Search Results (107)

Glioblastoma (GBM) is one of the most common and aggressive primary malignant tumors of the central nervous system, accounting for about half of all gliomas in adults. Despite intensive research and advances in molecular biology, genomics, and modern neuroimaging techniques, the prognosis for patients with GBM remains extremely poor. Despite the implementation of multimodal treatment involving surgery, radiotherapy, and chemotherapy with temozolomide, the average survival time of patients is only about 15 months. This is primarily due to the complex biology of this cancer, which involves numerous genetic and epigenetic abnormalities, as well as a highly heterogeneous tumor structure and the presence of glioblastoma stem cells with self renewal capacity. Mutations and abnormalities in genes such as IDH-wt, EGFR, PTEN, TP53, TERT, and CDKN2A/B are crucial in the pathogenesis of GBM. In particular, IDH-wt status (wild-type isocitrate dehydrogenase) is one of the most important identification markers distinguishing GBM from other, more favorable gliomas with IDH mutations. Frequent EGFR amplifications and TERT gene promoter mutations lead to the deregulation of tumor cell proliferation and increased aggressiveness. In turn, the loss of function of suppressor genes such as PTEN or CDKN2A/B promotes uncontrolled cell growth and tumor progression. The immunosuppressive tumor microenvironment also plays an important role, promoting immune escape and weakening the effectiveness of systemic therapies, including immunotherapy. The aim of this review is to summarize the current state of knowledge on the epidemiology, classification, pathogenesis, diagnosis, and treatment of glioblastoma multiforme, as well as to discuss the impact of recent advances in molecular and imaging diagnostics on clinical decision-making. A comprehensive review of recent literature (2018–2025) was conducted, focusing on WHO CNS5 classification updates, novel biomarkers (IDH, TERT, MGMT, EGFR), and modern diagnostic techniques such as liquid biopsy, radiogenomics, and next-generation sequencing (NGS). The results of the review indicate that the introduction of integrated histo-molecular diagnostics in the WHO 2021 classification has significantly increased diagnostic precision, enabling better prognostic and therapeutic stratification of patients. Modern imaging techniques, such as advanced magnetic resonance imaging (MRI), positron emission tomography (PET), and radiomics and radiogenomics tools, allow for more precise assessment of tumor characteristics, prediction of response to therapy, and monitoring of disease progression. Contemporary molecular techniques, including DNA methylation profiling and NGS, enable in-depth genomic and epigenetic analysis, which translates into a more personalized approach to treatment. Despite the use of multimodal therapy, which is based on maximum safe tumor resection followed by radiotherapy and temozolomide chemotherapy, recurrence is almost inevitable. GBM shows a high degree of resistance to treatment, which results from the presence of stem cell subpopulations, dynamic clonal evolution, and the ability to adapt to unfavorable microenvironmental conditions. Promising preclinical and early clinical results show new therapeutic strategies, including immunotherapy (cancer vaccines, checkpoint inhibitors, CAR-T therapies), oncolytic virotherapy, and Tumor Treating Fields (TTF) technology. Although these methods show potential for prolonging survival, their clinical efficacy still needs to be confirmed in large studies. The role of artificial intelligence in the analysis of imaging and molecular data is also increasingly being emphasized, which may contribute to the development of more accurate predictive models and therapeutic decisions. Despite these advancements, GBM remains a major therapeutic challenge due to its high heterogeneity and treatment resistance. The integration of molecular diagnostics, artificial intelligence, and personalized therapeutic strategies that may enhance survival and quality of life for GBM patients. Full article

With the expansion of unmanned aerial vehicles (UAVs) into complex three-dimensional (3D) terrains for reconnaissance, rescue, and related missions, traditional path planning methods struggle to meet multi-constraint and multi-objective requirements. Existing swarm intelligence algorithms, limited by the “no free lunch” theorem, also face challenges when the standard Information Acquisition Optimizer (IAO) is applied to such tasks, including low exploration efficiency in high-dimensional search spaces, rapid loss of population diversity, and improper boundary handling. To address these issues, this study proposes a Multi-Strategy Enhanced Information Acquisition Optimizer (MEIAO). First, a Levy Flight-based information collection strategy is introduced to leverage its combination of short-range local searches and long-distance jumps, thereby broadening global exploration. Second, an adaptive differential evolution operator is designed to dynamically balance exploration and exploitation via a variable mutation factor, while crossover and greedy selection mechanisms help maintain population diversity. Third, a globally guided boundary handling strategy adjusts out-of-bound dimensions to feasible regions, preventing the generation of low-quality paths. Performance was evaluated on the CEC2017 (dim = 30/50/100) and CEC2022 (dim = 10/20) benchmark suites by comparing MEIAO with eight algorithms, including VPPSO and IAO. Based on the mean, standard deviation, Friedman mean rank, and Wilcoxon rank-sum tests, MEIAO demonstrated superior performance in local exploitation of unimodal functions, global exploration of multimodal functions, and complex adaptation on composite functions while exhibiting stronger robustness. Finally, MEIAO was applied to 3D mountainous UAV path planning, where a cost model considering path length, altitude standard deviation, and turning smoothness was established. The experimental results show that MEIAO achieved an average path cost of 253.9190, a 25.7% reduction compared to IAO (341.9324), with the lowest standard deviation (60.6960) among all algorithms. The generated paths were smoother, collision-free, and achieved faster convergence, offering an efficient and reliable solution for UAV operations in complex environments. Full article

Cancer remains a persistent global health challenge, continuously driving the search for novel and effective therapeutic strategies. In the case of breast cancer, treatment decisions are primarily guided by factors such as the disease stage, histological grade, molecular receptor status, and the presence of genetic mutations. Understanding these parameters is crucial for tailoring interventions and improving clinical outcomes. To enhance prognostic and diagnostic accuracy, attention has increasingly turned to identifying molecular targets that play key roles in breast cancer development. Currently, standard treatments include surgery, chemotherapy, and radiotherapy. However, these approaches are often associated with significant side effects and a diminished quality of life. As a result, many breast cancer patients are turning to complementary therapies—including phytotherapy, nutritional interventions, and dietary supplements—to support conventional treatment, alleviate adverse effects, and improve overall well-being. Within the vast realm of medicinal flora, anticancer plants represent a compelling area of study, serving as a rich reservoir of bioactive compounds. These compounds have demonstrated significant promise in the ongoing battle against cancer. Often highlighted in traditional medicinal practices, these plants harbor a wide array of phytochemicals, such as alkaloids, flavonoids, polyphenols, and terpenoids. These phytochemicals manifest diverse biological activities, notably exhibiting pronounced anticancer properties. The exploration of these natural compounds has opened new avenues for developing innovative and targeted therapeutic strategies in cancer treatment. They achieve definitive chemotherapeutic and chemopreventive roles by integrating with specific molecular signals. Their multiple biological functions include antimutagenic, antiproliferative, antimetastatic, anti-angiogenesis, anti-inflammatory, antioxidant, and immunomodulatory properties, which collectively enable them to control cancer progression and intervene at various stages of cancer cell development. Moreover, these compounds are involved in regulating the cell cycle and microRNA, ultimately leading to cancer cell death by promoting apoptosis and autophagy, often mediated through ROS signaling. Thus, based on a large theoretical revision, we conclude that high-quality evidence is necessary in order to advise these products concerning their efficacy and safety. Also, clinical evidence should be supported by a comprehensive individual diagnosis and adequate research protocols in order to evaluate whether the benefits of these plant-produced interventions can outweigh their harms. Full article

Based on the analysis of solar array current data from a certain MEO-orbiting satellite, this paper reveals its short-period fluctuation characteristics and underlying mechanisms. The study finds that when solar panels face the sun during the light period, the output current exhibits significant short-period fluctuations in addition to being influenced by long-period factors such as sun–earth distance, incident light intensity changes, and space irradiation attenuation. Through theoretical analysis, we first confirm that the root cause of these short-period variations is the temperature change in the shunt circuit caused by load fluctuations, which in turn affects the output current characteristics. Unlike traditional methods that use static characteristic factors such as incident angles, this paper innovatively proposes using load current as a key characteristic factor. For asymmetric solar panel fault scenarios, load current, time phase, and fault-wing output current are used as characteristic factors to adaptively predict the current of normal wings. Meanwhile, feedforward neural network (FNN), Recurrent Neural Network (RNN), and long short-term memory (LSTM) are used for output current prediction. The experimental results show that these methods can accurately capture the short-period fluctuations caused by load mutations and adapt to the fluctuation trend of the normal wing during the prediction of current changes in the faulty wing. It is worth noting that, limited by the short-period fluctuation prediction scenario, the inherent advantage of LSTM in long-sequence prediction is not fully reflected. Full article

With increasing attention to sustainability and energy efficiency in transportation systems, advanced intelligent algorithms provide promising solutions for optimizing urban rail transit operations. This study addresses the challenge of optimizing train operation plans for urban rail transit systems characterized by spatiotemporal passenger flow imbalance. By exploring a combined short-turning and unpaired train operation mode, a three-objective optimization model was established, aiming to minimize operational costs, reduce passenger waiting times, and enhance load balancing. To effectively solve this complex problem, an Improved GOOSE (IGOOSE) algorithm incorporating elite opposition-based learning, probabilistic exploration based on elite solutions, and golden-sine mutation strategies were developed, significantly enhancing global search capability and solution robustness. A case study based on real operational data adjusted for confidentiality was conducted, and comparative analyses with Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO) demonstrated the superiority of IGOOSE. Furthermore, an ablation study validated the effectiveness of each enhancement strategy within the IGOOSE algorithm. The optimized operation planning model reduced passenger waiting times by approximately 12.72%, improved load balancing by approximately 39.30%, and decreased the overall optimization objective by approximately 10.25%, highlighting its effectiveness. These findings provide valuable insights for urban rail transit operation management and indicate directions for future research, underscoring the significant potential for energy savings and emission reductions toward sustainable urban development. Full article

Urban rail transit (URT) systems frequently face operational challenges arising from temporal and spatial imbalances in passenger demand, resulting in inefficiencies in train scheduling and resource utilization. To address these issues, this study proposes a multi-objective optimization model that jointly plans short-turn and full-length train services. The objectives of the model are to minimize total passenger waiting time and train mileage while improving passenger load distribution across the rail line, subject to practical constraints such as departure frequency limitations, rolling stock availability, and coverage of short-turn services. To efficiently solve this model, an improved Pelican Optimization Algorithm (POA) is developed, incorporating techniques such as Tent chaotic mapping, nonlinear weight adjustment, Cauchy mutation, and the sparrow alert mechanism, significantly enhancing convergence accuracy and computational efficiency. A real-world case study based on Nanjing Metro Line 1 demonstrates that the proposed framework substantially reduces average passenger waiting times and overall train mileage, achieving a more balanced distribution of passenger loads. In addition, the study reveals that flexible-ratio dispatching strategies, representing theoretically optimal solutions, outperform integer-ratio dispatching schemes that reflect real-world operational constraints. This finding underscores that investigating the practical feasibility and optimization potential of flexible-ratio scheduling strategies constitutes a valuable direction for future research. The outcomes of this study provide a scalable and intelligent decision-support framework for train scheduling in URT systems, effectively contributing to the sustainable and intelligent development of rail operations. Full article

The present Perspective analyzes the remarkable evolution of the Amyloid Cascade Hypothesis 2.0 (ACH2.0) theory of Alzheimer’s disease (AD) since its inception a few years ago, as reflected in the diminishing role of amyloid-beta (Aβ) in the disease. In the initial iteration of the ACH2.0, Aβ-protein-precursor (AβPP)-derived intraneuronal Aβ (iAβ), accumulated to neuronal integrated stress response (ISR)-eliciting levels, triggers AD. The neuronal ISR, in turn, activates the AβPP-independent production of its C99 fragment that is processed into iAβ, which drives the disease. The second iteration of the ACH2.0 stemmed from the realization that AD is, in fact, a disease of the sustained neuronal ISR. It introduced two categories of AD—conventional and unconventional—differing mainly in the manner of their causation. The former is caused by the neuronal ISR triggered by AβPP-derived iAβ, whereas in the latter, the neuronal ISR is elicited by stressors distinct from AβPP-derived iAβ and arising from brain trauma, viral and bacterial infections, and various types of inflammation. Moreover, conventional AD always contains an unconventional component, and in both forms, the disease is driven by iAβ generated independently of AβPP. In its third, the current, iteration, the ACH2.0 posits that proteolytic production of Aβ is suppressed in AD-affected neurons and that the disease is driven by C99 generated independently of AβPP. Suppression of Aβ production in AD seems an oxymoron: Aβ is equated with AD, and the later is inconceivable without the former in an ingrained Amyloid Cascade Hypothesis (ACH)-based notion. But suppression of Aβ production in AD-affected neurons is where the logic leads, and to follow it we only need to overcome the inertia of the preexisting assumptions. Moreover, not only is the generation of Aβ suppressed, so is the production of all components of the AβPP proteolytic pathway. This assertion is not a quantum leap (unless overcoming the inertia counts as such): the global cellular protein synthesis is severely suppressed under the neuronal ISR conditions, and there is no reason for constituents of the AβPP proteolytic pathway to be exempted, and they, apparently, are not, as indicated by the empirical data. In contrast, tau protein translation persists in AD-affected neurons under ISR conditions because the human tau mRNA contains an internal ribosomal entry site in its 5′UTR. In current mouse models, iAβ derived from AβPP expressed exogenously from human transgenes elicits the neuronal ISR and thus suppresses its own production. Its levels cannot principally reach AD pathology-causing levels regardless of the number of transgenes or the types of FAD mutations that they (or additional transgenes) carry. Since the AβPP-independent C99 production pathway is inoperative in mice, the current transgenic models have no potential for developing the full spectrum of AD pathology. What they display are only effects of the AβPP-derived iAβ-elicited neuronal ISR. The paper describes strategies to construct adequate transgenic AD models. It also details the utilization of human neuronal cells as the only adequate model system currently available for conventional and unconventional AD. The final alteration of the ACH2.0, introduced in the present Perspective, is that AβPP, which supports neuronal functionality and viability, is, after all, potentially produced in AD-affected neurons, albeit not conventionally but in an ISR-driven and -compatible process. Thus, the present narrative begins with the “omnipotent” Aβ capable of both triggering and driving the disease and ends up with this peptide largely dislodged from its pedestal and retaining its central role in triggering the disease in only one, although prevalent (conventional), category of AD (and driving it in none). Among interesting inferences of the present Perspective is the determination that “sporadic AD” is not sporadic at all (“non-familial” would be a much better designation). The term has fatalistic connotations, implying that the disease can strike at random. This is patently not the case: The conventional disease affects a distinct subpopulation, and the basis for unconventional AD is well understood. Another conclusion is that, unless prevented, the occurrence of conventional AD is inevitable given a sufficiently long lifespan. This Perspective also defines therapeutic directions not to be taken as well as auspicious ways forward. The former category includes ACH-based drugs (those interfering with the proteolytic production of Aβ and/or depleting extracellular Aβ). They are legitimate (albeit inefficient) preventive agents for conventional AD. There is, however, a proverbial snowball’s chance in hell of them being effective in symptomatic AD, lecanemab, donanemab, and any other “…mab” or “…stat” notwithstanding. They comprise Aβ-specific antibodies, inhibitors of beta- and gamma-secretase, and modulators of the latter. In the latter category, among ways to go are the following: (1) Depletion of iAβ, which, if sufficiently “deep”, opens up a tantalizing possibility of once-in-a-lifetime preventive transient treatment for conventional AD and aging-associated cognitive decline, AACD. (2) Composite therapy comprising the degradation of C99/iAβ and concurrent inhibition of the neuronal ISR. A single transient treatment could be sufficient to arrest the progression of conventional AD and prevent its recurrence for life. Multiple recurrent treatments would achieve the same outcome in unconventional AD. Alternatively, the sustained reduction/removal of unconventional neuronal ISR-eliciting stressors through the elimination of their source would convert unconventional AD into conventional one, preventable/treatable by a single transient administration of the composite C99/iAβ depletion/ISR suppression therapy. Efficient and suitable ISR inhibitors are available, and it is explicitly clear where to look for C99/iAβ-specific targeted degradation agents—activators of BACE1 and, especially, BACE2. Directly acting C99/iAβ-specific degradation agents such as proteolysis-targeting chimeras (PROTACs) and molecular-glue degraders (MGDs) are also viable options. (3) A circumscribed shift (either upstream or downstream) of the position of transcription start site (TSS) of the human AβPP gene, or, alternatively, a gene editing-mediated excision or replacement of a small, defined segment of its portion encoding 5′-untranslated region of AβPP mRNA; targeting AβPP RNA with anti-antisense oligonucleotides is another possibility. If properly executed, these RNA-based strategies would not interfere with the protein-coding potential of AβPP mRNA, and each would be capable of both preventing and stopping the AβPP-independent generation of C99 and thus of either preventing AD or arresting the progression of the disease in its conventional and unconventional forms. The paper is interspersed with “validation” sections: every conceptually significant notion is either validated by the existing data or an experimental procedure validating it is proposed. Full article

This study addresses the dual challenges of complex road environments and diverse task-safety requirements in mobile-robot path planning by proposing an innovative method that integrates a dual-layer fuzzy control system with an improved genetic algorithm. Initially, an expert system-based dual-layer fuzzy control system is developed. The first layer translates complex road conditions and obstacles into road-safety levels, while the second layer combines these with task-safety levels to generate fitness weights for the genetic algorithm. Furthermore, road-safety factors are incorporated into the genetic algorithm’s fitness function to enhance safety considerations in path planning. The algorithm implementation incorporates Bernoulli chaotic mapping, Gaussian operators, and Symmetrical Sigmoid operators to optimize the selection, crossover, and mutation processes, significantly boosting the algorithm’s global search capability and efficiency. Experimental results indicate that the proposed method reduces path distance by up to 5.9% and decreases the number of turns by up to 85.7%, demonstrating superior universality and robustness across various comparative experiments. This research contributes to resolving the issues posed by complex road environments and varying task-safety requirements in mobile-robot path planning. Full article

Background: The nuclear-encoded enzyme polymerase gamma (Pol-γ) is crucial in the replication of the mitochondrial genome (mtDNA), which in turn is vital for mitochondria and hence numerous metabolic processes and energy production in eukaryotic cells. Variants in the POLG gene, which encodes the catalytic subunit of Pol-γ, can significantly impair Pol-γ enzyme function. Pol-γ-associated disorders are referred to as POLG-spectrum disorders (POLG-SDs) and are mainly autosomal-recessively inherited. Clinical manifestations include muscle weakness and fatigue, and severe forms of the disease can lead to premature death in infancy, childhood, and early adulthood, often associated with seizures, liver failure, or intractable epilepsy. Here, we analyzed fibroblasts from a compound heterozygous patient with the established pathogenic variant c.2419C>T; p.(Arg807Cys) and a previously undescribed variant c.678G>C; p.(Gln226His) with a clinical manifestation compatible with POLG-SDs, sensory ataxic neuropathy, and infantile muscular atrophy. We conducted a battery of functional studies for Pol-γ and mitochondrial dysfunction on the patient’s fibroblasts, to test whether the novel variant c.678G>C; p.(Gln226His) may be causative in human disease. Aims/Methods: We analyzed skin-derived fibroblasts in comparison to a first-degree relative (the mother of the patient), an asymptomatic carrier harboring only the established c.2419C>T; p.(Arg807Cys) mutation. Assessments of mitochondrial function included measurements of mtDNA content, mRNA levels of mitochondrial genes, mitochondrial mass, and mitochondrial morphology. Case Presentation and Results: A 13-year-old male presented with symptoms starting at three years of age, including muscle weakness and atrophy in the lower extremities and facial muscles, which later extended to the upper limbs, voice, and back muscles, without further progression. The patient also reported fatigue and muscle pain after physical activity, with no sensory deficits. Extensive diagnostic tests such as electromyography, nerve conduction studies, muscle biopsy, and MRI were unremarkable. Exome sequencing revealed that he carried the compound heterozygous variants in POLG c.678G>C; p.(Gln226His) and c.2419C>T; p.(Arg807Cys), but no other potential genetic pathogenic causes. In comparison to a first-degree relative (his mother) who only carried the c.2419C>T; p.(Arg807Cys) pathogenic mutation, in vitro analyses revealed a significant reduction in mtDNA content (~50%) and mRNA levels of mtDNA-encoded proteins. Mitochondrial mass was reduced by approximately 20%, and mitochondrial interconnectivity within cells was impaired, as determined by fluorescence microscopy and mitochondrial staining. Conclusions: Our findings suggest that the c.678G>C; p.(Gln226His) variant, in conjunction with the c.2419C>T; p.(Arg807Cys) mutation, may compromise mtDNA replication and mitochondrial function and could result in clinically significant mitochondriopathy. As this study is based on one patient compared to a first-degree relative (but with an identical mitochondrial genome), the pathogenicity of c.678G>C; p.(Gln226His) of POLG should be confirmed in future studies, in particular, in conjunction with other POLG-variants. Full article

The epidermal growth factor receptor (EGFR) is one of the key oncomarkers in glioblastoma (GB) biomedical research. High levels of EGFR expression and mutations have been found in many GB patients, making the EGFR an attractive target for therapeutic treatment. The EGFRvIII mutant is the most studied, it is not found in normal cells and is positively associated with tumor cell aggressiveness and poor patient prognosis, not to mention there is a possibility of it being a tumor stem cell marker. Some anti-EGFR DNA aptamers have already been selected, including the aptamer U2. The goal of this study was to construct a more stable derivative of the aptamer U2, while not ruining its functional potential toward cell cultures from GB patients. A multiloop motif in a putative secondary structure of the aptamer U2 was taken as a key feature to design a novel minimal aptamer, Gol1, using molecular dynamics simulations for predicted 3D models. It turned out that the aptamer Gol1 has a similar putative secondary structure, with G-C base pairs providing its stability. The anti-proliferative activities of the aptamer Gol1 were assessed using patient-derived GB continuous cell cultures, G01 and BU881, with different abundances of EGFR and EGFRvIII. The transcriptome data for the cell culture G01, after aptamer Gol1 treatment, revealed significant changes in gene expression; it induced the transcription of genes associated with neurogenesis and cell differentiation, and it decreased the transcription of genes mediating key nuclear processes. There were significant changes in the gene transcription of key pro-oncogenic signaling pathways mediated by the EGFR. Therefore, the aptamer Gol1 could potentially be an efficient molecule for translation into biomedicine, in order to develop targeted therapy for GB patients. Full article

The growth and development of animals are dynamic processes characterized by fluctuations. Min pigs, a local breed renowned for their superior meat quality, present an intriguing yet poorly understood relationship between this quality and their growth and development patterns. To elucidate this relationship, we employed a multi-faceted approach that included comparative transcriptomics, quantitative real-time PCR (qRT-PCR), selection pressure analysis of key genes, and three-dimensional protein structure simulations. Our findings revealed that 150 days (150 d) of age represented a pivotal turning point in the growth and development of Min pigs. Thirteen key genes exhibiting significant differential expression between early and late growth stages were identified. Notably, the CDK2 gene demonstrated specific high expression in the hind limb muscles and adipose tissues during the later growth stages. Comparative analysis with the African warthog revealed that while the CDK2 protein structure remained conserved, base mutations in upstream and downstream non-coding regions resulted in strong positive selection pressure on the CDK2 gene. These results suggest that CDK2 plays a crucial role in defining the spatiotemporal characteristics of meat development during the domestication of Min pigs. This study provides critical insights into the growth and development patterns of domestic pigs and offers a robust scientific foundation for improving meat quality traits through domestication. Full article

The recent coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exerted considerable impact on global health. To prepare for rapidly mutating viruses and for the forthcoming pandemic, effective therapies targeting the critical stages of the viral life cycle need to be developed. Viruses are dependent on the interaction between the receptor-binding domain (RBD) of the viral Spike (S) protein (S-RBD) and the angiotensin-converting enzyme 2 (ACE2) receptor to efficiently establish infection and the following replicate. Targeting this interaction provides a promising strategy to inhibit the entry process of the virus, which in turn has both preventive and therapeutic effects. In this study, we developed a robust and straightforward assay based on the Yeast-Two Hybrid system (Y2H) for identifying inhibitors targeting the S-RBD-ACE2 interaction of SARS-CoV-2. Through high-throughput screening, two compounds were identified as potential entry inhibitors. Among them, IMB-1C was superior in terms of pseudovirus entry inhibition and toxicity. It could bind to both ACE2 and S-RBD and induce conformational change in the S-RBD+ACE2 complex. This is the first study to verify the feasibility of utilizing the Y2H system to discover potent SARS-CoV-2 inhibitors targeting the receptor recognition stage. This approach may also be applied in the discovery of other virus receptor recognition inhibitors. Full article

Background: The advent of next-generation sequencing (NGS) has revolutionized the analysis of genetic data, enabling rapid identification of pathogenic variants in patients with inborn errors of immunity (IEI). Sometimes, the use of NGS-based technologies is associated with challenges in the evaluation of the clinical significance of novel genetic variants. Methods: In silico prediction tools, such as SpliceAI neural network, are often used as a first-tier approach for the primary examination of genetic variants of uncertain clinical significance. Such tools allow us to parse through genetic data and emphasize potential splice-altering variants. Further variant assessment requires precise RNA assessment by agarose gel electrophoresis and/or cDNA Sanger sequencing. Results: We found two novel heterozygous variants in the coding region of the LYST gene (c.10104G>T, c.10894A>G) in an individual with a typical clinical presentation of Chediak–Higashi syndrome (CHS). The SpliceAI neural network predicted both variants as probably splice-altering. cDNA assessment by agarose gel electrophoresis revealed the presence of abnormally shortened splicing products in each variant’s case, and cDNA Sanger sequencing demonstrated that c.10104G>T and c.10894A>G substitutions resulted in a shortening of the 44 and 49 exons by 41 and 47 bp, respectively. Both mutations probably lead to a frameshift and the formation of a premature termination codon. This, in turn, may disrupt the structure and/or function of the LYST protein. Conclusions: We identified two novel variants in the LYST gene, predicted to be deleterious by the SpliceAI neural network. Agarose gel cDNA electrophoresis and cDNA Sanger sequencing allowed us to verify inappropriate splicing patterns and establish these variants as disease-causing. Full article

Glioblastoma (GBM) is the most common primary brain malignancy in the U.S. with a 5-year overall survival < 5% despite an aggressive standard of care. Laser interstitial thermal therapy (LITT) is a surgical approach to treating GBM that has gained traction, providing a safe option for reducing intracranial tumor burden. LITT is believed to potentially modulate GBM immune responses; however, the biochemical mechanisms underlying the modulation of immune checkpoints in GBM cells have been poorly characterized. The present study aimed to preliminarily evaluate the effects of thermal therapy and radiation on PD-L1 modulation in vitro, as a function of IDH mutational status. U87 cells and their IDH-mutant counterpart (U87^R132H), which was generated using a crispr-cas9 knock-in approach, were utilized for this preliminary evaluation. Cell heating was achieved by harvesting with trypsin centrifugation where the cell pellets were treated on a heat block for the associated time and temperature. Following thermal therapy, cells were resuspended and irradiated using a 37-Cesium irradiator at 0.6 Gy min⁻¹. Immediately following treatment, cells were either plated as single cells to allow colonies to form, and stained with Coomassie blue to be counted approximately 10–14 days later or harvested for Western blot analysis. Cell lysates were analyzed for PD-L1 expression with respect to various iron metabolic parameters (mortalin (HSPA9), transferrin receptor, and ferritin heavy chain) using a Western blotting approach. In both U87 and U87^R132H cell lines, thermal therapy showed a temperature-dependent cell-killing effect, but U87^R132H cells appeared more sensitive to thermal treatment when treated at 43 °C for 10 min. Moreover, thermal therapy had minimal effects on cell responses to 2 Gy irradiation. Treatment with thermal therapy downregulated PD-L1 expression in U87^R132H cells, which was associated with increased expression of the mitochondrial iron metabolic enzyme, HSPA9. Thermal therapy reversed the radiation-induced overexpression of PD-L1, transferrin receptor, and ferritin heavy chain in U87^R132H cells. No effects were observed in wild-type U87 cells. Moreover, Ga(NO₃)₃ depleted mitochondrial iron content which, in turn, significantly enhanced the sensitivity of U87^R132H cells to thermal therapy and 2 Gy irradiation and caused a significant increase in PD-L1 expression. These results suggest that thermal therapy alone can modulate the immune checkpoint PD-L1. This effect was more pronounced when thermal therapy was combined with radiation. Mechanistically, mitochondrial iron trafficking through HSPA9 may coordinate the regulation of PD-L1 in the context of thermal therapy and ionizing radiation, which can be targeted with gallium-based therapy. These novel, preliminary findings warrant further mechanistic investigations in pre-clinical models of LITT. Full article

Due to the limitations of low coverage, high repetition rate, and slow convergence speed of the basic genetic algorithm (GA) in robot complete coverage path planning, the state transition matrix of the Markov chain is introduced to guide individual mutation based on the genetic mutation path planning algorithm, which can improve the quality of population individuals, enhancing the search ability and convergence speed of the genetic algorithm. The proposed improved genetic algorithm is used for complete coverage path planning simulation analysis in different work areas. The analysis results show that compared to traditional genetic algorithms, the improved genetic algorithm proposed in this paper reduces the average path length by 21.8%, the average number of turns by 6 times, the repetition rate by 83.8%, and the coverage rate by 7.76% in 6 different work areas. The results prove that the proposed improved genetic algorithm is applicable in complete coverage path planning. To verify whether the Markov chain genetic algorithm (MCGA) proposed is suitable for agricultural robot path tracking and operation, it was used to plan the path of an actual land parcel. An automatic navigation robot can track the planned path, which can verify the feasibility of the MCGA proposed. Full article