Computational and Imaging Methods for Studying Neuronal Populations during Behavior

One of the central questions in neuroscience is how the nervous system generates and regulates behavior. To understand the neural code for any behavior, an ideal experiment would entail (i) quantitatively defining that behavior, (ii) recording neuronal activity in relevant brain regions to identify the underlying neuronal circuits and eventually (iii) manipulating them to test their function. Novel methods in neuroscience have greatly advanced our abilities to conduct such experiments but are still insufficient. In this thesis, I developed methods for these three goals. In Chapter 2, I describe an automatic behavior identification and classification method for the cnidarian Hydra vulgaris using machine learning. In Chapter 3, I describe a fast volumetric two-photon microscope with dual-color laser excitation that can image in 3D the activity of populations of neurons from visual cortex of awake mice. In Chapter 4, I present a machine learning method that identifies cortical ensembles and pattern completion neurons in mouse visual cortex, using two-photon calcium imaging data. These methods advance current technologies, providing opportunities for new discoveries

Comprehensive machine learning analysis of Hydra behavior reveals a stable basal behavioral repertoire

Animal behavior has been studied for centuries, but few efficient methods are available to automatically identify and classify it. Quantitative behavioral studies have been hindered by the subjective and imprecise nature of human observation, and the slow speed of annotating behavioral data. Here, we developed an automatic behavior analysis pipeline for the cnidarian Hydra vulgaris using machine learning. We imaged freely behaving Hydra, extracted motion and shape features from the videos, and constructed a dictionary of visual features to classify pre-defined behaviors. We also identified unannotated behaviors with unsupervised methods. Using this analysis pipeline, we quantified 6 basic behaviors and found surprisingly similar behavior statistics across animals within the same species, regardless of experimental conditions. Our analysis indicates that the fundamental behavioral repertoire of Hydra is stable. This robustness could reflect a homeostatic neural control of "housekeeping" behaviors which could have been already present in the earliest nervous systems

Rituals in Sakuma Shōzan’s Sōrei shisetsu : Focusing on the Sections of Chikan, Sakushu, Shiseki, and Bohi

Sōrei shisetsu was authored by Sakuma Shōzan (1811-1864), a renowned philosopher during the Bakumatsu period. When his mother passed away in 1861, Shōzan attempted to bury her according to the Confucian practices outlined in Zhu Xi’s Jiali but had to give in to the dominant Buddhist funeral traditions in the end. Shōzan took this opportunity to contemplate Japanese funeral rituals, arguing the importance of replacing Buddhist conventions with Confucian ones. In my previous works on Shōzan’s Sōrei shisetsu, I closely examined its structure and political resonance, as well as authorial intent. To supplement my earlier studies, in this paper, I focus on the sections related to Chikan 治棺, Sakushu 作主, Shiseki 誌石, and Bohi 墓碑. The research findings of this paper will shed light on social perceptions of Zhu Xi’s Jiali during the Edo period

Sleeping Bear Dunes Bay to Bay Hiking and Kayaking Trail

The Bay to Bay Trail Masters Project focused on the planning of a 35 mile hiking and paddling trail along the shoreline of Sleeping Bear Dunes National Lakeshore. The Bay to Bay Trail is named such because it would extend from Good Harbor Bay south to Platte Bay. The project was sponsored by the Rivers, Trails, and Conservation Assistance Michigan Office of the National Park Service and The Friends of Sleeping Bear Dunes. The team’s process included research into similar trails, field investigations and analyses, and development of a conceptual design for the trail that includes alternative trail routes, campgrounds, and kayak launch sites. The team gauged interest in the trail and gathered input through interviews with local outfitters and user groups. In addition, perspectives on paddlers’ and hikers’ preferences on trail qualities and amenities were gathered through a set of surveys. Finally, a campground matrix was created to assess and evaluate potential campground sites along the trail. The team’s survey and interview findings, maps of trail, campground, and launch site alternatives will be used in the Environmental Assessment of the trail. The water trail and kayak launch site data and analysis will directly benefit Michigan’s contribution to the Lake Michigan Water Trail: a four-state effort to create a contiguous water trail around the perimeter of Lake Michigan. Conceptual designs of the campgrounds, launch sites, and trail signage will be used in public meetings. Additionally, the team created mock-ups for a website and brochure to be used by Friends of Sleeping Bear Dunes and the Park. In sum, the project will aid in the actualization of a dual water/hiking trail: an unprecedented recreational feature in Michigan.Master of ScienceNatural Resources and EnvironmentUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/106546/1/SleepingBearDunes_BayToBayTrail.pd

Assessment of disaster preparedness and related impact factors among emergency nurses in tertiary hospitals: descriptive cross-sectional study from Henan Province of China

BackgroundThe aim of this study was to investigate the current state of disaster preparedness and to determine associated factors among emergency nurses from tertiary hospitals in Henan Province of China.MethodsThis multicenter descriptive cross-sectional study was conducted with emergency nurses from 48 tertiary hospitals in Henan Province of China between September 7, 2022–September 27, 2022. Data were collected through a self-designeds online questionnaire using the mainland China version of the Disaster Preparedness Evaluation Tool (DPET-MC). Descriptive analysis and multiple linear regression analysis were used to evaluate disaster preparedness and to determine factors affecting disaster preparedness, respectively.ResultsA total of 265 emergency nurses in this study displayed a moderate level of disaster preparedness with a mean item score of 4.24 out 6.0 on the DPET-MC questionnaire. Among the five dimensions of the DPET-MC, the mean item score for pre-disaster awareness was highest (5.17 ± 0.77), while that for disaster management (3.68 ± 1.36) was the lowest. Female gender (B = −9.638, p = 0.046) and married status (B = −8.618, p = 0.038) were negatively correlated with the levels of disaster preparedness. Five factors positively correlated with the levels of disaster preparedness included having attended in the theoretical knowledge training of disaster nursing since work (B = 8.937, p = 0.043), having experienced the disaster response (B = 8.280, p = 0.036), having participated in the disaster rescue simulation exercise (B = 8.929, p = 0.039), having participated in the disaster relief training (B = 11.515, p = 0.025), as well as having participated in the training of disaster nursing specialist nurse (B = 16.101, p = 0.002). The explanatory power of these factors was 26.5%.ConclusionEmergency nurses in Henan Province of China need more education in all areas of disaster preparedness, especially disaster management, which needs to be incorporated into nursing education, including formal and ongoing education. Besides, blended learning approach with simulation-based training and disaster nursing specialist nurse training should be considered as novel ways to improve disaster preparedness for emergency nurses in mainland China

The BR signaling pathway regulates primary root development and drought stress response by suppressing the expression of PLT1 and PLT2 in Arabidopsis thaliana

IntroductionWith the warming global climate, drought stress has become an important abiotic stress factor limiting plant growth and crop yield. As the most rapidly drought-sensing organs of plants, roots undergo a series of changes to enhance their ability to absorb water, but the molecular mechanism is unclear.Results and methodsIn this study, we found that PLT1 and PLT2, two important transcription factors of root development in Arabidopsis thaliana, are involved in the plant response to drought and are inhibited by BR signaling. PLT1- and PLT2-overexpressing plants showed greater drought tolerance than wild-type plants. Furthermore, we found that BZR1 could bind to the promoter of PLT1 and inhibit its transcriptional activity in vitro and in vivo. PLT1 and PLT2 were regulated by BR signaling in root development and PLT2 could partially rescue the drought sensitivity of bes1-D. In addition, RNA-seq data analysis showed that BR-regulated root genes and PLT1/2 target genes were also regulated by drought; for example, CIPK3, RCI2A, PCaP1, PIP1;5, ERF61 were downregulated by drought and PLT1/2 but upregulated by BR treatment; AAP4, WRKY60, and AT5G19970 were downregulated by PLT1/2 but upregulated by drought and BR treatment; and RGL2 was upregulated by drought and PLT1/2 but downregulated by BR treatment.DiscussionOur findings not only reveal the mechanism by which BR signaling coordinates root growth and drought tolerance by suppressing the expression of PLT1 and PLT2 but also elucidates the relationship between drought and root development. The current study thus provides an important theoretical basis for the improvement of crop yield under drought conditions

Pathogenesis and therapeutic implications of EBV-associated epithelial cancers

Epstein-Barr virus (EBV), one of the most common human viruses, has been associated with both lymphoid and epithelial cancers. Undifferentiated nasopharyngeal carcinoma (NPC), EBV associated gastric cancer (EBVaGC) and lymphoepithelioma-like carcinoma (LELC) are amongst the few common epithelial cancers that EBV has been associated with. The pathogenesis of EBV-associated NPC has been well described, however, the same cannot be said for primary pulmonary LELC (PPLELC) owing to the rarity of the cancer. In this review, we outline the pathogenesis of EBV-associated NPC and EBVaGCs and their recent advances. By drawing on similarities between NPC and PPLELC, we then also postulated the pathogenesis of PPLELC. A deeper understanding about the pathogenesis of EBV enables us to postulate the pathogenesis of other EBV associated cancers such as PPLELC

A Perspective on Cell Therapy and Cancer Vaccine in Biliary Tract Cancers (BTCs).

Biliary tract cancer (BTC) is a rare, but aggressive, disease that comprises of gallbladder carcinoma, intrahepatic cholangiocarcinoma and extrahepatic cholangiocarcinoma, with heterogeneous molecular profiles. Advanced disease has limited therapeutic options beyond first-line platinum-based chemotherapy. Immunotherapy has emerged as a viable option for many cancers with a similar unmet need. Therefore, we reviewed current understanding of the tumor immune microenvironment and recent advances in cellular immunotherapy and therapeutic cancer vaccines against BTC. We illustrated the efficacy of dendritic cell vaccination in one patient with advanced, chemorefractory, melanoma-associated antigen (MAGE)-positive gallbladder carcinoma, who was given multiple injections of an allogenic MAGE antigen-positive melanoma cell lysate (MCL)-based autologous dendritic cell vaccine combined with sequential anti-angiogenic therapy. This resulted in good radiological and tumor marker response and an overall survival of 3 years from diagnosis. We postulate the potential synergism of adding anti-angiogenic therapy, such as bevacizumab, to immunotherapy in BTC, as a rational scientific principle to positively modulate the tumor microenvironment to augment antitumor immunity

MODMA dataset: a Multi-modal Open Dataset for Mental-disorder Analysis

According to the World Health Organization, the number of mental disorder patients, especially depression patients, has grown rapidly and become a leading contributor to the global burden of disease. However, the present common practice of depression diagnosis is based on interviews and clinical scales carried out by doctors, which is not only labor-consuming but also time-consuming. One important reason is due to the lack of physiological indicators for mental disorders. With the rising of tools such as data mining and artificial intelligence, using physiological data to explore new possible physiological indicators of mental disorder and creating new applications for mental disorder diagnosis has become a new research hot topic. However, good quality physiological data for mental disorder patients are hard to acquire. We present a multi-modal open dataset for mental-disorder analysis. The dataset includes EEG and audio data from clinically depressed patients and matching normal controls. All our patients were carefully diagnosed and selected by professional psychiatrists in hospitals. The EEG dataset includes not only data collected using traditional 128-electrodes mounted elastic cap, but also a novel wearable 3-electrode EEG collector for pervasive applications. The 128-electrodes EEG signals of 53 subjects were recorded as both in resting state and under stimulation; the 3-electrode EEG signals of 55 subjects were recorded in resting state; the audio data of 52 subjects were recorded during interviewing, reading, and picture description. We encourage other researchers in the field to use it for testing their methods of mental-disorder analysis

The Genomes of Oryza sativa: A History of Duplications

We report improved whole-genome shotgun sequences for the genomes of indica and japonica rice, both with multimegabase contiguity, or almost 1,000-fold improvement over the drafts of 2002. Tested against a nonredundant collection of 19,079 full-length cDNAs, 97.7% of the genes are aligned, without fragmentation, to the mapped super-scaffolds of one or the other genome. We introduce a gene identification procedure for plants that does not rely on similarity to known genes to remove erroneous predictions resulting from transposable elements. Using the available EST data to adjust for residual errors in the predictions, the estimated gene count is at least 38,000–40,000. Only 2%–3% of the genes are unique to any one subspecies, comparable to the amount of sequence that might still be missing. Despite this lack of variation in gene content, there is enormous variation in the intergenic regions. At least a quarter of the two sequences could not be aligned, and where they could be aligned, single nucleotide polymorphism (SNP) rates varied from as little as 3.0 SNP/kb in the coding regions to 27.6 SNP/kb in the transposable elements. A more inclusive new approach for analyzing duplication history is introduced here. It reveals an ancient whole-genome duplication, a recent segmental duplication on Chromosomes 11 and 12, and massive ongoing individual gene duplications. We find 18 distinct pairs of duplicated segments that cover 65.7% of the genome; 17 of these pairs date back to a common time before the divergence of the grasses. More important, ongoing individual gene duplications provide a never-ending source of raw material for gene genesis and are major contributors to the differences between members of the grass family