bluuebunny/crossref_metadata_2025 huggingface dataset:
Subcellular activation of β-adrenergic receptors using a spatially restricted antagonist
Authors: Liccardo Federica , Morstein Johannes , Lin Ting-Yu , Pampel Julius , Lang Di , Shokat Kevan M. , Irannejad Roshanak
Published: September 2024

Gprotein-coupled receptors (GPCRs) regulate several physiological and pathological processes and represent the target of approximately 30% of Food and Drug Administration-approved drugs. GPCR-mediated signaling was thought to occur exclusively at the plasma membrane. However, recent studies have unveiled their presence and function at subcellular membrane compartments. There is a growing interest in studying compartmentalized signaling of GPCRs. This requires development of tools to separate GPCR signaling at the plasma membrane from the ones initiated at intracellular compartments. We leveraged the structural and pharmacological information available for β-adrenergic receptors (βARs) and focused on β1AR as exemplary GPCR that functions at subcellular compartments, and rationally designed spatially restricted antagonists. We generated a cell-impermeable βAR antagonist by conjugating a suitable pharmacophore to a sulfonate-containing fluorophore. This cell-impermeable antagonist only inhibited β1AR on the plasma membrane. In contrast, a cell-permeable βAR antagonist containing a nonsulfonated fluorophore efficiently inhibited both the plasma membrane and Golgi pools of β1ARs. Furthermore, the cell-impermeable antagonist selectively inhibited the phosphorylation of PKA downstream effectors near the plasma membrane, which regulate sarcoplasmic reticulum (SR) Ca
2+
release in adult cardiomyocytes, while the β1AR Golgi pool remained active. Our tools offer promising avenues for investigating compartmentalized βAR signaling in various contexts, potentially advancing our understanding of βAR-mediated cellular responses in health and disease. They also offer a general strategy to study compartmentalized signaling for other GPCRs in various biological systems.
Agile working and job satisfaction for localization language agents
Authors: Kassawat Madiha
Published: September 2024

The localization industry has developed at the levels of content, technology and workflow. While agility can describe any virtual job nowadays, its application in localization should be highlighted, since agile working is now widely adopted in developer teams. Job satisfaction has been researched within translation studies, sociology of work and organizational research. This article addresses the impact of agile working in localization, as a virtual and IT-related domain, on the job satisfaction of localization language agents. It is based on a survey and tackles agile working aspects that are relevant to the translation workflow in localization. It also borrows key job satisfaction elements from other domains, which can reveal understudied areas in our domain. The results show, for example, a positive relationship between job satisfaction and in-process and in-team recognition, as well as autonomy. Job satisfaction is lower when there is a lack of context or small-size projects.
Long-Lifetime Optical Trapping of a 40Ca+ Ion
Authors: Chen 陈 Zheng 正 , Wang 王 Miao 淼 , Zhang 张 Baolin 宝林 , Zhang 张 Huaqing 华青 , Ma 马 Zixiao 子晓 , Hu 胡 Ruming 如明 , Huang 黄 Yao 垚 , Gao 高 Kelin 克林 , Guan 管 Hua 桦
Published: September 2024

We have experimentally achieved the all-optical trapping of a 40Ca+ ion. An optical dipole trap was established using a high-power, far-detuned, tightly focused laser with a wavelength of 532 nm. The single 40Ca+ ion was trapped without any RF fields and demonstrated a long lifetime of over 3 s. In this experiment, we implemented several measures to improve the optical trapping probability, including focusing the dipole beam waist near the diffraction limit, precisely compensating for stray electric fields, and mitigating electron shelving in metastable states. The optical trapping of a 40Ca+ ion eliminates the influence of micromotion induced by RF fields, potentially paving the way for development of all-optical trapping ion optical clocks.
Effects of Nb doping on the thermoelectric performance of CuI doped n-type Bi2Te3
Authors: Marekwa Innocent Thato , Kihoi Samuel Kimani , Kahiu Joseph Ngugi , Kim Hyunji , Shin Dong Hyun , Lee Ho Seong
Published: September 2024

The thermoelectric (TE) properties of Nb-doped (CuI)0.003Bi2−x
Nb
x
Te2.7Se0.3 compounds (x = 0, 0.005, 0.01 and 0.03), were investigated at temperatures ranging from 300 to 600 K. Among the compounds studied, the lightly substituted (CuI)0.003Bi1.995Nb0.005Te2.7Se0.3 compound exhibited the best TE performance due to the improvement in its electrical conductivity and its relatively unchanged Seebeck coefficient due to Nb doping. Its figure of merit, ZT, was greater than the undoped (CuI)0.003Bi2Te2.7Se0.3 compound for the temperature range investigated. In particular, the ZT of (CuI)0.003Bi1.995Nb0.005Te2.7Se0.3 reached a value of 0.65 at 448 K in this study.
Percolation network study of highly sensitive buckled elastomeric piezoresistive sensors
Authors: Alidoust Alireza , Ansari Reza , Haghgoo Mojtaba
Published: September 2024

Flexible pressure sensors are needed for future artificial electronic skin applications. Carbon black (CB)-enhanced elastomers are known for their unique conductivity, allowing for special uses in sensor technology. This research analyzes the sensitivity of elastomeric sensors reinforced with CB, under a pre-strained buckle, using a modified percolation network model to enhance performance in sensing applications. The finite element method is employed to analyze the piezoresistive characteristics of the sensors across various thicknesses. The research involves analyzing the strain patterns of buckled piezoresistive sensors when an indenter applies a load, and how this influences the sensors’ resistivity. The mechanical parameter is directly correlated to the sensor sensitivity through the maximum principal strain. The model shows a good agreement with the experimental data. The pressure sensitivity resulting from indenter compressive contact is 0.03 and 0.0061 kPa−1 in the pressure range of 0–1 and 0–5 kPa for wavy and straight 1000 μm buckled sensors, respectively. The results show that the film with 50% taller waves has a 40%–60% narrower pressure sensing ranges. Moreover, results indicate that adding waves to the geometry of the sensor improves the piezoresistive behavior by increasing the relative displacements of edges. Results also reveal more stable performance from fewer waves and a higher working range by thicker sensors.
Damage sensing in multi-functional nanocomposite polymer bonded energetics with embedded multi-walled carbon nanotube sensing networks
Authors: Shirodkar Nishant , Talluru Viswajit , Seidel Gary D
Published: September 2024

This experimental investigation evaluates the strain and damage sensing abilities of multi-walled carbon nanotube (MWCNT) networks embedded in the binder phase of polymer-bonded energetics (PBEs). PBEs are a special class of particulate composite materials that consist of energetic crystals bound by a polymer matrix, wherein the polymer matrix serves to maintain the composite’s shape and form. The structural health monitoring (SHM) approach presented in this work exploits the piezoresistive properties of the distributed MWCNT networks. Major challenges faced during such implementation include the low binder concentrations of PBEs, the presence of conductive/non-conductive particulate phases, the high degree of heterogeneity in the PBE microstructure, and achieving the optimal MWCNT dispersion. In this study, ammonium perchlorate (AP) crystals as the oxidizer, Aluminum grains as the metallic fuel, and Polydimethylsiloxane (PDMS) as the binder are used as the constituents for fabricating PBEs. To study the effect of each constituent on the MWCNT network’s SHM abilities, various materials systems are comprehensively studied: MWCNT/PDMS materials are first evaluated to study the binder’s electromechanical response, followed by AP/MWCNT/PDMS to assess the impact of AP addition, and finally, AP/AL/MWCNT/PDMS to evaluate the impact of adding conductive aluminum grains. Compression samples (ASTM D695) were fabricated and subjected to monotonic compression. Electrical resistance is recorded in conjunction with the mechanical test via an LCR meter. Gauge factors relating to the change in normalized resistance to applied strain are calculated to quantify the electromechanical response. MWCNT dispersions and mechanical failure modes are analyzed via scanning electron microscopy imaging of the fracture surfaces. Correlations between the electrical behavior in response to the mechanical behavior are presented, and possible mechanisms that influence the electromechanical behavior are discussed. The results presented herein demonstrate the successful ability of MWCNT networks as SHM sensors capable of real-time strain and damage assessment of PBEs.
System identification and landscape stability of stochastic competition ecosystem
Authors: Zhang Hongxia , Lei Youming , Xu Wei
Published: September 2024

Motivated by the challenging issue in analyzing the stochastic stability from observed state time series in a competition ecosystem, we take a systematic study from system identification to landscape stability. The vector field manifold is utilized to discuss dynamic properties of the deterministic competition ecosystem. For the stochastic state time series, we integrate the stochastic Koopman operator, the Kolmogorov backward equation and the extended dynamic mode decomposition methods to approximate the drift expression, while the Kramers–Moyal formula is used to identify the noise intensity. The depth and width indicators of the energy landscape are constructed to verify the effectiveness of the system identification method and to examine the impact of noise on system stability. Results demonstrate that proposed indicators can effectively assess the stochastic stability. Moreover, we find the environmental disturbance can induce global instability of the stochastic competition system, but its relative stability impact on each potential well will be altered by species competitiveness.
Towards sustainable built environment: learning from socio-economic characteristics, housing norms and satisfactions of three settlement patterns in Semarang City, Indonesia
Authors: Manaf Asnawi , Irwansyah Mirza
Published: September 2024

his article presents the results of a comparative study of socio-economic characteristics, housing norms, and satisfaction of low-income families living in three different settlement patterns as a perspective toward the sustainable built environment in Semarang City, Indonesia. The research used the survey method to examine households living in Kaligawe low-cost rental flats, informal settlements, and landed houses near the Kaligawe flats. Data were obtained by distributing questionnaires to 97 respondents selected using a simple random sampling technique. The findings indicated that although respondents showed differences in housing satisfaction (performance) and housing deficits, they showed similarities in housing norms (importance). Thus, although their socioeconomic characteristics were generally different, their housing norms were similar. Based on an importance-performance analysis, the study offers recommendations regarding which aspects of housing and residential environments should be prioritized to support a sustainable housing-built environment. This study encourages policy-makers to prioritize aspects of the dwelling unit’s physical condition and the neighborhood environment’s livability in improving the quality of low-income housing in Semarang. The current study provides evidence of the complexity of the housing strategies used by households to meet their housing needs, especially in affordable housings. This is closely related to socio-economic characteristics, which is delve into sustainable built environment.
Exploring the opportunities for biophilic design application in urban pedestrian environments in China under the context of climate change: a perspective of affective experience
Authors: Li Kunyu , Abidin Nor Arbina Zainal , Mohamad Diana
Published: September 2024

Rapid urbanization has led to the urban heat island effect (UHI), exacerbating cities’ extreme temperatures and air pollution, thereby threatening residents’ well-being. To address this issue, many countries are utilizing green infrastructure to improve urban walking environments, promote walking, mitigate climate change, and reduce the impact of UHI. However, pedestrian landscape design often overlooks residents’ emotional needs and experiences. Biophilic Design (BD) offers a solution by promoting positive interactions between people and nature in urban environments, enhancing residents’ emotional connection with nature. This paper, focusing on densely populated and highly urbanized China, employs systematic literature review and text analysis methods to summarize affective experiential (AE) factors that positively influence residents’ walking intentions and corresponding environmental and landscape features. Based on this, a preliminary framework for applying Biophilic Design in urban pedestrian environments is proposed, aiming to provide scientific guidance for developing Biophilic Pedestrian Landscape Design (BPLD) schemes to enhance residents’ willingness to walk. Although specific guidelines for implementing biophilic walking landscapes in urban environments are lacking, their potential to improve urban livability and residents’ well-being is evident.
Micro, small, and medium enterprises (MSME) to promote sustainability of urban kampongs and cultural landscape in Semarang City-Indonesia: an examination on the typology
Authors: Sundaro Hendrianto , Rudiarto Iwan , Handayani Wiwandari , Febriyanto Ahady Farrel
Published: September 2024

Urban Kampongs are a typical settlement characterized by high density and poor infrastructure facilities in many developing countries, including Indonesia. The inhabitants are known to have strong social cohesion and kindship. In Semarang, the kampongs are widely spread in city centers. Located in the city hotspot, its existence is threatened, replaced by various commercial and modern urban activities. On the other hand, the increasingly massive development of the city offers opportunities to further strengthen the existence of urban kampong through strengthening the MSMEs, promoting the city with more locally based economic activities. Accordingly, sufficient comprehension of the kampong characteristics is needed mainly to maintain sustainability landscape and cultural urban kampong. This research aims to examine the typology of MSME-based urban kampongs in Semarang City. Overlay and density analyses are used to determine the location of MSME-based urban kampongs, while descriptive analysis is used to further explore the typology, which is linked to MSME activities in production and location aspects. The research results show three typologies of MSMEs-based urban kampongs in Semarang City: 1) Culinary kampongs, 2) Warungan kampongs, and 3) Groceries kampongs. These typologies can provide a better understanding of promoting the sustainability of urban kampongs and cultural landscapes.
Experimenting ‘gentle density’: using plot sizing tool to blend missing middle housing into existing neighborhoods in Tanah Abang TOD
Authors: Wellsan A , Harianto D J
Published: September 2024

Jakarta’s rapid growth and urbanization necessitate urgent demand for affordable housing that is well-connected to public transport and access to basic amenities. The lack of housing diversity poses challenges to sustainable urban growth, exacerbates traffic congestion, and limits housing choices. This research addresses the urgency of experimenting with density in Jakarta’s existing neighborhoods in the TOD area by focusing on the constraints depicted by existing regulatory frameworks, zoning restrictions, and potential community resistance. With Tanah Abang TOD as a pilot project, this paper outlines an approach to produce the most optimal design with parametric software of Rhino and Grasshopper ecosystem to compute various typologies of Missing Middle Housing in existing neighborhoods. While the computational ecosystem measures the performance of the design iterations, several dimensionalities are displayed in service coverage from transportation nodes, visibility index among the human visibility field, and cost affordability through the estimated cost of development. Ultimately, the methodology this paper provides can be also experimented with in other places with similar urban structures.
AI-enhanced smart urban design process for salutogenic residential area: the case of Capital City of Nusantara (IKN)
Authors: Gunawan Kelvin N. , Kartikasari Damara , Gumilar Jasin , Nolasari Annisa B. , Sugangga Marisa
Published: September 2024

Urban areas play a crucial role as a space that fulfills the human basic needs and activities, including providing healthy and suitable living environments for its inhabitants. However, future challenges facing cities have the potential to render cities increasingly uninhabitable, thereby threatening both the health and sustainability of their environment. This research aims to develop the design of residential areas with an emphasis on environmental feasibility and health through a salutogenic approach. In addition, this research also identifies AI methods and approaches in the urban design process to achieve salutogenic approaches. Research method in this research utilizes exploratory qualitative approach and literature review to understand the principles of design with a salutogenic approach and uncover the potential of contemporary AI in urban design. Conducted within the Residential Area of Ibu Kota Nusantara (IKN), the research shows AI accelerates the design process using a salutogenic approach, supporting Indonesia’s Smart and Sustainable Forest City concept. The design concept is termed “Toward Tomorrow’s Sanctuary,” encompassing four main missions: sustainability, humans, nature, and technology. The design output features biomimetic and vernacular building concepts, a 10-minute city with multilevel pedestrian circulation, and green infrastructure with renewable energy sources. While AI significantly contributes to the urban design process, the importance of human considerations remains the primary focus. This will ensure that the design outcomes align with expectations, local contexts, and considerations of ethical aspects.
Community-based environment and natural resources management: case of Parangtritis disaster resilient village
Authors: Yusrinawati Chafda , Damayanti Maya
Published: September 2024

Management of the environment and natural resources is a strategic key to reducing the risk of disasters as environmental problems and natural disasters are related to each other. This strategic key is implemented through active community participation in line with the Disaster Resilient Village program. Hence, this study aims to identify the community efforts to manage the environment and natural resources in the case of Parangtritis as one of the Main Resilient Villages (the highest level) in Bantul Regency. This research uses a quantitative descriptive approach by collecting data through document review, interviews, and questionnaires. The population studied was 97 people who were members of the Paris Resilience using census sampling techniques. The results of this study show that community efforts are realized in coastal area reforestation activities, drainage construction, dams and river embankments, river normalization, and waste bank management. The community actively participates in the form of manpower, opinions, and skills/expertise. It is expected that the results of this research can be a lesson for other disaster-resilient villages that are in the early stages of managing natural resources and the environment to reduce the risk of disasters for the community.
Photodegradation of RB5 dye with modified zeolites: influence of temperature and UV irradiation
Authors: Sánchez-Viveros José Manuel , Petranovskii Vitalii , Tlacuatl Gregorio Zacahua , Lara Hernández Minerva , Chávez–Rivas Fernando , Falcony–Guajardo Ciro , Espinoza–Tapia Julio César
Published: September 2024

This study explores the photocatalytic degradation of Reactive Black 5 (RB5) dye using thermally modified natural zeolites, aiming to improve water purification methods. Zeolites were calcined at 250 °C, 350 °C, and 500 °C, and characterized through x–ray diffraction (XRD), Scanning Electron Microscopy (SEM), and Fourier Transform Infrared Spectroscopy (FTIR) to analyze their structural and morphological transformations. The results reveal that calcination significantly enhances the photocatalytic performance, particularly for ZNM500, which exhibited the highest efficiency, reaching a 60% removal rate of RB5. The degradation process follows a pseudo-first-order kinetic model at lower dye concentrations but adheres more closely to the Langmuir–Hinshelwood equation at higher concentrations, emphasizing the role of surface adsorption in catalysis. UV irradiation was a key factor in boosting reaction rates, with shorter wavelengths (254 nm) providing greater energy, leading to more effective dye breakdown by facilitating the generation of reactive hydroxyl radicals (·OH). These findings suggest that thermally modified zeolites, especially ZNM500, represent a promising solution for wastewater treatment, offering an efficient, cost–effective, and environmentally friendly approach to removing synthetic dyes from contaminated water sources.
Energy-dependent barren plateau in bosonic variational quantum circuits
Authors: Zhang Bingzhi , Zhuang Quntao
Published: September 2024

Bosonic variational quantum circuits (VQCs) are crucial for information processing in microwave cavities, trapped ions, and optical systems, widely applicable in quantum communication, sensing and error correction. The trainability of such VQCs is less understood, hindered by the lack of theoretical tools such as t-design due to the infinite dimension of the continuous-variable systems involved. We overcome this difficulty to reveal an energy-dependent barren plateau in such VQCs. The variance of the gradient decays as

1

/

E

M
ν

, exponential in the number of modes M but polynomial in the (per-mode) circuit energy E. The exponent ν = 1 for shallow circuits and ν = 2 for deep circuits. We prove these results for state preparation of general Gaussian states and number states. We also provide numerical evidence demonstrating that the results extend to general state preparation tasks. As circuit energy is a controllable parameter, we provide a strategy to mitigate the barren plateau in bosonic continuous-variable VQCs.
The variability and predictability of summer southwest monsoon intensity measurement index across mainland indochina: from local synoptic to large scale perspectives
Authors: Oo Kyaw Than , Dong Yinshuo , Jonah Kazora
Published: September 2024

The mainland Indochina Southwest Monsoon (MSwM) is a crucial climatic phenomenon in Southeast Asia, significantly influencing the climate of countries such as Myanmar, Bangladesh, Thailand, Laos, and Southwest China. Traditionally, the intensity of the MSwM has been challenging to quantify due to its complex nature. This study introduces a new Southwest Monsoon Intensity Index (SMII), based on sea level pressure (SLP), which offers a more comprehensive understanding of the monsoon’s intraseasonal to interannual variability and its associated climate anomalies. The SMII is designed to overtake the limitations of local indices, which often rely on data from only two costal stations and may lack the resolution necessary for seasonal outlooks or long-term forecast modeling. By considering both south-north and west-east annual dominant pressure field gradients, the SMII provides a more robust measure of monsoon intensity. This large-scale index is influenced by key pressure systems, such as the Tibet Low and the Mascarenes High, and is characterized by the movement of a concentrated north-south rain belt and a quasi-stationary low-level jet. Our analysis reveals strong correlations between the SMII and regional rainfall patterns, particularly during the peak intensity of the summer months. Additionally, significant associations with El Niño Southern Oscillation (ENSO) indices and the eastern Indian Ocean suggest potential teleconnections, which can enhance predictive capabilities. This improved index is crucial for operational climate centers to monitor and predict monsoon behavior effectively, ultimately aiding in the forecasting and managing the MSwM’s socio-economic impacts.
Novel plant extract-chitosan nanocomposite (SCE/ChNPs) biosensor for trace level arsenic sensing in water samples using quartz crystal microbalance with dissipation monitoring
Authors: Siddiq Miad Ali
Published: September 2024

This study introduces a novel green biosensor for ultra-low arsenic detection in water, combining Saussurea costus ethanolic extract (SCE) with chitosan nanoparticles (ChNPs) in a Quartz Crystal Microbalance with Dissipation monitoring (QCM-D) system. The SCE/ChNPs were characterized using AFM, SEM, TEM, DLS, and zeta potential measurements, revealing a mean particle size of 37.0 ± 2.0 nm, spherical morphology, and a stable colloidal system with −28.3 mV surface charge. The QCM-D-based biosensor demonstrated exceptional performance with a detection limit of 0.05 ppb, significantly below the WHO guideline for arsenic in drinking water. It exhibited a linear response from 0.1 to 10 ppb (R2 = 0.99) and high selectivity against potential interferents. The sensor showed a rapid 10 s response time and maintained stability over five adsorption–desorption cycles. Validation in spiked tap water samples yielded results comparable to ICP spectroscopy, confirming the sensor’s applicability in complex matrices. This eco-friendly approach offers advantages over conventional methods, including high sensitivity, rapid response, and potential for on-site analysis. The synergistic combination of plant extract and biodegradable nanoparticles presents a sustainable solution for heavy metal sensing. Further research on long-term stability and field testing could lead to practical tools for monitoring arsenic contamination in water resources, contributing to public health and environmental safety.
Evaluating the levelized costs and life cycle greenhouse gas emissions of electricity generation from rooftop solar photovoltaics: a Swiss case study
Authors: Zhang Xiaojin , Walch Alina , Rüdisüli Martin , Bauer Christian , Burgherr Peter , McKenna Russell , Habert Guillaume
Published: September 2024

The transition to renewable energy sources is pivotal in addressing global climate change challenges, with rooftop solar photovoltaic (PV) systems playing a crucial role. For informed decision-making in energy policy, it is important to have a comprehensive understanding of both the economic and environmental performance of rooftop solar PV. This study provides a high-resolution analysis of existing rooftop solar PV systems in Switzerland by assessing the robustness of the potential estimation to properly derive the amount of electricity generated by individual systems, and subsequently quantify the levelized cost of electricity and life cycle greenhouse gas (GHG) emissions of electricity generation from PV and compare them with those of grid electricity supplies. Our results indicate substantial geographical variations between potential estimations and real-world installations, with notable underestimations of approximately 1.3 Gigawatt-peak, primarily for systems around 10 kWp in size, mainly due to the quality of input data and conservative estimation. The study finds that in many regions and for most of the installed capacity, electricity generated from rooftop PV systems is more economical than the grid electricity supply, mainly driven by factors including high electricity prices, larger installations and abundant solar irradiance. The GHG emissions assessment further emphasizes the importance of methodological choice, with stark contrasts between electricity certificate-based approaches and others that are based on the consumption mix. This study suggests the need for more accurate geographical potential estimations, enhanced support for small-scale rooftop PV systems, and more incentives to maximize the potential of their roof area for PV deployment. As Switzerland progresses towards its renewable energy goals, our research underscores the importance of informed policymaking based on a retrospective analysis of existing installations, essential for maximizing the potential and benefits of rooftop solar PV systems.
ASHP and ASHP Foundation Pharmacy Forecast 2025: Strategic Planning Guidance for Pharmacy Departments in Hospitals and Health Systems
Authors: DiPiro Joseph T , Hoffman, James M , Tichy Eric , Shea Suzanne , Sanborn Michael , Hung Anna , Fox Erin R , Watanabe Jonathan H , Torrise Virginia , Abourjaily Paul , Cunningham Francesca E , Schweitzer Pamela , Nelson Scott D , Stump Lisa S , Castro Harvey , Nesbit Todd W , Scott Christopher M
Published: September 2024

Purpose

The 2025 ASHP Pharmacy Forecast report is written to identify and contextualize emerging trends that will influence healthcare, health systems, and the pharmacy profession. It provides recommendations to inform strategic planning that should prompt action by pharmacists and health-system leaders.

Methods

Drawing on the “wisdom of crowds” concept, a survey was constructed by an advisory committee with 6 themes, each with 7 focused statements and a seventh theme on preparedness (54 survey items in total). A survey panel of 321 pharmacy leaders was purposefully designed to capture opinions from a wide range of pharmacists across the United States. Panelists were asked to consider the likelihood of the statements occurring in the next 5 years as being likely, somewhat likely, somewhat unlikely, or very unlikely to occur. Forecast panelists also assessed health systems’ preparedness (from very unprepared to very prepared) for 12 of the statements.

Results

The 6 survey themes identified were The Business of Healthcare: Challenges in Health-System Pharmacy, Managing Ultra-High-Cost Drugs, Addressing the Gap in Primary Care, Whole Person Health, Navigating Generative Artificial Intelligence: Opportunity and Risk, and Stabilizing the Pharmacy Workforce. The survey was completed by 269 respondents, yielding an 84% response rate. Descriptive statistics of the survey results were provided to chapter authors to inform commentary and strategic recommendations for each theme.

Conclusion

The Pharmacy Forecast provides insights on large-scale, long-term trends that will influence healthcare and the pharmacy profession over the years ahead. Insight from the report can stimulate strategic thinking and provides a starting point to proactively position leaders, their teams, and departments for potential future trends.
DGCL: dual-graph neural networks contrastive learning for molecular property prediction
Authors: Jiang Xiuyu , Tan Liqin , Zou Qingsong
Published: September 2024

In this paper, we propose DGCL, a dual-graph neural networks (GNNs)-based contrastive learning (CL) integrated with mixed molecular fingerprints (MFPs) for molecular property prediction. The DGCL-MFP method contains two stages. In the first pretraining stage, we utilize two different GNNs as encoders to construct CL, rather than using the method of generating enhanced graphs as before. Precisely, DGCL aggregates and enhances features of the same molecule by the Graph Isomorphism Network and the Graph Attention Network, with representations extracted from the same molecule serving as positive samples, and others marked as negative ones. In the downstream tasks training stage, features extracted from the two above pretrained graph networks and the meticulously selected MFPs are concated together to predict molecular properties. Our experiments show that DGCL enhances the performance of existing GNNs by achieving or surpassing the state-of-the-art self-supervised learning models on multiple benchmark datasets. Specifically, DGCL increases the average performance of classification tasks by 3.73$\%$ and improves the performance of regression task Lipo by 0.126. Through ablation studies, we validate the impact of network fusion strategies and MFPs on model performance. In addition, DGCL’s predictive performance is further enhanced by weighting different molecular features based on the Extended Connectivity Fingerprint. The code and datasets of DGCL will be made publicly available.
CMFHMDA: a prediction framework for human disease-microbe associations based on cross-domain matrix factorization
Authors: Chen Jing , Tao Ran , Qiu Yi , Yuan Qun
Published: September 2024

Predicting associations between microbes and diseases opens up new avenues for developing diagnostic, preventive, and therapeutic strategies. Given that laboratory-based biological tests to verify these associations are often time-consuming and expensive, there is a critical need for innovative computational frameworks to predict new microbe–disease associations. In this work, we introduce a novel prediction algorithm called Predicting Human Disease-Microbe Associations using Cross-Domain Matrix Factorization (CMFHMDA). Initially, we calculate the composite similarity of diseases and the Gaussian interaction profile similarity of microbes. We then apply the Weighted K Nearest Known Neighbors (WKNKN) algorithm to refine the microbe–disease association matrix. Our CMFHMDA model is subsequently developed by integrating the network data of both microbes and diseases to predict potential associations. The key innovations of this method include using the WKNKN algorithm to preprocess missing values in the association matrix and incorporating cross-domain information from microbes and diseases into the CMFHMDA model. To validate CMFHMDA, we employed three different cross-validation techniques to evaluate the model’s accuracy. The results indicate that the CMFHMDA model achieved Area Under the Receiver Operating Characteristic Curve scores of 0.9172, 0.8551, and 0.9351$\pm $0.0052 in global Leave-One-Out Cross-Validation (LOOCV), local LOOCV, and five-fold CV, respectively. Furthermore, many predicted associations have been confirmed by published experimental studies, establishing CMFHMDA as an effective tool for predicting potential disease-associated microbes.
How pairs of insertion mutations impact protein structure: an exhaustive computational study
Authors: Li Changrui , Zheng Yang , Jagodzinski Filip
Published: September 2024

Understanding how amino acid insertion mutations affect protein structure can inform pharmaceutical efforts targeting diseases that are caused by protein mutants. In silico simulation of mutations complements experiments performed on physical proteins which are time and cost prohibitive. We have computationally generated the exhaustive sets of two amino acid insertion mutations for five protein structures in the Protein Data Bank. To probe and identify how pairs of insertions affect structural stability and flexibility, we tally the count of hydrogen bonds and analyze a variety of metrics of each mutant. We identify hotspots where pairs of insertions have a pronounced effect, and study how amino acid properties such as size and type, and insertion into alpha helices, affect a protein’s structure. The findings show that although there are some residues, Proline and Tryptophan specifically, which if inserted have a significant impact on the protein’s structure, there is also a great deal of variance in the effects of the exhaustive insertions both for any single protein, and across the five proteins. That suggests that computational or otherwise quantitative efforts should consider large representative sample sizes especially when training models to make predictions about the effects of insertions.

Availability and implementation

The data underlying this article is available at https://multimute.cs.wwu.edu.
Chronogram: an R package for data curation and analysis of infection and vaccination cohort studies
Authors: Greenwood David , Shawe-Taylor Marianne , Townsley Hermaleigh , Gahir Joshua , Sahadeo Nikita , Alhassan Yakubu , Chaloner Charlotte , Galgut Oliver , Kelly Gavin , Bauer David L V , Wall Emma C , Wu Mary Y , Carr Edward J
Published: September 2024

Motivation

Observational cohort studies that track vaccine and infection responses offer real-world data to inform pandemic policy. Translating biological hypotheses, such as whether different patterns of accumulated antigenic exposures confer differing antibody responses, into analysis code can be onerous, particularly when source data is dis-aggregated.

Results

The R package chronogram introduces the class chronogram, where metadata is seamlessly aggregated with sparse infection episode, clinical and laboratory data. Each experimental modality is added sequentially, allowing the incorporation of new data, such as specialized time-consuming research assays, or their downstream analyses. Source data can be any rectangular data format, including database tables (such as structured query language databases). This supports annotations that aggregate data types/sources, for example, combining symptoms, molecular testing, and sequencing of one or more infectious episodes in a pathogen-agnostic manner. Chronogram arranges observational data to allow the translation of biological hypotheses into their corresponding code via a shared vocabulary.

Availability and implementation

Chronogram is implemented R and available under an MIT licence at: https://www.github.com/FrancisCrickInstitute/chronogram; a user manual is available at: https://franciscrickinstitute.github.io/chronogram/
Neoadjuvant therapy versus upfront surgery in resectable pancreatic cancer: reconstructed patient-level meta-analysis of randomized clinical trials
Authors: Aliseda Daniel , Martí-Cruchaga Pablo , Zozaya Gabriel , Blanco Nuria , Ponz Mariano , Chopitea Ana , Rodríguez Javier , Castañón Eduardo , Pardo Fernando , Rotellar Fernando
Published: September 2024

Background

Neoadjuvant treatment has shown promising results in patients with borderline resectable pancreatic ductal adenocarcinoma. The potential benefits of neoadjuvant treatment on long-term overall survival in patients with resectable pancreatic ductal adenocarcinoma have not yet been established. The aim of this study was to compare long-term overall survival of patients with resectable pancreatic ductal adenocarcinoma based on whether they received neoadjuvant treatment or underwent upfront surgery.

Methods

A systematic review including randomized clinical trials on the overall survival outcomes between neoadjuvant treatment and upfront surgery in patients with resectable pancreatic ductal adenocarcinoma was conducted up to 1 August 2023 from PubMed, MEDLINE and Web of Science databases. Patient-level survival data was extracted and reconstructed from available Kaplan–Meier curves. A frequentist one-stage meta-analysis was employed, using Cox-based models and a non-parametric method (restricted mean survival time), to assess the difference in overall survival between groups. A Bayesian meta-analysis was also conducted.

Results

Five randomized clinical trials comprising 625 patients were included. Among patients with resectable pancreatic ductal adenocarcinoma, neoadjuvant treatment was not significantly associated with a reduction in the hazard of death compared with upfront surgery (shared frailty HR 0.88, 95% c.i. 0.72 to 1.08, P = 0.223); this result was consistent in the non-parametric restricted mean survival time model (+2.41 months, 95% c.i. −1.22 to 6.04, P < 0.194), in the sensitivity analysis that excluded randomized clinical trials with a high risk of bias (shared frailty HR 0.91 (95% c.i. 0.72 to 1.15; P = 0.424)) and in the Bayesian analysis with a posterior shared frailty HR of 0.86 (95% c.i. 0.70 to 1.05).

Conclusion

Neoadjuvant treatment does not demonstrate a survival advantage over upfront surgery for patients with resectable pancreatic ductal adenocarcinoma.
Intergenerational Care and Subjective Well-being: A Study of the Particularities of Ageing Amongst the Indigenous Peoples of Chile
Authors: Valencia-Gálvez Lorena , Gallardo-Peralta Lorena , Andrade-Guzmán Carlos , Rain-Rain Alicia , Rodriguez-Venegas Viviana
Published: September 2024

This empirical study explores intergenerational caregiving and subjective well-being amongst older adults in Indigenous communities in rural Chile. Facing substantial social and economic challenges, these communities depend heavily on cultural traditions and family support systems. Data were collected from 1,348 older adults, aged sixty and above, using surveys to assess caregiving practices, intergenerational support and subjective well-being, measured by the Personal Wellbeing Index and the Perceived Social Support Questionnaire. Findings reveal that caregiving is deeply rooted in cultural and historical contexts, with positive aspects such as increased satisfaction and social connectedness, and negative aspects including stress and social isolation. Women predominantly assume caregiving roles, maintaining cultural traditions and supporting family well-being. Notable differences in intergenerational support and subjective well-being were observed based on ethnic group and gender. The implications for social work practice are insightful. The study highlights the need for culturally sensitive social work policies and inclusive strategies that address the well-being of older adults in these communities. Social workers and policymakers must consider cultural nuances and the unique needs of Indigenous populations, taking into account cultural identity, economic conditions and acculturation to develop effective support programmes.
Synthesis and characterization of a chiral spirobifluorene cyclic hexamer
Authors: Kobayashi Seika , Nakazono Rina , Okada Rikito , Schramm Michael P , Amaya Toru
Published: September 2024

A new chiral macrocycle 1-[6], consisting of six chiral spirobifluorene units linked in a cyclic arrangement, was successfully synthesized via a homo-coupling of the corresponding acyclic trimer. Notably, this chiral cyclic hexamer exhibited flexibility in solution, and both low-temperature nuclear magnetic resonance (NMR) experiments and density functional theory (DFT) calculations suggest that its stable structure is not the hexagonal D6-symmetric structure but rather the figure-eight-shaped D2-symmetric structure. In this D2-symmetric structure, the opposing bifluorenyl units are π-stacked, and it is suggested that this π-stacked region undergoes rapid dissociation and reformation at room temperature. The HOMO is distributed over the π-stacked region, with a HOMO-LUMO gap of 4.02 eV. The macrocycle exhibited strong violet fluorescence. The absorption dissymmetry factor |gabs| was 7.4 × 10−3, which is larger compared to the series of chiral smaller macrocycles 1-[n] (n = 3 to 5). Additionally, the CPL efficiency, indicated by a BCPL value of 189 M−1 cm−1, is relatively high among chiral organic luminescent molecules.
Determination of adsorption capacity, regeneration ability, and aggregation tendency toward inorganic and organic pollutants of metal-doped carbon–silica composites in multicomponent systems
Authors: Medykowska Magdalena , Wiś niewska Małgorzata , Szewczuk-Karpisz Katarzyna
Published: September 2024

The main aim of the study was to develop a method for determining the adsorption capacity, regeneration ability, and aggregation tendency of metal-doped carbon–silica composites (iron-doped, C/Fe/SiO2, and manganese-doped, C/Mn/SiO2) against heavy metals and selected organic substances. The properties of these composites were compared with those of metal-free silica–carbon composite (C/SiO2). Inductively coupled plasma–optical emission spectrometry (ICP–OES) and high-pressure liquid chromatography were used to determine the adsorbed amounts and the desorption degree of organic/inorganic pollutants. Potentiometric titrations and electrophoretic mobility measurements were conducted to understand the mechanisms that were driving adsorption and particle aggregation. The size of the aggregates formed in the systems as well as the stability of the examined suspension were estimated by using ultraviolet-visible spectrophotometry. The performed experiments showed that the selected combination of methods is appropriate to determine the potential of metal-doped carbon–silica composites as adsorbents as well as the ease of their removal with adsorbed contaminants from aqueous solutions by sedimentation.
Lymphangiogenesis: novel strategies to promote cutaneous wound healing
Authors: Jian Yang , Li Yanqi , Zhang Yanji , Tang Mingyuan , Deng Mingfu , Liu Chenxiaoxiao , Cheng Maolin , Xiao Shune , Deng Chengliang , Wei Zairong
Published: September 2024

The cutaneous lymphatic system regulates tissue inflammation, fluid balance and immunological responses. Lymphangiogenesis or lymphatic dysfunction may lead to lymphedema, immune deficiency, chronic inflammation etc. Tissue regeneration and healing depend on angiogenesis and lymphangiogenesis during wound healing. Tissue oedema and chronic inflammation can slow wound healing due to impaired lymphangiogenesis or lymphatic dysfunction. For example, impaired lymphangiogenesis or lymphatic dysfunction has been detected in nonhealing wounds such as diabetic ulcers, venous ulcers and bedsores. This review summarizes the structure and function of the cutaneous lymphatic vessel system and lymphangiogenesis in wounds. Furthermore, we review wound lymphangiogenesis processes and remodelling, especially the influence of the inflammatory phase. Finally, we outline how to control lymphangiogenesis to promote wound healing, assess the possibility of targeting lymphangiogenesis as a novel treatment strategy for chronic wounds and provide an analysis of the possible problems that need to be addressed.
Left motor cortex contributes to auditory phonological discrimination
Authors: Perron Maxime , Ross Bernhard , Alain Claude
Published: September 2024

Evidence suggests that the articulatory motor system contributes to speech perception in a context-dependent manner. This study tested 2 hypotheses using magnetoencephalography: (i) the motor cortex is involved in phonological processing, and (ii) it aids in compensating for speech-in-noise challenges. A total of 32 young adults performed a phonological discrimination task under 3 noise conditions while their brain activity was recorded using magnetoencephalography. We observed simultaneous activation in the left ventral primary motor cortex and bilateral posterior–superior temporal gyrus when participants correctly identified pairs of syllables. This activation was significantly more pronounced for phonologically different than identical syllable pairs. Notably, phonological differences were resolved more quickly in the left ventral primary motor cortex than in the left posterior–superior temporal gyrus. Conversely, the noise level did not modulate the activity in frontal motor regions and the involvement of the left ventral primary motor cortex in phonological discrimination was comparable across all noise conditions. Our results show that the ventral primary motor cortex is crucial for phonological processing but not for compensation in challenging listening conditions. Simultaneous activation of left ventral primary motor cortex and bilateral posterior–superior temporal gyrus supports an interactive model of speech perception, where auditory and motor regions shape perception. The ventral primary motor cortex may be involved in a predictive coding mechanism that influences auditory-phonetic processing.