Seasonal breeding is a universal reproductive strategy in many animals. Hypothalamic genes, especially type 2 and 3 iodothyronine deiodinases (Dio2/3), RFamide‐related peptide 3 (Rfrp‐3), kisspeptin (Kiss‐1) and gonadotropin‐releasing hormone (GnRH), are involved in a photoperiodic pathway that encodes seasonal signals from day length in many vertebrate species. However, the seasonal expression patterns of these genes in wild mammals are less studied. Here, we present a four‐year field investigation to reveal seasonal rhythm and age‐dependent reproductive activity in male Brandt's voles (Lasiopodomys brandtii) and to detect relationships among seasonal expression profiles of hypothalamic genes, testicular activity, age and annual day length. From breeding season (April) to nonbreeding season (October), adult male voles displayed a synchronous peak in gonadal activity with annual day length around summer solstice, which was jointly caused by age structure shifts and age‐dependent gonadal development patterns. Overwintered males maintained reproductive activity until late in the breeding season, whereas most newborn males terminated gonadal development completely, except for a minority of males born early in spring. Consistently, the synchronous and opposite expression profiles of Dio2/3 suggest their central function to decode photoperiodic signals and to predict the onset of the nonbreeding season. Moreover, changes in Dio2/3 signals may guide the actions of Kiss‐1 and Rfrp‐3 to regulate the age‐dependent divergence of reproductive strategy in wild Brandt's vole. Our results provide evidence on how hypothalamic photoperiod genes regulate seasonal breeding in a natural rodent population.

Accurate and reliable segmentation of liver tissue and liver tumor is essential for the follow-up of hepatic diagnosis. In this paper, we present a method for liver segmentation and a method for liver tumor segmentation. The two methods are grounded on a novel unified level set method (LSM), which incorporates both region information and edge information to evolve the contour. This level set framework is more resistant to edge leakage than the single-information driven LSMs for liver segmentation and surpasses many other models for liver tumor segmentation. Specifically, for liver segmentation, a hybrid image preprocessing scheme is used first to convert an input CT image into a binary image. Then with manual setting of a few seed points on the obtained binary image, the following region-growing is performed to extract a rough liver region with no leakage. The unified LSM is proposed at last to refine the segmentation result. For liver tumor segmentation, a local intensity clustering based LSM coupled with hidden Markov random field and expectation-maximization (HMRF-EM) algorithm is applied to construct an enhanced edge indicator for the unified LSM. With this development, expected segmentation results can be obtained via the unified LSM, even for complex tumors. The two methods were evaluated with various datasets containing a local hospital dataset, the public datasets SLIVER07, 3Dircadb, and MIDAS via five measures. The proposed liver segmentation method outperformed other previous semiautomatic methods on the SLIVER07 dataset and required less interaction. The proposed liver tumor segmentation method was also competitive with other state-of-the-art methods in both accuracy and efficiency on the 3Dircadb database. Our methods are evaluated to be accurate and efficient, which allows their adoptions in clinical practice.

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The methodology of a new OA(9) (3(4)) matrix and an analysis of variance technique were developed during the optimisation of extracting pesticidal alkaloids from Cynanchum komarovii. Many factors were found to affect the amount of alkaloids extracted: which parts of the plant were used - roots gave the highest yield; particle size of the material - highest yield when the plant was sieved through size 40 mesh; the type of solvent - a mixture of 0.1% hydrochloric acid with industrial alcohol was the best; The ratio of material to solvent - 1 part plant material to eight parts solvent gave the highest extraction; the duration of the extraction - 72 h and the number of re-extractions - three also improved yield. The ratio of material to solvent had the most important impact on extraction efficiency while the number of re-extractions had a minor effect. The pesticidal activity of extracts was enhanced using this optimised technique.

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