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Diabetic striatopathy (DS) is a rare medical condition with ambiguous nomenclature. We searched PubMed database from 1992 to 2018 for articles describing hyperglycemia associated with chorea/ballism and/or neuroimages of striatal abnormalities. Descriptive analysis was performed on demographic/clinical characteristics, locations of striatal abnormalities on neuroimages, pathology findings, treatment strategies, and outcomes. In total, 176 patients (male:female = 1:1.7) were identified from 72 articles with mean age 67.6 ± 15.9 (range, 8–92). Among them, 96.6% had type 2 DM with 17% being newly diagnosed. Average blood glucose and glycated hemoglobin concentrations were 414 mg/dL and 13.1%, respectively. Most patients (88.1%) presented with hemichorea/hemiballism. Isolated putamen and combined putamen-caudate nucleus involvements were most common on neuroimaging studies with discrepancies between CT and MRI findings in about one-sixth of patients. Unilateral arm-leg combination was the most frequent with bilateral chorea in 9.7% of patients. Chorea and imaging anomalies did not appear concomitantly in one-tenth of patients. Successful treatment rates of chorea with glucose-control-only and additional anti-chorea medications were 25.7% and 76.2%, respectively, with an overall recurrence rate being 18.2%. The most commonly used anti-chorea drug was haloperidol. To date, four out of six pathological studies revealed evidence of hemorrhage as a probable pathogenesis.

Analysis of health-related texts can be used to detect adverse drug reactions (ADR). The greatest challenge for ADR detection lies in imbalanced data distributions where words related to ADR symptoms are often minority classes. As a result, trained models tend to converge to a point that strongly biases towards the majority class and then ignores the minority class. Since the most used cross-entropy criteria is an approximation to accuracy, the model focuses more readily on the majority class to achieve high accuracy. To address this issue, existing methods apply either oversampling or down-sampling strategies to balance the data distribution and exploit the most difficult samples of the minority class. However, increasing or reducing the number of individual tokens alone in sequence labeling tasks will result in the loss of the syntactic relations of the sentence. This paper proposes a weighted variant of conditional random field (CRF) for data-imbalanced sequence labeling tasks. Such a weighting strategy can alleviate data distribution imbalances between majority and minority classes. Instead of using softmax in the output layer, the CRF can capture the relationship of labels between tokens. The locally interpretable model-agnostic explanations (LIME) algorithm was applied to investigate performance differences between models with and without the weighted loss function. Experimental results on two different ADR tasks show that the proposed model outperforms previously proposed sequence labeling methods.

ZFP36 family members include ZFP36, ZFP36L1, and ZFP36L2, which belong to CCCH-type zinc finger proteins with two tandem zinc finger (TZF) regions. Whether ZFP36L1 and ZFP36L2 have antiproliferative activities similar to that of ZFP36 is unclear. In this study, when ZFP36L1 or ZFP36L2 was overexpressed in T-REx-293 cells, cell proliferation was dramatically inhibited and the cell cycle was arrested at the G1 phase. The levels of cell-cycle-related proteins, including cyclin B, cyclin D, cyclin A, and p21, decreased; however, p53 increased in ZFP36L1-or ZFP36L2-overexpressing T-REx-293 cells. Forced expression of ZFP36L1 or ZFP36L2 also inhibited cell proliferation and cyclin D gene expression in three human colorectal cancer cell lines: HCT116 p53 +/+ , HCT116 p53 −/− , and SW620 (mutated p53) cells. However, it increased p53 and p21 expression only in HCT116 p53 +/+ cells. Knockdown of ZFP36L1 or ZFP36L2 increased cell proliferation and cyclin D expression; furthermore, the mutation of the TZF of ZFP36L1 or ZFP36L2 caused them to lose their antiproliferative ability, to the extent that they could not inhibit cyclin D expression in these three cell lines. The results indicated that ZFP36L1 and ZFP36L2 play a negative role in cell proliferation; the underlying mechanisms might be mediated through a cyclin D-dependent and p53-independent pathway.

Machine learning is useful for grid-based crime prediction. Many previous studies have examined factors including time, space, and type of crime, but the geographic characteristics of the grid are rarely discussed, leaving prediction models unable to predict crime displacement. This study incorporates the concept of a criminal environment in grid-based crime prediction modeling, and establishes a range of spatial-temporal features based on 84 types of geographic information by applying the Google Places API to theft data for Taoyuan City, Taiwan. The best model was found to be Deep Neural Networks, which outperforms the popular Random Decision Forest, Support Vector Machine, and K-Near Neighbor algorithms. After tuning, compared to our design’s baseline 11-month moving average, the F1 score improves about 7% on 100-by-100 grids. Experiments demonstrate the importance of the geographic feature design for improving performance and explanatory ability. In addition, testing for crime displacement also shows that our model design outperforms the baseline.

The protein disulfide isomerase (PDI) family is a group of thioredoxin endoplasmic reticulum (ER)-resident enzymes and molecular chaperones that play crucial roles in the correct folding of proteins. PDIs are upregulated in multiple cancer types and are considered a novel target for cancer therapy. In this study, we found that a potent pan-PDI inhibitor, E64FC26, significantly decreased the proliferation of pancreatic ductal adenocarcinoma (PDAC) cells. As expected, E64FC26 treatment increased ER stress and the unfolded protein response (UPR), as evidenced by upregulation of glucose-regulated protein, 78-kDa (GRP78), phosphorylated (p)-PKR-like ER kinase (PERK), and p-eukaryotic initiation factor 2α (eIF2α). Persistent ER stress was found to lead to apoptosis, ferroptosis, and autophagy, all of which are dependent on lysosomal functions. First, there was little cleaved caspase-3 in E64FC26-treated cells according to Western blotting, but a higher dose of E64FC26 was needed to induce caspase activity. Then, E64FC26-induced cell death could be reversed by adding the iron chelator, deferoxamine, and the reactive oxygen species scavengers, ferrostatin-1 and N-acetylcysteine. Furthermore, the autophagosome-specific marker, light chain 3B (LC3B)-II, increased, but the autolysosome marker, sequestosome 1 (SQSTM1)/p62, was not degraded in E64FC26-treated cells. Using the FUW mCherry-LC3 plasmid and acridine orange staining, we also discovered a lower number of acidic vesicles, such as autolysosomes and mature lysosomes, in E64FC26-treated cells. Finally, E64FC26 treatment increased the cathepsin L precursor (pre-CTSL) but decreased mature CTSL expression according to Western blotting, indicating a defective lysosome. These results suggested that the PDI inhibitor, E64FC26, might initially impede proper folding of proteins, and then induce ER stress and disrupt proteostasis, subsequently leading to lysosomal defects. Due to defective lysosomes, the extents of apoptosis and ferroptosis were limited, and fusion with autophagosomes was blocked in E64FC26-treated cells. Blockade of autolysosomal formation further led to the autophagic cell death of PDAC cells.

Based on a two-dimensional valence-arousal sentiment evaluation method, we used the sentiment extracted from the text of online news media and stock forums to predict future financial performance of publicly listed companies. A Chinese lexicon called the Chinese Valence-Arousal Words, provided by Yu et al. (2016), was used to obtain the valence and arousal scores of all Web text for each of the 183 large listed companies for each fiscal quarter over the Q1 2013 through Q3 2017 period. Our empirical results tended to support our two hypotheses that there is a positive association between the valence (under Hypothesis 1) or arousal-augmented valence (under Hypothesis 2) of online public opinion about the listed companies and their future financial performance. In particular, when the sentiment was positive (negative) in the current fiscal quarter, whether measured by the valence alone or by the arousal-augmented valence, the financial performance (measured by ROA, ROE, and Tobin’s Q) observed in the next quarter would tend to be better (worse).

Honokiol has been reported to possess anti-inflammatory and neuroprotective activities. However, the poor aqueous solubility of honokiol limits its clinical application for systemic administration. This study aims to develop a novel formulation of nanosome-encapsulated honokiol (NHNK) for intravenous therapy against mouse experimental autoimmune encephalomyelitis (EAE) that mimics human multiple sclerosis. Nanosomes and NHNK were prepared by using an ultra-high pressure homogenization (UHPH) method. Mice were treated with NHNK or empty nanosomes during the peak phase of EAE symptoms. Symptoms of EAE were monitored and samples of the spinal cord were obtained for histopathological examinations. The stock of NHNK containing honokiol in the nanosome formulation, which showed the structure of single phospholipid bilayer membranes, was well formulated with the particle size of 48.0 ± 0.1 nm and the encapsulation efficiency 58.1 ± 4.2%. Intravenous administration of NHNK ameliorated the severity of EAE accompanied by a significant reduction of demyelination and inflammation in the spinal cord. Furthermore, NHNK decreased the number of IL-6 , Iba-1 TNF , Iba-1 IL-12 p40 , and CD3 IFN-γ cells infiltrating the spinal cord. The UHPH method simplified the preparation of NHNK with uniformly distributed nanosize and high encapsulation efficiency. Intravenous administration of NHNK ameliorated the severity of EAE by suppressing the infiltration of activated microglia and Th1 cells into the spinal cord. Collectively, these results suggest that the formulation of NHNK is a prospective therapeutic approach for inflammatory CNS diseases, such as multiple sclerosis.

Background With the advancement of next generation sequencing technologies (NGS), whole-genome sequencing (WGS) has been deployed to a wide range of clinical scenarios. Rapid and accurate classification of drug-resistant Mycobacterium tuberculosis ( MTB ) would be advantageous in reducing the amplification of additional drug resistance and disease transmission. Methods In this study, a long-read sequencing approach was subjected to the whole-genome sequencing of clinical MTB clones with susceptibility test profiles, including isoniazid (INH) susceptible clones ( n  = 10) and INH resistant clones ( n  = 42) isolated from clinical specimens. Non-synonymous variants within the katG or inhA gene associated with INH resistance was identified using Nanopore sequencing coupled with a corresponding analytical workflow. Results In total, 54 nucleotide variants within the katG gene and 39 variants within the inhA gene associated with INH resistance were identified. Consistency among the results of genotypic profiles, susceptibility test, and minimal inhibitory concentration, the high-INH resistance signature was estimated using the area under the receiver operating characteristic curve with the existence of Ser315Thr (AUC = 0.822) or Thr579Asn (AUC = 0.875). Conclusions Taken together, we curated lists of coding variants associated with differential INH resistance using Nanopore sequencing, which may constitute an emerging platform for rapid and accurate identification of drug-resistant MTB clones.

Background Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive types of solid tumor, and novel strategies must be developed for treating it. Previous studies predominantly utilized circular RNA (circRNA) expression plasmids incorporating Alu elements to facilitate the indirect expression of circRNA. Methods Public databases and bioinformatics tools were used to identify hsa_circ_0004781 that is highly expressed in PDAC and its potential microRNA (miRNA) targets and corresponding mRNA targets. Real hsa_circ_0004781, which is identical to the native form of hsa_circ_0004781 without any exogenous sequences, was prepared through in vitro transcription by using a ribozyme and ion-pair reversed-phase high-performance liquid chromatography (IP-RP HPLC). The biological functions of hsa_circ_0004781 were evaluated using loss-of-function and gain-of-function approaches with circRNA expression plasmids and real hsa_circ_0004781. Results Knockdown of hsa_circ_0004781 inhibited the proliferation and migration of PDAC cells, whereas its overexpression produced opposite effects. Hsa_circ_0004781 was identified as a sponge for miR-9-5p and miR-338-3p, and its expression was negatively correlated with that of these miRNAs. Among the targets of miR-9-5p and miR-338-3p, Kruppel-like factor 5 ( KLF5 ) and a disintegrin and metalloproteinase domain 17 ( ADAM17 ) were negatively correlated with survival in patients with PDAC and were inversely regulated by these miRNAs. Furthermore, real hsa_circ_0004781 exhibited the same effects as those of the circRNA expression plasmids. Conclusions This study is the first to use real circRNAs to validate results obtained using circRNA expression plasmids. The results suggest that hsa_circ_0004781 functions as an oncogene, promoting the proliferation of PDAC cells through the miR-9-5p/ KLF5 and miR-338-3p/ ADAM17 axes. Therefore, hsa_circ_0004781 might be a therapeutic target for PDAC.

Bacteria of the genus Elizabethkingia are emerging infectious agents that can cause infection in humans. The number of published whole-genome sequences of Elizabethkingia is rapidly increasing. In this study, we used comparative genomics to investigate the genomes of the six species in the Elizabethkingia genus, namely E. meningoseptica , E. anophelis , E. miricola , E. bruuniana , E. ursingii , and E. occulta . In silico DNA–DNA hybridization, whole-genome sequence-based phylogeny, pan genome analysis, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed, and clusters of orthologous groups were evaluated. Of the 86 whole-genome sequences available in GenBank, 21 were complete genome sequences and 65 were shotgun sequences. In silico DNA–DNA hybridization clearly delineated the six Elizabethkingia species. Phylogenetic analysis confirmed that E. bruuniana , E. ursingii , and E. occulta were closer to E. miricola than to E. meningoseptica and E. anophelis . A total of 2,609 clusters of orthologous groups were identified among the six type strains of the Elizabethkingia genus. Metabolism-related clusters of orthologous groups accounted for the majority of gene families in KEGG analysis. New genes were identified that substantially increased the total repertoire of the pan genome after the addition of 86 Elizabethkingia genomes, which suggests that Elizabethkingia has shown adaptive evolution to environmental change. This study presents a comparative genomic analysis of Elizabethkingia , and the results of this study provide knowledge that facilitates a better understanding of this microorganism.