Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Single-cell genomics and regulatory networks for 388 human brains.

Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet, little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multi-omics datasets into a resource comprising >2.8M nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550K cell-type-specific regulatory elements and >1.4M single-cell expression-quantitative-trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Effects of Lonicera japonica Extract with Different Contents of Chlorogenic Acid on Lactation Performance, Serum Parameters, and Rumen Fermentation in Heat-Stressed Holstein High-Yielding Dairy Cows.

This examined the effects of Lonicera japonica extract (LJE) with different chlorogenic acid (CGA) contents on lactation performance, antioxidant status and immune function and rumen fermentation in heat-stressed high-yielding dairy cows. In total, 45 healthy Chinese Holstein high-yielding dairy cows, all with similar milk yield, parity, and days in milk were randomly allocated to 3 groups: (1) the control group (CON) without LJE; (2) the LJE-10% CGA group, receiving 35 g/(d·head) of LJE-10% CGA, and (3) the LJE-20% CGA group, receiving 17.5 g/(d·head) of LJE-20% CGA. The results showed that the addition of LJE significantly reduced RT, and enhanced DMI, milk yield, milk composition, and improved rumen fermentation in high-yielding dairy cows experiencing heat stress. Through the analysis of the serum biochemical, antioxidant, and immune indicators, we observed a reduction in CREA levels and increased antioxidant and immune function. In this study, while maintaining consistent CGA content, the effects of addition from both types of LJE are similar. In conclusion, the addition of LJE at a level of 4.1 g CGA/(d·head) effectively relieved heat stress and improved the lactation performance of dairy cows, with CGA serving as the effective ingredient responsible for its anti-heat stress properties.

UAV hyperspectral analysis of secondary salinization in arid oasis cotton fields: effects of FOD feature selection and SOA-RF.

Secondary salinization is a crucial constraint on agricultural progress in arid regions. The specific mulching irrigation technique not only exacerbates secondary salinization but also complicates field-scale soil salinity monitoring. UAV hyperspectral remote sensing offers a monitoring method that is high-precision, high-efficiency, and short-cycle. In this study, UAV hyperspectral images were used to derive one-dimensional, textural, and three-dimensional feature variables using Competitive adaptive reweighted sampling (CARS), Gray-Level Co-occurrence Matrix (GLCM), Boruta Feature Selection (Boruta), and Brightness-Color-Index (BCI) with Fractional-order differentiation (FOD) processing. Additionally, three modeling strategies were developed (Strategy 1 involves constructing the model solely with the 20 single-band variable inputs screened by the CARS algorithm. In Strategy 2, 25 texture features augment Strategy 1, resulting in 45 feature variables for model construction. Strategy 3, building upon Strategy 2, incorporates six triple-band indices, totaling 51 variables used in the model's construction) and integrated with the Seagull Optimization Algorithm for Random Forest (SOA-RF) models to predict soil electrical conductivity (EC) and delineate spatial distribution. The results demonstrated that fractional order differentiation highlights spectral features in noisy spectra, and different orders of differentiation reveal different hidden information. The correlation between soil EC and spectra varies with the order. 1.9th order differentiation is proved to be the best order for constructing one-dimensional indices; although the addition of texture features slightly improves the accuracy of the model, the integration of the three-waveband indices significantly improves the accuracy of the estimation, with an R2 of 0.9476. In contrast to the conventional RF model, the SOA-RF algorithm optimizes its parameters thereby significantly improving the accuracy and model stability. The optimal soil salinity prediction model proposed in this study can accurately, non-invasively and rapidly identify excessive salt accumulation in drip irrigation under membrane. It is of great significance to improve the growing conditions of cotton, increase the cotton yield, and promote the sustainable development of Xinjiang's agricultural economy, and also provides a reference for the prevention and control of regional soil salinization.

DEAD-box helicase 1 inhibited CD8+ T cell antitumor activity by inducing PD-L1 expression in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) does not respond well to current treatments, even immune checkpoint inhibitors. PD-L1 (programmed cell death ligand 1 or CD274 molecule)-mediated immune escape of tumor cells may be a key factor affecting the efficacy of immune checkpoint inhibitor (ICI) therapy. However, the regulatory mechanisms of PD-L1 expression and immune escape require further exploration. Here, we observed that DDX1 (DEAD-box helicase 1) was overexpressed in HCC tissues and associated with poor prognosis in patients with HCC. Additionally, DDX1 expression correlated negatively with CD8+ T cell frequency. DDX1 overexpression significantly increased interferon gamma (IFN-γ)-mediated PD-L1 expression in HCC cell lines. DDX1 overexpression decreased IFN-γ and granzyme B production in CD8+ T cells and inhibited CD8+ T cell cytotoxic function in vitro and in vivo. In conclusion, DDX1 plays an essential role in developing the immune escape microenvironment, rendering it a potential predictor of ICI therapy efficacy in HCC.

Ultrathin Carbon Sheet Obtained by Self-Template Method toward Highly Effective Charge Transfer for Si-Based Anodes.

A dynamic and stable charge transfer process is the key to exerting lithium storage characteristics of the silicon anode with a large volume change. In this work, the composite with an ultrathin carbon sheet skeleton is prepared by freeze-drying and a copyrolysis process after uniformly mixing citric acid and hydroxylated Si NPs, which is different from traditional conformal carbon coating derived from citric acid. A flexible carbon sheet reduces internal particle (Si-OH@NC) slip and cooperates with interfacial Si-O-C bonding to buffer machinal stress in the electrode during cycling. More importantly, the carbon sheet network increases the point-to-surface contact area between the active material and the conductive agent, ensures continuous electrical connection from the current collector to the active material, and promotes a rapid and stable electron transfer process. Besides, the N-doped C structure with remarkable nucleophilicity guarantees fast ion transport, which is confirmed by theoretical calculation. In this way, the reaction reversibility of the Si-based electrode is further realized during cycles. As a result, the electrode delivers excellent cycle performance (reversible capacity of 1001.9 mAh g-1 at 1 A g-1 after 500 cycles) and rate performance (capacity retention of 86.8 and 65.8% at 1 and 3 A g-1, respectively, compared to 0.2 A g-1). The idea of constructing a highly efficient electrode conductive network through a doped-carbon sheet network is also applicable to other active materials with huge volume changes during lithium storage.

Interpretable feature extraction and dimensionality reduction in ESM2 for protein localization prediction.

As the application of large language models (LLMs) has broadened into the realm of biological predictions, leveraging their capacity for self-supervised learning to create feature representations of amino acid sequences, these models have set a new benchmark in tackling downstream challenges, such as subcellular localization. However, previous studies have primarily focused on either the structural design of models or differing strategies for fine-tuning, largely overlooking investigations into the nature of the features derived from LLMs. In this research, we propose different ESM2 representation extraction strategies, considering both the character type and position within the ESM2 input sequence. Using model dimensionality reduction, predictive analysis and interpretability techniques, we have illuminated potential associations between diverse feature types and specific subcellular localizations. Particularly, the prediction of Mitochondrion and Golgi apparatus prefer segments feature closer to the N-terminal, and phosphorylation site-based features could mirror phosphorylation properties. We also evaluate the prediction performance and interpretability robustness of Random Forest and Deep Neural Networks with varied feature inputs. This work offers novel insights into maximizing LLMs' utility, understanding their mechanisms, and extracting biological domain knowledge. Furthermore, we have made the code, feature extraction API, and all relevant materials available at https://github.com/yujuan-zhang/feature-representation-for-LLMs.

Novel Ultra-Stable 2D SbBi Alloy Structure with Precise Regulation Ratio Enables Long-Stable Potassium/Lithium-Ion Storage.

The inferior cycling stabilities or low capacities of 2D Sb or Bi limit their applications in high-capacity and long-stability potassium/lithium-ion batteries (PIBs/LIBs). Therefore, integrating the synergy of high-capacity Sb and high-stability Bi to fabricate 2D binary alloys is an intriguing and challenging endeavor. Herein, a series of novel 2D binary SbBi alloys with different atomic ratios are fabricated using a simple one-step co-replacement method. Among these fabricated alloys, the 2D-Sb0.6 Bi0.4 anode exhibits high-capacity and ultra-stable potassium and lithium storage performance. Particularly, the 2D-Sb0.6 Bi0.4 anode has a high-stability capacity of 381.1 mAh g-1 after 500 cycles at 0.2 A g-1 (≈87.8% retention) and an ultra-long-cycling stability of 1000 cycles (0.037% decay per cycle) at 1.0 A g-1 in PIBs. Besides, the superior lithium and potassium storage mechanism is revealed by kinetic analysis, in-situ/ex-situ characterization techniques, and theoretical calculations. This mainly originates from the ultra-stable structure and synergistic interaction within the 2D-binary alloy, which significantly alleviates the volume expansion, enhances K+ adsorption energy, and decreases the K+ diffusion energy barrier compared to individual 2D-Bi or 2D-Sb. This study verifies a new scalable design strategy for creating 2D binary (even ternary) alloys, offering valuable insights into their fundamental mechanisms in rechargeable batteries.

Grafting a Polymer Coating Layer onto Li1.2 Ni0.13 Co0.13 Mn0.54 O2 Cathode by Benzene Diazonium Salts to Facilitate the Cycling Performance and High-Voltage Stability.

Li-rich Mn-based cathodes have been regarded as promising cathodes for lithium-ion batteries because of their low cost of raw materials (compared with Ni-rich layer structure and LiCoO2 cathodes) and high energy density. However, for practical application, it needs to solve the great drawbacks of Li-rich Mn-based cathodes like capacity degradation and operating voltage decline. Herein, an effective method of surface modification by benzene diazonium salts to build a stable interface between the cathode materials and the electrolyte is proposed. The cathodes after modification exhibit excellent cycling performance (the retention of specific capacity is 84.2% after 350 cycles at the current density of 1 C), which is mainly attributed to the better stability of the structure and interface. This work provides a novel way to design the coating layer with benzene diazonium salts for enhancing the structural stability under high voltage condition during cycling.

Air-Working Electrochromic Artificial Muscles.

Artificial muscles are indispensable components for next-generation robotics to mimic the sophisticated movements of living systems and provide higher output energies when compared with real muscles. However, artificial muscles actuated by electrochemical ion injection have problems with single actuation properties and difficulties in stable operation in air. Here, air-working electrochromic artificial muscles (EAMs) with both color-changing and actuation functions are reported, which are constructed based on vanadium pentoxide nanowires and carbon tube yarn. Each EAM can generate a contractile stroke of ≈12% during stable operation in the air with multiple color changes (yellow-green-gray) under ±4 V actuation voltages. The reflectance contrast is as high as 51%, demonstrating the excellent versatility of the EAMs. In addition, a torroidal EAM arrangement with fast response and high resilience is constructed. The EAM's contractile stroke can be displayed through visual color changes, which provides new ideas for future artificial muscle applications in soft robots and artificial limbs.

Core-Shell ZIF-8@ZIF-67-Derived Cobalt Nanoparticle-Embedded Nanocage Electrocatalyst with Excellent Oxygen Reduction Performance for Zn-Air Batteries.

Metal-nitrogen-carbon (M-N-C) catalysts obtained from zeolitic imidazolate frameworks (ZIFs) have great potential in the oxygen reduction reaction (ORR). Herein, based on the same three-dimensional (3D) topological structure of ZIF-67 and ZIF-8, ZIF-67 is grown on the ZIF-8 surface by the epitaxial growth method, and ZIF-8 is used as a sacrificial template to obtain a Co-embedded layered porous carbon nanocage (CoPCN) electrocatalyst. Meanwhile, the self-sacrificing template effectively improves the specific surface area of the porous structure and reduces the depletion of active sites. The CoPCN shows a high half-wave potential of 0.885 V and superior stability as well as excellent methanol resistance. Theoretical calculations demonstrate that the Co-N1-C2 sites of CoPCN effectively reduce the energy barrier of ORR. In addition, a zinc-air battery (ZAB) based on the CoPCN exhibits excellent peak power density (90 mW cm-2) and superior cycle performance. This work presents a novel idea in the design of ZIF precursor systems to synthesize efficient ORR catalysts.

SIRT1 Inhibition-Induced Mitochondrial Damage Promotes GSDME-Dependent Pyroptosis in Hepatocellular Carcinoma Cells.

Hepatocellular carcinoma (HCC) is a malignant tumor that affects the liver and poses a significant threat to human health. Further investigation is necessary to fully understand the role of SIRT1, a protein linked to tumorigenesis, in HCC development. To investigate the effect of SIRT1 on HCC and elucidate the underlying mechanism. Eight pairs of HCC and paracancerous normal tissue specimens were collected. The levels of SIRT1 and GSDME in tissue samples were assessed using immunohistochemistry and western blotting. SIRT1 levels were determined in HCC (Huh7, HepG2, SNU-423, SNU-398, and HCCLM3) and L-02 cells using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and western blotting. SNU-423 and HCCLM3 cells were transfected with si-SIRT1 and/or si-GSDME to knock down SIRT1 or GSDME expression. RT-qPCR and western blotting were performed to measure the expression of SIRT1, pro-casp-3, cl-casp-3, GSDME, GSDME-N, PGC-1α, Bax, and cytochrome c (Cyto C). Cell proliferation, migration, invasion, and apoptosis were assessed using the cell counting kit-8 (CCK-8), wound healing assay, Transwell invasion assay, and flow cytometry, respectively. The release of lactate dehydrogenase (LDH) was evaluated using an LDH kit. SIRT1 was upregulated in HCC tissues and cells, and a negative correlation was observed between SIRT1 and GSDME-N. SIRT1 silencing suppressed the proliferation, migration, and invasion of HCC cells while also promoting apoptosis and inducing mitochondrial damage. Additionally, the silencing of SIRT1 resulted in the formation of large bubbles on the plasma membrane of HCC cells, leading to cellular swelling and aggravated GSDME-dependent pyroptosis, resulting in an increase in LDH release. Inhibition of GSDME reduced SIRT1 silencing-induced cell swelling, decreased LDH release rate, and promoted apoptosis. SIRT1 silencing promotes GSDME-dependent pyroptosis in HCC cells by damaging mitochondria.

Identification of a Novel CD8+ T cell exhaustion-related gene signature for predicting survival in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) is a major health concern, necessitating a deeper understanding of its prognosis and underlying mechanisms. This study aimed to investigate the mechanism and prognostic value of CD8+ T Cell exhaustion (CD8+ TEX)-related genes in HCC and construct a survival prognosis prediction model for patients with HCC. METHODS: CD8+ TEX-related genes associated with HCC prognosis were analysed and identified, and a prognostic prediction model was constructed using the 'least absolute shrinkage and selection operator' Cox regression model. Immunohistochemistry was used to verify the expression of the model genes in HCC tissues. A nomogram was constructed based on risk scores and clinical features, and its predictive efficacy was verified. The expression of STAM, ANXA5, and MAD2L2 in HCC cell lines was detected by western blotting; subsequently, these genes were knocked down in HCC cell lines by small interfering RNA, and their effects on the proliferation and migration of HCC cell lines were detected by colony formation assay, cck8, wound healing, and transwell assays. RESULTS: Six genes related to CD8+ TEX were included in the risk-prediction model. The prognosis of patients with HCC in the low-risk group was significantly better than that of those in the high-risk group. Cox regression analysis revealed that the risk score was an independent risk factor for the prognosis of patients with HCC. The differentially expressed genes in patients with high-risk HCC were mainly enriched in the nucleotide-binding oligomerization domain-containing protein-like receptor, hypoxia-inducible factor-1, and tumour programmed cell death protein (PD)-1/PD-L1 immune checkpoint pathways. The CD8+ TEX-related genes STAM, ANXA5, and MAD2L2 were knocked down in HCC cell lines to significantly inhibit cell proliferation and migration. The prediction results of the nomogram based on the risk score showed a good fit and application value. CONCLUSION: The prediction model based on CD8+ TEX-related genes can predict the prognosis of HCC and provide a theoretical basis for the early identification of patients with poor HCC prognosis.

No causal effect of genetically determined circulating homocysteine levels on psoriasis in the European population: evidence from a Mendelian randomization study.

Background: Although numerous studies demonstrated a link between plasma homocysteine (Hcy) levels and psoriasis, there still exists a certain level of controversy. Therefore, we conducted a Mendelian randomization study to investigate whether homocysteine plays a causative role in the development or exacerbation of psoriasis. Methods: A two-sample Mendelian randomization (MR) analysis was conducted. Summary-level data for psoriasis were acquired from the latest R9 release results from the FinnGen consortium (9,267 cases and 364,071 controls). Single nucleotide polymorphisms (SNPs) robustly linked with plasma Hcy levels at the genome-wide significance threshold (p < 5 × 10-8) (18 SNPs) were recognized from the genome-wide meta-analysis on total Hcy concentrations (n = 44,147 participants) in individuals of European ancestry. MR analyses were performed utilizing the random-effect inverse variance-weighted (IVW), weighted median, and MR-Egger regression methods to estimate the associations between the ultimately filtrated SNPs and psoriasis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy. Results: MR analyses revealed no causal effects of plasma Hcy levels on psoriasis [IVW: odds ratio (OR) = 0.995 (0.863-1.146), p = 0.941; weighed median method: OR = 0.985 (0.834-1.164), p = 0.862; MR-Egger regression method: OR = 0.959 (0.704-1.305), p = 0.795]. The sensitivity analyses displayed no evidence of heterogeneity and directional pleiotropy, and the causal estimates of Hcy levels were not influenced by any individual SNP. Conclusion: Our study findings did not demonstrate a causal effect of genetically determined circulating Hcy levels on psoriasis.

Effects of Different Galacto-Oligosaccharide Supplementation on Growth Performance, Immune Function, Serum Nutrients, and Appetite-Related Hormones in Holstein Calves.

Our previous study showed that early supplementation with 10 g/(d·head) of galacto-oligosaccharides (GOS) in newborn Holstein dairy calves reduced the incidence of diarrhea and improved growth performance and mineral absorption. Since the dose of 10 g/(d·head) was the lowest by dose screening in our previous study, the present study was designed to investigate whether a lower amount of GOS has similar effects on growth performance, immune function, serum nutrients in newborn Holstein heifer calves, and to further investigate its effect on appetite-related hormones. Twenty-eight healthy newborn (1 day of age) Holstein heifers with similar average body weight (41.18 ± 1.90 kg) were randomly divided into four groups (n = 7): the control group (CON group), which received heated raw milk, and three experimental groups, which received heated raw milk supplemented with 2.5 (GOS2.5 group), 5 (GOS5 group), and 10 g/(d·head) (GOS10 group) GOS. All heifer calves were fed the same starter for 28 d. Supplementation with GOS linearly increased the final body weight, average daily gain, and feed efficiency in heifer calves (p < 0.01). Compared with the control group, the average daily gain and feed efficiency of heifer calves were significantly higher in the GOS5 and GOS10 groups than in the control group (p < 0.05). Furthermore, supplementation with GOS quadratically enhanced the starter and total average daily feed intake of the heifers (p < 0.01), especially in the GOS2.5 and GOS5 groups, (p < 0.05 vs. CON). The serum concentration of immunoglobulin A was linearly increased by GOS supplementation (p < 0.05), and the levels in the GOS5 and GOS10 groups were significantly higher than those in the CON group. Meanwhile, GOS linearly decreased serum interleukin-1ß and interleukin-6 concentrations (p < 0.05). The serum concentration of triglycerides was also linearly decreased (p < 0.05), whereas total protein and blood urea nitrogen were linearly increased (p < 0.05). Supplementation with GOS linearly decreased the serum concentration of leptin (p < 0.05) but increased cholecystokinin and glucagon-like peptide-1 (p < 0.05). Increasing doses of GOS linearly improved serum calcium and copper concentrations (p < 0.01) and quadratically enhanced the concentration of magnesium, which peaked in the GOS5 group (p < 0.05). In conclusion, GOS supplementation reduced the incidence of diarrhea and improved the growth performance and immune function of Holstein heifer calves.

From beasts to bytes: Revolutionizing zoological research with artificial intelligence.

Since the late 2010s, Artificial Intelligence (AI) including machine learning, boosted through deep learning, has boomed as a vital tool to leverage computer vision, natural language processing and speech recognition in revolutionizing zoological research. This review provides an overview of the primary tasks, core models, datasets, and applications of AI in zoological research, including animal classification, resource conservation, behavior, development, genetics and evolution, breeding and health, disease models, and paleontology. Additionally, we explore the challenges and future directions of integrating AI into this field. Based on numerous case studies, this review outlines various avenues for incorporating AI into zoological research and underscores its potential to enhance our understanding of the intricate relationships that exist within the animal kingdom. As we build a bridge between beast and byte realms, this review serves as a resource for envisioning novel AI applications in zoological research that have not yet been explored.

Chitosan-Delivered Chlorantraniliprole for Pest Control: Preparation Optimization, Deposition Behavior, and Application Potential.

Chitosan has emerged as a promising biopolymer carrier for the sustained release of pesticides owing to its good biocompatibility, biodegradability, and bioactivity. In this work, a controlled-release formulation of insecticide chlorantraniliprole was fabricated through coprecipitation-based synchronous encapsulation with chitosan, where the optimum preparation conditions, storage stability, deposition behavior, and application potential were investigated. Preparation of optimization data from response surface methodology showed high correlation coefficient (R2) of 0.9875 and adjusted coefficient (Radj2) of 0.9715. The resulting formulation displayed good loading content of 28.39%, high encapsulation efficiency of 75.71%, and good storage stability. Compared with the commercial suspension concentrate, the formulation exhibited better wettability and retention behaviors on plant leaves. Excitingly, effective control against one species of mealybug genus Paraputo Laing (outside the killing spectrum) on the Hippeastrum reticulatum plant was successfully achieved by spraying the controlled-release formulation at different time intervals. This work indicates the good potential of the developed formulation in expanding the application scope of chlorantraniliprole, which shows a new strategy for sustainable pest management.

Multiplexed emitting system for an energy-recovery-linac-based coherent light source.

Recently, a novel approach has been proposed to produce ultrashort, fully coherent high-repetition-rate EUV and X-ray radiation by combining an energy recovery linac (ERL) with the angular-dispersion-induced microbunching methodology. It is critical to maintain microbunching when the beam passes through bending magnets between the undulators, which results in difficulties supporting multiple beamlines. In this paper, the design of a multiplexed emitting system consisting of multi-bend achromats, matching sections and radiators to facilitate the multi-beamline operation is presented. Theoretical analysis and numerical simulations have been carried out and the results show that the microbunching and beam quality can be well maintained after four times of bending. Five radiation pulses with a central wavelength of 13.5 nm and peak power at the MW level have been produced by the same electron beam via this multiplexed emitting system. The proposed method holds potential in the multi-beamline operation of ERL- or storage-ring-based coherent light sources.

Early supplementation with zinc proteinate does not change rectal microbiota but increases growth performance by improving antioxidant capacity and plasma zinc concentration in preweaned dairy calves.

The present study evaluated the effects of early supplementation with zinc proteinate (ZnP) or zinc oxide (ZnO) for 2 weeks on the growth performance, redox status, plasma trace element concentrations, and rectal microbiota of preweaned dairy calves. A total of 60 newborn healthy female Holstein dairy calves, with initial body weight (BW): 41.33 ± 0.62 kg, were randomly allocated to 5 groups of 12 each: a control group (CON); three groups supplemented with 261 (L-ZnP), 523 (M-ZnP), and 784 (H-ZnP) mg/day ZnP, equivalent to 40, 80, and 120 mg/day zinc, respectively; and one group supplemented with 232 mg/day ZnO, equivalent to 180 mg/day zinc (ZnO). Zinc supplements were administered on days 1-14, and the calves were followed up until day 70. Zinc supplementation increased total dry matter intake (DMI) and starter DMI compared with the CON group (p < 0.01). The final BW, average daily gain, and feed efficiency were higher in the M-ZnP, H-ZnP, and ZnO groups (p < 0.05). The incidence of diarrhea on days 1-28 was reduced by zinc administration (p < 0.01), whereas the incidence on days 29-56 was lower in the M-ZnP and ZnO groups (p < 0.05). Serum glutathione peroxidase activity, total antioxidant capacity, immunoglobulin G and plasma zinc concentrations were increased linearly (p < 0.05), while the serum concentration of malondialdehyde was decreased linearly (p < 0.01), as the dose of ZnP increased. ZnP yielding 80 mg/day zinc had similar effects as ZnO yielding 180 mg/day zinc, except that final BW was higher in the ZnO group (p < 0.05). At the phylum level, ZnO decreased the relative abundance of Firmicutes while increasing the abundance of Bacteroidetes (p < 0.05). At the genus level, ZnO increased the relative abundances of Prevotella, Subdoligranulum, and Odoribacter (p < 0.05). These findings indicated that early supplementation with ZnP did not affect the rectal microbiota of preweaned dairy calves but increased their growth performance, antioxidant capacity, and plasma zinc concentration. In summary, ZnP is an organic zinc source with greater bioavailability than ZnO for preweaned dairy calves. Early dietary supplementation with ZnP yielding 80 mg/day zinc is recommended.

A Digital PCR Method Based on Highly Specific Taq for Detecting Gene Editing and Mutations.

Digital PCR (dPCR) has great potential for assessing gene editing or gene mutation due to its ability to independently inspect each DNA template in parallel. However, current dPCR methods use a fluorescence-labeled probe to detect gene variation events, and their ability to distinguish variated sequences from the wild-type sequence is limited by the probe's tolerance to mismatch. To address this, we have developed a novel dPCR method that uses a primer instead of a probe to sense gene variation. The enhanced Taq DNA polymerase in the PCR system has a high mismatch sensitivity, which enables our dPCR method to distinguish gene mutations from wild-type sequences. Compared to current dPCR methods, our method shows superior precision in assessing gene editing efficiency and single-base DNA mutation. This presents a promising opportunity to advance gene editing research and rare gene mutation detection.