A large-scale study on the prevalence of math anxiety in Qatar

BACKGROUND

Math anxiety (MA) is a worldwide appearing academic anxiety that can affect student mental health and deter students from math and science-related career choices.

METHOD

Using the Arabic version of the Modified-Abbreviated Math Anxiety Scale (m-AMAS), the prevalence of MA was investigated in a very large sample of students (N = 10093) from grades 7 to 12 in Qatar.

RESULTS

The results showed a better fit to the original two-factor model of the m-AMAS (learning MA and Evaluation MA) than to a single-factor solution. This two-factor model was also confirmed in each grade. Notably, the distribution of MA scores was right-skewed, especially for learning MA. Using the inter-quartiles ranges, norms for MA were provided: A score of ≤16 indicates low MA whereas a score of ≥30 identifies high MA. Previous studies conducted in Western countries defined high math-anxious students as those who score above the 90th percentile corresponding to a score of 30 on the m-AMAS. Using this cut-off criterion, the current study found that one-fifth of students in Qatar were highly math-anxious, with a higher proportion of females than males. We also calculated the percentage of participants selecting each response category for each questionnaire item. Results showed that attending a long math class was the context that elicited the highest levels of learning MA. In contrast, having an unexpected math test was the situation that triggered the highest levels of evaluation MA.

CONCLUSION

The prevalence of MA might vary across different cultures.

An optimized CT-dense agent perfusion and micro-CT imaging protocol for chick embryo developmental stages

Compared to classical techniques of morphological analysis, micro-CT (μ-CT) has become an effective approach allowing rapid screening of morphological changes. In the present work, we aimed to provide an optimized micro-CT dense agent perfusion protocol and μ-CT guidelines for different stages of chick embryo cardiogenesis. Our study was conducted over a period of 10 embryonic days (Hamburger-Hamilton HH36) in chick embryo hearts. During the perfusion of the micro-CT dense agent at different developmental stages (HH19, HH24, HH27, HH29, HH31, HH34, HH35, and HH36), we demonstrated that durations and volumes of the injected contrast agent gradually increased with the heart developmental stages contrary to the flow rate that was unchanged during the whole experiment. Analysis of the CT imaging confirmed the efficiency of the optimized parameters of the heart perfusion.

A loss-of-function AGTR1 variant in a critically-ill infant with renal tubular dysgenesis: case presentation and literature review

BACKGROUND

Renal tubular dysgenesis (RTD) is a severe disorder with poor prognosis significantly impacting the proximal tubules of the kidney while maintaining an anatomically normal gross structure. The genetic origin of RTD, involving variants in the ACE, REN, AGT, and AGTR1 genes, affects various enzymes or receptors within the Renin angiotensin system (RAS). This condition manifests prenatally with oligohydramninos and postnatally with persistent anuria, severe refractory hypotension, and defects in skull ossification.

CASE PRESENTATION

In this report, we describe a case of a female patient who, despite receiving multi vasopressor treatment, experienced persistent hypotension, ultimately resulting in early death at five days of age. While there was a history of parental consanguinity, no reported family history of renal disease existed. Blood samples from the parents and the remaining DNA sample of the patient underwent Whole Genome Sequencing (WGS). The genetic analysis revealed a rare homozygous loss of function variant (NM_000685.5; c.415C > T; p.Arg139*) in the Angiotensin II Receptor Type 1 (AGTR1) gene.

CONCLUSION

This case highlights the consequence of loss-of-function variants in AGTR1 gene leading to RTD, which is characterized by high mortality rate at birth or during the neonatal period. Furthermore, we provide a comprehensive review of previously reported variants in the AGTR1 gene, which is the least encountered genetic cause of RTD, along with their associated clinical features.

Burden of Mendelian disorders in a large Middle Eastern biobank

BACKGROUND

Genome sequencing of large biobanks from under-represented ancestries provides a valuable resource for the interrogation of Mendelian disease burden at world population level, complementing small-scale familial studies.

METHODS

Here, we interrogate 6045 whole genomes from Qatar-a Middle Eastern population with high consanguinity and understudied mutational burden-enrolled at the national Biobank and phenotyped for 58 clinically-relevant quantitative traits. We examine a curated set of 2648 Mendelian genes from 20 panels, annotating known and novel pathogenic variants and assessing their penetrance and impact on the measured traits.

RESULTS

We find that 62.5% of participants are carriers of at least 1 known pathogenic variant relating to recessive conditions, with homozygosity observed in 1 in 150 subjects (0.6%) for which Peninsular Arabs are particularly enriched versus other ancestries (5.8-fold). On average, 52.3 loss-of-function variants were found per genome, 6.5 of which affect a known Mendelian gene. Several variants annotated in ClinVar/HGMD as pathogenic appeared at intermediate frequencies in this cohort (1-3%), highlighting Arab founder effect, while others have exceedingly high frequencies (> 5%) prompting reconsideration as benign. Furthermore, cumulative gene burden analysis revealed 56 genes having gene carrier frequency > 1/50, including 5 ACMG Tier 3 panel genes which would be candidates for adding to newborn screening in the country. Additionally, leveraging 58 biobank traits, we systematically assess the impact of novel/rare variants on phenotypes and discover 39 candidate large-effect variants associating with extreme quantitative traits. Furthermore, through rare variant burden testing, we discover 13 genes with high mutational load, including 5 with impact on traits relevant to disease conditions, including metabolic disorder and type 2 diabetes, consistent with the high prevalence of these conditions in the region.

CONCLUSIONS

This study on the first phase of the growing Qatar Genome Program cohort provides a comprehensive resource from a Middle Eastern population to understand the global mutational burden in Mendelian genes and their impact on traits in seemingly healthy individuals in high consanguinity settings.

Novel Synonymous Variant in IL7R Causes Preferential Expression of the Soluble Isoform

PURPOSE

The interleukin-7 receptor (IL-7R) is primarily expressed on lymphoid cells and plays a crucial role in the development, proliferation, and survival of T cells. Autosomal recessive mutations that disrupt IL-7Rα chain expression give rise to a severe combined immunodeficiency (SCID), which is characterized by lymphopenia and a T-B+NK+ phenotype. The objective here was to diagnose two siblings displaying the T-B+NK+ SCID phenotype as initial clinical genetic testing did not detect any variants in known SCID genes.

METHODS

Whole genome sequencing (WGS) was utilized to identify potential variants causing the SCID phenotype. Splicing prediction tools were employed to assess the deleterious impact of the mutation. Polymerase Chain Reaction (PCR), Sanger sequencing, flow cytometry, and ELISA were then used to validate the pathogenicity of the detected mutation.

RESULTS

We discovered a novel homozygous synonymous mutation in the IL7R gene. Our functional studies indicate that this variant is pathogenic, causing exon 6, which encodes the transmembrane domain, to be preferentially spliced out.

CONCLUSION

In this study, we identified a novel rare synonymous mutation causing a loss of IL-7Rα expression at the cellular membrane. This case demonstrates the value of reanalyzing genetic data based on the clinical phenotype and highlights the significance of functional studies in determining the pathogenicity of genetic variants.

Physical-Chemical Coupling Coassembly Approach to Branched Magnetic Mesoporous Nanochains with Adjustable Surface Roughness

Self-assembly processes triggered by physical or chemical driving forces have been applied to fabricate hierarchical materials with subtle nanostructures. However, various physicochemical processes often interfere with each other, and their precise control has remained a great challenge. Here, in this paper, a rational synthesis of 1D magnetite-chain and mesoporous-silica-nanorod (Fe3O4&mSiO2) branched magnetic nanochains via a physical-chemical coupling coassembly approach is reported. Magnetic-field-induced assembly of magnetite Fe3O4 nanoparticles and isotropic/anisotropic assembly of mesoporous silica are coupled to obtain the delicate 1D branched magnetic mesoporous nanochains. The nanochains with a length of 2-3 µm in length are composed of aligned Fe3O4@mSiO2 nanospheres with a diameter of 150 nm and sticked-out 300 nm long mSiO2 branches. By properly coordinating the multiple assembly processes, the density and length of mSiO2 branches can well be adjusted. Because of the unique rough surface and length in correspondence to bacteria, the designed 1D Fe3O4&mSiO2 branched magnetic nanochains show strong bacterial adhesion and pressuring ability, performing bacterial inhibition over 60% at a low concentration (15 µg mL-1). This cooperative coassembly strategy deepens the understanding of the micro-nanoscale assembly process and lays a foundation for the preparation of the assembly with adjustable surface structures and the subsequent construction of complex multilevel structures.

The antihyperglycemic potential of pyrazolobenzothiazine 1, 1-dioxide novel derivative in mice using integrated molecular pharmacological approach

Diabetes Mellitus is a metabolic disease characterized by elevated blood sugar levels caused by inadequate insulin production, which subsequently leads to hyperglycemia. This study was aimed to investigate the antidiabetic potential of pyrazolobenzothiazine derivatives in silico, in vitro, and in vivo. Molecular docking of pyrazolobenzothiazine derivatives was performed against α-glucosidase and α-amylase and compounds were selected based on docking score, bonding interactions and low root mean square deviation (RMSD). Enzyme inhibition assay against α-glucosidase and α-amylase was performed in vitro using p-nitrophenyl-α-D-glucopyranoside (PNPG) and starch substrate. Synthetic compound pyrazolobenzothiazine (S1) exhibited minimal conformational changes during the 100 ns MD simulation run. S1 also revealed effective IC50 values for α-glucosidase (3.91 µM) and α-amylase (8.89 µM) and an enzyme kinetic study showed low ki (- 0.186 µM, - 1.267 µM) and ki' (- 0.691 µM, - 1.78 µM) values with the competitive type of inhibition for both enzymes α-glucosidase and α-amylase, respectively. Moreover, studies were conducted to check the effect of the synthetic compound in a mouse model. A low necrosis rate was observed in the liver, kidney, and pancreas through histology analysis performed on mice. Compound S1 also exhibited a good biochemical profile with lower sugar level (110-115 mg/dL), increased insulin level (25-30 μM/L), and low level of cholesterol (85 mg/dL) and creatinine (0.6 mg/dL) in blood. The treated mice group also exhibited a low % of glycated haemoglobin (3%). This study concludes that S1 is a new antidiabetic-agent that helps lower blood glucose levels and minimizes the complications associated with type-II diabetes.

Pre-prandial plasma liver-expressed antimicrobial peptide 2 (LEAP2) concentration in humans is inversely associated with hunger sensation in a ghrelin independent manner

PURPOSE

The liver-expressed antimicrobial peptide 2 (LEAP2) is a newly recognized peptide hormone that acts via the growth hormone secretagogue receptor (GHSR) blunting the effects of ghrelin and displaying ghrelin-independent actions. Since the implications of LEAP2 are beginning to be elucidated, we investigated if plasma LEAP2 concentration varies with feeding status or sex and whether it is associated with glucose metabolism and appetite sensations.

METHODS

We performed a single test meal study, in which plasma concentrations of LEAP2, ghrelin, insulin and glucose as well as visual analogue scales for hunger, desire to eat, prospective food consumption, fullness were assessed before and 60 min after breakfast in 44 participants (n = 21 females) with normal weight (NW) or overweight/obesity (OW/OB).

RESULTS

Pre-prandial plasma LEAP2 concentration was ~ 1.6-fold higher whereas ghrelin was ~ 2.0-fold lower in individuals with OW/OB (p < 0.001) independently of sex. After adjusting for body mass index (BMI) and sex, pre-prandial plasma LEAP2 concentration displayed a direct relationship with BMI (β: 0.09; 95%CI: 0.05, 0.13; p < 0.001), fat mass (β: 0.05; 95%CI: 0.01, 0.09; p = 0.010) and glycemia (β: 0.24; 95%CI: 0.05, 0.43; p = 0.021), whereas plasma ghrelin concentration displayed an inverse relationship with BMI and fat mass but not with glycemia. Postprandial plasma LEAP2 concentration increased ~ 58% in females with OW/OB (p = 0.045) but not in females with NW or in males. Pre-prandial plasma LEAP2 concentration displayed an inverse relationship with hunger score (β: - 11.16; 95% CI: - 18.52, - 3.79; p = 0.004), in a BMI-, sex- and ghrelin-independent manner.

CONCLUSIONS

LEAP2 emerges as a key hormone implicated in the regulation of metabolism and appetite in humans.

TRIAL REGISTRATION

The study was retrospectively registered in clinicaltrials.gov (April 2023).

CLINICALTRIALS

gov Identifier: NCT05815641.

Mechanical properties of human hepatic tissues to develop liver-mimicking phantoms for medical applications

Using liver phantoms for mimicking human tissue in clinical training, disease diagnosis, and treatment planning is a common practice. The fabrication material of the liver phantom should exhibit mechanical properties similar to those of the real liver organ in the human body. This tissue-equivalent material is essential for qualitative and quantitative investigation of the liver mechanisms in producing nutrients, excretion of waste metabolites, and tissue deformity at mechanical stimulus. This paper reviews the mechanical properties of human hepatic tissues to develop liver-mimicking phantoms. These properties include viscosity, elasticity, acoustic impedance, sound speed, and attenuation. The advantages and disadvantages of the most common fabrication materials for developing liver tissue-mimicking phantoms are also highlighted. Such phantoms will give a better insight into the real tissue damage during the disease progression and preservation for transplantation. The liver tissue-mimicking phantom will raise the quality assurance of patient diagnostic and treatment precision and offer a definitive clinical trial data collection.

Dietary patterns and their associations with postpartum weight retention: results of the MINA cohort study

PURPOSE

To examine the association of prepregnancy dietary patterns with postpartum weight retention at 6 months (PPWR6) among Lebanese and Qatari women.

METHODS

Data for this study were derived from the Mother and Infant Nutrition Assessment (MINA) prospective cohort study conducted in Lebanon and Qatar. Pregnant women were recruited during their first trimester and were followed up for three years. For the purpose of this study, data belonging to sociodemographic characteristics of participants, prepregnancy dietary intake, prepregnancy BMI as well as weight retention at 6 months were used. Dietary intake was examined using a 98-item food frequency questionnaire. Principal component analysis was used for the derivation of dietary patterns. The associations of dietary patterns with PPWR6 were examined using simple and multiple linear regressions.

RESULTS

Data was available for 177 participants (Lebanon: 93; Qatar: 84). Mean PPWR6 was 4.05 ± 5.29 kg. Significantly higher PPWR6 was observed among participants with pre-pregnancy overweight/obesity and among those with excessive gestational weight gain. Two dietary patterns were identified: the "Western" and the "Varied" patterns. After adjustment for confounders, a positive association was observed between the 'Western' pattern scores and PPWR6 (ß = 1.27; 95% CI 0.68-1.86; p value: < 0.0001).

CONCLUSION

Higher adherence to the Western pattern was associated with higher PPWR6 amongst women, hence underscoring the importance of public health interventions aimed at fostering healthier dietary habits during this crucial stage of the lifecycle.

Epidemiology, Clinical, and Microbiological Characteristics of Multidrug-Resistant Gram-Negative Bacteremia in Qatar

Antimicrobial resistance is a global healthcare threat with significant clinical and economic consequences peaking at secondary and tertiary care hospitals where multidrug-resistant Gram-negative bacteria (MDR GNB) lead to poor outcomes. A prospective study was conducted between January and December 2019 for all invasive bloodstream infections (BSIs) secondary to MDR GNB in Qatar identified during routine microbiological service to examine their clinical, microbiological, and genomic characteristics. Out of 3238 episodes of GNB BSIs, the prevalence of MDR GNB was 13% (429/3238). The predominant MDR pathogens were Escherichia coli (62.7%), Klebsiella pneumoniae (20.4%), Salmonella species (6.6%), and Pseudomonas aeruginosa (5.3%), while out of 245 clinically evaluated patients, the majority were adult males, with the elderly constituting almost one-third of the cohort and with highest observed risk for prolonged hospital stays. The risk factors identified included multiple comorbidities, recent healthcare contact, previous antimicrobial therapy, and admission to critical care. The in-hospital mortality rate was recorded at 25.7%, associated with multiple comorbidities, admission to critical care, and the acquisition of MDR Pseudomonas aeruginosa. Resistant pathogens demonstrated high levels of antimicrobial resistance but noticeable susceptibility to amikacin and carbapenems. Genomic analysis revealed that Escherichia coli ST131 and Salmonella enterica ST1 were the predominant clones not observed with other pathogens.

Unexpectedly High Propylene/Propane Separation Performance of Asymmetric Mixed-Matrix Membranes through Additive-Assisted In Situ ZIF-8 Filler Formation: Experimental and Computational Studies

Zeolitic-imidazolate framework-8 (ZIF-8), composed of a zinc center tetrahedrally coordinated with 2-methylimidazolate linkers, has garnered extensive attention as a selective filler for propylene-selective mixed-matrix membranes (MMMs). Recently, we reported an innovative and scalable MMM fabrication approach, termed "phase-inversion in sync with in situ MOF formation" (PIMOF), aimed at addressing the prevailing challenges in MMM processing. In this study, we intend to investigate the effect of additives, specifically sodium formate and 1,4-butanediol, on the modification of ZIF-8 filler formation within the polymer matrix in order to further improve the separation performance of the asymmetric MMMs prepared by the PIMOF. Remarkably, MMMs prepared with sodium formate as an additive in the coagulation bath exhibited an unprecedented C3H6/C3H8 separation factor of 222.5 ± 1.8 with a C3H6 permeance of 10.1 ± 0.3 GPU, surpassing that of MMMs prepared without additives (a C3 separation factor of 57.7 ± 11.2 with a C3 permeance of 22.5 ± 4.5 GPU). Our computational work complements the experimental investigation by studying the effect of ZIF-8 nanoparticle size on the specific surface interaction energy and apertures of ZIF-8. Calculations indicate that by having smaller ZIF-8 nanoparticles, stronger interactions are present with the polymer affecting the aperture of ZIF-8 nanoparticles. This reduction in aperture size is expected to improve selectivity toward propylene by reducing the permeability of propylene. These results represent a significant advancement, surpassing the performance of all previously reported propylene-selective MMMs and most high-quality polycrystalline ZIF-8 membranes. The notably enhanced separation performance primarily arises from the formation of exceedingly small ZIF-8-like particles with an amorphous or poorly crystalline structure, corroborated by our computational work.

Efficient crystal structure materials as reactive sorbent for the CO2 and CH4 adsorption and storage

The efficient dirubidium cobalt bis(dihydrogendiphosphate) dihydrate compound is successfully synthesized in a solution and used as a reactive sorbent for the CO2 and CH4 gases adsorption and storage. A crystal of this Rb2Co(H2P2O7)2·2H2O compound has been isolated and characterized by single X-ray diffraction analysis and was found to crystallize in the triclinic system ( P 1 ¯ ) with the cell parameters (Å): 6.980(1), 7.370(1), 7.816(1), 81.74(1), 70.35(1), 86.34(1); V = 374.68(9) Å3, Z = 2. The crystal-packing consists of a three-dimensional framework made upon corners and edges sharing of [RbO7], [H2P2O7] and [CoO6] entities, furthermore linked by a network of H-bonds. The UV-Vis spectroscopy revealed usual transitions between the ground state 4T1g and the upper levels 4T2g, 4A2g and 4T1g (P). Moreover, the CO2 and CH4 gases sorption measurements were successfully performed at two different temperatures (25 and 45 °C) and various pressures ranging from vacuum to 50 bar. Our results show that rate of CO2 and CH4 capturing was 3.10 mmol/g and 2.35 mmol/g at temperature 25 °C and pressure 50 bar, respectively. This compound showed a clear potential for CO2/CH4 adsorption and storage thereby paving the way towards its exploration and adaptation for capturing and collecting carbon dioxide and greenhouse gases from the air, and their conversion into hydrocarbon fuels using existing mature technologies. We have also conducted density functional theory calculations to study the CO2 and CH4 adsorption properties of Rb2Co(H2P2O7)2·2H2O. The simulation results show enhanced adsorption of both types of molecules on the surface of the material.

Bridging Homogeneous and Heterogeneous Catalysis: Phosphine-Functionalized Metal-Organic Frameworks

Phosphine-functionalized metal-organic frameworks (P-MOFs) as an emerging class of coordination polymers, have provided novel opportunities for the development of heterogeneous catalysts. Yet, compared with the ubiquitous phosphine systems in homogeneous catalysis, heterogenization of phosphines in MOFs is still at its early stage. In this Minireview, we summarize the synthetic strategies, characterization and catalytic reactions based on the P-MOFs reported in literature. In particular, various catalytic reactions are discussed in detail in terms of phosphine ligand structure-function relationship, including the potential obstacles for future development. Finally, we discuss the possible solutions, including new types of reactions and techniques as the perspectives for the development of P-MOF catalysts, highlighting the opportunities and challenges.

Influence of lack of blinding on the estimation of medication-related harms: a retrospective cohort study of randomized controlled trials

BACKGROUND

Empirical evidence suggests that lack of blinding may be associated with biased estimates of treatment benefit in randomized controlled trials, but the influence on medication-related harms is not well-recognized. We aimed to investigate the association between blinding and clinical trial estimates of medication-related harms.

METHODS

We searched PubMed from January 1, 2015, till January 1, 2020, for systematic reviews with meta-analyses of medication-related harms. Eligible meta-analyses must have contained trials both with and without blinding. Potential covariates that may confound effect estimates were addressed by restricting trials within the comparison or by hierarchical analysis of harmonized groups of meta-analyses (therefore harmonizing drug type, control, dosage, and registration status) across eligible meta-analyses. The weighted hierarchical linear regression was then used to estimate the differences in harm estimates (odds ratio, OR) between trials that lacked blinding and those that were blinded. The results were reported as the ratio of OR (ROR) with its 95% confidence interval (CI).

RESULTS

We identified 629 meta-analyses of harms with 10,069 trials. We estimated a weighted average ROR of 0.68 (95% CI: 0.53 to 0.88, P < 0.01) among 82 trials in 20 meta-analyses where blinding of participants was lacking. With regard to lack of blinding of healthcare providers or outcomes assessors, the RORs were 0.68 (95% CI: 0.53 to 0.87, P < 0.01 from 81 trials in 22 meta-analyses) and 1.00 (95% CI: 0.94 to 1.07, P = 0.94 from 858 trials among 155 meta-analyses) respectively. Sensitivity analyses indicate that these findings are applicable to both objective and subjective outcomes.

CONCLUSIONS

Lack of blinding of participants and health care providers in randomized controlled trials may underestimate medication-related harms. Adequate blinding in randomized trials, when feasible, may help safeguard against potential bias in estimating the effects of harms.

SARS-CoV-2 infection triggers more potent antibody-dependent cellular cytotoxicity (ADCC) responses than mRNA-, vector-, and inactivated virus-based COVID-19 vaccines

Neutralizing antibodies (NAbs) are elicited after infection and vaccination and have been well studied. However, their antibody-dependent cellular cytotoxicity (ADCC) functionality is still poorly characterized. Here, we investigated ADCC activity in convalescent sera from infected patients with wild-type (WT) severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) or omicron variant compared with three coronavirus disease 2019 (COVID-19) vaccine platforms and postvaccination breakthrough infection (BTI). We analyzed ADCC activity targeting SARS-CoV-2 spike (S) and nucleocapsid (N) proteins in convalescent sera following WT SARS-CoV-2-infection (n = 91), including symptomatic and asymptomatic infections, omicron-infection (n = 8), COVID-19 vaccination with messenger RNA- (mRNA)- (BNT162b2 or mRNA-1273, n = 77), adenovirus vector- (n = 41), and inactivated virus- (n = 46) based vaccines, as well as post-mRNA vaccination BTI caused by omicron (n = 28). Correlations between ADCC, binding, and NAb titers were reported. ADCC was elicited within the first month postinfection and -vaccination and remained detectable for ≥3 months. WT-infected symptomatic patients had higher S-specific ADCC levels than asymptomatic and vaccinated individuals. Also, no difference in N-specific ADCC activity was seen between symptomatic and asymptomatic patients, but the levels were higher than the inactivated vaccine. Notably, omicron infection showed reduced overall ADCC activity compared to WT SARS-CoV-2 infection. Although post-mRNA vaccination BTI elicited high levels of binding and NAbs, ADCC activity was significantly reduced. Also, there was no difference in ADCC levels across the four vaccines, although NAbs and binding antibody titers were significantly higher in mRNA-vaccinated individuals. All evaluated vaccine platforms are inferior in inducing ADCC compared to natural infection with WT SARS-CoV-2. The inactivated virus-based vaccine can induce N-specific ADCC activity, but its relevance to clinical outcomes requires further investigation. Our data suggest that ADCC could be used to estimate the extra-neutralization level against COVID-19 and provides evidence that vaccination should focus on other Fc-effector functions besides NAbs. Also, the decreased susceptibility of the omicron variant to ADCC offers valuable guidance for forthcoming efforts to identify the specific targets of antibodies facilitating ADCC.

Anatomy-aware computed tomography-to-ultrasound spine registration

BACKGROUND

Ultrasound (US) has demonstrated to be an effective guidance technique for lumbar spine injections, enabling precise needle placement without exposing the surgeon or the patient to ionizing radiation. However, noise and acoustic shadowing artifacts make US data interpretation challenging. To mitigate these problems, many authors suggested using computed tomography (CT)-to-US registration to align the spine in pre-operative CT to intra-operative US data, thus providing localization of spinal landmarks.

PURPOSE

In this paper, we propose a deep learning (DL) pipeline for CT-to-US registration and address the problem of a need for annotated medical data for network training. Firstly, we design a data generation method to generate paired CT-US data where the spine is deformed in a physically consistent manner. Secondly, we train a point cloud (PC) registration network using anatomy-aware losses to enforce anatomically consistent predictions.

METHODS

Our proposed pipeline relies on training the network on realistic generated data. In our data generation method, we model the properties of the joints and disks between vertebrae based on biomechanical measurements in previous studies. We simulate the supine and prone position deformation by applying forces on the spine models. We choose the spine models from 35 patients in VerSe dataset. Each spine is deformed 10 times to create a noise-free data with ground-truth segmentation at hand. In our experiments, we use one-leave-out cross-validation strategy to measure the performance and the stability of the proposed method. For each experiment, we choose generated PCs from three spines as the test set. From the remaining, data from 3 spines act as the validation set and we use the rest of the data for training the algorithm. To train our network, we introduce anatomy-aware losses and constraints on the movement to match the physics of the spine, namely, rigidity loss and bio-mechanical loss. We define rigidity loss based on the fact that each vertebra can only transform rigidly while the disks and the surrounding tissue are deformable. Second, by using bio-mechanical loss we stop the network from inferring extreme movements by penalizing the force needed to get to a certain pose.

RESULTS

To validate the effectiveness of our fully automated data generation pipeline, we qualitatively assess the fidelity of the generated data. This assessment involves verifying the realism of the spinal deformation and subsequently confirming the plausibility of the simulated ultrasound images. Next, we demonstrate that the introduction of the anatomy-aware losses brings us closer to state-of-the-art (SOTA) and yields a reduction of 0.25 mm in terms of target registration error (TRE) compared to using only mean squared error (MSE) loss on the generated dataset. Furthermore, by using the proposed losses, the rigidity loss in inference decreases which shows that the inferred deformation respects the rigidity of the vertebrae and only introduces deformations in the soft tissue area to compensate the difference to the target PC. We also show that our results are close to the SOTA for the simulated US dataset with TRE of 3.89 mm and 3.63 mm for the proposed method and SOTA respectively. In addition, we show that our method is more robust against errors in the initialization in comparison to SOTA and significantly achieves better results (TRE of 4.88 mm compared to 5.66 mm) in this experiment.

CONCLUSIONS

In conclusion, we present a pipeline for spine CT-to-US registration and explore the potential benefits of utilizing anatomy-aware losses to enhance registration results. Additionally, we propose a fully automatic method to synthesize paired CT-US data with physically consistent deformations, which offers the opportunity to generate extensive datasets for network training. The generated dataset and the source code for data generation and registration pipeline can be accessed via https://github.com/mfazampour/medphys_ct_us_registration.

Fully automated sinogram-based deep learning model for detection and classification of intracranial hemorrhage

PURPOSE

To propose an automated approach for detecting and classifying Intracranial Hemorrhages (ICH) directly from sinograms using a deep learning framework. This method is proposed to overcome the limitations of the conventional diagnosis by eliminating the time-consuming reconstruction step and minimizing the potential noise and artifacts that can occur during the Computed Tomography (CT) reconstruction process.

METHODS

This study proposes a two-stage automated approach for detecting and classifying ICH from sinograms using a deep learning framework. The first stage of the framework is Intensity Transformed Sinogram Sythesizer, which synthesizes sinograms that are equivalent to the intensity-transformed CT images. The second stage comprises of a cascaded Convolutional Neural Network-Recurrent Neural Network (CNN-RNN) model that detects and classifies hemorrhages from the synthesized sinograms. The CNN module extracts high-level features from each input sinogram, while the RNN module provides spatial correlation of the neighborhood regions in the sinograms. The proposed method was evaluated on a publicly available RSNA dataset consisting of a large sample size of 8652 patients.

RESULTS

The results showed that the proposed method had a notable improvement as high as 27% in patient-wise accuracies when compared to state-of-the-art methods like ResNext-101, Inception-v3 and Vision Transformer. Furthermore, the sinogram-based approach was found to be more robust to noise and offset errors in comparison to CT image-based approaches. The proposed model was also subjected to a multi-label classification analysis to determine the hemorrhage type from a given sinogram. The learning patterns of the proposed model were also examined for explainability using the activation maps.

CONCLUSION

The proposed sinogram-based approach can provide an accurate and efficient diagnosis of ICH without the need for the time-consuming reconstruction step and can potentially overcome the limitations of CT image-based approaches. The results show promising outcomes for the use of sinogram-based approaches in detecting hemorrhages, and further research can explore the potential of this approach in clinical settings.

B7-H3 at the crossroads between tumor plasticity and colorectal cancer progression: a potential target for therapeutic intervention

B7-H3 (B7 homology 3 protein) is an important transmembrane immunoregulatory protein expressed in immune cells, antigen-presenting cells, and tumor cells. Studies reveal a multifaceted role of B7-H3 in tumor progression by modulating various cancer hallmarks involving angiogenesis, immune evasion, and tumor microenvironment, and it is also a promising candidate for cancer immunotherapy. In colorectal cancer (CRC), B7-H3 has been associated with various aspects of disease progression, such as evasion of tumor immune surveillance, tumor-node metastasis, and poor prognosis. Strategies to block or interfere with B7-H3 in its immunological and non-immunological functions are under investigation. In this study, we explore the role of B7-H3 in tumor plasticity, emphasizing tumor glucose metabolism, angiogenesis, epithelial-mesenchymal transition, cancer stem cells, apoptosis, and changing immune signatures in the tumor immune landscape. We discuss how B7-H3-induced tumor plasticity contributes to immune evasion, metastasis, and therapy resistance. Furthermore, we delve into the most recent advancements in targeting B7-H3-based tumor immunotherapy as a potential approach to CRC treatment.

Human antigen R: Exploring its inflammatory response impact and significance in cardiometabolic disorders

RNA-binding proteins (RBPs) play a crucial role in the regulation of posttranscriptional RNA networks, which can undergo dysregulation in many pathological conditions. Human antigen R (HuR) is a highly researched RBP that plays a crucial role as a posttranscriptional regulator. HuR plays a crucial role in the amplification of inflammatory signals by stabilizing the messenger RNA of diverse inflammatory mediators and key molecular players. The noteworthy correlations between HuR and its target molecules, coupled with the remarkable impacts reported on the pathogenesis and advancement of multiple diseases, position HuR as a promising candidate for therapeutic intervention in diverse inflammatory conditions. This review article examines the significance of HuR as a member of the RBP family, its regulatory mechanisms, and its implications in the pathophysiology of inflammation and cardiometabolic illnesses. Our objective is to illuminate potential directions for future research and drug development by conducting a comprehensive analysis of the existing body of research on HuR.

Bothersome symptoms at midlife in relation to body fat percentage

OBJECTIVES

Increasing obesity has been associated with a higher frequency of symptoms at midlife. Bothersomeness represents an important measure of perceived symptom severity, but has received relatively little consideration, and relationships between symptom bothersomeness and obesity are not known. We evaluated the association between body fat percentage (%BF) and the bothersomeness of symptoms at midlife.

METHODS

This cross-sectional study included women aged 40-60 in Qatar (n = 841). Participants reported frequency and bothersomeness of midlife symptoms hypothesized to be related to body composition. Initially, we characterized the relationship between continuous %BF and presence (yes/no) and bothersomeness (yes/no) for each symptom using restricted cubic spline (RCS) models to test nonlinearity. Subsequently, we used multinomial logistic regressions to evaluate associations between %BF and multilevel symptom outcomes, where categories were: (a) no symptoms or bother, (b) symptoms without bothersomeness, and (c) symptoms with bothersomeness.

RESULTS

The highest frequency of bothersomeness was reported for aches/stiffness in joints (51%), followed by trouble sleeping (34%), night sweats (21%), urinary incontinence (18%), hot flashes (16%), and shortness of breath (15%). In unadjusted multinomial logistic regressions, aches/stiffness in joints with and without bothersomeness had the same significant relationship with %BF. Bothersome night sweats, urinary incontinence, and hot flashes were significantly associated with %BF (p < .05), but those same symptoms without bothersomeness were not significantly associated with %BF.

CONCLUSIONS

Our findings suggest that bothersomeness is an important variable that tracks with body fat and gives different information than report of the presence/absence of a symptom alone.

Polyolefin-Based Smart Self-Healing Composite Coatings Modified with Calcium Carbonate and Sodium Alginate

Corrosion-related damage incurs significant capital costs in many industries. In this study, an anti-corrosive pigment was synthesized by modifying calcium carbonate with sodium alginate (SA), and smart self-healing coatings were synthesized by reinforcing the anti-corrosive pigments into a polyolefin matrix. Structural changes during the synthesis of the anti-corrosive pigment were examined using scanning electron microscopy (SEM) and X-ray diffraction (XRD) analysis. Moreover, thermal gravimetric analysis confirmed the loading of the corrosion inhibitor, and electrochemical impedance spectroscopic analysis revealed a stable impedance value, confirming the improved corrosion resistance of the modified polyolefin coatings. The incorporation of the anticorrosive pigment into a polyolefin matrix resulted in improved pore resistance properties and capacitive behavior, indicating a good barrier property of the modified coatings. The formation of a protective film on the steel substrate reflected the adsorption of the corrosion inhibitor (SA) on the steel substrate, which further contributed to enhancing the corrosion resistance of the modified coatings. Moreover, the formation of the protective film was also analyzed by profilometry and elemental mapping analysis.

Piezo inkjet formation of Ag nanoparticles from microdots arrays for surface plasmonic resonance

The study aims to explore a novel approach for fabricating plasmonic nanostructures to enhance the optical properties and performance of various optoelectronic devices. The research begins by employing a piezo-inkjet printing technique to deposit drops containing Ag nanoparticles (NPs) onto a glass substrate at a predefined equidistance, with the goal of obtaining arrays of Ag microdots (Ag-µdots) on the glass substrate. This process is followed by a thermal annealing treatment. The printing parameters are first optimized to achieve uniform deposition of different sizes of Ag-µdots arrays by controlling the number of Ag ink drops. Subsequently, the printed arrays undergo thermal annealing at various temperatures in air for 60 min, enabling precise and uniform control over nanoparticle formation. The printed Ag nanoparticles are characterized using field emission scanning electron microscopy and atomic force microscopy to analyze their morphological features, ensuring their suitability for plasmonic applications. UV-Vis spectrophotometry is employed to investigate the enhanced surface-plasmonic-resonance properties of the printed AgNPs. Measurements confirm that the equidistant arrays of AgNPs obtained from annealing Ag microdots exhibit enhanced light-matter interaction, leading to a surface plasmon resonance response dependent on the Ag NPs' specific surface area. These enhanced surface plasmonic resonances open avenues for developing cutting-edge optoelectronic devices that leverage the benefits of plasmonic nanostructures, thereby enabling new opportunities for future technological developments across various fields.

Short-Term Effects of Heart Rate Variability Biofeedback on Working Memory

Drawing upon the well-documented impact of long-term heart rate variability biofeedback (HRVB) on psychophysiological responses, this study seeks to explore the short-term effects arising from a single HRVB session during and after paced breathing exercise. The research aligns with the neurovisceral integration model, emphasizing the link between heart rate variability (HRV) levels and cognitive performance. Therefore, a randomized controlled trial employing a between-subjects design was conducted with 38 participants. Each participant was assigned to either the paced breathing intervention group or the spontaneous breathing control group. The study assessed various parameters such as cardiac vagal tone, evaluated through vagally mediated HRV measures, and working memory, measured using the N-back task. Additionally, participants' affective states were assessed through self-reported questionnaires, specifically targeting attentiveness, fatigue, and serenity. The results notably reveal enhancements in the working memory task and an elevated state of relaxation and attention following the HRVB session, as evidenced by higher averages of correct responses, serenity and attentiveness scores. However, the findings suggest that this observed improvement is not influenced by changes in cardiac vagal tone, as assessed using a simple mediation analysis. In conclusion, this study presents promising insights into the impact of a single HRVB session, laying the foundation for future research advancements in this domain.

Genetic Susceptibility to Arrhythmia Phenotypes in a Middle Eastern Cohort of 14,259 Whole-Genome Sequenced Individuals

Background: The current study explores the genetic underpinnings of cardiac arrhythmia phenotypes within Middle Eastern populations, which are under-represented in genomic medicine research. Methods: Whole-genome sequencing data from 14,259 individuals from the Qatar Biobank were used and contained 47.8% of Arab ancestry, 18.4% of South Asian ancestry, and 4.6% of African ancestry. The frequency of rare functional variants within a set of 410 candidate genes for cardiac arrhythmias was assessed. Polygenic risk score (PRS) performance for atrial fibrillation (AF) prediction was evaluated. Results: This study identified 1196 rare functional variants, including 162 previously linked to arrhythmia phenotypes, with varying frequencies across Arab, South Asian, and African ancestries. Of these, 137 variants met the pathogenic or likely pathogenic (P/LP) criteria according to ACMG guidelines. Of these, 91 were in ACMG actionable genes and were present in 1030 individuals (~7%). Ten P/LP variants showed significant associations with atrial fibrillation p < 2.4 × 10-10. Five out of ten existing PRSs were significantly associated with AF (e.g., PGS000727, p = 0.03, OR = 1.43 [1.03, 1.97]). Conclusions: Our study is the largest to study the genetic predisposition to arrhythmia phenotypes in the Middle East using whole-genome sequence data. It underscores the importance of including diverse populations in genomic investigations to elucidate the genetic landscape of cardiac arrhythmias and mitigate health disparities in genomic medicine.

Photocatalytic degradation of organic dyes using reduced graphene oxide (rGO)

Photocatalysts have developed into a successful strategy for degrading synthetic and organic toxins, such as chemicals and dyes, in wastewater. In this study, graphene oxide was reduced at different temperatures and used for degrading indigo carmine and neutral red dyes. The wide surface areas, strong adsorption sites, and oxygen functionalities of reduced graphene oxide (rGO) at 250 °C (rGO-250) produced more photocatalytic degradation efficiency and adsorption percentage. The catalyst dosage, initial dye concentration, solution pH and recyclability were all used to optimize the photocatalytic activity of rGO-250. This research presents a capable nano-adsorbent photocatalyst for the efficient degradation of organic dyes. GO and rGOs were also investigated for carbon dioxide (CO2) absorption properties. Results showed that rGO-250 has better CO2 adsorption properties than other rGOs. Overall, it was observed that rGO-250 has better photocatalytic and CO2 adsorption capabilities compared to graphene oxide reduced at different temperatures.

Untargeted Metabolomic Profiling Reveals Differentially Expressed Serum Metabolites and Pathways in Type 2 Diabetes Patients with and without Cognitive Decline: A Cross-Sectional Study

Diabetes is recognized as a risk factor for cognitive decline, but the underlying mechanisms remain elusive. We aimed to identify the metabolic pathways altered in diabetes-associated cognitive decline (DACD) using untargeted metabolomics. We conducted liquid chromatography-mass spectrometry-based untargeted metabolomics to profile serum metabolite levels in 100 patients with type 2 diabetes (T2D) (54 without and 46 with DACD). Multivariate statistical tools were used to identify the differentially expressed metabolites (DEMs), and enrichment and pathways analyses were used to identify the signaling pathways associated with the DEMs. The receiver operating characteristic (ROC) analysis was employed to assess the diagnostic accuracy of a set of metabolites. We identified twenty DEMs, seven up- and thirteen downregulated in the DACD vs. DM group. Chemometric analysis revealed distinct clustering between the two groups. Metabolite set enrichment analysis found significant enrichment in various metabolite sets, including galactose metabolism, arginine and unsaturated fatty acid biosynthesis, citrate cycle, fructose and mannose, alanine, aspartate, and glutamate metabolism. Pathway analysis identified six significantly altered pathways, including arginine and unsaturated fatty acid biosynthesis, and the metabolism of the citrate cycle, alanine, aspartate, glutamate, a-linolenic acid, and glycerophospholipids. Classifier models with AUC-ROC > 90% were developed using individual metabolites or a combination of individual metabolites and metabolite ratios. Our study provides evidence of perturbations in multiple metabolic pathways in patients with DACD. The distinct DEMs identified in this study hold promise as diagnostic biomarkers for DACD patients.

A generic scope actuation system for flexible endoscopes

BACKGROUND

A scope actuation system assists a surgeon in steering a scope for navigating an operative field during an interventional or diagnostic procedure. Each system is tailored for a specific surgical procedure. The development of a generic scope actuation system could assist various laparoscopic and endoscopic procedures. This has the potential to reduce the deployment and maintenance costs for a hospital, making it more accessible for clinical usage.

METHODS

A modular actuation system (for maneuvering rigid laparoscopes) was adapted to enable incorporation of flexible endoscopes. The design simplifies the installation and disassembly processes. User studies were conducted to assess the ability of the system to focus onto a diagnostic area, and to navigate during a simulated esophagogastroduodenoscopy procedure. During the studies, the endoscope was maneuvered with (robotic mode) and without (manual mode) the actuation system to navigate the endoscope's focus on a predefined track.

RESULTS

Results show that the robotic mode performed better than the manual mode on all the measured performance parameters including (a) the total duration to traverse a track, (b) the percentage of time spent outside a track while traversing, and (c) the number of times the scope focus shifts outside the track. Additionally, robotic mode also reduced the perceived workload based on the NASA-TLX scale.

CONCLUSIONS

The proposed scope actuation system enhances the maneuverability of flexible endoscopes. It also lays the groundwork for future development of modular and generic scope assistant systems that can be used in both laparoscopic and endoscopic procedures.

COVID-19 lockdowns weigh heavily on youth: an analysis of the impact on BMI for Age Z scores in children and adolescents

BACKGROUND

The COVID-19 pandemic has significantly impacted the lifestyle and health of children and adolescents. This study aimed to assess the lifestyle changes brought about by COVID-19-related school closures and their impact on the Body Mass Index for Age Z (BAZ) scores of governmental school students in Qatar.

METHODS

An analytical cross-sectional study was conducted between June and August 2022 targeting students aged 8-15 years. Data on lifestyle behaviors were gathered through telephone interviews with parents of selected students. The BAZ scores before and after school closures that were automatically calculated by the electronic health records system were extracted.

RESULTS

We completed 1546 interviews. We found a significant increase in unhealthy food categories, a reduction in physical activity and an increase in the screen time over the period of schools' closure. The BAZ increased significantly by 0.30 (95% CI 0.26-0.35). The increase in BAZ scores was significantly higher among male students and the younger age group compared to females and older counterparts, respectively. The student's age group, sex, nationality and change in physical activity were significant predictors of the change in BAZ scores.

CONCLUSIONS

School closures during the COVID-19 pandemic negatively impacted the lifestyle of students in Qatar and resulted in a significant increase in the BAZ scores.

Optimization of the Consolidation Parameters for Enhanced Thermoelectric Properties of Gr-Bi2Te2.55Se0.45 Nanocomposites

Hot pressing represents a promising consolidation technique for ball-milled bismuth telluride alloys, yet deep investigations are needed to understand its effect on the thermoelectric properties. This paper studies the effect of hot-pressing parameters (temperature and pressure) on the thermoelectric properties of the n-type Gr-Bi2Te2.55Se0.45 nanocomposite. Ultra-high pressure, up to 1.5 GPa, is considered for the first time for consolidating Bi2(Te,Se)3 alloys. Results from this study show that increasing the temperature leads to changes in chemical composition and causes noticeable grain growth. On the contrary, increasing pressure mainly causes improvements in densification. Overall, increments in these two parameters improve the ZT values, with the temperature parameter having a higher influence. The highest ZT of 0.69 at 160 °C was obtained for the sample hot-pressed at 350 °C and 1 GPa for 5 min, which is indeed an excellent and competitive value when compared with results reported for this n-type Bi2Te2.55Se0.45 composition.

Unveiling the Protective Role of Melatonin in Osteosarcoma: Current Knowledge and Limitations

Melatonin, an endogenous neurohormone produced by the pineal gland, has received increased interest due to its potential anti-cancer properties. Apart from its well-known role in the sleep-wake cycle, extensive scientific evidence has shown its role in various physiological and pathological processes, such as inflammation. Additionally, melatonin has demonstrated promising potential as an anti-cancer agent as its function includes inhibition of tumorigenesis, induction of apoptosis, and regulation of anti-tumor immune response. Although a precise pathophysiological mechanism is yet to be established, several pathways related to the regulation of cell cycle progression, DNA repair mechanisms, and antioxidant activity have been implicated in the anti-neoplastic potential of melatonin. In the current manuscript, we focus on the potential anti-cancer properties of melatonin and its use in treating and managing pediatric osteosarcoma. This aggressive bone tumor primarily affects children and adolescents and is treated mainly by surgical and radio-oncological interventions, which has improved survival rates among affected individuals. Significant disadvantages to these interventions include disease recurrence, therapy-related toxicity, and severe/debilitating side effects that the patients have to endure, significantly affecting their quality of life. Melatonin has therapeutic effects when used for treating osteosarcoma, attributed to its ability to halt cancer cell proliferation and trigger apoptotic cell death, thereby enhancing chemotherapeutic efficacy. Furthermore, the antioxidative function of melatonin alleviates harmful side effects of chemotherapy-induced oxidative damage, aiding in decreasing therapeutic toxicities. The review concisely explains the many mechanisms by which melatonin targets osteosarcoma, as evidenced by significant results from several in vitro and animal models. Nevertheless, if further explored, human trials remain a challenge that could shed light and support its utility as an adjunctive therapeutic modality for treating osteosarcoma.

PVA-TiO2 Nanocomposite Hydrogel as Immobilization Carrier for Gas-to-Liquid Wastewater Treatment

This study investigates the development of polyvinyl alcohol (PVA) gel matrices for biomass immobilization in wastewater treatment. The PVA hydrogels were prepared through a freezing-thawing (F-T) cross-linking process and reinforced with high surface area nanoparticles to improve their mechanical stability and porosity. The PVA/nanocomposite hydrogels were prepared using two different nanoparticle materials: iron oxide (Fe3O2) and titanium oxide (TiO2). The effects of the metal oxide nanoparticle type and content on the pore structure, hydrogel bonding, and mechanical and viscoelastic properties of the cross-linked hydrogel composites were investigated. The most durable PVA/nanoparticles matrix was then tested in the bioreactor for the biological treatment of wastewater. Morphological analysis showed that the reinforcement of PVA gel with Fe2O3 and TiO2 nanoparticles resulted in a compact nanocomposite hydrogel with regular pore distribution. The FTIR analysis highlighted the formation of bonds between nanoparticles and hydrogel, which caused more interaction within the polymeric matrix. Furthermore, the mechanical strength and Young's modulus of the hydrogel composites were found to depend on the type and content of the nanoparticles. The most remarkable improvement in the mechanical strength of the PVA/nanoparticles composites was obtained by incorporating 0.1 wt% TiO2 and 1.0 wt% Fe2O3 nanoparticles. However, TiO2 showed more influence on the mechanical strength, with more than 900% improvement in Young's modulus for TiO2-reinforced PVA hydrogel. Furthermore, incorporating TiO2 nanoparticles enhanced hydrogel stability but did not affect the biodegradation of organic pollutants in wastewater. These results suggest that the PVA-TiO2 hydrogel has the potential to be used as an effective carrier for biomass immobilization and wastewater treatment.

Stability of Viscoelastic Solutions: BrijL4 and Sodium Cholate Mixtures with Metal Ions Across a Broad pH and Temperature Range

The impact of pH, temperature, and metal ions on the rheological and interfacial properties of aqueous mixed surfactant solutions composed of anionic NaC (sodium cholate) and nonionic BrijL4 [polyoxyethylene (4) lauryl ether] surfactants has been investigated. The various compound systems were analyzed, considering variations in each selected factor. The results highlight the unique characteristics of the BrijL4/NaC mixture, suggesting its potential as a viable alternative to other existing surfactants. The synergistic effect between BrijL4 and NaC significantly reduces the critical micelle concentration (CMC) and improves the wetting properties on hydrophobic surfaces, surpassing those of single-component solutions. Additionally, sodium, calcium, and magnesium ions enhance surface wetting and decrease the CMC. Besides, the BrijL4/NaC solutions exhibit viscoelastic fluid behavior at higher surfactant concentrations. These viscoelastic BrijL4/NaC solutions demonstrate stability over various pH and temperature variations, exhibiting lower flow activation and scission energy values than those of other viscoelastic surfactant solutions. Notably, the BrijL4/NaC mixture has potential applications in gel-based foliar fertilizers and drug delivery systems. Furthermore, the rheological studies examine the impact of humic acid on the rheological properties of BrijL4/NaC mixture solutions, revealing that incorporating additional humic acids can achieve stable rheological properties.

A Path towards Timely VAP Diagnosis: Proof-of-Concept Study on Pyocyanin Sensing with Cu-Mg Doped Graphene Oxide

In response to the urgent requirement for rapid, precise, and cost-effective detection in intensive care units (ICUs) for ventilated patients, as well as the need to overcome the limitations of traditional detection methods, researchers have turned their attention towards advancing novel technologies. Among these, biosensors have emerged as a reliable platform for achieving accurate and early diagnoses. In this study, we explore the possibility of using Pyocyanin analysis for early detection of pathogens in ventilator-associated pneumonia (VAP) and lower respiratory tract infections in ventilated patients. To achieve this, we developed an electrochemical sensor utilizing a graphene oxide-copper oxide-doped MgO (GO - Cu - Mgo) (GCM) catalyst for Pyocyanin detection. Pyocyanin is a virulence factor in the phenazine group that is produced by Pseudomonas aeruginosa strains, leading to infections such as pneumonia, urinary tract infections, and cystic fibrosis. We additionally investigated the use of DNA aptamers for detecting Pyocyanin as a biomarker of Pseudomonas aeruginosa, a common causative agent of VAP. The results of this study indicated that electrochemical detection of Pyocyanin using a GCM catalyst shows promising potential for various applications, including clinical diagnostics and drug discovery.

Rapid Visual Detection of Methicillin-Resistant Staphylococcus aureus in Human Clinical Samples via Closed LAMP Assay Targeting mecA and spa Genes

The emergence of antimicrobial resistance (AMR), particularly methicillin-resistant Staphylococcus aureus (MRSA), poses a significant global health threat as these bacteria increasingly become resistant to the most available therapeutic options. Thus, developing an efficient approach to rapidly screen MRSA directly from clinical specimens has become vital. In this study, we establish a closed-tube loop-mediated isothermal amplification (LAMP) method incorporating hydroxy-naphthol blue (HNB) colorimetric dye assay to directly detect MRSA from clinical samples based on the presence of mecA and spa genes. In total, 125 preidentified S. aureus isolates and 93 clinical samples containing S. aureus were sourced from the microbiology laboratory at Hamad General Hospital (HGH). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were computed based on conventional PCR. The assay demonstrated 100% specificity, 91.23% sensitivity, 0.90 Cohen Kappa (CK), 100% PPV, and 87.8% NPV for the clinical samples, while clinical isolates exhibited 100% specificity, 97% sensitivity, 0.926 CK, 100% PPV, and 88.89% NPV. Compared to cefoxitin disk diffusion, LAMP provided 100% specificity and sensitivity, 1.00 CK, and 100% for PPV and NPV. The study revealed that the closed-tube LAMP incorporating (HNB) dye is a rapid technique with a turnaround time of less than 1 h and high specificity and sensitivity.

Correlations between Resting Electrocardiogram Findings and Disease Profiles: Insights from the Qatar Biobank Cohort

BACKGROUND

Resting electrocardiogram (ECG) is a valuable non-invasive diagnostic tool used in clinical medicine to assess the electrical activity of the heart while the patient is resting. Abnormalities in ECG may be associated with clinical biomarkers and can predict early stages of diseases. In this study, we evaluated the association between ECG traits, clinical biomarkers, and diseases and developed risk scores to predict the risk of developing coronary artery disease (CAD) in the Qatar Biobank.

METHODS

This study used 12-lead ECG data from 13,827 participants. The ECG traits used for association analysis were RR, PR, QRS, QTc, PW, and JT. Association analysis using regression models was conducted between ECG variables and serum electrolytes, sugars, lipids, blood pressure (BP), blood and inflammatory biomarkers, and diseases (e.g., type 2 diabetes, CAD, and stroke). ECG-based and clinical risk scores were developed, and their performance was assessed to predict CAD. Classical regression and machine-learning models were used for risk score development.

RESULTS

Significant associations were observed with ECG traits. RR showed the largest number of associations: e.g., positive associations with bicarbonate, chloride, HDL-C, and monocytes, and negative associations with glucose, insulin, neutrophil, calcium, and risk of T2D. QRS was positively associated with phosphorus, bicarbonate, and risk of CAD. Elevated QTc was observed in CAD patients, whereas decreased QTc was correlated with decreased levels of calcium and potassium. Risk scores developed using regression models were outperformed by machine-learning models. The area under the receiver operating curve reached 0.84 using a machine-learning model that contains ECG traits, sugars, lipids, serum electrolytes, and cardiovascular disease risk factors. The odds ratio for the top decile of CAD risk score compared to the remaining deciles was 13.99.

CONCLUSIONS

ECG abnormalities were associated with serum electrolytes, sugars, lipids, and blood and inflammatory biomarkers. These abnormalities were also observed in T2D and CAD patients. Risk scores showed great predictive performance in predicting CAD.

A variant in sperm-specific glycolytic enzyme enolase 4 (ENO4) causes human male infertility

BACKGROUND

Although defects in sperm morphology and physiology lead to male infertility, in many instances, the exact disruption of molecular pathways in a given patient is often unknown. The glycolytic pathway is an essential process to supply energy in sperm cell motility. Enolase 4 (ENO4) is crucial for the glycolytic process, which provides the energy for sperm cells in motility. ENO4 is located in the sperm principal piece and is essential for the motility and organization of the sperm flagellum. In the present study, we characterized a family with asthenozoospermia and abnormal sperm morphology as a result of a variant in the enolase 4 (ENO4) gene.

METHODS

Computer-assisted semen analysis, papanicolaou smear staining and scanning electron microscopy were used to examine sperm motility and morphology for semen analysis in patients. For genetic analysis, whole-exome sequencing followed by Sanger sequencing was performed.

RESULTS

Two brothers in a consanguineous family were being clinically investigated for sperm motility and morphology issues. Genetic analysis by whole-exome sequencing revealed a homozygous variant [c.293A>G, p.(Lys98Arg)] in the ENO4 gene that segregated with infertility in the family, shared by affected but not controls.

CONCLUSIONS

In view of the association of asthenozoospermia and abnormal sperm morphology in Eno4 knockout mice, we consider this to be the first report describing the involvement of ENO4 gene in human male infertility. We also explore the possible involvement of another variant in explaining other phenotypic features in this family.

Investigating the Cell Entry Mechanism, Disassembly, and Toxicity of the Nanocage PCC-1: Insights into Its Potential as a Drug Delivery Vehicle

The porous coordination cage PCC-1 represents a new platform potentially useful for the cellular delivery of drugs with poor cell permeability and solubility. PCC-1 is a metal-organic polyhedron constructed from zinc metal ions and organic ligands through coordination bonds. PCC-1 possesses an internal cavity that is suitable for drug encapsulation. To better understand the biocompatibility of PCC-1 with human cells, the cell entry mechanism, disassembly, and toxicity of the nanocage were investigated. PCC-1 localizes in the nuclei and cytoplasm within minutes upon incubation with cells, independent of endocytosis and cargo, suggesting direct plasma membrane translocation of the nanocage carrying its guest in its internal cavity. Furthermore, the rates of cell entry correlate to extracellular concentrations, indicating that PCC-1 is likely diffusing passively through the membrane despite its relatively large size. Once inside cells, PCC-1 disintegrates into zinc metal ions and ligands over a period of several hours, each component being cleared from cells within 1 day. PCC-1 is relatively safe for cells at low micromolar concentrations but becomes inhibitory to cell proliferation and toxic above a concentration or incubation time threshold. However, cells surviving these conditions can return to homeostasis 3-5 days after exposure. Overall, these findings demonstrate that PCC-1 enters live cells by crossing biological membranes spontaneously. This should prove useful to deliver drugs that lack this capacity on their own, provided that the dosage and exposure time are controlled to avoid toxicity.

CFD estimation of gas production in tight carbonates using single and dual-porosity models

Tight Carbonate reservoirs are regarded as one of the most complex reservoir formations due to the heterogeneity and complexity of their mineral composition, pore structure, and storage model. It is uncommon to study the implementation of a transport model appropriate for such formation. Recent studies focused on tight reservoirs and developed models for shale or coal bed methane reservoirs. This study proposes a single and dual-porosity transport model that solely considers the tight matrix and acidized region to shed light on the transport models for tight carbonates. The numerical model included the effect of transport mechanisms such as Knudsen diffusion, desorption, and viscous flow. The proposed transport model includes the apparent permeability model defining these transport mechanisms. Finite element method analysis was conducted on the numerical model using COMSOL Multiphysics. Due to the presence of nanopores in both shale and tight Carbonate, transport models proposed for the former can be utilized to determine the fluid flow behavior in the latter. The adsorption isotherm, rock density, pore structure, porosity, and permeability of the tight carbonate reservoir, which contrasted with the shale results, were the defining features of the reservoir used in the transport model. The dual-porosity model yielded a peak production of 104,000 m3/day, whereas the proposed model represents a shallow production rate from the single-porosity reservoir. The results were validated with an analytical solution proposed in the literature. Based on the literature findings and the production profile, the desorption did not play a significant role in the total production due to calcite's low affinity towards CH4.

Effects of probiotic supplementation in adult with atopic dermatitis: a systematic review with meta-analysis

BACKGROUND

Atopic dermatitis (AD) is one of the most common chronic inflammatory skin diseases. The effect of probiotic administration on the severity of AD in adults has shown inconsistent results.

OBJECTIVES

To determine the effectiveness of probiotic supplementation as a therapeutic tool for adult AD.

METHODS

PubMed, Scopus and Embase were systematically searched to collect data from studies in which probiotics were administered to treat adult AD.

RESULTS

Out of 413 publications, 9 papers were included in the meta-analysis. Significant differences in the ScORing Atopic Dermatitis tool favouring probiotics were observed [relative risk (RR) -5.93, 95% confidence interval (CI) -8.43 to -3.43]. Lactobacillus salivarius presented with largest effect size (RR -9.79, 95% CI -13.04 to -6.54), followed by L. acidophilus (RR -5.77, 95% CI -10.82 to -0.72) and L. plantarum (RR -3.76, 95% CI -6.36 to -1.16). No benefit was observed with L. fermentum. Based on the severity of AD, probiotics showed better results in people with moderate-to-severe AD (RR -9.12, 95% CI -12.17 to -6.08) than in individuals with mild disease (RR -2.67, 95% CI -4.67 to -0.66). Serum levels of IgE and eosinophil count remained significantly unchanged after the probiotic intervention (RR 0.25, 95% CI -0.10 to 0.60; RR -0.27, 95% CI -0.68 to 0.13, respectively).

CONCLUSIONS

Current evidence supports a role for some probiotics as a therapeutic tool for the treatment of adult AD, particularly in patients with severe AD. The efficacy of probiotics is strain specific, with L. salivarius and L. acidophilus having the largest clinical benefit. Such benefit is apparently independent of IgE levels and eosinophil count. Despite these encouraging results, the decrease in AD severity did not translate into a clinically meaningful better quality of life as assessed by the Dermatology Life Quality Index. There currently is not enough reliable data to reach conclusions about the optimal dose and duration for probiotic treatment.

Influence of an Organic Salt-Based Stabilizing Additive on Charge Carrier Dynamics in Triple Cation Perovskite Solar Cells

Besides further improvement in the power conversion efficiency (PCE) of perovskite solar cells (PSC), their long-term stability must also be ensured. Additives such as organic cations with halide counter anions are considered promising candidates to address this challenge, conferring both higher performance and increased stability to perovskite-based devices. Here, a stabilizing additive (N,N-dimethylmethyleneiminium chloride, [Dmmim]Cl) is identified, and its effect on charge carrier mobility and lifetime under thermal stress in triple cation perovskite (Cs0.05 MA0.05 FA0.90 PbI3 ) thin films is investigated. To explore the fundamental mechanisms limiting charge carrier mobility, temperature-dependent microwave conductivity measurements are performed. Different mobility behaviors across two temperature regions are revealed, following the power law Tm , indicating two different dominant scattering mechanisms. The low-temperature region is assigned to charge carrier scattering with polar optical phonons, while a strong decrease in mobility at high temperatures is due to dynamic disorder. The results obtained rationalize the improved stability of the [Dmmim]Cl-doped films and devices compared to the undoped reference samples, by limiting temperature-activated mobile ions and retarding degradation of the perovskite film.

Automatic detection of ictal activity in EEG using synchronization and chaos-based attributes

Automatic seizure onset detectors (SODs) have been proposed to alert epileptic patients when a seizure is about to happen and in turn improve their quality of life. Yet, the detectors proposed in literature are complex and difficult to implement in real-time as they utilize large feature sets with redundant and irrelevant features. Hence, the aim of this work is to propose a simple and lightweight SOD that exploits two characteristics that reflect the neuronal behavior during a seizure. Namely, the synchronization between EEG channels and the chaoticity of the EEG; synchronization was measured by the condition number while the recurrence period density entropy estimated the chaoticity of an EEG signal. A support vector machine was trained and tested on 10 patients from a scalp EEG dataset and was able to detect the considered seizures with a sensitivity of 100% and a false positives rate of 0.5 per hour. The results indicate that synchronization and chaos attributes can reflect the manifestation of seizures in EEG data and can be used to develop SODs. This work emphasizes that even a single relevant feature can produce an SOD with comparable performance to SODs that use many features.

Genome-wide association of dry (Tamar) date palm fruit color

Date palm (Phoenix dactylifera) fruit (dates) are an economically and culturally significant crop in the Middle East and North Africa. There are hundreds of different commercial cultivars producing dates with distinctive shapes, colors, and sizes. Genetic studies of some date palm traits have been performed, including sex determination, sugar content, and fresh fruit color. In this study, we used genome sequences and image data of 199 dry dates (Tamar) collected from 14 countries to identify genetic loci associated with the color of this fruit stage. Here, we find loci across multiple linkage groups (LG) associated with dry fruit color phenotype. We recover both the previously identified VIRESCENS (VIR) genotype associated with fresh fruit yellow or red color and new associations with the lightness and darkness of dry fruit. This study will add resolution to our understanding of date color phenotype, especially at the most commercially important Tamar stage.

Nanoengineered, Pd-doped Co@C nanoparticles as an effective electrocatalyst for OER in alkaline seawater electrolysis

Water electrolysis is considered one of the major sources of green hydrogen as the fuel of the future. However, due to limited freshwater resources, more interest has been geared toward seawater electrolysis for hydrogen production. The development of effective and selective electrocatalysts from earth-abundant elements for oxygen evolution reaction (OER) as the bottleneck for seawater electrolysis is highly desirable. This work introduces novel Pd-doped Co nanoparticles encapsulated in graphite carbon shell electrode (Pd-doped CoNPs@C shell) as a highly active OER electrocatalyst towards alkaline seawater oxidation, which outperforms the state-of-the-art catalyst, RuO2. Significantly, Pd-doped CoNPs@C shell electrode exhibiting low OER overpotential of ≈213, ≈372, and ≈ 429 mV at 10, 50, and 100 mA/cm2, respectively together with a small Tafel slope of ≈ 120 mV/dec than pure Co@C and Pd@C electrode in alkaline seawater media. The high catalytic activity at the aforementioned current density reveals decent selectivity, thus obviating the evolution of chloride reaction (CER), i.e., ∼490 mV, as competitive to the OER. Results indicated that Pd-doped Co nanoparticles encapsulated in graphite carbon shell (Pd-doped CoNPs@C electrode) could be a very promising candidate for seawater electrolysis.

Modulation of SLFN11 induces changes in DNA Damage response in breast cancer

BACKGROUND

Lack of Schlafen family member 11 (SLFN11) expression has been recently identified as a dominant genomic determinant of response to DNA damaging agents in numerous cancer types. Thus, several strategies aimed at increasing SLFN11 are explored to restore chemosensitivity of refractory cancers. In this study, we examined various approaches to elevate SLFN11 expression in breast cancer cellular models and confirmed a corresponding increase in chemosensitivity with using the most successful efficient one. As oncogenic transcriptomic downregulation is often driven by methylation of the promotor region, we explore the demethylation effect of 5-aza-2'-deoxycytidine (decitabine), on the SLFN11 gene. Since SLFN11 has been reported as an interferon inducible gene, and interferon is secreted during an active anti-tumor immune response, we investigated the in vitro effect of IFN-γ on SLFN11 expression in breast cancer cell lines. As a secondary approach to pick up cross talk between immune cells and SLFN11 expression we used indirect co-culture of breast cancer cells with activated PBMCs and evaluated if this can drive SLFN11 upregulation. Finally, as a definitive and specific way to modulate SLFN11 expression we implemented SLFN11 dCas9 (dead CRISPR associated protein 9) systems to specifically increase or decrease SLFN11 expression.

RESULTS

After confirming the previously reported correlation between methylation of SLFN11 promoter and its expression across multiple cell lines, we showed in-vitro that decitabine and IFN-γ could increase moderately the expression of SLFN11 in both BT-549 and T47D cell lines. The use of a CRISPR-dCas9 UNISAM and KRAB system could increase or decrease SLFN11 expression significantly (up to fivefold), stably and specifically in BT-549 and T47D cancer cell lines. We then used the modified cell lines to quantify the alteration in chemo sensitivity of those cells to treatment with DNA Damaging Agents (DDAs) such as Cisplatin and Epirubicin or DNA Damage Response (DDRs) drugs like Olaparib. RNAseq was used to elucidate the mechanisms of action affected by the alteration in SLFN11 expression. In cell lines with robust SLFN11 promoter methylation such as MDA-MB-231, no SLFN11 expression could be induced by any approach.

CONCLUSION

To our knowledge this is the first report of the stable non-lethal increase of SLFN11 expression in a cancer cell line. Our results show that induction of SLFN11 expression can enhance DDA and DDR sensitivity in breast cancer cells and dCas9 systems may represent a novel approach to increase SLFN11 and achieve higher sensitivity to chemotherapeutic agents, improving outcome or decreasing required drug concentrations. SLFN11-targeting therapies might be explored pre-clinically to develop personalized approaches.

The Potential Role of Thyroid Hormone Therapy in Neural Progenitor Cell Differentiation and Its Impact on Neurodevelopmental Disorders

Thyroid hormone (T3) plays a vital role in brain development and its dysregulation can impact behavior, nervous system function, and cognitive development. Large case-cohort studies have associated abnormal maternal T3 during early pregnancy to epilepsy, autism, and attention deficit hyperactivity disorder (ADHD) in children. Recent experimental findings have also shown T3's influence on the fate of neural precursor cells and raise the question of its convergence with embryonic neural progenitors. Our objective was to investigate how T3 treatment affects neuronal development and functionality at the cellular level. In vitro experiments using neural precursor cells (NPCs) measured cell growth and numbers after exposure to varying T3 concentrations. Time points included week 0 (W0) representing NPCs treated with 100 nM T3 for 5 days, and differentiated cortical neurons assessed at weeks 3 (W3), 6 (W6), and 8 (W8). Techniques such as single-cell calcium imaging and whole-cell patch clamp were utilized to evaluate neuronal activity and function. IHC staining detected mature neuron markers, and RNA sequencing enabled molecular profiling. W6 and W8 neurons exhibited higher action potential frequencies, with W6 showing increased peak amplitudes and shortened inter-spike intervals by 50%, indicating enhanced activity. Transcriptomic analysis revealed that W6 T3-treated neurons formed a distinct cluster, suggesting accelerated maturation. Comparison with the whole transcriptome further unveiled a correlation between W6 neurons treated with T3 and neuronal regulatory elements associated with autism and ADHD. These findings provide insights into T3's impact on neuronal development and potential mechanisms of T3 dysregulation and neurodevelopmental disorders.

Understanding the Genetics of Early-Onset Obesity in a Cohort of Children From Qatar

CONTEXT

Monogenic obesity is a rare form of obesity due to pathogenic variants in genes implicated in the leptin-melanocortin signaling pathway and accounts for around 5% of severe early-onset obesity. Mutations in the genes encoding the MC4R, leptin, and leptin receptor are commonly reported in various populations to cause monogenic obesity. Determining the genetic cause has important clinical benefits as novel therapeutic interventions are now available for some forms of monogenic obesity.

OBJECTIVE

To unravel the genetic causes of early-onset obesity in the population of Qatar.

METHODS

In total, 243 patients with early-onset obesity (above the 95% percentile) and age of onset below 10 years were screened for monogenic obesity variants using a targeted gene panel, consisting of 52 obesity-related genes.

RESULTS

Thirty rare variants potentially associated with obesity were identified in 36 of 243 (14.8%) probands in 15 candidate genes (LEP, LEPR, POMC, MC3R, MC4R, MRAP2, SH2B1, BDNF, NTRK2, DYRK1B, SIM1, GNAS, ADCY3, RAI1, and BBS2). Twenty-three of the variants identified were novel to this study and the rest, 7 variants, were previously reported in literature. Variants in MC4R were the most common cause of obesity in our cohort (19%) and the c.485C>T p.T162I variant was the most frequent MC4R variant seen in 5 patients.

CONCLUSION

We identified likely pathogenic/pathogenic variants that seem to explain the phenotype of around 14.8% of our cases. Variants in the MC4R gene are the commonest cause of early-onset obesity in our population. Our study represents the largest monogenic obesity cohort in the Middle East and revealed novel obesity variants in this understudied population. Functional studies will be required to elucidate the molecular mechanism of their pathogenicity.