Industrial systems are increasingly threatened by cyberattackswith potentially disastrous consequences. To counter suchattacks, industrial intrusion detection systems strive to timelyuncover even the most sophisticated breaches. Due to its criticality for society, this fast-growing field attracts researchersfrom diverse backgrounds, resulting in 130 new detectionapproaches in 2021 alone. This huge momentum facilitatesthe exploration of diverse promising paths but likewise risksfragmenting the research landscape and burying promisingprogress. Consequently, it needs sound and comprehensibleevaluations to mitigate this risk and catalyze efforts into sustainable scientific progress with real-world applicability. Inthis paper, we therefore systematically analyze the evaluationmethodologies of this field to understand the current stateof industrial intrusion detection research. Our analysis of609 publications shows that the rapid growth of this researchfield has positive and negative consequences. While we observe an increased use of public datasets, publications stillonly evaluate 1.3 datasets on average, and frequently usedbenchmarking metrics are ambiguous. At the same time, theadoption of newly developed benchmarking metrics sees littleadvancement. Finally, our systematic analysis enables us toprovide actionable recommendations for all actors involvedand thus bring the entire research field forward.

Rasmussens encephalitis is a rare chronic neurological disorder, characterised by unilateral inflammation of the cerebral cortex, drug-resistant epilepsy, and progressive neurological and cognitive deterioration. Neuropathological and immunological studies support the notion that Rasmussens encephalitis is probably driven by a T-cell response to one or more antigenic epitopes, with potential additional contribution by autoantibodies. Careful analysis of the association between histopathology and clinical presentation suggests that initial damage to the brain is mediated by T cells and microglia, suggesting a window for treatment if Rasmussens encephalitis can be diagnosed early. Advances in neuroimaging suggest that progression of the inflammatory process seen with MRI might be a good biomarker in Rasmussens encephalitis. For many patients, families, and doctors, choosing the right time to move from medical management to surgery is a real therapeutic dilemma. Cerebral hemispherectomy remains the only cure for seizures, but there are inevitable functional compromises. Decisions of whether or when surgery should be undertaken are challenging in the absence of a dense neurological deficit, and vary by institutional experience. Further, the optimum time for surgery, to give the best language and cognitive outcome, is not yet well understood. Immunomodulatory treatments seem to slow rather than halt disease progression in Rasmussens encephalitis, without changing the eventual outcome.

Perivascular microglia activation is a hallmark of inflammatory demyelination in multiple sclerosis (MS), but the mechanisms underlying microglia activation and specific strategies to attenuate their activation remain elusive. Here, we identify fibrinogen as a novel regulator of microglia activation and show that targeting of the interaction of fibrinogen with the microglia integrin receptor Mac-1 (alpha(M)beta(2), CD11b/CD18) is sufficient to suppress experimental autoimmune encephalomyelitis in mice that retain full coagulation function. We show that fibrinogen, which is deposited perivascularly in MS plaques, signals through Mac-1 and induces the differentiation of microglia to phagocytes via activation of Akt and Rho. Genetic disruption of fibrinogen-Mac-1 interaction in fibrinogen-gamma(390-396A) knock-in mice or pharmacologically impeding fibrinogen-Mac-1 interaction through intranasal delivery of a fibrinogen-derived inhibitory peptide (gamma(377-395)) attenuates microglia activation and suppresses relapsing paralysis. Because blocking fibrinogen-Mac-1 interactions affects the proinflammatory but not the procoagulant properties of fibrinogen, targeting the gamma(377-395) fibrinogen epitope could represent a potential therapeutic strategy for MS and other neuroinflammatory diseases associated with blood-brain barrier disruption and microglia activation.

Rasmussen's encephalitis is a rare chronic neurological disorder, characterised by unilateral inflammation of the cerebral cortex, drug-resistant epilepsy, and progressive neurological and cognitive deterioration. Neuropathological and immunological studies support the notion that Rasmussen's encephalitis is probably driven by a T-cell response to one or more antigenic epitopes, with potential additional contribution by autoantibodies. Careful analysis of the association between histopathology and clinical presentation suggests that initial damage to the brain is mediated by T cells and microglia, suggesting a window for treatment if Rasmussen's encephalitis can be diagnosed early. Advances in neuroimaging suggest that progression of the inflammatory process seen with MRI might be a good biomarker in Rasmussen's encephalitis. For many patients, families, and doctors, choosing the right time to move from medical management to surgery is a real therapeutic dilemma. Cerebral hemispherectomy remains the only cure for seizures, but there are inevitable functional compromises. Decisions of whether or when surgery should be undertaken are challenging in the absence of a dense neurological deficit, and vary by institutional experience. Further, the optimum time for surgery, to give the best language and cognitive outcome, is not yet well understood. Immunomodulatory treatments seem to slow rather than halt disease progression in Rasmussen's encephalitis, without changing the eventual outcome.

We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose, volumes of interest were extracted from the head, neck, and trochanter of 146 ex vivo proximal femur specimens on multidetector computer tomography. The trabecular bone captured was characterized with (1) statistical moments of the BMD distribution, (2) geometrical features derived from the scaling index method (SIM), and (3) morphometric parameters, such as bone fraction, trabecular thickness, etc. Feature sets comprising DXA BMD and such supplemental features were used to predict the failure load (FL) of the specimens, previously determined through biomechanical testing, with multiregression and support vector regression. Prediction performance was measured by the root mean square error (RMSE); correlation with measured FL was evaluated using the coefficient of determination R². The best prediction performance was achieved by a combination of DXA BMD and SIM-derived geometric features derived from the femoral head (RMSE: 0.869 ± 0.121, R²: 0.68 ± 0.079), which was significantly better than DXA BMD alone (RMSE: 0.948 ± 0.119, R²: 0.61 ± 0.101) (p < 10^-4). For multivariate feature sets, SVR outperformed multiregression (p < 0.05). These results suggest that supplementing standard DXA BMD measurements with sophisticated femoral trabecular bone characterization and supervised learning techniques can significantly improve biomechanical strength prediction in proximal femur specimens.

To develop and characterize a clinically applicable, fast and efficient method for stem cell labeling with ferucarbotran and protamine for depiction with clinical MRI. The hydrodynamic diameter, zeta potential and relaxivities of ferucarbotran and varying concentrations of protamine were measured. Once the optimized ratio was found, human mesenchymal stem cells (MSCs) were labeled at varying incubation times (1–24 h). Viability was assessed via Trypan blue exclusion testing. 150,000 labeled cells in Ficoll solution were imaged with T1-, T2- and T2*-weighted sequences at 3 T, and relaxation rates were calculated. Varying the concentrations of protamine allows for easy modification of the physicochemical properties. Simple incubation with ferucarbotran alone resulted in efficient labeling after 24 h of incubation while assisted labeling with protamine resulted in similar results after only 1 h. Cell viability remained unaffected. R2 and R2* relaxation rates were drastically increased. Electron microscopy confirmed intracellular iron oxide uptake in lysosomes. Relaxation times correlated with results from ICP-AES. Our results show internalization of ferucarbotran can be accelerated in MSCs with protamine, an approved heparin antagonist and potentially clinically applicable uptake-enhancing agent.

Autoimmune limbic encephalitis (ALE) presents with new-onset mesial temporal lobe seizures, progressive memory disturbance, and other behavioral and cognitive changes. CD8 T cells are considered to play a key role in those cases where autoantibodies (ABs) target intracellular antigens or no ABs were found. Assessment of such patients presents a clinical challenge, and novel noninvasive imaging biomarkers are urgently needed. Here, we demonstrate that visualization of the translocator protein (TSPO) with [¹⁸F]DPA-714-PET-MRI reveals pronounced microglia activation and reactive gliosis in the hippocampus and amygdala of patients suspected with CD8 T cell ALE, which correlates with FLAIR-MRI and EEG alterations. Back-translation into a preclinical mouse model of neuronal antigen-specific CD8 T cell-mediated ALE allowed us to corroborate our preliminary clinical findings. These translational data underline the potential of [¹⁸F]DPA-714-PET-MRI as a clinical molecular imaging method for the direct assessment of innate immunity in CD8 T cell-mediated ALE.