Transportation Barriers to Healthcare in Adults 65+ in the Greater Burlington Area

Introduction. Missed appointments often lead to poorer health care outcomes for patients and pose a major economic burden on medical centers. Transportation is an obstacle to accessing medical care for elderly patients in Vermont and results in delayed medical appointments. Methods. We surveyed senior citizens in Chittenden county to determine both the type of transportation barriers and medical care missed due to the lack of transpor- tation. An original survey assessing the impact of transportation to health care was distributed in person and through an online platform. Participants were asked to identify the following in the past year: how often transportation was an issue for healthcare, specific barriers to transportation, and which specific health care appointments were missed due to lack of transportation. Ninety-six surveys out of a total of 251 collected were included in the analysis. Respondents were grouped into either having high transportation barriers, n=43, (always, often, sometimes had issues in the past year), or low transportation barriers, n=53, (rarely had issues). Results. The high barriers group reported more missed appointments, with eye appointments being the most frequent, and depended more on other modes of trans- portation. The low barriers group was able to drive themselves to their appointments more often. Conclusion. The results suggest a trend between barriers to transportation and a lack of access to healthcare appointments. Although more than half of the survey respondents indicated that they do not currently experience transportation barriers, many expressed concern about the transportation difficulties they could encounter in the future.https://scholarworks.uvm.edu/comphp_gallery/1263/thumbnail.jp

Risk-averse stochastic dynamic power dispatch based on deep reinforcement learning with risk-oriented Graph-Gan sampling

The increasing penetration of renewable energy sources (RES) brings volatile stochasticity, which significantly challenge the optimal dispatch of power systems. This paper aims at developing a cost-effective and robust policy for stochastic dynamic optimization of power systems, which improves the economy as well as avoiding the risk of high costs in some critical scenarios with small probability. However, it is hard for existing risk-neutral methods to incorporate risk measure since most samples are normal. For this regard, a novel risk-averse policy learning approach based on deep reinforcement learning with risk-oriented sampling is proposed. Firstly, a generative adversarial network (GAN) with graph convolutional neural network (GCN) is proposed to learn from historical data and achieve risk-oriented sampling. Specifically, system state is modelled as graph data and GCN is employed to capture the underlying correlation of the uncertainty corresponding to the system topology. Risk knowledge is the embedded to encourage more critical scenarios are sampled while aligning with historical data distributions. Secondly, a modified deep reinforcement learning (DRL) with risk-measure under soft actor critic framework is proposed to learn the optimal dispatch policy from sampling data. Compared with the traditional deep reinforcement learning which is risk-neutral, the proposed method is more robust and adaptable to uncertainties. Comparative simulations verify the effectiveness of the proposed method

Effects of novel coronavirus Omicron variant infection on pregnancy outcomes: a retrospective cohort study from Guangzhou

ObjectiveSince 2022, Omicron has been circulating in China as a major variant of the novel coronavirus, but the effects of infection with Omicron variants on pregnant women and newborns are unknown. The purpose of this study was to determine the clinical characteristics of Omicron infection during pregnancy and its effect on pregnancy outcomes.MethodsThis study retrospectively analyzed the data of 93 confirmed cases of novel coronavirus infection and 109 non-infected patients admitted to the isolation ward of Guangdong Maternal and Child Health Hospital from December 1, 2022 to January 31, 2023, and statistically analyzed the clinical features of Omicron variant infection during pregnancy and its impact on pregnancy outcomes. Further effects of underlying diseases on Omicron infection in pregnant women were analyzed.ResultsThe incubation period of COVID-19 infection was 0.99±0.86 days, 94.38% of patients had fever or other respiratory symptoms, the lymphocyte count in the infected group was lower than that in the uninfected group, and the lymphocyte count was further reduced in the patients with pregnancy complications or complications. Compared with the uninfected group, APTT and PT were prolonged, platelet count and fibrinogen were decreased in the infected group, all of which had statistical significance. COVID-19 infection during pregnancy increased the rate of cesarean section compared to uninfected pregnant patients, and COVID-19 infection in gestational diabetes resulted in a 4.19-fold increase in cesarean section rate. There was no statistically significant difference in gestational age between the two groups. The incidence of intrauterine distress, turbidity of amniotic fluid and neonatal respiratory distress were higher in the infection group. No positive cases of neonatal COVID-19 infection have been found.ConclusionThe patients infected with omicron during pregnancy often have febrile respiratory symptoms with lymphocyopenia, but the incidence of severe disease is low. Both Omicron infection and gestational diabetes further increase the incidence of cesarean section, and this study found no evidence of vertical transmission of Omicron

Self‐Assembly of Therapeutic Peptide into Stimuli‐Responsive Clustered Nanohybrids for Cancer‐Targeted Therapy

Clinical translation of therapeutic peptides, particularly those targeting intracellular protein–protein interactions (PPIs), has been hampered by their inefficacious cellular internalization in diseased tissue. Therapeutic peptides engineered into nanostructures with stable spatial architectures and smart disease targeting ability may provide a viable strategy to overcome the pharmaceutical obstacles of peptides. This study describes a strategy to assemble therapeutic peptides into a stable peptide–Au nanohybrid, followed by further self‐assembling into higher‐order nanoclusters with responsiveness to tumor microenvironment. As a proof of concept, an anticancer peptide termed β‐catenin/Bcl9 inhibitors is copolymerized with gold ion and assembled into a cluster of nanohybrids (pCluster). Through a battery of in vitro and in vivo tests, it is demonstrated that pClusters potently inhibit tumor growth and metastasis in several animal models through the impairment of the Wnt/β‐catenin pathway, while maintaining a highly favorable biosafety profile. In addition, it is also found that pClusters synergize with the PD1/PD‐L1 checkpoint blockade immunotherapy. This new strategy of peptide delivery will likely have a broad impact on the development of peptide‐derived therapeutic nanomedicine and reinvigorate efforts to discover peptide drugs that target intracellular PPIs in a great variety of human diseases, including cancer.A strategy for clinical translation of therapeutic peptides by assembling them into a stable peptide–Au nanohybrid, followed by further self‐assembling into higher‐order nanoclusters with responsiveness to the tumor microenvironment, is presented. An anticancer peptide termed β‐catenin/Bcl9 inhibitor is assembled into a cluster of nanohybrids termed pCluster, which potently inhibits tumor growth as well as metastasis, and synergizes with immunotherapy, while maintaining a highly favorable biosafety profile.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/1/adfm201807736.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/2/adfm201807736-sup-0001-S1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/148246/3/adfm201807736_am.pd

Selective fiber Bragg grating inscription in four-core fiber for two-dimension vector bending sensing

The paper presents selective fiber Bragg grating (FBG) inscription in four-core fiber based on a phase mask scanning method. The inscription factors are systematically investigated, which involves fiber core position and focused laser beam size in fiber, etc. Several specific inscriptions (including individual, dual and all inscriptions) are demonstrated. Two orthogonally positioned cores are selectively inscribed and applied to two-dimension vector bending measurement. The measured bending sensitivities of two FBGs range from −54.3 pm/m−1 to 52.2 pm/m−1 and −53.7 pm/m−1 to 52.8 pm/m−1, respectively. More importantly, it has been revealed that their sensitivities versus bending direction follow regular cosinoidal and sinusoidal distribution. The direction and amplitude of the vector bending can be recovered using measured central wavelength shifts of those two FBGs

Population Genetic Diversity and Phylogenetic Characteristics for High-Altitude Adaptive Kham Tibetan Revealed by DNATyperTM 19 Amplification System

Tibetans residing in the high-altitude inhospitable environment have undergone significant natural selection of their genetic architecture. Recently, highly mutational autosomal short tandem repeats were widely used not only in the anthropology and population genetics to investigate the genetic structure and relationships, but also in the medical genetics to explore the pathogenesis of multiple genetic diseases and in the forensic science to identify individual and parentage relatedness. However, genetic variants and forensic efficiency of DNATyperTM 19 amplification system and genetic background of Kham Tibetan remain uncharacterized. Thus, we genotyped 19 forensic genetic markers in 11,402 Kham Tibetans to gain insight into the genetic diversity of Chinese high-altitude adaptive population. Highly discriminating and polymorphic forensic measures were observed, which indicated that this new-developed DNATyper 19 PCR amplification is suitable for routine forensic identification purposes and Chinese national DNA database establishment. Pairwise genetic distances among the comprehensive population comparisons suggested that this high-altitude adaptive Kham Tibetan has genetically closer relationships with lowlanders of Tibeto-Burman-speaking populations (Chengdu Tibetan, Liangshan Tibetan, and Liangshan Yi). Genetic substructure analyses via phylogenetic reconstruction, principal component analysis, and multidimensional scaling analysis in both nationwide and worldwide contexts suggested that the genetic proximity exists along the linguistic, ethnic, and continental geographical boundary. Further studies with whole-genome sequencing of modern or archaic Kham Tibetans would be useful in reconstructing the Tibetan population history