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The delivery of listening instructions proved difficult for students, who also lacked interest in English subjects. One potential solution to improve their listening skills could be the use of effective learning media that engages their interest in the subject matter. The purposes of this study were to investigate students’ listening proficiency and figure out students’ perceptions of utilizing videos as media for learning English listening subjects. A quantitative research design was applied to gather the data required through a test and questionnaire. Furthermore, a test was used to gather data related to students' listening ability, and a questionnaire was used to find out students' perceptions of utilizing videos as sources of learning listening. Respondents in this study were twenty-five students from the eleventh grade of SMK N 1 Pleret, Yogyakarta. The findings of the present study revealed that the total mean score (????̅) of the students' test results was 76,8, which is categorized as a "Fair" level of achievement. Other findings revealed that the use of video brings a positive impact on students' learning situation because the use of videos made it possible for students to actively participated in their listening class activities. The results indicated that students enjoy watching videos, and believe that watching videos could enhance their listening proficiency. Besides, videos provide visual elements which can be the key element in assisting students to enhance their listening ability.

We revisit the resonant break-up of 19C on protons at intermediate energies. In this reaction, it was found, for the first time in a halo nucleus to our knowledge, that the cross section was largely dominated by the excitation of the core. In this contribution, we study the robustness of this conclusion against the choice of different optical potentials for the core.

17C structure is studied within a two-body model, a weakly bound neutron moving in a deformed potential generated by the core. A semi-microscopic method has been used to generate the deformed valencecore potential. The method consists of the convolution of a realistic nucleon-nucleon (NN) interaction with the core transition densities, which are obtained by antisymetrized molecular dynamics (AMD). The results highlight the important role of deformation for this nucleus and can be easily applied to reaction calculations.

This article introduces a novel approach to detecting honey adulteration by combining ultra-fast gas chromatography (UF-GC) with advanced machine learning techniques. Machine learning models, particularly support vector regression (SVR) and least absolute shrinkage and selection operator (LASSO), were applied to predict adulteration in orange blossom (OB) and sunflower (SF) honeys. The SVR model achieved R2 values above 0.90 for combined honey types. Treating OB and SF honeys separately resulted in a significant accuracy improvement, with R2 values exceeding 0.99. LASSO proved especially effective when honey types were treated individually. The integration of UF-GC with machine learning not only provides a reliable method for detecting honey adulteration, but also sets a precedent for future research in the application of this technique to other food products, potentially enhancing food authenticity across the industry. [ABSTRACT FROM AUTHOR]

Aims Methods and results Conclusion Uncertainty exists about defining true iron deficiency (ID) in heart failure (HF) patients. We assessed the relationship of different ID definitions with cardiac structure and function, congestion, exercise capacity, and prognosis in HF outpatients.Iron deficiency was defined according to guidelines (G‐ID: ferritin <100 ng/ml or ferritin 100–299 ng/ml with transferrin saturation [TSAT] <20%). Alternative ID definitions based on TSAT (<20%), iron (≤13 μmol/L), and ferritin (<100 or < 300 ng/ml) were explored. Relationships with rest/exercise measures of cardiac function and congestion using ultrasound, effort intolerance and adverse outcome (HF hospitalizations or all‐cause mortality) were assessed. Of 1502 patients (72% with left ventricular ejection fraction [LVEF] ≥50%), 471 (31%) had TSAT <20%, while 728 (48%) had G‐ID. Patients with TSAT <20% or G‐ID had greater left atrial volume but similar LVEF. Lower TSAT, iron and haemoglobin, but not ferritin, were associated with more signs of congestion by ultrasound. After correcting for multiple clinical variables, including haemoglobin, TSAT was directly associated with peak oxygen uptake (standardized coefficient 0.069, p = 0.041), while ferritin was not. There was no interaction with HF phenotype (HF with preserved vs. reduced LVEF). During a median follow‐up of 18 months, TSAT <20% and iron ≤13 μmol/L were associated with worse outcomes in models adjusted for clinical variables, including LVEF and N‐terminal pro‐B‐type natriuretic peptide (hazard ratio 2.48, 95% confidence interval 1.88–3.17 and 1.93, 1.48–2.52, respectively), while G‐ID or ferritin <100 or <300 ng/ml were not.In HF outpatients, TSAT <20% is more consistently associated with congestion by ultrasound and poorer functional capacity than other ID definitions, irrespective of LVEF. TSAT <20% and iron ≤13 μmol/L, but not G‐ID or ferritin‐based ID, predict a worse prognosis in HF outpatients with preserved and reduced LVEF. [ABSTRACT FROM AUTHOR]

Dopamine transmission from midbrain ventral tegmental area (VTA) neurons underlies behavioral processes related to motivation and drug addiction. The pedunculopontine tegmental nucleus (PPTg) is a brainstem nucleus containing glutamate-, acetylcholine-, and GABA-releasing neurons with connections to basal ganglia and limbic brain regions. Here we investigated the role of PPTg glutamate neurons in reinforcement, with an emphasis on their projections to VTA dopamine neurons. We used cell-type-specific anterograde tracing and optogenetic methods to selectively label and manipulate glutamate projections from PPTg neurons in mice. We used anatomical, electrophysiological, and behavioral assays to determine their patterns of connectivity and ascribe functional roles in reinforcement. We found that photoactivation of PPTg glutamate cell bodies could serve as a direct positive reinforcer on intracranial self-photostimulation assays. Further, PPTg glutamate neurons directly innervate VTA; photostimulation of this pathway preferentially excites VTA dopamine neurons and is sufficient to induce behavioral reinforcement. These results demonstrate that ascending PPTg glutamate projections can drive motivated behavior, and PPTg to VTA synapses may represent an important target relevant to drug addiction and other mental health disorders.Significance statementUncovering brain circuits underlying reward-seeking is an important step toward understanding the circuit bases of drug addiction and other psychiatric disorders. The dopaminergic system emanating from the ventral tegmental area (VTA) plays a key role in regulating reward-seeking behaviors. We used optogenetics to demonstrate that the pedunculopontine tegmental nucleus sends glutamatergic projections to VTA dopamine neurons, and that stimulation of this circuit promotes behavioral reinforcement. The findings support a critical role for pedunculopontine tegmental nucleus glutamate neurotransmission in modulating VTA dopamine neuron activity and behavioral reinforcement.

BackgroundN-terminal domains of BVU_4064 and BF1687 proteins from Bacteroides vulgatus and Bacteroides fragilis respectively are members of the Pfam family PF12985 (DUF3869). Proteins containing a domain from this family can be found in most Bacteroides species and, in large numbers, in all human gut microbiome samples. Both BVU_4064 and BF1687 proteins have a consensus lipobox motif implying they are anchored to the membrane, but their functions are otherwise unknown. The C-terminal half of BVU_4064 is assigned to protein family PF12986 (DUF3870); the equivalent part of BF1687 was unclassified.ResultsCrystal structures of both BVU_4064 and BF1687 proteins, solved at the JCSG center, show strikingly similar three-dimensional structures. The main difference between the two is that the two domains in the BVU_4064 protein are connected by a short linker, as opposed to a longer insertion made of 4 helices placed linearly along with a strand that is added to the C-terminal domain in the BF1687 protein. The N-terminal domain in both proteins, corresponding to the PF12985 (DUF3869) domain is a β-sandwich with pre-albumin-like fold, found in many proteins belonging to the Transthyretin clan of Pfam. The structures of C-terminal domains of both proteins, corresponding to the PF12986 (DUF3870) domain in BVU_4064 protein and an unclassified domain in the BF1687 protein, show significant structural similarity to bacterial pore-forming toxins. A helix in this domain is in an analogous position to a loop connecting the second and third strands in the toxin structures, where this loop is implicated to play a role in the toxin insertion into the host cell membrane. The same helix also points to the groove between the N- and C-terminal domains that are loosely held together by hydrophobic and hydrogen bond interactions. The presence of several conserved residues in this region together with these structural determinants could make it a functionally important region in these proteins.ConclusionsStructural analysis of BVU_4064 and BF1687 points to possible roles in mediating multiple interactions on the cell-surface/extracellular matrix. In particular the N-terminal domain could be involved in adhesive interactions, the C-terminal domain and the inter-domain groove in lipid or carbohydrate interactions.

Transport systems comprise roughly 10% of all proteins in a cell, playing critical roles in many processes. Improving and expanding their classification is an important goal that can affect studies ranging from comparative genomics to potential drug target searches. It is not surprising that different classification systems for transport proteins have arisen, be it within a specialized database, focused on this functional class of proteins, or as part of a broader classification system for all proteins. Two such databases are the Transporter Classification Database (TCDB) and the Protein family (Pfam) database. As part of a long-term endeavor to improve consistency between the two classification systems, we have compared transporter annotations in the two databases to understand the rationale for differences and to improve both systems. Differences sometimes reflect the fact that one database has a particular transporter family while the other does not. Differing family definitions and hierarchical organizations were reconciled, resulting in recognition of 69 Pfam 'Domains of Unknown Function', which proved to be transport protein families to be renamed using TCDB annotations. Of over 400 potential new Pfam families identified from TCDB, 10% have already been added to Pfam, and TCDB has created 60 new entries based on Pfam data. This work, for the first time, reveals the benefits of comprehensive database comparisons and explains the differences between Pfam and TCDB.