Pelvic skeletal metastasis of hepatocellular carcinoma with sarcomatous change: a case report

Sarcomatoid hepatocellular carcinoma (HCC) is a very rare histologic variant of HCC. The characteristic of skeletal metastatic sarcomatoid hepatocellular carcinoma has never been reported. We reported a patient with sarcomatoid hepatocellular carcinoma pelvic metastasis who presented with huge pelvic metastasis that had relatively small osteolytic lesion centrally located accompanied by huge bipeduncular invasive expansile lesions into surrounding soft tissue. The lesion showed almost non-isotope uptake in 99mTc-methylene diphosphonate bone scintigraphy study. He underwent radiotherapy and tumor excision but the tumor rapidly recurred. In addition, serum α-fetoprotein level was never elevated beyond normal limit (< 20 ng/mL) through the whole course of treatment. We considered sarcomatoid hepatocellular carcinoma bone metastasis a highly aggressive lesion with unusual metastatic pattern. Surgical treatment with adequate safe margin in such a huge tumor with hypervascularity and extensive invasion in the pelvis was difficult; and radiotherapy maybe refractory regarding the sarcomatous nature. Therefore, debulking operation with local symptoms control may provide a better quality of life. And the clinical course suggests sarcomatoid hepatocellular carcinoma is derived from the transition of an ordinary hepatocellular carcinoma

Artificial intelligence : A powerful paradigm for scientific research

Y Artificial intelligence (AI) coupled with promising machine learning (ML) techniques well known from computer science is broadly affecting many aspects of various fields including science and technology, industry, and even our day-to-day life. The ML techniques have been developed to analyze high-throughput data with a view to obtaining useful insights, categorizing, predicting, and making evidence-based decisions in novel ways, which will promote the growth of novel applications and fuel the sustainable booming of AI. This paper undertakes a comprehensive survey on the development and application of AI in different aspects of fundamental sciences, including information science, mathematics, medical science, materials science, geoscience, life science, physics, and chemistry. The challenges that each discipline of science meets, and the potentials of AI techniques to handle these challenges, are discussed in detail. Moreover, we shed light on new research trends entailing the integration of AI into each scientific discipline. The aim of this paper is to provide a broad research guideline on fundamental sciences with potential infusion of AI, to help motivate researchers to deeply understand the state-of-the-art applications of AI-based fundamental sciences, and thereby to help promote the continuous development of these fundamental sciences.Peer reviewe

Molecular subtypes predict the preferential site of distant metastasis in advanced breast cancer: a nationwide retrospective study

ObjectiveThis study aimed to explore possible associations between molecular subtypes and site of distant metastasis in advanced breast cancer (ABC).Methods3577 ABC patients were selected from 21 hospitals of seven geographic regions in China from 2012-2014. A questionnaire was designed to collect medical information regarding demographic characteristics, risk factors, molecular subtype, recurrence/metastasis information, and disease-free survival (DFS). The cancers were classified into Luminal A, Luminal B, HER2-enriched and Triple Negative subtypes. Chi-square test and multivariate Cox proportional hazard models were performed to explore the associations between molecular subtypes and distant metastasis sites.ResultsA total of 2393 cases with molecular subtypes information were finally examined. Patients with Luminal A (51.1%) and Luminal B (44.7%) were most prone to bone metastasis, whereas liver metastasis was more frequently observed in HER2-enriched ABC patients (29.1%).The cumulative recurrence and metastasis rates of ABC patients at 36 months of DFS were the most significant within molecular types, of which Triple Negative was the highest (82.7%), while that of Luminal A was the lowest (58.4%). In the adjusted Cox regression analysis, Luminal B, HER2-enriched and Triple Negative subtypes increased the risk of visceral metastasis by 23%, 46% and 87% respectively. In addition, Triple Negative patients had a higher probability of brain metastasis (HR 3.07, 95% CI: 1.04-9.07).ConclusionMolecular subtypes can predict the preferential sites of distant metastasis, emphasizing that these associations were of great help in choices for surveillance, developing appropriate screening and cancer management strategies for follow-up and personalized therapy in ABC patients

Current pretreatment technologies for the development of cellulosic ethanol and biorefineries

Lignocellulosic materials, such as forest, agriculture, and agroindustrial residues, are among the most important resources for biorefineries to provide fuels, chemicals, and materials in such a way to substitute for, at least in part, the role of petrochemistry in modern society. Most of these sustainable biorefinery products can be produced from plant polysaccharides (glucans, hemicelluloses, starch, and pectic materials) and lignin. In this scenario, cellulosic ethanol has been considered for decades as one of the most promising alternatives to mitigate fossil fuel dependence and carbon dioxide accumulation in the atmosphere. However, a pretreatment method is required to overcome the physical and chemical barriers that exist in the lignin–carbohydrate composite and to render most, if not all, of the plant cell wall components easily available for conversion into valuable products, including the fuel ethanol. Hence, pretreatment is a key step for an economically viable biorefinery. Successful pretreatment method must lead to partial or total separation of the lignocellulosic components, increasing the accessibility of holocellulose to enzymatic hydrolysis with the least inhibitory compounds being released for subsequent steps of enzymatic hydrolysis and fermentation. Each pretreatment technology has a different specificity against both carbohydrates and lignin and may or may not be efficient for different types of biomasses. Furthermore, it is also desirable to develop pretreatment methods with chemicals that are greener and effluent streams that have a lower impact on the environment. This paper provides an overview of the most important pretreatment methods available, including those that are based on the use of green solvents (supercritical fluids and ionic liquids)

Questionnaire-Based Maladaptive Decision-Coping Patterns Involved in Binge Eating Among 1013 College Students

Binge Eating Disorder (BED), considered a public health problem because of its impact on psychiatric, physical, and social functioning, merits much attention given its elevation to an independent diagnosis in the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5). Similar with substance use disorders, some neuropsychological and personality constructs are potentially implicated in the onset and development of BED, in which poor decision-making has been suggested to facilitate overeating and BED. The objective of this study was to investigate the associations between decision-coping patterns, monetary decision-making, and binge-eating behavior in young adults. A sample of 1013 college students, equally divided into binge-eating and non-binge-eating groups according to the scores on the Binge Eating Scale (BES), were administered multiple measures of decision-making including the Melbourne Decision-Making Questionnaire (MDMQ), the Delay-discounting Test (DDT), and the Probability Discounting Test (PDT). Compared with the non-binge-eating group, the binge-eating group displayed elevated scores on maladaptive decision-making patterns including Procrastination, Buck-passing, and Hypervigilance. Logistic regression model revealed that only Procrastination positively predicted binge eating. These findings suggest that different dimensions of decision-making may be distinctly linked to binge eating among young adults, with Procrastination putatively identified as a risk trait in the development of overeating behavior, which might promote a better understanding of this disorder

Comparison of impulsivity in non-problem, at-risk and problem gamblers

As a non-substance addiction, gambling disorder represents the model for studying the neurobiology of addiction without toxic consequences of chronic drug use. From a neuropsychological perspective, impulsivity is deemed as a potential construct responsible in the onset and development of drug addiction. The objective of this study was to investigate the associations between impulsivity and gambling status in young adults with varying severity of gambling. A sample of 1120 college students, equally divided into non-problem, at-risk and problem gamblers, were administered multiple measures of impulsivity including the UPPSP Impulsive Behaviors Scale (UPPSP), the Barratt Impulsiveness Scale-11 (BIS-11), and the Delay-discounting Test (DDT). Compared with non-problem gamblers, both at-risk gamblers and problem gamblers displayed elevated scores on Negative Urgency, Positive Urgency, Motor Impulsiveness, and Attentional Impulsiveness. Problem gamblers showed higher scores than at-risk gamblers on Positive Urgency. Logistic regression models revealed that only Negative Urgency positively predicted both at-risk gambling and problem gambling compared to non-problem gambling. These results suggest that dimensions of impulsivity may be differentially linked to gambling behavior in young adults, with Negative Urgency putatively identified as an important impulsivity-related marker for the development of gambling disorder, which may provide a better understanding of the pathogenesis.</p

Microstructure and Properties in Simulated Seawater of Copper-Doped Micro-arc Coatings on TC4 Alloy

Micro-arc oxidation (MAO) ceramic coatings were prepared on TC4 titanium alloys by adding CuSO4 to a (NaPO3)6 base solution. The microstructures of the MAO coatings were characterized by scanning electron microscopy (SEM), energy dispersive (EDS), and X-ray photoelectron spectroscopy (XPS). The corrosion resistance and wear resistance of these coatings were evaluated via hydrochloric acid immersion of weight deficit and friction tests. Those results indicated the presence of Cu in the MAO coating in the form of CuO and Cu2O. Incorporation of CuSO4 results in a thickness and roughness increase in the coating. The coating has a lower coefficient of friction (0.2) upon the addition of 4 g/L of CuSO4. The antibacterial properties of the MAO coatings were maximized at 6 g/L of CuSO4. However, the corrosion resistance of the copper-doped MAO coating did not exceed the undoped coating. This study shows that the addition of CuSO4 to the electrolyte successfully prepared copper-containing micro-arc oxidation coatings, which improved the wear resistance and antibacterial properties of the coating