ODD: A Benchmark Dataset for the NLP-based Opioid Related Aberrant Behavior Detection

Opioid related aberrant behaviors (ORAB) present novel risk factors for opioid overdose. Previously, ORAB have been mainly assessed by survey results and by monitoring drug administrations. Such methods however, cannot scale up and do not cover the entire spectrum of aberrant behaviors. On the other hand, ORAB are widely documented in electronic health record notes. This paper introduces a novel biomedical natural language processing benchmark dataset named ODD, for ORAB Detection Dataset. ODD is an expert-annotated dataset comprising of more than 750 publicly available EHR notes. ODD has been designed to identify ORAB from patients' EHR notes and classify them into nine categories; 1) Confirmed Aberrant Behavior, 2) Suggested Aberrant Behavior, 3) Opioids, 4) Indication, 5) Diagnosed opioid dependency, 6) Benzodiapines, 7) Medication Changes, 8) Central Nervous System-related, and 9) Social Determinants of Health. We explored two state-of-the-art natural language processing (NLP) models (finetuning pretrained language models and prompt-tuning approaches) to identify ORAB. Experimental results show that the prompt-tuning models outperformed the finetuning models in most cateogories and the gains were especially higher among uncommon categories (Suggested aberrant behavior, Diagnosed opioid dependency and Medication change). Although the best model achieved the highest 83.92% on area under precision recall curve, uncommon classes (Suggested Aberrant Behavior, Diagnosed Opioid Dependence, and Medication Change) still have a large room for performance improvement.Comment: Under revie

The SOFIA Massive (SOMA) Star Formation Survey. III. From Intermediate- to High-Mass Protostars

We present $\sim10-40\,\mu$m SOFIA-FORCAST images of 14 intermediate-mass protostar candidates as part of the SOFIA Massive (SOMA) Star Formation Survey. We build spectral energy distributions (SEDs), also utilizing archival Spitzer, Herschel and IRAS data. We then fit the SEDs with radiative transfer (RT) models of Zhang & Tan (2018), based on Turbulent Core Accretion theory, to estimate key protostellar properties. With the addition of these intermediate-mass sources, SOMA protostars span luminosities from $\sim10^{2}-10^{6}\:L_{\odot}$, current protostellar masses from $\sim0.5-30\:M_{\odot}$ and ambient clump mass surface densities, $\Sigma_{\rm cl}$ from $0.1-3\:{\rm{g\:cm}^{-2}}$. A wide range of evolutionary states of the individual protostars and of the protocluster environments are also probed. We have also considered about 50 protostars identified in Infrared Dark Clouds and expected to be at the earliest stages of their evolution. With this global sample, most of the evolutionary stages of high- and intermediate-mass protostars are probed. From the best fitting models, there is no evidence of a threshold value of protocluster clump mass surface density being needed to form protostars up to $\sim25\:M_\odot$. However, to form more massive protostars, there is tentative evidence that $\Sigma_{\rm{cl}}$ needs to be $\gtrsim1\:{\rm{g\,cm}}^{-2}$. We discuss how this is consistent with expectations from core accretion models that include internal feedback from the forming massive star.Comment: 40 pages, 21 figures, 4 tables, accepted to Ap

The cellular and synaptic architecture of the mechanosensory dorsal horn

The deep dorsal horn is a poorly characterized spinal cord region implicated in processing low-threshold mechanoreceptor (LTMR) information. We report an array of mouse genetic tools for defining neuronal components and functions of the dorsal horn LTMR-recipient zone (LTMR-RZ), a role for LTMR-RZ processing in tactile perception, and the basic logic of LTMR-RZ organization. We found an unexpectedly high degree of neuronal diversity in the LTMR-RZ: seven excitatory and four inhibitory subtypes of interneurons exhibiting unique morphological, physiological, and synaptic properties. Remarkably, LTMRs form synapses on between four and 11 LTMR-RZ interneuron subtypes, while each LTMR-RZ interneuron subtype samples inputs from at least one to three LTMR classes, as well as spinal cord interneurons and corticospinal neurons. Thus, the LTMR-RZ is a somatosensory processing region endowed with a neuronal complexity that rivals the retina and functions to pattern the activity of ascending touch pathways that underlie tactile perception

PPIP5K2 and PCSK1 are Candidate Genetic Contributors to Familial Keratoconus

Keratoconus (KC) is the most common corneal ectatic disorder affecting >300,000 people in the US. KC normally has its onset in adolescence, progressively worsening through the third to fourth decades of life. KC patients report significant impaired vision-related quality of life. Genetic factors play an important role in KC pathogenesis. To identify novel genes in familial KC patients, we performed whole exome and genome sequencing in a four-generation family. We identified potential variants in the PPIP5K2 and PCSK1 genes. Using in vitro cellular model and in vivo gene-trap mouse model, we found critical evidence to support the role of PPIP5K2 in normal corneal function and KC pathogenesis. The gene-trap mouse showed irregular corneal surfaces and pathological corneal thinning resembling KC. For the first time, we have integrated corneal tomography and pachymetry mapping into characterization of mouse corneal phenotypes which could be widely implemented in basic and translational research for KC diagnosis and therapy in the future

One-year delayed effect of fog on malaria transmission: a time-series analysis in the rain forest area of Mengla County, south-west China

Background: Malaria is a major public health burden in the tropics with the potential to significantly increase in response to climate change. Analyses of data from the recent past can elucidate how short-term variations in weather factors affect malaria transmission. This study explored the impact of climate variability on the transmission of malaria in the tropical rain forest area of Mengla County, south-west China. Methods: Ecological time-series analysis was performed on data collected between 1971 and 1999. Auto-regressive integrated moving average (ARIMA) models were used to evaluate the relationship between weather factors and malaria incidence. Results: At the time scale of months, the predictors for malaria incidence included: minimum temperature, maximum temperature, and fog day frequency. The effect of minimum temperature on malaria incidence was greater in the cool months than in the hot months. The fog day frequency in October had a positive effect on malaria incidence in May of the following year. At the time scale of years, the annual fog day frequency was the only weather predictor of the annual incidence of malaria. Conclusion: Fog day frequency was for the first time found to be a predictor of malaria incidence in a rain forest area. The one-year delayed effect of fog on malaria transmission may involve providing water input and maintaining aquatic breeding sites for mosquitoes in vulnerable times when there is little rainfall in the 6-month dry seasons. These findings should be considered in the prediction of future patterns of malaria for similar tropical rain forest areas worldwide

Large-scale genome-wide association studies and meta-analyses of longitudinal change in adult lung function.

BACKGROUND: Genome-wide association studies (GWAS) have identified numerous loci influencing cross-sectional lung function, but less is known about genes influencing longitudinal change in lung function. METHODS: We performed GWAS of the rate of change in forced expiratory volume in the first second (FEV1) in 14 longitudinal, population-based cohort studies comprising 27,249 adults of European ancestry using linear mixed effects model and combined cohort-specific results using fixed effect meta-analysis to identify novel genetic loci associated with longitudinal change in lung function. Gene expression analyses were subsequently performed for identified genetic loci. As a secondary aim, we estimated the mean rate of decline in FEV1 by smoking pattern, irrespective of genotypes, across these 14 studies using meta-analysis. RESULTS: The overall meta-analysis produced suggestive evidence for association at the novel IL16/STARD5/TMC3 locus on chromosome 15 (P  =  5.71 × 10(-7)). In addition, meta-analysis using the five cohorts with ≥3 FEV1 measurements per participant identified the novel ME3 locus on chromosome 11 (P  =  2.18 × 10(-8)) at genome-wide significance. Neither locus was associated with FEV1 decline in two additional cohort studies. We confirmed gene expression of IL16, STARD5, and ME3 in multiple lung tissues. Publicly available microarray data confirmed differential expression of all three genes in lung samples from COPD patients compared with controls. Irrespective of genotypes, the combined estimate for FEV1 decline was 26.9, 29.2 and 35.7 mL/year in never, former, and persistent smokers, respectively. CONCLUSIONS: In this large-scale GWAS, we identified two novel genetic loci in association with the rate of change in FEV1 that harbor candidate genes with biologically plausible functional links to lung function

ZIC1 Is Downregulated through Promoter Hypermethylation, and Functions as a Tumor Suppressor Gene in Colorectal Cancer

The transcription factor, Zinc finger of the cerebellum (ZIC1), plays a crucial role in vertebrate development. Recently, ZIC1 has also been found to participate in the progression of human cancers, including medulloblastomas, endometrial cancers, and mesenchymal neoplasms. However, the function of ZIC1 in colon cancer progression has not been defined. In this study, we demonstrate ZIC1 to be silenced or significantly downregulated in colon cancer cell lines. These effects were reversed by demethylation treatment with 5-aza-2′-deoxycytidine (Aza). ZIC1 expression is also significantly downregulated in primary colorectal cancer tissues relative to adjacent non-tumor tissues (p = 0.0001). Furthermore, methylation of ZIC1 gene promoter is frequently detected in primary tumor tissues (85%, 34/40), but not in adjacent non-tumor tissues. Ectopic expression of ZIC1 suppresses cell proliferation and induces apoptosis, which is associated with MAPK and PI3K/Akt pathways, as well as the Bcl-xl/Bad/Caspase3 cascade. To identify target candidates of ZIC1, we employed cDNA microarray and found that 337 genes are downregulated and 95 genes upregulated by ectopic expression of ZIC1, which were verified by 10 selected gene expressions by qRT-PCR. Taken together, our results suggest that ZIC1 may potentially function as a tumor suppressor gene, which is downregulated through promoter hypermethylation in colorectal cancers

PatternLab for proteomics: a tool for differential shotgun proteomics

<p>Abstract</p> <p>Background</p> <p>A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu <it>et al</it>. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen <it>et al</it>. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.</p> <p>Results</p> <p>To address the open issues above, we present a program termed PatternLab for proteomics. This program implements existing strategies and adds two new methods to pinpoint differences in protein profiles. The first method, ACFold, addresses experiments with less than three replicates from each state or having assays acquired by different protocols as described by Chen <it>et al</it>. ACFold uses a combined criterion based on expression fold changes, the AC test, and the false-discovery rate, and can supply a "bird's-eye view" of differentially expressed proteins. The other method addresses experimental designs having multiple readings from each state and is referred to as nSVM (natural support vector machine) because of its roots in evolutionary computing and in statistical learning theory. Our observations suggest that nSVM's niche comprises projects that select a minimum set of proteins for classification purposes; for example, the development of an early detection kit for a given pathology. We demonstrate the effectiveness of each method on experimental data and confront them with existing strategies.</p> <p>Conclusion</p> <p>PatternLab offers an easy and unified access to a variety of feature selection and normalization strategies, each having its own niche. Additionally, graphing tools are available to aid in the analysis of high throughput experimental data. PatternLab is available at <url>http://pcarvalho.com/patternlab</url>.</p

Responsiveness of sphingosine phosphate lyase insufficiency syndrome to vitamin B6 cofactor supplementation

Sphingosine- 1- phosphate (S1P) lyase is a vitamin B6- dependent enzyme that degrades sphingosine- 1- phosphate in the final step of sphingolipid metabolism. In 2017, a new inherited disorder was described caused by mutations in SGPL1, which encodes sphingosine phosphate lyase (SPL). This condition is referred to as SPL insufficiency syndrome (SPLIS) or alternatively as nephrotic syndrome type 14 (NPHS14). Patients with SPLIS exhibit lymphopenia, nephrosis, adrenal insufficiency, and/or neurological defects. No targeted therapy for SPLIS has been reported. Vitamin B6 supplementation has therapeutic activity in some genetic diseases involving B6- dependent enzymes, a finding ascribed largely to the vitamin’s chaperone function. We investigated whether B6 supplementation might have activity in SPLIS patients. We retrospectively monitored responses of disease biomarkers in patients supplemented with B6 and measured SPL activity and sphingolipids in B6- treated patient- derived fibroblasts. In two patients, disease biomarkers responded to B6 supplementation. S1P abundance and activity levels increased and sphingolipids decreased in response to B6. One responsive patient is homozygous for an SPL R222Q variant present in almost 30% of SPLIS patients. Molecular modeling suggests the variant distorts the dimer interface which could be overcome by cofactor supplementation. We demonstrate the first potential targeted therapy for SPLIS and suggest that 30% of SPLIS patients might respond to cofactor supplementation.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162713/2/jimd12238.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162713/1/jimd12238_am.pd