Ultraviolet photodepletion spectroscopy of dibenzo-18-crown-6-ether complexes with alkali metal cations

Ultraviolet photodepletion spectra of dibenzo-18-crown-6-ether complexes with alkali metal cations (M+-DB18C6, M = Cs, Rb, K, Na, and Li) were obtained in the gas phase using electrospray ionization quadrupole ion-trap reflectron time-of-flight mass spectrometry. The spectra exhibited a few distinct absorption bands in the wavenumber region of 35450−37800 cm^(−1). The lowest-energy band was tentatively assigned to be the origin of the S_0-S_1 transition, and the second band to a vibronic transition arising from the “benzene breathing” mode in conjunction with symmetric or asymmetric stretching vibration of the bonds between the metal cation and the oxygen atoms in DB18C6. The red shifts of the origin bands were observed in the spectra as the size of the metal cation in M^+-DB18C6 increased from Li^+ to Cs^+. We suggested that these red shifts arose mainly from the decrease in the binding energies of larger-sized metal cations to DB18C6 at the electronic ground state. These size effects of the metal cations on the geometric and electronic structures, and the binding properties of the complexes at the S_0 and S_1 states were further elucidated by theoretical calculations using density functional and time-dependent density functional theories

Unleashing the full potential of Hsp90 inhibitors as cancer therapeutics through simultaneous inactivation of Hsp90, Grp94, and TRAP1

Cancer therapeutics: Extending a drug's reach A new drug that blocks heat shock proteins (HSPs), helper proteins that are co-opted by cancer cells to promote tumor growth, shows promise for cancer treatment. Several drugs have targeted HSPs, since cancer cells are known to hijack these helper proteins to shield themselves from destruction by the body. However, the drugs have had limited success. Hye-Kyung Park and Byoung Heon Kang at Ulsan National Institutes of Science and Technology in South Korea and coworkers noticed that the drugs were not absorbed into mitochondria, a key cellular compartment, and HSPs in this compartment were therefore not being blocked. They identified a new HSP inhibitor that can reach every cellular compartment and inhibit all HSPs. Testing in mice showed that this inhibitor effectively triggered death of tumor cells, and therefore shows promise for anti-cancer therapy. The Hsp90 family proteins Hsp90, Grp94, and TRAP1 are present in the cell cytoplasm, endoplasmic reticulum, and mitochondria, respectively; all play important roles in tumorigenesis by regulating protein homeostasis in response to stress. Thus, simultaneous inhibition of all Hsp90 paralogs is a reasonable strategy for cancer therapy. However, since the existing pan-Hsp90 inhibitor does not accumulate in mitochondria, the potential anticancer activity of pan-Hsp90 inhibition has not yet been fully examined in vivo. Analysis of The Cancer Genome Atlas database revealed that all Hsp90 paralogs were upregulated in prostate cancer. Inactivation of all Hsp90 paralogs induced mitochondrial dysfunction, increased cytosolic calcium, and activated calcineurin. Active calcineurin blocked prosurvival heat shock responses upon Hsp90 inhibition by preventing nuclear translocation of HSF1. The purine scaffold derivative DN401 inhibited all Hsp90 paralogs simultaneously and showed stronger anticancer activity than other Hsp90 inhibitors. Pan-Hsp90 inhibition increased cytotoxicity and suppressed mechanisms that protect cancer cells, suggesting that it is a feasible strategy for the development of potent anticancer drugs. The mitochondria-permeable drug DN401 is a newly identified in vivo pan-Hsp90 inhibitor with potent anticancer activity

EM-Network: Oracle Guided Self-distillation for Sequence Learning

We introduce EM-Network, a novel self-distillation approach that effectively leverages target information for supervised sequence-to-sequence (seq2seq) learning. In contrast to conventional methods, it is trained with oracle guidance, which is derived from the target sequence. Since the oracle guidance compactly represents the target-side context that can assist the sequence model in solving the task, the EM-Network achieves a better prediction compared to using only the source input. To allow the sequence model to inherit the promising capability of the EM-Network, we propose a new self-distillation strategy, where the original sequence model can benefit from the knowledge of the EM-Network in a one-stage manner. We conduct comprehensive experiments on two types of seq2seq models: connectionist temporal classification (CTC) for speech recognition and attention-based encoder-decoder (AED) for machine translation. Experimental results demonstrate that the EM-Network significantly advances the current state-of-the-art approaches, improving over the best prior work on speech recognition and establishing state-of-the-art performance on WMT'14 and IWSLT'14.Comment: ICML 202

Urinary Phthalate Metabolites and Slow Walking Speed in the Korean Elderly Environmental Panel II Study

Background: Previous epidemiological studies have suggested that phthalate exposure may contribute to neurocognitive and neurobehavioral disorders and decreased muscle strength and bone mass, all of which may be associated with reduced physical performance. Walking speed is a reliable assessment tool for measuring physical performance in adults age 60 y and older. Objective: We investigated associations between urinary phthalate metabolites and slowness of walking speed in community-dwelling adults ages 60-98 y. Methods: We analyzed 1,190 older adults [range, 60-98 y of age; mean ± standard deviation (SD), 74.81 ± 5.99] from the Korean Elderly Environmental Panel II study and measured repeatedly up to three times between 2012 and 2014. Phthalate exposure was estimated using the following phthalate metabolites in urine samples: mono-(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP), mono-(2-ethyl-5-oxohexyl) phthalate (MEOHP), mono-n-butyl phthalate (MnBP), mono-(2-ethyl-5-carboxypentyl) phthalate (MECPP), and mono-benzyl phthalate (MBzP). Slowness was defined as a walking speed of < 1.0 meter/second. We used logistic and linear regression models to evaluate the association between each urinary phthalate metabolite and slowness or walking-speed change. We also used Bayesian kernel machine regression (BKMR) to examine overall mixture effects on walking speed. Results: At enrollment, MBzP levels were associated with an increased odds of slowness [odds ratio (OR) per doubling increase: 1.15, 95% confidence interval (CI): 1.02, 1.30; OR for the highest vs. lowest quartile: 2.20 (95% CI: 1.12, 4.35) with p-trend across quartiles = 0.031]. In longitudinal analyses, MEHHP levels showed an increased risk of slowness [OR per doubling increase: 1.15 (95% CI: 1.02, 1.29), OR for the highest vs. lowest quartile: 1.47 (95% CI: 1.04, 2.06), p−trend=0.035]; whereas those with higher MnBP showed a reduced risk of slowness [OR per doubling increase: 0.84 (95% CI: 0.74, 0.96), OR in the highest (vs. lowest) quartile: 0.64 (95% CI: 0.47, 0.87), p−trend=0.006]. For linear regression models, MBzP quartiles were associated with slower walking speed (p−trend=0.048) at enrollment, whereas MEHHP quartiles were associated with slower walking speed, and MnBP quartiles were associated with faster walking speed in longitudinal analysis (p−trend=0.026 and <0.001, respectively). Further, the BKMR analysis revealed negative overall trends between the phthalate metabolite mixtures and walking speed and DEHP group (MEHHP, MEOHP, and MECPP) had the main effect of the overall mixture. Discussion: Urinary concentrations of prevalent phthalates exhibited significant associations with slow walking speed in adults ages 60-98 y. https://doi.org/10.1289/EHP10549.This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korea Ministry of Education and the Korea Ministry of Science and Information and Communication Technology (grant numbers 2013R1A6A3A04059556; 2020R1A2C110170311). Also, this study was supported by the Susceptible Population Research Program (2008–2010) from the Korea Ministry of Environment (grant numbers 0411-20080013, 0411-20090007, 0411-20100016). E.G.-E. was supported by the Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP) (ESP21PI04/2021). The funders had no role in this study design, data collection, and analysis and prepared all results. All authors participated in literature search and data interpretation. Y.C. supervised the study; Y.C. and Y.H. participated in designing the study; H.K., S.K., and K.K. acquired the data; J.Y., J. Kim, and J. Kwak analyzed data; J.Y. wrote the manuscript; E.G.-E., J. Kim, J. Kwak, H.K., Y.H., and Y.C. critically revised the manuscript. Patient consent was obtained. This study was approved by the institutional review board (IRB) of Seoul National University Hospital/College of Medicine (IRB No. H-1209-004-424).S

Integrative analysis of plasma and substantia nigra in Parkinson’s disease: unraveling biomarkers and insights from the lncRNA–miRNA–mRNA ceRNA network

IntroductionParkinson’s disease (PD) is a rapidly growing neurological disorder characterized by diverse movement symptoms. However, the underlying causes have not been clearly identified, and accurate diagnosis is challenging. This study aimed to identify potential biomarkers suitable for PD diagnosis and present an integrative perspective on the disease.MethodsWe screened the GSE7621, GSE8397-GPL96, GSE8397-GPL97, GSE20163, and GSE20164 datasets in the NCBI GEO database to identify differentially expressed (DE) mRNAs in the substantia nigra (SN). We also screened the GSE160299 dataset from the NCBI GEO database to identify DE lncRNAs and miRNAs in plasma. We then constructed 2 lncRNA–miRNA–mRNA competing endogenous RNA (ceRNA) regulatory networks based on the ceRNA hypothesis. To understand the biological function, we performed Kyoto Encyclopedia of Genes and Genomes pathway and Gene Ontology analyses for each ceRNA network. The receiver operating characteristic analyses (ROC) was used to assess ceRNA results.ResultsWe identified 7 upregulated and 29 downregulated mRNAs as common DE mRNAs in the 5 SN datasets. In the blood dataset, we identified 31 DE miRNAs (9 upregulated and 22 downregulated) and 332 DE lncRNAs (69 upregulated and 263 downregulated). Based on the determined interactions, 5 genes (P2RX7, HSPA1, SLCO4A1, RAD52, and SIRT4) appeared to be upregulated as a result of 10 lncRNAs sponging 4 miRNAs (miR-411, miR-1193, miR-301b, and miR-514a-2/3). Competing with 9 genes (ANK1, CBLN1, RGS4, SLC6A3, SYNGR3, VSNL1, DDC, KCNJ6, and SV2C) for miR-671, a total of 26 lncRNAs seemed to function as ceRNAs, influencing genes to be downregulated.DiscussionIn this study, we successfully constructed 2 novel ceRNA regulatory networks in patients with PD, including 36 lncRNAs, 5 miRNAs, and 14 mRNAs. Our results suggest that these plasma lncRNAs are involved in the pathogenesis of PD by sponging miRNAs and regulating gene expression in the SN of the brain. We propose that the upregulated and downregulated lncRNA-mediated ceRNA networks represent mechanisms of neuroinflammation and dopamine neurotransmission, respectively. Our ceRNA network, which was associated with PD, suggests the potential use of DE miRNAs and lncRNAs as body fluid diagnostic biomarkers. These findings provide an integrated view of the mechanisms underlying gene regulation and interactions in PD