Segments Of Different Lengths Research Articles

Polyurethanes Made with Blends of Polycarbonates with Different Molecular Weights Showing Adequate Mechanical and Adhesion Properties and Fast Self-Healing at Room Temperature

Dynamic non-covalent interactions between polycarbonate soft segments have been proposed for explaining the intrinsic self-healing of polyurethanes synthesized with polycarbonate polyols (PUs) at 20 °C. However, these self-healing PUs showed insufficient mechanical properties, and their adhesion properties have not been explored yet. Different PUs with self-healing at 20 °C, acceptable mechanical properties, and high shear strengths (similar to the highest ones reported in the literature) were synthesized by using blends of polycarbonate polyols of molecular weights 1000 and 2000 Da (CD1000 + CD2000). Their structural, thermal, rheological, mechanical, and adhesion (single lap-shear tests) properties were assessed. PUs with higher CD1000 polyol contents exhibited shorter self-healing times and dominant viscous properties due to the higher amount of free carbonate groups, significant carbonate–carbonate interactions, and low micro-phase separation. As the CD2000 polyol content in the PUs increased, slower kinetics and longer self-healing times and higher mechanical and adhesion properties were obtained due to a dominant rheological elastic behavior, soft segments with higher crystallinities, and greater micro-phase separation. All PUs synthesized with CD1000 + CD2000 blends exhibited a mixed phase due to interactions between polycarbonate soft segments of different lengths which favored the self-healing and mobility of the polymer chains, resulting in increased mechanical properties.

Front Cover: Solvent‐Free Mechanosynthesis of Oligopeptides by Coupling Peptide Segments of Different Lengths – Elucidating the Role of Cesium Carbonate in Ball Mill Processes (Chem. Eur. J. 44/2024)

Front Cover: Solvent‐Free Mechanosynthesis of Oligopeptides by Coupling Peptide Segments of Different Lengths – Elucidating the Role of Cesium Carbonate in Ball Mill Processes (Chem. Eur. J. 44/2024)

Solvent-Free Mechanosynthesis of Oligopeptides by Coupling Peptide Segments of Different Lengths - Elucidating the Role of Cesium Carbonate in Ball Mill Processes.

We report an idea for the synthesis of oligopeptides using a solvent-free ball milling approach. Our concept is inspired by block play, in which it is possible to construct different objects using segments (blocks) of different sizes and lengths. We prove that by having a library of short peptides and employing the ball mill mechanosynthesis (BMMS) method, peptides can be easily coupled to form different oligopeptides with the desired functional and biological properties. Optimizing the BMMS process we found that the best yields we obtained when TBTU and cesium carbonate were used as reagents. The role of Cs2CO3 in the coupling mechanism was followed on each stage of synthesis by 1H, 13C and 133Cs NMR employing Magic Angle Spinning (MAS) techniques. It was found that cesium carbonate acts not only as a base but is also responsible for the activation of substrates and intermediates. The unique information about the BMMS mechanism is based on the analysis of 2D NMR data. The power of BMMS is proved by the example of different peptide combinations, 2+2, 3+2, 4+2, 5+2 and 4+4. The tetra-, penta-, hexa-, hepta- and octapeptides obtained under this project were fully characterized by MS and NMR techniques.

A multiscale and multicriteria generative adversarial network to synthesize 1-dimensional turbulent fields

This article introduces a new neural network stochastic model to generate a 1-dimensional stochastic field with turbulent velocity statistics. Both the model architecture and training procedure ground on the Kolmogorov and Obukhov statistical theories of fully developed turbulence, so guaranteeing descriptions of (1) energy distribution, (2) energy cascade and (3) intermittency across scales in agreement with experimental observations. The model is a generative adversarial network (GAN) with multiple multiscale optimization criteria. First, we use three physics-based criteria: the variance, skewness and flatness of the increments of the generated field, that retrieve respectively the turbulent energy distribution, energy cascade and intermittency across scales. Second, the GAN criterion, based on reproducing statistical distributions, is used on segments of different length of the generated field. Furthermore, to mimic multiscale decompositions frequently used in turbulence’s studies, the model architecture is fully convolutional with kernel sizes varying along the multiple layers of the model. To train our model, we use turbulent velocity signals from grid turbulence at Modane wind tunnel.

Visual monitoring of cisplatin-regulated caspase-3 activity in living cells based on a reduced graphene oxide-loaded fluorescent probe.

Cisplatin (DDP) is a potent chemotherapeutic drug, which can regulate tumor cell apoptosis by up-regulating caspase-3 activity. Thus, monitoring caspase-3 activity in breast cancer cells can directly illustrate the efficiency of DDP treatment. In this study, by using reduced graphene oxide (rGO) as a quencher of a fluorescence labeled peptide, we developed an "off to on" method to monitor the effect of DDP on caspase-3 in breast cancer cells. In this method, the rGO quenched fluorescence with an ultra-high level of efficiency. Caspase-3 hydrolyzed the polypeptide probe, generating two segments of different lengths. The release of a short segment marked with fluorophores led to the recovery of the fluorescence signal (Ex/Em = 450/521 nm). Under the optimal conditions, the linear range of caspase-3 was 0.4-7 U mL-1 and the limit of detection was 0.33 U mL-1. The upregulating effect of DDP on intracellular caspase-3 activity was visualized with the "off to on" method and flow cytometry assay showed that caspase-3 activity increased along with the apoptosis rate of tumor cells. The above results show the practical application of the method for evaluating the efficacy of drugs against cancer cells.

Deterministic Interpretation of the Malus Law and Correlation in Experiments with Entangled Photons

This paper examines a local deterministic model of an experiment involving correlated photons. The experimental setup involves a source that emits two linearly polarized photons in each act, two two-channel analyzers, and detectors included in the coincidence scheme. The orientation angle of the photon polarization plane is a random variable with a uniform distribution, and it is the same for simultaneously emitted photons. The model presented here is a generalization of the “naive example of hidden variable theory” described in A. Aspect's article ‘Bell's Theorem: The Naive View of an Experimentalist.
 In our model, the outcome of the photon interaction with the analyzer (hit in one of the two channels) is uniquely determined by the angle between the photon polarization plane and the analyzer axis and is described by a step function. The difference in our model is that the step function contains a large number of segments of different lengths. The location and lengths of the segments are set so that the probability of a photon hitting a specific channel of an ideal analyzer, determined by averaging the outcomes over small neighborhoods of angles, approaches the Malus law when the maximum length of a segment decreases. This ensures that the classical model is self-consistent.
 When ideal analyzers are used, the absolute value of the correlation coefficient of detector readings mainly does not exceed the values from Aspect's ‘naive example’. However, when analyzers with absorption are used, the calculated correlations for some orientations of the analyzers exceed the quantum mechanical values. Key words: linear polarization of photons, Malus law, entangled photons, correlations, hidden parameters.

Domain Structure, Thermal and Mechanical Properties of Polycaprolactone-Based Multiblock Polyurethane-Ureas under Control of Hard and Soft Segment Lengths.

A series of multiblock polyurethane-ureas (PUU) based on polycaprolactone diol (PCL) with a molecular mass of 530 or 2000 g/mol, as well as hard segments of different lengths and structures, were synthesized by the step-growth polymerization method. The chemical structure of the synthesized multiblock copolymers was confirmed by IR- and NMR-spectroscopy. Differential scanning calorimetry (DSC) and dynamic mechanical analysis (DMA) were used to determine the relaxation and phase transition temperatures for the entire series of the obtained PUU. The X-ray diffraction (XRD) method made it possible to identify PUU compositions in which the crystallizability of soft segments (SS) is manifested due to their sufficient length for self-organization and structuring. Visualization of the crystal structure and disordering of the stacking of SS with an increase in their molecular mobility during heating are shown using optical microscopy. The change in the size of the hard phase domains and the value of the interdomain distance depending on the PCL molecular mass, as well as the length and structure of the hard block in the synthesized PUU, were analyzed using small-angle X-ray scattering (SAXS) and small-angle neutron scattering (SANS). The evolution of the domain structure upon passing through the melting and crystallization temperatures of PUU soft blocks was studied using SANS. The studies carried out made it possible to reveal the main correlations between the chemical structure of the synthesized PUU and their supramolecular organization as well as thermal and mechanical properties.

An object detection and classification method for underwater visual images based on the bag-of-words model

In this study, an autonomous underwater vehicle (AUV) detection technique was used as the background to investigate the target classification method for underwater visual images. The target classification method is based on the bag-of-words model, with reduced classification accuracy when the edges of underwater objects are blurred, and when there are many noise points. To solve this problem, an improved visual dictionary generation method was proposed based on the bag-of-words model. The proposed method includes a step on decomposing the complete contour of the target before extracting the features. The DCE (discrete contour evolution) algorithm was used to decompose the complete contour into segments of different lengths, and the SC (shape context) method was applied to extract the features of the contour segments. The FCM (Fuzzy C-Means) algorithm was then used to generate a visual dictionary. To address the classification accuracy problem that causes the underwater targets to decrease after adding spatial location information to the bag-of-words model instead of increasing, an improved spatial location information description method was proposed. The contour segments with the nearest-neighbor relationship were represented as visual phrases, constituting the spatial information of the bag-of-words model. Additionally, for the problem of the shape information of contour segments with different shapes, and the relative position information between the contour segments having different contributions to the target classification, a method was developed to balance the contributions of the two using the optimal weight selected from the experiments. The experimental results demonstrated that the proposed method can effectively improve the classification accuracy of underwater target images.

How incidents impact congestion on roadways: A queuing network approach

Motivated by the need for transportation infrastructure and incident management planning, we study traffic density under non-recurrent congestion. This paper provides an analytical solution approximating the stationary distribution of traffic density in roadways where deterioration of service occurs unpredictably. The proposed solution generalizes a queuing model discussed in the literature to long segments that are not space-homogeneous. We compare single and tandem queuing approaches to segments of different lengths and verify whether each model is appropriate. A single-queue approach works sufficiently well in segments with similar traffic behavior across space. In contrast, a tandem-queue approach more appropriately describes the density behavior for long segments with sections having distinct traffic characteristics. These models have a comparable fit to the ones generated using a lognormal distribution. However, they also have interpretable parameters, directly connecting the distribution of congestion to the dynamics of roadway behavior. The proposed models are general, adaptable, and tractable, thus being instrumental in infrastructure and incident management. • Traffic congestion model for highways that may experience unexpected slowdowns. • Intuitive analytical solution with a clear relation between incidents and congestion. • A discussion of situations where tandem queues work better than single queues. • The proposed models are similar to lognormal in fit but have explainable parameters.

Low-Temperature-Meltable Elastomers Based on Linear Polydimethylsiloxane Chains Alpha, Omega-Terminated with Mesogenic Groups as Physical Crosslinker: A Passive Smart Material with Potential as Viscoelastic Coupling. Part II-Viscoelastic and Rheological Properties.

Rheological and viscoelastic properties of physically crosslinked low-temperature elastomers were studied. The supramolecularly assembling copolymers consist of linear polydimethylsiloxane (PDMS) elastic chains terminated on both ends with mesogenic building blocks (LC) of azobenzene type. They are generally and also structurally highly different from the well-studied LC polymer networks or LC elastomers: The LC units make up only a small volume fraction in our materials and act as fairly efficient physical crosslinkers with thermotropic properties. The aggregation (nano-phase separation) of the relatively rare, small and spatially separated terminal LC units generates temperature-switched viscoelasticity in the molten copolymers. Their rheological behavior was found to be controlled by an interplay of nano-phase separation of the LC units (growth and splitting of their aggregates) and of the thermotropic transitions in these aggregates (which change their stiffness). As a consequence, multiple gel points (up to three) are observed in temperature scans of the copolymers. The physical crosslinks also can be reversibly disconnected by large mechanical strain in the ‘warm’ rubbery state, as well as in melt (thixotropy). The kinetics of crosslink formation was found to be fast if induced by temperature and extremely fast in case of internal self-healing after strain damage. Thixotropic loop tests hence display only very small hysteresis in the LC-melt-state, although the melts show very distinct shear thinning. Our study evaluates structure-property relationships in three homologous systems with elastic PDMS segments of different length (8.6, 16.3 and 64.4 repeat units). The studied copolymers might be of interest as passive smart materials, especially as temperature-controlled elastic/viscoelastic mechanical coupling.

Low-Temperature Meltable Elastomers Based on Linear Polydimethylsiloxane Chains Alpha, Omega-Terminated with Mesogenic Groups as Physical Crosslinkers: A Passive Smart Material with Potential as Viscoelastic Coupling. Part I: Synthesis and Phase Behavior.

Physically crosslinked low-temperature elastomers were prepared based on linear polydimethylsiloxane (PDMS) elastic chains terminated on both ends with mesogenic building blocks (LC) of azobenzene type. They are generally (and also structurally) highly different from the well-studied LC polymer networks (light-sensitive actuators). The LC units also make up only a small volume fraction in our materials and they do not generate elastic energy upon irradiation, but they act as physical crosslinkers with thermotropic properties. Our elastomers lack permanent chemical crosslinks—their structure is fully linear. The aggregation of the relatively rare, small, and spatially separated terminal LC units nevertheless proved to be a considerably strong crosslinking mechanism. The most attractive product displays a rubber plateau extending over 100 °C, melts near 8 °C, and is soluble in organic solvents. The self-assembly (via LC aggregation) of the copolymer molecules leads to a distinctly lamellar structure indicated by X-ray diffraction (XRD). This structure persists also in melt (polarized light microscopy, XRD), where 1–2 thermotropic transitions occur. The interesting effects of the properties of this lamellar structure on viscoelastic and rheological properties in the rubbery and in the melt state are discussed in a follow-up paper (“Part II”). The copolymers might be of interest as passive smart materials, especially as temperature-controlled elastic/viscoelastic mechanical coupling. Our study focuses on the comparison of physical properties and structure–property relationships in three systems with elastic PDMS segments of different length (8.6, 16.3, and 64.4 repeat units).

Investigating an Optimal Signal Epoch Length for Cardiotocographic Classification

Abstract This work focuses on investigating an optimal foetal heart rate (FHR) signal segment to be considered for automatic cardiotocographic (CTG) classification. The main idea is to evaluate a set of signal segments of different length and location based on their classification performance. For this purpose, we employ a feature extraction operation based on two signal processing techniques, such as the Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and time-varying autoregressive modelling. For each studied segment, the features are extracted and evaluated based on their performance in CTG classification. For the proposed evaluation, we make use of real CTG data extracted from the CTU-UHB database. Results show that the classification performance depends considerably on the selected FHR segment. Likewise, we have found that an optimal FHR segment for foetal welfare assessment during labour corresponds to a segment of 30 minutes long.

Increasing the Uniformity of Genome Fragment Coverage for High-Throughput Sequencing of Influenza A Virus

The high variability of the influenza A virus poses a significant threat to public health, therefore monitoring viral strains and studying their genetic properties are important tasks. One part of this monitoring includes sequencing of influenza A viruses of any subtype and analysis of their whole genomes, which is especially important in cases of interspecies adaptation and reassortment. High-throughput sequencing technologies have significantly extended the capabilities of influenza virus epidemiological surveillance. The preparation stages for next generation sequencing (NGS) of influenza A virus include whole genome amplification using one-step RT-PCR, the results of which vary greatly depending on the sample type and quality, that, in turn, affects the coverage of virus fragments and the sequencing results in general. In this work, we propose to supplement the aforementioned technique of whole genome amplification of influenza A virus with sequential suppression PCRs to obtain an even coverage of viral segments of different lengths, which allows sequencing of samples with lower read coverage without decreasing the sequencing quality.

ECG-Based Subject Identification Using Statistical Features and Random Forest

In this work, a nonfiducial electrocardiogram (ECG) identification algorithm based on statistical features and random forest classifier is presented. Two feature extraction approaches are investigated: direct and band-based approaches. In the former, eleven simple statistical features are directly extracted from a single-lead ECG signal segment. In the latter, the single-lead ECG signal is first decomposed into bands, and the statistical features are extracted from each segment of a given band and concatenated to form the feature vector. Nonoverlapping segments of different lengths (i.e., 1, 3, 5, 7, 10, or 15 sec) are examined. The extracted feature vectors are applied to a random forest classifier, for the purpose of identification. This study considers 290 reference subjects from the ECG database of the Physikalisch-Technische Bundesanstalt (PTB). The proposed identification algorithm achieved an accuracy rate of 99.61% utilizing the single limb lead (I) with the band-based approach. A single chest lead (V1), augmented limb lead (aVF), and Frank’s lead (Vx) achieved an accuracy rate of 99.37%, 99.76%, and 99.76%, respectively, using the same approach.

Empirical estimate of resonance frequency at the Dead Sea basin

We carried out assessments of the fundamental frequencies of the southern Dead Sea basin using records of teleseisms and local earthquakes, obtained by the DESERT2000 (13 events) and DESIRE (40 events) projects that aimed in studying the Dead Sea fault in general and in particular the Dead Sea basin. The observed ground motions are from teleseisms with magnitude larger than 6.5 at distances of 1340–14,800 km, and of local earthquakes in the magnitude range 3.8–4.9 at distances of 90–660 km. We determine the fundamental resonance frequencies of the Dead Sea basin using (1) ratio between the spectra of seismograms recorded on site and those recorded at a reference site and (2) horizontal-to-vertical S-wave spectral ratio. Our results allow dividing the study area into three segments of different lengths: first 22 km (stations JB12–IB13), second 5 km (stations IB15–IB17), and third 45 km (stations IB19–ID27) with fundamental frequencies 0.1, 0.2, and 0.1 Hz, respectively. Amplification factors vary from 2 to 5. Thirteen reference stations are located on rock, at distances of 1–10 km away from the basin, which recorded vibrations in the range of 0.1–0.5 Hz, generated in the Dead Sea basin. We did not find locally induced surface waves, causing significant lengthening of the shaking duration and strong low-frequency amplification. It can be explained by the linear dimensions of the Dead Sea basin, its shape, and the relatively high velocity of shear waves that varies with depth from 800 to 3200 m/s. We use stochastic optimization algorithm to calculate the velocity model, yielding 1-D transfer function matching the observed H/V curves and resonance peaks.

Effect of Domain Structure of Segmented Poly(urethane-imide) Membranes with Polycaprolactone Soft Blocks on Dehydration of n-Propanol via Pervaporation.

Segmented poly(urethane-imide)s (PUIs) were synthesized by polyaddition reaction and applied for preparation of membranes. Tolylene-2,4-diisocyanate, pyromellitic dianhydride, and m-phenylenediamine for chain extension were used to form hard aromatic blocks. Polycaprolactone diols with molecular weights equal to 530 and 2000 g mol−1 were chosen as soft segments. The effect of the length of soft segments on the structure, morphology, and transport properties of segmented poly(urethane-imide) membranes were studied using atomic force microscopy, small-angle and wide-angle X-ray scattering, and pervaporation experiments. It was found that a copolymer with a shorter soft segment (530 g mol−1) consists of soft domains in a hard matrix, while the introduction of polycaprolactone blocks with higher molecular weight (2000 g mol−1) leads to the formation of hard domains in a soft matrix. Additionally, the introduction of hard segments prevents crystallization of polycaprolactone. Transport properties of membranes based on segmented PUIs containing soft segments of different length were tested for pervaporation of a model mixture of propanol/water with 20 wt % H2O content. It was found that a membrane based on segmented PUIs containing longer soft segments demonstrates higher flux (8.8 kg μm m−2 h−1) and selectivity (179) toward water in comparison with results for pure polycaprolactone reported in literature. The membrane based on segmented PUIs with 530 g mol−1 soft segment has a lower flux (5.1 kg μm m−2 h−1) and higher selectivity (437).

Structural and electronic effects of adatoms on metallic atomic chains in Si(111)5\u2009\xd7\u20092-Au

We investigate the effects of native Si adatoms on structural and electronic properties of the Si(111)5 × 2-Au surface, a representative one-dimensional metal-chain system, by means of scanning tunneling microscopy (STM) and density functional theory (DFT) calculations. High-resolution STM images of relatively long adatom-free chain segments evidence directly the inherent ×2 reconstruction, which is the essential part of a recently proposed structural model based on a renewed Au coverage of 0.7 monolayer. On the other hand, STM images for chain segments of different lengths reveal that the structural distortion induced by Si adatoms is confined in neighboring unit cells, in good agreement with DFT calculations based on that model. Si adatoms greatly affect the metallic bands of Au chains, one of which becomes fully occupied and represents a tightly confined electronic state to the distortion around Si adatoms, potentially forming short insulating segments within metallic chains. This finding provides an atomic-scale understanding of the observed gradual metal-insulator transition and atomic-scale phase separation induced by Si adatoms.

Structural and Functional Motifs in Influenza Virus RNAs.

Influenza A viruses (IAV) are responsible for recurrent influenza epidemics and occasional devastating pandemics in humans and animals. They belong to the Orthomyxoviridae family and their genome consists of eight (-) sense viral RNA (vRNA) segments of different lengths coding for at least 11 viral proteins. A heterotrimeric polymerase complex is bound to the promoter consisting of the 13 5′-terminal and 12 3′-terminal nucleotides of each vRNA, while internal parts of the vRNAs are associated with multiple copies of the viral nucleoprotein (NP), thus forming ribonucleoproteins (vRNP). Transcription and replication of vRNAs result in viral mRNAs (vmRNAs) and complementary RNAs (cRNAs), respectively. Complementary RNAs are the exact positive copies of vRNAs; they also form ribonucleoproteins (cRNPs) and are intermediate templates in the vRNA amplification process. On the contrary, vmRNAs have a 5′ cap snatched from cellular mRNAs and a 3′ polyA tail, both gained by the viral polymerase complex. Hence, unlike vRNAs and cRNAs, vmRNAs do not have a terminal promoter able to recruit the viral polymerase. Furthermore, synthesis of at least two viral proteins requires vmRNA splicing. Except for extensive analysis of the viral promoter structure and function and a few, mostly bioinformatics, studies addressing the vRNA and vmRNA structure, structural studies of the influenza A vRNAs, cRNAs, and vmRNAs are still in their infancy. The recent crystal structures of the influenza polymerase heterotrimeric complex drastically improved our understanding of the replication and transcription processes. The vRNA structure has been mainly studied in vitro using RNA probing, but its structure has been very recently studied within native vRNPs using crosslinking and RNA probing coupled to next generation RNA sequencing. Concerning vmRNAs, most studies focused on the segment M and NS splice sites and several structures initially predicted by bioinformatics analysis have now been validated experimentally and their role in the viral life cycle demonstrated. This review aims to compile the structural motifs found in the different RNA classes (vRNA, cRNA, and vmRNA) of influenza viruses and their function in the viral replication cycle.

RNA-seq facilitates development of chromosome-specific markers and transfer of rye chromatin to wheat

Transcriptome shotgun sequencing (RNA-seq) provides an abundant resource for developing molecular markers specifically related to functional genes. In this study, transcriptomes of Chinese rye cultivar Jingzhouheimai (JZHM) challenged with powdery mildew pathogen Bgt (Blumeria graminis f. sp. tritici) were obtained and used to develop expressed sequence tag (EST)-based simple sequence repeat (SSR) and sequence-tagged site (STS) markers. A total of 866 primer sets for EST-SSRs and STSs were designed, from which we developed 401 rye-specific markers. The highest level of polymorphism was observed in EST-SSRs (56.73%) followed by STS2 (49.07%) designed via rye-specific contigs and STS1 (35.90%) primers designed from upregulated contigs. Genotyping with newly developed markers along with cytogenetic techniques allowed us to identify nine wheat alien chromosome lines from the cross of Zhoumai 18/Jinghui 1 (Jinghui 1 is an amphiploid of wheat landrace Huixianhong and JZHM) carrying rye chromosome 6R or 6R segments of different length, which permitted preliminary location of the powdery mildew resistance gene PmJZHM6RL and 12 specific markers to 6RL FL 0.51–1.0. 5R-specific markers and genomic in situ hybridization/fluorescence in situ hybridization detected MtA5RL and T5AS·5AL-5RL chromosomes among 41 F5 plants from the cross CS ph1bph1b/MA5R, and aberrations permitted the location of the hairy peduncle gene (Hp) and marker XLFZ3473 to the region 5RL FL 0.78–1.0 with another nine markers locating to 5RL 0.0–0.78. The chromosome-specific markers and chromosome aberrations developed in this study will facilitate the introgression of rye chromatin into wheat.

Establishment of an efficient in vitro regeneration and Agrobacterium rhizogenes-mediated genetic transformation protocol for safed musli (Chlorophytum borivilianum Santapau & R.R.Fern.)

Safed musli (Chlorophytum borivilianum Santapau & R.R.Fern.) is a medicinal herb valued for its tuberous roots that contain several bioactive compounds. Conventionally, safed musli tubers are harvested for secondary metabolites 9 mo after planting. Alternatively, in vitro culture can be used for mass production and to shorten the time required to produce secondary metabolites. This study was designed to develop an efficient hairy root induction protocol for safed musli. Shoot bud explants of various lengths were tested on Murashige and Skoog medium with 3 mg L−1 6-benzylaminopurine. Shoot buds >4 cm resulted in 100% multiplication, but 2- to 4-cm shoot buds produced a high multiplication rate (92%), the highest number of multiple shoots (15.55 ± 0.37), and the longest shoots (6.83 ± 0.08 cm) after 30 d of culture. In vitro shoots were infected with one of five strains of Agrobacterium rhizogenes. Only strains MAFF106590, MAFF106591, and MAFF720002 induced the hairy root phenotype indicative of genetic transformation. MAFF720002 strain had a positive transformation response in all in vitro raised safed musli stem segments of different lengths. Stems 2.5 cm in length had the highest transformation percentage (76 to 81%), greatest number of hairy roots per explant (5.02 ± 0.06), and the longest hairy roots (23 ± 0.49 cm). PCR analysis detected the rolB gene in the transformed samples. The A. rhizogenes strain played a significant role in producing and promoting the growth of hairy roots in safed musli. This approach can potentially be utilized for the replacement of conventional field methods for secondary metabolite production from safed musli.