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Recently, many works have proposed various financial large language models (FinLLMs) by pre-training from scratch or fine-tuning open-sourced LLMs on financial corpora. However, existing FinLLMs exhibit unsatisfactory performance in understanding financial text when numeric variables are involved in questions. In this paper, we propose a novel LLM, called numeric-sensitive large language model (NumLLM), for Chinese finance. We first construct a financial corpus from financial textbooks which is essential for improving numeric capability of LLMs during fine-tuning. After that, we train two individual low-rank adaptation (LoRA) modules by fine-tuning on our constructed financial corpus. One module is for adapting general-purpose LLMs to financial domain, and the other module is for enhancing the ability of NumLLM to understand financial text with numeric variables. Lastly, we merge the two LoRA modules into the foundation model to obtain NumLLM for inference. Experiments on financial question-answering benchmark show that NumLLM can boost the performance of the foundation model and can achieve the best overall performance compared to all baselines, on both numeric and non-numeric questions.

Xiao J, Lin H, Zhu Y, Zhu Y, Chen L. Onco Targets Ther. 2016;9:5181–5193. The Editor and Publisher of OncoTargets and Therapy wish to retract the published article. It came to our attention that several figures within the paper appeared to be duplicated, specifically:● Figure 4A panels Noninfected and BLS-Lv-vector appear to be duplicated with images from Figure 3B panels Control and NC from Wang et al: MicroRNA-200b inhibits pituitary tumor cell proliferation and invasion by targeting PKCα (https://doi. org/10.3892/etm.2017.4681).● Figure 4A panel BLS-Lv-miR126 appears to be duplicated with an image from Figure 3B panel Mimics from Wang et al: MicroRNA-200b inhibits pituitary tumor cell proliferation and invasion by targeting PKCα(https://doi.org/10.3892/etm.2017.4681).● Figure 8A, the two right panels appear to be duplicated.● Figure 8B, the two left panels and the far right panel appear to be duplicated.We attempted to contact the authors of this article but despite multiple attempts received no response. The Editor has determined the findings of the study are no longer valid and requested for the article to be retracted. Our decision-making was informed by our policy on publishing ethics and integrity and the COPE guidelines on retraction. The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as “Retracted”. This retraction relates to this paper

BackgroundThe aim of this study was to compare intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) parameters such as standard apparent diffusion coefficient (ADCstandard), pure diffusion coefficient (Dslow), pseudodiffusion coefficient (Dfast) and perfusion fraction (ƒ) for differentiating pancreatic ductal adenocarcinoma (PDAC) with different pathological grades.MethodsInstitutional Review Board of our hospital approved this study protocol. Subjects comprised 38 PDACs confirmed by pathology. Pancreatic multiple b values DWI with 15 b values of 0, 10, 20, 40, 60, 80, 100, 150, 200, 400, 800, 1,000, 1200, 1,500, and 2,000 s/mm2 was performed using GE Discovery MR750 3.0T scanner. ADCstandard, Dslow, Dfast and ƒ values of all PDACs were calculated using mono- and bi-exponential models. Parameters of well/moderately differentiated and poorly differentiated PDAC were compared using Independent Sample t-test. P values <0.05 were considered significant.ResultsMean Dslow value of well/moderately differentiated PDAC was significantly lower than that of poorly differentiated PDAC (0.540×10-3vs. 0.676×10-3 mm2/s, P<0.001). Mean ƒ value of well/moderately differentiated PDAC was significantly higher than that of poorly differentiated PDAC (60.3% vs. 38.4%, P<0.001). The area under curve value of ƒ in differentiating well/moderately differentiated PDAC from poorly differentiated PDAC was slightly higher than that of Dslow (0.894>0.865). When the Dslow value was less than or equal to 0.599×10-3 mm2/s, the sensitivity and specificity were 100% and 84.6% respectively. When ƒ value was greater than 49.6%, the sensitivity and specificity were 92.0% and 84.6% respectively.ConclusionsDslow and ƒ derived from IVIM-DWI model can be used to distinguish well/moderately differentiated PDAC from poorly differentiated PDAC. And to serve this purpose, Dslow and ƒ have high diagnostic performance. IVIM-DWI is a promising and non-invasive tool for predicting patholog

This paper has been retracted.Jun Xiao, 1 Huan-Yi Lin, 2 Yuan-Yuan Zhu, 3 Yu-Ping Zhu, 1 Ling-Wu Chen 2 1Department of Urology, Anhui Provincial Hospital, Anhui Medical University, Hefei, 2Department of Urology, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 3Clinical Laboratory, Anhui Provincial Hospital, Anhui Medical University, Hefei, People’s Republic of China Objective: To assess whether microRNA-126 (miR-126) targets phosphatidylinositol 3-kinase regulatory subunit beta (PIK3R2) and to determine the potential roles of miR-126 in regulating proliferation and invasion via the PIK3R2-mediated phosphatidylinositol 3 kinase (PI3K)-protein kinase B (Akt) signaling pathway in the human bladder BLS cell line. Materials and methods: A recombinant lentivirus (Lv) vector expressing miR-216 (Lv-miR-126) was successfully constructed, and Lv-miR-126 and Lv vector were transfected into the BLS cell line. A direct regulatory relationship between miR-126 and the PIK3R 2 gene was demonstrated by luciferase reporter assays. To determine whether PIK3R2 directly participates in the miR-126-induced effects in BLS cells, anti-miR-126 and a PIK3R2 small interfering RNA (siRNA) were transfected into the BLS cells. Quantitative real-time polymerase chain reaction was used to measure miR-126 and PIK3R2 expressions. 5-Ethynyl-2'-deoxyuridine and colony formation assays to assess cell proliferation, flow cytometry for cell apoptosis and cell cycle analysis, Transwell assays for cell migration and invasion, and Western blots for PIK3R2, PI3K, phosphorylated PI3K (p-PI3K), Akt, and phosphorylated Akt (p-Akt) protein expressions were performed. Results: Lv-miR-126 significantly enhanced the relative expression of miR-126 in the BLS cells after infection (P< 0.0001). MiR-126 overexpression inhibited the proliferation, cloning, migration, and invasion of BLS cells, promoted cell apoptosis, and induced S phase arrest (all P< 0.05). PIK3R2, p-PI3K

Yang Guo,1 Zhuoli Zhang,1 Dong-Hyun Kim,1,5 Weiguo Li,1 Jodi Nicolai,1 Daniel Procissi,1 Yi Huan,2 Guohong Han,3 Reed A Omary,1,4,5 Andrew C Larson1,4,5 1Department of Radiology, Northwestern University, Chicago, IL, USA; 2Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, People's Republic of China; 3Department of Digestive Interventional Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, People's Republic of China; 4Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA; 5Robert H Lurie Comprehensive Cancer Center, Chicago, IL, USA Purpose: Photothermal ablation is a minimally invasive approach, which typically involves delivery of photothermal sensitizers to targeted tissues. The purpose of our study was to demonstrate that gold nanoparticles are phagocytosed by pancreatic cancer cells, thus permitting magnetic resonance imaging (MRI) of sensitizer delivery and photothermal ablation. Patients and methods: Iron-oxide core/gold-shell nanoparticles (GoldMag®, 30 nm diameter; Xi'an GoldMag Biotechnology Co, Xi'an, People's Republic of China) were used. In a 96-well plate, 3 × 104 PANC-1 (human pancreatic cancer cell line) cells were placed. GoldMag (0, 25, or 50 µg/mL) was added to each well and 24 hours allowed for cellular uptake. Samples were then divided into two groups: one treated with photothermal ablation (7.9 W/cm2) for 5 minutes, the other not treated. Photothermal ablation was performed using laser system (BWF5; B&W Tek, Inc, Newark, DE, USA). Intraprocedural temperature changes were measured using a fiber optic temperature probe (FTP-LN2; Photon Control Inc, Burnaby, BC, Canada). After 24 hours, the remaining number of viable cells was counted using trypan blue staining; cell proliferation percentage was calculated based on the total number of viable cells after treatment compared with c

Yang Guo,1 Zhuoli Zhang,1 Dong-Hyun Kim,1,5 Weiguo Li,1 Jodi Nicolai,1 Daniel Procissi,1 Yi Huan,2 Guohong Han,3 Reed A Omary,1,4,5 Andrew C Larson1,4,5 1Department of Radiology, Northwestern University, Chicago, IL, USA; 2Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, People's Republic of China; 3Department of Digestive Interventional Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, People's Republic of China; 4Department of Biomedical Engineering, Northwestern University, Chicago, IL, USA; 5Robert H Lurie Comprehensive Cancer Center, Chicago, IL, USA Purpose: Photothermal ablation is a minimally invasive approach, which typically involves delivery of photothermal sensitizers to targeted tissues. The purpose of our study was to demonstrate that gold nanoparticles are phagocytosed by pancreatic cancer cells, thus permitting magnetic resonance imaging (MRI) of sensitizer delivery and photothermal ablation. Patients and methods: Iron-oxide core/gold-shell nanoparticles (GoldMag®, 30 nm diameter; Xi'an GoldMag Biotechnology Co, Xi'an, People's Republic of China) were used. In a 96-well plate, 3 × 104 PANC-1 (human pancreatic cancer cell line) cells were placed. GoldMag (0, 25, or 50 µg/mL) was added to each well and 24 hours allowed for cellular uptake. Samples were then divided into two groups: one treated with photothermal ablation (7.9 W/cm2) for 5 minutes, the other not treated. Photothermal ablation was performed using laser system (BWF5; B&W Tek, Inc, Newark, DE, USA). Intraprocedural temperature changes were measured using a fiber optic temperature probe (FTP-LN2; Photon Control Inc, Burnaby, BC, Canada). After 24 hours, the remaining number of viable cells was counted using trypan blue staining; cell proliferation percentage was calculated based on the total number of viable cells after treatment compared with c