Regulation of candidalysin underlies Candida albicans persistence in intravascular catheters by modulating NETosis.

Candida albicans is a leading cause of intravascular catheter-related infections. The capacity for biofilm formation has been proposed to contribute to the persistence of this fungal pathogen on catheter surfaces. While efforts have been devoted to identifying microbial factors that modulate C. albicans biofilm formation in vitro, our understanding of the host factors that may shape C. albicans persistence in intravascular catheters is lacking. Here, we used multiphoton microscopy to characterize biofilms in intravascular catheters removed from candidiasis patients. We demonstrated that, NETosis, a type of neutrophil cell death with antimicrobial activity, was implicated in the interaction of immune cells with C. albicans in the catheters. The catheter isolates exhibited reduced filamentation and candidalysin gene expression, specifically in the total parenteral nutrition culture environment. Furthermore, we showed that the ablation of candidalysin expression in C. albicans reduced NETosis and conferred resistance to neutrophil-mediated fungal biofilm elimination. Our findings illustrate the role of neutrophil NETosis in modulating C. albicans biofilm persistence in an intravascular catheter, highlighting that C. albicans can benefit from reduced virulence expression to promote its persistence in an intravascular catheter.

Premature Progesterone Rise Is Associated with Higher Cumulative Live Birth Rate with Freeze-All Strategy.

Background/Objectives: This paper undertakes an investigation into the implications of premature progesterone rise (PPR) on pregnancy outcomes in freeze-all strategy cycles. Methods: A retrospective cohort study encompassing 675 IVF/ICSI cycles using a freeze-all strategy was enrolled. The cycles were categorized into two groups based on serum progesterone levels at the time of hCG administration: 526 cycles had levels below 1.5 ng/mL, while 149 cycles had levels equal to or above 1.5 ng/mL. Results: The findings revealed a significantly higher number of mature follicles and retrieved oocytes in patients with PPR across all AMH categories. Multiple analyses revealed factors influencing PPR, including the duration of induction and the number of retrieved oocytes. Within the same oocyte retrieval number group, patients with PPR demonstrated non-inferior pregnancy outcomes compared to non-PPR patients. Upon adjustment for age, AMH, and total follicle-stimulating hormone (FSH) dosage, PPR maintained a positive correlation with the cumulative live birth rate (LBR). Conclusions: The study showed that PPR correlates with an increase in retrieved oocytes while maintaining similar embryo quality and oocyte retrieval rates and results in a higher cumulative LBR.

STEAP2 promotes hepatocellular carcinoma progression via increased copper levels and stress-activated MAP kinase activity.

Six Transmembrane Epithelial Antigen of Prostate 2 (STEAP2) belongs to a family of metalloreductases, which indirectly aid in uptake of iron and copper ions. Its role in hepatocellular carcinoma (HCC) remains to be characterized. Here, we report that STEAP2 expression was upregulated in HCC tumors compared with paired adjacent non-tumor tissues by RNA sequencing, RT-qPCR, Western blotting, and immunostaining. Public HCC datasets demonstrated upregulated STEAP2 expression in HCC and positive association with tumor grade. Transient and stable knockdown (KD) of STEAP2 in HCC cell lines abrogated their malignant phenotypes in vitro and in vivo, while STEAP2 overexpression showed opposite effects. STEAP2 KD in HCC cells led to significant alteration of genes associated with extracellular matrix organization, cell adhesion/chemotaxis, negative enrichment of an invasiveness signature gene set, and inhibition of cell migration/invasion. STEAP2 KD reduced intracellular copper levels and activation of stress-activated MAP kinases including p38 and JNK. Treatment with copper rescued the reduced HCC cell migration due to STEAP2 KD and activated p38 and JNK. Furthermore, treatment with p38 or JNK inhibitors significantly inhibited copper-mediated cell migration. Thus, STEAP2 plays a malignant-promoting role in HCC cells by driving migration/invasion via increased copper levels and MAP kinase activities. Our study uncovered a novel molecular mechanism contributing to HCC malignancy and a potential therapeutic target for HCC treatment.

Integrative multi-omics characterization of hepatocellular carcinoma in Hispanic patients.

Background: The incidence and mortality rates of hepatocellular carcinoma (HCC) among Hispanics in the United States are much higher than those of non-Hispanic whites. We conducted comprehensive multi-omics analyses to understand molecular alterations in HCC among Hispanic patients. Methods: Paired tumor and adjacent non-tumor samples were collected from 31 Hispanic HCC in South Texas (STX-Hispanic) for genomic, transcriptomic, proteomic, and metabolomic profiling. Additionally, serum lipids were profiled in 40 Hispanic and non-Hispanic patients with or without clinically diagnosed HCC. Results: Exome sequencing revealed high mutation frequencies of AXIN2 and CTNNB1 in STX Hispanic HCCs, suggesting a predominant activation of the Wnt/ß-catenin pathway. The TERT promoter mutation frequency was also remarkably high in the Hispanic cohort. Cell cycles and liver functions were identified as positively- and negatively-enriched, respectively, with gene set enrichment analysis. Gene sets representing specific liver metabolic pathways were associated with dysregulation of corresponding metabolites. Negative enrichment of liver adipogenesis and lipid metabolism corroborated with a significant reduction in most lipids in the serum samples of HCC patients. Two HCC subtypes from our Hispanic cohort were identified and validated with the TCGA liver cancer cohort. The subtype with better overall survival showed higher activity of immune and angiogenesis signatures, and lower activity of liver function-related gene signatures. It also had higher levels of immune checkpoint and immune exhaustion markers. Conclusions: Our study revealed some specific molecular features of Hispanic HCC and potential biomarkers for therapeutic management of HCC and provides a unique resource for studying Hispanic HCC.

A Metastatic Cancer Expression Generator (MetGen): A Generative Contrastive Learning Framework for Metastatic Cancer Generation.

Despite significant advances in tumor biology and clinical therapeutics, metastasis remains the primary cause of cancer-related deaths. While RNA-seq technology has been used extensively to study metastatic cancer characteristics, challenges persist in acquiring adequate transcriptomic data. To overcome this challenge, we propose MetGen, a generative contrastive learning tool based on a deep learning model. MetGen generates synthetic metastatic cancer expression profiles using primary cancer and normal tissue expression data. Our results demonstrate that MetGen generates comparable samples to actual metastatic cancer samples, and the cancer and tissue classification yields performance rates of 99.8 ± 0.2% and 95.0 ± 2.3%, respectively. A benchmark analysis suggests that the proposed model outperforms traditional generative models such as the variational autoencoder. In metastatic subtype classification, our generated samples show 97.6% predicting power compared to true metastatic samples. Additionally, we demonstrate MetGen's interpretability using metastatic prostate cancer and metastatic breast cancer. MetGen has learned highly relevant signatures in cancer, tissue, and tumor microenvironments, such as immune responses and the metastasis process, which can potentially foster a more comprehensive understanding of metastatic cancer biology. The development of MetGen represents a significant step toward the study of metastatic cancer biology by providing a generative model that identifies candidate therapeutic targets for the treatment of metastatic cancer.

Sustainability of exercise-induced benefits on circulating MicroRNAs and physical fitness in community-dwelling older adults: a randomized controlled trial with follow up.

BACKGROUND: Circulating miRNAs (c-miR) have been shown to be potential biomarkers in sarcopenia, but the miRNAs response to aerobic exercise in older people remains inconclusive. We sought to examine the exercise benefits on physical fitness and miRNAs, and to explore the mediating effect of miRNAs on training-induced fitness changes. METHODS: This controlled trial recruited 58 community-dwelling older adults and randomized them into exercise group (EX) and control group (CON). EX received 8-week supervised moderate intensity cycling training 3x/week. C-miR expression (c-miR-21, c-miR-126, c-miR-146a, c-miR-222), physical fitness (body composition, cardiorespiratory fitness, muscular fitness) and physical activity level (PAL, measured as in daily step counts) were evaluated at baseline, post-training, and post-16-week follow-up. The mediating effect of miRNA expression onto exercise-induced physical fitness change was determined by causal mediation analysis (CMA). RESULTS: Exercise significantly improved body fat and cardiorespiratory fitness in older people while maintaining muscle mass and strength, and augmented expression of c-miR-126, c-miR-146a, and c-miR-222 for up to 16 weeks post-training. Notably, older people in EX had substantially higher daily step counts than CON throughout the study even after the active training period. However, CMA revealed no significant indirect effect but a potential mediating effect of c-miR-21, but not the rest, onto the body composition, cardiorespiratory fitness, and lower limb strength. CONCLUSION: An eight-week supervised MICT program promoted a higher level of physical activity up to 16 weeks post-training, which induces better cardiorespiratory fitness and resists decline in muscular measures. C-miRNA, especially c-miR-21, potentially mediates the training effect upon fitness.

Chloride- and Hydrosulfide-Bound 2Fe Complexes as Models of the Oxygen-Stable State of [FeFe] Hydrogenase.

[FeFe] hydrogenases demonstrate remarkable catalytic efficiency in hydrogen evolution and oxidation processes. However, susceptibility of these enzymes to oxygen-induced degradation impedes their practical deployment in hydrogen-production devices and fuel cells. Recent investigations into the oxygen-stable (Hinact) state of the H-cluster revealed its inherent capacity to resist oxygen degradation. Herein, we present findings on Cl- and SH-bound [2Fe-2S] complexes, bearing relevance to the oxygen-stable state within a biological context. A characteristic attribute of these complexes is the terminal Cl-/SH- ligation to the iron center bearing the CO bridge. Structural analysis of the t-Cl demonstrates a striking resemblance to the Hinact state of DdHydAB and CbA5H. The t-Cl/t-SH exhibit reversible oxidation, with both redox species, electronically, being the first biomimetic analogs to the Htrans and Hinact states. These complexes exhibit notable resistance against oxygen-induced decomposition, supporting the potential oxygen-resistant nature of the Htrans and Hinact states. The swift reductive release of the Cl-/SH-group demonstrates its labile and kinetically controlled binding. The findings garnered from these investigations offer valuable insights into properties of the enzymatic O2-stable state, and key factors governing deactivation and reactivation conversion. This work contributes to the advancement of bio-inspired molecular catalysts and the integration of enzymes and artificial catalysts into H2-evolution devices and fuel-cell applications.

Impact of metformin on neocortical development during pregnancy: Involvement of ERK and p35/CDK5 pathways.

Metformin, the most commonly prescribed drug for the treatment of diabetes, is increasingly used during pregnancy to address various disorders such as diabetes, obesity, preeclampsia, and metabolic diseases. However, its impact on neocortex development remains unclear. Here, we investigated the direct effects of metformin on neocortex development, focusing on ERK and p35/CDK5 regulation. Using a pregnant rat model, we found that metformin treatment during pregnancy induces small for gestational age (SGA) and reduces relative cortical thickness in embryos and neonates. Additionally, we discovered that metformin inhibits neural progenitor cell proliferation in the sub-ventricular zone (SVZ)/ventricular zone (VZ) of the developing neocortex, a process possibly mediated by ERK inactivation. Furthermore, metformin induces neuronal apoptosis in the SVZ/VZ area of the developing neocortex. Moreover, metformin retards neuronal migration, cortical lamination, and differentiation, potentially through p35/CDK5 inhibition in the developing neocortex. Remarkably, compensating for p35 through in utero electroporation partially rescues metformin-impaired neuronal migration and development. In summary, our study reveals that metformin disrupts neocortex development by inhibiting neuronal progenitor proliferation, neuronal migration, cortical layering, and cortical neuron maturation, likely via ERK and p35/CDK5 inhibition. Consequently, our findings advocate for caution in metformin usage during pregnancy, given its potential adverse effects on fetal brain development.

Fusion of memristor and digital compute-in-memory processing for energy-efficient edge computing.

Artificial intelligence (AI) edge devices prefer employing high-capacity nonvolatile compute-in-memory (CIM) to achieve high energy efficiency and rapid wakeup-to-response with sufficient accuracy. Most previous works are based on either memristor-based CIMs, which suffer from accuracy loss and do not support training as a result of limited endurance, or digital static random-access memory (SRAM)-based CIMs, which suffer from large area requirements and volatile storage. We report an AI edge processor that uses a memristor-SRAM CIM-fusion scheme to simultaneously exploit the high accuracy of the digital SRAM CIM and the high energy-efficiency and storage density of the resistive random-access memory memristor CIM. This also enables adaptive local training to accommodate personalized characterization and user environment. The fusion processor achieved high CIM capacity, short wakeup-to-response latency (392 microseconds), high peak energy efficiency (77.64 teraoperations per second per watt), and robust accuracy (<0.5% accuracy loss). This work demonstrates that memristor technology has moved beyond in-lab development stages and now has manufacturability for AI edge processors.

Predicting drug response through tumor deconvolution by cancer cell lines.

Large-scale cancer drug sensitivity data have become available for a collection of cancer cell lines, but only limited drug response data from patients are available. Bridging the gap in pharmacogenomics knowledge between in vitro and in vivo datasets remains challenging. In this study, we trained a deep learning model, Scaden-CA, for deconvoluting tumor data into proportions of cancer-type-specific cell lines. Then, we developed a drug response prediction method using the deconvoluted proportions and the drug sensitivity data from cell lines. The Scaden-CA model showed excellent performance in terms of concordance correlation coefficients (>0.9 for model testing) and the correctly deconvoluted rate (>70% across most cancers) for model validation using Cancer Cell Line Encyclopedia (CCLE) bulk RNA data. We applied the model to tumors in The Cancer Genome Atlas (TCGA) dataset and examined associations between predicted cell viability and mutation status or gene expression levels to understand underlying mechanisms of potential value for drug repurposing.

Association between chronic prostatitis and the subsequent benign prostatic hyperplasia: a population-based national cohort study.

PURPOSE: To explore the association between chronic prostatitis (CP) and the subsequent development of benign prostatic hyperplasia (BPH). METHODS: Data analyzed were medical claims of Taiwan's National Health Insurance program. From 2010 to 2017, 3571 patients ≧20 years with CP diagnosed by certified urologists were enrolled. Patients with past BPH diagnosis and diagnosis of prostate cancer, inguinal hernia, interstitial cystitis, and urethritis in the past and within one year after the first CP diagnosis were excluded. Age-matched controls were randomly selected from all non-CP individuals of the same exclusion criteria in the study period with a CP/non-CP ratio of 1:4. The follow-up was made from the first CP diagnosis to death or the end of 2018. The endpoint was the newly diagnosed BPH. Cox proportional hazard regression model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of BPH in association with CP. RESULTS: Over a maximum of 8 years of follow-up, 287 (8.03%) and 258 (0.43%) BPH events were noted for the CP and non-CP group, respectively, representing a covariate adjusted HR (aHR) of 4.30 (95% CI, 3.61-5.13). Younger patients tended to suffer from higher aHRs, especially those aged 20-39 years (aHR: 11.45, 95% CI, 5.12-25.64). CONCLUSION: The Taiwan national health database indicated that CP patients had a significantly higher risk of developing BPH later than non-CP patients. Interestingly, the younger the CP is diagnosed (under 40), the greater the risk.

An automatic system for recognizing fly courtship patterns via an image processing method.

Fruit fly courtship behaviors composed of a series of actions have always been an important model for behavioral research. While most related studies have focused only on total courtship behaviors, specific courtship elements have often been underestimated. Identifying these courtship element details is extremely labor intensive and would largely benefit from an automatic recognition system. To address this issue, in this study, we established a vision-based fly courtship behavior recognition system. The system based on the proposed image processing methods can precisely distinguish body parts such as the head, thorax, and abdomen and automatically recognize specific courtship elements, including orientation, singing, attempted copulation, copulation and tapping, which was not detectable in previous studies. This system, which has high identity tracking accuracy (99.99%) and high behavioral element recognition rates (> 97.35%), can ensure correct identification even when flies completely overlap. Using this newly developed system, we investigated the total courtship time, and proportion, and transition of courtship elements in flies across different ages and found that male flies adjusted their courtship strategy in response to their physical condition. We also identified differences in courtship patterns between males with and without successful copulation. Our study therefore demonstrated how image processing methods can be applied to automatically recognize complex animal behaviors. The newly developed system will largely help us investigate the details of fly courtship in future research.

MyD88 exacerbates inflammation-induced bone loss by modulating dynamic equilibrium between Th17/Treg cells and subgingival microbiota dysbiosis.

BACKGROUND: This study aimed to investigate the contribution of myeloid differentiation primary-response gene 88 (MyD88) on the differentiation of T helper type 17 (Th17) and regulatory T (Treg) cells and the emerging subgingival microbiota dysbiosis in Porphyromonas gingivalis-induced experimental periodontitis. METHODS: Alveolar bone loss, infiltrated inflammatory cells, immunostained cells for tartrate-resistant acid phosphatase (TRAP), the receptor activator of nuclear factor-kB ligand (RANKL), and osteoprotegerin (OPG) were quantified by microcomputerized tomography and histological staining between age- and sex-matched homozygous littermates (wild-type [WT, Myd88+/+] and Myd88-/- on C57BL/6 background). The frequencies of Th17 and Treg cells in cervical lymph nodes (CLNs) and spleen were determined by flow cytometry. Cytokine expression in gingival tissues, CLNs, and spleens were studied by quantitative polymerase chain reaction (qPCR). Analysis of the composition of the subgingival microbiome and functional annotation of prokaryotic taxa (FAPROTAX) analysis were performed. RESULTS: P. gingivalis-infected Myd88-/- mice showed alleviated bone loss, TRAP+ osteoclasts, and RANKL/OPG ratio compared to WT mice. A significantly higher percentage of Foxp3+CD4+ T cells in infected Myd88-/- CLNs and a higher frequency of RORγt+CD4+ T cells in infected WT mice was noted. Increased IL-10 and IL-17a expressions in gingival tissue at D14-D28 then declined in WT mice, whereas an opposite pattern was observed in Myd88-/- mice. The Myd88-/- mice exhibited characteristic increases in gram-positive species and species having probiotic properties, while gram-negative, anaerobic species were noted in WT mice. FAPROTAX analysis revealed increased aerobic chemoheterotrophy in Myd88-/- mice, whereas anaerobic chemoheterotrophy was noted in WT mice after P. gingivalis infection. CONCLUSIONS: MyD88 plays an important role in inflammation-induced bone loss by modulating the dynamic equilibrium between Th17/Treg cells and dysbiosis in P. gingivalis-induced experimental periodontitis.

shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning.

Advancing precision oncology requires accurate prediction of treatment response and accessible prediction models. To this end, we present shinyDeepDR, a user-friendly implementation of our innovative deep learning model, DeepDR, for predicting anti-cancer drug sensitivity. The web tool makes DeepDR more accessible to researchers without extensive programming experience. Using shinyDeepDR, users can upload mutation and/or gene expression data from a cancer sample (cell line or tumor) and perform two main functions: "Find Drug," which predicts the sample's response to 265 approved and investigational anti-cancer compounds, and "Find Sample," which searches for cell lines in the Cancer Cell Line Encyclopedia (CCLE) and tumors in The Cancer Genome Atlas (TCGA) with genomics profiles similar to those of the query sample to study potential effective treatments. shinyDeepDR provides an interactive interface to interpret prediction results and to investigate individual compounds. In conclusion, shinyDeepDR is an intuitive and free-to-use web tool for in silico anti-cancer drug screening.

reguloGPT: Harnessing GPT for Knowledge Graph Construction of Molecular Regulatory Pathways.

Motivation: Molecular Regulatory Pathways (MRPs) are crucial for understanding biological functions. Knowledge Graphs (KGs) have become vital in organizing and analyzing MRPs, providing structured representations of complex biological interactions. Current tools for mining KGs from biomedical literature are inadequate in capturing complex, hierarchical relationships and contextual information about MRPs. Large Language Models (LLMs) like GPT-4 offer a promising solution, with advanced capabilities to decipher the intricate nuances of language. However, their potential for end-to-end KG construction, particularly for MRPs, remains largely unexplored. Results: We present reguloGPT, a novel GPT-4 based in-context learning prompt, designed for the end-to-end joint name entity recognition, N-ary relationship extraction, and context predictions from a sentence that describes regulatory interactions with MRPs. Our reguloGPT approach introduces a context-aware relational graph that effectively embodies the hierarchical structure of MRPs and resolves semantic inconsistencies by embedding context directly within relational edges. We created a benchmark dataset including 400 annotated PubMed titles on N6-methyladenosine (m6A) regulations. Rigorous evaluation of reguloGPT on the benchmark dataset demonstrated marked improvement over existing algorithms. We further developed a novel G-Eval scheme, leveraging GPT-4 for annotation-free performance evaluation and demonstrated its agreement with traditional annotation-based evaluations. Utilizing reguloGPT predictions on m6A-related titles, we constructed the m6A-KG and demonstrated its utility in elucidating m6A's regulatory mechanisms in cancer phenotypes across various cancers. These results underscore reguloGPT's transformative potential for extracting biological knowledge from the literature. Availability and implementation: The source code of reguloGPT, the m6A title and benchmark datasets, and m6A-KG are available at: https://github.com/Huang-AI4Medicine-Lab/reguloGPT.

Clinical and biomarker results from a phase II trial of combined cabozantinib and durvalumab in patients with chemotherapy-refractory colorectal cancer (CRC): CAMILLA CRC cohort.

CAMILLA is a basket trial (NCT03539822) evaluating cabozantinib plus the ICI durvalumab in chemorefractory gastrointestinal cancer. Herein, are the phase II colorectal cohort results. 29 patients were evaluable. 100% had confirmed pMMR/MSS tumors. Primary endpoint was met with ORR of 27.6% (95% CI 12.7-47.2%). Secondary endpoints of 4-month PFS rate was 44.83% (95% CI 26.5-64.3%); and median OS was 9.1 months (95% CI 5.8-20.2). Grade≥3 TRAE occurred in 39%. In post-hoc analysis of patients with RAS wild type tumors, ORR was 50% and median PFS and OS were 6.3 and 21.5 months respectively. Exploratory spatial transcriptomic profiling of pretreatment tumors showed upregulation of VEGF and MET signaling, increased extracellular matrix activity and preexisting anti-tumor immune responses coexisting with immune suppressive features like T cell migration barriers in responders versus non-responders. Cabozantinib plus durvalumab demonstrated anti-tumor activity, manageable toxicity, and have led to the activation of the phase III STELLAR-303 trial.

Systems approach for congruence and selection of cancer models towards precision medicine.

Cancer models are instrumental as a substitute for human studies and to expedite basic, translational, and clinical cancer research. For a given cancer type, a wide selection of models, such as cell lines, patient-derived xenografts, organoids and genetically modified murine models, are often available to researchers. However, how to quantify their congruence to human tumors and to select the most appropriate cancer model is a largely unsolved issue. Here, we present Congruence Analysis and Selection of CAncer Models (CASCAM), a statistical and machine learning framework for authenticating and selecting the most representative cancer models in a pathway-specific manner using transcriptomic data. CASCAM provides harmonization between human tumor and cancer model omics data, systematic congruence quantification, and pathway-based topological visualization to determine the most appropriate cancer model selection. The systems approach is presented using invasive lobular breast carcinoma (ILC) subtype and suggesting CAMA1 followed by UACC3133 as the most representative cell lines for ILC research. Two additional case studies for triple negative breast cancer (TNBC) and patient-derived xenograft/organoid (PDX/PDO) are further investigated. CASCAM is generalizable to any cancer subtype and will authenticate cancer models for faithful non-human preclinical research towards precision medicine.

[Using Multiple Strategies to Improve the Accuracy of Hemodynamic Monitoring].

BACKGROUND & PROBLEMS: Hemodynamic monitoring is an important part of nursing care in the intensive care unit. Recent advances in medical technology and the diversification of intensive care equipment have increased the variety of instruments used in clinical hemodynamic monitoring. Many nurses who use new hemodynamic monitors are not familiar with instrument care, resulting in patient safety incidents caused by nurses not identifying warnings of hemodynamic data change and notifying doctors to provide treatment. The accuracy of hemodynamic monitoring care in our ward of 74.0% motivated this improvement project. PURPOSE: To improve the accuracy of hemodynamic monitoring care to 98.3%. RESOLUTION: Conduct educational training and plan professional education; establish an audit system to regularly monitor the accuracy of nursing care; provide tips to make the operation manual easier to read and understand; establish mobile learning to make learning immediate and more accessible; hold instrument operation practice sessions to improve nursing staff proficiency; monitor and upload data to the hospital information system. RESULTS: After the improvement project, the accuracy of hemodynamic monitoring care increased to 98.7%. CONCLUSIONS: The impact achieved met expectations, and the improvement project will be extended to other intensive care units in the hospital. Our nurses are now more familiar with the operation methods and the significance of monitoring values and interpretation of data. Also, when a value changes or becomes abnormal, they immediately notify the doctor for further evaluation and interventions to improve patient safety.

Dinaciclib inhibits the growth of acute myeloid leukemia cells through either cell cycle-related or ERK1/STAT3/MYC pathways.

Although immature differentiation and uncontrolled proliferation of hematopoietic stem cells are thought to be the primary mechanisms of acute myeloid leukemia (AML), the pathophysiology in most cases remains unclear. Dinaciclib, a selective small molecule targeting multiple cyclin-dependent kinases (CDKs), is currently being evaluated in oncological clinical trials. Despite the proven anticancer potential of dinaciclib, the differential molecular mechanisms by which it inhibits the growth of different AML cell lines remain unclear. In the current study, we treated HL-60 and KG-1 AML cell lines with dinaciclib and investigated the potential mechanisms of dinaciclib-induced AML cell growth inhibition using flow cytometry and western blotting assays. Data from HL-60 and KG-1 AML cells were validated using human primary AML cells. The results showed that the growth inhibitory effect of dinaciclib was more sensitive in HL-60 cells (IC50: 8.46 nM) than in KG-1 cells (IC50: 14.37 nM). The protein decline in Cyclin A/B and CDK1 and cell cycle arrest in the G2/M phase were more profound in HL-60 cells, corresponding to its growth inhibition. Although the growth inhibition of KG-1 cells by dinaciclib was still pronounced, the cell cycle-associated proteins were relatively insensitive. In addition to cell cycle regulation, the activation/expression of ERK1/STAT3/MYC signaling was significantly reduced by dinaciclib in KG-1 cells compared with that in HL-60 cells. Regarding the results of primary AML cells, we observed ERK1/STAT3/MYC inhibition and cell cycle regulation in different patients. These findings suggest that the cell cycle-associated and ERK1/STAT3/MYC signaling pathways might be two distinct mechanisms by which dinaciclib inhibits AML cells, which could facilitate the development of combination therapy for AML in the future.

A direct healthcare cost analysis of recombinant LH versus hMG supplementation on FSH during controlled ovarian hyperstimulation in the GnRH-antagonist protocol.

PURPOSE: We have previously published a retrospective matched-case control study comparing the effect of recombinant LH (r-hLH) versus highly purified human menopausal gonadotropin (hMG) supplementation on the follicle-stimulating hormone (FSH) during controlled ovarian hyperstimulation (COH) in the GnRH-antagonist protocol. The result from that study showed that the cumulative live birth rate (CLBR) was significantly higher in the r-hLH group (53% vs. 64%, p = 0.02). In this study, we aim to do a cost analysis between these two groups based on our previous study. METHODS: The analysis consisted of 425 IVF and ICSI cycles in our previous study. There were 259 cycles in the r-hFSH + hMG group and 166 cycles in the r-hFSH + r-hLH group. The total cost related to the treatment of each patient was recorded. Probabilistic sensitivity analysis (PSA) and a cost-effectiveness acceptability curve (CEAC) were performed and created. RESULTS: The total treatment cost per patient was significantly higher in the r-hFSH + r-hLH group than in the r-hFSH + hMG group ($4550 ± 798.86 vs. $4290 ± 734.6, p = 0.003). However, the mean cost per live birth in the r-hFSH + hMG group was higher at $8052, vs. $7059 in the r-hFSH + r-hLH group. The CEAC showed that treatment with hFSH + r-hLH proved to be more cost-effective than treatment with r-hFSH + hMG. Willingness-to-pay was evident when considering a hypothetical threshold of $18,513, with the r-hFSH + r-hLH group exhibiting a 99% probability of being considered cost-effective. CONCLUSION: The cost analysis showed that recombinant LH is more cost-effective than hMG supplementation on r-hFSH during COH in the GnRH-antagonist protocol.