Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.

This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with prostate cancer, differentiating between surgical and non-surgical treatments. The performances of the algorithms were measured using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, positive predictive value, negative predictive value. The Shapley Additive Explanations (SHAP) method was employed to investigate the key factors influencing the prediction process. Survival analysis methods were used to compare the survival rates of different treatment options. The CatBoost model yielded the best results (AUC = 0.939, sensitivity = 0.877, accuracy = 0.877). SHAP interpreters revealed that the T stage, cancer stage, age, cores positive percentage, prostate-specific antigen, and Gleason score were the most critical factors in predicting treatment options. The study found that surgery significantly improved survival rates, with patients undergoing surgery experiencing a 20.36% increase in 10-year survival rates compared with those receiving non-surgical treatments. Among surgical options, radical prostatectomy had the highest 10-year survival rate at 89.2%. This study successfully developed a predictive model to guide treatment decisions for prostate cancer. Moreover, the model enhanced the transparency of the decision-making process, providing clinicians with a reference for formulating personalized treatment plans.

Early-life malnutrition exposure associated with higher osteoporosis risk in adulthood: a large-scale cross-sectional study.

INTRODUCTION: Evidence on the association between early-life malnutrition exposure at different developmental stages and the subsequent risk of osteoporosis and fractures in adulthood remains sparse and equivocal. This study sought to elucidate the relationship between malnutrition exposure in early life and the occurrence of osteoporosis and fractures later in life. METHODS: This research is a cross-sectional analysis carried out within the framework of the China Community-based Cohort of Osteoporosis (CCCO), an ongoing community-based cohort study. Participants were stratified by birthdate into several categories: non-exposed, fetal, early childhood, mid-childhood, late childhood, and adolescence exposure groups. The non-exposure and adolescence exposure groups were consolidated into an "age-matched group" to provide a robust comparative framework for analyzing the probability of developing osteoporosis (defined as a T-score ≤ -2.5 in bone mineral density) and the frequency of self-reported fracture. Multiple logistic regression models were utilized to investigate the association between early-life malnutrition exposure and the risks of osteoporosis and fracture. Additionally, we validated our findings using the China Northwest Cohort (CNC). RESULTS: A total of 12,789 participants were included into the final analysis. After adjusting for various covariates, individuals exposed to malnutrition during their fetal and childhood stages (early, middle, and late) increased the likelihood of developing osteoporosis in adulthood, compared to their age-matched counterparts. In these four groups, the ORs (95% CI) for osteoporosis risk were 1.223 (1.035 to 1.445), 1.208 (1.052 to 1.386), 1.249 (1.097 to 1.421), and 1.101 (1.001 to 1.210), respectively (all P values < 0.05). Specifically, the late childhood exposure group showed a heightened risk of fracture, with an OR (95% CI) of 1.155 (1.033 to 1.291) and a P-value of 0.01127. Stratified analyses further found a significant correlation between early-life exposure to malnutrition and an elevated risk of osteoporosis in participants with lower educational attainment, overweight or obese participants. Additionally, corroborating evidence from the CNC confirmed the influence of malnutrition exposure on osteoporosis risk. CONCLUSIONS: Early-life exposure to malnutrition had a detrimental impact on bone health. Individuals who had experienced malnutrition during fetal and childhood stages (early, middle, and late) exhibited a high susceptibility to osteoporosis in adulthood, compared to age-matched cohorts. This susceptibility was particularly pronounced in women, and individuals who were overweight or obese, or had lower levels of education.

Polyaptamer-Driven Crystallization of Alendronate for Synergistic Osteoporosis Treatment through Osteoclastic Inhibition and Osteogenic Promotion.

Osteoclastic inhibition using antiresorptive bisphosphonates and osteogenic promotion using antisclerostin agents represent two distinct osteoporosis treatments in clinical practice, each individual treatment suffers from unsatisfactory therapeutic efficacy due to its indirect intervention in osteoclasis and promotion of osteogenesis simultaneously. Although this issue is anticipated to be resolved by drug synergism, a tempting carrier-free dual-medication nanoassembly remains elusive. Herein, we prepare such a nanoassembly made of antiresorptive alendronate (ALN) crystal and antisclerostin polyaptamer (Apt) via a nucleic acid-driven crystallization method. This nanoparticle can protect Apt from rapid nuclease degradation, avoid the high cytotoxicity of free ALN, and effectively concentrate in the cancellous bone by virtue of the bone-binding ability of DNA and ALN. More importantly, the acid microenvironment of cancellous bone triggers the disassociation of nanoparticles for sustained drug release, from which ALN inhibits the osteoclast-mediated bone resorption while Apt promotes osteogenic differentiation. Our work represents a pioneering demonstration of nucleic acid-driven crystallization of a bisphosphonate into a tempting carrier-free dual-medication nanoassembly. This inaugural advancement augments the antiosteoporosis efficacy through direct inhibition of osteoclasis and promotion of osteogenesis simultaneously and establishes a paradigm for profound understanding of the underlying synergistic antiosteoporosis mechanism of antiresorptive and antisclerostin components. It is envisioned that this study provides a highly generalizable strategy applicable to the tailoring of a diverse array of DNA-inorganic nanocomposites for targeted regulation of intricate pathological niches.

Gastroesophageal reflux disease and risk for arrhythmias: a Mendelian randomization analysis.

Background: Clinical observations and epidemiological studies suggest a potential linkage between gastroesophageal reflux disease (GERD) and arrhythmias, yet the underlying mechanism remains elusive. This study investigates the causal relationship between GERD and four types of arrhythmia through a genetic lens, employing Mendelian randomization analysis to elucidate the directionality of these associations. Methods: Selected single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) data were utilized as instrumental variables. The inverse variance weighting (IVW) method, MR-Egger regression analysis, and the weighted median method were employed in two-sample Mendelian randomization analysis. Horizontal pleiotropy was detected and corrected using the MR-PRESSO test and MR-Egger regression. The stability and reliability of the Mendelian randomization results were assessed using the leave-one-out method, Cochran's Q test, and funnel plots. The causal relationship between GERD and four types of arrhythmias was evaluated using the odds ratio (OR). Results: IVW results indicated that GERD could increase the risk of arrhythmias. A one standard deviation increases in the logarithmically transformed GERD score resulted in a 34% increase in the risk of arrhythmia (OR = 1.34; 95% CI 1.19-1.51; p = 1.66E-06). No significant correlation was found between GERD and other arrhythmias. Conclusion: A causal relationship exists between GERD and arrhythmias, suggesting that GERD increases the risk of developing these arrhythmias.

Acute kidney injury with intravenous colistin sulfate compared with polymyxin B in critically ill patients: A real-world, retrospective cohort study.

BACKGROUND: Polymyxins have re-emerged as a last-resort therapeutic option for infections caused by carbapenem-resistant gram-negative bacteria. Nephrotoxicity induced by polymyxins is a significant limitation of its use in the clinic. Polymyxin B and colistin sulfate are two widely used active formulations of polymyxins. However, there is a lack of studies conducting a comparative assessment of nephrotoxicity between the two formulations. This study aimed to compare the nephrotoxicity of polymyxin B and colistin sulfate in critically ill patients. METHODS: We conducted a retrospective cohort study among critically ill patients who received intravenous polymyxin B or colistin sulfate for over 48 h from January 2017 to January 2024. The primary outcome was the incidence of acute kidney injury (AKI) associated with polymyxins, and the secondary outcome was 30-day all-cause mortality. Additionally, the risk factors of polymyxins-induced AKI and 30-day all-cause mortality were identified by Cox proportional hazard regression analysis. RESULTS: A total of 473 patients were included in this study. The overall incidence of AKI was significantly higher in patients who received polymyxin B compared to those who received colistin sulfate in the unmatched cohort (20.8% vs. 9.0%, p = 0.002) and in the propensity score matching cohort (21.1% vs. 7.0%, p = 0.004), respectively. However, there was no significant difference in 30-day all-cause mortality between the two groups. Polymyxin type, septic shock, and concomitant use of vasopressors were identified as independent risk factors for polymyxin-induced AKI. CONCLUSIONS: The prevalence of AKI was higher among patients who received polymyxin B compared to those treated with colistin sulfate. However, there was no significant difference in 30-day all-cause mortality between the two groups. Further prospective, multicenter studies with larger sample sizes are needed to validate these findings.

Excitation-Inhibition Balance, Neural Criticality, and Activities in Neuronal Circuits.

Neural activities in local circuits exhibit complex and multilevel dynamic features. Individual neurons spike irregularly, which is believed to originate from receiving balanced amounts of excitatory and inhibitory inputs, known as the excitation-inhibition balance. The spatial-temporal cascades of clustered neuronal spikes occur in variable sizes and durations, manifested as neural avalanches with scale-free features. These may be explained by the neural criticality hypothesis, which posits that neural systems operate around the transition between distinct dynamic states. Here, we summarize the experimental evidence for and the underlying theory of excitation-inhibition balance and neural criticality. Furthermore, we review recent studies of excitatory-inhibitory networks with synaptic kinetics as a simple solution to reconcile these two apparently distinct theories in a single circuit model. This provides a more unified understanding of multilevel neural activities in local circuits, from spontaneous to stimulus-response dynamics.

Eye movement evidence for the V1 Saliency Hypothesis and the Central-peripheral Dichotomy theory in an anomalous visual search task.

Typically, searching for a target among uniformly tilted non-targets is easier when this target is perpendicular, rather than parallel, to the non-targets. The V1 Saliency Hypothesis (V1SH) - that V1 creates a saliency map to guide attention exogenously - predicts exactly the opposite in a special case: each target or non-target is a pair of equally-sized disks, a homo-pair of two disks of the same color, black or white, or a hetero-pair of two disks of the opposite color; the inter-disk displacement defines its orientation. This prediction - parallel advantage - was supported by the finding that parallel targets require shorter reaction times (RTs) to report targets' locations. Furthermore, it is stronger for targets further from the center of search images, as predicted by the Central-peripheral Dichotomy (CPD) theory entailing that saliency effects are stronger in peripheral than in central vision. However, the parallel advantage could arise from a shorter time required to recognize - rather than to shift attention to - the parallel target. By gaze tracking, the present study confirms that the parallel advantage is solely due to the RTs for the gaze to reach the target. Furthermore, when the gaze is sufficiently far from the target during search, saccade to a parallel, rather than perpendicular, target is more likely, demonstrating the Central-peripheral Dichotomy more directly. Parallel advantage is stronger among observers encouraged to let their search be guided by spontaneous gaze shifts, which are presumably guided by bottom-up saliency rather than top-down factors.

Programming Injectable DNA Hydrogels Yields Tumor Microenvironment-Activatable and Immune-Instructive Depots for Augmented Chemo-Immunotherapy.

Injectable hydrogels have attracted increasing attention for promoting systemic antitumor immune response through the co-delivery of chemotherapeutics and immunomodulators. However, the biosafety and bioactivity of conventional hydrogel depots are often impaired by insufficient possibilities for post-gelling injection and means for biofunction integration. Here, an unprecedented injectable stimuli-responsive immunomodulatory depot through programming a super-soft DNA hydrogel adjuvant is reported. This hydrogel system encoded with adenosine triphosphate aptamers can be intratumorally injected in a gel formulation and then undergoes significant molecular conformation change to stimulate the distinct release kinetics of co-encapsulated therapeutics. In this scenario, doxorubicin is first released to induce immunogenic cell death that intimately works together with the polymerized cytosine-phosphate-guanine oligodeoxynucleotide (CpG ODN) in gel scaffold for effectively recruiting and activating dendritic cells. The polymerized CpG ODN not only enhances tumor immunogenicity but minimizes free CpG-induced splenomegaly. Furthermore, the subsequently released anti-programmed cell death protein ligand 1 (aPDL1) blocks the corresponding immune inhibitory checkpoint molecule on tumor cells to sensitize antitumor T-cell immunity. This work thus contributes to the first proof-of-concept demonstration of a programmable super-soft DNA hydrogel system that perfectly matches the synergistic therapeutic modalities based on chemotherapeutic toxicity, in situ vaccination, and immune checkpoint blockade.

Complexity of cortical wave patterns of the wake mouse cortex.

Rich spatiotemporal dynamics of cortical activity, including complex and diverse wave patterns, have been identified during unconscious and conscious brain states. Yet, how these activity patterns emerge across different levels of wakefulness remain unclear. Here we study the evolution of wave patterns utilizing data from high spatiotemporal resolution optical voltage imaging of mice transitioning from barbiturate-induced anesthesia to wakefulness (N = 5) and awake mice (N = 4). We find that, as the brain transitions into wakefulness, there is a reduction in hemisphere-scale voltage waves, and an increase in local wave events and complexity. A neural mass model recapitulates the essential cellular-level features and shows how the dynamical competition between global and local spatiotemporal patterns and long-range connections can explain the experimental observations. These mechanisms possibly endow the awake cortex with enhanced integrative processing capabilities.

Overexpression of SQUALENE SYNTHASE Reduces Nicotiana benthamiana Resistance against Phytophthora infestans.

Plant triterpenoids play a critical role in plant resistance against Phytophthora infestans de Bary, the causal pathogen of potato and tomato late blight. However, different triterpenoids could have contrasting functions on plant resistance against P. infestans. In this study, we targeted the key biosynthetic gene of all plant triterpenoids, SQUALENE SYNTHASE (SQS), to examine the function of this gene in plant-P. infestans interactions. A post-inoculation, time-course gene expression analysis revealed that SQS expression was induced in Nicotiana benthamiana but was transiently suppressed in Solanum lycopersicum. Consistent with the host-specific changes in SQS expression, concentrations of major triterpenoid compounds were only induced in S. lycopersicum. A stable overexpression of SQS in N. benthamiana reduced plant resistance against P. infestans and induced the hyperaccumulation of stigmasterol. A comparative transcriptomics analysis of the transgenic lines showed that diverse plant physiological processes were influenced by SQS overexpression, suggesting that phytosterol content regulation may not be the sole mechanism through which SQS promotes plant susceptibility towards P. infestans. This study provides experimental evidence for the host-specific transcriptional regulation and function of SQS in plant interactions with P. infestans, offering a novel perspective in examining the quantitative disease resistance against late blight.

Discrepancy in Sterol Usage between Two Polyphagous Caterpillars, Mythimna separata and Spodoptera frugiperda.

Insects are sterol auxotrophs and typically obtain sterols from food. However, the sterol demand and metabolic capacity vary greatly among species, even for closely related species. The low survival of many insects on atypical sterols, such as cholestanol and cholestanone, raises the possibility of using sterol-modified plants to control insect herbivore pests. In this study, we evaluated two devastating migratory crop pests, Mythimna separata and Spodoptera frugiperda, in response to atypical sterols and explored the reasons that caused the divergences in sterol nutritional biology between them. Contrary to M. separata, S. frugiperda had unexpectedly high survival on cholestanone, and nearly 80% of the individuals pupated. Comparative studies, including insect response to multiple diets and larval body sterol/steroids analysis, were performed to explain their differences in cholestanone usage. Our results showed that, in comparison to M. separata, the superiority of S. frugiperda on cholestanone can be attributed to its higher efficiency of converting ketone into available stanol and its lower demand for sterols, which resulted in a better survival when cholesterol was unavailable. This research will help us to better understand insect sterol nutritional biology and the potential of using atypical sterols to control herbivorous insect pests.

Interfacial and confined molecular-assembly of poly(3-hexylthiophene) and its application in organic electronic devices.

Poly(3-hexylthiophene) (P3HT) is a typical conducting polymer widely used in organic thin-film transistors, polymer solar cells, etc., due to good processability and remarkable charging carrier and hole mobility. It is known that the ordered structure assembled by π-conjugated P3HT chains could promote the performance of electronic devices. Interfacial and confined molecular-assembly is one effective way to generate an ordered structure by tuning surface geometry and substrate interaction. Great efforts have been made to investigate the molecular chain assembly of P3HT on a curved surface that is confined to different geometry. In this report, we review the recent advances of the interfacial chain assembly of P3HT in a flat or curved confined space and its application to organic electronic devices. In principle, this interfacial assembly of P3HT at a nanoscale could improve the electronic properties, such as the current transport, power conversion efficiency, etc. Therefore, this review on interfacial and confined assembly of P3HT could give general implications for designing high-performance organic electronic devices.

Hyperbolic-Metamaterials-Based SPR Temperature Sensor Enhanced by a Nanodiamond-PDMS Hybrid for High Sensitivity and Fast Response.

A high-performance surface plasmon resonance (SPR) fiber sensor is proposed with hyperbolic metamaterials (HMMs), nanodiamonds (NDs), and polydimethylsiloxane (PDMS) to enhance the temperature sensitivity and response time. The HMM with tunable dispersion can break through the structural limitations of the optical fiber to improve the refractive index (RI) sensitivity, while NDs and PDMS with large thermo-optic coefficients enable to induce significant RI change under varied thermal fields. The ternary composite endows the sensor with a high temperature sensitivity of -9.021 nm/°C, which is 28.6 times higher than that of the conventional gold film-based SPR sensor. Furthermore, NDs with high thermal conductivity (2200 W/mK) effectively expedite the thermal response of PDMS, which reduces the response time from 80 to 6 s. It is believed that the proposed sensors with high sensitivity, fast response time, and compact size have great potential for applications in industrial production, healthcare, environmental monitoring, etc.

Construction and Electrochemical Properties of Solid-state Supercapacitors with Redox Additives.

Adding redox additives to conventional electrolytes is considered to be an effective method to improve electrochemical performance of the supercapacitors, which is ascribed to the additional Farady capacitance derived from the reversible redox reaction. Here, the influence of K3 Fe(CN)6 on electrochemical properties for single electrode system and the assembled solid-state supercapacitor are investigated. The carbon felt (CF) electrode in the mixed solution of K3 Fe(CN)6 /KCl exhibits remarkable specific capacitance of 2.45 F cm-2 after 5000 cycles, obviously much higher than conventional electrolyte KCl. The capacitance retention and the coulombic efficiency of the solid-state supercapacitor maintains 86.5% and 97% after 2500 cycles, symmetric supercapacitor shows a high energy density of 58 mWh L-1 at power density of 660 mW L-1 . Furthermore, the solid-state SCs exhibit excellent flexibility and four supercapacitors are capable of lighting up an LED lamp, demonstrating the potential of practical applications of the as-prepared solid-state SCs.

Less is more: wiring-economical modular networks support self-sustained firing-economical neural avalanches for efficient processing.

The brain network is notably cost-efficient, while the fundamental physical and dynamic mechanisms underlying its economical optimization in network structure and activity have not been determined. In this study, we investigate the intricate cost-efficient interplay between structure and dynamics in biologically plausible spatial modular neuronal network models. We observe that critical avalanche states from excitation-inhibition balance under modular network topology with less wiring cost can also achieve lower costs in firing but with strongly enhanced response sensitivity to stimuli. We derive mean-field equations that govern the macroscopic network dynamics through a novel approximate theory. The mechanism of low firing cost and stronger response in the form of critical avalanches is explained as a proximity to a Hopf bifurcation of the modules when increasing their connection density. Our work reveals the generic mechanism underlying the cost-efficient modular organization and critical dynamics widely observed in neural systems, providing insights into brain-inspired efficient computational designs.

Criticality enhances the multilevel reliability of stimulus responses in cortical neural networks.

Cortical neural networks exhibit high internal variability in spontaneous dynamic activities and they can robustly and reliably respond to external stimuli with multilevel features-from microscopic irregular spiking of neurons to macroscopic oscillatory local field potential. A comprehensive study integrating these multilevel features in spontaneous and stimulus-evoked dynamics with seemingly distinct mechanisms is still lacking. Here, we study the stimulus-response dynamics of biologically plausible excitation-inhibition (E-I) balanced networks. We confirm that networks around critical synchronous transition states can maintain strong internal variability but are sensitive to external stimuli. In this dynamical region, applying a stimulus to the network can reduce the trial-to-trial variability and shift the network oscillatory frequency while preserving the dynamical criticality. These multilevel features widely observed in different experiments cannot simultaneously occur in non-critical dynamical states. Furthermore, the dynamical mechanisms underlying these multilevel features are revealed using a semi-analytical mean-field theory that derives the macroscopic network field equations from the microscopic neuronal networks, enabling the analysis by nonlinear dynamics theory and linear noise approximation. The generic dynamical principle revealed here contributes to a more integrative understanding of neural systems and brain functions and incorporates multimodal and multilevel experimental observations. The E-I balanced neural network in combination with the effective mean-field theory can serve as a mechanistic modeling framework to study the multilevel neural dynamics underlying neural information and cognitive processes.

What county-level factors influence COVID-19 incidence in the United States? Findings from the first wave of the pandemic.

Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.

Ag23Au2 and Ag22Au3: A Model of Cocrystallization in Bimetal Nanoclusters.

The field of cocrystalline nanoclusters stabilized by thiolates is in a period of rapid development. However, the types of cocrystallization have been limited to a few reported until now, so it is of great importance to investigate and understand the novel cocrystallographic structures. Herein, we design and synthesize a new type of cocrystallization, [Ag23Au2(2-EBT)18Ag22Au3(2-EBT)18]2-[2(PPh4)]2+, characterized by thermogravimetric analysis, X-ray photoelectron spectroscopy, and single-crystal X-ray crystallography. Interestingly, both of the cocrystallized nanoclusters show the same outer-shell geometric structure but diffenent cores (Ag11Au2 vs Ag10Au3). The cocrystal lattice exhibits a multilayer structure in which both of the cocrystallized nanoclusters and the counterion assemble in a layer-by-layer model. Meanwhile, the counterion is found to be critical for formation and stabilization of the target cocrystal. In addition, the target cocrystal shows high thermal stability, and this result possibly originates from the electrostatic and weak interactions in the cocrystals.

Electrically reconfigurable non-volatile metasurface using low-loss optical phase-change material.

Active metasurfaces promise reconfigurable optics with drastically improved compactness, ruggedness, manufacturability and functionality compared to their traditional bulk counterparts. Optical phase-change materials (PCMs) offer an appealing material solution for active metasurface devices with their large index contrast and non-volatile switching characteristics. Here we report a large-scale, electrically reconfigurable non-volatile metasurface platform based on optical PCMs. The optical PCM alloy used in the devices, Ge2Sb2Se4Te (GSST), uniquely combines giant non-volatile index modulation capability, broadband low optical loss and a large reversible switching volume, enabling notably enhanced light-matter interactions within the active optical PCM medium. Capitalizing on these favourable attributes, we demonstrated quasi-continuously tuneable active metasurfaces with record half-octave spectral tuning range and large optical contrast of over 400%. We further prototyped a polarization-insensitive phase-gradient metasurface to realize dynamic optical beam steering.

Gamma Oscillations Facilitate Effective Learning in Excitatory-Inhibitory Balanced Neural Circuits.

Gamma oscillation in neural circuits is believed to associate with effective learning in the brain, while the underlying mechanism is unclear. This paper aims to study how spike-timing-dependent plasticity (STDP), a typical mechanism of learning, with its interaction with gamma oscillation in neural circuits, shapes the network dynamics properties and the network structure formation. We study an excitatory-inhibitory (E-I) integrate-and-fire neuronal network with triplet STDP, heterosynaptic plasticity, and a transmitter-induced plasticity. Our results show that the performance of plasticity is diverse in different synchronization levels. We find that gamma oscillation is beneficial to synaptic potentiation among stimulated neurons by forming a special network structure where the sum of excitatory input synaptic strength is correlated with the sum of inhibitory input synaptic strength. The circuit can maintain E-I balanced input on average, whereas the balance is temporal broken during the learning-induced oscillations. Our study reveals a potential mechanism about the benefits of gamma oscillation on learning in biological neural circuits.