Structural elements undergo multiple levels of damage at various locations due to environments and critical loading conditions. The level of damage and its location can be predicted using acoustic emission (AE) waveforms that are captured from the generation of inherent microcracks. Existing AE methods are reliant on the feature selection of the captured waveforms and may be subjective in nature. To automate this process, this paper proposes a deep-learning model to predict the damage severity and its expected location using AE waveforms. The model is based on a densely connected convolutional neural network (CNN) that offers superior feature extraction and minimal training data requirements. Time-domain AE waveforms are used as inputs of the proposed model to automate the process of predicting the severity of damage and identifying the expected location of the damage in structural elements. The proposed approach is validated using AE data collected from a concrete beam and a wooden beam and plate. The results show the capability of the proposed method for predicting the level of damage with an accuracy range of 92-95% and identifying the approximate location of damage with 90-100% accuracy. Thus, the proposed method serves as a robust technique for damage severity prediction and localization in civil structures.

Atezolizumab plus bevacizumab (Atez/BV) as first-line therapy and lenvatinib (LEN) as second-line therapy are the recommended treatments for patients with unresectable hepatocellular carcinoma. Adverse immune events caused by immune checkpoint inhibitors (such as Atez) generally only occur several months after administration; therefore, the potential influence of the first-line treatment on second-line treatment is not clear. The present study investigated the safety of second-line LEN treatment (2nd LEN) by comparing the adverse events (AEs) of 2nd LEN after first-line Atez/BV treatment for unresectable liver cancer, with those of first-line LEN treatment (1st LEN). Patients who received Atez/BV as first-line therapy and 2nd LEN, or those who received 1st LEN at Ogaki Municipal Hospital (Ogaki, Japan) between April 2018 and September 2023 were retrospectively evaluated for treatment duration and AEs. The median treatment duration for patients in the 1st LEN (n=39) and 2nd LEN (n=13) groups was 151.0 days [95% confidence interval (CI) 77-303 days] and 128.5 days (95% CI 68-270 days), respectively (P=0.385). A greater proportion of patients showed elevated aspartate aminotransferase/alanine aminotransferase levels in the 2nd LEN group (76.9%) compared with those in the 1st LEN group (46.2%) (P=0.016). Hypothyroidism was more common in those receiving 2nd LEN (46.2%) than 1st LEN (12.8%) (P=0.016). In addition, grade 1 (three patients) and grade 2 (three patients) hypothyroidism was observed in patients receiving 2nd LEN. For these six patients, during first-line Atez/BV treatment, four patients had grade 0 hypothyroidism and two patients had grade 1 hypothyroidism (P=0.025). In conclusion, patients receiving 2nd LEN after treatment with Atez/BV are at an increased risk of hypothyroidism.

Groundwater has a significant influence on the mechanical properties of surrounding rock. Aiming at the large deformation of surrounding rock of red layer soft rock tunnel affected by groundwater, the uniaxial graded loading tests were carried out on red beds soft rock with different water content. The failure process of the specimen was monitored by acoustic emission (AE) and the crack evolution law was analyzed, and the scanning electron microscopy (SEM) was used to compare the microstructure of the specimens before and after immersion. Combined with fractal theory, the monofractal and multifractal characteristics of AE ringing count during the loading process of red beds soft rock were analyzed. The results show that, with the gradual increase of water content, the AE ringing count before the yield stage gradually decreased, and the corresponding cumulative ringing count at the same time gradually decreased, and the decrease was large in the early stage of immersion, and decreased in the later stage. The cumulative ringing curve gradually slowed down, the internal crack appeared earlier, the cumulative ringing curve stepped significantly, the AE signal amplitude gradually weakened, and the bandwidth of each frequency band gradually decreased. The failure of red beds soft rock with different water content is dominated by shear crack, and with the gradual increase of water content, the proportion of shear crack increases gradually, and the AE b value decreases gradually. With the gradual increase of the relative peak strength, the correlation dimension D of red beds soft rock with different water content increases first and then decreases. At 80% of the relative peak strength, the correlation dimension D reaches its maximum value and then drops sharply until it is maintained at a relatively low level, and the correlation dimension D gradually decreases with the water content. The fitting correlation coefficients of different water content (lnC(r), lnr) are all above 0.9, indicating that the AE ringing count of water-bearing red beds soft rock has fractal characteristics, and the higher the correlation coefficient, the higher the self-similarity of AE ringing count sequence. As the weight q gradually increases, the generalized fractal dimension D(q) gradually decreases. When q ≠ 0, under the condition of the same q, D(q) presents a trend of first increasing and then decreasing. The multifractal characteristics of AE ringing count of red beds soft rock with different water content is inverted \'U\' shape. From the natural state to immerse 1 d, the ∆α gradually increases, and from 1 to 7 d, the ∆α gradually decreases, where Δα = αmax - αmin represents the spectral width of the multifractal spectrum. When saturation is not reached, ∆f < 0 indicates that the number of cracks in the specimen is small, when saturation is reached, ∆f > 0 indicates that a large number of cracks are generated inside the specimen and macro cracks are formed, where Δf = f (αmax) - f (αmin) represents the frequency relationship between different signals of different sizes. This research can provide a reliable theoretical basis for the construction and maintenance of large deformation of water-rich soft rock tunnel excavation, and have certain engineering significance.

UNASSIGNED: Systemic AL amyloidosis, a plasma cell dyscrasia, is characterized by the production of misfolded immunoglobulin light chain. These misfolded proteins aggregate into amyloid fibrils and deposit throughout the body, resulting in widespread organ dysfunction and ultimately death. Achieving rapid and maximal elimination of the plasma cell clone is crucial to long-term survival. Daratumumab, an anti-CD38 monoclonal antibody delivered intravenously, has been swiftly incorporated into standard first-line treatment regimens. A novel formulation of daratumumab has been developed that can be injected subcutaneously.
UNASSIGNED: As a retrospective qualitative review of prior publications involving daratumumab, this work briefly summarizes the existing data regarding the safety and efficacy of subcutaneous (SC) daratumumab, compared to intravenous (IV) daratumumab. SC daratumumab appears to deliver the same disease benefit as IV daratumumab to patients with decreased infusion-related reactions (IRRs), decreased time for administration, and similar rates of adverse events (AEs) intrinsically related to daratumumab.
UNASSIGNED: SC daratumumab is preferred over IV daratumumab, but the clinical situation ultimately should determine route of administration. Further investigation into cost-effectiveness benefit is warranted.

The pediatric febrile infection-related epilepsy syndrome (FIRES) manifests with encephalopathy with super-refractory status epilepticus (SE) a few days after or accompanying a febrile illness. It often results in refractory epilepsy and cognitive dysfunction in previously healthy children and adolescents. The underlying pathomechanism is unknown, which is why causative neuronal and/or synaptic antibodies have been discussed. We report a prospective consecutive cohort of 14 children (10 male, four female) diagnosed with FIRES in the acute phase, whose serum and CSF were comprehensively screened for underlying synaptic/neuronal autoantibodies. The median age at onset was 6  years (range 4-9  years). None of the children had a medical history of epilepsy. Duration of SE varied from less than 1 week to 2.5  months (Median: 1  month, range  < 1  week-2.5  months). Clinical response to treatment with antiseizure medications was poor as well as the outcome: one child died in the acute phase of SE, and two died in the long term. All surviving children showed neuropsychological impairments. No underlying synaptic or neuronal autoantibodies were identified in 13 of 14 children\'s sera or CSF. One child had currently uncharacterized neuronal autoantibodies in CSF, yet clinical presentation was atypical for FIRES. Based on our findings, the child was later diagnosed with autoimmune encephalitis (AE). We conclude that FIRES is not an autoantibody-mediated disease. However, a comprehensive screening for known and yet unknown antineuronal antibodies in serum and CSF is warranted to rule out AE mimicking FIRES.

Due to their complex aerosol characteristics, it is crucial to analyze the trends and properties of atmospheric aerosols over the eastern Mediterranean countries. This study comprehensively evaluates Aerosol Optical Depth (AOD) and Angström Exponent (AE) trends and aerosol classification over Türkiye, using the MERRA-2 reanalysis data from 1980 to 2019. The spatial distributions of AOD and AE were determined across various temporal scales, including multiannual, 5-year intervals, seasonal, and monthly periods. The analysis of the spatial distribution of AOD values revealed that the mean values in the northwestern areas, ranging from 0.20 to 0.25, were comparatively higher than those observed in the eastern regions, which ranged from 0.10 to 0.15. Between 1980 and 1994, the AOD values gradually increased, followed by a subsequent decline from 1995 to 2019. Based on 5-year intervals between 1980 and 2019, the coastal regions exhibited higher AOD values than the inland areas. Specifically, higher AOD values were noted between May and August, whereas lower values were observed during autumn and winter. Additionally, higher AE values were detected over the northwestern region, while the southeastern region had the lowest AE values, particularly during spring, attributed to the frequent occurrence of dust transport events in this area. The AOD and AE values were also examined in different city types, using the population thresholds of the European Commission. The global city category consisting only of Istanbul showed the highest AOD values across all seasons, while the category of very small cities, which includes 12 cities, had the lowest AOD values. Furthermore, this study investigated the contributions of dominant aerosol categories across various city types based on multiannual and seasonal variations of AOD and AE. The results showed that mixed and continental aerosols had higher portions across all city types. However, biomass burning/industrial and mixed aerosol categories were more prominent in global and large cities. Overall, this study provides a comprehensive overview of the atmospheric aerosol properties in Türkiye and can serve as a useful guide for researchers intending to conduct future studies utilizing AOD and AE data obtained through MERRA-2 aerosol diagnosis.

The condition of a joint in a human being is prone to wear and several pathologies, particularly in the elderly and athletes. Current means towards assessing the overall condition of a joint to assess for a pathology involve using tools such as X-ray and magnetic resonance imaging, to name a couple. These expensive methods are of limited availability in resource-constrained environments and pose the risk of radiation exposure to the patient. The prospect of acoustic emissions (AEs) presents a modality that can monitor the joints\' conditions passively by recording the high-frequency stress waves emitted during their motion. One of the main challenges associated with this sensing method is decoding and linking acquired AE signals to their source event. In this paper, we investigate AEs\' use to identify five kinds of joint-wear pathologies using a contrast of expert-based handcrafted features and unsupervised feature learning via deep wavelet decomposition (DWS) alongside 12 machine learning models. The results showed an average classification accuracy of 90 ± 7.16% and 97 ± 3.77% for the handcrafted and DWS-based features, implying good prediction accuracies across the various devised approaches. Subsequent work will involve the potential application of regressions towards estimating the associated stage and extent of a wear condition where present, which can form part of an online system for the condition monitoring of joints in human beings.

Fatigue strength is one of the most important properties of composite materials because it directly relates to their lifespan. Acoustic emission (AE) is a passive structural health monitoring (SHM) technique that provides real-time damage detection based on stress waves generated by cracks in the structure. This study evaluates the damage progression on glass fiber reinforced polyester composite specimens using different approaches of machine learning. Different methodologies for damage detection and characterization of AE parameters are presented. Three different ensemble learning methods namely, XGboost, LightGBM, and CatBoost were chosen to predict damages and AE parameters. SHAP values were used to select AE key features and K-means algorithms were employed to classify damage severity. The accuracy of these approaches demonstrates the reliability of various machine learning techniques in predicting the fatigue life of composite materials using acoustic emission.

Aspergillus endocarditis (AE) is a highly fatal infection that can occur in heart valve replacement, pacemaker implantation and other heart surgeries, and early recognition and sufficient diagnosis are challenging. Here, we report the case of a 68-year-old male with a history of dilated cardiomyopathy and pacemaker implantation who had a repeated fever with failed antibacterial treatment and sterile blood culture. He developed endocarditis, and the culture and biopsy of vegetation tissue showed the abundant presence of septate hyphae, which was subsequently identified as Aspergillus fumigatus by internal transcribed spacer (ITS) sequencing. Although the patient had serious side effects from voriconazole, he had a good prognosis following surgery and prolonged caspofungin antifungal therapy of 42 consecutive days. We discuss the diagnosis and treatment strategy of AE, and recommend galactomannan assays and next-generation sequencing for a timely diagnosis. Early surgical intervention combined with prompt antifungal therapy appears significant for survival.

Zinc is an important trace mineral in the human body and a daily intake of zinc is required to maintain a healthy status. Over the past decades, zinc has been used in formulating topical and systemic therapies for various skin disorders owing to its wound healing and antimicrobial properties. Zinc transporters play a major role in maintaining the integrity of the integumentary system by controlling zinc homeostasis within dermal layers. Mutations and abnormal function of zinc-transporting proteins can lead to disease development, such as spondylocheirodysplastic Ehlers-Danlos syndrome (SCD-EDS) and acrodermatitis enteropathica (AE) which can be fatal if left untreated. This review discusses the layers of the skin, the importance of zinc and zinc transporters in each layer, and the various skin disorders caused by zinc deficiency, in addition to zinc-containing compounds used for treating different skin disorders and skin protection.