1. Could you briefly introduce yourself and your current research topic to our readers?
I am no longer a youngster, but I continue to satisfy my curiosity through scientific activity. I consider myself curious, like many other researchers. In the last century, I have come across developing research on proteins covering many topics and methods, from purifications, sequences, structures, spectroscopic and chemical techniques, stability, folding, and evolution, up to the metabolic and genomic implications, both normal and pathological. Proteins are the object of my curiosity because they act, control, and regulate. They are the essence of life as we know it. Today, I am interested in interactomic technologies to study the human proteome, the one defined as deep and causal on the basis of normal and pathological states. Details of my life are included in the following links: https://scholar.google.com/citations?user=KqTA8UDZhMUC&hl=it; https://www.researchgate.net/profile/Giovanni-Colonna.

2. What criteria do you consider most important when evaluating a manuscript?
The criterion is unique with two faces—the consistency of the results with the fundamental principles of scientific research (experiment, data, critical analysis) but also with the human knowledge of the sector. Scientists must show project results experimentally, not by endorsing or explaining them with others' data. When writing a scientific project, it is important to use scientifically valid, certain, and reliable data to support the project; experiments must validate such data, not uphold unvalidated hypotheses. In biomedical sciences, there is often confusion between scientifically valid data and hypotheses. Many researchers still use decades-old deterministic methods, ignoring the complexity of the millennium and the indeterministic global systems biology approach better suited for complex problems like finding disease causes. The complexity of the human organism at all levels makes its properties unpredictable, demanding a global holistic approach to its study. The causes are always deep, microscopic, dictated by the genome and actuated by the proteome. Molecular-level causes follow indeterministic and non-causal physical laws and therefore do not linearly connect with the macroscopic observational world. Therefore, we must always seek causes in the concurrent action of hundreds of different biomolecules expressing a function while simultaneously performing other functions in the organism. For these reasons, defining a certain molecule in the medium under study by a Western blot or similar techniques makes little sense unless we show that its presence functionally connects to all other molecules with which it must collaborate to perform the specific function we are studying. Defining the causes of a pathology requires using relational networks of biomolecules with certain, reliable, and experimentally validated interactions. Proceeding without a solid foundation risk yielding results that are entirely false or entirely accurate.

3. As a reviewer, how do you balance encouraging research innovation with the strict requirements for methodological reliability? Could you give an example?
Innovation is a leap forward into the future that pushes beyond the boundaries of the known, but we don't always know where we end up. The Internet and AI could be two emblematic examples. One should always encourage innovation, even in the face of apparent failure, but only when it adheres to core principles. Innovating means improving what already exists, while evaluating a discovery is a distinct thing. Discovery means finding something new, often something existing but yet unobserved or understood. The evaluation criteria could be similar, but with some fundamental differences—while discoveries expand knowledge, innovations transform it into practical value. Both results must always be reproducible by other researchers.

4. Beyond “error correction”, what unique value do you think excellent peer review brings to the academic community?
A reviewer must prevent unvalidated, and therefore hypothetical, results from polluting human knowledge in the sector. Experience shows that many hypotheses have slowly spread through human knowledge and then gained acceptance as real and reliable events. In these cases, both the reviewer and the editorial team share responsibility: the reviewer did not ensure adherence to basic research principles, and the editorial team may have placed greater emphasis on timely processing.

5. In your research career, have you had an experience where reviewers’ feedback led to a research breakthrough?
I worked many years ago to develop a spectroscopic method to determine the solvent exposure of tyrosine residues in proteins. When folding and the stability of structures were just beginning to be studied, this was a useful method. Our representation was approximate from a mathematical point of view, since it was a matter of determining the second derivative of very "convoluted" spectra with many shoulders. The reviewer explained to us in simple terms how to show the results and how to use them effectively in complex situations. That method was the basis of many of my studies on folding and stability. Today, spectroscopic instruments directly calculate the derived spectra using a small chip.

6. How do you view the role of a reviewer in shaping the quality and integrity of published research?
The reviewer must guide the authors to avoid conclusions that are unclear to the reader while always keeping the results and discussions in line with the fundamental principles of scientific research. To do this, the reviewer reminds authors of the principles and then shows, using their data, how these principles were violated or circumvented. This is time-consuming and labour-intensive for the reviewer, so it is difficult and not always workable because of the time pressure imposed by all publishers. The authors must understand before they accept and correct their results.

7. What advice would you give to early career researchers who want to become strong peer reviewers?
The approach to biomedical research today is multidisciplinary, so you have to be multidisciplinary in the sense that you also have to understand the scientific language of those who express themselves from other corners of science. Otherwise, you risk not understanding the meaning of certain manuscripts. But, at its core, you always have to evaluate whether the results presented result from the principles of scientific research and whether the data presented derive from critically evaluated experiments. Starting any scientific projects requires careful preparation. The preparation of the project requires that its foundations rest on a careful evaluation of the literature data in terms of reliability and credibility. One of the major problems of our time is the widespread incoherence of many indirect results present in the scientific literature. They can lead to a loss of public trust and scepticism about published results if it becomes difficult for other researchers to replicate studies, a fundamental principle of science. Decisions based on inconsistent data can lead to ineffective or harmful policies. Therefore, addressing inconsistencies at the review stage is crucial to ensuring public trust and research integrity. It is therefore essential for early career researchers to promote transparent and rigorous review practices to improve the consistency and quality of scientific results.