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1.
Front Cell Infect Microbiol ; 14: 1367010, 2024.
Article in English | MEDLINE | ID: mdl-38469352

ABSTRACT

Stingless bees, a social corbiculate bee member, play a crucial role in providing pollination services. Despite their importance, the structure of their microbiome, particularly the fungal communities, remains poorly understood. This study presents an initial characterization of the fungal community associated with two Thai commercial stingless bee species, Lepidotrigona terminata (Smith) and Tetragonula pagdeni (Schwarz) from Chiang Mai, Thailand. Utilizing ITS amplicon sequencing, we identified distinct fungal microbiomes in these two species. Notably, fungi from the phyla Ascomycota, Basidiomycota, Mucoromycota, Mortierellomycota, and Rozellomycota were present. The most dominant genera, which varied significantly between species, included Candida and Starmerella. Additionally, several key enzymes associated with energy metabolism, structural strength, and host defense reactions, such as adenosine triphosphatase, alcohol dehydrogenase, ß-glucosidase, chitinase, and peptidylprolyl isomerase, were predicted. Our findings not only augment the limited knowledge of the fungal microbiome in Thai commercial stingless bees but also provide insights for their sustainable management through understanding their microbiome.


Subject(s)
Microbiota , Mycobiome , Bees , Animals , Thailand
2.
J Strength Cond Res ; 35(6): 1611-1619, 2021 Jun 01.
Article in English | MEDLINE | ID: mdl-33927114

ABSTRACT

ABSTRACT: Strand, KL, Cherup, NP, Totillo, MC, Castillo, DC, Gabor, NJ, and Signorile, JF. Periodized resistance training with and without functional training improves functional capacity, balance, and strength in Parkinson's disease. J Strength Cond Res 35(6): 1611-1619, 2021-Periodized progressive resistance training (PRT) is a common method used to improve strength in persons with Parkinson's disease (PD). Many researchers advocate the addition of functional training to optimize translation to activities of daily living; however, machine-based PRT, using both force and velocity training components, may elicit similar benefits. Thirty-five persons with PD (Hoehn and Yahr I-III) were randomized into a strength, power, and hypertrophy (SPH; n = 17) or strength, power, and functional (SP + Func; n = 18) group, training 3 times weekly for 12 weeks. Both groups performed machine-based strength and power training on days 1 and 2 each week, respectively; whereas, on day 3, SPH group performed machine-based hypertrophy training and SP + Func group performed functional training. Functional performance was tested using the timed up and go, 30-second sit-to-stand (30-s STS), gallon-jug shelf-transfer, and seated medicine ball throw (SMBT) tests. Balance (Mini-BESTest), strength, motor symptoms (UPDRS-III), quality of life, and freezing of gait (FOG) were also assessed. Repeated measures analysis of variance revealed a main effect for time (p ≤ 0.05) with significant improvements for the sample in the 30-s STS (p = 0.002), SMBT (p = 0.003), Mini-BESTest (p < 0.001), upper-body strength (p = 0.002) and lower-body strength (p < 0.001). A significant group × time interaction was seen for FOG, with SP + Func alone showing improvement (p = 0.04). Furthermore, the SPH group produced a clinically important difference for the UPDRS-III (mean difference = 4.39, p = 0.18). We conclude that both exercise strategies can be equally effective at improving functional capacity, balance, and muscular strength in individuals with PD. In addition, FOG and motor symptoms may be targeted through SP + Func and SPH, respectively. The results provide options for individualized exercise prescriptions.


Subject(s)
Gait Disorders, Neurologic , Parkinson Disease , Resistance Training , Activities of Daily Living , Exercise Therapy , Humans , Postural Balance , Quality of Life
3.
J Strength Cond Res ; 34(11): 3086-3093, 2020 Nov.
Article in English | MEDLINE | ID: mdl-33105358

ABSTRACT

Castillo, DC, Strand, KL, Oh, J, Eltoukhy, M, Totillo, MC, and Signorile, JF. The development of a regression model to predict object transfer power in older adults. J Strength Cond Res 34(11): 3086-3093, 2020-Declines in mechanical power affect independence in older adults; however, no practical clinical method exists to assess peak power (PP) and average power (AP) during transfer tasks in this population. Therefore, predictive models were developed and validated during performance of an existing transfer assessment, the gallon-jug shelf-transfer (GJST) test. Twenty-one independent-living older women (age = 74.8 ± 5.6) and men (age = 73.8 ± 4.5) participated in the development phase. Peak power and AP were computed using data from three-dimensional movement analyses while subjects moved five 1-gallon jugs from a low (0.59 m) to high shelf (1.43 m) as quickly as possible. Stepwise linear regression models using test duration, subject height, and age produced equations with high R values for PP (0.655-0.701; p < 0.0001) and AP (0.703-0.759; p < 0.0001). However, regression and Bland-Altman analyses showed models with declining agreement as power values increased. Therefore, analyses were repeated using a quadratic model, showing stronger predictive capacity (PP: R = 0.786; AP: R = 0.878; p < 0.0001). Validity of this model was evaluated in a second sample of 30 older women (age = 69.9 ± 4.7) and men (age = 70.7 ± 4.3). Computed GJST AP and PP were compared with power produced during dominant arm chest press and distance during the seated medicine ball throw. Generalizability of these models was also confirmed through cross-validation analyses. Our results indicate mechanical power in older adults can be accurately measured using the quadratic model, with test duration as the independent variable. This model provides a simple, safe, and inexpensive assessment tool that can be administered by clinicians to improve diagnostic and therapeutic processes in older persons.


Subject(s)
Activities of Daily Living , Geriatric Assessment/methods , Muscle Strength/physiology , Muscle, Skeletal/physiology , Age Factors , Aged , Aged, 80 and over , Body Height , Female , Humans , Linear Models , Male , Movement
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