Deep Sequencing Research Articles

Metagenomic Study Reveals Phage–Bacterial Interactome Dynamics in Gut and Oral Microbiota in Pancreatic Diseases

Individuals with pancreatic-related health conditions usually show lower diversity and different composition of bacterial and viral species between the gut and oral microbiomes compared to healthy individuals. We performed a thorough microbiome analysis, using deep shotgun sequencing of stool and saliva samples obtained from patients with chronic pancreatitis (CP), pancreatic ductal adenocarcinoma (PDAC), and healthy controls (HCs).We observed similar microbiota composition at the species level in both the gut and oral samples in PDAC patients compared to HCs, among which the most distinctive finding was that the abundance of oral-originated Fusobacterium nucleatum species did not differ between the oral and the gut samples. Moreover, comparing PDAC patients with HCs, Klebsiella oxytoca was significantly more abundant in the stool samples of PDAC patients, while Streptococcus spp. showed higher abundance in both the oral and stool samples of PDAC patients. Finally, the most important finding was the distinctive gut phage–bacterial interactome pattern among PDAC patients. CrAssphages, particularly Blohavirus, showed mutual exclusion with K. oxytoca species, while Burzaovirus showed co-occurrence with Enterobacteriaceae spp., which have been shown to be capable of inducing DNA damage in human pancreatic cells ex vivo. The interactome findings warrant further mechanistic studies, as our findings may provide new insights into developing microbiota-based diagnostic and therapeutic methods for pancreatic diseases.

Type I interferon signaling and peroxisomal dysfunction contribute to enhanced inflammatory cytokine production in IRGM1-deficient macrophages

The human IRGM gene has been linked to inflammatory diseases including sepsis and Crohn’s disease. Decreased expression of human IRGM, or of the mouse orthologues Irgm1 and Irgm2, leads to increased production of a number of inflammatory chemokines and cytokines in vivo and/or in cultured macrophages. Prior work has indicated that increased cytokine production is instigated by metabolic alterations and by changes in mitochondrial homeostasis; however, a comprehensive mechanism has not been elucidated. In the studies presented here, RNA deep sequencing and quantitative PCR were used to show that increases in cytokine production, as well as most changes in the transcriptional profile of Irgm1-/- bone marrow-derived macrophages (BMM), are dependent on increased type I IFN production seen in those cells. Metabolic alterations that drive increased cytokines in Irgm1-/- BMM - specifically increases in glycolysis and increased accumulation of acyl-carnitines - were unaffected by quenching type I IFN signaling. Dysregulation of peroxisomal homeostasis was identified as a novel upstream pathway that governs type I IFN production and inflammatory cytokine production. Collectively, these results enhance our understanding of the complex biochemical changes that are triggered by lack of Irgm1 and contribute to inflammatory disease seen with Irgm1-deficiency.

Application of a new highly multiplexed amplicon sequencing tool to evaluate Plasmodium falciparum antimalarial resistance and relatedness in individual and pooled samples from Dschang, Cameroon.

Resistance to antimalarial drugs remains a major obstacle to malaria elimination. Multiplexed, targeted amplicon sequencing is being adopted for surveilling resistance and dissecting the genetics of complex malaria infections. Moreover, genotyping of parasites and detection of molecular markers drug resistance in resource-limited regions requires open-source protocols for processing samples, using accessible reagents, and rapid methods for processing numerous samples including pooled sequencing. P lasmodium falciparum S treamlined M ultiplex A ntimalarial R esistance and R elatedness T esting ( Pf -SMARRT) is a PCR-based amplicon panel consisting of 15 amplicons targeting antimalarial resistance mutations and 9 amplicons targeting hypervariable regions. This assay uses oligonucleotide primers in two pools and a non-proprietary library and barcoding approach. We evaluated Pf -SMARRT using control mocked dried blood spots (DBS) at varying levels of parasitemia and a mixture of 3D7 and Dd2 strains at known frequencies, showing the ability to genotype at low parasite density and recall within-sample allele frequencies. We then piloted Pf -SMARRT to genotype 100 parasite isolates collected from uncomplicated malaria cases at three health facilities in Dschang, Western Cameroon. Antimalarial resistance genotyping showed high levels of sulfadoxine-pyrimethamine resistance mutations, including 31% prevalence of the DHPS A613S mutation. No K13 candidate or validated artemisinin partial resistance mutations were detected, but one low-level non-synonymous change was observed. Pf -SMARRT's hypervariable targets, used to assess complexity of infections and parasite diversity and relatedness, showed similar levels and patterns compared to molecular inversion probe (MIP) sequencing. While there was strong concordance of antimalarial resistance mutations between individual samples and pools, low-frequency variants in the pooled samples were often missed. Overall, Pf -SMARRT is a robust tool for assessing parasite relatedness and antimalarial drug resistance markers from both individual and pooled samples. Control samples support that accurate genotyping as low as 1 parasite per microliter is routinely possible. Malaria remains a critical global public health problem. Antimalarial drug resistance has repeatedly undermined control and the emergence of artemisinin partial resistance in Africa is the latest major challenge. Malaria molecular surveillance (MMS) has emerged as a powerful tool to monitor molecular markers of resistance and changes in the parasite population. Streamlined methods are needed that can be readily adopted in endemic countries. We developed P lasmodium falciparum S treamlined M ultiplex A ntimalarial R esistance and R elatedness T esting ( Pf -SMARRT), a multiplex amplicon deep sequencing approach that uses easily accessible products without proprietary steps and can be sequenced on any Illumina sequencer. We validated this tool using controls, including mocked dried blood spots, and then implemented it to evaluate resistance and parasite relatedness among 100 samples from Cameroon. The assay was able to reliably assess the within-sample allele frequency of antimalarial resistance markers and discriminate strains within and between individuals. We also evaluated a more cost-effective surveillance approach for antimalarial resistance polymorphisms using pooled samples. While within-pool frequencies of mutations were accurate in pools with higher numbers of samples, this resulted in the loss of the ability to detect variants uncommon in the pool. Overall Pf- SMARRT provides a new protocol for conducting MMS that is easily implementable in Africa.

Cases of endophthalmitis caused by Candida albicans and Candida dubliniensis identified via internal transcribed spacer deep sequencing

BackgroundWe report two cases of fungal endophthalmitis induced by Candida species identified based on internal transcribed spacer 1 (ITS1) sequencing.Case presentationIn two cases, endophthalmitis was suspected, and the patients underwent pars plana vitrectomy. Case 1 was a 64-year-old woman with a history of cataract surgery 10 days prior. She had a history of anal primary melanoma, which metastasized throughout the body and subsequently relapsed. Vitreous culture and ITS-1 deep sequencing revealed the presence of the rare fungus, Candida dubliniensis. Case 2 was a 54-year-old man with a history of liver cancer and kidney failure. Culture methods and ITS1 deep sequencing both revealed the presence of Candida albicans. Both patients exhibited good visual prognoses after treatment with topical and systemic antibiotics.ConclusionsWe present two cases of fungal endophthalmitis caused by two Candida species identified by both the culture method and ITS1 deep sequencing. The fungal pathogen was identified by ITS deep sequencing three days after sample submission; the culture method yielded results after 1 week. These findings support the applicability of ITS1 sequencing for timely pathogen identification for cases of fungal endophthalmitis and provide detailed taxonomic information at the species level.

Federated learning of medical concepts embedding using BEHRT.

Electronic health record data is often considered sensitive medical information. Therefore, the EHR data from different medical centers often cannot be shared, making it difficult to create prediction models using multicenter EHR data, which is essential for such models' robustness and generalizability. Federated learning (FL) is an algorithmic approach that allows learning a shared model using data in multiple locations without the need to store all data in a single central place. Our study aims to evaluate an FL approach using the BEHRT model for predictive tasks on EHR data, focusing on next visit prediction. We propose an FL approach for learning medical concepts embedding. This pretrained model can be used for fine-tuning for specific downstream tasks. Our approach is based on an embedding model like BEHRT, a deep neural sequence transduction model for EHR. We train using FL, both the masked language modeling (MLM) and the next visit downstream model. We demonstrate our approach on the MIMIC-IV dataset. We compare the performance of a model trained with FL to one trained on centralized data, observing a difference in average precision ranging from 0% to 3% (absolute), depending on the length of the patients' visit history. Moreover, our approach improves average precision by 4%-10% (absolute) compared to local models. In addition, we show the importance of the usage of pretrained MLM for the next visit diagnoses prediction task. We find that our FL approach reaches very close to the performance of a centralized model, and it outperforms local models in terms of average precision. We also show that pretrained MLM improves the model's average precision performance in the next visit diagnoses prediction task, compared to an MLM without pretraining.

Clinical and Technical Validation of OncoIndx® Assay-A Comprehensive Genome Profiling Assay for Pan-Cancer Investigations.

Comprehensive next-generation sequencing (NGS) assays enable the identification of clinically relevant mutations, enhancing the capability for targeted therapeutic interventions. In addition, genomic alterations driving the oncogenic roadmap and leading to resistance mechanisms are reshaping precision oncology. We report the workflow and clinical and technical validation of the OncoIndx® NGS platform-a comprehensive genomic profiling (CGP)-based assay for pan-cancer investigation. We evaluated the concordance between the OncoIndx® test findings and clinically established hotspot detection using SeraSeq reference standards. OncoIndx is a hybridization capture-based NGS assay for the targeted deep sequencing of all exons and selected introns of 1080 cancer-related genes. We show the outcome in the form of tier I and tier II single nucleotide variants (SNVs), copy number alterations (CNAs), and specific gene fusions. OncoIndx® also informs genome-wide tumor mutational burden (TMB), microsatellite instability (MSI), homologous recombination deficiency (HRD), and genomic loss of heterozygosity (gLOH). A total of 63 samples were utilized for validation with reference standards, clinical samples, and orthogonal assessment for genomic alterations. In addition, 49 cross-laboratory samples were validated for microsatellite instability (MSI), and for the tumor mutation burden (TMB), 18 samples as reference standards, 6 cross-laboratory samples, and 29 TCGA samples were utilized. We show a maximum clinical sensitivity of 98% and a positive predictive value (PPV) of 100% for the clinically actionable genomic variants detected by the assay. In addition, we demonstrate analytical validation with the performance of the assay, limit of detection (LoD), precision, and orthogonal concordance for various types of SVs, CNAs, genomic rearrangements, and complex biomarkers like TMB, MSI, and HRD. The assay offers reliable genomic predictions with the high-precision detection of actionable variants, validated by established reference standards.

Evolutionary comparison of lncRNAs in four cotton species and functional identification of LncR4682-PAS2-KCS19 module in fiber elongation.

Long non-coding RNAs (lncRNAs) play an important role in various biological processes in plants. However, there have been few reports on the evolutionary signatures of lncRNAs in closely related cotton species. The lncRNA transcription patterns in two tetraploid cotton species and their putative diploid ancestors were compared in this paper. By performing deep RNA sequencing, we identified 280 429 lncRNAs from 21 tissues in four cotton species. lncRNA transcription evolves more rapidly than mRNAs, and exhibits more severe turnover phenomenon in diploid species compared to that in tetraploid species. Evolutionarily conserved lncRNAs exhibit higher expression levels, and lower tissue specificity compared with species-specific lncRNAs. Remarkably, tissue expression of homologous lncRNAs in Gossypium hirsutum and G. barbadense exhibited similar patterns, suggesting that these lncRNAs may be functionally conserved and selectively maintained during domestication. An orthologous lncRNA, lncR4682, was identified and validated in fibers of G. hirsutum and G. barbadense with the highest conservatism and expression abundance. Through virus-induced gene silencing in upland cotton, we found that lncR4682 and its target genes GHPAS2 and GHKCS19 positively regulated fiber elongation. In summary, the present study provides a systematic analysis of lncRNAs in four closely related cotton species, extending the understanding of transcriptional conservation of lncRNAs across cotton species. In addition, LncR4682-PAS2-KCS19 contributes to cotton fiber elongation by participating in the biosynthesis of very long-chain fatty acids.

Identification and Characterization of Four Novel Viruses in Balclutha incisa.

Balclutha incisa (Cicadellidae: Deltocephalinae), a leafhopper prevalent in tropical and temperate regions, is notably abundant in grasses and rice. The virome of B. incisa was investigated using deep transcriptome sequencing, leading to the first identification of four viruses belonging to the families Aliusviridae, Iflaviridae, and Totiviridae in B. incisa. These viruses have been provisionally named B. incisa ollusvirus 1 (BiOV1), B. incisa ollusvirus 2 (BiOV2), B. incisa iflavirus 1 (BiIV1), and B. incisa totivirus 1 (BiTV1). The complete genome sequences of these viruses were obtained through rapid amplification of cDNA ends (RACE). BiOV1 has a linear genome of 15,125 nucleotides (nt), while BiOV2 possesses a circular genome of 14,853 nt. The BiIV1 genome, excluding the poly(A) tail, is 10,903 nt in length and encodes a single open reading frame (ORF) for a polyprotein consisting of 3194 amino acids (aa). The BiTV1 genome is 4357 nt long and contains two overlapping ORFs, with the viral RNA-dependent RNA polymerase (RdRp) translated via a -1 ribosomal frameshift. Phylogenetic and sequence identity analyses suggest that all these viruses are novel members of their respective families. This study significantly expands our understanding of the virome associated with B. incisa by reporting and characterizing these novel viruses.

Genomic Sequencing to Detect Cross-Breeding Quality in Dogs: An Example Studying Disorders in Sexual Development.

Disorders of sexual development (DSDs) in dogs, similar to humans, arise from genetic mutations, gonadal differentiation, or phenotypic sex development. The French Bulldog, a breed that has seen a surge in popularity and demand, has also shown a marked increase in DSD incidence. This study aims to characterize the genetic underpinnings of DSDs in a French Bulldog named Brutus, exhibiting ambiguous genitalia and internal sexual anatomy, and to explore the impact of breeding practices on genetic diversity within the breed. We utilized a comprehensive approach combining conventional cytogenetics, molecular techniques, and deep sequencing to investigate the genetic profile of Brutus. The sequence data were compared to three other male French Bulldogs' genome sequences with typical reproductive anatomy, including Brutus's father and the canine reference genome (CanFam6). We found a Robertsonian fusion involving chromosome 23 previously reported in dogs as a causative mutation responsible for sex reversal syndrome. Our findings revealed a 22% mosaicism (78,XX/77,XX), the absence of the sex-determining region (SRY) gene, and the presence of 43 unique Single Nucleotide Variants (SNVs) not inherited from the father. Notably, the run of homozygosity (ROH) analysis showed Brutus has a higher number of homozygous segments compared to other Bulldogs, with a total length of these fragments 50% greater than the average, strongly suggesting this dog is the product of the mating between siblings. Although no direct causative genes for the DSD phenotype were identified, four candidate loci warrant further investigation. Our study highlighted the need for a better annotated and curated reference dog genome to define genes causative of any specific phenotype, suggests a potential genetic basis for the DSD phenotype in dogs, and underscores the consequences of uncontrolled breeding practices in French Bulldogs. These findings highlight the importance of implementing strategic genetic management to preserve genetic health and diversity in canine populations.

Afatinib plus bevacizumab combination after osimertinib resistance in advanced EGFR-mutant non-small cell lung cancer: Phase II ABCD-study

IntroductionMany clinical studies showed a synergy of epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) and vascular endothelial growth factor inhibitors. We hypothesized afatinib plus bevacizumab exerts clinical potency after developing various osimertinib resistant mechanisms. MethodsEGFR-mutant non-small cell lung cancer patients were enrolled after osimertinib resistance. Afatinib at 30–40 mg/day and bevacizumab at 15 mg/kg tri-weekly were administered until progression. Plasma/histologic rebiopsied samples after osimertinib failure were analyzed to examine resistant mechanisms: gene alterations/copy-number gain using cancer personalized profiling by deep sequencing. ResultsBetween January 2018 and October 2020, 28 patients were enrolled. Response and disease control rates were 17.9 % and 78.6 %, respectively. Median duration of response was 9.0 (range, 4.2–22.3) months. Median progression-free and overall survivals were 2.7 and 9.3 months, respectively. Twenty-eight (100 %) plasma and/or 21 (75 %) histologic rebiopsies identified: 17 (61 %) TP53; 15 (54 %) T790M; 9 (32 %) uncommon EGFR; 9 (32 %) MET; 6 (21 %) C797S; 3 (11 %) BRAF; 2 (7 %) HER2; 2 (7 %) KRAS; and 2 (7 %) PI3K mutations. One (17 %) of 6 C797S patients showed complete response. Three (33 %) of 9 uncommon EGFR-mutated patients achieved radiographic response. Neither 15 T790M-positive nor 6 EGFR downstream signaling mutations: BRAF; KRAS; or PI3K-positive patients responded, but 5 (38 %) of 13 T790M-negative patients responded. Adverse events ≥ grade 3 and incidence ≥ 5 % were: hypertension (29 %); proteinuria (7 %); and diarrhea (7 %). There were neither treatment-related death nor interstitial lung disease. ConclusionsSelected population could obtain clinical benefit from afatinib plus bevacizumab, based on rebiopsy results after osimertinib resistance.

High frequency of artemisinin partial resistance mutations in the Great Lakes region revealed through rapid pooled deep sequencing.

In Africa, the first Plasmodium falciparum artemisinin partial resistance mutation, was Kelch13 (K13) 561H - detected and validated at appreciable frequency in Rwanda in 2014. Surveillance to better define the extent of the emergence in Rwanda and neighboring countries is critical. We used novel liquid blood drop preservation combined with pooled sequencing to provide cost-effective rapid assessment of resistance mutation frequencies at multiple collection sites across Rwanda and neighboring regions in Uganda, Tanzania, and the Democratic Republic of the Congo (DRC). Malaria-positive samples (n=5,465) from 39 health facilities collected between May 2022 and March 2023 were sequenced in 199 pools. In Rwanda, K13 561H and 675V were detected in 90% and 65% of sites with an average frequency of 19.0% (0-54.5%) and 5.0% (0-35.5%), respectively. In Tanzania, 561H had high frequency in multiple sites. 561H appeared at 1.6% in Uganda. 561H was absent from the DRC, although 675V was seen at low frequency. Concerningly candidate mutations were observed: 441L, 449A, and 469F co-occurred with validated mutations suggesting they are arising under the same pressures. Other markers for decreased susceptibility to artemether-lumefantrine are common: P. falciparum multidrug resistance protein 1 N86 at 98.0% (63.3-100%) and 184F at 47.0% (0-94.3%) and P. falciparum chloroquine resistance transporter 76T at 14.7% (0-58.6%). Additionally, sulfadoxine-pyrimethamine-associated mutations show high frequencies. K13 mutations are rapidly expanding in the region further endangering control efforts with the potential of engendering partner drug resistance.

AAVolve: Concatenated long-read deep sequencing enables whole capsid tracking during shuffled AAV library selection

Gene therapies using recombinant adeno-associated virus (AAV) vectors have demonstrated considerable clinical success in the treatment of genetic disorders. Improved vectors with favourable tropism profiles, decreased immunogenicity and enhanced manufacturability are poised to further improve the state of gene therapies. Such vectors can be identified through directed evolution, a process of subjecting a diverse capsid library to a selection pressure to identify individual variants with a desired trait. Currently, libraries that involve changes distributed throughout the AAV capsid coding region, such as DNA family shuffled libraries, are largely characterised using low-throughput Sanger sequencing of individual clones. However, improvements in long-read sequencing technologies have increased their applicability to capsid libraries and evaluation of the selection process. Here we explore the application of Oxford Nanopore Technologies refined by a concatemeric consensus method for initial library characterization and monitoring selection of a shuffled AAV capsid library. Furthermore, we present AAVolve, a bioinformatic pipeline for processing long-read data from AAV directed evolution experiments. Our approach allows high throughput characterisation of AAV capsids in a streamlined manner, facilitating deeper insights into library composition through multiple rounds of selection, and generalization through training of machine learning models.

New persistent plant RNA virus carries mutations to weaken viral suppression of antiviral RNA interference.

Persistent plant viruses are widespread in natural ecosystems. However, little is known about why persistent infection with these viruses may cause little or no harm to their host. Here, we discovered a new polerovirus that persistently infected wild rice plants by deep sequencing and assembly of virus-derived small-interfering RNAs (siRNAs). The new virus was named Rice tiller inhibition virus 2 (RTIV2) based on the symptoms developed in cultivated rice varieties following Agrobacterium-mediated inoculation with an infectious RTIV2 clone. We showed that RTIV2 infection induced antiviral RNA interference (RNAi) in both the wild and cultivated rice plants as well as Nicotiana benthamiana. It is known that virulent virus infection in plants depends on effective suppression of antiviral RNAi by viral suppressors of RNAi (VSRs). Notably, the P0 protein of RTIV2 exhibited weak VSR activity and carries alanine substitutions of two amino acids broadly conserved among diverse poleroviruses. Mixed infection with umbraviruses enhanced RTIV2 accumulation and/or enabled its mechanical transmission in N. benthamiana. Moreover, replacing the alanine at either one or both positions of RTIV2 P0 enhanced the VSR activity in a co-infiltration assay, and RTIV2 mutants carrying the corresponding substitutions replicated to significantly higher levels in both rice and N. benthamiana plants. Together, our findings show that as a persistent plant virus, RTIV2 carries specific mutations in its VSR gene to weaken viral suppression of antiviral RNAi. Our work reveals a new strategy for persistent viruses to maintain long-term infection by weak suppression of the host defence response.

Sequencing CURLY LEAF-associated RNAs in Arabidopsis revealed prevalent intergenic RNAs from the nuclear mitochondrial sequence

Polycomb Group (PcG) proteins play key roles in development by repressing thousands of targets through histone modifications. However, how PcG is recruited to specific targets is poorly understood. In Arabidopsis, certain noncoding RNAs are necessary for recruiting the PcG protein CURLY LEAF (CLF) to its target sites. However, RNAs associated with CLF have not been analyzed on a genomic scale, thus it is unknown whether long noncoding RNA (lncRNA)-mediated PcG recruitment is a widespread mechanism. Here, we systematically searched for CLF-associated RNAs by RNA immunoprecipitation followed by deep sequencing. We identified 1299 genic and 138 intergenic regions that produced CLF-associated mRNAs and putative lncRNAs, respectively. The genes producing CLF-associated RNAs are depleted in PcG targets, carry active chromatin marks, and are highly expressed, suggesting that CLF may have a non-specific or promiscuous RNA-binding affinity, similar to animal PcG proteins. Notably, a significant portion of the CLF-associated lncRNAs is derived from the nuclear mitochondrial sequence, which is extensively marked by H3K27me3. These findings indicate that while CLF-RNA interactions are widespread, they may not always correlate with PcG target sites, highlighting the complexity of PcG recruitment mechanisms in Arabidopsis.

Determining key residues of engineered scFv antibody variants with improved MMP-9 binding using deep sequencing and machine learning

Given the crucial role of specific matrix metalloproteinases (MMPs) in the extracellular matrix, an imbalance in the regulation of activation of matrix metalloproteinase-9 (MMP-9) zymogen and inhibition of the enzyme can result in various diseases, such as cancer, neurodegenerative, and gynecological diseases. Thus, developing novel therapeutics that target MMP-9 with single-chain antibody fragments (scFvs) is a promising approach. We used fluorescent-activated cell sorting (FACS) to screen a synthetic scFv antibody library displayed on yeast for enhanced binding to MMP-9. The screened scFv mutants demonstrated improved binding to MMP-9 compared to the natural inhibitor of MMPs, tissue inhibitor of metalloproteinases (TIMPs). To identify the molecular determinants of these engineered scFv variants that affect binding to MMP-9, we used next-generation DNA sequencing and computational protein structure analysis. Additionally, a deep-learning language model was trained on the screened scFv library of variants to predict the binding affinities of scFv variants based on their CDR-H3 sequences.

Deep Sequencing and Phenotyping in an Australian Tuberous Sclerosis Complex "No Mutations Identified" Cohort.

We describe the phenotypes in an Australian TSC NMI group (n = 18) and a molecular testing strategy implementable in a diagnostic laboratory. Massively parallel sequencing (MPS) of the whole genomic regions of TSC1 and TSC2 was performed using DNA extracted from multiple tissue samples per participant. Our study showed that the phenotype in TSC NMI individuals can be similar to those with heterozygous, particularly TSC1, variants. Although neurodevelopmental outcomes can be less severe, the number of organ systems involved was similar to the non-mosaic groups. A diagnostic yield of 72% (13/18) was achieved, with the majority (10/13) being mosaic variants and the remainder heterozygous variants missed on previous testing. Testing DNA from multiple tissue samples allowed for validation of otherwise discarded low-level mosaic variants and detection of mosaic variants by MPS without excessive cost or the need for specialised techniques. Implementing this approach in a diagnostic setting is viable and allows optimal clinical care of patients with NMI TSC.

A large corpus for the recognition of Greek Sign Language gestures

Sign language recognition (SLR) from videos constitutes a captivating problem in gesture recognition, requiring the interpretation of hand movements, facial expressions, and body postures. The complexity of sign formation, signing variability among signers, and the technical hurdles of visual detection and tracking render SLR a challenging task. At the same time, the scarcity of large-scale SLR datasets, which are critical for developing robust data-intensive deep-learning SLR models, exacerbates these issues. In this article, we introduce a multi-signer video corpus of Greek Sign Language (GSL), which is the largest GSL database to date, serving as a valuable resource for SLR research. This corpus comprises an extensive RGB+D video collection that conveys rich lexical content in a multi-modal fashion, encompassing three subsets: (i) isolated signs; (ii) continuous signing; and (iii) continuous alphabet fingerspelling of words. Moreover, we introduce a comprehensive experimental setup that paves the way for more accurate and robust SLR solutions. In particular, except for the multi-signer (MS) and signer-independent (SI) settings, we employ a signer-adapted (SA) experimental paradigm, facilitating a comprehensive evaluation of system performance across various scenarios. Further, we provide three baseline SLR systems for isolated signs, continuous signing, and continuous fingerspelling. These systems leverage cutting-edge methods in deep learning and sequence modeling to capture the intricate temporal dynamics inherent in sign gestures. The models are evaluated on the three corpus subsets, setting their state-of-the-art recognition benchmark. The SL-ReDu GSL corpus, including its recommended experimental frameworks, is publicly available at https://sl-redu.e-ce.uth.gr/corpus.

A Novel Urine DNA Predictor for Noninvasive Early Diagnosis and Monitoring Minimal Residual Disease of Upper Tract Urothelial Carcinoma.

For early detection and postoperative monitoring of upper tract urothelial carcinoma (UTUC), the traditional detection method was limited to its invasiveness and insufficient sensitivity. We aim to use urine tumour DNA (utDNA) for detecting minimal residual disease (MRD), early diagnosis and perioperative monitoring in UTUC. We previously established a utDNA multidimensional bioinformatic valuation model, named utLIFE, using low-coverage whole-genome sequencing and targeted deep sequencing. This prospective cohort enrolled 93 patients diagnosed with UTUC without metastasis. We collected morning urine samples on the day of surgery and the discharge day after the operation for utLIFE testing. In addition, we also enrolled 80 healthy controls to further validate the specificity of the utLIFE model in the study. The utLIFE of preoperative samples could discriminate UTUC with high specificity (96.25%, 77/80), and high sensitivity (96.77%, 90/93) regardless of stage and grade. The sensitivity of utLIFE was significantly higher than urine cytology (p < 0.001) and fluorescence insitu hybridisation (FISH) (p < 0.001) (N = 19), especially in early-stage and low-grade UTUC. Postoperative utLIFE scores were significantly decreased compared with those of preoperative samples (79 vs. 36, p < 0.001), indicating its association with tumour burden. For special pathology types, utLIFE performed less well in sensitivity and perioperative alteration. In conclusion, we established a bioinformatic utDNA valuation model, utLIFE, which was validated to be a rapid and noninvasive approach with high sensitivity for early detection and MRD monitoring for UTUC.

A pilot study of precision treatment for patients with lung cancer pain by Longteng Tongluo recipe using serum genomics.

To investigate the efficacy of Longteng Tongluo recipe (, LTTL) combined with three-step analgesia for the treatment of lung cancer pain, and the changes in serum miRNA expressions before- and after treatment with LTTL and its correlation with lung cancer pain. The possible mechanism underlying LTTL effects on the treatment of lung cancer pain was conducted. The pilot study was conducted at the oncology ward of the Yueyang Hospital and the Longhua Hospital between March 2018 and October 2019. A prospective, single-blind, placebo controlled, randomized clinical trial of LTTL or placebo combined with three-step analgesia treatments were administered to 24 cancer pain patients diagnosed with lung cancer. Analgesic efficacy was investigated as the primary outcome. Equivalent morphine consumption and numerical rating scale (NRS) scores were used as the secondary outcome. In the present study, we utilized deep sequencing techniques to compare the differential miRNA expressions in serum samples obtained from two groups: the lung cancer pain treatment group (LTTL + three-step analgesia) and the control group (placebo + three-step analgesia). Next, we employed the target prediction database to investigate the target genes for differential miRNA expressions and Gene Ontology (GO) analysis along with Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to examine the roles and the major biochemical and signaling pathways related to the differentially expressed target genes, respectively. LTTL treatment significantly reduces the NRS score (P = 0.021) as compared to those before treatment, along with significant reductions in the total morphine equivalent consumption (P = 0.007) and the average daily equivalent morphine consumption (P = 0.003) as opposed to the control group. The expressions of 31 miRNAs differed considerably between the two groups of patients (≥ 2 times up-modulated or down-regulated between these groups, P<0.05). For instance, the miRNAs expression levels for patients before treatment (has-miR-2110 and has-miR-7d-3p) were significantly enhanced as compared to the healthy people, after LTTL treatment, the expressions of miR-2110 and miR-7d-3p in patients with lung cancer pain reduced significantly. Studies show that the above two miRNAs were significantly associated with lung cancer pain, which could mediate lung cancer pain. Furthermore, we identified 355 genes as potential targets of the 31 differentially expressed miRNAs. Pathway enrichment analyses using KEGG and GO analysis indicated that these target genes may play a crucial role in the development and modulation of lung cancer pain. LTTL demonstrated a discernible impact on alleviating lung cancer pain and its mechanism of action may be related to the downregulation of has-miR-2110 and has-miR-7d-3p expressions. This pilot study provides support for further exploration of LTTL in patients with lung cancer pain.

Detection of airborne wild waterbird-derived DNA demonstrates potential for transmission of avian influenza virus via air inlets into poultry houses, the Netherlands, 2021 to 2022.

BackgroundOutbreaks of highly pathogenic avian influenza (HPAI) on poultry farms and in wild birds worldwide persists despite intensified control measures. It causes unprecedented mortality in bird populations and is increasingly affecting mammalian species. Better understanding of HPAI introduction pathways into farms are needed for targeted disease prevention and control. The relevance of airborne transmission has been suggested but research involving air sampling is limited and unequivocal evidence on transmission routes is lacking.AimWe aimed to investigate whether HPAI virus from wild birds can enter poultry houses through air inlets by characterising host materials through eukaryote DNA sequencing.MethodsWe collected particulate matter samples in and around three HPAI-affected poultry farms which were cleared and decontaminated before sampling. Indoor measurements (n = 61) were taken directly in the airflow entering through air inlets, while outdoor air samples (n = 60) were collected around the poultry house. Positive controls were obtained from a bird rehabilitation shelter. We performed metabarcoding on environmental DNA by deep sequencing 18S rRNA gene amplicons.ResultsWe detected waterbird DNA in air inside all three, and outside of two, poultry farms. Sequences annotated at species level included swans and tufted ducks. Waterbird DNA was present in all indoor and outdoor air samples from the bird shelter.ConclusionAirborne matter derived from contaminated wild birds can potentially introduce HPAI virus to poultry houses through air inlets. The eDNA metabarcoding could assess breaches in biosecurity for HPAI virus and other pathogens potentially transmitted through air via detection of their hosts.