Search Results (1,513)

Background: Lower phylogenetic species are known to rebuild cut-off caudal parts with regeneration of the central nervous system (CNS). In contrast, CNS regeneration in higher vertebrates is often attributed to immaturity, although this has never been conclusively demonstrated. The emergence of stem cells and their effective medical applications has intensified research into spinal cord regeneration. However, despite these advances, the impact of clinical trials involving spinal cord-injured (SCI) patients remains disappointingly low. Long-distance regeneration has yet to be proven. Methods: Our study involved a microsurgical dorsal myelotomy in fetal rats. The development of pioneering long primary afferent axons during early gestation was examined long after birth. Results: A single cut triggered the intrinsic ability of the dorsal root ganglion (DRG) neurons to reprogram. Susceptibility to hypoxia caused the axons to stop developing. However, the residual axonal outgrowth sheds light on the intriguing temporal and spatial events that reveal long-distance CNS regeneration. The altered phenotypes displayed axons of varying lengths and different features, which remained visible throughout life. The previously designed developmental blueprint was crucial for interpreting these enigmatic features. Conclusions: This research into immaturity enabled the exploration of the previously impenetrable domain of early life and the identification of a potential missing link in CNS regeneration research. Central axon regeneration appeared to occur much faster than is generally believed. The paradigm provides a challenging approach for exhaustive intrauterine reprogramming. When the results demonstrate pre-clinical effectiveness in CNS regeneration research, the transformational impact may ultimately lead to improved outcomes for patients with spinal cord injuries. Full article

Invasive infections with rare yeasts are increasing worldwide and are associated with higher mortality rates due to their resistance to antifungal drugs. Accurate antifungal susceptibility testing (AFST) is crucial for proper management of rare yeast infections. We performed AFST of 74 Candida kefyr isolates by Etest, EUCAST-based MICRONAUT-AM assay (MCN-AM) and reference Clinical and Laboratory Standards Institute broth microdilution method (CLSI). Essential agreement (EA, ±1 two-fold dilution), categorical agreement (CA), major errors (MEs) and very-major errors (VmEs) were determined using epidemiological cut-off values of ≤1.0 µg/mL, ≤0.03 µg/mL, ≤0.5 µg/mL and ≤1 µg/mL, defining wild-type isolates for fluconazole, voriconazole, micafungin and amphotericin B (AMB), respectively. Results for AMB susceptibility were correlated with ERG2/ERG3 mutations and total-cell sterols. CA of ≥97% was recorded between any two methods while EA varied between 72 and 82%, 87 and 92%, and 49 and 76% for fluconazole, voriconazole and micafungin, respectively. For AMB, CAs between CLSI and Etest; CLSI and MCN-AM; MCN-AM and Etest were 95% (4 ME, 0 VmE), 96% (3 ME, 0 VmE) and 99%, respectively, while EA varied from 32% to 69%. Non-synonymous ERG2/ERG3 mutations and no ergosterol were found in seven of eight isolates of non-wild types for AMB by Etest. Our data show that Etest, CLSI and MCN-AM methods are suitable for AFST of C. kefyr for fluconazole, voriconazole and micafungin. Excellent CAs for AMB between Etest and MCN-AM with concordant sterol profiles but not with CLSI suggest that Etest is also an excellent alternative for the detection of C. kefyr isolates with reduced susceptibility to AMB. Full article

Foodborne pathogenic bacteria critically threaten public health and food industry sustainability, serving as a predominant trigger of food contamination incidents. To mitigate these risks, the development of rapid, sensitive, and highly specific detection technologies is essential for early warning and effective control of foodborne diseases. In recent years, biosensors have gained prominence as a cutting-edge tool for detecting foodborne pathogens, owing to their operational simplicity, rapid response, high sensitivity, and suitability for on-site applications. This review provides a comprehensive evaluation of critical biorecognition elements, such as antibodies, aptamers, nucleic acids, enzymes, cell receptors, molecularly imprinted polymers (MIPs), and bacteriophages. We highlight their design strategies, recent advancements, and pivotal contributions to improving detection specificity and sensitivity. Additionally, we systematically examine mainstream biosensor-based detection technologies, with a focus on three dominant types: electrochemical biosensors, optical biosensors, and piezoelectric biosensors. For each category, we analyze its fundamental principles, structural features, and practical applications in food safety monitoring. Finally, this review identifies future research priorities, including multiplex target detection, enhanced processing of complex samples, commercialization, and scalable deployment of biosensors. These advancements are expected to bridge the gap between laboratory research and real-world food safety surveillance, fostering more robust and practical solutions. Full article

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

Lithium metal is a promising anode material for next-generation batteries due to its high specific capacity and low density. However, conventional mechanical processing methods are unsuitable due to lithium’s high reactivity and adhesion. Laser cutting offers a non-contact alternative, but photothermal effects can negatively impact the cutting quality and electrochemical performance. This study investigates the influence of pulse duration on the cutting-edge characteristics and electrochemical behavior of laser-cut 20 µm lithium metal on 10 µm copper foils using nanosecond and picosecond laser systems. It was demonstrated that shorter pulse durations significantly reduce the heat-affected zone (HAZ), resulting in improved cutting quality. Electrochemical tests in symmetric Li|Li cells revealed that laser-cut electrodes exhibit enhanced cycling stability compared with mechanically separated anodes, despite the presence of localized dead lithium “reservoirs”. While the overall pulse duration did not show a direct impact on ionic resistance, the characteristics of the cutting edge, particularly the extent of the HAZ, were found to influence the electrochemical performance. Full article

To address the issues of burr formation, structural deformation, and tearing in the conventional machining of Nomex honeycomb composites, this study aims to clarify the mechanisms by which ultrasonic vibration-assisted cutting enhances machining quality. A multi-scale analysis framework is developed to examine the effects of ultrasonic vibration on fiber distribution, cell-level shear response, and the overall cutting mechanics. At the microscale, analyses show that ultrasonic vibration mitigates stress concentrations, thereby shortening fiber length. At the mesoscale, elastic buckling and plastic yielding models show that ultrasonic vibration lowers shear strength and modifies the deformation. A macro-scale comparison of cutting behavior with and without ultrasonic vibration was conducted. The results indicate that the intermittent contact effect induced by vibration significantly reduces cutting force. Specifically, at an amplitude of 40 μm, the cutting force decreased by approximately 29.7% compared to the condition without ultrasonic vibration, with an average prediction error below 8.6%. Compared to conventional machining, which causes the honeycomb angle to deform to approximately 130°, ultrasonic vibration preserves the original 120° geometry and reduces burr length by 36%. These results demonstrate that ultrasonic vibration effectively reduces damage through multi-scale interactions, offering theoretical guidance for high-precision machining of fiber-reinforced composites. Full article

The use of aluminum honeycomb structures is fast expanding in advanced sectors such as the aeronautics, aerospace, marine, and automotive industries. However, processing these structures represents a major challenge for producing parts that meet the strict standards. To address this issue, an innovative manufacturing method using longitudinal ultrasonic vibration-assisted cutting, combined with a CDZ10 hybrid cutting tool, was developed to optimize the efficiency of traditional machining processes. To this end, a 3D numerical model was developed using the finite element method and Abaqus/Explicit 2017 software to simulate the complex interactions among the cutting tool and the thin walls of the structures. This model was validated by experimental tests, allowing the study of the influence of milling conditions such as feed rate, cutting angle, and vibration amplitude. The numerical results revealed that the hybrid technology significantly reduces the cutting force components, with a decrease ranging from 10% to 42%. In addition, it improves cutting quality by reducing plastic deformation and cell wall tearing, which prevents the formation of chips clumps on the tool edges, thus avoiding early wear of the tool. These outcomes offer new insights into optimizing industrial processes, particularly in fields with stringent precision and performance demands, like the aerospace sector. Full article

Background: Medullary thyroid carcinoma (MTC) is a rare malignancy derived from parafollicular C-cells, with calcitonin (Ct) as its key biomarker. While basal Ct (bCt) levels above 100 pg/mL strongly suggest MTC, intermediate elevations (10–100 pg/mL) may reflect C-cell hyperplasia (CCH) or other benign conditions, making diagnostics challenging. Although calcium stimulation testing enhances sensitivity, the optimal cut-off values and comparative efficacy of calcium gluconate (CG) versus calcium chloride (CC) remain insufficiently researched. Methods: Data on 176 patients who underwent total thyroidectomy between 2009 and 2025 were retrospectively analyzed. BCt values ranged from 10 to 100 pg/mL, and stimulated Ct (sCt) values were above 100 pg/mL. CG was used from 2009 to 2019, and CC was used from 2020 to 2025. Definitive pathohistological findings divided patients into those with MTC, CCH, or no C-cell pathology. Receiver operating characteristic (ROC) analysis identified optimal Ct thresholds for predicting MTC for each stimulatory agent. Results: Of the 176 patients, 36 (20.5%) had confirmed MTC. A bCt threshold of 31.1 pg/mL yielded 69.4% sensitivity and 87.1% specificity. For sCt, optimal cut-offs were 810.8 pg/mL for CG and 1076 pg/mL for CC. Lower thresholds (388.4 pg/mL for CG and 431.5 pg/mL for CC) improved sensitivity (≥76.9%) and negative predictive value (>91%). Conclusions: Calcium stimulation testing improves MTC detection in patients with moderate bCt elevation. Although CG showed marginally better diagnostic performance, CC remains a practical and reliable alternative, especially when higher cut-off values are considered. Early surgical intervention should be considered when sensitivity-driven thresholds are met. Full article

Subclinical mastitis causes economic losses due to reduced milk yield and elevated somatic cell counts (SCCs), despite no visible clinical signs. A higher incidence of subclinical mastitis has been reported in cattle infected with bovine leukemia virus (BLV). Levamisole (LMS), known for its immunomodulatory properties, has been suggested as a potential alternative to antibiotics for mastitis treatment; however, its efficacy in BLV-infected cows, particularly in relation to proviral load (PVL), remains unclear. This study aimed to evaluate the therapeutic effect of LMS on subclinical mastitis and its impact on milk immune responses by classifying BLV-infected cows based on PVL. A total of 42 dairy cows with subclinical mastitis (48 quarters) were grouped as BLV-negative, low-PVL, or high-PVL using a PVL cut-off value of 17.8 copies/10 ng DNA, and were administered LMS orally. Changes in viable bacterial counts, SCCs, and milk leukocyte populations were compared. LMS administration significantly reduced the SCC and milk macrophage numbers, especially in BLV-negative and low-PVL cows. These results suggest that LMS may improve subclinical mastitis in certain BLV-infected cows and that PVL may serve as a useful indicator for treatment responsiveness. However, the limited effect in high-PVL cows and the small sample size have limitations, warranting further investigation. Full article

Glucose metabolism reprogramming as a defining hallmark of cancer has become a pivotal frontier in oncology research. Recent technological advances in single-cell sequencing, spatial omics, and metabolic imaging have transformed the field from static bulk analyses to dynamic investigations of spatiotemporal heterogeneity at a single-cell resolution. This review systematically summarizes the current knowledge on tumor glucose metabolism dynamics, discussing spatial heterogeneity and temporal evolution patterns, metabolic subpopulation interactions revealed by single-cell metabolomics, the glucose metabolism–epigenetics–immunology regulatory axis, and therapeutic strategies targeting metabolic vulnerabilities. Recent technological advances in single-cell sequencing and spatial omics have transformed our understanding of tumor glucose metabolism by providing high-resolution insights into metabolic heterogeneity and regulatory mechanisms, contrasting with classical bulk analyses. Spatiotemporal heterogeneity critically influences therapeutic outcomes by enabling tumor cells to adapt metabolically under selective pressures (e.g., hypoxia, nutrient deprivation), fostering treatment resistance and relapse. Deciphering these dynamics is essential for developing spatiotemporally targeted strategies that address intratumoral diversity and microenvironmental fluctuations. By integrating cutting-edge advances, this review deepens our understanding of tumor metabolic complexity and provides a conceptual framework for developing spatiotemporally precise interventions. Full article

Polyethylene terephthalate (PET) pollution represents a significant environmental challenge due to its widespread use and recalcitrant nature. PET-degrading enzymes, particularly Ideonella sakaiensis PETases (IsPETase), have emerged as promising biocatalysts for mitigating this problem. This review provides a comprehensive overview of recent advancements in the discovery and heterologous expression of IsPETase and closely related enzymes. We highlight innovative approaches, such as in silico and AI-based enzyme screening and advanced screening assays. Strategies to enhance enzyme secretion and solubility, such as using signal peptides, fusion tags, chaperone co-expression, cell surface display systems, and membrane permeability modulation, are critically evaluated. Despite considerable progress, challenges remain in achieving industrial-scale production and application. Future research must focus on integrating cutting-edge molecular biology techniques with host-specific optimisation to achieve sustainable and cost-effective solutions for PET biodegradation and recycling. This review aims to provide a foundation for further exploration and innovation in the field of enzymatic plastic degradation. Full article

Background: Many patients harbor minimal residual disease (MRD)—small clusters of residual tumor cells that survive therapy and evade conventional detection but drive recurrence. Although advances in molecular and computational methods have improved circulating tumor DNA (ctDNA)-based MRD detection, these approaches face challenges: ctDNA shedding fluctuates widely across tumor types, disease stages, and histological features. Additionally, low levels of driver mutations originating from healthy tissues can create background noise, complicating the accurate identification of bona fide tumor-specific signals. These limitations underscore the need for refined technologies to further enhance MRD detection beyond DNA sequences in solid malignancies. Methods: Profiling circulating cell-free mRNA (cfmRNA), which is hyperactive in tumor and non-tumor microenvironments, could address these limitations to inform postoperative surveillance and treatment strategies. This study reported the development of OncoMRD BREAST, a customized, gene signature-informed cfmRNA assay for residual disease monitoring in breast cancer. OncoMRD BREAST introduces several advanced technologies that distinguish it from the existing ctDNA-MRD tests. It builds on the patient-derived gene signature for capturing tumor activities while introducing significant upgrades to its liquid biopsy transcriptomic profiling, digital scoring systems, and tracking capabilities. Results: The OncoMRD BREAST test processes inputs from multiple cutting-edge biomarkers—tumor and non-tumor microenvironment—to provide enhanced awareness of tumor activities in real time. By fusing data from these diverse intra- and inter-cellular networks, OncoMRD BREAST significantly improves the sensitivity and reliability of MRD detection and prognosis analysis, even under challenging and complex conditions. In a proof-of-concept real-world pilot trial, OncoMRD BREAST’s rapid quantification of potential tumor activity helped reduce the risk of incorrect treatment strategies, while advanced predictive analytics contributed to the overall benefits and improved outcomes of patients. Conclusions: By tailoring the assay to individual tumor profiles, we aimed to enhance early identification of residual disease and optimize therapeutic decision-making. OncoMRD BREAST is the world’s first and only gene signature-powered test for monitoring residual disease in solid tumors. Full article

Background: Recurrent implantation failure (RIF) poses a major challenge in assisted reproductive technologies, with thin endometrium (≤7 mm) being a frequently observed yet poorly understood condition. Emerging evidence implicates nuclear factor-kappa B (NF-κB), a key transcription factor in inflammatory signaling, in impaired endometrial receptivity. However, its clinical relevance and prognostic value for live birth outcomes still need to be fully elucidated. Objective: We aim to evaluate the expression levels of endometrial NF-κB in patients with RIF and thin endometrium and to determine its potential as a predictive biomarker for live birth outcomes following IVF treatment. Methods: In this prospective case–control study, 158 women were categorized into three groups: Group 1 (RIF with thin endometrium, ≤7 mm, n = 52), Group 2 (RIF with normal endometrium, >7 mm, n = 38), and fertile controls (n = 68). NF-κB levels were assessed using ELISA and immunohistochemical histoscore. Pregnancy outcomes were compared across groups. ROC analysis and multivariable logistic regression were performed to assess the predictive value of NF-κB. Results: NF-κB expression was significantly elevated in Group 1 compared to Group 2 and controls (p = 0.0017). ROC analysis identified a cut-off value of 7.8 ng/mg for live birth prediction (AUC = 0.72, sensitivity 74%, specificity 75%). Multivariable analysis confirmed NF-κB is an independent predictor of live birth (p = 0.045). Histological findings revealed increased NF-κB staining in luminal and glandular epithelial cells in the thin endometrium group. Conclusions: Increased endometrial NF-κB expression is associated with thin endometrium and reduced live birth rates in RIF patients. NF-κB may serve not only as a biomarker of pathological inflammation but also as a prognostic tool for treatment stratification in IVF. Based on findings in the literature, the therapeutic targeting of NF-κB may represent a promising strategy to improve implantation outcomes. Full article

According to the WHO, in 2022, there were 2.3 million women diagnosed with breast cancer (BC) and 670,000 deaths globally. BC remains the leading cause of cancer-related mortality, with therapeutic resistance representing a significant barrier to effective treatment, particularly in aggressive subtypes like triple-negative breast cancer (TNBC). This review article discusses emerging strategies to overcome resistance by integrating precision oncology, nanotechnology-based drug delivery, and immune modulation. Resistance mechanisms—such as metabolic reprogramming, tumor heterogeneity, immune evasion, autophagy, and the role of cancer stem cells—are critically examined. We highlight cutting-edge nanoplatforms that co-deliver chemotherapeutics and immune stimulants with spatiotemporal precision, including sonodynamic and photothermal systems, ADCs, and targeted nanoparticles. Moreover, advances in tumor microenvironment (TME) modulation, photoimmunotherapy, and exosomal miRNA targeting offer promising avenues to enhance immunogenicity and therapeutic durability. The integration of molecular profiling with advanced computational approaches, including artificial intelligence and biomimetic models, holds significant promise for the future development of personalized resistance-mitigating interventions, though a detailed exploration is beyond the current scope. Collectively, these strategies reflect a paradigm shift from conventional monotherapies toward multifaceted, precision-guided treatment approaches. This review aims to provide a comprehensive overview of current innovations and propose future directions for overcoming drug resistance in BC. Full article

Transposons are mobile genetic elements capable of moving within the genome. Leveraging this property—particularly the cut-and-paste mechanism of DNA transposons—has enabled the development of technologies for inserting exogenous DNA fragments into host genomes. While targeted integration is a key goal for therapeutic applications, this review highlights the value of their intrinsic randomness. By combining the ability to freely design the DNA cargo with the stochastic nature of transposon integration, it becomes possible to generate highly sensitive reporter cells. These can be used to efficiently identify functional markers, uncover novel signaling pathways, and establish innovative platforms for drug screening. As more subfamilies of transposons become available for research use, their complementary biases may enhance the coverage and diversity of genome-wide screening approaches. Although inherently unpredictable, this strategy embraces randomness as a strength, and we propose that it holds great promise for driving new advances in biology, cellular engineering, and medical research. Full article