Research progress of the chemokine/chemokine receptor axes in the oncobiology of multiple myeloma (MM).

BACKGROUND: The incidence of multiple myeloma (MM), a type of blood cancer affecting monoclonal plasma cells, is rising. Although new drugs and therapies have improved patient outcomes, MM remains incurable. Recent studies have highlighted the crucial role of the chemokine network in MM's pathological mechanism. Gaining a better understanding of this network and creating an overview of chemokines in MM could aid in identifying potential biomarkers and developing new therapeutic strategies and targets. PURPOSE: To summarize the complicated role of chemokines in MM, discuss their potential as biomarkers, and introduce several treatments based on chemokines. METHODS: Pubmed, Web of Science, ICTRP, and Clinical Trials were searched for articles and research related to chemokines. Publications published within the last 5 years are selected. RESULTS: Malignant cells can utilize chemokines, including CCL2, CCL3, CCL5, CXCL7, CXCL8, CXCL12, and CXCL13 to evade apoptosis triggered by immune cells or medication, escape from bone marrow and escalate bone lesions. Other chemokines, including CXCL4, CCL19, and CXCL10, may aid in recruiting immune cells, increasing their cytotoxicity against cancer cells, and inducing apoptosis of malignant cells. CONCLUSION: Utilizing anti-tumor chemokines or blocking pro-tumor chemokines may provide new therapeutic strategies for managing MM. Inspired by developed CXCR4 antagonists, including plerixafor, ulocuplumab, and motixafortide, more small molecular antagonists or antibodies for pro-tumor chemokine ligands and their receptors can be developed and used in clinical practice. Along with inhibiting pro-tumor chemokines, studies suggest combining chemokines with chimeric antigen receptor (CAR)-T therapy is promising and efficient.

Rapid and Non-Destructive Prediction of Moisture Content in Maize Seeds Using Hyperspectral Imaging.

The moisture content of corn seeds is a crucial indicator for evaluating seed quality and is also a fundamental aspect of grain testing. In this experiment, 80 corn samples of various varieties were selected and their moisture content was determined using the direct drying method. The hyperspectral imaging system was employed to capture the spectral images of corn seeds within the wavelength range of 1100-2498 nm. By utilizing seven preprocessing techniques, including moving average, S-G smoothing, baseline, normalization, SNV, MSC, and detrending, we preprocessed the spectral data and then established a PLSR model for comparison. The results show that the model established using the normalization preprocessing method has the best prediction performance. To remove spectral redundancy and simplify the prediction model, we utilized SPA, CASR, and UVE algorithms to extract feature wavelengths. Based on three algorithms (PLSR, PCR, and SVM), we constructed 12 predictive models. Upon evaluating these models, it was determined that the normalization-SPA-PLSR algorithm produced the most accurate prediction. This model boasts high RC2 and RP2 values of 0.9917 and 0.9914, respectively, along with low RMSEP and RMSECV values of 0.0343 and 0.0257, respectively, indicating its exceptional stability and predictive capabilities. This suggests that the model can precisely estimate the moisture content of maize seeds. The results showed that hyperspectral imaging technology provides technical support for rapid and non-destructive prediction of corn seed moisture content and new methods in seed quality evaluation.

MAD-UNet: A Multi-Region UAV Remote Sensing Network for Rural Building Extraction.

For the development of an idyllic rural landscape, an accurate survey of rural buildings is essential. The extraction of rural structures from unmanned aerial vehicle (UAV) remote sensing imagery is prone to errors such as misclassifications, omissions, and subpar edge detailing. This study introduces a multi-scale fusion and detail enhancement network for rural building extraction, termed the Multi-Attention-Detail U-shaped Network (MAD-UNet). Initially, an atrous convolutional pyramid pooling module is integrated between the encoder and decoder to enhance the main network's ability to identify buildings of varying sizes, thereby reducing omissions. Additionally, a Multi-scale Feature Fusion Module (MFFM) is constructed within the decoder, utilizing superficial detail features to refine the layered detail information, which improves the extraction of small-sized structures and their edges. A coordination attention mechanism and deep supervision modules are simultaneously incorporated to minimize misclassifications. MAD-UNet has been tested on a private UAV building dataset and the publicly available Wuhan University (WHU) Building Dataset and benchmarked against models such as U-Net, PSPNet, DeepLabV3+, HRNet, ISANet, and AGSCNet, achieving Intersection over Union (IoU) scores of 77.43% and 91.02%, respectively. The results demonstrate its effectiveness in extracting rural buildings from UAV remote sensing images across different regions.

Copper incorporated biomaterial-based technologies for multifunctional wound repair.

The treatment of wounds is a worldwide challenge, and wound infection can affect the effectiveness of wound treatment and further increase the disease burden. Copper is an essential trace element that has been shown to have broad-spectrum antibacterial effects and to be involved in the inflammation, proliferation, and remodeling stages of wound healing. Compared to treatments such as bioactive factors and skin grafts, copper has the advantage of being low-cost and easily available, and has received a lot of attention in wound healing. Recently, biomaterials made by incorporating copper into bioactive glasses, polymeric scaffolds and hydrogels have been used to promote wound healing by the release of copper ions. In addition, copper-incorporated biomaterials with catalytic, photothermal, and photosensitive properties can also accelerate wound healing through antibacterial and wound microenvironment regulation. This review summarizes the antibacterial mechanisms of copper- incorporated biomaterials and their roles in wound healing, and discusses the current challenges. A comprehensive understanding of the role of copper in wounds will help to facilitate new preclinical and clinical studies, thus leading to the development of novel therapeutic tools.

From Multiple Myeloma to Acute Myeloid Leukemia: A Case Report of a 61-year-old Woman after 8 Years of Chemotherapy and Immunotherapy.

BACKGROUND: As the second most prevalent hematologic malignancy, multiple myeloma (MM) affects plasma cells and is characterized by chromosomal abnormalities, particularly involving the immunoglobulin heavy chain switch region. MM represents a biologically and clinically heterogeneous hematological malignancy that serves as a clonal evolution model, exhibiting clonal heterogeneity throughout all stages from monoclonal gammopathy undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to MM. Although significant progress has been made in the treatment of MM, leading to improved patient outcomes, concerns are arising regarding disease relapse due to the presence and selection of pre-existing resistant clones or selective pressure during therapy. CASE PRESENTATION: We present a case of multiple myeloma (MM) in a female patient, who underwent an 8-year course of treatment, including chemotherapy, immunomodulators, hematopoietic stem cell transplantation, CD38 monoclonal antibody, and chimeric antigen receptor T-cell (CAR-T), and was recently diagnosed with concurrent progressive MM and acute myeloid leukemia (AML). This patient has witnessed the evolution of MM treatment paradigms. CONCLUSION: In this course, disease relapses occurred twice, one of which was manifested by a light chain escape (LCE). Moreover, through the course of the disease in this patient, we review the process of clonal evolution that may be relevant.

Regulation of metabolic microenvironment with a nanocomposite hydrogel for improved bone fracture healing.

Bone nonunion poses an urgent clinical challenge that needs to be addressed. Recent studies have revealed that the metabolic microenvironment plays a vital role in fracture healing. Macrophages and bone marrow-derived mesenchymal stromal cells (BMSCs) are important targets for therapeutic interventions in bone fractures. Itaconate is a TCA cycle metabolite that has emerged as a potent macrophage immunomodulator that limits the inflammatory response. During osteogenic differentiation, BMSCs tend to undergo aerobic glycolysis and metabolize glucose to lactate. Copper ion (Cu2+) is an essential trace element that participates in glucose metabolism and may stimulate glycolysis in BMSCs and promote osteogenesis. In this study, we develop a 4-octyl itaconate (4-OI)@Cu@Gel nanocomposite hydrogel that can effectively deliver and release 4-OI and Cu2+ to modulate the metabolic microenvironment and improve the functions of cells involved in the fracture healing process. The findings reveal that burst release of 4-OI reduces the inflammatory response, promotes M2 macrophage polarization, and alleviates oxidative stress, while sustained release of Cu2+ stimulates BMSC glycolysis and osteogenic differentiation and enhances endothelial cell angiogenesis. Consequently, the 4-OI@Cu@Gel system achieves rapid fracture healing in mice. Thus, this study proposes a promising regenerative strategy to expedite bone fracture healing through metabolic reprogramming of macrophages and BMSCs.

Bone-targeting engineered small extracellular vesicles carrying anti-miR-6359-CGGGAGC prevent valproic acid-induced bone loss.

The clinical role and underlying mechanisms of valproic acid (VPA) on bone homeostasis remain controversial. Herein, we confirmed that VPA treatment was associated with decreased bone mass and bone mineral density (BMD) in both patients and mice. This effect was attributed to VPA-induced elevation in osteoclast formation and activity. Through RNA-sequencing, we observed a significant rise in precursor miR-6359 expression in VPA-treated osteoclast precursors in vitro, and further, a marked upregulation of mature miR-6359 (miR-6359) in vivo was demonstrated using quantitative real-time PCR (qRT-PCR) and miR-6359 fluorescent in situ hybridization (miR-6359-FISH). Specifically, the miR-6359 was predominantly increased in osteoclast precursors and macrophages but not in neutrophils, T lymphocytes, monocytes and bone marrow-derived mesenchymal stem cells (BMSCs) following VPA stimulation, which influenced osteoclast differentiation and bone-resorptive activity. Additionally, VPA-induced miR-6359 enrichment in osteoclast precursors enhanced reactive oxygen species (ROS) production by silencing the SIRT3 protein expression, followed by activation of the MAPK signaling pathway, which enhanced osteoclast formation and activity, thereby accelerating bone loss. Currently, there are no medications that can effectively treat VPA-induced bone loss. Therefore, we constructed engineered small extracellular vesicles (E-sEVs) targeting osteoclast precursors in bone and naturally carrying anti-miR-6359 by introducing of EXOmotif (CGGGAGC) in the 3'-end of the anti-miR-6359 sequence. We confirmed that the E-sEVs exhibited decent bone/osteoclast precursor targeting and exerted protective therapeutic effects on VPA-induced bone loss, but not on ovariectomy (OVX) and glucocorticoid-induced osteoporotic models, deepening our understanding of the underlying mechanism and treatment strategies for VPA-induced bone loss.

Cholesterol paradox in the community-living old adults: is higher better?

OBJECTIVE: To evaluate the associations of lipid indicators and mortality in Beijing Elderly Comprehensive Health Cohort Study. METHODS: A prospective cohort was conducted based on Beijing Elderly Comprehensive Health Cohort Study with 4499 community older adults. After the baseline survey, the last follow-up was March 31, 2021 with an average 8.13 years of follow-up. Cox proportional hazard model was used to estimate the hazard ratios (HR) with 95% CI for cardiovascular disease (CVD) death and all-cause death in associations with baseline lipid indicators. RESULTS: A total of 4499 participants were recruited, and the mean levels of uric acid, body mass index, systolic blood pressure, diastolic blood pressure, fasting plasma glucose, total cholesterol (TC), triglyceride, and low-density lipoprotein cholesterol (LDL-C) showed an upward trend with the increasing remnant cholesterol (RC) quarters (Ptrend < 0.05), while the downward trend was found in high-density lipoprotein cholesterol (HDL-C). During the total 36,596 person-years follow-up, the CVD mortality and all-cause mortality during an average 8.13 years of follow-up was 3.87% (95% CI: 3.30%-4.43%) and 14.83% (95% CI: 13.79%-15.86%) with 174 CVD death participants and 667 all-cause death participants. After adjusting for confounders, the higher level of TC (HR = 0.854, 95% CI: 0.730-0.997), LDL-C (HR = 0.817, 95% CI: 0.680-0.982) and HDL-C (HR = 0.443, 95% CI: 0.271-0.724) were associated with lower risk of CVD death, and the higher level of HDL-C (HR = 0.637, 95% CI: 0.501-0.810) were associated with lower risk of all-cause death. The higher level of RC (HR = 1.276, 95% CI: 1.010-1.613) increase the risk of CVD death. Compared with the normal lipid group, TC ≥ 6.20 mmol/L group and LDL-C ≥ 4.10 mmol/L group were no longer associated with lower risk of CVD death, while RC ≥ 0.80 mmol/L group was still associated with higher risk of CVD death. In normal lipid group, the higher levels of TC, LDL-C and HDL-C were related with lower CVD death. CONCLUSIONS: In community older adults, higher levels of TC and HDL-C were associated with lower CVD mortality in normal lipid reference range. Higher RC was associated with higher CVD mortality, which may be a better lipid indicator for estimating the CVD death risk in older adults.