Search Results (22)

Background/Objectives: Cutaneous manifestations of inborn errors of immunity (IEI) are among the most common and often early signs of these disorders, estimated to affect about 40% of patients with IEI, and in some cases, they provide the first diagnostic clue. Skin findings in IEI are heterogeneous and include recurrent skin infections, severe atopic dermatitis, autoimmune manifestations, as well as atypical granulomatous dermatoses, neoplastic lesions, pigmentation disorders, and changes involving hair and nails. Early recognition of these manifestations and linking them to the appropriate immunologic defect is crucial for establishing the diagnosis and initiating targeted therapy. Methods: This paper reviews the dermatologic phenotypes associated with IEI, with particular emphasis on a tabular classification of skin lesions corresponding to specific immunologic defects. Relevant literature was analyzed to summarize characteristic cutaneous presentations and current diagnostic approaches, highlighting the importance of interdisciplinary evaluation. Results: Cutaneous findings in IEI encompass a wide spectrum of infectious, inflammatory, autoimmune, and neoplastic manifestations. Systematic classification of these lesions facilitates earlier recognition of underlying immune defects and supports differential diagnosis. Dermatologic signs frequently precede systemic manifestations, making them valuable early clinical indicators of IEI. Conclusions: Recognition of dermatologic manifestations is critical for early diagnosis of IEI. Interdisciplinary collaboration between dermatologists, immunologists, and other specialists improves diagnostic accuracy and patient management. Current therapeutic strategies range from symptomatic treatment to targeted therapies, and personalized approaches improve prognosis and quality of life in patients with IEI. Full article

Hair dyes are widely used cosmetic products that can contain trace metals and metalloids, posing potential health risks through dermal exposure. This study aimed to assess and compare the concentrations of selected metals and metalloids in six brands of commercial hair dyes sold in Brazil and Paraguay and to evaluate their average daily dermal exposure doses, hazard quotients, hazard indices, and carcinogenic risk. Concentrations of Cr, Cd, Co, Cu, Fe, Mn, Mo, Ni, As, Al, Pb, Ba, Ag, and Zn in hair dye were quantified by standardized analytical methods. The Paraguayan brand showed the highest levels for several elements, including As (4.17 mg/kg), Al (130.276 mg/kg), and Fe (30.033 mg/kg). Estimated dermal exposure doses reached up to 3.35 × 10⁻⁶ mg/kg/day for arsenic, 1.68 × 10⁻³ mg/kg/day for aluminum, and 8.59 × 10⁻⁸ mg/kg/day for chromium. Although all hazard indices remained below 1, suggesting low non-carcinogenic risk, the calculated carcinogenic risk for arsenic in the Paraguayan product was 1.23 × 10⁻⁵, entering the medium-risk range. These findings highlight relevant differences in raw material control and potential cumulative health risks, especially for frequent users. Continuous quality control, harmonized regulatory standards, clear labeling, and further biomonitoring studies are strongly recommended to minimize long-term exposure to toxic elements in hair dye formulations and to ensure safer consumer products. Full article

The Yanomami Indigenous Land (YIL) is heavily impacted by illegal gold mining, leading to significant contamination by methylmercury, a neurotoxin that poses severe risks to human health. The fetal brain is particularly susceptible to the neurotoxic effects of methylmercury, which can result in mild mental retardation (MMR). The goal of this study was to estimate the burden of disease (BoD) associated with methylmercury exposure in the YIL and its economic implications. The BoD calculations followed World Health Organization (WHO) methodologies. To estimate the local BoD, hair samples were collected from women of childbearing age in the Waikás, Mucajaí, Paapiu, and Maturacá regions. For broader estimates, data from the scientific literature were used. The average hair methylmercury concentrations in these investigated regions were 6.21 µg/g, 3.86 µg/g, 3.53 µg/g, and 2.96 µg/g, respectively. The MMR incidence rate (IR) in children ranged from 2.08 to 4.47 per 1000 in these regions. The Disability-Adjusted Life Years (DALYs) per 1000 births varied from 24.8 to 53.4. In the Worst-Case Scenario, MMR-IR reached 9 per 1000, with DALYs per 1000 births rising to 109.6. The estimated economic impact of methylmercury exposure ranged from USD 716,750 to USD 3,153,700. This study is the first to quantify the MMR incidence due to mercury in the YIL, highlighting the severe threat posed by gold mining to the health and survival of the Yanomami people. Full article

Deep Neural Networks (DNNs) have been widely adopted in several advanced artificial intelligence applications due to their competitive accuracy to the human brain. Nevertheless, the superior accuracy of a DNN is achieved at the expense of intensive computations and storage complexity, requiring custom expandable hardware, i.e., graphics processing units (GPUs). Interestingly, leveraging the synergy of parallelism and edge computing can significantly improve CPU-based hardware platforms. Therefore, this manuscript explores levels of parallelism techniques along with edge computation offloading to develop an innovative hardware platform that improves the efficacy of deep learning computing architectures. Furthermore, the multitask learning (MTL) approach is employed to construct a parallel multi-task classification network. These tasks include face detection and recognition, age estimation, gender recognition, smile detection, and hair color and style classification. Additionally, both pipeline and parallel processing techniques are utilized to expedite complicated computations, boosting the overall performance of the presented deep face analysis architecture. A computation offloading approach, on the other hand, is leveraged to distribute computation-intensive tasks to the server edge, whereas lightweight computations are offloaded to edge devices, i.e., Raspberry Pi 4. To train the proposed deep face analysis network architecture, two custom datasets (HDDB and FRAED) were created for head detection and face-age recognition. Extensive experimental results demonstrate the efficacy of the proposed pipeline-parallel architecture in terms of execution time. It requires 8.2 s to provide detailed face detection and analysis for an individual and 23.59 s for an inference containing 10 individuals. Moreover, a speedup of 62.48% is achieved compared to the sequential-based edge computing architecture. Meanwhile, 25.96% speed performance acceleration is realized when implementing the proposed pipeline-parallel architecture only on the server edge compared to the sever sequential implementation. Considering classification efficiency, the proposed classification modules achieve an accuracy of 88.55% for hair color and style classification and a remarkable prediction outcome of 100% for face recognition and age estimation. To summarize, the proposed approach can assist in reducing the required execution time and memory capacity by processing all facial tasks simultaneously on a single deep neural network rather than building a CNN model for each task. Therefore, the presented pipeline-parallel architecture can be a cost-effective framework for real-time computer vision applications implemented on resource-limited devices. Full article

Gastric ulcer disease and other potentially painful gastric conditions are among the most common afflictions adversely affecting the welfare of domestic equids. A large percentage of affected animals may not display the classic signs of gastric disease, such as unexplained weight loss, poor hair coat, and inappetence until the disease becomes severe. As a clinical service within our equine referral hospital, we routinely evaluate 24-h video recorded samples of horses to assist clinicians in identifying subtle discomfort and potential sources or to scan for infrequent neurologic or cardiac-related behavioral events. Empirically, we have recognized discomfort behaviors that appear to be uniquely associated with gastric disease. These include frequent attention to the cranial abdomen (nuzzling, swatting, nipping, and/or caudal gaze focused on the abdomen caudal to the elbow) and/or deep abdominal stretching, often within the context of eating, drinking, and/or anticipating feeding. To systematically evaluate the reliability of these purported gastric discomfort behaviors, we reviewed 30 recent 24-h video behavior evaluation cases for which (1) the clinical video behavior evaluation had been carried out without knowledge of the history and presenting complaint and (2) direct gastric examination had confirmed gastric disease status at the time. Twenty-four of the thirty cases showed gastric discomfort behavior, and all twenty-four had either gastric ulcers (n = 21) and/or gastric impaction (n = 3). Of the six cases not showing gastric discomfort behaviors, four were free of gastric disease, while two had mild lesions. Comparing horses with and without gastric disease, gastric discomfort behaviors were reported in 24 of the 26 (92%) with gastric ulcers or gastric impaction, compared to none of the four gastric disease-free horses. Although a larger prospectively designed study is needed to confidently estimate the sensitivity and specificity or the associations of behavior with the type or severity of gastric disease, these results confirm our long-held clinical impression of a behavioral signature for gastric discomfort in the horse. Full article

Objectives. To evaluate the accuracy and reproducibility of measurements obtained using the Bellus3D Face Application on a mobile smartphone by comparing them to direct measurements on pre-marked and blank face scans. Materials and Methods. Twenty-five healthy young adults (six males and nineteen females; age range 20–30 years) were included in this prospective cross-sectional study, with the only exclusion criterion being the presence of significant facial hair interfering with the placement and visualization of landmarks. Image acquisitions were performed using an iPhone XR with the Bellus3D FaceApp face scanning application, an iOS application for smartphones. Ten single midfacial and five paired bilateral landmarks were defined and marked. Two face scans were performed on each patient, both on blank and marked faces, and distances were measured directly with calipers and digitally. Results. The random error values were 1.0 mm and 0.4 mm for the manual point placement and measurements and virtual point placement on blank faces, respectively. The two methods used (the direct method and acquisition on faces with landmarks) demonstrate relatively similar reliability (ICC > 0.8); however, a paired t-test showed that the differences between several measurements were statistically significant (p < 0.05). Regardless of the method used, there was a systematic error for various values that included the nose and mouth (p < 0.05). The measurements demonstrating the most significant differences between the methods were those that included the tip of the nose, with the mean differences being −4.4–3.3 mm. The measurements of the distances that estimate face “depth” showed the greatest consistency irrespective of the tested method (p > 0.05 and ICC > 0.8). Conclusions. The use of the Bellus3D FaceApp is precise and reproducible for certain areas of the face, but digital reconstruction errors prohibit, for the time being, the use of this technology in everyday clinical practice. The noted discrepancies were consistent and more prevalent for specific areas such as the tip of the nose. Further investigations are required to determine other sources of error and for other smartphone-based applications released for 3D face image acquisitions. Full article

Tinea capitis is a fungal infection of the scalp and hair caused by dermatophyte molds, that most often affects children and may also affect adults. Previous estimates suggest that between 3% and 11% of all tinea capitis cases worldwide occur in adults, although updated epidemiological studies are needed to reassess the prevalence of tinea capitis in adult populations specifically. Postmenopausal adult women are most often affected by tinea capitis, with African American or Black women particularly at risk. Adults who experience crowded living conditions, who live in close proximity to animals, who are immunosuppressed, and/or who live in households with affected children are at greatest risk of infection. Tinea capitis can be non-inflammatory or inflammatory in nature, and the subtype affects the extent and severity of clinical symptoms. Fungal culture and potassium hydroxide preparations are the most commonly used diagnostic tools. Trichoscopy, defined as dermoscopic imaging of the scalp and hair, is a useful adjunct to the physical examination. The mainstay of therapy is oral antifungal therapy, and topical therapy alone is not recommended. Since tinea capitis infection is uncommon in adults, there are no widely accepted treatment guidelines. Rather, the same medications used for tinea capitis infection among children are recommended for adults at varying doses, including griseofulvin, and terbinafine, and, less commonly, itraconazole and fluconazole. The prognosis for tinea capitis in adults is typically excellent when prompt and adequate treatment is administered; however, delayed diagnosis or inadequate treatment can result in scarring alopecia. Over the past decade, dermatophyte infections resistant to treatment with topical and oral antifungal agents have emerged. While tinea capitis infections resistant to antifungal therapy have been rarely reported to date, antifungal resistance is rising among superficial fungal infections in general, and antifungal stewardship is necessary to ensure that resistance to treatment does not develop among dermatophytes that cause tinea capitis. Full article

Activity indices are used to determine the presence and activity of small mammals, such as the hair index derived from the use of hair tubes. In contrast to trapping animals, hair tubes are non-invasive and less labor-intensive, and appear to be a suitable alternative in appropriate settings. We developed a method to calculate hair density semi-automatically. In addition, hair tube data were validated with field data using wildlife cameras for the small mammal community in grassland, wheat crops, and hedges to assess how well data from hair tubes match data from wildlife cameras. Adhesive tape with hair from hair tubes was processed and scanned. The resulting images were analyzed using a newly developed computer program that enables background and adhesive tape to be automatically distinguished from hair, providing a quantitative measure of hair density. Based on validation with wildlife cameras, hair tubes seem to be a suitable tool to estimate small mammal activity at the community level in several habitats. There was a moderate-to-strong positive correlation of the hair tube index with the sum of voles and Apodemus individuals (activity index) recorded in grasslands (Spearman’s correlation coefficient 0.43), hedges (0.79), and wheat (0.44). The newly developed computer program allows the automatic calculation of hair density, making it easier to assess the activity of small mammals. Full article

The contexts where there are mining and agriculture activities are potential sources of risk to human health due to contamination by chemical mixtures. These contexts are frequent in several Colombian regions. This study explored the potential association between the frequency of micronuclei and pesticides and elements in regions with ferronickel (Montelibano, Córdoba) and gold (Nechí, Antioquia) mining, and a closed native mercury mine (Aranzazu, Caldas), with an emphasis in the potential effect of selenium as a potential chelator. A cross-sectional study was carried out with 247 individuals. Sociodemographic, occupational, and toxicological variables were ascertained. Blood and urine samples were taken for pesticide analysis (5 organophosphates, 4 organochlorines, and 3 carbamates), 68 elements were quantified in hair, and micronuclei were quantified in lymphocytes. The mixtures of elements were grouped through principal component analysis. Prevalence ratios were estimated with robust variance Poisson regressions to explore associations. Interactions of selenium with toxic elements were explored. The highest concentrations of elements were in the active mines. The potentially most toxic chemical mixture was observed in the ferronickel mine. Pesticides were detected in a low proportion of participants (<2.5%), except paraoxon-methyl in blood (27.55%) in Montelibano and paraoxon-ethyl in blood (18.81%) in Aranzazu. The frequency of micronuclei was similar in the three mining contexts, with means between 4 to 7 (p = 0.1298). There was great heterogeneity in the exposure to pesticides and elements. The “hormetic effect” of selenium was described, in which, at low doses, it acts as a chelator in Montelibano and Aranzazu, and at high doses, it can enhance the toxic effects of other elements, maybe as in Nechí. Selenium can serve as a protective agent, but it requires adaptation to the available concentrations in each region to avoid its toxic effects. Full article

Collagen VI-related myopathies are characterized by severe muscle involvement and skin involvement (keratosis pilaris and impaired healing with the development of abnormal scars, especially keloids). Scalp involvement and hair loss have not been reported among cutaneous changes associated with collagen VI mutations. The aim of this study is to describe the clinical, trichoscopic, and histological findings of the scalp changes in patients affected by COL VI mutations and to estimate their prevalence. Patients with Ullrich congenital muscular dystrophy were enrolled and underwent clinical and trichoscopic examinations and a scalp biopsy for histopathology. Five patients were enrolled, and all complained of hair loss and scalp itching. One patient showed yellow interfollicular scales with erythema and dilated, branched vessels, and the histological findings were suggestive of scalp psoriasis. Two patients presented with scarring alopecia patches on the vertex area, and they were histologically diagnosed with folliculitis decalvans. The last two patients presented with scaling and hair thinning, but they were both diagnosed with folliculitis and perifolliculitis. Ten more patients answered to a “scalp involvement questionnaire”, and six of them confirmed to have or have had scalp disorders and/or itching. Scalp involvement can be associated with COL VI mutations and should be investigated. Full article

(1) Objectives: To evaluate the frequency and factors associated with the Post-COVID-19 Syndrome (PCS) in COVID-19 survivors after 3 and 6 months of hospital discharge; (2) Methods: We conducted a cohort study with patients who were hospitalized with COVID-19 in a referral public hospital in Brasília, Federal District, Brazil. After 3 and 6 months of discharge, patients answered a questionnaire about PCS symptoms. Poisson regression with robust variance was used to estimate the crude and adjusted prevalence ratios (PR and aPR) of PCS. (3) Results: The prevalence of PCS was 81% and 61% after 3 and 6 months of hospital discharge, respectively. The main symptoms after 3 months of discharge were hair loss (44%), fatigue (42%), and memory loss (39%); while after 6 months, they were memory loss (29%) and fatigue (27%). In the multivariate analysis, the main factor associated with PCS was female gender (aPR): 1.28 (1.16–1.41) and 1.60 (1.34–1.90), 3 and 6 months after hospital discharge, respectively. Hypercholesterolemia was also associated with PCS after 3 months aPR of 1.15 (1.04–1.27). After 6 months of discharge, obesity [aPR: 1.22 (1.03–1.45)] and pronation [aPR: 1.15 (1.06–1.25)] were relevant associated factors. (4) Conclusions: The prevalence of PCS was high in COVID-19 survivors who had the moderate and severe forms of the disease. Memory loss was the most persistent symptom. Our data pointed to female gender, hypercholesterolemia, obesity, and pronation during hospitalization as relevant PCS-associated risk factors. Full article

Infantile hemangiomas occur in 3 to 10% of infants. To predict the clinical course and counsel on treatment, it is crucial to accurately determine the hemangiomas’ extension, volume, and location. However, this can represent a challenge because hemangiomas may present irregular patterns or be covered by hair, or their depth may be difficult to estimate. Diagnosis is commonly made by clinical inspection and palpation, with physicians basing their diagnoses on visual characteristics such as area, texture, and color. Doppler ultrasonography or magnetic resonance imaging are normally used to estimate depth or to confirm difficult assessments. This paper presents an alternative diagnosis tool—thermography—as a useful, immediate means of carrying out accurate hemangioma examinations. We conducted a study analyzing infantile hemangiomas with a custom thermographic system. In the first phase of the study, 55 hemangiomas of previously diagnosed patients were analyzed with a thermal camera over several sessions. An average temperature variation before and after treatment of −0.19 °C was measured. In the second phase, we selected nine patients and assessed their evolution over nine months by analyzing their thermographic images and implementing dedicated image processing algorithms. In all cases, we found that the thermal image analysis concurred with the independent diagnoses of two dermatologists. We concluded that a higher temperature inside the tumor in the follow-up was indicative of an undesirable evolution. Full article

Early and accurate detection of scalp hair loss is imperative to provide timely and effective treatment plans to halt further progression and save medical costs. Many techniques have been developed leveraging deep learning to automate the hair loss detection process. However, the accuracy and robustness of assessing hair loss severity still remain a challenge and barrier for transitioning such a technique into practice. The presented work proposes an efficient and accurate algorithm to classify hair follicles and estimate hair loss severity, which was implemented and validated using a multitask deep learning method via a Mask R-CNN framework. A microscopic image of the scalp was resized, augmented, then processed through pre-trained ResNet models for feature extraction. The key features considered in this study concerning hair loss severity include the number of hair follicles, the thickness of the hair, and the number of hairs in each hair follicle. Based on these key features, labeling of hair follicles (healthy, normal, and severe) were performed on the images collected from 10 men in varying stages of hair loss. More specifically, Mask R-CNN was applied for instance segmentation of the hair follicle region and to classify the hair follicle state into three categories, following the labeling convention (healthy, normal and severe). Based on the state of each hair follicle captured from a single image, an estimation of hair loss severity was determined for that particular region of the scalp, namely local hair loss severity index (P), and by combining P of multiple images taken and processed from different parts of the scalp, we constructed the hair loss severity estimation ($P_{avg}$) and visualized in a heatmap to illustrate the overall hair loss type and condition. The proposed hair follicle classification and hair loss severity estimation using Mask R-CNN demonstrated a more efficient and accurate algorithm compared to other methods previously used, enhancing the classification accuracy by 4 to 15%. This performance supports its potential for use in clinical settings to enhance the accuracy and efficiency of current hair loss diagnosis and prognosis techniques. Full article

Occupational illnesses, such as cancer, cause more deaths each year than occupational accidents. Occupational carcinogens include physical, chemical, biological and organizational hazards. In the United Arab Emirates (UAE), migrant workers account for 80% of labor. Being sometimes employed as unskilled workers and more willing to work in demanding jobs, their vulnerability and exposure may be increased. This study aimed to estimate the prevalence of occupational exposure to workplace carcinogens among migrant workers in the UAE. A sample of employees working in construction, cleaning, dry cleaning, mechanic workshops and hair salons were recruited and interviewed. Using OccIDEAS (an online assessment tool), participants were asked questions about their demographics, work history and regular tasks. Exposure to various carcinogens was estimated using the in-built algorithms of OccIDEAS. A sample of 1778 workers was included. The sample consisted of workers from Bangladesh (19.2%), India (31%), Nepal (4.7%), Pakistan (29.9%) and the Philippines (4.8%), with the rest from other nationalities. Overall, the prevalence of probable exposure was considerable, with the highest among drivers (96%) and the lowest among laundry workers (52%). Moderate to high exposure was found to 20 different carcinogens. Self-rated health among those who were exposed to carcinogens was significantly lower than among those not exposed (AOR = 0.783, 95% CI [0.638–0.961]). Exposure to several different carcinogens is relatively common in the UAE among migrant workers. Further strengthening policies and the implementation of tailored interventions are needed to prevent exposure to occupational carcinogens and, consequently, to combat occupational cancer in the UAE. Full article

Arsenic (As) and its compounds are widely used in many applications. Long-term exposure to As can cause acute and chronic poisoning. In severe cases, it can lead to adverse effects, such as gene mutation, cell cancer and fetal malformation. The objective of this study was to accurately estimate As exposure frequency and time. Quantitative analysis of As in single hairs obtained from APL (acute promyelocytic leukemia) patients treated with As₂O₃ was performed by LA-ICP-MS. An informative As concentration distribution profile of single hair was applied to estimate the As exposure frequency and time. As exposure frequency was estimated according to the number of As concentration peaks. As exposure time was estimated according to the hair growth length in combination with the hair growth rate. The validation results demonstrate that this method was more efficient than the traditional method; compared with the traditional method, which provides estimates in months, our model shortened the As exposure time estimate to the range of a few days, which considerably improved the inference accuracy. Therefore, these results can be used for forensic toxicology studies, environmental exposure monitoring, etc. Full article