The suprachiasmatic nucleus (SCN) receives direct retinal input from the intrinsically photosensitive retinal ganglion cells (ipRGCs) for circadian photoentrainment. Interestingly, the SCN is the only brain region that receives equal inputs from the left and right eyes. Despite morphological assessments showing that axonal fibers originating from ipRGCs cover the entire SCN, physiological evidence suggests that only vasoactive intestinal polypeptide (VIP)/ gastrin-releasing peptide (GRP) cells located ventrally in the SCN receive retinal input. It is still unclear, therefore, which subpopulation of SCN neurons receives synaptic input from the retina and how the SCN receives equal inputs from both eyes. Here, using single ipRGC axonal tracing and a confocal microscopic analysis in mice, we show that ipRGCs have elaborate innervation patterns throughout the entire SCN. Unlike conventional retinal ganglion cells (RGCs) that innervate visual targets either ipsilaterally or contralaterally, a single ipRGC can bilaterally innervate the SCN. ipRGCs form synaptic contacts with major peptidergic cells of the SCN, including VIP, GRP, and arginine vasopressin (AVP) neurons, with each ipRGC innervating specific subdomains of the SCN. Furthermore, a single SCNprojecting ipRGC can send collateral inputs to many other brain regions. However, the size and complexity of the axonal arborizations in non-SCN regions are less elaborate than those in the SCN. Our results provide a better understanding of how retinal neurons connect to the central circadian pacemaker to synchronize endogenous circadian clocks with the solar day.melanopsin | circadian | suprachiasmatic nucleus | non-image-forming functions | ipRGCs T he suprachiasmatic nucleus (SCN) houses a central pacemaker that orchestrates circadian (circa: "about" and diem: "day") behaviors that cycle with a period close to 24 h. This endogenous clock is self-sustained even in the complete absence of external stimuli, but can be entrained to the light/dark cycle of the solar day in a process defined as circadian photoentrainment (1). In mammals, phototransduction solely occurs in the retina (2). Retinal ganglion cells (RGCs) are projection neurons of the retina that send light information to brain targets (3). Although the majority of RGCs project to brain areas involved in object tracking and image formation, some RGCs also innervate non-image-forming brain regions to influence circadian activity, sleep, the pupillary light response, mood, and learning functions (4).Recent studies showed that a small subpopulation of RGCs expresses a photopigment called melanopsin (Opn4), making these cells intrinsically photosensitive (ip)RGCs (5-7). It is now known that there are at least five different ipRGC subtypes (M1-M5) (8, 9). Using genetic tracing techniques, it was shown that ipRGCs send projections to non-image-forming centers in the brain, including the SCN, which receives retinal input predominantly from M1 ipRGCs (10-12) and to a lesser extent from M2 ipRGCs (12). The SCN is a smal...

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Human papillomavirus (HPV) 52 and 58 are oncogenic HPV types prevalent in Asia. Our study aims to explore intratypic variants of HPV 52 and 58 in Taiwan. A total of 11,923 women were enrolled from seven townships in [1991][1992]. HPV DNA in their cervical cells was detected and typed by EasyChip V R HPV blot. Among 424 participants infected with HPV 52 and/or 58, nucleotide variations were determined in cervical cell samples of 406 participants by the polymerase chain reaction sequencing of the long control region, E6 and E7 genes. Nonprototype-like variants including lineages B and C were detected in 278 (99.3%) of 280 HPV 52 samples. The prototype and prototype-like group (lineage A) of HPV58 was found in 132 (98.5%) of 134 HPV 58 samples, with sublineage A1, A2 and A3 variant in 14.2, 27.6 and 56.7%, respectively. Among women infected with single HPV 52 type, the C variant (vs. B variant) was associated with an increased prevalence of cytologically diagnosed high-grade squamous intraepithelial lesion or worse lesions showing an age-adjusted odds ratio (95% confidence interval, CI) of 5.2 (1.0-27.6) and an increased prevalence of histologically confirmed high-grade cervical intraepithelial neoplasia or more severe lesions with an age-adjusted odds ratio (95% CI) of 7.6 (1.3-43.8). It was concluded that frequency distributions of HPV 52 and 58 variants in Taiwan were different from those in European and American populations. The association between C variant of HPV 52 and prevalence of cervical neoplasia needs further validation.Oncogenic human papillomavirus (HPV) is the major cause of cervical cancer. In addition to HPV 16 and 18, HPV 52 and 58 are also considered high-risk types for cervical intraepithelial lesions (CINs) and invasive carcinoma. 1,2 The unusually high prevalence of HPV 52 and 58 has been reported in Chinese populations living in China 3,4 and Taiwan. [5][6][7][8] In a previous report of our study, the prevalence of high-grade squamous intraepithelial lesion (HSIL) or worse lesions among participants with single-type infection of HPV 16, HPV 58 and HPV 52 at study entry was 31.9, 35.7 and 13.3%, respectively. 9 The participants infected with HPV 16, HPV 58 or HPV 52 had an increased prevalence of cervical cancer and carcinoma in situ (CIS).Intratypic HPV variants are characterized by the difference of less than 2% in nucleotide sequence from the prototypic L1 gene. 10 The genetic divergence among variants can differ by as much as 5% in the noncoding long control region (LCR). 11 But a study based on the complete genome analyses of HPV 16 showed that the E5-L2 intergenic region and the E4 and E5 genes are also hypervariable. 12 In a recent study, HPV variants can be classified based on their nucleotide sequence differences with most variants differing by <3%; type-specific variant lineages are defined based on a complete genome nucleotide sequence having >1% dissimilarity with the prototype and are named according to the phylogenetic tree topologies for each individual type. 13 Previous studie...

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Abstract. We introduce a novel framework for automatic 3D facial expression analysis in videos. Preliminary results demonstrate editing facial expression with facial expression recognition. We first build a 3D expression database to learn the expression space of a human face. The real-time 3D video data were captured by a camera/projector scanning system. From this database, we extract the geometry deformation independent of pose and illumination changes. All possible facial deformations of an individual make a nonlinear manifold embedded in a high dimensional space. To combine the manifolds of different subjects that vary significantly and are usually hard to align, we transfer the facial deformations in all training videos to one standard model. Lipschitz embedding embeds the normalized deformation of the standard model in a low dimensional generalized manifold. We learn a probabilistic expression model on the generalized manifold. To edit a facial expression of a new subject in 3D videos, the system searches over this generalized manifold for optimal replacement with the 'target' expression, which will be blended with the deformation in the previous frames to synthesize images of the new expression with the current head pose. Experimental results show that our method works effectively.

Changes in external light patterns can alter cell activities in peripheral tissues through slow entrainment of the central clock in suprachiasmatic nucleus (SCN). It remains unclear whether cells in otherwise photo-insensitive tissues can achieve rapid responses to changes in external light. Here we show that light stimulation of animals' eyes results in rapid activation of hair follicle stem cells with prominent hair regeneration. Mechanistically, light signals are interpreted by M1-type intrinsically photosensitive retinal ganglion cells (ipRGCs), which signal to the SCN via melanopsin. Subsequently, efferent sympathetic nerves are immediately activated. Increased norepinephrine release in skin promotes hedgehog signaling to activate hair follicle stem cells. Thus, external light can directly regulate tissue stem cells via an ipRGC-SCN autonomic nervous system circuit. Since activation of sympathetic nerves is not limited to skin, this circuit can also facilitate rapid adaptive responses to external light in other homeostatic tissues.