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Abstract Background Sarcomas are highly heterogeneous in molecular, pathologic, and clinical features. However, a classification of sarcomas by integrating different types of pathways remains mostly unexplored. Methods We performed hierarchical clustering analysis of sarcomas based on the enrichment scores of 14 pathways involved in immune, stromal, DNA damage repair (DDR), and oncogenic signatures in three bulk tumor transcriptome datasets. Results Consistently in the three datasets, sarcomas were classified into three subtypes: Immune Class (Imm-C), Stromal Class (Str-C), and DDR Class (DDR-C). Imm-C had the strongest anti-tumor immune signatures and the lowest intratumor heterogeneity (ITH); Str-C showed the strongest stromal signatures, the highest genomic stability and global methylation levels, and the lowest proliferation potential; DDR-C had the highest DDR activity, expression of the cell cycle pathway, tumor purity, stemness scores, proliferation potential, and ITH, the most frequent TP53 mutations, and the worst survival. We further validated the stability and reliability of our classification method by analyzing a single cell RNA-Seq (scRNA-seq) dataset. Based on the expression levels of five genes in the pathways of T cell receptor signaling, cell cycle, mismatch repair, focal adhesion, and calcium signaling, we built a linear risk scoring model (ICMScore) for sarcomas. We demonstrated that ICMScore was an adverse prognostic factor for sarcomas and many other cancers. Conclusions Our classification method provides novel insights into tumor biology and clinical implications for sarcomas.

Tumor stemness is associated with tumor progression and therapy resistance. The recent advances in sequencing, genomics, and computational technologies have facilitated investigation into the tumor stemness cell-like characteristics. We identified subtypes of lung adenocarcinoma (LUAD) in bulk tumors or single cells based on the enrichment scores of 12 stemness signatures by clustering analysis of their transcriptomic profiles. Three stemness subtypes of LUAD were identified: St-H, St-M, and St-L, having high, medium, and low stemness signatures, respectively, consistently in six different datasets. Among the three subtypes, St-H was the most enriched in epithelial-mesenchymal transition, invasion, and metastasis signaling, genomically instable, irresponsive to immunotherapies and targeted therapies, and hence had the worst prognosis. We observed that intratumor heterogeneity was significantly higher in high-stemness than in low-stemness bulk tumors, but significantly lower in high-stemness than in low-stemness single cancer cells. Moreover, tumor immunity was stronger in high-stemness than in low-stemness cancer cells, but weaker in high-stemness than in low-stemness bulk tumors. These differences between bulk tumors and single cancer cells could be attributed to the non-tumor cells in bulk tumors that confounded the results of correlation analysis. Furthermore, pseudotime analysis showed that many St-H cells were at the beginning of the cell evolution trajectory, compared to most St-L cells in the terminal or later phase, suggesting that many low-stemness cells are originated from high-stemness cells. The stemness-based classification of LUAD may provide novel insights into the tumor biology as well as precise clinical management of this disease.

BackgroundA central issue hindering the development of effective anti-fibrosis drugs for heart failure is the unclear interrelationship between fibrosis and the immune cells. This study aims at providing precise subtyping of heart failure based on immune cell fractions, elaborating their differences in fibrotic mechanisms, and proposing a biomarker panel for evaluating intrinsic features of patients’ physiological statuses through subtype classification, thereby promoting the precision medicine for cardiac fibrosis.MethodsWe inferred immune cell type abundance of the ventricular samples by a computational method (CIBERSORTx) based on ventricular tissue samples from 103 patients with heart failure, and applied K-means clustering to divide patients into two subtypes based on their immune cell type abundance. We also designed a novel analytic strategy: Large-Scale Functional Score and Association Analysis (LAFSAA), to study fibrotic mechanisms in the two subtypes.ResultsTwo subtypes of immune cell fractions: pro-inflammatory and pro-remodeling subtypes, were identified. LAFSAA identified 11 subtype-specific pro-fibrotic functional gene sets as the basis for personalised targeted treatments. Based on feature selection, a 30-gene biomarker panel (ImmunCard30) established for diagnosing patient subtypes achieved high classification performance, with the area under the receiver operator characteristic curve corresponding to 0.954 and 0.803 for the discovery and validation sets, respectively.ConclusionPatients with the two subtypes of cardiac immune cell fractions were likely having different fibrotic mechanisms. Patients’ subtypes can be predicted based on the ImmunCard30 biomarker panel. We envision that our unique stratification strategy revealed in this study will unravel advance diagnostic techniques for personalised anti-fibrotic therapy.

Circumscribed interests (CI) encompass a range of different interests and related behaviors that can be characterized by either a high intensity but otherwise usual topic [referred to as restricted interests (RI)] or by a focus on topics that are not salient outside of autism [referred to as unusual interests (UI)]. Previous research has suggested that there is pronounced variability across individuals in terms of the endorsement of different interests, however, this variability has not been quantified using formal subtyping approaches. Therefore, using Latent Profile Analysis in a sample of 1,892 autistic youth (Mage = 10.82, SDage = 4.14; 420 females), this study aimed to identify subgroups based on the RU and UI profiles. Three profiles of autistic individuals were identified. They were characterized as Low CI, Predominantly RI, and Predominantly UI. Importantly, profiles differed on several key demographic and clinical variables, including age, sex composition, IQ, language level, social and communication abilities, anxiety, and obsessive-compulsive behaviors. Although replication across other samples is needed, the profiles identified in this study are potentially promising for future research given their distinct profiles of RI and UI and unique patterns of associations with key cognitive and clinical variables. Therefore, this study represents an important initial step towards more individualized assessment and support for diverse presentations of CI in autistic youth.

IntroductionMuscle-invasive bladder cancer (MIBC) is a heterogeneous disease with several taxonomic molecular subtypes showing different genetic, clinical, and epidemiological profiles. It has been suggested that MIBC-subtypes follow different tumorigenesis pathways playing decisive roles at different stages of tumor development, resulting in distinct tumor microenvironment containing both innate and adaptive immune cells (T and B lymphocytes). We aim to characterize the MIBC tumor microenvironment by analyzing the tumor-infiltrating B and T cell repertoire according to the taxonomic molecular subtypes.MethodsRNAseq data from 396 MIBC samples included in TCGA were considered. The subtype information was collected from the international consensus taxonomic classification describing six subtypes: Basal/Squamous-like (Ba/Sq), Luminal papillary (LumP), Luminal non-Specify (LumNS), Luminal unstable (LumU), Stroma-rich, and Neuroendocrine-like (NE-like). Using MiXCR, we mapped the RNA read sequences to their respective B-cell receptor (BCR) and T-cell receptor (TCR) clonotypes. To evaluate the BCR and TCR differences among subtypes, we compared diversity measures (richness and diversity) using a Wilcoxon test and we performed a network analysis to characterize the clonal expansion. For the survival analysis stratified by subtypes, Cox regression models adjusted for age, region, and pathological stage were performed.ResultsOverall, we found different patterns of tumor-infiltrating immune repertoire among the different MIBC subtypes. Stroma-rich and Ba/Sq tumors showed the highest BCR and TCR infiltration while LumP showed the lowest. In addition, we observed that the Ba/Sq and Stroma-rich tumors were more clonally expanded than the Luminal subtypes. Moreover, higher TCR richness and diversity were significantly associated with better survival in the Stroma-rich and Ba/Sq subtypes.DiscussionThis study provides evidence that MIBC subtypes present differences in the tumor microenvironment, in particular, the Ba/Sq and the Stroma-rich are related with a higher tumoral-infiltrating immune repertoire, which seems to be translated into better survival. Determining the causes of the different tumoral-infiltrating immune repertoire according to the MIBC molecular subtypes will help to improve our understanding of the disease and the distinct responses to immunotherapy of MIBC.

The protozoan Cryptosporidium parvum is an important cause of gastroenteritis in humans and livestock, and cryptosporidiosis outbreaks are common. However, a multi-locus genotyping scheme is not widely adopted. We describe the further development and application of a seven-locus multi-locus variable number of tandem repeats analysis (MLVA) scheme. From 28th March to 31st July 2022, confirmed C. parvum stools (n = 213) from cryptosporidiosis patients (cases) in Wales (n = 95) and the north west of England (n = 118) were tested by MLVA. Typability (defined as alleles identified at all seven loci in a sample) was 81.2% and discriminatory power estimated by Hunter Gaston Discriminatory Index was 0.99. A MLVA profile was constructed from the alleles, expressed in chromosomal order. Profiles were defined as simple (single allele at each locus) or mixed (more than one allele at any locus). A total of 161 MLVA profiles were identified; 13 were mixed, an additional 38 simple profiles contained null records, and 110 were complete simple profiles. A minimum spanning tree was constructed of simple MLVA profiles and those identical at all seven loci defined genetic clusters of cases (here, null records were considered as an allele); 77 cases formed 25 clusters, ranging from two to nine (mode = two) cases. The largest cluster, following epidemiological investigation, signalled a newly-identified outbreak. Two other cases with mixed profiles that contained the outbreak alleles were included in the outbreak investigation. In another epidemiologically-identified outbreak of six initial cases, MLVA detected two additional cases. In a third, small outbreak of three cases, identical MLVA profiles strengthened the microbiological evidence. Review of the performance characteristics of the individual loci and of the seven-locus scheme suggested that two loci might be candidates for review, but a larger dataset over a wider geographical area and longer timeframe will help inform decision-making about the scheme by user laboratories and stakeholders (such as public health agencies). This MLVA scheme is straightforward in use, fast and cheap compared to sequence-based methods, identifies mixed infections, provides an important tool for C. parvum surveillance, and can enhance outbreak investigations and public health action.

Background: Recent theories on the possible interactions between the intestinal parasites and COVID-19 have stated that these co-infections may cause immune imbalance and further complications in the affected patients. Until now, there is no data about Blastocystis subtypes as an intestinal parasite in COVID-19 patients. Therefore, the present work was done to evaluate the molecular prevalence of Blastocystis spp. and related risk factors in Iranian patients with COVID-19. Method: Stool samples were gathered from 200 COVID-19 patients and 200 control, being matched regarding age, gender and residence. Then, stool samples were surveyed by parasitological methods, including direct slide smear and formalin-ether concentration. In the following, PCR and sequencing were used to detect Blastocystis spp. and their subtypes. Results: The frequency of Blastocystis spp. in patients with COVID-19 (7.5%; 15/200 by molecular method vs. 6%; 12/200 by microscopy method) was slightly higher than in individuals without COVID-19 (4.5%; 9/200 by molecular method vs. 4%; 8/200 by microscopy method), this difference was not statistically significant (P value = 0.57 for molecular method vs. P value = 0.81 for microscopy method). Regarding associated factors for Blastocystis spp., we found significant differences regarding the residence (rural), loose and watery stool with diarrhea, and duration of treatment (6 weeks

Abstract Background Alzheimer’s disease (AD) is a highly heterogeneous disease with diverse trajectories and outcomes observed in clinical populations. Understanding this heterogeneity can enable better treatment, prognosis and disease management. Studies to date have mainly used imaging or cognition data and have been limited in terms of data breadth and sample size. Here we examine the clinical heterogeneity of Alzheimer's disease patients using electronic health records (EHR) to identify and characterise disease subgroups using multiple clustering methods, identifying clusters which are clinically actionable. Methods We identified AD patients in primary care EHR from the Clinical Practice Research Datalink (CPRD) using a previously validated rule-based phenotyping algorithm. We extracted and included a range of comorbidities, symptoms and demographic features as patient features. We evaluated four different clustering methods (k-means, kernel k-means, affinity propagation and latent class analysis) to cluster Alzheimer’s disease patients. We compared clusters on clinically relevant outcomes and evaluated each method using measures of cluster structure, stability, efficiency of outcome prediction and replicability in external data sets. Results We identified 7,913 AD patients, with a mean age of 82 and 66.2% female. We included 21 features in our analysis. We observed 5, 2, 5 and 6 clusters in k-means, kernel k-means, affinity propagation and latent class analysis respectively. K-means was found to produce the most consistent results based on four evaluative measures. We discovered a consistent cluster found in three of the four methods composed of predominantly female, younger disease onset (43% between ages 42–73) diagnosed with depression and anxiety, with a quicker rate of progression compared to the average across other clusters. Conclusion Each clustering approach produced substantially different clusters and K-Means performed the best out of the four methods based on the four evaluative criteria. However, the consistent appearance of one particular cluster across three of the four methods potentially suggests the presence of a distinct disease subtype that merits further exploration. Our study underlines the variability of the results obtained from different clustering approaches and the importance of systematically evaluating different approaches for identifying disease subtypes in complex EHR.

Abstract Background Adjuvant chemotherapy reduces the risk of recurrence of stage III colon cancer (CC). However, more effective prognostic and predictive biomarkers are needed for better treatment stratification of affected patients. Here, we constructed a 55-gene classifier (55GC) and investigated its utility for classifying patients with stage III CC. Methods We retrospectively identified patients aged 20–79 years, with stage III CC, who received adjuvant chemotherapy with or without oxaliplatin, between the years 2009 and 2012. Results Among 938 eligible patients, 203 and 201 patients who received adjuvant chemotherapy with and without oxaliplatin, respectively, were selected by propensity score matching. Of these, 95 patients from each group were analyzed, and their 5-year relapse-free survival (RFS) rates with and without oxaliplatin were 73.7 and 77.1%, respectively. The hazard ratios for 5-year RFS following adjuvant chemotherapy (fluoropyrimidine), with and without oxaliplatin, were 1.241 (95% CI, 0.465–3.308; P = 0.67) and 0.791 (95% CI, 0.329–1.901; P = 0.60), respectively. Stratification using the 55GC revealed that 52 (27.3%), 78 (41.1%), and 60 (31.6%) patients had microsatellite instability (MSI)-like, chromosomal instability (CIN)-like, and stromal subtypes, respectively. The 5-year RFS rates were 84.3 and 72.0% in patients treated with and without oxaliplatin, respectively, for the MSI-like subtype (HR, 0.495; 95% CI, 0.145–1.692; P = 0.25). No differences in RFS rates were noted in the CIN-like or stromal subtypes. Stratification by cancer sidedness for each subtype showed improved RFS only in patients with left-sided primary cancer treated with oxaliplatin for the MSI-like subtype (P = 0.007). The 5-year RFS rates of the MSI-like subtype in left-sided cancer patients were 100 and 53.9% with and without oxaliplatin, respectively. Conclusions Subclassification using 55GC and tumor sidedness revealed increased RFS in patients within the MSI-like subtype with stage III left-sided CC treated with fluoropyrimidine and oxaliplatin compared to those treated without oxaliplatin. However, the predictive power of 55GC subtyping alone did not reach statistical significance in this cohort, warranting larger prospective studies. Trial registration The study protocol was registered in the University Hospital Medical Education Network (UMIN) clinical trial registry (UMIN study ID: 000023879 ).

Background: Cryptosporidium spp. are protozoan parasites that cause diarrhea in humans and animals. Subtyping data about Cryptosporidium spp. in Isfahan, Iran is limited; therefore, we aimed to study the prevalence rate of Cryptosporidium spp. in cancer patients, associated risk factors, and subtypes of Cryptosporidium spp. Methods: Fecal samples were collected from 187 cancer patients from the Oncology Department of Seyed-al-Shohada Hospital, Isfahan University of Medical Sciences during 2014–2020 and screened for Cryptosporidium spp. using microscopical techniques. Nested PCR amplifying 18S rRNA gene was used to detect Cryptosporidium spp. in samples, followed by subtyping using nested PCR amplifying gp60 sequences. Results: Overall, the rate of infection with Cryptosporidium spp. was 4.3% (n=8). Five samples out of eight samples were identified as Cryptosporidium spp. using a nested PCR for the 18S rRNA gene, two subtypes of C. parvum named IIaA18G3R1 (n = 2) and IIaA17G2R1 (n = 2), and one subtype of C. hominis named IbA6G3 were identified by sequencing of the gp60. The IbA6G3 subtype has rarely been detected in other investigations. Conclusion: This is the first survey on the subtyping of Cryptosporidium spp. in this region. The results of the present survey show both zoonotic and anthroponotic transmission routes in the region.

Simple Summary: Numerous factors, such as genomic mutations, chromosomal changes, transcriptional controls, phosphorylation, and protein–protein interactions, among others, can affect the activation status of proteins. Although each data type only partially reveals the status of a particular gene's disruption, downstream expression changes ultimately indicate the functional effects of cancer driver protein alterations. By combining data on transcriptome and genomic alterations, we have developed a Bayesian framework to infer driver activation state, and further tested our method to highlight both statistical and biological significance by applying our model to TCGA HNSCC patient data. Head and neck squamous cell cancer (HNSCC) is an aggressive cancer resulting from heterogeneous causes. To reveal the underlying drivers and signaling mechanisms of different HNSCC tumors, we developed a novel Bayesian framework to identify drivers of individual tumors and infer the states of driver proteins in cellular signaling system in HNSCC tumors. First, we systematically identify causal relationships between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) for each TCGA HNSCC tumor using the tumor-specific causal inference (TCI) model. Then, we generalize the most statistically significant driver SGAs and their regulated DEGs in TCGA HNSCC cohort. Finally, we develop machine learning models that combine genomic and transcriptomic data to infer the protein functional activation states of driver SGAs in tumors, which enable us to represent a tumor in the space of cellular signaling systems. We discovered four mechanism-oriented subtypes of HNSCC, which show distinguished patterns of activation state of HNSCC driver proteins, and importantly, this subtyping is orthogonal to previously reported transcriptomic-based molecular subtyping of HNSCC. Further, our analysis revealed driver proteins that are likely involved in oncogenic processes induced by HPV infection, even though they are not perturbed by genomic alterations in HPV+ tumors. [ABSTRACT FROM AUTHOR]

Background: Cryptosporidium spp. are protozoan parasites that cause diarrhea in humans and animals. Subtyping data about Cryptosporidium spp. in Isfahan, Iran is limited; therefore, we aimed to study the prevalence rate of Cryptosporidium spp. in cancer patients, associated risk factors, and subtypes of Cryptosporidium spp. Methods: Fecal samples were collected from 187 cancer patients from the Oncology Department of Seyed-al-Shohada Hospital, Isfahan University of Medical Sciences during 2014-2020 and screened for Cryptosporidium spp. using microscopical techniques. Nested PCR amplifying 18S rRNA gene was used to detect Cryptosporidium spp. in samples, followed by subtyping using nested PCR amplifying gp60 sequences. Results: Overall, the rate of infection with Cryptosporidium spp. was 4.3% (n=8). Five samples out of eight samples were identified as Cryptosporidium spp. using a nested PCR for the 18S rRNA gene, two subtypes of C. parvum named IIaA18G3R1 (n = 2) and IIaA17G2R1 (n = 2), and one subtype of C. hominis named IbA6G3 were identified by sequencing of the gp60. The IbA6G3 subtype has rarely been detected in other investigations. Conclusion: This is the first survey on the subtyping of Cryptosporidium spp. in this region. The results of the present survey show both zoonotic and anthroponotic transmission routes in the region. [ABSTRACT FROM AUTHOR]

Major depression is clinically heterogeneous. We aimed to identify classes of depressed adolescents with different symptom presentations and examine if these were differentially associated with illness severity, functioning, engagement with treatment, and clinical outcomes. Baseline depression symptoms of 454 depressed adolescents (age 11–17) from the IMPACT trial were subjected to latent class analysis. We compared classes on self-reported symptoms and social impairment at baseline and follow-up and their engagement in treatment. We identified three classes of participants which differed in the number and pattern of depression symptoms; Class 1—Severe- (37.2%)—endorsed almost all symptoms and were most functionally impaired; Class 2—Moderate- (41.9%)—endorsed fewer symptoms with high suicidal ideation, self-harm, and worthlessness; Class 3—Somatic (20.9%)—endorsed fewest symptoms, with high somatic symptoms. Groups did not differ on engagement, therapeutic alliance, or post-treatment symptom reduction. Adolescents in the severe and moderate subgroups reported symptom reductions after treatment ended, whilst those in the somatic subgroup did not. At presentation, high somatic features in depressed adolescents, rather than severity, or impairment levels, may indicate lower liability for responding to psychological treatment. [ABSTRACT FROM AUTHOR]

Background: Parkinson's disease (PD) is a clinically and neuroanatomically heterogeneous neurodegenerative disease characterized by different subtypes. To this date, no studies have used multimodal data that combines clinical, motor, cognitive and neuroimaging assessments to identify these subtypes, which may provide complementary, clinically relevant information. To address this limitation, we subtyped participants with mild-moderate PD based on a rich, multimodal dataset of clinical, cognitive, motor, and neuroimaging variables.Methods: Cross-sectional data from 95 PD participants from our randomized EXPANd (EXercise in PArkinson's disease and Neuroplasticity) controlled trial were included. Participants were subtyped using clinical, motor, and cognitive assessments as well as structural and resting-state MRI data. Subtyping was done by random forest clustering. We extracted information about the subtypes by inspecting their neuroimaging profiles and descriptive statistics.Results: Our multimodal subtyping analysis yielded three PD subtypes: a motor-cognitive subtype characterized by widespread alterations in brain structure and function as well as impairment in motor and cognitive abilities; a cognitive dominant subtype mainly impaired in cognitive function that showed frontoparietal structural and functional changes; and a motor dominant subtype impaired in motor variables without any brain alterations. Motor variables were most important for the subtyping, followed by gray matter volume in the right medial postcentral gyrus.Conclusions: Three distinct PD subtypes were identified in our multimodal dataset. The most important features to subtype PD participants were motor variables in addition to structural MRI in the sensorimotor region. These findings have the potential to improve our understanding of PD heterogeneity, which in turn can lead to personalized interventions and rehabilitation. [ABSTRACT FROM AUTHOR]

Prostate cancer (PC) is heterogeneous in the tumor immune microenvironment (TIME). Subtyping of PC based on the TIME could provide new insights into intratumor heterogeneity and its correlates of clinical features. Based on the enrichment scores of 28 immune cell types in the TIME, we performed unsupervised clustering to identify immune-specific subtypes of PC. The clustering analysis was performed in ten different bulk tumor transcriptomic datasets and in a single-cell RNA-Seq (scRNA-seq) dataset, respectively. We identified two PC subtypes: PC immunity high (PC-ImH) and PC immunity low (PC-ImL), consistently in these datasets. Compared to PC-ImL, PC-ImH displayed stronger immune signatures, worse clinical outcomes, higher epithelial-mesenchymal transition (EMT) signature, tumor stemness, intratumor heterogeneity (ITH) and genomic instability, and lower incidence of TMPRSS2-ERG fusion. Tumor mutation burden (TMB) showed no significant difference between PC-ImH and PC-ImL, while copy number alteration (CNA) was more significant in PC-ImL than in PC-ImH. PC-ImH could be further divided into two subgroups, which had significantly different immune infiltration levels and clinical features. In conclusion, "hot" PCs have stronger anti-tumor immune response, while worse clinical outcomes versus "cold" PCs. CNA instead of TMB plays a crucial role in the regulation of TIME in PC. TMPRSS2-ERG fusion correlates with decreased anti-tumor immune response while better disease-free survival in PC. The identification of immune-specific subtypes has potential clinical implications for PC immunotherapy. [ABSTRACT FROM AUTHOR]

Pulmonary sarcomatoid carcinoma (PSC) is a unique form of poorly differentiated nonsmall cell lung cancer (NSCLC) and is notorious for its highly malignant nature and dismal prognosis. To introduce effective treatment for PSC patients, precise subtyping of PSC is demanding. In our study, TTF‐1 and P40 immunohistochemistry (IHC) staining were applied to 56 PSC patients with multiomics data. According to IHC results, we categorized these patients into three subgroups and profiled their molecular contexture using bioinformatic skills. IHC results classified these patients into three subgroups: TTF‐1 positive subgroup (n = 27), P40 positive subgroup (n = 15) and double‐negative subgroup (n = 14). Spindle cell samples accounted for 35.71% (5/14) of double‐negative patients, higher than others (P =.034). The three subgroups were heterogeneous in the genomic alteration spectrum, showing significant differences in the RTK/RAS pathway (P =.004) and the cell cycle pathway (P =.030). The methylation profile of the double‐negative subgroup was between the other two subgroups. In similarity analysis, the TTF‐1 and p40 subgroups were closely related to LUAD and LUSC, respectively. The TTF‐1 positive subgroup had the highest leukocyte fraction (LF) among several cancer types, and the tumor mutation burden (TMB) of the p40 positive subgroup ranked third in the TMB list, suggesting the applicability of immunotherapy for PSC. The study established a new subtyping method of PSC based on IHC results and reveals three subgroups with distinct molecular features, providing evidence for refined stratification in the treatment of PSC. [ABSTRACT FROM AUTHOR]

The present study aimed to examine anxiety profiles among children and adolescents on the autism spectrum. It further aimed to characterize the association between the identified anxiety profiles and key clinical and developmental variables. The Spence Children's Anxiety Scale‐Parent Version (SCAS‐P) data from a large international pooled sample of 870 caregivers of autistic children and adolescents (Mage = 11.6 years, SDage = 2.77; 107 females) was used. Latent profile analysis identified a three‐anxiety profile solution exhibiting high entropy (0.80) and high latent profile probabilities, with good classification accuracy. Identified profiles fell along the severity spectrum and were named as the mild (n = 498), moderate (n = 272) and severe (n = 100) anxiety profiles. There were no statistically significant differences between the three anxiety profiles in terms of sex distribution. Participants in the mild profile were significantly younger than those in the severe profile, had significantly fewer social communication difficulties than youth in the moderate anxiety profile group and had significantly fewer restricted and repetitive behaviors and lower cognitive functioning scores compared to participants in moderate and severe anxiety profiles. This is the first study to move beyond identifying associations and group‐level differences to exploring and identifying characteristics of anxiety‐based subgroups at an individual level that differ on key clinical and developmental variables. The subgroups identified in this study are a preliminary, yet important, first step towards informing future assessment and individualized interventions aiming to support young people on the autism spectrum to reduce and manage anxiety. Lay Summary: This study tried to understand if there are subgroups of autistic young people who may have similar anxiety profiles. We found that we could meaningfully group young people into three groups based on how severe the anxiety symptoms their caregivers reported were: a group with low levels of anxiety, those with moderate anxiety, and those with more severe anxiety. We also found that the young people in the mild group were younger, had fewer autism traits and lower levels of intellectual functioning than young people in the other two groups. [ABSTRACT FROM AUTHOR]

Objective: Primary aldosteronism (PA), a significant cause of secondary hypertension affecting approximately 10% of patients with severe hypertension, exacerbates cardiovascular and cerebrovascular complications even after blood pressure control. PA is categorized into two main subtypes: unilateral aldosterone-producing adenomas (APA) and bilateral hyperaldosteronism (BHA), each requiring distinct treatment approaches. Accurate subtype classification is crucial for selecting the most effective treatment. The goal of this study was to develop novel blood-based proteomic biomarkers to differentiate between APA and BHA subtypes in patients with PA., Design and Methods: Five subtyping differential protein biomarker candidates (APOC3, CD56, CHGA, KRT5, and AZGP1) were identified through targeted proteomic profiling of plasma. The subtyping efficiency of these biomarkers was assessed at both the tissue gene expression and blood protein expression levels. To explore the underlying biology of APA and BHA, significant differential pathways were investigated., Results: The five-protein panel proved highly effective in distinguishing APA from BHA in both tissue and blood samples. By integrating these five protein biomarkers with aldosterone and renin, our blood-based predictive methods achieved remarkable ROC AUCs of 0.986 (95% CI: 0.963-1.000) for differentiating essential hypertension (EH) from PA, and 0.922 (95% CI: 0.846-0.998) for subtyping APA versus BHA. These outcomes surpass the performance of the existing Kobayashi score subtyping system. Furthermore, the study validated differential pathways associated with the pathophysiology of primary aldosteronism, aligning with current scientific knowledge and opening new avenues for advancing PA care., Conclusions: The new blood-based biomarkers for PA subtyping hold the potential to significantly enhance clinical utility and advance the practice of PA care., (© The Author(s) 2024. Published by Oxford University Press on behalf of European Society of Endocrinology.)

Adrenal vein sampling (AVS) is the current recommended procedure for identifying unilateral subtypes of primary aldosteronism (PA), which are amenable to surgery with the potential for cure. AVS is a technically challenging procedure usually undertaken by interventional radiologists at tertiary centres. However, there are numerous variations in AVS protocols relating to patient preparation, sampling techniques and interpretation which may impact the success of AVS and patient care. To reduce practice variations, improve the success rates of AVS and optimise patient outcomes, we established an Australian and New Zealand AVS Working Group and developed evidence-based expert consensus recommendations for the preparation, performance and interpretation of AVS. These recommendations can be used by all healthcare professionals in a multidisciplinary team who look after the diagnosis and management of PA., (© 2024 The Author(s). Clinical Endocrinology published by John Wiley & Sons Ltd.)

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors. In this study, we develop a clinically useful computational pathology platform for NSCLC that can be a foundation for multiple downstream applications and provide immediate value for patient care optimization and individualization. We train the primary multi-class tissue segmentation algorithm on a substantial, high-quality, manually annotated dataset of whole-slide images with lung adenocarcinoma and squamous cell carcinomas. We investigate two downstream applications. NSCLC subtyping algorithm is trained and validated using a large, multi-institutional (n = 6), multi-scanner (n = 5), international cohort of NSCLC cases (slides/patients 4,097/1,527). Moreover, we develop four AI-derived, fully explainable, quantitative, prognostic parameters (based on tertiary lymphoid structure and necrosis assessment) and validate them for different clinical endpoints. The computational platform enables the high-precision, quantitative analysis of H&E-stained slides. The developed prognostic parameters facilitate robust and independent risk stratification of patients with NSCLC., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Aim: During the pandemic of severe acute respiratory syndrome corona-virus 2 (SARS-CoV-2), many countries reported a significant decrease in the prevalence of influenza virus cases. The study aimed to characterize the flu seasons from 2018 to 2023 in Sarajevo Canton, Bosnia and Herzegovina (B&H), and to assess the possible impact of the SARS-CoV-2 pandemic on the influenza A and B virus circulation., Methods: The CDC Human Influenza Virus Real-Time RT-PCR Diagnostic Panels were used for the detection of influenza virus A and B, and subtyping of influenza virus A (H1pdm09 virus and H3). The data for this registry-based retrospective study were collected at the Clinical Centre of the University of Sarajevo, Unit for Clinical Microbiology (the laboratory that acts as a referral for the detection and characterization of influenza virus and SARS-CoV-2 in Federation B&H)., Results: In the 2018/2019 and 2019/2020, an equal percentage of positive cases was recorded (148/410; 36%, and 182/504; 36%, respectively). The absence of the influenza virus was observed in 2020/2021. During 2021/2022, influenza virus was detected among 19/104 (18%) patients and slightly increased in 2022/2023 (45/269; 17%). The switch of the influenza B virus lineage was observed., Conclusion: The SARS-CoV-2 virus had an impact on the prevalence of influenza virus infection among the population of the Sarajevo Canton, B&H. Since the interactions between these two viruses are not entirely clear, awareness of a possible threat to public health is crucial., (Copyright© by the Medical Association of Zenica-Doboj Canton.)

In the current study, an one pot quadruplex RT-qPCR assay was established and comprehensively evaluated. The assay's limit of detection could reach as low as 101 copies/reaction, with good repeatability profile and no cross-reaction with other respiratory pathogens. During clinical evaluation both by blinded samples and real clinical samples, the assay exhibited a 100% coincidence rate with individual commercial RT-qPCR assays. To the best of our knowledge, this is the first report on the simultaneous subtyping influenza A virus into H1, H3, N1, and N2 by one pot quadruplex RT-qPCR assay, which could improve the preparedness for future influenza outbreaks.

Background: We aimed to investigate the prevalence of Cryptosporidium species detected in humans and calves in the Van region of Turkey. Methods: A total of 150 patients, comprising 60 who were immunosuppressed, 50 who were immunosuppressed and had diarrhea, and 40 who had only diarrhea, were enrolled in this study in the Department of Medical Parasitology, Van Yuzuncu Yıl University Faculty of Medicine, Turkey. Stool samples were taken from the rectums of a total of 50 calves that had 30 diarrhea and 20 that did not have diarrhea, from the stables and farms of 10 central villages of Van, Turkey. All samples were analyzed using modified acid-fast staining, immunochromatographic test, and PCR. Cryptosporidium positive samples were also subtyped. Results: Only C. parvum subtypes were detected in all positive samples. C. parvum was detected in 30 (20%) of the 150 human stool samples, while it was detected in 5 (10%) of the 50 samples from the calves. The GP60 gene region was amplified and sent for sequence analysis to identify the C. parvum subtypes. Conclusion: As a result, C. parvum is found to be an active species that caused cryptosporidiosis is in the Van region. IIdA24G1 subtype of C. parvum were found in both human and calf. Therefore, due to the zoonotic feature of the C. parvum IIdA24G1 subtype, it has been shown that the calves in the region are a significant risk for humans.

Blastocystis is a genus of unicellular heterokont parasites belonging to a group of organisms known as Stramenopiles, which includes algae, diatoms, and water molds. Blastocystis includes several species that habitat in the gastrointestinal tracts of organisms as diverse as humans, farm animals, birds, rodents, reptiles, amphibians, fish, and cockroaches. It is important to public health and distributed globally, but its prevalence in dogs in Korea has not been reported to date. Here, we collected 787 canine fecal samples and assessed Blastocystis infection by age, sex, region, season, and diarrhea symptoms. We determined Blastocystis subtypes using phylogenetic analyses based on 18S rRNA gene sequences. We identified, 10 Blastocystis positive samples (1.3%). A higher proportion of infected dogs was asymptomatic; however, infection rates did not significantly differ according to region, age, sex, and season. Phylogenetic analysis showed that the Blastocystis sp. identified belonged to 4 subtypes (STs), ST1, ST5, ST10, and ST14, thus revealed the genetic diversity of Blastocystis sp. in dogs Korean. This is first report on the presence of Blastocystis sp. in dogs Korean. This study revealed a lower infection rate than expected and differed from previous studies in STs. Further studies are warranted to observe the national infection status of Blastocystis in dogs and the genetic characteristics of this genus. [ABSTRACT FROM AUTHOR]

Background. Nowadays, most of the C. parvum and C. hominis epidemiological studies are based on gp60 gene subtyping using the Sanger sequencing (SgS) method. Unfortunately, SgS presents the limitation of being unable to detect mixed infections. Next-Generation Sequencing (NGS) seems to be an interesting solution to overcome SgS limits. Thus, the aim of our study was to (i) evaluate the reliability of NGS as a molecular typing tool for cryptosporidiosis, (ii) investigate the genetic diversity of the parasite and the frequency of mixed infections, (iii) assess NGS usefulness in Cryptosporidium sp. outbreak investigations, and (iv) assess an interpretation threshold of sequencing data. Methods. 108 DNA extracts from positive samples were sequenced by NGS. Among them, two samples were used to validate the reliability of the subtyping obtained by NGS and its capacity to detect DNA mixtures. In parallel, 106 samples from French outbreaks were used to expose NGS to epidemic samples. Results. NGS proved suitable for Cryptosporidium sp. subtyping at the gp60 gene locus, bringing more genetic information compared to SgS, especially by working on many samples simultaneously and detecting more diversity. Conclusions. This study confirms the usefulness of NGS applied to C. hominis and C. parvum epidemiological studies, especially aimed at detecting minority variants. [ABSTRACT FROM AUTHOR]

Simple Summary: Germinal center-derived B-cell lymphomas constitute a very heterogeneous group of neoplasms with diverse clinical presentations, prognoses, and responses to therapy. They divide into a series of subtypes, such as Diffuse Large B-cell lymphomas (DLBCL), Burkitt Lymphomas (BL), Follicular lymphomas (FL), and further, into several subclasses and rarer subtypes of finer granularity, which makes them one of the most heterogeneous cancer entities. Molecular classification schemes, first of all, derived from whole transcriptome gene expression data largely improved subtyping and functional understanding. Based on a whole transcriptome landscape of B-cell lymphoma, we show that one major caveat in the task of classification is represented by the rather fuzzy distribution of individual tumors without clear-cut borderlines between most of the subtypes, preventing their unambiguous association with clear-cut entities. This landscape is governed by the germinal center (GC) reaction and relates different subtypes to different states along the reaction path. We discuss the relatedness between the expression landscape and classifier signatures and their functional cell of origin background. This view helps to stratify lymphomas in terms of modular building blocks of signature genes and to interpret rarer subclasses in the context of larger ones. Classification of lymphoid neoplasms is based mainly on histologic, immunologic, and (rarer) genetic features. It has been supplemented by gene expression profiling (GEP) in the last decade. Despite the considerable success, particularly in associating lymphoma subtypes with specific transcriptional programs and classifier signatures of up- or downregulated genes, competing molecular classifiers were often proposed in the literature by different groups for the same classification tasks to distinguish, e.g., BL versus DLBCL or different DLBCL subtypes. Moreover, rarer sub-entities such as MYC and BCL2 "double hit lymphomas" (DHL), IRF4-rearranged large cell lymphoma (IRF4-LCL), and Burkitt-like lymphomas with 11q aberration pattern (mnBLL-11q) attracted interest while their relatedness regarding the major classes is still unclear in many respects. We explored the transcriptional landscape of 873 lymphomas referring to a wide spectrum of subtypes by applying self-organizing maps (SOM) machine learning. The landscape reveals a continuum of transcriptional states activated in the different subtypes without clear-cut borderlines between them and preventing their unambiguous classification. These states show striking parallels with single cell gene expression of the active germinal center (GC), which is characterized by the cyclic progression of B-cells. The expression patterns along the GC trajectory are discriminative for distinguishing different lymphoma subtypes. We show that the rare subtypes take intermediate positions between BL, DLBCL, and FL as considered by the 5th edition of the WHO classification of haemato-lymphoid tumors in 2022. Classifier gene signatures extracted from these states as modules of coregulated genes are competitive with literature classifiers. They provide functional-defined classifiers with the option of consenting redundant classifiers from the literature. We discuss alternative classification schemes of different granularity and functional impact as possible avenues toward personalization and improved diagnostics of GC-derived lymphomas. [ABSTRACT FROM AUTHOR]

Background: Cryptosporidium parvum (C. parvum) is a cosmopolitan parasite that infects various livestock animals including cattle. Microsatellite typing tools for identification of C. parvum subtypes are currently employed to better understand the species-specific epidemiology of cattle cryptosporidiosis. The aim of this study was to analyse the population genetics of C. parvum strains infecting cattle and recognise geographical distribution and time-span correlations in subtype prevalence in Poland. In total, 1601 faecal samples were collected from 2014 to 2018 from healthy cattle from dairy, meat and mixed breeds at the age of 1 week to 4 months. The 267 farms visited were randomly selected and represented all Polish provinces. PCR–RFLP based identification of C. parvum at the 18 small subunit ribosomal RNA (SSU rRNA) locus was performed, followed by strain subtyping by GP60-PCR. Results: The overall prevalence of C. parvum in Polish cattle was estimated at 6.2% (100/1601). Animals below the age of 1 month were the major host for this parasite. Excluding one breed, that of dairy-meat mixed, there were no significant differences observed between breed and presence of C. parvum infections (95% TPIAll breeds: 1.67–73.53%; POPR = 0.05—0.95). Infected animals were detected in 15 out of 16 Polish provinces, with significant regional prevalence diffrences (Kruskal–Wallis rank sum test, Kruskal–Wallis χ2 = 13.46, p < 0.001). When the population genetics of C. parvum strains were analysed, 11 parasite subtypes from the IIa and IId genetic families were identified. Compared to other parasite strains, IIaA17G1R1 and IIaA17G2R1 appeared at statistically significantly higher frequency (F-test, F = 3.39; p = 0.0003). The prevalence of C. parvum subtypes in cattle was breed-related (Chi-squared test, χ2 = 143.6; p < 0.001). Conclusions: The analysis of the population genetics of C. parvum subtypes showed that strains from the IIa subtype family predominated in the tested cattle population. However, relations in changes of subtype prevalence and circulation over time were observed. They were associated with the disappearance of some strains and emergence of new variants from the same genetic family in different geographical locations. Highlights: C. parvum subtypes from the IIa allele family predominated in the tested cattle. The prevalence of C. parvum subtypes in cattle was breed-related. Dynamicity in the population C. parvum strains circulating in cattle was shown. [ABSTRACT FROM AUTHOR]

Background: Tinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a better understanding of tinnitus by capturing the fluctuations of tinnitus symptoms, such as distress and loudness, and psychological processes, such as emotional arousal, overall stress, mood, and concentration and how these variables interact over time. Whether any of those variables have an influence over the next day, that is, whether any of these variables are auto- or cross-correlated, is still unanswered. Objectives: Assess whether behavioral and symptom-related data from tinnitus users from the TrackYourTinnitus (TYT) mobile app have an impact on tinnitus loudness and distress on subsequent days. Methods: Anonymized data was collected from 278 users of the iOS or Android TYT apps between 2014 and 2020. Tinnitus-related distress, tinnitus loudness, concentration level, mood, emotional arousal, and overall stress level were assessed using either a slider or the Wong-Baker Pain FACES scale via a daily survey. Three modeling strategies were used to investigate whether tinnitus loudness and distress are affected by previous days symptoms or psychological processes: auto- and cross correlations, regressions with elastic net regularization, and subgrouping within group iterative multiple model estimation (S-GIMME). Results: No autocorrelation or cross-correlation was observed at the group level between the variables assessed. However, application of the regression models with elastic net regularization identified individualized predictors of tinnitus loudness and distress for most participants, with the models including contemporaneous and lagged information from the previous day. S-GIMME corroborated these findings by identifying individualized predictors of tinnitus loudness and distress from the previous day. Discussion: We showed that tinnitus loudness and tinnitus distress are affected by the contemporaneous and lagged dynamics of behavioral and emotional processes measured through EMA. These effects were seen at the group, and individual levels. The relevance EMA and the implications of the insights derived from it for tinnitus care are discussed, especially considering current trends toward the individualization of tinnitus care. [ABSTRACT FROM AUTHOR]

Simple Summary: Liver cancer subtypes differ in prognosis and genetic alterations. An accurate diagnosis made on time is the key aspect of clinical decision-making. Hence, a correct diagnosis is of pivotal importance for individual patients. In this study, we identified the most relevant clinical, radiological, and histological parameters for an improved subtype diagnosis of intrahepatic cholangiocarcinoma. As a result of our study, the radiologist should consider factors such as growth pattern, location, and contrast agent behavior. For the pathologist, precursor lesions, mucin secretion, and a periductal-infiltrating growth are of utmost importance, while immunohistochemical analyses are essential for exclusion of extrahepatic malignancies, but have so far only value for iCCA subtype analysis in the context with other parameters. Intrahepatic cholangiocarcinomas (iCCAs) may be subdivided into large and small duct types that differ in etiology, molecular alterations, therapy, and prognosis. Therefore, the optimal iCCA subtyping is crucial for the best possible patient outcome. In our study, we analyzed 148 small and 84 large duct iCCAs regarding their clinical, radiological, histological, and immunohistochemical features. Only 8% of small duct iCCAs, but 27% of large duct iCCAs, presented with initial jaundice. Ductal tumor growth pattern and biliary obstruction were significant radiological findings in 33% and 48% of large duct iCCAs, respectively. Biliary epithelial neoplasia and intraductal papillary neoplasms of the bile duct were detected exclusively in large duct type iCCAs. Other distinctive histological features were mucin formation and periductal-infiltrating growth pattern. Immunohistochemical staining against CK20, CA19-9, EMA, CD56, N-cadherin, and CRP could help distinguish between the subtypes. To summarize, correct subtyping of iCCA requires an interplay of several factors. While the diagnosis of a precursor lesion, evidence of mucin, or a periductal-infiltrating growth pattern indicates the diagnosis of a large duct type, in their absence, several other criteria of diagnosis need to be combined. [ABSTRACT FROM AUTHOR]

Blastocystis sp. is a gastrointestinal pathogen that is frequently found in humans and animals worldwide. In this study, 201 fecal samples were collected from captive Alpine musk deer (Moschus chrysogaster) at three farms in Gansu province. Blastocystis was detected and subtyped by amplifying and sequencing the small subunit ribosomal DNA gene. The overall prevalence of Blastocystis was 39.8% (80/201). Five known Blastocystis subtypes (STs), including ST1 (n = 1), ST4 (n = 12), ST10 (n = 50), ST14 (n = 6), and ST24 (n = 11) were identified using subtyping and evolutionary analysis. ST10 was the most common ST observed in each farm. This study showed the infection status and genetic characteristics of Blastocystis in M. chrysogaster. Based on the surveyed data, because various potentially zoonotic STs, such as ST1, ST4, ST10, ST14, and ST24, were detected, it is believed that the zoonotic risk of Blastocystis from the Alpine musk deer in this area cannot be ignored. [ABSTRACT FROM AUTHOR]

Background: We aimed to investigate the prevalence of Cryptosporidium species detected in humans and calves in the Van region of Turkey. Methods: A total of 150 patients, comprising 60 who were immunosuppressed, 50 who were immunosuppressed and had diarrhea, and 40 who had only diarrhea, were enrolled in this study in the Department of Medical Parasitology, Van Yuzuncu Yıl University Faculty of Medicine, Turkey. Stool samples were taken from the rectums of a total of 50 calves that had 30 diarrhea and 20 that did not have diarrhea, from the stables and farms of 10 central villages of Van, Turkey. All samples were analyzed using modified acid-fast staining, immunochromatographic test, and PCR. Cryptosporidium positive samples were also subtyped. Results: Only C. parvum subtypes were detected in all positive samples. C. parvum was detected in 30 (20%) of the 150 human stool samples, while it was detected in 5 (10%) of the 50 samples from the calves. The GP60 gene region was amplified and sent for sequence analysis to identify the C. parvum subtypes. Conclusion: As a result, C. parvum is found to be an active species that caused cryptosporidiosis is in the Van region. IIdA24G1 subtype of C. parvum were found in both human and calf. Therefore, due to the zoonotic feature of the C. parvum IIdA24G1 subtype, it has been shown that the calves in the region are a significant risk for humans. [ABSTRACT FROM AUTHOR]

Salmonella enterica subsp. enterica serovar Enteritidis remains one of the most important foodborne pathogens worldwide. To minimise its public health impact when outbreaks of the disease occur, timely investigation to identify and recall the contaminated food source is necessary. Central to this approach is the need for rapid and accurate identification of the bacterial subtype epidemiologically linked to the outbreak. While traditional methods of S. Enteritidis subtyping, such as pulsed field gel electrophoresis (PFGE) and phage typing (PT), have played an important role, the clonal nature of this organism has spurred efforts to improve subtyping resolution and timeliness through molecular based approaches. This study uses a cohort of 92 samples, recovered from a variety of sources, to compare these two traditional methods for S. Enteritidis subtyping with recently developed molecular techniques. These latter methods include the characterisation of two clustered regularly interspaced short palindromic repeats (CRISPR) loci, either in isolation or together with sequence analysis of virulence genes such as fimH. For comparison, another molecular technique developed in this laboratory involved the scoring of 60 informative single nucleotide polymorphisms (SNPs) distributed throughout the genome. Based on both the number of subtypes identified and Simpson's index of diversity, the CRISPR method was the least discriminatory and not significantly improved with the inclusion of fimH gene sequencing. While PT analysis identified the most subtypes, the SNP-PCR process generated the greatest index of diversity value. Combining methods consistently improved the number of subtypes identified, with the SNP/CRISPR typing scheme generating a level of diversity comparable with that of PT/PFGE. While these molecular methods, when combined, may have significant utility in real-world situations, this study suggests that CRISPR analysis alone lacks the discriminatory capability required to support investigations of foodborne disease outbreaks. [ABSTRACT FROM AUTHOR]

Background: Cryptosporidium is one of the most prevalent parasites infecting both birds and mammals. To examine the prevalence of Cryptosporidium species and evaluate the public health significance of domestic chickens in Guangdong Province, southern China, we analyzed 1001 fecal samples from 43 intensive broiler chicken farms across six distinct geographical regions. Methods: Individual DNA samples were subjected to nested PCR-based amplification and sequencing of the small subunit of the nuclear ribosomal RNA gene (SSU rRNA). Analysis of the 60 kDa glycoprotein gene (gp60) was performed to characterize the subtypes of C. meleagridis. Results: The overall prevalence of Cryptosporidium was 13.2% (95% CI 11.1–15.3) (24 of 43 farms), with C. meleagridis (7.8%), C. baileyi (4.8%) and mixed infections (0.6%). Using the gp60 gene, three subtype families, IIIb, IIIe and IIIg, were identified, including six subtypes: one novel (IIIgA25G3R1a) and five previously reported (IIIbA23G1R1c, IIIbA24G1R1, IIIbA21G1R1a, IIIeA17G2R1 and IIIeA26G2R1). Within these subtypes, five known subtypes were genetically identical to those identified in humans. Conclusions: This is the first report of C. meleagridis in chickens from Guangdong. The frequent occurrence of C. meleagridis in domestic chickens and the common C. meleagridis subtypes identified in both humans and chickens is of public health significance. Our study indicates that broiler chickens represent a potential zoonotic risk for the transmission of Cryptosporidium in this region. [ABSTRACT FROM AUTHOR]

BackgroundTinnitus is a heterogeneous condition which may be associated with moderate to severe disability, but the reasons why only a subset of individuals is burdened by the condition are not fully clear. Ecological momentary assessment (EMA) allows a better understanding of tinnitus by capturing the fluctuations of tinnitus symptoms, such as distress and loudness, and psychological processes, such as emotional arousal, overall stress, mood, and concentration and how these variables interact over time. Whether any of those variables have an influence over the next day, that is, whether any of these variables are auto- or cross-correlated, is still unanswered.ObjectivesAssess whether behavioral and symptom-related data from tinnitus users from the TrackYourTinnitus (TYT) mobile app have an impact on tinnitus loudness and distress on subsequent days.MethodsAnonymized data was collected from 278 users of the iOS or Android TYT apps between 2014 and 2020. Tinnitus-related distress, tinnitus loudness, concentration level, mood, emotional arousal, and overall stress level were assessed using either a slider or the Wong-Baker Pain FACES scale via a daily survey. Three modeling strategies were used to investigate whether tinnitus loudness and distress are affected by previous days symptoms or psychological processes: auto- and cross correlations, regressions with elastic net regularization, and subgrouping within group iterative multiple model estimation (S-GIMME).ResultsNo autocorrelation or cross-correlation was observed at the group level between the variables assessed. However, application of the regression models with elastic net regularization identified individualized predictors of tinnitus loudness and distress for most participants, with the models including contemporaneous and lagged information from the previous day. S-GIMME corroborated these findings by identifying individualized predictors of tinnitus loudness and distress from the previous day.DiscussionWe showed that tinnitus loudness and tinnitus distress are affected by the contemporaneous and lagged dynamics of behavioral and emotional processes measured through EMA. These effects were seen at the group, and individual levels. The relevance EMA and the implications of the insights derived from it for tinnitus care are discussed, especially considering current trends toward the individualization of tinnitus care.

Cryptosporidiosis is one of the major causes of diarrhea in immune-compromised individuals and children besides causing sporadic water-borne, food-borne, and zoonotic outbreaks. In 2016, Cryptosporidium species infection was the fifth leading cause of diarrhea and acute infection causing more than 4.2 million disability-adjusted life years lost besides a decrease in childhood growth. Human cryptosporidiosis is primarily caused by two species/genotype: Cryptosporidium hominis (anthroponotic) and Cryptosporidium parvum (zoonotic) besides other six rare species/genotypes. Transmission intensity, genetic diversity, and occurrence of genetic recombination have shaped the genus Cryptosporidium population structures into palmitic, clonal, and epidemic. Genetic recombination is more in C. parvum compared with C. hominis. Furthermore, parasite–host co-evolution, host adaptation, and geographic segregation have led to the formation of “subtype- families.” Host-adapted subtype-families have distinct geographical distribution and host preferences. Genetic exchanges between subtypes played an important role throughout the evolution of the genus leading to “adaptation introgression” that led to emergence of virulent and hyper-transmissible subtypes. The population structure of C. hominis in India appears to be more complex where both transmission intensity and genetic diversity are much higher. Further, study based on “molecular strain surveillance” has resulted newer insights into the epidemiology and transmission of cryptosporidiosis in India. The identification at the species and genotype levels is essential for the assessment of infection sources in humans and the public health potential of the parasite at large. The results of the study over three decades on cryptosporidiosis in India, in the absence of a national surveillance data, were analyzed highlighting current situation on epidemiology, genetic diversity, and distribution particularly among vulnerable population. Despite creditable efforts, there are still many areas need to be explored; therefore, the intent of this article is to facilitate future research approaches for mitigating the burden associated with this disease.

• Preliminary evidence of planning and motor subtypes of stuttering based on RSFC. • Increased connectivity in one subtype may relate to impaired biasing of phonemes. • Reduced connectivity in one subtype may relate to impaired timing and coordination. • Value of hypothesis-driven approach to identify potential sources of heterogeneity. We tested the hypothesis, generated from the Gradient Order Directions Into Velocities of Articulators (GODIVA) model, that adults who stutter (AWS) may comprise subtypes based on differing connectivity within the cortico-basal ganglia planning or motor loop. Resting state functional connectivity from 91 AWS and 79 controls was measured for all GODIVA model connections. Based on a principal components analysis, two connections accounted for most of the connectivity variability in AWS: left thalamus – left posterior inferior frontal sulcus (planning loop component) and left supplementary motor area – left ventral premotor cortex (motor loop component). A k-means clustering algorithm using the two connections revealed three clusters of AWS. Cluster 1 was significantly different from controls in both connections; Cluster 2 was significantly different in only the planning loop; and Cluster 3 was significantly different in only the motor loop. These findings suggest the presence of planning and motor subtypes of stuttering. [ABSTRACT FROM AUTHOR]

H5, H7 and H9 are the major subtypes of avian influenza virus (AIV) that cause economic losses in the poultry industry and sporadic zoonotic infection. Early detection of AIV is essential for preventing disease spread. Therefore, molecular diagnosis and subtyping of AIV via real-time RT-PCR (rRT-PCR) is preferred over other classical diagnostic methods, such as egg inoculation, RT-PCR and HI test, due to its high sensitivity, specificity and convenience. The singleplex rRT-PCRs for the Matrix, H5 and H7 gene used for the national surveillance program in Korea have been developed in 2017; however, these methods were not designed for multiplexing, and does not reflect the sequences of currently circulating strains completely. In this study, the multiplex H5/7/9 rRT-PCR assay was developed with sets of primers and probe updated or newly designed to simultaneously detect the H5, H7 and H9 genes. Multiplex H5/7/9 rRT-PCR showed 100% specificity without cross-reactivity with other subtypes of AIVs and avian disease-causing viruses or bacteria, and the limit of detection was 1–10 EID 50 /0.1 ml (50% egg infectious dose). Artificial mixed infections with the three different subtypes could be detected accurately with high analytical sensitivity even under highly biased relative molecular ratios by balancing the reactivities of each subtype by modifying the concentration of the primers and probes. The multiplex H5/7/9 rRT-PCR assay developed in this study could be a useful tool for large-scale surveillance programs for viral detection as well as subtyping due to its high specificity, sensitivity and robustness in discriminating viruses in mixed infections, and this approach would greatly decrease the time, cost, effort and chance of cross-contamination compared to the conventional method of testing three subtypes by different singleplex rRT-PCR methods in parallel or in series. • Primer and probe set for the multiplex H5/7/9 rRT-PCR detect various lineages of H5, H7, and H9 viruses with high sensitivity and specificity. • The multiplex H5/7/9 rRT-PCR showed 100% specificity without cross-reactivity and the limit of detection was 1–10 EID 50 /0.1 ml. • Multiplex H5/7/9 rRT-PCR assay was optimized to simultaneously detect H5, H7, and H9 genes mixed in even highly biased relative molecular ratios among them. • It is useful in the large-scale surveillance for H5, H7 and H9 AIVs due to its robustness to discriminate different subtypes at a single reaction. [ABSTRACT FROM AUTHOR]

Blastocystis is the most common intestinal parasite found in epidemiological studies in Iran. The genus Blastocystis comprises multiple subtypes (ST), evincing the existence of extensive intrageneric diversity. Meanwhile, information on Blastocystis STs in domestic animals in Iran is limited. This study was designed to identify the prevalence and subtype distribution of Blastocystis in domestic animals and to evaluate the extent of zoonotic origin of human Blastocystis carriage. A total of 395 faecal samples from farm animals (220 from poultry, 100 from sheep and 75 from cattle) and 23 Blastocystis positive samples from humans (available from the previous report of this study and included for reference) from the Khuzestan province, southwestern Iran, were analysed. Standard parasitological methods and PCR-based analysis of the SSU-rRNA gene were used. Overall, 115 (29.1%; 95% CI, 26.5%-31.6%) of the animals were positive for Blastocystis sp. by parasitological methods. The highest colonization rate was found in cattle (50.6%, 38/75), followed by sheep (32.0%, 32/100) and poultry (20.4%, 45/220). Eight Blastocystis STs were identified among 55 sequenced isolates from animals (n = 32) and humans (n = 23): ST3 (27.3%), ST14 (25.4%), ST1 (12.7%), ST7 (12.7%), ST2 (9.1%), ST6 (7.3%), ST5 (3.6%) and ST10 (1.8%). Blastocystis ST1 and ST3 were found in both human and non-human hosts, and examples of shared alleles (strains) were observed. Meanwhile, ST2 was observed only in humans, ST5 only in sheep, ST6 only in poultry and ST10 in only cattle. This is the most comprehensive report of Blastocystis STs in farm animals in Iran. [ABSTRACT FROM AUTHOR]

Early psychosocial adversities exist at many levels, including caregiving-related, extrafamilial, and sociodemographic, which despite their high interrelatedness may have unique impacts on development. In this paper, we focus on caregiving-related early adversities (crEAs) and parse the heterogeneity of crEAs via data reduction techniques that identify experiential cooccurrences. Using network science, we characterized crEA cooccurrences to represent the comorbidity of crEA experiences across a sample of school-age children (n = 258; 6–12 years old) with a history of crEAs. crEA dimensions (variable level) and crEA subtypes (subject level) were identified using parallel factor analysis/principal component analysis and graph-based Louvain community detection. Bagging enhancement with cross-validation provided estimates of robustness. These data-driven dimensions/subtypes showed evidence of stability, transcended traditional sociolegally defined groups, were more homogenous than sociolegally defined groups, and reduced statistical correlations with sociodemographic factors. Finally, random forests showed both unique and common predictive importance of the crEA dimensions/subtypes for childhood mental health symptoms and academic skills. These data-driven outcomes provide additional tools and recommendations for crEA data reduction to inform precision medicine efforts in this area. [ABSTRACT FROM AUTHOR]

Theimproving access to increasing amounts of biomedical data provides completely new chances for advanced patient stratification and disease subtyping strategies. This requires computational tools that produce uniformly robust results across highly heterogeneous molecular data. Unsupervised machine learning methodologies are able to discover de novo patterns in such data. Biclustering is especially suited by simultaneously identifying sample groups and corresponding feature sets across heterogeneous omics data. The performance of available biclustering algorithms heavily depends on individual parameterization and varies with their application. Here, we developedMoSBi (molecular signature identification using biclustering), an automated multialgorithm ensemble approach that integrates results utilizing an error model-supported similarity network. We systematically evaluated the performance of 11 available and established biclustering algorithms together with MoSBi. For this, we used transcriptomics, proteomics, and metabolomics data, as well as synthetic datasets covering various data properties. Profiting from multialgorithm integration, MoSBi identified robust group and diseasespecific signatures across all scenarios, overcoming single algorithm specificities. Furthermore, we developed a scalable network-based visualization of bicluster communities that supports biological hypothesis generation. MoSBi is available as an R package and web service to make automated biclustering analysis accessible for application in molecular sample stratification. [ABSTRACT FROM AUTHOR]

Background: Cluster analyses have become popular tools for data-driven classification in biological psychiatric research. However, these analyses are known to be sensitive to the chosen methods and/or modelling options, which may hamper generalizability and replicability of findings. To gain more insight into this problem, we used Specification-Curve Analysis (SCA) to investigate the influence of methodological variation on biomarker-based cluster-analysis results. Methods: Proteomics data (31 biomarkers) were used from patients (n = 688) and healthy controls (n = 426) in the Netherlands Study of Depression and Anxiety. In SCAs, consistency of results was evaluated across 1200 k-means and hierarchical clustering analyses, each with a unique combination of the clustering algorithm, fit-index, and distance metric. Next, SCAs were run in simulated datasets with varying cluster numbers and noise/outlier levels to evaluate the effect of data properties on SCA outcomes. Results: The real data SCA showed no robust patterns of biological clustering in either the MDD or a combined MDD/healthy dataset. The simulation results showed that the correct number of clusters could be identified quite consistently across the 1200 model specifications, but that correct cluster identification became harder when the number of clusters and noise levels increased. Conclusion: SCA can provide useful insights into the presence of clusters in biomarker data. However, SCA is likely to show inconsistent results in real-world biomarker datasets that are complex and contain considerable levels of noise. Here, the number and nature of the observed clusters may depend strongly on the chosen model-specification, precluding conclusions about the existence of biological clusters among psychiatric patients. [ABSTRACT FROM AUTHOR]

Subtyping of bacterial isolates of the same genus and species is an important tool in epidemiological investigations. A number of phenotypic and genotypic subtyping methods are available; however, most of these methods are labor-intensive and time-consuming and require considerable operator skill and a wealth of reagents. Matrix-Assisted Laser Desorption–Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF), an alternative to conventional subtyping methods, offers a rapid, reproducible method for bacterial identification with a high sensitivity and specificity and at minimal cost. The purpose of this study was to determine the feasibility of using MALDI-TOF to differentiate between six Salmonella serovars recovered from experimental microcosms inoculated with known strains of Salmonella. Following the establishment of a MALDI-TOF reference library for this project, the identity of 843 Salmonella isolates recovered from these microcosms was assessed using both MALDI-TOF and conventional methods (serotyping/PCR). All 843 isolates were identified as being Salmonella species. Overall, 803/843 (95%) of these isolates were identified similarly using the two different methods. Positive percent agreement at the serovar level ranged from 79 to 100%, and negative percent agreement for all serovars was greater than 98%. Cohen's kappa ranged from 0.85 to 0.98 for the different serovars. This study demonstrates that MALDI-TOF is a viable alternative for the rapid identification and differentiation of Salmonella serovars. [ABSTRACT FROM AUTHOR]

Clinically, accurate pathological diagnosis is often challenged by insufficient tissue amounts and the unaffordability of additional immunohistochemical or genetic tests; thus, there is an urgent need for a universal approach to improve the subtyping of lung cancer without the above limitations. Here we aimed to develop a deep learning system to predict the immunohistochemistry (IHC) phenotype directly from whole-slide images (WSIs) to improve the subtyping of lung cancer from surgical resection and biopsy specimens. A total of 1914 patients with lung cancer from three independent hospitals in China were enrolled for WSI-based immunohistochemical feature prediction system (WIFPS) development and validation. The WIFPS could directly predict the IHC status of nine subtype-specific biomarkers, including CK7, TTF-1, Napsin A, CK5/6, P63, P40, CD56, Synaptophysin, and Chromogranin A, achieving average areas under the curve (AUCs) of 0.912, 0.906, and 0.888 and overall diagnostic accuracies of 0.925, 0.941, and 0.887 in the validation datasets of total, external surgical resection specimens and biopsy specimens, respectively. The histological subtyping performance of the WIFPS remained comparable with that of general pathologists (GPs), with Cohen's kappa values ranging from 0.7646 to 0.8282. Furthermore, the WIFPS could be trained to not only predict the IHC status of anaplastic lymphoma kinase (ALK), programmed death-1 (PD-1), and programmed death ligand 1 (PD-L1), but also predict EGFR and KRAS mutation status, with AUCs from 0.525 to 0.917, as detected in separate populations. In this study, the WIFPS showed its proficiency as a useful complement to traditional histologic subtyping for integrated immunohistochemical spectrum prediction as well as potential in the detection of gene mutations. [ABSTRACT FROM AUTHOR]

Cryptosporidium parvum is one of the major causes of neonatal calf diarrhoea resulting in reduced farm productivity and compromised animal welfare worldwide. Livestock act as a major reservoir of this parasite, which can be transmitted to humans directly and/or indirectly, posing a public health risk. Research reports on the prevalence of Cryptosporidium in ruminants from east Mediterranean countries, including Cyprus, are limited. This study is the first to explore the occurrence of Cryptosporidium spp. in cattle up to 24 months old on the island of Cyprus. A total of 242 faecal samples were collected from 10 dairy cattle farms in Cyprus, all of which were screened for Cryptosporidium spp. using nested-PCR amplification targeting the small subunit of the ribosomal RNA (18S rRNA) gene. The 60 kDa glycoprotein (gp60) gene was also sequenced for the samples identified as Cryptosporidium parvum-positive to determine the subtypes present. The occurrence of Cryptosporidium was 43.8% (106/242) with at least one positive isolate in each farm sampled. Cryptosporidium bovis, Cryptosporidium ryanae and C. parvum were the only species identified, while the prevalence per farm ranged from 20–64%. Amongst these, the latter was the predominant species, representing 51.8% of all positive samples, followed by C. bovis (21.7%) and C. ryanae (31.1%). Five C. parvum subtypes were identified, four of which are zoonotic—IIaA14G1R1, IIaA15G1R1, IIaA15G2R1 and IIaA18G2R1. IIaA14G1R1 was the most abundant, representing 48.2% of all C. parvum positive samples, and was also the most widespread. This is the first report of zoonotic subtypes of C. parvum circulating in Cyprus. These results highlight the need for further research into the parasite focusing on its diversity, prevalence, host range and transmission dynamics on the island. [ABSTRACT FROM AUTHOR]

In routine surveillance for avian influenza viruses (AIVs) in the environments of live poultry markets (LPMs), certain samples were positive for AIVs type A while negative for subtypes (e.g., H5, H7, and H9). However, little attention has been paid to these unsubtyped AIVs samples. To reveal the dynamic distribution and molecular characteristics of AIVs, especially the unsubtyped AIVs, we reported and analyzed 1969 samples collected from the water environments of LPMs in Changsha, China, from January 2014 to November 2018. Our results revealed that 1504 (76.38%) samples were positive for AIV type A. Of these samples, the predominant hemagglutinin (HA) subtype was H9, followed by H5 and H7 (P < 0.05). The positive rate of H5 subtype in water environmental samples exhibited seasonality, which reached a peak in each winter–spring season from January 2014 to March 2017. The positive rates of AIVs (including type A, subtype H9, and mixed subtype H5/H7/H9) in non-central-city regions were higher than that in the central-city regions (P < 0.05). Notably, 161 unsubtyped AIVs samples were detected during the routine surveillance. However, subtyping with the commercial kit further identified eight different HA and seven different neuraminidase subtypes. Analyses unraveled that further subtyped AIVs H1, H6, and H11 had only one basic amino acid (R or K) at the cleavage site and residues Q226 and G228 at the receptor-binding associated sites. Overall, in addition to H5, H7, and H9 subtypes, we should also pay attention to unsubtyped AIVs samples during the routine surveillance for AIVs in the environments of LPMs. [ABSTRACT FROM AUTHOR]