Chloroplast genome characteristics and phylogeny of the sinodielsia clade (apiaceae: apioideae).

BACKGROUND: The Sinodielsia clade of the subfamily Apioideae (Apiacieae) was established in 2008, and it is composed of 37 species from 17 genera. Its circumscription is still poorly delimited and unstable, and interspecific relationships in the clade lack comprehensive analysis. Chloroplast (cp.) genomes provide valuable and informative data sources for evolutionary biology and have been widely used in studies on plant phylogeny. To infer the phylogenetic history of the Sinodielsia clade, we assembled complete cp. genomes of 39 species and then performed phylogenetic analysis based on these cp. genome sequence data combined with 66 published cp. genomes from 16 genera relative to the Sinodielsia clade. RESULTS: These 39 newly assembled genomes had a typical quadripartite structure with two inverted repeat regions (IRs: 17,599-31,486 bp) separated by a large single-copy region (LSC: 82,048-94,046 bp) and a small single-copy region (SSC: 16,343-17,917 bp). The phylogenetic analysis showed that 19 species were clustered into the Sinodielsia clade, and they were divided into two subclades. Six mutation hotspot regions were detected from the whole cp. genomes among the Sinodielsia clade, namely, rbcL-accD, ycf4-cemA, petA-psbJ, ycf1-ndhF, ndhF-rpl32 and ycf1, and it was found that ndhF-rpl32 and ycf1 were highly variable in the 105 sampled cp. genomes. CONCLUSION: The Sinodielsia clade was subdivided into two subclades relevant to geographical distributions, except for cultivated and introduced species. Six mutation hotspot regions, especially ndhF-rpl32 and ycf1, could be used as potential DNA markers in the identification and phylogenetic analyses of the Sinodielsia clade and Apioideae. Our study provided new insights into the phylogeny of the Sinodielsia clade and valuable information on cp. genome evolution in Apioideae.

Correlation of CCL8 expression with immune cell infiltration of skin cutaneous melanoma: potential as a prognostic indicator and therapeutic pathway.

BACKGROUND: The tumor microenvironment (TME) is critical in the progression and metastasis of skin cutaneous melanoma (SKCM). Differences in tumor-infiltrating immune cells (TICs) and their gene expression have been linked to cancer prognosis. Given that immunotherapy can be effective against SKCM, we aimed to identify key genes that regulate the immunological state of the TME in SKCM. METHODS: Data from 471 SKCM patients in the The Cancer Genome Atlas were analyzed using ESTIMATE algorithms to generate an ImmuneScore, StromalScore, and EstimateScore for each patient. Patients were classified into low- or high-score groups based on median values, then compared in order to identify differentially expressed genes (DEGs). Then a protein-protein interaction (PPI) network was developed, and a prognostic model was created using uni- and multivariate Cox regression as well as the least absolute shrinkage and selection operator (LASSO). Key DEGs were identified using the web-based tool GEPIA. Profiles of TIC subpopulations in each patient were analyzed using CIBORSORT, and possible correlations between key DEG expression and TICs were explored. Levels of CCL8 were determined in SKCM and normal skin tissue using immunohistochemistry. RESULTS: Two scores correlated positively with the prognosis of SKCM patients. Comparison of the low- and high-score groups revealed 1684 up-regulated and 18 down-regulated DEGs, all of which were enriched in immune-related functions. The prognostic model identified CCL8 as a key gene, which CIBERSORT found to correlate with M1 macrophages. Immunohistochemistry revealed strong expression in SKCM tissue, but failed to detect the protein in normal skin tissue. CONCLUSIONS: CCL8 is a potential prognostic marker for SKCM, and it may become an effective target for melanoma in which M1 macrophages play an important role.

WW Domain-Containing E3 Ubiquitin Protein Ligase 1: A Self-Disciplined Oncoprotein.

WW domain-containing E3 ubiquitin protein ligase 1 (WWP1) is a member of C2-WW-HECT E3 ligase family. Although it may execute carcinostatic actions in some scenarios, WWP1 functions as an oncoprotein under most circumstances. Here, we comprehensively review reports on regulation of WWP1 and its roles in tumorigenesis. We summarize the WWP1-mediated ubiquitinations of diverse proteins and the signaling pathways they involved, as well as the mechanisms how they affect cancer formation and progression. According to our analysis of database, in combination with previous reports, we come to a conclusion that WWP1 expression is augmented in various cancers. Gene amplification, as well as expression regulation mediated by molecules such as non-coding RNAs, may account for the increased mRNA level of WWP1. Regulation of enzymatic activity is another important facet to upregulate WWP1-mediated ubiquitinations. Based on the published data, we conclude that WWP1 employs interactions between multiple domains to autoinhibit its polyubiquitination activity in a steady state. Association of some substrates can partially release certain autoinhibition-related domains and make WWP1 have a moderate activity of polyubiquitination. Some cancer-related mutations can fully disrupt the inhibitory interactions and make WWP1 hyperactive. High expression level or hyperactivation of WWP1 may abnormally enhance polyubiquitinations of some oncoproteins or tumor suppressors, such as ΔNp63α, PTEN and p27, and ultimately promote cell proliferation, survival, migration and invasion in tumorigenesis. Given the dysregulation and oncogenic functions of WWP1 in some cancer types, it is promising to explore some therapeutic inhibitors to tune down its activity.

Copper metabolism in Saccharomyces cerevisiae: an update.

Copper is an essential element in all forms of life. It acts as a cofactor of some enzymes and is involved in forming proper protein conformations. However, excess copper ions in cells are detrimental as they can generate free radicals or disrupt protein structures. Therefore, all life forms have evolved conserved and exquisite copper metabolic systems to maintain copper homeostasis. The yeast Saccharomyces cerevisiae has been widely used to investigate copper metabolism as it is convenient for this purpose. In this review, we summarize the mechanism of copper metabolism in Saccharomyces cerevisiae according to the latest literature. In brief, bioavailable copper ions are incorporated into yeast cells mainly via the high-affinity transporters Ctr1 and Ctr3. Then, intracellular Cu+ ions are delivered to different organelles or cuproproteins by different chaperones, including Ccs1, Atx1, and Cox17. Excess copper ions bind to glutathione (GSH), metallothioneins, and copper complexes are sequestered into vacuoles to avoid toxicity. Copper-sensing transcription factors Ace1 and Mac1 regulate the expression of genes involved in copper detoxification and uptake/mobilization in response to changes in intracellular copper levels. Though numerous recent breakthroughs in understanding yeast's copper metabolism have been achieved, some issues remain unresolved. Completely elucidating the mechanism of copper metabolism in yeast helps decode the corresponding system in humans and understand how copper-related diseases develop.

Prefoldin subunit MM1 promotes cell migration via facilitating filopodia formation.

c-Myc modulator 1 (MM1), also known as PFDN5, is the fifth subunit of prefoldin. It was previously reported that MM1-based prefoldin promotes folding of actin during assembly of cytoskeleton, which plays key roles in cell migration. However, no evidence supports that MM1 affects cell migration. In the present study, we found that MM1 promotes cell migration in multiple cell lines. Further study revealed that MM1 promotes polymerization of ß-actin into filamentous form and increases both density and length of filopodia. Effects of MM1 on filopodia formation and cell migration depend on its prefoldin activity. Though c-Myc is repressed by MM1, simultaneous knock-down of c-Myc fails to rescue migration inhibition induced by MM1 ablation. Taken together, we here, for the first time, report that prefoldin subunit MM1 is involved in cell migration; this involvement of MM1 in cell migration is due to its prefoldin activity to boost polymerization of ß-actin during filopodia formation. Our findings may be helpful to elucidate the mechanism of cell migration and cancer metastasis.

The molecular mechanisms of copper metabolism and its roles in human diseases.

Copper is an essential element in cells; it can act as either a recipient or a donor of electrons, participating in various reactions. However, an excess of copper ions in cells is detrimental as these copper ions can generate free radicals and increase oxidative stress. In multicellular organisms, copper metabolism involves uptake, distribution, sequestration, and excretion, at both the cellular and systemic levels. Mammalian enterocytes take in bioavailable copper ions from the diet in a Ctr1-dependent manner. After incorporation, cuprous ions are delivered to ATP7A, which pumps Cu+ from enterocytes into the blood. Copper ions arrive at the liver through the portal vein and are incorporated into hepatocytes by Ctr1. Then, Cu+ can be secreted into the bile or the blood via the Atox1/ATP7B/ceruloplasmin route. In the bloodstream, this micronutrient can reach peripheral tissues and is again incorporated by Ctr1. In peripheral tissue cells, cuprous ions are either sequestrated by molecules such as metallothioneins or targeted to utilization pathways by chaperons such as Atox1, Cox17, and CCS. Copper metabolism must be tightly controlled in order to achieve homeostasis and avoid disorders. A hereditary or acquired copper unbalance, including deficiency, overload, or misdistribution, may cause or aggravate certain diseases such as Menkes disease, Wilson disease, neurodegenerative diseases, anemia, metabolic syndrome, cardiovascular diseases, and cancer. A full understanding of copper metabolism and its roles in diseases underlies the identification of novel effective therapies for such diseases.

Recent Advances in MEMS Metasurfaces and Their Applications on Tunable Lens.

The electromagnetic (EM) properties of metasurfaces depend on both structural design and material properties. microelectromechanical systems (MEMS) technology offers an approach for tuning metasurface EM properties by structural reconfiguration. In the past 10 years, vast applications have been demonstrated based on MEMS metasurfaces, which proved to have merits including, large tunability, fast speed, small size, light weight, capability of dense integration, and compatibility of cost-effective fabrication process. Here, recent advances in MEMS metasurface applications are reviewed and categorized based on the tuning mechanisms, operation band and tuning speed. As an example, the pros and cons of MEMS metasurfaces for tunable lens applications are discussed and compared with traditional tunable lens technologies followed by the summary and outlook.

Cytological Immunostaining of HMGA2, LRP1B, and TP63 as Potential Biomarkers for Triaging Human Papillomavirus-Positive Women.

BACKGROUND: Since human papillomavirus (HPV) DNA testing has been promoted as primary screening strategy, the triage method has also evolved from morphological testing to a molecular biomarker detection to improve screening efficiency. In this study, we investigated the performance of three HPV integration hot-spots, HMGA2, LRP1B, and TP63, as potential triage markers in HPV screening tests. MATERIALS AND METHODS: This cross-sectional study was conducted from November 2016 to December 2017 in the First Affiliated Hospital of Sun Yat-sen University. Immunocytochemistry was carried out using residual cervical cell samples from 121 HPV-positive cases (23 normal, 24 cervical intraepithelial neoplasia (CIN) 1, and 74 CIN2+). RESULTS: Of the 121 cases, 77 showed completely paired for the three biomarkers. In these 77 cases, receiver operating characteristic (ROC) analysis of HMGA2 showed the best potential for detecting CIN2+ among HPV+ cases (sensitivity 70%; specificity 91.89%; AUC 0.839). TP63 was second most effective biomarker (AUC 0.838; sensitivity 80%; specificity 81.08%). In contrast, LRP1B had the smallest AUC (0.801) among the three biomarkers but had the highest sensitivity (90%) and specificity (56.76%). To test the triage value of combining the three biomarkers, logistic regression was conducted followed by ROC comparison analysis. Promisingly, the combination of the three biomarkers gave the largest AUC of 0.951 with 92.5% sensitivity and 89.1% specificity (P < .0001 compared to liquid-based cytology test by Z-test). CONCLUSIONS: A combination of HMGA2, LRP1B, and TP63 as potential biomarkers may be useful for screening during triage of HPV-positive patients, particularly for detecting CIN2 + .

Approach the Invasive Potential with Hurthle Cell Tumors of Thyroid.

To observe the expression of P53, CyclinD1, Ki-67, Galectin-3, COX-2, Bcl-2 and approach their contribution on assessing the invasive potential for Hurthle cell tumors. Seventy-three cases of Hurthle cell tumor were collected for immunohistochemistry staining. The patients were followed up with 8 months to 5 years. Tumors were divided into four grades according to invasion and diameter:(1) extremely low risk (27 cases that less than 2 cm and without invasion), (2) low risk (18 cases that within 2-3.9 cm and without invasion), (3) moderate risk (21 cases that achieve 4 cm and without invasion), (4) high risk (7 cases that with invasion of capsule/vessel in spite of the diameter). Immunostaining presented that all 73 cases were positive with Galectin-3, COX-2 and Bcl-2. For each group, P53 positive were 29.6%, 55.6%, 90.5%, 100.0%; CyclinD1 stained with 7.4%,22.2%,52.4%,100.0% and Ki-67 were 0.0%,5.6%,9.5%,28.6%, respectively. The higher risk of tumor, the more cases that positive expressed P53 and CyclinD1. After following up within 49 patients, two of the recurring cases were positive with P53 and CyclinD1 and one of which was also highly expressed Ki-67. Detecting P53, CyclinD1 and Ki-67 might provide reference for invasive potential assessment with Hurthle cell tumors but not Galectin-3, COX-2 and Bcl-2.

Developing a Wireless, High Precision and Processing Speed Pulse Monitoring Headset Using Photoplethysmography.

In this paper, thorough improvement of pulse monitoring and analysis equipment with a headset structure is presented. In order to study the most suitable infrared wavelength for the acquisition of the pulse wave at the earlobe, Monte Carlo simulation was adapted. Both high frequency noise and baseline drift, generated in the signal acquisition process, are considered. To further optimize the system design and improve accuracy, for the sensor's dimensional drift, the corresponding compensation was carried on in the software. This paper introduced nonlinear quantization, especially in terms of very weak pulse signal, in the time domain analysis process. A quick extraction method named table look-up combing with interpolation was utilized to obtain frequency domain information whose processing speed can be increased by about 30 times compared with fast Fourier transformation setting the sampling point as 300. The results demonstrated the sensor's excellent performance in pulse signal acquisition whose maximum residual is less than 0.004 mV. The test on a random sample of 300 people indicates that the system had high correlation with reference, validating the system accuracy is extremely high. Overall, this paper provides a practical pulse monitoring and analysis system with high precision and processing speed that can be widely applied in the field of health management or medical measurement.

Amplification and overexpression of TP63 and MYC as biomarkers for transition of cervical intraepithelial neoplasia to cervical cancer.

OBJECTIVE: Biopsy confirmed that cervical intraepithelial neoplasia (CIN) may naturally regress or progress. Currently, the risk assessment for CIN progression to cervical cancer is still not satisfactory in clinical practice. We investigated copy number and protein expression of TP63 and MYC and explored the possibility to use them as progression biomarkers. METHODS: Copy numbers of TP63 and MYC, as well as human papilloma virus (HPV) integration status, were determined by fluorescence in situ hybridization in 39 patients with CIN and 66 patients with cervical cancer. Corresponding protein expressions were analyzed by immunohistochemistry. Receiver operating characteristic curves were used to measure the diagnostic test performance for the detection of cervical cancer from CIN. Sensitivity and specificity values of biomarkers were calculated. RESULTS: The average copy number and expression of TP63 and MYC, as well as the HPV integration rate, increased in the progression of CIN to cervical cancer. Receiver operating characteristic analysis for detection of cervical cancer resulted in area under the curve (AUC) values of TP63 copy number (AUC, 0.96; 95% confidence interval [CI], 0.91-1.00), MYC copy number (AUC, 0.92; 95% CI, 0.85-0.96), TP63 expression (AUC, 0.73; 95% CI, 0.61-0.85), and HPV-16 integration (AUC, 0.73; 95% CI, 0.60-0.85). MYC expression was not able to statistically distinguish cancer from CIN (P = 0.393). The combinations increased the specificity slightly but not sensitivity. Among them, TP63 amplification showed the best diagnostic performance. CONCLUSIONS: Amplification and overexpression of TP63 and MYC, and HPV integration rate, are associated with the transition of CIN to cervical cancer. Future studies on these biomarkers will help to assess the risk of CIN progression.