Miracle-dz/UniFAR-FTUs huggingface dataset:
Treatment of high-burden hepatocellular carcinoma: an oncologist perspective

Hepatocellular carcinoma (HCC) is recognized as a major global healthcare burden. Although there have been tremendous improvements in cancer screening and treatment, HCC mortality rate remains high. Many patients with HCC present late to medical attention and thus are not candidates for curative treatment. They typically have high tumor burden at presentation showing heterogeneity in anatomical factors and biochemical profile. Despite the relatively poor prognosis for these patients, significant improvements can still be made in survival if the optimal treatment modality is chosen. Currently, there is no international consensus on how to manage this group of heterogeneous, high-burden HCC. In this article, we will address this question by reviewing the latest available evidences. Our definition of “high-burden HCC” will be based on three factors: size, number of tumors and the presence of macrovascular invasion. The different treatment modalities, namely surgery, intra-arterial therapy, radiotherapy and systemic therapy, and their respective supportive evidences, will be discussed. In the end, we will summarize with our views on the future direction of research priorities for the management of high-burden HCC.
Air-mass factor formulation for spectroscopic measurements from satellites: application to formaldeh

We present a new formulation for the air mass factor (AMF) to convert slant column measurements of optically thin atmospheric species from space into total vertical columns. Because of atmospheric scattering, the AMF depends on the vertical distribution of the species. We formulate the AMF as the integral of the relative vertical distribution (shape factor) of the species over the depth of the atmosphere, weighted by altitude- dependent coefficients (scattering weights) computed independently from a radiative transfer model. The scattering weights are readily tabulated, and one can then obtain the AMF for any observation scene by using shape factors from a three dimensional (3-D) atmospheric chemistry model for the period of observation. This approach subsequently allows objective evaluation of the 3-D model with the observed vertical columns, since the shape factor and the vertical column in the model represent two independent pieces of information. We demonstrate the AMF method by using slant column measurements of formaldehyde at 346 nm from the Global Ozone Monitoring Experiment satellite instrument over North America during July 1996. Shape factors are computed with the Global Earth Observing System CHEMistry (GEOS-CHEM) global 3-D model and are checked for consistency with the few available aircraft measurements. Scattering weights increase by an order of magnitude from the surface to the upper troposphere. The AMFs are typically 20-40% less over continents than over the oceans and are approximately half the values calculated in the absence of scattering. Model-induced errors in the AMF are estimated to be  10%. The GEOS-CHEM model captures 50% and 60% of the variances in the observed slant and vertical columns, respectively. Comparison of the simulated and observed vertical columns allows assessment of model bias.
The molecular heterogeneity of sporadic colorectal cancer with different tumor sites in Chinese patients

Purpose To assess the biological variability of clinical meaningful molecular markers and their clinical correlations in Chinese patients with colorectal cancer (CRC). Materials and methods In this prospective observational study, frequencies and clinico-pathological features of RAS and BRAFV600E mutations, deficiency of DNA mismatch repair (dMMR) were evaluated in patients with colorectal cancer staged I-IV. The molecular heterogeneity between right-sided and left-sided colorectal cancers was studied in our series by classifying patients with different mutations and dMMR status. Results Among 400 evaluable patients, mutations in KRAS exon 2, exon 3 or 4, NRAS and BRAFV600E were detected in 36%, 7.5%, 3.5% and 2.5%, respectively. RAS mutations were significantly higher in metastatic CRCs (56.4% vs. 43.1%, p=0.015) and right-sided CRCs (62.5% vs 41.7%, p=0.003). In 212 RAS wild-type patients, V600E mutation was higher in older patients (9.5% vs. 2.2%, p=0.017), women (9.2% vs. 2.2%, p=0.021) and right-sided CRCs (10.5% vs. 3.4%, p=0.06). dMMR was detected in 7.75% of all stages of CRCs, with the highest dMMR rate of 40% in stage II right-sided colon cancer. Conclusions By assessing the mutations and clinical correlations of RAS and BRAF genes, and dMMR status, similar RAS mutation, dMMR frequency and lower BRAF mutation was observed in Chinese patients compared to western patients. A distinct molecular heterogeneity was found between patients with right-sided and left-sided CRCs.
How Does a Helicase Unwind DNA? Insights from RecBCD Helicase

DNA helicases are a class of molecular motors that catalyze processive unwinding of double stranded DNA. In spite of much study, we know relatively little about the mechanisms by which these enzymes carry out the function for which they are named. Most current views are based on inferences from crystal structures. A prominent view is that the canonical ATPase motor exerts a force on the ssDNA resulting in “pulling” the duplex across a “pin” or “wedge” in the enzyme leading to a mechanical separation of the two DNA strands. In such models, DNA base pair separation is tightly coupled to ssDNA translocation of the motors. However, recent studies of the Escherichia coli RecBCD helicase suggest an alternative model in which DNA base pair melting and ssDNA translocation occur separately. In this view, the enzyme‐DNA binding free energy is used to melt multiple DNA base pairs in an ATP‐independent manner, followed by ATP‐dependent translocation of the canonical motors along the newly formed ssDNA tracks. Repetition of these two steps results in processive DNA unwinding. We summarize recent evidence suggesting this mechanism for RecBCD helicase action.
AD-A 26 6 960 Segmenting Textured 3 D Surfaces Using the SpacelFrequency Representation

Segmenting 3D textured surfaces is critical for general image understanding. Unfortunately, current efforts at automatically understanding image texture are based on assumptions that make this goal impossible. Texture segmentation research assumes that the textures are flat and viewed from the front, while shape-from-texture work assumes that the textures have already been segmented. This deadlock means that none of these algorithms can be successfully applied to images of 3D textured surfaces. We have developed an algorithm that can segment an image containing nonfrontally viewed, planar, periodic textures. We use the spectrogram to compute local surface normals from many different regions of the image. This algorithm does not require unreliable image feature detection. Based on these surface normals, we compute a "frontalized" version of the local power spectrum which shows what the region's power spectrum would look like if viewed from the front. If neighboring regions have similar frontalized power spectra, they are merged. To our knowledge, this is the first program that can segment 3D textured surfaces by explicitly accounting for shape effects.
Changes of ferrous iron and its transporters after intracerebral hemorrhage in rats.

OBJECTIVE Ferrous iron is a major source inducing oxidative stress after intracerebral hemorrhage (ICH). Divalent metal transporter1 (DMT1) is the important and well-known plasma membrane transport protein which was proved to be involved in the transport of free ferrous iron in mammals. Ferroportin 1 (FPN1) is the unique exporter of ferrous iron from mammalian cells. The role of DMT1 and FPN1 in brain after ICH is still not elucidated. Therefore, we measure the expression of DMT1 and FPN1, to explore the correlations between ferrous iron and its specific transporters after ICH. METHODS Ninety-six Sprague-Dawley rats received intra-striatal infusions of 0.5 U type IV collagenase to establish ICH model. Ferrous iron content in brain was determined using Turnbull's method. DMT1 and FPN1 expression were examined by immunohistochemical staining and Real-Time quantitative polymerase chain reaction (RT-PCR). With the use of confocal laser microscopy, we determined the colocalization of DMT1 and FPN1 at 1, 3, 7 and 14 days after ICH. RESULTS Ferrous iron deposition was shown in the perihematomal zone as early as 1 day after ICH; it reached a peak after 7 days and was not elevated within 14 days following ICH. The expression of the DMT1 upregulated and reached to peak at day 7 after ICH. FPN1 reached a plateau at 3 days post-ICH. Expression levels of DMT1 and FPN1 were in parallel with ferrous iron deposition. There was a positive correlation between FPN1 and DMT1. DMT1 mainly localized in the cytoplasm of glias and neurons. FPN1 were mostly distributed on the membrane of endothelial cells and glias. Confocal microscope showed that DMT1 colocalized with FPN1. CONCLUSIONS DMT1 and FPN1 are positively influenced by ferrous iron status in brain after ICH. DMT1 and FPN1 attenuate iron overload after ICH via increasing transmembrane iron export.
Study of Cured Surface LED Array Multi-shadow Problem Based on Taguchi Method

Multi-shadow is an important problem for the reading lamp. In order to analyze the control factors of the multi-shadow of LED array on the curved surface plate,some experiments were designed by applying Taguchi method and simulated via Trace Pro software. After that,ANOVA theory was integrated to evaluate the influence of the control factors to the illumination. So that the control factors can be optimized efficiently. The experiment results show that the number of LEDs is the main influence on multi-shadow( 50. 17%) and the optimum combination of minimum multi-shadow is 1. 19 mm. Furthermore,the best combination of the control factors can be obtained by adjusting the angle between the LED chips and the optical axis.
Activation of NK Cells by an Endocytosed Receptor for Soluble HLA-G

Signaling from endosomes is emerging as a mechanism by which selected receptors provide sustained signals distinct from those generated at the plasma membrane. The activity of natural killer (NK) cells, which are important effectors of innate immunity and regulators of adaptive immunity, is controlled primarily by receptors that are at the cell surface. Here we show that cytokine secretion by resting human NK cells is induced by soluble, but not solid-phase, antibodies to the killer cell immunoglobulin-like receptor (KIR) 2DL4, a receptor for human leukocyte antigen (HLA)-G. KIR2DL4 was constitutively internalized into Rab5-positive compartments via a dynamin-dependent process. Soluble HLA-G was endocytosed into KIR2DL4–containing compartments in NK cells and in 293T cells transfected with KIR2DL4. Chemokine secretion induced by KIR2DL4 transfection into 293T cells occurred only with recombinant forms of KIR2DL4 that trafficked to endosomes. The profile of genes up-regulated by KIR2DL4 engagement on resting NK cells revealed a proinflammatory/proangiogenic response. Soluble HLA-G induced secretion of a similar set of cytokines and chemokines. This unique stimulation of resting NK cells by soluble HLA-G, which is endocytosed by KIR2DL4, implies that NK cells may provide useful functions at sites of HLA-G expression, such as promotion of vascularization in maternal decidua during early pregnancy.
Effects of Corn Steep Liquor Addition into Cassava Tubers during Retting

In this study, the effects of corn steep liquor addition to cassava tubers during retting were monitored. Peeled and washed Cassava tubers were cut to 4cm weighed and then soaked in different sample buckets containing 100.0%, 80:20%, 60:40%, 20: 80% and 0:100% water to corn steep liquor ratio. The Temperature, PH value and degree of softness was monitored. The highest temperature recorded was 30 o C at a pH of 3.75. It was observed that corn steep liquor increases the period of fermentation from 4 to 8days. When the corn steep liquor was neutralized with NaoH solution to PH 4.69 from 3.98, period of fermentation was reduced to 5days showing that the high acidity of the raw corn steep liquor was detrimental to cassava softening process.
Targeted Deep Sequencing in Multiple-Affected Sibships of European Ancestry Identifies Rare Deleterious Variants in PTPN22 That Confer Risk for Type 1 Diabetes

Despite finding more than 40 risk loci for type 1 diabetes (T1D), the causative variants and genes remain largely unknown. Here, we sought to identify rare deleterious variants of moderate-to-large effects contributing to T1D. We deeply sequenced 301 protein-coding genes located in 49 previously reported T1D risk loci in 70 T1D cases of European ancestry. These cases were selected from putatively high-risk families that had three or more siblings diagnosed with T1D at early ages. A cluster of rare deleterious variants in PTPN22 was identified, including two novel frameshift mutations (ss538819444 and rs371865329) and two missense variants (rs74163663 and rs56048322). Genotyping in 3,609 T1D families showed that rs56048322 was significantly associated with T1D and that this association was independent of the T1D-associated common variant rs2476601. The risk allele at rs56048322 affects splicing of PTPN22, resulting in the production of two alternative PTPN22 transcripts and a novel isoform of LYP (the protein encoded by PTPN22). This isoform competes with the wild-type LYP for binding to CSK and results in hyporesponsiveness of CD4+ T cells to antigen stimulation in T1D subjects. These findings demonstrate that in addition to common variants, rare deleterious variants in PTPN22 exist and can affect T1D risk.
The evolution of drug resistance in clinical isolates of Candida albicans

Candida albicans is both a member of the healthy human microbiome and a major pathogen in immunocompromised individuals. Infections are typically treated with azole inhibitors of ergosterol biosynthesis often leading to drug resistance. Studies in clinical isolates have implicated multiple mechanisms in resistance, but have focused on large-scale aberrations or candidate genes, and do not comprehensively chart the genetic basis of adaptation. Here, we leveraged next-generation sequencing to analyze 43 isolates from 11 oral candidiasis patients. We detected newly selected mutations, including single-nucleotide polymorphisms (SNPs), copy-number variations and loss-of-heterozygosity (LOH) events. LOH events were commonly associated with acquired resistance, and SNPs in 240 genes may be related to host adaptation. Conversely, most aneuploidies were transient and did not correlate with drug resistance. Our analysis also shows that isolates also varied in adherence, filamentation, and virulence. Our work reveals new molecular mechanisms underlying the evolution of drug resistance and host adaptation. DOI: http://dx.doi. org/10.7554/eLife.00662. 001
Improving Ammonia Emission Modeling and Inventories by Data Mining and Intelligent Interpretation of the National Air Emission Monitoring Study Database

Abstract: Ammonia emission is one of the greatest environmental concerns in sustainable agriculture development. Several limitations and fundamental problems associated with the current agricultural ammonia emission modeling and emission inventories have been identified. They were associated with a significant disconnection between field monitoring data and knowledge about the data. Comprehensive field measurement datasets have not been fully exploited for scientific research and emission regulations. This situation can be considerably improved if the currently available data are better interpreted and the new knowledge is applied to update ammonia emission modeling techniques. The world’s largest agricultural air quality monitoring database with more than 2.4 billion data points has recently been created by the United States’ National Air Emission Monitoring Study. New approaches of data mining and intelligent interpretation of the database are planned to uncover new knowledge and to answer a series of questions that have been raised. The expected results of this new research idea include enhanced fundamental understanding of ammonia emissions from animal agriculture and improved accuracy and scope in regional and national ammonia emission inventories.
Genetic Patterns of Domestication in Pigeonpea (Cajanus cajan (L.) Millsp.) and Wild Cajanus Relatives

Pigeonpea (Cajanus cajan) is an annual or short-lived perennial food legume of acute regional importance, providing significant protein to the human diet in less developed regions of Asia and Africa. Due to its narrow genetic base, pigeonpea improvement is increasingly reliant on introgression of valuable traits from wild forms, a practice that would benefit from knowledge of its domestication history and relationships to wild species. Here we use 752 single nucleotide polymorphisms (SNPs) derived from 670 low copy orthologous genes to clarify the evolutionary history of pigeonpea (79 accessions) and its wild relatives (31 accessions). We identified three well-supported lineages that are geographically clustered and congruent with previous nuclear and plastid sequence-based phylogenies. Among all species analyzed Cajanus cajanifolius is the most probable progenitor of cultivated pigeonpea. Multiple lines of evidence suggest recent gene flow between cultivated and non-cultivated forms, as well as historical gene flow between diverged but sympatric species. Evidence supports that primary domestication occurred in India, with a second and more recent nested population bottleneck focused in tropical regions that is the likely consequence of pigeonpea breeding. We find abundant allelic variation and genetic diversity among the wild relatives, with the exception of wild species from Australia for which we report a third bottleneck unrelated to domestication within India. Domesticated C. cajan possess 75% less allelic diversity than the progenitor clade of wild Indian species, indicating a severe “domestication bottleneck” during pigeonpea domestication.
Structure dependence of reduced saturation current influenced by source and drain resistances for 17 nm MOSFETs

In this work, we investigated the structure dependence of source and drain resistances on saturation currents for 17 nm bulk, SOI and Multi-Gate (MG) MOSFETs. An analytical saturation current model is proposed by considering with the higher order effects of source and drain resistances. For each structure, the saturation current (IDsat) were calculated by using the analytical current model. The reduction rates of the saturation currents for bulk, SOI and MG MOSFETs are 20.0, 21.6 and 19.7 %, respectively. It can be found that the reduction rate of SOI MOSFET is the largest. In order to find the physical reasons of the structure dependence, expansion components are analyzed. As a result, we found that the ratio of source resistance to channel resistance is the highly influential part.
Metal complexes in cancer therapy – an update from drug design perspective

In the past, metal-based compounds were widely used in the treatment of disease conditions, but the lack of clear distinction between the therapeutic and toxic doses was a major challenge. With the discovery of cisplatin by Barnett Rosenberg in 1960, a milestone in the history of metal-based compounds used in the treatment of cancers was witnessed. This forms the foundation for the modern era of the metal-based anticancer drugs. Platinum drugs, such as cisplatin, carboplatin and oxaliplatin, are the mainstay of the metal-based compounds in the treatment of cancer, but the delay in the therapeutic accomplishment of other metal-based compounds hampered the progress of research in this field. Recently, however, there has been an upsurge of activities relying on the structural information, aimed at improving and developing other forms of metal-based compounds and nonclassical platinum complexes whose mechanism of action is distinct from known drugs such as cisplatin. In line with this, many more metal-based compounds have been synthesized by redesigning the existing chemical structure through ligand substitution or building the entire new compound with enhanced safety and cytotoxic profile. However, because of increased emphasis on the clinical relevance of metal-based complexes, a few of these drugs are currently on clinical trial and many more are awaiting ethical approval to join the trial. In this review, we seek to give an overview of previous reviews on the cytotoxic effect of metal-based complexes while focusing more on newly designed metal-based complexes and their cytotoxic effect on the cancer cell lines, as well as on new approach to metal-based drug design and molecular target in cancer therapy. We are optimistic that the concept of selective targeting remains the hope of the future in developing therapeutics that would selectively target cancer cells and leave healthy cells unharmed.
Adaptive Super Twisting Controller for a quadrotor UAV

In this paper we present a robust quadrotor controller for tracking a reference trajectory in presence of uncertainties and disturbances. A Super Twisting controller is implemented using the recently proposed gain adaptation law [1], [2], which has the advantage of not requiring the knowledge of the upper bound of the lumped uncertainties. The controller design is based on the regular form of the quadrotor dynamics, without separation in two nested control loops for position and attitude. The controller is further extended by a feedforward dynamic inversion control that reduces the effort of the sliding mode controller. The higher order quadrotor dynamic model and proposed controller are validated using a SimMechanics physical simulation with initial error, parameter uncertainties, noisy measurements and external perturbations.
Lecture Video Indexing and Retrieval Using Topic Keywords

1 Abstract — In this paper, we propose a framework to help users to search and retrieve the portions in the lecture video of their interest. This is achieved by temporally segmenting and indexing the lecture video using the topic keywords. We use transcribed text from the video and documents relevant to the video topic extracted from the web for this purpose. The keywords for indexing are found by applying the non-negative matrix factorization (NMF) topic modeling techniques on the web documents. Our proposed technique first creates indices on the transcribed documents using the topic keywords, and these are mapped to the video to find the start and end time of the portions of the video for a particular topic. This time information is stored in the index table along with the topic keyword which is used to retrieve the specific portions of the video for the query provided by the users.