Abstract: Scavenging of electrogenerated superoxide radical anion (O2•−) by pyrogallol (PyH3) was investigated on the basis of cyclic voltammetry and in situ electrolytic electron spin resonance spectrum in N,N-dimethylformamide with the aid of density functional theory (DFT) calculations. Quasi-reversible dioxygen/O2•− redox coupe was modified by the presence of PyH3, suggesting that O2•− was scavenged by PyH3 through proton-coupled electron transfer (PCET) involving two proton transfer and one electron transfer. The DFT calculation suggested that the formation of hydrogen bond (HB) complex and the subsequent concerted-two-proton coupled electron transfer (2PCET) characterized by catechol moiety in PyH3 is plausible mechanism which embodies the superior kinetics of the O2•− scavenging by PyH3 as shown in the electrochemical results. Furthermore, it was clarified that three hydroxyl groups of PyH3 promote the formation of prereactive HB complex, in comparative analyses using related compounds, resulting the promotion of the O2•− scavenging.

Abstract: Elimination of superoxide radical anion (O2•−) by tocopherols (TOH), and related compounds was investigated on the basis of cyclic voltammetry and in situ electrolytic electron spin resonance spectral measurements in N,N-dimethylformamide (DMF) with the aid of density functional theory (DFT) calculations. Quasi-reversible O2/O2•− redox was modified by the presence of TOHs, suggesting that the electrogenerated O2•− was eliminated by α-, β-, γ-TOH through proton-coupled electron transfer (PCET), but not by δ-TOH. The structure–activity correlation of α-, β-, γ-, and δ-TOH characterized by methyl group on the 6-chromanol ring was experimentally confirmed, where the methyl group promotes the PCET mechanism. Furthermore, comparative analyses using some related chemical analogues suggested that methoxyl group of the 6-chromanol ring is required for a successful electron transfer (ET) to O2•− through the PCET. The electrochemical and DFT results in dehydrated DMF suggested that the PCET mechanism involves preceding proton transfer (PT) forming hydroperoxyl radical followed by a concerted PCET (ET–PT). The O2•− elimination by TOH proceeds efficiently along the net PCET mechanism involving one ET and two PTs.

The blood-brain barrier (BBB) acts as a structural and functional barrier for brain homeostasis. This review highlights the pathological contribution of BBB dysfunction to neuroimmunological diseases, including multiple sclerosis (MS), neuromyelitis optica spectrum disorder (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), autoimmune encephalitis (AE) and paraneoplastic neurological syndrome (PNS). The transmigration of massive lymphocytes across the BBB caused by the activation of cell adhesion molecules is involved in the early phase of MS, and dysfunction of the cortical BBB is associated with the atrophy of gray matter in the late phase of MS. In the onset of NMOSD, increased permeability of the BBB causes the entry of circulating AQP4 autoantibodies into the central nervous system (CNS). Recent reports have shown the importance of glucose-regulated protein (GRP) autoantibodies as BBB-reactive autoantibodies in NMOSD, inducing antibody-mediated BBB dysfunction. BBB breakdown has also been observed in MOGAD, NPSLE, and AE with anti-NMDAR antibodies. Our recent report demonstrated the presence of GRP78 autoantibodies in patients with MOGAD and the molecular mechanism responsible for GRP78 autoantibody-mediated BBB impairment. Disruption of the BBB may explain the symptoms in the brain and cerebellum in the development of PNS, as it induces the entry of pathogenic autoantibodies or lymphocytes into the CNS by autoimmunity against tumors in the periphery. GRP78 autoantibodies were detected in paraneoplastic cerebellar degeneration and Lambert-Eaton myasthenic syndrome and were associated with cerebellar ataxia with anti-P/Q type voltage-gated calcium channel antibodies. This review reports that therapies affecting the BBB that are currently available for disease-modifying therapies for neuroimmunological diseases have the potential to prevent BBB damage.

Aiming at solving difficulties related to aero-engine classification and identification, the infrared spectra of aero-engine hot jets are measured by telemetry Fourier transform infrared spectrometer, and a six types aero-engine hot jet spectrum data set is generated. The spectrum data set were randomly sampled at a ratio of 8:1:1 to generate training set, validation set and prediction set. In this paper, a Peak Finding Siamese Convolutional Neural Network (PF-SCNN) is designed to match and classify spectrum data. In the first place, the matching pairs of training set and validation set are made independently with the labels of positive and negative samples creating. The spectrum feature extraction and distance similarity calculation are carried out by the Siamese convolutional neural network (SCNN). When entering the prediction phase, the prediction set and training set are integrated to predict in the trained model. The prediction set labels are ultimately determined by matching them with the training set labels having the highest similarities to ensure accurate predictions. To improve the operation efficiency of the SCNN, a peak finding method is introduced to extract the spectrum peaks. Peak positions of high frequency are counted, while the peak data are extracted. The peak data are used to take the place of the original data for training and prediction. The performance measures are defined as Accuracy, Precision, Recall, Confusion matrix and F1-score, and the prediction accuracy was up to 99%. The experimental results indicate that the proposed PF-SCNN is suitable for our spectral dataset and can complete the task of infrared spectrum classification of aero-engine hot jets.

The radio spectrum is a scarce and extremely valuable resource that demands careful real-time monitoring and dynamic resource allocation. Dynamic spectrum access (DSA) is a new paradigm for managing the radio spectrum, which requires AI/ML driven algorithms for optimum performance under rapidly changing channel conditions and possible cyber-attacks in the electromagnetic domain. Fast sensing across multiple directions using array processors, with subsequent AI/ML based algorithms for sensing and perception of the waveforms that are measured from the environment is critical for providing decision support in DSA. As part of directional and wideband spectrum perception, the ability to finely channelize wideband inputs using efficient Fourier analysis is much needed. However, a fine-grain fast Fourier transform (FFT) across a large number of directions is computationally intensive and leads to high chip area and power consumption. We address this issue by exploiting recently proposed approximate discrete Fourier transforms (ADFT) which has its own sparse factorization for real-time implementation at low complexity and power consumption. The ADFT is used to create a wideband multi-beam RF digital beamformer and temporal spectrum-based attention unit which monitors 32~discrete directions across 32~sub-bands in real-time using a multiplierless algorithm having low computational complexity. The output of this spectral attention unit is applied as a decision variable to an intelligent receiver that adapts its center frequency and frequency resolution via FFT channelizers that are custom-built for real-time monitoring at high resolution. This two-step process allows the fine-gain FFT to be applied only to directions and bands of interest as determined by the ADFT based low-complexity 2D spacetime attention unit. The fine-grain FFT provides a spectral signature that can find future use cases in neural network engines for achieving modulation recognition, IoT device identification, and RFI identification. Beamforming and spectral channelization algorithms, digital computer architecture, and early prototypes using a 32-element fully digital multichannel receiver and field programmable gate array (FPGA)-based high-speed software defined radio (SDR) is provided.

This study assessed the performance of low-dose CT lung scans across various acquisition parameters and examined the impact of iterative reconstruction (IR) algorithms on image quality for lung cancer screening. The performance of multi-slice CT scanners was assessed by using a Catphan 600 phantom, specifically within the CTP404 test module that contains materials like Teflon, Delrin, Acrylic, Polystyrene, LDPE, PMP, Air, and water. Three protocols were selected and categorized into standard, low dose, and ultra-low dose. The standard protocol featured a tube voltage of 100 kVp for single-detector CT, a pitch of 0.75, detector collimation of 0.60 mm, and a gantry rotation time of 0.33 seconds, with 5 mm slice thickness. Images were reconstructed using standard kernels like B80f and 170f, combined with either FBP or various IR algorithms. Findings indicated that the noise power spectrum (NPS) peak value (HU2mm2) increased with higher IR levels, with FBP showing the highest peak. Additionally, NPS spatial frequency diminished as IR levels rose. Optimizing contrast and spatial resolution for both background and regions of interest involved adjusting the target transfer function (TTF) and contrast-to-noise ratio (CNR), crucial for protocol optimization. Proper adjustment of IR levels is vital, as higher levels can alter image texture and affect NPS spatial frequency. The results of this study showed that the use of IR algorithms in low-dose CT lung scans significantly improved image quality, particularly in terms of noise reduction and spatial resolution. However, the choice of acquisition parameters also played a crucial

The prevalence of diagnosed cases of autism has increased rapidly, which raise interest in studying the variables related to the well-being of these families. The purpose of this paper is to review recent literature on other variables related to family well-being such a parenting styles. We conducted a systematic review using PRISMA check list and bias assessment ESTROBE with the aim of analyzing if the concepts of autism, well-being and parenting style are related. We screened 753 references, 16 full text articles and abstracts were read. It was identified that authoritative parenting style, those based on warmth, establishing relationships and emotional bonding, and low expressed emotion were positively related to family well-being. On the other hand, authoritarian, permissive and overprotective styles, as well as critical, punishing and training-based were negatively associated with well-being and quality of family life.

Banana wilt caused by Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) is a devastating fungal disease. Biocontrol strategies owned immense potential in inhibiting the spread of Foc TR4. Here, thirty actinobacteria were isolated from soils and screened for their antagonistic activity against Foc TR4. Strain SCA4-21T exhibited broad-spectrum antifungal activity against nine phytopathogenic fungi including Foc TR4. The strain was identified as the genus Streptomyces according to phenotypic characteristics and 16S rRNA gene phylogenetic analysis. Multi-locus sequence analysis based on five house-keeping gene alleles (atpD, gyrB, recA, rpoB, and trpB) revealed that strain SCA4-21T clustered into S. hygroscopicus subsp. hygroscopicus NBRC 13472T with 100% of bootstrap value. Average nucleotide identity and dDDH were 98.49% and 44.30% above the threshold of novel species. Hence, strain SCA 4-21T represented a novel species within the genus Streptomyces, named as Streptomyces luomodiensis sp. nov.. The type strain is SCA4-21T (=GDMCC4.340T= JCM36555T). By the CAZymes analysis, 348 carbohydrate-active enzymes were detected, including 15 chitinases and 8 β-1,3-glucanases. The fermentation broth of strain SCA4-21T showed high activities of chitinase and β-1,3-glucanase, contributing to the antifungal activity. Our results showed an innovative potential biocontrol agent for managing plant fungal diseases, specifically banana fusarium wilt.

India ranks among the top ten nations in the world for grape production. Fungal pathogens inflict damage to crop plants in turn making cultivators bear huge economical losses. With an output of 1.21 million tons (about 2% of 57.40 million tons produced globally). 1.2% of the nation’s total fruit cropland is covered by grapes. But due to fungal diseases the effect of the yield produced ranges from 5-80% depending on the severity of diseases which will affect the yield of grape vineyard. In precision agriculture, new sensing technologies and artificial intelligence could be used to automatically identify grapevine and disease pest symptoms. Traditional manual disease-monitoring methods are inefficient, labor-intensive, and ineffective. Timely effective and precise evaluation of grape diseases is admitted as a critical step in the field management. In this paper, we are explaining about different optical sensing methods applied for RGB, Multispectral and Thermal cameras. Section-wise we will be describing environmental set up for image-aquation, data-preprocessing, different modelling methods, evaluation matrix, result, and reviewer’s comment.

Conducted within the scope of geochemical exploration in Eastern Thailand, this study aims to detect geochemical anomalies and potential mineral deposits. The objective was to interpret intricate spatial dispersion patterns and concentration levels of deposit pathfinder elements, specifically arsenic (As), copper (Cu), and zinc (Zn), using a comprehensive array of stream sediment geochemistry data. Methodologies involved integrating multifractal properties and traditional statistics, facilitated by the GeoDAS and ArcGIS platforms as instrumental analytical tools. In total, 5,376 stream sediment samples were collected and evaluated, leading to the development of an in-depth geochemical map. The results indicated distinct geological units marked by substantially elevated average values of the aforementioned elements. Identification of geochemical anomalies was achieved through the spatial distribution method and the subsequent application of the Spectrum-Area (S-A) multifractal model. An intriguing link was found between high As concentrations and gold deposits in the area, suggesting As as a viable pathfinder element for gold mineralization. The anomaly maps, generated from the stream sediment data, spotlighted potential zones of interest, offering valuable guidance for future mineral exploration and geological inquiries. Nonetheless, it is vital to recognize that the increased values noted in these maps may be influenced by regional geological factors, emphasizing the necessity for a diverse set of analytical methods for accurate interpretation. The study's significance lies in its pioneering use of the S-A multifractal model in geochemical data analysis. This innovative approach has deepened our comprehension of geochemical dispersion patterns and improved the precision of mineral exploration.

Bone marrow mononuclear cells (BMMNCs) have emerged as a potential therapeutic strategy for various incurable conditions including autism spectrum disorder (ASD). To study its safety and efficacy, we analyzed 1011 patients who underwent intrathecal administration of autologous BMMNCs along with neurorehabilitation. At mean follow-up of 19.3 months after intervention, 90.6% patients showed overall improvement. Improvements were observed in attention concentration, command following, eye contact, sitting tolerance, social interaction, hyperactivity, communication, speech, aggressiveness, stereotypical and self-injurious behavior. Statistically significant changes were observed in scores of Indian Scale of Autism Assessment and Childhood Autism Rating Scale (p<0.05). On subgroup analysis, improvements were recorded irrespective of age and disease severity and better outcome was observed in patients who took multiple doses of cell therapy compared to single dose. Comparative Brain PET-CT scan of 401 patients showed improved brain metabolism after the intervention. No major adverse events were reported. Only 9 out of 1011 patients experienced seizures which were managed using medications. 4 out of 9 had history of seizures while 5 had normal EEG with no history. However, improvements were still observed in these 9 patients. Thus, intrathecal transplantation of autologous BMMNCs along with neurorehabilitation is safe and efficacious in patients with ASD.

Equipped with an early social predisposition immediately post-birth, humans typically form associations with mothers and other family members through exposure learning, canalized by a spontaneous predisposition to biological motion, face configuration, and other cues of animacy. If impaired, reduced social preferences can lead to social interaction impairments such as autism spectrum disorder (ASD) via misguided canalization. Despite being taxonomically distant, domestic chicks also follow a homologous developmental trajectory toward adaptive socialization through imprinting, which is guided via predisposed preferences that are homologous to those of humans, thereby suggesting that chicks are valid animal models of ASD. In addition to the convergent similarities in predisposition with human newborns, accumulating evidence suggests the construct validity of the chick model. Considering the recent progress in the evolutionary neurobiology of vertebrates, we reviewed the advantages and limitations of the chick model of developmental mental diseases in humans.

Purpose: Hearing assistive technology (HAT) has been shown to be a viable solution to the speech-in-noise perception (SPIN) issue in children with autism spectrum disorder (ASD); however, little is known about its efficacy in tonal language speakers. This study compared sentence-level SPIN performance between Chinese children with ASD and neurotypical (NT) children and evaluated HAT use in improving SPIN performance and easing SPIN difficulty. Methods: Children with ASD (n=26) and NT children (n=19) aged 6-12 performed two adaptive tests in steady-state noise and three fixed-level tests in quiet and steady-state noise with and without using HAT. Speech recognition thresholds (SRT) and accuracy rates were assessed using adaptive and fixed-level tests, respectively. Parents or teachers of the ASD group completed a questionnaire regarding children’s listening difficulty under six circumstances before and after a ten-day trial period of HAT use. Results: Although the two groups of children had comparable SRTs, the ASD group showed a significantly lower SPIN accuracy rate than the NT group. Also, a significant impact of noise was found in the ASD group’s accuracy rate, but not in the NT group’s. There was a general improvement in the ASD group’s SPIN performance with HAT and a decrease in their listening difficulty ratings across all conditions after the device trial. Conclusion: The findings indicated inadequate SPIN in the ASD group using a relatively sensitive measure to gauge SPIN performance among children. The markedly increased accuracy rate in noise during HAT-on sessions for the ASD group confirmed the feasibility of HAT for improving SPIN performance in controlled laboratory settings, and the reduced post-use ratings of listening difficulty further confirmed the benefits of HAT use in daily scenarios.

For more than half a century, Manfred Deistler has been contributing to the construction of the rigorous theoretical foundations of the statistical analysis of time series and more general stochastic processes. Half a century of unremitting activity is not easily summarized in a few pages. In this short note, we chose to concentrate on a relatively little-known aspect of Manfred's contribution which nevertheless had quite an impact on the development of one of the most powerful tools of contemporary time series and econometrics: dynamic factor models.

Children and young people (CYP) with neurodevelopmental disorders (NDDs) may be particularly vulnerable to adverse mental health effects due to the COVID-19 pandemic. We conducted a cross-sectional U.K parent-reported study from 2nd April-2nd June 2020, using the Strengths & Difficulties Questionnaire. CYP with NDDs (n=371) compared to neurotypical controls, had a higher prevalence of emotional symptoms (42% vs 15%), conduct problems (28% vs 9%), and lower prosocial behaviours (54% vs 22%). Those with attention-deficit/hyperactivity disorder showed inflated conduct, and those with autism spectrum disorder exhibited decreased prosocial behaviours. Females with ASD had higher emotional symptoms compared to males.

This article presents a new theory on redshift of light from celestial bodies. Lately it has been found that the Hubble constant calculated from different methods discord so much that calls arise for new physics to explain. Also, in addition to many unsolved puzzles like dark matter and source of expansion force, we shall show in this article that the current theory of redshift implies a few hidden, unreasonale assumptions. By assuming photon has temperature and its thermal energy is fully converted to wave energy, this article shows that photon can have a new redshift called Temperature Redshift, which not only is more significant for remote stars or galaxies, but also better fits the observational data, including those used in Hubble constant calculation. As such, if true, this new theory not only adds to our new understanding of photons, but may totally change our current understanding of the Universe, i.e., the Big Bang theory.

An explosive growth in vehicular wireless services and applications gives rise to spectrum resource starvation. Cognitive radio has been used to vehicular networks to mitigate the impending spectrum starvation problem by allowing vehicles to fully exploit spectrum opportunities unoccupied by licensed users. Efficient and effective detection of licensed user is a critical issue to realize cognitive radio applications. However, spectrum sensing in vehicular environments is a very challenging task due to vehicles mobility. For instance, vehicle mobility has a large effect on the wireless channel, thereby impacting the detection performance of spectrum sensing. Thus, gargantuan efforts have been made in order to analyze the fading properties of mobile radio channel in vehicular environments. Indeed, numerous studies have demonstrated that the wireless channel in vehicular environments can be characterized by a temporally correlated Rayleigh fading. In this paper, we focus on energy detection for spectrum sensing and a counting rule for cooperative sensing based on Neyman-Pearson criteria. Further, we go into the effect of the sensing and reporting channels condition on spectrum sensing performance under temporally correlated Rayleigh sensing channel. For local and cooperative sensing, we derive some alternative expressions for average probability of miss detection. The pertinent numerical and simulating results are provided to further validate our theoretical analyses under a variety of scenarios.

Since general relativity (GR) has already established that matter can simultaneously have two different values of mass depending on its context, we argue that the missing mass attributed to non-baryonic dark matter (DM) actually obtains because there are two different values of mass for the baryonic matter involved. The globally obtained "dynamical mass'' of baryonic matter can be understood as a small perturbation to a background spacetime metric even though it's much larger than the locally obtained "proper mass". Having successfully fit the SCP Union2.1 SN Ia data without accelerating expansion or a cosmological constant, we employ the same ansatz to compute dynamical mass from proper mass and explain galactic rotation curves (THINGS data), the mass profiles of X-ray clusters (ROSAT and ASCA data) and the angular power spectrum of the cosmic microwave background (Planck 2015 data) without DM. We compare our fits to modified Newtonian dynamics (MOND), metric skew-tensor gravity (MSTG) and scalar-tensor-vector gravity (STVG) for each data set, respectively, since these modified gravity programs are known to generate good fits to these data. Overall, we find our fits to be comparable to those of MOND, MSTG and STVG. While this favorable comparison does not establish the validity of our proposition, it does provide confidence in using the fits to pursue an underlying action. Indeed, the functional form of our ansatz reveals an interesting structure in these fits.

Adaptive hyperactivity, characterized by increased activity levels and novelty-seeking traits without mood disorders, is prevalent among older adults in Sardinia's "blue zone," an area with high longevity. This study aims to evaluate the adaptive nature of hyperac-tivity concerning quality of life, social rhythms, and mood symptoms in individuals from this region, particularly among older adults over 80. Methods: This observational cross-sectional study included adults and older adults over 80 years from Sardinia's blue zone, recruited from the dermatology clinic at the University Hospital of Cagliari. Partici-pants underwent psychiatric interviews and completed the Mood Disorder Questionnaire (MDQ), Patient Health Questionnaire (PHQ-9), SF-12, and Brief Social Rhythm Scale (BSRS). Data were compared with national and regional normative data. Results: Older adults in the blue zone demonstrated higher MDQ positivity (22.58%) compared to na-tional averages (0.87%), without corresponding increases in dysregulated rhythms, de-pressive symptoms, or reduced quality of life. Younger elders (65-79 years) showed in-creased rhythm dysregulation (BSRS score: 20.64±7.02) compared to adults (17.40±6.09, p=0.040), but this trend was not observed in older elders (80+ years). No significant differ-ences were found in CH3SH and (CH3)2S levels between groups. Conclusions: Hyperactiv-ity observed in older adults from Sardinia's blue zone appears adaptive, not linked to so-cial rhythm dysregulation, depressive symptoms, or diminished quality of life, suggesting resilience factors that may contribute to longevity. These findings support the potential classification of such hyperactivity as beneficial rather than pathological, warranting fur-ther research into biomarkers and psychoeducational interventions to prevent the onset of bipolar disorders in predisposed individuals.

Photocatalytic processes offer promising solutions for environmental remediation and clean energy production, yet their efficiency under visible light remains a significant challenge. Here, we report a novel silver-graphene (Ag-G) modified TiO2 (Ag-G-TiO2) nanocomposite photocatalyst that demonstrates remarkably enhanced photocatalytic activity for both dye wastewater degradation and hydrogen production under visible and UV light irradiation. Through comprehensive characterization and performance analysis, we reveal that the Ag-G modification narrows the TiO2 bandgap from 3.12 eV to 1.79 eV, enabling efficient visible light absorption. The nanocomposite achieves a peak hydrogen production rate of 191 μmolesg-1h-1 in deionized water dye solution under visible light, significantly outperforming unmodified TiO2. Intriguingly, we observe an inverse relationship between dye degradation efficiency and hydrogen production rates in dye solutions with tap water versus deionized water, highlighting the critical role of water composition in photocatalytic processes. Our findings demonstrate sustained hydrogen production under visible light and rapid initial rates under UV irradiation, underscoring the versatility of Ag-G-TiO2 catalyst. This work not only advances our understanding of fundamental photocatalytic mechanisms but also presents a promising material for solar-driven environmental and energy applications, potentially contributing to the global transition towards sustainable technologies.

Spatial and temporal variation of the free electron concentration in the ionosphere affects SAR interferograms, in particular at low radar frequencies. In this work the identification, estimation and compensation of ionospheric path delay phases in PALSAR-3 and NISAR-L interferograms is discussed. Both these L-band sensors acquire simultaneously SAR data in a main spectral band and in an additional, spectrally separated, narrower second band to support the mitigation of ionospheric path delays. The methods presented permit separating the dispersive and the non-dispersive phase terms based on the double-difference interferogram between the two available spectral bands and the differential interferogram of the main band. The applicability of the proposed methods is demonstrated using PALSAR-3-like data that was simulated based on PALSAR-2 SM1 mode data.

Abstract: Fetal Alcohol Spectrum Disorder (FASD) is considered a lifelong disability that has been framed by neurobiological descriptions focused on the brain. These are important features but fail to tell the story of living with FASD. By surveying those with FASD, this work expands upon prior survey work which illustrated a multitude of early onset physiological issues occurring at rates much higher than typical of the general population. The current project, again using an anonymous survey methodology, seeks to open up other direct experiences to better understand the complexity of living with FASD. An anonymous online survey was used to gather data on advresity in childhood, schooling, employment, housing and finances, involvement with the criminal justice system as well as relationships and parenting. Results inform how supports can be enhanced and targeted with a goal of improving the quality of life. The survey was developed by adults living with FASD who have served as a long-standing advocacy and educational group influencing policy and practice in the field.

Despite the high prevalence of epilepsy in individuals with autism spectrum disorder (ASD) there is little information regarding whether seizure characteristics and treatment effectiveness change across age. Using an on-line survey, seizure characteristics, effectiveness of antiepileptic treatments, comorbidities and ASD diagnosis were collected from individuals with ASD and seizures. We previously reported overall general patterns of treatment effectiveness but did not examine the effect of seizure characteristics or age on antiepileptic treatment effectiveness. Such information would improve the personalized medicine approach to the treatment of seizures in ASD. Survey data from 570 individuals with ASD and clinical seizures were analyzed. Seizure severity (seizure/week) decreased with age of onset of seizures, plateauing in adolescence, with a greater reduction in generalized tonic clonic (GTC) seizures with age. Seizure severity was worse in those with genetic disorders, neurodevelopmental regression (NDR) and poor sleep maintenance. Carbamazepine and oxcarbazepine were reported to be more effective when seizures started in later childhood while surgery and the Atkin’s/Modified Atkin’s Diet (A/MAD) were reported to be more effective when seizures started early in life. A/MAD and the ketogenic diet were reported to be more effective in those with NDR. Interestingly, atypical Landau-Kleffner syndrome was associated with mitochondrial dysfunction and NDR, suggesting a novel syndrome. These interesting findings need to be verified in independent, prospectively collected cohorts, but none-the-less these data provide some insight into novel relationships that may assist in a better understanding of epilepsy in ASD and providing insight into personalizing epilepsy care in ASD.

Neurodevelopmental and late-onset neurodegenerative disorders present as separate entities that are clinically and neuropathologically quite distinct. However, recent evidence has highlighted surprising commonalities and converging features at the clinical, genomic, and molecular level between these two disease spectra. This is particularly striking in the context of autism spectrum disorder (ASD) and Parkinson’s disease (PD). Genetic causes and risk factors play a central role in disease pathophysiology and enable the identification of overlapping mechanisms and pathways. Here, we focus on clinico-genetic studies of causal variants and overlapping clinical and cellular features of ASD and PD. Several genes and genomic regions were selected for our review, including SNCA (alpha-synuclein), PARK2 (parkin RBR E3 ubiquitin protein ligase), chromosome 22q11 deletion/DiGeorge region, and FMR1 (fragile X mental retardation 1) repeat expansion, which influence development of both ASD and PD with converging features related to synaptic function and neurogenesis. Both PD and ASD display alterations and impairments at the synaptic level, representing early and key disease phenotypes which support the hypothesis of converging mechanisms between the two types of diseases. Therefore, understanding the underlying molecular mechanisms might inform on common targets and therapeutic approaches. We propose to re-conceptualize how we understand these disorders and provide a new angle into disease targets and mechanisms linking neurodevelopmental disorders and neurodegeneration.

As the telecommunications landscape braces for the post-5G era, this paper embarks on delineating the foundational pillars and pioneering visions that define the trajectory towards 6G wireless communication systems. Recognizing the insatiable demand for higher data rates, enhanced connectivity, and broader network coverage, we unravel the evolution from the existing 5G infrastructure to the nascent 6G framework, setting the stage for transformative advancements anticipated in the 2030s. Our discourse navigates through the intricate architecture of 6G, highlighting the paradigm shifts towards super convergence, non-IP-based networking protocols, and information-centric net-works, all underpinned by a robust 360-degree cybersecurity and privacy-by-engineering design. Delving into the core of 6G, we articulate a systematic exploration of the key technologies earmarked to revolutionize wireless communication including terahertz (THz) waves, optical wireless technology, and dynamic spectrum management,while elucidating the intricate tradeoffs necessitated by the integration of such innovations. This paper not only lays out a comprehensive 6G vision accentuated by high security, affordability, and intelligence but also charts the course for addressing the pivotal challenges of spectrum efficiency, energy consumption, and the seamless integration of emerging technologies. In this study, our goal is to enrich the existing discussions and research efforts by providing comprehen-sive insights into the development of 6G technology, ultimately supporting the creation of a thoroughly connected future world that meets evolving demands.

Helicobacter pylori infection constitutes a silent pandemic of global concern. In the last decades, the alarming increase of multidrug resistance evolved by this pathogen has led to a marked drop in the eradication rates of traditional therapies worldwide, encouraging scientific community to discover and develop new antimicrobial strategies. In the present work, we identified a battery of novel drug-like HsrA inhibitors with MIC values ranging from 0.031 to 4 mg/L against antibiotic-resistant strains of H. pylori. Most of these novel antimicrobials exhibited minor effects against both Gram-negative and Gram-positive species of human microbiota. The most potent anti-H. pylori candidate demonstrated a high therapeutic index, additive effect in combination with metronidazole and clarithromycin, as well as a strong antimicrobial action against Campylobacter jejuni, another clinically relevant pathogen of phylum Campylobacterota. Transcriptomic analysis suggested that in vivo inhibition of HsrA triggered lethal global disturbances in H. pylori physiology, including the arrest of protein biosynthesis, malfunction of respiratory chain, detriment in ATP generation, and oxidative stress. The novel drug-like HsrA inhibitors described here constitute valuable candidates to a new family of narrow-spectrum antibiotics that allow overcoming the current resistome, protecting from dysbiosis, and increasing therapeutic options for novel personalized treatments against H. pylori.

Background: Gluten and casein-containing foods could aggravate the symptoms of children and adolescents with autism spectrum disorder (ASD), and subsequently impact their quality of life. However, there is a mixed opinion among researchers concerning the impact of alternative diet on reducing ASD symptoms. Objective: This scoping review aimed at examining the impact of the ‘’gluten-free, casein-free’’ (GFCF) diet on health outcomes and the quality of life among autistic children and adolescents. Methods: A scoping review of the literature was performed following the Joanna Briggs Institute (JBI) guidelines. Four databases including EbscoHost, Medline, CINAHL and ProQuest were used to obtain subject-specific studies relevant to the research question and published between July 2013 and March 2024. A comprehensive search using keywords such as “autism spectrum disorder”, “gluten-free diet”, and “casein-free diet” was conducted to obtain articles related to the research focus area. Only full-text, peer-reviewed, written in English articles were selected. Data extraction and data analysis were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses- extension to Scoping Review (PRISMA-ScR) protocol. Results: From the initial 586 studies a total of 27 articles were included in the final analysis of the review. The thematic analysis included ‘GFCF diet and improvement of the core autistic symptoms’’, “the gut-brain link’’, ‘’dietary interventions and autism’’, ‘’possible side effects due to the GCFC diet’’, and ‘’ inconclusive studies and mixed opinions’’. Majority of the studies showed positive effect of the GFCF diet on a variety of autistic symptoms including positive changes in cognitive skills, behaviour, and gastrointestinal symptoms while some showed conflicting evidence. Conclusion: The currently available evidence on the impact of ‘GFCF’’ diet on the quality of life of autistic children and adolescents may warrant potentially effective interventions for alleviating symptoms of autism spectrum disorders. However, this scoping review highlighted the need for more research to provide more reliable evidence on the health outcomes and quality of life of ASD sufferers to guide practice.

The prevalence of autism has been increasing at an alarming rate. Even accounting for the expansion of autism spectrum disorder diagnostic (ASD) criteria throughout the 1990’s, there has been an over 300% increase in ASD prevalence since the year 2000. The often debilitating personal, familial, and societal sequelae of autism are generally believed to be lifelong. However, there have been several encouraging case reports demonstrating reversal of autism diagnoses with a therapeutic focus on addressing the environmental and modifiable lifestyle factors believed to be largely underlying the condition. This case report describes the reversal of autism among dizygotic, female twin toddlers and provides a review of related literature describing associations between modifiable lifestyle factors, environmental exposures, and various clinical approaches to treating autism. The twins were diagnosed with Level 3 severity ASD “requiring very substantial support” at approximately 20 months of age following concerns of limited verbal and non-verbal communication, repetitive behaviors, rigidity around transitions, and extensive gastrointestinal symptoms, among other common symptoms. A parent-driven, multidisciplinary, therapeutic intervention involving a variety of licensed clinicians focusing primarily on addressing environmental and modifiable lifestyle factors was personalized to each of the twin’s symptoms, labs, and other outcome measures. Dramatic improvements were noted within several months in most domains of the twins’ symptoms, which was manifested in reductions of Autism Treatment Evaluation Checklist (ATEC) scores from 76 to 32 in one of the twins and from 43 to 4 in the other twin. The improvement in symptoms and ATEC scores has remained relatively stable for six months at last assessment. While prospective studies are required, this case offers further encouraging evidence of ASD reversal through a personalized, multidisciplinary approach focusing predominantly on addressing environmental and lifestyle risk factors.

Neuromyelitis optica spectrum disorder (NMOSD), previously known as Devic disease or neuromyelitis optica (NMO), represents inflammatory conditions affecting the central nervous system. These disorders are characterized by severe immune-mediated demyelination and axonal damage, with a predilection for targeting optic nerves and the spinal cord. Key clinical features of NMOSD encompass acute episodes of bilateral or rapid sequential optic neuritis and transverse myelitis, typically exhibiting a relapsing course. These attacks endure for several days, and recovery varies, spanning from weeks to months. In this report, we present the case of a 35-year-old individual who initially complained of urinary retention, followed by decreasing vision in the left eye and subsequently in the right eye. These visual symptoms were succeeded by weakness in the right upper and lower limbs.

As distinct human societies, three unique intentional communities are investigated regarding their preferred consensus decision-making practices. It is Identified that each has adopted a different form of consensus decision-making to solve potential group-wide interpersonal conflict. The individual attributes of these three consensus decision-making practices are considered, both from the perspective of maintaining group stability and in relation to individual member's mental health. The communities are a Canadian self-directed public senior elementary and secondary school, an annual English conference for those self-identifying as on the autistic spectrum, and a self-producing Korean popular music (K-pop) group. It is found that the intentional community and participants’ mental health are sustained regarding each of the three consensus decision-making practices. Nevertheless, the resulting decisions generate various stresses within the communities, both as a whole and concerning the individual members. To retain group cohesion and maintain individual mental health, these stresses must be recognized and understood by participants. The novel finding of this research is that, dependent on the time available for decision-making, and the members’ perspective adopted, intentional communities might practice more than one form of consensus decision-making and still support both group cohesion and individual mental health, maintaining the democracy of these distinct societies.

Steel construction is used more often these days as an alternative to the R.C.C. when light weight, high strength, large-span structures with a faster erection are required. Extensive studies have been done by researchers to study the seismic performance of reinforced concrete and steel structures, both in terms of elastic and inelastic behavior. Composite construction is also a recent advancement in the building industry with similar advantages. However, no emphasis has been given to the comparison between the inelastic behavior of steel and composite structures when subjected to lateral loads. This study compares the inelastic behavior of steel and a composite frame designed to have the same plastic moment capacity for structural members. The responses, such as the formation of hinges, story drifts, story displacements, lateral stiffness, ductility, maximum strength, energy dissipated, joint accelerations, and performance points, are compared with the aid of the building analysis and design software ETABS-18. For this, response spectrum analysis, pushover analysis and nonlinear direct integration time history analysis have been performed on both frames. For design and analysis, international codes such as IS 800-2007, IS 875 (Part I, II, IV), IS 1893-2002, AISC 360 (16 &amp; 10) and FEMA 440 have been used. Part of this study also aims at comparing the response of these frames when subjected to near field and far field earthquakes. It can be concluded from the results that the post yield performance of the composite frame is superior to that of the steel frame when seismically excited.

Cancer cells can acquire a spectrum of stable hybrid epithelial/mesenchymal (E/M) states during epithelial-mesenchymal transition (EMT). Cells in these hybrid E/M phenotypes often combine epithelial and mesenchymal features and tend to migrate collectively commonly as small clusters. Such collectively migrating cancer cells play a pivotal role in seeding metastases and their presence in cancer patients indicates an adverse prognostic factor. Moreover, cancer cells in hybrid E/M phenotypes tend to be more associated with stemness which endows them with tumor-initiation ability and therapy resistance. Most recently, cells undergoing EMT have been shown to promote immune suppression for better survival. A systematic understanding of the emergence of hybrid E/M phenotypes and the connection of EMT with stemness and immune suppression would contribute to more effective therapeutic strategies. In this review, we first discuss recent efforts combining theoretical and experimental approaches to elucidate mechanisms underlying EMT multi-stability (i.e. the existence of multiple stable phenotypes during EMT) and the properties of hybrid E/M phenotypes. Following we discuss non-cell-autonomous regulation of EMT by cell cooperation and extracellular matrix. Afterwards, we discuss various metrics that can be used to quantify EMT spectrum. We further describe possible mechanisms underlying the formation of clusters of circulating tumor cells. Last but not least, we summarize recent systems biology analysis of the role of EMT in the acquisition of stemness and immune suppression.

Music has the innate potential to reach all parts of the brain, stimulates certain brain areas which are not achievable through other modalities. Music Therapy (MT) is being used for more than a century to treat individuals who needs personalized care. MT optimizes motor, speech and language responsibilities of the brain and improves cognitive performance. Pervasive developmentdisorder (PDD) is a multifaceted, neuro developmental disorder and autism spectrum disorder (ASD) comes under PDD, which is defined by deficiencies in three principal spheres: social connection with others, communicative and normal movement skills. The conventional imaging studies illustrate reduced brain area connectivity in people with ASD, involving selected parts of the brain cortex. People with ASD express much interest in musical activities which engages the brain network areas and improves communication and social skills.The main objective of this review is to analyze the potential role of MT in treating the neurological conditions, particularly ASD. Evidence based studies have reported the extensive therapeutic application of music on various part of the brain in a nonverbal child with autism through hearing or making music.Hence we hypothesized that MT intervention can improve the communication capacity in people with ASD, than customary neurorestoration therapy alone.

Autism Spectrum Disorder (ASD), a neurodevelopmental disorder, is increasingly diagnosed and significantly affects communication, behavior, and social interaction. The current diagnostic framework, guided by the DSM-5, has limitations that may lead to clinical gaps due to overlapping symptoms of ASD and other disorders. This study proposes a comprehensive approach to enhance ASD diagnosis through clinical stratification based on comorbidities. We applied precision medicine techniques to identify and categorize ASD into ten clinical profiles. Our findings contribute to a more profound understanding of ASD, including its varied clinical manifestations and comorbidities, and facilitate the development of personalized therapeutic strategies.

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine Operation and Maintenance (O&amp;M). Incorporating machine learning in developing condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Base Density for the Support Vector Machine (BDSVM) and the evolutionary Fourier spectra of vibrations. This method allows smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the BDSVM to timely determine the magnitude, frequency, and place of the failure occurring in wind turbine drive.

We propose an asynchronous acoustic chirp slope keying to map bit sequences on single or multiple bands without preamble or error correction coding on the physical layer. Details of the implementation are disclosed and discussed, the performance verified on laboratory scale in a pool measurement, as well as simulated for a channel containing Rayleigh fading and Additive White Gaussian Noise. For time-bandwidth products of 50 in single band mode, a raw data rate of 100~bit/s is simulated to achieve bit error rates below 0.001 for signal-to-noise ratios above -6~dB. In dual-band mode and a data rate of 200~bit/s, this bit error level was achieved for signal-to-noise ratios above 0~dB for time-bandwidth product of 25. The packet error rates follow this behavior with an offset of 1~dB.

SHANK3 encodes scaffold protein involved in postsynaptic receptor density in glutamatergic synapses, including those in the parvalbumin (PV)+inhibitory neurons – the key players in generation of sensory gamma oscillations, such as 40-Hz auditory steady-state response(ASSR). Here we describe a clinical and neurophysiological phenotype of a 15-years old girl (SH01) with microduplication of 16389 bp in 22q13.33, affecting the SHANK3 gene in comparison to typically developing children (n=32). EEG were recorded during the binaurally presentation of 40-Hz clicks’ trains lasting for 500 ms with inter-trial intervals 500-800 ms. SH01 was diagnosed with mild mental retardation and learning disabilities(F70.88) and had problems with reading and writing, as well as smaller vocabulary than TD peers. Her clinical phenotype generally resembled the phenotype of previously described patients with 22q13.33 microduplication. SH01 had mild autistic symptoms but below the threshold for ASD diagnosis. No seizures or MRI abnormalities were reported. While SH01 had relatively preserved auditory event-related potential(ERP) with slightly attenuated P1, her 40-Hz ASSR was totally absent significantly deviating from TD’s ASSR. Absence of 40-Hz ASSR in patient with microduplication, affected SHANK3 gene, indicates deficient temporal resolution of the auditory system, that might underlie language problems, and represent neurophysiological biomarker of SHANK3 abnormalities.

The i-4-1-Health project is a One Health project on the prevalence and spread of antimicrobial resistance in the human and veterinary domain in the Dutch-Belgian cross-border region. This paper describes the main components of the laboratory protocol that was developed to standardise the microbiological methods used for the detection of intestinal carriage of highly-resistant microorganisms.

The World Health Organization recently proposed the Tricycle Protocol for harmonized surveillance of extended-spectrum beta lactamase-producing E. coli (ESBL-Ec) as a proxy for AMR among humans, animals, and the environment. We implemented the Tricycle Protocol with ceftriaxone (CRO) to screen for ESBL-Ec using membrane filtration (TBX-CRO) and Colilert Quanti-Tray (CQT-CRO) workflows in parallel applied to water samples collected from four lakes. ESBL-Ec and E. coli abundance and prevalence, and ESBL-Ec to E. coli ratios were significantly higher in the two highly impacted lakes (receiving sewage treatment plant effluent, open defecation site adjacent to informal settlements) compared to less impacted lakes (wildlife sanctuary, recreational site). The cumulative burden of antibiotic compounds was also higher in the highly impacted lakes. Even in the “pristine” lake in a bird sanctuary, ESBL-Ec and an antibiotic compound were present. Overall, the CQT-CRO format yielded reasonable qualitative (K = 0.603) and quantitative agreement (intra-class correlation coefficient = 0.849) and linearity (r² = 0.785) with the TBX-CRO format adapted from the Tricycle Protocol. However, CQT-CRO doubled the prevalence of ESBL-Ec in settings with decreased E. coli abundance. Consistent with observations for other third-generation cephalosporins, CRO performed poorly for screening the ESBL phenotype. Further, confirmed ESBL-Ec isolates were not associated with an increased number of resistance phenotypes compared with non-ESBL isolates. Instead, the number of resistance phenotypes was associated with the lake from which the sample was collected. In high-burden settings, AMR surveillance efficiency could be increased by directly testing generic E. coli isolates for ESBL phenotype and antibiotic susceptibility. Our experience also suggests that sequencing ESBL-Ec will likely be required to determine epidemiologically appropriate risk mitigation strategies where ESBL-Ec are prevalent. Resource limitations could jeopardize the relevance of the Tricycle Protocol for changing the trajectory of AMR in high-burden low-resource settings globally.

Age-related macular degeneration (AMD) causes visual impairment in individuals >50 years of age. However, no study has investigated AMD using ultra-wide-field swept-source optical co-herence tomography (UWF SS-OCT). We aimed to evaluate central and peripheral choroidal thickness using UWF SS-OCT and compare AMD subtypes. We included 75 eyes of patients with typical AMD (tAMD), 56 with polypoidal choroidal vasculopathy (PCV), 29 with pachychoroid neovasculopathy (PNV), and 12 with retinal angiomatous proliferation (RAP). To compare cho-roidal thicknesses in the central and peripheral choroids, we established subfields of <3 mm, <9 mm, and 9–18 mm from the fovea. PNV patients were significantly younger than those with tAMD (P=0.01). The choroidal thicknesses of PNV were significantly greater than that of tAMD in all subfields (P<0.01) and choroidal thickness significantly correlated with age and axial length in all subfields (P<0.05). Even after adjusting for age and axial length, the choroidal thickness in PNV was significantly greater than that in tAMD (P<0.05). In addition, the ratio of the posterior < 9 mm to peripheral 9–18 mm choroidal thickness in PNV was significantly greater than that in tAMD (P<0.01). A thickened choroid in PNV was more pronounced in the posterior choroid than in the periphery.

A random variable X that is base b Benford will not in general be base c Benford when c is not equal to b. This paper builds on two of my earlier papers and is an attempt to cast some light on the issue of base dependence. Following some introductory material, the “Benford spectrum” of a positive random variable is introduced and known analytic results about Benford spectra are summarized. Some standard machinery for a “Benford analysis” is introduced and combined with my method of “seed functions” to yield tools to analyze the base c Benford properties of a base b Benford random variable. Examples are generated by applying these general methods to several families of Benford random variables. Berger and Hill's concept of “base-invariant significant digits” is discussed. Some potential extensions are sketched.

The textbook analysis of vacuum energy density (VED) in flat spacetime follows from Pauli’s lectures of 1951, in which quantum vacuum is modeled as a reservoir of free harmonic oscillators. In his lectures, Pauli shows that deriving a nearly vanishing VED is contingent upon fulfilling three corollary conditions called polynomial-in-mass-constraints. The goal of this work is to evaluate Pauli’s constraints against the Standard Model parameters and the Higgs mechanism of spontaneous symmetry breaking.

The transmission characteristic of COVID-19 is of similar magnitude to severe acute respiratory syndrome-related coronavirus (SARS-CoV) and the 1918 pandemic influenza. The virus is now in more than 100 countries and on nearly all continents. The World Health Organization (WHO) declared the COVID-19 outbreak a pandemic. There is no current evidence from random clinical trials (RCTs) to recommend any specific anti-COVID-19 treatment for patients with suspected or confirmed COVID-19 infection. In order to mitigate the impact of the COVID-19 outbreak, here we propose an innovative superinfection therapeutic (SIT) strategy, which could complement the development of prophylactic vaccines. SIT is based on clinical observations that unrelated viruses might interact in co-infected patients. During SIT, the patient benefit from superinfection with an apathogenic dsRNA virus such as the infectious bursal disease virus (IBDV), which is a powerful activator of the interferon-dependent antiviral gene program. An attenuated vaccine strain of IBDV was already successfully administered to resolve acute and persistent infections induced by two completely different viruses, the hepatitis B (DNA) and C (RNA) viruses (HBV/HCV). Importantly, the epidemiological efficacy of a similar strategy to SIT had already been successfully tested in large controlled trials. Standard live orally administered enterovirus vaccines that stimulate the production of endogenous interferon of the host mitigated the seasonal outbreaks of influenza and other associated acute respiratory infections in 152,042 individuals without adverse reactions.

The first part of the paper was aimed at analyzing the given nonlinear problem by different methods of computation of the Lyapunov exponents (Wolf method [1], Rosenstein method [2], Kantz method [3], method based on the modification of a neural network [4, 5], and the synchronization method [6, 7]) for the classical problems governed by difference and differential equations (Hénon map [8], hyper-chaotic Hénon map [9], logistic map [10], Rössler attractor [11], Lorenz attractor [12]) and with the use of both Fourier spectra and Gauss wavelets [13]. It was shown that a modification of the neural network method [4, 5] makes it possible to compute a spectrum of Lyapunov exponents, and then to detect a transition of the system regular dynamics into chaos, hyper-chaos, hyper hyper-chaos and deep chaos [14-16]. Different algorithms for computation of Lyapunov exponents were validated by comparison with the known dynamical systems spectra of the Lyapunov exponents. The carried out analysis helps comparatively estimate the employed methods in order to choose the most suitable/optimal one to study different kinds of dynamical systems and different classes of problems in both this and the next paper parts.

As artificial intelligence (AI) makes significant headway in various arenas, the field of Speech-Language Pathology is at the precipice of experiencing a transformative shift towards automation. This study introduces QuickPic AAC, an AI-driven application designed to generate topic-specific displays from photographs in a "just-in-time" manner. Using QuickPic AAC, this study aimed to (a) determine which of two AI algorithms (NLG-AAC and GPT-3.5) results in greater specificity of vocabulary (i.e., percentage of vocabulary kept/deleted by clinician relative to vocabulary generated by QuickPic AAC; percentage of vocabulary modified); and to (b) evaluate perceived usability of QuickPic AAC among practicing speech-language pathologists. Results revealed that the GPT-3.5 algorithm consistently resulted in greater specificity of vocabulary and that speech-language pathologists expressed high user satisfaction for the QuickPic AAC application. These results support continued study of the implementation of QuickPic AAC in clinical practice and demonstrate the possibility of utilizing topic-specific displays as just-in-time supports.

Background: Mental capacity is a fundamental aspect that enables patients to fully par-ticipate in various healthcare procedures. To assist healthcare professionals (HCPs) in assessing patients' capacity, especially in the mental health field, several standardized tools have been developed. These tools include the MacArthur Competence Assessment Tool for Treatment (MacCAT-T), the MacArthur Competence Assessment Tool for Clinical Research (MacCAT-CR), and the Competence Assessment Tool for Psychiatric Advance Directives (CAT-PAD). The core dimensions explored by these tools include Understanding, Appreciation, Reasoning, and Expression of a choice. Objective: This meta-analysis aimed to investigate potential differences in deci-sion-making capacity within the healthcare context among groups of patients with bi-polar disorder (BD) and schizophrenia spectrum disorder (SSD). Methods: A systematic search was conducted on Medline/Pubmed, and Scopus. Addi-tionally, Google Scholar was manually inspected, and a manual search of emerging re-views and reference lists of the retrieved papers was performed. Eligible studies were specifically cross-sectional, utilizing standardized assessment tools, and involving pa-tients diagnosed with BD and SSD. Data from the studies were independently extracted and pooled using random-effect models. Hedges g was used as a measure for outcomes. Results: Six studies were identified, with three studies using the MacCAT-CR, two studies the MacCAT-T, and one the CAT-PAD. The participants included 189 individuals with BD and 324 individuals with SSD. The meta-analysis revealed that patients with BD performed slightly better, and the difference was statistically significant, compared to patients with SSD, particularly in the domain of Appreciation (ES=0.23, 95% CI: 0.01 to 0.04, p=0.037). There was no statistically significant difference between the two groups for Understanding (ES=0.09, 95% CI: - 0.10 to 0.27, p=0.352), Reasoning (ES=0.18, 95% CI: - 0.12 to 0.47, p=0.074), and Expression of a choice (ES = 0.23, 95% CI: - 0.01 to 0.48, p=0.60). In the sensitivity analysis, furthermore, when considering only studies involving patients in symptomatic remission, the difference for Appreciation also resulted in non-significant (ES=0.21, 95% CI: -0.04 to 0.46, p=0.102). (ES=0.21, 95% CI: -0.04 to 0.46, p=0.102). Conclusions: These findings indicate that there are no significant differences between patients with BD and SSD during remission phases, while differences are minimal during acute phases. The usefulness of standardized assessment of capacity at any stage of the illness should be considered, both for diagnostic-therapeutic phases and for research and advance directives. Further studies are necessary to understand the reasons for the overlap in capacity between the two diagnostic categories compared in this study.

Statistical denoising techniques have been well studied, however many challenges still remain. This 9 article focuses on determining the least necessary number of significant samples in a statistical pop-10 ulation sampling, while minimizing the impact on the statistical detection of the fiber Bragg grating 11 (FBG) power spectra. This is achieved by using Bayesian decision making, small population statis-12 tics while excluding false detection. First, we investigate the impact of two-sided sliding window 13 technique applied near the cell under the test. The window size varies from 8 to 60 samples. The 14 considered maximum size of population sampling is connected with the number of wavelength 15 samples within the bandwidth of the symmetrical FBG power spectra peaks. Regarding the sym-16 metry of FBG power spectra peaks and the possible reduction of computational demands, we inves-17 tigate the impact of a one-sided sliding window. This enables to achieve less processing latency for 18 real time applications thus brings benefits to FBG-based fiber optical sensing. Both, two- and one-19 sided small population sampling techniques are then experimentally verified. Detection results are 20 analyzed in depth via calculating detection thresholds by using the small size window sliding along-21 side the waveband. From results achieved, it was found that the normality three-sigma rule does 22 not need to be followed while using the small population sampling. Experimental demonstrations 23 and analyses showed that the proposed concept of denoising and statistical threshold detection 24 based on the sliding window does not depend on the prior knowledge of probability distribution 25 functions of the FBG power spectra peaks level and background noise. We have also found that the 26 thresholds’ adaptability mainly depends on the statistical numerical characteristics of the above ad-27 ditive mixture of the FBG power spectra peaks signals and background noise.

The lung microbiota is a complex community of microorganisms that colonize the respiratory tract of individuals from or even before birth. Although the lungs were traditionally believed to be sterile, recent research has shown that there is a diversity of bacterial species in the respiratory system. Knowledge about the lung microbiota in the newborn and its relationship with bacterial infections is of vital importance to understand the pathogenesis of respiratory diseases in neona-tal patients undergoing mechanical ventilation. In this article, the current evidence on the compo-sition of the lung microbiota in the newborn will be reviewed, as well as its role in the develop-ment of bacterial infections in mechanically ventilated neonates. Although advances in many as-pects of the neonatal intensive care unit care have significantly improved the survival of preterm infants, the diagnosis and treatment of ventilator-associated pneumonia has not progressed in recent decades. Avoiding dysbiosis caused by inappropriate use of antibiotics around birth, as well as avoiding intubation of patients or promoting early removal of endotracheal tubes are among the most important preventive measures for ventilator-associated pneumonia. The use of probiotics and prebiotics to prevent infectious, allergic or metabolic complications in the short or long term constitutes a very important field of research in perinatal medicine.

Studies have previously described the occurrence of multidrug-resistant (MDR) Escherichia coli in human and veterinary medical settings, livestock, and, to a lesser extent, in the environment and food. While they mostly analyzed foodborne E. coli regarding phenotypic and sometimes genotypic antibiotic resistance and basic phylogenetic classification, we have limited understanding of the in vitro and in vivo virulence characteristics and global phylogenetic contexts of these bacteria. Here, we investigated an E. coli strain (PBIO3502) isolated from a pork sausage in Germany in 2021 in-depth. Whole-genome sequence analysis revealed sequence type (ST)58, which is an emerging international high-risk clonal lineage. In addition to its MDR phenotype that mostly matched the genotype, PBIO3502 demonstrated pronounced virulence features, including in vitro biofilm formation, siderophore secretion, serum resilience, and in vivo mortality in Galleria mellonella larvae. Along with the genomic analysis indicating close phylogenetic relatedness of our strain with publicly available, clinically relevant representatives of the same ST, these results suggest the zoonotic and pathogenic character of PBIO3502 with the potential to cause infection in humans and animals. Also, our study highlights the necessity of the One Health approach while integrating human, animal, and environmental health, as well as the role of meat products and food chains in the putative transmission of MDR pathogens.

Autism Spectrum Disorder etiopathogenesis is still unclear and no effective preventive and treatment measures have been identified. Research has focused on the potential role of neuroinflammation and kynurenine pathway. Here we review the nature of these interactions. Pre-natal or neonatal infections would induce microglial activation, with secondary consequences on behavior, cognition and neurotransmitter networks. Peripherally, higher levels of pro-inflammatory cytokines and anti-brain antibodies have been identified. Increased frequency of autoimmune diseases, allergies, and recurring infections have been demonstrated both in autistic patients and in their relatives. Genetic studies, also, have identified some important polymorphisms in chromosome loci related to human leukocyte antigen (HLA) system. The persistence of immune-inflammatory deregulation would lead to mitochondrial dysfunction and oxidative stress, creating a self-sustaining cytotoxic loop. Chronic inflammation activates kynurenine pathway with increase in neurotoxic metabolites and excitotoxicity, causing long-term changes in glutamatergic system, trophic support and synaptic function. Furthermore, overactivation of kynurenine’s branch induces depletion of melatonin and serotonin worsening ASD symptoms. In this scenario, kynurenine pathway appears as a pharmacological target to treat and prevent ASD. Thus, in genetically predisposed subjects aberrant neurodevelopment may derives from a complex interplay between inflammatory process, mitochondrial dysfunction, oxidative stress and kynurenine pathway overexpression. To validate previous hypothesis a new translational research approach is necessary.

In this paper we review dynamics and roughness of bonds in proteins on example of albumin, that is important from the physiological point of view. We have performed computer simulations of albumin chain. Statistics were collected by performing many simulations realizations for each experimental setting. We concentrate on hydrogen bonds, cation-π and π- π interactions and NP contacts. Histograms of hydrogen bonds length are positively skewed in contrary to histograms of interactions and HP contacts that are negatively skewed. Scaling exponents of power spectra of energies of bonds / interactions /contacts are in range -0.2 to -0.5 and significantly differ between various hydrogen bonds or interactions. Varying scaling of such spectra can be used to classify between distinct bonds or contacts. Concerning particular amino-acids, largest amount of HBO H20 bonds are between Glutamate (GLU) amino-acids and water particle, while large amount of HBO bonds are formed with Lysine (LYS). For HP contacts the mayor role plays Phenylalanine (PHE) and Leucine (LEU) amino-acids. From decay curves HBO H2O bonds decays in fastest rate, while HBO bonds and HP contacts at slowest rate. We present as well decay curves of bonds formed by particular amino-acids, that gives interesting results.

This study investigates Autism Spectrum Disorders (ASD) in Greece, focusing on estimating prevalence and identifying regional disparities in children aged 4 to 7 years. Utilizing a quantitative, descriptive, and exploratory methodology, the research employed a structured questionnaire to gather extensive maternal and child health data. The sample consisted of 517 mothers of children diagnosed with ASD from all over Greece contributing to a nuanced understanding of ASD predictors. The study aims to elucidate the role of prenatal factors in the likelihood of an ASD diagnosis and their impact on the subsequent functionality of children with ASD. The study identified significant predictors of lower functionality in children with ASD, including higher maternal age, delayed ASD diagnosis, lower family income, and higher birth order. Prenatal health issues, such as vaginal bleeding and infections, also influenced functional outcomes. Notably, a family history of neurological or psychiatric conditions appeared protective. The regression model demonstrated robust predictive power, underscoring the complexity of genetic, environmental, and socioeconomic factors in ASD development. The findings advocate for early diagnosis and intervention, systematic screening, and addressing socioeconomic disparities to improve functional outcomes. The results support evidence-based service development and policy adjustments to enhance early identification, intervention, and rehabilitation for children with ASD. Establishing standardized case-recording procedures and an ASD register at national and regional levels is recommended for systematic monitoring and resource evaluation.

Sensory processing challenges are crucial yet often neglected aspects in the care of children with neurodevelopmental disorders and genetic conditions. They represent a key area of interest in neuroscience, as they significantly impact children's daily functioning and quality of life. This observational study examines the characteristics of these challenges in a group of 614 children, aged 3 to 14 years and 11 months, divided into three groups: 183 with neurodevelopmental disorders (Autism Spectrum Disorder, Attention Deficit Hyperactivity Disorder, developmental delays, learning disorders), 89 with genetic conditions (22q11.2 Deletion Syndrome, Williams Syndrome, Pseudohypoparathyroidism), and 342 controls. Sensory processing was assessed using the Sensory Profile 2 (SP2). Results indicated that children with neurodevelopmental disorders and genetic conditions exhibited significant sensory processing difficulties compared to controls. The SP2 identified sensory challenges across different sensory systems, with varying configurations depending on the diagnosis. Children with neurodevelopmental disorders and genetic conditions show marked sensory processing challenges impacting daily lives and well-being. These findings highlight the importance of early identification and tailored evidence-based interventions to address these specific sensory processing issues. Further research should explore the long-term impact of these interventions in these different populations and their integration into broader therapeutic programs.

Autism spectrum disorder (ASD) is a neuropsychiatric condition characterized by impaired social interactions and repetitive stereotyped behaviors. Growing evidence highlights an important role of the gut-brain-microbiome axis in the pathogenesis of ASD. Research indicates an abnormal composition of the gut microbiome and the potential involvement of bacterial molecules in neuroinflammation and brain development disruptions. Concurrently, attention is directed towards the role of short-chain fatty acids (SCFAs) and impaired intestinal tightness. This comprehensive review emphasizes the potential impact of maternal gut microbiota changes on the development of autism in children, especially considering maternal immune activation (MIA). The following paper evaluates the impact of the birth route on the colonization of the child with bacteria in the first weeks of life. Furthermore, it explores the role of pro-inflammatory cytokines, such as IL-6 and IL-17a and mother’s obesity as potentially environmental factors of ASD. The purpose of the present analysis is to advance our understanding of ASD pathogenesis, while also searching for the positive implications of the latest therapies, such as probiotics, prebiotics or fecal microbiota transplantation, targeting the gut microbiota and reducing inflammation. This review aims to provide valuable insights that could instruct future studies and treatments for individuals affected by ASD.

This article proposes the use of intranasal rifampin as a means to improve protein homeostasis and disaggregate misfolded proteins in the age-related neurodegenerative proteinopathies. Alzheimer’s disease, Parkinson’s disease, multi-system atrophy, Lewy body dementia, frontotemporal dementia, amyotrophic lateral sclerosis and Huntington’s disease are all, at the core, proteinopathies. Although these diseases varying greatly in the specific disease-associated proteins, anatomic sites of the abnormal protein deposition and clinical presentations, what they have in common is disruption of normal “housekeeping” functions related to protein homeostasis, proteostasis. The prospect of pharmacologically augmenting autophagic capacity with a known drug repurposed to improve proteostasis is attractive; to accomplish these ends with an inexpensive drug with relative ease of delivery adds to the attractiveness. Rifampin can be delivered to the brain via the intranasal route. Rifampin has been used for decades primarily against mycobacterial infection; it has been given with intravenous, oral, intrathecal and topical routes including as eyedrops and nasal spray. Rifampin disaggregates toxic oligomers in vitro; given intranasally, rifampin improves memory and clears pathologic proteins in animal models of the proteinopathies. Rifampin acts as both a gatekeeper and a housekeeper against the abnormal proteins of these diseases. This article suggests the merit of a clinical trial with intranasal rifampin to boost protein homeostasis in the most common age-related neurodegenerative proteinopathy, Alzheimer’s disease. The primary outcome of such a trial is change in risk of Alzheimer’s pathology as measured by plasma-based amyloid peptide 42/40 testing pretreatment and follow-up testing after 6 months of intranasal rifampin.

Ferrocenium (Fc+) inherits a number of molecular/electronic properties from the neutral counterparts’ ferrocene (Fc) including the high symmetry. Both Fc+ and Fc prefer the eclipsed structure (D5h) over the staggered structure (D5d) by an energy of 0.36 kcal·mol-1. The present study using the recently developed excess orbital energy spectrum (EOES) shows that the open shell Fc+ cation exhibits similar conformer dependent configurational changes to the neutral Fc conformer pair. A further energy decomposition analysis (EDA) discloses that the reasons for the preferred structures are different between Fc+ and Fc. The dominant differentiating energy between the Fc+ conformers is the electrostatic energy (EEstat), whereas in neutral Fc, it is the quantum mechanical Pauli repulsive energy (EPauli). Within the D5h conformer of Fc+, the EOES reveals that the -electrons of Fc+ experience more substantial conformer dependent energy changes than the -electrons (assumed the hole is in a β orbital).

Fragile X Syndrome (FX) is the most common form of inherited cognitive impairment and falls under the broader category of Autism Spectrum Disorders (ASD). FX is caused by a CGG trinucleotide repeat expansion in the non-coding region of the X-linked Fragile X Messenger Ribonucleoprotein 1 (FMR1) gene, leading to its hypermethylation and epigenetic silencing. Animal models of FX rely on the deletion of the Fmr1 gene which fail to replicate the epigenetic silencing mechanism of the FMR1 gene seen in human patients. Human stem cells carrying FX repeat expansions have provided a better understanding of the basis of the epigenetic silencing of FMR1. Previous studies have found that 5-Azacytidine (5Azac) can reverse this methylation; however, 5Azac can be toxic and may limit its therapeutic potential. Here, we show that the dietary factor Ascorbic Acid (AsA) can reduce DNA methylation in the FMR1 locus and lead to an increase in FMR1 gene expression in FX iPSCs and cerebral organoids. In addition, AsA treatment rescued neuronal gene expression and the morphological defects observed in FX iPSC-derived cerebral organoids. Hence, we demonstrate that the dietary co-factor AsA can partially revert molecular and morphological defects seen in human FX models in vitro. Our findings have implications for the development of novel therapies for FX in the future.

This study investigates the emergence of ertapenem-resistant, meropenem-susceptible (ErMs) among non-carbapenemase producing (NCP) and carbapenemase producing (CP) Escherichia coli and Klebsiella pneumoniae. As mutations for ertapenem resistance establish the genetic background for non-carbapenemase meropenem resistance, there is a great need for antibiotic stewards and researchers to understand the determinants of a strain’s propensity to become resistant. Whole genome sequencing was conducted on clinical carbapenem-resistant E. coli (CREC) and K. pneumoniae (CRKP) across 5 hospitals in San Antonio, U.S. from 2012-2018. The majority of carbapenem resistant Enterobacterales (CRE) were NCP (54%; 41/76). The blaCTX-M was found to be most prevalent among NCP isolates (p = 0.02). LC-MS/MS analysis of carbapenem hydrolysis revealed that blaCTX-M-mediated carbapenem hydrolysis, indicating the need to reappraise the term, “non-carbapenemase (NCP)” for quantitatively uncharacterized CRE strains harboring blaCTX-M. Antimicrobial susceptibility results showed that 56% of all NCPE isolates had an ErMs phenotype (NCPE vs. CPE, p &lt; 0.001), with E. coli driving the phenotype (E. coli vs. K. pneumoniae, p &lt; 0.001). ErMs strains carrying blaCTX-M, had approximately 4-fold more copies of blaCTX-M than ceftriaxone-resistant but ertapenem and meropenem susceptible (EsMs) isolates (3.7 v. 0.9, p &lt; 0.001). ErMs also carried more mobile genetic elements (MGEs), particularly IS26 composite transposons, than EsMs (37 vs. 0.2, p &lt; 0.0001). Immunoblot analysis demonstrated the absence of OmpC expression in NCP-ErMs E. coli, with 92% of strains lacking full contig coverage of ompC. Overall, this work provides evidence of a collaborative effort between blaCTX-M and OmpC in NCP strains that confer resistance to ertapenem but not meropenem. To thwart potential mismanagement of CRE infected patients, future efforts should focus on understanding the mechanism(s) underlying OmpC loss, developing rapid methods to detect blaCTX-M copy number variants, and targeted antimicrobials for NCPE and ErMs strains.

The temporo-spatial theory of consciousness postulates that the brain implements its own inner time and space for conscious processing of outside world. In line with this hypothesis, I present a mechanistic model of mutually connected processes that encode the inner space and time. The model is used to elaborate the binding mechanism between two sets of processes representing the inner space and time, respectively. Further, a stochastic version of the model is developed to investigate the interplay between the binding strength and noise. The spectral entropy is used to characterize the noise effects on the systems of processes when the binding strength is varied. The stochastic modeling results reveal that the spectral entropy values for strongly bound systems have similar entropy values for weakly bound or even decoupled systems. Thus, the analysis performed in this study allows to conclude that the binding mechanism is noise-resilient.

The involvement of the prefrontal cortical dopaminergic system in psychopathology of epilepsies and comorbid conditions such as autism spectrum disorder (ASD) still needs to be explored. We used autoradiography to study the D1-like (D1DR) and D2-like (D2DR) receptor binding density in the prefrontal cortex of normal Wistar rats and Wistar-derived strains with generalized convulsive and/or nonconvulsive epilepsies. WAG/Rij rats served as a model for non-convulsive absence epilepsy, WAG/Rij-AGS as a model of mixed convulsive/non-convulsive forms, and KM strain was a model for convulsive epilepsy comorbiding with ASD-like behavioral phenotype. Prefrontal cortex of rats with any of epileptic pathology studied, demonstrated profound decreases in binding densities to both D1DR, D2DR; the effects were localized in the primary and secondary anterior cingulate cortexi, and adjacent regions. The local decreased D1DR and D2DR binding densities were independent (not correlated) from each other. The particular group of epileptic rats with ASD-like phenotype (KM strain), displayed changes in the lateral prefrontal cortex and adjacent regions: D1DR were lowered, but those to D2DR elevated, in anterior dysgranular insular cortex and adjacent regions. Thus, epilepsy-related changes in the dopaminergic system of rat archeocortex were localized in the medial regions, whereas ASD-related candidates were seen in the lateral aspects. The findings point to putative local dopaminergic dysfunctions, associated with generalized epilepsies and/or ASD.

Various vaccines have been developed in response to the SARS-CoV-2 pandemic, and the safety of vaccines has become an important issue. COVID-19 vaccines-related central nervous system inflammatory demyelinating diseases (CNS IDDs) have been reported recently. We present one case of AstraZeneca vaccine-related myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease and literature review another 78 patients published from January 2020 to October 2022. Patients were divided into three vaccine groups (viral vector, mRNA and inactivated vaccines) for further analyses. Among 79 patients with COVID-19 vaccines-related CNS IDDs, 49 (62%) cases received viral vector vaccines, 20 (25.3%) received mRNA vaccines and 10 (12.7%) received inactivated vaccines. Twenty-seven cases (34.2%) were confirmed with autoantibodies, including 15 patients (19%) with anti-MOG, 11 (13.9%) with anti-aquaporin 4 (AQP4), and one (1.3%) with both antibodies. Significantly, more males developed CNS IDDs post viral vector vaccines compared to mRNA and inactivated vaccines. Patients receiving mRNA vaccines were older than other groups. Furthermore, mRNA and inactivated vaccines correlated more with anti-AQP4 antibodies, while viral vector vaccines showed higher MOG positivity. The research suggests potential associations between COVID-19 vaccines-related CNS IDDs and gender, age, and autoantibodies, contingent on vaccine types. Protein sequence analysis implies similarities between the S protein and AQP4/MOG. Further studies may elucidate the mechanisms of CNS IDDs, aiding vaccine selection for specific groups.

Histamine (HA), a biogenic monoamine, exerts its pleiotropic effects through four H1R–H4R histamine receptors, which are also expressed in brain tissue. Together with the projections of HA-producing neurons located within the tuberomammillary nucleus (TMN), which innervate most areas of the brain, they constitute the histaminergic system. Thus, while remaining a mediator of the inflammatory reaction and immune system function, HA also acts as a neurotransmitter and a modulator of other neurotransmitter systems in the central nervous system (CNS). Although the detailed causes are still not fully understood, neuroinflammation seems to play a crucial role in the etiopathogenesis of both neurodevelopmental and neurodegenerative (neuropsychiatric) diseases, such as autism spectrum disorders (ASD), attention-deficit/hyperactivity disorder (ADHD), Alzheimer's disease (AD) and Parkinson's disease (PD). Given the increasing prevalence/diagnosis of these disorders and their socioeconomic impact, the need to develop effective forms of therapy has focused researchers' attention on the brain's histaminergic activity and other related signaling pathways. This review presents the current state of knowledge concerning the involvement of HA and the histaminergic system within the CNS in the development of neurodevelopmental and neurodegenerative disorders.

Post-COVID-19 bacterial infections are a significant threat to global health, mainly due to the overuse and misuse of antibiotics. The review highlights the importance of using antibiotics judiciously and following appropriate guidelines and recommendations. The article also examines the potential indirect contribution of steroids to antibiotic resistance through immune suppression in severe cases of COVID-19. Anti-microbial resistance (AMR) is one of the leading causes of death worldwide that continues as a silent pandemic caused by the major AMR superbug includes Carbapenem-resistant Acinetobacter baumannii (CRAB), Methicillin-resistant Staphylococcus aureus (MRSA), Carbapenem-resistant Enterobacterales (CRE), Extended-spectrum Beta Lactamase producing Enterobacterales (ESBL) which is resistant to cephalosporin and Multidrug-resistant (MDR) Pseudomonas aeruginosa. Ongoing surveillance and monitoring of antibiotic use and resistance helped to minimize the risk of antibiotic resistance and shrink it from pandemic to endemic.

The tryptophan (TRP)-kynurenine (KYN) metabolic pathway is a main player of TRP metabolism through which more than 95% of TRP is catabolized. The pathway is activated by acute and chronic immune responses leading to a wide range of illnesses including cancer, immune diseases, neurodegenerative diseases, and psychiatric disorders. The TRP-KYN pathway synthesizes multifarious metabolites including oxidants, antioxidants, neurotoxins, neuroprotectants, and immunomodulators. The immunomodulators are known to facilitate the immune system towards a tolerogenic state, resulting in chronic low-grade inflammation (LGI) that is commonly present in obesity, poor nutrition, exposer to chemicals or allergens, prodromal stage of various illnesses, and chronic diseases. KYN, kynurenic acid, xanthurenic acid, and cinnabarinic acid are aryl hydrocarbon receptor ligands that serve as immunomodulators. Furthermore, TRP-KYN pathway enzymes are known to be activated by the stress hormone cortisol and inflammatory cytokines, and genotypic variants were observed to contribute to inflammation and thus various diseases. The tryptophan 2,3-dioxygenase, the indoleamine 2, 3-oxygenases, and the kynurenine-3-monooxygenase are main enzymes in the pathway. This review article discusses the TRP-KYN pathway with special emphasis on its interaction with the immune system and the tolerogenic shift towards chronic LGI and overviews the major symptoms, pro- and anti-inflammatory cytokines, and toxic and protective KYNs to explore the linkage between chronic LGI, KYNs, and major psychiatric, including depressive disorder, bipolar disorder, substance use disorder, post-traumatic stress disorder, schizophrenia, and autism spectrum disorder.

Single particle tracking is a powerful technique to investigate the motion of molecules or particles. Here we review methods for analyzing the reconstructed trajectories, step needed for deciphering the underlying mechanisms driving the motion. First, we review the traditional analysis based on the mean square displacement (MSD), highlighting sometimes-neglected factors potentially affecting results accuracy. We then report methods that exploit distributions of parameters other than displacements, e.g. angles, velocities, and times and probabilities of reaching a target, discussing how they are more sensitive in characterizing heterogeneities and transient behaviors masked in MSD analysis. Hidden Markov Models are also used for this purpose, and these allow identifying different states, their populations and the switching kinetics. Finally, we discuss a rapidly expanding field: trajectory analysis based on machine learning. Various approaches, from random forest to deep learning, are used to classify trajectory motions, which can be identified by motion models or by model-free sets of trajectory features, either previously defined or automatically identified by the algorithms. We also review free software available for some of the analysis methods. We emphasize that approaches based on combined different methods, including classical statistics and machine learning, may be the way to obtain the most informative and accurate results.

Psychiatric disorders are mental, behavioral or emotional disorders. These conditions are prevalent, one in four adults suffer from any type of psychiatric disorders world-wide. It has always been observed that psychiatric disorders have a genetic component, however new methods to sequence full genomes of large cohorts have identified with high precision genetic risk loci for these conditions. Psychiatric disorders include, but are not limited to, bipolar disorder, schizophrenia, autism spectrum disorder, anxiety disorders, major depressive disorder, and attention-deficit and hyperactivity disorder. Several risk loci for psychiatric disorders fall within genes that encode for voltage-gated calcium channels (Ca_Vs). Calcium entering through Ca_Vs is key for multiple neuronal processes. In this review, we will summarize recent findings that link Ca_Vs and their auxiliary subunits to psychiatric disorders. First, we will provide a general overview of Ca_Vs structure, classification, function, expression and pharmacology. Next, we will summarize tools and databases to study risk loci associated with psychiatric disorders. We will examine functional studies of risk variations in Ca_V genes when available. We will review pharmacological evidence of the use of Ca_V modulators to treat psychiatric disorders. Our review will be of interest for those studying pathophysiological aspects of Ca_Vs.

X-band marine radar captures signal reflected from the sea surface. Theoretical studies indicate that the initial unfiltered signal contains meaningful information including parameters related to wind waves. Traditional methods for estimating significant wave height (SWH) rely on the physical laws describing signal reflection from rough surfaces. However, recent studies suggest the feasibility of employing artificial neural networks (ANNs) for SWH approximation. Both classical and ANN-based approaches necessitate costly in situ data. In this study, we propose generating synthetic radar images with specified wind wave parameters using Fourier-based approach and Pierson–Moskowitz wave spectrum as a viable alternative. We generate synthetic images and use them for unsupervised learning approach to train a convolutional component of an ANN. After that, we train a regression ANN based on the previous convolutional component to obtain SWH back from synthetic images. Then, we apply preliminary trained weights for the same regression model to train SWH approximation on the dataset of real sea clutter images. In this study, we demonstrate the increase in the accuracy of SWH estimation from radar images with the preliminary training on synthetic data.

N-methyl-D-aspartate receptors (NMDARs) are critical components of the mammalian central nervous system, involved in synaptic transmission, plasticity, and neurodevelopment. This review focuses on the structural and functional characteristics of NMDARs, with a particular emphasis on the GRIN2 subunits (GluN2A-D). The diversity of GRIN2 subunits, driven by alternative splicing and genetic variants, significantly impacts receptor function, synaptic localization, and disease manifestation. We explore the physiological properties and developmental regulation of these subunits, highlighting their roles in the pathophysiology of various NDDs, including ASD, epilepsy, and schizophrenia. By reviewing current knowledge and experimental models, including mouse models and human-induced pluripotent stem cells (hiPSCs), this article aims to elucidate different approaches through which the intricacies of NMDAR dysfunction in NDDs are currently being explored. The comprehensive understanding of NMDAR subunit composition and their mutations provides a foundation for developing targeted therapeutic strategies to address these complex disorders.

The Hyper-Torus Universe Model (HTUM) proposes a novel framework to unify quantum mechanics, cosmology, and consciousness. This paper introduces HTUM's core concept: a higher-dimensional hyper-torus encompassing all possible states of existence. HTUM suggests that the universe functions as a quantum system where all outcomes are inherently connected, with consciousness playing a significant role in actualizing reality. The model introduces several key innovations, including the universe's 4-dimensional toroidal structure (4DTS), providing a new geometric interpretation of spacetime. HTUM presents dark matter and dark energy as nonlinear probabilistic phenomena within this toroidal framework, offering a unique perspective on their nature and interactions. The model proposes a mechanism for wave function collapse through universal self-observation, bridging quantum mechanics and gravity. It introduces a Topological Vacuum Energy Modulator (TVEM) function, offering a potential resolution to the cosmological constant problem. Furthermore, HTUM integrates consciousness as a fundamental aspect of the universe, influencing quantum state actualization and potentially resolving the hard problem of consciousness. The model explores the implications of a timeless singularity and the emergence of time as a product of causal relationships within the toroidal structure. This framework addresses critical challenges in modern physics, including the nature of quantum entanglement, the origin and fate of the universe, and the relationship between mind and matter. The paper discusses the mathematical formulation of HTUM, its implications for quantum mechanics and cosmology, and its potential to bridge the gap between science and philosophy. We present detailed predictions for the cosmic microwave background (CMB) power spectrum, gravitational wave signatures, and large-scale structure formation, demonstrating how HTUM differs from the standard ΛCDM model. Our analysis reveals distinctive oscillatory patterns in the relative difference between HTUM and ΛCDM predictions, with deviations reaching up to ±20% at certain scales. The paper also explores the unification of fundamental forces within the HTUM framework, proposing novel approaches to particle physics and quantum field theory. It introduces the concept of unified mathematical operations, suggesting a more holistic approach to mathematical thinking that aligns with the model's interconnected view of the universe. Additional testable predictions and proposed experimental approaches are discussed, including advanced space-based tests and laboratory experiments probing quantum gravity effects. These specific, quantifiable predictions offer multiple avenues for empirical validation, highlighting HTUM's potential to be distinguished from ΛCDM and other alternative cosmological models. HTUM represents a significant new perspective in our understanding of the universe, inviting further research and exploration into the nature of reality, consciousness, and the fundamental structure of the cosmos. By providing a comprehensive framework that unifies various aspects of physics, cosmology, and consciousness studies, HTUM offers a promising path toward a more complete understanding of our universe.

Neurodegeneration is a major problem in neuroscience and medicine as it causes and worsens many neurological and psychiatric disorders. It involves gradual loss of neurons at different levels of the brain, affecting cognition, emotion, behavior, consciousness, and attention. Understanding the causes and consequences of neurodegeneration is crucial for identifying the risk factors, biomarkers, and treatments. However, the current therapies are mostly symptomatic and ineffective. Therefore, new and innovative methods, such as noninvasive brain stimulation (NIBS), are needed to modulate brain activity and plasticity in a safe and reversible manner. This field is rapidly developing, with a focus on exploring new clinical applications, mechanisms, and combinations of NIBS and drugs. This special issue covers the latest progress and challenges in the study of neurodegeneration in cognitive impairment and mood disorders from the experimental, clinical, and translational perspectives. It addresses the complexity and diversity of these conditions, the lack of disease-modifying treatments, the ethical and practical issues of conducting research in vulnerable and diverse populations, the integration and interpretation of data from multiple sources and modalities, and the development and validation of novel methods such as NIBS, artificial intelligence, and drug repurposing. Collaborative efforts among various stakeholders are needed to improve our knowledge and treatment of neurodegeneration underlying cognitive impairment and mood disorders.