Biosensors for Biomolecular Computing: a Review and Future Perspectives

Biomolecular computing is the field of engineering where computation, storage, communication, and coding are obtained by exploiting interactions between biomolecules, especially DNA, RNA, and enzymes. They are a promising solution in a long-term vision, bringing huge parallelism and negligible power consumption. Despite significant efforts in taking advantage of the massive computational power of biomolecules, many issues are still open along the way for considering biomolecular circuits as an alternative or a complement to competing with complementary metal–oxide–semiconductor (CMOS) architectures. According to the Von Neumann architecture, computing systems are composed of a central processing unit, a storage unit, and input and output (I/O). I/O operations are crucial to drive and read the computing core and to interface it to other devices. In emerging technologies, the complexity overhead and the bottleneck of I/O systems are usually limiting factors. While computing units and memories based on biomolecular systems have been successfully presented in literature, the published I/O operations are still based on laboratory equipment without a real development of integrated I/O. Biosensors are suitable devices for transducing biomolecular interactions by converting them into electrical signals. In this work, we explore the latest advancements in biomolecular computing, as well as in biosensors, with focus on technology suitable to provide the required and still missing I/O devices. Therefore, our goal is to picture out the present and future perspectives about DNA, RNA, and enzymatic-based computing according to the progression in its I/O technologies, and to understand how the field of biosensors contributes to the research beyond CMOS

Comparison between a new thyroglobulin assay with the well-established Beckman Access immunoassay: A preliminary report

Objectives: Measurement of serum thyroglobulin (Tg) plays a key role in the post-thyroidectomy management of differentiated thyroid carcinoma (DTC). In this context, the performance of new-generation thyroglobulin assay has clinical implications in the follow-up of DTC patients. Aim of this study was to compare the new highly sensitive Liaison Tg II (Tg-L) with the well-established Tg Access assay (Tg-A). Materials and methods: A total of 91 residual serum samples (23 positive and 68 negatives for Tg auto-antibodies) were tested by the Beckman Access and Diasorin Liaison assays. Study samples were from 21 patients with pathologically proven DTC and control samples from 70 (16 patients with benign thyroid disease and 54 apparently healthy subjects). Results: Our results showed that Tg-L was highly correlated with Tg-A for both values ranging between 0.2 and 50 ng/mL (Pearson's r = 0.933 [95%CI 0.894-0.958], P <.001) and higher than 50 ng/mL (Pearson's r = 0.849 [95%CI 0.609-0.946], P <.001). For Tg values lower than 0.2 ng/mL, the overall concordance rate was 92%. Moreover, we tested 7 fine-needle aspiration washout fluids (FNA), showing an overall concordance rate in discriminating negative and positive of 100%. Finally, we found no interference by Tg auto-antibodies (TgAbs) for both Tg-L and Tg-A. Conversely, rheumatoid factor (RF) interferes with Tg-A, but not with Tg-L in one patient with no relapsing thyroid carcinoma. Conclusions: Liaison Tg II demonstrated a good correlation with Access Tg assay both for sera and FNAs. Further studies on larger population are needed to evaluate Tg-L clinical impact on DTC patient's follow-up

Closure of a gastrocutaneous fistula by a tulip-bundle technique

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Reply to jue et al. Value of mri to improve deep learning model that identifies high-grade prostate cancer. comment on “gentile et al. optimized identification of high-grade prostate cancer by combining different psa molecular forms and psa density in a deep learning model. diagnostics 2021, 11, 335”

In their comment "Value of MRI to Improve Deep Learning Model That Identifies High-Grade Prostate Cancer [...]

Differential features of muscle fiber atrophy in osteoporosis and osteoarthritis

We demonstrated that osteoporosis is associated with a preferential type II muscle fiber atrophy, which correlates with bone mineral density and reduced levels of Akt, a major regulator of muscle mass. In osteoarthritis, muscle atrophy is of lower extent and related to disease duration and severity. INTRODUCTION: Osteoarthritis (OA) and osteoporosis (OP) are associated with loss of muscle bulk and power. In these diseases, morphological studies on muscle tissue are lacking, and the underlying mechanisms of muscle atrophy are not known. The aim of our study was to evaluate the OP- or OA-related muscle atrophy and its correlation with severity of disease. Muscle levels of Akt protein, a component of IGF-1/PI3K/Akt pathway, the main regulator of muscle mass, have been determined. METHODS: We performed muscle biopsy in 15 women with OP and in 15 women with OA (age range, 60-85 years). Muscle fibers were counted, measured, and classified by ATPase reaction. By statistical analysis, fiber-type atrophy was correlated with bone mineral density (BMD) in the OP group and with Harris Hip Score (HHS) and disease duration in the OA group. Akt protein levels were evaluated by Western blot analysis. RESULTS: Our findings revealed in OP a preferential type II fiber atrophy that inversely correlated with patients' BMD. In OA, muscle atrophy was of lower extent, homogeneous among fiber types and related to disease duration and HHS. Moreover, in OP muscle, the Akt level was significantly reduced as compared to OA muscles. CONCLUSIONS: This study shows that in OP, there is a preferential and diffuse type II fiber atrophy, proportional to the degree of bone loss, whereas in OA, muscle atrophy is connected to the functional impairment caused by the disease. A reduction of Akt seems to be one of the mechanisms involved in OP-related muscle atrophy

Preoperative insulin-like growth factor-binding protein-3 (IGFBP-3) blood level predicts gleason sum upgrading

In this study, we evaluated the ability of preoperative IGFBP-2, IGFBP-3, IL-6, and SIL-6R serum levels to predict Gleason score upgrade in 52 PCa patients

Perspective: Cancer Patient Management Challenges During the COVID-19 Pandemic

On March 11, 2020, the WHO has declared the coronavirus disease 2019 (COVID-19) a global pandemic. As the last few months have profoundly changed the delivery of health care in the world, we should recognize the effort of numerous comprehensive cancer centers to share experiences and knowledge to develop best practices to care for oncological patients during the COVID-19 pandemic. Patients as well as physicians must be aware of all these constraints and profound social, personal, and medical challenges posed by the tackling of this deadly disease in everyday life in order to adjust to such a completely novel scenario. This review will discuss facing the challenges and the current approaches that cancer centers in Italy and United States are adopting in order to cope with clinical and research activities

Colorimetric Test for Fast Detection of SARS-CoV-2 in Nasal and Throat Swabs

Mass testing is fundamental to face the pandemic caused by the coronavirus SARS-CoV-2 discovered at the end of 2019. To this aim, it is necessary to establish reliable, fast, and cheap tools to detect viral particles in biological material so to identify the people capable of spreading the infection. We demonstrate that a colorimetric biosensor based on gold nanoparticle (AuNP) interaction induced by SARS-CoV-2 lends itself as an outstanding tool for detecting viral particles in nasal and throat swabs. The extinction spectrum of a colloidal solution of multiple viral-target gold nanoparticles-AuNPs functionalized with antibodies targeting three surface proteins of SARS-CoV-2 (spike, envelope, and membrane)-is red-shifted in few minutes when mixed with a solution containing the viral particle. The optical density of the mixed solution measured at 560 nm was compared to the threshold cycle (Ct) of a real-time PCR (gold standard for detecting the presence of viruses) finding that the colorimetric method is able to detect very low viral load with a detection limit approaching that of the real-time PCR. Since the method is sensitive to the infecting viral particle rather than to its RNA, the achievements reported here open a new perspective not only in the context of the current and possible future pandemics, but also in microbiology, as the biosensor proves itself to be a powerful though simple tool for measuring the viral particle concentration

Quantification and Reduction of the Residual Chemical Reactivity of Passivated Biodegradable Porous Silicon for Drug Delivery Applications

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Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) Significantly Improve Prostate Cancer Detection at Initial Biopsy in a Total PSA Range of 2-10 ng/ml

Many efforts to reduce prostate specific antigen (PSA) overdiagnosis and overtreatment have been made. To this aim, Prostate Health Index (Phi) and Prostate Cancer Antigen 3 (PCA3) have been proposed as new more specific biomarkers. We evaluated the ability of phi and PCA3 to identify prostate cancer (PCa) at initial prostate biopsy in men with total PSA range of 2-10 ng/ml. The performance of phi and PCA3 were evaluated in 300 patients undergoing first prostate biopsy. ROC curve analyses tested the accuracy (AUC) of phi and PCA3 in predicting PCa. Decision curve analyses (DCA) were used to compare the clinical benefit of the two biomarkers. We found that the AUC value of phi (0.77) was comparable to those of %p2PSA (0.76) and PCA3 (0.73) with no significant differences in pairwise comparison (%p2PSA vs phi p = 0.673, %p2PSA vs. PCA3 p = 0.417 and phi vs. PCA3 p = 0.247). These three biomarkers significantly outperformed fPSA (AUC = 0.60), %fPSA (AUC = 0.62) and p2PSA (AUC = 0.63). At DCA, phi and PCA3 exhibited a very close net benefit profile until the threshold probability of 25%, then phi index showed higher net benefit than PCA3. Multivariable analysis showed that the addition of phi and PCA3 to the base multivariable model (age, PSA, %fPSA, DRE, prostate volume) increased predictive accuracy, whereas no model improved single biomarker performance. Finally we showed that subjects with active surveillance (AS) compatible cancer had significantly lower phi and PCA3 values (p < 0.001 and p = 0.01, respectively). In conclusion, both phi and PCA3 comparably increase the accuracy in predicting the presence of PCa in total PSA range 2-10 ng/ml at initial biopsy, outperforming currently used %fPSA