Dynamically Regulating Homologous Recombination Enables Precise Genome Editing in Ogataea polymorpha.

Methylotrophic yeast Ogataea polymorpha has become a promising cell factory due to its efficient utilization of methanol to produce high value-added chemicals. However, the low homologous recombination (HR) efficiency in O. polymorpha greatly hinders extensive metabolic engineering for industrial applications. Overexpression of HR-related genes successfully improved HR efficiency, which however brought cellular stress and reduced chemical production due to constitutive expression of the HR-related gene. Here, we engineered an HR repair pathway using the dynamically regulated gene ScRAD51 under the control of the l-rhamnose-induced promoter PLRA3 based on the previously constructed CRISPR-Cas9 system in O. polymorpha. Under the optimal inducible conditions, the appropriate expression level of ScRAD51 achieved up to 60% of HR rates without any detectable influence on cell growth in methanol, which was 10-fold higher than that of the wild-type strain. While adopting as the chassis strain for bioproductions, the dynamically regulated recombination system had 50% higher titers of fatty alcohols than that static regulation system. Therefore, this study provided a feasible platform in O. polymorpha for convenient genetic manipulation without perturbing cellular fitness.

Machine learning approach for the prediction of macrosomia.

Fetal macrosomia is associated with maternal and newborn complications due to incorrect fetal weight estimation or inappropriate choice of delivery models. The early screening and evaluation of macrosomia in the third trimester can improve delivery outcomes and reduce complications. However, traditional clinical and ultrasound examinations face difficulties in obtaining accurate fetal measurements during the third trimester of pregnancy. This study aims to develop a comprehensive predictive model for detecting macrosomia using machine learning (ML) algorithms. The accuracy of macrosomia prediction using logistic regression, k-nearest neighbors, support vector machine, random forest (RF), XGBoost, and LightGBM algorithms was explored. Each approach was trained and validated using data from 3244 pregnant women at a hospital in southern China. The information gain method was employed to identify deterministic features associated with the occurrence of macrosomia. The performance of six ML algorithms based on the recall and area under the curve evaluation metrics were compared. To develop an efficient prediction model, two sets of experiments based on ultrasound examination records within 1-7 days and 8-14 days prior to delivery were conducted. The ensemble model, comprising the RF, XGBoost, and LightGBM algorithms, showed encouraging results. For each experimental group, the proposed ensemble model outperformed other ML approaches and the traditional Hadlock formula. The experimental results indicate that, with the most risk-relevant features, the ML algorithms presented in this study can predict macrosomia and assist obstetricians in selecting more appropriate delivery models.

[Metabolic engineering for the efficient co-utilization of glucose and xylose].

Microbial production of chemicals from renewable biomass has emerged as a crucial route for sustainable bio-manufacturing. Lignocellulose with a renewable property and wide sources is supposed to be a promising feedstock for the second-generation biorefinery. The efficient co-utilization of mixed sugars from lignocellulosic hydrolysates represents one of the key challenges in reducing the production cost. However, most microorganisms prefer glucose over xylose due to carbon catabolite repression, which constrains the efficiency of lignocellulosic conversion. Therefore, developing the microbial platforms capable of simultaneously utilizing glucose and xylose is paramount for economically viable industrial-scale production. This article reviews the key strategies and studies of metabolic engineering for promoting efficient co-utilization of glucose and xylose by microorganisms. The representative strategies include relieving glucose repression, enhancing xylose transport, constructing xylose metabolic pathways, and directed evolution.

Engineering high production of fatty alcohols from methanol by constructing coordinated dual biosynthetic pathways.

Microbial cell factories provide an efficient approach for the green manufacturing of chemicals. However, the excessive use of sugars increases the potential risk of food crisis. Methanol, an abundant feedstock, holds promise in facilitating low-carbon production processes. However, the current methanol bioconversion is hindered by limited regulatory strategies and relatively low conversion efficiency. Here, a yeast biocatalyst was extensively engineered for efficient biosynthesis of fatty alcohols through reinforcement of precursor supply and methanol assimilation in Pichia pastoris. Furthermore, the dual cytoplasmic and peroxisomal biosynthetic pathways were constructed by mating and exhibited robust production of 5.6 g/L fatty alcohols by using methanol as the sole carbon source. This study provides a heterozygous diploid P. pastoris strain with dual cytoplasmic and peroxisomal biosynthetic pathways, which achieved the highest fatty alcohol production from one-carbon feedstocks to date.

Engineering yeast for high-level production of ß-farnesene from sole methanol.

Methanol, a rich one-carbon feedstock, can be massively produced from CO2 by the liquid sunshine route, which is helpful to realize carbon neutrality. ß-Farnesene is widely used in the production of polymers, surfactants, lubricants, and also serves as a suitable substitute for jet fuel. Constructing an efficient cell factory is a feasible approach for ß-farnesene production through methanol biotransformation. Here, we extensively engineered the methylotrophic yeast Ogataea polymorpha for the efficient bio-production of ß-farnesene using methanol as the sole carbon source. Our study demonstrated that sufficient supply of precursor acetyl-CoA and cofactor NADPH in an excellent yeast chassis had a 1.3-fold higher ß-farnesene production than that of wild-type background strain. Further optimization of the mevalonate pathway and enhancement of acetyl-CoA supply led to a 7-fold increase in ß-farnesene accumulation, achieving the highest reported sesquiterpenoids production (14.7 g/L with a yield of 46 mg/g methanol) from one-carbon feedstock under fed-batch fermentation in bioreactor. This study demonstrates the great potential of engineering O. polymorpha for high-level terpenoid production from methanol.

Engineering a versatile yeast platform for sesquiterpene production from glucose or methanol.

Natural sesquiterpene are valuable compounds with diverse applications in industries, such as cosmetics and energy. Microbial synthesis offers a promising way for sesquiterpene production. Methanol, can be synthesized from CO2 and solar energy, serves as a sustainable carbon source. However, it is still a challenge to utilize methanol for the synthesis of value-added compounds. Pichia pastoris (syn. Komagataella phaffii), known for its efficient utilization of glucose and methanol, has been widely used in protein synthesis. With advancements in technology, P. pastoris is gradually engineered for chemicals production. Here, we successfully achieved the synthesis of α-bisabolene in P. pastoris with dual carbon sources by expressing the α-bisabolene synthase gene under constitutive promoters. We systematically analyzed the effects of different steps in the mevalonate (MVA) pathway when methanol or glucose was used as the carbon source. Our finding revealed that the sesquiterpene synthase module significantly increased the production when methanol was used. While the metabolic modules MK and PMK greatly improved carbon source utilization, cell growth, and titer when glucose was used. Additionally, we demonstrated the synthesis of ß-farnesene from dual carbon source by replacing the α-bisabolene synthase with a ß-farnesene synthase. This study establishes a platform strain that is capable to synthesize sesquiterpene from different carbon sources in P. pastoris. Moreover, it paves the way for the development of P. pastoris as a high-efficiency microbial cell factory for producing various chemicals, and lays foundation for large-scale synthesis of high value-added chemicals efficiently from methanol in P. pastoris.

Altered Brain Glymphatic Function at Diffusion-Tensor MRI in Pre-cirrhotic Metabolic Dysfunction-Associated Fatty Liver Disease.

RATIONALE AND OBJECTIVES: To evaluate glymphatic function changes and their relationships with clinical features in patients with metabolic dysfunction-associated fatty liver disease (MAFLD), thereby facilitating early intervention before this disease progresses to cirrhosis. MATERIALS AND METHODS: A cross-sectional cohort of 46 pre-cirrhotic MAFLD patients and 30 age-, sex-, and education-matched controls was enrolled, with diffusion-tensor imaging (DTI) data, laboratory and neurocognitive scores collected. The DTI analysis along the perivascular space (DTI-ALPS) index was computed for qualifying glymphatic function. Generalized linear model and partial correlation analyses were applied to evaluate relationships between the ALPS index and clinical variables. RESULTS: MAFLD group exhibited a decreased ALPS index and increased diffusivity along the y-axis in the projection fiber compared to the controls. The altered ALPS index was associated with clock drawing test (CDT) score (3.931 [0.914, 6.947], P = 0.011) and was correlated with diastolic pressure level (r = -0.315, P = 0.033) in MAFLD group. The relationships of ALPS index with CDT score (6.263 [2.069, 10.458], P = 0.003) and diastolic pressure level (r = -0.518, P = 0.014) remained in the MAFLD with metabolic syndrome (MetS) group. Furthermore, the ALPS index was even associated with Auditory Verbal Learning Test-Immediate recall score (-23.853 [-45.417, -2.289], P = 0.030) in MAFLD with MetS group. CONCLUSION: MAFLD patients may have a glymphatic dysfunction prior to cirrhosis, and this alteration may be related to cognition and diastolic pressure. Glymphatic dysfunction has a more severe impact on cognition when MAFLD patient is accompanied by MetS.

Engineering Yeast Peroxisomes for α-Bisabolene Production from Sole Methanol with the Aid of Proteomic Analysis.

Microbial metabolic engineering provides a feasible approach to sustainably produce advanced biofuels and biochemicals from renewable feedstocks. Methanol is an ideal feedstock since it can be massively produced from CO2 through green energy, such as solar energy. However, engineering microbes to transform methanol and overproduce chemicals is challenging. Notably, the microbial production of isoprenoids from methanol is still rarely reported. Here, we extensively engineered Pichia pastoris (syn. Komagataella phaffii) for the overproduction of sesquiterpene α-bisabolene from sole methanol by optimizing the mevalonate pathway and peroxisomal compartmentalization. Furthermore, through label-free quantification (LFQ) proteomic analysis of the engineered strains, we identified the key bottlenecks in the peroxisomal targeting pathway, and overexpressing the limiting enzyme EfmvaE significantly improved α-bisabolene production to 212 mg/L with the peroxisomal pathway. The engineered strain LH122 with the optimized peroxisomal pathway produced 1.1 g/L α-bisabolene under fed-batch fermentation in shake flasks, achieving a 69% increase over that of the cytosolic pathway. This study provides a viable approach for overproducing isoprenoid from sole methanol in engineered yeast cell factories and shows that proteomic analysis can help optimize the organelle compartmentalized pathways to enhance chemical production.

Shear wave trajectory detection in ultra-fast M-mode images for liver fibrosis assessment: A deep learning-based line detection approach.

Stiffness measurement using shear wave propagation velocity has been the most common non-invasive method for liver fibrosis assessment. The velocity is captured through a trace recorded by transient ultrasonographic elastography, with the slope indicating the velocity of the wave. However, due to various factors such as noise and shear wave attenuation, detecting shear wave trajectory on wave propagation maps is a challenging task. In this work, we made the first attempt to use deep learning methods for shear wave trajectory detection on wave propagation maps. Specifically, we adopted five deep learning models in this task and evaluated them by using a well-acknowledged metric based on EA-Angular-Score (EAA) and task-specific metric based on Young s-Score (Ys) in the line-detection field. Furthermore, we proposed an end-to-end framework based on a Transformer and Hough transform, named Transformer-enhanced Hough Transform (TEHT). It took a wave propagation map as input image and directly output the slope of the shear wave trajectory. The framework extracts multi-scale local features from wave propagation maps, employs a deformable attention mechanism for feature fusion, identifies the target line using the Hough transform's voting mechanism, and calculates the contribution of each scale through channel attention. Wave propagation maps from 68 patients were utilized in this study, with manual annotation performed by a rater who was trained as a radiologist, serving as the reference value. The evaluation revealed that the SLNet model exhibited F-measure of EA and Ys values as 40.33 % and 40.72 %, respectively, while the TEHT model showed F-measure of EA and Ys values as 80.96 % and 98.00 %, respectively. TEHT yielded significantly better performance than other deep learning models. Moreover, TEHT demonstrated strong concordance with the gold standard, yielding R2 values of 0.967 and 0.968 for velocity and liver stiffness, respectively. The present study therefore suggests the application of the TEHT model for assessing liver fibrosis owing to its superiority among the five deep learning models.

Abnormalities in spontaneous brain activity and functional connectivity are associated with cognitive impairments in children with type 1 diabetes mellitus.

BACKGROUND: It remains unclear whether alterations in brain function occur in the early stage of pediatric type 1 diabetes mellitus(T1DM). We aimed to examine changes in spontaneous brain activity and functional connectivity (FC) in children with T1DM using resting-state functional magnetic resonance imaging (rs-fMRI), and to pinpoint potential links between neural changes and cognitive performance. METHODS: In this study, 22 T1DM children and 21 age-, sex-matched healthy controls underwent rs-fMRI. The amplitude of low frequency fluctuations (ALFF) and seed-based FC analysis were performed to examine changes in intrinsic brain activity and functional networks in T1DM children. Partial correlation analyses were utilized to explore the correlations between ALFF values and clinical parameters. RESULTS: The ALFF values were significantly lower in the lingual gyrus (LG) and higher in the left medial superior frontal gyrus (MSFG) in T1DM children compared to controls. Subsequent FC analysis indicated that the LG had decreased FC with bilateral inferior occipital gyrus, and the left MSFG had decreased FC with right precentral gyrus, right inferior parietal gyrus and right postcentral gyrus in children with T1DM. The ALFF values of LG were positively correlated with full-scale intelligence quotient and age at disease onset in T1DM children, while the ALFF values of left MSFG were positively correlated with working memory scores. CONCLUSION: Our findings revealed abnormal spontaneous activity and FC in brain regions related to visual, memory, default mode network, and sensorimotor network in the early stage of T1DM children, which may aid in further understanding the mechanisms underlying T1DM-associated cognitive dysfunction.

Freehand 3D Ultrasound Imaging Based on Probe-mounted Vision and IMU System.

OBJECTIVES: Freehand three-dimensional (3D) ultrasound (US) is of great significance for clinical diagnosis and treatment, it is often achieved with the aid of external devices (optical and/or electromagnetic, etc.) that monitor the location and orientation of the US probe. However, this external monitoring is often impacted by imaging environment such as optical occlusions and/or electromagnetic (EM) interference. METHODS: To address the above issues, we integrated a binocular camera and an inertial measurement unit (IMU) on a US probe. Subsequently, we built a tight coupling model utilizing the unscented Kalman algorithm based on Lie groups (UKF-LG), combining vision and inertial information to infer the probe's movement, through which the position and orientation of the US image frame are calculated. Finally, the volume data was reconstructed with the voxel-based hole-filling method. RESULTS: The experiments including calibration experiments, tracking performance evaluation, phantom scans, and real scenarios scans have been conducted. The results show that the proposed system achieved the accumulated frame position error of 3.78 mm and the orientation error of 0.36° and reconstructed 3D US images with high quality in both phantom and real scenarios. CONCLUSIONS: The proposed method has been demonstrated to enhance the robustness and effectiveness of freehand 3D US. Follow-up research will focus on improving the accuracy and stability of multi-sensor fusion to make the system more practical in clinical environments.

Ogataea polymorpha as a next-generation chassis for industrial biotechnology.

Ogataea (Hansenula) polymorpha is a nonconventional yeast with some unique characteristics, including fast growth, thermostability, and broad substrate spectrum. Other than common applications for protein production, O. polymorpha is attracting interest for chemical and protein production from methanol; a promising feedstock for the next-generation biomanufacturing due to its abundant sources and excellent characteristics. Benefiting from the development of synthetic biology, it has been engineered to produce value-added chemicals by extensively rewiring cellular metabolism. This Review discusses recently developed synthetic biology tools of O. polymorpha. The advances of chemicals production and systems biology were reviewed comprehensively. Finally, we look ahead to the developments of biomanufacturing in O. polymorpha to make an overall understanding of this chassis for academia and industry.

Synthetic biology for Taxol biosynthesis and sustainable production.

Incomplete understanding of the biosynthetic pathway of the anticancer compound Taxol hinders its production by metabolic engineering. Recent reports by Jiang et al. and other groups now describe the missing steps in Taxol biosynthesis, notably including oxetane ring formation. These findings will promote the sustainable production of Taxol through synthetic biology.

Automated analysis of pectoralis major thickness in pec-fly exercises: evolving from manual measurement to deep learning techniques.

This study addresses a limitation of prior research on pectoralis major (PMaj) thickness changes during the pectoralis fly exercise using a wearable ultrasound imaging setup. Although previous studies used manual measurement and subjective evaluation, it is important to acknowledge the subsequent limitations of automating widespread applications. We then employed a deep learning model for image segmentation and automated measurement to solve the problem and study the additional quantitative supplementary information that could be provided. Our results revealed increased PMaj thickness changes in the coronal plane within the probe detection region when real-time ultrasound imaging (RUSI) visual biofeedback was incorporated, regardless of load intensity (50% or 80% of one-repetition maximum). Additionally, participants showed uniform thickness changes in the PMaj in response to enhanced RUSI biofeedback. Notably, the differences in PMaj thickness changes between load intensities were reduced by RUSI biofeedback, suggesting altered muscle activation strategies. We identified the optimal measurement location for the maximal PMaj thickness close to the rib end and emphasized the lightweight applicability of our model for fitness training and muscle assessment. Further studies can refine load intensities, investigate diverse parameters, and employ different network models to enhance accuracy. This study contributes to our understanding of the effects of muscle physiology and exercise training.

Promoter engineering enables precise metabolic regulation towards efficient ß-elemene production in Ogataea polymorpha.

Precisely controlling gene expression is beneficial for optimizing biosynthetic pathways for improving the production. However, promoters in nonconventional yeasts such as Ogataea polymorpha are always limited, which results in incompatible gene modulation. Here, we expanded the promoter library in O. polymorpha based on transcriptional data, among which 13 constitutive promoters had the strengths ranging from 0-55% of PGAP, the commonly used strong constitutive promoter, and 2 were growth phase-dependent promoters. Subsequently, 2 hybrid growth phase-dependent promoters were constructed and characterized, which had 2-fold higher activities. Finally, promoter engineering was applied to precisely regulate cellular metabolism for efficient production of ß-elemene. The glyceraldehyde-3-phosphate dehydrogenase gene GAP was downregulated to drive more flux into pentose phosphate pathway (PPP) and then to enhance the supply of acetyl-CoA by using phosphoketolase-phosphotransacetylase (PK-PTA) pathway. Coupled with the phase-dependent expression of synthase module (ERG20∼LsLTC2 fusion), the highest titer of 5.24 g/L with a yield of 0.037 g/(g glucose) was achieved in strain YY150U under fed-batch fermentation in shake flasks. This work characterized and engineered a series of promoters, that can be used to fine-tune genes for constructing efficient yeast cell factories.

Palm-Sized Wireless Transient Elastography System with Real-Time B-Mode Ultrasound Imaging Guidance: Toward Point-of-Care Liver Fibrosis Assessment.

Transient elastography (TE), recommended by the WHO, is an established method for characterizing liver fibrosis via liver stiffness measurement (LSM). However, technical barriers remain towards point-of-care application, as conventional TE requires wired connections, possesses a bulky size, and lacks adequate imaging guidance for precise liver localization. In this work, we report the design, phantom validation, and clinical evaluation of a palm-sized TE system that enables simultaneous B-mode imaging and LSM. The performance of this system was validated experimentally using tissue-equivalent reference phantoms (1.45-75 kPa). Comparative studies against other liver elastography techniques, including conventional TE and two-dimensional shear wave elastography (2D-SWE), were performed to evaluate its reliability and validity in adults with various chronic liver diseases. Intra- and inter-operator reliability of LSM were established by an elastography expert and a novice. A good agreement was observed between the Young's modulus reported by the phantom manufacturer and this system (bias: 1.1-8.6%). Among 121 patients, liver stiffness measured by this system and conventional TE were highly correlated (r = 0.975) and strongly agreed with each other (mean difference: -0.77 kPa). Inter-correlation of this system with conventional TE and 2D-SWE was observed. Excellent-to-good operator reliability was demonstrated in 60 patients (ICCs: 0.824-0.913). We demonstrated the feasibility of employing a fully integrated phased array probe for reliable and valid LSM, guided by real-time B-mode imaging of liver anatomy. This system represents the first technical advancement toward point-of-care liver fibrosis assessment. Its small footprint, along with B-mode guidance capability, improves examination efficiency and scales up screening for liver fibrosis.

Long-term survival in a patient with multiple metastatic gastric cancer treated with PTX plus emvolimab and disitamab vedotin: case report and treatment experience: A case report.

RATIONALE: Most Chinese patients with locally advanced gastric cancer at diagnosis have an overall 5-year survival rate of <50%. Surgical resection alone is not suitable for patients with locally advanced gastric cancer. Currently, comprehensive treatment is the focus of locally advanced gastric cancer. PATIENTS CONCERNS: The patient, a 56-year-old female, was admitted to the hospital because of "4 + months of double hydronephrosis found during a physical examination." Who was admitted for computer tomography and gastroscopy examinations, and take pathological tissue specimens during endoscopic examination. DIAGNOSES: Computed tomography assessment indicated ulcerative gastric cancer with an abdominal implant, bladder, and bone metastases. An endoscopic examination revealed that the ulcer of the gastric angle was huge, and through relevant auxiliary examinations, the diagnosis of this disease is gastric cancer complicated with multiple metastases to bladder, rectum, lumbar spine, and peritoneum. Clinically diagnosed as cT4bN3M1. INTERVENTIONS: The patient is currently undergoing first, second, and third line neoadjuvant therapy, combined with immunotherapy, targeted therapy, neoadjuvant intraperitoneal systemic chemotherapy, nutritional support, and other treatment plans. OUTCOMES: After 15 cycles of treatment, the progression-free survival had reached 15 months. The patient had an NRS2002 score of 1, an ECOG score of I, a quality of life score of 55, albumin of 35.27 g/L, and a decrease in abdominal and pelvic fluid accumulation and exudation compared to before. LESSONS: We demonstrated high survival of almost 3 years in a patient with gastric cancer that was complicated by bone, peritoneal, rectal, and bladder metastases. The combination of immunotherapy, targeted therapy, and neoadjuvant intraperitoneal systemic chemotherapy, along with the maintenance of nutritional status and CTCs could be a valuable modality for the subsequent treatment and observation of similar patients.

De novo biosynthesis of the hops bioactive flavonoid xanthohumol in yeast.

The flavonoid xanthohumol is an important flavor substance in the brewing industry that has a wide variety of bioactivities. However, its unstable structure results in its low content in beer. Microbial biosynthesis is considered a sustainable and economically viable alternative. Here, we harness the yeast Saccharomyces cerevisiae for the de novo biosynthesis of xanthohumol from glucose by balancing the three parallel biosynthetic pathways, prenyltransferase engineering, enhancing precursor supply, constructing enzyme fusion, and peroxisomal engineering. These strategies improve the production of the key xanthohumol precursor demethylxanthohumol (DMX) by 83-fold and achieve the de novo biosynthesis of xanthohumol in yeast. We also reveal that prenylation is the key limiting step in DMX biosynthesis and develop tailored metabolic regulation strategies to enhance the DMAPP availability and prenylation efficiency. Our work provides feasible approaches for systematically engineering yeast cell factories for the de novo biosynthesis of complex natural products.

Dynamic tear meniscus parameters in complete blinking: insights into dry eye assessment.

AIM: To investigate the relationship between dynamic tear meniscus parameters and dry eye using an automated tear meniscus segmentation method. METHODS: The analysis of tear meniscus videos captured within 5s after a complete blink includes data from 38 participates. By processing video data, several key parameters including the average height of the tear meniscus at different lengths, the curvature of the tear meniscus's upper boundary, and the total area of the tear meniscus in each frame were calculated. The effective values of these dynamic parameters were then linearly fitted to explore the relationship between their changing trends and dry eye disease. RESULTS: In 94.74% of the samples, the average height of central tear meniscus increased over time. Moreover, 97.37% of the samples exhibited an increase in the overall tear meniscus height (TMH) and area from the nasal to temporal side. Notably, the central TMH increased at a faster rate compared to the nasal side with the temporal side showing the slowest ascent. Statistical analysis indicates that the upper boundary curvature of the whole tear meniscus as well as the tear meniscus of the nasal side (2, 3, and 4 mm) aid in identifying the presence of dry eye and assessing its severity. CONCLUSION: This study contributes to the understanding of tear meniscus dynamics as potential markers for dry eye, utilizing an automated and non-invasive approach that has implications for clinical assessment.

Ratoon Rice System of Production: A Rapid Growth Pattern of Multiple Cropping in China: A Review.

In this review, the significance of ratoon rice was introduced, and the research status and development trends of ratoon rice were also summarized. It is pointed out that mechanically harvested ratoon rice is the developing direction of future ratoon rice. On this basis, we analyzed the relationship between the yield of ratoon rice and many factors, such as variety characteristics, sowing date, water control, fertilizer, and many others. It is important to construct a comprehensive and practical evaluation system for rice regeneration that can provide a basis for high-yield cultivation of machine-harvested ratoon rice. At the same time, it is suggested that combining high-yield cultivation with the green ecological efficiency of rice can achieve better production and improve the quality of rice. Finally, some problems with ratoon rice development were put forward. An in-depth study on the rhizosphere biology and regulation techniques of ratoon rice and the effective ecological compensation mechanism increased the capacity and quality of ratoon rice. Further, the functioning of such research can enhance the planting area for ratoon rice and improve food security.