Search

This editorial is being published simultaneously in multiple journals. It highlights now as the time to treat the climate and nature crisis as one indivisible global health emergency. [ABSTRACT FROM AUTHOR]

Over 200 health journals have issued a joint statement calling on the United Nations, political leaders, and health professionals to recognize that climate change and biodiversity loss are interconnected crises that must be addressed together. The statement emphasizes that the current approach of treating these issues separately is a dangerous mistake. The impacts of these crises on human health are significant and include disruptions to social and economic systems, shortages of land, shelter, food, and water, and the spread of infectious diseases. The health community must advocate for the restoration of biodiversity and the mitigation of climate change, and political leaders must recognize the threats to health and the potential benefits of addressing these crises. The statement concludes by urging the World Health Organization to declare the climate and nature crisis as a global health emergency. [Extracted from the article]

The objective of this research was to study the morphometric measurements, productive and reproductive performances of indigenous cows and heifers in Northern Azad Jammu & Kashmir (AJ&K). A total 237 phenotypic characteristics was recorded visually. Five main coat colors (reddish brown, light brown, black, white and grey) were found with black muzzle and eye-lashes. The head length was 37.7±0.2 cm with small horns (11±0.3 cm). The positive correlation between horn length/horn base circumference, ear length/ear width, forehead width/horn length were found statistically significant (p≤0.01). The highest positive correlations were found between age/rump width (0.77), age/parity (0.66), body weight/heart girth (0.62) and parity/rump width (0.60). The average age at puberty (41.02±0.6 months), average age at first service (49.3±0.7 months), age at first calving (58.54±0.7 months), mean gestation period (279.6±0.2 days), mean post-partum heat period (253.2±14.8 days), mean service period (257.69±5.8 days), mean calving interval (17.87±0.4 months), mean service per conception (1.5±0.06) and average milk yield per day (1.20±0.06 litre) were also recorded. In conclusion, the indigenous cattle are short stature, reddish brown in color with poor reproductive and productive performance. [ABSTRACT FROM AUTHOR]

No abstract available.

Potentially toxic elements such as Cd or Pb are serious pollutants in aquatic ecosystems, accumulating in fish and posing risks to humans. Our study analyzed 10 such elements in the muscle tissue of eight carnivorous fish species from the Caspian Sea. The differences between species were minor. However, higher levels of mercury were found in larger species. The concentrations of cadmium and lead determined were high, which led to the risk analysis giving a concerning result for children. Inorganic arsenic posed an acceptable cancer risk. Overall, our findings underscore the need for constant monitoring of the area to safeguard both aquatic ecosystems and human health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: This study evaluated the association between bypass grafting with multiarterial grafts (MAG) and single arterial grafts (SAG) and all-cause mortality and major adverse cardiovascular and cerebrovascular events (MACCE), overall and across different patient subgroups from a Middle Eastern nation., Methods: This single-center retrospective cohort study included 23,798 patients. MAG and SAG groups were balanced using inverse probability weighting (IPW). Associations between MAG and outcomes were assessed using Cox regression. A series of covariate-adjusted Cox models were conducted to evaluate the effect of MAG on outcomes at different levels of independent variables, including age, sex, and cardiovascular risk factors., Results: In the study population (73.9% were men, 65.11 ± 9.94 years), 986 patients (4.1%) underwent MAG. Compared with the SAG group, MAG had lower crude mortality (14.1% vs 21.6%) and MACCE (28.8% vs 34.7%) rates during a median follow-up of 9.23 years (quartile 1-quartile 3, 9.13-9.33 years). Although MAG was significantly associated with reduced risk of study outcomes at the univariate level, these associations disappeared after matching (all-cause mortality (IPW hazard ratio, 0.90; 95% CI, 0.67-1.22) and MACCEs (IPW hazard ratio, 0.94; 95% CI, 0.76-1.15). However, covariate-adjusted models indicated that MAG was associated with a significantly reduced risk of adverse events, particularly MACCEs, in men, younger patients, and those without risk factors., Conclusions: MAG was not associated with improved postsurgery outcomes among the total coronary artery bypass graft population. Our findings, however, should be interpreted in the context of a relatively low total institutional MAG burden. Choosing a second arterial conduit over saphenous vein grafts in specific patient subgroups might be reasonable. This hypothesis-generating finding should be investigated in future clinical trials in these patients., Competing Interests: Disclosures Mario Gaudino is on The Annals of Thoracic Surgery Editorial Board. The other authors have no conflicts of interest to disclose., (Copyright © 2024 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.)

Microplastics (MPs) are concerning emerging pollutants. Here, MPs in four edible aquatic species of different trophic levels (between ∼2 and 4), including fish species Esox lucius (Esocidae: Esocinae); Cyprinus carpio (Cyprinidae: Cyprininae); and Luciobarbus caspius (Cyprinidae: Barbinae); and the swan mussel Anodonta cygnea (Unionidae), were assessed in the Anzali freshwater ecosystem. It is a listed wetland in the Montreux record. MPs were extracted from gastrointestinal tracts (GI), gills, muscles, and skin. All the studied fish and mussels (n = 33) had MPs. MP fibres, fragments and sheets were detected in every GI examined, however, fibres were the only type of MPs in skins, muscles and gills and were the most abundant MP. The MPs found in the fish and mussels were mainly made of nylon (35% of the total MPs), polypropylene-low density polyethylene (30%), and polycarbonate (25%). The average numbers of MPs found in every fish specimen, expressed per wet body mass, had a moderate negative correlation with the condition factor (K) (MP/g - K: Pearson correlation r = -0.413, p = 0.049), and there was no significant relation with the growth factor (b) (r = -0.376; p = 0.068). Importantly, Luciobarbus caspius (with trophic level 2.7-2.8) bioaccumulated MPs and presented a strong correlation between their MP contamination and age (r = 0.916 p < 0.05). Greater gill mass (or related factors) played an important role in the accumulation of MPs, and there was a strong correlation between these factors for Esox lucius and Cyprinus carpio (r = 0.876; r = 0.846; p < 0.05 respectively). The highest MP/g gills (1.91 ± 2.65) were in the filter feeder Anodonta cygnea inhabiting the benthic zone. Esox lucius (piscivorous, trophic level 4.1) was the most contaminated species overall (a total of 83 MPs in 8 individuals, with 0.92 MP/g fish), and their gills where MPs mainly accumulated. Cyprinus carpio was the most contaminated specimen (MPs in specimens), while the number of MPs per mass unit increased with the trophic level. Their feeding and ecological behavior in the aquatic habitat affected the level of accumulation. This work includes evidence of translocation of MPs within the aquatic organisms., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Hamid Reza Esmaeili reports a relationship with Shiraz University that includes: funding grants. Maryam Saemi reports a relationship with Ministry of Science Research and Technology of the Islamic Republic of Iran that includes: funding grants. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

Aims: This review aimed to investigate the different types of microparticles playing role in obesity-related diseases. Additionally, the factors participating in changing the microparticles amount in obese people will also be discussed., Material & Methods: The authors collected the relevant articles published until 2023 and these are carefully selected from three scientific databases based on keywords., Key Findings: It has been revealed that exercise might change the microparticle content in the body. The other factor which participates in obesity process is the oxidative stress which is increased in microparticles. Moreover, the obesity is implicated in metabolic conditions including diabetes and cardiovascular diseases., Significance: More than one-third of people on the planet today are known as overweight individuals. Microparticles (MPs) are small membrane-bound vesicles that are found in healthy people's blood and are elevated in patients with pathological conditions such as obesity. MPs mostly come from platelets, leukocytes, endothelial cells, and vascular smooth muscle cells. Considering the effect of obesity on microparticles, these small membrane-bound vesicles might play a crucial role in preventing or treatment of obesity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have influenced the work reported in this paper. This research received no specific grant from any funding., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Background: Cytokine-induced killer (CIK) cells are a novel subgroup of immune effectors, classified as one of the modified T cell-mediated arms for immunotherapy. These cells exert MHC-unrestricted cytotoxicity against both hematological and solid malignancies with low incidence of treatment-related severe complications. This study reviews the application of CIK cells in treating cases with hematologic malignancies., Main Body: CIK cells consist of CD3 + /CD56 +  natural killer (NK) T cells, CD3 - /CD56 + NK cells, and CD3 + /CD56 - cytotoxic T cells. In this regard, the CD3 + /CD56 +  NK T cells are the primary effectors. Compared with the previously reported antitumor immune cells, CIK cells are characterized by improved in vitro proliferation and amplification, enhanced migration and invasive capacity to tumor region, more significant antitumor activity, and a broader antitumor spectrum. CIK cells can also induce death in tumor cells via numerous pathways and mechanisms. Hence, CIKs-based therapy has been used in various clinical trials and has shown efficacy with a very low graft versus host disease (GVHD) against several cancers, such as hematologic malignancies, even in relapsing cases, or cases not responding to other therapies. Despite the high content of T cells, CIK cells induce low alloreactivity and, thus, pose a restricted threat of GVHD induction even in MHC-mismatched transplantation cases. Phase 1 and 2 clinical trials of CIK cell therapy have also highlighted satisfactory therapeutic advantages against hematologic cancers, indicating the safety of CIK cells even in haploidentical transplantation settings., Conclusion: CIK cells have shown promising results in the treatment of hematologic malignancies, especially in combination with other antitumor strategies. However, the existing controversies in achieving desired clinical responses underscore the importance of future studies., (© 2024. The Author(s).)

Recent composites are being developed to simplify shade matching in composite restorations. Only a limited amount of research has been conducted to determine the optical performance of this newly introduced composite in this area. This study investigated the Omnichroma (OMN) color matching (a single shade composite within type-I restorations) via simulated clinical cavities. A total of 72 frames were created by occupying the mold with Estelite Σ Quick (ES) of A1, A2, and A3 shades ( n = 24). Each shade of composite frame was divided into three subgroups ( n = 8) according to cavity dimension (width = 2, 3, and 4 mm/depth = 2 mm). Cavities were filled with Omnichroma. Color parameters were calculated based on CIEDE2000 (ΔE00) using a non-contact spectrophotometer. Finally, the data were analyzed using a two-way ANOVA (the Tukey HSD test) ( P = 0.05). The surrounding frame color significantly affected the color-matching capacity of OMN ( P < 0.0001). Groups A1 and A3 showed the lowest and highest amounts of ΔE00, respectively. The cavity width also influenced the color-matching ability of OMN ( P < 0.0001) significantly. According to the results, 4 mm cavity width showed the lowest amount of ΔE00, and 2 mm showed the highest amount. Monochromatic composites (OMN) did not match colors well in Class I cavities in posterior teeth. In cases of teeth with less chromatic surroundings, OMN matched shades better. OMN could better match shades in posterior teeth with wider cavities., Competing Interests: The authors declare no conflict of interest., (© 2024 The Author(s).)

Cancer treatment has become one of the biggest challenges in the world today. Different treatments are used against cancer; drug-based treatments have shown better results. On the other hand, designing new drugs for cancer is costly and time-consuming. Some computational methods, such as machine learning and deep learning, have been suggested to solve these challenges using drug repurposing. Despite the promise of classical machine-learning methods in repurposing cancer drugs and predicting responses, deep-learning methods performed better. This study aims to develop a deep-learning model that predicts cancer drug response based on multi-omics data, drug descriptors, and drug fingerprints and facilitates the repurposing of drugs based on those responses. To reduce multi-omics data's dimensionality, we use autoencoders. As a multi-task learning model, autoencoders are connected to MLPs. We extensively tested our model using three primary datasets: GDSC, CTRP, and CCLE to determine its efficacy. In multiple experiments, our model consistently outperforms existing state-of-the-art methods. Compared to state-of-the-art models, our model achieves an impressive AUPRC of 0.99. Furthermore, in a cross-dataset evaluation, where the model is trained on GDSC and tested on CCLE, it surpasses the performance of three previous works, achieving an AUPRC of 0.72. In conclusion, we presented a deep learning model that outperforms the current state-of-the-art regarding generalization. Using this model, we could assess drug responses and explore drug repurposing, leading to the discovery of novel cancer drugs. Our study highlights the potential for advanced deep learning to advance cancer therapeutic precision., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Mohammadzadeh-Vardin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Competing Interests: Competing interests: We have read and understood BMJ policy on declaration of interests and have no interests to declare.

Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to offer a systematic approach for drug repurposing to achieve cost savings and enhance human lives. In recent years, using biological network-based methods for drug repurposing has generated promising results. Nevertheless, these methods have limitations. Primarily, the scope of these methods is generally limited concerning the size and variety of data they can effectively handle. Another issue arises from the treatment of heterogeneous data, which needs to be addressed or converted into homogeneous data, leading to a loss of information. A significant drawback is that most of these approaches lack end-to-end functionality, necessitating manual implementation and expert knowledge in certain stages., Results: We propose a new solution, Heterogeneous Graph Transformer for Drug Repurposing (HGTDR), to address the challenges associated with drug repurposing. HGTDR is a three-step approach for knowledge graph-based drug repurposing: (1) constructing a heterogeneous knowledge graph, (2) utilizing a heterogeneous graph transformer network, and (3) computing relationship scores using a fully connected network. By leveraging HGTDR, users gain the ability to manipulate input graphs, extract information from diverse entities, and obtain their desired output. In the evaluation step, we demonstrate that HGTDR performs comparably to previous methods. Furthermore, we review medical studies to validate our method's top 10 drug repurposing suggestions, which have exhibited promising results. We also demonstrated HGTDR's capability to predict other types of relations through numerical and experimental validation, such as drug-protein and disease-protein inter-relations., Availability and Implementation: The source code and data are available at https://github.com/bcb-sut/HGTDR and http://git.dml.ir/BCB/HGTDR., (© The Author(s) 2024. Published by Oxford University Press.)

Introduction: Reduced left ventricular ejection fraction (LVEF) is a well-known predictor of adverse events after cardiac surgery. We aimed to assess the outcomes in patients with low LVEF undergoing coronary artery bypass graft., Methods: In this retrospective cohort, we included all patients with left ventricular ejection fraction ≤ 40 who underwent coronary artery bypass grafting between March 2007 and March 2016 (with a median follow-up of nine years) at Tehran Heart Center. Demographics and clinical characteristics were extracted from the data registry. Akaike information criterion (AIC) was used. The univariate Cox regression was performed. We investigated the predictors of mortality and major adverse cardiac and cerebrovascular events (MACCE) using Cox multivariable regression., Results: In total, 5,532 cases (79 % male) with a mean age of 65.58 were included in the study. The nine-year overall survival was calculated at 68 %, and more than half of the patients had MACCE (55 %). In adjusted multivariable Cox regression analysis, moderate to severe mitral valve regurgitation, glomerular filtration rate ≤ 60, mild right ventricular dysfunction, and valvular heart disease independently predicted higher mortality. The abovementioned predictors and peripheral vascular disease significantly increased MACCE., Conclusion: Our study indicates the clinical significance of mitral regurgitation, valvular heart disease, and renal function in patients with low ejection fraction treated by coronary artery bypass grafting surgery. Identifying predictors of adverse events can help with clinical decision-making and risk stratification, ultimately improving patient outcomes., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V.)

Competing Interests: Commissioning and peer review: Commissioned; not externally peer reviewed.

Drug synergy prediction plays a vital role in cancer treatment. Because experimental approaches are labor-intensive and expensive, computational-based approaches get more attention. There are two types of computational methods for drug synergy prediction: feature-based and similarity-based. In feature-based methods, the main focus is to extract more discriminative features from drug pairs and cell lines to pass to the task predictor. In similarity-based methods, the similarities among all drugs and cell lines are utilized as features and fed into the task predictor. In this work, a novel approach, called CFSSynergy, that combines these two viewpoints is proposed. First, a discriminative representation is extracted for paired drugs and cell lines as input. We have utilized transformer-based architecture for drugs. For cell lines, we have created a similarity matrix between proteins using the Node2Vec algorithm. Then, the new cell line representation is computed by multiplying the protein-protein similarity matrix and the initial cell line representation. Next, we compute the similarity between unique drugs and unique cells using the learned representation for paired drugs and cell lines. Then, we compute a new representation for paired drugs and cell lines based on the similarity-based features and the learned features. Finally, these features are fed to XGBoost as a task predictor. Two well-known data sets were used to evaluate the performance of our proposed method: DrugCombDB and OncologyScreen. The CFSSynergy approach consistently outperformed existing methods in comparative evaluations. This substantiates the efficacy of our approach in capturing complex synergistic interactions between drugs and cell lines, setting it apart from conventional similarity-based or feature-based methods.

The use of photobiomodulation therapy (PBMT) may be used for treating trauma to the maxillofacial region. The effects of PBMT on maxillofacial injuries were discussed in this review article. The electronic databases Pubmed, Scopus, and Web of Science were thoroughly searched. This review included in vitro, in vivo, and clinical studies describing how PBMT can be used in maxillofacial tissue engineering and regenerative medicine. Some studies suggest that PBMT may offer a promising therapy for traumatic maxillofacial injuries because it can stimulate the differentiation and proliferation of various cells, including dental pulp cells and mesenchymal stem cells, enhancing bone regeneration and osseointegration. PBMT reduces pain and swelling after oral surgery and tooth extraction in human and animal models of maxillofacial injuries. Patients with temporomandibular disorders also benefit from PBMT in terms of reduced inflammation and symptoms. PBMT still has some limitations, such as the need for standardizing parameters. PBMT must also be evaluated further in randomized controlled trials in various maxillofacial injuries. As a result, PBMT offers a safe and noninvasive treatment option for patients suffering from traumatic maxillofacial injuries. PBMT still requires further research to establish its efficacy in clinical practice and determine the optimal parameters., (© 2024 John Wiley & Sons Ltd.)

This study highlights the therapeutic potential of activating brown adipose tissue (BAT) for managing polycystic ovary syndrome (PCOS), a prevalent endocrine disorder associated with metabolic and reproductive abnormalities. BAT plays a crucial role in regulating energy expenditure and systemic insulin sensitivity, making it an attractive target for the treatment of obesity and metabolic diseases. Recent research suggests that impaired BAT function and mass may contribute to the link between metabolic disturbances and reproductive issues in PCOS. Additionally, abnormal white adipose tissue (WAT) can exacerbate these conditions by releasing adipokines and nonesterified fatty acids. In this review, we explored the impact of WAT changes on BAT function in PCOS and discussed the potential of BAT activation as a therapeutic strategy to improve PCOS symptoms. We propose that BAT activation holds promise for managing PCOS; however, further research is needed to confirm its efficacy and to develop clinically feasible methods for BAT activation., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Masoud Darabi reports financial support was provided by Tabriz University of Medical Sciences Drug Applied Research Center., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Background: Premenstrual syndrome (PMS) is one of the most prevalent disorders among reproductive women worldwide that negatively impact women's quality of life. This study aimed to investigate the effect of vitamin D supplementation on the severity of PMS symptoms in vitamin D insufficient women with PMS., Methods: In this randomized, double-blind clinical trial, 44 vitamin D insufficient women with PMS received either 50,000 IU vitamin D or a placebo fortnightly for 16 weeks. Participants completed the PMS Daily Symptoms Rating form at beginning and during the last two months of the intervention, and their blood samples were collected to assess 25(OH)D serum levels., Results: After the four months' intervention, the serum level of 25(OH)D in the vitamin D group raised from 21 ± 8 ng/ml to 40 ± 8 ng/ml (P < 0.001), while in the placebo group it raised from 21 ± 7 ng/ml to 23 ± 7 ng/ml (P = 0.03). Indeed, serum vitamin D levels in the placebo group could not reach a sufficient level. At the end of the intervention, the mean score of total PMS symptoms showed significant improvement in the vitamin supplemented group compared to the controls (p < 0.001). By grouping the PMS symptoms into five subgroups, the mean score of all five subgroups decreased post-supplementation compared to the baseline; however, the highest and lowest decrease were in depression (53 %) and water retention subgroups (28 %), respectively. This indicates a greater improvement in the mean scores of mood symptoms compared to physical symptoms in this study (p < 0.001)., Conclusion: Results obtained in this clinical trial represent the helpful effects of vitamin D supplementation on total, physical and mood symptoms in vitamin D insufficient women with PMS., Trial Registration: This randomized controlled trial at IRCT.ir on 2018-06-20 with Registration No: IRCT20180525039822N1., Competing Interests: Declaration of competing interest The authors declare that they have no competing interests., (Copyright © 2023 European Society for Clinical Nutrition and Metabolism. Published by Elsevier Ltd. All rights reserved.)

Background: The Drug-Target Interaction (DTI) prediction uses a drug molecule and a protein sequence as inputs to predict the binding affinity value. In recent years, deep learning-based models have gotten more attention. These methods have two modules: the feature extraction module and the task prediction module. In most deep learning-based approaches, a simple task prediction loss (i.e., categorical cross entropy for the classification task and mean squared error for the regression task) is used to learn the model. In machine learning, contrastive-based loss functions are developed to learn more discriminative feature space. In a deep learning-based model, extracting more discriminative feature space leads to performance improvement for the task prediction module., Results: In this paper, we have used multimodal knowledge as input and proposed an attention-based fusion technique to combine this knowledge. Also, we investigate how utilizing contrastive loss function along the task prediction loss could help the approach to learn a more powerful model. Four contrastive loss functions are considered: (1) max-margin contrastive loss function, (2) triplet loss function, (3) Multi-class N-pair Loss Objective, and (4) NT-Xent loss function. The proposed model is evaluated using four well-known datasets: Wang et al. dataset, Luo's dataset, Davis, and KIBA datasets., Conclusions: Accordingly, after reviewing the state-of-the-art methods, we developed a multimodal feature extraction network by combining protein sequences and drug molecules, along with protein-protein interaction networks and drug-drug interaction networks. The results show it performs significantly better than the comparable state-of-the-art approaches., (© 2024. The Author(s).)