Kinetic and competitive effects of sorption on multi-element migration through crushed granite and biotite gneiss in Ca-HCO3-SO4 type groundwater.

Crystalline rock is used as the host rock for the disposal of high-level radioactive waste. Two cationic elements (Cs(I) and Ni(II)) and three anionic elements (Se(IV/VI), Mo(VI), and U(VI)) were selected to comprehensively evaluate the sorption behaviors of these radionuclides on crystalline granite and biotite gneiss. The anionic elements showed weak sorption (log Kd (L·kg-1) < 1) and little competition effect, while the cationic elements (log Kd (L·kg-1) = 2-3) showed clear competition (18-98% in Kd values) even at low concentrations. Analysis by pseudo-second-order kinetics showed that Cs(I) sorbed at similar rates on both rocks (20% faster on biotite gneiss), but Ni(II) sorbed 190% faster on biotite gneiss than on granite. That is why the retardation factors for Cs(I) and Ni(II) were reversed in the biotite gneiss column compared to their distribution coefficients. Therefore, the sorption kinetics cannot be neglected in groundwater systems with high flow rates. In the desorption column test, the retardation followed the order of the distribution coefficient. The desorption column test revealed that the distribution coefficient determines the strength of sorption on crystalline rocks.

Prediction of Nili-Ravi buffalo bull fertility through Fourier harmonic analysis of sperm.

Fourier harmonic analysis (FHA) is a robust method for identification of minute changes in sperm nuclear shape that are indicative of reduced fertility. The current study was designed to develop a fertility prediction model for Nili-Ravi buffalo bulls through FHA of sperm. In experiment I, FHA technique was standardized, average sperm nuclear perimeter was measured and sperm nuclear shape plot of buffalo bull was constructed. Sperm of buffalo bulls (n = 10) were stained with YOYO-1 and Hoechst-33342 to differentiate live and dead, and digital images were captured using phase contrast and fluorescent microscopy. The images were analyzed by ImageJ software and 100 sperm/bull were evaluated. The results are described as mean ± SEM values of mean harmonic amplitude (mharm), skewness harmonic amplitude (skharm), kurtosis harmonic amplitude (kurharm) and variance harmonic amplitude (varharm) at Fourier frequencies 0-5 along with the cartesian and polar coordinate plots of buffalo bull sperm. In experiment II, a fertility prediction model was developed based on FHA of buffalo bull sperm. Semen samples of low (n = 6), medium (n = 3) and high (n = 8) fertility bulls were investigated for FHA of sperm and harmonic amplitudes (HA) were generated. Firstly, to determine if live and dead sperm population have unique nuclear shape distribution; the mean, skewness, kurtosis and variance HA 0-5 of 1700 live and 1294 dead spermatozoa of 17 bulls were evaluated. T-test signified a difference in the mharm0 (2.363 ± 0.01 vs. 2.439 ± 0.02), skharm0 (-0.0002 ± 0.07 vs. -0.266 ± 0.09), kurharm0 (-0.156 ± 0.07 vs. 0.260 ± 0.18), kurharm2 (0.142 ± 0.11 vs. 1.031 ± 0.32) and varharm4 (0.109 ± 0.00 vs. 0.082 ± 0.00) of live vs. dead sperm population (p < 0.05). Therefore, 100 live sperm/bull were further evaluated for mean, skewness, kurtosis and variance HA 0-5 values among high (n = 6) and low-fertility (n = 6) groups. Results of T-test showed higher values of mharm2 (0.739 ± 0.01 vs. 0.686 ± 0.00), mharm4 (0.105 ± 0.001 vs. 0.007 ± 0.001), and skharm0 (0.214 ± 0.109 vs. -0.244 ± 0.097) in high vs. low-fertility group (p < 0.05). In next step, five significantly different combinations of discriminant measures between high and low-fertility groups were obtained by discriminant analysis. In conclusion, mharm4, skharm0 and varharm2 correctly identified 91.7 % of bulls into their respective fertility groups, and upon cross validation the value of the canonical correlation was 0.928.

Peeling off the layers from microbial dark matter (MDM): recent advances, future challenges, and opportunities.

Microbes represent the most common organisms on Earth; however, less than 2% of microbial species in the environment can undergo cultivation for study under laboratory conditions, and the rest of the enigmatic, microbial world remains mysterious, constituting a kind of "microbial dark matter" (MDM). In the last two decades, remarkable progress has been made in culture-dependent and culture-independent techniques. More recently, studies of MDM have relied on culture-independent techniques to recover genetic material through either unicellular genomics or shotgun metagenomics to construct single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs), respectively, which provide information about evolution and metabolism. Despite the remarkable progress made in the past decades, the functional diversity of MDM still remains uncharacterized. This review comprehensively summarizes the recently developed culture-dependent and culture-independent techniques for characterizing MDM, discussing major challenges, opportunities, and potential applications. These activities contribute to expanding our knowledge of the microbial world and have implications for various fields including Biotechnology, Bioprospecting, Functional genomics, Medicine, Evolutionary and Planetary biology. Overall, this review aims to peel off the layers from MDM, shed light on recent advancements, identify future challenges, and illuminate the exciting opportunities that lie ahead in unraveling the secrets of this intriguing microbial realm.

First Report of Inclisiran Utilization for Hypercholesterolemia Treatment in Real-world Clinical Settings in a Middle East Population.

PURPOSE: Inclisiran is the first small interfering RNA-based treatment approved for reducing pro-atherogenic lipoproteins in patients with heterozygous familial hypercholesterolemia or clinical atherosclerotic cardiovascular disease, who require additional lowering of low-density lipoprotein cholesterol (LDL-C). We report the first evaluation of the effects of inclisiran in a Middle East population. METHODS: We conducted a retrospective review of patients initiating inclisiran treatment at an outpatient diabetology, endocrinology, and cardiology center between May 2021 and December 2022. All patients followed up for 90 days or more, or with at least 1 lipid determination post initiation were included. Participants were categorized into primary prevention (n = 57) and secondary prevention (n = 89) groups according to previous atherosclerotic cardiovascular disease. FINDINGS: Inclisiran was initiated in 146 patients; mean (SD) age was 54.8 (12.12) years, 82 patients (56.2%) were male, 28 patients (19.2%) had received a diagnosis of familial hypercholesterolemia, 89 patients (61%) had received a diagnosis of diabetes mellitus, and 35 patients (23.9%) had a statin intolerance. Median (interquartile range) follow-up was 137 (90 to 193) days. At 90 days, median (interquartile range) reductions in serum LDL-C and triglycerides were -37.9% (-9.5% to -51.2%) and -12.0% (-9.8% to -40.5%), respectively, in primary prevention and -54.1% (-17.1% to -71.4%) and -15.3% (-14% to -38.8%), respectively, in secondary prevention (all, P < 0.001). LDL-C goals were attained in 110 patients (75.3%). Nonattainment of LDL-C goal was attributed to system effect in 26 patients (72.2%), biological effect in 5 patients (13.9%), and discontinuation of treatment in 5 patients (13.9%). Therapy was well tolerated. IMPLICATIONS: This study is the first from the Middle East and North Africa region that reported the real-world efficacy and safety profile of inclisiran in a mixed-risk population of patients with heterozygous familial hypercholesterolemia and other non-familial hypercholesterolemia indications. Clinically meaningful and sustained reductions in pro-atherogenic lipids with good tolerability were observed after inclisiran initiation. Fewer AEs were reported in this predominantly Arabic population, consistent with previous safety reports for inclisiran. It is important to note that no patient stopped inclisiran treatment due to AEs. Strengths of our study included an optimal cohort, patient heterogeneity, and high retention. In addition, we were able to report mean robust effects of inclisiran and good medication tolerability, quite like randomized studies and open-label extension periods. Despite this, our study had some limitations, including selection bias due to the retrospective design and the absence of a comparative group.

Identification and characterization of integrated prophages and CRISPR-Cas system in Bacillus subtilis RS10 genome.

Bacteriophages have been extensively investigated due to their prominent role in the virulence and resistance of pathogenic bacteria. However, little attention has been given to the non-pathogenic Bacillus phages, and their role in the ecological bacteria genome is overlooked. In the present study, we characterized two Bacillus phages with a linear DNA genome of 33.6 kb with 44.83% GC contents and 129.3 kb with 34.70% GC contents. A total of 46 and 175 putative coding DNA sequences (CDS) were identified in prophage 1 (P1) and prophage 2 (P2), respectively, with no tRNA genes. Comparative genome sequence analysis revealed that P1 shares eight CDS with phage Jimmer 2 (NC-041976), and phage Osiris (NC-028969), and six with phage phi CT9441A (NC-029022). On the other hand, P2 showed high similarity with Bacill_SPbeta_NC_001884 and Bacillus phage phi 105. Further, genome analysis indicates several horizontal gene transfer events in both phages during the evolution process. In addition, we detected two CRISPR-Cas systems for the first time in B. subtilis. The identified CRISPR system consists of 24 and 25 direct repeats and integrase coding genes, while the cas gene which encodes Cas protein involved in the cleavage of a target sequence is missing. These findings will expand the current knowledge of soil phages as well as help to develop a new perspective for investigating more ecological phages to understand their role in bacterial communities and diversity.

A mechanistic approach to arsenic adsorption and immobilization in aqueous solution, groundwater, and contaminated paddy soil using pine-cone magnetic biochar.

Arsenic (As) poisoning in groundwater and rice paddy soil has increased globally, impacting human health and food security. There is an urgent need to deal with As-contaminated groundwater and soil. Biochar can be a useful remedy for toxic contaminants. This study explains the synthesis of pinecone-magnetic biochar (PC-MBC) by engineering the pinecone-pristine biochar with iron salts (FeCl3.6H2O and FeSO4.7H2O) to investigate its effects on As(V) adsorption and immobilization in water and soil, respectively. The results indicated that PC-MBC can remediate As(V)-contaminated water, with an adsorption capacity of 12.14 mg g-1 in water. Isotherm and kinetic modeling showed that the adsorption mechanism involved multilayer, monolayer, and diffusional processes, with chemisorption operating as the primary interface between As(V) and biochar. Post-adsorption analysis of PC-MBC, using FTIR and XRD, further revealed chemical fixing and outer-sphere complexation between As(V) and Fe, O, NH, and OH as the main reasons for As(V) adsorption onto PC-MBC. Recycling of PC-MBC also had excellent adsorption even after several regeneration cycles. Similarly, PC-MBC successfully immobilized As in paddy soil. Single and sequential extraction results showed the transformation of mobile forms of As to a more stable form, confirmed by non-destructive analysis using SEM, EDX, and elemental dot mapping. Thus, Fe-modified pine-cone biochar could be a suitable and cheap adsorbent for As-contaminated water and soil.

A Wearable Force Myography-Based Armband for Recognition of Upper Limb Gestures.

Force myography (FMG) represents a promising alternative to surface electromyography (EMG) in the context of controlling bio-robotic hands. In this study, we built upon our prior research by introducing a novel wearable armband based on FMG technology, which integrates force-sensitive resistor (FSR) sensors housed in newly designed casings. We evaluated the sensors' characteristics, including their load-voltage relationship and signal stability during the execution of gestures over time. Two sensor arrangements were evaluated: arrangement A, featuring sensors spaced at 4.5 cm intervals, and arrangement B, with sensors distributed evenly along the forearm. The data collection involved six participants, including three individuals with trans-radial amputations, who performed nine upper limb gestures. The prediction performance was assessed using support vector machines (SVMs) and k-nearest neighbor (KNN) algorithms for both sensor arrangments. The results revealed that the developed sensor exhibited non-linear behavior, and its sensitivity varied with the applied force. Notably, arrangement B outperformed arrangement A in classifying the nine gestures, with an average accuracy of 95.4 ± 2.1% compared to arrangement A's 91.3 ± 2.3%. The utilization of the arrangement B armband led to a substantial increase in the average prediction accuracy, demonstrating an improvement of up to 4.5%.

Inhibition of Acetylcholinesterase with Novel 1, 3, 4, Oxadiazole Derivatives: A Kinetic, In Silico, and In Vitro Approach.

Alzheimer's disease (AD) is a neurological disease that disturbs the memory, thinking skills, and behavior of the affected person. AD is a complex disease caused by the breakdown of acetylcholine via acetylcholinesterase (AChE). The present study aimed to assess the synthetic inhibitors of AChE that could be used to treat AD. For this purpose, synthetic compounds of oxadiazole derivatives (15-35) were evaluated and identified as promising inhibitors of AChE, exhibiting IC50 varying between 41.87 ± 0.67 and 1580.25 ± 0.7 µM. The kinetic parameters indicated that all the studied compounds bind to the allosteric site and decrease the efficiency of the AChE enzyme. In silico docking analysis showed that the majority of the compounds interact with the anionic subsite and Per-Arnt-Sim domain of AChE and are stabilized by various bonds including π-π and hydrogen bonding. The stability of the most potent compounds 16 and 17 with AChE interaction was confirmed by molecular dynamics simulations. Moreover, all compounds exhibited concentration-dependent calcium (Ca2+) antagonistic and spasmolytic activities. Among the whole series of oxadiazole derivatives, compounds 16 and 17 displayed the highest activities on spontaneous and potassium (K+)-induced contraction. Therefore, the AChE inhibitory potential, cytotoxicity safe profile, and Ca2+ antagonistic ability of these compounds make them potential therapeutic agents against AD and its associated problems in the future.

Synthesis and characterization of mesoporous bioactive glass nanoparticles loaded with peganum harmala for bone tissue engineering.

Globally, there is an increase in a number of bone disorders including osteoarthritis (OA), osteomyelitis, bone cancer, and etc., which has led to a demand for bone tissue regeneration. In order to take use of the osteogenic potential of natural herbs, mesoporous bioactive glass nanoparticles (MBGNs) have the ability to deliver therapeutically active chemicals locally. MBGNs influence bioactivity and osteointegration of materials making them suitable for bone tissue engineering (BTE). In the present study, we developed Peganum Harmala (P. harmala) loaded MBGNs (PH-MBGNs) synthesized via modified Stöber process. The MBGNs were analyzed in terms of surface morphology, chemical make-up, amorphous nature, chemical interaction, pore size, and surface area before and after loading with P. harmala. A burst release of drug from PH-MBGNs was observed within 8 h immersion in phosphate buffer saline (PBS). PH-MBGNs effectively prevented Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli) from spreading. Furthermore, PH-MBGNs developed a hydroxyapatite (HA) layer in the presence of simulated body fluid (SBF) after 21 days, which confirmed the in-vitro bioactivity of MBGNs. In conclusion, PH-MBGNs synthesized in this work are potential candidate for scaffolding or a constituent in the coatings for BTE applications.

Taxonomic Re-Classification and Expansion of the Phylum Chloroflexota Based on over 5000 Genomes and Metagenome-Assembled Genomes.

The phylum Chloroflexota (formerly Chloroflexi) encompasses metabolically diverse bacteria that often have high prevalence in terrestrial and aquatic habitats, some even with biotechnological application. However, there is substantial disagreement in public databases which lineage should be considered a member of the phylum and at what taxonomic level. Here, we addressed these issues through extensive phylogenomic analyses. The analyses were based on a collection of >5000 Chloroflexota genomes and metagenome-assembled genomes (MAGs) from public databases, novel environmental sites, as well as newly generated MAGs from publicly available sequence reads via an improved binning approach incorporating covariance information. Based on calculated relative evolutionary divergence, we propose that Candidatus Dormibacterota should be listed as a class (i.e., Ca. Dormibacteria) within Chloroflexota together with the classes Anaerolineae, Chloroflexia, Dehalococcoidia, Ktedonobacteria, Ca. Limnocylindria, Thermomicrobia, and two other classes containing only uncultured members. All other Chloroflexota lineages previously listed at the class rank appear to be rather orders or families in the Anaerolineae and Dehalococcoidia, which contain the vast majority of genomes and exhibited the strongest phylogenetic radiation within the phylum. Furthermore, the study suggests that a common ecophysiological capability of members of the phylum is to successfully cope with low energy fluxes.

Biomaterials evolution: from inert to instructive.

The field of biomaterials has experienced substantial evolution in recent years, driven by advancements in materials science and engineering. This has led to an expansion of the biomaterials definition to include biocompatibility, bioactivity, bioderived materials, and biological tissues. Consequently, the intended performance of biomaterials has shifted from a passive role wherein a biomaterial is merely accepted by the body to an active role wherein a biomaterial instructs its biological environment. In the future, the integration of bioinspired designs and dynamic behavior into fabrication technologies will revolutionize the field of biomaterials. This perspective presents the recent advances in the evolution of biomaterials in fabrication technologies and provides a brief insight into smart biomaterials.

SBXception: A Shallower and Broader Xception Architecture for Efficient Classification of Skin Lesions.

Skin cancer is a major public health concern around the world. Skin cancer identification is critical for effective treatment and improved results. Deep learning models have shown considerable promise in assisting dermatologists in skin cancer diagnosis. This study proposes SBXception: a shallower and broader variant of the Xception network. It uses Xception as the base model for skin cancer classification and increases its performance by reducing the depth and expanding the breadth of the architecture. We used the HAM10000 dataset, which contains 10,015 dermatoscopic images of skin lesions classified into seven categories, for training and testing the proposed model. Using the HAM10000 dataset, we fine-tuned the new model and reached an accuracy of 96.97% on a holdout test set. SBXception also achieved significant performance enhancement with 54.27% fewer training parameters and reduced training time compared to the base model. Our findings show that reducing and expanding the Xception model architecture can greatly improve its performance in skin cancer categorization.

The Scope of Practice for Primary Cardiovascular Disease Prevention Expanded to Advanced Practice Providers: What Does the Data Show?

PURPOSE OF REVIEW: The review aims to explore the available literature on the role of advance practice providers (APPs) in the primary prevention of cardiovascular diseases (CVD). RECENT FINDINGS: CVD are the major cause of death and disease with the growing burden of direct and indirect costs. Globally, one out of every three deaths is due to CVD. A total of 90% of CVD cases are due to modifiable risk factors which are preventable; however, challenges are faced by the already overburdened healthcare systems where the shortage of workforce is a common constraint. Different CVD preventive programs are working but, in a silo, and with different approaches except in few of the high-income countries where specialized workforce such as advance practice providers (APPs) is trained and employed in practice. Such initiatives are already proven more effective in terms of health and economic outcomes. Through an extensive literature search of APPs' role in the primary prevention of CVD, we identified very few high-income countries where APPs' role has already been integrated into the primary healthcare system. However, in low- and middle-income countries (LMICs), no such roles are defined. In these countries, either the overburdened physicians or any other health professionals (not trained in primary prevention of CVD) sometimes provide brief advice on CVD risk factors. Hence, prompt attention is appealed by the current scenario of CVD prevention specifically in LMICs.

An Integrated Computational Analysis of High-Risk SNPs in Angiopoietin-like Proteins (ANGPTL3 and ANGPTL8) Reveals Perturbed Protein Dynamics Associated with Cancer.

Angiopoietin-like proteins (ANGPTL) constitute a family of eight proteins (1-8) which play a pivotal role in the regulation of various pathophysiological processes. The current study sought to identify high-risk, "non-synonymous, single-nucleotide polymorphisms" (nsSNPs) in both ANGPTL3 and ANGPTL8 to evaluate the role that these nsSNPs play in various types of cancer. We retrieved a total of 301 nsSNPs from various databases; 79 of these candidates constitute high-risk nsSNPs. Moreover, we identified eleven high-risk nsSNPs that cause various types of cancer: seven candidates for ANGPTL3 (L57H, F295L, L309F, K329M, R332L, S348C, and G409R) and four candidates for ANGPTL8 (P23L, R85W, R138S, and E148D). Protein-protein interaction analysis revealed a strong association of ANGPTL proteins with several tumor-suppressor proteins such as ITGB3, ITGAV, and RASSF5. 'Gene-expression profiling interactive analysis' (GEPIA) showed that expression of ANGPTL3 is significantly downregulated in five cancers: sarcoma (SARC); cholangio carcinoma (CHOL); kidney chromophobe carcinoma (KICH); kidney renal clear cell carcinoma (KIRC); and kidney renal papillary cell carcinoma (KIRP). GEPIA also showed that expression of ANGPTL8 remains downregulated in three cancers: CHOL; glioblastoma (GBM); and breast invasive carcinoma (BRCA). Survival rate analysis indicated that both upregulation and downregulation of ANGPTL3 and ANGPTL8 leads to low survival rates in various types of cancer. Overall, the current study revealed that both ANGPTL3 and ANGPTL8 constitute potential prognostic biomarkers for cancer; moreover, nsSNPs in these proteins might lead to the progression of cancer. However, further in vivo investigation will be helpful to validate the role of these proteins in the biology of cancer.

Automatic Diagnosis of Glaucoma from Retinal Images Using Deep Learning Approach.

Glaucoma is characterized by increased intraocular pressure and damage to the optic nerve, which may result in irreversible blindness. The drastic effects of this disease can be avoided if it is detected at an early stage. However, the condition is frequently detected at an advanced stage in the elderly population. Therefore, early-stage detection may save patients from irreversible vision loss. The manual assessment of glaucoma by ophthalmologists includes various skill-oriented, costly, and time-consuming methods. Several techniques are in experimental stages to detect early-stage glaucoma, but a definite diagnostic technique remains elusive. We present an automatic method based on deep learning that can detect early-stage glaucoma with very high accuracy. The detection technique involves the identification of patterns from the retinal images that are often overlooked by clinicians. The proposed approach uses the gray channels of fundus images and applies the data augmentation technique to create a large dataset of versatile fundus images to train the convolutional neural network model. Using the ResNet-50 architecture, the proposed approach achieved excellent results for detecting glaucoma on the G1020, RIM-ONE, ORIGA, and DRISHTI-GS datasets. We obtained a detection accuracy of 98.48%, a sensitivity of 99.30%, a specificity of 96.52%, an AUC of 97%, and an F1-score of 98% by using the proposed model on the G1020 dataset. The proposed model may help clinicians to diagnose early-stage glaucoma with very high accuracy for timely interventions.

Spontaneous acute subdural hematoma as a complication of preeclampsia. A case report and literature review.

Background: Acute subdural hematoma (ASDH) is a common form of intracranial bleeding that may be fatal. Trauma is a major cause, while a subset of cases may occur spontaneously. The authors of this article present a case of spontaneous ASDH in the context of preeclampsia and review similar cases in the literature to identify the prognosis. Case Description: A healthy 27-year-old woman presented in her first pregnancy which was complicated with pregnancy-induced hypertension and was sent to a provincial local maternity hospital at 37 weeks of gestation. On day 4 postpartum, the patient complained of severe headache, vomiting and blurred vision. Fundus examination showed papilledema and magnetic resonance imaging showed right acute frontoparietal subdural hematoma. The hematoma was surgically evacuated with decompressive craniotomy. Postoperatively, the patient's symptoms improved. Conclusion: Spontaneous ASDH is a rare event in the context of preeclampsia; however, it should be considered as one of its possible complications. Research should be directed to emphasize on the possibility of spontaneous ASDH as a cause of neurological deterioration in those cases. A proper diagnosis and early intervention for these cases are crucial for both the mother and the fetus.

Nurse-led culturally relevant smoking reduction intervention among cardiovascular and respiratory patients in Pakistan.

INTRODUCTION: Socioeconomically deprived populations are at greater risk for smoking-induced diseases and death, such as cancers, and cardiovascular and respiratory illnesses. The initiation of a nurse-led smoking cessation program in clinical practice is an effective method to enhance smoking cessation among cardiovascular and respiratory patients in Pakistan. This study aimed to evaluate the effectiveness of nurse-led smoking reduction intervention performed at out-patient clinics in Karachi, Pakistan. METHODS: A single group pre-and post-test study was conducted on eligible patients (n = 83) with a typical profile of cardiovascular and respiratory diseases in a tertiary care hospital from December 2020 to July 2021. INTERVENTION: The multi-modal nurse-led intervention consisted of two face-to-face motivational counseling (30-min) and free nicotine replacement therapy with telephonic counseling and follow-ups offered to all eligible patients for 2 months. RESULTS: The nurse-led intervention resulted in a significant decrease in daily cigarette consumption in most of the patients (75.9%) by 50% and 16.9% of the patients reported smoking abstinence (quitter) at 1-week follow-up (p < .001), verified by a CO breath test. CONCLUSION: A nurse-managed smoking reduction intervention for even a short duration (2 months) in clinics is an effective approach in enhancing smoking abstinence and reduction among cardiovascular and respiratory patients.

Assessment of Low-Density Force Myography Armband for Classification of Upper Limb Gestures.

Using force myography (FMG) to monitor volumetric changes in limb muscles is a promising and effective alternative for controlling bio-robotic prosthetic devices. In recent years, there has been a focus on developing new methods to improve the performance of FMG technology in the control of bio-robotic devices. This study aimed to design and evaluate a novel low-density FMG (LD-FMG) armband for controlling upper limb prostheses. The study investigated the number of sensors and sampling rate for the newly developed LD-FMG band. The performance of the band was evaluated by detecting nine gestures of the hand, wrist, and forearm at varying elbow and shoulder positions. Six subjects, including both fit and amputated individuals, participated in this study and completed two experimental protocols: static and dynamic. The static protocol measured volumetric changes in forearm muscles at the fixed elbow and shoulder positions. In contrast, the dynamic protocol included continuous motion of the elbow and shoulder joints. The results showed that the number of sensors significantly impacts gesture prediction accuracy, with the best accuracy achieved on the 7-sensor FMG band arrangement. Compared to the number of sensors, the sampling rate had a lower influence on prediction accuracy. Additionally, variations in limb position greatly affect the classification accuracy of gestures. The static protocol shows an accuracy above 90% when considering nine gestures. Among dynamic results, shoulder movement shows the least classification error compared to elbow and elbow-shoulder (ES) movements.