Towards a standard benchmark for variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework.

Background: Computational approaches to support rare disease diagnosis are challenging to build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species data into variant and gene prioritisation algorithms (VGPAs). However, the performance of VGPAs has been difficult to measure and is impacted by many factors, for example, ontology structure, annotation completeness or changes to the underlying algorithm. Assertions of the capabilities of VGPAs are often not reproducible, in part because there is no standardised, empirical framework and openly available patient data to assess the efficacy of VGPAs - ultimately hindering the development of effective prioritisation tools. Results: In this paper, we present our benchmarking tool, PhEval, which aims to provide a standardised and empirical framework to evaluate phenotype-driven VGPAs. The inclusion of standardised test corpora and test corpus generation tools in the PhEval suite of tools allows open benchmarking and comparison of methods on standardised data sets. Conclusions: PhEval and the standardised test corpora solve the issues of patient data availability and experimental tooling configuration when benchmarking and comparing rare disease VGPAs. By providing standardised data on patient cohorts from real-world case-reports and controlling the configuration of evaluated VGPAs, PhEval enables transparent, portable, comparable and reproducible benchmarking of VGPAs. As these tools are often a key component of many rare disease diagnostic pipelines, a thorough and standardised method of assessment is essential for improving patient diagnosis and care.

Understanding potential opportunities and risks associated with feeding supplemental rumen available fats to mitigate enteric methane emissions in lactating dairy cows.

Supplemental dietary rumen available fats show promise as enteric methane (eCH4) mitigators for lactating dairy cows. However, concerns include variability in eCH4 response and possible negative effects on dairy cow performance. Successful implementation of this mitigation option requires better prediction of responses specifically to rumen available FA as well as understanding the modulating effects of other dietary and animal characteristics. Using meta-analytic and meta-regression techniques, 35 published studies with diet definition were used to assess changes in eCH4 emissions and lactation performance associated with supplemental fat, specific supplemental rumen available FA types, and other dietary characteristics. Enteric CH4 (g/d) was reduced by 3.77% per percentage unit of supplemental rumen available EE (RAEE). Supplemental rumen available PUFA (C18:2 and C18:3) and UFA (C18:1, C18:2, C18:3) mitigated eCH4 (g/d) emissions in dairy cows by 6.88 and 4.65% per percentage unit increase, respectively. The anti-methanogenic effects of PUFA, MUFA and MCFA increased with correspondingly greater basal dietary levels of each FA type. Higher rumen-degradable starch (RDS; > 18% DM) in the basal diet promoted greater reductions in eCH4 yield (eCH4/DMI, g/kg) with supplemental rumen available PUFA and UFA. Both milk fat percentage and yield (kg/d) were reduced with rumen available fat supplementation with a reduction of 7.8% and 6.0%, respectively, relative to control diets. Our results highlight the importance of determining basal levels of the rumen available FA before providing supplemental rumen available FA as an option for enteric eCH4 mitigation. Dairy nutritionists can use estimates generated from this analysis to predict changes in eCH4 emissions and dairy cow performance associated with dietary supplementation of rumen available EE and specific rumen available FA types for the purpose of eCH4 mitigation.

Clinical Characteristics of Children with THRA Mutations: Variable Phenotype and Good Response to Recombinant Human Growth Hormone Therapy.

INTRODUCTION: Mutations in the thyroid hormone receptor alpha (THRA) gene are a rare cause of thyroid hormone resistance, which leads to a pleomorphic phenotypic spectrum. Hormonal profiles are variable and subtle, making laboratory diagnoses challenging. Genetic evaluation can be a helpful tool in diagnosing these cases. CASE PRESENTATION: Three patients (P1, P2, and P3) from unrelated families presented to their endocrinologists with short stature and abnormalities in thyroid function results. P1 showed hypoactivity and mild thyroid-stimulating hormone (TSH) elevation. P2 presented with a mild developmental delay and a hormonal profile initially interpreted as central hypothyroidism. Patient P3 had severe symptoms, including hypotonia, developmental delay, normal TSH, hypercholesterolemia, severe hypertriglyceridemia, high amylase levels, and mild pericardial effusion. All the patients had low free thyroxine (FT4) levels, mild constipation, and short stature. The patients underwent exome sequencing analysis that identified three different heterozygous variants in the THRA gene (P1 and P2 had missense variants, and P3 had a stop codon variant). All patients were treated with levothyroxine replacement, improving their clinical symptoms, such as constipation, and neurological symptoms. P1 and P2 were also treated with the recombinant human growth hormone (rhGH). The improvements in growth velocity and height standard deviation scores (SDS) were remarkable. Notably, P1 had a total height gain of 2.5 SDS, reaching an adult height within the normal range. CONCLUSION: THRA gene defects can lead to growth disorders with different phenotypes. Children with THRA mutations can benefit from adequate treatment with levothyroxine and may respond well to rhGH treatment.

Assessment of infection of Stomoxys calcitrans larvae by entomopathogenic nematodes Heterorhabditis amazonensis NEPT11.

This study aimed to evaluate the virulence of Heterorhabditis amazonenses NEPT11 against larvae of Stomoxys calcitrans. Groups of 10 third-instar fly larvae were deposited in Petri dishes, to which were added 50, 100 and 200 EPNs/larva in 4ml of distilled water. The volume of the control group was the same as the treated group, but without EPNs. Larval mortality was observed daily, until larvae died or adults emerged. The Petri dishes were kept on laboratory shelves at 27 ± 1 °C and 70 ± 10% RH. The experiment was replicated six times. A regression analysis revealed quadratic behavior with increasing concentrations, indicating that the concentration of 200 EPNs/larva (48%) was the most efficient among the tested concentrations, while concentrations of 50 and 100 EPNs/larva killed 26.6 and 40% of larvae, respectively. In general, none of the treatments resulted in a mortality rate of more than 50%, but all the treated groups exhibited a higher mortality than that of the control group. It is concluded that the EPN H. amazonensis NEPT11 shows a promising potential to control third-instar larvae of S. calcitrans. However, further studies are needed in different situations to better understand the activity of this organism against the immature stages of the stable fly.

Este estudo teve como objetivo avaliar a ação do NEP Heterorhabditis amazonenses NEPT11 frente larvas de S. calcitrans. Grupos de 10 larvas de terceiro instar da mosca foram depositados em placas de Petri, em seguida, adicionou-se 50, 100, 200, 300 e 400 NEPs/larva em 4ml de água destilada. O volume do grupo controle foi o mesmo dos tratados, porém sem NEPs. A mortalidade das larvas foi observada diariamente, até a morte das larvas ou emergência de adultos. As placas foram mantidas em estantes de laboratório a 27 ± 1 °C e 70 ± 10% UR. O experimento teve seis repetições. Por meio da análise de regressão, foi observado comportamento quadrático com o aumento das concentrações, sendo a concentração de 200 NEPs/larva (48%) a de maior eficiência entre as concentrações testadas, já as concentrações de 50 e 100 NEPs/larva mataram 26,6 e 40% das larvas, respectivamente. De modo geral, nenhum tratamento proporcionou mortalidade superior a 50%, todavia, todos os grupos tratados apresentaram mortalidade superior à observada no controle. Conclui-se que H. amazonenses NEPT11 mostrou-se promissor no controle de larvas de terceiro instar de S. calcitrans, porém mais estudos devem ser feitos para o melhor entendimento da ação deste organismo frente aos estágios imaturos da mosca-dos-estábulos.

Immunohistochemistry assessment of tissue neutrophil-to-lymphocyte ratio predicts outcomes in melanoma patients treated with anti-programmed cell death 1 therapy.

Elevated neutrophil-to-lymphocyte ratio (NLR) is associated with diminished immunotherapy response in metastatic melanoma. Although NLR assessment in peripheral blood is established, tissue dynamics remain insufficiently explored. This study aimed to evaluate tissue NLR (tNLR)'s predictive potential through immunohistochemistry in immunotherapy-treated melanoma. Fifty melanoma patients who underwent anti-programmed cell death 1 (PD-1) therapy were assessed. Hematological, clinical and tumor features were collected from medical records. Responses were categorized using the Response Evaluation Criteria in Solid Tumors for immunotherapy (iRECIST) guidelines. Immunohistochemistry for tumor-infiltrating T cells (cluster differentiation 3) and neutrophils (myeloperoxidase) was performed on formalin-fixed paraffin-embedded tumor samples. NLR, derived NLR (dNLR) and tNLR were calculated. Overall survival (OS) and survival following immunotherapy (SFI) were calculated from diagnosis or immunotherapy start to loss of follow-up or death. Patients with high tNLR presented improved OS ( P =  0.038) and SFI with anti-PD-1 therapy ( P =  0.006). Both NLR and dNLR were associated with OS ( P =  0.038 and P =  0.046, respectively) and SFI ( P =  0.001 and P =  0.019, respectively). NLR was also associated with immunotherapy response ( P =  0.007). In conclusion, tNLR emerged as a novel potential biomarker of enhanced survival post anti-PD-1 therapy, in contrast to classical NLR and dNLR markers.

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch's APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch's data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch's analytic tools by developing a customized plugin for OpenAI's ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app.

HDAC specificity and kinase off-targeting by purine-benzohydroxamate anti-hematological tumor agents.

A series of hybrid inhibitors, combining pharmacophores of known kinase inhibitors bearing anilino-purines (ruxolitinib, ibrutinib) and benzohydroxamate HDAC inhibitors (nexturastat A), were generated in the present study. The compounds have been synthesized and tested against solid and hematological tumor cell lines. Compounds 4d-f were the most promising in cytotoxicity assays (IC50 ≤ 50 nM) vs. hematological cells and displayed moderate activity in solid tumor models (EC50 = 9.3-21.7 µM). Compound 4d potently inhibited multiple kinase targets of interest for anticancer effects, including JAK2, JAK3, HDAC1, and HDAC6. Molecular dynamics simulations showed that 4d has stable interactions with HDAC and members of the JAK family, with differences in the hinge binding energy conferring selectivity for JAK3 and JAK2 over JAK1. The kinase inhibition profile of compounds 4d-f allows selective cytotoxicity, with minimal effects on non-tumorigenic cells. Moreover, these compounds have favorable pharmacokinetic profiles, with high stability in human liver microsomes (e.g., see t1/2: >120 min for 4f), low intrinsic clearance, and lack of significant inhibition of four major CYP450 isoforms.

Heavy metal contamination in soils of a decommissioned landfill southern Brazil: Ecological and health risk assessment.

The incorrect disposal of waste negatively influences the population's quality of life and harms the environment. In Brazil, waste disposal in the open air is still a reality, which generates concerns about the contamination of the areas surrounding these dumpsites. The present work evaluated the possible environmental risks of a deactivated dumpsite in southern Brazil. The soil was characterized by physical and chemical tests, emphasizing the analysis of heavy metals Al, Fe, Cu, Mn, and Zn. Using geostatistical tools, it was possible to determine the distribution of these heavy metals in the influence of the landfill, since the metals Mn, Fe, and Zn showed a significant difference about the reference soil, indicating that they came from leaching from the landfill. The dispersion of the metals along the slope showed a tendency towards mobility since the highest concentrations were at elevations below the landfill. The area was considered contaminated due to the high scores of the evaluated indexes pollution, as the Improved Nemerow Pollution Index, which considers pollutant concentration, toxicity, and environmental impact to provide a measure of contamination, and was equivalent to 6.44, indicating that the area is contaminated. However, it presented low ecological risks, with a potential ecological risk of 18.55. As well as low risks to human health, with hazard index below the limit considered critical to health (HI < 1). Thus, the results of this study showed that the metals are released around the deactivated deposit, which compromises the environmental safety of the site, mainly due to its proximity to bodies of water that supply the region. Thus, the permanent control and monitoring of the areas of deactivated dumpsites are essential to avoid further pollution and should be included in the management plans for deactivating these deposits throughout the country.

The Venom Composition of the Snake Tribe Philodryadini: 'Omic' Techniques Reveal Intergeneric Variability among South American Racers.

Snakes of the Philodryadini tribe are included in the Dipsadidae family, which is a diverse group of rear-fanged snakes widespread in different ecological conditions, including habitats and diet. However, little is known about the composition and effects of their venoms despite their relevance for understanding the evolution of these snakes or even their impact on the occasional cases of human envenoming. In this study, we integrated venom gland transcriptomics, venom proteomics and functional assays to characterize the venoms from eight species of the Philodryadini tribe, which includes the genus Philodryas, Chlorosoma and Xenoxybelis. The most abundant components identified in the venoms were snake venom metalloproteinases (SVMPs), cysteine-rich secretory proteins (CRISPs), C-type lectins (CTLs), snake endogenous matrix metalloproteinases type 9 (seMMP-9) and snake venom serinoproteinases (SVSPs). These protein families showed a variable expression profile in each genus. SVMPs were the most abundant components in Philodryas, while seMMP-9 and CRISPs were the most expressed in Chlorosoma and Xenoxybelis, respectively. Lineage-specific differences in venom composition were also observed among Philodryas species, whereas P. olfersii presented the highest amount of SVSPs and P. agassizii was the only species to express significant amounts of 3FTx. The variability observed in venom composition was confirmed by the venom functional assays. Philodryas species presented the highest SVMP activity, whereas Chlorosoma species showed higher levels of gelatin activity, which may correlate to the seMMP-9 enzymes. The variability observed in the composition of these venoms may be related to the tribe phylogeny and influenced by their diets. In the presented study, we expanded the set of venomics studies of the Philodryadini tribe, which paves new roads for further studies on the evolution and ecology of Dipsadidae snakes.

Deciphering Divergent Trypanosomatid Nuclear Complexes by Analyzing Interactomic Datasets with AlphaFold2 and Genetic Approaches.

Acetylation signaling pathways in trypanosomatids, a group of early branching organisms, are poorly understood due to highly divergent protein sequences. To overcome this challenge, we used interactomic datasets and AlphaFold2 (AF2)-multimer to predict direct interactions and validated them using yeast two and three-hybrid assays. We focused on MORF4 related gene (MRG) domain-containing proteins and their interactions, typically found in histone acetyltransferase/deacetylase complexes. The results identified a structurally conserved complex, TcTINTIN, which is orthologous to human and yeast trimer independent of NuA4 for transcription interaction (TINTIN) complexes; and another trimeric complex involving an MRG domain, only seen in trypanosomatids. The identification of a key component of TcTINTIN, TcMRGBP, would not have been possible through traditional homology-based methods. We also conducted molecular dynamics simulations, revealing a conformational change that potentially affects its affinity for TcBDF6. The study also revealed a novel way in which an MRG domain participates in simultaneous interactions with two MRG binding proteins binding two different surfaces, a phenomenon not previously reported. Overall, this study demonstrates the potential of using AF2-processed interactomic datasets to identify protein complexes in deeply branched eukaryotes, which can be challenging to study based on sequence similarity. The findings provide new insights into the acetylation signaling pathways in trypanosomatids, specifically highlighting the importance of MRG domain-containing proteins in forming complexes, which may have important implications for understanding the biology of these organisms and developing new therapeutics. On the other hand, our validation of AF2 models for the determination of multiprotein complexes illuminates the power of using such artificial intelligence-derived tools in the future development of biology.

The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

The Ontology of Biological Attributes (OBA) - Computational Traits for the Life Sciences.

Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focused measurable trait data. Moreover, variations in gene expression in response to environmental disturbances even without any genetic alterations can also be associated with particular biological attributes. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.

Effect of Photobiomodulation With Different Wavelengths on Radiodermatitis Treatment.

Approximately 80% of patients submitted to radiotherapy develop radiodermatitis. Photobiomodulation based on light-emitted diode (LED) is one of the therapeutic strategies for treating inflammation. This study aimed to investigate the effect of the photobiomodulation with two wavelengths, in an acute radiodermatitis animal model. Methods: Twenty rats were submitted to one radiotherapy session. After 15 days, the rats that developed radiodermatitis were divided into control groups, LED-630 nm, LED-850 nm, and LED-630 + 850 nm. The treatment regimen was one session lasting 10 minutes on alternate days for 21 days. We analyzed macroscopy aspects (RTOG scale), vascular density, dermal appendages, VEGF-a, TNF-alpha, MMP-9, and MMP-9 genic expression level. Results: All LED groups revealed a two-point reduction on the radiodermatitis severity grade compared with the baseline classification. Dermal appendage and vascular analysis showed a higher counting in all LED groups compared to control. This study showed dermal appendages twice in the 630/850 nm group compared with the control group. The 630/850 nm group showed six times more arterioles than the control group. Regarding genic expression, this study showed a 10-fold decrease between LED-630 nm versus LED-630 + 850 nm (P = 0.02) interleukin-10 expression and a 12-fold decrease between control versus LED-630 nm (P = 0.006) and LED-850 nm (P = 0.002) in TNF-alpha. Conclusion: LED (630 nm, 850 nm, and 630 nm + 850 nm) showed benefit in the treatment of radiodermatitis, and the association of the 630 nm + 850 nm and 630 nm parameters demonstrated the best macroscopic and microscopic results.

Dynamics of annatto pigment synthesis and accumulation in seeds of Bixa orellana L. revealed by integrated chemical, anatomical, and RNA-Seq analyses.

Bixin is a commercially valuable apocarotenoid pigment found in the seed aril of Bixa orellana. The dynamics and regulation of its biosynthesis and accumulation during seed development remain largely unknown. Here, we combined chemical, anatomical, and transcriptomic data to provide stage-specific resolution of the cellular and molecular events occurring during B. orellana seed development. Seeds at five developmental stages (S1-S5) were used for analysis of bixin content and seed anatomy, and three of them (S1, S3, and S4) were selected for Illumina HiSeq sequencing. Bixin accumulated in large quantities in seeds compared with other tissues analyzed, particularly during the S2 stage, peaking at the S4 stage, and then decreasing slightly in the S5 stage. Anatomical analysis revealed that bixin accumulated in the large central vacuole of specialized cells, which were scattered throughout the developing mesotesta at the S2 stage, but enlarged progressively at later stages, until they occupied most of the parenchyma in the aril. A total of 13 million reads were generated and assembled into 73,381 protein-encoding contigs, from which 312 were identified as containing 1-deoxy-D-xylulose-5-phosphate/2-C-methyl-D-erythritol-4-phosphate (DOXP/MEP), carotenoid, and bixin pathways genes. Differential transcriptome expression analysis of these genes revealed that 50 of them were sequentially and differentially expressed through the seed developmental stages analyzed, including seven carotenoid cleavage dioxygenases, eight aldehyde dehydrogenases, and 22 methyltransferases. Taken together, these results show that bixin synthesis and accumulation in seeds of B. orellana are a developmentally regulated process involving the coordinated expression of DOXP/MEP, carotenoid, and bixin biosynthesis genes.

The value of artificial intelligence for detection and grading of prostate cancer in human prostatectomy specimens: a validation study.

BACKGROUND: The Gleason grading system is an important clinical practice for diagnosing prostate cancer in pathology images. However, this analysis results in significant variability among pathologists, hence creating possible negative clinical impacts. Artificial intelligence methods can be an important support for the pathologist, improving Gleason grade classifications. Consequently, our purpose is to construct and evaluate the potential of a Convolutional Neural Network (CNN) to classify Gleason patterns. METHODS: The methodology included 6982 image patches with cancer, extracted from radical prostatectomy specimens previously analyzed by an expert uropathologist. A CNN was constructed to accurately classify the corresponding Gleason. The evaluation was carried out by computing the corresponding 3 classes confusion matrix; thus, calculating the percentage of precision, sensitivity, and specificity, as well as the overall accuracy. Additionally, k-fold three-way cross-validation was performed to enhance evaluation, allowing better interpretation and avoiding possible bias. RESULTS: The overall accuracy reached 98% for the training and validation stage, and 94% for the test phase. Considering the test samples, the true positive ratio between pathologist and computer method was 85%, 93%, and 96% for specific Gleason patterns. Finally, precision, sensitivity, and specificity reached values up to 97%. CONCLUSION: The CNN model presented and evaluated has shown high accuracy for specifically pattern neighbors and critical Gleason patterns. The outcomes are in line and complement others in the literature. The promising results surpassed current inter-pathologist congruence in classical reports, evidencing the potential of this novel technology in daily clinical aspects.

Effectiveness of Intrarectal Povidone-iodine Cleansing Plus Formalin Disinfection of the Needle Tip in Decreasing Infectious Complications After Transrectal Prostate Biopsy: A Randomized Controlled Trial.

PURPOSE: Prostate biopsy is mostly performed through the transrectal route worldwide and infectious complications may occur in up to 7% of cases. Therefore, alternative strategies to decrease infectious complications are needed. Our aim was to evaluate the effectiveness of intrarectal povidone-iodine cleansing plus formalin disinfection of the needle tip in decreasing infectious complications after transrectal ultrasound guided prostate biopsy. MATERIALS AND METHODS: We conducted a prospective, single-center, phase III trial in patients undergoing transrectal ultrasound guided prostate biopsy randomized 1:1 to rectal mucosa cleansing with gauze soaked in 10% povidone-iodine solution wrapped around the gloved index finger and needle tip disinfection by immersion in a 10% formalin solution before each puncture vs control group. The primary end point was the rate of infectious complications defined as 1 or more of the following events: fever, urinary tract infection, or sepsis. RESULTS: Overall, 633 patients were randomized to the intervention group and 623 to the control group. The infectious complication rate was 3.9% in the intervention group and 6.4% in the control group (RR 0.61; 95% CI 0.36-0.99; P = .049). The rates of sepsis, urinary tract infection, and fever were 0.3% vs 0.5% (P = .646), 2.3% vs 4.1% (P = .071), and 1.3% vs 1.9% (P = .443), respectively. The positive urine culture rate was 5.2% in the intervention group and 9% in the control group (RR 0.57; P = .015). There was no statistically significant difference between the groups regarding the occurrence of noninfectious adverse events. CONCLUSIONS: Intrarectal povidone-iodine cleansing plus formalin disinfection of the biopsy needle tip was associated with a reduction in infectious complications after transrectal prostate biopsy.

Development and Validation of a Dermoscopic Severity Score for Female Pattern Hair Loss.

Introduction: Despite the high prevalence and impact on quality of life, there are no objective methods to estimate the severity of female pattern hair loss (FPHL). Here, we aimed to develop a dermoscopic severity score for FPHL. Methods: Cross-sectional study involving 76 women with FPHL and 12 controls. Standardized dermoscopic photos of the scalp were taken to evaluate the main findings of FPHL. The variable selection and their scores in the final model were defined by multivariate methods. Twenty participants were retested to assess the reliability, and 10 participants were tested before and after treatment for estimating its sensibility to change after 6 months. Results: Eight patients (11%) presented the Sinclair clinical scale grade I, 40 (53%) presented at grade II, 19 (25%) presented at grade III, and 9 (12%) presented at grades IV and V. In the multivariate exploration, the following variables were considered significant: total terminal hairs, total miniaturized hairs, brown peripilar sign, scalp honeycomb pigmentation, white peripilar sign, and yellow dots. The final model resulted in a high correlation (rho = 0.89) with the ranked clinical assessment. Conclusion: An objective and reliable severity score of FPHL was developed and validated, allowing its use as an additional outcome in therapeutic trials.