bluuebunny/crossref_metadata_2025 huggingface dataset:
TESTING THE USE OF XRCC6 GENE IN PHYLOGENETIC ANALYSES
Authors: Çelik Recep
Published: July 2024

In this study, we investigated the potential use of the XRCC6 gene in the construction of phylogenetic trees used to visualise evolutionary relationships among species. XRCC6 gene is an important evolutionarily conserved gene that plays a role in DNA repair processes [1, 2]. The phylogenetic tree constructed with the XRCC6 gene using the Neighbour-Joining (NJ) algorithm was compared with the phylogenetic tree previously constructed with the UPGMA algorithm using mtDNA sequences. As a result of the comparison, it was observed that the trees constructed by both algorithms overlapped to a great extent in terms of topological similarity, support values of branches and species position. These findings indicate that XRCC6 gene can be used as a reliable genetic marker in phylogenetic analyses. The use of XRCC6 gene in phylogenetic analyses may contribute to a more comprehensive and accurate understanding of evolutionary relationships.
Temporal asymmetry of neural representations predicts memory decisions
Authors: Ye Zhifang , Zhao Yufei , Allen Emily J. , Naselaris Thomas , Kay Kendrick , Hutchinson J. Benjamin , Kuhl Brice A.
Published: July 2024

A stimulus can be familiar for multiple reasons. It might have been recently encountered, or is similar to recent experience, or is similar to ‘typical’ experience. Understanding how the brain translates these sources of similarity into memory decisions is a fundamental, but challenging goal. Here, using fMRI, we computed neural similarity between a current stimulus and events from different temporal windows in the past and future (from seconds to days). We show that trial-by-trial memory decisions (is this stimulus ‘old’?) were predicted by thedifferencein similarity to past vs. future events (temporal asymmetry). This relationship was (i) evident in lateral parietal and occipitotemporal cortices, (ii) strongest when considering events from the recent past (minutes ago), and (iii) most pronounced when veridical (true) memories were weak. These findings suggest a new perspective in which the brain supports memory decisions by comparing what actually occurred to what is likely to occur.
Social Decision Preferences for Close Others are Embedded in Neural and Linguistic Representations
Authors: Guassi Moreira João F. , Esparza L. Concepción , Silvers Jennifer A. , Parkinson Carolyn
Published: July 2024

Humans frequently make decisions that impact close others. Prior research has shown that people have stable preferences regarding such decisions and maintain rich, nuanced mental representations of their close social partners. Yet, if and how such mental representations shape social decisions preferences remains to be seen. Using a combination of functional magnetic resonance imaging (fMRI) and natural language processing (NLP), this study investigated how neural and linguistic representations of close others influence social decision-making. Participants nominated a parent and a friend, rated their characteristics, and made hypothetical social decisions while undergoing fMRI. Neural representations of parents and friends, relative to the self, predicted social decision preferences. Specifically, greater neural similarity between self and parent in the temporoparietal junction (TPJ) and nucleus accumbens (NAcc) was associated with a preference for parents, while greater self-friend similarity in the medial prefrontal cortex (mPFC) predicted friend-preference. Additionally, linguistic analysis of written descriptions of close others revealed that social decision preferences could be reliably predicted from semantic features of the text. The convergence of neural and linguistic data further strengthened the prediction of social decision preferences. These findings elucidate the neural and linguistic underpinnings of social decision-making, emphasizing the critical role of mental representations in guiding choices involving familiar others.
Spatiotemporal transcriptomic profiling and modeling of mouse brain at single-cell resolution reveals cell proximity effects of aging and rejuvenation
Authors: Sun Eric D. , Zhou Olivia Y. , Hauptschein Max , Rappoport Nimrod , Xu Lucy , Negredo Paloma Navarro , Liu Ling , Rando Thomas A. , Zou James , Brunet Anne
Published: July 2024

Old age is associated with a decline in cognitive function and an increase in neurodegenerative disease risk1. Brain aging is complex and accompanied by many cellular changes2–20. However, the influence that aged cells have on neighboring cells and how this contributes to tissue decline is unknown. More generally, the tools to systematically address this question in aging tissues have not yet been developed. Here, we generate spatiotemporal data at single-cell resolution for the mouse brain across lifespan, and we develop the first machine learning models based on spatial transcriptomics (‘spatial aging clocks’) to reveal cell proximity effects during brain aging and rejuvenation. We collect a single-cell spatial transcriptomics brain atlas of 4.2 million cells from 20 distinct ages and across two rejuvenating interventions—exercise and partial reprogramming. We identify spatial and cell type-specific transcriptomic fingerprints of aging, rejuvenation, and disease, including for rare cell types. Using spatial aging clocks and deep learning models, we find that T cells, which infiltrate the brain with age, have a striking pro-aging proximity effect on neighboring cells. Surprisingly, neural stem cells have a strong pro-rejuvenating effect on neighboring cells. By developing computational tools to identify mediators of these proximity effects, we find that pro-aging T cells trigger a local inflammatory response likely via interferon-γ whereas pro-rejuvenating neural stem cells impact the metabolism of neighboring cells possibly via growth factors (e.g. vascular endothelial growth factor) and extracellular vesicles, and we experimentally validate some of these predictions. These results suggest that rare cells can have a drastic influence on their neighbors and could be targeted to counter tissue aging. We anticipate that these spatial aging clocks will not only allow scalable assessment of the efficacy of interventions for aging and disease but also represent a new tool for studying cell-cell interactions in many spatial contexts.
Conditional Sequence-Structure Integration: A Novel Approach for Precision Antibody Engineering and Affinity Optimization
Authors: Jamialahmadi Benyamin , Chamankhah Mahmood , Kohandel Mohammad , Ghodsi Ali
Published: July 2024

Antibodies, or immunoglobulins, are integral to the immune response, playing a crucial role in recognizing and neutralizing external threats such as pathogens. However, the design of these molecules is complex due to the limited availability of paired structural antibody-antigen data and the intricacies of structurally non-deterministic regions. In this paper, we introduce a novel approach to designing antibodies by integrating structural and sequence information of antigens. Our approach employs a protein structural encoder to capture both sequence and conformational details of antigen. The encoded antigen information is then fed into an antibody language model (aLM) to generate antibody sequences. By adding cross-attention layers, aLM effectively incorporates the antigen information from the encoder. For optimal model training, we utilized the Causal Masked Language Modeling (CMLM) objective. Unlike other methods that require additional contextual information, such as epitope residues or a docked antibody framework, our model excels at predicting the antibody sequence without the need for any supplementary data. Our enhanced methodology demonstrates superior performance when compared to existing models in the RAbD benchmark for antibody design and SKEPMI for antibody optimization.
A critical role of protein damage response in mediating cancer drug resistance
Authors: Shao Fangyuan , Li Jie , Xiao Hao , Li Ling , Li Bo , Chen YuJun , Chu Xiangpeng , Ran Maoxin , Tang Dongyang , Peng Yuzhong , Huang Yujian , Wang Lijian , Shi Yanxia , Shao Nan , Miao Kai , Zhang Changhua , Lin Ying , Yan Jun , Tam Kin Yip , Xu Xiaoling , Deng Chu-Xia
Published: July 2024

Multidrug resistance (MDR) frequently occurs during cancer therapy and remains a major obstacle for the cure of most cancers(1, 2). Drug resistance could exist intrinsically or be acquired by drug treatment(3–5), yet factors that regulate the resistance remain elusive. Here, we show that most anticancer drugs damage neosynthesized proteins prior to reaching their canonic targets and elicit profound cytotoxicity, which is largely compensated by protein damage response (PDR). We demonstrate that the PDR includes damage recognition and clearance that are mainly mediated by ubiquitin and proteasome systems, although some other factors, including cellular ATP levels and proliferation status, are also involved. We show that cancer stem cells (CSCs), which have lower protein synthesis, and drug resistance acquired cells (DRAC), which have higher proteasome activity, are more resistant than other cells. We further demonstrate that ATP promotes protein synthesis and suppresses proteasome activity, thus, increasing mitochondrial ATP production by PDK1 inhibition and using proteasome inhibitor to block protein damage clearance render CSCs and DRACs more vulnerable to anticancer drugs. Thus, patients with drug-resistant cancers and treatment-naïve patients with low ATP levels and/or high proteasome activity can be identified and subtyped, and therapies containing PDK1-I and/or proteasome-I may be effective options for these patients.
A viscoelastic-plastic deformation model of hemisphere-like tip growth in Arabidopsis zygotes
Authors: Kang Zichen , Nonoyama Tomonobu , Ishimoto Yukitaka , Matsumoto Hikari , Nakagawa Sakumi , Ueda Minako , Tsugawa Satoru
Published: July 2024

Plant zygote cells exhibit tip growth, producing a hemisphere-like tip. To understand how this hemisphere-like tip shape is formed, we revisited a viscoelastic-plastic deformation model that enabled us to simultaneously evaluate the shape, stress, and strain of Arabidopsis (Arabidopsis thaliana) zygote cells undergoing tip growth. Altering the spatial distribution of cell wall extensibility revealed that cosine-type distribution and growth in a normal direction to the surface creates a stable hemisphere-like tip shape. Assuming these as constraints for cell elongation, we determined the best-fitting parameters for turgor pressure and wall extensibility to computationally reconstruct an elongating zygote that retained its hemisphere-like shape using only cell contour data, leading to formulation of non-dimensional growth parameters. Our computational results demonstrate the different morphologies in elongating zygotes through effective non-dimensional parameters.
Oscillations create groove: A reservoir model for learning complex drumming performances
Authors: Kawai Yuji , Fujii Shinya , Asada Minoru
Published: July 2024

Musical performances, particularly drumming, intricately balance rhythmic patterns and creative expression, all heavily influenced by the concept of “groove.” This study explored how the brain learns and internalizes complex rhythms and grooves from a computational perspective. The cerebellum and basal ganglia play key roles in rhythm perception, production, and timing. We utilized an oscillation-driven reservoir computing model, which is a simplified recurrent neural network designed for timing learning, to acquire complex rhythms. The model was trained to replicate the drumming style of Jeff Porcaro by learning his hi-hat patterns. Analyses revealed that the model’s outputs, including fluctuations in interbeat timings and amplitudes, were similar to the original drumming. Next, it was trained to generate multidimensional drum kit performances for various genres (funk, jazz, samba, and rock). Model outputs had timing deviation and audio features related to a sense of groove, similar to the original performances. By incorporating the oscillations of multiple frequencies into the reservoir, the model reproduced fluctuations of timing intervals (microtiming) and amplitudes, as well as audio features of each musical genre. Our results indicated that oscillation-driven reservoir computing can successfully replicate the timing and rhythmic complexity of professional drumming, suggesting that it is a common computational principle for motor timing and rhythm generation. Furthermore, this approach offers insights into the neural underpinnings of musical groove, shedding light on how the brain processes and reproduces intricate rhythmic patterns.

Author summary

Drumming is a sophisticated art form combining rhythmic precision and creative flair, encapsulated by the elusive quality of “groove.” Understanding how the brain generates these complex rhythms can provide insights into both musical and neural functions. In this study, we employed oscillation-driven reservoir computing to model the principal neural processes involved in learning and generating complex drum rhythms in the cerebellum and basal ganglia. We trained the model using the renowned drummer Jeff Porcaro’s hi-hat patterns and expanded its capabilities to produce multi-instrument drum performances. By introducing oscillations of different frequencies to reservoir computing, we enhanced the reservoir’s complex dynamics to create dynamic, non-repetitive, fluctuating time intervals and amplitudes of skilled drumming perfromances. Our findings demonstrate that this computational approach can emulate the nuanced microtiming and audio features essential for skilled drumming, shedding light on the potential neural mechanisms underlying skilled musical performances.
RAB12-LRRK2 Complex Suppresses Primary Ciliogenesis and Regulates Centrosome Homeostasis in Astrocytes
Authors: Li Xingjian , Zhu Hanwen , Huang Bik Tzu , Li Xianting , Kim Heesoo , Tan Haiyan , Zhang Yuanxi , Choi Insup , Peng Junmin , Xu Pingyi , Sun Ji , Yue Zhenyu
Published: July 2024

Leucine-rich repeat kinase 2 (LRRK2) phosphorylates a subset of RAB GTPases, and the phosphorylation levels are elevated by Parkinson’s disease (PD)-linked mutations of LRRK2. However, the precise function of the specific RAB GTPase targeted by LRRK2 signaling in the brain remains to be elucidated. Here, we identify RAB12 as a robust LRRK2 substrate in the mouse brains through phosphoproteomics profiling and solve the structure of RAB12-LRRK2 protein complex through Cryo-EM analysis. Mechanistically, RAB12 cooperates with LRRK2 to inhibit primary ciliogenesis and regulate centrosome homeostasis in astrocytes through enhancing the phosphorylation of RAB10 and recruiting Rab interacting lysosomal protein like 1 (RILPL1), while the functions of RAB12 require a direct interaction with LRRK2 and LRRK2 kinase activity. Furthermore, the ciliary deficits and centrosome alteration caused by the PD-linked LRRK2-G2019S mutation are prevented by the deletion ofRab12in astrocytes. Thus, our study reveals a physiological function of the RAB12-LRRK2 complex in regulating ciliogenesis and centrosome homeostasis. The RAB12-LRRK2 structure offers a guidance in the therapeutic development of PD by targeting the RAB12-LRRK2 interaction.
Application of Digital Tools and Artificial Intelligence to the Myasthenia Gravis Core Examination
Authors: Garbey Marc , Lesport Quentin , Girma Helen , Öztosen Gülṣen , Abu-Rub Mohammed , Guidon Amanda C. , Juel Vern , Nowak Richard , Soliven Betty , Aban Inmaculada , Kaminski Henry J.
Published: July 2024

Background

Advances in video image analysis and artificial intelligence provide the opportunity to transform the approach to patient evaluation through objective digital evaluation.

Objectives

We assessed ability to quantitate Zoom video recordings of a standardized neurological examination the myasthenia gravis core examination (MG-CE), which had been designed for telemedicine evaluations.

Methods

We used Zoom (Zoom Video Communications) videos of patients with myasthenia gravis undergoing the MG-CE. Computer vision in combination with artificial intelligence methods were used to build algorithms to analyze videos with a focus on eye or body motions. For the assessment of examinations involving vocalization, signal processing methods were developed, including natural language processing. A series of algorithms were built that could automatically compute the metrics of the MG-CE.

Results

Fifty-one patients with MG with videos recorded twice on separate days and 15 control subjects were assessed once. We were successful in quantitating lid, eye, and arm positions and as well as well as develop respiratory metrics using breath counts. Cheek puff exercise was found to be of limited value for quantitation. Technical limitations included variations in illumination, bandwidth, and recording being done on the examiner side, not the patient.

Conclusions

Several aspects of the MG-CE can be quantitated to produce continuous measures via standard Zoom video recordings. Further development of the technology offer the ability for trained, non-physician, health care providers to perform precise examination of patients with MG outside the clinic, including for clinical trials.

Plain Language Summary

Advances in video image analysis and artificial intelligence provide the opportunity to transform the approach to patient evaluation. Here, we asked whether video recordings of the typical telemedicine examination for the patient with myasthenia gravis be used to quantitate examination findings? Despite recordings not made for purpose, we were able to develop and apply computer vision and artificial intelligence to Zoom recorded videos to successfully quantitate eye muscle, facial muscle, and limb fatigue. The analysis also pointed out limitations of human assessments of bulbar and respiratory assessments. The neuromuscular examination can be enhanced by advance technologies, which have the promise to improve clinical trial outcome measures as well as standard care.
Tandem standing duration is a rapid, sensitive and specific test of Parkinson’s Disease subtype
Authors: Hosli Sarah , Ciocca Matteo , Hadi Zaeem , Molloy Sophie , Tai Yen , Seemungal Barry M
Published: July 2024

Background

Parkinson’s Disease (PD) patients with postural instability and gait disorder (PIGD) subtype are at increased risk for falls compared to the tremor-dominant subtype. We aimed to establish an easy clinical balance tool to rapidly and reliably identify PIGD patients, potentially important for directing healthcare resources or research phenotyping.

Methods

45 consecutive patients with PD completed clinical testing including Romberg, tandem stance, single leg stance, 360° turning and 10-meter walking. MDS-UPDRS part II and III, collected as part of regular follow-up, was used to classify disease subtype. Multinominal logistic regression models were fitted to find optimal subtype predictors and compared using receiver operating characteristic (ROC) curves.

Results

Unassisted tandem stand duration and time to turn 360° were significantly different between PIGD and tremor dominant subtypes. Both tandem standing and 360° turning showed very high predictive accuracy to predict PD subtype with an area under the ROC curve (AUC) of 86.6% and 88% respectively, which increased to 91.4% by combining both measures. Optimal cut-off values for identifying PD subtypes were tandem standing less than 20s and 360° turning longer than 6.5s.

Conclusion

Tandem stand duration and 360° turning are easy to apply clinical tests that rapidly identify PD patients with PIGD subtype with high sensitivity and specificity. These findings may be useful in the clinic to identify PD patients’ current falls risk or screening for research studies.

Plain Language Summary

Balance problems and falls are common in late-stage Parkinson’s Disease, affecting nearly 70% of patients 10 years post-diagnosis. In contrast, Parkinson’s patients who complain mainly of shaking (tremor) are less liable to fall. We set out to find an easy and reliable bedside test to distinguish patients at risk of falls with early Parkinson’s. This is important so that resources can be targeted to patients in need of support such as physiotherapy and fall prevention. 45 patients with Parkinson’s disease participated in this study and completed a battery of balance tests completed within the time of their regular follow-up appointment. We found that tandem standing duration – a test where patient stand still in the heel-to-toe position – and time taken to complete a full circle, were highly reliable in detecting patients with balance and gait problems. Specifically, patients with balance and gait problems were unable to tandem stand for more than 20 seconds and took more than 6.5 seconds to turn a full circle. Together, these two tests that take a minute to complete in the clinic, and may help improve the care for patients with Parkinson’s as a quick screening tool to identify Parkinson’s disease at risk of falls.
Effect of disclosing a polygenic risk score for coronary heart disease on adverse cardiovascular events: 10-year follow-up of the MI-GENES randomized clinical trial
Authors: Naderian Mohammadreza , Hamed Marwan E. , Vaseem Ali A. , Norland Kristjan , Dikilitas Ozan , Teymourzadeh Azin , Bailey Kent R. , Kullo Iftikhar J.
Published: July 2024

Background

The MI-GENES clinical trial (NCT01936675), in which participants at intermediate risk of coronary heart disease (CHD) were randomized to receive a Framingham risk score (FRSg, n=103), or an integrated risk score (IRSg, n=104) that additionally included a polygenic risk score (PRS), demonstrated that after 6 months, participants randomized to IRSghad higher statin initiation and lower low-density lipoprotein cholesterol (LDL-C).

Objectives

In a post hoc 10-year follow-up analysis of the MI-GENES trial, we investigated whether disclosure of a PRS for CHD was associated with a reduction in adverse cardiovascular events.

Methods

Participants were followed from randomization beginning in October 2013 until September 2023 to ascertain adverse cardiovascular events, testing for CHD, and changes in risk factors, by blinded review of electronic health records. The primary outcome was the time from randomization to the occurrence of the first major adverse cardiovascular event (MACE), defined as cardiovascular death, non-fatal myocardial infarction, coronary revascularization, and non-fatal stroke. Statistical analyses were conducted using Cox proportional hazards regression and linear mixed-effects models.

Results

We followed all 203 participants who completed the MI-GENES trial, 100 in FRSgand 103 in IRSg(mean age at the end of follow-up: 68.2±5.2, 48% male). During a median follow-up of 9.5 years, 9 MACEs occurred in FRSgand 2 in IRSg(hazard ratio (HR), 0.20; 95% confidence interval (CI), 0.04 to 0.94;P=0.042). In FRSg, 47 (47%) underwent at least one test for CHD, compared to 30 (29%) in IRSg(HR, 0.51; 95% CI, 0.32 to 0.81;P=0.004). IRSgparticipants had a longer duration of statin therapy during the first four years post-randomization and a greater reduction in LDL-C for up to 3 years post-randomization. No significant differences between the two groups were observed for hemoglobin A1C, systolic and diastolic blood pressures, weight, and smoking cessation rate during follow-up.

Conclusions

The disclosure of an IRS that included a PRS to individuals at intermediate risk for CHD was associated with a lower incidence of MACE after a decade of follow-up, likely due to a higher rate of initiation and longer duration of statin therapy, leading to lower LDL-C levels.
The SAP-LAP and IRP approaches for formation of policy framework of electric vehicles and its charging infrastructure in India
Authors: Ruchita  , Shankar Ravi
Published: July 2024

Purpose

In today’s environment, electric vehicles (EVs) industries and services provided to consumers are facing many challenges. The public in large numbers is not adopting Electric Vehicles because of the unavailability of suitable EVs and not getting proper charging infrastructure to the consumers. The purpose of this study and research work is to analyze the condition of this industry, its charging infrastructure and E-government policies. Based on the above analysis, frameworks/models are to be designed to assist organizations in formulating strategies for the EV industry and providing proper infrastructure to the consumer.

Design/methodology/approach

The Variables for the EV and EVsCI case study are identified from an exhaustive literature review, stakeholders’ perspectives, experts’ opinions, existing EV policies, future policy blueprints and data available for this industry, applying the Situation Actor Process-Learning Action Performance (SAP-LAP) methodology. After that, the Interpretive Ranking Process (IRP) is integrated with the SAP-LAP approach to develop models.

Findings

The rankings of Actors Versus Processes and Actions Versus Performances have been obtained and then models have been developed. These models can serve policymakers in framing and implementing effective policies.

Originality/value

Although the SAP-LAP approach is an innovative approach for identifying variables, however, this approach lacks perfect interactive relationships among the variables. It may lead to imperfect decision-making. To avoid this, the IRP approach is integrated with the SAP-LAP approach which provides more accurate models for analysis and providing recommendations to government and organizations.
Unlocking circularity: the interplay between institutional pressures and supply chain integration
Authors: Calzolari Tommaso , Genovese Andrea , Brint Andrew , Seuring Stefan
Published: July 2024

Purpose

This paper investigates the role of institutional pressures (IPs) and supply chain integration (SCI) in driving the adoption of circular economy (CE) practices. It is hypothesised that, responding to IPs, firms might adopt higher levels of SCI in the attempt to implement CE practices.

Design/methodology/approach

A research model is developed and tested on a cross-sectional sample of 150 multi-national enterprises (MNEs). Textual content from corporate sustainability reports is used to measure the constructs of interest through an advanced coding approach.

Findings

Findings show that IPs are driving the adoption of CE practices primarily through the mediation of SCI; the prominent roles of coercive regulatory pressures (CRPs) and normative pressures (NPs) are also highlighted. CRPs influence on CE practices is partially mediated by SCI, with NPs influence being fully mediated by it.

Practical implications

The study shows that SCI is a key mechanism that lies in between IPs and CE practices; as such, organisations interested in implementing CE practices need to be aware of requirements for achieving higher levels of SCI.

Originality/value

This empirical study is the first large scale analysis that conceptualises how MNE-driven supply chains adopt CE practices. The study empirically validates the model and identifies research avenues in supply chain management (SCM) research to support the adoption of CE practices.
Modelling supply chain visibility: a framework with considerations for manufacturing and business
Authors: Sunmola Funlade T. , Apeji Uje D.
Published: July 2024

Purpose

Supply chain visibility plays a pivotal role in ensuring stakeholders have access to and share mutually beneficial information - information that is critical to processes, operations, and informed decision-making. This study leverages a framework to explore the influence of four key factors on supply chain visibility: supply chain linkages, supply chain relationships, green absorptive capacity, and information sharing.

Design/methodology/approach

This investigation adopted a survey-based research methodology to collect data. A sampling strategy was employed to recruit participants from various industry sectors, with a primary focus on manufacturing and business. A total of 204 useable questionnaires were obtained. Exploratory factor analysis was conducted to identify underlying factors within the data. Confirmatory factor analysis (CFA) was then used to assess the validity and reliability of the identified factors. Finally, structural equation modelling was employed to test the hypothesised relationships between the constructs studied.

Findings

This study's findings, particularly the significant positive correlations observed between information sharing, supply chain relationship, internal linkage, and green absorptive capacity, provide evidence that these factors are key drivers of supply chain visibility. Additionally, the analysis revealed that external linkages with supply chain partners further enhance information sharing within the chain.

Originality/value

This study offers a unique contribution by exploring the interplay between green absorptive capacity, information sharing, internal and external supply chain linkages, and their combined influence on supply chain visibility. Extending prior research that focused primarily on information sharing and traditional supply chain relationships, this study integrates green absorptive capacity and linkages within a novel framework. Our findings suggest that green absorptive capacity enhances information sharing within the supply chain network, ultimately leading to improved visibility. Furthermore, the study distinguishes the influence of internal vs external linkages on visibility.
How do adaptive market experimentation, open marketing and strategic flexibility contribute to small firms' business model innovation in the context of a crisis?
Authors: Massiera Philippe
Published: July 2024

Purpose

This research aims to investigate, in the context of a crisis, how adaptive marketing and open marketing capabilities directly contribute to enhance SMEs' business model innovation taking into consideration the mediating role of strategic flexibility.

Design/methodology/approach

Based on a sample of 120 small firms, our theoretical model is tested through a cross-sectional study. PLS-SEM is applied as the analytical technique.

Findings

The results show that open marketing capabilities are positively related to business model innovation and that this relationship is partially mediated by strategic flexibility. Furthermore, adaptive market experimentation capabilities enhance business model innovation only when fully mediated by strategic flexibility.

Research limitations/implications

Extending existing explorative research, our research illuminates how adaptive market experimentation and open marketing capabilities, in conjunction with strategic flexibility, can help SMEs to better adapt existing business models during a time of crisis. Our findings underline the potential contribution of planned test-driven activities, trial-and-error processes, data-based decisional processes and benchmarking activities. We also document how stronger networking capabilities and organizational openness strengthen the firm's ability to access the required additional resources and insights they need. These contributions remain however conditioned by the use of a convenient sampling design as well as the cross-sectional nature of the data.

Practical implications

Our findings underline the importance of empowering SMEs to nurture more effective experimental approaches in the long run, along with a more formalized open marketing posture. Our study also highlights the need for SMEs to improve their awareness of the risk of inertia and the benefits of nurturing their overall flexibility so they can adapt in an adequate and timely manner.

Originality/value

The findings of this study build on the perspective of adaptive marketing capabilities and add to the business model innovation literature in two ways. First, our study provides new insights into the cumulative and concrete consequences of market experimentation and open marketing capabilities on small firms' business model dynamics in the context of a crisis. Second, our findings illuminate the crucial role of strategic flexibility which, partly or entirely, contributes to the full realization of the potential of the marketing capabilities at hand.
Understanding turnover of generation Y early-career workers: the influence of values and field of study
Authors: Rueff-Lopes Rita , Velasco Ferran , Sayeras Josep , Junça-Silva Ana
Published: July 2024

Purpose

Generation Y early-career workers have the highest turnover rates ever seen. To better understand this phenomenon, this study combines the P-O values fit with the Cohort perspectives to (1) identify the work-related values of this generation, (2) explore the relation between values and turnover intentions and examine how the field of study influences this relationship and (3) verify if the turnover intentions materialized one year after the first data collection.

Design/methodology/approach

We interviewed 71 early-career workers and applied thematic analysis to identify the value categories. A classification decision tree tested whether the field of study influences the relation between values and turnover intentions. A post-test was conducted to determine whether the reported turnover intentions were materialized one year later.

Findings

Thematic analysis yielded 285 themes that were grouped into 12 values’ categories. Decision trees revealed that the combination of values that most predicted turnover was substantially different between Finance graduates (more instrumental and future-oriented values) and Innovation and Entrepreneurship graduates (more social and job-oriented values). The post-test confirmed that the number of respondents who reported an intention to quit their jobs during the interview with us and did quit one year later was statistically significant.

Originality/value

To our knowledge, this is the first study that uses critical incident interviews to explore the work-related values of this specific cohort and their relation to turnover. Our findings on the moderating effects of the field of study are unprecedented. We also identified three new work-value categories, and, to our knowledge, this is the first study that used decision trees to explore the relation between values and turnover.
Accounting information systems and organizational performance in the cloud computing era: evidence from SMEs
Authors: Vo Van Hien , Abu Afifa Malik , Saleh Isam
Published: July 2024

Purpose

This study aims to investigate whether cloud-based accounting information system (AIS) usage contributes to AIS effectiveness, with firm size acting as a moderator. Furthermore, the role of AIS effectiveness as a mediator in the relationship between cloud-based AIS usage and organizational performance (OP) is further evaluated. In this context, the study is a bridge to show that small and medium-sized enterprises (SMEs) try to apply cloud accounting to improve profitability, thereby funding more social-environmental activities on the path to sustainability.

Design/methodology/approach

The study conducted an online survey of chief accountants in Vietnam’s SMEs. Data from 193 responses were gathered and analyzed using partial least squares structural equation modeling.

Findings

The findings show that cloud-based AIS usage considerably contributes to AIS effectiveness and OP and that AIS effectiveness has a beneficial influence on OP. Furthermore, the study shows that firm size moderates the relationship between cloud-based AIS usage and AIS effectiveness. Further findings show that cloud-based AIS usage influences OP via AIS effectiveness.

Practical implications

The findings of this study expand the existing body of knowledge on cloud-based AIS usage and benefit managers when formulating their business information models. In practice, SMEs need to increase the use of cloud-based AIS to better manage AIS. Enhancing profitability through cloud accounting also determines the ability to finance sustainability activities in SMEs.

Social implications

One of the practical values of this study is the impact on Vietnam’s socioeconomic growth and sustainability. With cloud-based AIS, SMEs may enhance information and system quality, boost system usage frequency, gain satisfaction and increase performance. Furthermore, the comprehensiveness of AIS from cloud-based AIS usage is also a condition for SMEs to enhance accountability for social-environmental information in future sustainable reporting. These advantages improve the efficiency of strategic decision-making, hence increasing SMEs’ competitiveness and social-environmental performance. These benefits will work directly or indirectly toward fostering broader socioeconomic and environmental sustainability in developing economies.

Originality/value

To open a bright perspective of cloud-based AIS usage for AIS effectiveness as well as OP in SMEs toward sustainability in a developing economy, the authors conducted an exploratory study because this topic is quite new in these firms, especially in a developing economy such as Vietnam. These discoveries partly support SMEs to quickly achieve sustainable development goals in the future.
The general anti‐avoidance rule
Authors: Cowx Mary , Kerr Jon N.
Published: July 2024

The general anti‐avoidance rule, or GAAR, is an enforcement mechanism that gives a country's taxing authority broad power to deny a taxpayer tax benefits associated with any transaction. Although GAARs are becoming increasingly common, the presence of a GAAR is generally overlooked by researchers and thus has been left unstudied. In this paper, we provide an initial investigation by studying the effect of GAARs on firm‐level corporate tax avoidance behaviors. Using an indicator for the enactment or strengthening of a GAAR within a country in a stacked difference‐in‐differences design, we find GAAR enactment is associated with a statistically and economically significant decrease in firm‐level tax avoidance. Additional cross‐sectional analyses show that the decline in tax avoidance occurs for conventional GAARs and economic substance‐type rules, original and strengthened GAARs, and domestic and multinational firms. Results also show that the effect is strongest for firms with higher levels of pre‐GAAR‐enactment tax avoidance and for firms incorporated in countries where the burden of proof lies with the taxpayer.
Human‐induced risk drives behavioural decisions in a recovering brown bear population
Authors: Corradini Andrea , Falcinelli Daniele , Pedrotti Luca , Tattoni Clara , Ranc Nathan , Bragalanti Natalia , Groff Claudio , Ciolli Marco , Cagnacci Francesca
Published: July 2024

In human‐dominated landscapes, rebounding bear populations share space with people, which may lead to bear–human conflicts and, consequently, a decrease in acceptance and an increase in bear mortality linked to human causes. Previous analyses of brown bear (Ursus arctos) movement data have shown that bears adopt a security‐food trade‐off strategy in response to variable human‐related risk. However, brown bear flexibility to cope with these risky situations may be reduced when resting, mating or stocking fat in preparation for hibernation. In this study, we measured the multi‐scale spatial response of brown bears to human‐related risk and food resource distribution in a highly heterogeneous human‐dominated landscape. We examined habitat selection both within the population range (‘second‐order’ selection) and at bedding site locations (‘third‐order’) for GPS‐tagged brown bears of a recently reintroduced population in the Italian Alps. We identified resting locations by field‐validated spatio‐temporal cluster analysis of telemetry locations. We mapped food availability and distribution using dynamic geographic layers of fruiting wild berries, and human‐related risk using human mobility data (Strava‐based Cumulated Outdoor activity Index). Brown bears appeared to compromise their need for food resources for avoidance of anthropogenic disturbance when selecting home ranges, as they utilized areas richer in wild berries less when human use of outdoor tracks was higher. Furthermore, selection of resting site locations strongly depended on the avoidance of human‐related risk only, with less frequented, more concealed and inaccessible sites being selected. We conclude that humans compete for space with bears beyond their infrastructural impact, that is, by actively occupying key areas for bear survival, thereby potentially restricting the bears' realized niche. We propose mitigating actions to promote bear–human coexistence by selectively restricting human access to key areas during sensitive annual physiological phases for bear survival.
Selective exposure and echo chambers in partisan television consumption: Evidence from linked viewership, administrative, and survey data
Authors: Broockman David E. , Kalla Joshua L.
Published: July 2024

Influential theories doubt that partisan television's audience is sufficiently large, moderate, or isolated from cross‐cutting sources for it to meaningfully influence public opinion. However, limitations of survey‐based television consumption measures leave these questions unresolved. We argue that nonpolitical attributes of partisan channels can attract voters to form habits for watching channels with slants they do not fully share. We report findings from three novel datasets which each link behavioral measures of television consumption to political administrative or survey data. We find that approximately 15% of Americans consume over 8 hours/month of partisan television. Additionally, weak partisans, independents, and outpartisans comprise over half of partisan channels’ audiences. Finally, partisan television consumers largely consume only one partisan channel and remain loyal to it over time, consistent with “echo chambers.” These findings support our argument and suggest partisan television's potential to influence public opinion cannot be dismissed.
Next‐generation monitoring in obstetrics: Assessing the accuracy of non‐piezo portable ultrasound technology
Authors: Plöger Ruben , Behning Charlotte , Walter Adeline , Jimenez Cruz Jorge , Gembruch Ulrich , Strizek Brigitte , Recker Florian
Published: July 2024

Introduction

The emergence of handheld ultrasound devices capable of connecting to cell phones or tablets heralds a significant advancement in medical technology, particularly within the field of obstetrics. These devices offer the promise of immediate bedside ultrasound examinations, potentially revolutionizing patient care by enabling fetal assessments in diverse settings.

Material and Methods

This prospective study aimed to validate the reliability of non‐piezo, chip‐based handheld ultrasound devices in clinical obstetric practice. Conducted in a university hospital obstetric ward, the study included 100 pregnant women between 17 and 41 weeks of gestation. Participants underwent ultrasound examinations using both conventional and portable point‐of‐care ultrasound (POCUS) devices to compare the accuracy in estimating fetal weight and other parameters, such as cardiac activity, fetal presentation, placental location, and amniotic fluid volume. The reliability and agreement between the devices were assessed using intraclass correlation coefficients, Bland–Altman plots, and Pearson correlation coefficients.

Results

The results show a near‐perfect agreement (0.98) and correlation (r = 0.98, p < 0.001) for estimated fetal weight and most biometry measurements between the two types of ultrasound devices, with slight deviations in head circumference and amniotic fluid index measurements. Subgroup analysis revealed variations in agreement and correlation rates with higher BMI and advanced gestational age, indicating areas for further refinement.

Conclusions

These findings affirm the high reliability of handheld ultrasound devices for basic obstetric ultrasound evaluations, supporting their integration into daily clinical practice. This technology improves the flexibility and immediacy of prenatal care, although further research is needed to optimize its application across patient populations and treatment settings.
The effectiveness of mindfulness‐based intervention for psychological distress and emotion regulation in college students with non‐suicidal self‐injury
Authors: Zheng Qiongjuan , Zhou Han‐yu , Li Keshuang , Liu Yaohong , Nan Weizhi , Gong Jingbo
Published: July 2024

This study explored the effectiveness of a short‐term mindfulness‐based intervention (MBI) on psychological distress, mindfulness levels, emotion regulation, and impulsivity among college students with non‐suicidal self‐injury (NSSI). Participants completed four questionnaires, including the Five Facet Mindfulness Questionnaire, the Depression Anxiety Stress Scale, the Emotion Regulation Questionnaire, and the Brief Barratt Impulsivity Scale, and two behavioral tasks, including an emotion regulation task and a stop signal task (SST), at three time points. Compared with the healthy group, the NSSI group had a significantly greater level of psychological distress and a lower level of mindfulness. Compared with the NSSI control group and the healthy group, the NSSI MBI group had significantly increased mindfulness levels and decreased psychological distress after the intervention. In the NSSI MBI group, regardless of which emotion regulation strategy was adopted when viewing negative pictures, the intensity of negative emotions during the emotion regulation task was significantly reduced. Moreover, in the NSSI MBI group, the effectiveness of the MBI on the mindfulness level, stress level, and emotion regulation process was maintained at the follow‐up. The present study provided empirical support that short‐term MBI has the potential to help individuals with NSSI by enhancing their emotion regulation.
Nanoemulsion based lipid nanoparticles for effective demethylcantharidin delivery to cure liver cancer
Authors: Yan Zijun , Yu Ting , Wu Xiaoping , Deng Mengyue , Wei Panpan , Su Ning , Ding Yuzhen , Xia Die , Zhang Yuehui , Zhang Liangming , Chen Tong
Published: July 2024

Demethylcantharidin (DEM) is a widely used antitumor drug; however, its poor tumor targeting and serious organotoxicity limit its application. The aim of this study was to develop a new drug delivery system for efficient delivery of DEM. Nanoemulsion based lipid nanoparticles containing demethylcantharidin (DNLNs) were prepared by loading nanoemulsions into lipid nanoparticles. The cells proliferation, apoptosis, cycle, and uptake were investigated by Cell counting kit‐8 (CCK‐8), flow cytometry, and in situ fluorescence assays, respectively. Then, we established the H22 tumor‐bearing mouse model to evaluate the antitumor efficacy of DNLNs and further studied its organ toxicity and distribution. DNLNs significantly inhibited the proliferation and promoted apoptosis of H22 cells, and H22 cells could take up more DNLNs. Compared with DEM, DNLNs had certain tumor‐targeting properties, and the tumor inhibition rate increased by 23.24%. Moreover, DNLNs can increase white blood cell count and reduce organ toxicity. This study paves the way for nanoemulsion‐based lipid nanoparticle (NLNs)‐efficient DEM delivery to treat liver cancer.
Reading disability is characterized by reduced print–speech convergence
Authors: Yan Xiaohui , Fu Yang , Feng Guoyan , Li Hui , Su Haibin , Liu Xinhong , Wu Yu , Hua Jia , Cao Fan
Published: July 2024

Reading disability (RD) may be characterized by reduced print–speech convergence, which is the extent to which neurocognitive processes for reading and hearing words overlap. We examined how print–speech convergence changes from children (mean age: 11.07+0.48) to adults (mean age: 21.33+1.80) in 86 readers with or without RD. The participants were recruited in elementary schools and associate degree colleges in China (from 2020 to 2021). Three patterns of abnormalities were revealed: (1) persistent reduction of print–speech convergence in the left inferior parietal cortex in both children and adults with RD, suggesting a neural signature of RD; (2) reduction of print–speech convergence in the left inferior frontal gyrus only evident in children but not adults with RD, suggesting a developmental delay; and (3) increased print–speech convergence in adults with RD than typical adults in the bilateral cerebella/fusiform, suggesting compensations. It provides insights into developmental differences in brain functional abnormalities in RD.