Chinese Physics Letters最新文献

BRAF ^V600E pediatric low-grade gliomas frequently transform into high-grade gliomas (HGG) and poorly respond to chemotherapy, resulting in high mortality. Although combined BRAF and MEK inhibition (BRAFi+MEKi) outperforms chemotherapy, ∼70% of BRAF ^V600E HGG patients are therapy resistant and undergo unbridled tumor progression. BRAF ^V600E glioma have an immune-rich microenvironment suggesting that they could be responsive to immunotherapy but effects of BRAFi+MEKi on anti-tumor immunity are unclear. Using patient tumor tissue before and after BRAFi+MEKi, two novel syngeneic murine models of BRAF ^V600E HGG, and patient-derived cell lines, we examined the effects of clinically relevant BRAFi+MEKi with dabrafenib and trametinib on tumor growth, cell states, and tumor-infiltrating T cells. We find that BRAFi+MEKi treatment: i) upregulated programmed cell death protein-1 (PD-1) signaling genes and PD-1 ligand (PD-L1) protein expression in murine BRAF ^V600E HGG by stimulating IFNγ and IL-27, ii) attenuated T cell activity by IL-23, IL-27 and IL-32 production, which can promote the expansion of regulatory T cells, and iii) induced glial differentiation linked to a therapy-resistant PD-L1+ compartment through Galectin-3 secretion by tumor cells. Murine BRAF ^V600E HGG shrinkage by BRAFi+MEKi is associated with the upregulation of interferon-gamma response genes, MHC class I/II expression, and antigen presentation and processing programs, indicative of increased anti-tumor immunity. Combined BRAFi+MEKi with therapeutic antibodies inhibiting the PD-1 and cytotoxic T-lymphocyte associated protein 4 (CTLA-4) immune checkpoints re-activate T cells and provide a survival benefit over single therapy in a T cell-dependent manner. The quadruple treatment overcame BRAFi+MEKi resistance by invigorating T cell-mediated anti-tumor immunity in murine BRAF ^V600E HGG. PD-L1 expression was elevated in human BRAF-mutant versus BRAF-wildtype glioblastoma clinical specimen, complementing experimental findings and suggesting translational relevance for patient care.

Objective: Drug utilization studies (DUS) provide a framework for drug utilization at the national or targeted population level and important information on unmet medical needs, particularly in assessing the rationality of drug use. We aimed to systematically review DUS conducted in Turkiye.

Methods: We examined 162 DUS with an accessible full-text, published as "research articles" and conducted in Turkiye between 2000 and 2021 using medical records and prescription data. We included English or Turkish papers with English abstracts. We examined the scientific characteristics of the publications, source of the data, place/time of collection, research designs, and studied drug groups.

Results: We found that 79.6% of articles were in English, 45.1% were listed in SCI/SCIE, and 63.0% were on the WOS platform with 3.5 (interquartile range: 1-15) citations. The mean study period and publication time were 2.9±3.1 and 2.9±2.1 years, respectively. The highest number of studies (17.9%) were published in 2021 and (26.5%) were conducted nationwide. We identified that 93.8% of the studies had retrospective design, 67.8% were conducted in secondary/tertiary health-care institutions, and 54.9% used direct hospital data. We detected that 68.5% of the studies were conducted on the general population, 19.1% on adults, 12.4% on children, and 44.4% were antibiotic oriented.

Conclusion: Our study showed that a significant portion of the DUS, the trend of which has gained momentum in recent years, was antibiotic focused and conducted with a retrospective design from hospital-based data collected on the general patient population. This situation points to the necessity of expanding the existing DUS range by effectively using the new advantages provided by medical record databases and conducting more DUS that can provide critical clues for specific patients and drug groups.

Various factors influence speech perception in noise (SPIN): age, hearing loss, cognition, background noise, stimulus redundancy, type of stimulus used, and signal-to-noise ratio. The effect of age on SPIN with different stimuli is yet to be validated in the literature. This study aims to study the effect of age on SPIN results across different stimuli. The study is a cross-sectional study with ninety participants with normal hearing ability. All participants in the study were equally divided into three groups: the children's group aged 8 to 12 years, the adult group aged 18 to 30, and the older adult group aged 55 to 72 years. Speech perception in the background of Kannada speech babble was assessed across three stimuli: monosyllables (CV), phonemically balanced Kannada words, and Kannada sentences. The stimulus was presented at 60 dBSPL binaurally through a calibrated headphone at 0 dB SNR. The result indicated a significant main effect of age on SPIN across syllables, words, and sentences. Further, Mann-Whitney test results revealed a statistically significant difference between the SPIN scores of children and adults for syllables, words, and sentences. Also, a statistical difference was noted in SPIN scores between adults and older adults for syllables, words, and sentences. However, statistical differences between children and older adults were seen only for syllables. The trend showed that the SPIN scores for syllables, words, and sentences improve from childhood to adulthood, while scores deteriorate from the adult to older adult group. A similar trend was seen for all three stimulus types. However, the reduction in the SPIN score using syllables in the older adult group was more noticeable than words and sentences. It can be concluded that there is an effect of age on SPIN abilities across different stimuli. It highlights the importance of age-appropriate SPIN normative for various stimuli.

Academic medical centers (AMCs) excel in many ways, but struggle to succeed at delivering cost-effective care in value-based payment models. To the extent these payment models become more widespread, or mandatory, this could be a giant risk to the future success of AMCs. Many attributes of AMCs that have served them well in a fee-for-service payment system may hinder the transformation needed to succeed in value-based care. Much of the underperformance of AMCs may be explained by two core competencies that AMCs lack: the limited ability to redesign clinical workflows and inability to change their economic relationships with their own specialists and primary care providers. These limitations, in turn, flow from a combination of electronic medical record systems that lock-in existing practice patterns, compensation systems that reward volume over value, organizational structures that make it very hard to drive clinicians to change, workforces with too many specialists, and complex accounting systems. To preserve current margins in value-based care, AMCs need to reduce their cost structures and gain new skills in primary and preventive care. Alternative, AMCs may choose to eschew value-based care and raise their prices for fee-for-service to offset declines in patient volume.

Genetic pediatric eye disease frequently leads to severe vision impairment or blindness. Voretigene neparvovec is the first approved gene therapy for an inherited retinal dystrophy (IRD). Voretigene neparvovec has been shown to be well tolerated and safe, with encouraging results in terms of efficacy, mainly when administered early in childhood. While we assisted at the first gene therapy available in clinical practice for an IRD, some questions remain unanswered, especially when gene therapy is delivered in young children. We review here the most recent reports and promising ongoing studies concerning various approaches on gene therapy in pediatric ophthalmology.

Introduction: Groin hernia literature often uses the terms light- and heavyweight and small or large pores to describe meshes. There is no universal definition of these terms, and the aim of this scoping review was to assess how mesh weight and pore sizes are defined in the groin hernia literature. Methods: In this systematic scoping review, we searched PubMed, Embase, and Cochrane CENTRAL. We included randomised controlled trials with adults undergoing groin hernia repair with the Lichtenstein or laparoscopic techniques using a flat permanent polypropylene or polyester mesh. Studies had to use the terms lightweight, mediumweight, or heavyweight to be included, and the outcome was to report how researchers defined these terms as well as pore sizes. Results: We included 48 studies with unique populations. The weight of lightweight meshes ranged from 28 to 60 g/m² with a median of 39 g/m², and the pore size ranged from 1.0 to 4.0 mm with a median of 1.6 mm. The weight of heavyweight meshes ranged from 72 to 116 g/m² with a median of 88 g/m², and the pore size ranged from 0.08 to 1.8 mm with a median of 1.0 mm. Only one mediumweight mesh was used weighing 55 g/m² with a pore size of 0.75 mm. Conclusion: There seems to be a consensus that meshes weighing less than 60 g/m² are defined as lightweight and meshes weighing more than 70 g/m² are defined as heavyweight. The weight terms were used independently of pore sizes, which slightly overlapped between lightweight and heavyweight meshes.

Machine learning has been used to study chemical reactivity for a long time in fields such as physical organic chemistry, chemometrics and cheminformatics. Recent advances in computer science have resulted in deep neural networks that can learn directly from the molecular structure. Neural networks are a good choice when large amounts of data are available. However, many datasets in chemistry are small, and models utilizing chemical knowledge are required for good performance. Adding chemical knowledge can be achieved either by adding more information about the molecules or by adjusting the model architecture itself. The current method of choice for adding more information is descriptors based on computed quantum-chemical properties. Exciting new research directions show that it is possible to augment deep learning with such descriptors for better performance in the low-data regime. To modify the models, differentiable programming enables seamless merging of neural networks with mathematical models from chemistry and physics. The resulting methods are also more data-efficient and make better predictions for molecules that are different from the initial dataset on which they were trained. Application of these chemistry-informed machine learning methods promise to accelerate research in fields such as drug design, materials design, catalysis and reactivity.

Emotional awareness supports emotion regulation. Psychologists have children "color in feelings" to assess emotional awareness, yet whether this relates to emotion regulation is unknown. The present study used a novel coloring task examining behaviors related to coloring in and dictating emotions to assess children's (N=95) emotional awareness. Further, it was tested whether performance on this task predicted emotion regulation. Children's coloring behaviors indicating physiological emotional awareness predicted better emotion regulation. Results may inform the use of emotional awareness tasks in community and clinical settings. Findings also suggest that physiological emotional awareness may be a more salient clinical target in children.