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This study deals with 3D laser investigation on the border between the human lymph node T-zone and germinal centre. Only a few T-cells specific for antigen selected B-cells are allowed to enter germinal centres. This selection process is guided by sinus structures, chemokine gradients and inherent motility of the lymphoid cells. We measured gaps and wall-like structures manually, using IMARIS, a 3D image software for analysis and interpretation of microscopy datasets. In this paper, we describe alpha-actin positive and semipermeable walls and wall-like structures that may hinder T-cells and other cell types from entering germinal centres. Some clearly defined holes or gaps probably regulate lymphoid traffic between T- and B-cell areas. In lymphadenitis, the morphology of this border structure is clearly defined. However, in case of malignant lymphoma, the wall-like structure is disrupted. This has been demonstrated exemplarily in case of angioimmunoblastic T-cell lymphoma. We revealed significant differences of lengths of the wall-like structures in angioimmunoblastic T-cell lymphoma in comparison with wall-like structures in reactive tissue slices. The alterations of morphological structures lead to abnormal and less controlled T- and B-cell distributions probably preventing the immune defence against tumour cells and infectious agents by dysregulating immune homeostasis.
In Bone Tissue Engineering (BTE), autologous bone-regenerative cells are combined with a scaffold for large bone defect treatment (LBDT). Microporous, polylactic acid (PLA) scaffolds showed good healing results in small animals. However, transfer to large animal models is not easily achieved simply by upscaling the design. Increasing diffusion distances have a negative impact on cell survival and nutrition supply, leading to cell death and ultimately implant failure. Here, a novel scaffold architecture was designed to meet all requirements for an advanced bone substitute. Biofunctional, porous subunits in a load-bearing, compression-resistant frame structure characterize this approach. An open, macro- and microporous internal architecture (100 µm–2 mm pores) optimizes conditions for oxygen and nutrient supply to the implant’s inner areas by diffusion. A prototype was 3D-printed applying Fused Filament Fabrication using PLA. After incubation with Saos-2 (Sarcoma osteogenic) cells for 14 days, cell morphology, cell distribution, cell survival (fluorescence microscopy and LDH-based cytotoxicity assay), metabolic activity (MTT test), and osteogenic gene expression were determined. The adherent cells showed colonization properties, proliferation potential, and osteogenic differentiation. The innovative design, with its porous structure, is a promising matrix for cell settlement and proliferation. The modular design allows easy upscaling and offers a solution for LBDT.
Background: Recent advances in 3D printing technology have enabled the emergence of new educational and clinical tools for medical professionals. This study provides an exemplary description of the fabrication of 3D‐printed individualised patient models and assesses their educational value compared to cadaveric models in oral and maxillofacial surgery.
Methods: A single‐stage, controlled cohort study was conducted within the context of a curricular course. A patient's CT scan was segmented into a stereolithographic model and then printed using a fused filament 3D printer. These individualised patient models were implemented and compared against cadaveric models in a curricular oral surgery hands‐on course. Students evaluated both models using a validated questionnaire. Additionally, a cost analysis for both models was carried out. P‐values were calculated using the Mann‐Whitney U test.
Results: Thirty‐eight fourth‐year dental students participated in the study. Overall, significant differences between the two models were found in the student assessment. Whilst the cadaveric models achieved better results in the haptic feedback of the soft tissue, the 3D‐printed individualised patient models were regarded significantly more realistic with regard to the anatomical correctness, the degree of freedom of movement and the operative simulation. At 3.46 € (compared to 6.51 €), the 3D‐printed patient individualised models were exceptionally cost‐efficient.
Conclusions: 3D‐printed patient individualised models presented a realistic alternative to cadaveric models in the undergraduate training of operational skills in oral and maxillofacial surgery. Whilst the 3D‐printed individualised patient models received positive feedback from students, some aspects of the model leave room for improvement.
Background: The aim of this pilot study was to analyze postures during the work of neurologists with respect to their occupational activities.
Methods: A total data material of 64.8 h (3885.74 min) of nine (three m/six f) neurologists (assistant physicians) was collected. Kinematic data were collected using the CUELA system (electro-goniometry). In addition, the occupational tasks performed on-site were subject to a detailed objective activity analysis. All activities were assigned to the categories "Office activities" (I), "Measures on patients" (II) and "Other activities" (III). The angle values of each body region (evaluation parameters) were evaluated according to ergonomic ISO standards.
Results: Only 3.4% of the working hours were spent with (II), while 50.8% of time was spent with (I) and 45.8% with (III). All tasks of category (II) revealed an increased ergonomic risk to the head, neck, trunk and back areas. During category (I) especially neck and back movements in the sagittal plane showed higher ergonomic risk levels.
Conclusion: Despite frequently performed awkward body positions in (II), the ergonomic risk is considered as rather low, since the percentage time share totaled only 3.4%. As a result, "Office activities" have been detected as high predictor to cause stress load on the musculoskeletal system in the daily work of neurologists.
Background: Cognitive dysfunctions represent a core feature of schizophrenia and a predictor for clinical outcomes. One possible mechanism for cognitive impairments could involve an impairment in the experience-dependent modifications of cortical networks.
Methods: To address this issue, we employed magnetoencephalography (MEG) during a visual priming paradigm in a sample of chronic patients with schizophrenia (n = 14), and in a group of healthy controls (n = 14). We obtained MEG-recordings during the presentation of visual stimuli that were presented three times either consecutively or with intervening stimuli. MEG-data were analyzed for event-related fields as well as spectral power in the 1–200 Hz range to examine repetition suppression and repetition enhancement. We defined regions of interest in occipital and thalamic regions and obtained virtual-channel data.
Results: Behavioral priming did not differ between groups. However, patients with schizophrenia showed prominently reduced oscillatory response to novel stimuli in the gamma-frequency band as well as significantly reduced repetition suppression of gamma-band activity and reduced repetition enhancement of beta-band power in occipital cortex to both consecutive repetitions as well as repetitions with intervening stimuli. Moreover, schizophrenia patients were characterized by a significant deficit in suppression of the C1m component in occipital cortex and thalamus as well as of the late positive component (LPC) in occipital cortex.
Conclusions: These data provide novel evidence for impaired repetition suppression in cortical and subcortical circuits in schizophrenia. Although behavioral priming was preserved, patients with schizophrenia showed deficits in repetition suppression as well as repetition enhancement in thalamic and occipital regions, suggesting that experience-dependent modification of neural circuits is impaired in the disorder.
A message from the human placenta: structural and immunomodulatory defense against SARS-CoV-2
(2020)
The outbreak of the coronavirus disease 2019 (COVID-19) pandemic has caused a global public health crisis. Viral infections may predispose pregnant women to a higher rate of pregnancy complications, including preterm births, miscarriage and stillbirth. Despite reports of neonatal COVID-19, definitive proof of vertical transmission is still lacking. In this review, we summarize studies regarding the potential evidence for transplacental transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), characterize the expression of its receptors and proteases, describe the placental pathology and analyze virus-host interactions at the maternal-fetal interface. We focus on the syncytium, the barrier between mother and fetus, and describe in detail its physical andstructuraldefenseagainstviralinfections. Wefurtherdiscussthepotentialmolecularmechanisms, whereby the placenta serves as a defense front against pathogens by regulating the interferon type III signaling, microRNA-triggered autophagy and the nuclear factor-κB pathway. Based on these data, we conclude that vertical transmission may occur but rare, ascribed to the potent physical barrier, the fine-regulatedplacentalimmunedefenseandmodulationstrategies. Particularly,immunomodulatory mechanismsemployedbytheplacentamaymitigateviolentimmuneresponse,maybesoftencytokine storm tightly associated with severely ill COVID-19 patients, possibly minimizing cell and tissue damages, and potentially reducing SARS-CoV-2 transmission.
Unresolved inflammation maintained by release of danger‐associated molecular patterns, particularly high‐mobility group box‐1 (HMGB1), is crucial for hepatocellular carcinoma (HCC) pathogenesis. To further characterize interactions between leucocytes and necrotic cancerous tissue, a cellular model of necroinflammation was studied in which murine Raw 264.7 macrophages or primary splenocytes were exposed to necrotic lysates (N‐lys) of murine hepatoma cells or primary hepatocytes. In comparison to those derived from primary hepatocytes, N‐lys from hepatoma cells were highly active—inducing in macrophages efficient expression of inflammatory cytokines like C‐X‐C motif ligand‐2 , tumor necrosis factor‐α, interleukin (IL)‐6 and IL‐23‐p19. This activity associated with higher levels of HMGB1 in hepatoma cells and was curbed by pharmacological blockage of the receptor for advanced glycation end product (RAGE)/HMGB1 axis or the mitogen‐activated protein kinases ERK1/2 pathway. Analysis of murine splenocytes furthermore demonstrated that N‐lys did not comprise of functionally relevant amounts of TLR4 agonists. Finally, N‐lys derived from hepatoma cells supported inflammatory splenic Th17 and Th1 polarization as detected by IL‐17, IL‐22 or interferon‐γ production. Altogether, a straightforward applicable model was established which allows for biochemical characterization of immunoregulation by HCC necrosis in cell culture. Data presented indicate a remarkably inflammatory capacity of necrotic hepatoma cells that, at least partly, depends on the RAGE/HMGB1 axis and may shape immunological properties of the HCC microenvironment.
Motivation: Calculating the magnitude of treatment effects or of differences between two groups is a common task in quantitative science. Standard effect size measures based on differences, such as the commonly used Cohen's, fail to capture the treatment-related effects on the data if the effects were not reflected by the central tendency. The present work aims at (i) developing a non-parametric alternative to Cohen’s d, which (ii) circumvents some of its numerical limitations and (iii) involves obvious changes in the data that do not affect the group means and are therefore not captured by Cohen’s d.
Results: We propose "Impact” as a novel non-parametric measure of effect size obtained as the sum of two separate components and includes (i) a difference-based effect size measure implemented as the change in the central tendency of the group-specific data normalized to pooled variability and (ii) a data distribution shape-based effect size measure implemented as the difference in probability density of the group-specific data. Results obtained on artificial and empirical data showed that “Impact”is superior to Cohen's d by its additional second component in detecting clearly visible effects not reflected in central tendencies. The proposed effect size measure is invariant to the scaling of the data, reflects changes in the central tendency in cases where differences in the shape of probability distributions between subgroups are negligible, but captures changes in probability distributions as effects and is numerically stable even if the variances of the data set or its subgroups disappear.
Conclusions: The proposed effect size measure shares the ability to observe such an effect with machine learning algorithms. Therefore, the proposed effect size measure is particularly well suited for data science and artificial intelligence-based knowledge discovery from big and heterogeneous data.