Prospect of Gum Arabic-Cocoliposome Matrix to Encapsulate Curcumin for Oral Administration.

Curcumin is an antioxidant that can effectively eliminate free radicals. However, as its oral bioavailability is low, an effective delivery method is required. Phospholipid-based liposomes can encapsulate lipophilic drugs, such as curcumin, while liposome, cholesterol, and gum Arabic (GA) can enhance the internal and external stability of drug membranes. This present study used concentrations of cholesterol (Cchol) and GA (CGA), ranging from 0 to 10, 20, 30, and 40% as well as 0 to 5, 10, 15, 20, 30, and 40%, respectively, to encapsulate curcumin in a GA-cocoliposome (CCL/GA) matrix and test its efficacy in simulated intestinal fluid (SIF) and simulated gastric fluid (SGF). The absence of new characteristic peaks in the Fourier transform infrared (FTIR) spectra results indicate the presence of non-covalent interactions in the CCL/GA encapsulation. Furthermore, increasing the Cchol decreased the encapsulation efficiency (EE), loading capacity (LC), and antioxidant activity (IR) of the CCL/GA encapsulation but increased its release rate (RR). Conversely, increasing CGA increased its EE and IR but decreased its LC and RR. The two conditions applied confirmed this. Liposomal curcumin had the highest IR in SIF (84.081%) and the highest RR in SGF (0.657 ppm/day). Furthermore, liposomes loaded with 10% Cchol and 20% CGA performed best in SIF, while those loaded with 10% Cchol and 30% CGA performed best in SGF. Lastly, the CCL/GA performed better in SIF than SGF.

Development of Galectin-3 Targeting Drugs for Therapeutic Applications in Various Diseases.

Galectin-3 (Gal3) is one of the most studied members of the galectin family that mediate various biological processes such as growth regulation, immune function, cancer metastasis, and apoptosis. Since Gal3 is pro-inflammatory, it is involved in many diseases that are associated with chronic inflammation such as cancer, organ fibrosis, and type 2 diabetes. As a multifunctional protein involved in multiple pathways of many diseases, Gal3 has generated significant interest in pharmaceutical industries. As a result, several Gal3-targeting therapeutic drugs are being developed to address unmet medical needs. Based on the PubMed search of Gal3 to date (1987-2023), here, we briefly describe its structure, carbohydrate-binding properties, endogenous ligands, and roles in various diseases. We also discuss its potential antagonists that are currently being investigated clinically or pre-clinically by the public and private companies. The updated knowledge on Gal3 function in various diseases could initiate new clinical or pre-clinical investigations to test therapeutic strategies, and some of these strategies could be successful and recognized as novel therapeutics for unmet medical needs.

Current trends and future perspective of probiotic yeasts research in Indonesia.

Indonesia is a mega biodiversity country with various local wisdom, including the enormous variety of fermented foods and beverages. Indonesian researchers have conducted an intensive study to understand the diversity of microbes on those fermented products, one of which shows probiotic properties. Compared to that lactic acid bacteria, the study on probiotic yeasts is less explored. Probiotic yeast isolates are commonly isolated from traditional Indonesian fermented products. Saccharomyces, Pichia, and Candida are among Indonesia's most popular genera of probiotic yeasts, primarily applied in poultry and human health. The exploration of functional probiotic characteristics, such as antimicrobial, antifungal, antioxidant, and immunomodulator, has been widely reported from these local probiotic yeast strains. In vivo studies in a model organism such as mice conclude the prospective functional probiotic characteristics of the yeast isolates. Employment of current technology, such as omics, is essential in elucidating those functional properties. Advanced research and development of probiotic yeasts in Indonesia are gaining significant attention currently. For instance, probiotic yeasts-mediated fermentation in the production of kefir and kombucha are among the trend with promising economic value. The future trends of probiotic yeasts research in Indonesia are discussed in this review to give valuable sight into the application of indigenous probiotic yeasts in various fields.

Random forest-based simultaneous and proportional myoelectric control system for finger movements.

A classification scheme for myoelectric control systems (MCS) cannot mimic complex hand movements. This paper presents simultaneous and proportional MCS by estimating the angles of fourteen finger joints using time-domain feature extraction and random forest. The experimental results show that the best feature was the root mean square (RMS). Furthermore, the random forest attained an average coefficient of determination (R2) of 0.85 compared to other regressors which perform below 0.75. The ANOVA tests indicated that the performance of the proposed system was significantly different. Therefore, the proposed system will be the best option for real-time MCS applications in the future.

In Vitro Evaluation of Curcumin Encapsulation in Gum Arabic Dispersions under Different Environments.

Biopolymers, especially polysaccharides (e.g., gum Arabic), are widely applied as drug carriers in drug delivery systems due to their advantages. Curcumin, with high antioxidant ability but limited solubility and bioavailability in the body, can be encapsulated in gum Arabic to improve its solubility and bioavailability. When curcumin is encapsulated in gum Arabic, it is essential to understand how it works in various conditions. As a result, in Simulated Intestinal Fluid and Simulated Gastric Fluid conditions, we investigated the potential of gum Arabic as the drug carrier of curcumin. This study was conducted by varying the gum Arabic concentrations, i.e., 5, 10, 15, 20, 30, and 40%, to encapsulate 0.1 mg/mL of curcumin. Under both conditions, the greater the gum Arabic concentration, the greater the encapsulation efficiency and antioxidant activity of curcumin, but the worse the gum Arabic loading capacity. To achieve excellent encapsulation efficiency, loading capacity, and antioxidant activity, the data advises that 10% is the best feasible gum Arabic concentration. Regarding the antioxidant activity of curcumin, the findings imply that a high concentration of gum Arabic was effective, and the Simulated Intestinal Fluid brought an excellent surrounding compared to the Simulated Gastric Fluid solution. Moreover, the gum Arabic releases curcumin faster in the Simulated Gastric Fluid condition.

An Empirical Study on the Use of Digital Technologies to Achieve Cost-Effectiveness in Healthcare Management.

Objectives: Healthcare cost reduction is one of the major challenges of the current era. This study was based on the general system theory-based view to assess the significance of sensing communication technologies and processing actuation technologies in improving healthcare quality, leading to cost reduction. Moreover, the contingent rule of healthcare supply chain management in enhancing the influence of improved quality on healthcare cost reduction was also empirically tested. Methods: The sample of the study comprised 337 middle and senior healthcare managers employed in various government and private hospitals and health institutions in Jakarta, Indonesia. The administrative departments of each hospital and health institution was visited to take their consent to conduct this survey at their clinical and non-clinical departments. The data collected was analyzed using SmartPLS ver. 4 software. Results: Results reveal a significant direct and indirect influence of sensing communication technologies and processing actuation technologies on achieving cost-effectiveness in the healthcare sector, in the presence of perceived quality improvement as a mediator. However, the strength of the associations varied and was based on highly reliable and familiar nature of sensing communication technologies compared to processing actuation technologies which were emerging and gaining popularity in recent years. Conclusion: Considering the healthcare cost as a critical factor based on limited resources in emerging economies, healthcare institutions/centers should use digital technologies to achieve cost-effectiveness for providing healthcare facilities in the industry 4.0 era.

SARS-CoV-2 Antibody Neutralization Assay Platforms Based on Epitopes Sources: Live Virus, Pseudovirus, and Recombinant S Glycoprotein RBD.

The high virulent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus that emerged in China at the end of 2019 has generated novel coronavirus disease, coronavirus disease 2019 (COVID-19), causing a pandemic worldwide. Every country has made great efforts to struggle against SARS-CoV-2 infection, including massive vaccination, immunological patients' surveillance, and the utilization of convalescence plasma for COVID-19 therapy. These efforts are associated with the attempts to increase the titers of SARS-CoV-2 neutralizing Abs (nAbs) generated either after infection or vaccination that represent the body's immune status. As there is no standard therapy for COVID-19 yet, virus eradication will mainly depend on these nAbs contents in the body. Therefore, serological nAbs neutralization assays become a requirement for researchers and clinicians to measure nAbs titers. Different platforms have been developed to evaluate nAbs titers utilizing various epitopes sources, including neutralization assays based on the live virus, pseudovirus, and neutralization assays utilizing recombinant SARS-CoV-2 S glycoprotein receptor binding site, receptor-binding domain. As a standard neutralization assay, the plaque reduction neutralization test (PRNT) requires isolation and propagation of live pathogenic SARS-CoV-2 virus conducted in a BSL-3 containment. Hence, other surrogate neutralization assays relevant to the PRNT play important alternatives that offer better safety besides facilitating high throughput analyses. This review discusses the current neutralization assay platforms used to evaluate nAbs, their techniques, advantages, and limitations.

Subject-independent Classification on Brain-Computer Interface using Autonomous Deep Learning for finger movement recognition.

The degradation of the subject-independent classification on a brain-computer interface is a challenging issue. One method mostly taken to overcome this problem is by collecting as many subjects as possible and then training the system across all subjects. This article introduces streaming online learning called autonomous deep learning (ADL) to classify five individual fingers based on electroencephalography (EEG) signals to overcome the issue above. ADL is a deep learning architecture that can construct its structure by itself through streaming learning and adapt its structure to the changes occurring in the input. In this article, the input of ADL is a common spatial pattern (CSP) extracted from the EEG signal of healthy subjects. The experimental results on the subject-dependence classification across four subjects using 5fold cross-validation show that that ADL achieved the classification accuracy of around 77%. This performance was excellent compared to a random forest (RF) and a convolutional neural network (CNN). They achieved accuracies of about 53% and 72%, respectively. On the subject-independent classification, ADL outperforms CNN by resulting stable accuracies for both training and testing, different from CNN that experience accuracy degradation to approximately 50%. These results imply that ADL is a promising machine learning in dealing with the issue in the subject-independent classification.

A Novel Mechanism for Nitrosative Stress Tolerance Dependent on GTP Cyclohydrolase II Activity Involved in Riboflavin Synthesis of Yeast.

The biological functions of nitric oxide (NO) depend on its concentration, and excessive levels of NO induce various harmful situations known as nitrosative stress. Therefore, organisms possess many kinds of strategies to regulate the intracellular NO concentration and/or to detoxify excess NO. Here, we used genetic screening to identify a novel nitrosative stress tolerance gene, RIB1, encoding GTP cyclohydrolase II (GTPCH2), which catalyzes the first step in riboflavin biosynthesis. Our further analyses demonstrated that the GTPCH2 enzymatic activity of Rib1 is essential for RIB1-dependent nitrosative stress tolerance, but that riboflavin itself is not required for this tolerance. Furthermore, the reaction mixture of a recombinant purified Rib1 was shown to quench NO or its derivatives, even though formate or pyrophosphate, which are byproducts of the Rib1 reaction, did not, suggesting that the reaction product of Rib1, 2,5-diamino-6-(5-phospo-D-ribosylamino)-pyrimidin-4(3 H)-one (DARP), scavenges NO or its derivatives. Finally, it was revealed that 2,4,5-triamino-1H-pyrimidin-6-one, which is identical to a pyrimidine moiety of DARP, scavenged NO or its derivatives, suggesting that DARP reacts with N2O3 generated via its pyrimidine moiety.

Evaluation of feature extraction techniques and classifiers for finger movement recognition using surface electromyography signal.

Electromyography (EMG) in a bio-driven system is used as a control signal, for driving a hand prosthesis or other wearable assistive devices. Processing to get informative drive signals involves three main modules: preprocessing, dimensionality reduction, and classification. This paper proposes a system for classifying a six-channel EMG signal from 14 finger movements. A feature vector of 66 elements was determined from the six-channel EMG signal for each finger movement. Subsequently, various feature extraction techniques and classifiers were tested and evaluated. We compared the performance of six feature extraction techniques, namely principal component analysis (PCA), linear discriminant analysis (LDA), uncorrelated linear discriminant analysis (ULDA), orthogonal fuzzy neighborhood discriminant analysis (OFNDA), spectral regression linear discriminant analysis (SRLDA), and spectral regression extreme learning machine (SRELM). In addition, we also evaluated the performance of seven classifiers consisting of support vector machine (SVM), linear classifier (LC), naive Bayes (NB), k-nearest neighbors (KNN), radial basis function extreme learning machine (RBF-ELM), adaptive wavelet extreme learning machine (AW-ELM), and neural network (NN). The results showed that the combination of SRELM as the feature extraction technique and NN as the classifier yielded the best classification accuracy of 99%, which was significantly higher than those from the other combinations tested. Graphical abstract Mean of classification accuracies for 14 finger movements obtained with various pairs of SRELM and classifier.

Evaluation of extreme learning machine for classification of individual and combined finger movements using electromyography on amputees and non-amputees.

The success of myoelectric pattern recognition (M-PR) mostly relies on the features extracted and classifier employed. This paper proposes and evaluates a fast classifier, extreme learning machine (ELM), to classify individual and combined finger movements on amputees and non-amputees. ELM is a single hidden layer feed-forward network (SLFN) that avoids iterative learning by determining input weights randomly and output weights analytically. Therefore, it can accelerate the training time of SLFNs. In addition to the classifier evaluation, this paper evaluates various feature combinations to improve the performance of M-PR and investigate some feature projections to improve the class separability of the features. Different from other studies on the implementation of ELM in the myoelectric controller, this paper presents a complete and thorough investigation of various types of ELMs including the node-based and kernel-based ELM. Furthermore, this paper provides comparisons of ELMs and other well-known classifiers such as linear discriminant analysis (LDA), k-nearest neighbour (kNN), support vector machine (SVM) and least-square SVM (LS-SVM). The experimental results show the most accurate ELM classifier is radial basis function ELM (RBF-ELM). The comparison of RBF-ELM and other well-known classifiers shows that RBF-ELM is as accurate as SVM and LS-SVM but faster than the SVM family; it is superior to LDA and kNN. The experimental results also indicate that the accuracy gap of the M-PR on the amputees and non-amputees is not too much with the accuracy of 98.55% on amputees and 99.5% on the non-amputees using six electromyography (EMG) channels.

Adaptive myoelectric pattern recognition for arm movement in different positions using advanced online sequential extreme learning machine.

The performance of the myoelectric pattern recognition system sharply decreases when working in various limb positions. The issue can be solved by cumbersome training procedure that can anticipate all possible future situations. However, this procedure will sacrifice the comfort of the user. In addition, many unpredictable scenarios may be met in the future. This paper proposed a new adaptive myoelectric pattern recognition using advance online sequential extreme learning (AOS-ELM) for classification of the hand movements to five different positions. AOS-ELM is an improvement of OS-ELM that can verify the adaptation validity using entropy. The proposed adaptive MPR was able to classify eight different classes from eleven subjects by accuracy of 95.42 % using data from one position. After learning the data from whole positions, the performance of the proposed system is 86.13 %. This performance was better than the MPR that employed original OS-ELM, but it was worse than the MPR that utilized the batch classifiers. Nevertheless, the adaptation mechanism of AOS-ELM is preferred in the real-time application.

A robust myoelectric pattern recognition using online sequential extreme learning machine for finger movement classification.

A robust myoelectric pattern-recognition-system requires a system that should work in the real application as good as in the laboratory. However, this demand should be handled properly and rigorously to achieve a robust myoelectric system. Electrode shift is an issue that usually emerges when dealing with robustness issue. In daily life, the placement of electrodes becomes a significant issue that can downgrade the performance of the system. This paper proposed a new way to overcome the robustness issue by conducting an update to the system to anticipate changes in the future such as electrode shift, improvement in muscle strength or any other issue. Such update will be used to generate an adaptation. The adaptation is done according to the user's need by employing an online sequential extreme learning (OS-ELM) to learn the training data chunk by chunk. OS-ELM enables the myoelectric system to learn from a small number of data to avoid cumbersome training process. The day-to-day experiment shows that the proposed system can maintain its performance on average accuracy around 85% whereas the non-adaptive system could not.

Adipose-derived stromal cells promote allograft tolerance induction.

Amputations and unsalvageable injuries with devastating tissue loss are common in the combat wounded. Reconstructive transplantation in the civilian setting using vascular composite allotransplants (VCAs) with multiple tissues (skin, muscle, nerve, bone) combined with long-term multidrug immunosuppression has been encouraging. However, skin rejection remains a critical complication. Adipose-derived stromal/stem cells (ASCs) are easily obtained from normal individuals in high numbers, precluding ex vivo expansion. The reparative function and paracrine immunomodulatory capacity of ASCs has gained considerable attention. The present study investigated whether ASCs facilitate long-term skin allograft survival. ASCs were isolated from fresh human subcutaneous adipose lipoaspirate. Full-thickness skin grafts from BALB/c mice were transplanted onto the dorsal flanks of C57BL/6 mice treated with five doses of anti-CD4/CD8 monoclonal antibodies (10 mg/kg) on days 0, +2, +5, +7, and +14 relative to skin grafting. A single nonmyeloablative low dose of busulfan (5 mg/kg) was given on day +5. Seven days after skin transplantation, ASCs (3×10(6)) were infused i.v. with or without donor bone marrow cells (BMCs; 5×10(5)). ASC+BMC coinfusion with minimal conditioning led to stable lymphoid and myeloid macrochimerism, deletion of alloreactive T cells, expansion of regulatory T cells, and long-term allograft survival (>200 days). ASCs constitutively produced high levels of anti-inflammatory/immunoregulatory factors such as prostaglandin E2, indoleamine 2,3-dioxygenase, APO-1/Fas (CD95), and programmed cell death-1 ligand-2. These findings serve as a foundation for developing a translational advanced VCA protocol, embodying both ASCs and low-dose donor BMCs, in nonhuman primates, with the goal of enhancing functional outcomes and eliminating the complications associated with long-term immunosuppression.

A novel upper limb rehabilitation system with self-driven virtual arm illusion.

This paper proposes a novel upper extremity rehabilitation system with virtual arm illusion. It aims for fast recovery from lost functions of the upper limb as a result of stroke to provide a novel rehabilitation system for paralyzed patients. The system is integrated with a number of technologies that include Augmented Reality (AR) technology to develop game like exercise, computer vision technology to create the illusion scene, 3D modeling and model simulation, and signal processing to detect user intention via EMG signal. The effectiveness of the developed system has evaluated via usability study and questionnaires which is represented by graphical and analytical methods. The evaluation provides with positive results and this indicates the developed system has potential as an effective rehabilitation system for upper limb impairment.

Swarm-wavelet based extreme learning machine for finger movement classification on transradial amputees.

The use of a small number of surface electromyography (EMG) channels on the transradial amputee in a myoelectric controller is a big challenge. This paper proposes a pattern recognition system using an extreme learning machine (ELM) optimized by particle swarm optimization (PSO). PSO is mutated by wavelet function to avoid trapped in a local minima. The proposed system is used to classify eleven imagined finger motions on five amputees by using only two EMG channels. The optimal performance of wavelet-PSO was compared to a grid-search method and standard PSO. The experimental results show that the proposed system is the most accurate classifier among other tested classifiers. It could classify 11 finger motions with the average accuracy of about 94 % across five amputees.

Two-channel surface electromyography for individual and combined finger movements.

This paper proposes the pattern recognition system for individual and combined finger movements by using two channel electromyography (EMG) signals. The proposed system employs Spectral Regression Discriminant Analysis (SRDA) for dimensionality reduction, Extreme Learning Machine (ELM) for classification and the majority vote for the classification smoothness. The advantage of the SRDA is its speed which is faster than original LDA so that it could deal with multiple features. In addition, the use of ELM which is fast and has similar classification performance to well-known SVM empowers the classification system. The experimental results show that the proposed system was able to recognize the individual and combined fingers movements with up to 98 % classification accuracy by using only just two EMG channels.

Comparative analysis of gene transcripts for cell signaling receptors in bone marrow-derived hematopoietic stem/progenitor cell and mesenchymal stromal cell populations.

INTRODUCTION: Knowing the repertoire of cell signaling receptors would provide pivotal insight into the developmental and regenerative capabilities of bone marrow cell (BMC)-derived hematopoietic stem/progenitor cells (HSPCs) and bone marrow mesenchymal stromal cells (BMMSCs). METHODS: Murine HSPCs were enriched from fluorescence-activated cell sorting (FACS)-sorted Lin-c-Kit+Sca-1+ BMCs isolated from the tibia and femoral marrow compartments. Purified BMMSCs (CD73+, CD90+, CD105+, and CD45-, CD34-, CD31-, c-Kit-) with extensive self-renewal potential and multilineage differentiation capacity (into different mesodermal cell lineages including osteocytes, chrondrocytes, adipocytes) were derived from adherent BMC cultures after CD45+ cell depletion. Adherent colony-forming cells were passaged two to three times and FACS analysis was used to assess cell purity and validate cell-specific surface marker phenotype prior to experimentation. Gene transcripts for a number of cell signaling molecules were assessed using a custom quantitative real-time RT-PCR low-density microarray (94 genes; TaqMan® technology). RESULTS: We identified 16 mRNA transcripts that were specifically expressed in BMC-derived HSPC (including Ptprc, c-Kit, Csf3r, Csf2rb2, Ccr4, Cxcr3 and Tie-1), and 14 transcripts specifically expressed in BMMSCs (including Pdgfra, Ddr2, Ngfr, Mst1r, Fgfr2, Epha3, and Ephb3). We also identified 27 transcripts that were specifically upregulated (≥2-fold expression) in BMMSCs relative to HSPCs (Axl, Bmpr1a, Met, Pdgfrb, Fgfr1, Mertk, Cmkor1, Egfr, Epha7, and Ephb4), and 19 transcripts that were specifically upregulated in HSPCs relative to BMMSCs (Ccr1, Csf1r, Csf2ra, Epor, IL6ra, and IL7r). Eleven transcripts were equally expressed (<2-fold upregulation) in HSPCs and BMMSCs (Flt1, Insr, Kdr, Jak1, Agtrl1, Ccr3, Ednrb, Il3ra, Hoxb4, Tnfrsf1a, and Abcb1b), whilst another seven transcripts (Epha6, Epha8, Musk, Ntrk2, Ros1, Srms, and Tnk1) were not expressed in either cell population. CONCLUSIONS: We demonstrate that besides their unique immunophenotype and functional differences, BMC-derived HSPCs and BMMSCs have different molecular receptor signaling transcript profiles linked to cell survival, growth, cell differentiation status, growth factor/cytokine production and genes involved in cell migration/trafficking/adhesion that may be critical to maintain their pluripotency, plasticity, and stem cell function.

Heterotopic ossification in complex orthopaedic combat wounds: quantification and characterization of osteogenic precursor cell activity in traumatized muscle.

BACKGROUND: Heterotopic ossification frequently develops following high-energy blast injuries sustained in modern warfare. We hypothesized that differences in the population of progenitor cells present in a wound would correlate with the subsequent formation of heterotopic ossification. METHODS: We obtained muscle biopsy specimens from military service members who had sustained high-energy wartime injuries and from patients undergoing harvest of a hamstring tendon autograft. Plastic-adherent cells were isolated in single-cell suspension and plated to assess the prevalence of colony-forming cells. Phenotypic characteristics were assessed with use of flow cytometry. Individual colony-forming units were counted after an incubation period of seven to ten days, and replicate cultures were incubated in lineage-specific induction media. Immunohistochemical staining was then performed to determine the percentage of colonies that had differentiated along an osteogenic lineage. Quantitative real-time reverse-transcription polymerase chain reaction was used to identify changes in osteogenic gene expression. RESULTS: Injured patients had significantly higher numbers of muscle-derived connective-tissue progenitor cells per gram of tissue (p < 0.0001; 95% confidence interval [CI], 129,930 to 253,333), and those who developed heterotopic ossification had higher numbers of assayable osteogenic colonies (p < 0.016; 95% CI, 12,249 to 106,065). In the injured group, quantitative real-time reverse-transcription polymerase chain reaction performed on the in vitro expanded progeny of connective-tissue progenitors demonstrated upregulation of COL10A1, COL4A3, COMP, FGFR2, FLT1, IGF2, ITGAM, MMP9, PHEX, SCARB1, SOX9, and VEGFA in the patients with heterotopic ossification as compared with those without heterotopic ossification. CONCLUSIONS: Our study suggests that the number of connective-tissue progenitor cells is increased in traumatized tissue. Furthermore, wounds in which heterotopic ossification eventually forms have a higher percentage of connective-tissue progenitor cells committed to osteogenic differentiation than do wounds in which heterotopic ossification does not form. The early identification of heterotopic ossification-precursor cells and target genes in severe wounds not only may be an effective prognostic tool with which to assess whether heterotopic ossification will develop in a wound, but may also guide the future development of individualized prophylactic measures.

Infusion of Lin- bone marrow cells results in multilineage macrochimerism and skin allograft tolerance in minimally conditioned recipient mice.

Donor-specific immunological tolerance using high doses of donor bone marrow cells (BMC) has been demonstrated in mixed chimerism-based tolerance induction protocols; however, the development of graft versus host disease (GVHD) remains a risk. In the present study, we demonstrate that the infusion of low numbers of donor Lin(-) bone marrow cells (Lin(-) BMC) 7 days post allograft transplantation facilitates high level macrochimerism induction and graft tolerance. Full-thickness BALB/c skin allografts were transplanted onto C57BL/6 mice. Mice were treated with anti-CD4 and anti-CD8 mAbs on day 0, +2, +5, +7 and +14 along with low dose busulfan on day +5. A low dose of highly purified Lin(-) BMC from BALB/c donor mice was infused on day +7. Chimerism and clonal cell deletion were evaluated using flow cytometry. Donor-specific tolerance was tested by donor and third-party skin grafting and mixed leukocyte reaction (MLR). Lin(-) BMC infusion with minimal immunosuppression led to stable, mixed, multilineage macrochimerism and long-term allograft survival (>300 days). Mixed donor-recipient macrochimerism was observed. Donor-reactive T cells were clonally deleted and a 130% increase in CD4(+)CD25(+)Foxp3(+) regulatory T cells (Tregs) was observed in the spleen. Tolerant mice subsequently accepted second donor, but not third-party (C3H), skin grafts and recipient splenocytes failed to react with allogeneic donor cells indicating donor-specific immunological tolerance was achieved. We conclude that the infusion of donor Lin(-) BMC without cytoreductive recipient conditioning can induce indefinite survival of skin allografts via mechanisms involving the establishment of a multilineage macrochimeric state principally through clonal deletion of alloreactive T cells and peripherally induced CD4(+)Foxp3(+) Tregs.