The increasing power of computers, the availability of cheap hardware, and the digitization process overall have made technology an essential part of our daily routines. The massive adoption of technology has helped generate massive amounts of data, often referred to as big data. Such massive data cover all aspects of our life, from dealing with government services (e.g. getting a driving license) to recording sleep patterns with our smartphones.[1] Big data is conceptually more than “lots of data.” Big data has several characteristics in addition to huge volumes of data: Rapidly generated in real time or close to, comprehensive, relational, diverse, and fine grained. The concept of big data has been associated with rapidly advancing methods that enable novel ways of analysis that were impossible before. Machine learning, artificial intelligence, data science, and network science are just examples of such methods.[2] Having access to data, powerful methods of analysis have kindled a wave of optimism that data can solve the world’s most unyielding problems. There are, of course, several examples that have stimulated such big hopes. Many companies were able to harness the potentials of big data for their competitive advantage expanding reach and customer base. Several outstanding human innovations give compelling evidence of the power of big data and analytics. Take for example the several online translation services that can translate between several languages without knowing any and with impeccable quality.[1,2] Such advances have led to the upsurge of data-driven approaches to the degree that many claim that such data-driven methods are a replacement for scientific theory and traditional hypothesis-driven methods. In a much-discussed article, Chris Anderson argues that “we can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.[3]” While in many instances, this has proven useful, in many others, several spurious findings were obtained.[2] Thus, this argument has been largely debated as misleading and dangerous. A perfect scenario is to use big data to conduct robust analysis with maximized statistical power. Such analyses have been used to develop, for example, product recommender systems and academic dropout prediction systems. However, the data used by such systems are obtained from many individuals in most of the cases; or what is known as variable or group-based analysis. Typically, a large amount of data are collected from a sample that is hypothesized to be representative of the population. The analysis of such sample aims at devising universal laws that apply to all. For instance, the analysis of hypertensive patients would give an idea about the typical presentation of the disease, the typical prognosis, and response to treatment.[4,5] However, such generalization is a mere over-simplification and reductionist. Group-based analysis has several fundamental problems that pose considerable threat to the validity of results. The first problem is that group-based analysis assumes that the population is a homogenous group of individuals with no or little variations or heterogeneity. Such assumption is very unlikely to hold. Human physiology, pathology, and behavior are heterogeneous with obvious diversity and distinct trajectories. For example, patients with hypertension can have several different pathways of their clinical progression, response to treatment, complications, and disease outcome. Such heterogeneity has been poorly addressed in previous research.[4] The other problem with group-based analysis is that it assumes that the analyzed process is ergodic, that is, stable overtime, while human social and psychological processes have considerable time variations. Therefore, group-based analysis which lacks the dimension of time can poorly represent these processes. Such deficiencies make results of group-based analysis less likely to generalize to individuals.[4]  The frustration resulting from lack of generalizability of group-based insights is well-recognized. Several threads of research are emerging to address such challenges. Precision medicine, person-based research, and idiography are among the most promising. The main principle behind such methods is to devote more attention to the individual to identify the characteristics that define how their bodies work. Idiography, in particular, aims at collecting data from the individual over multiple times. By having several observations about an individual, researchers have enough data about a person that they can create statistical models based on the person’s data. Analysis of single person data offers a laser-sharp view of a person’s internal conditions. This approach is made possible by the availability of multiple data sources as well as devices that can facilitate data collection, for example, smartphones. In summary, a paradigm shift is happening, where the focus is on collecting big data from individuals. Such self-big data is more relevant, more representative, and offers a better opportunity for personalized insights. Such paradigm shift is moving from the big data of many others to self-big data.

Objectives : Damage to the peripheral and central nervous system lead to Neuropathic pain (NP) which is a widespread and devitalizing condition. chondroitin sulfate (CS), has been used in managing joint pain and osteoarthritis. In this study, the effectiveness of CS on NP induced by chronic constriction injury (CCI) is examined. Methods: Thirty Wistar rats were distributed at random into six groups (n = 5). Sciatic nerve ligation was carried out by encircling the nerve with four loose ligatures to induce NP. Allodynia (cold and mechanical) and heat hyperalgesia were assessed using Acetone, von Frey filament and Hot plate tests. CCI induction resulted to NP, prominent from the 3rd day after surgery. Structural architecture of sciatic nerves was evaluated via histological examination of the transverse section of the nerves. Results: Oral administration of CS (600 mg/kg and 900 mg/kg for 21 days) resulted in significant (P < 0.05) inhibition of allodynia (cold and mechanical) and thermal hyperalgesia. Lipid peroxidation, tumor necrosis factor-α (TNF-α), calcitonin gene related peptide (CGRP), C reactive protein (CRP), and oxidative stress were attenuated by CS. CS also improved interleukin (IL)-6, nitric oxide (NO), total antioxidant capacity (TAC). Conclusion: These findings suggest that CS attenuates allodynia, and thermal hyperalgesia induced by CCI by downregulating TNF-α, CRP, CGRP, oxidative enzymes, and upregulating IL-6, NO, and TAC. Nociceptive behavioral studies and histological findings showed significant improvement in the CS treated groups compared to CCI rats. These findings are responsible for the beneficial effect of CS in NP.

Objectives: The aim of this study is to determine the genetic relatedness of extended-spectrum beta-lactamases (ESBL)-producing Escherichia coli using the enterobacterial repetitive intergenic consensus-polymerase chain reaction (ERIC-PCR) technique. Methods: Suspected Gram-negative bacteria with their identities from the clinical samples were confirmed using Microgen GN-A-ID Kit. The double-disc synergy test was used to confirm for ESBL-producing E. coli. The susceptibility of the organisms was tested against eleven antimicrobial agents. A singleplex PCR assay was carried out targeting TEM, SHV, CTX-M, and OXA. ERIC-PCR performed, and band patterns obtained were visually evaluated. A dendrogram of the ERIC-PCR fingerprint pattern was done with the aid of DendroUPGMA using the cluster method. Results: Of the 576 clinical samples collected, 23 isolates were confirmed E. coli, and all (100%) are ESBL producers. The highest antibiotic resistance rate was recorded in cefixime (95.6%), and the least was amikacin (17.4%). The predominant ESBL gene is blaTEM genes (95.6%). Gel analysis of ERIC-PCR revealed 1–6 bands. The profiles of the ERIC-PCR differentiated the 23 E. coli isolates into four ERIC cluster types. Conclusion: More than 80% of the isolates are sensitive to amikacin, with greater than 95% harboring blaTEM genes. Overall, ERIC obtained from the clinical specimens indicated some evidence in the genetic relatedness of the ESBL genes among E. coli isolates.

Objectives: We aimed to evaluate the diagnostic efficacy of fast three-dimensional (3D) time-of-flight (TOF) magnetic resonance angiography (MRA) in the detection of cerebral aneurysms. Methods: We screened 1589 patients over a 3-year period, who underwent a magnetic resonance imaging for headache. Fast 3D TOF MRA images taken in addition to routine neuroimaging sequences, which were examined by two independent observers to assess cerebral aneurysms. Results: Sixty-nine aneurysms were detected in 63 patients. The locations of the aneurysms were as follows: Middle cerebral artery, 27.5% (n = 19); internal carotid artery, 53.6% (n = 37); anterior cerebral artery, 5.8% (n = 4); posterior cerebral artery, 5.8% (n = 4); anterior communicating artery, 5.8% (n = 4); and ophthalmic artery, 1.4% (n = 1). Thirty-five (50.7%) were 7 mm or less, 23 (33.3%) were 8–10 mm, and 11 (15.9%) were 11 mm or larger. About 88% of pathological cases (n = 61) were saccular and 12 (n = 8) were fusiform type aneurysms. The interobserver compliance was high (K = 0.83) for detecting the aneurysms. Conclusion: Considering the mortality and morbidity of subarachnoid hemorrhages, 3D TOF MRA is a successful, non-invasive method for detecting cerebral aneurysms. Results of the present study have shown that adding 3D TOF MRA to the routine brain imaging protocol is a beneficial tool for diagnosis.

Objectives: Metformin is widely used for the treatment of type 2 diabetes mellitus and found to have a crucial rule in the induction of apoptosis in several cancer types including pancreatic cell carcinoma, epithelial ovarian cancer, breast cancer, and renal cell carcinoma. In this study, we propose to explore the potential role of metformin as an adjuvant of irinotecan to target colorectal cancer (CRC) cell lines, exploring the effects underlying the anticancer properties of metformin on CRC cell lines. Methods: HCT116 and SW480 cell lines were treated with metformin, irinotecan and their combination. The effect of metformin on cell viability was evaluated using MTT assay. Flow cytometry technique was used to analyze apoptosis and cell cycle progression. While, detection of protein expression was analyzed by Western blot. Results: Metformin was found to inhibit growth in both HCT1116 and SW480 cell lines. On combination with irinotecan, it has been revealed that metformin sensitized CRC cells to irinotecan-induced cytotoxicity. Flow cytometry analysis showed that metformin did not induce apoptosis, but blocked cell cycle in G1 and S phases. This blockage was accompanied by decreased cyclin E and Cdk2 levels and increased p21 level. Conclusion: Combination of metformin with irinotecan may be an effective treatment strategy for targeting colorectal cancer that are resistant to irinotecan monotherapy.

Objective: Chest pain and swelling are routinely reported in women after breast cancer treatment and are often not valued by health professionals. In general, these patients suffer and without many effective solutions. The aim of the present study was to report the results of a novel technique for the treatment of chest pain related to breast cancer treatment. Methods: A  clinical trial was conducted involving 25 women with chest pain resulting from the treatment of breast cancer and submitted to treatment for lymphedema at the Godoy School in 2018. Godoy’s intermittent dermal therapy was performed on the participants 2–4  h/day for 2  days until the occurrence of a significant improvement or complete resolution of pain (measured using the visual analog pain scale). Results: All patients reported a significant reduction in pain in the first ½ h of treatment (P < 0.0001, Wilcoxon signed-rank test). Six of the 25  patients (24%) reported the absence of pain after treatment on the 1st  day and all (100%) reported the absence of pain at the end of treatment on the 2nd  day. Conclusion: Chronic chest pain in patients having been submitted to treatment for breast cancer can be significantly reduced with Godoy’s intermittent skin therapy, achieving standards of normality or near normality within only a few sessions.

Objective: The basic objective of this systematic review was to identify potential biomarkers for chronic stress. Methods: A systematic review of studies linking biomarkers in people with chronic stress was conducted using PRISMA guidelines. The last 40 years’ studies were included in the systematic review with no age restrictions; animal studies were excluded from the study. Electronic databases including PubMed, Embase, and Google Scholar were searched for the study purpose. The studies were searched using the combinations of search terms that comprised chronic stress together with the keywords hypothalamic-pituitary-adrenal axis (HPA axis), autonomic nervous system (ANS), immune system, metabolic biomarkers, cortisol, hair cortisol, salivary cortisol, urinary cortisol, epinephrine, norepinephrine, adrenocorticotropic hormone (ACTH), brain-derived neurotropic factor (BDNF), metabolic biomarkers, antioxidants, glucose, hemoglobin, C-reactive protein (CRP), cytokines, pro-inflammatory cytokines, anti-inflammatory cytokines, and tumor necrosis factor (TNF). Results: A total of 37 studies out of 671 studies met the eligibility criteria and were included in this review. Potential diagnostic biomarkers of chronic stress included cortisol, ACTH, BDNF, catecholamines, glucose, HbA1c, triglycerides, cholesterol, prolactin, oxytocin, dehydroepiandrosterone sulfate (DHEA-S), CRP, and interleukin - 6 and 8. While the others including antioxidants and natural killer (NK) cells require further validation. Taken together, addition, these stress biomarkers have critical prognostic capacities for stress-associated diseases and therapeutic guidance. Conclusion: This systematic review provides an update to the literature by highlighting the role of physiological biomarkers in chronic stress and describing their prognostic and therapeutic values.

Odontomas are common benign odontogenic tumors, being often detected on routine radiographs during the first two decades of life. Rarely, odontoma can interfere with jaw movements, causing mouth opening limitation. A 28-year-old male patient was referred complaining of restriction of mouth opening and mandibular movements, which started 6 months ago. Clinical examination revealed a painless increase of volume on the right maxilla, which interfered the mandibular movements, being associated with pain in these attempts. A well-defined, oval radiopaque lesion in close relationship with the impacted maxillary right third molar was detected in tomographic reconstructions. A surgical excision of the lesion was performed, and microscopy revealed complex odontoma. After 4 months of follow-up, the patient achieved adequate mouth opening and recovered mandibular movements. In the current case, the lesion was placed in a difficult access site, which directly interfered with the displacement of coronoid process.