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Hiding in plain sight: NUT carcinoma is an unrecognized subtype of squamous cell carcinoma of the lungs and head and neck
Acute TREM2 inhibition depletes MAFB-high microglia and hinders remyelination
We investigated the role of Triggering Receptor Expressed on Myeloid cells 2 (TREM2) in myelin regeneration in the brain. TREM2 is a receptor that activates microglia, which are crucial for clearing myelin debris and promoting remyelination. Previous studies in a mouse model of demyelination induced by the copper-chelating agent Cuprizone (CPZ) have shown that stimulation of TREM2 with a monoclonal antibody reduces demyelination, while deleting the Trem2 gene in mice impairs remyelination. Here, we blocked TREM2 function acutely with an antibody during both the demyelination and remyelination phases of the CPZ model and analyzed the impact of the antibody treatment on myelination and gene expression in single cells. We found that blocking TREM2 depleted a distinct population of microglia with high expression of the transcription factor MAFB during remyelination. The loss of these MAFB-high microglia was linked to impaired generation of myelinating oligodendrocytes. Importantly, we identified MAFB + microglia in acute and acute-chronic brain lesions from individuals with multiple sclerosis (MS), but not in inactive lesions. We conclude that TREM2 is essential for maintaining a population of MAFB-high microglia that is associated with myelin repair. This finding has significant implications for understanding demyelinating diseases like MS and suggests that stimulating TREM2 could be a promising therapeutic approach for myelin repair.
Correction: Biomechanical effects of saddle height changes in leisure cycling with unilateral transtibial prostheses: A simulated study
Optimizing sintering air volume for enhanced lean gas recovery and environmental performance
Perioperative chemotherapy superior to preoperative chemoradiotherapy for locally advanced EAC
De novo discovery of a molecular glue–like macrocyclic peptide that induces MCL1 homodimerization
Macrocyclic peptides have emerged as promising drug candidates, filling the gap between small molecules and large biomolecules in drug discovery. The antiapoptotic protein myeloid cell leukemia 1 (MCL1) is crucial for numerous cancers, yet it presents challenges for selective targeting by traditional inhibitors. In this study, we identified a macrocyclic peptide, 5L1, that strongly binds to MCL1, with a dissociation constant ( K D ) of 7.1 nM. This peptide shows the potential to specifically inhibit the function of MCL1, and demonstrates effective antitumor activity against several blood tumor cell lines with the half maximal inhibitory concentration (IC 50 ) values for cell-penetrating peptide-conjugated 5L1 in the range of 0.6 to 3 μM. Structural analysis revealed that it functions similarly to molecular glue, capable of binding to two MCL1 molecules simultaneously and inducing their homodimerization. This unique mechanism of action distinguishes it from traditional small-molecule MCL1 inhibitors, underscoring the potential of macrocyclic peptides functioning as molecular glues. Moreover, it inspires the development of highly selective inhibitors targeting MCL1 and other related targets with this glue-like mechanism.
Correction: From tradition to progressiveness: Analyzing Thailand’s image on youtube amid post-cannabis legalization
Performance of vertical steel plate anchor in layered cohesionless soil
Prediction of phase-separation propensities of disordered proteins from sequence
Phase separation is one possible mechanism governing the selective cellular enrichment of biomolecular constituents for processes such as transcriptional activation, mRNA regulation, and immune signaling. Phase separation is mediated by multivalent interactions of macromolecules including intrinsically disordered proteins and regions (IDRs). Despite considerable advances in experiments, theory, and simulations, the prediction of the thermodynamics of IDR phase behavior remains challenging. We combined coarse-grained molecular dynamics simulations and active learning to develop a fast and accurate machine learning model to predict the free energy and saturation concentration for phase separation directly from sequence. We validate the model using computational and previously measured experimental data, as well as new experimental data for six proteins. We apply our model to all 27,663 IDRs of chain length up to 800 residues in the human proteome and find that 1,420 of these (5%) are predicted to undergo homotypic phase separation with transfer free energies < −2 k B T . We use our model to understand the relationship between single-chain compaction and phase separation and find that changes from charge- to hydrophobicity-mediated interactions can break the symmetry between intra- and intermolecular interactions. We also provide proof of principle for how the model can be used in force field refinement. Our work refines and quantifies the established rules governing the connection between sequence features and phase-separation propensities, and our prediction models will be useful for interpreting and designing cellular experiments on the role of phase separation, and for the design of IDRs with specific phase-separation propensities.
Correction: Novel deep reinforcement learning based collision avoidance approach for path planning of robots in unknown environment
Advanced design of 3D knitted padding for wearable cushioning in knee protector
The visuomotor transformations underlying target-directed behavior
The visual system can process diverse stimuli and make the decision to execute appropriate behaviors, but it remains unclear where and how this transformation takes place. Innate visually evoked behaviors such as hunting, freezing, and escape are thought to be deeply conserved, and have been described in a range of species from insects to humans. We found that zebrafish larvae would respond to predator-like visual stimuli with immobility and bradycardia, both hallmarks of freezing, in a head-fixed behavioral paradigm. We then imaged the zebrafish visual system while larvae responded to different visual stimuli with hunting, freezing, and escape behaviors and systematically identified visually driven neurons and behaviorally correlated sensorimotor neurons. Our analyses indicate that within the optic tectum, broadly tuned sensory neurons are functionally correlated with sensorimotor neurons which respond specifically during one behavior, indicating that it contains suitable information for sensorimotor transformation. We also identified sensorimotor neurons in four other areas downstream of the tectum, and these neurons are also specific for one behavior, indicating that the segregation of the pathways continues in other areas. While our findings shed light on how sensorimotor neurons may integrate visual inputs, further investigation will be required to determine how sensorimotor neurons in different regions interact and where the decision to behave is made.
Trends of inequities in healthcare seeking behavior for diarrhea, fever, and ARI symptoms among women in reproductive age groups for their under-five children in Ethiopian: A multilevel Analysis of EDHS Surveys from 2000 to 2016
Background Ethiopia is one of the developing countries with the highest inequity in the healthcare seeking behavior for under-five children. Despite this fact, not much is known about the trend of inequity, in healthcare seeking-behavior for symptoms of diarrhea, fever and acute respiratory infections (ARIs) among under-five children. Objective This study aimed to measure trends of inequity in healthcare seeking -behavior for diarrhea, fever, and ARI symptoms and its determinant factors among under-five children in Ethiopia. Methods Data from 2000, 2005, 2011, and 2016 Ethiopian Demographic and Health Surveys (EDHSs) were analyzed using the 2019 updated version of the WHO’s Health Equity Assessment Toolkit (HEAT) software. Five equity dimensions were used to disaggregate datasets on healthcare seeking behavior for diarrhea, fever, and ARI symptoms: Based on wealth status, education, place of residence, sex of the child and administrative regions. Second, summary measures such as: equity gaps, equity ratios, population attributable fraction (PAF), population attributable Risk (PAR), absolute concentration index (ACI) and relative concentration index (RCI), was used. The concentration curve and horizontal inequity indices were used to evaluate the wealth-related disparities. To measure the determinants a multilevel logistic regression with 95% confidence interval was employed. Result This study showed remarkable improvement in healthcare seeking behavior for symptoms of diarrhea, fever and ARI among under-five children between 2000 and 2016. The increases are more, from the poorest subgroups compared to the wealthiest. The absolute percentage point changes (or healthcare seeking rate changes) between 2000 and 2016 among the poorest quintile of households are at least twice that of the wealthiest quintile for symptoms of diarrhea. However, significant disparities between the rich and the poor persist for the majority of the indicators examined for the three childhood morbidities. Moreover, horizontal inequity indices and the concentration curve both point out to the existence of pro-rich inequity in healthcare seeking behavior for under five children. In the multilevel analysis various demographic, parental and household characteristic show an association with healthcare seeking behavior for symptoms of diarrhea, fever and ARIs. Conclusion A promising trend is observed in healthcare seeking behavior for diarrhea, fever and ARI symptoms among under-five children. Faster progress in use of healthcare services among the poor than the wealthy in Ethiopia would potentially result in elimination of inequities and rapid improvement in health among the poor. Intervention programs that focused on the underprivileged, while also taking into account the wealthier sub-groups.
Structural changes in vortex vein ampullae in eyes with pachychoroid-spectrum disorder
Neural basis for individual differences in the attention-enhancing effects of methylphenidate
Stimulant drugs that boost dopamine, like methylphenidate (MP), enhance attention and are effective treatments for attention-deficit hyperactivity disorder (ADHD). Yet there is large individual variation in attentional capacity and response to MP. It is unclear whether this variation is driven by individual differences in relative density of dopamine receptor subtypes, magnitude of dopamine increases induced by MP, or both. Here, we extensively characterized the brain dopamine system with positron emission tomography (PET) imaging (including striatal dopamine D1 and D2/3 receptor availability and MP-induced dopamine increases) and measured attention task-evoked fMRI brain activity in two separate sessions (placebo and 60 mg oral MP; single-blind, counterbalanced) in 37 healthy adults. A network of lateral frontoparietal and visual cortices was sensitive to increasing attentional (and working memory) load, whose activity positively correlated with performance across individuals (partial r = 0.474, P = 0.008; controlling for age). MP-induced change in activity within this network correlated with MP-induced change in performance (partial r = 0.686, P < 0.001). The ratio of D1-to-D2/3 receptors in dorsomedial caudate positively correlated with baseline attentional network activity and negatively correlated with MP-induced changes in activity (all pFWE < 0.02). MP-induced changes in attentional load network activity mediated the association between D1-to-D2/3 ratio and MP-induced improvements in performance (mediation estimate = 23.20 [95%CI: −153.67 −81.79], P = 0.004). MP attention-boosting effects were not linked to the magnitude of striatal dopamine increases, but rather showed dependence on an individual’s baseline receptor density. Individuals with lower D1-to-D2/3 ratios tended to have lower frontoparietal activity during sustained attention and experienced greater improvement in brain function and task performance with MP.
Intraoperative phrenic nerve stimulation to prevent diaphragm fiber weakness during thoracic surgery
Thoracic surgery rapidly induces weakness in human diaphragm fibers. The dysfunction is thought to arise from combined effects of the surgical procedures and inactivity. This project tested whether brief bouts of intraoperative hemidiaphragm stimulation would mitigate slow and fast fiber loss of force in the human diaphragm. We reasoned that maintenance of diaphragm activity with brief bouts of intraoperative phrenic stimulation would mitigate diaphragm fiber weakness and myofilament protein derangements caused by thoracic surgery. Nineteen adults (9 females, age 59 ± 12 years) with normal inspiratory strength or spirometry consented to participate. Unilateral phrenic twitch stimulation (twitch duration 1.5 ms, frequency 0.5 Hz, current 2x the motor threshold, max 25 mA) was applied for one minute, every 30 minutes during cardiothoracic surgery. Thirty minutes following the last stimulation bout, biopsies were obtained from the hemidiaphragms for single fiber force mechanics and quantitation of myofilament proteins (abundance and phosphorylation) and compared by a linear mixed model and paired t-test, respectively. Subjects underwent 6 ± 2 hemidiaphragm stimulations at 17 ± 6 mA, during 278 ± 68 minutes of surgery. Longer-duration surgeries were associated with a progressive decline in diaphragm fiber force (p < 0.001). In slow-twitch fibers, phrenic stimulation increased absolute force (+25%, p < 0.0001), cross-sectional area (+16%, p < 0.0001) and specific force (+7%, p < 0.0005). Stimulation did not alter contractile function of fast-twitch fibers, calcium-sensitivity in either fiber type, and abundance and phosphorylation of myofilament proteins. In adults without preoperative weakness or lung dysfunction, unilateral phrenic stimulation mitigated diaphragm slow fiber weakness caused by thoracic surgery, but had no effect on myofilament protein abundance or phosphorylation.
Biomechanical changes in females with poly cystic ovarian syndrome: a case–control study
Abstract Polycystic ovarian syndrome (PCOS) is a prevalent endocrine disorder that causes an inversion of the normal luteinizing hormone (LH) to follicle-stimulating hormone (FSH) ratio. Females with PCOS also experience chronic inflammation. This hormonal imbalance and persistent inflammation can reduce muscle strength and mass. Consequently, this may affect the lumbopelvic muscles, potentially leading to postural abnormalities and spinal misalignment. The study’s goals were to find out how the biomechanics of women with PCOS differ from those who did not have the condition and to confirm the link between lumbopelvic parameters and the LH/FSH ratio in women with PCOS. The researcher conducted a case–control study on 95 nulliparous females, with 52 having PCOS and classified as a study group and 43 as a control group. The participants ranged in age from 25 to 35 years, and their body mass index ranged from 25 to 29.9 kg/m2. All participants were selected from the gynecological outpatient clinic of Om El-Masryeen Hospital. The researcher used a pelvic inclinometer to evaluate the pelvic inclination angle and an inclinometer to examine the lumbar angle. Additionally, the researcher simultaneously collected blood samples on the third day of the menstrual cycle. Females with PCOS had significantly higher pelvic inclination and lumbar curve angles than controls (p < 0.05). LH/FSH ratio strongly correlated with lumbar angle and pelvic inclination. Females with PCOS had greater pelvic tilting and exaggerated lumbar lordosis than controls. The LH/FSH ratio showed a strong correlation with both the lumbar curve angle and pelvic inclination in PCOS. Clinical trial: The clinical trial number [NCT03740932] with initial release date at 09/17/2024.
The narrow search effect and how broadening search promotes belief updating
Information search platforms, from Google to AI-assisted search engines, have transformed information access but may fail to promote a shared factual foundation. We demonstrate that the combination of users’ prior beliefs influencing their search terms and the narrow scope of search algorithms can limit belief updating from search. We test this “narrow search effect” across 21 studies (14 preregistered) using various topics (e.g., health, financial, societal, political) and platforms (e.g., Google, ChatGPT, AI-powered Bing, our custom-designed search engine and AI chatbot interfaces). We then test user-based and algorithm-based interventions to counter the “narrow search effect” and promote belief updating. Studies 1 to 5 show that users’ prior beliefs influence the direction of the search terms, thereby generating narrow search results that limit belief updating. This effect persists across various domains (e.g., beliefs related to coronavirus, nuclear energy, gas prices, crime rates, bitcoin, caffeine, and general food or beverage health concerns; Studies 1a to 1b, 2a to 2g, 3, 4), platforms (e.g., Google—Studies 1a to 1b, 2a to 2g, 4, 5; ChatGPT, Study 3), and extends to consequential choices (Study 5). Studies 6 and 7 demonstrate the limited efficacy of prompting users to correct for the impact of narrow searches on their beliefs themselves. Using our custom-designed search engine and AI chatbot interfaces, Studies 8 and 9 show that modifying algorithms to provide broader results can encourage belief updating. These findings highlight the need for a behaviorally informed approach to the design of search algorithms.
Selection index for economically important traits in Boer crossbred goats using principal component analysis
The optimal strategy for genetic selection is a selection index based on economic weight; however, in developing countries where economic weight estimation is not always evident and easy for breeders due to a lack of economic data. Thus, this study aimed to construct selection indices for crossbred goats, which could be used as an alternative to economic selection index and to explore the relationship among economically important traits. The data set contained records of birth weight (BW), weaning weight (WW), pre-weaning weight gain (ADG), pre-weaning Kleiber ratio (KR), pre-weaning relative growth rate (RGR), pre-weaning growth efficiency (GE), and pre-weaning survival (RR) of crossbred goats. Genetic parameter estimates were obtained using a single-trait animal model. General linear model, principal component analysis, and cluster procedures of SAS were also used for data analysis. Kid survival was negatively correlated with all investigated traits except BW. Traits such as KR, GE, RGR, WW, and ADG were highly and positively correlated. According to the Kaiser method, two principal components were selected from seven investigated traits. The first principal component (PC1) explained 57.71%, and the second principal component (PC2) explained 14.57% of the estimated breeding value variance, totaling 72.28% of the total genetic additive variance. PC1 explained most of the direct additive genetic variation and correlated with the estimated breeding value of WW, ADG, KR, GE, and RGR, whereas PC2 was correlated with the estimated breeding value of BW and RR. Besides, the cluster analysis categorized seven traits into two major groups. The first group includes BW and RR, whereas traits such as WW, ADG, KR, GE, and RGR were included in the second group. Therefore, two based selection indices, or principal component scores (PCS) were derived. Animals with higher PCS1 could be used to improve WW, ADG, KR, GE, and RGR, whereas animals with higher PCS2 scores could be used to improve BW and pre-weaning survival of crossbred kids. The selection of the most appropriate and specific selection index regarding the two groups of traits is determined by the breeding objectives defined for specific genetic improvement program. These selection indices could be used as an alternative approach when economic weights for traits of interests are not available to construct the economic selection index. However, further works should be done on refining the selection indices and validating them in independent datasets.