We present two approaches to forecasting parameters in the SABR model. The first approach is the vector autoregressive moving-average model (VARMA) for the time series of the in-sample calibrated parameters, and the second is based on machine learning techniques called epsilon-support vector regression (ε-SVR). Using daily data of S&P 500 ETF option prices from January 1, 2014, to December 31, 2018, we first calibrate the daily values of the model parameters from the training sample, then conduct out-of-sample forecasting of parameters and pricing of options. Both approaches produce good fits between the forecasted and calibrated parameters for out-of-sample dates. A comparison study shows that using forecasted parameters as inputs, the SABR model generates better pricing results than assuming constant parameters or using lag parameters. We also discuss the market conditions under which one approach outperforms the other.

Alternative bio actively chemicals may be found in natural goods and traditional herb medications, but only a few plant-information formulations have been rigorously studied and verified for their potential as medicinal therapies. The study of plant-derived elements' immunomodulation capabilities and their ability as provoke the immune system as combat various elemental disorders like cancer is, nonetheless, a promising area in current therapeutics information on plant-derived chemicals. This research showed how network pharmacology may be applied as define and validate natural individual elements or more complicated preparations as prospective cancer therapies information on their various aim capabilities in this research. We give a summary of the present state of understanding on network pharmacology, with a particular emphasis on various technical methods and their implications for cancer treatment.

Lung cancer is the leading cause of cancer-related deaths. Non-small cell lung cancer (NSCLC) accounts for about 85% of all lung cancers, and lung adenocarcinoma is the most common NSCLC. Most patients with lung cancer eventually lead to local and metastatic recurrence, including many patients who have completely removed the primary tumor during surgery and have no noticeable metastasis. There are two different deoxynucleotide triphosphate (dNTP) libraries in eukaryotic cells. The de novo synthesis of dNTPs in the cytoplasm is coordinated with the cell cycle and reaches a peak in the S phase, thereby providing deoxynucleotides for the replication of genomic DNA. In contrast, the mitochondrial pool of dNTPs is maintained through the mitochondrial deoxynucleoside rescue pathway throughout the cell cycle and is essential for mtDNA replication. Mitochondria are vital cell powers in assimilation and catabolism. Oxidative phosphorylation (OXPHOS) of mitochondria is essential for the self-renewal of cancer stem-like cells in lung cancer, glioblastoma and leukemia. Thymidine kinase 2 (TK2) and deoxyguanosine kinase (DGUOK) are two mitochondrial deoxynucleoside kinases, which are responsible for the transport of pyrimidine and purine deoxynucleoside in mitochondria. Apoptosis and autophagy are important processes that regulate cell proliferation and death in normal cells and cancer cells. Inducing cancer cell apoptosis and autophagy is an effective means to treat malignant tumors. This review discusses the research progress of the relationship between mitochondrial deoxyguanosine kinase and lung adenocarcinoma cell apoptosis and autophagy.

As an important part of Traditional Chinese Medicine (TCM) inspection, face diagnosis is significant in judging the rise and fall of viscera and essence and diagnosing and treating diseases. Cancer is a serious disease that endangers human life and health. Face diagnosis can play a great role in diagnosing and treating tumors, but this approach has not achieved the expected effects due to the lack of research. Herein, we summarized the research regarding facial expression, color, shape, and state, demonstrating that facial diagnosis is significant in diagnosing and treating tumors. We also propose that facial diagnosis must be combined with computer technology to realize the objectification of facial diagnosis as soon as possible to play a greater role in diagnosing and treating tumors.

Metastasis is the major cause of cancer-related mortality. Metastasis is a process through which cancer spreads from its initial location to other sections of the body. Cancer cells' epithelial-mesenchymal transition (EMT), anoikis resistance, cell migration, and angiogenesis are all well-known steps in this process. Investigating the molecular processes that govern cancer metastatic progression may lead to more effective diagnostic and treatment strategies. Long non-coding RNAs (lncRNAs) have recently discovered to have a vital more than 200 nucleotides. A rising body of research indicates that lncRNAs have a role in a wide range of biological processes and diseases, including cancer. The usage of LncRNA in cancer metastasis has been widely researched. However, according to current studies, lncRNA is mostly associated with the EMT process. This review focuses on the processes behind lncRNA involvement in cancer metastasis.

The requirement of having multiple nanocarriers (NCs) and active agents for improved therapy, imaging, and controlled release of medications efficiently in one platform has made the creation of therapeutics and theragnostic nanodrug delivery systems a difficult task for present researchers. Multiple drug resistance (MDR), a high clearance rate, severe side effects, undesirable drug distribution to the specific site of liver cancer, and a low concentration of medication that reaches liver cancer cells are just a few of the drawbacks of traditional liver cancer chemotherapy. As a result, new techniques and NCs must be developed to transport the medication molecules targeted to the malignant hepatocytes in an acceptable number and duration inside the therapeutic window. Because of the great efficacy of drug loading or drug encapsulation efficiency, high cellular uptake, high drug release, and minimal adverse effects, therapeutics and theragnostic systems have benefits over conventional chemotherapy. These NCs have a high drug accumulation rate in tumours while causing minimal toxicity in healthy tissues. This study focuses on current research on NC-based therapies and theragnostic drug delivery systems, omitting nanotechnology's negative consequences in the field of drug delivery systems. Clinical advancements of theragnostic NCs for liver cancer, on the other hand, are not covered in this article. Only the most current breakthroughs in NC-based drug delivery systems for liver cancer therapy and diagnosis are discussed in this study. This review will not go over the detrimental effects of individual NCs in the medication delivery system.