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Pre-harvest sprouting (PHS) poses a significant global challenge to cereal production, impacting both yield and quality. In this study, we employed genome-wide association studies (GWAS) on diverse rice accessions to identify novel PHS-associated haplotypes. An assessment of 127 cultivated accessions for panicle germination (PHS) and detached grain germination (germination rate of detached grains at the 14th day (D14)) revealed considerable phenotypic variation among rice ecotypes. GWAS analysis identified 91 significant signals at –log10(P-value)>5, including 15 SNPs for PHS and 76 SNPs for D14. A subsequent linkage disequilibrium (LD) block-based GWAS analysis detected 227 significant SNPs for both traits, consisting of 18 nonsynonymous substitutions located on the coding regions of nine genes. Further haplotype analysis identified 32 haplotypes, with 10 specific to cultivated accessions, 19 specific to the wild type, and three shared between them. A phenotypic assessment of major haplotypes revealed significant differences between resistant (Hap1 and Hap2) and susceptible haplotypes (Hap5, Hap27, and Hap28), distinguished by a G/A SNP within a novel gene, Os04g0545200. The identified haplotypes offer promising prospects for haplotype-based breeding aimed at enhancing PHS resistance in rice.

Multiparental mapping populations hold great potential for dissecting quantitative traits and rapidly identifying genetic determinants. We developed a japonica nested association mapping population, KNU_NAM, comprising 880 lines derived from ten recombinant inbred lines (RILs) families of prominent varieties and the elite Korean variety Shindongjin. Genetic characterization of KNU_NAM revealed 48,159 polymorphic SNPs, with family counts ranging from 18,787 to 42,578 and an average of 30,019 SNPs per family. Further molecular diversity analysis of KNU_NAM indicated reduced population structure and broad genetic diversity. Genome-wide association studies (GWAS) on five morphological traits identified 47 significant marker-trait associations (MTAs), with a set of 18 MTAs located on chromosome 9. Linkage disequilibrium (LD) block analysis of this region revealed 15 haplotypes and identified five key genes associated with panicle architecture: OsDEP1, OsEATB, OsLGD1, and OsSPL18. Additionally, two non-synonymous MTAs on chromosome 7 were located on the exon of OsPRR37/Ghd7.1, a gene associated with plant height, heading date, and grain number per panicle. Further phenotypic performance analysis of haplotypes from these hotspot regions revealed significant differences in the targeted traits. The study validates the potential of KNU_NAM and GWAS for high-resolution genetic mapping in rice breeding programs, highlighting the utility of these populations for enhancing genetic diversity and improving trait selection in rice.

The DMP (DUF679 membrane proteins) family is a plant-specific gene family that encodes membrane proteins. The DMP family genes are suggested to be involved in various programmed cell death processes and gamete fusion during double fertilization in Arabidopsis. However, their functional relevance in other crops remains unknown. This study identified 14 genes from the DMP family in soybean (Glycine max) and characterized their physiochemical properties, subcellular location, gene structure, and promoter regions using bioinformatics tools. Additionally, their tissue-specific and stress-responsive expressions were analyzed using publicly available transcriptome data. Phylogenetic analysis of 198 DMPs from monocots and dicots revealed six clades, with clade-I encoding senescence-related AtDMP1/2 orthologues and clade-II including pollen-specific AtDMP8/9 orthologues. The largest clade, clade-III, predominantly included monocot DMPs, while monocot- and dicot-specific DMPs were assembled in clade-IV and clade-VI, respectively. Evolutionary analysis suggests that soybean GmDMPs underwent purifying selection during evolution. Using 68 transcriptome datasets, expression profiling revealed expression in diverse tissues and distinct responses to abiotic and biotic stresses. The genes Glyma.09G237500 and Glyma.18G098300 showed pistil-abundant expression by qPCR, suggesting they could be potential targets for female organ-mediated haploid induction. Furthermore, cis-acting regulatory elements primarily related to stress-, hormone-, and light-induced pathways regulate GmDMPs, which is consistent with their divergent expression and suggests involvement in growth and stress responses. Overall, our study provides a comprehensive report on the soybean GmDMP family and a framework for further biological functional analysis of DMP genes in soybean or other crops.

Early season flooding is a major constraint in direct-seeded rice, as rice genotypes vary in their coleoptile length during anoxia. Trehalose-6-phosphate phosphatase 7 (OsTPP7, Os09g0369400) has been identified as the genetic determinant for anaerobic germination (AG) and coleoptile elongation during flooding. We evaluated the coleoptile length of a diverse rice panel under normal and flooded conditions and investigated the Korean rice collection of 475 accessions to understand its genetic variation, population genetics, evolutionary relationships, and haplotypes in the OsTPP7 gene. Most accessions displayed enhanced flooded coleoptile lengths, with the temperate japonica ecotype exhibiting the highest average values for normal and flooded conditions. Positive Tajima’s D values in indica, admixture, and tropical japonica ecotypes suggested balancing selection or population expansion. Haplotype analysis revealed 18 haplotypes, with three in cultivated accessions, 13 in the wild type, and two in both. Hap_1 was found mostly in japonica, while Hap-2 and Hap_3 were more prevalent in indica accessions. Further phenotypic performance of major haplotypes showed significant differences in flooded coleoptile length, flooding tolerance index, and shoot length between Hap_1 and Hap_2/3. These findings could be valuable for future selective rice breeding and the development of efficient haplotype-based breeding strategies for improving flood tolerance.

Gamma-tocopherol methyltransferase (γ-TMT), a key gene in the vitamin E biosynthesis pathway, significantly influences the accumulation of tocochromanols, thereby determining rice nutritional quality. In our study, we analyzed the γ-TMT gene in 475 Korean rice accessions, uncovering 177 genetic variants, including 138 SNPs and 39 InDels. Notably, two functional SNPs, tmt-E2-28,895,665-G/A and tmt-E4-28,896,689-A/G, were identified, causing substitutions from valine to isoleucine and arginine to glycine, respectively, across 93 accessions. A positive Tajima’s D value in the indica group suggests a signature of balancing selection. Haplotype analysis revealed 27 haplotypes, with two shared between cultivated and wild accessions, seven specific to cultivated accessions, and 18 unique to wild types. Further, profiling of vitamin E isomers in 240 accessions and their association with haplotypes revealed that Hap_2, distinguished by an SNP in the 3′ UTR (tmt-3UTR-28,897,360-T/A) exhibited significantly lower α-tocopherol (AT), α-tocotrienol (AT3), total tocopherol, and total tocotrienol, but higher γ-tocopherol (GT) in the japonica group. Additionally, in the indica group, Hap_2 showed significantly higher AT, AT3, and total tocopherol, along with lower GT and γ-tocotrienol, compared to Hap_19, Hap_20, and Hap_21. Overall, this study highlights the genetic landscape of γ-TMT and provides a valuable genetic resource for haplotype-based breeding programs aimed at enhancing nutritional profiles.

Rice is a globally cultivated crop and is primarily a staple food source for more than half of the world’s population. Various single-nucleotide polymorphism (SNP) arrays have been developed and utilized as standard genotyping methods for rice breeding research. Considering the importance of SNP arrays with more inclusive genetic information for GWAS and genomic selection, we integrated SNPs from eight different data resources: resequencing data from the Korean World Rice Collection (KRICE) of 475 accessions, 3,000 rice genome project (3 K-RGP) data, 700 K high-density rice array, Affymetrix 44 K SNP array, QTARO, Reactome, and plastid and GMO information. The collected SNPs were filtered and selected based on the breeder’s interest, covering all key traits or research areas to develop an integrated array system representing inclusive genomic polymorphisms. A total of 581,006 high-quality SNPs were synthesized with an average distance of 200 bp between adjacent SNPs, generating a 580 K Axiom Rice Genotyping Chip (580 K _ KNU chip). Further validation of this array on 4,720 genotypes revealed robust and highly efficient genotyping. This has also been demonstrated in genome-wide association studies (GWAS) and genomic selection (GS) of three traits: clum length, heading date, and panicle length. Several SNPs significantly associated with cut-off, −log10p-value >7.0, were detected in GWAS, and the GS predictabilities for the three traits were more than 0.5, in both rrBLUP and convolutional neural network (CNN) models. The Axiom 580 K Genotyping array will provide a cost-effective genotyping platform and accelerate rice GWAS and GS studies.

Sesame, one of the ancient oil crops, is an important oilseed due to its nutritionally rich seeds with high protein content. Genomic scale information for sesame has become available in the public databases in recent years. The genes and their families involved in oil biosynthesis in sesame are less studied than in other oilseed crops. Therefore, we retrieved a total of 69 genes and their translated amino acid sequences, associated with gene families linked to the oil biosynthetic pathway. Genome-wide in silico mining helped identify key regulatory genes for oil biosynthesis, though the findings require functional validation. Comparing sequences of the SiSAD (stearoyl-acyl carrier protein (ACP)-desaturase) coding genes with known SADs helped identify two SiSAD family members that may be palmitoyl-ACP-specific. Based on homology with lysophosphatidic acid acyltransferase (LPAAT) sequences, an uncharacterized gene has been identified as SiLPAAT1. Identified key regulatory genes associated with high oil content were also validated using publicly available transcriptome datasets of genotypes contrasting for oil content at different developmental stages. Our study provides evidence that a longer duration of active oil biosynthesis is crucial for high oil accumulation during seed development. This underscores the importance of early onset of oil biosynthesis in developing seeds. Up-regulating, identified key regulatory genes of oil biosynthesis during early onset of seed development, should help increase oil yields.

Laurus nobilis L. is an aromatic medicinal plant widely cultivated in many world regions. L. nobilis has been increasingly acknowledged over the years as it provides an essential contribution to the food and pharmaceutical industries and cultural integrity. The commercial value of this species derives from its essential oil, whose application might be extended to various industries. The chemical composition of the essential oil depends on environmental conditions, location, and season during which the plants are collected, drying methods, extraction, and analytical conditions. The characterization and chemotyping of L. nobilis essential oil are extremely important because the changes in composition can affect biological activities. Several aspects of the plant’s secondary metabolism, particularly volatile production in L. nobilis, are still unknown. However, understanding the molecular basis of flavor and aroma production is not an easy task to accomplish. Nevertheless, the time-limited efforts for conservation and the unavailability of knowledge about genetic diversity are probably the major reasons for the lack of breeding programs in L. nobilis. The present review gathers the scientific evidence on the research carried out on Laurus nobilis L., considering its cultivation, volatile composition, biochemical and molecular aspects, and antioxidant and antimicrobial activities.

A letter to the editor is presented regarding the progression of Bcr-Ablp210+ leukemia caused by deletion of Janus kinase 2 (JAK2).

This study was carried out in the Department of Obstetrics and Gynaecology of the Mahatma Gandhi Institute of Medical Sciences, Sevagram in Central India. In the 12 years between 1989 and 2000 a total of 16 cases of ruptured uterus were managed, the incidence of rupture of the pregnant uterus being 0·62 per 1000 births. One-quarter of the cases occurred between 1983 and 1988. No teenager or elderly woman (over 40) or grandmultipara sustained a uterine rupture. Four women had a rupture of a previous scar. In five rupture had occurred in association with malpresentations, one was a case of hydrocephalus, two had a morbidly adherent placenta praevia and four had a normal presentation, with lack of progress in labour. Two of these 16 women had twins. One had come with a retained second twin with transverse lie and the other was a booked case with multiple problems, including a previous caesarean section, present twin pregnancy and placent praevia accreta and she died. This was the only maternal death. Perinatal mortality was 77·77% compared to 5·88% maternal and 100% perinatal mortality in the cases reported previously between 83 and 88, from the same institution. Overall, there is some improvement in perinatal survival and one-quarter incidence of rupture of the pregnant uterus. [ABSTRACT FROM AUTHOR]

In peanut (Arachis hypogaea L.), the customization of fatty acid profile is an evolving area to fulfil the nutritional needs in the modern market. A total of 174 peanut genotypes, including 167 Indian cultivars, 6 advanced breeding lines and ‘SunOleic’‒ a double mutant line, were investigated using AS-PCRs, CAPS and gene sequencing for the ahFAD2 allele polymorphism, along with its fatty acid compositions. Of these, 80 genotypes were found having substitution (448G>A) mutation only in ahFAD2A gene, while none recorded 1-bp insertion (441_442insA) mutation in ahFAD2B gene. Moreover, 22 wild peanut accessions found lacking both the mutations. Among botanical types, the ahFAD2A mutation was more frequent in ssp. hypogaea (89%) than in ssp. fastigiata (17%). This single allele mutation, found affecting not only oleic to linoleic acid fluxes, but also the composition of other fatty acids in the genotypes studied. Repeated use of a few selected genotypes in the Indian varietal development programs were also eminently reflected in its ahFAD2 allele polymorphism. Absence of known mutations in the wild-relatives indicated the possible origin of these mutations, after the allotetraploidization of cultivated peanut. The SNP analysis of both ahFAD2A and ahFAD2B genes, revealed haplotype diversity of 1.05% and 0.95%, while Ka/Ks ratio of 0.36 and 0.39 respectively, indicating strong purifying selection pressure on these genes. Cluster analysis, using ahFAD2 gene SNPs, showed presence of both mutant and non-mutant genotypes in the same cluster, which might be due the presence of ahFAD2 gene families. This investigation provided insights into the large number of Indian peanut genotypes, covering various aspects related to O/L flux regulation and ahFAD2 gene polymorphism.

Introduction: The prevalence of autoimmune thyroid disease (AITD) in India is 7 - 8% and the association of other autoimmune disorders with AITD is well documented. The concomitance of celiac disease (CD) with AITD results in poor absorption of thyroid medications and results in higher doses of the same. The institution of gluten free diet (GFD) in this cohort has helped to reduce the medication doses. Aim: To study the prevalence of celiac disease in patients with autoimmune thyroid disease Materials and Methods : A total of 300 consecutive patients with AITD attending the thyroid OPD of a tertiary care hospital run by the municipal corporation of Mumbai were screened for the presence of tissue transglutaminase antibodies (IgA TTG) using Bio-Rad enzyme linked immunoabsorbent assay (ELISA). Those with a positive titre underwent upper gastrointestinal endoscopy and duodenal mucosal biopsy for the diagnosis of CD. Results: Of the 300 patients with AITD recruited in the study, results of CA screen are available for 80 patients. Five out of these 80(6.25%) patients are positive for CA. Conclusions: CA is commonly associated with AITD and screening for the same can diagnose many cases of undiagnosed CD. The prevalence of celiac disease in all 300 recruited patients and the clinical impact will be conglomerated and presented at ESICON 2012 [ABSTRACT FROM AUTHOR]

Introduction: Hypovitaminosis D, which has various skeletal and extraskeletal manifestations, is widely prevalent in India (70-95%). Different dosing protocols have been used for Vitamin D (VITD) supplementation. This study is designed to compare various supplemental regimens. Aim and Objectives: Comparison of serial VITD concentrations attained with various VITD supplementation protocols in VITD deficient subjects. Materials and Methods: A total of 242 healthy volunteers (20-60 years: BMI 21-26 kg/m2), were screened for vitamin D deficiency. Out of this, 139 subjects were deficient, and 105 consenting subjects with VITD <16 ng/ml were randomized to receive four different supplemental regimens, i.e., single dose 6 lac IU orally, 6 lac IU intramuscular, 60,000 IU once weekly for 8 weeks, and 2000 IU daily for 8 weeks. VITD, parathyroid hormone, calcium, phosphorus, alkaline phosphatase were monitored at 0, 1, 3, 6, 8, 12, and 16 weeks of therapy. Results: Conclusions: 1 All groups showed rise in VITD at 1 week. 2 At 3 weeks, there was a fall in VITD in 6 lac IU oral group, while a steady rising trend was observed in the other three groups. 3 Six subjects in Oral 6 lac group attained toxic levels of VITD while none from other groups developed toxic levels. Final results will be presented at ESICON2012. [ABSTRACT FROM AUTHOR]

Computationally expensive data processing in neuroimaging research places demands on energy consumption-and the resulting carbon emissions contribute to the climate crisis. We measured the carbon footprint of the functional magnetic resonance imaging (fMRI) preprocessing tool fMRIPrep, testing the effect of varying parameters on estimated carbon emissions and preprocessing performance. Performance was quantified using (a) statistical individual-level task activation in regions of interest and (b) mean smoothness of preprocessed data. Eight variants of fMRIPrep were run with 257 participants who had completed an fMRI stop signal task (the same data also used in the original validation of fMRIPrep). Some variants led to substantial reductions in carbon emissions without sacrificing data quality: for instance, disabling FreeSurfer surface reconstruction reduced carbon emissions by 48%. We provide six recommendations for minimising emissions without compromising performance. By varying parameters and computational resources, neuroimagers can substantially reduce the carbon footprint of their preprocessing. This is one aspect of our research carbon footprint over which neuroimagers have control and agency to act upon., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

While high circulating tumor DNA (ctDNA) levels are associated with poor survival for multiple cancers, variant-specific differences in the association of ctDNA levels and survival have not been examined. Here we investigate KRAS ctDNA (ctKRAS) variant-specific associations with overall and progression-free survival (OS/PFS) in first-line metastatic pancreatic ductal adenocarcinoma (mPDAC) for patients receiving chemoimmunotherapy ("PRINCE", NCT03214250), and an independent cohort receiving standard of care (SOC) chemotherapy. For PRINCE, higher baseline plasma levels are associated with worse OS for ctKRAS G12D (log-rank p = 0.0010) but not G12V (p = 0.7101), even with adjustment for clinical covariates. Early, on-therapy clearance of G12D (p = 0.0002), but not G12V (p = 0.4058), strongly associates with OS for PRINCE. Similar results are obtained for the SOC cohort, and for PFS in both cohorts. These results suggest ctKRAS G12D but not G12V as a promising prognostic biomarker for mPDAC and that G12D clearance could also serve as an early biomarker of response., (© 2024. The Author(s).)

There is a lack of consensus on the optimal screening strategy for insulin resistance (IR), particularly in lean women with polycystic ovary syndrome (PCOS). Therefore, we conducted a cross-sectional study in 80 women with PCOS (28 lean/52 obese) and 80 age- and body mass index (BMI)-matched controls. Using a 5-point 75-g oral glucose tolerance test (OGTT) (0, 30, 60, 90, 120 min), we examined glucose and insulin excursions, IR, insulin sensitivity, beta-cell function (ßF), and the effect of androgens on IR. Lean and obese women with PCOS had similar glucose but higher insulin (except fasting in lean women) and insulin AUC as compared to their respective controls (p < 0.05). Lean women with PCOS were equally insulin-resistant but more hyperinsulinemic than the obese controls (p < 0.05). Although ßF ([1st phase: 481.71 ± 263.53 vs. 430.56 ± 232.37], [2nd phase: 815.16 ± 447.12 vs. 752.66 ± 428.95]) was comparable in lean and obese women with PCOS, lean women had better insulin sensitivity (112.78 ± 66.26 vs. 75.49 ± 55.6) (p < 0.05). Dehydroepiandrosterone sulfate (DHEAS) and androstenedione decreased with increasing BMI in lean women, and this correlated with deteriorating insulin sensitivity and exaggerated hyperinsulinemia. In obese women with PCOS, sex hormone-binding globulin (SHBG) correlated negatively with BMI and hyperinsulinemia, and positively with insulin sensitivity. This data suggests that estimating only fasting insulin may miss IR in lean women with PCOS; hence, additional time points in OGTT will add value to screening for IR. DHEAS and androstenedione may have a beneficial effect on insulin sensitivity and may be used to screen IR in lean women, while SHBG can be used as a predictive marker for IR in obese women with PCOS., (© 2023. The Author(s), under exclusive licence to Society for Reproductive Investigation.)

MCL1 is a member of the BCL2 family of apoptosis regulators, which play a critical role in promoting cancer survival and drug resistance. We previously described PRT1419, a potent, MCL1 inhibitor with anti-tumor efficacy in various solid and hematologic malignancies. To identify novel biomarkers that predict sensitivity to MCL1 inhibition, we conducted a gene essentiality analysis using gene dependency data generated from CRISPR/Cas9 cell viability screens. We observed that clear cell renal cancer (ccRCC) cell lines with damaging PBRM1 mutations displayed a strong dependency on MCL1. PBRM1 (BAF180), is a chromatin-targeting subunit of mammalian pBAF complexes. PBRM1 is frequently altered in various cancers particularly ccRCC with ~40% of tumors harboring damaging PBRM1 alterations. We observed potent inhibition of tumor growth and induction of apoptosis by PRT1419 in various preclinical models of PBRM1-mutant ccRCC but not PBRM1-WT. Depletion of PBRM1 in PBRM1-WT ccRCC cell lines induced sensitivity to PRT1419. Mechanistically, PBRM1 depletion coincided with increased expression of pro-apoptotic factors, priming cells for caspase-mediated apoptosis following MCL1 inhibition. Increased MCL1 activity has been described as a resistance mechanism to Sunitinib and Everolimus, two approved agents for ccRCC. PRT1419 synergized with both agents to potently inhibit tumor growth in PBRM1-loss ccRCC. PRT2527, a potent CDK9 inhibitor which depletes MCL1, was similarly efficacious in monotherapy and in combination with Sunitinib in PBRM1-loss cells. Taken together, these findings suggest PBRM1 loss is associated with MCL1i sensitivity in ccRCC and provide rationale for the evaluation of PRT1419 and PRT2527 for the treatment for PBRM1-deficient ccRCC., Competing Interests: All authors are or were employees of Prelude Therapeutics, Inc at the time of research, and may own equity in the company., (Copyright © 2024 Fultang, Schwab, McAneny-Droz, Grego, Rodgers, Torres, Heiser, Scherle and Bhagwat.)

Context: An existing major challenge in Parkinson's disease (PD) research is the identification of biomarkers of disease progression. While magnetic resonance imaging is a potential source of PD biomarkers, none of the magnetic resonance imaging measures of PD are robust enough to warrant their adoption in clinical research. This study is part of a project that aims to replicate 11 PD studies reviewed in a recent survey (JAMA neurology, 78(10) 2021) to investigate the robustness of PD neuroimaging findings to data and analytical variations., Objective: This study attempts to replicate the results in Hanganu et al. (Brain, 137(4) 2014) using data from the Parkinson's Progression Markers Initiative (PPMI)., Methods: Using 25 PD subjects and 18 healthy controls, we analyzed the rate of change of cortical thickness and of the volume of subcortical structures, and we measured the relationship between structural changes and cognitive decline. We compared our findings to the results in the original study., Results: (1) Similarly to the original study, PD patients with mild cognitive impairment (MCI) exhibited increased cortical thinning over time compared to patients without MCI in the right middle temporal gyrus, insula, and precuneus. (2) The rate of cortical thinning in the left inferior temporal and precentral gyri in PD patients correlated with the change in cognitive performance. (3) There were no group differences in the change of subcortical volumes. (4) We did not find a relationship between the change in subcortical volumes and the change in cognitive performance., Conclusion: Despite important differences in the dataset used in this replication study, and despite differences in sample size, we were able to partially replicate the original results. We produced a publicly available reproducible notebook allowing researchers to further investigate the reproducibility of the results in Hanganu et al. (2014) when more data is added to PPMI., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Sokołowski et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The role of hematopoietic Hedgehog signaling in myeloproliferative neoplasms (MPNs) remains incompletely understood despite data suggesting that Hedgehog (Hh) pathway inhibitors have therapeutic activity in patients. We aim to systematically interrogate the role of canonical vs. non-canonical Hh signaling in MPNs. We show that Gli1 protein levels in patient peripheral blood mononuclear cells (PBMCs) mark fibrotic progression and that, in murine MPN models, absence of hematopoietic Gli1, but not Gli2 or Smo, significantly reduces MPN phenotype and fibrosis, indicating that GLI1 in the MPN clone can be activated in a non-canonical fashion. Additionally, we establish that hematopoietic Gli1 has a significant effect on stromal cells, mediated through a druggable MIF-CD74 axis. These data highlight the complex interplay between alterations in the MPN clone and activation of stromal cells and indicate that Gli1 represents a promising therapeutic target in MPNs, particularly that Hh signaling is dispensable for normal hematopoiesis., Competing Interests: Declaration of interests N.B. is employed by Prelude Therapeutics. S.K. received research grants from Geron, Janssen, AOP Pharma, and Novartis; received consulting fees from Pfizer, Incyte, Ariad, Novartis, AOP Pharma, Bristol Myers Squibb, Celgene, Geron, Janssen, CTI BioPharma, Roche, Bayer, PharmaEssentia, Sierra Oncology, Imago Biosciences, and GSK; payment or honoraria from Novartis, BMS/Celgene, and Pfizer; received travel/accommodation support from Alexion, Novartis, Bristol Myers Squibb, Incyte, AOP Pharma, CTI BioPharma, Pfizer, Celgene, Janssen, Geron, Roche, AbbVie, Sierra Oncology, and Karthos; and participated on advisory boards for Pfizer, Incyte, Ariad, Novartis, AOP Pharma, BMS, Celgene, Geron, Janssen, CTI BioPharma, Roche, Bayer, Sierra Oncology, PharmaEssentia, Imago Biosciences, and GSK. R.L.L. is on the supervisory board of QIAGEN and is a scientific advisor to Imago, Mission Bio, Zentalis, Ajax, Auron, Prelude, C4 Therapeutics, and Isoplexis; receives research support from Ajax, Zentalis, and Abbvie; consulted for Incyte, Janssen, and Astra Zeneca; and received honoraria from Astra Zeneca for invited lectures. R.K. has grants from Travere Therapeutics, Galapagos, Chugai, and Novo Nordisk and is a consultant for Bayer, Pfizer, Novo Nordisk, and Gruenenthal. I.G.C. has a grant from Illumina. R.K. and R.K.S. are founders and shareholders of Sequantrix GmbH. N.F. is employed by Sequantrix GmbH., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Expression of protein arginine methyltransferase 5 (PRMT5) is highly positively correlated to DNA damage repair (DDR) and DNA replication pathway genes in many types of cancer cells, including ovarian and breast cancer. In the current study, we investigated whether pharmacologic inhibition of PRMT5 downregulates DDR/DNA replication pathway genes and sensitizes cancer cells to chemotherapy and PARP inhibition. Potent and selective PRMT5 inhibitors significantly downregulate expression of multiple DDR and DNA replication genes in cancer cells. Mechanistically, PRMT5 inhibition reduces the presence of PRMT5 and H4R3me2s on promoter regions of DDR genes such as BRCA1/2, RAD51, and ATM. PRMT5 inhibition also promotes global alternative splicing changes. Our data suggest that PRMT5 inhibition regulates expression of FANCA, PNKP, and ATM by promoting exon skipping and intron retention. Combining C220 or PRT543 with olaparib or chemotherapeutic agents such as cisplatin demonstrates a potent synergistic interaction in breast and ovarian cancer cells in vitro. Moreover, combination of PRT543 with olaparib effectively inhibits the growth of patient-derived breast and ovarian cancer xenografts. Furthermore, PRT543 treatment significantly inhibits growth of olaparib-resistant tumors in vivo. These studies reveal a novel mechanism of PRMT5 inhibition and suggest beneficial combinatorial effects with other therapies, particularly in patients with tumors that are resistant to therapies dependent on DNA damage as their mechanism of action., Significance: Patients with advanced cancers frequently develop resistance to chemotherapy or PARP inhibitors mainly due to circumvention and/or restoration of the inactivated DDR pathway genes. We demonstrate that inhibition of PRMT5 significantly downregulates a broad range of the DDR and DNA replication pathway genes. PRMT5 inhibitors combined with chemotherapy or PARP inhibitors demonstrate synergistic suppression of cancer cell proliferation and growth in breast and ovarian tumor models, including PARP inhibitor-resistant tumors., (© 2023 The Authors; Published by the American Association for Cancer Research.)

Mantle cell lymphoma (MCL) is an incurable B-cell malignancy that comprises up to 6% of non-Hodgkin lymphomas diagnosed annually and is associated with a poor prognosis. The average overall survival of patients with MCL is 5 years, and for most patients who progress on targeted agents, survival remains at a dismal 3 to 8 months. There is a major unmet need to identify new therapeutic approaches that are well tolerated to improve treatment outcomes and quality of life. The protein arginine methyltransferase 5 (PRMT5) enzyme is overexpressed in MCL and promotes growth and survival. Inhibition of PRMT5 drives antitumor activity in MCL cell lines and preclinical murine models. PRMT5 inhibition reduced the activity of prosurvival AKT signaling, which led to the nuclear translocation of FOXO1 and modulation of its transcriptional activity. Chromatin immunoprecipitation and sequencing identified multiple proapoptotic BCL-2 family members as FOXO1-bound genomic loci. We identified BAX as a direct transcriptional target of FOXO1 and demonstrated its critical role in the synergy observed between the selective PRMT5 inhibitor, PRT382, and the BCL-2 inhibitor, venetoclax. Single-agent and combination treatments were performed in 9 MCL lines. Loewe synergy scores showed significant levels of synergy in most MCL lines tested. Preclinical, in vivo evaluation of this strategy in multiple MCL models showed therapeutic synergy with combination venetoclax/PRT382 treatment with an increased survival advantage in 2 patient-derived xenograft models (P ≤ .0001, P ≤ .0001). Our results provide mechanistic rationale for the combination of PRMT5 inhibition and venetoclax to treat patients with MCL., (© 2023 by The American Society of Hematology. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0), permitting only noncommercial, nonderivative use with attribution. All other rights reserved.)

Essential tremor (ET) is the most prevalent movement disorder with poorly understood etiology. Some neuroimaging studies report cerebellar involvement whereas others do not. This discrepancy may stem from underpowered studies, differences in statistical modeling or variation in magnetic resonance imaging (MRI) acquisition and processing. To resolve this, we investigated the cerebellar structural differences using a local advanced ET dataset augmented by matched controls from PPMI and ADNI. We tested the hypothesis of cerebellar involvement using three neuroimaging biomarkers: VBM, gray/white matter volumetry and lobular volumetry. Furthermore, we assessed the impacts of statistical models and segmentation pipelines on results. Results indicate that the detected cerebellar structural changes vary with methodology. Significant reduction of right cerebellar gray matter and increase of the left cerebellar white matter were the only two biomarkers consistently identified by multiple methods. Results also show substantial volumetric overestimation from SUIT-based segmentation-partially explaining previous literature discrepancies. This study suggests that current estimation of cerebellar involvement in ET may be overemphasized in MRI studies and highlights the importance of methods sensitivity analysis on results interpretation. ET datasets with large sample size and replication studies are required to improve our understanding of regional specificity of cerebellum involvement in ET. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 21 March 2022. The protocol, as accepted by the journal, can be found at: https://doi.org/10.6084/m9.figshare.19697776 ., (© 2023. The Author(s).)

Sumoylation is emerging as a posttranslation modification important for regulating chromosome duplication and stability. The origin recognition complex (ORC) that directs DNA replication initiation by loading the MCM replicative helicase onto origins is sumoylated in both yeast and human cells. However, the biological consequences of ORC sumoylation are unclear. Here we report the effects of hypersumoylation and hyposumoylation of yeast ORC on ORC activity and origin function using multiple approaches. ORC hypersumoylation preferentially reduced the function of a subset of early origins, while Orc2 hyposumoylation had an opposing effect. Mechanistically, ORC hypersumoylation reduced MCM loading in vitro and diminished MCM chromatin association in vivo. Either hypersumoylation or hyposumoylation of ORC resulted in genome instability and the dependence of yeast on other genome maintenance factors, providing evidence that appropriate ORC sumoylation levels are important for cell fitness. Thus, yeast ORC sumoylation status must be properly controlled to achieve optimal origin function across the genome and genome stability., (© 2022 Regan-Mochrie et al.; Published by Cold Spring Harbor Laboratory Press.)

Crossing over is essential for chromosome segregation during meiosis. Protein modification by SUMO is implicated in crossover control, but pertinent targets have remained elusive. Here we identify Msh4 as a target of SUMO-mediated crossover regulation. Msh4 and Msh5 constitute the MutSγ complex, which stabilizes joint-molecule (JM) recombination intermediates and facilitates their resolution into crossovers. Msh4 SUMOylation enhances these processes to ensure that each chromosome pair acquires at least one crossover. Msh4 is directly targeted by E2 conjugase Ubc9, initially becoming mono-SUMOylated in response to DNA double-strand breaks, then multi/poly-SUMOylated forms arise as homologs fully engage. Mechanistically, SUMOylation fosters interaction between Msh4 and Msh5. We infer that initial SUMOylation of Msh4 enhances assembly of MutSγ in anticipation of JM formation, while secondary SUMOylation may promote downstream functions. Regulation of Msh4 by SUMO is distinct and independent of its previously described stabilization by phosphorylation, defining MutSγ as a hub for crossover control., Competing Interests: Declaration of interests The authors declare no competing interests., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: The choice of preprocessing pipeline introduces variability in neuroimaging analyses that affects the reproducibility of scientific findings. Features derived from structural and functional MRI data are sensitive to the algorithmic or parametric differences of preprocessing tasks, such as image normalization, registration, and segmentation to name a few. Therefore it is critical to understand and potentially mitigate the cumulative biases of pipelines in order to distinguish biological effects from methodological variance., Methods: Here we use an open structural MRI dataset (ABIDE), supplemented with the Human Connectome Project, to highlight the impact of pipeline selection on cortical thickness measures. Specifically, we investigate the effect of (i) software tool (e.g., ANTS, CIVET, FreeSurfer), (ii) cortical parcellation (Desikan-Killiany-Tourville, Destrieux, Glasser), and (iii) quality control procedure (manual, automatic). We divide our statistical analyses by (i) method type, i.e., task-free (unsupervised) versus task-driven (supervised); and (ii) inference objective, i.e., neurobiological group differences versus individual prediction., Results: Results show that software, parcellation, and quality control significantly affect task-driven neurobiological inference. Additionally, software selection strongly affects neurobiological (i.e. group) and individual task-free analyses, and quality control alters the performance for the individual-centric prediction tasks., Conclusions: This comparative performance evaluation partially explains the source of inconsistencies in neuroimaging findings. Furthermore, it underscores the need for more rigorous scientific workflows and accessible informatics resources to replicate and compare preprocessing pipelines to address the compounding problem of reproducibility in the age of large-scale, data-driven computational neuroscience., (© The Author(s) 2021. Published by Oxford University Press GigaScience.)

We investigated the role of PRMT5 in myeloproliferative neoplasm (MPN) pathogenesis and aimed to elucidate key PRMT5 targets contributing to MPN maintenance. PRMT5 is overexpressed in primary MPN cells, and PRMT5 inhibition potently reduced MPN cell proliferation ex vivo . PRMT5 inhibition was efficacious at reversing elevated hematocrit, leukocytosis, and splenomegaly in a model of JAK2 V617F+ polycythemia vera and leukocyte and platelet counts, hepatosplenomegaly, and fibrosis in the MPL W515L model of myelofibrosis. Dual targeting of JAK and PRMT5 was superior to JAK or PRMT5 inhibitor monotherapy, further decreasing elevated counts and extramedullary hematopoiesis in vivo. PRMT5 inhibition reduced expression of E2F targets and altered the methylation status of E2F1 leading to attenuated DNA damage repair, cell-cycle arrest, and increased apoptosis. Our data link PRMT5 to E2F1 regulatory function and MPN cell survival and provide a strong mechanistic rationale for clinical trials of PRMT5 inhibitors in MPN. SIGNIFICANCE: Expression of PRMT5 and E2F targets is increased in JAK2 V617F+ MPN. Pharmacologic inhibition of PRMT5 alters the methylation status of E2F1 and shows efficacy in JAK2 V617F /MPL W515L MPN models and primary samples. PRMT5 represents a potential novel therapeutic target for MPN, which is now being clinically evaluated. This article is highlighted in the In This Issue feature, p. 1611 ., (©2020 American Association for Cancer Research.)

Purpose: To determine whether a multianalyte liquid biopsy can improve the detection and staging of pancreatic ductal adenocarcinoma (PDAC)., Experimental Design: We analyzed plasma from 204 subjects (71 healthy, 44 non-PDAC pancreatic disease, and 89 PDAC) for the following biomarkers: tumor-associated extracellular vesicle miRNA and mRNA isolated on a nanomagnetic platform that we developed and measured by next-generation sequencing or qPCR, circulating cell-free DNA (ccfDNA) concentration measured by qPCR, ccfDNA KRAS G12D/V/R mutations detected by droplet digital PCR, and CA19-9 measured by electrochemiluminescence immunoassay. We applied machine learning to training sets and subsequently evaluated model performance in independent, user-blinded test sets., Results: To identify patients with PDAC versus those without, we generated a classification model using a training set of 47 subjects (20 PDAC and 27 noncancer). When applied to a blinded test set ( N = 136), the model achieved an AUC of 0.95 and accuracy of 92%, superior to the best individual biomarker, CA19-9 (89%). We next used a cohort of 20 patients with PDAC to train our model for disease staging and applied it to a blinded test set of 25 patients clinically staged by imaging as metastasis-free, including 9 subsequently determined to have had occult metastasis. Our workflow achieved significantly higher accuracy for disease staging (84%) than imaging alone (accuracy = 64%; P < 0.05)., Conclusions: Algorithmically combining blood-based biomarkers may improve PDAC diagnostic accuracy and preoperative identification of nonmetastatic patients best suited for surgery, although larger validation studies are necessary., (©2020 American Association for Cancer Research.)

Crossover recombination is essential for accurate chromosome segregation during meiosis. The MutSγ complex, Msh4-Msh5, facilitates crossing over by binding and stabilizing nascent recombination intermediates. We show that these activities are governed by regulated proteolysis. MutSγ is initially inactive for crossing over due to an N-terminal degron on Msh4 that renders it unstable by directly targeting proteasomal degradation. Activation of MutSγ requires the Dbf4-dependent kinase Cdc7 (DDK), which directly phosphorylates and thereby neutralizes the Msh4 degron. Genetic requirements for Msh4 phosphorylation indicate that DDK targets MutSγ only after it has bound to nascent joint molecules (JMs) in the context of synapsing chromosomes. Overexpression studies confirm that the steady-state level of Msh4, not phosphorylation per se, is the critical determinant for crossing over. At the DNA level, Msh4 phosphorylation enables the formation and crossover-biased resolution of double-Holliday Junction intermediates. Our study establishes regulated protein degradation as a fundamental mechanism underlying meiotic crossing over., Competing Interests: Declaration of Interests The authors declare no competing interests., (Copyright © 2020 Elsevier Inc. All rights reserved.)

Detection of disease-associated, cell-free nucleic acids in body fluids enables early diagnostics, genotyping and personalized therapy, but is challenged by the low concentrations of clinically significant nucleic acids and their sequence homology with abundant wild-type nucleic acids. We describe a novel approach, dubbed NAVIGATER, for increasing the fractions of Nucleic Acids of clinical interest Via DNA-Guided Argonaute from Thermus thermophilus (TtAgo). TtAgo cleaves specifically guide-complementary DNA and RNA with single nucleotide precision, greatly increasing the fractions of rare alleles and, enhancing the sensitivity of downstream detection methods such as ddPCR, sequencing, and clamped enzymatic amplification. We demonstrated 60-fold enrichment of the cancer biomarker KRAS G12D and ∼100-fold increased sensitivity of Peptide Nucleic Acid (PNA) and Xenonucleic Acid (XNA) clamp PCR, enabling detection of low-frequency (<0.01%) mutant alleles (∼1 copy) in blood samples of pancreatic cancer patients. NAVIGATER surpasses Cas9-based assays (e.g. DASH, Depletion of Abundant Sequences by Hybridization), identifying more mutation-positive samples when combined with XNA-PCR. Moreover, TtAgo does not require targets to contain any specific protospacer-adjacent motifs (PAM); is a multi-turnover enzyme; cleaves ssDNA, dsDNA and RNA targets in a single assay; and operates at elevated temperatures, providing high selectivity and compatibility with polymerases., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Altered cerebral blood flow (CBF), as measured by arterial spin labelling (ASL), has been observed in several psychiatric conditions, but is a generally underutilized MRI technique, especially in the study of psychosis spectrum (PS) symptoms. We aimed to determine group differences in ASL resting state functional connectivity (rsFC) between PS and non-PS youth, and the reliability of a support vector machine (SVM) classifier trained on ASL rsFC features to differentiate PS and non-PS youth, especially compared to blood oxygen level dependent (BOLD) fMRI. 1146 youth aged 8-22 with ASL and BOLD data from the Philadelphia Neurodevelopmental Cohort were analyzed. Widespread ASL hyperconnectivity was found in the left cuneus, precuneus, and dorsolateral prefrontal cortex, and hypoconnectivity was found in the left cingulate cortex and orbitofrontal area (multiple linear regression, FDR corrected). An SVM trained on ASL and BOLD features outperformed either modality alone (AUC BOTH  = 0.72 versus AUC ASL  = 0.68 and AUC BOLD  = 0.67). Classification performance and precision improved when the non-PS group had no psychiatric comorbidities. The relative success of the classifier suggests ASL rsFC changes exist in PS individuals that differ from BOLD rsFC changes, and extends previous findings of CBF dysregulation in PS., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

Schizophrenia has a 1% incidence rate world-wide and those diagnosed present with positive (e.g. hallucinations, delusions), negative (e.g. apathy, asociality), and cognitive symptoms. However, both symptom burden and associated brain alterations are highly heterogeneous and intimately linked to prognosis. In this study, we present a method to predict individual symptom profiles by first deriving clinical subgroups and then using machine learning methods to perform subject-level classification based on magnetic resonance imaging (MRI) derived neuroanatomical measures. Symptomatic and MRI data of 167 subjects were used. Subgroups were defined using hierarchical clustering of clinical data resulting in 3 stable clusters: 1) high symptom burden, 2) predominantly positive symptom burden, and 3) mild symptom burden. Cortical thickness estimates were obtained in 78 regions of interest and were input, along with demographic data, into three machine learning models (logistic regression, support vector machine, and random forest) to predict subgroups. Random forest performance metrics for predicting the group membership of the high and mild symptom burden groups exceeded those of the baseline comparison of the entire schizophrenia population versus normal controls (AUC: 0.81 and 0.78 vs. 0.75). Additionally, an analysis of the most important features in the random forest classification demonstrated consistencies with previous findings of regional impairments and symptoms of schizophrenia., (Copyright © 2019. Published by Elsevier B.V.)

Machine learning is a powerful tool that has previously been used to classify schizophrenia (SZ) patients from healthy controls (HC) using magnetic resonance images. Each study, however, uses different datasets, classification algorithms, and validation techniques. Here, we perform a critical appraisal of the accuracy of machine learning methodologies used in SZ/HC classifications studies by comparing three machine learning algorithms (logistic regression [LR], support vector machines [SVMs], and linear discriminant analysis [LDA]) on three independent datasets (435 subjects total) using two tissue density estimates and cortical thickness (CT). Performance is assessed using 10-fold cross-validation, as well as a held-out validation set. Classification using CT outperformed tissue densities, but there was no clear effect of dataset. LR, SVMs, and LDA each yielded the highest accuracies for a different feature set and validation paradigm, but most accuracies were between 55 and 70%, well below previously reported values. The highest accuracy achieved was 73.5% using CT data and an SVM. Taken together, these results illustrate some of the obstacles to constructing effective disease classifiers, and suggest that tissue densities and CT may not be sufficiently sensitive for SZ/HC classification given current available methodologies and sample sizes., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: The development of diagnostic and prognostic tools for Alzheimer disease is complicated by substantial clinical heterogeneity in prodromal stages. Many neuroimaging studies have focused on case–control classification and predicting conversion from mild cognitive impairment to Alzheimer disease, but predicting scores from clinical assessments (such as the Alzheimer’s Disease Assessment Scale or the Mini Mental State Examination) using MRI data has received less attention. Predicting clinical scores can be crucial in providing a nuanced prognosis and inferring symptomatic severity., Methods: We predicted clinical scores at the individual level using a novel anatomically partitioned artificial neural network (APANN) model. The model combined input from 2 structural MRI measures relevant to the neurodegenerative patterns observed in Alzheimer disease: hippocampal segmentations and cortical thickness. We evaluated the performance of the APANN model with 10 rounds of 10-fold cross-validation in 3 experiments, using cohorts from the Alzheimer’s Disease Neuroimaging Initiative (ADNI): ADNI1, ADNI2 and ADNI1 + 2., Results: Pearson correlation and root mean square error between the actual and predicted scores on the Alzheimer’s Disease Assessment Scale (ADNI1: r = 0.60; ADNI2: r = 0.68; ADNI1 + 2: r = 0.63) and Mini Mental State Examination (ADNI1: r = 0.52; ADNI2: r = 0.55; ADNI1 + 2: r = 0.55) showed that APANN can accurately infer clinical severity from MRI data., Limitations: To rigorously validate the model, we focused primarily on large cross-sectional baseline data sets with only proof-of-concept longitudinal results., Conclusion: The APANN provides a highly robust and scalable framework for predicting clinical severity at the individual level using high-dimensional, multimodal neuroimaging data., Competing Interests: None declared., (© 2019 Joule Inc. or its licensors)

Circulating tumor cells (CTCs) carry valuable biological information. While enumeration of CTCs in peripheral blood is an FDA-approved prognostic indicator of survival in metastatic prostate and other cancers, analysis of CTC phenotypic and genomic markers is needed to identify cancer origin and elucidate pathways that can guide therapeutic selection for personalized medicine. Given the emergence of single-cell mRNA sequencing technologies, a method is needed to isolate CTCs with high sensitivity and specificity as well as compatibility with downstream genomic analysis. Flow cytometry is a powerful tool to analyze and sort single cells, but pre-enrichment is required prior to flow sorting for efficient isolation of CTCs due to the extreme low frequency of CTCs in blood (one in billions of blood cells). While current enrichment technologies often require many steps and result in poor recovery, we demonstrate a magnetic separator and acoustic microfluidic focusing chip integrated system that enriches rare cells in-line with FACS™ (fluorescent activated cell sorting) and single-cell sequencing. This system analyzes, isolates, and index sorts single cells directly into 96-well plates containing reagents for Molecular Indexing (MI) and transcriptional profiling of single cells. With an optimized workflow using the integrated enrichment-FACS system, we performed a proof-of-concept experiment with spiked prostate cancer cells in peripheral blood and achieved: (i) a rapid one-step process to isolate rare cancer cells from lysed whole blood; (ii) an average of 92% post-enrichment cancer cell recovery (R 2 = 0.9998) as compared with 55% recovery for a traditional benchtop workflow; and (iii) detection of differentially expressed genes at a single cell level that are consistent with reported cell-type dependent expression signatures for prostate cancer cells. These model system results lay the groundwork for applying our approach to human blood samples from prostate and other cancer patients, and support the enrichment-FACS system as a flexible solution for isolation and characterization of CTCs for cancer diagnosis. © 2018 International Society for Advancement of Cytometry., (© 2018 International Society for Advancement of Cytometry.)

Background: Deficits in neurocognition and social cognition are drivers of reduced functioning in schizophrenia spectrum disorders, with potentially shared neurobiological underpinnings. Many studies have sought to identify brain-based biomarkers of these clinical variables using a priori dichotomies (e.g., good vs. poor cognition, deficit vs. nondeficit syndrome)., Methods: We evaluated a fully data-driven approach to do the same by building and validating a brain connectivity-based biomarker of social cognitive and neurocognitive performance in a sample using resting-state and task-based functional magnetic resonance imaging (n = 74 healthy control participants, n = 114 persons with schizophrenia spectrum disorder, 188 total). We used canonical correlation analysis followed by clustering to identify a functional connectivity signature of normal and poor social cognitive and neurocognitive performance., Results: Persons with poor social cognitive and neurocognitive performance were differentiated from those with normal performance by greater resting-state connectivity in the mirror neuron and mentalizing systems. We validated our findings by showing that poor performers also scored lower on functional outcome measures not included in the original analysis and by demonstrating neuroanatomical differences between the normal and poorly performing groups. We used a support vector machine classifier to demonstrate that functional connectivity alone is enough to distinguish normal and poorly performing participants, and we replicated our findings in an independent sample (n = 75)., Conclusions: A brief functional magnetic resonance imaging scan may ultimately be useful in future studies aimed at characterizing long-term illness trajectories and treatments that target specific brain circuitry in those with impaired cognition and function., (Copyright © 2018 Society of Biological Psychiatry. All rights reserved.)

Computational models predicting symptomatic progression at the individual level can be highly beneficial for early intervention and treatment planning for Alzheimer's disease (AD). Individual prognosis is complicated by many factors including the definition of the prediction objective itself. In this work, we present a computational framework comprising machine-learning techniques for 1) modeling symptom trajectories and 2) prediction of symptom trajectories using multimodal and longitudinal data. We perform primary analyses on three cohorts from Alzheimer's Disease Neuroimaging Initiative (ADNI), and a replication analysis using subjects from Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL). We model the prototypical symptom trajectory classes using clinical assessment scores from mini-mental state exam (MMSE) and Alzheimer's Disease Assessment Scale (ADAS-13) at nine timepoints spanned over six years based on a hierarchical clustering approach. Subsequently we predict these trajectory classes for a given subject using magnetic resonance (MR) imaging, genetic, and clinical variables from two timepoints (baseline + follow-up). For prediction, we present a longitudinal Siamese neural-network (LSN) with novel architectural modules for combining multimodal data from two timepoints. The trajectory modeling yields two (stable and decline) and three (stable, slow-decline, fast-decline) trajectory classes for MMSE and ADAS-13 assessments, respectively. For the predictive tasks, LSN offers highly accurate performance with 0.900 accuracy and 0.968 AUC for binary MMSE task and 0.760 accuracy for 3-way ADAS-13 task on ADNI datasets, as well as, 0.724 accuracy and 0.883 AUC for binary MMSE task on replication AIBL dataset., Competing Interests: The authors have declared that no competing interests exist.

Improved diagnostics for pancreatic ductal adenocarcinoma (PDAC) to detect the disease at earlier, curative stages and to guide treatments is crucial to progress against this disease. The development of a liquid biopsy for PDAC has proven challenging due to the sparsity and variable phenotypic expression of circulating biomarkers. Here we report methods we developed for isolating specific subsets of extracellular vesicles (EV) from plasma using a novel magnetic nanopore capture technique. In addition, we present a workflow for identifying EV miRNA biomarkers using RNA sequencing and machine-learning algorithms, which we used in combination to classify distinct cancer states. Applying this approach to a mouse model of PDAC, we identified a biomarker panel of 11 EV miRNAs that could distinguish mice with PDAC from either healthy mice or those with precancerous lesions in a training set of n = 27 mice and a user-blinded validation set of n = 57 mice (88% accuracy in a three-way classification). These results provide strong proof-of-concept support for the feasibility of using EV miRNA profiling and machine learning for liquid biopsy. Significance: These findings present a panel of extracellular vesicle miRNA blood-based biomarkers that can detect pancreatic cancer at a precancerous stage in a transgenic mouse model. Cancer Res; 78(13); 3688-97. ©2018 AACR ., (©2018 American Association for Cancer Research.)

Accurate automated quantification of subcortical structures is a greatly pursued endeavour in neuroimaging. In an effort to establish the validity and reliability of these methods in defining the striatum, globus pallidus, and thalamus, we investigated differences in volumetry between manual delineation and automated segmentations derived by widely used FreeSurfer and FSL packages, and a more recent segmentation method, the MAGeT-Brain algorithm. In a first set of experiments, the basal ganglia and thalamus of thirty subjects (15 first episode psychosis [FEP], 15 controls) were manually defined and compared to the labels generated by the three automated methods. Our results suggest that all methods overestimate volumes compared to the manually derived "gold standard", with the least pronounced differences produced using MAGeT. The least between-method variability was noted for the striatum, whereas marked differences between manual segmentation and MAGeT compared to FreeSurfer and FSL emerged for the globus pallidus and thalamus. Correlations between manual segmentation and automated methods were strongest for MAGeT (range: 0.51 to 0.92; p<0.01, corrected), whereas FreeSurfer and FSL showed moderate to strong Pearson correlations (range 0.44-0.86; p<0.05, corrected), with the exception of FreeSurfer pallidal (r=0.31, p=0.10) and FSL thalamic segmentations (r=0.37, p=0.051). Bland-Altman plots highlighted a tendency for greater volumetric differences between manual labels and automated methods at the lower end of the distribution (i.e. smaller structures), which was most prominent for bilateral thalamus across automated pipelines, and left globus pallidus for FSL. We then went on to examine volume and shape of the basal ganglia structures using automated techniques in 135 FEP patients and 88 controls. The striatum and globus pallidus were significantly larger in FEP patients compared to controls bilaterally, irrespective of the method used. MAGeT-Brain was more sensitive to shape-based group differences, and uncovered widespread surface expansions in the striatum and globus pallidus bilaterally in FEP patients compared to controls, and surface contractions in bilateral thalamus (FDR-corrected). By contrast, after using a recommended cluster-wise thresholding method, FSL only detected differences in the right ventral striatum (FEP>Control) and one cluster of the left thalamus (Control>FEP). These results suggest that different automated pipelines segment subcortical structures with varying degrees of variability compared to manual methods, with particularly pronounced differences found with FreeSurfer and FSL for the globus pallidus and thalamus., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Comprehensive molecular analysis of rare circulating tumor cells (CTCs) and cell clusters is often hampered by low throughput and purity, as well as cell loss. To address this, we developed a fully integrated platform for flow cytometry-based isolation of CTCs and clusters from blood that can be combined with whole transcriptome analysis or targeted RNA transcript quantification. Downstream molecular signature can be linked to cell phenotype through index sorting. This newly developed platform utilizes in-line magnetic particle-based leukocyte depletion, and acoustic cell focusing and washing to achieve >98% reduction of blood cells and non-cellular debris, along with >1.5 log-fold enrichment of spiked tumor cells. We could also detect 1 spiked-in tumor cell in 1 million WBCs in 4/7 replicates. Importantly, the use of a large 200μm nozzle and low sheath pressure (3.5 psi) minimized shear forces, thereby maintaining cell viability and integrity while allowing for simultaneous recovery of single cells and clusters from blood. As proof of principle, we isolated and transcriptionally characterized 63 single CTCs from a genetically engineered pancreatic cancer mouse model (n = 12 mice) and, using index sorting, were able to identify distinct epithelial and mesenchymal sub-populations based on linked single cell protein and gene expression.