Sports (Basel). 2025 Jan 21;13(2):28. doi: 10.3390/sports13020028.

ABSTRACT

The present study aimed to verify the (1) differences between players' roles in relation to technical and tactical and time-motion indicators, and the (2) relationships between individual time-motion and technical and tactical indicators for each role in a men's Italian football Serie A team. A total of 227 performances were analyzed (28 players: 8 forwards, FWs; 11 midfielders, MDs; 9 defenders, DFs). Technical and tactical indicators, such as ball possession (played balls, successful passes, successful playing patterns, lost balls, ball possession time), offensive play (total and successful dribbles, crosses, assists), and shooting (total shots, shots on target) were obtained by means of Panini Digital (DigitalSoccer Project S.r.l). In addition, a time-motion analysis included the total distance, distances covered at intensities of 16.0-19.8 km/h, 19.8-25.2 km/h, and over 25.2 km/h, the average recovery time between metabolic power peaks, and burst occurrence, the latter of which was performed by means of a 18 Hz GPS device (GPexe Pro2 system tool) worn by the players. Results showed role-specific differences: MDs covered more distance, while DFs had better ball possession. MDs and DFs had more successful playing patterns, and MDs and FWs performed more dribbles and shots. Strong correlations (p < 0.01, ρ > 0.8) were found between bursts and assists for FWs, high-intensity running and ball possession for MDs, and distance, dribbling, and shots for DFs. These findings highlight the importance of individual and tailored training programs to optimize role-specific performance demands.

PMID:39997959 | DOI:10.3390/sports13020028

Toxics. 2025 Feb 19;13(2):142. doi: 10.3390/toxics13020142.

ABSTRACT

Chemical exposure in the environment can adversely affect the biodiversity of living organisms, particularly when persistent chemicals accumulate over time and disrupt the balance of microbial populations. In this study, we examined how chemical contaminants influence microorganisms in sediment and overlaying water samples collected from the Kinnickinnic, Milwaukee, and Menomonee Rivers near Milwaukee, Wisconsin, USA. We characterized these samples using shotgun metagenomic sequencing to assess microbiome diversity and employed chemical analyses to quantify more than 200 compounds spanning 16 broad classes, including pesticides, industrial products, personal care products, and pharmaceuticals. Integrative and differential comparative analyses of the combined datasets revealed that microbial density, approximated by adjusted total sequence reads, declined with increasing total chemical concentrations. Protozoan, metazoan, and fungal populations were negatively correlated with higher chemical concentrations, whereas certain bacterial (particularly Proteobacteria) and archaeal populations showed positive correlations. As expected, sediment samples exhibited higher concentrations and a wider dynamic range of chemicals compared to water samples. Varying levels of chemical contamination appeared to shape the distribution of microbial taxa, with some bacterial, metazoan, and protozoan populations present only at certain sites or in specific sample types (sediment versus water). These findings suggest that microbial diversity may be linked to both the type and concentration of chemicals present. Additionally, this study demonstrates the potential roles of multiple microbial kingdoms in degrading environmental pollutants, emphasizing the metabolic versatility of bacteria and archaea in processing complex contaminants such as polyaromatic hydrocarbons and bisphenols. Through functional and resistance gene profiling, we observed that multi-kingdom microbial consortia-including bacteria, fungi, and protozoa-can contribute to bioremediation strategies and help restore ecological balance in contaminated ecosystems. This approach may also serve as a valuable proxy for assessing the types and levels of chemical pollutants, as well as their effects on biodiversity.

PMID:39997957 | DOI:10.3390/toxics13020142

Metabolites. 2025 Feb 6;15(2):101. doi: 10.3390/metabo15020101.

ABSTRACT

Background/Objectives: Determining appropriate cellular objectives is crucial for the system-scale modeling of biological networks for metabolic engineering, cellular reprogramming, and drug discovery applications. The mathematical representation of metabolic objectives can describe how cells manage limited resources to achieve biological goals within mechanistic and environmental constraints. While rapidly proliferating cells like tumors are often assumed to prioritize biomass production, mammalian cell types can exhibit objectives beyond growth, such as supporting tissue functions, developmental processes, and redox homeostasis. Methods: This review addresses the challenge of determining metabolic objectives and trade-offs from multiomics data. Results: Recent advances in single-cell omics, metabolic modeling, and machine/deep learning methods have enabled the inference of cellular objectives at both the transcriptomic and metabolic levels, bridging gene expression patterns with metabolic phenotypes. Conclusions: These in silico models provide insights into how cells adapt to changing environments, drug treatments, and genetic manipulations. We further explore the potential application of incorporating cellular objectives into personalized medicine, drug discovery, tissue engineering, and systems biology.

PMID:39997726 | DOI:10.3390/metabo15020101

Metabolites. 2025 Jan 26;15(2):76. doi: 10.3390/metabo15020076.

ABSTRACT

Background: Elevated choline kinase alpha (ChoK) levels are observed in most solid tumors, including glioblastomas (GBM), and ChoK inhibitors have demonstrated limited efficacy in GBM models. Given that hypoxia is associated with resistance to GBM therapy, we hypothesized that tumor hypoxia could be responsible for the limited response. Therefore, we evaluated the effects of hypoxia on the function of JAS239, a potent ChoK inhibitor in four GBM cell lines. Methods: Rodent (F98 and 9L) and human (U-87 MG and U-251 MG) GBM cell lines were subjected to 72 h of hypoxic conditioning and treated with JAS239 for 24 h. NMR metabolomic measurements and analyses were performed to evaluate the signaling pathways involved. In addition, cell proliferation, cell cycle progression, and cell invasion parameters were measured in 2D cell monolayers as well as in 3D cell spheroids, with or without JAS239 treatment, in normoxic or hypoxic cells to assess the effect of hypoxia on JAS239 function. Results: Hypoxia and JAS239 treatment led to significant changes in the cellular metabolic pathways, specifically the phospholipid and glycolytic pathways, associated with a reduction in cell proliferation via induced cell cycle arrest. Interestingly, JAS239 also impaired GBM invasion. However, effects from JAS239 were variable depending on the cell line, reflecting the inherent heterogeneity of GBMs. Conclusions: Our findings indicate that JAS239 and hypoxia can deregulate cellular metabolism, inhibit cell proliferation, and alter cell invasion. These results may be useful for designing new therapeutic strategies based on ChoK inhibition, which can act on multiple pro-tumorigenic features.

PMID:39997701 | DOI:10.3390/metabo15020076

Healthcare (Basel). 2025 Feb 10;13(4):376. doi: 10.3390/healthcare13040376.

ABSTRACT

Background: The risk of dying from chronic liver diseases (CLDs) is two to three times higher for patients with diabetes (DM). Nonalcoholic fatty liver disease (NAFLD) is the primary cause of this increased risk, which has an etiology unrelated to alcohol or viruses. Previous research reported that diabetes and CLD are related, since they influence each other. Aim: Estimation of the impact of diabetes (DM) on liver diseases (LD), and of the impact of liver diseases on DM among Egyptian and Saudi patients. It is a descriptive and prospective analytical study design. The investigation was carried out in Saudi Arabia and Egypt at gastroenterology outpatient clinics. Methods: Prospective data were collected through face-to-face patient interviews during clinic visits between June 2021 and June 2023. The interviews covered the patients' basic characteristics and information on DM and LD. Certain laboratory tests were conducted on these patients, such as liver function, glucose level, lipid profile, INR, and prothrombin time. Results: The total of 2748 participants in this study included 1242 diabetic patients of both genders from Saudi Arabia and 1506 from Egypt. Most Saudis had between 10 and 20 years' duration of DM (35.5%), with HbA1c (7-10%) values of 47.8%, while the Egyptian patients had >20 years' duration of DM (39.8%), with HbA1c (7-10%) values of 49.8%. Regarding the impact of DM on the development of liver diseases, about 35.5% (Saudis) vs. 23.5% (Egyptians) had liver diseases due to DM, a significant difference (p-value = 0.011). Liver enzymes were increased in many of the Egyptian and Saudi patients (41.4% vs. 33%), while the presence of fatty liver (28.2% vs. 35.7%) and hepatocellular carcinoma (13.7% vs. 6.1%) were also significantly different (p-value = 0.047). While the impact of liver diseases on DM was observed more among Egyptian (59%) than among Saudi (46.4%) patients because of liver cirrhosis (HCV or HBV), known to be a reason for diabetes in Egyptians (27.9%) vs. Saudis (8.0%), a higher incidence of fatty liver leading to DM was observed in Saudis than in Egyptians (15.9% vs. 11.6%) (p-value = 0.000. Obesity was more prevalent among Saudi patients (63.8%) than among Egyptian patients (48.6%) (p-value = 0.019). Fewer Egyptians (about 65%) suffered from dyslipidemia than Saudis (about 80%). Higher INR and longer prothrombin times were observed in Egyptians (29.9% and 29.1%, respectively) than in Saudis (20.3% and 18.8%, respectively), with a significant difference between the two nations (p-value < 0.050). Conclusions: We may conclude that diabetes in most patients has a negative impact on the development of liver diseases (particularly fatty liver in Saudi patients). In addition, most liver diseases (liver cirrhosis) have a negative influence on the development of DM (more so in Egyptian patients). There is a link between DM and liver disease. In particular, liver cirrhosis and diabetes were found to influence each other. Therefore, correct medication, adherence to treatment, lifestyle modifications, successful cirrhosis control (in patients with liver diseases), and diabetic control (in diabetic patients) could lead to effective management of both diseases. The negative fallouts in the two cases were prompted by obesity, morbid eating, and poor quality of life.

PMID:39997251 | DOI:10.3390/healthcare13040376

Cells. 2025 Feb 12;14(4):266. doi: 10.3390/cells14040266.

ABSTRACT

Liver fibrosis, a consequence of chronic liver injury, represents a major global health burden and is the leading cause of liver failure, morbidity, and mortality. The pathological hallmark of this condition is excessive extracellular matrix deposition, driven primarily by integrin-mediated mechanotransduction. Integrins, transmembrane heterodimeric proteins that serve as primary ECM receptors, orchestrate complex mechanosignaling networks that regulate the activation, differentiation, and proliferation of hepatic stellate cells and other ECM-secreting myofibroblasts. These mechanical signals create self-reinforcing feedback loops that perpetuate the fibrotic response. Recent advances have provided insight into the roles of specific integrin subtypes in liver fibrosis and revealed their regulation of key downstream effectors-including transforming growth factor beta, focal adhesion kinase, RhoA/Rho-associated, coiled-coil containing protein kinase, and the mechanosensitive Hippo pathway. Understanding these mechanotransduction networks has opened new therapeutic possibilities through pharmacological manipulation of integrin-dependent signaling.

PMID:39996739 | DOI:10.3390/cells14040266

Cells. 2025 Feb 11;14(4):257. doi: 10.3390/cells14040257.

ABSTRACT

Cells in heart muscle need to generate ATP at or near peak capacity to meet their energy demands. Over 90% of this ATP comes from mitochondria, strategically located near myofibrils and densely packed with cristae to concentrate ATP generation per unit volume. However, a consequence of dense inner membrane (IM) packing is that restricted metabolite diffusion inside mitochondria may limit ATP production. Under physiological conditions, the flux of ATP synthase is set by ADP levels in the matrix, which in turn depends on diffusion-dependent concentration of ADP inside cristae. Computer simulations show how ADP diffusion and consequently rates of ATP synthesis are modulated by IM topology, in particular (i) number, size, and positioning of crista junctions that connect cristae to the IM boundary region, and (ii) branching of cristae. Predictions are compared with the actual IM topology of a cardiomyocyte mitochondrion in which cristae vary systematically in length and morphology. The analysis indicates that this IM topology decreases but does not eliminate the "diffusion penalty" on ATP output. It is proposed that IM topology normally attenuates mitochondrial ATP output under conditions of low workload and can be regulated by the cell to better match ATP supply to demand.

PMID:39996730 | DOI:10.3390/cells14040257

Adv Respir Med. 2025 Feb 6;93(1):3. doi: 10.3390/arm93010003.

ABSTRACT

BACKGROUND: Asthma significantly impacts global health, necessitating effective management strategies. A combination of inhaled corticosteroids (ICSs) and long-acting β2-agonists (LABA) is recommended for patients with inadequately controlled asthma.

METHOD: This prospective, open-label, multicenter study (PROMISING-SHIFT) study evaluated the safety and efficacy of once-daily Indacaterol/Mometasone (IND/MF) dry powder inhaler (DPI) in Indian asthma patients (≥12 years), inadequately controlled with prior therapies. Patients received IND/MF DPI in three strengths (150/80 mcg, 150/160 mcg, 150/320 mcg) over 12 weeks.

RESULTS: The study included a total of 174 participants, and 27 adverse events (AEs) in 25 patients (14.37%) were reported, primarily mild to moderate, with no serious adverse events (SAEs). Drug-related treatment-emergent adverse events (TEAEs) were observed in 11 patients. Significant improvements were noted in the mean trough FEV1 and FVC, increasing from baseline to week 4 and week 12 (p < 0.001). The mean ACQ-5 score significantly decreased from 3.0 ± 0.73 baseline to 2.50 ± 0.53 (16.67%) at week 4 and further to 1.73 ± 0.35 at week 12, along with reduced exacerbations (p < 0.001). The need for rescue medication declined from 13.79% to 8.62%, and 96.55% of patients reported treatment satisfaction by study completion.

CONCLUSION: Once-daily IND/MF DPI demonstrated a favorable safety profile with marked improvements in lung function, asthma control, and patient satisfaction, making it a promising option for long-term asthma management in Indian patients.

PMID:39996620 | DOI:10.3390/arm93010003

Neurol Genet. 2025 Feb 21;11(2):e200249. doi: 10.1212/NXG.0000000000200249. eCollection 2025 Apr.

ABSTRACT

OBJECTIVES: The primary objective of this paper was to present the establishment of the Spastic Paraplegia-Centers of Excellence Research Network (SP-CERN) aimed at promoting clinical trial readiness for hereditary spastic paraplegia (HSP). SP-CERN is unique in its approach to addressing the diagnostic and therapeutic challenges associated with HSP through a large-scale, collaborative effort.

METHODS: Participants with HSP are identified through multicenter collaborations across 11 institutions in the United States. SP-CERN systematically collects longitudinal clinical data, biospecimens, and wearable device data from patients. Data are stored in a centralized REDCap database, facilitating shared access for analysis. Patients are evaluated using standardized assessment tools for motor function, biomarkers, and digital outcome measures.

RESULTS: SP-CERN has established a biorepository, centralized data collection methods, and standardized clinical assessments. It is conducting natural history studies for all HSP subtypes, enabling the validation of biomarkers and development of gene-based therapies.

DISCUSSION: SP-CERN's collaborative approach bridges gaps in clinical care and research for HSP by improving diagnostic capabilities and promoting clinical trial readiness. This initiative represents a framework for rare disease research, accelerating the development of novel therapies and improving patient outcomes through standardized, multi-institutional collaboration.

PMID:39996129 | PMC:PMC11849523 | DOI:10.1212/NXG.0000000000200249

J Plast Surg Hand Surg. 2025 Feb 25;60:51-66. doi: 10.2340/jphs.v60.42953.

ABSTRACT

This qualitative systematic review aims to get a better understanding of what it means to live with a rare congenital craniofacial condition according to patients and their parents. Eight patient representatives provided input to this study. After a systematic search, 1,291 studies were screened and 32 qualitative and mixed methods articles (> 691 participants) were included. ENhancing Transparency in REporting the synthesis of Qualitative research (ENTREQ), Cochrane, and COnsolidated criteria for REporting Qualitative research (COREQ) checklists were used for reporting qualitative evidence synthesis and assessment of reporting of included studies. Studies predominantly included parents' perspectives and used mixed samples of diagnosis and sometimes combined the parent and patient perspectives. The results sections of the articles were analyzed inductively using Thematic Synthesis (i.e. line-by-line coding, generating descriptive and analytical themes). Five analytical themes were identified that describe experiences and perspectives: (1) Healthcare experiences, (2) Raising and Growing up, (3) Development of character, (4) Physical impact of the condition, and (5) Social experiences. Underlying themes illustrate that the different aspects throughout life are intertwined, that relationships in all different domains play an important role in shaping perspectives, and that experiences may change over time. Furthermore, it demonstrates that living with a craniofacial condition and undergoing treatment is multifaceted and that the perspectives of patients and parents may differ. In conclusion, well-being and quality of life of patients and their parents are dependent on many different aspects, and surgeons and other healthcare professionals should tailor their skills, expertise, and support to individual-specific needs besides medical indications and move beyond surgical excellence.

PMID:39995315 | DOI:10.2340/jphs.v60.42953

Am J Med Genet A. 2025 Feb 24:e63979. doi: 10.1002/ajmg.a.63979. Online ahead of print.

ABSTRACT

Transient abnormal myelopoiesis (TAM) is a transitory, myeloproliferative condition nearly exclusively present in infants with complete trisomy 21 (T21), or in its rare form, T21 mosaicism. We present here a case study of a neonate diagnosed with T21 mosaicism and TAM who did not exhibit the typical phenotypic features of down syndrome (DS), but displayed hematologic abnormalities, in addition to hepatosplenomegaly. Initial genetic testing suggested acute myeloid leukemia (AML) but subsequent evaluations were indicative of T21 mosaicism confined to the myeloid cell line, with negative results from lymphocytes cultured from a skin biopsy. A pathogenic GATA1 variant was found in the bone marrow in addition to three copies of RUNX1, associated with aberrant hematopoiesis in TAM. The infant responded to a brief course of chemotherapy and demonstrated normal growth and development at four years of age. In addition to this case, we identified 25 cases from the literature of mosaic T21 restricted to the myeloid cell line supporting normal development following treatment for TAM. As this case and the literature review demonstrate, T21 mosaicism apparently isolated to the bone marrow is unlikely to be associated with systemic or neurodevelopmental manifestations of DS.

PMID:39995092 | DOI:10.1002/ajmg.a.63979

Heliyon. 2025 Jan 23;11(3):e42197. doi: 10.1016/j.heliyon.2025.e42197. eCollection 2025 Feb 15.

ABSTRACT

BACKGROUND AND OBJECTIVE: Obesity is intricately linked with metabolic disturbances. The comprehensive exploration of metabolomes is important in unravelling the complexities of obesity development. This study was aimed to discern unique metabolite signatures in obese and lean individuals using liquid chromatography-mass spectrometry quadruple time-of-flight (LC-MS/Q-TOF), with the goal of elucidating their roles in obesity.

METHODS: A total of 160 serum samples (Discovery, n = 60 and Validation, n = 100) of obese and lean individuals with stable Body Mass Index (BMI) values were retrieved from The Malaysian Cohort biobank. Metabolic profiles were obtained using LC-MS/Q-TOF in dual-polarity mode. Metabolites were identified using a molecular feature and chemical formula algorithm, followed by a differential analysis using MetaboAnalyst 5.0. Validation of potential metabolites was conducted by assessing their presence through collision-induced dissociation (CID) using a targeted tandem MS approach.

RESULTS: A total of 85 significantly differentially expressed metabolites (p-value <0.05; -1.5 < FC > 1.5) were identified between the lean and the obese individuals, with the lipid class being the most prominent. A stepwise logistic regression revealed three metabolites associated with increased risk of obesity (14-methylheptadecanoic acid, 4'-apo-beta,psi-caroten-4'al and 6E,9E-octadecadienoic acid), and three with lower risk of obesity (19:0(11Me), 7,8-Dihydro-3b,6a-dihydroxy-alpha-ionol 9-[apiosyl-(1->6)-glucoside] and 4Z-Decenyl acetate). The model exhibited outstanding performance with an AUC value of 0.95. The predictive model underwent evaluation across four machine learning algorithms consistently demonstrated the highest predictive accuracy of 0.821, aligning with the findings from the classical logistic regression statistical model. Notably, the presence of 4'-apo-beta,psi-caroten-4'-al showed a statistically significant difference between the lean and obese individuals among the metabolites included in the model.

CONCLUSIONS: Our findings highlight the significance of lipids in obesity-related metabolic alterations, providing insights into the pathophysiological mechanisms contributing to obesity. This underscores their potential as biomarkers for metabolic dysregulation associated with obesity.

PMID:39995923 | PMC:PMC11848079 | DOI:10.1016/j.heliyon.2025.e42197

Pain Rep. 2025 Feb 21;10(2):e1248. doi: 10.1097/PR9.0000000000001248. eCollection 2025 Apr.

ABSTRACT

INTRODUCTION: The cytochrome P450 enzyme 2D6 (CYP2D6) and the catechol-O-methyltransferase (COMT) enzyme are involved in catecholamine metabolism, potentially influencing pain modulation. Catechol-O-methyltransferase has 3 major haplotypes related to pain sensitivity: low (LPS), average (APS), and high (HPS). However, the reliability of these haplotypes in predicting clinical outcomes is not well investigated. We present a 40-year-old female patient with fibromyalgia. Despite extensive pharmacotherapy with 120 mg/d duloxetine, 150 mg/d pregabalin, 80 mg/d oxycodone, 2 g/d paracetamol, and 1.6 g/d ibuprofen, she suffered from severe pain.

OBJECTIVES: We aim to investigate the patient's susceptibility to analgesic therapy failure (TF) and pain sensitivity with pharmacogenotyping.

METHODS: PGx panel testing, including CYP2D6 and COMT rs4680, was conducted by a commercial provider. Additional genotyping of COMT rs6269, rs4633 and rs4818 was performed applying PCR, restriction fragment length polymorphism assay and sanger sequencing.

RESULTS: The patient was identified as COMT HPS/HPS diplotype carrier and CYP2D6 intermediate metabolizer. CYP2D6 is mainly responsible for the bioactivation of oxycodone into oxymorphone. Reduced CYP2D6 activity may result in a lower oxycodone activation. Considering the coadministration of duloxetine (a moderate CYP2D6 inhibitor), the TF of oxycodone could also be the result of a drug-drug-gene interaction. No other medications were affected by her genetic profile.

CONCLUSION: We hypothesize that the broad TF of pain medications and associated high pain sensitivity could be related to the patient's genetic predisposition in CYP2D6 and COMT, warranting further investigation in a larger patient sample.

PMID:39995492 | PMC:PMC11850035 | DOI:10.1097/PR9.0000000000001248

Front Pharmacol. 2025 Feb 10;16:1552652. doi: 10.3389/fphar.2025.1552652. eCollection 2025.

NO ABSTRACT

PMID:39995412 | PMC:PMC11848066 | DOI:10.3389/fphar.2025.1552652

Curr Res Struct Biol. 2025 Feb 2;9:100164. doi: 10.1016/j.crstbi.2025.100164. eCollection 2025 Jun.

ABSTRACT

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, with an increasing number of structures being determined by cryo-EM each year, many at higher resolutions. However, challenges remain in accurately interpreting cryo-EM maps. Inaccuracies can arise in regions of locally low resolution, where manual model building is more prone to errors. Validation scores for structure models have been developed to assess both the compatibility between map density and the structure, as well as the geometric and stereochemical properties of protein models. Recent advancements have introduced artificial intelligence (AI) into this field. These emerging AI-driven tools offer unique capabilities in the validation and refinement of cryo-EM-derived protein atomic models, potentially leading to more accurate protein structures and deeper insights into complex biological systems.

PMID:39996138 | PMC:PMC11848767 | DOI:10.1016/j.crstbi.2025.100164

J Exp Orthop. 2025 Feb 24;12(1):e70181. doi: 10.1002/jeo2.70181. eCollection 2025 Jan.

ABSTRACT

PURPOSE: Through an analysis of findings from a survey about the use of artificial intelligence (AI) in orthopaedics, the aim of this study was to establish a scholarly foundation for the discourse on AI in orthopaedics and to elucidate key patterns, challenges and potential future trajectories for AI applications within the field.

METHODS: The International Society of Arthroscopy, Knee Surgery and Orthopaedic Sports Medicine (ISAKOS) Young Professionals Task Force developed a survey to collect feedback on issues related to the use of AI in the orthopaedic field. The survey included 26 questions. Data obtained from the completed questionnaires were transferred to a spreadsheet and then analyzed.

RESULTS: Two hundred and eleven orthopaedic surgeons completed the survey. The survey encompassed responses from a diverse cohort of orthopaedic professionals, predominantly comprising males (92.9%). There was wide representation across all geographic regions. A notable proportion (52.1%) reported uncertainty or lack of differentiation among AI, machine learning and deep learning (47.9%). Respondents identified imaging-based diagnosis (60.2%) as the primary field of orthopaedics poised to benefit from AI. A considerable proportion (25.1%) reported using AI in their practice, with primary reasons including referencing scientific literature/publications (40.3%). The vast majority expressed interest in leveraging AI technologies (95.3%), demonstrating an inclination towards incorporating AI into orthopaedic practice. Respondents indicated specific areas of interest for further study, including prediction of patient outcomes after surgery (30.8%) and image-based diagnosis of osteoarthritis (28%).

CONCLUSIONS: This survey demonstrates that there is currently limited use of AI in orthopaedic practice, mainly due to a lack of knowledge about the subject, a lack of proven evidence of its real utility and high costs. These findings are in accordance with other surveys in the literature. However, there is also a high level of interest in its use in the future, in increased study and further research on the subject, so that it can be of real benefit and make AI an integral part of the orthopaedic surgeon's daily work.

LEVEL OF EVIDENCE: Level IV, survey study.

PMID:39996084 | PMC:PMC11848192 | DOI:10.1002/jeo2.70181

Cogn Neurodyn. 2025 Dec;19(1):44. doi: 10.1007/s11571-025-10228-y. Epub 2025 Feb 22.

ABSTRACT

Brain signals and muscle movements have been analyzed using electroencephalogram (EEG) data in several studies. EEG signals contain a lot of noise, such as electromyographic (EMG) waves. Further studies have been done to improve the quality of the results, though it is thought that the combination of these two signals can lead to a significant improvement in the synergistic analysis of muscle movements and muscle connections. Using graph theory, this study examined the interaction of EMG and EEG signals during hand movement and estimated the synergy between muscle and brain signals. Mapping of the brain diagram was also developed to reconstruct the muscle signals from the muscle connections in the brain diagram. The proposed method included noise removal from EEG and EMG signals, graph feature analysis from EEG, and synergy calculation from EMG. Two methods were used to estimate synergy. In the first method, after calculating the brain connections, the features of the communication graph were extracted and then synergy estimating was made with neural networks. In the second method, a convolutional network created a transition from the matrix of brain connections to the synergistic EMG signal. This study reached the high correlation values of 99.8% and maximum MSE error of 0.0084. Compared to other graph-based methods, this method based on regression analysis had a very significant performance. This research can lead to the improvement of rehabilitation methods and brain-computer interfaces.

PMID:39996071 | PMC:PMC11846801 | DOI:10.1007/s11571-025-10228-y

Data Brief. 2025 Jan 28;59:111342. doi: 10.1016/j.dib.2025.111342. eCollection 2025 Apr.

ABSTRACT

Language bridges the gap of communication, and Sign Language (SL) is a native language among vocal and mute community. Every region has its own sign language. In Pakistan, Urdu Sign Language (USL) is a visual gesture language used by the deaf community for communication. The Urdu alphabet in Pakistan Sign Language consists not only of static gestures but also includes dynamic gestures. There are a total of 40 alphabets in Urdu sign language, with 36 being static and 4 being dynamic. While researchers have focused on the 36 static gestures, the 4 dynamic gestures have been overlooked. Additionally, there remains a lack of advancements in the development of Pakistan Sign Language (PSL) with respect to Urdu alphabets. A dataset named UAlpa40 has been compiled, comprising 22,280 images, among which 2,897 are originally created and 19,383 are created through noise or augmentation, representing the 36 static gestures and 393 videos representing the 4 dynamic gestures, completing the set of 40 Urdu alphabets. The standard gestures for USL are published by the Family Educational Services Foundation (FESF) for the deaf and mute community of Pakistan. This dataset was prepared in real-world environments under expert supervision, with volunteers ranging from males to females aged 20 to 45. This newly developed dataset can be utilized to train vision-based deep learning models, which in turn can aid in the development of sign language translators and finger-spelling systems for USL.

PMID:39996049 | PMC:PMC11848795 | DOI:10.1016/j.dib.2025.111342

Front Psychiatry. 2025 Feb 10;16:1494369. doi: 10.3389/fpsyt.2025.1494369. eCollection 2025.

ABSTRACT

BACKGROUND: Electrical activity recorded with electroencephalography (EEG) enables the development of predictive models for emotion recognition. These models can be built using two approaches: subject-dependent and subject-independent. Although subject-independent models offer greater practical utility compared to subject-dependent models, they face challenges due to the significant variability of EEG signals between individuals.

OBJECTIVE: One potential solution to enhance subject-independent approaches is to identify EEG channels that are consistently relevant across different individuals for predicting emotion. With the growing use of deep learning in emotion recognition, incorporating attention mechanisms can help uncover these shared predictive patterns.

METHODS: This study explores this method by applying attention mechanism layers to identify EEG channels that are relevant for predicting emotions in three independent datasets (SEED, SEED-IV, and SEED-V).

RESULTS: The model achieved average accuracies of 79.3% (CI: 76.0-82.5%), 69.5% (95% CI: 64.2-74.8%) and 60.7% (95% CI: 52.3-69.2%) on these datasets, revealing that EEG channels located along the head circumference, including Fp 1, Fp 2, F 7, F 8, T 7, T 8, P 7, P 8, O 1, and O 2, are the most crucial for emotion prediction.

CONCLUSION: These results emphasize the importance of capturing relevant electrical activity from these EEG channels, thereby facilitating the prediction of emotions evoked by audiovisual stimuli in subject-independent approaches.

PMID:39995952 | PMC:PMC11847823 | DOI:10.3389/fpsyt.2025.1494369

Research (Wash D C). 2025 Feb 24;8:0615. doi: 10.34133/research.0615. eCollection 2025.

ABSTRACT

The rapid evolution of deep learning has markedly enhanced protein-biomolecule binding site prediction, offering insights essential for drug discovery, mutation analysis, and molecular biology. Advancements in both sequence-based and structure-based methods demonstrate their distinct strengths and limitations. Sequence-based approaches offer efficiency and adaptability, while structure-based techniques provide spatial precision but require high-quality structural data. Emerging trends in hybrid models that combine multimodal data, such as integrating sequence and structural information, along with innovations in geometric deep learning, present promising directions for improving prediction accuracy. This perspective summarizes challenges such as computational demands and dynamic modeling and proposes strategies for future research. The ultimate goal is the development of computationally efficient and flexible models capable of capturing the complexity of real-world biomolecular interactions, thereby broadening the scope and applicability of binding site predictions across a wide range of biomedical contexts.

PMID:39995900 | PMC:PMC11848751 | DOI:10.34133/research.0615