The Effects of Enriched Environment on Paraventricular Hypothalamic Brain-derived Neurotrophic Factor Expression

The regulation of energy homeostasis involves a balance between food intake and energy expenditure. The hypothalamus is a crucial regulator for energy balance and consists of several discrete nuclei, including the arcuate (ARC), ventromedial (VMH), dorsomedial (DMH), and paraventricular (PVH) hypothalamus. Brain-derived neurotrophic factor (BDNF) expressed in hypothalamic nuclei is significant in regulating energy homeostasis. Our studies demonstrated that an enriched environment (EE), a complex housing with social and physical stimulation, upregulated BDNF expression in the ARC and VMH/DMH leading to an anti-obesity and anti-tumor phenotype. Moreover, the EE anti-obesity phenotype can be mimicked by overexpression of ARC and VMH/DMH Bdnf. While studies have shown diet- and genetic- induced obesity can be reversed by transferring the Bdnf gene to ARC and VMH/DMH, the roles of other nuclei in mediating the EE phenotype is not known. Research has shown that PVH BDNF has a strong and lasting impact on suppressing food intake and increasing energy expenditure, and the deletion of Bdnf in the PVH leads to hyperphagia and severe obesity. Thus, we hypothesized PVH Bdnf is upregulated by EE. Our results did not demonstrate significant upregulation of Bdnf expression in PVH or ARC after EE exposure. However, we observed a markedly increase of Vgf (non-acronymic) expression in PVH of EE mice, suggesting Vgf can be our next target gene of interest to study EE’s anti-obesity effects.No embargoAcademic Major: Neuroscienc

An Analysis of the Energy Consumption and Environmental Impact on the Emissions of Carbon Dioxide and Methane of the Offshore Natural Gas Liquefaction Process in Facilities with Utilizing Dual Mixed Refrigerant (DMR) Process Technology

The objective of this thesis is to evaluate the effects of the dual mixed refrigerant (DMR) process on energy consumption and greenhouse gas (GHG) emissions in terms of carbon dioxide (CO2) and methane (CH4) in an offshore liquid natural gas (LNG) facility based on the reliable data from the Gulf of Mexico in the United States. After comparing energy consumption and GHG (carbon dioxide and methane) emissions for a number of liquefaction technologies: including mixed fluid cascade (MFC), dual mixed refrigerant (DMR), single mixed refrigerant (SMR), mixed refrigerant with propane precooling (C3MR), and the Conoco Phillips Optimized Cascade processes, the evaluation showed that dual mixed refrigerant (DMR) process features both high energy consumption and high GHG (carbon dioxide and methane) emission in regards to the liquefaction process. With this result in mind, more technical enhancement is needed to update the DMR process to decrease energy consumption, and more research is needed to support the reduction of negative environmental impacts in the future. The results of this thesis will benefit research on the liquefaction process regarding energy consumption and environmental impacts

Regression-based heterogeneity analysis to identify overlapping subgroup structure in high-dimensional data

Heterogeneity is a hallmark of complex diseases. Regression-based heterogeneity analysis, which is directly concerned with outcome-feature relationships, has led to a deeper understanding of disease biology. Such an analysis identifies the underlying subgroup structure and estimates the subgroup-specific regression coefficients. However, most of the existing regression-based heterogeneity analyses can only address disjoint subgroups; that is, each sample is assigned to only one subgroup. In reality, some samples have multiple labels, for example, many genes have several biological functions, and some cells of pure cell types transition into other types over time, which suggest that their outcome-feature relationships (regression coefficients) can be a mixture of relationships in more than one subgroups, and as a result, the disjoint subgrouping results can be unsatisfactory. To this end, we develop a novel approach to regression-based heterogeneity analysis, which takes into account possible overlaps between subgroups and high data dimensions. A subgroup membership vector is introduced for each sample, which is combined with a loss function. Considering the lack of information arising from small sample sizes, an $l_2$ norm penalty is developed for each membership vector to encourage similarity in its elements. A sparse penalization is also applied for regularized estimation and feature selection. Extensive simulations demonstrate its superiority over direct competitors. The analysis of Cancer Cell Line Encyclopedia data and lung cancer data from The Cancer Genome Atlas shows that the proposed approach can identify an overlapping subgroup structure with favorable performance in prediction and stability.Comment: 33 pages, 16 figure

Prompt Learning with Optimal Transport for Vision-Language Models

With the increasing attention to large vision-language models such as CLIP, there has been a significant amount of effort dedicated to building efficient prompts. Unlike conventional methods of only learning one single prompt, we propose to learn multiple comprehensive prompts to describe diverse characteristics of categories such as intrinsic attributes or extrinsic contexts. However, directly matching each prompt to the same visual feature is problematic, as it pushes the prompts to converge to one point. To solve this problem, we propose to apply optimal transport to match the vision and text modalities. Specifically, we first model images and the categories with visual and textual feature sets. Then, we apply a two-stage optimization strategy to learn the prompts. In the inner loop, we optimize the optimal transport distance to align visual features and prompts by the Sinkhorn algorithm, while in the outer loop, we learn the prompts by this distance from the supervised data. Extensive experiments are conducted on the few-shot recognition task and the improvement demonstrates the superiority of our method

Clinical study on high-risk factors for contralateral lymph node metastasis in unilateral papillary thyroid carcinoma

Background and purpose: The occurrence of lymph node metastasis in papillary thyroid cancer (PTC) can have adverse effects on the prognosis of patients. This study aimed to investigate risk factors related to the occurrence of contralateral central lymph node metastases (CLNM) and contralateral lateral lymph node metastases (LLNM) when imaging suspected ipsilateral LLNM in unilateral PTC. Methods: We retrospectively analyzed the clinical data of 526 patients who received surgical treatment in the same treatment group of Jiangsu Cancer Hospital Head and Neck Surgery Department from January 2011 to December 2021. They were initially treated with total thyroidectomy and bilateral central lymph node dissection (CLND) ± lateral lymph node dissection, and their postoperative pathology was uni-PTC. This study analyzed the relevant high-risk factors of contralateral lymph node metastasis. Results: Among the 526 patients, 295 had CLNM, including 272 ipsilateral CLNM, 129 contralateral CLNM and 106 of both sides CLNM; 165 patients had LLNM including 129 ipsilateral LLNM, 18 contralateral LLNM, and 18 of both ipsilateral and contralateral LLNM. Contralateral CLNM occurred in 65 (17.8%) of 365 patients who underwent preventive CLND, and contralateral CLNM was found in 68 (42.2%) of 161 patients with therapeutic CLND. Univariate and multivariate regression analyses showed that contralateral CLNM was associated with maximum diameter of tumor ≥2 cm, multiple foci, no Hashimoto's thyroiditis, tumor invasion, number of CLNM≥6 and age <55 years (P<0.05). Maximum diameter of tumor ≥2 cm was related to contralateral LLNM (P<0.05), while lymph extracapsular extension and lymph node metastasis at tumor side were independent risk factors for contralateral CLNM and contralateral LLNM (P<0.05). Follow-up showed that 5-year overall survival (OS) rate was 97.9% and 5-year disease-free survival (DFS) rate was 97.5%. Conclusion: Contralateral CLNM is more likely to occur in patients with maximum diameter of tumor ≥2 cm, multiple foci, no Hashimoto's thyroiditis, number of CLNM ≥6, age <55 years, tumor and lymph extracapsular extension and lymph node metastasis at the cancer side. In clinical practice, bilateral CLND should be considered for patients with high-risk factors to reduce the residual recurrence of the tumor. Since metastatic rate of contralateral LLNM is relatively low, preventive contralateral lateral lymph node dissection should not be performed routinely when there are no high-risk factors mentioned above

Solid Electrolyte Interphase Formation in Tellurium Iodide Perovskites during Electrochemistry and Photoelectrochemistry

Halide perovskites are promising photoelectrocatalytic materials. Their further development requires understanding of surface processes during electrochemistry. Thin films of tellurium-based vacancy-ordered perovskites with formula A2TeI6, A = Cs, methylammonium (MA), were deposited onto transparent conducting substrates using aerosol-assisted chemical vapor deposition. Thin film stability as electrodes and photoelectrodes was tested in dichloromethane containing tetrabutylammonium PF6 (TBAPF6). Using photoemission spectroscopy, we show that the formation of a solid electrolyte interphase on the surface of the Cs2TeI6, consisting of CsPF6, enhances the stability of the electrode and allows extended chopped-light chronoamperometry measurements at up to 1.1 V with a photocurrent density of 16 μA/cm2. In contrast, (CH3NH3)2TeI6 does not form a passivating layer and rapidly degrades upon identical electrochemical treatment. This demonstrates the importance of surface chemistry in halide perovskite electrochemistry and photoelectrocatalysis

Chromosomal DNA deletion confers phage resistance to Pseudomonas aeruginosa.

Bacteria develop a broad range of phage resistance mechanisms, such as prevention of phage adsorption and CRISPR/Cas system, to survive phage predation. In this study, Pseudomonas aeruginosa PA1 strain was infected with lytic phage PaP1, and phage-resistant mutants were selected. A high percentage (~30%) of these mutants displayed red pigmentation phenotype (Red mutant). Through comparative genomic analysis, one Red mutant PA1r was found to have a 219.6 kb genomic fragment deletion, which contains two key genes hmgA and galU related to the observed phenotypes. Deletion of hmgA resulted in the accumulation of a red compound homogentisic acid; while A galU mutant is devoid of O-antigen, which is required for phage adsorption. Intriguingly, while the loss of galU conferred phage resistance, it significantly attenuated PA1r in a mouse infection experiment. Our study revealed a novel phage resistance mechanism via chromosomal DNA deletion in P. aeruginosa

Ambient PM Toxicity is Correlated with Expression Levels of Specific MicroRNAs

Uncertainties regarding optimized air pollution control remain as the underlying mechanisms of city-specific ambient particulate matter (PM)-induced health effects are unknown. Here, water-soluble extracts of PMs collected from four global cities via automobile air-conditioning filters were consecutively injected three times by an amount of 1, 2, and 2 mg into the blood circulation of Wistar rats after filtration by a 0.45 μm pore size membrane. Acute health effects, such as immune and inflammatory responses and hemorrhage in alveoli, were observed right after the PM extraction injection. Significant differences between cities in biomarker tumor necrosis factor-α (TNF-α) and monocyte chemoattractant protein-1 (MCP-1) levels were detected following the second and third PM injections. Rats’ inflammatory responses varied substantially with the injections of city-specific PMs. Repeated PM extract exposure rendered the rats more vulnerable to subsequent challenges, and downregulation of certain microRNAs was observed in rats. Among the studied miRNAs, miR-125b, and miR-21 were most sensitive to the PM exposure, exhibiting a negative dose–response-type relationship with a source-specific PM (oxidative potential) toxicity (r² = 0.63 and 0.57; p-values < 0.05). The results indicated that city-specific PMs could induce different health effects by selectively regulating different miRNAs, and that certain microRNAs, e.g., miR-125b and miR-21, may be externally mediated to neutralize PM-related health damages

Ambient PM Toxicity is Correlated with Expression Levels of Specific MicroRNAs

Uncertainties regarding optimized air pollution control remain as the underlying mechanisms of city-specific ambient particulate matter (PM)-induced health effects are unknown. Here, water-soluble extracts of PMs collected from four global cities via automobile air-conditioning filters were consecutively injected three times by an amount of 1, 2, and 2 mg into the blood circulation of Wistar rats after filtration by a 0.45 μm pore size membrane. Acute health effects, such as immune and inflammatory responses and hemorrhage in alveoli, were observed right after the PM extraction injection. Significant differences between cities in biomarker tumor necrosis factor-α (TNF-α) and monocyte chemoattractant protein-1 (MCP-1) levels were detected following the second and third PM injections. Rats’ inflammatory responses varied substantially with the injections of city-specific PMs. Repeated PM extract exposure rendered the rats more vulnerable to subsequent challenges, and downregulation of certain microRNAs was observed in rats. Among the studied miRNAs, miR-125b, and miR-21 were most sensitive to the PM exposure, exhibiting a negative dose–response-type relationship with a source-specific PM (oxidative potential) toxicity (r² = 0.63 and 0.57; p-values < 0.05). The results indicated that city-specific PMs could induce different health effects by selectively regulating different miRNAs, and that certain microRNAs, e.g., miR-125b and miR-21, may be externally mediated to neutralize PM-related health damages