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Far-red lights (FRs), with a wavelength range between 700 and 800 nm, have substantial impacts on plant growth, especially horticultural crops. Previous studies showed conflicting results on the effects of FRs on vegetable growth and quality. Therefore, we conducted a meta-analysis on the influence of FRs on vegetable growth, aiming to provide a comprehensive overview of their effects on the growth and nutritional indicators of vegetables. A total of 207 independent studies from 55 literature sources were analyzed. The results showed that FR treatment had significant effects on most growth indicators, including increasing the fresh weight (+25.27%), dry weight (+21.99%), plant height (+81.87%), stem diameter (+12.91%), leaf area (+18.57%), as well as reducing the content of chlorophyll (−11.88%) and soluble protein (−11.66%), while increasing soluble sugar content (+19.12%). Further subgroup analysis based on various factors revealed significant differences in the effects of FR on different physiological indicators, such as FR intensity, plant species, duration of FR exposure, and the ratio of red light to FR. In general, moderate FR treatment is beneficial for vegetable growth. This study provides important references and guidelines for optimizing the application of FR in the future. [ABSTRACT FROM AUTHOR]

The interplay between the immune system and cancer underscores the central role of immunotherapy in cancer treatment. In this context, the innate immune system plays a critical role in preventing tumor invasion. Myeloid differentiation factor 88 (MyD88) is crucial for innate immunity, and activation of MyD88 promotes the production of inflammatory cytokines and induces infiltration, polarization, and immune escape of immune cells in the tumor microenvironment. Additionally, abnormal MyD88 signaling induces tumor cell proliferation and metastasis, which are closely associated with poor prognosis. Therefore, MyD88 could serve as a novel tumor biomarker and is a promising target for cancer therapy. Current strategies targeting MyD88 including inhibition of signaling pathways and protein multimerization, have made substantial progress, especially in inflammatory diseases and chronic inflammation-induced cancers. However, the specific role of MyD88 in regulating tumor immunity and tumorigenic mechanisms remains unclear. Therefore, this review describes the involvement of MyD88 in tumor immune escape and disease therapy. In addition, classical and non-classical MyD88 inhibitors were collated to provide insights into potential cancer treatment strategies. Despite several challenges and complexities, targeting MyD88 is a promising avenue for improving cancer treatment and has the potential to revolutionize patient outcomes. [ABSTRACT FROM AUTHOR]

Drug–target interaction (DTIs) prediction plays a vital role in probing new targets for breast cancer research. Considering the multifaceted challenges associated with experimental methods identifying DTIs, the in silico prediction of such interactions merits exploration. In this study, we develop a feature-based method to infer unknown DTIs, called PsePDC-DTIs, which fuses information regarding protein sequences extracted by pseudo-position specific scoring matrix (PsePSSM), detrended cross-correlation analysis coefficient (DCCA coefficient), and an FP2 format molecular fingerprint descriptor of drug compounds. In addition, the synthetic minority oversampling technique (SMOTE) is employed for dealing with the imbalanced data after Lasso dimensionality reduction. Then, the processed feature vectors are put into a random forest classifier to perform DTIs predictions on four gold standard datasets, including nuclear receptors (NR), G-protein-coupled receptors (GPCR), ion channels (IC), and enzymes (E). Furthermore, we explore new targets for breast cancer treatment using its risk genes identified from large-scale genome-wide genetic studies using PsePDC-DTIs. Through five-fold cross-validation, the average values of accuracy in NR, GPCR, IC, and E datasets are 95.28%, 96.19%, 96.74%, and 98.22%, respectively. The PsePDC-DTIs model provides us with 10 potential DTIs for breast cancer treatment, among which erlotinib (DB00530) and FGFR2 (hsa2263), caffeine (DB00201) and KCNN4 (hsa3783), as well as afatinib (DB08916) and FGFR2 (hsa2263) are found with direct or inferred evidence. The PsePDC-DTIs model has achieved good prediction results, establishing the validity and superiority of the proposed method. [ABSTRACT FROM AUTHOR]

The interacted effects of photoperiod and nutrient solution concentrations (NSCs) on nutritional quality and antioxidant and mineral content in lettuce were investigated in this study. There were a total of nine treatments by three photoperiods (12 h/12 h, 15 h/9 h, and 18 h/6 h), with a combination of three NSCs (1/4, 1/2, and 3/4 NSC). The contents of photosynthetic pigment, mineral element, and nutritional quality were markedly affected by the combination of photoperiod and NSC. The highest leaf number and plant weight were found in lettuce under the combination of 18–0.25X. There was a higher content of photosynthetic pigment in treatment of 15-0.25X. Shorter photoperiod (12 h/12 h and 15 h/9 h) and NSC (1/4 and 1/2 NSC) contributed to reduced nitrate contents and higher contents of free amino acid, soluble protein, and vitamin C. Longer photoperiod and lower NSC could increase soluble sugar content. The content of total P, K, and Ca exhibited a similar trend under the combination of photoperiod and NSC, with a higher content at 3/4 NSC under different photoperiods. Lower contents of total Zn and N were found under longer photoperiod. Moreover, higher antioxidant contents, including 2, 2-diphenyl-1-picrylhydrazyl (DPPH), value of ferric-reducing antioxidant power (FRAP), flavonoid, polyphenol, and anthocyanin were observed under shorter photoperiod, with the peak under 12-0.50X. Generally, 12-0.50X might be the optimal treatment for the improvement of the nutritional quality of lettuce in a plant factory that produced high-quality vegetables. [ABSTRACT FROM AUTHOR]

A series of novel coumarin-based hydroxamate derivatives were designed and synthesized as histone deacetylase inhibitors (HDACis). Selective compounds showed a potent HDAC inhibition with nM IC50 values, with the best compound (10e) being nearly 90 times more active than vorinostat (SAHA) against HDAC1. Compounds 10e and 11d also increased the levels of acetylated histone H3 and H4, which is consistent with their strong HDAC inhibition. In addition, 10e and 11d displayed a higher potency toward human A549 and Hela cancer cell lines compared with SAHA. Moreover, 10e and 11d significantly arrested A549 cells at the G2/M phase and enhanced apoptosis. Molecular docking studies revealed the possible mode of interaction of compounds 10e and 12a with HDAC1. Our findings suggest that these novel coumarin-based HDAC inhibitors provide a promising scaffold for the development of new potential cancer chemotherapies. [ABSTRACT FROM AUTHOR]

Stroke is a severe cerebrovascular disease and is the second greatest cause of death worldwide. Because diagnostic tools (CT and MRI) to detect acute stroke cannot be used until the patient reaches the hospital setting, a portable diagnostic tool is urgently needed. Because biological tissues have different impedance spectra under normal physiological conditions and different pathological states, multi-frequency electrical impedance tomography (MFEIT) can potentially detect stroke. Accurate impedance spectra of normal brain tissue (gray and white matter) and stroke lesions (ischemic and hemorrhagic tissue) are important elements when studying stroke detection with MFEIT. To our knowledge, no study has comprehensively measured the impedance spectra of normal brain tissue and stroke lesions for the whole frequency range of 1 MHz within as short as possible an ex vivo time and using the same animal model. In this study, we established intracerebral hemorrhage and ischemic models in rabbits, then measured and analyzed the impedance spectra of normal brain tissue and stroke lesions ex vivo within 15 min after animal death at 10 Hz to 1 MHz. The results showed that the impedance spectra of stroke lesions significantly differed from those of normal brain tissue; the ratio of change in impedance of ischemic and hemorrhagic tissue with regard to frequency was distinct; and tissue type could be discriminated according to its impedance spectra. These findings further confirm the feasibility of detecting stroke with MFEIT and provide data supporting further study of MFEIT to detect stroke., Competing Interests: The authors declare no conflict of interest.