A single-cell atlas of the developing Drosophila ovary identifies follicle stem cell progenitors.

Addressing the complexity of organogenesis at a system-wide level requires a complete understanding of adult cell types, their origin, and precursor relationships. The Drosophila ovary has been a model to study how coordinated stem cell units, germline, and somatic follicle stem cells maintain and renew an organ. However, lack of cell type-specific tools have limited our ability to study the origin of individual cell types and stem cell units. Here, we used a single-cell RNA sequencing approach to uncover all known cell types of the developing ovary, reveal transcriptional signatures, and identify cell type-specific markers for lineage tracing. Our study identifies a novel cell type corresponding to the elusive follicle stem cell precursors and predicts subtypes of known cell types. Altogether, we reveal a previously unanticipated complexity of the developing ovary and provide a comprehensive resource for the systematic analysis of ovary morphogenesis.

Network architecture of intrinsic connectivity in a mammalian spinal cord (the central nervous system's caudal sector).

The vertebrate spinal cord (SP) is the long, thin extension of the brain forming the central nervous system's caudal sector. Functionally, the SP directly mediates motor and somatic sensory interactions with most parts of the body except the face, and it is the preferred model for analyzing relatively simple reflex behaviors. Here, we analyze the organization of axonal connections between the 50 gray matter regions forming the bilaterally symmetric rat SP. The assembled dataset suggests that there are about 385 of a possible 2,450 connections between the 50 regions for a connection density of 15.7%. Multiresolution consensus cluster analysis reveals a hierarchy of structure-function subsystems in this neural network, with 4 subsystems at the top level and 12 at the bottom-level. The top-level subsystems include a) a bilateral subsystem related most clearly to somatic and autonomic motor functions and centered in the ventral horn and intermediate zone; b) a bilateral subsystem associated with general somatosensory functions and centered in the base, neck, and head of the dorsal horn; and c) a pair of unilateral, bilaterally symmetric subsystems associated with nociceptive information processing and occupying the apex of the dorsal horn. The intrinsic SP network displayed no hubs, rich club, or small-world attributes, which are common measures of global functionality. Advantages and limitations of our methodology are discussed in some detail. The present work is part of a comprehensive project to assemble and analyze the neurome of a mammalian nervous system and its interactions with the body.

Intrinsic circuitry of the rhombicbrain (central nervous system's intermediate sector) in a mammal.

The rhombicbrain (rhombencephalon or intermediate sector) is the vertebrate central nervous system part between the forebrain-midbrain (rostral sector) and spinal cord (caudal sector), and it has three main divisions: pons, cerebellum, and medulla. Using a data-driven approach, here we examine intrinsic rhombicbrain (intrarhombicbrain) network architecture that in rat consists of 52,670 possible axonal connections between 230 gray matter regions (115 bilaterally symmetrical pairs). Our analysis indicates that only 8,089 (15.4%) of these connections exist. Multiresolution consensus cluster analysis yields a nested hierarchy model of rhombicbrain subsystems that at the top level are associated with 1) the cerebellum and vestibular nuclei, 2) orofacial-pharyngeal-visceral integration, and 3) auditory connections; the bottom level has 68 clusters, ranging in size from 2 to 11 regions. The model provides a basis for functional hypothesis development and interrogation. More granular network analyses performed on the intrinsic connectivity of individual and combined main rhombicbrain divisions (pons, cerebellum, medulla, pons + cerebellum, and pons + medulla) demonstrate the mutability of network architecture in response to the addition or subtraction of connections. Clear differences between the structure-function network architecture of the rhombicbrain and forebrain-midbrain are discussed, with a stark comparison provided by the subsystem and small-world organization of the cerebellar cortex and cerebral cortex. Future analysis of the connections within and between the forebrain-midbrain and rhombicbrain will provide a model of brain neural network architecture in a mammal.

Adenosinergic Modulation of Layer 6 Microcircuitry in the Medial Prefrontal Cortex Is Specific to Presynaptic Cell Type.

Adenosinergic modulation in the PFC is recognized for its involvement in various behavioral aspects including sleep homoeostasis, decision-making, spatial working memory and anxiety. While the principal cells of layer 6 (L6) exhibit a significant morphological diversity, the detailed cell-specific regulatory mechanisms of adenosine in L6 remain unexplored. Here, we quantitatively analyzed the morphological and electrophysiological parameters of L6 neurons in the rat medial prefrontal cortex (mPFC) using whole-cell recordings combined with morphological reconstructions. We were able to identify two different morphological categories of excitatory neurons in the mPFC of both juvenile and young adult rats with both sexes. These categories were characterized by a leading dendrite that was oriented either upright (toward the pial surface) or inverted (toward the white matter). These two excitatory neuron subtypes exhibited different electrophysiological and synaptic properties. Adenosine at a concentration of 30 µM indiscriminately suppressed connections with either an upright or an inverted presynaptic excitatory neuron. However, using lower concentrations of adenosine (10 µM) revealed that synapses originating from L6 upright neurons have a higher sensitivity to adenosine-induced inhibition of synaptic release. Adenosine receptor activation causes a reduction in the probability of presynaptic neurotransmitter release that could be abolished by specifically blocking A1 adenosine receptors (A1ARs) using 8-cyclopentyltheophylline (CPT). Our results demonstrate a differential expression level of A1ARs at presynaptic sites of two functionally and morphologically distinct subpopulations of L6 principal neurons, suggesting the intricate functional role of adenosine in neuronal signaling in the brain.

CEMIG: prediction of the cis-regulatory motif using the de Bruijn graph from ATAC-seq.

Sequence motif discovery algorithms enhance the identification of novel deoxyribonucleic acid sequences with pivotal biological significance, especially transcription factor (TF)-binding motifs. The advent of assay for transposase-accessible chromatin using sequencing (ATAC-seq) has broadened the toolkit for motif characterization. Nonetheless, prevailing computational approaches have focused on delineating TF-binding footprints, with motif discovery receiving less attention. Herein, we present Cis rEgulatory Motif Influence using de Bruijn Graph (CEMIG), an algorithm leveraging de Bruijn and Hamming distance graph paradigms to predict and map motif sites. Assessment on 129 ATAC-seq datasets from the Cistrome Data Browser demonstrates CEMIG's exceptional performance, surpassing three established methodologies on four evaluative metrics. CEMIG accurately identifies both cell-type-specific and common TF motifs within GM12878 and K562 cell lines, demonstrating its comparative genomic capabilities in the identification of evolutionary conservation and cell-type specificity. In-depth transcriptional and functional genomic studies have validated the functional relevance of CEMIG-identified motifs across various cell types. CEMIG is available at https://github.com/OSU-BMBL/CEMIG, developed in C++ to ensure cross-platform compatibility with Linux, macOS and Windows operating systems.

Identification and validation of gestational diabetes subgroups by data-driven cluster analysis.

AIMS/HYPOTHESIS: Gestational diabetes mellitus (GDM) is a heterogeneous condition. Given such variability among patients, the ability to recognise distinct GDM subgroups using routine clinical variables may guide more personalised treatments. Our main aim was to identify distinct GDM subtypes through cluster analysis using routine clinical variables, and analyse treatment needs and pregnancy outcomes across these subgroups. METHODS: In this cohort study, we analysed datasets from a total of 2682 women with GDM treated at two central European hospitals (1865 participants from Charité University Hospital in Berlin and 817 participants from the Medical University of Vienna), collected between 2015 and 2022. We evaluated various clustering models, including k-means, k-medoids and agglomerative hierarchical clustering. Internal validation techniques were used to guide best model selection, while external validation on independent test sets was used to assess model generalisability. Clinical outcomes such as specific treatment needs and maternal and fetal complications were analysed across the identified clusters. RESULTS: Our optimal model identified three clusters from routinely available variables, i.e. maternal age, pre-pregnancy BMI (BMIPG) and glucose levels at fasting and 60 and 120 min after the diagnostic OGTT (OGTT0, OGTT60 and OGTT120, respectively). Cluster 1 was characterised by the highest OGTT values and obesity prevalence. Cluster 2 displayed intermediate BMIPG and elevated OGTT0, while cluster 3 consisted mainly of participants with normal BMIPG and high values for OGTT60 and OGTT120. Treatment modalities and clinical outcomes varied among clusters. In particular, cluster 1 participants showed a much higher need for glucose-lowering medications (39.6% of participants, compared with 12.9% and 10.0% in clusters 2 and 3, respectively, p<0.0001). Cluster 1 participants were also at higher risk of delivering large-for-gestational-age infants. Differences in the type of insulin-based treatment between cluster 2 and cluster 3 were observed in the external validation cohort. CONCLUSIONS/INTERPRETATION: Our findings confirm the heterogeneity of GDM. The identification of subgroups (clusters) has the potential to help clinicians define more tailored treatment approaches for improved maternal and neonatal outcomes.

Heterogeneity of glycaemic phenotypes in type 1 diabetes.

AIMS/HYPOTHESIS: Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes. METHODS: In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison. RESULTS: We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes. CONCLUSIONS/INTERPRETATION: Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.

DendroX: multi-level multi-cluster selection in dendrograms.

BACKGROUND: Cluster heatmaps are widely used in biology and other fields to uncover clustering patterns in data matrices. Most cluster heatmap packages provide utility functions to divide the dendrograms at a certain level to obtain clusters, but it is often difficult to locate the appropriate cut in the dendrogram to obtain the clusters seen in the heatmap or computed by a statistical method. Multiple cuts are required if the clusters locate at different levels in the dendrogram. RESULTS: We developed DendroX, a web app that provides interactive visualization of a dendrogram where users can divide the dendrogram at any level and in any number of clusters and pass the labels of the identified clusters for functional analysis. Helper functions are provided to extract linkage matrices from cluster heatmap objects in R or Python to serve as input to the app. A graphic user interface was also developed to help prepare input files for DendroX from data matrices stored in delimited text files. The app is scalable and has been tested on dendrograms with tens of thousands of leaf nodes. As a case study, we clustered the gene expression signatures of 297 bioactive chemical compounds in the LINCS L1000 dataset and visualized them in DendroX. Seventeen biologically meaningful clusters were identified based on the structure of the dendrogram and the expression patterns in the heatmap. We found that one of the clusters consisting of mostly naturally occurring compounds is not previously reported and has its members sharing broad anticancer, anti-inflammatory and antioxidant activities. CONCLUSIONS: DendroX solves the problem of matching visually and computationally determined clusters in a cluster heatmap and helps users navigate among different parts of a dendrogram. The identification of a cluster of naturally occurring compounds with shared bioactivities implicates a convergence of biological effects through divergent mechanisms.

Unhealthy lifestyle behaviors, overweight, and obesity among childhood cancer survivors in the Netherlands: A DCCSS LATER study.

BACKGROUND: The objective of this study was to examine the prevalence of unhealthy lifestyle behaviors, overweight, and obesity in Dutch childhood cancer survivors (CCSs) compared with sibling controls and the Dutch general population. Other aims were to assess associated factors of unhealthy lifestyle behaviors, overweight, and obesity and to identify subgroups of CCSs at risk for these unhealthy statuses. METHODS: The authors included 2253 CCSs and 906 siblings from the Dutch Childhood Cancer Survivor Study-Late Effects After Childhood Cancer cohort, part 1, and added data from the Dutch general population. Questionnaire data were collected on overweight and obesity (body mass index >25.0 kg/m2), meeting physical activity guidelines (>150 minutes per week of moderate or vigorous exercises), excessive alcohol consumption (>14 and >21 alcoholic consumptions per week for women and men, respectively), daily smoking, and monthly drug use. Multivariable logistic regression analyses and two-step cluster analyses were performed to examine sociodemographic-related, health-related, cancer-related, and treatment-related associated factors of unhealthy lifestyle behaviors and to identify subgroups of CCSs at risk for multiple unhealthy behaviors. RESULTS: CCSs more often did not meet physical activity guidelines than their siblings (30.0% vs. 19.3%; p < .001). Married as marital status, lower education level, nonstudent status, and comorbidities were common associated factors for a body mass index ≥25.0 kg/m2 and insufficient physical activity, whereas male sex and lower education were shared associated factors for excessive alcohol consumption, daily smoking, and monthly drug use. A subgroup of CCSs was identified as excessive alcohol consumers, daily smokers, and monthly drug users. CONCLUSIONS: The current results emphasize the factors associated with unhealthy behaviors and the potential identification of CCSs who exhibit multiple unhealthy lifestyle behaviors.

Codon usage bias and phylogenetic analysis of chloroplast genome in 36 gracilariaceae species.

Gracilariaceae is a group of marine large red algae and main source of agar with important economic and ecological value. The codon usage patterns of chloroplast genomes in 36 species from Graciliaceae show that GC range from 0.284 to 0.335, the average GC3 range from 0.135 to 0.243 and the value of ENC range from 35.098 to 42.327, which indicates these genomes are rich in AT and prefer to use codons ending with AT in these species. Nc plot, PR2 plot, neutrality plot analyses and correlation analysis indicate that these biases may be caused by multiple factors, such as natural selection and mutation pressure, but prolonged natural selection is the main driving force influencing codon usage preference. The cluster analysis and phylogenetic analysis show that the differentiation relationship of them is different and indicate that codons with weak or unbiased preferences may also play an irreplaceable role in these species' evolution. In addition, we identified 26 common high-frequency codons and 8-18 optimal codons all ending in A/U in these 36 species. Our results will not only contribute to carrying out transgenic work in Gracilariaceae species to maximize the protein yield in the future, but also lay a theoretical foundation for further exploring systematic classification of them.

Raman developmental markers in root cell walls are associated with lodging tendency in tef.

MAIN CONCLUSION: Using Raman micro-spectroscopy on tef roots, we could monitor cell wall maturation in lines with varied genetic lodging tendency. We describe the developing cell wall composition in root endodermis and cylinder tissue. Tef [Eragrostis tef (Zucc.) Trotter] is an important staple crop in Ethiopia and Eritrea, producing gluten-free and protein-rich grains. However, this crop is not adapted to modern farming practices due to high lodging susceptibility, which prevents the application of mechanical harvest. Lodging describes the displacement of roots (root lodging) or fracture of culms (stem lodging), forcing plants to bend or fall from their vertical position, causing significant yield losses. In this study, we aimed to understand the microstructural properties of crown roots, underlining tef tolerance/susceptibility to lodging. We analyzed plants at 5 and 10 weeks after emergence and compared trellised to lodged plants. Root cross sections from different tef genotypes were characterized by scanning electron microscopy, micro-computed tomography, and Raman micro-spectroscopy. Lodging susceptible genotypes exhibited early tissue maturation, including developed aerenchyma, intensive lignification, and lignin with high levels of crosslinks. A comparison between trellised and lodged plants suggested that lodging itself does not affect the histology of root tissue. Furthermore, cell wall composition along plant maturation was typical to each of the tested genotypes independently of trellising. Our results suggest that it is possible to select lines that exhibit slow maturation of crown roots. Such lines are predicted to show reduction in lodging and facilitate mechanical harvest.

Identification of two hidden clinical subgroups among men with idiopathic cryptozoospermia.

STUDY QUESTION: Are there subgroups among patients with cryptozoospermia pointing to distinct etiologies? SUMMARY ANSWER: We reveal two distinct subgroups of cryptozoospermic (Crypto) patients based on testicular tissue composition, testicular volume, and FSH levels. WHAT IS KNOWN ALREADY: Cryptozoospermic patients present with a sperm concentration below 0.1 million/ml. While the etiology of the severely impaired spermatogenesis remains largely unknown, alterations of the spermatogonial compartment have been reported including a reduction of the reserve stem cells in these patients. STUDY DESIGN, SIZE, DURATION: To assess whether there are distinct subgroups among cryptozoospermic patients, we applied the statistical method of cluster analysis. For this, we retrospectively selected 132 cryptozoospermic patients from a clinical database who underwent a testicular biopsy in the frame of fertility treatment at a university hospital. As controls (Control), we selected 160 patients with obstructive azoospermia and full spermatogenesis. All 292 patients underwent routine evaluation for endocrine, semen, and histological parameters (i.e. the percentage of tubules with elongated spermatids). Moreover, outcome of medically assisted reproduction (MAR) was assessed for cryptozoospermic (n = 73) and Control patients (n = 87), respectively. For in-depth immunohistochemical and histomorphometrical analyses, representative tissue samples from cryptozoospermic (n = 27) and Control patients (n = 12) were selected based on cluster analysis results and histological parameters. PARTICIPANTS/MATERIALS, SETTING, METHODS: This study included two parts: firstly using clinical parameters of the entire cohort of 292 patients, we performed principal component analysis (PCA) followed by hierarchical clustering on principal components (i.e. considering hormonal values, ejaculate parameters, and histological information). Secondly, for histological analyses seminiferous tubules were categorized according to the most advanced germ cell type present in sections stained with Periodic acid Schif. On the selected cohort of 39 patients (12 Control, 27 cryptozoospermic), we performed immunohistochemistry for spermatogonial markers melanoma-associated antigen 4 (MAGEA4) and piwi like RNA-mediated gene silencing 4 (PIWIL4) followed by quantitative analyses. Moreover, the morphologically defined Adark spermatogonia, which are considered to be the reserve stem cells, were quantified. MAIN RESULTS AND THE ROLE OF CHANCE: The PCA and hierarchical clustering revealed three different clusters, one of them containing all Control samples. The main factors driving the sorting of patients to the clusters were the percentage of tubules with elongated spermatids (Cluster 1, all Control patients and two cryptozoospermic patients), the percentage of tubules with spermatocytes (Cluster 2, cryptozoospermic patients), and tubules showing a Sertoli cells only phenotype (Cluster 3, cryptozoospermic patients). Importantly, the percentage of tubules containing elongated spermatids was comparable between Clusters 2 and 3. Additional differences were higher FSH levels (P < 0.001) and lower testicular volumes (P < 0.001) in Cluster 3 compared to Cluster 2. In the spermatogonial compartment of both cryptozoospermic Clusters, we found lower numbers of MAGEA4+ and Adark spermatogonia but higher proportions of PIWIL4+ spermatogonia, which were significantly correlated with a lower percentage of tubules containing elongated spermatids. In line with this common alteration, the outcome of MAR was comparable between Controls as well as both cryptozoospermic Clusters. LIMITATIONS, REASONS FOR CAUTION: While we have uncovered the existence of subgroups within the cohort of cryptozoospermic patients, comprehensive genetic analyses remain to be performed to unravel potentially distinct etiologies. WIDER IMPLICATIONS OF THE FINDINGS: The novel insight that cryptozoospermic patients can be divided into two subgroups will facilitate the strategic search for underlying genetic etiologies. Moreover, the shared alterations of the spermatogonial stem cell compartment between the two cryptozoospermic subgroups could represent a general response mechanism to the reduced output of sperm, which may be associated with a progressive phenotype. This study therefore offers novel approaches towards the understanding of the etiology underlying the reduced sperm formation in cryptozoospermic patients. STUDY FUNDING/COMPETING INTEREST(S): German research foundation CRU 326 (grants to: SDP, NN). Moreover, we thank the Faculty of Medicine of the University of Münster for the financial support of Lena Charlotte Schülke through the MedK-program. We acknowledge support from the Open Access Publication Fund of the University of Münster. The authors have no potential conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

A cuproptosis score model and prognostic score model can evaluate clinical characteristics and immune microenvironment in NSCLC.

BACKGROUND: Cuproptosis-related genes (CRGs) are associated with lung adenocarcinoma. However, the links between CRGs and non-small-cell lung cancer (NSCLC) are not clear. In this study, we aimed to develop two cuproptosis models and investigate their correlation with NSCLC in terms of clinical features and tumor microenvironment. METHODS: CRG expression profiles and clinical data from NSCLC and normal tissues was obtained from GEO (GSE42127) and TCGA datasets. Molecular clusters were classified into three patterns based on CRGs and cuproptosis cluster-related specific differentially expressed genes (CRDEGs). Then, two clinical models were established. First, a prognostic score model based on CRDEGs was established using univariate/multivariate Cox analysis. Then, through principal component analysis, a cuproptosis score model was established based on prognosis-related genes acquired via univariate analysis of CRDEGs. NSCLC patients were divided into high/low risk groups. RESULTS: Eighteen CRGs were acquired, all upregulated in tumor tissues, 15 of which significantly (P < 0.05). Among the three CRG clusters, cluster B had the best prognosis. In the CRDEG clusters, cluster C had the best survival. In the prognostic score model, the high-risk group had worse prognosis, higher tumor mutation load, and lower immune infiltration while in the cuproptosis score model, a high score represented better survival, lower tumor mutation load, and high-level immune infiltration. CONCLUSIONS: The cuproptosis score model and prognostic score model may be associated with NSCLC prognosis and immune microenvironment. These novel findings on the progression and immune landscape of NSCLC may facilitate the provision of more personalized immunotherapy interventions for NSCLC patients.

Phenotypic subtypes of fibrotic hypersensitivity pneumonitis identified by machine learning consensus clustering analysis.

BACKGROUND: Patients with fibrotic hypersensitivity pneumonitis (f-HP) have varied clinical and radiologic presentations whose associated phenotypic outcomes have not been previously described. We conducted a study to evaluate mortality and lung transplant (LT) outcomes among clinical clusters of f-HP as characterized by an unsupervised machine learning approach. METHODS: Consensus cluster analysis was performed on a retrospective cohort of f-HP patients diagnosed according to recent international guideline. Demographics, antigen exposure, radiologic, histopathologic, and pulmonary function findings along with comorbidities were included in the cluster analysis. Cox proportional-hazards regression was used to assess mortality or LT risk as a combined outcome for each cluster. RESULTS: Three distinct clusters were identified among 336 f-HP patients. Cluster 1 (n = 158, 47%) was characterized by mild restriction on pulmonary function testing (PFT). Cluster 2 (n = 46, 14%) was characterized by younger age, lower BMI, and a higher proportion of identifiable causative antigens with baseline obstructive physiology. Cluster 3 (n = 132, 39%) was characterized by moderate to severe restriction. When compared to cluster 1, mortality or LT risk was lower in cluster 2 (hazard ratio (HR) of 0.42; 95% CI, 0.21-0.82; P = 0.01) and higher in cluster 3 (HR of 1.76; 95% CI, 1.24-2.48; P = 0.001). CONCLUSIONS: Three distinct phenotypes of f-HP with unique mortality or transplant outcomes were found using unsupervised cluster analysis, highlighting improved mortality in fibrotic patients with obstructive physiology and identifiable antigens.

Cluster analysis of cancer knowledge, attitudes and behaviors in the Moroccan population.

BACKGROUND: Cancer has become a major health concern due to the increasing morbidity and mortality rates, and its negative social, economic consequences and the heavy financial burden incurred by cancer patients. About 40% of cancers are preventable. The aim of this study was to assess the knowledge, attitudes, and practices regarding cancer prevention, and associated characteristics to inform the development of targeted cancer prevention campaigns and policies. METHODS: We conducted a cross-sectional survey of adult patients at Mohamed Sekkat and Sidi Othmane Hospitals in Casablanca, Morocco. Data collection was conducted by two trained interviewers who administered the questionnaire in-person in the local language. An unsupervised clustering approach included 17 candidate variables for the cluster analysis. The variables covered a wide range of characteristics, including demographics, health perceptions and attitudes. Survey answers were calculated to compose qualitative ordinal categories, including a cancer attitude score and knowledge score. RESULTS: The cluster-based analysis showed that participants in cluster 1 had the highest mean attitude score (13.9 ± 2.15) and percentage of individuals with a high level of knowledge (50.8%) whereas the lowest mean attitude score (9.48 ± 2.02) and knowledge level (7.5%.) were found in cluster 3. The participants with the lowest cancer attitude scores and knowledge levels were aged 34 to 47 years old (middle age group), predominantly females, living in rural settings, and were least likely to report health professionals as a source of health information. CONCLUSIONS: The findings showed that female individuals living in rural settings, belonging to an older age group, who were least likely to use health professionals as an information source had the lowest levels of knowledge and attitudes. These groups are amenable to targeted and tailored interventions aiming to modify their understanding of cancer in order to enhance the outcomes of Morocco's on-going efforts in cancer prevention and control strategies.

Free water alterations in different inflammatory subgroups in schizophrenia.

BACKGROUND: Accumulating evidence suggests that inflammatory dysregulation both in blood and the brain is implicated in the pathogenesis of schizophrenia. Alterations in peripheral cytokines are not evident in all patients and there may be discrete altered inflammatory subgroups in schizophrenia. Recent studies using a novel and in vivo free-water imaging to detect inflammatory processes, have shown increased free water in white matter in schizophrenia. However, no studies to date have investigated the free water alterations in different inflammatory subgroups in schizophrenia. METHODS: Forty-four patients with schizophrenia and 49 controls were recruited. The serum levels of interleukin-1 beta (IL-1ß), IL-6, IL-10, and IL-12p70 were measured and used for cluster analysis with K-means and hierarchical algorithms. Diffusion tensor imaging (DTI) images were collected for all participants and voxel-wise free water and fractional anisotropy of tissue (FA-t) were compared between groups with Randomise running in FSL. Partial correlation analysis was employed to explore the association of the peripheral cytokine levels with free water. RESULTS: We identified two statistically quantifiable discrete subgroups of patients based on the cluster analysis of cytokine measures. The peripheral levels of IL-1ß (P < 0.001), IL-10 (P = 0.041), and IL-12p70 (P < 0.001) showed significant differences between the two different inflammatory subgroups. In the inflammatory subgroup with a predominantly higher IL-1ß level, increased free water values in white matter were found mainly in the left posterior limb of the internal capsule, posterior corona radiata, and partly in the left sagittal stratum. These affected areas did not overlap with the regions that showed significant free water differences between patients and healthy controls. In the inflammatory subgroup with lower IL-1ß levels, peripheral IL-1ß was significantly associated with free water values in white matter while no such association was detected in the patient group. CONCLUSIONS: Localized free water differences were demonstrated between the two identified inflammatory subgroups in our data, and free water appears to be a feasible in vivo neuroimaging biomarker guiding the target of inflammatory intervention and development of new therapeutic strategies in an individualized manner in schizophrenia.

Recent trends in disease-modifying therapy use and associated sickness absence and disability pension among people with multiple sclerosis in Sweden.

BACKGROUND: Disease-modifying therapies (DMTs) have led to improved health and work productivity among people with multiple sclerosis (PwMS). OBJECTIVES: To describe trajectories of recent DMT use and their association with sickness absence and/or disability pension (SADP) among PwMS in Sweden. METHODS: A longitudinal register-based study was conducted among 1395 PwMS with treatment start in 2014/2015. While DMT use over 5 years was assessed using sequence analysis resulting in four clusters, a 7-year (Y-2 toY4) trend of SADP was analyzed using zero-inflated negative binomial regression. RESULTS: Four clusters of DMT use trajectories were identified: long-term non-high-efficacy (483, 34.6%), long-term high-efficacy (572, 41%), escalation (221, 15.8%), and discontinuation (119, 8.5%). Progressive MS and higher expanded disability status scale scores were associated with the escalation, long-term high-efficacy, or discontinuation clusters. PwMS in the long-term high-efficacy and escalation clusters had higher likelihood of being on SADP. However, PwMS initiating high-efficacy DMTs demonstrated steeper decline in SADP than others. CONCLUSION: Using sequence analysis, this study showed recent DMT use trajectories among PwMS where initiation of high-efficacy DMTs has become more common. The trend of SADP was stable and lower in those using non-high-efficacy DMTs and larger improvements were shown in those initiating high-efficacy DMTs.

Epidemiology and genotypes analysis of human papillomavirus infection in Beijing, China.

BACKGROUND: This study aimed to investigate the epidemiology of high-risk human papillomavirus (HPV) in the female population in Beijing, China, and identify the relationship between HPV genotypes and host factors. METHODS: HPV testing was performed on women aged 15-89 (mean age 38.0 ± 10.9 years) from Beijing in 2020. High-risk HPV genotyping real-time polymerase chain reaction was used to determine HPV genotypes. The overall prevalence, age-specific prevalence, genotype distribution, and the correlation between HPV genotypes and cervical cytology were analyzed. RESULTS: Among the 25,344 study participants, the single and double infection rates were 18.8% (4,777/25,344) and 4.2% (1,072/25,344), respectively. A total of 6,119 HPV-positive individuals were found to have 91.6% negative results for intraepithelial lesion or malignancy (NILM), 5.8% atypical squamous cells of undetermined significance (ASC-US), 0.9% low-grade squamous intraepithelial lesion (LSIL), and 1.7% high-grade squamous intraepithelial lesion (HSIL). In single HPV infections, the HPV16 genotype was highly associated with cervical cytology severity (χ2 trend = 172.487, P < 0.001). Additionally, HPV infection rates increased gradually with age, and statistical differences were observed across age groups (χ2 = 180.575; P < 0.001). High-risk HPV genotypes were highly prevalent in women below 25 years of age and those aged 55-59 years. Cluster analysis revealed that the 13 HPV genotypes could be roughly divided into two groups in a single infection; however, patterns of infection consistent with biological characteristics were not observed. CONCLUSION: High-risk HPV was found in 24.1% of outpatients, with HPV52, HPV58, HPV16, HPV39, and HPV51 being the most common high-risk genotypes. Single high-risk HPV infection was predominant. HPV16, HPV39, HPV51, and HPV52 were associated with cervical lesion progression. HPV16 infection was especially worrying since it aggravates cervical lesions. Because the infection rates of the 13 HPV genotypes differed by age, the peak HPV infection rate should not guide vaccination, screening, and prevention programs. Instead, these initiatives should be tailored based on the regional HPV distribution characteristics. Moreover, it was determined that Beijing's populace needed to receive treatment for HPV39 infection.

Preoperative prolapse phenotype is predictive of surgical outcome with minimally invasive sacrocolpopexy.

BACKGROUND: The gold-standard treatment for advanced pelvic organ prolapse is sacrocolpopexy. However, the preoperative features of prolapse that predict optimal outcomes are unknown. OBJECTIVE: This study aimed to develop a clinical prediction model that uses preoperative scores on the Pelvic Organ Prolapse Quantification examination to predict outcomes after minimally invasive sacrocolpopexy for stages 2, 3, and 4 uterovaginal prolapse and vaginal vault prolapse. STUDY DESIGN: A 2-institution database of pre- and postoperative variables from 881 cases of minimally invasive sacrocolpopexy was analyzed. Data from patients were analyzed in the following 4 groups: stage 2 uterovaginal prolapse, stage 3 to 4 uterovaginal prolapse, stage 2 vaginal vault prolapse, and stage 3 to 4 vaginal vault prolapse. Unsupervised machine learning was used to identify clusters and investigate associations between clusters and outcome. The k-means clustering analysis was performed with preoperative Pelvic Organ Prolapse Quantification points and stratified by previous hysterectomy status. The "optimal" surgical outcome was defined as postoperative Pelvic Organ Prolapse Quantification stage <2. Demographic variables were compared by cluster with Student t and chi-square tests. Odds ratios were calculated to determine whether clusters could predict the outcome. Age at surgery, body mass index, and previous prolapse surgery were used for adjusted odds ratios. RESULTS: Five statistically distinct prolapse clusters (phenotypes C, A, A>P, P, and P>A) were found. These phenotypes reflected the predominant region of prolapse (apical, anterior, or posterior) and whether support was preserved in the nonpredominant region. Phenotype A (anterior compartment prolapse predominant, posterior support preserved) was found in all 4 groups of patients and was considered the reference in the analysis. In 111 patients with stage 2 uterovaginal prolapse, phenotypes A and A>P (greater anterior prolapse than posterior prolapse) were found, and patients with phenotype A were more likely than those with phenotype A>P to have an optimal surgical outcome. In 401 patients with stage 3 to 4 uterovaginal prolapse, phenotypes C (apical compartment predominant, prolapse in all compartments), A, and A>P were found, and patients with phenotype A>P were more likely than those with phenotype A to have ideal surgical outcome. In 72 patients with stage 2 vaginal vault prolapse, phenotypes A, A>P, and P (posterior compartment predominant, anterior support preserved) were found, and those with phenotype A>P were less likely to have an ideal outcome than patients with phenotype A. In 297 patients with stage 3 to 4 vaginal vault prolapse, phenotypes C, A, and P>A (prolapse greater in posterior than in anterior compartment) were found, but there were no significant differences in rate of ideal outcome between phenotypes. CONCLUSION: Five anatomic phenotypes based on preoperative Pelvic Organ Prolapse Quantification scores were present in patients with stages 2 and 3 to 4 uterovaginal prolapse and vaginal vault prolapse. These phenotypes are predictive of surgical outcome after minimally invasive sacrocolpopexy. Further work needs to confirm the presence and predictive nature of these phenotypes. In addition, whether the phenotypes represent a progression of prolapse or discrete prolapse presentations resulting from different anatomic and life course risk profiles is unknown. These phenotypes may be useful in surgical counseling and planning.

C3G and Ig-MPGN-treatment standard.

Among the broad spectrum of membranoproliferative glomerulonephritis (MPGN), immunofluorescence distinguishes C3 glomerulopathy (C3G), with predominant C3 deposits, and immunoglobulin-associated MPGN (Ig-MPGN), with combined C3 and Ig. However, there are several intersections between C3G and Ig-MPGN. Primary C3G and Ig-MPGN share the same prevalence of low serum C3 levels and of abnormalities of the alternative pathway of complement, and patients who present a bioptic pattern of Ig-MPGN at onset may show a C3G pattern in a subsequent biopsy. There is no specific therapy for primary C3G and Ig-MPGN and prognosis is unfavourable. The only recommended indications are inhibitors of the renin-angiotensin system, lipid-lowering agents and other renoprotective agents. The other drugs used currently, such as corticosteroids and mycophenolate mofetil, are often ineffective. The anti-C5 monoclonal antibody eculizumab has been tested in several patients, with mixed results. One reason for the uncertainty is the extremely variable clinical course, most likely reflecting a heterogeneous pathogenesis. An unsupervised clustering analysis that included histologic, biochemical, genetic and clinical data available at onset in patients with primary C3G and Ig-MPGN identified four clusters characterized by specific pathogenic mechanisms. This approach may facilitate accurate diagnosis and development of targeted therapies. Several trials are ongoing with drugs targeting different molecules of the complement cascade, however it is important to consider which component of the cascade may be the most appropriate for each patient. We review the current standards of treatment and discuss novel developments in the pathophysiology, diagnosis, outcome prediction and management of C3G and Ig-MPGN.