The global patent landscape of emerging infectious disease monkeypox.

BACKGROUND: Monkeypox is an emerging infectious disease with confirmed cases and deaths in several parts of the world. In light of this crisis, this study aims to analyze the global knowledge pattern of monkeypox-related patents and explore current trends and future technical directions in the medical development of monkeypox to inform research and policy. METHODS: A comprehensive study of 1,791 monkeypox-related patents worldwide was conducted using the Derwent patent database by descriptive statistics, social network method and linear regression analysis. RESULTS: Since the 21st century, the number of monkeypox-related patents has increased rapidly, accompanied by increases in collaboration between commercial and academic patentees. Enterprises contributed the most in patent quantity, whereas the initial milestone patent was filed by academia. The core developments of technology related to the monkeypox include biological and chemical medicine. The innovations of vaccines and virus testing lack sufficient patent support in portfolios. CONCLUSIONS: Monkeypox-related therapeutic innovation is geographically limited with strong international intellectual property right barriers though it has increased rapidly in recent years. The transparent licensing of patent knowledge is driven by the merger and acquisition model, and the venture capital, intellectual property and contract research organization model. Currently, the patent thicket phenomenon in the monkeypox field may slow the progress of efforts to combat monkeypox. Enterprises should pay more attention to the sharing of technical knowledge, make full use of drug repurposing strategies, and promote innovation of monkeypox-related technology in hotspots of antivirals (such as tecovirimat, cidofovir, brincidofovir), vaccines (JYNNEOS, ACAM2000), herbal medicine and gene therapy.

Identification of critical SARS-CoV-2 amino acids associated with COVID-19 hospitalization rate using machine learning and statistical modeling: An observational study in the United States.

BACKGROUND: The COVID-19 pandemic has put many medical systems on the verge of collapse in the last two years. Virus mutation was one of the important factors affecting the COVID-19 infection severity and hospitalizations. Although over ten thousand SARS-CoV-2 mutations being reported since the beginning of the COVID-19 pandemic, only a small percentage of mutations are likely to affect the virus phenotype and change its severity. Finding out which amino acids have the greatest impact on COVID-19 hospitalization rate is an important research question. METHODS: This observational study used the COVID-19 case hospitalization ratio (CHR) to represent the virus severity related with hospitalization. The database is based on the daily state-level epidemiological and genomic sequential data in the United States from the Alpha wave to the first Omicron wave. The critical amino acids that mostly affected the CHR were determined by using four types of models including extreme gradient boosting decision trees (XGBoost), artificial neural networks (ANNs), logistic regression and Lasso regression models. RESULTS: The XGBoost, ANN, logistic regression, and Lasso regression models all produce excellent results (mean square error for all state-level models does not exceed 0.0008 using the testing dataset). Based on the rank of importance of all covariates, the critical amino acids most affecting the CHR were identified, including T19, L24, P25, P26, A27, A67, H69, V70, T95, G142, V143, Y145, E156, F157, N211, L212, V213, R214, D215, G339, R346, S373, L452, S477, T478, E484, N501, A570, P681, and T716. CONCLUSION: This study identified critical amino acids that are most likely to affect the hospitalization rate, allowing public health workers to monitor these highly risky amino acids and raise an alarm immediately when more severe mutations occur. Furthermore, the methodology and results may be extended to other regions.

How Population Aging Affects Industrial Structure Upgrading: Evidence from China.

The question of how to proactively respond to population aging has become a major global issue. As a country with the largest elderly population in the world, China suffers a stronger shock from population aging, which makes it more urgent to transform its industrial and economic development model. Concretely, in the context of the new macroeconomic environment that has undergone profound changes, the shock of population aging makes the traditional industrial structure upgrading model (driven by large-scale factor inputs, imitation innovation and low-cost technological progress, and strong external demand) more unsustainable, and China has an urgent need to transform it to a more sustainable one. Only with an in-depth analysis of the influence mechanism of population aging on the upgrading of industrial structure can we better promote industrial structure upgrading under the impact of population aging. Therefore, six MSVAR models were constructed from each environmental perspective based on data from 1987 to 2021. The probabilities of regime transition figures show that the influencing mechanisms have a clear two-regime feature from any view; specifically, the omnidirectional environmental transition occurs in 2019. A further impulse-response analysis shows that, comparatively speaking, under the new environment regime the acceleration of population aging (1) aggravates the labor shortage, thus narrowing the industrial structure upgrading ranges; (2) has a negative, rather than positive, impact on the capital stock, but leads to a cumulative increase in industrial structure upgrading; (3) forces weaker technological progress, but further leads to a stronger impact on the industrial structure upgrading; (4) forces greater consumption upgrading, which further weakens industrial structure upgrading; (5) narrows rather than expands the upgrading of investment and industrial structures; and (6) narrows the upgrading of export and industrial structures. Therefore, we should collaboratively promote industrial structure upgrading from the supply side relying heavily on independent innovation and talent, and the demand side relying heavily on the upgrading of domestic consumption and exports.

Impacts of social distancing, rapid antigen test and vaccination on the Omicron outbreak during large temperature variations in Hong Kong: A modelling study.

BACKGROUND: The impacts of non-pharmaceutical interventions (NPIs) and vaccine boosters on the transmission of the largest outbreak of COVID-19 (the fifth wave) in Hong Kong have not been reported. The outbreak, dominated by the Omicron BA.2 subvariant, began to spread substantially after the Spring Festival in February, 2022, when the temperature varied greatly (e.g. a cold surge event). Tightening social distancing measures did not succeed in containing the outbreak until later with the use of rapid antigen tests (RAT) and increased vaccination rates. Temperature has been previously found to have significant impact on the transmissibility. Understanding how the public health interventions influence the number of infections in this outbreak provide important insights on prevention and control of COVID-19 during different seasons. METHODS: We developed a transmission model incorporating stratified immunity with vaccine-induced antibody responses and the daily changes in population mobility, vaccination and weather factors (i.e. temperature and relative humidity). We fitted the model to the daily reported cases detected by either PCR or RAT between 1 February and 31 March using Bayesian statistics, and quantified the effects of individual NPIs, vaccination and weather factors on transmission dynamics. RESULTS: Model predicted that, with the vaccine uptake, social distancing reduced the cumulative incidence (CI) from 58.2% to 44.5% on average. The use of RAT further reduced the CI to 39.0%. Without vaccine boosters in these two months, the CI increased to 49.1%. While public health interventions are important in reducing the total infections, the outbreak was temporarily driven by the cold surge. If the coldest two days (8.5 °C and 8.8 °C) in February were replaced by the average temperature in that month (15.2 °C), the CI would reduce from 39.0% to 28.2%. CONCLUSION: Preventing and preparing for the transmission of COVID-19 considering the change in temperature appears to be a cost-effective preventive strategy to lead people to return to normal life.

Path to normality: Assessing the level of social-distancing measures relaxation against antibody-resistant SARS-CoV-2 variants in a partially-vaccinated population.

Introduction: Two years into the coronavirus 2019 (COVID-19) pandemic, populations with less built-up immunity continued to devise ways to optimize social distancing measures (SDMs) relaxation levels for outbreaks triggered by SARS-CoV-2 and its variants to resume minimal economics activities while avoiding hospital system collapse. Method: An age-stratified compartmental model featuring social mixing patterns was first fitted the incidence data in second wave in Hong Kong. Hypothetical scenario analysis was conducted by varying population mobility and vaccination coverages (VCs) to predict the number of hospital and intensive-care unit admissions in outbreaks initiated by ancestral strain and its variants (Alpha, Beta, Gamma, Delta and Omicron). Scenarios were "unsustainable" if either of admissions was larger than the maximum of its occupancy. Results: At VC of 65%, scenarios of full SDMs relaxation (mean daily social encounters prior to COVID-19 pandemic = 14.1 contacts) for outbreaks triggered by ancestral strain, Alpha and Beta were sustainable. Restricting levels of SDMs was required such that the optimal population mobility had to be reduced to 0.9, 0.65 and 0.37 for Gamma, Delta and Omicron associated outbreaks respectively. VC improvement from 65% to 75% and 95% allowed complete SDMs relaxation in Gamma-, and Delta-driven epidemic respectively. However, this was not supported for Omicron-triggered epidemic. Discussion: To seek a path to normality, speedy vaccine and booster distribution to the majority across all age groups is the first step. Gradual or complete SDMs lift could be considered if the hybrid immunity could be achieved due to high vaccination coverage and natural infection rate among vaccinated or the COVID-19 case fatality rate could be reduced similar to that for seasonal influenza to secure hospital system sustainability.

The application and perspective of hyperbaric oxygen therapy in acute ischemic stroke: From the bench to a starter?

Stroke has become a significant cause of death and disability globally. Along with the transition of the world's aging population, the incidence of acute ischemic stroke is increasing year by year. Even with effective treatment modalities, patients are not guaranteed to have a good prognosis. The treatment model combining intravenous thrombolysis/endovascular therapy and neuroprotection is gradually being recognized. After the clinical translation of pharmacological neuroprotective agents failed, non-pharmacological physical neuroprotective agents have rekindled hope. We performed a literature review using the National Center for Biotechnology Information (NCBI) PubMed database for studies that focused on the application of hyperbaric oxygen therapy in acute ischemic stroke. In this review, we present the history and mechanisms of hyperbaric oxygen therapy, focusing on the current status, outcomes, current challenges, perspective, safety, and complications of the application of hyperbaric oxygen in animal experiments and human clinical trials. Hyperbaric oxygen therapy, a non-pharmacological treatment, can improve the oxygenation level at the ischemic lesions in increased dissolved oxygen and oxygen diffusion radius to achieve salvage of neurological function, giving a new meaning to acute ischemic stroke.

The comprehensive and systematic identification of BLCA-specific SF-regulated, survival-related AS events.

Bladder urothelial carcinoma (BLCA) is a complex disease with high morbidity and mortality. Changes in alternative splicing (AS) and splicing factor (SF) can affect gene expression, thus playing an essential role in tumorigenesis. This study downloaded 412 patients' clinical information and 433 samples of transcriptome profiling data from TCGA. And we collected 48 AS signatures from SpliceSeq. LASSO and Cox analyses were used for identifying survival-related AS events in BLCA. Finally, 1,645 OS-related AS events in 1,129 genes were validated by Kaplan-Meier (KM) survival analysis, ROC analysis, risk curve analysis, and independent prognostic analysis. Finally, our survey provides an AS-SF regulation network consisting of five SFs and 46 AS events. In the end, we profiled genes that AS occurred in pan-cancer and five SFs' expression in tumor and normal samples in BLCA. We selected CLIP-seq data for validation the interaction regulated by RBP. Our study paves the way for potential therapeutic targets of BLCA.

Anterior Circulation Acute Ischemic Stroke in the Plateau of China: Risk Factors and Clinical Characteristics.

Background and Purpose: Acute ischemic stroke has a high incidence in the plateau of China. It has unique characteristics compared to the plains, and the specific relationship with altitude has not yet been appreciated. This study aimed to investigate the specificity of the plateau's anterior circulation acute ischemic stroke in China. Methods: To retrospectively collect clinical data of patients with first-episode acute ischemic stroke in the anterior circulation in Tianjin and Xining city. The differences in clinical presentation, laboratory, and imaging examinations were compared. Results: Patients at high altitudes showed a significant trend toward lower age (61.0 ± 10.2 vs. 64.8 ± 8.1, P = 0.010) and had a history of dyslipidemia, higher levels of inflammatory markers, erythrocytosis, and alcohol abuse. The main manifestations were higher diastolic blood pressure (85.5 ± 14.0 mmHg vs. 76.8 ± 11.6 mmHg, P < 0.001), triglycerides [2.0 (1.8) mmol/L vs. 1.3 (0.9) mmol/L, P < 0.001], CRP [4.7 (4.4) mg/L vs. 2.1 (1.9) mg/L, P < 0.001], homocysteine levels [14.5 (11.7) µmol/L vs. 11.2 (5.2) µmol/L, P < 0.001]; larger infarct volume [3.5 (4.8) cm3 vs. 9.0 (6.9) cm3, P < 0.001] and worse prognosis. Patients at high altitudes had higher atherosclerotic indexes in cIMT and plaque than those in plains. Conclusions: The natural habituation and genetic adaptation of people to the particular geo-climatic environment of the plateau have resulted in significant differences in disease characteristics. Patients with the anterior circulation acute ischemic stroke in the plateau show more unfavorable clinical manifestations and prognosis. This study provides a preliminary interpretation of the effects of altitude and suggests developing preventive and therapeutic protocol measures that are more appropriate for the plateau of China.

Assessing the impact of temperature and humidity exposures during early infection stages on case-fatality of COVID-19: A modelling study in Europe.

Background Although associations between key weather indicators (i.e. temperature and humidity) and COVID-19 mortality have been reported, the relationship between these exposures at different timings in early infection stages (from virus exposure up to a few days after symptom onset) and the probability of death after infection (also called case fatality rate, CFR) has yet to be determined. Methods We estimated the instantaneous CFR of eight European countries using Bayesian inference in conjunction with stochastic transmission models, taking account of delays in reporting the number of newly confirmed cases and deaths. The exposure-lag-response associations between fatality rate and weather conditions to which patients were exposed at different timings were obtained using distributed lag nonlinear models coupled with mixed-effect models. Results Our results show that the Odds Ratio (OR) of death is negatively associated with the temperature, with two maxima (OR = 1.29 (95% CI: 1.23, 1.35) at -0.1°C; OR = 1.12 (95% CI: 1.08, 1.16) at 0.1°C) occurring at the time of virus exposure and after symptom onset. Two minima (OR = 0.81 (95% CI: 0.71, 0.92) at 23.2°C; OR = 0.71 (95% CI: 0.63, 0.80) at 21.7°C) also occurred at these two distinct periods correspondingly. Low humidity (below 50%) during the early stages and high humidity (approximately 89%) after symptom onset were related to the lower fatality. Conclusion Environmental conditions may affect not only the initial viral load when patients are exposed to the virus, but also individuals' immune response around symptom onset. Warmer temperatures and higher humidity after symptom onset were linked to lower fatality.

Estimating effects of intervention measures on COVID-19 outbreak in Wuhan taking account of improving diagnostic capabilities using a modelling approach.

BACKGROUND: Although by late February 2020 the COVID-19 epidemic was effectively controlled in Wuhan, China, estimating the effects of interventions, such as transportation restrictions and quarantine measures, on the early COVID-19 transmission dynamics in Wuhan is critical for guiding future virus containment strategies. Since the exact number of infected cases is unknown, the number of documented cases was used by many disease transmission models to infer epidemiological parameters. This means that it was possible to produce biased estimates of epidemiological parameters and hence of the effects of intervention measures, because the percentage of all cases that were documented changed during the first 2 months of the epidemic, as a consequence of a gradually improving diagnostic capability. METHODS: To overcome these limitations, we constructed a stochastic susceptible-exposed-infected-quarantined-recovered (SEIQR) model, accounting for intervention measures and temporal changes in the proportion of new documented infections out of total new infections, to characterize the transmission dynamics of COVID-19 in Wuhan across different stages of the outbreak. Pre-symptomatic transmission was taken into account in our model, and all epidemiological parameters were estimated using the Particle Markov-chain Monte Carlo (PMCMC) method. RESULTS: Our model captured the local Wuhan epidemic pattern as two-peak transmission dynamics, with one peak on February 4 and the other on February 12, 2020. The impact of intervention measures determined the timing of the first peak, leading to an 86% drop in the Re from 3.23 (95% CI, 2.22 to 4.20) to 0.45 (95% CI, 0.20 to 0.69). The improved diagnostic capability led to the second peak and a higher proportion of documented infections. Our estimated proportion of new documented infections out of the total new infections increased from 11% (95% CI 1-43%) to 28% (95% CI 4-62%) after January 26 when more detection kits were released. After the introduction of a new diagnostic criterion (case definition) on February 12, a higher proportion of daily infected cases were documented (49% (95% CI 7-79%)). CONCLUSIONS: Transportation restrictions and quarantine measures together in Wuhan were able to contain local epidemic growth.

The effects of seasonal climate variability on dengue annual incidence in Hong Kong: A modelling study.

In recent years, dengue has been rapidly spreading and growing in the tropics and subtropics. Located in southern China, Hong Kong's subtropical monsoon climate may favour dengue vector populations and increase the chance of disease transmissions during the rainy summer season. An increase in local dengue incidence has been observed in Hong Kong ever since the first case in 2002, with an outbreak reaching historically high case numbers in 2018. However, the effects of seasonal climate variability on recent outbreaks are unknown. As the local cases were found to be spatially clustered, we developed a Poisson generalized linear mixed model using pre-summer monthly total rainfall and mean temperature to predict annual dengue incidence (the majority of local cases occur during or after the summer months), over the period 2002-2018 in three pre-defined areas of Hong Kong. Using leave-one-out cross-validation, 5 out of 6 observations of area-specific outbreaks during the major outbreak years 2002 and 2018 were able to be predicted. 42 out of a total of 51 observations (82.4%) were within the 95% confidence interval of the annual incidence predicted by our model. Our study found that the rainfall before and during the East Asian monsoon (pre-summer) rainy season is negatively correlated with the annual incidence in Hong Kong while the temperature is positively correlated. Hence, as mosquito control measures in Hong Kong are intensified mainly when heavy rainfalls occur during or close to summer, our study suggests that a lower-than-average intensity of pre-summer rainfall should also be taken into account as an indicator of increased dengue risk.

Latitudes mediate the association between influenza activity and meteorological factors: A nationwide modelling analysis in 45 Japanese prefectures from 2000 to 2018.

BACKGROUND: Cold and dry conditions were well-documented as a major determinant of influenza seasonality in temperate countries but the association may not be consistent when the climate in temperate areas is closer to that in sub-tropical areas. We hypothesized latitudes may mediate the association between influenza activity and meteorological factors in 45 Japanese prefectures. METHODS: We used the weekly incidence of influenza-like illness of 45 prefectures from 2000 to 2018 as a proxy for influenza activity in Japan, a temperate country lying off the east coast of Asia. A combination of generalized additive model and distributed lag nonlinear model was adopted to investigate the associations between meteorological factors (average temperature, relative humidity, total rainfall, and actual vapour pressure, a proxy for absolute humidity) and the influenza incidence. Kendall's tau b (τ) and Spearman correlation coefficient (rs) between latitude and the adjusted relative risk (ARR) of each meteorological factor were also assessed. RESULTS: A higher vapour pressure was significantly associated with a lower influenza risk but the ARR strongly weakened along with a lower latitude (τ = -0.23, p-value = 0.02; rs = -0.33, p-value = 0.03). Lower temperature and lower relatively humidity were significantly associated with higher influenza risks in over 65% and around 40% of the prefectures respectively but the strength and significance of the correlations between their ARRs and latitude were weaker than that from vapour pressure. CONCLUSION: Even though the range of latitudes in Japan is small (26°N-43°N), the relationships between meteorological factors and influenza activity were mediated by the latitude. Our study echoed absolute humidity played a more important role in relating influenza risk, but we on the other hand showed its effect on influenza activity could be hampered in a low-latitude temperate region, which have a warmer climate. These findings thus offer a high-resolution characterization of the role of meteorological factors on influenza seasonality.

Toll-Like Receptor 2 (TLR2) and TLR4 Mediate the IgA Immune Response Induced by Mycoplasma hyopneumoniae.

IgA plays an important role in mucosal immunity against infectious pathogens; however, the molecular mechanism of IgA secretion in response to infection remains largely unknown, particularly in Mycoplasma spp. In this study, we found that the levels of IgA in the peripheral blood serum, bronchoalveolar lavage fluid, nasal mucosa, trachea, hilar lymph nodes, and lung tissues of pigs increased significantly after infection with Mycoplasma hyopneumoniae Furthermore, IgA and CD11c were detected in the lungs and hilar lymph nodes by immunohistochemical analysis, and colocalization of these two markers indicates that CD11c+ cells play an important role in IgA mucosal immunity induced by M. hyopneumoniae To investigate the regulatory mechanism of IgA, we separated mouse dendritic cells (DCs) from different tissues and mouse macrophages from the lungs and then cultured mouse B cells together with either DCs or macrophages in vitro In the mouse lung-DC/B (LDC/B) cell coculture, IgA secretion was increased significantly after the addition of whole-cell lysates of M. hyopneumoniae The expression of both Toll-like receptor 2 (TLR2) and TLR4 was also upregulated, as determined by mRNA and protein expression analyses, whereas no obvious change in the expression of TLR3 and TLR7 was detected. Moreover, the IgA level decreased to the same as the control group when TLR2 or TLR4 was inhibited instead of TLR8 or TLR7/9. In conclusion, M. hyopneumoniae can stimulate the response of IgA through TLR2 and TLR4 in a mouse LDC/B cell coculture model, and the coculture model is an ideal tool for studying the IgA response mechanism, particularly that with Mycoplasma spp.

Clinical characteristics of patients with chronic obstructive pulmonary disease overlapped with bronchial asthma.

BACKGROUND: The clinical characteristics of patients with chronic obstructive pulmonary disease overlapped with bronchial asthma (COPD-BA) have not been discussed thoroughly. OBJECTIVE: To reveal the clinical features of patients with COPD-BA, to evaluate the risk factors of COPD-BA, and to provide suggestions for COPD individualized therapy. METHODS: A retrospective observational study was performed. A total of 182 patients with COPD (90 with COPD-BA and 92 with pure COPD) were recruited in the study. Information on the following items was collected: demographics, clinical manifestations, complications, laboratory findings, other histories, and inpatient treatments during exacerbation. RESULTS: A total of 182 patients were diagnosed with COPD, with 90 (49.45%) being classified as having COPD-BA. Patients with COPD-BA were more likely to be female (P = .004) and experienced more severe respiratory exacerbations (P = .04) despite being younger (P = .008). Those patients at onset of recurrent cough and sputum production were younger (P = .001). Significantly, a positive asthmatic family history (P = .03) was observed. Patients with COPD-BA usually had higher level of total serum IgE (although no differences were observed), had higher positive rates of the serum specific IgE (P = .004), and were more like to have an allergic history (P = .003). Allergic factor was the risk factor of COPD-BA (odds ratio, 4.477). During hospitalization, patients with COPD-BA tended to be treated with systemic corticosteroids (P = .008). CONCLUSION: Patients with COPD-BA were characterized by persistent airflow limitation with unique clinical features. Allergic factor was associated with the presence of asthmatic characteristics in patients with COPD. When hospitalized for exacerbation, the individualized therapy for COPD-BA might include the use of corticosteroids systemically.

Reducing lactate secretion by ldhA Deletion in L-glutamate- producing strain Corynebacterium glutamicum GDK-9

L-lactate is one of main byproducts excreted in to the fermentation medium. To improve L-glutamate production and reduce L-lactate accumulation, L-lactate dehydrogenase-encoding gene ldhA was knocked out from L-glutamate producing strain Corynebacterium glutamicum GDK-9, designated GDK-9ΔldhA. GDK-9ΔldhA produced approximately 10.1% more L-glutamate than the GDK-9, and yielded lower levels of such by-products as α-ketoglutarate, L-lactate and L-alanine. Since dissolved oxygen (DO) is one of main factors affecting L-lactate formation during L-glutamate fermentation, we investigated the effect of ldhA deletion from GDK-9 under different DO conditions. Under both oxygen-deficient and high oxygen conditions, L-glutamate production by GDK-9ΔldhA was not higher than that of the GDK-9. However, under micro-aerobic conditions, GDK-9ΔldhA exhibited 11.61% higher L-glutamate and 58.50% lower L-alanine production than GDK-9. Taken together, it is demonstrated that deletion of ldhA can enhance L-glutamate production and lower the unwanted by-products concentration, especially under micro-aerobic conditions.

Reducing lactate secretion by ldhA Deletion in L-glutamate- producing strain Corynebacterium glutamicum GDK-9.

L-lactate is one of main byproducts excreted in to the fermentation medium. To improve L-glutamate production and reduce L-lactate accumulation, L-lactate dehydrogenase-encoding gene ldhA was knocked out from L-glutamate producing strain Corynebacterium glutamicum GDK-9, designated GDK-9ΔldhA. GDK-9ΔldhA produced approximately 10.1% more L-glutamate than the GDK-9, and yielded lower levels of such by-products as α-ketoglutarate, L-lactate and L-alanine. Since dissolved oxygen (DO) is one of main factors affecting L-lactate formation during L-glutamate fermentation, we investigated the effect of ldhA deletion from GDK-9 under different DO conditions. Under both oxygen-deficient and high oxygen conditions, L-glutamate production by GDK-9ΔldhA was not higher than that of the GDK-9. However, under micro-aerobic conditions, GDK-9ΔldhA exhibited 11.61% higher L-glutamate and 58.50% lower L-alanine production than GDK-9. Taken together, it is demonstrated that deletion of ldhA can enhance L-glutamate production and lower the unwanted by-products concentration, especially under micro-aerobic conditions.

At-line near-infrared spectroscopy for monitoring concentrations in temperature-triggered glutamate fermentation.

Rapid development in the glutamate fermentation industry has dictated the need for effective fermentation monitoring by rapid and precise methods that provide real-time information for quality control of the end-product. In recent years, near-infrared (NIR) spectroscopy and multivariate calibration have been developed as fast, inexpensive, non-destructive and environmentally safe techniques for industrial applications. The purpose of this study was to develop models for monitoring glutamate, glucose, lactate and alanine concentrations in the temperature-triggered process of glutamate fermentation. NIR measurements of eight batches of samples were analyzed by partial least-squares regression with several spectral pre-processing methods. The coefficient of determination (R (2)), model root-mean square error of calibration (RMSEC), root-mean square error of prediction (RMSEP) and residual predictive deviation (RPD) of the test calibration for the glutamate concentration were 0.997, 3.11 g/L, 2.56 g/L and 19.81, respectively. For the glucose concentration, R (2), RMSEC, RMSEP and RPD were 0.989, 1.37 g/L, 1.29 g/L and 9.72, respectively. For the lactate concentration, R (2), RMSEC, RMSEP and RPD were 0.975, 0.078 g/L, 0.062 g/L and 6.29, respectively. For the alanine concentration, R (2), RMSEC, RMSEP and RPD were 0.964, 0.213 g/L, 0.243 g/L and 5.29, respectively. New batch fermentation as an external validation was used to check the models, and the results suggested that the predictive capacity of the models for the glutamate fermentation process was good.