Decreased fertility in female mice lacking urokinase plasminogen activator.

It is well established that mouse ovarian granulosa cells secrete urokinase plasminogen activator (uPA) under gonadotropin stimulation. The synthesis and secretion of the enzyme correlate well with the time of follicular rupture in vivo. Moreover, uPA is secreted by the trophoblast at the time of implantation. In the present study, we have analyzed whether the absence of uPA could influence follicular growth, ovulation, and embryo implantation. Our data show fewer preantral follicles in uPA-/- ovaries but no decrease in hormonally induced ovulation. However, we observed a significant decrease in the number of implanted embryos in uPA-/- animals and, therefore, a lower number of pups per family. Adding uPA to the epithelial and stromal uterine cell culture medium strongly upregulates the expression of prostaglandin-endoperoxide synthase 2 (Ptgs2), the enzyme required for prostaglandin production and embryo implantation. The uPA inhibitor amiloride abrogated this increase.

Myo-Inositol Reverses TGF-ß1-Induced EMT in MCF-10A Non-Tumorigenic Breast Cells.

Epithelial-Mesenchymal Transition (EMT), triggered by external and internal cues in several physiological and pathological conditions, elicits the transformation of epithelial cells into a mesenchymal-like phenotype. During EMT, epithelial cells lose cell-to-cell contact and acquire unusual motility/invasive capabilities. The associated architectural and functional changes destabilize the epithelial layer consistency, allowing cells to migrate and invade the surrounding tissues. EMT is a critical step in the progression of inflammation and cancer, often sustained by a main driving factor as the transforming growth factor-ß1 (TGF-ß1). Antagonizing EMT has recently gained momentum as an attractive issue in cancer treatment and metastasis prevention. Herein, we demonstrate the capability of myo-inositol (myo-Ins) to revert the EMT process induced by TGF-ß1 on MCF-10A breast cells. Upon TGF-ß1 addition, cells underwent a dramatic phenotypic transformation, as witnessed by structural (disappearance of the E-cadherin-ß-catenin complexes and the emergence of a mesenchymal shape) and molecular modifications (increase in N-cadherin, Snai1, and vimentin), including the release of increased collagen and fibronectin. However, following myo-Ins, those changes were almost completely reverted. Inositol promotes the reconstitution of E-cadherin-ß-catenin complexes, decreasing the expression of genes involved in EMT, while promoting the re-expression of epithelial genes (keratin-18 and E-cadherin). Noticeably, myo-Ins efficiently inhibits the invasiveness and migrating capability of TGF-ß1 treated cells, also reducing the release of metalloproteinase (MMP-9) altogether with collagen synthesis, allowing for the re-establishment of appropriate cell-to-cell junctions, ultimately leading the cell layer back towards a more compact state. Inositol effects were nullified by previous treatment with an siRNA construct to inhibit CDH1 transcripts and, hence, E-cadherin synthesis. This finding suggests that the reconstitution of E-cadherin complexes is an irreplaceable step in the inositol-induced reversion of EMT. Overall, such a result advocates for the useful role of myo-Ins in cancer treatment.

The Role of Inositols in the Hyperandrogenic Phenotypes of PCOS: A Re-Reading of Larner's Results.

Polycystic ovarian syndrome (PCOS) is the most common endocrinological disorder in women, in which, besides chronic anovulation/oligomenorrhea and ovarian cysts, hyperandrogenism plays a critical role in a large fraction of subjects. Inositol isomers-myo-Inositol and D-Chiro-Inositol-have recently been pharmacologically effective in managing many PCOS symptoms while rescuing ovarian fertility. However, some disappointing clinical results prompted the reconsideration of their specific biological functions. Surprisingly, D-Chiro-Ins stimulates androgen synthesis and decreases the ovarian estrogen pathway; on the contrary, myo-Ins activates FSH response and aromatase activity, finally mitigating ovarian hyperandrogenism. However, when the two isomers are given in association-according to the physiological ratio of 40:1-patients could benefit from myo-Ins enhanced FSH and estrogen responsiveness, while taking advantage of the insulin-sensitizing effects displayed mostly by D-Chiro-Ins. We need not postulate insulin resistance to explain PCOS pathogenesis, given that insulin hypersensitivity is likely a shared feature of PCOS ovaries. Indeed, even in the presence of physiological insulin stimulation, the PCOS ovary synthesizes D-Chiro-Ins four times more than that measured in control theca cells. The increased D-Chiro-Ins within the ovary is detrimental in preserving steroidogenic control, and this failure can easily explain why treatment strategies based upon high D-Chiro-Ins have been recognized as poorly effective. Within this perspective, two factors emerge as major determinants in PCOS: hyperandrogenism and reduced aromatase expression. Therefore, PCOS could no longer be considered a disease only due to increased androgen synthesis without considering the contemporary downregulation of aromatase and FSH receptors. Furthermore, these findings suggest that inositols can be specifically effective only for those PCOS phenotypes featured by hyperandrogenism.

Space Biomedicine: A Unique Opportunity to Rethink the Relationships between Physics and Biology.

Space biomedicine has provided significant technological breakthroughs by developing new medical devices, diagnostic tools, and health-supporting systems. Many of these products are currently in use onboard the International Space Station and have been successfully translated into clinical practice on Earth. However, biomedical research performed in space has disclosed exciting, new perspectives regarding the relationships between physics and medicine, thus fostering the rethinking of the theoretical basis of biology. In particular, these studies have stressed the critical role that biophysical forces play in shaping the function and pattern formation of living structures. The experimental models investigated under microgravity conditions allow us to appreciate the complexity of living organisms through a very different perspective. Indeed, biological entities should be conceived as a unique magnification of physical laws driven by local energy and order states overlaid by selection history and constraints, in which the source of the inheritance, variation, and process of selection has expanded from the classical Darwinian definition. The very specific nature of the field in which living organisms behave and evolve in a space environment can be exploited to decipher the underlying, basic processes and mechanisms that are not apparent on Earth. In turn, these findings can provide novel opportunities for testing pharmacological countermeasures that can be instrumental for managing a wide array of health problems and diseases on Earth.

Paradoxical Behavior of Oncogenes Undermines the Somatic Mutation Theory.

The currently accepted theory on the influence of DNA mutations on carcinogenesis (the Somatic Mutation Theory, SMT) is facing an increasing number of controversial results that undermine the explanatory power of mutated genes considered as "causative" factors. Intriguing results have demonstrated that several critical genes may act differently, as oncogenes or tumor suppressors, while phenotypic reversion of cancerous cells/tissues can be achieved by modifying the microenvironment, the mutations they are carrying notwithstanding. Furthermore, a high burden of mutations has been identified in many non-cancerous tissues without any apparent pathological consequence. All things considered, a relevant body of unexplained inconsistencies calls for an in depth rewiring of our theoretical models. Ignoring these paradoxes is no longer sustainable. By avoiding these conundrums, the scientific community will deprive itself of the opportunity to achieve real progress in this important biomedical field. To remedy this situation, we need to embrace new theoretical perspectives, taking the cell-microenvironment interplay as the privileged pathogenetic level of observation, and by assuming new explanatory models based on truly different premises. New theoretical frameworks dawned in the last two decades principally focus on the complex interaction between cells and their microenvironment, which is thought to be the critical level from which carcinogenesis arises. Indeed, both molecular and biophysical components of the stroma can dramatically drive cell fate commitment and cell outcome in opposite directions, even in the presence of the same stimulus. Therefore, such a novel approach can help in solving apparently inextricable paradoxes that are increasingly observed in cancer biology.

Microgravity Modifies the Phenotype of Fibroblast and Promotes Remodeling of the Fibroblast-Keratinocyte Interaction in a 3D Co-Culture Model.

Microgravity impairs tissue organization and critical pathways involved in the cell-microenvironment interplay, where fibroblasts have a critical role. We exposed dermal fibroblasts to simulated microgravity by means of a Random Positioning Machine (RPM), a device that reproduces conditions of weightlessness. Molecular and structural changes were analyzed and compared to control samples growing in a normal gravity field. Simulated microgravity impairs fibroblast conversion into myofibroblast and inhibits their migratory properties. Consequently, the normal interplay between fibroblasts and keratinocytes were remarkably altered in 3D co-culture experiments, giving rise to several ultra-structural abnormalities. Such phenotypic changes are associated with down-regulation of α-SMA that translocate in the nucleoplasm, altogether with the concomitant modification of the actin-vinculin apparatus. Noticeably, the stress associated with weightlessness induced oxidative damage, which seemed to concur with such modifications. These findings disclose new opportunities to establish antioxidant strategies that counteract the microgravity-induced disruptive effects on fibroblasts and tissue organization.

Personalization of medical treatments in oncology: time for rethinking the disease concept to improve individual outcomes.

The agenda of pharmacology discovery in the field of personalized oncology was dictated by the search of molecular targets assumed to deterministically drive tumor development. In this perspective, genes play a fundamental "causal" role while cells simply act as causal proxies, i.e., an intermediate between the molecular input and the organismal output. However, the ceaseless genomic change occurring across time within the same primary and metastatic tumor has broken the hope of a personalized treatment based only upon genomic fingerprint. Indeed, current models are unable in capturing the unfathomable complexity behind the outbreak of a disease, as they discard the contribution of non-genetic factors, environment constraints, and the interplay among different tiers of organization. Herein, we posit that a comprehensive personalized model should view at the disease as a "historical" process, in which different spatially and timely distributed factors interact with each other across multiple levels of organization, which collectively interact with a dynamic gene-expression pattern. Given that a disease is a dynamic, non-linear process - and not a static-stable condition - treatments should be tailored according to the "timing-frame" of each condition. This approach can help in detecting those critical transitions through which the system can access different attractors leading ultimately to diverse outcomes - from a pre-disease state to an overt illness or, alternatively, to recovery. Identification of such tipping points can substantiate the predictive and the preventive ambition of the Predictive, Preventive and Personalized Medicine (PPPM/3PM). However, an unusual effort is required to conjugate multi-omics approaches, data collection, and network analysis reconstruction (eventually involving innovative Artificial Intelligent tools) to recognize the critical phases and the relevant targets, which could help in patient stratification and therapy personalization.

Analytical Performance of COVID-19 Detection Methods (RT-PCR): Scientific and Societal Concerns.

Background. Health and social management of the SARS-CoV-2 epidemic, responsible for the COVID-19 disease, requires both screening tools and diagnostic procedures. Reliable screening tests aim at identifying (truely) infectious individuals that can spread the viral infection and therefore are essential for tracing and harnessing the epidemic diffusion. Instead, diagnostic tests should supplement clinical and radiological findings, thus helping in establishing the diagnosis. Several analytical assays, mostly using RT-PCR-based technologies, have become commercially available for healthcare workers and clinical laboratories. However, such tests showed some critical limitations, given that a relevant number of both false-positive and false-negative cases have been so far reported. Moreover, those analytical techniques demonstrated to be significantly influenced by pre-analytical biases, while the sensitivity showed a dramatic time dependency. Aim. Herein, we critically investigate limits and perspectives of currently available RT-PCR techniques, especially when referring to the required performances in providing reliable epidemiological and clinical information. Key Concepts. Current data cast doubt on the use of RT-PCR swabs as a screening procedure for tracing the evolution of the current SARS-COV-2 pandemic. Indeed, the huge number of both false-positive and false-negative results deprives the trustworthiness of decision making based on those data. Therefore, we should refine current available analytical tests to quickly identify individuals able to really transmit the virus, with the aim to control and prevent large outbreaks.

New statistical RI index allow to better track the dynamics of COVID-19 outbreak in Italy.

COVID-19 pandemic in Italy displayed a spatial distribution that made the tracking of its time course quite difficult. The most relevant anomaly was the marked spatial heterogeneity of COVID-19 diffusion. Lombardia region accounted for around 60% of fatal cases (while hosting 15% of Italian population). Moreover, 86% of fatalities concentrated in four Northern Italy regions. The 'explosive' outbreak of COVID-19 in Lombardia at the very beginning of pandemic fatally biased the R-like statistics routinely used to control the disease dynamics. To (at least partially) overcome this bias, we propose a new index RI = dH/dI (daily derivative ratio of H and I, given H = Healed and I = Infected), corresponding to the ratio between healed and infected patients relative daily changes. The proposed index is less flawed than R by the uncertainty related to the estimated number of infected persons and allows to follow (and possibly forecast) epidemic dynamics in a largely model-independent way. To analyze the dynamics of the epidemic, starting from the beginning of the virus spreading-when data are insufficient to make an estimate by adopting SIR model-a "sigmoidal family with delay" logistic model was introduced. That approach allowed in estimating the epidemic peak using the few data gathered even before mid-March. Based on this analysis, the peak was correctly predicted to occur by end of April. Analytical methodology of the dynamics of the epidemic we are proposing herein aims to forecast the time and intensity of the epidemic peak (forward prediction), while allowing identifying the (more likely) beginning of the epidemic (backward prediction). In addition, we established a relationship between hospitalization in intensive care units (ICU) versus deaths daily rates by avoiding the necessity to rely on precise estimates of the infected fraction of the population The joint evolution of the above parameters over time allows for a trustworthy and unbiased estimation of the dynamics of the epidemic, allowing us to clearly detect the qualitatively different character of the 'so-called' second wave with respect to the previous epidemic peak.

Complexity in Biological Organization: Deconstruction (and Subsequent Restating) of Key Concepts.

The "magic" word complexity evokes a multitude of meanings that obscure its real sense. Here we try and generate a bottom-up reconstruction of the deep sense of complexity by looking at the convergence of different features shared by complex systems. We specifically focus on complexity in biology but stressing the similarities with analogous features encountered in inanimate and artefactual systems in order to track an integrative path toward a new "mainstream" of science overcoming the actual fragmentation of scientific culture.