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Real-world evidence on persistence of interleukin-17 inhibitors (IL-17i) as a drug class among Japanese patients with psoriasis is lacking. Hence, we aimed to describe persistence rates of IL-17is among patients with psoriasis including psoriasis vulgaris (PsO), psoriatic arthritis (PsA), and generalized pustular psoriasis (GPP) or erythrodermic psoriasis (EP) in Japan. We analyzed claims data from the Medical Data Vision database. Patients ≥15 years old with a psoriasis diagnosis and an IL-17i prescription between November 2016 and August 2020 were included and followed through August 2021. Persistence rates of the IL-17i class among patients with psoriasis and its subtypes (PsO, PsA, and GPP or EP), and persistence rates of ixekizumab, secukinumab, or brodalumab among patients with PsO or PsA were analyzed using Kaplan-Meier method. Analyses were conducted in the bio-naïve and bio-experienced subgroups. The IL-17i class had >50% persistence rates up to 36 months among patients with psoriasis and its subtypes (PsO, PsA, and GPP or EP). 36-Month persistence rates for ixekizumab, secukinumab, and brodalumab were 46.2% to 57.7% in patients with PsO and 43.0% to 48.4% in patients with PsA. Across analyses, bio-naïve patients demonstrated similar or greater persistence rates than bio-experienced patients. IL-17is’ persistence rates over 36 months were >50% among patients with psoriasis and its subtypes (PsO, PsA, and GPP or EP) in Japan.

Converting solar energy into electricity provides an effective solution to the energy crisis the world is facing today. Organic Photovoltaics have shown potential to harness solar energy in a cost-effective way. Extensive progress has been achieved in understanding OPV photophysical phenomena and in identifying key factors needed to improve organic solar cell device power conversion efficiency (PCE). The newly synthesized polymer BDTP-Bz-1 and BDTP-Bz-2 composed of alternating benzotriazole and phenyl substituted benzodithiophene (Figure 1), yield 8% PCEs when blended in a bulk-hetero-junction (BHJ) structure with electron acceptor materials such as ITCC. The donor polymer BDTP-Bz-2 showed better device performance including short circuit current density (Jsc), open circuit voltage (Voc), and External Quentum Efficiency (EQE), which can contribute to its preference for the “face-on” polymer backbone orientation in which the π-conjugated polymer backbone planes lie parallel to the substrate surface, resulting in maximal contacts between organic photoactive materials and the ITO anode coated with electron transport layer (ZnO). This orientation of the π-π stacked structures would favor charge transport across the interface. By AFM analysis, it was revealed that the BDTP-Bz-2 : ITCC active layer showed lower surface roughness (10.6 nm) than BDTP-Bz-1 : ITCC active layer (12.5 nm). Lower surface roughness also helped form better interface contact between the active layer and the electrode.

Additional file 7: Fig. S1. a-b Violin plots showing GSVA score of cSE (a) or tSE (b) signature genes in four MB subgroups or NC of the indicated MB datasets. (c-d) Kaplan-Meier survival analysis of the GSVA scores of cSE (c) or tSE (d) genes in Cavalli dataset of MB. The patient cohort was stratified as high versus low groups by median GSVA score. Statistical significance was determined by one-way ANOVA (a-b), two-sided log-rank test (c-d). Fig. S2. a-c RT-qPCR analysis of vSE genes in MB002 or D425 cells when MYC (a), OTX2 (b) and CRX (c) were knocked down by shRNA individually. shSCR served as control. RT-qPCR assays were performed in triplicate and the data are presented as mean ± SD. Statistical significance was determined by two-tailed unpaired t test (a-c). Fig. S3. a Gene tracks of H3K27Ac ChIP-seq signal across G3-MB cells and tissues at SE regions near PSMB5. SE region is lined out over the gene tracks. b Gene tracks of H3K27Ac ChIP-seq signal across five G3-MB lines and non-G3-MB cells UW228 at SE regions near PSMB5. SE regions are lined out over the gene tracks. Positions of tested ChIP-qPCR amplicons, pooled-CRISPRi sgRNA targeting regions and 3C-PCR primers are shown below the tracks. c Box plots showing the FPKM values of PSMB5 from RNA-Seq replicates of D283, D425 and MB002 lines versus UW228, a control non-G3-MB line. d ChIP-qPCR analysis of H3K27Ac enrichment near PSMB5 in MB002, D283 and UW228, respectively. e 3C-PCR analysis of chromatin interaction between the H3K27Ac peak regions and promoter of PSMB5 in MB002, D283 and UW228. The workflow of 3C-PCR was shown in top panels, the agarose gel electrophoresis of 3C-PCR products was shown in bottom panels. The positions of 3C-PCR primers are shown in (b). f Negative control SE region of PSMB5 (NCP) without MboI site of 3C-PCR analysis related to Fig. S3 (e) was tested in MB002, D283 and UW228 by RT-qPCR. g-h Pooled-CRISPRi sgRNAs are designed to target the SE regions of PSMB5 in stable dCas9-KRAB expressing MB002 and D283, the PSMB5 expression level (g) is measured by RT-qPCR, and cell viabilities (h) are measured at Day 6. i RT-qPCR analysis of MYC and PSMB5 in D283 cells treated with 1 μM JQ1 or 0.1 μM THZ1 for 6 h. RT-qPCR analysis of PSMB5 in D283 when MYC (j), OTX2 (k) and CRX (l) were knocked down by shRNA individually (left). The cell viabilities were also measured (right). All RT-qPCR and cell viability assays were performed in triplicate and the data are presented as mean ± SD. Statistical significance was determined by one-way ANOVA (d) and two-tailed t test (c) and (g-i). Fig. S4. a UMAP plot showing MB subtypes (top left) or expression levels of PSMB5 in MB (top right) and GP3-MB (middle left), MYC (middle right), OTX2 (bottom left) and CRX (bottom right) in GP3-MB. Fig. S5. a Cell viability (top) and CI (bottom) of MB002 and D425 cells treated with THZ1 and Marizomib individually or in combination at the indicated concentrations for 72 h. b Cell viability (top) and CI (bottom) of D425 cells treated with JQ1 and Marizomib individually or in combination at the indicated concentrations for 72 h (top). c Cell viability of MB002 and D425 cells treated with Marizomib (3.25 nM for MB002, 125 nM for D425) and JQ1 (500 nM) individually or in combination were measured at Day 0/2/4 post treatment and normalized to Day 0-value. d The body weight of xenograft nude mice described in Fig. 4 (f-h) was recorded. Cell viability assays were performed in triplicate and the data are presented as mean ± SD. Line plot showing body weight of xenograft nude mice was presented as mean ± SEM in (d). Fig. S6. a UMAP plot showing MB subtypes (top left) or expression levels of ARL4D in MB (top right), GP3-MB (middle left) and GP4-MB (middle right), OTX2 (bottom two rows, left) and CRX (bottom two rows, right) in GP3- or GP4-MB. Fig. S7. a-b MB002 and D425 cells were infected with Cas13d empty vector (EV) or two separate clones of Cas13d-sgARL4D lentiviruses individually. After puromycin selection, the infected cells were then subjected to RT-qPCR analysis of ARL4D (a) as well as cell viability measurement at Day 0/2/4 (b). Uninfected tumor cells (Mock) were analyzed in parallel. RT-qPCR and cell viability results were normalized to EV or Day 0 sample, respectively. c UW228 cells were infected with Cas13d empty vector (EV) or two separate clones of Cas13d-sgARL4D lentivirus individually at the same MOI as MB002 and D425 in (a-b). Cell viability were measured at Day 0/2/4 and normalized to Day 0 sample. d-e FACS analyses of cell proliferation (d) and apoptosis (e) of MB002 and D425 cells upon ARL4D knockdown with Cas13d-sgARL4D. All RT-qPCR and cell viability assays were performed in triplicate and the data are presented as mean ± SD. Fig. S8. a Percentage ranking analysis of ARL4D as SE- or TE-target gene in five G3-MB cells and non-G3-MB cells UW228 was shown in the table. b Negative control SE region of ARL4D (NCA) without HindIII site of 3C-PCR analysis related to Fig. 6 (d) was tested in MB002 and UW228 by RT-qPCR. c-e 3C-PCR analysis of chromatin interaction between the H3K27Ac peak regions and promoter of the ARL4D in MB002. The positions of 3C-PCR primers are shown in (c). The same NCA region as above (neither containing the MboI site) was tested by RT-qPCR (d). The workflow of 3C-PCR was shown over the electrophoretogram of 3C-PCR products (e). f ChIP-qPCR analysis of OTX2 (top) and H3K27Ac (bottom) enrichment near ARL4D in MB002 upon OTX2 knockdown. g Phase changes of cell cycle in MB002 and D425 following ARL4D knockdown with two separate Cas13d-sgARL4D clones were determined by FACS as described in Fig. 7 (i). h The frequencies of tumorsphere-forming cells of MB002 and D425 upon ARL4D knockdown with two separate shRNA clones were determined by limiting dilution assay as described in Fig.7 (j) and analyzed by L-CalcTM software. ChIP-qPCR assay was performed in triplicate and the data are presented as mean ± SD. Statistical significance was determined by one-way ANOVA (f).

Most epithelium tissues continuously undergo self-renewal through proliferation and differentiation of epithelial stem cells (known as homeostasis), within a specialized stem cell niche. In highly innervated epithelium, peripheral nerves compose perineural niche and support stem cell homeostasis by releasing a variety of neurotransmitters, hormones, and growth factors and supplying trophic factors to the stem cells. Emerging evidence has shown that both sensory and motor nerves can regulate the fate of epithelial stem cells, thus influencing epithelium homeostasis. Understanding the mechanism of crosstalk between epithelial stem cells and neurons will reveal the important role of the perineural niche in physiological and pathological conditions. Herein, we review recent discoveries of the perineural niche in epithelium mainly in tissue homeostasis, with a limited touch in wound repair and pathogenesis.

We aimed to investigate the prevalence and predictors of diabetes and prediabetes among adults in Palau. We used data of 1915 adults, aged 25 to 64 years, who participated in the World Health Organization’s (WHO) STEPwise Approach to Risk Factor Surveillance (STEPS) study in Palau. Information on behavioral risk factors of NCDs and physical and biochemical measurements were obtained using standard methods of the WHO. The diagnosis of diabetes and prediabetes was based on the recent American Diabetes Association criteria. Predictors of the prevalence of diabetes and prediabetes were identified using multinomial logistic regression analysis. The overall age-standardized prevalence of prediabetes and diabetes were 40.4% (43.6% for men, 37.4% for women) and 17.7% (18.6% for men, 17% for women), respectively. Old age, overall obesity (high BMI), central obesity (large waist circumference or waist-hip ratio), hypertension and hypertriglyceridemia were significant predictors of prediabetes and/or diabetes. Diabetes occurred at a younger age in “obese” individuals than that of their “non-obese” counterparts. We confirmed that prediabetes and diabetes are highly prevalent in Palau affecting 40% and 18% adults, respectively. Introducing public health interventions to reduce and prevent obesity as early as possible could prove useful to curb the problem.