PSA testing: an evolving relationship with prostate cancer screening

Machine Learning and Radiomics of Bone Scintigraphy: Their Role in Predicting Recurrence of Localized or Locally Advanced Prostate Cancer

BACKGROUND

Machine-learning (ML) and radiomics features have been utilized for survival outcome analysis in various cancers. This study aims to investigate the application of ML based on patients' clinical features and radiomics features derived from bone scintigraphy (BS) and to evaluate recurrence-free survival in local or locally advanced prostate cancer (PCa) patients after the initial treatment.

METHODS

A total of 354 patients who met the eligibility criteria were analyzed and used to train the model. Clinical information and radiomics features of BS were obtained. Survival-related clinical features and radiomics features were included in the ML model training. Using the pyradiomics software, 128 radiomics features from each BS image's region of interest, validated by experts, were extracted. Four textural matrices were also calculated: GLCM, NGLDM, GLRLM, and GLSZM. Five training models (Logistic Regression, Naive Bayes, Random Forest, Support Vector Classification, and XGBoost) were applied using K-fold cross-validation. Recurrence was defined as either a rise in PSA levels, radiographic progression, or death. To assess the classifier's effectiveness, the ROC curve area and confusion matrix were employed.

RESULTS

Of the 354 patients, 101 patients were categorized into the recurrence group with more advanced disease status compared to the non-recurrence group. Key clinical features including tumor stage, radical prostatectomy, initial PSA, Gleason Score primary pattern, and radiotherapy were used for model training. Random Forest (RF) was the best-performing model, with a sensitivity of 0.81, specificity of 0.87, and accuracy of 0.85. The ROC curve analysis showed that predictions from RF outperformed predictions from other ML models with a final AUC of 0.94 and a p-value of <0.001. The other models had accuracy ranges from 0.52 to 0.78 and AUC ranges from 0.67 to 0.84.

CONCLUSIONS

The study showed that ML based on clinical features and radiomics features of BS improves the prediction of PCa recurrence after initial treatment. These findings highlight the added value of ML techniques for risk classification in PCa based on clinical features and radiomics features of BS.

Incidental detection of localized prostate cancer with low PSA by computed tomography scan: A report of two cases

Serum prostate-specific antigen (PSA) levels play an important role in the screening and diagnosis of prostate cancer (PCa). The recommended PSA cut-off in PCa screening is 4 ng/ml. We report two cases of localized PCa with low PSA levels that were incidentally found by computed tomography (CT) performed for another disease.

Advances in stem cell research for the treatment of primary hypogonadism

In Leydig cell dysfunction, cells respond weakly to stimulation by pituitary luteinizing hormone, and, therefore, produce less testosterone, leading to primary hypogonadism. The most widely used treatment for primary hypogonadism is testosterone replacement therapy (TRT). However, TRT causes infertility and has been associated with other adverse effects, such as causing erythrocytosis and gynaecomastia, worsening obstructive sleep apnoea and increasing cardiovascular morbidity and mortality risks. Stem-cell-based therapy that re-establishes testosterone-producing cell lineages in the body has, therefore, become a promising prospect for treating primary hypogonadism. Over the past two decades, substantial advances have been made in the identification of Leydig cell sources for use in transplantation surgery, including the artificial induction of Leydig-like cells from different types of stem cells, for example, stem Leydig cells, mesenchymal stem cells, and pluripotent stem cells (PSCs). PSC-derived Leydig-like cells have already provided a powerful in vitro model to study the molecular mechanisms underlying Leydig cell differentiation and could be used to treat men with primary hypogonadism in a more specific and personalized approach.

Noninvasive Precision Screening of Prostate Cancer by Urinary Multimarker Sensor and Artificial Intelligence Analysis

Screening for prostate cancer relies on the serum prostate-specific antigen test, which provides a high rate of false positives (80%). This results in a large number of unnecessary biopsies and subsequent overtreatment. Considering the frequency of the test, there is a critical unmet need of precision screening for prostate cancer. Here, we introduced a urinary multimarker biosensor with a capacity to learn to achieve this goal. The correlation of clinical state with the sensing signals from urinary multimarkers was analyzed by two common machine learning algorithms. As the number of biomarkers was increased, both algorithms provided a monotonic increase in screening performance. Under the best combination of biomarkers, the machine learning algorithms screened prostate cancer patients with more than 99% accuracy using 76 urine specimens. Urinary multimarker biosensor leveraged by machine learning analysis can be an important strategy of precision screening for cancers using a drop of bodily fluid.

Cell-cycle risk score more accurately determines the risk for metastases and death in prostatectomy patients compared with clinical features alone

BACKGROUND

Prostate cancer treatment aims to prevent metastases and disease-specific mortality. Pathologic parameters have limited ability to predict these outcomes, but biomarkers can improve risk discrimination. We evaluated the ability of cell-cycle progression and combined cell-cycle risk scores to predict metastases and disease-specific mortality after prostatectomy.

METHODS

Eligibility included (1) treatment with radical prostatectomy (1985-1997); (2) cell-cycle progression score; (3) preoperative prostate-specific antigen; (4) no neoadjuvant therapy; and (5) clinical follow-up (N = 360). Cancer of the prostate risk assessment postsurgical score was combined with cell cycle progression into the prespecified combined cell-cycle risk score. Hazard ratios (HRs) are reported per unit score.

RESULTS

In total, 11% (41/360) developed metastases and 9% (33/360) experienced disease-specific mortality. Combined cell-cycle risk score predicted metastases and disease-specific mortality post-radical prostatectomy (p < 1 × 10-8 ). Adjusting for cancer of the prostate risk assessment postsurgical score, the combined cell-cycle risk score remained a predictor of metastases (HR = 3.03 [95% confidence interval (CI): 1.49, 6.20]; p = .003] and disease-specific mortality (HR = 3.40 [95% CI: 1.52, 7.59]; p = .004). Of patients with biochemical recurrence, 25% (41/163) developed metastases. Cancer of the prostate risk assessment postsurgical score was predictive of metastases postbiochemical recurrence but was improved by the addition of cell cycle progression (HR = 1.70 [95% CI: 1.14, 2.53]; p = .012). The combined cell-cycle risk was also prognostic of metastases post-biochemical recurrence (HR = 1.56 [95% CI: 1.20, 2.03]; p = .001).

CONCLUSION

Combined cell-cycle risk and cell cycle progression scores predict metastases and disease-specific mortality post-radical prostatectomy and should help identify patients at greatest risk of treatment failure who might benefit from earlier intervention.

Research Progress for the Clinical Application of Circulating Tumor Cells in Prostate Cancer Diagnosis and Treatment

Prostate cancer is a life-threatening and highly heterogeneous malignancy. In the past decade, circulating tumor cells (CTCs) have been suggested to play a critical role in the occurrence and progression of prostate cancer. In particular, as the “seed” of the cancer metastasis cascade, CTCs determine numerous biological behaviors, such as tumor invasion into adjacent tissues and migration to distant organs. Many studies have shown that CTCs are necessary in the processes of tumor progression, including tumorigenesis, invasion, metastasis, and colonization. Furthermore, CTCs express various biomarkers relevant to prostate cancer and thus can be applied clinically in noninvasive tests. Moreover, CTCs can serve as potential prognostic targets in prostate cancer due to their roles in regulating many processes associated with cancer metastasis. In this review, we discuss the isolation and detection of CTCs as predictive markers of prostate cancer, and we discuss their clinical application in the diagnosis and prognosis of prostate cancer and in monitoring the response to treatment and the prediction of metastasis.

Incidence and disease burden of prostate cancer from 1990 to 2017: Results from the Global Burden of Disease Study 2017

BACKGROUND

The patterns of the incidence and mortality of prostate cancer (PC) have been changing over the years. In addition, the unclear etiology of PC necessitates further studies into the geographic distribution and age composition of patients with PC. This study was aimed at examining the patterns of the epidemiology of PC to help policymakers to allocate the limited resources of the health care system accordingly.

METHODS

Annual case data and age-standardized rates (ASRs) were obtained for the incidence, mortality, and disability-adjusted life-years (DALYs) of PC according to age from 1990 to 2017 and for 21 regions, including 195 countries and territories. The estimated annual percentage changes (EAPCs) of ASRs were calculated to evaluate the incidence and mortality trends of PC.

RESULTS

Worldwide, the age-standardized incidence rate (ASIR) of PC increased from 30.5 cases per 100,000 population in 1990 to 37.9 cases per 100,000 population in 2017 with an EAPC of 0.59 (95% confidence interval [CI], 0.49-0.7), whereas the mortality decreased with an EAPC of -0.73 (95% CI, -0.80 to -0.67). The ASIR was positively associated with the sociodemographic index (SDI) in most regions, and the increase in the ASIR was steeper with a higher SDI. The proportion of patients younger than 65 years increased from 23.6% in 1990 to 27.3% in 2017.

CONCLUSIONS

The incidence of PC has been increasing globally, whereas its mortality and DALYs have been decreasing. These trends are particularly significant in developed regions and vary across geographic regions. Adjustments to the medical strategy by governments and medical institutions are required.

Retrospective Study of the Significant Predictive Role of Inflammatory Degree in Initial and Repeat Prostate Biopsy Specimens for Detecting Prostate Cancer

Purpose

The purpose of this study was to determine whether histologic inflammation (HI) in initial and repeat prostate biopsy specimens was significantly associated with the detection of prostate cancer.

Materials and Methods

Between 2005 and 2017, the clinicopathological records of patients with high prostatespecific antigen (PSA) levels who underwent initial and repeat prostate biopsies were retrospectively reviewed. The presence of HI and its degree in each biopsied specimen were interpreted by one uropathologist with 20 years of experience. The association between HI and cancer diagnosis was statistically assessed, with p < 0.05 considered significant, and the cancer and non-cancer groups were compared.

Results

Among the 522 patients with a median PSA levels of 6.5 ng/dL, including 258 (49.4%) whose cancer was diagnosed following repeat biopsy, the median degrees of HI in the initial and repeat biopsies were 25.0% and 41.7%, respectively. Furthermore, 211 (40.4%) and 247 (47.3%) patients had HI (> 0%) on biopsied specimens, respectively. Comparison of the cancer and noncancer groups revealed that a greater rate of HI specimens in the initial biopsy was associated with fewer prostate cancer diagnoses following repeat biopsy (p < 0.001). Other comparisons between the cancer and non-cancer groups showed that the cancer group had a significantly higher rate of hypertension, whereas those non-cancer group had a significantly higher rate of benign prostatic hyperplasia and prostatitis (p < 0.05).

Conclusion

A finding of a lesser degree of HI in the initial and a greater degree of HI in the repeat biopsied specimens was associated with the higher probability of cancer diagnosis in patients with high PSA levels.

Academic Medical Centers as Innovation Ecosystems: Evolution of Industry Partnership Models Beyond the Bayh-Dole Act

Innovation ecosystems tied to academic medical centers (AMCs) are inextricably linked to policy, practices, and infrastructure resulting from the Bayh-Dole Act in 1980. Bayh-Dole smoothed the way to patenting and licensing new drugs and, to some degree, medical devices and diagnostic reagents. Property rights under Bayh-Dole provided significant incentive for industry investments in clinical trials, clinical validation, and industrial scale-up of products that advanced health care. Bayh-Dole amplified private investment in biotechnology drug development and, from the authors' perspective, did not significantly interfere with the ability of AMCs to produce excellent peer-reviewed science. In today's policy environment, it is increasingly difficult to patent and license products based on the laws of nature-as the scope of patentability has been narrowed by case law and development of a suitable clinical and business case for the technology is increasingly a gating consideration for licensees. Consequently, fewer academic patents are commercially valuable. The role of technology transfer organizations in engaging industry partners has thus become increasingly complex. The partnering toolbox and organizational mandate for commercialization must evolve toward novel collaborative models that exploit opportunities for future patent creation (early drug discovery), data exchange (precision medicine using big data), cohort assembly (clinical trials), and decision rule validation (clinical trials). These inputs contribute to intellectual property rights, and their clinical exploitation manifests the commercialization of translational science. New collaboration models between AMCs and industry must be established to leverage the assets within AMCs that industry partners deem valuable.

Applications of Nanoparticles Probes for Prostate Cancer Imaging and Therapy

Prostate cancer (PCa) is the most common type of cancer in men with high morbidity and mortality. However, the current treatment with drugs often leads to chemotherapy resistance. It is known that the multi-disciplines research on molecular imaging is very helpful for early diagnosing, staging, restaging and precise treatment of PCa. In the past decades, the tumor-specific targeted drugs were developed for the clinic to treat prostate cancer. Among them, the emerging nanotechnology has brought about many exciting novel diagnosis and treatments systems for PCa. Nanotechnology can greatly enhance the treatment activity of PCa and provide novel theranostics platform by utilizing the unique physical/chemical properties, targeting strategy, or by loading with imaging/therapeutic agents. Herein, this chapter focuses on state-of-art advances in imaging and diagnosing PCa with nanomaterials and highlights the approaches used for functionalization of the targeted biomolecules, and in the treatment for various aspects of PCa with multifunctional nanoparticles, nanoplatforms and nanodelivery system.

Incidental detection of prostate-specific antigen-negative metastatic prostate cancer initially presented with solitary pulmonary nodule on fluorodeoxyglucose positron emission tomography/computed tomography

A 71-year-old male patient with solitary pulmonary nodule underwent fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) showing slightly increased FDG uptake in this nodule. In addition, PET/CT detected hypermetabolic sclerotic bone lesions in the right second rib and 7^th thoracic vertebrae, which were interpreted as possible metastases, and mildly increased FDG uptake in the prostate gland highly suspicious of malignancy. The patient's prostate-specific antigen (PSA) level was within normal range (3.8 ng/dL). The histopathological examination of the lung nodule and right second rib lesion proved metastases from prostate cancer, then the prostate biopsy-confirmed prostate adenocarcinoma. The unique feature of this case is to emphasize the importance of performing PET/CT for solitary pulmonary nodule in detecting PSA-negative metastatic prostate cancer. This case indicated that it should be kept in mind that, even if the PSA is negative, a lung metastasis of prostate cancer may be an underlying cause in patients evaluated for solitary pulmonary nodule by FDG PET/CT.

PSA enzymatic activity: a new biomarker for assessing prostate cancer aggressiveness

BACKGROUND

With the advent of widespread prostate-specific antigen (PSA) testing in recent decades, prostate cancer (PCa) has emerged as the most frequently diagnosed non-skin cancer among men in the U.S. and Europe. Greater screening rates coupled with improved detection methods have caused a controversial upsurge in the number of men undergoing prostate biopsy and subsequent treatment. However, current diagnostic techniques generally suffer from limited ability to identify which seemingly indolent cancers are biologically aggressive.

METHODS

We collected prostatic fluid from 778 post-radical prostatectomy specimens and randomly selected samples from both the clinically confirmed aggressive (n = 50) and non-aggressive (n = 50) prostate cancer populations. We measured the level of proteolytic enzyme activity of PSA (aPSA) in each sample and used receiver operating characteristic (ROC) analysis to correlate aPSA levels with prostate cancer aggressiveness.

RESULTS

We found aPSA in prostatic fluid to be inversely proportional to disease stage, such that patients with the most aggressive PCa have on average significantly reduced aPSA compared to those with less aggressive disease. Significantly, our results suggest that many (22% in our study population) of the diagnosed patients with non-aggressive PCa could have averted or delayed radical prostatectomy.

CONCLUSIONS

Given the high level of debate surrounding PSA screening effectiveness [3-5] and the recent U.S. Preventative Services Task Force recommendation to discontinue PSA screening [6], our results provide renewed hope that a clinical monitoring tool may emerge that truly refines PCa treatment decision-making.

The current role of circulating tumor cells in the diagnosis and management of bone metastases in advanced prostate cancer

Prostate-specific antigen (PSA) has been used for over two decades as a serum marker for adenocarcinoma of the prostate. Although PSA screening remains an important part of disease screening and monitoring in early prostate cancer (PC), its utility in monitoring disease progression in advanced PC is undetermined. Furthermore, the role of PSA monitoring in the management of patients with PC and bone metastases appears limited. The purpose of this review is to evaluate the role of circulating tumor cells (CTCs) as potential novel biomarkers in advanced PC. We present a review of CTC testing and the clinical data supporting the prognostic potential of CTCs in this setting. We propose that combination of CTCs and PSA velocity or doubling-time assessments may offer insights into the prognosis and management of advanced PC.

Identification of AKAP-4 as a new cancer/testis antigen for detection and immunotherapy of prostate cancer

BACKGROUND

Prostate cancer (PC) is the second most common cancer in older men, after skin cancer. PC is difficult to diagnose because the prostate-specific antigen screening method is associated with many false positives. In addition there is a need to develop new and more effective treatments. Among presently available new treatments, immunotherapy is a promising approach. We investigated the expression of the cancer/testis antigen, AKAP-4, in PC patients to evaluate the possibility of exploiting AKAP-4 as a target for immunotherapy.

METHODS

We analyzed normal prostate tissues, 15 patients with PC and the LnCAP PC cell line by immunohistochemistry. We tested AKAP-4 immunogenicity through indirect ELISA on sera from patients and healthy subjects, and we generated in vitro AKAP-4-specific cytotoxic lymphocytes from peripheral blood mononuclear cells.

RESULTS

AKAP-4 was shown both at the cytoplasmic and surface levels of the LnCAP PC cell line. AKAP-4 was also highly expressed in PC cells from patients. We detected specific anti-AKAP-4 circulating immunoglobulins in AKAP-4 positive subjects. Using recombinant AKAP-4 loaded autologous dendritic cells, we generated AKAP-4-specific and HLA-I-restricted cytotoxic T lymphocytes able to kill PC cells in vitro. Further characterization indicated a Th-1 skewing in the cytokine secretion profile of these cells.

CONCLUSIONS

We demonstrate the aberrant expression of AKAP-4 in PC, which will potentially be developed as a biomarker in PC. We provide evidence that AKAP-4 is a potential target for PC adoptive immunotherapy or anti-tumor vaccination.

Sarcosine as a marker in prostate cancer progression: a rapid and simple method for its quantification in human urine by solid-phase microextraction-gas chromatography-triple quadrupole mass spectrometry

Sarcosine is an amino acid derivative of N-methylglycine and is involved in the amino acid metabolism and methylation processes that are enriched during prostate cancer progression. It could also serve as a new target to be measured during therapeutic interventions and help in the identification of aggressive tumors for radical treatment. In this study, we present a new urine test that can help early diagnosis of prostate cancer. The method for the quantification of sarcosine in urine consists of a solid-phase microextraction (SPME) step followed by gas chromatography-triple quadrupole mass spectrometry analysis. We used a preliminary derivatization step with ethyl chloroformate/ethanol and the corresponding ester was then extracted by SPME in immersion mode. Several fibers were evaluated and the optimization of the parameters affecting the SPME process was carried out using an experimental design. The optimal values were 20 min extraction time, 10% NaCl, and 270°C using a divinylbenzene/Carboxen/polydimethylsiloxane fiber. The triple quadrupole analyzer acquired data in selected reaction monitoring mode, allowing us to obtain reconstructed chromatograms with well-defined chromatographic peaks. The accuracy and precision of this method were evaluated at concentrations of 70, 250, and 800 ng/ml and were found to be acceptable. Very satisfactory values (0.10 and 0.16 ng/ml, respectively) were also achieved for the limit of detection and the limit of quantification. The proposed protocol represents a rapid, simple, selective, and sensitive tool to quantify sarcosine in urine samples for prostate cancer diagnosis and for a screening test.

Label-free electrical detection using carbon nanotube-based biosensors

Label-free detections of biomolecules have attracted great attention in a lot of life science fields such as genomics, clinical diagnosis and practical pharmacy. In this article, we reviewed amperometric and potentiometric biosensors based on carbon nanotubes (CNTs). In amperometric detections, CNT-modified electrodes were used as working electrodes to significantly enhance electroactive surface area. In contrast, the potentiometric biosensors were based on aptamer-modified CNT field-effect transistors (CNTFETs). Since aptamers are artificial oligonucleotides and thus are smaller than the Debye length, proteins can be detected with high sensitivity. In this review, we discussed on the technology, characteristics and developments for commercialization in label-free CNT-based biosensors.

Proteomic analysis of conditioned media from the PC3, LNCaP, and 22Rv1 prostate cancer cell lines: discovery and validation of candidate prostate cancer biomarkers

Early detection of prostate cancer is problematic due to the lack of a marker that has high diagnostic sensitivity and specificity. The prostate specific antigen (PSA) test, in combination with digital rectal examination, is the gold standard for prostate cancer diagnosis. However, this modality suffers from low specificity. Therefore, specific markers for clinically relevant prostate cancer are needed. Our objective was to proteomically characterize the conditioned media from three human prostate cancer cell lines of differing origin [PC3 (bone metastasis), LNCaP (lymph node metastasis), and 22Rv1 (localized to prostate)] to identify secreted proteins that could serve as novel prostate cancer biomarkers. Each cell line was cultured in triplicate, followed by a bottom-up analysis of the peptides by two-dimensional chromatography and tandem mass spectrometry. Approximately, 12% (329) of the proteins identified were classified as extracellular and 18% (504) as membrane-bound among which were known prostate cancer biomarkers such as PSA and KLK2. To select the most promising candidates for further investigation, tissue specificity, biological function, disease association based on literature searches, and comparison of protein overlap with the proteome of seminal plasma and serum were examined. On the basis of this, four novel candidates, follistatin, chemokine (C-X-C motif) ligand 16, pentraxin 3 and spondin 2, were validated in the serum of patients with and without prostate cancer. The proteins presented in this study represent a comprehensive sampling of the secreted and shed proteins expressed by prostate cancer cells, which may be useful as diagnostic, prognostic or predictive serological markers for prostate cancer.

Biomarkers, regerons, and pathways to lethal cancer

Cancer is a disease of "outlaw" cells that become mutated in regulatory mechanisms. They have lost normal self controls and relationships to the whole organism. Cancers can progress by several pathways from a normal cell to malignant cancer, from bad to worse. Questions about advisability of treatment for some cancers arise from the possibility that they are arrested during progression and so never become lethal. Techniques could be developed to determine the degree of progression and possibility for successful treatment. This article is intended to suggest a way of looking at cancer. It is not a review so references to research articles are infrequent.

Significant variations in nuclear structure occur between and within Gleason grading patterns 3, 4, and 5 determined by digital image analysis

BACKGROUND

Alterations in nuclei structure and DNA content captured from Gleason grading patterns 3, 4 and 5 of radical prostatectomy (RP) cases were determined by a computer-assisted microscope. Quantitative Nuclear Morphometry (QNM) profiles were created to evaluate variability in nuclear structure within each of these grades.

METHODS

A tissue microarray (TMA) was constructed using RP cases and the prostate cancer (PCa) TMA cores prepared from 20 GG-3, 9 GG-4, 10 GG-5 patterns, and 20 benign cancer-adjacent cases from RP archival paraffin blocks. Feulgen-stained nuclei were captured from 0.6 mm spots using the AutoCyte system. Pools of 1100 nuclei captured from each test group were used to calculate Multivariate Logistic Regression (MLR) models that generated predictive indices and predictive probabilities (PP) to make comparisons between and within each set of pooled nuclei.

RESULTS

A single QNM profiles yielded areas of receiver operator characteristic curves (ROC) that distinguished differences among benign cancer-adjacent nuclei and GG-3 (ROC-AUC = 0.78); GG-4 (ROC-AUC = 0.86) and GG-5 (ROC-AUC = 0.88) with accuracies of 73%, 78% and 80% respectively. Applying PP plots generated from MLR models of GG 3, 4, and 5 nuclei clearly demonstrated marked heterogeneity within each of these three GG patterns.

CONCLUSIONS

QNM signatures illustrate alterations in nuclei structure, based upon nuclear morphometry within each of these three GG patterns, and might signify potential variations in PCa disease risk of progression outcomes. In the future a modified system of Gleason grading that considers not only glandular architecture but also quantitative nuclear grade may ensure accuracy in prognosis.

Label-free immunosensor for prostate-specific antigen based on single-walled carbon nanotube array-modified microelectrodes

We have fabricated a label-free electrochemical immunosensor using microelectrode arrays modified with single-walled carbon nanotubes (SWNTs). Label-free detection of a cancer marker, total prostate-specific antigen (T-PSA), was carried out using differential pulse voltammetry (DPV). The current signals, derived from the oxidation of tyrosine (Tyr), and tryptophan (Trp) residues, increased with the interaction between T-PSA on T-PSA-mAb covalently immobilized on SWNTs. The selectivity of our biosensor was challenged using bovine serum albumin (BSA) as the target protein. The detection limit for T-PSA was determined as 0.25 ng/mL. Since the cut-off limit of T-PSA between prostate hyperplasia and cancer is 4 ng/mL, the performance of our label-free electrochemical immunosensor seems promising for further clinical applications.