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Objective: Current standard nonsurgical management of endometrial intraepithelial neoplasia (EIN) and grade 1 endometrioid endometrial cancer (g1EEC) is the Mirena levonorgestrel intrauterine device (M-IUD). This retrospective study was designed primarily to determine noninferiority of the Liletta IUD (L-IUD) for pathologic regression of EIN and g1EEC compared to the M-IUD at 6 months of continuous use. Secondary objectives include to determine noninferiority as above at 3, 9, and 12 months of continuous use and to identify factors including DNA mismatch repair (MMR) status associated with pathologic regression after LNG-IUD use., Methods: A retrospective observational study was performed with patients treated for EIN or g1EEC and managed continuously with M- or L-IUD. Patients with recent (within 6 months) or concurrent progesterone use were excluded. For the EIN group, the noninferiority margin of odds ratio was predetermined to be 0.58, and for the g1EEC group it was 0.64., Results: 62 patients from an academic center and a safety-net hospital were identified with continuous M-IUD (n = 44) or L-IUD (n = 18) use for EIN or g1EEC. 85% of patients treated with L-IUD were from a safety-net hospital, which had 63% with public insurance. At 3/6/9 months, 54/71/73% of patients with M-IUD and 80/83/100% with L-IUD had pathologic regression of EIN (95% confidence interval of estimated odds ratio 1.00-2.07/0.84-2.03/0.69-2.10). Lifetime smoking status, not MMR status, was significantly associated with pathologic regression., Conclusions: L-IUD is an effective fertility-sparing treatment for EIN. L-IUD is noninferior to M-IUD for pathologic regression of EIN after 3,6, and 9 months. Further larger studies are warranted to validate findings in EIN and g1EEC., 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., (© 2023 Published by Elsevier Inc.)

Hair follicles (HFs) are immersed within dermal white adipose tissue (dWAT), yet human adipocyte‒HF communication remains unexplored. Therefore, we investigated how perifollicular adipocytes affect the physiology of human anagen scalp HFs. Quantitative immunohistomorphometry, X-ray microcomputed tomography, and transmission electron microscopy showed that the number and size of perifollicular adipocytes declined during anagen‒catagen transition, whereas fluorescence-lifetime imaging revealed increased lipid oxidation in adipocytes surrounding the bulge and/or sub-bulge region. Ex vivo, dWAT tendentially promoted hair shaft production, and significantly stimulated hair matrix keratinocyte proliferation and HF pigmentation. Both dWAT pericytes and PREF1/DLK1 + adipocyte progenitors secreted HGF during human HF‒dWAT co-culture, for which the c-Met receptor was expressed in the hair matrix and dermal papilla. These effects were reproduced using recombinant HGF and abrogated by an HGF-neutralizing antibody. Laser-capture microdissection‒based microarray analysis of the hair matrix showed that dWAT-derived HGF upregulated keratin (K) genes (K27, K73, K75, K84, K86) and TCHH. Mechanistically, HGF stimulated Wnt/β-catenin activity in the human hair matrix (increased AXIN2, LEF1) by upregulating WNT6 and WNT10B, and inhibiting SFRP1 in the dermal papilla. Our study demonstrates that dWAT regulates human hair growth and pigmentation through HGF secretion, and thus identifies dWAT and HGF as important novel molecular and cellular targets for therapeutic intervention in human hair growth and pigmentation disorders., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Objectives: To determine if performing repeat tumor molecular profiling in solid malignancies over time can identify new findings that impact clinical care., Methods: All patients with a solid malignancy and more than 1 tumor molecular analysis were identified at a single institution. Each test report was examined to identify the genomic alterations. Chart review was performed to determine subsequent therapies following each test result and the impact of tumor profiling on clinical practice., Results: At a single institution, 110 patients were identified with having more than 1 tumor molecular analysis, with 98 subjects having test results available for review. Eighty-seven patients had differences in reported results at the time of subsequent analysis. These differences may reflect changes in tumor biology, be attributed to intra-patient or intra-tumor heterogeneity or be due to technical updates of the next generation sequencing platforms. Among the 98 subjects with solid tumors, the median time between tests was 10 months (range 0.5-66 months), with the majority of tests performed at the time of disease progression or recurrence. In this population, a total of 30 patients received targeted therapies that were associated with actionable findings on any tumor molecular analysis. Of these, 6 patients had new genomic findings identified on sequential testing that affected treatment., Conclusions: The future of cancer care must include precision medicine approaches. Evolution of next generation sequencing has contributed to this effort. Results of this single institution study summarize the reported findings on tumor molecular testing and suggest that subsequent testing may impact clinical care in a subset of patients. While only 6% of patients in this study saw a change in treatment based on new findings on sequential testing reports, this approach may be more clinically relevant in the future with the development of novel targeted therapies. This may be especially significant in a patient population that has progressed on standard therapies and where treatment options are limited., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to disclose., (Copyright © 2021. Published by Elsevier Inc.)

Purpose: Ocular anterior segment disorders (ASDs) are clinically and genetically heterogeneous, and genetic diagnosis often remains elusive. In this study, we demonstrate the value of a combined analysis protocol using phenotypic, genomic, and pedigree structure data to achieve a genetic conclusion., Methods: We utilized a combination of chromosome microarray, exome sequencing, and genome sequencing with structural variant and trio analysis to investigate a cohort of 41 predominantly sporadic cases., Results: We identified likely causative variants in 54% (22/41) of cases, including 51% (19/37) of sporadic cases and 75% (3/4) of cases initially referred as familial ASD. Two-thirds of sporadic cases were found to have heterozygous variants, which in most cases were de novo. Approximately one-third (7/22) of genetic diagnoses were found in rarely reported or recently identified ASD genes including PXDN, GJA8, COL4A1, ITPR1, CPAMD8, as well as the new phenotypic association of Axenfeld-Rieger anomaly with a homozygous ADAMTS17 variant. The remainder of the variants were in key ASD genes including FOXC1, PITX2, CYP1B1, FOXE3, and PAX6., Conclusions: We demonstrate the benefit of detailed phenotypic, genomic, variant, and segregation analysis to uncover some of the previously "hidden" heritable answers in several rarely reported and newly identified ocular ASD-related disease genes.

The solid-state properties of new chemical entities are critical to the stability and bioavailability of pharmaceutical drug products. The stability of the solid-state packing is described by the packing energy and an accurate prediction of this property for drug molecules would therefore be desirable. However, this has been difficult to achieve because of the lack of fundamental thermodynamic data on drug molecules. A potential solution would be to use calculated lattice energies to build a model and design molecules with desired physicochemical properties from an early stage, aligning with a "design by first intent" strategy for physicochemical properties. We first demonstrate the high correlation and interchangeability between QSPR models built using calculated lattice energies and experimental sublimation enthalpies for small organic molecules. We then present a QSPR model trained on in-house molecules using lattice energies calculated from crystal structures. The result is a model that enables fast prediction of the lattice energies of in-house molecules from 2-D molecular structure with reasonable accuracy (R 2  = 0.92, root mean square error = 3.58 kcal/mol). We explore the model elements to improve our understanding of the molecular properties that contribute to lattice energy and then suggest potential cross-industry aspects that may enhance the application of the concept., (Copyright © 2019 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.)