Optical Fingerprints of Upconversion Nanoparticles for Super-Capacity Multiplexing

University of Technology Sydney. Faculty of Science.This thesis includes six chapters. Chapter 1 outlines the background knowledge and motivation relevant to the development of luminescence materials for optical multiplexing. The materials include fluorescence dyes, quantum dots, metal particles and upconversion nanoparticles (UCNPs). This thesis introduces different optical dimensions of UCNPs. The challenges associated with luminescence materials for multiplexing are approached. These sections detail the motivation for and the specific aims of the current study—that is, to tune the energy-transfer process in the core-shell UCNPs and to achieve the optical multiplexing of UCNPs in the spectral and lifetime orthogonal dimensions. Chapter 2 provides detailed information on the materials, instruments and equipment, preparation and characterization methods. Chapter 3 is the first research chapter, and it investigates the peak tuning of the excited state population of powder samples in Nd-Yb-Tm core-shell UCNPs. For the take-off of upconversion emissions, the duration can be extended from 100 μs to 900 μs after the 808 nm excitation is switched off. This strategy creates a set of time-resolved emission profiles over a large dynamic range, where they can be tuned from either the time of rising or decay. Chapter 4 synthesizes two groups of UCNPs: Yb³⁺-Nd³⁺-Er³⁺ and Yb³⁺-Tm³⁺ core-shell UCNPs. This chapter outlines the systematic analysis (via the confocal microscope system) of the emission intensity/spectra and lifetimes of single UCNPs. Strategies to control the energy migration process and to arbitrarily tune the rising and decay times and the plateau moment are presented, where it is suggested a unique time-domain optical fingerprint can be assigned to each type of nanoparticles. Chapter 5 outlines the finding that the nanoparticles show a unique lifetime signature under wide-field systems upon 976 nm (Yb³⁺-Tm³⁺ doped UCNPs) and 808 nm (Yb³⁺-Nd³⁺-Er³⁺ doped UCNPs) excitation. To achieve high-throughput multiplexing, the lifetime profiles can be detected under a wide-field microscope system. A novel method is also introduced here (i.e., deep learning) to decode the lifetime fingerprints of 14 batches of UCNPs. Through deep learning, the large amount of optical data from different batches of UCNPs allows the classification of each single UCNPs for the untapped opportunity to decode these nanoscale lifetime barcodes. The classification capability associated with deep learning allows all 14 kinds of UCNPs to achieve accuracies of over 90%. Finally, the research results of this thesis are summarised in Chapter 6. Potential future developments and prospects regarding the multidimensional optical properties of UCNPs are discussed

Disorder-induced phase transitions in double Weyl semimetals

The double Weyl semimetal (DWSM) is a newly proposed topological material that hosts Weyl points with chiral charge n=2. The disorder effect in DWSM is investigated by adopting the tight-binding Hamiltonian. Using the transfer matrix method and the noncommutative Kubo formula, we numerically calculate the localization length and the Hall conductivity in the presence of the on-site nonmagnetic disorder or orbital (spin-flip) disorders, and give the corresponding global phase diagrams. For the on-site nonmagnetic disorder, the system undergoes the DWSM-3D quantum anomalous hall (3D QAH) and normal insulator (NI)-DWSM phase transitions, and evolves into the diffusive metal (DM) phase before being localized by strong disorders, which is consistent with the Weyl semimetal. For \sigma_x orbital disorder, we find that increasing disorder can generate a pair of Weyl nodes at the boundary of the Brillouin zone and induce a 3D QAH-DWSM phase transition. Then we investigate the combined effect of orbital disorders for both disordered 3D QAH phase and DWSM phase. The disorder-induced transitions can be well understood in terms of an effective medium theory based on self-consistent Born approximation.Comment: 8 pages, 9 figure

A nomogram based on ultrasonographic features and clinical indicators for differentiating mass-forming intrahepatic cholangiocarcinoma and liver metastatic colorectal adenocarcinoma

ObjectiveThis study aimed to develop and validate a nomogram based on ultrasonographic features and clinical indicators to differentiate mass-forming intrahepatic cholangiocarcinoma (MF-ICC) from hepatic metastatic colorectal adenocarcinoma.Materials and methodsA total of 343 patients with pathologically confirmed MF-ICC or metastatic colorectal adenocarcinoma were enrolled between October 2018 and July 2022. Patients were randomly assigned to training and validation sets at a ratio of 7:3. Preoperative ultrasound features and clinical indicators were retrieved. Univariate logistic regression analysis was employed to select relevant features. Multivariate logistic regression analysis was used to establish a predictive model, which was presented as a nomogram in training sets. The model’s performance was assessed in terms of discrimination, calibration, and clinical usefulness.ResultsThe study included 169 patients with MF-ICC and 174 with liver metastatic colorectal adenocarcinoma, assigned to training (n=238) and validation (n=105) cohorts. The nomogram incorporated ultrasound features (tumor size, lesion number, echogenicity, tumor necrosis, and rim arterial phase hyperenhancement) and clinical information (serum levels of CEA, CA19-9, CA125). The nomogram demonstrated promising performance in differentiating these two entities in both training and validation sets, with an AUC value of 0.937 (95%CI: 0.907,0.969) and 0.916 (95%CI: 0.863,0.968), respectively. The Hosmer–Lemeshow test and calibration curves confirmed good consistency between predictions and observations. Additionally, decision curve analysis confirmed the nomogram’s high clinical practicability.ConclusionThe nomogram based on ultrasound features and clinical indicators demonstrated good discrimination performance in differentiating MF-ICC from metastatic colorectal adenocarcinoma, which may enhance clinical decision-making process in managing these challenging diagnostic scenarios

The obesity paradox in intracerebral hemorrhage: a systematic review and meta-analysis

BackgroundIntracerebral hemorrhage (ICH) has a mortality rate which can reach 30–40%. Compared with other diseases, obesity is often associated with lower mortality; this is referred to as the ‘obesity paradox’. Herein, we aimed to summarize the studies of the relations between obesity and mortality after ICH.MethodFor this systematic review and meta-analysis (PROSPERO registry CRD42023426835), we conducted searches for relevant articles in both PubMed and Embase. Non-English language literature, irrelevant literature, and non-human trials were excluded. All included publications were then qualitatively described and summarized. Articles for which quantitative analyses were possible were evaluated using Cochrane’s Review Manager.ResultsTen studies were included. Qualitative analysis revealed that each of the 10 studies showed varying degrees of a protective effect of obesity, which was statistically significant in 8 of them. Six studies were included in the quantitative meta-analysis, which showed that obesity was significantly associated with lower short-term (0.69 [0.67, 0.73], p<0.00001) and long-term (0.62 [0.53, 0.73], p<0.00001) mortality. (Data identified as (OR [95%CI], p)).ConclusionObesity is likely associated with lower post-ICH mortality, reflecting the obesity paradox in this disease. These findings support the need for large-scale trials using standardized obesity classification methods.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023426835, identifier CRD42023426835

Spontaneous Browning of White Adipose Tissue Improves Angiogenesis and Reduces Macrophage Infiltration After Fat Grafting in Mice

Background: Fat grafting is a frequently used technique; however, its survival/ regeneration mechanism is not fully understood. The browning of white adipocytes, a process initiated in response to external stimuli, is the conversion of white to beige adipocytes. The physiologic significance of the browning of adipocytes following transplantation is unclear.Methods: C57BL/6 mice received 150 mg grafts of inguinal adipose tissue, and then the transplanted fat was harvested and analyzed at different time points to assess the browning process. To verify the role of browning of adipocytes in fat grafting, the recipient mice were allocated to three groups, which were administered CL316243 or SR59230A to stimulate or suppress browning, respectively, or a control group after transplantation.Results: Browning of the grafts was present in the center of each as early as 7 days post-transplantation. The number of beige cells peaked at day 14 and then decreased gradually until they were almost absent at day 90. The activation of browning resulted in superior angiogenesis, higher expression of the pro-angiogenic molecules vascular endothelial growth factor A (VEGF-A) and fibroblast growth factor 21 (FGF21), fewer macrophages, and ultimately better graft survival (Upregulation, 59.17% ± 6.64% vs. Control, 40.33% ± 4.03%, *p < 0.05), whereas the inhibition of browning led to poor angiogenesis, lower expression of VEGF-A, increased inflammatory macrophages, and poor transplant retention at week 10 (Downregulation, 20.67% ± 3.69% vs. Control, 40.33% ± 4.03%, *p < 0.05).Conclusion: The browning of WAT following transplantation improves the survival of fat grafts by the promotion of angiogenesis and reducing macrophage

Three-Dimensional Human Pose Estimation from Sparse IMUs through Temporal Encoder and Regression Decoder

Three-dimensional (3D) pose estimation has been widely used in many three-dimensional human motion analysis applications, where inertia-based path estimation is gradually being adopted. Systems based on commercial inertial measurement units (IMUs) usually rely on dense and complex wearable sensors and time-consuming calibration, causing intrusions to the subject and hindering free body movement. The sparse IMUs-based method has drawn research attention recently. Existing sparse IMUs-based three-dimensional pose estimation methods use neural networks to obtain human poses from temporal feature information. However, these methods still suffer from issues, such as body shaking, body tilt, and movement ambiguity. This paper presents an approach to improve three-dimensional human pose estimation by fusing temporal and spatial features. Based on a multistage encoder–decoder network, a temporal convolutional encoder and human kinematics regression decoder were designed. The final three-dimensional pose was predicted from the temporal feature information and human kinematic feature information. Extensive experiments were conducted on two benchmark datasets for three-dimensional human pose estimation. Compared to state-of-the-art methods, the mean per joint position error was decreased by 13.6% and 19.4% on the total capture and DIP-IMU datasets, respectively. The quantitative comparison demonstrates that the proposed temporal information and human kinematic topology can improve pose accuracy

TomoNet: A streamlined cryogenic electron tomography software pipeline with automatic particle picking on flexible lattices

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near-atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and three-dimensional (3D) classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in 1D, 2D, or 3D arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other using deep learning. TomoNet's hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNet's potential for broad applications to various cryoET projects targeting high-resolution in situ structures

Hierarchical organization and assembly of the archaeal cell sheath from an amyloid-like protein.

Certain archaeal cells possess external proteinaceous sheath, whose structure and organization are both unknown. By cellular cryogenic electron tomography (cryoET), here we have determined sheath organization of the prototypical archaeon, Methanospirillum hungatei. Fitting of Alphafold-predicted model of the sheath protein (SH) monomer into the 7.9 Å-resolution structure reveals that the sheath cylinder consists of axially stacked β-hoops, each of which is comprised of two to six 400 nm-diameter rings of β-strand arches (β-rings). With both similarities to and differences from amyloid cross-β fibril architecture, each β-ring contains two giant β-sheets contributed by ~ 450 SH monomers that entirely encircle the outer circumference of the cell. Tomograms of immature cells suggest models of sheath biogenesis: oligomerization of SH monomers into β-ring precursors after their membrane-proximal cytoplasmic synthesis, followed by translocation through the unplugged end of a dividing cell, and insertion of nascent β-hoops into the immature sheath cylinder at the junction of two daughter cells

Small Extracellular Vesicle-Derived Circular RNA hsa_circ_0007386 as a Biomarker for the Diagnosis of Pleural Mesothelioma

Pleural mesothelioma (PM) is a highly aggressive tumor that is caused by asbestos exposure and lacks effective therapeutic regimens. Current procedures for PM diagnosis are invasive and can take a long time to reach a definitive result. Small extracellular vesicles (sEVs) have been identified as important communicators between tumor cells and their microenvironment via their cargo including circular RNAs (circRNAs). CircRNAs are thermodynamically stable, highly conserved, and have been found to be dysregulated in cancer. This study aimed to identify potential biomarkers for PM diagnosis by investigating the expression of specific circRNA gene pattern (hsa_circ_0007386) in cells and sEVs using digital polymerase chain reaction (dPCR). For this reason, 5 PM, 14 non-PM, and one normal mesothelial cell line were cultured. The sEV was isolated from the cells using the gold standard ultracentrifuge method. The RNA was extracted from both cells and sEVs, cDNA was synthesized, and dPCR was run. Results showed that hsa_circ_0007386 was significantly overexpressed in PM cell lines and sEVs compared to non-PM and normal mesothelial cell lines (p < 0.0001). The upregulation of hsa_circ_0007386 in PM highlights its potential as a diagnostic biomarker. This study underscores the importance and potential of circRNAs and sEVs as cancer diagnostic tools