Pengaruh Terpaan Akun Instagram @Pendakiindonesia Terhadap Minat Traveling Pada Anggota Komunitas Petualang Kota Solo

Paparan media menjangkau seseorang melalui pesan yang muncul dari tayangan media. Selain terpaan pesan melalui media sosial, ada juga faktor yang berhubungan dengan ketertarikan seseorang yaitu kelompok referensi. Akun @pendakiindonesia menjadi kelompok refrensi sekaligus sumber informasi yang dicari wisatawan untuk menikmati keindahan gambar dan menimbulkan ketertarikan untuk berkunjung ke sebuah destinasi wisata. Metode penelitian adalah kuantitatif. Populasi penelitian ini adalah komunitas Rono Rene Adventure Surakarta. Seluruh populasi diambil 100 orang sebagai sampel. Teknik pengambilan sampel sensus adalah memilih seluruh populasi untuk dijadikan sampel. Pengumpulan data dalam penelitian ini menggunakan kuesioner dan wawancara. Sebelum digunakan untuk penelitian, kuesioner perlu diuji dengan pengujian validitas dan uji reliabilitas. Analisis data dalam penelitian ini menggunakan metode Regresi Linier sederhana. Setelah dilakukan analisis regresi sederhana selanjutnya akan dilakukan uji t dan uji F serta koefisien determinasi (R2). Hasil penelitian diketahui bahwa terpaan media Instagram @pendakiindonesia mampu mempengaruhi folowers dimana pengaruhnya positif dan signifikan. Besarnya pengaruh ekspos media Instagram @pendakiindonesia yang mampu mempengaruhi minat travelling sebesar 15,3%. Pengaruh yang dihasilkan dari paparan instagram @pendakiindonesia terhadap minat traveling komunitas Rono Rene Adventure Surakarta. Proses pengolahan rangsangan (organisme) yang terjadi pada anggota komunitas Rono Rene Adventure Surakarta menentukan bentuk respon berupa minat travelling

Preclinical evaluation of two 68Ga-siderophores as potential radiopharmaceuticals for Aspergillus fumigatus infection imaging

PURPOSE: Invasive pulmonary aspergillosis is mainly caused by Aspergillus fumigatus, and is one of the major causes of morbidity and mortality in immunocompromised patients. The mortality associated with invasive pulmonary aspergillosis remains high, mainly due to the difficulties and limitations in diagnosis. We have shown that siderophores can be labelled with (68)Ga and can be used for PET imaging of A. fumigatus infection in rats. Here we report on the further evaluation of the most promising (68)Ga-siderophore candidates, triacetylfusarinine (TAFC) and ferrioxamine E (FOXE). METHODS: Siderophores were labelled with (68)Ga using acetate buffer. Log P, protein binding and stability values were determined. Uptake by A. fumigatus was studied in vitro in cultures with high and low iron loads. In vivo biodistribution was determined in normal mice and an infection model was established using neutropenic rats inoculated with A. fumigatus. Static and dynamic muPET imaging was performed and correlated with CT images, and lung infection was evaluated ex vivo. RESULTS: (68)Ga-siderophores were labelled with high radiochemical purity and specific activity. (68)Ga-TAFC and (68)Ga-FOXE showed high uptake by A. fumigatus in iron-deficient cultures. In normal mice, (68)Ga-TAFC and (68)Ga-FOXE showed rapid renal excretion with high metabolic stability. In the rat infection model focal lung uptake was detected by muPET with both compounds and increased with severity of the infection, correlating with abnormal CT images. CONCLUSION: (68)Ga-TAFC and (68)Ga-FOXE displayed excellent in vitro stability and high uptake by A. fumigatus. Both compounds showed excellent pharmacokinetics, highly selective accumulation in infected lung tissue and good correlation with severity of disease in a rat infection model, which makes them promising agents for A. fumigatus infection imaging

Redox Modulation at Work: Natural Phytoprotective Polysulfanes From Alliums Based on Redox-Active Sulfur

Purpose of review: This article provides a brief overview of natural phytoprotective products of allium with a special focus on the therapeutic potential of diallyl polysulfanes from garlic, their molecular targets and their fate in the living organisms. A comprehensive overview of antimicrobial and anticancer properties of published literature is presented for the reader to understand the effective concentrations of polysulfanes and their sensitivity towards different human pathogenic microbes, fungi, and cancer cell lines. Recent findings: The article finds polysulfanes potentials as new generation novel antibiotics and chemo preventive agent. The effective dose rates of polysulfanes for antimicrobial properties are in the range of 0.5–40 mg/L and for anticancer 20–100 μM. The molecular targets for these redox modulators are mainly cellular thiols as well as inhibition and/or activation of certain cellular proteins in cancer cell lines. Summary: Antimicrobial and anticancer activities of polysulfanes published in the literature indicate that with further development, they could be promising candidates for cancer prevention due to their selectivity towards abnormal cells

Scintillation light detection in the 6-m drift-length ProtoDUNE Dual Phase liquid argon TPC

DUNE is a dual-site experiment for long-baseline neutrino oscillation studies, neutrino astrophysics and nucleon decay searches. ProtoDUNE Dual Phase (DP) is a 6  ×  6  ×  6 m 3 liquid argon time-projection-chamber (LArTPC) that recorded cosmic-muon data at the CERN Neutrino Platform in 2019-2020 as a prototype of the DUNE Far Detector. Charged particles propagating through the LArTPC produce ionization and scintillation light. The scintillation light signal in these detectors can provide the trigger for non-beam events. In addition, it adds precise timing capabilities and improves the calorimetry measurements. In ProtoDUNE-DP, scintillation and electroluminescence light produced by cosmic muons in the LArTPC is collected by photomultiplier tubes placed up to 7 m away from the ionizing track. In this paper, the ProtoDUNE-DP photon detection system performance is evaluated with a particular focus on the different wavelength shifters, such as PEN and TPB, and the use of Xe-doped LAr, considering its future use in giant LArTPCs. The scintillation light production and propagation processes are analyzed and a comparison of simulation to data is performed, improving understanding of the liquid argon properties

Genomic traits of Klebsiella oxytoca DSM 29614, an uncommon metal-nanoparticle producer strain isolated from acid mine drainages

Abstract Background: Klebsiella oxytoca DSM 29614 - isolated from acid mine drainages - grows anaerobically using Fe(III)- citrate as sole carbon and energy source, unlike other enterobacteria and K. oxytoca clinical isolates. The DSM 29614 strain is multi metal resistant and produces metal nanoparticles that are embedded in its very peculiar capsular exopolysaccharide. These metal nanoparticles were effective as antimicrobial and anticancer compounds, chemical catalysts and nano-fertilizers. Results: The DSM 29614 strain genome was sequenced and analysed by a combination of in silico procedures. Comparative genomics, performed between 85 K. oxytoca representatives and K. oxytoca DSM 29614, revealed that this bacterial group has an open pangenome, characterized by a very small core genome (1009 genes, about 2%), a high fraction of unique (43,808 genes, about 87%) and accessory genes (5559 genes, about 11%). Proteins belonging to COG categories “Carbohydrate transport and metabolism” (G), “Amino acid transport and metabolism” (E), “Coenzyme transport and metabolism” (H), “Inorganic ion transport and metabolism” (P), and “membrane biogenesis-related proteins” (M) are particularly abundant in the predicted proteome of DSM 29614 strain. The results of a protein functional enrichment analysis - based on a previous proteomic analysis – revealed metabolic optimization during Fe(III)- citrate anaerobic utilization. In this growth condition, the observed high levels of Fe(II) may be due to different flavin metal reductases and siderophores as inferred form genome analysis. The presence of genes responsible for the synthesis of exopolysaccharide and for the tolerance to heavy metals was highlighted too. The inferred genomic insights were confirmed by a set of phenotypic tests showing specific metabolic capability in terms of i) Fe2+ and exopolysaccharide production and ii) phosphatase activity involved in precipitation of metal ion-phosphate salts. Conclusion: The K. oxytoca DSM 29614 unique capabilities of using Fe(III)-citrate as sole carbon and energy source in anaerobiosis and tolerating diverse metals coincides with the presence at the genomic level of specific genes that can support i) energy metabolism optimization, ii) cell protection by the biosynthesis of a peculiar exopolysaccharide armour entrapping metal ions and iii) general and metal-specific detoxifying activities by different proteins and metabolites

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between data and simulation

Separation of track- and shower-like energy deposits in ProtoDUNE-SP using a convolutional neural network

Liquid argon time projection chamber detector technology provides high spatial and calorimetric resolutions on the charged particles traversing liquid argon. As a result, the technology has been used in a number of recent neutrino experiments, and is the technology of choice for the Deep Underground Neutrino Experiment (DUNE). In order to perform high precision measurements of neutrinos in the detector, final state particles need to be effectively identified, and their energy accurately reconstructed. This article proposes an algorithm based on a convolutional neural network to perform the classification of energy deposits and reconstructed particles as track-like or arising from electromagnetic cascades. Results from testing the algorithm on experimental data from ProtoDUNE-SP, a prototype of the DUNE far detector, are presented. The network identifies track- and shower-like particles, as well as Michel electrons, with high efficiency. The performance of the algorithm is consistent between experimental data and simulation