Analysis of complication risk factors in preoperative computed tomography-guided hookwire location of pulmonary nodules.

BACKGROUND: This study aimed to explore the efficacy of hookwire for computed tomography (CT)-guided pulmonary nodule (PN) localization before video-assisted thoracoscopic surgery (VATS) resection and determine the risk factors for localization-related complications. METHODS: We enrolled 193 patients who underwent preoperative CT-guided PN hookwire localization. The patients were categorized into groups A (103 patients had no complications) and B (90 patients had complications) according to CT and VATS. Uni- and multivariate logistic regression analyses were used to identify risk factors for localization-related complications. A numerical rating scale was used to evaluate hookwire localization-induced pain. RESULTS: We successfully performed localization in 173 (89.6%) patients. Pneumothorax was the main complication in 82 patients (42.5%). Patient gender, age, body mass index, tumor diameter, consolidation tumor ratio, pathologic diagnosis, position adjustment during location, lesion location, waiting time for surgery, and pleural adhesions were not significantly different between the two groups. The number of nodules, number of punctures, scapular rest position, and depth of insertion within the lung parenchyma were significant factors for successful localization. Multivariate regression analysis further validated the number of nodules, scapular rest position, and depth of insertion within the lung parenchyma as risk factors for hookwire-localization-related complications. Hookwire localization-induced pain is mainly mild or moderate pre- and postoperatively, and some patients still experience pain 7 days postoperatively. CONCLUSIONS: Hookwire preoperative PN localization has a high success rate, but some complications remain. Thus, clinicians should be vigilant and look forward to further improvement.

Energetic Information from Information-Theoretic Approach in Density Functional Theory as Quantitative Measures of Physicochemical Properties.

The Hohenberg-Kohn theorem of density functional theory (DFT) stipulates that energy is a universal functional of electron density in the ground state, so energy can be thought of having encoded essential information for the density. Based on this, we recently proposed to quantify energetic information within the framework of information-theoretic approach (ITA) of DFT (J. Chem. Phys. 2022, 157, 101103). In this study, we systematically apply energetic information to a variety of chemical phenomena to validate the use of energetic information as quantitative measures of physicochemical properties. To that end, we employed six ITA quantities such as Shannon entropy and Fisher information for five energetic densities, yielding twenty-six viable energetic information quantities. Then, they are applied to correlate with physicochemical properties of molecular systems, including chemical bonding, conformational stability, intermolecular interactions, acidity, aromaticity, cooperativity, electrophilicity, nucleophilicity, and reactivity. Our results show that different quantities of energetic information often behave differently for different properties but a few of them, such as Shannon entropy of the total kinetic energy density and information gain of the Pauli energy density, stand out and strongly correlate with several properties across different categories of molecular systems. These results suggest that they can be employed as quantitative measures of physicochemical properties. This work not only enriches the body of our knowledge about the relationship between energy and information, but also provides scores of newly introduced explicit density functionals to quantify physicochemical properties, which can serve as robust features for building machine learning models in future studies.

The Associations between Healthy Eating Patterns and Risk of Metabolic Dysfunction-Associated Steatotic Liver Disease: A Case-Control Study.

BACKGROUND: Although several epidemiological studies have identified an inverse association between healthy dietary patterns and metabolic dysfunction-associated steatotic liver disease (MASLD)/non-alcoholic fatty liver disease (NAFLD), little is known about the contribution of the food component to MASLD risk and the association between dietary patterns and severity of MASLD. This study aimed to investigate the association between healthy eating patterns and MASLD risk and severity of MASLD. METHODS: A case-control study including 228 patients diagnosed with MASLD and 228 controls was conducted. The modified Alternate Healthy Eating Index (AHEI), Dietary Approaches to Stop Hypertension (DASH) score, and Alternative Mediterranean Diet (AMED) score were evaluated based on information collected via a validated food-frequency questionnaire. MASLD was confirmed if participants presented with ultrasound-diagnosed fatty liver diseases along with at least one of five cardiometabolic risk factors and no other discernible cause. The logistic regression models were applied to estimate the odds ratio (OR) and 95% confidence interval (95% CI) of MASLD for dietary scores. RESULTS: Compared with participants in the lowest tertile, those in the highest tertile of AHEI had a 60% reduced risk of MASLD (OR: 0.40; 95% CI: 0.25-0.66). Similar associations were also observed for DASH and AMED, with ORs comparing extreme tertiles of 0.38 (95% CI: 0.22-0.66) and 0.46 (95% CI: 0.28-0.73), respectively. Further Stratified analysis revealed that the inverse associations between AHEI and DASH with MASLD risks were stronger among women than men, and the inverse associations between AMED and MASLD risks were more pronounced among participants with normal weight (OR: 0.22; 95% CI: 0.09-0.49). For components within the dietary score, every one-point increase in vegetable score and whole grain score within the AHEI was associated with an 11% (95% CI: 5-16%) and a 6% (95% CI: 0-12%) lower MASLD risk, respectively. Similar inverse associations with those scores were observed for the DASH and AMED. CONCLUSION: Greater adherence to healthy eating patterns was associated with reduced risk of MASLD, with vegetables and whole grains predominately contributing to these associations. These findings suggested that healthy eating patterns should be recommended for the prevention of MASLD.

Stem cell division and its critical role in mammary gland development and tumorigenesis: current progress and remaining challenges.

The origin of breast cancer (BC) has traditionally been a focus of medical research. It is widely acknowledged that BC originates from immortal mammary stem cells (MaSCs) and that these stem cells participate in two division modes: symmetric cell division (SCD) and asymmetric cell division (ACD). Although both of these modes are key to the process of breast development and their imbalance is closely associated with the onset of BC, the molecular mechanisms underlying these phenomena deserve in-depth exploration. In this review, we first outline the molecular mechanisms governing ACD/SCD and analyze the role of ACD/SCD in various stages of breast development. We describe that the changes in telomerase activity, the role of polar proteins, and the stimulation of ovarian hormones subsequently lead to two distinct consequences: breast development or carcinogenesis. Finally, gene mutations, abnormalities in polar proteins, modulation of signal-transduction pathways, and alterations in the microenvironment disrupt the balance of breast cancer stem cells (BCSCs) division modes and cause BC. Important regulatory factors such as mammalian Inscuteable (mInsc), Numb, Eya1, PKCα, PKCθ, p53, and IL-6 also play significant roles in regulating pathways of ACD/SCD and may constitute key targets for future research on stem cell division, breast development, and tumor therapy.

Kinetic Network in Milestoning: Clustering, Reduction, and Transition Path Analysis.

We present a reduction of the Milestoning (ReM) algorithm to analyze the high-dimensional Milestoning kinetic network. The algorithm reduces the Milestoning network to low dimensions but preserves essential kinetic information, such as local residence time, exit time, and mean first passage time between any two states. This is achieved in three steps. First, nodes (milestones) in the high-dimensional Milestoning network are grouped into clusters based on the metastability identified by an auxiliary continuous-time Markov chain. Our clustering method is applicable not only to time-reversible networks but also to nonreversible networks generated from practical simulations with statistical fluctuations. Second, a reduced network is established via network transformation, containing only the core sets of clusters as nodes. Finally, transition pathways are analyzed in the reduced network based on the transition path theory. The algorithm is illustrated using a toy model and a solvated alanine dipeptide in two and four dihedral angles.

Interleukin-33 increases the sensitivity of multiple myeloma cells to the proteasome inhibitor bortezomib through reactive oxygen species-mediated inhibition of nuclear factor kappa-B signal and stemness properties.

The proteasome inhibitor bortezomib (BTZ) is the first-line therapy for multiple myeloma (MM). BTZ resistance largely limits its clinical application in MM. Interleukin-33 (IL-33) exerts antitumor effects through various mechanisms, including enhancing antitumor immunity and promoting the apoptosis of cancer cells. Here, the synergistic anti-MM effect of IL-33 and BTZ was verified, and the underlying mechanisms were elucidated. Bioinformatic analysis indicated that IL-33 expression levels were downregulated in MM, and that BTZ-treated MM patients with high IL-33 levels had better prognosis than those with low IL-33 levels. Moreover, the patients with high IL-33 levels had a better treatment response to BTZ. Further immune analysis suggested that IL-33 can enhance the anti-MM immunity. IL-33 and BTZ synergistically inhibited proliferation and induced apoptosis of MM cells, which was mediated by the excessive accumulation of cellular reactive oxygen species (ROS). Furthermore, increased ROS hindered the nuclear translocation of NF-κB-p65, thereby decreasing the transcription of target stemness-related genes (SOX2, MYC, and OCT3/4). These effects induced by the combination therapy could be reversed by eliminating ROS by N-acetylcysteine. In conclusion, our results indicated that IL-33 enhanced the sensitivity of MM to BTZ through ROS-mediated inhibition of nuclear factor kappa-B (NF-κB) signal and stemness properties.

Pushing the Limit of Photo-Controlled Polymerization: Hyperchromic and Bathochromic Effects.

The photocatalyst (PC) zinc tetraphenylporphyrin (ZnTPP) is highly efficient for photoinduced electron/energy transfer reversible addition-fragmentation chain transfer (PET-RAFT) polymerization. However, ZnTPP suffers from poor absorbance of orange light by the so-called Q-band of the absorption spectrum (maximum absorption wavelength λmax = 600 nm, at which molar extinction coefficient εmax = 1.0×104 L/(mol·cm)), hindering photo-curing applications that entail long light penetration paths. Over the past decade, there has not been any competing candidate in terms of efficiency, despite a myriad of efforts in PC design. By theoretical evaluation, here we rationally introduce a peripheral benzo moiety on each of the pyrrole rings of ZnTPP, giving zinc tetraphenyl tetrabenzoporphyrin (ZnTPTBP). This modification not only enlarges the conjugation length of the system, but also alters the a1u occupied π molecular orbital energy level and breaks the accidental degeneracy between the a1u and a2u orbitals, which is responsible for the low absorption intensity of the Q-band. As a consequence, not only is there a pronounced hyperchromic and bathochromic effect (λmax = 655 nm and εmax = 5.2×104 L/(mol·cm)) of the Q-band, but the hyperchromic effect is achieved without increasing the intensity of the less useful, low wavelength absorption peaks of the PC. Remarkably, this strong 655 nm absorption takes advantage of deep-red (650-700 nm) light, a major component of solar light exhibiting good atmosphere penetration, exploited by the natural PC chlorophyll a as well. Compared with ZnTPP, ZnTPTBP displayed a 49% increase in PET-RAFT polymerization rate with good control, marking a significant leap in the area of photo-controlled polymerization.

3D-Printed Piezoelectric Stents for Electricity Generation Driven by Pressure Fluctuation.

Vascular stenting is a common procedure used to treat diseased blood vessels by opening the narrowed vessel lumen and restoring blood flow to ischemic tissues in the heart and other organs. In this work, we report a novel piezoelectric stent featuring a zigzag shape fabricated by fused deposition modeling three-dimensional (3D) printing with a built-in electric field. The piezoelectric composite was made of potassium sodium niobite microparticles and poly(vinylidene fluoride-co-hexafluoropropylene), complementing each other with good piezoelectric performance and mechanical resilience. The in situ poling yielded an appreciable piezoelectricity (d33 ∼ 4.2 pC N-1) of the as-printed stents. In vitro testing revealed that materials are nontoxic to vascular cells and have low thrombotic potential. Under stimulated blood pressure fluctuation, the as-printed piezoelectric stent was able to generate peak-to-peak voltage from 0.07 to 0.15 V corresponding to pressure changes from 20 to 120 Psi, giving a sensitivity of 7.02 × 10-4 V Psi-1. Biocompatible piezoelectric stents bring potential opportunities for the real-time monitoring of blood vessels or enabling therapeutic functions.

Active Dendrite Suppression by Ferroelectric Membrane Separators in Rechargeable Batteries.

Anodic dendrite formation is a critical issue in rechargeable batteries and often leads to poor cycling stability and quick capacity loss. Prevailing strategies for dendrite suppression aim at slowing down the growth rate kinetically but still leaving possibilities for dendrite evolution over time. Herein, we report a complete dendrite elimination strategy using a mesoporous ferroelectric polymer membrane as the battery separator. The dendrite suppression is realized by spontaneously reversing the surface energetics for metal ion reduction at the protrusion front, where a positive piezoelectric polarization is generated and superimposed as the protrusion compresses the separator. This effect is demonstrated first in a Zn electroplating process, and further in Zn-Zn symmetric cells and Zn-NaV3O8·1.5H2O full cells, where the dendritic Zn anode surfaces are completely turned into featureless flat surfaces. Consequently, a substantially longer charging/discharging cycle is achieved. This study provides a promising pathway toward high-performance dendrite-free rechargeable batteries.

Rapid and accurate quality evaluation of Angelicae Sinensis Radix based on near-infrared spectroscopy and Bayesian optimized LSTM network.

The authentic traditional Chinese medicines (TCMs) including Angelicae Sinensis Radix (ASR) are the representative of high-quality herbals in China. However, ASR from authentic region being adulterated or counterfeited is frequently occurring, and there is still a lack of rapid quality evaluation methods for identifying the authentic ASR. In this study, the color features of ASR were firstly characterized. The results showed that the authentic ASR cannot be fully identified by color characteristics. Then near-infrared (NIR) spectroscopy combined with Bayesian optimized long short-term memory (BO-LSTM) was used to evaluate the quality of ASR, and the performance of BO-LSTM with common classification and regression algorithms was compared. The results revealed that following the pretreatment of NIR spectra, the optimal NIR spectra combined with BO-LSTM not only successfully distinguished authentic, non-authentic, and adulterated ASR with 100 % accuracy, but also accurately predicted the adulteration concentration of authentic ASR (R2 > 0.99). Moreover, BO-LSTM demonstrated excellent performance in classification and regression compared with common algorithms (ANN, SVM, PLSR, etc.). Overall, the proposed strategy could quickly and accurately evaluate the quality of ASR, which provided a reference for other TCMs.

Self-Assembling Sulfated Lactobacillus Exopolysaccharide Nanoparticles as Adjuvants for SARS-CoV-2 Subunit Vaccine Elicit Potent Humoral and Cellular Immune Responses.

Coronavirus disease 2019 (COVID-19) has caused a global pandemic since its onset in 2019, and the development of effective vaccines for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to induce potent and long-lasting immunity remains a priority. Herein, we prepared two Lactobacillus exopolysaccharide (EPS) nanoparticle adjuvants (NPs 7-4 and NPs 8-2) that were constructed by using sulfation-modified EPS and quaternization-modified chitosan. These two NPs displayed a spherical morphology with sizes of 39 and 47 nm. Furthermore, the zeta potentials of NPs 7-4 and NPs 8-2 were 50.40 and 44.40 mV, respectively. In vitro assays demonstrated that NPs could effectively adsorb antigenic proteins and exhibited a sustained release effect. Mouse immunization tests showed that the NPs induced the expression of cytokines and chemokines at the injection site and promoted the uptake of antigenic proteins by macrophages. Mechanically, the NPs upregulated the expression of pattern recognition receptors (toll-like receptors and nod-like receptors) and activated the immune response of T cells and the production of neutralizing antibodies. In addition, the NP adjuvants had favorable immune-enhancing effects in cats, which are of great significance for controlling the trans-host transmission and re-endemicity of SARS-CoV-2. Overall, we demonstrated that NP-adjuvanted SARS-CoV-2 receptor binding domain proteins could induce robust specific humoral and cellular immunity.

EndoSRR: a comprehensive multi-stage approach for endoscopic specular reflection removal.

PURPOSE: Specular reflections in endoscopic images not only disturb visual perception but also hamper computer vision algorithm performance. However, the intricate nature and variability of these reflections, coupled with a lack of relevant datasets, pose ongoing challenges for removal. METHODS: We present EndoSRR, a robust method for eliminating specular reflections in endoscopic images. EndoSRR comprises two stages: reflection detection and reflection region inpainting. In the reflection detection stage, we adapt and fine-tune the segment anything model (SAM) using a weakly labeled dataset, achieving an accurate reflection mask. For reflective region inpainting, we employ LaMa, a fast Fourier convolution-based model trained on a 4.5M-image dataset, enabling effective inpainting of arbitrarily shaped reflection regions. Lastly, we introduce an iterative optimization strategy for dual pre-trained models to refine the results of specular reflection removal, named DPMIO. RESULTS: Utilizing the SCARED-2019 dataset, our approach surpasses state-of-the-art methods in both qualitative and quantitative evaluations. Qualitatively, our method excels in accurately detecting reflective regions, yielding more natural and realistic inpainting results. Quantitatively, our method demonstrates superior performance in both segmentation evaluation metrics (IoU, E-measure, etc.) and image inpainting evaluation metrics (PSNR, SSIM, etc.). CONCLUSION: The experimental results underscore the significance of proficient endoscopic specular reflection removal for enhancing visual perception and downstream tasks. The methodology and results presented in this study are poised to catalyze advancements in specular reflection removal, thereby augmenting the accuracy and safety of minimally invasive surgery.

The Development of a Novel Fiber-2 Subunit Vaccine against Fowl Adenovirus Serotype 4 Formulated with Oil Adjuvants.

Hepatitis-hydropericardium syndrome (HHS), caused by fowl adenovirus serotype 4 (FAdV-4), has been widely spread across China, resulting in great financial losses in the poultry industry. Therefore, efficient vaccines against this disease urgently need to be developed. In our study, the fiber-2 and penton base proteins derived from the FAdV-4 JS strain were expressed in a prokaryotic system (E. coli) in a soluble form. Then, the efficacy of the two recombinant proteins formulated with cheap and widely used adjuvants (Marcol™ 52 white oil) were respectively tested, and the minimum immune doses and safety of the above proteins were also determined. It was indicated that the fiber-2 (20 µg/bird, 200 µg/bird) and penton base (200 µg/bird) could provide complete protection against the highly pathogenic FAdV-4 and suppress its replication and shedding. Unfortunately, only the fiber-2 protein could induce complete protection (10/10) at a low dose (10 µg/bird). In addition, we confirmed that the fiber-2 subunit vaccine formulated with oil adjuvants was safe for vaccinated chickens. Conclusively, all of our results suggest that we successfully prepared an efficient and cheap fiber-2 subunit vaccine with few side effects.

Recurrent neural network-based simultaneous cardiac T1, T2, and T1ρ mapping.

The purpose of the current study was to explore the feasibility of training a deep neural network to accelerate the process of generating T1, T2, and T1ρ maps for a recently proposed free-breathing cardiac multiparametric mapping technique, where a recurrent neural network (RNN) was utilized to exploit the temporal correlation among the multicontrast images. The RNN-based model was developed for rapid and accurate T1, T2, and T1ρ estimation. Bloch simulation was performed to simulate a dataset of more than 10 million signals and time correspondences with different noise levels for network training. The proposed RNN-based method was compared with a dictionary-matching method and a conventional mapping method to evaluate the model's effectiveness in phantom and in vivo studies at 3 T, respectively. In phantom studies, the RNN-based method and the dictionary-matching method achieved similar accuracy and precision in T1, T2, and T1ρ estimations. In in vivo studies, the estimated T1, T2, and T1ρ values obtained by the two methods achieved similar accuracy and precision for 10 healthy volunteers (T1: 1228.70 ± 53.80 vs. 1228.34 ± 52.91 ms, p > 0.1; T2: 40.70 ± 2.89 vs. 41.19 ± 2.91 ms, p > 0.1; T1ρ: 45.09 ± 4.47 vs. 45.23 ± 4.65 ms, p > 0.1). The RNN-based method can generate cardiac multiparameter quantitative maps simultaneously in just 2 s, achieving 60-fold acceleration compared with the dictionary-matching method. The RNN-accelerated method offers an almost instantaneous approach for reconstructing accurate T1, T2, and T1ρ maps, being much more efficient than the dictionary-matching method for the free-breathing multiparametric cardiac mapping technique, which may pave the way for inline mapping in clinical applications.

Effects of Continuous Nutritional Intervention on Nutritional Status and Serum Albumin During Maintenance Therapy in Children with Acute Lymphoblastic Leukemia.

Background: Nutritional imbalances can significantly impact clinical efficacy and chemotherapy tolerance in cases of acute lymphoblastic leukemia. Despite the potential significance, there is limited research in this domain, and clinicians have paid limited attention to it. Objective: This study aims to investigate the impact of continuous nutritional intervention on pediatric patients with acute lymphoblastic leukemia. Methods: A comparative analysis was conducted by dividing the children into observation and control groups, examining the effects of intermittent diet intervention and continuous nutrition intervention post-nutritional risk assessment. Results: After the intervention, the observation group exhibited a higher proportion of good nutrition and elevated serum albumin levels compared to the control group (χ2=4.79, 5.49, P = .029, 0.019, t =-2.819, -5.559, P = .01, P < .001). Additionally, the complication rate in the observation group was significantly lower than that in the control group (χ2=5.247, P = .022). Conclusions: Continuous nutrition intervention emerges as a valuable strategy for improving the nutritional status and serum albumin levels in children undergoing maintenance treatment for acute lymphoblastic leukemia. Moreover, it contributes to a noteworthy reduction in the incidence of complications.

Toward the Rational Design of Organic Catalysts for Organocatalysed Atom Transfer Radical Polymerisation.

Thanks to their diversity, organic photocatalysts (PCs) have been widely used in manufacturing polymeric products with well-defined molecular weights, block sequences, and architectures. Still, however, more universal property-performance relationships are needed to enable the rational design of such PCs. That is, a set of unique descriptors ought to be identified to represent key properties of the PCs relevant for polymerisation. Previously, the redox potentials of excited PCs (PC*) were used as a good descriptor for characterising very structurally similar PCs. However, it fails to elucidate PCs with diverse chromophore cores and ligands, among which those used for polymerisation are a good representative. As showcased by model systems of organocatalysed atom transfer radical polymerisation (O-ATRP), new universal descriptors accounting for additional factors, such as the binding and density overlap between the PC* and initiator, are proposed and proved to be successful in elucidating the experimental performances of PCs in polymerisation. While O-ATRP is exemplified here, the approach adopted is general for studying other photocatalytic systems.

Unified construction of relativistic Hamiltonians.

It is shown that the four-component (4C), quasi-four-component (Q4C), and exact two-component (X2C) relativistic Hartree-Fock equations can be implemented in a unified manner by making use of the atomic nature of the small components of molecular 4-spinors. A model density matrix approximation can first be invoked for the small-component charge/current density functions, which gives rise to a static, pre-molecular mean field to be combined with the one-electron term. As a result, only the nonrelativistic-like two-electron term of the 4C/Q4C/X2C Fock matrix needs to be updated during the iterations. A "one-center small-component" approximation can then be invoked in the evaluation of relativistic integrals, that is, all atom-centered small-component basis functions are regarded as extremely localized near the position of the atom to which they belong such that they have vanishing overlaps with all small- or large-component functions centered at other nuclei. Under these approximations, the 4C, Q4C, and X2C mean-field and many-electron Hamiltonians share precisely the same structure and accuracy. Beyond these is the effective quantum electrodynamics Hamiltonian that can be constructed in the same way. Such approximations lead to errors that are orders of magnitude smaller than other sources of errors (e.g., truncation errors in the one- and many-particle bases as well as uncertainties of experimental measurements) and are, hence, safe to use for whatever purposes. The quaternion forms of the 4C, Q4C, and X2C equations are also presented in the most general way, based on which the corresponding Kramers-restricted open-shell variants are formulated for "high-spin" open-shell systems.

Some Recent Advances in Density-Based Reactivity Theory.

Establishing a chemical reactivity theory in density functional theory (DFT) language has been our intense research interest in the past two decades, exemplified by the determination of steric effect and stereoselectivity, evaluation of electrophilicity and nucleophilicity, identification of strong and weak interactions, and formulation of cooperativity, frustration, and principle of chirality hierarchy. In this Featured Article, we first overview the four density-based frameworks in DFT to appreciate chemical understanding, including conceptual DFT, use of density associated quantities, information-theoretic approach, and orbital-free DFT, and then present a few recent advances of these frameworks as well as new applications from our studies. To that end, we will introduce the relationship among these frameworks, determining the entire spectrum of interactions with Pauli energy derivatives, performing topological analyses with information-theoretic quantities, and extending the density-based frameworks to excited states. Applications to examine physiochemical properties in external electric fields and to evaluate polarizability for proteins and crystals are discussed. A few possible directions for future development are followed, with the special emphasis on its merger with machine learning.

HiOmics: A cloud-based one-stop platform for the comprehensive analysis of large-scale omics data.

Analyzing the vast amount of omics data generated comprehensively by high-throughput sequencing technology is of utmost importance for scientists. In this context, we propose HiOmics, a cloud-based platform equipped with nearly 300 plugins designed for the comprehensive analysis and visualization of omics data. HiOmics utilizes the Element Plus framework to craft a user-friendly interface and harnesses Docker container technology to ensure the reliability and reproducibility of data analysis results. Furthermore, HiOmics employs the Workflow Description Language and Cromwell engine to construct workflows, ensuring the portability of data analysis and simplifying the examination of intricate data. Additionally, HiOmics has developed DataCheck, a tool based on Golang, which verifies and converts data formats. Finally, by leveraging the object storage technology and batch computing capabilities of public cloud platforms, HiOmics enables the storage and processing of large-scale data while maintaining resource independence among users.