Miracle-dz/UniFAR-FTUs huggingface dataset:
Genome-wide analysis of Brucella melitensis genes required throughout intranasal infection in mice

Brucellae are facultative intracellular Gram-negative coccobacilli that chronically infect various mammals and cause brucellosis. Human brucellosis is among the most common bacterial zoonoses and the vast majority of cases are attributed to B. melitensis. Using transposon sequencing (Tn-seq) analysis, we showed that among 3369 predicted genes of the B. melitensis genome, 861 are required for optimal growth in rich medium and 186 additional genes appeared necessary for survival of B. melitensis in RAW 264.7 macrophages in vitro. As the mucosal immune system represents the first defense against Brucella infection, we investigated the early phase of pulmonary infection in mice. In situ analysis at the single cell level indicates a succession of killing and growth phases, followed by heterogenous proliferation of B. melitensis in alveolar macrophages during the first 48 hours of infection. Tn-seq analysis identified 94 additional genes that are required for survival in the lung at 48 hours post infection. Among them, 42 genes are common to RAW 264.7 macrophages and the lung conditions, including the T4SS and purine synthesis genes. But 52 genes are not identified in RAW 264.7 macrophages, including genes implicated in lipopolysaccharide (LPS) biosynthesis, methionine transport, tryptophan synthesis as well as fatty acid and carbohydrate metabolism. Interestingly, genes implicated in LPS synthesis and β oxidation of fatty acids are no longer required in Interleukin (IL)-17RA-/- mice and asthmatic mice, respectively. This demonstrates that the immune status determines which genes are required for optimal survival and growth of B. melitensis in vivo.
Regeneration of Capto Core 700 resin through high throughput and laboratory scale studies and impact on production of a SARS‐CoV‐2 vaccine candidate

During the development of a SARS‐CoV‐2 vaccine candidate, at the height of the COVID‐19 pandemic, raw materials shortages, including chromatography resins, necessitated the determination of a cleaning in place (CIP) strategy for a multimodal core‐shell resin both rapidly and efficiently. Here, the deployment of high throughput (HT) techniques to screen CIP conditions for cleaning Capto Core 700 resin exposed to clarified cell culture harvest (CCCH) of a SARS‐CoV‐2 vaccine candidate produced in Vero adherent cell culture are described. The best performing conditions, comprised of 30% n‐propanol and ≥0.75 N NaOH, were deployed in cycling experiments, completed with miniature chromatography columns, to demonstrate their effectiveness. The success of the CIP strategy was ultimately verified at the laboratory scale. Here, its impact was assessed across the entire purification process which also included an ultrafiltration/diafiltration step. It is shown that the implementation of the CIP strategy enabled the re‐use of the Capto Core 700 resin for up to 10 cycles without any negative impact on the purified product. Hence, the strategic combination of HT and laboratory‐scale experiments can lead rapidly to robust CIP procedures, even for a challenging to clean resin, and thus help to overcome supply shortages.
WHO drug-resistant TB guidelines 2022: what is new?

In May 2022, WHO released “Rapid communication: key changes to the treatment of drug-resistant tuberculosis”, 1 a prelude to the much-awaited complete version of the guidelines, to be released towards the end of this year. This document is timely and necessary, as with 500,000 new cases of multidrug- or rifampicin-resistant TB (MDR/RR-TB) each year, only 1 in 3 cases receive treatment. Furthermore, the COVID-19 pandemic may have contributed to the further spread of the MDR/RR-TB strains of Mycobacterium tuberculosis. The previous consolidated WHO drug-resistant TB guidelines were issued in 2020, incorporating new data from patients on WHO-recommended longer (>18 months) and shorter (<12 months) MDR-TB regimens. the definition of RR (resistance to rifampicin) and MDR-TB (combined resistance to rifampicin and isoniazid) remain the same, new definitions have been introduced with the addition of pre-XDR-TB (TB caused by MDR/RR-TB strains also resistant to later-generation fluoroquinolones)
CKAMP44 controls synaptic function and strength of relay neurons during early development of the dorsal lateral geniculate nucleus

Relay neurons of the dorsal lateral geniculate nucleus (dLGN) receive inputs from retinal ganglion cells via retinogeniculate synapses. These connections undergo pruning in the first 2 weeks after eye opening. The remaining connections are strengthened several‐fold by the insertion of AMPA receptors (AMPARs) into weak or silent synapses. In this study, we found that the AMPAR auxiliary subunit CKAMP44 is required for receptor insertion and function of retinogeniculate synapses during development. Genetic deletion of CKAMP44 resulted in decreased synaptic strength and a higher number of silent synapses in young (P9–11) mice. Recovery from desensitisation of AMPARs was faster in CKAMP44 knockout (CKAMP44–/–) than in wild‐type mice. Moreover, loss of CKAMP44 increased the probability of inducing plateau potentials, which are known to be important for eye‐specific input segregation and retinogeniculate synapse maturation. The anatomy of relay neurons in the dLGN was changed in young CKAMP44–/– mice showing a transient increase in dendritic branching that normalised during later development (P26–33). Interestingly, input segregation in young CKAMP44–/– mice was not affected when compared to wild‐type mice. These results demonstrate that CKAMP44 promotes maturation and modulates function of retinogeniculate synapses during early development of the visual system without affecting input segregation.
Glaucoma management in congenital ectropion uveae: Surgical outcomes from a large tertiary referral center in South India

Purpose To evaluate the long-term outcomes of glaucoma management in patients with congenital ectropion uveae (CEU) over a period of three decades at a single large referral tertiary eye care center. Methods Retrospective chart review of all patients with CEU treated surgically from 1990 to 2019 was performed. Primary combined trabeculotomy-trabeculectomy (CTT), trabeculectomy with and without mitomycin-C (MMC) (0.2 mg/mL for 1 min) and transscleral cyclophotocoagulation (TSCPC) were performed. Intraocular pressure (IOP) ≥6 and ≤16 mmHg without medications was considered as complete success and IOP≤ 16 mmHg with the use of upto 2 medications as qualified success. Results A total of 26 eyes of 21 patients were identified with a median age of 7 years (range, 6 days to 19 years) at the time of glaucoma surgery. Median follow-up was 51.1 months (range, 7–244.6 months). Primary CTT was performed in 17 eyes (65%), trabeculectomy in 5 eyes (19%) with application of MMC in 2 eyes, and 3 eyes (12%) underwent TSCPC. One painful blind eye (4%) underwent evisceration. Mean IOP reduced from 30.8 ± 7.6 mmHg on a mean of 1.3 ± 0.8 glaucoma medications preoperatively to a mean IOP of 15.2 ± 5.9 mmHg (P < 0.0001) on a mean of 0.2 ± 0.5 medications postoperatively at final follow-up (P = 0.0009). Complete success was achieved in 20 eyes, and qualified success in 2 eyes. Conclusions CTT is a safe and efficacious primary procedure for management of early-onset glaucoma in CEU. Trabeculectomy with or without adjuvant MMC is a viable second line of treatment in late-onset glaucoma with CEU for IOP control.
Effects of Milk Replacer-Based Lactobacillus on Growth and Gut Development of Yaks’ Calves: a Gut Microbiome and Metabolic Study

The host microbiome is a composite of the trillion microorganisms colonizing host bodies. It can be impacted by various factors, including diet, environmental conditions, and physical activities. ABSTRACT The gut microbiota and its metabolic activities are crucial for maintaining host homoeostasis and health, of which the role of probiotics has indeed been emphasized. The current study delves into the performance of probiotics as a beneficial managemental strategy, which further highlights their impact on growth performance, serologic investigation, gut microbiota, and metabolic profiling in yaks’ calves. A field experiment was employed consisting of 2 by 3 factorial controls, including two development stages, namely, 21 and 42 days (about one and a half month), with three different feeding treatments. Results showed a positive impact of probiotic supplements on growth performance by approximately 3.16 kg (P < 0.01) compared with the blank control. Moreover, they had the potential to improve serum antioxidants and biochemical properties. We found that microorganisms that threaten health were enriched in the gut of the blank control with the depletion of beneficial bacteria, although all yaks were healthy. Additionally, the gut was colonized by a microbial succession that assembled into a more mature microbiome, driven by the probiotics strategy. The gut metabolic profiling was also changed significantly after the probiotic strategy, i.e., the concentrations of metabolites and the metabolic pattern, including enrichments in protein digestion and absorption, vitamin digestion and absorption, and biosynthesis of secondary metabolites. In summary, probiotics promoted gut microbiota/metabolites, developing precise interventions and achieving physiological benefits based on intestinal microecology. Hence, it is important to understand probiotic dietary changes to the gut microbiome, metabolome, and the host phenotype. IMPORTANCE The host microbiome is a composite of the trillion microorganisms colonizing host bodies. It can be impacted by various factors, including diet, environmental conditions, and physical activities. The yaks’ calves have a pre-existing imbalance in the intestinal microbiota with an inadequate feeding strategy, resulting in poor growth performance, diarrhea, and other intestinal diseases. Hence, targeting gut microbiota might provide a new effective feeding strategy for enhancing performance and maintaining a healthy intestinal environment. Based on the current findings, milk replacer-based Lactobacillus feeding may improve growth performance and health in yaks’ calves.
Sex differences in the ventilatory responses to exercise in mild to moderate obesity

What is the central question of the study? What are the sex differences in ventilatory responses during exercise in adults with obesity? What is the main finding and its importance? Tidal volume and expiratory flows are lower in females when compared with males at higher levels of ventilation despite small increases in end‐expiratory lung volumes. Since dyspnoea on exertion is a frequent complaint, particularly in females with obesity, careful attention should be paid to unpleasant respiratory symptoms and mechanical ventilatory constraints while prescribing exercise.
Molecular and Functional Characterization of N-Acetyltransferases in Common Marmosets and Pigs

Arylamine N-acetyltransferases (NATs) are drug-metabolizing enzymes that are essential for the metabolism of endogenous substrates and xenobiotics. The molecular characteristics of NATs have been extensively investigated in humans but remain to be investigated in common marmosets and pigs, animal species that are often used in drug metabolism studies. In this study, marmoset NAT1 and pig NAT1 cDNAs were isolated from liver samples and were characterized by molecular analyses and drug-metabolism assays. These NAT genes were intronless and formed gene clusters with one other NAT gene in the genome, just as human NAT genes do. Marmoset NAT1 and pig NAT1 amino acid sequences showed high sequence identities (94% and 85%, respectively) to human NAT1. Phylogenetic analysis indicated that marmoset NAT1 and pig NAT1 were more closely clustered with human NATs than with rat or mouse NATs. Marmoset NAT1 and pig NAT1 mRNAs were expressed in all the tissue types analyzed, with the expression levels being highest in the small intestine. Metabolic assays using recombinant proteins found that marmoset NAT1 and pig NAT1 metabolized human NAT substrates p-aminobenzoic acid, 2-aminofluorene, sulfamethazine, and isoniazid. Marmoset NAT1 and pig NAT1 substantially acetylated p-aminobenzoic acid and 2-aminofluorene relevant human NAT1, but their activities were lower toward sulfamethazine and isoniazid than those of the relevant human NAT2. Therefore, marmoset and pig NATs are functional enzymes with molecular similarities to human NAT1, but their substrate specificities, while similar to human NAT1, differ somewhat from human NAT2. SIGNIFICANCE STATEMENT Marmoset N-acetyltransferase NAT1 and pig NAT1 were identified and showed high sequence identities to human NAT1. These NAT mRNAs were expressed in various tissues. Marmoset and pig NAT1s acetylated typical human NAT substrates, although their substrate specificities differed somewhat from human NAT2. Marmoset NAT1 and pig NAT1 have similarities with human NAT1 in terms of molecular and enzymatic characteristics.
How alternative splicing changes the properties of plant proteins

Abstract Abstract Most plant primary transcripts undergo alternative splicing (AS), and its impact on protein diversity is a subject of intensive investigation. Several studies have uncovered various mechanisms of how particular protein splice isoforms operate. However, the common principles behind the AS effects on protein function in plants have rarely been surveyed. Here, on the selected examples, we highlight diverse tissue expression patterns, subcellular localization, enzymatic activities, abilities to bind other molecules and other relevant features. We describe how the protein isoforms mutually interact to underline their intriguing roles in altering the functionality of protein complexes. Moreover, we also discuss the known cases when these interactions have been placed inside the autoregulatory loops. This review is particularly intended for plant cell and developmental biologists who would like to gain inspiration on how the splice variants encoded by their genes of interest may coordinately work.
Birefringent phase masks for laser beams shaping during laser material processing at imaging plane

Abstract. We present phase masks (PMs) made from birefringent CaCO3 crystal plates to create laser beams at an imaging plane with given shapes and intensity distributions close to flat-top distributions. The principle of PMs is based on creating the phase shift of π or 2π (depending on the initial plate thickness) in linearly polarized radiation passing through etched areas with given shapes. The phase shift in these areas is converted into the intensity distribution at an analyzer output, which can be projected with a demagnification by a high-quality lens into its imaging plane aligned with a microprocessing plane or target. In this research, we provide theoretical discussion of choosing PM configurations. PMs with the square and quadrating square shapes (such configurations are in demand in laser microprocessing and molecular optics) were fabricated by laser-induced microplasma and successfully tested in the experimental setup with a pulsed laser (with a wavelength of 1.06 μm and pulse duration of 120 ns). PMs were also used in this experimental setup for laser ablation of polished steel samples. Contours of footprints on samples were well matched with formed beam shapes.
Significance of the spectral correction of photon counting detector response in material classification from spectral x-ray CT

Abstract. Purpose: Photon counting imaging detectors (PCD) has paved the way for spectral x-ray computed tomography (spectral CT), which simultaneously measures a sample’s linear attenuation coefficient (LAC) at multiple energies. However, cadmium telluride (CdTe)-based PCDs working under high flux suffer from detector effects, such as charge sharing and photon pileup. These effects result in the severe spectral distortions of the measured spectra and significant deviation of the extracted LACs from the reference attenuation curve. We analyze the influence of the spectral distortion correction on material classification performance. Approach: We employ a spectral correction algorithm to reduce the primary spectral distortions. We use a method for material classification that measures system-independent material properties, such as electron density, ρe, and effective atomic number, Zeff. These parameters are extracted from the LACs using attenuation decomposition and are independent of the scanner specification. The classification performance with the raw and corrected data is tested on different numbers of energy bins and projections and different radiation dose levels. We use experimental data with a broad range of materials in the range of 6 ≤ Zeff ≤ 15, acquired with a custom laboratory instrument for spectral CT. Results: We show that using the spectral correction leads to an accuracy increase of 1.6 and 3.8 times in estimating ρe and Zeff, respectively, when the image reconstruction is performed from only 12 projections and the 15 energy bins approach is used. Conclusions: The correction algorithm accurately reconstructs the measured attenuation curve and thus gives better classification performance.
Sensor-based Activity Recognition using Deep Learning: A Comparative Study

With the wide availability of inertial sensors in smartphones and connected objects, interest in sensor-based activity recognition has risen. Yet, recognizing human actions from inertial data remains a challenging task because of the complexity of human movements and of inter-individual differences in movement execution. Recently, approaches based on deep neural networks have shown success on standardized activity recognition datasets, yet few works investigate systematically how these models generalize to other protocols for data collection. We present a study that evaluates the performance of various deep learning architectures for activity recognition from a single inertial measurement unit, on a recognition task combining data from six publicly available datasets. We found that the best performance on this combined dataset is obtained with an approach combining the continuous wavelet transform and 2D convolutional neural networks.
A Mobile Application for on-Demand Scheduling of Health Services

Context: The mass adoption of smartphones is reshaping the digital health market. Problem: Among the technological solutions for digital health exist those specifically for scheduling medical appointments. However, we observed that existing solutions are still professional-centric. Solution: In this work, we first (i) categorize existing scheduling models and then (ii) present a patient-centric mobile application. IS Theory: We use the Customer Focus Theory, taking into account customer satisfaction throughout the development and evaluation of our software. Method: We evaluate our solution using two known methods: (i) a self-assessment using the UXUG-AP technique and (ii) quantitative research using a questionnaire based on the well-known TAM indicators and sentences. Summary results: Our application complies with 84% of the items in the UXUP-AP technique. The usability survey results show that 68.6% of participants consider MedBe easy to use and, 62.9% disagree that using MedBe requires a lot of mental effort. Contribution and impact in the IS area: The main contributions are: (i) categorization of scheduling types, (ii) a mobile application that implements Scheduling 4.0, (iii) user experience evaluation, and (iv) application usability evaluation.
Analysis of variability in sign language hand trajectories: development of generative model

The analysis of human movement poses a well-known challenge that has already been addressed in various ways and needs to be adapted to the type of movement being considered. The focus here is on the analysis of hand movement in sign language. This study aims to characterize and model the different variations present in the data to develop a realistic generative model of hand movement in sign language. We identify two types of variations that play a key role in characterizing human movement: temporal variations and shape variations, i.e., variations in the speed of movement and the geometry of movement. However, separating these variations or understanding their relationship is a non-trivial task. A well-known model for the relationship between time, speed, and geometry is the 2/3 power-law demonstrated for several human movements, mainly constrained and planar. We find that the generalization of this law to a three-dimensional motion is not sufficient to explain variations in hand movement in sign language. We develop a new statistical modeling framework that is flexible and can respect the geometry of the movement signals. The two different variations are identified using the Frenet-Serret representation and modeled by mean geometry, mean speed, and their nonlinear transformations. The nonlinear variations in time and geometry are analyzed by functional principal component analysis. Then the generative model for the hand movement in sign language is built by imposing a joint probability model on the principal coefficients of these components.
Intelligent Information System for Extracting Knowledge from Pharmaceutical Package Inserts

Pharmaceutical package inserts are a rich source of information about medicines. To guide the patient, health professionals need information about the appropriate medication for an illness. This information can be found in the pharmaceutical package inserts. Extracting information from package inserts manually is a challenging task, especially when information is needed quickly and efficiently. Doubts about adverse reactions or interactions with others drugs are common. Automatically extracting information from package inserts can help health professionals to make decisions about therapies and drug prescriptions. This article describes the creation of an Artificial Intelligence model, using a hybrid approach called CRF+LG, which recognizes named entities of medicines, diseases and people in package inserts. The model was tested on two sets of package inserts: for stomach pain and diabetes treatment. This work was developed under the aegis of Soft Systems Theory. This research has a prescriptive character and its evaluation was carried out through the execution of experiments. The analysis of the results was carried out with a quantitative approach. The experiments showed that the model obtained, of measure F, 82.08% in the recognition of entities related to diseases, 59.14% of medicines and 94.26% of people. The main contribution of the article is the creation of a model that automatically recognizes entities named in pharmaceutical package inserts. This model can integrate an Intelligent Information System to assist health professionals in making decisions about therapies and drug prescription.
Energy management and control system for microgrid based wind-PV-battery using multi-agent systems

Energy generation is currently evolving into a smart distribution system that incorporates several green energy resources at a distributed level, ensuring that clean energy is generated without releasing harmful gases, that operational procedures are consistent, and that energy management and supervision arrangements are improved. This paper proposes a multi-agent system-based microgrid energy management and proper control in distributed systems. For the complexity of energy management in distributed systems, a multi-agent system-based decentralized control architecture was developed. The proposed technique is based on several smart agents, each agent is based on the microgrid data for energy management and frequency control. The proposed energy management system based on the multi-agent system was tested by simulation under renewable resource fluctuations and seasonal load demand. The simulation results show that the proposed energy management system proved to be more resilient and high-performance controls than conventional centralized energy control systems.