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Mycophenolate mofetil (MMF) is commonly included in post-transplant cyclophosphamide (PTCy) based graft-versus-host disease (GVHD) prophylaxis after haploidentical (haplo) hematopoietic cell transplant (HCT). In the non-PTCy setting, higher MMF dose/kg has been shown to reduce rates of acute graft-versus-host disease (GVHD). When used in conjunction with PTCy, MMF is dosed at 15 mg/kg three times daily up to a maximum dose of 3 g/day. Thus, patients who weigh ≥67 kg receive 3 g/day and a variable dose/kg of MMF. We investigated the impact of MMF dose/kg on clinical outcomes following haploidentical PBSCT with PTCy-based GVHD prophylaxis. All consecutive adult patients with hematologic malignancies receiving haploidentical T cell replete peripheral blood stem cell transplant (PBSCT) with PTCy/MMF and either tacrolimus or sirolimus at the Moffitt Cancer Center or City of Hope between April 2014-August 2020 were included. For analyses, MMF dose relative to patient actual body weight (mg/kg/day), was stratified into categories of low (<29 mg/kg/day), low intermediate (29-34 mg/kg/day), high intermediate (35-41 mg/kg/day), and high (>41 mg/kg/day). Three hundred eighty-six patients were included. Of these, 54 patients received low dose, 73 low intermediate, 137 high intermediate and 122 high dose MMF by relative weight exposure. In multivariate analysis, low MMF dose exposure was associated with reduced rates of relapse in comparison to the high dose group (HR = 0.45, 95% CI: 0.21 to 0.94, P = .03). This led to superior PFS among patients with low compared to high MMF dose exposure (HR = 0.58, 95% CI: 0.34 to 0.99, P = .045). MMF relative dose exposure was not associated with engraftment, GVHD, nonrelapse mortality, or OS. In this study of patients receiving haploidentical PBSCT with PTCy based GVHD prophylaxis, low MMF dose/kg was associated with improved rates of relapse and PFS. Future prospective studies should investigate optimal dosing strategies of MMF when given with the PTCy regimen.

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Fludarabine (Flu) and melphalan (Mel) reduced-intensity conditioning is frequently used for allogenic hematopoietic cell transplant (allo-HCT) in patients with acute myeloid leukemia (AML) and myelodysplastic syndromes (MDS). However, there is limited evidence on the impact of Mel dosing on toxicities and clinical outcomes of allo-HCT. We retrospectively compared 8/8 HLA-matched donor allo-HCT outcomes of 345 patients with AML or MDS receiving total Mel dose of 100 mg/m2 (Mel-100, n = 62) versus 140 mg/m2 (Mel-140, n = 283) in combination with Flu. Median age at allo-HCT was 66 years and median follow-up was 36.5 months. For Mel-100 versus Mel-140 groups, any grade gastrointestinal (GI) toxicity rates were 40.3% versus 67.8% (P < .001), day 100 grade II to IV acute graft-versus-host disease (GVHD) rates were 21.0% versus 43.1% (P = .001) and 2-year chronic GVHD rates were 17.4% versus 27.1% (P = .033). In multivariable analysis, Mel-140 resulted in higher risks of GI toxicity (HR = 1.83, P = .013), grade II to IV acute GVHD (HR=2.35, P = .003), and moderate/severe chronic GVHD (HR = 3.13, P = .007). Total Mel dose had no independent impact on oral mucositis, nonrelapse mortality, relapse, relapse-free survival, and overall survival. While independent validation of our observation is warranted, our findings support using Mel-100 in combination with Flu to minimize allo-HCT toxicities and morbidities related to GVHD.

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When inferring the evolution of a gene/gene family, it is advisable to use all available coding sequences (CDS) from as many species genomes as possible in order to infer and date all gene duplications and losses. Nowadays, this means using hundreds or even thousands of CDSs, which makes the inferred phylogenetic trees difficult to visualize and interpret. Therefore, it is useful to have an automated way of collapsing large phylogenetic trees according to a taxonomic term decided by the user (family, class, or order, for instance), in order to highlight the minimal set of sequences that should be used to recapitulate the full history of the gene/gene family being studied at that taxonomic level, that can be refined using additional software. Here we present the Phylogenetic Tree Collapser (PTC) program (https://github.com/pegi3s/phylogenetic-tree-collapser), a flexible tool for automated tree collapsing using taxonomic information, that can be easily used by researchers without a background in informatics, since it only requires the installation of Docker, Podman or Singularity. The utility of PTC is demonstrated by addressing the evolution of the ascorbic acid synthesis pathway in insects. A Docker image is available at Docker Hub (https://hub.docker.com/r/pegi3s/phylogenetic-tree-collapser) with PTC installed and ready-to-run.

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Background: PolyDeep is a computer-aided detection and classification (CADe/x) system trained to detect and classify polyps. During colonoscopy, CADe/x systems help endoscopists to predict the histology of colonic lesions. Objective: To compare the diagnostic performance of PolyDeep and expert endoscopists for the optical diagnosis of colorectal polyps on still images. Methods: PolyDeep Image Classification (PIC) is an in vitro diagnostic test study. The PIC database contains NBI images of 491 colorectal polyps with histological diagnosis. We evaluated the diagnostic performance of PolyDeep and four expert endoscopists for neoplasia (adenoma, sessile serrated lesion, traditional serrated adenoma) and adenoma characterization and compared them with the McNemar test. Receiver operating characteristic curves were constructed to assess the overall discriminatory ability, comparing the area under the curve of endoscopists and PolyDeep with the chi- square homogeneity areas test. Results: The diagnostic performance of the endoscopists and PolyDeep in the characterization of neoplasia is similar in terms of sensitivity (PolyDeep: 89.05%; E1: 91.23%, p=0.5; E2: 96.11%, p<0.001; E3: 86.65%, p=0.3; E4: 91.26% p=0.3) and specificity (PolyDeep: 35.53%; E1: 33.80%, p=0.8; E2: 34.72%, p=1; E3: 39.24%, p=0.8; E4: 46.84%, p=0.2). The overall discriminative ability also showed no statistically significant differences (PolyDeep: 0.623; E1: 0.625, p=0.8; E2: 0.654, p=0.2; E3: 0.629, p=0.9; E4: 0.690, p=0.09). In the optical diagnosis of adenomatous polyps, we found that PolyDeep had a significantly higher sensitivity and a significantly lower specificity. The overall discriminative ability of adenomatous lesions by expert endoscopists is significantly higher than PolyDeep (PolyDeep: 0.582; E1: 0.685, p < 0.001; E2: 0.677, p < 0.0001; E3: 0.658, p < 0.01; E4: 0.694, p < 0.0001). Conclusion: PolyDeep and endoscopists have similar diagnostic performance in the optical diagnosis of neoplastic lesions. However, endoscopists have a better global discriminatory ability than PolyDeep in the optical diagnosis of adenomatous polyps.

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BACKGROUND: The initial version of SEDA assists life science researchers without programming skills with the preparation of DNA and protein sequence FASTA files for multiple bioinformatics applications. However, the initial version of SEDA lacks a command-line interface for more advanced users and does not allow the creation of automated analysis pipelines. RESULTS: The present paper discusses the updates of the new SEDA release, including the addition of a complete command-line interface, new functionalities like gene annotation, a framework for automated pipelines, and improved integration in Linux environments. CONCLUSION: SEDA is an open-source Java application and can be installed using the different distributions available ( https://www.sing-group.org/seda/download.html ) as well as through a Docker image ( https://hub.docker.com/r/pegi3s/seda ). It is released under a GPL-3.0 license, and its source code is publicly accessible on GitHub ( https://github.com/sing-group/seda ). The software version at the time of submission is archived at Zenodo (version v1.6.0, http://doi.org/10.5281/zenodo.10201605 ).

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The vast amount of genome sequence data that is available, and that is predicted to drastically increase in the near future, can only be efficiently dealt with by building automated pipelines. Indeed, the Earth Biogenome Project will produce high-quality reference genome sequences for all 1.8 million named living eukaryote species, providing unprecedented insight into the evolution of genes and gene families, and thus on biological issues. Here, new modules for gene annotation, further BLAST search algorithms, further multiple sequence alignment methods, the adding of reference sequences, further tree rooting methods, the estimation of rates of synonymous and nonsynonymous substitutions, and the identification of positively selected amino acid sites, have been added to auto-phylo (version 2), a recently developed software to address biological problems using phylogenetic inferences. Additionally, we present auto-phylo-pipeliner, a graphical user interface application that further facilitates the creation and running of auto-phylo pipelines. Inferences on S-RNase specificity, are critical for both cross-based breeding and for the establishment of pollination requirements. Therefore, as a test case, we develop an auto-phylo pipeline to identify amino acid sites under positive selection, that are, in principle, those determining S-RNase specificity, starting from both non-annotated Prunus genomes and sequences available in public databases.

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SARS-CoV-2 amino acid variants that contribute to an increased transmissibility or to host immune system escape are likely to increase in frequency due to positive selection and may be identified using different methods, such as codeML, FEL, FUBAR, and MEME. Nevertheless, when using different methods, the results do not always agree. The sampling scheme used in different studies may partially explain the differences that are found, but there is also the possibility that some of the identified positively selected amino acid sites are false positives. This is especially important in the context of very large-scale projects where hundreds of analyses have been performed for the same protein-coding gene. To account for these issues, in this work, we have identified positively selected amino acid sites in SARS-CoV-2 and 15 other coronavirus species, using both codeML and FUBAR, and compared the location of such sites in the different species. Moreover, we also compared our results to those that are available in the COV2Var database and the frequency of the 10 most frequent variants and predicted protein location to identify those sites that are supported by multiple lines of evidence. Amino acid changes observed at these sites should always be of concern. The information reported for SARS-CoV-2 can also be used to identify variants of concern in other coronaviruses.

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Graft-versus-host disease (GVHD) prophylaxis with post-transplantation cyclophosphamide (PTCy), tacrolimus (Tac), and mycophenolate mofetil (MMF) for allogeneic haploidentical donor (haplo) hematopoietic cell transplantation (HCT) results in comparable outcomes to matched unrelated donor HCT. A phase II study from the Moffitt Cancer Center substituting sirolimus (Siro) for Tac in this prophylactic regimen reported comparable rates of grade II-IV acute GVHD (aGVHD). Many centers have substituted Siro for Tac in this setting based on a preferable side effect profile, although comparative data are limited. In this study, we retrospectively compared outcomes in haplo-HCT with PTCy/Siro/MMF versus haplo-HCT with PTCy/Tac/MMF. The study cohort included all consecutive patients receiving haploidentical donor T cell-replete peripheral blood stem cell (PBSC) HCT for hematologic malignancies at Moffitt Cancer Center or the City of Hope National Medical Center between 2014 and 2019. A total of 423 patients were included, of whom 84 (20%) received PTCy/Siro/MMF and 339 (80%) received PTCy/Tac/MMF. The median age for the entire cohort was 54 years (range, 18 to 78 years), and the median follow-up was 30 months. The Siro group had a higher proportion of patients age ≥60 years (58% versus 34%; P < .01), and the groups also differed in diagnosis type, conditioning regimen, and cytomegalovirus serostatus. There were no significant differences in the rates of grade II-IV aGVHD (45% versus 47%; P = .6) at day +100 or chronic GVHD (cGVHD) (47% versus 54%; P = .79) at 2 years post-HCT. In multivariate analysis, neutrophil engraftment at day +30 was significantly better in the Tac group (odds ratio, .30; 95% confidence interval, .1 to .83; P = .02), with a median time to engraftment of 17 days versus 18 days in the Siro group, but platelet engraftment was similar in the 2 groups. Otherwise, in multivariate analysis, GVHD prophylaxis type had no significant influence on aGVHD or cGVHD, nonrelapse mortality, relapse, GVHD-free relapse-free survival, disease-free survival, or overall survival after PBSC haplo-HCT. These findings suggest that Siro is a comparable alternative to Tac in combination with PTCy/MMF for GVHD prophylaxis, with overall similar clinical outcomes despite delayed engraftment after peripheral blood stem cell haplo-HCT. Although Tac remains the standard of care, Siro may be substituted based on the side effect profile of these medications, with consideration of patient medical comorbidities at HCT.

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Non-target species from agricultural areas might be exposed to sublethal pesticide concentrations favoring survival and reproduction of the resistance individuals. The objective of this study was to evaluate chlorpyrifos toxicity and detoxification enzymatic activities on three species (Hyalella curvispina, Heleobia parchappii and Girardia tigrina) from a drain channel with history of insecticide contamination (EF) and the Neuquén river (NR) in Argentina. Chlorpyrifos toxicity on amphipods (H. curvispina) and planarians (G. tigrina) from NR was about six- and two-fold higher than that of their counterparts from EF. Mean carboxylesterases (CarE) activities determined in the three species from NR were significantly different from EF, whereas mean glutathione-S-transferase (GST) activities were no significantly different. Finally, planarians from EF showed significantly higher mean 7-ethoxycoumarine O-deethylase (ECOD) activity than those from NR. Amphipods from both sites displayed similar ECOD activities. The present results suggest that chlorpyrifos resistance in amphipods from EF is not conferred by increased detoxification.

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During development, cells are subject to stochastic fluctuations in their positions (i.e. cell-level noise) that can potentially lead to morphological noise (i.e. stochastic differences between morphologies that are expected to be equal, e.g. the right and left sides of bilateral organisms). In this study, we explore new and existing hypotheses on buffering mechanisms against cell-level noise. Many of these hypotheses focus on how the boundaries between territories of gene expression remain regular and well defined, despite cell-level noise and division. We study these hypotheses and how irregular territory boundaries lead to morphological noise. To determine the consistency of the different hypotheses, we use a general computational model of development: EmbryoMaker. EmbryoMaker can implement arbitrary gene networks regulating basic cell behaviors (contraction, adhesion, etc.), signaling and tissue biomechanics. We found that buffering mechanisms based on the orientation of cell divisions cannot lead to regular boundaries but that other buffering mechanisms can (homotypic adhesion, planar contraction, non-dividing boundaries, constant signaling and majority rule hypotheses). We also explore the effects of the shape and size of the territories on morphological noise.

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BACKGROUND: This study investigates the proteomic landscapes of chromophobe renal cell carcinoma (chRCC) and renal oncocytomas (RO), two subtypes of renal cell carcinoma that together account for approximately 10% of all renal tumors. Despite their histological similarities and shared origins, chRCC is a malignant tumor necessitating aggressive intervention, while RO, a benign growth, is often subject to overtreatment due to difficulties in accurate differentiation. METHODS: We conducted a label-free quantitative proteomic analysis on solid biopsies of chRCC (n = 5), RO (n = 5), and normal adjacent tissue (NAT, n = 5). The quantitative analysis was carried out by comparing protein abundances between tumor and NAT specimens. Our analysis identified a total of 1610 proteins across all samples, with 1379 (85.7%) of these proteins quantified in at least seven out of ten LC‒MS/MS runs for one renal tissue type (chRCC, RO, or NAT). RESULTS: Our findings revealed significant similarities in the dysregulation of key metabolic pathways, including carbohydrate, lipid, and amino acid metabolism, in both chRCC and RO. Compared to NAT, both chRCC and RO showed a marked downregulation in gluconeogenesis proteins, but a significant upregulation of proteins integral to the citrate cycle. Interestingly, we observed a distinct divergence in the oxidative phosphorylation pathway, with RO showing a significant increase in the number and degree of alterations in proteins, surpassing that observed in chRCC. CONCLUSIONS: This study underscores the value of integrating high-resolution mass spectrometry protein quantification to effectively characterize and differentiate the proteomic landscapes of solid tumor biopsies diagnosed as chRCC and RO. The insights gained from this research offer valuable information for enhancing our understanding of these conditions and may aid in the development of improved diagnostic and therapeutic strategies.

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High-throughput sequencing of small RNA molecules such as microRNAs (miRNAs) has become a widely used approach for studying gene expression and regulation. However, analyzing miRNA-Seq data can be challenging because it requires multiple steps, from quality control and preprocessing to differential expression and pathway-enrichment analyses, with many tools and databases available for each step. Furthermore, reproducibility of the analysis pipeline is crucial to ensure that the results are accurate and reliable. Here, we present myBrain-Seq, a comprehensive and reproducible pipeline for analyzing miRNA-Seq data that incorporates miRNA-specific solutions at each step of the analysis. The pipeline was designed to be flexible and user-friendly, allowing researchers with different levels of expertise to perform the analysis in a standardized and reproducible manner, using the most common and widely used tools for each step. In this work, we describe the implementation of myBrain-Seq and demonstrate its capacity to consistently and reproducibly identify differentially expressed miRNAs and enriched pathways by applying it to a real case study in which we compared schizophrenia patients who responded to medication with treatment-resistant schizophrenia patients to obtain a 16-miRNA treatment-resistant schizophrenia profile.

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BACKGROUND: Obesity (body mass index [BMI] ≥30 kg/m2 ) is an important epidemiological risk factor for developing acute myeloid leukemia (AML). Therefore, the authors studied the association of obesity with clinical and genetic phenotype and its impact on outcome in adults with AML. METHODS: The authors analyzed BMI in 1088 adults who were receiving intensive remission induction and consolidation therapy in two prospective, randomized therapeutic clinical trials of the Eastern Cooperative Oncology Group-American College of Radiology Imaging Network: E1900 (ClinicalTrials.gov identifier NCT00049517; patients younger than 60 years) and E3999 (ClinicalTrials.gov identifier NCT00046930; patients aged 60 years or older). RESULTS: Obesity was prevalent at diagnosis (33%) and, compared with nonobesity, was associated with intermediate-risk cytogenetics group (p = .008), poorer performance status (p = .01), and a trend toward older age (p = .06). Obesity was not associated with somatic mutations among a selected 18-gene panel that was tested in a subset of younger patients. Obesity was not associated with clinical outcome (including complete remission, early death, or overall survival), and the authors did not identify any patient subgroup that had inferior outcomes based on BMI. Obese patients were significantly more likely to receive <90% of the intended daunorubicin dose despite protocol specification, particularly in the E1900 high-dose (90 mg/m2 ) daunorubicin arm (p = .002); however, this did not correlate with inferior overall survival on multivariate analysis (hazard ratio, 1.39; 95% confidence interval, 0.90-2.13; p = .14). CONCLUSIONS: Obesity is associated with unique clinical and disease-related phenotypic features in AML and may influence physician treatment decisions regarding daunorubicin dosing. However, the current study demonstrates that obesity is not a factor in survival, and strict adherence to body surface area-based dosing is not necessary because dose adjustments do not affect outcomes.

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Genomics studies routinely confront researchers with long lists of tumor alterations detected in patients. Such lists are difficult to interpret since only a minority of the alterations are relevant biomarkers for diagnosis and for designing therapeutic strategies. PanDrugs is a methodology that facilitates the interpretation of tumor molecular alterations and guides the selection of personalized treatments. To do so, PanDrugs scores gene actionability and drug feasibility to provide a prioritized evidence-based list of drugs. Here, we introduce PanDrugs2, a major upgrade of PanDrugs that, in addition to somatic variant analysis, supports a new integrated multi-omics analysis which simultaneously combines somatic and germline variants, copy number variation and gene expression data. Moreover, PanDrugs2 now considers cancer genetic dependencies to extend tumor vulnerabilities providing therapeutic options for untargetable genes. Importantly, a novel intuitive report to support clinical decision-making is generated. PanDrugs database has been updated, integrating 23 primary sources that support >74K drug-gene associations obtained from 4642 genes and 14 659 unique compounds. The database has also been reimplemented to allow semi-automatic updates to facilitate maintenance and release of future versions. PanDrugs2 does not require login and is freely available at https://www.pandrugs.org/.

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Deep learning object-detection models are being successfully applied to develop computer-aided diagnosis systems for aiding polyp detection during colonoscopies. Here, we evidence the need to include negative samples for both (i) reducing false positives during the polyp-finding phase, by including images with artifacts that may confuse the detection models (e.g., medical instruments, water jets, feces, blood, excessive proximity of the camera to the colon wall, blurred images, etc.) that are usually not included in model development datasets, and (ii) correctly estimating a more realistic performance of the models. By retraining our previously developed YOLOv3-based detection model with a dataset that includes 15% of additional not-polyp images with a variety of artifacts, we were able to generally improve its F1 performance in our internal test datasets (from an average F1 of 0.869 to 0.893), which now include such type of images, as well as in four public datasets that include not-polyp images (from an average F1 of 0.695 to 0.722).

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EvoPPI (http://evoppi.i3s.up.pt), a meta-database for protein-protein interactions (PPI), has been upgraded (EvoPPI3) to accept new types of data, namely, PPI from patients, cell lines, and animal models, as well as data from gene modifier experiments, for nine neurodegenerative polyglutamine (polyQ) diseases caused by an abnormal expansion of the polyQ tract. The integration of the different types of data allows users to easily compare them, as here shown for Ataxin-1, the polyQ protein involved in spinocerebellar ataxia type 1 (SCA1) disease. Using all available datasets and the data here obtained for Drosophila melanogaster wt and exp Ataxin-1 mutants (also available at EvoPPI3), we show that, in humans, the Ataxin-1 network is much larger than previously thought (380 interactors), with at least 909 interactors. The functional profiling of the newly identified interactors is similar to the ones already reported in the main PPI databases. 16 out of 909 interactors are putative novel SCA1 therapeutic targets, and all but one are already being studied in the context of this disease. The 16 proteins are mainly involved in binding and catalytic activity (mainly kinase activity), functional features already thought to be important in the SCA1 disease.

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A foundational idea of evo-devo is that morphological variation is not isotropic, that is, it does not occur in all directions. Instead, some directions of morphological variation are more likely than others from DNA-level variation and these largely depend on development. We argue that this evo-devo perspective should apply not only to morphology but to evolution at all phenotypic levels. At other phenotypic levels there is no development, but there are processes that can be seen, in analogy to development, as constructing the phenotype (e.g., protein folding, learning for behavior, etc.). We argue that to explain the direction of evolution two types of arguments need to be combined: generative arguments about which phenotypic variation arises in each generation and selective arguments about which of it passes to the next generation. We explain how a full consideration of the two types of arguments improves the explanatory power of evolutionary theory. Also see the video abstract here: https://youtu.be/Egbvma_uaKc.

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Schizophrenia (SZ) is a serious mental disorder that is typically treated with antipsychotic medication. Treatment-resistant schizophrenia (TRS) is the condition where symptoms remain after pharmacological intervention, resulting in long-lasting functional and social impairments. As the identification and treatment of a TRS patient requires previous failed treatments, early mechanisms of detection are needed in order to quicken the access to effective therapy, as well as improve treatment adherence. In this study, we aim to find a microRNA (miRNA) signature for TRS, as well as to shed some light on the molecular pathways potentially involved in this severe condition. To do this, we compared the blood miRNAs of schizophrenia patients that respond to medication and TRS patients, thus obtaining a 16-miRNA TRS profile. Then, we assessed the ability of this signature to separate responders and TRS patients using hierarchical clustering, observing that most of them are grouped correctly (~70% accuracy). We also conducted a network, pathway analysis, and bibliography search to spot molecular pathways potentially altered in TRS. We found that the response to stress seems to be a key factor in TRS and that proteins p53, SIRT1, MDM2, and TRIM28 could be the potential mediators of such responses. Finally, we suggest a molecular pathway potentially regulated by the miRNAs of the TRS profile.

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BACKGROUND: Monitoring bladder cancer over time requires invasive and costly procedures. Less invasive approaches are required using readily available biological samples such as urine. In this study, we demonstrate a method for longitudinal analysis of the urine proteome to monitor the disease course in patients with bladder cancer. METHODS: We compared the urine proteomes of patients who experienced recurrence and/or progression (n = 13) with those who did not (n = 17). We identified differentially expressed proteins within various pathways related to the hallmarks of cancer. The variation of such pathways during the disease course was determined using our differential personal pathway index (dPPi) calculation, which could indicate disease progression and the need for medical intervention. RESULTS: Seven hallmark pathways are used to develop the dPPi. We demonstrate that we can successfully longitudinally monitor the disease course in bladder cancer patients through a combination of urine proteomic analysis and the dPPi calculation, over a period of 62 months. CONCLUSIONS: Using the information contained in the patient's urinary proteome, the dPPi reflects the individual's course of bladder cancer, and helps to optimise the use of more invasive procedures such as cystoscopy.

Bladder cancer must be closely monitored for progression, but this requires expensive and invasive procedures such as cystoscopy. Less invasive procedures using readily available samples such as urine are needed. Here, we present an approach that measures the levels of various proteins in the urine. We compare protein levels at different points during the disease course in patients with bladder cancer, and show this helps to flag disease recurrence and the need for medical intervention. Our approach could help clinicians to determine which patients require more invasive testing and treatment.