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The process of developing new reversed-phase liquid chromatography methods can be both time-consuming and challenging. To meet this challenge, statistics-based strategies have emerged as cost-effective, efficient and flexible solutions. In the present study, we use a Bayesian response surface methodology, which takes advantage of the knowledge of the pKa values of the compounds present in the analyzed sample to model their retention behavior. A multi-criteria decision analysis (MCDA) was then developed to exploit the uncertainty information inherent in the model distributions. This strategic approach is designed to integrate seamlessly with quantitative structure retention relationship (QSRR) models, forming an initial in-silico screening phase. Of the two methods presented for MCDA, one showed promising results. The method development process was carried out with the optimization phase, generating a design space that corroborates the results of the selection phase., Competing Interests: Declaration of Competing Interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Laboratory for the Analysis of Medicines & Laboratory of Pharmaceutical Analytical Chemistry reports financial support was provided by Fund for Scientific Research. If there are other authors, they 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 © 2024 Elsevier B.V. All rights reserved.)

QSRR is a valuable technique for the retention time predictions of small molecules. This aims to bridge the gap between molecular structure and chromatographic behavior, offering invaluable insights for analytical chemistry. Given the challenge of simultaneous target prediction with variable experimental conditions and the scarcity of comprehensive data sets for such predictive modelings in chromatography, this study introduces a transfer learning-based multitarget QSRR approach to enhance retention time prediction. Through a comparative study of four models, both with and without the transfer learning approach, the performance of both single and multitarget QSRR was evaluated based on Mean Squared Error (MSE) and R 2 metrics. Individual models were also tested for their performance against benchmark studies in this field. The findings suggest that transfer learning based multitarget models exhibit potential for enhanced accuracy in predicting retention times of small molecules, presenting a promising avenue for QSRR modeling. These models will be highly beneficial for optimizing experimental conditions in method development by better retention time predictions in Reversed-Phase Liquid Chromatography (RPLC). The reliable and effective predictive capabilities of these models make them valuable tools for pharmaceutical research and development endeavors.

Quantitative structure-retention relationship models (QSRR) have been utilized as an alternative to costly and time-consuming separation analyses and associated experiments for predicting retention time. However, achieving 100 % accuracy in retention prediction is unrealistic despite the existence of various tools and approaches. The limitations of vast data availability and time complexity hinder the use of most algorithms for retention prediction. Therefore, in this study, we examined and compared two approaches for modelling retention time using a dataset of small molecules with retention times obtained at multiple conditions, referred to as multi-targets (five pH levels: 2.7, 3.5, 5, 6.5, and 8 at gradient times of 20 min of mobile phase). The first approach involved developing separate models for predicting retention time at each condition (single-target approach), while the second approach aimed to learn a single model for predicting retention across all conditions simultaneously (multi-target approach). Our findings highlight the advantages of the multi-target approach over the single-target modelling approach. The multi-target models are more efficient in terms of size and learning speed compared to the single-target models. These retention prediction models offer two-fold benefits. Firstly, they enhance knowledge and understanding of retention times, identifying molecular descriptors that contribute to changes in retention behaviour under different pH conditions. Secondly, these approaches can be extended to address other multi-target property prediction problems, such as multi-quantitative structure Property(X) relationship studies (mt-QS(X)R)., 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 © 2023. Published by Elsevier B.V.)

Surface-enhanced Raman scattering (SERS) is a vibrational widely used technique thanks to its multiple advantages such as its high specificity and sensitivity. The Raman signal exaltation comes from the use of metallic nanoparticles (Nps) acting as antennas by amplifying the Raman scattering. Controlling the Nps synthesis is a major point for the implementation of SERS in routine analysis and especially in quantitative applications. Effectively, nature, size and shape of these Nps considerably influence the SERS response intensity and repeatability. The Lee-Meisel protocol is the most common synthesis route used by the SERS community due to the low cost, rapidity and ease of manufacturing. However, this process leads to a significant heterogeneity in terms of particle size and shape. In this context, this study aimed to synthesize repeatable and homogeneous silver nanoparticles (AgNps) by chemical reduction. The Quality by Design strategy from quality target product profile to early characterization design was considered to optimize this reaction. The first step of this strategy aimed to highlight critical parameters by the means of an early characterization design. Based on an Ishikawa diagram, five process parameters were studied: the reaction volume as categorical variable and the temperature, the time of reaction, the trisodium citrate concentration and pH as continuous variables. A D-Optimal design of 35 conditions was performed. Three critical quality attributes were selected to maximize the SERS intensity, minimize the variation coefficient on SERS intensities and the polydispersity index of the AgNps. Considering these factors, it appeared that concentration, pH and time of reaction were identified as having a critical impact on the Nps formation and can then be considered for the further optimization step., 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 © 2023 Elsevier B.V. All rights reserved.)

Reversed-Phase Liquid Chromatography (RPLC) is a common liquid chromatographic mode used for the control of pharmaceutical compounds during their drug life cycle. Nevertheless, determining the optimal chromatographic conditions that enable this separation is time consuming and requires a lot of lab work. Quantitative Structure Retention Relationship models (QSRR) are helpful for doing this job with minimal time and cost expenditures by predicting retention times of known compounds without performing experiments. In the current work, several QSRR models were built and compared for their adequacy in predicting the retention times. The regression models were based on a combination of linear and non-linear algorithms such as Multiple Linear Regression, Support Vector Regression, Least Absolute Shrinkage and Selection Operator, Random Forest, and Gradient Boosted Regression. Models were built for five pH conditions, i.e., at pH 2.7, 3.5, 6.5, and 8.0. In the end, the model predictions were combined using stacking and the performances of all models were compared. The k-nearest neighbor-based application domain filter was established to assess the reliability of the prediction for further compound prioritization. Altogether, this study can be insightful for analytical chemists working with RPLC to begin with the computational prediction modeling such as QSRR to predict the separation of small molecules.

In the pharmaceutical field, and more precisely in quality control laboratories, robust liquid chromatographic methods are needed to separate and analyze mixtures of compounds. The development of such chromatographic methods for new mixtures can result in a long and tedious process even while using the design of experiments methodology. However, developments could be accelerated with the help of in silico screening. In this work, the usefulness of a strategy combining response surface methodology (RSM) followed by multicriteria decision analysis (MCDA) applied to predictions from a quantitative structure-retention relationship (QSRR) model is demonstrated. The developed strategy shows that selecting equations for the retention time prediction models based on the pKa of the compound allows flexibility in the models. The MCDA developed is shown to help to make decisions on different criteria while being robust to the user's decision on the weights for each criterion. This strategy is proposed for the screening phase of the method lifecycle. The strategy offers the possibility to the user to select chromatographic conditions based on multiple criteria without being too sensitive to the importance given to them. The conditions with the highest desirability are defined as the starting point for further optimization steps.

There is a rising interest in the modeling and predicting of chromatographic retention. The progress towards more complex and comprehensive models emphasized the need for broad reliable datasets. The present dataset comprises small pharmaceutical compounds selected to cover a wide range in terms of physicochemical properties that are known to impact the retention in reversed-phase liquid chromatography. Moreover, this dataset was analyzed at five pH with two gradient slopes. It provides a reliable dataset with a diversity of conditions and compounds to support the building of new models. To enhance the robustness of the dataset, the compounds were injected individually, and each sequence of injections included a quality control sample. This unambiguous detection of each compound as well as a systematic analysis of a quality control sample ensured the quality of the reported retention times. Moreover, three different liquid chromatographic systems were used to increase the robustness of the dataset., Competing Interests: 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., (© 2022 The Author(s). Published by Elsevier Inc.)

Inactivating variants as well as a missense variant in the centrosomal CEP78 gene have been identified in autosomal recessive cone-rod dystrophy with hearing loss (CRDHL), a rare syndromic inherited retinal disease distinct from Usher syndrome. Apart from this, a complex structural variant (SV) implicating CEP78 has been reported in CRDHL. Here we aimed to expand the genetic architecture of typical CRDHL by the identification of complex SVs of the CEP78 region and characterization of their underlying mechanisms. Approaches used for the identification of the SVs are shallow whole-genome sequencing (sWGS) combined with quantitative polymerase chain reaction (PCR) and long-range PCR, or ExomeDepth analysis on whole-exome sequencing (WES) data. Targeted or whole-genome nanopore long-read sequencing (LRS) was used to delineate breakpoint junctions at the nucleotide level. For all SVs cases, the effect of the SVs on CEP78 expression was assessed using quantitative PCR on patient-derived RNA. Apart from two novel canonical CEP78 splice variants and a frameshifting single-nucleotide variant (SNV), two SVs affecting CEP78 were identified in three unrelated individuals with CRDHL: a heterozygous total gene deletion of 235 kb and a partial gene deletion of 15 kb in a heterozygous and homozygous state, respectively. Assessment of the molecular consequences of the SVs on patient's materials displayed a loss-of-function effect. Delineation and characterization of the 15-kb deletion using targeted LRS revealed the previously described complex CEP78 SV, suggestive of a recurrent genomic rearrangement. A founder haplotype was demonstrated for the latter SV in cases of Belgian and British origin, respectively. The novel 235-kb deletion was delineated using whole-genome LRS. Breakpoint analysis showed microhomology and pointed to a replication-based underlying mechanism. Moreover, data mining of bulk and single-cell human and mouse transcriptional datasets, together with CEP78 immunostaining on human retina, linked the CEP78 expression domain with its phenotypic manifestations. Overall, this study supports that the CEP78 locus is prone to distinct SVs and that SV analysis should be considered in a genetic workup of CRDHL. Finally, it demonstrated the power of sWGS and both targeted and whole-genome LRS in identifying and characterizing complex SVs in patients with ocular diseases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Ascari, Rendtorff, De Bruyne, De Zaeytijd, Van Lint, Bauwens, Van Heetvelde, Arno, Jacob, Creytens, Van Dorpe, Van Laethem, Rosseel, De Pooter, De Rijk, De Coster, Menten, Rey, Strazisar, Bertelsen, Tranebjaerg and De Baere.)

Inactivating variants in the centrosomal CEP78 gene have been found in cone-rod dystrophy with hearing loss (CRDHL), a particular phenotype distinct from Usher syndrome. Here, we identified and functionally characterized the first CEP78 missense variant c.449T>C, p.(Leu150Ser) in three CRDHL families. The variant was found in a biallelic state in two Belgian families and in a compound heterozygous state-in trans with c.1462-1G>T-in a third German family. Haplotype reconstruction showed a founder effect. Homology modeling revealed a detrimental effect of p.(Leu150Ser) on protein stability, which was corroborated in patients' fibroblasts. Elongated primary cilia without clear ultrastructural abnormalities in sperm or nasal brushes suggest impaired cilia assembly. Two affected males from different families displayed sperm abnormalities causing infertility. One of these is a heterozygous carrier of a complex allele in SPAG17, a ciliary gene previously associated with autosomal recessive male infertility. Taken together, our data indicate that a missense founder allele in CEP78 underlies the same sensorineural CRDHL phenotype previously associated with inactivating variants. Interestingly, the CEP78 phenotype has been possibly expanded with male infertility. Finally, CEP78 loss-of-function variants may have an underestimated role in misdiagnosed Usher syndrome, with or without sperm abnormalities., (© 2020 The Authors. Human Mutation published by Wiley Periodicals, Inc.)

Purpose: ABCA4-associated disease, a recessive retinal dystrophy, is hallmarked by a large proportion of patients with only one pathogenic ABCA4 variant, suggestive for missing heritability., Methods: By locus-specific analysis of ABCA4, combined with extensive functional studies, we aimed to unravel the missing alleles in a cohort of 67 patients (p), with one (p = 64) or no (p = 3) identified coding pathogenic variants of ABCA4., Results: We identified eight pathogenic (deep-)intronic ABCA4 splice variants, of which five are novel and six structural variants, four of which are novel, including two duplications. Together, these variants account for the missing alleles in 40.3% of patients. Furthermore, two novel variants with a putative cis-regulatory effect were identified. The common hypomorphic variant c.5603A>T p.(Asn1868Ile) was found as a candidate second allele in 43.3% of patients. Overall, we have elucidated the missing heritability in 83.6% of our cohort. In addition, we successfully rescued three deep-intronic variants using antisense oligonucleotide (AON)-mediated treatment in HEK 293-T cells and in patient-derived fibroblast cells., Conclusion: Noncoding pathogenic variants, novel structural variants, and a common hypomorphic allele of the ABCA4 gene explain the majority of unsolved cases with ABCA4-associated disease, rendering this retinopathy a model for missing heritability in autosomal recessive disorders.

Purpose: RAX2 encodes a homeobox-containing transcription factor, in which four monoallelic pathogenic variants have been described in autosomal dominant cone-dominated retinal disease., Methods: Exome sequencing in a European cohort with inherited retinal disease (IRD) (n = 2086) was combined with protein structure modeling of RAX2 missense variants, bioinformatics analysis of deletion breakpoints, haplotyping of RAX2 variant c.335dup, and clinical assessment of biallelic RAX2-positive cases and carrier family members., Results: Biallelic RAX2 sequence and structural variants were found in five unrelated European index cases, displaying nonsyndromic autosomal recessive retinitis pigmentosa (ARRP) with an age of onset ranging from childhood to the mid-40s (average mid-30s). Protein structure modeling points to loss of function of the novel recessive missense variants and to a dominant-negative effect of the reported dominant RAX2 alleles. Structural variants were fine-mapped to disentangle their underlying mechanisms. Haplotyping of c.335dup in two cases suggests a common ancestry., Conclusion: This study supports a role for RAX2 as a novel disease gene for recessive IRD, broadening the mutation spectrum from sequence to structural variants and revealing a founder effect. The identification of biallelic RAX2 pathogenic variants in five unrelated families shows that RAX2 loss of function may be a nonnegligible cause of IRD in unsolved ARRP cases.

The original version of this Article contained an incorrect version of Fig. 3, which included two variants initially shown in black text in Fig. 3a that the authors removed from the final manuscript. The correct version of Fig. 3 without the two variants now appears in the PDF and HTML versions of the Article.

Purpose: Our goal was to design a customized microarray, arrEYE, for high-resolution copy number variant (CNV) analysis of known and candidate genes for inherited retinal dystrophy (iRD) and retina-expressed noncoding RNAs (ncRNAs)., Methods: arrEYE contains probes for the full genomic region of 106 known iRD genes, including those implicated in retinitis pigmentosa (RP) (the most frequent iRD), cone-rod dystrophies, macular dystrophies, and an additional 60 candidate iRD genes and 196 ncRNAs. Eight CNVs in iRD genes identified by other techniques were used as positive controls. The test cohort consisted of 57 patients with autosomal dominant, X-linked, or simplex RP., Results: In an RP patient, a novel heterozygous deletion of exons 7 and 8 of the HGSNAT gene was identified: c.634-408_820+338delinsAGAATATG, p.(Glu212Glyfs*2). A known variant was found on the second allele: c.1843G>A, p.(Ala615Thr). Furthermore, we expanded the allelic spectrum of USH2A and RCBTB1 with novel CNVs., Conclusion: The arrEYE platform revealed subtle single-exon to larger CNVs in iRD genes that could be characterized at the nucleotide level, facilitated by the high resolution of the platform. We report the first CNV in HGSNAT that, combined with another mutation, leads to RP, further supporting its recently identified role in nonsyndromic iRD.Genet Med 19 4, 457-466.

Inherited retinal dystrophies (iRDs) are a group of genetically and clinically heterogeneous conditions resulting from mutations in over 250 genes. Here, homozygosity mapping and whole-exome sequencing (WES) in a consanguineous family revealed a homozygous missense mutation, c.973C>T (p.His325Tyr), in RCBTB1. In affected individuals, it was found to segregate with retinitis pigmentosa (RP), goiter, primary ovarian insufficiency, and mild intellectual disability. Subsequent analysis of WES data in different cohorts uncovered four additional homozygous missense mutations in five unrelated families in whom iRD segregates with or without syndromic features. Ocular phenotypes ranged from typical RP starting in the second decade to chorioretinal dystrophy with a later age of onset. The five missense mutations affect highly conserved residues either in the sixth repeat of the RCC1 domain or in the BTB1 domain. A founder haplotype was identified for mutation c.919G>A (p.Val307Met), occurring in two families of Mediterranean origin. We showed ubiquitous mRNA expression of RCBTB1 and demonstrated predominant RCBTB1 localization in human inner retina. RCBTB1 was very recently shown to be involved in ubiquitination, more specifically as a CUL3 substrate adaptor. Therefore, the effect on different components of the CUL3 and NFE2L2 (NRF2) pathway was assessed in affected individuals' lymphocytes, revealing decreased mRNA expression of NFE2L2 and several NFE2L2 target genes. In conclusion, our study puts forward mutations in RCBTB1 as a cause of autosomal-recessive non-syndromic and syndromic iRD. Finally, our data support a role for impaired ubiquitination in the pathogenetic mechanism of RCBTB1 mutations., (Copyright © 2016 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

Background: With one million new cases of colorectal cancer (CRC) diagnosed annually in the world, CRC is the third most commonly diagnosed cancer in the Western world. Patients with stage I-III CRC can be cured with surgery but are at risk for recurrence. Colorectal cancer is characterized by the presence of chromosomal deletions and gains. Large genomic profiling studies have however not been conducted in this disease. The number of a specific genetic aberration in a tumour sample could correlate with recurrence-free survival or overall survival, possibly leading to its use as biomarker for therapeutic decisions. At this point there are not sufficient markers for prediction of disease recurrence in colorectal cancer, which can be used in the clinic to discriminate between stage II patients who will benefit from adjuvant chemotherapy. For instance, the benefit of adjuvant chemotherapy has been most clearly demonstrated in stage III disease with an approximately 30 percent relative reduction in the risk of disease recurrence. The benefits of adjuvant chemotherapy in stage II disease are less certain, the risk for relapse is much smaller in the overall group and the specific patients at risk are hard to identify., Materials and Methods: In this study, array-comparative genomic hybridization analysis (array-CGH) was applied to study high-resolution DNA copy number alterations in 93 colon carcinoma samples. These genomic data were combined with parameters like KRAS mutation status, microsatellite status and clinicopathological characteristics., Results: Both large and small chromosomal losses and gains were identified in our sample cohort. Recurrent gains were found for chromosome 1q, 7, 8q, 13 and 20 and losses were mostly found for 1p, 4, 8p, 14, 15, 17p, 18, 21 and 22. Data analysis demonstrated that loss of chromosome 4 is linked to a worse prognosis in our patients series. Besides these alterations, two interesting small regions of overlap were identified, which could be associated with disease recurrence. Gain of the 16p13.3 locus (including the RNA binding protein, fox-1 homolog gene, RBFOX1) was linked with a worse recurrence-free survival in our patient cohort. On the other hand, loss of RBFOX1 was only found in patients without disease recurrence. Most interestingly, above mentioned characteristics were also found in stage II patients, for whom there is a high medical need for the identification of new prognostic biomarkers., Conclusions: In conclusion, copy number variation of the 16p13.3 locus seems to be an important parameter for prediction of disease recurrence in colon cancer.