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Escherichia coli K1 is the leading cause of neonatal Gram-negative bacterial meningitis, but the pathogenesis of E. coli K1 meningitis remains unclear. Blood-brain barrier (BBB) penetration is a crucial step in E. coli meningitis development. Here, we uncovered the crucial role of CsiR, a GntR family regulator, in E. coli K1 virulence. During infection, csiR expression was induced due to the derepression by Fur in the blood and human brain microvascular endothelial cells (HBMECs). CsiR positively regulated ilvB expression, which is associated with branched chain amino acid synthesis. Furthermore, we revealed that IlvB activated the FAK/PI3â K pathway of HBMECs to induce actin cytoskeleton rearrangements, thereby promoting the bacterial invasion and penetration of the BBB. Overall, this study reveals a CsiR-mediated virulence regulation pathway in E. coli K1, which may provide a useful target for the prevention or therapy of E. coli meningitis.
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The original Harris hawks optimization (HHO) algorithm has the problems of unstable optimization effect and easy to fall into stagnation. However, most of the improved HHO algorithms can not effectively improve the ability of the algorithm to jump out of the local optimum. In this regard, an integrated improved HHO (IIHHO) algorithm is proposed. Firstly, the linear transformation escape energy used by the original HHO algorithm is relatively simple and lacks the escape law of the prey in the actual nature. Therefore, intermittent energy regulator is introduced to adjust the energy of Harris hawks, which is conducive to improving the local search ability of the algorithm while restoring the prey's rest mechanism; Secondly, to adjust the uncertainty of random vector, a more regular vector change mechanism is used instead, and the attenuation vector is obtained by modifying the composite function. Finally, the search scope of Levy flight is further clarified, which is conducive to the algorithm jumping out of the local optimum. Finally, in order to modify the calculation limitations caused by the fixed step size, Cardano formula function is introduced to adjust the step size setting and improve the accuracy of the algorithm. First, the performance of IIHHO algorithm is analyzed on the Computational Experimental Competition 2013 (CEC 2013) function test set and compared with seven improved evolutionary algorithms, and the convergence value of the iterative curve obtained is better than most of the improved algorithms, verifying the effectiveness of the proposed IIHHO algorithm. Second, the IIHHO is compared with another three state of the art (SOTA) algorithms with the Computational Experimental Competition 2022 (CEC 2022) function test set, the experiments show that the proposed IIHHO algorithm still has a strong ability to search for the optimal value. Third, IIHHO algorithm is applied in two different engineering experiments. The calculation results of minimum cost prove that IIHHO algorithm has certain advantages in dealing with the problem of search space. All these demonstrate that the proposed IIHHO is promising for numeric optimization and engineering applications.
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Background: Previously, our investigations have underscored the potential of hyperthermia to improve the therapeutic efficacy of gemcitabine (GEM) in pancreatic cancer (PC). Nonetheless, the precise underlying mechanisms remain elusive. Methods: We engineered two GEM-resistant PC cell lines (BxPC-3/GEM and PANC-1/GEM) and treated them with GEM alongside hyperthermia. The impact of hyperthermia on the therapeutic potency of GEM was ascertained through MTT assay, assessment of the concentration of its active metabolite dFdCTP, and evaluation of deoxycytidine kinase (dCK) activity. Lentivirus-mediated dCK silencing was further employed to validate its involvement in mediating the GEM-sensitizing effect of hyperthermia. The mechanism underlying hyperthermia-mediated dCK activation was explored using bioinformatics analyses. The interplay between hyperthermia and the ephrin A4 (EFNA4)/ß-catenin/dCK axis was investigated, and their roles in GEM resistance was further explored via the establishment of xenograft tumor models in nude mice. Results: Hyperthermia restored dCK expression in GEM-resistant cell lines, concurrently enhancing GEM sensitivity and fostering DNA damage and cell death. These observed effects were negated by dCK silencing. Regarding the mechanism, hyperthermia activated dCK by downregulating EFNA4 expression and mitigating ß-catenin activation. Overexpression of EFNA4 activated the ß-catenin while suppressing dCK, thus diminishing cellular GEM sensitivity-a phenomenon remediated by the ß-catenin antagonist MSAB. Consistently, in vivo, hyperthermia augmented the therapeutic efficacy of GEM on xenograft tumors through modulation of the ephrin A4/ß-catenin/dCK axis. Conclusion: This study delineates the role of hyperthermia in enhancing GEM sensitivity of PC cells, primarily mediated through the suppression of the EFNA4/ß-catenin axis and activation of dCK.
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With advancements in science and technology, the depth of human research on COVID-19 is increasing, making the investigation of medical images a focal point. Image segmentation, a crucial step preceding image processing, holds significance in the realm of medical image analysis. Traditional threshold image segmentation proves to be less efficient, posing challenges in selecting an appropriate threshold value. In response to these issues, this paper introduces Inner-based multi-strategy particle swarm optimization (IPSOsono) for conducting numerical experiments and enhancing threshold image segmentation in COVID-19 medical images. A novel dynamic oscillatory weight, derived from the PSO variant for single-objective numerical optimization (PSOsono) is incorporated. Simultaneously, the historical optimal positions of individuals in the particle swarm undergo random updates, diminishing the likelihood of algorithm stagnation and local optima. Moreover, an inner selection learning mechanism is proposed in the update of optimal positions, dynamically refining the global optimal solution. In the CEC 2013 benchmark test, PSOsono demonstrates a certain advantage in optimization capability compared to algorithms proposed in recent years, proving the effectiveness and feasibility of PSOsono. In the Minimum Cross Entropy threshold segmentation experiments for COVID-19, PSOsono exhibits a more prominent segmentation capability compared to other algorithms, showing good generalization across 6 CT images and further validating the practicality of the algorithm.
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Algoritmos , COVID-19 , SARS-CoV-2 , COVID-19/diagnóstico por imagem , Humanos , Processamento de Imagem Assistida por Computador/métodos , Aprendizado de MáquinaRESUMO
X-linked retinoschisis (XLRS) is a monogenic recessive inherited retinal disease caused by defects in retinoschisin (RS1). It manifests clinically as retinal schisis cavities and a disproportionate reduction of b-wave amplitude compared with the a-wave amplitude. Currently there is no approved treatment. In the last decade, there has been major progress in the development of gene therapy for XLRS. Previous preclinical studies have demonstrated the treatment benefits of hRS1 gene augmentation therapy in mouse models. However, outcomes in clinical trials have been disappointing, and this might be attributed to dysfunctional assembly of RS1 complexes and/or the impaired targeted cells. In this study, the human synapsin 1 gene promoter (hSyn) was used to control the expression of hRS1 to specifically target retinal ganglion cells and our results confirmed the specific expression and functional assembly of the protein. Moreover, our results demonstrated that a single intravitreal injection of rAAV2-hSyn-hRS1 results in architectural restoration of retinal schisis cavities and improvement in vision in a mouse model of XLRS. In brief, this study not only supports the clinical development of the rAAV2-hSyn-hRS1 vector in XLRS patients but also confirms the therapeutic potential of rAAV-based gene therapy in inherited retinal diseases.
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Dependovirus , Modelos Animais de Doenças , Terapia Genética , Vetores Genéticos , Injeções Intravítreas , Camundongos Knockout , Células Ganglionares da Retina , Retinosquise , Sinapsinas , Animais , Dependovirus/genética , Células Ganglionares da Retina/metabolismo , Células Ganglionares da Retina/patologia , Camundongos , Terapia Genética/métodos , Retinosquise/terapia , Retinosquise/genética , Humanos , Vetores Genéticos/genética , Vetores Genéticos/administração & dosagem , Sinapsinas/genética , Sinapsinas/metabolismo , Proteínas do Olho/genética , Proteínas do Olho/metabolismo , Expressão Gênica , Regiões Promotoras Genéticas , Retina/metabolismo , Retina/patologia , Técnicas de Transferência de GenesRESUMO
Domestic dogs are helpers in outdoor human work and companions for families; thus, individual canine identification and parentage testing are crucial in certain fields, including forensics and breeding programs. In this study, a six-dye fluorescent labeling multiplex amplification system containing 29 canine short tandem repeats (STRs) and the sex-determining marker DAmel was developed. The system was called the Tronfo Canine 30-plex STR Kit and was further validated according to the Scientific Working Group on DNA Analysis Methods and the Organization of Scientific Area Committees for Wildlife Forensics guidelines, including tests for PCR conditions, precision, species specificity, sensitivity, stability, repeatability and reproducibility, a population study, and a study of 16 paternity test cases. The results indicated that the novel canine STR assay was accurate, specific, reproducible, stable, and robust. Complete profiles were obtained with 31.25â¯pg of canine DNA. Additionally, 500 unrelated canine individuals were investigated using this novel system, and the combined power of discrimination and exclusion values were 0.999999999999999999 and 0.999996451039850, respectively. These results suggest that the Tronfo Canine 30-plex STR Kit is highly polymorphic, informative, and suitable for individual canine identification and parentage testing.
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Repetições de Microssatélites , Animais , Cães/genética , Reprodutibilidade dos Testes , Especificidade da Espécie , Reação em Cadeia da Polimerase , Masculino , Impressões Digitais de DNA , Reação em Cadeia da Polimerase Multiplex , Feminino , Genética Forense/métodosRESUMO
Semen is one of the common body fluids in sexual crime cases. The current methods of semen identification have certain limitations, so it is necessary to search for other methods. In addition, there are few reports of microbiome changes in body fluids under simulated crime scenes. It is essential to further reveal the changes in semen microbiomes after exposure to various simulated crime scenes. Semen samples from eight volunteers were exposed in closed plastic bags, soil, indoor, cotton, polyester, and wool fabrics. A total of 68 samples (before and after exposure) were collected, detected by 16S rDNA sequencing, and analyzed for the microbiome signature. Finally, a random forest model was constructed for body fluid identification. After exposure, the relative abundance of Pseudomonas and Rhodococcus changed dramatically in almost all groups. In addition, the treatment with the closed plastic bags or soil groups had a greater impact on the semen microbiome. According to the Shannon indices, the alpha diversity of the closed plastic bags and soil groups was much lower than that of the other groups. Attention should be given to the above two scenes in practical work of forensic medicine. In this study, the accuracy of semen recognition was 100%. The exposed semen can still be correctly identified as semen based on its microbiota characteristics. In summary, semen microbiomes exposed to simulated crime scenes still have good application potential for body fluid identification. IMPORTANCE: In this study, the microbiome changes of semen exposed to different environments were observed, and the exposed semen microbiome still has a good application potential in body fluid identification.
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Bactérias , Microbiota , RNA Ribossômico 16S , Sêmen , Sêmen/microbiologia , Humanos , Masculino , RNA Ribossômico 16S/genética , Bactérias/classificação , Bactérias/genética , Bactérias/isolamento & purificação , Adulto , Medicina Legal/métodosRESUMO
Diabetes mellitus induces a pathophysiological disorder known as diabetic cardiomyopathy and may eventually cause heart failure. Diabetic cardiomyopathy is manifested with systolic and diastolic contractile dysfunction along with alterations in unique cardiomyocyte proteins and diminished cardiomyocyte contraction. Multiple mechanisms contribute to the pathology of diabetic cardiomyopathy, mainly including abnormal insulin metabolism, hyperglycemia, glycotoxicity, cardiac lipotoxicity, endoplasmic reticulum stress, oxidative stress, mitochondrial dysfunction, calcium treatment damage, programmed myocardial cell death, improper Renin-Angiotensin-Aldosterone System activation, maladaptive immune modulation, coronary artery endothelial dysfunction, exocrine dysfunction, etc. There is an urgent need to investigate the exact pathogenesis of diabetic cardiomyopathy and improve the diagnosis and treatment of this disease. The nuclear receptor superfamily comprises a group of transcription factors, such as liver X receptor, retinoid X receptor, retinoic acid-related orphan receptor-α, retinoid receptor, vitamin D receptor, mineralocorticoid receptor, estrogen-related receptor, peroxisome proliferatoractivated receptor, nuclear receptor subfamily 4 group A 1(NR4A1), etc. Various studies have reported that nuclear receptors play a crucial role in cardiovascular diseases. A recently conducted work highlighted the function of the nuclear receptor superfamily in the realm of metabolic diseases and their associated complications. This review summarized the available information on several important nuclear receptors in the pathophysiology of diabetic cardiomyopathy and discussed future perspectives on the application of nuclear receptors as targets for diabetic cardiomyopathy treatment.