5 exposure and AE-IPF was reported in a case–control study of 152 Japanese patients with surgically confirmed IPF, in whom an increase of 10 μg/m3 in PM2.5 amplified the risk of AE of the disease by approximately 2.5-fold [2 and O3, suggesting a potential pathogenetic role of genetic predisposition and ethnic origin [2, PM2.5, and PM10 and the risk of AE-IPF, independent of age, lung function impairment, anti-fibrotic treatment, and smoking status [3 or PMs is associated with changes in the peripheral blood levels of IL-4, IL-13, and osteopontin, thus providing evidence for a biological link between long-term air pollution exposure and AE-IPF [10 storms in several areas of the world, including southern Europe, causing a meaningful increase in exacerbations of other chronic respiratory diseases [In the complex interplay between environmental factors and IPF pathogenesis, the relationship between environmental triggers and acute exacerbations of the disease (AE-IPF), unpredictable events with poor outcomes, is even more puzzling. AE-IPF are more common in the winter months, suggesting that seasonal factors  may contribute to their onset and development . In thisf AE-IPF . Sesè anpatients . Moreovewith IPF . The roln et al.  and Sesèn et al. , althoug2.5-fold . Conversc origin . In a reg status . Furtherd AE-IPF . The docdiseases .Although cigarette smoking (both direct and second hand) is one of the most recognized risk factors for the development of IPF ,80, its The recent literature on inhalational injuries from conflict-related disasters has focused on the first responders in the World Trade Center (WTC) attacks. These first responders, including police, firefighters, and emergency medical workers, were at the highest risk for potential injuries, as they were exposed to the highest concentration of toxins. High dust exposure following the WTC attacks has been associated with numerous acute and chronic respiratory diseases and symptoms, including IPF. The collapse of the WTC towers released aerosolized contaminants, including heavy metals, silica, asbestos fibers, wood dust, polyaromatic hydrocarbons (PAH), and polychlorinated biphenyls from the jet fuel, burned plastics, cellulose, and other materials . ExposurOutside of the WTC disaster, most of the literature on inhalational injuries from natural disasters has focused on the wildland fires in Australia and Canada and acute inhalational exposures or obstructive lung diseases, rather than ILD. One US study showed that firefighters have a higher risk of ILD and IPF compared to the working population , but theA recent study on US veterans showed that the incidence and prevalence of IPF in US veterans was higher than previously thought ,98. AddiWhile a growing body of evidence strengthens the role of environmental exposures in the pathogenesis and progression of IPF, the implications for the daily clinical management of these patients remain uncertain ,101. YetIt is still not known if wearing a face mask that filters out air particulates may affect clinical outcome of IPF patients. Moreover, to date, no data are available on the use of home-based air filters or other tools that may mitigate exposure to PM in patients with chronic fibrotic lung disease. In addition, the use of N95 or KF94 masks can interfere with the breathing of patients with advanced respiratory diseases and low pulmonary function, thus leading to uncomfortable respiration, an unsafe breathing pattern, and increased risk of respiratory failure . ProperlUnderstanding the interplay between genetic predisposition and environmental factors could contribute to determining whether there is susceptibility to certain exposures, thus promoting individualized protection approaches. To this purpose, studies should firstly focus on the development of specific and detailed questionnaires designed according to local customs and lifestyle, with the aim to isolate potentially relevant causes amongst the chronic and mixed exposures of a lifetime. Additionally, the identification of specific biomarkers of exposure may ideally contribute to the comprehensive assessment of environmental and professional history. In addition, investigations regarding the effect of environmental exposures on IPF comorbidities  are needed in order to understand the role of preventable traits on the major causes of death in this fragile population. Finally, involving trained professionals  in the objective assessment of exposure within different occupational environments may help to recognize and quantify the extent within the natural course of the disease.Despite all the difficulties in identifying and counteracting the harmful exposures interacting with the pathogenesis of IPF, we feel that a greater awareness on the potential effect of the environment on clinical outcomes in this subset of patients should be encouraged. Indeed, avoiding or mitigating the preventable environmental exposures could represent an adjunct and cost-effective “treatment strategy” with the aim to impact on quality of life and even prognosis.A multitude of occupational/environmental exposures, including, among others, respirable dust exposure in mining, construction, and manufacturing, has been associated with an increased risk of IPF , particu


Stenotrophomonas maltophilia has become one of the major gram-negative pathogens causing nosocomial infections. However, comprehensive analysis of the clinical characteristics and molecular epidemiology of patients with S. maltophilia remains limited.S. maltophilia were collected from April 2019 to March 2022 through the Multi-Drug Resistant organisms clinical research network (MDRnet), consisting of 12 tertiary care hospitals in Japan. The clinical characteristics, outcomes, antimicrobial susceptibility and molecular epidemiology of cases with S. maltophilia colonization and infection were investigated and compared.All patients with a clinical culture growing In total, 78 cases, 44 with colonization and 34 with infection, were included. The median age was 72.5 years (IQR: 61–78), and males accounted for 53 cases (67.9%). The most common comorbidity was localized solid malignancy (38.5%). Almost half of the patients (43.6%) were immunosuppressed, and the most common reason was antineoplastic chemotherapy (30.8%). Respiratory tract was the most common site of colonization (86.4%), whereas bacteremia accounted for more than half of infection cases (55.9%). The overall 30-day all-cause mortality rate was 20.5%, which was significantly higher in infection cases than in colonization cases . Susceptibility rates to ceftazidime, levofloxacin, minocycline, and sulfamethoxazole-trimethoprim were 14.1%, 65.2%, 87.2%, and 100%, respectively. Multilocus sequence typing of the 78 strains revealed that they belonged to 62 different sequence types (STs), of which 42 were known STs and 36 were novel STs.Kaplan-Meier survival analysisS. maltophilia frequently colonizes the respiratory tract, and the mortality is significantly higher in infection cases. Sulfamethoxazole-trimethoprim remains active, but susceptibility to levofloxacin appear to be declining. The strains were genetically highly diverse, consistent with the likely environmental origin.Masahiro Suzuki, PhD, KANTO Chemical co., inc.: Grant/Research Support Sho Saito, MD, PhD, Shionogi & Company, Limited: Grant/Research Support Yasufumi Matsumara, MD, PhD, Beckman Coulter: Grant/Research Support|Presicion System Science: Grant/Research Support|Toyobo: Grant/Research Support David van Duin, MD, PhD, Entasis: Advisor/Consultant|Merck: Advisor/Consultant|Merck: Grant/Research Support|Pfizer: Advisor/Consultant|Pfizer: Honoraria|Qpex: Advisor/Consultant|Roche: Advisor/Consultant|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Union: Advisor/Consultant|Utility: Advisor/Consultant Yohei Doi, MD, PhD, bioMerieux: Advisor/Consultant|FujiFilm: Advisor/Consultant|Gilead: Advisor/Consultant|Gilead: Honoraria|GSK: Advisor/Consultant|Meiji Seika Pharma: Advisor/Consultant|Moderna: Advisor/Consultant|Moderna: Honoraria|MSD: Advisor/Consultant|MSD: Honoraria|Shionogi: Advisor/Consultant|Shionogi: Grant/Research Support|Shionogi: Honoraria


We also analyse the effect of the COVID-19 pandemic on LTx in these populations. (2) Methods: A retrospective, population-based observational study was conducted using the Spanish National Hospital Discharge Database. Multivariable adjustment was conducted with logistic regression to analyse the IHM. (3) Results: We identified 1777 admissions for LTx during the study period, of which 573 (32.2%) were performed in patients with IPF. The number of hospital admissions for LTx rose from 2016 to 2020, both in patients with and without IPF, but a marked reduction was observed from year 2019 to year 2020. Over time, the proportion of single LTx decreased and bilateral LTx increased significantly in both groups. The incidence of LTx complications increased significantly over time along with the increase in the incidence of IPF. No significant differences in the incidence of complications or in the IHM between patients with and without IPF were found. Suffering any complication of the LTx and pulmonary hypertension were conditions positively associated with IHM in patients with and without IPF. The IHM remained stable from 2016 to 2020 in both study populations and was not affected by the COVID pandemic. (4) Conclusions: Patients with IPF account for almost a third of all lung transplants. The number of LTx increased over time in patients with and without IPF, but a marked reduction was observed from 2019 to 2020. Although the proportion of LTx complications increased significantly over time in both groups, the IHM did not change. IPF was not associated with increased complications or IHM after LTx. Lung transplantation (LTx) has been shown to improve the expectations and quality of life of patients with advanced lung disease . The IntLTx can be single or double. In recent years, an increase in the number of double-lung transplants has been detected in the United States and Europe. Although single-LTx means less time on the surgical waiting list, shorter procedure time, and lower risk of complications, double-LTx has shown greater survival and fewer chronic graft-versus-host rejections. Median post-transplant survival is 50% at 5 years ,16,17.The objectives of our study were as follows: (a) to assess the temporal trends in the incidence of LTx in Spain from 2016 to 2020 among subjects suffering or not from IPF; (b) to describe and compare the clinical conditions, such as comorbidities, complications of the transplanted lung, and post-transplant infections of these two populations; (c) to analyse the temporal trends in the length of hospital stay (LOHS) and the in-hospital mortality (IHM) among IPF and non-IPF patients who received a LTx; and (d) to assess whether the COVID 19 pandemic has affected the number or the outcomes of LTx in these patients.We conducted an observational study with data obtained from the Registro de Actividad de Atención Especializada-Conjunto Mínimo Básico de Datos (RAE-CMBD). This is a hospital discharge database that collects information on all admissions to public and private hospitals in Spain . We analThe variables collected by this registry include sex, data of birth, dates of admission and discharge, and if the patient has died in the hospital. Additionally, for each patient, and using the International Classification of Disease 10th version (ICD-10), up to 20 diagnoses and procedures can be recorded. The study population included subjects who had a code for LTx ; LTx were classified as single or bilateral LTx using the ICD-10 codes shown in We grouped admissions by IPF status. We considered IPF patients as those with any ICD10 codes J84.1xx in any diagnostic position, and the rest as non-IPF patients.To assess the presence of comorbidities, we used the Charlson comorbidity index (CCI), using ICD10 codes described by Sundararajan et al. . The CCIProcedures such as haemodialysis, extracorporeal membrane oxygenation, and tracheostomy were identified in any of the procedures fields of the database .The following complications of LTx were considered if recorded in any diagnostic position: lung transplant rejection, lung transplant failure, lung transplant infection, and other or unspecified complications of lung transplant . ComplicIn addition, we evaluated the presence of pneumonia and ventilator-associated pneumonia as complications .Staphylococcus bacteraemia, Gram-negative bacteraemia, Pseudomonas aeruginosa infection, Aspergillus infection, and Cytomegalovirus infection were identified in the database using the corresponding ICD10 diagnosis codes  for continuous variables and total frequencies with proportions for categorical variables. To assess changes over time we used Cochran–Armitage tests for categorical variables, and the test for linear trend or the Jonckheere–Terpstra test for continuous variables. 2 test and continuous variables with the t-test or the Mann–Whitney test, as required.We compared categorical variables using the χWe conducted three multivariable logistic regression models  with IHM as the dependent variable. To construct the multivariable models, the steps were as follows: 1. Bivariate analysis to assess the association of independent variables with the IHM. 2. We selected for the multivariable analysis those variables with a significant association in the bivariate tests, as well as other study variables that have been found relevant in previous investigations. 3. The Wald statistic was used to decide, one by one, if variables were included in the model. Using the likelihood ratio test, consecutive models were compared with the previous ones as new variables were added. 4. For the final model, linearity and interactions between variables in the model was checked to identify which study variables were independently associated with IHM. Odds ratios (ORs) are provided as measure of association along with their 95% confidence interval (95%CI).p value < 0.05 (2-sided) was considered significant.All statistical analysis was performed with Stata version 14 . A The anonymized database of the RAE-CMBD was provided to us by the Spanish Ministry of Health upon request, and after scientifical and ethical evaluation of our study protocol . In SpaiFrom 2016 to 2020, we identified 1777 admissions for LTx in Spain. Over the study period, 573 (32.2%) of all admissions for LTx were performed in IPF-patients. Of these, 291 were single (50.7%) and the remaining bilateral LTx. The number hospital admissions for LTx  in IPF-patients can be seen in p < 0.001); however, bilateral LTx increased significantly in both groups . Over the entire study period, IPF patients underwent more single LTx than non-IPF patients ; however, they underwent less bilateral LTx .The proportion of single LTx decreased significantly over time in patients with and without IPF . p < 0.001). Among the patients who underwent LTx, there were fewer women than men and proportionally fewer women in the IPF group vs. the non-IPF group . Only in non-IPF patients was mean age increased significantly (p = 0.025) between 2016 and 2020.The age ranged from 0 to 72 years for those without IPF and from 13 to 71 years for those with this condition. Over the entire study period, the mean age of IPF patients who underwent LTx was almost 7 years higher than that of those patients without IPF . According to the mean CCI, patients without IPF had more comorbidities than those with IPF (p < 0.001). However, the IHM was similar, 11.5% for IPF and 11.9% for non-IPF patients. Neither LOHS nor IHM changed significantly from 2016 to 2020 in any study group.The total mean LOHS was significantly shorter in the IPF patients (44.7 days) than the non-IPF patients . In the non-IPF group, a significantly increase in the frequency of moderate/severe liver disease and hemiplegia/paraplegia between 2016 and 2020 was observed. However, the prevalence of renal disease and cancer/metastatic solid tumour decreased overtime. The prevalence of rheumatoid disease was significantly higher in the IPF group than in the non-IPF group . Patients without IPF had a significantly higher prevalence of COPD (56.1% vs. 13.1%) and asthma (2.3% vs. 0.9%) than those with IPF. Current tobacco use was not codified in any IPF patient and only three non-IPF. Regarding comorbidities, in patients with IPF, the prevalence of pulmonary hypertension increased over time .As can been seen in Around 25% of the patients undergoing LTx suffered LTx rejections, and another 11% LTx infection. If any possible complications were considered, 51.0% and 49.8% of patients with and without IPF were affected. None of the LTx complications showed significant differences when patients with and without IPF were compared.p = 0.004).The proportion of LTx complications showed a significant increase over time in both groups analysed, specifically lung transplant rejection, lung transplant failure, other/unspecified complications of lung transplant, and any complication of lung transplant. Furthermore, the proportion of lung transplant infection in the IPF group increased significantly, almost four times, between 2016 and 2020 , followed by Pseudomonas aeruginosa (8.5%), and Gram-negative bacteraemia (6.6%). A very similar prevalence was codified among non-IPF patients. Regarding isolated pathogens, those most frequently found among IPF patients were Shown in p < 0.001). Crude IHM in patients with IPF was higher in single LTx, in women, in patients with higher CCI, and in those with any complications of lung transplant; however, all these differences were not significant.IHM was higher in patients with IPF presenting with pulmonary hypertension than those without this condition . IHM in patients with IPF was slightly higher in 2020 (14.0% in 2020 and 12.0% in 2019), but this difference was not significant. No differences were found between 2020 and 2019 in the IHM after stratification by type of procedure, sex, age, CCI, pulmonary hypertension, and any complication of lung transplant.Patients operated on in year 2020 had pulmonary hypertension coded in a higher proportion that those who underwent LTx in year 2019  and pulmonary hypertension  were conditions positively associated with IHM. These two same variables showed a significant association among those without IPF and in the entire population of LTx patients . As founFinally, from 2016 to 2020, and after adjusting by all study variables, IPF was not associated with IHM after LTx .In our study, we identified 1777 patients who received LTx in Spain during the period 2016–2020. Of them, 32.5% were patients with IPF, evidencing an increase in transplants in patients with this disease over time. However, in 2020 there was a marked reduction, both in the group of patients with IPF and in those without IPF. This reduction was due to the SARS-CoV-2 pandemic, and it has also been detected in other series. Thus, in England, the average number of transplants in the first months of the pandemic was 4 per month, while in the months of January and February 2020 it was 12.5 per month . In addiLTx can be single or double, with the advantages of the former being shorter surgical time, less trauma, shorter ischemia time, and shorter waiting time on the surgical list . The eviIn advanced stages, lung diseases are associated with many comorbidities, both respiratory and non-respiratory, which affect the quality of life of patients and may interfere with the transplant prognosis ,34. In oAs in our series, the use of extracorporeal membrane oxygenation is becoming widespread. However, the results obtained in the different series are contradictory and inconclusive. Thus, there are authors who have associated its use with a higher rate of complications , while oAnother complication in our series, which has been multiplied by four from 2016 to 2020, are infections . More specifically, pneumonia occurred in 6.1% of patients with IPF in 2016, compared to 8.1% in 2020. Infections are one of the main post-transplant complications, having been described as the second cause of death. Of these, the most common are respiratory infections, mostly bacterial. In the Spanish series by Aguilar et al., bacterial pneumonia 4 weeks after transplantation occurred in up to 44% of transplanted patients . In our Overall, it has been previously described that the survival of transplanted patients is 89% at 3 months, 80% at one year, and 31% at 10 years. The highest number of reported cases of mortality occur in the first 30 days, due to high rejection or infections, mainly by cytomegalovirus ,49. The In our series, we did not observe an increase in IHM over time in either of the two groups. The overall IHM of patients with IPF was 12.7% in patients with a single-lung transplant versus 11.0% in those with a double-lung transplant. These mortality results are similar to those described in the Spanish series by Prudencio-Ribera et al., who detected a figure of 13.4% in the group of patients with diffuse interstitial lung disease, with IPF being the most frequent disease, detected in 79.6% of patients . It is wEarly IHM in single-LTx has shown contradictory results, with an increase in the series by Arango et al.  and ForcOur study has several limitations. The main one is that the data have been obtained from an administrative database, in which the pathologies and procedures are coded according to the ICD-10-CM. The validity of the RAE-CMBD in identifying LTx has not been assessed; however, studies conducted in the US, using the National Inpatient Sample, concluded that discharge databases are reliable and accurate for national epidemiological investigations . FurtherFuture works, including more detailed clinical and biological data and information on long term mortality after LTx, should be conducted in our country to improve the knowledge and management of patients with IPF.In conclusion, patients with IPF account for almost a third of all lung transplants. The number of LTx increased over time in patients with and without IPF, but a marked reduction was observed from 2019 to 2020. The proportion of single LTx decreased significantly, while bilateral LTx increased significantly among both groups. Although the proportion of LTx complications increased significantly over time, the IHM did not change. IPF was not associated with IHM after LTx.


The Orthopaedic In-Training Examination (OITE) is a multiple-choice examination developed by the American Academy of Orthopaedic Surgeons annually since 1963 to assess orthopaedic residents' knowledge. This study's purpose is to analyze the 2017 to 2021 OITE trauma questions to aid orthopaedic residents preparing for the examination.The 2017 to 2021 OITEs on American Academy of Orthopaedic Surgeons' ResStudy were retrospectively reviewed to identify trauma questions. Question topic, references, and images were analyzed. Two independent reviewers classified each question by taxonomy.Trauma represented 16.6%  of OITE questions. Forty-nine percent of trauma questions included images (100/204), 87.0% (87/100) of which contained radiographs. Each question averaged 2.4 references, of which 94.9% were peer-reviewed articles and 46.8% were published within 5 years of the respective OITE. The most common taxonomic classification was T1 (46.1%), followed by T3 (37.7%) and T2 (16.2%).Journal of Orthopaedic Trauma (24.7%), Journal of the American Academy of Orthopaedic Surgeons (10.1%), and Journal of Bone and Joint Surgery, American Volume (9.3%) remain the most cited sources.Trauma represents a notable portion of the OITE. Prior OITE trauma analyses were published greater than 10 years ago. Since then, there has been an increase in questions with images and requiring higher cognitive processing. The  Trauma is reported to represent approximately 15% of the examination content annually.3The Orthopaedic In-Training Examination (OITE) is a multiple-choice examination developed by the American Academy of Orthopaedic Surgeons (AAOS) annually since 1963 to assess orthopaedic residents' knowledge during training.4-6 For program directors, the OITE is the only national test to objectively assess a resident's orthopaedic knowledge both as a benchmark on the efficacy of the residency education curriculum and on the progress of their individual residents.6 Given the importance of the examination, most residents are motivated to perform well, and most rely on an online learning platform, most commonly ResStudy and Orthobullets, to aid in preparation for the OITE. Only a minority of residents use journal reading as their primary learning material.7The OITE is an important examination for both residents and program directors. For residents, the OITE scores, particularly in the last year of postgraduate training, correlate with the American Board of Orthopaedic Surgery part I scores.8-10 These prior studies analyze questions preceding the conversion to a computer-based examination in 2009, which expanded the opportunity to include more advanced imaging and videos as part of the examination and thus could have influenced the examination content and the types of images included.9 Recently, multiple studies have published an updated analysis of OITE questions in other subspecialties, including pediatrics,11 oncology,12 hand,13 hip and knee reconstruction,14 basic science,15 spine,16 and sports.17 To our knowledge, no update on the analysis of the OITE trauma section has been published.Prior analyses of the trauma section of the OITE were published greater than 10 years ago and studied the OITE between 2004 and 2009.The primary purpose of this study is to determine the representation of trauma questions on the OITE between 2017 and 2021 and to analyze these questions for topic, references, imaging, and question taxonomy. Study results will help inform current orthopaedic residents as they prepare for the annual examination and residency program directors as they develop their program's educational curriculum.18 Taxonomy I questions (T1) assess information recognition and recall. Taxonomy II questions (T2) test data comprehension and interpretation through diagnosis or image interpretation. Taxonomy III questions (T3) test knowledge application for problem solving, such as multistep management or decision making. Chi-squared tests were used to compare categorical data. P < 0.05 was considered statistically significant.The 2017 to 2021 OITE questions published on AAOS's ResStudy online platform were retrospectively reviewed. Questions testing concepts related to musculoskeletal trauma were compiled for analysis. Questions related to traumatic injuries that could otherwise be categorized as spine or hand were excluded. This exclusion criterion aims for the questions analyzed to best reflect the type of injuries that are typically managed by a trauma-focused general orthopaedic surgeon and test orthopaedic trauma principles. By contrast, traumatic injuries to the hand and spine are typically treated by their respective subspecialists, and the authors believe that questions related to these topics are better analyzed in studies of the hand and spine domains of the OITE, respectively. For each question, all associated references, figures, and images were compiled. The percentage of trauma questions for each OITE examination was calculated. The topic of each question was categorized as shoulder and elbow, hip and femur, knee and leg, foot and ankle, pelvis and acetabulum, basic science, and general trauma principles. The number of references for each question was recorded. References were classified by publication year. The year of publication was compared with the year of the OITE, and the time elapsed between the reference publication and the OITE was recorded. For questions with figures, both the number of images included for each question and the imaging modality  were identified. Two independent reviewers classified each question by taxonomy, as previously defined by Buckwalter et al.Trauma questions represented 16.6%  of OITE questions between 2017 and 2021, ranging from 14.0 to 20.9% annually. Topics tested include shoulder and elbow (19.1%), hip and femur (18.6%), knee and leg (12.7%), foot and ankle (14.7%), pelvis and acetabulum (14.2%), basic science (10.8%), and general trauma principles (9.8%), as summarized in Table Images were included in 49.0% 100/204) of questions and 87.0% (87/100) of these contained radiographs, 67.0% of which included radiographs alone, and 20.0% included radiographs in combination with other imaging modalities. Other imaging modalities included were CT (21.0%), clinical images (8.0%), and diagrams (4.0%). Table 04 of queJournal of Orthopaedic Trauma (24.7%), the Journal of the American Academy of Orthopaedic Surgeons (10.1%), and the Journal of Bone and Joint Surgery, American Volume (9.3%). These top three journals account for 44.1% of references. Table On average, there are 2.4 references per question (ranging from 2 to 6). Peer-reviewed journal articles represent 94.9% of all references (ranging from 92.0% to 97.2%), whereas the remaining 5.1% of references were composed of textbooks, websites, and instructional course lectures. The three most common journals cited were the Volume 9.%. These On average, the most common taxonomic classification was T1 (46.1%), followed by T3 (37.7%) and T2 (16.2%). Table 3 but no difference was found compared with prior studies of the OITE that analyzed only questions defined by the AAOS as trauma questions between 2005 and 200910 (P = 0.240). These studies reported that trauma questions accounted for between 18.3% and 19.3% of questions on the examination each year,10 averaging 18.8% of the examination between 2005 and 2009.9 By contrast, another study on 2004 to 2008 OITE questions reported that 28.3% of OITE questions were trauma-related questions,8 which is significantly more than that found in our study (P < 0.001). This difference is likely a reflection of different inclusion and exclusion criteria for trauma questions across studies. Many questions related to traumatic injuries can be categorized as both a trauma question and a question in another orthopaedic subspecialty. For example, a traumatic ankle fracture could be categorized as both a foot and ankle and a trauma question. In our study, we opted to exclude questions related to hand and spine trauma because these injuries are typically managed by their respective subspecialist as opposed to a general orthopaedic surgeon.This study provides an updated analysis of the OITE musculoskeletal trauma section to better inform both residents as they prepare for the annual examination and program directors as they develop their program's educational curriculum. Trauma questions continue to account for a substantial proportion of the examination, representing 16.6% of questions between 2017 and 2021. This is slightly more than the 15% that the AAOS aims for trauma to represent,9 and 30.2%10 of questions. This represents a significant increase in trauma questions incorporating imaging in the past decade . The authors hypothesize that the increased incorporation of images may reflect the transition from a paper-based examination to a computer-based examination in 2009,9 which allows the inclusion of higher quality imaging studies and makes it both easier and less expensive to include images. Of the questions containing images in our study, 87.0% contained radiographs either alone or in combination with other imaging modalities. By contrast, 95% of questions with images contained plain radiographs between 2005 and 2009.10 Residents preparing for the OITE should aim to become proficient in the interpretation of both advanced imaging modalities and plain radiographs, but given the clear emphasis on plain radiographic imaging on the examination, test takers should be aware that plain radiographs are still the most frequently tested.Imaging studies, including plain radiographs, CT, and magnetic resonance imaging, are important in diagnostic and treatment decisions in orthopaedics. This study found that images were included in nearly half of all trauma questions tested. In comparison, prior studies from over a decade ago reported that images were included in only 28.3%2 Le et al2 highlighted that the AAOS recommends references should be published within the past 10 years, which held true for 72.1% of all references cited in our study. The majority (94.9%) of references were primary literature sources, an increase from the 75% that was reported in a prior study of trauma questions.8 The three most frequently cited sources in our study, the Journal of Orthopaedic Trauma, Journal of the American Academy of Orthopaedic Surgeons, and Journal of Bone and Joint Surgery, American Volume, were also among the most frequently cited sources identified in the prior reviews of trauma OITE questions.8-10 Interestingly, only 6% of residents report using journals as their primary study resource, but journals were also rated by the same group of surveyed residents as the most useful for preparation for the OITE.7 In contrast to reading journals, Theismann et al7 report that most residents use Orthobullets (53%), ResStudy (26%), JBJS Clinical Classroom (3%), textbooks (8%), or other resources (4%) in preparation for the OITE. The preference toward utilization of online learning platforms for OITE preparation is supported by program directors, 85% of which recommend the use of Orthobullets and 65.7% recommend the use of ResStudy.19 This highlights that residents should be aware of consistently high-yield journals such as the Journal of Orthopaedic Trauma, Journal of the American Academy of Orthopaedic Surgeons, and Journal of Bone and Joint Surgery, American Volume to supplement the secondary references they often use to prepare for the OITE.OITE question writers are encouraged to cite 2 to 6 high-impact journals for each examination question.18 in 1981, the OITE aims to test the complex cognitive processes necessary for the practice of orthopaedics. Questions are thus designed to fall into one of three different taxonomic classifications based on the cognitive processes required to correctly answer them. Taxonomy 1 questions test recognition and recall of information, taxonomy 2 questions test comprehension and interpretation of information, and taxonomy 3 questions test problem solving.18 Our study found that slightly less than half of questions (46.1%) were T1 questions, which represents a slight decrease from the prior analysis of AAOS-defined trauma questions that reported 60.6%9 and 69.0%10 of questions to be T1 (P < 0.001). The next most frequently tested questions are T3 questions that represent 38% of trauma questions, increased compared with 19.7%9 and 21.6%10 on prior analysis of AAOS-defined trauma questions (P < 0.001). Together, these results suggest that although nearly half of questions still test recognition and recall, there is a slight shift toward inclusion of questions requiring higher levels of cognitive reasoning to correctly answer in our study relative to prior studies of AAOS-defined trauma questions. Residents can focus on case-based practice questions, which are more likely to require higher-order cognitive processing, to adequately prepare for the increased proportion of these questions.20 Of note, there was no difference in the taxonomic distribution of questions that our study reported relative to Seybold et al8's analysis of 2004 to 2008 musculoskeletal trauma OITE questions (P = 0.18), which reported 50.8% T1, 11.0% T2, and 38.2% T3 questions. This study by Seybold et al included both AAOS-defined trauma questions and questions defined by AAOS under different domains, which the authors believed also tested musculoskeletal trauma concepts. The difference in inclusion criteria for this study limits our ability to directly compare it with our findings.As first described by Buckwalter et al8-10 The inability to directly compare the inclusion and exclusion criteria across studies limits our ability to compare our study findings with those reported in previous studies. As the AAOS stopped publishing the complete study guide with the official categorization of all questions in 2016,14 we are unable to compare the questions we categorized under the domain of trauma with those that the AAOS intended to test trauma principles. In addition, our study examines the five most recent OITE examinations that are available on AAOS's ResStudy. Greater understanding of trends in questions may have been possible if we were able to examine all questions since the most recent trauma question analysis in 2009.There are several limitations to our study. The trauma domain is broad and overlaps with nearly all 10 other domains on the OITE. In the design of this study, the authors opted to define trauma questions based on injuries typically treated by a general trauma-focused orthopaedic surgeon and thus excluded questions that could be considered traumatic spine injuries and traumatic hand injuries. Although the authors believe that this definition most accurately reflects the intended domain of question writers, the AAOS does not publish their definition of the musculoskeletal trauma domain for comparison nor do prior studies of the OITE trauma questions.This study highlights that trauma continues to account for a notable proportion of the OITE, which has increased somewhat in recent years. The development of a digital examination has resulted in a substantial increase in the use of images for the trauma questions. Consistent with prior reports, high-impact journals remain notable sources of information for the chosen questions, and questions emphasize higher-level cognitive processes . The results suggest that strategies for residents should include interpretation of images, development of higher-level cognitive processes through case-based practice questions, and awareness of high-impact journals.