Miracle-dz/UniFAR-FTUs huggingface dataset:
Breastfeeding Infants with Ankyloglossia: Insight into Mothers' Experiences.

INTRODUCTION Breastfeeding difficulty from ankyloglossia can affect both the mother and baby in a breastfeeding dyad. With renewed emphasis in today's culture on breast milk, mothers may feel increasing pressure to breastfeed, and the inability for some to do so may cause significant distress. Recently, online parenting forums have seen exponential growth; these forums allow mothers to connect with peers undergoing similar life transitions. The purpose of this study was to review online discussions regarding ankyloglossia to understand mothers' experiences with breastfeeding. MATERIALS AND METHODS We performed an ethnographic content analysis of 76 online threads and 501 posts regarding ankyloglossia based on six domains: (1) initial expectations, (2) breastfeeding complications, (3) questions, (4) diagnosis, (5) treatment, and (6) outcomes. RESULTS About one-fourth of women who participated in online forum discussions had initial expectations to breastfeed, however, many found it impossible due to poor latch or pain. Concerns were frequently exacerbated by healthcare providers who reportedly missed or overlooked ankyloglossia. Although these complications made breastfeeding a challenging experience, mothers often described both subjective and physical improvements after frenotomy. CONCLUSION Breastfeeding difficulty was a commonly voiced concern in online ankyloglossia forums. Forum analysis is an effective way to gain insight into patients' experiences, which allows providers to anticipate concerns and provides more effective counseling.
Coordinate pattern of secretion of luteinizing hormone and testosterone in mature male turkeys under continuous and intermittent photoschedules.

Secretory patterns of luteinizing hormone (LH) and testosterone (T) were determined in sexually mature male turkeys housed under Continuous [14 h light (L): 10 h dark (D), n = 3)] or Intermittent [8 x (1L:2D), n = 3] photoschedules. Jugular vein cannulas were implanted on Day 0 and serial blood samples were taken at 5-min intervals for 12 h on Day 3 and again 4 to 7 d later. Most increases in T concentration were preceded by an increase in LH concentration for both photoschedules. Treatment differences for overall mean T [1.77 +/- . 58 (SE) ng/mL], baseline T (.92 +/- .30 ng/mL), T peak number (6.1 +/- 1.2 per 12 h), T peak amplitude (2.77 +/- 1.70 ng/mL), or T peak length (79 +/- 24 min) were not significant (P > .05). The number of LH peaks was greater in the Continuous than Intermittent group (11.7 +/- .6 vs 6.8 +/- 1.4 per 12 h, P < .05), but there were no treatment differences in overall mean LH (4.56 +/- 2.09 ng/mL), baseline LH (4.10 +/- 2.11 ng/mL), LH peak amplitude (2.80 +/- .92 ng/mL), or LH peak length (15.9 +/- 3.1 min). There were no differences in T or LH concentrations between the photo- and scotophases in the continuous group, and pulses of both were seen in both phases in both lighting treatments. It was concluded that minor differences in patterns of LH secretion may occur between Continuous and Intermittent stimulatory lighting treatments in sexually mature male turkeys.
Benchmarking Commercial Conformer Ensemble Generators

We assess and compare the performance of eight commercial conformer ensemble generators (ConfGen, ConfGenX, cxcalc, iCon, MOE LowModeMD, MOE Stochastic, MOE Conformation Import, and OMEGA) and one leading free algorithm, the distance geometry algorithm implemented in RDKit. The comparative study is based on a new version of the Platinum Diverse Dataset, a high-quality benchmarking dataset of 2859 protein-bound ligand conformations extracted from the PDB. Differences in the performance of commercial algorithms are much smaller than those observed for free algorithms in our previous study (J. Chem. Inf. MODEL 2017, 57, 529-539). For commercial algorithms, the median minimum root-mean-square deviations measured between protein-bound ligand conformations and ensembles of a maximum of 250 conformers are between 0.46 and 0.61 Å. Commercial conformer ensemble generators are characterized by their high robustness, with at least 99% of all input molecules successfully processed and few or even no substantial geometrical errors detectable in their output conformations. The RDKit distance geometry algorithm (with minimization enabled) appears to be a good free alternative since its performance is comparable to that of the midranked commercial algorithms. Based on a statistical analysis, we elaborate on which algorithms to use and how to parametrize them for best performance in different application scenarios.
Paradigm shift in bacteriophage-mediated delivery of anticancer drugs: from targeted ‘magic bullets’ to self-navigated ‘magic missiles’

ABSTRACT Introduction: New phage-directed nanomedicines have emerged recently as a result of the in-depth study of the genetics and structure of filamentous phage and evolution of phage display and phage nanobiotechnology. This review focuses on the progress made in the development of the cancer-targeted nanomaterials and discusses the trends in using phage as a bioselectable molecular navigation system. Areas covered: The merging of phage display technologies with nanotechnology in recent years has proved promising in different areas of medicine and technology, such as medical diagnostics, molecular imaging, vaccine development and targeted drug/gene delivery, which is the focus of this review. The authors used data obtained from their research group and sourced using Science Citation Index (Web of Science) and NCBI PubMed search resources. Expert opinion: First attempts of adapting traditional concepts of direct targeting of tumor using phage-targeted nanomedicines has shown minimal improvements. With discovery and study of biological and technical barriers that prevent anti-tumor drug delivery, a paradigm shift from traditional drug targeting to nanomedicine navigation systems is required. The advanced bacteriophage-driven self-navigation systems are thought to overcome those barriers using more precise, localized phage selection methods, multi-targeting ‘promiscuous’ ligands and advanced multifunctional nanomedicine platforms.
Statistical Analysis of Tract-Tracing Experiments Demonstrates a Dense, Complex Cortical Network in the Mouse

Anatomical tract tracing methods are the gold standard for estimating the weight of axonal connectivity between a pair of pre-defined brain regions. Large studies, comprising hundreds of experiments, have become feasible by automated methods. However, this comes at the cost of positive-mean noise making it difficult to detect weak connections, which are of particular interest as recent high resolution tract-tracing studies of the macaque have identified many more weak connections, adding up to greater connection density of cortical networks, than previously recognized. We propose a statistical framework that estimates connectivity weights and credibility intervals from multiple tract-tracing experiments. We model the observed signal as a log-normal distribution generated by a combination of tracer fluorescence and positive-mean noise, also accounting for injections into multiple regions. Using anterograde viral tract-tracing data provided by the Allen Institute for Brain Sciences, we estimate the connection density of the mouse intra-hemispheric cortical network to be 73% (95% credibility interval (CI): 71%, 75%); higher than previous estimates (40%). Inter-hemispheric density was estimated to be 59% (95% CI: 54%, 62%). The weakest estimable connections (about 6 orders of magnitude weaker than the strongest connections) are likely to represent only one or a few axons. These extremely weak connections are topologically more random and longer distance than the strongest connections, which are topologically more clustered and shorter distance (spatially clustered). Weak links do not substantially contribute to the global topology of a weighted brain graph, but incrementally increased topological integration of a binary graph. The topology of weak anatomical connections in the mouse brain, rigorously estimable down to the biological limit of a single axon between cortical areas in these data, suggests that they might confer functional advantages for integrative information processing and/or they might represent a stochastic factor in the development of the mouse connectome.
Quantifying Differences and Similarities in Whole-Brain White Matter Architecture Using Local Connectome Fingerprints

Quantifying differences or similarities in connectomes has been a challenge due to the immense complexity of global brain networks. Here we introduce a noninvasive method that uses diffusion MRI to characterize whole-brain white matter architecture as a single local connectome fingerprint that allows for a direct comparison between structural connectomes. In four independently acquired data sets with repeated scans (total N=213), we show that the local connectome fingerprint is highly specific to an individual, allowing for an accurate self-versus-others classification that achieved 100% accuracy across 17,398 identification tests. The estimated classification error was approximately one thousand times smaller than fingerprints derived from diffusivity-based measures or region-to-region connectivity patterns. The local connectome fingerprint also revealed neuroplasticity within an individual reflected as a decreasing trend in self-similarity across time, whereas this change was not observed in the diffusivity measures. Moreover, the local connectome fingerprint can be used as a phenotypic marker, revealing 12.51% similarity between monozygotic twins, 5.14% between dizygotic twins, and 4.51% between none-twin siblings. This novel approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome. Author Summary The local organization of white matter architecture is highly unique to individuals, making it a tangible metric of connectomic differences. The variability in local white matter architecture is found to be partially determined by genetic factors, but largely plastic across time. This approach opens a new door for probing the influence of pathological, genetic, social, or environmental factors on the unique configuration of the human connectome.
Time series matrix factorization prediction of internet traffic matrices

Traffic matrices (TMs) are very important for traffic engineering and if they can be predicted, the network operations can be made beforehand. However, existing prediction methods are neither accurate nor efficient in practice. In this paper, we utilize the spatio-temporal property and low rank nature to directly predict the total TMs. The problem is that conventional matrix interpolation only works well when elements are missing uniformly and randomly. But in the case of TMs prediction, an entire part of the matrix is unknown. To solve this problem, we utilize some essential properties of TMs and add the time series forecasting into the matrix interpolation. We analyze our algorithm and evaluate its performance. The experiment result shows that our method can predict TMs under an NMAE of 30% in most cases, even predicting all the elements of next 3 weeks.
Comparative Investigations on Ultra-High Performance Concrete with and without Coarse Aggregates

SUMMARY In the present paper UHPC was produced with crushed basalt with the particle size from 2 to 5 mm. The compressive strength has reached the same magnitude as reactive powder concrete (RPC) in which the maximal aggregate size is smaller than 1.0 mm. The use of the coarse aggregates led not only to the decrease in cementitious paste volume fraction, but also to some changes in mixing process and in mechanical properties. UHPC containing coarse aggregate was easier to be fluidised and homogenized. The mixing time can be shorter than that for RPC. The both tested UHPC exhibited a similar behaviour under compressive stresses, except somewhat different modulus of elasticity and strain at peak stress, which related to the stiffness of the used aggregates. The lower paste volume fraction and the hindrance of the stiffer basalt split resulted in a lower autogenous shrinkage of UHPC containing coarse aggregates.
Renal clearance and intestinal generation of p-cresyl sulfate and indoxyl sulfate in CKD.

BACKGROUND AND OBJECTIVES p-Cresyl sulfate and indoxyl sulfate contribute to cardiovascular disease and progression of renal disease. Renal clearance of both solutes mainly depends on tubular secretion, and serum concentrations are widely dispersed for any given stage of CKD. From this information, it is inferred that estimated GFR is not a suitable proxy of the clearance of these solutes. Formal clearance studies have, however, not been performed to date. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS This study analyzed renal clearances of p-cresyl sulfate and indoxyl sulfate in the Leuven CKD cohort (NCT00441623; inclusion between November of 2005 and September of 2006) and explored their relationship with estimated GFR. Multivariate linear regression models were built to evaluate contributions of estimated GFR, demographics, and generation rates to p-cresyl sulfate and indoxyl sulfate serum concentrations. RESULTS Renal clearances were analyzed in 203 patients with CKD stages 1-5. Indoxyl sulfate clearances (median=17.7, interquartile range=9.4-33.2 ml/min) exceeded p-cresyl sulfate clearances (median=6.8, interquartile range=3.4-12.0 ml/min) by about threefold. A linear relationship was observed between estimated GFR and clearances of p-cresyl sulfate (R(2)=0.50, P<0.001) and indoxyl sulfate (R(2)=0.55, P<0.001). In multivariate regression, p-cresyl sulfate concentrations were associated (R(2)=0.75) with estimated GFR and generation rate (both P<0.001). Indoxyl sulfate concentrations were associated (R(2)=0.74) with estimated GFR, generation rate (both P<0.001), age (P<0.05), and sex (P<0.05). CONCLUSIONS Estimated GFR provides an acceptable estimate of renal clearance of p-cresyl sulfate and indoxyl sulfate. Remarkably, clearances of indoxyl sulfate exceed clearances of p-cresyl sulfate by approximately threefold, suggesting substantial differences between tubular transporter affinities and/or involvement of separate transporter systems for p-cresyl sulfate and indoxyl sulfate.
DM-BLD: differential methylation detection using a hierarchical Bayesian model exploiting local dependency

Motivation: The advent of high-throughput DNA methylation profiling techniques has enabled the possibility of accurate identification of differentially methylated genes for cancer research. The large number of measured loci facilitates whole genome methylation study, yet posing great challenges for differential methylation detection due to the high variability in tumor samples. Results: We have developed a novel probabilistic approach, differential methylation detection using a hierarchical Bayesian model exploiting local dependency (DM-BLD), to detect differentially methylated genes based on a Bayesian framework. The DM-BLD approach features a joint model to capture both the local dependency of measured loci and the dependency of methylation change in samples. Specifically, the local dependency is modeled by Leroux conditional autoregressive structure; the dependency of methylation changes is modeled by a discrete Markov random field. A hierarchical Bayesian model is developed to fully take into account the local dependency for differential analysis, in which differential states are embedded as hidden variables. Simulation studies demonstrate that DM-BLD outperforms existing methods for differential methylation detection, particularly when the methylation change is moderate and the variability of methylation in samples is high. DM-BLD has been applied to breast cancer data to identify important methylated genes (such as polycomb target genes and genes involved in transcription factor activity) associated with breast cancer recurrence. Availability and Implementation: A Matlab package of DM-BLD is available at http://www.cbil. ece.vt.edu/software.htm. Contact: Xuan@vt.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Berberine nanoparticles with enhanced in vitro bioavailability: characterization and antimicrobial activity

Background Berberine is an isoquinoline alkaloid widely used in Ayurveda and traditional Chinese medicine to treat illnesses such as hypertension and inflammatory conditions, and as an anticancer and hepato-protective agent. Berberine has low oral bioavailability due to poor aqueous solubility and insufficient dissolution rate, which can reduce the efficacy of drugs taken orally. In this study, evaporative precipitation of nanosuspension (EPN) and anti-solvent precipitation with a syringe pump (APSP) were used to address the problems of solubility, dissolution rate and bioavailability of berberine. Methods Semi-crystalline nanoparticles (NPs) of 90–110 nm diameter for APSP and 65–75 nm diameter for EPN were prepared and then characterized using differential scanning calorimetry (DSC) and X-ray powder diffractometry (XRD). Thereafter, drug content solubility and dissolution studies were undertaken. Berberine and its NPs were evaluated for their antibacterial activity. Results The results indicate that the NPs have significantly increased solubility and dissolution rate due to conversion of the crystalline structure to a semi-crystalline form. Conclusion Berberine NPs produced by both APSP and EPN methods have shown promising activities against Gram-positive and Gram-negative bacteria, and yeasts, with NPs prepared through the EPN method showing superior results compared to those made with the APSP method and the unprocessed drug.
Coupling of phosphorus recovery to an enhanced biological phosphorus removal process through a sidestream : a pilot scale study

This research was initiated with the purpose to remove and recover phosphorus simultaneously, by coupling a sidestream for phosphorus recovery to an enhanced biological phosphorus removal (EBPR) process. Sidestream process comprised of a phosphorus release unit along with a clarifier connected to the M A P (magnesium ammonium phosphate) crystallizer. To understand the sidestream process and to investigate the optimum operating conditions, the configuration was simulated using ASM2-Delft metabolic bio-P model on A Q U A S I M platform. The simulation exercise revealed that anoxic is the best zone to take sidestream when taken individually and anoxic/anaerobic when taken in combination. In both the cases N : P molar ratio of the supernatant was more than 1:1 which is essential for the recovery of phosphorus as struvite. The minimum hydraulic retention time required in the phosphate release unit was found to be around one to two hours, above which there was no considerable amount of phosphate released. Potentially, up to 78 % of the incoming phosphorus is estimated to be recovered by implementing sidestream technology. Based on the simulation results, sidestream process was successfully implemented at U B C pilot plant for both membrane and conventional enhanced biological phosphorous removal processes (MEBPR and CEBPR). The M A P crystallizer was used to recover phosphorus as struvite. Although, the recovery efficiency obtained was not very high (approximately 60 %), the refined conditions as suggested should yield better results. Sidestream wasting method to control the solid retention time of the process indicated selective increase of phosphorus accumulating organisms in the main EBPR process. Sidestream wasting also reduced the phosphorus rich sludge wasting from the aerobic zone of the EBPR process. Magnesium (Mg) was added to the influent of the process to increase the M g 2 + concentration in the sidestream supernatant to provide better conditions for struvite formation. The CEBPR and M E B P R processes experienced poor phosphorus removal after M g addition was started. More detailed investigation is suggested to look in to the effects of magnesium on the EBPR process along with potassium.
ODINI: Escaping Sensitive Data From Faraday-Caged, Air-Gapped Computers via Magnetic Fields

Air-gapped computers are devices that are kept isolated from the Internet, because they store and process sensitive information. When highly sensitive data is involved, an air-gapped computer might also be kept secluded in a Faraday cage. The Faraday cage prevents the leakage of electromagnetic signals emanating from various computer parts, which may be picked up remotely by an eavesdropping adversary. The air-gap separation, coupled with the Faraday shield, provides a high level of isolation, preventing the potential leakage of sensitive data from the system. In this paper, we show how attackers can bypass Faraday cages and air-gaps in order to leak data from highly secure computers. Our method is based on exploitation of the magnetic field generated by the computer’s CPU. Unlike electromagnetic radiation (EMR), low frequency magnetic fields propagate through the air, penetrating metal shielding such as Faraday cages (e.g., a compass still works inside a Faraday cage). Since the CPU is an essential part of any computer, the magnetic covert channel is relevant to virtually any device with a CPU: desktop PCs, servers, laptops, embedded systems, and Internet of Things (IoT) devices. We introduce a malware codenamed ‘ODINI’ that can control the low frequency magnetic fields emitted from the infected computer by regulating the load of the CPU cores. Arbitrary data can be modulated and transmitted on top of the magnetic emission and received by a magnetic ‘bug’ located nearby. We implement a malware prototype and discuss the design considerations along with the implementation details. We also show that the malicious code does not require special privileges (e.g., root) and can successfully operate from within isolated virtual machines (VMs) as well. Finally, we propose different types of defensive countermeasures such as signal detection and signal jamming to cope with this type of threat (demonstration video: https://www.youtube.com/watch? v=h07iXD-aSCA).
Th-POK regulates mammary gland lactation through mTOR-SREBP pathway

The Th-inducing POK (Th-POK, also known as ZBTB7B or cKrox) transcription factor is a key regulator of lineage commitment of immature T cell precursors. It is yet unclear the physiological functions of Th-POK besides helper T cell differentiation. Here we show that Th-POK is restrictedly expressed in the luminal epithelial cells in the mammary glands that is upregulated at late pregnancy and lactation. Lineage restrictedly expressed Th-POK exerts distinct biological functions in the mammary epithelial cells and T cells in a tissue-specific manner. Th-POK is not required for mammary epithelial cell fate determination. Mammary gland morphogenesis in puberty and alveologenesis in pregnancy are phenotypically normal in the Th-POK-deficient mice. However, Th-POK-deficient mice are defective in triggering the onset of lactation upon parturition with large cellular lipid droplets retained within alveolar epithelial cells. As a result, Th-POK knockout mice are unable to efficiently secret milk lipid and to nurse the offspring. Such defect is mainly attributed to the malfunctioned mammary epithelial cells, but not the tissue microenvironment in the Th-POK deficient mice. Th-POK directly regulates expression of insulin receptor substrate-1 (IRS-1) and insulin-induced Akt-mTOR-SREBP signaling. Th-POK deficiency compromises IRS-1 expression and Akt-mTOR-SREBP signaling in the lactating mammary glands. Conversely, insulin induces Th-POK expression. Thus, Th-POK functions as an important feed-forward regulator of insulin signaling in mammary gland lactation.