A Neural Network Model Combining [-2]proPSA, freePSA, Total PSA, Cathepsin D, and Thrombospondin-1 Showed Increased Accuracy in the Identification of Clinically Significant Prostate Cancer.

BACKGROUND: The Prostate Health Index (PHI) and Proclarix (PCLX) have been proposed as blood-based tests for prostate cancer (PCa). In this study, we evaluated the feasibility of an artificial neural network (ANN)-based approach to develop a combinatorial model including PHI and PCLX biomarkers to recognize clinically significant PCa (csPCa) at initial diagnosis. METHODS: To this aim, we prospectively enrolled 344 men from two different centres. All patients underwent radical prostatectomy (RP). All men had a prostate-specific antigen (PSA) between 2 and 10 ng/mL. We used an artificial neural network to develop models that can identify csPCa efficiently. As inputs, the model uses [-2]proPSA, freePSA, total PSA, cathepsin D, thrombospondin, and age. RESULTS: The output of the model is an estimate of the presence of a low or high Gleason score PCa defined at RP. After training on a dataset of up to 220 samples and optimization of the variables, the model achieved values as high as 78% for sensitivity and 62% for specificity for all-cancer detection compared with those of PHI and PCLX alone. For csPCa detection, the model showed 66% (95% CI 66-68%) for sensitivity and 68% (95% CI 66-68%) for specificity. These values were significantly different compared with those of PHI (p < 0.0001 and 0.0001, respectively) and PCLX (p = 0.0003 and 0.0006, respectively) alone. CONCLUSIONS: Our preliminary study suggests that combining PHI and PCLX biomarkers may help to estimate, with higher accuracy, the presence of csPCa at initial diagnosis, allowing a personalized treatment approach. Further studies training the model on larger datasets are strongly encouraged to support the efficiency of this approach.

Loading of Polydimethylsiloxane with a Human ApoB-Derived Antimicrobial Peptide to Prevent Bacterial Infections.

BACKGROUND: medical device-induced infections affect millions of lives worldwide and innovative preventive strategies are urgently required. Antimicrobial peptides (AMPs) appear as ideal candidates to efficiently functionalize medical devices surfaces and prevent bacterial infections. In this scenario, here, we produced antimicrobial polydimethylsiloxane (PDMS) by loading this polymer with an antimicrobial peptide identified in human apolipoprotein B, r(P)ApoBLPro. METHODS: once obtained loaded PDMS, its structure, anti-infective properties, ability to release the peptide, stability, and biocompatibility were evaluated by FTIR spectroscopy, water contact angle measurements, broth microdilution method, time-killing kinetic assays, quartz crystal microbalance analyses, MTT assays, and scanning electron microscopy analyses. RESULTS: PDMS was loaded with r(P)ApoBLPro peptide which was found to be present not only in the bulk matrix of the polymer but also on its surface. ApoB-derived peptide was found to retain its antimicrobial properties once loaded into PDMS and the antimicrobial material was found to be stable upon storage at 4 °C for a prolonged time interval. A gradual and significant release (70% of the total amount) of the peptide from PDMS was also demonstrated upon 400 min incubation and the antimicrobial material was found to be endowed with anti-adhesive properties and with the ability to prevent biofilm attachment. Furthermore, PDMS loaded with r(P)ApoBLPro peptide was found not to affect the viability of eukaryotic cells. CONCLUSIONS: an easy procedure to functionalize PDMS with r(P)ApoBLPro peptide has been here developed and the obtained functionalized material has been found to be stable, antimicrobial, and biocompatible.

A Combinatorial Neural Network Analysis Reveals a Synergistic Behaviour of Multiparametric Magnetic Resonance and Prostate Health Index in the Identification of Clinically Significant Prostate Cancer.

BACKGROUND: The widespread use of prostate specific antigen (PSA) caused high rate of overdiagnosis. Overdiagnosis leads to unnecessary definitive treatments of prostate cancer (PCa) with detrimental side effects, such as erectile dysfunction and incontinence. The aim of this study was to evaluate the feasibility of an artificial neural network-based approach to develop a combinatorial model including prostate health index (PHI) and multiparametric magnetic resonance (mpMRI) to recognize clinically significant PCa at initial diagnosis. METHODS: To this aim we prospectively enrolled 177 PCa patients who underwent radical prostatectomy and had received PHI tests and mpMRI before surgery. We used artificial neural network to develop models that can identify aggressive PCa efficiently. The model receives as an input PHI plus PI-RADS score. RESULTS: The output of the model is an estimate of the presence of a low or high Gleason score. After training on a dataset of 135 samples and optimization of the variables, the model achieved values of sensitivity as high as 80% and 68% specificity. CONCLUSIONS: Our preliminary study suggests that combining mpMRI and PHI may help to better estimate the risk category of PCa at initial diagnosis, allowing a personalized treatment approach. The efficiency of the method can be improved even further by training the model on larger datasets.

Fluorescence Emission of Self-assembling Amyloid-like Peptides: Solution versus Solid State.

Analysis of the intrinsic UV-visible fluorescence exhibited by self-assembling amyloid-like peptides in solution and in solid the state highlights that their physical state has a profound impact on the optical properties. In the solid state, a linear dependence of the fluorescence emission peaks as a function of excitation wavelength is detected. On the contrary, an excitation-independent emission is observed in solution. The present findings constitute a valuable benchmark for current and future explanations of the fluorescence emission by amyloids.

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 [...].

Optimized Identification of High-Grade Prostate Cancer by Combining Different PSA Molecular Forms and PSA Density in a Deep Learning Model.

After skin cancer, prostate cancer (PC) is the most common cancer among men. The gold standard for PC diagnosis is based on the PSA (prostate-specific antigen) test. Based on this preliminary screening, the physician decides whether to proceed with further tests, typically prostate biopsy, to confirm cancer and evaluate its aggressiveness. Nevertheless, the specificity of the PSA test is suboptimal and, as a result, about 75% of men who undergo a prostate biopsy do not have cancer even if they have elevated PSA levels. Overdiagnosis leads to unnecessary overtreatment of prostate cancer with undesirable side effects, such as incontinence, erectile dysfunction, infections, and pain. Here, we used artificial neuronal networks to develop models that can diagnose PC efficiently. The model receives as an input a panel of 4 clinical variables (total PSA, free PSA, p2PSA, and PSA density) plus age. The output of the model is an estimate of the Gleason score of the patient. After training on a dataset of 190 samples and optimization of the variables, the model achieved values of sensitivity as high as 86% and 89% specificity. The efficiency of the method can be improved even further by training the model on larger datasets.

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.

Time-gated luminescence imaging of positively charged poly-l-lysine-coated highly microporous silicon nanoparticles in living Hydra polyp.

The development of non-toxic fluorescent agents alternative to heavy metal-based semiconductor quantum dots represents a relevant topic in biomedical research and in particular in the bioimaging field. Herein, highly luminescent Si─H terminal microporous silicon nanoparticles with µs-lived photoemission are chemically modified with a two step process and successfully used as label-free probes for in vivo time-gated luminescence imaging. In this context, Hydra vulgaris is used as model organism for in vivo study and validity assessment. The application of time gating allows to pursue an effective sorting of the signals, getting rid of the most common sources of noise that are fast-decay tissue autofluorescence and excitation scattering within the tissue. Indeed, an enhancement by a factor ~ 20 in the image signal-to-noise ratio can be estimated.

Biomimetic hydroxyapatite nanocrystals are an active carrier for Salmonella bacteriophages.

PURPOSE: The use of bacteriophages represents a valid alternative to conventional antimicrobial treatments, overcoming the widespread bacterial antibiotic resistance phenomenon. In this work, we evaluated whether biomimetic hydroxyapatite (HA) nanocrystals are able to enhance some properties of bacteriophages. The final goal of this study was to demonstrate that biomimetic HA nanocrystals can be used for bacteriophage delivery in the context of bacterial infections, and contribute - at the same time - to enhance some of the biological properties of the same bacteriophages such as stability, preservation, antimicrobial activity, and so on. MATERIALS AND METHODS: Phage isolation and characterization were carried out by using Mitomycin C and following double-layer agar technique. The biomimetic HA water suspension was synthesized in order to obtain nanocrystals with plate-like morphology and nanometric dimensions. The interaction of phages with the HA was investigated by dynamic light scattering and Zeta potential analyses. The cytotoxicity and intracellular killing activities of the phage-HA complex were evaluated in human hepatocellular carcinoma HepG2 cells. The bacterial inhibition capacity of the complex was assessed on chicken minced meat samples infected with Salmonella Rissen. RESULTS: Our data highlighted that the biomimetic HA nanocrystal-bacteriophage complex was more stable and more effective than phages alone in all tested experimental conditions. CONCLUSION: Our results evidenced the important contribution of biomimetic HA nanocrystals: they act as an excellent carrier for bacteriophage delivery and enhance its biological characteristics. This study confirmed the significant role of the mineral HA when it is complexed with biological entities like bacteriophages, as it has been shown for molecules such as lactoferrin.

Self-Assembling of Fmoc-GC Peptide Nucleic Acid Dimers into Highly Fluorescent Aggregates.

The study of molecules that self-assemble through noncovalent interactions is one of the most attractive topics in supramolecular chemistry. The use of short peptides or modified nucleotides as building blocks for the aggregates is particularly intriguing because these are very easy to synthesize; moreover, subtle changes in the chemical structure of such building blocks may drastically affect the properties of the aggregates. The ability of peptide nucleic acids (PNA) to aggregate has been very little explored, despite its practical applications. In this work we investigated the self-assembling properties of a PNA dimer, conjugated at the N-terminus to a fluorenylmethoxycarbonyl group. This PNA dimer forms nano-aggregates at low concentration in CHCl3 /CH3 OH mixtures. The aggregates retain very interesting fluorescent properties (high quantum yield in the visible region with lifetimes on the nanosecond scale), which make them promising materials for applications in optoelectronics.

Time-resolved analysis of DNA-protein interactions in living cells by UV laser pulses.

Interactions between DNA and proteins are mainly studied through chemical procedures involving bi-functional reagents, mostly formaldehyde. Chromatin immunoprecipitation is used to identify the binding between transcription factors (TFs) and chromatin, and to evaluate the occurrence and impact of histone/DNA modifications. The current bottleneck in probing DNA-protein interactions using these approaches is caused by the fact that chemical crosslinkers do not discriminate direct and indirect bindings or short-lived chromatin occupancy. Here, we describe a novel application of UV laser-induced (L-) crosslinking and demonstrate that a combination of chemical and L-crosslinking is able to distinguish between direct and indirect DNA-protein interactions in a small number of living cells. The spatial and temporal dynamics of TF bindings to chromatin and their role in gene expression regulation may thus be assessed. The combination of chemical and L-crosslinking offers an exciting and unprecedented tool for biomedical applications.

Ultraviolet laser-induced cross-linking in peptides.

RATIONALE: The aim of this study was to demonstrate, and to characterize by high-resolution mass spectrometry that it is possible to preferentially induce covalent cross-links in peptides by using high-energy femtosecond ultraviolet (UV) laser pulses. The cross-link is readily formed only when aromatic amino acids are present in the peptide sequence. METHODS: Three peptides, xenopsin, angiotensin I, and interleukin, individually or in combination, were exposed to high-energy femtosecond UV laser pulses, either alone or in the presence of spin trapping molecules, the reaction products being characterized by high resolution mass spectrometry. RESULTS: High-resolution mass spectrometry and spin trapping strategies showed that cross-linking occurs readily, proceeds via a radical mechanism, and is the highly dominant reaction, proceeding without causing significant photo-damage in the investigated range of experimental parameters. CONCLUSIONS: High-energy femtosecond UV laser pulses can be used to induce covalent cross-links between aromatic amino acids in peptides, overcoming photo-oxidation processes, that predominate as the mean laser pulse intensity approaches illumination conditions achievable with conventional UV light sources.

Light assisted antibody immobilization for bio-sensing.

Ultrashort UV pulses at 258 nm with repetition rate of 10 kHz have been used to irradiate buffer solution of antibody. The tryptophan residues strongly absorb this radiation thus becoming capable to disrupt the disulfide bridges located next to them. Due to their high reactivity the opened bridges can anchor a gold plate more efficiently than other sites of the macromolecule giving rise to preferential orientations of the variable part of the antibody. UV irradiation has been applied to anchor antiIgG antibody to the electrode of a Quartz Crystal Microbalance (QCM) that lends itself as a sensor, the antibody acting as the bio-receptor. An increase of the QCM sensitivity and of the linear range has been measured when the antibody is irradiated with UV laser pulses. The photo-induced reactions leading to disulfide bridge breakage have been analyzed by means of a chemical assay that confirms our explanation. The control of disulfide bridges by UV light paves the way to important applications for sensing purpose since cysteine in combination with tryptophan can act as a hook to link refractory bio-receptors to surfaces.