Distortion-product otoacoustic emissions and auditory brainstem responses sensitivity assessment in cisplatin-induced ototoxicity in rats

SummaryCisplatin (cis-diamminedicloroplatinum) is an antineoplastic drug used in the treatment of a variety of cancers, especially head-and-neck cancer. Its ototoxicity, however, has been noted as a common side-effect which limits its use and causes significant morbidity.Aimto assess distortion-product otoacoustic emissions (DPOAE) and brainstem evoked response audiometry (BERA) sensitivity to detect secondary ototoxicity caused by different doses and means of administration of cisplatin in rats.Study DesignExperimental.Materials and MethodsMale Wistar rats were intraperitoneally (i.p.) injected with 24 mg/kg cisplatin, divided into three equal doses (8mg/kg) or a single i.p. injection of 16 mg/kg. The animals were evaluated by distortion product otoacoustic emission (DPOAE) or brainstem evoked response audiometry (BERA) on the 3rd and 4th days after the cisplatin injection.ResultsTreatment with cisplatin 24 mg/kg resulted in significant DPOAE decrease and it raised the BERA electrophysiological threshold. The 16mg/kg dose could not significantly reduce the DPOAE amplitude, but it raised the animals' hearing thresholds – detected by the BERA.ConclusionIn rats, BERA was more sensitivity than DPOAE at detecting cisplatin-induced ototoxicity in rats considering different doses and means of administration

Experimental Model of Zymosan-Induced Arthritis in the Rat Temporomandibular Joint: Role of Nitric Oxide and Neutrophils

Aims. To establish a new model of zymosan-induced temporomandibular joint (TMJ) arthritis in the rat and to investigate the role of nitric oxide. Methods. Inflammation was induced by an intra-articular injection of zymosan into the left TMJ. Mechanical hypernociception, cell influx, vascular permeability, myeloperoxidase activity, nitrite levels, and histological changes were measured in TMJ lavages or tissues at selected time points. These parameters were also evaluated after treatment with the nitric oxide synthase (NOS) inhibitors L-NAME or 1400 W. Results. Zymosan-induced TMJ arthritis caused a time-dependent leucocyte migration, plasma extravasation, mechanical hypernociception, and neutrophil accumulation between 4 and 24 h. TMJ immunohistochemical analyses showed increased inducible NOS expression. Treatment with L-NAME or 1400 W inhibited these parameters. Conclusion. Zymosan-induced TMJ arthritis is a reproducible model that may be used to assess both the mechanisms underlying TMJ inflammation and the potential tools for therapies. Nitric oxide may participate in the inflammatory temporomandibular dysfunction mechanisms

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Pervasive gaps in Amazonian ecological research

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

Pervasive gaps in Amazonian ecological research

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

Data-centric approach for online P-margin estimation from noisy phasor measurements

A new estimation method for load P-margin of transmission systems is proposed by using machine learning techniques. The estimation solution uses a reduced number of features as inputs to the machine learning algorithm and does not rely on power flow measurements, avoiding using time-varying grid parameters. The method involves investigating the performance of several machine learning algorithms to undertake the estimation task and explore different data transformation processes, including an optimized feature selection scheme, enabling an enhanced performance of the machine learning algorithms. Moreover, the method comprises the use of different Explainable-AI approaches to better understand the behavior of the solution. The method’s performance for different noise levels is widely studied by employing a noise model available in the recent technical literature. The mean absolute percentage error - MAPE and the root mean square error - RMSE are calculated for performance assessment. Numerical examples of the proposed technique are presented using the IEEE 14-bus test system, considering normal and contingency (N-1,N-2) conditions for a wide range of load cases

Efeito de inibidores da sintase de óxido nítrico na dor inflamatória articular e influxo celular da artrite induzida por zymosan em ratos

OBJETIVO: Investigar o papel do óxido nítrico (NO) no influxo celular (IC) e a incapacitação articular (IA) na artrite por zymosan (AZy). MÉTODOS: Ratos Wistar receberam injeção de Zy (1mg) no joelho direito. Grupos-controles receberam salina. A IA foi avaliada pelo Teste de incapacitação articular para ratos. Após sacrifício, o IC e a liberação de PGE2 foram avaliados no lavado articular. Avaliou-se o edema pela diferença peso úmido/peso seco do tecido articular. Grupos foram tratados i.p. com L-NAME - inibidor de sintases de NO (NOS) (LN=30-300mg/kg) ou aminoguanidina (AG= 30-300mg/kg) - inibidor seletivo de iNOS 30 min antes ou 2 h após o Zy. RESULTADOS: O pré-tratamento com L-NAME ou AG inibiu de forma dose-dependente a IA e o IC, mas não o edema ou a liberação de PGE2, sendo máximo para LN ou AG (100mg/kg). L-arginina (1g/kg) co-injetada com LN (100mg/kg) reverteu a inibição da IA e do IC. D-NAME (100mg/kg) não teve efeito. Co-injeção de naloxona (antagonista opióide) reverteu o efeito de LN e AG sobre a IA. A pressão arterial média elevou-se (p<0,01) após LN (100mg/kg), mas não com AG (100mg/kg). LN e AG (100mg/kg) dados 2 h após Zy não tiveram efeito. Azul de metileno (inibidor de GMPc), e não hemoglobina (scavenger de NO), reduziu IA e IC (p<0,01). Nitroprussiato de sódio (doador de NO) dado 2 h após Zy, reduziu a IA, mas não o IC (p<0,01). CONCLUSÕES: A antinocicepção na AZy por inibição da iNOS só ocorre como pré-tratamento, por efeito antiinflamatório via GMPc, independentemente de NO exógeno ou de PGE2, associada à liberação de opióides endógenos. Um doador de NO produz analgesia na AZy. Enfim, o trabalho demonstra efeito analgésico de um doador de NO em um modelo de periartrite, abrindo a perspectiva do uso dessas substâncias em humanos