Food-related inhibitory control deficits in young male adults with obesity: Behavioral and ERP evidence from a food-related go/no-go task.

PURPOSE: Obesity poses a pervasive challenge to global public health, which is linked to adverse physical health outcomes and cognitive decline. Cognitive function, particularly food-related cognitive function, plays a critical role in sustaining a healthy weight and mitigating the progression of obesity. The aim of this study was to investigate the behavioral and neuroelectronic aspects of food-related inhibitory functions in young adult males with obesity. METHODS: Forty-nine participants with obesity and healthy-weight were recruited (BMI = 35.83 ± 5.06 kg/m2 vs. 22.55 ± 1.73 kg/m2, age = 24.23 ± 4.55 years vs. 26.00 ± 3.97 years). A food-related Go/No-go task which included 6 distinct blocks in a randomized order was conducted to investigate the general and food-related inhibitory control. 180 stimulus images from the Food Picture Database encompassing high-calorie food, low-calorie food, and neutral images were selected. Behavioral (Go RT, Go ACC, No-go ACC) and event-related potential measures (N2 and P3 amplitude) during the food-related Go/No-go task were measured. RESULTS: The main findings indicated that the group with obesity exhibited lower No-go accuracy, slower go reaction times, and smaller P3 amplitudes in high-calorie, low-calorie foods, and neutral picture, compared to the normal-weight group, but with no group difference in N2. Additionally, high-calorie food induced larger N2 and P3 amplitude than the neutral stimuli. CONCLUSIONS: Young male adults with obesity exhibit poorer inhibitory control in both food and non-food domains, specifically in slower reaction time and reduced accuracy, featuring difficulties in neural resource recruitment during the inhibitory control process. Additionally, the P3 component could serve as sensitive indicators to reveal the neural mechanisms of inhibitory control deficits in obesity, while the N2 and P3 components may differentiate the neural differences between high-calorie foods and non-foods in inhibitory control processing. Food, especially high-calorie food, induces more neural resources and may exacerbate the poor inhibitory ability towards food in obesity. Targeted interventions such as exercise interventions, cognitive training as well as neuromodulation interventions are warranted in the future to improve impaired general and food-related inhibitory functions in the obese populations, offering both theoretical and practical frameworks for obesity prevention and treatment.

Long distance high resolution FMCW laser ranging with phase noise compensation and 2D signal processing.

A long distance high resolution frequency-modulated continuous wave (FMCW) laser rangefinder with phase noise compensation and two-dimensional (2D) data processing skills is developed. Range-finding ladar consists of a continuously chirped laser source, an auxiliary reference interferometer, and a monostatic optical transceiver for target illumination and return photon collection. To extend the range unambiguity and lower the electronic processing bandwidth, a two-step laser frequency chirping scheme is adopted, where a long pulse width, small frequency bandwidth laser chirping signal are used in step 1 for coarse distance estimation, and a short pulse width and large frequency bandwidth laser chirping signal are applied afterwards for step 2 high resolution distance realization. An auxiliary reference interferometer is to record the phase noise originated from the laser source to compensate for phase errors induced in the target return photons. The 2D data processing skill helps to coherently sum up all the phase noise removed echo photons to achieve high resolution range peak extraction with high detection sensitivity. Experimental demonstration shows that the proposed FMCW ladar at 1550 nm wavelength with a laser chirping bandwidth of 10 GHz and electronic processing bandwidth of 200 MHz can measure a corner cube test target in an outdoor atmospheric environment, and the measurement results are 12013.905 m with a 2.4 cm range resolution under strong return photon levels and 12013.920 m with a 2.5 cm range resolution under weak return photon levels.

FMCW lidar multitarget detection based on skeleton tree waveform matching.

Frequency-modulated continuous-wave lidar realizes 4D (three-dimensional space and velocity) imaging of the scene by emitting positive and negative frequency sweep laser signals. The premise of it is to identify the frequency points corresponding to the same target in the positive and negative sweep echo signals. For dechirp receiving, there is usually one peak in the frequency spectrum of the positive and negative sweep signals, respectively. Therefore, it is easy to identify and match the peaks. But in a complex environment, the laser beam will irradiate multiple targets at the same time. In addition, beam scanning and target motion cause the echo spectrum to broaden. The above reasons make it extremely difficult to identify and match peaks in practice. To solve this problem, the waveform-matching algorithm based on the skeleton tree is first applied to multitarget echo pairing. The basic idea of the algorithm is to quantify the target echo hierarchically to generate a skeleton tree. The generation of nodes is based on the relative amplitude of waveform peaks and reflects the characteristics of wave crests nesting. Then the similarity of the signal is determined by comparing the distance between the two signal waveform feature trees. Finally, the waveforms are matched in terms of similarity. To further substantiate the role of the proposed algorithm, imaging experiments and related comparative data for different targets have been completed. The results show that the accuracy of matching processed by the algorithm exceeds 90%, which is improved by about 50% compared with not using the algorithm for the target whose overlapping part accounts for a large proportion of itself.

Correction to: Fine mapping of powdery mildew resistance gene Pm4e in bread wheat (Triticum aestivum L.).

Unfortunately, the style of the units was incorrectly published ("cm" instead of "cM") throughout the original article.

Fine mapping of powdery mildew resistance gene Pm4e in bread wheat (Triticum aestivum L.).

MAIN CONCLUSION: Fine mapping of wheat powdery mildew-resistance gene Pm4e to a 0.19 cM interval with sequence-based markers provides the foundation for map-based cloning and marker-assisted selection with breeder-friendly markers. Powdery mildew caused by Blumeria graminis f. sp. tritici is a wheat foliar disease that poses a serious threat to global wheat production. Pm4 is a resistance gene locus that has played a key role in controlling this disease in wheat production and a few resistance alleles of this locus have been identified. We have previously mapped the Pm4e allele to a 6.7 cM interval on chromosome 2AL. In this study, Pm4e was delimited to a 0.19 cM interval flanked by Xwgrc763 and Xwgrc865, through employment of a larger segregating population, derived from the cross of resistant parent D29 with susceptible parent Yangmai 158 (Y158), and enrichment of the genetic interval with markers developed on Chinese Spring (C.S.) survey sequence. In this interval, Pm4e co-segregated with a few markers, some of which were either D29-dominant or Y158-dominant, implying great sequence variation in the interval between D29 and Y158. Most of these co-segregation markers could not differentiate the Pm4 alleles from each other. Survey of 55 wheat cultivars with four co-dominant markers showed that the Pm4e-co-segregating loci always co-exist. Annotation of the Pm4e interval-corresponding C.S. sequence revealed more than a dozen resistance gene analogs clustered in a 2.4 Mb region, although C.S. is susceptible to the Pm4e-avirulent isolate Bgt2. This study has established the foundation for map-based cloning of Pm4e. Moreover, some of the co-dominant markers developed in this study could help in marker-assisted transfer of Pm4e into elite cultivars.