Current aging science最新文献

Introduction and objective: There is limited research on the changes that can occur in the gait biomechanical parameters of older adults over long-distance walking. Thus, this study aimed to evaluate the gait characteristics of older women of a specific Portuguese community over the six-minute walk test (6MWT) along with gait spatial and temporal parameters and angular kinematics of the lower limb joints.

Materials and methods: Twenty-six older women voluntarily participated. Each woman performed the 6MWT, and during this, their spatial and temporal parameters were collected through plantar pressure data (100Hz) and angular kinematics through an inertial sensor system (100Hz). The 6MWT was divided into four intervals, and the Friedman test was used to compare them. The median age of the women was calculated, and the Mann-Whitney test was used to compare women above and below the median age value.

Results: An increase in gait speed, stance phase, and double stance phase along the intervals was observed, as well as larger angular displacements of the hip, knee, and ankle (p<0.05). Women below or above the median age value also yielded these behaviours. Gait speed, cadence, stride length, and step length were higher in women below the median age value, while stride and step duration were lower (p<0.05).

Conclusion: Older women yielded changes in gait spatial and temporal parameters along the 6MWT, as well as larger angular displacements of the lower limb joints. Older women (compared to younger ones) yielded lower gait speed, cadence, stride length, and step length, higher stance and double stance phases, and shorter angular displacements of the lower limb joints.

Aims and objective: This study aimed to compare and determine the correlation of BMI on physical health, including muscle strength, balance, and cardiorespiratory fitness in older adults without sedentary behavior.

Methods: A total of 65 older adults without sedentary behavior were recruited and divided into 3 groups on the basis of body mass index (BMI): normal weight (n= 22/group), overweight (n= 22/- group), and obese (n= 21/group). All the older adults were evaluated for upper limb muscle strength using the handgrip strength test, lower limb muscle strength using the sit-to-stand (STS10) test, balance ability using the time up and go (TUG) test, and cardiorespiratory fitness using the 6-minute walk test (6MWT).

Results: The handgrip strength test, STS10 test, and distance of 6MWT showed no difference among the groups (p> 0.05). However, overweight group had a significantly longer duration for the TUG test when compared to normal weight, while obese group had a significantly longer duration for the TUG test when compared with overweight and normal weight groups (p< 0.01). In addition, BMI was positively correlated with the duration of the TUG test. Whereas, the handgrip strength test, STS10 test, and distance of 6MWT were not correlated with BMI.

Conclusion: The BMI does not impact upper and lower limb muscle strength or the cardiorespiratory fitness test, except for the ability to balance in older adults without sedentary behavior.

Background: X-linked mutations are highly important in clinical diagnosis, and at least 533 disorders are related to the genes located on the X chromosome.

Case presentation: A 21-year-old Caucasian woman with a 24-year-old Caucasian man as her fiancé referred Clinical genetic lab for premarital genetic counseling (carrier screening). None of them had any abnormal manifestations. Following genetic counseling, Whole Exome Sequencing (WES) test performed to find the possible pathogenic mutations. Also, after drawing the couple's pedigree, candidate mutations were examined in the woman's parents as well as her uncles. Additionally, in silico investigations were performed through SWISS-MODEL, MolProbity, ProSA, Py- Mol, and FATCAT tools. The most important mutation diagnosed in the woman (R1362Q in the 35th exon of CACNA1F), was observed in her mother and her two uncles. The mutation was also screened in both her father and her fiancé, but they had no mutations. After medical examinations of carriers, there was no sign of any eye impairment. Other mutations were TCTN2 (c.1613-2A>G), TARS (p.K319E), SPEG (p.E3020K), CPS1 (p.A1180V), MYO3A (p.I736M), NNT (p.R968Q), MED23 (p.K406T). Bioinformatics analyses indicated no alteration in the mutant structure of CACNA1F (Q1362) compared with the normal structure (R1362).

Conclusion: Conclusively, the current study emphasizes the non-pathogenic effect of missense mutation R1362Q in the 35th exon of CACNA1F in association with ocular diseases. This will ensure the reports of this mutation as healthy instead of uncertain in the literature and databanks.

Aims: Epilepsy, the tendency to have recurrent seizures, can have various causes, including brain tumors, genetics, stroke, brain injury, infections, and developmental disorders. Epileptic seizures are usually transient events. They normally leave no trace after the postictal recovery period has passed.

Background: An electroencephalogram (EEG) can only detect brain activity during the recording. It will be detected if an epileptogenic focus or generalized abnormality is active during the recording.

Objective: This work demonstrated a smart seizure detection system for Healthcare IoT, which is a challenging problem of EEG data analysis.

Method: The study suggested an integrated methodology in recognition of the drawbacks of manual identification and the significant negative effects of uncontrollable seizures on patients' lives.

Result: The research shows remarkable accuracy, up to 100% in some experiments, by combining classifier ensembles like Decision Trees, Logistic Regression, and Support Vector Machine with different signal processing techniques like Discrete Wavelet Transform, Hjorth Parameters, and statistical features. The results were compared using the kNN classifier, compared with other datasets and other state-of-the-art techniques.

Conclusion: Healthcare IoT is further utilized by the methodology, which takes a comprehensive approach using classifier ensembles and signal processing approaches resulting in real-time data to help them make better decisions. This demonstrates how well the suggested method works for smart seizure detection, which is a crucial development for better patient outcomes.