Morphological description of the temporomandibular joint ligaments in domestic pigs.

The temporomandibular joint (TMJ) ligaments play crucial roles in its function or dysfunction. The objective of this study was to describe the macro and microscopic morphology of these ligaments in domestic pigs, aiming to: (1) expand knowledge about the species; (2) provide anatomical references for advancing veterinary therapy and utilizing pigs as animal models in craniofacial research. Heads of young Sus scrofa domesticus were dissected to identify TMJ ligaments. Fragments of these ligaments were collected and processed for subsequent histological analysis with Haematoxylin and eosin staining. The results were qualitatively described. Pigs exhibited a TMJ reinforced by three individualized capsular ligaments: a lateral ligament, attaching to the ventral margin of the zygomatic process of the temporal bone and the lateral margin of the mandibular neck; a caudomedial ligament, attaching to the retroarticular process of the squamous part of the temporal bone and the caudomedial margin of the mandibular neck and a caudolateral ligament, attaching to the ventral margin of the base of the zygomatic process of the temporal bone and the caudal margin of the mandibular neck. The lateral ligament exhibited a greater constitution of dense irregular connective tissue, while the caudomedial and caudolateral ligaments showed a greater constitution of dense regular connective tissue. It is concluded that the TMJ of pigs presents one more ligament than horses, cattle, dogs, cats and what has been described for pigs themselves. We believe these results may contribute to the improvement of veterinary clinical and surgical therapy overall, as well as provide essential morphological information for a better interpretation and application of interspecies results in craniofacial research using pigs as an experimental model, as in the case of humans.

Cauda equina myxopapillary ependymoma in von Hippel-Lindau disease: A case report.

Background: Patients affected by Von Hippel-Lindau (VHL) are prone to develop central nervous system neoplasms such as hemangioblastomas (HBs). Myxopapillary ependymoma (MPE) is not commonly associated with VHL disease. Case Description: We present the first case of a VHL patient affected by simultaneous silent cauda equina MPE and a symptomatic conus medullaris HB. The patient was first operated for systemic tumors and followed for asymptomatic HBs. Simple surveillance was maintained until neurological symptoms appeared. Regular follow-up demonstrated objective growth of the cystic conus medullaris tumor while the cauda equina lesion remained stable. Surgery was performed to avoid further neurological worsening. Histopathological examination showed conus medullaris HB and a nearby cauda equina MPE. Conclusion: Simultaneous spinal HBs and isolated MPE may exceptionally occur in VHL patients.

Angiotensin-(1-5) is a Potent Endogenous Angiotensin AT 2 -Receptor Agonist.

Background: The renin-angiotensin system involves many more enzymes, receptors and biologically active peptides than originally thought. With this study, we investigated whether angiotensin-(1-5) [Ang-(1-5)], a 5-amino acid fragment of angiotensin II, has biological activity, and through which receptor it elicits effects. Methods: The effect of Ang-(1-5) (1µM) on nitric oxide release was measured by DAF-FM staining in human aortic endothelial cells (HAEC), or Chinese Hamster Ovary (CHO) cells stably transfected with the angiotensin AT 2 -receptor (AT 2 R) or the receptor Mas. A potential vasodilatory effect of Ang-(1-5) was tested in mouse mesenteric and human renal arteries by wire myography; the effect on blood pressure was evaluated in normotensive C57BL/6 mice by Millar catheter. These experiments were performed in the presence or absence of a range of antagonists or inhibitors or in AT 2 R-knockout mice. Binding of Ang-(1-5) to the AT 2 R was confirmed and the preferred conformations determined by in silico docking simulations. The signaling network of Ang-(1-5) was mapped by quantitative phosphoproteomics. Results: Key findings included: (1) Ang-(1-5) induced activation of eNOS by changes in phosphorylation at Ser1177 eNOS and Tyr657 eNOS and thereby (2) increased NO release from HAEC and AT 2 R-transfected CHO cells, but not from Mas-transfected or non-transfected CHO cells. (3) Ang-(1-5) induced relaxation of preconstricted mouse mesenteric and human renal arteries and (4) lowered blood pressure in normotensive mice - effects which were respectively absent in arteries from AT 2 R-KO or in PD123319-treated mice and which were more potent than effects of the established AT 2 R-agonist C21. (5) According to in silico modelling, Ang-(1-5) binds to the AT 2 R in two preferred conformations, one differing substantially from where the first five amino acids within angiotensin II bind to the AT 2 R. (6) Ang-(1-5) modifies signaling pathways in a protective RAS-typical way and with relevance for endothelial cell physiology and disease. Conclusions: Ang-(1-5) is a potent, endogenous AT 2 R-agonist.

BRSET: A Brazilian Multilabel Ophthalmological Dataset of Retina Fundus Photos.

INTRODUCTION: The Brazilian Multilabel Ophthalmological Dataset (BRSET) addresses the scarcity of publicly available ophthalmological datasets in Latin America. BRSET comprises 16,266 color fundus retinal photos from 8,524 Brazilian patients, aiming to enhance data representativeness, serving as a research and teaching tool. It contains sociodemographic information, enabling investigations into differential model performance across demographic groups. METHODS: Data from three São Paulo outpatient centers yielded demographic and medical information from electronic records, including nationality, age, sex, clinical history, insulin use, and duration of diabetes diagnosis. A retinal specialist labeled images for anatomical features (optic disc, blood vessels, macula), quality control (focus, illumination, image field, artifacts), and pathologies (e.g., diabetic retinopathy). Diabetic retinopathy was graded using International Clinic Diabetic Retinopathy and Scottish Diabetic Retinopathy Grading. Validation used a ConvNext model trained during 50 epochs using a weighted cross entropy loss to avoid overfitting, with 70% training (20% validation), and 30% testing subsets. Performance metrics included area under the receiver operating curve (AUC) and Macro F1-score. Saliency maps were calculated for interpretability. RESULTS: BRSET comprises 65.1% Canon CR2 and 34.9% Nikon NF5050 images. 61.8% of the patients are female, and the average age is 57.6 (± 18.26) years. Diabetic retinopathy affected 15.8% of patients, across a spectrum of disease severity. Anatomically, 20.2% showed abnormal optic discs, 4.9% abnormal blood vessels, and 28.8% abnormal macula. A ConvNext V2 model was trained and evaluated BRSET in four prediction tasks: "binary diabetic retinopathy diagnosis (Normal vs Diabetic Retinopathy)" (AUC: 97, F1: 89); "3 class diabetic retinopathy diagnosis (Normal, Proliferative, Non-Proliferative)" (AUC: 97, F1: 82); "diabetes diagnosis" (AUC: 91, F1: 83); "sex classification" (AUC: 87, F1: 70). DISCUSSION: BRSET is the first multilabel ophthalmological dataset in Brazil and Latin America. It provides an opportunity for investigating model biases by evaluating performance across demographic groups. The model performance of three prediction tasks demonstrates the value of the dataset for external validation and for teaching medical computer vision to learners in Latin America using locally relevant data sources.

Platelet transcription factors license the pro-inflammatory cytokine response of human monocytes.

In humans, blood Classical CD14+ monocytes contribute to host defense by secreting large amounts of pro-inflammatory cytokines. Their aberrant activity causes hyper-inflammation and life-threatening cytokine storms, while dysfunctional monocytes are associated with 'immunoparalysis', a state of immune hypo responsiveness and reduced pro-inflammatory gene expression, predisposing individuals to opportunistic infections. Understanding how monocyte functions are regulated is critical to prevent these harmful outcomes. We reveal platelets' vital role in the pro-inflammatory cytokine responses of human monocytes. Naturally low platelet counts in patients with immune thrombocytopenia or removal of platelets from healthy monocytes result in monocyte immunoparalysis, marked by impaired cytokine response to immune challenge and weakened host defense transcriptional programs. Remarkably, supplementing monocytes with fresh platelets reverses these conditions. We discovered that platelets serve as reservoirs of key cytokine transcription regulators, such as NF-κB and MAPK p38, and pinpointed the enrichment of platelet NF-κB2 in human monocytes by proteomics. Platelets proportionally restore impaired cytokine production in human monocytes lacking MAPK p38α, NF-κB p65, and NF-κB2. We uncovered a vesicle-mediated platelet-monocyte-propagation of inflammatory transcription regulators, positioning platelets as central checkpoints in monocyte inflammation.

Image quality comparison of AirDoc portable retina camera versus eyer in a diabetic retinopathy screening program.

BACKGROUND: Diabetic retinopathy (DR) stands as the foremost cause of preventable blindness in adults. Despite efforts to expand DR screening coverage in the Brazilian public healthcare system, challenges persist due to various factors including social, medical, and financial constraints. Our objective was to evaluate the quality of images obtained with the AirDoc, a novel device, compared to Eyer portable camera which has already been clinically validated. METHODS: Images were captured by two portable retinal devices: AirDoc and Eyer. The included patients had their fundus images obtained in a screening program conducted in Blumenau, Santa Catarina. Two retina specialists independently assessed image's quality. A comparison was performed between both devices regarding image quality and the presence of artifacts. RESULTS: The analysis included 129 patients (mean age of 61 years), with 29 (43.28%) male and an average disease duration of 11.1 ± 8 years. In Ardoc, 21 (16.28%) images were classified as poor quality, with 88 (68%) presenting artifacts; in Eyer, 4 (3.1%) images were classified as poor quality, with 94 (72.87%) presenting artifacts. CONCLUSIONS: Although both Eyer and AirDoc devices show potential as screening tools, the AirDoc images displayed higher rates of ungradable and low-quality images, that may directly affect the DR and DME grading. We must acknowledge the limitations of our study, including the relatively small sample size. Therefore, the interpretations of our analyses should be approached with caution, and further investigations with larger patient cohorts are warranted to validate our findings.

Adult transverse sinus capillary hemangioma: case report and review of the literature.

BACKGROUND: Adult intracranial capillary hemangioma (ICH) is an extremely rare disease with very few cases reported in the literature. Natural history is poorly understood and therapeutic management has not been clearly defined. METHODS: Using PRISMA guidelines, we systematically reviewed all published adult cases of ICH, to which we added our own case. CASE PRESENTATION: A 24-year-old patient with intracranial hypertension underwent stenting for left transverse sinus ICH. Recurrence was managed by subtotal resection, and radiotherapy was undertaken after a second relapse. Radiotherapy achieved complete response at last follow-up. RESULTS: Among cases of ICH found in the literature, 36 concerned adults (55.3%), with clear female predominance, and only 2 cases affecting the transverse sinus (8.1%). Adult ICHs grew over time, and pregnancy seemed to accelerate natural progression. Complete resection was achieved in most cases, and radiotherapy was used in case of relapse, with high rates of tumor control. CONCLUSION: Transverse sinus ICH is uncommon, and venous stenting is a suitable option in case of tumor invasion to treat intracranial hypertension. Surgery is the gold-standard treatment, and radiotherapy is a very effective alternative, with high rates of tumor control. Natural history is not benign, particularly in case of pregnancy.

Measurements of Impoverishing and Catastrophic Surgical Health Expenditures in Low- and Middle-Income Countries and Reduction Interventions in the Last 30 Years: A Systematic Review.

INTRODUCTION: Approximately 33 million people suffer catastrophic health expenditure (CHE) from surgery and/or anesthesia costs. The aim of this systematic review is to evaluate catastrophic and impoverishing expenditure associated with surgery and anesthesia in low- and middle-income countries (LMICs). METHODS: We performed a systematic review of all studies from 1990 to 2021 that reported CHE in LMICs for treatment of a condition requiring surgical intervention, including cesarean section, trauma care, and other surgery. RESULTS: 77 studies met inclusion criteria. Tertiary facilities (23.4%) were the most frequently studied facility type. Only 11.7% of studies were conducted in exclusively rural health-care settings. Almost 60% of studies were retrospective in nature. The cost of procedures ranged widely, from $26 USD for a cesarean section in Mauritania in 2020 to $74,420 for a pancreaticoduodenectomy in India in 2018. GDP per capita had a narrower range from $315 USD in Malawi in 2019 to $9955 USD in Malaysia in 2015 (Median = $1605.50, interquartile range = $1208.74). 35 studies discussed interventions to reduce cost and catastrophic expenditure. Four of those studies stated that their intervention was not successful, 18 had an unknown or equivocal effect on cost and CHE, and 13 concluded that their intervention did help reduce cost and CHE. CONCLUSIONS: CHE from surgery is a worldwide problem that most acutely affects vulnerable patients in LMICs. Existing efforts are insufficient to meet the true need for affordable surgical care unless assistance for ancillary costs is given to patients and families most at risk from CHE.

Impact of preaneurysmal M1 length in unruptured middle cerebral artery aneurysm: mid-term outcome and single-center experience.

OBJECTIVE: This study was design to investigate the surgical and functional outcome based on the preaneurysmal M1 length for unruptured MCA aneurysm. METHODS: Among 250 consecutive patients with unruptured aneurysms operated in our institution between 2015 and 2017, 72 were MCA aneurysms. Risk factors for IR (i.e., intraoperative rupture) were investigated including age, sex, preaneurysmal M1 length, maximal MCA aneurysm diameter, neck size, aneurysm shape, sphenoid ridge proximation sign. Outcome was measured at discharge, 1 yr and last follow-up. Outcome was compared according to the preaneurysmal M1 length. RESULTS: Among 68 patients included, five patients (7.3%) suffered IR. Mean maximal diameter of MCA aneurysm (7.9 mm ± 3.4 vs. 4.5 ± 1.8; p = 0.01) was significantly associated with IR risk. Mean M1 length seemed to be shorter in the IR group although not statistically significant (16.2 mm ± 5.1 vs. 11.5 mm ± 4.8; p = 0.053). Mid-term outcome was favorable for all patients at last follow-up but was worsen in case of short preaneurysmal M1 segment (10.7 mm ± 4.8 vs. 16.4 mm ± 5.3, p = 0.02). Complete aneurysm occlusion was achieved for sixty-nine patients (95.5%) with 6.9% of early postoperative complications. CONCLUSIONS: The microsurgical treatment of unruptured MCA aneurysm was associated with favorable mid-term outcome in all patients and high rates of complete occlusion. Aneurysm size was significantly associated with the intraoperative rupture risk for unruptured MCA aneurysm and patients with a short preaneurysmal M1 segment seemed to have a greater risk of intraoperative rupture although not statistically significant. Short preaneurysmal M1 patients had worsen mid-term outcome.

Automated Identification of Different Severity Levels of Diabetic Retinopathy Using a Handheld Fundus Camera and Single-Image Protocol.

Purpose: To evaluate the performance of artificial intelligence (AI) systems embedded in a mobile, handheld retinal camera, with a single retinal image protocol, in detecting both diabetic retinopathy (DR) and more-than-mild diabetic retinopathy (mtmDR). Design: Multicenter cross-sectional diagnostic study, conducted at 3 diabetes care and eye care facilities. Participants: A total of 327 individuals with diabetes mellitus (type 1 or type 2) underwent a retinal imaging protocol enabling expert reading and automated analysis. Methods: Participants underwent fundus photographs using a portable retinal camera (Phelcom Eyer). The captured images were automatically analyzed by deep learning algorithms retinal alteration score (RAS) and diabetic retinopathy alteration score (DRAS), consisting of convolutional neural networks trained on EyePACS data sets and fine-tuned using data sets of portable device fundus images. The ground truth was the classification of DR corresponding to adjudicated expert reading, performed by 3 certified ophthalmologists. Main Outcome Measures: Primary outcome measures included the sensitivity and specificity of the AI system in detecting DR and/or mtmDR using a single-field, macula-centered fundus photograph for each eye, compared with a rigorous clinical reference standard comprising the reading center grading of 2-field imaging protocol using the International Classification of Diabetic Retinopathy severity scale. Results: Of 327 analyzed patients (mean age, 57.0 ± 16.8 years; mean diabetes duration, 16.3 ± 9.7 years), 307 completed the study protocol. Sensitivity and specificity of the AI system were high in detecting any DR with DRAS (sensitivity, 90.48% [95% confidence interval (CI), 84.99%-94.46%]; specificity, 90.65% [95% CI, 84.54%-94.93%]) and mtmDR with the combination of RAS and DRAS (sensitivity, 90.23% [95% CI, 83.87%-94.69%]; specificity, 85.06% [95% CI, 78.88%-90.00%]). The area under the receiver operating characteristic curve was 0.95 for any DR and 0.89 for mtmDR. Conclusions: This study showed a high accuracy for the detection of DR in different levels of severity with a single retinal photo per eye in an all-in-one solution, composed of a portable retinal camera powered by AI. Such a strategy holds great potential for increasing coverage rates of screening programs, contributing to prevention of avoidable blindness. Financial Disclosures: F.K.M. is a medical consultant for Phelcom Technologies. J.A.S. is Chief Executive Officer and proprietary of Phelcom Technologies. D.L. is Chief Technology Officer and proprietary of Phelcom Technologies. P.V.P. is an employee at Phelcom Technologies.

Turbulence hierarchy in foreign exchange markets.

We present a multiscale stochastic analysis of foreign exchange rates using the H-theory formalism, which provides a hierarchical intermittency model for the information cascade in the currency market. We examine the distributions of returns and volatilities for the three most traded currency pairs: euro-U.S. dollar, U.S. dollar-Japanese yen, and British pound-U.S. dollar. We find that these markets have a hierarchy of timescales, with larger markets exhibiting more hierarchy levels. We provide a theoretical framework for understanding why the number of levels in the information cascade increases with market size, in analogy with similar behavior for the energy cascade in turbulence as a function of Reynolds number. We briefly argue that using turbulence-like models for financial markets can also provide valuable insights for developing efficient algorithmic trading strategies.

Automated machine learning model for fundus image classification by health-care professionals with no coding experience.

To assess the feasibility of code-free deep learning (CFDL) platforms in the prediction of binary outcomes from fundus images in ophthalmology, evaluating two distinct online-based platforms (Google Vertex and Amazon Rekognition), and two distinct datasets. Two publicly available datasets, Messidor-2 and BRSET, were utilized for model development. The Messidor-2 consists of fundus photographs from diabetic patients and the BRSET is a multi-label dataset. The CFDL platforms were used to create deep learning models, with no preprocessing of the images, by a single ophthalmologist without coding expertise. The performance metrics employed to evaluate the models were F1 score, area under curve (AUC), precision and recall. The performance metrics for referable diabetic retinopathy and macular edema were above 0.9 for both tasks and CDFL. The Google Vertex models demonstrated superior performance compared to the Amazon models, with the BRSET dataset achieving the highest accuracy (AUC of 0.994). Multi-classification tasks using only BRSET achieved similar overall performance between platforms, achieving AUC of 0.994 for laterality, 0.942 for age grouping, 0.779 for genetic sex identification, 0.857 for optic, and 0.837 for normality with Google Vertex. The study demonstrates the feasibility of using automated machine learning platforms for predicting binary outcomes from fundus images in ophthalmology. It highlights the high accuracy achieved by the models in some tasks and the potential of CFDL as an entry-friendly platform for ophthalmologists to familiarize themselves with machine learning concepts.

Retrospective case series of high-density silicone oil (Oxane HD) in severe proliferative vitreorretinal retinal detachment patients.

BACKGROUND: Describe complications and clinical outcomes of heavy silicone oil (HSO) Oxane HD® use as an alternative to overcome the challenges of performing vitrectomy to treat tractional and rhegmatogenous retinal detachments with proliferative vitreoretinopathy (PVR). METHODS: A retrospective, observational study was performed on patients from one center from August 2014 to Aug 2023. It was included patients who underwent surgery using HSO Oxane HD® to treat rhegmatogenous retinal detachment with PVR or mixed tractional and rhegmatogenous diabetic retinal detachment. Severely ill patients who could not attend to follow up were excluded. The primary outcome was successful retinal attachment at first postoperative month. A descriptive analysis was performed. RESULTS: Among the 31 patients, 29 (93.5%) underwent surgeries due to rhegmatogenous retinal detachment and two (6.5%) for diabetic retinal detachment. The primary anatomic success was achieved in 27 (87.1%) patients. At the final visit, 17 (56.6%) had vision better than 20/400 (range, 20/30 to light perception). The vision was stable or improved in 22 (76.8%) patients at the end of follow-up. Nineteen (61.3%) patients required hypotensive eye drops after HSO use and twelve (38.7%) still required hypotensive eye drops at the final follow-up; three (9.7%) patients required additional glaucoma surgeries. CONCLUSIONS: HSO is safe and useful for complex retinal detachments cases specially with inferior tears and PVR. Ocular hypertension is frequent and usually clinically controlled with hypotensive eyedrops. Close postoperatively follow-up is advised due to the ocular complications, particularly elevated intraocular pressure and emulsification.

BRSET: A Brazilian Multilabel Ophthalmological Dataset of Retina Fundus Photos.

Introduction: The Brazilian Multilabel Ophthalmological Dataset (BRSET) addresses the scarcity of publicly available ophthalmological datasets in Latin America. BRSET comprises 16,266 color fundus retinal photos from 8,524 Brazilian patients, aiming to enhance data representativeness, serving as a research and teaching tool. It contains sociodemographic information, enabling investigations into differential model performance across demographic groups. Methods: Data from three São Paulo outpatient centers yielded demographic and medical information from electronic records, including nationality, age, sex, clinical history, insulin use, and duration of diabetes diagnosis. A retinal specialist labeled images for anatomical features (optic disc, blood vessels, macula), quality control (focus, illumination, image field, artifacts), and pathologies (e.g., diabetic retinopathy). Diabetic retinopathy was graded using International Clinic Diabetic Retinopathy and Scottish Diabetic Retinopathy Grading. Validation used Dino V2 Base for feature extraction, with 70% training and 30% testing subsets. Support Vector Machines (SVM) and Logistic Regression (LR) were employed with weighted training. Performance metrics included area under the receiver operating curve (AUC) and Macro F1-score. Results: BRSET comprises 65.1% Canon CR2 and 34.9% Nikon NF5050 images. 61.8% of the patients are female, and the average age is 57.6 years. Diabetic retinopathy affected 15.8% of patients, across a spectrum of disease severity. Anatomically, 20.2% showed abnormal optic discs, 4.9% abnormal blood vessels, and 28.8% abnormal macula. Models were trained on BRSET in three prediction tasks: "diabetes diagnosis"; "sex classification"; and "diabetic retinopathy diagnosis". Discussion: BRSET is the first multilabel ophthalmological dataset in Brazil and Latin America. It provides an opportunity for investigating model biases by evaluating performance across demographic groups. The model performance of three prediction tasks demonstrates the value of the dataset for external validation and for teaching medical computer vision to learners in Latin America using locally relevant data sources.

Neuroproteomics: Unveiling the Molecular Insights of Psychiatric Disorders with a Focus on Anxiety Disorder and Depression.

Anxiety and depression are two of the most common mental disorders worldwide, with a lifetime prevalence of up to 30%. These disorders are complex and have a variety of overlapping factors, including genetic, environmental, and behavioral factors. Current pharmacological treatments for anxiety and depression are not perfect. Many patients do not respond to treatment, and those who do often experience side effects. Animal models are crucial for understanding the complex pathophysiology of both disorders. These models have been used to identify potential targets for new treatments, and they have also been used to study the effects of environmental factors on these disorders. Recent proteomic methods and technologies are providing new insights into the molecular mechanisms of anxiety disorder and depression. These methods have been used to identify proteins that are altered in these disorders, and they have also been used to study the effects of pharmacological treatments on protein expression. Together, behavioral and proteomic research will help elucidate the factors involved in anxiety disorder and depression. This knowledge will improve preventive strategies and lead to the development of novel treatments.

Bibliometric Analysis of Cannabis sativa Research: Trends, Challenges, and Future Directions.

Introduction: The use of medical Cannabis remains unregulated in several countries due to the scarcity of clinical studies with high scientific evidence that establish safety and efficacy of Cannabis products. This study aimed to comprehensively analyze how knowledge has been created in this field, as well as perform a bibliographic mapping to identify knowledge gaps, and investigate key authors and journals that have significantly contributed to advancing our understanding of Cannabis. Method: The study protocol was registered in the International Prospective Register of Systematic Review (CRD42020223084). A systematic search was conducted in the Cochrane Central Register of Controlled Trials, Lilacs, Google Scholar, PubMed, SciELO, Scopus, and Web of Science databases. The bibliographic analysis and mapping were registered using the VOSviewer, Sci2tool, CiteSpace, and PoP software. Results: The systematic search identified 27,597 records, with 17,020 duplicates, resulting in a total of 10,577 articles included. The authors who published the most were Marilyn Ann Huestis (n=108) and Sagnik Bhattacharyya (n=71), while Elisaldo A. Carlini and Raphael Mechoulam published 8 and 22 articles, respectively. The journals Drug and Alcohol Dependence (n=297), Psychopharmacology (n=159) and Addictive Behaviors (n=150) were the ones that published the most on Cannabis. The journals suggest that the articles are correlated with the adverse and toxicological effects of recreational Cannabis use; however, most articles focus on medical Cannabis. The peak of publications was in 2021 (n=1,481). The countries that published the most were the United States (n=9,735), while Brazil occupied the 11th position (n=422). Most publications were carried out in "Pharmacology and Pharmacy" (11.31%), followed by "Psychiatry" (7.66%) and "Medicine" (5.80%). The areas of "Neurosciences" (1.59%), "Biochemistry," "Genetics," and "Molecular Biology" (0.79%) were little explored. Conclusion: This study captured the characteristics of publications about Cannabis and clinical studies in the scientific literature, yielding >10,000 articles, representing a large literature review, to date. Therefore, the most productive countries included the United States, the United Kingdom, and Canada, while the most productive authors were Marilyn Ann Huestis and Sagnik Bhattacharyya, with a peak of publications in 2021. Finally, the most chosen journals were Drug and Alcohol Dependence and Psychopharmacology.

Impact of low-level laser therapy on the quality of life of patients with xerostomia undergoing head and neck radiotherapy: a systematic review.

PURPOSE: To carry out a systematic review to assess whether low-level laser therapy can improve the quality of life of patients with xerostomia undergoing head and neck radiotherapy. METHODS: A systematic search was performed through Embase, Medline/PubMed, Cochrane, Scopus, Web of Science, nonpeer-reviewed clinicaltrials.gov and LILACS. The strategy included clinical studies were selected that prospectively followed or evaluated the quality of life by directly comparing the use of low-level laser therapy for xerostomia induced by head and neck radiotherapy with alternative therapies without the use of a laser. The risk of bias in the studies was assessed by RoB 2.0 and Robins I. RESULTS: After all application of the predetermined criteria, four studies were included, dated between the years 2014 and 2023. Three studies described as randomized clinical trials were included, one of which was a randomized pilot study and only one was a prospective clinical trial. A total of 126 patients were evaluated, all four studies used the infrared wavelength, with two studies using the combination with the red wavelength. It was observed that low-level laser therapy can change the sensation of dry mouth, improving patients' quality of life. In addition, changes related to increased stimulated and unstimulated salivary flow were also identified. CONCLUSION: The use of low-level laser therapy has promising results on xerostomia, consequently improving the quality of life of patients undergoing radiotherapy in the head and neck region.

Breath-holding as model for the evaluation of EEG signal during respiratory distress.

PURPOSE: Research describes the existence of a relationship between cortical activity and the regulation of bulbar respiratory centers through the evaluation of the electroencephalographic (EEG) signal during respiratory challenges. For example, we found evidences of a reduction in the frequency of the EEG (alpha band) in both divers and non-divers during apnea tests. For instance, this reduction was more prominent in divers due to the greater physiological disturbance resulting from longer apnea time. However, little is known about EEG adaptations during tests of maximal apnea, a test that voluntarily stops breathing and induces dyspnea. RESULTS: Through this mini-review, we verified that a protocol of successive apneas triggers a significant increase in the maximum apnea time and we hypothesized that successive maximal apnea test could be a powerful model for the study of cortical activity during respiratory distress. CONCLUSION: Dyspnea is a multifactorial symptom and we believe that performing a successive maximal apnea protocol is possible to understand some factors that determine the sensation of dyspnea through the EEG signal, especially in people not trained in apnea.

An emergency room influx and trauma cases prediction in a Brazilian ophthalmological hospital by an ophthalmologist without code experience / Predição do influxo de atendimentos e casos de trauma em um serviço de urgência oftalmológico brasileiro realizado por um oftalmologista sem experiência em programação

ABSTRACT Purpose: The emergency medical service is a fundamental part of healthcare, albeit crowded emergency rooms lead to delayed and low-quality assistance in actual urgent cases. Machine-learning algorithms can provide a smart and effective estimation of emergency patients' volume, which was previously restricted to artificial intelligence (AI) experts in coding and computer science but is now feasible by anyone without any coding experience through auto machine learning. This study aimed to create a machine-learning model designed by an ophthalmologist without any coding experience using AutoML to predict the influx in the emergency department and trauma cases. Methods: A dataset of 356,611 visits at Hospital da Universidade Federal de São Paulo from January 01, 2014 to December 31, 2019 was included in the model training, which included visits/day and the international classification disease code. The training and prediction were made with the Amazon Forecast by 2 ophthalmologists with no prior coding experience. Results: The forecast period predicted a mean emergency patient volume of 216.27/day in p90, 180.75/day in p50, and 140.35/day in p10, and a mean of 7.42 trauma cases/ day in p90, 3.99/day in p50, and 0.56/day in p10. In January of 2020, there were a total of 6,604 patient visits and a mean of 206.37 patients/day, which is 13.5% less than the p50 prediction. This period involved a total of 199 trauma cases and a mean of 6.21 cases/day, which is 55.77% more traumas than that by the p50 prediction. Conclusions: The development of models was previously restricted to data scientists' experts in coding and computer science, but transfer learning autoML has enabled AI development by any person with no code experience mandatory. This study model showed a close value to the actual 2020 January visits, and the only factors that may have influenced the results between the two approaches are holidays and dataset size. This is the first study to apply AutoML in hospital visits forecast, showing a close prediction of the actual hospital influx.

RESUMO Objetivo: Esse estudo tem como objetivo criar um modelo de Machine Learning por um oftalmologista sem experiência em programação utilizando auto Machine Learning predizendo influxo de pacientes em serviço de emergência e casos de trauma. Métodos: Um dataset de 366,610 visitas em Hospital Universitário da Universidade Federal de São Paulo de 01 de janeiro de 2014 até 31 de dezembro de 2019 foi incluído no treinamento do modelo, incluindo visitas/dia e código internacional de doenças. O treinamento e predição foram realizados com o Amazon Forecast por dois oftalmologistas sem experiência com programação. Resultados: O período de previsão estimou um volume de 206,37 pacientes/dia em p90, 180,75 em p50, 140,35 em p10 e média de 7,42 casos de trauma/dia em p90, 3,99 em p50 e 0,56 em p10. Janeiro de 2020 teve um total de 6.604 pacientes e média de 206,37 pacientes/dia, 13,5% menos do que a predição em p50. O período teve um total de 199 casos de trauma e média de 6,21 casos/dia, 55,77% mais casos do que a predição em p50. Conclusão: O desenvolvimento de modelos era restrito a cientistas de dados com experiencia em programação, porém a transferência de ensino com a tecnologia de auto Machine Learning permite o desenvolvimento de algoritmos por qualquer pessoa sem experiencia em programação. Esse estudo mostra um modelo com valores preditos próximos ao que ocorreram em janeiro de 2020. Fatores que podem ter influenciados no resultado foram feriados e tamanho do banco de dados. Esse é o primeiro estudo que aplicada auto Machine Learning em predição de visitas hospitalares com resultados próximos aos que ocorreram.