Search Results (34)

The recent discovery of TIGR-Tas (Tandem Interspaced Guide RNA-Targeting Systems) marks a major advance in the field of genome editing, introducing a new class of compact, programmable DNA-targeting systems that function independently of traditional CRISPR-Cas pathways. TIGR-Tas effectors use a novel dual-spacer guide RNA (tigRNA) to recognize both strands of target DNA without requiring a protospacer adjacent motif (PAM). These Tas proteins introduce double-stranded DNA cuts with characteristic 8-nucleotide 3′ overhangs and are significantly smaller than Cas9, offering delivery advantages for in vivo editing. Structural analyses reveal homology to box C/D snoRNP proteins, suggesting a previously unrecognized evolutionary lineage of RNA-guided nucleases. This review positions TIGR-Tas at the forefront of a new wave of RNA-programmable genome-editing technologies. In parallel, I provide comparative insight into the diverse and increasingly modular CRISPR-Cas systems, including Cas9, Cas12, Cas13, and emerging effectors like Cas3, Cas10, CasΦ, and Cas14. While the CRISPR-Cas universe has revolutionized molecular biology, TIGR-Tas systems open a complementary and potentially more versatile path for programmable genome manipulation. I discuss mechanistic distinctions, evolutionary implications, and potential applications in human cells, synthetic biology, and therapeutic genome engineering. Full article

Background/Objectives: Preventive health behaviors are key to disease prevention and health system sustainability; however, population-level factors remain understudied in multilingual regions. South Tyrol, an autonomous multilingual province in Northern Italy, provides a unique setting to examine how sociodemographic and linguistic factors shape preventive behaviors. Methods: A stratified, population-representative survey of 2090 adults (aged ≥18 years) was conducted in South Tyrol in 2024. Preventive behavior was assessed using the validated 16-item Good Health Practices Scale (GHP-16). Key predictors included age, sex, education, living situation, language group, employment in the health/social sector, health literacy (HLS-EU-Q16), patient activation (PAM-10), and the mistrust of professional health information. Weighted statistics and multivariable linear regression were used to identify associations. Results: The GHP-16 scores varied significantly across sociodemographic and psychosocial strata. Female sex, older age, higher education, higher patient activation, and sufficient health literacy were independently associated with greater engagement in preventive behaviors. Patient activation showed the strongest graded effect (β = 1.739). The mistrust of health professionals was inversely associated with behavior (β = –0.050, 95% CI: –0.090 to –0.009). Italian speakers reported higher GHP-16 scores than German speakers (β = 0.377), even after adjusting for covariates. Item-level analysis revealed small but consistent differences, particularly in information-seeking and vaccination behavior. Conclusions: Preventive behaviors in South Tyrol are shaped by demographic, psychosocial, and linguistic factors. Patient activation and health literacy are key modifiable predictors, whereas language group differences suggest structural and trust-related disparities that require tailored public health strategies in multilingual settings. Full article

Multi-fingered dexterous hands provide superior dexterity in complex manipulation tasks due to their high degrees of freedom (DOFs) and biomimetic structures. Inspired by the anatomical structure of human tendons and muscles, numerous robotic hands powered by pneumatic artificial muscles (PAMs) have been created to replicate the compliant and adaptable features of biological hands. Nonetheless, PAMs have inherent nonlinear and hysteresis behaviors that create considerable challenges to achieving real-time control accuracy and stability in dexterous hands. In order to address these challenges, this paper proposes a hierarchical control architecture that employs a fuzzy PID strategy to optimize the nonlinear control of pneumatic artificial muscles (PAMs). The FPGA-based hardware integrates a multi-channel digital-to-analog converter (DAC) and a multiplexed acquisition module, facilitating the independent actuation of 20 PAMs and the real-time monitoring of 20 joints. The software implements a fuzzy PID algorithm that dynamically adjusts PID parameters based on both the error and the error rate, thereby effectively managing the nonlinear behaviors of the hand. Experimental results demonstrate that the designed control system achieves high precision in controlling the angle of a single finger joint, with errors maintained within ±1°. In scenarios involving multi-finger cooperative grasping and biomimetic motion demonstrations, the system exhibits excellent synchronization and real-time performance. These results validate the efficacy of the fuzzy PID control strategy and confirm that the proposed system fulfills the precision and stability requirements for complex operational tasks, providing robust support for the application of PAM-driven multi-fingered dexterous hands. Full article

In future hybrid fiber and radio access networks, wavelength division multiplexing passive optical networks (WDM-PON) based fifth-generation (5G) fronthaul systems are anticipated to coexist with current protocols, potentially leading to non-linearity impairment due to stimulated Raman scattering (SRS). To meet the loss budget requirements of 5G fronthaul networks, this paper investigates the power changes induced by SRS in WDM-PON based 5G fronthaul systems. The study examines wavelength allocation schemes utilizing both the C-band and O-band, with modulation formats including non-return-to-zero (NRZ), optical double-binary (ODB), and four-level pulse amplitude modulation (PAM4). Simulation results indicate that SRS non-linearity impairment causes a power depletion of 1.3 dB in the 20 km C-band link scenario, regardless of whether the modulation formats are 25 Gb/s or 50 Gb/s NRZ, ODB, and PAM4, indicating that the SRS-induced power changes are largely independent of both modulation formats and modulation rates. This effect occurs when only the upstream and downstream wavelengths of the 5G fronthaul are broadcast. However, when the 5G fronthaul wavelengths coexist with previous protocols, the maximum power depletion increases significantly to 10.1 dB. In the O-band scenario, the SRS-induced maximum power depletion reaches 1.5 dB with NRZ, ODB, and PAM4 modulation formats at both 25 Gb/s and 50 Gb/s. Based on these analyses, the SRS non-linearity impairment shall be fully considered when planning the wavelengths for 5G fronthaul transmission. Full article

Three-dimensional printing is promising in the pharmaceutical industry for personalized medicine, on-demand production, tailored drug loading, etc. Pressure-assisted microsyringe (PAM) printing is popular due to its low cost, simple operation, and compatibility with heat-sensitive drugs but is limited by ink formulations lacking the essential characteristics, impacting their performance. This study evaluates inks based on sodium alginate (SA), hydroxypropyl cellulose (HPC H), and hydroxypropyl methylcellulose (HPMC K100 and K4) for PAM 3D printing by analyzing their rheology. The formulations included the model drug Fenofibrate, functional excipients (e.g., mannitol, polyethylene glycol, etc.), and water or water–ethanol mixtures. Pills and thin films as an oral dosage were printed using a 410 μm nozzle, a 10 mm/s speed, a 50% infill density, and a 60 kPa pressure. Among the various formulated inks, only the ink containing 0.8% SA achieved successful prints with the desired shape fidelity, linked to its rheological properties, which were assessed using flow, amplitude sweep, and thixotropy tests. This study concludes that (i) an ink’s rheological properties—viscosity, shear thinning, viscoelasticity, modulus, flow point, recovery, etc.—have to be considered to determine whether it will print well; (ii) printability is independent of the dosage form; and (iii) the optimal inks are viscoelastic solids with specific rheological traits. This research provides insights for developing polymer-based inks for effective PAM 3D printing in pharmaceuticals. Full article

Purpose: Naegleria fowleri is the main etiologic agent implicated in primary amoebic meningoencephalitis (PAM). It is also known as the brain-eating amoeba because of the severe brain inflammation following infection, with a survival rate of about 5%. This review aims to identify Naegleria fowleri infections and evaluate patients’ progression. This literature review emphasizes the importance of rapid diagnosis and treatment of infected patients because only prompt initiation of appropriate therapy can lead to medical success. Compared to other articles of this kind, this one analyzes a large number of reported cases and all the factors that affected patients’ evolution. Materials and methods: Two independent reviewers used “Naegleria fowleri” and “case report” as keywords in the Clarivate Analytics—Web of Science literature review, obtaining 163 results. The first evaluation step was article title analysis. The two reviewers determined if the title was relevant to the topic. The first stage removed 34 articles, leaving 129 for the second stage. Full-text articles were evaluated after reading the abstract, and 77 were eliminated. This literature review concluded with 52 articles. Key findings: This review included 52 case report articles, 17 from the USA, eight from India, seven from China, four from Pakistan, two from the UK, and one each from Thailand, Korea, Japan, Italy, Iran, Norway, Turkey, Costa Rica, Zambia, Australia, Taiwan, and Venezuela, and Mexico. This study included 98 patients, with 17 women (17.4%) and 81 men (82.6%). The cases presented in this study show that waiting to start treatment until a diagnosis is confirmed can lead to rapid worsening and bad outcomes, especially since there is currently no drug that works very well as a treatment and the death rate is around 98%. Limitations: The lack of case presentation standardization may lead to incomplete case information in the review since the cases did not follow a writing protocol. The small number of global cases may also lead to misleading generalizations, especially about these patients’ treatment. Due to the small number of cases, there is no uniform sample of patients, making it difficult to determine the exact cause of infection. Full article

Photoacoustic imaging has emerged as a promising modality for medical imaging since its introduction. Photoacoustic microscopy (PAM), which is based on the photoacoustic effect, combines the advantages of both optical and acoustic imaging modalities. PAM facilitates high-sensitivity, high-resolution, non-contact, and non-invasive imaging by employing optical absorption as its primary contrast mechanism. The ability of PAM to specifically image parameters such as blood oxygenation and melanin content makes it a valuable addition to the suite of modern biomedical imaging techniques. This review aims to provide a comprehensive overview of the diverse technical approaches and methods employed by researchers to enhance the resolution of photoacoustic microscopy. Firstly, the fundamental principles of the photoacoustic effect and photoacoustic imaging will be presented. Subsequently, resolution enhancement methods for both acoustic-resolution photoacoustic microscopy (AR-PAM) and optical-resolution photoacoustic microscopy (OR-PAM) will be discussed independently. Finally, the aforementioned resolution enhancement methods for photoacoustic microscopy will be critically evaluated, and the current challenges and future prospects of this technology will be summarized. Full article

Photovoltaic (PV) power generation is highly stochastic and intermittent, which poses a challenge to the planning and operation of existing power systems. To enhance the accuracy of PV power prediction and ensure the safe operation of the power system, a novel approach based on seasonal division and a periodic attention mechanism (PAM) for PV power prediction is proposed. First, the dataset is divided into three components of trend, period, and residual under fuzzy c-means clustering (FCM) and the seasonal decomposition (SD) method according to four seasons. Three independent bidirectional long short-term memory (BiLTSM) networks are constructed for these subsequences. Then, the network is optimized using the improved Newton–Raphson genetic algorithm (NRGA), and the innovative PAM is added to focus on the periodic characteristics of the data. Finally, the results of each component are summarized to obtain the final prediction results. A case study of the Australian DKASC Alice Spring PV power plant dataset demonstrates the performance of the proposed approach. Compared with other paper models, the MAE, RMSE, and MAPE performance evaluation indexes show that the proposed approach has excellent performance in predicting output power accuracy and stability. Full article

A hyperspectral image (HSI) is often corrupted by various types of noise during image acquisition, e.g., Gaussian noise, impulse noise, stripes, deadlines, and more. Thus, as a preprocessing step, HSI denoising plays a vital role in many subsequent tasks. Recently, a variety of mixed noise removal approaches have been developed for HSI, and the methods based on spatial–spectral double factor and total variation (DFTV) regularization have achieved comparable performance. Additionally, the nonlocal low-rank tensor model (NLR) is often employed to characterize spatial nonlocal self-similarity (NSS). Generally, fully exploring prior knowledge can improve the denoising performance, but it significantly increases the computational cost when the NSS prior is employed. To solve this problem, this article proposes a novel DFTV-based NLR regularization (DFTVNLR) model for HSI mixed noise removal. The proposed model employs low-rank tensor factorization (LRTF) to characterize the spectral global low-rankness (LR), introduces 2-D and 1-D TV constraints on double-factor to characterize the spatial and spectral local smoothness (LS), respectively. Meanwhile, the NLR is applied to the spatial factor to characterize the NSS. Then, we developed an algorithm based on proximal alternating minimization (PAM) to solve the proposed model effectively. Particularly, we effectively controlled the computational cost from two aspects, namely taking small-sized double factor as regularization object and putting the time-consuming NLR model before the main loop with fewer iterations to solve it independently. Finally, considerable experiments on simulated and real noisy HSI substantiate that the proposed method is superior to the related state-of-the-art methods in balancing the denoising effect and speed. Full article

Experimental findings to contribute to the preliminary design of a metal foil pump for fuel separation in the Direct Internal Recycling loop of the DEMO fusion device are presented. In parametric studies on a small-scale superpermeation experiment with a microwave plasma source and two different metal foil materials, niobium Nb and vanadium V, a substantial increase in permeation with plasma power and with a decrease in pressure was observed. To ease operation in the typical fusion environment, in-situ heating procedures were developed to recover from impurity contamination. The temperature independence of plasma-driven permeation from 600 to 900 °C metal foil temperature was demonstrated. No proof of an isotopic effect for plasma-driven permeation of protium and deuterium could be found. The highest repeatable permeation flux achieved was 6.7 Pa∙m³/(m²∙s) or ~5.5 × 10⁻³ mol H/(m²∙s). The found compression ratios do safely allow the operation of the metal foil pump using ejector pumps as backing stages for the permeate. In a dedicated experimental setup, the operation of the plasma source in a strong magnetic field was tested. Parametric studies of pressure, power input, magnetic flux density, field gradient and field angle are presented. Full article

An innovative method, the clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 gene editing system, has significantly revolutionized agriculture by improving the quality of crops and sustaining the environment. CRISPR technology is based on the natural defense mechanism that bacteria and archaea have adapted against invading viruses or other foreign DNA. A genome engineering tool employs a similar mechanism for exceptional crop breeding progression due to its precise gene editing accuracy. This study outlines the present application of CRISPR/Cas9 technology to assess agricultural crop yield, quality, and texture modulation, palatability, nutritional components, disease resistance, and environmental stress. In plants, CRISPR/Cas9 geneediting includes the selection of specific target sites, single guide (sgRNA) design and synthesis, ribonucleoprotein (RNP) or transformation carrier delivery in plant cells, and gene-edited plant transformation and regeneration. The knockout of three mlo genes in wheat confers wheat resistance to powdery mildew disease. The CRISPR/Cas9 system knockout gene Clpsk1, which encodes phytosulfokine, indicates that watermelon with enhanced Fusarium wilt disease resistance can regulate plant immunity. The geneppa6 knockout has improved rice’s ability to withstand alkaline stress. Furthermore, the simultaneous editing of multiple genes has contributed to pathway-level plant biotechnology research that widely expands the genome engineering of agronomic traits and its adoptability. All the CRISPR/Cas systems require a specific PAM sequence, which guides the editing sites with specificity. Consequently, developing a PAM-independent CRISPR/Cas system, exploring new relationship between Cas proteins and the modification of Cas enzymes for expanding PAM variants will boost the application of CRISPR/Cas in applied research on agriculture, precision breeding, and ensuring food security. Full article

Extracellular vesicles (EVs) of protozoan parasites have diverse biological functions that are essential for parasite survival and host–parasite interactions. In this study, we characterized the functional properties of EVs from Naegleria fowleri, a pathogenic amoeba that causes a fatal brain infection called primary amoebic meningoencephalitis (PAM). N. fowleri EVs (NfEVs) have been shown to be internalized by host cells such as C6 glial cells and BV-2 microglial cells without causing direct cell death, indicating their potential roles in modulating host cell functions. NfEVs induced increased expression of proinflammatory cytokines and chemokines such as TNF-α, IL-1α, IL-1β, IL-6, IL-17, IFN-γ, MIP-1α, and MIP-2 in BV-2 microglial cells; these increases were initiated via MyD88-dependent TLR-2/TLR-4. The production levels of proinflammatory cytokines and chemokines in NfEVs-stimulated BV-2 microglial cells were effectively downregulated by inhibitors of MAPK, NF-κB, or JAK-STAT. Phosphorylation levels of JNK, p38, ERK, p65, JAK-1, and STAT3 were increased in NfEVs-stimulated BV-2 microglial cells but were effectively suppressed by each corresponding inhibitor. These results suggest that NfEVs could induce proinflammatory immune responses in BV-2 microglial cells via the NF-κB-dependent MAPK and JAK-STAT signaling pathways. Taken together, these findings suggest that NfEVs are pathogenic factors involved in the contact-independent pathogenic mechanisms of N. fowleri by inducing proinflammatory immune responses in BV-2 microglial cells, further contributing to deleterious inflammation in infected foci by activating subsequent inflammation cascades in other brain cells. Full article

Neutrophils are an essential cellular component of innate immunity and control bacterial infections through a combination of intracellular and extracellular killing methods. Although the importance of neutrophils has been established, the exact methods used to handle particular bacterial challenges and the efficiency of bacterial killing remain not well understood. In this study, we addressed how neutrophils eliminate Streptococcus pneumoniae (Spn), a leading cause of community acquired and post-influenza bacterial pneumonia. We analyzed killing methods with variable bacterial:neutrophil concentrations and following priming with PAM3CSK4 (P3CSK), an agonist for Toll-like-receptor 2 (TLR2). Our results show that murine neutrophils display surprisingly weak bactericidal activity against Spn, employing a predominantly extracellular mode of killing at lower concentrations of bacteria, whereas challenges with higher bacterial numbers induce both extracellular and intracellular elimination modes but require TLR2 activation. TLR2 activation increased reactive oxygen species (ROS) and neutrophil extracellular trap (NET) formation in response to Spn. Despite this, supernatants from P3CSK-stimulated neutrophils failed to independently alter bacterial replication. Our study reveals that unstimulated neutrophils are capable of eliminating bacteria only at lower concentrations via extracellular killing methods, whereas TLR2 activation primes neutrophil-mediated killing using both intracellular and extracellular methods under higher bacterial burdens. Full article

Gene expression can be used to subtype breast cancer with improved prediction of risk of recurrence and treatment responsiveness over that obtained using routine immunohistochemistry (IHC). However, in the clinic, molecular profiling is primarily used for ER+ breast cancer, which is costly, tissue destructive, requires specialised platforms, and takes several weeks to obtain a result. Deep learning algorithms can effectively extract morphological patterns in digital histopathology images to predict molecular phenotypes quickly and cost-effectively. We propose a new, computationally efficient approach called hist2RNA inspired by bulk RNA sequencing techniques to predict the expression of 138 genes (incorporated from 6 commercially available molecular profiling tests), including luminal PAM50 subtype, from hematoxylin and eosin (H&E)-stained whole slide images (WSIs). The training phase involves the aggregation of extracted features for each patient from a pretrained model to predict gene expression at the patient level using annotated H&E images from The Cancer Genome Atlas (TCGA, n = 335). We demonstrate successful gene prediction on a held-out test set (n = 160, corr = 0.82 across patients, corr = 0.29 across genes) and perform exploratory analysis on an external tissue microarray (TMA) dataset (n = 498) with known IHC and survival information. Our model is able to predict gene expression and luminal PAM50 subtype (Luminal A versus Luminal B) on the TMA dataset with prognostic significance for overall survival in univariate analysis (c-index = 0.56, hazard ratio = 2.16 (95% CI 1.12–3.06), p < 5 × 10⁻³), and independent significance in multivariate analysis incorporating standard clinicopathological variables (c-index = 0.65, hazard ratio = 1.87 (95% CI 1.30–2.68), p < 5 × 10⁻³). The proposed strategy achieves superior performance while requiring less training time, resulting in less energy consumption and computational cost compared to patch-based models. Additionally, hist2RNA predicts gene expression that has potential to determine luminal molecular subtypes which correlates with overall survival, without the need for expensive molecular testing. Full article

Developmentally regulated features of innate immunity are thought to place preterm and term infants at risk of infection and inflammation-related morbidity. Underlying mechanisms are incompletely understood. Differences in monocyte function including toll-like receptor (TLR) expression and signaling have been discussed. Some studies point to generally impaired TLR signaling, others to differences in individual pathways. In the present study, we assessed mRNA and protein expression of pro- and anti-inflammatory cytokines in preterm and term cord blood (CB) monocytes compared with adult controls stimulated ex vivo with Pam3CSK4, zymosan, polyinosinic:polycytidylic acid, lipopolysaccharide, flagellin, and CpG oligonucleotide, which activate the TLR1/2, TLR2/6, TLR3, TLR4, TLR5, and TLR9 pathways, respectively. In parallel, frequencies of monocyte subsets, stimulus-driven TLR expression, and phosphorylation of TLR-associated signaling molecules were analyzed. Independent of stimulus, pro-inflammatory responses of term CB monocytes equaled adult controls. The same held true for preterm CB monocytes—except for lower IL-1β levels. In contrast, CB monocytes released lower amounts of anti-inflammatory IL-10 and IL-1ra, resulting in higher ratios of pro-inflammatory to anti-inflammatory cytokines. Phosphorylation of p65, p38, and ERK1/2 correlated with adult controls. However, stimulated CB samples stood out with higher frequencies of intermediate monocytes (CD14⁺CD16⁺). Both pro-inflammatory net effect and expansion of the intermediate subset were most pronounced upon stimulation with Pam3CSK4 (TLR1/2), zymosan (TR2/6), and lipopolysaccharide (TLR4). Our data demonstrate robust pro-inflammatory and yet attenuated anti-inflammatory responses in preterm and term CB monocytes, along with imbalanced cytokine ratios. Intermediate monocytes, a subset ascribed pro-inflammatory features, might participate in this inflammatory state. Full article