Miracle-dz/UniFAR-FTUs huggingface dataset:
Pilot Clinical Evaluation of PoreSkin: A Human Acellular Dermal Matrix in Burn Scars.

Background An extensive full-thickness wound need a graft, sometime very large. However, donor sites are often limited. Dermal substitutes are among the tissue-engineered products applied to clinical use. PoreSkin, a human acellular dermal matrix (hADM) manufactured by the Faculty of Medicine, Chulalongkorn University, is the first human dermal substitute developed in Thailand. Objective Assess the safety and ability in achieving durable and definitively cosmetic coverage using PoreSkin. Material and Method Eleven hypertrophic burn scars were enrolled in the present study. After scar excision, PoreSkin was placed followed by delayed split-thickness skin graft, three weeks later. The primary outcomes were the engraftment rate of the Poreskin and the skin graft. The secondary outcomes included complications and the final cosmetic appearance. Results The engraftment rate of PoreSkin was 97.7% at day 21. The engraftment rate of autologous sheet skin graft placed over PoreSkin was 91.8%. Regarding the quality of the scar, using the Vancouver scar scale, it shows a statistically significant improvement (p<0.05). No major complications or rejection were observed. Conclusion The performance of PoreSkin as a human acellular dermal matrix (hADM) is comparable to other commercial dermal substitutes in term of engraftment rate, complications, and rejection.
Eighty-eight year-old demented woman lives alone independently

Dear Editor, An 88‐year‐old female with a Mini–Mental State Examination (MMSE)[1] score of 14 lives alone independently in Ogatsu ward, Ishinomaki, Japan. She has hypertension, and she is taken care of by our visiting care service. One day, we found that she could not take her drugs in a punctual manner. Drugs that had been left for 120 days or more were found in her house. She lives alone, cooks, washes, cleans the house, and also takes care of her garden. The Barthel Index[2] was fully scored, showing that her basic activity of daily living (ADL) was independent, whereas her instrumental ADL (IADL) was 4/8 on the IADL scale by Lawton and Brody. [3] Although she could not perform a 3‐word recall and calculation in the MMSE, she can call telephone to her daughter and pay the doctor’s fee correctly. She never travels far by herself as she cannot drive a car.
An Insight on Small Molecule Induced Foot-Print Free Naive Pluripotent Stem Cells in Livestock

Bona fide embryonic stem cell (ESC) lines from livestock species have been challenging to derive and maintain, contrasting mouse and human ESCs. However, induced pluripotent stem cells (iPSC) generated by reprogramming somatic cells tender an option, as they display characteristic features of ESC. The comprehension that induced pluripotent stem cells (iPSC) could be created with in no time also holds the potential of allowing pluripotent cells to be derived from animal models vital in biomedical research. Endeavors to produce bona fide pluripotent stem cells (PSC) from livestock have been going on for more than two decades. But, attempts to derive bona fide livestock iPS cells have met with limited success. Recently it’s been reported that small molecules can augment reprogramming efficiency and may be used to substitute few or all transcription factors used for reprogramming. It is assumed that the reprogramming factors are conserved among species, and this small molecule reprogramming approach will probably apply to livestock species as well. So this review will focus mainly on the accomplishments of small molecules on accelerating cell reprogramming and obtaining naive pluripotency, and raise a new insight on, exogenous genes free, livestock naive iPSC generation with a new bullet, small molecule.
Effect of two cosmetic compounds on the growth, biofilm formation activity, and surface properties of acneic strains of Cutibacterium acnes and Staphylococcus aureus

Increasing popularity of preservative‐free cosmetics necessitates in‐depth research, specifically as bacteria can react to local factors by important metabolic changes. In this respect, investigating the effect of cosmetic preparations on pathogenic strains of commensal species such as acneic forms of Cutibacterium acnes (former Propionibacterium acnes) and bacteria behaving both as commensals and opportunistic pathogens such as Staphylococcus aureus is of major interest. In this study, we studied the effect of commonly used cosmetics, Uriage™ thermal water (UTW) and a rhamnose‐rich polysaccharide (PS291®) on RT4 and RT5 acneic strains of C. acnes and a cutaneous strain of S. aureus. UTW affected the growth kinetic of acneic C. acnes essentially by increasing its generation time and reducing its biomass, whereas only the S. aureus final biomass was decreased. PS291 had more marginal effects. Both compounds showed a marked antibiofilm activity on C. acnes and S. aureus. For S. aureus that appeared essentially due to inhibition of initial adhesion. Cosmetics did not modify the metabolic activity of bacteria. Both C. acnes and S. aureus showed marked hydrophobic surface properties. UTW and PS291 had limited effect on C. acnes but increased the hydrophobic character of S. aureus. This work underlines the effect of cosmetics on cutaneous bacteria and the potential limitations of preservative‐free products.
An improvement scheme for the overall line effectiveness of a production line: A case study

This paper formulates an overall line effectiveness (OLE) improvement scheme for a production line on the basis of Fourier amplitude sensitivity test (FAST) and stochastic Kriging (SK) surrogate model. It is known that improving the key parameters that have great influence on the target performance can bring better effect on the performance than improving other parameters. Thus this paper is concentrated on improving the OLE of a production line through improving multiple key parameters related to the OLE. In the proposed procedure, FAST is used to identify the key parameters for the OLE and a SK surrogate model is built to evaluate the OLE of the production line instead of a simulation model, improving the work efficiency effectively. At last, a comparison with the continuous improvement process (CIP) shows that the scheme formulated with FAST and SK surrogate model is easier to be implemented than the one generated by CIP, because the procedure provided in this paper can give further suggestion to improve the OLE when the improvement of the bottleneck is limited.
Learning Influence-Receptivity Network Structure with Guarantee

Traditional works on community detection from observations of information cascade assume that a single adjacency matrix parametrizes all the observed cascades. However, in reality the connection structure usually does not stay the same across cascades. For example, different people have different topics of interest, therefore the connection structure depends on the information/topic content of the cascade. In this paper we consider the case where we observe a sequence of noisy adjacency matrices triggered by information/event with different topic distributions. We propose a novel latent model using the intuition that a connection is more likely to exist between two nodes if they are interested in similar topics, which are common with the information/event. Specifically, we endow each node with two node-topic vectors: an influence vector that measures how influential/authoritative they are on each topic; and a receptivity vector that measures how receptive/susceptible they are to each topic. We show how these two node-topic structures can be estimated from observed adjacency matrices with theoretical guarantee on estimation error, in cases where the topic distributions of the information/event are known, as well as when they are unknown. Experiments on synthetic and real data demonstrate the effectiveness of our model and superior performance compared to state-of-the-art methods.
Inflammatory bowel disease: new therapies from antisense oligonucleotides

Abstract Inflammatory bowel diseases (IBD) are chronic inflammatory conditions of the gastrointestinal tract encompassing two main clinical entities: Crohn’s disease (CD) and ulcerative colitis (UC). These disorders are characterized by various grades of tissue damage and development of local complications and extra-intestinal manifestations. The cause of IBD remains unknown but accumulating evidence indicates that both CD and UC arise in genetically predisposed individuals as a result of the action of multiple environmental factors, which ultimately trigger excessive and poorly controlled immune response against antigens of the luminal flora. Despite this realization, a full understanding of IBD pathogenesis is still out of reach and, consequently, treatment is far from optimal. However, in recent years, several pathways of intestinal damage have been delineated and the improved knowledge has contributed to the development of new therapies. Various approaches have been used to either inhibit the expression and/or function of inflammatory molecules or enhance counter-regulatory mechanisms. This review summarizes the available pre-clinical and clinical data for antisense oligonucleotides and oligonucleotide-based therapy to provide a comprehensive understanding of the rationale and mechanism of action of these compounds in IBD. Key messages Preclinical studies and clinical trials show that antisense oligonucleotide (ASO)-based therapy could be of benefit in inflammatory bowel diseases. ASOs have an excellent safety profile. Technical issues emerged from clinical trials suggest that changes in drug formulation and/or route of administration could improve ASO efficacy.
Action Learning for 3D Point Cloud Based Organ Segmentation

We propose a novel point cloud based 3D organ segmentation pipeline utilizing deep Q-learning. In order to preserve shape properties, the learning process is guided using a statistical shape model. The trained agent directly predicts piece-wise linear transformations for all vertices in each iteration. This mapping between the ideal transformation for an object outline estimation is learned based on image features. To this end, we introduce aperture features that extract gray values by sampling the 3D volume within the cone centered around the associated vertex and its normal vector. Our approach is also capable of estimating a hierarchical pyramid of non rigid deformations for multi-resolution meshes. In the application phase, we use a marginal approach to gradually estimate affine as well as non-rigid transformations. We performed extensive evaluations to highlight the robust performance of our approach on a variety of challenge data as well as clinical data. Additionally, our method has a run time ranging from 0.3 to 2.7 seconds to segment each organ. In addition, we show that the proposed method can be applied to different organs, X-ray based modalities, and scanning protocols without the need of transfer learning. As we learn actions, even unseen reference meshes can be processed as demonstrated in an example with the Visible Human. From this we conclude that our method is robust, and we believe that our method can be successfully applied to many more applications, in particular, in the interventional imaging space.
eview n vitro models of medulloblastoma : Choosing the right tool for the job

The recently-defined four molecular subgroups of medulloblastoma have required updating of our understanding of in vitro models to include molecular classification and risk stratification features from clinical practice. This review seeks to build a more comprehensive picture of the in vitro systems available for modelling medulloblastoma. The subtype classification and molecular characterisation for over 40 medulloblastoma cell-lines has been compiled, making it possible to identify the strengths and weaknesses in current model systems. Less than half (18/44) of established medulloblastoma cell-lines have been subgrouped. The majority of the subgrouped cell-lines (11/18) are Group 3 with MYC-amplification. SHH cell-lines are the next most common (4/18), half of which exhibit TP53 mutation. WNT and Group 4 subgroups, accounting for 50% of patients, remain underrepresented with 1 and 2 cell-lines respectively. ormal brain co-culture In vitro modelling relies not only on incorporating appropriate tumour cells, but also on using systems with the relevant tissue architecture and phenotype as well as normal tissues. Novel ways of improving the clinical relevance of in vitro models are reviewed, focusing on 3D cell culture, extracellular matrix, co-cultures with normal cells and organotypic slices. This paper champions the establishment of a collaborative online-database and linked cell-bank to catalyse preclinical medulloblastoma research. © 2016 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
A case study of medical big data processing: Data mining for the hyperuricemia

Today, the world comes into a booming information age. With the rapid development of computer and sensors, various bits of data are continuously being generated as time goes by. The amount of data to be processed has entered into the big data category. Data mining is widely used to discover hidden information in the large amounts of data. However, data mining applied to medical databases is a challenging process. The unavailability of large raw data and data complexity are some of the difficulties encountered. This research work proposes a way of dealing with big medical data with a case study of gout disease. Gout is common chronic disease caused by the most important risk factor hyperuricemia. There is no drug to completely cure the gout, the patient is suffering a lot of pain. It is important to control the occurrence of gout and to study the association of gout with other metabolic diseases. This paper discusses methods for the analysis of this complex dataset of this disease, to help get more understanding of the disease and associated diseases. Association Rule is used as the mining algorithm for the data processing. An associated relation is proposed according to the experiments, which applies auxiliary support for doctor's clinical diagnosis and disease research in the local.
Interlinked Visual Tracking and Robotic Manipulation of Articulated Objects

Robotic manipulation tasks require the knowledge on the configuration of the object in use. Since most objects are generally not equipped with any sensor, an estimator is required. Furthermore, if an object is articulated, i.e., includes passive joints, the estimation process has to reconstruct the pose of the object floating base and its joints variables, concurrently with the manipulation control. We address the estimation problem with an online virtual visual servoing paradigm written as a quadratic program. Our estimator is integrated in closed-loop with the manipulation control governing the robot, which is also a quadratic program. Tracking and manipulation experiments, using a humanoid, show the effectiveness of our approach.
Cyber-Threat Mitigation Exploiting the Birth–Death–Immigration Model

We consider the problem of mitigating the effect of malicious cyber-threats spreading across multiple subnets of a data network. Three fundamental issues arise: 1) providing a manageable model of threat propagation; 2) quantifying the danger associated to different subnets; and 3) optimizing the allocation of the countermeasures. We address these issues by providing the following novel contributions. First, a convenient mathematical abstraction of threat propagation is proposed, which employs the birth-and-death process with immigration pioneered by Kendall in his seminal work of 1948. Then, exploiting the notable properties of such a model, we show how to retrieve analytical solutions for optimal resource allocation across subnets, for the case where the parameters of the attack are perfectly known. Finally, the assumption of perfect knowledge is removed, and the unknown attack parameters are estimated using maximum-likelihood estimators.
Measurement of dairy calf behavior prior to onset of clinical disease and in response to disbudding using automated calf feeders and accelerometers

ABSTRACT We determined if feeding and lying behavior, recorded by automatic calf feeding systems (ACFS) and accelerometers, could be used to detect changes in behavior before onset of neonatal calf diarrhea (NCD) or in response to disbudding pain in dairy calves. At 4 d of age, 112 calves had accelerometers attached to their hind leg and were housed in pens with ACFS. Calves were examined daily for signs of illness or injury. Of the 112 calves monitored, 18 were diagnosed with NCD; activities of calves with NCD were then compared with those of 18 healthy controls (calves that had no symptoms of NCD, other illnesses, or injury). Feeding (milk consumption and the number of rewarded and unrewarded visits to the feeder) and lying behavior during the 5 d leading up to calves displaying clinical signs of NCD were analyzed. Calves with NCD performed fewer unrewarded visits and consumed less milk than healthy calves during the 2- and 4-d periods before diagnosis with NCD, respectively. Calves with NCD tended to perform fewer lying bouts than healthy calves over the 5-d period before diagnosis with NCD. At 3 wk of age, a subset of 51 healthy calves were allocated to 1 of 5 treatment groups: (1) sham handling (SHAM, n = 10), (2) cautery disbudding (DB, n = 11), (3) administration of local anesthetic (LA) and DB (LA+DB, n = 11), 4) administration of a nonsteroidal anti-inflammatory drug (NSAID) and DB (NSAID+DB, n = 9), and (5) administration of LA, NSAID and DB (LA+NSAID+DB, n = 10). Feeding and lying behavior were recorded continuously for 24 h pre- and postdisbudding. We found no effect of treatment on the number of rewarded or unrewarded visits to the feeder and milk volume consumed 24 h before administration of treatments. During the 24-h postdisbudding period, SHAM calves performed more unrewarded visits than DB, LA+DB, and NSAID+DB calves, but the number of unrewarded visits did not differ between SHAM and LA+NSAID+DB calves. During the first hour of the posttreatment period we noted a difference in lying times among treatments, with DB and NSAID+DB calves spending less time lying than SHAM calves and lying times being similar between SHAM, LA+DB, and LA+NSAID+DB calves. The ACFS and accelerometers have the potential to automatically gather valuable information regarding health status and pain in calves. Therefore, it may be advantageous to combine both of these measures (ACFS and accelerometers) when evaluating NCD on farm or pain in calves in future research.
Performance Analysis of Secret Precoding-Aided Spatial Modulation With Finite-Alphabet Signaling

The precoding-aided spatial modulation (PSM) is first characterized with respect to its secrecy performance, which shows that the PSM is a secrecy embedded communication scheme when operated in the time-division duplex mode, but experiences security risk under frequency-division duplex mode. Therefore, we extend the PSM to a secret PSM (SPSM) that is suitable for operation in any communications scenarios experiencing passive eavesdropping. In the proposed SPSM, the secrecy performance is enhanced by using a part of transmit power to interfere the eavesdropper’s reception. In this paper, the secrecy performance of SPSM with discrete inputs is comprehensively investigated in terms of both bit error rate and secrecy rate and by both analysis and simulations. Relying on the asymptotic analysis, we also derive the upper and lower bounds for the error performance and secrecy rate of SPSM. Furthermore, we study the power allocation between information and interference transmission in order to maximize SPSM’s secrecy performance. Our studies result in a range of expressions, which are validated by Monte Carlo simulations. Furthermore, our studies demonstrate that the analytical formulas are beneficial to the optimization of SPSM systems for maximizing its security performance.
Dynamic succession of substrate-associated bacterial composition and function during Ganoderma lucidum growth

Background Ganoderma lucidum, a valuable medicinal fungus, is widely distributed in China. It grows alongside with a complex microbial ecosystem in the substrate. As sequencing technology advances, it is possible to reveal the composition and functions of substrate-associated bacterial communities. Methods We analyzed the bacterial community dynamics in the substrate during the four typical growth stages of G. lucidum using next-generation sequencing. Results The physicochemical properties of the substrate (e.g. acidity, moisture, total nitrogen, total phosphorus and total potassium) changed between different growth stages. A total of 598,771 sequences from 12 samples were obtained and assigned to 22 bacterial phyla. Proteobacteria and Firmicutes were the dominant phyla. Bacterial community composition and diversity significantly differed between the elongation stage and the other three growth stages. LEfSe analysis revealed a large number of bacterial taxa (e.g. Bacteroidetes, Acidobacteria and Nitrospirae) with significantly higher abundance at the elongation stage. Functional pathway prediction uncovered significant abundance changes of a number of bacterial functional pathways between the elongation stage and other growth stages. At the elongation stage, the abundance of the environmental information processing pathway (mainly membrane transport) decreased, whereas that of the metabolism-related pathways increased. Discussion The changes in bacterial community composition, diversity and predicted functions were most likely related to the changes in the moisture and nutrient conditions in the substrate with the growth of G. lucidum, particularly at the elongation stage. Our findings shed light on the G. lucidum-bacteria-substrate relationships, which should facilitate the industrial cultivation of G. lucidum.
Ambient Temperature-Induced Device Self-Heating Effects on Multi-Fin Si n-FinFET Performance

Device self-heating effects (SHEs) in nonplanar Si MOS transistors such as fin field-effect transistors (FinFETs) and nanowire FETs have become a serious issue in designing well-tempered CMOS devices for future logic nodes. The device thermal contact resistances are strongly influenced by both the ambient temperature and within device lattice temperature. The ambient heat energy coupling through the thermal contact resistances will strongly impact device SHE in FinFETs due to increase in the surface-to-volume ratio of confined geometry thin Si Fin. In this paper, we report a 3-D quantum-corrected electrothermal numerical device analysis involving a coupled hydrodynamic and thermodynamic transport models for a target Si 3-Fin bulk n-FinFET. The numerical device simulations quantitatively predicted the impact of ambient and electrical contact temperatures on device short-channel effect immunity and performance. The simulation parameters are calibrated with the state-of-the-art Si FinFET measurement data from the literature. Our numerical simulation findings establish the phenomena of ambient temperature-induced device SHE on Si n-FinFETs performance for sub-14-nm technology nodes. The simulation predictions establish the fact that the thermal contact resistances and the within-chip ambient temperature ( ${T}_{A}$ ) have adverse effects on device lumped thermal resistance ( ${R}_{\text {th,eff}}$ ) and performance metrics. Finally, we have numerically analyzed the FinFET design solutions (tapered source and drain regions) to improve the tolerance against the ambient temperature-induced SHE.