Leaf morphometric analysis and potential distribution modelling contribute to taxonomic differentiation in the Quercus microphylla complex.

Mexico is a major center of evolutionary radiation for the genus Quercus, with oak species occurring across different habitat types and showing a wide variation in morphology and growth form. Despite representing about 20% of Mexican species, scrub oaks have received little attention and even basic aspects of their taxonomy and geographic distribution remain unresolved. In this study, we analyzed the morphological and climatic niche differentiation of scrub oak populations forming a complex constituted by six named species, Quercus cordifolia, Quercus frutex, Quercus intricata, Quercus microphylla, Quercus repanda, Quercus striatula and a distinct morphotype of Q. striatula identified during field and herbarium work (hereafter named Q. striatula II). Samples were obtained from 35 sites covering the geographic distribution of the complex in northern and central Mexico. Morphological differentiation was analyzed through geometric morphometrics of leaf shape and quantification of trichome traits. Our results indicated the presence of two main morphological groups with geographic concordance. The first was formed by Q. frutex, Q. microphylla, Q. repanda and Q. striatula, distributed in the Trans-Mexican Volcanic Belt, the Sierra Madre Occidental and a little portion of the south of the Mexican Altiplano (MA). The second group consists of Q. cordifola, Q. intricata and Q. striatula II, found in the Sierra Madre Oriental and the MA. Therefore, our evidence supports the distinctness of the Q. striatula II morphotype, indicating the need for a taxonomic revision. Within the two groups, morphological differentiation among taxa varied from very clear to low or inexistent (i.e. Q. microphylla-Q. striatula and Q. cordifolia-Q. striatula II) but niche comparisons revealed significant niche differentiation in all pairwise comparisons, highlighting the relevance of integrative approaches for the taxonomic resolution of complicated groups such as the one studied here.

Plasmocitoma extramedular mamario. Reporte de caso y revisión de la literatura / Extramedullary plasmacytoma of the breast: case report and literature review / Plasmocitoma extramedular mamário: relato de caso e revisão da literatura

El plasmocitoma extramedular es una neoplasia infrecuente y el compromiso mamario es en extremo raro, con alrededor de 83 casos reportados desde 1928. Se presenta el caso de una paciente de 63 años con antecedente de mieloma múltiple, con cuadro clínico de un mes de evolución de masa blanda de 4.5 cm en la mama derecha, indolora, con progresión rápida. Se realizó ecografía mamaria con reporte Bi-RADS 4, por sospecha de malignidad se realizó biopsia y fue remitida al servicio de mastología. El estudio básico de patología e inmunohistoquímica concluye que la lesión corresponde a un plasmocitoma extramedular y luego de múltiples líneas de tratamiento oncológico el plasmocitoma mamario presenta una excelente respuesta clínica e imagenológica. Se hace la descripción del caso y la revisión de literatura.

Extramedullary plasmacytoma is a rare neoplasm, and involvement of the breast is extremely uncommon, with approximately 83 cases reported since 1928. We present the case of a 63-year-old patient with a history of multiple myeloma, who presented with a one-month history of a rapidly progressing, painless, soft mass measuring 4.5 cm in the right breast. Breast ultrasound showed a Bi-RADS 4 lesion, and due to suspicion of malignancy, a biopsy was performed and the patient was referred to the mastology department. Basic pathological and immunohistochemical studies concluded that the injury corresponded to an extramedullary plasmacytoma. After multiple lines of oncological treatment, the breast plasmacytoma showed an excellent clinical and imaging response. The case is described, and a literature review is presented.

O plasmocitoma extramedular é neoplasia pouco frequente e o acometimento mamário extremamente raro, com cerca de 83 casos relatados desde 1928. Apresentamos o caso de uma doente de 63 anos com antecedentes de mieloma múltiplo, com quadro clínico com um mês de evolução de uma massa mole de 4,5 cm na mama direita, indolor, de rápida evolução. Foi realizada ultrassonografia mamária com laudo Bi-RADS 4, realiza-da biópsia por suspeita de malignidade e encaminhada ao serviço de mastologia. O estudo básico de patologia e imuno-histoquímica conclui que a lesão corresponde a um plasmocitoma extramedular e após múltiplas linhas de tratamento oncológico, o plasmocitoma mamário apresenta uma excelente resposta clínica e imagiológica. É feita a descrição do caso e revisão da literatura.

Using Machine Learning Algorithms on Electroencephalographic Signals to Assess Engineering Students' Focus While Solving Math Exercises / Uso de Algoritmos de Aprendizaje Automático en Señales Electroencefalográficas para Evaluar la Concentración de Estudiantes de Ingeniería al Resolver Ejercicios Matemáticos

Abstract In this paper, we present an attention classification method using Machine-Learning Algorithms. The EEG signals were recorded from ten engineering students with an EPOC+BCI using the electrodes F3, F4, P7, and P8 while solving some mathematical operations. The recording time for these activities is around 20 minutes. Next, a similar time EEG register is obtained while doing non-academic activities, such as chattering with the staff, checking cell phones, or playing a video game. With these EEG registers, we obtained a set of features to train and evaluate attention using Machine Learning algorithms. This research shows how engineering students interact with math topics in solving mental operations and complex reasoning by increasing brain domain and knowledge for mathematical reasoningrelated processes, such as sustained and shifting attention and logical constructions for object interaction during operations resolution. The Random Forest algorithm (RF) obtained the highest accuracy with 0.7392, an F1 Score of 0.7430, and the highest Specificity/Accuracy with 0.7261.

Resumen Se presenta un método de clasificación de la atención utilizando algoritmos de aprendizaje automático. Con las señales EEG de diez estudiantes de ingeniería adquiridas utilizando los electrodos F3, F4, P7 y P8 de una BCI EPOC+ mientras resuelven productos escalares, multiplicaciones algebraicas simples, simplificaciones e integrales por aproximadamente 20 minutos. Posteriormente, se obtiene un registro EEG de tiempo similar mientras se realizan actividades no académicas, como charlar con el personal, consultar el móvil o jugar a un videojuego. Se obtienen algunas características/parámetros, se entrenan y evalúan varios algoritmos de aprendizaje automático para la clasificación de la atención. Los resultados de esta investigación pueden mejorar la forma en que los estudiantes de ingeniería interactúan con los temas matemáticos en la resolución de operaciones mentales y razonamientos complejos, aumentando el dominio y el conocimiento cerebral para los procesos relacionados con el razonamiento matemático, como la atención sostenida y cambiante y las construcciones lógicas para la interacción con objetos durante la resolución de operaciones. El clasificador Random Forest obtuvo la mayor precisión con 0.7392, una puntuación F1 de 0.7430 y la mayor especificidad/precisión con 0.7261.

Sensor for Real-Time Glucose Measurement in Aqueous Media based on Nanomaterials Incorporating an Artificial Neural Network Algorithm on a System-On-Chip / Sensor para Medición de Glucosa en Tiempo Real para Medios Acuosos basado en Nanomateriales Incorporando un Algoritmo de Red Neuronal Artificial en un Sistema en Chip

Abstract The aim of this paper is to present the development of a real-time measurement system for glucose in aqueous media. The proposed system incorporates two lines of research: i) design, synthesis, and implementation of a non-enzymatic electrochemical sensor of Multi-Walled Carbon Nanotubes with Copper nanoparticles (MWCNT-Cu) and ii) design and implementation of a machine learning algorithm based on an Artificial Neural Network Multilayer Perceptron (ANN-MLP), which is embedded in an ESP32 SoC (System on Chip). From the current data that is extracted in real-time during the oxidation-reduction process to which an aqueous medium is subjected, it feeds the algorithm embedded in the ESP32 SoC to estimate the glucose value. The experimental results show that the nanostructured sensor improves the resolution in the amperometric response by identifying an ideal place for data collection. For its part, the incorporation of the algorithm based on an ANN embedded in a SoC provides a level of 97.8 % accuracy in the measurements. It is concluded that incorporating machine learning algorithms embedded in low-cost SoC in complex experimental processes improves data manipulation, increases the reliability of results, and adds portability.

Resumen El objetivo de este artículo es presentar el desarrollo de un sistema de medición en tiempo real de glucosa en medios acuosos. El sistema que se implementa incorpora dos lineas de investigación: i) diseño, síntesis e implementación de un sensor electroquímico no enzimático de Nanotubos de Carbono de Pared Múltiple con nanopartículas de Cobre (NTCPM-Cu) y ii) diseño e implementación de un algoritmo de aprendizaje automático basado en una Red Neuronal Perceptrón Multicapa (RN-PM), embebido en un ESP32 SoC (Sistema en Chip). Un dato de corriente que se extrae en tiempo real durante el proceso de oxidación-reducción a la que se somete un medio acuoso, alimenta el algoritmo embebido en el ESP32 para estimar el valor de glucosa. De los resultados experimentales se demuestra que el sensor nanoestructurado mejora la resolución en la respuesta amperométrica al identificar un lugar ideal para la toma de datos. Por su parte, la incorporación del algoritmo basado en una RN embebido en SoC otorga un nivel de 97.8 % de exactitud en la mediciones. Se concluye que incorporar algoritmos de aprendizaje automático embebidos en SoC de bajo costo en procesos experimentales complejos, mejora la manipulación de datos, incrementa la confiabilidad en resultados y adiciona portabilidad.

Epidemiology and Mortality of Cryptococcal Disease in Guatemala: Two-Year Results of a Cryptococcal Antigen Screening Program.

Cryptococcal disease is an important opportunistic infection among people living with HIV. The cryptococcal antigen (CrAg) can be detected before the clinical onset of meningitis and its screening is recommended. Here, we evaluated CrAg frequency, and describe the epidemiological characteristics and mortality at 180 days in a cohort of HIV patients from Guatemala. A total of 3457 patients were screened with a CrAg lateral flow assay in serum between January 2017 and December 2018. CrAg positivity was 11.5% in patients with ≤100 CD4/mm3, 8.7% in patients with <200 CD4/mm3, and 6.3% in patients with <350 CD4/mm3. In Latin America, we estimated 9.2% CrAg positivity (IC95% 7.9−10.7%) in patients with ≤100 CD4/mm3. Among patients newly diagnosed with HIV, we estimated 4416 incident cases per year in Latin America in those with <200 CD4/mm3 and 5289 in those with <350 CD4/mm3. In addition, we calculated the burden in people not on ARV or without viral suppression and found 28,672 cases. CrAg screening should be considered in patients who have a CD4 cell count < 350 cells/mm3. Cryptococcal meningitis was associated with 30.8% mortality in Guatemala. Global access to diagnosis as well as to liposomal amphotericin B and flucytosine is a priority.

Incidence of Histoplasmosis in a Cohort of People with HIV: From Estimations to Reality.

Among people with HIV, histoplasmosis represents an important cause of mortality. Previous studies provided estimates of the disease incidence. Here, we compared those estimates with the results obtained from a screening program implemented in Guatemala, which included histoplasmosis detection for people with HIV. To compare the results of this program with previous estimations, a literature search was performed and reports concerning histoplasmosis incidence were analyzed. The screening program enrolled 6366 patients. The overall histoplasmosis incidence in the screening program was 7.4%, which was almost double that estimated in previous studies. From 2017 to 2019, the screening program showed an upward trend in histoplasmosis cases from 6.5% to 8.8%. Histoplasmosis overall mortality among those who were newly HIV diagnosed showed a decrease at 180 days from 32.8% in 2017 to 21.2% in 2019. The screening approach using rapid diagnostic assays detects histoplasmosis cases more quickly, allowing a specific treatment to be administered, which decreases the mortality of the disease. Therefore, the use of these new techniques, especially in endemic areas of histoplasmosis, must be implemented.

Impact of the COVID-19 pandemic on HIV care in Guatemala.

OBJECTIVES: To describe the impact of the coronavirus disease 2019 (COVID-19) pandemic on the diagnosis of human immunodeficiency virus (HIV) and deaths from opportunistic infections in Guatemala. METHODS: A retrospective study was conducted to investigate the impact of the COVID-19 pandemic on people with HIV at a referral clinic (Clinica Familiar Luis Angel García, CFLAG), as well as the disruption of services at a diagnostic laboratory hub (DLH) which provides diagnosis for opportunistic infections to a network of 13 HIV healthcare facilities. Comparative analysis was undertaken using the months March-August from two different time periods: (i) pre-COVID-19 (2017-2019); and (ii) during the COVID-19 period (2020). RESULTS: During the COVID-19 period, 7360 HIV tests were performed at Clinica Familiar Luis Angel García, compared with an average of 16,218 tests in the pre-COVID-19 period; a reduction of 54.7% [95% confidence interval (CI) 53.8-55.4%],Deaths from opportunistic infections at 90 days were 10.7% higher in 2020 compared with 2019 (27.3% vs 16.6%; P = 0.05). Clinical samples sent to the DLH for diagnosis of opportunistic infections decreased by 43.7% in 2020 (95% CI 41.0-46.2%). CONCLUSION: The COVID-19 pandemic is having a substantial impact on HIV care in Guatemala. Diagnostic services for HIV have been severely affected and deaths from opportunistic infections have increased. The lessons learnt must guide the introduction of strategies to reduce the impact of the pandemic.

A Rapid Screening Program for Histoplasmosis, Tuberculosis, and Cryptococcosis Reduces Mortality in HIV Patients from Guatemala.

Opportunistic infections (OIs) and advanced HIV disease (AHD) contribute to HIV-related mortality. Here, we analyzed the situation of AHD and OIs in a cohort of newly diagnosed HIV patients from Guatemala. We included 2127 adult patients from 13 facilities across the country during 2017 to 2018. Patients were screened for tuberculosis (TB), nontuberculous mycobacteria (NTM), histoplasmosis, and cryptococcal disease, independently of their CD4 cell count. Of the 2127 enrolled patients, 1682 (79.1%) had a CD4 cell count available; of which 52% presented with AHD. Of the Mayan population, 65% had AHD. The overall OI incidence was 21%. Histoplasmosis was the most frequent OI (7.9%), followed by TB (7.1%); 94.4% of these infections occurred in patients with a CD4 < 350 cells/mm3. Mortality at 180 days was significantly higher in those with OIs than without OIs (29.7% vs. 5.9%, p < 0.0001). In one year, this program decreased the OI mortality by 7% and increased the OI treatment by 5.1%. Early OI diagnosis and appropriate therapy reduced OI mortality among newly diagnosed HIV patients in Guatemala. Screening for OIs should be considered in all newly diagnosed HIV patients who have a CD4 cell count < 350 cells/mm3 or those without a CD4 cell count available. To improve results, interventions such as early HIV detection and access to flucytosine and liposomal amphotericin B are required.

Comparative performance of the laboratory assays used by a Diagnostic Laboratory Hub for opportunistic infections in people living with HIV.

OBJECTIVES: We evaluated the comparative performance of different assays used in a Diagnostic Laboratory Hub that linked 13 HIV healthcare facilities for the diagnosis of tuberculosis (TB), histoplasmosis, and cryptococcosis, and describing its functions in Guatemala compared with other National Reference Laboratories. METHODS: The following diagnostic techniques were analyzed in 24 months (2017-2018) in a cohort of patients with HIV: smear microscopy, mycobacterial and fungal cultures, isolator blood culture, PCR assays, and antigen detection tests. RESULTS: A total of 4245 patients were included, 716 (16.2%) had an opportunistic infection: 249 (34.7%) TB, 40 (5.6%) nontuberculous mycobacteria, 227 (31.7%) histoplasmosis, 138 (19.3%) cryptococcosis, and 62 (8.6%) had multiple opportunistic infections. Two hundred sixty-three [92.6%; 95% confidence interval (CI), 89-95.1] of TB cases were diagnosed by PCR. Urine antigen assay detected 94% (95% CI, 89-96) of the disseminated histoplasmosis cases. A lateral flow assay to detect cryptococcal antigen diagnosed 97% (95% CI, 93.3-98.7%) of the cryptococcal cases. In 85 patients (51.5%) with a cerobrospinal fluid sample, cryptococcal meningitis was diagnosed in 55 (64.7%), of which 18 (32.7%) were only detected by cryptococcal antigen. CONCLUSION: Validated commercial antigen tests, as used in this program, should be the new gold standard for histoplasmosis and cryptococcosis diagnosis. In their absence, 35% of disseminated histoplasmosis and 32.7% of cryptococcal meningitis cases would have been missed. Patients with multiple opportunistic infections were frequently diagnosed and strategies should be designed to screen patients irrespective of their clinical presentation. In low resource settings, Diagnostic Laboratory Hubs can deliver quality diagnostics services in record time at affordable prices.

Design and Construction of an ROV for Underwater Exploration.

The design of a remotely operated vehicle (ROV) with a size of 18.41 cm × 29.50 cm × 33.50 cm, and a weight of 15.64 kg, is introduced herein. The main goal is to capture underwater video by remote control communication in real time via Ethernet protocol. The ROV moves under the six brushless motors governed through a smart PID controller (Proportional + Integral + Derivative) and by using pulse-wide modulation with short pulses of 1 µs to improve the stability of the position in relation to the translational, ascent or descent, and rotational movements on three axes to capture images of 800 × 640 pixels on a video graphic array standard. The motion control, 3D position, temperature sensing, and video capture are performed at the same time, exploiting the four cores of the Raspberry Pi 3, using the threading library for parallel computing. In such a way, experimental results show that the video capture stage can process up to 42 frames per second on a Raspberry Pi 3. The remote control of the ROV is executed under a graphical user interface developed in Python, which is suitable for different operating systems, such as GNU/Linux, Windows, Android, and OS X. The proposed ROV can reach up to 100 m underwater, thus solving the issue of divers who can only reach 30 m depth. In addition, the proposed ROV can be useful in underwater applications such as surveillance, operations, maintenance, and measurement.

The uncertain future of protected lands and waters.

Protected areas are intended to safeguard biodiversity in perpetuity, yet evidence suggests that widespread legal changes undermine protected area durability and efficacy. We documented these legal changes-protected area downgrading, downsizing, and degazettement (PADDD) events-in the United States and Amazonian countries and compiled available data globally. Governments of the United States and Amazonian countries enacted 269 and 440 PADDD events, respectively. Between 1892 and 2018, 73 countries enacted 3749 PADDD events, removing 519,857 square kilometers from protection and tempering regulations in an additional 1,659,972 square kilometers; 78% of events were enacted since 2000. Most PADDD events (62%) are associated with industrial-scale resource extraction and development, suggesting that PADDD may compromise biodiversity conservation objectives. Strategic policy responses are needed to address PADDD and sustain effective protected areas.

Implementing a Chaotic Cryptosystem by Performing Parallel Computing on Embedded Systems with Multiprocessors.

Profiling and parallel computing techniques in a cluster of six embedded systems with multiprocessors are introduced herein to implement a chaotic cryptosystem for digital color images. The proposed encryption method is based on stream encryption using a pseudo-random number generator with high-precision arithmetic and data processing in parallel with collective communication. The profiling and parallel computing techniques allow discovery of the optimal number of processors that are necessary to improve the efficiency of the cryptosystem. That is, the processing speed improves the time for generating chaotic sequences and execution of the encryption algorithm. In addition, the high numerical precision reduces the digital degradation in a chaotic system and increases the security levels of the cryptosystem. The security analysis confirms that the proposed cryptosystem is secure and robust against different attacks that have been widely reported in the literature. Accordingly, we highlight that the proposed encryption method is potentially feasible to be implemented in practical applications, such as modern telecommunication devices employing multiprocessors, e.g., smart phones, tablets, and in any embedded system with multi-core hardware.