Investigating the antitumoral activity and mechanism of action of a xanthone derivative

Chapter I refers to the introduction, and has the role of providing an initial overview of the issues addressed directly or indirectly in the rest of the study. Initially, an overview of the cell cycle, its regulation and control is given. In the sequence, a greater emphasis is given to mitosis, which is described in detail from its cascade of events to the molecular machinery of the mitotic spindle. Still at this stage, the dynamics that occur between kinetochore-microtubules, correlated errors and their due corrections are described. Next, we provide an overview of the Spindle Assembly Checkpoint (SAC), dissecting the functions triggered by this mechanism, as well as the proteins involved in this important cellular control mechanism. Following, an introduction was given about drugs that use the targeting of mitosis for cancer therapy, namely through microtubules, providing an overview of current approaches, their limitations and future directions. Finally, a correlation was made between xanthones and cancer, demonstrating how this class of compounds (as well as their derivatives) is already used as a starting point in the development of new anticancer drugs. Chapter II concerns what motivated the project, as well as its specific objectives. Chapter III refers to the materials and methods used throughout the study, so that it was possible to dissect the mechanism of action of the compound. Chapter IV will demonstrate the results about the compound's mechanism of action, through: in vitro characterization of the compound's antimitotic activity, identification of the underlying mechanism of action and evaluation of the combined treatment of PX2 with paclitaxel in promoting cell death of tumoral cells. Chapter V provides a discussion, correlating previous studies and the present study. Chapter VI provides general conclusions about the mechanism of action of PX2 and the prospects for future research. Chapter VII contains a list of all references cited in the course of the thesis.This work was supported by CESPU - Cooperativa de Ensino Superior Politécnico e Universitário Crl [grant number ComeTarget_CESPU_2017 and ComeTax-PFT-IINFACTS-2019]. This research was partially supported by FCT/MCTES - Foundation for Science and Technology from the Minister of Science, Technology and Higher Education and European Regional Development Fund (ERDF) under the projects, co-financed by COMPETE 2020, Portugal 2020, PTDC/SAU-PUB/28736/2017 (POCI-01-0145-FEDER-028736) and within the scope of UIDB/04423/2020, UID/QUI/5000612019, and UIDP/04423/2020 (Group of Natural Products and Medicinal Chemistry). ACH thanks FCT for her PhD grant (SFRH/BD/140844/2018). DRPL thanks FCT for her PhD grant (SFRH/BD/140844/2018). JXS thanks for the FCT PhD Programmes, specifically by the BiotechHealth Programme (PD/00016/2012), and for the grants (SFRH/BD/98105/2013 and SFRH/BD/116167/2016). To Departamento de Química da Universidade de Aveiro (Portuguese NMR network) for the NMR analysis

Predictive value of CDKN2A/p16INK4a expression in the malignant transformation of oral potentially malignant disorders: Systematic review and meta-analysis

[Abstract] Background: Management of oral potentially malignant disorders (OPMDs) is still challenging. Despite the diagnostic ascertainment by bioptic examination, this method is poorly informative of the prognosis and subsequent malignant transformation. Prognosis is based on histological findings by grading of dysplasia. Immunohistochemical expression of p16INK4a has been investigated in different studies, with controversial results. In this scenario, we systematically revised the current evidence about p16INK4a immunohistochemical expression and the risk of malignization of OPMDs. Material and methods: After a proper set of keywords combination, 5 databases were accessed and screened to select eligible studies. The protocol was previously registered on PROSPERO (Protocol ID: CRD42022355931). Data were obtained directly from the primary studies as a measure to determine the relationship between CDKN2A/P16INK4a expression and the malignant transformation of OPMDs. Heterogeneity and publication bias were investigated by different tools, such as Cochran’s Q test, Galbraith plot and Egger and Begg Mazumdar’s rank tests. Results: Meta-analysis revealed a twofold increased risk to malignant development (RR = 2.01, 95% CI = 1.36–2.96 - I2 = 0%). Subgroup analysis did not highlight any relevant heterogeneity. Galbraith plot showed that no individual study could be considered as an important outlier. Conclusion: Pooled analysis showed that p16INK4a assessment may arise adjunct tool to dysplasia grading, leading to an optimized determination of the potential progression to cancer of OPMDs. The p16INK4a overexpression analysis by immunohistochemistry techniques has a multitude of virtues that may facilitate its incorporation in the day-to-day prognostic study of OPMDs

Predictive value of CDKN2A/p16INK4a expression in the malignant transformation of oral potentially malignant disorders: Systematic review and meta-analysis

Background Management of oral potentially malignant disorders (OPMDs) is still challenging. Despite the diagnostic ascertainment by bioptic examination, this method is poorly informative of the prognosis and subsequent malignant transformation. Prognosis is based on histological findings by grading of dysplasia. Immunohistochemical expression of p16INK4a has been investigated in different studies, with controversial results. In this scenario, we systematically revised the current evidence about p16INK4a immunohistochemical expression and the risk of malignization of OPMDs. Material and methods After a proper set of keywords combination, 5 databases were accessed and screened to select eligible studies. The protocol was previously registered on PROSPERO (Protocol ID: CRD42022355931). Data were obtained directly from the primary studies as a measure to determine the relationship between CDKN2A/P16INK4a expression and the malignant transformation of OPMDs. Heterogeneity and publication bias were investigated by different tools, such as Cochran's Q test, Galbraith plot and Egger and Begg Mazumdar’s rank tests. Results Meta-analysis revealed a twofold increased risk to malignant development (RR = 2.01, 95% CI = 1.36–2.96 - I2 = 0%). Subgroup analysis did not highlight any relevant heterogeneity. Galbraith plot showed that no individual study could be considered as an important outlier. Conclusion Pooled analysis showed that p16INK4a assessment may arise adjunct tool to dysplasia grading, leading to an optimized determination of the potential progression to cancer of OPMDs. The p16INK4a overexpression analysis by immunohistochemistry techniques has a multitude of virtues that may facilitate its incorporation in the day-to-day prognostic study of OPMDsS

Correlation of Bcl-2 expression with prognosis and survival in patients with head and neck cancer: a systematic review and meta-analysis

Head and neck cancer (HNC) is a growing disease, affecting more than 700.000 cases per year and ranking as the sixth most prevalent type of cancer worldwide. The impossibility of properly entering into apoptosis directly influences uncontrolled growth and consequently tumor development and progression. Bcl-2 emerged as a key regulator in the balance between cell apoptosis and proliferation in apoptosis machinery. This systematic review and meta-analysis aimed to review all published studies investigating changes in Bcl-2 protein expression assessed by immunohistochemistry (IHC) and related to prognostic and survival values of patients with HNC. After applying the inclusion and exclusion factors, we reached the number of 20 articles included in the meta-analysis. The random-effect pooled HR (CI95%) value of OS related to Bcl-2 IHC expression in tissues from HNC patients was 1.80 (CI95% 1.21–2.67) (p 0.0001) and DFS was 1.90 (CI95% 1.26–2.86 (p 0.0001). The OS value for the specific oral cavity tumors was 1.89 (1.34–2.67), while in the larynx it was 1.77 (0.62–5.06), and the DFS in the pharynx was 2.02 (1.46–2.79). The univariate and multivariate analyses of OS were respectively 1.43 (1.11–1.86) and 1.88 (1.12–3.16), while in DFS it was 1.70 (0.95–3.03) and 2.08 (1.55–2.80). The OS considering a low cut-off for Bcl-2 positivity was 1.19 (0.60–2.37) and DFS was 1.48 (0.91–2.41), while studies with a high cut-off demonstrated OS of 2.28 (1.47–3.52) and DFS of 2.77 (1.74–4.40). Our meta-analysis demonstrates that Bcl-2 protein overexpression can result in worse LNM, OS, and DFS in patients with HNC, however, it is not a reliable conclusion, due to the wide divergences between the original studies and the fact that many studies have a very high range of confidence and also a high risk of bias

Pyrosequencing analysis of O-6-methylguanine-DNA methyltransferase methylation at different cut-offs of positivity associated with treatment response and disease-specific survival in Isocitrate Dehydrogenase-wildtype grade 4 glioblastoma

The O-6-methylguanine-DNA methyltransferase (MGMT) gene is a critical guardian of genomic integrity. MGMT methylation in diffuse gliomas serves as an important determinant of patients’ prognostic outcomes, more specifically in glioblastomas (GBMs). In GBMs, the absence of MGMT methylation, known as MGMT promoter unmethylation, often translates into a more challenging clinical scenario, tending to present resistance to chemotherapy and a worse prognosis. A pyrosequencing (PSQ) technique was used to analyze MGMT methylation status at different cut-offs (5%, 9%, and 11%) in a sample of 78 patients diagnosed with IDH-wildtype grade 4 GBM. A retrospective analysis was provided to collect clinicopathological and prognostic data. A statistical analysis was used to establish an association between methylation status and treatment response (TR) and disease-specific survival (DSS). The patients with methylated MGMT status experienced progressive disease rates of 84.6%, 80%, and 78.4% at the respective cut-offs of 5%, 9%, and 11%. The number was considerably higher when considering unmethylated patients, as all patients (100%), regardless of the cut-off, presented progressive disease. Regarding disease-specific survival (DSS), the Hazard Ratio (HR) was HR = 0.74 (0.45–1.24; p = 0.251); HR = 0.82 (0.51–1.33; p = 0.425); and HR = 0.79 (0.49–1.29; p = 0.350), respectively. Our study concludes that there is an association between MGMT unmethylation and worse TR and DSS. The 9% cut-off demonstrated a greater potential for patient survival as a function of time, which may shed light on the future need for standardization of MGMT methylation positivity parameters in PSQ

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

The Prevalence of the Burnout Syndrome and Factors Associated in the Students of Dentistry in Integral Clinic: A Cross-Sectional Study

Background. Burnout syndrome (BS) is composed of three interrelated dimensions (emotional exhaustion, depersonalization, and personal fulfillment), and it has been documented that it affects health professionals from an early age. Aims. Determine the prevalence of BS and associated factors in the integral clinic of the Dentistry Pilot School. Material and Methods. Two instruments were applied: (1) Maslach Burnout Inventory, which measures the degree of professional burnout through 22 items that describe the professional’s attitudes and feelings toward work, as well as symptoms associated with this phenomenon; (2) the second questionnaire determines the possible symptoms of BS and consists of 14 questions that describe tiredness, sleep problems, digestive problems, respiratory problems and headaches, temporomandibular joint (TMJ), neck pain, back pain, and upper and lower extremity pain. The instruments were answered anonymously by a total of 300 students who participated in the study. Results. The emotional exhaustion of the participants was 48.3% at a higher level, the depersonalization was 46.7% at a higher level, and the low perception of personal fulfillment was 73%. In addition, it was shown that BS is significantly related to marital status (p<0.001∗), with single people reporting being more exhausted, with the 6-month level (p=0.011) and with the following symptoms: non-neck pain, head, TMJ, back, waist, upper and lower body pain. Conclusion. It was found that the BS had a prevalence of high levels of exhaustion and depersonalization correlated with the marital status and level of preparation (academic degree) of the person, finding a prevalence of symptoms such as pain in the neck, head, TMJ, and back