Precise control of microtubule disassembly in living cells.

Microtubules tightly regulate various cellular activities. Our understanding of microtubules is largely based on experiments using microtubule-targeting agents, which, however, are insufficient to dissect the dynamic mechanisms of specific microtubule populations, due to their slow effects on the entire pool of microtubules. To overcome this technological limitation, we have used chemo and optogenetics to disassemble specific microtubule subtypes, including tyrosinated microtubules, primary cilia, mitotic spindles, and intercellular bridges, by rapidly recruiting engineered microtubule-cleaving enzymes onto target microtubules in a reversible manner. Using this approach, we show that acute microtubule disassembly swiftly halts vesicular trafficking and lysosomal dynamics. It also immediately triggers Golgi and ER reorganization and slows the fusion/fission of mitochondria without affecting mitochondrial membrane potential. In addition, cell rigidity is increased after microtubule disruption owing to increased contractile stress fibers. Microtubule disruption furthermore prevents cell division, but does not cause cell death during interphase. Overall, the reported tools facilitate detailed analysis of how microtubules precisely regulate cellular architecture and functions.

RTL1/PEG11 imprinted in human and mouse brain mediates anxiety-like and social behaviors and regulates neuronal excitability in the locus coeruleus.

RTL1/PEG11, which has been associated with anxiety disorders, is a retrotransposon-derived imprinted gene in the placenta. However, imprinting patterns and functions of RTL1 in the brain have not been well-investigated. We found Rtl1 was paternally, but not maternally, expressed in brain stem, thalamus, and hypothalamus of mice, and imprinting status of RTL1 was maintained in human brain. Paternal Rtl1 knockout (Rtl1m+/p-) mice had higher neonatal death rates due to impaired suckling, and low body weights beginning on embryonic day 16.5. High paternal expression of Rtl1 was detected in the locus coeruleus (LC) and Rtl1m+/p- mice showed an increased delay in time of onset for action potentials and inward currents with decreased neuronal excitability of LC neurons. Importantly, Rtl1m+/p- mice exhibited behaviors associated with anxiety, depression, fear-related learning and memory, social dominance, and low locomotor activity. Taken together, our findings demonstrate RTL1 is imprinted in brain, mediates emotional and social behaviors, and regulates excitability in LC neurons.

Multi-Functional 2D Covalent Organic Frameworks with Diketopyrrolopyrrole as Electron Acceptor.

2D covalent organic framework (COF) materials with extended conjugated structure and periodic columnar π-arrays exhibit promising applications in organic optoelectronics. However, there is a scarcity of reports on optoelectronic COFs, mainly due to the lack of suitable π-skeletons. Here, two multi-functional optoelectronic 2D COFs DPP-TPP-COF and DPP-TBB-COF are constructed with diketopyrrolopyrrole as electron acceptor (A), and 1,3,6,8-tetraphenylpyrene and 1,3,5-triphenylbenzene as electron donor (D) through imine bonds. Both 2D COFs showed good crystallinities and AA stacking with a rhombic framework for DPP-TPP-COF and hexagonal one for DPP-TBB-COF, respectively. The electron D-A and ordered intermolecular packing structures endow the COFs with broad UV-vis absorptions and narrow bandgaps along with suitable HOMO/LUMO energy levels, resulting in multi-functional optoelectronic properties, including photothermal conversion, supercapacitor property, and ambipolar semiconducting behavior. Among them, DPP-TPP-COF exhibits a high photothermal conversion efficiency of 47% under 660 nm laser irradiation, while DPP-TBB-COF exhibits superior specific capacitance of 384 F g-1. Moreover, P-type doping and N-type doping are achieved by iodine and tetrakis(dimethylamino)ethylene on a single host COF, resulting in ambipolar semiconducting behavior. These results provide a paradigm for the application of multi-functional optoelectronic COF materials.

Neuronal NLRP3 inflammasome mediates spreading depolarization-evoked trigeminovascular activation.

Spreading depolarization (SD), the underlying mechanism of migraine aura, may trigger the opening of the pannexin 1 (PANX1) pore to sustain the cortical neuroinflammatory cascades involved in the genesis of headache. Yet, the mechanism underlying SD-evoked neuroinflammation and trigeminovascular activation remains incompletely understood. We characterized the identity of inflammasome activated following SD-evoked PANX1 opening. Pharmacological inhibitors targeting PANX1 or NLRP3 as well as genetic ablation of Nlrp3 and Il1b were applied to investigate the molecular mechanism of the downstream neuroinflammatory cascades. In addition, we examined whether SD-triggered microglial activation facilitates neuronal NLRP3-mediated inflammatory cascades. Pharmacological inhibition of toll-like receptors TLR2/4, the potential receptors of the damage-associated molecular pattern HMGB1, was further employed to interrogate the neuron-microglia interplay in SD-induced neuroinflammation. We found that NLRP3 but not NLRP1 or NLRP2 inflammasome was activated following PANX1 opening after single or multiple SDs evoked by either KCl topical application or non-invasively with optogenetics. The SD-evoked NLRP3 inflammasome activation was observed exclusively in neurons but not microglia or astrocytes. Proximity ligation assay demonstrated that the assembly of the NLRP3 inflammasome occurred as early as 15 min after SD. Genetic ablation of Nlrp3 or Il1b or pharmacological inhibition of PANX1 or NLRP3 ameliorated SD-induced neuronal inflammation, middle meningeal artery dilatation, calcitonin gene-related peptide expression in trigeminal ganglion and c-Fos expression in trigeminal nucleus caudalis. Moreover, multiple SDs induced microglial activation subsequent to neuronal NLRP3 inflammasome activation, which in turn orchestrated with neurons to mediate cortical neuroinflammation, as demonstrated by decreased neuronal inflammation after pharmacological inhibition of microglia activation or blockade of the TLR2/4 receptors. To conclude, single or multiple SDs evoked activation of neuronal NLRP3 inflammasomes and its downstream inflammatory cascades to mediate cortical neuroinflammation and trigeminovascular activation. In the context of multiple SDs, the cortical inflammatory processes could be facilitated by SD-evoked microglia activation. These findings may implicate the potential role of innate immunity in migraine pathogenesis.

The effect of a bone-preserving board game program on the knowledge, attitudes and preventive behaviors of osteoporosis in older adults.

Osteoporosis predisposes to fractures, which affect the quality of life and can be life-threatening. However, the knowledge, attitudes and preventive behaviors of osteoporosis in older adults are insufficient. The aim of this paper was to develop and test the effect of a bone-preserving board game program among older adults. A convenience sample of 85 older adults recruited from two community activity centers in southern Taiwan were assigned to either an experimental group or a control group. The experimental group played a bone-preserving board game for 4 weeks, and the control group participated in routine community center activities. The generalized estimating equation showed significantly larger improvements in knowledge, attitudes, and preventive behaviors in the experimental group than in the control group. Board games designed for older adults can support public health education and help prevent osteoporosis. Our results provide a reference for educators, clinical practitioners and researchers.

Hyperbranched Diketopyrrolopyrrole-based Polymers Constructed via Linear Side-Chains towards Organic Field-Effect Transistors.

Conjugated polymers with high charge mobilities have drawn increasing attention in organic field-effect transistors (OFETs) in recent years. However, OFETs of conjugated polymers with high mobility and good device stability remain a challenge. In this article, we report a hyperbranched polymer approach to improve the charge mobility and device stability. Three hyperbranched diketopyrrolopyrrole-based polymers were designed and synthesized via linear alkyl side-chain linkers. The results show that 2D topological hyperbranched polymers form stable thin film microstructures, and thus improve the device stability, since the conjugated moiety is interconnected by linear alkyl chain. Besides, the incorporation of linear alkyl chain instead of branching alkyl one reduce steric hindrance, and improve the microstructure ordering as well as the charge mobility. Bar-coated OFETs result demonstrates that the devices mobilities and operational stabilities (bias stability and bending resistance) are both improved. All these indicate that hyperbranched polymer is a potential candidate for future application.

Investigation of New Psychoactive Substances (NPS), Other Illicit Drugs, and Drug-Related Compounds in a Taiwanese Wastewater Sample Using High-Resolution Mass-Spectrometry-Based Targeted and Suspect Screening.

The proliferation of new psychoactive substances (NPSs) in recent years has posed a significant challenge to public health. Traditional monitoring methods have proven insufficient in tracking these constantly evolving substances, leading to the development of alternative approaches such as wastewater-based epidemiology (WBE). The present study aims to utilize high-resolution mass spectrometry (HRMS)-based targeted and suspect screening to profile NPS, other illicit drugs, and drug-related compounds in a Taiwanese wastewater sample. For the targeted analysis, 8 out 18 standards of illicit drugs have been identified. The suspect screening approach based on approximately 3600 substances in the SWGDRUG library can further identify 92 compounds, including opiate analgesics, synthetic cathinones, phenylalkylamines derivatives, phenethylamine derivatives, tryptamine derivatives, steroids, and ephedrine-related compounds. Additionally, the presence of 5-methoxy-2-aminoindane (MEAI) in the wastewater indicates that drug dealers have recently sold this potential NPS to evade drug regulations. This study firstly reports the HRMS-based comprehensive profile of NPS, other illicit drugs, and drug-related compounds in Taiwan, which could be applied as biomarkers for estimating the consumption of drugs.

The efficacy of a mindfulness-based exercise program in older residents of a long-term care facility in Taiwan.

Older people living in long-term care facilities remain largely inactive, and therefore promoting exercise in this population is necessary. This study evaluated the efficacy of a mindfulness-based exercise program in older residents of a long-term care facility in Taiwan. A convenience sample of 72 older residents of a long-term care facility were recruited and assigned to either an experimental group or a control group. The experimental group (n = 36) participated in an 8-week mindfulness-based exercise program, and the control group (n = 36) received routine care. The generalized estimating equation showed significantly larger improvements in a fear of falling, exercise self-efficacy, dynamic balance, and muscle strength in the experimental group than in the control group from baseline to the end of the intervention and 3 months after the end of the intervention. This study provides a reference for how to improve exercise practice in older people living in long-term care facilities.

Non-symmetric Half-Fused B←N Coordinated Diketopyrrolopyrrole Building Block for n-type Semiconducting Polymers.

The development of conjugated polymers with high semiconducting performance and high reliability is of great significance for flexible electronics. Herein, we developed a new type of electron-accepting building block; i.e., non-symmetric half-fused B←N coordinated diketopyrrolopyrrole (DPP) (HBNDPP), for amorphous conjugated polymers toward flexible electronics. The rigid B←N fusion part of HBNDPP endows the resulting polymers with decent electron transport, while its non-symmetric structure causes the polymer to exhibit multiple conformation isomers with flat torsional potential energies. Thus, it gets packed in an amorphous manner in solid state, ensuring good resistance to bending strain. Combined with hardness and softness, the flexible organic field-effect transistor devices exhibit n-type charge properties with decent mobility, good bending resistance, and good ambient stability. The preliminary study makes this building block a potential candidate for future design of conjugated materials for flexible electronic devices.

Fluid intelligence is associated with cortical volume and white matter tract integrity within multiple-demand system across adult lifespan.

BACKGROUND: Fluid intelligence (Gf) is the innate ability of an individual to respond to complex and unexpected situations. Although some studies have considered that the multiple-demand (MD) system of the brain was the biological foundation for Gf, further characterization of their relationships in the context of aging is limited. The present study hypothesized that the structural metrics of the MD system, including cortical thickness, cortical volumes, and white matter (WM) tract integrity, was the brain correlates for Gf across the adult life span. Partial correlation analysis was performed to investigate whether the MD system could still explain Gf independent of the age effect. Moreover, the partial correlations between Gf and left/right structural metrics within the MD regions were compared to test whether the correlations displayed distinct lateralization. METHODS: The participants were recruited from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) databank, comprising the images of 603 healthy participants aged 18-88 years acquired on a 3-T system. The MRI data included high-resolution T1-weighted and diffusion-weighted images, from which gray matter and WM structural metrics of the MD system were analyzed, respectively. The structural metrics of gray matter were quantified in terms of cortical volume/thickness of five pairs of cortical regions, and those of WM were quantified in terms of the mean axial diffusivity (DA), radial diffusivity (DR), mean diffusivity (DM), and generalized fractional anisotropy (GFA) on five pairs of tracts. Partial correlation controlling for age and sex effects, was performed to investigate the associations of Gf scores with the mean DA, DR, DM and GFA of all tracts in the MD system, those of left and right hemispheric tracts, and those of each tract. Fisher's exact test was used to compare the partial correlations between left and right MD regions. RESULTS: The linear relationship between cortical volumes and Gf was evident across all levels of the MD system even after controlling for age and sex. For the WM integrity, diffusion indices including DA, DR, DM and GFA displayed linear relationships with Gf scores at various levels of the MD system. Among the 10 WM tracts connecting the MD regions, bilateral superior longitudinal fasciculus I and bilateral frontal aslant tracts exhibited the strongest and significant associations. Our results did not show significant inter-hemispheric differences in the associations between structural metrics of the MD system and Gf. CONCLUSION: Our results demonstrate significant associations between Gf and both cortical volumes and tract integrity of the MD system across the adult lifespan in a population-based cohort. We found that the association remained significant in the entire adult lifespan despite simultaneous decline of Gf and the MD system. Our results suggest that the MD system might be a structural underpinning of Gf and support the fronto-parietal model of cognitive aging. However, we did not find hemispheric differences in the Gf-MD correlations, not supporting the hemi-aging hypothesis.

Diminution of context association memory structure in subjects with subjective cognitive decline.

Alzheimer's disease (AD) progresses insidiously from the preclinical stage to dementia. While people with subjective cognitive decline (SCD) have normal cognitive performance, some may be in the preclinical stage of AD. Neurofibrillary tangles appear first in the transentorhinal cortex, followed by the entorhinal cortex in the clinically silent stage of AD. We expected the earliest changes in subjects with SCD to occur in medial temporal subfields other than the hippocampal proper. These selective structural changes would affect specific memory subcomponents. We used the Family Picture subtest of the Wechsler Memory Scale-III, which was modified to separately compute character, activity, and location subscores for episodic memory subcomponents. We recruited 43 subjects with SCD, 44 subjects with amnesic mild cognitive impairment, and 34 normal controls. MRI was used to assess cortical thickness, subcortical gray matter volume, and fractional anisotropy. The results demonstrated that SCD subjects showed significant cortical atrophy in their bilateral parahippocampus and perirhinal and the left entorhinal cortices but not in their hippocampal regions. SCD subjects also exhibited significantly decreased mean fractional anisotropy in their bilateral uncinate fasciculi. The diminution of cortical thickness over the mesial temporal subfields corresponded to brain areas with early tangle deposition, and early degradation of the uncinate fasciculus was in accordance with the retrogenesis hypothesis. The parahippocampus and perirhinal cortex contribute mainly to context association memory while the entorhinal cortex, along with the uncinate fasciculus, contributes to content-related contextual memory. We proposed that context association and related memory structures are vulnerable in the SCD stage.

CURE: A deep learning framework pre-trained on large-scale patient data for treatment effect estimation.

Treatment effect estimation (TEE) aims to identify the causal effects of treatments on important outcomes. Current machine-learning-based methods, mainly trained on labeled data for specific treatments or outcomes, can be sub-optimal with limited labeled data. In this article, we propose a new pre-training and fine-tuning framework, CURE (causal treatment effect estimation), for TEE from observational data. CURE is pre-trained on large-scale unlabeled patient data to learn representative contextual patient representations and fine-tuned on labeled patient data for TEE. We present a new sequence encoding approach for longitudinal patient data embedding both structure and time. Evaluated on four downstream TEE tasks, CURE outperforms the state-of-the-art methods, marking a 7% increase in area under the precision-recall curve and an 8% rise in the influence-function-based precision of estimating heterogeneous effects. Validation with four randomized clinical trials confirms its efficacy in producing trial conclusions, highlighting CURE's capacity to supplement traditional clinical trials.

A Comprehensive Review of Safety, Efficacy, and Indications for the Use of Alpha-Lipoic Acid and Acetyl-L-Carnitine in Neuropathic Pain.

The debilitating, chronic symptoms of neuropathic pain result in decreased quality of life, depressed mood, and anxiety in patients suffering from neuropathic pain. Despite hundreds of dollars in monthly treatment-related costs, more than half of the patients report inadequate pain relief. Traditional first-line agents are expensive and may have disruptive side effects. Given the disease burden of neuropathic pain, many patients turn to over-the-counter supplements. Here we review two supplements, alpha-lipoic acid (ALA), also known as thioctic acid, and acetyl-L-carnitine (ALC), and data of treatment outcomes from the available literature suggest comparable efficacy to currently available pharmaceuticals for the treatment of neuropathic pain. Meta-analysis of randomized controlled trials demonstrates that ALA can significantly improve neuropathic pain and nerve conduction velocity. ALA has been evaluated in the treatment of multiple sources of neuropathic pain, including chemotherapy-induced peripheral neuropathy, entrapment neuropathies, radicular nerve pain, and burning mouth syndrome. Common dose-dependent side effects include nausea, vomiting, and vertigo. Cost analysis from June 2022 indicates that a clinically effective dose (600 mg/day) of ALA costs patients $14.40 monthly. Two randomized control trials demonstrate that ALC exhibits neuroprotective effects, can regenerate nerves, and improve vibratory perception in the early stages of DPN. In terms of adverse reactions, no significant differences were observed between treatment and placebo groups, implying that ALC is generally well-tolerated. Cost analysis from June 2022 indicates that a clinically effective dose of ALC (2000 mg/day) costs patients $27.60 monthly. Comparable efficacy in clinical trials, minimal side effects, and lower monthly costs suggest that ALA and ALC should be considered among the accepted first-line treatment options for neuropathic pain.

Network properties determine neural network performance.

Machine learning influences numerous aspects of modern society, empowers new technologies, from Alphago to ChatGPT, and increasingly materializes in consumer products such as smartphones and self-driving cars. Despite the vital role and broad applications of artificial neural networks, we lack systematic approaches, such as network science, to understand their underlying mechanism. The difficulty is rooted in many possible model configurations, each with different hyper-parameters and weighted architectures determined by noisy data. We bridge the gap by developing a mathematical framework that maps the neural network's performance to the network characters of the line graph governed by the edge dynamics of stochastic gradient descent differential equations. This framework enables us to derive a neural capacitance metric to universally capture a model's generalization capability on a downstream task and predict model performance using only early training results. The numerical results on 17 pre-trained ImageNet models across five benchmark datasets and one NAS benchmark indicate that our neural capacitance metric is a powerful indicator for model selection based only on early training results and is more efficient than state-of-the-art methods.

Clinicopathological features and cancer transcriptomic profiling of poorly cohesive gastric carcinoma subtypes.

Gastric poorly cohesive carcinoma (PCC) manifests with a diffuse pattern and diverse tumor cell morphologies, often indicating a more unfavorable prognosis. Recent consensus has reclassified PCC based on the proportion of signet-ring cells (SRCs) in tumors for research purposes. The two most distinct subtypes, poorly cohesive carcinoma not otherwise specified (PCC-NOS) and signet-ring cell carcinoma (SRCC), are characterized by less than 10% and more than 90% SRCs, respectively. However, research comparing the clinicopathological and transcriptomic differences between these subtypes remains limited. In this study, we conducted a comparative analysis of clinicopathological features in 55 advanced-stage PCCs, consisting of 43 PCC-NOS and 12 SRCC cases. Subsequently, 12 PCC-NOS and 5 SRCC cases were randomly selected for initial cancer-related gene expression profiling and pathway enrichment analysis using the GeoMx digital spatial profiler, followed by validation in a separate validation group comprising 16 PCC-NOS and 6 SRCC cases. These transcriptomic findings were then correlated with tumor morphology and clinicopathological data. PCC-NOS cases exhibited larger tumor size, a higher prevalence of pathological N3 disease, and a worse 1-year progression-free survival rate compared to SRCC cases. Clustering of PCC-NOS and SRCC was successfully achieved using the GeoMx Cancer Transcriptome Atlas. Among all studied genes, only MMP7 showed differential expression, with its overexpression significantly associated with the PCC-NOS subtype, increased perineural invasion, and earlier disease progression. Pathway analysis revealed significantly enriched pathways in PCC-NOS related to vesicle-mediated transport, adaptive immune systems, oncogenic signaling, and extracellular matrix organization, while SRCC displayed significant enrichment in pathways associated with respiratory electron transport and the cell cycle. In conclusion, this study compares and correlates clinicopathological features and transcriptomic data between PCC-NOS and SRCC at advanced stages, employing the latest consensus classification and a novel platform for analysis.

Linear Non-benzenoid Isomer of Acene Fusing Chrysene with Azulene Units.

Non-benzenoid polycyclic aromatic hydrocarbons (PAHs) have received considerable attention owing to their distinctive optical and electrical properties. Nevertheless, the synthesis and optoelectronic application of non-benzenoid PAHs remain challenging. Herein, we present a facile synthesis of linear non-benzenoid PAH with an armchair edge, diACh, by fusing chrysene with two azulene units. We systematically investigated the optical and electrical properties, which were also compared to its isomers, including benzenoid and non-benzenoid zigzag edge isomers. diACh exhibits global aromaticity, good planarity, and suitable highest occupied molecular orbital/lowest unoccupied molecular orbital energy levels. The protonation of diACh in solution successively forms a stable tropylium cation and dication. Moreover, the neutral, cationic, and dicationic states of diACh can be transformed with remarkable reversibility during the protonation-deprotonation process, as confirmed by ultraviolet-visible absorptions, fluorescence spectra, 1H nuclear magnetic resonance, and theoretical calculations. Additionally, we fabricate p-type organic field-effect transistor (OFET) devices based on diACh with hole mobility up to 0.026 cm2 V-1 s-1, and we further develop OFET-based acid vapor sensors with good sensitivity, recyclability, and selectivity. These findings underscore the unique properties of linear non-benzenoid PAHs with an armchair edge engendered by the fusion of azulene with the acene backbone, showcasing prospective applications in organic optoelectronics.

Study on Anti-Inflammatory Effects of and Muscle Recovery Associated with Transdermal Delivery of Chaenomeles speciosa Extracts Using Supersonic Atomizer on Rat Model.

Repetitive motion or exercise is associated with oxidative stress and muscle inflammation, which can lead to declining grip strength and muscle damage. Oleanolic acid and ursolic acid have anti-inflammatory and antioxidant properties and can be extracted from Chaenomeles speciosa through ultrasonic sonication. We investigated the association between grip strength declines and muscle damage induced by lambda carrageenan (LC) injection and exercise exposure in rats. We also assessed the reparative effects of transdermal pretreatment and post-treatment with C. speciosa extracts (CSEs) by using a supersonic atomizer. The half-maximal inhibitory concentration (IC50) of CSEs for cells was 10.5 mg/mL. CSEs significantly reduced the generation of reactive oxygen species and inflammatory factors (interleukin [IL]-6 and IL-1ß) in in vitro cell tests. Rats subjected to LC injection and 6 weeks of exercise exhibited significantly increased inflammatory cytokine levels (IL-1ß, TNF-α, and IL-6). Hematoxylin and eosin staining revealed inflammatory cell infiltration and evident muscle damage in the gastrocnemius muscle, which exhibited splitting and the appearance of the endomysium and perimysium. The treated rats' grip strength significantly declined. Following treatment with CSEs, the damaged muscles exhibited decreased IL-1ß, TNF-α, and IL-6 levels and normal morphologies. Moreover, grip strength significantly recovered. Pretreatment with CSEs yielded an immediate and significant increase in grip strength, with an increase of 180% and 165% occurring in the rats exposed to LC injection and exercise within the initial 12 h period, respectively, compared with the control group. Pretreatment with CSEs delivered transdermally using a supersonic atomizer may have applications in sports medicine and training or competitions.

Impact of the Radiology Scholars Certificate Program: Does It Persist Years After Program Completion?

RATIONALE AND OBJECTIVE: The Radiology Scholars Certificate Program (RSCP) is an elective course for preclinical medical students which aims to improve radiology knowledge, dispel misconceptions regarding the field, and train future clinicians who have a greater understanding of the scope of the field. Previously, we have shown that students demonstrate improved knowledge of radiological topics as well as improved perception of radiology as a field after completing the program. In this study we attempt to determine whether these effects persist up to two years following program completion. MATERIAL AND METHODS: A two-part questionnaire was sent to all third- and fourth-year medical students at our institution in order to assess their objective ability to select appropriate imaging studies and interpret basic imaging findings, as well as evaluate their subjective attitudes and comfort level with radiology topics. Statistical analysis compared students who completed the RSCP to non-RSCP controls. RESULTS: A total of 54 students responded to the survey (34 had previously completed the RSCP). RSCP participants were significantly more likely to select appropriate imaging workups and correctly interpret imaging findings compared to controls (p < 0.001). Furthermore, RSCP participants reported significantly higher confidence in their ability to order imaging (p < 0.001) and significantly higher satisfaction with their radiology education (p < 0.001). RSCP participants were less likely to agree with negative stereotypes regarding radiology and reported more favorable perceptions of the field. CONCLUSION: Preclinical radiology-driven medical student education programs like the RSCP offer the potential for lasting improvements in students' understanding of and attitudes toward radiology as a field. We believe that such programs will help address challenges facing the field of radiology regarding recruitment, diversity, and interdisciplinary understanding.

A bovine whey protein extract can induce the generation of regulatory T cells and shows potential to alleviate asthma symptoms in a murine asthma model.

The number of people with asthma has dramatically increased over the past few decades and the cost of care is more than $11·3 billion per year. The use of steroids is the major treatment to control asthma symptoms, but the side effects are often devastating. Seeking new drugs or new strategies to reduce the dose of steroid taken has always been an important task. A bovine whey protein extract (WPE), which is enriched in transforming growth factor-ß (TGF-ß), has been demonstrated to have the potential for reducing symptoms associated with mild-to-moderate T-helper cell type 1-mediated psoriasis in human subjects. However, whether WPE also has potential for inhibiting T-helper cell type 2 (Th2)-mediated disease remains unclear. In the present study, using a murine asthma model, we found that sensitised mice fed WPE daily, before they were challenged, resulted in reducing airway inflammation, serum ovalbumin-specific IgE, Th2-related cytokine production and airway hyperresponsiveness. Increase in the regulatory T cell (Treg) population in vitro and in vivo was observed when treated with WPE. According to the results from the TGF-ß-blocking antibody study, we suggest that TGF-ß is the main component that endows WPE with the potential to reduce the generation of Treg. Thus, the present data suggest that WPE has the potential to alleviate the symptoms of asthma by inducing the generation of Treg. Therefore, regular administration of WPE might be potentially beneficial for patients with asthma.

Benchmarking machine learning robustness in Covid-19 genome sequence classification.

The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional approaches to understanding the diversity, dynamics, and evolution of viruses, is nonetheless a rich resource for machine learning (ML) approaches as alternatives for extracting such important information from these data. It is of hence utmost importance to design a framework for testing and benchmarking the robustness of these ML models. This paper makes the first effort (to our knowledge) to benchmark the robustness of ML models by simulating biological sequences with errors. In this paper, we introduce several ways to perturb SARS-CoV-2 genome sequences to mimic the error profiles of common sequencing platforms such as Illumina and PacBio. We show from experiments on a wide array of ML models that some simulation-based approaches with different perturbation budgets are more robust (and accurate) than others for specific embedding methods to certain noise simulations on the input sequences. Our benchmarking framework may assist researchers in properly assessing different ML models and help them understand the behavior of the SARS-CoV-2 virus or avoid possible future pandemics.