Browse Articles

Cell-free expression and SMA copolymer encapsulation of a functional receptor tyrosine kinase disease variant, FGFR3-TACC3

Abstract Despite their high clinical relevance, obtaining structural and biophysical data on transmembrane proteins has been hindered by challenges involved in their expression and extraction in a homogeneous, functionally-active form. The inherent enzymatic activity of receptor tyrosine kinases (RTKs) presents additional challenges. Oncogenic fusions of RTKs with heterologous partners represent a particularly difficult-to-express protein subtype due to their high flexibility, aggregation propensity and the lack of a known method for extraction within the native lipid environment. One such protein is the fibroblast growth factor receptor 3 fused with transforming acidic coiled-coil-containing protein 3 (FGFR3-TACC3), which has failed to express to sufficient quality or functionality in traditional expression systems. Cell-free protein expression (CFPE) is a burgeoning arm of synthetic biology, enabling the rapid and efficient generation of recombinant proteins. This platform is characterised by utilising an optimised solution of cellular machinery to facilitate protein synthesis in vitro. In doing so, CFPE can act as a surrogate system for a range of proteins that are otherwise difficult to express through traditional host cell-based approaches. Here, functional FGFR3-TACC3 was expressed through a novel cell-free expression system in under 48 h. The resultant protein was reconstituted using SMA copolymers with a specific yield of 300 µg/mL of lysate. Functionally, the protein demonstrated significant kinase domain phosphorylation ( t  <  0.0001 ). Currently, there is no published, high-resolution structure of any full-length RTK. These findings form a promising foundation for future research on oncogenic RTKs and the application of cell-free systems for synthesising functional membrane proteins.

Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach

Improved robustness of sequentially deposited potassium cesium antimonide photocathodes achieved by increasing the potassium content towards theoretical stoichiometry

Abstract Alkali antimonide semiconductor photocathodes are promising candidates for high-brightness electron sources for advanced accelerators, including free-electron lasers (FEL), due to their high quantum efficiency (QE), low emittance, and high temporal resolution. Two challenges with these photocathodes are (1) the lack of a universal deposition recipe to achieve crystal stoichiometries and (2) their high susceptibility to vacuum contamination, which restricts their operation pressure to ultrahigh vacuums and leads to a short lifetime and low extraction charge. To resolve these issues, it is essential to understand the elemental compositions of deposited photocathodes and correlate them to robustness. Here, we report depth profiles for potassium cesium antimonide photocathodes, which were investigated using synchrotron radiation x-ray photoelectron spectroscopy, and the robustness of those photocathodes. We prepared two types of photocathodes with different potassium contents via sequential thermal evaporation. Depth profiles revealed that the photocathodes with a potassium deficit had excess cesium at the surface, while the ratio of potassium and cesium to antimony decreased rapidly within the film. In contrast, the photocathodes with sufficient potassium had close to the theoretical stoichiometry of K2CsSb at the surface and maintained that stoichiometry for over half the entire film thickness. Both photocathode types had a similar maximum QE at 532 nm; however, exposure to oxygen revealed that the photocathode with a crystalline stoichiometry of K2CsSb maintained QE at one order of magnitude higher pressure compared to its potassium-deficit counterpart. These results highlight the importance of synthesizing potassium cesium antimonide photocathodes with sufficient potassium to achieve the theoretical crystalline stoichiometry for both high QE and improved robustness.

Pharmacological and structural insights into nanvuranlat, a selective LAT1 (SLC7A5) inhibitor, and its N-acetyl metabolite with implications for cancer therapy

Climatic zoning of Xinjiang for heterogeneous production of high-quality wine

Relationships between structural stigma, societal stigma, and minority stress among gender minority people

Abstract Structural stigma towards gender minority (GM; people whose current gender does not align with sex assigned at birth) people is an important contributor to minority stress (i.e., stress experienced due to one’s marginalized GM identity), although existing variables are unclear in their inclusion of social norms, or societal stigma, as a key component of the construct. We examined potential variables representing structural stigma, including variables that are inclusive of societal stigma, to identify those that most strongly relate to minority stress outcomes. We tested variables identified in the literature as measures of structural stigma inclusive of societal stigma (LGBT + Business Climate Index, state voting behaviors, and Google Trends search data), the most commonly used structural stigma variable (State Policy Environment Tally), and proxy variables (region, population density) for comparison. The relationships between structural stigma and minority stress model outcomes were tested in a sample of GM participants from The Population Research in Identity and Disparities for Equality (PRIDE) Study (N = 2,094) 2019 Annual Questionnaire using a structural equation model (SEM). Lower structural stigma (i.e., higher LGBT Business Climate Index) was associated with lower experienced stigma (β= -0.260, p < .01) and lower anticipated stigma (β= -0.433, p < .001). Greater conservative voting behavior was associated with less experienced stigma (β= -0.103, p < .01). Living in a more densely populated county was also associated with lower anticipated stigma (β=-0.108, p < .001) and greater identity outness (β = 0.053, p < .05). Two of the identified structural stigma variables that were inclusive of societal stigma (i.e., LGBT + Business Climate Index, conservative voting behaviors) and one proxy variable (population density) were associated with minority stress outcomes. However, the most commonly used variable for structural stigma (State Policy Environment Tally) was not associated with any outcomes. The State LGBT + Business Climate Index showed the most promise for use as a structural stigma variable in future research. The application of this variable should be investigated further to explore its association with health outcomes and to inform efforts to reduce health equity barriers experienced by GM people through addressing structural stigma in a manner inclusive of societal stigma.

Correction to “Edge Length-Programmed Single-Stranded RNA Origami for Predictive Innate Immune Activation and Therapy”

Muscular TOR knockdown and endurance exercise ameliorate high salt and age-related skeletal muscle degradation by activating the MTOR-mediated pathway

The target of rapamycin(TOR)gene is closely related to metabolism and cellular aging, but it is unclear whether the TOR pathways mediate endurance exercise against the accelerated aging of skeletal muscle induced by high salt intake. In this study, muscular TOR gene overexpression and RNAi were constructed by constructing MhcGAL4/TOR-overexpression and MhcGAL4/TORUAS-RNAi systems in Drosophila. The results showed that muscle TOR knockdown and endurance exercise significantly increased the climbing speed, climbing endurance, the expression of autophagy related gene 2(ATG2), silent information regulator 2(SIR2), and pparγ coactivator 1(PGC-1α) genes, and superoxide dismutases(SOD) activity, but it decreased the expression of the TOR gene and reactive oxygen species(ROS) level, and it protected the myofibrillar fibers and mitochondria of skeletal muscle in Drosophila on a high-salt diet. TOR overexpression yielded similar results to the high salt diet(HSD) alone, with the opposite effect of TOR knockout found in regard to endurance exercise and HSD-induced age-related skeletal muscle degradation. Therefore, the current findings confirm that the muscle TOR gene plays an important role in endurance exercise against HSD-induced age-related skeletal muscle degeneration, as it determines the activity of the mammalian target of rapamycin(MTOR)/SIR2/PGC-1α and MTOR/ATG2/PGC-1α pathways in skeletal muscle.

Cooperative Anion−π Catalysis with Chiral Molecular Cages toward Enantioselective Desymmetrization of Anhydrides

The PSO-IFAH optimization algorithm for transient electromagnetic inversion

As a non-contact method, the transient electromagnetic (TEM) method has the characteristics of high efficiency, small impact of device, no limitation of site range, and high resolution, and is a hot topic in current research. However, the research on the refined data processing method of TEM is lag, which seriously restricts the application in superficial engineering investigation and is a key problem that needs to be solved urgently. The particle swarm optimization (PSO) algorithm and firefly algorithm (FA) were successful swarm intelligence algorithms inspired by nature. However, the accuracy and efficiency of the algorithm restrict its further development. In this paper, the particle moving velocity of FA algorithm is defined according to the concept of particle moving velocity in PSO algorithm, so as to improve the local fast convergence ability of FA algorithm. On this basis, the appropriate velocity of particle movement is improved, so that the improved algorithm can overcome the oscillation problem around the optimal solution and improve the computational efficiency. And finally, an improved PSO-IFA hybrid optimization algorithm (PSO-IFAH) was proposed in the paper. The proposed algorithm can exploit the strong points of both PSO and FA algorithm mechanisms. A typical layered model was established, and the PSO algorithm, FA algorithm, and PSO-IFAH algorithm were applied to inversion calculations. The results show that the PSO-IFAH algorithm improves calculation accuracy by more than 80% and efficiency by over 60% compared to the PSO and FA algorithms, respectively. The PSO-IFAH algorithm also exhibits high inversion accuracy and stability, with superior anti-noise properties compared to the other algorithms. When implemented in ground TEM measurement data processing, the PSO-IFAH algorithm enhances the resolution of anomalies and low-resistance details, aligning well with actual excavation results. This highlights the algorithm’s capability to depict underground electrical structures and karst developments accurately, thereby improving the precision of TEM data processing and interpretation.

Long, Synthetic <i>Staphylococcus aureus</i> Type 8 Capsular Oligosaccharides Reveal Structural Epitopes for Effective Immune Recognition

Exploring the association between sleep quality, internet addiction, and related factors among adolescents in Dakshinkali Municipality, Nepal

Background Poor sleep quality and internet addiction are significant issues affecting adolescents globally, and Nepal is no exception. Several studies have independently assessed the prevalence and associated factors of poor sleep quality and internet addiction among Nepali adolescents and youth, but the relationship between sleep-related attributes and internet addiction remains unexplored. This study aimed to explore the prevalence and contributing factors of poor sleep quality and internet addiction along with the relationship between sleep quality-related attributes and internet addiction. Material and methods A cross-sectional study was conducted among 243 adolescents of Dakshinkali Municipality, Nepal. Pittsburgh Sleep Quality Index and Young’s Internet Addiction Test scale were used to measure sleep quality and internet addiction. Pearson’s chi-square test and binary logistic regression were performed at a 5% level of significance to examine the associated factors. Results The prevalence of poor sleep quality was 27.6% (95% CI: 22.6–33.7) while potential internet addiction was 49.4% (95% CI: 42.0–56.7). Poor sleep quality was associated with internet addiction (aOR: 1.845; 95% CI: 1.344–3.608), poor perceived relation with teachers (aOR: 2.274; 95% CI: 1.149–4.497), and presence of family conflict (aOR: 2.355; 95% CI: 1.040–5.329). Bad subjective sleep quality (aOR: 5.613; 95% CI: 2.007–15.701), sleep disturbance (aOR: 1.781; 95% CI: 1.251–4.872), frequent daytime dysfunction (aOR: 1.902; 95% CI: 1.083–4.638), and poor perceived relation with teachers (aOR: 2.298; 95% CI: 1.233–4.285), and presence of family conflict (aOR: 1.606; 95% CI: 1.202–3.675) were associated with internet addiction. Conclusion Almost a quarter of adolescents’ experience poor sleep quality, while nearly half screened positive for potential internet addiction. Established interrelations between sleep quality and internet usage underscore the importance of integrated intervention approaches combining lifestyle modification and family/school support to protect and promote the mental health and well-being of Nepalese adolescents.

Mechanistic Investigations of Cobalt-Catalyzed, Aminoquinoline-Directed C(sp²)–H Bond Functionalization

Knowledge, attitude, and practice toward coronary heart disease secondary prevention among coronary heart disease patients in Shanghai, China

Background This study aimed to investigate knowledge, attitude, and practice (KAP) toward coronary heart disease (CHD) secondary prevention among CHD patients. Methods This web-based cross-sectional study enrolled patients with CHD who visited the Yangpu District Central Hospital in Shanghai (China) between October 18, 2022, and March 25, 2023. The administered questionnaire assessed demographic information and KAP; factors associated with good practice were identified by multivariate logistic regression. Results A total of 507 participants were included in the study, with 361 (71.2%) being male. In terms of education, 125 (24.7%) had a junior high school level or below. The mean scores for knowledge, attitudes, and practices were 31.28 ± 7.30 (possible range: 0–42), 54.09 ± 3.33 (possible range: 12–60), and 35.48 ± 3.36 (possible range: 11–55), respectively. For specific knowledge items on CHD, 57.6% of participants correctly identified that women are more susceptible to CHD. Physical labor and emotional excitement as triggers for CHD were correctly recognized by 94.1%. The need for long-term medication and follow-up after a CHD diagnosis had the highest correctness rate at 98.8%. Additionally, 84.6% correctly understood that recurrence of CHD is possible after PCI surgery. Multivariate analysis indicated that smoking and diabetes status were significantly associated with Practice scores. Current smokers reported lower practice levels than never smokers (OR = 2.858, 95% CI: 1.442–5.662, P = 0.003). Participants with diabetes reported higher practice levels than those without diabetes (OR = 4.169, 95% CI: 2.329–7.463, P &lt; 0.001). Conclusions Patients with CHD in Shanghai, China, demonstrated good knowledge and positive attitudes toward CHD secondary prevention, although there were some gaps in actual practice behaviors. Enhancing targeted educational interventions and support systems in clinical settings may help bridge these gaps and improve adherence to recommended preventive practices.

High Mobility Emissive Organic Semiconductors for Optoelectronic Devices

Automated extracellular volume fraction measurement for diagnosis and prognostication in patients with light-chain cardiac amyloidosis

Aims T1 mapping on cardiac magnetic resonance (CMR) imaging is useful for diagnosis and prognostication in patients with light-chain cardiac amyloidosis (AL-CA). We conducted this study to evaluate the performance of T1 mapping parameters, derived from artificial intelligence (AI)-automated segmentation, for detection of cardiac amyloidosis (CA) in patients with left ventricular hypertrophy (LVH) and their prognostic values in patients with AL-CA. Methods and results A total of 300 consecutive patients who underwent CMR for differential diagnosis of LVH were analyzed. CA was confirmed in 50 patients (39 with AL-CA and 11 with transthyretin amyloidosis), hypertrophic cardiomyopathy in 198, hypertensive heart disease in 47, and Fabry disease in 5. A semi-automated deep learning algorithm (Myomics-Q) was used for the analysis of the CMR images. The optimal cutoff extracellular volume fraction (ECV) for the differentiation of CA from other etiologies was 33.6% (diagnostic accuracy 85.6%). The automated ECV measurement showed a significant prognostic value for a composite of cardiovascular death and heart failure hospitalization in patients with AL-CA (revised Mayo stage III or IV) (adjusted hazard ratio 4.247 for ECV ≥40%, 95% confidence interval 1.215–14.851, p-value = 0.024). Incorporation of automated ECV measurement into the revised Mayo staging system resulted in better risk stratification (integrated discrimination index 27.9%, p = 0.013; categorical net reclassification index 13.8%, p = 0.007). Conclusions T1 mapping on CMR imaging, derived from AI-automated segmentation, not only allows for improved diagnosis of CA from other etiologies of LVH, but also provides significant prognostic value in patients with AL-CA.

Correction to “Total Syntheses of Scabrolide A and Yonarolide”

Citrus diseases detection using innovative deep learning approach and Hybrid Meta-Heuristic

Citrus farming is one of the major agricultural sectors of Pakistan and currently represents almost 30% of total fruit production, with its highest concentration in Punjab. Although economically important, citrus crops like sweet orange, grapefruit, lemon, and mandarins face various diseases like canker, scab, and black spot, which lower fruit quality and yield. Traditional manual disease diagnosis is not only slow, less accurate, and expensive but also relies heavily on expert intervention. To address these issues, this research examines the implementation of an automated disease classification system using deep learning and optimal feature selection. The system incorporates data augmentation and transfer learning with pre-trained models such as DenseNet-201 and AlexNet to improve diagnostic accuracy, efficiency, and cost-effectiveness. Experimental results on a citrus leaves dataset show an impressive 99.6% classification accuracy. The proposed framework outperforms existing methods, offering a robust and scalable solution for disease detection in citrus farming, contributing to more sustainable agricultural practices.

Biochemical and Computational Characterization of Haloalkane Dehalogenase Variants Designed by Generative AI: Accelerating the S_N2 Step

Prevalence and risk factors of the most common multimorbidity among Canadian adults

Background The number of persons living with multimorbidity–defined as the co-occurrence of at least two chronic conditions in the same individual–is growing globally, especially in developed countries. Traditionally, this increase has been attributed to a growing aging population, sedentary lifestyle, obesity, low socioeconomic status, and individual genetic susceptibility. Objective To investigate the prevalence and associated risk factors of the most common multimorbidity (MCM) among Canadian middle-aged and older adults. Method Relevant data on all 30,097 middle-aged and older Canadian adults (aged 45 to 85 years) from the Canadian Longitudinal Study on Aging were used for this study. To identify the specific sociodemographic risk factors associated with the MCM, we used survey-specific logistic regression. Findings Overall, co-occurrence of osteoarthritis and hypertension was identified as the MCM among Canadian adults aged 45+ with an estimated prevalence of 16.5%. The results from multivariate analysis showed that seven factors were significantly associated with increased odds of the MCM, which included increasing age, being retired from work (retired vs not retired), poorer rating of perceived health, (very good, good, poor vs excellent), increasing problems with sleep quality (satisfied, dissatisfied vs neutral), and abnormal body-mass index (underweight, overweight, obese vs normal). Also, residents in other urban centres had significantly lower odds than those in urban core. Persons living in Atlantic Canada, Ontario and Quebec were at increased odds of having the MCM compared to those in British Columbia. The odds of the MCM associated with increasing age was significantly higher among Females (OR = 1.12, 95% CI = 1.11–1.13) than Males (OR = 1.08, 95% CI = 1.07–1.10). Conclusion Multimorbidity is a common feature among Canadian adults. The identification of the most prevalent patterns and associated risk factors in this study provides fresh insights into the etiology, progression, and possible prevention of the MCM among Canadian adults.