bluuebunny/crossref_metadata_2025 huggingface dataset:
DNA damage signalling histone H2AX is required for tumour growth
Authors: Contreras Lizbeth , García-Gaipo Lorena , Casar Berta , Gandarillas Alberto
Published: February 2024

Cancer most frequently develops in self-renewal tissues that are the target of genetic alterations due to mutagens or intrinsic DNA replication errors. Histone γH2AX has a critical role in the cellular DNA repair pathway cascade and contributes to genomic stability. However, the role of γH2AX in the ontology of cancer is unclear. We have investigated this issue in the epidermis, a self-renewal epithelium continuously exposed to genetic hazard and replication stress. Silencing H2AX caused cell cycle hyperactivation, impaired DNA repair and epidermal hyperplasia in the skin. However, mutagen-induced carcinogenesis was strikingly reduced in the absence of H2AX. KO tumours appeared significantly later than controls and were fewer, smaller and more benign. The stem cell marker Δp63 drastically diminished in the KO epidermis. We conclude that H2AX is required for tissue-making during both homoeostasis and tumourigenesis, possibly by contributing to the control and repair of stem cells. Therefore, although H2AX is thought to act as a tumour suppressor and our results show that it contributes to homeostasis, they also indicate that it is required for the development of cancer.
Intestinal microbiota composition of children with glycogen storage Type I patients
Authors: Gokalp Sabire , Dinleyici Ener Cagri , Muluk Cansu , Inci Asli , Aktas Emine , Okur Ilyas , Ezgu Fatih , Tumer Leyla
Published: February 2024

Aim

Dietary therapy of glycogen storage disease I (GSD I) is based on frequent feeding, with a high intake of complex carbohydrates (supplied by uncooked cornstarch), restriction of sugars, and a lower amount of lipids. There is limited information about the dietary regimen in patients with GSD, which might affect the intestinal luminal pH and microbiota composition. The aim of this study to investigate the intestinal microbiota composition in patients with GSD receiving diet treatment.

Method

Twelve patients who were followed up with GSD I after the diagnosis receiving diet therapy and 11 healthy children have been enrolled. Intestinal microbiota composition was evaluated by 16 s rRNA gene sequencing.

Results

A significant difference was found for beta-diversity between the GSD group and controls. A significantly lower abundance of Firmicutes and higher abundance of Actinobacteria was found in GSD group compared to the controls. Akkermansia, Pseudoalteromonas, Uruburella, and Castellaniella were dominant in the GSD patients at the genus level, while Faecalibacterium, Bacterioides, Gemmiger, Parabacteroides in the control group. At species level, Faecalibacterium prausnitzii decreased, and Akkermansia muciniphila were dominant in children with GSD.

Discussion

There is a substantial change in the composition of the gut microbiota, reduction of F. prausnitzii and an increase of A. muciniphila in children with GSD receiving consumption of uncooked cornstarch. Alterations of the intestinal microbiota might be related with the disease itself or dietary restrictions in patients with GSD, however, in certain condition, dysbiosis can negatively affect the course and make it difficult to control the disease.
Creation of a point-of-care therapeutics sensor using protein engineering, electrochemical sensing and electronic integration
Authors: Cai Rong , Ngwadom Chiagoziem , Saxena Ravindra , Soman Jayashree , Bruggeman Chase , Hickey David P. , Verduzco Rafael , Ajo-Franklin Caroline M.
Published: February 2024

Point-of-care sensors, which are low-cost and user-friendly, play a crucial role in precision medicine by providing quick results for individuals. Here, we transform the conventional glucometer into a 4-hydroxytamoxifen therapeutic biosensor in which 4-hydroxytamoxifen modulates the electrical signal generated by glucose oxidation. To encode the 4-hydroxytamoxifen signal within glucose oxidation, we introduce the ligand-binding domain of estrogen receptor-alpha into pyrroloquinoline quinone-dependent glucose dehydrogenase by constructing and screening a comprehensive protein insertion library. In addition to obtaining 4-hydroxytamoxifen regulatable engineered proteins, these results unveil the significance of both secondary and quaternary protein structures in propagation of conformational signals. By constructing an effective bioelectrochemical interface, we detect 4-hydroxytamoxifen in human blood samples as changes in the electrical signal and use this to develop an electrochemical algorithm to decode the 4-hydroxytamoxifen signal from glucose. To meet the miniaturization and signal amplification requirements for point-of-care use, we harness power from glucose oxidation to create a self-powered sensor. We also amplify the 4-hydroxytamoxifen signal using an organic electrochemical transistor, resulting in milliampere-level signals. Our work demonstrates a broad interdisciplinary approach to create a biosensor that capitalizes on recent innovations in protein engineering, electrochemical sensing, and electrical engineering.
Observation of geometric phase effect through backward angular oscillations in the H + HD → H2 + D reaction
Authors: Li Shihao , Huang Jiayu , Lu Zhibing , Shu Yiyang , Chen Wentao , Yuan Daofu , Wang Tao , Fu Bina , Zhang Zhaojun , Wang Xingan , Zhang Dong H. , Yang Xueming
Published: February 2024

Quantum interference between reaction pathways around a conical intersection (CI) is an ultrasensitive probe of detailed chemical reaction dynamics. Yet, for the hydrogen exchange reaction, the difference between contributions of the two reaction pathways increases substantially as the energy decreases, making the experimental observation of interference features at low energy exceedingly challenging. We report in this paper a combined experimental and theoretical study on the H + HD → H2 + D reaction at the collision energy of 1.72 eV. Although the roaming insertion pathway constitutes only a small fraction (0.088%) of the overall contribution, angular oscillatory patterns arising from the interference of reaction pathways were clearly observed in the backward scattering direction, providing direct evidence of the geometric phase effect at an energy of 0.81 eV below the CI. Furthermore, theoretical analysis reveals that the backward interference patterns are mainly contributed by two distinct groups of partial waves (J ~ 10 and J ~ 19). The well-separated partial waves and the geometric phase collectively influence the quantum reaction dynamics.
Midbrain signaling of identity prediction errors depends on orbitofrontal cortex networks
Authors: Liu Qingfang , Zhao Yao , Attanti Sumedha , Voss Joel L. , Schoenbaum Geoffrey , Kahnt Thorsten
Published: February 2024

Outcome-guided behavior requires knowledge about the identity of future rewards. Previous work across species has shown that the dopaminergic midbrain responds to violations in expected reward identity and that the lateral orbitofrontal cortex (OFC) represents reward identity expectations. Here we used network-targeted transcranial magnetic stimulation (TMS) and functional magnetic resonance imaging (fMRI) during a trans-reinforcer reversal learning task to test the hypothesis that outcome expectations in the lateral OFC contribute to the computation of identity prediction errors (iPE) in the midbrain. Network-targeted TMS aiming at lateral OFC reduced the global connectedness of the lateral OFC and impaired reward identity learning in the first block of trials. Critically, TMS disrupted neural representations of expected reward identity in the OFC and modulated iPE responses in the midbrain. These results support the idea that iPE signals in the dopaminergic midbrain are computed based on outcome expectations represented in the lateral OFC.
Induced neural phase precession through exogenous electric fields
Authors: Wischnewski Miles , Tran Harry , Zhao Zhihe , Shirinpour Sina , Haigh Zachary J. , Rotteveel Jonna , Perera Nipun D. , Alekseichuk Ivan , Zimmermann Jan , Opitz Alexander
Published: February 2024

The gradual shifting of preferred neural spiking relative to local field potentials (LFPs), known as phase precession, plays a prominent role in neural coding. Correlations between the phase precession and behavior have been observed throughout various brain regions. As such, phase precession is suggested to be a global neural mechanism that promotes local neuroplasticity. However, causal evidence and neuroplastic mechanisms of phase precession are lacking so far. Here we show a causal link between LFP dynamics and phase precession. In three experiments, we modulated LFPs in humans, a non-human primate, and computational models using alternating current stimulation. We show that continuous stimulation of motor cortex oscillations in humans lead to a gradual phase shift of maximal corticospinal excitability by ~90°. Further, exogenous alternating current stimulation induced phase precession in a subset of entrained neurons (~30%) in the non-human primate. Multiscale modeling of realistic neural circuits suggests that alternating current stimulation-induced phase precession is driven by NMDA-mediated synaptic plasticity. Altogether, the three experiments provide mechanistic and causal evidence for phase precession as a global neocortical process. Alternating current-induced phase precession and consequently synaptic plasticity is crucial for the development of novel therapeutic neuromodulation methods.
Pore evolution mechanisms during directed energy deposition additive manufacturing
Authors: Zhang Kai , Chen Yunhui , Marussi Sebastian , Fan Xianqiang , Fitzpatrick Maureen , Bhagavath Shishira , Majkut Marta , Lukic Bratislav , Jakata Kudakwashe , Rack Alexander , Jones Martyn A. , Shinjo Junji , Panwisawas Chinnapat , Leung Chu Lun Alex , Lee Peter D.
Published: February 2024

Porosity in directed energy deposition (DED) deteriorates mechanical performances of components, limiting safety-critical applications. However, how pores arise and evolve in DED remains unclear. Here, we reveal pore evolution mechanisms during DED using in situ X-ray imaging and multi-physics modelling. We quantify five mechanisms contributing to pore formation, migration, pushing, growth, removal and entrapment: (i) bubbles from gas atomised powder enter the melt pool, and then migrate circularly or laterally; (ii) small bubbles can escape from the pool surface, or coalesce into larger bubbles, or be entrapped by solidification fronts; (iii) larger coalesced bubbles can remain in the pool for long periods, pushed by the solid/liquid interface; (iv) Marangoni surface shear flow overcomes buoyancy, keeping larger bubbles from popping out; and (v) once large bubbles reach critical sizes they escape from the pool surface or are trapped in DED tracks. These mechanisms can guide the development of pore minimisation strategies.
Vestigial singlet pairing in a fluctuating magnetic triplet superconductor and its implications for graphene superlattices
Authors: Poduval Prathyush P. , Scheurer Mathias S.
Published: February 2024

Stacking and twisting graphene layers allows to create and control a two-dimensional electron liquid with strong correlations. Experiments indicate that these systems exhibit strong tendencies towards both magnetism and triplet superconductivity. Motivated by this phenomenology, we study a 2D model of fluctuating triplet pairing and spin magnetism. Individually, their respective order parameters, d and N, cannot order at finite temperature. Nonetheless, the model exhibits a variety of vestigial phases, including charge-4e superconductivity and broken time-reversal symmetry. Our main focus is on a phase characterized by finite d ⋅ N, which has the same symmetries as the BCS state, a Meissner effect, and metastable supercurrents, yet rather different spectral properties: most notably, the suppression of the electronic density of states at the Fermi level can resemble that of either a fully gapped or nodal superconductor, depending on parameters. This provides a possible explanation for recent tunneling experiments in the superconducting phase of graphene moiré systems.
Coverage enhancement accelerates acidic CO2 electrolysis at ampere-level current with high energy and carbon efficiencies
Authors: Yu Xiaohan , Xu Yuting , Li Le , Zhang Mingzhe , Qin Wenhao , Che Fanglin , Zhong Miao
Published: February 2024

Acidic CO2 electroreduction (CO2R) using renewable electricity holds promise for high-efficiency generation of storable liquid chemicals with up to 100% CO2 utilization. However, the strong parasitic hydrogen evolution reaction (HER) limits its selectivity and energy efficiency (EE), especially at ampere-level current densities. Here we present that enhancing CO2R intermediate coverage on catalysts promotes CO2R and concurrently suppresses HER. We identified and engineered robust Cu6Sn5 catalysts with strong *OCHO affinity and weak *H binding, achieving 91% Faradaic efficiency (FE) for formic acid (FA) production at 1.2 A cm−2 and pH 1. Notably, the single-pass carbon efficiency reaches a new benchmark of 77.4% at 0.5 A cm−2 over 300 hours. In situ electrochemical Fourier-transform infrared spectroscopy revealed Cu6Sn5 enhances *OCHO coverage ~2.8× compared to Sn at pH 1. Using a cation-free, solid-state-electrolyte-based membrane-electrode-assembly, we produce 0.36 M pure FA at 88% FE over 130 hours with a marked full-cell EE of 37%.
Toward stabilization of formamidinium lead iodide perovskites by defect control and composition engineering
Authors: Liang Yuhang , Li Feng , Cui Xiangyuan , Lv Taoyuze , Stampfl Catherine , Ringer Simon P. , Yang Xudong , Huang Jun , Zheng Rongkun
Published: February 2024

Phase instability poses a serious challenge to the commercialization of formamidinium lead iodide (FAPbI3)-based solar cells and optoelectronic devices. Here, we combine density functional theory and machine learning molecular dynamics simulations, to investigate the mechanism driving the undesired α-δ phase transition of FAPbI3. Prevalent iodine vacancies and interstitials can significantly expedite the structural transition kinetics by inducing robust covalency during transition states. Extrinsically, the detrimental roles of atmospheric moisture and oxygen in degrading the FAPbI3 perovskite phase are also rationalized. Significantly, we discover the compositional design principles by categorizing that A-site engineering primarily governs thermodynamics, whereas B-site doping can effectively manipulate the kinetics of the phase transition in FAPbI3, highlighting lanthanide ions as promising B-site substitutes. A-B mixed doping emerges as an efficient strategy to synergistically stabilize α-FAPbI3, as experimentally demonstrated by substantially higher initial optoelectronic characteristics and significantly enhanced phase stability in Cs-Eu doped FAPbI3 as compared to its Cs-doped counterpart. This study provides scientific guidance for the design and optimization of long-term stable FAPbI3-based solar cells and other optoelectronic devices through defect control and synergetic composition engineering.
Rapid deep learning-assisted predictive diagnostics for point-of-care testing
Authors: Lee Seungmin , Park Jeong Soo , Woo Hyowon , Yoo Yong Kyoung , Lee Dongho , Chung Seok , Yoon Dae Sung , Lee Ki- Baek , Lee Jeong Hoon
Published: February 2024

Prominent techniques such as real-time polymerase chain reaction (RT-PCR), enzyme-linked immunosorbent assay (ELISA), and rapid kits are currently being explored to both enhance sensitivity and reduce assay time for diagnostic tests. Existing commercial molecular methods typically take several hours, while immunoassays can range from several hours to tens of minutes. Rapid diagnostics are crucial in Point-of-Care Testing (POCT). We propose an approach that integrates a time-series deep learning architecture and AI-based verification, for the enhanced result analysis of lateral flow assays. This approach is applicable to both infectious diseases and non-infectious biomarkers. In blind tests using clinical samples, our method achieved diagnostic times as short as 2 minutes, exceeding the accuracy of human analysis at 15 minutes. Furthermore, our technique significantly reduces assay time to just 1-2 minutes in the POCT setting. This advancement has the potential to greatly enhance POCT diagnostics, enabling both healthcare professionals and non-experts to make rapid, accurate decisions.
NAAA-regulated lipid signaling in monocytes controls the induction of hyperalgesic priming in mice
Authors: Fotio Yannick , Mabou Tagne Alex , Squire Erica , Lee Hye-lim , Phillips Connor M. , Chang Kayla , Ahmed Faizy , Greenberg Andrew S. , Villalta S. Armando , Scarfone Vanessa M. , Spadoni Gilberto , Mor Marco , Piomelli Daniele
Published: February 2024

Circulating monocytes participate in pain chronification but the molecular events that cause their deployment are unclear. Using a mouse model of hyperalgesic priming (HP), we show that monocytes enable progression to pain chronicity through a mechanism that requires transient activation of the hydrolase, N-acylethanolamine acid amidase (NAAA), and the consequent suppression of NAAA-regulated lipid signaling at peroxisome proliferator-activated receptor-α (PPAR-α). Inhibiting NAAA in the 72 hours following administration of a priming stimulus prevented HP. This effect was phenocopied by NAAA deletion and depended on PPAR-α recruitment. Mice lacking NAAA in CD11b+ cells – monocytes, macrophages, and neutrophils – were resistant to HP induction. Conversely, mice overexpressing NAAA or lacking PPAR-α in the same cells were constitutively primed. Depletion of monocytes, but not resident macrophages, generated mice that were refractory to HP. The results identify NAAA-regulated signaling in monocytes as a control node in the induction of HP and, potentially, the transition to pain chronicity.
How probiotics, prebiotics, synbiotics, and postbiotics prevent dental caries: an oral microbiota perspective
Authors: Luo Si-Chen , Wei Si-Min , Luo Xin-Tao , Yang Qiong-Qiong , Wong Ka-Hing , Cheung Peter C. K. , Zhang Bo-Bo
Published: February 2024

Dental caries, a highly prevalent oral disease, impacts a significant portion of the global population. Conventional approaches that indiscriminately eradicate microbes disrupt the natural equilibrium of the oral microbiota. In contrast, biointervention strategies aim to restore this balance by introducing beneficial microorganisms or inhibiting cariogenic ones. Over the past three decades, microbial preparations have garnered considerable attention in dental research for the prevention and treatment of dental caries. However, unlike related pathologies in the gastrointestinal, vaginal, and respiratory tracts, dental caries occurs on hard tissues such as tooth enamel and is closely associated with localized acid overproduction facilitated by cariogenic biofilms. Therefore, it is insufficient to rely solely on previous mechanisms to delineate the role of microbial preparations in the oral cavity. A more comprehensive perspective should involve considering the concepts of cariogenic biofilms. This review elucidates the latest research progress, mechanisms of action, challenges, and future research directions regarding probiotics, prebiotics, synbiotics, and postbiotics for the prevention and treatment of dental caries, taking into account the unique pathogenic mechanisms of dental caries. With an enhanced understanding of oral microbiota, personalized microbial therapy will emerge as a critical future research trend.
Synaptic loss and its association with symptom severity in Parkinson’s disease
Authors: Holmes Sophie E. , Honhar Praveen , Tinaz Sule , Naganawa Mika , Hilmer Ansel T. , Gallezot Jean-Dominique , Dias Mark , Yang Yanghong , Toyonaga Takuya , Esterlis Irina , Mecca Adam , Van Dyck Christopher , Henry Shannan , Ropchan Jim , Nabulsi Nabeel , Louis Elan D. , Comley Robert , Finnema Sjoerd J. , Carson Richard E. , Matuskey David
Published: February 2024

Parkinson’s disease (PD) is the fastest growing neurodegenerative disease, but at present there is no cure, nor any disease-modifying treatments. Synaptic biomarkers from in vivo imaging have shown promise in imaging loss of synapses in PD and other neurodegenerative disorders. Here, we provide new clinical insights from a cross-sectional, high-resolution positron emission tomography (PET) study of 30 PD individuals and 30 age- and sex-matched healthy controls (HC) with the radiotracer [11C]UCB-J, which binds to synaptic vesicle glycoprotein 2A (SV2A), and is therefore, a biomarker of synaptic density in the living brain. We also examined a measure of relative brain perfusion from the early part of the same PET scan. Our results provide evidence for synaptic density loss in the substantia nigra that had been previously reported, but also extend this to other early-Braak stage regions known to be affected in PD (brainstem, caudate, olfactory cortex). Importantly, we also found a direct association between synaptic density loss in the nigra and severity of symptoms in patients. A greater extent and wider distribution of synaptic density loss in PD patients with longer illness duration suggests that [11C]UCB-J PET can be used to measure synapse loss with disease progression. We also demonstrate lower brain perfusion in PD vs. HC groups, with a greater extent of abnormalities in those with longer duration of illness, suggesting that [11C]UCB-J PET can simultaneously provide information on changes in brain perfusion. These results implicate synaptic imaging as a useful PD biomarker for future disease-modifying interventions.
A history of avoidance does not impact extinction learning in male rats
Authors: López-Moraga Alba , Luyten Laura , Beckers Tom
Published: February 2024

Pervasive avoidance is one of the central symptoms of all anxiety-related disorders. In treatment, avoidance behaviors are typically discouraged because they are assumed to maintain anxiety. Yet, it is not clear if engaging in avoidance is always detrimental. In this study, we used a platform-mediated avoidance task to investigate the influence of avoidance history on extinction learning in male rats. Our results show that having the opportunity to avoid during fear acquisition training does not significantly influence the extinction of auditory-cued fear in rats subjected to this platform-mediated avoidance procedure, which constitutes a realistic approach/avoidance conflict. This holds true irrespective of whether or not avoidance was possible during the extinction phase. This suggests that imposing a realistic cost on avoidance behavior prevents the adverse effects that avoidance has been claimed to have on extinction. However, avoidance does not appear to have clear positive effects on extinction learning nor on retention either.
Remote Sensing-Based Extension of GRDC Discharge Time Series - A Monthly Product with Uncertainty Estimates
Authors: Elmi Omid , Tourian Mohammad J. , Saemian Peyman , Sneeuw Nico
Published: February 2024

The Global Runoff Data Center (GRDC) data set has faced a decline in the number of active gauges since the 1980s, leaving only 14% of gauges active as of 2020. We develop the Remote Sensing-based Extension for the GRDC (RSEG) data set that can ingest legacy gauge discharge and remote sensing observations. We employ a stochastic nonparametric mapping algorithm to extend the monthly discharge time series for inactive GRDC stations, benefiting from satellite imagery- and altimetry-derived river width and water height observations. After a rigorous quality assessment of our estimated discharge, involving statistical validation, tests and visual inspection, results in the extension of discharge records for 3377 out of 6015 GRDC stations. The quality of discharge estimates for the rivers with a large or medium mean discharge is quite satisfactory (average KGE value > 0.5) however for river reaches with a low mean discharge the average KGE value drops to 0.33.The RSEG data set regains monitoring capability for 83% of total river discharge measured by GRDC stations, equivalent to 7895 km3/month.
Ocular microvascular alteration in patients with myocardial infarction—a new OCTA study
Authors: Wu Jun-Yi , Hu Jin-Yu , Ge Qian-Min , Xu San-Hua , Zou Jie , Kang Min , Ying Ping , Wei Hong , Ling Qian , He Liang-Qi , Chen Cheng , Shao Yi
Published: February 2024

Myocardial infarction is defined as a sudden decrease or interruption in blood flow to the coronary arteries, causing ischemic necrosis of the corresponding cardiomyocytes. It is unclear whether systemic macrovascular alterations are associated with retinal microvascular changes. This study utilized optical coherence tomography angiography (OCTA) to compare variations in conjunctival vascular density and fundus retinal vessel density between patients with myocardial infarction (MI) and healthy controls. This study recruited 16 patients (32 eyes) with MI and 16 healthy controls (32 eyes). The superficial retinal layer (SRL), deep retinal layer (DRL) and conjunctival capillary plexus in each eye were evaluated by OCTA. Parameters measured included the density of the temporal conjunctival capillary, retinal microvascular (MIR) and macrovascular (MAR) alterations and total MIR (TMI). The microvascular density of each retinal region was evaluated by the hemisphere segmentation (SR, SL, IL, and IR), annular partition (C1, C2, C3, C4, C5 and C6), and modified early treatment of diabetic retinopathy study (R, S, L, and I) methods. In the macular area, the superficial and deep retinal microvascular densities displayed notable variations. In the superficial layers, the superficial TMI, superficial MIR, and superficial MAR, as well as densities in the SL, IL, S, L, C1, C2, C5 and C6 regions, were significantly lower in MI patients (p < 0.05 each). In the deep layers, the deep MIR and deep TMI), as well as densities in the SL, IL, L, C1, C2 and C6 regions were significantly lower in MI patients (p < 0.05 each). In contrast, the conjunctival microvascular density was significantly higher in MI patients than in healthy controls (p < 0.001). The microvascular densities measured in the deep and superficial retinal layers and in the conjunctiva differ in MI patients and healthy controls. OCTA is effective in detecting changes in the ocular microcirculation.
In vivo imaging of cathepsin B in activated glia in the brain after orofacial formalin test
Authors: McIlwrath Sabrina L. , Carroll-Portillo Amanda C. , Lin Henry C. , Westlund Karin N.
Published: February 2024

PURPOSE Cathepsin B (Cat B) is a cysteine lysosomal protease that is upregulated in many inflammatory diseases and widely expressed in the brain. Here, we used a Cat B activatable near-infrared (NIR) imaging probe to measure glial activation in vivo in the formalin test, a standard orofacial inflammatory pain model. The probe’s efficacy was quantified with immunohistochemical analysis of the somatosensory cortex. PROCEDURES Three different concentrations of Cat B imaging probe (30, 50, 100 pmol/200 g bodyweight) were injected intracisternally into the foramen magnum of rats under anesthesia. Four hours later formalin (1.5%, 50 μl) was injected into the upper lip and the animal’s behaviors recorded for 45 min. Subsequently, animals were repeatedly scanned using the IVIS Spectrum (8, 10, and 28 h post imaging probe injection) to measure extracellular Cat B activity. Aldehyde fixed brain sections were immunostained with antibodies against microglial marker Iba1 or astrocytic GFAP and detected with fluorescently labeled secondary antibodies to quantify co-localization with the fluorescent probe. RESULTS The Cat B imaging probe only slightly altered the formalin test results. Nocifensive behavior was only reduced in phase 1 in the 100 pmol group. In vivo measured fluorescence efficiency was highest in the 100 pmol group 28 h post imaging probe injection. Post-mortem immunohistochemical analysis of the somatosensory cortex detected the greatest amount of NIR fluorescence localized on microglia and astrocytes in the 100 pmol imaging probe group. Sensory neuron neuropeptide and cell injury marker expression in ipsilateral trigeminal ganglia was not altered by the presence of fluorescent probe. CONCLUSIONS These data demonstrate a concentration- and time-dependent visualization of extracellular Cat B in activated glia in the formalin test using a NIR imaging probe. Intracisternal injections are well suited for extracellular CNS proteinase detection in conditions when the blood–brain barrier is intact.
Alcohol consumption as a socially contagious phenomenon in the Framingham Heart Study social network
Authors: van den Ende Maarten W. J. , van der Maas Han L. J. , Epskamp Sacha , Lees Mike H.
Published: February 2024

We use longitudinal social network data from the Framingham Heart Study to examine the extent to which alcohol consumption is influenced by the network structure. We assess the spread of alcohol use in a three-state SIS-type model, classifying individuals as abstainers, moderate drinkers, and heavy drinkers. We find that the use of three-states improves on the more canonical two-state classification, as the data show that all three states are highly stable and have different social dynamics. We show that when modelling the spread of alcohol use, it is important to model the topology of social interactions by incorporating the network structure. The population is not homogeneously mixed, and clustering is high with abstainers and heavy drinkers. We find that both abstainers and heavy drinkers have a strong influence on their social environment; for every heavy drinker and abstainer connection, the probability of a moderate drinker adopting their drinking behaviour increases by $$40\%$$

40
%

and $$18\%$$

18
%

, respectively. We also find that abstinent connections have a significant positive effect on heavy drinkers quitting drinking. Using simulations, we find that while both are effective, increasing the influence of abstainers appears to be the more effective intervention compared to reducing the influence of heavy drinkers.
Development of a CD8+ T cell associated signature for predicting the prognosis and immunological characteristics of gastric cancer by integrating single-cell and bulk RNA-sequencing
Authors: Li Jianxin , Han Ting , Wang Xin , Wang Yinchun , Yang Rui , Yang Qingqiang
Published: February 2024

The universally poor clinical outcome makes gastric cancer (GC) still a significant public health threat, the main goal of our research is to develop a prognostic signature that can forecast the outcomes and immunological characteristics of GC via integrating single-cell and bulk RNA-sequencing. The CD8+ T cell feature genes were screened out by exploring single-cell RNA-sequencing (scRNA-seq) profiles retrieved from the TISCH2 database. Then, Cox and LASSO regressions were exploited for constructing a prognostic model in TCGA cohort based on these CD8+ T cell feature genes. Survival analysis was conducted to investigate the predictive capability of the signature for the clinical outcome of GC patients in TCGA and GEO cohorts. Additionally, we further examined the correlations between the risk signature and tumor immunotherapeutic response from the perspectives of immune infiltration, tumor mutation burden (TMB), immune checkpoint biomarker (ICB) expression, tumor microenvironment (TME), microsatellite instability (MSI), TIDE, and TCIA scores. In total, 703 CD8+ T cell feature genes were identified, eight of which were selected for constructing a prognostic signature. GC patients who possess high-risk score had significantly poorer survival outcomes than those who possess low-risk score in TCGA and GEO cohorts. Immune infiltration analysis proved that the risk score was negatively connected with the infiltration abundance of CD8+ T cells. Then, our findings demonstrated that GC patients in the high-risk subgroup possess a higher proportion of MSI-L/MSS, lower immune checkpoint biomarker expression, lower TMB, higher TIDE scores and lower TCIA scores compared to those in the low-risk subgroup. What’s more, immunotherapy cohort analysis confirmed that patients who possess high-risk score are not sensitive to anti-cancer immunotherapy. Our study developed a reliable prognostic signature for GC that was significantly correlated with the immune landscape and immunotherapeutic responsiveness. The risk signature may guide clinicians to adopt more accurate and personalized treatment strategies for GC patients.
Hippocampal volume changes after (R,S)-ketamine administration in patients with major depressive disorder and healthy volunteers
Authors: Evans Jennifer W. , Graves Morgan C. , Nugent Allison C. , Zarate Carlos A.
Published: February 2024

The hippocampus and amygdala have been implicated in the pathophysiology and treatment of major depressive disorder (MDD). Preclinical models suggest that stress-related changes in these regions can be reversed by antidepressants, including ketamine. Clinical studies have identified reduced volumes in MDD that are thought to be potentiated by early life stress and worsened by repeated depressive episodes. This study used 3T and 7T structural magnetic resonance imaging data to examine longitudinal changes in hippocampal and amygdalar subfield volumes associated with ketamine treatment. Data were drawn from a previous double-blind, placebo-controlled, crossover trial of healthy volunteers (HVs) unmedicated individuals with treatment-resistant depression (TRD) (3T: 18 HV, 26 TRD, 7T: 17 HV, 30 TRD) who were scanned at baseline and twice following either a 40 min IV ketamine (0.5 mg/kg) or saline infusion (acute: 1–2 days, interim: 9–10 days post infusion). No baseline differences were noted between the two groups. At 10 days post-infusion, a slight increase was observed between ketamine and placebo scans in whole left amygdalar volume in individuals with TRD. No other differences were found between individuals with TRD and HVs at either field strength. These findings shed light on the timing of ketamine’s effects on cortical structures.
Spectrofluorimetric determination of butylated hydroxytoluene and butylated hydroxyanisole in their combined formulation: application to butylated hydroxyanisole residual analysis in milk and butter
Authors: Galal Sara Abdel Basset , Elzanfaly Eman Saad , Hussien Emad Mohamed , Amer Enas Abdel Hakim , Zaazaa Hala Elsayed
Published: February 2024

Butylated hydroxytoluene (BHT) and butylated hydroxyanisole (BHA) are two antioxidants that have been extensively used in many applications. Both are well known for their debatable health risks due to their multiple intake sources. Therefore, conservative limits are set for them in different regulations adapted to the matrices in which they exist. Here we present a simple spectrofluorimetric method for the determination of BHT and BHA based on their native fluorescence and synchronous scanning mode. The type of solvent and the interval between emission and excitation wavelengths were carefully optimized. Under the optimized conditions, good linearities were obtained between the emission intensity and the corresponding concentrations of BHT and BHA over the range of 3–18 µg/mL and 0.1–7 µg/mL, respectively with a good correlation coefficient (r > 0.99). The limits of detection were 0.9 and 0.02 µg/mL, and the quantification limits were 3 and 0.05 µg/mL for BHT and BHA, respectively. The suggested procedure was validated according to ICH guidelines Q2 (R1). Furthermore, the method’s greenness was assessed by three different methods, and it proved to be eco-reasonable. The method was successfully applied to the determination of BHT and BHA in pharmaceutical formulations. We also applied the suggested method for monitoring the residual BHA in conventional, powdered milk and butter, with good recovery in spiked samples.
Fibroblast mediated dynamics in diffusively uncoupled myocytes: a simulation study using 2-cell motifs
Authors: Sridhar S. , Clayton Richard H.
Published: February 2024

In healthy hearts myocytes are typically coupled to nearest neighbours through gap junctions. Under pathological conditions such as fibrosis, or in scar tissue, or across ablation lines myocytes can uncouple from their neighbours. Electrical conduction may still occur via fibroblasts that not only couple proximal myocytes but can also couple otherwise unconnected regions. We hypothesise that such coupling can alter conduction between myocytes via introduction of delays or by initiation of premature stimuli that can potentially result in reentry or conduction blocks. To test this hypothesis we have developed several 2-cell motifs and investigated the effect of fibroblast mediated electrical coupling between uncoupled myocytes. We have identified various regimes of myocyte behaviour that depend on the strength of gap-junctional conductance, connection topology, and parameters of the myocyte and fibroblast models. These motifs are useful in developing a mechanistic understanding of long-distance coupling on myocyte dynamics and enable the characterisation of interaction between different features such as myocyte and fibroblast properties, coupling strengths and pacing period. They are computationally inexpensive and allow for incorporation of spatial effects such as conduction velocity. They provide a framework for constructing scar tissue boundaries and enable linking of cellular level interactions with scar induced arrhythmia.
Splenectomy has opposite effects on the growth of primary compared with metastatic tumors in a murine colon cancer model
Authors: Kaneko Yuki , Miyato Hideyo , Tojo Mineyuki , Futoh Yurie , Takahashi Kazuya , Kimura Yuki , Saito Akira , Ohzawa Hideyuki , Yamaguchi Hironori , Sata Naohiro , Kitayama Joji , Hosoya Yoshinori
Published: February 2024

The spleen is a key source of circulating and tumor-infiltrating immune cells. However, the effect of splenectomy on tumor growth remains unclear. At 3 weeks after splenectomy, we subcutaneously injected LuM1 cells into BALB/c mice and evaluated the growth of primary tumors and lung metastases at 4 weeks after tumor inoculation. In addition, we examined the phenotypes of immune cells in peripheral blood by using flow cytometry and in tumor tissue by using multiplex immunohistochemistry. The growth of primary tumors was reduced in splenectomized mice compared with the sham-operated group. Conversely, splenectomized mice had more lung metastases. Splenectomized mice had fewer CD11b+cells, especially monocytic MDSCs (CD11b+Gr-1neg-lowLy6chigh), and NK cells (CD49b+CD335+). The proportion of NK cells was inversely correlated with the number of lung metastases. In splenectomized mice, the density of CD3+ and granzyme B+ CD8+ T cells was increased, with fewer M2-type macrophages in primary tumors, but NK cells were decreased markedly in lung. Splenectomy concurrently enhances T cell-mediated acquired immunity by reducing the number of monocytic MDSCs and suppresses innate immunity by decreasing the number of NK cells. Splenectomy has opposite effects on primary and metastatic lesions through differential regulation on these two immune systems.
A comparative study of advanced evolutionary algorithms for optimizing microgrid performance under dynamic pricing conditions
Authors: Elazab Rasha , Abdelnaby Ahmed T. , Ali A.A.
Published: February 2024

The integration of microgrids into the existing power system framework enhances the reliability and efficiency of the utility grid. This manuscript presents an innovative mathematical paradigm designed for the optimization of both the structural and operational aspects of a grid-connected microgrid, leveraging the principles of Demand-Side Management (DSM). The focus of this work lies in a comprehensive exploration of the implications brought about by the Renewable Generation-Based Dynamic Pricing Demand Response (RGDP-DR) mechanism, particularly in terms of its influence on the optimal microgrid configuration, considering perspectives from end-users and the utility entity. This inquiry is rooted in a holistic assessment that encompasses technical and economic performance benchmarks. The RGDP-induced DR framework adeptly addresses the needs of the consumer base, showcasing notable efficiency and economic feasibility. To address the intricate nonlinear optimization challenge at hand, we employ an evolutionary algorithm named the "Dandelion Algorithm" (DA). A rigorous comparative study is conducted to evaluate the efficacy of four optimization techniques, affirming the supremacy of the proposed DA. Within this discourse, the complexity of microgrid sizing is cast as a dual-objective optimization task. The twin objectives involve minimizing the aggregate annual outlay and reducing emissions. The results of this endeavor unequivocally endorse the superiority of the DA over its counterparts. The DA demonstrates exceptional proficiency in orchestrating the most cost-effective microgrid and consumer invoice, surpassing the performance of alternative optimization methodologies.
Prevalence and risk factors analysis of postpartum depression at early stage using hybrid deep learning model
Authors: Lilhore Umesh Kumar , Dalal Surjeet , Varshney Neeraj , Sharma Yogesh Kumar , Rao K. B. V. Brahma , Rao V. V. R. Maheswara , Alroobaea Roobaea , Simaiya Sarita , Margala Martin , Chakrabarti Prasun
Published: February 2024

Postpartum Depression Disorder (PPDD) is a prevalent mental health condition and results in severe depression and suicide attempts in the social community. Prompt actions are crucial in tackling PPDD, which requires a quick recognition and accurate analysis of the probability factors associated with this condition. This concern requires attention. The primary aim of our research is to investigate the feasibility of anticipating an individual's mental state by categorizing individuals with depression from those without depression using a dataset consisting of text along with audio recordings from patients diagnosed with PPDD. This research proposes a hybrid PPDD framework that combines Improved Bi-directional Long Short-Term Memory (IBi-LSTM) with Transfer Learning (TL) based on two Convolutional Neural Network (CNN) architectures, respectively CNN-text and CNN audio. In the proposed model, the CNN section efficiently utilizes TL to obtain crucial knowledge from text and audio characteristics, whereas the improved Bi-LSTM module combines written material and sound data to obtain intricate chronological interpersonal relationships. The proposed model incorporates an attention technique to augment the effectiveness of the Bi-LSTM scheme. An experimental analysis is conducted on the PPDD online textual and speech audio dataset collected from UCI. It includes textual features such as age, women's health tracks, medical histories, demographic information, daily life metrics, psychological evaluations, and ‘speech records’ of PPDD patients. Data pre-processing is applied to maintain the data integrity and achieve reliable model performance. The proposed model demonstrates a great performance in better precision, recall, accuracy, and F1-score over existing deep learning models, including VGG-16, Base-CNN, and CNN-LSTM. These metrics indicate the model's ability to differentiate among women at risk of PPDD vs. non-PPDD. In addition, the feature importance analysis demonstrates that specific risk factors substantially impact the prediction of PPDD. The findings of this research establish a basis for improved precision and promptness in assessing the risk of PPDD, which may ultimately result in earlier implementation of interventions and the establishment of support networks for women who are susceptible to PPDD.
Critical scaling of a two-orbital topological model with extended neighboring couplings
Authors: Kartik Y. R. , Kumar Ranjith R. , Sarkar Sujit
Published: February 2024

Extended-range models are the interesting systems, which has been widely used to understand the non-local properties of the fermions at quantum scale. We aim to study the interplay between criticality and extended range couplings under various symmetry constraints. Here, we consider a two orbital Bernevig–Hughes–Zhang model in one dimension with longer (finite neighbor) and long-range (infinite neighbor) couplings. We study the behavior of model using scaling laws and universality class for models with Hermitian, parity-time ($$\mathscr{P}\mathscr{T}$$

P
T

) symmetric and broken time-reversal symmetries. We observe the interesting results on multi-criticalities, where the universality class of critical exponent is different than the normal criticalities. Also, the results can be generalized by considering the interplay between criticalities and different symmetry classes of Hamiltonian. Also, with the introduction of extended-range of coupling, there occurs different criticalities, and we provide the analogy to characterize their universality classes. We also show the violation of Lorentz invariance at multi-criticalities and evaluation of short-range limit in long-range models as the highlights of this work.
A novel neural network-based framework to estimate oil and gas pipelines life with missing input parameters
Authors: Shaik Nagoor Basha , Jongkittinarukorn Kittiphong , Benjapolakul Watit , Bingi Kishore
Published: February 2024

Dry gas pipelines can encounter various operational, technical, and environmental issues, such as corrosion, leaks, spills, restrictions, and cyber threats. To address these difficulties, proactive maintenance and management and a new technological strategy are needed to increase safety, reliability, and efficiency. A novel neural network model for forecasting the life of a dry gas pipeline system and detecting the metal loss dimension class that is exposed to a harsh environment is presented in this study to handle the missing data. The proposed strategy blends the strength of deep learning techniques with industry-specific expertise. The main advantage of this study is to predict the pipeline life with a significant advantage of predicting the dimension classification of metal loss simultaneously employing a Bayesian regularization-based neural network framework when there are missing inputs in the datasets. The proposed intelligent model, trained on four pipeline datasets of a dry gas pipeline system, can predict the health condition of pipelines with high accuracy, even if there are missing parameters in the dataset. The proposed model using neural network technology generated satisfactory results in terms of numerical performance, with MSE and R2 values closer to 0 and 1, respectively. A few cases with missing input data are carried out, and the missing data is forecasted for each case. Then, a model is developed to predict the life condition of pipelines with the predicted missing input variables. The findings reveal that the model has the potential for real-world applications in the oil and gas sector for estimating the health condition of pipelines, even if there are missing input parameters. Additionally, multi-model comparative analysis and sensitivity analysis are incorporated, offering an extensive comprehension of multi-model prediction abilities and beneficial insights into the impact of various input variables on model outputs, thereby improving the interpretability and reliability of our results. The proposed framework could help business plans by lowering the chance of severe accidents and environmental harm with better safety and reliability.