COOL, a Context Outlooker, and its Application to Question Answering and other Natural Language Processing Tasks

Vision outlookers improve the performance of vision transformers, which implement a self-attention mechanism by adding outlook attention, a form of local attention. In natural language processing, as has been the case in computer vision and other domains, transformer-based models constitute the state-of-the-art for most processing tasks. In this domain, too, many authors have argued and demonstrated the importance of local context. We present and evaluate an outlook attention mechanism, COOL, for natural language processing. COOL adds, on top of the self-attention layers of a transformer-based model, outlook attention layers that encode local syntactic context considering word proximity and consider more pair-wise constraints than dynamic convolution operations used by existing approaches. A comparative empirical performance evaluation of an implementation of COOL with different transformer-based approaches confirms the opportunity of improvement over a baseline using the neural language models alone for various natural language processing tasks, including question answering. The proposed approach is competitive with state-of-the-art methods

Analysis of monitoring results of food microbial pathogenic factors in Zhoushan City from 2017 to 2019

Objective To understand the contamination status of microorganisms and pathogenic factors in 19 kinds of food in Zhoushan City, so as to provide basic data for food safety risk monitoring and early warning. Methods A total of 1 246 food samples were collected from 2017 to 2019 according to the requirements of the national risk monitor manual of food contamination and harmful factors from 2017 to 2019. The samples were tested for food microbial pathogenic factors. Results A total of 243 pathogenic factors were detected and the total detection rate was 19.50% (243/1 246). The detection rate of Salmonella in raw meat was 41.67% (30/72), the detection rate of Vibrio parahaemolyticus in bivalve shellfish was 31.58% (48/152), the detection rate of Anisakid in fresh marine fish was 27.00% (27/100), and the detection rate of Staphylococcus aureus in cold-made pastry was 16.25% (13/80). The detection rate of microorganism and its pathogenic factors in bulk food was higher than that in pre-packaged food. The difference was statistically significant (χ2=92.333, P<0.05). In different sampling locations, the highest detection rate of pathogenic factors was found in farmers’ markets (32.54%, 150/461), followed by online stores (25.44%, 29/114) and small restaurants (23.88%, 16/67). Conclusion From 2017 to 2019, 19 types of food on sale in Zhoushan City were contaminated by microorganisms and pathogenic factors at varying degrees. The contamination of microorganisms and pathogenic factors in take-out meals, raw animal meat and bivalve shellfish products was relatively serious. It is suggested to strengthen hygiene supervision on these types of food to prevent the occurrence of foodborne diseases

Role of Leptin in Mood Disorder and Neurodegenerative Disease

The critical regulatory role of leptin in the neuroendocrine system has been widely reported. Significantly, leptin can improve learning and memory, affect hippocampal synaptic plasticity, exert neuroprotective efficacy and reduce the risk of several neuropsychiatric diseases. In terms of depression, leptin could modulate the levels of neurotransmitters, neurotrophic factors and reverse the dysfunction in the hypothalamic-pituitary-adrenal axis (HPA). At the same time, leptin affects neurological diseases during the regulation of metabolic homeostasis. With regards to neurodegenerative diseases, leptin can affect them via neuroprotection, mainly including Alzheimer’s disease and Parkinson’s disease. This review will summarize the mechanisms of leptin signaling within the neuroendocrine system with respect to these diseases and discuss the therapeutic potential of leptin

Selecting an Anti-Malarial Clinical Candidate from Two Potent Dihydroisoquinolones

BACKGROUND: The ongoing global malaria eradication campaign requires development of potent, safe, and cost-effective drugs lacking cross-resistance with existing chemotherapies. One critical step in drug development is selecting a suitable clinical candidate from late leads. The process used to select the clinical candidate SJ733 from two potent dihydroisoquinolone (DHIQ) late leads, SJ733 and SJ311, based on their physicochemical, pharmacokinetic (PK), and toxicity profiles is described. METHODS: The compounds were tested to define their physicochemical properties including kinetic and thermodynamic solubility, partition coefficient, permeability, ionization constant, and binding to plasma proteins. Metabolic stability was assessed in both microsomes and hepatocytes derived from mice, rats, dogs, and humans. Cytochrome P450 inhibition was assessed using recombinant human cytochrome enzymes. The pharmacokinetic profiles of single intravenous or oral doses were investigated in mice, rats, and dogs. RESULTS: Although both compounds displayed similar physicochemical properties, SJ733 was more permeable but metabolically less stable than SJ311 in vitro. Single dose PK studies of SJ733 in mice, rats, and dogs demonstrated appreciable oral bioavailability (60-100%), whereas SJ311 had lower oral bioavailability (mice 23%, rats 40%) and higher renal clearance (10-30 fold higher than SJ733 in rats and dogs), suggesting less favorable exposure in humans. SJ311 also displayed a narrower range of dose-proportional exposure, with plasma exposure flattening at doses above 200 mg/kg. CONCLUSION: SJ733 was chosen as the candidate based on a more favorable dose proportionality of exposure and stronger expectation of the ability to justify a strong therapeutic index to regulators

Discovery of Novel, Orally Bioavailable, Antileishmanial Compounds Using Phenotypic Screening

Leishmaniasis is a parasitic infection that afflicts approximately 12 million people worldwide. There are several limitations to the approved drug therapies for leishmaniasis, including moderate to severe toxicity, growing drug resistance, and the need for extended dosing. Moreover, miltefosine is currently the only orally available drug therapy for this infection. We addressed the pressing need for new therapies by pursuing a two-step phenotypic screen to discover novel, potent, and orally bioavailable antileishmanials. First, we conducted a high-throughput screen (HTS) of roughly 600,000 small molecules for growth inhibition against the promastigote form of the parasite life cycle using the nucleic acid binding dye SYBR Green I. This screen identified approximately 2,700 compounds that inhibited growth by over 65% at a single point concentration of 10 μM. We next used this 2700 compound focused library to identify compounds that were highly potent against the disease-causing intra-macrophage amastigote form and exhibited limited toxicity toward the host macrophages. This two-step screening strategy uncovered nine unique chemical scaffolds within our collection, including two previously described antileishmanials. We further profiled two of the novel compounds for in vitro absorption, distribution, metabolism, excretion, and in vivo pharmacokinetics. Both compounds proved orally bioavailable, affording plasma exposures above the half-maximal effective concentration (EC50) concentration for at least 12 hours. Both compounds were efficacious when administered orally in a murine model of cutaneous leishmaniasis. One of the two compounds exerted potent activity against trypanosomes, which are kinetoplastid parasites related to Leishmania species. Therefore, this compound could help control multiple parasitic diseases. The promising pharmacokinetic profile and significant in vivo efficacy observed from our HTS hits highlight the utility of our two-step phenotypic screening strategy and strongly suggest that medicinal chemistry optimization of these newly identified scaffolds will lead to promising candidates for an orally available anti-parasitic drug

A HALP score-based prediction model for survival of patients with the upper tract urothelial carcinoma undergoing radical nephroureterectomy

The combination of hemoglobin, albumin, lymphocyte, and platelet (HALP) score has been confirmed as an important risk biomarker in several cancers. Hence, we aimed at evaluating the prognostic value of the HALP score in patients with non-metastatic upper tract urothelial carcinoma (UTUC). We retrospectively enrolled 533 of the 640 patients from two centers (315 and 325 patients, respectively) who underwent radical nephroureterectomy (RNU) for UTUC in this study. The cutoff value of HALP was determined using the Youden index by performing receiver operating characteristic (ROC) curve analysis. The relationship between postoperative survival outcomes and preoperative HALP level was assessed using Kaplan-Meier analysis and Cox regression analysis. As a result, the cutoff value of HALP was 28.67 and patients were then divided into HALP<28.67 group and HALP≥28.67 group. Kaplan-Meier analysis and log-rank test revealed that HALP was significantly associated with overall survival (OS) (P<0.001) and progression-free survival (PFS) (P<0.001). Multivariate analysis demonstrated that lower HALP score was an independent risk factor for OS (HR=1.54, 95%CI, 1.14-2.01, P=0.006) and PFS (HR=1.44, 95%CI, 1.07-1.93, P=0.020). Nomograms of OS and PFS incorporated with HALP score were more accurate in predicting prognosis than without. In the subgroup analysis, the HALP score could also stratify patients with respect to survival under different pathologic T stages. Therefore, pretreatment HALP score was an independent prognostic factor of OS and PFS in UTUC patients undergoing RNU

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer