bluuebunny/crossref_metadata_2025_split huggingface dataset:
The abundance of the remaining mammalian fauna and the impacts of hunting in a biodiversity hotspot´s hotspot in the Atlantic forest of north-eastern Brazil
Authors: Melo Éverton Renan Andrade , Gadelha José Ramon , Lucena Leandro Ricardo Rodrigues , Pontes Antonio Rossano Mendes 
Published: September 2023

Abstract

Although hunting in the north-eastern Atlantic forest of Brazil began more than 500 years ago, no studies to date have evaluated its impacts on the region´s mammalian fauna. For one year we carried out diurnal and nocturnal surveys using the Line Transect method in forest fragments varying from 7.32 ha to 469.76 ha, within a 4,000 ha forest island archipelago. We calculated species density, population size, biomass and synergetic biomass, and recorded direct and indirect human impacts along the study transects. We recorded 44 mammalian species, of which 45.5% (n = 20) went extinct. The smallest forest fragment had the lowest richness (n = 1), diversity (0.0001), population size (n = 10), and total biomass (38.91 kg/km2). It also had no synergetic biomass. The largest fragment had the highest richness (n = 7), total density (279.52 ind./km2), and population size (n = 1,298 individuals). There was a statistically significant relationship between fragment area and number of gunshots heard (r = 0.825, p = 0.022) and suspended hunting platforms found (r = 0.958, p = 0.001); between population size and gunshots heard (r = 0.871, p = 0.011), suspended hunting platforms (rho = 0.896, p = 0.006), free-roaming and feral dogs (r = 0.786, p = 0.036), and between total density and free-roaming and feral dogs (r = 0.783, p = 0.037). After more than 500 years of colonization hunting is still devastating, with larger fragments being linked to more hunters. Higher mammal abundances attracted more free-roaming and feral dogs, which have adapted to hunt wildlife on their own. Unless we protect every single forest fragment and create sustainable landscapes, we will not be able to save this hotspot´s hotspot.
Optimizing application of the Species Threat Abatement and Restoration (STAR) metric in meeting national biodiversity conservation targets
Authors: Asefa Addisu , Delellegn Yilma , Debella Abdeta Robi , Mario Melese , Dalle Gemedo , Wakjira Kumara , Vergez Antonin , Curet Florence , Tessema Mekbeb 
Published: September 2023

Abstract

The Species Threat Abatement and Restoration (STAR) metric was developed to quantify the contributions that abating threats (STAR-T) and restoring habitats (STAR-R) offer towards reducing global species extinction risk. Currently, global level estimated STAR score is calculated for 5,359 vertebrate species spanning 195 countries, using global level data. Although the STAR metric is scalable across species, threats and geographies, disaggregating the global STAR scores down to national level may be prone to error due to spatial variations in species and threats presence. Thus, verification based on national level data is needed. Yet it may not always be possible to conduct verification due to lack of data in developing countries. Here, we used simple calibration and verification strategies to show how to overcome such setbacks and optimize application of the metric at national scale for Ethiopia. We revised the species and threats lists included in the global level estimated STAR, (re)calculated STAR scores and ranked the threats. Then, we compared consistency of this threat ranking with threat ranking based on national biodiversity experts’ opinions. Our total estimated STAR-T and STAR-R scores for Ethiopia were 12504.65 and 5360.53, respectively. Crop and livestock productions appeared to be the most impactful threats to the species. We found strong correlation in threat ranks between the STAR score and experts’ opinion. We conclude that simple verification processes can optimise the application of the STAR metric at national level to support conservation actions and achieve science-based objectives.
Expression and clinical significance of CREB1 and CREB3 in gastric cancer and precancerous lesions
Authors: Liu Lixia , Li Xiaoxia , Kang Ruxue , Ye Qianru , Wang Hui , Yue Xin , Chai Jianyuan , Wang Chi 
Published: September 2023

Abstract
Background: To investigate the expression and clinical significance of cyclic adenosine monophosphate responsive CREB1 and CREB3 in gastric cancer and precancerous lesions.
Methods and Results: All data was collected in June 2021 to April 2022 from the second affiliated hospital of Baotou medical college with archive wax block of 40 cases of chronic superficial gastritis. The expressions of CREB1 and CREB3 in different gastric tissues were detected by Western blot. Kaplan-meier Plotter was used to analyze the correlation between the expression of CREB1 and CREB3 and overall survival and progression-free survival of gastric cancer patients. The positions of CREB1 and CREB3 in the signaling pathway and their related upstream and downstream genes were analyzed using STRING database. (1) Immunohistochemistry staining results showed the positive expression rates of CREB1 and CREB3 in gastric cancer group significantly higher than those in chronic atrophic gastritis with intestinal metaplasia, but there was no significant difference between them and dysplasia group. Clinicopathological parameters analysis showed that the expression levels of both were correlated with depth of invasion, TNM stage, vascular invasion and lymph node metastasis. (2) Western blot results indicated that the protein expression of CREB1 and CREB3 increased successively in chronic superficial gastritis, chronic atrophic gastritis with intestinal metaplasia, and gastric cancer, and the difference was statistically significant.
Conclusion: CREB1 and CREB3 may be related to the occurrence, development and metastasis of gastric cancer, and the high expression of CREB1 and CREB3 may be related to the poor prognosis of gastric cancer patients.
Enhancing Intrusion Detection in Wireless Sensor Networks through Deep Hybrid Network Empowered by SC-Attention Mechanism
Authors: Gatate Veeranna , Agarkhed Jayashree 
Published: September 2023

Abstract

WSNs are often deployed in unattended or hostile environments, making them vulnerable to various types of attacks. Ensuring the security of WSNs is crucial, especially if the data being monitored is sensitive or critical. An intrusion detection system (IDS) can help detect unauthorized access or malicious activities within the network. In the field of network intrusion detection systems (NIDS), traditional approaches face limitations in effectively detecting evolving threats and unknown attack patterns. To overcome these challenges, this research proposes a novel approach called the Deep Hybrid Network with spatial and channel attention (DHN-SCA) that integrates deep learning techniques with attention mechanisms. The DHN combines convolutional neural networks (CNNs) with a Local Attention Module to enhance the accuracy and efficiency of intrusion detection. The Local Attention Module consists of two sub-modules: Spatial Attention and Channel Attention. Spatial Attention applies average pooling to the feature tensor, while Channel Attention incorporates global average pooling and global max pooling followed by fully connected layers. These sub-modules refine the feature tensor through element-wise multiplication operations with the original features. Experiments and evaluations are conducted on benchmark datasets to assess the performance of the DHN. Evaluation metrics such as accuracy, precision, recall, and F1 score are employed to compare the DHN's effectiveness with existing intrusion detection approaches.
Development of a tool for predicting HNF1B mutations in children with congenital anomalies of the kidneys and urinary tract – a retrospective multicenter study
Authors: Kolbuc Marcin , Kolek Mateusz , Motyka Rafal , Bienias Beata , Habbig Sandra , Burgmaier Kathrin , Prikhodina Larisa , Papizh Svetlana , Tasic Velibor , Okorn Christine , Szczepanska Maria , Kilis-Pstrusinska Katarzyna , Wasilewska Anna , Adamczyk Piotr , Tkaczyk Marcin , Panczyk-Tomaszewska Malgorzata , Miklaszewska Monika , Pawlaczyk Krzysztof , Bukowska-Olech Ewelina , Jamsheer Aleksander , Jankauskiene Augustina , König Jens , Cheong Hae Il , Ahn Yo Han , Kaspar Sophie , Sikora Przemyslaw , Beck Bodo , Zaniew Marcin 
Published: September 2023

Abstract
Background The diagnosis of HNF1B disease is a challenge. We aimed to developa tool for predicting HNF1B mutations in children with congenital abnormalities of the kidneys and urinary tract (CAKUT).
Methods The clinical and laboratory data from 234 children and young adults with known HNF1B mutation status were collected and analyzed retrospectively. All subjects were randomly divided into a training (70%) and
a validation set (30%). A random forest model was constructed to predict HNF1B mutations. The recursive feature elimination algorithm was used for feature selection into the model, and receiver operating characteristiccurve statistics were used to verify its predictive effect.
Results 213 patients were analyzed, including HNF1B‑positive (mut+, n=109) and HNF1B‑negative (mut−, n=104) subjects. The majority of patients had mild chronic kidney disease. Kidney phenotype was similar between groups, but bilateral kidney anomalies were more frequent in the mut+ group. Hypomagnesemia and hypermagnesuria were the most common abnormalities in mut+ patients, and were highly selective of HNF1B. Hypomagnesemia based on age‑appropriate norms had a better discriminatory value than the age‑independent cutoff of 0.7 mmol/l. Pancreatic anomalies were almost exclusively found in mut+ patients. No subjects had hypokalemia; the mean serum potassium level was lower in the HNF1Bcohort. The above‑mentioned, discriminative parameters were selected for the model, which showed a good performance (area under the curve: 0.85; sensitivity of 93.67%, specificity of 73.57%). A corresponding calculator was developed for use and validation.
ConclusionThis study developed a simple tool for predicting HNF1B mutations in children with CAKUT.
Dissecting coral recovery: Bleaching reduces reproductive output in Acropora millepora
Authors: Briggs Nico D , Page Cathie A , Giuliano Christine , Alessi Cinzia , Hoogenboom Mia , Bay Line K , Randall Carly J 
Published: September 2023

Abstract

Increasingly frequent and severe bleaching events driven by climate change are decreasing coral populations worldwide. Recovery of these populations relies on reproduction by the survivors of such events including local and upstream larval sources. Yet, corals that survive bleaching may be impaired by sublethal effects that suppress reproduction, reducing larval input to reefs, and consequently impeding recovery. We investigated the impact of the 2020 mass-bleaching event on Acropora millepora reproduction on inshore, turbid reefs in Woppaburra sea Country (the Keppel Islands), to improve our understanding of the effects of bleaching on coral populations. A. millepora experienced high bleaching incidence but low mortality across the island group during this event and thus constituted an ideal population to investigate potential sublethal effects on reproductive output. Six months after the heat wave, and just prior to spawning, we collected, decalcified, and dissected samples from 94 tagged A. millepora colonies with a known 2020 bleaching response, to investigate the relationships between stress severity and reproduction. Despite having regained their pigmentation, we detected a significant reduction in fecundity in colonies that had bleached severely. Considering the impact of the bleaching event on the coral population sampled (i.e. mortality, bleaching severity and colony size), coupled with reductions in fecundity, we estimated a total decrease in population-level reproductive output of 21%. These results suggest that reduced reproductive output may impact recovery of coral populations following bleaching and should be considered alongside traditional estimates from coral mortality.
Two Hidden Layer’s Markov Model for Studying Type 2 Diabetes
Authors: padi Tirupati Rao , Narendra Surnam 
Published: September 2023

Abstract
Diabetes is a metabolic disorder that can be regulated through proper physical activity and diet management. This paper is about developing a stochastic model by using Layered Hidden Markov Model (LHMM) for diabetes. In LHMM, we considered two hidden layers and one emission state layer. Here, we find out the probability of emission state sequence by the forward algorithm. Further, we derived probability mass function for one-state, two-state and three-state sequences for non-diabetes and diabetes emission states. We also derived the explicit relations for mean, variance and other Pearson’s coefficients of Skewness and Kurtosis of the formulated probability distribution. The model behaviour is studied in detail with real-time data on diabetes from secondary data sources. This study considered three variables, namely (i) physical activity, (ii) obesity category based on BMI, and (iii) having diabetes. It is assumed that diabetes is influenced by obesity, and obesity is influenced by physical activity. After a thorough analysis of data, it is observed that (i) from one day sequence, the state of non-diabetes is more likely, (ii) from the two-day sequence, the chances of the probability for two consecutive occurrences of the emission state of non-diabetes is 0.50; and (iii) from the three-day sequence, the chance of three consecutive occurrences of the emission state non-diabetes is around 0.38. From the transition and emission probability matrices, we found that those who are doing physical activity daily have less chance of obesity, and those who are not doing physical activity have a high chance of obesity, and later, they will be getting the risk of diabetes
Adapting cognitive remediation group therapy: A community-based, focus group study
Authors: Eaton Andrew D. , Hui Jenny , Muchenje Marvelous , Kon Taylor , Murzin Kate , Carusone Soo Chan , Novik Nuelle , Quigley Adria , Kokorelias Kristina , Ibáñez-Carrasco Francisco 
Published: September 2023

Abstract

Cognitive impairment is a significant health issue for people aging with HIV/AIDS. With pharmacological treatment lacking, psychosocial group therapies may best help people aging with HIV who experience cognitive challenges cope with their symptoms. The COVID-19 pandemic revealed how in-person group therapies need adaptation for hybrid or online delivery. Peer-led focus groups discussed adapting cognitive remediation group therapy (CRGT) as a hybrid or online intervention. CRGT combines mindfulness-based stress reduction and brain training activities. Purposive sampling was used to recruit people aging with HIV (40+) who self-identified cognitive concerns and resided in one of two Canadian provinces. Thematic content analysis was employed on transcripts by seven independent coders. Ten, two-hour focus groups were conducted between August and November 2022. Participant (n=45) demographics included age (M=53.22, SD=7.62), gender (45% women, 42% men, 13% trans/non-binary), sexual orientation (42% gay, 40% heterosexual, 18% other), ethnicity (45% White, 33% Black, 13% Indigenous, 9% mixed-race), and employment (33% employed, 67% retired/disability), and all on treatment and retained in care. Overall, participants responded favourably to CRGT’s modalities. Alongside support for its continued implementation in-person, participants requested online synchronous and online asynchronous formats. Preferred intervention facilitators were peers and mental health professionals. We also discuss how to adapt psychosocial HIV therapies for technology-mediated delivery, with consideration for behavioral HIV research.
Fermionization of a few-body Bose system immersed into a Bose-Einstein condensate
Authors: Keller Tim , Fogarty Thomás , Busch Thomas 
Published: September 2023

We study the recently introduced self-pinning transition [Phys. Rev. Lett. 128, 053401 (2022)] in a quasi-one-dimensional two-component quantum gas in the case where the component immersed into the Bose-Einstein condensate has a finite intraspecies interaction strength. As a result of the matter-wave backaction, the fermionization in the limit of infinite intraspecies repulsion occurs via a first-order phase transition to the self-pinned state, which is in contrast to the asymptotic behavior in static trapping potentials. The system also exhibits an additional superfluid state for the immersed component if the interspecies interaction is able to overcome the intraspecies repulsion. We approximate the superfluid state in an analytical model and derive an expression for the phase transition line that coincides with well-known phase separation criteria in binary Bose systems. The full phase diagram of the system is mapped out numerically for the case of two and three atoms in the immersed component.
The role of metallic nickel nanoparticles to remove dispersed oil from produced water in Sudan oil field plant
Authors: Suliman M. S. , Yasin Sahl , Mohammed Abdelhafeez M. A. 
Published: September 2023

Abstract

In this study, nickel nanoparticles (NiNPs) were synthesized and utilized for removing dispersed oil from oilfield-produced water in Sudan. The synthesis process involved using two concentration of hydrazine as a reducing agent and sodium hydroxide as solvent. Physiochemical characterizations, such as X-ray diffraction (XRD) and transmission electron microscopy (TEM), confirmed the successful preparation of NiNPs. The TEM analysis revealed an average particle size ranging from 70 to 90 nm, with a change in morphology from star-shaped to monodispersed spherical particles. The crystal structure analysis confirmed the face-centered-cubic (FCC) configuration of the NiNPs, validating their structural properties. Significantly, the NiNPs demonstrated an impressive capability to remove oil form produced water, achieving a remarkable efficiency of 98% in eliminating dispersed oil from produced water. The oil removal process followed Freundlich isotherms, as evidenced by the high value of the linear regression coefficient. Additionally, the kinetics of the oil removal process conformed well to the pseudo-second-order model, indicating a rapid reaction. This study successfully demonstrated the efficient removal of dispersed oil from produced water using nickel nanoparticles, which interacted physically with the oil particles. These findings highlight the potential of NiNPs as an effective adsorbent for treating oilfield-produced water and mitigating environmental contamination.
Screening of Immune-related lncRNAs in Lung Adenocarcinoma and
Establishing a Survival Prognostic Risk Prediction Model
Authors: Jiang Wenxia , Zhu Xuyou , Bo Jiaqi , Ma Jun 
Published: September 2023

Objective:
This study aimed to improve lung adenocarcinoma (LUAD) prognosis prediction
based on a signature of immune-related long non-coding RNAs (lncRNAs).

Methods:
LUAD samples from the TCGA database were divided into the immunity_H group and
the immunity_L group. Differentially expressed RNAs (DERs) between the two groups were identified.
Optimized immune-related lncRNAs combination was obtained using LASSO Cox regression.
A prognostic risk prediction (RS) model was built and further validated in the training and validation
datasets. A network among lncRNAs in the RS model, their co-expressed DERs, and the related
KEGG pathways were established. Critical lncRNAs were validated in LUAD tissue samples.

Results:
In total, 255 DERs were obtained, and 11 immune-related lncRNAs were significantly related
to prognosis. Six lncRNAs were demonstrated as an optimal combination for building the RS
model, including LINC00944, LINC00930, LINC00607, LINC00582, LINC00543, and
LINC00319. The KM curve and ROC curve revealed the RS model to be a reliable indicator for
LUAD prognosis. LINC00944 and LINC00582 showed a co-expression relationship with the
MS4A1. LINC00944, LINC00582, and MS4A1 were successfully validated in LUAD samples.

Conclusion:
We have established a promising LUAD patient survival prediction model based on
six immune-related lncRNAs. For LUAD patients, this prognostic model could guide personalized
treatment.
Mini Review on Clinical Aspects of Monkeypox
Authors: Saraswat Yash , Shah Kamal 
Published: September 2023

Abstract:
Monkeypox is a disease caused by the monkeypox virus, which is a type of orthopox
virus that comes from the virus family Poxviridae. Its first case reported in animals and humans
was in 1958 and 1970, respectively. It is a viral zoonosis disease with two modes of transmission:
animal to human (via direct contact or eating the meat of an infected animal) and human to human
(via contact or contact with skin lesions, body fluids, and infected person’s contaminated objects).
The literature depicts that monkeypox is less contagious among individuals in contrast to smallpox;
the infection chain of monkeypox is nearly five to six patients approximately. It has two
clades, the West African and the Central African (the Congo basin). The Congo basin subgroup of
monkeypox is highly transmissible and severe. The symptoms of monkeypox include fever, lethargy,
headache, lymphadenopathy, myalgia, myodynia, fainting, shivers, backache, and rashes on
the face and extremities. The most common symptom of monkeypox is lymphatic hyperplasia or,
lymph adenopathy or swollen lymph nodes. It is proven to be very useful in the diagnosis of monkeypox.
The antiviral drugs that are used for its treatment are tecovirimat, brincidofovir and
cidofovir. Tecovirimat has fewer side effects and it shows better therapeutic action in comparison
to brincidofovir and cidofovir. For the prevention of monkeypox, the Center for Disease Control
and Prevention recommends the administration of the same vaccine used for smallpox
named INVAMUNE, which is currently in its third generation. Its first and second generations
have adverse side effects in patients having HIV or atopic dermatitis.
Drug Delivery System Approaches for Rheumatoid Arthritis Treatment: A
Review
Authors: Garhwal Anushka , Kendya Priyadarshi , Soni Sakshi , Kori Shivam , Soni Vandana , Kashaw Sushil Kumar 
Published: September 2023

Abstract:
Rheumatoid arthritis (RA) is a chronic autoimmune disease that has traditionally been
treated using a variety of pharmacological compounds. However, the effectiveness of these treatments
is often limited due to challenges associated with their administration. Oral and parenteral routes of
drug delivery are often restricted due to issues such as low bioavailability, rapid metabolism, poor
absorption, first-pass effect, and severe side effects. In recent years, nanocarrier-based delivery methods
have emerged as a promising alternative for overcoming these challenges. Nanocarriers, including
nanoparticles, dendrimers, micelles, nanoemulsions, and stimuli-sensitive carriers, possess unique
properties that enable efficient drug delivery and targeted therapy. Using nanocarriers makes it possible
to circumvent traditional administration routes' limitations. One of the key advantages of nanocarrier-
based delivery is the ability to overcome resistance or intolerance to traditional antirheumatic
therapies. Moreover, nanocarriers offer improved drug stability, controlled release kinetics, and enhanced
solubility, optimizing the therapeutic effect. They can also protect the encapsulated drug, prolonging
its circulation time and facilitating sustained release at the target site. This targeted delivery
approach ensures a higher concentration of the therapeutic agent at the site of inflammation, leading to
improved therapeutic outcomes. This article explores potential developments in nanotherapeutic regimens
for RA while providing a comprehensive summary of current approaches based on novel drug
delivery systems. In conclusion, nanocarrier-based drug delivery systems have emerged as a promising
solution for improving the treatment of rheumatoid arthritis. Further advancements in nanotechnology
hold promise for enhancing the efficacy and safety of RA therapies, offering new hope for patients
suffering from this debilitating disease.