Case report of three consecutive lues maligna infections in an HIV-infected patient

Lues maligna is a rare presentation of an infection with Treponema pallidum. Here we report three lues maligna infections with severe dermatological manifestations in a single HIV-1 infected individual. Despite the start of highly active antiretroviral therapy and a substantial increase in CD4 cell count after the first episode, he developed consecutive episodes. We assume a specific immunological predisposition to react to T. pallidum in this patient

Auswirkungen und Veränderungen bei HIV-assoziierten Hauterkrankungen durch HAART (Highly Active Antiretroviral Therapy)

Prevalence of HIV-associated skin diseases under HAART (highly active antiretroviral therapy) Introduction: The spectrum of skin diseases in HIV-infected patients is wide, with cutaneous infections being most common. The introduction of highly active antiretroviral therapy [HAART], especially in combination with protease inhibitors, strongly improved the immune functions and reduced the incidence, morbidity and lethality of HIV associated opportunistic infections [OI]. In order to evaluate the functional immune reconstitution under HAART, with the increasing number of CD4-T cells, we analysed frequency and severity of HIV associated skin diseases. Methods: In a retrospective study we selected two different cohorts of the HIV outpatient clinic, Department of Dermatology and Allergology, University of Munich. Cohort I included 157 HIV-infected patients treated with HAART, documented from 1996-98. Cohort II included 753 HIV-infected patients without HAART, documented from 1985-95. Mantel-Haenszel’s test for comparison of cohorts was used. In addition, we performed an intra-individual analysis of all parameters in 56 patients of cohort I. Findings: The prevalence of oral candidiasis, Kaposi sarcoma [KS], persistent ulcerating herpes simplex was lower than estimated, especially at CD4 counts under 200/µl. The prevalence of recurrent herpes simplex , zoster and ano-genital warts increased under HAART. With the increasing of the CD4 counts the prevalence of mollusca contagiosa and oral hairy leukoplakia decreased. On the whole the severity of HIV associated skin diseases was milder under HAART. Discussion: Our data demonstrated that HAART directly impairs the manifestation of candidiasis and KS. Our data show that the functional immune reconstitution under HAART indirectly influences the manifestation of recurrent herpes simplex , zoster and ano-genital warts. This retrospective study of 910 HIV-infected patients shows that the spectrum of HIV associated skin diseases altered under HAART. The estimation of the immune status and the life expectancy as determined by the absolute CD4-T cells in the peripheral blood and the viral load has to be re-evaluated.Auswirkungen und Veränderungen bei HIV-assoziierten Hauterkrankungen durch HAART (highly active antiretroviral therapy) Einleitung: Das Spektrum HIV-assoziierter Hauterkrankungen ist groß. Seit Einführung der hochaktiven antiretroviralen Therapie [HAART] wurde eine Verbesserung der immunologischen Lage sowie die Abnahme der Inzidenz opportunistischer Erkrankungen [OI], der Morbidität und der Letalität beobachtet. Ziel dieser Arbeit war es, die Wirkung der seit 1996 eingesetzten HAART, bestehend aus zwei reversen Transkriptasehemmern und einem Proteaseinhibitor, und deren Induktion von CD4-Lymphozyten auf die Häufigkeit und den Verlauf von HIV-assoziierten Hauterkrankungen hin zu untersuchen. Methoden: Es wurden 157 HIV-Patienten unter HAART mit 753 HIV-Patienten ohne HAART verglichen, die sich in der Immunambulanz der Klinik und Poliklinik für Dermatologie und Allergologie der LMU München in den Jahren 85-98 vorstellten. Darüber hinaus wurde bei 56 HAART-behandelten Patienten zwischen 1996 und 1998 die Verteilung der Häufigkeit und des Ausprägungsgrades HIV-assoziierter Hauterkrankungen im Zusammenhang mit der Modifikation von CD4-Zellen und Viruslast [VL] bestimmt. Die Auswertung erfolgte aufgrund der in der Immunambulanz retrospektiv angefertigten Basis- und Verlaufsdokumentations-bögen; die statistische Auswertung erfolgte mittels des für Kohorten geeigneten Signifikanztestes nach Mantel-Haenszel. Ergebnisse: Die Prävalenz des Mundsoors [OK], der Kaposi Sarkome [KS], des persistierenden/ulzerierenden Herpes simplex [HSV] nahm unter HAART stärker ab als es durch den Anstieg der CD4-Zellen zu erwarten war. Die Prävalenz des HSV-rezidivans, des Zosters und der Condyloma acuminata nahm unter HAART deutlich zu. Mit Anstieg der CD4-Zellen unter HAART nahm die Prävalenz der Mollusca contagiosa und der oralen Haarleukoplakie ab. Insgesamt nahm der Ausprägungs-grad HIV-assoziierter Hauterkrankungen unter HAART ab. Diskussion: Die Ergebnisse dieser Arbeit zeigen erstens, dass HAART einen direkten Einfluß auf die Entwicklung von KS und OK haben muß, zweitens, dass HAART indirekt durch partielle Immunrekonstitution auf HSV-rezidivans, Zoster und Condylomata acuminata wirkt. Zusammengefaßt zeigt die retrospektive Studie an 910 HIV-Patienten, dass HAART die HIV-assoziierten opportunistischen Krankheiten der Haut sehr unterschiedlich beeinflußt. Die Aussagekraft der wichtigsten Surrogat-Marker, die Konzentration der CD4-Zellen im peripheren Blut und die VL, muß bei Patienten mit HAART neu evaluiert werden

Comparison of translation loads for standard and alternative genetic codes

<p>Abstract</p> <p>Background</p> <p>The (almost) universality of the genetic code is one of the most intriguing properties of cellular life. Nevertheless, several variants of the standard genetic code have been observed, which differ in one or several of 64 codon assignments and occur mainly in mitochondrial genomes and in nuclear genomes of some bacterial and eukaryotic parasites. These variants are usually considered to be the result of non-adaptive evolution. It has been shown that the standard genetic code is preferential to randomly assembled codes for its ability to reduce the effects of errors in protein translation.</p> <p>Results</p> <p>Using a genotype-to-phenotype mapping based on a quantitative model of protein folding, we compare the standard genetic code to seven of its naturally occurring variants with respect to the fitness loss associated to mistranslation and mutation. These fitness losses are computed through computer simulations of protein evolution with mutations that are either neutral or lethal, and different mutation biases, which influence the balance between unfolding and misfolding stability. We show that the alternative codes may produce significantly different mutation and translation loads, particularly for genomes evolving with a rather large mutation bias. Most of the alternative genetic codes are found to be disadvantageous to the standard code, in agreement with the view that the change of genetic code is a mutationally driven event. Nevertheless, one of the studied alternative genetic codes is predicted to be preferable to the standard code for a broad range of mutation biases.</p> <p>Conclusions</p> <p>Our results show that, with one exception, the standard genetic code is generally better able to reduce the translation load than the naturally occurring variants studied here. Besides this exception, some of the other alternative genetic codes are predicted to be better adapted for extreme mutation biases. Hence, the fixation of alternative genetic codes might be a neutral or nearly-neutral event in the majority of the cases, but adaptation cannot be excluded for some of the studied cases.</p

Eosinophilic pustular folliculitis (EPF) in a patient with HIV infection

Eosinophilic pustular folliculitis is a chronic, recurrent dermatosis, of unknown etiology, which is histologically characterized by folliculotropic inflammatory infiltrates with admixed eosinophils in the dermis. It has often presented with immunosuppression and especially with HIV-Infection. In the HAART-era, eosinophilic pustular folliculitis has become a rarity. It is often being misdiagnosed as acne vulgaris, rosacea, bacterial folliculitis, dermatomycosis and seborrheic dermatitis. The treatment of this disease may be difficult

T Cell Responses against Orthopoxviruses in HIV-Positive Patients

A global outbreak of predominantly sexually transmitted mpox infections, outside endemic regions, was reported in May 2022. Thereafter, risk groups were vaccinated against smallpox, a structurally related orthopoxvirus. In the current study, we analyzed T cell responses against peptides derived from orthopoxviruses in 33 HIV-positive patients after two vaccinations against smallpox and in 10 patients after mpox infection. We established an ELISpot assay, detecting either the secretion of the pro-inflammatory cytokine interferon (IFN)-γ or interleukin (IL)-2. After vaccination, 21 out of 33 patients (64%) showed specific IFN-γ secretion and 18 (55%) specific IL-2 secretion, defined as >3-fold higher specific value than negative control and at least 4 spots above the negative control. After mpox infection, all patients showed specific IFN-γ secretion and 7 out of 10 (70%) IL-2 secretion. In vaccinated patients, IFN-γ responses were significantly lower than in patients with mpox infection (median response 4.5 vs. 21.0 spots, p p < 0.05). Thus, T cell responses were detectable in two thirds of HIV-positive patients after vaccination and were even more abundant and vigorous after mpox infection

Superior skin cancer classification by the combination of human and artificial intelligence

Background: In recent studies, convolutional neural networks (CNNs) outperformed dermatologists in distinguishing dermoscopic images of melanoma and nevi. In these studies, dermatologists and artificial intelligence were considered as opponents. However, the combination of classifiers frequently yields superior results, both in machine learning and among humans. In this study, we investigated the potential benefit of combining human and artificial intelligence for skin cancer classification. Methods: Using 11,444 dermoscopic images, which were divided into five diagnostic categories, novel deep learning techniques were used to train a single CNN. Then, both 112 dermatologists of 13 German university hospitals and the trained CNN independently classified a set of 300 biopsy-verified skin lesions into those five classes. Taking into account the certainty of the decisions, the two independently determined diagnoses were combined to a new classifier with the help of a gradient boosting method. The primary end-point of the study was the correct classification of the images into five designated categories, whereas the secondary end-point was the correct classification of lesions as either benign or malignant (binary classification). Findings: Regarding the multiclass task, the combination of man and machine achieved an accuracy of 82.95%. This was 1.36% higher than the best of the two individual classifiers (81.59% achieved by the CNN). Owing to the class imbalance in the binary problem, sensitivity, but not accuracy, was examined and demonstrated to be superior (89%) to the best individual classifier (CNN with 86.1%). The specificity in the combined classifier decreased from 89.2% to 84%. However, at an equal sensitivity of 89%, the CNN achieved a specificity of only 81.5% Interpretation: Our findings indicate that the combination of human and artificial intelligence achieves superior results over the independent results of both of these systems. (C) 2019 The Author(s). Published by Elsevier Ltd

Systematic outperformance of 112 dermatologists in multiclass skin cancer image classification by convolutional neural networks

Background: Recently, convolutional neural networks (CNNs) systematically outperformed dermatologists in distinguishing dermoscopic melanoma and nevi images. However, such a binary classification does not reflect the clinical reality of skin cancer screenings in which multiple diagnoses need to be taken into account. Methods: Using 11,444 dermoscopic images, which covered dermatologic diagnoses comprising the majority of commonly pigmented skin lesions commonly faced in skin cancer screenings, a CNN was trained through novel deep learning techniques. A test set of 300 biopsy-verified images was used to compare the classifier's performance with that of 112 dermatologists from 13 German university hospitals. The primary end-point was the correct classification of the different lesions into benign and malignant. The secondary end-point was the correct classification of the images into one of the five diagnostic categories. Findings: Sensitivity and specificity of dermatologists for the primary end-point were 74.4% (95% confidence interval [CI]: 67.0-81.8%) and 59.8% (95% CI: 49.8-69.8%), respectively. At equal sensitivity, the algorithm achieved a specificity of 91.3% (95% CI: 85.5-97.1%). For the secondary end-point, the mean sensitivity and specificity of the dermatologists were at 56.5% (95% CI: 42.8-70.2%) and 89.2% (95% CI: 85.0-93.3%), respectively. At equal sensitivity, the algorithm achieved a specificity of 98.8%. Two-sided McNemar tests revealed significance for the primary end-point (p < 0.001). For the secondary end-point, outperformance (p < 0.001) was achieved except for basal cell carcinoma (on-par performance). Interpretation: Our findings show that automated classification of dermoscopic melanoma and nevi images is extendable to a multiclass classification problem, thus better reflecting clinical differential diagnoses, while still outperforming dermatologists at a significant level (p < 0.001). (C) 2019 The Author(s). Published by Elsevier Ltd