Implications For Management Research Articles

Lecithin-complexed oregano essential oil-encapsulated fibrous barriers prevent postoperative adhesions by regulating Nrf2/NF-κB signaling pathways

Postoperative adhesions are prone to a variety of complications, which can adversely affect the quality of life (QOL) of patients. While anti-adhesion scaffolds rapidly degrade, foreign body reactions (FBR), exaggerated inflammatory reactions, and oxidative stress may increase tissue adhesions. This necessitates the development of anti-adhesion scaffolds with multifunctional anti-inflammatory, anti-bacterial, and anti-oxidative characteristics. The objective of this study was to simultaneously leverage natural antimicrobial and anti-oxidative bioactive molecules, such as lecithin (L) and Oregano essential oil (O) to afford poly(lactic-co-glycolic acid) (PLGA)-based electrospun membranes for postoperative anti-adhesion management. A series of assays revealed a beneficial effect of L and O co-loaded membranes (P@LO) to suppress bacterial growth, reduce the proliferation of fibroblasts, and confer anti-oxidative and anti-inflammatory functionalities to membranes than that of the control (P) or only a single cue-loaded groups (P@L and P@O). The underlying molecular mechanism of the anti-inflammatory effect may be an upregulation of the activation of nuclear factor erythroid 2-related factor 2 (Nrf2) phosphorylation. An assessment of membranes in an abdominal and a tendon adhesion model showed a significant effect of P@LO membranes to prevent post-operative tissue adhesion. The P@LO membranes were found to up-regulate the phosphorylation of Nrf2 while down-regulate the phosphorylation of nuclear factor kappa-B (NF-κB) P65. This resulted in lower expression of collagen Ⅰ (Col-Ⅰ), collagen Ⅲ (Col-Ⅲ), and alpha-smooth muscle actin (α-SMA) alongside inflammation resolution and less transition of fibroblasts to myofibroblasts. Taken together, these multifunctional scaffolds may have broad implications for postoperative adhesion management.

EXPRESS: Do Gender-Diverse Teams Deliver Better Operational Performance: an Experimental Study

The routines-based approach to operations management emphasizes the role of routines in operational performance. However, little is known about how gender diversity in teams could alter coordination and change behaviors of team members, potentially impacting performance. In this study, we report on two laboratory experiments that induce routines to assess the stability of coordination and adaptability to organizational changes across mixed-gender teams of varying diversity and empirically examine operational performance via routines. Based on frequentist and Bayesian statistical approaches, our findings reveal that compared to other mixed-gender teams, balanced-gender teams (a) attain stability in routines faster, (b) exhibit varying levels of adaptability to internal and external changes, and (c) deliver better economic benefits via resource- and time- efficiencies under normal and change conditions, and this is attributable to their higher pace of routine formation. We find the operational-performance effect more prominent in situations of change than in normal conditions. Alongside our theoretical contributions, our study has several implications for management and effective operations management in terms of team composition, hiring, and staffing decisions.

Spatiotemporal variations of ecosystem services in the Aral Sea basin under different CMIP6 projections

The Aral Sea, located in Central Asia, has undergone significant reduction in surface area owing to the combined impacts of climate change and human activities. This reduction has led to a regional ecological crisis and profound repercussions on ecosystem services. Investigating the spatiotemporal variations and synergistic trade-offs of ESs in the Aral Sea basin is crucial for fostering the integrated development of the region’s socioeconomic ecology. This study utilizes the Future Land-Use Simulation and InVEST models to analyze future land-use scenarios, integrating CMIP6 projections to assess the quality of four key ecosystem services: water production, soil conservation, carbon storage, and habitat quality over two timeframes: the historical period (1995–2020) and the projected future (2021–2100). Employing Spearman correlation, the study explores the trade-offs and synergies among these ecosystem services. Findings reveal that the primary forms of land-use change in the Aral Sea basin are the reduction in water area (− 49.59%) and the rapid expansion of urban areas (+ 504.65%). Temporally, habitat quality exhibits a declining trend, while carbon storage shows an increasing trend, and water production and soil retention fluctuate initially decreasing and then increasing. Spatially, water production and carbon storage demonstrate an increasing trend from the northwest to the southeast. Habitat quality exhibits a higher spatial pattern in the southeast and south, contrasting with lower spatial patterns in the north and west. Low-level soil conservation is predominantly distributed in the northwest, while medium to low-level soil conservation is prevalent in the east of the basin. The trade-off and synergy analysis indicates that between 1995 and 2020, a trade-off relationship existed between carbon storage and habitat quality and water production, whereas synergies were observed between soil conservation and carbon storage, water production and habitat quality, and soil conservation. The correlation between water production and soil conservation emerges as the strongest, whereas the correlation between carbon storage and habitat quality appears to be the weakest. The dynamic spatiotemporal changes, trade-offs, and collaborative relationships of ESs constitute major aspects of ecosystem service research, holding substantial implications for the effective management of the regional ecological environment.

Deep learning algorithm-enabled sediment characterization techniques to determination of water saturation for tight gas carbonate reservoirs in Bohai Bay Basin, China

Understanding water saturation levels in tight gas carbonate reservoirs is vital for optimizing hydrocarbon production and mitigating challenges such as reduced permeability due to water saturation (Sw) and pore throat blockages, given its critical role in managing capillary pressure in water drive mechanisms reservoirs. Traditional sediment characterization methods such as core analysis, are often costly, invasive, and lack comprehensive spatial information. In recent years, several classical machine learning models have been developed to address these shortcomings. Traditional machine learning methods utilized in reservoir characterization encounter various challenges, including the ability to capture intricate relationships, potential overfitting, and handling extensive, multi-dimensional datasets. Moreover, these methods often face difficulties in dealing with temporal dependencies and subtle patterns within geological formations, particularly evident in heterogeneous carbonate reservoirs. Consequently, despite technological advancements, enhancing the reliability, interpretability, and applicability of predictive models remains imperative for effectively characterizing tight gas carbonate reservoirs. This study employs a novel data-driven strategy to prediction of water saturation in tight gas reservoir powered by three recurrent neural network type deep/shallow learning algorithms—Gated Recurrent Unit (GRU), Recurrent Neural Networks (RNN), Long Short-Term Memory (LSTM), Support Vector Machine (SVM), K-nearest neighbor (KNN) and Decision tree (DT)—customized to accurately forecast sequential sedimentary structure data. These models, optimized using Adam's optimizer algorithm, demonstrated impressive performance in predicting water saturation levels using conventional petrophysical data. Particularly, the GRU model stood out, achieving remarkable accuracy (an R-squared value of 0.9973) with minimal errors (RMSE of 0.0198) compared to LSTM, RNN, SVM, KNN and, DT algorithms, thus showcasing its proficiency in processing extensive datasets and effectively identifying patterns. By achieving unprecedented accuracy levels, this study not only enhances the understanding of sediment properties and fluid saturation dynamics but also offers practical implications for reservoir management and hydrocarbon exploration in complex geological settings. These insights pave the way for more reliable and efficient decision-making processes, thereby advancing the forefront of reservoir engineering and petroleum geoscience.

Insulin Requirements According to Sex and Weight in a Population of 9036 Adult Persons With Type 1 Diabetes Using Closed-Loop Insulin Delivery.

The prediction of the individual insulin needs may facilitate the initiation of insulin therapy. Our aim was to explore the relationships between body weight, sex, and daily amounts of insulin delivered by a hybrid closed-loop system. We performed a retrospective data collection of all consenting adult patients with type 1 diabetes who were equipped in Europe with the Diabeloop Generation 1 (DBLG1) hybrid closed-loop insulin delivery device between March 1, 2021 and February 28, 2023. A total of 9036 users (59% females, age 45.6 ± 14.3 years) were included, reaching a mean follow-up of 320 ± 143 days, an overall 2 887 188 days of data. We observed a mean insulin-weight ratio of 0.617 ± 0.207 U/kg (0.665 ± 0.217 for males and 0.584 ± 0.193 for females, P < .001). Exploratory analysis of a subset of 4066 patients reaching >70% Time in Range (70-180 mg/dL) showed a mean insulin-weight ratio of 0.55 ± 0.17 U/kg (P < .001) (0.59 ± 0.18 for the 1438 males and 0.53 ± 0.16 for the 2628 females). This large real-world analysis provides a quantitative estimation of the daily insulin requirements in adult patients with type 1 diabetes and shows significant differences between sex. These findings have relevant implications in the practical management of insulin therapy.

MOG Antibody Disease: Nuances in Presentation, Diagnosis, and Management.

Myelin oligodendrocyte glycoprotein antibody disease (MOGAD) is a distinct neuroinflammatory condition characterized by attacks of optic neuritis, transverse myelitis, and other demyelinating events. Though it can mimic multiple sclerosis and neuromyelitis optica spectrum disorder, distinct clinical and radiologic features which can discriminate these conditions are now recognized. This review highlights recent advances in our understanding of clinical manifestations, diagnosis, and treatment of MOGAD. Studies have identified subtleties of common clinical attacks and identified more rare phenotypes, including cerebral cortical encephalitis, which have broadened our understanding of the clinicoradiologic spectrum of MOGAD and culminated in the recent publication of proposed diagnostic criteria with a familiar construction to those diagnosing other neuroinflammatory conditions. These criteria, in combination with advances in antibody testing, should simultaneously lead to wider recognition and reduced incidence of misdiagnosis. In addition, recent observational studies have raised new questions about when to treat MOGAD chronically, and with which agent. MOGAD pathophysiology informs some of the relatively unique clinical and radiologic features which have come to define this condition, and similarly has implications for diagnosis and management. Further prospective studies and the first clinical trials of therapeutic options will answer several remaining questions about the peculiarities of this condition.

Neurotourism Insights: Eye Tracking and Galvanic Analysis of Tourism Destination Brand Logos and AI Visuals

This pioneering study explores the intersection between Neurotourism, defined as the integration of neurosciences in tourism, and the perception of tourism Brand Personality (BP) through the advanced use of psychophysiology techniques, specifically Eye-Tracking (ET) and Galvanic Skin Response (GSR). It analyses how tourism destination brand logos/combination marks and images generated by artificial intelligence (AI) influence consumer attention and emotional response. Focusing on the five dimensions of BP proposed by Aaker (1997) - sincerity, excitement, sophistication, competence, and ruggedness - this study highlights significant differences in how men and women process and react to brand values associated with specific cities. Employing a rigorous methodological approach and the application of non-parametric statistical analyses, the findings reveal distinct patterns of visual attention and emotional responses across genders, emphasising the importance of considering BP in the marketing and design of tourism destination brand logos/combination marks. This work not only advances theoretical understanding of tourist consumer behaviour but also offers relevant practical implications for tourism marketing and destination management.

Comparison of machine and deep learning algorithms using Google Earth Engine and Python for land classifications

Classifying land use and land cover (LULC) is essential for various environmental monitoring and geospatial analysis applications. This research focuses on land classification in District Sukkur, Pakistan, employing the comparison between machine and deep learning models. Three satellite indices, namely, NDVI, MNDWI, and NDBI, were derived from Landsat-8 data and utilized to classify four primary categories: Built-up Area, Water Bodies, Barren Land, and Vegetation. The main objective of this study is to evaluate and compare the effectiveness of comparison of machine and deep learning models. The machine learning models including Random Forest achieved an overall accuracy of 91.3% and a Kappa coefficient of 0.90. It accurately classified 2.7% of the area as Built-up Area, 1.9% as Water Bodies, 54.8% as Barren Land, and 40.4% as Vegetation. While slightly less accurate, Decision Tree model provided reliable classifications. Deep learning models showed significant accuracy, of Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN). The CNN model achieved an impressive overall accuracy of 97.3%, excelling in classifying Water Bodies with User and Producer Accuracy exceeding 99%. The RNN model, with an overall accuracy of 96.2%, demonstrated strong performance in categorizing Vegetation. These findings offer valuable insights into the potential applications of machine learning and deep learning models for perfect land classifications, with implications for environmental monitoring management and geospatial analysis. The rigorous validation and comparative analysis of these models contribute to advancing remote sensing techniques and their utilization in land classification tasks. This research presents a significant contribution to the field and underscores the importance of precise land classification in the context of sustainable land management and environmental conservation.

Revealing Hidden Genes in Botrytis cinerea: New Insights into Genes Involved in the Biosynthesis of Secondary Metabolites

Utilizing bioinformatics tools, this study expands our understanding of secondary metabolism in Botrytis cinerea, identifying novel genes within polyketide synthase (PKS), non-ribosomal peptide synthetase (NRPS), sesquiterpene cyclase (STC), diterpene cyclase (DTC), and dimethylallyltryptophan synthase (DMATS) families. These findings enrich the genetic framework associated with B. cinerea’s pathogenicity and ecological adaptation, offering insights into uncharted metabolic pathways. Significantly, the discovery of previously unannotated genes provides new molecular targets for developing targeted antifungal strategies, promising to enhance crop protection and advance our understanding of fungal biochemistry. This research not only broadens the scope of known secondary metabolites but also opens avenues for future exploration into B. cinerea’s biosynthetic capabilities, potentially leading to novel antifungal compounds. Our work underscores the importance of integrating bioinformatics and genomics for fungal research, paving the way for sustainable agricultural practices by pinpointing precise molecular interventions against B. cinerea. This study sets a foundation for further investigations into the fungus’s secondary metabolism, with implications for biotechnology and crop disease management.

Low methylation marker levels among human papillomavirus-vaccinated women with cervical high-grade squamous intraepithelial lesions.

Cervical cancer screening programs, including triage tests, need redesigning as human papillomavirus (HPV)-vaccinated women are entering the programs. Methylation markers offer a potential solution to reduce false-positive rates by identifying clinically relevant cervical lesions with progressive potential. In a nested case-control study, 9242 women who received the three-dose HPV16/18-vaccine at ages 12-15 or 18 in a community-randomized trial were included. Subsequently, they were re-randomized for either frequent or infrequent cervical cancer screening trials. Over a 15-year post-vaccination follow-up until 2022, 17 high-grade squamous intraepithelial lesion (HSIL) and 15 low-grade (LSIL) cases were identified at the 25-year screening round, alongside 371 age and community-matched HPV16/18-vaccinated controls. Methylation analyses were performed on cervical samples collected at age 25, preceding histologically confirmed LSIL or HSIL diagnoses. DNA methylation of viral (HPV16/18/31/33) and host-cell genes (EPB41L3, FAM19A4, and miR124-2) was measured, along with HPV-genotyping. No HPV16/18 HSIL cases were observed. The predominant HPV-genotypes were HPV52 (29.4%), HPV59/HPV51/HPV58 (each 23.5%), and HPV33 (17.7%). Methylation levels were generally low, with no significant differences in mean methylation levels of viral or host-cell genes between the LSIL/HSIL and controls. However, a significant difference in methylation levels was found between HSIL cases and controls when considering a combination of viral genes and EPB41L3 (p value = .0001). HPV-vaccinated women with HSIL had HPV infections with uncommon HPV types that very rarely cause cancer and displayed low methylation levels. Further investigation is warranted to understand the likely regressive nature of HSIL among HPV-vaccinated women and its implications for management.

Characteristics, aetiology and implications for management of multiple primary renal tumours: a systematic review.

In a subset of patients with renal tumours, multiple primary lesions may occur. Predisposition to multiple primary renal tumours (MPRT) is a well-recognised feature of some inherited renal cancer syndromes. The diagnosis of MPRT should therefore provoke a thorough assessment for clinical and genetic evidence of disorders associated with predisposition to renal tumourigenesis. To better define the clinical and genetic characteristics of MPRT, a systematic literature review was performed for publications up to 3 April 2024. A total of 7689 patients from 467 articles were identified with MPRT. Compared to all patients with renal cell carcinoma (RCC), patients with MPRT were more likely to be male (71.8% versus 63%) and have an earlier age at diagnosis (<46 years, 32.4% versus 19%). In 61.1% of cases MPRT were synchronous. The proportion of cases with similar histology and the proportion of cases with multiple papillary renal cell carcinoma (RCC) (16.1%) were higher than expected. In total, 14.9% of patients with MPRT had a family history of cancer or were diagnosed with a hereditary RCC associated syndrome with von Hippel-Lindau (VHL) disease being the most common one (69.7%), followed by Birt-Hogg-Dubé (BHD) syndrome (14.2%). Individuals with a known or likely genetic cause were, on average, younger (43.9 years versus 57.1 years). In rare cases intrarenal metastatic RCC can phenocopy MPRT. We review potential genetic causes of MPRT and their implications for management, suggest an approach to genetic testing for individuals presenting with MPRT and considerations in cases in which routine germline genetic testing does not provide a diagnosis.

Relationships Between Theme Park Ride Experience and Loyalty: The Moderating Role of Past Experience

ABSTRACT Understanding the relationship between theme park ride experiences and visitor loyalty is crucial yet still not fully elucidated, particularly regarding differences between first-time and repeat visitors. Drawing upon the experience economy framework and the theory of experienced utility, this study explores how various aspects of theme park ride experience (education, aesthetics, entertainment, and escapism) influence visitor loyalty (revisit and recommendation intentions), considering the moderating effect of past experience. Structural equation modeling and invariance tests were conducted on data collected from 412 theme park visitors in China. Results indicate that the four dimensions of theme park ride experience have varying impacts on patrons’ revisit and recommendation intentions. Additionally, first-time visitors’ intentions are more influenced by active participation experiences compared to repeat visitors. This study advances the theoretical knowledge of theme park ride experience and offers practical implications for park management.

Association of right aortic arch and agenesis of ductus arteriosus in prenatal tetralogy of Fallot spectrum and its clinical implications.

In our center, we observed an increased frequency of right aortic arch (RAA) with an agenesis of the ductus arteriosus (ADA) in prenatally diagnosed tetralogy of Fallot (ToF) and its variations. This study aimed to determine whether there is an association of RAA and ADA in fetuses with ToF. Distribution of genetic anomalies and impact on postnatal outcome were further evaluated. Single-center retrospective observational study including pregnancies with prenatal diagnosis of ToF from 2010 to 2023. All cases were subdivided into ToF with pulmonary stenosis (PS) and pulmonary atresia (PA). Clinical and echocardiographic databases were reviewed for pregnancy outcome, genetic anomalies, and postnatal course. The cohort included 169 cases, 124 (73.4%) with ToF/PS and 45(26.6%) with ToF/PA. Agenesis of the ductus arteriosus was significantly associated with RAA in both subtypes of ToF (p=0.001) compared to left aortic arch and found in 82.5% (33/40) versus 10.7% (9/84) of fetuses with ToF/PS and in 57.1% (8/14) versus 12.9% (4/31) of fetuses with ToF/PA. In both ToF/PS and ToF/PA, RAA/ADA versus RAA/patent DA revealed a significantly higher risk for the presence of genetic abnormalities, especially microdeletion 22q11.2, major aorto-pulmonary collateral arteries and a shorter time to complete surgical repair. We demonstrated a significantly increased frequency of RAA/ADA in patients with prenatally diagnosed ToF. Although this association revealed no significant impact on overall survival, the prenatal detection of RAA/ADA has implications for counseling, genetic evaluation and postnatal management.

Characterization of Alternaria blotch disease of apple in Himachal Pradesh, India: insights on morphology, pathogenicity, and molecular features.

Alternaria blotch disease in Himachal Pradesh, India, caused by Alternaria spp., adversely affects apple cultivars, resulting in reduced fruit size and quality accompanied by premature leaf fall. Sixteen Alternaria isolates from apple growing regions underwent comprehensive analysis including morphology, pathogenicity, and molecular characterization. Variations in conidiophore and conidia dimensions, shapes, and divisions were observed among isolates. Pathogenicity assays revealed differences in incubation periods, latent phases, and disease responses. Molecular characterization via nuclear ITS rDNA and RAPD analysis indicated 99-100% homology with Alternaria alternata, Alternaria mali, and other Alternaria spp., with a close phylogenetic relationship to Chinese isolates. Differentiation of isolates based on origin, cultural characteristics, and morphology was achieved using RAPD markers. The study identifies diverse genotypes and morphotypes of Alternaria contributing to apple blotch disease in Himachal Pradesh. These findings highlight the complexity of the pathogenic environment and hold significant implications for disease management in apple orchards.

Distribution pattern, population structure and habitat geography of Betula utilis subalpine forests of Kashmir region in the western Himalayas: implications for conservation and sustainable management

Distribution pattern, population structure and habitat geography of Betula utilis subalpine forests of Kashmir region in the western Himalayas: implications for conservation and sustainable management

Assessing Customer Satisfaction in Mahindra’s Automotive Division: The Role of Service Quality and Technological Integration

This study examines customer satisfaction in Mahindra's automotive division, highlighting the impact of technological integration and service excellence. Using a mixed-methods approach, the study examines qualitative insights from in-depth interviews with consumers and service staff in addition to quantitative data from customer surveys. The results show that excellent customer satisfaction is greatly increased by high service quality, with personnel competency, promptness, and reliability being important contributing variables. To further enhance the client experience, cutting-edge technology integration is essential. Examples of these are linked car features and digital service platforms. The report emphasizes how crucial it is for Mahindra to keep coming up with new ideas and tweaking its service plans in order to stay ahead of the competition and satisfy changing customer demands. The management implications emphasize how crucial it is to allocate resources to both human resources and The findings show that timeliness, dependability, and professionalism—the three qualities that make up service quality—are crucial in influencing consumer satisfaction. Additionally, by offering convenience and customized services, the integration of cutting-edge technologies—like digital service interfaces and linked car features—significantly improves the client experience. The results indicate that in order to exceed customer expectations and maintain competitive advantage, Mahindra should give equal weight to ongoing improvements in service quality and technology advances. In order to promote long-term customer loyalty and happiness, the study offers management practical insights by highlighting the necessity of strategic investments in personnel training and state-of-the-art technologies. Keywords: Customer satisfaction, Technology integration, Strategic investments, Competitive advantage, Personalized services, Management insights, Digital service interfaces, Connected car features.

Tangible or intangible satisfiers? Comparative study of visitor satisfaction in a nature-based tourism destination in the pre- and during-COVID pandemic

Nature-based destinations started to become objects of travel for various visitor segments during the COVID-19 pandemic. The changing environment and the travel conditions influence overall visitor satisfaction and its determinants. This study identifies the role of tangible and intangible factors in forming overall visitor satisfaction with a stay in a nature-based tourism destination and their changes due to the COVID-19 pandemic. A Generalized Linear Model with a logit link function was used to identify the significant satisfiers and to determine the factors that play a critical role in visitor satisfaction in the during-COVID era compared to the pre-COVID period. The results show that intangible satisfiers play a more significant role than tangible ones in the COVID time. Surprisingly, natural features are insignificant in explaining overall satisfaction at a nature-based destination in the during-COVID in comparison with the pre-COVID period. In contrast, active sports options have become a significant satisfier in the COVID era. This comparison results contribute to the current theory, and the findings indicate the practical implications for Destination Management Organisations regarding sustainable tourism development. Management implications•Destination Management Organisations (DMO) in nature-based destinations should become more conscious of changing visitor structures concerning destination satisfaction.•DMOs could focus more on promoting activities such as active sports options and tourism infrastructure than natural features regarding current visitor preferences; however, sustainability should be a fundamental goal of competitive tourism destinations.•There is a need to carefully deal with the expanding tourism infrastructure development and prevent uncontrolled growth of commercial activities and attractions that would act against the interests of residents and endanger the value of the natural environment.•DMOs should educate the changing visitors about the importance of responsible tourism.•DMOs should focus on environmental-friendly activities which do not negatively impact nature in terms of using land and natural areas for commercial activities and construction.•DMOs should make efforts to attract their environmental sensitive pre-COVID visitors and target new segments searching for health and sustainability, such as the Lifestyle of Health and Sustainability (LOHAS) segment and the Free Independent Travellers (FIT).

Skin manifestations and human immunodeficiency virus infection in the Tigray region, Ethiopia: Implications for clinical management and epidemiologic surveillance

AbstractBackgroundPatients with human immunodeficiency virus (HIV) infection may present a large variety of skin manifestations, often associated with significant morbidity. In turn, dermatological diseases may represent an early sign of HIV infection, particularly in resource‐limited settings.ObjectivesThis study aimed to assess the spectrum of dermatological diseases and their potential value as clinical proxies for the early detection and management of HIV in a rural region of Ethiopia.MethodsThe study was performed on a population of 67,161 patients with skin diseases attending the Italian Dermatological Center in Mekele, Tigray region, Ethiopia. HIV infection was diagnosed in 1892 individuals (1065 female), all naïve to antiretroviral therapy.ResultsInfectious skin diseases were present in 57.2% of the total HIV population. Among the infectious skin manifestations, dermatophytosis (20.5%), impetigo (5.9%), candidiasis (4.7%) and molluscum contagiosum (4.7%) were significantly more represented in patients with HIV infection (p &lt; 0.001). Regarding the noninfectious manifestations, pruritus and atrophy of the papillae on the tongue were significantly associated with HIV (p &lt; 0.001). Notably, females had a significantly higher incidence of dermatophytosis and seborrheic dermatitis as compared to their male counterparts (p &lt; 0.001), whereas scabies, psoriasis and leishmaniasis were significantly more frequent in males (p &lt; 0.001).ConclusionsSkin manifestations are common in HIV patients, often reflecting compromised immune status. In addition, Dermatophytosis and pruritus were the most frequently reported manifestations of HIV, thus representing useful clinical proxies to raise the suspicion of an underlying HIV infection. Besides, gender differences in skin manifestations should also be considered in the clinical evaluation.

Determinants of Purchasing Intention of Agricultural Products via E-commerce Platforms in Jakarta, Indonesia

The emergence of the internet as a global phenomenon is swiftly reshaping consumers' shopping habits and the process of purchasing goods and services. Consumers now have access to a wide array of products and services, especially with the aid of e-commerce. Additionally, companies can analyse consumer behaviour and gain a deeper understanding of their habits with the assistance of e-commerce or social media. The objective of this research is to ascertain the factors that impact consumers' intention to buy agricultural products. In April 2022, we performed an online consumer survey among 200 internet shoppers in Jakarta, Indonesia. The data was then analyzed using the WarpPLS software and Structural Equation Modeling (SEM). Our research showed that among the respondents, women, with an average age of 20–25 accounted for nearly 60% of respondents who purchased agricultural produce online in Jakarta. Moreover, SEM-PLS method revealed that the following factors had highly significant effects on consumers' purchasing intention to buy agricultural products in Indonesia: consumer behavior, subjective norms, demographic variables, time savings, and convenience. In light of these findings, it offers valuable technical and practical implications for agribusiness management and policymakers.

Cribriform versus Intraductal: How to Determine the Difference

Over the years, our understanding of cribriform and intraductal prostate cancer (PCa) has evolved significantly, leading to substantial changes in their classification and clinical management. This review discusses the histopathological disparities between intraductal and cribriform PCa from a diagnostic perspective, aiming to aid pathologists in achieving accurate diagnoses. Furthermore, it discusses the ongoing debate surrounding the different recommendations between ISUP and GUPS, which pose challenges for practicing pathologists and complicates consensus among them. Recent studies have shown promising results in integrating these pathological features into clinical decision-making tools, improving predictions of PCa recurrence, cancer spread, and mortality. Future research efforts should focus on further unraveling the biological backgrounds of these entities and their implications for clinical management to ultimately improve PCa patient outcomes.