Phagocytosis: A Practical Approach for Evaluating Neutrophil Function in Health and Disease

Neutrophils, crucial players in the effector phase of the immune response, are recognized as important mediators of both innate and adaptive immune responses. Through the production of pro- and anti-inflammatory cytokines, they modulate the function of T and other lymphoid cells. Countless reports have highlighted the importance of these cells as efficient antimicrobial agents and annotated their involvement in the pathology of infectious and noninfectious diseases. The development of modern, sophisticated technologies has allowed the study of the functions of these cells in clinical settings. These advanced technologies include fluorescence-activated cell sorters, confocal microscopy, automated cell image analyzers, and live cell analysis instruments. Unfortunately, the cost of these modern instruments, maintenance, reagents, and the need for qualified technicians prohibit their use in low-income laboratories and universities in developing countries. With this in mind, we propose a series of basic tests that can be used in low-input clinical laboratories and universities to evaluate the function of neutrophils in health and disease. Our methodology allows us to assess in a practical and low-cost manner the functions of neutrophils in the phagocytic process, including opsonization, ingestion, ROI production (NBT reduction), myeloperoxidase content, phagosome-lysosome fusion, microbicidal activity, and NET production. Thus, under a disadvantageous ambiance, this may guide physicians in deciding whether a patient’s illness involves phagocytic defects without imposing a heavy financial burden.Graphical Abstract[-rId13-]

Microsurgical management of radicular cyst using guided tissue regeneration technique:A case report

BACKGROUND Radicular cyst is a lesion of odontogenic origin that arises from epithelial remains due to periapical periodontitis caused by inflammatory reactions generated at the apex of affected teeth with infected or necrotic pulps.The therapeutic mana gement of radicular cysts is controversial.There is only one case report of enucleation of a radicular cyst managed with microsurgery and apicoectomy,but without the use of the guided tissue regeneration(GTR)technique in the same surgical procedure.The present clinical case describes the management of a radicular cyst with microsurgical approach,performance of an apicoectomy of the tooth associated with the entity,application of GTR technique,use of a resorbable membrane of type I bovine collagen,and bovine xenograft.CASE SUMMARY A 68-year-old patient presented with a radicular cyst from an upper lateral incisor.The microsurgical management used was aimed at enucleating the chemical membrane,performing apicoectomy of the tooth along with careful and precise retrograde filling,and implementing GTR technique using a resorbable collagen membrane and bovine xenograft.The diagnosis of radicular cyst was confirmed using histopathological analysis.The patient underwent follow-up evaluations at 10 and 30 d postoperatively.At 4 months postoperative evaluation,she remained asymptomatic,and radiographs showed significant periapical healing with adequate bone formation.CONCLUSION These results suggest that microsurgical management using the GTR technique with collagen membrane and xenograft,contributes to bone regeneration.

Current concepts in ameloblastoma-targeted therapies in B-raf proto-oncogene serine/threonine kinase V600E mutation: Systematic review

BACKGROUND Ameloblastomas are common benign epithelial odontogenic neoplasms that present an aggressive and unpredictable behavior that may modify treatment strategies.Different signaling pathways that participate in the progression of these tumors have been identified.B-raf proto-oncogene serine/threonine kinase(BRAF)is a protein involved in the behavior of ameloblastomas,and it is related to many cell mechanisms.BRAF gene mutations have been identified in ameloblastomas,of which the BRAF V600E(valine substituted by glutamic acid at amino acid 600)mutation has been the most common and can be present concomitantly with other mutations that may be involved in its behavior.Targeted therapies have been used as an alternative in the case of resistance or contraindications to conventional treatments.AIM To document the presence of BRAF V600E and additional mutations,their behavior,and targeted therapies in these tumors.METHODS An electronic literature search was conducted according to PRISMA guidelines in PubMed/MEDLINE,Cochrane,EMBASE,and SpringerLink using the terms“ameloblastomas”,“BRAF V600E”,“additional mutations”,and“targeted therapies”.Ameloblastomas were classified according to WHO guidelines.Inclusion criteria were articles in English,published not more than 10 years ago,and studies with laboratory works related to BRAF V600E.Articles were evaluated by two independent reviewers and retrieved for full-text evaluation.The EBLIP Critical Appraisal Checklist was used to evaluate the quality of the eligible studies.Descriptive statistical analysis was performed.RESULTS Two independent reviewers,with a substantial concordance indicated by a kappa coefficient of k=0.76,evaluated a total of 19 articles that were included in this study.The analysis registered 521 conventional ameloblastomas(AM),81 unicystic ameloblastomas(UA),13 ameloblastic carcinomas(AC),three metastatic ameloblastomas(MA),and six peripheral ameloblastomas(PA),of which the histopathological type,anatomic location,laboratory tests,expression of BRAF mutation,and additional mutations were registered.The BRAF V600E mutation was found in 297 AM(57%),63 UA(77.7%),3 AC(23%),1 MA(50%),and 5 PA(83.3%).Follicular type predominated with a total of 116 cases(40%),followed by plexiform type with 63 cases(22.1%).Furthermore,both types presented additional mutations,in which alterations in JAK3 P132T,SMARCB1,PIK3CA,CTNNB1,SMO,and BRAF G606E genes were found.Four case reports were found with targeted therapy to BRAF V600E.CONCLUSION The identification of BRAF V600E and additional mutations as an aid in targeted therapies has been a breakthrough in alternative treatments of ameloblastomas where surgical treatments are contraindicated.

Serum levels of chemokines in adolescents with major depression treated with fluoxetine

BACKGROUND Major depressive disorder(MDD)is a global health issue that affects 350 million people of all ages.Although between 2%and 5.6%of affected individuals are adolescents,research on young patients is limited.The inflammatory response contributes to the onset of depression,and in adult MDD patients,symptom severity has been linked to chemokine levels.AIM To determine the differences in circulatory levels of chemokines in healthy volunteers(HVs)and adolescents with MDD,and assess the changes induced by fluoxetine consume.METHODS The 22 adolescents with MDD were monitored during the first 8 wk of clinical follow-up and clinical psychiatric evaluation was done using the Hamilton depresión rating scale(HDRS).The serum levels of monocyte chemoattractant protein-1(MCP-1),macrophage inflammatory protein(MIP)-1α,MIP-1β,interleukin(IL)-8,interferon gamma-induced protein(IP)-10,and eotaxin were measured in patients and HVs.RESULTS In all cases,significant differences were detected in circulating chemokine levels between patients before treatment and HVs(P<0.0001).All chemokines decreased at 4 wk,but only MCP-1 and IL-8 significantly differed(P<0.05)between 0 wk and 4 wk.In the patients,all chemokines rose to their initial concentrations by 8 wk vs 0 wk,but only IP-10 did so significantly(P<0.05).All patients experienced a significant decrease in HDRS scores at 4 wk(P<0.0001)and 8 wk(P<0.0001)compared with 0 wk.CONCLUSION Despite the consumption of fluoxetine,patients had significantly higher chemokine levels,even after considering the improvement in HDRS score.The high levels of eotaxin,IP-10,and IL-8 partially explain certain aspects that are affected in MDD such as cognition,memory,and learning.

Going beyond Computation and Its Limits: Injecting Cognition into Computing

Cognition is the ability to process information, apply knowledge, and change the circumstance. Cognition is associated with intent and its accomplishment through various processes that monitor and control a system and its environment. Cognition is associated with a sense of “self” (the observer) and the systems with which it interacts (the environment or the “observed”). Cognition extensively uses time and history in executing and regulating tasks that constitute a cognitive process. Whether cognition is computation in the strict sense of adhering to Turing-Church thesis or needs additional constructs is a very relevant question for addressing the design of self-managing (autonomous) distributed computing systems. In this paper we argue that cognition requires more than mere book-keeping provided by the Turing machines and certain aspects of cognition such as self-identity, self-description, self-monitoring and self-management can be implemented using parallel extensions to current serial von-Neumann stored program control (SPC) Turing machine implementations. We argue that the new DIME (Distributed Intelligent Computing Element) computing model, recently introduced as the building block of the DIME network architecture, is an analogue of Turing’s O-machine and extends it to implement a recursive managed distributed computing network, which can be viewed as an interconnected group of such specialized Oracle machines, referred to as a DIME network. The DIME network architecture provides the architectural resiliency, which is often associated with cellular organisms, through auto-failover;auto-scaling;live-migration;and end-to-end transaction security assurance in a distributed system. We argue that the self-identity and self-management processes of a DIME network inject the elements of cognition into Turing machine based computing as is demonstrated by two prototypes eliminating the complexity introduced by hypervisors, virtual machines and other layers of ad-hoc management software in today’s distributed computing environments.

The Global HIV Archive: Facilitating the Transition from Science to Practice of Efficacious HIV Prevention Interventions

This paper describes the development, content, and capabilities of the online Global HIV Archive (GHA). With the goal of facilitating widespread adaptation and appropriate use of efficacious HIV prevention programs throughout the globe, GHA has: 1) expanded and updated the search for HIV prevention programs originating in low-resource countries;2) identified those meritorious HIV prevention programs meeting established efficacy criteria of technical merit, replicability, and positive outcomes;3) prepared both implementation and evaluation materials from the efficacious programs for public use;4) developed interactive wizards or capacity-building tools to facilitate appropriate program selection, implementation, and adaptation;5) made the efficacious programs and accompanying wizards available to health practitioners throughout the globe in both printed and online formats.

Presenilin mutations and their impact on neuronal differentiation in Alzheimer’s disease

The presenilin genes(PSEN1 and PSEN2)are mainly responsible for causing early-onset familial Alzheimer’s disease,harboring~300 causative mutations,and representing~90%of all mutations associated with a very aggressive disease form.Presenilin 1 is the catalytic core of theγ-secretase complex that conducts the intramembranous proteolytic excision of multiple transmembrane proteins like the amyloid precursor protein,Notch-1,N-and E-cadherin,LRP,Syndecan,Delta,Jagged,CD44,ErbB4,and Nectin1a.Presenilin 1 plays an essential role in neural progenitor maintenance,neurogenesis,neurite outgrowth,synaptic function,neuronal function,myelination,and plasticity.Therefore,an imbalance caused by mutations in presenilin 1/γ-secretase might cause aberrant signaling,synaptic dysfunction,memory impairment,and increased Aβ42/Aβ40 ratio,contributing to neurodegeneration during the initial stages of Alzheimer’s disease pathogenesis.This review focuses on the neuronal differentiation dysregulation mediated by PSEN1 mutations in Alzheimer’s disease.Furthermore,we emphasize the importance of Alzheimer’s disease-induced pluripotent stem cells models in analyzing PSEN1 mutations implication over the early stages of the Alzheimer’s disease pathogenesis throughout neuronal differentiation impairment.

Achieving higher photoabsorption than groupⅢ-Ⅴsemiconductors in ultrafast thin silicon photodetectors with integrated photon-trapping surface structures

The photosensitivity of silicon is inherently very low in the visible electromagnetic spectrum,and it drops rapidly beyond 800 nm in near-infrared wavelengths.We have experimentally demonstrated a technique utilizing photon-trapping surface structures to show a prodigious improvement of photoabsorption in 1-μm-thin silicon,surpassing the inherent absorption efficiency of gallium arsenide for a broad spectrum.The photon-trapping structures allow the bending of normally incident light by almost 90 deg to transform into laterally propagating modes along the silicon plane.Consequently,the propagation length of light increases,contributing to more than one order of magnitude improvement in absorption efficiency in photodetectors.This high-absorption phenomenon is explained by finitedifference time-domain analysis,where we show an enhanced photon density of states while substantially reducing the optical group velocity of light compared to silicon without photon-trapping structures,leading to significantly enhanced light–matter interactions.Our simulations also predict an enhanced absorption efficiency of photodetectors designed using 30-and 100-nm silicon thin films that are compatible with CMOS electronics.Despite a very thin absorption layer,such photon-trapping structures can enable high-efficiency and high-speed photodetectors needed in ultrafast computer networks,data communication,and imaging systems,with the potential to revolutionize on-chip logic and optoelectronic integration.

Genetic algorithms for computational materials discovery accelerated by machine learning

Materials discovery is increasingly being impelled by machine learning methods that rely on pre-existing datasets.Where datasets are lacking,unbiased data generation can be achieved with genetic algorithms.Here a machine learning model is trained on-the-fly as a computationally inexpensive energy predictor before analyzing how to augment convergence in genetic algorithm-based approaches by using the model as a surrogate.This leads to a machine learning accelerated genetic algorithm combining robust qualities of the genetic algorithm with rapid machine learning.The approach is used to search for stable,compositionally variant,geometrically similar nanoparticle alloys to illustrate its capability for accelerated materials discovery,e.g.,nanoalloy catalysts.The machine learning accelerated approach,in this case,yields a 50-fold reduction in the number of required energy calculations compared to a traditional“brute force”genetic algorithm.This makes searching through the space of all homotops and compositions of a binary alloy particle in a given structure feasible,using density functional theory calculations.

Predicting aqueous stability of solid with computed Pourbaix diagram using SCAN functional

In this work,using the SCAN functional,we develop a simple method on top of the Materials Project(MP)Pourbaix diagram framework to accurately predict the aqueous stability of solids.We extensively evaluate the SCAN functional’s performance in computed formation enthalpies for a broad range of oxides and develop Hubbard U corrections for transition-metal oxides where the standard SCAN functional exhibits large deviations.The performance of the calculated Pourbaix diagram using the SCAN functional is validated with comparison to the experimental and the MP PBE Pourbaix diagrams for representative examples.Benchmarks indicate the SCAN Pourbaix diagram systematically outperforms the MP PBE in aqueous stability prediction.We further show applications of this method in accurately predicting the dissolution potentials of the state-of-the-art catalysts for oxygen evolution reaction in acidic media.

Random forest machine learning models for interpretable X-ray absorption near-edge structure spectrum-property relationships

X-ray absorption spectroscopy(XAS)produces a wealth of information about the local structure of materials,but interpretation of spectra often relies on easily accessible trends and prior assumptions about the structure.Recently,researchers have demonstrated that machine learning models can automate this process to predict the coordinating environments of absorbing atoms from their XAS spectra.However,machine learning models are often difficult to interpret,making it challenging to determine when they are valid and whether they are consistent with physical theories.In this work,we present three main advances to the data-driven analysis of XAS spectra:we demonstrate the efficacy of random forests in solving two new property determination tasks(predicting Bader charge and mean nearest neighbor distance),we address how choices in data representation affect model interpretability and accuracy,and we show that multiscale featurization can elucidate the regions and trends in spectra that encode various local properties.

Tracking materials science data lineage to manage millions of materials experiments and analyses

In an era of rapid advancement of algorithms that extract knowledge from data,data and metadata management are increasingly critical to research success.In materials science,there are few examples of experimental databases that contain many different types of information,and compared with other disciplines,the database sizes are relatively small.Underlying these issues are the challenges in managing and linking data across disparate synthesis and characterization experiments,which we address with the development of a lightweight data management framework that is generally applicable for experimental science and beyond.Five years of managing experiments with this system has yielded the Materials Experiment and Analysis Database(MEAD)that contains raw data and metadata from millions of materials synthesis and characterization experiments,as well as the analysis and distillation of that data into property and performance metrics via software in an accompanying open source repository.The unprecedented quantity and diversity of experimental data are searchable by experiment and analysis attributes generated by both researchers and data processing software.The search web interface allows users to visualize their search results and download zipped packages of data with full annotations of their lineage.The enormity of the data provides substantial challenges and opportunities for incorporating data science in the physical sciences,and MEAD’s data and algorithm management framework will foster increased incorporation of automation and autonomous discovery in materials and chemistry research.

Applications of Highly Ionized Ion Beams

The ECR ion sources have mainly been used until now for injection of cyclotrons and a large number of these sources are presently in operation through the world.Most cyclotrons are used today for nuclear physics researches but an increasing number of these accelerators are now devoted to medical applications.The ECR ion sources have also been extensively used for producing low energy beams for academic researches in atomic and surface physics.These studies led to very encouraging results opening the way to industrial applications. In this talk some of the most promising applications of HCI beams will be reviewed.The development of these applications will require some important improvements of the ECR sources which will be discussed.A special emphasis will be given to the respective roles of ECR and EBIS ion sources in these industrial applications, and some economic and market considerations discussed.

SARS-CoV-2:Air pollution highly correlated to the increase in mortality.The case of Guadalajara,Jalisco,Mexico

Objectives:To determine whether air pollution or changes in SARS-CoV-2 lineages lead to an increase in mortality.Methods:Descriptive statistics were used to calculate rates of infection(2020-2021).RT ePCR was used to compare viral loads from October 2020 to February 2021.Nextgeneration sequencing(NGS)(n=92)was used to examine and phylogenetically map SARS-CoV-2 lineages.A correlative“air pollution/temperature”index(I)was developed using regression analysis.PM_(2.5),PM_(10),O_(3),NO_(2),SO_(2),and CO concentrations were analyzed and compared to the mortality.Results:The mortality rate during the last year was~32%.Relative SARS-CoV-2 viral loads increased in December 2020 and January 2021.NGS revealed that approximately 80%of SARS-CoV-2 linages were B.1.243(33.7%),B1.1.222(11.2%),B.1.1(9%),B.1(7%),B.1.1.159(7%),and B.1.2(7%).Two periods were analyzed,the prehigh-and high-mortality periods and no significant lineage differences or new lineages were found.Positive correlations of air pollution/temperature index values with mortality were found for IPM_(2.5) and IPM_(10).INO_(2).ISO_(2),and ICO but not for O_(3).Using ICO,we developed a model to predict mortality with an estimated variation of~±5 deaths per day.

术后恶心呕吐的新疗法：统计学意义与临床意义的比较

术后恶心呕吐（postoperative nausea and vomiting，PONV）是住院和门诊手术患者常见的并发症。PONV是一种复杂的生理现象其包括多个神经生理通路，涉及中枢及外周受体机制。常用的止吐药具有多巴胺受体、乙酰胆碱受体、组胺受体和5-羟色胺受体阻断的特性。最近，神经激肽-1（NK-1）受体拮抗剂也被证实具有预防和治疗PONV的作用。