Two-Plasmid Packaging System for Recombinant Adeno-Associated Virus

A number of packaging systems are available for production of recombinant adeno-associated virus vectors (rAAVs). Among these, the use of a two-plasmid cotransfection system, in which Rep and Cap genes and Ad helper genes are on the same plasmid, has not been frequently employed for good manufacturing practices (GMP) production, even though it presents some practical advantages over the common three-plasmid (triple) transfection method. To confirm and expand the utility of the two-plasmid system, we generated GMP-compatible versions of this system and used those package reporter genes in multiple capsid variants in direct comparison with triple transfection. Vector yields, purity, and empty-to-full ratios were comparable between double and triple transfection methods for all capsid variants tested. We performed an in vivo side-by-side comparison of double and triple transfection vectors following both intravenous injection and intramuscular injection in mice. Expression and transduction were evaluated in muscle and liver 4 weeks after injection. Additional studies of bioactivity were conducted in vivo using packaged vectors carrying a variety of cargos, including the therapeutic transgene, microRNA, and single- or double-stranded vector. Results showed that cargos packaged using double transfection were equivalently bioactive to those packaged using a triple transfection system. In conclusion, these data suggest the utility of midrange (1E12-1E16) GMP-compatible packaging of adeno-associated virus (AAV) vectors for several AAV capsids

DeepSeek LLM: Scaling Open-Source Language Models with Longtermism

The rapid development of open-source large language models (LLMs) has been truly remarkable. However, the scaling law described in previous literature presents varying conclusions, which casts a dark cloud over scaling LLMs. We delve into the study of scaling laws and present our distinctive findings that facilitate scaling of large scale models in two commonly used open-source configurations, 7B and 67B. Guided by the scaling laws, we introduce DeepSeek LLM, a project dedicated to advancing open-source language models with a long-term perspective. To support the pre-training phase, we have developed a dataset that currently consists of 2 trillion tokens and is continuously expanding. We further conduct supervised fine-tuning (SFT) and Direct Preference Optimization (DPO) on DeepSeek LLM Base models, resulting in the creation of DeepSeek Chat models. Our evaluation results demonstrate that DeepSeek LLM 67B surpasses LLaMA-2 70B on various benchmarks, particularly in the domains of code, mathematics, and reasoning. Furthermore, open-ended evaluations reveal that DeepSeek LLM 67B Chat exhibits superior performance compared to GPT-3.5

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Age-Dependent Upper Limb Myoelectric Control Capability in Typically Developing Children

Research in EMG-based control of prostheses has mainly utilized adult subjects who have fully developed neuromuscular control. Little is known about children’s ability to generate consistent EMG signals necessary to control artificial limbs with multiple degrees of freedom. As a first step to address this gap, experiments were designed to validate and benchmark two experimental protocols that quantify the ability to coordinate forearm muscle contractions in typically developing children. Non-disabled, healthy adults and children participated in our experiments that aimed to measure an individual’s ability to use myoelectric control interfaces. In the first experiment, participants performed 8 repetitions of 16 different hand/wrist movements. Using offline classification analysis based on Support Vector Machine, we quantified their ability to consistently produce distinguishable muscle contraction patterns. We demonstrated that children had a smaller number of highly independent movements (can be classified with >90% accuracy) than adults did. The second experiment measured participants’ ability to control the position of a cursor on a 1-DoF virtual slide using proportional EMG control with three different visuomotor gain levels. We found that children had higher failure rates and slower average target acquisitions than adults did, primarily due to longer correction times that did not improve over repetitive practice. We also found that the performance in both experiments was age-dependent in children. The results of this study provide novel insights into the technical and empirical basis to better understand neuromuscular development in children with upper-limb loss

Research on Fault Diagnosis of Highway Bi-LSTM Based on Attention Mechanism

Deep groove ball bearings are widely used in rotary machinery. Accurate for bearing faults diagnosis is essential for equipment maintenance. For common depth learning methods, the feature extraction of inverse time domain signal direction and the attention to key features are usually ignored. Based on the long short term memory(LSTM) network, this study proposes an attention-based highway bidirectional long short term memory (AHBi-LSTM) network for fault diagnosis based on the raw vibration signal. By increasing the Attention mechanism and Highway, the ability of the network to extract features is increased. The bidirectional LSTM network simultaneously extracts the raw vibration signal in positive and inverse time-domains to better extract the fault features. Six deep groove ball bearings with different health conditions were used to validate the AHBi-LSTM method in an experiment. The results showed that the accuracy of the proposed method for bearing fault diagnosis was over 98%, which was 8.66% higher than that of the LSTM model. The AHBi-LSTM model is also better than other relevant models for bearing fault diagnosis

Atrial Fibrillation Detection Based on a Residual CNN Using BCG Signals

Atrial fibrillation (AF) is the most common arrhythmia and can seriously threaten patient health. Research on AF detection carries important clinical significance. This manuscript proposes an AF detection method based on ballistocardiogram (BCG) signals collected by a noncontact sensor. We first constructed a BCG signal dataset consisting of 28,214 ten-second nonoverlapping segments collected from 45 inpatients during overnight sleep, including 9438 for AF, 9570 for sinus rhythm (SR), and 9206 for motion artifacts (MA). Then, we designed a residual convolutional neural network (CNN) for AF detection. The network has four modules, namely a downsampling convolutional module, a local feature learning module, a global feature learning module, and a classification module, and it extracts local and global features from BCG signals for AF detection. The model achieved precision, sensitivity, specificity, F1 score, and accuracy of 96.8%, 93.7%, 98.4%, 95.2%, and 96.8%, respectively. The results indicate that the AF detection method proposed in this manuscript could serve as a basis for long-term screening of AF at home based on BCG signal acquisition

Ligand-Free Iron-Catalyzed Regiodivergent Hydroboration of Unactivated Terminal Alkenes

The control of regioselectivities has been recognized as the elementary issue for alkene hydroboration. Despite considerable progress, the specificity of alkene substrates or the adjustment of ligands were necessary for specific regioselectivities, which restrict the universality and practicability. Herein, we report a ligand-free iron-catalyzed regiodivergent hydroboration of unactivated terminal alkenes that obtains both Markovnikov and anti-Markovnikov hydroboration products in excellent regioselectivities. Notably, solvents and bases were shown to be crucial factors influencing the regioselectivities and further studies suggested the iron-boron alkoxide ate complex is the key intermediate that determines the unusual Markovnikov regioselectivity. Terminal alkenes with diverse structures (mono-substituted and 1,1-disubstituted, open-chain and exocyclic) underwent the transformation smoothly. The reaction does not require the addition of auxiliary ligands and it can be performed on a gram scale, thus providing an efficient and sustainable method for the synthesis of primary, secondary, and tertiary alkyl borates

A comparative study on the comprehensive properties of natural microfibers isolated from the large-clustered bamboos in the southwest of China using steam explosion

To develop sustainable functional fibers and expand their novel applications, the large-clustered dendrocalamus sinicus (DS) and the dendrocalamus giganteus (DG) planted in the southwest of China were effectively isolated by steam explosion (SE). The fine and uniform bamboo microfibers of DS and DG corresponding to the smallest average widths of 18.24 μm and 17.16 μm were obtained, respectively. The relative content of cellulose in two bamboo species had a marked increase after SE but a decrease for hemicellulose and lignin without any introduction of toxic chemical reagents. The SE treatment improved the thermal stability, the crystallinity, and the surface hydrophilicity of bamboo samples with their morphologies varying from rod-shaped strips to fibrous filaments. The degrees of crystallinity for DS and DG increased from 57.63% and 57.53% to 73.67% and 74.10%, respectively. The thermal stability, mechanical properties, and hydrophobicity of bamboo microfibers derived from DS were superior to those of DG, which showed a higher maximum decomposition temperature (5.24°C), tensile strength (181 MPa), elongation at break (1.1%), and water contact angle (7.8°)