Heterogenous Subtypes of Late-Life Depression and Their Cognitive Patterns: A Latent Class Analysis.

Background: Late-life depression (LLD), characterized by cognitive deficits, is considered heterogeneous across individuals. Previous studies have identified subtypes with diverse symptom profiles, but their cognitive patterns are unknown. This study aimed to investigate the subtypes of LLD and the cognitive profile of each group. Methods: In total, 109 depressed older adults were enrolled. We performed latent class analysis using Geriatric Depression Scale items as indicators to generate latent classes. We compared the sociodemographic and clinical characteristics with cognitive functions between groups and conducted regression analysis to investigate the association between class membership and variables with significant differences. Results: Two classes were identified: the "pessimistic" group was characterized by pessimistic thoughts and the "worried" group with a relatively high prevalence of worry symptoms. The two groups did not differ in sociodemographic characteristics. The "pessimistic" group showed a higher rate of past history of depression and lower age of onset. The "worried" group had more physical comorbidities and a higher rate of past history of anxiety. The "pessimistic" group was more impaired in general cognitive function, executive function, information processing speed, and attention. Lower general and executive functions were associated with the membership in the "pessimistic" group. Conclusions: Subjects with pessimistic symptoms and subjects with a propensity to worry may form two distinct subtypes of late-life depression with different cognitive profiles. Further, the cognitive evaluation of subjects with pessimistic symptoms is of utmost importance.

Frequency-specific age-related changes in the amplitude of spontaneous fluctuations in autism.

Background: Autism spectrum disorder is characterized by atypical developmental changes during brain maturation, but regional brain functional changes that occur with age and across different frequency bands are unknown. Therefore, the current study aimed to explore potential age and frequency band-related changes in the regional brain activities in autism. Methods: A total of 65 participants who met the DSM-IV criteria for autistic disorder and 55 typically developed (TD) participants (both age 6-30 years) were recruited in the current study. The two groups were matched in age (t=-1.314, P=0.191) and gender (χ2=2.760, P=0.097). The amplitude of low-frequency fluctuations (ALFF) was employed to explore the effect of development on spontaneous brain activity in individuals with autism and in TD participants across slow-5 (0.01-0.027 Hz), slow-4 (0.027-0.073 Hz), and slow-3 (0.073-0.1 Hz) frequency bands. The diagnosis-by-age interaction effect in the whole brain voxels in autism and TD groups was investigated. Results: Autism individuals showed significantly higher ALFF in the dorsal striatum in childhood (Caudate cluster: t=3.626, P=0.001; Putamen cluster: t=2.839, P=0.007) and remarkably lower ALFF in the dorsal striatum in adulthood (Caudate cluster: t=-2.198, P=0.038; Putamen cluster: t=-2.314, P=0.030) relative to TD, while no significant differences were observed in adolescence (all P>0.05). In addition, abnormal ALFF amplitudes were specific to the slow-4 (0.027-0.073 Hz) frequency band in the clusters above. Conclusions: The current study indicated abnormal development patterns in the spontaneous activity of the dorsal striatum in autism and highlighted the potential role of the slow-4 frequency band in the pathology of autism. Also, the potential brain mechanism of autism was revealed, suggesting that autism-related variations should be investigated in a specific frequency.

Effects of altrenogest on reproductive performance of gilts and sows: A meta-analysis.

Altrenogest is a synthetic progestogen that allows for synchronization of the time of estrus in swine. Its effect on reproductive performance, however, is inconsistent due to conflicting data in the scientific literature. A meta-analysis of published data, therefore, was performed to determine whether altrenogest affects gilt and sow reproductive performance. Altrenogest administration to pigs enhanced the number of piglets born alive per litter (NBA), total number born per litter (TNB), estrous rate within 10 days after treatment (ER10) and pregnancy rate (PR) as well as the farrowing rate (FR) of gilts. The NBA and TNB of primiparous sows fed altrenogest were improved although FR was less. In multiparous sows, altrenogest treatment did not result in any improvement for any of the five analyzed variables. Additionally, 14-day treatment regimens for gilts and >8-days for primiparous sows improved reproductive performance and extent of estrous synchrony. The effects of altrenogest on reproductive performance of swine were parity and treatment duration dependent.

[Characteristic wavelength variable optimization of near-infrared spectroscopy based on Kalman filtering].

Combining classical Kalman filter with NIR analysis technology, a new method of characteristic wavelength variable selection, namely Kalman filtering method, is presented. The principle of Kalman filter for selecting optimal wavelength variable was analyzed. The wavelength selection algorithm was designed and applied to NIR detection of soybean oil acid value. First, the PLS (partial leastsquares) models were established by using different absorption bands of oil. The 4 472-5 000 cm(-1) characteristic band of oil acid value, including 132 wavelengths, was selected preliminarily. Then the Kalman filter was used to select characteristic wavelengths further. The PLS calibration model was established using selected 22 characteristic wavelength variables, the determination coefficient R2 of prediction set and RMSEP (root mean squared error of prediction) are 0.970 8 and 0.125 4 respectively, equivalent to that of 132 wavelengths, however, the number of wavelength variables was reduced to 16.67%. This algorithm is deterministic iteration, without complex parameters setting and randomicity of variable selection, and its physical significance was well defined. The modeling using a few selected characteristic wavelength variables which affected modeling effect heavily, instead of total spectrum, can make the complexity of model decreased, meanwhile the robustness of model improved. The research offered important reference for developing special oil near infrared spectroscopy analysis instruments on next step.

Matrix effects in analysis of ß-agonists with LC-MS/MS: influence of analyte concentration, sample source, and SPE type.

The synergistic influences of analyte concentration, sample source, and solid-phase extraction (SPE) type on matrix effects in the multiresidue analyses of eight ß-agonists with LC-ESI-MS/MS were evaluated. Porcine muscle and liver extracts and urine from diverse sources were purified by strong or mixed-mode cation exchange and molecularly imprinted polymer SPE cartridges, respectively. Three spiked concentrations (2, 10, and 20 ng/mL) of eight ß-agonists in the purified matrices and the different sample sources were analyzed. The results show that for most ß-agonists there are significant differences in matrix effects between analyte concentrations or sample sources (P < 0.05), whereas there is no significant difference in matrix effects between different SPE cartridges (P > 0.05). Results from main effects testing indicated that analyte concentration was the main effector.