Clinical-radiomics nomogram for the risk prediction of esophageal fistula in patients with esophageal squamous cell carcinoma treated with intensity-modulated radiation therapy or volumetric-modulated arc therapy.

Background: Esophageal fistula (EF) is a serious adverse event as a result of radiotherapy in patients with esophageal cancer (EC). We aimed to identify the predictive factors and establish a prediction model of EF in patients with esophageal squamous cell carcinoma (ESCC) who underwent intensity-modulated radiation therapy (IMRT) or volumetric-modulated arc therapy (VMAT). Methods: Patients with ESCC treated with IMRT or VMAT from January 2013 to December 2020 at Xijing Hospital were retrospectively analyzed. Ultimately, 43 patients with EF and 129 patients without EF were included in the analysis and propensity-score matched in a 1:3 ratio. The clinical characteristics and radiomics features were extracted. Univariate and multivariate stepwise logistic regression analyses were used to determine the risk factors associated with EF. Results: The median follow-up time was 24.0 months (range, 1.3-104.9 months), and the median overall survival (OS) was 13.1 months in patients with EF. A total of 1,158 radiomics features were extracted, and eight radiomics features were selected for inclusion into a model for predicting EF, with an area under the receiver operating characteristic curve (AUC) value of 0.794. Multivariate analysis showed that tumor length, tumor volume, T stage, lymphocyte rate (LR), and grade IV esophagus stenosis were related to EF, and the AUC value of clinical model for predicting EF was 0.849. The clinical-radiomics model had the best performance in predicting EF with an AUC value of 0.896. Conclusions: The clinical-radiomics nomogram can predict the risk of EF in ESCC patients and is helpful for the individualized treatment of EC.

Cancer Cell-Mimicking Prussian Blue Nanoplatform for Synergistic Mild Photothermal/Chemotherapy via Heat Shock Protein Inhibition.

Combined mild-temperature photothermal/chemotherapy has emerged as a highly promising modality for tumor therapy. However, its therapeutic efficacy is drastically compromised by the heat-induced overexpression of heat shock proteins (HSPs) by the cells, which resist heat stress and apoptosis. The purpose of this study was to downregulate HSPs and enhance the mild-temperature photothermal/chemotherapy effect. In detail, the colon cancer cell membrane (CT26M)-camouflaged HSP90 inhibitor ganetespib and the chemotherapeutic agent doxorubicin (DOX)-coloaded hollow mesoporous Prussian blue (HMPB) nanoplatform (named PGDM) were designed for synergistic mild photothermal/chemotherapy via HSP inhibition. In addition to being a photothermal agent with a high efficiency of photothermal conversion (24.13%), HMPB offers a hollow hole that can be filled with drugs. Concurrently, the cancer cell membrane camouflaging enhances tumor accumulation through a homologous targeting mechanism and gives the nanoplatform the potential to evade the immune system. When exposed to NIR radiation, HMPB's photothermal action (44 °C) not only causes tumor cells to undergo apoptosis but also causes ganetespib to be released on demand. This inhibits the formation of HSP90, which enhances the mild photothermal/chemotherapy effect. The results confirmed that the combined treatment regimen of mild photothermal therapy (PTT) and chemotherapy showed a better therapeutic efficacy than the individual treatment methods. Therefore, this multimodal nanoparticle can advance the development of drugs for the treatment of malignancies, such as colon cancer, and has prospects for clinical application.

Spatiotemporal drivers of urban water pollution: Assessment of 102 cities across the Yangtze River Basin.

Effective management of large basins necessitates pinpointing the spatial and temporal drivers of primary index exceedances and urban risk factors, offering crucial insights for basin administrators. Yet, comprehensive examinations of multiple pollutants within the Yangtze River Basin remain scarce. Here we introduce a pollution inventory for urban clusters surrounding the Yangtze River Basin, analyzing water quality data from 102 cities during 2018-2019. We assessed the exceedance rates for six pivotal indicators: dissolved oxygen (DO), ammonia nitrogen (NH3-N), chemical oxygen demand (COD), biochemical oxygen demand (BOD), total phosphorus (TP), and the permanganate index (CODMn) for each city. Employing random forest regression and SHapley Additive exPlanations (SHAP) analyses, we identified the spatiotemporal factors influencing these key indicators. Our results highlight agricultural activities as the primary contributors to the exceedance of all six indicators, thus pinpointing them as the leading pollution source in the basin. Additionally, forest coverage, livestock farming, chemical and pharmaceutical sectors, along with meteorological elements like precipitation and temperature, significantly impacted various indicators' exceedances. Furthermore, we delineate five core urban risk components through principal component analysis, which are (1) anthropogenic and industrial activities, (2) agricultural practices and forest extent, (3) climatic variables, (4) livestock rearing, and (5) principal polluting sectors. The cities were subsequently evaluated and categorized based on these risk components, incorporating policy interventions and administrative performance within each region. The comprehensive analysis advocates for a customized strategy in addressing the discerned risk factors, especially for cities presenting elevated risk levels.

Dietary fiber and polyphenols from whole grains: effects on the gut and health improvements.

Cereals are the main source of energy in the human diet. Compared to refined grains, whole grains retain more beneficial components, including dietary fiber, polyphenols, proteins, vitamins, and minerals. Dietary fiber and bound polyphenols (biounavailable) in cereals are important active substances that can be metabolized by the gut microorganisms and affect the intestinal environment. There is a close relationship between the gut microbiota structures and various disease phenotypes, although the consistency of this link is affected by many factors, and the specific mechanisms are still unclear. Remodeling unfavorable microbiota is widely recognized as an important way to target the gut and improve diseases. This paper mainly reviews the interaction between the gut microbiota and cereal-derived dietary fiber and polyphenols, and also summarizes the changes to the gut microbiota and possible molecular mechanisms of related glycolipid metabolism. The exploration of single active ingredients in cereals and their synergistic health mechanisms will contribute to a better understanding of the health benefits of whole grains. It will further help promote healthier whole grain foods by cultivating new varieties with more potential and optimizing processing methods.

Chiral Jahn-Teller Distortion in Quasi-Planar Boron Clusters.

In this work, we have observed that some chiral boron clusters (B16-, B20-, B24-, and B28-) can simultaneously have helical molecular orbitals and helical spin densities; these seem to be the first compounds discovered to have this intriguing property. We show that chiral Jahn-Teller distortion of quasi-planar boron clusters drives the formation of the helical molecular spin densities in these clusters and show that elongation/enhancement in helical molecular orbitals can be achieved by simply adding more building blocks via a linker. Aromaticity of these boron clusters is discussed. Chiral boron clusters may find potential applications in spintronics, such as molecular magnets.

Sequential respiratory support in septic patients undergoing continuous renal replacement therapy: A study based on MIMIC-III database.

Objective: Oxygen and hemodynamic management are important for providing a sufficient adequate oxygen-containing blood to the organs for septic patients. In present study, we aimed to explore the application of sequential respiratory support (SRS) and the association of SRS with the outcome of septic patients who needed continuous renal replacement therapy (CRRT). Methods: We extracted the medical information of septic patients who received CRRT within 24 h of intensive care unit (ICU) admission from the MIMIC-III v1.4. SRS was defined as receiving firstly oxygen therapy followed by mechanical ventilation (MV) within 24 h of admission to ICU. The propensity score matching (PSM) was performed to compare the differences in clinical characteristics and outcomes of patients with or without SRS. Finally, we developed logistic regression models to analyze the effects of SRS on hospital mortality. Results: A total of 181 patients entered in this study, and there were 80 patients undergoing MV including SRS group (n = 61) and non-SRS group (n = 19). In the multivariate logistic regression, the value of SRS was associated with the lower risk of hospital mortality adjusted by minimum systolic BP (SBP), maximum lactate, vasopressor use, and sequential organ failure assessment (SOFA) score or Logistic Organ Dysfunction System (LODS) scores within the first 24 h of ICU stay. After PSM adjusted by SBP, maximum lactate, vasopressor use, SOFA, and LODS, there were 31 patients in SRS group with a and 18 cases in non-SRS group, displaying a significantly lower hospital mortality in SRS group than that in patients without SRS (19.4 % vs. 83.3 %, P < 0.001). In addition, age, qSOFA, necessitating the administration of vasopressor, and duration of vasopressor were significantly correlated with the hospital mortality in septic patients undergoing CRRT and SRS. Conclusions: Receiving SRS within the first 24 h upon admission to the ICU was independently associated with the hospital mortality in patient with sepsis undergoing CRRT, and patients who were directly received MV had a high risk of death.

[Research advances in exosomes involved in the occurrence, development and clinical diagnosis and treatment of sepsis].

Sepsis is a life-threatening organ dysfunction caused by a dysregulated host immune response to infection. The development of sepsis is accompanied by the secretion of exosomes by a variety of cells, including non-coding RNA, metabolic small molecules and proteins, which play an important role in immune inflammatory response, oxidative stress, and coagulation dysfunction. The rapid development of new detection technologies has promoted the application of exosomes in the early warning, severity stratification, treatment effect and prognosis evaluation of sepsis. This article reviews the new detection technology of exosomes, the involvement of exosomes in the pathological progress of sepsis, and the latest progress in the early diagnosis, disease assessment and treatment of sepsis, in order to provide new ideas for the diagnosis and treatment of sepsis.

Macrophage migration inhibitor factor (MIF): Potential role in cognitive impairment disorders.

Macrophage migration inhibitory factor (MIF) is a cytokine in the immune system, participated in both innate and adaptive immune responses. Except from immune cells, MIF is also secreted by a variety of non-immune cells, including hematopoietic cells, endothelial cells (ECs), and neurons. MIF plays a crucial role in various diseases, such as sepsis, rheumatoid arthritis, acute kidney injury, and neurodegenerative diseases. The role of MIF in the neuropathogenesis of cognitive impairment disorders is emphasized, as it recruits multiple inflammatory mediators, leading to activating microglia or astrocyte-derived neuroinflammation. Furthermore, it contributes to the cell death of neurons and ECs with the binding of apoptosis-inducing factor (AIF) through parthanatos-associated apoptosis-inducing factor nuclease (PAAN) / MIF pathway. This review comprehensively delves into the relationship between MIF and the neuropathogenesis of cognitive impairment disorders, providing a series of emerging MIF-targeted pharmaceuticals as potential treatments for cognitive impairment disorders.

Machine learning assisted combined systems of wastewater treatment plants with constructed wetlands optimal decision-making.

This study proposed an efficient framework for optimizing the design and operation of combined systems of wastewater treatment plants (WWTP) and constructed wetlands (CW). The framework coupled a WWTP model with a CW model and used a multi-objective evolutionary algorithm to identify trade-offs between energy consumption, effluent quality, and construction cost. Compared to traditional design and management approaches, the framework achieved a 27 % reduction in WWTP energy consumption or a 44 % reduction in CW cost while meeting strict effluent discharge limits for Chinese WWTP. The framework also identified feasible decision variable ranges and demonstrated the impact of different optimization strategies on system performance. Furthermore, the contributions of WWTP and CW in pollutant degradation were analyzed. Overall, the proposed framework offers a highly efficient and cost-effective solution for optimizing the design and operation of a combined WWTP and CW system.

CircAKT3 alleviates postoperative cognitive dysfunction by stabilizing the feedback cycle of miR-106a-5p/HDAC4/MEF2C axis in hippocampi of aged mice.

Circular RNAs (circRNAs) have garnered significant attention in the field of neurodegenerative diseases including Alzheimer's diseases due to their covalently closed loop structure. However, the involvement of circRNAs in postoperative cognitive dysfunction (POCD) is still largely unexplored. To identify the genes differentially expressed between non-POCD (NPOCD) and POCD mice, we conducted the whole transcriptome sequencing initially in this study. According to the expression profiles, we observed that circAKT3 was associated with hippocampal neuronal apoptosis in POCD mice. Moreover, we found that circAKT3 overexpression reduced apoptosis of hippocampal neurons and alleviated POCD. Subsequently, through bioinformatics analysis, our data showed that circAKT3 overexpression in vitro and in vivo elevated the abundance of miR-106a-5p significantly, resulting in a decrease of HDAC4 protein and an increase of MEF2C protein. Additionally, this effect of circAKT3 was blocked by miR-106a-5p inhibitor. Interestingly, MEF2C could activate the transcription of miR-106a-5p promoter and form a positive feedback loop. Therefore, our findings revealed more potential modulation ways between circRNA-miRNA and miRNA-mRNA, providing different directions and targets for preclinical studies of POCD.

Fragment-Based Deep Learning for Simultaneous Prediction of Polarizabilities and NMR Shieldings of Macromolecules and Their Aggregates.

Simultaneous prediction of the molecular response properties, such as polarizability and the NMR shielding constant, at a low computational cost is an unresolved issue. We propose to combine a linear-scaling generalized energy-based fragmentation (GEBF) method and deep learning (DL) with both molecular and atomic information-theoretic approach (ITA) quantities as effective descriptors. In GEBF, the total molecular polarizability can be assembled as a linear combination of the corresponding quantities calculated from a set of small embedded subsystems in GEBF. In the new GEBF-DL(ITA) protocol, one can predict subsystem polarizabilities based on the corresponding molecular wave function (thus electron density and ITA quantities) and DL model rather than calculate them from the computationally intensive coupled-perturbed Hartree-Fock or Kohn-Sham equations and finally obtain the total molecular polarizability via a linear combination equation. As a proof-of-concept application, we predict the molecular polarizabilities of large proteins and protein aggregates. GEBF-DL(ITA) is shown to be as accurate enough as GEBF, with mean absolute percentage error <1%. For the largest protein aggregate (>4000 atoms), GEBF-DL(ITA) gains a speedup ratio of 3 compared with GEBF. It is anticipated that when more advanced electronic structure methods are used, this advantage will be more appealing. Moreover, one can also predict the NMR chemical shieldings of proteins with reasonably good accuracy. Overall, the cost-efficient GEBF-DL(ITA) protocol should be a robust theoretical tool for simultaneously predicting polarizabilities and NMR shieldings of large systems.

Inter-site structural heterogeneity induction of single atom Fe catalysts for robust oxygen reduction.

Metal-nitrogen-carbon catalysts with hierarchically dispersed porosity are deemed as efficient geometry for oxygen reduction reaction (ORR). However, catalytic performance determined by individual and interacting sites originating from structural heterogeneity is particularly elusive and yet remains to be understood. Here, an efficient hierarchically porous Fe single atom catalyst (Fe SAs-HP) is prepared with Fe atoms densely resided at micropores and mesopores. Fe SAs-HP exhibits robust ORR performance with half-wave potential of 0.94 V and turnover frequency of 5.99 e-1s-1site-1 at 0.80 V. Theoretical simulations unravel a structural heterogeneity induced optimization, where mesoporous Fe-N4 acts as real active centers as a result of long-range electron regulation by adjacent microporous sites, facilitating O2 activation and desorption of key intermediate *OH. Multilevel operando characterization results identify active Fe sites undergo a dynamic evolution from basic Fe-N4 to active Fe-N3 under working conditions. Our findings reveal the structural origin of enhanced intrinsic activity for hierarchically porous Fe-N4 sites.

A nonmetallic plasmonic catalyst for photothermal CO2 flow conversion with high activity, selectivity and durability.

The meticulous design of active sites and light absorbers holds the key to the development of high-performance photothermal catalysts for CO2 hydrogenation. Here, we report a nonmetallic plasmonic catalyst of Mo2N/MoO2-x nanosheets by integrating a localized surface plasmon resonance effect with two distinct types of active sites for CO2 hydrogenation. Leveraging the synergism of dual active sites, H2 and CO2 molecules can be simultaneously adsorbed and activated on N atom and O vacancy, respectively. Meanwhile, the plasmonic effect of this noble-metal-free catalyst signifies its promising ability to convert photon energy into localized heat. Consequently, Mo2N/MoO2-x nanosheets exhibit remarkable photothermal catalytic performance in reverse water-gas shift reaction. Under continuous full-spectrum light irradiation (3 W·cm-2) for a duration of 168 h, the nanosheets achieve a CO yield rate of 355 mmol·gcat-1·h-1 in a flow reactor with a selectivity exceeding 99%. This work offers valuable insights into the precise design of noble-metal-free active sites and the development of plasmonic catalysts for reducing carbon footprints.

Enhancing Cu-ligand interaction for efficient CO2 reduction towards multi-carbon products.

Electrochemical CO2 reduction (CO2R) to valuable products provides a promising strategy to enable CO2 utilization sustainably. Here, we report the strategy of using Cu-DAT (3,5-diamino-1,2,4-triazole) as a catalyst precursor for efficient CO2 reduction, demonstrating over 80% selectivity towards multicarbon products at 400 mA cm-2, with intrinsic activity over 19 times higher than that of Cu nanoparticles. The catalyst's active phase is determined to be metallic copper wrapped with the DAT ligand. We attribute this enhanced CO2R performance to the accelerated steps of *CO adsorption and C-C coupling induced by the closely cooperated DAT ligand.

Investigation of the structure, rheology and 3D printing characteristics of corn starch regulated by glycyrrhizic acid.

This study aimed to construct a novel corn starch-glycyrrhizic acid (CS-GA) ink and systematically investigate the effects of GA on the water distribution, microstructure, rheology and 3D printing properties of CS hydrogels. The results showed that the CS chains could form strong hydrogen bonds with GA molecules, inhibit the formation of short-range ordered structure of CS and reduce the content of B-type starch. The low-field nuclear magnetic results showed that the introduction of GA could increase bound water content in CS-GA hydrogels. With the increase of GA content, the CS-GA hydrogel changed from CS-dominated to a GA-dominated gel network system. Rheological results showed that all samples exhibited typical shear thinning behavior. High GA concentration was beneficial to increasing the self-supporting properties and thixotropic recovery of CS-GA hydrogels. Compared with the pure CS hydrogel, the 3D printing characteristics of CS-GA hydrogels were significantly enhanced due to the increased bound water content and the enhancement of rheological properties. At 40 % GA content, CS-GA hydrogel showed the highest printing accuracy of 96.4 % ± 0.30 %. The printed product could perfectly replicate the preset model. Therefore, this study provided a theoretical basis for regulating starch's rheology and 3D printing characteristics and developing novel food-grade 3D printing inks.

In silico MS/MS prediction for peptidoglycan profiling uncovers novel anti-inflammatory peptidoglycan fragments of the gut microbiota.

Peptidoglycan is an essential exoskeletal polymer across all bacteria. Gut microbiota-derived peptidoglycan fragments (PGNs) are increasingly recognized as key effector molecules that impact host biology. However, the current peptidoglycan analysis workflow relies on laborious manual identification from tandem mass spectrometry (MS/MS) data, impeding the discovery of novel bioactive PGNs in the gut microbiota. In this work, we built a computational tool PGN_MS2 that reliably simulates MS/MS spectra of PGNs and integrated it into the user-defined MS library of in silico PGN search space, facilitating automated PGN identification. Empowered by PGN_MS2, we comprehensively profiled gut bacterial peptidoglycan composition. Strikingly, the probiotic Bifidobacterium spp. manifests an abundant amount of the 1,6-anhydro-MurNAc moiety that is distinct from Gram-positive bacteria. In addition to biochemical characterization of three putative lytic transglycosylases (LTs) that are responsible for anhydro-PGN production in Bifidobacterium, we established that these 1,6-anhydro-PGNs exhibit potent anti-inflammatory activity in vitro, offering novel insights into Bifidobacterium-derived PGNs as molecular signals in gut microbiota-host crosstalk.

To explore the potential mechanisms of cognitive impairment in children with MRI-negative pharmacoresistant epilepsy due to focal cortical dysplasia: A pilot study from gray matter structure view.

Objectives: To investigate the characteristics of brain structure in children with focal cortical dysplasia (FCD)-induced pharmacoresistant epilepsy, and explore the potential mechanisms of cognitive impairment from the view of gray matter alteration. Methods: 25 pharmacoresistant pediatric patients with pathologically confirmed focal cortical dysplasia (FCD), and 25 gender-matched healthy controls were included in this study. 3.0T MRI data and intelligence tests using the Wechsler Intelligence Scale for Children-Forth Edition (WISC-IV) were generated for all subjects. Voxel-based morphometry (VBM)-diffeomorphic anatomical registration through exponentiated lie algebra (DARTEL) and surface-based morphometry (SBM) analyses were performed to analyze gray matter volume and cortical structure. Two-sample t-tests were used to compare the differences in gray matter volume (P＜0.05, FWE) and cortical thickness (P＜0.001, FWE) between the two groups. Also, the Spearman rank correlation analyses were employed to determine the relationship between structural alterations and neuropsychological results. Results: The WISC-IV scores of the FCD group were significantly lower than those of the HC group in terms of full-scale intelligence quotient (FSIQ), verbal comprehension index (VCI), perceptual reasoning index (PRI), working memory index (WMI), and processing speed index (PSI) (all P＜0.01). Compared with the HC group, in the FCD group, the gray matter volume (GMV) reduced significantly in the left cerebellum_8, cerebellum_Crus2, and bilateral thalamus (P＜0.05, FWE); the GMV increased in the bilateral medial frontal gyrus, right precuneus, and left inferior temporal gyrus (P＜0.05, FWE), and the cortical thickness increased in the bilateral frontal, parietal, and temporal areas (P＜0.001, FWE). Correlation analyses showed that the age of seizure onset had positive correlations with the WISC-IV scores significantly. Meanwhile, the cortex thicknesses of the left pars opercularis gyrus, left middle temporal gyrus, and right inferior temporal gyrus had negative correlations with the WISC-IV scores significantly. Conclusion: FCD patients showed subtle structural abnormalities in multiple brain regions, with significant involvement of the primary visual cortex and language function cortex. And we also demonstrated a crucial correlation between gray matter structural alteration and cognitive impairment.

Study on antimicrobial activity of sturgeon skin mucus polypeptides (Rational Design, Self-Assembly and Application).

Despite the favorable biocompatibility of natural antimicrobial peptides (AMPs), their scarcity limits their practical application. Through rational design, the activity of AMPs can be enhanced to expand their application. In this study, we selected a natural sturgeon epidermal mucus peptide, AP-16 (APATPAAPALLPLWLL), as the model molecule and studied its conformational regulation and antimicrobial activity through amino acid substitutions and N-terminal lipidation. The structural and morphological transitions of the peptide self-assemblies were investigated using circular dichroism and transmission electron microscopy. Following amino acid substitution, the conformation of AL-16 (AKATKAAKALLKLWLL) did not change. Following N-terminal alkylation, the C8-AL-16 and C12-AL-16 conformations changed from random coil to ß-sheet or α-helix, and the self-assembly changed from nanofibers to nanospheres. AL-16, C8-AL-16, and C8-AL-16 presented significant antimicrobial activity against Pseudomonas and Shewanella at low concentrations. N-terminal alkylation effectively extended the shelf life of Litopenaeus vannamei. These results support the application of natural AMPs.

Laser-Induced Skin-like Flexible Pressure Sensor for Artificial Intelligence Speech Recognition.

Skin-like flexible pressure sensors with good sensing performance have great application potential, but their development is limited owing to the need for multistep, high-cost, and low-efficiency preparation processes. Herein, a simple, low-cost, and efficient laser-induced forming process is proposed for the first time to prepare a skin-like flexible piezoresistive sensor. In the laser-induced forming process, based on the photothermal effect of graphene and the foaming effect of glucose, a skin-like polydimethylsiloxanes (PDMS) film with porous structures and surface protrusions is obtained by using infrared laser irradiation of the glucose/graphene/PDMS prepolymer film. Further, based on the skin-like PDMS film with a graphene conductive layer, a new skin-like flexible piezoresistive sensor is obtained. Due to the stress concentration caused by the surface protrusions and the low stiffness caused by the porous structures, the flexible piezoresistive sensor realizes an ultrahigh sensitivity of 1348 kPa-1 at 0-2 kPa, a wide range of 200 kPa, a fast response/recovery time of 52 ms/35 ms, and good stability over 5000 cycles. The application of the sensor to the detection of human pulses and robot clamping force indicates its potential for health monitoring and soft robots. Furthermore, in combination with the neural network (CNN) algorithm in artificial intelligence technology, the sensor achieves 95% accuracy in speech recognition, which demonstrates its great potential for intelligent wearable electronics. Especially, the laser-induced forming process is expected to facilitate the efficient, large-scale preparation of flexible devices with multilevel structures.

Decade Milestone Advancement of Defect-Engineered g-C3N4 for Solar Catalytic Applications.

Over the past decade, graphitic carbon nitride (g-C3N4) has emerged as a universal photocatalyst toward various sustainable carbo-neutral technologies. Despite solar applications discrepancy, g-C3N4 is still confronted with a general fatal issue of insufficient supply of thermodynamically active photocarriers due to its inferior solar harvesting ability and sluggish charge transfer dynamics. Fortunately, this could be significantly alleviated by the "all-in-one" defect engineering strategy, which enables a simultaneous amelioration of both textural uniqueness and intrinsic electronic band structures. To this end, we have summarized an unprecedently comprehensive discussion on defect controls including the vacancy/non-metallic dopant creation with optimized electronic band structure and electronic density, metallic doping with ultra-active coordinated environment (M-Nx, M-C2N2, M-O bonding), functional group grafting with optimized band structure, and promoted crystallinity with extended conjugation π system with weakened interlayered van der Waals interaction. Among them, the defect states induced by various defect types such as N vacancy, P/S/halogen dopants, and cyano group in boosting solar harvesting and accelerating photocarrier transfer have also been emphasized. More importantly, the shallow defect traps identified by femtosecond transient absorption spectra (fs-TAS) have also been highlighted. It is believed that this review would pave the way for future readers with a unique insight into a more precise defective g-C3N4 "customization", motivating more profound thinking and flourishing research outputs on g-C3N4-based photocatalysis.