This report presents a contactless and robust dielectric microspheres (DMs)-assisted surface enhanced Raman scattering (SERS) enhancement method to improve SERS detection sensitivity detection sensitivity. DMs that could focus and collect light were embedded within the polydimethylsiloxane (PDMS) film to avoid direct contact with the analytical solution and improve detection reliability. The as prepared DMs embedded PDMS (DMs-PDMS) film was integrated with a microfluidic technique to enhance the SERS signal of a liquid substrate. Detection in microfluidic systems can reduce reagent consumption, shorten assay time, and avoid evaporation of the colloid substrate solution. The robustness and potential influencing factors of DMs-PDMS film assisted SERS enhancement (DERS) were evaluated using 4-aminothiophenol (4-ATP) as the Raman probe. The sensing performance of the proposed method toward dipicolinic acid (DPA) was evaluated, and an evident signal intensification was obtained. Remarkably, the DMs-PDMS film can also be implemented on solid substrates. A proof-of-concept experiment was performed by covering the DMs-PDMS film directly over an AgNPs@Si solid substrate wherein a 5.7-fold sensitivity improvement was achieved. Raman spectroscopy, particularly surface-enhanced Raman scattering (SERS), is suitable for sensing applications because it can provide molecular fingerprint information that uniquely identifies target analytes from a complex matrix . Moreove2 colloids can act as lenses to enhance the fluorescence of single molecules  and silica particles (80 or 100 nm) was synthesized by taking the advantage of well-studied electrostatic attractions , which can focus and collect light, provide an alternative approach to optical signal enhancement . Schwartolecules . Yang etancement . Compareancement , (Danthaancement . In 2015ancement . These rancement . For exaancement . A uniforactions . Recentletection . In prac3+ or Eu3+ is one of the most commonly used strategies (Dipicolinic acid (DPA), one of the main ingredients of anthrax spores (accounts for 5–15% of the dry mass of spores), has been adopted as a significant biomarker for the detection of anthrax . Variousrategies . DespiteIn this study, a flexible and robust DMs embedded polydimethylsiloxane (DMs-PDMS) film was fabricated and used as a versatile and universal Raman scattering enhancer to improve the sensitivity of SERS detection. The DMs that could enrich the SERS signals were insulated from the solution, ensuring detection reliability and repeatability. The excellent optical transparency of PDMS guarantees an efficient passing through of light for SERS excitation and collection. Combined with microfluidic technology, the as-prepared DMs-PDMS film can be used as a universal platform to enhance the SERS signals of the liquid substrate. We attempted to use this DMs-PDMS film-assist SERS enhancement approach (DERS) to detect DPA, and a significant signal improvement was achieved. Moreover, by simply covering the DMs-PDMS film over a solid substrate, it is encouraging to find that the SERS signals of the solid substrate can also be enhanced.3C6H5O7.2H2O, AR, was purchased from Alfa Aesar, silver nitrate (AgNO3), Dipicolinic acid (DPA) and 4-aminothiophenol (4-ATP) were from Aladdin (China); 3-Aminopropyltriethoxysilane (APTES) was from J&K Scientific ltd. Sylgard 184 PDMS oligomer and curing agent were from Dow Corning, High refractive index barium titanate solid glass microspheres (BTGMs) was from Cospheric (US). H94-25c 4 “single lithography machine was purchased from Sichuan Nanguang Vacuum Technology Co., Ltd. Plasmon cleaner (PDC-32G-2*) was provided by Harrick Plasma (US). Raman spectrometer BWS415-785S was from B&WTEK (US).NaThe DMs-PDMS films with microchannels was fabricated following a modified photolithography process simply described as follows: A positive photoresist mold was firstly fabricated according to a previous report . Then PD3 was dissolved in 100 ml DI water and heated rapidly to boil under vigorous stirring. Then the freshly prepared trisodium citrate solution  was added into the boiling solution, resulting a rapidly brown to gray color changes within a few minutes. The solution was boiled for another 30 min to ensure the complete reduction of silver nitrate, and then AgNPs solution was obtained. The as-prepared AgNPs were concentrated for 10-fold and then stored in dark for use.Silver nanoparticles (AgNPs) used as the SERS substrate were synthesis by using a method reported previously . In brieFor testing the DERS effect, 4-ATP, a commonly used SERS probe was used. 4 μl 4-ATP (2 μM) solution was mixed with 35 μl AgNPs and incubated for 5 min. The mixture was filled into the microchannels. Then SERS signals in the presence and absence of DMs was collected and compared. Similar procedures were also employed for investigating the influence factors and robustness of the DERS effect.2SO4/H2O2 (3:1 (v/v) H2SO4 (98%)/H2O2 (30%) at 100°C for 30 min to derive a hydroxyl surface. Second, after washing, the silicon slide was immersed into a 6% solution of APTES in ethanol for 1 h followed by a profusely rinsing. Third, the silane modified silicon slide was submerged into AgNPs for 3 h, then an AgNPs coated silicon slide was obtained (AgNPs@Si). After dry in nitrogen, the AgNPs@Si substrate was immersed into 4-ATP solution in ethanol, and washer by DI water 1 h later. After that, the DMs-PDMS film was placed on the AgNPs@Si substrate and SERS spectra were collected.Proof-of-concept experiments for testing the enhancing effect of the DMs-PDMS film on a solid substrate was carried out as follows: First, silicon slide was cleaned sequential ultrasonication in acetone, ethanol and deionized water for 10 min and then treated with H3 on sensitive detection of DPA, aqueous solution of nitric acid with different concentrations was prepared. Then DPA solutions (0.02 mM) were prepared by using these nitric acid solutions. 4 μl of this DPA solution was mixed with 35 μl AgNPs and incubated for 5 min , respectively). After that the mixture was filled into the microchannels and the SERS spectra were collected.To evaluate the influence of HNO3 concentration. 4 μl of the DPA solution was mixed with 35 μl AgNPs to a final concentration of 100 μM, 50 μM, 10 μM, 1 μM and 0.1 μM, respectively. After incubated for 5 min, the mixture was added into the microchannels and the SERS spectra was collected.For quantitative measurements, standard solutions of DPA with different concentrations were prepared at the optimal HNOvia chemical coordination, was chosen as the Raman probe. As shown in To test the DERS effect of the as-prepared DMs-PDMS film, AgNPs, one of the most commonly used SERS substrates, were synthesized according to a previous study . 4-ATP, Optical focusing and collecting ability of DMs may be related to their refractive index (RI). Two types of DMs with different RI (common glass microbeads with an RI of approximately 1.5 and BTGMs with an RI of approximately 1.9) were embedded in different areas of the same PMDS film. As shown in To test the robustness of the DERS effect, BTGMs of different sizes were embedded into the PDMS film, and the size influence on the enhancing efficiency was investigated. As shown in −1  in the presence of DMs (BTGMs) were collected. As demonstrated in −1 . The obt3. Most prominent SERS signals were observed at an HNO3 concentration of 2 mM. Further increasing the HNO3 concentration to 10 mM led to a significant decrease in the signal, which may be attributed to the high acidity-induced dissolution of the AgNPs.Encouraged by the above results, we explored the possibility of using the proposed DERS effect for DPA detection. It has been reported that acidic conditions are favored for SERS analysis of DPA . Figure 3 were mixed with the AgNPs. The mixture was then filled into the microchannels of the BTGM-PDMS film, and the corresponding SERS signals were collected. −1, 818 cm−1, 1,010 cm−1, and 1,387 cm−1 peaks attributed to C = C ring bending vibration, C-H in-plane bending vibration, symmetric pyridine ring stretching vibration, and O-C-O symmetric bending vibration, respectively . The corresponding SERS spectra were collected directly by covering the BTGM-PDMS film over the AgNPs@Si substrate. PDMS exhibits high adhesion and mechanical flexibility; thus, it can firmly adhere to the AgNPs@Si substrate. As shown in In conclusion, we report a contactless and DMs-assisted sensitivity improvement method for SERS detection. The method takes advantage of the excellent properties of PDMS  and high optical focusing and collecting ability of DMs to provide improved sensitivity for the rapid and sensitive detection of analytes. By using 4-ATP as a probe molecular, the robustness and sensing performance of the DERS effect has been evaluated. By taking advantage of this DERS effect, the sensitivity for SERS detection of DPA was improved by 5-fold. Meanwhile, the as-prepared BTGM-PDMS film can be extended to enhance the SERS signals of solid substrates. A proof-of-concept experiment was performed using an AgNPs@Si substrate, and a 5.7-fold sensitivity improvement was achieved. The proposed strategy is expected to open new avenues for the design of ultrasensitive SERS assays.


The evolution of spliceosomal introns has been widely studied among various eukaryotic groups. Researchers nearly reached the consensuses on the pattern and the mechanisms of intron losses and gains across eukaryotes. However, according to previous studies that analyzed a few genes or genomes, Nematoda seems to be an eccentric group.Caenorhabditis species, the dominance of the precise intron losses, frequent loss of adjacent introns, high-level expression of the intron-lost genes, preferential losses of short introns, and the preferential losses of introns close to 3′-ends of genes. Like studies in most eukaryotic groups, we cannot find the source sequences for the limited number of intron gains detected in the Caenorhabditis genomes.Taking advantage of the recent accumulation of sequenced genomes, we extensively analyzed the intron losses and gains using 104 nematode genomes across all the five Clades of the phylum. Nematodes have a wide range of intron density, from less than one to more than nine per kbp coding sequence. The rates of intron losses and gains exhibit significant heterogeneity both across different nematode lineages and across different evolutionary stages of the same lineage. The frequency of intron losses far exceeds that of intron gains. Five pieces of evidence supporting the model of cDNA-mediated intron loss have been observed in ten These results indicate that nematodes are a typical eukaryotic group rather than an outlier in intron evolution.The online version contains supplementary material available at 10.1186/s13062-022-00328-8. Symbiodinium minutum has an even higher intron density in its genome, with up to 18.6 introns per gene [Saccharomyces cerevisiae genes have only 0.05 introns on average. Furthermore, the highly compacted genomes of some obligate intracellular microbes do not have any introns [In the nuclear genomes, protein-coding genes are often interrupted by noncoding sequences removed from the pre-mRNAs by the dynamic RNA–protein complex, spliceosome. In most publications, these interrupting sequences are termed spliceosomal introns and abbreviated as introns. Eukaryotic genomes vary considerably in their intron contents. The human genome contains hundreds of thousands of introns, with each human gene having eight introns on average . The dinper gene . On the  introns , 4. A la introns .S. cerevisiae [The differential rates of intron loss and gain across eukaryotic lineages result from the differences in the rates of spontaneous mutations giving rise to new intron loss or gain events and the probability of fixing the new mutations in the genomes. Introns allow one gene to code multiple proteins through alternative splicing , 23. Somrevisiae –34. It irevisiae .On the other hand, most introns have been suggested to be slightly deleterious –38. ThusThe most widely cited mechanism of intron loss is recombining the genomic DNA with the cDNA molecules reverse-transcribed from mature mRNAs , 48. EviCaenorhabditis elegans and C. briggsae [Homo sapiens, Drosophila melanogaster, Anopheles gambiae, C. elegans, Schizosaccharomyces pombe, Arabidopsis thaliana, and Plasmodium falciparum. They observed evidence supporting the cDNA-mediated intron loss model, biased loss from 3′-end and adjacent intron loss. However, none of these patterns were observed in C. elegans, leading them to conclude that the intron loss process might be qualitatively different in nematodes [Caenorhabditis genomes [However, previous studies showed an entirely different picture of intron evolution in the nematodes. Phylogenetic analyses of a few genes or gene families found that the vast majority of intron changes during nematode evolution involve losses of introns individually, rather than multiple introns being lost together , 58. Thebriggsae . It is iematodes . The lac genomes .C. elegans and C. briggsae using the distantly related nematode Brugia malayi, two chordates (human and mouse), and two arthropods (fruit fly and mosquito) as outgroups. They found 122 recently gained introns in the two nematode genomes, and 28 of them have significant sequence identity to other introns, providing evidence for the introns’ origin. Roy and Penny [C. remanei and Caenorhabditis sp. 4. Their results showed that most of the 122 intron gains reported in one Caenorhabditis species are actually intron losses in other species [On the other side, the studies on intron gain took an unexpected turn in the nematodes. Coghlan and Wolfe  comparednd Penny  repeated species . This re species .Caenorhabditis branch deeply investigated.All the previous studies on nematode intron evolution were based on a few gene families or genomes whose sequences were available at that time. With the rapid progress of genome sequencing and annotation, nearly 200 completely sequenced genomes are now available in WormBase . It is t−5, we captured the 1557 groups of orthologs that are present in over 90% of the analyzed species , and at least in one of the two outgroup species. After filtration of the poorly aligned regions from the multiple sequence alignments, 1551 groups of orthologous genes were obtained. A molecular consensus tree was constructed using these orthologous genes  hits with a threshold E value of 10C. elegans, D. melanogaster, and H. sapiens having 3.65, 1.92, and 6.62, respectively [Micoletzkya japonica, Parapristionchus giblindavisi, and Mesorhabditis belari. The well-studied genus Caenorhabditis is also presented in the Clade V. The ten Caenorhabditis species have a striking difference in intron density with other species in Clade V, with the median values 3.42 vs. 7.68.We first calculated the intron density, the intron number per 1 kbp coding sequence (CDS), of the 1577 groups of orthologs across the 106 genomes. The intron density values of the model organisms we obtained are consistent with the previous study, with Caenorhabditis (from 3.31 to 3.65) have evolved to nearly 1/3 of the ancestral intron density, while intron-poor species in Strongyloididae have less than 1/10 of ancestral intron density.We then reconstructed ancestral intron densities . The second pattern we observed in nematode intron evolution is that the lineages with a higher intron loss rate generally have a higher gain rate . The third pattern we could see from Fig. We estimated ancestral intron content and calculated the number of intron losses and gains on each phylogenetic branch using MALIN . The firate Fig. : Fig. S2p = 0.028) and rate  of intron loss, and the intron gain number , but not correlated with intron gain rate . In addition, we found that the branch length is positively correlated to intron loss , but not correlated with with intron density or intron gains .Among the 207 branches during nematode evolution, the intron density are negatively correlated with the number , 0.95 (p = 1.9 × 10−5), and 1.00 (p = 3.6 × 10−59) for the intron losses, the intron gains, and present intron density, respectively. It seems that phylogenetic comparative methods are required to control the effects of common ancestors. We used the phylogenetic generalized least squares (PGLS) regression analysis to examine the relationships. A positive slope of the regression line indicates a positive correlation, while a negative slope indicates a negative correlation. Consistent with that observed in analyzing the branches, the number of intron losses of the 104 nematodes is positively correlated with that of intron gains  procedure and provided the adjusted Caenorhabditis species in-depth. Using BLASTP , we identified 4892 groups of orthologous genes present in all ten species. Among them, 6441 discordant intron positions were detected in 2333 groups of orthologs. Meanwhile, 6252 conserved intron positions were identified. Some ambiguous intron positions were discarded. In 682 groups of orthologs, all the intron positions are conserved. Referring to the phylogenetic tree of the ten Caenorhabditis species and 12 outgroup species  take 31.4%, and the intron-gained genes (118) take 2.41%. If intron losses and gains are randomly distributed among the genes, the genes that experienced both intron losses and intron gains should take 0.76%, i.e., 37 genes. This expected number is significantly smaller than the observed 80 genes . The same patterns were observed in C. japonica, C. elegans, and C. brenneri .Moreover, we noticed some genes that experienced both intron losses and intron gains Table . Among tp values are smaller than 0.05. We also found that the intron-lost genes are consistently longer than the intron-conserved genes in all the ten species . It should be noted that the number of lost introns was not counted in the intron number of the intron-lost genes.We propose that long genes might have more introns and thus be more likely to lose some of their introns just by chance. Therefore, we compared the number of introns between intron-lost and intron-conserved genes. As shown in Table Caenorhabditis clade, 4844 cases (96%) are precise intron losses. The percentage of accurate intron losses in each genome ranges from 90.2 to 100% , lost introns were significantly shorter than conserved introns . However, in the other three species , no statistically significant differences were found . Then, we performed this comparison within the intron-lost genes by combining all the intron-lost genes of the ten species into one large sample. Here, we found that the lost introns are significantly shorter than the extant introns of the same genes , we find that the lost introns are significantly close to the 3′-ends of genes than the conserved introns . Then, we confined this comparison within the intron-lost genes. We averaged the relative distances of the conserved introns and those of the lost introns for each intron-lost gene. Although the lost introns' mean and median values are consistently smaller than those of the conserved introns, statistically significant differences were not observed in any species after the BH correction for multiple comparisons . However, when all the intron-lost genes from different species are considered together, they exhibit a significant difference: the lost introns are closer to the 3′-ends of genes than the current introns of the same genes, with the median values of the relative distance to the 3′-ends of genes being 0.485 and 0.517, respectively . As an mRNA with more copies in the cytoplasm is more likely to be reverse-transcribed into cDNA, the higher expression levels of the intron-lost genes could be regarded as another piece of evidence supporting the model of cDNA-mediated intron loss.Finally, we compared the expression levels of the intron-lost genes and the intron-conserved genes using the fragments per kilobase of transcript per million mapped reads (FPKM) values to estimate the gene expression level. The median FPKM values of the intron-lost and intron-conserved genes are 5.81 and 1.62, respectively  has 130 new introns. Followed by later diverged species, there are 16 new introns in C. japonica, 13 new introns in C. elegans, seven new introns in C. brenneri, and only two new introns in C. briggsae. No new introns were detected in other Caenorhabditis species. The 130 novel introns of C. angaria were distributed in 118 protein-coding genes, with five pairs of adjacent novel introns. No adjacent novel introns were found in other Caenorhabditis species. Hoping to find the possible source sequences for the novel introns, we searched the highly similar sequences of the novel introns in the nr/nt database and the National Center for Biotechnology Information (NCBI) genome database. Unfortunately, no possible source sequences of the new introns were identified.From the 6441 discordant intron positions, we identified 168 novel introns  using Mann–Whitney U tests. The intron-gained genes have significantly more introns than with more introns than conserved genes . The difference was still highly significant even the newly acquired introns were not counted in the number of the intron-gained genes (p = 3.3 × 10−7). Meanwhile, we found that the coding sequences length and gene length of the intron-gained genes are significantly longer than the conserved genes in C. angaria .The features of the 168 newly gained introns were characterized. First, most (166) were gained without causing insertions to or deletions from the flanking exonic sequences. Second, all the 168 new introns have the gt-ag conservative splicing signals and the polypyrimidine tracts. Third, we compared the intron-loss genes with the intron-conserved genes of the same genome. Because C. brenneri and C. briggsae, we grouped all the 168 new introns as one sample in our comparison. The appearance of short, direct repeats was compared pairwisely between the conserved introns and the novel introns of the intron-gained genes. Short directed repeats ranging from three to eight base pairs were surveyed within ten bp sequences symmetrically across the exon–intron boundaries. The appearances of three to five bp short, direct repeats flanking the novel introns were significantly higher than those flanking conserved introns . No significant differences were detected in the appearance of short, direct repeats ranging from six to eight bp . No statistically significant differences in GC-content between the new introns and the conserved introns were detected . The novel introns do not have significantly different sizes from the conserved introns  but are substantially more proximate to the 3′ ends of genes .One intron gain model is that the new intron was inserted into genomic DNA during DNA double-strand break repair . EvidencC. elegans, we characterized the intron-lost genes, intron-gained genes, and intron-conserved genes by gene ontology (GO) enrichment analysis, the cutoff P-value being set to 0.01 [Taking advantage of the wealth of genomic information in  to 0.01 . The sigWith numerous studies on eukaryotic intron evolution, general patterns have been revealed. First, widespread heterogeneity in intron gain and loss rates has been repeatedly observed across both lineages and historical stages of the same lineage , 67, 68.Caenorhabditis species. First, both intron-lost and intron-gained genes had longer coding sequences, longer gene sequences, and more introns. Then, We examined five aspects of lost introns that are generally believed as evidence supporting the model of cDNA-mediated intron loss. In the ten Caenorhabditis species, the dominance of the precise intron losses and high-level expression of the intron-lost genes were all fully confirmed. When the lost introns and the conserved introns were compared within each species, only some species exhibited significant differences in the preferential losses of short introns and the preferential losses of introns close to 3′-ends of genes. However, when the intron-lost genes from different species are considered together, the lost introns are significantly shorter and near the 3′-ends of genes than the extant introns of the same genes. As we see, the lacking of significance in some species should be attributed to the small sample sizes. Of course, the biased position and frequent loss of adjacent introns are not so strong as the other three aspects, precise intron losses, preferential loss of short introns, and high-level expression of the intron-lost genes. Although the 3′-biased position was initially suggested as evidence for the cDNA-mediated intron loss [Benefiting from the unprecedented availability of genomic sequences, we carried out a large-scale, comprehensive analysis of the intron evolution of nematodes. The risk of biased observations resulting from small samples could be minimized, and a general conclusion for the intron evolution of the phylum, Nematoda, has approached. By analyzing the 104 nematode genomes, we showed that, in the aspect of intron evolution, the nematodes are a typical rather than an eccentric group of eukaryotes. Their intron densities range from less than one to more than nine species, almost as wide as previously reported across all eukaryotes [ron loss , it is nron loss , 71. TheCaenorhabditis is consistent with previous studies on other eukaryotic groups [Caenorhabditis. The source sequences are the molecular smoking gun in identifying novel introns [Caenorhabditis, like the observations of adjacent intron losses and adjacent intron gains, and the 3-biased positions of both lost introns and newly gained introns.The mystery of intron gains left in c groups , 55, 72. introns , 73. Alt introns . The fir introns , 40, 42.Caenorhabditis are similar to that observed in most eukaryotic lineages. The abnormal pattern observed by previous studies should be attributed to the small samples analyzed. This study highlights the importance of a large sample in intron evolution studies and contributes to the coming consensus on the pattern and the mechanisms of intron losses and gains.Our large-scale analysis showed that the intron evolution dynamics of the nematodes and the mechanisms of intron loss and gains in D. melanogaster, H. sapiens, and the 104 Nematoda species from Ensembl Metazoa 48, Ensembl 101, and WormBase (release WBPS14), respectively [We downloaded the genome sequences and annotation files of ectively , 74, 75.The orthologous genes of the 106 species were identified using BLAST v2.2.26  . The twoCaenorhabditis species were selected for the in-depth analysis of intron evolution, including C. angaria, C. brenneri, C. briggsae, C. elegans, C. japonica, C. latens, C. nigoni, C. remanei, C. sinica, and C. tropicalis. The orthologs of Caenorhabditis were also identified using the two-way best reciprocal BLAST hits  [The ten = 10−10) . A totalWe used CLUSTALW version 2.1)  to align.1  to alWe inferred the ancestral introns from 1577 sets of orthologs of the 104 nematode genomes using the MALIN package . We geneMALIN provides a variety of models to calculate the loss and gain rates and estimate intron content. The previous studies have shown that the model fit was significantly impacted by variations in loss rate across intron sites . MoreoveThen, we used MALIN to calculate the log-likelihood of the two models. We used 100 bootstrap rounds of the intron table to assess the uncertainty about the inferred rate parameters and the intron site histories for every node. For model comparison, the likelihood-ratio test statistic calculated asL1 is the log-likelihood of the constant rate model , and the L2 is the log-likelihood of the rate-variation rate model . The likelihood-ratio test statistic is 2967, which was then compared to χ2 distribution with df = 1, and the p-value is 0. Therefore, we rejected the constant rate model and chose the rate-variation model for calculating loss and gain rate.The Besides, we inferred the ancestral intron number of branch nodes by Dollo parsimony. Then, we scaled the number of inferred introns to intron density by,N is the present intron number by Dollo parsimony, and the 3.65 and 373 are intron density and intron number of C. elegans in the orthologous dataset, respectively. C. elegans was used as a reference because its genome has a high-quality annotation  with a posterior probability ≥ 0.99.Caenorhabditis species were aligned using CLUSTALW [The coding sequences of orthologs of CLUSTALW  and MUSCCLUSTALW . The ortDollo and polymorphism parsimony algorithm (version 3.697) identified intron loss and potential intron gain, using parameter parsimony method = Dollo, and the input tree was shown in figure S2.. The probability that a gene losses adjacent intron is Pr{d|l,r}. d: pairs of lost adjacent introns (0 ~ l-1), l: lost introns, r: conserved intron and lost introns.We first calculated the probabilities of adjacent intron losses referring to Roy and Gilbert . The proCaenorhabditis species  , the number of lost-gene were too much to calculate.We calculated the bias of adjacent intron loss of seven e) Table . For theCaenorhabditis  and counted the pair number of adjacent positions for each gene. Then, the pair number obtained in resampling the 43 intron-lost genes was compared with the observed number 26. The null hypothesis is that intron loss was a random event, and so the pair numbers obtained in resamplings should be, on average, close to 26. On the contrary, if the pair number was much smaller than 26 in most rounds of resamplings, adjacent introns tend to be lost more frequently than randomly. The probability  was the ratio of the resampling times with equal or more adjacent positions (≥ 26 pairs) divided by the total resampling times . In 100,000 times random resampling, only 11 resampling results showed that adjacent pairs were higher than or equal to 26. As a result, the probability was 11 divided by 100,000 (1.1 × 10−4). It refused the null hypothesis, so the introns were not lost randomly at different positions.Secondly, the probability of simultaneous loss of adjacent introns was estimated using the random sampling principle for ten is Table . For exaC. remanei was taken as a representative intron of the lost intron of C. latens. For the introns in C. sinica, the introns at orthologous positions in C. briggsae and C. nigoni were considered representative introns. The representative length of the C. sinica intron was the average length of the orthologous introns in C. briggsae and C. nigoni. In the length comparison between lost introns and conserved introns, representative lengths were also used for the conserved introns.The length of a lost intron was represented by the length of its orthologous intron in the most closely related species, defined by the phylogenetic relationships shown in figure S2. For instance, the intron at the orthologous position of Microhomology is defined as a pair of short, direct repeats around each end of an intron. Ten bp sequences symmetrically across the exon–intron boundaries of targeted introns between upstream and downstream were surveyed for the presence/absence of microhomology. We sequentially extracted the repeat sequences from the upstream and downstream boundary-positioned sequences and compared the similarities between the two regions. The repeat sizes were set from 3 to 8. Only the two sequences with entire consistency were regarded as homologous repeats.Caenorhabditis worms from embryo to adult can be divided into four larval stages, L1 to L4 [C. briggsae (SRR7781208), C. remanei , and C. brenneri (SRR7781211), sampled from the L4-early adult stage were also downloaded from the same database. All these RNA-seq files are listed in Additional file With abundant food, optimal temperature (20 °C), and sparse population, the development of L1 to L4 . We downL1 to L4 . The RNARNA-Seq reads were aligned to the reference genomes using TopHat algorithm v2.0.14 (using parameters—library-type fr-unstranded—min-segment-intron 10—max-segment-intron 20000) . The mapThe RNA-seq count data of early embryos tissues  were normalized to Fragments Per Kilobase per Million (FPKM) mapped reads using Cufflinks v2.2.1, an open-source software program, using the parameters—G-library-type fr-unstranded . The FPKU test (wilcox.test), Benjamini–Hochberg test (p.adjust function), and PGLS were calculated using the R packages, phytools v0.7-70 [Data calculations were performed using a series of custom Perl scripts. Statistical analysis and plotting were performed using R v4.0.3 and SPSS R26.0.0. Chi-square test (chisq.test function), Mann–Whitney  v0.7-70 , ape v5. v0.7-70 , MASS v7 v0.7-70 , mvtnorm v0.7-70 , and cap v0.7-70 . The phy v0.7-70 .Additional file 1.Table S1. The genomic and taxonomical information of the studied nematode species. Table S2. The predicted number and rate of intron losses and gains of each branch. Table S3. Correlations of intron length among Caenorhabditis species. Table S4. Data for Fig. Table S5. Data for Fig. Table S6. The detailed information of 168 cases of recently gained introns in Caenorhabditis. Table S7. GO annotations of the intron-lost, intron-gained, and intron-conserved genes in C. elegans. Table S8. The project IDs of the RNA-Seq data used in this study.Additional file 2.Figure S1. Ancestral intron densities during the evolution of nematodes. Figure S2. Rates of intron losses and gains during the evolution of nematodes. Figure S3. Phylogenetic tree of Caenorhabditis andoutgroups. Figure S4. The identities of multiple sequence alignment.


As a result, these ternary composites with almost no Ag nanoparticles wrapped by graphene possessed improved properties for the photocatalytic reduction of nitro-aromatics as compared to those with some Ag nanoparticles covered by graphene. Furthermore, this phenomenon of barrier effect caused by graphene could be found in the control reaction with metal silver as the main catalyst; this indicated that by avoiding the possible negative influence of graphene on other cocatalysts, the properties of composites with graphene-containing multi cocatalysts could be further improved.Graphene-based cocatalysts can improve the photocatalytic properties of semiconductors, but sometimes, they also function as barrier-like materials, influencing the photoactivity of composites. However, in a multi-cocatalyst system, less attention is paid to these negative effects of graphene on the performance of other cocatalysts. In this study, by adjusting the loading sequence of graphene and Ag cocatalyst on the surface of TiO By avoiding the possible barrier influence of graphene on other cocatalysts, the photocatalytic properties of the composites containing multi-cocatalysts could be further improved. Since the size of graphene sheets is usually larger than that of metal nanoparticles, there are two typical position states for these two cocatalysts on the surface of the as-modified photocatalysts, in which graphene sheets may or may not wrap the metal nanoparticles, as shown in Generally, there are three strategies to obtain graphene and metal-containing composite photocatalysts: (1) using graphene sheets to wrap the metal-loaded semiconductors,31–37 For example, enwrapping a bacteria in graphene-based sheets could protect the bacteria from outside distractions. Analogously, it could be speculated that in the graphene and metal binary cocatalyst system, when wrapped by graphene sheets  were purchased from Alfa Aesar Chemical Corporation. Tetrabutyl titanate (98%), silver nitrate (99.8%), formic acid (98%), and sodium borohydride (96%) were purchased from Shanghai Chemical Corporation. (3-Aminopropyl)-trimethoxysilane (97%) and 4-nitrophenol (99.5%) were purchased from Aladdin Chemical Corporation. All chemicals were used without further treatment.38 and small GO sheets (about 300–400 nm) were obtained through sonication and centrifugation.39,40 TiO2 spheres were synthesized using the method reported by Yin and co-authors41,42 and then modified by (3-aminopropyl)-trimethoxysilane (APTMS). The details about the preparation of small GO sheets and modification of TiO2 can be found in our previous study.36Graphene oxide (GO) sheets were prepared from natural graphite using Hummers method,2 samples (labeled as TG) were also prepared according to our previous studies. Typically, a GO dispersion  was added to a TiO2 suspension (50 mg of modified TiO2 was dispersed in 50 mL of water), which was stirred for 12 h at room temperature to form GO-wrapped TiO2 composites (labeled as TGO0.5). After this, TGO0.5 samples that were dried at 60 °C were redispersed in ethanol (50 mL) and then irradiated with ultraviolet light  for 2 h under a N2 atmosphere to obtain TG0.5 composites.Graphene-wrapped TiO2 composites were prepared using a modified photo-deposition method. For example, a AgNO3 solution  was added to a TiO2 suspension (100 mg of modified TiO2 was dispersed in 100 mL of ethanol), and the mixed liquid was irradiated with the same ultraviolet light for 2 h under a N2 atmosphere. The as-formed Ag-decorated TiO2 samples were labeled as TA0.5. The subscript in these abbreviations was the added content of GO or/and Ag, and the other graphene or Ag-containing composites with different contents of graphene or Ag were prepared through the same process.Ag-modified TiO2 spheres were replaced by TA samples, and the final composites were labeled as TAxGy . Similarly, when Ag-modified TG samples were constructed, TGO composites were used as precursors for loading Ag nanoparticles. The photo-deposition process of Ag was consistent with that of TA samples, and the as-prepared ternary samples were labeled as TGxAy.The as-obtained binary samples were used as starting materials to prepare our ternary composites. The preparation process of graphene-wrapped TA composites was similar to that of TG, but the pure TiO2-based samples (ca. 40 mg) and formic acid (30 μL) were added to a 4-nitrophenol solution  in a quartz vial. Then, the suspensions were stirred in dark for 0.5 h under N2 protection. Ultraviolet light  was used as the irradiation source. At a given time interval of light irradiation, the reaction solution was withdrawn and filtered, and the filtrate with the products was analyzed by high-performance liquid chromatography (Waters-2998).In a typical reaction, TiO43 Typically, aqueous solutions of 4-nitrophenol  and NaBH4  were added to deionized water (2.5 mL) in a quartz cuvette. Then, TiO2 with different contents of graphene and Ag (0.36 mg dispersed in 0.18 mL of water) was added. After proceeding the reaction for a certain time, the solution was filtered, and the filtrate was analyzed by UV-vis spectroscopy .Control tests were carried out according to our previous study.−1 in an air flow. Inductively coupled plasma spectroscopy  was used to investigate the content of the metal component. The zeta-potentials of samples were tested by the Malvern Zetasizer Nano-ZS90 particle analyzer. Atomic force microscopy  in tapping mode was used to measure the size of the GO flakes. X-ray photoelectron spectroscopy (XPS) studies were carried out via a Thermo Scientific Escalab 250 X-ray photoelectron spectrometer using Mg Kα (hν = 1253.6 eV) X-ray as the excitation source. Raman spectra were obtained from 200 to 2000 cm−1via a Raman microprobe (Renishaw Invia) using a 514.5 nm argon ion laser. The morphology of composites was analyzed by a transmission electron microscope  and a field emission scanning electron microscope . Photo-electrochemical measurements were carried out using the Autolab electrochemical workstation in a three-electrode cell with 0.2 M Na2SO4 as the electrolyte. Ag/AgCl in saturated KCl and Pt wire were used as the reference and counter electrodes, respectively. Indium-tin oxide glasses coated with samples were used as the working electrodes. UV light was generated by a 500 W xenon lamp , and a 0.5 M KCl solution containing 0.01 M K3[Fe(CN)6]/K4[Fe(CN)6] was utilized to investigate the Nyquist impedance.X-ray diffraction (XRD) measurements were performed using a diffractometer (Bruker D8 Advance) with Cu Kα radiation. Thermogravimetric tests were performed using a thermogravimetric analyzer (Mettler Toledo) from 25 to 800 °C at the heating rate of 5 °C min2 spheres (400 nm) were chosen as the starting materials to construct ternary composites based on our previous research.36 In our composite systems, Ag nanoparticles were decorated on the surface of TiO2 spheres (or GO-wrapped TiO2) by traditional photo-deposition methods in an ethanol solution. On the other hand, these GO sheets  that were enwrapping TiO2 (+22 mV) or Ag-modified TiO2 spheres (+21 mV) through electrostatic adsorption were reduced by a photo-reduction strategy according to previous studies.44–47As is known, there are many methods to prepare graphene and metal-containing ternary composite photocatalysts. However, less attention is paid to the potential structural difference (derived from the loading strategy) of these two kinds of cocatalysts in composites. In this study, we loaded graphene and metal nanoparticles on semiconductors by a stepwise method. The process for loading each cocatalyst was almost the same, but the loading sequence was reversed. Moreover, to enable graphene sheets to better wrap the metal nanoparticles on the surface of semiconductors, small GO sheets , some Ag nanoparticles on the surface of TiO2 were covered by these subsequently loaded graphene sheets, as shown with arrows in 2 was random; thus, not every Ag nanoparticle was covered by these carbon sheets. By contrast, since the graphene sheets were already attached on the surface of the TiO2 spheres, these subsequently loaded Ag nanoparticles were inclined to load on the surface of the composite spheres. As shown in 0.5A0.5 composites, which were not covered by the already loaded graphene sheets. In theory, it is possible that Ag nanoparticles can decorate the surface of pasted graphene due to its electron collection ability. However, these subsequently loaded Ag nanoparticles could still be considered as unwrapped  scale" fill="currentColor" stroke="none"><path d="M0 440 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z M0 280 l0 -40 320 0 320 0 0 40 0 40 -320 0 -320 0 0 -40z"/></g></svg>O) in the TA0.5GO0.5 and TA0.5G0.5 samples, it was found that these added GO sheets could be reduced through photocatalytic reduction .As demonstrated in many studies, either graphene sheets or noble metals can improve the photocatalytic reduction performance of semiconductors for reducing nitro-aromatics to corresponding amino-aromatics with the assistance of a hole scavenger; this is mainly due to their excellent photo-generated charge separation/transport abilities.ure TiO2 . Certain0.5G0.5 and TG0.5A0.5 composites. By comparison, the conversion of 4-nitrophenol using TG0.5A0.5 composite was ca. 97% after irradiation for 9 min, which was about 10 points higher than that of TA0.5G0.5. 0.5A0.5 was always higher than that of the TA0.5G0.5 samples after each cycle  was always higher than that of the graphene-wrapped Ag–TiO2 composites (TAxGy). Taking the dosage of GO precursor as about 0.5 wt% for example, when the dosage of Ag was changed from 0.1 to 1.0 wt%, the photocatalytic performance of TG0.5Ax was higher than that of TAxG0.5  and Ag (−4.72 eV),10,11 as shown in the scheme in 55 From the photocurrent results shown in 0.5G0.5 was indeed lower than that of TG0.5A0.5 samples in our system. Accordingly, the photocatalytic reactions driven by these photo-generated electrons were also disturbed in the TAG samples; this resulted in a decrease in the catalytic performance as compared to that of the TGA samples.We attribute these differences to the possible barrier effect of graphene sheets on these Ag nanoparticles that might hinder the effective contact of Ag with external environment. As demonstrated recently, graphene-based sheets can function as barrier materials owing to their inherent structure and properties.43,56–58 As is well-known, this reaction is rapid in the presence of metallic surfaces. Thus, it can be speculated that when their surfaces are enwrapped (0.5A0.5 samples could convert 92% of 4-nitrophenol after reacting for 18 min (0.5G0.5 was used as a catalyst (xA0.5 was hardly disturbed by the dosage change of GO sheets (0.5Gx composites decreased obviously with an increase in the dosage of GO sheets (2 were wrapped by these graphene sheets.Furthermore, the barrier effect of graphene sheets on these Ag nanoparticles could be further confirmed by a benchmark reduction of 4-nitrophenol to 4-aminophenol using sodium borohydride as the reductant.nwrapped , the perr 18 min , whereascatalyst . MoreoveO sheets . HoweverO sheets ; this wa2 semiconductors (Accordingly, our study has shown that in a graphene/Ag-containing photocatalysis system, the enwrapping of graphene sheets on Ag nanoparticles could be controlled by simply adjusting the loading order of these two kinds of cocatalysts on the surface of TiOnductors . Since A2 composite photocatalysts with tiny structural differences by stepwise photoinduced loading methods. When Ag was loaded on TiO2 first, the subsequently added graphene-based sheets could wrap some Ag nanoparticles. However, when the loading order was reversed, the Ag nanoparticles were not covered by these pre-coated carbon sheets. Since graphene sheets usually function as barrier-like layers, when they wrap some Ag nanoparticles in TAG samples, the performance of these Ag particles as cocatalysts is affected, especially the reactions occurring on their surfaces. Based on the results of photocatalytic reduction of 4-nitrophenol, it was shown that these TGA samples with uncovered Ag nanoparticles possessed better photocatalytic properties than the graphene-wrapped TAG composites in the case of the same dosage of these two cocatalysts. Moreover, the barrier effect of graphene in our samples could be found in the typical chemical reduction of 4-nitrophenol using Ag as the catalyst.In this study, we have prepared graphene and Ag-containing TiOOur study demonstrated that in a composite system with graphene-containing multi cocatalysts, by avoiding the potential influence of graphene on other cocatalysts, the properties of composites could be further improved, which provided us a new strategy to construct efficient composite materials in the future.There is no conflict of interest.RA-008-C8RA02268B-s001


ProKnow) used to obtain clinical diagnoses. In this work, we define ProKnow as an ordered set of information that maps to evidence-based guidelines or categories of conceptual understanding to experts in a domain. We also introduce a new dataset of diagnostic conversations guided by safety constraints and ProKnow that healthcare professionals use (ProKnow-data). We develop a method for natural language question generation (NLG) that collects diagnostic information from the patient interactively . We demonstrate the limitations of using state-of-the-art large-scale language models (LMs) on this dataset. ProKnow-algo incorporates the process knowledge through explicitly modeling safety, knowledge capture, and explainability. As computational metrics for evaluation do not directly translate to clinical settings, we involve expert clinicians in designing evaluation metrics that test four properties: safety, logical coherence, and knowledge capture for explainability while minimizing the standard cross entropy loss to preserve distribution semantics-based similarity to the ground truth. LMs with ProKnow-algo generated 89% safer questions in the depression and anxiety domain (tested property: safety). Further, without ProKnow-algo generations question did not adhere to clinical process knowledge in ProKnow-data (tested property: knowledge capture). In comparison, ProKnow-algo-based generations yield a 96% reduction in our metrics to measure knowledge capture. The explainability of the generated question is assessed by computing similarity with concepts in depression and anxiety knowledge bases. Overall, irrespective of the type of LMs, ProKnow-algo achieved an averaged 82% improvement over simple pre-trained LMs on safety, explainability, and process-guided question generation. For reproducibility, we will make ProKnow-data and the code repository of ProKnow-algo publicly available upon acceptance.Virtual Mental Health Assistants (VMHAs) are utilized in health care to provide patient services such as counseling and suggestive care. They are not used for patient diagnostic assistance because they cannot adhere to safety constraints and specialized clinical process knowledge ( Mental health disorders such as Major Depressive Disorder (MDD)ProKnow). Incorporating ProKnow as an additional component in convAI can steer the natural language generation (NLG) to capture information relevant to clinical diagnoses and constrain the VMHA from steering the topic of conversation into unchartered territory. This is defined as . Further, the VMHA would be able to explain its generation in terms of clinical concepts and processes that patient responses map to. In this research, we would focus on follow-up question generation, a task within conversational AI that is targeted toward improving engagement between agent and user I think you should” to the user's query “Should I kill myself?” raised concerns for the immediate adoption of GPT-3-like language models in mental healthcareSafety Lexicon as a dictionary of concepts that a clinician would be able to relate to a mental health condition. For instance, concepts like “anxiety,” “anxiousness,” “anxious,” “agita,” “agitation,” “Prozac,” “sweating,” and “panic attacks” in question are safe as they would infer AD. Concepts like “depression,” “depressed,” “antidepressant,” “depressant,” and others would describe MDD. ProKnow-driven NLG enhances medical knowledge capture, and leads to considerable reduction in harmful conversation (safety). Since ProKnow-driven NLG leverage questionnaires or clinical guidelines, every generation can be evaluated for explainability.Current research in question generation by large language models is at the mercy of datasets that need to represent safe and valid responses for adequate quality control. Nabla, a Paris-based Healthcare Technology firm, leveraged GPT-3 for preventive care. To their surprise, GPT-3's response, “ProKnow-data and demonstrate a feasible ProKnow-algo for safety-constrained and explainable mental health diagnostic assistance.In this research, we create a dataset We want to highlight the quality of our dataset. Achieving a high-quality dataset for sensitive domains like Mental Health is a cumbersome task. We made sure that our dataset achieved substantial annotator agreement before we could explore the development of methodology. This distinguishes us from prior mental health datasets with far less annotator agreement. Since the dataset defines a specific task of achieving safety and explainability through process knowledge, we define an improvement over the existing language models  in their use in VMHAs for mental health diagnostic assistance. Incorporating such clinical process knowledge and making the corresponding algorithmic modifications to language modeling methods addresses the following research questions:ProKnow-data impose constraints on conceptual flow on questions generated by ProKnow-algo-based LMs and pre-trained LMs?RQ1: Adherence to Process Knowledge: Does ProKnow-algo constrain the safety of the generated questions? Additionally, does augmentation of a Safety Lexicon enhance the safety of ProKnow-algo's question generation?RQ2: Patient safety in conversation: Does ProKnow-data help the explanation of ProKnow-algo's question generation? Further, does semantic annotation of ProKnow-algo's question generation using KB enhance explanation quality as judged qualitatively by clinicians?RQ3: User and clinician-focused explanations: We define a generated follow-up question to be explainable if it is easily understood by clinicians and gathers informative responses from the patients. Do the tags in It is important to note that along with the data and methods, the evaluation metrics also need domain adaptation for ensuring domain user satisfaction, i.e., clinicians in this case , is safe (Average Unsafe Matches), and is explainable (Average Knowledge Context Matches). Through the constructed We identify related work across three aspects, datasets, algorithms, and documented and verifiable human biases.ProKnow into the dataset. Liang et al.  contextual passage and (b) a ground truth answer. This scenario is very similar to SQUADv1, Natural Questions, WebQuestions, etc.  approaches have tried to model a generation process ProKnow by rewarding the model with adherence to ground truth using general language understanding evaluations (GLUE) task metrics such as BLEU-n and ROUGE-L. However, they do not ProKnow-algo (Section 4) that employs heuristics enabling ProKnow guided control over sentence generation for use in sensitive domains such as Mental Health Triaging. Heuristic 1  and rank, which regulates the order in which the generated questions appear. Without these heuristics, generated questions can lose clinically relevant semantics and order. Heuristics 2 (refer to point 3) ensure the generated question has entities in the mental health knowledge base . Given the user's content, this enforces the preservation of clinical context in the generated question. Heuristic 3 (refer to point 4) include semantic lexicons built from PHQ-9 and the GAD-7, with support from involved clinicians. The purpose of lexicons is to ensure that terms that refer to question 1 in the questionnaire are present in the generated question. Without this heuristic, it would not be easy to rank the generated question. Prior studies like Retrofitting  and Anxiety Disorder (AD). The process of creating the dataset starts with the existing questionnaires used by clinicians to judge the severity of MDD and AD in patients. These were the Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder (GAD-7). PHQ-9 has nine questions, and GAD-7 has seven questions. We leverage Google SERP API and Microsoft BING API to extract People Also Ask (PAA) questions. People ask these questions on Google Search or Microsoft Bing Search Engine. The naturalness of these questions drives our motivation to enhance the sensitivity and specificity of the PHQ-9 and GAD-7 scales. The challenges concerning the safety and explainability aspect of PAA questions urged the need for domain experts to curate the list of potential questions extracted from PAA. Therefore, for each question in either PHQ-9 or GAD-7, a list of 120 additional questions (16*120: 1920 questions) was extracted, out of which 40 on average per PHQ-9/GAD-7 questions were kept for evaluation and further curation by domain experts. The first step of filtering was performed by students having research experience in mental healthcare research. Approximately 640 questions were sent to domain experts, a group of 3 personnel: one senior psychiatrist (SP) and two resident psychiatrists (RPs). The annotation task was designed so that two RPs (RP1 and RP2) would annotate the questions for relevance and the order in which they should be asked within a question from PHQ-9/GAD-7. The first phase of annotation yielded agreement scores of 0.72 (SP and RP1) and 0.713 (SP and RP2) (Cohen's kappa), which is below the acceptance threshold defined by mental health professionals. Krippendorff agreement was 0.68 (SP and RP1) and 0.667 (SP and RP2) when checking the agreement on the ordering of the questions. After that, SP defines the guideline for annotation following SCID, which denotes Structured Clinical Interviews for DSM-5. It is a handbook of questions from which questionnaires like PHQ-9 and GAD-7 are created. SCID-defined guidelines exemplify ProKnow and reflect on clinical process knowledge embedded in PHQ-9 and GAD-7. With the use of SCID to streamline the annotation process, SP and RPs found information pertinent to MDD and AD, which can contextualize the PAA questions better than simply finding PAA questions from PHQ-9 and GAD-7. Hence, we  repeated the process of extracting PAA questions. This time, we augmented the questions with contextual information provided by SP. We extracted 640 questions across 16 questions in combined PHQ-9 and GAD-7, which were higher in quality. The annotation agreement on these questions measured 0.805 (Cohen's kappa), which is substantial compared to the first round. The agreement was measured in an independent pairing of SP and RP, giving two agreement scores: 0.805 (SP and RP1) and 0.811 (SP and RP2). In this annotation round, the Krippendorff agreement score went to 0.733 (SP and RP1) and 0.748 (SP and RP2) from 0.68 and 0.667, respectively.The D to be a triplet 〈x, Y, P〉, where x is a question from a medical questionnaire (PHQ-9 or GAD-7), Y is a set of questions that elaborate on x (by RPs), and P, the process knowledge, is a set of  tuples corresponding to the elaboration questions in Y (by an SP). An example triplet 〈x, Y, P〉 is seen in We define each data point in our dataset ProKnow-data.We created a sizeable dataset with MDD and AD-defined questions and information from SCID. However, more is needed in training a convAI agent, which requires large-scale datasets. Hence, we are challenged with two hurdles: (a) How to create a richer dataset that would enable a convAI to generate information-gathering questions whose responses from patients would be assistive to the psychiatrist? Which we completed with support from mental health professionals, and (b) How to scale it to a larger number of samples? To address (b), we expand this dataset using a T5 paraphrasing model to obtain 800,000 data points that contain conversations similar to the annotated datasetProKnow-data, we propose a search algorithm mounted over pre-trained LMs that explicitly compares the generated question against the ProKnow-data ground-truth questions, Safety Lexicon, and a knowledge base (KB). This introduces an additional loss function along with cross-entropy (CE) loss that promotes medical knowledge capture and safety. Further ProKnow-algo enforces conceptual flow in question generation, thus capturing precise, relevant information using the rank in ProKnow-data. The additional “loss function” is optimized to ensure that the question generation follows ProKnow. It can be seen as choosing the right branch on a process flowchart where the branching decision tests for the number of ProKnow violations per branch (and chooses the minimum one). Thus, even if a response is better in terms of achieving a higher gradient on the standard CE loss surface, the nudge in that direction may be unsafe due to distributional semantics improvements not coinciding with what is a clinically correct and safer response.The parametric knowledge within pre-trained language models (LMs) have often been exploited in downstream task through distillation , the tag and rank of Qk, KB, and safety lexicon (L) to compute a score that reflects on safety, medical knowledge capture, and explainability of the generated question. The KB comprises comprehensive mental health lexicons that have been built using PHQ-9, GAD-7, and other questionnaires  to signify the end of the questions set for a query x similar to a 〈EOS〉 token. QG-LSTM: Qk is passed as input to the Transformer Type 1, which generates the first token for EOS〉 token is seen. Transformer Type 1 stops generating questions when the end of list sentence is seen  to signify the end of the questions set for a query x similar to a 〈EOS〉 token.QG-Transformer (QG-T): This model has the identical architecture to QG-LSTM, except that the LSTMs are replaced with Transformers. Our experiments find that the QG-T and T5-FT (Fine-tuned) perform best. On the Utility of Algorithm 1: Through intersectionality with the knowledge base (KB) shown in point 3 of ProKnow-algo, we seek specificity in the generated questions, as shown in the following examples. The generated question “Do you feel anxious or nervous?” is better than one from the vanilla transformer/sequence-to-sequence model “Do you feel afraid of something?.” Another example from the depression context is “Is depression medication helping with the things bothering you?” is better than “how many antidepressants are you taking for the things that are bothering?.” (b) Through intersectionality with the Lexicon, as shown in point 4 of ProKnow-algo, we made sure the generated questions are as diagnostic as the medical questionnaire. For instance, “How long have you struggled with sleep difficulties” is clinically more relevant than “Would you like to know about some major sleep disorders?.” Another example of the generated question by including point 4 in ProKnow-algo is “how often did you miss the medication?.” It is information-seeking and more relevant compared to “do you know about prozac?.” Through Tag and Rank Heuristic, as shown in point 2 of ProKnow-algo, we made sure the questions have a conceptual flow that follows the medical questionnaires. We reviewed prior studies that utilize principles of natural language inference to achieve conceptual flow. For instance, RoBERTa trained on SNLI and MNLI datasets are used in downstream applications requiring flow in question generation or response generation  or attention matrix (QG-T) with numerical representation of concepts in KB.To validate the two novel architectures of We introduce three evaluation metrics in this research to assess the model's performance in capturing knowledge context, being safe, and being explainable in question generation.This is defined as the number of named entities, n-grams, and longest common subsequence in the generated questions that do not have an exact match or partial match with the concepts in the safety lexicon. This is computed as an average over all the model-generated questions against the concepts in the safety lexicon . Such a t(x) denote the tokens in the generated text x. We define AUM as the set intersectionFormally, let Thus, lower is better.t-test over multiple rounds of training and cross-validation results. We do the same for AUM. Formally, we define AKCM asFurther to AUM, AKCM focuses specifically on triples comprising of subject, predicate, and object extracted from the generated question. Thereafter, computing word mover distance between the embedding of triples ) and concepts in the lexicon (BERT(concepts)). The range of AKCM is between 1.0 and 3.0, and the higher AKCM, the better the model. However, we found that not always a higher AKCM signifies a better model as a small addition of a meaningful concept can increase AKCM. Thus, we perform a statistical student x where ASRE for a sequence S = {xi}, asThis metric measures the model's tendency to generate questions following causal tag and rank. For example, if Q1, Q2, Q3, and Q4 are generated in the correct order for a patient, then the total rank is 4. For another patient, if Q2, Q1, Q3, and Q4 are generated, only then Q3 and Q4 are in the correct order, giving a rank of 2. The range of ASRE is 0.0 to 1.0, where lower is better. Further, we used Wilcoxon signed-rank test to measure the statistical significance of the model's generated sequence of questions over multiple cross-validation turns. Formally, we define xi represents a question in the generated sequence and i is its position in the sequence. R(xi) denotes the classifier tag for xi given previous questions in the sequence, trained on ground truth positions from the ProKnow-data.where In ProKnow-algo to every variant of seq2seq and transformer model to show generalizability. Multiple statistical tests were performed to achieve consistency and stability in the model outcome. Large language models are vulnerable to overshoot, leading to erroneous and sometimes harmful results. The results of hypothesis tests are acceptance and rejection of the null hypothesis from the point of the p-value  are finicky, as shown by recent studies  “Did you check your dopamine?,” (b) “Do you feel your brain is affected?,” and (c) “Did you intend to indulge in risky behaviors?.” Whereas, QG-T† selects from the following top-3 generated questions: (a) “What does lack of pleasure mean to you?,” (b) “Do you feel little pleasure doing things you used to enjoy?,” and (c) “How long have you struggled with lack of interest in things you used to enjoy?.” AUM measured generations from QG-T† to be safer than QG-T because terms like dopamine, brain, risky behaviors do not show up in the safety lexicon. Likewise, among the generated, “Do you feel irritable?” and “Do you feel easily annoyed or destructive?”, the former scored a higher probability of being safe. This is because destructive is associated with more unsafe phrases and is not present in the Safety Lexicon. Thus, the ProKnow-algo steered the generation to the former sentence.The questions generated using ProKnow-algo enforced checks on conceptual flow in pre-trained LMs in the last hidden state before question generation. In the following example, a user mentions that “He is bothered by trouble concentrating while reading the newspaper or watching television,” then T5-FT generated question in the following order: (1) “Do you have a hard time falling asleep and staying asleep?,” (2) “Do you feel like you sleep a lot but are still tired?,” (3) “Would you like to know about some major sleep disorders?, and (4) “Would you like to know about the 5 major sleep disorder types?.” If you observe carefully, these questions have following tagged order: Symptoms→Symptoms→Yes/No (Also an irrelevant generated question). Whereas the questions generated by T5-FT† are in the following order: (1) “How many hours of sleep do you get on average each night?,” (2) “Do you feel like you sleep a lot but are still tired?,” (3) “How long have you struggled with sleep difficulties,” and (4) “Have you been diagnosed with any sleep disorder?.” The process followed by these questions is Cause→Symptoms→Cause and Symptoms→Diagnosis, which is a process-guided question generation. Further, among the generated text, “Do you feel nervous often?” and “Do you feel anxious about something?,” the former scored a higher probability of being the next sentence. However, as the former is associated with a tag of Degree/frequency and the latter is associated with a tag of Yes/No, the ProKnow-algo leads the algorithm to choose the latter sentence. Overall, 82% of the time, the ProKnow-algo-based question generations were safe, explainable, and followed the clinical guidelines.ASRE recorded that questions generated using models with † had almost 96% reduction in ordinal error. This implies that rank 2. This is erroneous as the former is of rank 1. Thus, we see that due to the lack of variety in the phrasing of certain sentences generated, the rank in the heuristic is wrongly computed. Further, among the generated rank 2 and the latter scored a rank 1. This is erroneous as the former is of rank 1. Once again, we see that the rank in the heuristic is wrongly computed. In our experiments, we see a negative outcome 18% of the time, which implies we need to conduct more studies with more diverse datasets. These errors occur when sentence generation requires relatively high semantic variations.Among the generated text, “Do you feel nervous?” and “Do you feel nervous often?” both sentences scored a ProKnow-algo and data and compare the text generation quality against the T5 model fine-tuned on the ProKnow-data. We see that the prototype's generations are safer regarding the evaluation metrics defined in Section 5. The ProKnow-algo is incorporated in the question generation component of the mental health chatbot demonstrated here: ProKnowDemo. The user responses in the demo were simulated using the annotated dataset from Reddit conversations on mental health subreddits  is critical in making AI safe and explainable. Existing pre-trained language models have yielded out-of-context or factually incorrect resultsWe implemented our method using PyTorch on top of the HuggingFace Transformer Library (Wolf et al., ProKnow-data construction took considerable effort and covered depression and anxiety. Creating a similar dataset for other mental health conditions like schizophrenia and suicide can be more challenging. This also implies a huge scope for improvement and extension in ProKnow-driven mental health assistance.Our current research focuses on targeted question generation, specifically to train the deep language model to follow a conceptual flow. Conversation generation is an active phenomenon requiring appropriate and safe response generation. Although our proposed approach offers several advantages over the existing models for question generation in the mental health domain, there are also several limitations. Since the main idea behind our approach is using the “process knowledge,” it can be computationally expensive and time-consuming to generate the follow-up questions. Further, we demonstrated the efficacy of our approach in a closed-domain task, its utility in an open domain hadn't been explored. The ProKnow-algorithm. The Senior Psychiatrist gave the medical guidelines for constructing this dataset by adhering to the PHQ-9 and GAD-7 questionnaires. Further, two Resident Psychiatrists from different hospitals created detailed questions. The dataset is annotated using expert annotators. Possible biases in our model predictions could be due to the annotation techniques and are not deliberate. The content concerning AD and MDD results in unfavorable real-life interaction scenarios. However, the current research aims to establish a claim that clinical process knowledge can be infused into deep language models to make them explainable and safe. In our algorithm, we mitigate the unfavorable cases as unfavorable sentences are not diagnostically acceptable to clinicians using AI-based assistance. The ProKnow-data will be made publicly available by following best practices of ethical research (Benton et al., This paper provides a novel mental health dataset constructed using our proposed The original contributions presented in the study are included in the article/KR, VR, and MG were involved in the development of the research ideas, code, and datasets in collaboration with our clinical partners duly acknowledged. MS specifically contributed in coding baselines and conducting extensive experiments. AK and AS played advisory roles in shaping the research goals and objectives as well as providing valuable feedback toward writing of the manuscript. All authors contributed to the article and approved the submitted version.


Rationale: Idiopathic pulmonary fibrosis (IPF) is characterized by mitochondrial dysfunction. However, details about the non-mitochondrial enzymes that sustain the proliferative nature of IPF are unclear. Aconitases are a family of enzymes that sustain metabolism inside and outside mitochondria. It is hypothesized that aconitase 1 (ACO1) plays an important role in the pathogenesis of IPF given that ACO1 represents an important metabolic hub in the cytoplasm.Objectives: To determine if ACO1 expression in IPF lungs shows specific patterns that may be important in the pathogenesis of IPF. To determine the similarities and differences in ACO1 expression in IPF, bleomycin-treated, and aging lungs.Methods: ACO1 expression in IPF lungs were characterized and compared to non-IPF controls by western blotting, immunostaining, and enzymatic activity assay. ACO1-expressing cell types were identified by multicolor immunostaining. Using similar methods, the expression profiles of ACO1 in IPF lungs versus bleomycin-treated and aged mice were investigated.Measurements and main results: Lower lobes of IPF lungs, unlike non-IPF controls, exhibit significantly high levels of ACO1. Most of the signals colocalize with von Willebrand factor (vWF), a lineage marker for vascular endothelial cells. Bleomycin-treated lungs also show high ACO1 expressions. However, most of the signals colocalize with E-cadherin and/or prosurfactant protein C, representative epithelial cell markers, in remodeled areas.Conclusions: A characteristic ACO1 expression profile observed in IPF vasculatures may be a promising diagnostic target. It also may give clues as to how de novo angiogenesis contributes to the irreversible nature of IPF. One of the pathognomonic histological features that distinguish IPF from other fibrotic lung diseases is aberrant cell proliferation and metabolism; targeting them is a reasonable strategy to develop new therapies . To dateACO1 and Aconitase 2  encoded by ACO2. In addition to the enzymatic roles in the cytoplasm, ACO1 also is known to bind to mRNAs of specific genes and maintain iron homeostasis . Mammalian cells possess two distinct isoforms of aconitase encoded by different genes: Aconitase 1  encoded by eostasis . Emergineostasis . Howevereostasis . Howevereostasis .Please see the online supplement for details of materials and methods.The following cell lines and cell types were propagated using established methods or according to the manufacturer’s instructions. A549, H441 cell lines, Human Bronchial Epithelial Cells , Human Lung Microvascular Endothelial Cells , T7 cells , C22 cells , and primary lung fibroblasts.Primary fibroblasts were isolated from the lungs of WT mice at 7–9 weeks of age using enzymatic digestion based on published techniques with some modifications .WT are a gift from Dr. Pascale Fanen . Transfection of the plasmids was performed using Lipofectamine 2000  as described previously . pcDNA3.1/V5-His-TOPO and pcDNA3.1/V5-His-TOPO-pro-SPCeviously .Age (7–9 weeks) and sex-matched C57BL/6J mice were utilized for the bleomycin fibrosis model. 50 μl of sterile phosphate-buffered saline (PBS) (control group) or bleomycin  dissolved in 50 μl of PBS was intratracheally administered. Lung samples were collected as described previously using an institutionally approved protocol .The activity of aconitase in the lung homogenate was measured using a commercially available enzymatic assay kit .This study involving human tissues adheres to the Declaration of Helsinki and has received approval from the University of South Florida Institutional Review Board (IRB) charged with oversight of human studies (IRB protocol Pro00032158). All human explant lung tissues were obtained from subjects with end-stage lung disease undergoing lung transplantation at Tampa General Hospital, a University of South Florida Morsani College of Medicine affiliated institution, Tampa, Florida . All patProtein lysates were prepared from human lung tissues, cell cultures, and mouse lungs based on established protocols as described in the online supplement.Immunohistochemical (IHC) staining was done based on standardized protocols . After Ip/cgi-bin/NLS_Mapper_form.cgihttp://nls-mapper.iab.keio.ac.j)  . The preorm.cgi) .p-value was adjusted using Bonferroni’s method when multiple comparisons were performed on data comprised of more than two groups. GraphPad Prism Version 7.0  was used for analysis.Student’s t-test and Mann–Whitney U test were used, respectively for parametric and non-parametric comparisons. The Previous studies show increased cis-aconitate in IPF . It is hLung sections from IPF and non-IPF were immunohistochemically labeled for ACO1 and lineage markers, vWF and E-cadherin (E-cad), to identify the cell types that highly express ACO1 . The resPrevious studies demonstrate that ACO1 assumes either an enzymatic or RNA-binding form based on extracellular factors such as iron and oxygen levels . The relPro-fibrotic phenoconversion of type II AECs is implicated in IPF pathogenesis . The expBleomycin (BLM)-induced pneumopathy in mice is a widely used fibrosis model . ImmunohAging is associated with decreased lung regeneration . StudiesNext, the expression patterns of ACO1 were characterized. Immunohistochemical double staining for ACO1 and E-cad was performed on lung sections from 7-9-weeks-old and 22-mth-old mice. The results show that the signal intensity of ACO1 in the bronchiolar epithelium of 22-mth-old mice  is compaTherefore, western blotting, using whole lung lysates from mice at different ages, was performed to quantify the expressions of E-cad and pro-SPC, both of which are representative markers that reflect the integrity of type II AECs . The resTo explore this concept, the expressions of cldn10 in lung lysates of mice at different ages were quantified. Results show that expression of cldn10 increases in an age-dependent manner, supporting the hypothesis that loss of functionally mature type II AECs and emergence of type II AEC-committed club cells is likely age-associated.The role of ACO1 in IPF has not been previously investigated. For the first time, these data demonstrate that ACO1 expression and aconitase activity correlate with fibrogenesis in IPF. Furthermore, ACO1 expression is localized to the small vessels in the fibrotic areas which suggests that ACO1 may accelerate vascular endothelial cell (VEC) proliferation in IPF .de novo angiogenesis in fibrotic areas of IPF lungs is a compensatory response or plays a causative role in disease progression  ACO1 actively mediates glutaminolysis and reductive carboxylation in proliferating vascular endothelial cells and ii) only specific linear portions of the mitochondrial TCA cycle actively work to fulfill the anabolic requirements  Supplem.The data presented in this study demonstrate that the specific expression patterns of ACO1 in fibrotic areas of IPF lungs, as manifested by immunohistochemical staining, are not observed in non-IPF chronic lung diseases. Second, the higher expression of ACO1 in the lower lobes of IPF lungs  is assocThis study has certain limitations. First, it remains unclear whether high levels of ACO1 in enzymatic form change the behaviors of VECs. Verifying this is difficult since ACO1 appears in two different forms, enzymatic or RNA-binding, depending on the environment. Second, the sample size is limited. Nevertheless, hypothesis-generating observations underlie the foundations for future validation studies. Furthermore, the site-specific heterogeneous expression patterns of ACO1 have been validated by collecting multiple sample blocks from each IPF subject .In conclusion, ACO1 expression and aconitase activity parallels the severity of fibrosis in IPF. Furthermore, it is hypothesized that aberrant ACO1 expression in vasculatures is a key event in IPF . These d


In this study, the atomistic-scale mechanisms affecting the interfacial stability of a thermoplastic polymer/graphene oxide interface are investigated using molecular dynamics simulations. Different combinations of thermoplastic polymers (polyethersulfone (PES) and polyetherimide (PEI)) and graphene oxides modified with –O–, –OH, and –COOH are prepared. PES is found to be more strongly stabilized with modified/functionalized graphene oxide in the order of –COOH, –OH, –O–, which is opposite to the stability order of PEI. Our results suggest that these orders of stability are governed by a balance between the following two factors resulting from electrostatic interactions: (1) atoms with a strong charge bias attract each other, thereby stabilizing the interface; (2) the excluded-volume effect of the functional groups on graphene oxide destabilizes the interface by preventing  Recently, carbon fiber-reinforced thermoplastic polymer composites (CFRTPs) have attracted significant attention for application as structural materials in automobiles ,6,7,8,9.The performance of CFRTPs not only depends on the properties of reinforcing fibers and matrix polymers but also on their interfacial properties ,12,13,14Various simulation studies have been conducted to clarify the thermomechanical properties of polymers ,22,23,24As indicated by the aforementioned studies, the MD simulation used in this study has certain advantages over the finite element method (FEM), which is usually used to investigate the mechanical properties of a composite. MD simulations calculate the thermodynamic properties based on atomic motion, whereas FEM requires the constitutive law of a material expressed as a continuum body. Therefore, MD simulations enable us to investigate the dependence of the interfacial strength on the material species at the atomistic scale . The purThe remainder of this paper is organized as follows. The next section outlines the procedures used to construct the composite model and its equilibrium structures using MD simulations. In the third section, the simulation results and corresponding discussions are presented. Finally, concluding statements are provided in the fourth section of this manuscript.MD simulations were employed to calculate the energy at the interface between the graphene sheets and polymers. For this purpose, the layered structure of the graphene sheets and polymers was constructed using the following procedures.12H8O3S)n, degree of polymerization n = 10) and PEI ((C37H24O6N2)n, degree of polymerization n = 4) were constructed using Marvin Sketch [First, four types of graphene sheets and two types of matrix polymers were fabricated separately. Atomistic models of a pure graphene sheet and three types of functionalized graphene sheets modified with –OH, –O–, and –COOH were prepared using Graphene Builder in PolyPerGen ,47. Eachn Sketch  and Polyn Sketch , and then Sketch . The elen Sketch ,52.Next, three graphene layers were placed at the center of the simulation cell with interlayer distances of 0.335 nm. Only pure graphene was used as the second layer, whereas pure or functionalized graphene sheets were used as the first and third layers, wherein the side containing functional groups faced outward. For the matrix portion of the composite, PESs or PEIs were randomly arranged above and below the graphene layers such that the density of atoms in the simulation cell was about 0.3 g/cc. It indicates the system is stretched in the z-direction compared to the equilibrium state; here, the z-axis direction is defined as the direction perpendicular to the graphene plane. The total number of atoms in the simulation cell was approximately 30,000.The relaxation calculation procedure used to obtain the equilibrium structure of the composite models is described below.First, structural optimization was performed to minimize the internal energy of the system while maintaining the volume of the system at a constant value.NVT and NPT ensembles for 200 ps and 1 ns, respectively, where N denotes the total number of atoms, V denotes the system volume, P denotes the pressure, and T denotes the temperature. In the relaxation under an NPT ensemble, a pressure of 1 bar was applied in the XY-plane directions, and a pressure of 10 bar was applied along the z-axis direction to bring a lower density system closer to a system with appropriate density.Next, the equilibrium structure at 600 K was obtained by stepwise relaxations under T = 300 K) was obtained by stepwise relaxation as follows: In the first step, the temperature of the system was decreased from 600 K to 300 K at a cooling rate of 6.0 × 109 K/s under an NVT ensemble. Note that this cooling rate is much greater than that in the usual experiment (tens K/hour). The effect of the different conditions on the structure eventually disappears with sufficiently long relaxation calculations. Next, a relaxation calculation was performed for 200 ps under an NVT ensemble at T = 300 K. The equilibrium structure was obtained by relaxation for 10 ns under an NPT ensemble at T = 300 K and P = 1 bar along with the xyz-axis directions. The equilibrium structures of the composite model composed of PEI and graphene with -OH are illustrated in Finally, the equilibrium structure at room temperature  between the functional groups in functional graphene and each atom component in the polymer are presented in In the case of PEI, the trend of charge observed in the magnitude of interfacial energy is opposite to that observed for the PES. For example, the interfacial energy is the highest with FGR–COOH , although the corresponding RDFs demonstrate sharp peaks owing to electrostatic interactions between the functional groups, as mentioned above. For PEI, the interfacial energy is the lowest with FGR–O despite the absence of noticeable peaks in the RDF compared to other combinations, as shown in The interfacial stabilities of the different composite models are presented in In conclusion, there exist two mechanisms via which the functional groups introduced into graphene sheets contribute to interfacial stability. First, a functional group with a larger charge bias attracts the atoms in the polymer, which stabilizes the interface. Second, a functional group with a large excluded volume prevents the formation of Atomistic-scale mechanisms that determine the interfacial stability between thermoplastic polymers and graphene oxides are important for the development of CFRTPs with excellent mechanical properties. In this study, the interfacial energy was evaluated using full atomistic MD simulations. We prepared eight species of layered structures of CFRTPs by combining two types of thermoplastic polymers, namely PES and PEI, and four types of graphene sheets modified with and without different functional groups, including –O–, –OH, and –COOH. Based on the MD simulation results, the stability of the interface between PES and functionalized graphene decreased in the order of –COOH, –OH, and –O. This is in contrast to the interface stability with PEI, which decreased in the order of –O–, –OH, and –COOH. RDF analysis suggested that electrostatic interactions between atoms with a stronger charge bias around the interface play an important role in determining the order of the interfacial stability of PES. The interface between PES and graphene-modified with –COOH was found to be the most stable among the various species investigated. This is attributed to the attractive forces between the atomic combinations of S and H atoms in PES and O atoms in FGR–COOH, which have positive and negative charge biases, respectively. Furthermore, our results also suggest that the functional groups of FGR prevent


Sarcoidosis is a multisystem granulomatous disorder that is characterized histologically by noncaseating granulomas. Typically, it presents clinically in young adults with initially one or more of the following: hilar lymphadenopathy, pulmonary reticular opacities, and skin, joint, and/or eye lesion. Radiographic findings commonly include bilateral hilar and mediastinal lymphadenopathy and pulmonary reticular opacities but may resemble pneumonia with airspace consolidation and opacities. We report a case of sarcoidosis that presented as a persistent case of pneumonia. This case is a reminder that common diseases such as pneumonia are not always what they seem, and diseases such as sarcoidosis that have specific characteristics may not present traditionally each time. Sarcoidosis is a multisystem granulomatous disorder that typically presents in adults between the ages of 20 and 60 . It is c2 of 93% on room air, and body mass index of 47. Laboratory examination was significant for a white blood cell count of 9.3 × 103/µL and an elevated CRP of 5.9 mg/dL and a D-dimer of 4.21 mg/L. Repeat chest X-ray and CTA showed continued mediastinal and hilar lymphadenopathy with the consolidation of the right middle lobe and no evidence of pulmonary emboli  13 days before admission. He was diagnosed with a flare of childhood asthma and was given oral steroids and an albuterol inhaler. He presented to the Emergency Department (ED) eight days prior to admission with worsening symptoms. At the ED a CTA was performed that showed mediastinal and bilateral hilar adenopathy consistent with sarcoidosis or lymphoma and right middle lobe consolidation consistent with pneumonia  scan was performed, and the findings included extensive lymphadenopathy which was suspicious for sarcoidosis. Follow-up CTA was also performed and showed unchanged hilar and mediastinal lymphadenopathy with resolved right middle lobe consolidation. A decision was made to biopsy the lesions with a mediastinoscopy, and pathology revealed non-necrotizing granulomatous inflammation for a final diagnosis of sarcoidosis.Sarcoidosis is a multisystem granulomatous disorder that typically presents in young adults between the ages of 20 and 60 . SarcoidSarcoidosis tends to have a distinct clinical presentation that includes initially one or more of the following findings: bilateral hilar adenopathy, pulmonary reticular opacities, and skin, joint, and/or eye lesions. The disease most frequently involves the lung but has also been shown to involve a range of organs, including, but not limited to, the skin, lymph nodes, eyes, liver, muscle, kidneys, nervous system, heart, and kidneys. When the disease involves the lungs, it can commonly present with cough, dyspnea, chest pain, fatigue, weight loss, malaise, and fever. Furthermore, because it can involve so many different organ systems, patients may also have symptoms such as visual changes, skin lesions such as erythema nodosum, dry eyes or mouth, palpitations, joint pain, muscle weakness, parotid swelling, and syncope .Pulmonological radiographic findings for sarcoidosis can be classified by typical and atypical characteristics -5. ImagiWhen airspace consolidation and opacities are seen in sarcoidosis, it is called alveolar sarcoid -5. AlveoLaboratory evaluation of sarcoidosis often reveals leukopenia, hypercalciuria, a slight elevation in serum alkaline phosphatase, hypergammaglobulinemia, an elevated erythrocyte sedimentation rate, and an elevated CRP ,6. SerolOur patient had some characteristics of worsening pneumonia as well as a few characteristics of sarcoidosis. Because the patient only had radiographic findings of pneumonia, no leukocytosis, and negative blood and BAL cultures, our patient likely had an acute exacerbation of sarcoidosis with typical and atypical pulmonological radiographic findings. However, the patient’s condition did improve with intravenous antibiotics, his CRP levels progressively declined, and his right middle lobe consolidation did improve, which points to a unique presentation of sarcoidosis.There is no definitive diagnostic test for patients with sarcoidosis ,6. ThereIn cases such as ours, it is important to take all findings into consideration and perform appropriate testing to help exclude other diseases that might present similarly to sarcoidosis. Our case was a unique presentation of sarcoidosis with the patient presenting with sepsis and only a few of the classical findings of sarcoidosis. Our patient had worsening pneumonia-like symptoms as well as airspace consolidation on imaging. This presentation is an example of how uncommon diseases such as sarcoidosis may present like common diseases such as pneumonia.