Miracle-dz/UniFAR-FTUs huggingface dataset:
Selectivity and molecular stress responses to classical and botanical acaricides in the predatory mite Phytoseiulus persimilis Athias-Henriot (Acari: Phytoseiidae).

BACKGROUND Acaricide application remains an integral component of IPM for the two-spotted spider mite Tetranychus urticae. Species and strains of phytoseiid predatory mites vary significantly in their response to acaricides. For the success of IPM, it is imperative to identify the determinants of selectivity and molecular stress responses of acaricides in predatory mites. RESULTS The three classical acaricides bifenazate, cyflumetofen, and fenbutatin oxide, did not affect survival and fecundity of Phytoseiulus persimilis regardless of the route of exposure. Selectivity of the orange oil- and terpenoid blend-based botanical acaricides was low via a combination of direct exposure, acaricide-laced diet, and residual exposure but improved when limiting exposure only to the diet. To gain insights into the molecular stress responses, the transcriptome of P. persimilis was assembled. Subsequent gene expression analysis of predatory mites orally exposed to fenbutatin oxide and orange oil yielded only a limited xenobiotic stress response. In contrast, P. persimilis exhibited target-site resistance mutations, including I260M in SdhB, I1017M in CHS1, and kdr and super-kdr in VGSC. Extending the screen using available Phytoseiidae sequences uncovered I136T, S141F in cytb, G119S in AChE, and A2083V in ACC, well-known target-sites of acaricides. CONCLUSION Selectivity of the tested botanical acaricides to P. persimilis was low but could be enhanced by restricting exposure to a single route. Differential gene expression analysis did not show a robust induced stress response after sub-lethal exposure. In contrast, this study uncovered target-site mutations that may help explain the physiological selectivity of several classical acaricides to phytoseiid predators. This article is protected by copyright. All rights reserved.
Down-regulation of hsa_circ_0045474 induces macrophage autophagy in tuberculosis via miR-582-5p/TNKS2 axis

Macrophage autophagy plays a major role in the control and elimination of invading Mycobacterium tuberculosis. However, the function and mechanism of circRNA on macrophage autophagy in tuberculosis remain unclear. Therefore, this study aimed to explore the role of circRNA underlying macrophage autophagy in tuberculosis. Quantitative real-time polymerase chain reaction was used to detect the expression of hsa_circ_0045474, miR-582-5p and TNKS2. Autophagy was detected by LC3B immunofluorescence and transmission electron microscopy. Dual-luciferase reporter assays were used to detect the relationship of miR-582-5p and hsa_circ_0045474 or TNKS2. Western blot was used to detect the expression of LC3-І and LC3-ІІ. The results showed that hsa_circ_0045474 was down-regulated in monocytes from patients with tuberculosis and induced autophagy in macrophages. hsa_circ_0045474 sponged miR-582-5p and negatively regulated miR-582-5p expression. Overexpression of miR-582-5p affected by hsa_circ_0045474 induced autophagy in macrophages. TNKS2 served as a target of miR-582-5p and down-regulation of TNKS2 induced autophagy in macrophages regulated by miR-582-5p. In conclusion, our results demonstrated that hsa_circ_0045474 down-regulation induced macrophage autophagy in tuberculosis via miR-582-5p/ TNKS2 axis, implying a novel strategy to treat the occurrence of active pulmonary tuberculosis caused by immune escape of M. tuberculosis.
Root cultures and in vitro production of alkannin in arnebia hispidissima (lehm). dc.

Alkannin, a red-purple dye and bioactive compound found in the roots of Arnebia hispidissima. It has antibiotic and anti-inflammatory properties and also used in cosmetic and textile industries. The present communication demonstrates the establishment of root cultures of A. hispidissima with the aim of optimizing the production of alkannin. The maximum number of adventitious roots (4.2 per culture bottle) could be initiated from the in vitro regenerated shoots on half strength MS medium containing 1.0 mg L -1 Indole-3 butyric acid (IBA). Highest alkannin content and profuse rooting was also recorded on this media combination. Production of alkannin was influenced by the different culture media. The present investigation may be applicable in designing systems for the large-scale cultivation of A. hispidissima roots for the production of alkannin.
Can Lumbar Puncture Be Safely Deferred in Patients With Mild Presumed Idiopathic Intracranial Hypertension?

Background: Lumbar puncture (LP) is considered an essential component of the diagnosis of idiopathic intracranial hypertension (IIH) and ruling out IIH mimics, such as meningeal inflammation and neoplastic disease. Such mimics are unlikely in patients who are systemically well and fit the clinical demographic of IIH. It is important to take into account the risks of performing a LP as patients commonly experience mild adverse effects and infrequently more serious ones including psychological distress. LP can also be difficult to obtain in some health care settings, requiring inpatient admission. We examined the clinical course of a subset of presumed patients with IIH with mild vision loss and papilledema to determine whether LP can be safely deferred in this group. Methods: This was a retrospective study looking at the clinical characteristics, final visual outcome, and diagnosis of patients with presumed IIH and papilledema determined by clinical examination who did not undergo LP. The inclusion criteria included i) no symptoms suspicious for systemic infectious/neoplastic/inflammatory processes, ii) no secondary causes of raised intracranial pressure seen on magnetic resonance imaging/magnetic resonance venography, iii) optical coherence tomography (OCT)-RNFL thickness ≤300 µm, and iv) automated mean deviation (MD) ≤ −5.00 dB v) at least one follow-up visit. Results: A total of 132 eyes of 68 patients (66 female and 2 male) were included in the study. The mean ± SD age was 31.4 ± 10.2 years, and body mass index was 35.1 ± 6.8 kg/m2. Systemic symptoms included headache (n = 47), pulsatile tinnitus (n = 28), transient visual obscurations (n = 10), and diplopia (n = 2). Presenting logarithm of the minimum angle of resolution visual acuity was 0.020 ± 0.090, automated MD was −2.23 ± 1.38 dB, and OCT RNFL thickness was 150.8 ± 48.4 µm. Patients were followed for a mean number of 63.3 ± 78.3 weeks. No additional cause of intracranial hypertension was discovered, and all patients remained systemically well. Two patients were started on acetazolamide, and 31 patients lost at least some weight. There was a significant improvement in the automated MD (−1.73 ± 1.74 dB; P < 0.001) and OCT RNFL thickness (128.1 ± 38.6 µm; P < 0.001) at final follow-up. Seventy-six eyes of 38 patients were considered to have resolved papilledema at the final follow-up. Conclusions: Some patients with presumed IIH may not be able to undergo LP because of patient factors such as refusal, failed attempts, or the environment in which neuro-ophthalmologists practice. This study suggests that it may be acceptable to defer LP for patients with suspected IIH who are under the care of a neuro-ophthalmologist with experience in diagnosing and managing IIH. These patients should be systemically well, in a typical demographic for IIH patients, have mild optic disc edema, and preserved visual function. Patients should be informed about the controversial nature of this decision.
Adaptive switching control method and its application to tracking control of a robot

In this paper, the authors develop an adaptive switching control method for servo systems with large structured parameter uncertainty by using a supervisor. Two design methods of the supervisor with small switching interval are investigated. Several experimental results of tracking control of a SCARA-type robot with unknown payload are given to show the effectiveness of the proposed method.
Dual extended Kalman filter for vehicle state and parameter estimation

The article demonstrates the implementation of a model-based vehicle estimator, which can be used for combined estimation of vehicle states and parameters. The estimator is realised using the dual extended Kalman filter (DEKF) technique, which makes use of two Kalman filters running in parallel, thus ‘splitting’ the state and parameter estimation problems. Note that the two problems cannot be entirely separated due to their inherent interdependencies. This technique provides several advantages, such as the possibility to switch off the parameter estimator, once a sufficiently good set of estimates has been obtained. The estimator is based on a four-wheel vehicle model with four degrees of freedom, which accommodates the dominant modes only, and is designed to make use of several interchangeable tyre models. The paper demonstrates the appropriateness of the DEKF. Results to date indicate that this is an effective approach, which is considered to be of potential benefit to the automotive industry.
Predicting Risk of Stroke From Lab Tests Using Machine Learning Algorithms: Development and Evaluation of Prediction Models

Background Stroke, a cerebrovascular disease, is one of the major causes of death. It causes significant health and financial burdens for both patients and health care systems. One of the important risk factors for stroke is health-related behavior, which is becoming an increasingly important focus of prevention. Many machine learning models have been built to predict the risk of stroke or to automatically diagnose stroke, using predictors such as lifestyle factors or radiological imaging. However, there have been no models built using data from lab tests. Objective The aim of this study was to apply computational methods using machine learning techniques to predict stroke from lab test data. Methods We used the National Health and Nutrition Examination Survey data sets with three different data selection methods (ie, without data resampling, with data imputation, and with data resampling) to develop predictive models. We used four machine learning classifiers and six performance measures to evaluate the performance of the models. Results We found that accurate and sensitive machine learning models can be created to predict stroke from lab test data. Our results show that the data resampling approach performed the best compared to the other two data selection techniques. Prediction with the random forest algorithm, which was the best algorithm tested, achieved an accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and area under the curve of 0.96, 0.97, 0.96, 0.75, 0.99, and 0.97, respectively, when all of the attributes were used. Conclusions The predictive model, built using data from lab tests, was easy to use and had high accuracy. In future studies, we aim to use data that reflect different types of stroke and to explore the data to build a prediction model for each type.
Context-dependent transcriptional regulation of microglial proliferation

Microglia proliferation occurs during brain development and brain lesions, but how this is coordinated at the transcriptional level is not well understood. Here, we investigated transcriptional mechanisms underlying proliferation of mouse microglia during postnatal development and in adults in models of induced microglial depletion-repopulation and brain demyelination. While each proliferative subset displayed globally a distinct signature of gene expression, they also co-expressed a subgroup of 1,370 genes at higher levels than quiescent microglia. Furthermore, expression of these may be coordinated by one of two modes of regulation. A first mode augments expression of genes already expressed in quiescent microglia and is subject to regulation by Klf/Sp, Nfy, and Ets transcription factors. Alternatively, a second mode enables de novo transcription of cell cycle genes and requires additional regulatory input from Lin54 and E2f factors. Overall, proliferating microglia integrate regulation of cell cycle gene expression with their broader, context-dependent, transcriptional landscape.
Rationale for and Development of the Pancreatic Quantitative Sensory Testing Consortium to Study Pain in Chronic Pancreatitis

Supplemental digital content is available in the text. Objectives Abdominal pain is the primary symptom of chronic pancreatitis (CP), but pain is difficult to assess, and objective methods for pain assessment are lacking. The characterization of the sensory component of pain as a surrogate for nociception can be achieved by sensory testing using standardized stimuli. Herein, we describe the rationale for and development of an international consortium to better understand and characterize CP pain. Methods A collaboration was initially formed between the University of Aalborg, Johns Hopkins University, and the University of Pittsburgh. This group refined the protocol for pancreatic quantitative sensory testing (P-QST) and then expanded the collaboration with plans for incorporating P-QST into prospective studies. Results The collaboration has successfully developed a P-QST nomogram. Chronic pancreatitis patients identified with P-QST as having widespread hyperalgesia had higher pain intensity scores, higher prevalence of constant pain, and decreased quality of life. Psychiatric comorbidities were independent of pain phenotypes. Multiple studies are underway to validate these findings and evaluate their utility in clinical trials. Conclusions Development of the P-QST Consortium will facilitate collaborative efforts to use P-QST as a means for evaluation and characterization of pain in CP patients, and optimize methods to guide individualized pain management approaches.
Morphology and distribution of antennal sensilla in adults of Xylotrechus quadripes

Xylotrechus quadripes (Chevrolat) is the serious woodborer pest of arabica coffee (Coffea arabica L.). To further elucidate the behavior mechanism of the insect based on chemical odorant and to advance effective trapping methods, the typology, distribution, and abundance of antennal sensilla were investigated meticulously in both sexes of X. quadripes by scanning electron microscopy. The filiform antennae of both sexes are composed of 11 segments, namely the scape, pedicel, and nine flagellomeres (f1–9). Ten types (14 subtypes) of sensilla were identified morphologically: sensilla chaetica (three subtypes, Ch.1–3), sensilla basiconica (three subtypes, Ba.1–3), Böhm bristles (Bb), sensilla dentiform (De), sensilla trichodea (Tr), sensilla auricillica (Au), sensilla campaniformia (Ca), grooved peg sensilla (Gp), cuticular pores (Cp), and a newly observed sensillum, named sensilla cone (Cone). The sensilla were mainly distributed in flagellomeres, and the types and amounts increased in frequency from scape to the ninth flagellomere. The numbers of sensilla were the highest on the antennal dorsal side, while the lowest on the ventral side. The types of sensilla were the most abundant on the lateral side, and two sensilla basiconica (Ba.1–2) were found exclusively. The average number of Tr, Ba, and Au on the antenna of the males was significantly greater than females, while the Gp and Cp on the antenna of the females were significantly greater than males. Ca was exclusively occurred on the male antennae but was absent in females. This study discusses the putative functions of the antennal sensilla in adults of X. quadripes based on their characteristics in related species' sensilla, and these results provide an important foundation to clarify the ecological adaption, olfactory recognition mechanism, and to develop the chemical ecology control of X. quadripes.
Modulation of the Human Pancreatic Ductal Adenocarcinoma Immune Microenvironment by Stereotactic Body Radiotherapy

Purpose: Stereotactic body radiotherapy (SBRT) is an emerging treatment modality for pancreatic ductal adenocarcinoma (PDAC), which can effectively prime cytotoxic T cells by inducing immunogenic tumor cell death in preclinical models. SBRT effects on human PDAC have yet to be thoroughly investigated; therefore, this study aimed to characterize immunomodulation in the human PDAC tumor microenvironment following therapy. Experimental Design: Tumor samples were obtained from patients with resectable PDAC. Radiotherapy was delivered a median of 7 days prior to surgical resection, and sections were analyzed by multiplex IHC (mIHC), RNA sequencing, and T-cell receptor sequencing (TCR-seq). Results: Analysis of SBRT-treated tumor tissue indicated reduced tumor cell density and increased immunogenic cell death relative to untreated controls. Radiotherapy promoted collagen deposition; however, vasculature was unaffected and spatial analyses lacked evidence of T-cell sequestration. Conversely, SBRT resulted in fewer tertiary lymphoid structures and failed to lessen or reprogram abundant immune suppressor populations. Higher percentages of PD-1+ T cells were observed following SBRT, and a subset of tumors displayed more clonal T-cell repertoires. Conclusions: These findings suggest that SBRT augmentation of antitumor immunogenicity may be dampened by an overabundance of refractory immunosuppressive populations, and support the continued development of SBRT/immunotherapy combination for human PDAC.
Experimental Framework for Controller Design of a Rotorcraft Unmanned Aerial Vehicle Using Multi-Camera System

This paper describes the experimental framework for the control system design and validation of a rotorcraft unmanned aerial vehicle (UAV). Our approach follows the general procedure of nonlinear modeling, linear controller design, nonlinear simulation and flight test but uses an indoor-installed multi-camera system, which can provide full 6-degree of freedom (DOF) navigation information with high accuracy, to overcome the limitation of an outdoor flight experiment. In addition, a 3-DOF flying mill is used for the performance validation of the attitude control, which considers the characteristics of the multi-rotor type rotorcraft UAV. Our framework is applied to the design and mathematical modeling of the control system for a quad-rotor UAV, which was selected as the test-bed vehicle, and the controller design using the classical proportional-integral-derivative control method is explained. The experimental results showed that the proposed approach can be viewed as a successful tool in developing the controller of new rotorcraft UAVs with reduced cost and time.
Incorporating Prior Information in Adaptive Model Predictive Control for Multivariable Artificial Pancreas Systems

Background: Adaptive model predictive control (MPC) algorithms that recursively update the glucose prediction model are shown to be promising in the development of fully automated multivariable artificial pancreas systems. However, the recursively updated glycemic prediction models do not explicitly consider prior knowledge in the identification of the model parameters. Prior information of the glycemic effects of meals and physical activity can improve model accuracy and yield better glycemic control algorithms. Methods: A glucose prediction model based on regularized partial least squares (rPLS) method where the prior information is encoded as the regularization term is developed to provide accurate predictions of the future glucose concentrations. An adaptive MPC is developed that incorporates dynamic trajectories for the glucose setpoint and insulin dosing constraints based on the estimated plasma insulin concentration (PIC). The proposed adaptive MPC algorithm is robust to disturbances caused by unannounced meals and physical activities even in cases with missing glucose measurements. The effectiveness of the proposed adaptive MPC based on rPLS is investigated with in silico subjects of the multivariable glucose-insulin-physiological variables simulator (mGIPsim). Results: The efficacy of the proposed adaptive MPC strategy in regulating the blood glucose concentration (BGC) of people with T1DM is assessed using the average percent time in range (TIR) for glucose, defined as 70 to 180 mg/dL inclusive, and the average percent time in hypoglycemia (<70 and >54 mg/dL) and level 2 hypoglycemia (≤54 mg/dL). The TIR for a cohort of 20 virtual subjects of mGIPsim is 81.9% ± 7.4% (with no hypoglycemia or severe hypoglycemia) for the proposed MPC compared with 73.9% ± 7.6% (0.2% ± 0.1% in hypoglycemia and 0.1% ± 0.1% in level 2 hypoglycemia) for an MPC based on a recursive autoregressive exogenous (ARX) model. Conclusions: The adaptive MPC algorithm that incorporates prior knowledge in the recursive updating of the glucose prediction model can contribute to the development of fully automated artificial pancreas systems that can mitigate meal and physical activity disturbances.
Self-Harm Among Forensic Psychiatric Inpatients With Schizophrenia Spectrum Disorders: An Explorative Analysis

The burden of self-injury among offenders undergoing inpatient treatment in forensic psychiatry is substantial. This exploratory study aims to add to the previously sparse literature on the correlates of self-injury in inpatient forensic patients with schizophrenia spectrum disorders (SSD). Employing a sample of 356 inpatients with SSD treated in a Swiss forensic psychiatry hospital, patient data on 512 potential predictor variables were retrospectively collected via file analysis. The dataset was examined using supervised machine learning to distinguish between patients who had engaged in self-injurious behavior during forensic hospitalization and those who had not. Based on a combination of ten variables, including psychiatric history, criminal history, psychopathology, and pharmacotherapy, the final machine learning model was able to discriminate between self-injury and no self-injury with a balanced accuracy of 68% and a predictive power of AUC = 71%. Results suggest that forensic psychiatric patients with SSD who self-injured were younger both at the time of onset and at the time of first entry into the federal criminal record. They exhibited more severe psychopathological symptoms at the time of admission, including higher levels of depression and anxiety and greater difficulty with abstract reasoning. Of all the predictors identified, symptoms of depression and anxiety may be the most promising treatment targets for the prevention of self-injury in inpatient forensic patients with SSD due to their modifiability and should be further substantiated in future studies.
Vision system for deriving 3D gripping information for a robot

This paper describes a 3D vision system that allows the derivation of gripping information for a robot. Its capabilities are demonstrated in a benchmark that consisted in the task of clearing cafeteria trays. The system can handle a fair number of objects with substantial mutual occlusion. The objects can be transparent and specularly reflecting. In order to guarantee true 3D object recognition the system used three cameras. Two of these take `skylines' of the tray with dishes and cutlery pieces on it from the side, and a third camera takes a gray-level image from above. A ROI in each of the skyline contours pertaining to the highest object is analyzed, and features are extracted. Information from all three images is combined in a rule-based evidence accumulation scheme to determine the identity of the object in focus. The same features that voted for this object also allow the determination of its position and orientation. Finally the gripping points are calculated, depending on object, pose, and approach direction.