Lithobius (Ezembius) ternidentatus sp. n. (Lithobiomorpha, Lithobiidae), a new species from China

Lithobius (Ezembius) ternidentatus sp. n. (Lithobiomorpha, Lithobiidae), recently discovered from Wuyuezhai Mountain, Lingshou County, Shijiazhuang City, Hebei Province, China, is described. Morphologically it resembles L. (E.) multispinipes Pei, Lu, Liu, Hou, Ma & Zapparoli, 2016, but can be easily distinguished from the latter by having a different sized Tömösváry’s organ, different numbers of ocelli, obvious differences in ventral plectrotaxy of legs 14, and tarsal articulation ill-defined on legs 1–13, well-defined on legs 14–15. The main morphological characters of the known Chinese species of the subgenus Ezembius Chamberlin, 1919 based on adult specimens is presented

Two new species of Lithobius on Qinghai-Tibetan plateau identified from morphology and COI sequences (Lithobiomorpha: Lithobiidae)

Lithobius (Ezembius) longibasitarsus sp. n. and Lithobius (Ezembius) datongensis sp. n. (Lithobiomorpha: Lithobiidae), recently discovered from Qinghai-Tibet Plateau, China, are described. A key to the species of the subgenus Ezembius in China is presented. The partial mitochondrial cytochrome c oxidase subunit I barcoding gene was amplified and sequenced for eight individuals of the two new species and the dataset was used for molecular phylogenetic analysis and genetic distance determination. Both morphology and molecular data show that the specimens examined should be referred to Lithobius (Ezembius)

Isolation and complete genomic characterization of H1N1 subtype swine influenza viruses in southern China through the 2009 pandemic

<p>Abstract</p> <p>Background</p> <p>The swine influenza (SI) is an infectious disease of swine and human. The novel swine-origin influenza A (H1N1) that emerged from April 2009 in Mexico spread rapidly and caused a human pandemic globally. To determine whether the tremendous virus had existed in or transmitted to pigs in southern China, eight H1N1 influenza strains were identified from pigs of Guangdong province during 2008-2009.</p> <p>Results</p> <p>Based on the homology and phylogenetic analyses of the nucleotide sequences of each gene segments, the isolates were confirmed to belong to the classical SI group, with HA, NP and NS most similar to 2009 human-like H1N1 influenza virus lineages. All of the eight strains were low pathogenic influenza viruses, had the same host range, and not sensitive to class of antiviral drugs.</p> <p>Conclusions</p> <p>This study provides the evidence that there is no 2009 H1N1-like virus emerged in southern China, but the importance of swine influenza virus surveillance in China should be given a high priority.</p

Accuracy of a novel real-time continuous glucose monitoring system: a prospective self-controlled study in thirty hospitalized patients with type 2 diabetes

AimsThe present study aimed to investigate the accuracy of the Glunovo® real-time continuous glucose monitoring system (rtCGMS).MethodsWe conducted a 14-day interstitial glucose level monitoring using Glunovo® rtCGMS on thirty hospitalized patients with type 2 diabetes. The flash glucose monitoring (FGM) was used as a self-control. Consistency tests, error grid analysis, and calculation of the mean absolute relative difference (MARD) were performed using R software to assess the accuracy of Glunovo® rtCGMS.ResultsGlunovo® exhibited an overall MARD value of 8.89% during hospitalization, compared to 10.42% for FGM. The overall percentages of glucose values within ±10%/10, ± 15%/15, ± 20%/20, ± 30%/30, and ±40%/40 of the venous blood glucose reference value were 63.34%, 81.31%, 90.50%, 97.29%, and 99.36% for Glunovo®, respectively, compared with 61.58%, 79.63%, 88.31%, 96.22% and 99.23% for FGM. The Clarke Error Grid Analysis showed that 99.61% of Glunovo® glucose pairs and 100.00% of FGM glucose pairs within zones A and B.ConclusionOur study confirms the superior accuracy of Glunovo® in monitoring blood glucose levels among hospitalized patients with type 2 diabetes

Single photon detection performance of highly disordered NbTiN thin films

We experimentally investigated the detection performance of highly disordered NbxTi1-xN based superconducting nanowire single photon detectors (SNSPDs). The dependence on the composition of the transition temperature Tc for NbxTi1-xN films show a dome-like behavior on the Nb content, with a maximal Tc at xNb~0.65 , and the Nb0.65Ti0.35N films also combine relatively large sheet resistance and intermediate residual resistivity ratio. Moreover, 60-nm-wide and 7-nm-thick Nb0.65Ti0.35N nanowires show a switching current as high as 14.5 uA, and saturated intrinsic detection efficiency with a plateau of more than 2 uA at 2.4 K. Finally, the corresponding SNSPDs on an alternative SiO2/Ta2O5 dielectric mirror showed a system detection efficiency of approximately 92% for 1550 nm photons, and the timing jitter is around 26 ps. Our results demonstrate that the highly disordered NbxTi1-xN films are promising for fabricating SNSPDs for near- and middle-infrared single photons with high detection efficiency and low timing jitter.Comment: 9 pages,5 figure

Predictors of lung adenocarcinoma with leptomeningeal metastases: A 2022 targeted-therapy-assisted molGPA model

Objective: To explore prognostic indicators of lung adenocarcinoma with leptomeningeal metastases (LM) and provide an updated graded prognostic assessment model integrated with molecular alterations (molGPA). Methods: A cohort of 162 patients was enrolled from 202 patients with lung adenocarcinoma and LM. By randomly splitting data into the training (80%) and validation (20%) sets, the Cox regression and random survival forest methods were used on the training set to identify statistically significant variables and construct a prognostic model. The C-index of the model was calculated and compared with that of previous molGPA models. Results: The Cox regression and random forest models both identified four variables, which included KPS, LANO neurological assessment, TKI therapy line, and controlled primary tumor, as statistically significant predictors. A novel targeted-therapy-assisted molGPA model (2022) using the above four prognostic factors was developed to predict LM of lung adenocarcinoma. The C-indices of this prognostic model in the training and validation sets were higher than those of the lung-molGPA (2017) and molGPA (2019) models. Conclusions: The 2022 molGPA model, a substantial update of previous molGPA models with better prediction performance, may be useful in clinical decision making and stratification of future clinical trials

“Caracterización de los sistemas de producción de ovinos de pelo en el suroeste del departamento de Matagalpa 2010”

Con el objetivo de caracterizar los sistemas de producción de ovinos de pelo en el territorio suroeste del departamento de Matagalpa 2010. (Sébaco, Ciudad Darío, San Isidro y Matagalpa). Se aplicó una encuesta a 103 productores que poseen ovinos de pelo, la muestra se definió aleatoriamente utilizando la ecuación planteada por Scheaffer (1987), se utilizó la técnica de muestreo de bola de nieve, planteada por Frey et al (2000). Esta investigación permitió conocer las debilidades y oportunidades en los sistemas de explotación de esta especie promisoria para la zona seca del país. Con los resultados obtenidos de las encuestas se procedió ha elaborar una base de datos en el programa SPSS versión 11.5 en español. Encontrando un predominio del sexo femenino como titulares de las explotaciones ovinas, 58.3% cursó educación primaria, el 98% de las explotaciones cuentan con raza pelibuey, el 100% de las explotaciones realizan destete y monta de forma natural, una media de mortalidad de corderos de 1, alimentan a las ovejas con potrero sin división (81.6%), se suministra pasto de corte, pastoreo, leguminosas y se suplementa sal común 49.5%, aplican vacunas contra ántrax y pierna negra (63.1%), desparasitaciones internas y externas (66%), ambos con una frecuencia de 2 veces al año, en el manejo productivo no se lleva control en la actividad ovina (100%), los equipo e instalaciones son rústicas, los corrales ovinos el son elaborados con alambre y/o madera, techado con plástico y/o zinc (49.51%), en cuanto a asistencia técnica el 58.3% ha recibid

Integrating Growth and Environmental Parameters to Discriminate Powdery Mildew and Aphid of Winter Wheat Using Bi-Temporal Landsat-8 Imagery

Monitoring and discriminating co-epidemic diseases and pests at regional scales are of practical importance in guiding differential treatment. A combination of vegetation and environmental parameters could improve the accuracy for discriminating crop diseases and pests. Different diseases and pests could cause similar stresses and symptoms during the same crop growth period, so combining growth period information can be useful for discerning different changes in crop diseases and pests. Additionally, problems associated with imbalanced data often have detrimental effects on the performance of image classification. In this study, we developed an approach for discriminating crop diseases and pests based on bi-temporal Landsat-8 satellite imagery integrating both crop growth and environmental parameters. As a case study, the approach was applied to data during a period of typical co-epidemic outbreak of winter wheat powdery mildew and aphids in the Shijiazhuang area of Hebei Province, China. Firstly, bi-temporal remotely sensed features characterizing growth indices and environmental factors were calculated based on two Landsat-8 images. The synthetic minority oversampling technique (SMOTE) algorithm was used to resample the imbalanced training data set before model construction. Then, a back propagation neural network (BPNN) based on a new training data set balanced by the SMOTE approach (SMOTE-BPNN) was developed to generate the regional wheat disease and pest distribution maps. The original training data set-based BPNN and support vector machine (SVM) methods were used for comparison and testing of the initial results. Our findings suggest that the proposed approach incorporating both growth and environmental parameters of different crop periods could distinguish wheat powdery mildew and aphids at the regional scale. The bi-temporal growth indices and environmental factors-based SMOTE-BPNN, BPNN, and SVM models all had an overall accuracy high than 80%. Meanwhile, the SMOTE-BPNN method had the highest G-means among the three methods. These results revealed that the combination of bi-temporal crop growth and environmental parameters is essential for improving the accuracy of the crop disease and pest discriminating models. The combination of SMOTE and BPNN could effectively improve the discrimination accuracy of the minor disease or pest