Star1 gene mutation reveals the essentiality of 11-ketotestosterone and glucocorticoids for male fertility in Nile Tilapia (Oreochromis niloticus).

Steroidogenic acute regulatory protein (Star) plays an essential role in the biosynthesis of corticosteroids and sex steroids by mediating the transport of cholesterol from the outer to the inner membrane of mitochondria. Two duplicated Star genes, namely star1 and star2, have been identified in non-mammalian vertebrates. To investigate the roles of star genes in fish steriodogenesis, we generated two mutation lines of star1-/- and star1-/-/star2-/- in Nile tilapia (Oreochromis niloticus). Previous studies revealed that deficiency of star2 gene caused delayed spermatogenesis, sperm apoptosis and sterility in male tilapia. Our present data revealed that mutation of star genes impaired male fertility. Disordered seminiferous lobules and spermatic duct obstruction were found in the testis of both types of mutants. Moreover, significant decline in semen volume, sperm abnormality and impaired fertility were also detected in star1-/- and star1-/-/star2-/- males. In star1-/- male fish, lipid accumulation, up-regulation of steroidogenic enzymes, and significant decline of androgens were found. Additionally, hyperplasic interrenal cells, elevated steroidogenic gene expression level and decline of serum glucocorticoids were detected in star1 mutants. Intriguingly, either 11-KT or cortisol supplementation successfully rescued the impaired fertility of the star1-/- mutants. Taken together, these results further indicate that Star1 might play critical roles in the production of both 11-KT and glucocorticoids, which are indispensable for the maintenance of male fertility in fish.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity.

BACKGROUND: Early prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients. METHODS: The DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways. RESULTS: A 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635-0.741 and AUC = 0.650, 95%CI: 0.595-0.705) and tested (AUC = 0.686, 95%CI: 0.594-0.778 and AUC = 0.626, 95%CI: 0.529-0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722-0.816 and test: 0.762, 95%CI: 0.679-0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665-0.767 and test AUC = 0.695, 95%CI: 0.656-0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system. CONCLUSION: Dynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

Mechanistic insights into cardiovascular effects of ultrafine particle exposure: A longitudinal panel study.

BACKGROUND: Ultrafine particle (UFP) has been linked with higher risks of cardiovascular diseases; however, the biological mechanisms remain to be fully elucidated. OBJECTIVES: This study aims to investigate the cardiovascular responses to short-term UFP exposure and the biological pathways involved. METHODS: A longitudinal panel study was conducted among 32 healthy, non-smoking young adults in Shanghai, China, who were engaged in five rounds of follow-ups between December 2020 and November 2021. Individual exposures were calculated based on the indoor and outdoor real-time measurements. Blood pressure, arterial stiffness, targeted biomarkers, and untargeted proteomics and metabolomics were examined during each follow-up. Linear mixed-effect models were applied to analyze the exposure and health data. The differential proteins and metabolites were used for pathway enrichment analyses. RESULTS: Short-term UFP exposure was associated with significant increases in blood pressure and arterial stiffness. For example, systolic blood pressure increased by 2.10 % (95 % confidence interval: 0.63 %, 3.59 %) corresponding to each interquartile increase in UFP concentrations at lag 0-3 h, while pulse wave velocity increased by 2.26 % (95 % confidence interval: 0.52 %, 4.04 %) at lag 7-12 h. In addition, dozens of molecular biomarkers altered significantly. These effects were generally present within 24 h after UFP exposure, and were robust to the adjustment of co-pollutants. Molecular changes detected in proteomics and metabolomics analyses were mainly involved in systemic inflammation, oxidative stress, endothelial dysfunction, coagulation, and disturbance in lipid transport and metabolism. DISCUSSION: This study provides novel and compelling evidence on the detrimental subclinical cardiovascular effects in response to short-term UFP exposure. The multi-omics profiling further offers holistic insights into the underlying biological pathways.

Gut microbial alterations in arginine metabolism determine bone mechanical adaptation.

Although mechanical loading is essential for maintaining bone health and combating osteoporosis, its practical application is limited to a large extent by the high variability in bone mechanoresponsiveness. Here, we found that gut microbial depletion promoted a significant reduction in skeletal adaptation to mechanical loading. Among experimental mice, we observed differences between those with high and low responses to exercise with respect to the gut microbial composition, in which the differential abundance of Lachnospiraceae contributed to the differences in bone mechanoresponsiveness. Microbial production of L-citrulline and its conversion into L-arginine were identified as key regulators of bone mechanoadaptation, and administration of these metabolites enhanced bone mechanoresponsiveness in normal, aged, and ovariectomized mice. Mechanistically, L-arginine-mediated enhancement of bone mechanoadaptation was primarily attributable to the activation of a nitric-oxide-calcium positive feedback loop in osteocytes. This study identifies a promising anti-osteoporotic strategy for maximizing mechanical loading-induced skeletal benefits via the microbiota-metabolite axis.

Comprehensive analysis reveals that LTBR is a immune-related biomarker for glioma.

Glioma is a common malignant brain tumor with great heterogeneity and huge difference in clinical outcomes. Although lymphotoxin (LT) beta receptor (LTBR) has been linked to immune system and response development for decades, the expression and function in glioma have not been investigated. To confirm the expression profile of LTBR, integrated RNA-seq data from glioma and normal brain tissues were analyzed. Functional enrichment analysis, TMEscore analysis, immune infiltration, the correlation of LTBR with immune checkpoints and ferroptosis, and scRNAseq data analysis in gliomas were in turn performed, which pointed out that LTBR was pertinent to immune functions of macrophages in gliomas. In addition, after being trained and validated in the tissue samples of the integrated dataset, an LTBR DNA methylation-based prediction model succeeded to distinguish gliomas from non-gliomas, as well as the grades of glioma. Moreover, by virtue of the candidate LTBR CpG sites, a prognostic risk-score model was finally constructed to guide the chemotherapy, radiotherapy, and immunotherapy for glioma patients. Taken together, LTBR is closely correlated with immune functions in gliomas, and LTBR DNA methylation could serve as a biomarker for diagnosis and prognosis of gliomas.

Improvement of Lung Function by Micronutrient Supplementation in Patients with COPD: A Systematic Review and Meta-Analysis.

BACKGROUND: A healthy, well-balanced diet plays an essential role in respiratory diseases. Since micronutrient deficiency is relatively common in patients with chronic obstructive pulmonary disease (COPD), micronutrient supplementation might have the beneficial health effects in those patients. This systematic review and meta-analysis aimed to demonstrate the impact of micronutrient supplementation on the lung function of patients with COPD. METHODS: The PubMed, Cochrane Library, and Web of Science databases were searched from their corresponding creation until February 2024. Search terms included 'chronic obstructive pulmonary disease', 'COPD', 'micronutrients', 'dietary supplements', 'vitamins', 'minerals', and 'randomized controlled trials'. Meta-analysis was performed to evaluate the effects of micronutrient supplementation alone or complex on lung function in patients with COPD. RESULTS: A total of 43 RCTs fulfilled the inclusion criteria of this study. Meta-analysis revealed that vitamin D supplementation could significantly improve FEV1% (WMDdifferences between baseline and post-intervention (de): 6.39, 95% CI: 4.59, 8.18, p < 0.01; WMDpost-intervention indicators (af): 7.55, 95% CI: 5.86, 9.24, p < 0.01) and FEV1/FVC% (WMDde: 6.88, 95%CI: 2.11, 11.65, WMDaf: 7.64, 95% CI: 3.18, 12.10, p < 0.001), decrease the odds of acute exacerbations, and improve the level of T-cell subsets, including CD3+%, CD4+%, CD8+%, and CD4+/CD8+% (all p < 0.01). The effects of compound nutrients intervention were effective in improving FEV1% (WMDde: 8.38, 95%CI: 1.89, 14.87, WMDaf: 7.07, 95%CI: -0.34, 14.48) and FEV1/FVC% (WMDde: 7.58, 95% CI: 4.86, 10.29, WMDaf: 6.00, 95% CI: 3.19, 8.81). However, vitamin C and vitamin E supplementation alone had no significant effects on lung function (p > 0.05). CONCLUSIONS: Micronutrient supplementation, such as vitamin D alone and compound nutrients, has improved effect on the lung function of patients with COPD. Therefore, proper supplementation with micronutrients would be beneficial to stabilize the condition and restore ventilation function for COPD patients.

Influencing factors of kinesiophobia among stroke patients with hemiplegia: A mixed methods study.

OBJECTIVES: There is a scarcity of data regarding the effects of kinesiophobia on stroke patients with hemiplegia. Therefore, this paper aims to evaluate the level of kinesiophobia experienced by stroke patients with hemiplegia in China, examine the elements that influence it, and investigate the unique psychological experience of kinesiophobia combined with a qualitative study. METHODS: This mixed study was conducted in two steps. Four approved scales were used to evaluate a total of 163 patients: (i) Tampa Scale of Kinesiophobia, (ii) Pain Catastrophizing Scale, (iii) Self-Efficacy for Exercise Scale, and (iv) Hospital Anxiety and Depression Scale. A multivariate linear regression model was used to evaluate the predictors of kinesiophobia in stroke patients with hemiplegia. Subsequently, semi-structured interviews with 15 stroke patients with hemiplegia were conducted using an objective sampling method, and the Colaizzi 7-step analysis process was utilized to analyze the interview data. RESULTS: A total of 163 stroke patients with hemiplegia were included in this study, of them, 47.9% reported kinesiophobia. Multiple linear regression revealed that the influencing factors of kinesiophobia in stroke patients with hemiplegia were a history of falls, exaggeration, helplessness, anxiety, depression, and low exercise self-efficacy (P<0.05). The qualitative research focuses on two main topics: personal adoption of negative coping styles and insufficient external support. CONCLUSION: Our study showed that the kinesiophobia in stroke patients with hemiplegia was high, with several factors influencing their kinesiophobia. Some of these factors are modifiable and should be considered when formulating kinesiophobia intervention strategies for stroke patients with hemiplegia.

TIE1 promotes cervical cancer progression via Basigin-matrix metalloproteinase axis.

Background: Tyrosine kinase with immunoglobulin and EGF-like domains 1 (TIE1) is known as an orphan receptor prominently expressed in endothelial cells and participates in angiogenesis by regulating TIE2 activity. Our previous study demonstrated elevated TIE1 expression in cervical cancer cells. However, the role of TIE1 in cervical cancer progression, metastasis and treatment remains elusive. Methods: Immunohistochemistry staining for TIE1 and Basigin was performed in 135 human cervical cancer tissues. Overexpressing vectors and siRNAs were used to manipulate gene expression in tumor cells. Colony formation, wound healing, and transwell assays were used to assess cervical cancer cell proliferation and migration in vitro. Subcutaneous xenograft tumor and lung metastasis mouse models were established to examine tumor growth and metastasis. Co-Immunoprecipitation and Mass Spectrometry were applied to explore the proteins binding to TIE1. Immunoprecipitation and immunofluorescence staining were used to verify the interaction between TIE1 and Basigin. Cycloheximide chase assay and MG132 treatment were conducted to analyze protein stability. Results: High TIE1 expression was associated with poor survival in cervical cancer patients. TIE1 overexpression promoted the proliferation, migration and invasion of cervical cancer cells in vitro, as well as tumor growth and metastasis in vivo. In addition, Basigin, a transmembrane glycoprotein, was identified as a TIE1 binding protein, suggesting a pivotal role in matrix metalloproteinase regulation, angiogenesis, cell adhesion, and immune responses. Knockdown of Basigin or treatment with the Basigin inhibitor AC-73 reversed the tumor-promoting effect of TIE1 in vitro and in vivo. Furthermore, we found that TIE1 was able to interact with and stabilize the Basigin protein and stimulate the Basigin-matrix metalloproteinase axis. Conclusion: TIE1 expression in cervical cells exerts a tumor-promoting effect, which is at least in part dependent on its interaction with Basigin. These findings have revealed a TIE2-independent mechanism of TIE1, which may provide a new biomarker for cervical cancer progression, and a potential therapeutic target for the treatment of cervical cancer patients.

Bioinformatic Identification of Signaling Pathways and Hub Genes in Vascular Dementia.

BACKGROUND: Vascular dementia (VaD) is a prevalent neurodegenerative disease characterized by cognitive impairment due to cerebrovascular factors, affecting a significant portion of the aging population and highlighting the critical need to understand specific targets and mechanisms for effective prevention and treatment strategies. We aimed to identify pathways and crucial genes involved in the progression of VaD through bioinformatics analysis and subsequently validate these findings. METHODS: We conducted differential expression analysis, Weighted Gene Co-expression Network Analysis (WGCNA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and Protein-Protein Interaction (PPI) analysis. We utilized pheochromocytoma 12 (PC12) cells to create an in vitro oxygen-glucose deprivation (OGD) model. We investigated the impact of overexpression and interference of adrenoceptor alpha 1D (ADRA1D) on OGD PC12 cells using TdT-mediated dUTP nick-end labeling (TUNEL), reverse transcription-quantitative polymerase chain reaction (RT-qPCR), western blot (WB), and Fluo-3-pentaacetoxymethyl ester (Fluo-3 AM) analysis. RESULTS: We found 187 differentially expressed genes (DEGs) in the red module that were strongly associated with VaD and were primarily enriched in vasoconstriction, G protein-coupled amine receptor activity, and neuroactive ligand-receptor interaction, mitogen-activated protein kinase (MAPK) signaling pathway, and cell adhesion. Among these pathways, we identified ADRA1D as a gene shared by vasoconstriction, G protein-coupled amine receptor activity, and neuroactive ligand-receptor interaction. The TUNEL assay revealed a significant decrease in PC12 cell apoptosis with ADRA1D overexpression (p < 0.01) and a significant increase in apoptosis upon silencing ADRA1D (p < 0.01). RT-qPCR and WB analysis revealed elevated ADRA1D expression (p < 0.001) and decreased phospholipase C beta (PLCß) and inositol 1,4,5-trisphosphate receptor (IP3R) expression (p < 0.05) with ADRA1D overexpression. Moreover, the Fluo-3 AM assessment indicated significantly lower intracellular Ca2+ levels with ADRA1D overexpression (p < 0.001). Conversely, interference with ADRA1D yielded opposite results. CONCLUSION: Our study provides a new perspective on the pathogenic mechanisms of VaD and potential avenues for therapeutic intervention. The results highlight the role of ADRA1D in modulating cellular responses to OGD and VaD, suggesting its potential as a target for VaD treatment.

Chromosome-scale genomes of Quercus sichourensis and Quercus rex provide insights into the evolution and adaptation of Fagaceae.

The Fagaceae, a plant family with a wide distribution and diverse adaptability, has garnered significant interest as a subject of study in plant speciation and adaptation. Meanwhile, certain Fagaceae species are regarded as highly valuable wood resources due to the exceptional quality of their wood. In this study, we present two high-quality, chromosome-scale genome sequences for Quercus sichourensis (848.75 Mb) and Quercus rex (883.46 Mb). Comparative genomics analysis reveals that the difference in the number of plant disease resistance genes and the nonsynonymous and synonymous substitution ratio (Ka/Ks) of protein-coding genes among Fagaceae species are related to different environmental adaptations. Interestingly, most genes related to starch synthesis in the investigated Quercoideae species are located on a single chromosome, as compared to the outgroup species, Fagus sylvatica. Furthermore, resequencing and population analysis of Q. sichourensis and Q. rex reveal that Q. sichourensis has lower genetic diversity and higher deleterious mutations compared to Q. rex. The high-quality, chromosome-level genomes and the population genomic analysis of the critically endangered Q. sichourensis and Q. rex will provide an invaluable resource as well as insights for future study in these two species, even the genus Quercus, to facilitate their conservation.

We Reduced the Incidence of Postoperative Complications in Neonatal Ostomy Patients by Using Simple Devices.

Background: Complications frequently occur after neonatal enterostomy. Enterostomy formation is a common outcome following an emergency neonatal laparotomy. This study investigated whether the incidence of complications after enterostomy could be decreased with a drainage device (composed of foreskin cerclage staple, a condom, and a 0-Mersilk braided nonabsorbable suture) fixed in the proximal ostomy bowel tube to improve proximal enterostomy in newborns. Methods: This study was a retrospective case note review of the incidence of emergency neonatal enterostomy incidence over a 3-year period (2/2016-2/2019) at the authors' center. A single surgeon conducted all surgeries. The incidence of intraoperative and postoperative complications was compared between modified and traditional surgery groups. Results: All 47 surgeries were successfully completed (32 boys and 15 girls; sex ratio: 2.13:1). The mean (±SD) birth weight, gestational period, and daily age were 2.64 ± 0.81 kg 35.62 ± 3.76 weeks and 3.49 ± 5.61 days, respectively. The patients were divided into modified surgery groups (20 cases) and traditional surgery groups (27 cases). The modified surgery group had significantly lower rates of total complications, unplanned reoperations, wound-related complications, and stoma-related complications than the traditional group (p <0.05). Conclusions: The preliminary observations suggested that the simple drainage device was a safe and effective operation device that reduced the risk of stoma-related complications.

Comparative analysis of sipeimine content, metabolome and chloroplast genome in cultivated and wild varieties of Fritillaria taipaiensis.

BACKGROUND: The wild variety Fritillaria taipaiensis E.B (EB) is known for its superior therapeutic effects, but its limited production cannot meet demand. As a result, the cultivated variety F. taipaiensis P. Y. Li (PY) has been widely grown. In this study, we conducted a comprehensive analysis comparing EB and PY in terms of external features, sipeimine content, metabolome and chloroplast genome to differentiate these two varieties. RESULTS: Our research revealed that the petals and pods of EB are green, while those of PY have purple markings. The bulbs of EB contain significantly higher levels of sipeimine compared to those of PY. Metabolomic analysis identified 56 differentially expressed metabolites (DMs), with 23 upregulated and 33 downregulated in EB bulbs. Particularly, 3-hydroxycinnamic acid and secoxyloganin may serve as distinctive DMs. These DMs were associated with 17 KEGG pathways, including pyrimidine metabolism, alanine, aspartate and glutamate metabolism, and galactose metabolism. Differences in the length of the chloroplast genome were primarily observed in the large single-copy (LSC) region, with the largest variation in the trnH-GUC-psbA region. The placement of the trnH gene and the rps gene in proximity to the LSC/IRb boundary differs between EB and PY. CONCLUSION: The results of this study provide valuable insights for the introduction and comprehensive development of wild F. taipaiensis from a scientific perspective. © 2024 Society of Chemical Industry.

Radiomics signature of osteoarthritis: Current status and perspective.

Osteoarthritis (OA) is one of the fast-growing disability-related diseases worldwide, which has significantly affected the quality of patients' lives and brings about substantial socioeconomic burdens in medical expenditure. There is currently no cure for OA once the bone damage is established. Unfortunately, the existing radiological examination is limited to grading the disease's severity and is insufficient to precisely diagnose OA, detect early OA or predict OA progression. Therefore, there is a pressing need to develop novel approaches in medical image analysis to detect subtle changes for identifying early OA development and rapid progressors. Recently, radiomics has emerged as a unique approach to extracting high-dimensional imaging features that quantitatively characterise visible or hidden information from routine medical images. Radiomics data mining via machine learning has empowered precise diagnoses and prognoses of disease, mainly in oncology. Mounting evidence has shown its great potential in aiding the diagnosis and contributing to the study of musculoskeletal diseases. This paper will summarise the current development of radiomics at the crossroads between engineering and medicine and discuss the application and perspectives of radiomics analysis for OA diagnosis and prognosis. The translational potential of this article: Radiomics is a novel approach used in oncology, and it may also play an essential role in the diagnosis and prognosis of OA. By transforming medical images from qualitative interpretation to quantitative data, radiomics could be the solution for precise early OA detection, progression tracking, and treatment efficacy prediction. Since the application of radiomics in OA is still in the early stages and primarily focuses on fundamental studies, this review may inspire more explorations and bring more promising diagnoses, prognoses, and management results of OA.

Glutamine metabolism prognostic index predicts tumour microenvironment characteristics and therapeutic efficacy in ovarian cancer.

Mounting evidence has highlighted the multifunctional characteristics of glutamine metabolism (GM) in cancer initiation, progression and therapeutic regimens. However, the overall role of GM in the tumour microenvironment (TME), clinical stratification and therapeutic efficacy in patients with ovarian cancer (OC) has not been fully elucidated. Here, three distinct GM clusters were identified and exhibited different prognostic values, biological functions and immune infiltration in TME. Subsequently, glutamine metabolism prognostic index (GMPI) was constructed as a new scoring model to quantify the GM subtypes and was verified as an independent predictor of OC. Patients with low-GMPI exhibited favourable survival outcomes, lower enrichment of several oncogenic pathways, less immunosuppressive cell infiltration and better immunotherapy responses. Single-cell sequencing analysis revealed a unique evolutionary trajectory of OC cells from high-GMPI to low-GMPI, and OC cells with different GMPI might communicate with distinct cell populations through ligand-receptor interactions. Critically, the therapeutic efficacy of several drug candidates was validated based on patient-derived organoids (PDOs). The proposed GMPI could serve as a reliable signature for predicting patient prognosis and contribute to optimising therapeutic strategies for OC.

SIRT3: A Potential Target of Different Types of Osteoporosis.

Osteoporosis (OP) is a common age-related disease. OP is mainly a decrease in bone density and mass caused by the destruction of bone microstructure, which leads to an increase in bone fragility. SIRT3 is a mitochondrial deacetylase that plays critical roles in mitochondrial homeostasis, metabolic regulation, gene transcription, stress response, and gene stability. Studies have shown that the higher expression levels of SIRT3 are associated with decreased levels of oxidative stress in the body and may play important roles in the prevention of age-related diseases. SIRTs can enhance the osteogenic potential and osteoblastic activity of bone marrow mesenchymal stromal cells not only by enhancing PGC-1α, FOXO3, SOD2, and oxidative phosphorylation, but also by anti-aging and reducing mitochondrial autophagy. SIRT3 is able to upregulate antioxidant enzymes to exert an inhibitory effect on osteoclasts, however, it has been shown that the inflammatory cascade response can in turn increase SIRT3 and inhibit osteoclast differentiation through the AMPK-PGC-1ß pathway. SIRT3 plays an important role in different types of osteoporosis by affecting osteoblasts, osteoclasts, and bone marrow mesenchymal cells. In this review, we discuss the classification and physiological functions of SIRTs, the effects of SIRT3 on OCs osteoblasts, and BMSCs, and the roles and mechanisms of SIRT3 in different types of OP, such as diabetic OP, glucocorticoid-induced OP, postmenopausal OP, and senile OP.

Global-best brain storm optimization algorithm based on chaotic difference step and opposition-based learning.

Recently, the following global-best strategy and discussion mechanism have been prevailing to solve the slow convergence and the low optimization accuracy in the brain storm optimization (BSO) algorithm. However, the traditional BSO algorithm also suffers from the problem that it is easy to fall into local optimum. Therefore, this work innovatively designed the chaotic difference step strategy. This strategy introduced four commonly used chaotic maps and difference step to expand the population search space to improve the situation. Moreover, opposition-based learning thought was innovatively adopted into the BSO algorithm. The thought aims to generate the opposition-based population, increase the search density, and make the algorithm out of the local optimum as soon as possible. In summary, this work proposed a global-best brain storm optimization algorithm based on the chaotic difference step and opposition-based learning (COGBSO). According to the CEC2013 benchmark test suit, 15 typical benchmark functions were selected, and multiple sets of simulation experiments were conducted on MATLAB. The COGBSO algorithm was also compared to recent competitive algorithms based on the complete CEC2018 benchmark test suit. The results demonstrate that the COGBSO outperforms BSO and other improved algorithms in solving complex optimization problems.

Possible potential spread of Anopheles stephensi, the Asian malaria vector.

BACKGROUND: Anopheles stephensi is native to Southeast Asia and the Arabian Peninsula and has emerged as an effective and invasive malaria vector. Since invasion was reported in Djibouti in 2012, the global invasion range of An. stephensi has been expanding, and its high adaptability to the environment and the ongoing development of drug resistance have created new challenges for malaria control. Climate change is an important factor affecting the distribution and transfer of species, and understanding the distribution of An. stephensi is an important part of malaria control measures, including vector control. METHODS: In this study, we collected existing distribution data for An. stephensi, and based on the SSP1-2.6 future climate data, we used the Biomod2 package in R Studio through the use of multiple different model methods such as maximum entropy models (MAXENT) and random forest (RF) in this study to map the predicted global An. stephensi climatically suitable areas. RESULTS: According to the predictions of this study, some areas where there are no current records of An. stephensi, showed significant areas of climatically suitable for An. stephensi. In addition, the global climatically suitability areas for An. stephensi are expanding with global climate change, with some areas changing from unsuitable to suitable, suggesting a greater risk of invasion of An. stephensi in these areas, with the attendant possibility of a resurgence of malaria, as has been the case in Djibouti. CONCLUSIONS: This study provides evidence for the possible invasion and expansion of An. stephensi and serves as a reference for the optimization of targeted monitoring and control strategies for this malaria vector in potential invasion risk areas.

Case report: diagnosis and treatment of advanced high-grade serous ovarian carcinoma aided by 68Ga-FAPI PET/MR scan.

High-grade serous ovarian cancer (HGSOC) is the most common type of epithelial ovarian cancer with insidious onset, rapid growth, and invasive spread. Here, we reported the diagnosis and treatment of a 53-year-old patient with a history of hysterectomy aided by the 68Ga-FAPI PET/MR scan. The patient was first presented to the local hospital with a lump on the left side of the neck with a biopsy suggesting metastatic cancer. Pelvic ultrasonography revealed two irregular masses. After admission, tumor markers, pathology consultation of the biopsy, and the 68Ga-FAPI PET/MR scan were administered. The biopsy of the lump suggested poorly differentiated adenocarcinoma and CA125 was elevated at 530.6 U/ml. The 68Ga-FAPI PET/MR scan showed several abnormal lymph nodes and two soft tissue masses with borders of dispersed restriction displaying internally uneven signals depicted by slightly elongated T1 and T2 signals within the pelvic cavity suggesting that pelvic mass could be the primary lesion. The patient received cytoreductive surgery including bilateral adnexectomy, omentectomy, and appendectomy. Post-surgical pathology suggested left and right HGSOC with left fallopian tube invasion. The patient completed six courses of first-line chemotherapy and remained progression-free for 14 months up to date. To conclude, 68Ga-FAPI PET/MR aids in primary tumor determination and tumor burden assessment and provides a guide for the management of late-stage HGSOC patients.

A Trisulfide Bond Containing Biodegradable Polymer Delivering Pt(IV) Prodrugs to Deplete Glutathione and Donate H2S to Boost Chemotherapy and Antitumor Immunity.

The clinical application of cisplatin (CisPt) is limited by its dose-dependent toxicity. To overcome this, we developed reduction-responsive nanoparticles (NP(3S)s) for the targeted delivery of a platinum(IV) (Pt(IV)) prodrug to improve efficacy and reduce the toxicity. NP(3S)s could release Pt(II) and hydrogen sulfide (H2S) upon encountering intracellular glutathione, leading to potent anticancer effects. Notably, NP(3S)s induced DNA damage and activated the STING pathway, which is a known promoter for T cell activation. Comparative RNA profiling revealed that NP(3S)s outperformed CisPt in enhancing T cell immunity, antitumor immunity, and oxidative stress pathways. In vivo experiments showed that NP(3S)s accumulated in tumors, promoting CD8+ T cell infiltration and boosting antitumor immunity. Furthermore, NP(3S)s exhibited robust in vivo anticancer efficacy while minimizing the CisPt-induced liver toxicity. Overall, the results indicate NP(3S)s hold great promise for clinical translation due to their low toxicity profile and potent anticancer activity.

Deep learning-based target tracking with X-ray images for radiotherapy: a narrative review.

Background and Objective: As one of the main treatment modalities, radiotherapy (RT) (also known as radiation therapy) plays an increasingly important role in the treatment of cancer. RT could benefit greatly from the accurate localization of the gross tumor volume and circumambient organs at risk (OARs). Modern linear accelerators (LINACs) are typically equipped with either gantry-mounted or room-mounted X-ray imaging systems, which provide possibilities for marker-less tracking with two-dimensional (2D) kV X-ray images. However, due to organ overlapping and poor soft tissue contrast, it is challenging to track the target directly and precisely with 2D kV X-ray images. With the flourishing development of deep learning in the field of image processing, it is possible to achieve real-time marker-less tracking of targets with 2D kV X-ray images in RT using advanced deep-learning frameworks. This article sought to review the current development of deep learning-based target tracking with 2D kV X-ray images and discuss the existing limitations and potential solutions. Finally, it also discusses some common challenges and potential future developments. Methods: Manual searches of the Web of Science, and PubMed, and Google Scholar were carried out to retrieve English-language articles. The keywords used in the searches included "radiotherapy, radiation therapy, motion tracking, target tracking, motion estimation, motion monitoring, X-ray images, digitally reconstructed radiographs, deep learning, convolutional neural network, and deep neural network". Only articles that met the predetermined eligibility criteria were included in the review. Ultimately, 23 articles published between March 2019 and December 2023 were included in the review. Key Content and Findings: In this article, we narratively reviewed deep learning-based target tracking with 2D kV X-ray images in RT. The existing limitations, common challenges, possible solutions, and future directions of deep learning-based target tracking were also discussed. The use of deep learning-based methods has been shown to be feasible in marker-less target tracking and real-time motion management. However, it is still quite challenging to directly locate tumor and OARs in real-time with 2D kV X-ray images, and more technical and clinical efforts are needed. Conclusions: Deep learning-based target tracking with 2D kV X-ray images is a promising method in motion management during RT. It has the potential to track the target in real time, recognize motion, reduce the extended margin, and better spare the normal tissue. However, it still has many issues that demand prompt attention, and further development before it can be put into clinical practice.