Browse Articles

Systematic identification and characterization of high efficiency Cas9 guide RNAs for therapeutic targeting of ADAR

Therapeutic targeting of the adenosine deaminase ADAR has great potential in cancer and other indications; however, it remains unclear what approach can enable effective and selective therapeutic inhibition. Herein, we conduct multi-staged guide RNA screening and identify high efficiency Cas9 guide RNAs to enable a CRISPR/Cas-based approach for ADAR knockout. Through characterization in human primary immune cell systems we observe similar activity with two-part guide RNA and single guide RNA, dose responsive activity, similar guide activity rank order across different cell types, and favorable computational off-target profiles of candidate guide RNAs. We determine that knockout of ADAR using these guide RNAs induces pharmacodynamic responses primarily consisting of immunological responses such as a type I interferon response, consistent with the known function of ADAR as a key regulator of dsRNA sensing. We observe similar biological effects with targeting only the p150 isoform or both p110 and p150 isoforms of ADAR, indicating that at least in the contexts evaluated, loss of p150 ADAR mediates the primary response. These findings provide a resource of well-characterized, high efficiency ADAR-targeting Cas9 guide RNAs suitable for genomic medicines utilizing different delivery modalities and addressing different therapeutic areas.

Unstable foveation’s impact on reading, object tracking, and its implications for diagnosing and intervening in reading difficulties

Evaluation of stroke sequelae and rehabilitation effect on brain tumor by neuroimaging technique: A comparative study

This study aims at the limitations of traditional methods in the evaluation of stroke sequelae and rehabilitation effect monitoring, especially for the accurate identification and tracking of brain injury areas. To overcome these challenges, we introduce an advanced neuroimaging technology based on deep learning, the SWI-BITR-UNet model. This model, introduced as novel Machine Learning (ML) model, combines the SWIN Transformer’s local receptive field and shift mechanism, and the effective feature fusion strategy in the U-Net architecture, aiming to improve the accuracy of brain lesion region segmentation in multimodal MRI scans. Through the application of a 3-D CNN encoder and decoder, as well as the integration of the CBAM attention module and jump connection, the model can finely capture and refine features, to achieve a level of segmentation accuracy comparable to that of manual segmentation by experts. This study introduces a 3D CNN encoder-decoder architecture specifically designed to enhance the processing capabilities of 3D medical imaging data. The development of the 3D CNN model utilizes the ADAM optimization algorithm to facilitate the training process. The Bra2020 dataset is utilized to assess the accuracy of the proposed deep learning neural network. By employing skip connections, the model effectively integrates the high-resolution features from the encoder with the up-sampling features from the decoder, thereby increasing the model’s sensitivity to 3D spatial characteristics. To assess both the training and testing phases, the SWI-BITR-Unet model is trained using reliable datasets and evaluated through a comprehensive array of statistical metrics, including Recall (Rec), Precision (Pre), F1 test score, Kappa Coefficient (KC), mean Intersection over Union (mIoU), and Receiver Operating Characteristic-Area Under Curve (ROC-AUC). Furthermore, various machine learning models, such as Random Forest (RF), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Adaptive Boosting (AdaBoost), and K-Nearest Neighbor (KNN), have been employed to analyze tumor progression in the brain, with performance characterized by Hausdorff distance. In From the performance of ML models, the SWI-BITR-Unet model was more accurate than other models. Subsequently, regarding DICE coefficient values, the segmentation maps (annotation maps of brain tumor distributions) generated by the ML models indicated the models’s capability to autonomously delineate areas such as the tumor core (TC) and the enhancing tumor (ET). Moreover, the efficacy of the proposed machine learning models demonstrated superiority over existing research in the field. The computational efficiency and the ability to handle long-distance dependencies of the model make it particularly suitable for applications in clinical Settings. The results showed that the SNA-BITR-UNet model can not only effectively identify and monitor the subtle changes in the stroke injury area, but also provided a new and efficient tool in the rehabilitation process, providing a scientific basis for developing personalized rehabilitation plans.

Optimizing irrigation and nitrogen levels to achieve sustainable rice productivity and profitability

Abstract The global scarcity of irrigation water poses a significant challenge to the sustainable production of rice and its availability worldwide. With a growing population driving increased demand for rice, it is crucial to enhance rice production while minimizing water usage. Achieving this requires a comprehensive understanding of the complex interactions between water and nitrogen dynamics and the formulation of strategies to optimize the application of irrigation water and nitrogen fertilizers. This study aims to investigate the impact of varying irrigation regimes and nitrogen application rates on rice growth attributes, yield performance, overall crop productivity, and economic returns. In the 2021 and 2022 rice growing season, two field experiments were carried out in split plot design with four nitrogen levels in sub plots [N0: Control, N1: 75% RDN (Recommended dose of nitrogen; @ 120 kg N ha−1), N2: 100% RDN, and N3: 125% RDN] and four irrigation treatments in main plots [I1: recommended irrigation scheduling, I2: at field capacity (20 L m−2), I3: 10% depletion from field capacity (20 L m−2), and I4: 20% depletion from field capacity (20 L m−2). The experiments were replicated three times. The suggested irrigation scheduling treatment (flooded) showed improved growth characteristics, such as plant height, dry matter accumulation, leaf area index, tiller count, SPAD (Soil Plant Analysis Development) value, NDVI (Normalized Difference Vegetation Index) value, leaf relative water content, and yield attributes; however, these were comparable to the application of irrigation water at field capacity. Due to improved plant growth and yield-attributing characteristics, the I1 treatment recorded the highest grain yield of 8.58 t ha−1 and 8.4 t ha−1, although it was comparable to the I2 treatment, which had grain yields of 8.27 t ha−1 and 8.15 t ha−1 in 2021 and 2022. The grain yield reported by the N3 treatment were significantly greater than those of the N2 treatment, IN 2021 and 2022 respectively. Applying nitrogen at 125% RDN (Recommended dose of nitrogen) and irrigation water at field capacity produced the highest benefit–cost ratio (1.64), which was closely followed by the same irrigation regime and 100% RDN application (1.60 BC ratio). Comparable to irrigation at field capacity, the suggested irrigation schedule demonstrated enhanced growth features, yield attributes, productivity, and profitability. The best way to achieve the optimum growth, productivity, and profitability in transplanted rice was to provide irrigation water at field capacity and nitrogen @ 100% RDN.

Trekking across Nepal to bridge its gender gap in the sciences

Pathways to sustainability: Higher education and green productivity

The research conducted theoretical analysis and empirical testing on the relationship between higher education and regional green productivity based on panel data from 30 Chinese provinces from 2003 to 2021. The study’s findings demonstrate that higher education can have a major impact on local green production. In order to determine whether industrial structure upgrading and the digital economy work together to promote the development of green productivity, higher education is added to these factors at the same time as the new economic growth mode transformation in the digital economy era. The research hypothesis aligns with the results, suggesting that higher education and the digital economy collaborate to enhance green productivity levels. Higher education has a more significant impact on green productivity the greater the level of regional economic growth, according to a further nonlinear test utilizing the partial linear function coefficient (PLFC) model. Higher education’s influence on green production varies by place and period, becoming more pronounced as time passes and the degree of regional economic growth rises. In order to fully utilize higher education’s capacity for scientific research, innovation, and talent, as well as to increase the direct contribution of its scientific and technological innovations to the advancement of national industry and production promotion, it is imperative that people actively promote the new type of industrialization, develop the digital economy, and work in tandem with higher education.

Cone beam computed tomography based upper airway measurement after orthognathic surgery: a comparative evaluation of different imaging software

Abstract Cone-beam computed tomography (CBCT) enhances understanding of the upper airway (UA). This study compared three software products’ abilities in visualizing and quantifying specific upper airway changes using CBCT. We conducted a retrospective analysis of pre- and post-operative CBCT images from 29 patients using Dolphin (Do), Romexis 5 (Ro5), and Romexis 6 (Ro6) software, focusing on alterations in oropharyngeal volume and minimum cross-sectional area as key indicators of orthognathic surgery outcomes. ANOVA analysis showed significant differences in volume measurements between Do/Ro5 (p = 0.034) and Do/Ro6 (p = 0.047), but no difference between Ro5 and Ro6 (p = 0.685). No significant differences were found in minimum cross-sectional area parameters. Despite standardized protocols, interpretation discrepancies exist between Do and Ro 5/6, possibly due to program-specific properties. Further studies on threshold value comparability are needed for data standardization. Direct comparisons of clinical data from Do, Ro5, and Ro6 are limited due to methodological disparities. Nonetheless, these programs allow reproducible and quantifiable measurements for clinical assessments of these specific airway changes following orthognathic surgery.

Mutational alterations in the QRDR regions associated with fluoroquinolone resistance in Pseudomonas aeruginosa of clinical origin from Savar, Dhaka

Bacterial DNA gyrase and topoisomerase IV are the major targets of quinolone antibiotic, and mutational alterations in quinolone resistance determining regions (QRDR) serve as major mechanism of resistance in most bacterial species, including P. aeruginosa. The present investigation was aimed to study the molecular mechanism of fluoroquinolone resistance among clinical P. aeruginosa isolated from Dhaka, Bangladesh, including alterations in target sites of the antimicrobial action. Laboratory collection of 53 P. aeruginosa were subjected to conventional cultural and biochemical characterization, followed by molecular identification using 16S rDNA sequencing. Susceptibility to ciprofloxacin and levofloxacin was tested by disc diffusion method followed by MIC assay. Resistant isolates were analyzed for mutation in their QRDR regions of gyrA and parC, and subjected to PCR detection of plasmid mediated quinolone resistance (PMQR) genes qnrA, qnrS and qnrB. Among the isolates, 28% were found to be resistant to both fluoroquinolones tested. All of the fluoroquinolone resistant isolates carried a single mutation in gyrA (Thr-83-Ile), while 20% carried a single parC mutation (Ser-87-Leu). Higher level of MIC was observed in isolates carrying alterations at both sites. None of the isolates harbored any PMQR genes investigated, suggesting that chromosomal mutations in QRDR regions to be the major contributing factor for quinolone resistance in P. aeruginosa under investigation.

Genetic analyses reveal association between rosacea and cardiovascular diseases

Time-sensitive effects of quercetin on rat basophilic leukemia (RBL-2H3) cell responsiveness and intracellular signaling

Quercetin is known for its ability to inhibit mast cell degranulation and reduce the release of inflammatory mediators. However, it has also been reported to sensitize mast cells, potentially leading to hyperresponsiveness. This necessitates careful optimization of its use in the treatment of chronic inflammatory diseases. To fully harness quercetin’s therapeutic potential, this study investigated the effects of quercetin on rat basophilic leukemia (RBL-2H3) cells responsiveness over varying durations of exposure. We employed comprehensive transcriptome analysis and subsequent functional validation of key signaling pathways. Our findings revealed that quercetin initially reduced cell activity with short-term treatment. However, with prolonged exposure, quercetin transiently enhanced both IgE cross-linkage-mediated and non-IgE-mediated responses. Specifically, prolonged quercetin treatment downregulated IgE-mediated degranulation and FcεRI expression, while potentially sensitizing RBL-2H3 cells to other non-IgE secretagogues through enhanced PKC activity. Given quercetin’s multifaceted effects on intracellular signaling pathways, it is crucial to further investigate its efficacy and potential risk of adverse effects. Future studies should focus on a deeper understanding of these mechanisms to optimize quercetin’s therapeutic applications while mitigating any possible negative outcomes.

Shear wave elastography, as a feasible tool, can be used to reflect the lower limb dysfunction in patients with chronic obstructive pulmonary disease?

UK PhD students welcome 8% pay boost, but demand more to meet rising living costs

Victimization status among persons with disabilities and its predictors: Evidence from Bangladesh National Survey on Persons with Disabilities

Background Persons with disabilities often face various forms of victimization, yet there is limited research exploring this phenomenon in Bangladesh. This study aims to investigate the victimization status among persons with disabilities and identify its predictors. Methods Data of 4293 persons with disabilities analyzed in this study were extracted from the 2021 National Survey on Persons with Disabilities. Victimization status (yes, no) was considered as the outcome variables. Explanatory variables considered were factors at the individual, household, and community levels. A multilevel mixed-effect logistic regression model was used to explore the association of the outcome variable with explanatory variables by dividing the total sample into age groups of 0–17 years, 18–59 years, and ≥ 60 years. Results The study found that 44% of persons with disabilities in Bangladesh experienced victimization, primarily involving neighbours (90.64%), relatives (43.41%), friends (28.41%), and family members (27.07%). Among persons aged 0–17 years, increasing age was associated with a higher likelihood of being victimized, while residing in the wealthiest households or in certain divisions like Khulna and Rangpur was associated with lower likelihoods. Conversely, among respondents aged 18–59 and ≥ 60 years, increasing age was associated with a lower likelihood of being victimized. Unmarried respondents aged 18–59 years had an increased likelihood of victimization compared to married individuals. For persons with disabilities aged ≥ 60 years, a higher level of schooling was associated with a reduced likelihood of being victimized. We also found divisional differences in the likelihood of victimization, with respondents residing in Chattogram, Khulna, Mymensingh, Rangpur, and Sylhet reporting lower likelihoods compared to those residing in the Barishal division, among persons with disabilities aged 18–59 and ≥ 60 years. Conclusion This study’s findings underscore that around 4 in 10 persons with disabilities are being victimized. Tailored programs and awareness-building initiatives covering neighbours, relatives, friends, and family members of persons with disabilities are important to ensure dignified lives for this population.

Intermittent hypoxia-induced enhancements in corticospinal excitability predict gains in motor learning and metabolic efficiency

Exploring cotton plant compounds for novel treatments against brain-eating Naegleria fowleri: An In-silico approach

To find potential inhibitors of Naegleria fowleri S-adenosyl-L-homocysteine hydrolase (NfSAHH), a brain-eating parasite, structure-based drug design was adopted. N. fowlerica causes primary amebic meningoencephalitis (PAM), a fatal central nervous system (CNS) disorder if untreated. NfSAHH protein (PDB ID: 5v96), involved in parasite growth and gene regulation, was targeted and screened against 163 metabolites from Gossypium hirsutum (cotton plant). With the aid of different software and web tools, the metabolites were subjected to several analyses. The RMSD was evaluated to validate our molecular docking strategy. Neplanocin A, a common anti-parasitic medication, was used as a reference to select top ligands for post-docking studies. Significant interactions were observed with residues THR-198, HIS-395, and MET-400. The drug-likeness of the top fifty hits was analyzed using Lipinski, Ghose, Veber, Egan, and Muegge rules. The top ten compounds following Lipinski’s RO5 were studied regarding medicinal chemistry, pharmacokinetic simulation, and Swiss target prediction. Advanced strategies, including molecular dynamic simulations, binding energy calculations, and principal component analysis, were employed for the top three hits, namely curcumin, heliocide H2, and piceid, which indicated that heliocide H2 is the most promising candidate, while curcumin and piceid may need further optimization to improve their stability. Overall, the top ten phytochemicals, dotriacontanol, melissic acid, curcumin, 6,6′-dimethoxygossypol, phytosphingosine 2, methyl stearate, stearic acid, piceid, heliocide H2, and 6-methoxygossypol, reported in our study, are worthy enough to be subjected to in vivo and in vitro experimentation to find a novel drug to treat PAM.

Spleen volume in relation to ulcerative colitis and Crohn’s disease: a Mendelian randomization study

Daily briefing: What science photos do that AI-generated images can’t

Field-based investigation of failure modes and thresholds of granite residual soil slopes under heavy rainfall conditions

Rainfall is a primary coefficient of slope instability. To study patterns of slope failure mode and key index threshold values of slope instability under varying rainfall intensities, real-time data from in-situ monitoring tests of an engineering slope were utilized. This data facilitated the analysis of the temporal and spatial responses of a rainfall infiltration slope. Four field tests were conducted under four different rainfall intensities, namely 75mm/h, 125mm/h, 150mm/h, and 175mm/h, to study the progressive failure characteristics of the granite residual soil slope. These characteristics were studied based on water-time and displacement-time curves, and the rainfall duration and threshold for slope instability were proposed. The result revealed that the granite residual soil slope undergoes progressive failure under rainfall conditions, which can be categorized into four modes: “shallow local sliding”,“shallow global sliding and collapse”, “deep local sliding”, and“deep global sliding”. It takes 25 ~ 135min for the shallow sliding failure characteristics from significant deformation to instability, while the deep sliding only lasts for 18 ~ 20min. A significant correlation was observed between soil moisture content and slope instability. Instability symptoms such as cracking and peristaltic deformation begin to appear when the soil moisture content in the shallow layer of the slope increases to 42 ~ 45%. When the soil moisture content escalates to 47 ~ 50%, the slope begins to disintegrate, leading to rapid landslides and collapses.

Comparative metabolomic analysis reveals shared and unique features of COVID-19 cytokine storm and surgical sepsis

Outcomes of percutaneous transhepatic gallbladder drainage versus percutaneous transhepatic biliary drainage for obstructive jaundice

Percutaneous transhepatic gallbladder drainage (PTGBD) is an alternative to percutaneous transhepatic biliary drainage (PTBD) for cases with obstructive jaundice in which the bile duct obstruction is below the confluence of the cystic ducts. This retrospective study aimed to evaluate the usefulness of PTGBD and PTBD in patients with obstructive jaundice. We recruited patients who had undergone percutaneous biliary drainage for acute cholangitis and obstructive jaundice at two institutions between January 2017 and March 2024. In principle, PTBD was the first choice. PTGBD was selected for cases where the intrahepatic bile duct diameter was ≤ 5 mm or ≥ 6 mm with significant respiratory-related variability of the positioning of the bile ducts. In other cases, PTBD was chosen. Fifty-five patients were included in this analysis. However, patients with intrahepatic or hilar bile duct stenosis, post choledocholithiasis, complex cholecystitis, total bilirubin levels of < 2.0 mg/dL, and uncorrectable bleeding tendency and those who had undergone the procedure and later discontinued without puncture were excluded. The technical success rates, clinical success rates, and complication rates of the procedure were evaluated. The technical success rates were 96.3% (26/27) and 82.1% (23/28) in the PTGBD and PTBD groups, respectively. The clinical success rates were 85.2% (23/27) and 67.9% (19/28) in the PTGBD and PTBD groups, respectively. The complication rates were 18.5% (5/27) and 25.0% (7/28) in the PTGBD and PTBD groups, respectively. No serious complications were observed in either group. Hence, the two groups did not significantly differ in any of the endpoints. The outcomes of PTGBD were comparable to those of PTBD in patients with obstructive jaundice. Hence, PTGBD is a reasonable treatment option for cases of obstructive jaundice in which PTBD is not feasible.