Porokeratosis: Two Faces, One Family

Porokeratosis is a disorder of keratinisation whose pathogenesis is yet unclear. It has been postulated that it results from the proliferation of an abnormal clone of keratinocytes, triggered by several factors, such as immunosuppression or prolonged ultraviolet exposure. Various clinical forms are recognized whose common denominator is a keratotic ring surrounding a central zone of atrophy. The histological hallmark is the cornoid lamella, a thin column of hyperproliferative abnormal keratinocytes. We describe two cases of porokeratosis. A 67-year-old woman with an erythematous purplish round plaque surrounded by a keratotic border that had appeared 6 years previously on the left sural region was diagnosed as ‘giant’ porokeratosis. A 49-year-old man presented with small papules coalescent in an erythematous oval plaque on the lateral side of the left foot consistent with linear porokeratosis

Identification of the Red-Necked Longhorn Beetle Aromia bungii (Faldermann, 1835) (Coleoptera: Cerambycidae) with real-Time PCR on frass

Aromia bungii (Faldermann, 1835) (Coleoptera: Cerambycidae), the red-necked longhorn beetle is native to eastern Asia, where it is an important wood-borer of fruit and ornamental species of the genus Prunus. A. bungii is a quarantine pest in the European Union, following its accidental introduction and establishment in Germany and Italy, and is currently included in the list of priority pests. To confirm its infestations in outbreak areas, adult or larval specimens are needed to perform morphological or molecular analyses. The presence of A. bungii larvae inside the attacked trees makes the collection of specimens particularly difficult. Thus, we present two diagnostic protocols based on frass analysis with real-time PCR (probe and SYBR Green). The results obtained show that a non-invasive approach for detecting the presence of this harmful invasive pest can be a reliable and accurate alternative diagnostic tool in phytosanitary surveys, as well as to outline a sustainable pest management strategy

The proliferation marker Chromatin Assembly Factor-1 is of clinical value in predicting the biological behaviour of salivary gland tumours.

Salivary gland tumours (SGT) constitute a diagnostically challenging group of neoplasms with frequently unpredictable clinical outcome. The proliferation rate facilitates the identification of aggressive SGT. The Chromatin Assembly Factor-1 (CAF-1) is a major epigenetic regulator of nuclear chromatin organization during DNA replication. It plays a critical function in human tumourigenesis and has been proposed as a new proliferation and prognostic marker for some malignancies. This study focused on the role of CAF-1/p60 protein as a marker of clinical value for SGT. The expression of CAF-1/p60 was evaluated by immunohistochemistry on a retrospective series of 362 surgically excised benign and malignant SGT with different histogenesis and, when available, on fine-needle pre-surgical cytological biopsies. The resulting data were compared with traditional prognostic parameters, including the expression of the routine proliferation marker ki67/MIB1. CAF-1/p60 was detectable in all SGT, with highest degree of expression in metastasizing malignant tumours. Moreover, the cases of benign tumours which progressed to carcinoma during the follow-up, showed significantly higher CAF-1/p60 expression than non-progressing benign SGT, both on histological sections and cytological smears of the primary tumour. Cox's multiple regression analysis selected CAF-1/p60 expression as the best independent predictor of cancer development for benign SGT (p<0.0001), and the best independent predictor of metastasis onset for malignant tumours (p<0.0004). Overexpression of CAF-1/p60, on histological and/or cytological samples, characterizes malignant SGT with aggressive behaviour, irrespective of their specific histotype, and allows the early diagnosis of progression toward malignancy of morphologically benign tumours

Development of a loop-mediated isothermal amplification (LAMP) assay for the identification of the invasive wood borer Aromia bungii (Coleoptera: Cerambycidae) from frass

The red-necked longhorn beetle Aromia bungii (Faldermann, 1835) (Coleoptera: Cerambycidae) is native to east Asia, where it is a major pest of cultivated and ornamental species of the genus Prunus. Morphological or molecular discrimination of adults or larval specimens is required to identify this invasive wood borer. However, recovering larval stages of the pest from trunks and branches causes extensive damage to plants and is timewasting. An alternative approach consists in applying non-invasive molecular diagnostic tools to biological traces (i.e., fecal pellets, frass). In this way, infestations in host plants can be detected without destructive methods. This paper presents a protocol based on both real-time and visual loop-mediated isothermal amplification (LAMP), using DNA of A. bungii extracted from fecal particles in larval frass. Laboratory validations demonstrated the robustness of the protocols adopted and their reliability was confirmed performing an inter-lab blind panel. The LAMP assay and the qPCR SYBR Green method using the F3/B3 LAMP external primers were equally sensitive, and both were more sensitive than the conventional PCR (sensitivity > 103 to the same starting matrix). The visual LAMP protocol, due to the relatively easy performance of the method, could be a useful tool to apply in rapid monitoring of A. bungii and in the management of its outbreaks

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

The Gene Ontology knowledgebase in 2023

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project