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ObjectiveBased on response surface methodology combined with principal component analysis(PCA), the optimal decocting process of Moringa oleifera leaf standard decoction was optimized, and its multi-index quality evaluation system was established, in order to provide scientific basis for the quality control of this standard decoction. MethodResponse surface methodology and PCA were used to optimize the decoction process by taking the relative peak areas of 8 characteristic peaks and dry extract yield as indexes. Based on this, the quality of 15 batches of the standard decoction was evaluated by high performance liquid chromatography(HPLC) characteristic chromatogram, determination of major components(neochlorogenic acid, L-tryptophan, cryptochlorogenic acid, vicenin-2, isoquercetin, astragalin), determination of active parts(total flavonoids, total organic acids, total polysaccharides, total α-amino acids, total sinapine), dry extract yield, specific gravity and pH. ResultThe optimal decocting process was to soak M. oleifera leaves(100.00 g) for 30 min and decoct twice with the first decoction of 12 times the amount of water for 30 min and the second decoction of 10 times the amount of water for 20 min. Standard decoction containing 0.2 g·mL-1 of crude drug was defined by x¯±30%, the specific gravity was 0.722-1.340, pH was 3.86-7.16, dry extract yield was 23.1%-42.9%, and the alcohol-soluble extract content was 8.26%-15.34%. Calculated according to the dried products of the standard decoction, the contents of neochlorogenic acid, L-tryptophan, cryptochlorogenic acid, vicenin-2, isoquercetin and astragalin were 1.99-3.69, 1.20-2.22, 1.44-2.67, 0.53-0.99, 2.45-4.55, 1.22-2.26 mg·g-1, the relative transfer rates relative to the herbs were 34.37%-63.83%, 62.43%-115.94%, 64.65%-120.06%, 56.98%-105.82%, 37.46%-69.57%, 41.81%-77.64%, respectively. The contents of total flavonoids, total organic acids, total polysaccharides, total α-amino acids, total sinapine were 10.19-18.92, 11.82-21.96, 94.07-174.71, 42.69-79.27, 9.55-17.73 mg·g-1, the relative transfer rates for herbs were 25.72%-47.77%, 41.78%-77.59%, 64.90%-120.54%, 42.30%-78.57%, 34.99%-64.99%, respectively. ConclusionThe optimized decocting technology of M. oleifera leaf standard decoction is stable and feasible, and the established multi-indicator quality evaluation system can lay the foundation for the quality control of this standard decoction.
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Objective To establish a method for simultaneous determination of 11 components of Solanum nigrum from different producing areas,and to evaluate the quality by chemometrics and entropy weight-technique for order preference by similarity to ideal solution(EW-TOPSIS).Methods The 17 batches of Solanum nigrum samples from 8 provinces were collected.The high performance liquid chromatography(HPLC)method was used to simultaneously determine the contents of medioresino,pinoresinol,quercetin,rutoside,solasonine,solamargine,khasianine,solasodine,desgalactotigonin,diosgenin and β-sitosterol,and the multi-components quantitative control mode of Solanum nigrum was established.The quality evaluation model of Solanum nigrum was established by using chemical recognition pattern and EW-TOPSIS method,and the overall quality was evaluated comprehensively.Results When the 11 components were in the 0.78-39.00,0.55-27.50,0.34-17.00,0.21-10.50,41.87-2 093.50,60.95-3 047.50,2.58-129.00,1.02-51.00,0.46-23.00,1.05-52.50 and 0.42-21.00 μg/mL(r>0.999 0),their linear relationships were good.The average recovery was 96.81%-100.28%with the RSD<2.0%(n=9).17 batches of samples clustered into 3 categories.Solamargine,solasonine,desgalactotigonin and medioresino may be the main potential markers affecting the quality of Solanum nigrum.The results of EW-TOPSIS method showed that,the quality evaluation closeness of 17 batches of Solanum nigrum were 0.433 6,0.416 8,0.624 2,0.500 8,0.479 1,0.636 1,0.568 3,0.250 0,0.190 9,0.222 1,0.170 7,0.720 0,0.698 3,0.744 7,0.717 9,0.720 9 and 0.718 3,respectively,indicating that the overall quality of Solanum nigrum from Liaoning,Jilin and Heilongjiang were better,followed by Jiangsu,Henan and Anhui.Conclusion The established HPLC method for simultaneous determination of 11 components in Solanum nigrum is convenient and accurate.Chemometrics and EW-TOPSIS method are objective and comprehensive,which can be used for the overall quality evaluation of Solanum nigrum.
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Objective To establish the UPLC fingerprint chromatogram combined with chemometric analysis for the quality evaluation of classical formula Linggui Zhugan Decoction.Methods SHIMADZU Shim-Pack GIST C18 column(100 mm×2.1 mm,2.0 μm)was used with acetonitrile-0.1%phosphoric acid aqueous solution as mobile phase,gradient elution;flow rate was 0.2 mL/min;the detection wavelength was 266 nm for the first 30 minutes and 235 nm for the last 36 minutes;the column temperature was 30℃.The UPLC fingerprint of Linggui Zhugan Decoction was established by Similarity Evaluation System for Chromatographic Fingerprint of TCM(2012.130723 version),and the common peak was determined and the similarity evaluation was carried out.Based on the peak area determination results of the common peak of the fingerprint,the quality of different batches of Linggui Zhugan Decoction was evaluated by chemometrics such as clustering analysis and principal component analysis.Results A total of 24 common peaks were confirmed and 14 components were identified by using reference substances.The similarity of 10 batches of Linggui Zhugan Decoction samples was greater than 0.950,which could be divided into two categories by chemometrics,and the principal component 1-4 were the main factors affecting its quality evaluation.OPLS-DA identified 6 differential markers.Conclusion The fingerprint research method established in the study is simple,reliable and reproducible.Through the method of fingerprint combined with chemometrics analysis,the differences between Linggui Zhugan Decoction from different origins of medicinal materials are identified,which provides a reference for the internal quality evaluation of Linggui Zhugan Decoction.
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Objective To analyze the characteristics and distribution of TCM syndromes of advanced gastric cancer;To provide reference for the standardization and clinical research of TCM syndromes of advanced gastric cancer.Methods The four diagnosis information with advanced gastric cancer was retrospectively collected at Dongzhimen Hospital of Beijing University of Chinese Medicine from January 2010 to December 2020.And the investigation results were analyzed by combining principal component analysis and clustering analysis,so as to explore the distribution pattern of TCM syndromes of advanced gastric cancer.Results Totally 164 patients were included,involving 601 case-times.10 principal components were obtained through principal component analysis on 29 items of four diagnosis information.The four diagnosis information with factor coefficient>0.4 were selected and allocated to the 10 principal components.Then,based on the results of principal component analysis,clustering analysis was conducted to obtain the distribution proportion of the three types of TCM syndromes.According to the syndrome differentiation by professional clinicians,the results were followed by the frequency distribution as cold coagulation and blood stasis(356,59.28%),stomach yin deficiency(145,24.17%)and phlegm-heat accumulation(100,16.55%).Conclusion There are three basic TCM syndromes of advanced gastric cancer,which are cold coagulation and blood stasis,stomach yin deficiency and phlegm-heat accumulation.Cold coagulation and blood stasis occupies the largest proportion,and the treatment should be based on warming the middle to dissipate cold and promoting blood circulation to remove blood stasis.
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AIM To establish an UPLC-MS/MS method for simultaneous content determination of protocatechuic acid,epicatechin,chlorogenic acid,quercitrin,gaultherin and gaultheroside A in Gaultheria leucocarpa var.yunnanensis.METHODS The analysis was performed on a 40℃thermostatic Waters BEH C18 column(100 mm×2.1 mm,1.7 μm),with the mobile phase comprising of water(containing 0.1%formic acid)-acetonitrile(containing 0.1%formic acid)flowing at 0.3 mL/min in a gradient elution manner,and electron spray inoization source was adopted in positive and negative ion scanning with multiple reaction monitoring(MRM)mode.Hierarchical cluster analysis(HCA)and principal component analysis(PCA)was used to screen important components that affect the quality of medicinal materials.RESULTS Six constituents showed good linear relationships within their own ranges(R2≥0.998 2),whose average recoveries were 98.76%-101.88%with the RSDs of 1.0%-2.5%.The constituents of G.leucocarpa in the roots and aerial parts were quite different.Gaultherin,epicatechin and protocatechuic acid may be the quality mark constituents of G.leucocarpa.CONCLUSION This accurate and efficient method can be used for the quality control of G.leucocarpa.
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AIM To simultaneously determine the contents of neochlorogenic acid,caffeic acid,chlorogenic acid,cryptochlorogenic acid,hydroxysafflor yellow A,ferulic acid,senkyunolide I,senkyunolide H and senkyunolide A in Fuyang Granules,and to make chemical pattern recognition.METHODS The UHPLC was performed on a 35℃thermostatic Waters Acquity UPLC?BEH C18 column(150 mm×2.1 mm,1.7 μm),with the mobile phase comprising of acetonitrile-0.01%phosphoric acid flowing at 0.4 mL/min in a gradient elution manner,and the detection wavelengths were set at 278,322,325,390 nm.Then heatmap clustering analysis and principal component analysis were adopted.RESULTS Nine constituents showed good linear relationships within their own ranges(r>0.999 0),whose average recoveries were 93.89%-102.25%with the RSDs of 0.85%-2.88%.Different batches of samples from the same enterprises demonstrated consistent overall qualities,while the overall qualities of samples from different enterprises exhibited obvious differences.CONCLUSION This simple and accurate method can be used for the quality control of Fuyang Granules.
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AIM To determine the contents of aspartic acid,glutamic acid,serine,glycine,threonine,citrulline,arginine,alanine,γ-amino-butyric acid,tyrosine,valine,phenlalanine,isoleucine,ornithine,leucine,lysine and proline in Gualoupi Injection and its intermediates,and to analyze their change laws.METHODS The OPA-FMOC online derivatization analysis was performed on a 45℃ thermostatic Waters XBridge C18 column(4.6 mm×100 mm,3.5 μm),with the mobile phase comprising of phosphate buffer solution-[methanol-acetonitrile-water(45 : 45 : 10)]flowing at 1 mL/min in a gradient elution manner,and the detection wavelengths were set at 262,338 nm.Principal component analysis and heatmap analysis were adopted in chemical pattern recognition for the corresponding intermediates in ten processes of six batches of samples.RESULTS Seventeen amino acids showed good linear relationships within their own ranges(R2>0.998 0),whose average recoveries were 83.4%-119.5%with the RSDs of 0.91%-7.94%.Different batches of samples in the same process were clustered,and the corresponding intermediates in different processed were clustered into three groups.Alcohol precipitation and cation exchange column demonstrated the biggest influences on amino acid composition.CONCLUSION This experiment can provide important references for the critical factors on quality control of Gualoupi Injection,thus ensure the stability and uniformity of final product.
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AIM To investigate the variation rules of main secondary metabolites in Hedysari Radix before and after rubbing strip.METHODS UPLC-MS/MS was adopted in the content determination of formononetin,ononin,calycosin,calycosin-7-glucoside,medicarpin,genistein,luteolin,liquiritigenin,isoliquiritigenin,vanillic acid,ferulic acid,γ-aminobutyric acid,adenosine and betaine,after which cluster analysis,principal component analysis and orthogonal partial least squares discriminant analysis were used for chemical pattern recognition to explore differential components.RESULTS After rubbing strip,formononetin,calycosin,liquiritigenin and γ-aminobutynic acid demonstrated increased contents,along with decreased contents of ononin,calycosin-7-glucoside and vanillic acid.The samples with and without rubbing strip were clustered into two types,calycosin-7-glucoside,formononetin,γ-aminobutynic acid,vanillic acid,calycosin-7-glucoside and formononetin were differential components.CONCLUSION This experiment clarifies the differences of chemical constituents in Hedysari Radix before and after rubbing strip,which can provide a reference for the research on rubbing strip mechanism of other medicinal materials.
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Objective The contents of 11 nucleosides and base components in 10 batches of samples from 5 provinces(cities)including Chongqing,Yunnan and Shaanxi were determined,and the differences in nucleosides and base components in Fritillaria taipaiensis were compared by chemometric analysis,and the quality was comprehensively evaluated,so as to provide a reference for the cultivation of excellent varieties and the selection of medicinal materials.Methods Nucleoside and base components were extracted from Fritillaria taipaiensis by ultrasonication in aqueous solutions,and the content of each component was determined by HPLC-DAD method.The origin was classified by principal component analysis(PCA)and hierarchical cluster analysis(HCA).Partial least squares discriminant analysis(PLS-DA)was used to determine the differentiated index components in Fritillaria taipaiensis.Then the differences in the contents of the index components among samples from different origins were compared.Results It was found that 11 nucleoside and base components differed significantly among different origins of Fritillaria taipaiensis.Principal component analysis and hierarchical cluster analysis indicated that all samples could be clustered into 4 categories.Five characteristic components,including uracil,cytosine,uridine,inosine,and adenosine,were identified by PLS-DA.The nucleosides and bases in samples from Chongqing and Hubei were relatively high,and the quality of the samples was comparatively superior.Conclusion This method is simple,reproducible,accurate and reliable.It has screened out the index nucleoside and base components in the identification of Fritillaria taipaiensis of different origins,which can be used to initially elucidate the differences of samples between different origins.Additionally,it can better reflect the quality of Fritillaria taipaiensis,and can provide reference for the selection of procurement origin and the quality control for Fritillaria taipaiensis.
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Objective To establish a method for simultaneous determination of HPLC fingerprint and multi-target ingredients in Atractylodis Macrocephalae Rhizoma(AMR),in order to provide reference for its quality control.Methods HPLC-DAD multi-wavelength switching method was used to establish fingerprint of AMR,similarity evaluation combined with hierarchical clustering analysis(HCA),principal components analysis(PCA)and discriminant analysis of partial least squares(PLS-DA)were used to carry out chemometric study.The contents of differential component such as atractylenolide Ⅰ,Ⅱ,Ⅲ and atractylon were determined simultaneously.Results The HPLC fingerprint of 37 batches of AMR was established.Nine common peaks were marked,and 4 of them were identified as atractylon,atractylenolide Ⅰ,Ⅱ,Ⅲ.The similarity degrees were between 0.539 and 0.996,the quality of AMR from different origin and different batches varies greatly.Atractylon,atractylenolide Ⅰ,Ⅱ,Ⅲ and one unknown component(peak 9)are the important factors affecting the quality of AMR.Conclusion The combination methods of HPLC fingerprint and simultaneous determinations of multiple components are simple,stable,accurate and reliable,which can provide reference for the quality evaluation of AMR and the improvement of quality standard,as well as lay a foundation for the basic research of its pharmacodynamic substances and related compound.
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@#Objective To propose a heart sound segmentation method based on multi-feature fusion network. Methods Data were obtained from the CinC/PhysioNet 2016 Challenge dataset (a total of 3 153 recordings from 764 patients, about 91.93% of whom were male, with an average age of 30.36 years). Firstly the features were extracted in time domain and time-frequency domain respectively, and reduced redundant features by feature dimensionality reduction. Then, we selected optimal features separately from the two feature spaces that performed best through feature selection. Next, the multi-feature fusion was completed through multi-scale dilated convolution, cooperative fusion, and channel attention mechanism. Finally, the fused features were fed into a bidirectional gated recurrent unit (BiGRU) network to heart sound segmentation results. Results The proposed method achieved precision, recall and F1 score of 96.70%, 96.99%, and 96.84% respectively. Conclusion The multi-feature fusion network proposed in this study has better heart sound segmentation performance, which can provide high-accuracy heart sound segmentation technology support for the design of automatic analysis of heart diseases based on heart sounds.
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@#Objective To develop a shake-flask stage culture process for E.coli with higher biomass and higher bacterial viability based on Quality by Design(QbD)concept.Methods Using different shake-flask configurations as the investigation factors,and A600value of the bacterial suspension,wet weight of the culture and viability value of the bacteria as the indicators for investigation of the culture results,ANOVA was used for the analysis of culture results to obtain the third amplification flask configurations with high biomass and high bacterial viability.The two-factor two-level full-factor test was carried out with the shaker temperature and shaker speed as the test factors,the A value of bacterial suspension as the response value,the culture accumulation time as a variable factor,and the real-time online temperature and self-test speed of the shaker as the supplemented variable factors.The functional principal component analysis(FPCA)method was used to perform a generalized regression model to model the quasi-growth curve,and the optimized culture stop time and culture process were obtained by the growth curve model.The design space of the shaker culture process was optimized again using Monte Carlo simulation(MCS)with random noise added to the response value.The worst condition in the design space was selected as the setting condition for verification test,and serial 10 batch verification tests were performed in stages with different culture stop time.Results The third amplification shake-flask configurations:5 L disposable high-efficiency shakeflask and large area breathable film cover.The culture process design space:shaker temperature of 36.5-37.5 ℃,shaker speed of 220-230 r/min,and the design culture stop time of 18 h.The worst condition verification test showed that when the culture was stopped for 16 h,the culture results of higher cell viability value and lower biomass could be obtained,and when the culture was stopped for 18 h,the results of higher biomass and bacterial viability value could be obtained.Conclusion The shake-flask stage culture process for E.coli designed in this study has the characteristics of high biomass and high bacterial viability,and can be adjusted according to the adaptability of this culture process to meet different culture needs.
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Objective:To compare the chemical composition of decoction and granules of Sangju Decoction; To provide a method for quality evaluation of Sangju Decoction.Methods:HPLC was used to establish fingerprints, and a comprehensive comparative study was conducted on the traditional decoction and formula granules of Sangju Decoction from four aspects: chemical composition type, fingerprint similarity, chemical pattern recognition analysis, and representative index component content.Results:The fingerprint similarity of the 10 batches of traditional decoction was >0.988. 35 peaks were identified and 12 peaks were identified as common peaks (neochlorogenic acid for peak 7, chlorogenic acid for peak 10, cryptochlorogenic acid for peak 11, 1,3-dicaffeoylquinic acid for peak 13, rutin for peak 17, lenoside A for peak 19, lignan for peak 20, isochlorogenic acid B for peak 24, ammonium glycyrrhizate for peak 25). The fingerprint similarity of the formulation pellets was >0.983, and 29 characteristic peaks were identified. Compared with the traditional decoction, some batches of the granules lacked peaks 14, 26, 27, 30, 32 and 34, and clustering analysis (CA), principal component analysis (PCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) could distinguish between the two. The contents of the 10 index components neochlorogenic acid, chlorogenic acid, cryptochlorogenic acid, 1,3-dicaffeoylquinic acid, forsythia ester glycoside A, grass glycosides, isochlorogenic acid B, 3,5-O-dicaffeoylquinic acid, forsythia glycosides, monkshood glycosides in the traditional soup were higher than that in the granules, and the contents of rutin and ammonium glycyrrhizate in the granules were higher than that in traditional decoction.Conclusions:The content and composition of traditional decoction and formula granules of Sangju Decoction are significantly different. The combination of fingerprinting and chemical pattern identification effectively can effectively evaluate the difference between traditional decoction and formula granules of Sangju Decoction, which can lay a foundation for the quality control and rational clinical application of formula granules of Sangju Decoction.
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ObjectiveTo screen the differential markers by analyzing volatile components in Dalbergia odorifera and its counterfeits, in order to provide reference for authentication of D. odorifera. MethodThe volatile components in D. odorifera and its counterfeits were detected by headspace gas chromatography-mass spectrometry(HS-GC-MS), and the GC conditions were heated by procedure(the initial temperature of the column was 50 ℃, the retention time was 1 min, and then the temperature was raised to 300 ℃ at 10 ℃ for 10 min), the carrier gas was helium, and the flow rate was 1.0 mL·min-1, the split ratio was 10∶1, and the injection volume was 1 mL. The MS conditions used electron bombardment ionization(EI) with the scanning range of m/z 35-550. The compound species were identified by database matching, the relative content of each component was calculated by the peak area normalization method, and principal component analysis(PCA), orthogonal partial least squares-discrimination analysis(OPLS-DA) and cluster analysis were performed on the detection results by SIMCA 14.1 software, and the differential components of D. odorifera and its counterfeits were screened out according to the variable importance in the projection(VIP) value>2 and P<0.05. ResultA total of 26, 17, 8, 22, 24 and 7 volatile components were identified from D. odorifera, D. bariensis, D. latifolia, D. benthamii, D. pinnata and D. cochinchinensis, respectively. Among them, there were 11 unique volatile components of D. odorifera, 6 unique volatile components of D. bariensis, 3 unique volatile components of D. latifolia, 6 unique volatile components of D. benthamii, 8 unique volatile components of D. pinnata, 4 unique volatile components of D. cochinchinensis. The PCA results showed that, except for D. latifolia and D. cochinchinensis, which could not be clearly distinguished, D. odorifera and other counterfeits could be distributed in a certain area, respectively. The OPLS-DA results showed that D. odorifera and its five counterfeits were clustered into one group each, indicating significant differences in volatile components between D. odorifera and its counterfeits. Finally, a total of 31 differential markers of volatile components between D. odoriferae and its counterfeits were screened. ConclusionHS-GC-MS combined with SIMCA 14.1 software can systematically elucidate the volatile differential components between D. odorifera and its counterfeits, which is suitable for rapid identification of them.
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@#Abstract: Kirsten rat sarcoma viral oncogene homolog (KRAS) gene is one of the most commonly mutated oncogenes. It has been found that KRAS inhibitors have the potential therapeutic effect on cancer patients with this gene mutation. In this study, machine learning was applied to develop a QSAR(quantitative structure-activity relationship) model for KRAS small molecule inhibitors. A total of 1857data points of IC50 and SMILES(simplified molecular input line entry system) for KRAS inhibitors were collected from three databases: ChEMBL, BindingDB, and PubChem. And nine different classifiers were constructed using three different feature screening methods combined with three machine learning models, namely, random forest, support vector machine, and extreme gradient boosting machine. The results showed that the SVM model combined with mutual information feature selection exhibited the best performance: AUCtest=0.912, ACCtest=0.859, F1test=0.890. Moreover, it also demonstrated good predictive performance on the external validation set(AUCExt=0.944, RecallExt=0.856, FPRExt=0.111). This study provides a new technical route for KRAS inhibitor screening in natural product databases using artificial intelligence methods.
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ABSTRACT Introduction: In ice hockey games, the team's performance is influenced by many contextual factors, and understanding playing styles allows to reveal how key performance indicators vary under different situations. Objective: This research aims to explore the playing styles of elite ice-hockey teams and to identify key performance aspects under different final goal difference situations. Methods: This article analyzed compared the match performance of 31 National Hockey League teams during 1271 matches considering their playing styles and final goal difference. Results: The principal component analysis obtained 8 performance components describing the technical-tactical styles of the teams. The subsequent analysis found that there was significant difference between three match outcomes in unfavorable state, major penalties, puck possession maintaining ability, shot defending ability, aggressive performance (p<0.001; = 0.007-0.273). Conclusions: Higher-ranked teams winning the unbalanced games showed better performance in shot defending ability and aggressive performance. Lower-ranked teams losing in unbalanced games kept less possession of the puck and were more likely to be shorthanded (p<0.05, ES=0.131-1.410). The study demonstrates how playing styles can be used to contextualize key determinants from ice hockey games. Level of evidence I; Therapeutic Studies Investigating the Results of Treatment.
RESUMEN Introducción: En los juegos de hockey sobre hielo, el rendimiento del equipo está influenciado por varios factores contextuales, y comprender los estilos de juego permite revelar cómo varían los indicadores clave de rendimiento en diferentes situaciones. Objetivo: Esta investigación tiene como objetivo explorar los estilos de juego de los equipos de hockey sobre hielo de élite e identificar aspectos clave del rendimiento en diferentes situaciones de diferencia de gol final. Métodos: El rendimiento del partido de 31 equipos de la Liga Nacional de Hockey durante 1271 partidos fue analizado y comparado, considerando el estilo de juego y la diferencia de gol final. Resultados: El análisis de componentes principales obtuvo 8 componentes de rendimiento que describen los estilos técnico-tácticos de los equipos. El análisis posterior encontró que hubo una diferencia significativa entre tres resultados de partido en estado desfavorable, penalizaciones principales, habilidad para mantener la posesión del disco, habilidad para defender el tiro, desempeño agresivo (p<0,001; = 0,007-0,273). Conclusión: Los equipos de clasificación más alta que ganaron los juegos desequilibrados mostraron un mejor rendimiento en la capacidad de defensa de disparos y en el rendimiento agresivo. Los equipos de clasificación más baja que perdieron en juegos desequilibrados mantuvieron menos posesión del disco y tenían más probabilidades de estar en desventaja numérica (p<0,05, ES=0,131-1,410). El estudio demuestra cómo los estilos de juego pueden utilizarse para contextualizar los determinantes clave de los juegos de hockey sobre hielo. Nivel de Evidencia I; Estudios Terapéuticos que Investigan los Resultados del Tratamiento.
RESUMO Introdução: Nos jogos de hóquei no gelo, o desempenho da equipe é influenciado por vários fatores contextuais, e entender os estilos de jogo permite revelar como os principais indicadores de desempenho variam em diferentes situações. Objetivo: Esta pesquisa tem como objetivo explorar os estilos de jogo das equipes de hóquei no gelo de elite e identificar aspectos-chave de desempenho em diferentes estilos de jogo e a diferença do resultado final. Métodos: O desempenho de partida de 31 equipes da National Hockey League durante 1271 partidas foi analisado e comparado, considerando o estilo de jogo e a diferença de gol final. Resultados: A análise de componentes principais retornou 8 componentes de desempenho, descrevendo os estilos técnico-táticos das equipes. A análise subsequente revelou que houve diferença significativa entre três resultados de jogo em estado desfavorável, penalidades principais, habilidade de manter a posse do disco, habilidade de defender o lance e desempenho agressivo (p<0,001; = 0,007-0,273). Conclusão: As equipes de classificação mais alta que venceram os jogos em desequilíbrio numérico de jogadores apresentaram melhor desempenho na habilidade de defender o lance e no desempenho agressivo. As equipes de classificação mais baixa, que perderam em jogos desequilibrados, mantiveram menos posse do disco e tiveram maior probabilidade de ficar com um jogador a menos (p <0,05, ES = 0,131-1,410). O estudo demonstra como os estilos de jogo podem ser usados para contextualizar os principais determinantes dos jogos de hóquei no gelo. Nível de Evidência I; Estudos Terapêuticos Investigação dos Resultados do Tratamento.
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Introducción. La población de personas mayores (PM) en Chile presenta un incremento sostenido con importantes tasas de fragilidad y riesgo de caídas (RC). El desempeño de marcha permite valorarlo mediante parámetros mecánicos y fisiológicos. Nos preguntamos, ¿cuáles podrían ser los más relevantes para estimar RC en condiciones de marcha confortable (MC) y máxima (MM)? Objetivo. Identificar los principales parámetros de marcha que podrían explicar RC en PM autovalentes de la comunidad. Métodos. Estudio observacional y transversal en el cual participaron 53 PM autovalentes de la comuna de Talca, Chile (edad 71±7años; IMC 29,1±3,4 kg/m2). Se solicitó a los participantes la ejecución de MC (n=53) y posteriormente MM (n=36). Ambas modalidades fueron desarrolladas en un circuito elíptico de 40m durante 3min. El RC se categorizó como: "sin riesgo", "riesgo dinámico" según prueba timed up and go (TUG) positiva, "riesgo estático" según estación unipodal (EUP) positiva y "riesgo mixto" con ambas pruebas positivas. Para la visualización de la variación gráfica en el morfoespacio de los individuos según RC, se realizó un análisis de componentes principales (ACP) mediante el Programa RStudio, utilizando 6 variables cinemáticas: i) velocidad promedio de marcha (VPM), ii) cadencia, iii) máximo despeje del pie (MDP), iv) coeficiente de variación (%CV) del MDP, v) longitud de zancada (LZ) y vi) %CV de la LZ. Además de 2 variables fisiológicas: i) % frecuencia cardiaca de reserva utilizada (%FCRu) y ii) el índice de costo fisiológico según la relación entre FC y VM (latidos/metros). Resultados. Para MC las dimensiones del ACP explican el 56% de la variabilidad de los datos, siendo los indicadores de seguridad de RC la VM, cadencia, LZ y MDP. La variabilidad de marcha explica RC mixto y el ICF junto al %FCRu se asocian a RC dinámico. En condiciones de MM, el ACP explica 60% de la variabilidad de datos, donde las PM sin RC se asocian con VM, LZ y MDP. Por su parte, la variabilidad del MDP se vincula con RC dinámico y las variables fisiológicas con el RC mixto. Conclusiones. Los parámetros de marcha que mejor explican una marcha segura y eficiente son cinemáticos de la fase de balanceo, mientras que la variabilidad y el costo fisiológico se asocian como indicadores de RC dinámico y mixto.
Background. Introduction: The elderly population (EP) in Chile is experiencing a sustained increase with significant rates of frailty and risk of falls (RF). Gait performance can be assessed using mechanical and physiological parameters. We wonder, which ones could be the most relevant to estimate RF in self-selected walking speed (SSWS) and maximum walking speed (MWS) conditions? Objective. Identify the main gait parameters that could explain RF in self-sufficient elderly individuals from the community. Methods. This observational and cross-sectional study included 53 self-sufficient elderly individuals from the commune of Talca, Chile (age 71±7 years; BMI 29.1±3.4 kg/m2). Participants were asked to perform SSWS (n=53) and subsequently MWS (n=36). Both modalities were conducted on a 40m elliptical circuit for 3 minutes. RF was categorized as: "no risk," "dynamic risk" based on a positive timed up and go test, "static risk" based on a positive one-legged stance test, and "mixed risk" with both tests positive. To visualize the graphical variation in the morphospace of individuals according to RF, a principal component analysis (PCA) was conducted using RStudio, utilizing 6 kinematic variables: i) walking speed (WS), ii) cadence, iii) maximum foot clearance (MFC), iv) coefficient of variation (%CV) of MFC, v) stride length (SL), and vi) %CV of SL. In addition to 2 physiological variables: i) % of reserve heart rate used (%RHRu) and ii) the physiological cost index based on the relationship between heart rate and WS (heartbeats/meters). Results. For SSWS, the PCA dimensions explained 56% of the data variability, with gait safety indicators such as WS, cadence, SL, and MFC explaining RF. Gait variability explains mixed RF, while the physiological cost index and %RHRu are associated with dynamic RF. In MWS conditions, PCA explains 60% of the data variability, where the elderly persons without RF are associated with WS, SL, and MFC. On the other hand, MFC variability is related to dynamic RF, and physiological variables are associated with mixed RF. Conclusions. The gait parameters that best explain safe and efficient walking are kinematic parameters of the swing phase, while variability and physiological cost are indicators of dynamic and mixed RF.
ABSTRACT
Background: The global population continues to rise at different rates in different parts of the world. While some countries are seeing a fast population increase, others are experiencing population loss. Significant ramifications of such changes in the global population distribution would be felt, as they are critical for meeting the Sustainable Development Goals (SDGs), or we might say that rapid population expansion poses obstacles to sustainable development. Estimating the population size and composition by age, sex, and other demographic parameters is crucial for analyzing the country’s future influence on poverty, sustainability, and development. This study tries to look at these parameters covered by the National Family Health Survey- 5 (NFHS 5) to see how accurate and trustworthy the predictors of district population size are. Methodology: The study assessed the predictors of the population size of any district. It was conducted using the secondary data of phase 1 of NFHS-5. The outcome variable is the population of each district. Household profiles, literacy among women, their marriage and fertility, contraceptive usage, and unmet need for family planning were considered to assess their potential as a predictor of the district’s population size. Principal component analysis (PCA) was conducted to identify the predictors. Result: PCA was conducted on 18 variables, resulting in 7 principal components. Cumulatively, these components explained 77.6% of the total variation in data. On multiple linear regression, four principal components were found significant and these were related to women’s literacy, contraceptive usage, early pregnancy, the marriage of fewer than 18 years, and those using health insurance. Conclusion: Thus, women’s literacy plays a pivotal role in determining a region’s population size.
ABSTRACT
The study aimed to evaluate the composition and diversity of algae in the JP Lake of Jahangirnagar University campus. The research was carried out between the period of December 2021 to November 2022. A total of 72 water samples were used to carry out the investigation. Shannon and Simpson diversity indexes were used to determine the level of diversity. 234 phytoplankton species under 98 genera were found belonging to 8 classes (Cyanophyceae, Chlorophyceae, Bacillariophyceae, Synurophyceae, Euglenophyceae, Cryptophyceae, Dinophyceae, and Xanthophyceae). According to the generic percentage composition, Chlorophyceae comprised 46%, followed by Bacillariophyceae (20%) and Cyanophyceae (18%). At the species level, Euglenophyceae were found to dominate (34%) the studied sites that were followed by Chlorophyceae (31%) and Cyanophyceae (18%). The total density of phytoplankton was 387.34×105 ind/l. The highest phytoplankton density was found in April, and the lowest one was in November. Cell dispersion was below average in May for Cyanophyceae, Bacillariophyceae, Cryptophyceae, and Synurophyceae. Oscillatoria, Monoraphidium, Actinastrum, Cosmarium, Trachelomonas, and Euglena dominated the surveyed region. The Shannon Diversity Index showed a value of 1.51, while Simpson's Diversity Index showed a value of 0.28. The overall variation (80.73%) among the classes was represented by PCA cells. According to the Shannon and Simpson Diversity Indexes, the diversity was low.
ABSTRACT
Background: Sufficient and quality healthcare services are basic requirement for overall development of a nation. Public healthcare infrastructure is one of the major determinants of health outcomes in a country, and public healthcare services have a considerable impact on people's health status. The rural population primarily relies on public healthcare services. Assam is not an exception in this regard, where the insufficiency of public healthcare services is still an issue. 86 % of the population of Assam lives in rural areas. Objectives: The present work attempts to study the inter-district variation regarding public health infrastructure in 33 districts of Assam. Methods: The Inter district variation is estimated with a composite index of public health infrastructure. Principal Component Analysis (PCA) is adopted to construct a composite index using nine health infrastructure indicators. Results: The study has observed variations in health infrastructure among the various districts of Assam, reflecting the shortage of health infrastructure-physical and human in rural and remote areas of the state. The study finds inter-district variations in the state.