Lithium (Li) metal is an ideal anode candidate for rechargeable batteries because of its ultra-high theoretical specific capacity. Unfortunately, the practical application of Li metal anodes is severely limited by the uncontrollable formation and growth of dendrites and infinite volume expansion. Thus, a protective layer is essential for stable and high-performance Li metal anodes. In this work, we demonstrate an organic-inorganic hybrid interfacial protective layer on Li foil surface (pa-Li) consisting of the organic polyvinylidene fluoride-hexafluoropropylene copolymer（PVDF-HFP）and inorganic Ag-LixAgy composite species. Going beyond conventional protective layers, we demonstrate that our hybrid protective layer is flexible and enabled strong interfacial adherence due to an alloying process. Furthermore, owing to the protective layer’s outstanding lithiophilicity and mechanical stability, the pa-Li││pa-Li symmetric cell exhibits satisfactory stability and reversibility for 1000 h at 5 mA cm-2, 5 mA h cm-2 with a low voltage hysteresis of ~ 70 mV, while the full cell with a LiFePO4 cathode delivers an excellent reversible capacity of 128.9 mA h g-1 for 900 cycles at 2 C with a capacity decay rate of 0.009% per cycle. This work proposes a design protocol for synergistic effect of PVDF-HFP organic species and Ag-LixAgy inorganic species and provides a prospective way to practical application of highly efficient, long lifespan Li metal batteries.

Miargyrite silver antimony chalcogenide (AgSbS2) exhibits a promising photoresponse to sunlight. However, the large band gap (~1.7 eV) limits its practical application, especially in 1300-1550 nm range require for laser communication. Although selenization can reduce the band gap of AgSbS2 film, the effectiveness is hindered by the compact crystal grain structure, resulting in limited selenization only at the top surface and an insufficient selenization rate. In this work, we prepare a gradient structure AgSbS2(Se) film through spray pyrolysis with a post selenization. To achieve a high selenization rate, we construct a loose AgSbS2 precursor via innovatively adding some indium nitrate to the spray solution. By optimizing the process, we successfully fabricated broadband photodetectors with a response range extending beyond 1920 nm. The fabricated photodetectors not only exhibit excellent broadband response characteristics but also demonstrate a high bandwidth of up to 0.3 MHz and a rapid response time of 1.12 μs. These outstanding features indicate great potential for application in high-speed photon computation and communication systems. This novel gradient structure AgSbS2(Se) film opens up new possibilities for developing high-performance broadband photodetectors essential for advancing laser communication technology.

Despite the historical use of T. cordifolia in Ayurveda for diabetes, its potential for promoting diabetic wound healing remains unexplored. This study evaluated the diabetic wound healing ability of aqueous ethanolic stem extract of T. cordifolia (AETC) in streptozotocin-nicotinamide (STZ-NAD) induced diabetic rats. AETC extracts were extracted using 70% aqueous ethanolic solvent via Soxhlet extraction. A full-thickness excision wound was created on the dorsal skin of STZ-NAD-induced diabetic rats and followed by a 14-day treatment with AETC extract at high (500 mg/kg) and low (250 mg/kg) doses. The key parameters, including blood glucose levels, wound contraction percentage, and epithelisation time were evaluated. Wound tissues were collected for histopathological analysis. Oral administration of AETC significantly reduced blood glucose levels over 14 days (p ≤ 0.01) and notably improved the percentage of wound contraction compared to diabetic controls (p < 0.05). Both doses also displayed significant improvement in epithelisation time (p < 0.05). Histopathological analysis consistently unveiled the healing of the epidermis, a reduction in inflammation, as well as the enhancement of granulation tissue formation and collagen deposition. This study demonstrated the potential ability of AETC not only in lowering the blood glucose level but also in ameliorating diabetic wound healing.

Sepsis is a life-threatening organ dysfunction that results from dysregulated host response to infection. Multiple organ system dysfunction syndromes are prevalent among septic patients and are essential hallmarks of sepsis diagnosis. These syndromes involve failure of the pulmonary, hepatic, circulatory, renal, gastrointestinal and central nervous systems. Neurological dysfunction is part of this syndrome and has gained research attention recently [1]. Sepsis induces neuroinflammation, BBB disruption, cerebral hypoxia, neuronal mitochondrial dysfunction and cell death causing sepsis-associated encephalopathy (SAE). These pathological consequences lead to short- and long-term neurobehavioral deficits. Till now there is no specific treatment that directly improves SAE and its associated behavioral impairments. In this review, we discuss the underlying mechanisms of sepsis-induced brain injury with a focus on the latest progress regarding neuroprotective effects of SIRT1 (silent mating type information regulation-2 homologue-1). SIRT1 is an NAD+-dependent class III protein deacetylase. It is able to modulate multiple downstream signals (including NF-κB, HMGB, AMPK, PGC1α and FoxO) which are involved in the development of SAE by its deacetylation activity. There are multiple recent studies showing the neuroprotective effects of SIRT1 in neuroinflammation related diseases. The proposed neuroprotective action of SIRT1 is meant to bring a promising therapeutic strategy for managing SAE and ameliorating its related behavioural deficits.

One of the aspects of the “neural efficiency” hypothesis is decreased cortical activity in experts during professional actions compared to their rest condition as a sort of event-related synchronization (ERS). Previous research revealed that “Football Players Do Not Show “Neural Efficiency” in Cortical Activity Related to Visuospatial Information Processing During Football Scenes: An EEG Mapping Study” (Del Percio et al., 2019) and demonstrated that footballers do not show “neural efficiency” in parietal cortical activity. In our study, we checked this hypothesis and registration of brain activity during football training and compared this result at rest. This is the first study occupied during live football training. The participants were professional football players. The EEG was recorded in the prefrontal cortex using the NeuroSky device. The brain oscillations were checked in the eyes-closed at rest and during football training on the pitch in the eyes-open condition. A study result is statistically significant between at rest and during movement and obtained as the summary value of bands (1-50 Hz). The results of the paired-t test indicated that there is a difference between “Before” and “After” conditions (t = -2.13; p<.05). Thus, compared to the rest condition, this data showed a reduced power spectrum of EEG bands in the prefrontal cortex among all rhythms during football training and confirmed the “neural efficiency” hypothesis (selective cortical activation) among football players. We suggest that the brain of professional football players has different activation by separate brain parts.

Gullies and ravines are common landforms in raised marine fine-grained deposits in Norway. Gullies in marine clay are significant landforms indicative of soil erosion, natural hazards and are of high conservation value. As a result of the substantial impact of human intervention over the past century, marine clay gullies are now red-listed. To monitor the condition of these landforms we need to improve our understanding of their spatial extent, complexity, and morphology. We explore the applicability of automated approaches that uses a methodology of combining deep learning (DL), fully convolutional neural networks (FCNN), and a U-Net model with ArcPy libraries and ground truth data to derive a high-resolution map of gullies in raised marine fine-grained deposits. Predictors used comprise solely terrain derivatives to broaden the usage of the pre-trained model to other regions. Our best model achieved a precision score of 0.82 and a recall of 0.75. We find that our pre-trained model can successfully predict gullies in blind-test areas. The model performs better in regions with similar geological settings, scoring a length-weighted overlap of >72% with reference datasets. We also find that the model's applicability increases when we post-process the predictions by eliminating noise, especially by using the predictions derived from ensembled models. We, therefore, conclude that the pre-trained models can effectively be used to supplement the geomorphological mapping of marine clay gullies in Norway. The outcome of this research contributes towards mapping the spatial extent and condition of red-listed landforms in Norway, as well as the development of monitoring systems for future landscape change.  Keywords: gullies, ravines, landforms, marine clay, deep learning, U-net 

Psychopathy is characterized by glibness and superficial charm, as well as a lack of empathy, guilt, and remorse, and is often accompanied by antisocial behavior. The cerebral bases of this syndrome have been mostly studied in violent subjects or those with a criminal history. However, the antisocial component of psychopathy is not central to its conceptualization and, in fact, psychopathic traits are present in well-adjusted, non-criminal individuals within the general population. Interestingly, certain psychopathy characteristics appear to be particularly pronounced in some groups or professions. Importantly, as these so-called adaptive or successful psychopaths do not show antisocial tendencies or have significant psychiatric comorbidities, they may represent an ideal population to study this trait. Here we investigated such a group, specifically elite female judo athletes, and compared them to matched non-athletes. Participants completed psychopathy, anger, perspective-taking and empathic concern questionnaires and underwent structural magnetic resonance imaging (MRI). Grey matter density (GMD) was computed using voxel-based morphometry from the T1-weighted images. Athletes scored significantly higher in primary psychopathy and anger, and lower in empathy and perspective taking. They also exhibited smaller GMD in the right Temporal Pole, left Occipital Cortex, and left Amygdala/Hippocampus. GMD values for the latter cluster significantly correlated with primary psychopathy scores across both groups. These results confirm and extend previous findings to a little-studied population and provide support for the conceptualization of psychopathy as a dimensional personality trait which, not only is not necessarily associated with antisocial behavior, but may potentially have adaptive value.

In a dielectric barrier reactor (DBD), plasma-assisted direct conversion of CH4 and CO2 to liquid products (methanol, ethanol, etc.) under atmospheric conditions was performed. Due to its excellent ability to activate CO2 and promote chain growth, Fe is an ideal candidate for catalyst design. Meanwhile, graphite carbon nitride (g-C3N4) with Lewis and Brönsted basic sites further enhances its catalytic performance. Therefore, combining Fe and g-C3N4 holds great potential for catalyst synthesis and applications. In this paper, we prepared a highly active catalyst (Fe/g-C3N4) using a non-noble metal by impregnating Fe onto the g-C3N4 support. When 10% Fe/g-C3N4 was half-filled in the discharge region, the conversions of CH4 and CO2 were 22% and 18%, respectively, and the liquid product selectivity was 40.1%. In the liquid products, the selectivity of alcohol liquid products can reach 35%, of which methanol can reach 24.4%, higher than the reported 11.9%.

Magnetic resonance imaging (MRI) plays an important role in precision medicine that is hampered by the lack of contrast agents with high efficiency and the ability to translate diagnostic accuracy into therapeutic intervention. Herein, we demonstrate a DNA-based MRI probe that overcomes previous single-mode enhancement and provides a mechanism of action for aggregation-induced dual-mode MRI signal enhancement. A facile method is developed to produce aggregated T1/T2 dual-mode NaGdF4:Dy@PDA-DNA MRI probes. When aggregated, this probe can further amplify MRI signal intensity and exhibits improved geometrical and positional stability in vivo. The performance of the NaGdF4:Dy@PDA-DNA MRI probe toward MRI-guided preoperative planning and visualization-guided surgery is verified using an orthotopic tumor-bearing mouse model. The result shows that the rapid metabolism of the degraded probe leads to the mitigation of long-term toxic effects. Therefore, the developed high-performance MRI probe is of great significance for enhancing MRI diagnostic accuracy into precision medical therapeutic interventions.

Background: The diagnosis of Crohn’s disease (CD) is still challenging, and the search for novel biomarkers is a worthwhile endeavor. Mast cells can be activated in various ways. Whether serum IgE, anti-IgE and anti-IgE high-affinity receptor (FcεRI) antibodies are involved in the pathogenesis of CD was investigated by bridging FcεRI to activate MCs. The relationship between MCs and CD is also explored in this research.Methods: Microplates with human FcεRIα were coated and an enzyme-labeled anti-human IgG was used as the tracer to successfully establish an indirect enzyme-linked immunosorbent assay (ELISA) method for semi-detection of IgG anti-FcεRI. The optimal working conditions were explored, followed by conducting the method evaluation. The serum samples and clinical data of 117 CD patients and 75 healthy controls were collected. IgE was measured by the rate turbidity turbidimetry; IgG anti-IgE and IgG anti-FcεRI were detected by ELISA. IgG anti-pancreatic antibody (PAB) and anti-Saccharomyces cerevisiae antibody (ASCA) were determined by indirect immunofluorescence assay. Data were analyzed concerning the clinical characteristics.Conclusions: An ELISA for the detection of anti-FcεRI was established and validated, which may contribute to facilitating the study of mast cell-related diseases. Anti-FcεRI positive CD patients were associated with adverse phenotypes, suggesting its value in the diagnosis and management of CD.

Madeleine M. Ostwald*, Valentina A. Venegas, and Katja C. Seltmann

A document by Ayad Tareq Imam. Click on the document to view its contents.

A document by Ayad Tareq Imam. Click on the document to view its contents.

Component-based software development has been regarded as one of the newest trends in the software development industry. In some ways, component-based software development focuses on reusability. In fact, high-quality software components refer to components that are highly cohesion internally, and also have the least coupling with other components, or in other words, are independent. Thus, using such components will lead to faster software development. In this way, this study aims to identify reusable components in software. To do this, first, software components were extracted from the source code of software systems. To identify reusable components, an artificial neural network algorithm has been used. On the other hand, the reusable components recognized by the evolutionary particle swarm optimization algorithm have been clustered. In this study, the particle swarm optimization algorithm was modified to apply to clustering problems. Finally, with the help of these clusters, the KNN classifier was trained, and during identifying reused inputs, the cluster to which the input belongs was determined by the classifier. This way, we will have a library of reusable components, where similar components are placed in a cluster. The proposed algorithm was experimentally evaluated on nine open-source software systems belonging to different domains. The results of this study show that the counted software components are potentially reusable and confirm the research findings.

Anemia occurs when the hemoglobin (Hgb) value falls below a certain reference range. It requires many blood tests, radiological images, and tests for diagnosis and treatment. By processing medical data from patients with artificial intelligence and machine learning methods, disease predictions can be made for newly ill individuals and decision-support mechanisms can be created for physicians with these predictions. Thanks to these methods, which are very important in reducing the margin of error in the diagnoses made by doctors, the evaluation of data records in health institutions is also important for patients and hospitals. In this study, three hybrid models are proposed to classify non-anemia records, Hgb-anemia, folate deficiency anemia (FDA), iron deficiency anemia (IDA), and B12 deficiency anemia by combining artificial intelligence and machine learning methods TreeBagger with Crow Search Algorithm (CSO), Chicken Swarm Optimization Algorithm (CSO) and JAYA methods. The proposed hybrid models aim to achieve high performance by better emphasizing the importance of parameters. To solve the multiclass anemia classification problem, fuzzy logic-based parameter optimization is applied to improve the class-based accuracy as well as the overall accuracy in the dataset. The classification performances of the proposed methods are evaluated using accuracy, F-score, precision, and recall criteria to build a prediction model to identify the anemia type of anemic patients. A result of the study on the dataset taken from the Kaggle database found that the three proposed hybrid methods outperformed other studies using the same dataset and similar studies in the literature.

A document by Yuanyuan Shi. Click on the document to view its contents.

Background Spontaneous preterm birth is the leading global cause of neonatal death, and countless efforts have failed to establish a single effective treatment for preterm labor, partly because the mechanisms that regulate the uterus and the cervix during pregnancy are not well understood. When a post-term pregnancy truly exists, its cause is mostly unknown. Objective To support the hypothesis. Study Design: This study investigated the current evidence-based literature and research that may support the hypothesis, accompanied by 40-second 3D animations. Results Light-dark cycle modulation of interactive inhibitory and stimulatory systems divides gestation into five clinical phases: growth, maturation, transition, parturition, and involution. During the maturation phase (30–40 weeks), nocturnal synchronisation and synergy of the inhibitory and stimulatory systems, secondary to light-dark cycle modulation, make the cervix progressively transform into the lower uterine segment and lose its strength, eventually causing EUWT failure. The clock that measures the duration of pregnancy consists of two interacting timers, an interval timer measuring the overall length of gestation and a circadian timer that defines when a 24-hour cycle birth occurs. Pregnancy intervals and circadian timers are achieved by a single mechanism, namely EUWT failure, secondary to the complete loss of cervical strength nocturnally. Inhibitory system malfunction causes preterm labor, and most of the current therapeutic modalities for preterm labor focus on delaying or preventing EUWT failure. Stimulatory system malfunctions cause post-term pregnancy. Conclusion The creation, autonomic maintenance, and eventually autonomic EUWT termination make pregnancy an autonomic cycle with constant intervals and circadian timers where its malfunctions change the timing of birth and pregnancy duration. Laplace’s law measures EUWT, which might be the law of physics that controls pregnancy duration.

Background Our hypothesis suggests another view regarding the following: Labor physiology. Labor progress. Labor dystocia. Objective To support the hypothesis. Study Design This study investigated the current evidence-based literature and research that may support the hypothesis. Results Intrinsic myometrial cell character ensures that parturition is an autonomic, intrinsic, and interactive repetitive contraction and relaxation cycle, secondary to myometrial tension changes that cause labor progression and protect the foetus against hypoxia. The progress during the first stage of labor and what is called cervical dilatation is the complete transformation of the cervix into the LUS, which has a clinical and radiological presentation. The clinical presentation is effacement, and dilatation. Radiologically, the cervix transforms into the LUS through an inverted inside-out TYVU and an inverted U pattern formation. In the second stage of labor, the cervix has completely transformed into the LUS which is a wedge-shaped birth canal that extends from the vaginal vault (cervicovaginal junction) into the physiologic retraction ring. All these changes reverse instantly after foetal delivery, and the cervix returns to its anatomical site and regains its full anatomical shape. Concomitant malfunctions of the inhibitory and stimulatory systems cause labor dystocia. Conclusion Labor dystocia is the failure of the complete transformation of the cervix into the lower uterine segment secondary to combined inhibitory and stimulatory system malfunction. Most of the cervical transformation into the LUS takes place during the third trimester and is completed during the first stage of labor. So, the treatment of labor dystocia should focus on the causes of the stimulatory system’s malfunction before the onset of labor. There is evidence to support the hypothesis, and it should be in the interest of obstetricians, physiologists, midwives, neonatologists, and those with a research interest in maternal and family welfare.

Background Despite a considerable body of literature gathered from the few species that have been studied, the mechanisms responsible for the maintenance of pregnancy and the initiation of parturition have not been fully elucidated. Failure to understand uterine function during pregnancy is a major shortcoming in healthcare. Objective To support the hypothesis. Study Design This study investigated the current evidence-based literature and research that may support the hypothesis, accompanied by 40-second 3D animations. Results The isthmus of the cervix does not seem to exist embryologically, anatomically, histologically, or functionally. The isthmus of the cervix may be a flaw in the concept of human parturition, which creates a block barrier that prevents understanding of uterine function. Mechanotransduction is the process by which cells sense physical forces and translate them into biochemical and biological responses. Uterine mechanotransduction has functional and molecular components, wherein intrinsic myometrial cell character (IMCC) is the molecular component and Exponential uterine wall tension (EUWT) is the functional component. IMCC enables the uterus to control its functions autonomically and intrinsically, secondary to changes in tension, where high tension induces relaxation and low tension induces contraction. EUWT is created and maintained by a complex interaction between the gestational sac, uterus, and cervix, for which the primary function is to maintain EUWT. EUWT mechano-transduction and progesterone/estrogen induce the stretch-dependent inhibitory system, and indirectly, they also induce the stimulatory system by inducing myometrial hyperplasia and hypertrophy. Pregnancy is mainly maintained through a stretch-dependent inhibitory system, in addition to direct myometrial relaxants. Contractions of the stimulatory system in the presence of the foetus create direct and indirect uterine-cervical interactions (DIDUCI). DIDUCI transforms the cervix into the lower uterine segment through TYVU pattern formation and causes EUWT failure. So, the functional components of the stimulatory system (DIDUCI) are the uterus corpus, fetus, cervix, and bony pelvic inlet. Conclusion Pregnancy is a state of balance between the two opposing and interactive inhibitory and stimulatory systems secondary to EUWT mechanotransduction and progesterone/estrogen stimulation. EUWT is measured using Laplace’s law, which might be the law of physics that controls uterine function during pregnancy.

An improved method for accurate and precise determination of metal to calcium ratio in mass limited calcium carbonate samples has been developed. We used an Agilent ®5800 ICP-OES for major elements (Na/Mg/Sr to Ca) and an Agilent ®8900 QQQ-ICP-MS for minor and trace elements (Li/B/Na/Mg/Al/Mn/Fe/Zn/Sr/Cd/Ba/U to Ca). Our method has a long-term precision of ≤1%(1s), determined by repeat analysis over different analytical sessions (n≥6) of multiple external standards spanning a large range of concentrations. We quasi-quantitatively eliminated potential matrix effect raising from high [Ca] by analyzing samples and standards at identical concentrations (∆[Ca] ≤ ±5%) during both ICP-OES and ICP-QQQ-MS sessions. ICP-OES analyses were done on 200µl of sample at 60 ppm [Ca], consuming ~30µg of CaCO 3 per analysis. Whereas trace element analyses by ICP-QQQ-MS required ~150µl of sample at 20 ppm [Ca], consuming ~7.5µg of CaCO 3 per analysis. Thus, the present method allows for high precision determination of TE/Ca in <40µg of CaCO 3. The sensitivity and stability of ICP-OES was optimized for selected elements (Na, Mg, Ca and Sr) by tuning for gas flows, plasma power, viewing height in order to select wavelengths which exhibits minimal interferences, high sensitivity and linearity. For choice of Ca lines, the focus was on the minimization of self-matrix effect. The optimization of ICP-QQQ-MS method focused on the selection of right isotope(s) for elements with minimal to no interferences, relatively high absolute abundance. We minimized instrumental drift by conditioning the cones with 20 ppm Ca. Furthermore, the present method allows for precise B/Ca determination sans the use of HF matrix. In summary, this paper presents an easily adopted method for determining element-to-calcium ratios, suitable for analyzing limited-mass carbonate samples including foraminifera and coral samples from culture experiments, and core-top/down-core samples using readily-available-instrumentation.

Objective: To calculate the incidence and assess risk factors leading to permanent brachial plexus birth injury (BPBI) in Southern Finland Design: Retrospective population-based study Setting: Helsinki University Women’s Hospital and Helsinki University New Children’s Hospital, Finland Sample: All children born from 2006 to 2022 in Southern Finland with a permanent BPBI and their mothers Methods: Birth information of all mothers and their children born from 2006 to 2022 in Southern Finland were gathered from the national database and compared to prospectively collected data from mothers and their children with a permanent BPBI delivered within the same period. Permanent injury was defined as limited active or passive range of motion or decreased strength in the affected limb detected at one year of age. The severity of the injury was assessed using the 3-month Toronto test score. Main outcome measures: Permanent brachial plexus birth injury Results: Altogether, 298 428 children were born within the study period, of which 100 acquired a permanent BPBI. The incidence of a permanent BPBI was 0.4 per 1000 vaginal live births (0.34 all births), with a declining trend. Children born to immigrant mothers and women of Black ethnicity had a higher incidence of permanent injury (0.85 and 1.52 per 1000). Non-white background and immigrant status correlated with a more severe injury (β=-1.12 range, -2.17 to -0.07, p=0.004), with children to Black mothers having the least favorable outcome (β= -1.64 range, -2.79 to -0.49, p=0.005). Conclusion: The overall incidence of permanent BPBI is declining. Immigrant status and Black ethnicity increase the risk of a permanent BPBI.

Document Layout Analysis plays an important part in understanding the content of the document and extracting OCR text. Existing methods rely primarily on parallel analytical and identification techniques. Based on the analysis of the advantages and disadvantages of parallel methods, this article proposes a Serial Classification Recognition Method based on the improved architecture of the Mask R-CNN. To be specific, an improved feature pyramid model SCBAM-FPN is proposed, which utilizes Spatial Attention Module and Channel Attention Module as well as Atrous Convolution to reduce the loss of local information in feature maps and expand the receptive field, thereby increasing the performance of FPN express ability. Experiments show that using SCBAM-FPN to replace the original feature pyramid network in Mask R-CNN improves the detection performance of Mask R-CNN network for multi-scale targets. In addition, in order to improve the accuracy of segmentation, a Mask edge correction algorithm is proposed, which combines the FCN semantic segmentation results with edge superpixel information and uses the Mask-IoU mechanism to perform edge corrections on Masks with scores of less than 90%. The serial classification recognition method utilizes the improved Mask R-CNN architecture to perform Document Layout Analysis. Firstly, the document image is recognized and the table is segmented. Secondly, the image after the split table is used to identify and segment the illustrations. Finally, identify the title and paragraph of the image after removing the table and the illustration. Although the serial classification and recognition method has a certain degree of decline in speed, this method solves the problem of competition among multiple attributes and improves the accuracy of recognition compared with existing methods. In this article, experiments that were conducted on three datasets show that the proposed method surpasses existing methods in terms of accuracy and efficiency.

Analysis of transcription factors and chromatin modifications at the genome-wide level provides insights into gene regulatory processes, such as transcription, cell differentiation and cellular response. Chromatin immunoprecipitation is the most popular and powerful approach for mapping chromatin, and other enzyme-tethering techniques have recently become available for living cells. Among these, CUT&Tag is a relatively novel chromatin profiling method that has rapidly gained popularity in the field of epigenetics since 2019. It has also been widely adapted to map chromatin modifications and TFs in different species, illustrating the association of these chromatin epitopes with various physiological and pathological processes. Scalable single-cell CUT&Tag can be combined with distinct platforms to distinguish cellular identity, epigenetic features and even spatial chromatin profiling. In addition, CUT&Tag has been developed as a strategy for joint profiling of the epigenome, transcriptome or proteome on the same sample. In this review, we will mainly consolidate the applications of CUT&Tag and its derivatives on different platforms, give a detailed explanation of the pros and cons of this technique as well as the potential development trends and applications in the future.

Aquaporins (AQPs) are intrinsic membrane proteins responsible for facilitating water transport across biological membranes. AQPs found in plant membrane vesicles (MV) have been related to the functionality and stability of the vesicles. In this study, we focused on AQPs obtained from Brassica oleracea var. L. italica (broccoli) by the great potential for different biotechnological applications. To gain further insight into the role of AQPs in MV and advance the biotechnological applications of AQPs, we describe the heterologous overexpression of two broccoli AQPs (BoPIP1;2 and BoPIP2;2) in Pichia pastoris, resulting in the purification of both AQPs with high yield (0.14 and 0.99 mg per gram cells for BoPIP1;2 and BoPIP2;2, respectively). We reconstituted purified AQPs in liposomes to study their functionality, showing no changes in size compared to liposomes. BoPIP2;2 facilitated water transport, which was preserved for seven days at 4oC and 25ºC but not at 37oC, whereas BoPIP1;2 did not enhance water transport across the proteoliposome membrane. Additionally, BoPIP2;2 was incorporated into liposomes to encapsulate a resveratrol extract in proteoliposome vesicles, resulting in increased entrapment efficiency compared to conventional liposomes. Molecular docking identified potential binding sites for resveratrol in PIP2s, highlighting the role of AQPs in the improved entrapment efficiency of resveratrol. Moreover, a modelling study was conducted, demonstrating interactions between a plant AQP and human integrin, which may be a benefit to increase contact and internalization by the human target cells. Thus, our results suggest that AQPs-based alternative encapsulation systems can be used in specifically target biotechnological applications.