Developmental change of brain volume in Rett syndrome in Taiwan.

OBJECTIVE: Rett syndrome (RTT) is characterized by neurological regression. This pioneering study investigated the effect of age on brain volume reduction by analyzing magnetic resonance imaging findings in participants with RTT, ranging from toddlers to adults. METHODS: Functional evaluation and neuroimaging were performed. All scans were acquired using a Siemens Tim Trio 3 T scanner with a 32-channel head coil. RESULTS: The total intracranial volume and cerebral white matter volume significantly increased with age in the control group compared with that in the RTT group (p < 0.05). Cortical gray matter volume reduction in the RTT group continued to increase in bilateral parietal lobes and left occipital lobes (p < 0.05). The differences in cortical gray matter volume between typically developing brain and RTT-affected brain may tend to continuously increase until adulthood in both temporal lobes although not significant after correction for multiple comparison. CONCLUSIONS: A significant reduction in brain volume was observed in the RTT group. Cortical gray matter volume in the RTT group continued to reduce in bilateral parietal lobes and left occipital lobes. These results provide a baseline for future studies on the effect of RTT treatment and related neuroscience research.

Astrocyte-secreted lipocalin-2 elicits bioenergetic failure-induced neuronal death that is causally related to high fatality in a mouse model of hepatic encephalopathy.

Hepatic encephalopathy (HE) is a neurological complication arising from acute liver failure with poor prognosis and high mortality; the underlying cellular mechanisms are still wanting. We previously found that neuronal death caused by mitochondrial dysfunction in rostral ventrolateral medulla (RVLM), which leads to baroreflex dysregulation, is related to high fatality in an animal model of HE. Lipocalin-2 (Lcn2) is a secreted glycoprotein mainly released by astrocytes in the brain. We noted the presence of Lcn2 receptor (Lcn2R) in RVLM neurons and a parallel increase of Lcn2 gene in astrocytes purified from RVLM during experimental HE. Therefore, our guiding hypothesis is that Lcn2 secreted by reactive astrocytes in RVLM may underpin high fatality during HE by eliciting bioenergetic failure-induced neuronal death in this neural substrate. In this study, we first established the role of astrocyte-secreted Lcn2 in a liver toxin model of HE induced by azoxymethane (100 µg/g, ip) in C57BL/6 mice, followed by mechanistic studies in primary astrocyte and neuron cultures prepared from postnatal day 1 mouse pups. In animal study, immunoneutralization of Lcn2 reduced apoptotic cell death in RVLM, reversed defunct baroreflex-mediated vasomotor tone and prolonged survival during experimental HE. In our primary cell culture experiments, Lcn2 produced by cultured astrocytes and released into the astrocyte-conditioned medium significantly reduced cell viability of cultured neurons. Recombinant Lcn2 protein reduced cell viability, mitochondrial ATP (mitoATP) production, and pyruvate dehydrogenase (PDH) activity but enhanced the expression of pyruvate dehydrogenase kinase (PDK) 1, PDK3 and phospho-PDHA1 (inactive PDH) through MAPK/ERK pathway in cultured neurons, with all cellular actions reversed by Lcn2R knockdown. Our results suggest that astrocyte-secreted Lcn2 upregulates PDKs through MAPK/ERK pathway, which leads to reduced PDH activity and mitoATP production; the reinforced neuronal death in RVLM is causally related to baroreflex dysregulation that underlies high fatality associated with HE.

Parylene Double-Layer Coated Screen-Printed Carbon Electrode for Label-Free and Reagentless Capacitive Aptasensing of Gliadin.

Celiac patients are required to strictly adhere to a gluten-free diet because even trace amounts of gluten can damage their small intestine and leading to serious complications. Despite increased awareness, gluten can still be present in products due to cross-contamination or hidden ingredients, making regular monitoring essential. With the goal of guaranteeing food safety for consuming labeled gluten-free products, a capacitive aptasensor was constructed to target gliadin, the main allergic gluten protein for celiac disease. The success of capacitive aptasensing was primarily realized by coating a Parylene double-layer (1000 nm Parylene C at the bottom with 400 nm Parylene AM on top) on the electrode surface to ensure both high insulation quality and abundant reactive amino functionalities. Under the optimal concentration of aptamer (5 µM) used for immobilization, a strong linear relationship exists between the amount of gliadin (0.01-1.0 mg/mL) and the corresponding ΔC response (total capacitance decrease during a 20 min monitoring period after sample introduction), with an R2 of 0.9843. The detection limit is 0.007 mg/mL (S/N > 5), equivalent to 0.014 mg/mL (14 ppm) of gluten content. Spike recovery tests identified this system is free from interferences in corn and cassava flour matrices. The analytical results of 24 commercial wheat flour samples correlated well with a gliadin ELISA assay (R2 = 0.9754). The proposed label-free and reagentless capacitive aptasensor offers advantages of simplicity, cost-effectiveness, ease of production, and speediness, making it a promising tool for verifying products labeled as gluten-free (gluten content <20 ppm).

Comparative analysis of gut microbiota in children with obstructive sleep apnea: assessing the efficacy of 16S rRNA gene sequencing in metabolic function prediction based on weight status.

Background: Analyzing bacterial microbiomes consistently using next-generation sequencing (NGS) is challenging due to the diversity of synthetic platforms for 16S rRNA genes and their analytical pipelines. This study compares the efficacy of full-length (V1-V9 hypervariable regions) and partial-length (V3-V4 hypervariable regions) sequencing of synthetic 16S rRNA genes from human gut microbiomes, with a focus on childhood obesity. Methods: In this observational and comparative study, we explored the differences between these two sequencing methods in taxonomic categorization and weight status prediction among twelve children with obstructive sleep apnea. Results: The full-length NGS method by Pacbio® identified 118 genera and 248 species in the V1-V9 regions, all with a 0% unclassified rate. In contrast, the partial-length NGS method by Illumina® detected 142 genera (with a 39% unclassified rate) and 6 species (with a 99% unclassified rate) in the V3-V4 regions. These approaches showed marked differences in gut microbiome composition and functional predictions. The full-length method distinguished between obese and non-obese children using the Firmicutes/Bacteroidetes ratio, a known obesity marker (p = 0.046), whereas the partial-length method was less conclusive (p = 0.075). Additionally, out of 73 metabolic pathways identified through full-length sequencing, 35 (48%) were associated with level 1 metabolism, compared to 28 of 61 pathways (46%) identified through the partial-length method. The full-length NGS also highlighted complex associations between body mass index z-score, three bacterial species (Bacteroides ovatus, Bifidobacterium pseudocatenulatum, and Streptococcus parasanguinis ATCC 15912), and 17 metabolic pathways. Both sequencing techniques revealed relationships between gut microbiota composition and OSA-related parameters, with full-length sequencing offering more comprehensive insights into associated metabolic pathways than the V3-V4 technique. Conclusion: These findings highlight disparities in NGS-based assessments, emphasizing the value of full-length NGS with amplicon sequence variant analysis for clinical gut microbiome research. They underscore the importance of considering methodological differences in future meta-analyses.

The sleep problems in individuals with Rett syndrome and their caregivers.

LAY ABSTRACT: Sleep problems are common and impactful among individuals with Rett syndrome (RTT) and their caregivers. We examined the sleep patterns of 29 RTT patients and their primary caregivers using various assessment tools. The study found that a majority of the patients experienced sleep disturbances, with younger patients showing more sleep difficulties. Caregivers also reported poor sleep quality. The findings emphasize the need to address sleep problems in RTT management, as improving sleep quality can positively impact the well-being of individuals with RTT and their caregivers.

A precise performance-based reimbursement model for the multi-centre NAPKON cohorts - development and evaluation.

Fair allocation of funding in multi-centre clinical studies is challenging. Models commonly used in Germany - the case fees ("fixed-rate model", FRM) and up-front staffing and consumables ("up-front allocation model", UFAM) lack transparency and fail to suitably accommodate variations in centre performance. We developed a performance-based reimbursement model (PBRM) with automated calculation of conducted activities and applied it to the cohorts of the National Pandemic Cohort Network (NAPKON) within the Network of University Medicine (NUM). The study protocol activities, which were derived from data management systems, underwent validation through standardized quality checks by multiple stakeholders. The PBRM output (first funding period) was compared among centres and cohorts, and the cost-efficiency of the models was evaluated. Cases per centre varied from one to 164. The mean case reimbursement differed among the cohorts (1173.21€ [95% CI 645.68-1700.73] to 3863.43€ [95% CI 1468.89-6257.96]) and centres and mostly fell short of the expected amount. Model comparisons revealed higher cost-efficiency of the PBRM compared to FRM and UFAM, especially for low recruitment outliers. In conclusion, we have developed a reimbursement model that is transparent, accurate, and flexible. In multi-centre collaborations where heterogeneity between centres is expected, a PBRM could be used as a model to address performance discrepancies.Trial registration: https://clinicaltrials.gov/ct2/show/NCT04768998 ; https://clinicaltrials.gov/ct2/show/NCT04747366 ; https://clinicaltrials.gov/ct2/show/NCT04679584 .

How Does Mg2+(aq) Interact with ATP(aq)? Biomolecular Structure through the Lens of Liquid-Jet Photoemission Spectroscopy.

Liquid-jet photoemission spectroscopy (LJ-PES) allows for a direct probing of electronic structure in aqueous solutions. We show the applicability of the approach to biomolecules in a complex environment, exploring site-specific information on the interaction of adenosine triphosphate in the aqueous phase (ATP(aq)) with magnesium (Mg2+(aq)), highlighting the synergy brought about by the simultaneous analysis of different regions in the photoelectron spectrum. In particular, we demonstrate intermolecular Coulombic decay (ICD) spectroscopy as a new and powerful addition to the arsenal of techniques for biomolecular structure investigation. We apply LJ-PES assisted by electronic-structure calculations to study ATP(aq) solutions with and without dissolved Mg2+. Valence photoelectron data reveal spectral changes in the phosphate and adenine features of ATP(aq) due to interactions with the divalent cation. Chemical shifts in Mg 2p, Mg 2s, P 2p, and P 2s core-level spectra as a function of the Mg2+/ATP concentration ratio are correlated to the formation of [Mg(ATP) 2]6-(aq), [MgATP]2-(aq), and [Mg2ATP](aq) complexes, demonstrating the element sensitivity of the technique to Mg2+-phosphate interactions. The most direct probe of the intermolecular interactions between ATP(aq) and Mg2+(aq) is delivered by the emerging ICD electrons following ionization of Mg 1s electrons. ICD spectra are shown to sensitively probe ligand exchange in the Mg2+-ATP(aq) coordination environment. In addition, we report and compare P 2s data from ATP(aq) and adenosine mono- and diphosphate (AMP(aq) and ADP(aq), respectively) solutions, probing the electronic structure of the phosphate chain and the local environment of individual phosphate units in ATP(aq). Our results provide a comprehensive view of the electronic structure of ATP(aq) and Mg2+-ATP(aq) complexes relevant to phosphorylation and dephosphorylation reactions that are central to bioenergetics in living organisms.

Site-Specific Photochemistry along a Protonated Peptide Scaffold.

We present a detailed study of the time-dependent photophysics and photochemistry of a known conformation of the two protonated pentapeptides Leu-enkephalin (Tyrosine-Glycine-Glycine-Phenylalanine-Leucine, YGGFL) and its chromophore-swapped analogue FGGYL, carried out under cryo-cooled conditions in the gas phase. Using ultraviolet-infrared (UV-IR) double resonance, we record excited state IR spectra as a function of time delay between UV and IR pulses. We identify unique Tyr OH stretch transitions due to the S1 state and the vibrationally excited triplet state(s) formed by intersystem crossing, Tn(v). Photofragment mass spectra are recorded out of the S1 origin and following UV-IR double resonance. Several competing site-specific fragmentation pathways are discovered involving peptide backbone cleavage, Tyr side chain loss, and N-terminal NH3 loss mediated by electron transfer. In YGGFL, IR excitation in the S1 state promotes electron transfer (ET) from the aromatic ring to the N-terminal R-NH3+ group leading to loss of neutral NH3. This product channel is missing in FGGYL due to the larger distance for ET from Y(4) to NH3+. Selective loss of the Tyr side chain occurs out of an excited state process following UV excitation and is further enhanced by IR excitation in S1 and Tn(v) states of both YGGFL and FGGYL. Finally, IR excitation in the S1 or Tn(v) states fragments the peptide backbone exclusively at amide(4), producing the b4 cation. We postulate that this selective fragmentation results from intersystem crossing to produce vibrationally excited triplets with enough energy to launch the proton along a proton conduit present in the known starting structure.

Nutritional, physicochemical, and functional properties of Hawaiian taro (Colocasia esculenta) flours: A comparative study.

Taro (Colocasia esculenta) flour is a viable carbohydrate alternative and a functional additive for food formulation; however, different taro varieties may possess distinct characteristics that may influence their suitability for food production. This study evaluated the nutritional, physicochemical, and functional properties of flours from five Hawaiian taro varieties: Bun-Long, Mana Ulu, Moi, Kaua'i Lehua, and Tahitian. Tahitian, Bun-long, and Moi had high total starch contents of 40.8, 38.9, and 34.1 g/100 g, respectively. Additionally, Moi had the highest neutral detergent fiber (25.5 g/100 g), lignin (1.39 g/100 g), and cellulose (5.31 g/100 g). In terms of physicochemical properties, Tahitian showed the highest water solubility index (33.3 g/100 g), while Tahitian and Moi exhibited the two highest water absorption indices (5.81 g/g and 5.68 g/g, respectively). Regarding functional properties, Tahitian had the highest water absorption capacity (3.48 g/g), and Tahitian and Moi had the two highest oil absorption capacities (3.15 g/g and 2.68 g/g, respectively). Therefore, the flours from these Hawaiian taro varieties possess promising characteristics that could enhance food quality when used as alternative additives in food processing.

LAVRF: Sign language recognition via Lightweight Attentive VGG16 with Random Forest.

Sign language recognition presents significant challenges due to the intricate nature of hand gestures and the necessity to capture fine-grained details. In response to these challenges, a novel approach is proposed-Lightweight Attentive VGG16 with Random Forest (LAVRF) model. LAVRF introduces a refined adaptation of the VGG16 model integrated with attention modules, complemented by a Random Forest classifier. By streamlining the VGG16 architecture, the Lightweight Attentive VGG16 effectively manages complexity while incorporating attention mechanisms that dynamically concentrate on pertinent regions within input images, resulting in enhanced representation learning. Leveraging the Random Forest classifier provides notable benefits, including proficient handling of high-dimensional feature representations, reduction of variance and overfitting concerns, and resilience against noisy and incomplete data. Additionally, the model performance is further optimized through hyperparameter optimization, utilizing the Optuna in conjunction with hill climbing, which efficiently explores the hyperparameter space to discover optimal configurations. The proposed LAVRF model demonstrates outstanding accuracy on three datasets, achieving remarkable results of 99.98%, 99.90%, and 100% on the American Sign Language, American Sign Language with Digits, and NUS Hand Posture datasets, respectively.

Interfacial Layer Materials with a Truxene Core for Dopant-Free NiOx -Based Inverted Perovskite Solar Cells.

Nickel oxide (NiOx ) is commonly used as a holetransporting material (HTM) in p-i-n perovskite solar cells. However, the weak chemical interaction between the NiOx and CH3 NH3 PbI3 (MAPbI3 ) interface results in poor crystallinity, ineffective hole extraction, and enhanced carrier recombination, which are the leading causes for the limited stability and power conversion efficiency (PCE). Herein, two HTMs, TRUX-D1 (N2 ,N7 ,N12 -tris(9,9-dimethyl-9H-fluoren-2-yl)-5,5,10,10,15,15-hexaheptyl-N2 ,N7 ,N12 -tris(4-methoxyphenyl)-10,15-dihydro-5H-diindeno[1,2-a:1',2'-c]fluorene-2,7,12-triamine) and TRUX-D2 (5,5,10,10,15,15-hexaheptyl-N2 ,N7 ,N12 -tris(4-methoxyphenyl)-N2 ,N7 ,N12 -tris(10-methyl-10H-phenothiazin-3-yl)-10,15-dihydro-5H-diindeno[1,2-a:1',2'-c]fluorene-2,7,12-triamine), are designed with a rigid planar C3 symmetry truxene core integrated with electron-donating amino groups at peripheral positions. The TRUX-D molecules are employed as effective interfacial layer (IFL) materials between the NiOx and MAPbI3 interface. The incorporation of truxene-based IFLs improves the quality of perovskite crystallinity, minimizes nonradiative recombination, and accelerates charge extraction which has been confirmed by various characterization techniques. As a result, the TRUX-D1 exhibits a maximum PCE of up to 20.8% with an impressive long-term stability. The unencapsulated device retains 98% of their initial performance following 210 days of aging in a glove box and 75.5% for the device after 80 days under ambient air condition with humidity over 40% at 25 °C.

High incidence of cerebrovascular lesions on magnetic resonance imaging in pediatric COVID-19 during omicron outbreak - A retrospective case series.

BACKGROUND: The incidence of pediatric hospitalizations has significantly increased since the spread of the omicron variant of COVID-19. Changes of characteristics in respiratory and neurological symptoms have been reported. We performed a retrospective, cross-sectional study to characterize the MRI change in children with an emphasis on the change of cerebral vasculatures. METHODS: We retrospectively collected clinical and MRI data of 31 pediatric patients with neurological symptoms during the acute infection and abnormalities on MRI during the outbreak of omicron variant from April 2022 to June 2022 in Taiwan. The clinical manifestations and MRI abnormalities were collected and proportion of patients with vascular abnormalities was calculated. RESULTS: Among 31 pediatric patients with post-COVID-19 neurological symptoms, MRI abnormalities were observed in 15 (48.4%), predominantly encephalitis/encephalopathy (73.3%). Notable MRI findings included focal diffusion-weighted imaging (DWI) hyperintensity in cerebral cortex and thalamus, diffuse cortical T2/DWI hyperintensity, and lesions in the medulla, pons, cerebellum, and splenium of corpus callosum. Vascular abnormalities were seen in 12 (80%) patients with MRI abnormalities, mainly affecting the middle cerebral arteries. The spectrum of neurological manifestations ranged from seizures to Alice in Wonderland syndrome, underscoring the diverse impact of COVID-19 on pediatric patients. CONCLUSION: A high proportion of vascular abnormalities was observed in pediatric patients with neurological involvements, suggesting that vascular involvement is an important mechanism of neurological manifestations in omicron variant infection.

Long-term impacts of endocrine-disrupting chemicals exposure on kidney function: A community-based cohort study.

This study explores the extended renal effects of endocrine-disrupting chemicals (EDCs) exposure, a linkage already established with adverse health outcomes, notably chronic kidney disease. To delve deeper, the Chang Gung Community Research Center conducted a longitudinal study with 887 participants. Among them, 120 individuals were scrutinized based on EDC scores, analyzing 17 urinary EDCs and renal function. Findings revealed elevated mono-(2-ethylhexyl) phthalate (MEHP) and bisphenol A levels in higher EDC exposure cases. MEHP notably correlated with increased urinary albumin-to-creatinine ratio (UACR), predicting a > 15% decline in estimated glomerular filtration rate. Higher MEHP levels also hinted at declining renal function. UACR escalation linked significantly with specific EDCs: MEHP, methylparaben, nonylphenol, and 4-tert-octylphenol. This research underscores enduring renal hazards tied to environmental EDC exposure, particularly MEHP, emphasizing the urgent call for robust preventive public health strategies.

Neurological manifestations of SARS-CoV-2 infection in children in Taiwan: A cross-section, multicenter study.

BACKGROUND: The SARS-CoV-2 virus has been a global public health threat since December 2019. This study aims to investigate the neurological characteristics and risk factors of coronavirus disease 2019 (COVID-19) in Taiwanese children, using data from a collaborative registry. METHODS: A retrospective, cross-sectional, multi-center study was done using an online network of pediatric neurological COVID-19 cohort collaborative registry. RESULTS: A total of 11160 COVID-19-associated emergency department (ED) visits and 1079 hospitalizations were analyzed. Seizures were the most common specific neurological symptom, while encephalitis and acute disseminated encephalomyelitis (ADEM) was the most prevalent severe involvement. In ED patients with neurological manifestations, severe neurological diagnosis was associated with visual hallucination, seizure with/without fever, behavior change, decreased GCS, myoclonic jerk, decreased activity/fatigue, and lethargy. In hospitalized patients with neurological manifestations, severe neurological diagnosis was associated with behavior change, visual hallucination, decreased GCS, seizure with/without fever, myoclonic jerk, fatigue, and hypoglycemia at admission. Encephalitis/ADEM was the only risk factor for poor neurological outcomes at discharge in hospitalized patients. CONCLUSION: Neurological complications are common in pediatric COVID-19. Visual hallucination, seizure, behavior change, myoclonic jerk, decreased GCS, and hypoglycemia at admission are the most important warning signs of severe neurological involvement such as encephalitis/ADEM.

MESMERIC: Machine Learning-Based Trust Management Mechanism for the Internet of Vehicles.

The emerging yet promising paradigm of the Internet of Vehicles (IoV) has recently gained considerable attention from researchers from academia and industry. As an indispensable constituent of the futuristic smart cities, the underlying essence of the IoV is to facilitate vehicles to exchange safety-critical information with the other vehicles in their neighborhood, vulnerable pedestrians, supporting infrastructure, and the backbone network via vehicle-to-everything communication in a bid to enhance the road safety by mitigating the unwarranted road accidents via ensuring safer navigation together with guaranteeing the intelligent traffic flows. This requires that the safety-critical messages exchanged within an IoV network and the vehicles that disseminate the same are highly reliable (i.e., trustworthy); otherwise, the entire IoV network could be jeopardized. A state-of-the-art trust-based mechanism is, therefore, highly imperative for identifying and removing malicious vehicles from an IoV network. Accordingly, in this paper, a machine learning-based trust management mechanism, MESMERIC, has been proposed that takes into account the notions of direct trust (encompassing the trust attributes of interaction success rate, similarity, familiarity, and reward and punishment), indirect trust (involving confidence of a particular trustor on the neighboring nodes of a trustee, and the direct trust between the said neighboring nodes and the trustee), and context (comprising vehicle types and operating scenarios) in order to not only ascertain the trust of vehicles in an IoV network but to segregate the trustworthy vehicles from the untrustworthy ones by means of an optimal decision boundary. A comprehensive evaluation of the envisaged trust management mechanism has been carried out which demonstrates that it outperforms other state-of-the-art trust management mechanisms.

Investigating the impact of probiotic on neurological outcomes in Rett syndrome: A randomized, double-blind, and placebo-controlled pilot study.

LAY ABSTRACT: Rett syndrome often involves gastrointestinal symptoms and gut microbiota imbalances. We conducted a study to explore the feasibility of probiotic Lactobacillus plantarum PS128 and the impact on neurological functions in Rett syndrome. The results of our investigation demonstrated that the supplementation of probiotic L. plantarum PS128 was feasible and well tolerated, with 100% retention rate and 0% withdrawal rate. In addition, there was only one participant who had loose stool after taking L. plantarum PS128. Further, there was a tendency to enhance overall cognitive developmental level, as assessed using Mullen Scales of Early Learning. In addition, it significantly improved dystonia, as assessed using the Burke-Fahn-Marsden Movement Scale, in comparison with the placebo group. This study provides a strong foundation for future research and clinical trials exploring the potential of L. plantarum PS128 probiotics as a complementary therapy for individuals with Rett syndrome.

TIPE proteins control directed migration of human T cells by directing GPCR and lipid second messenger signaling.

Tissue infiltration by circulating leukocytes via directed migration (also referred to as chemotaxis) is a common pathogenic mechanism of inflammatory diseases. G protein-coupled receptors (GPCRs) are essential for sensing chemokine gradients and directing the movement of leukocytes during immune responses. The tumor necrosis factor α-induced protein 8-like (TIPE or TNFAIP8L) family of proteins are newly described pilot proteins that control directed migration of murine leukocytes. However, how leukocytes integrate site-specific directional cues, such as chemokine gradients, and utilize GPCR and TIPE proteins to make directional decisions are not well understood. Using both gene knockdown and biochemical methods, we demonstrated here that 2 human TIPE family members, TNFAIP8 and TIPE2, were essential for directed migration of human CD4+ T cells. T cells deficient in both of these proteins completely lost their directionality. TNFAIP8 interacted with the Gαi subunit of heterotrimeric (α, ß, γ) G proteins, whereas TIPE2 bound to PIP2 and PIP3 to spatiotemporally control immune cell migration. Using deletion and site-directed mutagenesis, we established that Gαi interacted with TNFAIP8 through its C-terminal amino acids, and that TIPE2 protein interacted with PIP2 and PIP3 through its positively charged amino acids on the α0 helix and at the grip-like entrance. We also discovered that TIPE protein membrane translocation (i.e. crucial for sensing chemokine gradients) was dependent on PIP2. Collectively, our work describes a new mechanistic paradigm for how human T cells integrate GPCR and phospholipid signaling pathways to control directed migration. These findings have implications for therapeutically targeting TIPE proteins in human inflammatory and autoimmune diseases.

Inhibition of SARS-CoV-2 3CL protease by the anti-viral chimeric protein RetroMAD1.

COVID-19 results from SARS-CoV-2, which mutates frequently, challenging current treatments. Therefore, it is critical to develop new therapeutic drugs against this disease. This study explores the interaction between SARS-CoV-2 3CLpro and RetroMAD1, a well-characterized coronavirus protein and potential drug target, using in-silico methods. The analysis through the HDOCK server showed stable complex formation with a binding energy of -12.3, the lowest among reference drugs. The RetroMAD1-3CLpro complex underwent a 100 ns molecular dynamics simulation (MDS) in an explicit solvation system, generating various trajectories, including RMSD, RMSF, hydrogen bonding, radius of gyration, and ligand binding energy. MDS results confirmed intact interactions within the RetroMAD1-3CLpro complex during simulations. In vitro experiments validated RetroMAD1's ability to inhibit 3CLpro enzyme activity and prevent SARS-CoV-2 infection in human bronchial cells. RetroMAD1 exhibited antiviral efficacy comparable to Remdesivir without cytotoxicity at effective concentrations. These results suggest RetroMAD1 as a potential drug candidate against SARS-CoV-2, warranting further in vivo and clinical studies to assess its efficiency.

EnViTSA: Ensemble of Vision Transformer with SpecAugment for Acoustic Event Classification.

Recent successes in deep learning have inspired researchers to apply deep neural networks to Acoustic Event Classification (AEC). While deep learning methods can train effective AEC models, they are susceptible to overfitting due to the models' high complexity. In this paper, we introduce EnViTSA, an innovative approach that tackles key challenges in AEC. EnViTSA combines an ensemble of Vision Transformers with SpecAugment, a novel data augmentation technique, to significantly enhance AEC performance. Raw acoustic signals are transformed into Log Mel-spectrograms using Short-Time Fourier Transform, resulting in a fixed-size spectrogram representation. To address data scarcity and overfitting issues, we employ SpecAugment to generate additional training samples through time masking and frequency masking. The core of EnViTSA resides in its ensemble of pre-trained Vision Transformers, harnessing the unique strengths of the Vision Transformer architecture. This ensemble approach not only reduces inductive biases but also effectively mitigates overfitting. In this study, we evaluate the EnViTSA method on three benchmark datasets: ESC-10, ESC-50, and UrbanSound8K. The experimental results underscore the efficacy of our approach, achieving impressive accuracy scores of 93.50%, 85.85%, and 83.20% on ESC-10, ESC-50, and UrbanSound8K, respectively. EnViTSA represents a substantial advancement in AEC, demonstrating the potential of Vision Transformers and SpecAugment in the acoustic domain.