Bone Marrow Adipocyte: An Intimate Partner With Tumor Cells in Bone Metastasis

The high incidences of bone metastasis in patients with breast cancer, prostate cancer and lung cancer still remains a puzzling issue. The “seeds and soil” hypothesis suggested that bone marrow (soil) may provide a favorable “niche” for tumor cells (seed). When seeking for effective ways to prevent and treat tumor bone metastasis, most researchers focus on tumor cells (seed) but not the bone marrow microenvironment (soil). In reality, only a fraction of circulating tumor cells (CTCs) could survive and colonize in bone. Thus, the bone marrow microenvironment could ultimately determine the fate of tumor cells that have migrated to bone. Bone marrow adipocytes (BMAs) are abundant in the bone marrow microenvironment. Mounting evidence suggests that BMAs may play a dominant role in bone metastasis. BMAs could directly provide energy for tumor cells, enhance the tumor cell proliferation, and resistance to chemotherapy and radiotherapy. BMAs are also known for releasing some inflammatory factors and adipocytokines to promote or inhibit bone metastasis. In this review, we made a comprehensive summary for the interaction between BMAs and bone metastasis. More importantly, we discussed the potentially promising methods for the prevention and treatment of bone metastasis. Genetic disruption and pharmaceutical inhibition may be effective in inhibiting the formation and pro-tumor functions of BMAs

Does Incident Solar Ultraviolet Radiation Lower Blood Pressure?

Background Hypertension remains a leading global cause for premature death and disease. Most treatment guidelines emphasize the importance of risk factors, but not all are known, modifiable, or easily avoided. Population blood pressure correlates with latitude and is lower in summer than winter. Seasonal variations in sunlight exposure account for these differences, with temperature believed to be the main contributor. Recent research indicates that UV light enhances nitric oxide availability by mobilizing storage forms in the skin, suggesting incident solar UV radiation may lower blood pressure. We tested this hypothesis by exploring the association between environmental UV exposure and systolic blood pressure (SBP) in a large cohort of chronic hemodialysis patients in whom SBP is determined regularly. Methods and Results We studied 342 457 patients (36% black, 64% white) at 2178 US dialysis centers over 3 years. Incident UV radiation and temperature data for each clinic location were retrieved from the National Oceanic and Atmospheric Administration database. Linear mixed effects models with adjustment for ambient temperature, sex/age, body mass index, serum Na+/K+ and other covariates were fitted to each location and combined estimates of associations calculated using the DerSimonian and Laird procedure. Pre-dialysis SBP varied by season and was ≈4 mm Hg higher in black patients. Temperature, UVA and UVB were all linearly and inversely associated with SBP. This relationship remained statistically significant after correcting for temperature. Conclusions In hemodialysis patients, in addition to environmental temperature, incident solar UV radiation is associated with lower SBP. This raises the possibility that insufficient sunlight is a new risk factor for hypertension, perhaps even in the general population.</p

Elucidation of the 1-phenethylisoquinoline pathway from an endemic conifer Cephalotaxus hainanensis

Cephalotaxines harbor great medical potential, but their natural source, the endemic conifer Cephalotaxus is highly endangered, creating a conflict between biotechnological valorization and preservation of biodiversity. Here, we construct the whole biosynthetic pathway to the 1-phenethylisoquinoline scaffold, as first committed compound for phenylethylisoquinoline alkaloids (PIAs), combining metabolic modeling, and transcriptome mining of Cephalotaxus hainanensis to infer the biosynthesis for PIA precursor. We identify a novel protein, ChPSS, driving the Pictet–Spengler condensation and show that this enzyme represents the branching point where PIA biosynthesis diverges from the concurrent benzylisoquinoline-alkaloids pathway. We also pinpoint ChDBR as crucial step to form 4-hydroxydihydrocinnamaldehyde diverging from lignin biosynthesis. The elucidation of the early PIA pathway represents an important step toward microbe-based production of these pharmaceutically important alkaloids resolving the conflict between biotechnology and preservation of biodiversity

Prioritization of schizophrenia risk genes from GWAS results by integrating multi-omics data

Schizophrenia (SCZ) is a polygenic disease with a heritability approaching 80%. Over 100 SCZ-related loci have so far been identified by genome-wide association studies (GWAS). However, the risk genes associated with these loci often remain unknown. We present a new risk gene predictor, rGAT-omics, that integrates multi-omics data under a Bayesian framework by combining the Hotelling and Box–Cox transformations. The Bayesian framework was constructed using gene ontology, tissue-specific protein–protein networks, and multi-omics data including differentially expressed genes in SCZ and controls, distance from genes to the index single-nucleotide polymorphisms (SNPs), and de novo mutations. The application of rGAT-omics to the 108 loci identified by a recent GWAS study of SCZ predicted 103 high-risk genes (HRGs) that explain a high proportion of SCZ heritability (Enrichment = 43.44 and p=9.30×10−9). HRGs were shown to be significantly (padj=5.35×10−7) enriched in genes associated with neurological activities, and more likely to be expressed in brain tissues and SCZ-associated cell types than background genes. The predicted HRGs included 16 novel genes not present in any existing databases of SCZ-associated genes or previously predicted to be SCZ risk genes by any other method. More importantly, 13 of these 16 genes were not the nearest to the index SNP markers, and them would have been difficult to identify as risk genes by conventional approaches while ten out of the 16 genes are associated with neurological functions that make them prime candidates for pathological involvement in SCZ. Therefore, rGAT-omics has revealed novel insights into the molecular mechanisms underlying SCZ and could provide potential clues to future therapies

Clinical efficacy of ultrasound-guided interventional therapy in patients with benign ovarian cysts: a meta-analysis

This study aimed to explore the clinical efficacy of ultrasound-guided interventional therapy in patients with benign ovarian cysts through meta-analysis. A literature search was performed on PubMed, Web of Science, Embase, CNKI, and WanFang databases to obtain clinical randomized controlled trials on ultrasound-guided interventional therapy for benign ovarian cysts published between 2010 and 2022. A total of 1395 studies were initially retrieved, and finally 12 studies were included for meta-analysis. The results showed that the observation group (ultrasound-guided interventional therapy) had higher treatment effective rate than the control group (conventional laparotomy or laparoscopic cyst resection), but the incidence of adverse reactions was markedly lower. Additionally, the length of hospital stay, intraoperative blood loss, and operation time showed significant lower levels in the observation group. In terms of ovarian function, postoperative luteinizing hormone and follicle-stimulating hormone levels in the observation group were lower than the control group, while oestradiol levels were higher. In conclusion, compared with conventional surgical treatment, ultrasound-guided interventional therapy can significantly improve the clinical effective rate, shorten the hospital stay and reduce intraoperative blood loss. Such therapy can protect ovarian reserve, with high value of clinical promotion.IMPACT STATEMENT What is already known on this subject? Main surgical methods for ovarian cysts consist of laparotomy, laparoscopic surgery, and interventional therapy. What the results of this study add? With the advancement of surgical techniques and instruments, many minimally invasive surgeries have been applied to treat ovarian cysts with good clinical results. However, there is no exact evidence to prove its clinical efficacy. Given the lack in this field, we conducted a meta-analysis of all clinical studies of ultrasound-guided interventional therapy for ovarian cysts to evaluate its efficacy and safety. What the implications are of these findings for clinical practice and/or further research? Compared with conventional laparotomic or laparoscopic cyst resection, ultrasound-guided interventional therapy for ovarian cysts significantly improves the treatment effectiveness, shortens the hospital stay and reduces intraoperative blood loss. This therapy with good clinical efficacy also has advantages of small wound, rapid recovery and less adverse reactions, and can protect ovarian reserve. This safe and effective surgical method for ovarian cysts is worth promoting clinically

Uterine rupture after high-intensity focused ultrasound ablation of adenomyosis: a case report and literature review

AbstractAim High-intensity focused ultrasound (HIFU) is a non-invasive treatment of adenomyosis. Uterine rupture during pregnancy is a rare adverse event after HIFU treatment, because HIFU treatment results in tissue coagulative necrosis.Methods We reported a case of uterine rupture in a 34-year-old woman. The woman had HIFU treatment for adenomyosis eight months before unplanned pregnancy. She was closely monitored during the pregnancy and the antenatal course was uneventful. At the gestational age of 38 weeks and 2 days, an emergency lower segment cesarean section was performed because of inexplainable abdominal pain. After delivery of the fetus, a 2 × 2 cm serous membrane rupture was observed in the HIFU treatment area.Conclusion Uterine rupture during pregnancy after HIFU is a rare adverse event, however, attention is required during the whole pregnancy in case of unexpected uterine rupture

Coseismic Kinematics of the 2023 Kahramanmaras, Turkey Earthquake Sequence From InSAR and Optical Data

Abstract We derive the ALOS‐2 coseismic interferograms, pixel‐offsets and Sentinel‐2 sub‐pixel offsets of the 2023 Mw7.8 and Mw7.7 Kahramanmaras, Turkey earthquake sequence. Offset maps show that the sequence ruptured ∼300 km along the East Anatolian Fault (EAF) and ∼180 km along the secondary Cardak and Dogansehir faults. We infer the coseismic slip distribution and interseismic fault motion by inverting the co‐ and inter‐seismic observations. Inversion results show that the coseismic slip (∼8.0 m) and interseismic strike‐slip rate (∼4.6 mm/yr) on the main rupture of the Mw7.8 event are basically consistent with the ∼8.4 m and ∼3.9 mm/yr of the Mw7.7 event. Most coseismic slips of the Mw7.8 and Mw7.7 events occur within 10 and 12 km at depth, respectively, in keeping with the interseismic locking depth of 10.4 ± 3.3 km and 11.1 ± 3.1 km. This implies that the coseismic rupture kinematics correlate with the interseismic strain accumulation. Moreover, static stress changes show that the Mw7.7 event is likely promoted by ∼2 bar stress increase from the Mw7.8 event on the central section of its main rupture

An uncertainty-based interpretable deep learning framework for predicting breast cancer outcome

Abstract Background Predicting outcome of breast cancer is important for selecting appropriate treatments and prolonging the survival periods of patients. Recently, different deep learning-based methods have been carefully designed for cancer outcome prediction. However, the application of these methods is still challenged by interpretability. In this study, we proposed a novel multitask deep neural network called UISNet to predict the outcome of breast cancer. The UISNet is able to interpret the importance of features for the prediction model via an uncertainty-based integrated gradients algorithm. UISNet improved the prediction by introducing prior biological pathway knowledge and utilizing patient heterogeneity information. Results The model was tested in seven public datasets of breast cancer, and showed better performance (average C-index = 0.691) than the state-of-the-art methods (average C-index = 0.650, ranged from 0.619 to 0.677). Importantly, the UISNet identified 20 genes as associated with breast cancer, among which 11 have been proven to be associated with breast cancer by previous studies, and others are novel findings of this study. Conclusions Our proposed method is accurate and robust in predicting breast cancer outcomes, and it is an effective way to identify breast cancer-associated genes. The method codes are available at: https://github.com/chh171/UISNet