Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Early-Life Gastrointestinal Microbiota in the Presence of Antibiotics Alters the Severity of Acute DSS-Induced Colitis in Mice

This study investigated resident microbiota in the whole gastrointestinal (GI) tract to explore gut microbiota development in early life and found that early-life antibiotic exposure exacerbated alterations in gut microbiota and murine dextran sulfate sodium (DSS)-induced colitis. Furthermore, the presence of bacteria in the GI tract of mice before birth and the importance of the lactation period in GI microbiota development were confirmed. ABSTRACT Early-life gastrointestinal microbiota development is crucial for physiological development and immunological homeostasis. In the current study, perinatal microbiota and the development of gastrointestinal microbiota in different early-life periods (perinatal, lactation, and postweaning nutrition periods) were explored by using an antibiotic-interfered mouse model and a dextran sulfate sodium-induced colitis mouse model. Gut microbiota samples were collected from mother mice and litters. The results of 16S rRNA gene sequences suggested that microbiota in the gastrointestinal system were present in prenatal fetal mice, and microbiota structures in different parts of the gastrointestinal system of the fetal mice were similar to those in the corresponding gut parts of maternal mice. Microbiota in mucus samples from different regions exhibited higher diversity at birth than at other periods and varied substantially over time with diet change. Moreover, antibiotic treatment in early life affected the composition and diversity of gastrointestinal microbiota in adult mice and enhanced susceptibility to experimental colitis in mice, particularly in the lactation period. This approach of exploring gut microbiota evolution is hoped to provide an enhanced view of how resident microbiota develop in early life, which in turn might facilitate understanding of gut microbiota and related diseases. IMPORTANCE This study investigated resident microbiota in the whole gastrointestinal (GI) tract to explore gut microbiota development in early life and found that early-life antibiotic exposure exacerbated alterations in gut microbiota and murine dextran sulfate sodium (DSS)-induced colitis. Furthermore, the presence of bacteria in the GI tract of mice before birth and the importance of the lactation period in GI microbiota development were confirmed.
The Proteomic Profile of Interstitial Lung Abnormalities.

Rationale Knowledge on biomarkers of interstitial lung disease is incomplete. Interstitial lung abnormalities (ILA) are radiologic changes that may present in its early stages. Objectives To uncover blood proteins associated with ILA using large-scale proteomics methods. Methods Data from two prospective cohort studies, the AGES-Reykjavik study (n=5,259) for biomarker discovery and the Genetic Epidemiology of COPD (COPDGene) study (n=4,899) for replication, were used. Blood proteins were measured using DNA aptamers, targeting over 4,700 protein analytes. The association of proteins with ILA and ILA progression was assessed with regression modelling, as were associations with genetic risk factors. Adaptive LASSO models were applied to bootstrap data samples to discover sets of proteins predictive of ILA and their progression. Measurements and Main Results Of 287 associations, SFTPB (OR 3.71 [95% CI 3.20-4.30], P 4.28×10-67), SCG3AB1 (OR 2.43 [2.13-2.77], P 8.01×10-40) and WFDC2 (OR 2.42 [2.11-2.78], P 4.01×10-36) were most significantly associated with ILA in AGES-Reykjavik and were replicated in COPDGene. In AGES-Reykjavik, levels of SFTPB were associated with the rs35705950 MUC5B promoter polymorphism and SFTPB and WFDC2 had the strongest associations with ILA progression. Multivariate models of ILA in AGES-Reykjavik, ILA in COPDGene and ILA progression in AGES-Reykjavik, had validated areas under the receiver operating characteristic curve of 0.880, 0.826 and 0.824, respectively. Conclusions Novel, replicated associations of ILA, its progression and genetic risk factors with numerous blood proteins are demonstrated as well as machine-learning based models with favourable predictive potential. Several proteins are revealed as potential markers of early fibrotic lung disease.
A randomised phase II study of azacitidine (AZA) alone or with Lenalidomide (LEN), Valproic acid (VPA) or Idarubicin (IDA) in higher‐Risk MDS or low blast AML: GFM's “pick a winner” trial, with the impact of somatic mutations

In order to improve the outcome observed with azacitidine (AZA) in higher‐risk Myelodysplastic syndrome (MDS), its combination with other drugs in MDS must be evaluated. So far, no combination has not been shown to be more effective than AZA alone. AZA‐PLUS was a phase II trial that, in a “pick a winner” approach, randomly assigned patients with higher‐risk MDS, CMML and low blast count AML to: AZA; AZA plus lenalidomide; AZA plus Valproic Acid or AZA plus Idarubicin. 322 patients were included. After six cycles, 69 (21.4%) CR + PR were observed with no benefit from any combination. Median EFS and OS were 17.2 and 19.7 months in the whole cohort, respectively, with no difference across randomised arms. Infection and rates of hospitalisation during the first six cycles were higher in the AZA‐LEN And AZA‐IDA arm, related to increased myelosuppression. Factors associated with better response were IPSS, favourable or intermediate karyotype, haemoglobin, lower circulating blast count, fibrinogen level and lower LDH, while poorer survival was seen in therapy‐related MDS and, in the case of TP53, PTPN11 or CSF3R mutation. The combinations used did not improve the outcome obtained with AZA alone. However, our “pick a winner” randomised strategy may remain useful with potentially more active drugs to be tested in combination with AZA.
Delay-based Passenger Car Equivalent at Signalized Intersections in Iran

Due to their different sizes and operational characteristics, vehicles other than passenger cars have a different influence on traffic operations especially at intersections. The passenger car equivalent (PCE) is the parameter that shows how many passenger cars must be substituted for a specific heavy vehicle to represent its influence on traffic operation. PCE is commonly estimated using headway-based methods that consider the excess headway utilized by heavy vehicles. In this research, the PCE was estimated based on the delay parameter at three signalized intersections in Tehran, Iran. The data collected were traffic volume, travel time for each movement, signalization, and geometric design information. These data were analysed and three different models, one for each intersection, were constructed and calibrated using TRAF-NETSIM simulation software for unsaturated traffic conditions. PCE was estimated under different scenarios and the number of approach movements at each intersection. The results showed that for approaches with only one movement, PCE varies from 1.1 to 1.65. Similarly, for approaches with two and three movements, the PCE varies from 1.07 to 1.99 and from 0.76 to 3.6, respectively. In addition, a general model was developed for predicting PCE for intersections with all of the movements considered. The results obtained from this model showed that the average PCE of 1.5 is similar to the value recommended by the HCM (Highway Capacity Manual) 1985. However, the predicted PCE value of 1.9 for saturated threshold is closer to the PCE value of 2 which was recommended by the HCM 2000 and HCM 2010.
A split green fluorescent protein system to enhance spatial and temporal sensitivity of translating ribosome affinity purification

Translating ribosome affinity purification (TRAP) utilizes transgenic plants expressing a ribosomal protein fused to a tag for affinity purification of ribosomes and the mRNAs that they are translating. These actively translated mRNAs (translatome) can be interrogated by qPCR or RNAseq. Condition- or cell-specific promoters can be utilized to isolate the translatome of specific cell types, at different growth stages and/or in response to environmental variables. While advantageous for revealing differential expression, this approach may not provide sufficient sensitivity when activity of the condition/cell-specific promoter is weak, when ribosome turnover is low in the cells of interest, or when the targeted cells are ephemeral. In these situations, expressing tagged ribosomes under the control of these specific promoters may not yield sufficient polysomes for downstream analysis. Here, we describe a new TRAP system that employs two transgenes: one is constitutively expressed and encodes a ribosomal protein fused to one fragment of a split GFP; the second is controlled by a stimulus-specific promoter and encodes the second GFP fragment fused to an affinity purification tag. In cells where both transgenes are active, the purification tag is attached to ribosomes by bi-molecular folding and assembly of the split GFP fragments. This approach provides increased sensitivity and better temporal resolution because it labels pre-existing ribosomes and does not depend on rapid ribosome turnover. We describe the optimization and key parameters of this system, and then apply it to a plant-pathogen interaction in which spatial and temporal resolution are difficult to achieve with current technologies. Significance Translating ribosome affinity purification (TRAP) has been modified to allow with increased sensitivity the isolation of RNA from sets of cells in which the activity of condition/cell-specific promoters is weak, ribosome turnover is low, or cells whose nature is ephemeral. Based on the use of a split linker constituted of the GFP driven by a pathogen-inducible promoter, this new TRAP system enabled efficient isolation of translated RNA from pathogen-infected leaf cells.
The Quality of Internet Websites for People Experiencing Psychosis: Pilot Expert Assessment

Background Clinicians need to be able to assess the quality of the available information to aid clinical decision-making. The internet has become an important source of health information for consumers and their families. Objective This study aimed to rate the quality of websites with psychosis-related information (to provide clinicians with a basis for recommending material to guide clinical decision-making with consumers and their families), using a validated instrument as well as a purpose-developed checklist, and consider improvement in quality over a 4-year period. Methods Two measures of website quality were used: the DISCERN scale and the Psychosis Website Quality Checklist (PWQC). Terms related to psychosis, including “psychotic,” “psychosis,” “schizophrenia,” “delusion,” and “hallucination,” were entered into Google, and the first 25 results were analyzed. In total, 6 raters with varying health professional backgrounds were used to evaluate the websites across two time points: January-March 2014 and January-March 2018. Results Of the 25 websites rated, only the 6 highest ranked websites achieved a DISCERN score, indicating that they were of “good” quality (51-62 out of a possible 75), while the mean score of the websites (mean 43.96, SD 12.08) indicated an overall “fair” quality. The PWQC revealed that websites scored highly on “availability and usability” (mean 16.82, SD 3.96) but poorly on “credibility” (mean 20.99, SD 6.68), “currency” (mean 5.16, SD 2.62), and “breadth and accuracy” (mean 77.87, SD 23.20). Most sites lacked information about early intervention, recreational drug use and suicide risk, with little change in content over time. Stating an editorial or review process on the website (found in 56% of websites) was significantly associated with a higher quality score on both scales (the DISCERN scale, P=.002; the PWQC, P=.006). Conclusions The information on the internet available for clinicians to recommend to people affected by psychosis tended to be of “fair” quality. While higher-quality websites exist, it is generally not easy way to assess this on face value. Evidence of an editorial or review process was one indicator of website quality. While sites generally provided basic clinical information, most lacked material addressing weighing up risks and benefits of medication and alternatives, the role of coercive treatment and other more contentious issues. Insufficient emphasis is placed on detailed information on early intervention and importance of lifestyle modifications or how families and friends can contribute. These are likely to be the very answers that consumers and carers are seeking and this gap contributes to unmet needs among this group. We suggest that clinicians should be aware of what is available and where there are gaps.
Living an ordinary life – yet not: the everyday life of children and adolescents living with a parent with deafblindness

ABSTRACT Introduction The family life of people living with one family member with deafblindness has been sparsely described. Purpose The aim of the study was to explore how children experience their everyday family life when having a parent with deafblindness. Methods An explorative study in which data have been collected by qualitative interviews of children. Qualitative content analysis has been used for analysing the data. Results Overall theme; Living an ordinary life—yet not, is based on four categories with subcategories. A family like any other describes: Having the same family life as their friends, Acting like other children and It is what it is. Different everyday life describes: Acknowledging differences, Adjusting to the parent’s needs and Financial strain. Being there for the parent describes: Helping the parent and Protecting the parent from harm. Being emotionally affected describes: Feelings of frustration, Feelings of compassion and Need for support. Conclusion Children as relatives of parents with deafblindness have been given a voice. The children live an ordinary life, but at the same time a different ordinary life. Professionals need to take the child and their needs into account when support is given.
Gender and Awareness of Laws on Intimate Partner Violence: A Study Among Bengali, Garo, and Santal Ethnic Communities in Rural Bangladesh

Previous studies on intimate partner violence (IPV) against women in Bangladesh rarely focused on the effectiveness of primary prevention strategies like legal remedies. There is also a lack of studies on the issues among the ethnic minority communities in the country. This study examines the awareness of laws on IPV (such as recognizing the abusive acts and knowing the sanctions) among the ethnic Garo and Santal and mainstream Bengali communities in rural Bangladesh. The study randomly included 1929 married women and men from 24 villages. It appeared that the respondents were not adequately aware of the relevant legal provisions. There were also gender and ethnic differences in the issues. On average, the respondents maintained a low score on recognizing abusive acts. The awareness was further lower among the women compared to the men. In addition, multivariate analysis indicated that the Bengali women had relatively a better understanding of the issues than the Garo and Santal women. However, the Garo men showed poorer awareness of recognizing the abusive acts than the Bengali and Santal men. On the other hand, the respondents also maintained a very insufficient knowledge of the sanctions against such abusive acts, whereas women also showed a lower awareness compared to their male counterparts. Data further revealed that the Santal women had a more inadequate understanding of the issues than the Bengali and Garo women. However, the Garo men had more awareness of the sanctions than the Bengali and Santal men. The study reveals that people are unfamiliar with the laws governing IPV. It shows that understanding legal issues is another field of gender and ethnic inequality in the country. We suggest that there should be intervention to make aware the citizen, mainly women of all ethnicities, to ensure the efficacy of the laws.
Efficient Near-Infrared Luminescence in Lanthanide-Doped Vacancy-Ordered Double Perovskite Cs2ZrCl6 Phosphors via Te4+ Sensitization.

All-inorganic lead-free perovskite-derivative metal halides have shown great promise in optoelectronics, however, it remains challenging to realize efficient near-infrared (NIR) luminescence in these materials. Herein, we report a novel strategy based on Te4+/Ln3+ (Ln = Er, Nd, and Yb) co-doping to achieve efficient NIR luminescence in vacancy-ordered double perovskite Cs2ZrCl6 phosphors, which are excitable by a low-cost near-ultraviolet light-emitting diode (LED) chip. Through sensitization by the spin-orbital allowed 1S0 → 3P1 transition of Te4+, intense and multi-wavelength NIR luminescence originating from the 4f → 4f transitions of Er3+, Nd3+, and Yb3+ was acquired, with a quantum yield of 6.1% for the Er3+ emission. These findings provide a general approach to achieve efficient NIR emission in lead-free metal halides through ns2-metal and lanthanide ion co-doping, thereby opening up a new avenue for exploring NIR-emitting perovskite derivatives towards versatile applications such as NIR-LEDs and bioimaging.
Sequential Regulation of Maternal mRNAs through a Conserved Sequential Regulation of Maternal mRNAs through a Conserved cis-Acting Element in Their 3′ UTRs cis-Acting Element in Their 3′ UTRs

and b -marcepthanol at 95 (cid:2) C for 5 minutes. The samples were loaded in a Mini-PROTEAN TGX 4%–20% gradient SDS-PAGE gels and run at 110V for 1 hour. The proteins were then transferred to a 0.20 m m nitrocellulose membrane at 100V for 1 hour at 4 (cid:2) C. After transfer, the membrane was blocked in 5% milk in PBST for 2 hours at RT and 1 (cid:2) antibody prepared in 5% milk in PBST was added to the membrane and incubated at 4 (cid:2) C O/N. The membrane was rinsed in 0.5% milk in PBST 4-5 times before adding 2 (cid:2) antibody prepared in 5% milk in PBST. After 2 hours the membrane was rinsed 500ng of DNase treated RNA was reverse transcribed using Super Script III. For RT-PCR experiments, 1.5 m L of cDNA was ampliﬁed using 0.5 m L of 10 m M of each reverse and forward primers, 0.5 m L of 10 m M (d)NTP and 0.125 m L Taq Polymerase and 2.5 m L 10XTaq Polymerase Buffer. The thermal cycling conditions for PCR was 95 (cid:2) C for 30 s, 32 cycles of 95 (cid:2) C for 30 s, 3 (cid:2) below the T m of the lowest T m primer for 30 s, 68 (cid:2) C for 1 minute, and 1 cycle of 68 (cid:2) C for 4 minutes. After PCR, 2.8 m L of Orange-G dye was added to each sample and 10 m L of PCR product was ran on a 1% agarose gel stained with ethidium bromide to visualize bands. For qRT-PCR experiments, 0.5 m L of cDNA was ampliﬁed using 5 m L of SYBR green Master Mix, 0.3 m L of 10 m M of each reverse and forward primers. The thermal cycling conditions were as follows: 50 (cid:2) C for 2 min, 95 (cid:2) C for 10 min, 40 cycles at 95 (cid:2) C for 15 s, and 60 (cid:2) C for 60 s. The experiments were carried out in technical triplicate and three biological replicates for each data point.
Near net shape thermoplastic preforming with continuously automated cutting and robotic pick and place processes

Today’s automated production lines for carbon fiber reinforced thermoplastic (CFRTP) parts of the aerospace industry are mostly designed for one special part or application. Changing part geometry or material would lead to a complete re-design of the whole process chain. Here comes the flexible and highly automated the DLR process into game: A continuously automated production line “from fabric delivery to the near net shape pre-form – ready for consolidation”. With the paper and presentation, the authors would like to contribute to the industry’s increasing needs of continuously automated but highly flexible process chains for variable high vol-ume CFRTP parts.
de-Low-Resource Tibetan Dialect Acoustic Modeling Based on Transfer Learning

Deep neural network (DNN) based acoustic model has made great breakthroughs in speech recognition. However, low-resource Sino-Tibetan languages such as Tibetan still need further studies, especially when dealing with dialects. Based on a TDNN acoustic model trained according to lattice-free M-MI criteria, this paper demonstrates baseline systems for two Tibetan dialects: ¨U-Tsang and Amdo. Transfer learning is also employed to improve our systems. Experiment results show that for low resource Tibetan dialect recognition, transfer learning can consistently outperform the baseline
The impact of news media on Bitcoin prices: modelling data driven discourses in the crypto-economy with natural language processing

This paper examines the relationship between events reported in international news via categorical discourses and Bitcoin price. Natural language processing was adopted in this study to model data-driven discourses in the crypto-economy, specifically the Bitcoin market. Using topic modelling, namely Latent Dirichlet Allocation, a text analysis of cryptocurrency articles (N = 4218) published from 60 countries in international news media identified key topics associated with cryptocurrency in the international news media from 2018 to 2020. This study provides empirical evidence that across the corpora of international news articles, 18 key topics were framed around the following categorical macro discourses: crypto-related crime, financial governance, and economy and markets. Analysis shows that the identified discourses may have had a ‘social signal’ effect on movements in the crypto-financial markets, particularly on Bitcoin's price volatility. Results show these specific discourses proved to have a negative effect on Bitcoin's market price, within 24 h of when the crypto news articles were published. Further, the study found that in some cases, the source of the news may have amplified the volatility effect, particularly in terms of geographical region, relative to broader market conditions.
Supervised learning for analysing movement patterns in a virtual reality experiment

The projection into a virtual character and the concomitant illusionary body ownership can lead to transformations of one’s entity. Both during and after the exposure, behavioural and attitudinal changes may occur, depending on the characteristics or stereotypes associated with the embodied avatar. In the present study, we investigated the effects on physical activity when young students experience being old. After assignment (at random) to a young or an older avatar, the participants’ body movements were tracked while performing upper body exercises. We propose and discuss the use of supervised learning procedures to assign these movement patterns to the underlying avatar class in order to detect behavioural differences. This approach can be seen as an alternative to classical feature-wise testing. We found that the classification accuracy was remarkably good for support vector machines with linear kernel and deep learning by convolutional neural networks, when inserting time sub-sequences extracted at random and repeatedly from the original data. For hand movements, associated decision boundaries revealed a higher level of local, vertical positions for the young avatar group, indicating increased agility in their performances. This occurrence held for both guided movements as well as achievement-orientated exercises.
Sequestration of Arsenate from Surface Water Using Chemically Activated Carbon of Black Velvet Tamarind Fruit Shell

Chemically activated carbon of BVT fruit shell was investigated for its potential adsorption functionalities to remove As (V) from surface water in a batch system. The AC showed maximum removal efficiency of approximately 75% depicting Qmax of 0.00018mg/g at an initial sorbate concentration of 0.016mg/L, a contact time of 26min, and a carbon dosage of 1g. The sorption isotherm studies revealed a better fit for Langmuir isotherm. Hence, a homogeneous monolayer surface adsorption process has taken place.